Evidence map›Paper›PMID 39859410›Full record

ReviewInternational journal of molecular sciences2025

In Vivo and In Vitro Models of Hepatic Fibrosis for Pharmacodynamic Evaluation and Pathology Exploration.

Yanting Hu, Zhongrui Zhang, Akida Adiham, Hong Li, Jian Gu, Puyang Gong

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. 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

6 authors.

Yanting HuCollege of Pharmacy and Food, Southwest Minzu University, Chengdu 610093, China.
Zhongrui ZhangCollege of Pharmacy and Food, Southwest Minzu University, Chengdu 610093, China.
Akida AdihamCollege of Pharmacy and Food, Southwest Minzu University, Chengdu 610093, China.
Hong LiCollege of Pharmacy and Food, Southwest Minzu University, Chengdu 610093, China.
Jian GuCollege of Pharmacy and Food, Southwest Minzu University, Chengdu 610093, China.
Puyang GongCollege of Pharmacy and Food, Southwest Minzu University, Chengdu 610093, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hepatic fibrosis (HF) is an important pathological state in the progression of chronic liver disease to end-stage liver disease and is usually triggered by alcohol, nonalcoholic fatty liver, chronic hepatitis viruses, autoimmune hepatitis (AIH), or cholestatic liver disease. Research on novel therapies has become a hot topic due to the reversibility of HF. Research into the molecular mechanisms of the pathology of HF and potential drug screening relies on reliable and rational biological models, mainly including animals and cells. Hence, a number of modeling approaches have been attempted based on human dietary, pathological, and physiological factors in the development of HF. In this review, classical and novel methods of modeling HF in the last 10 years were collected from electronic databases, including Web of Science, PubMed, ScienceDirect, ResearchGate, Baidu Scholar, and CNKI. Animal models of HF are usually induced by chemical toxicants, special diets, pathogenic microorganisms, surgical operations, and gene editing. The advantages and limitations of hepatic stellate cells (HSCs), organoids, and 3D coculture-based HF modeling methods established in vitro were also proposed and summarized. This information provides a scientific basis for the discovery of the pathological mechanism and treatment of HF.

Indexed as

Liver CirrhosisModels, BiologicalAnimalsDisease Models, AnimalHepatic Stellate CellsHumansanimal modeldrug screeninghepatic fibrosishepatic stellate cells

Identifiers

PMID39859410
PMCPMC11766297

What OpenQuestion holds

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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.