Purpose: To provide insights into a dose-response relationship between training and time-trial performance, as assessed in both a "fresh" and a "fatigued" state (durability), including proposed underlying factors for durability: gross efficiency and substrate oxidation (FatOx and CarbOx).
Methods: Ten male semiprofessional cyclists underwent a performance test in both "fresh" and "fatigued" state (after 38.6 [4.6] kJ·kg-1) before and after an 8-week training period, containing the measurement of gross efficiency, FatOx, and CarbOx at submaximal intensity and maximal time trials of 1 (PO1) and 10 minutes (PO10). Relationships were assessed with the session rating of perceived exertion, kilojoules spent, Lucia training impulse, Training Stress Score, polarization index, and time spent in 3 zones in the intervening period.
Results: No significant relationship was found between higher training load and performance on PO1 and PO10, with a large variation between assessed training-load measures and individual participants. However, CarbOx showed a strong correlation with training volume in the "fresh" state and with time spent below first-lactate-threshold intensity in the "fatigued" state. Also, the relationship between training load and change in performance between tests showed different trends for "fresh" compared with "fatigued" state, especially for FatOx and CarbOx.
Conclusions: The fact that no clear relationships between dose (training) and response (time-trial performance) were shown in this study indicates that a single load measure is not able to predict performance improvements after an 8-week training period. However, the current study shows that the same training can have a different effect on "fresh" versus "fatigued" performance, having implications for the design of training plans.
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http://dx.doi.org/10.1123/ijspp.2024-0321 | DOI Listing |
Int J Sports Physiol Perform
March 2025
Division of Movement Science and Exercise Therapy (MSET), Department of Exercise, Sport and Lifestyle Medicine, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch, South Africa.
Purpose: To provide insights into a dose-response relationship between training and time-trial performance, as assessed in both a "fresh" and a "fatigued" state (durability), including proposed underlying factors for durability: gross efficiency and substrate oxidation (FatOx and CarbOx).
Methods: Ten male semiprofessional cyclists underwent a performance test in both "fresh" and "fatigued" state (after 38.6 [4.
PLoS One
March 2025
State Key Laboratory Basis of Xinjiang Indigenous Medicinal Plants Resource Utilization, Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Urumqi, People's Republic of China.
Meiju Oral Liquid (MOL), a representative medicinal formula in China, stems from the traditional use of specific Chinese medicinal herbs known for their anti-fatigue properties, including rose, jujube, chicory, and wolfberry. While these individual herbs have been recognized for their benefits, the formulation of MOL itself has not been extensively studied. This study was designed to evaluate the potential anti-fatigue effects of MOL, prepared from these natural herbs, and to explore its underlying mechanisms.
View Article and Find Full Text PDFNephrol Nurs J
March 2025
Professor Emeritus, College of Nursing, Wayne State University, Detroit, MI.
The purpose of this secondary analysis was to report the psychometric properties of the Patient-Reported Out comes Measurement Information Systems (PROMIS) Computer Adaptive Test (CAT) - Fatigue in individuals receiving hemodialysis (HD) treatment. Measures included Piper Fatigue Scale-12, Six-Minute Walk Test, PROMIS CAT-Fatigue, and Charlson Comorbidity Index. English-speaking adults older than 18 years, cognitively intact, receiving two to three times weekly HD treatment were included.
View Article and Find Full Text PDFIEEE Trans Neural Syst Rehabil Eng
March 2025
Myoelectric interfaces hold promise for enabling intuitive and natural control of prostheses and exoskeletons. Muscle fatigue, whether due to prolonged use or heavy weight loads, can alter the distribution of electromyographic (EMG) signals, leading to inconsistencies compared to non-fatigued conditions. This presents significant challenges for accurately decoding user intentions.
View Article and Find Full Text PDFThe integration of EEG signals and deep learning methods is emerging as an effective approach for brain fatigue detection, particularly utilizing Graph Neural Networks(GNNs) that excel in capturing complex electrode relationships. A significant challenge within GNNs is the construction of an effective adjacency matrix that enhances spatial information learning. Concurrently, electrode aggregation in EEG has emerged as a pivotal area of research.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!