Mutation of foxl1 Results in Reduced Cartilage Markers in a Zebrafish Model of Otosclerosis
Bibliographic record
Abstract
Bone diseases such as otosclerosis (conductive hearing loss) and osteoporosis (low bone mineral density) can result from the abnormal expression of genes that regulate cartilage and bone development. The forkhead box transcription factor FOXL1 has been identified as the causative gene in a family with autosomal dominant otosclerosis and has been reported as a candidate gene in GWAS meta-analyses for osteoporosis. This potentially indicates a novel role for foxl1 in chondrogenesis, osteogenesis, and bone remodelling. We created a foxl1 mutant zebrafish strain as a model for otosclerosis and osteoporosis and examined jaw bones that are homologous to the mammalian middle ear bones, and mineralization of the axial skeleton. We demonstrate that foxl1 regulates the expression of collagen genes such as collagen type 1 alpha 1a and collagen type 11 alpha 2, and results in a delay in jawbone mineralization, while the axial skeleton remains unchanged. foxl1 may also act with other forkhead genes such as foxc1a, as loss of foxl1 in a foxc1a mutant background increases the severity of jaw calcification phenotypes when compared to each mutant alone. Our zebrafish model demonstrates atypical cartilage formation and mineralization in the zebrafish craniofacial skeleton in foxl1 mutants and demonstrates that aberrant collagen expression may underlie the development of otosclerosis.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".