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Dr. Kumaraswamy

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Dr. Madhu .K.P M.D. (Ay) Dr. Sushrutha . C.K

M.D.(Ay)

Dr. Ashok B.K Dr. Janardhana.V.Hebbar M.D. (Ay) Dr. Shwetha Hari Venkatesh B.A.M.S. Dr. Vidhya Priya Dharshini. K.R. Mr. R. Giridharan Miss. Shyamala Rupavahini

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M.Tech (Bio-tech) M.Sc., M.Phil (Bio-Chem)

Honarary Members - Editorial Board Dr. Shubha Ganguly M.V.Sc.,Ph.D Dr Farhad Mirzaei, M.Sc., Ph.D.,

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NEED OF PHARMACOVIGILANCE IN ĀYURVEDA

Ujjaliya Nitin B L1

Remadevi R2

Dept of Dravyaguna, V.P.S.V. Ayurveda College, Kottakkal Prof. & HOD. Dept of Dravyaguna, V.P.S.V. Ayurveda College, Kottakkal

Corresponding author: Dr. Nitin Ujjaliya, PG. Scholar, Dept. of Dravyaguna Vijnana V. P. S. V. Ayurveda College, Kottakkal. Kerala, India Mob. - +919037714387 Email: drnujjaliya@gmail.com Received: 04/01/2012 Revised: 27/01/2012 Accepted: 31/01/2012 Abstract: Adverse effect of a drug may be uncommon but very serious and can put patients at risk before the relationship between adverse effect and drug is recognized. This gave birth to a new branch of medical science called pharmacovigilance. The rationale of this branch is to help health professionals to participate in a very important process of continuous surveillance of safety and efficacy of the pharmaceutical products which are used in clinical practice. Now a day, Āyurvedic medicines are gaining global popularity. The uses of Āyurvedic medicine along with synthetic one, has increased the chances of interactions causing harm to the patient. Some examples of these types of interactions lessen the demand of Āyurvedic medicines. Though many of them due to poor quality of preparation. For a scientific and convincing answer on these reports; there is a necessity of well established pharmacovigilance system in Āyurveda. IPGT&RA, Jamnagar has prepared National Pharmacovigilance Program for ASU Drugs in 2008. Implementation of this will generate confidence as well as increase the popularity of Āyurvedic preparations. Present article reveals about pharmacovigilance, pharmacovigilance in Āyurveda and its need, National Pharmacovigilance Program for Āyurveda, Siddha, Unani Drugs.

Key words: ADRs, Pharmacovigilance, pharmacovigilance in Āyurveda, NPP for ASU drugs.

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Introduction Adverse drug reactions significantly diminish quality of life, increases hospitalization and mortality.1 Presentation of ADRs along with a single disease makes it complex. Nowadays the cost of treatment is being increased due to this complexity. New drugs are being approved for marketing without much long term safety studies. Multinational marketing make it more risky because the drug can be made available easily and widely with in short period of time. Removal of restriction and self medication enhance the chance of herbdrug interactions and possible adverse reactions. The WHO set up its International drug monitoring program after the thalidomide disaster. Since 1978 the program has been carried out by UMC (Uppsala Monitoring Centre) Sweden. Emphasizing patient safety, it started Pharmacovigilance program at global level. According to WHO, Pharmacovigilance is the pharmacological science relating to detection, assessment, understanding and prevention of adverse effects particularly long term and short term side effects of medicine.2 The main aim of Pharmacovigilance is the safe and rational use of medical and para-medical interventions. Traditional medical system like Āyurveda has become more popular globally. Safe and more effective, if used for long terms are the two mis-interpretable words in case of natural medicine. Proper and rational use of Āyurvedic medicine ensures safety and efficacy but blind prescription and concomitant use with other synthetic drug may lead to interaction. Scientific documentation reveals that some herbs enhance or decrease effectiveness of other medicament.3 So, there is a need of a properly working Pharmacovigilance system in Āyurveda. It is necessary to generate confidence in the mind of user as well as prescriber. This system helps not only to the patients but also to the health professionals and governing authorities to prove safety and effectiveness of Āyurvedic medicine at international level.

Vigilance in Āyurveda Ācaryas have emphasized many a time on rational use of medicine and patient care like own child.4 In Caraka samhita it is mentioned that there is nothing which cannot be therapeutically useful.5 Each and every substance can be used in the management of disease or to maintain the health of an individual. But certain parameters have to be examined prior to the application of a therapy.6,7 Quality of Bhesajam (medicine), Pariksha (complete examination of disease and diseased) and application of Yukti (intellectual power of vaidya) has been mentioned as the key of the success of treatment.8,9 Ācarya Vagabhatta divided treatment into two types, pure and impure.10 Improper or impure line of treatment arise new symptoms or disease which will complex the previous one and can put a patient at risk.10 It is mentioned that a good medicine is not an isolated entity. It is expected to have multiple actions and dosage forms.11 While mentioning the therapeutic classification of dravya; samana, kopana and swasthvrita; Ācaryas were very meticulous to account the effects of drugs.12,13 So, Vaidya has the responsibility to consider assessment and categorization of potency to reduce the chances of intoxication and related complications.14 Need in Āyurveda According to the WHO global survey on the national policy and regulation of traditional medicine; there are three common difficulties and challenges: lack of information sharing; lack of safety monitoring for herbal medicine and lack of methods to evaluate their safety and efficacy.15 These hurdles are also before Āyurvedic community. Increase in use of Āyurvedic medicine along with synthetic formulations is raising the concern of vigilance for Āyurvedic medicine. Though the guidelines for manufacturing and clinical practices are mentioned in classics but are not being followed by industries as well as health professionals.16,17 System of pharmacovigilance was not necessary at that time but now the scenario has been changed. Due to

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unavailability of genuine raw material thereby unauthentic substitution and adulteration in classical formulations has to be checked for safety and efficiency using modern tools. A workshop conducted by countries of the WHO South East Asia Region (SEAR) for the regulation of herbal medicine in South East Asia Region with the objectives of requirements for registration and regulation of pharmacovigilance for herbal medicines.18 According to their guidelines herbal medicines can be classified into 4 categories; Indigenous herbal medicine, Herbal medicine in system, Modified herbal medicine and Imported products with herbal medicine base. Except first category of herbal medicine, all have required some sort of documentation and studies on safety and efficacy.18

Table no. 1

Recent scientific researches show the interactions, adverse drug reactions when used with other medicaments and issues on poor quality control of Āyurvedic formulations. Few examples are Herbal medicine and venoSevere occlusive disease in India,19 hypokalaemia with paralysis induced by small doses of liquorice,20 Indian herbal medicine for diabetes as a cause for lead poisoning,21 Heavy metal content of Ayurvedic herbal medicine products.22,23 These reports diminish the progress of Āyurvedic medicines globally. A developed pharmacovigilance system in Āyurveda can provide a better answer on herb interactions, with systematic documentations to the scientific world. Few examples of herb – drug interactions are given in table no. 1.

