Pseudoephedrine and circadian rhythm interaction on neuromuscular performance
Bibliographic record
Abstract
This study analyzed the effects of pseudoephedrine (PSE) provided at different time of day on neuromuscular performance, side effects, and violation of the current doping cut-off threshold [World Anti-Doping Agency (WADA)]. Nine resistance-trained males carried out bench press and full squat exercises against four incremental loads (25%, 50%, 75%, and 90% one repetition maximum [1RM]), in a randomized, double-blind, cross-over design. Participants ingested either 180 mg of PSE (supra-therapeutic dose) or placebo in the morning (7:00 h; AM(PLAC) and AM(PSE)) and in the afternoon (17:00 h; PM(PLAC) and PM(PSE)). PSE enhanced muscle contraction velocity against 25% and 50% 1RM loads, only when it was ingested in the mornings, and only in the full squat exercise (4.4-8.7%; P < 0.05). PSE ingestion raised urine and plasma PSE concentrations (P < 0.05) regardless of time of day; however, cathine only increased in the urine samples. PSE ingestion resulted in positive tests occurring in 11% of samples, and it rose some adverse side effects such us tachycardia and heart palpitations. Ingestion of a single dose of 180 mg of PSE results in enhanced lower body muscle contraction velocity against low and moderate loads only in the mornings. These mild performance improvements are accompanied by undesirable side effects and an 11% risk of surpassing the doping threshold.
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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 | 0.000 |
| 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".