Doctor of Philosophy

dissertationThermal ablation is widely used, first line local-regional therapy for unresectable hepatocellular carcinoma (HCC). Although high temperature delivered by thermal energy results in efficient coagulation necrosis in tumor cells, various factors including tumor size, shape, location, and cirrhosis can lead to un-uniform heat distribution and inefficient cell damage. As a result, the incomplete ablation causes high rates of tumor recurrence and poor survival for HCC patients. Cells that are not completely ablated can induce heat shock proteins (HSPs), which are cellular gatekeepers to protect tumor cells from thermal damage and prepare them for future neoplastic growth. Synchronous adjuvant chemotherapy targeting those cells can achieve more complete tumor abrogation and prevent future tumor recurrence. This dissertation describes a strategy to combat postablation recurrence by synchronous inhibition of heat shock protein 90 (HSP90) by thermo-responsive, elastin-like polypeptide (ELP)-based biopolymer conjugates. ELP copolymer carries high concentrations of a potent HSP90 inhibitor, geldanamycin (GA), which inhibit the induction of HSP90 and further destabilize numerous HSP90 client proteins critical for cell survival. It is hypothesized that combination of thermal ablation with concomitant inhibition of HSP90 via ELP-GA conjugates can achieve synergistic anticancer effect. Specifically, the ablation-created hyperthermia will sensitize tumor cells to be more vulnerable to the drug, which will be conjugated with high concentrations through thermally targeted, ELP-based biopolymer systems. The ELP conjugates, in turn, will reach and kill the remaining viable cells to prevent future recurrence. ELP-GA conjugates that ferry multiple GAs and rapidly respond to hyperthermia were synthesized, characterized, and evaluated for activity in HCC models. The cytotoxicity of ELP-GA conjugates was enhanced with hyperthermia treatment, and effective HSP90 inhibition was achieved in HCC cell lines. In a tumor-bearing mouse model, electrocautery-based thermal ablation offered effective destruction of tumor core and created a hyperthermia zone for targeted delivery and accumulation of ELP-GA conjugates. Results demonstrate that the combination of thermal ablation and targeted HSP90 inhibition can enhance the anticancer effect and cellular delivery of macromolecular chemotherapeutics to achieve safe, synergistic, and long-term anticancer effect with no tumor recurrence observed. The combination approach paves the way for developing molecular-targeted intervention to increase the efficacy of first-line local-regional therapies for HCC

CAN THE INTERNET HELP RELIEVE DEPRESSION?

Depression is a very serious problem in our modern society. It can influence people negatively in many ways. Although many scientists are trying to find efficient ways to deal with depression, there are still no final conclusions. Using data from the China Health and Retirement Longitudinal Study (CHARLS), this study shows that in China, internet use among older people (aged 45 and above) helps relieve their depression symptoms. Combining this finding with steadily growing cellphone use, this suggests that developing specially APPs for older people to use smart phones can help combat depression in China. Other ways to reach the rural population via the internet can also be powerful tools to help with depression

Recover Triggered States: Protect Model Against Backdoor Attack in Reinforcement Learning

A backdoor attack allows a malicious user to manipulate the environment or corrupt the training data, thus inserting a backdoor into the trained agent. Such attacks compromise the RL system's reliability, leading to potentially catastrophic results in various key fields. In contrast, relatively limited research has investigated effective defenses against backdoor attacks in RL. This paper proposes the Recovery Triggered States (RTS) method, a novel approach that effectively protects the victim agents from backdoor attacks. RTS involves building a surrogate network to approximate the dynamics model. Developers can then recover the environment from the triggered state to a clean state, thereby preventing attackers from activating backdoors hidden in the agent by presenting the trigger. When training the surrogate to predict states, we incorporate agent action information to reduce the discrepancy between the actions taken by the agent on predicted states and the actions taken on real states. RTS is the first approach to defend against backdoor attacks in a single-agent setting. Our results show that using RTS, the cumulative reward only decreased by 1.41% under the backdoor attack

The residential coal consumption : disparity in urban-rural China

We appreciate the support of the Program for Major Projects in Philosophy and Social Science Research of the Ministry of Education of China (No. 14JZD031), Key Program of National Social Science Fund of China (No. 15AJY005), National Natural Science Foundation of China (Nos. 71473203, 71171001, and 71471001), and New Century Excellent Talents in University (No. NCET-12-0595).Peer reviewedPostprin