Effects of genetics and in utero diet on murine pancreatic development
Bibliographic record
Abstract
Intrauterine (IU) malnutrition could alter pancreatic development. In this study, we describe the effects of high-fat diet (HFD) during pregnancy on fetal growth and pancreatic morphology in an 'at risk' animal model of metabolic disease, the glucose transporter 4 (GLUT4) heterozygous mouse (G4+/-). WT female mice mated with G4+/- males were fed HFD or control diet (CD) for 2 weeks before mating and throughout pregnancy. At embryonic day 18.5, fetuses were killed and pancreata isolated for analysis of morphology and expression of genes involved in insulin (INS) cell development, proliferation, apoptosis, glucose transport and function. Compared with WT CD, WT HFD fetal pancreata had a 2.4-fold increase in the number of glucagon (GLU) cells (P=0.023). HFD also increased GLU cell size by 18% in WT pancreata compared with WT CD. Compared with WT CD, G4+/- CD had an increased number of INS cells and decreased INS and GLU cell size. Compared with G4+/- CD, G4+/- HFD fetuses had increased pancreatic gene expression of Igf2, a mitogen and inhibitor of apoptosis. The expression of genes involved in proliferation, apoptosis, glucose transport, and INS secretion was not altered in WT HFD compared with G4+/- HFD pancreata. In contrast to WT HFD pancreata, HFD exposure did not alter pancreatic islet morphology in fetuses with GLUT4 haploinsufficiency; this may be mediated in part by increased Igf2 expression. Thus, interactions between IU diet and fetal genetics may play a critical role in the developmental origins of health and disease.
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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 | 0.001 |
| 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".