Development of an ante-mortem diagnostic test for enzootic nasal tumor virus and detection of neutralizing antibodies in host serum
Why this work is in the frame
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Bibliographic record
Abstract
Enzootic nasal adenocarcinoma (ENA) is a contagious neoplasm of the nasal mucosa of sheep and goats and is associated with enzootic nasal tumour virus (ENTV). As ENA is a common disease in North America and there are no vaccines against ENTV-1, diagnostic tests that can identify infected animals and assist with eradication and disease surveillance efforts are greatly needed. In this study, we endeavoured to develop a novel, non-invasive diagnostic tool that could be used not only to validate clinical signs of ENA but also to detect ENTV-1 infection prior to the onset of disease signs (i.e. pre-clinical diagnosis). Cytology, serology and reverse transcription (RT)-PCR-based diagnostic methods were investigated. Although the cytology-based assay was able to detect ENTV-1 infection in some animals, it had poor sensitivity and specificity and thus was not developed further as an ante-mortem diagnostic method. Three different assays, including ELISA, Western blotting and virus neutralization, were developed to detect the presence of ENTV-1-specific antibodies in sheep serum. Whilst a surprisingly large number of sheep mounted an antibody-mediated immune response against ENTV-1, and in some cases neutralizing, correlation with disease status was poor. In contrast, RT-PCR on RNA extracted from nasal swabs reliably detected exogenous ENTV-1 sequences, did not amplify endogenous ovine betaretroviral sequences, demonstrated high concordance with immunohistochemical staining for ENTV-1 envelope protein, and had perfect sensitivity and specificity. This report describes a practical and highly specific RT-PCR technique for the detection of clinical and pre-clinical ENA that may prove beneficial in future control or eradication programmes.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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