In vitro and in vivo induction of B7-H1 and B7-DC expression by human rhinovirus infection of airway epithelial cells (46.5)
Bibliographic record
Abstract
Abstract We have found that human airway epithelial cells express costimulatory molecules B7-H1, B7-H2, B7-H3 and B7-DC mRNA and cell-surface protein. IFN? and TNF? selectively induce B7-H1 and B7-DC and glucocorticoid fluticasone (FP) inhibits this induction. We now report that human rhinovirus infection (HRV-16), a key trigger of exacerbations of chronic rhinosinusitis and asthma, results in selective induction of B7-H1 and B7-DC expression in airway epithelial cells both in vitro and in vivo. In vitro exposure of human primary bronchial epithelial cells (PBEC) to HRV-16 (TCID50 5 X 103.1) resulted in induction of cell surface expression of B7-H1 as measured by flow cytometry (from 42±9 to 56±8 MFI, p<0.05) and B7-DC (from 5±1 to 9±2 MFI, p<0.01) (n=6). Pretreatment with FP (10-7 M) inhibited the induction of B7-H1 by 64% (p<0.05) and B7-DC by 95% (p<0.01). Additionally, in vitro exposure of PBEC to TLR3 agonist dsRNA (25 ug/ml), a surrogate for HRV16 infection, mirrored the effect of HRV-16 infection. Nasal scrapings taken at the time of peak symptom scores 4 days after infection of 6 human subjects with HRV-16 showed selective increases in levels of mRNA for B7-H1 (8.5±2.5 fold, p<0.03) and B7-DC (3.2±1.1 fold, p<0.07). These data show that exposure to TLR3 agonist dsRNA or HRV-16 infection induces B7-H1 and B7-DC on epithelial cells and this may influence the development of adaptive immune responses in the airways.
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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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".