表达Strep-tag II的重组塞内卡病毒的构建与鉴定

为构建表达Strep-tag II的重组塞内卡病毒(SVA),本研究在感染性cDNA克隆p SVA-I212V/S460L的基础上,采用重叠延伸PCR扩增Strep-tag II并采用无缝克隆法将其插入SVA VP1基因C端,构建感染性cDNA克隆,命名为p SVA-Strep,并采用双酶切和测序鉴定正确后,将p SVA-Strep转染BHK-21细胞拯救重组病毒,收集病变细胞上清,并将含有病毒的细胞上清和野生型SVA(SVA-WT)分别感染BHK-21细胞,以未感染病毒的BHK-21细胞作为阴性对照,感染后24 h分别以鼠源SVA VP2蛋白单克隆抗体(MAb)5D10(1∶1000)、鼠源Strep-tag II MAb(1∶2000)作为一抗,以FITC标记的山羊抗小鼠Ig G(1∶2000)为二抗,采用间接免疫荧光试验(IFA)对重组病毒鉴定。IFA结果显示,以鼠源SVA VP2蛋白MAb 5D10为一抗,SVA-WT和重组病毒感染的细胞均出现绿色荧光,以Strep-tag II MAb作为一抗时,仅有重组病毒感染的细胞出现绿色荧光,经SVA-WT感染的BHK-21细胞及阴性对照细胞均无绿色荧光,表明拯救了Strep-tag II标记的重组病毒,并将其命名为r SVA-Strep。将r SVA-Strep在BHK-21细胞中连续传10代,每隔2代采用引物VP1-F/R经PCR鉴定并对第10代重组病毒的VP1基因测序以鉴定r SVA-Strep的遗传稳定性。结果显示,每隔两代的重组病毒经PCR扩增后均出现约780 bp的目的条带,第10代重组病毒扩增的VP1基因测序结果显示Strep-tag II基因仍在重组病毒中,且无基因突变,表明r SVA-Strep的遗传稳定性较强;将SVA-WT和r SVA-Strep分别以MOI 0.01感染BHK-21细胞,在感染后4 h、8 h、12 h、24 h、36 h、48 h和72 h收获病毒测定病毒滴度并绘制生长曲线,结果显示在病毒感染36 h内r SVA-Strep和SVA-WT生长动力学基本一致,表明Strep-tag II的引入在病毒感染36 h内对SVA的复制基本无影响。采用0.2%甲醛充分灭活r SVA-Strep,并利用Strep-TactinRXT Purification纯化试剂盒纯化该灭活病毒,将r SVA-Strep灭活病毒上清加至Strep-Tactin亲和层析柱,分别用不同体积洗脱缓冲液依次洗脱病毒并通过western blot鉴定病毒的纯化效果。对纯化过程中不同洗脱液洗脱病毒的western blot结果显示,不同体积的洗脱液中E1、E2和E3均出现VP0和VP2两条带,且E1和E2的条带最明显,表明洗脱缓冲液的最佳洗脱体积约为2.2 CV;以上结果表明r SVA-Strep可通过Strep-Tactin亲和层析柱一步法纯化。本研究在SVA中插入Strep-tag II标签,为SVA灭活疫苗的快速纯化提供技术手段,也为其他病原的快速纯化方法的建立提供参考。

Joint Modeling of Citation Networks and User Preferences for Academic Tagging Recommender System

In the tag recommendation task on academic platforms,existing methods disregard users’customized preferences in favor of extracting tags based just on the content of the articles.Besides,it uses co-occurrence techniques and tries to combine nodes’textual content for modelling.They still do not,however,directly simulate many interactions in network learning.In order to address these issues,we present a novel system that more thoroughly integrates user preferences and citation networks into article labelling recommendations.Specifically,we first employ path similarity to quantify the degree of similarity between user labelling preferences and articles in the citation network.Then,the Commuting Matrix for massive node pair paths is used to improve computational performance.Finally,the two commonalities mentioned above are combined with the interaction paper labels based on the additivity of Poisson distribution.In addition,we also consider solving the model’s parameters by applying variational inference.Experimental results demonstrate that our suggested framework agrees and significantly outperforms the state-of-the-art baseline on two real datasets by efficiently merging the three relational data.Based on the Area Under Curve(AUC)and Mean Average Precision(MAP)analysis,the performance of the suggested task is evaluated,and it is demonstrated to have a greater solving efficiency than current techniques.

