In Silico Syndrome Prediction for Coronary Artery Disease in Traditional Chinese Medicine

Coronary artery disease (CAD) is the leading causes of deaths in the world. The differentiation of syndrome (ZHENG) is the criterion of diagnosis and therapeutic in TCM. Therefore, syndrome prediction in silico can be improving the performance of treatment. In this paper, we present a Bayesian network framework to construct a high-confidence syndrome predictor based on the optimum subset, that is, collected by Support Vector Machine (SVM) feature selection. Syndrome of CAD can be divided into asthenia and sthenia syndromes. According to the hierarchical characteristics of syndrome, we firstly label every case three types of syndrome (asthenia, sthenia, or both) to solve several syndromes with some patients. On basis of the three syndromes' classes, we design SVM feature selection to achieve the optimum symptom subset and compare this subset with Markov blanket feature select using ROC. Using this subset, the six predictors of CAD's syndrome are constructed by the Bayesian network technique. We also design Naïve Bayes, C4.5 Logistic, Radial basis function (RBF) network compared with Bayesian network. In a conclusion, the Bayesian network method based on the optimum symptoms shows a practical method to predict six syndromes of CAD in TCM

A survey of blockchain and artificial intelligence for 6G wireless communications

The research on the sixth-generation (6G) wireless communications for the development of future mobile communication networks has been officially launched around the world. 6G networks face multifarious challenges, such as resource-constrained mobile devices, difficult wireless resource management, high complexity of heterogeneous network architectures, explosive computing and storage requirements, privacy and security threats. To address these challenges, deploying blockchain and artificial intelligence (AI) in 6G networks may realize new breakthroughs in advancing network performances in terms of security, privacy, efficiency, cost, and more. In this paper, we provide a detailed survey of existing works on the application of blockchain and AI to 6G wireless communications. More specifically, we start with a brief overview of blockchain and AI. Then, we mainly review the recent advances in the fusion of blockchain and AI, and highlight the inevitable trend of deploying both blockchain and AI in wireless communications. Furthermore, we extensively explore integrating blockchain and AI for wireless communication systems, involving secure services and Internet of Things (IoT) smart applications. Particularly, some of the most talked-about key services based on blockchain and AI are introduced, such as spectrum management, computation allocation, content caching, and security and privacy. Moreover, we also focus on some important IoT smart applications supported by blockchain and AI, covering smart healthcare, smart transportation, smart grid, and unmanned aerial vehicles (UAVs). Moreover, we thoroughly discuss operating frequencies, visions, and requirements from the 6G perspective. We also analyze the open issues and research challenges for the joint deployment of blockchain and AI in 6G wireless communications. Lastly, based on lots of existing meaningful works, this paper aims to provide a comprehensive survey of blockchain and AI in 6G networks. We hope this surve..

Exome sequencing revealed PDE11A as a novel candidate gene for early-onset Alzheimer\u27s disease

To identify novel risk genes and better understand the molecular pathway underlying Alzheimer\u27s disease (AD), whole-exome sequencing was performed in 215 early-onset AD (EOAD) patients and 255 unrelated healthy controls of Han Chinese ethnicity. Subsequent validation, computational annotation and in vitro functional studies were performed to evaluate the role of candidate variants in EOAD. We identified two rare missense variants in the phosphodiesterase 11A (PDE11A) gene in individuals with EOAD. Both variants are located in evolutionarily highly conserved amino acids, are predicted to alter the protein conformation and are classified as pathogenic. Furthermore, we found significantly decreased protein levels of PDE11A in brain samples of AD patients. Expression of PDE11A variants and knockdown experiments with specific short hairpin RNA (shRNA) for PDE11A both resulted in an increase of AD-associated Tau hyperphosphorylation at multiple epitopes in vitro. PDE11A variants or PDE11A shRNA also caused increased cyclic adenosine monophosphate (cAMP) levels, protein kinase A (PKA) activation and cAMP response element-binding protein phosphorylation. In addition, pretreatment with a PKA inhibitor (H89) suppressed PDE11A variant-induced Tau phosphorylation formation. This study offers insight into the involvement of Tau phosphorylation via the cAMP/PKA pathway in EOAD pathogenesis and provides a potential new target for intervention

Effects of gamma-Valerolactone/H2O Solvent on the Degradation of pubescens for Its Fullest Utilization

