Combined Treatment with MEK and mTOR Inhibitors is Effective in In Vitro and In Vivo Models of Hepatocellular Carcinoma.

Background: Hepatocellular carcinoma (HCC) is the most common primary liver cancer histotype, characterized by high biological aggressiveness and scarce treatment options. Recently, we have established a clinically relevant murine HCC model by co-expressing activated forms of v-akt murine thymoma viral oncogene homolog (AKT) and oncogene c-mesenchymal-epithelial transition (c-Met) proto-oncogenes in the mouse liver via hydrodynamic tail vein injection (AKT/c-MET mice). Tumor cells from these mice demonstrated high activity of the AKT/ mammalian target of rapamycin (mTOR) and Ras/ Mitogen-activated protein kinase (MAPK) signaling cascades, two pathways frequently co-induced in human HCC. Methods: Here, we investigated the therapeutic efficacy of sorafenib, regorafenib, the MEK inhibitor PD901 as well as the pan-mTOR inhibitor MLN0128 in the AKT/c-Met preclinical HCC model. Results: In these mice, neither sorafenib nor regorafenib demonstrated any efficacy. In contrast, administration of PD901 inhibited cell cycle progression of HCC cells in vitro. Combined PD901 and MLN0128 administration resulted in a pronounced growth constraint of HCC cell lines. In vivo, treatment with PD901 or MLN0128 alone moderately slowed HCC growth in AKT/c-MET mice. Importantly, the simultaneous administration of the two drugs led to a stable disease with limited tumor progression in mice. Mechanistically, combined mitogen-activated extracellular signal-regulated kinase (MEK) and mTOR inhibition resulted in a stronger cell cycle inhibition and growth arrest both in vitro and in vivo. Conclusions: Our study indicates that combination of MEK and mTOR inhibitors might represent an effective therapeutic approach against human HCC

Modelling Heat Transfer of Carbon Nanotubes

Modelling heat transfer of carbon nanotubes is important for the thermal management of nanotube-based composites and nanoelectronic device. By using a finite element method for three-dimensional anisotropic heat transfer, we have simulated the heat conduction and temperature variations of a single nanotube, a nanotube array and a part of nanotube-based composite surface with heat generation. The thermal conductivity used is obtained from the upscaled value from the molecular simulations or experiments. Simulations show that nanotube arrays have unique cooling characteristics due to its anisotropic thermal conductivity.Comment: 10 pages, 4 figure

Spin-glass ground state in a triangular-lattice compound YbZnGaO4_4

We report on comprehensive results identifying the ground state of a triangular-lattice structured YbZnGaO$_4$ to be spin glass, including no long-range magnetic order, prominent broad excitation continua, and absence of magnetic thermal conductivity. More crucially, from the ultralow-temperature a.c. susceptibility measurements, we unambiguously observe frequency-dependent peaks around 0.1 K, indicating the spin-glass ground state. We suggest this conclusion to hold also for its sister compound YbMgGaO$_4$, which is confirmed by the observation of spin freezing at low temperatures. We consider disorder and frustration to be the main driving force for the spin-glass phase.Comment: Version as accepted to PR

Interference Modeling And Control In Wireless Networks

With the successful commercialization of IEEE802.11 standard, wireless networks have become a tight-knit of our daily life. As wireless networks are increasingly applied to real- time and mission-critical tasks, how to ensuring real-time, reliable data delivery emerges as an important problem. However, wireless communication is subject to various dynamics and uncertainties due to the broadcast nature of wireless signal. In particular, co-channel interfer- ence not only reduces the reliability and throughput of wireless networks, it also increases the variability and uncertainty in data communication [64, 80, 77]. A basis of interference control is the interference model which \emph{predicts} whether a set of concurrent transmissions may interfere with one another. Two commonly used models, the \textit{SINR model} and the \textit{radio-K model}, are thoroughly studied in our work. To address the limitations of those models, we propose the physical-ratio-K(PRK) interference model as a reliablility-oriented instantiation of the ratio-K model, where the link-specific choice of K adapts to network and environmental conditions as well as application QoS requirements to ensure certain minimum reliability of every link. On the other hand, the interference among the transmissions, limits the number of con- current transmissions. We formulate the concept of \emph{interference budget} that, given a set of scheduled transmissions in a time slot, characterizes the additional interference power that can be tolerated by all the receivers without violating the application requirement on link reliability. We propose the scheduling algorithm \emph{iOrder} that optimizes link ordering by considering both interference budget and queue length in scheduling. Through both simulation and real-world experiments, we observe that optimizing link ordering can improve the performance of existing algorithms by a significant. Based on the strong preliminary research result on interference modeling and control, we will extend our method into distributed protocol designs. One future work will focus on imple- menting the \textit{PRK model} in a distributed protocols. We will also explore the benefits of using multiple channels in the interference control

Three Essays On Insurance Asset Management

The insurance industry manages a large amount of financial assets. In recent years, a growing number of investment companies are providing insurance asset management solutions, and the use of external asset management by the insurance industry is increasing over time. Therefore, understanding insurance asset management is important for academics and practitioners in both insurance and general finance. In the first essay, we investigate industrial portfolio tilt (referred to as “industry bias”) in the U.S. property liability insurers’ comstock portfolios. We find that U.S. property-liability insurers exhibit a negative industry bias by tilting their portfolios away from their own industry. We examine the nature of the industry bias and find that property-liability insurers have asymmetric information in investing in industrially close stocks but that their underwriting risk drives their portfolio tilt away from these stocks. Therefore, the property-liability insurers’ negative industry bias is driven by hedging in spite of information advantages. In the second essay, we investigate the betting-against-beta strategy in the presence of leverage in the U.S. property-liability insurance industry and empirically test whether these institutional investors’ leverage is an important determinant of their portfolio beta choice. Through empirical analysis, we find that property-liability insurers’ portfolio beta is not negatively related to their leverage, implying that these institutional investors do not bet against beta. In addition, we explore its explanation using a holdings-based calendar-time portfolio approach and find that these institutional investors’ low-beta portfolio does not outperform their high-beta portfolio. Overall, our results suggest that betting-against-beta strategy does not exist. In the third essay, we investigate the relation between cash holdings and market concentration in the U.S. property-liability insurance industry. We leverage the highly disaggregated nature of insurer statutory data to construct a refined market concentration measure, market space weighted concentration, which more accurately reflects an insurer’s state-line market space. Through our empirical analysis, we provide evidence in support of the predation risk theory. Specifically, insurers exposed to higher market concentration tend to hold more cash, and their cash is used to support future growth by reducing predation risk