MOTS-c repairs myocardial damage by inhibiting the CCN1/ERK1/2/EGR1 pathway in diabetic rats
Bibliographic record
Abstract
Cardiac structure remodeling and dysfunction are common complications of diabetes, often leading to serious cardiovascular events. MOTS-c, a mitochondria-derived peptide, regulates metabolic homeostasis by accelerating glucose uptake and improving insulin sensitivity. Plasma levels of MOTS-c are decreased in patients with diabetes. MOTS-c can improve vascular endothelial function, making it a novel therapeutic target for the cardiovascular complications of diabetes. We investigated the effects of MOTS-c on cardiac structure and function and analyzed transcriptomic characteristics in diabetic rats. Our results indicate that treatment with MOTS-c for 8-week repaired myocardial mitochondrial damage and preserved cardiac systolic and diastolic function. Transcriptomic analysis revealed that MOTS-c altered 47 disease causing genes. Functional enrichment analysis indicated MOTS-c attenuated diabetic heart disease involved apoptosis, immunoregulation, angiogenesis and fatty acid metabolism. Moreover, MOTS-c reduced myocardial apoptosis by downregulating CCN1 genes and thereby inhibiting the activation of ERK1/2 and the expression of its downstream EGR1 gene. Our findings identify potential therapeutic targets for the treatment of T2D and diabetic cardiomyopathy.
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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 | 0.001 | 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".