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  • Open Access

    ARTICLE

    Identification prognostic features related to sphingolipid metabolism and experimental validation of TRIM47 in hepatocellular carcinoma

    JIAN TANG1, CHENQIANG ZHU1, YUN CHEN1, YUNLONG WU1, MING HE1, YI ZHOU2, MINGHUA XIE2,*

    BIOCELL, Vol.48, No.4, pp. 639-651, 2024, DOI:10.32604/biocell.2024.047562

    Abstract Background: The specific impact of sphingolipid metabolism on developing hepatocellular Carcinoma (HCC) remains unclear. This study aims to explore the relationship between sphingolipid metabolism and HCC prognosis, immune response, and drug sensitivity. Methods: Data were obtained from The Cancer Genome Atlas (TCGA)-Hepatocellular Carcinoma (LIHC) and Gene Expression Omnibus (GEO, GSE14520 datasets). 47 sphingolipid metabolism genes were obtained from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. After classifying HCC samples using the Non-negative Matrix Factorization (NMF) clustering method, differentially expressed genes were screened. Then, 8 risk genes were obtained by univariate analysis, survival random forest reduction and lasso analysis.… More > Graphic Abstract

    Identification prognostic features related to sphingolipid metabolism and experimental validation of TRIM47 in hepatocellular carcinoma

  • Open Access

    ARTICLE

    Genome-Wide Exploration of the Grape GLR Gene Family and Differential Responses of VvGLR3.1 and VvGLR3.2 to Low Temperature and Salt Stress

    Honghui Sun1,2,#, Ruichao Liu1,2,#, Yueting Qi1, Hongsheng Gao1, Xueting Wang1, Ning Jiang1,2, Xiaotong Guo1,2, Hongxia Zhang1, Chunyan Yu1,2,*

    Phyton-International Journal of Experimental Botany, Vol.93, No.3, pp. 533-549, 2024, DOI:10.32604/phyton.2024.049417

    Abstract Grapes, one of the oldest tree species globally, are rich in vitamins. However, environmental conditions such as low temperature and soil salinization significantly affect grape yield and quality. The glutamate receptor (GLR) family, comprising highly conserved ligand-gated ion channels, regulates plant growth and development in response to stress. In this study, 11 members of the VvGLR gene family in grapes were identified using whole-genome sequence analysis. Bioinformatic methods were employed to analyze the basic physical and chemical properties, phylogenetic trees, conserved domains, motifs, expression patterns, and evolutionary relationships. Phylogenetic and collinear analyses revealed that the VvGLRs were divided into three… More >

  • Open Access

    ARTICLE

    The Identification of Phenylalanine Ammonia-Lyase (PAL) Genes from Pinus yunnanensis and an Analysis of Enzyme Activity in vitro

    Dejin Mu1,2, Lin Chen1,2, Heze Wang1,2, Zhaoliu Hu1,2, Sihui Chen1,2, Shi Chen1,2, Nianhui Cai1,2, Yulan Xu1,2, Junrong Tang1,2,*

    Phyton-International Journal of Experimental Botany, Vol.93, No.3, pp. 503-516, 2024, DOI:10.32604/phyton.2024.048786

    Abstract Phenylalanine ammonia lyase (PAL) is the rate-limiting and pivotal enzyme of the general phenylpropanoid pathway, but few reports have been found on PAL genes in Pinus yunnanensis. In the present study, three PAL genes were cloned and identified from P. yunnanensis seedlings for the first time, namely, PyPAL-1, PyPAL-2, and PyPAL-3. Our results indicated that the open-reading frames of PyPAL genes were 2184, 2157, and 2385 bp. Phylogenetic tree analysis revealed that PyPALs have high homology with other known PAL genes in other plants. In vitro enzymatic analysis showed that all three PyPAL recombinant proteins could catalyze the deamination of… More >

  • Open Access

    ARTICLE

    Identification and Transcriptional Regulation of CAMTA Genes in Liriodendron chinense

    Kaiyue Hong, Yasmina Radani, Teja Manda, Jinhui Chen, Liming Yang*

    Phyton-International Journal of Experimental Botany, Vol.93, No.3, pp. 413-425, 2024, DOI:10.32604/phyton.2024.047739

    Abstract This study explores CAMTA genes in the rare and endangered Chinese plant species, Liriodendron chinense. Despite the completion of whole-genome sequencing, the roles of CAMTA genes in calcium regulation and stress responses in this species remain largely unexplored. Within the L. chinense genome, we identified two CAMTA genes, Lchi09764 and Lchi222536, characterized by four functional domains: CG-1, TIG, ANK repeats, and IQ motifs. Our analyses, including phylogenetic investigations, cis-regulatory element analyses, and chromosomal location studies, aim to elucidate the defining features of CAMTA genes in L. chinense. Applying Weighted Gene Co-Expression Network Analysis (WGCNA), we explored the impact of CAMTAMore >

  • Open Access

    ARTICLE

    Applying an Improved Dung Beetle Optimizer Algorithm to Network Traffic Identification

    Qinyue Wu, Hui Xu*, Mengran Liu

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4091-4107, 2024, DOI:10.32604/cmc.2024.048461

    Abstract Network traffic identification is critical for maintaining network security and further meeting various demands of network applications. However, network traffic data typically possesses high dimensionality and complexity, leading to practical problems in traffic identification data analytics. Since the original Dung Beetle Optimizer (DBO) algorithm, Grey Wolf Optimization (GWO) algorithm, Whale Optimization Algorithm (WOA), and Particle Swarm Optimization (PSO) algorithm have the shortcomings of slow convergence and easily fall into the local optimal solution, an Improved Dung Beetle Optimizer (IDBO) algorithm is proposed for network traffic identification. Firstly, the Sobol sequence is utilized to initialize the dung beetle population, laying the… More >

