Arhiv za higijenu rada i toksikologiju-Archives of Industrial Hygiene and Toxicology

ISSN 0004-1254

ARHIV ZA HIGIJENU RADA I TOKSIKOLOGIJU

ARCHIVES OF INDUSTRIAL HYGIENE AND TOXICOLOGY

Arh Hig Rada Toksikol • Vol. 65 • No. 3 • pp. 251-346 • ZAGREB, CROATIA 2014

CONTENTS Review Current trends in estimating risk of cancer from exposure to low doses of ionising radiation

Marija Majer, Željka Knežević, and Saveta Miljanić

251

Angel M. Dzhambov, Donka D. Dimitrova, and Tanya H. Turnovska

259

Ljiljana Cvejanov-Kezunović, Jadranka Mustajbegović, Milan Milošević, and Rok Čivljak

273

Occupational exposure to blood among hospital workers in Montenegro

Maja Lazarus, Andreja Prevendar Crnić, Nina Bilandžić, Josip Kusak, and Slaven Reljić

281

Cadmium, lead, and mercury exposure assessment among Croatian consumers of free-living game

Katsuhiko Warita, Tomoko Mitsuhashi, Nobuhiko Hoshi, Ken-ichi Ohta, Shingo Suzuki, Yoshiki Takeuchi, and Takanori Miki

293

A unique pattern of bisphenol A effects on nerve growth factor gene expression in embryonic mouse hypothalamic cell line N-44

Mert Gürkan, Ayşe Çetin, and Sibel Hayretdağ

301

Acute toxic effects of cadmium in larvae of the green toad, Pseudepidalea variabilis (Pallas, 1769) (Amphibia: Anura)

David Hernández-Moreno, Irene de la Casa-Resino, José María Flores, Manuel José González-Gómez, Carlos María Neila, Francisco Soler, and Marcos Pérez-López

311

Different enzymatic activities in carp (Cyprinus carpio L.) as potential biomarkers of exposure to the pesticide methomyl

Lucineide Aparecida Maranho, Leila Teresinha Maranho, Rafael Grossi Botelho, and Valdemar Luiz Tornisielo

319

Dissolved heavy metal determination and ecotoxicological assessment: a case study of the Corumbataí River (São Paulo, Brazil)

Karolina Wilman, Łukasz Stępień, Izabela Fabiańska, and Piotr Kachlicki

329

Plant-pathogenic fungi in seeds of different pea cultivars in Poland

Faheem Maqbool, Haji Bahadar, and Mohammad Abdollahi

339

Anton Marović i Siniša Štimac

341

Original articles Improving traffic noise simulations using space syntax: preliminary results from two roadway systems

Viewpoints Exposure to mercury from dental amalgams: a threat to society Medicinsko vještačenje pravične novčane naknade po prijedlogu medicinskih tablica iz 2013. godine

Cover page: A brown bear named Mladi Dol enjoying his days at the Kuterevo Bear Refuge, Croatia. Photographed by Prof Ä?uro Huber.

Disclaimer: This photo is intended to evoke the content of this issue of the journal. It is not intended for instructional or scientific purposes.

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Majer M, et al. LOW-DOSE IONISING RADIATION AND CANCER RISK Arh Hig Rada Toksikol 2014;65:251-257

DOI: 10.2478/10004-1254-65-2014-2425

Review

Current trends in estimating risk of cancer from exposure to low doses of ionising radiation Marija Majer, Željka Knežević, and Saveta Miljanić Ruđer Bošković Institute, Zagreb, Croatia Received in July 2013 CrossChecked in July 2014 Accepted in July 2014

Although ionising radiation has proven beneficial in the diagnosis and therapy of a number of diseases, one should keep in mind that irradiating healthy tissue may increase the risk of cancer. In order to justify an exposure to radiation, both the benefits and the risks must be evaluated and compared. The deleterious effects of medium and high doses are well known, but it is much less clear what effects arise from low doses (below 0.1 Gy), which is why such risk estimates are extremely important. This review presents the current state, important assumptions and steps being made in deriving cancer risk estimates for low dose exposures.

KEY WORDS: Dose and Dose-Rate Effectiveness Factor; epidemiology; Life Span Study; low-LET radiation; Linear No Threshold model; radiation risk

Its great benefits aside, any use of ionising radiation in the diagnosis and treatment of disease is also a potential threat for the occurrence of unwanted, harmful effects. Ionising radiation can damage DNA, either directly due to an ejected electron or indirectly through the production of free radicals. Among the many types of DNA damage, double strand breaks (DSBs) are considered to be the most dangerous, as they can lead to cell death or carcinogenesis and heritable effects if their reparation fails (1).

It is very important to know what kind of health risks arise from specific radiation doses. Sufficiently high doses of radiation (above 0.5 Gy) will kill a sufficient number of cells to cause tissue reactions (“deterministic effects”) (2). Deterministic effects are characterised by threshold doses below which effects do not occur and the severity of effects increases as the dose increases. Radiosurgery and radiotherapy use very high doses for killing off (or disabling) cancer cells. Non-lethal cell damage can cause cancer and heritable effects (“stochastic effects”) and the

probability (but not severity) of stochastic effects depends on the dose (2).

During diagnostic radiology all organs, and during radiotherapy and radiosurgery out-of-field organs, are exposed to low doses (below 0.1 Gy). That is why knowledge on cancer risk estimates for low doses is very important. Lately, this topic has attracted increased interest due to three main reasons. First, developments in photon therapy techniques such as Intensity Modulated Radiotherapy (IMRT) and tomotherapy have yielded a more conformal target dose distribution but, compared to previous conventional radiotherapy techniques, whole body exposure to low doses from scattered and leakage radiation has increased. The increasing use of these new techniques has raised interest regarding second cancer risk for patients undergoing radiotherapy.

Second, the prognosis for many cancers, including some that largely rely on radiotherapy (e.g., prostate, breast, etc.), is steadily improving; an increasing number of patients are surviving periods comparable to or larger than the latent period for the incidence of

252 a cancer induced by radiation. Third, the use of Computed Tomography (CT) constantly and significantly increases. CT has established itself as an essential tool, not only for diagnosis but also for the follow-up of diseases, as an aid in intervention and for radiotherapy imaging. It is associated with low doses (organ doses within the scanned volume are typically a few tens of mGy), but doses considerably larger in comparison to corresponding conventional radiographs (3). Many medical procedures require more than one CT scan, which increases the cumulative patient dose. Finally, it should be emphasized that children are of particular interest because cancer risks generally increase strongly as age lowers and children are expected to survive for periods much longer than the latent period of irradiation-induced cancer incidence.

This paper describes the current state and important assumptions and steps being made in deriving cancer risk estimates after exposures to low doses of X and gamma rays. The upper limit for the low dose region is not strictly defined, but this article assumes them to be below 0.1 Gy (4).

Cancer risk estimate for low doses The statistical models describing the dose-cancer risk relationship used here have been derived from data gathered in epidemiological studies taking into account experimental results from radiobiology (2, 13-15). Epidemiology is used to quantify risk from past exposures by following and comparing irradiated and non-irradiated populations.

The most important epidemiological study for cancer risk modelling is the study on Japanese atomic bomb survivors from Hiroshima and Nagasaki (the so-called Life Span Study, LSS). The LSS cohort of approximately 120,000 survivors (but for the most recent analysis, it was restricted to under 100,000) of the atomic bombings in Hiroshima and Nagasaki is the largest cohort selected for other reasons than disease or occupation. It includes both genders and all ages at exposure, whole-body exposure (mainly to external gamma rays, but a non-negligible ratio of neutrons was also present) with a wide range of doses (ranging from low doses relevant to diagnostic radiology to much higher, even lethal doses) and has a long follow-up period (more than 50 years), which makes it a very important and unique source of data for cancer risk assessment (5-8). The first cancer associated with radiation in the LSS population was leukaemia and it has had the highest relative risk (ratio

Majer M, et al. LOW-DOSE IONISING RADIATION AND CANCER RISK Arh Hig Rada Toksikol 2014;65:251-257

of the cancer rate in the irradiated group and cancer rate among the non-irradiated group) of any other cancer.

Statistical modelling cannot begin before cancer data assembled during the follow-up period has been assigned to dose data. Doses for the LSS population were reconstructed using DS86 and DS02 dosimetry (9, 10).

What we know from current data For medium doses (approx. 0.1-2.5 Gy), LSS data suggest an approximately linear relationship between dose and solid cancer induction. Leukaemia is a major exception for which a linear-quadratic model is the accepted standard, because it fits the data significantly better than the linear model (7, 11). Above and below the medium dose range, the situation is much less clear. Although epidemiological data for doses below 0.1 Gy exist, statistical limitations, i.e. uncertainties, are large. The size of an exposed cohort that would be required to detect a statistically significant increase in cancer risk from doses of interest approximately increase as the inverse square of the dose (12). For low doses, extremely large epidemiological studies would be required to maintain the statistical significance of cancer risk results. Therefore, linear extrapolation from higher doses, suggested by different standard bodies (2, 13-15), is a reasonable solution for low doses.

However, we have to be aware that some known effects and phenomena suggest scenarios where linear extrapolation could underestimate (e.g., bystander effect) or overestimate risk (e.g., adaptive response).

On the other side of the dose-risk curve, for doses above 2.5 Gy, the deviation from linearity and reduction of risk due to cell killing and repopulation effects are expected.

The Linear No Threshold model Several risk models have been developed by standard bodies to estimate cancer incidence and mortality for low doses: Committee on the Biological Effects of lonizing Radiation [BEIR (13)], National Council on Radiation Protection and Measurements [NCRP (14)], International Commission on Radiological Protection [ICRP (2)], and United Nations Scientific Committee on the Effects of Atomic Radiation [UNSCEAR (15)]. They all have in common the assumption of the Linear No Threshold (LNT) dose-risk relationship. In other words, risk is directly

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proportional to the received dose and exists for each dose. The uncertainties associated with each model are close to, or exceed, variations between the models.

Using LNT models for a dozen or so different types of cancers, as a function of important parameters such as gender, age at exposure and time since exposure, have been developed. It has also been established and used in the field of radiation protection that the average risk of developing cancer induced by whole body low dose exposures during a lifetime is approximately 5 % per Sv (2).

Dose and Dose-Rate Effectiveness Factor (DDREF) value Because the LSS population was exposed to a high dose rate and risk estimates for low doses had to be based on data for higher doses, which following linear extrapolation overestimates the risk for low doses, the reduction factor called Dose and Dose-Rate Effectiveness Factor (DDREF) was introduced. In another words, DDREF implies that the radiobiological effectiveness of low dose and/or low dose rate exposures differs from the effectiveness of high dose and/or high dose rate exposures. Values for DDREF have been mainly deduced from experiments with laboratory animals, radiobiological measurements, and statistical methods (Bayesian analysis) on epidemiological data.

In order to be able to rely on the developed models, one should be aware of their uncertainty. There are two important sources of uncertainty: the very procedure to determine the DDREF value and the “transport” of cancer risk estimations based on a Japanese population to non-Japanese populations, particularly those predominantly Caucasian.

BEIR VII and ICRP reduced cancer risk values in atomic bomb survivors by a DDREF of 1.5 and 2.0, respectively (2, 13). However, a recent review article on cancer risk in radiation workers after low dose rate and moderate dose exposures reported higher cancer risks than BEIR VII and ICRP, implying that their DDREF values were overestimated (16).

To clarify the DDREF, we should use knowledge from radiobiology. For doses of up to a few Gy, an effect E(D) (e.g., chromosomal aberrations, mutations, animal carcinogenesis) induced by an acute dose of low-LET (Linear Energy Transfer) radiation (such as X and gamma rays) delivered over a few minutes can be described by a linear-quadratic function (17): E(D)=αD+βD2 (I)

Theoretically, the linear and quadratic term can be associated with “single-track action” (cell damages (e.g. DSBs) are caused by a single track) and “doubletrack action” (two or more tracks increase damage of the cell), respectively (18). Although, equation (I) is most suited for medium doses (0.1-2.5 Gy), it is better to use a more simpler linear function (EMedium(D)=αMD) for fitting data because the corresponding error for risk estimates is much smaller than the one caused by the uncertainties of the data.

As already mentioned, equation (I) should be used only for leukaemia. For low doses, the probability for “double-track action” is negligible, so the quadratic term in (I) can be neglected and only the linear term is important (ELow(D)=αD). EMedium(D) and ELow(D) are different linear functions. If applied for low doses, E Medium(D) overestimates the risk and therefore reduction factor DDREF is used.

The second important source of uncertainty is the “transport” of data and the conclusions that arise from it from the studied Japanese population to other populations that may have different genetic and lifestyle characteristics leading to different baseline risks.

Basic terms used for risk estimate The most recent statistical analyses of epidemiological data made for the purpose of cancer risk estimates are based on either Excess Absolute Risk (EAR) models or Excess Relative Risk (ERR) models (2, 13-15). EAR models express excess risk as the difference in the total risk and the background risk, while ERR models express excess risk relative to the background risk. Several measures of lifetime risk have been introduced, but our focus is primarily on Lifetime Attributable Risk (LAR). LAR is defined as the probability that an irradiated person during his life could develop cancer induced by radiation. The LAR for a person exposed to dose D at age e is calculated as follows (13): (II) where a = attained age e = age at exposure L = latent period i.e. the period during cancer incidences caused by radiation are not expected (BEIR VII has adopted L = 2 for leukaemia and L = 5 for solid cancers) S(a) = probability of surviving until age a

254 S(e) = probability of surviving until age e M(D, e, a) is a linear combination of EAR(D, e, a) and ERR(D, e, a) that depends on how transport from one studied population to another is made.

Two approaches that have been used are multiplicative or relative risk transport and additive or absolute risk transport (2, 13-15). The first approach assumes that the cancer risk induced by radiation exposure is proportional to the baseline risk, whereas the second presumes the opposite. Results from these two approaches can be very different. For example, the baseline risk for stomach cancer is much higher in Japan than in the United States (13) and there is almost an order-of-magnitude difference in the estimates of stomach cancer risks based on absolute and relative risk transport. For cancer sites other than breast, thyroid and lung, BEIR VII (13) recommends a weight of 0.7 for the estimates obtained using relative risk transport and a weight of 0.3 for the estimates obtained using absolute risk transport with the weighting done on a logarithmic scale. For example, if lifetime attributable risks for the aforementioned stomach cancer based on relative and absolute risk transport are LARr and LARa, respectively, the final result for LAR, combined and adjusted by DDREF is:

(III) Diagrams on Figure 1 illustrate LAR data estimated

by BEIR VII (13). The BEIR VII table 12D-1 provides LAR data for leukaemia and cancer for several radiosensitive organs of persons exposed to a single dose of 0.1 Gy. Both sexes and eleven discrete ages at exposure are covered and LARs for the measured organ doses in other studies can be estimated by using linear extrapolation and/or interpolation. According to these results, the risks are highest for children and decrease with age at exposure. For most radiosensitive organs, women endure higher risks than men. They also have the highest LAR for breast, lung, and thyroid cancer, while the highest male LAR is for colon and lung cancer.

Other studies There have been many studies on medically, occupationally, and environmentally exposed populations whose results have been compared against those from the LSS. The results of comparisons are always expressed within certain statistical limits.

A few years ago, the largest study of nuclear workers found radiation-induced cancer risk consistent

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with the LNT cancer risk models based on LSS data (19). Medical studies include patients irradiated for the treatment of disease or diagnosis and provide valuable information for understanding radiation risk, especially for some specific cancers (e.g., thyroid and breast) (20). Analysis of childhood cancer risks after prenatal X-ray exposures found increased cancer risk for the dose of 10 mSv (21). Due to increased interest for cancer risk estimate after CT, currently more than ten studies concerning risk of cancer after CT for different national cohorts are in progress (22).

Recently, results for the British (23) and Australian (24) cohort of children and young adults have been published and both assessed the excess cancer risk after CT scans. Environmental radiation studies comparing medical and occupational data are mostly limited and uncertain. The most valuable information can be derived from studies after the Chernobyl accident (mostly regarding increased risk of radiationinduced thyroid cancer among children due to exposure to radioactive iodine); a recent study (28) reports statistically significant increased risk for children and adolescents but not for older people.

The validity of the LNT model and concluding remarks Between 50 and 100 mGy, cancer risk estimates based on LSS data lose their conventional statistical significance, but for the low dose region they remain consistent with the LNT model as well as with some nonlinearities (7). Although there is evidence that doses of approximately 10 mGy increase the risk of certain cancers (21), according to present epidemiological data the lowest dose of photon radiation for which reasonably reliable evidence of increased cancer risk exists is about 10-50 mGy for single and 50-100 mGy for protracted exposure (25).

There is no doubt that present cancer risk models can be used for doses above the mentioned limit, but one should always be careful with extrapolation to lower doses (especially below 10 mGy).

Reducing the dose and approaching the level of background radiation, things become even more unclear and it has to be borne in mind that values for estimated risk of radiation-induced cancer will be very small and comparable with variations in baseline risk (e.g., smoking). It would be impossible to make an adequate epidemiological LNT test for doses below approx.10 mGy and controversies (26, 27) will always exist.

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Figure 1 Diagrams illustrate LAR data for cancer incidences presented in BEIR VII table 12D-1 (13). LAR is expressed as a number of cancer cases among 100,000 irradiated persons exposed to a single dose of 0.1Â Gy. Only organs with the highest cancer risk values are presented

However, evidence for cancer risk after low dose exposure exists and that risk can be predicted by current LNT models. The LNT model is still the most robust and most frequently used model for making cost-benefit decisions in medical exposures, but improvements to existing models as well as new findings for the low dose region are eagerly awaited.

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Br J Radiol 2008;81:362-78. doi: 10.1259/bjr/01948454 4. Wakeford R, Tawn EJ. The meaning of low dose and low dose rate. J Radiol Prot 2010;30:1-3. doi: 10.1088/09524746/30/1/E02 5. Preston DL, Shimizu Y, Pierce DA, Suyama A, Mabuchi K. Studies of mortality of atomic bomb survivors. Report 13.

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6. Preston DL, Ron E, Tokuoka S, Funamoto S, Nishi N, Soda M, Mabuchi K, Kodama K. Solid cancer incidence in atomic bomb survivors: 1958-1998. Radiat Res 2007;168:1-64. doi: 10.1667/RR0763.1 7. Pierce DA, Preston DL. Radiation-related cancer risk at low doses among atomic bomb survivors. Radiat Res 2000;154:178-86. PMID: 10931690 8. Pawel D, Preston D, Pierce D, Cologne J. Improved estimates of cancer site-specific risks for a bomb survivors. Radiat Res 2008;169:87-98. doi: 10.1667/RR1092.1 9. Young RW, Kerr GD. Report of the joint US-Japan working group. Reassessment of the Atomic Bomb Radiation Dosimetry for Hiroshima and Nagasaki - Dosimetry System 2002. Hiroshima: The Radiation Effects Research Foundation; 2005.

10. Kerr GD. DS86 and DS02 organ dose calculations. Radiat Prot Dosim 2012;149:15-20. doi: 10.1093/rpd/ncr255 11. Kaiser JC, Walsh L. Independent analysis of the radiation risk for leukaemia in children and adults with mortality data (1950-2003) of Japanese A-bomb survivors. Radiat Environ Biophys 2013;52:17-27. doi: 10.1007/s00411-012-0437-6 12. Land CE. Estimating risk from low doses of ionizing radiation.

Science 1980;209:1197-203. doi: 10.1126/science.7403879 13. National Research Council Committee (NRCC). Health Risks from Exposure to Low Levels of Ionizing Radiation: Biological Effects of Ionizing Radiation BEIR VII Phase 2.

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16. Jacob P, Ruhm W, Walsh L, Blettner M, Hammer G, Zeeb H. Is cancer risk of radiation workers larger than expected? Occup Environ Med 2009;66:789-96. doi: 10.1136/oem.2008.043265 17. Cox R, Thacker J, Goodhead DT. Inactivation and mutation of cultured mammalian cells by aluminium characteristic ultrasoft X-rays II. Dose-responses of Chinese hamster and human diploid cells to aluminium X-rays and radiations of defferent LET. Int J Radiat Biol Relat Stud Phys Chem Med 1977;31:561-76. PMID: 301865 18. Shah DJ, Sacks RK, Wilson DJ. Radiation-induced cancer: a modern view. Br J Radiol 2012;85:e1166-73. doi: 10.1259/ bjr/25026140 19. Muirhead CR, O’Hagan JA, Haylock RG, Philipson MA, Willcock T, Berridge GL, Zhang W. Mortality and cancer incidence following occupational radiation exposure: third analysis of the National Ragistry for Radiation Workers. Br J Cancer 2009;100:206-12. doi: 10.1038/sj.bjc.6604825 20. United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR). Sources and Effects of Ionizing Radiation: UNSCEAR 2000 Report to the General Assembly, Volume II: Effects. New York (NY): UNSCEAR; 2000.

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Parker L, Berrington de González A. Radiation exposure from CT scans in childhood and subsequent risk of leukaemia and brain tumours: a retrospective cohort study. Lancet 2012;380:499-505. doi: 10.1016/S0140-6736(12)60815-0 Mathews JD, Forsythe AV, Brady Z, Butler MW, Goergen SK, Byrnes GB, Giles GG, Wallace AB, Anderson PR, Guiver TA, McGale P, Cain TM, Dowty JG, Bickerstaffe AC, Darby SC. Cancer risk in 680 000 people exposed to computed tomography scans in childhood or adolescence: data linkage study of 11 milion Australians. BMJ 2013;346:f2360. doi: 10.1136/bmj.f2360 Brenner DJ, Doll R, Goodhead DT, Hall EJ, Land CE, Little JB, Lubin JH, Preston DL, Preston RJ, Puskin JS, Ron E, Sachs RK, Samet JM, Setlow RB, Zaider M. Cancer risk attributable to low doses of ionizing radiation: Assessing what we really know. Proc Natl Acad Sci USA 2003;100:13761-6. PMID: 14610281 Little MP, Wakeford R, Tawn EJ, Bouffler SD, Berrington de Gonzalez A. Risks associated with low doses and low dose rates of ionizing radiation: why linearity may be (almost) the best we can do. Radiology 2009;251:6-12. doi: 10.1148/radiol.2511081686 Tubiana M, Feinendegen L, Yang C, Kaminski JM. The linear no-threshold relationship is inconsistent with radiation biologic and experimental data. Radiology 2009:13-22. doi: 10.1148/radiol.2511080671 Ivanov VK, Kashcheev VV, Chekin SYu, Maksioutov MA, Tumanov KA, Vlasov OK, Schukina NV, Tsyb AF. Radiationepidemiological studies of thyroid cancer incidence in Russia after the Chernobyl accident (estimation of radiation risks, 1991-2008 follow-up period). Rad Prot Dos 2012;151:489499. doi:10.1093/rpd/ncs019

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Sažetak Procjena rizika za nastanak karcinoma zbog izloženosti malim dozama ionizirajućeg zračenja Unatoč velikoj važnosti i koristi ionizirajućeg zračenja u dijagnosticiranju i liječenju mnogih bolesti, treba imati na umu da se ozračivanjem zdravog tkiva može povećati rizik od karcinoma. Stoga je vrlo važno znati kakve rizike možemo očekivati ovisno o primljenoj dozi zračenja. Za razliku od područja srednjih i velikih doza za koje su štetni učinci dobro poznati, područje malih doza (ispod 0,1 Gy) puno je nejasnoća, a procjena rizika vrlo je važna. U ovom radu prikazane su osnovne pretpostavke i koraci u procjeni rizika od karcinoma uzrokovanih zračenjem u području malih doza.

KLJUČNE RIJEČI: faktor DDREF; epidemiologija; LSS; model LNT; radijacijski rizik; zračenje niskog LET-a

CORRESPONDING AUTHOR: Marija Majer Ruđer Bošković Institute Bijenička 54 10000 Zagreb, Croatia E-mail: mmajer@irb.hr

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Dzhambov AM, et al. SPACE SYNTAX IN TRAFFIC NOISE SIMULATIONS Arh Hig Rada Toksikol 2014;65:259-272

DOI: 10.2478/10004-1254-65-2014-2469

Original article

Improving traffic noise simulations using space syntax: preliminary results from two roadway systems Angel M. Dzhambov1, Donka D. Dimitrova2, and Tanya H. Turnovska3 Faculty of Medicine1, Department of Health Care Management, Health Economics and Primary Care2, Department of Hygiene and Ecomedicine3, Medical University of Plovdiv, Bulgaria Received in November 2013 CrossChecked in November 2013 Accepted in August 2014

Noise pollution is one of the four major pollutions in the world. In order to implement adequate strategies for noise control, assessment of traffic-generated noise is essential in city planning and management. The aim of this study was to determine whether space syntax could improve the predictive power of noise simulation. This paper reports a record linkage study which combined a documentary method with space syntax analysis. It analyses data about traffic flow as well as field-measured and computer-simulated traffic noise in two Bulgarian agglomerations. Our findings suggest that space syntax might have a potential in predicting traffic noise exposure by improving models for noise simulations using specialised software or actual traffic counts. The scientific attention might need to be directed towards space syntax in order to study its further application in current models and algorithms for noise prediction.

KEY WORDS: noise exposure; noise mapping; noise pollution; prediction; theoretical models

Noise pollution is one of the four major pollutions (air, noise, water, and soil) in the world. Approximately 80 million people in the European Union suffer unacceptable noise levels (>65 dB) and over 170 million are exposed to noise levels between 55 and 65 dB (1, 2). Noise levels above 85 dB can cause hearing impairment (3). Even when environmental noise is not loud enough to cause physiological and psychological symptoms, it significantly affects the quality of life (4, 5).

According to the World Health Organization (6), at least one million healthy life years are lost every year from traffic-related noise in Western Europe.

Bulgaria has been estimated to have lost about € 11.6 million annually due to traffic noise-attributed myocardial infarction (7).

Noise pollution continues to grow in extent, frequency, and severity as a result of population growth, urbanisation, and technological development (8). It is a common cause of various types of psycho-

social and health-related impairments (9-12). In Europe, road traffic noise constitutes the dominant source of noise annoyance (13).

Land use and transportation development policies have significant effects on urban environment and health (14). In city planning and management it is therefore essential to assess traffic-generated noise in order to implement adequate strategies for noise control (15, 16). Traditionally, local authorities address this issue by creating strategic noise maps based on computer simulations, taking into account the plan of the city, acoustical properties of buildings, open spaces, street corridors, and the distribution of noise in this system (15). This is an alternative to measuring the acoustic characteristics of the whole city, which may not be feasible due to the great number of measurement points, time, and resources required (16).

There are various simulation software packages to predict noise. In Bulgaria, for example, LimA v. 5 (Brüel & Kjær, Nærum, Denmark) (17) was used to

260 create strategic noise maps. To achieve high quality in simulations, a precise mathematical modelling of the environment, of the sources, and of the propagation law of sound is needed (18), and such high quality is mandatory because many protected facilities in Bulgaria like schools and hospitals are exposed to unacceptably high noise levels.

Noise mapping simulations might be somewhat problematic because “noise map accuracy can be greatly affected by several data inputs at the model building stage”, including grid resolution (16). A general limitation of this approach is that simulations take into account only the factors associated with the distribution of sound waves in reference to their possible source and the barriers that they come in contact with. With “NMPB-Routes-96”, which is used in Bulgaria, on the other hand, the noise level is overestimated in downward propagation conditions (18). Quartieri et al. (19) therefore proposed a purely theoretical statistical procedure for traffic-noise prediction, independent of experimental data.

Studying the application of space syntax (SS) - an architectural technique developed to predict human navigation in urban environments - in traffic prediction, we encountered an interesting phenomenon; some SS measures seemed to be highly associated with traffic-generated noise. Further investigation of their relationship showed that those SS measures actually could predict noise exposure above and beyond traffic counts and could improve the predicting model when complemented by traffic counts as predictors of noise. This potential contribution of SS to noise prediction models has not been addressed in literature before. The first step towards implementing SS in actual noise predicting simulation would be to understand the predictive potential of SS, like Penn and Croxford (20) suggested in their research, by replicating its findings on a larger scale and by modelling the unique variance in noise exposure that they were hypothesised to explain.

The SS theory was developed in the 1970s, and it reflects the relationship between the configuration of the road network and vehicular and pedestrian flows (21-23). Being an alternative to the classical theories of traffic assignment (21), SS has the ability to capture the trends of vehicular travel demands (24). Traffic flow has not been contextualised in the spatial configuration of Bulgarian cities (25). There is also a gap in the literature about implementing SS in noise prediction. Nevertheless, SS has been found to predict well average and extreme vehicular carbon monoxide

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concentrations (20). Hence, as both air and noise pollutions are caused by traffic, SS might be able to predict noise exposure as well.

The aim of this study was to determine whether SS could significantly improve the predictive power of noise simulation. In this paper we propose possible use of SS in noise control and look into the mechanism of its explanatory power. We hope to inspire future research that would ultimately explore its potential in noise prediction and identify the practical benefits of including SS in simulation algorithms.

MATERIALS AND METHODS Study design This paper reports a record linkage study that combined the documentary method with space syntax analysis. It analyses field-measured and computersimulated traffic noise levels in the two most populated Bulgarian agglomerations. As it does not involve human participants and uses official municipality reports, it was not subjected to ethical evaluation by the University Committee.

Study area The cities of Sofia and Plovdiv were selected for the analyses because they are the two most populated agglomerations in Bulgaria; moreover, relevant official data sources were available which ensured a satisfactory sample size.

Sofia is the capital and the largest city in Bulgaria, with a territory of 492 km2. It is located at the foot of Mount Vitosha in the western part of the country and has a population of over 1.2 million (26). The city centre is highly integrated with areas stretching along the major boulevards towards the periphery (Figure 1). The periphery consists of concentrically located neighbourhoods with lower integration.

The city of Plovdiv is the second largest city in Bulgaria with a population of 341 thousand people (26) and a territory of 101.98 km2. It is situated on the banks of the Maritza River. Plovdiv has a well-defined core with high southwest integration (Figure 2). There is an old grid of small winding streets in the centre of the city. The surroundings have a concentric character with stronger integration towards the south and west.

Several highly integrated lines stretch through the city and outwards. There are also some spatially isolated

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Figure 1* Axial total integration map of the city of Sofia.

Red colour indicates higher while blue indicates lower integration

areas close to the agricultural fields in Plovdiv’s surroundings, the Roma ghetto, the old part in the city centre, and a northern district neighbourhood across the Maritza River (25).

Data extraction The analyses included 69 street segments in Sofia and 52 in Plovdiv because these were covered by official records that included LimA-simulated and field-measured traffic noise levels (See Appendix).

Field noise measurements had been carried out by municipality experts following the ISO 1996-1/2005 (27) and ISO 1996-2/1987 procedures (28). Sound levels were measured in the field using “Brüel & Kjær Type 2240” sound meter and “Brüel & Kjær Type

Figure 2* Axial total integration map of the city of Plovdiv. Red colour indicates higher while blue indicates lower integration

4231” calibrator. These data were extracted from the reports “Development of strategic noise map of Plovdiv agglomeration” (29) and “Development of strategic noise map of Sofia agglomeration” (30).

Plovdiv field measurements were taken twice and then averaged to improve their accuracy. Those field measurements had been used to validate the strategic noise maps created in compliance with Environmental Noise Directive 2002/49/EC (31) by comparing them to the computer-simulated noise levels. Noise map simulations were made with the LimA v. 5 software (17), using as input data geographic information to construct a city plan and calculated noise levels in order to calibrate the analyses. Traffic-generated noise was calculated based on the French national method “NMPB-Routes-96” (32) and the French standard “ХPS 31-133” (33). Correction for the roadway surface was applied according to “EN ISO 11819-1” (34). The simulations assume standard meteorological conditions: 10 °C, 70 % humidity, and “quiet” wind conditions.

Axial maps of Sofia and Plovdiv The graphic representation of Sofia’s and Plovdiv’s streets was based on cartographic information (35) and was made using MapInfo Professional v. 9.0 (MapInfo Corp., New York, NY, USA). Street layer was drawn by hand to adjust for street functionality and the like, as complex plans take too long to analyse with automatic generation of an axial map. Axial maps of Plovdiv and Sofia were created by identifying the minimal set of longest and fewest accessible lines representing the roadway structure of the city.

