Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 161

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

A DNAzyme Feedback Amplification Strategy for Biosensing

Liu, Meng, Zhang, Qiang, Chang, Dingran, Gu, Jimmy, Brennan, John D., Li, Yingfu·2017·Angewandte Chemie International Edition

Abstract

We report a signal amplification strategy termed DNAzyme feedback amplification (DFA) that takes advantage of rolling‐circle amplification (RCA) and an RNA‐cleaving DNAzyme (RCD). DFA employs two specially programmed DNA complexes, one composed of a primer and a circular template containing the antisense sequence of an RCD, and the other composed of the same circular template and an RNA‐containing substrate for the RCD. RCA is initiated at the first complex to produce RCD elements that go on to cleave the substrate in the second complex. This cleavage event triggers the production of more input complexes for RCA. This reaction circuit continues autonomously, resulting in exponential DNA amplification. We demonstrate the versatility of this approach for biosensing through the design of DFA systems capable of detecting a microRNA sequence and a bacterium, with sensitivity improvements of 3–6 orders of magnitude over conventional methods.

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 · 10.1002/anie.201700054

Cites

3 of 3 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

Show all 3 references

Cited by

See all 161

Metadata

Authors
Liu, M., Zhang, Q., Chang, D., Gu, J., Brennan, J. D., & Li, Y.
Venue
Angewandte Chemie International Edition
Publisher
Wiley
Published
2017-03-28
Volume
56
Issue
22
Pages
6142-6146
ISSN
  • 1433-7851 (ISSN-L)
  • 1521-3773
OpenAlex
W2601600255
Cited by
161
References
3
FWCI
7.38
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

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: A DNAzyme Feedback Amplification Strategy for Biosensing. https://app.cochat.ai/papers/10.1002/anie.201700054
The paper
Liu, M., Zhang, Q., Chang, D., Gu, J., Brennan, J. D., & Li, Y. (2017). A DNAzyme Feedback Amplification Strategy for Biosensing. Angewandte Chemie International Edition. https://doi.org/10.1002/anie.201700054

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.