Bibliographic record
Abstract
Abstract GLI1, GLI2 and GLI3 transcription factors are the key effectors of mammalian Hedgehog signalling. Mutations in these transcription factors are implicated in severe congenital malformations and malignancies in humans and in mice. Analysis of mouse models has revealed that the patterning and development of multiple organ systems is dependent on a tightly regulated balance of Gli activator and repressor activity. Consequently, mutations in the Hh pathway machinery that affect Gli function or processing result in phenotypes with a striking resemblance to GLI‐associated disorders. The primary cilium was identified as a critical component of Hh signalling due to the phenotypic overlap between Hh‐pathway mutants and mice with defects in ciliogenesis. Many mutations in genes regulating cilia structure and function have been identified in human ciliopathies. This new class of diseases shares significant phenotypic overlap with GLI‐related syndromes. Phenotypic analysis of mice with compromised cilia function has revealed new aspects of Gli regulation demonstrating the utility of mouse models in the characterisation of novel disease phenotypes. Key Concepts: Balance of GLI activator and repressor is required for normal development. Shift of the balance towards low or high GLI3R levels results in severe congenital malformations. Shift of the balance towards high GLI activator results in cancer. Mutations affecting different domains of bifunctional transcription factor Gli3 give rise to distinct phenotypes. Mutations affecting Hh pathway machinery affect Gli processing and activity and result in Gli‐related phenotypes. The primary cilium is critical for Hh signal transduction. Mutations in regulators of primary cilia structure and function result in ciliopathies, which share many overlapping phenotypes with GLI‐associated syndromes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".