tetano
Editor, Senior Moderator
PLoS One. 2013 Sep 16;8(9):e73497. doi: 10.1371/journal.pone.0073497.
Microdroplet sandwich real-time rt-PCR for detection of pandemic and seasonal influenza subtypes.
Angione SL, Inde Z, Beck CM, Artenstein AW, Opal SM, Tripathi A.
Source
School of Engineering, Center for Biomedical Engineering, Brown University, Providence, Rhode Island, United States of America.
Abstract
As demonstrated by the recent 2012/2013 flu epidemic, the continual emergence of new viral strains highlights the need for accurate medical diagnostics in multiple community settings. If rapid, robust, and sensitive diagnostics for influenza subtyping were available, it would help identify epidemics, facilitate appropriate antiviral usage, decrease inappropriate antibiotic usage, and eliminate the extra cost of unnecessary laboratory testing and treatment. Here, we describe a droplet sandwich platform that can detect influenza subtypes using real-time reverse-transcription polymerase chain reaction (rtRT-PCR). Using clinical samples collected during the 2010/11 season, we effectively differentiate between H1N1p (swine pandemic), H1N1s (seasonal), and H3N2 with an overall assay sensitivity was 96%, with 100% specificity for each subtype. Additionally, we demonstrate the ability to detect viral loads as low as 10(4) copies/mL, which is two orders of magnitude lower than viral loads in typical infected patients. This platform performs diagnostics in a miniaturized format without sacrificing any sensitivity, and can thus be easily developed into devices which are ideal for small clinics and pharmacies.
PMID:
24066051
[PubMed - in process]
PMCID:
PMC3774678
Free full text
http://www.ncbi.nlm.nih.gov/pubmed/24066051
Microdroplet sandwich real-time rt-PCR for detection of pandemic and seasonal influenza subtypes.
Angione SL, Inde Z, Beck CM, Artenstein AW, Opal SM, Tripathi A.
Source
School of Engineering, Center for Biomedical Engineering, Brown University, Providence, Rhode Island, United States of America.
Abstract
As demonstrated by the recent 2012/2013 flu epidemic, the continual emergence of new viral strains highlights the need for accurate medical diagnostics in multiple community settings. If rapid, robust, and sensitive diagnostics for influenza subtyping were available, it would help identify epidemics, facilitate appropriate antiviral usage, decrease inappropriate antibiotic usage, and eliminate the extra cost of unnecessary laboratory testing and treatment. Here, we describe a droplet sandwich platform that can detect influenza subtypes using real-time reverse-transcription polymerase chain reaction (rtRT-PCR). Using clinical samples collected during the 2010/11 season, we effectively differentiate between H1N1p (swine pandemic), H1N1s (seasonal), and H3N2 with an overall assay sensitivity was 96%, with 100% specificity for each subtype. Additionally, we demonstrate the ability to detect viral loads as low as 10(4) copies/mL, which is two orders of magnitude lower than viral loads in typical infected patients. This platform performs diagnostics in a miniaturized format without sacrificing any sensitivity, and can thus be easily developed into devices which are ideal for small clinics and pharmacies.
PMID:
24066051
[PubMed - in process]
PMCID:
PMC3774678
Free full text
http://www.ncbi.nlm.nih.gov/pubmed/24066051