Examples of Herb-Drug interaction3,33,34,35 Synthetic Drugs Effects

No. Herbs

Procyclidine

Decreases drug effect

Tambula patra (Piper betle Linn.) 2.

Methika

(Trigonella

foenum-graecum Anticoagulant

Increases bleeding risk

Linn.) 3.

Rasona (Allium sativum Linn.)

Anticoagulant

Increases drug effect

Karkati (Carica papaya Linn.)

Anticoagulant

Increases drug effect

Sarpagandha (Rauvolfia serpentine (L.) NSAID

Increases gastric ulcer

Benth.ex Kurz)

risk

Raja shimbi (Glycine max (L.) Merr. )

Anticoagulant

Decreases drug effect

Kumari (Aloe vera (L.) Burm.f.)

Antidiabetic

Lowers sugar level

Yasthimadhu (Glycyrrhiza glabra Linn.)

Diuretics

Decreases drug effect

Propanolol

Decreases drug effect

Digoxin

Increases side effect

9. Guggulu (Commiphora wightii (Arn.) Bhandari) 10. Yasthimadhu (Glycyrrhiza glabra Linn.)

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National Pharmacovigilance Program for ASU Drugs Central drug standard control organization, ministry of health and family welfare, Govt. of India launched the National Pharmacovigilance Program (NPP) in 24 November 2004. The guidelines of NPP are based on the recommendations made by WHO for pharmacovigilance. The main aim of this program is to collect information from health care professionals on hazardous effect of medicaments. It works as a link between informer and Uppsala Monitoring Centre (UMC) Sweden; which is the top centre for pharmacovigilance at international level. In 2002, WHO emphasized that herbals and traditional medicines should be included under pharmacovigilance program.25 Hence, Institute for Post Graduation Teaching & Research in Ayurveda, Jamnagar took a task and conducted a workshop in December 2007 and prepared a protocol; Pharmacovigilance for Ä&#x20AC;yurveda, Siddha and Unani drugs, 2008.21 Pharmacovigilance for ASU has 5 National Pharmacovigilance Resource Centre, 8 Regional and 30 Peripheral Pharmacovigilance Centre, where information can be submitted in a prescribed format through surface mail or on website. Only a health professional can submit the information but a common man can report through his physician under whom he had undergone treatment. Each and every report evaluated and assessed on the causality with the suspected herbal medicine. After an assessment of information NPC report to the Governing body AYUSH regarding result and decision. Once, causality between medicines is established, it should be circulated through the same channel and published in news bulletins to make awareness among public regarding hazards of particular medicine. What to Report The NPP for ASU drugs is encouraging reporting of all adverse events suspected to have been caused by new drug, suspected drug interactions and all reactions to any other drug which can cause death, life threatening risk,

hospitalization, malformation.26

disability

congenital

Sources of Reports27 Clinical trials Spontaneous reports Reports from consumers Reports from manufacturer National poison centre Drug information centre Consumer organizations What can be done? A report of adverse reaction should be evaluated and properly assessed to establish the causality with the suspected herbal medicine. Health professional have to ask to the patient about the use of herbal medicine including medical food, other medicaments and beverages. Certain point can be made to make an easy assessment:25 A literary search of the herbal product, their constitution and comedication. Establishment of time â&#x20AC;&#x201C; adverse reaction relationship. The dosage used should be compared with traditional dose described in literature. Searching of database for similar case reports for easy association. Assessment of quality of herbal medicine for adulteration and substitution. Phases of Pharmacovigilance28 Data collection Data management Signal detection Safety issue assessment Decision making Communication /Action Examples The Uppsala Monitoring Centre of WHO is getting 500,000 to 700,000 reports every year all around the world.29 The WHO

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program for drug monitoring has now entered 7 million Adverse Drug Reactions (ADRs) reports from countries contribution to the WHO Global Individual Case Safety Report (ICSR) database, which is called VigiBase.30 Due to the continuous reporting and assessment of causality, many drugs have been recognized as having an association with hazards of medicament. Thalidomide is a famous example of patient negligence in the last century.31 It was introduced in 1957 and widely prescribed as harmless treatment for morning sickness. Very soon it was linked to a congenital malformation in the children of women who have been taken during pregnancy. As a result in 1965 it had been removed from the market. Likewise, herbs also can produce abnormality in patients. According to a study32, Pueraria tuberose D.C. produced gynacomastasis with deep pigmentation of areola in a patient treated by it.

The use of Āyurvedic medicine is increasing worldwide day by day. But in many cases Āyurvedic medicines are being utilized as non-prescription medicine also along with other medicaments. Concomitant use of herbals and synthetic preparations can alter the mechanism of action leading to less effect, toxicity, adverse drug reaction or side effects of medicine. It is difficult to predict all adverse reactions prior to the therapy but rational use of Āyurvedic as well as modern medicine prevent from hazards of medicine. Ācaryas have mentioned several guidelines for safe and rational use of medicine but now are not being practiced by physician as well as manufacturer. Currently the majority of adverse events of herbals are related to poor quality of or improper use of medicine. Through the system of pharmacovigilance; it is easy to make causality between hazards and herbal medicine. Effective establishment of this system will popularize Āyurveda in terms of safety and efficacy at global level.

Conclusion References 1. ISDB EU (2005): Berlin Declaration on Pharmacovigilance, Berlin (ISDB Workshop on 31 October/ 01 November 2003); 5. 2. World health organization (2004), WHO guidelines on safety monitoring of herbal medicines in pharmacovigilance system, WHO, Geneva; 19 3. Ujjaliya Nitin et al. (2011), Herb-Drug Interaction – An Overview, Aryavaidyan, Vol. XXV, No. 1, August – October; 27 – 30. 4. Kavirar Shastri Ambikadatta (2005), Susruta Samhita of Maharsi Susruta, Edited with Ayurveda-Tatva-Sandipika Teeka, Chaukhambha Sanskrit Sansthan, Varanasi, Part-I, Sutra Sthāna 25/43 – 44; 106. 5. Sastri Kashinath and Chaturvedi Gorakhnath (2001), Agniveśa ’Caraka Samhita’, revised by Caraka and Drudhabala with ‘Ayurveda Dīpikā’ commentary, by Cakrapānīdatta, Chaukhamba Vishvabharti, Varanasi (India),Sutra Sthāna 26/12.

