Attribute Reduction of Hybrid Decision Information Systems Based on Fuzzy Conditional Information Entropy

The presence of numerous uncertainties in hybrid decision information systems(HDISs)renders attribute reduction a formidable task.Currently available attribute reduction algorithms,including those based on Pawlak attribute importance,Skowron discernibility matrix,and information entropy,struggle to effectively manages multiple uncertainties simultaneously in HDISs like the precise measurement of disparities between nominal attribute values,and attributes with fuzzy boundaries and abnormal values.In order to address the aforementioned issues,this paper delves into the study of attribute reduction withinHDISs.First of all,a novel metric based on the decision attribute is introduced to solve the problem of accurately measuring the differences between nominal attribute values.The newly introduced distance metric has been christened the supervised distance that can effectively quantify the differences between the nominal attribute values.Then,based on the newly developed metric,a novel fuzzy relationship is defined from the perspective of“feedback on parity of attribute values to attribute sets”.This new fuzzy relationship serves as a valuable tool in addressing the challenges posed by abnormal attribute values.Furthermore,leveraging the newly introduced fuzzy relationship,the fuzzy conditional information entropy is defined as a solution to the challenges posed by fuzzy attributes.It effectively quantifies the uncertainty associated with fuzzy attribute values,thereby providing a robust framework for handling fuzzy information in hybrid information systems.Finally,an algorithm for attribute reduction utilizing the fuzzy conditional information entropy is presented.The experimental results on 12 datasets show that the average reduction rate of our algorithm reaches 84.04%,and the classification accuracy is improved by 3.91%compared to the original dataset,and by an average of 11.25%compared to the other 9 state-of-the-art reduction algorithms.The comprehensive analysis of these research results clearly indicates that our algorithm is highly effective in managing the intricate uncertainties inherent in hybrid data.

New insights into the interactions between the gut microbiota and the inflammatory response to ulcerative colitis in a mouse model of dextran sodium sulfate and possible mechanisms of action for treatment with PE&AFWE

Background:Inflammatory bowel disease(IBD),comprising Crohn's disease(CD)and ulcerative colitis(UC),is a heterogeneous state of chronic intestinal inflammation.Intestinal innate immunity,including innate immune cells,defends against pathogens and excessive entry of gut microbiota,while preserving immune tolerance to resident intestinal microbiota,and may be characterized by its capacity to produce a rapid and nonspecific reaction.The association between microbiota dysbiosis and the pathogenesis of IBD is complex and dynamic.When the intestinal ecosystem is in dysbiosis,the reduced abundance and diversity of intestinal gut microbiota make the host more vulnerable to the attack of exogenous and endogenous pathogenic gut microbiota.The aim of our study was to comprehensively assess the relationship between microbial populations within UC,the signaling pathways of pathogenic gut microbe therein and the inflammatory response,as well as to understand the effects of using PE&AFWE(poppy extract[Papaver nudicaule L.]and Artemisia frigida Willd.extract)on UC modulation.Methods:A UC mouse model was established by inducing SPF-grade C57BL/6 mice using dextrose sodium sulfate(DSS).Based on metagenomic sequencing to characterize the gut microbiome,the relationship between gut microbiota dysbiosis and gut microbiota was further studied using random forest and Bayesian network analysis methods,as well as histopathological analysis.Results:(1)We found that the 5 gut microbiota with the highest relative abundance of inflammatory bowel disease UC model gut microbiota were consistent with the top 5 ranked natural bacteria.There were three types of abundance changes in the model groups:increases(Chlamydiae/Proteobacteria and Deferribacteres),decreases(Firmicutes),and no significant changes(Bacteroidetes).The UC model group was significantly different from the control group,with 1308 differentially expressed species with abundance changes greater than or equal to 2-fold.(2)The proportion of the fecal flora in the UC group decreased by 37.5%in the Firmicutes and increased by 14.29%in the proportion of Proteobacteria compared to the control group before treatment.(3)The significantly enriched and increased signaling pathways screened were the'arachidonic acid metabolic pathway'and the'phagosomal pathway',which both showed a decreasing trend after drug administration.(4)Based on the causal relationship between different OTUs and the UC model/PE&AFWE administration,screening for directly relevant OTU networks,the UC group was found to directly affect OTU69,followed by a cascade of effects on OTU12,OTU121,OTU93,and OTU7,which may be the pathway of action that initiated the pathological changes in normal mice.(5)We identified a causal relationship between common differentially expressed OTUs and PE&AFWE and UC in the pre-and post-PE&AFWE-treated groups.Thereby,we learned that PE&AFWE can directly affect OTU90,after which it inhibits UC,inhibiting the activity of arachidonic acid metabolic pathway by affecting OTU118,which in turn inhibits the colonization of gut microbiota by OTU93 and OTU7.(6)Histopathological observation and scoring(HS)of the colon showed that there was a significant difference between the model group and the control group(p<0.001),and that there was a significant recovery in both the sulfasalazine(SASP)and the PE&AFWE groups after the administration of the drug(p<0.0001).Conclusion:We demonstrated causal effects and inflammatory metabolic pathways in gut microbiota dysbiosis and IBD,with five opportunistic pathogens directly contributing to IBD.PE&AFWE reduced the abundance of proteobacteria in the gut microbiota,and histopathology showed significant improvement.

