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  1. Book ; Online: Immunization

    Wang, Ning / Wang, Ting

    Vaccine Adjuvant Delivery System and Strategies

    2018  

    Keywords Public health & preventive medicine ; immune response, nanocarrier, cellular immunity, nanoparticle, polymer, poultry
    Language English
    Size 1 electronic resource (122 pages)
    Publisher IntechOpen
    Document type Book ; Online
    Note English
    HBZ-ID HT030646059
    ISBN 9781838817831 ; 1838817832
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  2. Article ; Online: Singapore’s Experience and Enlightenment of Building a “Smart Nation”

    Wang Ning

    E3S Web of Conferences, Vol 251, p

    2021  Volume 01069

    Abstract: Singapore’s construction of a “smart country” has achieved remarkable results, and many countries around the world are currently building a smart society. This article summarizes the construction concepts and experience values of the “Smart Nation” ... ...

    Abstract Singapore’s construction of a “smart country” has achieved remarkable results, and many countries around the world are currently building a smart society. This article summarizes the construction concepts and experience values of the “Smart Nation” project in Singapore, it is intended to provide some references for the construction of china’s smart society.
    Keywords Environmental sciences ; GE1-350
    Language English
    Publishing date 2021-01-01T00:00:00Z
    Publisher EDP Sciences
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: GAFF-Based Polarizable Force Field Development and Validation for Ionic Liquids.

    Wang, Ning / Maginn, Edward J

    The journal of physical chemistry. B

    2024  Volume 128, Issue 3, Page(s) 871–881

    Abstract: Ionic liquids (ILs) have been used in many applications, including gas separations, electrochemistry, lubrication, and catalysis. Understanding how the different properties of ILs are related to their chemical structure and composition is crucial for ... ...

    Abstract Ionic liquids (ILs) have been used in many applications, including gas separations, electrochemistry, lubrication, and catalysis. Understanding how the different properties of ILs are related to their chemical structure and composition is crucial for these applications. Experimental investigations often provide limited insights and can be tedious in exploring a range of state points. Therefore, molecular simulations have emerged as a powerful tool that not only offers a microscopic perspective but also enables rapid screening and prediction of physical properties. The accuracy of these predictions, however, depends on the quality of the intermolecular potentials (force fields) used. The widely used classical fixed charge models, such as GAFF, OPLS, and CL&P, are popular due to their simplicity and computational efficiency. However, it has been shown that the use of integer charges with these classical models leads to sluggish dynamics. The use of scaled charge models can improve the dynamics, but these mean-field approaches are unable to account for polarization effects explicitly. Several different approaches have been proposed to include polarizability in IL force fields. In this work, we follow the protocol of the CL&Pol model to develop a Drude oscillator model based on the GAFF force field (Goloviznina, K., et al.
    Language English
    Publishing date 2024-01-16
    Publishing country United States
    Document type Journal Article
    ISSN 1520-5207
    ISSN (online) 1520-5207
    DOI 10.1021/acs.jpcb.3c07238
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Induction of Meiotic Initiation in Long-Term Mouse Spermatogonial Stem Cells Under Retinoid Acid and Nutrient Restriction Conditions.

    Zhang, Xiaoyu / Wang, Ning

    Methods in molecular biology (Clifton, N.J.)

    2024  Volume 2770, Page(s) 113–121

    Abstract: Spermatogonial stem cells (SSCs) produce haploid sperm via mitosis and meiosis in vivo. Although the technique to culture mouse SSCs has been well established, induction of meiosis in vitro has remained a challenge. Retinoic acid (RA) is required for ... ...

    Abstract Spermatogonial stem cells (SSCs) produce haploid sperm via mitosis and meiosis in vivo. Although the technique to culture mouse SSCs has been well established, induction of meiosis in vitro has remained a challenge. Retinoic acid (RA) is required for meiosis in vivo; however, RA alone is not sufficient to induce meiosis in vitro. Here, we describe a method in which nutrient restriction and RA synergistically induce meiotic initiation into meiotic prophase I in cultured mouse SSCs.
    MeSH term(s) Male ; Mice ; Animals ; Meiosis ; Retinoids ; Semen ; Tretinoin/pharmacology ; Stem Cells ; Nutrients ; Spermatogonia ; Spermatogenesis ; Cell Differentiation
    Chemical Substances Retinoids ; Tretinoin (5688UTC01R)
    Language English
    Publishing date 2024-02-13
    Publishing country United States
    Document type Journal Article
    ISSN 1940-6029
    ISSN (online) 1940-6029
    DOI 10.1007/978-1-0716-3698-5_9
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Innovative translational platforms for rapid developing clinical vaccines against COVID-19 and other infectious disease.

