Modeling the roles of protein kinase Cβ and η in single-cell wound repair
Bibliographic record
Abstract
Wounded cells such as Xenopus oocytes respond to damage by assembly and closure of an array of actin filaments and myosin-2 controlled by Rho GTPases, including Rho and Cdc42. Rho and Cdc42 are patterned around wounds in a characteristic manner, with active Rho concentrating in a ring-like zone inside a larger, ring-like zone of active Cdc42. How this patterning is achieved is unknown, but Rho and Cdc42 at wounds are subject to regulation by other proteins, including the protein kinases C. Specifically, Cdc42 and Rho activity are enhanced by PKCβ and inhibited by PKCη. We adapt a mathematical model of Simon and coworkers to probe the possible roles of these kinases. We show that PKCβ likely affects the magnitude of positive Rho-Abr feedback, whereas PKCη acts on Cdc42 inactivation. The model explains both qualitative and some overall quantitative features of PKC-Rho GTPase regulation. It also accounts for the previous, peculiar observation that ∼ 20% of cells overexpressing PKCη display zone inversions--that is, displacement of active Rho to the outside of the active Cdc42.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".