Cytoskeletal regulation in cell motility and invasion

Cell motility and invasion are important for development, immunity, wound healing, and tumor cell metastasis. Cells on two dimensional substrates migrate in three steps: protrusion of the front end, translocation of the cell body, and retraction of the rear end. For cells to migrate efficiently, these steps need to be well organized, and the actin cytoskeleton plays a critical role in each step. One of the actin structures important for cell motility is the stress fiber, a bundle of contractile actin filaments required for translocation of the cell body. Invasion or migration in three dimensional environments requires specialized actin rich membrane protrusions, called invadopodia, which regulate proteolytic activities that remodel the extracellular matrix for invasion. The purpose of this dissertation is to better understand the mechanisms regulating the actin cytoskeleton during cell motility and invasion. The first specific aim of this study was to elucidate the mechanism of how cysteine-rich protein 1 (CRP1) binds or bundles actin, and is localized to actin stress fibers. Using CRP1 mutants in cosedimentation assays and fluorescence microscopy, we showed that LIM1 and glycine-rich region 1 (GR1) of CRP1 are required for actin binding/bundling and localization to actin stress fibers. This is the first report of the function of the glycine-rich region, unique to CRPs, in regulating the cytoskeleton, and LIM1/GR1 as a stand alone actin binding/bundling domain. The second specific aim was to determine the role of calpain 2 in glioblastoma cell invasion. Using a calpain 2 knockdown cell line and cell permeable calpain inhibitors in transwell assays or scratch assays, we demonstrated that calpain 2 activity is required for glioblastoma cell invasion, but not migration. Using gelatin zymography, calpain 2 was shown to be important for maintaining the level of extracellular pro-MMP2 and MMP2. These data clearly demonstrate that calpain 2 is required for glioblastoma cell invasion via regulation of invadopodia associated MMP2. Overall, the work in this thesis has advanced our understanding of actin cytoskeletal regulation in stress fibers and invadopodia important for the extracellular matrix remodeling and tumor cell invasion

Local information-based control for probabilistic swarm distribution guidance

This paper proposes a closed-loop decentralised framework for swarm distribution guidance, which disperses homogeneous agents over bins to achieve a desired density distribution by using feedback gains from the current swarm status. The key difference from existing works is that the proposed framework utilises only local information, not global information ,to generate the feedback gains for stochastic policies. Dependency on local information entails various advantages including reduced inter-agent communication, a shorter timescale for obtaining new information, asynchronous implementation, and deployability without a priori mission knowledge. Our theoretical analysis shows that, even utilising only local information, the proposed framework guarantees convergence of the agents to the desired status, while maintaining the advantages of existing closed-loop approaches. Also, the analysis explicitly provides the design requirements to achieve all the advantages of the proposed framework. We provide implementation examples and report the results of empirical tests. The test results confirm the effectiveness of the proposed framework and also validate the robustness enhancement in a scenario of partial disconnection of the communication network

Anonymous hedonic game for task allocation in a large-scale multiple agent system

This paper proposes a novel game-theoretical autonomous decision-making framework to address a task allocation problem for a swarm of multiple agents. We consider cooperation of self-interested agents, and show that our proposed decentralized algorithm guarantees convergence of agents with social inhibition to a Nash stable partition (i.e., social agreement) within polynomial time. The algorithm is simple and executable based on local interactions with neighbor agents under a strongly connected communication network and even in asynchronous environments. We analytically present a mathematical formulation for computing the lower bound of suboptimality of the outcome, and additionally show that at least 50% of suboptimality can be guaranteed if social utilities are nondecreasing functions with respect to the number of coworking agents. The results of numerical experiments confirm that the proposed framework is scalable, fast adaptable against dynamical environments, and robust even in a realistic situation

An integrated decision-making framework of a heterogeneous aerial robotic swarm for cooperative tasks with minimum requirements

Given a cooperative mission consisting of multiple tasks spatially distributed, an aerial robotic swarm’s decision-making issues include team formation, team-to-task assignment, agent-to-work-position assignment and trajectory optimisation with collision avoidance. The problem becomes even more complicated when involving heterogeneous agents, tasks’ minimum requirements and fair allocation. This paper formulates all the combined issues as an optimisation problem and then proposes an integrated framework that addresses the problem in a decentralised fashion. We approximate and decouple the complex original problem into three subproblems (i.e. coalition formation, position allocation and path planning), which are sequentially addressed by three different proposed modules. The coalition formation module based on game theories deals with a max-min problem, the objective of which is to partition the agents into disjoint task-specific teams in a way that balances the agents’ work resources in proportion to the task’s minimum workload requirements. For agents assigned to the same task, given reasonable assumptions, the position allocation subproblem can be efficiently addressed in terms of computational complexity. For the trajectory optimisation, we utilise a Model Predictive Control and Sequential Convex Programming algorithm, which reduces the size of the problem so that the agents can generate collision-free trajectories on a real-time basis. As a proof of concept, we implement the framework into an unmanned aerial vehicle swarm’s cooperative stand-in jamming mission scenario and show its feasibility, fault tolerance and near-optimality based on numerical experiment

