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  • Open Access

    REVIEW

    Omics sciences for cervical cancer precision medicine from the perspective of the tumor immune microenvironment

    GUANTING PANG1,4,#, YAOHAN LI2,4,#, QIWEN SHI3, JINGKUI TIAN4, HANMEI LOU4,5,*, YUE FENG4,5,*

    Oncology Research, Vol.33, No.4, pp. 821-836, 2025, DOI:10.32604/or.2024.053772 - 19 March 2025

    Abstract Immunotherapies have demonstrated notable clinical benefits in the treatment of cervical cancer (CC). However, the development of therapeutic resistance and diverse adverse effects in immunotherapy stem from complex interactions among biological processes and factors within the tumor immune microenvironment (TIME). Advanced omic technologies offer novel insights into a more expansive and thorough layer of the TIME. Furthermore, integrating multidimensional omics within the frameworks of systems biology and computational methodologies facilitates the generation of interpretable data outputs to characterize the clinical and biological trajectories of tumor behavior. In this review, we present advanced omics technologies that More >

  • Open Access

    ARTICLE

    A Nomogram for Predicting Survival for Patients with Brain Metastatic and EGFR Mutation Advanced Non-Small Cell Lung Cancer

    JIYUN PANG1,2,#, WEIGANG XIU1,#, YUEYUN CHEN4, WENJING LIAO1,2, QIN ZHANG3,*, HUASHAN SHI4,*

    Oncology Research, Vol.33, No.4, pp. 895-904, 2025, DOI:10.32604/or.2024.053363 - 19 March 2025

    Abstract Background: Non-small cell lung cancer (NSCLC) is often accompanied by brain metastasis (BM), and the prognosis of patients with BM is poor. This study assesses the prognostic impact of BM in NSCLC patients with epidermal growth factor receptor (EGFR) mutations. Methods: We retrospectively evaluated 692 advanced NSCLC patients with EGFR mutations treated with tyrosine kinase inhibitors (TKIs) at West China Hospital from 2015 to 2019. The overall survival rate (OS), progression-free survival rate (PFS), objective response rate (ORR), disease control rate (DCR), and clinical parameters of the BM and non-BM groups were compared. Univariable and multivariable… More >

  • Open Access

    ARTICLE

    An Intrusion Detection System Based on HiTar-2024 Dataset Generation from LOG Files for Smart Industrial Internet-of-Things Environment

    Tarak Dhaouadi1, Hichem Mrabet1,2,*, Adeeb Alhomoud3, Abderrazak Jemai1,4

    CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4535-4554, 2025, DOI:10.32604/cmc.2025.060935 - 06 March 2025

    Abstract The increasing adoption of Industrial Internet of Things (IIoT) systems in smart manufacturing is leading to raise cyberattack numbers and pressing the requirement for intrusion detection systems (IDS) to be effective. However, existing datasets for IDS training often lack relevance to modern IIoT environments, limiting their applicability for research and development. To address the latter gap, this paper introduces the HiTar-2024 dataset specifically designed for IIoT systems. As a consequence, that can be used by an IDS to detect imminent threats. Likewise, HiTar-2024 was generated using the AREZZO simulator, which replicates realistic smart manufacturing scenarios.… More >

  • Open Access

    ARTICLE

    Modified Neural Network Used for Host Utilization Predication in Cloud Computing Environment

    Arif Ullah1, Siti Fatimah Abdul Razak2,*, Sumendra Yogarayan2, Md Shohel Sayeed2

    CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 5185-5204, 2025, DOI:10.32604/cmc.2025.059355 - 06 March 2025

    Abstract Networking, storage, and hardware are just a few of the virtual computing resources that the infrastructure service model offers, depending on what the client needs. One essential aspect of cloud computing that improves resource allocation techniques is host load prediction. This difficulty means that hardware resource allocation in cloud computing still results in hosting initialization issues, which add several minutes to response times. To solve this issue and accurately predict cloud capacity, cloud data centers use prediction algorithms. This permits dynamic cloud scalability while maintaining superior service quality. For host prediction, we therefore present a… More >

  • Open Access

    ARTICLE

    Evaluation of Some Egyptian Barley Cultivars Resistance to Foliar Fungal Diseases in Drought-Prone Environments under Field Conditions

    Sally Negm1, Badwy Mohdly2, Motrih Al-Mutiry3, Wael Shehata4, Karima Ahmed5, Mohamed Abou-Zeid2,*, Rana Elessawy6, Ashgan Abdel-Azim5, Amr Abdel-Fattah2, Amani Omar Abuzaid7, Enas A. Almanzalawi7, Tahani M. Alqahtani7, Shouaa A. Alrobaish8, Diaa Abd El Moneim9, Ahmed M. Abbas10,11, Mohammed O. Alshaharni10, Huda Alghamdi10, Shaimaa G. Salama12, Kairy Amer5

    Phyton-International Journal of Experimental Botany, Vol.94, No.2, pp. 347-377, 2025, DOI:10.32604/phyton.2025.057448 - 06 March 2025

    Abstract Barley (Hordeum vulgare L.) is a significant global crop that thrives in various climatic and drought-stress conditions. Furthermore, increased drought intervals and more significant weather variability resulting from climate change can affect the severity of plant diseases. Therefore, two primary objectives of integrated disease management regarding climate change are identifying cultivars resistant to foliar diseases and understanding disease progression under abiotic stress. In the current study, we assessed the quantitative foliar disease resistance of 17 commercial barley cultivars under both normal and water stress conditions over two growing seasons (from 2020/21 to 2021/22). The findings demonstrated… More >

