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News
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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Murine models of colorectal cancer: the azoxymethane (AOM)/dextran sulfate sodium (DSS) model of colitis-associated cancer

PeerJ. 2023. Vol. 11. Article e16159.
Dzhalilova D., Zolotova N., Fokichev N., Makarova O.

Background

Colorectal cancer (CRC) is the third most common cancer. It is a heterogeneous disease, including both hereditary and sporadic types of tumors. CRC results from complex interactions between various genetic and environmental factors. Inflammatory bowel disease is an important risk factor for developing CRC. Despite growing understanding of the CRC biology, preclinical models are still needed to investigate the etiology and pathogenesis of the disease, as well as to find new methods of treatment and prevention.

Objectives

The purpose of this review is to describe existing murine models of CRC with a focus on the models of colitis-associated CRC. This manuscript could be relevant for experimental biologists and oncologists.

Methodology

We checked PubMed and Google from 01/2018 to 05/2023 for reviews of CRC models. In addition, we searched PubMed from 01/2022 to 01/2023 for articles using the azoxymethane (AOM)/dextran sulfate sodium (DSS) CRC model.

Results

Existing murine models of CRC include spontaneous, genetically engineered, transplantation, and chemically induced models. For the study of colitis-associated cancer (CAC), the AOM/DSS model is predominantly used. This model is very similar in histological and molecular characteristics to the human CAC, and is highly reproducible, inexpensive, and easy to use. Despite its popularity, the AOM/DSS model is not standardized, which makes it difficult to analyze and compare data from different studies.

Conclusions

Each model demonstrates particular advantages and disadvantages, and allows to reproduce different subtypes or aspects of the pathogenesis of CRC.

Research target: Biology Medical Biotechnologies
Language: English
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DOI
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Keywords: gastroenterologyгастроэнтерологияoncologyонкологияклеточная биологияpathologyCancer cell biology
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