1.Differentiation of pulmonary mucosa-associated lymphoid tissue lymphoma and pulmonary adenocarcinoma by radiomics
Bin LIN ; Tao WANG ; Keren SHEN ; Xiaojun XU ; Quanquan GU ; Xiaojun GUAN ; Minming ZHANG
Chinese Journal of Radiology 2018;52(10):766-769
Objective To differentiate between pulmonary mucosa-associated lymphoid tissue lymphoma (MALT) and adenocarcinoma by radiomics, and then evaluate the diagnostic value of this novel approach. Methods We retrospectively analyzed CT images of pulmonary MALT lymphoma (n=16) and invasive pulmonary adenocarcinoma (n=41) and all these cases were confirmed by pathology in the Second Affiliated Hospital of Zhejiang University School of Medicine from June 2012 to June 2017. After we delineated the lesions as region of interest (ROI), sixty-one radiomics features were extracted from each individual's CT images by Radcloud 1.0. All cases in each group were randomly divided into training set (70%cases) and testing set(30%cases), with 7 features (Wilcoxon test) of which showed group differences and were used to train and validate a support vector machine (SVM) classifier. Results Seven of 61 radiomics features showed differences between the two groups, i.e. 10th percentile, mean, median, minimum, total energy, run length non uniformity, gray level non uniformity. Using these 7 features, the resulted SVM successfully differentiated two diseases. The SVM showed high performance with 90%precision, recall 0.89, F1-score 0.87, ROC 0.75. Conclusions Pulmonary MALT and adenocarcinoma differ in radiomics features and machine learning can utilize these features to differentiate between pulmonary MALT and adenocarcinoma. Combination of radiomics and machine learning is promising in the differential diagnosis of these two diseases.
2.Effects of Microbiota on the Treatment of Obesity with the Natural Product Celastrol in Rats
Weiyue HU ; Lingling WANG ; Guizhen DU ; Quanquan GUAN ; Tianyu DONG ; Ling SONG ; Yankai XIA ; Xinru WANG
Diabetes & Metabolism Journal 2020;44(5):747-763
Obesity has become one of the most serious issues threatening the health of humankind, and we conducted this study to examine whether and how celastrol protects against obesity. We fed male Sprague-Dawley rats a high-fat diet and administered celastrol to obese rats for 3 weeks. By recording body weight (BW) and other measures, we identified the effective dose of celastrol for obesity treatment. Feces were collected to perform 16S rRNA sequencing, and hypothalami were extracted for transcriptome sequencing. We then treated leptin knockout rats with celastrol and explored the changes in energy metabolism. Male Institute of Cancer Research (ICR) mice were used to test the acute toxicity of celastrol. We observed that celastrol reduced BW and promoted energy expenditure at a dose of 500 µg/kg BW but that food intake was not changed after administration. The diversity of the gut microbiota was improved, with an increased ratio of Our study revealed that celastrol decreased the BW of obese rats by enhancing energy expenditure but not by suppressing food intake and that this effect was mediated by the improvement of the gut microbiota and the activation of the hypothalamic leptin signaling pathway.