Evidence map›Paper›PMID 37714972›Full record

ArticleAnalytical and bioanalytical chemistry2023

Characterizing lignins from various sources and treatment processes after optimized sample preparation techniques and analysis via ESI-HRMS and custom mass defect software tools.

Dane R Letourneau, Bryan P Marzullo, Anastasia Alexandridou, Mark P Barrow, Peter B O'Connor, Dietrich A Volmer

Open access · hybridAbstract read
In one paragraph

Article in Analytical and bioanalytical chemistry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 47% of its field
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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
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

6 authors at 2 institutions in 2 countries.

Dane R LetourneauDepartment of Chemistry, Humboldt University Berlin, 12489, Berlin, Germany.ORCID http://orcid.org/0000-0002-6720-3561
Bryan P MarzulloDepartment of Chemistry, University of Warwick, Coventry, CV4 7AL, UK.ORCID http://orcid.org/0000-0002-1874-6906
Anastasia AlexandridouDepartment of Chemistry, Humboldt University Berlin, 12489, Berlin, Germany.ORCID http://orcid.org/0000-0003-3633-4021
Mark P BarrowDepartment of Chemistry, University of Warwick, Coventry, CV4 7AL, UK.ORCID http://orcid.org/0000-0002-6474-5357
Peter B O'ConnorDepartment of Chemistry, University of Warwick, Coventry, CV4 7AL, UK.ORCID http://orcid.org/0000-0002-6588-6274
Dietrich A VolmerDepartment of Chemistry, Humboldt University Berlin, 12489, Berlin, Germany. Dietrich.Volmer@hu-berlin.de.ORCID http://orcid.org/0000-0003-2820-1480
Humboldt-Universität zu Berlin · DEUniversity of Warwick · GB

Funding

Berlin University Alliance 501_LinkLabDeutsche Forschungsgemeinschaft VO 1355/4-3
6 · The paper itself

Abstract

Sample preparation of complex, natural mixtures such as lignin prior to mass spectrometry analysis, however minimal, is a critical step in ensuring accurate and interference-free results. Modern shotgun-MS techniques, where samples are directly injected into a high-resolution mass spectrometer (HRMS) with no prior separation, usually still require basic sample pretreatment such as filtration and appropriate solvents for full dissolution and compatibility with atmospheric pressure ionization interfaces. In this study, sample preparation protocols have been established for a unique sample set consisting of a wide variety of degraded lignin samples from numerous sources and treatment processes. The samples were analyzed via electrospray (ESI)-HRMS in negative and positive ionization modes. The resulting information-rich HRMS datasets were then transformed into the mass defect space with custom R scripts as well as the open-source Constellation software as an effective way to visualize changes between the samples due to the sample preparation and ionization conditions as well as a starting point for comprehensive characterization of these varied sample sets. Optimized conditions for the four investigated lignins are proposed for ESI-HRMS analysis for the first time, giving an excellent starting point for future studies seeking to better characterize and understand these complex mixtures.

Indexed as

Analytical methodsCustom softwareLigninMass defectMass spectrometrySample preparation

Identifiers

PMID37714972
PMCPMC10598097
OpenAlexW4386760534

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.