Evidence map›Paper›PMID 40241741›Full record

ReviewBiology methods & protocols2025

Optimized immunofluorescence for liver structure analysis: Enhancing 3D resolution and minimizing tissue autofluorescence.

Elena Zoppolato, Hasse Mol, Carlos Estrella-García, Nicole Vizcaino-Rodríguez, Diana Sanchez, Nicole Procel, Isabel Baroja, Leticia Sansores-Garcia, Iván M Moya

Abstract readReview
In one paragraph

Review in Biology methods & protocols, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

9 authors.

Elena ZoppolatoVIB Center for Cancer Biology and KU Leuven Department of Oncology, KU Leuven, Leuven, 3000, Belgium.
Hasse MolVIB Center for Cancer Biology and KU Leuven Department of Oncology, KU Leuven, Leuven, 3000, Belgium.
Carlos Estrella-GarcíaCancer Research Group, School of Biotechnology, Faculty of Engineering and Applied Sciences, Universidad de Las Américas, Quito, 170124, Ecuador.ORCID https://orcid.org/0009-0005-3533-6924
Nicole Vizcaino-RodríguezCancer Research Group, School of Biotechnology, Faculty of Engineering and Applied Sciences, Universidad de Las Américas, Quito, 170124, Ecuador.ORCID https://orcid.org/0009-0007-8412-3962
Diana SanchezCancer Research Group, School of Biotechnology, Faculty of Engineering and Applied Sciences, Universidad de Las Américas, Quito, 170124, Ecuador.
Nicole ProcelCancer Research Group, School of Biotechnology, Faculty of Engineering and Applied Sciences, Universidad de Las Américas, Quito, 170124, Ecuador.
Isabel BarojaCancer Research Group, School of Biotechnology, Faculty of Engineering and Applied Sciences, Universidad de Las Américas, Quito, 170124, Ecuador.
Leticia Sansores-GarciaVIB Center for Cancer Biology and KU Leuven Department of Oncology, KU Leuven, Leuven, 3000, Belgium.
Iván M MoyaCancer Research Group, School of Biotechnology, Faculty of Engineering and Applied Sciences, Universidad de Las Américas, Quito, 170124, Ecuador.ORCID https://orcid.org/0000-0003-1562-7634

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The study of liver biology and pathology through marker expression analysis and tissue structure visualization is constrained by the high autofluorescence caused by the presence of lipofuscins, vitamin A, and lipid droplets, which traditional staining methods do not effectively quench. This leads to low signal-to-noise ratios, obscured expression levels, and reduced structural resolution. We mitigated liver tissue autofluorescence using Sudan Black B staining, which effectively quenches background signals from lipid and lipofuscin accumulation. Additionally, these protocols typically use thin paraffin sections (5-7 µm), which limit the analysis of larger and more complex liver structures. Liver tissue is highly organized in three dimensions, with large hepatocytes (20-30 µm in diameter) arranged around sinusoids and bile canaliculi, which form intricate branching networks. Thin sections cannot capture this 3D organization, providing only a "snapshot" of the tissue at one plane. Here, we present an optimized immunofluorescence protocol using 100-200 µm vibratome-cut liver sections to enable a more comprehensive 3D-like analysis of liver architecture. Finally, our protocol includes antigen retrieval steps tailored to each antibody, maximizing epitope accessibility and signal clarity. Together, these improvements provide a robust method for detailed liver studies with enhanced specificity and structural resolution in immunofluorescent staining. This protocol is particularly suited for researchers focused on liver regeneration, cancer, chronic disease pathology, and structural analysis. However, other researchers interested in exploring complex tissue structures in other autofluorescent tissues, such as the kidney, brain, pancreas, spleen, and adipose tissue, will also find this method beneficial.

Indexed as

3D structuresLiverTissue autofluorescence

Identifiers

PMID40241741
PMCPMC11999924

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LicenceCC BY
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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.