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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.
September 7, 2026
Biologists Discover 'Molecular Fingerprint' of Preeclampsia
Researchers at HSE University employed a new method to model hypoxia in placental cells during pregnancies complicated by preeclampsia and identified molecular markers of tissue hypoxia. Since hypoxia is one of the key mechanisms underlying preeclampsia, these findings are important for a more accurate and timely diagnosis of the disease and for the development of effective treatment methods. The paper has been published in Placenta.
September 7, 2026
‘Speech, Facial Expressions, and Gestures Cannot Lie
Would you like to know whether a speaker’s trembling voice or an accidental gesture can give them away? At HSE University in Nizhny Novgorod, researchers are developing an algorithm that analyses speech, facial expressions, and gestures, and determines whether information is truthful with 92% accuracy. The project has applications ranging from forensic examination and bank recruitment to fundamental research. Anna Khomenko, head of the research group and Senior Research Fellow at the Centre for Language and Brain at the HSE Faculty of Humanities in Nizhny Novgorod, explains how students and researchers are working together to create a corpus of video recordings, train a classifier, and prepare to introduce computer vision technology.

 

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Fra-2 overexpression upregulates pro-metastatic cell-adhesion molecules, promotes pulmonary metastasis, and reduces survival in a spontaneous xenograft model of human breast cancer

Journal of Cancer Research and Clinical Oncology. 2021. Vol. 148. No. 6. P. 1525–1542.
Arnold S., Cortland J., Maltseva D., Nersisyan S., Tonevitsky A., Struken C.

Purpose:

The transcription factor Fra-2 affects the invasive potential of breast cancer cells by dysregulating adhesion molecules in vitro. Previous results suggested that it upregulates the expression of E- and P-selectin ligands. Such selectin ligands are important members of the leukocyte adhesion cascade, which govern the adhesion and transmigration of cancer cells into the stroma of the host organ of metastasis. As so far, no in vivo data are available, this study was designed to elucidate the role of Fra-2 expression in a spontaneous breast cancer metastasis xenograft model.

Methods:

The effect of Fra-2 overexpression in two stable Fra-2 overexpressing clones of the human breast cancer cell line MDA MB231 on survival and metastatic load was studied after subcutaneous injection into scid and E- and P-selectin deficient scid mice.

Results:

Fra-2 overexpression lead to a significantly shorter overall survival and a higher amount of spontaneous lung metastases not only in scid mice, but also in E- and P-deficient mice, indicating that it regulates not only selectin ligands, but also selectin-independent adhesion processes.

Conclusion:

Thus, Fra-2 expression influences the metastatic potential of breast cancer cells by changing the expression of adhesion molecules, resulting in increased adherence to endothelial cells in a breast cancer xenograft model.

Research target: Basic Medicine Biology
Language: English
Full text
DOI
Text on another site
Keywords: Рак молочной железыBreast cancerTranscription factorsMetastasisметастазированиеAP-1Fra-2транскрипционный факторAP-1Fra-2
Publication based on the results of:
Creation of a metastasis-on-chip microphysiological platform for studying the biology of the tumor process (mathematical modeling) (2021)
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