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Background: Spinal cord injury (SCI) compromises the communication between the brain and spinal circuits involved in locomotion, resulting in severe motor dysfunction. However, currently available therapies have limited effectiveness in restoring motor function after SCI.
Objective: Recent research has highlighted the importance of the central pattern generator (CPG), a spinal circuitry responsible for generating coordinated patterns of leg motor activity in the absence of brain-derived inputs, in locomotor recovery. Therefore, a highly promising approach for restorative treatment after SCI involves reactivating the CPG network to harness its rhythmic activity-generating capabilities. Various forms of neuromodulation, such as pharmacological agents, electrical stimulation, and light-based regulatory strategies, have been utilized for this purpose.
Results: This review summarizes the organizational structure and functional characteristics of CPG networks, examines CPG alterations following SCI, and evaluates recent advances in neuromodulation strategies aimed at restoring motor function through CPG reactivation.
Conclusions: This review also highlights existing challenges and outlines prospective directions for future research in the field.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12338084 | PMC |
http://dx.doi.org/10.1002/jsp2.70100 | DOI Listing |
Sci Prog
September 2025
Shenzhen University Sixth Affiliated Hospital, Shenzhen Nanshan People's Hospital, Shenzhen, China.
Colorectal cancer ranks among the most prevalent and lethal malignant tumors globally. Historically, the incidence of colorectal cancer in China has been lower than that in developed European and American countries; however, recent trends indicate a rising incidence due to changes in dietary patterns and lifestyle. Lipids serve critical roles in human physiology, such as energy provision, cell membrane formation, signaling molecule function, and hormone synthesis.
View Article and Find Full Text PDFInt J Surg
September 2025
Department of Pharmacy, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, School of Clinical Medicine, Henan University, Zhengzhou, Henan, China.
Background: Antiplatelet therapy is a cornerstone in the management of atherosclerotic cardiovascular disease. However, the risk profile of central nervous system (CNS) hematomas associated with antiplatelet agents remains incompletely characterized.
Methods: We analyzed CNS-related hematoma adverse event (hAE) reports across the four antiplatelet drugs, using data from the U.
Int J Surg
September 2025
Department of Gynecology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, Hainan, China.
Background: Ovarian cancer remains the most lethal gynecological cancer, with fewer than 50% of patients surviving more than five years after diagnosis. This study aimed to analyze the global epidemiological trends of ovarian cancer from 1990 to 2021 and also project its prevalence to 2050, providing insights into these evolving patterns and helping health policymakers use healthcare resources more effectively.
Methods: This study comprehensively analyzes the original data related to ovarian cancer from the GBD 2021 database, employing a variety of methods including descriptive analysis, correlation analysis, age-period-cohort (APC) analysis, decomposition analysis, predictive analysis, frontier analysis, and health inequality analysis.
J Nephrol
September 2025
Department of Psychology, Institute of Psychiatry, Psychology & Neuroscience, Health Psychology Section, King's College London, 5th Floor Bermondsey Wing, Guy's Campus, London Bridge, London, SE1 9RT, UK.
Background: Depression and anxiety are common in chronic kidney disease (CKD) and worsen clinical outcomes. Psycho-behavioural interventions offer a promising, non-pharmacological approach. However, most evidence comes from people with kidney failure with distinct treatment needs, limiting relevance to earlier stages of CKD, where timely support may enhance self-management and slow progression.
View Article and Find Full Text PDFDrugs Aging
September 2025
Dalla Lana School of Public Health, University of Toronto, V1 06, 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada.
Background And Objectives: Older adults living with dementia are a heterogeneous group, which can make studying optimal medication management challenging. Unsupervised machine learning is a group of computing methods that rely on unlabeled data-that is, where the algorithm itself is discovering patterns without the need for researchers to label the data with a known outcome. These methods may help us to better understand complex prescribing patterns in this population.
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