The effect of Rho drugs on mast cell activation and degranulation
Bibliographic record
Abstract
Mast cells are tissue-resident immune cells that produce potent proinflammatory mediators, which are stored in cytoplasmic granules. Stimulation triggers degranulation, a process that mobilizes granules to dock and fuse to the plasma membrane, releasing mediators. Mast cell degranulation has an important role in immunity but can also intensify inflammation and contribute to allergic disorders. Hence, it is important to understand signaling pathways that regulate mast cell degranulation. Here, we examined the role of Rho proteins in regulating mast cell activation leading to degranulation. RBL-2H3 cells and bone marrow-derived mast cells (BMMCs) were stimulated through aggregation of FcεRI receptors. Stimulated cells showed a large increase in the levels of activated Rac and, to a lesser extent, RhoA. Drugs were used to acutely inhibit the function of specific Rho proteins. The Rac inhibitor EHT-1864 and the RhoA inhibitor rhosin inhibited degranulation. Microscopic characterization showed that, upon stimulation, RBL-2H3 cells formed surface ridges that grew into large protrusions reminiscent of circular dorsal ruffles, which flattened into large lamellipodia. LysoTracker-labeled cells showed granules stream into peripheral protrusions. EHT-1864 reduced granule motility, whereas rhosin increased motility; both drugs affected the formation of peripheral protrusions. These results showed that, in response to stimuli, Rho proteins control discrete cytoskeletal remodeling processes that are needed for granule exocytosis. Rac is required to stimulate the remodeling of mast cells, triggering actin-mediated flattening of the cell periphery to create an active degranulation zone, whereas RhoA controls the streaming of highly motile granules into the active zone.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".