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Comprehensive Analysis Reveals the Potential Diagnostic Value of Biomarkers Associated With Aging and Circadian Rhythm in Knee Osteoarthritis.
Orthop Surg
January 2025
Department of Orthopedics, Tianjin Medical University General Hospital, International Science and Technology Cooperation Base of Spinal Cord Injury, Tianjin Key Laboratory of Spine and Spinal Cord, Tianjin, China.
Objective: Knee osteoarthritis (KOA) is characterized by structural changes. Aging is a major risk factor for KOA. Therefore, the objective of this study was to examine the role of genes related to aging and circadian rhythms in KOA.
View Article and Find Full Text PDFA 3D decoupling Alzheimer's disease prediction network based on structural MRI.
Health Inf Sci Syst
December 2025
School of Mathematics and Computing, University of Southern Queensland, 487-535 West Street, Toowoomba, QLD 4350 Australia.
Purpose: This paper aims to develop a three-dimensional (3D) Alzheimer's disease (AD) prediction method, thereby bettering current predictive methods, which struggle to fully harness the potential of structural magnetic resonance imaging (sMRI) data.
Methods: Traditional convolutional neural networks encounter pressing difficulties in accurately focusing on the AD lesion structure. To address this issue, a 3D decoupling, self-attention network for AD prediction is proposed.
Machine learning applications in placenta accreta spectrum disorders.
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March 2025
Mother and Newborn Health Research Center, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
This review examines the emerging applications of machine learning (ML) and radiomics in the diagnosis and prediction of placenta accreta spectrum (PAS) disorders, addressing a significant challenge in obstetric care. It highlights recent advancements in ML algorithms and radiomic techniques that utilize medical imaging modalities like magnetic resonance imaging (MRI) and ultrasound for effective classification and risk stratification of PAS. The review discusses the efficacy of various deep learning models, such as nnU-Net and DenseNet-PAS, which have demonstrated superior performance over traditional diagnostic methods through high AUC scores.
View Article and Find Full Text PDFCol1A1 as a new decoder of clinical features and immune microenvironment in ovarian cancer.
Front Immunol
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Department of Gynecology, Sichuan Provincial Women's and Children's Hospital, The Affiliated Women's and Children's Hospital of Chengdu Medical College, Chengdu, Sichuan, China.
Backgrounds: Collagen type I alpha 1 chain (COL1A1) is a key protein encoding fibrillar collagen, playing a crucial role in the tumor microenvironment (TME) due to its complex functions and close association with tumor invasiveness. This has made COL1A1 a focal point in cancer biology research. However, studies investigating the relationship between COL1A1 expression levels and clinical characteristics of ovarian cancer (OC) remain limited.
View Article and Find Full Text PDFImpact of glioma metabolism-related gene ALPK1 on tumor immune heterogeneity and the regulation of the TGF-β pathway.
Front Immunol
January 2025
Department of Neurological Care Unit, The First Affiliated Hospital of YangTze University, Jingzhou, Hubei, China.
Background: Recent years have seen persistently poor prognoses for glioma patients. Therefore, exploring the molecular subtyping of gliomas, identifying novel prognostic biomarkers, and understanding the characteristics of their immune microenvironments are crucial for improving treatment strategies and patient outcomes.
Methods: We integrated glioma datasets from multiple sources, employing Non-negative Matrix Factorization (NMF) to cluster samples and filter for differentially expressed metabolic genes.
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