Advancing Parkinson’s diagnosis: seed amplification assay for α-synuclein detection in minimally invasive samples

Molecular and Cellular Biochemistry, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 6, 2025

Language: Английский

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Unraveling the Molecular Mechanisms of Osteoarthritis: The Potential of Polyphenols as Therapeutic Agents

Phytotherapy Research, Journal Year: 2025, Volume and Issue: unknown

Published: March 5, 2025

The complex nature of osteoarthritis (OA), driven by the intricate interplay genetic, environmental, and lifestyle factors, necessitates development a single treatment method, which is highly challenging. long-term use non-steroidal anti-inflammatory drugs (NSAIDs) corticosteroids often leads to adverse side effects like kidney damage stomach ulcers. Major health threats obesity aging create milieu chronic low-grade inflammation increased mechanical stress on joints resulting in cartilage deterioration. Additionally, postmenopausal women with lower circulating 17β-estradiol levels experience accelerated joint deterioration due immune activity production pro-inflammatory cytokines, elevated MMP expression decreased type II collagen synthesis. Polyphenols are nature's gifted magic molecules, possess diverse biological properties anti-oxidant, anti-bacterial, anti-inflammatory, estrogenic, insulin-sensitizing effects, can manage treat all multi-factorial contributing factors OA effectively. Certain polyphenols act as phytoestrogens mimic natural estrogen binding ERα ERβ SERMs prevent degradation articular thereby alleviating osteoarthritic conditions. These molecules downregulate various apoptotic genes, matrix-degrading proteases (MMPs) while upregulating major ECM proteins collagen, aggrecan, proteoglycans animal models. This review provides comprehensive overview molecular mechanisms involved also explores therapeutic potential different mitigating their protective effect inhibiting extracellular matrix (ECM) enhancing homeostasis.

Language: Английский

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Development and evaluation of a machine learning model for osteoporosis risk prediction in Korean women

BMC Women s Health, Journal Year: 2025, Volume and Issue: 25(1)

Published: March 28, 2025

The aim of this study was to develop a machine learning (ML) model for classifying osteoporosis in Korean women based on large-scale population cohort study. This also aimed assess ML performance compared with traditional screening tools. Furthermore, examine the factors influencing risk through variable importance. Data collected from 4199 aged 40-69 years baseline survey Ansan and Ansung Genome Epidemiology Study. Osteoporosis set as dependent classification models. Independent variables included 122 related risk, such socio-demographic characteristics, anthropometric parameters, lifestyle factors, reproductive nutrient intakes, diet quality indices, medical history, medication family biochemical genetic factors. six models were developed using techniques, including decision tree, random forest, multilayer perceptron, support vector machine, light gradient boosting extreme (XGBoost). two tools, assessment instrument (ORAI) self-assessment tool (OST). performances evaluated confusion matrix area under curve (AUC) metrics. Variable importance assessed XGBoost technique investigate showed highest out models, an accuracy 0.705, precision 0.664, recall 0.830, F1 score 0.738. Moreover, higher AUC than ORAI OST. scores identified 69 associated Age at menopause ranked first Variables arthritis, physical activities, hypertension, education level, income level; alcohol intake, potassium homeostatic insulin resistance; energy vitamin C gout; dietary inflammatory index top 20 variables, technique. found that can be utilized classify women. is significant factor followed by level.

Language: Английский

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Incidence of Total Knee Arthroplasty in Older Females with Knee Osteoarthritis and Osteoporosis Treated with Denosumab Compared with Those Treated Using Bisphosphonates: A Population-Based Cohort Study

Life, Journal Year: 2024, Volume and Issue: 14(12), P. 1704 - 1704

Published: Dec. 23, 2024

This study aimed to evaluate the incidence of total knee arthroplasty (TKA), a marker severe osteoarthritis (OA), among older females with concurrent OA and osteoporosis (OP) who were treated denosumab or bisphosphonates. By analyzing large population-based cohort, we sought clarify how these treatments influence progression point requiring surgical intervention. We used data from Taiwan National Health Insurance Research Database, including aged ≥ 50 years diagnosed OP initiated treatment between 2012 2019. Propensity score matching (1:1) resulted in selection 13,774 patients (6897 per group). The TKA was analyzed using Cox proportional hazards models. Patients had lower than those bisphosphonates (6.9 vs. 8.5 1000 person-years). adjusted hazard ratio (aHR) for group 0.77 (95% CI: 0.62–0.97; p = 0.024), most pronounced effect observed 80 (aHR 0.39, 95% 0.20–0.77; 0.007). These findings suggest that reduces risk more effectively may serve as superior option mitigating progression, especially adults.

Language: Английский

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