    Wang, Ning / Wang, Ting

    Biotechnology journal

    2024  Volume 19, Issue 2, Page(s) e2300658

    Abstract: A vaccine is a biological preparation that contains the antigen capable of stimulating the immune system to form the defense against pathogens. Vaccine development often confronts big challenges, including time/energy-consuming, low efficacy, lag to ... ...

    Abstract A vaccine is a biological preparation that contains the antigen capable of stimulating the immune system to form the defense against pathogens. Vaccine development often confronts big challenges, including time/energy-consuming, low efficacy, lag to pathogen emergence and mutation, and even safety concern. However, these seem now mostly conquerable through constructing the advanced translational platforms that can make innovative vaccines, sometimes, potentiated with a distinct multifunctional VADS (vaccine adjuvant delivery system), as evidenced by the development of various vaccines against the covid-19 pandemic at warp speed. Particularly, several covid-19 vaccines, such as the viral-vectored vaccines, mRNA vaccines and DNA vaccines, regarded as the innovative ones that are rapidly made via the high technology-based translational platforms. These products have manifested powerful efficacy while showing no unacceptable safety profile in clinics, allowing them to be approved for massive vaccination at also warp speed. Now, the proprietary translational platforms integrated with the state-of-the-art biotechnologies, and even the artificial intelligence (AI), represent an efficient mode for rapid making innovative clinical vaccines against infections, thus increasingly attracting interests of vaccine research and development. Herein, the advanced translational platforms for making innovative vaccines, together with their design principles and immunostimulatory efficacies, are comprehensively elaborated.
    MeSH term(s) Humans ; COVID-19 Vaccines ; COVID-19/prevention & control ; Artificial Intelligence ; Pandemics/prevention & control ; Viral Vaccines ; Communicable Diseases
    Chemical Substances COVID-19 Vaccines ; Viral Vaccines
    Language English
    Publishing date 2024-02-25
    Publishing country Germany
    Document type Journal Article ; Review
    ZDB-ID 2221885-3
    ISSN 1860-7314 ; 1860-6768
    ISSN (online) 1860-7314
    ISSN 1860-6768
    DOI 10.1002/biot.202300658
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.A 6349: Show issues Location:
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  6. Book ; Online: Adaptive Graph Convolutional Network Framework for Multidimensional Time Series Prediction

    Wang, Ning

    2022  

    Abstract: In the real world, long sequence time-series forecasting (LSTF) is needed in many cases, such as power consumption prediction and air quality prediction.Multi-dimensional long time series model has more strict requirements on the model, which not only ... ...

    Abstract In the real world, long sequence time-series forecasting (LSTF) is needed in many cases, such as power consumption prediction and air quality prediction.Multi-dimensional long time series model has more strict requirements on the model, which not only needs to effectively capture the accurate long-term dependence between input and output, but also needs to capture the relationship between data of different dimensions.Recent research shows that the Informer model based on Transformer has achieved excellent performance in long time series prediction.However, this model still has some deficiencies in multidimensional prediction,it cannot capture the relationship between different dimensions well. We improved Informer to address its shortcomings in multidimensional forecasting. First,we introduce an adaptive graph neural network to capture hidden dimension dependencies in mostly time series prediction. Secondly,we integrate adaptive graph convolutional networks into various spatio-temporal series prediction models to solve the defect that they cannot capture the relationship between different dimensions. Thirdly,After experimental testing with multiple data sets, the accuracy of our framework improved by about 10\% after being introduced into the model.

