In Vivo Inhibition of Type I Interferon Transcription in Genital HSV-2 Lesions (134.72)
Bibliographic record
Abstract
Abstract We performed transcriptional analysis and immunocytochemistry (ICC) of sequential biopsies of lesional tissue of immunocompetent persons with recurrent HSV-2 infection. Histologic analysis of these biopsies indicated a massive infiltration of monocytes/macrophages along with a large amount of myeloid and a small number of plasmacytoid dendritic cells in the dermis of these lesional biopsies. IFNB1 and IFN-α were weakly expressed and IFNG potently induced during time periods in which there was abundant detection of HSV-2 antigens and gene expression. Transcriptional arrays of the same anatomic area over time (newly healed, 2 and 4 weeks post healing) in which no HSV DNA/RNA or antigen was detected continued to show that IFNB1 and IFN-α were barely detectable. IFNG persisted in lesional tissue, albeit at lower levels as compared with active lesions. Interferon-stimulated genes (ISGs) were also markedly up-regulated with expression patterns more clearly resembling those in primary human fibroblasts treated by IFNG than by IFNB1. The presence of a very large number of innate cells capable of sensing HSV-2 infection and synthesizing type I IFN by both histologic and transcriptional analyses associated with extremely low levels of IFN-α and IFNB1 even in the earliest lesional biopsies suggests a potent alteration in host defense during HSV-2 infection in vivo. This block of type I IFN by HSV-2 may be a major factor in allowing the virus to breakthrough host mucosal defenses.
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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) | 0.002 | 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".