6. Caraka Samhita, Vimāna Sthāna 8/94 – 130, Ibidem 7. Caraka Samhita, Vimāna Sthāna 8/68 – 78, Ibidem 8. Caraka Samhita, SutraSthāna 2/16, Ibidem. 9. Caraka Samhita, Vimāna Sthāna 8/68, Ibidem. 10. Astanga Samgraha of Vagabhatta, translated by Murthy Srikantha K.R. (2005), Chaukhamba Orientalia, Varanasi, Vol. I, Sutra Sthana 21/29; 390. 11. Astanga Samgraha of Vagabhatta, Sutra Sthana 2/22; 27 Ibidem. 12. Caraka Samhita, SutraSthāna 1/67, Ibidem. 13. Vagabhatta’s Astanga Hrudayam, translated by Murthy Srikantha K. R. (2007), Chauhamba Orientalia, Varanasi, Sutra Sthana 1/16; 10. 14. Caraka Samhita, SutraSthāna 1/123 – 126; 48, Ibidem. 15. Guidelines for regulation of herbal medicines in the South – East Asia Region, developed at the regional

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workshop on the regulation of herbal medicines, Bangkok, 24 – 26 June; 6, (SEA – Trad. Med.-82) 16. Bhaisajyaratnavali of Shri Govinda Dasji (2006), Edited and Enlarged by Bhishagratna Shri Brahmashankara Mishra, Chaukhambha Sanskrit Bhavan, Varanasi, Vol. I, Chepter 2; 14 – 54. 17. Sarangdhara Samhita by Sarangadhara, translated in English by Murthy Srikantha K.R. (2007), Chauhamba Orientalia, Varanasi, Madhyama khanda. 18. Guidelines for regulation of herbal medicines in the South – East Asia Region, developed at the regional workshop on the regulation of herbal medicines, Bangkok, 24 – 26 June; 8 – 11, (SEA – Trad. Med.-82) 19. Datta DV. et al (1978), Herbal medicine and veno-occlusive disease in India, Postgrad. Med. J.;54;511 – 15. 20. Cumming AM. et al (1980), Severe hypokalaemia with paralysis induced by small doses of liquorice, Postgrad. Med. J.,56;526 – 29. 21. Keen RW. et al (1994), Indian herbal medicine for diabetes as a cause for lead poisoning, Postgrad. Med. J.,70;113 – 14. 22. Seper Robert B. et al (2004), Heavy metal content of Ayurvedic herbal medicine products, 23. Seper Robert B. et al (2008), Lead, Murcury and Arsenic in US and Indian manufactured Ayurvedic medicines sold via the Internet, 24. Adithan C. (2005), National Pharmacovigilance Program, Editorial, Indian J. Pharmacol, December 2005, Vol. 37, Issue 6; 347. 25. World health organization (2004), WHO guidelines on safety monitoring of herbal medicines in pharmacovigilance system, WHO, Geneva; 32 – 35. 26. Protocol for National Pharmacovigilance Program for ASU Drugs (2008), prepared and published by IPGT&RA, Gujrat Ayurved

University, Jamnagar;23. (Downloaded from www.ayushsuraksha.com) 27. World health organization (2004), WHO guidelines on safety monitoring of herbal medicines in pharmacovigilance system, WHO, Geneva; 18. 28. European Commission (2006), Assessment of the European community system of pharmacovigilance: final report – final version, submitted by institute systems and innovation research, Karlsruhe, Director General, unit F2, pharmaceuticals. 29. R.D. Mann, Andreus EB, John Wiley & Sons Ltd.(2002), Pharmacovigilance, Chichester. 30. http://www.who-umc.org accessed on January 2nd, 2012. 31. World Health Organization, Pharmacovigilance: ensuring the safe use of medicines (2004), WHO policy perspective on medicine, October 2004, WHO, Geneva;4. 32. Acharya R.N. (2004), Clinico – Pharmacognostical standardization of Vidari, Souvenir of International seminar on plant based medicine, NIA, Jaipur. 33. http://www.webmd.com/vitaminssupplements/ingredientsmonoALOE_side effects (Downloaded on January 31st 2012). 34. http://www.herbal-supplimentresource.com/adhotoda-vasica.html (Downloaded on January 31st 2012). 35. Dalvi SS. Et al (1994), Effects of gugulipid on bioavailability of diltiazem and propanolol. J. Assoc. Physicians India: 42(6);454 – 5.

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THE MODELING OF SOME MORPHOLOGICAL CHARACTERISTICS WITH LEAF LENGTH AND LEAF NUMBER IN SCOLYMUS HISPANICUS L. Ali Osman SARI1, *Mehmet Serhat ODABAS2, Mehmet TUTAR1

Aegean Agricultural Research Institute,35661, Menemen, Izmir, Turkey

Ondokuzmayis University, Bafra Vocational School, 55400, Samsun, Turkey

*Corresponding Author’s E- mail: mserhat@omu.edu.tr Received: 19/12/2011;

Revised: 19/01/2012;

Accepted: 31/01/2012

Abstract

Golden thistle (Scolymus hispanicus L.), Asteraceae, is native to Mediterranean region. The root cortex of the plant is used for medicinal purposes as well as vegetable. Since the root of the thistle is harvested before flowering, reliable modeling based on aerial plant parts and root parts have crucial importance for breeding. The objective of the present study is to develop a mathematical model to predict growth parameters in Scolymus hispanicus L. Morphological characteristics include root weight, root diameter, root cortex weight, root xylem weight, root xylem diameter, root length. The best estimating equations for some morphological characteristics are formulized as MC = (a) + [b x (L x N2)] where MC is morphological characteristics, L is leaf length (cm), N is leaf number and a, b are coefficiencies. Multiple regression analysis was carried out until the least sum of square (R²) was obtained. R2 value 0.77 for root xylem diameter and 0.83 for root length. Standard errors were found to be significant at the p<0.001.

Key Words: Scolymus hispanicus L., modeling, multiple regression.

Abbreviations: MC - morphological characteristics; L - leaf length (cm); N - leaf number; SE- standard error; R² - regression coefficiency;

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Introduction Golden thistle (Scolymus hispanicus L.), of Asteraceae, is a biennial or perennial spiny plant native to Mediterranean region (Vavilov, 1994). It is distributed throughout the southern Europe, North Africa, extending to northwestern France and Turkey. Golden thistle has a root cortex with basal leaves and has been used as a vegetable in Mediterranean region since olden times (Abak and Düzenli, 1989; Nuez and Hernandez Bermejo, 1994). It is considered that golden thistle has antisudorific and diuretic properties. In addition, its roots are used in folk remedy to remove calculi from kidneys in Turkey. A clinically registered medicine called “Lityazol Cemil”, made of root extracts of the thistle, had been produced from 1930’s to 1990’s in Turkey for the same purposes (Başer, 1993). Although golden thistle was cultivated in Spain, today there are no known cultivation practices and it is wild crafted in all countries. However, it has quite good potential, both as a vegetable and medicinal plant. Developmental models are commonly explored using computational or simulation techniques (Uzun, 1996; Odabas, 2003). The simulation software may be of general-purpose, intended to capture a variety of developmental processes depending on the input files, or special-purpose, intended to capture a specific phenomenon. Input data range from a few parameters in models capturing a fundamental mechanism to thousands of measurements calibrated descriptive models of specific plants (species or individuals). Standard numerical outputs (i.e. numbers or plots) may be complemented by computer-generated images and animations (Prusinkiewicz, 2004). Most of the researches have investigations focused on plant developmental periods from seed sowing to reproductive stages and from reproductive stages to harvest (Ellis et. al.1990).

