Offspring from maternal nutrient restriction in mice show variations in adult glucose metabolism similar to human fetal growth restriction
Bibliographic record
Abstract
Fetal growth restriction (FGR) is a pregnancy condition in which fetal growth is suboptimal for gestation, and this population is at increased risk for type 2 diabetes as adults. In humans, maternal malnutrition and placental insufficiency are the most common causes of FGR, and both result in fetal undernutrition. We hypothesized that maternal nutrient restriction (MNR) in mice will cause FGR and alter glucose metabolism in adult offspring. Pregnant CD-1 mice were subjected to MNR (70% of average ad libitum) or control (ad libitum) from E6.5 to birth. Following birth, mice were fostered by mothers on ad libitum feeds. Weight, blood glucose, glucose tolerance and tissue-specific insulin sensitivity were assessed in male offspring. MNR resulted in reduced fetal sizes but caught up to controls by 3 days postnatal age. As adults, glucose intolerance was detected in 19% of male MNR offspring. At 6 months, liver size was reduced (P = 0.01), but pAkt-to-Akt ratios in response to insulin were increased 2.5-fold relative to controls (P = 0.004). These data suggest that MNR causes FGR and long-term glucose intolerance in a population of male offspring similar to human populations. This mouse model can be used to investigate the impacts of FGR on tissues of importance in glucose metabolism.
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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) | 0.000 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".