Fast and Secure Key Generation with Channel Obfuscation in Slowly Varying Environments

Physical-layer secret key generation has emerged as a promising solution for establishing cryptographic keys by leveraging reciprocal and time-varying wireless channels. However, existing approaches suffer from low key generation rates and vulnerabilities under various attacks in slowly varying environments. We propose a new physical-layer secret key generation approach with channel obfuscation, which improves the dynamic property of channel parameters based on random filtering and random antenna scheduling. Our approach makes one party obfuscate the channel to allow the legitimate party to obtain similar dynamic channel parameters, yet prevents a third party from inferring the obfuscation information. Our approach allows more random bits to be extracted from the obfuscated channel parameters by a joint design of the K-L transform and adaptive quantization. Results from a testbed implementation show that our approach, compared to the existing ones that we evaluate, performs the best in generating high entropy bits at a fast rate and is able to resist various attacks in slowly varying environments. Specifically, our approach can achieve a significantly faster secret bit generation rate at roughly 67 bit/pkt, and the key sequences can pass the randomness tests of the NIST test suite

Fast and Secure Key Generation with Channel Obfuscation in Slowly Varying Environments

Physical-layer secret key generation has emerged as a promising solution for establishing cryptographic keys by leveraging reciprocal and time-varying wireless channels. However, existing approaches suffer from low key generation rates and vulnerabilities under various attacks in slowly varying environments. We propose a new physical-layer secret key generation approach with channel obfuscation, which improves the dynamic property of channel parameters based on random filtering and random antenna scheduling. Our approach makes one party obfuscate the channel to allow the legitimate party to obtain similar dynamic channel parameters, yet prevents a third party from inferring the obfuscation information. Our approach allows more random bits to be extracted from the obfuscated channel parameters by a joint design of the K-L transform and adaptive quantization. Results from a testbed implementation show that our approach, compared to the existing ones that we evaluate, performs the best in generating high entropy bits at a fast rate and is able to resist various attacks in slowly varying environments. Specifically, our approach can achieve a significantly faster secret bit generation rate at roughly 67 bit/pkt, and the key sequences can pass the randomness tests of the NIST test suite

A Computational Drug-Target Network for Yuanhu Zhitong Prescription

Yuanhu Zhitong prescription (YZP) is a typical and relatively simple traditional Chinese medicine (TCM), widely used in the clinical treatment of headache, gastralgia, and dysmenorrhea. However, the underlying molecular mechanism of action of YZP is not clear. In this study, based on the previous chemical and metabolite analysis, a complex approach including the prediction of the structure of metabolite, high-throughput in silico screening, and network reconstruction and analysis was developed to obtain a computational drug-target network for YZP. This was followed by a functional and pathway analysis by ClueGO to determine some of the pharmacologic activities. Further, two new pharmacologic actions, antidepressant and antianxiety, of YZP were validated by animal experiments using zebrafish and mice models. The forced swimming test and the tail suspension test demonstrated that YZP at the doses of 4 mg/kg and 8 mg/kg had better antidepressive activity when compared with the control group. The anxiolytic activity experiment showed that YZP at the doses of 100 mg/L, 150 mg/L, and 200 mg/L had significant decrease in diving compared to controls. These results not only shed light on the better understanding of the molecular mechanisms of YZP for curing diseases, but also provide some evidence for exploring the classic TCM formulas for new clinical application

Prediction of Drug Positioning for Quan-Du-Zhong Capsules Against Hypertensive Nephropathy Based on the Robustness of Disease Network

