Evidence map›Paper›PMID 32679693›Full record

ArticleMolecules (Basel, Switzerland)2020

A Mass Spectrometry-Based Approach for Characterization of Red, Blue, and Purple Natural Dyes.

Katarzyna Lech, Emilia Fornal

Abstract read
In one paragraph

Article in Molecules (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

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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

13 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

2 authors.

Katarzyna LechFaculty of Chemistry, Warsaw University of Technology, Noakowskiego 3, 00-664 Warsaw, Poland.ORCID 0000-0003-4476-2261
Emilia FornalDepartment of Pathophysiology, Medical University of Lublin, Jaczewskiego 8b, 20-090 Lublin, Poland.ORCID 0000-0002-0503-0706

Funding

Ministerstwo Nauki i Szkolnictwa Wyższego 0008/NPRH3/H11/82/2014Wydzial Chemiczny, Politechniki Warszawskiej statutory funds
6 · The paper itself

Abstract

Effective analytical approaches for the identification of natural dyes in historical textiles are mainly based on high-performance liquid chromatography coupled with spectrophotometric detection and tandem mass spectrometric detection with electrospray ionization (HPLC-UV-Vis-ESI MS/MS). Due to the wide variety of dyes, the developed method should include an adequate number of reference color compounds, but not all of them are commercially available. Thus, the present study was focused on extending of the universal analytical HPLC-UV-Vis-ESI MS/MS approach to commercially unavailable markers of red, purple, and blue dyes. In the present study, HPLC-UV-Vis-ESI MS/MS was used to characterize the colorants in ten natural dyes (American cochineal, brazilwood, indigo, kermes, lac dye, logwood, madder, orchil, Polish cochineal, and sandalwood) and, hence, to extend the analytical method for the identification of natural dyes used in historical objects to new compounds. Dye markers were identified mostly on the basis of triple quadrupole MS/MS spectra. In consequence, the HPLC-UV-Vis-ESI MS/MS method with dynamic multiple reaction monitoring (dMRM) was extended to the next 49 commercially unavailable colorants (anthraquinones and flavonoids) in negative ion mode and to 11 (indigoids and orceins) in positive ion mode. These include protosappanin B, protosappanin E, erythrolaccin, deoxyerythrolaccin, nordamnacanthal, lucidin, santalin A, santalin B, santarubin A, and many others. Moreover, high-resolution QToF MS data led to the establishment of the complex fragmentation pathways of α-, β-, and γ- aminoorceins, hydroxyorceins, and aminoorceinimines extracted from wool dyed with

Indexed as

ColorMass SpectrometryChromatography, High Pressure LiquidColoring AgentsSpectrometry, Mass, Electrospray IonizationTandem Mass SpectrometryWoodColoring Agentsbrazilwoodnatural dyesorchilsandalwoodtandem mass spectrometrytextile

Identifiers

PMID32679693
PMCPMC7397139

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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.