- Table View
- List View
Machine Learning in Medicine - Cookbook Two
by Aeilko H. Zwinderman Ton J. CleophasThe amount of data medical databases doubles every 20 months, and physicians are at a loss to analyze them. Also, traditional data analysis has difficulty to identify outliers and patterns in big data and data with multiple exposure / outcome variables and analysis-rules for surveys and questionnaires, currently common methods of data collection, are, essentially, missing. Consequently, proper data-based health decisions will soon be impossible. Obviously, it is time that medical and health professionals mastered their reluctance to use machine learning methods and this was the main incentive for the authors to complete a series of three textbooks entitled "Machine Learning in Medicine Part One, Two and Three, Springer Heidelberg Germany, 2012-2013", describing in a nonmathematical way over sixty machine learning methodologies, as available in SPSS statistical software and other major software programs. Although well received, it came to our attention that physicians and students often lacked time to read the entire books, and requested a small book, without background information and theoretical discussions and highlighting technical details. For this reason we produced a 100 page cookbook, entitled "Machine Learning in Medicine - Cookbook One", with data examples available at extras. springer. com for self-assessment and with reference to the above textbooks for background information. Already at the completion of this cookbook we came to realize, that many essential methods were not covered. The current volume, entitled "Machine Learning in Medicine - Cookbook Two" is complementary to the first and also intended for providing a more balanced view of the field and thus, as a must-read not only for physicians and students, but also for any one involved in the process and progress of health and health care. Similarly to Machine Learning in Medicine - Cookbook One, the current work will describe stepwise analyses of over twenty machine learning methods, that are, likewise, based on the three major machine learning methodologies: Cluster methodologies (Chaps. 1-3) Linear methodologies (Chaps. 4-11) Rules methodologies (Chaps. 12-20) In extras. springer. com the data files of the examples are given, as well as XML (Extended Mark up Language), SPS (Syntax) and ZIP (compressed) files for outcome predictions in future patients. In addition to condensed versions of the methods, fully described in the above three textbooks, an introduction is given to SPSS Modeler (SPSS' data mining workbench) in the Chaps. 15, 18, 19, while improved statistical methods like various automated analyses and Monte Carlo simulation models are in the Chaps. 1, 5, 7 and 8. We should emphasize that all of the methods described have been successfully applied in practice by the authors, both of them professors in applied statistics and machine learning at the European Community College of Pharmaceutical Medicine in Lyon France. We recommend the current work not only as a training companion to investigators and students, because of plenty of step by step analyses given, but also as a brief introductory text to jaded clinicians new to the methods. For the latter purpose, background and theoretical information have been replaced with the appropriate references to the above textbooks, while single sections addressing "general purposes", "main scientific questions" and "conclusions" are given in place. Finally, we will demonstrate that modern machine learning performs sometimes better than traditional statistics does. Machine learning may have little options for adjusting confounding and interaction, but you can add propensity scores and interaction variables to almost any machine learning method.
Machine Learning in Medicine – A Complete Overview
by Aeilko H. Zwinderman Ton J. CleophasAdequate health and health care is no longer possible without proper data supervision from modern machine learning methodologies like cluster models, neural networks, and other data mining methodologies. The current book is the first publication of a complete overview of machine learning methodologies for the medical and health sector, and it was written as a training companion, and as a must-read, not only for physicians and students, but also for any one involved in the process and progress of health and health care.In this second edition the authors have removed the textual errors from the first edition. Also, the improved tables from the first edition, have been replaced with the original tables from the software programs as applied. This is, because, unlike the former, the latter were without error, and readers were better familiar with them.The main purpose of the first edition was, to provide stepwise analyses of the novel methods from data examples, but background information and clinical relevance information may have been somewhat lacking. Therefore, each chapter now contains a section entitled "Background Information".Machine learning may be more informative, and may provide better sensitivity of testing than traditional analytic methods may do. In the second edition a place has been given for the use of machine learning not only to the analysis of observational clinical data, but also to that of controlled clinical trials.Unlike the first edition, the second edition has drawings in full color providing a helpful extra dimension to the data analysis.Several machine learning methodologies not yet covered in the first edition, but increasingly important today, have been included in this updated edition, for example, negative binomial and Poisson regressions, sparse canonical analysis, Firth's bias adjusted logistic analysis, omics research, eigenvalues and eigenvectors.
