Evidence map›Paper›PMID 36551113›Full record

ArticleBiosensors2022

Visual and Ultrasensitive Detection of a Coronavirus Using a Gold Nanorod Probe under Dark Field.

Xuejia Qian, Yuanzhao Shen, Jiasheng Yuan, Chih-Tsung Yang, Xin Zhou

Open access · goldAbstract read
In one paragraph

Article in Biosensors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 42% 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

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
  2. Review
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

5 authors at 2 institutions in 2 countries.

Xuejia QianCollege of Veterinary Medicine, Institute of Comparative Medicine, Yangzhou University, Yangzhou 225009, China.
Yuanzhao ShenCollege of Veterinary Medicine, Institute of Comparative Medicine, Yangzhou University, Yangzhou 225009, China.ORCID 0000-0001-8428-3340
Jiasheng YuanCollege of Veterinary Medicine, Institute of Comparative Medicine, Yangzhou University, Yangzhou 225009, China.
Chih-Tsung YangFuture Industries Institute, Mawson Lakes Campas, University of South Australia, Adelaide, SW 5095, Australia.
Xin ZhouCollege of Veterinary Medicine, Institute of Comparative Medicine, Yangzhou University, Yangzhou 225009, China.ORCID 0000-0003-2515-704X
Yangzhou University · CNUniversity of South Australia · AU

Funding

National Natural Science Foundation of China Grant No: 31870989Priority Academic Program Development of Jiangsu Higher Education Institutions PAPD
6 · The paper itself

Abstract

Porcine epidemic diarrhea virus (PEDV), a coronavirus that causes highly infectious intestinal diarrhea in piglets, has led to severe economic losses worldwide. Rapid diagnosis and timely supervision are significant in the prophylaxis of PEDV. Herein, we proposed a gold-nanorod (GNR) probe-assisted counting method using dark field microscopy (DFM). The antibody-functionalized silicon chips were prepared to capture PEDV to form sandwich structures with GNR probes for imaging under DFM. Results show that our DFM-based assay for PEDV has a sensitivity of 23.80 copies/μL for simulated real samples, which is very close to that of qPCR in this study. This method of GNR probes combined with DFM for quantitative detection of PEDV not only has strong specificity, good repeatability, and a low detection limit, but it also can be implemented for rapid on-site detection of the pathogens.

Indexed as

CoronavirusCoronavirus InfectionsPorcine epidemic diarrhea virusSwine DiseasesAnimalsGoldSwineGolddark field microscopy (DFM)gold-nanorod probe (GNR probe)low detection limiton-site detectionporcine epidemic diarrhea virus (PEDV)

Identifiers

PMID36551113
PMCPMC9775988
OpenAlexW4311855684

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.