Changes In The Proportion Of Cd56dim And Cd56bright Natural Killer Cells During Incremental Exercise
Bibliographic record
Abstract
Our previous research has shown changes in the proportions of natural killer (NK) cell subsets with different cy to toxic ities during one month of intensive training. These changes could partly explain an observed decrease in lytic units per NK cell at the end of training. There has been no report on changes in NK cell subset proportions during an acute bout of exercise. Researcher indicated that the increase in NK cell cytolytic activity following vigorous exercise was less than that expected from the associated increase in NK cell counts. PURPOSE We investigated the cell counts and the relative proportions of CD3-CD16brightCD56dim (CD56dim) and CD3-CD16dim/-CD56bright (CD56bright) NK cells during an incremental exercise to test the hypothesis that high-intensity exercise induces an increase in the proportion of low cytotoxic NK cells in the peripheral blood. METHODS Nine male students exercised on a cycle ergometer for 5 min at 50, 90, 120 and 140% ventilatory threshold (VT)-VO. Blood samples were taken at rest and at the end of each exercise-intensity stage. The phenotypes of circulating NK cells were determined by flow cytometry. RESULTS Both CD56dim (cells with high cytotoxicity, p<0.001) and CD56bright (cells with low cytotoxicity, p<0.02) cell counts increased exponentially as exercise intensity increased. Total NK cell cytolytic activity followed a corresponding pattern (p<0.001). The proportion of CD56dim NK cell expressed as a percentage of total lymphocyte counts increased significantly (p<0.001). In contrast, the percentage of CD56bright NK cells remained unchanged throughout the experiments. CONCLUSIONS These results suggest that a bout of high-intensity exercise did not induce an increase in the proportion of the CD56bright NK cell subset with low cytolytic activities. Supported by Meiji Life Insurance Company.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".