Evidence map›Paper›PMID 35519189›Full record

ArticleRSC advances2020

Early detection of metabolic changes in drug-induced steatosis using metabolomics approaches.

Helena Y Yong, Gerald Larrouy-Maumus, Mire Zloh, Rosemary Smyth, Rayan Ataya, Christopher M Benton, Michael R Munday

Open access · goldAbstract read
In one paragraph

Article in RSC advances, 2020. 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
0.4field-weighted citation impact, top 33% 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

5 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Article
  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

7 authors at 3 institutions in 4 countries.

Helena Y YongDepartment of Pharmaceutical and Biological Chemistry, University of London UK h.yong@ucl.ac.uk.ORCID https://orcid.org/0000-0001-5310-4565
Gerald Larrouy-MaumusMRC Centre for Molecular Bacteriology and Infection, Department of Life Science, Faculty of Natural Sciences, Imperial College London UK.ORCID https://orcid.org/0000-0001-6614-8698
Mire ZlohDepartment of Pharmaceutical and Biological Chemistry, University of London UK h.yong@ucl.ac.uk.
Rosemary SmythDepartment of Pharmaceutical and Biological Chemistry, University of London UK h.yong@ucl.ac.uk.
Rayan AtayaDepartment of Pharmaceutical and Biological Chemistry, University of London UK h.yong@ucl.ac.uk.
Christopher M BentonAgilent Technologies Ltd Cheshire UK.
Michael R MundayDepartment of Pharmaceutical and Biological Chemistry, University of London UK h.yong@ucl.ac.uk.
University of London · GBAgilent Technologies (United States) · USImperial College London · GB

Funding

Medical Research Council MR/P028225/1
6 · The paper itself

Abstract

Steatosis is the accumulation of triglycerides in hepatic cells wherein fats exceed 5% of the entire liver weight. Although steatotic liver damage is reversible due to the liver's regenerative capability, protracted damage often and typically leads to irreversible conditions such as cirrhosis and hepatocellular carcinoma (HCC). Therefore, early steatotic detection is critical for preventing progression to advanced liver diseases. This also becomes particularly important given the higher prevalence of drug usage, as drugs are a frequent cause of liver damage. Currently, the recommendation to diagnose steatosis is using liver enzymes and performing a liver biopsy. Liver biopsy remains the gold standard method of detection, but the procedure is invasive and an unreliable diagnostic tool. Non-invasive, specific and sensitive diagnostic solutions such as biomarkers are therefore needed for the early detection of steatosis. Our aim is to identify changes in urinary metabolites in tetracycline-induced hepatic steatotic rats at different stages of the diseases using metabolomic-based techniques. Sprague Dawley male rats are treated by intraperitoneal injection (I.P.) with either 62.5 mg kg

Identifiers

PMID35519189
PMCPMC9057704
OpenAlexW3103387343

What OpenQuestion 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 OpenQuestion graph.