Changes in exercise capacity and serum BDNF following long-term sprint interval training in well-trained cyclists
Bibliographic record
Abstract
The study determined the effects of sprint interval training on the acute and chronic changes of serum brain-derived neurotrophic factor (BDNF) and aerobic capacity. Twenty-six cyclists were divided into experimental (E) and control groups. Both groups executed a 6-month exercise intervention involving high-intensity interval training (HIIT) and continuous endurance training (CET) with group E replacing HIIT and CET sessions with sprint interval training (SIT) that was executed twice a week. Two exercise tests were administered prior to the intervention and at 2 and 6 months after study outset. Incremental exercise test assessed aerobic capacity by measuring maximal oxygen uptake and work output; the sprint interval exercise test (SIXT) comprises 3 sets of four 30-s all-out repetitions interspersed with 90 s of rest with sets separated by 25-40 min of active recovery. Oxygen uptake, work output, BDNF, and vascular endothelial growth factor A (VEGF-A) concentrations (baseline, 10 min after first set, and 10 and 60 min after third SIXT set) were taken during the SIXT. Significant decreases in BDNF relative to baseline values were observed 10 min after the first set and 60 min after the third set in group E at the 2- and 6-month assessments. Increases in baseline VEGF-A after 2 and 6 months of training and increases in maximal oxygen uptake after 2 months of training were also observed only in group E. The inclusion of SIT with HIIT and CET shows positive long-term effects, including increased maximal oxygen uptake and baseline VEGF-A and a reduction in BDNF below baseline levels during and after SIXT.
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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".