Control of gastrula cell motility by the <i>Goosecoid</i>/<i>Mix.1</i>/ <i>Siamois</i> network: Basic patterns and paradoxical effects
Bibliographic record
Abstract
In the vegetal half of the Xenopus gastrula, cell populations differ with respect to migration on fibronectin substratum. We show that the paired-class homeodomain transcription factors Goosecoid (Gsc), Mix.1, and Siamois (Sia) are involved in the modulation of migration velocity and cell polarity. Mix.1 is expressed in the whole vegetal half and serves as a competence factor that is necessary, but not sufficient, for rapid cell migration and polarization. In the head mesoderm, Gsc and Sia are coexpressed with Mix.1, promoting rapid cell migration and polarization. Ectopic expression of Gsc and Sia in both vegetal and ventral regions often generates paradoxical effects; if a factor activates a certain motility trait in one region, it inhibits it in the other. Migration velocity and cell polarity are regulated independently. Fast and efficiently migrating multipolar cells and slow-moving polarized cells can be obtained by ectopic expression of these transcription factors in different combinations.
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) | 0.000 | 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 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".