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Oct 162017
 

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Oct 142017
 

Sigma Proteins: Evolution of the Concept of Sigma Receptors (Handbook of Experimental Pharmacology)


Two sigma receptor subtypes have been proposed, sigma1 and 2. Much of our understanding of this system is based on biochemical and pharmacological characterization of the cloned sigma1 receptor subtype (Sigma1). It has become clear that sigma receptors are not canonical receptors. Sigma1 is highly conserved among mammalian species, however, it does not share significant homology with any other mammalian protein. Although a range of structurally diverse small molecules bind Sigma1 with high affinity, and it has been associated with a broad range of signaling systems, Sigma1 itself has no known signaling or enzymatic activity. The evolution of this field over nearly four decades has more recently led to a fundamental shift in the concept of “sigma receptors” to what may more accurately and generally be called sigma proteins. Largely based on traditional pharmacologic approaches, the Sigma1 protein has been associated with a broad range of signaling systems, including G-protein coupled receptors, NMDA receptors, and ion channels. Sigma proteins have been linked to a range of physiological processes, including intracellular calcium signaling, neuroprotection, learning, memory, and cognition. Emerging genetic, clinical, and mechanism focused molecular pharmacology data demonstrate the involvement of proteins in a range of pathophysiologies and disorders including neurodegenerative disease, pain, addiction, psychomotor stimulant abuse, and cancer. However, an understanding of the physiological role of sigma proteins has remained elusive. Emerging data associate Sigma1 with chaperone-like activities or molecular scaffold functions. This book aims to provide an updated perspective on this rapidly evolving field undergoing changes in fundamental concepts of key importance to the discipline of pharmacology. It focusses on the reported roles of sigma proteins in pathophysiology and on emergent therapeutic initiatives.
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Oct 122017
 

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Oct 092017
 

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Oct 042017
 

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Oct 012017
 

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Sep 262017
 

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Sep 252017
 

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Sep 232017
 

Big Data in Healthcare: Extracting Knowledge from Point-of-Care Machines (SpringerBriefs in Pharmaceutical Science & Drug Development)


This book reviews a number of issues including: Why data generated from POC machines are considered as Big Data. What are the challenges in storing, managing, extracting knowledge from data from POC devices? Why is it inefficient to use traditional data analysis with big data?

What are the solutions for the mentioned issues and challenges? What type of analytics skills are required in health care? What big data technologies and tools can be used efficiently with data generated from POC devices? This book shows how it is feasible to store vast numbers of anonymous data and ask highly specific questions that can be performed in real-time to give precise and meaningful evidence to guide public health policy.

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Sep 222017
 

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