Evidence map›Paper›PMID 32111327›Full record

ArticlePoultry science2020

Combining impedance biosensor with immunomagnetic separation for rapid screening of Salmonella in poultry supply chains.

Lei Wang, Li Xue, Ruya Guo, Lingyan Zheng, Siyuan Wang, Lan Yao, Xiaoting Huo, Ning Liu, Ming Liao, Yanbin Li and 1 more

Open access · goldAbstract read
In one paragraph

Article in Poultry science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.5field-weighted citation impact, top 11% 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

11 citing papers in PubMed, 43 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Review
  9. Review
  10. Review
  11. 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

11 authors at 3 institutions in 2 countries.

Lei WangKey Laboratory of Agricultural Information Acquisition Technology, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100083, China.
Li XueKey Laboratory of Agricultural Information Acquisition Technology, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100083, China.
Ruya GuoKey Laboratory of Agricultural Information Acquisition Technology, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100083, China.
Lingyan ZhengKey Laboratory of Agricultural Information Acquisition Technology, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100083, China.
Siyuan WangKey Laboratory of Agricultural Information Acquisition Technology, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100083, China.
Lan YaoKey Laboratory of Agricultural Information Acquisition Technology, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100083, China.
Xiaoting HuoKey Laboratory of Agricultural Information Acquisition Technology, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100083, China.
Ning LiuKey Laboratory of Agricultural Information Acquisition Technology, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100083, China.
Ming LiaoCollege of Veterinary Medicine, South China Agricultural University, Guangzhou 510642, China.
Yanbin LiDepartment of Biological and Agricultural Engineering, University of Arkansas, Fayetteville, AR 72701.
Jianhan LinKey Laboratory of Agricultural Information Acquisition Technology, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100083, China. Electronic address: Jianhan@cau.edu.cn.
Ministry of Agriculture and Rural Affairs · CNSouth China Agricultural University · CNUniversity of Arkansas at Fayetteville · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Salmonella screening is a key to ensure food safety in poultry supply chains. Currently available Salmonella detection methods including culture, polymerase chain reaction and enzyme-linked immuno-sorbent assay could not achieve rapid, sensitive, and in-field detection. In this study, different strategies for separation and detection of Salmonella were proposed, compared, and improved based on our previous studies on immunomagnetic separation and impedance biosensor. First, the coaxial capillary for immunomagnetic separation of target bacteria was improved with less contamination, and 3 strategies based on the improved capillary and immunomagnetic nanoparticles were compared to separate the target bacteria from sample and form the magnetic bacteria. The experimental results showed that the strategy of capture in tube and separation in capillary was the most suitable with separation efficiency of approximately 88%. Then, the immune gold nanoparticles coated with urease were used to label the magnetic bacteria, resulting in the formation of enzymatic bacteria, which were injected into the capillary. After the urea was catalyzed by the urease on the enzymatic bacteria in the capillary, different electrodes were compared to measure the impedance of the catalysate and the screen-printed electrode with higher sensitivity and better stability was the most suitable. This impedance biosensor-based bacterial detection strategy was able to detect Salmonella as low as 10

Indexed as

Biosensing TechniquesChickensDucksImmunomagnetic SeparationAnimalsElectric ImpedanceFood MicrobiologyFood SafetySalmonellaSensitivity and Specificityfood safetyimmunomagnetic separationimpedance biosensorpoultry supply chainsSalmonella screening

Identifiers

PMID32111327
PMCPMC7587860
OpenAlexW3002376498

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.