Knowledge Domain and Emerging Trends of IgG Glycosylation: A Bibliometric Study Based on CiteSpace

Background: The purpose of this paper is to evaluate the international scientic output of Igg glycosylation research by a stoichiometric analysis of the related papers published in the eld of IGG glycosylation from 2009 to 2020, to explore the hot spot of IGG glycosylation and the evolution path of IGG glycosylation. Methods: Using the Web of Science core database (WoSCC) to collect the articles related to IgG glycosylation from 2009 to 2020 as the research object, using CiteSpace visualization software to analyze the co-occurrence of countries and institutions, core authors, and keywords. Cited authors and literature, Co-citation analysis of journals, obtaining cooperation maps of research countries / institutions and core authors, literature citation and clustering maps, co-occurrence maps of high-frequency subject headings, displaying related clusters, mutual inuences between clusters and Keyword timeline view spectrum of the historical span of important keywords in clustering. Results: We searched 482 articles related to IgG glycosylation published in 227 journals, and observed that in the past 10 years, the number of articles published has generally increased year by year; it has been cited 13262 times, with an average of 27.5 citations per article, showing an upward trend year by year. The core team in the eld of IGG glycosylation is mainly from University and research institutes in USA, Australia, Netherlands, Croatia, England, Germany, Ireland, Scotland, China and Japan. A total of 2408 authors participated in the writing of literature on Igg glycosylation, Among them, Wuhrer, Manfred (cid:0) Lauc, Gordan (cid:0) Irena Trbojevic Akmacic, Wei Wang and other scholars are the representatives of this research eld and have important inuence. There are 281 keywords under the theme of IgG glycosylation, of which there are 4 keywords with word frequency ≥ 100, and hot keywords that serve as bridges are pregnancy (cid:0) complex (cid:0) glycan (cid:0) biosimilar (cid:0) N-linked glycosylation (cid:0) hilic-uplc (cid:0)


Background
In recent years, people have conducted in-depth research on the glycosylation of various proteins, and clearly understand the important role of protein glycosylation in the occurrence and development of various diseases in humans [1][2][3][4][5][6] . People's interest in the research of immunoglobulin G (Ig G) glycosylation has increased dramatically, and many magazines have published a large number of articles on IgG glycosylation. Many studies have shown that changes in Ig G glycosylation level and sugar chain structure are often accompanied by the occurrence and development of various chronic disease [6][7][8] ,Because Ig G glycosylation is highly heterogeneous and can be regarded as a disease phenotype, it may be used as a dynamic disease biomarker from the perspective of predictive, preventive and personalized medicine Thing [9][10][11][12][13][14] . With the rapid increase in the number of articles published, it becomes very di cult to identify new developments and new trends in IgG glycosylation research. The author found that there is no researcher at home and abroad to analyze the development trend of IgG glycosylation in the process of analyzing and analyzing relevant documents of IgG glycosylation, and there is still a lack of a comprehensive literature visualization measurement widely used in the knowledge structure and development of speci c research eld's analysis.
CiteSpace "Citation space" is one of the information visualization software developed by Chaomei Chen, a famous Chinese-American scholar and professor at Drexel University in the United States. It was used to measure and analyze scienti c literature data [15,16] . It focuses on nding the key points in the evolution of a research eld. It combines methods such as cluster analysis, social network analysis, and multi-dimensional scale analysis. It can achieve co-citation analysis, keyword co-occurrence analysis, and collaborative analysis of agency authors [17] . By drawing a knowledge map of the development of science and technology, it can intuitively display the panoramic view of information in the eld of scienti c knowledge, explore key literature, hot research and frontier directions in a scienti c eld. Compared with other visualization software, CiteSpace V has convenient data processing, Good visualization effect, easy interpretation, etc., can meet the requirements of large sample literature co-citation and keyword cooccurrence analysis [18,19] . The software has been widely used to evaluate the productivity of different regions, countries, institutions, authors of various University subjects, compare the cooperation of authors in national institutions, and explore research hotspots and development trends in a speci c subject area. [17] . From an objective and quantitative point of view, bibliometric analysis is a typical method of using citation relationships to generate effective materials for scientists, so it can re ect hot spots, evolutions and emerging trends in speci c elds [20] .
This article uses CiteSpace5.6.R5 to conduct a comprehensive visual analysis of the research literature of IgG glycosylation in 2009-2020 in the Web of Science database using document measurement methods and data mining algorithms. CiteSpace shows the history of knowledge development in a eld and status quo. Measure and analyze the content of relevant research institutions and related research scholars in the eld through the volume of statistics; draw and interpret the knowledge map of hot keywords in the eld of IgG glycosylation research, establish an IgG glycosylation research cluster and discuss current research Hot spots and future development trends, with a view to providing a more comprehensive reference for further research on IgG glycosylation. The second part introduces the data sources and research methods. The third part visually analyzes the results of IgG glycosylation research articles and shows the latest development and emerging trends of IgG glycosylation. The fourth part draws the main conclusions of this study, and points out the future research direction and limitations.

