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- W2945101900 abstract "Inhalable environmental pollutants induce pulmonary malfunction, which alters thoracoabdominal respiratory conditions. Traditional methods of recording pressure differences or existing machine vision analyses for detecting respiratory abnormalities are not suitable for synchronous thoracic and abdominal respiratory detections. The present study provides a new method that combines a model of thoracoabdominal localization and distribution based on respiratory physiological characteristics and a machine vision analysis on respiratory conditions in mice exposed to aqueous aerosol containing cadmium with classical symptoms. Thoracoabdominal respirations of mice were similar to male humans based on thoracic and abdominal composite respiration and the primarily presented abdominal respiration. Under environmental inhalable cadmium doses (1, 3, 5 mM CdCl2 in solution respectively atomized to be 112.41, 337.23, 562.05 μg/g Cd/Aerosol), the pathological thoracoabdominal respirations of mice showed that abdominal respiration contributed more to respiratory compensation and presented greater adaptive adjustments and more obvious fluctuations during lung injury than thoracic respiration, which suggests that toxic aerosol from a high-risk work environment quickly induces discernible respiratory clinical manifestations in occupational groups, as a warning for health, and abdominal obesity is unfavorable for male respiratory compensation. The respiratory abnormality shown in machine vision analysis was verified in pulmonary structural changes and hypoxia stress. Conclusively, the present method may be used to test the effects of aerosols on respiratory state and provides new prospects for toxicity determinations and risk evaluations of aerosols in the respiratory system in vivo." @default.
- W2945101900 created "2019-05-29" @default.
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- W2945101900 date "2019-09-01" @default.
- W2945101900 modified "2023-09-24" @default.
- W2945101900 title "Thoracoabdominal respiratory disorder induced by cadmium aerosol and analyzed with a new machine vision model in vivo" @default.
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- W2945101900 doi "https://doi.org/10.1016/j.scitotenv.2019.05.146" @default.
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