Subsequently the axial map was converted into a segment map (removing axial stubs with less than 25 % of the line) (36). Because choosing adequate radius for the analysis is arbitrary and varies across roadway systems, the segment analysis was performed with a series of specified metric radii (n, 250, 500, 750, 1000, 1250, 1500, 2000, 2500, 3000, 4000, 5000) in order to avoid the edge effect (36, 37). This was done because some segments might be closer to the boundary of the axial map and distort the values.

Angular segment analysis breaks axial lines into segments and then records the sum of the angles turned from the starting segment to any other segment within the system (37). The angle of turn is closely related to how people perceive the world (38, 39). For angular segment analysis for the segment map we used Depthmap v.10 (University College London, London, England) (37, 40).

*As our hardcopies are printed in black and white, please refer to the online edition of this article at http://www.degruyter. com/view/j/aiht

262 Variables SS variables (unweighted and weighted choice and integration) were derived from segment maps of Plovdiv and Sofia assuming different radii around each segment. Integration is a measure of how accessible each segment is from all the others, and therefore how much potential it has as a destination for movement (36). Choice measures the through-movement potential of each segment within that radius in contrast to the to-movement potential measured by integration (36). Choice is a more intuitive model of movement than integration (37). Weighting the choice measure by the product of the lengths of the origin and destination nodes helps integrate axial and road-centre lines (36, 37).

The main outcome variable was field-measured equivalent noise level (Laeq). Independent variables were LimA-simulated Laeq for the same street segments and a combined choice and integration variable at radius “n” as both a destination and a route according to the formula proposed by Hillier: Integration x [log (Choice+2)] (36).

The analyses were adjusted for the city where measurements were taken as a “dummy” variable.

Traffic counts were represented by light motor vehicles (total laden weight <3.5 t) per hour and heavy motor vehicles (total laden weight >3.5 t) per hour.

Mean velocity of light and heavy vehicles, type of traffic flow (accelerated pulsed flow/decelerated pulsed flow/combined flow), direction of traffic flow (one-way/two-way), and the number of lanes on the street segment were included as well. These data had been collected by the local authorities in order to use them as input for constructing noise maps (29, 30) Statistics and data analytic strategy The data were screened for univariate outliers and winsorised accordingly (41). Missing values were tested for response pattern with Little’s MCAR test and replaced using the expectation-maximisation algorithm. To check the normality of distribution we used graphical analysis and D’Agostino-Pearson K2 test (42). First, we computed correlations between SS variables and field-measured Laeq. For comparison of two correlation coefficients we used the tools proposed by Weaver and Wuensch (43). Then we ran three hierarchical regressions to determine 1) the predictive power of SS measures above and beyond

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the LimA-simulated Laeq while controlling for relevant confounders; 2) the same model on local scale in Sofia and Plovdiv; 3) the improvement of traffic count-predicted Laeq after adding SS measures while controlling for roadway characteristics associated with field-measured Laeq.

In order to make inferences from the data without making strong distributional assumptions in the parametric tests we used the bootstrapping method (5000 samples) with bias-corrected confidence estimates. The significance level was set at p<0.05 (two-tailed).

All statistical analyses were performed with the SPSS software (IBM SPSS Statistics for Windows, Version 21.0, 2012. Armonk, NY, USA.).

RESULTS The partial correlation matrix of all SS measures and field-measured Laeq controlling for the city in which the measures were taken revealed that the highest coefficients were associated with Choice-n (r(118)=0.482; p<0.001), Integration-n (r(118)=0.531; p<0.001), Weighted choice-n (r(118)=0.386; p<0.001), and Weighted integration-n (r(118)=0.485; p<0.001). In order to improve the associations with field-measured Laeq we computed two combined “Choice + Integration” measures – one weighted and one unweighted – according to Hillier’s formula and included them in the correlation matrix (36). “Choice-n + Integration-n” (Cn+In) had significantly higher (t(118)=2.086; p=0.039) correlation with field-measured Laeq (r(118)=0.604; p<0.001) than “Weighted choice-n +Weighted integration-n” (r(118)=0.538; p<0.001). We performed all follow-up analyses using both measures, but we report mainly Cn+In, because it yielded a better model fit. However, we compare the results with those obtained from WCn+WIn, which theoretically is the better choice of predictor because it helps integrate axial and road-centre lines (36, 37). Cn+In also had a stronger association with LimA-simulated Laeq (r(118)=0.628; p<0.001) than any other SS measure.

Cn+In alone explained 37 % (Adjusted R2) of the variance in field-measured Laeq (β=0.955; p<0.001), controlling for the city where the measurements were taken. Then we performed a hierarchical multiple regression with field-measured Laeq as dependent variable, LimA-simulated Laeq in the first block of predictors, and Cn+In in the second block. The city of measurement was also included in both blocks in

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order to adjust the associations for it. The coefficients for the model are presented in Table 1.

The quantile-normal plot of the residuals confirmed normality of errors, and the residual versus fit plot confirmed linearity and equal variance.

Multicollinearity was not detected (VIF<5; tolerance >0.200). Overall, LimA-simulated Laeq predicted 59 % of the variance in field-measured Laeq, controlling for the city where the data were collected.

When Cn+In was added in the second regression block, the model improved by 2.4 %, which was statistically significant. Moreover, when adjusted for the city and LimA-simulated Laeq, Cn+In turned out to be a significant predictor and therefore had unique contribution to the model.

Although we controlled for the city where the measurements were taken, we wanted to see how Cn+In would perform at a local scale. We conducted hierarchical regressions similar to those described above for each of the two cities (without “city” as covariate). For brevity, Table 2 shows only the model summary with R2 statistics. Cn+In improved the model for Sofia and Plovdiv by 1.9 % and 3.5 %, respectively.

While for Sofia this change was statistically significant (we consider p=0.05 marginally significant), for Plovdiv it was not, which might be attributed to the fewer measurements taken in Plovdiv and therefore lower statistical power. This might further be illustrated by the fact that after taking a random sample from the data collected for Sofia with a size equal to that of Plovdiv, the statistical significance exceeded 0.05.

Compared to Cn+In, WCn+WIn produced 1.8 % improvement in the model, controlling for the city where the measurements were taken, which was significant at p=0.023. At individual city level it yielded a 1.9 % and 3.2 % increase in R2, respectively.

In the final regression we included the counted light and heavy motor vehicles per hour as predictors of field-measured Laeq, controlling for the city where the measurements were taken, the number of lanes of the segment, and the velocity of vehicles, which all correlated significantly with field-measured Laeq (See Table 3). They accounted for 60 % of the variance in field-measured Laeq. Adding Cn+In improved the model significantly by 5.8 %. The difference between the two tested types of prediction models (the first with the LimA-simulated Laeq and the second with motor vehicle counts as predictors) is that while the first implies how SS might improve simulation software’s performance and noise mapping, the second suggests that it may improve the predictive capacity through traffic noise formulas based on traffic counts such as those proposed by Quartieri et al. (19) and the French national method “NMPB-Routes-96”.

DISCUSSION Key findings Overall, our findings suggest that SS might have some potential in predicting noise exposure above and

Table 1 Coefficient for hierarchical multiple regression model predicting field-measured Laeq from LimA-simulated Laeq and space syntax measures Cn+In, while controlling for the city where the measurements were taken

Block I

B

SE

β

t

p

LimA-simulated Laeq

0.759

0.089

0.772

13.009

<0.001

0.580

0.917

Plovdiv

-0.024

0.424

-0.004

-0.060

0.957

-0.894

0.799

R2=0.596 II

R2=0.621

95% BCa CI Lower Upper

Predictor

Adjusted R2=0.590

p<0.001

F(2, 118)=87.209

LimA-simulated Laeq Cn+In

0.634

0.090

0.645

8.684

<0.001

0.456

0.795

0.0001

0.00004

0.319

2.729

0.008

0.00003

0.0002

Plovdiv

1.497

0.689

0.223

2.206

0.030

0.105

2.721

Adjusted R2=0.611

F(3, 117)=63.797

p<0.001

∆R2=0.024

Sig. ∆F=0.007

The city of Plovdiv is coded as a “dummy” variable in reference to the city of Sofia. The p-values and SE are bootstrap-generated.

LimA – noise simulation software; Laeq - equivalent noise level; Cn+In – combined space syntax measure of choice and integration with “n” radius.

B-unstandardized regression coefficient; SE-standard error of B; β-standardized regression coefficient; t-t-test; BCa CIbias-corrected and accelerated confidence intervals

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Table 2 Improvement in noise prediction models in both cities of measurement after adding space syntax measure Cn+In

City

Block

R2

Change statistics

Adjusted R2

∆R

∆F

2

df

Sig. ∆F

I 0.668 0.663 0.668 134.804 1; 67 <0.001 II 0.687 0.677 0.019 3.959 1; 66 0.050 I 0.289 0.275 0.289 20.304 1; 50 <0.001 Plovdiv II 0.323 0.296 0.035 2.501 1; 49 0.120 The predictor in the first block is LimA-simulated Laeq and in the second block Cn+In is added. LimA-noise simulation software; Laeq-equivalent noise level; Cn+In-combined space syntax measure of choice and integration with “n” radius Sofia

beyond the simulations currently available through specialised software LimA and actual traffic counts.

Unweighted measures for the total roadway system provided the best fit of the regression models, but their superiority to the weighted measures was negligible.

According to Hillier (36), the segment length weighting version of the measure partially neutralises the fact that block size in cities grows from the centre outwards. Having a measure with a fixed radius, on the other hand, is particularly useful, because it can facilitate noise predictions. If SS can indeed be incorporated in noise predictions, it will be challenging to determine what radius should be used for each roadway system. Would that radius depend on the segments where the measurements should be predicted? We need a theoretical basis for determining

the SS measures, because establishing the correlations between SS and noise levels empirically will also give us the actual noise exposure and would render the use of SS irrelevant, as finer predictions could be achieved by hypothesising future noise exposure based on these measured values.

Alternatively, our goal should be to provide adequate predictions without knowing the actual noise levels, for example, in newly developing or already existing street networks that have undergone significant alteration in traffic flow for whatever reason. According to Quartieri et al. (18) the aim of traffic noise modelling is to help plan new infrastructures in order to avoid post-construction mitigation actions that often present a greater cost and to minimise measurement campaign in existing road

Table 3 Regression coefficients for hierarchical multiple model predicting field-measured Laeq from traffic counts and space syntax measure Cn+In, controlling for roadway characteristics

Block I

Predictor LMV/h HMV/h Plovdiv Lanes VLMV VHMV R2=0.619

II

R2=0.678

LMV/h HMV/h Plovdiv Lanes VLMV VHMV Cn+In

B

0.001 <0.001 0.008 0.004 1.783 0.465 0.157 0.235 -0.003 0.028 0.117 0.029 Adjusted R2 =0.599 0.001 <0.001 0.009 0.003 3.670 0.599 0.028 0.219 0.001 0.026 0.104 0.027 <0.001 <0.001

Adjusted R2=0.658

β

t

p

0.415 0.175 0.266 0.047 -0.010 0.427

5.153 2.317 3.833 0.670 -0.0997 3.956

<0.001 0.022 <0.001 0.504 0.923 <0.001

SE

F(6, 114)=30.925 0.276 0.181 0.548 0.008 0.003 0.381 0.464

F(7, 113)=33.966

3.426 2.600 6.129 0.129 0.035 3.801 4.526 p<0.001

95 % BCa CI Lower Upper 0.001 0.002 0.001 0.016 0.861 2.704 -0.308 0.623 -0.058 0.053 0.058 0.175

p<0.001 0.001 0.011 <0.001 0.897 0.972 <0.001 <0.001

<0.001 0.002 2.483 -0.405 -0.050 0.050 <0.001

∆R2=0.058

0.001 0.015 4.856 0.462 0.052 0.158 <0.001

Sig. ∆F<0.001

The city of Plovdiv is coded as a dummy variable in reference to the city of Sofia. The p-values and SE are bootstrap-generated.

LMV/h-light motor vehicles per hour; HMV/h-heavy motor vehicles per hour; VLMV-velocity of light motor vehicles; VHMV-velocity of heavy motor vehicles; Laeq-equivalent noise level; Cn+In-combined space syntax measure of choice and integration with “n” radius.

B-unstandardized regression coefficient; SE-standard error of B; β-standardized regression coefficient; t-t-test; BCa CI-bias-corrected and accelerated confidence intervals

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networks. In our study we propose an interesting insight in the possibility to theoretically derive the needed SS radii and measures without any data on actual noise levels. In fact, just like the field-measured Laeq, the LimA-simulated Laeq correlated better with Cn+In than with any other SS measures. If this proves valid for various roadway systems, then researchers might consider implementing some form of SS to improve noise simulations with radii selected based on correlations with computer-simulated noise levels.

Quartieri et al. (19) proposed a statistical model for overcoming the need of experimental data, something they call “parameter free” model. “In this way” – they stated – “one can avoid the noise measurement campaign, in spite of collecting only easy to obtain road info, resulting in a strong save of time and resources” (19). However, a limitation to their approach is that it still requires traffic-flow data. Our goal was to inquire whether predictions could be based on the physical environment and geomorphology as much as possible. Much work needs to be done to justify this hypothesis. Our study is a by-product of a wider research not directly aimed at traffic prediction; it should therefore be considered a hypothesis and its practical implications should not be extrapolated beyond the analysed sample without scrutiny.

Because there is no information in the literature about the mechanisms through which SS might explain noise exposure independently of traffic counts, we propose several options. The main purpose for which SS was developed as a theory was to explain drivers’ and pedestrians’ behaviour and route choice when navigating through a roadway system (21-23). On the other hand, because SS is a one-dimensional representation of space (44), it can not account for the variance in noise exposure by supplementing geomorphological or geometrical data to simulations, unless it captures some of the correlated variance or linear combination of other traffic-flow and roadway factors. We therefore believe that SS somehow reflects and encompasses some of the variances in noise exposure explained by traffic-flow and some roadway characteristics such as the number of lanes, street-line length, speed limit, etc. Penn and Croxford (20) suggested that “since the pedestrian consumer, the vehicular producer and wind dispersion are all related to the spatial configuration of the built complex, […] spatial variations in pollutant concentrations […] might […] lead to differential exposure of the pedestrian population as they moved through the city”.

We hypothesize that part of the explanatory power of

SS is due to the fact that it corresponds to the accessibility of a street as both destination and pathway to other destinations. Thus more integrated streets with higher choice values are more likely to attract pedestrians and business and lead to the construction of city centres, malls, markets, schools, cafés, etc., which generate some of the street noise.

Moreover, these facilities are also more likely to be exposed to traffic noise. In these terms, SS may not only predict exposure levels but the distribution of exposed facilities and populations as well. Conversely, it is not likely to explain peripheral streets and highways. Regardless of whether its predictive capacity is socio-topological in nature, linking street segment use and functioning with noise exposure, or it acts as a mathematical “reflection” of correlations between other factors and noise exposure, if its performance is consistent, it might be of practical use.

Moreover, should SS be incorporated in algorithms relying on traffic-counting such as Quartieri’s and his group’s (19), it might help model that traffic flow.

Limitations There are some major limitations to our study which render the interpretation of its results preliminary. First, controlling for “city” balanced the predictions and yielded only a 2.4 % improvement in the model after inclusion of Cn+In. However, this should be critically interpreted because of the small number of measurements. In real life one would want to predict traffic noise in a specific city and hence such control variable distorts the model. It might be argued that controlling for city is not the same as analysing the data for each of the two cities separately, and this argument would be true. However, because of the significant difference in sample sizes, in Plovdiv the association between Cn+In and field-measured Laeq was not significant. Statistically significant does not always correspond to scientifically important (45).

Fewer measurements taken might also be associated with unequal distribution throughout the city (for example, measurements taken at arterial streets and highways neglecting inner-neighbourhood streets).

There are also issues with expertise, quality of noise measurement, and simulation protocols performed by local authorities in different cities. Some inaccuracies arising from our record linkage, which is susceptible to human error, are also possible, although, if present, they should not have significantly affected the results. Hand-drawing the axial maps

266 implies some imprecision but it is a viable option and it allowed us to exclude some pedestrianised streets.

From the statistical point of view, critics might be concerned about several issues. On one hand, small sample sizes at local scale are typical for SS studies (46). On the other, there is no consensus for statistical data handling in SS. Are outliers to be winsorised and what are the means to detect them? Paul (47) for example, reported significant improvement in their R2 value after removing the outliers, but whether to keep outliers depends on whether they are meaningful values in the sample and relies on subjective judgment by the analyst. The presence of outliers in a dataset might be justified on some occasions. Also, some authors considered a p-value of 0.10 marginally significant (48). Hayes also suggested that we should not be so strict in adhering to a 0.05 criterion (49).

The observed 3.5 % improvement in the predictive model of Plovdiv corresponds to 2.1 dB, if we assume that we are trying to predict Laeq=60 dB. This might not considerably affect decision-making and transportation policy, but if SS can be easily implemented, why not take the advantage of those 2.1 dB? Moreover, if SS theorists, acoustics experts, and computer scientists find practical benefits in our findings from both theoretical and empirical point of view, they might find ways to refine SS and give it more predictive power.

Variables associated with street geomorphology and traffic laws, which are supposed to affect traffic flow, were not included in the regression model using the LimA-simulated Laeq as predictor because the city plan and geomorphology are parameters already present in noise simulation algorithms. Nevertheless, other simulation packages should be tested by including SS measures.

Finally, SS is often criticised for the so-called “edge effect”, which is associated with the total radius “n” that we used (36).

Implementation This study might inspire further investigation into the ways to enhance the predictive capacity of current simulation algorithms. The next logical step for experts in the field of acoustics and architecture would be to replicate our findings and to conceptualise SS in this new light. Larger sample sizes, simulations with different programs, and inclusion of SS in the actual mathematical procedures of noise mapping will provide sufficient data whether our hypothesis holds.

Finally, experimentation and field testing might be of

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use in revealing the intrinsic mechanisms through which SS adds explanatory power to noise modelling.

CONCLUSION This paper provides an insight into the possibilities of implementing space syntax in traffic noise prediction with the aim to improve noise prediction or at least make it less dependent on empirical data collection. In our study, space syntax improved traffic noise predicting power of both traffic counts and simulation models, but the intrinsic mechanisms of this effect remain unclear. Currently we are broadening our research by including data from more diverse roadway systems. However, it is beyond the scope of this paper and the competence of its authors to study the mathematical justification of such approach.

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Sažetak Primjena prostorne sintakse radi poboljšanja simulacija buke: preliminarni rezultati iz dvaju cestovnih sustava Buka je jedan od četiriju glavnih oblika onečišćenja u svijetu. Da bi se urbanim planiranjem i upravljanjem gradovima mogle osmisliti i primijeniti odgovarajuće strategije ograničavanja buke, ključni je korak procijeniti razinu prometne buke u nekom gradu. Cilj je ovog istraživanja bio utvrditi može li prostorna sintaksa, koja se od 70-ih godina prošlog stoljeća rabi za predviđanje kretanja ljudi u gradskom okolišu, pridonijeti većoj prediktivnoj snazi simulacija buke. Analizirani su podaci o prometnim tokovima i o prometnoj buci dobiveni mjerenjima na terenu i računalnim simulacijama u dvama bugarskim gradovima: Sofiji i Plovdivu. Rezultati upućuju na to da prostorna sintaksa može poslužiti u predviđanju izloženosti prometnoj buci s obzirom na to da je u ovom istraživanju poboljšala postojeće modele simulacije buke koji se temelje na računalnim izračunima odnosno stvarnim mjerenjima. Nadamo se da ćemo ovim privući pozornost znanstvene zajednice na prostornu sintaksu kako bi se nastavila istraživati njena primjena u postojećim modelima i algoritmima predviđanja buke.

KLJUČNE RIJEČI: izloženost buci; mapiranje buke; onečišćenje bukom; predviđanje; teorijski modeli

CORRESPONDING AUTHOR: Angel M. Dzhambov Faculty of Medicine, Medical University of Plovdiv, 15-А Vasil Aprilov Blvd, 4002 Plovdiv, Bulgaria E-mail: angelleloti@gmail.com

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Appendix Basic input data for the analyses

Street segment â&#x201E;&#x2013; Sofia 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42

LMV/h

HMV/h

VLMV

VHMV

Fieldmeasured Laeq [dB]

LimAsimulated Laeq [dB]

Cn+In

5779 1516 1819 1074 1322 2908 2040 1345 3753 3197 1746 6417 1635 1800 3334 2249 1647 4213 1629 2183 1667 1756 1850 2528 1319 2498 1864 1251 1881 1356 3445 495 3436 1764 1245 887 1205 799 311 131 1095 1442

234 163 164 71 125 201 178 70 57 18 230 208 74 67 114 81 124 91 111 137 59 37 159 132 71 29 38 27 30 23 311 2 336 181 71 35 77 75 13 2 57 91

70 55 10 50 40 65 60 45 40 45 60 70 65 65 50 70 40 75 65 60 35 45 60 50 60 40 35 40 40 50 55 45 45 40 30 40 30 30 25 25 45 45

70 45 10 50 40 45 40 40 30 35 50 70 60 55 40 50 30 60 50 50 35 40 60 45 55 40 30 40 40 45 55 35 35 35 35 40 35 35 30 20 40 40

81 71.8 72.2 71 70.2 74.4 71.3 72.5 71.8 68.1 70.3 80.1 75.04 79.9 69.7 72.6 71.1 75.6 73.2 72.4 70.6 71 72.3 72.5 71.6 73.1 71.9 70.2 75.4 72.88 73.8 66.5 70.2 70.2 70.2 69.2 68.9 70.3 65.5 60.8 70 70.7

79.2 73.2 74.02 72.18 72.06 73.2 70.41 73.35 69.2 65.94 72.7 78.55 69.47 76.46 67.56 74.05 73.91 75.47 70.93 75.83 69.7 68.14 72.4 70.19 72.95 75.48 74.84 70.73 72.58 73.69 75.18 64.6 69.94 71.98 69.07 68.76 65.79 67.61 65.23 62.81 68.16 68.94

44955.23 37773.19 40042.09 29812.51 36661.1 31151.4 32376.08 31904.9 25665.94 26684.81 36910.77 44940.01 43874.7 43326.24 35042.3 38659.8 38996.72 37377.41 33825.75 38642.21 27197.07 41555.27 37708.98 30387.78 28192.88 42071.28 42349.43 38187.25 34537.03 42605.67 36218.34 24396.26 41887.45 37874.36 37217.7 42207.48 20579.16 25340.46 16927.15 17508.96 24935.67 24854.3

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Street segment № 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 Plovdiv 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85

LMV/h

HMV/h

VLMV

VHMV

Fieldmeasured Laeq [dB]

LimAsimulated Laeq [dB]

Cn+In

1168 1824 1107 100 2342 216 932 950 803 30 1954 1467.68 778 270 826 69 1300 2157 520 986 233 1249 77 582 1864 177 1543

81 334 233 7 186 16 73 80 143 3 31 40.93 100 112 74 12 211 156 75 190 53 17 10 12 19 3 62

40 50 65 35 70 40 35 60 50 50 60 36.7 50 60 55 40 50 60 50 50 50 40 40 40 40 5 50

40 50 60 30 80 20 35 60 40 30 60 30.51 50 50 50 30 45 50 45 40 40 40 30 35 35 5 45

70.1 75 73.4 62.2 76 64.5 68 75.1 72.7 60.4 72.6 67.96 71.4 71.3 70.9 63.8 72.1 74.4 70.6 72 67.9 71 62.3 70 70.2 64.5 69.7

68.05 73.9 76.14 64.69 77.86 66.91 66.41 72.91 74.96 62.09 75.44 69.84 60.95 68.69 68.77 65.98 74.19 74.06 72.98 73.38 68.13 68.71 63.99 69.07 68.76 66.83 67.44

31957.86 22958.04 34981.51 19908.12 29711.56 17481.98 29942.46 31056.65 26290.04 17530.29 46932.51 21772.55 21873.29 25431.56 25619.7 15005.46 29197.91 34286.43 29172.59 31011.59 30577.52 36661.86 22525.88 31922.18 27189.62 32919.91 30478.71

355 863 723 975 962 637 825 903 948 971 696 592 962 972 945 955

25 46 66 63 60 35 28 53 56 25 9 28 64 96 100 62

40 46.04 40 40 46.69 60 46.69 40 50 50 40 50 50 40 50 55

30 36.04 40 30 30 30 40 20 30 50 30 40 43 30 40 55

65.31 69.57 73.03 70.8 72.63 70.8 68.67 71.52 70.22 68.14 72.33 70.13 71.18 71.82 71.47 72.36

66.68 68.48 70.39 72.04 73.15 69.68 70.49 71.03 68.05 70.33 69.6 67.68 71.51 69.63 68.64 71.72

12965.27 16720.02 14134.13 16024.48 16205.69 13918.76 16760.89 17463.83 16792.72 18944.17 19525.87 17039.14 17430.56 17501.33 16536.43 14256.89

272 Street segment №

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LMV/h

HMV/h

VLMV

VHMV

Fieldmeasured Laeq [dB]

LimAsimulated Laeq [dB]

Cn+In

86 498 0 20 7.5 65.51 68.33 10946.33 87 960 55 55 55 71.19 68.19 15864.3 88 87 5 35 35 66.95 68.32 14214.69 89 973 69 45 45 70.35 71.07 16139.52 90 259 5 30 30 66.36 69.34 18871.25 91 393 5 30 10 67.62 67.24 19092.04 92 369.7 31.99 27.33 20.07 67.35 71.61 16497.82 93 1064.29 66.91 43.33 22.37 71.55 67.31 17899.69 94 835 18 30 30 68.91 69.9 16530.74 95 335 12 30 20 69.06 70.27 12999.37 96 659 43 60 40 68.9 70.38 17452.76 97 1286 89 55 30 70.78 67.53 16208.06 98 372 19 40 30 69.58 66.21 18144.33 99 887 50 50 30 70.85 70.36 18513.17 100 1113 39 50 40 70.95 73.98 19666.89 101 503 11 60 40 69.23 67.84 19650.3 102 635 32 50 30 68.66 68.79 16078.42 103 606 16 50 30 68 66.22 12653.95 104 949 61 60 40 73.07 70.29 15792.13 105 750 42 50 30 67.9 66.98 14598.81 106 836 45 40 30 70.59 70.31 11039.68 107 714 41 40 40 69.3 70.48 16470.02 108 634 43 40 30 66.05 67.35 16072.92 109 940 74 60 40 70.67 67.77 17837.2 110 934 67 60 40 72.45 72.48 18895.05 111 295 32 40 30 66.33 67.48 8638.1 112 332 37 40 30 67.66 66.57 8305.71 113 656 54 50 40 69.68 71.59 19787.06 114 914 71 60 40 71.44 71.25 19758.51 115 949 87 40 40 74.6 72.59 19602.74 116 978 68 50 40 72.7 70.92 19193.2 117 952 76 50 30 72.88 70.98 20738.31 118 526 29 30 30 69.81 66.03 14540.07 119 962 75 40 40 73.72 70.94 13063.25 120 895 25 50 30 71.14 73.6 19195.69 121 382 14 40 30 68.67 66.87 10866.59 LMV/h – light motor vehicles per hour; HMV/h-heavy motor vehicles per hour; VLMV-velocity of light motor vehicles; VHMV-velocity of heavy motor vehicles; LimA-noise simulation software; Laeq-equivalent noise level; Cn+In-combined space syntax measure of choice and integration with “n” radius

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DOI: 10.2478/10004-1254-65-2014-2493

Original article

Occupational exposure to blood among hospital workers in Montenegro Ljiljana Cvejanov-Kezunović1, Jadranka Mustajbegović2, Milan Milošević2, and Rok Čivljak3 School of Medicine Podgorica, University of Montenegro, Podgorica, Montenegro1, Andrija Štampar School of Public Health, School of Medicine, University of Zagreb2, Dr Fran Mihaljević Zagreb University Hospital for Infectious Diseases3, Zagreb, Croatia Received in January 2014 CrossChecked in January 2014 Accepted in September 2014

This cross-sectional study was performed in nine Montenegrin hospitals to estimate the burden of occupational exposure to blood among hospital workers in Montenegro in 2010 using a modified Croatian self-reporting questionnaire on exposure to blood-borne infections. Of the 1043 respondents, 517 (49.6 %) reported exposure to blood. Variations between the hospitals were not significant, except for the hospital in Kotor, which stands out with the high percentage of exposed hospital workers (p<0.05). More than 77 % of exposures were not reported through standard hospital protocols at the time of the incident. The most exposed group to blood were nurses (357 of 517; 69.1 %), but the percentage of exposed nurses within the group did not stand out compared to other occupations and was close to that reported by physicians (50.57 % vs. 57.49 %, respectively). The number of hospital workers with appropriate HBV vaccination was surprisingly low (35.7 %) and significantly below the recommended best practice (at least two consecutive doses of HBV vaccine documented for 100 % of employees) (p<0.001). Even with its limitations, our study fills a gap in knowledge about the actual number of sharps incidents and other occupational exposure to blood among hospital workers in Montenegro as well as about the issue of underreporting, which is very common. It also confirms the urgent need for active implementation of special, comprehensive measures to prevent needle-stick and other sharps injuries. Constant staff training, life-long learning, and standardising post-exposure procedures are also recommended.

KEY WORDS: blood-borne infections; epidemiology; sharps injuries

Occupational exposure to blood among hospital workers poses a significant risk of blood-borne infection (BBI) to pathogens such as the hepatitis B virus (HBV), the hepatitis C virus (HCV), and the human immunodeficiency virus (HIV) and consequent transmission of blood-borne diseases. The most likely type of occupational exposure is the sharps, or more specifically, needlestick injury (NSI), followed by the contact of the mucous membrane or non-intact skin (exposed skin that is chapped, abraded, or afflicted with dermatitis) with blood, tissue, or potentially infectious body fluids (1, 2). However, NSIs are believed to be grossly underreported (often half the incidents are not reported) (3, 4).

In the worldwide healthcare population of 35 million, about three million percutaneous exposures to blood-borne pathogens are reported every year.

These exposures are estimated to result in 16,000 hepatitis C, 66,000 hepatitis B, and 1,000 HIV infections among healthcare workers (5). Over 90 % of these infections occur in low-income countries, and most are preventable (5, 6). The transmission of HBV, HIV, and HCV to patients by infected healthcare workers has also been documented (7).

While the risk of HBV infection after a needlestick injury is 6-30 %, the risk of HIV is about 0.3 %.

Occupational risk of HCV infection after documented exposure is about 2 % (8). However, HBV infection

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can be prevented by vaccination. Furthermore, if a susceptible (non-vaccinated or vaccine nonresponsive) individual is exposed to HBV, prophylaxis with hepatitis B immune globulin is also effective (9).

A range of interventions has been implemented to maximise the safety of healthcare workers in highincome countries, including standard/universal precautions, personal protective equipment, routine hepatitis B vaccination, post-exposure prophylaxis, engineered safety devices, injury surveillance, and enactment of relevant legislation (10). However, these benefits are rarely available to healthcare workers in low-income countries where less attention is paid to the risks associated with occupational exposure to blood, and the risks are arguably greater because of suboptimal infection control practices and higher incidence of BBIs (2). Other risk-promoting factors include hospital overcrowding, low healthcare workerto-patient ratio, limited awareness of the risks associated with exposure to blood (11), failure to implement universal precautions; low supply of the basic safety equipment for handling contaminated needles and other sharps (2, 11, 12), and unavailable hepatitis B immunisation and post-exposure prophylaxis for HIV. In developing countries, Montenegro included, exposure and health impacts are rarely monitored and much remains to be done to protect healthcare workers from the risks of infection, illness, disability, and death. To better target prevention efforts, information on the burden caused by occupational transmission would be useful (5, 12-14).

Since reporting on sharps incidents and occupational BBIs among Montenegrin hospital workers is low, we wanted to establish the extent of occupational exposure to blood and the risk of BBI from all sources among hospital workers by occupation and by hospital.

We also wanted to assess hepatitis B immunisation coverage and the awareness of BBIs at work among hospital workers.

PARTICIPANTS AND METHODS This cross-sectional multicentre study was carried out among hospital workers at nine centres: the Clinical Centre of Montenegro (CCMNE), six general hospitals (Bar, Berane, Bijelo Polje, Cetinje, Kotor, Nikšić), and two specialist hospitals (Brezovik Hospital for Pulmonary Diseases and Tuberculosis,

and Risan Orthopaedic Hospital) from April to September 2011.