Machine Learning in Radiation Oncology
by Issam El Naqa Ruijiang Li Martin J. MurphyThis book provides a complete overview of the role of machine learning in radiation oncology and medical physics, covering basic theory, methods, and a variety of applications in medical physics and radiotherapy. An introductory section explains machine learning, reviews supervised and unsupervised learning methods, discusses performance evaluation, and summarizes potential applications in radiation oncology. Detailed individual sections are then devoted to the use of machine learning in quality assurance; computer-aided detection, including treatment planning and contouring; image-guided radiotherapy; respiratory motion management; and treatment response modeling and outcome prediction. The book will be invaluable for students and residents in medical physics and radiation oncology and will also appeal to more experienced practitioners and researchers and members of applied machine learning communities.
Machine Learning in Team Sports: Performance Analysis and Talent Identification in Beach Soccer & Sepak-takraw (SpringerBriefs in Applied Sciences and Technology)
by Mohamad Razali Abdullah Rabiu Muazu Musa Anwar P.P. Abdul Majeed Norlaila Azura KosniThis brief highlights the application of performance analysis tools in data acquisition, and various machine learning algorithms for evaluating team performance as well as talent identification in beach soccer and sepak takraw. Numerous performance indicators and human performance parameters are considered based on their relevance to each sport. The findings presented here demonstrate that the key performance indicators as well as human performance parameters can be used in the future evaluation of team performance as well as talent identification in these sports. Accordingly, they offer a valuable resource for coaches, club managers, talent identification experts, performance analysts and other relevant stakeholders involved in performance assessments.
Machine Learning with Health Care Perspective: Machine Learning and Healthcare (Learning and Analytics in Intelligent Systems #13)
by Jyotir Moy Chatterjee Vishal JainThis unique book introduces a variety of techniques designed to represent, enhance and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. Providing a unique compendium of current and emerging machine learning paradigms for healthcare informatics, it reflects the diversity, complexity, and the depth and breadth of this multi-disciplinary area. Further, it describes techniques for applying machine learning within organizations and explains how to evaluate the efficacy, suitability, and efficiency of such applications. Featuring illustrative case studies, including how chronic disease is being redefined through patient-led data learning, the book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare challenges.
Machine Learning with R: Learn techniques for building and improving machine learning models, from data preparation to model tuning, evaluation, and working with big data, 4th Edition
by Brett LantzLearn how to solve real-world data problems using machine learning and RPurchase of the print or Kindle book includes a free eBook in PDF format.Key FeaturesThe 10th Anniversary Edition of the bestselling R machine learning book, updated with 50% new content for R 4.0.0 and beyondHarness the power of R to build flexible, effective, and transparent machine learning modelsLearn quickly with this clear, hands-on guide by machine learning expert Brett LantzBook DescriptionMachine learning, at its core, is concerned with transforming data into actionable knowledge. R offers a powerful set of machine learning methods to quickly and easily gain insight from your data. Machine Learning with R, Fourth Edition, provides a hands-on, accessible, and readable guide to applying machine learning to real-world problems. Whether you are an experienced R user or new to the language, Brett Lantz teaches you everything you need to know for data pre-processing, uncovering key insights, making new predictions, and visualizing your findings. This 10th Anniversary Edition features several new chapters that reflect the progress of machine learning in the last few years and help you build your data science skills and tackle more challenging problems, including making successful machine learning models and advanced data preparation, building better learners, and making use of big data.You'll also find this classic R data science book updated to R 4.0.0 with newer and better libraries, advice on ethical and bias issues in machine learning, and an introduction to deep learning. Whether you're looking to take your first steps with R for machine learning or making sure your skills and knowledge are up to date, this is an unmissable read that will help you find powerful new insights in your data.What you will learnLearn the end-to-end process of machine learning from raw data to implementationClassify important outcomes using nearest neighbor and Bayesian methodsPredict future events using decision trees, rules, and support vector machinesForecast numeric data and estimate financial values using regression methodsModel complex processes with artificial neural networksPrepare, transform, and clean data using the tidyverseEvaluate your models and improve their performanceConnect R to SQL databases and emerging big data technologies such as Spark, Hadoop, H2O, and TensorFlowWho this book is forThis book is designed to help data scientists, actuaries, data analysts, financial analysts, social scientists, business and machine learning students, and any other practitioners who want a clear, accessible guide to machine learning with R. No R experience is required, although prior exposure to statistics and programming is helpful.