A U-Shaped Network-Based Grid Tagging Model for Chinese Named Entity Recognition

Chinese named entity recognition(CNER)has received widespread attention as an important task of Chinese information extraction.Most previous research has focused on individually studying flat CNER,overlapped CNER,or discontinuous CNER.However,a unified CNER is often needed in real-world scenarios.Recent studies have shown that grid tagging-based methods based on character-pair relationship classification hold great potential for achieving unified NER.Nevertheless,how to enrich Chinese character-pair grid representations and capture deeper dependencies between character pairs to improve entity recognition performance remains an unresolved challenge.In this study,we enhance the character-pair grid representation by incorporating both local and global information.Significantly,we introduce a new approach by considering the character-pair grid representation matrix as a specialized image,converting the classification of character-pair relationships into a pixel-level semantic segmentation task.We devise a U-shaped network to extract multi-scale and deeper semantic information from the grid image,allowing for a more comprehensive understanding of associative features between character pairs.This approach leads to improved accuracy in predicting their relationships,ultimately enhancing entity recognition performance.We conducted experiments on two public CNER datasets in the biomedical domain,namely CMeEE-V2 and Diakg.The results demonstrate the effectiveness of our approach,which achieves F1-score improvements of 7.29 percentage points and 1.64 percentage points compared to the current state-of-the-art(SOTA)models,respectively.

Serum proteins differentially expressed in gestational diabetes mellitus assessed using isobaric tag for relative and absolute quantitation proteomics

BACKGROUND As a well-known fact to the public,gestational diabetes mellitus(GDM)could bring serious risks for both pregnant women and infants.During this important investigation into the linkage between GDM patients and their altered expression in the serum,proteomics techniques were deployed to detect the differentially expressed proteins(DEPs)of in the serum of GDM patients to further explore its pathogenesis,and find out possible biomarkers to forecast GDM occurrence.METHODS Subjects were divided into GDM and normal control groups according to the IADPSG diagnostic criteria.Serum samples were randomly selected from four cases in each group at 24-28 wk of gestation,and the blood samples were identified by applying iTRAQ technology combined with liquid chromatography-tandem mass spectrometry.Key proteins and signaling pathways associated with GDM were identified by bioinformatics analysis,and the expression of key proteins in serum from 12 wk to 16 wk of gestation was further verified using enzyme-linked immunosorbent assay (ELISA).RESULTS Forty-seven proteins were significantly differentially expressed by analyzing the serum samples between the GDMgravidas as well as the healthy ones. Among them, 31 proteins were found to be upregulated notably and the rest16 proteins were downregulated remarkably. Bioinformatic data report revealed abnormal expression of proteinsassociated with lipid metabolism, coagulation cascade activation, complement system and inflammatory responsein the GDM group. ELISA results showed that the contents of RBP4, as well as ANGPTL8, increased in the serumof GDM gravidas compared with the healthy ones, and this change was found to initiate from 12 wk to 16 wk ofgestation.CONCLUSION GDM symptoms may involve abnormalities in lipid metabolism, coagulation cascade activation, complementsystem and inflammatory response. RBP4 and ANGPTL8 are expected to be early predictors of GDM.

