PROTECTION AGAINST ENDOTHELIAL INFLAMMATION BY GREEN TEA FLAVONOIDS

Endothelial inflammation is a pivotal early event in the development of atherosclerosis. Long term exposure to cardiovascular risk factors will ultimately exhaust those protective anti-inflammatory factors such as the heme oxygenase (HO) system. The HO system plays a critical role in cellular and tissue self-defense against oxidative stress and inflammation. Caveolae are membrane domains and are particularly abundant in endothelial cells, where they are believed to play a major role in the regulation of endothelial vesicular trafficking as well as the uptake of lipids and related lipophilic compounds, possibly including bioactive food components such as flavonoids. Research in this dissertation addresses the role of HO-1 and caveolae on dietary flavonoid epigallocatechin gallate (EGCG) mediated protection against pro-inflammatory cytokine tumor necrosis factor-α (TNF-α) and linoleic acid-induced activation of endothelial cells. The data support the hypothesis that EGCG protects against TNF-α-induced monocyte recruitment and adhesion partially through the induction of HO-1 and bilirubin. The observed anti-inflammatory effects of EGCG are mimicked by the HO-1 inducer cobalt protoporphyrin (CoPP) and abolished by HO-1 gene silencing. Nrf2 is the major transcription factor of phase II antioxidant enzymes including HO-1. Results clearly show that EGCG-induced HO-1 expression and subsequent bilirubin productions are dependent on functional Nrf2. EGCG also can down-regulate the base-line level of caveolin-1. Furthermore, silencing of the caveolin-1 gene can markedly down-regulate linoleic acid-induced COX-2 and MCP-1, indicating that caveolae may be a critical platform regulating inflammatory signaling pathways. Similar to EGCG treatment, silencing of caveolin-1 can also result in the activation of Nrf2, up-regulation of HO-1 and bilirubin. This may be one of the mechanisms to explain the protection effect of caveolin-1 gene silencing against endothelial inflammation. Moreover, EGCG rapidly accumulates in caveolae, which is associated with caveolin-1 displacement from the plasma membrane towards the cytosol. Caveolin-1 gene silencing can significantly reduce the uptake of EGCG in endothelial cells within 30 min. These data suggest that caveolae may play a role in the uptake and transport of EGCG in endothelial cells. These studies provide a novel target through which EGCG functions to protect against inflammatory diseases such as atherosclerosis

An Empirical Study of Bank Capital and Risk Taking: Evidence from the Recent Financial Crisis

In this paper, we examine the relationship between bank capital and risk taking in the United States. We use bank capital data in 2007, and bank risk-taking data in 2008. We measure risk taking in three ways: allowance for loan and lease losses, net charge-offs, and provision for loan and lease losses. We measure capital also in three ways: tier 1 leverage ratio, tier 1 risk-based capital ratio, and total risk-based capital ratio. Overall, our results suggest that banks with higher capital ratios take more risk

Selective disruption of high sensitivity heat activation but not capsaicin activation of TRPV1 channels by pore turret mutations.

The capsaicin receptor transient receptor potential vanilloid (TRPV)1 is a highly heat-sensitive ion channel. Although chemical activation and heat activation of TRPV1 elicit similar pungent, painful sensation, the molecular mechanism underlying synergistic activation remains mysterious. In particular, where the temperature sensor is located and whether heat and capsaicin share a common activation pathway are debated. To address these fundamental issues, we searched for channel mutations that selectively affected one form of activation. We found that deletion of the first 10 amino acids of the pore turret significantly reduced the heat response amplitude and shifted the heat activation threshold, whereas capsaicin activation remained unchanged. Removing larger portions of the turret disrupted channel function. Introducing an artificial sequence to replace the deleted region restored sensitive capsaicin activation in these nonfunctional channels. The heat activation, however, remained significantly impaired, with the current exhibiting diminishing heat sensitivity to a level indistinguishable from that of a voltage-gated potassium channel, Kv7.4. Our results demonstrate that heat and capsaicin activation of TRPV1 are structurally and mechanistically distinct processes, and the pore turret is an indispensible channel structure involved in the heat activation process but is not part of the capsaicin activation pathway. Synergistic effect of heat and capsaicin on TRPV1 activation may originate from convergence of the two pathways on a common activation gate

Deep Sufficient Representation Learning via Mutual Information

We propose a mutual information-based sufficient representation learning (MSRL) approach, which uses the variational formulation of the mutual information and leverages the approximation power of deep neural networks. MSRL learns a sufficient representation with the maximum mutual information with the response and a user-selected distribution. It can easily handle multi-dimensional continuous or categorical response variables. MSRL is shown to be consistent in the sense that the conditional probability density function of the response variable given the learned representation converges to the conditional probability density function of the response variable given the predictor. Non-asymptotic error bounds for MSRL are also established under suitable conditions. To establish the error bounds, we derive a generalized Dudley's inequality for an order-two U-process indexed by deep neural networks, which may be of independent interest. We discuss how to determine the intrinsic dimension of the underlying data distribution. Moreover, we evaluate the performance of MSRL via extensive numerical experiments and real data analysis and demonstrate that MSRL outperforms some existing nonlinear sufficient dimension reduction methods.Comment: 43 pages, 6 figures and 5 table

Predicting Strategic Energy Storage Behaviors

Energy storage are strategic participants in electricity markets to arbitrage price differences. Future power system operators must understand and predict strategic storage arbitrage behaviors for market power monitoring and capacity adequacy planning. This paper proposes a novel data-driven approach that incorporates prior model knowledge for predicting the strategic behaviors of price-taker energy storage systems. We propose a gradient-descent method to find the storage model parameters given the historical price signals and observations. We prove that the identified model parameters will converge to the true user parameters under a class of quadratic objective and linear equality-constrained storage models. We demonstrate the effectiveness of our approach through numerical experiments with synthetic and real-world storage behavior data. The proposed approach significantly improves the accuracy of storage model identification and behavior forecasting compared to previous blackbox data-driven approaches.Comment: accepted by IEEE Transactions on Smart Grid, 202

Fresnel diffraction patterns as accelerating beams

We demonstrate that beams originating from Fresnel diffraction patterns are self-accelerating in free space. In addition to accelerating and self-healing, they also exhibit parabolic deceleration property, which is in stark contrast to other accelerating beams. We find that the trajectory of Fresnel paraxial accelerating beams is similar to that of nonparaxial Weber beams. Decelerating and accelerating regions are separated by a critical propagation distance, at which no acceleration is present. During deceleration, the Fresnel diffraction beams undergo self-smoothing, in which oscillations of the diffracted waves gradually focus and smooth out at the critical distance