The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.
Aptamer-based assays and aptasensors for detection of pathogenic bacteria in food samples
Abstract
Abstract Due to increased concerns about food safety, rapid, specific and highly sensitive monitoring of pathogen bacteria in food samples is of great importance to ensure public health. Although traditional detection methods are available, they are time consuming, labor intensive, unsuitable for on-site detection, and need highly trained personnel. To overcome these limitations, many efforts have been devoted to develop a new class of bioassays, aptamer-based assays, which use nucleic acid as bio-recognition elements. Aptamer-based assays and aptasensors, as emerging analytical methods, have opened new horizons for simple, specific and sensitive detection of microorganisms including pathogen bacteria. This review therefore will focus on new developed aptamer-based assays and aptasensors for pathogenic bacteria in food samples. We will also highlight advantages and drawbacks of various types of assays developed for pathogen bacteria detection.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Foodborne illness acquired in the United States—Major pathogens
Scallan, E., Hoekstra, R. M., Angulo, F. J., Tauxe, R. V., Widdowson, M.-A., Roy, S. L., Jones, J. L., & Griffin, P. M. (2011) · Emerging Infectious Diseases · doi:10.3201/eid1701.p11101 · Cited by 7,657
Analytical applications of aptamers
Tombelli, S., Minunni, M., & Mascini, M. (2005) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2004.11.006 · Cited by 1,017
Colorimetric Biosensing Using Smart Materials
Song, Y., Wei, W., & Qu, X. (2011) · Advanced Materials · doi:10.1002/adma.201101853 · Cited by 666
Optical Biosensors for the Detection of Pathogenic Microorganisms
Yoo, S. M., & Lee, S. Y. (2016) · Trends in Biotechnology · doi:10.1016/j.tibtech.2015.09.012 · Cited by 571
Chemiluminescence as diagnostic tool. A review
Dodeigne, C. (2000) · Talanta · doi:10.1016/s0039-9140(99)00294-5 · Cited by 563
Replacing antibodies with aptamers in lateral flow immunoassay
Chen, A., & Yang, S. (2015) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2015.04.041 · Cited by 551
Methodology for detection and typing of foodborne microorganisms
de Boer, E. (1999) · International Journal of Food Microbiology · doi:10.1016/s0168-1605(99)00081-1 · Cited by 394
Liu, Y., Zhou, H., Hu, Z., Yu, G., Yang, D., & Zhao, J. (2017) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2017.02.032 · Cited by 388
Xu, H., Aguilar, Z. P., Yang, L., Kuang, M., Duan, H., Xiong, Y., Wei, H., & Wang, A. (2011) · Biomaterials · doi:10.1016/j.biomaterials.2011.08.076 · Cited by 381
Interdigitated array microelectrodes based impedance biosensors for detection of bacterial cells
Varshney, M., & Li, Y. (2009) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2008.10.001 · Cited by 360
Metadata
- Authors
- Majdinasab, M., Hayat, A., & Marty, J. L.
- Venue
- TrAC Trends in Analytical Chemistry
- Publisher
- Elsevier BV
- Published
- 2018-10
- Volume
- 107
- Pages
- 60-77
- ISSN
- 0165-9936 (ISSN-L)
- OpenAlex
- W2885045697
- Cited by
- 257
- References
- 55
- FWCI
- 8.40
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Aptamer-based assays and aptasensors for detection of pathogenic bacteria in food samples. https://app.cochat.ai/papers/10.1016/j.trac.2018.07.016
- The paper
- Majdinasab, M., Hayat, A., & Marty, J. L. (2018). Aptamer-based assays and aptasensors for detection of pathogenic bacteria in food samples. TrAC Trends in Analytical Chemistry. https://doi.org/10.1016/j.trac.2018.07.016
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.