Vav1 Is Essential for Mechanotactic Crawling and Migration of Neutrophils out of the Inflamed Microvasculature
Bibliographic record
Abstract
Mac-1-dependent crawling is a new step in the leukocyte recruitment cascade that follows LFA-1-dependent adhesion and precedes emigration. Neutrophil adhesion via LFA-1 has been shown to induce cytoskeletal reorganization through Vav1-dependent signaling, and the current study investigates the role of Vav1 in the leukocyte recruitment process in vivo with particular attention to the events immediately downstream of LFA-1-dependent adhesion. Intravital and spinning-disk-confocal microscopy was used to investigate intravascular crawling in relation to endothelial junctions in vivo in wild-type and Vav1(-/-) mice. Adherent wild-type neutrophils almost immediately began crawling perpendicular to blood flow via Mac-1 until they reached an endothelial junction where they often changed direction. This pattern of perpendicular, mechanotactic crawling was recapitulated in vitro when shear was applied. In sharp contrast, the movement of Vav1(-/-) neutrophils was always in the direction of flow and appeared more passive as if the cells were dragged in the direction of flow in vivo and in vitro. More than 80% of Vav1(-/-) neutrophils moved independent of Mac-1 and could be detached with LFA-1 Abs. An inability to release the uropod was frequently noted for Vav1(-/-) neutrophils, leading to greatly elongated tails. The Vav1(-/-) neutrophils failed to stop or follow junctions and ultimately detached, leading to fewer emigrated neutrophils. The Vav1(-/-) phenotype resulted in fewer neutrophils recruited in a relevant model of infectious peritonitis. Clearly, Vav1 is critical for the complex interplay between LFA-1 and Mac-1 that underlies the programmed intravascular crawling of neutrophils.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".