HMP-1/α-catenin promotes junctional mechanical integrity during morphogenesis
Bibliographic record
Abstract
Adherens junctions (AJs) are key structures regulating tissue integrity and maintaining adhesion between cells. During morphogenesis, junctional proteins cooperate closely with the actomyosin network to drive cell movement and shape changes. How the junctions integrate the mechanical forces in space and in time during an in vivo morphogenetic event is still largely unknown, due to a lack of quantitative data. To address this issue, we inserted a functional Fluorescence Resonance Energy Transfer (FRET)-based force biosensor within HMP-1/α-catenin of Caenorhabditis elegans. We find that the tension exerted on HMP-1 has a cell-specific distribution, is actomyosin-dependent, but is regulated differently from the tension on the actin cortex during embryonic elongation. By using time-lapse analysis of mutants and tissue-specific rescue experiments, we confirm the role of VAB-9/Claudin as an actin bundle anchor. Nevertheless, the tension exerted on HMP-1 did not increase in the absence of VAB-9/Claudin, suggesting that HMP-1 activity is not upregulated to compensate for loss of VAB-9. Our data indicate that HMP-1 does not modulate HMR-1/E-cadherin turnover, is required to recruit junctional actin but not stress fiber-like actin bundles. Altogether, our data suggest that HMP-1/α-catenin acts to promote the mechanical integrity of adherens junctions.
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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".