  • Open Access

    ARTICLE

    Childhood Environmental Unpredictability and Psychopathy: Mediating Roles of Insecure Attachment and Life History Strategy

    Fengbo Guo1,2,3,#, Leru Zhong1,#, Xingru Huang1, Zewei Chen1, Xiaoyuan Sun1,3,*

    International Journal of Mental Health Promotion, Vol.27, No.2, pp. 111-124, 2025, DOI:10.32604/ijmhp.2025.058874 - 03 March 2025

    Abstract Background: Childhood environmental unpredictability (CEU) is crucial to personal development, profoundly influence physical and psychological growth particularly, and psychopathy is recognized as a dark personality trait. The aim of this study is to investigate the effects of insecure attachment and life history strategy (LHS) on the relationship between CEU and psychopathy by establishing a sequential mediation model based on evolutionary life history theory and cognitive-affective personality system. Methods: A group of 532 undergraduates completed the measurements for CEU, insecure attachment, LHS, and psychopathy, and Bootstrap mediation test through SPSS 25.0 and PROCESS macro tool was… More >

  • Open Access

    ARTICLE

    A Bioinspired Method for Optimal Task Scheduling in Fog-Cloud Environment

    Ferzat Anka1, Ghanshyam G. Tejani2,3,*, Sunil Kumar Sharma4, Mohammed Baljon5

    CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 2691-2724, 2025, DOI:10.32604/cmes.2025.061522 - 03 March 2025

    Abstract Due to the intense data flow in expanding Internet of Things (IoT) applications, a heavy processing cost and workload on the fog-cloud side become inevitable. One of the most critical challenges is optimal task scheduling. Since this is an NP-hard problem type, a metaheuristic approach can be a good option. This study introduces a novel enhancement to the Artificial Rabbits Optimization (ARO) algorithm by integrating Chaotic maps and Levy flight strategies (CLARO). This dual approach addresses the limitations of standard ARO in terms of population diversity and convergence speed. It is designed for task scheduling… More >

  • Open Access

    ARTICLE

    ANNDRA-IoT: A Deep Learning Approach for Optimal Resource Allocation in Internet of Things Environments

    Abdullah M. Alqahtani1,*, Kamran Ahmad Awan2, Abdulaziz Almaleh3, Osama Aletri4

    CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 3155-3179, 2025, DOI:10.32604/cmes.2025.061472 - 03 March 2025

    Abstract Efficient resource management within Internet of Things (IoT) environments remains a pressing challenge due to the increasing number of devices and their diverse functionalities. This study introduces a neural network-based model that uses Long-Short-Term Memory (LSTM) to optimize resource allocation under dynamically changing conditions. Designed to monitor the workload on individual IoT nodes, the model incorporates long-term data dependencies, enabling adaptive resource distribution in real time. The training process utilizes Min-Max normalization and grid search for hyperparameter tuning, ensuring high resource utilization and consistent performance. The simulation results demonstrate the effectiveness of the proposed method, More >

  • Open Access

    REVIEW

    Targeting myeloid-derived suppressor cells in the tumor microenvironment: potential therapeutic approaches for osteosarcoma

    HYE IN KA#, SE HWAN MUN#, SORA HAN#, YOUNG YANG*

    Oncology Research, Vol.33, No.3, pp. 519-531, 2025, DOI:10.32604/or.2024.056860 - 28 February 2025

    Abstract Osteosarcoma is a bone malignancy characterized by strong invasiveness and rapid disease progression. The tumor microenvironment of osteosarcoma contains various types of immune cells, including myeloid-derived suppressor cells, macrophages, T cells, and B cells. Imbalances of these immune cells can promote the proliferation and metastasis of osteosarcoma. Recent studies have indicated a substantial increase in the levels of myeloid-derived suppressor cells, an immune cell associated with immunosuppressive and pro-cancer effects, in the peripheral blood of patients with osteosarcoma. Moreover, the levels of the pro-inflammatory cytokine interleukin 18 are positively correlated with those of myeloid-derived suppressor More >

  • Open Access

    REVIEW

    Lignocellulosic Biocomposite Membranes for Air Filtration and Environmental Protection: A Review

    Abiodun Abdulhameed Amusa1,*, Anwar Johari1, Kamil Kayode Katibi2,3, Ibrahim Garba Shitu4,5, Abdulrahman Oyekanmi Adeleke6, Mohd Fairus Mohd Yasin7, Muhammad Thalhah Zainal8

    Journal of Renewable Materials, Vol.13, No.2, pp. 251-272, 2025, DOI:10.32604/jrm.2025.057487 - 20 February 2025

    Abstract The increasing severity of air pollution necessitates more effective and sustained air filtration technology. Concurrently, the desire for more environmentally friendly, sustainable materials with better filtering performance and less environmental impact drives the move away from conventional synthetic membranes. This review presents lignocellulosic biocomposite (LigBioComp) membranes as an alternative to traditional synthetic membranes. It focuses on their materials, fabrication, and functionalization techniques while exploring challenges and proposing methods for resourceful utilization. Renowned for their abundance and renewable nature, lignocellulosic materials consist of cellulose, hemicellulose, and lignin. Various applications can benefit from their antibacterial properties,… More > Graphic Abstract

    Lignocellulosic Biocomposite Membranes for Air Filtration and Environmental Protection: A Review

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