The day/night proteome in the murine heart
Bibliographic record
Abstract
Circadian rhythms are essential to cardiovascular health and disease. Temporal coordination of cardiac structure and function has focused primarily at the physiological and gene expression levels, but these analyses are invariably incomplete, not the least because proteins underlie many biological processes. The purpose of this study was to reveal the diurnal cardiac proteome and important contributions to cardiac function. The 24-h day-night murine cardiac proteome was assessed by two-dimensional difference in gel electrophoresis (2D-DIGE) and liquid chromatography-mass spectrometry. Daily variation was considerable, as ∼7.8% (90/1,147) of spots exhibited statistical changes at paired times across the 24-h light- (L) dark (D) cycle. JTK_CYCLE was used to investigate underlying diurnal rhythms in corresponding mRNA. We next revealed that disruption of the L:D cycle altered protein profiles and diurnal variation in cardiac function in Langendorff-perfused hearts, relative to the L:D cycle. To investigate the role of the circadian clock mechanism, we used cardiomyocyte clock mutant (CCM) mice. CCM myofilaments exhibited a loss of time-of-day-dependent maximal calcium-dependent ATP consumption, and altered phosphorylation rhythms. Moreover, the cardiac proteome was significantly altered in CCM hearts, especially enzymes regulating vital metabolic pathways. Lastly, we used a model of pressure overload cardiac hypertrophy to demonstrate the temporal proteome during heart disease. Our studies demonstrate that time of day plays a direct role in cardiac protein abundance and indicate a novel mechanistic contribution of circadian biology to cardiovascular structure and function.
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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".