Flow stabilization with active hydrodynamic cloaks

We demonstrate that fluid flow cloaking solutions, based on active hydrodynamic metamaterials, exist for two-dimensional flows past a cylinder in a wide range of Reynolds numbers (Re's), up to approximately 200. Within the framework of the classical Brinkman equation for homogenized porous flow, we demonstrate using two different methods that such cloaked flows can be dynamically stable for Re's in the range of 5-119. The first highly efficient method is based on a linearization of the Brinkman-Navier-Stokes equation and finding the eigenfrequencies of the least stable eigenperturbations; the second method is a direct numerical integration in the time domain. We show that, by suppressing the von Kármán vortex street in the weakly turbulent wake, porous flow cloaks can raise the critical Reynolds number up to about 120 or five times greater than for a bare uncloaked cylinder. © 2012 American Physical Society.

B cells in rheumatoid synovitis.

In rheumatoid arthritis, T cells, B cells, macrophages, and dendritic cells invade the synovial membranes, establishing complex microstructures that promote inflammatory/tissue destructive lesions. B cell involvement has been considered to be limited to autoantibody production. However, recent studies suggest that B cells support rheumatoid disease through other mechanisms. A critical element of rheumatoid synovitis is the process of ectopic lymphoid neogenesis, with highly efficient lymphoid architectures established in a nonlymphoid tissue site. Rheumatoid synovitis recapitulates the pathways of lymph node formation, and B cells play a key role in this process. Furthermore, studies of rheumatoid lesions implanted in immunodeficient mice suggest that T cell activation in synovitis is B cell dependent, indicating the role played by B cells in presenting antigens and providing survival signals.

Polyploidy and Mitotic Cell Death are Two Distinct HIV-1 Vpr-Driven Outcomes in Renal Tubule Epithelial Cells

Given the emerging epidemic of renal disease in HIV+ patients and the fact that HIV DNA and RNA persist in the kidneys of HIV+ patients despite therapy, it is necessary to understand the role of direct HIV-1 infection of the kidney. HIV-associated kidney disease pathogenesis is attributed in large part to viral proteins. Expression of Vpr in renal tubule epithelial cells (RTECs) induces G2 arrest, apoptosis and polyploidy. The ability of a subset of cells to overcome the G2/M block and progress to polyploidy is not well understood. Polyploidy frequently associates with a bypass of cell death and disease pathogenesis. Given the ability of the kidney to serve as a unique compartment for HIV-1 infection, and the observed occurrence of polyploid cells in HIV+ renal cells, it is critical to understand the mechanisms and consequences of Vpr-induced polyploidy.

Here I determined effects of HIV-1 Vpr expression in renal cells using highly efficient transduction with VSV.G pseudotyped lentiviral vectors expressing Vpr in the HK2 human tubule epithelial cell line. Using FACS, fluorescence microscopy, and live cell imaging I show that G2 escape immediately precedes a critical junction between two distinct outcomes in Vpr+ RTECs: mitotic cell death and polyploidy. Vpr+ cells that evade aberrant mitosis and become polyploid have a substantially higher survival rate than those that undergo complete mitosis, and this survival correlates with enrichment for polyploidy in cell culture over time. Further, I identify a novel role for ATM kinase in promoting G2 arrest escape and polyploidy in this context. In summary, my work identifies ATM-dependent override of Vpr-mediated G2/M arrest as a critical determinant of cell fate Vpr+ RTECs. Further, our work highlights how a poorly understood HIV mechanism, ploidy increase, may offer insight into key processes of reservoir establishment and disease pathogenesis in HIV+ kidneys.

A Molecular-scale Programmable Stochastic Process Based On Resonance Energy Transfer Networks: Modeling And Applications

While molecular and cellular processes are often modeled as stochastic processes, such as Brownian motion, chemical reaction networks and gene regulatory networks, there are few attempts to program a molecular-scale process to physically implement stochastic processes. DNA has been used as a substrate for programming molecular interactions, but its applications are restricted to deterministic functions and unfavorable properties such as slow processing, thermal annealing, aqueous solvents and difficult readout limit them to proof-of-concept purposes. To date, whether there exists a molecular process that can be programmed to implement stochastic processes for practical applications remains unknown.

In this dissertation, a fully specified Resonance Energy Transfer (RET) network between chromophores is accurately fabricated via DNA self-assembly, and the exciton dynamics in the RET network physically implement a stochastic process, specifically a continuous-time Markov chain (CTMC), which has a direct mapping to the physical geometry of the chromophore network. Excited by a light source, a RET network generates random samples in the temporal domain in the form of fluorescence photons which can be detected by a photon detector. The intrinsic sampling distribution of a RET network is derived as a phase-type distribution configured by its CTMC model. The conclusion is that the exciton dynamics in a RET network implement a general and important class of stochastic processes that can be directly and accurately programmed and used for practical applications of photonics and optoelectronics. Different approaches to using RET networks exist with vast potential applications. As an entropy source that can directly generate samples from virtually arbitrary distributions, RET networks can benefit applications that rely on generating random samples such as 1) fluorescent taggants and 2) stochastic computing.

By using RET networks between chromophores to implement fluorescent taggants with temporally coded signatures, the taggant design is not constrained by resolvable dyes and has a significantly larger coding capacity than spectrally or lifetime coded fluorescent taggants. Meanwhile, the taggant detection process becomes highly efficient, and the Maximum Likelihood Estimation (MLE) based taggant identification guarantees high accuracy even with only a few hundred detected photons.

Meanwhile, RET-based sampling units (RSU) can be constructed to accelerate probabilistic algorithms for wide applications in machine learning and data analytics. Because probabilistic algorithms often rely on iteratively sampling from parameterized distributions, they can be inefficient in practice on the deterministic hardware traditional computers use, especially for high-dimensional and complex problems. As an efficient universal sampling unit, the proposed RSU can be integrated into a processor / GPU as specialized functional units or organized as a discrete accelerator to bring substantial speedups and power savings.