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The renin‐angiotensin system: a link between obesity, inflammation and insulin resistance

2011· review· en· W1897553699 on OpenAlexaff
Nishan S. Kalupahana, Naïma Moustaïd‐Moussa

Bibliographic record

VenueObesity Reviews · 2011
Typereview
Languageen
FieldMedicine
TopicRenin-Angiotensin System Studies
Canadian institutionsCanadian Obesity Network
Fundersnot available
KeywordsInsulin resistanceAdipose tissueObesityEndocrinologyInternal medicineDiabetes mellitusMedicineRenin–angiotensin systemType 2 diabetesInsulinBlood pressure

Abstract

fetched live from OpenAlex

The renin-angiotensin system (RAS) is classically known for its role in regulation of blood pressure, fluid and electrolyte balance. Recently, several local RASs in organs such as brain, heart, pancreas and adipose tissue have also been identified. Evidence from clinical trials suggests that in addition to anti-hypertensive effects, pharmacological inhibition of RAS also provides protection against the development of type-2 diabetes. Moreover, animal models with targeted inactivation of RAS genes exhibit improved insulin sensitivity and are protected from high-fat diet-induced obesity and insulin resistance. Because there is evidence for RAS overactivation in obesity, it is possible that RAS is a link between obesity and insulin resistance. This review summarizes the evidence and mechanistic insights on the associations between RAS, obesity and insulin resistance, with special emphasis on the role of adipose tissue RAS in the pathogenesis of metabolic derangements in obesity.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.080
GPT teacher head0.320
Teacher spread0.240 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations275
Published2011
Admission routes1
Has abstractyes

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