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- W2600522174 abstract "Nuclear magnetic resonance (NMR) technique is a powerful analytical tool in determining the presence of bacterial contaminants in complex biological samples. In this paper, a portable NMR-based (pNMR) biosensor and assay to detect the foodborne bacteria Escherichia coli O157:H7 is reported. It uses antibody-functionalized polymer-coated magnetic nanoparticles as proximity biomarker of the bacteria which accelerates NMR resonance signal decay. The pNMR biosensor operates at 0.47 Tesla of magnetic strength and consists of a high-power pulsed RF transmitter and an ultra-low noise sensing circuitry capable of detecting weak NMR signal at 0.1 μV. The pNMR biosensor assay and sensing mechanism is used in detecting E. coli O157:H7 bacteria in drinking water and milk samples. Experimental results demonstrate that by adding a filtration step in the assay, the pNMR biosensor is able to detect E. coli O157:H7 as low as 76 CFU/mL in water samples and as low as 92 CFU/mL in milk samples in about one min. The pNMR biosensor assay and sensing system is innovative for foodborne bacterial detection in food matrices. The lowest detection level for E. coli O157:H7 in water and milk samples is essentially 101 CFU/mL. Although the linear range of detection is only from 101 to 104 CFU/mL, the wider detection range spans from 101 CFU/mL to 107 CFU/mL. Existing pNMR biosensors have detection limits at 103-104 CFU/mL only. The detection technique can be extended to other microbial or viral organisms by merely changing the specificity of the antibodies. Besides food safety, the pNMR biosensor described in this paper has potential to be applied as a rapid detection device in biodefense and healthcare diagnostic applications." @default.
- W2600522174 created "2017-04-07" @default.
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- W2600522174 date "2017-03-27" @default.
- W2600522174 modified "2023-10-18" @default.
- W2600522174 title "Portable nuclear magnetic resonance biosensor and assay for a highly sensitive and rapid detection of foodborne bacteria in complex matrices" @default.
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- W2600522174 doi "https://doi.org/10.1186/s13036-017-0053-8" @default.
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