Recent Advances in the Search for Antiviral Agents against Human Papillomaviruses
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
Infection by human papillomavirus (HPV) is extremely common and associated with the development of benign warts or malignant lesions of the skin and mucosa. Infection by a high-risk (oncogenic) anogenital HPV type, most often through sexual contacts, is the starting point of virtually all cases of cervical cancers and the majority of anal cancers. The same viral types are also increasingly being linked with a subset of head-and-neck and non-melanoma skin cancers. Although prophylactic vaccines are now available to protect against the four types most commonly found in cervical and anal cancers (HPV16 and HPV18) and anogenital warts (HPV6 and HPV11), these neither protect against all genital HPVs nor are of therapeutic utility for already infected patients. Thus, the need for antiviral agents to treat HPV-associated diseases remains great, but none currently exist. This article reviews the recent progress made towards the development of antiviral agents to treat HPV infections, from target identification and validation to the discovery of lead compounds with therapeutic potential. Emphasis has been placed on novel low-molecular-weight compounds that antagonize HPV proteins or, alternatively, inhibit cellular proteins which have been usurped by papillomaviruses and are mediating their pathogenic effects.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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