Evidence map›Paper›PMID 32601890›Full record

ArticleMikrochimica acta2020

Dark field microscope-based single nanoparticle identification coupled with statistical analysis for ultrasensitive biotoxin detection in complex sample matrix.

Shaohua Xu, Longhua Guo, Lifen Chen, Fang Luo, Bin Qiu, Zhenyu Lin

Abstract read
PubMed Publisher
In one paragraph

Article in Mikrochimica acta, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.6field-weighted citation impact, top 36% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 10 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Shaohua XuMinistry of Education Key Laboratory for Analytical Science of Food Safety and Biology, Fujian Provincial Key Laboratory of Analysis and Detection for Food Safety, College of Chemistry, Fuzhou University, Fuzhou, 350116, Fujian, China.
Longhua GuoCollege of Biological, Chemical Sciences and Engineering, Jiaxing University, Jiaxing, 314001, China. guolh@zjxu.edu.cn.ORCID 0000-0003-0706-0973
Lifen ChenCollege of Biological, Chemical Sciences and Engineering, Jiaxing University, Jiaxing, 314001, China. chenlf@zjxu.edu.cn.
Fang LuoMinistry of Education Key Laboratory for Analytical Science of Food Safety and Biology, Fujian Provincial Key Laboratory of Analysis and Detection for Food Safety, College of Chemistry, Fuzhou University, Fuzhou, 350116, Fujian, China.
Bin QiuMinistry of Education Key Laboratory for Analytical Science of Food Safety and Biology, Fujian Provincial Key Laboratory of Analysis and Detection for Food Safety, College of Chemistry, Fuzhou University, Fuzhou, 350116, Fujian, China. summer328cn@163.com.
Zhenyu LinMinistry of Education Key Laboratory for Analytical Science of Food Safety and Biology, Fujian Provincial Key Laboratory of Analysis and Detection for Food Safety, College of Chemistry, Fuzhou University, Fuzhou, 350116, Fujian, China.
Fuzhou University · CNJiaxing University · CN

Funding

Jilin Scientific and Technological Development Program (CN) 2018Y4007National Natural Science Foundation of China 21675028Nature Sciences Funding of Fujian Province 2018J01682Nature Sciences Funding of Fujian Province 2019J01238STS Key Project of Fujian Province 2017T3007
6 · The paper itself

Abstract

A novel approach for ultrasensitive ochratoxin A (OTA) detection is reported based on dark field microscope-based single nanoparticle identification coupled with a statistical analysis method. OTA aptamers were firstly hybridized with a single-stranded DNA (DNA1) to form an identification probe (DNA1-Apt). The aptamers separate from DNA1 in the presence of OTA and are released from the identification probe. Then, another single-stranded DNA (DNA2) hybridizes with DNA1 and result in the aggregation of gold nanoparticles (AuNPs). Therefore, the presence of AuNP aggregates is the evidence of the presence of OTA, while AuNP aggregates can be easily identified together with the monomers under dark field microscopic inspection. On the other hand, by counting the aggregation rate (the number of AuNP aggregates versus the number of AuNP monomers) with a statistical analysis method, OTA could be quantitatively detected. The detection range for OTA was 0.1 pg/mL ~ 30 ng/mL and the limit of detection was 0.1 pg/mL. The proposed sensor has comparative detection performance to sensors utilizing a number of signal amplification procedures, with the additional advantages of simplicity and high efficiency. The sensor can also be adopted for other target detection simply by replacing the identification probes. Graphical abstract The schematic of the AuNP aggregation for OTA detection. The OTA aptamers were competitively banded by OTA and induced form AuNP aggregation after adding DNA2 and AuNPs2. Subsequently, AuNPs were detected under dark field microscope and statistical analysis.

Indexed as

Aptamers, NucleotideBiosensing TechniquesDNAFood ContaminationGoldImmobilized Nucleic AcidsLimit of DetectionMetal NanoparticlesMicroscopyNucleic Acid HybridizationOchratoxinsWineAptamers, NucleotideDNAGoldImmobilized Nucleic Acidsochratoxin AOchratoxinsAggregationDark field microscopyOchratoxin ASingle nanoparticleStatistical analysis

Identifiers

PMID32601890
OpenAlexW3040095625

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.