Evidence map›Paper›PMID 40109726›Full record

ReviewFrontiers in medicine2025

The hepatocellular model of fatty liver disease: from current imaging diagnostics to innovative proteomics technologies.

Renee Hernandez, Natasha S Garcia-Rodriguez, Marco A Arriaga, Ricardo Perez, Auwal A Bala, Ana C Leandro, Vince P Diego, Marcio Almeida, Jason G Parsons, Eron G Manusov and 1 more

Abstract readReview
In one paragraph

Review in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Review
  5. 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

11 authors.

Renee HernandezDivision of Human Genetics, School of Medicine, The University of Texas Rio Grande Valley, Brownsville, TX, United States.
Natasha S Garcia-RodriguezDivision of Human Genetics, School of Medicine, The University of Texas Rio Grande Valley, Brownsville, TX, United States.
Marco A ArriagaDivision of Human Genetics, School of Medicine, The University of Texas Rio Grande Valley, Brownsville, TX, United States.
Ricardo PerezDivision of Human Genetics, School of Medicine, The University of Texas Rio Grande Valley, Brownsville, TX, United States.
Auwal A BalaDivision of Human Genetics, School of Medicine, The University of Texas Rio Grande Valley, Brownsville, TX, United States.
Ana C LeandroDivision of Human Genetics, School of Medicine, The University of Texas Rio Grande Valley, Brownsville, TX, United States.
Vince P DiegoDivision of Human Genetics, School of Medicine, The University of Texas Rio Grande Valley, Brownsville, TX, United States.
Marcio AlmeidaDivision of Human Genetics, School of Medicine, The University of Texas Rio Grande Valley, Brownsville, TX, United States.
Jason G ParsonsDivision of Human Genetics, School of Medicine, The University of Texas Rio Grande Valley, Brownsville, TX, United States.
Eron G ManusovDivision of Human Genetics, School of Medicine, The University of Texas Rio Grande Valley, Brownsville, TX, United States.
Jacob A GalanDivision of Human Genetics, School of Medicine, The University of Texas Rio Grande Valley, Brownsville, TX, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) is a prevalent chronic liver condition characterized by lipid accumulation and inflammation, often progressing to severe liver damage. We aim to review the pathophysiology, diagnostics, and clinical care of MASLD, and review highlights of advances in proteomic technologies. Recent advances in proteomics technologies have improved the identification of novel biomarkers and therapeutic targets, offering insight into the molecular mechanisms underlying MASLD progression. We focus on the application of mass spectrometry-based proteomics including single cell proteomics, proteogenomics, extracellular vesicle (EV-omics), and exposomics for biomarker discovery, emphasizing the potential of blood-based panels for noninvasive diagnosis and personalized medicine. Future research directions are presented to develop targeted therapies and improve clinical outcomes for MASLD patients.

Indexed as

exposomicsMASHMASLDproteogenomicsproteomicssingle-cell

Identifiers

PMID40109726
PMCPMC11919916

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.