Environmental conditions affect the dry matter production rate, rooting percentage and the rooting degree of the plants. Different physiological processes occur in different periods of plant growth stage (Pearson et al.1993; Cirak et al. 2005; Cirak et al. 2007; Odabas et al., 2005). There is no known study on mathematical modeling for morphological characteristics on leaf length and leaf number of Scolymus hispanicus L. This study has been focused on producing a reliable and practical mathematical equation for the relations among some morphological characteristics on leaf length and leaf number in Scolymus hispanicus L. Material and Methods Plant material The golden thistle seeds were collected from Ege, Marmara and the West Karadeniz regions of Turkey in August, summer season 2007. The seeds were trashed and stored in cold for one month before sowing, since it significantly increased seed germination (Sari and Tutar, 2009). The seeds were sown on drip irrigated field by 70x70cm space, in an experiment field of Aegean Agricultural Research Institute, Menemen, Izmir, Turkey, on 03 October 2007. There were around 3000 plants in selection nursery. The thistle plants were harvested using a sapling digger at the end of rosette leaf stage, just before stalking up on 15 April 2008, since root cortex of the plant is used as a vegetable as well as medicine. Just before harvest the number and length of rosette leaves for 100 plants were determined to develop a reliable mathematical model, predicting yield of root and root parts. After harvest, root weights and lengths were immediately determined. Root and xylem diameter were measured just below the basal leaves. Root cortex was peeled and cortex and xylem were separately weighed.

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Photo 1: Experimental field of S. hispanicus

Photo 2: S. hispanicus after emergence

Photo 3: Field of S. hispanicus

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Model Construction Multiple regression analysis of the data obtained from the first year’s study was performed for morphological characteristics. A search for the best model to predict the morphological characteristics was conducted with various subsets of the independent variables, namely, leaf length (cm) and leaf number. The best estimating equations for the root weight, root diameter, root cortex weight, root

xylem weight, root xylem diameter root length were determined with the R- program and formulized as MC = (a) + [b x (L x N2)] where MC is morphological characteristics, L is leaf length (cm), N is leaf number and a, b are coefficiencies of the produced equation (Table 1). Multiple regression analysis was carried out until the least sum of square (R²) was obtained. Three dimension graphics was performed by Slidewrite program.

Table 1. The coefficients, their standard errors and R² values of the newly produced equations predicting some morphologic characteristics in Scolymus hispanicus L. Some Morphologic Characteristics and Standard Coefficient

L x (LN)2

R²

Root Weight (g)

32.153±3.383***

0.004938±6.07E-4 ***

0.80

Root Diameter (cm)

19.562±0.844***

0.001135±1.50E-4 ***

0.82

Root Cortex Weight (g)

26.218±2.457***

0.000356±4.41E-4 ***

0.82

Root Xylem Weight (g)

5.935±1.045***

0.001381±1.88E-4 ***

0.81

Root Xylem Diameter (cm)

10.130±0.580***

0.000678±1.04E-4 ***

0.77

Root Length (cm)

24.124±0.584***

0.000185±1.05E-4 ***

0.83

Errors (SE)

R²:

regression coefficiency, SE: standard error, L: Leaf Length, LN: Leaf Number. *, **, ***: Significant at the level of p < 0.05, 0.01 and 0.001, respectively.

Photo 4: Habit of S. hispanicus

Photo 5: S. hispanicus at rosette stage

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Photo 6: Flower of S.hispanicus

Photo 7: Edible roots of S. hispanicus

Figure 1. Relationship between actual and predicted root weight (g) for Scolymus hispanicus L. 120

Predicted root weight (g)

100

40 R2 = 0.8058

0 0

100

Actual root weight (g)

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120

140

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Result and Discussion Root Weight (g): Multiple regression analysis used for the determination of the best fitting equation for root weight (g) in S. hispanicus. L. here showed that the highest of the variation of rooting was explained by the parameters leaf length (cm) and leaf number. The variation explained by both parameters was 80 % for S. hispanicus. L. (Figure 1). Standard errors were shown as (SE) and found to be significant at the p<0.001 level.

RW = (32.153) + [0.004938 x (L x N²)] SE = 3.383*** 6.07E-4*** R²= 0.80 The equation of the selected parameters in validation of the model developed in this study (leaf length and leaf number) produced the highest coefficient as R²= 0.80 (Figure 2). This result indicates statistical acceptability of the produced model. As seen in the Figure 2, the root weight kept increasing by leaf length and leaf number. The highest root weight was determined where leaf length is 50 cm and leaf number is 20 leaves.

Figure 2. Changes in predicted root weight (g) with leaf length (cm) and leaf number for Scolymus hispanicus L.

(g) Predicted Root Weight

140

112

56 28 20

16 10 Lea 20 f Le ngt h(

30 cm )

8 4

40 50

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Root Diameter (cm): The variability between actual and predicted root diameter of S. hispanicus L. was explained by 82% of the observed cases (Figure 3). Root diameter was estimated by following equation:

Root Cortex Weight (g): The variation explained by both parameters was 82 % for plant (Figure 5). Standard errors were shown as (SE) and found to be significant at the p<0.001 level. This result indicates statistical acceptable.

RD = (19.562) + [0.001135 x (L x N²) SE = 0.844*** 1.50E-4*** R² = 0.82 Where RD: root diameter, SE: Standard errors, L: leaf length and N: leaf number. The largest root weight was determined where leaf length was 50 cm and leaf number was 20 leaves (Figure 4).

RCW = (26.218) + [0.000356 x (L x N²)] SE = 2.457*** 4.41E-4*** R²= 0.82 The equation of the selected parameters in validation of the model developed in this study (leaf length and leaf number) produced the highest coefficient as R²= 0.82 (Figure 5). As seen in the Figure 6, the root cortex weight kept increasing by leaf length and leaf number. The highest root cortex weight was determined where leaf length was 50 cm and leaf number was 20 leaves.

Figure 3. Relationship between actual and predicted root diameter (cm) for Scolymus hispanicus L. 40

Predicted root diameter (cm)

35 30 25 20 15 R2 = 0.8249

10 5 0 0

Actual root diameter (cm)

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Figure 4. Changes in predicted root diameter (cm) with leaf length (cm) and leaf number for Scolymus hispanicus L.

(cm) Predicted Root Diameter

20 10 20

16 10 Lea fL

12 20 eng t

30 h( cm )

40 50

a Le

er mb u fN

Figure 5. Relationship between actual and predicted root cortex weight (g) for Scolymus hispanicus L. 90

Predicted root cortex weight (g)

80 70 60 50 40 30 20

R2 = 0.824

10 0 0

Actual root cortex weight (g)

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100

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Figure 6. Changes in predicted root cortex weight (g) with leaf length (cm) and leaf number for Scolymus hispanicus L.

Predicted Root Cortex Weight (g)

120 96 72 48 24 20

16 10 20 Leaf Length 30

12 8

(cm)

Root Xylem Weight (g): The actual and predicted root xylem weight of plant were explained by 81 % of the observed cases (Figure 7). Root diameter was estimated by the following equation:

RXW = (5.935) + [0.001381 x (L x N²) SE = 1.045*** 1.88E-4*** R² = 0.81 The highest root xylem weight was determined where leaf length was 50 cm and leaf number was 20 leaves (Figure 8). Root Xylem Diameter (cm): The variation was 77 % for S. hispanicus L. (Figure 9). Standard errors were shown as (SE) and found to be significant at the p<0.001 level. This result indicates statistical acceptable.

