Fank1 and Jazf1 promote multiciliated cell differentiation in the mouse airway epithelium
Bibliographic record
Abstract
ABSTRACT The airways are lined by secretory and multiciliated cells which function together to remove particles and debris from the respiratory tract. The transcriptome of multiciliated cells has been extensively studied, but the function of many of the genes identified is unknown. We have established an assay to test the ability of over-expressed transcripts to promote multiciliated cell differentiation in mouse embryonic tracheal explants. Overexpression data indicated that Fibronectin type 3 and ankyrin repeat domains 1 (Fank1) and JAZF zinc finger 1 (Jazf1) promoted multiciliated cell differentiation alone, and cooperatively with the canonical multiciliated cell transcription factor Foxj1. Moreover, knock-down of Fank1 or Jazf1 in adult mouse airway epithelial cultures demonstrated that these factors are both required for ciliated cell differentiation in vitro. This analysis identifies Fank1 and Jazf1 as novel regulators of multiciliated cell differentiation. Moreover, we show that they are likely to function downstream of IL6 signalling and upstream of Foxj1 activity in the process of ciliated cell differentiation. In addition, our in vitro explant assay provides a convenient method for preliminary investigation of over-expression phenotypes in the developing mouse airways. This article has an associated First Person interview with the first author of the paper.
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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 | 0.000 | 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".