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Record W2003646970 · doi:10.1177/1479164110369848

Tissue-specific effects of valsartan on <i>rstn</i> and <i>fiaf</i> gene expression in the <i>ob/ob</i> mouse

2010· article· en· W2003646970 on OpenAlexafffund
S A Imran, RE Brown, Michael Wilkinson

Bibliographic record

VenueDiabetes and Vascular Disease Research · 2010
Typearticle
Languageen
FieldMedicine
TopicAdipokines, Inflammation, and Metabolic Diseases
Canadian institutionsDalhousie University
FundersHealth CanadaNovartis PharmaNova Scotia Health Research Foundation
KeywordsEndocrinologyInternal medicineValsartanMedicineAdipokineAdipose tissueHypothalamusResistinDiabetes mellitusInsulin resistanceBlood pressure

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.449
Threshold uncertainty score0.535

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.017
GPT teacher head0.297
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2010
Admission routes2
Has abstractyes

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