Bibliometric analysis of global research trends on regulatory T cells in neurological diseases

Bibliometric analysis of global research trends on regulatory T cells in neurological diseases | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Bibliometric analysis of global research trends on regulatory T cells in neurological diseases Qian Gao, Xinmin Li, Yan Li, Junzi Long, Mengyang Pan, Jing Wang, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3234444/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This bibliometric study aimed to summarize and visualize the current research status, emerging trends and research hotspots of regulatory T (Treg) cells in neurological diseases. Relevant documents were retrieved from the Web of Science Core Collection. Tableau Public, VOSviewer and CiteSpace software were applied to perform bibliometric analysis and network visualization. A total of 2739 documents were included, and research on Treg cells in neurological diseases is still in a prolific period. The documents included in the research were sourced from 85 countries/regions, with the majority of them originating from the United States, and 2811 organizations, with a significant proportion of them coming from Harvard Medical School. Despite being the most prolific author in this research area, Gendelman HE had relatively few collaborations with researchers from other organizations. Considering the number of documents and citations, impact factors and JCR partitions, Frontiers in Immunology was the most popular journal in this research area. Keywords “multiple sclerosis”, “inflammation”, “regulatory T cells”, “neuroinflammation”, “autoimmunity”, “cytokines” and “immunomodulation” were identified as high frequency keywords. Additionally, “gut microbiota” has recently emerged as a new topic of interest. The study of Treg cells in neurological diseases continues to be a hot topic. Immunomodulation, gut microbiota, and cytokines represent the current research hotspots and frontiers in this field. Treg cell-based immunomodulatory approaches have shown immense potential in the treatment of neurological diseases. Modifying gut microbiota or regulating cytokines to boost the numbers and functions of Treg cells represents a promising therapeutic strategy for neurological diseases. Biological sciences/Immunology Health sciences/Diseases Health sciences/Molecular medicine Health sciences/Neurology Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1. Introduction The nervous system serves as the body’s command center, and interruptions or impairments of its function can induce neurological diseases, including stroke, spinal cord injury, traumatic brain injury, multiple sclerosis (MS), Alzheimer’s disease (AD), Parkinson’s disease (PD), etc [1]. Unfortunately, neurological diseases remain highly prevalent, with a scarcity of effective therapeutic strategies [2,3]. As a result, these disorders pose a considerable socioeconomic burden to society, underscoring the urgent need for continued research and development of effective therapies in the field of neurology. While inflammation may not be the direct cause of neurological diseases, accumulating evidence suggests its involvement in their pathogenesis once these diseases have manifested. Recent research indicates that disordered innate and adaptive immune responses play a crucial role in the pathological processes of neurological diseases, potentially resulting in autoimmunity, tissue and cellular damage, and subsequent neurological degeneration [4]. By addressing the underlying pathological processes that contribute to neurological disease, it is possible to improve the neurological symptoms for individuals affected by these conditions. Therefore, developing effective therapeutic strategies to manage immune-mediated inflammation is crucial in preventing or delaying the onset and progression of neurological diseases. Regulatory T (Treg) cells are a minor subpopulation of CD4 + T cells defined by constitutive expression of IL-2 receptor alpha (CD25) and forkhead box p3 (Foxp3) [5]. Studies have indicated that Treg cells play a beneficial role in delaying the onset and progression of neurological diseases, while dysfunction in Treg cells may lead to the development of autoimmune disease and the progression of neuroinflammation. [6]. By suppressing adaptive immune responses and regulating innate immune responses, Treg cells are capable of curtailing excessive immune responses and preserving immune homeostasis [7]. The findings of a study on experimental autoimmune encephalomyelitis indicated that Treg cells play a facilitative role in the remyelination process and exert suppressive effects on neuroinflammatory responses during the chronic stages of MS [8]. The expansion of Treg cells has been shown to effectively suppress immune responses and mitigate dopaminergic neurodegeneration in A53T-α-synuclein PD mice [9]. In short, promoting the production and activity of Treg cells represents promising therapeutic strategies for managing immune-mediated inflammation in neurological diseases. Therefore, it is extremely important to understand the current research status and development trends concerning Treg cells in neurological diseases. Gaining such knowledge can help to further explore immunological mechanisms and therapeutic strategies of neurological diseases, and address relevant clinical problems. Bibliometric analysis can analyze and visualize scientific outputs, research hotspots and trending topics of a certain field in the public literature databases [10]. Bibliometric tools, including VOSviewer and CiteSpace, are commonly applied to visualize results of document analysis, which have been widely used in medical fields [11–14]. VOSviewer, a free Java-based software, can be used to analyze a large number of documents data in an easy-to-interpret way and display it in the form of a map [11]. By using CiteSpace, a Java-based software, research results in a certain field can be visualized to help researchers and experts understand the knowledge domain, research frontier and development trend [15]. Although bibliometric studies on neurological diseases have been conducted, there has yet to be a bibliometric analysis of Treg cells in neurological diseases [16,17]. This study aimed to bridge this knowledge gap by conducting a bibliometric analysis of documents on Treg cells in neurological diseases. Specifically, this analysis identified major contributors and current research status, and evaluated future development prospects and research trends in this field. 2. Methods 2.1 Data sources and search strategy All data was downloaded from the Web of Science Core Collection online database, and the search strategy was as follows: TS=(“regulatory T cell*” OR “regulatory T-cell*” OR “Treg*” OR “T-reg*”) AND TS=(“neuro*”) [17]. Subsequently, we limited the document types to articles and review articles, and selected documents written in English. Finally, relevant data was exported in plain text file with full records and cited references. 2.2 Bibliometric analysis We analyzed relevant data in the following aspects: the annual number of documents, countries/regions, organizations, authors, journals, keywords, and references. Online platform ( http://www.bioinformatics.com.cn ) was used to plot the annual document output. Software Tableau Public was applied to draw the geographical distribution of documents. VOSviewer v.1.6.1 and CiteSpace v.6.1.R6 were applied to perform the bibliometric analysis and network visualization, including co-authorship analysis of countries/regions, organizations and authors, co-occurrence analysis of keywords, citation analysis of journals and documents, and co-citation analysis of references. 3. Results 3.1 The trend of document outputs A total of 2739 documents, including 1737 articles and 1002 review articles, were collected from the Web of Science Core Collection on August 02, 2023. The research selection process and the reasons for excluding documents are shown in Fig. 1 . As shown in Fig. 2 , the research trend can be divided into three stages. During the first stage, spanning from 1991 to 2003 and comprising 20 documents, the output of published research on Treg cells in neurological diseases gradually increased from 1 to 6. This suggests that the field was still in a nascent period, with relatively few studies conducted on the topic at the time. The second stage was from 2004 to 2019, during which the annual output climbed rapidly with a slight fluctuation in 2011. Starting from 2020, the third stage has been a volatile but prolific period in which the annual output of research on Treg cells in neurological diseases has consistently exceeded 210 documents, despite fluctuations. Only 7 months of documents were counted in 2023, but the overall trend in published research was stable. It suggested that the role of Treg cells in neurological diseases has attracted extensive attention worldwide since 2004, and remains a continuing hotspot. 3.2 Countries/Regions A total of 85 countries/regions dabbled in the role of Treg cells in neurological diseases (Fig. 3 a). The United States, China and Germany were the top three countries/regions with the most documents on Treg cells in neurological diseases (Table 1 ). The United States not only had the largest number of documents and citations but also had the highest total link strength and centrality, making it a leading contributor to research on Treg cells in neurological diseases. Annual outputs of the top 10 countries/regions are shown in Fig. 3 b. The United States posted significantly more annual output than any other country/region until 2021, after which the United States decreased, while China overtook other countries/regions to rank first. In addition, the United States was the earliest country to focus on this research area, while China didn’t begin to bloom until 2015. The United States, Germany, France and England had the highest centrality, indicating that they had a strong bridge role in this field (Fig. 3 c). Some of documents were completed in cooperation with multiple countries/regions. The United States had collaborated with 57 countries/regions, and Germany had collaborated with 48 countries/regions. Table 1 Top10 countries/regions with the most documents. Rank Country/Region Documents Citations Total link strength Centrality 1 USA 1050 63033 554 0.38 2 China 458 12210 186 0.07 3 Germany 328 20735 308 0.18 4 Italy 195 10065 145 0.04 5 England 135 7240 178 0.1 6 Japan 111 6519 59 0 7 Spain 108 4743 100 0.03 8 France 106 4287 98 0.15 9 Canada 104 6127 120 0.06 10 Australia 101 5131 107 0.02 3.3 Organizations A total of 2739 documents were published by 2811 different organizations, and 61 met the threshold (minimum number of documents of an organization: 15). After excluding disjointed organizations, the remaining 59 organizations were visualized (Fig. 4 a). The top 10 organizations with the most documents are listed in Table 2 , and 7 of the top 10 organizations were affiliated with the United States. Harvard Medical School ranked first in terms of the number of documents and citations, total link strength and centrality, indicating that it was the most prolific organization and had the most cooperation with other organizations. In addition, the University of California system, including University of California, San Francisco and University of California, Los Angeles, was another important organization in this research area. As shown in Fig. 4 b, Harvard Medical School, University of Pittsburgh and Fudan University (nodes with yellow color) were the most recent organizations to publish more documents. The top 3 organizations with the strongest citation bursts were Consejo Superior de Investigaciones Cientificas (CSIC) from 2006 to 2013, Harvard University from 2000 to 2009 and Weizmann Institute of Science from 2001 to 2005 (Fig. 4 c). The citation bursts in many organizations have continued until 2023, suggesting that Treg cells in neurological diseases remain the hotspot for future research by many organizations. Table 2 Top10 organizations with the most documents. Rank Organization Country/Region Documents Citations Total link strength Centrality 1 Harvard Medical School USA 64 4019 43 0.17 2 Consejo Superior de Investigaciones Cientificas (CSIC) Spain 47 1814 5 0.04 3 Weizmann Institute of Science Israel 45 2586 6 0.03 4 University of California, San Francisco USA 36 3426 23 0.05 5 Fudan University China 35 1482 16 0.04 6 University of Nebraska Medical Center USA 35 1801 3 0.01 7 University of California, Los Angeles USA 34 1459 26 0.03 8 Harvard University USA 33 3543 10 0.09 9 Stanford University USA 31 2717 39 0.13 10 University of Pittsburgh USA 31 2394 21 0.09 3.4 Authors A total of 13859 authors were involved in Treg cells in neurological diseases, and 185 met the threshold (minimum number of documents of an author: 5). The largest set of connected items consisted of 51 authors (Fig. 5 a). The top 15 core authors in this field are listed in Table 3 , of which 6 authors came from the United States. The top 15 authors published 271 documents, accounting for 9.89% total number. Gendelman HE was top author with the largest number of documents and citations, followed by Mosley RL. Notably, both of them affiliated with University of Nebraska Medical Center in the United States, which ranked sixth in terms of the number of documents about the role of Treg cells in neurological diseases. As shown in the visualization map of authors (Fig. 5 a), Wiendl H was the center of authors’ co-authorship relations and had the longest citation bursts. However, Gendelman HE was not involved in the largest connected cooperative network. A total of 8 authors had cooperation with Gendelman HE, and they were all affiliated with University of Nebraska Medical Center (Fig. 5 b). Several emerging scholars (nodes with yellow color) have also begun to dabble in this field, suggesting that Treg cells in neurological diseases are still