Is Exercise-Induced Lactate Accumulation Associated with Changes in Acylated Ghrelin? A Systematic Review and Individual Participant Data Meta-Analysis
Bibliographic record
Abstract
INTRODUCTION: Lactate has been proposed to suppress the release and activation of the orexigenic peptide acylated ghrelin, though no study has synthesized available evidence from acute exercise trials. PURPOSE: To determine if exercise-induced lactate accumulation predicts and/or is associated with changes in acylated ghrelin. METHODS: A systematic search strategy was developed and conducted in four databases for studies exploring changes in acylated ghrelin and lactate during acute exercise interventions. Using Covidence, studies were identified and included if participants were between the ages of 18 and 65 years, healthy (absence of medical condition or disease), conducted an acute exercise trial, and measured both acylated ghrelin and lactate pre and postexercise. Corresponding authors of eligible studies were contacted for individual data, and linear mixed-effect models were fitted and repeated measures correlations were conducted to determine if change in (Δ) lactate predicts and/or was associated with Δ acylated ghrelin and acylated ghrelin incremental area under the curve (iAUC). RESULTS: Twelve data sets (169 participants) were included in the Δ acylated ghrelin analysis and nine data sets (105 participants) were included in the acylated ghrelin iAUC analysis. There was a significant effect of Δ lactate for both Δ acylated ghrelin (β = -8.1, standard error = 1.1, P < 0.001) and Δ acylated ghrelin iAUC (β = -698, standard error = 69, P < 0.001) and Δ lactate had a negative correlation with both outcomes (r m = -0.41, P < 0.001; and r m = -0.59, P < 0.001). CONCLUSIONS: Overall, this study suggests that exercise-induced lactate accumulation significantly affects Δ acylated ghrelin and acylated ghrelin iAUC and is negatively associated, suggesting that greater exercise-induced lactate accumulation would be associated with the suppression of ghrelin.
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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 | 0.025 | 0.069 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.042 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".