Evidence map›Paper›PMID 31270509›Full record

ArticleNature protocols2019

Solidifying framework nucleic acids with silica.

Xinxin Jing, Fei Zhang, Muchen Pan, Xinpei Dai, Jiang Li, Lihua Wang, Xiaoguo Liu, Hao Yan, Chunhai Fan

Abstract read
PubMed Publisher
In one paragraph

Article in Nature protocols, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Programmable Functional Silicification of DNA Origami Nanostructures.Advanced materials (Deerfield Beach, Fla.) · 2026
    Article
  2. Article
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  5. Review
  6. Article
  7. Review
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  12. DNA Assembly-Based Stimuli-Responsive Systems.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2021
    Review
  13. Review
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

9 authors.

Xinxin Jing *Division of Physical Biology and Bioimaging Center, Shanghai Synchrotron Radiation Facility, CAS Key Laboratory of Interfacial Physics and Technology, Shanghai Institute of Applied Physics, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, China.ORCID http://orcid.org/0000-0001-5335-0387
Fei Zhang *Center for Molecular Design and Biomimetics, Biodesign Institute, Tempe, AZ, USA.
Muchen PanDivision of Physical Biology and Bioimaging Center, Shanghai Synchrotron Radiation Facility, CAS Key Laboratory of Interfacial Physics and Technology, Shanghai Institute of Applied Physics, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, China.ORCID http://orcid.org/0000-0002-7703-8061
Xinpei DaiDivision of Physical Biology and Bioimaging Center, Shanghai Synchrotron Radiation Facility, CAS Key Laboratory of Interfacial Physics and Technology, Shanghai Institute of Applied Physics, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, China.ORCID http://orcid.org/0000-0003-3707-3273
Jiang LiDivision of Physical Biology and Bioimaging Center, Shanghai Synchrotron Radiation Facility, CAS Key Laboratory of Interfacial Physics and Technology, Shanghai Institute of Applied Physics, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, China.
Lihua WangDivision of Physical Biology and Bioimaging Center, Shanghai Synchrotron Radiation Facility, CAS Key Laboratory of Interfacial Physics and Technology, Shanghai Institute of Applied Physics, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, China.
Xiaoguo LiuSchool of Chemistry and Chemical Engineering, and Institute of Molecular Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China. liuxiaoguo@sjtu.edu.cn.ORCID http://orcid.org/0000-0002-7834-399X
Hao YanCenter for Molecular Design and Biomimetics, Biodesign Institute, Tempe, AZ, USA.
Chunhai FanDivision of Physical Biology and Bioimaging Center, Shanghai Synchrotron Radiation Facility, CAS Key Laboratory of Interfacial Physics and Technology, Shanghai Institute of Applied Physics, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, China.ORCID http://orcid.org/0000-0002-7171-7338

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Soft matter can serve as a template to guide the growth of inorganic components with well-controlled structural features. However, the limited design space of conventional organic and biomolecular templates restricts the complexity and accuracy of templated growth. In past decades, the blossoming of structural DNA nanotechnology has provided us with a large reservoir of delicate-framework nucleic acids with design precision down to a single base. Here, we describe a DNA origami silicification (DOS) approach for generating complex silica composite nanomaterials. By utilizing modified silica sol-gel chemistry, pre-hydrolyzed silica precursor clusters can be uniformly coated onto the surface of DNA frameworks; thus, user-defined DNA-silica hybrid materials with ~3-nm precision can be achieved. More importantly, this method is applicable to various 1D, 2D and 3D DNA frameworks that range from 10 to >1,000 nm. Compared to pure DNA scaffolds, a tenfold increase in the Young's modulus (E modulus) of these composites was observed, owing to their soft inner core and solid silica shell. We further demonstrate the use of solidified DNA frameworks to create 3D metal plasmonic devices. This protocol provides a platform for synthesizing inorganic materials with unprecedented complexity and tailored structural properties. The whole protocol takes ~10 d to complete.

Indexed as

Elastic ModulusNanotechnologyNucleic AcidsPhase TransitionSilicon DioxideNucleic AcidsSilicon Dioxide

Identifiers

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Registered trials

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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.