Cooperative Jamming with AF Relay in Power Monitoring and Communication Systems for Mining

In underground mines, physical layer security (PLS) technology is a promising method for the effective and secure communication to monitor the mining process. Therefore, in this paper, we investigate the PLS of an amplify-and-forward relay-aided system in power monitoring and communication systems for mining, with the consideration of multiple eavesdroppers. Explicitly, we propose a PLS scheme of cooperative jamming and precoding for a full-duplex system considering imperfect channel state information. To maximize the secrecy rate of the communications, an effective block coordinate descent algorithm is used to design the precoding and jamming matrix at both the source and the relay. Furthermore, the effectiveness and convergence of the proposed scheme with high channel state information uncertainty have been proven

New advances of DNA methylation in liver fibrosis, with special emphasis on the crosstalk between microRNAs and DNA methylation machinery

AbstractEpigenetics refers to the study of heritable changes in the pattern of gene expression that is controlled by a mechanism specifically not due to changes the primary DNA sequence. Well-known epigenetic mechanisms include DNA methylation, post-translational histone modifications and RNA-based mechanisms including those controlled by small non-coding RNAs (miRNAs). Recent studies have shown that epigenetic modifications orchestrate the hepatic stellate cell (HSC) activation and liver fibrosis. In this review we focus on the aberrant methylation of CpG island promoters of select genes is the prominent epigenetic mechanism to effectively silence gene transcription facilitating HSC activation and liver fibrosis. Furthermore, we also discuss epigenetic dysregulation of tumor-suppressor miRNA genes by promoter DNA methylation and the interaction of DNA methylation with miRNAs involved in the regulation of HSC activation and liver fibrosis. Recent advances in epigenetics alterations in the pathogenesis of liver fibrosis and their possible use as new therapeutic targets and biomarkers

Prompt-based Node Feature Extractor for Few-shot Learning on Text-Attributed Graphs

Text-attributed Graphs (TAGs) are commonly found in the real world, such as social networks and citation networks, and consist of nodes represented by textual descriptions. Currently, mainstream machine learning methods on TAGs involve a two-stage modeling approach: (1) unsupervised node feature extraction with pre-trained language models (PLMs); and (2) supervised learning using Graph Neural Networks (GNNs). However, we observe that these representations, which have undergone large-scale pre-training, do not significantly improve performance with a limited amount of training samples. The main issue is that existing methods have not effectively integrated information from the graph and downstream tasks simultaneously. In this paper, we propose a novel framework called G-Prompt, which combines a graph adapter and task-specific prompts to extract node features. First, G-Prompt introduces a learnable GNN layer (\emph{i.e.,} adaptor) at the end of PLMs, which is fine-tuned to better capture the masked tokens considering graph neighborhood information. After the adapter is trained, G-Prompt incorporates task-specific prompts to obtain \emph{interpretable} node representations for the downstream task. Our experiment results demonstrate that our proposed method outperforms current state-of-the-art (SOTA) methods on few-shot node classification. More importantly, in zero-shot settings, the G-Prompt embeddings can not only provide better task interpretability than vanilla PLMs but also achieve comparable performance with fully-supervised baselines.Comment: Under revie

Efficacy and safety of guselkumab for the treatment of patients with moderate-to-severe plaque psoriasis: A metaanalysis of randomized clinical trials

Purpose: To conduct a systematic analysis on data from randomized controlled trials (RCTs) on different doses of guselkumab, and provide high-quality evidence for its use in the treatment of patients with moderate-to-severe plaque psoriasis (PsO). Methods: Related studies were searched using online search engines including MEDLINE, PubMed, and central registry of Cochrane controlled trials from January 2001 to October 2017. Only randomized, placebo-controlled, double-blind clinical trials involving guselkumab- and placebo-treated PsO subjects were included. Results: Five eligible double-blind, randomized, and placebo-controlled trials involving patients with moderate-to-severe PsO subjects treated with guselkumab were included. Compared with the placebo groups, the proportion of patients with improvements in Psoriasis Area and Severity Index (PASI) 75 (RR= 12.14; 95% CI= 9.11-16.16; p < 0.001); PASI 90 (RR= 23.26; 95% CI =14.57-37.13; p < 0.001), and PASI 100 (RR = 37.66; 95% CI = 15.81-89.69; p < 0.001) were significantly higher than those in guselkumab-treated groups. Furthermore, the guselkumab-treated groups showed significant decreases in Physician’s Global Assessment (PGA) score (RR = 10.46; 95% CI = 7.96-13.83; p < 0.001) and the Dermatology Life Quality Index (DLQI) score (SMD = -1.3; 95% CL = -1.4 to -1.19; p < 0.001), when compared with the placebo groups. However, there were no significant differences in adverse events (AEs) (RR = 1.01; 95% CL = 0.93-1.11; p > 0.05); severe adverse events (SAEs) (RR = 1.32; 95% CI =0.69-2.54; p > 0.05) and study discontinuations (RR = 0.79; 95% CI = 0.42-1.48; p > 0.05) between the two groups. Conclusion: This meta-analysis summarizes available evidence for the use of guselkumab in psoriasis. The results suggest that guselkumab is superior to placebo in moderate-to-severe psoriasis, and is welltolerated, effective, and safe in improving the severity of disease and quality of life. Keywords: Guselkumab, Effectiveness, Safety, Plaque psoriasis, Meta-analysis, Quality of lif

Network pharmacology-based elucidation of the molecular mechanism underlying the anti-migraine effect of Asari Radix et Rhizoma

Purpose: To determine the molecular mechanism involved in the anti-migraine effect of Asari Radix et Rhizoma (ARR) using network pharmacology. Methods: The compounds present in ARR were identified through information retrieval from literature and public databases, and were screened based on absorption, distribution, metabolism, excretion and toxicity. Target genes related to the selected compounds and migraine were identified or predicted from public databases. Hub genes in ARR against migraine were identified through analysis of interactions in overlapping genes between compounds and migraine target genes, based on STRING database. Gene enrichment analysis of overlapping genes was performed using Database for Annotation, Visualization and Integrated Discovery. Results: A total of 138 compounds were selected as potential bioactive compounds in ARR. Target genes related to the selected compounds (611 genes) and migraine (278 genes) were obtained, including 71 overlapping genes. The hub genes in the anti-migraine effect of ARR were BDNF, IL6, COMT, APP and TNF. Gene enrichment analysis showed the top 10 biological processes or pathways involved in the mechanism of anti-migraine action of ARR. The tissue source of the overlapping genes was not limited to the brain. The results from gene enrichment analysis revealed that the effect of ARR on migraine was holistic, which is characteristic of traditional Chinese medicines. Conclusion: Network pharmacology has been used to decipher the molecular mechanism involved in the action of ARR against migraine. The results provide a scientific basis for the clinical effect of ARR on migraine