Research progress on the relationship between intestinal microecology and intestinal bowel disease

Intestinal microecology is the main component of human microecology.Intestinal microecology consists of intestinal microbiota,intestinal epithelial cells,and intestinal mucosal immune system.These components are interdependent and establish a complex interaction network that restricts each other.According to the impact on the human body,there are three categories of symbiotic bacteria,opportunistic pathogens,and pathogenic bacteria.The intestinal microecology participates in digestion and absorption,and material metabolism,and inhibits the growth of pathogenic microorganisms.It also acts as the body’s natural immune barrier,regulates the innate immunity of the intestine,controls the mucosal barrier function,and also participates in the intestinal epithelial cells’physiological activities such as hyperplasia or apoptosis.When the steady-state balance of the intestinal microecology is disturbed,the existing core intestinal microbiota network changes and leads to obesity,diabetes,and many other diseases,especially irritable bowel syndrome,inflammatory bowel disease(IBD),and colorectal malignancy.Intestinal diseases,including tumors,are particularly closely related to intestinal microecology.This article systematically discusses the research progress on the relationship between IBD and intestinal microecology from the pathogenesis,treatment methods of IBD,and the changes in intestinal microbiota.

Genetic Parameters and Genome-Wide Association Studies for Body Size Traits of Shuxuan Cattle in China

In domestic cattle,the body size traits have important implications in terms of breed characteristics and production performance.Shuxuan cattle is a dual-purpose breed mainly raised in Sichuan province,China,for which we have known less about the genetic parameters and underlying candidate genes in relation to the body size traits.In this study,we obtained the genome-wide single nucleotide polymorphisms(SNPs)using the Illumina Bovine BeadChip in 275 Shuxuan cattle.These SNPs were first used for estimating genetic parameters for the withers height(WH)and diagonal body length(BL).Using the bivariate animal model,the estimates(±standard error)of heritabilities were 0.71±0.22 and 0.49±0.29 for BL,and their genetic correlation was 0.64±0.37.Second,the genome-wide association study(GWAS)was performed.However,these did not result into genome-wide significant SNPs for both WH and BL traits.According to a less stringent suggestive significance,some positional candidate genes were found,and some of them(such as FAM110B,TAS1R2,PAX3,and FHIT)were previously reported in literature to be associated with body size traits in cattle.In conclusion,we estimated the genetic parameters in Shuxuan cattle using genomic information for the first time,which are required for implementing the genomic selection programs in the future.

Tectonic implications of Late Paleozoic stratigraphic distribution in Northeast China and adjacent region

An analysis of the distribution of the Late Paleozoic strata on Northeast China and adjacent region reveals a zonal pattern of the distribution around the core of the Jiamusi-Mongolia Block. The main part of Late Paleozoic marine strata in this area is co

HMOD： An Omics Database for Herbal Medicine Plants

Dear Editor ,More than 50% of drugs are derived from chemical compounds that have been isolated from various plants （Fabricant and Farnsworth, 2001; Yarnell and Abascal, 2002）. With the development of sequencing technology and synthetic biology, we can obtain molecular information from the transcriptomic and genomic data of plants and then utilize bacteria to synthesize desired chemical compounds （Atanasov et al., 2015; Smanski et al., 2016）. Increasing numbers of researchers have started to publish omics data generated from herbal plants.