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June 5, 2026
Neural Network Maps as a Method for Constructing Mathematical Models
Scientists from HSE University–Nizhny Novgorod and the Institute of Physics Belgrade, Serbia, are jointly exploring the application of machine learning techniques and neural networks to the study of nonlinear dynamics. Natalya Stankevich, Leading Research Fellow at the Laboratory of Topological Methods in Dynamics of the Faculty of Informatics, Mathematics, and Computer Science at HSE University–Nizhny Novgorod, spoke to the HSE News Service about this international project.
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HSE Scientists Develop Method to Compress Large Language Models Without Losing Quality
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed a new compression method for large language models such as GPT and LLaMA that reduces their size by 25–36% without additional training or significant loss of accuracy. This is the first approach to use mathematical transformations—specifically, rotations of model weights—to make models more amenable to compression with structured matrices. The study results have been published in ACL Findings 2025. The code is available on GitHub.

 

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The Gene Expression of Proteins Involved in Intercellular Signaling and Neurodegeneration in the Substantia Nigra in a Mouse Subchronic Model of Parkinson’s Disease

International Journal of Molecular Sciences. 2023. Vol. 24. No. 3. Article 3027.
Kolacheva A., Pavlova E., Bannikova A., Bogdanov V., Troshev D., Ugrumov M.

Given the limited access to clinical material for studying the pathogenesis of Parkinson's disease (PD), these studies should be carried out on experimental models. We have recently developed a subchronic model of the progressive development of PD with a gradual transition from the preclinical (asymptomatic) stage to the clinical (symptomatic) one. The aim of this study was to evaluate changes in the expression of a wide range of genes in the substantia nigra (SN), the central link in the regulation of motor function, in mice in our subchronic model of PD. We have found changes in the expression of a number of genes encoding enzymes involved in the synthesis and degradation of dopamine as well as proteins involved in the vesicular cycle, axonal transport, protein degradation in the proteasome system, neuroinflammation, and cell death in the SN of our mouse model of the clinical stage of PD. Similar changes in gene expression were previously demonstrated in patients (postmortem), indicating good reproducibility of PD in our model. Further analysis of the gene expression in the SN of mice has shown that the expression of some genes also changes in the model of the preclinical stage, when dopaminergic neurons have not yet died. Thus, this study opens up broad prospects for further evaluation of the molecular mechanisms of PD pathogenesis and the development of a test system for drug screening.

Research target: Medical Biotechnologies
Language: English
DOI
Text on another site
Keywords: Parkinson’s diseaseGene expression dopaminergic neuronsneurodegenerationsubstantia nigra
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