Evidence map›Paper›PMID 34741237›Full record

ReviewCell biology and toxicology2022

Animal models of drug-induced pulmonary fibrosis: an overview of molecular mechanisms and characteristics.

Shuchan Li, Jianrong Shi, Huifang Tang

Abstract readReview
PubMed Publisher
In one paragraph

Review in Cell biology and toxicology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 1 pooled it
7.2field-weighted citation impact, top 2% 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

44 citing papers in PubMed, 1 synthesis or guideline pooled it, 66 citations in OpenAlex.

  1. Pooled it
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  14. Mechanisms and Therapeutic Potential of Myofibroblast Transformation in Pulmonary Fibrosis.Journal of respiratory biology and translational medicine · 2025
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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

3 authors at 2 institutions in 1 country.

Shuchan LiDepartment of Pharmacology, School of Basic Medical Sciences, Zhejiang University, Hangzhou, 310058, China.
Jianrong ShiDepartment of Clinical Laboratory, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, 310052, China.
Huifang TangDepartment of Pharmacology, School of Basic Medical Sciences, Zhejiang University, Hangzhou, 310058, China. tanghuifang@zju.edu.cn.
Zhejiang University · CNChildren's Hospital of Zhejiang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Idiopathic pulmonary fibrosis (IPF) is a progressive interstitial lung disease characterized by progressive loss of pulmonary function. Drug-induced interstitial lung disease has been reported as a severe adverse effect of some drugs, such as bleomycin, amiodarone, and methotrexate. Based on good characteristics, drug-induced pulmonary fibrosis (PF) animal model has played a key role in our understanding of the molecular mechanisms of PF pathogenesis and recapitulates the specific pathology in patients and helps develop therapeutic strategies. Here, we summarize the mechanisms and characteristics of given fibrotic drug-induced animal models for PFs. Together with the key publications describing these models, this brief but detailed overview would be helpful for the pharmacological research with animal models of PFs. Potential mechanisms underlying drug induced lung toxicity.

Indexed as

AmiodaroneIdiopathic Pulmonary FibrosisLung Diseases, InterstitialAnimalsBleomycinDisease Models, AnimalLungMethotrexateAmiodaroneBleomycinMethotrexateAmiodaroneAnimal modelBleomycinMethotrexatePulmonary fibrosis

Identifiers

PMID34741237
OpenAlexW3210478990

What OpenQuestion holds

Textmetadata
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.