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Record W2110809035 · doi:10.1139/o2012-012

Vitamin A status affects obesity development and hepatic expression of key genes for fuel metabolism in Zucker fatty rats

2012· article· en· W2110809035 on OpenAlexvenueno aff
Yan Zhang, Rui Li, Li Yang, Wei Chen, Shi Zhao, Guoxun Chen

Bibliographic record

VenueBiochemistry and Cell Biology · 2012
Typearticle
Languageen
FieldMedicine
TopicCholesterol and Lipid Metabolism
Canadian institutionsnot available
FundersAllen FoundationAmerican Heart Association
KeywordsEndocrinologyInternal medicineWeaningLeptinObesityFatty liverLipid metabolismTriglycerideVitaminMedicineBiologyDiseaseCholesterol

Abstract

fetched live from OpenAlex

We hypothesized that vitamin A (VA) status may affect obesity development. Male Zucker lean (ZL) and fatty (ZF) rats after weaning were fed a synthetic VA deficient (VAD) or VA sufficient (VAS) diet for 8 weeks before their plasma parameters and hepatic genes' expression were analyzed. The body mass (BM) of ZL or ZF rats fed the VAD diet was lower than that of their corresponding controls fed the VAS diet at 5 or 2 weeks, respectively. The VAD ZL and ZF rats had less food intake than the VAS rats after 5 weeks. The VAD ZL and ZF rats had lower plasma glucose, triglyceride, insulin, and leptin levels, as well as lower liver glycogen content, net mass of epididymal fat, and liver/BM and epididymal fat/BM ratios (ZL only) than their respective VAS controls. VAD rats had lower hepatic Cyp26a1, Srebp-1c, Fas, Scd1, Me1, Gck, and Pklr (ZL and ZF); and higher Igfbp1 (ZL and ZF), Pck1(ZF only), and G6pc (ZF only) mRNA levels than their respective VAS controls. We conclude that ZL and ZF rats responded differently to dietary VA deficiency. VA status affected obesity development and altered the expression of hepatic genes for fuel metabolism in ZF rats. The mechanisms will help us to combat metabolic diseases.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.433

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.012
GPT teacher head0.245
Teacher spread0.233 · 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

Citations46
Published2012
Admission routes1
Has abstractyes

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