Caffeine increases time to fatigue by maintaining force and not by altering firing rates during submaximal isometric contractions
Bibliographic record
Abstract
Caffeine increases time to fatigue [limit of endurance (T(lim))] during submaximal isometric contractions without altering whole muscle activation or neuromuscular junction transmission. We used 10 male volunteers in a randomized, double-blind, repeated-measures experiment to examine single motor unit firing rates during intermittent submaximal contractions and to determine whether administering caffeine increased T(lim) by maintaining higher firing rates. On 2 separate days, subjects performed intermittent 50% maximal voluntary contractions of the quadriceps to T(lim), 1 h after ingesting a caffeine (6 mg/kg) or placebo capsule. Average motor unit firing rates recorded with tungsten microelectrodes were constant for the duration of contractions. Caffeine increased average T(lim) by 20.5 +/- 8.1% (P < 0.05) compared with placebo conditions. This increase was due to seven subjects, termed responders, who increased T(lim) significantly. Two other subjects showed no response, and a third had a shorter T(lim). Neither the increased T(lim) nor the responders' performance could be explained by alterations in firing rates or other neuromuscular variables. However, the amplitude of the evoked twitch and its maximal instantaneous rate of relaxation did not decline to the same degree in the caffeine trial of the responders; this resulted in values 20 and 30% higher at the time point matching the end of the placebo trial (P < 0.05). The amplitude of the evoked twitch and the maximal instantaneous rate of relaxation were linearly correlated (caffeine r = 0.72, placebo r = 0.80, both P < 0.001), suggesting that the increase in T(lim) may be partially explained by caffeine's effects on calcium reuptake and twitch force.
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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) | 0.001 | 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".