Role of CrkII in Fcγ Receptor-mediated Phagocytosis
Bibliographic record
Abstract
Phagocytosis of IgG-opsonized pathogens by Fcgamma receptors requires extensive remodeling of the actin cytoskeleton, a process regulated by the small GTPase Rac. Vav was thought to be the guanine nucleotide exchange factor responsible for the activation of Rac, but recent evidence indicates that Fcgamma receptor-mediated phagocytosis is unaffected in macrophages lacking all three isoforms of Vav. We therefore tested whether another GEF, DOCK180, participates in Fcgamma receptor-initiated phagocytosis. DOCK180 associates with the adaptor protein Crk, which mediates recruitment of the GEF to sites of tyrosine phosphorylation. CrkII and DOCK180 were found to accumulate at the phagocytic cup. Knockdown of Crk or DOCK180 in murine macrophages using small interfering RNA inhibited phagocytosis of IgG-opsonized particles. Moreover, transfection of dominant negative CrkII prevented both recruitment of DOCK180 and the activation of Rac at the phagocytic cup. This is the first report of a role for either Crk or DOCK180 in Fcgamma receptor-mediated phagocytosis. The Crk-DOCK180 complex is involved in the clearance of apoptotic cells, which unlike the ingestion of IgG-opsonized particles, is an anti-inflammatory process. The finding that CrkII-DOCK180 is also responsible, at least in part, for the effects of Fcgamma receptors implies that additional, parallel pathways must account for the associated pro-inflammatory effect.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".