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This work focuses on electro-chemical-mechanical multi-scale simulation of the excitation-contraction of skeletal muscle, including electro-chemical excitation process in the neural system which activates the contraction of muscle fibers, the combined effects of active fiber contraction and passive extracellular matrix (ECM) mechanical deformation, and their resulting force generation in the muscle components. In the neural systems, the Fitzhugh-Nagumo (FHN) equation is solved to simulate the propagation of neural signals (action potential) in neural trees and muscle fibers using multi-dimensional FHN discretizations. The calculated neural signal is consequently used as the input for the calcium dynamics model, which describes the chemical processes in the muscle fibers. Based on the calculated calcium concentration, the activation distribution in the muscle tissue is then obtained, which determines the active force muscle fiber can generate voluntarily. To study the mechanics associated with the composition of muscle fibers and ECM, the microstructure of skeletal muscle is reconstructed from images, from which the homogenized material property in the continuum level is calculated. By varying the microstructure model, their morphological effect on the muscle performance is studied and compared with experimental observation.

Computationally, the physiological models in excitation dynamics are solved by finite difference methods, and their accuracy, efficiency and stability conditions are studied respectively. For the cellular and component scale models, the 3-dimensional reproducing kernel particle method (RKPM) together with stabilized conforming nodal integration are employed. The simulation models are constructed based on medical images, where the pixel points are directly used as meshfree nodes. This computational model has been used to investigate the source of reduced force generation associated with ageing or diseases within muscles due to the malfunctioning in the subscale units. Through the proposed computational models, this research demonstrates how the stiffened connective tissue reduces force generation and how the frequency of neural stimulation affects force generation in the skeletal muscle.

Nanomedicine is a flourishing scientific field involving the design and control of matter on the nanometer scale for therapeutic use. One emerging avenue within the nanomedicine field is biodetoxification-based therapy, in which nano-sized structures are used to capture and retain biotoxins that would otherwise attack host cells, cause cellular damage, and trigger damage-associated signaling pathways to propagate diseases. Particularly, inflammation is a biological process that involves complex signaling networks and disease-specific cellular responses, posing significant challenge for designing medicine with high specificity and potency. To this end, the design flexibility of nanoparticle size and surface modification, and unique particle-cell interaction at the nanoscale can lead to novel and efficacious routes for anti-inflammatory therapy. Herein, we discuss the new generations of cell membrane-coated nanoparticles specifically tailored for biodetoxification-based anti-inflammatory therapy. Firstly, recent advances in neutralizing inflammatory cytokine will be discussed. The second portion of this dissertation will present neutrophil membrane-coated nanoparticle (neutrophil-NP) for therapeutic treatment of inflammatory arthritis. Neutrophil-NPs targeted and penetrated into the inflamed tissue, and effectively neutralized inflammatory cytokines. The third portion will cover the development of macrophage membrane-coated nanoparticle for neutralization of bacterial endotoxin and inflammatory cytokines, and management of bacterial sepsis. Finally, we will focus on the design of a unique ‘lure and kill’ nanoparticle for effective inhibition of phospholipase A2 (PLA2). The cell membrane works synergistically with a PLA2 attractant to ‘lure’ PLA2 for attack, then the PLA2 inhibitor in the cell membrane further ‘kills’ the enzyme. With effective inhibition of venomous PLA2, these nanoparticles further demonstrated strong inhibitory activity against PLA2 and attenuation of the inflammatory cascade during acute pancreatitis progression. This dissertation will serve as a paradigm for rational design of cell membrane-coated nanoparticles for therapeutic treatment of inflammatory disorders. By tapping into the biological challenges associated with anti-inflammatory therapy, cell membrane-coated nanoparticles can be tailored towards its designated biological target. By harnessing the design flexibility, this nanotechnology holds great potential to be developed into a class of drug-free anti-inflammatory nanomedicine that will be extraordinarily valuable for biomedical researchers and clinicians alike.

Inspired by the Open mHealth application architecture, which emphasizes user-controlled data security, reusable common modules and inter-operability among different mHealth applications, this dissertation introduces NDNFit, a mobile health (mHealth) application built on the Named Data Networking (NDN) architecture, while offer users the familiar user experience as traditional mHealth applications. An equally important motivation for NDNFit is NDN's application-driven architecture development philosophy -- NDNFit serves as a use case to experiment with integrating multiple NDN components into one coherent application ecosystem, as well as drive the design and development of NDN architecture and protocol.

During the design and implementation process of NDNFit, we identified and solved five problems. First, because NDN mandates that all data packets be authenticated, NDNFit builds a namespace and certificate management system to manage identity and certificate, and defines trust policies for consumers to verify data packets; to protect confidentiality, it employs NAC to encrypt Data content, and makes the first effort to obscure Data names. Second, NDNFit employs Named Function Networking (NFN) to implement data processing services, defines name conversion services to enable sharing of named functions across multiple mHealth applications, and designs key delegation mechanisms for named functions to properly secure processed data. Third, to provide reliable data storage service, NDNFit designs DSU command protocol for users to communication with the storage, and designs mechanisms to employ State Vector Synchronization (SVS) protocol to replicate data in a distributed data storage system. Fourth, NDNFit introduces catalog and denial of existence packets for efficient data transferring among different components. Last, NDNFit recognizes the issue of application mobility and refine forwarding hint to enable data reachability and support producer application mobility.

