Dendritic Cell Adhesion to Cerebral Endothelium: Role of Endothelial Cell Adhesion Molecules and Their Ligands
Bibliographic record
Abstract
Dendritic cells (DCs) have been increasingly implicated in the pathogenesis of neuroinflammation, and there is evidence that they are recruited to the brain across the blood-brain barrier. The molecular mechanisms mediating DC trafficking to the central nervous system are poorly understood. This study used an in vitro model of the human blood-brain barrier and monocyte-derived DCs to investigate the role of endothelial cell (EC) adhesion molecules and their ligands in the adhesion of immature and mature DCs to cerebral microvascular ECs. Adhesion of DCs to resting brain ECs was minimal, but activation of ECs with tumor necrosis factor significantly upregulated adhesion. Immature DCs adhered to activated ECs more avidly than mature DCs; this correlated with differences in the expression of adhesion molecule ligands between the mature and immature DCs. Blocking studies indicated that adhesion to cytokine-activated blood-brain barrier endothelium is mediated by intercellular adhesion molecule (ICAM)-1, ICAM-2, platelet-EC adhesion molecule (PECAM)-1, vascular cell adhesion molecule 1, CD18, and DC-specific ICAM-3-grabbing nonintegrin (DC-SIGN) for immature DCs and ICAM-1, CD18, DC-SIGN, and PECAM-1 for mature DCs. These results suggest that DC adhesion to cerebral ECs depends on the maturation state of DCs and the activation state of the endothelium, and that it is regulated by specific receptor-ligand interactions. This study thus further highlights the active role of human brain microvascular ECs in neuroinflammation.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".