Evidence map›Paper›PMID 36968093›Full record

ReviewiScience2023

Advances in self-assembled Au-DNA nanomachines.

Qianying Zhang, Shengshi Xu, Jingyi Zheng, Jian-Rong Zhang, Jun-Jie Zhu

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in iScience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

5 authors.

Qianying ZhangState Key Laboratory of Analytical Chemistry for Life Science, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, China.
Shengshi XuState Key Laboratory of Analytical Chemistry for Life Science, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, China.
Jingyi ZhengState Key Laboratory of Analytical Chemistry for Life Science, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, China.
Jian-Rong ZhangState Key Laboratory of Analytical Chemistry for Life Science, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, China.
Jun-Jie ZhuState Key Laboratory of Analytical Chemistry for Life Science, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Au-DNA self-assembled nanomachines can perform intelligent tasks such as sensing biomarkers and delivery of drug molecules through rational customization and programming. By virtue of their efficient signal amplification and flexible scalability, Au-DNA nanomachines have developed into one of the most promising nanodevices. In this review, we summarize the latest progress in Au-DNA self-assembled nanomachines for biosensing applications. First, the functional modules for building Au-DNA nanomachines are introduced. Subsequently, we summarize the biosensing applications of Au-DNA nanomachines with electrochemical or fluorescent signals as the output, respectively. Finally, we discuss the challenges and potential opportunities for Au-DNA nanomachines in biomedical applications.

Indexed as

Materials chemistryMaterials scienceMaterials synthesis

Identifiers

PMID36968093
PMCPMC10031160

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.