Fat1 interacts with Fat4 to regulate neural tube closure, neural progenitor proliferation and apical constriction during mouse brain development
Bibliographic record
Abstract
Mammalian brain development requires coordination between neural precursor proliferation, differentiation and cellular organization to create the intricate neuronal networks of the adult brain. Here, we examined the role of the atypical cadherins Fat1 and Fat4 in this process. We show that mutation of Fat1 in mouse embryos causes defects in cranial neural tube closure, accompanied by an increase in the proliferation of cortical precursors and altered apical junctions, with perturbations in apical constriction and actin accumulation. Similarly, knockdown of Fat1 in cortical precursors by in utero electroporation leads to overproliferation of radial glial precursors. Fat1 interacts genetically with the related cadherin Fat4 to regulate these processes. Proteomic analysis reveals that Fat1 and Fat4 bind different sets of actin-regulating and junctional proteins. In vitro data suggest that Fat1 and Fat4 form cis-heterodimers, providing a mechanism for bringing together their diverse interactors. We propose a model in which Fat1 and Fat4 binding coordinates distinct pathways at apical junctions to regulate neural progenitor proliferation, neural tube closure and apical constriction.
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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 | 0.000 | 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".