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  1. Book ; Online: LAMBDA

    Liu, Lihao / Feng, Tianyue / Xing, Xingyu / Chen, Junyi

    Covering the Solution Set of Black-Box Inequality by Search Space Quantization

    2022  

    Abstract: Black-box functions are broadly used to model complex problems that provide no explicit information but the input and output. Despite existing studies of black-box function optimization, the solution set satisfying an inequality with a black-box function ...

    Abstract Black-box functions are broadly used to model complex problems that provide no explicit information but the input and output. Despite existing studies of black-box function optimization, the solution set satisfying an inequality with a black-box function plays a more significant role than only one optimum in many practical situations. Covering as much as possible of the solution set through limited evaluations to the black-box objective function is defined as the Black-Box Coverage (BBC) problem in this paper. We formalized this problem in a sample-based search paradigm and constructed a coverage criterion with Confusion Matrix Analysis. Further, we propose LAMBDA (Latent-Action Monte-Carlo Beam Search with Density Adaption) to solve BBC problems. LAMBDA can focus around the solution set quickly by recursively partitioning the search space into accepted and rejected sub-spaces. Compared with La-MCTS, LAMBDA introduces density information to overcome the sampling bias of optimization and obtain more exploration. Benchmarking shows, LAMBDA achieved state-of-the-art performance among all baselines and was at most 33x faster to get 95% coverage than Random Search. Experiments also demonstrate that LAMBDA has a promising future in the verification of autonomous systems in virtual tests.
    Keywords Computer Science - Machine Learning ; Computer Science - Artificial Intelligence ; Computer Science - Robotics ; Mathematics - Optimization and Control
    Subject code 006
    Publishing date 2022-03-25
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Lianhua Qingwen protects LPS-induced acute lung injury by promoting M2 macrophage infiltration.

    Li, Shanshan / Feng, Tianyue / Zhang, Yingwen / Shi, Qiqi / Wang, Wanqiao / Ren, Jingyu / Shen, Gangyi / Gu, Haihui / Luo, Chengjuan / Li, Yanxin

    Journal of ethnopharmacology

    2023  Volume 320, Page(s) 117467

    Abstract: Ethnopharmacological relevance: Traditional Chinese medicine Lianhua Qingwen (LHQW) was used to treat regular seasonal influenza. In recent years, LHQW exerts significant therapeutic effects in treating influenza and Coronavirus Disease 2019 (COVID-19). ...

    Abstract Ethnopharmacological relevance: Traditional Chinese medicine Lianhua Qingwen (LHQW) was used to treat regular seasonal influenza. In recent years, LHQW exerts significant therapeutic effects in treating influenza and Coronavirus Disease 2019 (COVID-19). However, the potential mechanisms are not yet understood and need further study.
    Aim of study: This study aims to look into the influence of LHQW on lung inflammation and macrophage phenotype, and to clarify the connection between macrophage plasticity and LHQW.
    Methods: The cell viability, marker expression, response to LPS stimulation, and phagocytosis of Raw264.7 were detected after LHQW treatment. In an LPS-induced acute lung injury (ALI) mouse model, the alleviating effect of LHQW on lung injury was investigated. The total macrophages and M2 macrophages in mice lungs and the peripheral blood monocytes after LHQW treatment were detected. The cell viability and polarization of peripheral blood macrophages treated with LHQW were detected.
    Results: Here, we demonstrate that LHQW protects LPS-induced ALI by promoting M2 macrophage infiltration. LHQW treatment inhibited the inflammatory response and pro-inflammatory phenotype of Raw264.7 macrophages. High concentrations of LHQW promoted the phagocytic capacity of Raw264.7 macrophages. In an ALI mouse model, LHQW alleviated lung injury and no significant hepatotoxicity was observed. By Immunohistochemistry (IHC) analysis, LHQW increased the infiltration of macrophages, mainly M2 macrophages. Consistent with Raw264.7, LHQW also decreased the expression of M1 markers in peripheral blood macrophages. In addition, LHQW blood plasma promoted the M2-type polarization of peripheral blood macrophages.
    Conclusions: Taken together, our data demonstrate that LHQW reduces the inflammatory response and ameliorates acute lung injury by promoting anti-inflammatory polarization of macrophages.
    MeSH term(s) Mice ; Animals ; Humans ; Lipopolysaccharides/toxicity ; Lipopolysaccharides/metabolism ; Influenza, Human ; Macrophages ; Acute Lung Injury/chemically induced ; Acute Lung Injury/drug therapy ; Acute Lung Injury/prevention & control ; Pneumonia/metabolism ; Disease Models, Animal ; Lung
    Chemical Substances Lipopolysaccharides
    Language English
    Publishing date 2023-11-18
    Publishing country Ireland
    Document type Journal Article
    ZDB-ID 134511-4
    ISSN 1872-7573 ; 0378-8741
    ISSN (online) 1872-7573
    ISSN 0378-8741
    DOI 10.1016/j.jep.2023.117467
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: MYCN protein stability is a better prognostic indicator in neuroblastoma.

    Yang, Yi / Zhao, Jie / Zhang, Yingwen / Feng, Tianyue / Yv, Bo / Wang, Jing / Gao, Yijin / Yin, Minzhi / Tang, Jingyan / Li, Yanxin

    BMC pediatrics

    2022  Volume 22, Issue 1, Page(s) 404

    Abstract: Objective: MYCN oncogene amplification is associated with treatment failure and poor prognosis in neuroblastoma. To date, most detection methods of MYCN focus on DNA copy numbers instead of protein expression, which is the real one performing biological ...

    Abstract Objective: MYCN oncogene amplification is associated with treatment failure and poor prognosis in neuroblastoma. To date, most detection methods of MYCN focus on DNA copy numbers instead of protein expression, which is the real one performing biological function, for poor antibodies. The current investigation was to explore a fast and reliable way to detect MYCN protein expression and evaluate its performance in predicting prognosis.
    Methods: Several MYCN antibodies were used to detect MYCN protein expression by immunohistochemistry (IHC), and one was chosen for further study. We correlated the IHC results of MYCN from 53 patients with MYCN fluorescence in situ hybridization (FISH) and identified the sensitivity and specificity of IHC. The relationship between patient prognosis and MYCN protein expression was detected from this foundation.
    Results: MYCN amplification status detected by FISH was most valuable for INSS stage 3 patients. In the cohort of 53 samples, IHC test demonstrated 80.0-85.7% concordance with FISH results. Further analyzing those cases with inconsistent results, we found that patients with MYCN amplification but low protein expression tumors always had a favorable prognosis. In contrast, if patients with MYCN non-amplified tumors were positive for MYCN protein, they had a poor prognosis.
    Conclusion: MYCN protein level is better than MYCN amplification status in predicting the prognosis of neuroblastoma patients. Joint of FISH and IHC could confirm MYCN protein stability and achieve better prediction effect than the singular method.
    MeSH term(s) Gene Amplification ; Humans ; In Situ Hybridization, Fluorescence ; N-Myc Proto-Oncogene Protein/genetics ; N-Myc Proto-Oncogene Protein/metabolism ; Neuroblastoma/diagnosis ; Neuroblastoma/genetics ; Neuroblastoma/metabolism ; Prognosis ; Protein Stability
    Chemical Substances MYCN protein, human ; N-Myc Proto-Oncogene Protein
    Language English
    Publishing date 2022-07-11
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2041342-7
    ISSN 1471-2431 ; 1471-2431
    ISSN (online) 1471-2431
    ISSN 1471-2431
    DOI 10.1186/s12887-022-03449-1
    Database MEDical Literature Analysis and Retrieval System OnLINE

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