Evidence map›Paper›PMID 32494726›Full record

ArticleScience advances2020

Exosome-templated nanoplasmonics for multiparametric molecular profiling.

Xingjie Wu, Haitao Zhao, Auginia Natalia, Carine Z J Lim, Nicholas R Y Ho, Chin-Ann J Ong, Melissa C C Teo, Jimmy B Y So, Huilin Shao

Abstract read
In one paragraph

Article in Science advances, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.

0numbers the graph read from it
0cells of the map it votes in
47citing 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

47 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

9 authors.

Xingjie WuInstitute for Health Innovation and Technology, National University of Singapore, Singapore 117599, Singapore.ORCID 0000-0002-8768-5633
Haitao ZhaoInstitute for Health Innovation and Technology, National University of Singapore, Singapore 117599, Singapore.ORCID 0000-0003-4462-0394
Auginia NataliaInstitute for Health Innovation and Technology, National University of Singapore, Singapore 117599, Singapore.ORCID 0000-0001-7487-6759
Carine Z J LimInstitute for Health Innovation and Technology, National University of Singapore, Singapore 117599, Singapore.
Nicholas R Y HoInstitute for Health Innovation and Technology, National University of Singapore, Singapore 117599, Singapore.ORCID 0000-0002-9031-5633
Chin-Ann J OngDivision of Surgical Oncology, National Cancer Centre, Singapore 169610, Singapore.ORCID 0000-0003-4573-7738
Melissa C C TeoDivision of Surgical Oncology, National Cancer Centre, Singapore 169610, Singapore.
Jimmy B Y SoDepartment of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore.
Huilin ShaoInstitute for Health Innovation and Technology, National University of Singapore, Singapore 117599, Singapore.ORCID 0000-0003-4513-1410

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Exosomes are nanoscale vesicles distinguished by characteristic biophysical and biomolecular features; current analytical approaches, however, remain univariate. Here, we develop a dedicated platform for multiparametric exosome analysis-through simultaneous biophysical and biomolecular evaluation of the same vesicles-directly in clinical biofluids. Termed templated plasmonics for exosomes, the technology leverages in situ growth of gold nanoshells on vesicles to achieve multiselectivity. For biophysical selectivity, the nanoshell formation is templated by and tuned to distinguish exosome dimensions. For biomolecular selectivity, the nanoshell plasmonics locally quenches fluorescent probes only if they are target-bound on the same vesicle. The technology thus achieves multiplexed analysis of diverse exosomal biomarkers (e.g., proteins and microRNAs) but remains unresponsive to nonvesicle biomarkers. When implemented on a microfluidic, smartphone-based sensor, the platform is rapid, sensitive, and wash-free. It not only distinguished biomarker organizational states in native clinical samples but also showed that the exosomal subpopulation could more accurately differentiate patient prognosis.

Identifiers

PMID32494726
PMCPMC7202874

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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.