MétaCan
Menu
Back to cohort
Record W4410513389 · doi:10.1126/scisignal.adw1245

Technical recommendations for analyzing oxylipins by liquid chromatography–mass spectrometry

2025· review· en· W4410513389 on OpenAlexafffund
Nils Helge Schebb, Nadja Kampschulte, Gerhard Hagn, Kathrin Plitzko, Sven W. Meckelmann, Soumita Ghosh, Robin Joshi, Julia Kuligowski, Dajana Vuckovic, Marina Tonetti Botana, Ángel Sánchez‐Illana, Fereshteh Zandkarimi, Aditi Das, Jun Yang, Louis Schmidt, Antonio Checa, Helen M. Roche, Aaron M. Armando, Matthew L. Edin, Fred B. Lih, Juan J. Aristizabal‐Henao, Sayuri Miyamoto, Francesca Giuffrida, Arieh Moussaieff, Michael Rothe, Christine Hinz, Ujjalkumar Subhash Das, Katharina M. Rund, Ameer Y. Taha, R. Hofstetter, Markus Werner, Oliver Werz, Astrid S. Kahnt, Justine Bertrand‐Michel, Pauline Le Faouder, Robert Gurke, Dominique Thomas, Federico Torta, Ivana Milic, Irundika H.K. Dias, Corinne M. Spickett, Denise Biagini, Tommaso Lomonaco, Helena Idborg, Jun‐Yan Liu, Maria Fedorova, David A. Ford, Anne Barden, Trevor A. Mori, Paul D. Kennedy, Kirk M. Maxey, Julijana Ivanišević, Héctor Gallart‐Ayala, Cécile Gladine, Markus R. Wenk, Jean-Marie Galano, Thierry Durand, Ken D. Stark, Coral Barbas, Ulrike Garscha, Stacy G. Wendell, Uta Ceglarek, Nicolas Flamand, Julian L. Griffin, Robert Ahrends, Makoto Arita, Darryl C. Zeldin, Francisco J. Schöpfer, Oswald Quehenberger, Randall K. Julian, Anna Nicolaou, Ian A. Blair, Michael P. Murphy, Bruce D. Hammock, Bruce Α. Freeman, Gerhard Liebisch, Charles N. Serhan, Harald Köfeler, P.‐J. Jakobsson, Dieter Steinhilber, Michael H. Gelb, Michal Holčapek, Ruth Andrew, Martin Giera, Garret A. FitzGerald, Robert C. Murphy, John W. Newman, Edward A. Dennis, Kim Ekroos, Ginger L. Milne, Miguel A. Gijón, Hubert W. Vesper, Craig E. Wheelock, Valerie B. O’Donnell

Bibliographic record

VenueScience Signaling · 2025
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEicosanoids and Hypertension Pharmacology
Canadian institutionsInstitut universitaire de cardiologie et de pneumologie de QuébecUniversity of WaterlooConcordia University
FundersAgency for Toxic Substances and Disease RegistryNational Institute of Environmental Health SciencesNational Heart, Lung, and Blood InstituteInstituto de Salud Carlos IIIMedical Research CouncilNational Institutes of HealthNational Institute of Neurological Disorders and StrokeNational Institute of General Medical SciencesMinisterio de Ciencia e InnovaciónBundesministerium für Bildung und ForschungAgencia Estatal de InvestigaciónFundação de Amparo à Pesquisa do Estado de São PauloEuropean CommissionAlzheimer's AssociationCentro de Estudos Ambientais e Marinhos, Universidade de AveiroWellcome TrustDeutsche ForschungsgemeinschaftCenters for Disease Control and PreventionNatural Sciences and Engineering Research Council of CanadaU.S. Department of Agriculture
KeywordsLipidomicsMass spectrometryChromatographyChemistryLiquid chromatography–mass spectrometryOxylipinBiochemistry

Abstract

fetched live from OpenAlex

Several oxylipins are potent lipid mediators that regulate diverse aspects of health and disease and whose quantitative analysis by liquid chromatography-mass spectrometry (LC-MS) presents substantial technical challenges. As members of the lipidomics community, we developed technical recommendations to ensure best practices when quantifying oxylipins by LC-MS.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.009
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.002
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0040.002
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0180.041

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.367
Teacher spread0.337 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations34
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueScience SignalingSame topicEicosanoids and Hypertension PharmacologyFrench-language works237,207