Circulating RAS in Mice with Prorenin Receptor Gene Deletion Specificly in Adipose Tissue
Bibliographic record
Abstract
Introduction Adipose tissue (AT) renin‐angiotensin system (RAS) has been involved in the pathogenesis of obesity, where the role of the prorenin/renin receptor [(P)RR], which acts in an angiotensin‐dependent and ‐independent manner is not clear yet. Our previous results suggest the (P)RR plays a role in the regulation of body weight (BW), fat mass and insulin sensitivity (IS). Material and methods Mice with deletion of the (P)RR gene specificly in AT (KO) created by cre‐loxp technology, were kept either on regular chow (ND) or high‐fat/high‐carbohydrate diet (HF/HC) for 10 weeks. BW measured weekly. Body composition assessed by Echo‐MRI. Glucose homeostasis evaluated by OGTT. At the end of protocol, mice euthanized, subcutaneous, visceral (VF) fat pads separated, weighed, flash frozen. Plasma renin activity (PRA), Angiotensin I (Ang‐I) concentration were measured by immunoassay (DBC, Canada). Results Male KO mice had a 20% lower BW compared to wild‐type mice (WT), p0.001, whereas KO female mice had a 4.3% decrease on ND, p<0.01 and 14.12%, p0.001 on HF/HC. The VF mass in KO male mice was lower by 2.4 fold, p0.001 compared to WT, in female KO mice ‐1.3 fold lower on ND, p0.01 and 2.4 folds on HF/HC, p0.001. In addition, although KO and WT mice had similar glycemia during OGTT, fasting and stimulated insulinemia were lower in KO mice which suggests an improved IS. These phenotypes were not associated with any changes in circulating Ang‐I and PRA. Conclusion Our results suggest that AT specific deletion of the (P)RR regulates body weight, fat mass, glucose homeostasis without changing circulating RAS.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".