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- W4385332592 abstract "Helicobacter pylori is a major human pathogen that infects approximately half of the global population and is becoming a serious health threat due to its increasing antibiotic resistance. It is the causative agent of chronic active gastritis, peptic ulcer disease, and gastric cancer and has been classified as a Group I Carcinogen by the International Agency for Research on Cancer. Therefore, the rapid and accurate diagnosis of H. pylori and the determination of its antibiotic resistance are important for the efficient eradication of this bacterial pathogen. Currently, H. pylori diagnosis methods mainly include the urea breath test (UBT), the antigen test, the serum antibody test, gastroscopy, the rapid urease test (RUT), and bacterial culture. Among them, the first three detection methods are noninvasive, meaning they are easy tests to conduct. However, bacteria cannot be retrieved through these techniques; thus, drug resistance testing cannot be performed. The last three are invasive examinations, but they are costly, require high skills, and have the potential to cause damage to patients. Therefore, a noninvasive, rapid, and simultaneous method for H. pylori detection and drug resistance testing is very important for efficiently eradicating H. pylori in clinical practice. This protocol aims to present a specific procedure involving the string test in combination with quantitative polymerase chain reaction (qPCR) for the rapid detection of H. pylori infection and antibiotic resistance. Unlike bacterial cultures, this method allows for easy, rapid, noninvasive diagnosis of H. pylori infection status and drug resistance. Specifically, we used qPCR to detect rea for H. pylori infection and mutations in the 23S rRNA and gyrA genes, which encode resistance against clarithromycin and levofloxacin, respectively. Compared to routinely used culturing techniques, this protocol provides a noninvasive, low-cost, and time-saving technique to detect H. pylori infection and determine its antibiotic resistance using qPCR." @default.
- W4385332592 created "2023-07-29" @default.
- W4385332592 date "2023-07-29" @default.
- W4385332592 modified "2023-09-23" @default.
- W4385332592 title "JoVE Video Dataset" @default.
- W4385332592 doi "https://doi.org/10.3791/65689-v" @default.
- W4385332592 hasPublicationYear "2023" @default.
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