Evidence map›Paper›PMID 41168486›Full record

ArticleNature methods2025

High-resolution imaging mass cytometry to map subcellular structures.

Alina Bollhagen, James Whipman, Ricardo Coelho, Viola Heinzelmann-Schwarz, Francis Jacob, Bernd Bodenmiller

Abstract read
In one paragraph

Article in Nature methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Review
  2. Emerging technologies in the spatial proteomics landscape.Analytical and bioanalytical chemistry · 2026
    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

6 authors.

Alina Bollhagen *Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland.ORCID http://orcid.org/0000-0003-3592-8282
James Whipman *Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland.
Ricardo CoelhoOvarian Cancer Research, Department of Biomedicine, University Hospital Basel and University of Basel, Basel, Switzerland.ORCID http://orcid.org/0000-0002-9340-3612
Viola Heinzelmann-SchwarzOvarian Cancer Research, Department of Biomedicine, University Hospital Basel and University of Basel, Basel, Switzerland.
Francis JacobOvarian Cancer Research, Department of Biomedicine, University Hospital Basel and University of Basel, Basel, Switzerland.ORCID http://orcid.org/0000-0002-0446-1942
Bernd BodenmillerDepartment of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland. bernd.bodenmiller@uzh.ch.ORCID http://orcid.org/0000-0002-6325-7861

Funding

Co-registration of Cell Organization, Phenotype and Function in the Human Pancreas During Type 1 DiabetesR01DK131059 · NIDDK · UNIVERSITY OF FLORIDA · PI ATKINSON, MARK A. · 2021 to 2025
$2.5M
EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020) 866074NIDDK NIH HHS R01 DK131059Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Swiss National Science Foundation) 310030_205007U.S. Department of Health & Human Services | National Institutes of Health (NIH) 5R01DK131059-04
6 · The paper itself

Abstract

Imaging mass cytometry (IMC) is a powerful multiplexed imaging technology used to investigate cell phenotypes and spatial organization of tissue in health and disease. The spatial resolution of IMC is presently at 1 µm, enabling the resolution of single cells and large subcellular compartments but not submicrometer intracellular structures. Here we report a method to improve the resolution of IMC so that it approaches that of light microscopy. High-resolution IMC (HR-IMC) uses an oversampling approach coupled with point-spread function-based deconvolution to achieve a resolution below 350 nm. We demonstrate the performance of HR-IMC in resolving subcellular structures, such as nuclear foci and mitochondrial networks previously undetectable with IMC, and applied it to visualize chemotherapy-induced perturbation of patient-derived ovarian cancer cells. HR-IMC extends highly multiplex IMC analyses into the subcellular regime, enabling analysis of cell biological features and characteristics of disease.

Indexed as

Image CytometryCell Line, TumorCell NucleusFemaleHumansImage Processing, Computer-AssistedMitochondriaOvarian Neoplasms

Identifiers

PMID41168486
PMCPMC12695663

What OpenQuestion holds

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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.