Evidence map›Paper›PMID 39291650›Full record

ArticleJournal of the American Society for Mass Spectrometry2024

An Automated Analysis of Homocoupling Defects Using MALDI-MS and Open-Source Computer Software.

Maria Bochenek, Michał Aleksander Ciach, Sander Smeets, Omar Beckers, Jochen Vanderspikken, Błażej Miasojedow, Barbara Domżał, Dirk Valkenborg, Wouter Maes, Anna Gambin

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Article in Journal of the American Society for Mass Spectrometry, 2024. 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
–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

2 citing papers in PubMed.

  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

10 authors.

Maria BochenekFaculty of Mathematics, Informatics and Mechanics, University of Warsaw, Banacha 2, Warsaw 02-097, Poland.
Michał Aleksander CiachFaculty of Mathematics, Informatics and Mechanics, University of Warsaw, Banacha 2, Warsaw 02-097, Poland.
Sander SmeetsInstitute for Materials Research (IMO), Hasselt University, Agoralaan, Diepenbeek 3590, Belgium.
Omar BeckersInstitute for Materials Research (IMO), Hasselt University, Agoralaan, Diepenbeek 3590, Belgium.
Jochen VanderspikkenInstitute for Materials Research (IMO), Hasselt University, Agoralaan, Diepenbeek 3590, Belgium.ORCID 0000-0001-7059-0155
Błażej MiasojedowFaculty of Mathematics, Informatics and Mechanics, University of Warsaw, Banacha 2, Warsaw 02-097, Poland.ORCID 0000-0002-3691-9372
Barbara DomżałFaculty of Mathematics, Informatics and Mechanics, University of Warsaw, Banacha 2, Warsaw 02-097, Poland.ORCID 0000-0001-6098-9138
Dirk ValkenborgData Science Institute, Hasselt University, Hasselt 3500, Belgium.
Wouter MaesInstitute for Materials Research (IMO), Hasselt University, Agoralaan, Diepenbeek 3590, Belgium.ORCID 0000-0001-7883-3393
Anna GambinFaculty of Mathematics, Informatics and Mechanics, University of Warsaw, Banacha 2, Warsaw 02-097, Poland.ORCID 0000-0003-3476-3017

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Conjugated organic polymers have substantial potential for multiple applications but their properties are strongly influenced by structural defects such as homocoupling of monomer units and unexpected end-groups. Detecting and/or quantifying these defects requires complex experimental techniques, which hinder the optimization of synthesis protocols and fundamental studies on the influence of structural defects. Mass spectrometry offers a simple way to detect these defects but a manual analysis of many complex spectra is tedious and provides only approximate results. In this work, we develop a computational methodology for analyzing complex mass spectra of organic copolymers. Our method annotates spectra similarly to a human expert and provides quantitative information about the proportions of signal assigned to each ion. Our method is based on the open-source Masserstein algorithm, which we modify to handle large libraries of reference spectra required for annotating complex mass spectra of polymers. We develop a statistical methodology to analyze the quantitative annotations and compare the statistical distributions of structural defects in polymer chains between samples. We apply this methodology to analyze commercial and lab-made samples of a benchmark polymer and show that the samples differ both in the amount and in the types of structural defects.

Identifiers

PMID39291650
PMCPMC11450816

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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.