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  • Open Access

    ARTICLE

    One Novel Nortriterpenoid from the Mastic (Pistacia lentiscus) and Its Anti-Inflammatory Activity

    Yan Wu1, Xuerui An1, Haofan Lv1, Zhiqiang Zhao1, Wei Liu1,2,*, Chunpeng Wan1,3,*

    Phyton-International Journal of Experimental Botany, Vol.94, No.1, pp. 199-207, 2025, DOI:10.32604/phyton.2025.059581 - 24 January 2025

    Abstract A novel pair of oleanane nor-triterpenes, with compound 1 featuring a unique 18α-H structure, was isolated from mastic, and this compound represents a noteworthy new entity not previously reported in the literature. The absolute configurations of their structures were further determined using a combination of different analytical methods such as NMR, high-resolution mass spectrometry (HR-MS), ultraviolet (UV), infrared (IR) and single-crystal X-ray diffraction (SXRD). The compound actively mitigated inflammations by efficiently quenching nitric oxide (NO) synthesis within an ex vivo system using lipopolysaccharide activated murine macrophage RAW264.7 cells. Moreover, compound 1 exhibit a better IC50 concentration of More >

  • Open Access

    ARTICLE

    Encapsulation of Clove Oil Nanoemlusion in Chitosan-Based Nano-Composite: In Vitro and in Vivo Antifungal Activity against Rhizoctonia solani and Sclerotium rolfsii

    Ahmed Mahmoud Ismail1,2,3,*, Eman Said Elshewy3, Isra H. Ali4,5, Naglaa Abd Elbaki Sallam Muhanna3, Eman Yehia Khafagi3

    Phyton-International Journal of Experimental Botany, Vol.93, No.11, pp. 2787-2811, 2024, DOI:10.32604/phyton.2024.057518 - 30 November 2024

    Abstract Rhizoctonia solani Kühn and Sclerotium rolfsii Sacc. are the primary soil-borne plant diseases responsible for significant reductions in global crop yields. The primary goal of this study was to investigate the antifungal potentials of clove essential oil (CEO), nanoemulsion form (CEONE) and chitosan/nanoemulsion nanocomposite (CS/CEONE) against R. solani and S. rolfsii through in vitro and in vivo trials. Both CEONE and CS/CEONE were prepared and investigated for their physical chemical and morphological characterization. The poisoned medium method was utilized to evaluate the inhibitory effects of CEO, CEONE and CS/CEONE on the mycelial growth and enzymatic activity of R. solani and S. rolfsii. The… More >

  • Open Access

    ARTICLE

    Phytochemical and Pharmacological Study on the Dry Extract of Matricaria discoidea DC. herb and Its Amino Acids Preparations

    Oleh Koshovyi1,2,*, Janne Sepp1, Valdas Jakštas3, Vaidotas Žvikas3, Karina Tolmacheva4, Igor Kireyev4, Jyrki Heinämäki1, Ain Raal1,*

    Phyton-International Journal of Experimental Botany, Vol.93, No.11, pp. 2909-2925, 2024, DOI:10.32604/phyton.2024.056536 - 30 November 2024

    Abstract Pineappleweed (Matricaria discoidea DC., Asteraceae) herb is an essential oil containing raw material with spasmolytic and anti-inflammatory activity. It is also rich in phenolics, which may be used in pharmaceutical practice. This study aimed to investigate the phenolic and amino acid composition and the hyporific and analgesic effects of the M. discoidea aqueous-ethanolic extract and its amino acid modifications. In addition, we developed a polyethylene oxide gel formulation with M. discoidea extracts for the 3D-printed oral solid dosage preparations. In M. discoidea extracts, 16 phenolic substances and 14 amino acids were established. The extract and its amino acid preparations More >

  • Open Access

    ARTICLE

    An Investigation of Frequency-Domain Pruning Algorithms for Accelerating Human Activity Recognition Tasks Based on Sensor Data

    Jian Su1, Haijian Shao1,2,*, Xing Deng1, Yingtao Jiang2

    CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2219-2242, 2024, DOI:10.32604/cmc.2024.057604 - 18 November 2024

    Abstract The rapidly advancing Convolutional Neural Networks (CNNs) have brought about a paradigm shift in various computer vision tasks, while also garnering increasing interest and application in sensor-based Human Activity Recognition (HAR) efforts. However, the significant computational demands and memory requirements hinder the practical deployment of deep networks in resource-constrained systems. This paper introduces a novel network pruning method based on the energy spectral density of data in the frequency domain, which reduces the model’s depth and accelerates activity inference. Unlike traditional pruning methods that focus on the spatial domain and the importance of filters, this… More >

  • Open Access

    ARTICLE

    Robust Human Interaction Recognition Using Extended Kalman Filter

    Tanvir Fatima Naik Bukht1, Abdulwahab Alazeb2, Naif Al Mudawi2, Bayan Alabdullah3, Khaled Alnowaiser4, Ahmad Jalal1, Hui Liu5,*

    CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2987-3002, 2024, DOI:10.32604/cmc.2024.053547 - 18 November 2024