Data sources and retrieval methods
The data required for this research is obtained from the Web of Science database, select Web of Science Core Collection [21] , The search conditions are: TS=( Glycan OR Glycosylation) AND TS=(Ig G OR Immunoglobulin G), The time span is from 2009 to 2020, and the deadline is (April 20, 2020). After screening, 482 eligible documents were obtained, and each piece of data was downloaded as a full-text plain text format. (Table 1

Research methods
Import full-record plain text information into CiteSpace V 5.6.R5 software for visual analysis. The time span was selected from 2009 to 2020. In order to obtain high-impact nodes from the data set, according to the analysis method in Professor Chen Chaomei's article Set the time slice to one, and divide it into 11 periods from 2009 to 2020. Analyze the node types to select Author, Country, Institution, Keyword, Reference, Cited Author, and Cited Journal. The source of the subject word is selected by default; the threshold selection system default: Top N per slice = 50, which means that the top 50 nodes with the highest number of citations in each year are selected to build the network of the year, and then the network of each year is synthesized. Draw a visual knowledge map of IgG glycosylation. In order to study the details of collaboration more clearly, we use Pruning Path nder Pruning sliced networks Pruning each merged network to improve the clarity of the composite network. This research uses four scienti c measurement techniques: (1) Co-author analysis, including co-authors of authors, countries, and institutions; (2) Cod analysis to determine keywords and topic categories; (3) Co-author analysis, including cooperative journals, Co-authors and co-authored literature; (4) Cluster analysis based on cocited literature and keyword analysis. (Figure 1 On the superimposed result of the double images of the journal, the citation map is on the left and the citation map is on the right. The curve is a citation line, which completely shows the ins and outs of the citation. In the gure on the left, the more papers published in the journal, the longer the vertical axis of the ellipse; the more the number of authors, the longer the horizontal axis of the ellipse. (Figure3)

Country / Region and institution cooperation network analysis
The 482 articles included in the analysis were supported by 750 fund projects, and the National Natural Science Foundation of China Nation funded a maximum of 42 projects. Figure 3a below shows the academic cooperation between 53 countries / regions conducting IgG glycosylation research. Overall, the cooperation between countries in the eld of IgG glycosylation research is relatively close. The top ten countries in frequency are USA (136), Netherlands (96), China (75), Germany (63), Croatia (60), England (53), Australia (28), Japan (27), Ireland (24), and Scotland (22). Centrality describes the importance of nodes. The size of Centrality was re ected in the purple circle on the outer edge of the node on the cooperative network map. The highest Centrality country in the map we made is USA (centrality = 0.48) followed by GERMANY (centrality = 0.35), AUSTRALIA (centrality = 0.27), ENGLAND (centrality = 0.23), CROATIA (centrality = 0.22) According to the meaning of centrality described above, that is, intermediary centrality ≥0.1 represents the node has a turning point in the network, indicating that these ve countries 3.4 Research Focus and cutting-edge cluster analysis Key words are the most concentrated words that can show the main content of the paper. The frequency of key words is usually positively correlated with the research focus, this shows that by analyzing the frequency of keywords appearing in the literature of a certain eld, we can nd out the current research hotspot of this eld, and we can understand the development and changes of this eld according to the appearance of keywords in different periods [18] . In the co-occurrence graph, the frequency of the keywords indicates the extent of the research in this eld. We can identify the research hotspots in this eld by the terms of high Centrality or Bursts, according to the frequency of emergence words in different periods, we can understand the development of this eld in the time line, and then judge the research frontiers and trends. Bursts refers to the signi cant increase in the frequency of keyword use in a short period of time, and measures the rate of change in the frequency of citation of literature containing keywords, the high Bursts vocabulary will become the hot spot in the future. Using key words that can reveal or express the core content of the literature in a eld of frequency of keyword frequency analysis could be found in the center and frequency of emergence of vocabulary.