The total number of hospital workers in Montenegro is 4,008, and the total number of hospital workers in the nine participating hospitals is 3,639. We distributed 1,600 questionnaires to hospital workers with at least one year of working experience, whose job involves the risk of BBI. This includes staff not providing health care but providing services that may put them at risk such as cleaning, delivery, and maintenance. We excluded the first-year employees because the questionnaire asks participants to report events of the previous year (13, 14). We also excluded hospital administrative staff for obvious reasons. The response rate was 65.2 %; of the 1,043 respondents 865 (82.9 %) were women and 178 (17.1 %) men (Table 1).

Table 1 Respondent demographic data (n=1043)

n

%

Hospital

CCMNE Bar Cetinje Kotor Bijelo Polje Brezovik Risan Nikšić Berane

456 157 38 56 88 59 51 66 72

43.7 15.1 3.6 5.4 8.4 5.7 4.9 6.3 6.9

Gender

Male Female

178 865

17.1 82.9

Occupation

Physicians Nurses Lab personnel Other non-HCW*

167 706 68 102

16.0 67.7 6.5 9.8

Age (years): mean±SD Years of work: mean±SD

41.78±10.87 18.18±10.71

CCMNE – Clinical Centre of Montenegro

*Servicing staff such as cleaning, delivery, and maintenance whose job involves incidental exposure to blood

The study protocol was approved by the Ethics Committee of the Clinical Centre of Montenegro, the institution responsible for the approval of all research in humans. All hospital directors and senior personnel were informed about the study aims and questionnaire content.

We made it clear for the participants that participation was voluntary and anonymous and all were fully informed about the design and purpose of the study. The questionnaires were distributed and

Cvejanov-Kezunović Lj, et al. BLOOD EXPOSURE IN MONTENEGRIN HOSPITAL WORKERS Arh Hig Rada Toksikol 2014;65:273-280

collected in unmarked envelopes by one of the authors with the help of senior hospital personnel. Those who did not wish to participate were asked to return a blank questionnaire.

Questionnaire We used an anonymous self-reporting questionnaire on exposure to blood-borne infections in hospital workers. The questionnaire had been utilised in several studies in Croatia (13, 14) and we modified it to obtain quantitative and qualitative data on exposure to blood through skin (sharps injuries, needlestick, cuts from sharp objects) and mucosa, on hepatitis B vaccination coverage, on HBV, HCV, and HIV test findings, incident reporting and reasons for non-reporting, and whether the site had a protocol in place for postexposure prevention. The definition of NSI included injuries caused by sharps such as hypodermic needles, blood collection needles, i.v. cannulas, suture needles, winged needle i.v. sets, and needles used to connect parts of the i.v. delivery systems. Hospital workers were asked to report the frequency of occupational exposure to blood and other body fluids in the previous year (2010) and over their working lifetime. Those who had an injury were also asked whether they reported the injury when it happened and why not if they did not.

Other data included demographics (hospital site, gender, occupation, age, and years of work), compliance with universal precautions, hepatitis B immunisation status, availability of safety equipment, perception of risk, awareness of BBI transmission, perception of workplace safety climate, and barriers to implementation of safe practices.

Statistical analysis Data distribution was tested using the KolmogorovSmirnov test. Differences between exposure to blood, exposure reporting, and hepatitis B vaccination status between hospitals, occupations, and departments were analysed using the chi-square test. The rate of exposure to blood per 100 occupied beds per year was calculated by dividing the total number of blood exposure incidents reported over one year (2010) (numerator) with the number of occupied hospital beds in an institution for the same time period (denominator) multiplied with 100. We used this denominator, as it corrects for unused hospital beds. All p values below 0.05 were considered significant. All statistical

275

calculations were made in Statistica, version 10.0 (Stat Soft, Inc Tulsa, USA).

RESULTS AND DISCUSSION Table 1 shows the demographic data about the 1043 respondents (hospital, gender, occupation, age, and years of work). Exposure to blood, hepatitis B vaccination coverage, and exposure reporting are shown in Table 2. Nearly 50 % of the respondents had experienced at least one incident of occupational exposure to blood in 2010, but more than 75 % did not report them through standard hospital protocols.

In terms of best practice (100 % reporting rate), underreporting was significant (p<0.001). The primary reason for underreporting incidents was that workers were not aware of a protocol for reporting or protective procedures after an incident. More than one-quarter replied that the reason for not reporting was that the patients involved in the incident did not belong to groups at risk. Similarly, a cross-sectional study in Iranian nurses showed that only 36.8 % of those who experienced a needle-stick injury reported the incident through regular proceedings. The primary reasons for not reporting were dissatisfaction with follow-up investigations (33.3 %) and low-risk considerations concerning source patients (29.2 %) (15).

It would be interesting to explore the relationship between organisational and workplace characteristics of individual hospitals with varying levels of exposure, but this is beyond the scope of our study. However, it is important to note that NSI rates are affected by a number of factors, including the level of NSI underreporting and the types of patients a hospital treats. For example, the CCMNE is likely to treat a higher number of patients requiring intensive care than a community hospital and may therefore have a higher NSI rate per patient.

HBV vaccination turned out to be surprisingly low: only 35.7 % of the respondents reported to have received at least two doses of HBV vaccine whereas more than 60 % worked without adequate HBV protection. Again, in terms of the best practice (at least two consecutive doses of HBV vaccine documented for 100 % of employees), the undervaccination was statistically significant (p<0.001) (3).

Table 3 shows the distribution of exposed and unexposed hospital workers by occupation and department. Physicians had the highest rate of multiple exposures compared to other occupations (p<0.001),

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Table 2 Exposure to blood, hepatitis B vaccination coverage, and exposure reporting in Montenegrin hospitals in 2010

Exposure to blood in 2010, n (%) Hospital

Missing data

Was exposure reported through hospital protocol, n (%)‡

No

Yes, in <50 % of cases

Yes, in ≥50 % of cases

Missing data

HBV vaccination, n (%)*

Yes

No

Missing data

Yes

No

CCMNE (n=456)

236 (51.8)

142 (31.1)

78 (17.1)

175 (74.2)

36 (15.3)

23 (9.7)

2 (0.5)

131 (28.8)

323 (71.0)

2 (0.2)

Bar (n=157)

68 (43.3)

75 (47.8)

14 (8.9)

44 (64.7)

18 (26.5)

6 (8.8)

0 (0.0)

85 (54.2)

71 (45.2)

1 (0.6)

Cetinje (n=38)

18 (47.9)

15 (39.5)

5 (13.2)

13 (72.2)

2 (11.1)

3 (16.7)

0 (0.0)

6 (15.8)

32 (84.2)

0 (0.0)

Kotor (n=56) Bijelo Polje (n=88) Brezovik (n=59)

40 (71.4)†

9 (16.1)

7 (12.5)

35 (87.5)

2 (5.0)

3 (7.5)

0 (0.0)

26 (46.4)

30 (53.6)

0 (0.0)

36 (40.9)

21 (23.9)

31 (35.2)

34 (94.4)

1 (2.8)

1 (2.8)

0 (0.0)

43 (48.9)

44 (50.0)

1 (1.1)

25 (42.4)

18 (30.5)

16 (27.1)

21 (84.0)

2 (8.0)

2 (8.0)

0 (0.0)

8 (13.6)

51 (86.4)

0 (0.0)

Risan (n=51)

25 (49.0)

15 (29.4)

11 (21.6)

21 (84.0)

4 (16.0)

0 (0.0)

0 (0.0)

21 (41.2)

30 (58.8)

0 (0.0)

Nikšić (n=66)

29 (43.9)

17 (25.8)

20 (30.3)

21 (72.4)

2 (6.9)

6 (20.7)

0 (0.0)

25 (37.9)

41 (62.1)

0 (0.0)

Berane (n=72)

40 (55.6)

21 (29.2)

11 (15.3)

35 (87.5)

1 (2.5)

4 (10.0)

0 (0.0)

27 (37.5)

45 (62.5)

0 (0.0)

Total (n=1043)

517 (49.6)

333 (31.9)

193 (18.5)

399 (77.2)

68 (13.2)

48 (9.3)

2 (0.4)

372 (35.7)

667 (64.0)

4 (0.3)

CCMNE–Clinical Centre of Montenegro † Significant difference (chi-square test; p<0.05) compared to total average exposure to blood in 2010 (49.6 %) ‡ All values compared to recommended best practice (100 % reporting rate) were statistically significant (chi-square test; p<0.001)

*All values compared to recommended best practice values (at least two consecutive doses of HBV vaccine documented for 100 % of employees) were statistically significant (chi-square test; p<0.001)

whereas differences between departments were not significant. However, even the lowest reported rate of 13.6 % in the non-surgery departments is alarmingly high (8). A Croatian survey (13) showed that the risk of occupational exposure in gynaecology and obstetrics departments was greater than expected; 89 % of healthcare workers experienced at least one type of exposure throughout their working life. A number of studies have shown that healthcare workers who perceived that they were at high risk of occupational exposure to BBIs reported more sharps injuries in the preceding year than those who did not see themselves at risk (14,16). It is possible that this perception of risk is related to the actual experience of sharps injuries and that healthcare workers who

experience sharps injuries are more likely to associate health care in general with increased risk. In turn, healthcare workers who are more compliant with the universal precautions are less likely to experience a sharps injury. This relationship between occupational exposure to blood and compliance with the universal precautions has been demonstrated by Garb (17) and Grime et al. (18) and reinforces the assumption that the universal precautions enhance the safety of health care workers who use them.

Table 4 presents the rate of blood exposure incidents per occupied bed per day. The average daily census of occupied hospital beds for the same year as the reported needle-sticks served as the denominator since it corrects for unused hospital beds. This gives

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Table 3 Distribution of exposed and unexposed hospital workers by occupation and department

Number of respondents exposed to blood in 2010

Occupation

Without exposures Physicians (n=167) Nurses (n=706) Lab personnel (n=68) Other non-HCW (n=102)*

One exposure

Multiple exposures

n (%)

n (%)

n (%)

71 (42.5) 350 (49.6) 40 (58.8) 65 (63.8)

51 (30.5) 260 (36.8) 18 (26.5) 23 (22.5)

45 (27.0) 96 (13.6) 10 (14.7) 14 (13.7)

One vs.

Without exposures p value

Multiple vs. Without exposures p value

0.012

<0.001

Department

Non-surgical (n=546) 295 (54.0) 177 (32.4) 74 (13.6) Surgical (n=378) 158 (41.8) 146 (38.6) 74 (19.6) 0.001 0.003 Laboratory (n=113) 67 (59.3) 29 (25.7) 17 (15.0) No data (n=6) 6 (100.0) 0 (0.0) 0 (0.0) *Servicing staff such as cleaning, delivery, and maintenance whose job involves incidental exposure to blood

a rough idea of the institutional needle-stick experience, which can then be used to track NSI levels over time (19, 20).

Table 5 shows that the most common cause of exposure to blood (multiple exposures included) were hollow needle injuries (31.4 %).

The proportion of exposure incidents reported in our study (totalling 1015) is comparable to that found in studies on other low-income countries. A study on Turkey included 988 hospital workers: 500 nurses (51 %), 212 residents (21 %), 152 nursing assistants (15 %), and others (13 %) and showed that 634 (64 %) of the HCWs had been exposed to blood and body fluids at least once in their professional life (0.85 % exposure per person-years). Of the injured hospital workers, 60 (28 %) had no form of personal protective equipment at the time of the incident, and 144 (67 %) sought no medical advice about the injury (21).

Experience from China showed that the subjects with the highest risk of needle-stick and other sharps injuries were from departments of gynaecology and obstetrics, surgical departments, intensive care units and emergency rooms (22). The sharps injuries mainly occurred when the healthcare workers were breaking ampoule or vial glass (incidence 46.7 %), withdrawing needles (31 %), preparing sharp devices (25.7 %), or performing surgery (14.5 %).

When interpreting the findings of this study, some limitations should be considered. Retrospective reporting of occupational exposures is subject to recall bias. Furthermore, it was not possible to identify the characteristics of non-respondents and establish

whether they were different in some important way from respondents.

Even with its limitations, our study fills a gap in knowledge about the actual number of sharps incidents and other occupational exposure to blood among hospital workers in Montenegro as well as about the issue of underreporting, which is very common. It also confirms the urgent need for active implementation of special, comprehensive measures to prevent needlestick and other sharps injuries. Constant staff training, life-long learning, and standardising post-exposure procedures are also recommended.

Hospitals should adopt systematic control measures, prospective record keeping, and set up a Table 4 Blood exposure among respondents adjusted for occupied beds per day in 2010

Hospital

Exposure (n)

Occupied beds

Exposure to blood per 100 occupied beds (%)

CCMNE Bar Cetinje Kotor Bijelo Polje Brezovik Risan Nikšić Berane

501 188 55 69 42 29 37 46 48

493 125 65 99 100 118 83 167 133

101.62 150.40 84.62 69.70 42.00 24.58 44.58 27.54 36.09

Total 1015 1383 CCMNE – Clinical Centre of Montenegro

73.39

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Table 5 Specific causes of blood exposure (including multiple exposures) among 517 respondents reporting exposure in 2010

Cause of exposure

Sharps injuries

Non-sharps exposure

Total n (%)

Hollow needle injury

319 (31.4)

Surgical needle injury

132 (13.0)

Glass cut Scalpel cut

110 (10.8) 97 (9.6)

Contact with non-intact skin

171 (16.8)

Contact with mucus Other exposures Patient bite Total

116 (11.4) 41 (4.0) 29 (2.9) 1015 (100)

special occupational health and safety unit to implement these measures. On the national level, it is necessary to establish specific programmes for health workers and adapt the existing laws and regulations to the specific needs of healthcare jobs.

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2. Gessessew A, Kahsu A. Occupational exposure of health workers to blood and body fluids in six hospitals of Tigray region (August 1-30, 2006): magnitude and management.

Ethiop Med J 2009;47:213-9. PMID: 19954124 3. Kuhar DT, Henderson DK, Struble KA, Heneine W, Thomas V, Cheever LW, Gomaa A, Panlilio AL; USPHS Working Group on Occupational Postexposure Prophylaxis; National Center for Emerging and Zoonotic Infectious Diseases (US) Division of Healthcare Quality Promotion. Guidelines for the Management of Occupational Exposures to HIV Updated U.S. Public Health Service guidelines for the management of occupational exposures to HIV and recommendations for postexposure prophylaxis. MMWR Recomm Rep 2013 September 9:1-48.

4. Kermode M, Jolley D, Langkham B, Thomas MS, Crofts N. Occupational exposure to blood and risk of bloodborne virus infection among health care workers in rural north Indian health care settings. Am J Infect Control 2005;33:34-41.

PMID: 15685133 5. Panlilio AL, Cardo DM, Grohskopf LA, Heneine W, Ross CS, Service USPH. Updated US Public Health Service guidelines for the management of occupational exposures to HIV and recommendations for postexposure prophylaxis.

MMWR Recomm Rep 2005;54:1-17.

6. Centers for Disease Control and Prevention, U.S. Public Health Service Task Force. U.S. Public Health Service Task

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Force recommendations for use of antiretroviral drugs in pregnant HIV-1-infected women for maternal health and interventions to reduce perinatal HIV-1 transmission in the United States. MMWR Recomm Rep 2002;51:1-38;quiz CE1-4. PMID:12489844 Centers for Disease Control and Prevention. Updated CDC Recommendations for the Management of Hepatitis B VirusInfected Health-Care Providers and Students. MMWR Recomm Rep 2012 [displayed 3 September 2014]. Available at http://www.cdc.gov/mmwr/preview/mmwrhtml/rr6103a1. htm Au E, Gossage JA, Bailey SR. The reporting of needlestick injuries sustained in theatre by surgeons: are we underreporting? J Hosp Infect 2008;70:66-70. doi: 10.1016/j. jhin.2008.04.025 West DJ. The risk of hepatitis B infection among health professionals in the United States: a review. Am J Med Sci 1984;287:26-33. PMID: 6369984 Makary MA, Al-Attar A, Holzmueller CG, Sexton JB, Syin D, Gilson MM, Sulkowski MS, Pronovost PJ. Needlestick injuries among surgeons in training. New Engl J Med 2007;356:2693-9. PMID: 17596603 Richman KM, Rickman LS. The potential for transmission of human immunodeficiency virus through human bites. J Acquir Immune Defic Syndr 1993;6:402-6. PMID: 8455145 Prüss-Ustün A, Rapiti E, Hutin Y. Estimation of the global burden of disease attributable to contaminated sharps injuries among health-care workers. Am J Ind Med 2005;48:482-90.

PMID: 16299710 Obad I PD, Čivljak R, Milošević M, Stamenić V, Kalenić S. Procjena profesionalne izloženosti infekcijama koje se prenose krvlju u djelatnika ginekološko-porodiljskih odjela u Hrvatskoj [Assessment of occupational exposure to blood borne infections among personnel at obstetrics and gynecology departments in Croatia, in Croatian]. Infektološki glasnik 2012;32:159-66. Čivljak R. Učinak propisanog snopa postupaka na smanjenje rizika profesionalne izloženosti bolničkog osoblja infekcijama koje se prenose krvlju. [Care bundles in lowering hospital workers occupational risk exposure to the blood borne infection, in Croatian]. PhD thesis. Zagreb: Zagreb University School of Medicine; 2014.

Azadi A, Anoosheh M, Delpisheh A. Frequency and barriers of underreported needlestick injuries amongst Iranian nurses, a questionnaire survey. J Clin Nurs 2011;20:488-93. doi: 10.1111/j.1365-2702.2010.03252.x Puro V, De Carli G, Petrosillo N, Ippolito G. Risk of exposure to bloodborne infection for Italian healthcare workers, by job category and work area. Studio Italiano Rischio Occupazionale da HIV Group. Infect Control Hosp Epidemiol 2001;22:206-10. PMID: 11379710 Garb JR. One-year study of occupational human immunodeficiency virus postexposure prophylaxis. J Occup Environ Med 2002;44:265-70. PMID: 11911028 Grime PR, Ris L, Binns C, Carruthers JR, Williams S. PanThames survey of occupational exposure to HIV and the use of post-exposure prophylaxis in 71 NHS trusts. J Infect 2001;42:27-32. PMID: 11243750 Magnavita N, Placentino RA, Puro V, Sacco A. Management of health care workers with blood-borne infections. Arch Intern Med 2003;163:1489-90; author reply 1490. PMID: 12824103

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20. Gajić Z, Rajčević S, Đurić P, Ilić S, Dugandžija T. Knowledge and attitudes of health care workers from the Primary Health Center Indjija, Serbia, on occupational exposures to bloodborne infections. Arh Hig Rada Toksikol 2013;64:14551. doi: 10.2478/10004-1254-64-2013-2268 21. Azap A, Ergönül O, Memikoğlu KO, Yeşilkaya A, Altunsoy A, Bozkurt GY, Tekeli E. Occupational exposure to blood

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and body fluids among health care workers in Ankara, Turkey. Am J Infect Control 2005;33:48-52. PMID: 15685135 22. Shi CL, Zhang M, Xie C. [Study on status of needle-stick and other sharps injuries among healthcare workers in a general hospital, in Chinese]. Zhonghua Lao Dong Wei Sheng Zhi Ye Bing Za Zhi 2011;29:939-43. PMID: 22470951

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Sažetak Profesionalna izloženost krvi u bolničkih radnika u Crnoj Gori Kako bi se procijenila profesionalna izloženost krvi bolničkih radnika u Crnoj Gori tijekom 2010. godine, provedeno je presječno istraživanje prilagođenim Hrvatskim upitnikom samoprocjene izloženosti infekcijama koje se prenose krvlju u devet bolnica. Od 1043 ispitanika, njih 517 (49,6 %) prijavilo je izloženost krvi.

Nije bilo značajnih razlika između bolnica, osim bolnice u Kotoru koja se izdvaja visokim udjelom izloženih bolničkih radnika (p<0,05). Više od 77 % izloženosti nije prijavljeno u vrijeme nastanka incidenta putem standardnog bolničkog protokola. Najizloženija skupina bile su medicinske sestre (357 od 517; 69,1 %), ali udio izloženih sestara unutar skupine nije se značajno razlikovao u usporedbi s liječnicima (50,57 % prema 57,49 %). Broj bolničkih radnika koji imaju odgovarajući HBV cjepni status bio je iznenađujuće nizak (35,70 %) i značajno ispod preporučene dobre prakse (najmanje dvije uzastopne doze HBV cjepiva koje su dokumentirane u 100 % zaposlenih; p<0,001). Unatoč svojim ograničenjima, rezultati istraživanja popunjavaju raskorak u spoznajama o stvarnom broju ozljeda oštrim predmetima, ostalim profesionalnim izloženostima krvi i o vrlo uobičajenoj praksi bolničkih radnika u Crnoj Gori da ne prijavljuju te incidente.

Također potvrđuju potrebu hitnog djelovanja u aktivnom uvođenju specifičnih i sveobuhvatnih mjera za prevenciju ubodnih incidenata i ozljeda oštrim predmetima. Preporučuje se kontinuirana obuka osoblja, cjeloživotno učenje i standardiziranje postekspozicijskih postupaka.

KLJUČNE RIJEČI: epidemiologija; infekcije prenosive krvlju; ozljede oštrim predmetima

CORRESPONDING AUTHOR: Ljiljana Cvejanov Kezunović, MD PhD Associate Professor Chair, Department of Occupational Health Medical Faculty Podgorica, University of Montenegro Kruševac bb, Podgorica 20 000, Montenegro E-mail: ljiljakez@hotmail.com, kezunoviclj@ac.me

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DOI: 10.2478/10004-1254-65-2014-2527

Original article

Cadmium, lead, and mercury exposure assessment among Croatian consumers of free-living game Maja Lazarus1, Andreja Prevendar Crnić2, Nina Bilandžić4, Josip Kusak3, and Slaven Reljić3 Analytical Toxicology and Mineral Metabolism Unit, Institute for Medical Research and Occupational Health1, Department of Pharmacology and Toxicology2, Department of Biology3, Veterinary Faculty, University of Zagreb, Laboratory for Residue Control, Croatian Veterinary Institute4, Zagreb, Croatia Received in April 2014 CrossChecked in April 2014 Accepted in July 2014

Free-living game can be an important source of dietary cadmium and lead; the question is whether exposure to these two elements is such that it might cause adverse health effects in the consumers. The aim of this study was to estimate dietary exposure to cadmium, lead, and mercury from free-living big game (fallow deer, roe deer, red deer, wild boar, and brown bear), and to mercury from small game (pheasant and hare), hunted in Croatia from 1990 to 2012. The exposure assessment was based on available literature data and our own measurements of metal levels in the tissues of the game, by taking into account different consumption frequencies (four times a year, once a month and once a week). Exposure was expressed as percentage of (provisional) tolerable weekly intake [(P)TWI] values set by the European Food Safety Authority (EFSA). Consumption of game meat (0.002-0.5 % PTWI) and liver (0.005-6 % PTWI) assumed for the general population (four times a year) does not pose a health risk to consumers from the general population, nor does monthly (0.02-6 % PTWI) and weekly (0.1-24 % PTWI) consumption of game meat.

However, because of the high percentage of free-living game liver and kidney samples exceeding the legislative limits for cadmium (2-99 %) and lead (1-82 %), people should keep the consumption of certain game species’ offal as low as possible. Children and pregnant and lactating women should avoid eating game offal altogether. Free-living game liver could be an important source of cadmium if consumed on a monthly basis (3-74 % TWI), and if consumed weekly (11-297 % TWI), it could even give rise to toxicological concern.

KEY WORDS: brown bear; deer; hare; liver; meat; pheasant; provisional tolerable weekly intake; toxic metal; wild boar

Hunting in Croatia has a long history (officially since the enactment of the Hunting Bill in 1893) as leisure, economic activity, and source of quality food.

Game meat is served in restaurants and households throughout the country. Considered a delicacy, it is far more valued for its exceptional taste than for its nutritive properties; it is rich in proteins, minerals Fe, Mg, P, K, Zn, vitamins riboflavin, niacin, pyridoxine, and cobalamine (1) and has a favourable fatty acid composition (2). However, being part of the terrestrial soil-plant-animal food chain, free-living game have

generally been reported having higher Cd, Pb, and Hg levels than farmed animals (3). Food is the main source of non-occupational exposure to Cd, Pb, and Hg in the non-smoking adult population (4-6). Free-living game is dominantly consumed by hunters and their families and friends (2, 7-11). The 65,000 hunters registered in Croatia in 2012 constituted about 1.4 % of the general population (12).

The Scientific Panel on Contaminants in the Food Chain (CONTAM) conducted a risk assessment of various food contaminants in European countries,

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which was endorsed by the European Food Safety Authority (EFSA). EFSA considers frequent consumers of free-living game meat and offal to be exposed to higher Cd (only from offal) and Pb levels than the general adult population (5, 6). In 2011 and 2012, German, Swedish, Spanish, and British national food authorities advised pregnant women and children to reduce game consumption [reviewed by Green and Pain (13) and Meltzer et al. (11)].

Several recent European studies (7, 10, 14-17) focused on exposure to toxic metals from consumption of free-living animals. Some pointed out that regular intake of free-living game is likely to result in exceeding the provisional tolerable weekly intake (PTWI) for Cd and Pb (14-17) proposed by the EFSA (5, 18). Epidemiological studies reported an association between human blood Pb concentration and consumption of free-living game, small, especially birds (13, 19, 20), and big, like deer, moose, and reindeer (8, 11, 21, 22), but some studies did not report such association for Cd and Hg (21, 22). The prevailing sources of high Pb in free-living game meat appear to be fragments of lead ammunition (16, 23-25). High Cd levels in game are the consequence of accumulation, especially in the liver and kidney (6). The same applies to Hg but at much lower levels. In 2008, the Croatian regulation on maximum allowed levels of metals (26) was harmonised with EU legislation (27) and since then, the monitoring of Hg in animal tissues (other than fish) for human consumption was no longer obligatory. On the national level, at least 100 samples of marketed free-living game are tested for Cd and Pb every year according to the Commission Decision (28). However, the vast majority of game is not controlled for residues because non-marketed food is not subject to these tests. Data about toxic metal levels in free-living game from Croatia are mainly limited to scientific research (29-39). In 2012, the Croatian Food Agency published a heavy metal exposure assessment (40) based on data for wild boar meat, liver, and kidney. Data for the roe and red deer were available only for the liver.

Considering that comprehensive exposure assessments have not yet been conducted in Croatia involving multiple element data from regularly hunted game species, the present study aimed to gather relevant data in one place and contribute to existing knowledge with estimations of Cd, Pb, and Hg exposure of the Croatian population due to consumption of the most common game species, big and small. Our assessment is based on recently published data and

available consumption frequency data for the Croatian population. As a novel contribution, this study also provides data on Pb levels in brown bears from Croatia, along with updated Cd and Hg levels in brown bear tissues. The data were discussed according to the current legislative maximum levels (ML) for farmed animals and exposure according to (P)TWI levels of toxic metals by the EFSA.

MATERIALS AND METHODS Study area and data collection The animals included in this study were all legally hunted on Croatian territory (Figure 1) between 1990 and 2012. Of all species, only brown bears were hunted in Gorski kotar and Lika, mountainous regions of Croatia. Fallow deer was hunted on the small northAdriatic island of Brijuni, and the rest of the species originated from the Pannonian (lowland) region. These three geographical regions vary by climate and geomorphological properties. Considering the here observed metals (Cd, Pb, and Hg) topsoil concentrations in the Pannonian region and Brijuni were generally much lower than in the mountainous regions. A noteworthy exception was the higher Pb levels in the soil of Drava and Mura valley on the very north of Croatia. The highest soil Hg concentrations were reported in the north and north-west part of Gorski kotar, probably due to mining of small cinnabar deposits in Tršće near Čabar (41) and proximity of the now closed second largest Hg-mine in the world (Idrija, Slovenia). Furthermore, elevated levels of Cd and Pb of anthropogenic origin were reported near industrial areas (cities of Zagreb, Sisak, Kutina, Osijek, Šibenik), as well as high Pb deposition in the Drava valley (42).

A part of data on toxic metal levels in the muscle, liver, or kidney tissue used in this study to estimate exposure have been published elsewhere and include pheasant [Phasianus colchicus (29)], hare [Lepus europaeus P. (30)], fallow deer [Dama dama L. (31)], roe deer [Capreolus capreolus L. (32, 33)], red deer [Cervus elaphus L. (34-36)], wild boar [Sus scrofa L. (33, 35, 37, 38)], and brown bear [Ursus arctos L. (39)]. Data on pheasant and hare are limited to Hg whereas fallow deer data are limited to Cd. This study also brings our own unpublished data regarding Pb, Cd, and Hg levels in 206 more brown bear tissues,

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Figure 1 Map showing the hunting areas where animals were sampled. The hunting estates and areas are marked dark gray (1 - Molve; 2 - Brijuni Islands; 3 - Medvednica; 4 - Vrbovec; 5 - Kupčina; 6 - Tuhelj; 7 - Đurđevac; 8 - Slatina; 9 - Črnovšćak; 10 - Pokupski bazen; 11 - Spačva; 19 - Petrova gora; 20 - Podunavlje-Podravlje). The counties relevant for the study are marked light gray (12 - Osječko-baranjska county; 13 - Vukovarsko-srijemska county; 14 - Virovitičkopodravska county; 15 - Požeško-slavonska county; 16 - Brodsko-posavska county; 17 - Sisačko-moslavačka county; 18 - Bjelovarsko-bilogorska county).

Black dots represent the exact coordinates of locations where brown bears were hunted (based on data for animals from this study and reference 39). Fallow deer was hunted at Brijuni Islands – 2 (based on reference 32). Roe deer originated from hunting estates 3, 4, 5, 6, 7, 8, 9, 10, 11 (based on references 32, 33). Red deer was hunted at locations 12, 13, 14, 15, 20 (based on references 34-37). Wild boar was hunted at locations 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19 (based on references 33-38). Pheasant and hare were hunted at hunting estate Molve – 1 (based on references 29, 30)

which together with previously reported findings (39) represents a total of 317 brown bears tissues analysed in Croatia by 2012.

Details about sampling and metal analysis in tissues of each species, performed by three independent expert analytical laboratories, are available in the respective references. For the purpose of this study, we used raw data (metal mass fractions for each animal) with the approval from the authors. Data on one species from several reports (e.g. red deer, wild boar) were merged and do not include age and sex distribution. All levels are presented in mg kg -1 of wet tissue mass (w. m.).

For descriptive statistics of the raw data, which includes arithmetic mean, range, and the 95 th percentile, we used Statistica for Windows, version 12.0 (StatSoft, Inc., Tulsa, USA). For this purpose, metal levels below the limit of detection (LOD) were assigned their separate LOD value (upper-bound

values) as recommended by the WHO (43). Fallow deer Cd data represent less than 50 samples and less than 25 quantified results, so lower-bound values were reported in the text together with upper-bound values (43), while in the tables and Figure 2 only the upperbound value was indicated. However, it should be noted that due to the differences in the LODs designated within the analytical methods, the presented results should be taken with reserve.

Exposure assessment Exposure assessments for the consumers of big game (deer species, wild boar and brown bear) were based on Cd, Pb, and Hg levels in meat and liver. We assumed that kidney consumption is negligible and thus did not include it in the estimation. For small game, only Hg exposure estimation was done. Weekly exposure to Cd, Pb, and Hg from meat and liver was estimated based on mean or 95th percentile metal levels

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and three consumption scenarios, i.e. consumption once a week (often), once a month (regular), and four times a year (rare). These scenarios were based on free-living game consumption frequency reported by Florijančić (9) in a population group whose 93 % declared to consume game and 51 % were hunters and their household members. Categorisation by consumption frequency was taken over from the study

by Meltzer et al. (11). In our calculations we assumed that an average adult person weighs 70 kg and that a meal of raw meat or liver weighed 150 g wet mass [100 g when cooked; (44)], based on average mass of meat and offal eaten a day by adults from other countries (45, 46), since reliable data for Croatia do not exist.

The amount of game eaten by a person in our study scenarios ranged from 2.88 g per person per week (rare consumption) over 37.5 g per person per week (regular consumption) to 150 g per person per week (often consumption). Weekly metal exposure from game consumption was expressed as the percentage of (provisional) tolerable weekly intake [(P)TWI] and termed “added weekly exposure” as existence of other metal intake sources are presumed, apart from game consumption (4-6, 18). For the worst case-scenario we took weekly (often) consumption of meat or liver with the highest metal levels (95th percentile).

