Performance Enhancement With Maintenance of Resting Immune Status After Intensified Cycle Training
Bibliographic record
Abstract
BACKGROUND: Unaccustomed intense endurance exercise is associated with short-term suppression of natural immunity. However, it is not established whether intensified endurance training alters resting immune status or increases the risk of upper respiratory infection (URI). PURPOSE: This study examined the effect of intensified endurance training for performance enhancement on resting immune status in nine healthy, male competitive cyclists. DESIGN: Data were collected during 4 weeks of usual training (baseline), followed by prescribed cycle training that consisted of volume-building at customary training intensity (V phase, 6 weeks), unaccustomed very high intensity interval training at 100% maximal heart rate (I phase, 18 days), and an unloading taper (U phase, 10 days). METHODS: The main performance criterion was a simulated 20 km time-trial. Aerobic capacity measures included power output at ventilatory threshold (POT(vent)) and maximal oxygen uptake (VO(2max)). Markers of immune status (lymphocyte subset counts, serum cytokine levels, and new URI cases) and physiological indicators of training stress (cycling economy, 24-hour urinary cortisol excretion, and serum testosterone concentration) were evaluated in the rested state, 36 to 44 hours postexercise, during baseline, and after each training phase. RESULTS: Time-trial performance, POT9(vent), VO(2max), and cycling economy improved significantly (p < 0.001) after the V phase, and remained higher than baseline (p < 0.001) after the I and U phases. As compared with the V phase, performance time was faster after the U phase (p < 0.01). In contrast, lymphocyte counts, cytokine levels, incidence of URI, cortisol excretion, and serum testosterone concentration were not significantly different from baseline in any phase. CONCLUSIONS: Cycling efficiency and performance improved while resting immune status was maintained throughout the 10-week training program. This study provides encouraging data in support of immunological robustness during intensified endurance training.
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) | 0.000 | 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".