Written for biomedical engineering students and biomedical scientists, Physiological Control Systems, offers an updated edition of this key resource for understanding classical control theory and its application to physiological systems. It also contains contemporary topics and methodologies that shape bioengineering research today.
Written for biomedical engineering students and biomedical scientists, Physiological Control Systems, offers an updated edition of this key resource for understanding classical control theory and its application to physiological systems. It also contains contemporary topics and methodologies that shape bioengineering research today.
Physiological Control Systems Solutions Manual Michael Khoo
Single-organ systems often achieve a high degree of biological authenticity, allowing evaluation of the response of a specific organ to a compound or mixture of compounds. Multi-organ systems provide a framework to examine the potential interaction of one organ with at least one other, principally through the exchange of metabolites or soluble signalling molecules. Both single-OoC and multi-OoC systems are often referred to as microphysiological systems, as they are designed to model features of human or animal biology within a microscale culture44. Multi-OoC systems, which model the physiological systemic response in the body, are commonly referred to as body-on-a-chip35. The choice of a single-organ or multi-organ system depends on the desired functionalities needed for the system to be a good model of the physiological processes. The degree of complexity should be kept to the minimum required to represent the biological application without introducing unnecessary factors that make the system difficult to use and analyse. Multi-organ systems tend to involve more complex engineering design than single-organ systems. This allows control of the transport and distribution of culture media between the individual organs. Consequently, there is a trend in the OoC systems that have been developed, where single-OoCs are more biologically detailed models of an organ whereas multi-OoCs use less detailed organ models and focus on the systemic interactions between organs35.
Development and deployment of OoCs require the coordination of various multidisciplinary elements, such as cells, biomaterials, engineering controls, interconnects and sensors. Reproducibility of OoC systems largely depends on the correct matching and interplay of the different elements as well as their isolated reproducibility. The more variability single elements present, the more the error propagates, and the more difficult consistent outcomes become. In general, modularity and the possibility of individual and timed quality control of the single elements greatly increases system yield and directly dependent reproducibility of experiments using OoC systems. Understanding robustness and producing data of statistical relevance additionally require a minimal number of replicates per conditions. Increasing physiological complexity needs consideration of operational complexity and potential limited scalability.
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