Evidence map›Paper›PMID 42237551›Full record

ReviewJournal of immunology research2026

Characteristic Changes in the Immune Landscape of Aging Liver: From Basic Mechanism to Clinical Transformation.

Tong Zhu, Aijing Xu, Wei Yin, Chengzhong Li

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Journal of immunology research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

4 authors.

Tong ZhuDepartment of Infectious Diseases, Changhai Hospital, Naval Medical University, Shanghai, 200433, China, smmu.edu.cn.ORCID https://orcid.org/0000-0002-5905-288X
Aijing XuDepartment of Infectious Diseases, Changhai Hospital, Naval Medical University, Shanghai, 200433, China, smmu.edu.cn.ORCID https://orcid.org/0000-0001-6638-6979
Wei YinDepartment of Infectious Diseases, Changhai Hospital, Naval Medical University, Shanghai, 200433, China, smmu.edu.cn.ORCID https://orcid.org/0000-0002-8457-8306
Chengzhong LiDepartment of Infectious Diseases, Changhai Hospital, Naval Medical University, Shanghai, 200433, China, smmu.edu.cn.ORCID https://orcid.org/0000-0002-1641-0640

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The global population is aging at an unprecedented rate, significantly increasing the burden of age-related liver diseases. While the mechanisms of liver aging remain incompletely understood, immune senescence within the hepatic microenvironment has emerged as a pivotal, yet underexplored, contributing factor. With advancing age, the liver undergoes profound remodeling of its immune landscape, encompassing dysfunction in both innate and adaptive immunity. This immunosenescence heightens susceptibility to infectious liver diseases, accelerates the progression of metabolic liver conditions, increases the risk of drug-induced liver injury (DILI), and promotes hepatocellular carcinoma (HCC) through compromised immune surveillance. In conclusion, aging-driven reorganization of the hepatic immune microenvironment elevates disease risk and undermines treatment efficacy. Targeting these age-related immune alterations therefore represents a promising therapeutic strategy for improving liver health in the elderly.

Indexed as

AgingLiverLiver DiseasesLiver NeoplasmsAdaptive ImmunityAnimalsCarcinoma, HepatocellularCellular MicroenvironmentHumansImmunity, InnateImmunologic SurveillanceImmunosenescenceage-related liver diseasesimmune microenvironmentimmunosenescenceinflammagingliver aging

Identifiers

PMID42237551
PMCPMC13581049

What OpenQuestion holds

Textmetadata
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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.