Evidence map›Paper›PMID 42395638›Full record

ReviewLiver research (Beijing, China)2026

From bench to bedside: Molecular mechanisms, diagnostic tools, and therapeutic strategies in liver fibrosis.

Zhen Yang, Weizhao Tong, Kanglong Zhang, Guoxin Hu

Abstract readReview
In one paragraph

Review in Liver research (Beijing, China), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Zhen YangShantou University Medical College, Shantou, Guangdong, China.
Weizhao TongDepartment of Infectious Diseases, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China.
Kanglong ZhangDepartment of Infectious Diseases, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China.
Guoxin HuDepartment of Infectious Diseases, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Liver fibrosis is a key pathological process in the progression of chronic liver disease toward cirrhosis and liver failure. The development of liver fibrosis is closely related to a variety of etiologies, including alcoholic hepatitis, metabolic dysfunction-associated steatotic liver disease (MASLD), viral hepatitis, and drug-induced liver injury. Although advances in antiviral therapies for hepatitis B have contributed to a decline in its incidence, other etiologies such as MASLD and alcoholic hepatitis are becoming the main drivers for liver fibrosis. Currently, the management of liver fibrosis primarily focuses on controlling the underlying causes of liver fibrosis, including antiviral therapy and the cessation of alcohol or drug exposure. However, effective therapeutic options for advanced fibrosis remain limited, resulting in severe complications such as hepatic encephalopathy and portal hypertension, which markedly increase patient mortality and socioeconomic burden. Therefore, early diagnosis and timely intervention for liver fibrosis are essential to prevent disease progression. With the ongoing advancement of modern molecular biology technologies, our understanding of the pathogenesis and pathophysiology of liver fibrosis continues to deepen. In this review, we summarize the molecular mechanisms, diagnostic approaches, current treatments, and potential therapeutic targets for liver fibrosis.

Indexed as

Antifibrotic therapyExtracellular matrix (ECM)Hepatic stellate cells (HSCs)Liver fibrosisNoninvasive diagnosisOxidative stress

Identifiers

PMID42395638
PMCPMC13324216

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.