University of Macau

About: University of Macau is a education organization based out in Macao, Macau, China. It is known for research contribution in the topics: Population & Control theory. The organization has 6636 authors who have published 18324 publications receiving 327384 citations. The organization is also known as: UM & UMAC.

Targeting the Endocytic Pathway and Autophagy Process as a Novel Therapeutic Strategy in COVID-19.

Abstract: Coronaviruses (CoVs) are a group of enveloped, single-stranded positive genomic RNA viruses and some of them are known to cause severe respiratory diseases in human, including Severe Acute Respiratory Syndrome (SARS), Middle East Respiratory Syndrome (MERS) and the ongoing coronavirus disease-19 (COVID-19). One key element in viral infection is the process of viral entry into the host cells. In the last two decades, there is increasing understanding on the importance of the endocytic pathway and the autophagy process in viral entry and replication. As a result, the endocytic pathway including endosome and lysosome has become important targets for development of therapeutic strategies in combating diseases caused by CoVs. In this mini-review, we will focus on the importance of the endocytic pathway as well as the autophagy process in viral infection of several pathogenic CoVs inclusive of SARS-CoV, MERS-CoV and the new CoV named as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and discuss the development of therapeutic agents by targeting these processes. Such knowledge will provide important clues for control of the ongoing epidemic of SARS-CoV-2 infection and treatment of COVID-19.

On False Data-Injection Attacks against Power System State Estimation: Modeling and Countermeasures

Abstract: It is critical for a power system to estimate its operation state based on meter measurements in the field and the configuration of power grid networks. Recent studies show that the adversary can bypass the existing bad data detection schemes, posing dangerous threats to the operation of power grid systems. Nevertheless, two critical issues remain open: 1) how can an adversary choose the meters to compromise to cause the most significant deviation of the system state estimation, and 2) how can a system operator defend against such attacks? To address these issues, we first study the problem of finding the optimal attack strategy--i.e., a data-injection attacking strategy that selects a set of meters to manipulate so as to cause the maximum damage. We formalize the problem and develop efficient algorithms to identify the optimal meter set. We implement and test our attack strategy on various IEEE standard bus systems, and demonstrate its superiority over a baseline strategy of random selections. To defend against false data-injection attacks, we propose a protection-based defense and a detection-based defense, respectively. For the protection-based defense, we identify and protect critical sensors and make the system more resilient to attacks. For the detection-based defense, we develop the spatial-based and temporal-based detection schemes to accurately identify data-injection attacks.

Adaptive Neural Output Feedback Tracking Control for a Class of Uncertain Discrete-Time Nonlinear Systems

Abstract: This brief studies an adaptive neural output feedback tracking control of uncertain nonlinear multi-input-multi-output (MIMO) systems in the discrete-time form. The considered MIMO systems are composed of n subsystems with the couplings of inputs and states among subsystems. In order to solve the noncausal problem and decouple the couplings, it needs to transform the systems into a predictor form. The higher order neural networks are utilized to approximate the desired controllers. By using Lyapunov analysis, it is proven that all the signals in the closed-loop system is the semi-globally uniformly ultimately bounded and the output errors converge to a compact set. In contrast to the existing results, the advantage of the scheme is that the number of the adjustable parameters is highly reduced. The effectiveness of the scheme is verified by a simulation example.

Theranostic Liposomes with Hypoxia-Activated Prodrug to Effectively Destruct Hypoxic Tumors Post-Photodynamic Therapy.

Abstract: Photodynamic therapy (PDT), a noninvasive cancer therapeutic method triggered by light, would lead to severe tumor hypoxia after treatment. Utilizing a hypoxia-activated prodrug, AQ4N, which only shows toxicity to cancer cells under hypoxic environment, herein, a multipurpose liposome is prepared by encapsulating hydrophilic AQ4N and hydrophobic hexadecylamine conjugated chlorin e6 (hCe6), a photosensitizer, into its aqueous cavity and hydrophobic bilayer, respectively. After chelating a 64Cu isotope with Ce6, the obtained AQ4N-64Cu-hCe6-liposome is demonstrated to be an effective imaging probe for in vivo positron emission tomography, which together with in vivo fluorescence and photoacoustic imaging uncovers efficient passive homing of those liposomes after intravenous injection. After being irradiated with the 660 nm light-emitting diode light, the tumor bearing mice with injection of AQ4N-hCe6-liposome show severe tumor hypoxia, which in turn would trigger activation of AQ4N, and finally contributes t...