a hotspot for future research. The top 3 authors with the strongest citation bursts were Delgado M from 2006 to 2010, Schwartz, M from 2001 to 2005 and Gendelman HE from 2009 to 2011, indicating that they were leaders of this field in a certain period (Fig. 5 c). Table 3 Top15 authors with the most documents. Rank Author Organization Country/Region Documents Citations Total link strength 1 Gendelman HE University of Nebraska Medical Center USA 34 1935 80 2 Mosley RL University of Nebraska Medical Center USA 27 1655 76 3 Delgado M Consejo Superior de Investigaciones Cientificas (CSIC) Spain 26 859 48 4 Gonzalez-rey E Consejo Superior de Investigaciones Cientificas (CSIC) Spain 24 806 51 5 Bae H Kyung Hee University Korea 20 529 33 6 Wiendl, H University of Münster Germany 20 1217 38 7 Offner H VA Portland Health Care System, Oregon Health & Science University USA 17 687 23 8 Schwartz M The Weizmann Institute of Science Israel 17 1242 4 9 Olson KE University of Nebraska Medical Center USA 14 402 44 10 Appel SH Houston Methodist Research Institute USA 12 1078 25 11 Fragoso G Univ Nacl Autonoma Mexico Mexico 12 173 40 12 Hu X University of Pittsburgh School of Medicine USA 12 749 27 13 Kipnis J The Weizmann Institute of Science Israel 12 569 2 14 Liesz A Heidelberg University Germany 12 1251 10 15 Meuth SG Heinrich-Heine University of Düsseldorf Germany 12 606 25 3.5 Journals A total of 859 journals published 2739 documents concerning Treg cells in neurological diseases. The top 11 journals are listed in Table 4 , they published 618 documents, accounting for approximately 22.56% of the total. The most prolific journal was Frontiers in Immunology with 134 documents, followed by Journal of Immunology with 90 documents, and Journal of Neuroinflammation with 75 documents. Impact factors of the top 11 journals ranged from 3.3 to 15.1, of which Brain Behavior and Immunity was the highest, and Journal of Neuroimmunology was the lowest. Of the top 11 journals, 6 journals belonged to Q1, 4 journals belonged to Q2, and the remaining 1 journal belonged to Q3. Notably, Journal of Experimental Medicine , with the most citations (4352 times), was not among the top 11 journals. The document “HIF1 alpha-dependent glycolytic pathway orchestrates a metabolic checkpoint for the differentiation of T(H)17 and T-reg cells” published in this journal in July 2011 was cited 1215 times, which ranked second in terms of the number of citations. Although the number of documents published in Journal of Experimental Medicine was relatively small, the quality of documents was relatively high, which had conspicuously pushed forward the progress in this field. In short, both the number and the quality of documents need to be considered in the evaluation of prolific journals. Considering the number of documents and citations, impact factors and JCR partitions, Frontiers in Immunology was the most popular journal in this research area. Table 4 Top11 journals with the most documents. Rank Journal Documents Citations Total link strength Impact factor (2022) JCR partition 1 Frontiers in Immunology 134 4351 603 7.3 Q1 2 Journal of Immunology 90 4323 463 4.4 Q2 3 Journal of Neuroinflammation 75 3057 405 9.3 Q1 4 Journal of Neuroimmunology 72 2117 335 3.3 Q3 5 International Journal of Molecular Sciences 47 1273 212 5.6 Q1 6 PLoS One 46 1925 199 3.7 Q2 7 Brain Behavior and Immunity 38 1440 188 15.1 Q1 8 Scientific Reports 33 955 116 4.6 Q2 9 Journal of Neuroimmune Pharmacology 29 1144 161 6.2 Q1 10 Immunology 27 1365 148 6.4 Q2 11 Proceedings of the National Academy of Sciences of the United States of America 27 3238 299 11.1 Q1 3.6 Keywords A total of 4868 author keywords were involved in 2558 documents and 354 met the threshold (minimum number of documents of a keyword: 5). The overlay visualization map showed the co-occurrence relations of keywords (Fig. 6 a), in which “multiple sclerosis”, “inflammation”, “regulatory T cells”, “neuroinflammation”, “autoimmunity”, “microglia” “cytokines”, “experimental autoimmune encephalomyelitis” “immunotherapy” and “immunomodulation” were identified as high frequency keywords. Moreover, these keywords were mostly associated with neuroprotection, neuroimmunology and immunoregulation in 2014, interconnected with myasthenia gravis, MS and neurodegeneration in 2016, related to PD, AD and spinal cord injury in 2018, and currently linked to ischemic stroke, gut microbiota and gut-brain axis. Recently, the role of gut microbiota in neurological diseases has gained significant attention, with substantial evidence linking it to neuroinflammation. As shown in Fig. 6 b, the timeline view of keywords clustering analysis was displayed to show the basic knowledge structure and the evolution over time of Treg cells in neurological diseases. The modularity Q was 0.4075, indicating that the network structure was consequential, and mean silhouette S was 0.6183, implying that clustering was credible. Keywords with close relationship were automatically grouped into a cluster, which was named by the keyword with the largest Log-likelihood rate. Cluster “#0 expression” “#2 multiple sclerosis” and “#4 activation” appeared earliest, and cluster “#1 parkinsons disease” appeared latest. Cluster “#0 expression”, “#1 parkinsons disease” and “#6 gut microbiota” related studies were available in 2023, which may become frontiers of Treg cells in neurological diseases in the future. while cluster “#2 multiple sclerosis”, “#3 tryptophan”, “#4 activation” and “#5 gene expression” gradually decreased or even disappeared. The top 30 keywords with the strongest citation bursts are showed in Fig. 6 c, which were considered as consequential milestones for the science mapping research. “Immune privilege” and “anterior chamber” were important contents of the earliest research, suggesting that the immune privilege of the anterior chamber was an early research hotspot and had occupied a major position in this field. Keywords “antigen” had the longest, 16 years of duration burst. In addition, “experimental allergic encephalomyelitis” had the highest burst strength from 1998 to 2011, which implied that scholars can never ignore its equally important existence when conducting research in this field, followed by “myelin basic protein” and “vasoactive intestinal peptide”. 3.7 Citations The top 10 documents with the most citations are listed in Table 5 , and the range of citations was from 597 to 2058. The top 3 documents with the most citations were documents written by Scheller J in 2011 [18], Shi LZ in 2011 [19] and Setoguchi R in 2005 [20], which all introduced the role of cytokines in autoimmune neurological diseases. Document written by Lee YK in 2011 [21], pointed out gut microbiota impacts the balance between pro-and anti-inflammatory immune responses during experimental autoimmune encephalomyelitis. Document written by Wang MN in 2017 [22], focused on the role of tumor microenvironment in tumorigenesis of glioma, glioblastoma and other cancers. Documents, written by Lakhan SE in 2009 [23], Karussis D in 2010 [24] and Haroon E in 2012 [25], introduced the immunological mechanisms underlying several therapeutic approaches for neurological diseases, such as ischemic stroke, MS, amyotrophic lateral sclerosis and depression. Table 5 Top 10 documents with the most citations. Rank Title First author Journal Citations 1 The pro- and anti-inflammatory properties of the cytokine interleukin-6 Scheller J (2011) Biochimica Et Biophysica Acta-Molecular Cell Research 2058 2 HIF1 alpha-dependent glycolytic pathway orchestrates a metabolic checkpoint for the differentiation of T(H)17 and T-reg cells Shi LZ (2011) Journal of Experimental Medicine 1215 3 Homeostatic maintenance of natural Foxp3(+) CD25(+) CD4(+) regulatory T cells by interleukin (IL)-2 and induction of autoimmune disease by IL-2 neutralization Setoguchi R (2005) Journal of Experimental Medicine 941 4 Proinflammatory T-cell responses to gut microbiota promote experimental autoimmune encephalomyelitis Lee YK (2011) Proceedings of the National Academy of Sciences of the United States of America 910 5 Role of tumor microenvironment in tumorigenesis Wang MN (2017) Journal of Cancer 798 6 Inflammatory mechanisms in ischemic stroke: therapeutic approaches Lakhan SE (2009) Journal of Translational Medicine 705 7 Safety and Immunological Effects of Mesenchymal Stem Cell Transplantation in Patients With Multiple Sclerosis and Amyotrophic Lateral Sclerosis Karussis D (2010) Archives of Neurology 679 8 The Immunomodulatory and Anti-Inflammatory Role of Polyphenols Yahfoufi N (2018) Nutrients 676 9 Psychoneuroimmunology Meets Neuropsychopharmacology: Translational Implications of the Impact of Inflammation on Behavior Haroon E (2012) Neuropsychopharmacology 626 10 Effects of stress on immune function: the good, the bad, and the beautiful Dhabhar FS (2014) Immunologic Research 597 Co-citation analysis of cited references was performed by VOSviewer. A total of 162113 cited references were involved in 2739 documents, and 131 met the threshold (minimum number of citations of a cited reference: 40). The density visualization map of cited references based on citations is shown in Fig. 7 a, and the top 10 cited references with the most citations are shown in Table 6 . Reference with the most citations was article written by Liesz A in 2009, which indicated that research in this article may be a research hotspot, followed by references written by Viglietta V in 2004 and Hori S in 2003. Among the top 10 cited references, 5 references [26–30] focused on the neuroprotective role of Treg cells in neurological diseases, including stroke, MS and PD. 5 reference [26,31–34] highlighted the important role of cytokines, including Foxp3, IL-10, IL-2 and TGF-β, in the generation, development and function of Treg cells, suggesting that cytokines have always been the research focus in this field. Reference burst detection can help find the most influential cited references, and discover research frontiers and trends. 7 references with the strongest citation bursts were obtained (Fig. 7 b). Reference written by Liesz A in 2009, had the highest burst and highest number of citations, indicating that the research discussed in this article is authoritative and has been a hotspot in this field. Judging from the past 6 years, reference published by Liddelow SA in 2017 [35], has become the latest research frontier so far and may continue in the next decade. This reference titled “Neurotoxic reactive astrocytes are induced by activated microglia”, suggested that inflammatory cells contribute to the death of neurons in Alzheimer’s disease, PD, amyotrophic lateral sclerosis and MS, and provided opportunities for the development of cell-based immunotherapies for these diseases. Table 6 Top 10 references with the most citations. Rank Title First author Journal Citations 1 Regulatory T cells are key cerebroprotective immunomodulators in acute experimental stroke Liesz A (2009) Nature Medicine 250 2 Loss of functional suppression by CD4(+)CD25(+) regulatory T cells in patients with multiple sclerosis Viglietta V (2004) Journal of Experimental Medicine 199 3 Control of regulatory T cell development by the transcription factor Foxp3 Hori S (2003) Science 174 4 Foxp3 programs the development and function of CD4(+)CD25(+) regulatory T cells Fontenot JD (2003) Nature Immunology 155 5 Regulatory T cells and immune tolerance Sakaguchi S (2008) Cell 143 6 Neuroprotective activities of CD4 + CD25 + regulatory T cells in an animal model of Parkinson’s disease Reynolds AD (2007) Journal of Leukocyte Biology 138 7 Reciprocal developmental pathways for the generation of pathogenic effector T(H)17 and regulatory T cells Bettelli E (2006) Nature 125 8 Immunologic self-tolerance maintained by activated T cells expressing IL-2 receptor alpha-chains (CD25). Breakdown of a single mechanism of self-tolerance causes various autoimmune diseases Sakaguchi S (1995) Journal of Immunology 120 9 Regulatory T Cells Attenuate Th17 Cell-Mediated Nigrostriatal Dopaminergic Neurodegeneration in a Model of Parkinson’s Disease Reynolds AD (2010) Journal of Immunology 111 10 The immunology of stroke: from mechanisms to translation Iadecola C (2011) Nature Medicine 103 4. Discussion Annual documents on Treg cells in neurological diseases showed an overall upward trend, suggesting that this research field remains an active hotspot. Among 85 countries/regions publishing documents on this topic, the United States was the largest contributor, with double the number of documents and citations compared to China and far ahead of other countries/regions. Additionally, among the top 10 most productive organizations, seven were based in the United States, and among the top 15 most prolific authors, six were also from the United States, underscoring its substantial contributions to this research field. However, China has emerged as a potential contributor in this field, with its annual output overtaking other countries/regions and ranking first in 2022. Harvard Medical School was identified as the most important organization and a major driver of research on the role of Treg cells in neurological diseases. Nearly 25% of relevant research results were published in the top 11 journals, demonstrating their high quality and authoritative role as communication platforms for research related to Treg cells in neurological diseases. Notably, Frontier in Immunology was the most popular journal, playing an active role in promoting the development of Treg cells in neurological diseases. Gendelman HE, currently affiliated with University of Nebraska Medical Center, has published the most documents on Treg cells in neurological diseases. These documents primarily focused on neuroimmunity, neuromodulatory, immunomodulation and neuroprotection. Among these documents, the document “Regulatory T cells attenuate Th17 cell-mediated nigrostriatal dopaminergic neurodegeneration in a model of Parkinson’s disease” has achieved the most citations. This