Comprehensive analysis of advanced glycation end-products in commonly consumed foods:presenting a database for dietary AGEs and associated exposure assessment

Advanced glycation end-products(AGEs)are a group of heterogeneous compounds formed in heatprocessed foods and are proven to be detrimental to human health.Currently,there is no comprehensive database for AGEs in foods that covers the entire range of food categories,which limits the accurate risk assessment of dietary AGEs in human diseases.In this study,we first established an isotope dilution UHPLCQq Q-MS/MS-based method for simultaneous quantification of 10 major AGEs in foods.The contents of these AGEs were detected in 334 foods covering all main groups consumed in Western and Chinese populations.Nε-Carboxymethyllysine,methylglyoxal-derived hydroimidazolone isomers,and glyoxal-derived hydroimidazolone-1 are predominant AGEs found in most foodstuffs.Total amounts of AGEs were high in processed nuts,bakery products,and certain types of cereals and meats(>150 mg/kg),while low in dairy products,vegetables,fruits,and beverages(<40 mg/kg).Assessment of estimated daily intake implied that the contribution of food groups to daily AGE intake varied a lot under different eating patterns,and selection of high-AGE foods leads to up to a 2.7-fold higher intake of AGEs through daily meals.The presented AGE database allows accurate assessment of dietary exposure to these glycotoxins to explore their physiological impacts on human health.

Databases of 2D material-substrate interfaces and 2D charged building blocks

Discovery of materials using“bottom-up”or“top-down”approach is of great interest in materials science.Layered materials consisting of two-dimensional(2D)building blocks provide a good platform to explore new materials in this respect.In van der Waals(vdW)layered materials,these building blocks are charge neutral and can be isolated from their bulk phase(top-down),but usually grow on substrate.In ionic layered materials,they are charged and usually cannot exist independently but can serve as motifs to construct new materials(bottom-up).In this paper,we introduce our recently constructed databases for 2D material-substrate interface(2DMSI),and 2D charged building blocks.For 2DMSI database,we systematically build a workflow to predict appropriate substrates and their geometries at substrates,and construct the 2DMSI database.For the 2D charged building block database,1208 entries from bulk material database are identified.Information of crystal structure,valence state,source,dimension and so on is provided for each entry with a json format.We also show its application in designing and searching for new functional layered materials.The 2DMSI database,building block database,and designed layered materials are available in Science Data Bank at https://doi.org/10.57760/sciencedb.j00113.00188.

A MySQL-Based Software System of Urban Land Planning Database of Shanghai in China

With the development of the digital city,data and data analysis have become more and more important.The database is the foundation of data analysis.In this paper,the software system of the urban land planning database of Shanghai in China is developed based on MySQL.The conceptual model of the urban land planning database is proposed,and the entities,attributes and connections of this model are discussed.Then the E-R conceptual model is transformed into a logical structure,which is supported by the relational databasemanagement system(DBMS).Based on the conceptual and logical structures,by using Spring Boot as the back-end framework and using MySQL and Java API as the development tools,a platformwith datamanagement,information sharing,map assistance and other functions is established.The functionalmodules in this platformare designed.The results of J Meter test show that the DBMS can add,store and retrieve information data stably,and it has the advantages of fast response and low error rate.The software system of the urban land planning database developed in this paper can improve the efficiency of storing and managing land data,eliminating redundant data and sharing data.

