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Predicting the location of coordinated metal ion-ligand binding sites using geometry-aware graph neural networks.
Comput Struct Biotechnol J
December 2024
Department of Electrical Engineering and Computer Science, Bond Life Sciences Center, University of Missouri, Columbia, MO, USA.
More than 50 % of proteins bind to metal ions. Interactions between metal ions and proteins, especially coordinated interactions, are essential for biological functions, such as maintaining protein structure and signal transport. Physiological metal-ion binding prediction is pivotal for both elucidating the biological functions of proteins and for the design of new drugs.
View Article and Find Full Text PDFThe combination treatment of RC48 and STAT3 inhibitor acts as a promising therapeutic strategy for basal bladder cancer.
Front Immunol
January 2025
Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China.
As an antibody-drug conjugate (ADC), disitamab vedotin (RC48) is a promising treatment targeting ERBB2 for locally advanced and metastatic bladder cancer (BLCA). However, the subtype heterogeneity of muscle-invasive bladder cancer (MIBC) often leads to different therapeutic outcomes. In our study, we aim to explore sensitivity differences and mechanisms of different molecular subtypes of MIBC to RC48 treatment and develop a strategy for combination therapy against cancer.
View Article and Find Full Text PDFAccelerating materials property prediction via a hybrid Transformer Graph framework that leverages four body interactions.
NPJ Comput Mater
January 2025
School of Mechanical, Aerospace, and Manufacturing Engineering, University of Connecticut, Storrs, CT USA.
Machine learning has advanced the rapid prediction of inorganic materials properties, yet data scarcity for specific properties and capturing thermodynamic stability remains challenging. We propose a framework utilizing a Graph Neural Network with composition-based and crystal structure-based architectures, combined with a transfer learning scheme. This approach accurately predicts energy-related properties (e.
View Article and Find Full Text PDFLevel measurement, regional variations, and the dynamic evolution of active aging in China-analysis based on CHARLS tracking data.
Front Public Health
January 2025
School of Sports Economics and Management, Xi'an Physical Education University, Xi'an, China.
Introduction: Given the world's largest and increasingly serious aging population, China has elevated "positively responding to aging of population" to a national strategy. Exploring the current state and evolutionary trends of active aging over the past decade is a fundamental prerequisite and the primary task for implementing this strategy.
Methods: Based on data from the China Health and Retirement Longitudinal Study (2011-2018), this study primarily employs methods such as the entropy method, Gini coefficient, Moran index, and Kernel density estimation to analyze the development level, regional differences, and dynamic evolution of active aging in China.
Enhancing photon-counting computed tomography reconstruction via subspace dictionary learning and spatial sparsity regularization.
Quant Imaging Med Surg
January 2025
Henan Key Laboratory of Imaging and Intelligent Processing, Information Engineering University, Zhengzhou, China.
Background: Photon-counting computed tomography (CT) is an advanced imaging technique that enables multi-energy imaging from a single scan. However, the limited photon count assigned to narrow energy bins leads to increased quantum noise in the reconstructed spectral images. To address this issue, leveraging the prior information in the spectral images is essential.
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