Machine Medical Ethics
by Simon Peter van Rysewyk Matthijs PontierThe essays in this book, written by researchers from both humanities and science, describe various theoretical and experimental approaches to adding medical ethics to a machine, what design features are necessary in order to achieve this, philosophical and practical questions concerning justice, rights, decision-making and responsibility in medical contexts, and accurately modeling essential physician-machine-patient relationships. In medical settings, machines are in close proximity with human beings: with patients who are in vulnerable states of health, who have disabilities of various kinds, with the very young or very old and with medical professionals. Machines in these contexts are undertaking important medical tasks that require emotional sensitivity, knowledge of medical codes, human dignity and privacy. As machine technology advances, ethical concerns become more urgent: should medical machines be programmed to follow a code of medical ethics? What theory or theories should constrain medical machine conduct? What design features are required? Should machines share responsibility with humans for the ethical consequences of medical actions? How ought clinical relationships involving machines to be modeled? Is a capacity for empathy and emotion detection necessary? What about consciousness? This collection is the first book that addresses these 21st-century concerns.
Machine Vision and Augmented Intelligence—Theory and Applications: Select Proceedings of MAI 2021 (Lecture Notes in Electrical Engineering #796)
by Manish Kumar Bajpai Koushlendra Kumar Singh George GiakosThis book comprises the proceedings of the International Conference on Machine Vision and Augmented Intelligence (MAI 2021) held at IIIT, Jabalpur, in February 2021. The conference proceedings encapsulate the best deliberations held during the conference. The diversity of participants in the event from academia, industry, and research reflects in the articles appearing in the volume. The book theme encompasses all industrial and non-industrial applications in which a combination of hardware and software provides operational guidance to devices in the execution of their functions based on the capture and processing of images. This book covers a wide range of topics such as modeling of disease transformation, epidemic forecast, COVID-19, image processing and computer vision, augmented intelligence, soft computing, deep learning, image reconstruction, artificial intelligence in healthcare, brain-computer interface, cybersecurity, and social network analysis, natural language processing, etc.
Machine Vision and Navigation
by Oleg Sergiyenko Wendy Flores-Fuentes Paolo MercorelliThis book presents a variety of perspectives on vision-based applications. These contributions are focused on optoelectronic sensors, 3D & 2D machine vision technologies, robot navigation, control schemes, motion controllers, intelligent algorithms and vision systems. The authors focus on applications of unmanned aerial vehicles, autonomous and mobile robots, industrial inspection applications and structural health monitoring. Recent advanced research in measurement and others areas where 3D & 2D machine vision and machine control play an important role, as well as surveys and reviews about vision-based applications. These topics are of interest to readers from diverse areas, including electrical, electronics and computer engineering, technologists, students and non-specialist readers.• Presents current research in image and signal sensors, methods, and 3D & 2D technologies in vision-based theories and applications; • Discusses applications such as daily use devices including robotics, detection, tracking and stereoscopic vision systems, pose estimation, avoidance of objects, control and data exchange for navigation, and aerial imagery processing; • Includes research contributions in scientific, industrial, and civil applications.
Machine and Deep Learning in Oncology, Medical Physics and Radiology
by Issam El Naqa Martin J. MurphyThis book, now in an extensively revised and updated second edition, provides a comprehensive overview of both machine learning and deep learning and their role in oncology, medical physics, and radiology. Readers will find thorough coverage of basic theory, methods, and demonstrative applications in these fields. An introductory section explains machine and deep learning, reviews learning methods, discusses performance evaluation, and examines software tools and data protection. Detailed individual sections are then devoted to the use of machine and deep learning for medical image analysis, treatment planning and delivery, and outcomes modeling and decision support. Resources for varying applications are provided in each chapter, and software code is embedded as appropriate for illustrative purposes. The book will be invaluable for students and residents in medical physics, radiology, and oncology and will also appeal to more experienced practitioners and researchers and members of applied machine learning communities.
