Evidence map›Paper›PMID 42134320›Full record

ArticleCell reports methods2026

An optimized method to visualize lipid droplets in mouse brain tissue.

Alicia Rey, Francesco Petrelli, Diana Panfilova, Sofia Madsen, Noéline Héritier, Marlen Knobloch

Abstract read
In one paragraph

Article in Cell reports 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

6 authors.

Alicia ReyDepartment of Biomedical Sciences, Faculty of Biology and Medicine, University of Lausanne, 1005 Lausanne, Switzerland.
Francesco PetrelliDepartment of Biomedical Sciences, Faculty of Biology and Medicine, University of Lausanne, 1005 Lausanne, Switzerland.
Diana PanfilovaDepartment of Biomedical Sciences, Faculty of Biology and Medicine, University of Lausanne, 1005 Lausanne, Switzerland.
Sofia MadsenDepartment of Biomedical Sciences, Faculty of Biology and Medicine, University of Lausanne, 1005 Lausanne, Switzerland.
Noéline HéritierDepartment of Biomedical Sciences, Faculty of Biology and Medicine, University of Lausanne, 1005 Lausanne, Switzerland.
Marlen KnoblochDepartment of Biomedical Sciences, Faculty of Biology and Medicine, University of Lausanne, 1005 Lausanne, Switzerland. Electronic address: marlen.knobloch@unil.ch.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lipid droplets (LDs) are lipid-storage organelles that have gained interest in neurodegenerative diseases, yet their physiological role in the brain is not fully understood. Classical LD detection using lipophilic dyes like BODIPY 493/503 (BD493) or antibodies against LD coat proteins typically reveals few LDs in healthy brain tissue. In contrast, our recently developed endogenous LD-reporter mouse showed numerous LDs in the developing and adult brain without staining. To understand this discrepancy, we examined how tissue preparation and detergent influence LD detection. We found that BD493 performs poorly in brain tissue, whereas other lipophilic dyes allow visualization of many LDs. Antibody-based detection is sensitive to tissue pretreatment but can reveal similar LD numbers as the LD-reporter mouse. We here present an optimized protocol, demonstrating that LDs are abundant in healthy young and aged brains, with larger LDs in aged mice. However, LD detection in aged brains requires caution due to strong LD-like autofluorescence.

Indexed as

BrainLipid DropletsAgingAnimalsFluorescent DyesMiceMice, Inbred C57BLFluorescent DyesagingautofluorescenceBD493/503brainCP: cell biologyCP: imaginglipid dropletslipophilic dyesneuroscienceperilipinstaining

Identifiers

PMID42134320
PMCPMC13282654

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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.