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Numerical Modeling in Biomedical Engineering brings together the integrative set of computational problem solving tools important to biomedical engineers.Through the use of comprehensive homework exercises, relevant examples and extensive case studies, this book integrates principles and techniques of numerical analysis.

\"This book addresses the need for a comprehensive book on the design, synthesis, and characterization of synthetic carbohydrate-based polymeric materials along with their biological applications. The first two chapters cover the synthesis and self-assembly of glycopolymers and different techniques for creating these synthetic polymers. Subsequent chapters account for the preparation of block copolymers, branched glycopolymers, glycosurfaces, glycodendrimers, cationic glycopolymers, bioconjugates, glyconanoparticles and hydrogels. While these chapters comprehensively review the synthetic and characterization methods of those carbohydrate-based materials, their biological applications are discussed in detail.\"--Provided by publisher.

In recent years, the development of nanoparticles has expanded into a broad range of clinical applications. Nanoparticles have been developed to overcome the limitations of free therapeutics and navigate biological barriers — systemic, microenvironmental and cellular — that are heterogeneous across patient populations and diseases. Overcoming this patient heterogeneity has also been accomplished through precision therapeutics, in which personalized interventions have enhanced therapeutic efficacy. However, nanoparticle development continues to focus on optimizing delivery platforms with a one-size-fits-all solution. As lipid-based, polymeric and inorganic nanoparticles are engineered in increasingly specified ways, they can begin to be optimized for drug delivery in a more personalized manner, entering the era of precision medicine. In this Review, we discuss advanced nanoparticle designs utilized in both non-personalized and precision applications that could be applied to improve precision therapies. We focus on advances in nanoparticle design that overcome heterogeneous barriers to delivery, arguing that intelligent nanoparticle design can improve efficacy in general delivery applications while enabling tailored designs for precision applications, thereby ultimately improving patient outcome overall.Advances in nanoparticle design could make substantial contributions to personalized and non-personalized medicine. In this Review, Langer, Mitchell, Peppas and colleagues discuss advances in nanoparticle design that overcome heterogeneous barriers to delivery, as well as the challenges in translating these design improvements into personalized medicine approaches.

This updated edition of an Artech House classic introduces readers to the importance of engineering in medicine. Bioelectrical phenomena, principles of mass and momentum transport to the analysis of physiological systems, the importance of mechanical analysis in biological tissues/organs and biomaterial selection are discussed in detail. Readers learn about the concepts of using living cells in various therapeutics and diagnostics, compartmental modeling, and biomedical instrumentation. The book explores fluid mechanics, strength of materials, statics and dynamics, basic thermodynamics, electrical circuits, and material science. A significant number of numerical problems have been generated using data from recent literature and are given as examples as well as exercise problems. These problems provide an opportunity for comprehensive understanding of the basic concepts, cutting edge technologies and emerging challenges. Describing the role of engineering in medicine today, this comprehensive volume covers a wide range of the most important topics in this burgeoning field.

Cellular models are needed to study human development and disease in vitro, and to screen drugs for toxicity and efficacy. Current approaches are limited in the engineering of functional tissue models with requisite cell densities and heterogeneity to appropriately model cell and tissue behaviors. Here, we develop a bioprinting approach to transfer spheroids into self-healing support hydrogels at high resolution, which enables their patterning and fusion into high-cell density microtissues of prescribed spatial organization. As an example application, we bioprint induced pluripotent stem cell-derived cardiac microtissue models with spatially controlled cardiomyocyte and fibroblast cell ratios to replicate the structural and functional features of scarred cardiac tissue that arise following myocardial infarction, including reduced contractility and irregular electrical activity. The bioprinted in vitro model is combined with functional readouts to probe how various pro-regenerative microRNA treatment regimes influence tissue regeneration and recovery of function as a result of cardiomyocyte proliferation. This method is useful for a range of biomedical applications, including the development of precision models to mimic diseases and the screening of drugs, particularly where high cell densities and heterogeneity are important. Cellular models are needed to study disease in vitro and to screen drugs for toxicity and efficacy. Here the authors develop a bioprinting approach to transfer spheroids into self-healing support hydrogels at high resolution, which enables their patterning and fusion into high-cell density microtissues of prescribed spatial organization.