Differential Expression Analysis of Proteins Regulated by Rare Earth Cerium in Soybean Leaves at Seedling Stage

This study was to explore the functional mechanism of rare earth regulating soybean leaves and the characteristics and functions of differentially expressed proteins under the regulation of rare earth. In this study, Dongnong 42 was used as material, and 30 mg·L^(-1) CeCl_(3) solution was sprayed on soybean leaves at the seedling stage. Tandem mass tag(TMT) quantitative proteomics technique and bioinformatics analysis were used to identify soybean leaf proteins. A total of 8 510 proteins were identified, and 127 differentially expressed proteins(DEPs) in response to rare earth cerium regulation were identified, among which 64 were upregulated and 63 were down-regulated. The gene ontology(GO) annotation indicated that DEPs were mainly involved in metabolic process, cellular process, response to stimulus, biological regulation, and response to a stimulus;DEPs in cell module categories were mainly involved in cells, cell part, organelle, membrane, membrane part, organelle par, and protein-containing complex;DEPs in molecular functional categories were mainly involved in catalytic activity, binding and antioxidant activity. Kyoto encyclopedia of genes and genomes(KEGG) pathway significantly enriched starch and sucrose metabolism, glycolysis/gluconeogenesis, galactose metabolism, pentose phosphate pathway, and MAPK signaling pathway-plant. These DEPs were mainly involved in photosynthesis, glucose metabolism and stress response. Forty-six differential protein interaction networks were identified by protein interaction network analysis. This experiment provided a reference for studies of the mechanism of rare earth cerium regulating soybean leaf function from the proteomic perspective.

34.TAG·西海美术馆:面朝大海的艺术长廊

设计:让·努维尔事务所地点:山东青岛西海岸新区时间:2012—2021年规模:17000 m^(2)TAG·西海美术馆位于一座半岛的海边,远离市区^([1,2])。从规划意图看,整个项目由美术馆和艺术工坊两部分组成,但由于工坊部分处于停工状态,艺术社区氛围尚未形成,作为主体建筑的美术馆便成了荒野中的孤独存在,公众可达性较差(图1)。尽管如此,从设计研究角度,这座美术馆仍有许多精彩看点值得关注。

TAG HEUER 竞速激情

继去年以卡莱拉系列Skipper计时码表的精钢版本标志着品牌重返帆船运动与航海领域之后,TAG Heuer泰格豪雅如今欣然发布一款以18K 5N玫瑰金打造的全新版本。金质的Skipper计时码表与精钢版本类似,同样基于2023年前期为纪念卡莱拉系列计时码表60周年推出且热销的“玻璃盒”(glassbox)设计,并搭载品牌自制机心Heuer 02(型号:TH20-06),这是一款为帆船赛计时而特别调整的Heuer 02机心。

铜麦6号苗期耐高铵与耐盐特性的鉴定及TaGS基因的表达模式分析

为鉴定小麦品种铜麦6号的耐高铵及耐盐特性,对铜麦6号、中国春及抗逆性较强的烟农19、三抗10号、矮优王、烟农21、山农25的发芽势和发芽率进行测定,发现铜麦6号的耐铵指数位列第一,耐盐指数位列第二。以中国春为对照品种,在高铵、高盐及其双重胁迫处理下,测定其苗期的叶片鲜重、根鲜重、主根和第一叶叶片长度以及根冠比,发现高铵、高盐及其双重胁迫处理7 d后,铜麦6号的上述指标均不同程度高于中国春(除铜麦6号的根冠比在高盐处理1 d后低于中国春外),说明铜麦6号具有较强的耐高铵和耐高盐特性。进一步采用qRT-PCR检测小麦苗期谷氨酰胺合成酶TaGS基因家族成员(根中TaGS1;1、TaGS1;2和TaGS1;3基因以及叶片中TaGS2基因)的表达模式,发现高铵、高盐及其双重处理均可诱导铜麦6号苗期TaGS基因上调表达,且高盐处理下上调表达更明显,其中除高铵与高盐双重处理7 d后的TaGS1;2基因以及高铵和高盐处理1 d后的TaGS2基因在铜麦6号中的表达量低于中国春外,其他三种处理不同时间点铜麦6号中这两个基因的相对表达量均不同程度高于中国春。这些结果说明,铜麦6号苗期TaGS基因家族与其耐高铵和耐高盐特性相关,其中TaGS1;2和TaGS2基因的贡献较大。

