Evidence map›Paper›PMID 36944690›Full record

ArticleScientific reports2023

Network-level analysis of ageing and its relationship with diseases and tissue regeneration in the mouse liver.

Manisri Porukala, P K Vinod

Open access · goldFull text read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
3.9field-weighted citation impact, top 6% 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, 18 citations in OpenAlex.

  1. Article
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  5. Cgref1 is a CREB-H-regulated hepatokine that promotes hepaticInternational journal of biological sciences · 2025
    Article
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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

2 authors at 1 institution in 1 country.

Manisri PorukalaCentre for Computational Natural Sciences and Bioinformatics, IIIT, Hyderabad, 500032, India.
P K VinodCentre for Computational Natural Sciences and Bioinformatics, IIIT, Hyderabad, 500032, India. vinod.pk@iiit.ac.in.
Indian Institute of Technology Hyderabad · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The liver plays a vital role in maintaining whole-body metabolic homeostasis, compound detoxification and has the unique ability to regenerate itself post-injury. Ageing leads to functional impairment of the liver and predisposes the liver to non-alcoholic fatty liver disease (NAFLD) and hepatocellular carcinoma (HCC). Mapping the molecular changes of the liver with ageing may help to understand the crosstalk of ageing with different liver diseases. A systems-level analysis of the ageing-induced liver changes and its crosstalk with liver-associated conditions is lacking. In the present study, we performed network-level analyses of the ageing liver using mouse transcriptomic data and a protein-protein interaction (PPI) network. A sample-wise analysis using network entropy measure was performed, which showed an increasing trend with ageing and helped to identify ageing genes based on local entropy changes. To gain further insights, we also integrated the differentially expressed genes (DEGs) between young and different age groups with the PPI network and identified core modules and nodes associated with ageing. Finally, we computed the network proximity of the ageing network with different networks of liver diseases and regeneration to quantify the effect of ageing. Our analysis revealed the complex interplay of immune, cancer signalling, and metabolic genes in the ageing liver. We found significant network proximities between ageing and NAFLD, HCC, liver damage conditions, and the early phase of liver regeneration with common nodes including NLRP12, TRP53, GSK3B, CTNNB1, MAT1 and FASN. Overall, our study maps the network-level changes of ageing and their interconnections with the physiology and pathology of the liver.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsNon-alcoholic Fatty Liver DiseaseAnimalsComputational BiologyGene Expression ProfilingGene Regulatory NetworksIntracellular Signaling Peptides and ProteinsMiceProtein Interaction MapsIntracellular Signaling Peptides and Proteins

Identifiers

PMID36944690
PMCPMC10030664
OpenAlexW4328129485

What Socratic holds

Textfull text, public
LicenceCC BY
measurements read3
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.