Evidence map›Paper›PMID 37517003›Full record

ReviewAnalytical sciences : the international journal of the Japan Society for Analytical Chemistry2023

Development of practical techniques for simultaneous detection and distinction of current and emerging SARS-CoV-2 variants.

Tuocen Fan, Chengjie Li, Xinlei Liu, Hongda Xu, Wenhao Li, Minghao Wang, Xifan Mei, Dan Li

Abstract readReview
PubMed Publisher
In one paragraph

Review in Analytical sciences : the international journal of the Japan Society for Analytical Chemistry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 87% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

8 authors at 1 institution in 1 country.

Tuocen FanJinzhou Medical University, Jinzhou, 121000, China.
Chengjie LiJinzhou Medical University, Jinzhou, 121000, China.
Xinlei LiuJinzhou Medical University, Jinzhou, 121000, China.
Hongda XuJinzhou Medical University, Jinzhou, 121000, China.
Wenhao LiJinzhou Medical University, Jinzhou, 121000, China.
Minghao WangJinzhou Medical University, Jinzhou, 121000, China.
Xifan MeiJinzhou Medical University, Jinzhou, 121000, China. meixifan@jzmu.edu.cn.ORCID http://orcid.org/0000-0003-3698-0525
Dan LiJinzhou Medical University, Jinzhou, 121000, China. danli@jzmu.edu.cn.ORCID http://orcid.org/0000-0002-3452-0798
Jinzhou Medical University · CN

Funding

the 2021 Scientific Research Funding Project of Liaoning Provincial Department of Education No. LJKZ0818
6 · The paper itself

Abstract

Countless individuals have fallen victim to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and have generated antibodies, reducing the risk of secondary infection in the short term. However, with the emergence of mutated strains, the probability of subsequent infections remains high. Consequently, the demand for simple and accessible methods for distinguishing between different variants is soaring. Although monitoring viral gene sequencing is an effective approach for differentiating between various types of SARS-CoV-2 variants, it may not be easily accessible to the general public. In this article, we provide an overview of the reported techniques that use combined approaches and adaptable testing methods that use editable recognition receptors for simultaneous detection and distinction of current and emerging SARS-CoV-2 variants. These techniques employ straightforward detection strategies, including tests capable of simultaneously identifying and differentiating between different variants. Furthermore, we recommend advancing the development of uncomplicated protocols for distinguishing between current and emerging variants. Additionally, we propose further development of facile protocols for the differentiation of existing and emerging variants.

Indexed as

COVID-19SARS-CoV-2HumansDetectionDifferentiationMutantsSARS-CoV-2SimutaneousVariants

Identifiers

PMID37517003
OpenAlexW4385392458

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.