study highlighted the potential of Treg cells in regulating neurodestructive immunity and laid the foundation for immunization strategies of PD [29]. However, Gendelman HE has collaborated less frequently with researchers from other organizations, possibly limiting academic exchanges between organizations and countries/regions and thereby impeding the development of research in this field. Therefore, we strongly recommend that researchers from different organizations and countries/regions engage in broader collaboration and communication to jointly advance the development of Treg cells in neurological diseases. Such collaborations can lead to more comprehensive research and better knowledge sharing. Keywords are powerful tools for understanding the theme and research focus of scientific documents, and they can help identify hotspots and trends of Treg cells in neurological diseases. The most cited documents often signify important research directions and breakthroughs in the field. Co-cited references reflect the historical development and roots of the field, while references with citation bursts reveal the emerging hotspots within it. By combining keyword and citation analyses, we have identified the following aspects as current research hotspots and trends of Treg cells in neurological diseases: Given their beneficial and protective properties, Treg cells are considered excellent candidates for immunomodulation. Treg cell-based therapeutic strategies have been actively developing in transplantation and autoimmune diseases [36]. The absence of Treg cells in the lymphoid aggregates of MS patients’ brain indicates that the reduction of Treg cells may play a role in the progression of the disease [37]. Thus, therapies based on Treg cells have the potential to ameliorate MS. A phase I clinical trial evaluating the adoptive transfer of Treg cells into patients with relapsing-remitting MS found it to be safe and well-tolerated, without adverse events [38]. Nonetheless, additional research is necessary to assess the efficacy and safety of Treg cell-based therapeutic strategies for patients with MS, given the limited knowledge about how Treg cells influence immune homeostasis and inflammation resolution. PD is a neurodegenerative disorder characterized by neuroinflammation that may be caused by an imbalance between Treg cells and Th17 cells. Treg cells have been shown to attenuate Th17 cell-mediated death of nigrostriatal dopaminergic neurons [39]. An in vitro study revealed that human adipose tissue-derived mesenchymal stem cells could inhibit the differentiation of CD4 + T cells isolated from patients with PD into Th17 cells. This inhibitory effect was mainly mediated by an increase in Treg cells and secretion of IL-10, indicating that Treg cells play an anti-inflammatory and neuroprotection role in PD [40]. Immunomodulation through Treg cell expansion was found to be an effective treatment for PD mice in a recent study, providing evidence that immunotherapy may offer a disease-modifying option for patients with PD [9]. Although the precise mechanism by which Treg cells facilitate post-stroke recovery remains unclear, studies have indicated that Treg cell-derived osteopontin contributes to a tissue-reparative microglial response, resulting in improved oligodendrocyte regeneration and remyelination during the chronic stages of stroke. As such, an increase in Treg cells could potentially improve long-term stroke recovery [36,41]. Recently, engineered Treg cells have been used for adoptive immunotherapy. Firstly, human Treg cells are isolated from human peripheral blood, umbilical cord blood or thymus. These Treg cells are then cultured in vitro to generate polyclonal Treg cells or antigen-specific Treg cells. Finally, qualified Treg cells are infused into patients to treat related diseases [42]. Therefore, immunomodulatory strategies based on Treg cells are novel and promising therapies for neurological diseases, and deserve continued research by scholars. Substantial evidence has indicated that the gut-brain axis likely plays a crucial role in neurological diseases, with an altered gut microbiota potentially having significant implications on immune responses in both the gut and distal effector immune sites such as the central nervous system [43]. A study involving experimental autoimmune encephalomyelitis mice found that the gut microbiota greatly influenced the balance between pro- and anti-inflammatory immune responses. This discovery suggested that modulating gut microbiota could provide new targets for treating extraintestinal inflammatory diseases like MS [21]. Specific metabolites of gut microbiota, such as the tryptophan metabolite FICZ [6-formylindolo (3‐2b) carbazole], are associated with the production of pro-inflammatory cytokines and the generation of Th17 cells. Conversely, commensal bacteria and their metabolites, including Lactobacilli and Bacillus -derived poly-gamma-glutamic acid (gamma-PGA), can stimulate Treg cell generation to promote immune suppression. Therefore, the immunomodulatory effects of gut microbiota may be mediated primarily via the Th17/Treg axis [44]. Exposure to MS microbiota or MS-associated Acinetobacter calcoaceticus extract was shown to alter lymphocyte differentiation in healthy individuals, resulting in an increase in Th1 cells and a decrease in CD25 + Foxp3 + Treg cells, while exposure to Parabacteroides distasonis extract increased Treg cell differentiation [45]. Patients with MS display a reduction in commensal microbiota levels compared to healthy individuals, and therapies targeting the microbiota have demonstrated to increase the microbiota and improve MS by decreasing Th1- and Th17-cell levels and increasing Treg cell levels [46]. Patients with neurological diseases often exhibit gut microbial dysbiosis and altered microbial metabolites, highlighting the potential of microbial components or commensal bacteria as immunomodulatory agents to correct Th17/Treg imbalances and then treat neurological diseases [47]. Therefore, developing therapeutic interventions targeting the gut microbiome could represent a promising strategy for managing neurological diseases. Cytokines are under active investigation as immune modulators to boost the numbers and functions of Treg cells in neurological diseases. The development and function of CD4 + CD25 + Treg cells are regulated by Foxp3, while peripheral CD4 + CD25 − T cells can acquire suppressor function through ectopic Foxp3 expression. This discovery opens up a new way for cell-based therapies for autoimmunity [32]. IL-2 is an essential factor for the development, survival, and function of Foxp3 + natural Treg cells, playing a critical role in maintaining Treg cells homeostasis [20,33]. Studies have revealed that low-dose IL-2 therapy can selectively promote the persistence and survival of Treg cells while limiting effects on other T cell subsets. The therapeutic efficacy of this approach has been demonstrated in both animal models and clinical trials, highlighting its potential as a promising treatment option [48,49]. The aberrant TGF-β signaling observed in individuals with MS is strongly associated with Treg cell dysfunction [50]. Consequently, targeting and modulating TGF-β signaling may hold promise for addressing this defect and potentially alleviating the symptoms of MS. IL-6 plays a pivotal role in regulating the balance between Th17 and Treg cells. Specifically, IL-6 supports the differentiation of Th17 cells from naive T cells together with TGF-β, and inhibits TGF-β-induced Treg differentiation [51]. Tocilizumab, an anti-IL-6 receptor monoclonal antibody, has been approved for treating inflammatory diseases [18]. Therefore, the utilization of cytokines as immune modulators to regulate the differentiation and function of Treg cells represents a significant therapeutic approach in the treatment of neurological diseases. Furthermore, relevant immunomodulatory agents have transformed recent clinical practice to prevent and reverse pathology of neurological diseases. However, a delivery system that can cross the blood-brain barrier to carry immunomodulatory agents is still the direction of scholars’ unremitting exploration. Limitations This study is the first bibliometric analysis to systematically analyze documents related to Treg cells in neurological diseases. Nevertheless, there are still some deficiencies here. Firstly, only English language articles and reviews published in the Web of Science Core Collection were collected, which may lead to language and publication bias. Furthermore, as bibliometric analysis is closely linked to timeliness, it is essential to continuously update the results and trends of research on Treg cells in neurological diseases to keep pace with ongoing scientific exploration. This will enable a more comprehensive understanding of the topic as well as provide more precise predictions of future trends. However, given the large enough number of documents in this analysis, we believe that this study provides an instructive perspective for the research of Treg cells in neurological diseases and guides future research in this field. 5. Conclusions Through VOSviewer, CiteSpace and Tableau Public software, we have carried out a bibliometric analysis on Treg cells in neurological diseases. The study of Treg cells in neurological diseases continues to be a hot topic. The United States was the largest contributor among 85 countries/regions, and China was the most potential country. More than half of the top 10 most prolific organizations were located in the United States, and Harvard Medical School was the most important organization in this field. Near half of authors who make major contributions belonged to the United States organizations when publishing documents. Frontiers in Immunology was the most popular journal in this research area. Immunomodulation, gut microbiota, and cytokines represent the current research hotspots and frontiers in this field. Treg cell-based immunomodulatory approaches have shown immense potential in the treatment of neurological diseases. Modifying gut microbiota or regulating cytokines to boost the numbers and functions of Treg cells represents a promising therapeutic strategy for neurological diseases. Declarations Data availability Te data sets generated and/or analyzed during the current study are available upon request from the corresponding author. Author contributions Q.G.: Conceptualization, Data curation, writing original draft preparation, writing review and editing. X.L.: Conceptualization, Validation, writing review and editing. Y.L.: Validation, Project administration, Funding acquisition. J.L.: Methodology. M.P.: Formal analysis. J.W.: Visualization. F.Y.: Software. Y.Z.: Supervision, Project administration, Funding acquisition. All authors have read and agreed to the published version of the manuscript. Competing interests The authors declare no competing interests. References Chrousos, G. P. & Gold, P. W. The concepts of stress and stress system disorders. Overview of physical and behavioral homeostasis. Jama 267 , 1244-1252 (1992). Gunata, M., Parlakpinar, H. & Acet, H. A. Melatonin: A review of its potential functions and effects on neurological diseases. Rev . Neurol . (Paris) 176 , 148-165. https://doi.org/10.1016/j.neurol.2019.07.025 (2020). Xu, W. H. Editorial for focused issue "Neurological Diseases". Ann . Trans . l Med . 8 , 1. https://doi.org/10.21037/atm.2019.12.77 (2020). Schwab, A. D. et al. Immunotherapy for Parkinson's disease. Neurobiol . Dis . 137 , 104760. https://doi.org/10.1016/j.nbd.2020.104760 (2020). Ferreira, L. M. R., Muller, Y. D., Bluestone, J. A. & Tang, Q. Next-generation regulatory T cell therapy. Nat . Rev . Drug Discov . 18 , 749-769. https://doi.org/10.1038/s41573-019-0041-4 (2019). Liston, A., Dooley, J. & Yshii, L. Brain-resident regulatory T cells and their role in health and disease. Immunol . Lett . 248 , 26-30. https://doi.org/10.1016/j.imlet.2022.06.005 (2022). Kleinewietfeld, M. & Hafler, D. A. Regulatory T cells in autoimmune neuroinflammation. Immunol . Rev . 259 , 231-244. https://doi.org/10.1111/imr.12169 (2014). McIntyre, L. L. et al. Regulatory T cells promote remyelination in the murine experimental autoimmune encephalomyelitis model of multiple sclerosis following human neural stem cell transplant. Neurobiol . Dis . 140 , 104868. https://doi.org/10.1016/j.nbd.2020.104868 (2020). Badr, M. et al. Expansion of regulatory T cells by CD28 superagonistic antibodies attenuates neurodegeneration in A53T-α-synuclein Parkinson's disease mice. J . Neuroinflammation 19 , 319. https://doi.org/10.1186/s12974-022-02685-7 (2022). Chen, S. et al. Publication trends and hot spots in postoperative cognitive dysfunction research: A 20-year bibliometric analysis. J . Clin . Anesth . 67 , 110012. https://doi.org/10.1016/j.jclinane.2020.110012 (2020). van Eck, N. J. & Waltman, L. Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 84 , 523-538. https://doi.org/10.1007/s11192-009-0146-3 (2010). Synnestvedt, M. B., Chen, C. & Holmes, J. H. CiteSpace II: visualization and knowledge discovery in bibliographic databases. AMIA Annu . Symp . Proc . 2005 , 724-728 (2005). Teles, R. H. G. et al. Advances in Breast Cancer Management and Extracellular Vesicle Research, a Bibliometric Analysis. Curr . Oncol . 28 , 4504-4520. https://doi.org/10.3390/curroncol28060382 (2021). Wu, H. et al. Mapping Knowledge Structure and Themes Trends of Osteoporosis in Rheumatoid Arthritis: A Bibliometric Analysis. Front . Med (Lausanne) . 8 , 787228. https://doi.org/10.3389/fmed.2021.787228 (2021). Chen, C. M. CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature. Journal of the American Society for Information Science and Technology 57 , 359-377. https://doi.org/10.1002/asi.20317 (2006). Zheng, F., Wang, L., Zeng, Z. & Wu, S. International Technologies on Prevention and Treatment of Neurological and Psychiatric Diseases: Bibliometric Analysis of Patents. JMIR Ment . Health 9 , e25238. https://doi.org/10.2196/25238 (2022). Wang, Y., Zhang, J., Zhang, Y. & Yao, J. Bibliometric analysis of global research profile on ketogenic diet therapies in neurological diseases: Beneficial diet therapies deserve more attention. Front . Endocrinol (Lausanne) . 