| Title |
Paper-based immune-affinity arrays for detection of multiple mycotoxins in cereals
|
|---|---|
| Published in |
Analytical & Bioanalytical Chemistry, February 2018
|
| DOI | 10.1007/s00216-018-0895-z |
| Pubmed ID | |
| Authors |
Li Li, Hongpu Chen, Xiaolan Lv, Min Wang, Xizhi Jiang, Yifei Jiang, Heye Wang, Yongfu Zhao, Liru Xia |
| Abstract |
Mycotoxins produced by different species of fungi may coexist in cereals and feedstuffs, and could be highly toxic for humans and animals. For quantification of multiple mycotoxins in cereals, we developed a paper-based mycotoxin immune-affinity array. First, paper-based microzone arrays were fabricated by photolithography. Then, monoclonal mycotoxin antibodies were added in a copolymerization reaction with a cross-linker to form an immune-affinity monolith on the paper-based microzone array. With use of a competitive immune-response format, paper-based mycotoxin immune-affinity arrays were successfully applied to detect mycotoxins in samples. The detection limits for deoxynivalenol, zearalenone, T-2 toxin, and HT-2 toxin were 62.7, 10.8, 0.36, and 0.23 μg·kg-1, respectively, which meet relevant requirements for these compounds in food. The recovery rates were 81-86% for deoxynivalenol, 89-117% for zearalenone, 79-86% for T-2 toxin, and 78-83% for HT-2 toxin, and showed the paper-based immune-affinity arrays had good reproducibility. In summary, the paper-based mycotoxin immune-affinity array provides a sensitive, rapid, accurate, stable, and convenient platform for detection of multiple mycotoxins in agro-foods. Graphical abstract Paper-based immune-affinity monolithic array. DON deoxynivalenol, HT-2 HT-2 toxin, T-2 T-2 toxin, PEGDA polyethylene glycol diacrylate, ZEN zearalenone. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 26 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 35% |
| Student > Doctoral Student | 3 | 12% |
| Unspecified | 2 | 8% |
| Student > Master | 2 | 8% |
| Librarian | 1 | 4% |
| Other | 2 | 8% |
| Unknown | 7 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 6 | 23% |
| Biochemistry, Genetics and Molecular Biology | 2 | 8% |
| Unspecified | 2 | 8% |
| Agricultural and Biological Sciences | 2 | 8% |
| Psychology | 1 | 4% |
| Other | 3 | 12% |
| Unknown | 10 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 March 2018.
All research outputs
#17,242,285
of 25,382,440 outputs
Outputs from Analytical & Bioanalytical Chemistry
#5,585
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Outputs of similar age
#281,272
of 446,116 outputs
Outputs of similar age from Analytical & Bioanalytical Chemistry
#81
of 189 outputs
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