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Indeed, EGR-1 was found to contribute to the pathogenesis of atherosclerosis [123], stenosed calcific valvular disease [124], and cardiac hypertrophy [125,126]

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feet per gallon vary based on surface porosity and the number of coats required to produce the desired effect

We recently developed a novel machine learning technique, the robust support vector machine (rSVM), that can achieve highly accurate classification in the face of data uncertainty from noise in training data, ubiquitous in clinical research.[1] Methods: We used the rSVM to classify participants as having manifest/nonmanifest HD based on UHDRS motor subscores, with observerrated DCL classifications forming the reference standard