Ythdf2 regulates cardiac remodeling through its mRNA target transcripts.

m6A mRNA methylation controls cardiomyocyte function and increased overall m6A levels are a stereotyping finding in heart failure independent of the underlying etiology. However, it is largely unknown how the information is read by m6A reader proteins in heart failure. Here we show that the m6A reader protein Ythdf2 controls cardiac function and identified a novel mechanism how reader proteins control gene expression and cardiac function. Deletion of Ythdf2 in cardiomyocytes in vivo leads to mild cardiac hypertrophy, reduced heart function, and increased fibrosis during pressure overload as well as during aging. Similarly, in vitro the knockdown of Ythdf2 results in cardiomyocyte growth and remodeling. Mechanistically, we identified the eucaryotic elongation factor 2 as post-transcriptionally regulated by Ythdf2 using cell type specific Ribo-seq data. Our study expands our understanding on the regulatory functions of m6A methylation in cardiomyocytes and how cardiac function is controlled by the m6A reader protein Ythdf2.

The cardiac Fas (APO-1/CD95) Receptor/Fas ligand system : relation to diastolic wall stress in volume-overload hypertrophy in vivo and activation of the transcription factor AP-1 in cardiac myocytes.

BACKGROUND: Fas (APO-1/CD95) is a transmembrane receptor belonging to the tumor necrosis factor receptor superfamily. Cross-linking of Fas by Fas ligand (FasL), a tumor necrosis factor-alpha-related cytokine, promotes apoptosis and/or transcription factor activation in a highly cell-type-specific manner. The biological consequences of Fas activation in cardiomyocytes and the regulation of Fas and FasL abundance in the myocardium in vivo remain largely unknown. METHODS AND RESULTS: As shown by immunohistochemistry, Fas was expressed on the sarcolemma of cardiomyocytes in left ventricular tissue sections. Moreover, FasL was constitutively expressed in the myocardium and in isolated cardiomyocytes, as revealed by reverse transcription polymerase chain reaction and Western blotting. Left ventricular abundance of Fas but not FasL was upregulated in a rat model of compensated volume-overload hypertrophy and was closely related to diastolic but not systolic wall stress as determined by MRI. Cardiomyocyte apoptosis was not enhanced in volume-overload hypertrophy despite the increased expression of Fas and the presence of FasL in the myocardium. Moreover, injection of mice with an agonistic anti-Fas antibody promoted hepatocyte but not cardiomyocyte apoptosis in vivo. Stimulation of isolated cardiomyocytes with recombinant FasL promoted an activation of the transcription factor AP-1 as shown by electrophoretic mobility shift assays but did not induce cell death. CONCLUSIONS: Fas and FasL are constitutively expressed in the myocardium and in cardiomyocytes. Myocardial expression of Fas is closely related to diastolic loading conditions in vivo. Signaling pathways emanating from Fas are coupled to an activation of the transcription factor AP-1 in cardiomyocytes.

An integer programming model to limit hospital selection in studies with repeated sampling.

OBJECTIVE: We describe an integer programming model that, for studies requiring repeated sampling from hospitals, can aid in selecting a limited set of hospitals from which medical records are reviewed. STUDY SETTING: The model is illustrated in the context of two studies: (1) an analysis of the relationship between variations in hospital admission rates across geographic areas and rates of inappropriate admissions; and (2) a validation of computerized algorithms that screen for complications of hospital care. STUDY DESIGN: Common characteristics of the two studies: (1) hospitals are classified into categories, e.g., high, medium, and low; (2) the classification process is repeated several times, e.g., for different medical conditions; (3) medical records are selected separately for each iteration of the classification; and (4) for budgetary and logistical reasons, reviews must be concentrated in a relatively small subset of hospitals. DATA COLLECTION/EXTRACTION METHODS. In each study, hospitals are ranked based on analysis of hospital discharge abstract data. CONCLUSIONS: The model is useful for identifying a subset of hospitals at which more intensive reviews will be conducted.