Development of a real-time TaqMan PCR assay for the detection of porcine and bovine Torque teno virus
Bibliographic record
Abstract
AIMS: The goal of this study was to develop and to optimize molecular tools to detect the presence of Torque teno virus (TTV) in swine and cattle. A novel real-time polymerase chain reaction (PCR) using a TaqMan probe was developed to detect both genogroups of TTV strains. METHODS AND RESULTS: Oligonucleotide primers and hybridization probes were designed based on sequence analysis of the noncoding region, a highly conserved part of the genome. The real-time PCR assay specifically detected bovine and porcine TTV DNA without cross-amplification of other common pathogens. The assay was compared with conventional PCR and nested-PCR assays for the detection of porcine genogroups 1 and 2 and bovine TTV on plasma and faecal samples, and the assay was found faster, more reliable and reduced the risk of false positive results. CONCLUSIONS: The real-time PCR assay provided better detection results for the two TTV genogroups in both swine and cattle compared to the conventional PCR assays. SIGNIFICANCE AND IMPACT OF THE STUDY: This new TaqMan PCR assay will be a useful tool for the detection of animal TTV strains, to evaluate the viral load from animal host and finally to identify the presence of these viruses in the agri-food continuum.
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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 | 0.003 |
| 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 | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".