Effect of formoterol, a long-acting β<sub>2</sub>-adrenergic agonist, on muscle strength and power output, metabolism, and fatigue during maximal sprinting in men
Bibliographic record
Abstract
The aim was to investigate the effect of the long-acting β2-adrenergic agonist formoterol on muscle strength and power output, muscle metabolism, and phosphorylation of CaMKII Thr(287) and FXYD1 during maximal sprinting. In a double-blind crossover study, 13 males [V̇o2 max: 45.0 ± 0.2 (means ± SE) ml·min(-1)·kg(-1)] performed a 30-s cycle ergometer sprint after inhalation of either 54 μg of formoterol (FOR) or placebo (PLA). Before and after the sprint, muscle biopsies were collected from vastus lateralis and maximal voluntary contraction (MVC), and contractile properties of quadriceps were measured. Oxygen uptake was measured during the sprint. During the sprint, peak power, mean power, and end power were 4.6 ± 0.8, 3.9 ± 1.1, and 9.5 ± 3.2% higher (P < 0.05) in FOR than in PLA, respectively. Net rates of glycogenolysis and glycolysis were 45.7 ± 21.0 and 28.5 ± 13.4% higher (P < 0.05) in FOR than in PLA, respectively, and the decrease in ATP content was lower (P < 0.05) in FOR than in PLA (3.7 ± 1.5 vs. 8.0 ± 1.6 mmol/kg dry weight). There was no difference in breakdown of phosphocreatine and oxygen uptake between treatments. Before and after the sprint, MVC and peak twitch force were higher (P < 0.05) in FOR than in PLA. No differences were observed in phosphorylation of CaMKII Thr(287) and FXYD1 between treatments before the sprint, whereas phosphorylation of CaMKII Thr(287) and FXYD1 was greater (P < 0.05) in FOR than in PLA after the sprint. In conclusion, formoterol-induced enhancement in power output during maximal sprinting is associated with increased rates of glycogenolysis and glycolysis that may counteract development of fatigue.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".