Fog2 Is Required for Normal Diaphragm and Lung Development in Mice and Humans
Bibliographic record
Abstract
Congenital diaphragmatic hernia and other congenital diaphragmatic defects are associated with significant mortality and morbidity in neonates; however, the molecular basis of these developmental anomalies is unknown. In an analysis of E18.5 embryos derived from mice treated with N-ethyl-N-nitrosourea, we identified a mutation that causes pulmonary hypoplasia and abnormal diaphragmatic development. Fog2 (Zfpm2) maps within the recombinant interval carrying the N-ethyl-N-nitrosourea-induced mutation, and DNA sequencing of Fog2 identified a mutation in a splice donor site that generates an abnormal transcript encoding a truncated protein. Human autopsy cases with diaphragmatic defect and pulmonary hypoplasia were evaluated for mutations in FOG2. Sequence analysis revealed a de novo mutation resulting in a premature stop codon in a child who died on the first day of life secondary to severe bilateral pulmonary hypoplasia and an abnormally muscularized diaphragm. Using a phenotype-driven approach, we have established that Fog2 is required for normal diaphragm and lung development, a role that has not been previously appreciated. FOG2 is the first gene implicated in the pathogenesis of nonsyndromic human congenital diaphragmatic defects, and its necessity for pulmonary development validates the hypothesis that neonates with congenital diaphragmatic hernia may also have primary pulmonary developmental abnormalities.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".