Overlapping Roles of P-Selectin and α4 Integrin to Recruit Leukocytes to the Central Nervous System in Experimental Autoimmune Encephalomyelitis
Bibliographic record
Abstract
Experimental autoimmune encephalomyelitis (EAE) is mediated by inflammatory cells recruited from the circulation to the CNS. We used intravital microscopy to investigate the mechanisms of this recruitment. No leukocyte rolling and very little adhesion was observed in healthy control mice. In contrast, both rolling and adhesion was observed in brain postcapillary venules before onset of physical symptoms of EAE. Rolling and adhesion remained elevated for 2 wk and returned to near normal levels by 5 wk postsymptom onset. Consistent with a role for P-selectin in recruitment to the CNS, P-selectin protein was detected in the brains and spinal cords of EAE mice. Expression was highest before symptom onset and decreased over the next 2 wk. The importance of alpha(4) integrin increased with time as anti-alpha(4) integrin blocked approximately 20, 50, and 60% of leukocyte rolling 2 days before disease onset, 5 days and 2 wk postonset of symptoms, respectively, and 85% of rolling 5 wk postsymptoms. Addition of anti-P-selectin to alpha(4) integrin Ab-treated mice blocked all remaining rolling at each time point. Interestingly, however, alpha(4) integrin-mediated rolling appeared to be entirely dependent on P-selectin as anti-P-selectin alone was able to completely block all leukocyte rolling. In the absence of rolling (with P-selectin Ab), a 70% reduction in adhesion was noted. A very similar reduction was seen when mice were treated with alpha(4) integrin-blocking Ab. In conclusion, we describe increased leukocyte trafficking in the brains of EAE mice with important overlapping roles for both P-selectin and alpha(4) integrin in mediating leukocyte-endothelial cell interactions.
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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) | 0.001 | 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".