Evidence map›Paper›PMID 40195958›Full record

ArticleJournal of inflammation research2025

The Role of Cuproptosis in Hyperoxia-Induced Lung Injury and Its Potential for Treatment.

Kaihua Yu, Yunfei Gu, Ying Yao, Jianchun Li, Suheng Chen, Hong Guo, Yulan Li, Jian Liu

Abstract read
In one paragraph

Article in Journal of inflammation research, 2025. 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. Review
  2. 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

8 authors.

Kaihua Yu *The First School of Clinical Medicine, Lanzhou University, Lanzhou, Gansu, People's Republic of China.
Yunfei Gu *Anesthesiology Department, Gansu Provincial Maternity and Child-Care Hospital (Gansu Provincial Center Hospital), Lanzhou, Gansu, People's Republic of China.
Ying YaoThe First School of Clinical Medicine, Lanzhou University, Lanzhou, Gansu, People's Republic of China.
Jianchun LiDepartment of Intensive Care Unit, Suzhou Science and Technology City Hospital, Nanjing, Jiangsu, People's Republic of China.
Suheng ChenThe First School of Clinical Medicine, Lanzhou University, Lanzhou, Gansu, People's Republic of China.
Hong GuoDepartment of Anesthesiology, Inner Mongolia Hospital of Peking University Cancer Hospital, Hohhot, Inner Mongolia, People's Republic of China.
Yulan LiDepartment of Anesthesiology, First Hospital of Lanzhou University, Lanzhou, Gansu, People's Republic of China.
Jian LiuThe First School of Clinical Medicine, Lanzhou University, Lanzhou, Gansu, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Oxygen supplementation is essential for patients with a multitude of diseases but can cause severe hyperoxia-induced lung injury (HLI), necessitating the identification of therapeutic targets to improve clinical outcomes. Cuproptosis, a novel copper-dependent form of cell death characterized by proteotoxic stress resulting from lipoylated protein aggregation and loss of iron-sulfur cluster proteins, is distinct from other forms of cell death. However, the role of cuproptosis in HLI remains unclear. Methods: We established an HLI model in MLE-12 cells and C57BL/6 mice to investigate the involvement of cuproptosis in hyperoxia-induced toxicity. Results: We observed a time-dependent increase in the cuproptosis-related gene Conclusion: Our study identifies the involvement of cuproptosis in HLI, providing new insights into the pathogenesis of hyperoxic lung injury and potential therapeutic strategies.

Indexed as

coppercuproptosisFDX1hyperoxiahyperoxia-induced lung injurylung injury

Identifiers

PMID40195958
PMCPMC11975008

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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.