Evidence mapPaperPMID 38544909Full record

ArticleLiver research (Beijing, China)2024

Targeting nuclear receptors for NASH/MASH: From bench to bedside.

Rohit A Sinha

Open access · goldAbstract read
In one paragraph

Article in Liver research (Beijing, China), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
5.0field-weighted citation impact, top 4% of its field
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

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Review
  5. Review
  6. Article
  7. Review
  8. 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

1 author at 1 institution in 1 country.

Rohit A SinhaDepartment of Endocrinology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India.
Sanjay Gandhi Post Graduate Institute of Medical Sciences · IN

Funding

DBT-Wellcome Trust India Alliance IA/I/16/2/502691Wellcome Trust
6 · The paper itself

Abstract

The onset of metabolic dysfunction-associated steatohepatitis (MASH) or non-alcoholic steatohepatitis (NASH) represents a tipping point leading to liver injury and subsequent hepatic complications in the natural progression of what is now termed metabolic dysfunction-associated steatotic liver diseases (MASLD), formerly known as non-alcoholic fatty liver disease (NAFLD). With no pharmacological treatment currently available for MASH/NASH, the race is on to develop drugs targeting multiple facets of hepatic metabolism, inflammation, and pro-fibrotic events, which are major drivers of MASH. Nuclear receptors (NRs) regulate genomic transcription upon binding to lipophilic ligands and govern multiple aspects of liver metabolism and inflammation. Ligands of NRs may include hormones, lipids, bile acids, and synthetic ligands, which upon binding to NRs regulate the transcriptional activities of target genes. NR ligands are presently the most promising drug candidates expected to receive approval from the United States Food and Drug Administration as a pharmacological treatment for MASH. This review aims to cover the current understanding of NRs, including nuclear hormone receptors, non-steroid hormone receptors, circadian NRs, and orphan NRs, which are currently undergoing clinical trials for MASH treatment, along with NRs that have shown promising results in preclinical studies.

Indexed as

DrugLiverMetabolic dysfunction-associated steatohepatitis (MASH)Metabolic dysfunction-associated steatotic liver disease (MASLD)Nuclear receptor (NR)Transcription factor

Identifiers

PMID38544909
PMCPMC7615772
OpenAlexW4392714133

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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.