Bibliographic record
Abstract
Tissue thinning and spreading, a morphogenetic movement termed epiboly, is used widely during animal development. In zebrafish, epiboly is a prominent cell movement during gastrulation, whereby a squamous epithelium (the enveloping layer), a multi-layer of loosely packed cells (the deep cells), and a yolk nuclear syncytium (the yolk syncytial layer) undergo coordinated expansion to engulf the yolk and close the blastopore. Elucidating the mechanisms that underlie epiboly is important not only for understanding animal development in general, but also for providing insights into fundamental cell behaviors including cell intercalation, cell adhesion, cell signaling, and epithelial morphogenesis. Here, recent work is reviewed with a focus on findings that advance our understanding of (1) the role of actomyosin motors in the yolk cell to drive epiboly, (2) the mechanisms that underlie the spreading of the epithelial enveloping layer, and (3) the regulation of deep cell movements by E-cadherin based adhesion. A discussion of how these new insights add to the current view of epiboly and future prospects is also presented. Overall, the study of zebrafish epiboly can provide general and broadly applicable insights into the genetic, molecular, and cellular control of morphogenesis.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".