Journal of chemical information and modeling
Sep 25, 2025
Traf2-and Nck-interacting kinase (TNIK) has been implicated in fibrosis-associated signaling pathways and has recently emerged as a promising therapeutic target for idiopathic pulmonary fibrosis (IPF). In this study, we employed an integrated strateg...
Journal of chemical information and modeling
Sep 25, 2025
The rapid emergence of drug resistance in viral infections represents a significant global health challenge, threatening the efficacy of treatments for multiple diseases. Machine learning models have emerged as valuable tools for predicting antiviral...
Oxicams, a major category of nonsteroidal anti-inflammatory drugs, are widely used in daily life. However, excessive consumption of oxicams can pose significant risks to human health. Herein, we introduce an innovative and highly sensitive fluorescen...
Medical healthcare has advanced substantially due to advancements in Artificial Intelligence (AI) techniques for early disease detection alongside support for clinical decisions. However, a gap exists in widespread adoption of results of these algori...
Molecular medicine (Cambridge, Mass.)
Sep 25, 2025
BACKGROUND: Juvenile idiopathic arthritis (JIA) is a rare autoimmune disease arising from a complex interplay between genetic and environmental factors. Epigenetic modifications such as DNA methylation (DNAm) have been described as potential mediator...
Robotic-assisted radical prostatectomy (RARP) has become the gold standard treatment for localized prostate cancer. However, predicting post-operative outcomes remains challenging. This study aims to develop and validate predictive models for key out...
Environmental monitoring and assessment
Sep 25, 2025
Lake topography, which serves as a crucial basis for water resource monitoring, has been extensively applied in hydrological and geomorphological research. However, monitoring lake dynamics in data-scarce regions remains challenging due to the limite...
Patients with type 2 diabetes mellitus (T2DM) have a significantly higher risk of cardiovascular disease (CVD) compared to the general population. Accurately predicting this risk is crucial for developing personalized treatment plans and public healt...
This study aimed to verify and interpret a model for predicting the number of home runs per year using sensor data from professional baseball players during batting practice. A machine learning model was constructed using Random Forest from the bat k...
This study investigates the feasibility of using tear sample analysis, based on protein corona formation on gold nanoparticles combined with electrospray ionization mass spectrometry (ESI-MS) and machine learning techniques, as a non-invasive approac...
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