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Yazar "Oz, Mustafa Emin" seçeneğine göre listele

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    A high-resolution melting assay to differentiate a peste des petits ruminants virus vaccine strain from field isolates in Turkey
    (Springer Wien, 2022) Oz, Mustafa Emin; Torlak, Emrah
    Peste des petits ruminants (PPR) mostly affects small ruminants. Vaccination with attenuated vaccines derived from PPR virus (PPRV) provides successful protection against the disease. However, current molecular methods are unable to distinguish vaccine strains from field strains. In this study, we used an EvaGreen-based high-resolution melting (HRM) assay to differentiate a PPRV vaccine strain (Nigeria 75/1) from Turkish field isolates of lineage IV based on melting peaks and melting profiles.
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    A new molecular approach to the diagnosis of small ruminant morbillivirus with EvaGreen based assay
    (Tubitak Scientific & Technological Research Council Turkey, 2021) Oz, Mustafa Emin; Torlak, Emrah; Avci, Oguzhan; Dogan, Muge; Uncu, Ali Tevfik
    The present work describes a new method that is anticipated to contribute to the global control and eradication strategies of small ruminant morbillivirus (SRMV), which negatively affects sheep and goat breeding in many countries where outbreaks emerge. Described assay was developed to detect SRMV by targeting the fusion glycoprotein gene. In the study, the EvaGreen based real-time RT-PCR method is compared with real-time RT-PCR based on TaqMan probe, which is recommended as the diagnostic test by World Organisation for Animal Health (OIE). Detection limit, normalized fluorescence values, and sensitivity of the methods were evaluated in the analysis. The lowest limit of detection obtained was approximately 12 RNA copies per reaction corresponding to a C-T value of 36.79. According to the results, it was observed that the developed in-house method has a specific, sensitive, and powerful detection limit as much as the gold standard test. As a result, it was concluded that the proposed method, which was developed as a more cost-effective and easily optimized analysis, could provide an advantage for detecting SRMV in diagnostic laboratories.

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