Microbiota-Brain Axis Books

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The Gut Brain Axis


The Gut Brain Axis
  • Author : Niall Hyland
  • Publisher : Academic Press
  • Release : 2016-05-13
  • ISBN : 9780128025444
  • Language : En, Es, Fr & De
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The Gut-Brain Axis: Dietary, Probiotic, and Prebiotic Interventions on the Microbiota examines the potential for microbial manipulation as a therapeutic avenue in central nervous system disorders in which an altered microbiota has been implicated, and explores the mechanisms, sometimes common, by which the microbiota may contribute to such disorders. Focuses on specific areas in which the microbiota has been implicated in gut-brain communication Examines common mechanisms and pathways by which the microbiota may influence brain and behavior Identifies novel therapeutic strategies targeted toward the microbiota in the management of brain activity and behavior

Gut Microbiota


Gut Microbiota
  • Author : Alper Evrensel
  • Publisher : BoD – Books on Demand
  • Release : 2018-12-12
  • ISBN : 9781789848144
  • Language : En, Es, Fr & De
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The gut-brain axis has gained considerable attention from different branches of the scientific community in recent years. In this book, scientists from different disciplines present current scientific knowledge on the topic. The interaction between the prokaryote and eukaryote cells stimulates the evolutionary processes, and results in various systemic illnesses such as neuropsychiatric disorders and may help the continuity of health. Nature has provided us with healthy food that builds our pharmacy. This natural pharmacy store may help the body's healing processes through its effects on gut microbiota and the immune system. This book aims to provide the reader with detailed analyses of the current scientific knowledge on the gut-brain axis and its relation with health and disease. We hope that the reader benefits from the presented material.

Microbial Endocrinology


Microbial Endocrinology
  • Author : Mark Lyte
  • Publisher : Springer Science & Business Media
  • Release : 2010-04-06
  • ISBN : 9781441955760
  • Language : En, Es, Fr & De
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Microbial endocrinology represents a newly emerging interdisciplinary field that is formed by the intersection of the fields of neurobiology and microbiology. This book will introduce a new perspective to the current understanding not only of the factors that mediate the ability of microbes to cause disease, but also to the mechanisms that maintain normal homeostasis. The discovery that microbes can directly respond to neuroendocrine hormones, as evidenced by increased growth and production of virulence-associated factors, provides for a new framework with which to investigate how microorganisms interface not only with vertebrates, but also with invertebrates and even plants. The reader will learn that the neuroendocrine hormones that one most commonly associates with mammals are actually found throughout the plant, insect and microbial communities to an extent that will undoubtedly surprise many, and most importantly, how interactions between microbes and neuroendocrine hormones can influence the pathophysiology of infectious disease.

Microbial Endocrinology The Microbiota Gut Brain Axis in Health and Disease


Microbial Endocrinology  The Microbiota Gut Brain Axis in Health and Disease
  • Author : Mark Lyte
  • Publisher : Springer
  • Release : 2014-07-05
  • ISBN : 9781493908974
  • Language : En, Es, Fr & De
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The field of microbial endocrinology is expressly devoted to understanding the mechanisms by which the microbiota (bacteria within the microbiome) interact with the host (“us”). This interaction is a two-way street and the driving force that governs these interactions are the neuroendocrine products of both the host and the microbiota. Chapters include neuroendocrine hormone-induced changes in gene expression and microbial endocrinology and probiotics. This is the first in a series of books dedicated to understanding how bi-directional communication between host and bacteria represents the cutting edge of translational medical research, and hopefully identifies new ways to understand the mechanisms that determine health and disease.​

Python for Probability Statistics and Machine Learning


Python for Probability  Statistics  and Machine Learning
  • Author : José Unpingco
  • Publisher : Springer
  • Release : 2019-06-29
  • ISBN : 9783030185459
  • Language : En, Es, Fr & De
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This book, fully updated for Python version 3.6+, covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas. All the figures and numerical results are reproducible using the Python codes provided. The author develops key intuitions in machine learning by working meaningful examples using multiple analytical methods and Python codes, thereby connecting theoretical concepts to concrete implementations. Detailed proofs for certain important results are also provided. Modern Python modules like Pandas, Sympy, Scikit-learn, Tensorflow, and Keras are applied to simulate and visualize important machine learning concepts like the bias/variance trade-off, cross-validation, and regularization. Many abstract mathematical ideas, such as convergence in probability theory, are developed and illustrated with numerical examples. This updated edition now includes the Fisher Exact Test and the Mann-Whitney-Wilcoxon Test. A new section on survival analysis has been included as well as substantial development of Generalized Linear Models. The new deep learning section for image processing includes an in-depth discussion of gradient descent methods that underpin all deep learning algorithms. As with the prior edition, there are new and updated *Programming Tips* that the illustrate effective Python modules and methods for scientific programming and machine learning. There are 445 run-able code blocks with corresponding outputs that have been tested for accuracy. Over 158 graphical visualizations (almost all generated using Python) illustrate the concepts that are developed both in code and in mathematics. We also discuss and use key Python modules such as Numpy, Scikit-learn, Sympy, Scipy, Lifelines, CvxPy, Theano, Matplotlib, Pandas, Tensorflow, Statsmodels, and Keras. This book is suitable for anyone with an undergraduate-level exposure to probability, statistics, or machine learning and with rudimentary knowledge of Python programming.