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Record W2039663505 · doi:10.1017/s0954422410000168

High-fat diet-induced obesity in animal models

2010· review· en· W2039663505 on OpenAlexafffund
Niloofar Hariri, Louise Thibault

Bibliographic record

VenueNutrition Research Reviews · 2010
Typereview
Languageen
FieldNeuroscience
TopicRegulation of Appetite and Obesity
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsObesityGhrelinLeptinEndocrinologyAdipose tissueInternal medicineHormoneDietary fatBiologyMedicine

Abstract

fetched live from OpenAlex

Epidemiological studies have shown a positive relationship between dietary fat intake and obesity. Since rats and mice show a similar relationship, they are considered an appropriate model for studying dietary obesity. The present paper describes the history of using high-fat diets to induce obesity in animals, aims to clarify the consequences of changing the amount and type of dietary fats on weight gain, body composition and adipose tissue cellularity, and explores the contribution of genetics and sex, as well as the biochemical basis and the roles of hormones such as leptin, insulin and ghrelin in animal models of dietary obesity. The major factors that contribute to dietary obesity - hyperphagia, energy density and post-ingestive effects of the dietary fat - are discussed. Other factors that affect dietary obesity including feeding rhythmicity, social factors and stress are highlighted. Finally, we comment on the reversibility of high-fat diet-induced 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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.392
GPT teacher head0.463
Teacher spread0.071 · 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

Citations1,084
Published2010
Admission routes2
Has abstractyes

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