Impact of methylenetetrahydrofolate reductase deficiency and low dietary folate on the development of neural tube defects insplotch mice
Bibliographic record
Abstract
BACKGROUND: The etiology of neural tube defects (NTDs) is multifactorial, with environmental and genetic determinants. Folate supplementation prevents the majority of NTDs, and a polymorphism in methylenetetrahydrofolate reductase (MTHFR) has become recognized as a genetic risk factor. The mechanisms by which folate affects NTD development are unclear. The Splotch (Sp) mouse is a well-characterized mouse model for studying spontaneous NTDs. To assess the potential interaction between folate metabolism and the Sp mutant in NTD development, we studied mice with both Sp and Mthfr mutations, as well as the interaction between Sp and low dietary folate. METHODS: Wild-type, single Mthfr+/-mutant, single Sp/+mutant, and double mutant (Mthfr+/-, Sp/+) female mice were mated with males of the same genotype. Embryos were examined for NTDs on gestational day (GD) 13.5. To investigate the effects of folate deficiency on Sp mice, Sp/+female mice were fed a control diet (CD), a moderately folic acid-deficient diet (MFADD), or a severely folic acid-deficient diet (SFADD). They were mated with Sp/+males and the embryos were examined. RESULTS: There were no differences in the incidence or severity of NTDs in embryos from double-mutant mating pairs compared to those from single Sp mutants. Embryos from Mthfr+/-dams did not exhibit NTDs. Diets deficient in folate did not influence the incidence or severity of NTDs in embryos from Sp/+mice. CONCLUSIONS: We did not observe an interaction between Sp and Mthfr mutations, or between the Sp mutation and low dietary folate, in NTD development in Splotch mice.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".