Dopamine/noradrenaline reuptake inhibition in women improves endurance exercise performance in the heat
Bibliographic record
Abstract
Catecholamine reuptake inhibition improves the performance of male volunteers exercising in warm conditions, but sex differences in thermoregulation, circulating hormones, and central neurotransmission may alter this response. With local ethics committee approval, nine physically active women (mean ± SD age 21 ± 2 years; height 1.68 ± 0.08 m; body mass 64.1 ± 6.0 kg; VO 2peak 51 ± 7 mL/kg/min) were recruited to examine the effect of pre‐exercise administration of Bupropion ( BUP ; 4 × 150 mg) on prolonged exercise performance in a warm environment. Participants completed a VO 2peak test, two familiarization trials, and two randomized, double‐blind experimental trials. All trials took place during the first 10 days of the follicular phase of the menstrual cycle. Participants cycled for 1 h at 60% VO 2peak followed by a 30‐min performance test. Total work done was greater during the BUP trial (291 ± 48 kJ) than the placebo trial (269 ± 46 kJ, P = 0.042, d = 0.497). At the end of the performance test, core temperature was higher on the BUP trial (39.5 ± 0.4 °C) than on the placebo trial (39.2 ± 0.6 °C, P = 0.021; d = 0.588), as was heart rate (185 ± 9 vs 179 ± 13, P = 0.043; d = 0.537). The results indicate that during the follicular phase of the menstrual cycle, an acute dosing protocol of BUP can improve self‐regulated performance in warm conditions.
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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) | 0.002 | 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".