ZHEN WANG¹, JUN FU¹, SAISAI ZHU¹, HAODONG TANG², KUI SHI¹, JIHUA YANG³, MENG WANG³, MENGGE WU¹, DUNFENG QI^1,*

Oncology Research, Vol.32, No.12, pp. 1851-1866, 2024, DOI:10.32604/or.2024.055286 - 13 November 2024

Abstract Background: Pancreatic ductal adenocarcinoma (PDAC) has a rich and complex tumor immune microenvironment (TIME). M2 macrophages are among the most extensively infiltrated immune cells in the TIME and are necessary for the growth and migration of cancers. However, the mechanisms and targets mediating M2 macrophage infiltration in pancreatic cancer remain elusive. Methods: The M2 macrophage infiltration score of patients was assessed using the xCell algorithm. Using weighted gene co-expression network analysis (WGCNA), module genes associated with M2 macrophages were identified, and a predictive model was designed. The variations in immunological cell patterns, cancer mutations, and… More > Graphic Abstract

Yinyu Xu¹, Zheng Li¹, Qian Wen², Hao He¹, Pengtu Shi¹, Wenhua Zhou^2,*

Phyton-International Journal of Experimental Botany, Vol.93, No.9, pp. 2367-2382, 2024, DOI:10.32604/phyton.2024.047949 - 30 September 2024

Abstract The diversity of metabolites produced in fermented pine needles at different stages of fermentation has rarely been investigated. In the present study, untargeted metabolomic analysis using GC-MS and LC-MS was performed to detect metabolites in fermented pine needles at different fermentation stages. A total of 30 samples of pine needles fermented first with yeast (Saccharomyces cerevisiae) and then with a mixed bacterial culture of Lactobacillus fermentum CECT5716 and Bifidobacterium Breve M16V, were used to detect differential metabolites at different stages of fermentation. Pearson’s correlation analysis was used to determine correlations between metabolites and key microbial communities. A… More >

Mingyuan Luo¹, Shiyu Tian¹, Xinzhuan Yao², Yue Wan⁴, Zhouzhuoer Chen¹, Zifan Yang⁴, Huagen Hao⁴, Fei Liu³, Hu Tang^1,2,*, Litang Lu^1,2,*

Phyton-International Journal of Experimental Botany, Vol.93, No.8, pp. 2019-2036, 2024, DOI:10.32604/phyton.2024.052938 - 30 August 2024

Abstract The ATP-binding cassette (ABC) transporter is a gene superfamily in plants. ATP-binding cassette subfamily C (ABCC) protein is a multidrug resistance-associated (MRP) transporter. They play various roles in plant growth, development, and secondary metabolite transport. However, there are few studies on ABCC transporters in tea plants. In this study, genome-wide association study (GWAS) analysis of epigallocatechin gallate (EGCG) content in 108 strains of Kingbird revealed that CsABCCs may be involved in EGCG transport. We identified 25 CsABCC genes at the genomic level of the tea plant, their phylogenetic tree, gene structure, targeted miRNA and other bioinformatics… More >

S. Vidivelli^*, Manikandan Ramachandran^*, A. Dharunbalaji

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2423-2442, 2024, DOI:10.32604/cmc.2024.054360 - 15 August 2024

Abstract This exploration acquaints a momentous methodology with custom chatbot improvement that focuses on proficiency close by viability. We accomplish this by joining three key innovations: LangChain, Retrieval Augmented Generation (RAG), and enormous language models (LLMs) tweaked with execution proficient strategies like LoRA and QLoRA. LangChain takes into consideration fastidious fitting of chatbots to explicit purposes, guaranteeing engaged and important collaborations with clients. RAG’s web scratching capacities engage these chatbots to get to a tremendous store of data, empowering them to give exhaustive and enlightening reactions to requests. This recovered data is then decisively woven into… More >