RESULTS AND DISCUSSION Game meat and offal have been recognized by the EFSA as food items with elevated content of Cd and Pb thus raising concern about exposure to these toxic metals in “high consumers” (frequent intake over long time period) (5, 6). By assessing the harmful potential of metals ingested through game consumption, a few important facts should be kept in mind in order to include all possible exposure scenarios, but at the same time not to overestimate health risks thereby discouraging consumption of this nutritionally valuable food item.

In estimating exposure to metals through game meat and offal consumption, one should be aware of (a) heavy metal levels in meat and offal; (b) meat and offal consumption preference; (c) consumption frequency; (d) vulnerable population groups (children, pregnant/lactating women); (e) other sources of metal intake (e. g., other food from the diet, air, smoking, metal-related occupation, hobbies); and (f) individual

factors influencing metal toxicity (age, sex, reproductive status, nutritional status).

Cd, Pb, and Hg in game tissues Figure 2 shows the levels of Hg in small game, and Cd, Pb, and Hg levels in tissues of big game hunted in Croatia.

Due to a high level of uncertainty in fallow deer Cd data (low number of samples, high number of quantified samples) we specified upper and lower-bound mean values for muscle: 0.0243 and 0.0193 mg kg -1 w. m., and liver: 0.127 and 0.124 mg kg -1 w. m.

Keeping in mind the limitations of such presentation (different quantification methods, merged data), toxic metal levels in the game follow a general trend the lowest levels in the muscle tissue and the highest in the kidney. The exception are muscle Pb levels, which may be overestimated due to left-censored data and varying LODs between the methods (that in some cases differed with more than an order of magnitude (0.05 vs. 0.0018 mg kg -1 w. m.). A high percentage of data below 0.05 mg kg -1 w. m. (the LOD of one method) shifted the mean to the right. The other likely reason are outliers, probably Pb ammunitioncontaminated samples, which are common in game meat (16, 17, 24, 25). Because of the tiny diameter of Pb particles, their wide radiation from the bullet path, and bioavailability (47, 48), it is almost impossible to absolutely exclude exposure to Pb by consumption of free-living game [especially minced meat, as shown

by Meltzer et al. (11)] hunted with Pb-bullets (16), even if meat around the wound is discarded. Switching to lead-free ammunition would definitely lower Pb exposure in humans and wildlife (49) and would allow quantification of exclusively environmental Pb in free-living game.

Left censoring for Cd and Hg in muscle tissue was low because, unlike with Pb, measurements below the method’s LOD were far less common (Tables 2-4).

Median values, especially for Cd and Pb in muscles, were around one order of magnitude lower than the respective means in all of the analysed animals (data not shown).

Mercury levels in the liver and kidney as organs of metal accumulation were lower in small game species than in the big ones. Furthermore, large herbivores showed lower Cd, Pb, and Hg levels than the omnivores (Figure 2). The liver and kidney of brown bear showed the highest metal accumulation.

In contrast, wild boar had the highest metal levels in the muscle, a tissue most relevant for consumption.

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Table 1 Percentage of free-living game samples collected in Croatia between 1990 and 2012 exceeding legislative maximum levels (ML)

% of samples exceeding maximum level Kidney

Muscle

Cd

Pb

Cd

Pb

Cd

Pb

(1.00)

(0.50)

(0.50)

(0.50)

(0.05)

(0.10)

Brown bear

99

82

76

41

6

4

Wild boar

78

7

24

6

19

11

Red deer

67

2

2

1

23

9

Roe deer

88

0

37

3

4

29

Fallow deer

5

N/A

11

N/A

11

N/A

ML (mg kg ) *

*

Liver

-1

Maximum level (27)

N/A - data not available

Cd, Pb, and Hg game levels in respect to legislative limits (maximum level; ML) Table 1 shows that the percentage of samples exceeding legislative Cd and Pb ML in meat and offal (27) was highest for brown bear tissues, then roe deer, wild boar and red deer. Cd levels were the most frequently above ML in renal and, in lower portion, in hepatic samples. Pb levels above ML were most frequently found in muscles of wild boars, red deer, and roe deer, unlike brown bears. In brown bears, tissue Pb ML was crossed in the highest number of renal samples, followed by hepatic and very small

number of muscle samples. Comparing the number of samples above Cd and Pb ML for muscle, we noticed a similar number that did not comply with legislation.

The EU legislation regulates only maximum levels in meat and offal of farmed animals, i.e. cow, sheep, pig, and poultry (27), even though it is an established scientific fact that free-living game animals have higher Cd and Pb levels (3). For example, in the Croatian National Residue Monitoring Program (NRMP) in 2009, Cd and Hg levels in kidney, and Pb in muscle were reported as the most frequent samples above the legislation ML (88 % of all farmed and free-living samples above ML were free-living game

Table 2 Cadmium exposure estimations for adult consumers of meat and liver of free-living game collected in Croatia between 1990 and 2012, based on mean or 95th percentile levels in tissues

Cd Muscle Fallow deer Roe deer Red deer Wild boar Brown bear Liver Fallow deer Roe deer Red deer Wild boar Brown bear

Level in game (mg kg -1 w. m.)

Added weekly exposure to Cd as % TWI by2:

Mean (P95)1

% <LOD

Often consumption

Regular consumption

Rare consumption

0.0243 (0.129) 0.0107 (0.046) 0.0584 (0.278) 0.0519 (0.200) 0.0252 (0.0521)

47 6 28 17 -

2 (11) 1 (4) 5 (24) 4 (17) 2 (4)

1 (3) 0.2 (1) 1 (6) 1 (4) 1 (1)

0.04 (0.2) 0.02 (0.1) 0.1 (0.5) 0.09 (0.3) 0.04 (0.1)

0.127 (0.714) 0.511 (1.24) 0.152 (0.449) 0.393 (1.42) 1.25 (3.46)

37 3 4 -

11 (61) 44 (106) 13 (38) 34 (122) 107 (297)

3 (15) 11 (27) 3 (10) 8 (30) 27 (74)

0.2 (1) 0.8 (2) 0.3 (1) 1 (2) 2 (6)

P95 - 95th percentile; % <LOD - percent of samples whose metal level was below the limit of detection Calculations were made for mean and P95 (in parenthesis) Cd levels in game tissue, a meal size of 150 g wet mass (raw), a 70 kg body mass person, and Cd tolerable weekly intake (TWI) of 2.5 µg kg -1 body mass (18).

1 2

Often, regular, and rare consumption refers to once a week, once a month, and four times a year, respectively

286

Lazarus M, et al. Cd, Pb, AND Hg LEVELS IN CROATIAN FREE-LIVING GAME Arh Hig Rada Toksikol 2014;65:281-292

Figure 2 Cadmium, lead, and mercury in tissues of game collected in Croatia between 1990 and 2012. Bars represent mean levels and whisker range of levels (min-max) on a log scale (base 10)

samples) (50) and in 2008, Cd, Pb, and Hg levels were above the ML in 76 %, 26 %, and 18 % of free-living game liver and kidney samples, respectively (51).

Current practice requires that foodstuffs exceeding these limits are safely disposed of, which incurs financial loss to the product owner. Clearly, current regulations need to include separate limit values for free-living game and farmed animals, as the former reflect environmental conditions better, contain higher metal level but also are consumed much less frequent.

Cd, Pb, and Hg exposure assessment Number of registered hunters and hunted large game in Croatia increased in the period 2009-2012 (12, 52). These facts, together with the enhanced availability of game meat to the average consumer via restaurants and supermarkets, lead to a possibility that game consumption is also increasing. Generally, game consumption frequency data with average amount eaten per year/week are very scarce in the literature (7, 10, 53) for both hunters and general population, with no data for Croatia. Each year the Central Bureau of Statistics of the Republic of Croatia (CBS) publishes rough estimates of annual average personal consumption of particular food items. In that report, game and rabbit meat belong to one food category,

game offal and farmed animal offal to another, which means that data on the consumption of game tissue alone are not available. According to CBS reports, 0.43 kg of game and rabbit meat per year per person (8 g per person per week) and 1.10 kg game and farmed animal offal per year per person (21 g per person per week) was consumed in Croatian households on average in the period 1999-2011 (12).

Italy is the only neighbouring country with available data about consumed game meat and liver amounts for hunters and their household members (mean: 113 g per person per week for meat, 38 g per person per week for liver) (10), but only for wild boar. Vahteristo et al. (7) reported mean consumption of moose meat among moose hunters in Finland to be 392 g per person per week and moose liver 18 g per person per week.

In its dietary exposure model for especially high exposure to Cd and Pb EFSA has assumed that a person eats 200 g of meat and 100 g of offal per week (5, 6).

It is important to differentiate exposure estimation for general population, and hunters, their household members and friends who in Croatia, like in other countries, are the vast majority of free-living game consumers (7-11). Consumption frequency in this subpopulation is independent of the availability of

287

Lazarus M, et al. Cd, Pb, AND Hg LEVELS IN CROATIAN FREE-LIVING GAME Arh Hig Rada Toksikol 2014;65:281-292

Table 3 Lead exposure estimations for adult consumers of meat and liver of free-living game collected in Croatia between 1990 and 2012, based on mean or 95th percentile levels in tissues

Pb Muscle Roe deer Red deer Wild boar Brown bear Liver Roe deer Red deer Wild boar Brown bear

Level in game (mg kg -1 w.m.)

Added weekly exposure to Pb as % PTWI by2

Mean (P95)1

% <LOD

Often consumption

Regular consumption

Rare consumption

0.176 (1.11) 0.171 (0.354) 0.188 (0.230) 0.016 (0.091)

35 43 31 32

2 (10) 1 (3) 2 (2) 0.1 (1)

0.4 (2) 0.4 (0.8) 0.4 (0.5) 0.03 (0.2)

0.03 (0.2) 0.03 (0.06) 0.03 (0.04) 0.003 (0.01)

0.087 (0.484) 0.080 (0.191) 0.174 (0.606) 0.594 (1.65)

10 20 24 -

0.7 (4) 0.7 (2) 1 (5) 5 (14)

0.2 (1) 0.2 (0.4) 0.4 (1) 1 (4)

0.01 (0.08) 0.01 (0.03) 0.03 (0.1) 0.1 (0.3)

P95 - 95th percentile; % <LOD - percent of samples whose metal level was below the limit of detection Calculations were made for mean and P95 (in parenthesis) Pb levels in game tissue, a meal size of 150 g wet mass (raw), a 70 kg body mass person, and Pb provisional tolerable weekly intake (PTWI) of 25 µg kg -1 body mass (5).

1 2

Often, regular, and rare consumption refers to once a week, once a month, and four times a year, respectively

Table 4 Mercury exposure estimations for adult consumers of meat and liver of free-living game collected in Croatia between 1990 and 2012, based on mean or 95th percentile levels in tissues Hg

Level in game (µg kg -1 w.m.)

Added weekly exposure to Hg as % TWI by2

Mean (P95)1

% <LOD

Often consumption

Regular consumption

Rare consumption

Pheasant

2.43 (6.00)

62

0.1 (0.3)

0.03 (0.08)

0.002 (0.01)

Hare

2.71 (9.00)

57

0.1 (0.5)

0.04 (0.1)

0.003 (0.01)

Roe deer

1.48 (3.53)

-

0.1 (0.2)

0.02 (0.05)

0.002 (0.004)

Red deer

3.71 (12.7)

-

0.2 (0.7)

0.05 (0.2)

0.004 (0.01)

Wild boar

8.87 (26.0)

1

0.5 (1)

0.1 (0.3)

0.009 (0.03)

Brown bear

3.92 (10.3)

11

0.2 (0.6)

0.05 (0.1)

0.004 (0.01)

Pheasant

4.52 (18.0)

40

0.2 (1)

0.06 (0.2)

0.005 (0.02)

Hare

31.7 (79.0)

-

2 (4)

0.4 (1)

0.03 (0.08)

Roe deer

8.82 (21.3)

-

0.5 (1)

0.1 (0.3)

0.01 (0.02)

Red deer

7.42 (16.0)

-

0.4 (1)

0.1 (0.2)

0.01 (0.02)

Wild boar

53.4 (142)

-

3 (8)

0.7 (2)

0.05 (0.1)

Brown bear

53.9 (143)

-

3 (8)

0.7 (2)

0.06 (0.1)

Muscle

Liver

P95 - 95th percentile; % <LOD - percent of samples whose metal level was below the limit of detection 2 Calculations were made for mean and P95 (in parenthesis) Hg levels in game tissue, a meal size of 150 g wet mass (raw), a 70 kg body mass person, and tolerable weekly intake (TWI) for inorganic Hg of 4 µg kg -1 body mass (4).

Total Hg level in game from second column was regarded as inorganic mercury for the purpose of calculation % TWI, as done

by EFSA (4).

1

Often, regular, and rare consumption refers to once a week, once a month, and four times a year, respectively

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game in food stores and its price - two reasons most often indicated in the general population as responsible for the under-representation of free-living game consumption (9). It will more likely depend on the hunting score. Johansen et al. (20) reported the highest consumption of game upon hunting season closure in ethnic Greenlanders. On the other hand, freezing game meat allowed extended consumption throughout the year (7, 53) but frequency of game consumption was shown to also depend on the consumers’ preferences to eat particular game species.

Tables 2-4 show that free-living game meat is a low source of Cd, Pb, and Hg, regardless of the consumption scenario, given the respective (P)TWI and mean metal concentrations (0.002-5 %). However, weekly consumption of big game meat (relevant for hunters) with high Cd levels (95th percentile) could significantly contribute to exposure to Cd (4-24 % TWI). Meat with high Pb and Hg levels is a low source of metal intake even if often consumed.

Game meat preferences can influence the intake of metals due to differences in metal content between the species. One Croatian study showed that roe deer meat is the first on the list of preferences, followed by red deer, wild boar, and small game meat (9). Brown bear consumption has not been investigated. To the authors’ knowledge, bear meat is less frequently consumed in the general population compared to other investigated game, but among bear hunters there is a possibility of higher consumption preference and frequency due to availability of their own hunted bear meat. In 2012 wild boar was the most hunted large game species in Croatia according to number of hunted individuals, followed by roe deer, red deer (12), and brown bear (52).

Mean weekly dietary intake of Pb and Cd from food in the Croatian general population was estimated in 1996 to be 701 and 121.4 µg per person per week [40 and 69 % of the last proposed (P)TWI], respectively (54). Weekly consumption of big game meat from our study adds 1-7 % and 0.3-4 % (if calculated with mean Cd and Pb concentrations in meat) or 6-34 % and 2-24 % (if calculated with P95 concentrations in meat) to the estimated mean weekly dietary intake of Cd and Pb, respectively, in the general population, depending on the species consumed.

Same as for domestic animals, game meat consumption largely prevails over consumption of offal (7, 10). There are no official data towards game offal consumption preferences in Croatia. Results of the Italian specific diet survey conducted on 262

hunters and their household members revealed that, all 37 % of examinees who stated wild boar offal consumption ate only liver, none consumed kidney (10). On the other hand, among Finish moose hunters and moose meat eaters (N=711), 69 % consumed liver and 23 % kidneys (7). Our assumption was thereby that free-living game consumers in Croatia avoid eating kidneys or consume it in a negligible number of occasions. Although there is a general recommendation for consumers to avoid eating liver and kidneys of free-living game animals in Croatia because of their high Cd content (40, 55), it is assumed that offal is still being consumed in some households, preferentially that of young animals (40). Our findings (Tables 2-4) show that game liver is a low source of Pb and Hg, regardless of the consumption scenario.

Regarding the consumed species, consumers of bear liver had the highest intake of Cd, Pb, and Hg, although wild boar liver also had similar Hg content. If consumed on a regular basis (once a month), game liver can be a low to significant (3-74 % TWI) source of Cd, depending on the concentration. Depending on species and Cd concentration range, frequent consumption (weekly) can result in significant to even very high exposure to Cd (11-297 % TWI) in the worst case scenario. Even a single meal of bear liver with average Cd levels, or roe deer/wild boar/brown bear liver with high Cd levels can exceed the EFSA weekly intake considered safe for health. Often consumption of big game liver from this study adds 16-155 % and 2-13 % (if calculated with mean Cd and Pb concentrations in meat) or 55-428 % and 4-35 % (if calculated with P95 concentrations in meat) to the estimated mean weekly dietary intake of Cd and Pb, respectively, in the general population, depending on the species consumed.

Several authors have estimated exposure to metals (mostly Pb and Cd) from game consumption (5-7, 15-17, 25) using different methods, scenarios, and variables (e.g. meat portion) which makes any comparison unreliable. Nevertheless, metal content in game tissues have the strongest impact on exposure estimation so it is pretty safe to say that exposure to Cd and Pb from Croatian big game is similar or lower than the expected exposure in Finland (7), Italy (10), Poland (14), Spain (15, 16), or Norway (17).

Implications of our exposure assessment for vulnerable population groups Foetuses and children, breastfed infants in particular, are considered vulnerable population group

Lazarus M, et al. Cd, Pb, AND Hg LEVELS IN CROATIAN FREE-LIVING GAME Arh Hig Rada Toksikol 2014;65:281-292

because of the transfer through the placenta (foetuses) or milk (breastfed infants) (4-6) or because of the hand-to-mouth behaviour, greater intestinal absorption, and not fully developed blood-brain barrier (infants and children), which all increase metal bioavailability to young organisms in respect to adults. Greater bioavailability increases the risk of adverse health effects because of the higher sensitivity of developing organisms.

Another vulnerable group are child-bearing and lactating women, who also absorb more toxic metals from food. Health risks are associated with higher bone turnover and therefore higher Pb blood content (Pb released from bone).

Because of the new evidence that there are no safe threshold levels below which Pb does not induce developmental neurotoxicity in children, and cardiovascular effects and nephrotoxicity in adults, EFSA has withdrawn the current PTWI for Pb, except for the calculations of the margin of exposure (5). With this in mind, children and pregnant/lactating women should be advised to avoid free-living game altogether, as its meat may be contaminated by lead ammunition (13) and its offal is likely to have high Cd and Hg content.

CONCLUSIONS Metal content monitoring of free-living big game in Croatia could expand to include wild boar and deer species from the mountainous parts of Croatia and small game from the whole country. Muscle contamination with Pb in the most frequently consumed species (wild boar, roe deer, red deer) might be avoided by using non-lead ammunition. Because of the high percentage of free-living game offal samples exceeding the limits for Cd and Pb, adults should keep its consumption as low as possible, while children and pregnant and lactating women should avoid it.

Our study estimates suggests that rare consumption of free-living game meat and liver (which is a likely scenario for the general population) does not pose a health risk to consumers. However, free-living game liver could become an important additional source of Cd if consumed on a monthly basis, and weekly consumption may give rise to toxicological concern.

Future estimates should focus on food (free-living game and other items of toxicological concern) preference and frequency surveys among the Croatian

289

population to enable more reliable exposure and risk assessments.

Acknowledgements This study was supported by the Ministry of Science, Education and Sports of the Republic of Croatia (grant no. 022-0222148-2135) and by the European Commission under the “HUNT” project of the 7th Framework Programme for Research and Technological Development. The help of local hunters and experts in the collection of samples is gratefully acknowledged. The authors wish to thank Mr Dado Čakalo for language advice.

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Bišćan A, Budor I, Domazetović Z, Fontana Pudić K, Francetić I, Gospočić S, Grubešić M, Huber Đ, Modrić M, Sindičić M, Šprem N, Štrbenac A, Tomljanović M, Jakšić Z, Reljić S. Action plan for brown bear management in the Republic of Croatia in 2013. Zagreb, Croatia: Ministry of Agriculture, Directorate for Forestry, Hunting and Wood Industry, Ministry of Environmental and Nature Protection, Directorate for Nature Protection; 2013.

Burger J, Gochfeld M. Role of wild game in the diet of recreationists in South Carolina. J Environ Plann Manage 2002;45:103-28. doi: 10.1080/09640560120100213 Sapunar-Postružnik J, Bazulic D, Kubala H, Balint L. Estimation of dietary intake of lead and cadmium in the general population of the Republic of Croatia. Sci Total Environ 1996;177:31-5. PMID: 8584917 National Residue Monitoring Program (NRMP). Uputa za uzimanje uzoraka za potrebe državnog programa monitoringa rezidua (DPMR-a) i postupanje po nesukladnom nalazu [Instructions for sampling for the purpose of National Residue Monitoring Program and measures taken upon noncompliant result, in Croatian] 2012 [displayed 8 January 2014]. Available at http://www.veterinarstvo.hr/ UserDocsImages/HranaZivPod/programNadzora/27%20 11%2012%20%20izmjene%20-%20UPUTA%20ZA%20 UZIMANJE%20UZORAKA%20ZA%20POTREBE%20 %20DPMR-web.pdf

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Sažetak Procjena izloženosti kadmiju, olovu i živi pri konzumaciji slobodne divljači u Hrvatskoj Procjena izloženosti kadmiju, olovu i živi pri konzumaciji slobodne divljači u Hrvatskoj Slobodna divljač značajan je izvor kadmija i olova u prehrani ljudi te se nameće pitanje je li izloženost ovim metalima tolika da može štetno utjecati na zdravlje potrošača. Procijenili smo izloženost kadmiju, olovu i živi pri konzumaciji velike slobodne divljači (jelen lopatar, srna, obični jelen, divlja svinja i smeđi medvjed) te živi pri konzumaciji male divljači (fazan, zec) koja je ulovljena u Hrvatskoj između 1990. i 2012. godine. Procjena izloženosti temelji se na dostupnim literaturnim podacima i našim rezultatima mjerenja metala u tkivima divljači te različitoj učestalosti konzumacije (četiri puta godišnje, jedanput mjesečno, jedanput tjedno).

Izloženost je prikazana kao postotak vrijednosti (privremeno) prihvatljivog tjednog unosa [(P)TWI] koju je postavila Europska agencija za sigurnost hrane (EFSA). Izloženost toksičnim metalima pri rijetkoj konzumaciji (pretpostavljena za opću populaciju) mesa (0,002-0,5 % PTWI) i jetre divljači (0,005-6 % PTWI) ne predstavlja zdravstveni rizik za potrošače, kao ni redovita (0,02-6 % PTWI) i česta (0,1-24 % PTWI) konzumacija mesa divljači. Preporuka je što više smanjiti konzumaciju iznutrica nekih vrsta divljači zbog visokog postotka uzoraka jetre, a posebno bubrega, koji prelaze zakonom propisane maksimalne razine kadmija (2-99 %) i olova (1-82 %). Djeca, trudnice i dojilje trebale bi izbjegavati konzumaciju iznutrica divljači. Jetra divljači može biti značajan dodatni izvor kadmija ako se redovito konzumira (374 % PTWI), a čestom konzumacijom jetre (11-297 % PTWI) može se povećati rizik od štetnih učinaka na zdravlje.

KLJUČNE RIJEČI: divlja svinja; fazan; jelen; jetra; meso; prihvatljivi tjedni unos; smeđi medvjed; toksični metali; zec

CORRESPONDING AUTHOR: Maja Lazarus Institute for Medical Research and Occupational Health P. O. Box 291, HR-10001 Zagreb, Croatia E-mail: mlazarus@imi.hr

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Warita K, et al. BPA EFFECTS ON NGF IN MOUSE CELL LINE Arh Hig Rada Toksikol 2014;65:293-299

DOI: 10.2478/10004-1254-65-2014-2494

Original article

A unique pattern of bisphenol A effects on nerve growth factor gene expression in embryonic mouse hypothalamic cell line N-44 Katsuhiko Warita1,3, Tomoko Mitsuhashi3, Nobuhiko Hoshi2, Ken-ichi Ohta1, Shingo Suzuki1, Yoshiki Takeuchi1, and Takanori Miki1 Department of Anatomy and Neurobiology, Faculty of Medicine, Kagawa University, Kagawa1, Department of Bioresource Science, Graduate School of Agricultural Science, Kobe University, Kobe2, Japan, Department of Pathology, University of Pittsburgh, School of Medicine, Pittsburgh, USA3 Received in January 2014 CrossChecked in January 2014 Accepted in July 2014

We investigated the toxicity of bisphenol A (BPA) by determining the gene expression of nerve growth factor (Ngf) in the embryonic mouse cell line mHypoE-N44 derived from the hypothalamus exposed to BPA dose range between 0.02 and 200 µmol L-1 for 3 h. Ngf mRNA levels decreased in a dose-dependent manner, with significant reductions observed in the 2 to 50 µmol L-1 BPA treatment groups compared to controls. However, at 100 to 200 µmol L-1 the Ngf mRNA gradually increased and was significantly higher than control, while the expression of the apoptosis-related genes Caspase 3 and transformation-related protein 73 decreased significantly. These results suggest that in an embryonic hypothalamic cell line the higher doses of BPA induce a unique pattern of Ngf gene expression and that BPA has the potential to suppress apoptosis essential for early-stage brain development.

KEY WORDS: Caspase 3; developmental toxicity; foetal hypothalamus; nerve growth factor; transformation-related protein 73

Bisphenol A (BPA) is one of the most abundantly produced chemicals worldwide that can disrupt endocrine function by mimicking the action of oestrogen. It has been detected in maternal serum, umbilical cord, foetal serum, and full-term amniotic fluid passing through the placenta (1, 2) and can also penetrate the blood-brain barrier (3). Because foetuses are extremely sensitive to chemicals with hormonelike activity, and even small changes induced by oestrogen-mimicking chemicals can lead to changes in brain function and behaviour (4), there is a growing concern that BPA exposure can disrupt foetal brain development/function or neuronal differentiation.

Recent studies have demonstrated that BPA exposure can affect neurogenesis during gestation (5, 6) or in young adult mice (7).

Neurotrophins are crucial to the survival, development/differentiation, and function of neurons.

The neurotrophin family includes nerve growth factor (NGF), brain-derived neurotrophic factor (BDNF), neurotrophin-3 (NT-3), and NT-4/5 (8). NGF and BDNF initiate signalling by binding to specific highaffinity receptors, namely neurotrophic tyrosine kinase receptor type 1 (NTRK1) and type 2 (NTRK2), respectively (9). We previously showed that BPA decreased the Bdnf gene expression in embryonic hypothalamic cells and affected the BDNF-NTRK2 neurotrophin system (10). Seki et al. (11) have found that BPA causes morphological changes in NGFinduced differentiation and inhibits neurite extension in a PC12 cell line. It has also been reported to induce changes in both dendritic and synaptic development

294 in foetal hypothalamic cells (12). Because NGF regulates dendritic morphology and synaptic connectivity during development (13), these findings suggest that BPA would affect NGF-related development in embryonic hypothalamic cells and that the NGF-NTRK1 neurotrophin system could be a target of BPA. However, little is known about the relationship between BPA and NGF in developing hypothalamic cells.

Another mechanism potentially affected by BPA and regulated by neurotrophins is apoptosis (programmed cell death). In neural development, apoptosis plays an essential role in optimising synaptic connections, removing unnecessary neurons, and forming neuronal patterns (14). In embryonic neurons such apoptosis is regulated by neurotrophins (15, 16).

Therefore, we also wanted to see how the effects of BPA on the NGF-NTRK1 neurotrophin system affect apoptosis in developing hypothalamic cells.

MATERIALS AND METHODS We focused our study on the previously unknown effects of BPA on the gene expression of Ngf, Ntrk1, Caspase 3 (Casp3), and the transformation-related protein 73 (Trp73), which is also involved in apoptosis (17), in developing hypothalamic cells. We used the embryonic mouse hypothalamic cell line N-44 (mHypoE-N44) as the foetal hypothalamic cell model and assessed the effects of BPA on gene expression using real-time reverse transcription polymerase chain reaction (real-time RT-PCR).

Cell culture The mHypoE-N44 cell line was purchased from CELLutions Biosystems, Inc. (Toronto, ON, Canada).

This cell line is immortalised from mouse embryonic hypothalamic primary cultures (days 15, 17, and 18) by retroviral transfer of SV40 T-Ag. We used this cell line as a suitable model for foetal hypothalamus. The cells were plated at a density of 2x104 cells in 35-mm tissue culture dishes pre-coated with collagen type I (Corning, Inc., Corning, NY, USA) and were cultured in minimum essential medium alpha (MEMα; Invitrogen-Gibco, Carlsbad, CA, USA) supplemented with 10 % foetal bovine serum (FBS; Biowest, Nuaille, France). The cells were incubated at a permissive temperature (37 °C) in a humid atmosphere with 5 % CO2.

Warita K, et al. BPA EFFECTS ON NGF IN MOUSE CELL LINE Arh Hig Rada Toksikol 2014;65:293-299

Incubation of the mHypoE-N44 cells with BPA BPA (Junsei Chemical Co., Tokyo, Japan) in the concentration range of 0.02 to 200 µmol L-1 was dissolved in 0.1 % (final concentration) dimethyl sulphoxide (DMSO; Wako, Osaka, Japan). The choice of the upper range limit was based on an in vitro study

by Kim et al. (18) showing no notable cytotoxicity of BPA in concentrations ≤200 µmol L-1. We therefore assumed that treatment with ≤200 µmol L-1 BPA for 3 h would have no effect on cell viability. In addition, the 0.1 % DMSO vehicle was not toxic to the mHypoE-N44 cells and had no effect on cell viability or cell division. The cells were first cultured in phenolred-free MEMα supplemented with 0.5 % charcoalstripped FBS at 37 °C for 24 h. Then the medium was supplemented with BPA, and incubation continued for another 3 h. The cells treated with 0.1 % DMSO served as controls. All experiments were performed in triplicate.

Separation of total RNA and real-time RT-PCR Total cellular RNA was extracted from the mHypoE-N44 cells using an RNeasy kit (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. DNase-treated RNA (1 μg) was reverse transcribed to cDNA using the Super Script III FirstStrand Synthesis System (Invitrogen Corp., Carlsbad, CA, USA). Gene expression was examined using quantitative RT-PCR. The cDNA was amplified through PCR with primer sets specific to mouse Ngf, Ntrk1, Casp3, Trp73, and oestrogen-related receptor γ (Errγ), which is a putative BPA receptor. Real-time PCR was performed using a LightCycler rapid thermal cycler system (Roche Diagnostics Ltd., Lewes, UK) with LightCycler FastStart DNA MasterPLUS SYBR Green I mix (Roche Diagnostics Ltd.). Primer sequences for Ngf, Ntrk1, Trp73, and glyceraldehyde3’-phosphate dehydrogenase (Gapdh) have been described previously (10, 19). Casp3 primer sequences were 5’-CTG CCG GAG TCT GAC TGG AA-3’ and 5’-ATC AGT CCC ACT GTC TGT CTC AAT G-3’.

Errγ primer sequences were 5’-TCA AAG CCC TCA CCA CAC TCT-3’ and 5’-GCC AGG GAC AGT GTG GAG AA-3’. Amplification of Gapdh mRNA was used as an internal positive control. The level of Gapdh mRNA was stable and similar between each sample, and the amounts of each mRNA were normalised to the Gapdh mRNA level in each sample.

Warita K, et al. BPA EFFECTS ON NGF IN MOUSE CELL LINE Arh Hig Rada Toksikol 2014;65:293-299

Statistical analysis Statistical analyses were performed using one-way analysis of variance (ANOVA) and Bonferroni–Dunn post-hoc tests with the StatView software (version 5.0; SAS Institute Inc., Cary, NC, USA). The data for each BPA-treated group were compared with those for the controls. P values of less than 0.05 were considered statistically significant.

RESULTS AND DISCUSSION Figure 1 shows the effects of the 3 h of exposure to BPA in the range between 0.02 and 200 µmol L-1 on the expression of Ngf in mHypoE-N44 cells. The Ngf mRNA level gradually decreased in a dosedependent manner. A significant drop (P<0.01) was observed in the cells treated with 2, 20, and 50 µmol L-1 BPA compared to control. An in vitro study by Yokosuka et al. (12) has shown that BPA induces changes in both dendritic and synaptic development in foetal rat hypothalamic cells via alteration of microtubule-associated protein 2 (MAP2) and synapsin I expression, which serve as protein markers of neuronal growth and synaptogenesis, respectively (20). In addition to MAP2 and synapsin I, we believe

295 that hypothalamic cell dendritic and synaptic development is also affected by changes in Ngf expression, given the important role of NGF in both dendritic morphology and synaptic connectivity (13).

