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Search Results (109)
  • Open Access


    Deoxynortryptoquivaline: A unique antiprostate cancer agent


    Oncology Research, Vol.31, No.6, pp. 845-853, 2023, DOI:10.32604/or.2023.030266

    Abstract The androgen receptor (AR) is a critical target in all the clinical stages of prostate cancer. To identify a new AR inhibitor, we constructed a new screening system using the androgen-dependent growth of prostate cancer cell lines as a screening indicator. We screened 50,000 culture broths of microorganisms using this screening system and found that the fermentation broth produced by a fungus inhibited androgen-dependent growth of human prostate cancer LNCaP cells without cytotoxicity. Purification of this culture medium was performed, and this resulted in deoxynortryptoquivaline (DNT) being identified as a novel inhibitor of AR function. DNT showed potent inhibition of… More > Graphic Abstract

    Deoxynortryptoquivaline: A unique antiprostate cancer agent

  • Open Access


    Identification of a dihydroorotate dehydrogenase inhibitor that inhibits cancer cell growth by proteomic profiling


    Oncology Research, Vol.31, No.6, pp. 833-844, 2023, DOI:10.32604/or.2023.030241

    Abstract Dihydroorotate dehydrogenase (DHODH) is a central enzyme of the de novo pyrimidine biosynthesis pathway and is a promising drug target for the treatment of cancer and autoimmune diseases. This study presents the identification of a potent DHODH inhibitor by proteomic profiling. Cell-based screening revealed that NPD723, which is reduced to H-006 in cells, strongly induces myeloid differentiation and inhibits cell growth in HL-60 cells. H-006 also suppressed the growth of various cancer cells. Proteomic profiling of NPD723-treated cells in ChemProteoBase showed that NPD723 was clustered with DHODH inhibitors. H-006 potently inhibited human DHODH activity in vitro, whereas NPD723 was approximately… More >

  • Open Access


    Molecular dynamics-driven exploration of peptides targeting SARS-CoV-2, with special attention on ACE2, S protein, Mpro, and PLpro: A review


    BIOCELL, Vol.47, No.8, pp. 1727-1742, 2023, DOI:10.32604/biocell.2023.029272

    Abstract Molecular dynamics (MD) simulation is a computational technique that analyzes the movement of a system of particles over a given period. MD can provide detailed information about the fluctuations and conformational changes of biomolecules at the atomic level over time. In recent years, MD has been widely applied to the discovery of peptides and peptide-like molecules that may serve as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) inhibitors. This review summarizes recent advances in such explorations, focusing on four protein targets: angiotensin-converting enzyme 2 (ACE2), spike protein (S protein), main protease (Mpro), and papain-like protease (PLpro). These four proteins are… More > Graphic Abstract

    Molecular dynamics-driven exploration of peptides targeting SARS-CoV-2, with special attention on ACE2, S protein, M<sup>pro</sup>, and PL<sup>pro</sup>: A review

  • Open Access


    AI Safety Approach for Minimizing Collisions in Autonomous Navigation

    Abdulghani M. Abdulghani, Mokhles M. Abdulghani, Wilbur L. Walters, Khalid H. Abed*

    Journal on Artificial Intelligence, Vol.5, pp. 1-14, 2023, DOI:10.32604/jai.2023.039786

    Abstract Autonomous agents can explore the environment around them when equipped with advanced hardware and software systems that help intelligent agents minimize collisions. These systems are developed under the term Artificial Intelligence (AI) safety. AI safety is essential to provide reliable service to consumers in various fields such as military, education, healthcare, and automotive. This paper presents the design of an AI safety algorithm for safe autonomous navigation using Reinforcement Learning (RL). Machine Learning Agents Toolkit (ML-Agents) was used to train the agent with a proximal policy optimizer algorithm with an intrinsic curiosity module (PPO + ICM). This training aims to improve AI… More >

  • Open Access


    New Nano Polymer Materials for Composite Exterior-Wall Coatings

    Yue Yu*

    FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.10, pp. 2681-2694, 2023, DOI:10.32604/fdmp.2023.028250

    Abstract A triethylenetetramine epoxy mixture was synthesized through the reaction of a low-molecular-weight liquid epoxy resin with triethylenetetramine (TETA). Then triethyltetramine (TETA) was injected dropwise into a propylene glycol methyl ether (PM) solution for chain extension reaction. A hydrophilic and flexible polyether segment was introduced into the hardener molecule. The effects of TETA/DGEPG, reaction temperature and reaction time on the epoxy conversion of polyethylene glycol diglycidyl ether (DGEPG) were studied. In addition, several alternate strategies to add epoxy resin to the high-speed dispersion machine and synthesize MEA DGEBA adduct (without catalyst and with bisphenol A diglycidyl ether epoxy resin) were compared.… More >

