Evidence map›Paper›PMID 34138261›Full record

ArticleNano-micro letters2021

Gold Nanostars-AIE Theranostic Nanodots with Enhanced Fluorescence and Photosensitization Towards Effective Image-Guided Photodynamic Therapy.

Mohammad Tavakkoli Yaraki, Min Wu, Eshu Middha, Wenbo Wu, Soroosh Daqiqeh Rezaei, Bin Liu, Yen Nee Tan

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nano-micro letters, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

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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

7 authors.

Mohammad Tavakkoli YarakiInstitute of Materials Research and Engineering, Agency for Science, Technology and Research (A*STAR), Singapore, 138634, Singapore.
Min Wu *Department of Chemical and Biomolecular Engineering, National University of Singapore, 4 Engineering Drive 4, Singapore, 117585, Singapore.
Eshu Middha *Department of Chemical and Biomolecular Engineering, National University of Singapore, 4 Engineering Drive 4, Singapore, 117585, Singapore.
Wenbo WuDepartment of Chemical and Biomolecular Engineering, National University of Singapore, 4 Engineering Drive 4, Singapore, 117585, Singapore.
Soroosh Daqiqeh RezaeiInstitute of Materials Research and Engineering, Agency for Science, Technology and Research (A*STAR), Singapore, 138634, Singapore.
Bin LiuDepartment of Chemical and Biomolecular Engineering, National University of Singapore, 4 Engineering Drive 4, Singapore, 117585, Singapore. cheliub@nus.edu.sg.
Yen Nee TanInstitute of Materials Research and Engineering, Agency for Science, Technology and Research (A*STAR), Singapore, 138634, Singapore. yennee.tan@newcastle.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dual-functional aggregation-induced photosensitizers (AIE-PSs) with singlet oxygen generation (SOG) ability and bright fluorescence in aggregated state have received much attention in image-guided photodynamic therapy (PDT). However, designing an AIE-PS with both high SOG and intense fluorescence via molecular design is still challenging. In this work, we report a new nanohybrid consisting of gold nanostar (AuNS) and AIE-PS dots with enhanced fluorescence and photosensitization for theranostic applications. The spectral overlap between the extinction of AuNS and fluorescence emission of AIE-PS dots (665 nm) is carefully selected using five different AuNSs with distinct localized surface plasmon (LSPR) peaks. Results show that all the AuNSs can enhance the

Indexed as

Aggregation-induced emissionFluorescence imagingPhotosensitizerPlasmon enhancementTheranostics

Identifiers

PMID34138261
PMCPMC8187487

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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.