B7 Expression and Antigen Presentation by Human Brain Endothelial Cells: Requirement for Proinflammatory Cytokines
Bibliographic record
Abstract
Interaction between systemic immune cells with cells of the blood-brain barrier is a central step in development of CNS-directed immune responses. Endothelial cells are the first cells of the blood-brain barrier encountered by migrating lymphocytes. To investigate the antigen-presenting capacity of human adult brain endothelial cells (HBECs), we used HBECs derived from surgically resected temporal lobe tissue, cocultured with allogeneic peripheral blood derived CD4+ T lymphocytes. HBECs in response to IFN-gamma, but not under basal culture conditions, expressed HLA-DR, B7.1 and B7.2 antigens. Despite such up-regulation, these IFN-gamma-treated HBECs, in contrast to human microglia and PB monocytes, did not sustain allogeneic CD4+ cell proliferation, supported only low levels of IL-2 and IFN-gamma production, and did not stimulate IL-2 receptor expression. CD4+ T cell proliferation and increased IL-2 receptor expression could be obtained by addition of IL-2. Our data suggests that, although HBECs cannot alone support T cell proliferation and cytokine production, HBECs acting in concert with cytokines derived from a proinflammatory environment could support such a response.
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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".