Abstract 9817: Shift Work Disrupts Circadian Rhythm and Mitochondrial Quality Control in the Heart
Bibliographic record
Abstract
Circadian mis-alignment is a disturbance in the normal 24-hour light/dark cycle that regulates physiological processes in all living organisms. Mis-alignment of the circadian, such as seen in shift workers, is associated with increased risk of ischemic heart disease and worsened outcomes following myocardial infarction. However, the mechanisms by which circadian disruption leads to cardiovascular disease, is still in its infancy. In this study, we show that short-term shift work leads to loss of critical cellular quality control mechanisms from impaired autophagy gene expression. When subjected to cardiac ischemia, shift work mice exhibit greater cardiac injury and ventricular dysfunction, compared with non-shift work control mice. Cardiac dysfunction coincided with morphological defects to mitochondria and accumulation of cellular debris from impaired autophagy. Notably, shift work mice subjected to an exercise protocol prior to ischemia, had restored autophagy gene expression, resulting in a concomitant increase in autophagic flux. Restoring autophagy rescued cardiac dysfunction and attenuated morphological and structural impairments to mitochondria. Interestingly, however, exercise failed to rescue autophagy gene expression and protect against cardiac dysfunction in Clock d19 mice which are genetically deficient for Clock gene activity. These findings demonstrate that the cardioprotective effects of exercise are in part related to improved cellular quality control mechanisms that increase autophagy. Our data provide the first direct evidence that circadian mis- alignment exacerbates cardiac injury in shift work models from impaired autophagy quality control mechanisms.
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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) | 0.005 | 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".