Further studies such as Western blotting should be conducted to evaluate the changes at the protein level.

Unexpectedly however, the Ngf mRNA level significantly increased with exposure to ≥100 µmol L-1 BPA (P<0.01) compared to control. Lee et al. (21) reported that the effect of BPA on neuronal cells derived from the E18 rat cortex differed between low (below 50 µmol L-1) and high (higher than 100 µmol L-1) doses of BPA. In addition, the authors suggested that a concentration of 50 µmol L-1 BPA might be a cut-off dose for the induction of adverse effects in neuronal cells. In our study, the dramatic change in Ngf mRNA expression was observed between 50 and 100 µmol L-1.

At the moment, we can not pinpoint the exact mechanism of or the reason for this switching effect on Ngf mRNA expression, but our results suggest that embryonic hypothalamic cells may have a similar flexion point (also around 50 µmol L-1 BPA) to that reported for cortical cells by Lee et al. (21).

Despite the surprising reversal in Ngf mRNA expression observed at 200 µmol L-1 BPA (P<0.01 compared to control), the gene expression of the highaffinity NGF receptor Ntrk1 did not change (Figure

Figure 1 Quantitative reverse transcription-polymerase chain reaction (RT-PCR) analysis of Ngf mRNA levels in mHypoE-N44 cells treated with BPA for 3 h.

The data have been normalised to the Gapdh mRNA level in each sample and are expressed as a value relative to this internal control. Each column represents the mean ± SD (standard deviation) (n=3 for each group). *P<0.01 (significantly different from control)

296 2). We have previously reported that treatment with 200 µmol L-1 BPA decreases Bdnf gene expression without affecting the BDNF receptor gene Ntrk2 (10).

Both our studies suggest that the adverse effects of higher BPA doses on the NGF/NTRK1 and BDNF/ NTRK2 systems occur through the alteration of gene expression of the ligands, not of their receptors.

Figure 2 Quantitative RT-PCR analysis of Ngf and Ntrk1 mRNA levels in mHypoE-N44 cells treated with 200 µmol L-1 of BPA for 3 h.

The data have been normalised to the Gapdh mRNA level in each sample and are expressed as a value relative to this internal control. Each column represents the mean ± SD (n=3 for each group). *P<0.01 (significantly different from control)

On the other hand, Casp3 and Trp73 mRNA expression did not drop significantly in the cells treated with lower doses of BPA (data not shown), but only in those treated with 200 µmol L-1 BPA (P<0.01 and P<0.05, respectively, compared to the controls) (Figure 3). In the early developmental stage, apoptosis is an essential physiological process for the formation of a normal central nervous system (CNS), and Casp3 plays an important role in apoptosis during brain development (14). TRP73 is also reported to induce apoptosis (22, 23). Therefore, our results suggest that BPA has the potential to suppress normal apoptosis in embryonic hypothalamic cells and are in line with the findings of Negishi et al. (24), who reported that BPA significantly inhibited Casp3 activity in foetal rat neurons treated with staurosporine, an inducer of apoptosis. Given that our highest dose of BPA decreased the expression of Casp3 and Trp73 and increased the expression of Ngf, which supports the survival and maintenance of neurons in the brain during embryonic development (25), we assume that

Warita K, et al. BPA EFFECTS ON NGF IN MOUSE CELL LINE Arh Hig Rada Toksikol 2014;65:293-299

high levels of BPA adversely affect normal development of the foetal hypothalamus by allowing the survival of cells that are destined for apoptotic thinning necessary for normal formation of the CNS. Furthermore, because the effect of BPA on the Ngf gene expression significantly differed with doses, adverse effects resulting from the change in Ngf levels may also be dose-dependent. It is possible that the effects shift from altering dendritic and synaptic development to affecting naturally occurring essential cell death.

Figure 3 Quantitative RT-PCR analysis of Casp3 and Trp73 mRNA levels in mHypoE-N44 cells treated with 200 µmol L-1 of BPA for 3 h.

The data have been normalised to the Gapdh mRNA level in each sample and are expressed as a value relative to this internal control. Each column represents the mean ± SD (n=3 for each group). *P<0.05, **P<0.01 (significantly different from control)

Matsushima et al. (26) have reported that BPA binds strongly to ERRγ, a receptor highly expressed in the placenta (27), which suggests that BPA has a high potential for accumulating in the placental tissue.

In our study, Errγ mRNA expression gradually started to decrease from 100 µmol L-1 BPA only to reach significant reduction at 200 µmol L-1 (Figure 4).

Although it is unclear how much a dose of BPA can affect the embryonic hypothalamus through the placenta, higher doses may downregulate Errγ gene expression in foetal hypothalamic cells.

In summary, our findings suggest that in an embryonic hypothalamic cell line BPA has the potential to suppress apoptosis by lowering Casp3 and Trp73 mRNA levels and that higher doses of BPA may modulate NGF-mediated neuronal development by altering Ngf gene expression, but the effect is strongly

Warita K, et al. BPA EFFECTS ON NGF IN MOUSE CELL LINE Arh Hig Rada Toksikol 2014;65:293-299

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Figure 4 Quantitative reverse transcription-polymerase chain reaction (RT-PCR) analysis of Errγ mRNA levels in mHypoE-N44 cells treated with BPA for 3 h.

The data have been normalised to the Gapdh mRNA level in each sample and are expressed as a value relative to this internal control. Each column represents the mean ± SD (n=3 for each group). *P<0.05 (significantly different from the control)

dose-dependent. Further investigation is needed to determine the significance of these results at the level of organism.

Acknowledgements This work was supported in part by the Grant-inAid for Young Scientists (B) (#21791037) from the Ministry of Education, Culture, Sports, Science, and Technology of Japan.

Conflicts of interest The authors declare no conflict of interest.

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299

Sažetak Jedinstveni obrazac djelovanja bisfenola A na ekspresiju gena čimbenika rasta živca embrionske mišje stanične linije N-44 dobivene iz hipotalamusa U istraživanju toksičnosti bisfenola A (BPA) utvrđena je ekspresija gena čimbenika rasta živca (eng. nerve growth factor - NGF) embrionske mišje stanične linije mHypoE-N44 dobivene iz hipotalamusa nakon trosatnog izlaganja BPA-u u rasponu doza od 0,02 do 200 µmol L-1. Razine Ngf mRNA snizile su se ovisno o dozi, a značajne razlike od kontrolne skupine zamijećene su za raspon od 2 do 50 µmol L-1. Međutim, počevši od doze od 100 do 200 µmol L-1, razine Ngf mRNA značajno su se povećale u odnosu na kontrolu, a ekspresija gena kaspaze 3 i transformacijskog proteina 73 značajno snizila. Ti rezultati upućuju na to da visoke doze BPA u embrionskoj hipotalamičkoj staničnoj liniji stvaraju jedinstveni obrazac ekspresije gena Ngf te da BPA može suprimirati apoptozu koja je nužna za rani razvoj mozga.

KLJUČNE RIJEČI: čimbenik rasta živca; fetalni hipotalamus; kaspaza 3; razvojna toksičnost; transformacijski protein 73

CORRESPONDING AUTHOR: Katsuhiko Warita Department of Anatomy and Neurobiology Faculty of Medicine, Kagawa University 1750-1 Ikenobe, Miki-cho, Kita-gun, Kagawa 761-0793, Japan E-mail: warita@med.kagawa-u.ac.jp

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DOI: 10.2478/10004-1254-65-2014-2522

Original article

Acute toxic effects of cadmium in larvae of the green toad, Pseudepidalea variabilis (Pallas, 1769) (Amphibia: Anura) Mert Gürkan, Ayşe Çetin, and Sibel Hayretdağ Department of Biology, Zoology Section, Faculty of Arts and Sciences, Çanakkale Onsekiz Mart University, Turkey Received in April 2014 CrossChecked in April 2014 Accepted in August 2014

The environmental impact of cadmium use and its accumulation in nature have increased to alarming levels. This study aimed to morphologically and histologically investigate the acute toxic effects of cadmium on green toad, Pseudepidalea variabilis (Pallas, 1769) larvae. Embryos were obtained from specimens collected in amplexus from nature and kept under laboratory conditions until stage 26, when they were exposed to cadmium (0, 1, 5, 10, 25, and 50 µg L-1) for 96 h. The LC10, LC50, and LC90 values of cadmium were calculated to be 26.98, 35.35, and 46.31 µg L-1, respectively. Our results showed that cadmium had a negative effect on the body size of P. variabilis larvae (over 1 µg L-1). Histological examination detected a fusion of gill lamellae, liver haemorrhage, oedema in the abdominal cavity, and deformations of pronephric tubules (over 10 µg L-1). Our findings suggest that the green toad was sensitive to the cadmium treatment, with LC50 values lower than those reported by other studies. Thus, this species could be considered a reliable indicator species of environmental stress in aquatic ecosystem.

KEY WORDS: embryotoxicity; heavy metal; histopathology; lethal concentrations

The decline in amphibian populations has reached striking dimensions in recent years (1, 2). There are several hypotheses about the possible reasons behind this phenomenon (3, 4). Some of these hypotheses include impact of urbanization due to rapid increase in settlements and industrialization, chemical pollution, habitat degradation/destruction, and diseases (5-8). Among these, the destruction of habitats and increased pollution significantly threaten the survival of amphibians, which spend their embryonic and larval stages exclusively in water and play a significant role in biomonitoring programmes (9-11). That is why amphibian larvae are among the preferred bioindicators for aquatic toxicology studies (12-16).

Cadmium is present in the environment naturally; however, it is not an essential element for organisms (17). Increases in the amount of cadmium in nature might be either due to natural factors, like the ablation

of rocks resulting from erosion and rain, or anthropogenic factors (18). In Turkey, for instance, one study (19) found the mean cadmium concentration in surface waters to be 110 µg L-1.

The half-life of cadmium in organisms is 20 years (20). It cannot be excreted from the body and accumulates in the organism and throughout the food chain. Its biomagnification poses threats for human health as well as the ecosystem as a whole. Therefore, cadmium has recently become the subject of many investigations (16, 21-25). The toxic effects of cadmium investigated in freshwater fish include development abnormalities detected in many teleost species (26-28). Cadmium led to larval teratogenic and developmental abnormalities (29), to micronucleus induction at environmental levels of 2, 10, and 30 µg L-1, and to increased concentration-dependent quantities of micronucleus after contamination with 10 and 30 µg L-1 in Xenopus larvae (30). In addition,

302 cadmium exposure caused a decline in the survival numbers of Bufo americanus (13), developmental delays in tadpoles of Bufo raddei (31), and toxic acute effects on early-life stages in Duttaphrynus melanostictus at levels of 0.2 mg L-1 (23). On the contrary, cadmium stimulated growth and development in amphibian larvae at concentrations from 0.25 to 5 µg L-1 (32).

Known as the green toad, Pseudepidalea variabilis is a common amphibian species in Turkey. This terrestrial and nocturnal species is water-dependent in the breeding season, when it is known to stay in water for long periods of time (33). This species generally inhabits slow-flowing and stagnant waters, seasonal ponds, and shallow pits filled with water for egg-laying (34). Its aquatic habitats are prone to increased heavy metal concentrations due to agricultural and industrial activities. To our knowledge, until now no related study on the acute toxic effects of cadmium on P. variabilis larvae has been conducted.

This study aimed to determine the lethal concentrations (LC10, LC50, and LC90) of cadmium and the acute toxic effects on the tissues and organs of P. variabilis larvae after a 96-h acute exposure.

MATERIALS AND METHODS Animals and treatment The green toad, Pseudepidalea variabilis (Pallas, 1769), is included in the “data deficient” (DD) category of the IUCN Red List (35). Tadpoles were obtained in the laboratory from 4 adult (2 ♂♂, 2 ♀♀) P. variabilis caught in amplexus in March 2010, in a seasonal pond in Çanakkale, north-western Turkey. P. variabilis specimens were transferred to the laboratory and kept in polypropylene containers until ovulation.

After ovulation, embryos were transferred to 30×30×25 cm glass aquaria. After hatching, the larvae were fed with fish feed of plant origin (100 g/ carbohydrate: 30.16 g; sugars: 7.33 g; dietary fibre: 9.3 g; fat: 19.94 g; protein: 36.49 g; energy: 450 kcal) and boiled lettuce leaves until stage 26 (36).

Cadmium chloride (CdCl2) was supplied from Sigma-Aldrich Chemical Company Inc. (St. Louis, MO, USA). A stock solution of 100 µg L -1 was prepared by dissolving CdCl2 powder in distilled water.

Larvae at stage 26 were exposed to concentrations of 1, 5, 10, 25, and 50 µg L-1 of cadmium. The dosing

Gürkan M, et al. Cd TOXICITY IN GREEN TOAD LARVAE Arh Hig Rada Toksikol 2014;65:301-309

solutions were prepared by appropriate dilutions of the stock solution.

Twenty randomly selected P. variabilis larvae were exposed to control (water) and each cadmium concentration, in acute (96 h) exposure experiments, in a static bioassay test system. Aquaria were filled with 2 L of water or cadmium solutions and during exposure, temperature, pH, and dissolved oxygen levels were measured daily with an Elmetron CO-401 meter (analysio GmbH, Greifswald, Germany). The treatment was carried out in a 14:10-h light-dark cycle and the number of dead tadpoles was recorded and faeces removed every 24 hours.

Morphology and histology Ten randomly selected larvae from the control and each treatment group were measured for total length, width, and tail length. Furthermore, wet weights of the larvae were determined (0 and 96 h). Wet weight (precision 0.001 g) and total length (precision 0.01 mm) were measured after euthanasia with a digital scale and digital calipers. Ten larvae survived after the 96 h of exposure were fixed in Bouin’s solution for histological examination after macroscopic evaluation. Afterwards, these larvae were processed through alcohol, xylene, and paraffin series and then paraffin blocks were prepared. Serial cross sections 6-8 μm in thickness were obtained from these blocks, stained with hematoxylin and eosin (H&E), and histopathologically examined under a light microscope.

Finally, the histological imaging of the preparations was carried out using a camera mounted on an Olympus BX51 light microscope (Japan) and analysed using the DP2-BSW software.

Statistical analysis Finney’s Probit analysis method was used to calculate 96-h LC10, LC50, and LC90 values of cadmium for P. variabilis larvae. Lethal concentrations were calculated at 95 % confidence intervals. Comparisons of total length, tail length, width and weight between control and treatment groups were done using one-way analysis of variance (ANOVA). Discriminant analysis was done in order to show the possible total differences of the concentrations tested. Statistical analyses were performed using SPSS software (ver. 16.0) and alpha was set at 0.05.

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RESULTS Acute toxicity Mean water temperature was 21.2±2 °C, while pH and dissolved oxygen in aquaria were 6.8±0.3 and 8.2±0.4 mg L -1, respectively. No mortality was recorded in the control group and in the cadmium groups exposed to 1 and 5 µg L-1. The highest mortality was observed at 50 µg L-1, where 10 larvae died within the first 24 h and only one larva survived at the end of the exposure period. After 72 h, a dead larva was found in the 10 µg L-1 group, whereas 8 larvae died in the 25 µg L-1 group. Values of 96-h LC10, LC50, and LC90 are presented in Table 1.

Morphology and histology Total length was the only parameter found to be significantly different between treatments (p<0.05).

Comparisons of total length, width, tail length, and wet weight between control and treatment groups are presented in Table 2. Since only one larva survived the 50 µg L-1 concentration to the end, this group was not included in the statistical analysis.

The canonic discriminant analysis was performed to assess differences in total body length among groups. It showed two functions, which explained 100 % of the total variance (Figure 1) and the p-value of function 1 was significant (Table 3).

No abnormalities were found in the histological examinations of larvae from the control group.

Likewise, no significant histological findings were detected in the groups exposed to 1 and 5 µg L-1 of cadmium. However, deformations and gill lamellar fusions were recorded in some larvae at 10 and 25 µg L-1 (Figure 2).

Furthermore, effects such as deformations of pronephric tubules structure were prominent and clearly observed at increasing concentrations (Figure 3).

No histopathological alterations were encountered in the cross sections of the livers of larvae in the

Figure 1 According to total length measurements, the total differences of exposure concentrations between groups

control group. Nevertheless, deformation and haemorrhage in liver were observed in most of the larvae exposed to 10 and 25 µg L-1 of cadmium. In addition, vacuolization and increments in the distance of the intercellular area were observed in the hepatocytes of the same sections (Figure 4).

A severe visceral oedema was detected in larvae at 25 µg L-1 in the cross-sections of the internal organs (Figure 5). As only one larva survived at 50 µg L-1, the histopathological findings are not presented here.

The incidence of observed histopathological findings of the ten larvae is presented in Table 4.

DISCUSSION There is a strong relationship between increasing concentrations of cadmium and the decline in the hatching success of frog embryos (37). Cadmium LC50 values determined in previous acute toxicity studies on amphibian larvae vary considerably. The 96-h LC50 of cadmium for Bufo arenarum larvae was reported in the range from 2.19 to 6.77 mg L-1 (38). The LC50 values for cadmium in R. ridibunda larvae calculated in two different studies were 0.45 mg L-1 (39) and 71.8 mg L-1 (40). This last value is very close to the 90-h LC50 reported in Xenopus laevis larvae - 80 to

Table 1 Lethal concentrations after cadmium exposure in P. viridis for 96 hours

Lethal concentrations LC10 LC50 LC90

Concentration (µg L-1) 26.98 35.35 46.31

95 % Confidence interval Lower bound Upper bound 21.05 31.24 30.41 41.09 40.05 59.36

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Table 2 Comparison of morphological measurements of treatment groups

Measurements

Total length (mm)

Width (mm)

Tail length (mm)

Wet weight (g)

Cd (µg L-1)

n

mean

SD

SE

0 1 5 10 25 0 1 5 10 25 0 1 5 10 25 0 1 5 10 25

10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10

15.76 15.08 14.88 14.78 13.45 3.08 3.20 3.03 3.29 2.97 9.62 9.19 9.39 9.43 8.78 0.03 0.03 0.03 0.03 0.02

0.89 1.18 0.75 1.30 1.38 0.31 0.85 0.37 0.25 0.36 0.78 0.78 0.87 0.87 1.19 0.01 0.01 0.01 0.01 0.01

0.28 0.37 0.26 0.45 0.48 0.09 0.27 0.13 0.09 0.12 0.24 0.24 0.35 0.30 0.42 0.01 0.01 0.01 0.01 0.01

100 mg L-1 (41), but both were substantially above the LC50 calculated for X. laevis embryos - 850 μg L-1.

The cadmium 96-h LC50 for stage 26 P. variabilis larvae in our study was 35.35 μg L-1. The dissimilar lethal concentration values calculated in all of these studies might have been due to differences in environmental conditions in habitats, such as temperature and pH, or perhaps due to general differences in species. The developmental stage at the moment of exposure also influences lethal concentration estimations. In a study on juvenile R. ridibunda, the LC50 calculated after a 96-h exposure to cadmium was 51.2 mg L-1 (42), a value greater than or similar to the LC50 found for the larvae of this species. It is therefore important to analyse the water at several stages; not only once. According to Turkish regulations, the highest acceptable value is 100 μg L-1 (43), while this value was set at 200 μg L-1 in the 2008 TSE limits (the Turkish Standards Institution) (43).

This study detected serious declines in survival percentages of the larvae resulting from cadmium exposure at between 25 and 50 μg L-1. We could say that cadmium levels within 25-50 μg L-1 were critical for P. variabilis larvae. This is most strongly confirmed by the survival of one larva in the group exposed to 50 μg L-1 of cadmium. James and Little (13) reported that 540 μg L-1 of chronically applied cadmium

95 % Confidence interval for mean Lower bound 15.12 14.23 14.25 13.69 12.29 2.85 2.59 2.72 3.07 2.66 9.07 8.64 7.75 8.70 7.79 0.02 0.02 0.02 0.02 0.01

Upper bound 16.40 15.92 15.51 15.86 14.61 3.30 3.82 3.35 3.50 3.27 10.18 9.75 9.53 10.15 9.78 0.03 0.03 0.03 0.03 0.03

Min.

Max.

13.95 12.72 13.95 13.18 10.70 2.51 0.92 2.14 3.04 2.15 7.90 7.72 7.54 7.90 6.25 0.03 0.03 0.03 0.02 0.01

16.77 16.99 15.88 16.47 14.91 3.61 4.04 3.27 3.77 3.37 10.38 10.11 10.78 10.70 10.20 0.04 0.04 0.04 0.04 0.04

p

0.00

0.69

0.34

0.33

reduced survival and extended the metamorphosis period in Bufo americanus larvae, but prematurely induced metamorphosis at 5 and 54 μg L-1. Cadmium exposure at 0.25-5 μg L-1 stimulated growth and metamorphosis in Rana pipiens larvae (16, 32). In another study (15), chronic exposure to 0-855 μg L-1 of cadmium did not affect the survival rate of X. laevis larvae. When discussing the complexity of amphibian larval development (under extensive hormonal regulation), it may be concluded that small concentrations of cadmium exposure may even have a stimulating effect on this process.

Figure 2 Cross sections of the gill lamellae of (a) control group, (b) 10 µg L-1 cadmium, and (c) 25 µg L-1 cadmium (lamellar fusion shown with arrows), H&E staining

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Table 3 Statistically significant values of the discriminant analysis made so as to reveal the difference among the groups following cadmium exposure in P. viridis larvae for 96 hours

Function 1 2

Eigenvalue

Variance (%)

Total (%)

Canonical Correlation

Wilks Lambda

Chi-square

df

p

0.648 0.041

94 6

94 100.0

0.627 0.199

0.583 0.960

24.556 1.835

8 3

0.00 0.60

Figure 3 Cross sections of the pronephric tubules of (a) control group, and (b) 25 µg L-1 cadmium (deformations of pronephric tubules shown with asterisk), H&E staining Table 4 The incidence of observed histopathological findings in the gill, kidney, and liver of larvae administered cadmium

Lesions Gills lamellar fusions Kidney deformation of pronephric tubules Liver deformation and haemorrhage Vacuolisation Visceral oedema

Cadmium (µg L-1) 0

1

5

10

25

0 0 0 0 0

0 0 0 0 0

0 1 1 0 3

5 3 3 6 5

7 6 6 8 8

n=10. Values indicate the numbers of larvae with observed lesions in their sections

Figure 4 Cross sections of the liver of (a) control group, (b) 10 µg L-1 cadmium and (c) 25 µg L-1 cadmium (haemorrhage shown with asteriks, vacuolization shown with arrows), H&E staining

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Figure 5 Cross sections of the internal organs of (a) control group, and (b) 25 µg L-1 cadmium (visceral edema shown with asteriks), H&E staining

Heavy metal exposure at sub-lethal concentrations initially affects the gills, with the potential risk of accumulation (44). Gill damage, in particular fusion of secondary lamellae, has been reported in Channa punctatus exposed to 172 mg L-1 of cadmium during 10 days (45). The most important cause of gill lamellar fusion due to pollutant exposure is their function as a barrier for preventing pollutant entry into the body (46). Likewise, fusions in gill lamellae in our study were found in larvae exposed to 10 and 25 μg L-1 of cadmium.

Cadmium causes histopathological changes in the liver, kidney, gill, spleen, and bone marrow, as well as hypocalcemia and hypoglycemia, and inhibits the intake of Ca2+ through gills, therefore affecting plasma ion composition and osmoregulation (27). It has also been reported that cadmium has hepatotoxic effects and causes hepatic dysfunctions and increases in certain enzyme activities (14), as well as histopathological lesions in the liver and necrosis in hepatocytes (45, 47). Furthermore, a study on Bufo arenarum revealed that cadmium accumulates particularly in the liver (48). Much like in other sources, our study also detected serious deformations in the hepatic and renal tubules. The damage observed in liver cross-sections, necrosis, lesions, and haemorrhages verify that cadmium primarily targets the liver. Effects on kidneys include epithelial cell deformations in the pronephric tubules and enlargement of the tubular lumen. Similar results were reported for Rana ridibunda in a study that revealed progressive nephropathy and glomerulonephropathy as a result of cadmium exposure (14).

In conclusion, even though the histopathological findings of our study support the results of previous studies, its main contribution is that it is the first to report results for P. variabilis, which has shown to be a very good indicator species for aquatic ecosystems.

Our LC50 values were lower than those reported by

other investigators. The mechanisms and biological route of cadmium, with special reference to amphibians, has not yet been fully clarified and further detailed acute, sublethal, and chronic toxicity studies are necessary.

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308 40. Loumbourdis NS, Kyriakopoulou-Sklavounou P, Zachariadis G. Effects of cadmium exposure on bioaccumulation and larval growth in the frog Rana ridibunda. Environ Pollut 1999;104:429-33. doi: 10.1016/S0269-7491(98)00172-9 41. Woodal C, Maclean N, Crossley F. Responses of the trout fry (Salmo gairdneri) and Xenopus laevis tadpoles to cadmium and zinc. Comp Biochem Physiol C 1988;89:93-9. doi: 10.1016/0742-8413(88)90151-X 42. Selvi M, Gül A, Yılmaz M. Investigation of acute toxicity of cadmium chloride (CdCl2·H2O) metal salt and behavioral changes it causes on water frog (Rana ridibunda Pallas, 1771). Chemosphere 2003;52:259-63. doi: 10.1016/S00456535(03)00262-5 43. Kayhan FE. Su ürünlerinde kadmiyum biyobirikimi ve toksisitesi [Bioaccumulaton and toxicity of cadmium in the water products, in Turkish]. J Fish Aquat Sci 2006;23:215-20.

44. Flos R, Tort L, Balasch J. Effects of zinc sulphate on haematological parameters in the dogfish Scyliorhinus

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Mallat J. Fish gill structural changes induced by toxicants and other irritants: A statistical review. Can J Fish Aquat Sci 1985;42:630-48. doi: 10.1139/f85-083 Mitsumori K, Shibutani M, Sato S, Onodera H, Nakagava J, Hayashi Y, Ando M. Relationship between the development of hepato-renal toxicity and cadmium accumulation in rats given minimum to large amounts of cadmium chloride in the long-term: Preliminary study. Arch Toxicol 1998;72:54552. doi: 10.1007/s002040050541 Pérez-Coll CS, Herkovits J, Salibian A. [Effects of cadmium on the development of an amphibian, in Spanish]. Arch Biol Med Exp (Santiago) 1985;18:33-9. PMID: 3939390

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Sažetak Akutni toksični učinci kadmija na ličinke zelene žabe, Pseudepidalea variabilis (Pallas, 1769) (Amphibia: Anura) Štetni utjecaji kadmija na okoliš i njegovo nakupljanje u prirodi posljednjih su godina poprimili zabrinjavajuće razmjere. U okviru ove studije istražili smo akutne toksične učinke kadmija na morfologiju i histologiju ličinaka zelene žabe, Pseudepidalea variabilis (Pallas, 1769). Embriji žabe dobiveni su od jedinki koje su u fazi ampleksusa prikupljene u prirodi. U laboratorijskim uvjetima embriji su bili držani do razvojnog stadija 26, kada su izloženi kadmiju u koncentracijama od 0, 1, 5, 10, 25 i 50 µg L-1 tijekom 96 sati. U pokusu smo odredili sljedeće letalne koncentracije kadmija: LC10 26,98 µg L-1, LC50 35,35 µg L-1 i LC90 46,31 µg L-1. Izloženost kadmiju u koncentracijama većim od 1 µg L-1 negativno je utjecala na veličinu tijela ličinaka. Histološke analize upućuju na sljepljivanje škržnih listića, krvarenja u jetrima, pojavu edema u trbušnoj šupljini i deformacije pronefričkih kanalića (pri koncentracijama većim od 10 µg L-1). Dobiveni rezultati pokazali su da je zelena žaba vrlo osjetljiva na kadmij, na što upućuje vrijednost LC50 koja je u našem pokusu bila niža od vrijednosti zabilježenih u drugim istraživanjima. Prema tome, ta se vrsta može smatrati pouzdanim pokazateljem okolišnog stresa u slatkovodnim ekosustavima.

KLJUČNE RIJEČI: embriotoksičnost; histopatologija; letalne koncentracije; teški metal

CORRESPONDING AUTHOR: Sibel Hayretdağ Terzioğlu Campus, 17100 Çanakkale, Turkey E-mail: sibelhayretdag@gmail.com

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DOI: 10.2478/10004-1254-65-2014-2538

Original article

Different enzymatic activities in carp (Cyprinus carpio L.) as potential biomarkers of exposure to the pesticide methomyl David Hernández-Moreno1,2, Irene de la Casa-Resino1, José María Flores1, Manuel José GonzálezGómez1, Carlos María Neila1, Francisco Soler1, and Marcos Pérez-López1 Toxicology Unit, Veterinary School of Caceres, Caceres, Spain1, Universidad Autónoma de Chile, Chile2 Received in May 2014 CrossChecked in May 2014 Accepted in July 2014

This study investigated the influence of the pesticide methomyl on different enzymatic activities in carp.

The fish were exposed to a sub-lethal concentration (0.34 mg L-1) of methomyl for 15 days. On days 4 and 15, catalase (CAT) and glutathione-S-transferase (GST) activities were measured in the liver and gills.

Acetylcholinesterase (AChE) activity in brain and muscle was also determined. Liver catalase activity slightly increased in exposed fish when compared to controls, but it was statistically significant only at the beginning of the experiment. No changes in CAT activity in the gills of exposed and control animals were observed (mean values were in the range 10.7-11.7 nmol min-1 per mg of protein). Liver GST activity was slightly inhibited in the exposed animals at the beginning of the study; however, it was significantly inhibited in the gills. Brain AChE activity was diminished throughout the experiment and significantly decreased after 96 h of exposure compared to controls (0.041 vs. 0.075 nmol min-1 per mg of protein; p<0.001). Our findings suggest that CAT, GST, and AChE are reliable biomarkers of effect after exposure to methomyl.

KEY WORDS: acetylcholinesterase; carbamate; catalase; fish; glutathione S-transferase

Common carp (Cyprinus carpio L.) is one of the most important fish cultured in the world, either as food or for recreational fishing. Carp is often recommended for the baseline evaluation of emerging pollutants in aquatic ecosystems (1) and commonly used in experimental models due to its availability and good adaptation to laboratory conditions (2).

Methomyl [S-methyl N-((methylcarbamoyl)oxy) thioacetimidate], a carbamate insecticide, has been classified as a highly toxic pesticide for aquatic organisms (3). Its acute toxicity to various freshwater fish, with 96-h LC50 values ranging from 0.9 mg L-1 (bluegill sunfish) to 3.4 mg L-1 (rainbow trout), was reported in several studies (4, 5). It is widely used to control insect pests in many countries around the world, and by entering water bodies directly or indirectly it affects both surface and ground waters.

In spite of advancements in chromatographic techniques, the detection of low pesticide levels in water can be difficult because they may fall below detection limits (6). In such instances, the effects of chronic (or sub-lethal) concentrations of pesticides on non-target organisms can be studied by detecting changes in organisms at the physiological, biochemical, or molecular levels, providing “early warning” tools in environment quality monitoring (7, 8). The inhibition and induction of these biomarkers are good approaches to measuring the potential impact of pollutants on environmental organisms. For example, acetylcholinesterase (AChE) activity in fish has proven useful for monitoring the contamination of marine and freshwater ecosystems and this specific inhibitory effect has been directly associated to carbamate and organophosphorus pesticides (9).

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Moreover, many of these potentially toxic compounds or their metabolites have shown toxic effects related to oxidative stress in fish (4, 9-11). Cells have a variety of defence mechanisms to neutralize the harmful effects of free radicals (10). One of the main antioxidative enzymes that serve to detoxify reactive oxygen species are catalases (CAT). CAT is a ubiquitous heme protein that degrades hydrogen peroxide (H2O2) to oxygen and water and is involved with the Haber–Weiss reaction (12). Similarly, glutathione S-transferases (GST) are a group of widely distributed enzymes that catalyse the conjugation of glutathione (GSH) with various electrophilic substances. GST-mediated conjugation is involved in the detoxification of many xenobiotics, playing an important role in protecting tissues from oxidative stress (13).

Taking into account the great relevance of effectbiomarkers when no levels of pesticides can be detected in the environment, the aim of this study was to evaluate the alterations in different biochemical parameters in several tissues of carp (cholinesterase activity in muscle and brain, as well as glutathione S-transferase and catalase enzymatic activities in liver and gills) exposed to methomyl.

