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Identification of fatty acid anabolism patterns to predict prognosis and immunotherapy response in gastric cancer.
Discov Oncol
January 2025
Department of Clinical Laboratory, Laboratory Medicine Center, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China.
Gastric cancer (GC), one of the most common and heterogeneous malignancies, is the second leading cause of cancer death worldwide and is closely related to dietary habits. Fatty acid is one of the main nutrients of human beings, which is closely related to diabetes, hypertension and other diseases. However, the correlation between fatty acid metabolism and the development and progression of GC remains largely unknown.
View Article and Find Full Text PDFNovel model of the region of interest modified Mayo Adhesive Probability score.
World J Urol
January 2025
Department of Urology, National Cancer Center Hospital East, Chiba, Japan.
Purpose: To evaluate the association between the newly developed region of interest (ROI)-modified Mayo Adhesive Probability (MAP) score, in which stranding was re-evaluated by computed tomography (CT) number, for predicting operation time in robot-assisted partial nephrectomy (RAPN).
Methods: The study participants were 119 patients who underwent transperitoneal RAPN. With regard to stranding, ROIs were evaluated, and the mean CT numbers were assigned a score ranging from 0 to 3.
Gastrointestinal lesions of eosinophilic granulomatosis with polyangiitis: a prediction model and clinical patterns.
Arthritis Res Ther
January 2025
Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, the Ministry of Education Key Laboratory, Chinese Academy of Medical Sciences & Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases, Beijing, China.
Objective: Severe gastrointestinal lesions are associated with a poor prognosis in eosinophilic granulomatosis with polyangiitis (EGPA). The goal of this study was to develop an effective predictive model for gastrointestinal lesions and to examine clinical patterns, associated factors, treatment, and outcomes of gastrointestinal lesions in EGPA.
Methods: We retrospectively enrolled 165 EGPA patients.
Machine learning models predicting risk of revision or secondary knee injury after anterior cruciate ligament reconstruction demonstrate variable discriminatory and accuracy performance: a systematic review.
BMC Musculoskelet Disord
January 2025
Division of Orthopaedic Surgery, Department of Surgery, McMaster University, Hamilton, ON, Canada.
Background: To summarize the statistical performance of machine learning in predicting revision, secondary knee injury, or reoperations following anterior cruciate ligament reconstruction (ACLR), and to provide a general overview of the statistical performance of these models.
Methods: Three online databases (PubMed, MEDLINE, EMBASE) were searched from database inception to February 6, 2024, to identify literature on the use of machine learning to predict revision, secondary knee injury (e.g.
Predicting purulent meningitis in very preterm infants: a novel clinical model.
BMC Pediatr
January 2025
Department of Pediatrics, Qilu Hospital, Shandong University, No.107, West Culture Road, Lixia District, Jinan City, Shandong Province, 250000, China.
Background: Purulent meningitis (PM) is a commonly encountered infectious condition in newborns, which unfortunately can result in infant mortality. Newborns with PM often present nonspecific symptoms. The success of lumbar puncture, an invasive test, relies on the operator's expertise.
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