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"Wang, Ning"
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ADMETlab: a platform for systematic ADMET evaluation based on a comprehensively collected ADMET database
Current pharmaceutical research and development (R&D) is a high-risk investment which is usually faced with some unexpected even disastrous failures in different stages of drug discovery. One main reason for R&D failures is the efficacy and safety deficiencies which are related largely to absorption, distribution, metabolism and excretion (ADME) properties and various toxicities (T). Therefore, rapid ADMET evaluation is urgently needed to minimize failures in the drug discovery process. Here, we developed a web-based platform called ADMETlab for systematic ADMET evaluation of chemicals based on a comprehensively collected ADMET database consisting of 288,967 entries. Four function modules in the platform enable users to conveniently perform six types of drug-likeness analysis (five rules and one prediction model), 31 ADMET endpoints prediction (basic property: 3, absorption: 6, distribution: 3, metabolism: 10, elimination: 2, toxicity: 7), systematic evaluation and database/similarity searching. We believe that this web platform will hopefully facilitate the drug discovery process by enabling early drug-likeness evaluation, rapid ADMET virtual screening or filtering and prioritization of chemical structures. The ADMETlab web platform is designed based on the Django framework in Python, and is freely accessible at
http://admet.scbdd.com/
.
Journal Article
How China became capitalist
\"How China Became Capitalist details the extraordinary, and often accidental, journey that China has taken over the past thirty years in transforming itself from a closed agrarian socialist economy to an indomitable force in the international arena. The authors revitalize the debate around the development of the Chinese system through the use of primary sources. They persuasively argue that the reforms implemented by the Chinese leaders did not represent a concerted attempt to create a capitalist economy, but that the ideas from the West eventually culminated in a fundamental change to their socialist model, forming an accidental path to capitalism. Coase and Wang argue that the pragmatic approach of \"seeking truth from fact\" is in fact much more in line with Chinese culture. How China Became Capitalist challenges the received wisdom about the future of the Chinese economy, arguing that while China has enormous potential for growth, this could be hampered by the leaders' propensity for control, both in terms of economics and their monopoly of ideas and power\"-- Provided by publisher.
Book
Research on coal and gas outburst risk prediction based on improved search algorithm optimized deep learning network
With the gradual deepening of coal mining, the surrounding rock pressure significantly increases, and the risk of gas release and accumulation also increases, increasing the likelihood of coal and gas outburst hazards. This study used boxplot and data interpolation method to preprocess data and used correlation to screen out highly correlated influencing factors as disaster prediction indicators. Build an initial prediction model framework using Convolutional Neural Network (CNN), optimize model hyperparameters using Chaos Mapping and Levy Flight Improved Crow Search Algorithm (ICSA), and establish a coal and gas outburst prediction model based on ICSA-CNN. Finally, a comparative model was established to compare the evaluation indicators and confusion matrix. According to the results, the ICSA-CNN model stood out as the most accurate in its predictive capabilities, better robustness and generalization ability, and higher security.
Journal Article
Lee Kuan Yew through the eyes of Chinese scholars
\"A compilation of essays by highly-respected Chinese scholars in which they evaluate the life, work and philosophy of Lee Kuan Yew, founding Prime Minister of Singapore. Presenting a range of views from a uniquely Chinese/Asian perspective, this book provides valuable insights for those who wish to gain a fuller and deeper understanding of Lee Kuan Yew, the man, as well as Singapore, his nation\"-- Provided by publisher.
Book
Association between sarcopenia and osteoarthritis: A protocol for meta-analysis
Sarcopenia, a relatively new syndrome referring to the age-related decline of muscle strength and degenerative loss of skeletal muscle mass and function, often resulting in frailty, disability, and mortality. Osteoarthritis, as a prevalent joint degenerative disease, is affecting over 250 million patients worldwide, and it is the fifth leading cause of disability. Despite the high prevalence of osteoarthritis, there are still lack of efficient treatment potions in clinics, partially due to the heterogeneous and complexity of osteoarthritis pathology. Previous studies revealed the association between sarcopenia and osteoarthritis, but the conclusions remain controversial and the prevalence of sarcopenia within osteoarthritis patients still needs to be elucidated. To identify the current evidence on the prevalence of sarcopenia and its association with osteoarthritis across studies, we performed this systematic review and meta-analysis that would help us to further confirm the association between these two diseases. Electronic sources including PubMed, Embase, and Web of Science will be searched systematically following appropriate strategies to identify relevant studies from inception up to 28 February 2022 with no language restriction. Two investigators will evaluate the preselected studies independently for inclusion, data extraction and quality assessment using a standardized protocol. Meta-analysis will be performed to pool the estimated effect using studies assessing an association between sarcopenia and osteoarthritis. Subgroup analyses will also be performed when data are sufficient. Heterogeneity and publication bias of included studies will be investigated.