13 , 1066785. https://doi.org/10.3389/fendo.2022.1066785 (2022). Scheller, J., Chalaris, A., Schmidt-Arras, D. & Rose-John, S. The pro- and anti-inflammatory properties of the cytokine interleukin-6. Biochim . Biophys . Acta . 1813 , 878-888. https://doi.org/10.1016/j.bbamcr.2011.01.034 (2011). Shi, L. Z. et al. HIF1alpha-dependent glycolytic pathway orchestrates a metabolic checkpoint for the differentiation of TH17 and Treg cells. J . Exp . Med . 208 , 1367-1376. https://doi.org/10.1084/jem.20110278 (2011). Setoguchi, R., Hori, S., Takahashi, T. & Sakaguchi, S. Homeostatic maintenance of natural Foxp3(+) CD25(+) CD4(+) regulatory T cells by interleukin (IL)-2 and induction of autoimmune disease by IL-2 neutralization. J . Exp . Med . 201 , 723-735. https://doi.org/10.1084/jem.20041982 (2005). Lee, Y. K., Menezes, J. S., Umesaki, Y. & Mazmanian, S. K. Proinflammatory T-cell responses to gut microbiota promote experimental autoimmune encephalomyelitis. Proc . Natl . Acad . Sci . USA 108 Suppl 1 , 4615-4622. https://doi.org/10.1073/pnas.1000082107 (2011). Wang, M. et al. Role of tumor microenvironment in tumorigenesis. J . Cancer 8 , 761-773. https://doi.org/10.7150/jca.17648 (2017). Lakhan, S. E., Kirchgessner, A. & Hofer, M. Inflammatory mechanisms in ischemic stroke: therapeutic approaches. J . Transl . Med . 7 , 97. https://doi.org/10.1186/1479-5876-7-97 (2009). Karussis, D. et al. Safety and immunological effects of mesenchymal stem cell transplantation in patients with multiple sclerosis and amyotrophic lateral sclerosis. Arch . Neurol . 67 , 1187-1194. https://doi.org/10.1001/archneurol.2010.248 (2010). Haroon, E., Raison, C. L. & Miller, A. H. Psychoneuroimmunology meets neuropsychopharmacology: translational implications of the impact of inflammation on behavior. Neuropsychopharmacology 37 , 137-162. https://doi.org/10.1038/npp.2011.205 (2012). Liesz, A. et al. Regulatory T cells are key cerebroprotective immunomodulators in acute experimental stroke. Nat . Med . 15 , 192-199. https://doi.org/10.1038/nm.1927 (2009). Viglietta, V., Baecher-Allan, C., Weiner, H. L. & Hafler, D. A. Loss of functional suppression by CD4+CD25+ regulatory T cells in patients with multiple sclerosis. J . Exp . Med . 199 , 971-979. https://doi.org/10.1084/jem.20031579 (2004). Reynolds, A. D., Banerjee, R., Liu, J., Gendelman, H. E. & Mosley, R. L. Neuroprotective activities of CD4+CD25+ regulatory T cells in an animal model of Parkinson's disease. J . Leukoc . Biol . 82 , 1083-1094. https://doi.org/10.1189/jlb.0507296 (2007). Reynolds, A. D. et al. Regulatory T cells attenuate Th17 cell-mediated nigrostriatal dopaminergic neurodegeneration in a model of Parkinson's disease. J . Immunol . 184 , 2261-2271. https://doi.org/10.4049/jimmunol.0901852 (2010). Iadecola, C. & Anrather, J. The immunology of stroke: from mechanisms to translation. Nat . Med . 17 , 796-808. https://doi.org/10.1038/nm.2399 (2011). Hori, S., Nomura, T. & Sakaguchi, S. Control of regulatory T cell development by the transcription factor Foxp3. Science 299 , 1057-1061. https://doi.org/10.1126/science.1079490 (2003). Fontenot, J. D., Gavin, M. A. & Rudensky, A. Y. Foxp3 programs the development and function of CD4+CD25+ regulatory T cells. Nat . Immunol . 4 , 330-336. https://doi.org/10.1038/ni904 (2003). Sakaguchi, S., Yamaguchi, T., Nomura, T. & Ono, M. Regulatory T cells and immune tolerance. Cell 133 , 775-787. https://doi.org/10.1016/j.cell.2008.05.009 (2008). Bettelli, E. et al. Reciprocal developmental pathways for the generation of pathogenic effector T(H)17 and regulatory T cells. Nature 441 , 235-238. https://doi.org/10.1038/nature04753 (2006). Liddelow, S. A. et al. Neurotoxic reactive astrocytes are induced by activated microglia. Nature 541 , 481-487. https://doi.org/10.1038/nature21029 (2017). Wang, M. et al. Regulatory T lymphocytes as a therapy for ischemic stroke. Semin . Immunopathol . https://doi.org/10.1007/s00281-022-00975-z (2022). Bell, L., Lenhart, A., Rosenwald, A., Monoranu, C. M. & Berberich-Siebelt, F. Lymphoid Aggregates in the CNS of Progressive Multiple Sclerosis Patients Lack Regulatory T Cells. Front . Immunol . 10 , 3090. https://doi.org/10.3389/fimmu.2019.03090 (2019). Chwojnicki, K. et al. Administration of CD4(+)CD25(high)CD127(-)FoxP3(+) Regulatory T Cells for Relapsing-Remitting Multiple Sclerosis: A Phase 1 Study. BioDrugs 35 , 47-60. https://doi.org/10.1007/s40259-020-00462-7 (2021). Sommer, A. et al. Th17 Lymphocytes Induce Neuronal Cell Death in a Human iPSC-Based Model of Parkinson's Disease. Cell Stem Cell 23 , 123-131.e126. https://doi.org/10.1016/j.stem.2018.06.015 (2018). Bi, Y. et al. Human Adipose Tissue-Derived Mesenchymal Stem Cells in Parkinson's Disease: Inhibition of T Helper 17 Cell Differentiation and Regulation of Immune Balance Towards a Regulatory T Cell Phenotype. Clin . Interv . Aging 15 , 1383-1391. https://doi.org/10.2147/cia.S259762 (2020). Shi, L. et al. Treg cell-derived osteopontin promotes microglia-mediated white matter repair after ischemic stroke. Immunity 54 , 1527-1542.e1528. https://doi.org/10.1016/j.immuni.2021.04.022 (2021). Qu, G. et al. Current status and perspectives of regulatory T cell-based therapy. J . Genet . Genomics 49 , 599-611. https://doi.org/10.1016/j.jgg.2022.05.005 (2022). Parodi, B. & Kerlero de Rosbo, N. The Gut-Brain Axis in Multiple Sclerosis. Is Its Dysfunction a Pathological Trigger or a Consequence of the Disease? Front . Immunol . 12 , 718220. https://doi.org/10.3389/fimmu.2021.718220 (2021). Haase, S., Haghikia, A., Wilck, N., Müller, D. N. & Linker, R. A. Impacts of microbiome metabolites on immune regulation and autoimmunity. Immunology 154 , 230-238. https://doi.org/10.1111/imm.12933 (2018). Cekanaviciute, E. et al. Gut bacteria from multiple sclerosis patients modulate human T cells and exacerbate symptoms in mouse models. Proc . Natl . Acad . Sci . USA 114 , 10713-10718. https://doi.org/10.1073/pnas.1711235114 (2017). Mangalam, A. et al. Human Gut-Derived Commensal Bacteria Suppress CNS Inflammatory and Demyelinating Disease. Cell Rep . 20 , 1269-1277. https://doi.org/10.1016/j.celrep.2017.07.031 (2017). Chen, P. & Tang, X. Gut Microbiota as Regulators of Th17/Treg Balance in Patients With Myasthenia Gravis. Front . Immunol . 12 , 803101. https://doi.org/10.3389/fimmu.2021.803101 (2021). Li, J., Zhang, Z., Du, S. & Guo, Q. Interleukin 2 Ameliorates Autoimmune Neuroinflammation by Modulating the Balance of T Helper 17 Cells and Regulatory T Cells in Mouse. Ann . Clin . Lab . Sci . 51 , 529-534 (2021). Giovannelli, I. et al. Amyotrophic lateral sclerosis transcriptomics reveals immunological effects of low-dose interleukin-2. Brain Commun . 3 , fcab141. https://doi.org/10.1093/braincomms/fcab141 (2021). Lee, P. W., Severin, M. E. & Lovett-Racke, A. E. TGF-β regulation of encephalitogenic and regulatory T cells in multiple sclerosis. Eur . J . Immunol . 47 , 446-453. https://doi.org/10.1002/eji.201646716 (2017). Kimura, A. & Kishimoto, T. IL-6: regulator of Treg/Th17 balance. Eur . J . Immunol . 40 , 1830-1835. https://doi.org/10.1002/eji.201040391 (2010). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3234444","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":224382520,"identity":"357290a6-b461-4df8-87b0-d7316f386173","order_by":0,"name":"Qian Gao","email":"","orcid":"","institution":"Henan University of Chinese Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Qian","middleName":"","lastName":"Gao","suffix":""},{"id":224382521,"identity":"9eb5963a-c394-4be7-987c-74796c7adbc0","order_by":1,"name":"Xinmin Li","email":"","orcid":"","institution":"Henan University of Chinese 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10:59:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3234444/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3234444/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":41379933,"identity":"880b413b-d5d3-4964-b0f2-0ed7d15b3bfb","added_by":"auto","created_at":"2023-08-10 15:16:36","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":962374,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of the document-screening process and research framework.\u003c/p\u003e","description":"","filename":"Figure1.Flowchartofthedocumentscreeningprocessandresearchframework.png","url":"https://assets-eu.researchsquare.com/files/rs-3234444/v1/f7e5263f064ad9b5c79c2e88.png"},{"id":41378121,"identity":"d40a50d9-318e-48c1-85da-0a865e3cdf2f","added_by":"auto","created_at":"2023-08-10 15:00:36","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":165540,"visible":true,"origin":"","legend":"\u003cp\u003eTrends of annual documents related to Treg cells in neurological diseases.\u003c/p\u003e","description":"","filename":"Figure2.TrendsofannualdocumentsrelatedtoTregcellsinneurologicaldiseases.png","url":"https://assets-eu.researchsquare.com/files/rs-3234444/v1/ff8779757426cbc804b78a70.png"},{"id":41378763,"identity":"5d86383e-8e85-4f05-b129-29fede6892ee","added_by":"auto","created_at":"2023-08-10 15:08:36","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1669844,"visible":true,"origin":"","legend":"\u003cp\u003eCo-authorship analysis of countries/regions. (a) Geographical distribution of documents. The darker the color, the more documents in this country/region; (b) Trends of annual documents of the top 10 countries/regions; (c) Visualization map of countries/regions collaboration analysis. Each node represents a country/region, and the node size is positively correlated with the number of documents. The connection between nodes represents collaboration. Countries/regions with citation bursts are presented with red nodes, and nodes with purple rings have high centrality values.\u003c/p\u003e","description":"","filename":"Figure3.Coauthorshipanalysisofcountries.png","url":"https://assets-eu.researchsquare.com/files/rs-3234444/v1/238282f4ec45a24ce4a9db82.png"},{"id":41378764,"identity":"f060bc64-ed07-4a8d-8a60-881dfec064d3","added_by":"auto","created_at":"2023-08-10 15:08:36","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":830920,"visible":true,"origin":"","legend":"\u003cp\u003eCo-authorship analysis of organizations. (a) Visualization map of organizations collaboration analysis. Each node represents an organization, and the node size is positively correlated with the number of documents. The connection between nodes represents collaboration, the distance and thickness of the connection represent the relative strength of the relationship; (b) Visualization map of the top 10 organizations collaboration. The color means the average published year; (c) Top 24 organizations with the strongest citation bursts. Minimum duration: 2.\u003c/p\u003e","description":"","filename":"Figure4.Coauthorshipanalysisoforganizations.png","url":"https://assets-eu.researchsquare.com/files/rs-3234444/v1/fb1783d62c2f8d03599733fe.png"},{"id":41378125,"identity":"ef1acecf-4efa-4b0f-8b29-4c94a9a37f63","added_by":"auto","created_at":"2023-08-10 15:00:36","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":850583,"visible":true,"origin":"","legend":"\u003cp\u003eCo-authorship analysis authors. (a) Visualization map of authors collaboration analysis. Each node represents an author, and the node size is positively correlated with the number of documents. The connection between nodes represents collaboration, the distance and thickness of the connection represent the relative strength of the relationship. The color means the average published year; (b) Cooperative network of Gendelman HE; (c) Top 13 authors with the strongest citation bursts. Minimum duration: 2.\u003c/p\u003e","description":"","filename":"Figure5.Coauthorshipanalysisauthors.png","url":"https://assets-eu.researchsquare.com/files/rs-3234444/v1/deb76c00979cff29d7418e16.png"},{"id":41378127,"identity":"a51e1091-0f08-4123-b3df-12baa702bae9","added_by":"auto","created_at":"2023-08-10 15:00:36","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1407719,"visible":true,"origin":"","legend":"\u003cp\u003eCo-occurrence analysis of keywords. (a) Visualization map of author keywords analysis. Each node represents an author keyword, and the node size is positively correlated with the number of documents containing the author keyword. The connection between nodes represents co-occurrence. The color means the average published year; (b) Timeline view of keywords clustering analysis. The different colored horizontal lines on the right represent the clusters formed by the keywords, nodes on the horizontal lines represent keywords, and the position of nodes on the horizontal lines represents the year in which document containing the keywords first appeared; (c) Top 30 keywords with the strongest citation bursts. Minimum duration: 6.\u003c/p\u003e","description":"","filename":"Figure6.Cooccurrenceanalysisofkeywords.png","url":"https://assets-eu.researchsquare.com/files/rs-3234444/v1/9ea96b814690a6df6e79e45c.png"},{"id":41378766,"identity":"0c745426-a572-465d-ac51-01eb2a040b91","added_by":"auto","created_at":"2023-08-10 15:08:36","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1196267,"visible":true,"origin":"","legend":"\u003cp\u003eCo-citation analysis of cited references. (A) The density map of cited references based on citations. The opacity of yellow is positively related to citations; (B) Top 7 references with the strongest citation bursts. Minimum duration: 6.\u003c/p\u003e","description":"","filename":"Figure7.Cocitationanalysisofcitedreferences.png","url":"https://assets-eu.researchsquare.com/files/rs-3234444/v1/0247fc4691ebf4192fb2bcac.png"},{"id":44297184,"identity":"0c823efa-9778-4d50-9aee-daae8d46ab10","added_by":"auto","created_at":"2023-10-09 13:37:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3995231,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3234444/v1/c09a6ce1-85e3-428d-a5ed-7f32c1892829.