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Artemisia argyi extract subfraction exerts an antifungal effect against dermatophytes by disrupting mitochondrial morphology and function

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Chinese Journal of Natural Medicines 2024年第1期22卷 47-61页

作者： CHEN Le ZHU Yunyun GUO Chaowei GUO Yujie ZHAO Lu MIAO Yuhuan DU Hongzhi liu dahui College of Pharmacy Hubei University of Chinese MedicineWuhan 430065China National Resource Center for Chinese Materia Medica China Academy of Chinese Medical SciencesBeijing 100700China College of Pharmacy Nanjing University of Chinese MedicineNanjing 210023China

Artemisia argyi(***),a plant with a longstanding history as a raw material for traditional medicine and functional diets in Asia,has been used traditionally to bathe and soak feet for its disinfectant and itch-relieving *** its widespread use,scientific evidence validating the antifungal efficacy of *** water extract(AAWE)against dermatophytes,particularly Trichophyton rubrum,Trichophyton mentagrophytes,and Microsporum gypseum,remains *** study aimed to substantiate the scientific basis of the folkloric use of *** by evaluating the antifungal effects and the underlying molecular mechanisms of its active subfraction against *** results indicated that AAWE exhibited excellent antifungal effects against the three aforementioned dermatophyte *** subfraction AAWE6,isolated using D101 macroporous resin,emerged as the most potent *** minimum inhibitory concentrations(MICs)of AAWE6 against ***,***,and *** were 312.5,312.5,and 625μg·mL−1,*** electron microscopy(TEM)results and assays of enzymes linked to cell wall integrity and cell membrane function indicated that AAWE6 could penetrate the external protective barrier of ***,creating breaches(“small holes”),and disrupt the internal mitochondrial structure(“granary”).Furthermore,transcriptome data,quantitative real-time PCR(RT-qPCR),and biochemical assays corroborated the severe disruption of mitochondrial function,evidenced by inhibited tricarboxylic acid(TCA)cycle and energy ***,chemical characterization and molecular docking analyses identified flavonoids,primarily eupatilin(131.16±4.52 mg·g^(−1))and jaceosidin(4.17±0.18 mg·g^(−1)),as the active components of *** conclusion,the subfraction AAWE6 from *** exerts antifungal effects against dermatophytes by disrupting mitochondrial morphology and *** research validates the traditional use of *** and provides scient

关键词： Artemisia argyi Dermatophyte Antifungal activity Mitochondrial structure Mitochondrial function Transcriptome analysis

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氢动力船加注过程高压氢气泄漏数值模拟

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太阳能学报 2024年第3期45卷 298-304页

作者：孔祥宇胡始弘康济川闫发锁刘大辉董岩烟台哈尔滨工程大学研究院烟台266000 哈尔滨工程大学船舶工程学院哈尔滨150001 中国船舶与海洋工程设计研究院上海200011 中集海洋工程研究院有限公司烟台264670

该文针对氢动力船加注过程中可能发生的高压氢气泄漏问题进行了数值模拟研究。首先,通过与已有实验结果对比,验证了CFD虚喷嘴模型和分层流动模型的有效性。其次,结合氢动力船实际加注场景,着重分析风速、障碍物对高压氢气扩散行为的影... 详细信息

该文针对氢动力船加注过程中可能发生的高压氢气泄漏问题进行了数值模拟研究。首先,通过与已有实验结果对比,验证了CFD虚喷嘴模型和分层流动模型的有效性。其次,结合氢动力船实际加注场景,着重分析风速、障碍物对高压氢气扩散行为的影响。最后,利用半球扩散模型划分疏散区域,提高氢动力船加注过程的安全性。结果表明:分层流动模型与实验结果拟合性更好;高速的风可阻止氢气上浮,增加氢气泄漏距离,降低氢气浓度;泄漏源下游设置障碍物一定程度上缩短了易燃云在水平方向上的扩散距离。

