Tricuspid regurgitation (TR) is the most frequent valvular complication after heart transplantation with different clinical sequelae. In its most severe form, it can cause right heart failure with a poor long-term prognosis. Its management is complex, both medical, surgical, and percutaneous.
View Article and Find Full Text PDFCRISPR screens are powerful tools to identify key genes that underlie biological processes. One important type of screen uses fluorescence activated cell sorting (FACS) to sort perturbed cells into bins based on the expression level of marker genes, followed by guide RNA (gRNA) sequencing. Analysis of these data presents several statistical challenges due to multiple factors including the discrete nature of the bins and typically small numbers of replicate experiments.
View Article and Find Full Text PDFGene regulatory networks ensure that important genes are expressed at precise levels. When gene expression is sufficiently perturbed, it can lead to disease. To understand how gene expression disruptions percolate through a network, we must first map connections between regulatory genes and their downstream targets.
View Article and Find Full Text PDFK-Ras must interact primarily with the plasma membrane (PM) for its biological activity. Therefore, disrupting K-Ras PM interaction is a tractable approach to block oncogenic K-Ras activity. Here, we found that avicin G, a family of natural plant-derived triterpenoid saponins from Acacia victoriae, mislocalizes K-Ras from the PM and disrupts PM spatial organization of oncogenic K-Ras and H-Ras by depleting phosphatidylserine (PtdSer) and cholesterol contents, respectively, at the inner PM leaflet.
View Article and Find Full Text PDFThe primary site for KRAS signaling is the inner leaflet of the plasma membrane (PM). We previously reported that oxanthroquinone G01 (G01) inhibited KRAS PM localization and blocked KRAS signaling. In this study, we identified acylpeptide hydrolase (APEH) as a molecular target of G01.
View Article and Find Full Text PDFAdvances in high-throughput sequencing have enabled profiling of microRNAs (miRNAs), however, a consensus pipeline for sequencing of small RNAs has not been established. We built and optimized an analysis pipeline using Partek Flow, circumventing the need for analyzing data via scripting languages. Our analysis assessed the effect of alignment reference, normalization method, and statistical model choice on biological data.
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