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Bibliometric analysis of global research trends on regulatory T cells in neurological diseases","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe nervous system serves as the body\u0026rsquo;s command center, and interruptions or impairments of its function can induce neurological diseases, including stroke, spinal cord injury, traumatic brain injury, multiple sclerosis (MS), Alzheimer\u0026rsquo;s disease (AD), Parkinson\u0026rsquo;s disease (PD), etc [1]. Unfortunately, neurological diseases remain highly prevalent, with a scarcity of effective therapeutic strategies [2,3]. As a result, these disorders pose a considerable socioeconomic burden to society, underscoring the urgent need for continued research and development of effective therapies in the field of neurology. While inflammation may not be the direct cause of neurological diseases, accumulating evidence suggests its involvement in their pathogenesis once these diseases have manifested. Recent research indicates that disordered innate and adaptive immune responses play a crucial role in the pathological processes of neurological diseases, potentially resulting in autoimmunity, tissue and cellular damage, and subsequent neurological degeneration [4]. By addressing the underlying pathological processes that contribute to neurological disease, it is possible to improve the neurological symptoms for individuals affected by these conditions. Therefore, developing effective therapeutic strategies to manage immune-mediated inflammation is crucial in preventing or delaying the onset and progression of neurological diseases.\u003c/p\u003e \u003cp\u003eRegulatory T (Treg) cells are a minor subpopulation of CD4\u003csup\u003e+\u003c/sup\u003e T cells defined by constitutive expression of IL-2 receptor alpha (CD25) and forkhead box p3 (Foxp3) [5]. Studies have indicated that Treg cells play a beneficial role in delaying the onset and progression of neurological diseases, while dysfunction in Treg cells may lead to the development of autoimmune disease and the progression of neuroinflammation. [6]. By suppressing adaptive immune responses and regulating innate immune responses, Treg cells are capable of curtailing excessive immune responses and preserving immune homeostasis [7]. The findings of a study on experimental autoimmune encephalomyelitis indicated that Treg cells play a facilitative role in the remyelination process and exert suppressive effects on neuroinflammatory responses during the chronic stages of MS [8]. The expansion of Treg cells has been shown to effectively suppress immune responses and mitigate dopaminergic neurodegeneration in A53T-α-synuclein PD mice [9]. In short, promoting the production and activity of Treg cells represents promising therapeutic strategies for managing immune-mediated inflammation in neurological diseases. Therefore, it is extremely important to understand the current research status and development trends concerning Treg cells in neurological diseases. Gaining such knowledge can help to further explore immunological mechanisms and therapeutic strategies of neurological diseases, and address relevant clinical problems.\u003c/p\u003e \u003cp\u003eBibliometric analysis can analyze and visualize scientific outputs, research hotspots and trending topics of a certain field in the public literature databases [10]. Bibliometric tools, including VOSviewer and CiteSpace, are commonly applied to visualize results of document analysis, which have been widely used in medical fields [11\u0026ndash;14]. VOSviewer, a free Java-based software, can be used to analyze a large number of documents data in an easy-to-interpret way and display it in the form of a map [11]. By using CiteSpace, a Java-based software, research results in a certain field can be visualized to help researchers and experts understand the knowledge domain, research frontier and development trend [15]. Although bibliometric studies on neurological diseases have been conducted, there has yet to be a bibliometric analysis of Treg cells in neurological diseases [16,17]. This study aimed to bridge this knowledge gap by conducting a bibliometric analysis of documents on Treg cells in neurological diseases. Specifically, this analysis identified major contributors and current research status, and evaluated future development prospects and research trends in this field.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Data sources and search strategy\u003c/h2\u003e \u003cp\u003eAll data was downloaded from the Web of Science Core Collection online database, and the search strategy was as follows: TS=(\u0026ldquo;regulatory T cell*\u0026rdquo; OR \u0026ldquo;regulatory T-cell*\u0026rdquo; OR \u0026ldquo;Treg*\u0026rdquo; OR \u0026ldquo;T-reg*\u0026rdquo;) AND TS=(\u0026ldquo;neuro*\u0026rdquo;) [17]. Subsequently, we limited the document types to articles and review articles, and selected documents written in English. Finally, relevant data was exported in plain text file with full records and cited references.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Bibliometric analysis\u003c/h2\u003e \u003cp\u003eWe analyzed relevant data in the following aspects: the annual number of documents, countries/regions, organizations, authors, journals, keywords, and references. Online platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.bioinformatics.com.cn\u003c/span\u003e\u003cspan address=\"http://www.bioinformatics.com.cn\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was used to plot the annual document output. Software Tableau Public was applied to draw the geographical distribution of documents. VOSviewer v.1.6.1 and CiteSpace v.6.1.R6 were applied to perform the bibliometric analysis and network visualization, including co-authorship analysis of countries/regions, organizations and authors, co-occurrence analysis of keywords, citation analysis of journals and documents, and co-citation analysis of references.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e3.1 The trend of document outputs\u003c/h2\u003e \u003cp\u003eA total of 2739 documents, including 1737 articles and 1002 review articles, were collected from the Web of Science Core Collection on August 02, 2023. The research selection process and the reasons for excluding documents are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the research trend can be divided into three stages. During the first stage, spanning from 1991 to 2003 and comprising 20 documents, the output of published research on Treg cells in neurological diseases gradually increased from 1 to 6. This suggests that the field was still in a nascent period, with relatively few studies conducted on the topic at the time. The second stage was from 2004 to 2019, during which the annual output climbed rapidly with a slight fluctuation in 2011. Starting from 2020, the third stage has been a volatile but prolific period in which the annual output of research on Treg cells in neurological diseases has consistently exceeded 210 documents, despite fluctuations. Only 7 months of documents were counted in 2023, but the overall trend in published research was stable. It suggested that the role of Treg cells in neurological diseases has attracted extensive attention worldwide since 2004, and remains a continuing hotspot.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Countries/Regions\u003c/h2\u003e \u003cp\u003eA total of 85 countries/regions dabbled in the role of Treg cells in neurological diseases (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). The United States, China and Germany were the top three countries/regions with the most documents on Treg cells in neurological diseases (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The United States not only had the largest number of documents and citations but also had the highest total link strength and centrality, making it a leading contributor to research on Treg cells in neurological diseases. Annual outputs of the top 10 countries/regions are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eb. The United States posted significantly more annual output than any other country/region until 2021, after which the United States decreased, while China overtook other countries/regions to rank first. In addition, the United States was the earliest country to focus on this research area, while China didn\u0026rsquo;t begin to bloom until 2015. The United States, Germany, France and England had the highest centrality, indicating that they had a strong bridge role in this field (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003ec). Some of documents were completed in cooperation with multiple countries/regions. The United States had collaborated with 57 countries/regions, and Germany had collaborated with 48 countries/regions.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTop10 countries/regions with the most documents.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRank\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCountry/Region\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDocuments\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCitations\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal link strength\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCentrality\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e63033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e554\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e458\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12210\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGermany\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e328\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20735\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e308\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eItaly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEngland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7240\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJapan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6519\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4743\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCanada\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAustralia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Organizations\u003c/h2\u003e \u003cp\u003eA total of 2739 documents were published by 2811 different organizations, and 61 met the threshold (minimum number of documents of an organization: 15). After excluding disjointed organizations, the remaining 59 organizations were visualized (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). The top 10 organizations with the most documents are listed in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, and 7 of the top 10 organizations were affiliated with the United States. Harvard Medical School ranked first in terms of the number of documents and citations, total link strength and centrality, indicating that it was the most prolific organization and had the most cooperation with other organizations. In addition, the University of California system, including University of California, San Francisco and University of California, Los Angeles, was another important organization in this research area. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003eb, Harvard Medical School, University of Pittsburgh and Fudan University (nodes with yellow color) were the most recent organizations to publish more documents. The top 3 organizations with the strongest citation bursts were Consejo Superior de Investigaciones Cientificas (CSIC) from 2006 to 2013, Harvard University from 2000 to 2009 and Weizmann Institute of Science from 2001 to 2005 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003ec). The citation bursts in many organizations have continued until 2023, suggesting that Treg cells in neurological diseases remain the hotspot for future research by many organizations.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTop10 organizations with the most documents.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRank\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOrganization\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCountry/Region\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDocuments\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCitations\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal link strength\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCentrality\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHarvard Medical School\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConsejo Superior de Investigaciones Cientificas (CSIC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWeizmann Institute of Science\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIsrael\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2586\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversity of California, San Francisco\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3426\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFudan University\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1482\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversity of Nebraska Medical Center\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1801\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversity of California, Los Angeles\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1459\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHarvard University\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3543\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStanford University\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2717\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversity of Pittsburgh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2394\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Authors\u003c/h2\u003e \u003cp\u003eA total of 13859 authors were involved in Treg cells in neurological diseases, and 185 met the threshold (minimum number of documents of an author: 5). The largest set of connected items consisted of 51 authors (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). The top 15 core authors in this field are listed in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, of which 6 authors came from the United States. The top 15 authors published 271 documents, accounting for 9.89% total number. Gendelman HE was top author with the largest number of documents and citations, followed by Mosley RL. Notably, both of them affiliated with University of Nebraska Medical Center in the United States, which ranked sixth in terms of the number of documents about the role of Treg cells in neurological diseases. As shown in the visualization map of authors (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003ea), Wiendl H was the center of authors\u0026rsquo; co-authorship relations and had the longest citation bursts. However, Gendelman HE was not involved in the largest connected cooperative network. A total of 8 authors had cooperation with Gendelman HE, and they were all affiliated with University of Nebraska Medical Center (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003eb). Several emerging scholars (nodes with yellow color) have also begun to dabble in this field, suggesting that Treg cells in neurological diseases are still a hotspot for future research. The top 3 authors with the strongest citation bursts were Delgado M from 2006 to 2010, Schwartz, M from 2001 to 2005 and Gendelman HE from 2009 to 2011, indicating that they were leaders of this field in a certain period (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003ec).