Carbohydrate ingestion attenuates the increase in plasma interleukin‐6, but not skeletal muscle interleukin‐6 mRNA, during exercise in humans
Bibliographic record
Abstract
1. The present study was undertaken to examine the effects of exercise and carbohydrate (CHO) ingestion on interleukin-6 (IL-6) gene expression in skeletal muscle and plasma IL-6 concentration. 2. Seven moderately trained men completed 60 min of exercise at a workload corresponding to each individual's lactate threshold on four randomised occasions. Two trials were conducted on a bicycle ergometer (Cyc) and two on a running treadmill (Run) either with (CHO) or without (Con) the ingestion of a CHO beverage throughout the exercise. Muscle biopsies were obtained from the vastus lateralis before and immediately after exercise and IL-6 gene expression in these samples was determined using real-time PCR. In addition, venous blood samples were collected at rest, and after 30 min during and at the cessation of exercise. These samples were analysed for plasma IL-6. 3. Irrespective of exercise mode or CHO ingestion, exercise resulted in a 21 +/- 4-fold increase (P < 0.01; main exercise effect) in IL-6 mRNA expression. In contrast, while the mode of exercise did not affect the exercise-induced increase in plasma IL-6, CHO ingestion blunted (P < 0.01) this response. 4. These data demonstrate that CHO ingestion attenuates the plasma IL-6 concentration during both cycling and running exercise. However, because IL-6 mRNA expression was unaffected by CHO ingestion, it is likely that the ingestion of CHO during exercise attenuates IL-6 production by tissues other than skeletal muscle.
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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".