Automated multidimensional image analysis reveals a role for Abl in embryonic wound repair
Bibliographic record
Abstract
The embryonic epidermis displays a remarkable ability to repair wounds rapidly. Embryonic wound repair is driven by the evolutionary conserved redistribution of cytoskeletal and junctional proteins around the wound. Drosophila has emerged as a model to screen for factors implicated in wound closure. However, genetic screens have been limited by the use of manual analysis methods. We introduce MEDUSA, a novel image-analysis tool for the automated quantification of multicellular and molecular dynamics from time-lapse confocal microscopy data. We validate MEDUSA by quantifying wound closure in Drosophila embryos, and we show that the results of our automated analysis are comparable to analysis by manual delineation and tracking of the wounds, while significantly reducing the processing time. We demonstrate that MEDUSA can also be applied to the investigation of cellular behaviors in three and four dimensions. Using MEDUSA, we find that the conserved nonreceptor tyrosine kinase Abelson (Abl) contributes to rapid embryonic wound closure. We demonstrate that Abl plays a role in the organization of filamentous actin and the redistribution of the junctional protein β-catenin at the wound margin during embryonic wound repair. Finally, we discuss different models for the role of Abl in the regulation of actin architecture and adhesion dynamics at the wound margin.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".