An update to the list of mouse mutants with neural tube closure defects and advances toward a complete genetic perspective of neural tube closure
Bibliographic record
Abstract
The number of mouse mutants and strains with neural tube defects (NTDs) now exceeds 240, including 205 representing specific genes, 30 for unidentified genes, and 9 multifactorial strains. These mutants identify genes needed for embryonic neural tube closure. Reports of 50 new NTD mutants since our 2007 review (Harris and Juriloff, 2007) were considered in relation to the previously reviewed mutants to obtain new insights into mechanisms of NTD etiology. In addition to null mutations, some are hypomorphs or conditional mutants. Some mutations do not cause NTDs on their own, but do so in digenic, trigenic, and oligogenic combinations, an etiology that likely parallels the nature of genetic etiology of human NTDs. Mutants that have only exencephaly are fourfold more frequent than those that have spina bifida aperta with or without exencephaly. Many diverse cellular functions and biochemical pathways are involved; the NTD mutants draw new attention to chromatin modification (epigenetics), the protease-activated receptor cascade, and the ciliopathies. Few mutants directly involve folate metabolism. Prevention of NTDs by maternal folate supplementation has been tested in 13 mutants and reduces NTD frequency in six diverse mutants. Inositol reduces spina bifida aperta frequency in the curly tail mutant, and three new mutants involve inositol metabolism. The many NTD mutants are the foundation for a future complete genetic understanding of the processes of neural fold elevation and fusion along mechanistically distinct cranial-caudal segments of the neural tube, and they point to several candidate processes for study in human NTD etiology.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.005 |
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".