MATERIALS AND METHODS Chemicals and reagents All chemicals and reagents were of analytical grade and purchased from Sigma-Aldrich (St. Louis, MO, USA). Tested substance methomyl (CAS No. 1675277-5) was of 99 % purity. Its stock solution was prepared by dissolving the pesticide in 1 mL of absolute ethanol in a standard volumetric flask.

Fish Carp specimens with a weight of 30.0±5.2 g and length of 8-11 cm were acquired from a local fish hatchery in Badajoz (Spain) and acclimated to laboratory conditions for 15 days prior to the beginning of the experiment. Fish were kept in two batches (control and exposed group) of 15 individuals into independent tanks (1 m×0.4 m×0.5 m, 160 effective litres). During the experiment, fish were fed daily with a commercial dry diet (OVN Dibaq-Diproteg, Segovia, Spain) ad libitum until the end of the experiment. Fish were starved for 24 h before sacrifice.

Experimental design The experimental group was exposed to a sublethal concentration of the pesticide (0.34 mg L-1) during 15 days. This concentration represented 10 % of LC50 previously established for rainbow trout (14), being similar to the environmental level found in water samples taken near Cáceres, Spain (unpublished data).

Although the stock solution of pesticide was prepared in ethanol, the final amount of solvent in the aquaria, considering the total volume of the tanks, was negligible, as recommended by OCDE test guidelines (15).

Water quality characteristics (temperature, alkalinity, conductivity, total hardness, dissolved oxygen, ammonia, nitrate and nitrite) were routinely monitored during the experiment and all were within acceptable limits. Furthermore, once a week, water samples (V=250 mL) were taken from each tank and subjected to high-performance liquid chromatography (HPLC) analysis in order to assess the effective concentrations of the pesticide. Standard HPLC technique with acetonitrile and water as mobile phase and a Nucleosyl 120 C18 column was applied, according to the method previously described for other carbamate pesticides (11).

Animal maintenance and experimental procedures were conducted in accordance with the Guide for Use and Care of Laboratory Animals (16), and efforts were made to minimize animal suffering and reduce number of specimens. The experimental design was approved by the Ethics Committee of the University of Extremadura (Spain) and carried out in accordance with current legislation (17).

Exposed and control animals (n=5) were removed on three occasions from each aquarium: at the beginning of the experiment (day 0), and after 4 and 15 days of the experiment.

Fish were anesthetized with a solution of tricaine methanesulfonate (MS222; Sigma-Aldrich, St. Louis, MO, USA) at a concentration of 0.1 g L-1. (11).

Animals were sacrificed; and liver, gills, brain and a portion of muscle were removed, weighed, and individually frozen at -80 °C until biochemical analyses.

Liver and gills of each animal were homogenised in 1:10 (w/v) ice cold potassium phosphate buffer (0.1 mol L-1, pH 7.4). The homogenate was centrifuged for 20 min at 10000 g (4 °C) to obtain the postmitochondrial supernatant. Brain and muscle tissues were homogenized in cold potassium phosphate buffer

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(0.1 mol L-1, pH 7.2). The obtained homogenate was centrifuged at 6000 g for 15 min at 4 °C. The supernatant was used to determine AChE activity (nmol min-1 per mg of protein). AChE activity was spectrophotometrically determined according to Ellman (18), adapted to microplate, by measuring the increase in absorbance of the sample at 405 nm in the presence of 1 mmol L-1 acetylthiocholine as substrate, and 0.1 mmol L-1 5,5,-dithiobis-2-dinitrobenzoic acid (DTNB) as chromogen.

CAT activity assay was carried out by spectrophotometric measurement at 240 nm following the method of Clairborne (19). The enzymatic GST activity was measured at 340 nm according to Habig et al. (20). Specific enzyme activity of was defined as nmol min-1 per mg of protein. Protein content was estimated by the Bradford method (21), using bovine serum albumin as standard.

Statistical analyses were performed using GraphPad Prism v.5 software. All values are represented as mean±standard deviation (SD). Data were treated by means of the non-parametric Kruskal Wallis test followed by the post-hoc Dunn’s test in order to delimitate the groups in which significant differences occurred.

RESULTS AND DISCUSSION Recent environmental monitoring in the Cáceres area indicated the presence of methomyl residues. We therefore decided to perform an experiment to investigate whether an environmentally relevant methomyl concentration, when tested in laboratory conditions, poses risk to carp, a typical fish species that inhabits local freshwater bodies.

In the course of our experiment, despite exposure to the pesticide, no mortality or visual changes on fish indicating potential impairments in the nervous system appeared in any of the considered experimental groups. Methomyl presence in the tested water samples was monitored during the experiment and confirmed by HPLC to be within 20 % of the nominal concentration, with the same retention time as the commercial standard.

The effects of methomyl exposure on CAT, GST, and AChE activity in the tissues of common carp are shown in Figure 1.

Whereas hepatic CAT activity in the exposed fish increased compared to controls both on day 4 (p<0.05) and day 15 of exposure, branchial CAT activity did

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not show any significant difference between control and exposed animals during the whole experiment (mean values 10.7-11.7 nmol min-1 per mg of protein).

In the course of the experiment, liver CAT activity increased both in the control and exposed fish, which was statistically significant only after 4 days of exposure (Figure 1). The higher results appeared after 15 days, which had no relevance with respect to the previous sampling day due to the increased value of CAT in the controls at the same sampling. Ensibi et al. (22) also reported that CAT values in carp exposed to carbamates did not change and tended to be similar to controls after 15 days of treatment, exhibiting changes after only 4 days of exposure. Increased values in controls from the last sampling with respect to controls from day 4 can be explained by external conditions influencing animal behaviour, thus showing the importance of having a control group for each day of experiment.

With respect to hepatic GST activity, significant inhibition in the exposed animals (p<0.05) was observed at the beginning of the experiment compared to control animals (mean GST activity of 72.4 and 87.0 nmol min-1 per mg of protein, respectively), with highly significant inhibition in the gills (p<0.01) of the exposed fish. However, the hepatic inhibitory effect disappeared at the end of the experiment (control and exposed animal GST activities were within 6872 nmol min-1 per mg of protein), whereas the same initial effect quantified in gills remained, although at a lower level of significance (p<0.05).

The differences between the levels of GST activity in the liver of the control fish measured on days 4 and 15 were statistically significant. On the contrary, in the exposed fish no significant differences were observed in the activities of this enzyme on day 4 and day 15 (Figure 1). These changes might have been generated by environmental changes other than the ones covered by this study, which is for control animals more because the antioxidant system of exposed fish is already affected by the pesticide.

Indeed, it was reported that the unchanged GST activity after insecticide exposure may indicate enzyme inactivation by a pesticide or GSH depletion, inducing GST to lose its activity (22).

Some authors reported a lack of effect in CAT levels in gills of fish exposed to carbamates, appearing only after exposure to high concentrations (23).

However, decreased CAT levels were found in C. punctatus exposed to pyrethrins (24). Even when gills are the first contact-point with xenobiotics, they do

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Figure 1 Levels of catalase (CAT), glutathione-S-transferase (GST), and acetylcholinesterase (AChE) measured in tissues of common carp exposed to 0.34 mg L-1 of methomyl in laboratory conditions.

Control 1 corresponds to results from day 4, as it was established at the beginning of the experiment and Control 2 corresponds to results from day 15, as it was established at the end of the experiment. *p<0.05; **p<0.01; ***p<0.001

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not always have an effect over this tissue, passing directly through this barrier and acting on other tissues like liver. In fact, CAT levels were reported higher in liver as a result of breaking down toxins present in the blood and processing metabolic products for degradation (25, 26).

Ferrari et al. (27) showed that different pesticides induced hepatic CAT activity during the first 48 h of exposure, and similarly, Capkin and Altinok (28) observed that rainbow trout exposed to 25 µg L-1 of carbamate carbosulfan for 60-days significantly increased liver CAT activity when compared to controls.

However, oxidative stress levels in fish from waters contaminated by different concentrations of pesticides were entirely different (29), and in some cases a clearly inhibitory effect was observed. Crestani et al. (30) for instance, observed a reduction in CAT activity in the liver of silver catfish exposed to the herbicide clomazone. Similar effects were found by Pandey et al. (31) in the liver of the freshwater fish Channa punctatus evaluated after 24 h of treatment with endosulfan. Blahová et al. (32) observed a significant decline in CAT activity in zebrafish exposed to atrazine. Curiously, this same xenobiotic was assayed

by Nwani et al. (33), who noticed an elevation of liver CAT activity after the exposure of Channa punctatus.

The first line of defence against oxidative stress consists of antioxidant enzymes (e.g., CAT) and a decrease in their activity changes the redox status of the cells. Thus, it is possible that an increase in the activity of these enzymes contributes to the elimination of ROS induced by cells exposed to pesticides (34, 35).

GST has also been widely used as an environmental biomarker. In some studies, hepatic GST activity decreased after 5 days of exposure to a mixture of pesticides (36). Similarly, liver of fish fed with a standard diet and exposed to the herbicide quinclorac showed a marked inhibition of GST activity (2).

Nevertheless, some studies have also observed an opposite effect, as for example low level exposure of Galaxias maculatus, Galaxias truttaceus, and Salmo gairdneri to the fungicide tetrachloroisophthalonitrile resulted with the induction of the liver GST activity (37).

When considering studies focused on carbamate pesticides and fish, a clear inhibition of GST activity was spotted after 96 h of exposition to methomyl (4).

These results are in agreement not only with ours, but also with those of Rendón-von Osten et al. (9), who

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found a significant inhibition of GST activity in mosquito fish (G. yucatana) gills after 24 h exposure to 0.06 mg L-1 of carbofuran. GST inhibition has also been reported in gills of mosquito fish exposed to carbofuran and liver of Ancistrus multispinis exposed to deltamethrin (38). The observed decrease of GST activity may have occurred because liver and gills are two of the first organs in the contact with pesticides.

However, this decrease may lead to a different response where the antioxidant defence is disrupted by pesticides or its derived products, indicating a toxic situation caused by insecticide exposure (39).

As shown in Figure 1, methomyl exposure caused a clear and significant decrease in AChE activity compared to controls both in brain (p<0.001 on day 4; p<0.01 on day 15) and muscle (p<0.01 on day 4 and 15). Thus, our results indicate that AChE activity varied according to tissue type at least during the first days of exposure, with brain tissue being more susceptible. This phenomenon could be related to the higher number of neurons in the brain than in the muscles, i.e. more receptors were available directly.

After first contact with the pesticide, and thus after saturation of the synaptic sites in both tissues, the inhibition rate reached equilibrium.

There were no significant differences in the AChE activities measured in brain and muscle of control fish on days 4 and 15. Comparison of the values measured in the exposed fish indicate that brain AChE activity was significantly lower on day 4 as compared to day 15 (Figure 1). Several studies reported a similarity between the AChE activity of exposed fish and controls after an initial period of inhibition (11, 40).

Reactivations of the carbamate-mediated anticholinesterase effect, or even an enzyme superproduction as a response to inhibition, have been reported as cause for that phenomenon (41).

The highest inhibition in brain samples took place at day 4 (0.041 nmol min-1 per mg of protein in exposed animals, and 0.075 nmol min-1 per mg of protein in control), clearly showing the inhibitory effect of carbamate pesticides and rendering AChE activity as the most adequate biomarker for exposition to carbamates in fish. The same was reported in several studies on freshwater and marine fish (42-44). For instance, Hernández-Moreno et al. (43) observed that brain and muscle cholinesterase activities in seabass (Dicentrarchus labrax) exposed to 250 mg L-1 of carbofuran were significantly inhibited, showing a 47 % of inhibition in brain and 41 % in muscle, compared to the control. Moreover, Bretaud et al. (40)

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reported a significant inhibition of both brain and muscle AChE activity in the goldfish (Carassius auratus) after 48 h of exposure to 500 mg L-1 of carbofuran. The same pesticide also caused AChE activity inhibition in tench (Tinca tinca) exposed to 100 μg L-1 of carbofuran, whereas an exposure to deltamethrin did not affect AChE activity (11). Li et al. (4) evaluated the acute toxicity of the pesticide methomyl on the topmouth gudgeon (Pseudorasbora parva). In our study, the pesticide caused a sharp decrease in specific brain AChE activity (around 48 %) with concentrations between 0.043 and 0.213 mg L-1.

These results were similar to those obtained by other authors, with C. auratus exposed in vitro to methomyl for 8 min at 30 °C in which AChE activity was sharply inhibited (44).

To conclude, catalase, GST and AChE showed to be good biomarkers of effect after exposure to methomyl, whereas carps proved suitable for biomonitoring the environments they inhabit.

Although limited by only one concentration tested, our study suggests that exposing the common carp to methomyl at sub-lethal levels could provoke changes in enzyme activity, which is in accordance with previously published literature on the subject.

Acknowledgements This study was in part supported by fellowship PRE09001 (Irene de la Casa-Resino) from Consejería de Empleo, Empresa e Innovación (Gobierno de Extremadura, Spain).

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Silva Filho MV, Oliveira MM, Salles JB, Cunha Bastos VLF, Cassano VPF, Cunha Bastos J. Methyl-paraoxon comparative inhibition kinetics for acetylcholinesterases from brain of neotropical fishes. Toxicol Lett 2004;153:247-54. doi: 10.1016/j.toxlet.2004.04.026 Hernández-Moreno D, Pérez-López M, Soler F, Gravato C, Guilhermino L. Effects of carbofuran on the sea bass (Dicentrarchus labrax L.): study of biomarkers and behaviour alterations. Ecotoxicol Environ Saf 2011;74:190512. doi: 10.1016/j.ecoenv.2011.07.016 Yi MQ, Liu HX, Shi XY, Liang P, Gao XW. Inhibitory effects of four carbamate insecticides on acetylcholinesterase of male and female Carassius auratus in vitro. Comp Biochem Physiol C Toxicol Pharmacol 2006;143:113-6. doi: 10.1016/j. cbpc.2005.12.008

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Sažetak Razlike u enzimskim aktivnostima u tkivima šarana (Cyprinus carpio L.) kao mogući biološki pokazatelji izloženosti pesticidu metomilu Istražen je utjecaj pesticida metomila na razine enzimskih aktivnosti u tkivima šarana izloženih subletalnoj koncentraciji od 0,34 mg L-1 tijekom 15 dana. Nakon 4 i 15 dana u jetrima i škrgama pokusnih životinja izmjerene su aktivnosti katalaze i glutation S-transferaze (GST), a aktivnost acetilkolinesteraze (AChE) u mozgu i mišićima. Aktivnost katalaze u jetrima blago se smanjila u izloženih riba u usporedbi s kontrolnom skupinom, no to je smanjenje bilo statistički značajno tek na početku pokusa. Istovremeno nisu zamijećene značajne promjene u aktivnosti katalaze u škrgama izloženih i kontrolnih riba (srednje vrijednosti bile su u rasponu 10,7-11,7 nmol min-1 po miligramu proteina. Dok je aktivnost enzima GST u jetrima izloženih riba bila tek blago inhibirana na početku pokusa, u škrgama je utvrđena značajna inhibicija. Aktivnost acetilkolinesteraze u mozgu s vremenom se smanjivala i pokazala značajan pad nakon 96 sati izloženosti (0,041 vs. 0,075 nmol min-1 po miligramu proteina; p<0.001). Rezultati upućuju na zaključak da su katalaza, GST i AChE pouzdani biološki pokazatelji učinka izloženosti metomilu.

KLJUČNE RIJEČI: acetilkolinesteraza; karbamat; katalaza; ribe; glutation S-transferaza

CORRESPONDING AUTHOR: Marcos Pérez-López Toxicology Unit, Veterinary School of Caceres Avda de la Universidad s/n.

10003 Caceres, Spain E-mail: marcospl@unex.es

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DOI: 10.2478/10004-1254-65-2014-2551

Original article

Dissolved heavy metal determination and ecotoxicological assessment: a case study of the Corumbataí River (São Paulo, Brazil) Lucineide Aparecida Maranho1, Leila Teresinha Maranho2, Rafael Grossi Botelho1, and Valdemar Luiz Tornisielo1 Laboratório de Ecotoxicologia Aquática, Centro de Energia Nuclear na Agricultura, Universidade de São PauloCENA/USP1, Programa de Pós-graduação em Gestão Ambiental, Universidade Positivo-UP2, Campo Comprido, Curitiba, PR, Brazil Received in June 2014 CrossChecked in June 2014 Accepted in September 2014

The aim of this one-year study (August 2009 to July 2010) was to evaluate the Corumbataí River water polluted by anthropogenic sources and see how it affects the reproduction of the microcrustacean Ceriodaphnia dubia (Richard, 1984) in laboratory conditions over seven days of exposure to water samples collected monthly at six different locations. We determined the concentrations of zinc (Zn), copper (Cu), nickel (Ni), lead (Pb), and cadmium (Cd), as well as physicochemical parameters such as dissolved oxygen, conductivity, water temperature, and pH. Dissolved oxygen and conductivity demonstrated anthropogenic influence, as dissolved oxygen concentration decreased and conductivity increased from the upstream to the downstream stretch of the river. The effects on C. dubia were observed in the months with high precipitation, but the toxicity cannot be associated with any particular contaminant. Heavy metal levels kept well below the limit values. Zn and Pb had the highest concentrations in the water during the sampling period, probably due to the industrial and agricultural influence. However, these levels do not seem to be associated with precipitation, which suggests that their primary source was industry. Physicochemical parameters, the ecotoxicological assay, and determination of heavy metals proved to be efficient tools to evaluate aquatic environments.

KEY WORDS: Ceriodaphnia dubia; inorganic contaminants; physicochemical parameters; toxicity test; water

Rivers are often polluted by indiscriminate disposal of sewage and industrial wastes and a plethora of human activities. Preservation of river water quality requires effective monitoring, but the assessment of aquatic environment contamination is often limited to physicochemical analyses (1). According to Forget et al. (2) and Cairns (3), this is not enough to determine the real state of water quality and the analysis should be complemented with ecotoxicological assays that look into the interaction between the living organisms and the concentrations of chemical agents in the

aquatic environment. For this purpose, ecotoxicological assays often use sensitive organisms such as microcrustaceans.

In addition to physicochemical parameters and ecotoxicological assays, water monitoring should include the determination and quantification of metals (4-6). Although their impact has no visible influence compared to other pollutants, heavy metals can cause long-term effects on ecosystems (7) due to their persistence, bioaccumulation, and biomagnification in the food chain (8).

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The aim of our study was to evaluate the water quality of the Corumbataí River by combining these three monitoring methods over a one-year period.

The Corumbataí River basin is an important water source located in the state of São Paulo, Brazil, between latitude 22°05’–22°30’S and longitude 47°30’–47°50’W, and includes an area of approximately 1.690 km2 (9). This river was chosen for this study because it is located in one of the most industrialised regions of São Paulo and receives effluents from industries such as textile, ethanol, and chemistry. In addition, this is one of the largest sugarcaneproducing regions of Brazil (10), and according to Wahlberg et al. (11) agricultural areas may also contribute to heavy metal contamination of aquatic environments.

Earlier studies conducted in the Corumbataí River to characterise its water quality have used different methodologies, but never a combination that would involve long-term ecotoxicological assays and heavy metal determination. In one of these studies, Jardim et al. (12) established acute and chronic toxicity of the Corumbataí River water and sediment to the microcrustaceans Daphnia magna (Straus, 1820) and Daphnia similis (Claus, 1876) in two sampling periods over less than a year. In another study, Cetra and Petrere (9) observed that species richness was the highest in locations with greater vegetation cover and preserved riparian forest.

The only study (by Pescim et al., 13) determining metals in the Corumbataí River reinforces the need for further investigation into the influence of industrial and agricultural effluents on this ecosystem.

MATERIALS AND METHODS Sampling sites and physicochemical parameters Surface water samples were collected from six locations along the centre of the Corumbataí River course on a monthly basis from August 2009 to July 2010 (see Figure 1).

Physicochemical parameters dissolved oxygen and water temperature, were measured at the river using a YSI Model 55 (12-feet cable length) handheld oxymeter (YSI, Yellow Springs, OH, USA).

Conductivity (conductivimeter Ação Científica MPA150 P, Marconi, Piracicaba, Brazil) and pH (pH meter Ação Científica MPA-210 P) were determined in the

Figure 1 Water sampling points (P) (n=72) along the Corumbataí River, São Paulo, Brazil P1 and P2: upstream and downstream of the Corumbataí City; P3 and P4: upstream and downstream of the city of Rio Claro; P5 and P6: upstream of and in Piracicaba, respectively

laboratory immediately after sampling. The sampling followed the Standard Methods of Examination of Water and Wastewater of the American Public Health Association (14). The results of physicochemical parameters are expressed as the mean±standard deviation of all measurements over the sampling period, including the range and the coefficient of variation.

Precipitation Precipitation data (rainfall accumulation) in the Corumbataí River for the study period was provided by the Water and Electric Energy Department (DAEE) of Piracicaba (São Paulo, Brazil). Precipitation was measured monthly at four monitoring locations in the cities of Analândia, Corumbataí, Rio Claro, and Piracicaba.

Culturing and toxicity testing with Ceriodaphnia dubia Ceriodaphnia dubia was used in the this study because it has been standardised for ecotoxicological studies by the Brazilian Technical Standard Association (ABNT) (15) and is readily available and easy to cultivate in a laboratory. All procedures for culturing and toxicity testing followed the ABNT NBR 13373 standard (15). The cultures (reconstituted water) were maintained in the Laboratory of Aquatic Ecotoxicology, Centre for Nuclear Energy in Agriculture (Piracicaba, São Paulo, Brazil) in an incubator (40 organisms in

Maranho LA, et al. HEAVY METAL AND ECOTOXICOLOGICAL ASSESSMENT OF THE CORUMBATAÍ RIVER Arh Hig Rada Toksikol 2014;65:319-328

each culture) at 25±2 °C and 16:8 h light/dark cycle.

Reconstituted water was prepared using 18 MΩ deionised water and reagent-grade chemicals. The pH ranged from 7 to 7.6 and hardness from 48 to 50 mg L-1 of CaCO3, which was in accordance with the ABNT recommendations. The culture medium was renewed twice a week, and the C. dubia was fed with algae Pseudokirchneriella subcapitata (Hindak, 1990) three times a week (1x105 cells per organism). Once a month, the test organisms were evaluated for their sensitivity (lethality) using NaCl as a reference substance (15). The 48-hour median lethal concentration (LC 50) of NaCl to C. dubia was determined using the Trimmed Spearman-Karber method (16).

For the toxicity test, one individual of C. dubia (<24 h old) was housed in a 30-mL glass container with 20 mL of test solution (unfiltered and undiluted water sample). Ten replicates were used for each sampling point plus a control group (culture medium).

The test was conducted under the same conditions as the culture maintenance. Water samples were kept in a refrigerator below -20 °C to maintain their characteristics. The test lasted seven days, and the solutions were renewed every two days with the adult microcrustacean transferred to the new solution. During the renewal, the organisms were fed with P. subcapitata (1x105 cells per organism), and the number of neonates produced was recorded as reproduction endpoint.

Metal determination Water samples were homogenised, filtered through 0.45-μm syringe filters, and added to a 300-mL beaker.

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They were then acidified with 4 mL of HNO3 and evaporated on a heating plate to 10 mL. After the heating, the samples were maintained at reflux for 30 min, and then transferred to 50-mL volumetric flasks, and the volume was filled up with deionised water. Cd, Zn, Cu, Pb, and Ni were analysed using a flame atomic absorption spectrometer (AA 7000, Shimadzu, Columbia, MA, USA).

The limit of quantification and the limit of detection for each metal were determined following the guideline about the validation of analytical methods by the National Agency for Sanitary Vigilance (ANVISA) (17).

Statistical analysis To compare the mean values of C. dubia reproduction between the control group and the groups treated with the Corumbataí River water we used oneway analysis of variance (ANOVA) followed by Tukey’s test. Data were analysed using SAS software version 9.2 (SAS Institute Inc, Cary, NC, USA).

RESULTS AND DISCUSSION Precipitation Figure 2 shows the Corumbataí River precipitation over the sampling period. High precipitation was recorded in November 2009 (244.00 mm) for Analândia and December 2009 (375.90 mm), January 2010 (582.90mm), and February 2010 (238.90 mm) for Rio Claro.

Figure 2 Total precipitation (mm) in the Corumbataí River during the sampling period

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Physicochemical parameters The physicochemical features of sampled water are presented in Table 1. Mean water temperature varied between 19.37 °C and 21.74 °C. Water temperature increased from Point 1 to Point 6 (downstream) (Table 1), probably due to the heat produced by sunlight because the water samples were collected in the morning starting at Point 1 and ending in the afternoon at Point 6.

For its biota to be preserved, the Brazilian rivers should have a pH ranging from 6 to 9, according to CONAMA (18). In our study, the mean pH ranged from 7.21 to 7.51 (Table 1), which is within this range.

In contrast, according to CONAMA (18), dissolved oxygen should not drop below 5.0 mg L-1, but the mean values of dissolved oxygen at all sampling points were below this limit (Table 1). They decreased from the upstream to the downstream of the river, probably due to water temperature increase, as mentioned above.

Domestic sewage from Rio Claro and Piracicaba may have also contributed its drop.

The highest conductivity values were observed at Points 3, 4, 5, and 6 (Table 1). High conductivity is expected in samples collected in areas affected by industrial and agricultural activities that release dissolved ions through effluents and soil leachates. Accordingly, only Points 1 and 2 were not affected by industrial activities.

Chronic toxicity test with C. dubia The mean, 48-hour LC50 of NaCl to C. dubia for all months was 1.89±0.22 mg L-1, with the coefficient

of variation of 11.64 %. These values are within the variability limit (mean±2 standard deviation) and acceptable by the national standard (15).

Water was considered toxic to organisms when mean reproduction was significantly lower than control (p<0.05). This was the case with water samples collected at nearly all sampling points from November 2009 to February 2010 (Table 2). Water collected from August to October 2009 and from March to July 2010 showed lower toxicity, as one or two points presented a significant difference compared to control (p<0.05).

It is difficult to associate the cause of toxicity with a particular substance or element when organisms are exposed to river waters, because rivers contain complex mixtures of contaminants. In the case of the Corumbataí River, for example, many substances such as heavy metals have been detected in the water, sediments, and fish (19, 20). Beside heavy metals, several classes of herbicides have been reported (21).

Botelho (22) reported atrazine and ametrine in the Piracicaba River, which make part of the same basin as the Corumbataí River. These two herbicides are often used in sugarcane crops in the region. Many authors demonstrated the toxicity of herbicides to aquatic organisms (23-28).

Our chronic toxicity findings seem to be associated with run-offs carrying contaminants such as pesticides from agricultural areas, as indicated by precipitation rates. The samples that had higher toxicity were collected in the months with higher precipitation. The exception is March, which showed toxicity at two

Table 1 Physicochemical parameters measured at the sampling points from August 2009 to July 2010

Points 1 2 3 4 5 6

Mean±SD Range Coefficient of variation Mean±SD Range Coefficient of variation Mean±SD Range Coefficient of variation Mean±SD Range Coefficient of variation Mean±SD Range Coefficient of variation Mean±SD Range Coefficient of variation

Water temperature (°C) 19.37±3.43 12.40-23.50 17.71 19.73±3.45 12.90-23.80 17.49 21.14±3.50 14.10-23.80 16.56 21.41±3.76 14.10-25.70 17.42 21.41±4.02 14.70-26.90 18.78 21.74±3.92 15.70-28.50 18.03

pH 7.51±0.51 6.70-8.61 6.79 7.44±0.64 6.43-8.66 8.60 7.22±0.47 6.44-8.06 6.51 7.21±0.48 6.23-7.88 6.66 7.21±0.47 6.65-8.11 6.52 7.36±0.43 6.37-8.07 5.84

Conductivity (µs cm-1) 44.66±7.68 34.30-58.20 17.20 40.30±6.74 30.10-46.90 16.72 56.48±12.41 37.80-71.60 21.97 89.48±19.78 72.50-116.00 22.10 89.48±52.76 52.60-233.10 58.96 148.30±46.56 99.30-215.70 52.06

Dissolved oxygen (mg L-1) 4.70±1.19 2.82-7.21 25.32 4.67±1.18 2.49-6.86 25.27 4.04±1.21 2.50-6.16 29.95 3.49±0.90 2.11-5.24 25.78 3.64±1.11 2.23-6.02 30.50 3.74±0.86 1.94-5.12 22.00

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Table 2 Mean values of Ceriodaphnia dubia reproduction (neonates/female) from August 2009 to July 2010 after exposure to the Corumbataí River water Samples Control Point 1 Point 2 Point 3 Point 4 Point 5 Point 6

Aug

Sep

Oct

Nov

Dec

19.70a 7.88b* 11.00ab 14.00ab 16.44ªb 13.60ªb 11.50ªb

21.70ª 13.00ab 8.66b* 14.50ªb 14.50ªb 17.60ªb 10.90b*

21.70ª 8.33b* 10.90b 12.70ªb 14.90ªb 11.11ªb 7.20b*

21.10ª 5.57b* 6.37b* 13.22b* 23.88ª 19.77ªb 15.40ªb

22.80ª 11.70b* 10.60b* 13.20ªb 11.40b* 20.30ªb 11.70b*

Months Jan 24.50ª 13.50b* 10.20b* 10.66b* 11.33b* 15.20b* 13.70b*

Differing letters denote significant difference (Tukey’s test; p<0.05). *toxic

sampling points only but had high precipitation (Tables 1 and 2).

During the rainy season, contamination of the aquatic environment increases due to the availability of contaminants and nutrients from agricultural soils.

Affonso et al. (29) established high trophic state index (TSI) in a lake in Brazil during the rainy season and concluded that the run-off of nutrients into the lake may have caused the eutrophication. The same was observed by Alves et al. (30). Likewise, Armas et al.

(21) observed higher levels of herbicides (atrazine, ametrine, simazine, glyphosate, and clomazone) in the Corumbataí River at the beginning of the rainy season, confirming that run-off is an important route of contamination of aquatic environments.

Metal findings The tremendous use of Pb, Zn, Ni, Cd, and Cu over the past few decades has resulted in an increased concentration in the aquatic systems (31, 32). Due to their role in carrying away municipal and industrial wastewater and run-off from agricultural land, rivers are among the most vulnerable water bodies to metal pollution (33).

The method we used for the detection of metals in the Corumbataí River water had the coefficient of correlation higher than 0.99 for all metals and therefore high sensitivity. Its limit of quantification and detection are presented in Table 3.

Spatial variations of metal concentrations during the sampling period are presented in Table 4. Mean concentrations over the study period were lower than those set by the Brazilian environmental legislation (18) and World Health Organization (34). However, we can not be sure whether the measured concentrations are toxic or not to the aquatic organisms living in this river, as we have not conducted metal-specific toxicity assays. The most common was Zn, followed by Pb, Cd, and Ni. Cu kept below the limit of detection,

Feb

Mar

Apr

May

Jun

Jul

23.00a 15.80ªb 22.80ª 6.60b* 8.00b* 2.71b* 5.60b*

21.40ª 11.30b* 14.55ªb 14.33ªb 20.40ªb 14.90ªb 4.22b*

22.70ª 13.20b* 18.44ªb 19.14ªb 17.50ªb 19.50ªb 18.87ab

23.50ª 11.85b* 14.20b* 16.55ab 18.11ªb 21.33ªb 26.33ab

21.30ª 12.22ªb 13.75ªb 9.20b* 8.80b* 16.50ªb 19.10ª

18.80b 7.42c** 7.70c** 24.90ªb 33.10ª* 26.77ªb 32.90ª*

probably due to the water filtration of organic matter to which Cu binds (Table 4).

Points 1 (upstream of Corumbataí City) and 2 (downstream of Corumbataí City) are considered the locations with a lower influence of industrial activities, as they are located upstream and downstream from a small city. Points 3 through 6 are located in an area with higher industrial influence close to or within big cities such as Rio Claro and Piracicaba. Points with the higher occurrence of metals (in decreasing order) were 6, 3, 2, 1, 4, and 5. Although Points 1 and 2 are not considered under industrial influence, higher heavy metal levels compared to Points 4 and 5 may point to run-off of from soils cultivated with sugarcane.

In any case, the occurrence of any of the metals cannot be attributed to any specific activity as the river runs through both industrial and agricultural areas. Zn had the highest concentrations at Point 3 followed by Points 1, 4, 5, 2, and 6. Cd was determined at a higher concentration at Point 6 followed by Points 2 and 3.

