从选定的氧化应激参数、肌肉损伤指数和炎症标志物预测足球和曲棍球运动员的有氧和无氧能力

Q3 Health Professions
S. Sarkar, S. K. Dey, G. Datta, A. Bandyopadhyay
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Muscle damage indices (creatine kinase (CK), lactate dehydrogenase (LDH), cortisol), inflammatory markers (interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α)), antioxidant variables (malondialde-hyde (MDA), superoxide dismutase (SOD), glutathione (GSH), glutathione peroxidase (GPx)) and performance variables (indicated as V̇O2max and Wpeak) were assessed using standard protocols. Results The most significant (sig p ---lt--- 0.001) prediction of V̇O2max = (0.763) MDA+ (5.644) SOD+ (0.039) GSH- (0.154) GPx+ (0.002) LDH- (0.011) CK+ (0.038) cortisol+ (1.232) IL+ (1.135) TNF+ 20.018. The strongest correlations were found between V̇O2max vs MDA (R2 = 0.852), V̇O2max vs IL-6 (R2 = 0.589), V̇O2max vs TNF-α (R2 = 0.385). Conclusions Artificial neural network perceptron model depicted stronger prediction of V̇O2max (R2 = 0.872) in comparison to Wpeak (R2 = 0.271), with MDA and CK as the major predictors for V̇O2max and Wpeak, respectively. 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引用次数: 0

摘要

摘要引言本研究的目的是寻找运动诱导的生物标志物(抗氧化剂、肌肉损伤和炎症标志物)与耐力和无氧能力的关系。该研究还旨在开发最大摄氧量(V̇O2max)和相对厌氧功率(Wpeak)的预测回归模型,以确定基本的性能限制因素。材料和方法选择86名耐力男性运动员(即足球(n=39)和曲棍球(n=47))作为本研究的受试者。使用标准方案评估肌肉损伤指数(肌酸激酶(CK)、乳酸脱氢酶(LDH)、皮质醇)、炎症标志物(白细胞介素-6(IL-6)、肿瘤坏死因子-α(TNF-α))、抗氧化变量(丙二醛(MDA)、超氧化物歧化酶(SOD)、谷胱甘肽(GSH)、谷胱甘肽过氧化物酶(GPx))和性能变量(表示为V?O2max和Wpeak)。结果V̇O2max=(0.763)MDA+(5.644)SOD+(0.039)GSH-(0.154)GPx+(0.002)LDH-(0.011)CK+(0.038)皮质醇+(1.232)IL+(1.135)TNF+20.018。结论人工神经网络感知器模型对V(R2=0.872)和W(R2=0.271)的预测能力更强,MDA和CK分别是V和W的主要预测因子。在所有生物标志物中,MDA、IL-6和TNF-α被确定为显著预测耐力的最有价值的指标。MDA、SOD、GPx、IL-6和TNF-α与V̇O2max和LDH呈强相关,皮质醇与Wpeak呈强相关。相反,运动诱导的生物标志物不能预测无氧能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prediction of Aerobic and Anaerobic Capacity From Selected Oxidative Stress Parameters, Muscle Damage Indices and Inflammatory Markers in Soccer and Hockey Players
Abstract Introduction The aim of the present study was to find the relation of exercise-induced biomarkers (antioxidant, muscle damage, and inflammatory markers) with endurance capacity and anaerobic power. The study also aimed to develop predicting regression models for maximal oxygen uptake (V̇O2max) and relative anaerobic power (Wpeak) to specify the essential performance limiting elements. Material and Methods Eighty-six endurance male players (i.e., football (n = 39) and field hockey (n = 47)) were selected as test subjects for the present study. Muscle damage indices (creatine kinase (CK), lactate dehydrogenase (LDH), cortisol), inflammatory markers (interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α)), antioxidant variables (malondialde-hyde (MDA), superoxide dismutase (SOD), glutathione (GSH), glutathione peroxidase (GPx)) and performance variables (indicated as V̇O2max and Wpeak) were assessed using standard protocols. Results The most significant (sig p ---lt--- 0.001) prediction of V̇O2max = (0.763) MDA+ (5.644) SOD+ (0.039) GSH- (0.154) GPx+ (0.002) LDH- (0.011) CK+ (0.038) cortisol+ (1.232) IL+ (1.135) TNF+ 20.018. The strongest correlations were found between V̇O2max vs MDA (R2 = 0.852), V̇O2max vs IL-6 (R2 = 0.589), V̇O2max vs TNF-α (R2 = 0.385). Conclusions Artificial neural network perceptron model depicted stronger prediction of V̇O2max (R2 = 0.872) in comparison to Wpeak (R2 = 0.271), with MDA and CK as the major predictors for V̇O2max and Wpeak, respectively. Among all biomarkers, MDA, IL-6, and TNF-α were identified as the most valuable indicators to predict endurance capacity significantly. While MDA, SOD, GPx, IL-6, and TNF-α were strongly correlated with V̇O2max and LDH, cortisol was strongly correlated with Wpeak. Contrarily, exercise-induced biomarkers failed to predict anaerobic power.
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来源期刊
Polish Journal of Sport and Tourism
Polish Journal of Sport and Tourism Health Professions-Physical Therapy, Sports Therapy and Rehabilitation
CiteScore
1.00
自引率
0.00%
发文量
19
审稿时长
8 weeks
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