Evidence map›Paper›PMID 30323298›Full record

ArticleNature communications2018

Single Particle Automated Raman Trapping Analysis.

Jelle Penders, Isaac J Pence, Conor C Horgan, Mads S Bergholt, Christopher S Wood, Adrian Najer, Ulrike Kauscher, Anika Nagelkerke, Molly M Stevens

Abstract read
In one paragraph

Article in Nature communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing 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

33 citing papers in PubMed.

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  20. Recent developments in biosensing methods for extracellular vesicle protein characterization.Wiley interdisciplinary reviews. Nanomedicine and nanobiotechnology · 2023
    Review
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.

Jelle PendersDepartment of Materials, Imperial College London, London, SW7 2AZ, UK.
Isaac J PenceDepartment of Materials, Imperial College London, London, SW7 2AZ, UK.
Conor C HorganDepartment of Materials, Imperial College London, London, SW7 2AZ, UK.
Mads S BergholtDepartment of Materials, Imperial College London, London, SW7 2AZ, UK.
Christopher S WoodDepartment of Materials, Imperial College London, London, SW7 2AZ, UK.ORCID http://orcid.org/0000-0001-8337-876X
Adrian NajerDepartment of Materials, Imperial College London, London, SW7 2AZ, UK.
Ulrike KauscherDepartment of Materials, Imperial College London, London, SW7 2AZ, UK.
Anika NagelkerkeDepartment of Materials, Imperial College London, London, SW7 2AZ, UK.
Molly M StevensDepartment of Materials, Imperial College London, London, SW7 2AZ, UK. m.stevens@imperial.ac.uk.ORCID http://orcid.org/0000-0002-7335-266X

Funding

Wellcome Trust 098411
6 · The paper itself

Abstract

Enabling concurrent, high throughput analysis of single nanoparticles would greatly increase the capacity to study size, composition and inter and intra particle population variance with applications in a wide range of fields from polymer science to drug delivery. Here, we present a comprehensive platform for Single Particle Automated Raman Trapping Analysis (SPARTA) able to integrally analyse nanoparticles ranging from synthetic polymer particles to liposomes without any modification. With the developed highly controlled automated trapping process, single nanoparticles are analysed with high throughput and sensitivity to resolve particle mixtures, obtain detailed compositional spectra of complex particles, track sequential functionalisations, derive particle sizes and monitor the dynamics of click reactions occurring on the nanoparticle surface. The SPARTA platform opens up a wide range of new avenues for nanoparticle research through label-free integral high-throughput single particle analysis, overcoming key limitations in sensitivity and specificity of existing bulk analysis methods.

Identifiers

PMID30323298
PMCPMC6189196

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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.