Hong Kong Polytechnic University

About: Hong Kong Polytechnic University is a education organization based out in Hong Kong, China. It is known for research contribution in the topics: Computer science & Tourism. The organization has 29633 authors who have published 72136 publications receiving 1956312 citations. The organization is also known as: HKPU & PolyU.

Noninvasive detection of cancer-associated genome-wide hypomethylation and copy number aberrations by plasma DNA bisulfite sequencing

Abstract: We explored the detection of genome-wide hypomethylation in plasma using shotgun massively parallel bisulfite sequencing as a marker for cancer. Tumor-associated copy number aberrations (CNAs) could also be observed from the bisulfite DNA sequencing data. Hypomethylation and CNAs were detected in the plasma DNA of patients with hepatocellular carcinoma, breast cancer, lung cancer, nasopharyngeal cancer, smooth muscle sarcoma, and neuroendocrine tumor. For the detection of nonmetastatic cancer cases, plasma hypomethylation gave a sensitivity and specificity of 74% and 94%, respectively, when a mean of 93 million reads per case were obtained. Reducing the sequencing depth to 10 million reads per case was found to have no adverse effect on the sensitivity and specificity for cancer detection, giving respective figures of 68% and 94%. This characteristic thus indicates that analysis of plasma hypomethylation by this sequencing-based method may be a relatively cost-effective approach for cancer detection. We also demonstrated that plasma hypomethylation had utility for monitoring hepatocellular carcinoma patients following tumor resection and for detecting residual disease. Plasma hypomethylation can be combined with plasma CNA analysis for further enhancement of the detection sensitivity or specificity using different diagnostic algorithms. Using the detection of at least one type of aberration to define an abnormality, a sensitivity of 87% could be achieved with a specificity of 88%. These developments have thus expanded the applications of plasma DNA analysis for cancer detection and monitoring.

Green Industrial Internet of Things Architecture: An Energy-Efficient Perspective

Abstract: The Internet of Things (IoT) can support collaboration and communication between objects automatically. However, with the increasing number of involved devices, IoT systems may consume substantial amounts of energy. Thus, the relevant energy efficiency issues have recently been attracting much attention from both academia and industry. In this article we adopt an energy-efficient architecture for Industrial IoT (IIoT), which consists of a sense entities domain, RESTful service hosted networks, a cloud server, and user applications. Under this architecture, we focus on the sense entities domain where huge amounts of energy are consumed by a tremendous number of nodes. The proposed framework includes three layers: the sense layer, the gateway layer, and the control layer. This hierarchical framework balances the traffic load and enables a longer lifetime of the whole system. Based on this deployment, a sleep scheduling and wake-up protocol is designed, supporting the prediction of sleep intervals. The shifts of states support the use of the entire system resources in an energy-efficient way. Simulation results demonstrate the significant advantages of our proposed architecture in resource utilization and energy consumption.