RXD = (10.130) + [0.000678 x (L x N²)] SE = 0.580*** 1.04E-4*** R²= 0.77

40 50

Leaf Number

The equation of the selected parameters in validation of the model developed in this study (leaf length and leaf number) produced the highest coefficient as R²= 0.77 (Figure 9). As seen in the Figure 10, the root xylem diameter kept increasing by leaf length and leaf number. The highest root xylem diameter was determined where leaf length was 50 cm and leaf number was 20 leaves. Root Length (cm): The variability between actual and predicted root length of S. hispanicus L. were explained by 83 % of the observed cases (Figure 11). Root length was estimated by the following equation:

RL = (24.124) + [0.000185 x (L x N²) SE = 0.584*** 1.05E-4*** R² = 0.83 Where RL: root length, SE: Standard errors, L: leaf length and N: leaf number.

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The highest root weight was determined where leaf length is 50 cm and leaf number was 20 leaves (Figure 12).

Conclusion In present study, we have developed prediction models for some morphological characteristics (root weight, root diameter, root cortex weight, root xylem weight, root xylem diameter and root length) with leaf length and leaf number for a plant used both as a medicine

and vegetable. Produced models to determine the effect of leaf length and leaf number of S. hispanicus L. were found statistically acceptable. The best results were obtained where, leaf length was 50 cm and leaf number was 20 leaves for all morphological characteristics. The models of morphological characteristics were found by using simple equations. Hence, the models produced in the present study can be used by researchers, especially by breeders to predict root and root cortex yield.

Figure 7. Relationship between actual and predicted root xylem weight (g) for Scolymus hispanicus L.

Predicted root xylem weight (g)

10 R2 = 0.8122 5

0 0

Actual root xylem weight (g)

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Figure 8. Changes in predicted root xylem weight (g) with leaf length (cm) and leaf number for Scolymus hispanicus L.

Weight (g) Predicted Root Xylem

16 8 20

16 10 Lea 20 f Le 30 ngt h (c m)

12 8 4

40 50

a Le

r be um N f

Figure 9. Relationship between actual and predicted root xylem diameter (cm) for Scolymus hispanicus L.

Predicted root xylem diameter (cm)

R2 = 0.7797

0 0

Actual root xylem diameter (cm)

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Figure 10. Changes in predicted root xylem diameter (cm) with leaf length (cm) and leaf number for Scolymus hispanicus L.

Diameter (cm) Predicted Root Xylem

16 8 20

16 10 Lea 20 f Le ngt h(

12 8

30 cm )

N af Le

40 50

be um

Figure 11. Relationship between actual and predicted root length (cm) for Scolymus hispanicus L. 28

Predicted root length (cm)

27 27 26 26 25 R2 = 0.8356 25 24 24 0

Actual root length (cm)

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Figure 12. Changes in predicted root length (cm) with leaf length (cm) and leaf number for Scolymus hispanicus L.

Predicted Root Length

(cm)

16 8 20

16 10 Lea 20 f Le 30 ngt h (c m)

12 8 4

40 50

References Abak K, Düzenli A (1989) Use of some wild plants as vegetables in Turkey. Acta Hort. 242:107-114. Başer KHC (1993) 60 year-old a Turkish plant made medicine: Lityazol Cemil. TAB Bulletin Anadolu University, Eskişehir, Turkey. 1:13-18. Cirak C, Ayan AK, Odabas MS (2007) Modeling the effect of temperature on the days to germination in seeds of flue-cured and oriental tobacco (Nicotiana tabacum L.). Journal of Plant Science.2(3):358361. Cirak C, Odabas MS, Ayan AK (2005) Leaf area prediction model for summer Snowflake (Leucojum aestivum L.). International Journal of Botany. 1(1):1214. Ellis RH, Hadley P, Roberts EH (1990) Quantitative relations between

af Le

e mb Nu

temperature and crop development and growth. In climatic Change and Plant Genetic Resources. Belhaven Press, London and New York. pp 432. Nuez F, Hernandez Bermejo JE (1994) Neglected horticultural crops. In Neglected Crops: 1492 from a Different Perspective (Eds.:J.E. Hernándo Bermejo and J. León). Plant Production and Protection Series No. 26, FAO. pp 303-332. Odabas MS (2003) The quantitative effect of temperature and light on growth, development and yield of Broad Bean (Vicia faba L.). Unpublished ph.D Thesis, Samsun, Turkey, pp 280. Odabas MS, Kevseroglu K, Cirak C (2005) Non-destructive estimation of leaf area in some medicinal plants. Tr. J. of Field Crops. (10)1: 29-31.

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Pearson S, Hadley P, Wheldon AE (1993) A reanalysis of the effects of temperature and irradiance on time to flowering in chrysanthernum (Dendranthema grandflora). Journal of Horticultural Science. 68: 89-97. Prusinkiewicz P (2004) Modeling plant growth and development. Current Opinion in Plant Biology.7:79â&#x20AC;&#x201C;83. Sari AO, Tutar M (2009) Effects of light, cold storage and temperature on seed germination of golden thistle (Scolymus hispanicus L.). Journal of Herbs Spices

Medicinal & Aromatic Plants. 15(4): 318-325. Uzun S (1996) The quantitative effects of temperature and light environment on the growth, development and yield of tomato and aubergine (unpublished PhD thesis). The Univ. Of Reading, England. Pp. 120150. Vavilov NI (1994) The phyto-geographical basis for plant breeding. In Origin and Geography of Cultivated Plants (Ed. V.F. Dorofeyev). Cambridge University Press, U. K. pp 344.

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ANTI-AMNESIC AND ANTI-ANXIETY EFFECTS OF MEMORHIS, A POLY HERBAL FORMULATION IN THE MANAGEMENT OF MEMORY DYSFUNCTIONS

Hanumanthachar Joshi 1*, Milind Parle 2 1

Division of pharmacognosy, Dept. of Postgraduate studies and Research, Sarada Vilas College of Pharmacy, Mysore- 570004, Karnataka, India. 2

Division of Pharmacology, Department of Pharm. Sciences, Guru Jambheshwar University, Hiar-125001, Haryana, India *Corresponding Author Phone: 91-9448632253 [R] Email: amanjoshi17@yahoo.com

Received: 27/12/2011;

Revised: 28/01/2012;

Accepted: 10/02/2012

Abstract

The present study was undertaken to assess the potential of MEMORHIS as a memory enhancer. Elevated plus maze and passive avoidance paradigm were employed to evaluate antianxiety, learning and memory parameters. MEMORHIS (50, 100 and 250 mg/kg, p.o.) was administered for 8 successive days to both young and aged mice. MEMORHIS (100 and 250 mg/kg, p.o.) significantly improved learning and memory in young mice and also reversed the amnesia induced by diazepam (1 mg/kg, i.p.), and scopolamine (0.4 mg/kg, i.p.). Furthermore, it also reversed aging induced amnesia due to natural aging of mice. It exhibited potential antianxiety activity. MEMORHIS profoundly increased whole brain acetyl cholinesterase inhibition activity. Hence, MEMORHIS might prove to be a useful memory restorative agent in the treatment of dementia seen in the elderly. The underlying mechanism of its action may be attributed to its antioxidant and acetyl cholinesterase inhibition property.

