The human papillomavirus replication cycle, and its links to cancer progression: a comprehensive review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
HPVs (human papillomaviruses) infect epithelial cells and their replication cycle is intimately linked to epithelial differentiation. There are over 200 different HPV genotypes identified to date and each displays a strict tissue specificity for infection. HPV infection can result in a range of benign lesions, for example verrucas on the feet, common warts on the hands, or genital warts. HPV infects dividing basal epithelial cells where its dsDNA episomal genome enters the nuclei. Upon basal cell division, an infected daughter cell begins the process of keratinocyte differentiation that triggers a tightly orchestrated pattern of viral gene expression to accomplish a productive infection. A subset of mucosal-infective HPVs, the so-called 'high risk' (HR) HPVs, cause cervical disease, categorized as low or high grade. Most individuals will experience transient HR-HPV infection during their lifetime but these infections will not progress to clinically significant cervical disease or cancer because the immune system eventually recognizes and clears the virus. Cancer progression is due to persistent infection with an HR-HPV. HR-HPV infection is the cause of >99.7% cervical cancers in women, and a subset of oropharyngeal cancers, predominantly in men. HPV16 (HR-HPV genotype 16) is the most prevalent worldwide and the major cause of HPV-associated cancers. At the molecular level, cancer progression is due to increased expression of the viral oncoproteins E6 and E7, which activate the cell cycle, inhibit apoptosis, and allow accumulation of DNA damage. This review aims to describe the productive life cycle of HPV and discuss the roles of the viral proteins in HPV replication. Routes to viral persistence and cancer progression are also discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it