Magi Is Associated with the Par Complex and Functions Antagonistically with Bazooka to Regulate the Apical Polarity Complex
Bibliographic record
Abstract
The mammalian MAGI proteins play important roles in the maintenance of adherens and tight junctions. The MAGI family of proteins contains modular domains such as WW and PDZ domains necessary for scaffolding of membrane receptors and intracellular signaling components. Loss of MAGI leads to reduced junction stability while overexpression of MAGI can lead to increased adhesion and stabilization of epithelial morphology. However, how Magi regulates junction assembly in epithelia is largely unknown. We investigated the single Drosophila homologue of Magi to study the in vivo role of Magi in epithelial development. Magi is localized at the adherens junction and forms a complex with the polarity proteins, Par3/Bazooka and aPKC. We generated a Magi null mutant and found that Magi null mutants were viable with no detectable morphological defects even though the Magi protein is highly conserved with vertebrate Magi homologues. However, overexpression of Magi resulted in the displacement of Baz/Par3 and aPKC and lead to an increase in the level of PIP3. Interestingly, we found that Magi and Baz functioned in an antagonistic manner to regulate the localization of the apical polarity complex. Maintaining the balance between the level of Magi and Baz is an important determinant of the levels and localization of apical polarity complex.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".