Recruitment of Neutrophils across the Blood–Brain Barrier: The Role of E- and P-selectins
Bibliographic record
Abstract
The adult central nervous system parenchyma is resistant to inflammation, but in juvenile rats the injection of inflammatory mediators, interleukin-1 beta for example, gives rise to extensive neutrophil recruitment and neutrophil-dependent blood-brain barrier breakdown. The factors that confer this resistant phenotype are unknown. In this study, the authors demonstrate that E- and P-selectin expression is increased to a similar extent in adult and juvenile brain after the intracerebral injection of IL-1 beta. Thus, the refractory nature of the brain parenchyma cannot be attributed to an absence of selectin expression. However, in injuries where the resistant characteristic of the brain parenchyma is compromised, and neutrophil recruitment occurs, selectin blockade may be an advantage. The authors investigated the contribution that selectins make to neutrophil recruitment during acute inflammation in the brain. The authors examined neutrophil recruitment by immunohistochemistry on brain sections of juvenile rats killed four hours after the intracerebral injection of IL-1 beta and the intravenous injection of neutralizing anti-selectin monoclonal antibodies (mAb). The administration of the P-selectin blocking mAb inhibited neutrophil recruitment by 85% compared with controls. Surprisingly, E-selectin blockade had no effect on neutrophil recruitment to the brain parenchyma. Thus, P-selectin appears to play a pivotal role in mediating neutrophil recruitment to the brain parenchyma during acute inflammation.
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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 | 0.000 |
| 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 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".