ArticleBiomicrofluidics2012
Rapid detection of live methicillin-resistant Staphylococcus aureus by using an integrated microfluidic system capable of ethidium monoazide pre-treatment and molecular diagnosis.
Article in Biomicrofluidics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 28 citations in OpenAlex.
- Microfluidic-Based Nucleic Acid Amplification Systems in Microbiology.Micromachines · 2019Review
- Quantitative Polymerase Chain Reaction Coupled With Sodium Dodecyl Sulfate and Propidium Monoazide for Detection of ViableFrontiers in microbiology · 2019Article
- Vancomycin-resistant gene identification from live bacteria on an integrated microfluidic system by using low temperature lysis and loop-mediated isothermal amplification.Biomicrofluidics · 2017Article
- Toward a Molecular Understanding of the Antibacterial Mechanism of Copper-Bearing Titanium Alloys against Staphylococcus aureus.Advanced healthcare materials · 2016Article
- Advances and Challenges in Viability Detection of Foodborne Pathogens.Frontiers in microbiology · 2016Review
- An automated microfluidic system for single-stranded DNA preparation and magnetic bead-based microarray analysis.Biomicrofluidics · 2015Article
- Hydrogel-based microfluidic incubator for microorganism cultivation and analyses.Biomicrofluidics · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Methicillin-resistant Staphylococcus aureus (MRSA) is a bacterium resistant to all existing penicillin and lactam-based antimicrobial drugs and, therefore, has become one of the most prevalent antibiotic-resistant pathogens found in hospitals. The multi-drug resistant characteristics of MRSA make it challenging to clinically treat infected patients. Therefore, early diagnosis of MRSA has become a public-health priority worldwide. Conventionally, cell-culture based methodology and microscopic identification are commonly used for MRSA detection. However, they are relatively time-consuming and labor-intensive. Recently, molecular diagnosis based on nucleic acid amplification techniques, such as polymerase chain reaction (PCR), has been widely investigated for the rapid detection of MRSA. However, genomic DNA of both live and dead pathogens can be distinguished by conventional PCR. These results thus could not provide sufficient confirmation of an active infection for clinicians. In this study, live MRSA was rapidly detected by using a new integrated microfluidic system. The microfluidic system has been demonstrated to have 100% specificity to detect live MRSA with S. aureus and other pathogens commonly found in hospitals. The experimental results showed that the limit of detection for live MRSA from biosamples was approximately 10(2) CFU/μl. In addition, the entire diagnostic protocol, from sample pre-treatment to fluorescence observation, can be automatically completed within 2.5 h. Consequently, this microfluidic system may be a powerful tool for the rapid molecular diagnosis of live MRSA.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.