A Novel Multifunctional Nanowire Platform for Highly Efficient Isolation and Analysis of Circulating Tumor-Specific Markers

Circulating tumor-specific markers are crucial to understand the molecular and cellular processes underlying cancer, and to develop therapeutic strategies for the treatment of the disease in clinical applications. Many approaches to isolate and analyze these markers have been reported. Here, we propose a straightforward method for highly efficient capture and release of exosomes and circulating tumor cells (CTCs) in a single platform with well-ordered three-dimensional (3D) architecture that is constructed using a simple electrochemical method. Conductive polypyrrole nanowires (Ppy NWs) are conjugated with monoclonal antibodies that specifically recognize marker proteins on the surface of exosomes or CTCs. In response to electrical- or glutathione (GSH)-mediated stimulation, the captured exosomes or cells can be finely controlled for retrieval from the NW platform. A surface having nano-topographic structures allows the specific recognition and capture of small-sized exosome-like vesicles (30–100 nm) by promoting topographical interactions, while physically blocking larger vesicles (i.e., microvesicles, 100–1,000 nm). In addition, vertically aligned features greatly improve cell capture efficiency after modification with desired high-binding affinity biomolecules. Notably, exosomes and CTCs can be sequentially isolated from cancer patients' blood samples using a single NW platform via modulating electrochemical and chemical cues, which clearly exhibits great potential for the diagnosis of various cancer types and for downstream analysis due to its facile, effective, and low-cost performance

Optimal control and analysis of bulk service queueing systems

Queueing Theory has been successfully and extensively applied to the scheduling, control, and analysis of complex stochastic systems. In this dissertation, the problems of optimal scheduling, control and analysis of bulk service queueing systems are studied. A Dynamic Programming formulation is provided for the optimal service strategy of a two-server bulk queue. An extension of the general bulk service rule is shown to be optimal in the sense of minimizing either the finite discounted or average waiting cost. It is shown that the optimal dispatching rule is a multi-stage threshold type where servers are dispatched only when the number of waiting customers exceeds certain threshold values depending both on the number of waiting customers and the number of servers available at decision epochs. It is conjectured that the result is extendable to the case for more than two servers. Exact analysis of the state probability in equilibrium is carried out under the optimal policy obtained for a queue with two bulk servers. Comparison of the optimal threshold policy is carried out by evaluating a single stage vs. a two-stage threshold two-server system. By calculating the mean number of customers waiting in the queue of both systems, it is shown that a two-stage threshold policy yields optimal performance over the general bulk service rule under any operating condition. Examples for different parameter sets are provided. A network of two bulk service queues served by a common transport carrier with finite capacity is analyzed where the general bulk service rule is applied only at one queue. Decomposition is employed to provide an exact analysis of the steady-state probability distribution, mean waiting time distribution, and mean number of customers waiting at both queues in equilibrium. Networks of more than two bulk service queues can be analyzed by direct extension of the methodology. An optimization procedure for the optimal threshold value to minimize total mean waiting cost is also discussed