Migration of Multiple Sclerosis Lymphocytes Through Brain Endothelium
Bibliographic record
Abstract
CONTEXT: T-lymphocyte migration through the blood-brain barrier is a central event in the process of lesion formation in multiple sclerosis (MS). OBJECTIVES: To assess the ability of lymphocytes derived from the peripheral blood of patients with clinically active and inactive MS to migrate across an artificial model of the blood-brain barrier and to elucidate the molecular mechanisms involved in such a process. DESIGN: We developed an in vitro model of lymphocyte migration using a Boyden chamber coated with a monolayer of human brain microvascular endothelial cells. RESULTS: The rates of migration of lymphocytes obtained from patients with acutely relapsing and active secondary progressive MS was significantly increased compared with those obtained from healthy controls and patients with inactive secondary progressive disease. Ribonuclease protection assays and enzyme-linked immunosorbent assays indicated that monocyte chemoattractant protein 1 and interleukin 8 were the major chemokines produced by brain endothelial cells grown under the culture conditions used for the migration assays. The rate of migration of the MS lymphocytes could be inhibited by 60% with an antimonocyte chemoattractant protein 1 monoclonal antibody, indicating a functional role for this chemokine in the migration process. In agreement with previous reports, we found that the tissue inhibitor of metalloproteinase 1, a matrix metalloproteinase inhibitor, also reduced migration of MS lymphocytes by 50%. CONCLUSIONS: The results demonstrate an increased migration rate of MS T lymphocytes across the brain endothelium barrier and that such migration is dependent on chemokine monocyte chemoattractant protein 1 and on matrix metalloproteinases.
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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) | 0.001 | 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".