Evidence map›Paper›PMID 36743821›Full record

ArticleSensors and actuators. B, Chemical2023

RT-RPA-Cas12a-based assay facilitates the discrimination of SARS-CoV-2 variants of concern.

Guiyue Tang, Zilong Zhang, Wei Tan, Fei Long, Jingxian Sun, Yingying Li, Siwei Zou, Yujiao Yang, Kezhu Cai, Shenwei Li and 7 more

Abstract read
In one paragraph

Article in Sensors and actuators. B, Chemical, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

5 citing papers in PubMed.

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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

17 authors.

Guiyue TangCAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
Zilong ZhangShanghai International Travel Healthcare Center, Shanghai Customs District P. R. China, Shanghai 200335, China.
Wei TanCAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
Fei LongCAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
Jingxian SunCAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
Yingying LiCAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
Siwei ZouCAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
Yujiao YangCAS Key Laboratory of Synthetic Biology, CAS Center for Excellence in Molecular Plant Sciences, Chinese Academy of Sciences, Shanghai 200032, China.
Kezhu CaiCAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
Shenwei LiShanghai International Travel Healthcare Center, Shanghai Customs District P. R. China, Shanghai 200335, China.
Zhiyi WangShanghai International Travel Healthcare Center, Shanghai Customs District P. R. China, Shanghai 200335, China.
Jiakun LiuCAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
Guobing MaoCAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
Yingxin MaCAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
Guo-Ping ZhaoCAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
Zhen-Gan TianShanghai International Travel Healthcare Center, Shanghai Customs District P. R. China, Shanghai 200335, China.
Wei ZhaoCAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Timely and accurate detection of SARS-CoV-2 variants of concern (VOCs) is urgently needed for pandemic surveillance and control. Great efforts have been made from a mass of scientists in increasing the detection sensitivity and operability, and reducing the turn-around time and cost. Here, we report a nucleic acid testing-based method aiming to detect and discriminate SARS-CoV-2 mutations by combining RT-RPA and CRISPR-Cas12a detecting assays (RRCd). With a detection limit of 10 copies RNA/reaction, RRCd was validated in 194 clinical samples, showing 89% positive predictive agreement and 100% negative predictive agreement, respectively. Critically, using specific crRNAs, representatives of single nucleotide polymorphisms and small deletions in SARS-CoV-2 VOCs including N501Y, T478K and ΔH69-V70 were discriminated by RRCd, demonstrating 100% specificity in clinical samples with

Indexed as

CRISPRPoint-of-care testingRRCdSARS-CoV-2Variant of concern

Identifiers

PMID36743821
PMCPMC9884195

What OpenQuestion holds

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Registered trials

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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.