Beyond Circulating Cytokines: Impact Of Exercise Intensity On Anti-inflammatory Cytokine Action In Monocytes And Lymphocytes
Bibliographic record
Abstract
Exercise-induced changes in circulating cytokine concentrations are widely used to support the anti-inflammatory effects of exercise. However, circulating cytokines do not capture important functional changes in cytokine action occurring at the cellular level. PURPOSE: To test the novel hypothesis that anti-inflammatory cytokine signaling in blood leukocytes - directly reflecting cellular cytokine action - is altered in an exercise intensity-dependent manner. METHODS: Active young adults completed a no-exercise control session (CTRL) or two exercise sessions involving work-matched (350 kcal) continuous cycling above (heavy intensity continuous exercise; HICE) or below (moderate intensity continuous exercise; MICE) lactate threshold in a counterbalanced crossover design with serial intravenous blood samples obtained before and after exercise. Changes in major immune cell subtypes were quantified using a hematology analyzer and phosphorylation of signal transducer and activation of transcription 3 (STAT3; a key intracellular transducer of anti-inflammatory cytokine action) was measured using flow cytometry following interleukin (IL)-6 (10 ng/mL) and IL-10 (100 ng/mL) stimulation of blood leukocytes ex vivo. RESULTS: Preliminary data from 6 participants (5 males, 1 female; age: 29 ± 2 years, BMI: 25 ± 2 kg/m2; VO2peak: 51 ± 5 ml/kg/min), revealed increases in total white blood cells (~48%), lymphocytes (~70%), monocytes (~38%), and neutrophils (~37%) immediately following HICE (p < 0.05), with no corresponding changes over time in CTRL (p > 0.49) or MICE (p > 0.12). IL-6 and IL-10 mediated STAT3 phosphorylation in CD14+ monocytes and CD4+ lymphocytes was reduced (~15-20%) immediately and 90 minutes following HICE (both p < 0.05). No changes in IL-10 or IL-6 mediated STAT3 phosphorylation were apparent over time in CTRL (p > 0.3) or MICE (p > 0.07). CONCLUSIONS: Contrary to the well documented increases in anti-inflammatory cytokine concentrations after exercise, our preliminary observations suggest that the ability of IL-6 and IL-10 to activate anti-inflammatory signaling pathways may be transiently blunted following acute heavy intensity exercise. Further work is needed to provide insight into the mechanisms and consequences of reduced anti-inflammatory cytokine signaling following HICE.
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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".