Acute natural killer cells response to a continuous moderate intensity and a work-matched high intensity interval exercise session in metastatic cancer patients treated with chemotherapy
Bibliographic record
Abstract
Background: It has been suggested that the acute natural killer (NK) cell response to aerobic exercise might contribute to the tumor suppressor effect of regular exercise observed in preclinical studies. Moreover, because this response is modulated by exercise intensity, high-intensity intervals exercise (HIIE) might represent an interesting therapeutic approach in cancer patients. However, this immune response remains unstudied in cancer patients currently undergoing chemotherapy. Objective: To characterize the acute NK cell response following a moderate-intensity continuous aerobic exercise session (MOD), and a HIIE session in metastatic cancer patients treated with chemotherapy. Methods: ) subset was evaluated for its expression of the differentiation markers CD57 and CD158a, the activating receptor NKG2D, the immune checkpoints TIM-3 and PD-1, and the chemokine receptors CXCR3, CXCR4 and CCR2. Results: cNK cell blood counts increased immediately following MOD (p < 0.001) and decreased back to pre-exercise values 1 h after exercise cessation (p < 0.001). The most responsive cNK cell subsets were expressing CD57, CD158a, NKG2D, TIM-3 and CXCR3. The HIIE trial elicited a similar biphasic response, without any difference between trials (all p ≥ 0.38). However, significant changes in the MFI values of CXCR4 and NKG2D were observed in the cNK cell subset following HIIE (all p ≤ 0.038), but not MOD. Conclusion: In metastatic cancer patients undergoing chemotherapy, both MOD and HIIE can elicit an acute mobilisation and egress of NK cells exhibiting phenotypic characteristics associated with high cytotoxicity and tumor homing. Future longitudinal trials are needed to determine if combining aerobic exercise training and chemotherapy will translate towards favorable immune and clinical outcomes.
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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".