Regulation of activation of Rac1 and Cdc42 GTPases in CHRF‐288‐11 cells
Bibliographic record
Abstract
Rac1 and Cdc42 are members of the Rho family of small GTPases and have been shown to promote the formation of lamellipodia and filopodia at the leading edge of motile cells and thus affect cell migration. In the current study we have investigated the activation of Rac1 and Cdc42 by thrombin or collagen in the megakaryocytic cell line, CHRF‐288‐11. Maximal activation of Rac1 by thrombin or collagen was observed at 3 min and 1 min respectively. Similar results were obtained for the thrombin or collagen mediated activation of Cdc42. The calmodulin specific inhibitor, W7, abolished the thrombin or collagen mediated activation of Rac1 in CHRF‐288‐11 cells. However, W7 had no effect on the activation of Cdc42 by thrombin or collagen. The less potent calmodulin inhibitor, W5, did not have any effect on Rac1 or Cdc42 activation by thrombin or collagen. Transient over‐expression of calmodulin in CHRF‐288‐11 cells increased the basal and thrombin mediated activation of Rac1 when compared to control but had no effect on the basal and thrombin mediated activation of Cdc42 when compared to control. The results demonstrate a role for calmodulin in the activation step of Rac1 in CHRF‐288‐11 cells. This is similar to the results for Rac1 regulation in platelets and suggests that the CHRF cells can serve as a model for platelets. This work was supported by a grant to RPB from the Heart & Stroke Foundation of Manitoba.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".