Integrating cellular experiments, single-cell sequencing, and machine learning to identify endoplasmic reticulum stress biomarkers in idiopathic pulmonary fibrosis
This study identifies ERS-related biomarkers in IPF, highlighting SPP1 and M2 macrophages. The resulting diagnostic and prognostic models offer strong predictive capabilities, unveiling new therapeutic avenues.
Authors
- Qiunan Zuo
- Yan Yang (ORCID: https://orcid.org/0000-0003-1421-8003)
- Xianxia Chen
- Yi Liao (ORCID: https://orcid.org/0000-0003-4826-0314)
- Shujin Guo (ORCID: https://orcid.org/0000-0002-5540-1560)
- Xiaying Peng
- Yang� Yang (ORCID: https://orcid.org/0000-0003-1222-1209)
- Lijuan Chen (ORCID: https://orcid.org/0000-0002-8076-163X)
- Hongyan Li (ORCID: https://orcid.org/0000-0002-1158-5871)
- Guanghong Zhou (ORCID: https://orcid.org/0000-0002-8960-2141)
- Jun Zou (ORCID: https://orcid.org/0000-0002-4781-2538)
Institutions
- University of Electronic Science and Technology of China (CN)
Publication Details
- Journal
- Annals of Medicine
- Published
- 2024-09-28
- DOI
- https://doi.org/10.1080/07853890.2024.2409352
- Citations
- 8
- Primary Topic
- Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
- Type
- article
- Field-Weighted Citation Impact
- 3.35