Suppressive Role of Bam32/DAPP1 in Chemokine-Induced Neutrophil Recruitment
Bibliographic record
Abstract
Bam32 (B cell adaptor molecule of 32 kDa) functions in the immune responses of various leukocytes. However, the role of neutrophil Bam32 in inflammation is entirely unknown. Here, we determined the role of Bam32 in chemokine CXCL2-induced neutrophil chemotaxis in three mouse models of neutrophil recruitment. By using intravital microscopy in the mouse cremaster muscle, we found that transmigrated neutrophil number, neutrophil chemotaxis velocity, and total neutrophil chemotaxis distance were increased in Bam32−/− mice when compared with wild-type (WT) mice. In CXCL2-induced mouse peritonitis, the total emigrated neutrophils were increased in Bam32−/− mice at 2 but not 4 h. The CXCL2-induced chemotaxis distance and migration velocity of isolated Bam32−/− neutrophils in vitro were increased. We examined the activation of small GTPases Rac1, Rac2, and Rap1; the levels of phospho-Akt2 and total Akt2; and their crosstalk with Bam32 in neutrophils. The deficiency of Bam32 suppressed Rap1 activation without changing the activation of Rac1 and Rac2. The pharmacological inhibition of Rap1 by geranylgeranyltransferase I inhibitor (GGTI298) increased WT neutrophil chemotaxis. In addition, the deficiency of Bam32, as well as the inhibition of Rap1 activation, increased the levels of CXCL2-induced Akt1/2 phosphorylation at Thr308/309 in neutrophils. The inhibition of Akt by SH-5 attenuated CXCL2-induced adhesion and emigration in Bam32−/− mice. Together, our results reveal that Bam32 has a suppressive role in chemokine-induced neutrophil chemotaxis by regulating Rap1 activation and that this role of Bam32 in chemokine-induced neutrophil recruitment relies on the activation of PI3K effector Akt.
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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 | 0.001 |
| 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".