Exercise‐induced changes in left ventricular strain are affected by interleukin‐6 activity: An exploratory analysis of a randomised‐controlled trial in humans with abdominal obesity
Bibliographic record
Abstract
Whilst the exercise-induced myokine interleukin-6 (IL-6) plays a beneficial role in cardiac structural adaptations, its influence on exercise-induced functional cardiac outcomes remains unknown. We hypothesised that IL-6 activity is required for exercise-induced improvements in left ventricular global longitudinal strain (LV GLS). In an exploratory study 52 individuals with abdominal obesity were randomised to 12 weeks' high-intensity exercise or no exercise in combination with IL-6 receptor inhibition (IL-6i) or placebo. LV strain and volume measurements were assessed by cardiac magnetic resonance. Exercise improved LV GLS by -5.4% [95% CI: -9.1% to -1.6%] (P = 0.007). Comparing the change from baseline in LV GLS in the exercise + placebo group (-4.8% [95% CI: -7.4% to -2.2%]; P < 0.0004) to the exercise + IL-6i group (-1.1% [95% CI: -3.8% to 1.6%]; P = 0.42), the exercise + placebo group changed -3.7% [95% CI: -7.4% to -0.02%] (P = 0.049) more than the exercise + IL6i group. However, the interaction effect between exercise and IL-6i was insignificant (4.5% [95% CI: -0.8% to 9.9%]; P = 0.09). Similarly, the exercise + placebo group improved LV global circumferential strain by -3.1% [95% CI: -6.0% to -0.1%] (P = 0.04) more compared to the exercise + IL-6i group, yet we found an insignificant interaction between exercise and IL-6i (4.2% [95% CI: -1.8% to 10.3%]; P = 0.16). There was no effect of IL-6i on exercise-induced changes to volume rates. This study underscores the importance of IL-6 in improving LV GLS in individuals with abdominal obesity suggesting a role for IL-6 in cardiac functional exercise adaptations.
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".