Day-night dependence of gene expression and inflammatory responses in the remodeling murine heart post-myocardial infarction
Bibliographic record
Abstract
Diurnal or circadian rhythms are fundamentally important for healthy cardiovascular physiology and play a role in timing of onset and tolerance to myocardial infarction (MI) in patients. Whether time of day of MI triggers different molecular and cellular responses that can influence myocardial remodeling is not known. This study was designed to test whether time of day of MI triggers different gene expression, humoral, and innate inflammatory responses that contribute to cardiac repair after MI. Mice were infarcted by left anterior descending coronary artery ligation (MI model) within a 2-h time window either shortly after lights on or lights off, and the early remodeling responses at 8 h postinfarction were examined. We found that sleep-MI preferentially triggers early expression of genes associated with inflammatory responses, whereas wake-MI triggers more genes associated with metabolic pathways and transcription/translation, by microarray analyses. Homozygous clock mutant mice exhibit altered diurnal gene expression profiles, consistent with their cycling before onset of MI. In the first 8 h, crucial for innate immune responses to MI, there are also significant differences in sleep-MI and wake-MI serum cytokine responses and in neutrophil infiltration to infarcted myocardium. By 1-wk post-MI, there are differences in survivorship between the sleep and wake MI mice that could be explained by the different molecular and cellular responses. Our whole body physiology, tissues, and cells exhibit endogenous daily rhythms, and understanding their role in triggering effective responses after MI could lead to new strategies to benefit patients with cardiovascular disease.
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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 | 0.001 |
| 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".