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High-throughput Detection of Respiratory Pathogens in Animal Specimens by Nanoscale PCR
Published on: November 28, 2016
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Challenges in navigating molecular diagnostics for common equine respiratory viruses
Nicola Pusterla1, Christian M Leutenegger2, Samantha Barnum1
1Department of Medicine and Epidemiology, School of Veterinary Medicine, University of California, Davis, CA 95616, USA.
Veterinary Journal (London, England : 1997)
|September 6, 2021
Summary
Molecular diagnostics, like PCR, are crucial for equine respiratory virus detection. Accurate interpretation of results is vital for managing outbreaks and ensuring horse health.
Area of Science:
- Veterinary Virology
- Equine Infectious Diseases
- Molecular Diagnostics
Background:
- Equine respiratory viruses cause significant morbidity and mortality.
- Increased international trade and susceptible horse populations exacerbate outbreaks.
- Molecular techniques like PCR are replacing traditional methods for rapid diagnosis.
Purpose of the Study:
- To guide equine practitioners in interpreting molecular diagnostic results for respiratory viruses.
- To address challenges in diagnosing less-characterized equine viruses.
- To enhance understanding of viral state and virulence through advanced molecular techniques.
Main Methods:
- Review of current molecular diagnostic techniques, focusing on Polymerase Chain Reaction (PCR).
- Analysis of interpretation strategies for common and less-characterized equine respiratory viruses.
- Discussion of advanced molecular applications like viral quantitation and genotyping.
Main Results:
- PCR offers faster, more sensitive detection compared to traditional methods.
- Interpretation requires consideration of clinical status, sample type, and assay.
- Quantitation and genotyping provide valuable insights into viral virulence and state.
Conclusions:
- Molecular diagnostics are essential for equine respiratory virus management.
- Careful interpretation of PCR results is critical for accurate diagnosis and treatment.
- Advanced molecular data aids in outbreak management and biosecurity.

