ArticleFrontiers in cellular and infection microbiology2023
Development of droplet digital PCR-based detection of bacterial pathogens in prosthetic joint infection: a preliminary study using a synthesized model plasmid.
Article in Frontiers in cellular and infection microbiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 9 citations in OpenAlex.
- Revisiting Strategies for Bacterial Enumeration: The Case for Viable but Nonculturable (VBNC) Cells in Supplement Products.Probiotics and antimicrobial proteins · 2026Review
- Global trends in biomarker research for periprosthetic joint infection: a bibliometric analysis.Arthroplasty (London, England) · 2026Article
- Advances in methods for rapid detection of Staphylococcus aureus and methicillin-resistant S. aureus.Analytical sciences : the international journal of the Japan Society for Analytical Chemistry · 2025Review
- CRISPR-driven diagnostics: Molecular mechanisms, clinical efficacy and translational challenges.Clinical and translational medicine · 2025Review
- Beyond Cultures: The Evolving Role of Molecular Diagnostics, Synovial Biomarkers and Artificial Intelligence in the Diagnosis of Prosthetic Joint Infections.Journal of clinical medicine · 2025Review
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
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Abstract
Periprosthetic joint infection (PJI) can be diagnosed to characterize the microorganisms constituting a biofilm, which is an essential procedure for proper treatment. The gold standard method for detecting and identifying the causative microorganism is culture of microorganisms from patients-derived sample.; however, this method takes a long time and has low sensitivity. To compensate for these limitations, identification methods based on real-time PCR (RT-PCR) have been widely used. However, RT-PCR also has limitations, including low sensitivity and the requirement of a standard curve for quantification. Therefore, to prevent significant proliferation of pathogenic bacteria, it is important to detect a limited number of infectious bacteria during early stages of PJI. In the present study, we developed droplet digital PCR-based detection of bacterial pathogens in PJI. And we evaluated the analytical performance of the assay using a model plasmid, based on the 16S ribosomal DNA sequence of target bacteria commonly found in PJI. We also prepared genomic DNA extracted from
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