Time-dependent Effects of Moderate- and High-intensity Exercises on Myocardial Transcriptomics
Bibliographic record
Abstract
The heart is a highly adaptable organ that responds to changes in functional requirements due to exposure to internal and external stimuli. Physical exercise has unique stimulatory effects on the myocardium in both healthy individuals and those with health disorders, where the effects are primarily determined by the intensity and recovery time of exercise. We investigated the time-dependent effects of different exercise intensities on myocardial transcriptional expression in rats. Moderate intensity exercise induced more differentially expressed genes in the myocardium than high intensity exercise, while 16 differentially expressed genes were down-regulated by moderate intensity exercise but up-regulated by high intensity exercise at 12 h post- exercise. Both Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis indicated that moderate intensity exercise specifically regulated gene expression related to heart adaptation, energy metabolism, and oxidative stress, while high intensity exercise specifically regulated gene expression related to immunity, inflammation, and apoptosis. Moreover, there was increased expression of Tbx5, Casq1, Igsf1, and Ddah1 at all time points after moderate intensity exercise, while there was increased expression of Card9 at all time points after high intensity exercise. Our study provides a better understanding of the intensity dependent effects of physical exercise of the molecular mechanisms of cardiac adaptation to physical exercise.
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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".