INTEGRATING MACHINE LEARNING MODELS WITH MULTI-OMICS ANALYSIS TO DECIPHER THE PROGNOSTIC SIGNIFICANCE OF MITOTIC CATASTROPHE HETEROGENEITY IN BLADDER CANCER

Integrating machine learning models with multi-omics analysis to decipher the prognostic significance of mitotic catastrophe heterogeneity in bladder cancer

Abstract Background Mitotic catastrophe is well-known as a major pathway of endogenous tumor death, but the prognostic significance of its heterogeneity regarding bladder cancer (BLCA) remains unclear.Methods Our study focused on digging deeper into the TCGA and GEO databases.Through differential expression analysis as well as Weighted Gene Co-expr

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GESTATIONAL DIABETES MELLITUS: A MODERN VIEW ON THE ACTUAL PROBLEM

A review of world literature has shown that gestational diabetes mellitus (GDM) is the most frequently encountered extra genital pathology of gestation and represents a serious medical and social problem, increasing the incidence of unwanted pregnancy outcomes for both the mother and the fetus.Significant variability of opinions on the frequency ka

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Distribution of phytoliths in plants: a review

Phytoliths are ergastic siliceous substances present abundantly within intercellular spaces as well as inside the cells of numerous plants.Being made up of silica, they are nondegradable and hence found preserved as microfossils in various substrata.This property of phytoliths extends its significance in the field of paleobotany, kaiser copy stands

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