Downregulation of oxytocin and natriuretic peptides in diabetes: possible implications in cardiomyopathy
Bibliographic record
Abstract
Regular physical activity is beneficial in preventing the risk of cardiovascular complications of diabetes. Recent studies showed a cardioprotective role of oxytocin (OT) to induce natriuretic peptides (NPs) and nitric oxide (NO) release. It is not known if the diabetic state is associated with a reduced OT-NPs-NO system and if exercise training improves this system. To address this, we investigated the effects of treadmill running using the db/db mouse model of type 2 diabetes. Eight-week-old db/db mice were subjected to running 5 days per week for a period of 8 weeks. The lean db/+ littermates were used as controls. Sedentary db/db mice were obese and hyperglycaemic, and exercise training was not effective in reducing body weight and the hyperglycaemic state. Compared to control mice, db/db mice had lower heart weight and heart-to-body weight ratios. In these mice, this was associated with augmented cardiac apoptosis, cardiomyocyte enlargement and collagen deposits. In addition, db/db mice displayed significant downregulation in gene expression of OT (76%), OT receptors (65%), atrial NP (ANP; 43%), brain NP (BNP; 87%) and endothelial nitric oxide synthase (eNOS) (54%) in the heart (P < 0.05). Exercise training had no effect on expression of these genes which were stimulated in control mice. In response to exercise training, the significant increment of anti-apoptotic Bcl-2 gene expression was observed only in control mice (P < 0.05). In conclusion, downregulation of the OT-NPs-NO system occurs in the heart of the young db/db mouse. Exercise training was not effective in reversing the defect, suggesting impairment of this cardiac protective system in diabetes.
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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".