Tandem Mass Tag-based proteomics analysis reveals the vital role of inflammation in traumatic brain injury in a mouse model

Proteomics is a powerful tool that can be used to elucidate the underlying mechanisms of diseases and identify new biomarkers.Therefore,it may also be helpful for understanding the detailed pathological mechanism of traumatic brain injury(TBI).In this study,we performed Tandem Mass Tag-based quantitative analysis of cortical proteome profiles in a mouse model of TBI.Our results showed that there were 302 differentially expressed proteins in TBI mice compared with normal mice 7 days after injury.Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses showed that these differentially expressed proteins were predominantly involved in inflammatory responses,including complement and coagulation cascades,as well as chemokine signaling pathways.Subsequent transcription factor analysis revealed that the inflammation-related transcription factors NF-κB1,RelA,IRF1,STAT1,and Spi1 play pivotal roles in the secondary injury that occurs after TBI,which further corroborates the functional enrichment for inflammatory factors.Our results suggest that inflammation-related proteins and inflammatory responses are promising targets for the treatment of TBI.

Efficient and robust missing key tag identification for large-scale RFID systems

Radio Frequency Identification(RFID)technology has been widely used to identify missing items.In many applications,rapidly pinpointing key tags that are attached to favorable or valuable items is critical.To realize this goal,interference from ordinary tags should be avoided,while key tags should be efficiently verified.Despite many previous studies,how to rapidly and dynamically filter out ordinary tags when the ratio of ordinary tags changes has not been addressed.Moreover,how to efficiently verify missing key tags in groups rather than one by one has not been explored,especially with varying missing rates.In this paper,we propose an Efficient and Robust missing Key tag Identification(ERKI)protocol that consists of a filtering mechanism and a verification mechanism.Specifically,the filtering mechanism adopts the Bloom filter to quickly filter out ordinary tags and uses the labeling vector to optimize the Bloom filter's performance when the key tag ratio is high.Furthermore,the verification mechanism can dynamically verify key tags according to the missing rates,in which an appropriate number of key tags is mapped to a slot and verified at once.Moreover,we theoretically analyze the parameters of the ERKI protocol to minimize its execution time.Extensive numerical results show that ERKI can accelerate the execution time by more than 2.14compared with state-of-the-art solutions.

Encrypted optical fiber tag based on encoded fiber Bragg grating array

Optical fibers are typically used in telecommunications services for data transmission,where the use of fiber tags is essential to distinguish between the different transmission fibers or channels and thus ensure the working functionality of the communication system.Traditional physical entity marking methods for fiber labeling are bulky,easily confused,and,most importantly,the label information can be accessed easily by all potential users.This work proposes an encrypted optical fiber tag based on an encoded fiber Bragg grating(FBG)array that is fabricated using a point-by-point femtosecond laser pulse chain inscription method.Gratings with different resonant wavelengths and reflectivities are realized by adjusting the grating period and the refractive index modulations.It is demonstrated that a binary data sequence carried by a fiber tag can be inscribed into the fiber core in the form of an FBG array,and the tag data can be encrypted through appropriate design of the spatial distributions of the FBGs with various reflection wavelengths and reflectivities.The proposed fiber tag technology can be used for applications in port identification,encrypted data storage,and transmission in fiber networks.

Mobilizing the seed storage oil in milk thistle (Silybum marianum) can supply energy for seed germination and early seedling growth and apply as TAGs breakdown marker

