Evidence map›Paper›PMID 41115890›Full record

ArticleScientific data2025

Development of a High-Resolution Tandem Mass Spectral Library for Pyrrolizidine Alkaloids (PASL).

Leonie V Straub, Patrick P J Mulder, Han Zuilhof, Federico Padilla Gonzalez, Laura Righetti

Abstract read
In one paragraph

Article in Scientific data, 2025. 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. 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

5 authors.

Leonie V StraubWageningen Food Safety Research, Wageningen University & Research, Wageningen, The Netherlands.
Patrick P J MulderWageningen Food Safety Research, Wageningen University & Research, Wageningen, The Netherlands.
Han ZuilhofLaboratory of Organic Chemistry, Wageningen University & Research, Wageningen, The Netherlands.ORCID 0000-0001-5773-8506
Federico Padilla GonzalezWageningen Food Safety Research, Wageningen University & Research, Wageningen, The Netherlands. federico.padillagonzalez@wur.nl.
Laura RighettiWageningen Food Safety Research, Wageningen University & Research, Wageningen, The Netherlands. laura.righetti@wur.nl.ORCID 0000-0003-4238-0665

Funding

European Commission (EC) WOT-02-001-064
6 · The paper itself

Abstract

This Data Descriptor reports the submission of a High-Resolution Orbitrap Mass Spectral Library of Pyrrolizidine Alkaloids (PASL) to public repositories. The library contains 165 tandem mass spectra (MS/MS) from 84 pyrrolizidine alkaloid (PA) standards, along with 18 additional PAs manually annotated in crude plant extracts. This collection comprises most commercially available PAs and a unique selection of annotated (in crude extracts) and synthesized compounds. The PASL serves as a valuable resource for identifying PAs in complex mixtures without analytical standards and facilitates the annotation of novel PAs through molecular networking approach. To ensure high quality, the library was validated by dereplicating its spectra against the GNPS libraries and applying it to the annotation of two PA-producing plant species. The spectra of the PASL can be accessed through GNPS ( https://gnps.ucsd.edu/ProteoSAFe/gnpslibrary.jsp?library=PYRROLIZIDINE-ALKALOID-SPECTRAL-LIBRARY ), with accession numbers ranging from CCMSLIB00014205782 to CCMSLIB00014205946 . The PASL in .mgf format can be downloaded from GNPS under: https://external.gnps2.org/gnpslibrary . The PASL enables rapid and straightforward annotation of both known and novel PAs, accelerating research in food safety and related fields.

Indexed as

Pyrrolizidine AlkaloidsDatasets as TopicTandem Mass SpectrometryPyrrolizidine Alkaloids

Identifiers

PMID41115890
PMCPMC12537953

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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.