Research progress in the role of SR-BI protein in cholesterol gallstones / 国际外科学杂志

Gallstone is one of the most common diseases in hepatobiliary, cholesterol gallstone is the most common type of gallstone. One of the important causes of gallstone formation is the precipitation of cholesterol crystals caused by cholesterin supersaturation. Scavenger receptor type BI (SR-BI) is a kind of multifunctional membrane receptor protein, which can mediate the selective uptake of cholesterol in liver and then affect the content of cholesterol in bile. Its role in the formation of gallstone has been initially revealed. In this paper, the relationship between the occurrence of cholesterol gallstones and scavenger receptor type B type I was summarized in order to provide new ideas for the further study of the pathogenesis of gallstone.

Bioinformatics analysis of leptin regulating gallbladder contraction and secretion in mice / 国际外科学杂志

Objective To identify the key pathogenic genes of leptin regulating gallbladder contraction and secretion in mice and to reveal the potential molecular mechanism by comprehensive bioinformatics.Methods The expression profile of GSE3293 was downloaded from Gene Expression Omnibus (GEO) database.The data contained 8 samples,including 4 leptin-treated gallbladder samples and 4 saline-treated gallbladder samples.The most valuable 250 differentially expressed genes (DEGs) were obtained by grouping analysis of GEO online GEO 2 R-TOP 250 software or tools,and further analyzed by bioinformatics.The GO function and KEGG pathway enrichment of DEGs were analyzed by DAVID online software.The protein-protein interaction (PPI) network of DEGs was constructed from STRING database.Results A total of 250 differentially expressed genes were identified from the GSE3293 dataset,of which 197 genes were up-regulated and 53 genes were down-regulated.GO analysis showed that the biological functions of DEGs were mainly concentrated on MHC class Ⅱ protein complexes,plasma membrane,extracellular exosome.KEGG pathway analysis showed that these DEGs were mainly involved in tuberculosis,leishmaniasis,cell adhesion molecules,bacteriophages,infection and other signaling pathways.PPI network showed that these DEGs coded proteins interacted strongly,and the first five pairs of DEGs with the strongest correlation were screened out.Conclusions The molecular mechanism of cholelithiasis is predicted from gene level by bioinformatics analysis of function enrichment and PPI of DEGs in mouse gallbladder.However,the function of DEGs still needs a lot of clinical and molecular biological experiments to confirm.

Bioinformatics analysis of leptin regulating gallbladder contraction and secretion in mice / 国际外科学杂志

Objective@#To identify the key pathogenic genes of leptin regulating gallbladder contraction and secretion in mice and to reveal the potential molecular mechanism by comprehensive bioinformatics.@*Methods@#The expression profile of GSE3293 was downloaded from Gene Expression Omnibus (GEO) database. The data contained 8 samples, including 4 leptin-treated gallbladder samples and 4 saline-treated gallbladder samples. The most valuable 250 differentially expressed genes (DEGs) were obtained by grouping analysis of GEO online GEO 2 R-TOP 250 software or tools, and further analyzed by bioinformatics. The GO function and KEGG pathway enrichment of DEGs were analyzed by DAVID online software. The protein-protein interaction (PPI) network of DEGs was constructed from STRING database.@*Results@#A total of 250 differentially expressed genes were identified from the GSE3293 dataset, of which 197 genes were up-regulated and 53 genes were down-regulated. GO analysis showed that the biological functions of DEGs were mainly concentrated on MHC class II protein complexes, plasma membrane, extracellular exosome. KEGG pathway analysis showed that these DEGs were mainly involved in tuberculosis, leishmaniasis, cell adhesion molecules, bacteriophages, infection and other signaling pathways. PPI network showed that these DEGs coded proteins interacted strongly, and the first five pairs of DEGs with the strongest correlation were screened out.@*Conclusions@#The molecular mechanism of cholelithiasis is predicted from gene level by bioinformatics analysis of function enrichment and PPI of DEGs in mouse gallbladder. However, the function of DEGs still needs a lot of clinical and molecular biological experiments to confirm.

Function of leptin in gallstone formation / 国际外科学杂志

Objective To investigate the function of serum and bile leptin in the formation of gallstones.Methods Patients were divided into two groups:gallbladder cholesterol gallstone group (group A,n =58) and non-gallstone group (group B,n =33).With a body mass index of 24 kg/m2 for the standard,the group A was also divided into the group A1 (body mass index ≥24 kg/m2,n =30) and group A2 (body mass index ＜ 24 kg/m2,n =28).Group B was divided into group B1 (body mass index≥24 kg/m2,n =18) and group B2 (body mass index ＜24 kg/m2,n =15).Fasting blood samples from all study participants were assayed for total bile acid,total cholesterol,triglyceride,low density lipoprotein,high density lipoprotein,apolipoprotein AI,apolipoprotein B,lipoprotein (a).Serum leptin and bile leptin were measured using an enzyme-linked immunosorbent assay.Results A total of 58 patients with gallbladder cholesterol gallstone and 33 controls were included in the study.The serum level of leptin,total cholesterol,low density lipoprotein,apolipoprotein B and triglyceride were significantly increased,high density lipoprotein and apolipoprotein AI significantly decreased in patients with gallbladder cholesterol gallstone compared with controls(P ＜0.05).While bile leptin,total Bile acid,lipoprotein(a) were no significant difference between group A and group B (P ＞ 0.05).Serum leptin in patients with gallbladder cholesterol gallstone were significantly positively correlated with Body Mass Index(r =0.65,P =0.01),Especially when Body Mass Index ≥ 24 kg/m2 (r =0.73,P ＜ 0.01).Conclusions Changes in levels of serum leptin may affect levels of blood lipid,some lipoprotein and bile leptin,then promote the formation of cholesterol stones.

Implementation of a Particle Swarm Optimization-based Classification Algorithm for Analyzing DNA Chip Data

DNA chips are used for experiments on genes and provide useful information that could be further analyzed. Using the data extracted from the DNA chips to find useful patterns or information has become a very important issue. In this paper, we explain the application developed for classifying DNA chip data using a classification method based on the Particle Swarm Optimization (PSO) algorithm. Considering that DNA chip data is extremely large and has a fuzzy characteristic, an algorithm that imitates the ecosystem such as the PSO algorithm is suitable to be used for analyzing such data. The application enables researchers to customize the PSO algorithm parameters and see detail results of the classification rules.

A Clustering Tool Using Particle Swarm Optimization for DNA Chip Data

DNA chips are becoming increasingly popular as a convenient way to perform vast amounts of experiments related to genes on a single chip. And the importance of analyzing the data that is provided by such DNA chips is becoming significant. A very important analysis on DNA chip data would be clustering genes to identify gene groups which have similar properties such as cancer. Clustering data for DNA chips usually deal with a large search space and has a very fuzzy characteristic. The Particle Swarm Optimization algorithm which was recently proposed is a very good candidate to solve such problems. In this paper, we propose a clustering mechanism that is based on the Particle Swarm Optimization algorithm. Our experiments show that the PSO-based clustering algorithm developed is efficient in terms of execution time for clustering DNA chip data, and thus be used to extract valuable information such as cancer related genes from DNA chip data with high cluster accuracy and in a timely manner.