Caloric restriction improves inflammation in different tissues of the Wistar rats with obesity and 2K1C renovascular hypertension
Bibliographic record
Abstract
Renovascular hypertension (RHV) is the cause of high blood pressure due to left renal ischemia, and obesity and hypertension cause an inflammatory response. This work analyzed the inflammatory and tissue repair profile in renal, hepatic, and cardiac tissues in an animal model of RVH associated with a high-fat diet and caloric restriction. The expressions of RORγ-t, IL-17, T-bet, and TNF-α decreased and IFN-γ increased in the right kidney. In relation to the left kidney, caloric restriction decreased the expression of IFN-γ. In the liver, caloric restriction decreased RORγ-t, IL-17, and T-bet. Hypertension associated with obesity decreased the expression of IFN-γ, while caloric restriction increased. In the right kidney, hypertension and obesity, associated or not with caloric restriction, increased the area of collagen fibers. In the heart and liver, caloric restriction reduced the area of collagen fibers. Caloric restriction increased vascular endothelial growth factor, reduced levels of growth transformation factor-β1 (TGF-β), and increased collagen I in the left kidney. Hypertension/obesity, submitted or not having caloric restriction, increased TGF-β in liver. The results suggest that caloric restriction has beneficial effects in lowering blood pressure and regulating tissue proinflammatory cytokines. However, there was no change in the structure and composition of tissue repair markers.
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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".