Evidence mapPaperPMID 41789674Full record

ReviewInternational journal of molecular medicine2026

Treatment of pulmonary fibrosis: From disease mechanisms to future novel therapies (Review).

Sen Lu, Yunfei Liu, Xiaohua Li, Qipeng Yao

Abstract readReview
In one paragraph

Review in International journal of molecular medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Journal of thoracic disease · 2026
    Article
  2. The effect and mechanism of total alkaloids ofFrontiers in pharmacology · 2026
    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

4 authors.

Sen Lu *Department of Critical Care Medicine, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan 610072, P.R. China.
Yunfei Liu *Department of Anesthesiology, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan 610072, P.R. China.
Xiaohua LiDepartment of Thoracic Surgery, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Sichuan Clinical Research Center for Kidney Diseases, Chengdu, Sichuan 610072, P.R. China.
Qipeng YaoDepartment of Chinese Medicine, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan 610072, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pulmonary fibrosis (PF) is a progressive and fatal interstitial lung disease characterized by irreversible lung scarring and frequently associated with lung cancer. Currently, there remains a lack of effective therapies capable of significantly improving long‑term outcomes or reversing the disease course. Although antifibrotic drugs are widely used and have enhanced the mechanistic understanding of PF, their efficacy is limited. This review systematically explores the core pathobiological processes and epigenetic regulatory networks involved in PF pathogenesis. Simultaneously, a critical review of the most promising emerging therapeutic strategies in recent years, including stem cell therapy, novel targeted agents, nucleic acid delivery technologies and epigenetic interventions, is provided. An in‑depth analysis of the transformative role of artificial intelligence (AI) in integrating multi‑omics data, predicting disease trajectories and optimizing personalized treatment plans is also presented. However, significant challenges hinder the clinical translation of these novel approaches. While AI‑based models offer valuable insights, they are constrained by the complex heterogeneity of PF. Epigenetic therapies, despite their promise, face obstacles related to drug development, delivery efficiency and long‑term clinical impact. Moving forward, the fundamental shift from palliative management to a disease‑modifying paradigm for PF will not rely on a single technological breakthrough. Instead, it necessitates deep interdisciplinary integration. This involves the systematic convergence of the potential of regenerative medicine, the precision of gene editing, the molecular intervention of targeted therapy and the dynamic decision‑making capabilities driven by AI. The goal is to construct a next‑generation, individualized treatment framework capable of adapting to disease heterogeneity and evolving with the patient's condition. Despite the considerable challenges, this multimodal integrated strategy is paving a viable new path toward ultimately conquering pulmonary fibrosis.

Indexed as

Pulmonary FibrosisAnimalsArtificial IntelligenceEpigenesis, GeneticHumansStem Cell Transplantationartificial intelligenceepigenetic therapynucleic acid deliverypulmonary fibrosisstem cell therapytargeting agent

Identifiers

PMID41789674
PMCPMC12959616

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.