Endothelium dysfunction in hind limb arteries of male Zucker Diabetic-Sprague Dawley rats
Bibliographic record
Abstract
Endothelium dysfunction produces peripheral vascular disease comorbidities in type 2 diabetes, including hypertension, and critical limb ischemia. In this study we aimed to test endothelial dysfunction, the vasodilator effects of a proteinase-activated receptor 2 (PAR2) agonist (2fLIGRLO), and thromboxane A2 synthase inhibitor (ozagrel) on PAR2 vasodilation in hind limb arteries ex vivo, using Zucker Diabetic-Sprague Dawley (ZDSD) rats, a model of type 2 diabetes. Male Sprague Dawley rats (SD) and ZDSD were fed a high-fat content ‘Western diet’ from 16 to 20 weeks of age (wks) then fed a standard laboratory diet. We identified diabetic ZDSD rats by two consecutive blood glucose measurements > 12.5 mM, based on weekly monitoring. We used acetylcholine, 2fLIGRLO, and nitroprusside with wire-myograph methods to compare relaxations of femoral, and saphenous arteries from diabetic ZDSD (21–23 wks) to age-matched normoglycemic SD. All arteries showed evidence of endothelium dysfunction using acetylcholine (reduced maximum relaxations, reduced sensitivity), and higher sensitivities to 2fLIGRLO, and nitroprusside in ZDSD vs SD. Ozagrel treatment of ZDSD distal segments, and end-branches of saphenous arteries decreased their sensitivities to 2fLIGRLO. We tested aortas for altered expression of endothelium-specific gene targets using PCR array and qPCR. PAR2, and placental growth factor gene transcripts were 1.5, and 4-times higher in ZDSD than SD aortas. Hind limb arteries of ZDSD exhibit endothelium dysfunction having less GPCR agonist induced vasodilation by endothelial NO-release. Different expression of several endothelial genes in ZDSD vs SD aortas, including PAR2, suggests altered inflammatory, and angiogenesis signaling pathways in the endothelium of ZDSD.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".