Machines in Our Hearts: The Cardiac Pacemaker, the Implantable Defibrillator, and American Health Care
by Kirk JeffreyToday hundreds of thousands of Americans carry pacemakers and implantable cardioverter-defibrillators (ICDs) within their bodies. These battery-powered machines—small computers, in fact—deliver electricity to the heart to correct dangerous disorders of the heartbeat. But few doctors, patients, or scholars know the history of these devices or how "heart-rhythm management" evolved into a multi-billion-dollar manufacturing and service industry. Machines in Our Hearts tells the story of these two implantable medical devices. Kirk Jeffrey, a historian of science and technology, traces the development of knowledge about the human heartbeat and follows surgeons, cardiologists, and engineers as they invent and test a variety of electronic devices. Numerous small manufacturing firms jumped into pacemaker production but eventually fell by the wayside, leaving only three American companies in the business today. Jeffrey profiles pioneering heart surgeons, inventors from the realms of engineering and medical research, and business leaders who built heart-rhythm management into an industry with thousands of employees and annual revenues in the hundreds of millions. As Jeffrey shows, the pacemaker (first implanted in 1958) and the ICD (1980) embody a paradox of high-tech health care: these technologies are effective and reliable but add billions to the nation's medical bill because of the huge growth in the number of patients who depend on implanted devices to manage their heartbeats.
Machining of Bone and Hard Tissues
by Narendra Dahotre Sameehan JoshiThis book provides an in-depth review of state-of-the-art orthopaedic techniques and basic mechanical operations (drilling, boring, cutting, grinding/milling) involved in present day orthopaedic surgery. Casting a light on exploratory hybrid operations, as well as non-conventional techniques such as laser assisted operations, this book further extends the discussion to include physical aspects of the surgery in view of material (bone) and process parameters. Featuring detailed discussion of the computational modeling of forces (mechanical and thermal) involved in surgical procedures for the planning and optimization of the process/procedure and system development, this book lays the foundations for efforts towards the future development of improved orthopaedic surgery. With topics including the role of bone machining during surgical operations; the physical properties of the bone which influence the response to any machining operation, and robotic automation, this book will be a valuable and comprehensive literature source for years to come.
Macro Roles for MicroRNAs in the Life and Death of Neurons
by Bart De StrooperThe discovery of microRNAs has revealed an unexpected and spectacular additional level of fine tuning of the genome and how genes are used again and again in different combinations to generate the complexity that underlies for instance the brain. Since the initial studies performed in C.elegans, we gave gone a far way to begin to understand how microRNA pathways can have an impact on health and disease in human. Although microRNAs are abundantly expressed in the brain, relatively little is known about the multiple functions of these RNA molecules in the nervous system. Nevertheless, we know already that microRNA pathways play major roles in the proliferation, differentiation, function and maintenance of neuronal cells. Several intriguing studies have linked microRNAs as major regulators of the neuronal phenotype, and have implicated specific microRNAs in the regulation of synapse formation and plasticity. Dysfunction of microRNA pathways is also slowly emerging as a potential important contributor to the pathogenesis of major neurodegenerative disorders such as Alzheimer's disease and Parkinson's disease. These novel insights appear to be particular promising for the understanding of the very frequent and badly understood sporadic forms of these diseases as compared to the genetic forms. Thus, the better understanding of the implications of this novel field of molecular biology is crucial for the broad area of neurosciences, from the fundamental aspects to the clinic, and from novel diagnostic to potentially therapeutic applications for severe neurological and maybe psychiatric diseases.