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTop15 authors with the most documents.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRank\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAuthor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOrganization\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCountry/Region\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDocuments\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCitations\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTotal link strength\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGendelman HE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUniversity of Nebraska Medical Center\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1935\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMosley RL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUniversity of Nebraska Medical Center\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1655\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDelgado M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eConsejo Superior de Investigaciones Cientificas (CSIC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSpain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e859\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGonzalez-rey E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eConsejo Superior de Investigaciones Cientificas (CSIC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSpain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e806\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBae H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKyung Hee University\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eKorea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e529\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWiendl, H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUniversity of M\u0026uuml;nster\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGermany\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOffner H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVA Portland Health Care System, Oregon Health \u0026amp; Science University\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e687\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSchwartz M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe Weizmann Institute of Science\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIsrael\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOlson KE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUniversity of Nebraska Medical Center\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e402\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAppel SH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHouston Methodist Research Institute\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFragoso G\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUniv Nacl Autonoma Mexico\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMexico\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHu X\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUniversity of Pittsburgh School of Medicine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e749\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKipnis J\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe Weizmann Institute of Science\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIsrael\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e569\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLiesz A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHeidelberg University\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGermany\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1251\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMeuth SG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHeinrich-Heine University of D\u0026uuml;sseldorf\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGermany\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e606\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Journals\u003c/h2\u003e \u003cp\u003eA total of 859 journals published 2739 documents concerning Treg cells in neurological diseases. The top 11 journals are listed in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, they published 618 documents, accounting for approximately 22.56% of the total. The most prolific journal was \u003cem\u003eFrontiers in Immunology\u003c/em\u003e with 134 documents, followed by \u003cem\u003eJournal of Immunology\u003c/em\u003e with 90 documents, and \u003cem\u003eJournal of Neuroinflammation\u003c/em\u003e with 75 documents. Impact factors of the top 11 journals ranged from 3.3 to 15.1, of which \u003cem\u003eBrain Behavior and Immunity\u003c/em\u003e was the highest, and \u003cem\u003eJournal of Neuroimmunology\u003c/em\u003e was the lowest. Of the top 11 journals, 6 journals belonged to Q1, 4 journals belonged to Q2, and the remaining 1 journal belonged to Q3. Notably, \u003cem\u003eJournal of Experimental Medicine\u003c/em\u003e, with the most citations (4352 times), was not among the top 11 journals. The document \u0026ldquo;HIF1 alpha-dependent glycolytic pathway orchestrates a metabolic checkpoint for the differentiation of T(H)17 and T-reg cells\u0026rdquo; published in this journal in July 2011 was cited 1215 times, which ranked second in terms of the number of citations. Although the number of documents published in \u003cem\u003eJournal of Experimental Medicine\u003c/em\u003e was relatively small, the quality of documents was relatively high, which had conspicuously pushed forward the progress in this field. In short, both the number and the quality of documents need to be considered in the evaluation of prolific journals. Considering the number of documents and citations, impact factors and JCR partitions, \u003cem\u003eFrontiers in Immunology\u003c/em\u003e was the most popular journal in this research area.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTop11 journals with the most documents.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRank\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJournal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDocuments\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCitations\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal link strength\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eImpact factor (2022)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eJCR partition\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrontiers in Immunology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4351\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e603\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eQ1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJournal of Immunology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4323\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e463\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eQ2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJournal of Neuroinflammation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eQ1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJournal of Neuroimmunology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e335\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eQ3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInternational Journal of Molecular Sciences\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eQ1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePLoS One\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1925\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e199\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eQ2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrain Behavior and Immunity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1440\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e15.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eQ1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eScientific Reports\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e955\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eQ2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJournal of Neuroimmune Pharmacology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eQ1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eImmunology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1365\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eQ2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProceedings of the National Academy of Sciences of the United States of America\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3238\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eQ1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e3.6 Keywords\u003c/b\u003e \u003c/p\u003e \u003cp\u003eA total of 4868 author keywords were involved in 2558 documents and 354 met the threshold (minimum number of documents of a keyword: 5). The overlay visualization map showed the co-occurrence relations of keywords (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e6\u003c/span\u003ea), in which \u0026ldquo;multiple sclerosis\u0026rdquo;, \u0026ldquo;inflammation\u0026rdquo;, \u0026ldquo;regulatory T cells\u0026rdquo;, \u0026ldquo;neuroinflammation\u0026rdquo;, \u0026ldquo;autoimmunity\u0026rdquo;, \u0026ldquo;microglia\u0026rdquo; \u0026ldquo;cytokines\u0026rdquo;, \u0026ldquo;experimental autoimmune encephalomyelitis\u0026rdquo; \u0026ldquo;immunotherapy\u0026rdquo; and \u0026ldquo;immunomodulation\u0026rdquo; were identified as high frequency keywords. Moreover, these keywords were mostly associated with neuroprotection, neuroimmunology and immunoregulation in 2014, interconnected with myasthenia gravis, MS and neurodegeneration in 2016, related to PD, AD and spinal cord injury in 2018, and currently linked to ischemic stroke, gut microbiota and gut-brain axis. Recently, the role of gut microbiota in neurological diseases has gained significant attention, with substantial evidence linking it to neuroinflammation.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e6\u003c/span\u003eb, the timeline view of keywords clustering analysis was displayed to show the basic knowledge structure and the evolution over time of Treg cells in neurological diseases. The modularity Q was 0.4075, indicating that the network structure was consequential, and mean silhouette S was 0.6183, implying that clustering was credible. Keywords with close relationship were automatically grouped into a cluster, which was named by the keyword with the largest Log-likelihood rate. Cluster \u0026ldquo;#0 expression\u0026rdquo; \u0026ldquo;#2 multiple sclerosis\u0026rdquo; and \u0026ldquo;#4 activation\u0026rdquo; appeared earliest, and cluster \u0026ldquo;#1 parkinsons disease\u0026rdquo; appeared latest. Cluster \u0026ldquo;#0 expression\u0026rdquo;, \u0026ldquo;#1 parkinsons disease\u0026rdquo; and \u0026ldquo;#6 gut microbiota\u0026rdquo; related studies were available in 2023, which may become frontiers of Treg cells in neurological diseases in the future. while cluster \u0026ldquo;#2 multiple sclerosis\u0026rdquo;, \u0026ldquo;#3 tryptophan\u0026rdquo;, \u0026ldquo;#4 activation\u0026rdquo; and \u0026ldquo;#5 gene expression\u0026rdquo; gradually decreased or even disappeared.\u003c/p\u003e \u003cp\u003eThe top 30 keywords with the strongest citation bursts are showed in Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e6\u003c/span\u003ec, which were considered as consequential milestones for the science mapping research. \u0026ldquo;Immune privilege\u0026rdquo; and \u0026ldquo;anterior chamber\u0026rdquo; were important contents of the earliest research, suggesting that the immune privilege of the anterior chamber was an early research hotspot and had occupied a major position in this field. Keywords \u0026ldquo;antigen\u0026rdquo; had the longest, 16 years of duration burst. In addition, \u0026ldquo;experimental allergic encephalomyelitis\u0026rdquo; had the highest burst strength from 1998 to 2011, which implied that scholars can never ignore its equally important existence when conducting research in this field, followed by \u0026ldquo;myelin basic protein\u0026rdquo; and \u0026ldquo;vasoactive intestinal peptide\u0026rdquo;.