Evidence map›Paper›PMID 35658974›Full record

ReviewJournal of nanobiotechnology2022

Interfacing DNA nanotechnology and biomimetic photonic complexes: advances and prospects in energy and biomedicine.

Xu Zhou, Su Lin, Hao Yan

Open access · goldAbstract readReview
In one paragraph

Review in Journal of nanobiotechnology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.9field-weighted citation impact, top 14% of its field
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

8 citing papers in PubMed, 23 citations in OpenAlex.

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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

3 authors at 1 institution in 1 country.

Xu ZhouCenter for Molecular Design and Biomimetics at the Biodesign Institute, Arizona State University, Tempe, AZ, 85287, USA.
Su LinCenter for Molecular Design and Biomimetics at the Biodesign Institute, Arizona State University, Tempe, AZ, 85287, USA.
Hao YanCenter for Molecular Design and Biomimetics at the Biodesign Institute, Arizona State University, Tempe, AZ, 85287, USA. hao.yan@asu.edu.
Arizona State University · US

Funding

Department of Energy DE-SC0016353
6 · The paper itself

Abstract

Self-assembled photonic systems with well-organized spatial arrangement and engineered optical properties can be used as efficient energy materials and as effective biomedical agents. The lessons learned from natural light-harvesting antennas have inspired the design and synthesis of a series of biomimetic photonic complexes, including those containing strongly coupled dye aggregates with dense molecular packing and unique spectroscopic features. These photoactive components provide excellent features that could be coupled to multiple applications including light-harvesting, energy transfer, biosensing, bioimaging, and cancer therapy. Meanwhile, nanoscale DNA assemblies have been employed as programmable and addressable templates to guide the formation of DNA-directed multi-pigment complexes, which can be used to enhance the complexity and precision of artificial photonic systems and show the potential for energy and biomedical applications. This review focuses on the interface of DNA nanotechnology and biomimetic photonic systems. We summarized the recent progress in the design, synthesis, and applications of bioinspired photonic systems, highlighted the advantages of the utilization of DNA nanostructures, and discussed the challenges and opportunities they provide.

Indexed as

BiomimeticsNanostructuresDNANanotechnologyOptics and PhotonicsDNABioimagingBiosensingCancer therapyDNA nanotechnologyDye aggregatesEnergy transfer

Identifiers

PMID35658974
PMCPMC9164479
OpenAlexW4281686132

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.