Omega-3E treatment regulates matrix metalloproteinases and prevents vascular reactivity alterations in diabetic rat aortaThis article is one of a selection of papers published in a special issue on Advances in Cardiovascular Research.
Bibliographic record
Abstract
It is known that increased generation of oxidants and (or) reduced endogenous antioxidant defense mechanisms are associated with the etiology of diabetic vascular complications. Although a close correlation exists between increased oxidative stress and the activation of matrix metalloproteinases (MMPs), little is known about the effect of hyperglycemia on the regulation and contribution of MMPs in the vascular system. Therefore, we aimed to examine whether omega-3E (50 mg/kg per day for 4 weeks), a long-chain (n-3) polyunsaturated fatty acid enriched with vitamin E, has a beneficial effect on vascular dysfunction via affecting MMPs in streptozotocin-diabetic rat aorta. Omega-3E treatment improved the diabetes-induced impairment of phenylephrine-induced contraction and isoproterenol-induced relaxation responses of aorta. It also exhibited marked protection against diabetes-induced degenerative changes in smooth muscle cell morphology. Biochemical data showed that this treatment significantly prevented important changes, such as inhibition of MMP-2 and MMP-9 activity, loss of tissue inhibitor of matrix metalloproteinase-4 (TIMP-4) protein, increase in tissue levels of thiol oxidation, endothelin-1, protein kinase C (PKC), and cAMP production, and decrease in tissue level of nitrite. These results indicated that omega-3E significantly improved impaired vascular responses and regulated the activity of MMPs via preventing oxidative injury. Overall, the data suggest that omega-3E ameliorates or prevents vascular reactivity alterations in diabetes. Such an observation provides preliminary evidence for omega-3E's potential as a therapeutic agent for the prevention of vascular disorders in diabetes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 teacher head, 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".