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September 11, 2026
How to Assess Students Knowledge in the Age of AI
A researcher at HSE University has proposed a flowchart to help lecturers decide how to assess students who use artificial intelligence. It shows where the use of AI should be restricted and where it can be incorporated into the learning process. The article has been published in IT Professional.
September 9, 2026
‘Balkan Hospitality Opens Doors: Studying Dialects on the Verge of Extinction
You cannot study spoken dialects from books. Instead, you need to go to a village, seek out its elders, and earn the trust of local residents before you can record hours of spontaneous stories. This is how Natalia Muravleva, Associate Professor at the Faculty of Humanities, conducts her research. Her internship in Serbia continued her long-standing study of dialects spoken by Macedonian settlers. In this interview, she discusses how diaspora cultural centres help researchers reach informants, why native speakers need to be interviewed only in their own language (otherwise, as she puts it, they may 'break'), and how a single field season helped her finalise her monograph. She also shares warm memories of autumn in Belgrade and of colleagues with whom grammar can be discussed in three languages at once.
September 9, 2026
Scientists Train Neural Network to Generate Process Plans from 3D Models
Researchers at the HSE FCS AI and Digital Science Institute have developed CAD2TechSpec, a framework that converts 3D models of mechanical parts into machining process plans—step-by-step instructions for machine tools. The solution aims to reduce the time required for the design and preparation of technical process documentation in mechanical engineering, aircraft manufacturing, and other high-tech industries. The study findings have been published in PeerJ Computer Science.

 

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Atomic-Scale Molecular Dynamics Simulations of DNA-Polycation Complexes: Two Distinct Binding Patterns.

Journal of Physical Chemistry B. 2016.
Kondinskaia D., Kostritskii A., Antipina A., Nesterenko A., Gurtovenko A.

Synthetic cationic polymers represent a promising class of delivery vectors for gene therapy. Here, we employ atomistic molecular dynamics simulations to gain insight into the structure and properties of complexes of DNA with four linear polycations: polyethylenimine (PEI), poly-l-lysine (PLL), polyvinylamine (PVA), and polyallylamine (PAA). These polycations differ in their polymer geometries, protonation states, and hydrophobicities of their backbone chains. Overall, our results demonstrate for the first time the existence of two distinct patterns of binding of DNA with polycations. For PEI, PLL, and PAA, the complex is stabilized by the electrostatic attraction between protonated amine groups of the polycation and phosphate groups of DNA. In contrast, PVA demonstrates an alternative binding pattern as it gets embedded into the DNA major groove. It is likely that both the polymer topology and affinity of the backbone chain of PVA to the DNA groove are responsible for such behavior. The differences in binding patterns can have important biomedical implications: embedding PVA into a DNA groove makes it less sensitive to changes in the aqueous environment (pH level, ionic strength, etc.) and could therefore hinder the intracellular release of genetic material from a delivery vector, leading to lower transfection activity.

Language: English
DOI
Keywords: geneticspolymersReaction mechanismspolyethylenimine
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