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  • Open Access


    Biological function of miRNA-145-5p in angiotensin II induced renal inflammation


    BIOCELL, Vol.48, No.4, pp. 601-611, 2024, DOI:10.32604/biocell.2024.047404

    Abstract Objective: Chronic kidney disease (CKD) is a progressive disorder characterized by intricate structural and functional alterations in the kidneys, attributable to diverse causative factors. Notably, the therapeutic promise of miR-145-5p in addressing renal pathologies has been discerned. This investigation seeks to elucidate the functional role of miR-145-5p in injured kidneys by subjecting human glomerular mesangial cells (HGMCs) to stimulation with Angiotensin II (AngII). Materials and Methods: Cellular viability and the levels of inflammatory mediators were evaluated utilizing Cell Counting Kit-8 (CCK-8), quantitative real-time polymerase chain reaction (qRT-PCR), and western blot methodologies, both in the presence of AngII incubation and in… More >

  • Open Access


    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


    Plant Nitrogen Metabolism: Balancing Resilience to Nutritional Stress and Abiotic Challenges

    Muhammad Farhan1,#, Manda Sathish2, Rafia Kiran1, Aroosa Mushtaq3, Alaa Baazeem4, Ammarah Hasnain5, Fahad Hakim1, Syed Atif Hasan Naqvi1,#,*, Mustansar Mubeen6, Yasir Iftikhar6,*, Aqleem Abbas7, Muhammad Zeeshan Hassan1, Mahmoud Moustafa8

    Phyton-International Journal of Experimental Botany, Vol.93, No.3, pp. 581-609, 2024, DOI:10.32604/phyton.2024.046857


    Plant growth and resilience to abiotic stresses, such as soil salinity and drought, depend intricately on nitrogen metabolism. This review explores nitrogen’s regulatory role in plant responses to these challenges, unveiling a dynamic interplay between nitrogen availability and abiotic stress. In the context of soil salinity, a nuanced relationship emerges, featuring both antagonistic and synergistic interactions between salinity and nitrogen levels. Salinity-induced chlorophyll depletion in plants can be alleviated by optimal nitrogen supplementation; however, excessive nitrogen can exacerbate salinity stress. We delve into the complexities of this interaction and its agricultural implications. Nitrogen, a vital element within essential plant structures… More >

  • Open Access


    A Security Trade-Off Scheme of Anomaly Detection System in IoT to Defend against Data-Tampering Attacks

    Bing Liu1, Zhe Zhang1, Shengrong Hu2, Song Sun3,*, Dapeng Liu4, Zhenyu Qiu5

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4049-4069, 2024, DOI:10.32604/cmc.2024.048099

    Abstract Internet of Things (IoT) is vulnerable to data-tampering (DT) attacks. Due to resource limitations, many anomaly detection systems (ADSs) for IoT have high false positive rates when detecting DT attacks. This leads to the misreporting of normal data, which will impact the normal operation of IoT. To mitigate the impact caused by the high false positive rate of ADS, this paper proposes an ADS management scheme for clustered IoT. First, we model the data transmission and anomaly detection in clustered IoT. Then, the operation strategy of the clustered IoT is formulated as the running probabilities of all ADSs deployed on… More >

  • Open Access


    Federated Machine Learning Based Fetal Health Prediction Empowered with Bio-Signal Cardiotocography

    Muhammad Umar Nasir1, Omar Kassem Khalil2, Karamath Ateeq3, Bassam SaleemAllah Almogadwy4, Muhammad Adnan Khan5, Muhammad Hasnain Azam6, Khan Muhammad Adnan7,*

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3303-3321, 2024, DOI:10.32604/cmc.2024.048035

    Abstract Cardiotocography measures the fetal heart rate in the fetus during pregnancy to ensure physical health because cardiotocography gives data about fetal heart rate and uterine shrinkages which is very beneficial to detect whether the fetus is normal or suspect or pathologic. Various cardiotocography measures infer wrongly and give wrong predictions because of human error. The traditional way of reading the cardiotocography measures is the time taken and belongs to numerous human errors as well. Fetal condition is very important to measure at numerous stages and give proper medications to the fetus for its well-being. In the current period Machine learning… More >

  • Open Access


    BSTFNet: An Encrypted Malicious Traffic Classification Method Integrating Global Semantic and Spatiotemporal Features