关键词：氢气泄漏数值模型氢动力船

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Estimating Design Loads with Environmental Contour Approach Using Copulas for an Offshore Jacket Platform

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Journal of Ocean University of China 2020年第5期19卷 1029-1041页

作者： ZHAO Yuliang liu dahui DONG Sheng College of Engineering Ocean University of ChinaQingdao 266100China CIMC Offshore Engineering Institute Co. Ltd.Yantai 264670China

Jacket-type offshore platforms are widely used for oil, gas field, and energy development in shallow water. The design of a jacket structure is highly dependent on target environmental variables. This study focuses on a strategy to estimate design loads for offshore jacket structures based on an environmental contour approach. In addition to the popular conditional distribution model, various classes of bivariate copulas are adopted to construct joint distributions of environmental variables. Analytical formulations of environmental contours based on various models are presented and discussed in this study. The design loads are examined by dynamic response analysis of jacket platform. Results suggest that the conditional model is not recommended for use in estimating design loads in sampling locations due to poor fitting results. Independent copula produces conservative design loads and the extreme response obtained using the conditional model are smaller than those determined by copulas. The suitability of a model for contour construction varies with the origin of wave data. This study provides a reference for the design load estimation of jacket structures and offers an alternative procedure to determine the design criteria for offshore structures.

关键词： design loads jacket platform joint probability distribution conditional model copula theory environmental contour method

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基于GBS简化基因组技术的蕲艾遗传多样性分析

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中国实验方剂学杂志 2024年第18期30卷 171-177页

作者：陈昌婕肖闯马钰洋苗玉焕刘大会湖北中医药大学药学院武汉430065 湖北时珍实验室武汉430065

目的:探究45份艾种质资源的遗传关系,揭示其遗传变异特点。方法:基于基因分型(GBS)的简化基因组技术对45份资源进行了单核苷酸多态性(SNP)位点挖掘,并利用SNP标记进行了主成分分析、系统发育分析、群体遗传结构分析和遗传变异分析。结果... 详细信息

目的:探究45份艾种质资源的遗传关系,揭示其遗传变异特点。方法:基于基因分型(GBS)的简化基因组技术对45份资源进行了单核苷酸多态性(SNP)位点挖掘,并利用SNP标记进行了主成分分析、系统发育分析、群体遗传结构分析和遗传变异分析。结果:共获得111.91 Gb数据,测序结果的Q20和Q30分别为96.39%和90.33%,平均GC含量为39.37%,clean reads与参考基因组的比对率为70.24%~98.97%,共获得22 399个Indel和170 539个SNP位点,其中第10对染色体上的变异位点最多;主成分分析、聚类分析和遗传多样性分析表明,45份资源可以被分为3个类群,类群Ⅰ包含的3份资源均来源于蕲春县,第Ⅱ类群资源均为野生种,类群Ⅲ包含31份种质,来源最为复杂;同时,这45份种质可分为3亚类,包含来源于3个祖先的遗传信息,说明不同种源的艾遗传组成比较复杂,尤其是来源于湖北省蕲春县的种质。结论:该研究可为蕲艾的新品种选育、特异性SNP标记的开发、艾的亲缘关系研究提供理论支撑。

关键词：蕲艾基因分型(GBS) 单核苷酸多态性(SNP)标记遗传多样性分析聚类分析

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高质量文本数据驱动的命名实体识别加速镍基单晶高温合金材料知识发现

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金属学报 2024年第10期60卷 1429-1438页

作者：刘悦姚文轩刘大晖丁琳杨正伟刘微于涛施思齐上海大学计算机工程与科学学院上海200444 上海大学材料基因组工程研究院上海200444 钢铁研究总院功能材料研究所北京100081 上海大学材料科学与工程学院上海200444