Macro Social Influences on Loneliness in Later Life: Towards a Better Understanding of the Loneliness Paradox in Europe (International Perspectives on Aging #47)
by Marja Aartsen Iuliana Precupetu Bianca SuanetThis open access book explores the macro-social influences on loneliness in later life, emphasizing how societal structures, cultural contexts, and broader social transformations shape the experience of loneliness. Dedicated to the social construction of loneliness and the notable heterogeneity in its prevalence across European countries, this volume brings together a distinguished selection of experts who share their latest insights on meso- and macro-level influences, cultural and structural theories, and the impact of digitalization, climate change, and societal crises. Divided into five parts, the book addresses key aspects of this complex issue. The first part introduces the central themes, outlining the relevance of loneliness as a societal concern and discussing the limitations of existing research, which predominantly focuses on individual-level factors. It highlights the need for a multi-level approach that incorporates micro, meso, and macro perspectives to fully understand the contextual influences on loneliness. The second part delves into theoretical perspectives, offering a comprehensive framework for understanding loneliness at different levels. It examines the interplay between individual, relational, and societal factors while also exploring cultural and social exclusion perspectives that shed light on how loneliness manifests across different contexts. The third part presents empirical evidence, focusing on variations in loneliness across different social groups and regions in Europe. It synthesizes research on micro- and meso-level determinants while also providing a review of macro-level influences. This part highlights the role of welfare regimes, demographic trends, and broader societal conditions in shaping the prevalence and experience of loneliness. The fourth part explores recent societal developments that may influence loneliness, including digitalization, migration, climate change, and societal crises. These emerging topics illustrate how macro-level transformations can either alleviate or exacerbate loneliness, depending on how they interact with existing social structures and individual circumstances. The final part discusses methodological advancements and policy implications. It introduces an innovative approach to analyzing macro-social influences on loneliness and revisits the &‘loneliness paradox&’ in light of new findings. The book concludes with policy recommendations and future research directions, emphasizing the need for a holistic approach that integrates individual, relational, and societal dimensions to develop more effective interventions against loneliness. In sum, by adopting a macro-social lens, this book contributes to a deeper understanding of the societal, cultural, and policy-related determinants of loneliness. It offers a foundation for evidence-based interventions that go beyond individual-level solutions, recognizing loneliness as a socially embedded phenomenon shaped by broader societal forces. It is our hope and expectation that the book and its content will fundamentally change our understanding of loneliness and strategies to combat it.
Macro, Micro, and Nano-Biosensors: Potential Applications and Possible Limitations
by Mahendra Rai Avinash P. Ingle Anatoly Reshetilov Yulia PlekhanovaThis book includes an international group of researchers who present the latest achievements in the field of enzyme, immune system, and microbial and nano-biosensors. It highlights the experimental evidence for formation of biological fuel cells (BFCs)-which has a dual purpose – as a device that produces electricity and the systems which produce it simultaneously cleaning up the environment from polluting organic compounds. Considering the work in the field of macro, micro and nano-biosensors, considerable attention is paid to the use of nanomaterials for the modification of working electrodes. Nanomaterials in some cases can significantly improve the parameters of analytical systems. Readers will be interested in the projection of the presented theoretical and experimental materials in the field of practical application of modern analytical developments. The presented results in many cases imply the possibility of using the created models of macro, micro and nano-biosensors, and biofuel elements in the field of health, and protection/restoration of the environment. It includes information about all existing types of transducers of signals in biosensors – electrochemical, optical and quantum-optics, thermoelectric, data of atomic force microscopy, piezoelectric, and more. On the basis of these principles, descriptions are given about the functioning of macro, micro and nano- biosensors for the detection of compounds used in medicine, detection of compounds that clog the environment, and thus affect human health, for compounds that are potentially the basis for the production of drugs, for the selection of compounds that have medicinal activity, for immunodetection, and to assess the quality of food. These questions form the basis of research carried out in the field of biosensors in the world. Since the described models of biosensors have high sensitivity, high measurement speed and selectivity, the described results attract the attention of both the ordinary reader and business class specialists who create and implement analytical technologies. This book is very useful for researchers in life sciences, chemical sciences, physics, and engineering. In addition, it will be useful for the persons working in industry. Advanced technologies specialists will be attracted by the novelty of the proposed solutions and their relevance and ease of implementation. Since the studies contain sections describing the parameters of different biosensors, BFCs, they are easily navigated into assessing the effectiveness of the practical use of the proposed device. The relevant sections indicate such characteristics as detection ranges, life span, type of biological material used, the method of formation of the bio-receptor part. These parameters are of interest to both developers of new models of biosensors and BFC, and their manufacturers.
Macro-Glycoligands
by Xue-Long SunThis volume details methods and protocols for the synthesis and characterization of glycopolymers and their biomedical applications. Chapters are divided into three parts covering synthesis and characterization of glycopolymers; glycopolymer-nanoparticle conjugates; and surface immobilized glycopolymers. Written for the Methods in Molecular Biology series, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, Macro-Glycoligands: Methods and Protocols aims to ensure successful results in the further study of this vital field.
