Evidence map›Paper›PMID 31240357›Full record

ArticleAnalytical and bioanalytical chemistry2019

Systematic evaluation of repeatability of IR-MALDESI-MS and normalization strategies for correcting the analytical variation and improving image quality.

Anqi Tu, David C Muddiman

Abstract read
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In one paragraph

Article in Analytical and bioanalytical chemistry, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Quantitative mass spectrometry imaging (qMSI): A tutorial.Journal of mass spectrometry : JMS · 2024
    Article
  6. Quantitative mass spectrometry imaging: therapeutics & biomolecules.Chemical communications (Cambridge, England) · 2024
    Review
  7. Article
  8. Review
  9. Review
  10. Article
  11. Article
  12. Article
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  15. Article
  16. Review
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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

2 authors.

Anqi TuFTMS Laboratory for Human Health Research, Department of Chemistry, North Carolina State University, Raleigh, NC, 27695, USA.
David C MuddimanFTMS Laboratory for Human Health Research, Department of Chemistry, North Carolina State University, Raleigh, NC, 27695, USA. david_muddiman@ncsu.edu.

Funding

Development and Application of New Ionization Methods for Biological Mass SpectrometryR01GM087964 · NIGMS · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI MUDDIMAN, DAVID C. · 2010 to 2025
$4.7M
NIGMS NIH HHS R01 GM087964NIGMS NIH HHS R01GM087964
6 · The paper itself

Abstract

Mass spectrometry imaging is a powerful tool widely used in biological, clinical, and forensic research, but its often poor repeatability limits its application for quantitative and large-scale analysis. A systematic evaluation of infrared matrix-assisted laser desorption electrospray ionization mass spectrometry (IR-MALDESI-MS) repeatability in absolute ion abundances during short- and long-term experiments was carried out on liver slices from the same rat with minimal biological variability to be expected. Results of median %RSDs ranging from 14 to 45, pooled %RMADs ranging from 11 to 33, and Pearson correlation coefficients ranging from 0.83 to 1.00 demonstrated an acceptable repeatability of IR-MALDESI-MS. Normalization is commonly applied for the purpose of accounting for analytical variability of spectra generated from different runs so as to reveal real biological differences. Nine data normalization strategies were performed on the rat liver data sets to examine their effects on reducing analytical variation, and further on a hen ovary data set containing more morphological features for the investigation of their impact on ion images. Results demonstrated that the majority of normalization approaches benefit data quality to some extent, and local normalization methods significantly outperform their global counterparts, resulting in a reduction of median %RSD up to 22. Local median normalization was found to be promisingly robust for both homogeneous and heterogeneous samples.

Indexed as

AnimalsChickensFemaleRatsReproducibility of ResultsSpectrometry, Mass, Electrospray IonizationSpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationIR-MALDESIMass spectrometry imagingNormalizationRepeatability

Identifiers

PMID31240357
PMCPMC6706294

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Registered trials

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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.