镍基单晶高温合金构效关系知识常常以非结构化文本的形式存储在海量公开发表的科学文献中。利用命名实体识别(NER)方法从非结构化文本中挖掘关键信息已成为助力新材料研发的重要方式。然而,已有NER方法依赖于大量语料数据支撑且不适用... 详细信息

镍基单晶高温合金构效关系知识常常以非结构化文本的形式存储在海量公开发表的科学文献中。利用命名实体识别(NER)方法从非结构化文本中挖掘关键信息已成为助力新材料研发的重要方式。然而,已有NER方法依赖于大量语料数据支撑且不适用于处理跨领域任务,导致其难以适配镍基单晶高温合金领域。本工作提出基于语义特征融合的深度学习命名实体识别方法(SF-NER),以准确挖掘摘要文本中蕴含的镍基单晶高温合金知识。在领域知识指导下创建材料领域词典以实现远程监督,并建立了高质量镍基单晶高温合金标注语料库(含8类实体类型的19405个实体数据);为准确捕捉特定材料术语,提出了融合编码的词表征策略以捕获关键材料语义特征;构建双向长短期记忆网络-条件随机场(Bi-LSTM-CRF)模型捕捉句子序列中的关键语义信息以实现实体标签的精准预测。实验结果表明,SF-NER能够精准识别镍基单晶高温合金实体类别(评价指标F1值为0.84),有效筛选影响高温合金服役性能的关键因素,并推荐出可用于服役性能构效关系挖掘的高重要度描述符。

关键词：数据质量深度学习命名实体识别镍基单晶高温合金领域知识

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艾与7个近缘种形态及挥发性成分的比较研究

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植物科学学报 2024年第4期42卷 509-518页

作者：陈昌婕苗玉焕马钰洋肖闯刘大会湖北中医药大学药学院武汉430065 湖北时珍实验室武汉430065

采用目视鉴定和气相色谱仪-质谱联用(GC-MS)技术,从形态和挥发性成分方面比较艾(Artemisia argyi Lé*** Van.)和其他7个近缘种,并利用主成分分析(PCA)与聚类分析进行系统评价。结果显示,艾的植株形态与近缘种有明显的差异,具有植株高... 详细信息

采用目视鉴定和气相色谱仪-质谱联用(GC-MS)技术,从形态和挥发性成分方面比较艾(Artemisia argyi Lé*** Van.)和其他7个近缘种,并利用主成分分析(PCA)与聚类分析进行系统评价。结果显示,艾的植株形态与近缘种有明显的差异,具有植株高大、香气明显、叶厚而柔韧、茎秆被短白毛且有明显纵棱纹等特点;从挥发性成分中鉴定出28种共有成分和28种特征成分,通过PCA进一步筛选出17个差异代谢物,利用聚类分析可将各物种彼此区分。本研究结果可为艾及其近缘种的鉴定提供参考。

关键词：艾蒿属形态特征挥发性成分物种鉴定

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整合代谢组学和网络药理学探究蕲艾的安全性与毒理学机制

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中草药 2024年第10期55卷 3331-3344页

作者：陈乐汪喻巧朱芸芸徐文丽杜鸿志刘大会湖北中医药大学中药资源中心湖北武汉430065 湖北中医药大学湖北时珍实验室湖北武汉430065 南京中医药大学江苏省中药资源产业化过程协同创新中心中药资源产业化与方剂创新药物国家地方联合工程研究中心国家中医药管理局中药资源循环利用重点研究室江苏南京210023

目的基于代谢组学和网络药理学分析相结合的方法探究蕲艾Artemisia argyi的安全性与毒理学机制。方法采用气相色谱-质谱(gas chromatography-mass spectrometry,GC-MS)和超高效液相色谱串联四极杆飞行时间质谱(ultra performance liquid... 详细信息

