id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
bam-13952	Zen, Ling-Jun; Tian, Jun-Cai; Hu, Xu; Zhang, Ting-Ting; Dai, Qing-Qing; Wei, Ming-Li	Shared diagnostic genes and potential mechanisms between asthma and lung cancer revealed by integrated transcriptomic analysis and machine learning	2025	11	.pdf	application/pdf	5033	227	49	Layout 1 Analysis of asthma and lung cancer through integrated transcriptomic analysis and machine learning Eur J Transl Myol 35 (3) 13952, 2025 doi: 10.4081/ejtm.2025.13952 Lung cancer continues to be one of the most significant public health challenges, with a high global incidence and mortality rate. NSCLC encompasses a spectrum of histological subtypes, including adenocarcinoma, squamous cell carcinoma, and large-cell carcinoma, each with distinct pathological and molecular features.2 Known risk factors for lung cancer include smoking, exposure to environmental pollutants (e.g., asbestos, radon, air pollution), genetic mutations, and various molecular alterations that drive tumorigenesis.	cache/bam-13952.pdf	txt/bam-13952.txt