The Developing Microbiome: Lessons from Early Life focuses on the establishment of the microbiome in early life, exposing it as a key mediator of diseases and health throughout the lifecycle. The content presents a comprehensive view of the status of the field and draws real-world correlations to health and disease states. It collates the significant research being done in the pediatric microbiome research space and bridges the knowledge gap showing the factors that impact health and disease states throughout the lifecycle. Finally, it offers knowledge on how the microbiome is and can be manipulated to promote change. This is a perfect reference for both researchers and clinical scientists who are interested in the role of the infant microbiome in health and disease, as well as gastroenterologists and pediatricians looking to affect change in their patients.

This textbook provides a comprehensive, yet accessible, introduction to statistical mechanics. Crafted and class-tested over many years of teaching, it carefully guides advanced undergraduate and graduate students who are encountering statistical mechanics for the first time through this – sometimes – intimidating subject. The book provides a strong foundation in thermodynamics and the ensemble formalism of statistical mechanics. An introductory chapter on probability theory is included. Applications include degenerate Fermi systems, Bose-Einstein condensation, cavity radiation, phase transitions, and critical phenomena. The book concludes with a treatment of scaling theories and the renormalization group. In addition, it provides clear descriptions of how to understand the foundational mathematics and physics involved and includes exciting case studies of modern applications of the subject in physics and wider interdisciplinary areas. Key Features: Presents the subject in a clear and entertaining style which enables the author to take a sophisticated approach whilst remaining accessible Contains contents that have been carefully reviewed with a substantial panel to ensure that coverage is appropriate for a wide range of courses, worldwide Accompanied by volumes on thermodynamics and non-equilibrium statistical mechanics, which can be used in conjunction with this book, on courses which cover both thermodynamics and statistical mechanics

Systems and Synthetic Metabolic Engineering provides an overview of the development of metabolic engineering within medicine that is fueled by systems and synthetic biology. These newly developed, successful strategies of metabolic engineering guide the audience on how to propose and test proper strategies for metabolic engineering research. In addition to introductory, regulatory and challenges in the field, the book also covers dynamic control and autonomous regulation to control cell metabolism, along with computational modeling and industrial applications. The book is written by leaders in the field, making it ideal for synthetic biologists, researchers, students and anyone working in this area.

Cancer: Oxidative Stress and Dietary Antioxidants, Second Edition, covers the science of oxidative stress in cancer and the potentially therapeutic usage of natural antioxidants in the diet or food matrix. The processes within the science of oxidative stress are described in concert with other processes, such as apoptosis, cell signaling, and receptor-mediated responses. This approach recognizes that diseases are often multifactorial and that oxidative stress is a single component. Other sections cover new organ site tumors-skin and liver cancer, the role of polymorphisms, cytochrome p450s, COX gene, fatty acids, apoptosis, T cells and mitochondria, prevention/protection with anthocyanins, esculetin, nanoparticles, and more. This book is a valuable resource for cancer researchers, oncologists, nutritionists and other members of the biomedical field who are interested in enhancing treatment outcome, improving the quality of life of patients, and developing new treatments in the fight against cancer.

Nanoengineering in Musculoskeletal Regeneration provides the reader an updated summary of the therapeutic pipeline-from biomedical discovery to clinical implementation-aimed at improving treatments for patients with conditions of the muscles, tendons, cartilage, meniscus, and bone. Regenerative medicine focuses on using stem cell biology to advance medical therapies for devastating disorders. This text presents novel, significant, and interdisciplinary theoretical and experimental results related to nanoscience and nanotechnology in musculoskeletal regeneration. Content includes basic, translational, and clinical research addressing musculoskeletal repair and regeneration for the treatment of diseases and injuries of the skeleton and its associated tissues. Musculoskeletal degeneration and complications from injuries have become more prevalent as people live longer and increasingly participate in rigorous athletic and recreational activities. Additionally, defects in skeletal tissues may immobilize people and cause inflammation and pain. Musculoskeletal regeneration research provides solutions to repair, restore, or replace skeletal elements and associated tissues that are affected by acute injury, chronic degeneration, genetic dysfunction, and cancer-related defects. The goal of musculoskeletal regeneration medicine research is to improve quality of life and outcomes for people with musculoskeletal injury or degradation.

