Evidence map›Paper›PMID 28223805›Full record

ReviewInternational journal of nanomedicine2017

Harnessing supramolecular peptide nanotechnology in biomedical applications.

Kiat Hwa Chan, Wei Hao Lee, Shuangmu Zhuo, Ming Ni

Open access · goldAbstract readReview
In one paragraph

Review in International journal of nanomedicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
3.2field-weighted citation impact, top 8% 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

18 citing papers in PubMed, 48 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

4 authors at 3 institutions in 3 countries.

Kiat Hwa ChanDivision of Science, Yale-NUS College, Singapore.
Wei Hao LeeDepartment of Chemistry, Krieger School of Arts & Sciences, Johns Hopkins University, Baltimore, MD, USA.
Shuangmu ZhuoFujian Provincial Key Laboratory for Photonics Technology, Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Normal University, Fuzhou, People's Republic of China.
Ming NiFujian Provincial Key Laboratory for Photonics Technology, Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Normal University, Fuzhou, People's Republic of China.
Fujian Normal University · CNJohns Hopkins University · USYale-NUS College · SG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The harnessing of peptides in biomedical applications is a recent hot topic. This arises mainly from the general biocompatibility of peptides, as well as from the ease of tunability of peptide structure to engineer desired properties. The ease of progression from laboratory testing to clinical trials is evident from the plethora of examples available. In this review, we compare and contrast how three distinct self-assembled peptide nanostructures possess different functions. We have 1) nanofibrils in biomaterials that can interact with cells, 2) nanoparticles that can traverse the bloodstream to deliver its payload and also be bioimaged, and 3) nanotubes that can serve as cross-membrane conduits and as a template for nanowire formation. Through this review, we aim to illustrate how various peptides, in their various self-assembled nanostructures, possess great promise in a wide range of biomedical applications and what more can be expected.

Indexed as

Biomedical TechnologyNanomedicineBiocompatible MaterialsHumansNanostructuresNanotechnologyPeptide FragmentsBiocompatible MaterialsPeptide Fragmentsnanotechnologypeptidesself-assembly

Identifiers

PMID28223805
PMCPMC5310635
OpenAlexW2586189357

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.