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  • Open Access

    COMMENTARY

    GlycoRNA: A new player in cellular communication

    HYUNG SEOK KIM*

    Oncology Research, Vol.33, No.5, pp. 995-1000, 2025, DOI:10.32604/or.2025.060616 - 18 April 2025

    Abstract The discovery of glycosylated RNA molecules, known as glycoRNAs, introduces a novel dimension to cellular biology. This commentary explores the transformative findings surrounding glycoRNAs, emphasizing their unique roles in cancer progression and the therapeutic opportunities they present. GlycoRNAs, through interactions with lectins and immune receptors, may contribute to tumor immune evasion. Moreover, the therapeutic potential of this emerging knowledge includes interventions targeting glycoRNA synthesis and modulation of associated signaling pathways. By highlighting these critical insights, this commentary aims to encourage the development of innovative strategies that could improve cancer prognosis and treatment. More >

  • Open Access

    ARTICLE

    End-to-End Audio Pattern Recognition Network for Overcoming Feature Limitations in Human-Machine Interaction

    Zijian Sun1,2, Yaqian Li3,4,*, Haoran Liu1,2, Haibin Li3,4, Wenming Zhang3,4

    CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 3187-3210, 2025, DOI:10.32604/cmc.2025.061920 - 16 April 2025

    Abstract In recent years, audio pattern recognition has emerged as a key area of research, driven by its applications in human-computer interaction, robotics, and healthcare. Traditional methods, which rely heavily on handcrafted features such as Mel filters, often suffer from information loss and limited feature representation capabilities. To address these limitations, this study proposes an innovative end-to-end audio pattern recognition framework that directly processes raw audio signals, preserving original information and extracting effective classification features. The proposed framework utilizes a dual-branch architecture: a global refinement module that retains channel and temporal details and a multi-scale embedding… More >

  • Open Access

    ARTICLE

    Multimodal Neural Machine Translation Based on Knowledge Distillation and Anti-Noise Interaction

    Erlin Tian1, Zengchao Zhu2,*, Fangmei Liu2, Zuhe Li2

    CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2305-2322, 2025, DOI:10.32604/cmc.2025.061145 - 16 April 2025

    Abstract Within the realm of multimodal neural machine translation (MNMT), addressing the challenge of seamlessly integrating textual data with corresponding image data to enhance translation accuracy has become a pressing issue. We saw that discrepancies between textual content and associated images can lead to visual noise, potentially diverting the model’s focus away from the textual data and so affecting the translation’s comprehensive effectiveness. To solve this visual noise problem, we propose an innovative KDNR-MNMT model. The model combines the knowledge distillation technique with an anti-noise interaction mechanism, which makes full use of the synthesized graphic knowledge… More >

  • Open Access

    ARTICLE

    CG-FCLNet: Category-Guided Feature Collaborative Learning Network for Semantic Segmentation of Remote Sensing Images

    Min Yao1,*, Guangjie Hu1, Yaozu Zhang2

    CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2751-2771, 2025, DOI:10.32604/cmc.2025.060860 - 16 April 2025

    Abstract Semantic segmentation of remote sensing images is a critical research area in the field of remote sensing. Despite the success of Convolutional Neural Networks (CNNs), they often fail to capture inter-layer feature relationships and fully leverage contextual information, leading to the loss of important details. Additionally, due to significant intra-class variation and small inter-class differences in remote sensing images, CNNs may experience class confusion. To address these issues, we propose a novel Category-Guided Feature Collaborative Learning Network (CG-FCLNet), which enables fine-grained feature extraction and adaptive fusion. Specifically, we design a Feature Collaborative Learning Module (FCLM)… More >

  • Open Access

    ARTICLE

    Association between Mental Distress and Weight-Related Self-Stigma via Problematic Social Media and Smartphone Use among Malaysian University Students: An Application of the Interaction of Person-Affect-Cognition- Execution (I-PACE) Model

    Wan Ying Gan1,#,*, Wei-Leng Chin2,3,#, Shih-Wei Huang4,5, Serene En Hui Tung6, Ling Jun Lee1, Wai Chuen Poon7, Yan Li Siaw8, Kerry S. O’Brien9, Iqbal Pramukti10, Kamolthip Ruckwongpatr11, Jung-Sheng Chen12, Mark D. Griffiths13, Chung-Ying Lin10,11,14,15,*

    International Journal of Mental Health Promotion, Vol.27, No.3, pp. 319-331, 2025, DOI:10.32604/ijmhp.2025.060049 - 31 March 2025

    Abstract Background: Weight-related self-stigma (WRSS) is prevalent among individuals with different types of weight status and is associated with a range of negative health outcomes. Social support and coping models explain how individuals may use different coping methods to deal with their mental health needs. Psychological distress (e.g., depression and stress) could lead to overuse of social media and smartphones. When using social media or smartphones, individuals are likely to be exposed to negative comments regarding weight/shape/size posted on the social media. Consequently, individuals who experience problematic social media use (PSMU) or problematic smartphone use (PSPU)… More >