Drug Resistance in Colorectal Cancer: Molecular Mechanisms and Therapeutic Strategies, Volume Eight, summarizes the molecular mechanisms of drug resistance in colorectal cancer, along with the most up-to-date therapeutic strategies available. The book discusses reasons why colorectal tumors become refractory during the progression of the disease, but also explains how drug resistance occurs during chemotherapy. In addition, users will find the current therapeutic strategies used by clinicians in their practice in treating colorectal cancer. The combination of conventional anticancer drugs with chemotherapy-sensitizing agents plays a pivotal role in improving the outcome of colorectal cancer patients, in particular those with drug-resistant cancer cells. From a clinical point-of-view, the content of this book provides clinicians with updated therapeutic strategies for a better choice of drugs for drug-resistant colorectal cancer patients. It will be a valuable source for cancer researchers, oncologists and several members of biomedical field who are dedicated to better treat patients with colorectal cancer.

Integrative Pancreatic Intervention Therapy: A Holistic Approach summarizes, in a systematic manner, the diagnosis and treatment of late, critical pancreatic diseases. The book gives insights into each interventional technique, with an ultimate goal of improving survival rates for late stage pancreatic cancer patients. Six sections cover basic and transformation research on pancreatic diseases, interventional therapy for benign pancreatic disease, interventional therapy for malignant pancreatic diseases, interventional therapy for pancreative cancer-related lesions, stem cell and targeted molecular therapy for pancreative carcinoma, and combined interventional therapy for pancreative carcinoma. This book will be useful for those looking to understand how best to apply interventional therapy for the improvement of late state pancreatic cancer treatment.

This book shows how to decompose high-dimensional microarrays into small subspaces (Small Matryoshkas, SMs), statistically analyze them, and perform cancer gene diagnosis. The information is useful for genetic experts, anyone who analyzes genetic data, and students to use as practical textbooks.Discriminant analysis is the best approach for microarray consisting of normal and cancer classes. Microarrays are linearly separable data (LSD, Fact 3). However, because most linear discriminant function (LDF) cannot discriminate LSD theoretically and error rates are high, no one had discovered Fact 3 until now. Hard-margin SVM (H-SVM) and Revised IP-OLDF (RIP) can find Fact3 easily. LSD has the Matryoshka structure and is easily decomposed into many SMs (Fact 4). Because all SMs are small samples and LSD, statistical methods analyze SMs easily. However, useful results cannot be obtained. On the other hand, H-SVM and RIP can discriminate two classes in SM entirely. RatioSV is the ratio of SV distance and discriminant range. The maximum RatioSVs of six microarrays is over 11.67%. This fact shows that SV separates two classes by window width (11.67%). Such easy discrimination has been unresolved since 1970. The reason is revealed by facts presented here, so this book can be read and enjoyed like a mystery novel. Many studies point out that it is difficult to separate signal and noise in a high-dimensional gene space. However, the definition of the signal is not clear. Convincing evidence is presented that LSD is a signal. Statistical analysis of the genes contained in the SM cannot provide useful information, but it shows that the discriminant score (DS) discriminated by RIP or H-SVM is easily LSD. For example, the Alon microarray has 2,000 genes which can be divided into 66 SMs. If 66 DSs are used as variables, the result is a 66-dimensional data. These signal data can be analyzed to find malignancy indicators by principal component analysis and cluster analysis.

This book presents a variety of techniques designed to enhance and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. It is intended to provide a unique compendium of current and emerging machine learning paradigms for healthcare informatics, reflecting the diversity, complexity, and depth and breadth of this multi-disciplinary area.

BEST: Implementing Career Development Activities for Biomedical Research Trainees provides an instructional guide for institutions wanting to create, supplement or improve their career and professional development offerings. Each chapter provides an exclusive perspective from an administrator from the 17 Broadening Experiences in Scientific Training (BEST) institutions. The book can aid institutions who train graduate students in a variety of careers by teaching faculty and staff how to create and implement career development programming, how to highlight the effectiveness of offerings, how to demonstrate that creating a program from scratch is doable, and how to inform faculty and staff on getting institutional buy-in. This is a must-have for graduate school deans and faculty and staff who want to implement and institutionalize career development programing at their institutions. It is also ideal for graduate students and postdocs.

