Impact of an Acute Bout of Submaximal Aerobic Exercise on Circulating Leukocytes in Individuals with Spinal Cord Injury
Bibliographic record
Abstract
International Journal of Exercise Science 15(3): 1085-1104, 2022. Individuals with spinal cord injury (SCI) may experience cardiovascular, musculoskeletal and organ function dysregulation. Sequelae include reduced catecholamine secretion and attenuated immune responses which may impact exercise-induced leukocytosis. The purpose of this study was to characterize major leukocyte subtypes following 30 minutes of acute, submaximal aerobic exercise, in line with updated international SCI exercise guidelines for adults. It was hypothesized that exercise would increase major leukocyte subtypes when compared to fasted baseline. Eight participants with SCI (incomplete n = 6; complete n = 2) completed a 30-minute bout of aerobic exercise on an arm cycle ergometer at 60% of their peak power output followed by 90 minutes of recovery, or a 2-hour seated control condition, in a randomized crossover design, separated by 7-14 days. Blood samples were taken at baseline, post exercise, and 90 minutes after exercise (with time matched control). Leukocyte subtypes were analyzed via flow cytometry and plasma catecholamines by ELISA. Several leukocytes increased from pre- to post-exercise (time X condition interaction; all P < 0.05; mean ± SD), including CD3+ Lymphocytes (19 ± 16%), CD4+ T helper (16 ± 13%), CD8+ T cytotoxic (24 ± 23%), CD3+/CD56+ natural killer T (31 ± 34%), and CD3-/CD56+ natural killer (63 ± 82%). CD16+/CD14dim monocytes decreased by 27 ± 38% following exercise to 90 minutes post-exercise. No changes were observed for catecholamines for either condition. Thirty minutes of acute submaximal aerobic exercise sufficiently increased most lymphocyte subsets with effector functions, while leading to decreased proinflammatory monocytes during the recovery phase. This exercise duration and intensity appear to be an appropriate option for modulating circulating immune cells in individuals with SCI.
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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".