The "Mammograms Available Due to Resources and Education" (MADRE) Study: Rationale and Design.

Background: Latinas suffer disproportionately from breast cancer, partially due to lower uptake of guideline-concordant breast cancer screening. We describe the design of a study to compare two approaches addressing this important public health problem.

Design/methods: We are conducting a 5-year randomized controlled trial.

Biochemical and neurophysiological effects of deficiency of the mitochondrial import protein TIMM50.

TIMM50, an essential TIM23 complex subunit, is suggested to facilitate the import of ~60% of the mitochondrial proteome. In this study, we characterized a disease-causing mutation in human fibroblasts and noted significant decreases in TIM23 core protein levels (TIMM50, TIMM17A/B, and TIMM23). Strikingly, TIMM50 deficiency had no impact on the steady-state levels of most of its putative substrates, suggesting that even low levels of a functional TIM23 complex are sufficient to maintain the majority of TIM23 complex-dependent mitochondrial proteome.

Molecular Characteristics and Processing Technologies of Dairy Products from Non-Traditional Species.

Non-bovine dairy animals, commonly referred to as non-traditional dairy species, include goats, sheep, yaks, buffalo, donkeys, alpacas, llamas, and other less commonly farmed species. These animals have been integral to livestock systems since ancient times, providing milk and other essential products. Despite their historical significance, dairy production from many of these species remains predominantly confined to rural areas in developing countries, where scientific advancements and technical improvements are often limited.

A novel, machine-learning model for prediction of short-term ASCVD risk over 90 and 365 days.

Background: Current atherosclerotic cardiovascular disease (ASCVD) risk assessment tools like the Pooled Cohort Equations (PCEs) and PREVENT™ scores offer long-term predictions but may not effectively drive behavior change. Short-term risk predictions using mobile health (mHealth) data and electronic health records (EHRs) could enhance clinical decision-making and patient engagement. The aim of this study was to develop a short-term ASCVD risk prediction model for hypertensive individuals using mHealth and EHR data and compare its performance to existing risk assessment tools.