We aimed to investigate the regulatory mechanism of lentivirus-mediated overexpression of cystic fibrosis transmembrane conductance regulator (CFTR) in oxidative stress injury and inflammatory response in the lung tissue of mouse model of chronic obstructive pulmonary disease (COPD). COPD mouse model induced by cigarette smoke was established and normal mice were used as control. The mice were assigned into a normal group (control), a model group (untreated), an oe-CFTR group (injection of lentivirus overexpressing CFTR), and an oe-NC group (negative control, injection of lentivirus expressing irrelevant sequences). Compared with the oe-NC group, the oe-CFTR group had higher CFTR expression and a better recovery of pulmonary function. CFTR overexpression could inhibit the pulmonary endothelial cell apoptosis, reduce the levels of glutathione (GSH), reactive oxygen species (ROS), and malondialdehyde (MDA) and increase the values of superoxide dismutase (SOD), GSH peroxidase (GSH-Px), and total antioxidant capacity (T-AOC). The overexpression also led to reductions in the white blood cell (WBC) count in alveolus pulmonis, the concentrations of C-reactive protein (CRP), interleukin (IL)-6, and tumor necrosis factor-α, and the protein expressions of NF-κB p65, ERK, JNK, p-EPK, and p-JNK related to MAPK/NF-κB p65 signaling pathway. In conclusion, CFTR overexpression can protect lung tissues from injuries caused by oxidative stress and inflammatory response in COPD mouse model. The mechanism behind this may be related to the suppression of MAPK/NF-κB p65 signaling pathway.
The aim of the present study was to identify the potential target biomarkers associated with burn sepsis using microarray. GSE1781 was downloaded from Gene Expression Omnibus and included a collective of three biological replicates for each of the three conditions: Sham‑Sham, Sham‑cecal ligation and puncture (CLP) and Burn‑CLP. Subsequently, limma was applied to screen the differentially expressed genes (DEGs). Additionally, functional annotations were predicted by pathway enrichment. Furthermore, the transcription factors were screened according to the transcriptional regulation from patterns to profiles database. Furthermore, the interaction associations of the proteins were obtained from the STRING database and the protein‑protein interaction (PPI) network was constructed using Cytoscape. Finally, the gene co‑expression analysis was conducted using CoExpress. In total, compared with Sham‑Sham, a total of 476 DEGs and 682 DEGs were obtained in Sham‑CLP and Burn‑CLP, respectively. Additionally, 230 DEGs were screened in Burn‑CLP compared with Sham‑CLP. Acadm, Ehhadh and Angptl4 were significantly enriched in the PPAR signaling pathway. Additionally, Gsta3, Gstm2 and Gstt1 in Burn‑CLP were significantly enriched in glutathione metabolism. In the PPI network, the transcription factor Ppargc1a interacted with Angptl4, while Acadm interacted with Ehhadh. The gene co‑expression analysis showed that Ehhadh could be co‑expressed with Aqp8. In conclusion, Acadm, Ehhadh, Aqp8, Gsta3, Gstm2, Gstt1, Ppargc1a and Angptl4 may be potential target genes for the treatment of burn sepsis.
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