| Title: | Digital PCR method for detection and quantification of specific antimicrobial drug-resistance mutations in human cytomegalovirus |
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| Authors: | ID Bogožalec Košir, Alexandra (Author)
ID Cvelbar, Tašja (Author)
ID Kammel, Martin (Author)
ID Grunert, Hans-Peter (Author)
ID Zeichhardt, Heinz (Author)
ID Milavec, Mojca (Author) |
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| Files: |  PDF - Presentation file, download (5,71 MB)
MD5: 54FD3DB85846B646F8A56CCC86F678DC
 URL - Source URL, visit https://doi.org/10.1016/j.jviromet.2020.113864
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| Language: | English |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: |  NIB - National Institute of Biology
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| Abstract: | Antimicrobial drug resistance is one of the biggest threats to human health worldwide. Timely detection and quantification of infectious agents and their susceptibility to antimicrobial drugs are crucial for efficient management of resistance to antiviral drugs. In clinical settings, viral drug resistance is most often associated with prolonged treatment of chronic infections, and assessed by genotyping methods; e.g., sequencing and PCR. These approaches have limitations: sequencing can be expensive and does not provide quantification; and qPCR quantification is hampered by a lack of reference materials for standard curves. In recent years, digital PCR has been introduced, which provides absolute quantification without the need for reference materials for standard curves. Using digital PCR, we have developed a rapid, sensitive and accurate method for genotyping and quantification of the most prevalent mutations that cause human cytomegalovirus resistance to ganciclovir. |
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| Keywords: | digital PCR, antimicrobial-drug resistance, HCMV, polymerase chain reaction, viruses |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Publication date: | 01.07.2020 |
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| Year of publishing: | 2020 |
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| Number of pages: | str. 1-16 |
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| Numbering: | Vol. 281, [article] 113864 |
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| PID: | 20.500.12556/DiRROS-19515  |
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| UDC: | 577 |
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| ISSN on article: | 0166-0934 |
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| DOI: | 10.1016/j.jviromet.2020.113864 |
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| COBISS.SI-ID: | 15879683 |
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| Publication date in DiRROS: | 22.07.2024 |
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| Views: | 10 |
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| Downloads: | 4 |
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