目的基于代谢组学和网络药理学分析相结合的方法探究蕲艾Artemisia argyi的安全性与毒理学机制。方法采用气相色谱-质谱(gas chromatography-mass spectrometry,GC-MS)和超高效液相色谱串联四极杆飞行时间质谱(ultra performance liquid chromatography coupled to tandem quadrupole time-of-flight mass spectrometry,UPLC-Q-TOF-MS)技术分析蕲艾挥发油组分(essential oil from ***,AAEO)、石油醚组分、醋酸乙酯组分、正丁醇组分和水组分的化学组成;利用KM小鼠连续7 d给药评价AAEO和4个非挥发性组分的安全性;代谢组学技术检测AAEO干预前后肝脏内源性代谢物的变化;网络药理学分析AAEO肝毒性的潜在成分和作用靶点;整合代谢组学和网络药理学并构建“代谢物-反应-酶-基因”相互作用网络揭示AAEO肝毒性的毒理学机制。结果共鉴定出AAEO中39个成分,占挥发油含量的89.30%;从4个非挥发性组分中共鉴定出34个成分。与对照组比较,AAEO显著增加小鼠肝脏指数(P<0.05、0.01),上调肝脏丙氨酸氨基转移酶(alanine aminotransferase,ALT)和天冬氨酸氨基转移酶(aspartate aminotransferase,AST)的活性(P<0.01),并损伤肝脏组织病理结构呈现出明显肝毒性。代谢组学结果显示给予AAEO后肝脏的17个代谢物水平发生显著变化,包含9种氨基酸,主要涉及苯丙氨酸、酪氨酸和色氨酸生物合成,丙氨酸、天冬氨酸和谷氨酸代谢等途径;网络药理学分析提示樟脑、侧柏酮、石竹素、(−)-宁酮等10个成分是AAEO中潜在的肝毒性物质;整合代谢组学和网络药理学分析筛选出苯丙氨酸羟化酶(phenylalanine hydroxylase,PAH)为AAEO肝毒性的关键靶点,且PAH mRNA和蛋白表达在AAEO高、低剂量组均显著降低(P<0.05、0.01),揭示AAEO通过下调PAH表达抑制酪氨酸生物合成产生肝毒性。分子对接结果显示10个潜在毒性物质与PAH结合能均小于−20.00 kJ/mol。结论结合代谢组学和网络药理学阐明了蕲艾的毒性组分、可能的毒性物质及毒理学机制,为蕲艾产业的发展和临床应用提供了依据。

关键词：蕲艾安全性代谢组学网络药理学苯丙氨酸羟化酶挥发油樟脑侧柏酮石竹素 (−)-宁酮

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Data quantity governance for machine learning in materials science

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National Science Review 2023年第7期10卷 234-250页

作者： Yue liu Zhengwei Yang Xinxin Zou Shuchang Ma dahui liu Maxim Avdeev Siqi Shi School of Computer Engineering and Science Shanghai University Shanghai Engineering Research Center of Intelligent Computing System Australian Nuclear Science and Technology Organisation School of Chemistry The University of Sydney State Key Laboratory of Advanced Special Steel School of Materials Science and Engineering Shanghai University Materials Genome Institute Shanghai University

Data-driven machine learning(ML) is widely employed in the analysis of materials structure-activity relationships,performance optimization and materials design due to its superior ability to reveal latent data patterns and make accurate ***,because of the laborious process of materials data acquisition,ML models encounter the issue of the mismatch between a high dimension of feature space and a small sample size(for traditional ML models) or the mismatch between model parameters and sample size(for deep-learning models),usually resulting in terrible ***,we review the efforts for tackling this issue via feature reduction,sample augmentation and specific ML approaches,and show that the balance between the number of samples and features or model parameters should attract great attention during data quantity *** this,we propose a synergistic data quantity governance flow with the incorporation of materials domain *** summarizing the approaches to incorporating materials domain knowledge into the process of ML,we provide examples of incorporating domain knowledge into governance schemes to demonstrate the advantages of the approach and *** work paves the way for obtaining the required high-quality data to accelerate materials design and discovery based on ML.

