Evidence map›Paper›PMID 41912798›Full record

ArticleNature methods2026

Differentiation of sphingomyelin and cholesterol by hyperspectral mid-infrared detection of single-bond vibrational modes in the fingerprint region.

Francesca Gasparin, Alexander Prebeck, Alice Soldà, Nasire Uluç, Sarah Glasl, Constantin Berger, Miguel A Pleitez, Vasilis Ntziachristos

Abstract read
In one paragraph

Article in Nature methods, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

8 authors.

Francesca GasparinChair of Biological Imaging, Central Institute for Translational Cancer Research (TranslaTUM), School of Medicine and Health & School of Computation, Information and Technology, Technical University of Munich, Munich, Germany.ORCID http://orcid.org/0000-0001-6354-939X
Alexander PrebeckChair of Biological Imaging, Central Institute for Translational Cancer Research (TranslaTUM), School of Medicine and Health & School of Computation, Information and Technology, Technical University of Munich, Munich, Germany.ORCID http://orcid.org/0009-0005-3584-6174
Alice SoldàChair of Biological Imaging, Central Institute for Translational Cancer Research (TranslaTUM), School of Medicine and Health & School of Computation, Information and Technology, Technical University of Munich, Munich, Germany.
Nasire UluçChair of Biological Imaging, Central Institute for Translational Cancer Research (TranslaTUM), School of Medicine and Health & School of Computation, Information and Technology, Technical University of Munich, Munich, Germany.
Sarah GlaslChair of Biological Imaging, Central Institute for Translational Cancer Research (TranslaTUM), School of Medicine and Health & School of Computation, Information and Technology, Technical University of Munich, Munich, Germany.
Constantin BergerChair of Biological Imaging, Central Institute for Translational Cancer Research (TranslaTUM), School of Medicine and Health & School of Computation, Information and Technology, Technical University of Munich, Munich, Germany.ORCID http://orcid.org/0000-0001-5528-4870
Miguel A PleitezChair of Biological Imaging, Central Institute for Translational Cancer Research (TranslaTUM), School of Medicine and Health & School of Computation, Information and Technology, Technical University of Munich, Munich, Germany.ORCID http://orcid.org/0000-0002-7379-4409
Vasilis NtziachristosChair of Biological Imaging, Central Institute for Translational Cancer Research (TranslaTUM), School of Medicine and Health & School of Computation, Information and Technology, Technical University of Munich, Munich, Germany. bioimaging.translatum@tum.de.ORCID http://orcid.org/0000-0002-9988-0233

Funding

Deutsche Forschungsgemeinschaft (German Research Foundation) CRC 1123 (Z1)Deutsche Forschungsgemeinschaft (German Research Foundation) FOR 5298 (iMAGO, subproject TP3, GZ: PL825/3-1)Deutsche Forschungsgemeinschaft (German Research Foundation) Gottfried Wilhelm Leibniz Prize 2013; NT 3/10-1.EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020) No 101058111 (GLUMON)EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020) No 694968 (PREMSOT)
6 · The paper itself

Abstract

Lipids play a central role in a multitude of biological functions associated with cancer, obesity, diabetes, cardiovascular and neurological pathologies. However, sensing and mapping of lipid classes in living cells remains challenging. Here we introduce a label-free approach to lipid imaging, which differentiates lipid species in living cells by hyperspectral mid-infrared detection of single-bond vibrational modes within the fingerprint region. Hyperspectral fingerprint optoacoustic microscopy is shown to resolve phosphatidylcholine, sphingomyelin or cholesterol in test samples and in synthetic giant unilamellar vesicles used as models of cell membranes. Then, mapping of total cholesterol and sphingomyelin content and accumulation dynamics are demonstrated in living cells. Hyperspectral fingerprint optoacoustic microscopy demonstrates sensitivity not only in discerning lipids with substantially different chemical structures, such as cholesterol and phospholipids, but also lipids that are chemically similar, such as sphingomyelins and glycerophospholipids.

Indexed as

CholesterolSphingomyelinsAnimalsHumansSpectrophotometry, InfraredUnilamellar LiposomesVibrationCholesterolSphingomyelinsUnilamellar Liposomes

Identifiers

PMID41912798
PMCPMC13076221

What Socratic 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 Socratic graph.