    Comment: 5 pages,2 figures
    Keywords Computer Science - Machine Learning ; Computer Science - Artificial Intelligence
    Subject code 006
    Publishing date 2022-05-08
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Book ; Online: M2R2

    Wang, Ning

    Missing-Modality Robust emotion Recognition framework with iterative data augmentation

    2022  

    Abstract: This paper deals with the utterance-level modalities missing problem with uncertain patterns on emotion recognition in conversation (ERC) task. Present models generally predict the speaker's emotions by its current utterance and context, which is ... ...

    Abstract This paper deals with the utterance-level modalities missing problem with uncertain patterns on emotion recognition in conversation (ERC) task. Present models generally predict the speaker's emotions by its current utterance and context, which is degraded by modality missing considerably. Our work proposes a framework Missing-Modality Robust emotion Recognition (M2R2), which trains emotion recognition model with iterative data augmentation by learned common representation. Firstly, a network called Party Attentive Network (PANet) is designed to classify emotions, which tracks all the speakers' states and context. Attention mechanism between speaker with other participants and dialogue topic is used to decentralize dependence on multi-time and multi-party utterances instead of the possible incomplete one. Moreover, the Common Representation Learning (CRL) problem is defined for modality-missing problem. Data imputation methods improved by the adversarial strategy are used here to construct extra features to augment data. Extensive experiments and case studies validate the effectiveness of our methods over baselines for modality-missing emotion recognition on two different datasets.
    Keywords Computer Science - Sound ; Computer Science - Artificial Intelligence ; Electrical Engineering and Systems Science - Audio and Speech Processing
    Subject code 006
    Publishing date 2022-05-05
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Article ; Online: Simultaneous Extraction and Analysis of Seven Major Saikosaponins from

    Wang, Ning / Li, Qian

    Molecules (Basel, Switzerland)

    2023  Volume 28, Issue 15

    Abstract: Saikosaponins (SS) are the main active components ... ...

    Abstract Saikosaponins (SS) are the main active components of
    MeSH term(s) Antioxidants/pharmacology ; Antioxidants/chemistry ; Molecular Docking Simulation ; Saponins/pharmacology ; Saponins/analysis
    Chemical Substances Antioxidants ; saikosaponin D (UR635J3F00) ; 2,2'-azino-di-(3-ethylbenzothiazoline)-6-sulfonic acid (28752-68-3) ; Saponins
    Language English
    Publishing date 2023-08-04
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 1413402-0
    ISSN 1420-3049 ; 1431-5165 ; 1420-3049
    ISSN (online) 1420-3049
    ISSN 1431-5165 ; 1420-3049
    DOI 10.3390/molecules28155872
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.MO 81: Show issues

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  9. Article ; Online: Identification of metabolism-related gene signature in lung adenocarcinoma.

    Wang, Ning / Wang, Hui

    Medicine

    2023  Volume 102, Issue 47, Page(s) e36267

    Abstract: Aim: Lung cancer is one of the most common cancers in China and has a high mortality rate. Most patients who are diagnosed have lost the opportunity to undergo surgery. Aberrant metabolism is closely associated with tumorigenesis. We aimed to identify ... ...

