Human dendritic cells promote an antiviral immune response when stimulated by CVT-E002
Bibliographic record
Abstract
OBJECTIVES: There is interest in developing new compounds to enhance the immune response to airway virus infections. CVT-E002 is a patented ginseng extract shown to decrease symptoms of virus infection in clinical trials. We hypothesized that the mechanism for this antiviral effect could be through modulation of dendritic cells leading to enhanced T-cell activation. METHODS: Human monocyte-derived dendritic cells (moDC) exposed to CVT-E002 (or not) were co-cultured with autologous T cells, with or without virus (respiratory syncytial virus or parainfluenza virus). Effects of CVT-E002 on cell function were determined through flow cytometry, 5-bromo-2'-deoxyuridine (BrdU) incorporation and ELISA. KEY FINDINGS: moDC cultured with CVT-E002 or virus induced greater activation of T cells, as measured by CD25 expression and BrdU incorporation, compared with untreated moDC. Responding T cells were CD4+CD45RO+. Co-cultures of CVT-E002 treated moDC with T cells responded with increased release of Th1-type cytokines (interferon-gamma, tumour necrosis factor and interleukin-12). CVT-E002-treated moDC showed increased expression of CD83, CD80 and CD86. Lipopolysaccharide levels were not detected in CVT-E002 and antagonists for Toll-like receptor-4 did not inhibit CVT-E002-induced moDC maturation. CONCLUSIONS: CVT-E002 induced moDC maturation, which caused increased memory T-cell activation and Th1-type cytokine 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".