Rest Profoundly Protects Against Cardiac Remodeling and Benefits Repair
Bibliographic record
Abstract
Abstract Cardiovascular disease is a leading cause of morbidity and mortality worldwide1. Although rest has long been considered beneficial to patients2, remarkably there are no evidence-based experimental models determining how it benefits disease outcomes. Here, we create a novel experimental rest model in mice, whereby light-induced manipulation of the circadian system briefly extends the rest period by 4 hours each morning. We found, in two different cardiovascular disease conditions (cardiac hypertrophy, myocardial infarction), that imposing a short, extended period of rest each day persistently reduces cardiac remodeling, as compared to control mice subjected to only normal periods of rest, supporting the therapeutic benefits of rest to slow functional decompensation in heart disease. Mechanistically, rest reduces hemodynamic stress on the cardiovascular system, imposing changes on myofilament contractile function in the heart independently consistent within each disease phenotype. Molecular analyses reveal attenuation of cardiac remodeling genes, consistent with the benefits on cardiac structure and function. These same cardiac remodeling genes underlie the pathophysiology of many major human cardiovascular conditions, as demonstrated by interrogating open-source transcriptomic data, and thus patients with other conditions may also benefit from a morning rest period in a similar manner. In summary, we report that rest is a key driver of physiology, leading to the development of an entirely new field on the nature of rest, and provide a strong rationale for advancement of rest based therapy for major clinical diseases.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".