Key words: MEMORHIS; Amnesia; Learning; Memory.

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INTRODUCTION

Memory function is vulnerable to a variety of pathologic processes including neurodegenerative diseases, strokes, tumors, head trauma, hypoxia, cardiac surgery, malnutrition, attention deficit disorder, depression, anxiety, the side effects of medication, and normal ageing (Rowan, 2012). As such, memory impairment is commonly seen by physicians in multiple disciplines including neurology, psychiatry, medicine, and surgery (Mesulam, 2000). MEMORHIS is a poly-herbal formulation comprising of the herbal ingredients and pharmaceutical adjuvants. The plant extracts used for formulating this preparation were selected since they had exhibited very promising cognition improving effects in mice. This suspension was prepared in our research laboratory using plant extracts of Nardostachys grandiflora DC., Ocimum tenuiflorum L., Asparagus racemosus Willd., Piper nigrum L., Mimusops elengi L., Phyllanthus niruri L., Glycyrrhiza glabra L., Other ingredients of the preparations were ascorbic acid, cardamom oil, methyl paraben, propyl paraben, propylene glycol, sodium carboxy methyl cellulose and purified water.

METHODS Preparation of poly-herbal formulationMEMORHIS

MEMORHIS suspension was prepared using lyophilized extracts of N. grandiflora DC., O. tenuiflorum L., A. racemosus Willd., P. nigrum L., M. elengi L., P. niruri L., G. glabra L., and other ingredients were ascorbic acid, cardamom oil, methyl paraben, propyl paraben, propylene glycol, sodium carboxy methyl cellulose and purified water. Each 5 ml of MEMORHIS contained lyophilized extracts of N. grandiflora DC. (20 mg), O. tenuiflorum L. (20 mg), A. racemosus Willd. (20 mg), P. nigrum L. (5 mg), M. elengi L. (20 mg), P. niruri L.(10 mg), G. glabra L.(10 mg), ascorbic acid (5 mg) and cardamom oil (Q.S.).

Acute toxicity studies Acute toxicity studies were performed according to OECD/OCDE 421 guidelines (Ecobichon, 1997). Male Swiss mice selected by random sampling technique were employed in this study. The animals were fasted for 4 h with free access to water only. The experimental protocol was approved by the IAEC, dept. of pharm. Sciences, Guru Jambheshwar University, Hisar, Haryana. Laboratory models for testing memory Elevated plus Maze (Parle et al., 2007, Davis et al., 2012). Passive shock avoidance paradigm (Parle et al., 2004, Lu et al., 2012). Estimation of brain acetyl cholinesterase (AChE) activity (Ellman et al., 1961). Light and dark box test (Crawley et al., 1980) Open field test (Toriizuka et al., 2005) Experimental protocol

The animals were divided into various groups and each group consisted of a minimum of five animals. Separate animals were used for each observation. Group I & V: Represented Control groups of young and aged mice. Distilled water (DW), was administered orally for 8 days. Transfer latency (TL) was noted after 45 min of administration on 8th day and again after 24 h i. e on 9th day. Group II & VI: Piracetam, 200 mg/kg, i.p. was injected to both young and aged mice. TL was noted after 45 min of injection 8th day and again on 9th day. Group III & IV: MEMORHIS (MEM, 50, 100 and 250 mg/kg, per oral (p.o.) was administered orally to young mice for 8 days. TL was noted on 8th day and again after 24 h. Group VII & VIII: MEMORHIS (MEM, 50, 100 and 250 mg/kg, p.o.) was administered orally to aged mice for 8 days. TL was noted on 8th day and again after 24 h i.e. on 9th day.

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Group IX: Diazepam (1 mg/kg, i.p.) was administered to young mice and TL was noted after 45 min of injection on 8th day and again after 24 h i.e. on 9th day. Group X: Piracetam (200 mg/kg, i.p.) was administered to young mice for 8 days. After 90 min of administration of the last dose on 8th day, diazepam (1 mg/kg, i.p.) was administered. TL was noted after 45 min of administration of diazepam on 3rd day and again after 24 h i.e. on the 9th day. Group XI & XII: MEMORHIS (MEM, 50, 100 and 250 mg/kg, p.o.) was administered to young mice for 8 days. After 90 min of administration of the last dose on 8th day, diazepam was administered. TL was noted after 45 min of administration of diazepam on 8th day and again after 24 h i.e. on the 9th day. Group XIII: Scopolamine (0.4 mg/kg, i.p.) was administered to young mice and TL was noted on 8th day and again after 24 h i.e. on 9th day. Group XIV: Piracetam (200 mg/kg, i.p.) was administered to young mice for 8 days. After 90 min of administration of the last dose on 8th day, scopolamine was administered. TL was noted after 45 min of administration of scopolamine on 8th day and again after 24 h i.e. on the 9th day. Group XV & XVI: MEMORHIS (MEM, 50, 100 and 250 mg/kg, p.o.) was administered to young mice for 8 days. After 90 min of administration of the last dose on 8th day, scopolamine was administered. TL was noted after 45 min of administration of scopolamine on 8th day and again after 24 h i.e. on the 9th day. GroupXVII & XXI: Control groups for young and aged mice. Distilled water (1 ml/100 g, p.o.) was administered for 8 days. Step down latency (SDL) was recorded on the 9th day. Group XVIII & XXII: Piracetam (200 mg/kg, i.p.) was administered to both young and aged

mice consecutively for 8 days. SDL was recorded on the 9th day. Group XIX & XX (n=5 each): MEMORHIS (MEM, 50, 100 and 250 mg/kg, p.o.) was administered orally for 8 days to young mice. SDL was recorded on 8th day and after 24 h. Group XXIII and XXIV: MEMORHIS (MEM, 50, 100 and 250 mg/kg, p.o.) was administered to youg and aged mice for 8 days. SDL was recorded on 9th day. Group XXV: Diazepam (1 mg/kg, i.p.) was administered to young mice for 8 days. SDL was recorded on 9th day. Group XXVI: Piracetam (200 mg/kg, p.o.) was administered to young mice consecutively for 8 days. After 90 min of administration of the last dose, diazepam was administered. SDL was recorded on 9th day. Group XXVII & XXVIII: MEMORHIS (MEM, 50, 100 and 250 mg/kg, p.o.) was administered to young mice for 8 days. After 90 min of administration of the last dose, diazepam was administered. SDL was recorded on 9th day. Group XXIX: Scopolamine (0.4 mg/kg, i.p.) was administered to young mice. SDL was recorded on 9th day. Group XXX: Piracetam (200 mg/kg, i.p.) was administered to young mice consecutively for 8 days. After 90 min of administration of the last dose, scopolamine was administered. SDL was recorded on 9th day. Group XXXI & XXXII: MEMORHIS (MEM, 50, 100 and 250 mg/kg, p.o.) was administered to young mice for 8 days. Scopolamine was administered i.p. to young mice. SDL was on 9th day. Group XXXIII & XXXVIII: Served as control groups for young and aged mice. Distilled water was administered for 8 days. Whole brain AChE activity was determined.

