Timing of Maternal Exposure to a High Fat Diet and Development of Obesity and Hyperinsulinemia in Male Rat Offspring: Same Metabolic Phenotype, Different Developmental Pathways?
Bibliographic record
Abstract
Objective. Offspring born to mothers either fed an obesogenic diet throughout their life or restricted to pregnancy and lactation demonstrate obesity, hyperinsulinemia, and hyperleptinemia, irrespective of their postweaning diet. We examined whether timing of a maternal obesogenic diet results in differential regulation of pancreatic adipoinsular and inflammatory signaling pathways in offspring. Methods. Female Wistar rats were randomized into 3 groups: (1) control (CONT): fed a control diet preconceptionally and during pregnancy and lactation; (2) maternal high fat (MHF): fed an HF diet throughout their life and during pregnancy and lactation; (3) pregnancy and lactation HF (PLHF): fed a control diet throughout life until mating, then HF diet during pregnancy and lactation. Male offspring were fed the control diet postweaning. Plasma and pancreatic tissue were collected, and mRNA concentrations of key factors regulating adipoinsular axis signaling were determined. Results. MHF and PLHF offspring exhibited increased adiposity and were hyperinsulinemic and hyperleptinemic compared to CONT. Despite a similar anthropometric phenotype, MHF and PLHF offspring exhibited distinctly different expression for key pancreatic genes, dependent upon maternal preconceptional nutritional background. Conclusions. These data suggest that despite using differential signaling pathways, obesity in offspring may be an adaptive outcome of early life exposure to HF during critical developmental windows.
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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 | 0.000 |
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".