Human neural tube defects: Genetic causes and prevention
Bibliographic record
Abstract
Neural tube defects (NTDs) are severe congenital malformations affecting 1-2 in 1,000 live births, whose etiology is multifactorial, involving environmental and genetic factors. NTDs arise as consequence of the failure of fusion of the neural tube early during embryogenesis. NTDs' pathogenesis has been linked to genes involved in folate metabolism, consistent with an epidemiologic evidence that 70% of NTDs can be prevented by maternal periconceptional supplementation. However, polymorphisms in such genes are not linked in all populations, suggesting that other genetic factors and environmental factors could be involved. Animal models have provided crucial mechanistic information and possible candidate genes to explain susceptibility to NTDs. A crucial role has been assigned to the planar cell polarity (PCP) pathway, a highly conserved, non-canonical Wnt-frizzled-dishevelled signaling cascade that plays a key role in establishing and maintaining polarity in the plane of the epithelium and in the process of convergent extension during gastrulation and neurulation in vertebrates. The Loop-tail (Lp) mouse that develops craniorachischisis carry missense mutations in the PCP core gene Vangl2, that is the mammalian homolog of the Drosophila Strabismus/Van gogh (Stbm/Vang). The presence of mutations in human VANGL1 and VANGL2 genes encourages us to extend the investigation to other PCP genes that, with VANGL, play an essential role in neurulation during development.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".