Epitaxial Electrodeposition of Zinc on Different Single Crystal Copper Substrates for High Performance Aqueous Batteries.

The aqueous zinc metal battery holds great potential for large-scale energy storage due to its safety, low cost, and high theoretical capacity. However, challenges such as corrosion and dendritic growth necessitate controlled zinc deposition. This study employs epitaxy to achieve large-area, dense, and ultraflat zinc plating on textured copper foil.

Exploring the pivotal variables of tongue diagnosis between patients with chronic kidney disease and health participants.

Introduction: Chronic kidney disease (CKD) is a significant global health problem associated with high morbidity and mortality rates. Traditional Chinese Medicine (TCM) utilizes tongue diagnosis to differentiate symptoms and predict prognosis. This study examines the relationship between tongue characteristics and CKD severity using an automatic tongue diagnosis system (ATDS), which captures tongue images non-invasively to provide objective diagnostic information.

Carcinogenic Air Pollutants and Breast Cancer Risk in the Arkansas Rural Community Health Study: A Nested Case-Control Study.

Background: Previous epidemiological studies on the associations between hazardous air pollutants (HAPs) and breast cancer (BC) have largely neglected rural, medically underserved areas in the United States, which differ in exposures and disparities compared to urban areas.

Objectives: We aimed to examine the associations between carcinogenic HAPs and BC risk in a rural population.

Methods: Using a nested case-control design, 574 cases and 2,295 incidence density-sampled controls matched 1:4 on index age and race were included from the Arkansas Rural Community Health study.

Simulating 500 million years of evolution with a language model.

More than three billion years of evolution have produced an image of biology encoded into the space of natural proteins. Here we show that language models trained at scale on evolutionary data can generate functional proteins that are far away from known proteins. We present ESM3, a frontier multimodal generative language model that reasons over the sequence, structure, and function of proteins.

Use of Machine Learning to Predict the Incidence of Type 2 Diabetes Among Relatively Healthy Adults: A 10-Year Longitudinal Study in Taiwan.

: The prevalence of diabetes is increasing worldwide, particularly in the Pacific Ocean island nations. Although machine learning (ML) models and data mining approaches have been applied to diabetes research, there was no study utilizing ML models to predict diabetes incidence in Taiwan. We aimed to predict the onset of diabetes in order to raise health awareness, thereby promoting any necessary lifestyle modifications and help mitigate disease burden.