Tissue-specific effects of valsartan on <i>rstn</i> and <i>fiaf</i> gene expression in the <i>ob/ob</i> mouse
Bibliographic record
Abstract
The RAS is a novel target in the study of diabetes, and clinical trials have indicated that ARBs, such as valsartan, may exert some of their clinical effects through an influence on adipose tissue. We studied the effect of valsartan on adipokine genes resistin (rstn) and fasting-induced adipose factor (fiaf) using obese and diabetic ob/ob mice. In addition to visceral and subcutaneous fat, rstn and fiaf mRNA levels were also measured in several other tissues known to express these adipokines, including the pituitary, cerebral cortex and hypothalamus. The significant findings were that (a) fiaf gene expression was elevated two- to fourfold in visceral and subcutaneous fat from ob/ob mice, compared with lean controls; (b) the increase in fiaf mRNA in subcutaneous, but not visceral, fat from ob/ob mice was returned to lean control levels following 2 weeks of valsartan treatment; (c) fiaf expression was reduced in the hypothalamus, but not in the cortex or pituitary, of ob/ob mice; (d) rstn expression was greatly reduced in visceral fat from ob/ob mice, compared with lean controls, but this was unaffected by valsartan; and (e) rstn expression was unchanged in all other tissues from ob/ob mice, with or without valsartan treatment.
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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) | 0.000 | 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".