Evidence map›Paper›PMID 36701560›Full record

ArticleAnalytical chemistry2023

New Model for Quantifying the Nanoparticle Concentration Using SERS Supported by Multimodal Mass Spectrometry.

Aristea Anna Leventi, Kharmen Billimoria, Dorota Bartczak, Stacey Laing, Heidi Goenaga-Infante, Karen Faulds, Duncan Graham

Abstract read
In one paragraph

Article in Analytical chemistry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 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.

Aristea Anna LeventiDepartment of Pure and Applied Chemistry, Technology and Innovation Centre, University of Strathclyde, 99 George Street, GlasgowG1 1RD, U.K.ORCID 0000-0002-1931-6684
Kharmen BillimoriaNational Measurement Laboratory, LGC, Teddington, MiddlesexTW11 0LY, U.K.
Dorota BartczakNational Measurement Laboratory, LGC, Teddington, MiddlesexTW11 0LY, U.K.ORCID 0000-0002-5440-2924
Stacey LaingDepartment of Pure and Applied Chemistry, Technology and Innovation Centre, University of Strathclyde, 99 George Street, GlasgowG1 1RD, U.K.
Heidi Goenaga-InfanteNational Measurement Laboratory, LGC, Teddington, MiddlesexTW11 0LY, U.K.
Karen FauldsDepartment of Pure and Applied Chemistry, Technology and Innovation Centre, University of Strathclyde, 99 George Street, GlasgowG1 1RD, U.K.ORCID 0000-0002-5567-7399
Duncan GrahamDepartment of Pure and Applied Chemistry, Technology and Innovation Centre, University of Strathclyde, 99 George Street, GlasgowG1 1RD, U.K.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Surface-enhanced Raman scattering (SERS) is widely explored for the elucidation of underlying mechanisms behind biological processes. However, the capability of absolute quantitation of the number of nanoparticles from the SERS response remains a challenge. Here, we show for the first time the development of a new 2D quantitation model to allow calibration of the SERS response against the absolute concentration of SERS nanotags, as characterized by single particle inductively coupled plasma mass spectrometry (spICP-MS). A novel printing approach was adopted to prepare gelatin-based calibration standards containing the SERS nanotags, which consisted of gold nanoparticles and the Raman reporter 1,2-bis(4-pyridyl)ethylene. spICP-MS was used to characterize the Au mass concentration and particle number concentration of the SERS nanotags. Results from laser ablation inductively coupled plasma time-of-flight mass spectrometry imaging at a spatial resolution of 5 μm demonstrated a homogeneous distribution of the nanotags (between-line relative standard deviation < 14%) and a linear response of

Identifiers

PMID36701560
PMCPMC9909670

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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.