Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 501

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Hybridization Chain Reaction Amplification of MicroRNA Detection with a Tetrahedral DNA Nanostructure-Based Electrochemical Biosensor

Ge, Zhilei, Lin, Meihua, Wang, Ping, Pei, Hao, Yan, Juan, Shi, Jiye, Huang, Qing, He, Dannong, Fan, Chunhai, Zuo, Xiaolei·2014·Analytical Chemistry

Abstract

There remains a great challenge in the sensitive detection of microRNA because of the short length and low abundance of microRNAs in cells. Here, we have demonstrated an ultrasensitive detection platform for microRNA by combining the tetrahedral DNA nanostructure probes and hybridization chain reaction (HCR) amplification. The detection limits for DNA and microRNA are 100 aM and 10 aM (corresponding to 600 microRNAs in a 100 μL sample), respectively. Compared to the widely used supersandwich amplification, the detection limits are improved by 3 orders of magnitude. The uncontrolled surface immobilization and consumption of target molecules that limit the amplification efficiency of supersandwich are eliminated in our platform. Taking advantage of DNA nanotechnology, we employed three-dimensional tetrahedral DNA nanostructure as the scaffold to immobilize DNA recognition probes to increase the reactivity and accessibility, while DNA nanowire tentacles are used for efficient signal amplification by capturing multiple catalytic enzymes in a highly ordered way. The synergetic effect of DNA tetrahedron and nanowire tentacles have proven to greatly improve sensitivity for both DNA and microRNA detection.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1021/ac4037262

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Cited by

See all 501

Metadata

Authors
Ge, Z., Lin, M., Wang, P., Pei, H., Yan, J., Shi, J., Huang, Q., He, D., Fan, C., & Zuo, X.
Venue
Analytical Chemistry
Published
2014-02-04
Volume
86
Issue
4
Pages
2124-2130
ISSN
  • 0003-2700 (ISSN-L)
  • 1520-6882
OpenAlex
W2008662133
Cited by
501
References
2
FWCI
18.62
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.