Professors Publish in Prestigious Nature Communications

AARON J. WOLFE, research professor in the Lewis School of Health Sciences and the chief science officer of Ichor Life Sciences — an industry partner of Clarkson — co-published “Disentangling the recognition complexity of a protein hub using a nanopore,” citing implications in medical diagnostics, including earlier detection of diseases and resulting in a better prognosis for patients.

As its name implies, a nanopore is a nanometer-sized pore that can be used as a single-molecule detector. Here the detection of proteins is pushed to the extreme where each interaction can be counted and analyzed individually.

The manuscript describes the study of the development and validation of a protein nanopore that can detect and count a repeat protein called “WD40 repeat protein 5,” which is involved in the formation of chromosomes. This nanopore sensor used in the research detects the biomarker of mixed lineage leukemia.

“This research clearly allows us to envision a tool at the forefront of protein-based diagnostics for cancers and other diseases,” says Wolfe. “We at Ichor feel that this collaboration is a strong testament to what is possible when the barriers between academic and industrial sciences are reduced.”

ERIK BOLLT, W. Jon Harrington Professor of Mathematics and professor of electrical and computer engineering, and his co-authors at The Ohio State University published their research on “Next generation reservoir computing” or NG-RC.

Reservoir computing (RC) is a machine learning algorithm developed in the early 2000s used to solve extremely complex computing problems. It mimics how the human brain works and allows scientists to tackle some of the most complex information processing problems.

RC is a variation of deep learning where most of the internal weights are selected randomly rather than the usual computationally intensive training phase required of most neural network methods. Nonetheless, the reservoir computing approach can perform on par with the standard fully trained neural networks. However, it was long an open question as to how and why a random method could work so well.

Bollt and his team have further developed a next generation version of NG-RC, which will make standard reservoir computing work much more efficiently — up to millions of times faster — but requires significantly fewer computing resources and less data input.

Chemical and Biomedical Science Professors OLEH SMUTOK, EVGENY KATZ and ARTEM MELMAN (d. November 25, 2021) co-published, with a team of Australian scientists led by Kirill Alexandrov of Queensland University of Technology, a paper titled “Design of a methotrexate-controlled chemical dimerization system and its use in bio-electronic devices.” The paper reports on a novel artificial enzyme produced by genetic engineering that can be activated with drug (methotrexate) molecules. The artificial enzyme was immobilized at an electrode surface and used for drug biosensing with extremely high sensitivity and specificity.

In addition, the study is highly relevant for practical biomedical applications. Methotrexate is a toxic drug used in anti-cancer chemotherapy, and its overdose has serious, life-threatening side effects. Thus, the methotrexate analysis in biological fluids is important for keeping the drug at the optimal concentration. The study opens future options for biomedical applications of the developed biosensor and possibilities for other biosensing systems based on the same concept.

The research team has operated for several years with over $1 million in grants from the Human Frontier Science Program and the U.S. Department of Defense.

Wolfe

Bollt

Smutok

Katz

Melman