Browsing by Subject "fatty liver disease"

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    Automated assessment of steatosis in murine fatty liver
    (PLOS, 2018-05-10) Sethunath, Deepak; Morusu, Siripriya; Tuceryan, Mihran; Cummings, Oscar W.; Zhang, Hao; Yin, Xiao-Ming; Vanderbeck, Scott; Chalasani, Naga; Gawrieh, Samer; Computer and Information Science, School of Science
    Although mice are commonly used to study different aspects of fatty liver disease, currently there are no validated fully automated methods to assess steatosis in mice. Accurate detection of macro- and microsteatosis in murine models of fatty liver disease is important in studying disease pathogenesis and detecting potential hepatotoxic signature during drug development. Further, precise quantification of macrosteatosis is essential for quantifying effects of therapies. Here, we develop and validate the performance of automated classifiers built using image processing and machine learning methods for detection of macro- and microsteatosis in murine fatty liver disease and study the correlation of automated quantification of macrosteatosis with expert pathologist’s semi-quantitative grades. The analysis is performed on digital images of 27 Hematoxylin & Eosin stained murine liver biopsy samples. An expert liver pathologist scored the amount of macrosteatosis and also annotated macro- and microsteatosis lesions on the biopsy images using a web-application. Using these annotations, supervised machine learning and image processing techniques, we created classifiers to detect macro- and microsteatosis. For macrosteatosis prediction, the model’s precision, sensitivity and area under the receiver operator characteristic (AUROC) were 94.2%, 95%, 99.1% respectively. When correlated with pathologist’s semi-quantitative grade of steatosis, the model fits with a coefficient of determination value of 0.905. For microsteatosis prediction, the model has precision, sensitivity and AUROC of 79.2%, 77%, 78.1% respectively. Validation by the expert pathologist of classifier’s predictions made on unseen images of biopsy samples showed 100% and 63% accuracy for macro- and microsteatosis, respectively. This novel work demonstrates that fully automated assessment of steatosis is feasible in murine liver biopsies images. Our classifier has excellent sensitivity and accuracy for detection of macrosteatosis in murine fatty liver disease.
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    Intakes of magnesium, calcium and risk of fatty liver disease and prediabetes
    (Cambridge, 2018-08) Li, Wenshuai; Zhu, Xiangzhu; Song, Yiqing; Fan, Lei; Wu, Lijun; Kabagambe, Edmond; Hou, Lifang; Shrubsole, Martha; Liu, Jie; Dai, Qi; Epidemiology, School of Public Health
    Objective Obesity and insulin resistance play important roles in the pathogenesis of non-alcoholic fatty liver disease (NAFLD). Mg intake is linked to a reduced risk of metabolic syndrome and insulin resistance; people with NAFLD or alcoholic liver disease are at high risk of Mg deficiency. The present study aimed to investigate whether Mg and Ca intakes were associated with risk of fatty liver disease and prediabetes by alcohol drinking status. Design We analysed the association between Ca or Mg intake and fatty liver disease, prediabetes or both prediabetes and fatty liver disease in cross-sectional analyses. Setting Third National Health and Nutrition Examination Survey (NHANES III) follow-up cohort of US adults. Subjects Nationally representative sample of US adults in NHANES (n 13 489). Results After adjusting for potential confounders, Mg intake was associated with approximately 30 % reduced odds of fatty liver disease and prediabetes, comparing the highest intake quartile v. the lowest. Mg intake may only be related to reduced odds of fatty liver disease and prediabetes in those whose Ca intake is less than 1200 mg/d. Mg intake may also only be associated with reduced odds of fatty liver disease among alcohol drinkers. Conclusions The study suggests that high intake of Mg may be associated with reduced risks of fatty liver disease and prediabetes. Further large studies, particularly prospective cohort studies, are warranted to confirm the findings.
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    Relevance of autophagy to fatty liver diseases and potential therapeutic applications
    (Springer, 2017-12) Yan, Shengmin; Huda, Nazmul; Khambu, Bilon; Yin, Xiao-Ming; Pathology and Laboratory Medicine, School of Medicine
    Autophagy is an evolutionarily conserved lysosome-mediated cellular degradation program. Accumulating evidence shows that autophagy is important to the maintenance of liver homeostasis. Autophagy involves recycling of cellular nutrients recycling as well as quality control of subcellular organelles. Autophagy deficiency in the liver causes various liver pathologies. Fatty liver disease (FLD) is characterized by the accumulation of lipids in hepatocytes and the dysfunction in energy metabolism. Autophagy is negatively affected by the pathogenesis of FLD and the activation of autophagy could ameliorate steatosis, which suggests a potential therapeutic approach to FLD. In this review, we will discuss autophagy and its relevance to liver diseases, especially FLD. In addition, we will discuss recent findings on potential therapeutic applications of autophagy modulators for FLD.