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Group XXXIV & XXXIX: phenytoin (12 mg/kg, p.o.) was administered to young and aged mice for 8 days. Whole brain AChE activity was determined.

change in the locomotor function of animals (score 222±1.9, 219±1.3 and 213±11) as compared to control group (score 216.4±12) when tested using a photoactometer.

Group XXXV & XL: Piracetam (200 mg/kg, i.p.) was administered to both young and aged mice for consecutive 8 days. Whole brain AChE activity was determined.

Effect on transfer latency (TL) using elevated plus maze: MEMORHIS (50, 100 and 200 mg/kg, p.o.) showed dose-dependent reduction in TL of 8th day and 9th day, indicating remarkable improvement in learning ability and memory of the young and aged mice as compared to respective control groups (Fig. 1). Diazepam (1 mg/kg, i.p.) and scopolamine (0.4 mg/kg, i.p.) significantly increased (P < 0.01) the TL of 9th day indicating impairment in memory (amnesia). MEMORHIS (100 and 250 mg/kg, p.o.) successfully (P< 0.001) reversed the amnesia induced by both diazepam and scopolamine (Fig. 2).

Group XXXVI and XXXVII: MEMORHIS (MEM, 50, 100 and 250 mg/kg, p.o.) was administered for 8 days to young mice and whole brain acetyl cholinesterase activity was determined on 9th day. Group XLI and XLII: MEMORHIS (MEM, 50, 100 and 250 mg/kg, p.o.) was administered for 8 days to aged mice and whole brain acetyl cholinesterase activity was determined. STATISTICAL ANALYSIS

All the results were expressed as mean ± standard error (SEM). The data was analyzed using one-way ANOVA followed by Tukey Kramer’s test. P values <0.05 were considered as statistically significant. RESULTS Acute toxicity studies: All the doses (5, 50, 250, 500 and 2000 mg/kg, p.o.) of MEMORHIS (MEM) did not produce any mortality even with the highest dose (2000 mg/kg, p.o.) employed. Three submaximal doses (50, 100 and 250 mg/kg, p.o.) were selected for further psychopharmacological and biochemical studies. Effect on locomotor activity In the present study, MEMORHIS (50, 100 and 250 mg/kg, p.o.)) did not show any significant

Effect on step down latency (SDL) using passive avoidance paradigm MEMORHIS (50, 100 and 250 mg/kg, p.o.) administered to young and aged mice for consecutive 8 days, showed dose-dependent increase in SDL values as compared to respective control groups (Fig. 3). MEMORHIS (50, 100 and 250 mg/kg, p.o.) also exhibited reversal of amnesia induced by diazepam and scopolamine in young mice (Fig. 4). Effect on brain cholinesterase activity MEMORHIS (50, 100 and 250 mg/kg, p.o.) showed a remarkable reduction in the brain acetyl cholinesterase activity in young and aged mice, as compared to respective control groups. Whereas, phenytoin (12 mg/kg, p.o.) significantly (P< 0.01) increased the acetyl cholinesterase activity.

Treatment Dose (p.o.) mg/kg Number of squares crossed Rearing Normal 1 ml /kg 134 ±6.52 20.5±1.40 Diazepam 0.5 69.5 ± 5.07a 9.33±1.22a MEMORHIS 50 119.23±7.2 15.36±1.8 MEMORHIS 100 124.17±8.84 18.16±0.90 a MEMORHIS 250 53.50±11.60 9.33±0.84a N=6 in each group. Values are expressed as Mean ± SE. p values a <0.001, b<0.05 as compared to normal treated group. Statistical test employed was ANOVA followed by Tukey-Kramer multiple comparison test. Table 1: Effect of on time spent by mice behavior in open field test Global Journal of Research on Medicinal Plants & Indigenous Medicine

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Learning

Transfer Latency (Sec)

Memory

b c

b a

c c

10 5 0 Control Piracetam MEM 50 (Young) (Young) (Young)

MEM 100 MEM 250 Control (Young) (Young) (Aged)

Piracetam MEM 50 (Aged) (Aged)

MEM 100 MEM 250 (Aged) (Aged)

Values are mean ÂąS.E.M. (n=6); * indicates P< 0.01 as compared to control group of young mice; a indicates P< 0.001 as compared to control group of young mice; b indicates P< 0.01 as compared to control group of aged mice; c indicates P< 0.001 as compared to control group of aged mice; (One way ANOVA followed by Tukey-kramer multiple comparison tests)

Fig. 1. Effect of MEMORHIS (MEM, 50, 100 and 250 mg/kg) administered orally for eight successive days on transfer latency of young and aged mice using elevated plus maze. Piracetam (200 mg/kg, i.p.) was used as a standard drug.

Learning Memory

Transfer Latency (Sec)

* 40

c a

c a a

c c d

d d

0 Control (Young)

Dia

Piracetam MEM 50 + Dia + Dia

MEM 100 + Dia

MEM 250 + Dia

Sco

Piracetam MEM 50 + Sco + Sco

MEM 100 MEM 250 + Sco + Sco

Values are mean ÂąS.E.M. (n=6); * indicates P< 0.01 as compared to control group of young mice; a indicates P< 0.01 as compared to diazepam (Dia) group alone; b indicates P< 0.001 as compared to diazepam (Dia) group alone. c indicates P< 0.01 as compared to scopolamine (Sco) group alone; d indicates P< 0.001 as compared to scopolamine (Sco) group alone; (One way ANOVA followed by Tukey-kramer multiple comparison tests)

Fig. 2. Effect of MEMORHIS (MEM, 50, 100 and 250 mg/kg, p.o.) on diazepam (Dia, 1 mg/kg, i.p.) and scopolamine (Sco, 0.4 mg/kg, i.p.) induced amnesia in young mice using elevated plus maze. Piracetam (200 mg/kg, i.p.) was used as a standard drug. Global Journal of Research on Medicinal Plants & Indigenous Medicine

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250 a

Step Down Latency (Sec)

200

* 150

* c

100

c b

0 Control (Young)

Piracetam MEM 50 (Young) (Young)

MEM 100 MEM 250 (Young) (Young)

Control (Aged)

Piracetam MEM 50 MEM 100 MEM 250 (Aged) (Aged) (Aged) (Aged)

Values are mean ÂąS.E.M. (n=6). * indicates P< 0.01 as compared to control group of young mice; a indicates P< 0.001 as compared to control group of young mice. b indicates P< 0.01 as compared to control group of aged mice. c indicates P< 0.001 as compared to control group of aged mice. (One way ANOVA followed by Tukey-kramer multiple comparison tests)

Fig. 3. Effect of MEMORHIS (MEM, 50, 100 and 250 mg/kg) administered orally for eight successive days on step down latency of young and aged mice using passive avoidance apparatus. Piracetam (200 mg/kg, i.p.) was used as a standard drug.

