Gene Expression Profile of Herpesvirus-Infected T Cells Obtained Using Immunomicroarrays: Induction of Proinflammatory Mechanisms
Bibliographic record
Abstract
Herpesvirus infections can frequently lead to acute inflammation, yet the mechanisms regulating this event remain poorly understood. In order to determine some of the immunological mechanisms regulated by human herpesvirus infections, we studied the gene expression profile of lymphocytes infected with human herpesvirus 6 (HHV-6) by using a novel immunomicroarray. Our nylon-based immunomicroarray contained more than 1,150 immune response-related genes and was highly consistent between experiments. Experimentally, we found that independently of the HHV-6 strain used to infect T cells, multiple proinflammatory genes were increased and anti-inflammatory genes were decreased at the mRNA and protein levels. HHV-6 strains A and B increased expression of the genes for interleukin-18 (IL-18), the IL-2 receptor, members of the tumor necrosis factor alpha superfamily receptors, mitogen-activated protein kinase, and Janus kinase signaling proteins. As reported previously, CD4 protein levels were also increased significantly. Specific type 2 cytokines, including IL-10, its receptor, and IL-14, were downregulated by HHV-6 infection and, interestingly, amyloid precursor proteins and type 1 and 2 presenilins. Thus, T cells respond to HHV-6 infection by inducing a type 1 immune response that may play a significant role in the development and progression of diseases associated with HHV-6, including pediatric, hematologic, transplant, and neurologic disorders.
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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 | 0.001 | 0.001 |
| 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".