Increased Extravasation of Macromolecules in Skeletal Muscles of the Zucker Rat Model
Bibliographic record
Abstract
OBJECTIVE: Assess whether changes in permeability of the muscle regional microcirculation occur in the obese Zucker rat model. RESEARCH METHODS AND PROCEDURES: Capillary permeability to albumin was assessed in vivo in Zucker rats (n = 15) and lean controls (n = 15) by quantifying the extravasation of albumin-bound Evans Blue (EB) in different organs. Unanaesthetized animals were injected with EB 20 mg/kg in the caudal vein, and EB was extracted by formamide from selected organs collected after exsanguination. RESULTS: Relative to control animals, Zucker rats had higher body weight (Delta = +33%; p < 0.001), plasma triglycerides (Delta = +244%; p < 0.001), and insulin (Delta = +240%; p < 0.001) concentrations. Plasma glucose concentrations were not different between the two groups (p = not significant). Using the EB technique, we showed a 30% to 50% (p < 0.01) increase in the extravasation of EB in the obese rats, regardless of the skeletal muscle group studied. This increase in skeletal muscle vasopermeability was not paralleled by any increase in the expression of the muscle endothelium-nitric oxide (NO) system because the total NO synthase (NOS) activity in skeletal muscle of the obese Zucker rat was significantly lower (p < 0.001), as was the endothelial NOS immunoreactive mass (p < 0.001), compared with lean controls. DISCUSSION: In conclusion, there seems to be dissociation between capillary permeability and local regulation of microcirculation in skeletal muscles of the obese Zucker rat. It is suggested that the increase in skeletal muscle vasopermeability (extravasation of macromolecules) is a compensation for the loss of NO-dependent vasodilation and capillary recruitment noted in this model of obesity and insulin resistance.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".