Hepatitis B virus(HBV) infection is one the leading risk factors for chronic hepatitis, liver fibrosis, cirrhosis and hepatocellular cancer(HCC), which are a major global health problem. A large number of clinical stu...Hepatitis B virus(HBV) infection is one the leading risk factors for chronic hepatitis, liver fibrosis, cirrhosis and hepatocellular cancer(HCC), which are a major global health problem. A large number of clinical studies have shown that chronic HBV persistent infection causes the dysfunction of innate and adaptive immune response involving monocytes/macrophages, dendritic cells, natural killer(NK) cells, T cells. Among these immune cells, cell subsets with suppressive features have been recognized such as myeloid derived suppressive cells(MDSC),NK-reg, T-reg, which represent a critical regulatory system during liver fibrogenesis or tumourigenesis. However, the mechanisms that link HBVinduced immune dysfunction and HBV-related liver diseases are not understood.In this review we summarize the recent studies on innate and adaptive immune cell dysfunction in chronic HBV infection, liver fibrosis, cirrhosis, and HCC, and further discuss the potential mechanism of HBV-induced immunosuppressive cascade in HBV infection and consequences. It is hoped that this article will help ongoing research about the pathogenesis of HBV-related hepatic fibrosis and HBV-related HCC.展开更多
AIM: To determine whether contrast-enhanced ultrasound(CEUS) can improve the precision of breast imaging reporting and data system(BI-RADS) categorization. METHODS: A total of 230 patients with 235 solid breast lesion...AIM: To determine whether contrast-enhanced ultrasound(CEUS) can improve the precision of breast imaging reporting and data system(BI-RADS) categorization. METHODS: A total of 230 patients with 235 solid breast lesions classified as BI-RADS 4 on conventional ultrasound were evaluated. CEUS was performed within one week before core needle biopsy or surgical resection and a revised BI-RADS classification was assigned based on 10 CEUS imaging characteristics. Receiver operating characteristic curve analysis was then conducted to evaluate the diagnostic performance of CEUS-based BI-RADS assignment with pathological examination as reference criteria. RESULTS: The CEUS-based BI-RADS evaluation classified 116/235(49.36%) lesions into category 3, 20(8.51%), 13(5.53%) and 12(5.11%) lesions into categories 4A, 4B and 4C, respectively, and 74(31.49%) into category 5. Selecting CEUS-based BI-RADS category 4A as an appropriate cut-off gave sensitivity and specificity values of 85.4% and 87.8%, respectively, for the diagnosisof malignant disease. The cancer-to-biopsy yield was 73.11% with CEUS-based BI-RADS 4A selected as the biopsy threshold compared with 40.85% otherwise, while the biopsy rate was only 42.13% compared with 100% otherwise. Overall, only 4.68% of invasive cancers were misdiagnosed.CONCLUSION: This pilot study suggests that evaluation of BI-RADS 4 breast lesions with CEUS results in reduced biopsy rates and increased cancer-to-biopsy yields.展开更多
AIM: To build and evaluate predictive models for contrast-enhanced ultrasound(CEUS) of the breast to distinguish between benign and malignant lesions. METHODS: A total of 235 breast imaging reporting and data system(B...AIM: To build and evaluate predictive models for contrast-enhanced ultrasound(CEUS) of the breast to distinguish between benign and malignant lesions. METHODS: A total of 235 breast imaging reporting and data system(BI-RADS) 4 solid breast lesions were imaged via CEUS before core needle biopsy or surgical resection. CEUS results were analyzed on 10 enhancing patterns to evaluate diagnostic performance of three benign and three malignant CEUS models, with pathological results used as the gold standard. A logistic regression model was developed basing on the CEUS results, and then evaluated with receiver operating curve(ROC). RESULTS: Except in cases of enhanced homogeneity, the rest of the 9 enhancement appearances were statistically significant(P < 0.05). These 9 enhancement patterns were selected in the final step of the logistic regression analysis, with diagnostic sensitivity and specificity of 84.4% and 82.7%, respectively, and the area under the ROC curve of 0.911. Diagnostic sensitivity, specificity, and accuracy of the malignant vs benign CEUS models were 84.38%, 87.77%, 86.38% and 86.46%, 81.29% and 83.40%, respectively. CONCLUSION: The breast CEUS models can predict risk of malignant breast lesions more accurately, decrease false-positive biopsy, and provide accurate BIRADS classification.展开更多
The Three Rivers Headwaters Region(TRHR) plays a key role in regulating water supply and climate of East Asia. A comprehensive understanding of the processes and driving forces of the long-term land use dynamics of th...The Three Rivers Headwaters Region(TRHR) plays a key role in regulating water supply and climate of East Asia. A comprehensive understanding of the processes and driving forces of the long-term land use dynamics of the TRHR is needed to guide sustainable land resource management and regional ecological conservation strategies. This study examined long-term land change patterns in the TRHR and investigated the driving forces of the change. First, Landsat TM/ETM+ images covering TRHR of four time points from 1987 to 2016 were used to derive land use patterns, and statistical metrics were applied to quantify the spatial and temporal changes. Second, Principal Component Analysis and correlation analysis were employed to analyze environmental and social-economic data to identify the driving forces of land use change. Third, potential influences of the religion of Tibetan Buddhism on land use change were explored using GIS analysis, questionnaire survey and field observation. Results showed that areas of barren land, agricultural land, and built-up land largely increased, while areas of grassland and forest greatly decreased, with the highest change rate occurring in the most recent decade of analysis(from 2007 to 2016). Among the three headwater regions, the Yellow River Headwater Region showed an overall higher changing speed than the other two headwater regions. The regional driving forces of change in TRHR includedsocial-economic development, climatic condition, pressure of population growth, and environmental protection activities. It was also found that Tibetan Buddhism can help slow down the changes caused by human activities.展开更多
基金the National Natural Science Foundation of China,No.81373143 and No.81571535 to Tu ZKKey Projects of Basic Research and Applied Basic Research in Universities of Guangdong Province,No.2018KZDXM055 to Tu ZK
文摘Hepatitis B virus(HBV) infection is one the leading risk factors for chronic hepatitis, liver fibrosis, cirrhosis and hepatocellular cancer(HCC), which are a major global health problem. A large number of clinical studies have shown that chronic HBV persistent infection causes the dysfunction of innate and adaptive immune response involving monocytes/macrophages, dendritic cells, natural killer(NK) cells, T cells. Among these immune cells, cell subsets with suppressive features have been recognized such as myeloid derived suppressive cells(MDSC),NK-reg, T-reg, which represent a critical regulatory system during liver fibrogenesis or tumourigenesis. However, the mechanisms that link HBVinduced immune dysfunction and HBV-related liver diseases are not understood.In this review we summarize the recent studies on innate and adaptive immune cell dysfunction in chronic HBV infection, liver fibrosis, cirrhosis, and HCC, and further discuss the potential mechanism of HBV-induced immunosuppressive cascade in HBV infection and consequences. It is hoped that this article will help ongoing research about the pathogenesis of HBV-related hepatic fibrosis and HBV-related HCC.
