Accelerated embryonic development associated with increased risk of neural tube defects induced by maternal diet in offspring of SELH/Bc mice
Bibliographic record
Abstract
BACKGROUND: The SELH/Bc mouse strain has a high risk of the NTD, exencephaly, caused by multifactorial genetics. All SELH/Bc embryos have delayed elevation of neural folds; some never elevate (future exencephalics). Maternal diets affect SELH/Bc exencephaly rates: 25-35% on Purina Diet 5015 versus 5-10% on Purina Diet 5001. We hypothesized that in SELH/Bc, the diets affect maternal blood glucose and embryonic developmental rate. METHODS: We compared mice fed the two diets. On GD 9.4 we tested maternal blood glucose and examined embryos for developmental age (somite count) and cranial neural fold morphology. We observed GD 14 exencephaly rates. RESULTS: Diet 5015 caused fivefold more exencephaly (40 vs. 7% on GD 14), significantly higher mean maternal blood glucose in replicate experiments (6.3 vs. 5.5, p < .05; 6.3 vs. 5.3 mmol/L, p < .05), and significantly higher mean litter somite count on GD 9.4 (18.4 vs. 15.0, p < .05; 16.7 vs. 14.4 somites, p < .05). Among midrange embryos (15-16 somites), embryos from Diet 5015 were significantly shifted to earlier stages of midbrain fold morphology and had significantly more distance between the tips of the folds (p < .05). CONCLUSIONS: In SELH/Bc mice, the 5015 diet causes higher maternal blood glucose, a faster overall embryonic developmental rate during neural tube closure, and delayed midbrain fold elevation relative to overall development. This pattern suggests that maternal dietary effects that modestly increase embryonic growth rate may exacerbate a lack of coordination between genetically delayed neural folds and normally developing underlying tissues, increasing risk of NTD.
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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 | 0.001 | 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".