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Application of tabu search-based Bayesian networks in exploring related factors of liver cirrhosis complicated with hepatic encephalopathy and disease identification.

ABSTRACT: This study aimed to explore the related factors and strengths of hepatic cirrhosis complicated with hepatic encephalopathy (HE) by multivariate logistic regression analysis and tabu search-based Bayesian networks (BNs), and to deduce the probability of HE in patients with cirrhosis under different conditions through BN reasoning. Multivariate logistic regression analysis indicated that electrolyte disorders, infections, poor spirits, hepatorenal syndrome, hepatic diabetes, prothrombin time, and total bilirubin are associated with HE. Inferences by BNs found that infection, electrolyte disorder and hepatorenal syndrome are closely related to HE. Those three variables are also related to each other, indicating that the occurrence of any of those three complications may induce the other two complications. When those three complications occur simultaneously, the probability of HE may reach 0.90 or more. The BN constructed by the tabu search algorithm can analyze not only how the correlative factors affect HE but also their interrelationships. Reasoning using BNs can describe how HE is induced on the basis of the order in which doctors acquire patient information, which is consistent with the sequential process of clinical diagnosis and treatment.

SUBMITTER: Zhang Z

PROVIDER: S-EPMC6472503 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Application of tabu search-based Bayesian networks in exploring related factors of liver cirrhosis complicated with hepatic encephalopathy and disease identification.

Zhang Zhuang Z Zhang Jie J Wei Zhen Z Ren Hao H Song Weimei W Pan Jinhua J Liu Jinchun J Zhang Yanbo Y Qiu Lixia L

Scientific reports 20190418 1

This study aimed to explore the related factors and strengths of hepatic cirrhosis complicated with hepatic encephalopathy (HE) by multivariate logistic regression analysis and tabu search-based Bayesian networks (BNs), and to deduce the probability of HE in patients with cirrhosis under different conditions through BN reasoning. Multivariate logistic regression analysis indicated that electrolyte disorders, infections, poor spirits, hepatorenal syndrome, hepatic diabetes, prothrombin time, and ...[more]

PMID: 31000773

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Project description:BACKGROUND: Protein structure prediction (PSP) has important applications in different fields, such as drug design, disease prediction, and so on. In protein structure prediction, there are two important issues. The first one is the design of the structure model and the second one is the design of the optimization technology. Because of the complexity of the realistic protein structure, the structure model adopted in this paper is a simplified model, which is called off-lattice AB model. After the structure model is assumed, optimization technology is needed for searching the best conformation of a protein sequence based on the assumed structure model. However, PSP is an NP-hard problem even if the simplest model is assumed. Thus, many algorithms have been developed to solve the global optimization problem. In this paper, a hybrid algorithm, which combines genetic algorithm (GA) and tabu search (TS) algorithm, is developed to complete this task. RESULTS: In order to develop an efficient optimization algorithm, several improved strategies are developed for the proposed genetic tabu search algorithm. The combined use of these strategies can improve the efficiency of the algorithm. In these strategies, tabu search introduced into the crossover and mutation operators can improve the local search capability, the adoption of variable population size strategy can maintain the diversity of the population, and the ranking selection strategy can improve the possibility of an individual with low energy value entering into next generation. Experiments are performed with Fibonacci sequences and real protein sequences. Experimental results show that the lowest energy obtained by the proposed GATS algorithm is lower than that obtained by previous methods. CONCLUSIONS: The hybrid algorithm has the advantages from both genetic algorithm and tabu search algorithm. It makes use of the advantage of multiple search points in genetic algorithm, and can overcome poor hill-climbing capability in the conventional genetic algorithm by using the flexible memory functions of TS. Compared with some previous algorithms, GATS algorithm has better performance in global optimization and can predict 3D protein structure more effectively.

Project description:UNLABELLED:Altered gut microbiome is associated with systemic inflammation and cirrhosis decompensation. However, the correlation of the oral microbiome with inflammation in cirrhosis is unclear. Our aim was to evaluate the oral microbiome in cirrhosis and compare with stool microbiome. Outpatients with cirrhosis (with/without hepatic encephalopathy [HE]) and controls underwent stool/saliva microbiome analysis (for composition and function) and also systemic inflammatory evaluation. Ninety-day liver-related hospitalizations were recorded. Salivary inflammation was studied using T helper 1 cytokines/secretory immunoglobulin A (IgA), histatins and lysozyme in a subsequent group. A total of 102 patients with cirrhosis (43 previous HE) and 32 age-matched controls were included. On principal component analysis (PCA), stool and saliva microbiome clustered far apart, showing differences between sites as a whole. In salivary microbiome, with previous HE, relative abundance of autochthonous families decreased whereas potentially pathogenic ones (Enterobacteriaceae, Enterococcaceae) increased in saliva. Endotoxin-related predicted functions were significantly higher in cirrhotic saliva. In stool microbiome, relative autochthonous taxa abundance reduced in previous HE, along with increased Enterobacteriaceae and Enterococcaceae. Cirrhotic stool microbiota demonstrated a significantly higher correlation with systemic inflammation, compared to saliva microbiota, on correlation networks. Thirty-eight patients were hospitalized within 90 days. Their salivary dysbiosis was significantly worse and predicted this outcome independent of cirrhosis severity. Salivary inflammation was studied in an additional 86 age-matched subjects (43 controls/43 patients with cirrhosis); significantly higher interleukin (IL)-6/IL-1?, secretory IgA, and lower lysozyme, and histatins 1 and 5 were found in patients with cirrhosis, compared to controls. CONCLUSIONS:Dysbiosis, represented by reduction in autochthonous bacteria, is present in both saliva and stool in patients with cirrhosis, compared to controls. Patients with cirrhosis have impaired salivary defenses and worse inflammation. Salivary dysbiosis was greater in patients with cirrhosis who developed 90-day hospitalizations. These findings could represent a global mucosal-immune interface change in cirrhosis.

Dataset Information

Application of tabu search-based Bayesian networks in exploring related factors of liver cirrhosis complicated with hepatic encephalopathy and disease identification.

Publications

Application of tabu search-based Bayesian networks in exploring related factors of liver cirrhosis complicated with hepatic encephalopathy and disease identification.

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