Prognostic Factors of Liver Transplantation for Hepatocellular Carcinoma: A Surveillance, Epidemiology, and End Results (SEER) Database Analysis

Objective We aimed to identify new,more accurate risk factors of liver transplantation for liver cancer through using the Surveillance,Epidemiology,and End Results(SEER)database.Methods Using the SEER database,we identified patients that had undergone surgical resection for non-metastatic hepatocellular carcinoma(HCC)and subsequent liver transplantation between 2010 and 2017.Overall survival(OS)was estimated using Kaplan-Meier plotter.Cox proportional hazards regression modelling was used to identify factors independently associated with recurrent disease[presented as adjusted hazard ratios(HR)with 95%CIs].Results Totally,1530 eligible patients were included in the analysis.There were significant differences in ethnicity(P=0.04),cancer stage(P<0.001),vascular invasion(P<0.001)and gall bladder involvement(P<0.001)between the groups that survived,died due to cancer,or died due to other causes.In the Cox regression model,there were no significant differences in OS at 5 years with different operative strategies(autotransplantation versus allotransplantation),nor at survival at 1 year with neoadjuvant radiotherapy.However,neoadjuvant radiotherapy did appear to improve survival at both 3 years(HR:0.540,95%CI:0.326–0.896,P=0.017)and 5 years(HR:0.338,95%CI:0.153–0.747,P=0.007)from diagnosis.Conclusion This study demonstrated differences in patient characteristics between prognostic groups after liver resection and transplantation for HCC.These criteria can be used to inform patient selection and consent in this setting.Preoperative radiotherapy may improve long-term survival post-transplantation.

Phylobone: a comprehensive database of bone extracellular matrix proteins in human and model organisms

The bone extracellular matrix(ECM) contains minerals deposited on highly crosslinked collagen fibrils and hundreds of noncollagenous proteins. Some of these proteins are key to the regulation of bone formation and regeneration via signaling pathways,and play important regulatory and structural roles. However, the complete list of bone extracellular matrix proteins, their roles, and the extent of individual and cross-species variations have not been fully captured in both humans and model organisms. Here, we introduce the most comprehensive resource of bone extracellular matrix(ECM) proteins that can be used in research fields such as bone regeneration, osteoporosis, and mechanobiology. The Phylobone database(available at https://phylobone.com) includes 255proteins potentially expressed in the bone extracellular matrix(ECM) of humans and 30 species of vertebrates. A bioinformatics pipeline was used to identify the evolutionary relationships of bone ECM proteins. The analysis facilitated the identification of potential model organisms to study the molecular mechanisms of bone regeneration. A network analysis showed high connectivity of bone ECM proteins. A total of 214 functional protein domains were identified, including collagen and the domains involved in bone formation and resorption. Information from public drug repositories was used to identify potential repurposing of existing drugs. The Phylobone database provides a platform to study bone regeneration and osteoporosis in light of(biological) evolution,and will substantially contribute to the identification of molecular mechanisms and drug targets.

Fusion of Hash-Based Hard and Soft Biometrics for Enhancing Face Image Database Search and Retrieval

The utilization of digital picture search and retrieval has grown substantially in numerous fields for different purposes during the last decade,owing to the continuing advances in image processing and computer vision approaches.In multiple real-life applications,for example,social media,content-based face picture retrieval is a well-invested technique for large-scale databases,where there is a significant necessity for reliable retrieval capabilities enabling quick search in a vast number of pictures.Humans widely employ faces for recognizing and identifying people.Thus,face recognition through formal or personal pictures is increasingly used in various real-life applications,such as helping crime investigators retrieve matching images from face image databases to identify victims and criminals.However,such face image retrieval becomes more challenging in large-scale databases,where traditional vision-based face analysis requires ample additional storage space than the raw face images already occupied to store extracted lengthy feature vectors and takes much longer to process and match thousands of face images.This work mainly contributes to enhancing face image retrieval performance in large-scale databases using hash codes inferred by locality-sensitive hashing(LSH)for facial hard and soft biometrics as(Hard BioHash)and(Soft BioHash),respectively,to be used as a search input for retrieving the top-k matching faces.Moreover,we propose the multi-biometric score-level fusion of both face hard and soft BioHashes(Hard-Soft BioHash Fusion)for further augmented face image retrieval.The experimental outcomes applied on the Labeled Faces in the Wild(LFW)dataset and the related attributes dataset(LFW-attributes),demonstrate that the retrieval performance of the suggested fusion approach(Hard-Soft BioHash Fusion)significantly improved the retrieval performance compared to solely using Hard BioHash or Soft BioHash in isolation,where the suggested method provides an augmented accuracy of 87%when executed on 1000 specimens and 77%on 5743 samples.These results remarkably outperform the results of the Hard BioHash method by(50%on the 1000 samples and 30%on the 5743 samples),and the Soft BioHash method by(78%on the 1000 samples and 63%on the 5743 samples).