    Abstract In the field of computer vision and pattern recognition, knowledge based on images of human activity has gained popularity as a research topic. Activity recognition is the process of determining human behavior based on an image. We implemented an Extended Kalman filter to create an activity recognition system here. The proposed method applies an HSI color transformation in its initial stages to improve the clarity of the frame of the image. To minimize noise, we use Gaussian filters. Extraction of silhouette using the statistical method. We use Binary Robust Invariant Scalable Keypoints (BRISK) and SIFT More >

  • Open Access

    ARTICLE

    Exploring the therapeutic potential of precision T-Cell Receptors (TCRs) in targeting KRAS G12D cancer through in vitro development

    WEITAO ZHENG1, DONG JIANG2, SONGEN CHEN1, MEILING WU1, BAOQI YAN2, JIAHUI ZHAI2, YUNQIANG SHI2, BIN XIE1, XINGWANG XIE2, KANGHONG HU1,*, WENXUE MA3,*

    Oncology Research, Vol.32, No.12, pp. 1837-1850, 2024, DOI:10.32604/or.2024.056565 - 13 November 2024

    Abstract Objectives: The Kirsten rat sarcoma virus (KRAS) G12D oncogenic mutation poses a significant challenge in treating solid tumors due to the lack of specific and effective therapeutic interventions. This study aims to explore innovative approaches in T cell receptor (TCR) engineering and characterization to target the KRAS G12D7-16 mutation, providing potential strategies for overcoming this therapeutic challenge. Methods: In this innovative study, we engineered and characterized two T cell receptors (TCRs), KDA11-01 and KDA11-02 with high affinity for the KRAS G12D7-16 mutation. These TCRs were isolated from tumor-infiltrating lymphocytes (TILs) derived from tumor tissues of patients More >

  • Open Access

    ARTICLE

    Associations between Physical Activity, Depression, Self-Esteem, and Suicide Ideation in Adolescents

    Dojin An1, Nguyen Hoang Minh Thuan2, Youngho Kim1,*

    International Journal of Mental Health Promotion, Vol.26, No.10, pp. 847-853, 2024, DOI:10.32604/ijmhp.2024.055568 - 31 October 2024

    Abstract Background: In contemporary society, it has been widely witnessed that a surprising number of adolescents suffer emotional and mental health problems, and such turmoil is very often carried over into adulthood with serious implications for adjustment during the post-adolescent years. The purpose of the current study is to investigate the associations of physical activity with self-esteem, depression, and suicidal ideation. In addition, this study examined whether self-esteem and depression mediate the relationship between physical activity and suicide ideation in adolescents. Methods: The study participants were 946 (male: 527, female: 419) who attended junior high and… More >

  • Open Access

    ARTICLE

    Modeling of the Adsorption Allowing for the Changing Adsorbent Activity at Various Stages of the Process

    Marat Satayev1,2,*, Abdugani Azimov2, Arnold Brener2, Nina Alekseyeva1, Zulfia Shakiryanova2

    Frontiers in Heat and Mass Transfer, Vol.22, No.5, pp. 1533-1558, 2024, DOI:10.32604/fhmt.2024.052901 - 30 October 2024

    Abstract The goal of this work is, first of all, to construct a mathematical model of the mass transfer process in porous adsorption layers, taking into account the fact that in most cases the adsorption process is carried out in non-stationary technological modes, which requires a clear description of its various stages. The scientific contribution of the novel model is based on a probability approach allowing for deriving a differential equation that takes into account the diffusion migration of adsorbed particles. Solving this equation allows us to calculate the reduced degree of the adsorption surface coverage… More >

  • Open Access

    ARTICLE

    Virtual Assembly Collision Detection Algorithm Using Backpropagation Neural Network

    Baowei Wang1,2,*, Wen You2

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1085-1100, 2024, DOI:10.32604/cmc.2024.055538 - 15 October 2024

    Abstract As computer graphics technology continues to advance, Collision Detection (CD) has emerged as a critical element in fields such as virtual reality, computer graphics, and interactive simulations. CD is indispensable for ensuring the fidelity of physical interactions and the realism of virtual environments, particularly within complex scenarios like virtual assembly, where both high precision and real-time responsiveness are imperative. Despite ongoing developments, current CD techniques often fall short in meeting these stringent requirements, resulting in inefficiencies and inaccuracies that impede the overall performance of virtual assembly systems. To address these limitations, this study introduces a… More >

  • Open Access

    ARTICLE

    Efficient Real-Time Devices Based on Accelerometer Using Machine Learning for HAR on Low-Performance Microcontrollers

    Manh-Tuyen Vi1, Duc-Nghia Tran2, Vu Thi Thuong3,4, Nguyen Ngoc Linh5,*, Duc-Tan Tran1,*

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1729-1756, 2024, DOI:10.32604/cmc.2024.055511 - 15 October 2024

    Abstract Analyzing physical activities through wearable devices is a promising research area for improving health assessment. This research focuses on the development of an affordable and real-time Human Activity Recognition (HAR) system designed to operate on low-performance microcontrollers. The system utilizes data from a body-worn accelerometer to recognize and classify human activities, providing a cost-effective, easy-to-use, and highly accurate solution. A key challenge addressed in this study is the execution of efficient motion recognition within a resource-constrained environment. The system employs a Random Forest (RF) classifier, which outperforms Gradient Boosting Decision Trees (GBDT), Support Vector Machines… More >

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