Maternal resveratrol administration protects against gestational diabetes‐induced glucose intolerance and islet dysfunction in the rat offspring
Bibliographic record
Abstract
KEY POINTS: Maternal resveratrol (RESV) administration in gestational diabetes (GDM) restored normoglycaemia and insulin secretion. GDM-induced obesity was prevented in male GDM+RESV offspring but not in females. GDM+RESV offspring exhibited improved glucose tolerance and insulin sensitivity. GDM+RESV restored hepatic glucose homeostasis in offspring. Glucose-stimulated insulin secretion was enhanced in GDM+RESV offspring. ABSTRACT: ) in the third week of pregnancy could improve maternal glycaemia and protect the offspring from developing metabolic dysfunction. Female Sprague-Dawley rats consumed a high-fat and sucrose (HFS) diet to induce GDM. Lean controls consumed a low-fat (LF) diet. In the third trimester, when maternal hyperglycaemia was observed, the HFS diet was supplemented with RESV. At weaning, offspring were randomly assigned a LF or HFS diet until 15 weeks of age. In pregnant dams, RESV restored glucose tolerance, normoglycaemia and improved insulin secretion. At 15 weeks of age, GDM+RESV-HFS male offspring were less obese than the GDM-HFS offspring. By contrast, the female GDM+RESV-HFS offspring were similarly as obese as the GDM-HFS group. Hepatic steatosis, insulin resistance, glucose intolerance and dysregulated gluconeogenesis were observed in the male GDM offspring and were attenuated in the offspring of GDM+RESV dams. The dysregulation of several metabolic genes (e.g. ppara, lpl, pepck and g6p) in the livers of GDM offspring was attenuated in the GDM+RESV offspring group. Glucose stimulated insulin secretion was also improved in the islets from offspring of GDM+RESV dams. Thus, maternal RESV supplementation during the third trimester of pregnancy and lactation induced several beneficial metabolic health outcomes for both mothers and offspring. Therefore, RESV could be an alternative to current GDM treatments.
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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 | 0.000 | 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".