Continued Postnatal Administration of Resveratrol Prevents Diet-Induced Metabolic Syndrome in Rat Offspring Born Growth Restricted
Bibliographic record
Abstract
OBJECTIVE: A prenatal hypoxic insult leading to intrauterine growth restriction (IUGR) increases the susceptibility to develop metabolic syndrome (MetS) later in life. Since resveratrol (Resv), the polyphenol produced by plants, exerts insulin-sensitizing effects, we tested whether Resv could prevent deleterious metabolic effects of being born IUGR. RESEARCH DESIGN AND METHODS: Pregnant rats were exposed to either a normoxic (control; 21% O(2)) or a hypoxic (IUGR; 11.5% O(2)) environment during the last third of gestation. After weaning, male offspring were randomly assigned to receive either a high-fat (HF; 45% fat) diet or an HF diet with Resv (4 g/kg diet) for 9 weeks when various parameters of the MetS were measured. RESULTS: Relative to normoxic controls, hypoxia-induced IUGR offspring developed a more severe MetS, including glucose intolerance and insulin resistance, increased intra-abdominal fat deposition and intra-abdominal adipocyte size, and increased plasma triacylglycerol (TG) and free fatty acids, as well as peripheral accumulation of TG, diacylglycerol, and ceramides. In only IUGR offspring, the administration of Resv reduced intra-abdominal fat deposition to levels comparable with controls, improved the plasma lipid profile, and reduced accumulation of TG and ceramides in the tissues. Moreover, Resv ameliorated insulin resistance and glucose intolerance as well as impaired Akt signaling in the liver and skeletal muscle of IUGR offspring and activated AMP-activated protein kinase, which likely contributed to improved metabolic parameters in Resv-treated IUGR rats. CONCLUSIONS: Our results suggest that early, postnatal administration of Resv can improve the metabolic profile of HF-fed offspring born from pregnancies complicated by IUGR.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".