Ramendra Pati Pandey – författare

Nanotherapeutics for Inflammatory Arthritis: Design, Diagnosis, and Treatment highlights nanobiotechnology and its therapeutic applications in the field of inflammatory arthritis, the interaction of nanomaterials in the biological systems, and clinical development of nanomedicines. It also covers the discovery of personalized therapeutics, diagnostics, and nanoparticular delivery systems, the role of bioinformatics nanobiotechnology in personalized oncology. The use of nanosensors for the detection and current challenges in the development of personalized medicine is explained including recent nanotechnology-based strategies.

Features:

This book is aimed at researchers and professionals in nanotechnology, biomaterial, drug delivery, and inflammatory arthritis.

Nanotherapeutics for Inflammatory Arthritis: Design, Diagnosis, and Treatment highlights nanobiotechnology and its therapeutic applications in the field of inflammatory arthritis, the interaction of nanomaterials in the biological systems, and clinical development of nanomedicines. It also covers the discovery of personalized therapeutics, diagnostics, and nanoparticular delivery systems, the role of bioinformatics nanobiotechnology in personalized oncology. The use of nanosensors for the detection and current challenges in the development of personalized medicine is explained including recent nanotechnology-based strategies.

Features:

This book is aimed at researchers and professionals in nanotechnology, biomaterial, drug delivery, and inflammatory arthritis.

This volume reviews the use of machine learning (ML) to predict antibiotic resistance in pathogens based on gene content and genome composition as data sets comprising hundreds or thousands of pathogen genomes become available. One of the main goals of this work is to promote the use of ML in front-line contexts while simultaneously emphasizing the additional improvements that are required to use these techniques in a secure and confident manner. Given the variety of quantitative and qualitative laboratory indicators of AMR, the issue of what to anticipate is not an easy one.

This book is intended for academia, students of medical science, microbiology, biology, and biotechnology, as well as experts and scientists working in the fields of infectious diseases, government health organizations, and medicine.

This volume reviews the use of machine learning (ML) to predict antibiotic resistance in pathogens based on gene content and genome composition as data sets comprising hundreds or thousands of pathogen genomes become available. One of the main goals of this work is to promote the use of ML in front-line contexts while simultaneously emphasizing the additional improvements that are required to use these techniques in a secure and confident manner. Given the variety of quantitative and qualitative laboratory indicators of AMR, the issue of what to anticipate is not an easy one.

This book is intended for academia, students of medical science, microbiology, biology, and biotechnology, as well as experts and scientists working in the fields of infectious diseases, government health organizations, and medicine.

This book integrates the latest advancements in biomedical science related to metabolic syndrome and microbiome research. It comprehensively covers a broad range of topics including composition and function of the gut microbiota in metabolic syndrome, mechanisms linking the gut microbiome to metabolic syndrome, dietary interventions, pharmacological approaches, exercise, lifestyle modifications, psychosocial factors, role of the gut microbiome in obesity and insulin resistance, and clinical applications and translational perspectives.  

Despite significant research on metabolic syndrome, its risk factors, therapeutic interventions and the role of microbiome, there is still lack of recent updates and massive efforts are required to update the information on these topics with special emphasis on potential interventions targeting the gut microbiome to mitigate metabolic syndrome risk. This book focuses on leveraging the intricate relationship between the microbiome, gut health, and metabolic syndrome, including dysbiosis, inflammation, impaired gut barrier function, mechanisms through which the gut microbiome influences metabolic syndrome including host-microbiota interactions, microbial metabolites, and immune modulation to develop innovative interventions aimed at improving overall health outcomes. The purpose of this research is to explore microbiome-based interventions that can positively influence gut ecology and mitigate the risk factors associated with metabolic syndrome. By understanding how specific dietary interventions, probiotics, prebiotics, and other microbiome-targeted therapies can modulate the gut microbiome, this work aims to develop effective strategies for optimizing gut health and metabolic function.

Through interdisciplinary collaboration and cutting-edge research methodologies, this work strives to pave the way for personalized approaches to healthcare that prioritize the microbiome as a key determinant of overall health and well-being. The principal audience for this book comprises of pharmacologists, microbiologists, clinical pharmacists, and toxicologists.