Energy Consumption Analysis for Continuous Phase Modulation in Smart-Grid Internet of Things of beyond 5G.

Wireless sensor network (WSN) underpinning the smart-grid Internet of Things (SG-IoT) has been a popular research topic in recent years due to its great potential for enabling a wide range of important applications. However, the energy consumption (EC) characteristic of sensor nodes is a key factor that affects the operational performance (e.g., lifetime of sensors) and the total cost of ownership of WSNs. In this paper, to find the modulation techniques suitable for WSNs, we investigate the EC characteristic of continuous phase modulation (CPM), which is an attractive modulation scheme candidate for WSNs because of its constant envelope property. We first develop an EC model for the sensor nodes of WSNs by considering the circuits and a typical communication protocol that relies on automatic repeat request (ARQ)-based retransmissions to ensure successful data delivery. Then, we use this model to analyze the EC characteristic of CPM under various configurations of modulation parameters. Furthermore, we compare the EC characteristic of CPM with that of other representative modulation schemes, such as offset quadrature phase-shift keying (OQPSK) and quadrature amplitude modulation (QAM), which are commonly used in communication protocols of WSNs. Our analysis and simulation results provide insights into the EC characteristics of multiple modulation schemes in the context of WSNs; thus, they are beneficial for designing energy-efficient SG-IoT in the beyond-5G (B5G) and the 6G era.

Slug overexpression induces stemness and promotes hepatocellular carcinoma cell invasion and metastasis.

Detection of metastasis of hepatocellular carcinoma (HCC) is crucial for early diagnosis. Epithelial-mesenchymal transition (EMT) is a common event in the metastasis of tumor cells. Slug and Snail are homologous proteins, which play an important role in EMT. The present study aimed to investigate whether Slug and Snail overexpression is associated with the invasiveness of HCC in vitro and in vivo. Invasion, colony formation and wound healing assays, as well as flow cytometry analysis, were performed to examine the invasiveness and proliferation capabilities of HepG2 cells following transfection with cNDA or the siRNA of Slug or Snail. The effects of Slug on HCC in vivo were examined using a xenograft model. Slug upregulation increased the percentage of cluster of differentiation (CD)133+ cells among HepG2 cells, and induced cell invasion and proliferation; whereas Snail upregulation did not affect the cells in vitro. The Slug overexpression group exhibited the highest rate of tumor growth compared with the Snail overexpression and control groups in vivo. These findings demonstrated that Slug increases the percentage of CD133+ cells, promotes the clonigenicity of HCC cells and induces a stronger stemness in Slug-overexpressing cells. These changes activate dormant developmental pathways in invading tumor cells. Thus, Slug may serve as a novel target for HCC prognosis and therapy.

Differential expression of STAT1 and p21 proteins predicts pancreatic cancer progression and prognosis.

OBJECTIVE: The transcription factor Stat1 is a member of the family of signal transducers and transcription activators and responds to interferon-γ stimulation. p21 is a p53-responsive gene for cell cycle regulation and mediates Stat1 antitumor activity. The aim of this study was to analyze their expression for prediction of pancreatic cancer progression and prognosis. METHODS: A total of 100 pancreatic adenocarcinoma tissue specimens were used for construction of a pancreatic cancer tissue microarray for immunohistochemical staining of Stat1 and p21 expression. RESULTS: Stat1 and p21 proteins were expressed in 88% (88/100) and 82% (82/100) of pancreatic adenocarcinoma tissue specimens, and the expression was inversely associated with tumor differentiation, clinical stages, and lymph node metastasis of pancreatic cancer. There was no association with age, tumor size, or invasion. Moreover, the Kaplan-Meier curve analysis showed that patients with higher Stat1 and p21 expression had better overall survival rates than those with low expression of Stat1 and p21 proteins. CONCLUSIONS: The loss of expression of Stat1 and p21 proteins corresponded to lymph node metastasis, advanced stage, tumor dedifferentiation, and poor prognosis in patients with pancreatic cancer.