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Objective To determine the role of replication factor C subunit 5 (RFC5) in acute myeloid leukemia (AML) from four aspects: expression, prognosis, biological functions, and its effects on the immune system.Methods The RFC5 gene expression and survival analyses, biological function analyses including functional enrichment analysis of genes co-expressed with RFC5, RFC5-interacted gene network construction, gene set enrichment analysis (GSEA), and immune infiltration analysis were performed using data based on GDC TCGA and GEO. The CIBERSORT algorithm was employed to quantify immune cell fractions. All the statistical analyses were performed in SPSS software, GraphPad Prism, and R software.Results RFC5 expression was abnormally expressed in AML (P

In this study, we collected plant material from Pseudotsuga sinensis in Guizhou, China, and sequenced it. The complete chloroplast genome consisted of 122,243 bp, including a large single-copy (LSC) region, a small single-copy (SSC) region, and two inverted repeat regions like those in P. sinensis var. wilsoniana. The GC content of P. sinensis and P. sinensis var. wilsoniana are 38.7% and 38.8%, respectively. The reconstructed phylogenetic tree reveals that P. sinensis was a sister species to P. sinensis var. wilsoniana. Hence, the availability of the chloroplast genome of P. sinensis will promote further phylogenetic studies of the family Pinaceae.

Text classification is a common task in natural language processing,in which there are a lot of research and progress based on machine learning and deep learning.However,these traditional methods can only process Euclidean spatial data,and cannot express the semantic information of the document effectively.To break the traditional learning mode,many recent studies start to use graphs to represent complicated relationships among entities in the document,and explore graph convolutional neural network for text representation.This paper reviews the text classification methods based on graph convolutional network.Firstly,the background and principle of graph convolutional network are summarized.Then,text classification methods based on graph convolutional network are described in detail according to different types of graph-based networks.Meanwhile,it analyzes the limi-tation of graph convolutional network in the depth of networks,and introduces the latest developments of deep networks in text classification.Finally,the classification performance of models involved in this paper is compared through some experiments,and the challenges and future research direction in this field are discussed.

Ubiquitination is one of the most important post-translational modifications in eukaryotes. The ubiquitination cascade includes ubiquitin-activating enzymes (E1), ubiquitin-conjugating enzymes (E2), and ubiquitin ligases (E3). The E3 ligases, responsible for substrate recognition, are the most abundant and varied proteins in the cascade and the most studied. SKP1-CUL1-F-Box (SCF)-type E3 ubiquitin ligases are multi-subunit RING (Really Interesting New Gene) E3 ubiquitin ligases, composed of CUL1 (Cullin 1), RBX1 (RING BOX 1), SKP1 (S-phase Kinase-associated Protein 1), and F-box proteins. In vitro ubiquitination assays, used for studying the specific recognition of substrate proteins by E3 ubiquitin ligases, require the purification of all components involved in the cascade, and for assays with SCF-type E3 ligases, additional proteins (several SCF complex subunits). Here, the Duet expression system was used to co-express E1, E2, ubiquitin, ubiquitylation target (substrate), and the four subunits of a SCF-type E3 ligase in E. coli. When these proteins co-exist in bacterial cells, ubiquitination occurs and can be detected by Western Blot. The effectiveness of this bacterial system for detecting ubiquitination cascade activity was demonstrated by replicating both AtSCFTIR1-mediated and human SCFFBXO28-mediated ubiquitylation in bacteria. This system provides a basic but adaptable platform for the study of SCF-type E3 ubiquitin ligases. [ABSTRACT FROM AUTHOR]

The microservice decomposition of the monolithic system can effectively alleviate the problems of system redundancy and difficulty in maintenance of the monolithic architecture.However,the existing microservice decomposition methods fail to make full use of the attribute information of the microservice architecture,which leads to the low rationality of service decomposition results.This paper proposes a service decomposition method based on microservice architecture.The method constructs an entity-attribute relationship graph through the association information of system services and attributes.Then the service decomposition rules are formulated by combining the feature information of the microservice architecture with the demand information of the target system,the association information between the two types of vertices is quantified,and a weighted entity-attribute graph is generated.Finally,the weighted GN algorithm is applied to realize the microservice decomposition of the system automatically.The experimental results show that the method greatly improves the timeliness of service decomposition,and the gene-rated microservice decomposition scheme performs better in terms of various evaluation metrics.

