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DOI 10.7717/peerj.13632

Медицинская библиотека · PeerJ · 2022

Inflammation and fibrosis in the coal dust-exposed lung described by confocal Raman spectroscopy.

Wang Wenyang, Mu Min, Zou Yuanjie, Li Bing, Cao Hangbing, Hu Dong, Tao Xinrong

СтатьяПоддержка исследования: вне правительства СШАПеревод в очереди

Аннотация

BACKGROUND

Coal workers' pneumoconiosis (CWP) is an occupational disease that severely damages the life and health of miners. However, little is known about the molecular and cellular mechanisms changes associated with lung inflammation and fibrosis induced by coal dust. As a non-destructive technique for measuring biological tissue, confocal Raman spectroscopy provides accurate molecular fingerprints of label-free tissues and cells. Here, the progression of lung inflammation and fibrosis in a murine model of CWP was evaluated using confocal Raman spectroscopy.

METHODS

A mouse model of CWP was constructed and biochemical analysis in lungs exposed to coal dust after 1 month (CWP-1M) and 3 months (CWP-3M) vs control tissues (NS) were used by confocal Raman spectroscopy. H&E, immunohistochemical and collagen staining were used to evaluate the histopathology alterations in the lung tissues.

RESULTS

The CWP murine model was successfully constructed, and the mouse lung tissues showed progression of inflammation and fibrosis, accompanied by changes in NF-κB, p53, Bax, and Ki67. Meanwhile, significant differences in Raman bands were observed among the different groups, particularly changes at 1,248, 1,448, 1,572, and 746 cm-1. These changes were consistent with collagen, Ki67, and Bax levels in the CWP and NS groups.

CONCLUSION

Confocal Raman spectroscopy represented a novel approach to the identification of the biochemical changes in CWP lungs and provides potential biomarkers of inflammation and fibrosis.

Для цитирования: Wang Wenyang, Mu Min, Zou Yuanjie, Li Bing, Cao Hangbing, Hu Dong, Tao Xinrong. Inflammation and fibrosis in the coal dust-exposed lung described by confocal Raman spectroscopy.. PeerJ. 2022. DOI: 10.7717/peerj.13632.

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