Toward understanding the genetic basis of neural tube defects
Bibliographic record
Abstract
Neural tube defects (NTDs) represent a common group of severe congenital malformations that result from failure of neural tube closure during early development. Their etiology is quite complex involving environmental and genetic factors and their underlying molecular and cellular pathogenic mechanisms remain poorly understood. Animal studies have recently demonstrated an essential role for the planar cell polarity pathway (PCP) in mediating a morphogenetic process called convergent extension during neural tube formation. Alterations in members of this pathway lead to NTDs in vertebrate models, representing novel and exciting candidates for human NTDs. Genetic studies in NTDs have focused mainly on folate-related genes based on the finding that perinatal folic acid supplementation reduces the risk of NTDs by 60-70%. A few variants in these genes have been found to be significantly associated with an increased risk for NTDs. The candidate gene approach investigating genes involved in neurulation has failed to identify major causative genes in the etiology of NTDs. Despite this history of generally negative findings, we are achieving a rapid and impressive progress in understanding the genetic basis of NTDs, based mainly on the powerful tool of animal models.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".