Integrative analysis of bulk and single-cell RNA sequencing data reveals distinct subtypes of MAFLD based on N1-methyladenosine regulator expression

Background:Metabolic dysfunction-associated fatty liver disease(MAFLD)is now the most prevalent chronic liver disease worldwide,with an increasing incidence rate.MAFLD is a heterogeneous disease that can have a low or high-risk profile for developing severe liver disease in its natural course.Recent evidence has highlighted the critical role of RNA methylation modification in the pathogenesis of various liver diseases.However,it remains unclear whether the RNA N1-methyladenosine(m1A)modification of immune cells could potentially contribute to the pathogenesis and heterogeneity of MAFLD.Materials and methods:To address this issue,we conducted an integrated bioinformatics analysis of MAFLD bulk and single-cell RNA sequencing(scRNA-seq)data to pinpoint m1A regulators in the network.This was followed by a description of the immune landscape,pathway enrichment analysis,and molecular subtyping.Results:The expression patterns of m1A regulatory genes stratify MAFLD into two molecular subtypes,Cluster 1 and Cluster 2.These subtypes demonstrate different immune cell infiltration with distinct inflammation characteristics,which suggest different immune-inflammatory responses in the liver.Notably,Cluster 2 is associated with pro-inflammation and may be more likely to lead to progressive stages of MAFLD.Through intersection analysis of weighted gene co-expression network analysis(WGCNA)and m1A regulatory genes,three true hub genes(ALKBH1,YTHDC1,and YTHDF3)were identified,all of which were strongly correlated with infiltrating immune cells.The specific signaling pathways involved in the three core genes were derived from genomic variation analysis.Furthermore,scRNA-seq data from 33,168 cells from six liver samples identified 26 cell clusters and eight cell types,with endothelial cells,macrophages,and monocytes showing the most significant differences between MAFLD and normal controls.The cell-cell communication network between immune cells and nonparenchymal cells was extremely sophisticated and changed significantly in MAFLD.Conclusions:In summary,these findings demonstrate the involvement of m1A in MAFLD heterogeneity and emphasize the crucial role of m1A modulation of immune cells in regulating inflammation in MAFLD.These results may suggest potential therapeutic strategies for MAFLD.

Analysis of air quality characteristics of Beijing–Tianjin–Hebei and its surrounding air pollution transport channel cities in China

Beijing–Tianjin–Hebei(BTH)and its surrounding areas are very important to air pollution control in China.To analyze the characteristics of BTH and its surrounding areas of China,we collected 5,641,440 air quality data from 161 air monitoring stations and 37,123,000 continuous monitoring data from air polluting enterprises in BTH and surrounding cities to establish an indicator system for urban air quality portraits.The results showed that particulate matter with aerodynamic diameters of<2.5μm(PM2.5),particulate matter with aerodynamic diameters of<10μm(PM10)and SO2 improved significantly in 31 cities from2015 to 2018,but ozone deteriorated.Air quality in BTH and the surrounding areas showed obvious seasonal characteristics,among which PM2.5,PM10,SO2,and NO2 showed a"U"type distribution from January to December,while O3 had an"inverted U"distribution.The hourly changes in air quality revealed that peaks of PM2.5,PM10 and NO2 appeared from 8:00 to 10:00,while those for O3 appeared at 15:00–16:00.The exposure characteristics of the 31 cities showed that six districts in Beijing had the highest air quality population exposure,and that exposure levels in Zhengzhou,Puyang,Anyang,Jincheng were higher than the average of the 31 investigated cities.Additionally,multiple linear regression revealed a negative correlation between meteorological factors(especially wind and precipitation)and air quality,while a positive correlation existed between industrial pollution emissions and air quality in most of BTH and its surrounding cities.

Expression and Regulatory Network Analysis of Function of Small Nucleolar RNA Host Gene 4 in Hepatocellular Carcinoma

Background and Aims:Long non-coding RNA small nucleolar RNA host genes(SNHGs)play a critical role in the occurrence and development of tumors.In this study,we aimed to investigate the role of SNHG4 in hepatocellular carcinoma(HCC)and its underlining mechanism.Methods:Datasets were acquired from The Cancer Genome Atlas(TCGA)database.lncLocator 2.0 was used to identify the distribution of SNHG4 in HCC cells.Gene expression,Kaplan-Meier survival,microRNA and transcription factor target analyses were performed with the University of Alabama Cancer(UALCAN)Database,Kaplan-Meier Plotter,LinkedOmics,WebGestalt and gene set enrichment analysis,respectively.Gene Ontology and pathway enrichment analyses and assessment of RNA binding proteins were performed by R software,circlncRNAnet and Encyclopedia of RNA Interactomes(EN-CORI).In addition,CirclncRNAnet and ENCORI were used to find the correlation between SNHG4 and important proteins,while the prognostic value was assessed with the Human Protein Atlas database and Kaplan-Meier Plotter.Results:Expression of SNHG4 in HCC is higher in HCC tissue than in normal healthy liver tissues and is mainly distributed in the nucleus.SNHG4 positively correlated with poor prognosis(p<0.01 for overall survival and recurrence-free survival).Functional enrichment analysis revealed SNHG4 involve-ment with regulation of ribosomal RNA synthesis and the RNA processing and surveillance pathway.SNHG4 is closely associated with miR-154 and miR-206,transcription factor target E2F family and the signaling pathway for MAPK/ERK and mTOR.U2 auxiliary factor 2(U2AF2)showed strong correlation with SNHG4,while low-expression of U2AF2 showed good prognosis.Conclusions:Based on our find-ings,we infer SNHG4 may play a role in the formation of HCC via regulation of tumor-related pathways.

Achieving air pollutant emission reduction targets with minimum abatement costs:An enterprise-level allocation method with constraints of fairness and feasibility

For achieving air pollutant emission reduction targets,total pollutant amount control is being continuously promoted in China.However,the traditional pattern of pollutant emission reduction allocation regardless of economic cost often results in unreasonable emission reduction pathways,and industrial enterprises as the main implementers have to pay excessively high costs.Therefore,this study adopted economic efficiency as its main consideration,used specific emission reduction measures(ERMs)of industrial enterprises as minimum allocation units,and constructed an enterprise-level pollutant emission reduction allocation(EPERA)model with minimization of the total abatement cost(TAC)as the objective function,and fairness and feasibility as constraints for emission reduction allocation.Taking City M in China as an example,the EPERA model was used to construct a Pareto optimal frontier and obtain the optimal trade-off result.Results showed that under basic and strict emission reduction regulations,the TAC of the optimal trade-off point was reduced by 46.40%and 45.77%,respectively,in comparison with that achieved when only considering fairness,and the Gini coefficient was 0.26 and 0.31,respectively.The abatement target was attained with controllable cost and relatively fair and reasonable allocation.In addition,enterprises allocated different emission reduction quotas under different ERMs had specific characteristics that required targeted optimization of technology and equipment to enable them to achieve optimal emission reduction effects for the same abatement cost.