Salivary and Serum Concentrations of Cortisol and Testosterone at Rest and in Response to Intense Exercise in Boys Versus Men
Bibliographic record
Abstract
This study compared salivary and serum concentrations of testosterone and cortisol at rest and in response to intense multitask exercise in boys and men. Early morning saliva and venous blood samples were obtained before and 15 minutes after exercise from 30 competitive swimmers (15 boys, age 14.3 [1.9] y; 15 men, age 21.7 [3.1] y). Exercise included a swim-bench maximal strength task and an all-out 200-m swim, followed by a high-intensity interval swimming protocol (5 × 100 m, 5 × 50 m, and 5 × 25 m). At baseline, fasting testosterone (but not cortisol) concentration was higher in men than boys in serum and saliva (P < .05). Salivary and serum cortisol increased postexercise, with a greater increase in men compared with boys (men: 226% and 242%; boys: 78% and 64%, respectively; group by time interaction, P < .05). Testosterone was reduced postexercise in serum but not in saliva (men: -14.7% and 0.1%; boys: -33.9% and -4.5%, respectively, fluid by time interaction, P < .01). Serum and salivary cortisol (but not testosterone), preexercise and postexercise values were strongly correlated in both men and boys (r = .79 and .82, respectively; P < .01). In summary, early morning high-intensity exercise results in a decrease in testosterone in serum, but not saliva, and an increase in cortisol irrespective of the fluid used, in both boys and men. When examining immediate postexercise changes, the lack of correlation in testosterone between saliva and serum suggests that saliva may not be an appropriate fluid to examine changes in testosterone. The high correlation observed between serum and saliva for cortisol indicates that, in both boys and men, saliva may be used to monitor the immediate cortisol response to exercise.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".