Reviews of Environmental Contamination and Toxicology attempts to provide concise, critical reviews of timely advances, philosophy and significant areas of accomplished or needed endeavor in the total field of xenobiotics, in any segment of the environment, as well as toxicological implications.

Theory of Endobiogeny, Volume 3: Advanced Concepts for Treatment of Complex Clinical Conditions explains complex and multi-factorial disorders and diseases using the theory of endobiogeny. It provides detailed applications of biological modeling, in-depth assessment into common disorders, an endobiogenic analysis, guidance on using biological modeling tools, and suggestions for treatment using standard of care treatments that also take into account diet, lifestyle and medicinal plants. This approach is an evolution in thinking from reductionism to holism, offering advice for symptomatic treatments that can be used in conjunction with a new way of thinking about diseases and disease management.

Complexes of physically interacting proteins constitute fundamental functional units that drive almost all biological processes within cells. A faithful reconstruction of the entire set of protein complexes (the "complexosome") is therefore important not only to understand the composition of complexes but also the higher level functional organization within cells. Advances over the last several years, particularly through the use of high-throughput proteomics techniques, have made it possible to map substantial fractions of protein interactions (the "interactomes") from model organisms including Arabidopsis thaliana (a flowering plant), Caenorhabditis elegans (a nematode), Drosophila melanogaster (fruit fly), and Saccharomyces cerevisiae (budding yeast). These interaction datasets have enabled systematic inquiry into the identification and study of protein complexes from organisms. Computational methods have played a significant role in this context, by contributing accurate, efficient, and exhaustive ways to analyze the enormous amounts of data. These methods have helped to compensate for some of the limitations in experimental datasets including the presence of biological and technical noise and the relative paucity of credible interactions. In this book, we systematically walk through computational methods devised to date (approximately between 2000 and 2016) for identifying protein complexes from the network of protein interactions (the protein-protein interaction (PPI) network). We present a detailed taxonomy of these methods, and comprehensively evaluate them for protein complex identification across a variety of scenarios including the absence of many true interactions and the presence of false-positive interactions (noise) in PPI networks. Based on this evaluation, we highlight challenges faced by the methods, for instance in identifying sparse, sub-, or small complexes and in discerning overlapping complexes, and reveal how a combination of strategies is necessary to accurately reconstruct the entire complexosome.

The book presents nine mini-courses from a summer school, Dynamics of Biological Systems, held at the University of Alberta in 2016, as part of the prestigious seminar series: Seminaire de Mathematiques Superieures (SMS). It includes new and significant contributions in the field of Dynamical Systems and their applications in Biology, Ecology, and Medicine. The chapters of this book cover a wide range of mathematical methods and biological applications. They - explain the process of mathematical modelling of biological systems with many examples, - introduce advanced methods from dynamical systems theory, - present many examples of the use of mathematical modelling to gain biological insight - discuss innovative methods for the analysis of biological processes, - contain extensive lists of references, which allow interested readers to continue the research on their own. Integrating the theory of dynamical systems with biological modelling, the book will appeal to researchers and graduate students in Applied Mathematics and Life Sciences.

The Theory of Endobiogeny Volume 1: Global Systems Thinking and Biological Modeling for Clinical Medicine offers researchers and clinicians a detailed introduction to the theory of Endobiogeny. The book presents a new approach to medicine that is at once scientific and humanistic, quantitative, and qualitative. The philosophical and experimental basis of a global complex systems approach to physiology is presented along with a mathematical approach to modeling the dynamism of the terrain. The importance of the history and physical examination are renewed as a source of "big data" readily available to clinicians for greater insight into the patient's state. Expansion of the therapeutic compendium is proposed based on a rational, clinical approach correlated to mathematical indicators of the physiologic state. What is proposed in this work is a fundamental shift in scientific thinking with a resulting expansion of the boundaries of clinical medicine for the 21st century and beyond.