Junqing Bai¹, Qiuchao Dai^1,*, Yingying Li²

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 5083-5103, 2024, DOI:10.32604/cmc.2024.050921 - 20 June 2024

Abstract To support the explosive growth of Information and Communications Technology (ICT), Mobile Edge Computing (MEC) provides users with low latency and high bandwidth service by offloading computational tasks to the network’s edge. However, resource-constrained mobile devices still suffer from a capacity mismatch when faced with latency-sensitive and compute-intensive emerging applications. To address the difficulty of running computationally intensive applications on resource-constrained clients, a model of the computation offloading problem in a network consisting of multiple mobile users and edge cloud servers is studied in this paper. Then a user benefit function EoU (Experience of Users) is… More >

Ayda Khadhri¹, Mohamed Mendili¹, Marwa Bannour-Scharinger¹, Eric Masson², Antonio Pizzi^2,*

Journal of Renewable Materials, Vol.12, No.4, pp. 827-842, 2024, DOI:10.32604/jrm.2024.046950 - 12 June 2024

Abstract This study is the first to evaluate the phytochemical content and biological properties of Tunisian T. platyphyllos Scop. A total of 23 compounds of essential oils were identified by gas chromatography-mass spectrometry (GC-MS) analysis of bracts and fruit extracts. The results show that oxygenated monoterpenes were the dominant class of essential oils. The phenolic composition was investigated by matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF). The analysis showed that the chemical profiles of the ethanolic extracts of bracts and fruits are substantially similar. The highest polyphenol content was found in the ethanolic extracts of the fruits (7.65… More > Graphic Abstract

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 - 28 March 2024

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 CAMTA genes on More >

Yunhe Wang¹, Yuxin Xia², Shuai Liu^2,*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4489-4507, 2024, DOI:10.32604/cmc.2024.048813 - 26 March 2024

Abstract In recent years, skeleton-based action recognition has made great achievements in Computer Vision. A graph convolutional network (GCN) is effective for action recognition, modelling the human skeleton as a spatio-temporal graph. Most GCNs define the graph topology by physical relations of the human joints. However, this predefined graph ignores the spatial relationship between non-adjacent joint pairs in special actions and the behavior dependence between joint pairs, resulting in a low recognition rate for specific actions with implicit correlation between joint pairs. In addition, existing methods ignore the trend correlation between adjacent frames within an action… More >

Pengchao Li^1,2,3,*, Fang Xu^1,2,3,4, Jintao Wang^1,2, Haibing Guo⁴, Mingmin Liu⁴, Zhenjun Du⁴

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1755-1771, 2024, DOI:10.32604/cmc.2023.047057 - 27 February 2024

Abstract We propose a novel image segmentation algorithm to tackle the challenge of limited recognition and segmentation performance in identifying welding seam images during robotic intelligent operations. Initially, to enhance the capability of deep neural networks in extracting geometric attributes from depth images, we developed a novel deep geometric convolution operator (DGConv). DGConv is utilized to construct a deep local geometric feature extraction module, facilitating a more comprehensive exploration of the intrinsic geometric information within depth images. Secondly, we integrate the newly proposed deep geometric feature module with the Fully Convolutional Network (FCN8) to establish a… More >

Yajing Ma^1,2,3, Gulila Altenbek^1,2,3,*, Yingxia Yu¹

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 695-712, 2024, DOI:10.32604/cmc.2023.045486 - 30 January 2024

Abstract Due to the structural dependencies among concurrent events in the knowledge graph and the substantial amount of sequential correlation information carried by temporally adjacent events, we propose an Independent Recurrent Temporal Graph Convolution Networks (IndRT-GCNets) framework to efficiently and accurately capture event attribute information. The framework models the knowledge graph sequences to learn the evolutionary representations of entities and relations within each period. Firstly, by utilizing the temporal graph convolution module in the evolutionary representation unit, the framework captures the structural dependency relationships within the knowledge graph in each period. Meanwhile, to achieve better event… More >