    Abstract Aim: Lung cancer is one of the most common cancers in China and has a high mortality rate. Most patients who are diagnosed have lost the opportunity to undergo surgery. Aberrant metabolism is closely associated with tumorigenesis. We aimed to identify an effective metabolism-related prediction model for assessing prognosis based on the cancer genome atlas (TCGA) and GSE116959 databases.
    Methods: TCGA and GSE116959 datasets from Gene Expression Omnibus were used to obtain lung adenocarcinoma (LUAD) data. Additionally, we captured metabolism-related genes (MRGs) from the GeneCards database. First, we extracted differentially expressed genes using R to analyze the LUAD data. We then selected the same differentially expressed genes, including 168 downregulated and 77 upregulated genes. Finally, 218 differentially expressed MRGs (DEMRGs) were included to perform functional enrichment analysis and construct a protein-protein interaction network with the help of Cytoscape and Search Tool for the Retrieval of Interacting Genes database. Cytoscape was used to visualize the intensive intervals in the network. Then univariate and Least Absolute Shrinkage and Selection Operator Cox regression analyses, which assisted in identifying the overall survival (OS)-related DEMRGs and building a 10-DEMRG prognosis model, were performed. The prognostic values, tumor immunity relevance, and molecular mechanism were further investigated. A nomogram incorporating signature, age, gender, and TNM stage was established.
    Results: A 10-DEMRG model was established to forecast the OS of LUAD through Least Absolute Shrinkage and Selection Operator regression analysis. This prognostic signature stratified LUAD patients into low-risk and high-risk groups. The receiver operating characteristic curve and K-M analysis indicated good performance of the DEMRGs signature at predicting OS in the TCGA dataset. Univariate and multivariate Cox regression also revealed that the DEMRGs signature was an independent prognosis factor in LUAD. We noticed that the risk score was substantially related to the clinical parameters of LUAD patients, covering age and stage. Immune analysis results showed that risk score was associated with some immune cells and immune checkpoints. Nomogram also verified the clinical value of the DEMRGs signature.
    Conclusion: In this study, we constructed a DEMRGs signature and established a prognostic nomogram that is robust and reliable to predict OS in LUAD. Overall, the findings could help with therapeutic customization and personalized therapies.
    MeSH term(s) Humans ; Adenocarcinoma of Lung/genetics ; Lung Neoplasms/genetics ; Nomograms ; Carcinogenesis ; Cell Transformation, Neoplastic
    Language English
    Publishing date 2023-11-25
    Publishing country United States
    Document type Journal Article
    ZDB-ID 80184-7
    ISSN 1536-5964 ; 0025-7974
    ISSN (online) 1536-5964
    ISSN 0025-7974
    DOI 10.1097/MD.0000000000036267
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Ua VI Zs.171: Show issues Location:
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  10. Article ; Online: Long-term variations of global dust emissions and climate control.

    Wang, Ning / Zhang, Yuanyuan

    Environmental pollution (Barking, Essex : 1987)

    2023  Volume 340, Issue Pt 1, Page(s) 122847

    Abstract: Dust discharged from the surface into the air has an important impact on global climate change, the ecological environment, and human health. However, the spatiotemporal variations of global dust emissions and the climate control of dust emissions from ... ...

    Abstract Dust discharged from the surface into the air has an important impact on global climate change, the ecological environment, and human health. However, the spatiotemporal variations of global dust emissions and the climate control of dust emissions from different dust sources in recent decades are still unclear. This study explores the spatiotemporal variations of global dust emissions from 1980 to 2020 based on the MERRA-2 dust emissions dataset and provides a detailed investigation of the interannual variations of dust emissions from major dust sources in the world and their contribution to the global dust cycle. On this basis, the association between global dust emissions and average wind speed (AWS), surface air temperature (SAT), precipitation (Ppt), relative humidity (RH), soil evaporation (SE), soil moisture (SM), and solar radiation (SR) were explored. In particular, the comparative importance of these climatic factors and their combined structures on dust emissions from different dust sources. The results show that North Africa contributed the most to global dust emissions, contributing 58% of the total global emissions, while South Africa and North America contributed the least to global dust emissions, at less than 1%, respectively. Classification and Regression Tree (CART) analysis shows that SR was the major factor affecting the dust emissions of Australia, East Asia, South America, and Central Asia. AWS was the major factor influencing dust emissions in North Africa and South Asia. SAT, RH, and SM were the major factors affecting dust emissions in West Asia, North America, and South Africa, respectively. There were great differences in the climatic factors combinations on dust emissions intensity in different dust sources. These findings assist us in better understanding the control of climatic factors on dust emissions from global dust sources and have important scientific significance for accurately predicting dust events and reducing disaster risks.
    MeSH term(s) Humans ; Air Conditioning ; Asia, Eastern ; Asia, Southern ; Dust ; Soil
    Chemical Substances Dust ; Soil
    Language English
    Publishing date 2023-10-31
    Publishing country England
    Document type Journal Article
    ZDB-ID 280652-6
    ISSN 1873-6424 ; 0013-9327 ; 0269-7491
    ISSN (online) 1873-6424
    ISSN 0013-9327 ; 0269-7491
    DOI 10.1016/j.envpol.2023.122847
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.A 2599: Show issues Location:
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