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June 4, 2026
Machine Learning Models Can Help Reduce Volatility and Boost Stock Market Returns
The use of machine learning models makes it possible to achieve greater accuracy in predicting risks in the Russian stock market compared to classical econometric approaches. The predictive power of these models increases by 23%, while the average investor’s return can reach up to 13% per annum. These conclusions were drawn by Nikita Lysenok from the Department of Financial Market Infrastructure at the HSE Faculty of Economic Sciences. The paper has been published in Fundamental and Applied Mathematics.
June 3, 2026
Pocket Money, Personal Interest, and Family Practices: What Shapes Students Economic Literacy?
University students' economic literacy depends not only on their field of study but also on their interest in economics, the learning environment, and family financial practices. For example, students who received pocket money irregularly tend to perform better on economic literacy tests than their peers who received financial support on a regular basis. These findings come from a study conducted by HSE University involving more than 1,100 students from five Russian universities. The findings have been published in Cakrawala Pendidikan.
June 3, 2026
Creative Work as a Remedy for Burnout
The creative, supportive atmosphere and innovative methods at the Centre for Sociocultural Research make it appealing to early-career scholars. Over years of working at HSE University, they grow into researchers and lecturers recognised both in Russia and abroad. Chief Research Fellow Zarina Lepshokova and Leading Research Fellow Ekaterina Bushina spoke about their journey at the centre and at HSE, their research, and the role of mentors in their academic success.

 

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Prevention of tumor growth driven by PIK3CA and HPV oncogenes by targeting mTOR signaling with metformin in oral squamous carcinomas expressing OCT3

Cancer Prevention Research. 2015. Vol. 8. No. 3. P. 197–207.
Madera D., Vitale-Cross L., Martin D., Schneider A., Molinolo A., Gangane N., Carey T., McHugh J., Komarck C., Walline H., William, Jr. W., Seethala R., Ferris R., Gutkind J. S.

Most head and neck squamous cell carcinomas (HNSCC) exhibit a persistent activation of the PI3K-mTOR signaling pathway. We have recently shown that metformin, an oral antidiabetic drug that is also used to treat lipodystrophy in HIV-infected (HIV+) individuals, diminishes mTOR activity and prevents the progression of chemically-induced experimental HNSCC premalignant lesions. Here, we explored the preclinical activity of metformin in HNSCCs harboring PIK3CA mutations and HPV oncogenes, both representing frequent HNSCC alterations, aimed at developing effective targeted preventive strategies.

The biochemical and biological effects of metformin were evaluated in representative HNSCC cells expressing mutated PIK3CA or HPV oncogenes (HPV+). The oral delivery of metformin was optimized to achieve clinical relevant blood levels. Molecular determinants of metformin sensitivity were also investigated, and their expression levels examined in a large collection of HNSCC cases.

We found that metformin inhibits mTOR signaling and tumor growth in HNSCC cells expressing mutated PIK3CA and HPV oncogenes, and that these activities require the expression of organic cation transporter 3 (OCT3/SLC22A3), a metformin uptake transporter. Co-expression of OCT3 and the mTOR pathway activation marker pS6 were observed in most HNSCC cases, including those arising in HIV+ patients.

Activation of the PI3K-mTOR pathway is a widespread event in HNSCC, including HPV− and HPV+ lesions arising in HIV+ patients, all of which co-express OCT3. These observations may provide a rationale for the clinical evaluation of metformin to halt HNSCC development from precancerous lesions, including in HIV+ individuals at risk of developing HPV-associated cancers.

Research target: Basic Medicine Biology
Language: English
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Keywords: HIVcancer preventionmTORmetforminHPV
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