The (pro)renin receptor blocker peptide effects on regulation of body weight and glucose homeostasis in mice with diet‐induced obesity (1101.10)
Bibliographic record
Abstract
Introduction. The Prorenin receptor [(P)RR] is a recently discovered member of the renin‐angiotensin system (RAS). Adipose tissue (AT) is a 2 nd major source of circulating angiotensinogen during obesity and (P)RR effects in adipose tissue have not been clearly identified yet. In this study, we investigated the relationship between (P)RR and body weight (BW) and expression of gene and proteins in the insulin signaling pathway in AT. Material and methods. 12 week‐old C57BL/6 male mice were placed on a high‐fat/high‐carbohydrate (HF/HC) or normal diet (ND) and treated with a (P)RR blocker [(P)RR‐B] or saline for 10 weeks. BW and food intake was assessed weekly. At the end of treatment, mice were euthanized, plasma was collected for the measurement of glucose (G) and insulin (I); AT were separated, weighed and flash frozen. The GLUTs gene expressions were measured by q‐PCR; PKB proteins detected by Western‐Blot. Results.(P)RR‐B administration lowered BW in mice on HF/HC as a result of lower body fat mass. Circulating levels of G,I and the G/I ratio were lowered by the (P)RR‐B on both diet. The GLUTs gene expression in AT was affected by HF/HC and improved with (P)RR‐B administration. Moreover, the PKB phosphorylation in AT was affected with HF/HC, where (P)RR‐B administration improve PKB phosphorylation in both diet. Conclusion. The pharmacologic blockade of the (P)RR lowered BW in mice on a HF/HC, improved glucose homeostasis potentially by improving GLUTs gene expression profile and PKB phosphorylation in AT. Grant Funding Source : Supported by CDA, MDRC
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".