Our study explores the complex dynamics of the integrated stress response (ISR) axis, highlighting PIM2 kinase's critical role and its interaction with the BCL2 protein family, uncovering key mechanisms of cell survival and tumor progression. Elevated PIM2 expression, a marker of various cancers, often correlates with disease aggressiveness. Using a model of normal and malignant plasma cells, we show that inhibiting PIM2 kinase inhibits phosphorylated BAD production and activates ISR-mediated NOXA expression.
View Article and Find Full Text PDFThe role of vitamin D in regulating calcium metabolism and skeletal growth and disease is widely recognized. Indeed, current recommendations for serum vitamin D concentrations are based on these parameters. A serum vitamin D <20 ng/mL is considered deficient, concentrations between 20 and 30 ng/mL are insufficient, and >30 ng/mL is adequate.
View Article and Find Full Text PDFBackground: The Prostate Imaging-Reporting and Data System (PI-RADS) calls for reporting the prostate index lesion and the location within the transition (TZ) or peripheral zone (PZ) and location on a corresponding sector map. The aim of this study was to train a deep learning DL-based algorithm for automatic prostate sector mapping and to validate its' performance.
Methods: An automatic 24-sector grid-map (ASG) of the prostate was developed, based on an automatic zone-specific deep learning segmentation of the prostate.
Introduction: Early radical cystectomy (eRC) can be performed for high or very high risk non-muscle-invasive bladder cancer (NMIBC). Whether immediate eRC is beneficial is still unclear. The objective of this study was to compare outcomes between immediate eRC, delayed eRC and radical cystectomy (RC) at diagnosis of muscle-invasive bladder cancer (MIBC).
View Article and Find Full Text PDFPrevious models of depression outcomes have been limited by symptom heterogeneity within populations. This study conducted a retrospective analysis using latent growth mixture models to identify heterogeneous trajectories within a clinical population, subsequently developing machine learning models to predict clinical outcomes based on baseline characteristics and symptom measures. The study analyzed approximately 15,000 clients aged 18-89 in a real-world clinical setting, treated for up to 180-days between 2015 and 2020.
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