Cannabinoids ‘Cannabinoids’ is a broad term covering a group of natural products from Cannabis sativa, one of which locks on to specific receptors – protein molecules on the surface of cells – known as cannabinoid receptors. Over the past decades scientists have found that cannabinoid receptors and their endogenous ligands, the endocannabinoids, are involved in a vast array of physiological functions, including helping to control brain activity, energy metabolism, heart function, the immune system and even reproduction. In Cannabinoids, Vincenzo Di Marzo has assembled contributions from international experts to provide the definitive guide to what continues to be a rapidly developing research field. After an introductory historical chapter, the book continues by looking at the biochemical, genetic and molecular elements of cannabinoids, followed by chapters covering their role in health and disease. The final chapter outlines the need for a new nomenclature to reflect the complex and multi-disciplinary nature of this area. An authoritative guide to the history, development and possible future of cannabinoid research. Includes contributions from leading international experts in the field. Clearly written, well organised and logically presented. Cannabinoids will prove invaluable to researchers, practitioners and students across a wide range of disciplines, needing an up-to-date guide to this significant area of research.
Networks constitute the backbone of complex systems, from the human brain to computer communications, transport infrastructures to online social systems and metabolic reactions to financial markets. Characterising their structure improves our understanding of the physical, biological, economic and social phenomena that shape our world. Rigorous and thorough, this textbook presents a detailed overview of the new theory and methods of network science. Covering algorithms for graph exploration, node ranking and network generation, among others, the book allows students to experiment with network models and real-world data sets, providing them with a deep understanding of the basics of network theory and its practical applications. Systems of growing complexity are examined in detail, challenging students to increase their level of skill. An engaging presentation of the important principles of network science makes this the perfect reference for researchers and undergraduate and graduate students in physics, mathematics, engineering, biology, neuroscience and the social sciences.
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