Macrolides as Immunomodulatory Agents (Progress in Inflammation Research #92)
by Bruce K. Rubin Masaharu ShinkaiFor over 50 years, clinicians have known that macrolide antibiotics have effects on inflammation and the immune system that are not related to their antimicrobial properties. These immunomodulatory properties, best described for treating inflammatory airway diseases, protect the lung and the host and improve clinical status. This book summarizes our current knowledge regarding proposed mechanisms for these properties, established clinical results, and what the future may hold with emphasis on novel clinical applications and the fascinating development of non-antimicrobial macrolides with preserved and enhanced immunomodulatory properties.
Macromolecular Anticancer Therapeutics
by Patrick Couvreur L. Harivardhan ReddyIn spite of the development of various anticancer drugs, the therapy of cancer has remained challenging for decades. The current therapy of cancer is overwhelmed because of the inability to deliver therapeutics to all regions of a tumor in effective therapeutic concentrations, intrinsic or acquired resistance to the treatment with currently available agents via genetic and epigenetic mechanisms, and toxicity. As a result, cancer therapy using conventional therapeutics and different types of treatment regimens using this therapeutics has not led to a convincing survival benefit of the patients. In this context, Macromolecular therapeutics offer several advantages over conventional low molecular therapeutics by various ways such as, enable the use of larger doses of these agents by limiting the toxicity, by enhanced permeability and retention into tumors, by tumor targeting using tumor-specific antibodies, by specific inhibition of oncogenes using anticancer oligonucleotides etc. Cancer treatment using this macromolecular therapeutics has considerably improved the survival benefit for patients. As a result, various macromolecular therapeutics are already commercialized or are under clinical development. Although we are far from a real magic bullet today, looking at the pace of research and current success in this field of macromolecular therapeutics, it appears that we are approaching a magic bullet for the efficient treatment of cancer. Thus, we believe that the subject of this book is very timely, and that the book will fill an unmet need in the market. This book is unique and assembles various types and aspects of macromolecular anticancer therapeutics for cancer therapy in one shell and conveys the importance of this interdisciplinary field to the broad audience. Thus, in a nutshell, this book details the basics of cancer, and various therapeutic strategies such as those based on macromolecular therapeutics hence can become an important reference for practitioners, oncologists, medical pharmacologists, medicinal chemists, biomedical scientists, experimental pharmacologists, pharmaceutical technologists, and particularly it can essentially become a handbook of macromolecular therapeutics for cancer therapy for graduates, post-graduates and Ph.D. students in these fields.
Macromolecular Drug Delivery
by Mattias BeltingMacromolecular drugs hold the promise of becoming new therapeutics for several major disorders, including cancer and cardiovascular disease. This incredible potential is explored in Macromolecular Drug Delivery, a volume which gives a wide-ranging overview of contemporary methods used in the field, and which addresses the limitations presented by a lack of safe and efficient drug delivery strategies. Chapters offer information on both in vitro and in vivo methods of macromolecular delivery, thus appealing to a broad scientific audience. Composed in the highly successful Methods in Molecular BiologyTM series format, each chapter contains a brief introduction, step-by-step methods, a list of necessary materials, and a Notes section which shares tips on troubleshooting and avoiding known pitfalls. Comprehensive and cutting-edge, Macromolecular Drug Delivery offers a platform for interdisciplinary collaboration, which should provide opportunities for new discoveries at the interface between disciplines. Ultimately, this cooperation will lead to the use of macromolecular drugs as novel diagnostic tools and, even more importantly, as a means to revolutionize the way we view and treat diseases.
Macroneural Theories in Cognitive Neuroscience
by William R. UttalIn this book, William R. Uttal continues his analysis and critique of theories of mind. This book considers theories that are based on macroneural responses (such as those obtained from fMRI) that represent the averaged or cumulative responses of many neurons. The analysis is carried out with special emphasis on the logical and conceptual difficulties in developing a theory but with special attention to some of the current attempts to go from these cumulative responses to explanations of the grand question of how the mind is generated by the brain. While acknowledging the importance of these macroneural techniques in the study of the anatomy and physiology of the brain, Uttal concludes that this macroneural approach is not likely to produce a valid neural theory of cognition because the critical information—the states of the individual neurons—involved in brain activity becoming mental activity is actually lost in the process of summation. Controversial topics are considered in detail including discussions of empirical, logical, and technological barriers to theory building in cognitive neuroscience.