  • Open Access

    REVIEW

    Impact of Soil Microbes and Abiotic Stress on Strawberry Root Physiology and Growth: A Review

    Hira Akhtar1, Akhtar Hameed1,*, Rana Binyamin1, Kashif Riaz2, Hafiz Muhammad Usman Aslam1,3, Faizan Ali4, Subhan Ali1, Zuniara Akash5, Muhammad Saqlain Zaheer6,*, Kamran Ikram6, Yasir Niaz6, Hafiz Haider Ali7,8

    Phyton-International Journal of Experimental Botany, Vol.94, No.3, pp. 561-581, 2025, DOI:10.32604/phyton.2025.061262 - 31 March 2025

    Abstract Strawberry (Fragaria ananassa) is well known among consumers because of its attractive color, delicious taste, and nutritional benefits. It is widely grown worldwide, but its production has become a significant challenge due to changing climatic conditions that lead to abiotic stresses in plants, which results in poor root development, nutrient deficiency, and poor plant health. In this context, the major abiotic stresses are temperature fluctuations, water shortages, and high levels of soil salinity. The accumulation of salts in excessive amounts disrupts the osmotic balance and impairs physiological processes. However, drought reduces fruit size, yield, and quality.… More >

  • Open Access

    ARTICLE

    Syntax-Enhanced Entity Relation Extraction with Complex Knowledge

    Mingwen Bi1, Hefei Chen2,*, Zhenghong Yang3,*

    CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 861-876, 2025, DOI:10.32604/cmc.2025.060517 - 26 March 2025

    Abstract Entity relation extraction, a fundamental and essential task in natural language processing (NLP), has garnered significant attention over an extended period., aiming to extract the core of semantic knowledge from unstructured text, i.e., entities and the relations between them. At present, the main dilemma of Chinese entity relation extraction research lies in nested entities, relation overlap, and lack of entity relation interaction. This dilemma is particularly prominent in complex knowledge extraction tasks with high-density knowledge, imprecise syntactic structure, and lack of semantic roles. To address these challenges, this paper presents an innovative “character-level” Chinese part-of-speech… More >

  • Open Access

    REVIEW

    Targeting MDM2-p53 interaction for breast cancer therapy

    AMJAD YOUSUF1, NAJEEB ULLAH KHAN2,*

    Oncology Research, Vol.33, No.4, pp. 851-861, 2025, DOI:10.32604/or.2025.058956 - 19 March 2025

    Abstract Breast cancer is a significant global concern, with limited effective treatment options. Therefore, therapies with high efficacy and low complications, unlike the existing chemotherapies, are urgently required. To address this issue, advances have been made in therapies targeting molecular pathways related to the murine double minute 2 proto-oncogene (MDM2)-tumor proteinp53 (TP53) interaction. This review aims to investigate the efficacy of MDM2 inhibition in restoring TP53 activity in breast cancer cells, as evidenced by clinical studies, reviews, and trials. TP53 is a tumor suppressor and MDM2 facilitates proteasomal degradation of TP53. MDM2 and TP53 activity More > Graphic Abstract

    Targeting MDM2-p53 interaction for breast cancer therapy

  • Open Access

    ARTICLE

    Delocalized Nonlinear Vibrational Modes in Bcc Lattice for Testing and Improving Interatomic Potentials

    Denis S. Ryabov1, Igor V. Kosarev2,3, Daxing Xiong4, Aleksey A. Kudreyko5, Sergey V. Dmitriev2,6,*

    CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 3797-3820, 2025, DOI:10.32604/cmc.2025.062079 - 06 March 2025

    Abstract Molecular dynamics (MD) is a powerful method widely used in materials science and solid-state physics. The accuracy of MD simulations depends on the quality of the interatomic potentials. In this work, a special class of exact solutions to the equations of motion of atoms in a body-centered cubic (bcc) lattice is analyzed. These solutions take the form of delocalized nonlinear vibrational modes (DNVMs) and can serve as an excellent test of the accuracy of the interatomic potentials used in MD modeling for bcc crystals. The accuracy of the potentials can be checked by comparing the… More >

  • Open Access

    ARTICLE

    Harmonization of Heart Disease Dataset for Accurate Diagnosis: A Machine Learning Approach Enhanced by Feature Engineering

    Ruhul Amin1, Md. Jamil Khan1, Tonway Deb Nath1, Md. Shamim Reza2, Jungpil Shin3,*

    CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 3907-3919, 2025, DOI:10.32604/cmc.2025.061645 - 06 March 2025

    Abstract Heart disease includes a multiplicity of medical conditions that affect the structure, blood vessels, and general operation of the heart. Numerous researchers have made progress in correcting and predicting early heart disease, but more remains to be accomplished. The diagnostic accuracy of many current studies is inadequate due to the attempt to predict patients with heart disease using traditional approaches. By using data fusion from several regions of the country, we intend to increase the accuracy of heart disease prediction. A statistical approach that promotes insights triggered by feature interactions to reveal the intricate pattern… More >

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