IgG glycosylation research keywords general situation
We used the CiteSpace 5.6.R5 software to analyze the collinearity of keywords, and generated 211 nodes and a high frequency keyword co-occurrence graph of 906 connections ( Figure 6). The node size represents the frequency of keywords, that is, the larger the cross shape, the higher the frequency of changing keywords. The connection between nodes indicates that the connected keywords appear together in the literature, and the thickness of the connection re ects the number of co-occurrences to re ect the degree of keyword relevance in the research [19] . From January 2009 to April 2020, there were 281 keywords in 482 articles under the theme of IgG glycosylation research. The basic vocabulary of this research eld, so we have not analyzed it speci cally. It could be seen in Figure 5 that rheumatoid arthritis has the highest number of occurrences, 121 times, which may be related to IgG glycosylation that has been used as an effective diagnostic biomarker for autoimmune diseases in recent years. Followed by Anti-in ammatory activity, appeared 104 times. Immunoglobulin G and Glycosylation are in the central area of the network map and the keywords distributed around it are mainly rheumatoid arthritis, Antiin ammatory activity, igg, antibody, monoclonal antibody, mass spectrometry, glycol, galactosylation. The top 5 in Centrality are mass spectrometry 0.17, liquid chromatography 0.12, oligosaccharide 0.11, ame 0.10, identi cation 0.10; the top 5 in Bursts are biomarker 9.00, N-glycan 7.12, oligosaccharide 5.76, structural change 4.99, N-glycosylation 4. 64. It is worth noting that although the biomarker appears only 36 times, it is Centrality = 0.01, Bursts = 9.00, indicating that it has an important position in recent research. Table5 Table6

Dynamic frontier evolution of IgG glycosylation keywords
From the change of keywords, we can nd that IgG glycosylation involves a lot of content. To better analyze the research direction of IgG glycosylation, use the Timeline view function in CiteSpace software to display the dynamic frontier map to see the IgG glycosylation Clustering and development of keywords in the process of research. Taking the publication year as the X-axis and the cluster number as the Y-axis to obtain the IgG glycosylation timeline evolution chart can clearly see the literature of these 7 clusters. The more important. The research on IgG glycosylation is mainly divided into 7 major themes, namely # 0pregnancy, # 1complex, # 2glycan, # 3, biosimilar, # 4N-linked glycosylation, # 5 hilic-uplc, # 6 glycation.
Based on the results of keyword clustering, we can draw the development and structural changes of IgG glycosylation research hotspots in recent years. (Figure7)

Frontier topics in IgG glycosylation research
We use CiteSpace to select keywords with a large frequency of change. According to the frequency of changes, we can judge the development trend of IgG glycosylation research and Burst by keywords provides a reasonable basis for the research frontier prediction. In the gure, there is a ashing bar after with an average of 29.9 articles per article. Table3 shows the top ten most cited journals. According to the number of citations, the best journal is "Journal of Biological Chemistry", there are 328 cited records. Therefore, we can think that "Journal of Biological Chemistry" is our journal. The best reference source for the research topic of IgG glycosylation; in terms of impact factor (IF), there is no doubt that "Science" (IF = 41.037) and "Nature" (IF = 43.070) have the greatest impact on our research and the most signi cant Farreaching. In the visual map, we can also see that there are multiple journal nodes surrounded by purple rings. These journals have a high Centrality. Centrality was used as an indicator to measure and discover the importance of nodes in the graph. Purple rings indicate the structure of nodes The characteristic, the thickness of which implies the degree of centrality, here the nodes with intermediary centrality ≥0.1 are highlighted with purple circles [15] In the map, you can see "Molecular Immunology" (centrality = 0.17); "Current Opinion in Immunology" (centrality = 0.11); "Cell" (centrality = 0.11), these journals play an important role in connecting different journals, and are IgG An important turning point in glycosylation research. In the visual analysis, we found that some journals have burst. Figure 4 shows the main journal and citation Burst detection. Burst detection acts as an indicator of active nodes in the visualization process. We can see that the nodes of "Scienti c Reports" (burst strength = 21.72, 2016) and "Frontiers in Immunology" (burst strength = 19.99, 2017) are red, which proves that Burst appears, indicating that the articles published by the journal are in the near future Being cited heavily, the journal has attracted great attention from peers in a short period of time [18] (Figure9)

Co-citation analysis of References
In bibliometric, the research frontier represents the development status of a research eld, and the citations of research frontier articles constitute the subject knowledge base of the research eld. Cocitation analysis is one of the important methods of bibliometric. Since Small [26] introduced the concept of co-citation, and de ned it as "two documents appear in the reference list of the third citing document together", we conducted a total of literature citations on a collection of literature spatial data sets. Consider the process of mining cited relationships could as co-cited analysis of the literature. It could also be said that when certain literatures are cited in large numbers by other authors in the eld, the theoretical knowledge re ected in the literature is widely recognized by the scienti c community [27] The citation frequency of the citation can be used to measure the academic in uence of the article [28] Articles with high citation frequency show the core achievements in this eld. At the same time, citations can also be used to nd "classical articles" in the eld through the co-citation network. [29] We made 446nodes and 2297lines of the literature total citation map through the software shown in Figure 6. We can see in Figure  6 that 10 articles cited more than 45 times are at the core of the literature co-cited network graph. Table 7 lists the 10 articles with the highest cited frequency. Puci M (2011) the article titled "High throughput isolation and glycosylation analysis of IgG-variability and heritability of the IgG glycome in three isolated human populations" published in MOL CELL PROTEOMICS was cited the most, namely 100 times. Pucic M conducts IgG glycosylation studies at Genos Ltd, Glycobiology Division in Croatia, Zagreb. Through the continuous efforts of researchers in the eld of IgG glycosylation, the knowledge structure of research in this eld has been formed and developed, which provides a more comprehensive knowledge network for the subsequent research of IgG glycosylation. Overall, the network of core co-citation relationships is complex, indicating that academic research results in the eld of IgG glycosylation have a strong cocitation relationship. (Figure 10 Table8 Table9)

Discussion
This article uses CiteSpace software to perform a retrospective visual analysis of the literature on IgG glycosylation in the Web of Science database from 2009 to 2020. The combination of analysis and reference co-citation analysis and keyword co-occurrence analysis can basically re ect the research hotspots and development trends in the eld of IgG glycosylation in the past decade. To the best of our knowledge, this article is the rst article to use CiteSpace software to perform bibliometric analysis of IgG glycosylation. This study can deepen researchers' understanding and understanding of IgG glycosylation research from the following aspects. It can provide help for the further development of IgG glycosylation.

IgG glycosylation research status
In the third part, it could be seen that the amount of articles published in the eld of IgG glycosylation is generally increasing year by year. Judging from the connection and color of each node in the visual knowledge graph, from 2009 to now, institutions in various countries have cooperated closely and formed a high-yield network diagram with the university laboratory as the core. In particular, Leiden University in the Netherlands and the University of Zagreb in the Republic of Croatia are the most eye-catching, indicating that countries with a dominant position in the eld of proteomics also have certain advantages in the eld of IgG glycosylation. The distribution of institutions and authors involved in IgG glycosylation research is relatively concentrated, mainly based on intra-team cooperation, and most articles belong to multiple authors. An Authors 'cooperative relationship network with Wuhrer, Manfred, Lauc, Gordan, Irena Trbojevic Akmacic, and Wei Wang as core nodes. They promote the development of the IgG glycosylation eld with a higher volume of posts. The major in uencers are NETHERLANDS, Wuider of Leiden University, Professor Manfred 's team, CROATIA, University of Zagreb 's Lauc, Professor Gordan 's team, CHINA, Capital Medical University Professor Wei Wang's team has made great contributions to the development of the IgG glycosylation eld with high in uence and published articles and a relatively high citation frequency. The line color between the author and the institution was mainly based on warm colors, which shows that the authors in the eld of IgG glycosylation have cooperated more in recent years. Since 2014, with the further deepening of proteomics and glycemic research, IgG glycosylation has attracted more and more attention as a biomarker for early detection and diagnosis of various chronic diseases, and corresponding research results have continuously emerged. However, it could be seen that there are not many countries participating in IgG glycosylation research. This is because the extraction methods and testing equipment required for IgG glycosylation research are more expensive, and the research institutions need stronger scienti c research capabilities. The inconsistency and imbalance in the development of scienti c research capabilities of different institutions in different countries have a great relationship.
The articles of IgG glycosylation research were mainly published in professional journals such as JOURNAL OF PROTEOME RESEARCH, Molecular and Cellular Endocrinology, ANALYTICAL CHEMISTRY, SCIENTIFIC REPORTS. In recent years, Glycobiology, Moll Cell Proteomics and other professional magazines also have a large number of reference sources in top magazines such as Science and Nature, which shows that the direction of IgG glycosylation research has been more and more widely valued.

Research hot content analysis
Since all IgG contains polysaccharides and the speci c interaction of IgG Fc domain with Fc receptors is in antibody-dependent cell-mediated cytotoxicity (ADCC) [30] , complement-dependent cytotoxicity (CDC) [31] , Anti-in ammatory activity [32][33][34] , pharmacokinetic half-life [35] and immunology [36] all play an important role, so IgG glycosylation modi cation research has been subject to the development of tumor immunology, biosimilar, and antibody drugs Attention to the eld. Protein glycosylation is involved in many human physiological and pathological processes, such as cancer [37][38][39][40][41][42] , aging [1,[43][44][45] , congenital glycosylation disease [46] , diabetes [47][48][49] , neurological diseases [6,50,51] , pregnancy-related diseases [52] , autoimmune diseases [53,54] , primary desiccation syndrome [55] , thrombocytopenic purpura (ITP), chronic in ammatory demyelination Multiple neuropathy (CIDP), myasthenia gravis, and some rare diseases. At the same time, glycosylation also plays an important role in the human immune system, and these roles help us to speci cally recognize these reactions [56] . Because IgG is the most abundant glycoprotein in immunoglobulin and its N-glycan participates in many physiological case processes, it was often considered an effective biomarker for us to recognize a certain disease [9,11,57] . It can also be seen from the cutting-edge trends of this research that since 2018, IgG glycosylation as a diagnostic biomarker for chronic diseases has gradually become a major research hotspot in the eld.
In addition, as antibody drugs have been developed as effective preparations for disease prevention, diagnosis and treatment for hundreds of years in recent years, the vast majority of antibody drugs approved abroad are IgG1 and are expected to become the fastest growing in the entire pharmaceutical industry One of the areas. Since all IgG contains polysaccharides and the Fc domain of IgG speci cally interacts with Fc receptors, these glycans all bind to the Fc R-terminus and C1q [58,59] , thus affecting the function of IgG, which has led to the development of therapeutic monoclonal antibodies that enhance the effectiveness of antibody-dependent cell-mediated cytotoxicity (ADCC) in glycosylation engineering of these Fc glycans [60,61] . This kind of glycosylation modi cation of the Fc region of the antibody controls the oligosaccharide composition of the antibody to enhance its e cacy. This process was called glycosylation engineering. One of the goals of the new generation of antibody drug development is mainly glycosylation engineering antibodies , Mainly including three directions: (1) lack of core fucose to improve antibody ADCC response function [62] , (2) increase bismuth acetyl glucosamine content to improve antibody ADCC effect [63] , (3) Increase the sialic acid content to increase the anti-in ammatory activity of antibodies [64] . At the same time, in recent years, more and more IgG is used for the immunomodulation of acute and chronic autoimmune diseases through intravenous injection (IVIG) or subcutaneous injection (SCIG) [65,66] , so some scholars believe that a small part of IgG The occurrence of Fab sialylation leads to the anti-in ammatory effects of intravenous immunoglobulin (IVIG). Fleur S. van de Bovenkamp et al. proved through a series of experiments that Fab glycosylation could enhance the a nity of antibodies for homologous antigens [61] . Therefore, IgG glycosylation occupies an important position in the eld of antibody preparation research and development.

Limitations of this study
This study only includes the literature collected from the Web of Science database from 2009 to the present. Due to the year of the database, the number of articles included may be lacking, and it needs to be more detailed and comprehensive in related research in the future.

Conclusion
Through this study, we found that the amount of articles published in the eld of IgG glycosylation is generally increasing year by year. Using CiteSpace software to carry out quantitative analysis of IgG