16 research outputs found

    CIDEA Regulates De Novo Fatty Acid Synthesis in Bovine Mammary Epithelial Cells by Targeting the AMPK/PPARγ Axis and Regulating SREBP1

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    Cell-death-inducing DNA fragmentation factor-α-like effector A (CIDEA) is a lipid-droplet-associated protein that helps to promote lipid metabolism in adipocytes of mice and humans. However, studies on the regulatory mechanism of CIDEA on lipid metabolism in the mammary glands of dairy cows are rare. Therefore, the role of CIDEA in bovine mammary epithelial cells (bMECs) was investigated in this study. The CIDEA expression levels in the mammary glands of high-fat-milk-producing cows were significantly higher compared to those in low-fat-milk-producing cows. Results of in vitro studies in bMECs showed that the inhibition of CIDEA inhibited the expression of fatty acid synthesis-related genes and triglyceride (TAG) synthesis-related genes. Conversely, the overexpression of CIDEA leads to an increase in the content of TAG and fatty acid. The results of mechanistic studies indicated that the overexpression of CIDEA inhibits AMP-activated protein kinase (AMPK) activity, which enhances the expression of peroxisome proliferator-activated receptor-γ (PPARγ) and consequently increases the TAG content. Furthermore, the overexpression of CIDEA promoted the nuclear translocation of sterol regulatory element-binding protein 1 (SREBP1). Therefore, a theoretical framework is provided by this study for the regulation of lipid metabolism in dairy cows by means of nutrition and the hormone targeting of CIDEA

    Can We Predict Individual Combined Benefit and Harm of Therapy? Warfarin Therapy for Atrial Fibrillation as a Test Case

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    <div><p>Objectives</p><p>To construct and validate a prediction model for individual combined benefit and harm outcomes (stroke with no major bleeding, major bleeding with no stroke, neither event, or both) in patients with atrial fibrillation (AF) with and without warfarin therapy.</p><p>Methods</p><p>Using the Kaiser Permanente Colorado databases, we included patients newly diagnosed with AF between January 1, 2005 and December 31, 2012 for model construction and validation. The primary outcome was a prediction model of composite of stroke or major bleeding using polytomous logistic regression (PLR) modelling. The secondary outcome was a prediction model of all-cause mortality using the Cox regression modelling.</p><p>Results</p><p>We included 9074 patients with 4537 and 4537 warfarin users and non-users, respectively. In the derivation cohort (n = 4632), there were 136 strokes (2.94%), 280 major bleedings (6.04%) and 1194 deaths (25.78%) occurred. In the prediction models, warfarin use was not significantly associated with risk of stroke, but increased the risk of major bleeding and decreased the risk of death. Both the PLR and Cox models were robust, internally and externally validated, and with acceptable model performances.</p><p>Conclusions</p><p>In this study, we introduce a new methodology for predicting individual combined benefit and harm outcomes associated with warfarin therapy for patients with AF. Should this approach be validated in other patient populations, it has potential advantages over existing risk stratification approaches as a patient-physician aid for shared decision-making</p></div

    Table_1_Transfer RNA-derived small RNAs and their potential roles in the therapeutic heterogeneity of sacubitril/valsartan in heart failure patients after acute myocardial infarction.docx

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    BackgroundIt has been reported that sacubitril/valsartan can improve cardiac function in acute myocardial infarction (AMI) patients complicated by heart failure (HF). However, a number of patients cannot be treated successfully; this phenomenon is called sacubitril/valsartan resistance (SVR), and the mechanisms remain unclear.MethodsIn our present research, the expression profiles of transfer RNA (tRNA)-derived small RNAs (tsRNAs) in SVR along with no sacubitril/valsartan resistance (NSVR) patients were determined by RNA sequencing. Through bioinformatics, quantitative real-time PCR (qRT-PCR), and cell-based experiments, we identified SVR-related tsRNAs and confirmed their diagnostic value, predicted their targeted genes, and explored the enriched signal pathways as well as regulatory roles of tsRNAs in SVR.ResultsOur research indicated that 36 tsRNAs were upregulated and that 21 tsRNAs were downregulated in SVR. Among these tsRNAs, the expression of tRF-59:76-Tyr-GTA-2-M3 and tRF-60:76-Val-AAC-1-M5 was upregulated, while the expression of tRF-1:29-Gly-GCC-1 was downregulated in the group of SVR. Receiver operating characteristic (ROC) curve analysis demonstrated that these three tsRNAs were potential biomarkers of the therapeutic heterogeneity of sacubitril/valsartan. Moreover, tRF-60:76-Val-AAC-1-M5 might target Tnfrsf10b and Bcl2l1 to influence the observed therapeutic heterogeneity through the lipid and atherosclerosis signaling pathways.ConclusionHence, tsRNA might play a vital role in SVR. These discoveries provide new insights for the mechanistic investigation of responsiveness to sacubitril/valsartan.</p