Milk thistle(Silybum marianum)is a crucial medicinal plant containing a large amount of oil.In the study,the changes in storage oil during seed germination and seedling transition from heterotrophic phases were investigated.The results showed that seed oil decreased from 19.53%to 0.88%on the 7th day of seedling development.Oil hydrolysis continued until the 4th day of germination with a low slope,but then increased the use of oils in seed germination end seedling growth metabolism.The results indicated that the quantitative changes in fatty acids,presented at lower amount,were relatively higher than dominant fatty acids.There were decreasing phenolic content in the developing seedlings,but overall,lowest level of total phenolic content can be attributed to the control(30.52 mg⋅100 g⋅Oil^(-1)).In contrast,the maximum peroxide value(2.58 meq⋅kg Oil^(-1))in the developing seedling was observed on the last day of the experiment.The results showed that there was a significant correlation between saturated fatty acid,unsaturated fatty acid,and lipase activity.However,the correlation between lipase activity and polyunsaturated fatty acids was significantly higher than between lipase activity and monounsaturated fatty acids(R^(2)=90%and R^(2)=77%,respectively).Therefore,the lipolysis process acts selectively in milk thistle oils.According to the results,C12:0 exhibits a greater impact on the early seedling growth rather than on the germination process and is one of the determining factors in the transition from heterotroph to autotroph.Also,it can be a marker for TAGs breakdown.

MSCNN-LSTM Model for Predicting Return Loss of the UHF Antenna in HF-UHF RFID Tag Antenna

High-frequency(HF)and ultrahigh-frequency(UHF)dual-band radio frequency identification(RFID)tags with both near-field and farfield communication can meet different application scenarios.However,it is time-consuming to calculate the return loss of a UHF antenna in a dualband tag antenna using electromagnetic(EM)simulators.To overcome this,the present work proposes a model of a multi-scale convolutional neural network stacked with long and short-term memory(MSCNN-LSTM)for predicting the return loss of UHF antennas instead of EM simulators.In the proposed MSCNN-LSTM,the MSCNN has three branches,which include three convolution layers with different kernel sizes and numbers.Therefore,MSCNN can extract fine-grain localized information of the antenna and overall features.The LSTM can effectively learn the EM characteristics of different structures of the antenna to improve the prediction accuracy of the model.Experimental results show that the mean absolute error(0.0073),mean square error(0.00032),and root mean square error(0.01814)of theMSCNNLSTM are better than those of other prediction methods.In predicting the return loss of 100UHFantennas,compared with the simulation time of 4800 s for High Frequency Structure Simulator(HFSS),MSCNN-LSTM takes only 0.927519 s under the premise of ensuring prediction accuracy,significantly reducing the calculation time,which provides a basis for the rapid design of HF-UHF RFID tag antenna.ThenMSCNN-LSTM is used to determine the dimensions of the UHF antenna quickly.The return loss of the designed dualband RFID tag antenna is−58.76 and−22.63 dB at 13.56 and 915 MHz,respectively,achieving the desired goal.

TAG HEUER 赛车场上的王者选择

⼤约100年前,由于技术的发展,计时的精准度得到了⼤幅提升,计时码表成为了这⼀时代最热⻔的流⾏趋势,TAG HEUER泰格豪雅作为专业计时码表的历史,也可以追溯到那个时代。伴随着泰格豪雅的计时码表品质提升,它成为了众多航空⻜⾏器和汽⻋仪表盘的专业计时配件供应商,同时也成为了众多体育赛事的专业计时。

一种针对Cache Tag单错及邻位双错的低开销容错方法

Cache是处理器重要的存储模块,对处理器性能提升有着至关重要的作用.空间环境中,保护Cache免受软错误影响已成为设计新一代高可靠微处理器日益严峻的挑战.设计一种针对Cache Tag单错及邻位双错的低开销容错方法.可以保证Cache访问、Cache行填充和Cache行回写不受单位错误和邻位双错的影响,与传统SEC-FastTag容错方法相比,Tag单位及邻位双错容错能力得到提高.通过扩展FastTag结构优化设计,降低SEC-DAEC编解码逻辑带来的面积、功耗以及性能方面的开销.以四路组相连写回Cache为目标系统,与传统SEC-DAEC容错方法相比,本文提出的方法面积开销降低8.47%,功耗开销降低37.7%,关键路径时延减小0.13 ns.

