Maternal resveratrol supplementation in gestational diabetes prevents cardio-metabolic disease development and improves cardiac structure in the rat offspring
Bibliographic record
Abstract
Gestational diabetes mellitus (GDM), a common complication of pregnancy, arises during the third trimester and is characterized by hyperglycemia. GDM increases cardio-metabolic disease risk in mothers and offspring. Current treatments have disadvantages. Resveratrol (RESV), a naturally produced polyphenol, has anti-oxidant and positive metabolic health effects. Thus, we hypothesized that RESV supplementation during the third trimester and lactation would improve maternal glucose tolerance and prevent cardio-metabolic disease in the offspring. A diet-induced GDM model was utilized for this thesis. Different metabolic tests were performed. Echocardiography was used to assess cardiac structure and function. Immunoblotting, qPCR and cardiomyocyte isolations were performed to study mechanisms. RESV supplementation prevented maternal glucose intolerance and cardio-metabolic disease development in the offspring by improving glucose homeostasis and inhibiting cardiac remodelling. Supplementing maternal diets with RESV at the onset of GDM may become a newer intervention to protect mothers and their offspring from GDM-induced short and long-term consequences.
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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) | 0.002 | 0.001 |
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".