Zebrafish yolk syncytial nuclei migrate along a dynamic microtubule network
Bibliographic record
Abstract
Abstract In teleosts, the yolk syncytial layer is a multinucleate syncytium that functions as an extraembryonic signaling center to pattern the mesendoderm, coordinate morphogenesis and supply nutrients to the embryo. The zebrafish is an excellent system for studying this morphogenetically active tissue. The external yolk syncytial nuclei (e-YSN) undergo microtubule dependent epiboly movements that distribute the nuclei over the yolk. How e-YSN epiboly proceeds, and what role the yolk microtubule network plays is not understood but currently it is proposed that e-YSN are pulled vegetally as the microtubule network shortens from the vegetal pole. Data from our live imaging studies suggest that the yolk microtubule network is dismantled from the animal and vegetal regions and show that a region of stabilized microtubules forms before nuclear migration begins. e-YSN do not appear to be pulled vegetally but rather move along a dynamic microtubule network. We also show that overexpression of the KASH domain of Syne2a impairs e-YSN movement, implicating the LINC complex in e-YSN migration. This work provides new insights into the role of microtubules in morphogenesis of an extraembryonic tissue. Summary Statement Analysis of yolk syncytial nuclear migration during zebrafish epiboly reveals that nuclei migrate along and largely beneath a dynamically yolk microtubule network.
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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) | 0.002 | 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".