Epstein-Barr Virus Induces MCP-1 Secretion by Human Monocytes via TLR2
Bibliographic record
Abstract
Epstein-Barr virus (EBV) is a gammaherpesvirus infecting the majority of the human adult population in the world. TLR2, a member of the Toll-like receptor (TLR) family, has been implicated in the immune responses to different viruses including members of the herpesvirus family, such as human cytomegalovirus, herpes simplex virus type 1, and varicella-zoster virus. In this report, we demonstrate that infectious and UV-inactivated EBV virions lead to the activation of NF-kappaB through TLR2 using HEK293 cells cotransfected with TLR2-expressing vector along with NF-kappaB-Luc reporter plasmid. NF-kappaB activation in HEK293-TLR2 cells (HEK293 cells transfected with TLR2) by EBV was not enhanced by the presence of CD14. The effect of EBV was abrogated by pretreating HEK293-TLR2 cells with blocking anti-TLR2 antibodies or by preincubating viral particles with neutralizing anti-EBV antibodies 72A1. In addition, EBV infection of primary human monocytes induced the release of MCP-1 (monocyte chemotactic protein 1), and the use of small interfering RNA targeting TLR2 significantly reduced such a chemokine response to EBV. Taken together, these results indicate that TLR2 may be an important pattern recognition receptor in the immune response directed against EBV infection.
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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) | 0.003 | 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".