Rosaceae fruit transcriptome database(ROFT)-a useful genomic resource for comparing fruits of apple,peach,strawberry,and raspberry

Rosaceae is a large plant family consisting of many economically important fruit crops including peach,apple,pear,strawberry,raspberry,plum,and others.Investigations into their growth and development will promote both basic understanding and progress toward increasing fruit yield and quality.With the ever-increasing high-throughput sequencing data of Rosaceae,comparative studies are hindered by inconsistency of sample collection with regard to tissue,stage,growth conditions,and by vastly different handling of the data.Therefore,databases that enable easy access and effective utilization of directly comparable transcript data are highly desirable.Here,we describe a database for comparative analysis,ROsaceae Fruit Transcriptome database(ROFT),based on RNA-seq data generated from the same laboratory using similarly dissected and staged fruit tissues of four important Rosaceae fruit crops:apple,peach,strawberry,and red raspberry.Hence,the database is unique in allowing easy and robust comparisons among fruit gene expression across the four species.ROFT enables researchers to query orthologous genes and their expression patterns during different fruit developmental stages in the four species,identify tissue-specific and tissue-/stage-specific genes,visualize and compare ortholog expression in different fruit types,explore consensus co-expression networks,and download different data types.The database provides users access to vast amounts of RNA-seq data across the four economically important fruits,enables investigations of fruit type specification and evolution,and facilitates the selection of genes with critical roles in fruit development for further studies.

SCSMRD: A database for single-cell skeletal muscle regeneration

Skeletal muscle regeneration is a complex process where various cell types and cytokines are involved.Single-cell RNA-sequencing (scRNA-seq) provides the opportunity to deconvolute heterogeneous tissue into individual cells based on their transcriptomic profiles.Recent scRNA-seq studies on mouse muscle regeneration have provided insights to understand the transcriptional dynamics that underpin muscle regeneration.However,a database to investigate gene expression profiling during skeletal muscle regeneration at the single-cell level is lacking.Here,we collected over 105 000 cells at 7 key regenerative time-points and non-injured muscles and developed a database,the Singlecell Skeletal Muscle Regeneration Database (SCSMRD).SCSMRD allows users to search the dynamic expression profiles of genes of interest across different cell types during the skeletal muscle regeneration process.It also provides a network to show the activity of regulons in different cell types at different time points.Pesudotime analysis showed the state changes trajectory of muscle stem cells (MuSCs) during skeletal muscle regeneration.This database is freely available at https://scsmrd.fengs-lab.com.

Comment on: Bibliometric analysis of glaucoma-related literature based on SCIE database: a 10-year literature analysis from 2009 to 2018

Dear Editor,Sun et al[1]recently published a bibliometric paper in the International Journal of Ophthalmology entitled“Bibliometric analysis of glaucoma-related literature based on SCIE database:a 10-year literature analysis from 2009 to 2018”.The authors mentioned in section MATERIALS AND METHODS that“SCIE database established by Institute for Scientific Information(ISI)was used for the purpose of this study.”and“The search strategy was as follows:theme=(glaucoma OR ocular hypertension),and the‘theme’field contains:title,abstract,author keywords,and keywords plus.Document type=(article),and other types of articles,such as case reports,reviews,letters to the editors,and so on,were excluded.The time period of publications was focused on the latest 10y from 2009 to 2018.And the search date was 2019-3-29.”

