Zobrazeno 1 - 10
of 644
pro vyhledávání: '"coal workers pneumoconiosis"'
Autor:
Mohanakrishnan Deivasigamani, Manikandan Nagesh, Balamurugan Shanthalingam, Chandrasekar Chokalingam
Publikováno v:
The Journal of Association of Chest Physicians, Vol 12, Iss 3, Pp 124-127 (2024)
Progressive massive fibrosis (PMF) is a severe form and late-stage chronic pneumoconiosis defined by the clustering of silicotic nodules fused with connective tissue in silicosis and coal macules surrounded by fibrous tissue in coal workers’ pneumo
Externí odkaz:
https://doaj.org/article/1c6068a0a07c4a5fb22b80795376fb1c
Autor:
Xiaolu LIU, Baoping LI, Fuhai SHEN, Zhiping SUN, Yongmei ZHAO, Bowen HOU, Lini GAO, Qianqian LI, Xinyu LI, Chaoyi MA
Publikováno v:
环境与职业医学, Vol 41, Iss 6, Pp 625-631 (2024)
BackgroundPneumoconiosis is a widespread occupational disease in China at present. As a type of lung diseases, its pathological damage is mainly irreversible fibrotic changes in the lungs. Several studies have shown that the occurrence and developmen
Externí odkaz:
https://doaj.org/article/51b88bbfc2014ecd89cde79c4e81dd10
Publikováno v:
环境与职业医学, Vol 41, Iss 6, Pp 687-693 (2024)
BackgroundCoal workers' pneumoconiosis (CWP) is a serious occupational lung disease and one of the prescript occupational diseases in China. Epithelial-mesenchymal transition (EMT) is involved in the diffuse fibrosis of lung tissue of pneumoconiosis
Externí odkaz:
https://doaj.org/article/e6263e5290c147ac85b5f474e275f81b
Publikováno v:
The Clinical Respiratory Journal, Vol 17, Iss 7, Pp 684-693 (2023)
Abstract Purpose The purpose of this study is to propose an efficient coal workers' pneumoconiosis (CWP) clinical prediction system and put it into clinical use for clinical diagnosis of pneumoconiosis. Methods Patients with CWP and dust‐exposed wo
Externí odkaz:
https://doaj.org/article/f264545d404a49c6b1394a6c6efc5b87
Publikováno v:
Pharmacogenomics and Personalized Medicine, Vol Volume 16, Pp 537-549 (2023)
Zhifei Hou,1,2 Xinran Zhang,3 Yong Gao,4 Jing Geng,2 Yu Jiang,5 Huaping Dai,1,2 Chen Wang1,2 1Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, People’s Republic of China; 2Department of Pulmonary and Critical Care Medicin
Externí odkaz:
https://doaj.org/article/795026f0e2024c32bce813d86aff64b0
Autor:
Bing Li, Jianhua Wang, Yehong Zhao, Yuanjie Zou, Hangbing Cao, Haibo Jin, Xinrong Tao, Min Mu
Publikováno v:
Ecotoxicology and Environmental Safety, Vol 271, Iss , Pp 115972- (2024)
Coal worker's pneumoconiosis (CWP) is a common occupational disease that coal miners are highly susceptible due to long-term exposure to coal dust particles (CDP). CWP can induce the accumulation of immune cells surrounding the bronchioles and alveol
Externí odkaz:
https://doaj.org/article/3794068a88784f42b4604a6cf3eb0ff2
Autor:
Çiğdem Keleş, Emily Sarver
Publikováno v:
Data in Brief, Vol 51, Iss , Pp 109656- (2023)
This dataset comprises an image library of 282 respirable silica particles. The particles were identified in samples of respirable coal mine dust (RCMD) collected in numerous US underground mines, and samples of lab-generated respirable dust that wer
Externí odkaz:
https://doaj.org/article/499ca2a5581147d6b9af9c74b1198ab4
Publikováno v:
Minerals, Vol 13, Iss 12, p 1526 (2023)
In recent years, the Mineral Liberation Analyser (MLA) has played a pivotal role in analysing respirable and inhalable ambient air samples collected on filters from both underground coal and metalliferous mines. Leveraging backscattered electron (BSE
Externí odkaz:
https://doaj.org/article/3f8f63e122ee4df0a7552f27e2cfe0c4
Akademický článek
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Publikováno v:
BMC Pulmonary Medicine, Vol 22, Iss 1, Pp 1-14 (2022)
Abstract Purpose This paper aims to develop a successful deep learning model with data augmentation technique to discover the clinical uniqueness of chest X-ray imaging features of coal workers' pneumoconiosis (CWP). Patients and methods We enrolled
Externí odkaz:
https://doaj.org/article/4efbb6c466664313a26372dac0f101ab