    Hong Huang1, Xingxing Zhang1,*, Ye Lu1, Ze Li1, Shaohua Zhou2

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3929-3951, 2024, DOI:10.32604/cmc.2024.047918

    Abstract While encryption technology safeguards the security of network communications, malicious traffic also uses encryption protocols to obscure its malicious behavior. To address the issues of traditional machine learning methods relying on expert experience and the insufficient representation capabilities of existing deep learning methods for encrypted malicious traffic, we propose an encrypted malicious traffic classification method that integrates global semantic features with local spatiotemporal features, called BERT-based Spatio-Temporal Features Network (BSTFNet). At the packet-level granularity, the model captures the global semantic features of packets through the attention mechanism of the Bidirectional Encoder Representations from Transformers (BERT) model. At the byte-level granularity,… More >

  • Open Access


    Enhancing Energy Efficiency with a Dynamic Trust Measurement Scheme in Power Distribution Network

    Yilei Wang1, Xin Sun1, Guiping Zheng2,3, Ahmar Rashid4, Sami Ullah5, Hisham Alasmary6, Muhammad Waqas7,8,*

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3909-3927, 2024, DOI:10.32604/cmc.2024.047767

    Abstract The application of Intelligent Internet of Things (IIoT) in constructing distribution station areas strongly supports platform transformation, upgrade, and intelligent integration. The sensing layer of IIoT comprises the edge convergence layer and the end sensing layer, with the former using intelligent fusion terminals for real-time data collection and processing. However, the influx of multiple low-voltage in the smart grid raises higher demands for the performance, energy efficiency, and response speed of the substation fusion terminals. Simultaneously, it brings significant security risks to the entire distribution substation, posing a major challenge to the smart grid. In response to these challenges, a… More >

  • Open Access


    Data Secure Storage Mechanism for IIoT Based on Blockchain

    Jin Wang1,2, Guoshu Huang1, R. Simon Sherratt3, Ding Huang4, Jia Ni4,*

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4029-4048, 2024, DOI:10.32604/cmc.2024.047468

    Abstract With the development of Industry 4.0 and big data technology, the Industrial Internet of Things (IIoT) is hampered by inherent issues such as privacy, security, and fault tolerance, which pose certain challenges to the rapid development of IIoT. Blockchain technology has immutability, decentralization, and autonomy, which can greatly improve the inherent defects of the IIoT. In the traditional blockchain, data is stored in a Merkle tree. As data continues to grow, the scale of proofs used to validate it grows, threatening the efficiency, security, and reliability of blockchain-based IIoT. Accordingly, this paper first analyzes the inefficiency of the traditional blockchain… More >

  • Open Access


    A Framework for Enhancing Privacy and Anonymity in Blockchain-Enabled IoT Devices

    Muhammad Saad1, Muhammad Raheel Bhutta2, Jongik Kim3,*, Tae-Sun Chung1

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4263-4282, 2024, DOI:10.32604/cmc.2024.047132

    Abstract With the increase in IoT (Internet of Things) devices comes an inherent challenge of security. In the world today, privacy is the prime concern of every individual. Preserving one’s privacy and keeping anonymity throughout the system is a desired functionality that does not come without inevitable trade-offs like scalability and increased complexity and is always exceedingly difficult to manage. The challenge is keeping confidentiality and continuing to make the person innominate throughout the system. To address this, we present our proposed architecture where we manage IoT devices using blockchain technology. Our proposed architecture works on and off blockchain integrated with… More >

  • Open Access


    CL2ES-KDBC: A Novel Covariance Embedded Selection Based on Kernel Distributed Bayes Classifier for Detection of Cyber-Attacks in IoT Systems

    Talal Albalawi, P. Ganeshkumar*

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3511-3528, 2024, DOI:10.32604/cmc.2024.046396

    Abstract The Internet of Things (IoT) is a growing technology that allows the sharing of data with other devices across wireless networks. Specifically, IoT systems are vulnerable to cyberattacks due to its opennes The proposed work intends to implement a new security framework for detecting the most specific and harmful intrusions in IoT networks. In this framework, a Covariance Linear Learning Embedding Selection (CL2ES) methodology is used at first to extract the features highly associated with the IoT intrusions. Then, the Kernel Distributed Bayes Classifier (KDBC) is created to forecast attacks based on the probability distribution value precisely. In addition, a… More >

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