ARGs-OAP v3.0:Antibiotic-Resistance Gene Database Curation and Analysis Pipeline Optimization

Antibiotic resistance,which is encoded by antibiotic-resistance genes(ARGs),has proliferated to become a growing threat to public health around the world.With technical advances,especially in the popularization of metagenomic sequencing,scientists have gained the ability to decipher the profiles of ARGs in diverse samples with high accuracy at an accelerated speed.To analyze thousands of ARGs in a highthroughput way,standardized and integrated pipelines are needed.The new version(v3.0)of the widely used ARGs online analysis pipeline(ARGs-OAP)has made significant improvements to both the reference database-the structured ARG(SARG)database-and the integrated analysis pipeline.SARG has been enhanced with sequence curation to improve annotation reliability,incorporate emerging resistance genotypes,and determine rigorous mechanism classification.The database has been further organized and visualized online in the format of a tree-like structure with a dictionary.It has also been divided into sub-databases for different application scenarios.In addition,the ARGs-OAP has been improved with adjusted quantification methods,simplified tool implementation,and multiple functions with userdefined reference databases.Moreover,the online platform now provides a diverse biostatistical analysis workflow with visualization packages for the efficient interpretation of ARG profiles.The ARGs-OAP v3.0 with an improved database and analysis pipeline will benefit academia,governmental management,and consultation regarding risk assessment of the environmental prevalence of ARGs.

dbSCI:A manually curated database of SARS-CoV-2 inhibitors for COVID-19

Severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)is the pathogen of the ongoing coronavirus disease 2019(COVID-19)global pandemic.Here,by centralizing published cell-based experiments,clinical trials,and virtual drug screening data from the NCBI PubMed database,we developed a database of SARS-CoV-2 inhibitors for COVID-19,dbSCI,which includes 234 SARS-CoV-2 inhibitors collected from publications based on cell-based experiments,81 drugs of COVID-19 in clinical trials and 1305 potential SARS-CoV-2 inhibitors from bioinformatics analyses.dbSCI provides four major functions:(1)search the drug target or its inhibitor for SARS-CoV-2,(2)browse target/inhibitor information collected from cell experiments,clinical trials,and virtual drug screenings,(3)download,and(4)submit data.Each entry in dbSCI contains 18 types of information,including inhibitor/drug name,targeting protein,mechanism of inhibition,experimental technique,experimental sample type,and reference information.In summary,dbSCI provides a relatively comprehensive,credible repository for inhibitors/drugs against SARS-CoV-2 and their potential targeting mechanisms and it will be valuable for further studies to control COVID-19.

Query Optimization Framework for Graph Database in Cloud Dew Environment

The query optimizer uses cost-based optimization to create an execution plan with the least cost,which also consumes the least amount of resources.The challenge of query optimization for relational database systems is a combinatorial optimization problem,which renders exhaustive search impossible as query sizes rise.Increases in CPU performance have surpassed main memory,and disk access speeds in recent decades,allowing data compression to be used—strategies for improving database performance systems.For performance enhancement,compression and query optimization are the two most factors.Compression reduces the volume of data,whereas query optimization minimizes execution time.Compressing the database reduces memory requirement,data takes less time to load into memory,fewer buffer missing occur,and the size of intermediate results is more diminutive.This paper performed query optimization on the graph database in a cloud dew environment by considering,which requires less time to execute a query.The factors compression and query optimization improve the performance of the databases.This research compares the performance of MySQL and Neo4j databases in terms of memory usage and execution time running on cloud dew servers.