Concentrations of Ni were higher at Points 4, 6, and 1, whereas Pb presented higher concentrations at Point 6 followed by Points 2, 5, and 1.

Pb and Zn are among the most common toxic pollutants in industrial wastewater. Pb is a normal constituent of the earth’s crust and trace amounts naturally occur in soil and water. According to Yi et al. (35), Pb may also originate from metal processing, Table 3 Limit of quantification (µg L-1) and limit of detection (µg L-1) for each of the metals analysed in the water samples of the Corumbataí River using flame atomic absorption spectrometry

Metals Zn Cd Cu Pb Ni

Limit of quantification

Limit of detection

0.17 0.005 0.25 0.20 0.26

0.11 0.003 0.16 0.13 0.17

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Maranho LA, et al. HEAVY METAL AND ECOTOXICOLOGICAL ASSESSMENT OF THE CORUMBATAÍ RIVER Arh Hig Rada Toksikol 2014;65:319-328

Table 4 Mean metal concentrations (µg L-1) at each sampling point in the Corumbataí River from August 2009 to July 2010

Points

Metal means±SD (µg L-1)

Zn Cd Cu Ni Pb 1 0.30±0.54 <LD <LD 0.06±0.14 0.10±0.19 2 0.18±0.32 0.17±0.05 <LD <LD 2.79±1.14 3 0.44±0.67 0.02±0.02 <LD <LD 0.24±0.42 4 0.29±0.18 <LD <LD 0.17±0.21 <LD 5 0.19±0.23 <LD <LD <LD 2.20±1.39 6 0.08±0.13 0.30±0.11 <LD 0.08±0.27 3.51±1.20 a a a a 180 1 9 25 10a Maximally permitted -1 b b b b value (µg L ) 10 3 2000 20 10b a b <LD = below the limit of detection. and refers to the maximally permitted value according to CONAMA (18) and WHO (34), respectively

Figure 3 Temporal variations of Zn, Cd, Ni, and Pb at Points 1 through 6

Maranho LA, et al. HEAVY METAL AND ECOTOXICOLOGICAL ASSESSMENT OF THE CORUMBATAÍ RIVER Arh Hig Rada Toksikol 2014;65:319-328

electroplating industries, industrial wastewater, and domestic sewage. In addition to industrial effluents, the occurrence of Pb in our study can be associated with erosion and run-off with Pb-containing particles from soil cultivated with sugar cane.

Zn as zinc oxide is used in the ceramics industry, while zinc sulphate is common in textile industry and fertilisers, all of which are present in the Corumbataí River basin. Zn is toxic to very many aquatic species.

For example, Zhu et al. (36) demonstrated that Zn significantly affects the development of Gobiocypris rarus (Ye and Fu, 1983) fish embryos, especially the development of body and heart after exposure from 0.01 to 1.000 mg L-1.

Figure 3 shows temporal variations of the elements at each sampling point. With the exception of Zn at Point 1, the results suggest that metal levels in the Corumbataí River are not related to precipitation (Figures 2 and 3). This reinforces our assumption that the contamination was mainly owed to industrial effluents as opposed to run-off. Many studies of the rivers of São Paulo have been developed to identify and quantify metals in different matrices. For example, Fostier et al. (20) observed that Hg contaminated all compartments (water, sediment, soil, and fish) in the Piracicaba River Basin. In the same basin França et al. (37) found more than 30 elements in suspended sediments, including those of great environmental importance such as Se, Sb, Cr, Mo, Zn, and Hg. In the study by Meche et al. (38), 11 of 14 metals (Al, As, Cd, Co, Cr, Cu, Mn, Ni, Pb, Se, and Zn) were above the limit allowed by CONAMA (18). All these findings, including our own, confirm that all aquatic compartments are being contaminated. Considering that both population and industrial activity will increase heavy metals levels should be carefully monitored in the São Paulo Rivers.

CONCLUSION According to the physicochemical parameters (conductivity and dissolved oxygen) determined in our study, water quality decreased downstream of the river, probably due to the influence of industrial and domestic effluents. C. dubia turned out to be a sensitive organism for the evaluation of environmental contamination. The effects of the Corumbataí River water on the microcrustacean seem to be associated with precipitation, but the toxicity cannot be associated with any particular contaminant, and especially not

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with the metals measured in this study, whose levels kept well below the limit values. Zn and Pb had the highest concentrations in the water during the sampling period probably due to the industrial and agricultural influence. However, these levels do not seem to be associated with precipitation, which suggests that their primary source was industry.

Acknowledgments This study was supported by Fundação de Amparo à Pesquisa do Estado de São Paulo-FAPESP. Conflict of interest The authors declare no conflict of interest.

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Sažetak Određivanje otopljenih teških metala i ekotoksikološka procjena: prikaz istraživanja na rijeci Corumbataí (São Paulo, Brazil) Cilj ovog jednogodišnjeg istraživanja (od kolovoza 2009. do srpnja 2010.) bio je ocijeniti kakvoću rijeke Corumbataí, koja je onečišćena antropogenim izvorima, te ispitati kako ona utječe na razmnožavanje račića Ceriodaphnia dubia (Richard, 1984.) u laboratorijskim uvjetima sedmodnevne izloženosti uzorcima vode prikupljenima svakog mjeseca sa šest lokacija. Utvrđene su koncentracije cinka (Zn), bakra (Cu), nikla (Ni), olova (Pb) i kadmija (Cd) te fizikalnokemijskih parametara poput otopljenog kisika, provodljivosti, temperature vode i pH. Razine otopljenog kisika i provodljivost ukazali su na antropogene utjecaje, budući da se razina otopljenog kisika snižavala, a provodljivost rasla nizvodno. Toksično djelovanje na C. dubia zamijećeno je u uzorcima prikupljenima tijekom kišnih mjeseci, ali se ona ne može povezati s pojedinačnim zagađivalima. Razine teških metala bile su daleko ispod propisanih gornjih granica. Najviše koncentracije u vodi izmjerene su za Zn i Pb, što je vjerojatno povezano s industrijskom i poljoprivrednom aktivnosti.

Te se razine međutim ne daju povezati s padalinama, što upućuje na zaključak da je njihov glavni izvor industrija. Fizikalnokemijski parametri, ekotoksikološki test i određivanje teških metala pokazali su se korisnim alatima za procjenu onečišćenosti vodenog okoliša.

KLJUČNE RIJEČI: anorganska zagađivala; Ceriodaphnia dubia; fizikalnokemijski parametri; test toksičnosti; voda

CORRESPONDING AUTHOR: Rafael Grossi Botelho Laboratório de Ecototixoclogia Aquática, Avenida Centenário303, 13416-000, São Dimas, Piracicaba-SP, Brazil E-mail: rafaelgrossib@hotmail.com

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Wilman K, et al. PATHOGENIC FUNGI IN PEA SEEDS Arh Hig Rada Toksikol 2014;65:329-338

DOI: 10.2478/10004-1254-65-2014-2480

Original article

Plant-pathogenic fungi in seeds of different pea cultivars in Poland Karolina Wilman, Łukasz Stępień, Izabela Fabiańska, and Piotr Kachlicki Department of Pathogen Genetics and Plant Resistance, Institute of Plant Genetics, Polish Academy of Sciences, Poznań, Poland Received in December 2013 CrossChecked in December 2013 Accepted in July 2014

Legume crops are exposed to infection by fungal pathogens, which often results in contamination with mycotoxins. The aim of this study was to evaluate the level of field resistance/susceptibility of edible and fodder pea cultivars to the colonization of seeds by fungal pathogens in two subsequent seasons, as well as to identify the pathogens present in the seeds of the tested cultivars. Alternaria spp. were the most common fungi isolated from pea seeds in both seasons, followed by Fusarium spp., Stemphylium spp., Ulocladium spp., Botrytis cinerea Pers., Epicoccum nigrum Link., and Phoma pinodella L. K. Jones.

The highest percentage of infected seeds (55 %) was recorded for cultivar Ezop. The presence of a large number of fungi was found in 2012 for cultivars Santana, Tarchalska, Medal, Cysterski, Mentor, Lasso, and Ezop. Fodder cultivars displayed a lower infection level than edible cultivars. We can conclude that Alternaria spp. were the most frequent fungi present in pea seeds in Poland and Fusarium spp. were likely the most dangerous, having in mind their established mycotoxigenic abilities.

KEY WORDS: Alternaria; Fusarium; molecular identification; mycotoxins; seed-borne pathogens; seedtransmitted diseases

As many other plant species, legume crops are exposed to infection by fungal pathogens, which often cause the accumulation of mycotoxins in plant tissues. The consumption of contaminated plant material poses a serious risk to human and animal health. Fungal species, including Fusarium spp., Phoma pinodella L. K. Jones, Ascochyta pisi Lib., and Alternaria spp., are among the most important agents involved in field pea (Pisum sativum L.) diseases (1).

Ascochyta pea diseases (blights), caused by Ascochyta spp. and Phoma spp., are responsible for limiting seed yield worldwide. The first disease symptoms relate to the formation of spores on aerial organs. The infection progresses quickly and results in necrotic lesions (2). Pea-infecting Ascochyta and Phoma fungi are able to produce several phytotoxins

that have a key role in the damage of plant cells (3, 4).

Fusarium species are widely spread and infect plants independently of developmental stage. The growth of the Fusarium fungi and the accumulation of their mycotoxins can affect grain quality (5).

Occurrence of pea root rot is associated with two pathogens: F. solani f. sp. pisi F. R. Jones (6) and F. avenaceum (Fr.) Sacc. (7). A vascular pathogen, Fusarium oxysporum f.sp. pisi (Fop) Schltdl., which infects the xylem tissue and is a known factor in Fusarium wilt (8). The progress of symptoms depends on the Fop race (9).

The Alternaria genus includes saprobiotic, endophytic, and pathogenic species that may cause various plant diseases. According to Thomma (10), melanin production by fungal isolates has significant

330 impact on the virulence of the isolate. Tentoxin plays a role in pathogenesis (11) by blocking the ATPase responsible for the hydrolysis of ATP in plant chloroplasts. This leads to the chlorosis of sensitive hosts.

Infections of plant tissues by pathogenic fungi can cause yield losses as high as 50-75 % (12). It is therefore important to know the specific susceptibility level of different pea cultivars to fungal pathogens. Many fungal species belong to seed-borne pathogens, as they spread along the plant during growth. One possible reaction of a plant resistant to fungal infection is hypersensitivity and seed abortion. Genotypes that do not respond to the infection process may produce fungicontaminated seeds.

The aim of the present study was to evaluate the level of resistance/susceptibility of edible and fodder cultivars of field pea to infection by fungal pathogens and identify the pathogens present in the seeds of the tested cultivars. This knowledge could help single out and grow only resistant cultivars, which would in turn prevent the contamination of food and agricultural products with harmful mycotoxins. This study is the first to provide such an extensive and detailed analysis of seed contamination in pea cultivars in Poland. In addition, we also compared the specific weather conditions at the two studied locations in order to analyse the factors affecting fungal contamination and emphasise the differences in local pathogen populations.

MATERIALS AND METHODS Isolation of fungal strains Seeds of seven pea cultivars (Santana, Medal, Lasso, Sokolik, Turnia, Ezop, Tarchalska) were tested for fungal occurrence. Each cultivar was sown at two distinct localities in central Poland (Radzików and Wiatrowo) during the 2011 and 2012 seasons.

Additionally, five other cultivars, not sown purely for the purposes of this study, were examined in 2011 (Wiato, Hubal, Wenus, Eureka, Gwarek) and three in 2012 (Milwa, Cysterski, Mentor). Table 1 contains the full list of cultivars tested along with their description (edible or fodder cultivar). Among the cultivars tested, 8 were edible and 7 grown for

Wilman K, et al. PATHOGENIC FUNGI IN PEA SEEDS Arh Hig Rada Toksikol 2014;65:329-338

Table 1 Pea cultivars used for the evaluation of fungal species presence on the seeds harvested in 2011 and 2012 seasons.(+) cultivar tested for fungal occurrence in season, (-) cultivar not tested for fungal occurrence in season

Cultivar Edible SANTANA TARCHALSKA EZOP LASSO MENTOR MEDAL WENUS CYSTERSKI Fodder WIATO SOKOLIK EUREKA GWAREK HUBAL MILWA TURNIA

2011

2012

+ + + + + + -

+ + + + + + +

+ + + + + +

+ + +

fodder. Each cultivar was grown in four replicates and two localities; therefore, the overall number of seeds tested was 400 per cultivar. Plant material was harvested in July of each year of cultivation and samples of 50 seeds from each cultivar in four replicates were grown at two localities were used for evaluating presence of fungi. Seeds were surface disinfected with 0.5 % sodium hypochlorite (Javel, Warsaw, Poland) for 30 s. After surface treatment, the plant material was rinsed three times with sterile water.

The seeds were placed on a single layer of watersoaked, sterile filter paper (Whatman no. 1) in Petri dishes, which were incubated for 7 days at 20-25 °C and checked by observation of fungal presence every day. Mycelia from seeds with visible fungal growth were transferred to new plates with potato dextrose agar (PDA) medium (Oxoid, Wesel, Germany).

Morphological identification The purified isolates were cultured for 7 days on the synthetic nutrient agar (SNA) medium (glucose, sucrose, potassium dihydrogen phosphate, potassium nitrate, magnesium sulfate anhydrous, potassium chloride from Sigma-Aldrich, Steinheim, Germany; agar from Oxoid, Wesel, Germany). Subsequently, the strains were identified according to their morphological characteristics, structure of hyphaae,

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Wilman K, et al. PATHOGENIC FUNGI IN PEA SEEDS Arh Hig Rada Toksikol 2014;65:329-338

phialides and conidia (13). An optical microscope (Olympus, Tokyo, Japan), set at 200x of total magnification was used for genus identification of fungal isolates.

Molecular analyses Mycelia for DNA extraction were scraped from 7-day-old PDA cultures of individual isolates.

Isolation of total DNA was done using a Cetyltrimethyl Ammonium Bromide (CTAB method) (14). Fungal material was incubated at 65 °C for 20 min in 800 µL CTAB buffer (Sigma-Aldrich, Steinheim, Germany), 0.4 % β-merkaptoethanol (Sigma-Aldrich, Steinheim, Germany) and 150 µL chloroform/isoamyl alcohol (24:1/volumes mix, Sigma-Aldrich, Steinheim, Germany). Then the tubes were incubated at room temperature for 10 min. After incubation and addition of 150 µL of chloroform/isoamyl mixture, the samples were mixed and centrifuged at 12,000 rpm (equivalent to 15.294 x g) for 15 min. In the next step, the aqueous phase was transferred to new tubes and 60 µL of 3 mol L-1 sodium acetate were added. For the DNA precipitation, two volumes of 96 % cold solution of ethanol were used. The tubes were then left at -20 °C for 20 min. The samples were centrifuged at 12,000 rpm for 20 min and the pellet was dissolved in 150 µL TE buffer (10 mmol L-1 Tris-HCl, 1 mmol L-1 EDTA from Sigma-Aldrich, Steinheim, Germany). Molecular identification of isolates was performed based on partial sequences of the translation elongation factor tef-1α and ITS1-ITS2 region of the rDNA gene cluster.

P r i m e r p a i r s E f 7 2 8 M ( C AT C G A G A A GTTCGAGAAGG)/Tef1R (GCCATCCTTGGA GATACCAGC) and ITS4 (TCCTCCGCTTA TTGATATGC)/ITS5 (GGAAGTAAAAG TCGTAAC AAGG), validated in previous studies (15, 16), were used for the tef-1α gene fragment and the ITS region amplification.

The polymerase chain reaction was done in 20 μL reaction mixture containing 1 unit of Phire II HotStart Taq DNA polymerase (Thermo Scientific, Espoo, Finland), 4 μL of 5× PCR buffer, 12.5 pmol L-1 of forward/reverse primers, 2.5 mmol L-1 of each dNTP and 1 μL 50 ng of fungal DNA. The amplification conditions were as follows: initial denaturation 30 s at 98 °C, 35 cycles of 10 s at 98 °C, 5 s at 58 °C (for the ITS region) or 63 °C (for the tef-1α fragment), 15 s at 72 °C with a final elongation of 1 min at 72 °C. Amplification products were electrophoresed in 1.5 % agarose gels (Invitrogen, Carlsbad, CA, USA)

in 1×TBE buffer (0.178 mol L -1 Tris-borate, 0.178 mol L-1 boric acid, 0.004 mol L-1 EDTA from Sigma-Aldrich, Steinheim, Germany) containing ethidium bromide.

For sequence reading, the PCR products were purified and sequenced according to the previously described protocol (17). Sequences were edited using Chromas v. 1.43 (Technelysium, Tewantin, Australia) and analysed using BLASTn algorhitm (18).

Weather conditions Temperature and total rainfall were obtained at WeatherOnline Poland (19). The weather conditions were monitored for two localities in Poland (Radzików and Wiatrowo). The average monthly temperature and rainfall were recorded from April to July in 2011 and 2012.

Statistical analyses An infection degree (frequency of infected seeds) was estimated for each sample. This average number of infected seeds for each cultivar was calculated taking into account four replicates of each pea cultivar, which enabled us to determine the exact degree of fungal infection in the pea seeds.

Chi-square test (20) was used to exclude the differences between the infection levels of the same cultivar at two distinct localities. Due to the differences in weather conditions within the two years as well as in the susceptibility of the cultivars, the analysis was conducted separately for each cultivar in 2011 and 2012.

The test resulted in the equation: k

(O j − E j ) 2

j =1

Ej

χ =∑ 2

Oj – number of infected seeds, Ej – expected number of infected seeds.

The critical value was read from the Chi-Square Distribution Table for degrees of freedom df=2, and α=0.01.

RESULTS The percentage of seed material contaminated with fungal pathogens was different for individual cultivars (Figure 1). Edible cultivars (e.g., Ezop, Santana, Cysterski) displayed a higher contamination level than fodder cultivars (e.g., Sokolik, Turnia, Wiato). Fungal

332 infection of cultivars Hubal, Gwarek, Sokolik, and Wiato was very low in 2011 (Figure 1A). The seeds of cv. Wiato from Radzików were free from detectable fungi. Three of the edible pea cultivars (Santana, Tarchalska, and Ezop) displayed a considerably high infection degree, nevertheless, the highest percentage (55 %) of cv. Ezop infection was noted in Wiatrowo.

The infection degree of cv. Santana was higher in 2012 compared to 2011(Figure 1B). Seed contamination of cv. Tarchalska was similar to that recorded in the previous year (reaching 30 % of seeds contaminated with fungi). A high degree of contamination was also found for the seeds of cultivars Medal, Cysterski, Mentor, Lasso (about 40 % at both localities), and Ezop (Wiatrowo). Seeds of cv.

Sokolik were not infected in any of the two distinct regions and the seed material of cv. Turnia in Radzików was also not contaminated (Figure 1B).

Alternaria spp. were the most commonly isolated fungal species among all of the isolates obtained in 2011 (90 % of fungal isolates, Table 3). Turnia and Ezop cultivars were infected by Fusarium species at both localities. Ezop from Wiatrowo was the most contaminated cultivar (110 fungi were found, including 19 % belonging to the Fusarium genus).

Fusarium species were also detected on seeds of other genotypes. In Wiatrowo, these included cvs.

Wilman K, et al. PATHOGENIC FUNGI IN PEA SEEDS Arh Hig Rada Toksikol 2014;65:329-338

Wiato, Sokolik, and Tarchalska, and in Radzików cv. Eureka. Using molecular techniques, three Fusarium species were identified: F. verticillioides (Sacc.) Nirenberg, F. proliferatum (Matsush.)

Nirenberg, and F. poae (Peck) Wollenw. Stemphylium sp., Ulocladium sp., and Botrytis cinerea Pers. were isolated from the seeds only in a smaller number of occasions (2 %, Table 3).

Similarly, in the 2012 season Alternaria sp. were the most common fungi isolated from pea seeds.

Their frequency was about 94 %, regardless of the cultivar or locality. The average frequency of samples containing Fusarium spp. was 3.2 % and the identified species included F. avenaceum, F. proliferatum, F. equiseti (Corda) Sacc., and F. poae.

Fusarium-infected cultivars were genotypes Santana, Medal, Turnia, Tarchalska, Milwa, and Cysterski from Wiatrowo and Mentor from Radzików. Other fungal strains were represented by Stemphylium spp., Ulocladium spp., Epicoccum nigrum Link., and Phoma pinodella (Table 2).

The average air temperatures for April-July of 2011 and 2012 at the two localities did not differ significantly (Figure 2). Moreover, the amounts of rainfall were also similar. High rainfalls were reported only in July 2011.

Figure 1A Level of fungal contamination [in % of contaminated seeds] of the seed material of pea cultivars grown in Radzików and Wiatrowo in 2011. (E) edible cultivars used in human diet, (F) fodder cultivars for feed production. First seven cultivars have been tested in 2011 and 2012 seasons

333

Wilman K, et al. PATHOGENIC FUNGI IN PEA SEEDS Arh Hig Rada Toksikol 2014;65:329-338

Figure 1B Level of fungal contamination [in % of contaminated seeds] of the seed material of pea cultivars grown in Radzików and Wiatrowo in 2012. (E) edible cultivars used in human diet, (F) fodder cultivars for feed production. First seven cultivars have been tested in 2011 and 2012 seasons

Table 2A Results of chi-square test for seeds harvested in 2011.Critical value is equal to 9.21034 for the degrees of freedom df=2, and α=0.01 (data from Chi-Square Distribution Table). Low value χ2 excludes the differences between the seeds infection level dependent on the localities

Cultivar

Number of infected seeds in Radzików

Expected number of infected seeds in Radzików

WIATO

0

3

6

3

6.100

HUBAL

1

1.5

2

1.5

0.342

WENUS

22

23.5

25

23.5

0.194

EUREKA

8

8.5

9

8.5

0.062

GWAREK

3

3.5

4

3.5

0.144

SANTANA

62

58.5

55

58.5

0.592

MEDAL

43

33

23

33

0.592

LASSO

7

28.5

50

28.5

37.828 *

SOKOLIK

9

8

7

8

0.260

TURNIA

19

19.5

20

19.5

0.028

EZOP

50

79

108

79

70.363 *

45

44.5

44

44.5

0.016

TARCHALSKA

*value χ > critical value (9.21034), statistically significant result 2

Number of Expected number infected seeds of infected seeds in in Wiatrowo Wiatrowo

χ2

334

Wilman K, et al. PATHOGENIC FUNGI IN PEA SEEDS Arh Hig Rada Toksikol 2014;65:329-338

Table 2B Results of chi-square test for seeds harvested in 2012.Critical value is equal to 9.21034 for the degrees of freedom df=2, and α=0.01 (data from Chi-Square Distribution Table). Low value χ2 excludes the differences between the seeds infection level dependent on the localities

Cultivar

Number of Expected number infected seeds in of infected seeds Radzików in Radzików

Number of infected seeds in Wiatrowo

Expected number of infected seeds in Wiatrowo

χ2

SANTANA

22

22.6

81

82.4

0.203

MEDAL

14

16.8

70

67.2

0.879

LASSO

12

12.2

49

48.8

0.005

SOKOLIK

0

0

0

0

0.000

TURNIA

9

3.4

8

13.6

12.371 *

EZOP

7

10.4

45

41.6

1.755

TARCHALSKA

14

13.4

53

53.6

0.046

MILWA

4

6

26

24

0.948

CYSTERSKI

11

16.4

71

65.6

3.308

67

61.6

3.487

MENTOR 10 15.4 2 *value χ > critical value (9.21034), statistically significant result

DISCUSSION Legume crops, including field pea, are frequently colonized by pathogenic or endophytic fungi (21). The overall frequency of fungal isolate detection in pea seeds of different cultivars was calculated in order to evaluate the degree of infection. A decreased level of pea infestation was observed for fodder cultivars. However, increased infestations were observed in the case of edible cultivars (Figures 1A, 1B), which corresponds to Marcinkowska (22), who concluded that edible cultivars, due to the influence of weather, are more susceptible to infection by pathogens. In a study by Embaby et al. (23), an increase of the infestation degree was observed with high moisture content in the seed samples. In the present study, seed samples were collected after the very rainy season of 2011 (Figure 2) and their high fungal infection was likely the result of high moisture content during the formation of pods.

However, it seems that water availability after that stage did not have such a strong impact. High rainfalls in July 2011 did not result in higher seed contamination, while in 2012 higher precipitation in May and June resulted in an overall increase of fungal contamination (Figures 1 and 2). Weather conditions play the most significant role and dramatically affect fungal growth and mycotoxin biosynthesis (24). Water availability and temperature at specific plant growth stage are particularly crucial for disease development and severity. Woudenberg et al. (25) indicated that fungi can infect different parts of a plant at various

growth stages. Nevertheless, the major factors causing plant contamination with pathogens are local and temporary weather conditions that affect the development of fungal infection (26).

The influence of precipitation on fungal incidence is particularly well visible for Radzików in 2011, where it was considerably rainier than in Wiatrowo. The overall contamination of cultivars was higher, as well (Figures 1 and 2).

F. proliferatum and F. verticillioides colonise a wide range of hosts, but they are primarily known as maize pathogens (27, 28). However, Ivić et al.

(29) managed to isolate F. proliferatum and F. verticillioides from pea.

In the present study, F. proliferatum was predominantly isolated from seeds of cultivar Turnia, whereas F. verticillioides was found in seeds of cultivar Ezop - both harvested in 2011 (Table 3).

The observed presence of Fusarium spp. in the analysed pea seeds suggests the possibility of contamination with mycotoxins, as both F. proliferatum and F. verticillioides have the ability to produce fumonisins. Fumonisin biosynthesis is determined by the activity of the FUM gene cluster comprising of 17 FUM genes (30, 31) and numerous studies have shown that the sequence analysis of FUM1 gene may be successfully used to identify Fusarium strains (32-35). An analysis of the genetic divergences of this particular gene among the peaderived strains and the strains originating from different host species has shown a higher level of similarity between the strains of F. proliferatum

335

Wilman K, et al. PATHOGENIC FUNGI IN PEA SEEDS Arh Hig Rada Toksikol 2014;65:329-338

Figure 2 Mean monthly temperatures and rainfall for two localities studied in April-July period in 2011 and 2012 seasons

isolated from the same plant host (33, 35). Moreover, analysis of FUM1 sequence can be used to evaluate the contamination with fumonisins; however, significant intraspecific differences in mycotoxigenic abilities have been reported (33). Though mycotoxin analyses were not planned for this study, they definitely would contribute to knowledge in the field (some analyses have already been performed and more extensive research is planned on this material). In fact, significant amounts of fumonisins have been found in the seeds of cultivars Eureka and Turnia (35). Taking our results into account, it can be concluded that some pea-originating Fusarium strains can be regarded as Table 3 Number of isolates of different fungal species isolated from total number of 200 seeds of each cultivar grown in two distinct localities in Poland (W-Wiatrowo, R-Radzików) in 2011 and 2012 seasons

Fungal species

2011

2012

W

R

W

R

Alternaria spp.

304

270

440

91

Botrytis cinerea

2

-

-

-

-

-

2

-

Fusarium spp.* Phoma medicaginis var. pinodella Stemphylium spp.

38

12

15

3

-

-

3

-

2

-

3

-

Ulocladium spp.

7

1

7

-

Total number of isolates

353

283

470

94

Epicoccum nigrum

*In the Fusarium genus F. avenaceum, F. equiseti, F. poae, F. verticillioides and F. proliferatum were identified

specific for the host, although results have also shown that susceptibility of individual pea cultivars to pathogenic fungi vary.

Fusarium avenaceum is the major agent causing rot in pea roots (36). The prevalence of this species in pea seeds was high in 2012 (Table 3). Moreover, the domination of this pathogen in field pea has already been reported in earlier studies (37). Compared to 2011, it can be suggested that the presence of F. avenaceum was related to weather conditions (especially to the air temperature of about 25-30 °C).

The emergence of F. avenaceum on pea seeds could have also been related to the rotation of crop species, due to a wide range of hosts potentially infected by this fungus, which would indicate a lack of hostspecificity among the strains of this species (38, 39).

Sørensen et al. (40) described naturally occurring F. avenaceum isolates collected from apples that were able to produce enniatins. These cytotoxic compounds may pose a risk to consumer health in cases other than just those involving apples. The fact that F. avenaceum had the highest frequency in cultivars from Wiatrowo indicated a possibility of the presence of enniatins in pea tissues. In our study, four out of five F. avenaceuminfected cultivars were edible peas: Tarchalska, Santana, Medal and Cysterski, while only one strain was isolated from the fodder cultivar Turnia. The results obtained are in good accordance with earlier observations stating that edible cultivars are more susceptible to fungal infections (22).

336 The ability to synthesise mycotoxins is perhaps the most important threat arising from plantpathogenic fungi. Certain reports have stated the specific profile of toxic secondary metabolites produced by individual fungal strains (16, 23). In the present study, it would be extremely difficult to perform mycotoxin analyses for all of the isolates.

The identification and quantification of this mycotoxin group in collected pea plant material has been planned for future research. However, for some of the pathogens identified, the ability to produce specific mycotoxins (e.g., moniliformin and enniatins for F. avenaceum and fumonisins for F. proliferatum and F. verticillioides) is well-studied and proven for virtually all strains isolated from plant species (17, 33, 34). As for seed material, some of the samples were tested for the presence of mycotoxins. The measured levels, however, were extremely low; therefore, the results were not given.

A few isolates of Phoma medicaginis var. pinodella were found on the tested pea seeds.

Davidson et al. (41) described the symptoms in pea seedlings caused by Phoma sp. and indicated that this fungus might be a seed-borne pathogen.

However, in our experiments the pathogen was not commonly present in seed material. The most likely explanation of the low level of seed infection was probably related to the accumulation of reactive oxygen species (ROS) in plant tissues. The increase of ROS in aging pea seeds was observed in a study

by Yao et al. (42) and higher ROS levels may have resulted in the inhibition of fungal growth (43).

In conclusion, the results obtained in the present study clearly show different levels of susceptibility to fungal infestations presented by pea cultivars grown in Poland. They also serve as a source of information on mycotoxins possibly present in seed material. Our future research will focus mainly on investigating the content of mycotoxins specific for individual fungal species in pea cultivar seed material. Such an approach could contribute to general knowledge in the area of common plant pathogens in agricultural environments of central Europe.

Acknowledgements This study was supported by Project no. RM 111138-11 (decision of the Polish Council of Ministers 149/2011) “Improvement of national plant protein sources, their production, trading system and use in animal feeding, WP 2.7: Identification of pathogenic

Wilman K, et al. PATHOGENIC FUNGI IN PEA SEEDS Arh Hig Rada Toksikol 2014;65:329-338

fungi present on leguminous plant seeds and analysis of their toxic and anti-nutritional metabolites” Conflict of interest Authors declare no conflict of interest.

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338

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Sažetak Patogene plijesni u sjemenkama različitih sorti graška u Poljskoj Mahunasti usjevi izloženi su infekcijama patogenih plijesni, što često rezultira zarazom mikotoksinima.

Cilj ovoga istraživanja bio je procijeniti stupanj otpornosti/podložnosti jestivih sorti graška i onih koji se koriste za krmivo na kolonizaciju sjemenki patogenim plijesnima tijekom dviju sezona te identificirati patogene u sjemenkama istraživanih sorti. Najčešća plijesan izdvojena iz sjemenki tijekom obiju sezona bila je Alternaria spp., a nju su brojnošću pratile Fusarium spp., Stemphylium spp., Ulocladium spp., Botrytis cinerea Pers., Epicoccum nigrum Link. i Phoma pinodella L. K. Jones. Najviši postotak zaraženih sjemenki (55 %) zabilježen je za sortu Ezop. Prisutnost većeg broja plijesni pronađen je 2012. u sortama Santana, Tarchalska, Medal, Cysterski, Mentor, Lasso i Ezop. Sorte korištene za krmivo pokazale su općenito nižu razinu zaraženosti od jestivih. Možemo zaključiti kako je Alternaria spp. bila najčešća plijesan u sjemenkama graška u Poljskoj, a Fusarium spp. vjerojatno najopasnija, uzimajući u obzir njene ustanovljene mikotoksigenične sposobnosti.

