Ulcerative colitis is an inflammatory disease of the intestine caused by many reasons, and it may even develop into colon cancer. Probiotics are normal bacteria that exist in the human body and have been proven to regulate the balance of intestinal flora and alleviate inflammation. The current study aimed to study the effect of Lactobacillus fermentum ZS40 (ZS40) on dextran sulfate sodium (DSS)-induced ulcerative colitis mice. The length and weight of the colon were measured, and the histopathological morphological changes of colon tissue were observed to evaluate the effects of ZS40 on colitis. Biochemical kits, ELISA kits, real-time quantitative PCR (RT-qPCR), and western blot were also used to detect the effects of ZS40 on serum and colon tissue related oxidative indicators and pro-inflammatory and anti-inflammatory cytokines. We found that ZS40 could reduce colonic inflammatory cell infiltration and goblet cell necrosis, increase total superoxide dismutase and catalase in mouse serum, and reduce myeloperoxidase and malondialdehyde levels. ZS40 could down-regulate the level of proinflammatory cytokines and up-regulate the level of anti-inflammatory cytokines. More importantly, ZS40 down-regulated the relative expression of nuclear factor-κB p65 (NF-κBp65), IL-6, and TNF-α mRNA and protein, up-regulated the relative expression of inhibitor kapa B alpha (IκB-α). By regulating the NF-κB and MAPK pathways to down-regulated the relative expression of p38 and JNK1/2 mRNA and p38, p-p38, JNK1/2, and p-JNK1/2 proteins. Our study suggested that ZS40 may serve as a potential therapeutical strategy for ulcerative colitis.
Acute respiratory distress syndrome (ARDS) is one of the more serious diseases in human lung disease. Reducing its incidence rate is an important task in current clinical research. Dynamic monitoring of serum protein in patients will help to achieve the early diagnosis and treatment of ARDS. In this study, a protein monitoring model based on artificial neural network is proposed. First, surface enhanced laser desorption ionization time-of-flight mass spectrometry is used for protein detection, and then BP neural network is used for protein classification and content analysis. In the experimental analysis, serum samples from patients with acute respiratory distress syndrome in our hospital from November 2020 to August 2021 were selected for experimental testing. The experimental results show that the serum protein monitoring model based on BP neural network has low error and high convergence ability and can monitor individual protein in protein monitoring, and the area under the ROC curve in diagnostic performance reaches 0.854. The above results show that the artificial neural network has a good effect on the dynamic monitoring of serum protein in acute respiratory distress syndrome, and the diagnostic performance evaluation can reach 0.854, which has the ability to significantly improve the clinical diagnosis and treatment of acute respiratory distress syndrome.
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