Shariful Islam – författare

Nutritional Epigenetics: Food-Derived microRNAs in Health and Disease offers perspective on the role of dietary microRNAs as pivotal epigenetic regulators influencing health trajectories and disease susceptibility. The book brings together current research on the bioavailability and molecular mechanisms by which plant and food-derived microRNAs modulate gene expression, including their crosstalk with DNA methylation, histone modifications, and gut microbiota. Detailed food-specific chapters examine the epigenetic impact of key dietary sources such as Brassicaceae (crucifers), rice, milk, and fermented products, highlighting their transgenerational and life-stage effects. Practical insights into food processing, culinary traditions, and the design of microRNA-fortified products bridge the gap between bench science and real-world applications. Nutritional Epigenetics equips researchers, clinicians, and industry innovators with a resource that advances the understanding of microRNA-mediated nutritional epigenomics, while guiding the development and safety assessment of microRNA-enhanced functional foods. By integrating molecular biology with population-level evidence and translational strategies, this text fosters the development of novel dietary interventions aimed at optimizing health across the lifespan and mitigating chronic disease risk.Examines the molecular mechanisms by which dietary microRNAs modulate epigenetic regulationAnalyzes the bioavailability and gene-targeting specificity of plant-derived microRNAsEvaluates transgenerational and life-stage impacts of food-derived microRNAs on health outcomesInterprets current epidemiological evidence and regulatory policies relevant to microRNA-enhanced functional foodsDevelops strategies for designing and implementing microRNA-fortified foods in clinical and commercial contexts

This book represents a unique and comprehensive resource for understanding the intersection of advanced artificial intelligence (AI) and neurology. By focusing on graph neural networks (GNNs), the book addresses a crucial gap in the current literature, providing valuable insights into the analysis and interpretation of complex brain networks and neurological data. Intended for a diverse audience, including clinicians, scientists, researchers, and students, it demystifies the complexities of GNNs and their applications in neurology. For clinicians and healthcare practitioners, the book illustrates how GNNs can enhance diagnostic accuracy, inform personalized treatment plans and predict disease progression. This leads to improved patient outcomes and a deeper understanding of neurological conditions such as Alzheimer's, Parkinson's, multiple sclerosis and epilepsy. Researchers will find the book particularly valuable as it delves into the methodologies and technical aspects of GNNs, showcasing their ability to handle diverse data sources including genetic, imaging and clinical information. By integrating these datasets, GNNs reveal hidden patterns and biomarkers, offering new avenues for research and potential therapeutic targets.A Guide to Graph Neural Networks for Neurological Disorders addresses the challenge of missing data, a common issue in neurological research, and demonstrates how GNNs can manage and mitigate these gaps. For students, both undergraduate and postgraduate, the book serves as an educational tool, providing clear explanations and practical examples that make complex concepts accessible. It equips the next generation of neuroscientists and data scientists with the knowledge and skills needed to contribute to this rapidly evolving field. The book aims to provide a foundational understanding of GNNs, demonstrate their practical applications in neurology, and inspire further research and innovation. By bridging the gap between AI and medical practice, the book empowers readers to leverage cutting-edge technology in the quest to understand and treat neurological illnesses, ultimately enhancing the quality of care and advancing the field of neuroscience.

This book represents a unique and comprehensive resource for understanding the intersection of advanced artificial intelligence (AI) and neurology. By focusing on graph neural networks (GNNs), the book addresses a crucial gap in the current literature, providing valuable insights into the analysis and interpretation of complex brain networks and neurological data. Intended for a diverse audience, including clinicians, scientists, researchers, and students, it demystifies the complexities of GNNs and their applications in neurology. For clinicians and healthcare practitioners, the book illustrates how GNNs can enhance diagnostic accuracy, inform personalized treatment plans and predict disease progression. This leads to improved patient outcomes and a deeper understanding of neurological conditions such as Alzheimer's, Parkinson's, multiple sclerosis and epilepsy. Researchers will find the book particularly valuable as it delves into the methodologies and technical aspects of GNNs, showcasing their ability to handle diverse data sources including genetic, imaging and clinical information. By integrating these datasets, GNNs reveal hidden patterns and biomarkers, offering new avenues for research and potential therapeutic targets.A Guide to Graph Neural Networks for Neurological Disorders addresses the challenge of missing data, a common issue in neurological research, and demonstrates how GNNs can manage and mitigate these gaps. For students, both undergraduate and postgraduate, the book serves as an educational tool, providing clear explanations and practical examples that make complex concepts accessible. It equips the next generation of neuroscientists and data scientists with the knowledge and skills needed to contribute to this rapidly evolving field. The book aims to provide a foundational understanding of GNNs, demonstrate their practical applications in neurology, and inspire further research and innovation. By bridging the gap between AI and medical practice, the book empowers readers to leverage cutting-edge technology in the quest to understand and treat neurological illnesses, ultimately enhancing the quality of care and advancing the field of neuroscience.

Seminar paper from the year 2017 in the subject Pedagogy - Media Pedagogy, grade: 1.0, International Islamic University Malaysia, language: English, abstract: This paper aims to prove that gaming can enhance children's intellectual development by developing higher cognitive abilities using therapeutic interventions to target psychiatric disorders and improving multi-tasking abilities.