Towards sparse matrix operations:graph database approach for power grid computation

The construction of new power systems presents higher requirements for the Power Internet of Things(PIoT)technology.The“source-grid-load-storage”architecture of a new power system requires PIoT to have a stronger multi-source heterogeneous data fusion ability.Native graph databases have great advantages in dealing with multi-source heterogeneous data,which make them suitable for an increasing number of analytical computing tasks.However,only few existing graph database products have native support for matrix operation-related interfaces or functions,resulting in low efficiency when handling matrix calculations that are commonly encountered in power grids.In this paper,the matrix computation process is expressed by a strategy called graph description,which relies on the natural connection between the matrix and structure of the graph.Based on that,we implement matrix operations on graph database,including matrix multiplication,matrix decomposition,etc.Specifically,only the nodes relevant to the computation and their neighbors are concerned in the process,which prunes the influence of zero elements in the matrix and avoids useless iterations compared to the conventional matrix computation.Based on the graph description,a series of power grid computations can be implemented on graph database,which reduces redundant data import and export operations while leveraging the parallel computing capability of graph database.It promotes the efficiency of PIoT when handling multi-source heterogeneous data.An comprehensive experimental study over two different scale power system datasets compares the proposed method with Python and MATLAB baselines.The results reveal the superior performance of our proposed method in both power flow and N-1 contingency computations.

Power Information System Database Cache Model Based on Deep Machine Learning

At present,the database cache model of power information system has problems such as slow running speed and low database hit rate.To this end,this paper proposes a database cache model for power information systems based on deep machine learning.The caching model includes program caching,Structured Query Language(SQL)preprocessing,and core caching modules.Among them,the method to improve the efficiency of the statement is to adjust operations such as multi-table joins and replacement keywords in the SQL optimizer.Build predictive models using boosted regression trees in the core caching module.Generate a series of regression tree models using machine learning algorithms.Analyze the resource occupancy rate in the power information system to dynamically adjust the voting selection of the regression tree.At the same time,the voting threshold of the prediction model is dynamically adjusted.By analogy,the cache model is re-initialized.The experimental results show that the model has a good cache hit rate and cache efficiency,and can improve the data cache performance of the power information system.It has a high hit rate and short delay time,and always maintains a good hit rate even under different computer memory;at the same time,it only occupies less space and less CPU during actual operation,which is beneficial to power The information system operates efficiently and quickly.

Analysis of the expression profile of miRNAs related to skin photoaging in the GEO database

Background:Skin aging has recently gained significant attention in both society and skin care research.Understanding the biological processes of photoaging caused by long-term skin exposure to ultraviolet radiation is critical for preventing and treating skin aging.Therefore,it is important to identify genes related to skin photoaging and shed light on their functions.Methods:We used data from the Gene Expression Omnibus(GEO)database and conducted bioinformatics analyses to screen and extract microRNAs(miRNAs)and their downstream target genes related to skin photoaging,and to determine possible biological mechanisms of skin photoaging.Results:A total of 34 differentially expressed miRNAs and their downstream target genes potentially related to the biological process of skin photoaging were identified.Gene Ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis showed that these target genes were enriched in pathways related to human papillomavirus infection,extracellular matrix(ECM)-receptor signaling,estrogen receptor,skin development,epidermal development,epidermal cell differentiation,keratinocyte differentiation,structural components of the ECM,structural components of the skin epidermis,and others.Conclusion:Based on the GEO database-derived findings,we determined that target genes of two miRNAs,namely miR-4667-5P-KRT79 and miR-139-5P-FOS,play an important role in skin photoaging.These observations could provide theoretical support and guidance for further research on skin aging-related biological processes.

Type-2 Neutrosophic Set and Their Applications in Medical Databases Deadlock Resolution

