Effect of fluid ingestion on neuromuscular function during prolonged cycling exercise
Bibliographic record
Abstract
OBJECTIVES: To investigate the effects of fluid ingestion on neuromuscular function during prolonged cycling exercise. METHODS: Eight well trained subjects exercised for 180 minutes in a moderate environment at a workload requiring approximately 60% maximal oxygen uptake. Two conditions, fluid (F) and no fluid (NF) ingestion, were investigated. RESULTS: During maximal voluntary isometric contraction (MVC), prolonged cycling exercise reduced (p<0.05) the maximal force generating capacity of quadriceps muscles (after three hours of cycling) and root mean square (RMS) values (after two hours of cycling) with no difference between the two conditions despite greater body weight loss (p<0.05) in NF. The mean power frequency (MPF) for vastus lateralis muscle was reduced (p<0.05) and the rate of force development (RFD) was increased (p<0.05) only during NF. During cycling exercise, integrated electromyographic activity and perceived exertion were increased in both conditions (p<0.05) with no significant effect of fluid ingestion. CONCLUSIONS: The results suggest that fluid ingestion did not prevent the previously reported decrease in maximal force with exercise duration, but seems to have a positive effect on some indicators of neuromuscular fatigue such as mean power frequency and rate of force development during maximal voluntary contraction. Further investigations are needed to assess the effect of change in hydration on neural mechanisms linked to the development of muscular fatigue during prolonged exercise.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".