The effects of acute alcohol consumption and eccentric muscle damage on neuromuscular function
Bibliographic record
Abstract
Voluntary and electrically stimulated muscular performance was examined to identify the effects of acute alcohol consumption on neuromuscular function in the presence and absence of exercise-induced muscle damage (EIMD). After initial neuromuscular performance measures were made, 12 subjects completed a bout of eccentric exercise (EX) using the quadriceps muscles of 1 leg while the remaining 11 subjects did not exercise (NX). Subjects then consumed either an alcoholic beverage containing 1 g·kg(-1) body weight (ALC) or a nonalcoholic beverage (OJ). On another occasion the contralateral leg of both groups was tested and those in the EX group performed an equivalent bout of eccentric exercise after which the other beverage was consumed. Measurements of neuromuscular function were made pre-exercise and 36 and 60 h post-beverage consumption. Creatine kinase (CK) was measured pre-exercise and at 12, 36, and 60 h. Significantly greater (p < 0.01) decrements in maximal voluntary isometric contraction were observed with EX ALC at 36 and 60 h compared with EX OJ, and no change was seen in the NX group. Significant decreases in voluntary activation were observed at 36 h (p = 0.003) and 60 h (p = 0.01) with EX ALC only. Elevations in CK were observed at all posteccentric exercise time points (all p < 0.05) under both EX OJ and ALC. No change in electromyography or low-frequency fatigue was observed under either treatment in either group. These results suggest that decreased neural drive appears to contribute to alcohol's effect on the magnitude of EIMD-related decrements in voluntary force generation.
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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) | 0.000 | 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) | 0.002 | 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".