Evidence map›Paper›PMID 38391982›Full record

ReviewBiosensors2024

Digital PCR for Single-Cell Analysis.

Weibo Fang, Xudong Liu, Mariam Maiga, Wenjian Cao, Ying Mu, Qiang Yan, Qiangyuan Zhu

Open access · goldAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Biosensors, 2024. 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
4.7field-weighted citation impact, top 4% 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, 20 citations in OpenAlex.

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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

7 authors at 3 institutions in 1 country.

Weibo FangResearch Center for Analytical Instrumentation, Institute of Cyber-Systems and Control, College of Control Science and Engineering, State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, China.
Xudong LiuResearch Center for Analytical Instrumentation, Institute of Cyber-Systems and Control, College of Control Science and Engineering, State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, China.
Mariam MaigaResearch Center for Analytical Instrumentation, Institute of Cyber-Systems and Control, College of Control Science and Engineering, State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, China.
Wenjian CaoResearch Center for Analytical Instrumentation, Institute of Cyber-Systems and Control, College of Control Science and Engineering, State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, China.
Ying MuResearch Center for Analytical Instrumentation, Institute of Cyber-Systems and Control, College of Control Science and Engineering, State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, China.
Qiang YanDepartment of Hepatobiliary and Pancreatic Surgery, Huzhou Central Hospital, Huzhou Key Laboratory of Intelligent and Digital Precision Surgery, Department of General Surgery, Affiliated Huzhou Hospital, School of Medicine, Zhejiang University, Huzhou 313000, China.
Qiangyuan ZhuResearch Center for Analytical Instrumentation, Institute of Cyber-Systems and Control, College of Control Science and Engineering, State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, China.
State Key Laboratory of Industrial Control TechnologyZhejiang University · CNZhejiang University of Technology · CN

Funding

Science and Technology Plan of Huzhou Science and Technology Bureau No. 2021GZ73the Fundamental Research Funds for the Central Universities No. 226-2023-00006
6 · The paper itself

Abstract

Single-cell analysis provides an overwhelming strategy for revealing cellular heterogeneity and new perspectives for understanding the biological function and disease mechanism. Moreover, it promotes the basic and clinical research in many fields at a single-cell resolution. A digital polymerase chain reaction (dPCR) is an absolute quantitative analysis technology with high sensitivity and precision for DNA/RNA or protein. With the development of microfluidic technology, digital PCR has been used to achieve absolute quantification of single-cell gene expression and single-cell proteins. For single-cell specific-gene or -protein detection, digital PCR has shown great advantages. So, this review will introduce the significance and process of single-cell analysis, including single-cell isolation, single-cell lysis, and single-cell detection methods, mainly focusing on the microfluidic single-cell digital PCR technology and its biological application at a single-cell level. The challenges and opportunities for the development of single-cell digital PCR are also discussed.

Indexed as

DNAMicrofluidicsPolymerase Chain ReactionRNASingle-Cell AnalysisDNARNAdigital PCRmicrofluidic chipsingle-cell analysis

Identifiers

PMID38391982
PMCPMC10886679
OpenAlexW4391169165

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.