Evidence map›Paper›PMID 37284141›Full record

ArticleJHEP reports : innovation in hepatology2023

Characterisation of hepatic lipid signature distributed across the liver zonation using mass spectrometry imaging.

Patcharamon Seubnooch, Matteo Montani, Sofia Tsouka, Emmanuelle Claude, Umara Rafiqi, Aurel Perren, Jean-Francois Dufour, Mojgan Masoodi

Abstract read
In one paragraph

Article in JHEP reports : innovation in hepatology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. A novel subset of hepatocytes is simultaneously gluconeogenic andbioRxiv : the preprint server for biology · 2026
    Article
  6. Article
  7. Review
  8. Article
  9. Review
  10. Review
  11. Article
  12. Article
  13. Frontiers in nutrition · 2025
    Article
  14. Article
  15. Review
  16. Article
  17. Recent Analytical Methodologies in Lipid Analysis.International journal of molecular sciences · 2024
    Review
  18. Review
  19. 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.

Patcharamon SeubnoochInstitute of Clinical Chemistry, Inselspital, Bern University Hospital, Bern, Switzerland.
Matteo MontaniInstitute of Tissue Medicine and Pathology, University of Bern, Bern, Switzerland.
Sofia TsoukaInstitute of Clinical Chemistry, Inselspital, Bern University Hospital, Bern, Switzerland.
Emmanuelle ClaudeWaters Corporation, Wilmslow, UK.
Umara RafiqiInstitute of Tissue Medicine and Pathology, University of Bern, Bern, Switzerland.
Aurel PerrenInstitute of Tissue Medicine and Pathology, University of Bern, Bern, Switzerland.
Jean-Francois DufourDepartment of Visceral Surgery and Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Mojgan MasoodiInstitute of Clinical Chemistry, Inselspital, Bern University Hospital, Bern, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background & Aims: Lipid metabolism plays an important role in liver pathophysiology. The liver lobule asymmetrically distributes oxygen and nutrition, resulting in heterogeneous metabolic functions. Periportal and pericentral hepatocytes have different metabolic functions, which lead to generating liver zonation. We developed spatial metabolic imaging using desorption electrospray ionisation mass spectrometry to investigate lipid distribution across liver zonation with high reproducibility and accuracy. Methods: Fresh frozen livers from healthy mice with control diet were analysed using desorption electrospray ionisation mass spectrometry imaging. Imaging was performed at 50 μm × 50 μm pixel size. Regions of interest (ROIs) were manually created by co-registering with histological data to determine the spatial hepatic lipids across liver zonation. The ROIs were confirmed by double immunofluorescence. The mass list of specific ROIs was automatically created, and univariate and multivariate statistical analysis were performed to identify statistically significant lipids across liver zonation. Results: A wide range of lipid species was identified, including fatty acids, phospholipids, triacylglycerols, diacylglycerols, ceramides, and sphingolipids. We characterised hepatic lipid signatures in three different liver zones (periportal zone, midzone, and pericentral zone) and validated the reproducibility of our method for measuring a wide range of lipids. Fatty acids were predominantly detected in the periportal region, whereas phospholipids were distributed in both the periportal and pericentral zones. Interestingly, phosphatidylinositols, PI(36:2), PI(36:3), PI(36:4), PI(38:5), and PI(40:6) were located predominantly in the midzone (zone 2). Triacylglycerols and diacylglycerols were detected mainly in the pericentral region. Conclusions: The ability to accurately assess zone-specific hepatic lipid distribution in the liver could lead to a better understanding of lipid metabolism during the progression of liver disease. Impact and Implications: Zone-specific hepatic lipid metabolism could play an important role in lipid homoeostasis during disease progression. Herein, we defined the zone-specific references of hepatic lipid species in the three liver zones using molecular imaging. The

Indexed as

De novo triacylglycerol biosynthesisHepatic lipid distributionLipid metabolismLiverLiver zonationPathway analysis

Identifiers

PMID37284141
PMCPMC10240278

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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.