Solvent-thermal conversion of biomass was promising for obtaining value-added chemicals. However, little was known about the interactions between solvents and biomass in the process, which hindered the effective utilization of biomass. The effects of gamma-valerolactone (GVL) and H2O on enhancing pubescens degradation via the cleavage of inter-and intramolecular linkages were studied. At 160 degrees C, H2O selectively promoted the cleavage of the intermolecular linkages by forming hydrogen bonds, making mainly contributions to hemicellulose dissolution, while GVL and H2O promoted lignin dissolution by forming hydrogen bonds with -OCH3 group of lignin. H2O promoted the cleavage of beta-(1,4)-glycosidic bonds in hemicellulose derived oligomers to xylose, while the oxygen in the ring of GVL might interact with hydroxyl groups of xylose unit to enhance the dehydration of xylose to furfural, whereas GVL with H2O promoted the depolymerization of lignin to oligomers mainly including beta-O-4' and beta-beta' linkages connecting to G and S units

Peer Reading Promotion in University Libraries

University libraries use social networks to promote reading; however, there are challenges to increasing the use of these library platforms, such as poor promotion and low reader participation. Therefore, these libraries need to find ways of dealing with the behavior characteristics of social network readers. In this study, a simulation experiment was developed to explore the behaviors of readers seeking book reviews and opinions on social networks. The study draws on social network theory to find the causes of students’ behavior and how these affect their selection of information. Finally, it presents strategies for peer reading promotion in university libraries

Effects of Electrolytic Copper Foil Roughness on Lithium-Ion Battery Performance

Improving the interfacial properties between the electrode materials and current collectors plays a significant role in lithium-ion batteries. Here, four kinds of electrolytic copper foils with roughness (Rz) values of 1.2, 1.5, 2.2, and 2.8 μm were prepared via an electropolishing technique. Reducing the roughness of the electrolytic copper foil can effectively improve the wettability of the anode slurry. The electrolytic copper foil with a roughness value of 1.2 μm shows the best coating uniformity of the graphite anode slurry. The battery with this electrolytic copper foil (Rz = 1.2 μm) as the current collector exhibits fifth-cycle capacities of 358.7 and 102.5 mAh g−1 at 0.2 and 3.0 C, respectively, showing excellent rate capability. In addition, at 0.5 C, the battery exhibits an initial discharge capacity of 319.5 mAh g−1 and a 100th-cycle capacity retention rate of 98.1%, demonstrating a high level of cycling performance. These results indicate that reducing the roughness of electrolytic copper foil can provide a feasible route to improve the performance of lithium-ion batteries

A Simple Two-Step Method for the Selective Conversion of Hemicellulose in <i>Pubescens</i> to Furfural

A two-step method was adopted to produce furfural from the selective dissolution and conversion of hemicellulose in <i>pubescens</i>. First, in GVL­(γ-valerolactone)-H₂O co-solvent at 160 °C, H₂O promoted the cleavage of chemical bonds linking hemicellulose, lignin, and cellulose, and GVL further helped the co-dissolution of hemicellulose (93.6 wt %) and lignin derivatives (80.2 wt %), leaving a high purity cellulose (83.3 wt %). Heating to 200 °C, the liquid system obtained with NaCl and THF added, achieved the maximum yield of 76.9 mol % with 82.2% selectivity to furfural based on the moles of converted hemicellulose using a 5 wt % <i>pubescens</i> to solvent ratio. It was demonstrated that NaCl with GVL promoted the depolymerization of oligomers to small molecular products (Mw < 150 Da), while the co-contribution of NaCl and co-solvent improved the selectivity to furfural. Cl^– could interact strongly with C-OH-2,3,4 of the xylose unit, and the dehydration of xylose to form furfural might first occur on C-OH-4 of xylose, then on C-OH-2,3 of xylose, which enhanced the dehydration and ring open reaction via the cleavage of C₁–O₆ bonds, then promoted the formation of furfural by inhibiting the retro-aldol reaction to form lactic acid. The co-contribution of NaCl and co-solvent was benefical not only for the selective conversion of the mixture containing hemicellulose-derived monomers and oligomers to furfural but also for obtaining a lower molecular weight lignin derivatives (150–500 Da) that could be further used