Short Communication: Ischemia/Reperfusion Tolerance Is Time-of-Day–Dependent
Bibliographic record
Abstract
RATIONALE: Cardiovascular physiology and pathophysiology vary dramatically over the course of the day. For example, myocardial infarction onset occurs with greater incidence during the early morning hours in humans. However, whether myocardial infarction tolerance exhibits a time-of-day dependence is unknown. OBJECTIVE: To investigate whether time of day of an ischemic insult influences clinically relevant outcomes in mice. METHODS AND RESULTS: Wild-type mice were subjected to ischemia/reperfusion (I/R) (45 minutes of ischemia followed by 1 day or 1 month of reperfusion) at distinct times of the day, using the closed-chest left anterior descending coronary artery occlusion model. Following 1 day of reperfusion, hearts subjected to ischemia at the sleep-to-wake transition (zeitgeber time [ZT]12) resulted in 3.5-fold increases in infarct size compared to hearts subjected to ischemia at the wake-to-sleep transition (ZT0). Following 1 month of reperfusion, prior ischemic event at ZT12 versus ZT0 resulted in significantly greater infarct volume, fibrosis, and adverse remodeling, as well as greater depression of contractile function. Genetic ablation of the cardiomyocyte circadian clock (termed cardiomyocyte-specific circadian clock mutant [CCM] mice) attenuated/abolished time-of-day variations in I/R outcomes observed in wild-type hearts. Investigation of Akt and glycogen synthase kinase-3beta in wild-type and CCM hearts identified these kinases as potential mechanistic ties between the cardiomyocyte circadian clock and I/R tolerance. CONCLUSIONS: We expose a profound time-of-day dependence for I/R tolerance, which is mediated by the cardiomyocyte circadian clock. Further understanding of I/R tolerance rhythms will potentially provide novel insight regarding the etiology and treatment of ischemia-induced cardiac dysfunction.
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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) | 0.001 | 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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".