The NDNFit design illustrates that NDN's data-centric approach to networking -- naming and securing data directly, and sharing namespace between application layer and network layer -- provides a superior solution over the existing TCP/IP based solution for Open mHealth application architecture, as NDN network primitives enable users' control over their own data and facilitate interoperability among multiple applications, without relying on underlying transport layers and other third party services. The NDNFit design also demonstrates the power of NDN naming conventions -- how Data packets are named, and what is the relationship between different Data names -- in simplifying application design, that good naming conventions can help in many aspects: enable data-centric security, speed up data dissemination, or even improve data reachability.

At the end of this dissertation, we present the initial implementation of NDNFit as well as its demonstration on NDN testbed. Experimental results show that NDNFit design works well, and the lessons we learned from NDNFit design and development can benefit those of future NDN-based applications.

Protein kinases control nearly every facet of cellular function, integrating diverse inputs to regulate complex physiological processes, and aberrant kinase signaling is linked to numerous diseases. While fluorescent protein-based biosensors have revolutionized the study of kinase signaling, powerful new molecular tools capable of robustly tracking kinase activity dynamics across diverse experimental contexts are needed to fully dissect the role of kinase signaling in physiology and pathology To study PKA, we developed an ultrasensitive, second-generation excitation-ratiometric protein kinase A (PKA) activity reporter (ExRai-AKAR2), obtained via high-throughput linker library screening, which enables sensitive and rapid monitoring of live-cell PKA activity across multiple fluorescence detection modalities, including plate reading, cell sorting, one- or two-photon imaging and visual cortex imaging in awake mice. UsingExRai-AKAR2, we performed a plate reader based screen of the Johns Hopkins Drug Library, which consists of over 4000 FDA approved drugs or other clinically relevant compounds, to uncover unknown mechanisms of PKA regulation and promising drugs that could be repurposed to perturb PKA signaling pathways. We successfully discovered several novel PKA activators and inhibitors, and discovered that the inhibition of respiratory chain in mitochondria leads to the activation of soluble adenylyl cyclase and PKA. In addition, we also engineered new FRET-based AKARs with enhanced dynamic range via linker engineering. At the same time, we identified the nonspecific phosphorylation of AKARs by a nucleus localized kinase, MSK1 and engineered a new variant, AKAR6-s, to abolish the nonspecific phosphorylation by re-engineering the sensor substrate. We introduced these improved FRET-based AKARs with better sensitivity and specificity as a tool kit for studying PKA activities under specific requirements and in different imaging modalities.

Designing a biomimetic nanoparticle is a challenging topic. Despite the advances in surface chemistry and material science, it’s still impossible to fully replicate the complex interface that presents in nature. Besides, the bottom-up method fails to prevent the exposure of foreign material when administrated in vivo. To solve this challenge, we directly fuse the natural cell membrane onto the synthetic core. This top-down method quickly generates natural stealth for the synthetic material and preserves the biofunction from the resource cell. Due to its unique properties, cell membrane coating technology displays great potential in the field of drug delivery, detoxification, vaccination and biosensing.

In my dissertation, I work on engineering multi-dimensional cell-membrane coated nanoparticles (also known as “nanosponge”) to treat bacterial infection. Instead of direct inhibiting the bacteria growth, nanosponge targets the virulence factors that bacteria secrete to subvert immune surveillance, which is known to place less evolutionary pressure to induce the antibiotic resistance. In the first thrust, antivirulence efficacy is carried out solely by biomimetic nanosponges. Two types of cell membrane from different origins are explored in this direction. In the second thrust, nanosponges are mixed with the supporting material to form a stable composite, which in turn boosts the antivirulence efficacy of the nanosponge. Together, the cell membrane coating technology offers us a great tool to solve the clinical challenges by mimicking the biological events in the natural biointerface.

Securing network communications is a major challenge facing the Internet today.Due to the point-to-point communication model of TCP/IP architecture, at the time when security became a necessity, the channel-based security model, represented by Secure Sockets Layer (SSL) and its successor Transport Layer Security (TLS), was applied to secure network communication between hosts. However, designed for synchronous channels over the network infrastructure, this security solution does not fit many emerging network scenarios that require asynchronous communication. In addition, with the growth of content delivery applications, the mismatch between what application needs, i.e., secured data, and what is provided by the channel-based security model, i.e., secured channels, has also been observed in recent years.

A newly proposed architecture, Named Data Networking (NDN), has been developed over the past decade.Departing from TCP/IP's network model, NDN considers named secured data, instead of channels, as the building block of the communication, and provides an alternative to today's security model by securing data directly. Not relying on the network context, a piece of named secured data can be forwarded, cached, and reused without breaking the security primitives. To deliver named secured data at the network layer, NDN uses a stateful forwarding plane and forwards packets by names instead of IP addresses.

Under this background, there is an urge to understand the difference between the conventional channel-based security model and the new data-centric security model, and explore how to utilize the new way of doing network security to address today's security issues.For this purpose, we first revisit the key concepts of network security from the application's perspective and analyze the main features of the two security models. Then, we present our design of a number of security solutions built over NDN's named secured data, including (i) a self-contained smart home control system, (ii) a DDoS mitigation mechanism that supports fine-grained traffic throttling, (iii) a distributed ledger system for distributed rooftop solar energy system, (iv) a multiparty signing and verification toolset, and (v) a secured data prefetching system for vehicular networking.

We also describe two security solutions built on to the application level for (i) asynchronous and privacy-preserving single sign-on (SSO) and (ii) reliable leaker identification in sensitive data sharing, respectively.While not directly built over NDN because of today's deployment constraints, they follow the notion of the data-centric security model.

Through the design discussion of these systems, we confirm the unique advantages of the data-centric security model and demonstrate how the new security model and especially, NDN's named secured data, can be applied to address some challenges that are intractable to the channel-based security model.