Temporal and Geographic Clustering of Polyomavirus-Associated Olfactory Tumors in 10 Free-Ranging Raccoons ( <i>Procyon lotor</i> )
Bibliographic record
Abstract
Reports of primary nervous system tumors in wild raccoons are extremely rare. Olfactory tumors were diagnosed postmortem in 9 free-ranging raccoons from 4 contiguous counties in California and 1 raccoon from Oregon within a 26-month period between 2010 and 2012. We describe the geographic and temporal features of these 10 cases, including the laboratory diagnostic investigations and the neuropathologic, immunohistochemical, and ultrastructural characteristics of these tumors in the affected animals. All 9 raccoons from California were found within a localized geographic region of the San Francisco Bay Area (within a 44.13-km radius). The tight temporal and geographic clustering and consistent anatomic location in the olfactory system of tumor types not previously described in raccoons (malignant peripheral nerve sheath tumors and undifferentiated sarcomas) strongly suggest either a common cause or a precipitating factor leading to induction or potentiation of neuro-oncogenesis and so prompted an extensive diagnostic investigation to explore possible oncogenic infectious and/or toxic causes. By a consensus polymerase chain reaction strategy, a novel, recently reported polyomavirus called raccoon polyomavirus was identified in all 10 tumors but not in the normal brain tissue from the affected animals, suggesting that the virus might play a role in neuro-oncogenesis. In addition, expression of the viral protein T antigen was detected in all tumors containing the viral sequences. We discuss the potential role of raccoon polyomavirus as an oncogenic virus.
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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 | 0.000 |
| 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 | 0.001 |
| 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".