Cells serve as basic units of life and represent intricate biological molecular systems. The vast number of cellular molecules with their signaling and regulatory circuitries forms an intertwined network. In this network, each pathway interacts non-linearly with others through different intermediates. Thus, the challenge of manipulating cellular functions for desired outcomes, such as cancer eradication and controlling viral infection lies within the integrative system of regulatory circuitries. By using a closed-loop system control scheme, we can efficiently analyze biological signaling networks and manipulate their behavior through multiple stimulations on a collection of pathways. Specifically, we aimed to maximize the reactivation of Kaposi's Sarcoma-associated Herpesvirus (KSHV) in a Primary Effusion Lymphoma cell line. The advantage of this approach is that it is wellsuited to study complex integrated systems; it circumvents the need for detailed information of individual signaling components; and it investigates the network as a whole by utilizing key systemic outputs as indicators.
An unsteady microfluidic T-form mixer driven by pressure disturbances was designed and investigated. The performance of the mixer was examined both through numerical simulation and experimentation. Linear Stokes equations were used for these low Reynolds number flows. Unsteady mixing in a micro-channel of two aqueous solutions differing in concentrations of chemical species was described using a convection-dominated diffusion equation. The task was greatly simplified by employing linear superimposition of a velocity field for solving a scalar species concentration equation. Low-order-based numerical codes were found not to be suitable for simulation of a convection-dominated mixing process due to erroneous computational dissipation. The convection-dominated diffusion problem was addressed by designing a numerical algorithm with high numerical accuracy and computational-cost effectiveness. This numerical scheme was validated by examining a test case prior to being applied to the mixing simulation. Parametric analysis was performed using this newly developed numerical algorithm to determine the best mixing conditions. Numerical simulation identified the best mixing condition to have a Strouhal number (St)of 0.42. For a T-junction mixer (with channel width = 196 μm), about 75% mixing can be finished within a mixing distance of less than 3 mm (i.e. 15 channel width) at St = 0.42 for flow with a Reynolds number less than 0.24. Numerical results were validated experimentally by mixing two aqueous solutions containing yellow and blue dyes. Visualization of the flow field under the microscope revealed a high level of agreement between numerical simulation and experimental results.
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