Effect of caffeine on self‐sustained firing in human motor units
Bibliographic record
Abstract
This study examined the effect of caffeine on self-sustained firing (SSF) of human motor units. At physiological doses, caffeine acts as a competitive antagonist to the inhibitory effects of adenosine. This antagonism has many possible effects on the central nervous system. One of these effects is to increase the release of the excitatory neurotransmitters serotonin and noradrenaline. In addition, caffeine increases serotonin concentration in brainstem regions that have excitatory projections to spinal motor neurons. Since plateau potentials, which are responsible for SSF, are facilitated by these neurotransmitters, we hypothesized that caffeine would increase the frequency at which SSF occurs. A double-blind, repeated-measures design using either drug (6 mg kg(-1) caffeine) or placebo (flour) was carried out on seven male subjects who reported ingesting less than 200 mg week(-1) caffeine. We investigated the occurrence of SSF in tibialis anterior motor units (214 trials) and found a significant (P < 0.05) increase in the occurrence of SSF in the caffeine trial (87.0 +/- 5.8 %) compared to the placebo (64.6 +/- 9.7 %). These data further verify the presence of SSF in the tibialis anterior motor units of young men and provide indirect evidence of the facilitation of plateau potentials by monoamines in the human neuromuscular system.
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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) | 0.001 | 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".