Development and validation of an interpretable machine learning model for predicting left atrial thrombus or spontaneous echo contrast in non-valvular atrial fibrillation patients.

PurposeLeft atrial thrombus or spontaneous echo contrast (LAT/SEC) are widely recognized as significant contributors to cardiogenic embolism in non-valvular atrial fibrillation (NVAF).This study aimed to construct and validate an interpretable predictive model of LAT/SEC risk in NVAF patients using machine learning (ML) methods.MethodsElectronic me

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Evolution of vacuolar proton pyrophosphatase domains and volutin granules: clues into the early evolutionary origin of the acidocalcisome

Abstract Background Volutin granules appear to be universally distributed and are morphologically and chemically identical to acidocalcisomes, which are electron-dense granular organelles rich in calcium and phosphate, whose functions include storage of phosphorus and various metal ions, metabolism of polyphosphate, maintenance of intracellular pH,

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