Modulation of cellular polarization and migration by ephrin/Eph signal-mediated boundary formation
Bibliographic record
Abstract
Compartment boundaries are essential for ensuring proper cell organization during embryo development and in adult tissues, yet the mechanisms underlying boundary establishment are not completely understood. A number of mechanisms, including (i) differential adhesion, (ii) differential tension, and (iii) cell signaling-mediated cell repulsion, are known to contribute and likely a context-dependent balance of each of these dictates boundary implementation. The ephrin/Eph signaling pathway is known to impact boundary formation in higher animals. In different contexts, ephrin/Eph signaling is known to modulate adhesive properties and migratory behavior of cells. Furthermore it has been proposed that ephrin/Eph signaling may modulate cellular tensile properties, leading to boundary implementation. It remains unclear however, whether, in different contexts, ephrin/Eph act through distinct dominant action modes (e.g. differential adhesion vs. cell repulsion), or whether ephrin/Eph signaling elicits multiple cellular changes simultaneously. Here, using micropatterning of cells over-expressing either EphB3 or ephrinB1, we assess the contribution of each these factors in one model. We show that in this system ephrinB1/EphB3-mediated boundaries are accompanied by modulation of tissue-level architecture and polarization of cell migration. These changes are associated with changes in cell shape and cytoskeletal organization also suggestive of altered cellular tension.
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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) | 0.000 | 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".