Modality-specific training adaptations – do they lead to a dampened acute inflammatory response to exercise?
Bibliographic record
Abstract
While adaptations to a short-term training program can dampen the acute inflammatory response to exercise, less is known about the influence of chronic modality-specific adaptations to training. This study compares the acute inflammatory response to upper- and lower-body interval exercise in individuals chronically trained in these respective modalities. Ninety minutes of interval exercise matched for relative power output on an arm-crank (ARM) and cycle ergometer (LEG) was performed by 8 trained paddlers and 8 trained cyclists. Blood samples were taken before and after exercise. Interleukin-6 (IL-6) concentrations were analysed in plasma, while the expression of intracellular heat shock protein 72 (iHsp72) was assessed in monocytes. IL-6 was increased following both modalities (fold change – ARM: 7.23 ± 3.56, p < 0.001; LEG: 9.03 ± 4.82, p < 0.001), in both groups (cyclists, p < 0.001; paddlers, p < 0.001), but the increase was smaller in ARM compared with LEG (time × modality, p < 0.001). ARM induced a smaller iHsp72 response compared with LEG (fold change – ARM: 1.07 ± 0.14, p = 0.102; LEG: 1.18 ± 0.14, p < 0.001; time × modality, p = 0.039). Following ARM, iHsp72 expression was increased in the cyclists only (fold change cyclists: 1.12 ± 0.11, p = 0.018; paddlers: 1.03 ± 0.17, p = 0.647), while iHsp72 expression following LEG was increased in both groups (fold change cyclists: 1.14 ± 0.15, p = 0.027; paddlers: 1.22 ± 0.13, p < 0.001). Taken together, the acute inflammatory response to lower-body interval exercise was larger compared with work-matched upper-body interval exercise. Moreover, adaptations to upper-body exercise training dampened the iHsp72 response to this modality. Therefore, exercise may be less effective in reducing chronic low-grade inflammation in individuals relying on their upper body, such as wheelchair users.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".