首页|Data on Cancer Reported by Joaquim Pombo and Colleagues (Detection of senescence using machine learning algorithms based on nuclear features)
Data on Cancer Reported by Joaquim Pombo and Colleagues (Detection of senescence using machine learning algorithms based on nuclear features)
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New research on Cancer is the subject of a report. According to news reporting originating in London, United Kingdom, by NewsRx journalists, research stated, “Cellular senescence is a stress response with broad pathophysiological implications. Senotherapies can induce senescence to treat cancer or eliminate senescent cells to ameliorate ageing and age-related pathologies.” The news reporters obtained a quote from the research, “However, the success of senotherapies is limited by the lack of reliable ways to identify senescence. Here, we use nuclear morphology features of senescent cells to devise machine-learning classifiers that accurately predict senescence induced by diverse stressors in different cell types and tissues. As a proof-of-principle, we use these senescence classifiers to characterise senolytics and to screen for drugs that selectively induce senescence in cancer cells but not normal cells. Moreover, a tissue senescence score served to assess the efficacy of senolytic drugs and identified senescence in mouse models of liver cancer initiation, ageing, and fibrosis, and in patients with fatty liver disease.”
LondonUnited KingdomEuropeAlgorithmsCancerCyborgsEmerging TechnologiesHealth and MedicineMachine LearningOncology
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