Apical extracellular matrix regulates fold morphogenesis in the <i>Drosophila</i> wing disc
Bibliographic record
Abstract
Summary Tissue folding is a fundamental process occurring often in animal organ development. Here, we study the progression of fold shape and the underlying mechanics in the development of the Drosophila wing disc. We present a 3D segmentation of the apical surface of the wing disc proper from larval stages, when folds grow, to early pupariation, when the tissue unfolds and remodels into a bilayer. We establish morphological metrics to quantify and resolve fold shape in this dataset, introducing a definition of fold depth and width that can be used to characterize folds on a curved surface. Furthermore, we identify fibrous extracellular matrix on the apical side (aECM) that physically connects the two opposing sides of the folds. By modeling a tissue fold with a lateral vertex model endowed by an adhesive layer representing the aECM, we predict that unfolding in the wing disc is preceded by the removal of aECM. Using genetic perturbations, we confirm that aECM adhesion affects fold stability and mechanics: loss of aECM leads to abnormal fold shape and unfolding dynamics, whereas failure to remove aECM at pupariation inhibits unfolding. Finally, we show that these aECM perturbations in larval stages cause morphological phenotypes in the adult wing, demonstrating that the fold morphology of the wing disc helps to define adult wing shape. In total, our work establishes a key mechanical role for aECM in wing disc growth and morphogenesis and advances our general understanding of how epithelial tissue folds can be mechanically stabilized during development.
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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".