Hypertensive nephropathy (HN) is a medical condition in which chronic high blood pressure causes different kidney damage, including vascular, glomerular and tubulointerstitial lesions. For HN patients, glomerular and tubulointerstitial lesions occur in different renal structure with distinct mechanisms in the progression of renal damage. As an extraction of Eucommia ulmoides, Quan-du-zhong capsule (QDZJN) has the potential to treat HN due to antihypertensive and renal protective activities. Complicated mechanism of HN underlying various renal lesions and the “multi-component and multi-target” characteristics of QDZJN make identifying drug positioning for various renal lesions of HN complex. Here, we proposed an approach based on drug perturbation of disease network robustness, that is used to assess QDZJN positioning for various HN lesions. Topological characteristics of drug-attacked nodes in disease network were used to evaluated nodes importance to network. To evaluate drug attack on the whole disease network of various HN lesions, the robustness of disease networks before/after drug attack were assessed and compared with null models generated from random networks. We found that potential targets of QDZJN were specifically expressed in the kidneys and tended to participate in the “inflammatory response,” “regulation of blood pressure,” and “response to LPS and hypoxia,” and they were also key factors of HN. Based on network robustness assessment, QDZJN may specifically target glomeruli account to the stronger influence on glomerular network after removal of its potential targets. This prediction strategy of drug positioning is suitable for multi-component drugs based on drug perturbation of disease network robustness for two renal compartments, glomeruli and tubules. A stronger influence on the disease network of glomeruli than of tubules indicated that QDZJN may specifically target glomerular lesion of HN patients and will provide more evidence for precise clinical application of QDZJN against HN. Drug positioning approach we proposed also provides a new strategy for predicting precise clinical use of multi-target drugs

Curcumin Reduces Cognitive Deficits by Inhibiting Neuroinflammation through the Endoplasmic Reticulum Stress Pathway in Apolipoprotein E4 Transgenic Mice.

Apolipoprotein E4 (ApoE4) is the main genetic risk factor for Alzheimer's disease (AD), but the exact way in which it causes AD remains unclear. Curcumin is considered to have good therapeutic potential for AD, but its mechanism has not been clarified. This study aims to observe the effect of curcumin on ApoE4 transgenic mice and explore its possible molecular mechanism. Eight-month-old ApoE4 transgenic mice were intraperitoneally injected with curcumin for 3 weeks, and the Morris water maze test was used to evaluate the cognitive ability of the mice. Immunofluorescence staining, immunohistochemistry, western blotting, and enzyme-linked immunosorbent assay (ELISA) were used to examine the brain tissues of the mice. Curcumin reduced the high expression of ApoE4 and the excessive release of inflammatory factors in ApoE4 mice. In particular, the expression of marker proteins of endoplasmic reticulum (ER) stress was significantly increased in ApoE4 mice, while curcumin significantly reduced the increase in the expression of these proteins. Collectively, curcumin alleviates neuroinflammation in the brains of ApoE4 mice by inhibiting ER stress, thus improving the learning and cognitive ability of transgenic mice

Analysis of Oxoglaucine in the Treatment of Breast Cancer Based on Network Pharmacology and Bioinformatics

To explore the potential molecular mechanism of Oxoglaucine(OG) in the treatment of Breast Cancer(BC) based on network pharmacology and bioinformatics. TCMSP and SwissTargetPrediction databases search for OG Related targets, and GeneCards database finds all BC-related targets. Take the intersection of OG and BC as all potential targets that inhibit BC. All potential targets are topologically analyzed by Cytoscape 3.7.1 software, and finally the core target is obtained. The start analysisi function in the DAVID database performs bioinformatics analysis on all core targets, and further visualizes them with the help of R language tools. As a result, 104 potential targets were obtained, of which SRC, PIK3CA, EGFR, MTOR, ESR1, MAPK1, PTGS2, AR, and NOS3 were the main core targets. OG inhibits the occurrence of BC through Pathways in cancer, PI3K-Akt signaling pathway, Proteoglycans in cancer, ErbB signaling pathway, HIF-1 signaling pathway related pathways, mainly involving signal transduction, protein phosphorylation, negative regulation of apoptotic process, positive regulation of transcription from RNA polymerase II promoter, phosphatidylinositol-mediated signaling biological processes. This study initially reveals the molecular mechanism of OG inhibiting BC, which provides a reference for further research