  • Open Access

    ARTICLE

    Identification of Software Bugs by Analyzing Natural Language-Based Requirements Using Optimized Deep Learning Features

    Qazi Mazhar ul Haq1, Fahim Arif2,3, Khursheed Aurangzeb4, Noor ul Ain3, Javed Ali Khan5, Saddaf Rubab6, Muhammad Shahid Anwar7,*

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4379-4397, 2024, DOI:10.32604/cmc.2024.047172

    Abstract Software project outcomes heavily depend on natural language requirements, often causing diverse interpretations and issues like ambiguities and incomplete or faulty requirements. Researchers are exploring machine learning to predict software bugs, but a more precise and general approach is needed. Accurate bug prediction is crucial for software evolution and user training, prompting an investigation into deep and ensemble learning methods. However, these studies are not generalized and efficient when extended to other datasets. Therefore, this paper proposed a hybrid approach combining multiple techniques to explore their effectiveness on bug identification problems. The methods involved feature selection, which is used to… More >

  • Open Access

    ARTICLE

    Unmanned Ship Identification Based on Improved YOLOv8s Algorithm

    Chun-Ming Wu1, Jin Lei1,*, Wu-Kai Liu1, Mei-Ling Ren1, Ling-Li Ran2

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3071-3088, 2024, DOI:10.32604/cmc.2023.047062

    Abstract Aiming at defects such as low contrast in infrared ship images, uneven distribution of ship size, and lack of texture details, which will lead to unmanned ship leakage misdetection and slow detection, this paper proposes an infrared ship detection model based on the improved YOLOv8 algorithm (R_YOLO). The algorithm incorporates the Efficient Multi-Scale Attention mechanism (EMA), the efficient Reparameterized Generalized-feature extraction module (CSPStage), the small target detection header, the Repulsion Loss function, and the context aggregation block (CABlock), which are designed to improve the model’s ability to detect targets at multiple scales and the speed of model inference. The algorithm… More >

  • Open Access

    REVIEW

    Survey and Prospect for Applying Knowledge Graph in Enterprise Risk Management

    Pengjun Li1, Qixin Zhao1, Yingmin Liu1, Chao Zhong1, Jinlong Wang1,*, Zhihan Lyu2

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3825-3865, 2024, DOI:10.32604/cmc.2024.046851

    Abstract Enterprise risk management holds significant importance in fostering sustainable growth of businesses and in serving as a critical element for regulatory bodies to uphold market order. Amidst the challenges posed by intricate and unpredictable risk factors, knowledge graph technology is effectively driving risk management, leveraging its ability to associate and infer knowledge from diverse sources. This review aims to comprehensively summarize the construction techniques of enterprise risk knowledge graphs and their prominent applications across various business scenarios. Firstly, employing bibliometric methods, the aim is to uncover the developmental trends and current research hotspots within the domain of enterprise risk knowledge… More >

  • Open Access

    ARTICLE

    A Modified Principal Component Analysis Method for Honeycomb Sandwich Panel Debonding Recognition Based on Distributed Optical Fiber Sensing Signals

    Shuai Chen1, Yinwei Ma2, Zhongshu Wang2, Zongmei Xu3, Song Zhang1, Jianle Li1, Hao Xu1, Zhanjun Wu1,*

    Structural Durability & Health Monitoring, Vol.18, No.2, pp. 125-141, 2024, DOI:10.32604/sdhm.2024.042594

    Abstract The safety and integrity requirements of aerospace composite structures necessitate real-time health monitoring throughout their service life. To this end, distributed optical fiber sensors utilizing back Rayleigh scattering have been extensively deployed in structural health monitoring due to their advantages, such as lightweight and ease of embedding. However, identifying the precise location of damage from the optical fiber signals remains a critical challenge. In this paper, a novel approach which namely Modified Sliding Window Principal Component Analysis (MSWPCA) was proposed to facilitate automatic damage identification and localization via distributed optical fiber sensors. The proposed method is able to extract signal… More > Graphic Abstract

    A Modified Principal Component Analysis Method for Honeycomb Sandwich Panel Debonding Recognition Based on Distributed Optical Fiber Sensing Signals

  • Open Access

    ARTICLE

    Identification of prognostic molecular subtypes and model based on CD8+ T cells for lung adenocarcinoma

    HONGMIN CAO1,#,*, YING XUE2,#, FEI WANG1, GUANGYAO LI1, YULAN ZHEN1, JINGWEN GUO1

    BIOCELL, Vol.48, No.3, pp. 473-490, 2024, DOI:10.32604/biocell.2024.048946

    Abstract Background: Cytotoxic T lymphocytes (CD8+ T) cells function critically in mediating anti-tumor immune response in cancer patients. Characterizing the specific functions of CD8+ T cells in lung adenocarcinoma (LUAD) could help better understand local anti-tumor immune responses and estimate the effect of immunotherapy. Methods: Gens related to CD8+ T cells were identified by cluster analysis based on the single-cell sequencing data of three LUAD tissues and their paired normal tissues. Weighted gene co-expression network analysis (WGCNA), consensus clustering, differential expression analysis, least absolute shrinkage and selection operator (LASSO) and Cox regression analysis were conducted to classify molecular subtypes for LUAD… More > Graphic Abstract

    Identification of prognostic molecular subtypes and model based on CD8+ T cells for lung adenocarcinoma

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