Evidence map›Paper›PMID 36466682›Full record

ArticleFrontiers in microbiology2022

Internet of medical things-enabled CRISPR diagnostics for rapid detection of SARS-CoV-2 variants of concern.

Huihuang Lin, Weibo Zheng, Shenwei Li, Yu Wang, Dong Wei, Leiying Xie, Wei Lu, Zhengan Tian, Shaowei Wang, Jieming Qu and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in microbiology, 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
0.9field-weighted citation impact, top 28% 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, 10 citations in OpenAlex.

  1. Article
  2. 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 5 institutions in 1 country.

Huihuang LinDepartment of Pulmonary and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Weibo ZhengState Key Laboratory of Infrared Physics, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai, China.
Shenwei LiShanghai International Travel Healthcare Center, Shanghai, China.
Yu WangShanghai Institute for Advanced Immunochemical Studies and School of Life Science and Technology, ShanghaiTech University, Shanghai, China.
Dong WeiDepartment of Infectious Diseases, Research Laboratory of Clinical Virology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Leiying XieState Key Laboratory of Infrared Physics, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai, China.
Wei LuState Key Laboratory of Infrared Physics, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai, China.
Zhengan TianShanghai International Travel Healthcare Center, Shanghai, China.
Shaowei WangState Key Laboratory of Infrared Physics, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai, China.
Jieming QuDepartment of Pulmonary and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Jia LiuShanghai Institute for Advanced Immunochemical Studies and School of Life Science and Technology, ShanghaiTech University, Shanghai, China.
Shanghai Institute of Technical Physics · CNShanghai Jiao Tong University · CNShanghaiTech University · CNShenzhen International Travel Health Care Center · CNRuijin Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Previous studies have highlighted CRISPR-based nucleic acid detection as rapid and sensitive diagnostic methods for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Here, we reported an optimized CRISPR-Cas12a diagnostic platform for the safe and rapid detection of SARS-CoV-2 variants of concern (VOCs). This platform, which was referred to as CALIBURN-v2, could complete the diagnosis on extracted RNA samples within 25 min in a closed-lid reaction mode and had 100-fold increase in detection sensitivity in comparison with previous platforms. Most importantly, by integrating a portable device and smartphone user interface, CALIBURN-v2 allowed for cloud server-based data collection and management, thus transforming the point-of-care testing (POCT) platform to internet of medical things (IoMT) applications. It was found that IoMT-enabled CALIBURN-v2 could achieve 95.56% (172 out of 180) sensitivity for SARS-CoV-2 wild type and 94.38% (84 out of 89) overall sensitivity for SARS-CoV-2 variants including Delta and Omicron strains. Therefore, our study provides a feasible approach for IoMT-enabled CRISPR diagnostics for the detection of SARS-CoV-2 VOCs.

Indexed as

closed-lidCRISPR-Cas12ainternet of medical thingspoint-of-care testingSARS-CoV-2smartphone controlvariants of concern

Identifiers

PMID36466682
PMCPMC9715597
OpenAlexW4309264996

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.