Evidence map›Paper›PMID 35590941›Full record

ArticleSensors (Basel, Switzerland)2022

Fluorescence DNA Switch for Highly Sensitive Detection of miRNA Amplified by Duplex-Specific Nuclease.

Xiaoqiang Li, Zhenzhen Guo, Gangyin Luo, Peng Miao

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 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
0.3field-weighted citation impact, top 49% 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, 3 citations in OpenAlex.

  1. Article
  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

4 authors at 2 institutions in 1 country.

Xiaoqiang LiSchool of Biomedical Engineering (Suzhou), University of Science and Technology of China, Hefei 230026, China.
Zhenzhen GuoSuzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China.
Gangyin LuoSuzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China.
Peng MiaoSchool of Biomedical Engineering (Suzhou), University of Science and Technology of China, Hefei 230026, China.ORCID 0000-0003-3993-4778
Chinese Academy of Sciences · CNUniversity of Science and Technology of China · CN

Funding

Science and Technology Project of Ji Hua Laboratory X190191TD190Strategic Priority Research Program of the Chinese Academy of Sciences XDA16021101
6 · The paper itself

Abstract

DNA is a type of promising material for the construction of sensors owing to its sequence programmability to control the formation of certain structures. MicroRNA (miRNA) can be applied as promising biomarkers for the diagnosis of a range of diseases. Herein, a novel fluorescent sensing strategy for miRNA is proposed combining duplex-specific nuclease (DSN)-mediated amplification and dumbbell DNA structural switch. Gold nanoparticles (AuNPs) are employed, which provide a 3D reaction interface. They also act as effective fluorescence quenchers. The proposed sensor exhibits high sensitivity (sub-femtomolar level) with a wide dynamic range. In addition, excellent selectivity to distinguish homology sequences is achieved. It also performs satisfactorily in biological samples. Overall, this fluorescent sensor provides a powerful tool for the analysis of miRNA levels and can be applied for related biological studies and clinical diagnosis.

Indexed as

Biosensing TechniquesMetal NanoparticlesMicroRNAsDNAEndonucleasesGoldLimit of DetectionNucleic Acid Amplification TechniquesDNAEndonucleasesGoldMicroRNAsDNA switchduplex-specific nucleasefluorescent sensorgold nanoparticlesmiRNA

Identifiers

PMID35590941
PMCPMC9104181
OpenAlexW4224312033

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.