Value of second harmonic generation/two-photon excitation fluorescence in quantitative evaluation of liver fibrosis in mice with nonalcoholic fatty liver disease
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摘要:
目的通过二次谐波(SHG)和双光子激发荧光(TPEF)显微成像技术分析非酒精性脂肪性肝病(NAFLD)小鼠模型胶原参数动态变化,找出并建立适合蛋氨酸胆碱缺乏饲料(MCD)诱导的NAFLD小鼠的自动化定量评估参数,为SHG/TPEF显微成像技术应用于临床提供实验依据。方法获取MCD饮食小鼠不同时间点(0、4、8、12、16、20和24周)的肝组织标本,行HE、Masson和天狼猩红(SR)染色,并计算胶原蛋白比例面积(CPA)和羟脯氨酸(HYP)。使用SHG/TPEF纤维成像技术分析100个胶原参数。以造模后不同时间点和不同纤维化分期(S0~S4)为标准,采用支持向量机算法(SVM)模型分析胶原参数,并对参数行受试者工作特征曲线(ROC曲线)分析,同时与CPA、HYP进行比较。结果在MCD小鼠模型中,HE和SR染色后可以观察到随着造模时间的延长,肝小叶内脂肪变形成,纤维化逐渐加重。分别基于造模不同时间点和不同肝纤维化分期,选出26和27个参数;进一步采用SVM模型分析筛选出7个共同参数(#StrCV、#ShortStrCV、#ThickStrCV、#StrPTAgg、#StrPSAgg、...
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关键词:
- 非酒精性脂肪性肝病 /
- 肝硬化 /
- 显微成像技术 /
- 小鼠,近交C57BL
Abstract:Objective To investigate the dynamic changes in collagen parameters in mice with nonalcoholic fatty liver disease (NAFLD) by second harmonic generation (SHG) /two-photon excitation fluorescence (TPEF) , to establish the parameters for automatic quantitative evaluation of mice with NAFLD induced by methionine-and choline-deficient diet (MCD) , and to provide an experimental basis for the application of SHG/TPEF in clinical practice. Methods Liver tissue specimens of MCD mice were collected at weeks 0, 4, 8, 12, 16, 20, and 24, and HE staining, Masson staining, and sirius red (SR) staining were performed. Collagen proportionate area (CPA) and hydroxyproline (HYP) were calculated. SHG/TPEF was used to analyze 100 collagen parameters. With time points and fibrosis stage (S0-S4) as criteria, the SVM model was used to analyze the collagen parameters. A receiver operating characteristic (ROC) curve analysis was performed for the collagen parameters, and these parameters were compared with CPA and HYP in terms of the area under the ROC curve (AUC) . Results In the MCD mice, HE and SR staining showed that over the time of modeling, hepatic steatosis was observed in hepatic lobules, with gradual aggravation of fibrosis. A total of 26 parameters were screened out based on their correlation with time point, and 27 parameters were screened out based on their correlation with liver fibrosis stage. The analysis based on the SVM model identified 7 shared parameters (#StrCV, #ShortStrCV, #ThickStrCV, #StrPTAgg, #StrPSAgg, #LongStrPSAgg, and StrLengthPSAgg) . These 7 parameters had anAUC of 0. 857-0. 923 (P < 0. 05) in predicting different stages of liver fibrosis and an AUC of 0. 823-0. 976 (P < 0. 05) in predicting liver fibrosis at different time points. These 7 parameters were compared with CPA and HYP in terms of their value in predicting liver fibrosis, and it was found that the 7 parameters had a similar AUC as CPA and HYP in predicting S0 fibrosis, while the 7 parameters had a significantly higher AUC than CPA and HYP in predicting S1-S4 fibrosis. The 7 parameters had a similar AUC as CPA and HYP at week 0 of modeling, while at week 4 of modeling, the 7 parameters had a significantly higher AUC than CPA and HYP. Conclusion Seven parameters associated with fibrosis stage and time point can accurately reflect the changes in liver fibrosis in different stages and at different time points in a model of MCD-induced NAFLD, and therefore, they can be used for specific and accurate monitoring of liver fibrosis in a quantitative manner in this model.
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