Carbon dots(CDs) have attracted extensive attention of researchers because of their excellent fluorescence performance,low toxicity,extensive raw materials and good biocompatibility.However,the emission wavelengths of most CDs are in short-wavelength region of blue and green light,limiting their widespread application.The synthesis of multicolor CDs can guide the realization of long wavelength CDs and broaden the application of CDs.Therefore, the multicolor emitting mechanism of CDs from sizes,inner structures and surface states of CDs was reviewed,the adjusting measures of achieving multicolor CDs were presented,including raw materials,reaction conditions,surface modification,and separation and purification.Furthermore,the application of multicolor CDs in light emitting diode and bioimaging was also summarized.

Berberis weiningensis is a frequently-used traditional Chinese medicinal herb that included various active alkaloids. In this study, we assembled the complete chloroplast (cp) genome of B. weiningensis. The complete cp genome of B. weiningensis is 166,275 bp in length, and has a typical structure with large single-copy (LSC 73,624 bp) and small single-copy (SSC 18,608 bp) regions separated by a pair of inverted repeats (IRs 37,019 bp) of large size. The B. weiningensis cp genome contains 147 genes, of which 101 protein-coding genes, 8 rRNA genes, and 38 tRNA genes. The phylogenetic analysis revealed that Berberis species closely clustered with Mahonia species, which obviously support that Mahonia and Berberis are not monophyletic.

Objective To discuss the related factors influencing the initiation time of forensic psychiatric assessment by analysis of the initiation time of forensic psychiatric assessment of criminal cases in Hunan Province. Methods Related data in assessment files of criminal cases accepted by 8 forensic psychiatric assessment institutions in Hunan Province from January 1, 2011 to December 31, 2016 were extracted. The Logistic regression analysis was used to explore the factors influencing the initiation time of forensic psychiatric assessment. After using property score matching （PSM） to control the influence of confounding factors, the efficiency of public security organs to initiate assessments of suspects with （without） mental disorders and with （without） responsibilities were compared. Results A total of 4 346 cases were included. The Logistic regression analysis suggested that the factors independently related to the initiation time of assessment include： cause of assessment, nationality of the assessed, history of diagnosis and treatment of mental illnesses, history of crimes, history of drug abuse, and status of alcohol consumption before the crime （all P

Objective To identify Parkinson’s disease (PD)-associated deregulated pathways and genes, to further elucidate the pathogenesis of PD. Methods Dataset GSE100054 was downloaded from the Gene Expression Omnibus, and differentially expressed genes (DEGs) in PD samples were identified. Functional enrichment analyses were conducted for the DEGs. The top 10 hub genes in the protein–protein interaction (PPI) network were screened out and used to construct a support vector machine (SVM) model. The expression of the top 10 genes was then validated in another dataset, GSE46129, and a clinical patient cohort. Results A total of 333 DEGs were identified. The DEGs were clustered into two gene sets that were significantly enriched in 12 pathways, of which 8 were significantly deregulated in PD, including cytokine–cytokine receptor interaction, gap junction, and actin cytoskeleton regulation. The signature of the top 10 hub genes in the PPI network was used to construct the SVM model, which had high performance for predicting PD. Of the 10 genes, GP1BA , GP6 , ITGB5 , and P2RY12 were independent risk factors of PD. Conclusion Genes such as GP1BA , GP6 , P2RY12, and ITGB5 play critical roles in PD pathology through pathways including cytokine−cytokine receptor interaction, gap junctions, and actin cytoskeleton regulation.

East Asia contains “relict” plant species that persist under narrow climatic conditions after once having wider distributions. Here, using distribution records coupled with ecological niche models, the authors identify long-term stable refugia possessing past, current and future climatic suitability favoring ancient plant lineages.

Isoetes yunguiensis is a rare and endangered fern endemic to Yunnan–Guizhou Plateau, China. The complete chloroplast genome sequence of I. yunguiensis was generated by de novo assembly using whole genome next-generation sequencing. The cp genome of I. yunguiensis was a circular structure and 145,355 bp in length, comprising a pair of inverted repeat (IR) regions of 26,130 bp, a large single copy (LSC) of 91,923 bp, and a small single copy (SSC) of 27,302 bp. The genome encoded 124 unique genes consisting of 82 protein-coding genes, 32 transfer RNA, four ribosomal RNA genes, and six pseudogenes. A maximum-likelihood phylogenetic analysis revealed that I. yunguiensis was closely related to I. butleri, I. engelmannii, I. flaccida, I. melanospora, and I. valida, with strong support values.

In the original version of this Article, an incorrect sample size was provided for the number of relict species (443 instead of 442) and the number of relict forests (423 instead of 422). These errors have been corrected in both the PDF and HTML versions of the Article.