Recruitment of Neutrophils across the Blood–Brain Barrier: The Role of E- and P-selectins
Why this work is in the frame
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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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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it