Comparing exercise determinants between Black and White older adults with heart failure

Abstract Background Heart Failure is a leading cause of mortality among older adults. Engaging in regular exercise at moderate-to-vigorous intensity has been shown to improve survival rates. Theory-informed methodologies have been recommended to promote exercise, but limited application of theoretical framework has been conducted for understanding racial disparities among older adults with heart failure. This study aimed to use the Health Belief Model to compare exercise behavior determinants between Black and White older adults diagnosed with heart failure. Methods The HF-ACTION Trial is a multi-site study designed to promote exercise among individuals with heart failure that randomized participants to an experimental (three months of group exercise sessions followed by home-based training) or control arm. The present study used structural equation modeling to test the change in Health Belief Model constructs and exercise behavior across 12 months among older adults. Results Participants (n = 671) were older adults, 72.28 (SD = 5.41) years old, (Black: n = 230; White, n = 441) diagnosed with heart failure and reduced ejection fraction. The model found perceived benefits, self-efficacy, perceived threats, and perceived barriers to predict exercise behavior among Black and White older adults. However, among these constructs, only perceived benefits and self-efficacy were facilitated via intervention for both races. Additionally, the intervention was effective for addressing perceived barriers to exercise only among White participants. Finally, the intervention did not result in a change of perceived threats for both races. Conclusions Among health belief model constructs, perceived threats and barriers were not facilitated for both races in the experimental arm, and the intervention did not resolve barriers among Black older adults. Racial differences need to be considered when designing interventions for clinical populations as future studies are warranted to address barriers to exercise among Black older adults with heart failure

Protocol to perform integrative analysis of high-dimensional single-cell multimodal data using an interpretable deep learning technique

Summary: The advent of single-cell multi-omics sequencing technology makes it possible for researchers to leverage multiple modalities for individual cells. Here, we present a protocol to perform integrative analysis of high-dimensional single-cell multimodal data using an interpretable deep learning technique called moETM. We describe steps for data preprocessing, multi-omics integration, inclusion of prior pathway knowledge, and cross-omics imputation. As a demonstration, we used the single-cell multi-omics data collected from bone marrow mononuclear cells (GSE194122) as in our original study.For complete details on the use and execution of this protocol, please refer to Zhou et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics