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Citation network analysis attracts increasing attention from disciplines of complex network analysis and science of science. One big challenge in this regard is that there are unreasonable citations in citation networks, i.e., cited papers are not relevant to the citing paper. Existing research on citation analysis has primarily concentrated on the contents and ignored the complex relations between academic entities. In this paper, we propose a novel research topic, that is, how to detect anomalous citations. To be specific, we first define anomalous citations and propose a unified framework, named ACTION, to detect anomalous citations in a heterogeneous academic network. ACTION is established based on non-negative matrix factorization and network representation learning, which considers not only the relevance of citation contents but also the relationships among academic entities including journals, papers, and authors. To evaluate the performance of ACTION, we construct two anomalous citation datasets. Experimental results demonstrate the effectiveness of the proposed method. Detecting anomalous citations carry profound significance for academic fairness.

Ovarian cancer is one of the most common gynecological diseases with high mortality rates. Previous studies have shown that microRNA (miR)-638 is associated with tumorigenesis. The present study aimed to assess the role and underlying mechanisms of miR-638 in ovarian cancer. miR-638 expression was detected in ovarian cancer tissues and miR-638 was overexpressed or knocked down in ovarian cancer OVCAR-3 and Caov-3 cells. The clinical results revealed that miR-638 expression was downregulated in ovarian cancer tissues compared with in adjacent normal tissues. miR-638 expression was also found to be relatively low in OVCAR-3 cells whilst being relatively high in Caov-3 cells among the five ovarian cancer cell lines tested. miR-638 overexpression inhibited cell viability, arrested the cell cycle at the G1 phase and promoted apoptosis in OVCAR-3 cells. By contrast, miR-638 knockdown increased Caov-3 cell viability, facilitated cell cycle progression and inhibited apoptosis. miR-638 reduced the expression of high mobility group A1 (HMGA1) by directly targeting its 3' untranslated region. HMGA1 overexpression reversed the inhibition of proliferation induced by miR-638 overexpression in OVCAR-3 cells. These results suggest that miR-638 may serve to be a suppressor of ovarian cancer by regulating HMGA1, which may provide a potential therapeutic target for ovarian cancer.

This paper investigates the impact of institutes and papers over time based on the heterogeneous institution-citation network. A new model, IPRank, is introduced to measure the impact of institution and paper simultaneously. This model utilises the heterogeneous structural measure method to unveil the impact of institution and paper, reflecting the effects of citation, institution, and structural measure. To evaluate the performance, the model first constructs a heterogeneous institution-citation network based on the American Physical Society (APS) dataset. Subsequently, PageRank is used to quantify the impact of institution and paper. Finally, impacts of same institution are merged, and the ranking of institutions and papers is calculated. Experimental results show that the IPRank model better identifies universities that host Nobel Prize laureates, demonstrating that the proposed technique well reflects impactful research. Refereed/Peer-reviewed

The peri-urban rivers are one of the critical interfaces between urban-rural symbiotic ecosystems and appear to be a reservoir of antibiotic resistance genes (ARGs) in the environment. To prevent the transmission risks of ARGs between peri-urban river and human, it is essential to explore the prevalence and source of ARGs in the environment for designing potential mitigation strategies. In this study, we focused on the characterization and source-tracking of ARGs in the sediments of a typical peri-urban river in Beijing, Chaobai River. Twenty-seven ARGs frequently reported in the environment, and two integrons (intI1 and intI2) were detected using high-throughput quantitative PCR. The profile of bacterial community was determined by performing 16S rRNA gene sequencing. Meanwhile, crAssphage, a novel recently-discovered DNA bacteriophage, was employed for tracking the contribution of human fecal pollution to the prevalence of ARGs. Results showed that the targeted ARGs were detected widely in the sediments of Chaobai River. Relatively, the abundances of ARGs in downstream were higher than those in the upstream, likely suggesting a gradient impact of anthropogenic activities along the river. Remarkably, the int1 gene was correlated significantly with most of the ARGs and might be the key factor influencing the shaping of ARGs in the river sediments. However, no significant correlations were observed between the ARGs and selective pressure factors, including antibiotics and metals. Of the identified 1039 genera, Escherichia-Shigella, Bacteroides, Arcobacter, Dechloromonas and Pseudomonas were the top most abundant organisms. Microbial source tracking based on the crAssphage annotation suggested that human sewage might be one of the potential sources of resistance bacteria in the river sediments. The study can advance our knowledge about ARGs in the peri-urban river and provides a management reference for ARG pollution control.

The over-use of antibiotics causes growing concerns about human health risks induced by increasing rates of antimicrobial resistance. Riverine systems are considered generally as a natural reservoir of antibiotic resistance genes (ARGs). In this study, several methods including high-throughput sequencing-based metagenomics approach, statistical analysis and network analysis were applied jointly to characterize the wide-spectrum profile of ARGs in the sediments of an urban river in Beijing. Furthermore, contribution of human activities for the presence of ARGs was identified through comparative studies on the metagenomic profiling of ARGs between the river sediments and pristine niches (remote Antarctic soils and deep sea sediments). In total, 442 ARG subtypes belonging to 22 ARG types were detected in the human-impacted river sediments with an abundance range of 1.1 × 10−1–8.1 × 10−1 copy of ARG per copy of 16S-rRNA gene. The most abundant and diverse ARGs were commonly associated with antibiotics that have been extensively used in that area, likely indicating the spread of ARGs in river environments because of the selective pressure resulting from antibiotic use. As a whole, anthropogenic activities were the dominant contributor of major ARG types, for example, occupying 100% for sulfonamide-ARGs, 97% for beta-lactam-ARGs, 94% for aminoglycoside-ARGs and 64% for tetracycline-ARGs. This study provides insights into the role of human activities in accelerating the dissemination and proliferation of ARGs in urban river environment and draws attention to controlling the use and discharge of antibiotics for protection of public health.

Despite the growing interest in exploring the collaboration patterns and the structure of collaboration networks, the impact of collaboration associated with time-varying scholarly networks is hardly known. This paper investigates collaboration and productivity in a science career and quantifies the impact of collaboration in the collaboration-citation network. Moreover, this paper also investigates collaboration patterns and examines the typical duration of research collaborations. A SCIRank model is proposed to quantify the impact of scientific collaboration, which not only reveals the impact of co-author pairs but also identifies scholarly papers with the outstanding impact that leads to Nobel Prize awards. Refereed/Peer-reviewed

Globally, the recommendation services have become important due to the fact that they support e-commerce applications and different research communities. Recommender systems have a large number of applications in many fields, including economic, education, and scientific research. Different empirical studies have shown that the recommender systems are more effective and reliable than the keyword-based search engines for extracting useful knowledge from massive amounts of data. The problem of recommending similar scientific articles in scientific community is called scientific paper recommendation. Scientific paper recommendation aims to recommend new articles or classical articles that match researchers' interests. It has become an attractive area of study since the number of scholarly papers increases exponentially. In this paper, we first introduce the importance and advantages of the paper recommender systems. Second, we review the recommendation algorithms and methods, such as Content-based, collaborative filtering, graph-based, and hybrid methods. Then, we introduce the evaluation methods of different recommender systems. Finally, we summarize the open issues in the paper recommender systems, including cold start, sparsity, scalability, privacy, serendipity, and unified scholarly data standards. The purpose of this survey is to provide comprehensive reviews on the scholarly paper recommendation. Refereed/Peer-reviewed

Author impact evaluation and prediction play a key role in determining rewards, funding, and promotion. In this paper, we first introduce the background of the author impact evaluation and prediction. Then, we review the recent developments of the author impact evaluation, including data collection, data preprocessing, data analysis, feature selection, algorithm design, and algorithm evaluation. Third, we provide an in-depth literature review on the author impact predictive models and the common evaluation metrics. Finally, we look into the representative research issues, including author impact inflation, unified evaluation standards, academic success gene, identification of the origins of hot streaks, and higher-order academic networks analysis. This paper should help the researchers obtain a broader understanding of the author impact evaluation and prediction and provides future research directions. Refereed/Peer-reviewed

OAPA Quantifying the impact of scientific papers objectively is crucial for research output assessment, which subsequently affects institution and country rankings, research funding allocations, academic recruitment and national/international scientific priorities. While most of the assessment schemes based on publication citations may potentially be manipulated through negative citations, in this study, we explore Conflict of Interest (COI) relationships and discover negative citations and subsequently weaken the associated citation strength. PANDORA (Positive And Negative COI- Distinguished Objective Rank Algorithm) has been developed, which captures the positive and negative COI, together with the positive and negative suspected COI relationships. In order to alleviate the influence caused by negative COI relationship, collaboration times, collaboration time span, citation times and citation time span are employed to determine the citing strength; while for positive COI relationship, we regard it as normal citation relationship. Furthermore, we calculate the impact of scholarly papers by PageRank and HITS algorithms, based on a credit allocation algorithm which is utilized to assess the impact of institutions fairly and objectively. Experiments are conducted on the publication dataset from American Physical Society (APS) dataset, and the results demonstrate that our method significantly outperforms the current solutions in Recommendation Intensity of list R at top-K and Spearman & #x2019;s rank correlation coefficient at top-K. Refereed/Peer-reviewed

Quantifying success in science plays a key role in guiding funding allocations, recruitment decisions, and rewards. Recently, a significant amount of progresses have been made towards quantifying success in science. This lack of detailed analysis and summary continues a practical issue. The literature reports the factors influencing scholarly impact and evaluation methods and indices aimed at overcoming this crucial weakness. We focus on categorizing and reviewing the current development on evaluation indices of scholarly impact, including paper impact, scholar impact, and journal impact. Besides, we summarize the issues of existing evaluation methods and indices, investigate the open issues and challenges, and provide possible solutions, including the pattern of collaboration impact, unified evaluation standards, implicit success factor mining, dynamic academic network embedding, and scholarly impact inflation. This paper should help the researchers obtaining a broader understanding of quantifying success in science, and identifying some potential research directions. Refereed/Peer-reviewed

The failure of landing a job for college students could cause serious social consequences such as drunkenness and suicide. In addition to academic performance, unconscious biases can become one key obstacle for hunting jobs for graduating students. Thus, it is necessary to understand these unconscious biases so that we can help these students at an early stage with more personalized intervention. In this paper, we develop a framework, i.e., MAYA (Multi-mAjor emploYment stAtus) to predict students' employment status while considering biases. The framework consists of four major components. Firstly, we solve the heterogeneity of student courses by embedding academic performance into a unified space. Then, we apply a generative adversarial network (GAN) to overcome the class imbalance problem. Thirdly, we adopt Long Short-Term Memory (LSTM) with a novel dropout mechanism to comprehensively capture sequential information among semesters. Finally, we design a bias-based regularization to capture the job market biases. We conduct extensive experiments on a large-scale educational dataset and the results demonstrate the effectiveness of our prediction framework.

Citation prediction of scholarly papers is of great significance in guiding funding allocations, recruitment decisions, and rewards. However, little is known about how citation patterns evolve over time. By exploring the inherent involution property in scholarly paper citation, we introduce the Paper Potential Index (PPI) model based on four factors: inherent quality of scholarly paper, scholarly paper impact decaying over time, early citations, and early citers' impact. In addition, by analyzing factors that drive citation growth, we propose a multi-feature model for impact prediction. Experimental results demonstrate that the two models improve the accuracy in predicting scholarly paper citations. Compared to the multi-feature model, the PPI model yields superior predictive performance in terms of range-normalized RMSE. The PPI model better interprets the changes in citation, without the need to adjust parameters. Compared to the PPI model, the multi-feature model performs better prediction in terms of Mean Absolute Percentage Error and Accuracy; however, their predictive performance is more dependent on the parameter adjustment Refereed/Peer-reviewed

River is considered generally as a natural reservoir of antibiotic resistance genes (ARGs) in environments. For the prevention and control of ARG risks, it is critical to comprehensively characterize the antibiotic resistomes and their associations in riverine systems. In this study, we proposed a metagenomic framework for identifying antibiotic resistomes in river sediments from multiple categories, including ARG potential, ARG hosts, pathogenicity potential, co-selection potential and gene transfer potential, and applied it to understand the presence, hosts, and co-occurrence of ARGs in the sediments of an urban river in Beijing. Results showed that a total of 203 ARG subtypes belonging to 21 ARG types were detected in the river sediments with an abundance range of 107.7–1004.1×/Gb, dominated by multidrug, macrolide-lincosamide-streptogramin, bacitracin, quinolone and sulfonamide resistance genes. Host-tracking analysis identified Dechloromonas, Pseudoxanthomonas, Arenimonas, Lysobacter and Pseudomonas as the major hosts of ARGs. A number of ARG-carrying contigs (ACCs) were annotated as fragments of pathogenic bacteria and carried multiple multidrug-ARGs. In addition, various biocide/metal resistance genes (B/MRGs) and mobile genetic elements (MGEs), including prophages, plasmids, integrons and transposons, were detected in the river sediments. More importantly, the co-occurrence analysis via ACCs showed a strong association of ARGs with B/MRGs and MGEs, indicating high potential of co-selection and active horizontal transmission for ARGs in the river environment, likely driven by the frequent impact of anthropogenic activities in that area.

The first question to make a virtual reality system is to create a virtual scene. This virtual scene should be made up with factors which including three-dimensional (3d) model, 3d animation, video, sound, etc. Because people's vision is the most sensitive, the 3d model for the spread of information is the largest, and creating a realistic scenario model and a real-time dynamic display effect for virtual reality system is very important. Unity 3d is a development tool of which often used in the virtual reality system, but the scene model making function and 3d animation production ability are not good, 3DS MAX is powerful and very popular 3d modeling software. It is suitable to make 3d model for virtual reality system. This paper mainly discusses the problems of 3DS MAX in the use of virtual reality modeling.

Virtual reality eventually display need to use the camera, and the camera is an essential element in virtual reality scene, through the camera to present 3d scene. This paper mainly discusses the use of the camera in the virtual reality software Unity 3d.

Quantifying the impact of a scholarly paper is of great significance, yet the effect of geographical distance of cited papers has not been explored. In this paper, we examine 30,596 papers published in Physical Review C, and identify the relationship between citations and geographical distances between author affiliations. Subsequently, a relative citation weight is applied to assess the impact of a scholarly paper. A higher-order weighted quantum PageRank algorithm is also developed to address the behavior of multiple step citation flow. Capturing the citation dynamics with higher-order dependencies reveals the actual impact of papers, including necessary self-citations that are sometimes excluded in prior studies. Quantum PageRank is utilized in this paper to help differentiating nodes whose PageRank values are identical. Refereed/Peer-reviewed

Innovation diffusion is the process of adopting novel things, which is deemed as the diffusion of human behaviors. Previous studies mainly posit an unclear distinction with information diffusion. However, there exist critical differences in both social and economic areas. Inspired by this observation, we propose a practical method for innovation diffusion based on the process of behavior diffusion, which integrates threshold model with social imitation strategy. The primary goal of our proposed model is to combine individuals' economic as well as social characteristics to study innovation diffusion. The interplay of these two strategies is studied in the context of a coordination game. According to the simulation results on Erdös-Rényi random networks and small-world networks, we find that the conjunction of these two approaches can greatly improve the efficiency of innovation diffusion. In addition, we further study the impacts of varied initial seeds' selection strategies on the overall performance of innovation diffusion using our proposed model.

OAPA The field of Artificial Intelligence (AI) has shown an upward trend of growth in the 21st Century (from 2000 to 2015). The evolution in AI has advanced the development of human society in our own time, with dramatic revolutions shaped by both theories and techniques. However, the multidisciplinary and fast-growing features make AI a field difficult to be well understood. In this paper, we study the evolution of AI at the beginning of the 21st Century using publication metadata extracted from 9 top-tier journals and 12 top-tier conferences of this discipline. We find that the area is in sustainable development and its impact continues to grow. From the perspective of reference behavior, the decrease in self-references indicates that AI is becoming more and more open-minded. The influential papers/researchers/institutions we identified outline landmarks in the development of this field. Last but not least, we explore the inner structure in terms of topics evolution over time. We have quantified the temporal trends at the topic level and discovered the inner connection among these topics. These findings provide deep insights into the current scientific innovations, as well as shedding light on funding policies. Refereed/Peer-reviewed

Citation recommendation is an interesting and significant research area as it solves the information overload in academia by automatically suggesting relevant references for a research paper. Recently, with the rapid proliferation of information technology, research papers are rapidly published in various conferences and journals. This makes citation recommendation a highly important and challenging discipline. In this paper, we propose a novel citation recommendation method that uses only easily obtained citation relations as source data. The rationale underlying this method is that, if two citing papers are significantly co-occurring with the same citing paper(s), they should be similar to some extent. Based on the above rationale, an association mining technique is employed to obtain the paper representation of each citing paper from the citation context. Then, these paper representations are pairwise compared to compute similarities between the citing papers for collaborative filtering. We evaluate our proposed method through two relevant real-world data sets. Our experimental results demonstrate that the proposed method significantly outperforms the baseline method in terms of precision, recall, and F1, as well as mean average precision and mean reciprocal rank, which are metrics related to the rank information in the recommendation list.

A novel poly (trimethylol propane triacrylate-co-ethylene dimethacrylate) [poly (TMPTA-co-EDMA)] monolith was prepared by in situ free-radical polymerization in a 50 mm × 4.6mm i.d. stainless steel column and was investigated for high performance liquid chromatography (HPLC). The porous structure of monolith was optimized by changing the conditions of polymerization. The chemical group of the monolithic column was confirmed by a Fourier transform infrared spectroscopy (FT-IR) method and the morphology of column structure was characterized by scanning electron microscopy (SEM). The mechanical strength and permeability were also studied. Finally, a series of low-molecular-weight organic compounds were utilized to evaluate the retention behaviors of the monolithic column. The result demonstrated that the prepared column exhibited an RP-chromatographic behavior and good separation performance. The method reproducibility was obtained by evaluating the run-to-run and column-to-column with relative standard deviations (RSDs) less than 0.7% (n=6) and 2.9% (n=6), respectively, which indicated that prepared monolithic columns had good reproducibility and stability.

A porous monolith was prepared by in situ free-radical polymerization using N-isopropylacrylamide (NIPAAm) and trimethylol propane triacrylate (TMPTA) as functional monomers, ethylene dimethacrylate (EDMA) as crosslinking agent. The chemical group of the monolith was assayed by a Fourier transform infrared spectroscopy (FT-IR) method and the morphology of optimized monolithic column was characterized by scanning electron microscopy (SEM). The mechanical strength and permeability have been studied in detail as well. The run-to-run and column-to-column reproducibility of the retention times were less than 0.9% and 3.0%, respectively. Furthermore, the influence of temperature and mobile phase composition on the separation of aromatic compounds was investigated. The results indicated that poly (trimethylol propane triacrylate-co-N-isopropylacrylamide-co-ethylenedimethacrylate) (TMPTA-co-NIPAAm-co-EDMA) monolithic column not only had high porosity and strong rigidity, but also was a promising tool for analyzing small molecule compounds with a short analysis time by controlling the column temperature.

Scholarly article impact reflects the significance of academic output recognised by academic peers, and it often plays a crucial role in assessing the scientific achievements of researchers, teams, institutions and countries. It is also used for addressing various needs in the academic and scientific arena, such as recruitment decisions, promotions, and funding allocations. This article provides a comprehensive review of recent progresses related to article impact assessment and prediction. The review starts by sharing some insight into the article impact research and outlines current research status. Some core methods and recent progress are presented to outline how article impact metrics and prediction have evolved to consider integrating multiple networks. Key techniques, including statistical analysis, machine learning, data mining and network science, are discussed. In particular, we highlight important applications of each technique in article impact research. Subsequently, we discuss the open issues and challenges of article impact research. At the same time, this review points out some important research directions, including article impact evaluation by considering Conflict of Interest, time and location information, various distributions of scholarly entities, and rising stars. Refereed/Peer-reviewed

With the support of cloud computing techniques, social coding platforms have changed the style of software development. Github is now the most popular social coding platform and project hosting service. Software developers of various levels keep entering Github, and use Github to save their public and private software projects. The large amounts of software developers and software repositories on Github are posing new challenges to the world of software engineering. This paper tries to tackle one of the important problems: analyzing the importance and influence of Github repositories. We proposed a HITS based influence analysis on graphs that represent the star relationship between Github users and repositories. A weighted version of HITS is applied to the overall star graph, and generates a different set of top influential repositories other than the results from standard version of HITS algorithm. We also conduct the influential analysis on per-month star graph, and study the monthly influence ranking of top repositories.

In mammals, xylose is found as the first sugar residue of the tetrasaccharide GlcAbeta1-3Galbeta1-3Galbeta1-4Xylbeta1-O-Ser, initiating the formation of the glycosaminoglycans heparin/heparan sulfate and chondroitin/dermatan sulfate. It is also found in the trisaccharide Xylalpha1-3Xylalpha1-3Glcbeta1-O-Ser on epidermal growth factor repeats of proteins, such as Notch. UDP-xylose synthase (UXS), which catalyzes the formation of the UDP-xylose substrate for the different xylosyltransferases through decarboxylation of UDP-glucuronic acid, resides in the endoplasmic reticulum and/or Golgi lumen. Since xylosylation takes place in these organelles, no obvious requirement exists for membrane transport of UDP-xylose. However, UDP-xylose transport across isolated Golgi membranes has been documented, and we recently succeeded with the cloning of a human UDP-xylose transporter (SLC25B4). Here we provide new evidence for a functional role of UDP-xylose transport by characterization of a new Chinese hamster ovary cell mutant, designated pgsI-208, that lacks UXS activity. The mutant fails to initiate glycosaminoglycan synthesis and is not capable of xylosylating Notch. Complementation was achieved by expression of a cytoplasmic variant of UXS, which proves the existence of a functional Golgi UDP-xylose transporter. A approximately 200 fold increase of UDP-glucuronic acid occurred in pgsI-208 cells, demonstrating a lack of UDP-xylose-mediated control of the cytoplasmically localized UDP-glucose dehydrogenase in the mutant. The data presented in this study suggest the bidirectional transport of UDP-xylose across endoplasmic reticulum/Golgi membranes and its role in controlling homeostasis of UDP-glucuronic acid and UDP-xylose production.

To reveal the information hiding in the scholarly big data, relationship analysis among academic entities has been studied from different perspectives in recent years. In this paper, we focus on the problem of collaboration relationship prediction between authors in heterogeneous information networks, and a new method called MACP, i.e., Meta path and author Attribute based Collaboration Prediction model, is proposed to solve this problem. We use a two-phase collaboration probability learning approach. First, topological features with author attributes are extracted from the network, and then a supervised learning algorithm is employed to find the best weight associated with each feature to determine the collaboration relationship. We present the experiments on a real information network, namely the APS network, which shows that our proposed model can generate more accurate results compared with the method only considering structural features.

In the environmental event of hazardous release into river, quick and accurate identification of the contamination source is important for emergence response. Generally, given a noisy and finite set of monitoring information, determining the source items (i.e. location, strength and release time) is an ill-posed inverse problem. In this study, a Markov chain Monte Carlo method combined with advection-dispersion equation (ADE) was proposed for the source identification of contamination event in river system based on a Bayesian probabilistic inferential framework. Case study with analytical solution for one-dimensional ADE showed that the proposed methodology was effective and the mean posterior errors for all source parameters were lower than 3%. Case simulation based on two-dimensional ADE with numerical solution obtained similar results and further demonstrated the utility of the proposed approach for source identification. We hope the study will provide a helpful guidance to develop approach for contamination event source identification to support environmental risk management of river system.

Evaluating the sustainability of cropland use is essential for guaranteeing a secure food supply and accomplishing agriculture sustainable development. This study was conducted in the ecologically vulnerable Loess Plateau region of China to evaluate the sustainability of cropland use based on an ecological footprint model that integrates emergy analysis. One modified method proposed in 2005 is known as the emergetic ecological footprint (EEF). We enhanced the method by accounting for both the surface soil energy in the carrying capacity calculation and the net topsoil loss for human consumption in the EF calculation. This paper evaluates whether the cropland of the study area was overloaded or sustainably managed during the period from 1981 to 2009. Toward this end, the final results obtained from EEF were compared to conventional EF and previous methods. The results showed that the cropland of Yuanzhou County has not been used sustainably since 1983, and the conventional EF analysis provided similar results. In contrast, a deficit did not appear during this time period when previous calculation methods of others were used. Additionally, the ecological sustainable index (ESI) from three models indicated that the recently used cropland system is unlikely to be unsustainable.

Blue tides at the head of Tokyo Bay are a hydro-environmental phenomenon where seawater appears to be milky blue because of the reflection of the sunlight off surface water containing large amounts of sulphur particles. Its appearance is due to the coastal upwelling of bottom oxygen-depleted water induced by northeasterly wind-driven circulation. Blue tides cause the death of many shellfish and other aquatic animals across the head of Tokyo Bay and consequently result in substantial economic losses to coastal fisheries. This paper examines the occurrence of wind-driven blue tides in Tokyo Bay, based on a simplified hydrodynamic model and observational analysis. The model assumed a two-layer structure with a wind-driven upper layer and an oxygen-depleted lower layer. In this study, we derived a simple analytical solution to determine a critical wind condition for which the lower layer outcrops at the surface if the wind forcing is sufficiently strong, resulting in the mixing of the two layers and giving rise to blue tide. The results of sensitivity analyses of the analytical solution to all incorporated factors were found to be in accordance with a qualitative understanding of the blue tide phenomenon. More importantly, comparisons of observational data with real cases of blue tide during 1978–2016 and without blue tide during 2003–2016 suggested that this analytical solution was mostly valid. This study would be helpful for gaining a better understanding of the hydro-dynamical mechanism of blue tide.

A family of five beta1,3-galactosyltransferases has been characterized that catalyze the formation of Galbeta1,3GlcNAcbeta and Galbeta1,3GalNAcbeta linkages present in glycoproteins and glycolipids (beta3GalT1, -2, -3, -4, and -5). We now report a new member of the family (beta3GalT6), involved in glycosaminoglycan biosynthesis. The human and mouse genes were located on chromosomes 1p36.3 and 4E2, respectively, and homologs are found in Drosophila melanogaster and Caenorhabditis elegans. Unlike other members of the family, beta3GalT6 showed a broad mRNA expression pattern by Northern blot analysis. Although a high degree of homology across several subdomains exists among other members of the beta3-galactosyltransferase family, recombinant enzyme did not utilize glucosamine- or galactosamine-containing acceptors. Instead, the enzyme transferred galactose from UDP-galactose to acceptors containing a terminal beta-linked galactose residue. This product, Galbeta1,3Galbeta is found in the linkage region of heparan sulfate and chondroitin sulfate (GlcAbeta1,3Galbeta1,3Galbeta1,4Xylbeta-O-Ser), indicating that beta3GalT6 is the so-called galactosyltransferase II involved in glycosaminoglycan biosynthesis. Its identity was confirmed in vivo by siRNA-mediated inhibition of glycosaminoglycan synthesis in HeLa S3 cells. Its localization in the medial Golgi indicates that this is the major site for assembly of the linkage region.

We report the characterization of two Chinese hamster ovary cell lines that produce large amounts of sulfated N-linked oligosaccharides. Clones 26 and 489 were derived by stable transfection of the glycosaminoglycan-deficient cell mutant pgsA-745 with a cDNA library prepared from wild-type cells. Peptide:N-glycanase F released nearly all of the sulfate label, indicating that sulfation had occurred selectively on the Asn-linked glycans. Hydrazinolysis followed by nitrous acid treatment at pH 4 and borohydride reduction yielded reduced sulfated disaccharides that comigrated with standard Gal3SO4beta1-4anhydromannitol. The disaccharides were resistant to periodate oxidation but became sensitive after the sulfate group was removed by methanolysis, indicating that the sulfate was located at C3 of the galactose residues. Maackia amurensis lectin bound to the sulfated glycopeptides on the cell surface and in free form, even after sialidase treatment. This finding indicates that the lectin requires only a charged group at C3 of the galactose unit and not an intact sialic acid. Growth of cells with chlorate restored sialidase sensitivity to lectin binding, indicating that sulfation and sialylation occurred largely at the same sites. The enhanced sulfation was due to elevated sulfotransferase activity that catalyzed transfer of sulfate from phosphoadenosine-5'-phosphosulfate to Galbeta1-4(3)GlcNAcbeta-O-naphthalenemethanol.

To study how the pattern of sulfation along a heparan sulfate chain affects its turnover, we examined heparan sulfate catabolism in wild-type Chinese hamster ovary cells and mutant pgsF-17, defective in 2-O-sulfation of uronic acid residues (Bai, X., and Esko, J. D. (1996) J. Biol. Chem. 271, 17711-17717). Heparan sulfate from the mutant contains normal amounts of 6-O-sulfated glucosamine residues and iduronic acid and somewhat higher levels of N-sulfated glucosamine residues but lacks any 2-O-sulfated iduronic or glucuronic acid residues. Pulse-chase experiments showed that both mutant and wild-type cells transport newly synthesized heparan sulfate proteoglycans to the plasma membrane, where they shed into the medium or move into the cell through endocytosis. Internalization of the cell-associated molecules leads to sequential endoglycosidase (heparanase) fragmentation of the chains and eventual lysosomal degradation. In wild-type cells, the chains begin to degrade within 1 h, leading to the accumulation of intermediate (10-20-kDa) and small (4-7-kDa) oligosaccharides. Mutant cells did not generate these intermediates, although internalization and intracellular trafficking of the heparan sulfate chains appeared normal, and the chains degraded with normal kinetics. This difference was not due to defective heparanase activities in the mutant, since cytoplasmic extracts from mutant cells cleaved wild-type heparan sulfate chains in vitro. Instead, the heparan sulfate chains from the mutant were relatively resistant to degradation by cellular heparanases. These findings suggest that 2-O-sulfated iduronic acid residues in heparan sulfate are important for cleavage by endogenous heparanases but not for the overall catabolism of the chains.

The interaction of heparan sulfate with protein ligands depends on unique oligosaccharide sequences containing iduronic acid (IdUA), N-sulfated glucosamine residues, and O-sulfated sugars. To study the role of O-sulfation in greater detail, we isolated a Chinese hamster ovary cell mutant defective in 2-O-sulfation of iduronic acid. The mutant, pgsF-17, was identified by a colony blotting assay in which colonies of mutagen-treated cells were replica plated to two disks of polyester cloth. One disk was blotted with 125I-labeled basic fibroblast growth factor (bFGF) to measure binding to cell surface proteoglycans. The other disk was incubated with 35SO4 to measure proteoglycan biosynthesis. Autoradiography revealed a colony that did not bind 125I-bFGF, but incorporated 35SO4 normally (mutant pgsF-17). Complete deaminative cleavage of heparan sulfate revealed that material from pgsF-17 lacked IdUA(2OSO3)-GlcNSO3 and IdUA(2OSO3)-GlcNSO3(6OSO3), but contained a higher proportion of glucuronic acid GlcUA-GlcNSO3(6OSO3) and IdUA-GlcNSO3(6OSO3). Assay of the 2-O-sulfotransferase that acts on IdUA residues showed that mutant 17 lacked enzyme activity. Interestingly, the alteration resulted in accumulation of GlcNSO3 groups, suggesting that under normal conditions 2-O-sulfation decreases GlcNAc N-deacetylation/N-sulfation, and that the reactions occur simultaneously. The formation of IdUA and 6-O-sulfated glucosaminyl residues appears to be independent of 2-O-sulfation. pgsF-17 also lacks 2-O-sulfated GlcUA residues, suggesting that the same enzyme is responsible for 2-O-sulfation of IdUA and GlcUA residues. Mutant 17 provides a useful tool for studying the regulation of heparan sulfate biosynthesis and the relationship of heparan sulfate fine structure to its biological function.

This paper analyzes the situation of the library digital resources integration in China and abroad, following service oriented criterion. This paper divides resources into three types, which are local special database resource, introduced resource, and Internet resource. Based on these resources, this paper proposes service-oriented integration technology. This system puts forward library digital resources retrieval process design and digital resource integration design. The system has the higher resources retrieval and resources integration ability. Keywords-Library; Digital Resources; Retrieval System; Integration

Due to the insecurity of Internet, many enterprises and schools develop and adopt a Virtual Private Network (VPN) technology for secure intercommunication in this global open network. VPN arouses people's attention with its characteristics of safe, reliable, economical and effective transmission via a public network. This paper introduces the concept of VPN, its technological composition, classification, application and implementation. Because the education network access speed is slow, in addition visiting some data resources of the library limit the IP address range, we can't get access to the digital inner resources of school library outside the university. This article has solved library resources question accessed outside the university. It describes in detail the establishment of PPTP VPN servers, focuses on three VPN users' dialing methods aimed at different operating systems, and presents the approaches to handling common errors.

The human epidermal growth factor (EGF) receptor (HER) family members cooperate in malignancy. Of this family, HER2 does not bind growth factors and HER3 does not encode an active tyrosine kinase. This diversity creates difficulty in creating pan-specific therapeutic HER family inhibitors. We have identified single amino acid changes in epidermal growth factor receptor (EGFR) and HER3 which create high affinity sequestration of the cognate ligands, and may be used as receptor decoys to downregulate aberrant HER family activity. In silico modeling and high throughput mutagenesis were utilized to identify receptor mutants with very high ligand binding activity. A single mutation (T15S; EGFR subdomain I) enhanced affinity for EGF (two-fold), TGF-alpha (twenty-six-fold), and heparin-binding (HB)-EGF (six-fold). This indicates that T15 is an important, previously undescribed, negative regulatory amino acid for EGFR ligand binding. Another mutation (Y246A; HER 3 subdomain II) enhanced neuregulin (NRG)1-beta binding eight-fold, probably by interfering with subdomain II-IV interactions. Further work revealed that the HER3 subunit of an EGFR:HER3 heterodimer suppresses EGFR ligand binding. Optimization required reversing this suppression by mutation of the EGFR tether domain (G564A; subdomain IV). This mutation resulted in enhanced ligand binding (EGF, ten-fold; TGF-alpha, thirty-four-fold; HB-EGF, seventeen-fold; NRG1-beta, thirty-one-fold). This increased ligand binding was reflected in improved inhibition of in vitro tumor cell proliferation and tumor suppression in a human non-small cell lung cancer xenograft model. In conclusion, amino acid substitutions were identified in the EGFR and HER3 ECDs that enhance ligand affinity, potentially enabling a pan-specific therapeutic approach for downregulating the HER family in cancer.

All four members of the human epidermal growth factor (EGF) receptor (HER) family are implicated in human cancers. Although efficacious in a subset of patients, resistance to single-targeted anti-HER therapy [i.e., cetuximab (Erbitux) and trastuzumab (Herceptin)] is often associated with coexpression of other HER family members. This may be overcome by a HER ligand binding molecule that sequesters multiple EGF-like ligands, preventing ligand-dependent receptor activation. Toward this end, we have combined the HER-1/EGFR and HER-3 ligand binding domains, dimerized with fusion of an Fc fragment of human IgG1. This resulted in a mixture of HER-1/Fc homodimer (HFD100), HER-3/Fc homodimer (HFD300), and HER-1/Fc:HER-3/Fc heterodimer (RB200), also termed Hermodulins. The purified first-generation RB200 bound EGF and neuregulin 1 (NRG1)-β1 ligands, determined by cross-linking and direct binding studies. The binding affinity for both was ∼10 nmol/L by dissociation-enhanced lanthanide fluorescence immunoassay using europium (Eu)-labeled ligands. Competition studies with RB200 using Eu-EGF or Eu-NRG1-β1 revealed that RB200 bound HER-1 ligands, including transforming growth factor-α and heparin-binding EGF, and HER-3 ligands NRG1-α and NRG1-β3. RB200 inhibited EGF- and NRG1-β1–stimulated tyrosine phosphorylation of HER family proteins, proliferation of a diverse range of tumor cells in monolayer cell growth assays, tumor cell proliferation as a single agent and in synergy with tyrosine kinase inhibitors, lysophosphatidic acid–stimulated cell proliferation, and tumor growth in two human tumor xenograft nude mouse models. Taken together, the data reveal that RB200 has the potential to sequester multiple HER ligands and interfere with signaling by HER-1, HER-2, and HER-3. [Mol Cancer Ther 2008;7(10):3223–36]

The Fc effector functions of immunoglobulin G (IgG) antibodies are in part determined by structural features of carbohydrates linked to each of the paired gamma heavy chains in the antibody constant domain (C(H)2). One glycoform that has been shown to be advantageous is G2, where both arms of complex bi-antennary N-glycans terminate in galactose. In vitro treatment with glycosyltransferases can remodel heterogeneous IgG glycoforms, enabling preparation of IgG molecules with homogeneous glycan chains. Here we describe optimization of conditions for use of a soluble recombinant galactosyltransferase in vitro to remodel glycans of human serum IgG, and we demonstrate a scaled-up reaction in which >98% of neutral glycans attached to 1 kg IgG are converted to the G2 glycoform. Removal of glycosylation reagents from the product is achieved in one step by affinity chromatography on immobilized Protein A.

In previous studies, we reported the isolation and characterization of a Chinese hamster ovary cell mutant (pgsG) defective in glucuronyltransferase I (GlcATI). This enzyme adds the terminal GlcA residue in the core protein-linkage tetrasaccharide (GlcAbeta1,3Galbeta1,3Galbeta1, 4Xylbeta-O-) on which glycosaminoglycan assembly occurs (Bai, X. M., Wei, G., Sinha, A., and Esko, J. D. (1999) J. Biol. Chem. 274, 13017-13024; Wei, G., Bai, X. M., Sarkar, A. K., and Esko, J. D. (1999) J. Biol. Chem. 274, 7857-7864). Here we show that incorporation of 35SO4 into glycosaminoglycans in the mutant is temperature-sensitive, with greater synthesis occurring at 33 degrees C compared with 37 degrees C. Wild-type cells show the opposite thermal dependence. Rabbit antiserum to hamster GlcATI failed to detect cross-reactive material in pgsG cells by immunofluorescence and Western blotting. Furthermore, expression of chimeric proteins composed of mutant GlcATI fused to IgG binding domain of protein A or to green fluorescent protein did not yield the proteins at the expected mass. The green fluorescent protein-tagged version appeared as a truncated protein, and immunofluorescence showed large perinuclear bodies at 30 degrees C. At 37 degrees C, the fusion protein was not readily detectable. Sequencing cDNAs from mutant and wild-type cells revealed a single base transition (G331A) in the open reading frame in pgsG cells, which resulted in a Val-111--Met substitution. These data suggest that pgsG cells contain a labile form of GlcATI that causes conditional expression of glycosaminoglycans dependent on temperature.

To understand how 2-O-sulfation of uronic acid residues influences the biosynthesis of anticoagulant heparan sulfate, the cDNA encoding glucosaminyl 3-O-sulfotransferase-1 (3-OST-1) was introduced into wild-type Chinese hamster ovary cells and mutant pgsF-17 cells, which are defective in 2-O-sulfation. 3-OST-1-transduced cells gained the ability to bind to antithrombin. Structural analysis of the heparan sulfate chains showed that 3-OST-1 generates sequences containing GlcUA-GlcN(SO(3))3(SO(3)) and GlcUA-GlcN(SO(3))3(SO(3))6(SO(3)) in both wild-type and mutant cells. In addition, IdoUA-GlcN(SO(3))3(SO(3)) and IdoUA-GlcN(SO(3))3(SO(3))6(SO(3)) accumulate in the mutant chain. These disaccharides were also observed by tagging [6-(3)H]GlcN-labeled pgsF-17 heparan sulfate in vitro with [(35)S]PAPs and purified 3-OST-1. Heparan sulfate derived from the transduced mutant also had approximately 2-fold higher affinity for antithrombin than heparan sulfate derived from the transduced wild-type cells, and it inactivated factor Xa more efficiently. This study demonstrates for the first time that (i) 3-O-sulfation by 3-OST-1 can occur independently of the 2-O-sulfation of uronic acids, (ii) 2-O-sulfation usually occurs before 3-O-sulfation, (iii) 2-O-sulfation blocks the action of 3-OST-1 at glucosamine residues located to the reducing side of IdoUA units, and (iv) that alternative antithrombin-binding structures can be made in the absence of 2-O-sulfation.

In the preceding article (Manzi,A.E., Norgard-Sumnicht,K., Argade,S., Marth,J.D., van Halbeek,H. and Varki.A. [2000] GLYCOBIOLOGY:, 10, 669-688), we reported a comprehensive approach for the extraction, fractionation, and isolation of all of the major classes of sugar chains (glycans) from vertebrate tissues. Here we apply this "Glycan Isolation Protocol" to a variety of cultured mammalian cell lines, including two wild-type Chinese hamster ovary (CHO) cell lines and some of their genetically modified variants that were predicted or known to have defined abnormalities in the biosynthesis of one or more classes of glycans. We also use this approach to characterize clone 489, a new derivative of the GAG-deficient CHO clone pgsA-745, in which sulfation has been restored by transfection of a wild-type CHO cDNA library. By metabolically labeling the cell lines with [6-(3)H]glucosamine we were able to monitor the recovery of all major classes of glycans. The results allow us to reach several conclusions: first, the protocol described in the preceding paper is further validated by finding good recovery of total radioactivity and appropriate distribution of label in the correct glycan classes in the fractions from a variety of cell lines; second, the amount of radioactivity recovered in free glycosylphosphatidylinositol (GPI) lipids is remarkably high when compared to that found in GPI anchors, with the former being the dominant form in some cells; third, cells with known genetic mutations in specific glycosylation pathways are shown to have the expected changes in the distribution of recovered radioactivity in the appropriate fractions; fourth, the N- and O- glycans recovered via the protocol are of adequate quality to demonstrate marked differences in their structural profiles and/or content; fifth, the protocol can pick up unexpected differences of glycan classes not predicted to be affected by the primary defect; finally, the reappearance of sulfation in the novel clone 489 is not due to restoration of GAG sulfation, but rather due to the new expression of sulfation in the fraction enriched in N- and O-linked glycopeptides. These results demonstrate the power of this comprehensive approach for the concurrent exploration and profiling of the different major classes of glycans in cells.

Heparan sulfate formation occurs by the copolymerization of glucuronic acid (GlcA) and N-acetylglucosamine (GlcNAc) residues. Recent studies have shown that these reactions are catalyzed by a copolymerase encoded by EXT1 and EXT2, members of the exostosin family of putative tumor suppressors linked to hereditary multiple exostoses. Previously, we identified a collection of Chinese hamster ovary cell mutants (pgsD) that failed to make heparan sulfate (Lidholt, K., Weinke, J. L., Kiser, C. S., Lugemwa, F. N., Bame, K. J., Cheifetz, S., Massagué, J., Lindahl, U., and Esko, J. D. (1992) Proc. Natl. Acad. Sci. U. S. A. 89, 2267-2271). Here, we show that pgsD mutants contain mutations that either alter GlcA transferase activity selectively or that affect both GlcNAc and GlcA transferase activities. Expression of EXT1 corrects the deficiencies in the mutants, whereas EXT2 and the related EXT-like cDNAs do not. Analysis of the EXT1 mutant alleles revealed clustered missense mutations in a domain that included a (D/E)X(D/E) motif thought to bind the nucleotide sugar from studies of other transferases. These findings provide insight into the location of the GlcA transferase subdomain of the enzyme and indicate that loss of the GlcA transferase domain may be sufficient to cause hereditary multiple exostoses.

The proteoglycans of animal cells typically contain one or more heparan sulfate or chondroitin sulfate chains. These glycosaminoglycans assemble on a tetrasaccharide primer, -GlcAbeta1, 3Galbeta1,3Galbeta1,4Xylbeta-O-, attached to specific serine residues in the core protein. Studies of Chinese hamster ovary cell mutants defective in the first or second enzymes of the pathway (xylosyltransferase and galactosyltransferase I) show that the assembly of the primer occurs by sequential transfer of single monosaccharide residues from the corresponding high energy nucleotide sugar donor to the non-reducing end of the growing chain. In order to study the other reactions involved in linkage tetrasaccharide assembly, we have devised a powerful selection method based on induced resistance to a mitotoxin composed of basic fibroblast growth factor-saporin. One class of mutants does not incorporate 35SO4 and [6-3H]GlcN into glycosaminoglycan chains. Incubation of these cells with naphthol-beta-D-xyloside (Xylbeta-O-Np) resulted in accumulation of linkage region intermediates containing 1 or 2 mol of galactose (Galbeta1, 4Xylbeta-O-Np and Galbeta1, 3Galbeta1, 4Xylbeta-O-Np) and sialic acid (Siaalpha2,3Galbeta1, 3Galbeta1, 4Xylbeta-O-Np) but not any GlcA-containing oligosaccharides. Extracts of the mutants completely lacked UDP-glucuronic acid:Galbeta1,3Gal-R glucuronosyltransferase (GlcAT-I) activity, as measured by the transfer of GlcA from UDP-GlcA to Galbeta1,3Galbeta-O-naphthalenemethanol (