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News
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.
June 5, 2026
‘In the Age of Technology, It Is Interesting to Look into the Past and Think about What We Can Take from It
Polina Tabakova decided to apply for a Philology degree at HSE in Nizhny Novgorod because she grew up in Mari El and did not want to move far away from the Russian forests. In an interview for the Young Scientists of HSE University project, she spoke about the genre of the campus novel, the existential drama of Kolobok, and a blackout version of Eugene Onegin.
June 5, 2026
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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First vertebrate BRICHOS antimicrobial peptides: β-hairpin host defense peptides in limbless amphibia lung resemble those of marine worms

Biochemical and Biophysical Research Communications. 2024. Vol. 712-713. Article 149913.
Smetanin R., Sukhareva M., Vladimirova E., Zharkova M., Mikushina A., Komlev A., Khaydukova M., Filatenkova T., Kalganova A., Pipiya S., Terekhov S., Orlov D., Shamova O., Igor E. Eliseev

Innate immunity of invertebrates offers potent antimicrobial peptides (AMPs) against drug-resistant infections. To identify new worm β-hairpin AMPs, we explored the sequence diversity of proteins with a BRICHOS domain, which comprises worm AMP precursors. Strikingly, we discovered new BRICHOS AMPs not in worms, but in caecilians, the least studied clade of vertebrates. Two precursor proteins from Microcaecilia unicolorand Rhinatrema bivittatum resemble SP-C lung surfactants and bear worm AMP-like peptides at C-termini. The analysis of M. unicolor tissue transcriptomes shows that the AMP precursor is highly expressed in the lung along with regular SP-C, suggesting a different, protective function. The peptides form right-twisted β-hairpins, change conformation upon lipid binding, and rapidly disrupt bacterial membranes. Both peptides exhibit broad-spectrum activity against multidrug-resistant ESKAPE pathogens with 1–4 μM MICs and remarkably low toxicity, giving 40–70-fold selectivity towards bacteria. These BRICHOS AMPs, previously unseen in vertebrates, reveal a novel lung innate immunity mechanism and offer a promising antibiotics template.

Research target: Biology Basic Medicine
Language: English
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Keywords: antibiotic resistanceantimicrobial peptidesBRICHOS domainβ-hairpin peptidesCaeciliansPeptide discoveryPulmonary surfactant SP-C
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