A complex regulatory network of transcription factors critical for ocular development and disease
Bibliographic record
Abstract
The PITX2 'homeobox' and FOXC1 and FOXC2 'forkhead box' transcription factors are critical for eye development and cause human ocular diseases when mutated. We have identified biochemical and genetic links between these transcription factors and a transcriptional regulator protein PRKC apoptosis Wilms' tumor 1 regulator (PAWR) that we propose to functionally connect all these proteins in a common pathway critically involved in eye development. We discovered all binary physical interactions between FOXC1, PITX2, FOXC2 and PAWR. Importantly, PAWR modulates the abilities of PITX2, FOXC1 and FOXC2 to activate their genetic targets. Together with either FOXC1 or FOXC2, PAWR increases PITX2 activity. PAWR reduces PITX2 activity in the absence of FOXC1 or FOXC2. At the same time, PAWR also exerts different regulatory effects on different FOXC target sites. Furthermore, morpholino knockdown of pitx2, foxc1 and pawr in zebrafish indicate that PAWR, FOXC1 and PITX2 genetically interact, and are in the same developmental pathway. These data for the first time tie PITX2, FOXC1, FOXC2 and PAWR into a common regulatory pathway. We have therefore identified a functional link between three transcription factors, modulated by PAWR, which we propose underlies the similar ocular phenotypes and glaucoma pathology caused by mutations of these genes.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".