文摘AIM: To determine whether contrast-enhanced ultrasound(CEUS) can improve the precision of breast imaging reporting and data system(BI-RADS) categorization. METHODS: A total of 230 patients with 235 solid breast lesions classified as BI-RADS 4 on conventional ultrasound were evaluated. CEUS was performed within one week before core needle biopsy or surgical resection and a revised BI-RADS classification was assigned based on 10 CEUS imaging characteristics. Receiver operating characteristic curve analysis was then conducted to evaluate the diagnostic performance of CEUS-based BI-RADS assignment with pathological examination as reference criteria. RESULTS: The CEUS-based BI-RADS evaluation classified 116/235(49.36%) lesions into category 3, 20(8.51%), 13(5.53%) and 12(5.11%) lesions into categories 4A, 4B and 4C, respectively, and 74(31.49%) into category 5. Selecting CEUS-based BI-RADS category 4A as an appropriate cut-off gave sensitivity and specificity values of 85.4% and 87.8%, respectively, for the diagnosisof malignant disease. The cancer-to-biopsy yield was 73.11% with CEUS-based BI-RADS 4A selected as the biopsy threshold compared with 40.85% otherwise, while the biopsy rate was only 42.13% compared with 100% otherwise. Overall, only 4.68% of invasive cancers were misdiagnosed.CONCLUSION: This pilot study suggests that evaluation of BI-RADS 4 breast lesions with CEUS results in reduced biopsy rates and increased cancer-to-biopsy yields.
文摘AIM: To build and evaluate predictive models for contrast-enhanced ultrasound(CEUS) of the breast to distinguish between benign and malignant lesions. METHODS: A total of 235 breast imaging reporting and data system(BI-RADS) 4 solid breast lesions were imaged via CEUS before core needle biopsy or surgical resection. CEUS results were analyzed on 10 enhancing patterns to evaluate diagnostic performance of three benign and three malignant CEUS models, with pathological results used as the gold standard. A logistic regression model was developed basing on the CEUS results, and then evaluated with receiver operating curve(ROC). RESULTS: Except in cases of enhanced homogeneity, the rest of the 9 enhancement appearances were statistically significant(P < 0.05). These 9 enhancement patterns were selected in the final step of the logistic regression analysis, with diagnostic sensitivity and specificity of 84.4% and 82.7%, respectively, and the area under the ROC curve of 0.911. Diagnostic sensitivity, specificity, and accuracy of the malignant vs benign CEUS models were 84.38%, 87.77%, 86.38% and 86.46%, 81.29% and 83.40%, respectively. CONCLUSION: The breast CEUS models can predict risk of malignant breast lesions more accurately, decrease false-positive biopsy, and provide accurate BIRADS classification.
基金supported by the Graduate Research Support Scheme,Faculty of Arts and Social Sciences,National University of Singapore
文摘The Three Rivers Headwaters Region(TRHR) plays a key role in regulating water supply and climate of East Asia. A comprehensive understanding of the processes and driving forces of the long-term land use dynamics of the TRHR is needed to guide sustainable land resource management and regional ecological conservation strategies. This study examined long-term land change patterns in the TRHR and investigated the driving forces of the change. First, Landsat TM/ETM+ images covering TRHR of four time points from 1987 to 2016 were used to derive land use patterns, and statistical metrics were applied to quantify the spatial and temporal changes. Second, Principal Component Analysis and correlation analysis were employed to analyze environmental and social-economic data to identify the driving forces of land use change. Third, potential influences of the religion of Tibetan Buddhism on land use change were explored using GIS analysis, questionnaire survey and field observation. Results showed that areas of barren land, agricultural land, and built-up land largely increased, while areas of grassland and forest greatly decreased, with the highest change rate occurring in the most recent decade of analysis(from 2007 to 2016). Among the three headwater regions, the Yellow River Headwater Region showed an overall higher changing speed than the other two headwater regions. The regional driving forces of change in TRHR includedsocial-economic development, climatic condition, pressure of population growth, and environmental protection activities. It was also found that Tibetan Buddhism can help slow down the changes caused by human activities.