  • Open Access


    Targeting the “undruggable” cancer driver genes: Ras, myc, and tp53


    BIOCELL, Vol.47, No.7, pp. 1459-1472, 2023, DOI:10.32604/biocell.2023.028790

    Abstract The term “undruggable” is to describe molecules that are not targetable or at least hard to target pharmacologically. Unfortunately, some targets with potent oncogenic activity fall into this category, and currently little is known about how to solve this problem, which largely hampered drug research on human cancers. Ras, as one of the most common oncogenes, was previously considered “undruggable”, but in recent years, a few small molecules like Sotorasib (AMG-510) have emerged and proved their targeted anti-cancer effects. Further, myc, as one of the most studied oncogenes, and tp53, being the most common tumor suppressor genes, are both considered… More >

  • Open Access


    Implementation of Strangely Behaving Intelligent Agents to Determine Human Intervention During Reinforcement Learning

    Christopher C. Rosser, Wilbur L. Walters, Abdulghani M. Abdulghani, Mokhles M. Abdulghani, Khalid H. Abed*

    Journal on Artificial Intelligence, Vol.4, No.4, pp. 261-277, 2022, DOI:10.32604/jai.2022.039703

    Abstract Intrinsic motivation helps autonomous exploring agents traverse a larger portion of their environments. However, simulations of different learning environments in previous research show that after millions of timesteps of successful training, an intrinsically motivated agent may learn to act in ways unintended by the designer. This potential for unintended actions of autonomous exploring agents poses threats to the environment and humans if operated in the real world. We investigated this topic by using Unity’s Machine Learning Agent Toolkit (ML-Agents) implementation of the Proximal Policy Optimization (PPO) algorithm with the Intrinsic Curiosity Module (ICM) to train autonomous exploring agents in three… More >

  • Open Access


    Modélisation sémantique et programmation générative pour une simulation multi-agent dans le contexte de gestion de catastrophe

    Claire Prudhomme1 , Ana Roxin2 , Christophe Cruz2 , Frank Boochs1

    Revue Internationale de Géomatique, Vol.30, No.1, pp. 37-65, 2020, DOI:10.3166/rig.2020.00102

    Abstract Disaster management requires collaborative preparedness among the various stakeholders. Collaborative exercises aim to train stakeholders to apply the plans prepared and to identify potential problems and areas for improvement. As these exercises are costly, computer simulation is an interesting tool to optimize preparation through a wider variety of contexts. However, research on simulation and disaster management focuses on a particular problem rather than on the overall optimization of the plans prepared. This limitation is explained by the challenge of creating a simulation model that can represent and adapt to a wide variety of plans from various disciplines. The work presented… More >

  • Open Access


    Numérique versus symbolique

    Dialogue ontologique entre deux approches

    Hélène Mathian1, Lena Sanders2

    Revue Internationale de Géomatique, Vol.31, No.1, pp. 21-45, 2022, DOI:10.3166/RIG31.21-45

    Abstract The aim of this article is to compare a statistical approach, “geometric data analysis” (GDA), and a simulation approach, the multi-agent systems (MAS), considered as representative, respectively, of a numerical and a symbolic approach of modelling. The case study concerns segregation of scholar space in the Parisian area. First the different steps leading from a thematic question to the development of an operational model to analyze this question are presented. The central and essential role of a conceptual framework at the interface of both is shown. Indeed, before operationalisation, it is necessary to verify the compatibility between the theoretical backgrounds… More >

  • Open Access


    Real-Time Memory Data Optimization Mechanism of Edge IoT Agent

    Shen Guo*, Wanxing Sheng, Shuaitao Bai, Jichuan Zhang, Peng Wang

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 799-814, 2023, DOI:10.32604/iasc.2023.038330

    Abstract With the full development of disk-resident databases (DRDB) in recent years, it is widely used in business and transactional applications. In long-term use, some problems of disk databases are gradually exposed. For applications with high real-time requirements, the performance of using disk database is not satisfactory. In the context of the booming development of the Internet of things, domestic real-time databases have also gradually developed. Still, most of them only support the storage, processing, and analysis of data values with fewer data types, which can not fully meet the current industrial process control system data types, complex sources, fast update… More >

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