Displacement of basolateral Bazooka/PAR-3 by regulated transport and dispersion during epithelial polarization in<i>Drosophila</i>
Bibliographic record
Abstract
Polarity landmarks guide epithelial development. In the early Drosophila ectoderm, the scaffold protein Bazooka (Drosophila PAR-3) forms apicolateral landmarks to direct adherens junction assembly. However, it is unclear how Bazooka becomes polarized. We report two mechanisms acting in concert to displace Bazooka from the basolateral membrane. As cells form during cellularization, basally localized Bazooka undergoes basal-to-apical transport. Bazooka requires its three postsynaptic density 95, discs large, zonula occludens-1 (PDZ) domains to engage the transport mechanism, but with the PDZ domains deleted, basolateral displacement still occurs by gastrulation. Basolateral PAR-1 activity appears to act redundantly with the transport mechanism. Knockdown of PAR-1 sporadically destabilizes cellularization furrows, but basolateral displacement of Bazooka still occurs by gastrulation. In contrast, basolateral Bazooka displacement is blocked with disruption of both the transport mechanism and phosphorylation by PAR-1. Thus Bazooka is polarized through a combination of transport and PAR-1-induced dispersion from basolateral membranes. Our work complements recent findings in Caenorhabditis elegans and thus suggests the coupling of transport and dispersion is a common protein polarization strategy.
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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 | 0.001 |
| 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".