Development of a PCR Assay to detect Papillomavirus Infection in the Snow Leopard
Bibliographic record
Abstract
BACKGROUND: Papillomaviruses (PVs) are a group of small, non-encapsulated, species-specific DNA viruses that have been detected in a variety of mammalian and avian species including humans, canines and felines. PVs cause lesions in the skin and mucous membranes of the host and after persistent infection, a subset of PVs can cause tumors such as cervical malignancies and head and neck squamous cell carcinoma in humans. PVs from several species have been isolated and their genomes have been sequenced, thereby increasing our understanding of the mechanism of viral oncogenesis and allowing for the development of molecular assays for the detection of PV infection. In humans, molecular testing for PV DNA is used to identify patients with persistent infections at risk for developing cervical cancer. In felids, PVs have been isolated and sequenced from oral papillomatous lesions of several wild species including bobcats, Asian lions and snow leopards. Since a number of wild felids are endangered, PV associated disease is a concern and there is a need for molecular tools that can be used to further study papillomavirus in these species. RESULTS: We used the sequence of the snow leopard papillomavirus UuPV1 to develop a PCR strategy to amplify viral DNA from samples obtained from captive animals. We designed primer pairs that flank the E6 and E7 viral oncogenes and amplify two DNA fragments encompassing these genes. We detected viral DNA for E6 and E7 in genomic DNA isolated from saliva, but not in paired blood samples from snow leopards. We verified the identity of these PCR products by restriction digest and DNA sequencing. The sequences of the PCR products were 100% identical to the published UuPV1 genome sequence. CONCLUSIONS: We developed a PCR assay to detect papillomavirus in snow leopards and amplified viral DNA encompassing the E6 and E7 oncogenes specifically in the saliva of animals. This assay could be utilized for the molecular investigation of papillomavirus in snow leopards using saliva, thereby allowing the detection of the virus in the anatomical site where oral papillomatous lesions develop during later stages of infection and disease development.
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.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".