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.7 Citations\u003c/h2\u003e \u003cp\u003eThe top 10 documents with the most citations are listed in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, and the range of citations was from 597 to 2058. The top 3 documents with the most citations were documents written by Scheller J in 2011 [18], Shi LZ in 2011 [19] and Setoguchi R in 2005 [20], which all introduced the role of cytokines in autoimmune neurological diseases. Document written by Lee YK in 2011 [21], pointed out gut microbiota impacts the balance between pro-and anti-inflammatory immune responses during experimental autoimmune encephalomyelitis. Document written by Wang MN in 2017 [22], focused on the role of tumor microenvironment in tumorigenesis of glioma, glioblastoma and other cancers. Documents, written by Lakhan SE in 2009 [23], Karussis D in 2010 [24] and Haroon E in 2012 [25], introduced the immunological mechanisms underlying several therapeutic approaches for neurological diseases, such as ischemic stroke, MS, amyotrophic lateral sclerosis and depression.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTop 10 documents with the most citations.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRank\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTitle\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFirst author\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eJournal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCitations\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe pro- and anti-inflammatory properties of the cytokine interleukin-6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eScheller J (2011)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBiochimica Et Biophysica Acta-Molecular Cell Research\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2058\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHIF1 alpha-dependent glycolytic pathway orchestrates a metabolic checkpoint for the differentiation of T(H)17 and T-reg cells\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eShi LZ (2011)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eJournal of Experimental Medicine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1215\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHomeostatic maintenance of natural Foxp3(+) CD25(+) CD4(+) regulatory T cells by interleukin (IL)-2 and induction of autoimmune disease by IL-2 neutralization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSetoguchi R (2005)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eJournal of Experimental Medicine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e941\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProinflammatory T-cell responses to gut microbiota promote experimental autoimmune encephalomyelitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLee YK (2011)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProceedings of the National Academy of Sciences of the United States of America\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e910\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRole of tumor microenvironment in tumorigenesis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWang MN (2017)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eJournal of Cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e798\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInflammatory mechanisms in ischemic stroke: therapeutic approaches\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLakhan SE (2009)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eJournal of Translational Medicine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e705\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSafety and Immunological Effects of Mesenchymal Stem Cell Transplantation in Patients With Multiple Sclerosis and Amyotrophic Lateral Sclerosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKarussis D (2010)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eArchives of Neurology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e679\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe Immunomodulatory and Anti-Inflammatory Role of Polyphenols\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYahfoufi N (2018)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNutrients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e676\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePsychoneuroimmunology Meets Neuropsychopharmacology: Translational Implications of the Impact of Inflammation on Behavior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHaroon E (2012)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNeuropsychopharmacology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e626\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEffects of stress on immune function: the good, the bad, and the beautiful\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDhabhar FS (2014)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eImmunologic Research\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e597\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eCo-citation analysis of cited references was performed by VOSviewer. A total of 162113 cited references were involved in 2739 documents, and 131 met the threshold (minimum number of citations of a cited reference: 40). The density visualization map of cited references based on citations is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e7\u003c/span\u003ea, and the top 10 cited references with the most citations are shown in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. Reference with the most citations was article written by Liesz A in 2009, which indicated that research in this article may be a research hotspot, followed by references written by Viglietta V in 2004 and Hori S in 2003. Among the top 10 cited references, 5 references [26\u0026ndash;30] focused on the neuroprotective role of Treg cells in neurological diseases, including stroke, MS and PD. 5 reference [26,31\u0026ndash;34] highlighted the important role of cytokines, including Foxp3, IL-10, IL-2 and TGF-β, in the generation, development and function of Treg cells, suggesting that cytokines have always been the research focus in this field.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eReference burst detection can help find the most influential cited references, and discover research frontiers and trends. 7 references with the strongest citation bursts were obtained (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e7\u003c/span\u003eb). Reference written by Liesz A in 2009, had the highest burst and highest number of citations, indicating that the research discussed in this article is authoritative and has been a hotspot in this field. Judging from the past 6 years, reference published by Liddelow SA in 2017 [35], has become the latest research frontier so far and may continue in the next decade. This reference titled \u0026ldquo;Neurotoxic reactive astrocytes are induced by activated microglia\u0026rdquo;, suggested that inflammatory cells contribute to the death of neurons in Alzheimer\u0026rsquo;s disease, PD, amyotrophic lateral sclerosis and MS, and provided opportunities for the development of cell-based immunotherapies for these diseases.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTop 10 references with the most citations.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRank\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTitle\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFirst author\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eJournal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCitations\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRegulatory T cells are key cerebroprotective immunomodulators in acute experimental stroke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLiesz A (2009)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNature Medicine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e250\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLoss of functional suppression by CD4(+)CD25(+) regulatory T cells in patients with multiple sclerosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eViglietta V (2004)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eJournal of Experimental Medicine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e199\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl of regulatory T cell development by the transcription factor Foxp3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHori S (2003)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eScience\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e174\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFoxp3 programs the development and function of CD4(+)CD25(+) regulatory T cells\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFontenot JD (2003)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNature Immunology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e155\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRegulatory T cells and immune tolerance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSakaguchi S (2008)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCell\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e143\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNeuroprotective activities of CD4\u0026thinsp;+\u0026thinsp;CD25\u0026thinsp;+\u0026thinsp;regulatory T cells in an animal model of Parkinson\u0026rsquo;s disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReynolds AD (2007)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eJournal of Leukocyte Biology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e138\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReciprocal developmental pathways for the generation of pathogenic effector T(H)17 and regulatory T cells\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBettelli E (2006)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNature\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eImmunologic self-tolerance maintained by activated T cells expressing IL-2 receptor alpha-chains (CD25). Breakdown of a single mechanism of self-tolerance causes various autoimmune diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSakaguchi S (1995)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eJournal of Immunology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRegulatory T Cells Attenuate Th17 Cell-Mediated Nigrostriatal Dopaminergic Neurodegeneration in a Model of Parkinson\u0026rsquo;s Disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReynolds AD (2010)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eJournal of Immunology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e111\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe immunology of stroke: from mechanisms to translation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIadecola C (2011)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNature Medicine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e103\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eAnnual documents on Treg cells in neurological diseases showed an overall upward trend, suggesting that this research field remains an active hotspot. Among 85 countries/regions publishing documents on this topic, the United States was the largest contributor, with double the number of documents and citations compared to China and far ahead of other countries/regions. Additionally, among the top 10 most productive organizations, seven were based in the United States, and among the top 15 most prolific authors, six were also from the United States, underscoring its substantial contributions to this research field. However, China has emerged as a potential contributor in this field, with its annual output overtaking other countries/regions and ranking first in 2022. Harvard Medical School was identified as the most important organization and a major driver of research on the role of Treg cells in neurological diseases. Nearly 25% of relevant research results were published in the top 11 journals, demonstrating their high quality and authoritative role as communication platforms for research related to Treg cells in neurological diseases. Notably, \u003cem\u003eFrontier in Immunology\u003c/em\u003e was the most popular journal, playing an active role in promoting the development of Treg cells in neurological diseases.\u003c/p\u003e \u003cp\u003eGendelman HE, currently affiliated with University of Nebraska Medical Center, has published the most documents on Treg cells in neurological diseases. These documents primarily focused on neuroimmunity, neuromodulatory, immunomodulation and neuroprotection. Among these documents, the document \u0026ldquo;Regulatory T cells attenuate Th17 cell-mediated nigrostriatal dopaminergic neurodegeneration in a model of Parkinson\u0026rsquo;s disease\u0026rdquo; has achieved the most citations. This study highlighted the potential of Treg cells in regulating neurodestructive immunity and laid the foundation for immunization strategies of PD [29]. However, Gendelman HE has collaborated less frequently with researchers from other organizations, possibly limiting academic exchanges between organizations and countries/regions and thereby impeding the development of research in this field. Therefore, we strongly recommend that researchers from different organizations and countries/regions engage in broader collaboration and communication to jointly advance the development of Treg cells in neurological diseases. Such collaborations can lead to more comprehensive research and better knowledge sharing.