Wounded cells drive rapid epidermal repair in the early<i>Drosophila</i>embryo
Bibliographic record
Abstract
Epithelial tissues are protective barriers that display a remarkable ability to repair wounds. Wound repair is often associated with an accumulation of actin and nonmuscle myosin II around the wound, forming a purse string. The role of actomyosin networks in generating mechanical force during wound repair is not well understood. Here we investigate the mechanisms of force generation during wound repair in the epidermis of early and late Drosophila embryos. We find that wound closure is faster in early embryos, where, in addition to a purse string around the wound, actomyosin networks at the medial cortex of the wounded cells contribute to rapid wound repair. Laser ablation demonstrates that both medial and purse-string actomyosin networks generate contractile force. Quantitative analysis of protein localization dynamics during wound closure indicates that the rapid contraction of medial actomyosin structures during wound repair in early embryos involves disassembly of the actomyosin network. By contrast, actomyosin purse strings in late embryos contract more slowly in a mechanism that involves network condensation. We propose that the combined action of two force-generating structures--a medial actomyosin network and an actomyosin purse string--contributes to the increased efficiency of wound repair in the early embryo.
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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".