Low-intensity exercise in the prevention of cardiac insulin resistance-related inflammation and disturbances in NOS and MMP-9 regulation in fructose-fed ovariectomized rats
Bibliographic record
Abstract
Exercise is important nonpharmacological treatment for improvement of insulin sensitivity in menopause. However, its effect on menopausal cardiac insulin resistance is needing further research. We investigated protective effects of low-intensity exercise on cardiac insulin signaling, inflammation, regulation of nitric oxide synthase (NOS) and matrix metalloproteinase 9 (MMP-9) in ovariectomized (OVX) Wistar rats, submitted to 10% fructose solution for 9 weeks. OVX rats were divided into control, sedentary fructose, and exercise fructose groups. Measurements of physical and biochemical characteristics were carried out to evaluate metabolic syndrome development. Messenger RNA and protein levels and phosphorylation of cardiac insulin signaling molecules, endothelial and inducible NOS (eNOS and iNOS), p65 subunit of nuclear factor κB (NFκB), tumor necrosis factor α (TNF-α), suppressor of cytokine signaling 3 (SOCS3), and MMP-9 were analyzed. Fructose increased insulin level, homeostasis model assessment (HOMA) index, and visceral adipose tissue weight, while low-intensity exercise prevented insulin level and HOMA index increase. Fructose also decreased cardiac pAkt (Ser473), peNOS (Ser1177) and increased insulin receptor substrate 1 (IRS1) phosphorylation at Ser307, pNFκB (Ser276) and NFκB and MMP-9 content, without any effect on iNOS, protein-tyrosine phosphatase 1B, TNF-α, and SOCS3. Exercise prevented changes in pIRS1 (Ser307), pAkt (Ser473), peNOS (Ser1177), pNFκB (Ser276), and NFκB expression. In addition, exercise increased pIRS1 (Tyr632), pAkt (Thr308), and eNOS expression. Low-intensity exercise prevented cardiac insulin signaling disarrangement in fructose-fed OVX rats and therefore eNOS dysfunction, as well as pro-inflammatory signaling activation, without effect on tissue remodeling, suggesting physical training as a way to reduce cardiovascular risk.
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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 | 0.000 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".