Electronic patient data gives many advantages,but also new difficulties.Deadlocks may delay procedures like acquiring patient information.Distributed deadlock resolution solutions introduce uncertainty due to inaccurate transaction properties.Soft computing-based solutions have been developed to solve this challenge.In a single framework,ambiguous,vague,incomplete,and inconsistent transaction attribute information has received minimal attention.The work presented in this paper employed type-2 neutrosophic logic,an extension of type-1 neutrosophic logic,to handle uncertainty in real-time deadlock-resolving systems.The proposed method is structured to reflect multiple types of knowledge and relations among transactions’features that include validation factor degree,slackness degree,degree of deadline-missed transaction based on the degree of membership of truthiness,degree ofmembership of indeterminacy,and degree ofmembership of falsity.Here,the footprint of uncertainty(FOU)for truth,indeterminacy,and falsity represents the level of uncertainty that exists in the value of a grade of membership.We employed a distributed real-time transaction processing simulator(DRTTPS)to conduct the simulations and conducted experiments using the benchmark Pima Indians diabetes dataset(PIDD).As the results showed,there is an increase in detection rate and a large drop in rollback rate when this new strategy is used.The performance of Type-2 neutrosophicbased resolution is better than the Type-1 neutrosophic-based approach on the execution ratio scale.The improvement rate has reached 10%to 20%,depending on the number of arrived transactions.

New perspectives on robotic pancreaticoduodenectomy:An analysis of the National Cancer Database

BACKGROUND Pancreatic ductal adenocarcinoma is a common malignancy.Despite all advancements,the prognosis remains,poor with an overall 5-year survival of only 10.8%.Recently,a robotic platform has become an attractive tool for treating pancreatic cancer(PC).While recent studies indicated improved lymph node(LN)harvest during robotic pancreaticoduodenectomy(PD),data on long-term outcomes are insufficient.AIM To evaluate absolute LN harvest during PD.Secondary outcomes included evaluating the association between LN harvest and short-and long-term oncological outcomes for three different surgical approaches.METHODS We conducted an analysis of the National Cancer Database,including patients diagnosed with PC who underwent open,laparoscopic,or robotic PD in 2010-2018.One-way analysis of variance was used to compare continuous variables,chi-square test-for categorical.Overall survival was defined as the time between surgery and death.Median survival time was estimated with the Kaplan-Meier method,and groups were compared with the Wilcoxon test.A Cox proportional hazards model was used to assess the association of covariates with survival after controlling for patient characteristics and procedure type.RESULTS 17169 patients were included,8859(52%)males;mean age 65;14509(85%)white.13816(80.5%)patients had an open PD,2677(15.6%)and 676(3.9%)-laparoscopic and robotic PD respectively.Mean comorbidity index(Charlson-Deyo Score)0.50.On average,18.84 LNs were harvested.Mean LN harvest during open,laparoscopic and robotic PD was 18.59,19.65 and 20.70 respectively(P<0.001).On average 2.49 LNs were positive for cancer and did not differ by the procedure type(P=0.26).Vascular invasion was noted in 42.6%of LNs and did differ by the approach:42.1%for open,44.0%for laparoscopic and 47.2%for robotic PD(P=0.015).Median survival for open PD was 26.1 mo,laparoscopic-27.2 mo,robotic-29.1 mo(P=0.064).Survival was associated with higher LN harvest,while higher number of positive LNs was associated with higher mortality.CONCLUSION Our study suggests that robotic PD is associated with increased intraoperative LN harvest and has comparable short-term oncological outcomes and survival compared to open and laparoscopic approaches.

CHDTEPDB:Transcriptome Expression Profile Database and Interactive Analysis Platform for Congenital Heart Disease

CHDTEPDB(URL:http://chdtepdb.com/)is a manually integrated database for congenital heart disease(CHD)that stores the expression profiling data of CHD derived from published papers,aiming to provide rich resources for investigating a deeper correlation between human CHD and aberrant transcriptome expression.The develop-ment of human diseases involves important regulatory roles of RNAs,and expression profiling data can reflect the underlying etiology of inherited diseases.Hence,collecting and compiling expression profiling data is of critical significance for a comprehensive understanding of the mechanisms and functions that underpin genetic diseases.CHDTEPDB stores the expression profiles of over 200 sets of 7 types of CHD and provides users with more convenient basic analytical functions.Due to the differences in clinical indicators such as disease type and unavoidable detection errors among various datasets,users are able to customize their selection of corresponding data for personalized analysis.Moreover,we provide a submission page for researchers to submit their own data so that increasing expression profiles as well as some other histological data could be supplemented to the database.CHDTEPDB is a user-friendly interface that allows users to quickly browse,retrieve,download,and analyze their target samples.CHDTEPDB will significantly improve the current knowledge of expression profiling data in CHD and has the potential to be exploited as an important tool for future research on the disease.