Journal Article
Quantitative study on hepatic genotoxicity of neodymium and its molecular mechanisms based on Benchmark Dose method
Neodymium, a rare earth element, has been shown to induce genotoxicity in mice, but the molecular mechanisms behind this effect are not fully understood. This study aims to investigate the genotoxic effects of intragastric administration of neodymium nitrate (Nd(NO
)
) over 28 consecutive days and to elucidate the underlying molecular mechanisms.
We detected the content of neodymium in mouse liver tissue using ICP-MS and assessed the percentage of tail DNA in mouse hepatocytes using the alkaline comet assay to evaluate genotoxicity. Additionally, we evaluated genetic toxicological biomarkers (reactive oxygen species (ROS), 8-hydroxy-2'-deoxyguanosine (8-OHdG), and γ-H2AX) and the expression levels of genes related to the p53 pathway in the mouse liver.
Our findings indicate a potential accumulation of (Nd(NO
)
) in the livers of mice, leading to DNA double-strand breaks in hepatocytes, as evidenced by comet and γ-H2AX assays. Nd(NO3)3 significantly increased the percentage of tail DNA in hepatocytes and upregulated the expression of molecules related to the p53 pathway, including ATM, Wip1, ATR, Chk2, MDM2, p53, p21, and NF-κB, at the transcriptional level. The treatment also effectively triggered the production of ROS, 8-OHdG, and γ-H2AX in liver tissue.
These results suggest that (Nd(NO
)
) induces hepatic genotoxicity and injury in mice and modulates the expression of genes associated with DNA damage response, carcinogenesis, and inflammatory processes. The study provides insights into the molecular mechanisms by which neodymium nitrate exerts its genotoxic effects and underscores the importance of further investigating the potential health risks associated with neodymium exposure.
Journal Article
Analytics and optimization for renewable energy integration
The scope of this book covers the modeling and forecast of renewable energy and operation and planning of power system with renewable energy integration. The first part presents mathematical theories of stochastic mathematics; the second presents modelling and analytic techniques for renewable energy generation; the third provides solutions on how to handle the uncertainty of renewable energy in power system operation. It includes advanced stochastic unit commitment models to acquire the optimal generation schedule under uncertainty, efficient algorithms to calculate the probabilistic power, and an efficient operation strategy for renewable power plants participating in electricity markets.
Book
Using the Fuzzy Method and Multi-Criteria Decision Making to Analyze the Impact of Digital Economy on Urban Tourism
Urban tourism promotes the economic growth of a nation around the year through direct and indirect incomes. In recent years, the digital economy has impacted the growth of urban tourism through hassle-free money transactions and expenditures. This article, therefore, introduces a Multi-Criteria Fuzzy-based Decision-Making Method (MCFDMM) for validating the impact of the digital economy impact over tourism. The study introduces a new framework, DLFDSS-RRM, that uses deep learning and fuzzy decision support systems for residence right management, enhancing resource allocation, security, and resident satisfaction in urban residential communities. The criteria such as expenses, positive response, and repeated payments are validated by the tourists across their travel plan. These conditions satisfying the tourist’s expectations are estimated based on their reviews of economic conditions are validated. The validation is performed against the growth of the country from urban tourism. The fuzzy process validates the growth of the country between two successive financial quarters based on the above conditions. In the condition analysis, the fuzzy process identifies the least derivatives contributing to minimal economic growth. This is reversed using the hiking condition that occurs in any quarter and hinders economic growth. Therefore, the process is validated using the metrics growth rate, condition satisfaction, analysis rate, analysis time, and unrelated assessment. The comparative analysis across various models reveals growth rates ranging from 0.263 to 0.4055, condition satisfaction percentages from 53.747 to 74.351, and analysis rates from 0.275 to 0.4662.
Journal Article