Vitamin A status affects obesity development and hepatic expression of key genes for fuel metabolism in Zucker fatty rats
Bibliographic record
Abstract
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.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".