Modeling the Development of Cleft Lip and Palate in Variable Clefting Mouse Strains
Bibliographic record
Abstract
Epigenetic modifications in A‐strain mice can lead to cleft lip and palate (CLP). All A‐strain mice have a retrotransposon present near the Wnt9b gene, yet, two A‐strain mice cleft at very different rates. A/WySn clefts at 25% while A/J clefts at 5%, yet each line isogenic . The difference in clefting rates is thought to be due to changes in methylation of the retrotransposon. This variation in the penetrance of clefting among strains makes this an interesting model for human orofacial clefting as CLP is also variably penetrant in humans. Here, we test the hypothesis that these mice have subtle variations in 3D cell proliferation and apoptosis that cause variation in the shape of the facial tissues during crucial steps of facial formation, leading to CLP. Further, we predict these changes in proliferation, apoptosis and morphology correlate with Wnt9b levels . Genome changes between related A‐strain mice with different CLP levels also suggest that other loci may be involved in the variable clefting present in these mice. Combined, these results imply that variation in gene expression within a genotype leads to variation in cellular dynamics and the resulting morphogenesis, producing CLP leading to cleft development in a subset of A‐strain mice. Support or Funding Information NIH NIDCR R01 DE019638 to RS and BH. CIHR Foundation Grant to BH and RS. CIHR Postdoctoral Fellowship to RG. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".