The effects of exercise training and caloric restriction on the cardiac oxytocin natriuretic peptide system in the diabetic mouse
Bibliographic record
Abstract
Tom L Broderick,1 Marek Jankowski,2 Jolanta Gutkowska2 1Department of Physiology, Laboratory of Diabetes and Exercise Metabolism, Midwestern University, Glendale, AZ, USA; 2Department of Medicine, Laboratory of Cardiovascular Biochemistry, Centre Hospitalier de l‘Université de Montréal-Hôtel-Dieu, Montréal, QC, Canada Background: Regular exercise training (ET) and caloric restriction (CR) are the frontline strategies in the treatment of type 2 diabetes mellitus with the aim at reducing cardiometabolic risk. ET and CR improve body weight and glycemic control, and experimental studies indicate that these paradigms afford cardioprotection. In this study, the effects of combined ET and CR on the cardioprotective oxytocin (OT)–natriuretic peptide (NP) system were determined in the db/db mouse, a model of type 2 diabetes associated with insulin resistance, hyperglycemia, and obesity. Methods: Five-week-old male db/db mice were assigned to the following groups: sedentary, ET, and ET + CR. Nonobese heterozygote littermates served as controls. ET was performed on a treadmill at moderate intensity, and CR was induced by reducing food intake by 30% of that consumed by sedentary db/db mice for a period of 8 weeks. Results: After 8 weeks, only ET + CR, but not ET, slightly improved body weight compared to sedentary db/db mice. Regardless of the treatment, db/db mice remained hyperglycemic. Hearts from db/db mice demonstrated reduced expression of genes linked to the cardiac OT–NP system. In fact, compared to control mice, mRNA expression of GATA binding protein 4 (GATA4), OT receptor, OT, brain NP, NP receptor type C, and endothelial nitric oxide synthase (eNOS) was decreased in hearts from sedentary db/db mice. Both ET alone and ET + CR increased the mRNA expression of GATA4 compared to sedentary db/db mice. Only ET combined with CR produced increased eNOS mRNA and protein expression. Conclusion: Our data indicate that enhancement of eNOS by combined ET and CR may improve coronary endothelial vasodilator dysfunction in type 2 diabetes but did not prevent the downregulation of cardiac expression in the OT–NP system, possibly resulting from the sustained hyperglycemia and obesity in diabetic mice. Keywords: running, diabetes, GATA4, oxytocin, natriuretic peptides, db/db
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".