Light and dark box test Diazepam (0.5 mg/kg) significantly increased the time spent in light compartment (P<0.001) compared to normal group (Table 1). Significant increase in the time spent in the light compartment P<0.05 was seen with administration of MEMORHIS (50, 100 and 250 mg/kg, p.o as compared to normal.

Open field test MEMORHIS 250 mg/kg showed good anxiolytic activity as compared with normal mice. There was marked decrease in locomotion activity in animals treated with MEMORHIS (50, 100 and 250 mg/kg, p.o as the number of squares crossed in the perimeter was decreased between the MEMORHIS treated groups and differed significantly from the control groups. The frequency of rearing also decreased significantly (Table 2).

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Treatment

Dose (p.o.) mg/kg

Normal Diazepam MEMORHIS MEMORHIS MEMORHIS

1 ml /kg 0.5 mg/kg 50 100 250

Time spent (sec) in social interaction 38.3 ±3.9 69.16± 1.64a 41.16 ±1.32 48.16±5.51 59.83±1.64b

N=6 in each group. Values are expressed as Mean ± SE. p values a <0.001, b<0.01 as compared to normal treated group. Statistical test employed was ANOVA followed by Tukey-Kramer multiple comparison test. Table 2: Effect of on time spent by mice behavior in social interaction test

200

160

Step Down Latency (Sec)

180

140

120

100 80 60

20 0 Control (Young)

Dia

Piracetam MEM 50 + Dia + Dia

MEM 100 MEM 250 + Dia + Dia

Values are mean ±S.E.M. (n=6). * indicates P< 0.01 as compared to control group of young mice.; b indicates P< 0.001 as compared to diazepam (Dia) group alone; d indicates P< 0.001 as compared to scopolamine (Sco) group alone;

Sco

Piracetam MEM 50 + Sco + Sco

MEM 100 MEM 250 + Sco + Sco

a indicates P< 0.01 as compared to diazepam (Dia) group alone. c indicates P< 0.01 as compared to scopolamine (Sco) group alone. (One way ANOVA followed by Tukey-kramer multiple comparison tests)

Fig. 4. Effect of MEMORHIS (MEM, 50, 100 and 250 mg/kg, p.o.) on diazepam (Dia, 1 mg/kg, i.p.) and scopolamine (Sco, 0.4 mg/kg, i.p.) induced amnesia in young mice using passive avoidance apparatus. Piracetam (200 mg/kg, i.p.) was used as a standard drug.

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250

b AChE activity (µ moles)

200

150

* b

100

* 50

c a

c c

0 Control Phenytoin Piracetam MEM 50 MEM 100 MEM 250 Control (Young) (Young) (Young) (Young) (Young) (Young) (Aged)

Values are mean ±S.E.M. (n=6).; a indicates P< 0.001 as compared to control group of young mice; c indicates P< 0.001 as compared to control group of aged mice;

Phenytoin Piracetam MEM 50 (Aged) (Aged) (Aged)

MEM 100 MEM 250 (Aged) (Aged)

* indicates P< 0.01 as compared to control group of young mice; b indicates P< 0.01 as compared to control group of aged mice; (One way ANOVA followed by Tukey-kramer multiple comparison tests)

Fig. 5. Effect of MEMORHIS (MEM, 50, 100 and 250 mg/kg, p.o.) on brain cholinesterase (AChE) activity of young and aged mice using Ellman’s colorimetric method. Piracetam (200 mg/kg, i.p.) was used as a standard drug. Phenytoin ((12 mg/kg, p.o.) was used as negative control. 2006e). They had also reversed diazepam, scopolamine and ageing-induced impairment in learning and memory in mice (Joshi et al., DISCUSSION Memory loss is often the most disabling 2005). feature of many disorders, impairing the normal Glycyrrhiza glabra and ascorbic acid daily activities of the patients and profoundly were proved to be memory enhancers in earlier affecting their families (Alpesh et al., 2011). studies (Parle et al., 2004; 2003) from our The ancient Ayurvedic physicians had laboratory. MEMORHIS successfully reversed understood the delicate cellular mechanisms of scopolamine, diazepam or ageing-induced the body and the deterioration of the functional amnesia, when administered for successive 8 efficiency of the body tissues. These Ayurvedic days. Piracetam, the established nootropic scientists had thus developed certain dietary agent was used in the present study for and therapeutic measures to delay the ageing comparison because, it improves memory as a process, while rejuvenating functional net result of several protective actions such as dynamics of the body organs. This increased resistance to adverse conditions, revitalization and rejuvenation is known as the brain protection against physical and chemical ‘rasayana chikitsa’ (rejuvenation therapy) injuries and enhancement of reserve energy (Govindarajan et al., 2005). Rasayana drugs act stores. Piracetam also increased choline uptake inside the human body by modulating the in cholinergic nerve endings, thereby facilitating cholinergic transmission. Plant nuero-endocrino-immune systems and have extracts of Zingiber officinale (Joshi et al., been found to be a rich source of antioxidants (Brahma et al., 2003). Brahmi rasayana, 2006), Nardostachys jatamansi (Joshi et al., Trikatu churna were reported to exhibit 2006a), Foeniculum vulgare (Joshi et al., significant decrease in AChE activity in whole 2006b), Hibiscus sabdariffa (Joshi et al., brain homogenates of mice, indicating their 2006c), and Desmodium gangeticum (Joshi et anti-cholinesterase potential (Joshi et al., al., 2006d), Piper nigrum (Joshi et al., 2005) Global Journal of Research on Medicinal Plants & Indigenous Medicine

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have been found to posses nootropic effects and they had significantly lowered the whole brain AChE activity thereby elevating acetylcholine levels in the brain. Piracetam elevated the density of frontal cortex acetylcholine receptors by 30 – 40%, restoring the levels of acetylcholine in the brain (Wang et al., 2012, Wierzbicka-Chmiel et al., 2011, Balaraman et al., 2002). MEMORHIS exhibited highly significant anticholinesterase activity in both and young and aged mice. Thus, it is possible that enhanced cholinergic transmission resulting from increased acetylcholine synthesis in brain due to abundant availability of choline and reduction of brain cholinesterase activity in young and aged mice may explain the memory improving effect exhibited by MEMORHIS.

CONCLUSION MEMORHIS can be of enormous use in the preliminary management of early symptoms of cognitive dysfunctions such as Alzheimer’s disease and dementia. Further investigations using human volunteers are warranted for further confirmation of nootropic potential. The possible involvement of other neurotransmitters like glutamate, GABA, catecholamines, serotonin etc. in the pathogenesis of cognitive disorders. ACKNOWLEDGEMENT The authors are thankful to the management, Sarada vilas educational institutions, Mysore, for the encouragement.

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