Mouse mutants with neural tube closure defects and their role in understanding human neural tube defects
Bibliographic record
Abstract
BACKGROUND: The number of mouse mutants and strains with neural tube closure defects (NTDs) now exceeds 190, including 155 involving known genes, 33 with unidentified genes, and eight "multifactorial" strains. METHODS: The emerging patterns of mouse NTDs are considered in relation to the unknown genetics of the common human NTDs, anencephaly, and spina bifida aperta. RESULTS: Of the 150 mouse mutants that survive past midgestation, 20% have risk of either exencephaly and spina bifida aperta or both, parallel to the majority of human NTDs, whereas 70% have only exencephaly, 5% have only spina bifida, and 5% have craniorachischisis. The primary defect in most mouse NTDs is failure of neural fold elevation. Most null mutations (>90%) produce syndromes of multiple affected structures with high penetrance in homozygotes, whereas the "multifactorial" strains and several null-mutant heterozygotes and mutants with partial gene function (hypomorphs) have low-penetrance nonsyndromic NTDs, like the majority of human NTDs. The normal functions of the mutated genes are diverse, with clusters in pathways of actin function, apoptosis, and chromatin methylation and structure. The female excess observed in human anencephaly is found in all mouse exencephaly mutants for which gender has been studied. Maternal agents, including folate, methionine, inositol, or alternative commercial diets, have specific preventative effects in eight mutants and strains. CONCLUSIONS: If the human homologs of the mouse NTD mutants contribute to risk of common human NTDs, it seems likely to be in multifactorial combinations of hypomorphs and low-penetrance heterozygotes, as exemplified by mouse digenic mutants and the oligogenic SELH/Bc strain.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".