Repeated high-intensity Wingate cycle bouts influence markers of lymphocyte migration but not apoptosis
Bibliographic record
Abstract
Studies have shown significant changes in lymphocytes during continuous exercise, but little has been shown on the effect of repeated high intensity bouts. This study was designed to examine the effect of repeated intermittent bouts on lymphocyte subset cell count, apoptosis, and migration. A series of 6 Wingate anaerobic cycle tests were performed by participants (N = 8) with blood samples attained before, immediately following, and after a designated recovery period (excess postexercise oxygen consumption (EPOC)) to observe lymphocyte changes. Lymphocyte subsets (CD4+, CD4/CD45RA+, CD8+, CD8+/CD45RA+, CD19+) were assessed for apoptosis (annexin V+) and cellular migration (CX(3)CR1). Our results indicate that the CD8+ and CD8+/CD45RA+ subsets were significantly influenced by the repetitive Wingate cycling protocol such that cell counts increased with exercise, and then decreased at EPOC termination (p = 0.016). The observed postexercise decrease in CD8+ and CD8+/CD45RA+ cells was accompanied by a significant change in the CX(3)CR1 cell migration receptor (p = 0.019), but not apoptosis (p = 0.87). This indicates that with repetitive high-intensity cycling, the response in CD8+ cells following the bout is likely due to cell migration rather than cell death.
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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".