Evidence map›Paper›PMID 23162691›Full record

ArticleScientific reports2012

DNA Nanostructure-based Interfacial engineering for PCR-free ultrasensitive electrochemical analysis of microRNA.

Yanli Wen, Hao Pei, Ye Shen, Junjie Xi, Meihua Lin, Na Lu, Xizhong Shen, Jiong Li, Chunhai Fan

Erratum issuedAbstract read
In one paragraph

Article in Scientific reports, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing 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

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

37 citing papers in PubMed.

  1. Review
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  4. Article
  5. Review
  6. Article
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  8. Article
  9. Development of Electrochemical Biosensor for miR204-Based Cancer Diagnosis.Interdisciplinary sciences, computational life sciences · 2022
    Article
  10. MoSBioactive materials · 2021
    Review
  11. Article
  12. DNA Transformations for Diagnosis and Therapy.Advanced functional materials · 2021
    Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
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4 · The record

Corrections and comments

  • Erratum issued
5 · Who and what money

Authors and funding

9 authors.

Yanli WenLaboratory of Physical Biology, Shanghai Institute of Applied Physics , Chinese Academy of Sciences, Shanghai 201800, China.
Hao Pei
Ye Shen
Junjie Xi
Meihua Lin
Na Lu
Xizhong Shen
Jiong Li
Chunhai Fan

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MicroRNAs (miRNAs) have been identified as promising cancer biomarkers due to their stable presence in serum. As an alternative to PCR-based homogenous assays, surface-based electrochemical biosensors offer great opportunities for low-cost, point-of-care tests (POCTs) of disease-associated miRNAs. Nevertheless, the sensitivity of miRNA sensors is often limited by mass transport and crowding effects at the water-electrode interface. To address such challenges, we herein report a DNA nanostructure-based interfacial engineering approach to enhance binding recognition at the gold electrode surface and drastically improve the detection sensitivity. By employing this novel strategy, we can directly detect as few as attomolar (<1, 000 copies) miRNAs with high single-base discrimination ability. Given that this ultrasensitive electrochemical miRNA sensor (EMRS) is highly reproducible and essentially free of prior target labeling and PCR amplification, we also demonstrate its application by analyzing miRNA expression levels in clinical samples from esophageal squamous cell carcinoma (ESCC) patients.

Indexed as

Electrochemical TechniquesBiosensing TechniquesCarcinoma, Squamous CellDNAElectrodesEsophageal NeoplasmsGoldHumansMicroRNAsNanostructuresPoint-of-Care SystemsPolymerase Chain ReactionDNAGoldMicroRNAsMIRN21 microRNA, human

Identifiers

PMID23162691
PMCPMC3499757

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.