Cooperative control for a flight array of UAVs and an application in radar jamming

This paper proposes a flight array system and an integrated approach to cope with its operational issues raised in mission-planning level (i.e., task allocation) and control level (i.e., control allocation). The proposed flight array system consists of multiple ducted-fan UAVs that can assemble with each other to fly together, as well as dissemble themselves to fly individually for accomplishing a given mission. To address the task allocation problem, a game-theoretical framework is developed. This framework enables agents to converge into an agreed task allocation in a decentralised and scalable manner, while guaranteeing a certain level of global optimality. In addition, this paper suggests a cooperative control scheme based on sliding mode control and weighted pseudo-inverse techniques so that the system’s non-linearity and control allocation issue are effectively handled. As a proof-of-concept, a prototype simulation program is developed and validated in a cooperative jamming mission. The numerical simulations manifest the feasibility of effectiveness of the proposed approach

Optimal application of compressive palatal stents following mesiodens removal in pediatric patients:a Randomized Controlled Trial

There is no scientific evidence supporting the choice of a palatal stent in patients who underwent removal of an impacted supernumerary tooth. We aimed to investigate the effects of palatal stents in patients who underwent supernumerary tooth removal through a palatal approach and to suggest the optimal stent thickness and material. We recruited 144 patients who underwent extraction of a supernumerary tooth between the maxillary anterior teeth. Subjects were assigned to a control group (CG) or one of four compressive palatal stent groups (CPSGs) classified by the thickness and material of the thermoplastic acrylic stent used. Palatal gingival swelling and objective indices (healing, oral hygiene, gingival, and plaque) were evaluated before surgery and on postoperative days (PODs) 3, 7, and 14; pain/discomfort and the Child Oral Health Impact Profile (COHIP) were assessed as subjective indices of the effects of the stent. The CPSGs showed faster healing than did the CG on PODs 7 (P<0.001) and 14 (P=0.043); swelling was measured by 1.64±0.88 mm and 4.52±0.39 mm, respectively. Although swelling was least in the 4-mm hard group (0.92±0.33 mm), the difference compared with that in the 2-mm hard group (1.01±0.18 mm) was not significant (P=0.077). The CPSGs showed better COHIP (P<0.001-0.036) and pain scores (P<0.001) than did the CG on PODs 1-3. Compressive palatal stents reduce discomfort by decreasing pain and alleviating swelling. Although a stent is effective regardless of its thickness and material, 2-mm hard stents maximized such positive effects with minimal discomfort

Transparent graphene films with a tunable piezoresistive response

We demonstrate a graphene-coated polymer film as a transparent piezoresistive strain sensor. Strain sensitivity was tuned by controlling the thickness and density of the graphene layer as well as the adhesion force between graphene and the substrate. Chemically reducing the graphene oxide, thereby maximizing its adhesion to the substrate, while minimizing the coating density and thickness resulted in excellent transparency and high gauge factors. The fabrication method presented allows design optimization of transparent, high-performance, and sensitivity-tunable piezoresistive sensors, which can make inroads into such applications as wide-area strain sensors, self-sensing flexible electronics, and intelligent structural health monitoring.close0

Large-scale preparation of active caspase-3 in E. coli by designing its thrombin-activatable precursors

<p>Abstract</p> <p>Background</p> <p>Caspase-3, a principal apoptotic effector that cleaves the majority of cellular substrates, is an important medicinal target for the treatment of cancers and neurodegenerative diseases. Large amounts of the protein are required for drug discovery research. However, previous efforts to express the full-length caspase-3 gene in <it>E. coli </it>have been unsuccessful.</p> <p>Results</p> <p>Overproducers of thrombin-activatable full-length caspase-3 precursors were prepared by engineering the auto-activation sites of caspase-3 precursor into a sequence susceptible to thrombin hydrolysis. The engineered precursors were highly expressed as soluble proteins in <it>E. coli </it>and easily purified by affinity chromatography, to levels of 10–15 mg from 1 L of <it>E. coli </it>culture, and readily activated by thrombin digestion. Kinetic evaluation disclosed that thrombin digestion enhanced catalytic activity (<it>k</it>_cat/<it>K</it>_<it>M</it>) of the precursor proteins by two orders of magnitude.</p> <p>Conclusion</p> <p>A novel method for a large-scale preparation of active caspase-3 was developed by a strategic engineering to lack auto-activation during expression with amino acid sequences susceptible to thrombin, facilitating high-level expression in <it>E. coli</it>. The precursor protein was easily purified and activated through specific cleavage at the engineered sites by thrombin, generating active caspase-3 in high yields.</p