Survey of veterinary conference attendees for evidence of zoonotic infection by feline retroviruses
Bibliographic record
Abstract
OBJECTIVE: To examine exposure risks, possibility of zoonosis, and potential disease associations for feline retroviruses among a group of occupationally exposed individuals. DESIGN: Unlinked voluntary cross-sectional epidemiologic survey. SAMPLE POPULATION: 204 veterinarians, laboratory scientists, and other occupationally exposed individuals who attended a veterinary conference on feline geriatric medicine. PROCEDURE: Blood was collected from participants who also completed a 13-question survey requesting demographic, occupational, exposure, and health information. Blood specimens were fractionated into plasma and mononuclear cell components. Plasma was tested for antibodies against feline immunodeficiency virus (FIV) and feline foamy virus (FeFV), as well as p27 antigen of FeLV. Mononuclear cell lysates were tested for FeLV provirus. RESULTS: Subjects reported extensive duration of work with cats (mean, 17.3 years) and multiple high-risk exposures (eg, cat bites, scratches, and injuries with sharp instruments) per year. However, neither serologic nor molecular evidence of zoonosis with any of the 3 feline retroviruses was detected. CONCLUSIONS AND CLINICAL RELEVANCE: Veterinarians encounter occupational exposures to animal material that place them at high risk for zoonoses. For feline retroviruses, the risk of zoonosis among healthy adult humans appears to be extremely small. However, potential for retroviral zoonosis, especially for viruses such as FeLV and FeFV that can replicate in human cells, cannot be eliminated, and universal precautions to reduce potential exposures should be used when handling sick cats.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".