关键词： machine learning data governance data quantity materials science

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Domain knowledge discovery from abstracts of scientific literature on Nickel-based single crystal superalloys

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Science China(Technological Sciences) 2023年第6期66卷 1815-1830页

作者： liu Yue DING Lin YANG ZhengWei GE XianYuan liu dahui liu Wei YU Tao AVDEEV Maxim SHI SiQi School of Computer Engineering and Science Shanghai UniversityShanghai 200444China Shanghai Engineering Research Center of Intelligent Computing System Shanghai 200444China State Key Laboratory of Advanced Special Steel&Shanghai Key Laboratory of Advanced Ferrometallurgy&School of Materials Science and Engineering Shanghai UniversityShanghai 200444China Materials Genome Institute Shanghai UniversityShanghai 200444China Institute of Functional Materials Central Iron&Steel Research InstituteBeijing 100081China Australian Nuclear Science and Technology Organisation Locked Bag 2001Kirrawee DC NSW 2232Australia School of Chemistry The University of SydneySydney 2006Australia Zhejiang Laboratory Hangzhou 311100China

Despite the huge accumulation of scientific literature,it is inefficient and laborious to manually search it for useful information to investigate structure-activity ***,we propose an efficient text-mining framework for the discovery of credible and valuable domain knowledge from abstracts of scientific literature focusing on Nickel-based single crystal ***,the credibility of abstracts is quantified in terms of source timeliness,publication authority and author’s academic ***,eight entity types and domain dictionaries describing Nickel-based single crystal superalloys are predefined to realize the named entity recognition from the abstracts,achieving an accuracy of 85.10%.Thirdly,by formulating 12 naming rules for the alloy brands derived from the recognized entities,we extract the target entities and refine them as domain knowledge through the credibility *** this,we also map out the academic cooperative“Author-Literature-Institute”network,characterize the generations of Nickel-based single crystal superalloys,as well as obtain the fractions of the most important chemical elements in *** extracted rich and diverse knowledge of Nickel-based single crystal superalloys provides important insights toward understanding the structure-activity relationships for Nickel-based single crystal superalloys and is expected to accelerate the design and discovery of novel superalloys.

关键词： Nickel-based single crystal superalloys text mining named entity recognition credibility analysis domain knowledge

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Generative artificial intelligence and its applications in materials science:Current situation and future perspectives

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Journal of Materiomics 2023年第4期9卷 798-816页

作者： Yue liu Zhengwei Yang Zhenyao Yu Zitu liu dahui liu Hailong Lin Mingqing Li Shuchang Ma Maxim Avdeev Siqi Shi School of Computer Engineering and Science Shanghai UniversityShanghai200444China State Key Laboratory of Advanced Special Steel School of Materials Science and EngineeringShanghai UniversityShanghai200444China Materials Genome Institute Shanghai UniversityShanghai200444China Shanghai Engineering Research Center of Intelligent Computing System Shanghai200444China Australian Nuclear Science and Technology Organisation Sydney2232Australia School of Chemistry The University of SydneySydney2006Australia

Generative Artificial Intelligence(GAI)is attracting the increasing attention of materials community for its excellent capability of generating required *** the introduction of Prompt paradigm and reinforcement learning from human feedback(RLHF),GAI shifts from the task-specific to general pattern gradually,enabling to tackle multiple complicated tasks involved in resolving the structure-activity ***,we review the development status of GAI comprehensively and analyze pros and cons of various generative models in the view of *** applications of task-specific generative models involving materials inverse design and data augmentation are also *** ChatGPT as an example,we explore the potential applications of general GAI in generating multiple materials content,solving differential equation as well as querying materials ***,we summarize six challenges encountered for the use of GAI in materials science and provide the corresponding *** work paves the way for providing effective and explainable materials data generation and analysis approaches to accelerate the materials research and development.

关键词： Machine learning Artificial intelligence Generative artificial intelligence Materials science Novel materials discovery Deep learning

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