Differences in Transcriptional Activity of Human Papillomavirus Type 6 Molecular Variants in Recurrent Respiratory Papillomatosis
Bibliographic record
Abstract
A significant proportion of recurrent respiratory papillomatosis (RRP) is caused by human papillomavirus type 6 (HPV-6). The long control region (LCR) contains cis-elements for regulation of transcription. Our aim was to characterize LCR HPV-6 variants in RRP cases, compare promoter activity of these isolates and search for cellular transcription factors (TFs) that could explain the differences observed. The complete LCR from 13 RRP was analyzed. Transcriptional activity of 5 variants was compared using luciferase assays. Differences in putative TFs binding sites among variants were revealed using the TRANSFAC database. Chromatin immunoprecipation (CHIP) and luciferase assays were used to evaluate TF binding and impact upon transcription, respectively. Juvenile-onset RRP cases harbored exclusively HPV-6vc related variants, whereas among adult-onset cases HPV-6a variants were more prevalent. The HPV-6vc reference was more transcriptionally active than the HPV-6a reference. Active FOXA1, ELF1 and GATA1 binding sites overlap variable nucleotide positions among isolates and influenced LCR activity. Furthermore, our results support a crucial role for ELF1 on transcriptional downregulation. We identified TFs implicated in the regulation of HPV-6 early gene expression. Many of these factors are mutated in cancer or are putative cancer biomarkers, and must be further studied.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".