RNA Delivery Function for Anticancer Therapeutics by
This book presents an overview of the current status of translating the RNAi cancer therapeutics in the clinic, a brief description of the biological barriers in drug delivery, and the roles of imaging in aspects of administration route, systemic circulation, and cellular barriers for the clinical translation of RNAi cancer therapeutics, and with partial content for discussing the safety concerns. It then focuses on imaging-guided delivery of RNAi therapeutics in preclinical development, including the basic principles of different imaging modalities, and their advantages and limitations for biological imaging. With growing number of RNAi therapeutics entering the clinic, various imaging methods will play an important role in facilitating the translation of RNAi cancer therapeutics from bench to bedside. RNAi technique has become a powerful tool for basic research to selectively knock down gene expression in vitro and in vivo. Our scientific and industrial communities have started to develop RNAi therapeutics as the next class of drugs for treating a variety of genetic disorders, such as cancer and other diseases that are particularly hard to address with current treatment strategies. Key Features　 Provides　insight　into　the　current　advances　and　hurdles　of　RNAi　therapeutics.　　 Accelerates　RNAi,　miRNAs, and siRNA　drug　development　for cancer therapy　from　bench　to　bedside.　 Addresses　various modifications and　novel　delivery　strategies for miRNAs,　piRNAs　and siRNA delivery　in　anticancer therapeutics.　　 Explores the need for the interaction　of　hematologists, cell　biologists,　immunologists, and material　scientists　in the development of 　novel　cancer therapies. 　 Describes the　current status　of clinical trials related to miRNA and siRNA-based cancer therapy　 Presents　remaining issues that need to be overcome to establish　successful therapies.　
Cyanobacteria Biotechnology by
Unites a biological and a biotechnological perspective on cyanobacteria, and includes the industrial aspects and applications of cyanobacteria Cyanobacteria Biotechnology offers a guide to the interesting and useful features of cyanobacteria metabolism that keeps true to a biotechnology vision. In one volume the book brings together both biology and biotechnology to illuminate the core acpects and principles of cyanobacteria metabolism. Designed to offer a practical approach to the metabolic engineering of cyanobacteria, the book contains relevant examples of how this metabolic "module" is currently being engineered and how it could be engineered in the future. The author includes information on the requirements and real-world experiences of the industrial applications of cyanobacteria. This important book: Brings together biology and biotechnology in order to gain insight into the industrial relevant topic of cyanobacteria Introduces the key aspects of the metabolism of cyanobacteria Presents a grounded, practical approach to the metabolic engineering of cyanobacteria Offers an analysis of the requirements and experiences for industrial cyanobacteria Provides a framework for readers to design their own processes Written for biotechnologists, microbiologists, biologists, biochemists, Cyanobacteria Biotechnology provides a systematic and clear volume that brings together the biological and biotechnological perspective on cyanobacteria.
Compendium of Biomedical Instrumentation by
An essential reference filled with 400 of today's current biomedical instruments and devices Designed mainly for the active bio-medical equipment technologists involved in hands-on functions like managing these technologies by way of their usage, operation & maintenance and those engaged in advancing measurement techniques through research and development, this book covers almost the entire range of instruments and devices used for diagnosis, imaging, analysis, and therapy in the medical field. Compiling 400 instruments in alphabetical order, it provides comprehensive information on each instrument in a lucid style. Each description in Compendium of Biomedical Instrumentation covers four aspects: purpose of the instrument; principle of operation, which covers physics, engineering, electronics, and data processing; brief specifications; and major applications. Devices listed range from the accelerometer, ballistocardiograph, microscopes, lasers, and electrocardiograph to gamma counter, hyperthermia system, microtome, positron emission tomography, uroflowmeter, and many more. Covers almost the entire range of medical instruments and devices which are generally available in hospitals, medical institutes at tertiary, secondary, and peripheral level facilities Presents broad areas of applications of medical instruments/technology, including specialized equipment for various medical specialties, fully illustrated with figures & photographs Contains exhaustive description on state of the art instruments and also includes some generation old legacy instruments which are still in use in some medical facilities. Compendium of Biomedical Instrumentation is a must-have resource for professionals and undergraduate and graduate students in biomedical engineering, as well as for clinical engineers and bio-medical equipment technicians.
Principles of Biomedical Instrumentation by
This accessible yet in-depth textbook describes the step-by-step processes involved in biomedical device design. Integrating microfabrication techniques, sensors and digital signal processing with key clinical applications, it covers: the measurement, amplification and digitization of physiological signals, and the removal of interfering signals; the transmission of signals from implanted sensors through the body, and the issues surrounding the powering of these sensors; networks for transferring sensitive patient data to hospitals for continuous home-monitoring systems; tests for ensuring patient safety; the cost-benefit and technological trade-offs involved in device design; and current challenges in biomedical device design. With dedicated chapters on electrocardiography, digital hearing aids and mobile health, and including numerous end-of-chapter homework problems, online solutions and additional references for extended learning, it is the ideal resource for senior undergraduate students taking courses in biomedical instrumentation and clinical technology.
Signal Processing and Machine Learning for Biomedical Big Data by
Within the healthcare domain, big data is defined as any ``high volume, high diversity biological, clinical, environmental, and lifestyle information collected from single individuals to large cohorts, in relation to their health and wellness status, at one or several time points.'' Such data is crucial because within it lies vast amounts of invaluable information that could potentially change a patient's life, opening doors to alternate therapies, drugs, and diagnostic tools. Signal Processing and Machine Learning for Biomedical Big Data thus discusses modalities; the numerous ways in which this data is captured via sensors; and various sample rates and dimensionalities. Capturing, analyzing, storing, and visualizing such massive data has required new shifts in signal processing paradigms and new ways of combining signal processing with machine learning tools. This book covers several of these aspects in two ways: firstly, through theoretical signal processing chapters where tools aimed at big data (be it biomedical or otherwise) are described; and, secondly, through application-driven chapters focusing on existing applications of signal processing and machine learning for big biomedical data. This text aimed at the curious researcher working in the field, as well as undergraduate and graduate students eager to learn how signal processing can help with big data analysis. It is the hope of Drs. Sejdic and Falk that this book will bring together signal processing and machine learning researchers to unlock existing bottlenecks within the healthcare field, thereby improving patient quality-of-life. Provides an overview of recent state-of-the-art signal processing and machine learning algorithms for biomedical big data, including applications in the neuroimaging, cardiac, retinal, genomic, sleep, patient outcome prediction, critical care, and rehabilitation domains. Provides contributed chapters from world leaders in the fields of big data and signal processing, covering topics such as data quality, data compression, statistical and graph signal processing techniques, and deep learning and their applications within the biomedical sphere. This book's material covers how expert domain knowledge can be used to advance signal processing and machine learning for biomedical big data applications.
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