No longer confined to medical devices, medical software has become a pervasive technology giving healthcare operators access to clinical information stored in electronic health records and clinical decision support systems, supporting robot-assisted telesurgery, and providing the technology behind ambient assisted living. These systems and software must be designed, built and maintained according to strict regulations and standards to ensure that they are safe, reliable and secure. Engineering High Quality Medical Software illustrates how to exploit techniques, methodologies, development processes and existing standards to realize high-confidence medical software. After an introductory survey of the topic the book covers global regulations and standards (including EU MDD 93/42/EEC, FDA Title 21 of US CFR, ISO 13485, ISO 14971, IEC 52304, IEEE 1012 and ISO/IEC 29119), verification and validation techniques and techniques, and methodologies and engineering tasks for the development, configuration and maintenance of medical software.

Bioinformatics is an integrative field of computer science, genetics, genomics, proteomics, and statistics, which has undoubtedly revolutionized the study of biology and medicine in past decades. It mainly assists in modeling, predicting and interpreting large multidimensional biological data by utilizing advanced computational methods. Despite its enormous potential, bioinformatics is not widely integrated into the academic curriculum as most life science students and researchers are still not equipped with the necessary knowledge to take advantage of this powerful tool. Hence, the primary purpose of our book is to supplement this unmet need by providing an easily accessible platform for students and researchers starting their career in life sciences. This book aims to avoid sophisticated computational algorithms and programming. Instead, it focuses on simple DIY analysis and interpretation of biological data with personal computers. Our belief is that once the beginners acquire these basic skillsets, they will be able to handle most of the bioinformatics tools for their research work and to better understand their experimental outcomes. Our second title of this volume set In Silico Life Sciences: Medicine provides hands-on experience in analyzing high throughput molecular data for the diagnosis, prognosis, and treatment of monogenic or polygenic human diseases. The key concepts in this volume include risk factor assessment, genetic tests and result interpretation, personalized medicine, and drug discovery. This volume is expected to train readers in both single and multi-dimensional biological analysis using open data sets, and provides a unique learning experience through clinical scenarios and case studies.

Scholars and policymakers alike agree that innovation in the biosciences is key to future growth. The field continues to shift and expand, and it is certainly changing the way people live their lives in a variety of ways. With a large share of federal research dollars devoted to the biosciences, the field is just beginning to live up to its billing as a source of innovation, economic productivity and growth. Vast untapped potential to imagine and innovate exists in the biosciences given new tools now widely available. In The Biologist's Imagination, William Hoffman and Leo Furcht examine the history of innovation in the biosciences, tracing technological innovation from the late eighteenth century to the present and placing special emphasis on how and where technology evolves. Place is often key to innovation, from the early industrial age to the rise of the biotechnology industry in the second half of the twentieth century. The book uses the distinct history of bioinnovation to discuss current trends as they relate to medicine, agriculture, energy, industry, ecosystems, and climate. Fast-moving research fields like genomics, synthetic biology, stem cell research, neuroscience, bioautomation and bioprinting are accelerating these trends. Hoffman and Furcht argue that our system of bioscience innovation is itself in need of innovation. It needs to adapt to the massive changes brought about by converging technologies and the globalization of higher education, workforce skills, and entrepreneurship. The Biologist's Imagination is both a review of past models for bioscience innovation and a forward-looking, original argument for what future models should take into account.

This book reviews the advances and challenges of structure-based drug design in the preclinical drug discovery process, addressing various diseases, including malaria, tuberculosis and cancer. Written by internationally recognized researchers, this edited book discusses how the application of the various in-silico techniques, such as molecular docking, virtual screening, pharmacophore modeling, molecular dynamics simulations, and residue interaction networks offers insights into pharmacologically active novel molecular entities. It presents a clear concept of the molecular mechanism of different drug targets and explores methods to help understand drug resistance. In addition, it includes chapters dedicated to natural-product- derived medicines, combinatorial drug discovery, the CryoEM technique for structure-based drug design and big data in drug discovery. The book offers an invaluable resource for graduate and postgraduate students, as well as for researchers in academic and industrial laboratories working in the areas of chemoinformatics, medicinal and pharmaceutical chemistry and pharmacoinformatics.