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https://www.selleckchem.com/products/on123300.html During mitotic chromosome segregation, the protease separase severs cohesin between sister chromatids. A probe for separase activity has shown that separase undergoes abrupt activation shortly before anaphase onset, after being suppressed throughout metaphase; however, the relevance of this control remains unclear. Here, we report that separase activates precociously, with respect to anaphase onset, during prolonged metaphase in multiple types of cancer cell lines. The artificial extension of metaphase in chromosomally stable diploid cells leads to precocious activation and, subsequently, to chromosomal bridges in anaphase, which seems to be attributable to incomplete cohesin removal. Conversely, shortening back of a prolonged metaphase restores the activation of separase and ameliorates anaphase bridge formation. These observations suggest that retarded metaphase progression affects the separase activation profile and its enzymatic proficiency. Our findings provide an unanticipated etiology for chromosomal instability in cancers and underscore the relevance of swift mitotic transitions for fail-safe chromosome segregation.It is well known that the development of drug resistance in cancer cells can lead to changes in cell morphology. Here, we describe the use of deep neural networks to analyze this relationship, demonstrating that complex cell morphologies can encode states of signaling networks and unravel cellular mechanisms hidden to conventional approaches. We perform high-content screening of 17 cancer cell lines, generating more than 500 billion data points from ∼850 million cells. We analyze these data using a deep learning model, resulting in the identification of a continuous 27-dimension space describing all of the observed cell morphologies. From its morphology alone, we could thus predict whether a cell was resistant to ErbB-family drugs, with an accuracy of 74%, and predict the potential mechanism of re

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