ReviewJACS Au2025
A Perspective on Unintentional Fragments and Their Impact on the Dark Metabolome, Untargeted Profiling, Molecular Networking, Public Data, and Repository Scale Analysis.
Review in JACS Au, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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.
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.
Who cites it
11 citing papers in PubMed.
- From known chemical space to unannotated metabolites: a cluster-guided retention-time driven framework for biologically informed annotation.Metabolomics : Official journal of the Metabolomic Society · 2026Article
- When context matters: community and environmental context to elicit natural products.Essays in biochemistry · 2026Review
- Benchmarking MS/MS Featurization Strategies for Machine Learning-Driven Metabolite Structure Annotation.Journal of the American Society for Mass Spectrometry · 2026Article
- Agentic AI for Structural Elucidation and Discovery of Drug Metabolites from Mass Spectrometry Data.bioRxiv : the preprint server for biology · 2026Article
- IMFrag: A Tool to Recognize In-Source Fragmentation in Ion Mobility-Enabled Data-Independent Acquisition Workflows.Analytical chemistry · 2026Article
- Untargeted metabolomics suggests a trade-off between phenolamides and flavonoids in the pollen of Petunia hybrida with contrasting flower colours.BMC plant biology · 2026Article
- Listening to Cellular Whispers through Glycosphingolipids: A Comprehensive Review of Recent Advancements in Glycosphingolipid Analysis and Annotation.Analytical chemistry · 2026Review
- Cross-Disease Breathomics by PTR-TOF-MS: Multiclass Machine Learning and Network Remodeling Across Asthma, COPD, Cystic Fibrosis, and Lymphangioleiomyomatosis.International journal of molecular sciences · 2026Article
- Pan-Metabolomics Repository Mapping of the Carnitine Landscape.bioRxiv : the preprint server for biology · 2026Article
- MS/MS Mass Spectrometry Filtering Tree for Bile Acid Regio- and Stereoisomer Annotation.Analytical chemistry · 2026Article
- Learning molecular fingerprints of foods to decode dietary intake.Research square · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
In/postsource fragments (ISFs) arise during electrospray ionization or ion transfer in mass spectrometry when molecular bonds break, generating ions that can complicate data interpretation. Although ISFs have been recognized for decades, their contribution to untargeted metabolomicsparticularly in the context of the so-called "dark matter" (unannotated MS or MS/MS spectra) and the "dark metabolome" (unannotated molecules)remains unsettled. This ongoing debate reflects a central tension: while some caution against overinterpreting unidentified signals lacking biological evidence, others argue that dismissing them too quickly risks overlooking genuine molecular discoveries. These discussions also raise a deeper question: what exactly should be considered part of the metabolome? As metabolomics advances toward large-scale data mining and high-throughput computational analysis, resolving these conceptual and methodological ambiguities has become essential. In this perspective, we propose a refined definition of the "dark metabolome" and present a systematic overview of ISFs and related ion forms, including adducts and multimers. We examine their impact on metabolite annotation, experimental design, statistical analysis, computational workflows, and repository-scale data mining. Finally, we provide practical recommendationsincluding a set of dos and do nots for researchers and reviewersand discuss the broader implications of ISFs for how the field explores unknown molecular space. By embracing a more nuanced understanding of ISFs, metabolomics can achieve greater rigor, reduce misinterpretation, and unlock new opportunities for discovery.
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What OpenQuestion holds
Registered trials
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.