ESCRT-III-dependent adhesive and mechanical changes are triggered by a mechanism detecting alteration of septate junction integrity in Drosophila epithelial cells
Bibliographic record
Abstract
Barrier functions of proliferative epithelia are constantly challenged by mechanical and chemical constraints. How epithelia respond to and cope with disturbances of barrier functions to allow tissue integrity maintenance is poorly characterised. Cellular junctions play an important role in this process and intracellular traffic contribute to their homeostasis. Here, we reveal that, in Drosophila pupal notum , alteration of the bi- or tricellular septate junctions (SJs) triggers a mechanism with two prominent outcomes. On one hand, there is an increase in the levels of E-cadherin, F-actin, and non-muscle myosin II in the plane of adherens junctions. On the other hand, β-integrin/Vinculin-positive cell contacts are reinforced along the lateral and basal membranes. We found that the weakening of SJ integrity, caused by the depletion of bi- or tricellular SJ components, alters ESCRT-III/Vps32/Shrub distribution, reduces degradation and instead favours recycling of SJ components, an effect that extends to other recycled transmembrane protein cargoes including Crumbs, its effector β-Heavy Spectrin Karst, and β-integrin. We propose a mechanism by which epithelial cells, upon sensing alterations of the SJ, reroute the function of Shrub to adjust the balance of degradation/recycling of junctional cargoes and thereby compensate for barrier junction defects to maintain epithelial integrity.
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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".