Evidence map›Paper›PMID 34902150›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2022

Enhancing Metabolite Coverage for Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging Through Multiple On-Tissue Chemical Derivatizations.

Kelly C O'Neill, Maria Emilia Dueñas, Evan Larson, Trevor T Forsman, Young-Jin Lee

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
5.8field-weighted citation impact, top 3% 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

4 citing papers in PubMed, 10 citations in OpenAlex.

  1. Review
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  4. 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 at 1 institution in 1 country.

Kelly C O'NeillDepartment of Chemistry, Iowa State University, Ames, IA, USA.
Maria Emilia DueñasDepartment of Chemistry, Iowa State University, Ames, IA, USA.
Evan LarsonDepartment of Chemistry, Iowa State University, Ames, IA, USA.
Trevor T ForsmanDepartment of Chemistry, Iowa State University, Ames, IA, USA.
Young-Jin LeeDepartment of Chemistry, Iowa State University, Ames, IA, USA. yjlee@iastate.edu.
Iowa State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ability to study and visualize metabolites on a cellular and sub-cellular level is important for gaining insights into biological pathways and metabolism of multicellular organisms. Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) is a powerful analytical tool for metabolomics experiments due to its high sensitivity and small sampling size. The spatial resolution in MALDI-MSI is mainly limited by the number of molecules available in a small sampling size. When the sampling size is low enough to achieve cellular or subcellular spatial resolution, signal intensity is sacrificed making poorly ionized metabolites difficult to detect. To overcome this limitation, on-tissue chemical derivatization reactions have been used to enhance the desorption/ionization efficiency of selected classes of compounds by adding a functional group with a permanent positive charge or one that can be easily ionized. By utilizing several chemical derivatizations in parallel, metabolite coverage can be drastically improved. This chapter outlines methodology for sample preparation and data analysis for on-tissue chemical derivatization using various derivatization reagents.

Indexed as

MetabolomicsSpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationDiagnostic ImagingLasersSpecimen HandlingMass spectrometry imagingMatrix-assister laser desorption/ionizationMetabolite coverageMetabolomicsOn-tissue derivatization

Identifiers

PMID34902150
OpenAlexW4200032591

What OpenQuestion holds

Textmetadata
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.