Apoptotic extracellular vesicles (ApoEVs), natural bilayer nanoparticles released during programmed cell death, have emerged as pivotal regulators and promising therapeutic agents for bone regeneration. They function as innate multimodal signaling en... read more
OBJECTIVES: To develop and validate an interpretable machine learning (ML) model for early prediction of peri-implant mucositis (PIM). MATERIAL AND METHODS: This retrospective study enrolled patients receiving dental implants between October 2011 to ... read more
Ultrasensitive detection of low-abundance protein biomarkers is essential for early disease diagnosis and therapeutic monitoring. While droplet digital enzyme-linked immunosorbent assay (ddELISA) addresses this need by enabling attomolar sensitivity,... read more
Warnings of pathogens manufactured to target a specific ethnic group, so-called genetic bioweapons, have recently received considerable media attention. Genetic bioweapons figure prominently in reports on potential future risks emerging from combinin... read more
With the vigorous development of artificial intelligence and the semiconductor industry, the treatment of a mass of copper- and fluorine-containing industrial wastewater poses a challenge to the sustainable development of human society and the enviro... read more
Journal of chemical information and modeling
Apr 5, 2026
Accurate prediction of proton dissociation constants (pKa) is essential for downstream drug discovery and molecular modeling workflows. While several proprietary pKa prediction tools have been established as popular choices in the field, open-source ... read more
INTRODUCTION: Non-invasive neuromodulation techniques like repetitive transcranial magnetic stimulation (rTMS) have shown promise in treating psychopathology. However, emerging evidence suggests that the brain's functional state during stimulation ma... read more
BACKGROUND: Neurologists have a significant challenge due to the progressive nature of Alzheimer's disease (AD) and its severe effects on cognitive function. Recent advances in neuroimage analysis have opened the door to novel machine-learning techni... read more
BACKGROUND: Frailty is common among individuals with cardiovascular disease (CVD) and is a strong predictor of adverse outcomes. Machine learning (ML) methods have been applied independently in CVD research for risk prediction and in frailty research... read more
Cardiovascular disease (CVD) is a major comorbidity in asthma and chronic obstructive pulmonary disease (COPD), yet the contribution of artificial intelligence (AI) and machine learning (ML) to CVD risk assessment and management in these conditions r... read more
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