A large number of papers are appearing in the biomedical engineering literature that describe the use of machine learning techniques to develop classifiers for detection or diagnosis of disease. However, the usefulness of this approach in developing clinically validated diagnostic techniques so far has been limited and the methods are prone to overfitting and other problems which may not be immediately apparent to the investigators. This commentary is intended to help sensitize investigators as well as readers and reviewers of papers to some potential pitfalls in the development of classifiers, and suggests steps that researchers can take to help avoid these problems. Building classifiers should be viewed not simply as an add-on statistical analysis, but as part and parcel of the experimental process. Validation of classifiers for diagnostic applications should be considered as part of a much larger process of establishing the clinical validity of the diagnostic technique.

As a fundamental feature of solid surfaces, wettability is playing an increasingly important role in our daily life. Benefitting from the inspiration of biological paradigms and the development in manufacturing technology, numerous wettability materials with elaborately designed surface topology and chemical compositions have been fabricated. Based on these advances, wettability materials have found broad technological implications in various fields ranging from academy, industry, agriculture to biomedical engineering. Among them, the practical applications of wettability materials in biomedical‐related fields are receiving remarkable researches during the past decades because of the increasing attention to healthcare. In this review, the research progress of materials with specific wettability is discussed. After briefly introducing the underlying mechanisms, the fabrication strategies of artificial materials with specific wettability are described. The emphasis is put on the application progress of wettability biomaterials in biomedical engineering. The prospects for the future trend of wettability materials are also presented. As a fundamental feature of solid surfaces, wettability is playing an indispensable role in various fields such as academy, industry, agriculture, and biomedical engineering. This review comprehensively discusses the research progress of materials with specific wettability in biomedical engineering, ranging from underlying mechanisms, fabrication strategies, and application advances to their future prospects.

Shape-Memory Polymers (SMPs) are considered a kind of smart material able to modify size, shape, stiffness and strain in response to different external (heat, electric and magnetic field, water or light) stimuli including the physiologic ones such as pH, body temperature and ions concentration. The ability of SMPs is to memorize their original shape before triggered exposure and after deformation, in the absence of the stimulus, and to recover their original shape without any help. SMPs nanofibers (SMPNs) have been increasingly investigated for biomedical applications due to nanofiber’s favorable properties such as high surface area per volume unit, high porosity, small diameter, low density, desirable fiber orientation and nanoarchitecture mimicking native Extra Cellular Matrix (ECM). This review focuses on the main properties of SMPs, their classification and shape-memory effects. Moreover, advantages in the use of SMPNs and different biomedical application fields are reported and discussed.

Challenges in drug development of neurological diseases remain mainly ascribed to the blood–brain barrier (BBB). Despite the valuable contribution of animal models to drug discovery, it remains difficult to conduct mechanistic studies on the barrier function and interactions with drugs at molecular and cellular levels. Here we present a microphysiological platform that recapitulates the key structure and function of the human BBB and enables 3D mapping of nanoparticle distributions in the vascular and perivascular regions. We demonstrate on-chip mimicry of the BBB structure and function by cellular interactions, key gene expressions, low permeability, and 3D astrocytic network with reduced reactive gliosis and polarized aquaporin-4 (AQP4) distribution. Moreover, our model precisely captures 3D nanoparticle distributions at cellular levels and demonstrates the distinct cellular uptakes and BBB penetrations through receptor-mediated transcytosis. Our BBB platform may present a complementary in vitro model to animal models for prescreening drug candidates for the treatment of neurological diseases. Developing an in vitro blood-brain-barrier (BBB) model that reproduces the organ’s complex structure and function is an open challenge. Here the authors present a BBB-on-a-chip that includes endothelial cells, pericytes and a 3D astrocytic network which resembles the morphology and function of astrocytes in the BBB in vivo.

Small animals support a wide range of pathological phenotypes and genotypes as versatile, affordable models for pathogenesis of cardiovascular diseases and for exploration of strategies in electrotherapy, gene therapy, and optogenetics. Pacing tools in such contexts are currently limited to tethered embodiments that constrain animal behaviors and experimental designs. Here, we introduce a highly miniaturized wireless energy-harvesting and digital communication electronics for thin, miniaturized pacing platforms weighing 110 mg with capabilities for subdermal implantation and tolerance to over 200,000 multiaxial cycles of strain without degradation in electrical or optical performance. Multimodal and multisite pacing in ex vivo and in vivo studies over many days demonstrate chronic stability and excellent biocompatibility. Optogenetic stimulation of cardiac cycles with in-animal control and induction of heart failure through chronic pacing serve as examples of modes of operation relevant to fundamental and applied cardiovascular research and biomedical technology. Pacing tools that support small animals and can serve as models for pathogenesis of cardiovascular diseases are currently not available. Here, the authors report a miniaturized wireless battery-free implantable multimodal and multisite pacemaker that provides unlimited stimulation to test subjects.