Evidence map›Paper›PMID 42420601›Full record

ArticleInternational journal of obesity (2005)2026

Characterization of white adipocyte heterogeneity using data-driven microscopy.

Jieyu Zhang, Christian Simonsson, Ayesha Fawad, Wathik Alsalim, Allan Vaag, Mathis Neuhaus, Karin G Stenkula

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Article in International journal of obesity (2005), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Jieyu Zhang *Department of Experimental Medical Science, Lund University, Lund, Sweden.
Christian Simonsson *Department of Experimental Medical Science, Lund University, Lund, Sweden.ORCID http://orcid.org/0000-0003-3805-1674
Ayesha FawadDepartment of Endocrinology, Skåne University Hospital, Malmö, Sweden.
Wathik AlsalimDepartment of Endocrinology, Skåne University Hospital, Malmö, Sweden.
Allan VaagDepartment of Endocrinology, Skåne University Hospital, Malmö, Sweden.
Mathis NeuhausDepartment of Experimental Medical Science, Lund University, Lund, Sweden.ORCID http://orcid.org/0000-0003-1091-4757
Karin G StenkulaDepartment of Experimental Medical Science, Lund University, Lund, Sweden. karin.stenkula@med.lu.se.ORCID http://orcid.org/0000-0002-0739-1150

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRecent advancements in single-cell transcriptomic analyses have greatly expanded our understanding of cellular diversity in adipose tissue, indicating transcriptionally distinct subpopulations of adipocytes. Here we sought to rigorously test such heterogeneity at the protein level.

methodsA data-driven imaging platform was tailored to assess cellular protein levels based on immunofluorescence staining in primary adipocytes isolated from human adipose tissue biopsies (abdominal and gluteal adipose tissue from n = four subjects). Isolated adipocytes were co-labeled for GLUT4 and the previously proposed adipocyte subtype markers PLIN1 and DDR2 to assess their relative expression levels.

resultsThe platform enabled a two-step gating, shape-based filtering approach, which allowed accurate identification of mature adipocytes of a large cell-size range. The software was able to accurately detect hundreds of adipocytes spanning a broad size range. When comparing cells isolated from a single adipose tissue depot and subject, we found that a large proportion of cells had relatively high levels of both DDR2 and PLIN1. No notable differences in GLUT4 levels were observed within this group of cells.

conclusionsThe described approach, based on population-wide imaging, could serve as a robust tool to further validate cellular characteristics at a single-cell level. The fact that we detected distinct protein levels of the proposed adipocyte markers may reflect the presence of mature adipocyte subtypes.

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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.