Field-Deployable Reverse Transcription-Insulated Isothermal PCR (RT-iiPCR) Assay for Rapid and Sensitive Detection of Foot-and-Mouth Disease Virus
Bibliographic record
Abstract
Foot-and-mouth disease (FMD) is a highly contagious viral disease of cloven-hoofed animals, which can decimate the livestock industry and economy of countries previously free of this disease. Rapid detection of foot-and-mouth disease virus (FMDV) is critical to containing an FMD outbreak. Availability of a rapid, highly sensitive and specific, yet simple and field-deployable assay would support local decision-making during an FMDV outbreak. Here we report validation of a novel reverse transcription-insulated isothermal PCR (RT-iiPCR) assay that can be performed on a commercially available, compact and portable POCKIT™ analyser that automatically analyses data and displays ‘+’ or ‘−’ results. The FMDV RT-iiPCR assay targets the 3D region of the FMDV genome and was capable of detecting 9 copies of in vitro-transcribed RNA standard with 95% confidence. It accurately identified 63 FMDV strains belonging to all seven serotypes and showed no cross-reactivity with viruses causing similar clinical diseases in cloven-hoofed animals. The assay was able to identify FMDV RNA in multiple sample types including oral, nasal and lesion swabs, epithelial tissue suspensions, vesicular and oral fluid samples, even before the appearance of clinical signs. Clinical sensitivity of the assay was comparable or slightly higher than the laboratory-based real-time RT-PCR assay in use. The assay was able to detect FMDV RNA in vesicular fluid samples without nucleic acid extraction. For RNA extraction from more complex sample types, a commercially available taco™ mini transportable magnetic bead-based, automated extraction system was used. This assay provides a potentially useful field-deployable diagnostic tool for rapid detection of FMDV in an outbreak in FMD-free countries or for routine diagnostics in endemic countries with less structured laboratory systems.
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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) | 0.001 | 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".