Evidence map›Paper›PMID 28553485›Full record

ArticleChemical science2017

Visualization of drug delivery processes using AIEgens.

Youyong Yuan, Bin Liu

Open access · diamondAbstract read
In one paragraph

Article in Chemical science, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
6.7field-weighted citation impact, top 2% 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

15 citing papers in PubMed, 88 citations in OpenAlex.

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  15. Theranostics based on AIEgens.Theranostics · 2018
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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

2 authors at 2 institutions in 1 country.

Youyong YuanDepartment of Chemical and Biomolecular Engineering , National University of Singapore , 4 Engineering Drive 4 , Singapore 117585 . Email: cheliub@nus.edu.sg.
Bin LiuDepartment of Chemical and Biomolecular Engineering , National University of Singapore , 4 Engineering Drive 4 , Singapore 117585 . Email: cheliub@nus.edu.sg.ORCID 0000-0002-0956-2777
Agency for Science, Technology and Research · SGNational University of Singapore · SG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drug delivery systems (DDSs) have been extensively studied as carriers to deliver small molecule chemo-drugs to tumors for cancer therapy. The therapeutic efficiency of chemo-drugs is crucially dependent on the effective drug concentrations in tumors and cancer cells. Novel DDSs that can simultaneously unveil drug distribution, drug release/activation behaviors and offer early evaluation of their therapeutic responses are highly desirable. Traditional fluorescent dye-labeled DDSs may suffer from notorious aggregation-caused quenching (ACQ) with limited sensitivity for bioimaging; in addition, the intrinsic fluorescence of these dyes requires careful selection of energy acceptor or quencher moieties for a light-up probe design, which complicates the development of self-reporting DDSs, especially the ones for reporting multiple processes. The recently emerged fluorogens with aggregation-induced emission characteristics (AIEgens) offer a straightforward solution to tackle this challenge. Thanks to the unique properties of AIEgens, new theranostic DDSs have been developed for simultaneous drug delivery and bioimaging with high signal to background ratio and multiple signal reporting capabilities. In this mini-review, we summarize the recent development of theranostic DDSs based on AIEgens for monitoring the drug distribution, drug activation and prediction of the therapeutic responses. Through illustration of their design principles and application examples, we hope to stimulate the interest in the design of more advanced theranostic DDSs for biomedical research.

Identifiers

PMID28553485
PMCPMC5431685
OpenAlexW2573250016

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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.