Pattern formation of Rho GTPases in single cell wound healing
Bibliographic record
Abstract
The Rho GTPases-Rho, Rac, and Cdc42-control an enormous variety of processes, many of which reflect activation of these GTPases in spatially confined and mutually exclusive zones. By using mathematical models and experimental results to establish model parameters, we analyze the formation and segregation of Rho and Cdc42 zones during Xenopus oocyte wound repair and the role played by Abr, a dual guanine nucleotide exchange factor-GTPase-activating protein, in this process. The Rho and Cdc42 zones are found to be best represented as manifestations of spatially modulated bistability, and local positive feedback between Abr and Rho can account for the maintenance and dynamic properties of the Rho zone. In contrast, the invocation of an Abr-independent positive feedback loop is required to account for Cdc42 spatial bistability. In addition, the model replicates the results of previous in vivo experiments in which Abr activity is manipulated. Further, simulating the model with two closely spaced wounds made nonintuitive predictions about the Rho and Cdc42 patterns; these predictions were confirmed by experiment. We conclude that the model is a useful tool for analysis of Rho GTPase signaling and that the Rho GTPases can be fruitfully considered as components of intracellular pattern formation systems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".