A Highly Selective CCR2 Chemokine Agonist Encoded by Human Herpesvirus 6
Bibliographic record
Abstract
The chemokine-like, secreted protein product of the U83 gene from human herpesvirus 6, here named vCCL4, was chemically synthesized to be characterized in a complete library of the 18 known human chemokine receptors expressed individually in stably transfected cell lines. vCCL4 was found to cause calcium mobilization as efficiently as the endogenous chemokine ligand CCL2 through the CCR2 receptor, whereas the virally encoded chemokine did not affect any of the other 17 human chemokine receptors tested. Mutual cross-desensitization between CCL2 and vCCL4 was demonstrated in the CCR2-transfected cells. The affinity of vCCL4 for the CCR2 receptor was 79 nm as determined in competition binding against radioactively labeled CCL2. In the murine pre-B lymphocyte cell line L1.2 stably transfected with the CCR2 receptor, vCCL4 acted as a relatively low potency but highly efficacious chemoattractant being equally or more efficacious in causing cell migration than CCL2 and CCL7 and considerably more efficacious than CCL8 and CCL13. It is concluded that human herpesvirus 6 encodes a highly selective and efficacious CCR2 agonist, which will attract CCR2 expressing cells, for example macrophages and monocytes, conceivably for the virus to infect and to establish latency in. It is suggested that vCCL4 during reactivation of the virus in for example monocyte-derived microglia could perhaps be involved in the pathogenesis of the CCR2-dependent disease, multiple sclerosis.
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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".