Genotype–Phenotype Correlation of Tracheal Cartilaginous Sleeves and <i>Fgfr2</i> Mutations in Mice
Bibliographic record
Abstract
Objectives To characterize tracheal cartilage morphology in mouse models of fibroblast growth factor receptor (Fgfr2)‐related craniosynostosis syndromes. To establish relationships between specific Fgfr2 mutations and tracheal cartilaginous sleeve (TCS) phenotypes in these mouse models. Methods Postnatal day 0 knock‐in mouse lines with disease‐specific genetic variations in the Fgfr2 gene (Fgfr2C342Y/C342Y, Fgfr2C342Y/+, Fgfr2+/Y394C, Fgfr2+/S252W, and Fgfr2+/P253R) as well as line‐specific controls were utilized. Tracheal cartilage morphology as measured by gross analyses, microcomputed tomography (μCT), and histopathology were compared using Chi‐squared and single‐factor analysis of variance statistical tests. Results A greater proportion of rings per trachea were abnormal in Fgfr2C342Y/+ tracheas (63%) than Fgfr2+/S252W (17%), Fgfr2+/P253R (17%), Fgfr2+/Y394C (12%), and controls (10%) (P < .001 for each vs. Fgfr2C342Y/+). TCS segments were found only in Fgfr2C342Y/C342Y (100%) and Fgfr2C342Y/+ (72%) tracheas. Cricoid and first‐tracheal ring fusion was noted in all Fgfr2C342Y/C342Y and 94% of Fgfr2C342Y/+ samples. The Fgfr2C342Y/C342Y and Fgfr2C342Y/+ groups were found to have greater areas and volumes of cartilage than other lines on gross analysis and μCT. Histologic analyses confirmed TCS among the Fgfr2C342Y/C342Y and Fgfr2C342Y/+ groups, without appreciable differences in cartilage morphology, cell size, or density; no histologic differences were observed among other Fgfr2 lines compared to controls. Conclusion This study found TCS phenotypes only in the Fgfr2C342Y mouse lines. These lines also had increased tracheal cartilage compared to other mutant lines and controls. These data support further study of the Fgfr2 mouse lines and the investigation of other Fgfr2 variants to better understand their role in tracheal development and TCS formation. Level of Evidence NA Laryngoscope, 131:E1349–E1356, 2021
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".