Development of real-time PCR assay for detection of porcine circovirus-like virus P1 in domestic pigs in China
Bibliographic record
Abstract
BACKGROUND: The porcine circovirus-like agent P1 is a newly discovered DNA virus with a single-stranded circular genome that is highly homologous to that of porcine circovirus type 2. P1 infection can cause symptoms resembling postweaning multisystemic wasting syndrome. This study aims to develop a rapid, sensitive and specific method to detect P1. RESULTS: A pair of primers was designed and used to amplify a 119 bp DNA fragment to generate a recombinant plasmid which was served as the standard. A SYBR I qPCR protocol was established using the P1 recombinant plasmid standard and the sensitivity, specificity and stability of this method was analyzed. The results demonstrate a strong correlation with P1 recombinant plasmid titers when virus DNA copy numbers fall in between 10(0) ~ 10(9) copies/μL. This method doesn't detect pseudo rabies, porcine parvovirus or porcine reproductive and respiratory syndrome virus; moreover it can distinguish porcine circovirus type 2 from P1 by melting temperature analysis. Coefficient of variation for each batch of reaction is less than 5%. The serum virus titers of P1 positive in this study were measured by this protocol to be 10(3) to 10(7) copies/mL. CONCLUSIONS: The established qPCR is sensitive, specific, and reliable, which could be a useful tool when applied to quantification of P1 in a variety of samples from infected pigs.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".