50-OR: Metabolic Dysfunction Attenuates D-dopachrome Tautomerase (DDT) Expression in the Heart—A Key Mechanism Exacerbates Myocardial Post-ischemic Injury
Bibliographic record
Abstract
Metabolic abnormalities affect clinical recovery and long-term survival in patients with acute myocardial infarction, but the underlying mechanisms remain unclear. D-dopachrome tautomerase (DDT) in cardiomyocytes protects the heart from injury during hypoxia-ischemia in mice. Our present study found that metabolic dysfunction induced by high fat diet (HFD) was associated with reduced cardiac DDT expression and aggravated cardiac injury following ischemia-reperfusion. Supplementation of DDT prior to ischemia decreased post-ischemic injury in these hearts, suggesting that DDT reduction is an important mechanism regulating post-ischemic cardiac injury associated with metabolic dysfunction. Among all the major fatty acid species in HFD, high palmitic acid (PA) triggered the expression and activation of protease activated receptor 2 (PAR2), which upregulated the transcriptional factors, CREB1 and FOXO1 leading to downregulation of DDT expression in the heart. PAR2 stimulated ERK phosphorylation, thereby upregulating CREB1 phosphorylation. Attenuation of CREB by siRNA significantly decreased FOXO1 expression and accumulation in the nucleus, thereby reducing cardiac DDT expression. Accordingly, PAR2 deficient mice exhibited normal ERK and CREB phosphorylation and DDT levels in the heart following HFD and reversed cardiac function recovery following reperfusion. Overall, our data reveal for the first time a novel role for DDT in mediating myocardial ischemia-reperfusion injury associated with metabolic dysfunction. Disclosure L. Li: None. Y. Qi: None. N. Cui: None. L. Leng: None. H. Wu: None. R. Bucala: None. D. Qi: None. Funding This study was supported by National Sciences and Engineering Research Council of Canada (NSERC: RGPIN-2017-04542) and Canadian Institutes of Health Research (CIHR Project Grant: PJT-156116).
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".