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Multi-stream and multi-scale fusion rib fracture segmentation network based on UXNet.
Quant Imaging Med Surg
January 2025
School of Computer Science and Technology, Changchun University of Science and Technology, Changchun, China.
Background: Accurate segmentation of rib fractures represents a pivotal procedure within surgical interventions. This meticulous process not only mitigates the likelihood of postoperative complications but also facilitates expedited patient recuperation. However, rib fractures in computed tomography (CT) images exhibit an uneven morphology and are not fixed in position, posing difficulties in segmenting fractures.
View Article and Find Full Text PDFThe pharmacodynamic modulation effect of oxytocin on resting state functional connectivity network topology.
Front Pharmacol
January 2025
MOE Key Laboratory for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China.
Introduction: Neuroimaging studies have demonstrated that intranasal oxytocin has extensive effects on the resting state functional connectivity of social and emotional processing networks and may have therapeutic potential. However, the extent to which intranasal oxytocin modulates functional connectivity network topology remains less explored, with inconsistent findings in the existing literature. To address this gap, we conducted an exploratory data-driven study.
View Article and Find Full Text PDFIntegrating pharmacogenomics and cheminformatics with diverse disease phenotypes for cell type-guided drug discovery.
Genome Med
January 2025
Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, 181 Longwood Avenue, Boston, MA, 02115, USA.
Background: Large-scale pharmacogenomic resources, such as the Connectivity Map (CMap), have greatly assisted computational drug discovery. However, despite their widespread use, CMap-based methods have thus far been agnostic to the biological activity of drugs as well as to the genomic effects of drugs in multiple disease contexts. Here, we present a network-based statistical approach, Pathopticon, that uses CMap to build cell type-specific gene-drug perturbation networks and integrates these networks with cheminformatic data and diverse disease phenotypes to prioritize drugs in a cell type-dependent manner.
View Article and Find Full Text PDFAdvancing COVID-19 Treatment: The Role of Non-covalent Inhibitors Unveiled by Integrated Machine Learning and Network Pharmacology.
Curr Pharm Des
January 2025
Center of Bioinformatics, College of Life Sciences, Northwest Agriculture and Forestry University, Yangling, Shaanxi, 712100, China.
Introduction: The COVID-19 pandemic has necessitated rapid advancements in therapeutic discovery. This study presents an integrated approach combining machine learning (ML) and network pharmacology to identify potential non-covalent inhibitors against pivotal proteins in COVID-19 pathogenesis, specifically B-cell lymphoma 2 (BCL2) and Epidermal Growth Factor Receptor (EGFR).
Method: Employing a dataset of 13,107 compounds, ML algorithms such as k-Nearest Neighbors (kNN), Support Vector Machine (SVM), Random Forest (RF), and Naïve Bayes (NB) were utilized for screening and predicting active inhibitors based on molecular features.
A Graph Neural Network-Based Approach to XANES Data Analysis.
J Phys Chem A
January 2025
Institute of high energy physics, Chinese academy of sciences, Beijing 100049, China.
The determination of three-dimensional structures (3D structures) is crucial for understanding the correlation between the structural attributes of materials and their functional performance. X-ray absorption near edge structure (XANES) is an indispensable tool to characterize the atomic-scale local 3D structure of the system. Here, we present an approach to simulate XANES based on a customized 3D graph neural network (3DGNN) model, XAS3Dabs, which takes directly the 3D structure of the system as input, and the inherent relation between the fine structure of spectrum and local geometry is considered during the model construction.
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