Evidence map›Paper›PMID 32394009›Full record

ArticleNanoscale research letters2020

Detection of microRNA-335-5p on an Interdigitated Electrode Surface for Determination of the Severity of Abdominal Aortic Aneurysms.

Bei Lu, Leiting Liu, Jingrui Wang, Yuan Chen, Zhijiang Li, Subash C B Gopinath, Thangavel Lakshmipriya, Zongwei Huo

Abstract read
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Article in Nanoscale research letters, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

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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

9 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

8 authors.

Bei LuDepartment of Hepato-pancreato-biliary Surgery, The Affiliated Hangzhou First People's Hospital of Zhejiang University School of Medicine, Zhejiang, 310006, Hangzhou, China.
Leiting LiuDepartment of General Thoracic and Vascular Surgery, Wuhan No. 1 Hospital, Wuhan, 430022, Hubei, China.
Jingrui WangDepartment of Hepato-pancreato-biliary Surgery, The Affiliated Hangzhou First People's Hospital of Zhejiang University School of Medicine, Zhejiang, 310006, Hangzhou, China.
Yuan ChenDepartment of Endocrinology, The First People's Hospital of Zunyi, Zunyi, 563000, Guizhou, China.
Zhijiang LiDepartment of Gallbladder Pancreas and Vascular Surgery, Jingmen No. 1 People's Hospital, Jingmen, 448000, Hubei, China.
Subash C B GopinathSchool of Bioprocess Engineering, Universiti Malaysia Perlis, 02600, Arau, Perlis, Malaysia.
Thangavel LakshmipriyaInstitute of Nano Electronic Engineering, Universiti Malaysia Perlis, 01000, Kangar, Perlis, Malaysia.
Zongwei HuoDepartment of Nuclear Medicine, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, 250117, Shandong, China. huozunwei2019@sina.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Abdominal aortic aneurysm (AAA) refers to the enlargement of the lower artery of the abdominal aorta, and identification of an early detection tool is urgently needed for diagnosis. In the current study, an interdigitated electrode (IDE) sensing surface was used to identify miRNA-335-5p, which reflects the formation of AAAs. The uniformity of the silica material was observed by 3D profilometry, and the chemically modified highly conductive surface improved the detection via the I-V mode. The targeted miRNA-335-5p was detected in a dose-dependent manner and based on linear regression and 3σ analyses, the sensitivity was determined to be 1 fM with a biotinylated probe. The high specificity was shown by discriminating the target sequence from noncomplementary and single- and triple-mismatched sequences. These outputs demonstrated the high-performance detection of miRNA-335-5p with good reproducibility for determination of the severity of AAA.

Indexed as

BiosensorBulging aortaEarly diagnosisNoncoding RNAStreptavidin-biotin

Identifiers

PMID32394009
PMCPMC7214562

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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.