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Abstract
To study a new method for establishing animal models of prenatal bronchopulmonary dysplasia (BPD), we used lung ultrasound score (LUS) to semi-quantitatively assess the severity of lung lesions in model rats. Lipopolysaccharide (LPS) was injected into the right lung of the fetus of the rat under ultrasound-guided, and the right lung of the neonates were scanning for LUS. Specimens were collected for pathological scoring and detection of pulmonary surfactant-associated glycoprotein (SP)-C and vascular endothelial growth factor (VEGF) expression quantity. The correlation between LUS and pathological scores was analyzed. (1) The animal models were consistent with the pathological manifestations of BPD. (2) It showed a strong positive correlation between LUS and pathological scores in animal models (r = 0.84, P < 0.005), and the expression quantity of SP-C and VEGF in lung tissue were decreased (both P < 0.05). Animal models established by ultrasound-guided puncture of the lung of rats and injection of LPS were consistent with the manifestation of BPD. This method could be used to establish animal models of BPD before birth, and the severity of BPD could be assessed by using LUS.
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Details
1 Second Affiliated Hospital of Fujian Medical University, Department of Ultrasound, Quanzhou, China (GRID:grid.488542.7) (ISNI:0000 0004 1758 0435); Quanzhou Hospital of Traditional Chinese Medicine, Department of Ultrasound, Quanzhou, China (GRID:grid.477749.e)
2 Second Affiliated Hospital of Fujian Medical University, Department of Ultrasound, Quanzhou, China (GRID:grid.488542.7) (ISNI:0000 0004 1758 0435)
3 Fujian Province Maternity and Children’s Hospital, Department of Ultrasound, Fuzhou, China (GRID:grid.488542.7)
4 Second Affiliated Hospital of Fujian Medical University, Department of Ultrasound, Quanzhou, China (GRID:grid.488542.7) (ISNI:0000 0004 1758 0435); Quanzhou Medical College, Collaborative Innovation Center of Maternal and Child Health Service Technology, Quanzhou, China (GRID:grid.410737.6) (ISNI:0000 0000 8653 1072)