Development and use of a triplex real-time PCR assay for detection of three DNA viruses in psittacine birds
Bibliographic record
Abstract
Aves polyomavirus 1, psittacine beak and feather disease virus, and psittacid herpesvirus 1 are important pathogens of psittacine birds with the potential to cause substantial morbidity and mortality. Using publically available nucleotide sequences, we developed and validated a triplex real-time PCR (rtPCR) assay to rapidly detect these 3 viruses. The assay had high analytical sensitivity, detecting <6 copies of viral DNA per reaction, and 100% analytical specificity, showing no cross-reactivity with 59 other animal pathogens. Archived formalin-fixed, paraffin-embedded tissues from psittacine birds diagnosed at postmortem as infected with each of the viruses as well as virus-negative birds were used to validate the utility of the assay. Birds were selected for the positive cohort if they showed histologic evidence of infection (i.e., characteristic inclusion bodies in tissues); birds in the negative cohort had final diagnoses unrelated to the pathogens of interest. The triplex rtPCR assay confirmed 98% of histopathology-positive cases, and also identified subclinical infections that were not observed by histologic examination, including coinfections. Birds that tested positive only by rtPCR had significantly higher cycle threshold values compared to those with histologic evidence of infection. Positive, negative, and overall percentage agreements as well as the kappa statistic between the results of the assay and histopathology were high, demonstrating the usefulness of the assay as a tool to confirm disease diagnoses, and to improve detection of subclinical infections.
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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 | 0.002 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".