Dalton transactions (Cambridge, England : 2003)
Jan 26, 2026
Food spoilage arising from protein degradation and microbial activities leads to the release of biogenic amines (BAs) and volatile amines (VAs), which compromise its quality and pose health hazards. Conventional chromatographic techniques for monitor... read more
Angioimmunoblastic T-cell lymphoma (AITL) is an aggressive peripheral T-cell lymphoma with a poor prognosis. Lymphomatous serous effusion, defined as the presence of malignant lymphoma cells in the pleural, pericardial, or peritoneal fluid, is a rare... read more
Memristors, whose conductance depends on their past electrical history, are the foundation of emerging brain-inspired artificial computing architectures. Here, we demonstrate a unipolar memristor in which both ionic conductance and electroosmotic flo... read more
Journal of chemical theory and computation
Jan 26, 2026
In this paper, we introduce ZORANet, a Fermionic neural network framework for the relativistic calculations based on scalar zeroth-order regular approximation (ZORA), which greatly expands the scope of deep neural network-based electronic structure m... read more
With the advancement of the Internet of Things (IoT) and artificial intelligence (AI) technologies, wearable sensors will play a significant role in smart healthcare and behavior detection. Based on multiscale convolutional channel attention residual... read more
Biological systems comprise a complex milieu of macromolecules, small molecules, and ions comprising tens of thousands of distinct species. Various clinical conditions alter the identities and concentrations of these species in a spatiotemporal-depen... read more
OBJECTIVES: Intracranial hemorrhage (ICH) is a time-critical neurological emergency in which rapid CT-based assessment directly informs treatment decisions. This study aimed to develop an automated deep-learning pipeline to enhance ICH detection, seg... read more
PURPOSE: Prediction of Torsades de Pointes (TdP) risk using hiPSC-CM assays remains challenging, as many models fail to capture nonlinear patterns and exhibit unstable performance across different drugs. We examined whether a stacking ensemble can im... read more
AIM: This study aimed to develop a machine learning (ML)-assisted model to predict the risk of upstaging (subsequent higher stage on repeat pathology) in non-muscle-invasive bladder cancer (NMIBC). METHODS: A retrospective cohort study was conducted ... read more
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