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  • Open Access

    ARTICLE

    High-Value-Added Utilization of Turpentine: Screening of Anti-Influenza Virus Agents from β-Pinene Derivatives

    Yiwen Li1,#, Hongyan Si1,#, Peng Wang1, Hai Luo1, Minggui Shen2, Xiaoping Rao3, Zhanqian Song2, Shibin Shang2, Zongde Wang1,*, Shengliang Liao1,*

    Journal of Renewable Materials, Vol.12, No.1, pp. 45-56, 2024, DOI:10.32604/jrm.2023.031089

    Abstract Turpentine is a renewable and resourceful forest product. The deep processing and utilization of turpentine, particularly its primary component β-pinene, has garnered widespread attention. This study aimed to synthesize 40 derivatives of β-pinene, including nopinone, 3-cyanopyridines of nopinone, myrtanyl acid, myrtanyl acylthioureas, and myrtanyl amides. We assessed the antiviral activities of these β-pinene derivatives against influenza virus A/Puerto Rico/8/34 (H1N1) using the 3-(4,5-dimetylthiazol-2-yl)-2,5-diphenyltetrazolium bromide method. The β-pinene derivatives were used before and after cellular infection with the influenza virus to evaluate their preventive and therapeutic effects against the H1N1 virus. The results showed that only compound 10o exhibited a preventive… More > Graphic Abstract

    High-Value-Added Utilization of Turpentine: Screening of Anti-Influenza Virus Agents from <i>β</i>-Pinene Derivatives

  • Open Access

    ARTICLE

    Swarming Computational Techniques for the Influenza Disease System

    Sakda Noinang1, Zulqurnain Sabir2, Gilder Cieza Altamirano3, Muhammad Asif Zahoor Raja4, Manuel Jesús Sànchez-Chero5, María-Verónica Seminario-Morales5, Wajaree Weera6,*, Thongchai Botmart6

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4851-4868, 2022, DOI:10.32604/cmc.2022.029437

    Abstract The current study relates to designing a swarming computational paradigm to solve the influenza disease system (IDS). The nonlinear system’s mathematical form depends upon four classes: susceptible individuals, infected people, recovered individuals and cross-immune people. The solutions of the IDS are provided by using the artificial neural networks (ANNs) together with the swarming computational paradigm-based particle swarm optimization (PSO) and interior-point scheme (IPA) that are the global and local search approaches. The ANNs-PSO-IPA has never been applied to solve the IDS. Instead a merit function in the sense of mean square error is constructed using the differential form of each… More >

  • Open Access

    ARTICLE

    Machine Learning-Based Two-Stage Data Selection Scheme for Long-Term Influenza Forecasting

    Jaeuk Moon, Seungwon Jung, Sungwoo Park, Eenjun Hwang*

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 2945-2959, 2021, DOI:10.32604/cmc.2021.017435

    Abstract One popular strategy to reduce the enormous number of illnesses and deaths from a seasonal influenza pandemic is to obtain the influenza vaccine on time. Usually, vaccine production preparation must be done at least six months in advance, and accurate long-term influenza forecasting is essential for this. Although diverse machine learning models have been proposed for influenza forecasting, they focus on short-term forecasting, and their performance is too dependent on input variables. For a country’s long-term influenza forecasting, typical surveillance data are known to be more effective than diverse external data on the Internet. We propose a two-stage data selection… More >

  • Open Access

    ARTICLE

    Integrated analysis of human influenza A (H1N1) virus infectionrelated genes to construct a suitable diagnostic model

    WENBIAO CHEN, KEFAN BI, JINGJING JIANG, XUJUN ZHANG, HONGYAN DIAO*

    BIOCELL, Vol.45, No.4, pp. 885-899, 2021, DOI:10.32604/biocell.2021.012938

    Abstract The genome characteristics and structural functions of coding proteins correlate with the genetic diversity of the H1N1 virus, which aids in the understanding of its underlying pathogenic mechanism. In this study, analyses of the characteristic of the H1N1 virus infection-related genes, their biological functions, and infection-related reversal drugs were performed. Additionally, we used multi-dimensional bioinformatics analysis to identify the key genes and then used these to construct a diagnostic model for the H1N1 virus infection. There was a total of 169 differently expressed genes in the samples between 21 h before infection and 77 h after infection. They were used… More >

  • Open Access

    ARTICLE

    Forecast the Influenza Pandemic Using Machine Learning

    Muhammad Adnan Khan1,*, Wajhe Ul Husnain Abidi1,2, Mohammed A. Al Ghamdi3, Sultan H. Almotiri3, Shazia Saqib1, Tahir Alyas1, Khalid Masood Khan1, Nasir Mahmood4

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 331-340, 2021, DOI:10.32604/cmc.2020.012148

    Abstract Forecasting future outbreaks can help in minimizing their spread. Influenza is a disease primarily found in animals but transferred to humans through pigs. In 1918, influenza became a pandemic and spread rapidly all over the world becoming the cause behind killing one-third of the human population and killing one-fourth of the pig population. Afterwards, that influenza became a pandemic several times on a local and global levels. In 2009, influenza ‘A’ subtype H1N1 again took many human lives. The disease spread like in a pandemic quickly. This paper proposes a forecasting modeling system for the influenza pandemic using a feed-forward… More >

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