Analysis of E2F3 gene variants,expression and clinical significance in melanoma based on multiple databases

Objective:To investigate the variation,expression and clinical significance of E2F3 gene in melanoma.Methods:Firstly,cBioportal database,Oncomine database and GEO database were used to analyze the variation and expression level of E2F3 gene in melanoma.OSskcm database and TISIDB database were used to analyze the relationship between E2F3 and melanoma prognosis and tumor immune infiltrating cells.Then,the LinkedOmics database was used to identify the differential genes related to E2F3 expression in melanoma and analyze their biological functions.Finally,small molecule compounds for the treatment of melanoma were screened through the CMap database.Results:The mutation rate of E2F3 gene in melanoma is about 4%,and there are 21 mutation sites.Compared with normal skin tissues,the expression of E2F3 gene in melanoma was significantly increased(P<0.01).The mutation and increased expression of E2F3 gene were associated with the shortened overall survival(OS)of melanoma patients(P<0.05).The CNA level of E2F3 was negatively correlated with the expression levels of lymphocytes such as pDC,Neutrophil,Act DC and Th17,and negatively correlated with the expression levels of chemokines such as CXCL5,CCL13 and CCR1.The methylation level of E2F3 was positively correlated with the expression levels of Th1,Neutrophil,Act DC and other lymphocytes,and positively correlated with the expression levels of CXCL16,CXCL12,CCR1 and other chemokines.The expression level of E2F3 was negatively correlated with the expression levels of lymphocytes such as Th17,Tcm CD4 and Th1,and negatively correlated with the expression levels of chemokines such as CXCL 16,CCL 22 and CCL 2.The expression of 96 genes such as UHRF1BP1 in melanoma was significantly correlated with the expression of E2F3(|cor|0.5,P<0.05).The above genes were mainly related to RNA transport,eukaryotic ribosome biogenesis,cell cycle and other pathways.Among them,WDR12,WDR43,RBM28,UTP18,DKC1,PAK1IP1,DDX31,TEX10,TRUB1 and TRMT61B were the top 10 hub genes.YC-1,simvastatin,cytochalasin-d,Deforolimus and cytochalasin-b may be five small molecule compounds for the treatment of melanoma.Conclusion:The mutation and increased expression level of E2F3 gene are related to the poor prognosis of melanoma and participate in the occurrence and development of melanoma by affecting the expression of different tumor immune infiltrating cell subtypes,which may be a potential diagnostic marker and therapeutic target for melanoma.

FAST Pulsar Database.I.Polarization Profiles of 682 Pulsars

Pulsar polarization profiles form a very basic database for understanding the emission processes in a pulsar magnetosphere.After careful polarization calibration of the 19-beam L-band receiver and verification of beamoffset observation results,we obtain polarization profiles of 682 pulsars from observations by the Five-hundredmeter Aperture Spherical radio Telescope(FAST)duringthe Galactic Plane Pulsar Snapshot survey and other normal FAST projects.Among them,polarization profiles of about 460 pulsars are observed for the first time.The profiles exhibit diverse features.Some pulsars have a polarization position angle curve with a good S-shaped swing,some with orthogonal modes;some have components with highly linearly polarized components or strong circularly polarized components;some have a very wide profile,coming from an aligned rotator,and some have an interpulse from a perpendicular rotator;some wide profiles are caused by interstellar scattering.We derive geometric parameters for 190 pulsars from the S-shaped position angle curves or with orthogonal modes.We find that the linear and circular polarization or the widths of pulse profiles have various frequency dependencies.Pulsars with a large fraction of linear polarization are more likely to have a large Edot.