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Antibody-Based Sensors: Principles, Problems and Potential for Detection of Pathogens and Associated Toxins
Open accessAbstract
Antibody-based sensors permit the rapid and sensitive analysis of a range of pathogens and associated toxins. A critical assessment of the implementation of such formats is provided, with reference to their principles, problems and potential for ‘on-site’ analysis. Particular emphasis is placed on the detection of foodborne bacterial pathogens, such as Escherichia coli and Listeria monocytogenes, and additional examples relating to the monitoring of fungal pathogens, viruses, mycotoxins, marine toxins and parasites are also provided.
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Cited by
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Ngoepe, M., Choonara, Y., Tyagi, C., Tomar, L., Du Toit, L., Kumar, P., Ndesendo, V., & Pillay, V. (2013) · Sensors · doi:10.3390/s130607680 · Cited by 92
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Puumala, L. S., Grist, S. M., Morales, J. M., Bickford, J. R., Chrostowski, L., Shekhar, S., & Cheung, K. C. (2022) · Biosensors · doi:10.3390/bios13010053 · Cited by 55
Metadata
- Authors
- Byrne, B., Stack, E., Gilmartin, N., & O’Kennedy, R.
- Venue
- Sensors
- Publisher
- MDPI AG
- Published
- 2009-06-05
- Volume
- 9
- Issue
- 6
- Pages
- 4407-4445
- ISSN
- 1424-8220 (ISSN-L)
- OpenAlex
- W2146218061
- Cited by
- 422
- References
- 0
- FWCI
- 9.12
- Type
- journal article
- Language
- en
- Open access
- gold
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- Byrne, B., Stack, E., Gilmartin, N., & O’Kennedy, R. (2009). Antibody-Based Sensors: Principles, Problems and Potential for Detection of Pathogens and Associated Toxins. Sensors. https://doi.org/10.3390/s90604407
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.