Evidence map›Paper›PMID 30274514›Full record

ArticleAnalytical chemistry2018

Next Generation Histology-Directed Imaging Mass Spectrometry Driven by Autofluorescence Microscopy.

Nathan Heath Patterson, Michael Tuck, Adam Lewis, Alexis Kaushansky, Jeremy L Norris, Raf Van de Plas, Richard M Caprioli

Abstract read
In one paragraph

Article in Analytical chemistry, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed
3.9field-weighted citation impact, top 5% 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

39 citing papers in PubMed, 66 citations in OpenAlex.

  1. Review
  2. Article
  3. Enhancing the Sensitivity of Mass Spectrometry Imaging through Spatial Signal Averaging.Journal of the American Society for Mass Spectrometry · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. A lipid atlas of the human kidney.Science advances · 2025
    Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Mass spectrometry in animal health laboratories: recent history, current applications, and future directions.Journal of veterinary diagnostic investigation : official publication of the American Association of Veterinary Laboratory Diagnosticians, Inc · 2024
    Review
  14. Review
  15. Article
  16. Prospective on Imaging Mass Spectrometry in Clinical Diagnostics.Molecular & cellular proteomics : MCP · 2023
    Review
  17. MALDI IMS-Derived Molecular Contour Maps: Augmenting Histology Whole-Slide Images.Journal of the American Society for Mass Spectrometry · 2023
    Article
  18. Article
  19. Emerging Computational Methods in Mass Spectrometry Imaging.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022
    Review
  20. 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

7 authors at 2 institutions in 2 countries.

Nathan Heath PattersonORCID 0000-0002-0064-1583
Michael Tuck
Adam LewisCenter for Infectious Disease Research , formerly Seattle Biomedical Research Institute, Seattle , Washington 98109 , United States.
Alexis KaushanskyCenter for Infectious Disease Research , formerly Seattle Biomedical Research Institute, Seattle , Washington 98109 , United States.ORCID 0000-0001-5721-258X
Jeremy L Norris
Raf Van de PlasDelft Center for Systems and Control (DCSC) , Delft University of Technology , 2628 CD , Delft , The Netherlands.ORCID 0000-0002-2232-7130
Richard M CaprioliORCID 0000-0001-5859-3310
Vanderbilt University · USCenter for Infectious Disease Research · US

Funding

Training (pp 214-245)P41GM103391 · NIGMS · VANDERBILT UNIVERSITY · PI REYZER, MICHELLE L · 2012 to 2020
$17.7M
Perturbations of host cell signaling by a complex hepatotropic pathogenR01GM101183 · NIGMS · SEATTLE CHILDREN'S HOSPITAL · PI KAUSHANSKY, ALEXIS · 2013 to 2021
$3.6M
NIGMS NIH HHS P41 GM103391NIGMS NIH HHS R01 GM101183
6 · The paper itself

Abstract

Histology-directed imaging mass spectrometry (IMS) is a spatially targeted IMS acquisition method informed by expert annotation that provides rapid molecular characterization of select tissue structures. The expert annotations are usually determined on digital whole slide images of histological stains where the staining preparation is incompatible with optimal IMS preparation, necessitating serial sections: one for annotation, one for IMS. Registration is then used to align staining annotations onto the IMS tissue section. Herein, we report a next-generation histology-directed platform implementing IMS-compatible autofluorescence (AF) microscopy taken prior to any staining or IMS. The platform enables two histology-directed workflows, one that improves the registration process between two separate tissue sections using automated, computational monomodal AF-to-AF microscopy image registration, and a registration-free approach that utilizes AF directly to identify ROIs and acquire IMS on the same section. The registration approach is fully automated and delivers state of the art accuracy in histology-directed workflows for transfer of annotations (∼3-10 μm based on 4 organs from 2 species) while the direct AF approach is registration-free, allowing targeting of the finest structures visible by AF microscopy. We demonstrate the platform in biologically relevant case studies of liver stage malaria and human kidney disease with spatially targeted acquisition of sparsely distributed (composing less than one tenth of 1% of the tissue section area) malaria infected mouse hepatocytes and glomeruli in the human kidney case study.

Indexed as

Optical ImagingAnimalsFemaleHumansKidney DiseasesMalariaMiceMice, Inbred BALB CMicroscopy, FluorescenceSpectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization

Identifiers

PMID30274514
PMCPMC6309458
OpenAlexW2895342445

What OpenQuestion holds

Textmetadata
LicenceTDM
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.