KLJUČNE RIJEČI: Alternaria; bolesti prenosive sjemenkama; Fusarium; molekularna identifikacija; mikotoksini; patogeni sjemenki

CORRESPONDING AUTHOR: Łukasz Stępień Department of Pathogen Genetics and Plant Resistance Institute of Plant Genetics, Polish Academy of Sciences ul. Strzeszyńska 34, 60-479 Poznań, Poland E-mail: lste@igr.poznan.pl

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Maqbool F et al. MERCURY IN DENTAL AMALGAMS Arh Hig Rada Toksikol 2014:65:339-340

DOI: 10.2478/10004-1254-65-2014-2543

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Exposure to mercury from dental amalgams: a threat to society Faheem Maqbool, Haji Bahadar, and Mohammad Abdollahi Pharmaceutical Sciences Research Center, and Faculty of Pharmacy, Tehran University of Medical Sciences, International Campus, Tehran, Iran

The intention of this article is to call the reader’s attention to the underestimated, yet very serious issue of chronic exposure to elemental mercury from dental amalgams.

Dental amalgam is an alloy used for tooth fillings that contains about 50 % of elemental mercury and has been used in hundreds of millions of patients for the last 160 years throughout the world (1). According to the 2001-2004 statistics, 181.1 million people in the US have 1.46 billion restored teeth, mostly with dental amalgam (2). As its use continues in dentistry, it is quite likely that the rate of exposure to mercury keeps increasing. Additionally, mercury is used as a preservative or antiseptic in pharmaceutical and cosmetic products and is present in the human food chain, especially in fish.

With each chewing and brushing of the teeth, dental amalgam releases low levels of elemental mercury, but due to its properties it goes undetected by the exposed person. It is generally considered safe for adults and children above six years of age by regulatory bodies such as the US Food and Drug Administration (US FDA). However, more and more evidence suggests that mercury-containing dental materials could be a source of chronic exposure to mercury (3). It is estimated that 30 µg of mercury particles per cm2 of dental amalgam is released every day (4). The risk of exposure is greater in persons having more than one filling, and mercury toxicity is greater than that of lead. According to the World Health Organization (WHO) (5) no level of mercury exposure can be considered harmless. Furthermore, the WHO believes that dental amalgam accounts for 84 % of daily exposure to mercury.

Mercury release from dental amalgam has become a major risk factor for a number of diseases. It has been evidenced to produce neurological and renal impairments (6-8). It binds to the sulphhydryl groups of enzymes and may have toxic effects on the cardiovascular, gastrointestinal, respiratory, and reproductive system (7, 9). Epidemiological studies also suggest that mercury from amalgams may be harmful for humans and responsible for several chronic diseases (10). A cohort study in Swedish women established a link between mercury release and myocardial infarction, stroke, diabetes, and cancer (11). A study in humans conducted by SandborughEnglund et al. (12) found high mercury concentrations in biological fluids such as plasma, blood, and urine of a population with dental amalgams.

Harmful effects of mercury from dental amalgams are in fact unavoidable. Its release is enhanced by chewing, brushing, and changes in the pH of saliva (13). In a study by Pizzichini et al. (14) mercury in the saliva lowered total antioxidant activity (TAA) and caused a number of diseases. A number of studies have proved that mercury released from dental amalgam reacts with many other metals to yield different bonds that generate reactive oxygen species and increase oxidative stress (14-16).

The effects of mercury after release from dental amalgam or other sources may affect human life very badly (17), and every action is called for to minimize human exposure (18).

Unfortunately, in general medical practice, no physician seeks to rule out mercury poisoning when they are trying to establish the cause of a chronic disease or other diagnosis. This is of course the case

340 with many environmental toxic substances that humans may be exposed to in concentrations high enough to cause chronic illnesses. The WHO has seriously taken the issue of monitoring mercury toxicity and has set a goal for mercury-free healthcare by the year 2020 (19). This is why we believe that the issue of mercury use in dental amalgam should not be underestimated. We hope that future epidemiological and evidence-based studies will convince health professionals about the role of mercury in causing human chronic diseases and health decision-makers to take appropriate action to replace mercurycontaining amalgams with non-toxic compounds.

Therefore, we hope that research shall take this direction as soon as possible.

REFERENCES 1. Lorscheider FL, Vimy MJ, Summers AO. Mercury exposure from “silver” tooth fillings: emerging evidence questions a traditional dental paradigm. FASEB J 1995 ;9: 504-8.

2. Richardson G, Wilson R, Allard D, Purtill C, Douma S, Gravière J. Mercury exposure and risks from dental amalgam in the US population, post-2000. Sci Total Environ 2011;409:4257-68. doi: 10.1016/j.scitotenv.2011.06.035 3. Vimy MJ, Lorscheider FL. Intra-oral air mercury released from dental amalgam. J Dent Res 1985;64:1069-71. PMID: 3860538 4. Brune D, Evje DM. Man’s mercuy loading from a dental amalgam. Sci Total Environ 1985;44:51-63. PMID: 4023695 5. Grandjean P, Weihe P, White RF, Debes F. Cognitive performance of children prenatally exposed to “safe” levels of methylmercury. Environ Research 1998;77:165-72.

6. Counter SA, Buchanan LH. Mercury exposure in children: a review. Toxicol Appl Pharmacol 2004;198:209-30. PMID: 15236954 7. Nylander M, Friberg L, Lind B. Mercury concentrations in the human brain and kidneys in relation to exposure from dental amalgam fillings. Swed Dent J 1987;11:179-87.

PMID: 3481133 8. Barregård L, Svalander C, Schütz A, Westberg G, Sällsten G, Blohmé I, Mölne J, Attman PO, Haglind P. Cadmium, mercury, and lead in kidney cortex of the general swedish population: a study of biopsies from living kidney donors.

Environ Health Perspect 1999;107:867-71. PMID: 10544153 9. Houston MC. Role of mercury toxicity in hypertension, cardiovascular disease, and stroke. J Clin Hypertens 2011; 13:621-7. doi: 10.1111/j.1751-7176.2011.00489.x 10. Mackert J, Berglund A. Mercury exposure from dental amalgam fillings: absorbed dose and the potential for adverse health effects. Crit Rev Oral Biol Med 1997;8:410-36. doi: 10.1177/10454411970080040401 11. Ahlqwist M, Bengtsson C, Lapidus L. Number of amalgam fillings in relation to cardiovascular disease, diabetes, cancer and early death in Swedish women. Community Dent Oral Epidemiol 1993;21:40-4. doi: 10.1111/j.1600-0528.1993. tb00717.x

Maqbool F et al. MERCURY IN DENTAL AMALGAMS Arh Hig Rada Toksikol 2014:65:339-340

12. Sandborgh-Englund G, Elinder C-G, Langworth S, Schütz A, Ekstrand J. Mercury in biological fluids after amalgam removal. J Dent Res 1998;77:615-24. doi: 10.1177/00220345980770041501 13. Brune D, Evje DM. Man’s mercury loading from a dental amalgam. Sci Total Environ 1985;44:51-63. PMID: 4023695 14. Pizzichini M, Fonzi M, Sugherini L, Fonzi L, Gasparoni A, Comporti M, Pompella A. Release of mercury from dental amalgam and its influence on salivary antioxidant activity.

Sci Total Environ 2002;284:19-25. PMID: 11846163 15. Stohs S, Bagchi D. Oxidative mechanisms in the toxicity of metal ions. Free Radic Biol Med 1995;18:321-36. PMID: 7744317 16. Messer RL, Lockwood PE, Tseng WY, Edwards K, Shaw M, Caughman GB, et al. Mercury (II) alters mitochondrial activity of monocytes at sublethal doses via oxidative stress mechanisms. J Biomed Mater Res B Appl Biomater 2005;75: 257-63.

17. Mostafalou S, Abdollahi M. Environmental pollution by mercury and related health concerns: renotice of a silent threat. Arh Hig Rada Toksikol 2013;64:179-81. doi: 10.2478/10004-1254-64-2013-2325 18. Sowlat MH, Abdollahi M, Gharibi H, Yunesian M, Rastkari N. Removal of vapor-phase elemental mercury from stack emissions with sulfur-impregnated activated carbon. Rev Environ Contam Toxicol 2014;230:1-34. doi: 10.1007/9783-319-04411-8_1 19. WHO. WHO calls for the phase out of mercury fever thermometers and blood pressure measuring devices by 2020 [displayed 29 July 2014]. Available at: http://www.who.int/ mediacentre/news/notes/2013/mercury-medicaldevices-20131011/en/

CORRESPONDING AUTHOR: Mohammad Abdollahi Division of Toxicology, Department of Toxicology and Pharmacology Faculty of Pharmacy and Pharmaceutical Sciences Research Center Tehran University of Medical Science Tehran 1417614411, Iran E-mail: Mohammad@TUMS.Ac.Ir

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Medicinsko vještačenje pravične novčane naknade po prijedlogu medicinskih tablica iz 2013. godine Anton Marović1, Siniša Štimac2 Klinički bolnički centar Split, Klinika za neurologiju1, Odvjetnički ured Siniša Štimac2, Split, Hrvatska

U postupcima naknade nematerijalne / neimovinske štete u Republici se Hrvatskoj primjenjuju nacionalni orijentacijski medicinski kriteriji iz 1996. (1), koji su 2008. dopunjeni psihijatrijskim kriterijima (2), a namijenjeni su svim sudionicima – i pravne i medicinske struke – u postupcima naknade neimovinske štete. Jednostavni su, jasni i laki u primjeni svim sudionicima u postupku (sucima, odvjetnicima, vještacima, strankama), što je najveća njihova prednost. Podobni su za vještačenje primjenom Zakona o obveznim odnosima (ZOO) iz 1991. (3-7) i ZOO-a iz 2005. (8, 9), pogotovo drugog, koji teži poboljšanju položaja oštećenika, afirmirajući pravo osobnosti iz Ustava Republike Hrvatske i Europske konvencije o zaštiti ljudskih prava i temeljnih sloboda, na kojima se izgradila dosadašnja usklađena sudska praksa. Godine 2013. skupina autora izradila je nove tablice (10) koje krajnje restriktivno tumače ZOO iz 2005. Cilj je da budu obvezujuće ne samo u postupcima naknade neimovinske štete nego i u drugim područjima, bez konzultiranja šire i stručne i društvene javnosti.

To znači da dovode ne samo oštećenika u bitno pogoršan položaj u odnosu na prijašnje stanje nego i do drastičnog pada procjena trajnih posljedica i, sljedno tome, do drastičnog pada novčanih naknada.

U ovom članku autori iznose nekoliko primjera iz Orijentacijskih tablica iz 2013. (10) upozoravajući na njihovu restriktivnost i tešku primjenjivost i za specijalizirane sudionike postupka naknade neimovinske štete, medicinske vještake, te na složenost navedenih tablica.

U postupcima naknade nematerijalne / neimovinske štete isprepletena je pravna i medicinska problematika.

Medicinski dio te problematike odnosi se na medicinsko vještačenje. Naime, kod ozljeda i

posljedica, a posebno smanjenja životne aktivnosti, nužna je procjena medicinskog vještaka, i o toj procjeni ovisi visina dosuđene svote nematerijalne / neimovinske štete. Samo se na temelju pravičnog i objektivnog vještačenja može dosuditi pravična novčana naknada koja je zakonski uvjet u obeštećenju oštećenika (čl. 200., st. 1. Zakona o obveznim odnosima iz 1991. (3-7) i čl. 1100., st. 1. Zakona o obveznim odnosima iz 2005. (8, 9). Upravo radi ujednačavanja sudske prakse kako bi se donijela pravična ocjena na kojoj će se temeljiti sudska odluka, trebaju postojati orijentacijski medicinski kriteriji (11).

Zašto orijentacijski? Upravo zato da bi omogućili medicinskim vještacima holističkim pristupom ocijeniti možebitne trajne posljedice za zdravlje i sveukupno funkcioniranje svakog pojedinca, uz puno uvažavanje njegove jedinstvenosti i osobnosti. Uz to, poželjno je da postoje jedinstvene medicinske orijentacijske tablice upravo radi pravnog dijela odnosno ujednačavanja sudske prakse na čitavom teritoriju Republike Hrvatske, ne u cilju „uranilovke“ nego uvažavanja jednakosti svih građana Republike Hrvatske pred sudom i zakonom i pravičnog suđenja u smislu čl. 14. i čl. 29. Ustava Republike Hrvatske (12) i čl.6. Europske konvencije o pravu na pravično suđenje (13-16).

Sud donosi presudu na temelju sveukupne dokumentacije u spisu. U pravilu, sud poziva medicinskog vještaka radi procjene ozljeda i njihovih posljedica (uključujući i psihičke). Jasno je da su tu potrebni neobvezujući orijentacijski medicinski kriteriji da bi vještak donio objektivnu i nepristranu procjenu. Tako je procjena sudskih vještaka temelj za dosudu svote naknade uz primjenu Orijentacijskih kriterija i iznosa za utvrđivanje visine pravične

342 novčane naknade nematerijalne štete Vrhovnog suda Republike Hrvatske (VSRH) od 29.11.2002. (pravnih kriterija) (17). Tim su kriterijima, u rasponima postotaka, određene novčane vrijednosti koje se dosuđuju (tako npr. do 25 % smanjenja životne aktivnosti (SŽA) dosuđuje se 7500 kn na svakih 10 %, od 60 do 80 % dosuđuje se 45 000 kn, a od 80 do 100 % SŽA 75 000 kn za svakih 10 %. Prilikom procjene i određivanja postotka SŽA za koji se vezuju navedene svote sudski vještak primjenjuje orijentacijske medicinske kriterije (18, 19). U sudskoj su praksi u Republici Hrvatskoj općeprihvaćeni i primjenjuju se orijentacijski medicinski kriteriji iz 1996. (20, 21).

Tijekom medicinskog vještačenja potrebno je uzeti u obzir i jedne i druge kriterije (pravne i medicinske) jer su međusobno povezani i uvjetovani. Na temelju navedenih medicinskih i pravnih kriterija uspostavljena je uhodana dugogodišnja sudska praksa. Dakle, svaka izmjena dosadašnjih medicinskih kriterija utječe i na primjenu (izmjenu) i pravnih kriterija, pri čemu ponajprije treba voditi računa jesu li te promjene na korist ili na štetu oštećenika kao najslabije karike u postupku.

Skupina stručnjaka iz raznih područja izradila je Orijentacijske medicinske tablice za procjenu smanjenja životne aktivnosti (10), koje su prihvaćene 16. srpnja 2013. odlukom Upravnog odbora Hrvatskoga društva za medicinska vještačenja Hrvatskoga liječničkog zbora i članova Upravnog odbora medicinske sekcije Hrvatskoga društva sudskih vještaka te ponuđene medicinskoj i pravnoj struci.

Autori su u uvodnom dijelu istaknuli razloge za njihovo donošenje. Prema njihovim riječima, to su prve tablice za procjenu smanjenja životne aktivnosti koje su sastavili kliničari i nisu nastale pod pritiskom odvjetnika ni osiguravateljnih društava. Izrađene su iz potrebe za ujednačavanjem medicinskog vještačenja na čitavom području Republike Hrvatske i za usklađivanjem s Europskim indikativnim tablicama i europskom praksom procjene smanjenja životne aktivnosti. Iz toga proizlazi da je usklađivanje financijskih odšteta za nematerijalne / neimovinske štete u Hrvatskoj s odštetama u drugim zemljama Europske unije moguće samo onda kada se gubitak određenog organa ili određene funkcije oštećenog organa ili organizma u čitavoj Europskoj uniji jednako procjenjuje, odnosno kada se isto zdravstveno oštećenje u svim zemljama jednako mjeri. Uz to, bitno je da oštećenik nakon pretrpljene tjelesne ozljede ima posljedično ograničenje svakodnevnih životnih

Marović A i Štimac S. NOVČANA NAKNADA ZA MEDICINSKE VJEŠTAKE Arh Hig Rada Toksikol 2014;65:341-346

aktivnosti (radne i opće sposobnosti), da to utječe na kvalitetu njegova života te da su procjene funkcionalnih psihofizičkih posljedica, koje su u Tablici izražene u postotcima, samo orijentir za procjenu smanjenja životne aktivnosti i samo jedan od elemenata za prosudbu neimovinske štete.

Autori ističu da postotke u Tablicama mogu koristiti samo liječnici specijalisti i subspecijalisti zbog mogućnosti tumačenja funkcioniranja organizma mogućim kompenzacijskim mehanizmima koji se mogu aktivirati u određenom trenutku liječenja i rekonvalescencije. Također navode da u zdrave osobe postoji idealna sinergija svih psihičkih i fizičkih funkcija, stoga ima stopostotnu životnu aktivnost. Kad je o oštećenoj osobi riječ, ako ozljeda nije ostavila trajne posljedice na životnu aktivnost (ŽA), ona je i nakon ozljede stopostotna odnosno ne utječe na funkcijske kapacitete organizma; smanjena ŽA do 4 % minimalno utječe na funkcionalne kapacitete organizma, stoga oštećena osoba može bez ulaganja pojačanih napora uredno zadovoljavati sve svoje životne potrebe. Istaknuto je da se smanjenje ŽA od 5 % do 20 % svrstava u lakše posljedice, i u tom će slučaju oštećenik morati uložiti pojačan napor da bi zadovoljio sve svoje životne potrebe.

Govoreći o trajnim posljedicama, autori ocjenjuju da su srednje teške posljedice do 40 % i da u njima organizam može aktivirati kompenzacijske mehanizme i uspostaviti zadovoljavajuću životnu aktivnost; u smanjenoj ŽA do 60 % organizam ni uz kompenzacijske mehanizme nije u mogućnosti uspostaviti zadovoljavajuću ŽA, što znači da je oštećenoj osobi potrebna povremena pomoć. Ako je ŽA smanjena do 80 %, preostala ŽA je tek 20 % i nije dovoljna da se zadovolje sve životne potrebe. Iako je djelomično samozbrinjavanje moguće, nedvojbeno je da je takvoj oštećenoj osobi potrebna svakodnevna pomoć i povremena medicinska njega.

U uvodnom dijelu autori objašnjavanju i neke pravne pojmove, iznoseći svoj stav kako bi se ispravno provodilo medicinsko vještačenje prema Zakonu o obveznim odnosima iz 2005. Također navode da su sudski medicinski vještaci dužni u medicinskom vještačenju svaki postotak temeljito obrazložiti kao podlogu za procjenu preostale životne aktivnosti oštećene osobe.

Temeljno je, što već izvire iz uvodnog dijela, da autori izvode pogrešan zaključak o činjenicama na koje se pozivaju, odnosno o ciljevima koje su htjeli postići.

Marović A i Štimac S. NOVČANA NAKNADA ZA MEDICINSKE VJEŠTAKE Arh Hig Rada Toksikol 2014;65:341-346

To se u prvom redu odnosi na tzv. Europske indikativne tablice (Guide barreme europeen d’ evaluation des atteintes a l’integrite physique et psychique) (22), koje neki autori u Hrvatskoj (pa i autori navedenih Tablica iz 2013. (10) ) nazivaju Europskim indikativnim tablicama (što one i nisu, kako proizlazi iz hrvatskoga prijevoda izvornog naslova na francuskom jeziku). Te tablice ne samo da nisu prihvaćene ni u jednoj državi Europske unije nego ni kao pravna stečevina Europske unije.

Naime, u Europi ne postoji ujednačeni pristup naknadi kod ozljeda i posljedica u postupcima nematerijalne / neimovinske štete. Ne postoji model Europske unije, ne postoji samo jedna metoda, ne postoje jedinstvene medicinske tablice. Svaka zemlja ima svoje nacionalne medicinske kriterije, vodeći se načelom „ujedinjeni u različitosti“, što je slogan Europske unije – United in diversity (23-25). Te tzv.

Europske indikativne tablice rezultat su rada privatne skupine medicinskih vještaka koji za razne urednike pišu svoje tablice. Bitno je da ne postoji zajednička jedinstvena europska metoda procjene ozljeda i njihovih posljedica prilikom utvrđivanja naknade nematerijalne / neimovinske štete. Unatoč tome, jedna skupina medicinskih vještaka, pravnika i predstavnika osigurateljnih kuća inzistira na statutarnim medicinskim tablicama na razini Europske unije, i to su tablice koje kruže Europom. Mora biti jasno da to nisu europske medicinske tablice i da ih je sastavila skupina ljudi koja je svoje djelo nazvala europskim.

Te su tablice (prijedlog tablica) objavljene bez prethodne rasprave i razgovora između male skupine medicinskih vještaka i odvjetnika koji nisu pripadali toj skupini i drugih involviranih u postupcima utvrđivanja naknade neimovinske štete.

Taj su prijedlog kritizirale brojne skupine, među kojima i Paneuropsko udruženje odvjetnika za tjelesna oštećenja (PEOPIL) (17, 26).

Na devetoj stranici uvodnog dijela autori govore da su te tablice podloga za procjenu preostale životne aktivnosti oštećene osobe, čime zapravo pogrešno pristupaju biti pravične novčane naknade za duševne boli zbog smanjenja životne aktivnosti, odnosno povrede prava osobnosti na tjelesno i duševno zdravlje. Naime, prema zakonima o obveznim odnosima iz 1991. (3-7) i iz 2005. (8, 9) i prema dugogodišnjoj sudskoj praksi, upravo je bitno utvrditi u kojem je stupnju smanjena (umanjena ili ograničena) oštećenikova životna aktivnost. Svrha određivanja naknade nematerijalne / neimovinske štete nije utvrditi ono što oštećena osoba može raditi, nego ono što više

343 ne može raditi, što se upravo nadoknađuje institutom pravične novčane naknade.

Ističemo da oštećenici novim tablicama iz 2013.

(10) dolaze u znatno nepovoljniju situaciju nego prije (umnogome su smanjeni postotci procjena smanjenja životne aktivnosti, često uvjetovani drugim oštećenjima i posljedicama).

Proizvoljna je i krajnje restriktivna procjena stupnja smanjenja životne aktivnosti. Tako na primjer autori smanjenje životne aktivnosti od 5 do 20 % ubrajaju u lakše posljedice, kod kojih će oštećenik uz ulaganje pojačanog napora zadovoljiti sve životne potrebe. No u tu se kategoriju svrstava i niz težih ozljeda i njihovih posljedica. Time su vještaci ograničeni u procjeni jer teške ozljede i njihove trajne posljedice, koje znatno utječu na smanjenje životne aktivnosti i kvalitete života, moraju procijeniti u rasponu od 5 do 20 %, odnosno kao lakše posljedice, kod kojih će oštećenik moći obavljati sve što je i prije obavljao, ali ulažući pojačani napor.

Apsurdno je što se pokušava podmetnuti teza o onome što se dalje može činiti, premda je jedna tjelesna funkcija ili dio tijela izgubljen. U postupcima pravične novčane naknade nematerijalne / neimovinske štete nadoknađuje se ono što je izgubljeno, a ne honorira se ono što nije izgubljeno. Primjerice, u SŽA od 5 % do 20 % ubraja se sljedeće: potpuno ukočenje zglobova ručnog palca u nepovoljnom položaju (uvodi se i razlikovanje dominantne i nedominantne strane tijela), što iznosi 18 % odnosno 15 %. Mogu li autori objasniti kako i koliko pojačanog napora mora uložiti klavirist ili neurokirurg da bi postigao svoj prijašnji opći radni kapacitet odnosno životnu aktivnost?

U navedenim se tablicama (str. 35.–36.) amputacija svih nožnih prstiju procjenjuje s 13 %, amputacija palca i prve kosti metatarzusa 15 %, amputacija palca 10 %, a amputacija 2. do 5. prsta 3 % – i karakteriziraju se kao lakše posljedice. Jasno je da s takvim ozljedama i posljedicama dosadašnju životnu aktivnost ne mogu obavljati profesionalni i amaterski boksači, sportaši, pomorci i osobe ostalih brojnih zanimanja gdje su potrebna fizička naprezanja. To najbolje znaju osobe koje su prošle procjenu radne sposobnosti (npr. u medicini rada). Napominjemo da znamo kako procjena radne sposobnosti i procjena smanjenja životne aktivnosti nisu jedno te isto (27). Bitno je da sve navedene posljedice izazivaju duševne boli zbog smanjenja životne aktivnosti odnosno povredu prava osobnosti na tjelesno i duševno zdravlje, ne ulazeći u profesionalnu i radnu sposobnost koje su sastavni dio smanjenja životne aktivnosti.

344 Jasna je tendencija umanjenja procjena posljedica ozljeda središnjeg živčanog sustava, pa se izdvajaju posljedice traumatskih ozljeda glave i mozga nabrajanjem morfoloških posljedica, uz ubacivanje u njih postkomocijskog sindroma i tek ponovo kao točka 5. (iste glave) navode kognitivne smetnje (opet s tendencijom minoriziranja), i kao dio njih, epilepsije (koje nisu posebno istaknute). Tu se svrstavaju (ponavljamo: 5–20 % autori smatraju da je lakša posljedica) različiti oblici epilepsije, a autori ne uzimaju u obzir da sama dijagnoza epilepsije znači diskvalifikaciju iz mnogih područja svakodnevnog života (vožnja automobila, razna zanimanja, aktivnosti). Mogu li autori odgovoriti smije li „lakše ozlijeđeni“ pilot s 5.5.1. (komunikacijske smetnje u razumijevanju govora) i sa 6.6.2.1 (jednostavni žarišni epilepsijski napadaji) voziti putnički zrakoplov, a ako smije, uz kakvo to ulaganje pojačanog napora (automatskog pilota ili nečeg drugog). Nameće se pitanje može li doista ozljeda koja čovjeka dovodi u neposrednu životnu ugrozu, koja zahtijeva medicinsku, operativnu obradu, biti definirana kao lakša tjelesna ozljeda odnosno posljedica (28). Tako se, primjerice, na stranici 43. Tablica procjene pod točkom 2.1.1. a) Potpuni gubitak lijevog plućnog krila iznosi 20 % i pod točkom 2.1.2. Gubitak jednog režnja pluća 10 %, bez funkcijskih pulmoloških pretraga, i teške posljedice, svode na lakše posljedice, što dovodi oštećenike u nepovoljniji položaj u odnosu na prijašnje stanje (29). U lakše se posljedice prema Tablicama iz 2013. svrstava i gubitak obaju testisa za osobe starije od 60 godina (procijenjeno s 20 %) ili gubitak jednog testisa (10 %) za osobe mlađe od 60 godina, kao i gubitak jednog testisa (5 %) za osobe starije od 60 godina. I medicinskom je laiku jasna uloga spolnosti u ljudskom životu, u kvaliteti života, uključujući i muškarce s navršenih 60 godina, pa doista nije jasno kako takva osoba može bez obaju testisa obavljati dosadašnju spolnu aktivnost uz pojačani napor.

U Tablicama na stranici 59. navodi se da se tek dvije-tri godine nakon traumatskog događaja može dati zaključna procjena vještačenja, katkada i nakon mnogo više godina. To praktično znači negiranje učinkovitog vođenja parničnog postupka u razumnom vremenu i uvođenje vremenskog ograničenja potraživanja naknade štete, što je u koliziji s dosadašnjom sudskom praksom i pozitivnim propisima gdje se to pravo nigdje ne ograničava. Ne smijemo zaboraviti da spora pravda nije pravda. Ovdje se ne radi o ugovornom osiguranju niti o primjeni tablica koje su stranke ranije ugovorile, nego o izvanugovornoj

Marović A i Štimac S. NOVČANA NAKNADA ZA MEDICINSKE VJEŠTAKE Arh Hig Rada Toksikol 2014;65:341-346

odgovornosti, pa nije potrebno mijenjati dosadašnju uhodanu sudsku praksu (i to na štetu najslabije stranke, oštećenika).

Uveden je i pojam dominantnosti i nedominantnosti strane tijela. Za oštećenika je puno složenije i nepovoljnije određivanje ukupnog smanjenja životne aktivnosti kod istovremenog oštećenja više organa i organskih sustava (Balthazarova formula), s jasnom tendencijom umanjenja kumulativne, ukupne procjene smanjenja životne aktivnosti.

Već smo naveli kako autori jasno navode da postotke u Tablicama mogu koristiti samo liječnici i to specijalisti i subspecijalisti, za razliku od ranijih neobvezujućih orijentacijskih kriterija/tablica koje su mogli koristiti svi sudionici (kako pravne tako i medicinske struke) u postupcima naknade nematerijalne/neimovinske štete.

Mora se primijetiti da se u Tablicama (npr. str. 55.) pogrešno koristi izraz invaliditet. To je pojam ugovornog osiguranja, koji se pogrešno koristi kod izvanugovorne odgovornosti i nespojiv je s naknadnom štete. Stoga se nameće pitanje za čiju su upotrebu rađene te tablice (ugovorno osiguranje...) (30-32).

Utvrđivanjem visine odštete prema određenim rigidnim kriterijima ne uvažava se sva različitost ljudskih osobitosti, što je u suprotnosti s poštivanjem i uvažavanjem individualnih potreba svake osobe. U konačnici, time se ne odražava interes oštećenika i ne jamči pravedna zaštita žrtava (33).

Treba voditi računa o tome da je takvim medicinskim kriterijima upravo stradalnik odnosno oštećenik najslabiji čimbenik u postupcima naknade nematerijalne / neimovinske štete, u kojima bi trebao biti pravično obeštećen, a zapravo je doveden u još neravnopravniji položaj. Pritom ne smijemo zanemariti ni snagu stranaka u postupku, od kojih se najčešće traži obeštećenje i njihov utjecaj na ostale sudionike tog postupka (34).

Zato orijentacijski medicinski kriteriji trebaju biti objektivni, lako shvatljivi, jednostavni za primjenu i razumljivi svim sudionicima u postupku, dakle ne samo vještacima medicinske struke nego i medicinskim laicima (većinom pravne struke). U Tablicama iz 2013. to nije slučaj, jer je izrijekom navedeno da se postotcima u Tablicama mogu koristiti samo liječnici, i to specijalisti i subspecijalisti.

Napominjemo da tijekom izrade Tablica 2013. (10) nije provedena javna rasprava i nije bio uključen veći broj sudionika (što je bilo nužno) ne samo medicinske struke (npr. brojni vještaci koji su članovi spomenutih udruga a nisu bili uključeni u izradu tih tablica i

Marović A i Štimac S. NOVČANA NAKNADA ZA MEDICINSKE VJEŠTAKE Arh Hig Rada Toksikol 2014;65:341-346

vještaci koji nisu članovi tih udruga) nego i nemedicinske struke (pravobranitelj za osobe s invaliditetom, suci, državni odvjetnici, pravnici u gospodarstvu i drugi), pa promjena sudske prakse primjenom TI 2013. na štetu oštećenika doista nije potrebna.

Republika Hrvatska ima usklađene (nacionalne) medicinske kriterije (1, 2) (Barbat 1996., Goreta iz 2008., koji su objedinjeni u Priručniku o medicinskom vještačenju nematerijalne / neimovinske štete po zakonima o obveznim odnosima iz 1991. i 2005. godine, Dalmatina tisak, 2011) (17) i pravne kriterije (VS RH 2002.) u skladu sa zaključcima Hrvatske odvjetničke komore od 28. veljače 2012. Ti kriteriji omogućuju ostvarenje pravične novčane naknade i upravo se na njima razvila uhodana i dugogodišnja sudska praksa.

Navedenim postojećim nacionalnim kriterijima (medicinskim i pravnim) jamči se ostvarenje pravične novčane naknade i postupanje u skladu s europskim pravnim standardima u smislu čl. 29. Ustava Republike Hrvatske, odnosno čl. 6. Europske konvencije o zaštiti ljudskih prva i temeljnih sloboda, čl. 3. Povelje o temeljnim pravima Europske unije (poštivanje tjelesne i duševne cjelovitosti) i Rezolucije Vijeća Europe 75/7 o naknadi za tjelesna oštećenja.

Tako se usklađuje sudska praksa u Republici Hrvatskoj sa sudskom praksom koja se temelji na Europskoj konvenciji suda u Strasbourgu i na sudskoj praksi Europskog suda pravde u Luksemburgu.

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Napomena: stavovi izneseni u članku predstavljaju osobna mišljenja potpisanih autora te stoga nužno ne odražavaju mišljenje i stavove uredništva i/ili izdavača časopisa.

CORRESPONDING AUTHOR:

Dr.sc. Anton Marović, dr. med., spec. neurolog KBC Split Klinika za neurologiju Spinčićeva 1, 21000 Split E-mail: anton.marovic@gmail.com