New way of screening toxic chemicals mimics mammal senses

Researchers from our University have developed a new approach for analysing toxic chemicals in complex samples that mimics the way mammals smell and taste.

The technique could reduce the need for laboratory animals in biomedical research and other areas of chemical testing.

In the study a fluorescent assay combines a mixture of environmental-sensitive fluorescent dyes and human skin cells that generate fluorescence spectra patterns distinctive for particular physiological conditions. Using multivariate data analysis, the optical signal is further processed, providing qualitative information and fast diagnostics.

The study, which is supported by the Dr Hadwen Trust, was originally inspired by the operating principle of the electronic noses and tongues systems which mimic mammalian smell and taste recognition, combining semi-specific sensors and chemometric techniques for monitoring biochemical processes.

Alexander Gorban, Professor of Applied Mathematics in the Department of Mathematics at the University of Leicester, said: “Firstly, we represented each signal by its projections on other signals. Secondly, we applied the classical and very popular model reduction method, Principal Component Analysis, and found five main components of the signals.

“Then we used dozens of various linear and nonlinear data analysis methods for the five-dimensional signals and validate the classifiers on the previously unseen data. Our approach can be considered as ‘explicit deep learning’, an explicit version of widely popularized (implicit) deep learning algorithms.”

Sergey Piletsky, Professor of Bioanalytical Chemistry in the Department of Chemistry, said: “The latest finding is a big step not only in toxicology, providing a modern, inexpensive and more efficient in vitro method but also in development of sensor assays for rapid quantification of a wide range of analytes which has always been a great challenge faced by analytical scientists."

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