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http://dx.doi.org/10.1016/s0368-1742(64)80024-2 | DOI Listing |
J Orthop Surg Res
January 2025
Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, 300072, China.
Background: Knee Osteoarthritis (KOA) is a prevalent condition worldwide, significantly diminishing quality of life and productivity. Except for the alignment change, muscle activation patterns (MAP) have garnered increasing attention as another crucial factor contributing to KOA.
Objective: This study explores the factors, characteristics, and effects of MAP changes caused by KOA, providing a neuromuscular-based causal analysis for the rehabilitation treatment of KOA.
Superficial arteriovenous malformations are rare fast-flow lesions. They consist of arteriovenous shunts, without cellular hyperplasia or proliferation, which develop in the surrounding tissues (cutaneous, subcutaneous, muscular, bone). Although benign, they are among the most severe of superficial malformations.
View Article and Find Full Text PDFJ Neuroeng Rehabil
January 2025
Department of Mechanical and Aerospace Engineering, University of Florida, PO Box 116250, Gainesville, FL, 32611, USA.
Background: Motor module (a.k.a.
View Article and Find Full Text PDFHum Genomics
January 2025
Department of Biology, Tor Vergata University of Rome, Via della Ricerca Scientifica 1, 00133, Rome, Italy.
Background: The Immunoglobulin Heavy Chain (IGH) genomic region is responsible for the production of circulating antibodies and warrants careful investigation for its association with COVID-19 characteristics. Multiple allelic variants within and across different IGH gene segments form a limited set of haplotypes. Previous studies have shown associations between some of these haplotypes and clinical outcomes of COVID-19.
View Article and Find Full Text PDFMalar J
January 2025
MIVEGEC, Univ. Montpellier, CNRS, IRD, Montpellier, France.
Background: The increasing availability of electronic health system data and remotely-sensed environmental variables has led to the emergence of statistical models capable of producing malaria forecasts. Many of these models have been operationalized into malaria early warning systems (MEWSs), which provide predictions of malaria dynamics several months in advance at national and regional levels. However, MEWSs rarely produce predictions at the village-level, the operational scale of community health systems and the first point of contact for the majority of rural populations in malaria-endemic countries.
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