VLAN中Tagged与Untagged探讨

简要阐述了VLAN技术在网络中的重要性,在网络配置过程中对于tagged与untagged两个参数的选择存在的疑问;深入讲解tag的定义,同时结合实例,全面分析了VLAN的端口在untagged与tagged两种状态下,数据帧在通信过程中是否出现tag header的标识;总结出规律,有助于在VLAN中如何准确地使用tagged与untagged.

漆酶N端融合His-tag或S-tag标签促进其在大肠杆菌中可溶性表达

来源于地衣芽孢杆菌的漆酶具有催效率高,底物范围广等优点在工农业等领域具有重要的应用前景,但该酶在外源基因表达系统中的表达量低,影响了其在工农业等领域的应用。His-tag和S-tag两种标签由于具有分子量小,且一般不影响外源蛋白性质等特点,在外源蛋白的纯化和检测中具有重要的应用。本研究发现将来源于地衣芽孢杆菌的漆酶Cot A的N端融合Histag或S-tag构建于p ET-22b载体,并转化大肠杆菌BL21(DE3)后可以显著提高其在大肠杆菌中的可溶性表达量,其表达量较N端无融合标签的构建,His-tag可提高漆酶表达量约为37倍,S-tag约可提高20倍,His-tag与S-tag共作用约可提高28倍。

大西洋中脊TAG热液活动区海底热液沉积物的硫同位素组成及其地质意义

对 1 98 8年取自大西洋中脊TAG热液活动区的海底表层热液沉积物中 36件硫化物样品进行了硫同位素组成分析。结合ODPLeg1 58的近期成果 ,对TAG区热液沉积物的硫同位素组成及其时空演变、硫源、硫同位素偏重的原因和硫的演化进行了探讨 ,得出如下结论 :( 1 )TAG区表层热液沉积物的δ34S值从 3 9‰— 7 6‰变化 ,均值为 5 98‰ ,与其它洋中脊热液活动区相比明显偏重。 ( 2 )从海底表层区到蚀变玄武岩区 ,热液沉积物的硫同位素组成有增大的趋势 ,而时间对热液沉积物的硫同位素组成则没有明显的控制。 ( 3)热液沉积物中硫主要来自玄武岩 ,部分来自海水硫酸盐 ,是海水硫酸盐和玄武岩中硫不同程度混合的结果 ,且各硫源在不同阶段提供硫的比例分配和方式明显不同。 ( 4 )与其它无沉积物覆盖洋中脊中热液活动区相比 ,相对较大比例海水来源硫的加入是导致TAG区硫同位素组成偏重的一个重要原因 ,而TAG区具备有利海水硫酸盐还原作用进行的温度和水 /岩比值条件则是促使该区热液沉积物中海水来源硫相对较多的主要原因。 ( 5)海水的直接混入、流体 -玄武岩相互作用、先期形成硫化物的重溶作用和硫酸盐矿物的还原作用是海水和玄武岩直接或间接提供硫的主要方式 ,也是导致本区硫同位素演化复杂化的主要原因 ,且硫的演化?

6×His-tag在抗菌肽表达纯化中的应用及其对抗菌肽活性的影响

为方便抗菌肽的体外表达和纯化,以蝎子防御素为对象,在其编码基因末端加入6×His-tag,在酵母表达系统中表达,获得有活性的防御素Sd和融合蛋白Sd-His。进一步纯化、体外抑菌活性及热酸稳定性等试验发现,6×His-tag不但没有降低防御素的抑菌活性,反而有稍微的增强趋势。结果表明,6×His-tag可用于抗菌肽的融合表达且不影响其活性,为抗菌肽的表达纯化提供了一个更简便有效的方法。

Tag和现代教育技术

Tag是新一代互联网模式Web2.0的核心应用之一,它实现了分众分类的思想,具有自发性、共享性和动态自适应性的特点。Tag的推广和应用将会增强人们的概括意识,引发评价标准和分类原则的多元化,促进人们的远程交流,有利于社会网络的形成,因此,Tag将在一定程度上影响人们的思维方式和生活方式。本文在分析Tag对网络文化的影响的基础上,指出了Tag在教育技术中诸多方面应用的可行性和优越性。