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Context: The liver is both the largest metabolic and the largest immune organ and is closely related to the mechanisms of disease development. Clarifying the immune environment of the NAFLD liver to determine its interactions with biomarkers would be beneficial in exploring the mechanisms of disease development. Objective: The study aimed to identify biomarkers and immune cells associated with nonalcoholic fatty liver disease (NAFLD) and to analyze the correlation between key genes and immune cells in NAFLD, to improve the understanding of the mechanisms underlying NAFLD and provide potential therapeutic targets. Design: The research team performed a genetic study. Setting: The study took place at Qingdao, Shandong Province, China. Outcome Measures: The research team: (1) obtained the NAFLD-related datasets GSE63067, GSE48452, and GSE89632 from the Gene Expression Omnibus (GEO) database; (2) analyzed immune-cell infiltrates using single-sample gene set enrichment analysis (ssGSEA) to determine the hub immune cells; (3) selected the differentially expressed genes (DEGs) between the NAFLD and normal samples and screened them to identify the hub genes; (4) evaluated the efficiency of the hub genes using receiver operating characteristic (ROC) curves; and (5) analyzed the correlations between hub genes and immune cells. Results: The research team: (1) found 28 differential immune cells; (2) identified monocytes as the hub immune cells; (3) identified 55 DEGs; (4) comparing the top 10 genes, identified five hub genes: S100 calcium binding proteins A12 (S100A12), S100A9, S100A8, selectin L (SELL), and sex hormone binding globulin (SHBG); (5) for all five, the area under the ROC curve (AUC) was greater than 0.6-training set: AUCSA00A12 = 0.699, AUCSELL = 0.743, AUCS100A9 = 0.735, AUCSHBG = 0.752, and AUCS100A8 = 0.703; and validation set: AUCSA00A12 = 0.852, AUCSELL = 0.905, AUCS100A9 = 0.819, AUCSHBG = 0.830, and AUCS100A8 = 0.822; (6) negatively correlated SHBG with immune cells (P > .05, r=-0.09); and (7) positively correlated S100A12, S100A9, S100A8, and SELL with immune cells-rS100A8 = 0.40, rS100A9 = 0.50, rS100A12 = 0.38, and rSELL = 0.42, respectively. Conclusions: Based on bioinformatic analyses, the progression of NAFLD may involve monocytes through promotion of liver inflammation. The hub genes S100A12, S100A9, S100A8, SELL, and SHBG are potential biomarkers that may be useful as diagnostic tools or therapeutic targets for NAFLD.
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ETHNOPHARMACOLOGICAL RELEVANCE: Diabetes mellitus, characterized by abnormal blood glucose evaluation, is a serious chronic disease. In the treatment of the disease, α-glycosidase inhibitors play an important role for controlling the postprandial blood glucose level. Cortex Mori, a traditional Chinese herbal medicine, has a long history of use for the treatment of headaches, cough, edema and diabetes. Modern pharmacological studies have shown that the herb has beneficial effects on the suppression of postprandial blood glucose levels by inhibiting α-glycosidase activity in the small intestine. 1-Deoxynojirimycin (DNJ), the main active ingredient of this herb, is recognized as a potent α-glycosidase inhibitor. Our previous studies have shown that the hypoglycemic effect of Cortex Mori extract (CME) was significantly improved when giving CME in combination with Radix Pueraria flavonoids (RPF). In the present study, the pharmacokinetics and intestinal permeability of DNJ were comparatively investigated in rats after being given orally or by intestinal perfusion with CME alone or in CME-RPF pairs, to explore the mechanism of this synergistic effect. MATERIALS AND METHODS: The role of RPF on the plasma and urine concentrations of DNJ from CME orally administered was investigated. Four groups of rats received a single oral dose of either CME or CME-RPF, at DNJ equivalent doses of 20 and 40mg/kg, respectively. After dosing, plasma and urine were collected and assayed by LC/MS/MS. In addition, another two groups of rats were used for small intestinal perfusion with CME or CME-RPF at DNJ concentration of 10µM. RESULTS: Compared to the data when dosing with CME alone, the Cmax of DNJ were decreased from 5.78 to 2.94µg/ml (p<0.05) and 10.66 to 5.35µg/ml (p<0.01); Tmax were delayed from 0.40 to 0.55h and 0.35 to 0.50h (p<0.05); and MRT were significantly prolonged from 1.14 to 1.72h (p<0.05) and 0.95 to 1.62h (p<0.01), after dosing with CME-RPF at DNJ doses of 20 and 40mg/kg, respectively. In addition, the urinary recovery of DNJ over the first 4h after dosing significantly decreased from 48.76% to 33.86%. Effective permeability (Peff) of DNJ was decreased from 7.53×10(-3) to 3.09×10(-3)cm/s (p<0.05) when RPF was added to CME, when it was evaluated using the rat intestinal perfusion model. CONCLUSIONS: All the above results demonstrate that RPF was able to suspend and delay the absorption of DNJ, but did not affect the total amount of DNJ in the body. The resulting higher concentration of DNJ in the small intestine produced a relatively stronger effect of depressing the elevation of the postprandial blood glucose level. These findings support the important role of RPF in the application of CME on blood glucose control.