DOCK5 functions as a key signaling adaptor that links FcεRI signals to microtubule dynamics during mast cell degranulation
Bibliographic record
Abstract
Mast cells play a key role in the induction of anaphylaxis, a life-threatening IgE-dependent allergic reaction, by secreting chemical mediators that are stored in secretory granules. Degranulation of mast cells is triggered by aggregation of the high-affinity IgE receptor, FcεRI, and involves dynamic rearrangement of microtubules. Although much is known about proximal signals downstream of FcεRI, the distal signaling events controlling microtubule dynamics remain elusive. Here we report that DOCK5, an atypical guanine nucleotide exchange factor (GEF) for Rac, is essential for mast cell degranulation. As such, we found that DOCK5-deficient mice exhibit resistance to systemic and cutaneous anaphylaxis. The Rac GEF activity of DOCK5 is surprisingly not required for mast cell degranulation. Instead, DOCK5 associated with Nck2 and Akt to regulate microtubule dynamics through phosphorylation and inactivation of GSK3β. When DOCK5-Nck2-Akt interactions were disrupted, microtubule formation and degranulation response were severely impaired. Our results thus identify DOCK5 as a key signaling adaptor that orchestrates remodeling of the microtubule network essential for mast cell degranulation.
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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) | 0.001 | 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".