Macrophage Migration Inhibitory Factor: Methods and Protocols (Methods in Molecular Biology #2080)
by James Harris Eric F. MorandThis volume looks at--and discusses the techniques of--a range of areas in biology in which macrophage migration inhibitory factor (MIF) is studied. Topics covered in this book include methods to quantify MIF in cell supernatants and human samples, using ELISA and western blot; detection and analysis of intracellular MIF using flow cytometry; genotyping of human MIF polymorphisms, detection of MIF expression in a marine invertebrate using rapid amplification of cDNA RACE; studying the MIF receptor CD74 in tissues using immunohistochemistry; and studying MIF in models of disease such as asthma, Plasmodium infection, and gout. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Comprehensive and practical, Macrophage Migration Inhibitory Factor: Methods and Protocols is a valuable resource that will help researchers gain a new understanding of MIF biology in health and disease.
Macrophage Targeted Delivery Systems: Basic Concepts and Therapeutic Applications
by Yashwant V. Pathak Swati GuptaThe proposed book is envisioned for the nascent and entry-level researchers who are interested to work in the field of drug delivery and its applications specifically for macrophage targeting. Macrophages have gained substantial attention as therapeutic targets for drug delivery considering their major role in health and regulation of diseases. Macrophage-targeted therapeutics have now added significant value to the lives and quality of life of patients, without undue adverse effects in multiple disease settings. We anticipate examining and integrating the role of macrophages in the instigation and advancement of various diseases. The major focus of the book is on recent advancements in various targeting strategies using delivery systems or nanocarriers followed by application of these nanocarriers for the treatment of macrophage associated disorders. Macrophage Targeted Delivery Systems is primarily targeted to Pharmaceutical Industry & Academia, Medical & Pharmaceutical Professionals, Undergraduate & Post graduate students and Research Scholars, Ph.D, post docs working in the field of medical and pharmaceutical sciences.
Macrophages & Cancer (Routledge Revivals)
by Amy M. Fulton Gloria H. HeppnerFirst Published in 1988, this book offers a full, comprehensive guide into the relationship between macrophages and Cancer. Carefully compiled and filled with a vast repertoire of notes and references this book serves as a useful reference for Students of Medicine, Oncology and other practitioners in their respective fields.
Macrophages and Dendritic Cells
by Neil E. ReinerIn light of the critical contributions of macrophages and dendritic cells to diverse inflammatory diseases and to immunity and host defense, state-of-the-art approaches to the investigation of their behavior are essential. In Macrophages and Dendritic Cells: Methods and Protocols, expert researchers contribute laboratory protocols involving these two vital cell types functioning at the junction of the innate and acquired immune systems. The volume delves first into isolation and cell culturing then continues with topics such as phagocytosis, genetic manipulation, macrophage activation, and lipid signaling. Written in the highly successful Methods in Molecular BiologyTM series format, chapters include brief introductions to their respective subjects, lists of the necessary materials and reagents, step-by-step, readily reproducible protocols, and notes on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Macrophages and Dendritic Cells: Methods and Protocols provides a timely and useful guide for both seasoned investigators and neophytes pursuing this imperative field of study.
Macrophages: Biology and Role in the Pathology of Diseases
by Subhra K. Biswas Alberto MantovaniMacrophages are a key component of the innate immune system and play an integral role in host defense and homeostasis. On one hand, these cells contribute to host defence by triggering inflammation, displaying microbicidal/tumoricidal properties, regulating the activation of adaptive immunity and promoting resolution of inflammation. On the other hand, they contribute to essential trophic functions such as neural patterning, bone morphogenesis and ductal branching in mammary glands. Thus, macrophages are extremely versatile cells that can respond efficiently to tissue micro environmental cues by polarizing to distinct phenotypes, depending on the functions they need to perform. Indeed, functional diversity and plasticity are hallmarks of these cells. Macrophages may also play a detrimental role. An overwhelming body of literature has indicated their crucial role in pathogenesis. The list includes sepsis, cancer, metabolic syndrome, immunodeficiency, auto-immune disease-virtually impacting every major pathology that we know. These observations have suggested macrophages and their related molecules as potential targets in therapeutic applications. Available evidence proclaims macrophages as a key player in homeostasis, host defense and disease. Crucial developments in the past few years call for a re-evaluation and update of our understanding of macrophages. The present book is an endeavour that attempts provide state-of-the art knowledge of these cells in health and disease.