The axonal repellent, Slit2, inhibits directional migration of circulating neutrophils
Bibliographic record
Abstract
In inflammatory diseases, circulating neutrophils are recruited to sites of injury. Attractant signals are provided by many different chemotactic molecules, such that blockade of one may not prevent neutrophil recruitment effectively. The Slit family of secreted proteins and their transmembrane receptor, Robo, repel axonal migration during CNS development. Emerging evidence shows that by inhibiting the activation of Rho-family GTPases, Slit2/Robo also inhibit migration of other cell types toward a variety of chemotactic factors in vitro and in vivo. The role of Slit2 in inflammation, however, has been largely unexplored. We isolated primary neutrophils from human peripheral blood and mouse bone marrow and detected Robo-1 expression. Using video-microscopic live cell tracking, we found that Slit2 selectively impaired directional migration but not random movement of neutrophils toward fMLP. Slit2 also inhibited neutrophil migration toward other chemoattractants, namely C5a and IL-8. Slit2 inhibited neutrophil chemotaxis by preventing chemoattractant-induced actin barbed end formation and cell polarization. Slit2 mediated these effects by suppressing inducible activation of Cdc42 and Rac2 but did not impair activation of other major kinase pathways involved in neutrophil migration. We further tested the effects of Slit2 in vivo using mouse models of peritoneal inflammation induced by sodium periodate, C5a, and MIP-2. In all instances, Slit2 reduced neutrophil recruitment effectively (P<0.01). Collectively, these data demonstrate that Slit2 potently inhibits chemotaxis but not random motion of circulating neutrophils and point to Slit2 as a potential new therapeutic for preventing localized inflammation.
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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 | 0.001 |
| 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".