\u003c/p\u003e \u003cp\u003eKeywords are powerful tools for understanding the theme and research focus of scientific documents, and they can help identify hotspots and trends of Treg cells in neurological diseases. The most cited documents often signify important research directions and breakthroughs in the field. Co-cited references reflect the historical development and roots of the field, while references with citation bursts reveal the emerging hotspots within it. By combining keyword and citation analyses, we have identified the following aspects as current research hotspots and trends of Treg cells in neurological diseases:\u003c/p\u003e \u003cp\u003eGiven their beneficial and protective properties, Treg cells are considered excellent candidates for immunomodulation. Treg cell-based therapeutic strategies have been actively developing in transplantation and autoimmune diseases [36]. The absence of Treg cells in the lymphoid aggregates of MS patients\u0026rsquo; brain indicates that the reduction of Treg cells may play a role in the progression of the disease [37]. Thus, therapies based on Treg cells have the potential to ameliorate MS. A phase I clinical trial evaluating the adoptive transfer of Treg cells into patients with relapsing-remitting MS found it to be safe and well-tolerated, without adverse events [38]. Nonetheless, additional research is necessary to assess the efficacy and safety of Treg cell-based therapeutic strategies for patients with MS, given the limited knowledge about how Treg cells influence immune homeostasis and inflammation resolution. PD is a neurodegenerative disorder characterized by neuroinflammation that may be caused by an imbalance between Treg cells and Th17 cells. Treg cells have been shown to attenuate Th17 cell-mediated death of nigrostriatal dopaminergic neurons [39]. An in vitro study revealed that human adipose tissue-derived mesenchymal stem cells could inhibit the differentiation of CD4\u003csup\u003e+\u003c/sup\u003e T cells isolated from patients with PD into Th17 cells. This inhibitory effect was mainly mediated by an increase in Treg cells and secretion of IL-10, indicating that Treg cells play an anti-inflammatory and neuroprotection role in PD [40]. Immunomodulation through Treg cell expansion was found to be an effective treatment for PD mice in a recent study, providing evidence that immunotherapy may offer a disease-modifying option for patients with PD [9]. Although the precise mechanism by which Treg cells facilitate post-stroke recovery remains unclear, studies have indicated that Treg cell-derived osteopontin contributes to a tissue-reparative microglial response, resulting in improved oligodendrocyte regeneration and remyelination during the chronic stages of stroke. As such, an increase in Treg cells could potentially improve long-term stroke recovery [36,41]. Recently, engineered Treg cells have been used for adoptive immunotherapy. Firstly, human Treg cells are isolated from human peripheral blood, umbilical cord blood or thymus. These Treg cells are then cultured in vitro to generate polyclonal Treg cells or antigen-specific Treg cells. Finally, qualified Treg cells are infused into patients to treat related diseases [42]. Therefore, immunomodulatory strategies based on Treg cells are novel and promising therapies for neurological diseases, and deserve continued research by scholars.\u003c/p\u003e \u003cp\u003eSubstantial evidence has indicated that the gut-brain axis likely plays a crucial role in neurological diseases, with an altered gut microbiota potentially having significant implications on immune responses in both the gut and distal effector immune sites such as the central nervous system [43]. A study involving experimental autoimmune encephalomyelitis mice found that the gut microbiota greatly influenced the balance between pro- and anti-inflammatory immune responses. This discovery suggested that modulating gut microbiota could provide new targets for treating extraintestinal inflammatory diseases like MS [21]. Specific metabolites of gut microbiota, such as the tryptophan metabolite FICZ [6-formylindolo (3‐2b) carbazole], are associated with the production of pro-inflammatory cytokines and the generation of Th17 cells. Conversely, commensal bacteria and their metabolites, including \u003cem\u003eLactobacilli\u003c/em\u003e and \u003cem\u003eBacillus\u003c/em\u003e-derived poly-gamma-glutamic acid (gamma-PGA), can stimulate Treg cell generation to promote immune suppression. Therefore, the immunomodulatory effects of gut microbiota may be mediated primarily via the Th17/Treg axis [44]. Exposure to MS microbiota or MS-associated \u003cem\u003eAcinetobacter calcoaceticus\u003c/em\u003e extract was shown to alter lymphocyte differentiation in healthy individuals, resulting in an increase in Th1 cells and a decrease in CD25\u003csup\u003e+\u003c/sup\u003eFoxp3\u003csup\u003e+\u003c/sup\u003e Treg cells, while exposure to \u003cem\u003eParabacteroides distasonis\u003c/em\u003e extract increased Treg cell differentiation [45]. Patients with MS display a reduction in commensal microbiota levels compared to healthy individuals, and therapies targeting the microbiota have demonstrated to increase the microbiota and improve MS by decreasing Th1- and Th17-cell levels and increasing Treg cell levels [46]. Patients with neurological diseases often exhibit gut microbial dysbiosis and altered microbial metabolites, highlighting the potential of microbial components or commensal bacteria as immunomodulatory agents to correct Th17/Treg imbalances and then treat neurological diseases [47]. Therefore, developing therapeutic interventions targeting the gut microbiome could represent a promising strategy for managing neurological diseases.\u003c/p\u003e \u003cp\u003eCytokines are under active investigation as immune modulators to boost the numbers and functions of Treg cells in neurological diseases. The development and function of CD4\u003csup\u003e+\u003c/sup\u003eCD25\u003csup\u003e+\u003c/sup\u003e Treg cells are regulated by Foxp3, while peripheral CD4\u003csup\u003e+\u003c/sup\u003eCD25\u003csup\u003e\u0026minus;\u003c/sup\u003e T cells can acquire suppressor function through ectopic Foxp3 expression. This discovery opens up a new way for cell-based therapies for autoimmunity [32]. IL-2 is an essential factor for the development, survival, and function of Foxp3\u003csup\u003e+\u003c/sup\u003e natural Treg cells, playing a critical role in maintaining Treg cells homeostasis [20,33]. Studies have revealed that low-dose IL-2 therapy can selectively promote the persistence and survival of Treg cells while limiting effects on other T cell subsets. The therapeutic efficacy of this approach has been demonstrated in both animal models and clinical trials, highlighting its potential as a promising treatment option [48,49]. The aberrant TGF-β signaling observed in individuals with MS is strongly associated with Treg cell dysfunction [50]. Consequently, targeting and modulating TGF-β signaling may hold promise for addressing this defect and potentially alleviating the symptoms of MS. IL-6 plays a pivotal role in regulating the balance between Th17 and Treg cells. Specifically, IL-6 supports the differentiation of Th17 cells from naive T cells together with TGF-β, and inhibits TGF-β-induced Treg differentiation [51]. Tocilizumab, an anti-IL-6 receptor monoclonal antibody, has been approved for treating inflammatory diseases [18]. Therefore, the utilization of cytokines as immune modulators to regulate the differentiation and function of Treg cells represents a significant therapeutic approach in the treatment of neurological diseases. Furthermore, relevant immunomodulatory agents have transformed recent clinical practice to prevent and reverse pathology of neurological diseases. However, a delivery system that can cross the blood-brain barrier to carry immunomodulatory agents is still the direction of scholars\u0026rsquo; unremitting exploration.\u003c/p\u003e \u003cp\u003e \u003cb\u003eLimitations\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThis study is the first bibliometric analysis to systematically analyze documents related to Treg cells in neurological diseases. Nevertheless, there are still some deficiencies here. Firstly, only English language articles and reviews published in the Web of Science Core Collection were collected, which may lead to language and publication bias. Furthermore, as bibliometric analysis is closely linked to timeliness, it is essential to continuously update the results and trends of research on Treg cells in neurological diseases to keep pace with ongoing scientific exploration. This will enable a more comprehensive understanding of the topic as well as provide more precise predictions of future trends. However, given the large enough number of documents in this analysis, we believe that this study provides an instructive perspective for the research of Treg cells in neurological diseases and guides future research in this field.\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eThrough VOSviewer, CiteSpace and Tableau Public software, we have carried out a bibliometric analysis on Treg cells in neurological diseases. The study of Treg cells in neurological diseases continues to be a hot topic. The United States was the largest contributor among 85 countries/regions, and China was the most potential country. More than half of the top 10 most prolific organizations were located in the United States, and Harvard Medical School was the most important organization in this field. Near half of authors who make major contributions belonged to the United States organizations when publishing documents. \u003cem\u003eFrontiers in Immunology\u003c/em\u003e was the most popular journal in this research area. Immunomodulation, gut microbiota, and cytokines represent the current research hotspots and frontiers in this field. Treg cell-based immunomodulatory approaches have shown immense potential in the treatment of neurological diseases. Modifying gut microbiota or regulating cytokines to boost the numbers and functions of Treg cells represents a promising therapeutic strategy for neurological diseases.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTe data sets generated and/or analyzed during the current study are available upon request from the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eQ.G.: Conceptualization, Data curation, writing original draft preparation, writing review and editing. X.L.: Conceptualization, Validation, writing review and editing. Y.L.: Validation, Project administration, Funding acquisition. J.L.: Methodology. M.P.: Formal analysis. J.W.: Visualization. F.Y.: Software. Y.Z.: Supervision, Project administration, Funding acquisition. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eChrousos, G. P. \u0026amp; Gold, P. W. The concepts of stress and stress system disorders. Overview of physical and behavioral homeostasis. \u003cem\u003eJama\u003c/em\u003e \u003cstrong\u003e267\u003c/strong\u003e, 1244-1252 (1992).\u003c/li\u003e\n\u003cli\u003eGunata, M., Parlakpinar, H. \u0026amp; Acet, H. A. Melatonin: A review of its potential functions and effects on neurological diseases. \u003cem\u003eRev\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Neurol\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e (Paris)\u003c/em\u003e \u003cstrong\u003e176\u003c/strong\u003e, 148-165. https://doi.org/10.1016/j.neurol.2019.07.025 (2020).\u003c/li\u003e\n\u003cli\u003eXu, W. H. Editorial for focused issue \u0026quot;Neurological Diseases\u0026quot;. \u003cem\u003eAnn\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Trans\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003el Med\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003cstrong\u003e8\u003c/strong\u003e, 1. https://doi.org/10.21037/atm.2019.12.77 (2020).\u003c/li\u003e\n\u003cli\u003eSchwab, A. D.\u003cem\u003e et al.\u003c/em\u003e Immunotherapy for Parkinson\u0026apos;s disease. \u003cem\u003eNeurobiol\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Dis\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003cstrong\u003e137\u003c/strong\u003e, 104760. https://doi.org/10.1016/j.nbd.2020.104760 (2020).\u003c/li\u003e\n\u003cli\u003eFerreira, L. M. R., Muller, Y. D., Bluestone, J. A. \u0026amp; Tang, Q. Next-generation regulatory T cell therapy. \u003cem\u003eNat\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Rev\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Drug Discov\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003cstrong\u003e18\u003c/strong\u003e, 749-769. https://doi.org/10.1038/s41573-019-0041-4 (2019).\u003c/li\u003e\n\u003cli\u003eListon, A., Dooley, J. \u0026amp; Yshii, L. Brain-resident regulatory T cells and their role in health and disease. \u003cem\u003eImmunol\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Lett\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003cstrong\u003e248\u003c/strong\u003e, 26-30. https://doi.org/10.1016/j.imlet.2022.06.005 (2022).\u003c/li\u003e\n\u003cli\u003eKleinewietfeld, M. \u0026amp; Hafler, D. A. Regulatory T cells in autoimmune neuroinflammation. \u003cem\u003eImmunol\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Rev\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003cstrong\u003e259\u003c/strong\u003e, 231-244. https://doi.org/10.1111/imr.12169 (2014).\u003c/li\u003e\n\u003cli\u003eMcIntyre, L. L.\u003cem\u003e et al.\u003c/em\u003e Regulatory T cells promote remyelination in the murine experimental autoimmune encephalomyelitis model of multiple sclerosis following human neural stem cell transplant. \u003cem\u003eNeurobiol\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Dis\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003cstrong\u003e140\u003c/strong\u003e, 104868. https://doi.org/10.1016/j.nbd.2020.104868 (2020).\u003c/li\u003e\n\u003cli\u003eBadr, M.\u003cem\u003e et al.\u003c/em\u003e Expansion of regulatory T cells by CD28 superagonistic antibodies attenuates neurodegeneration in A53T-\u0026alpha;-synuclein Parkinson\u0026apos;s disease mice. \u003cem\u003eJ\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Neuroinflammation\u003c/em\u003e \u003cstrong\u003e19\u003c/strong\u003e, 319. https://doi.org/10.1186/s12974-022-02685-7 (2022).\u003c/li\u003e\n\u003cli\u003eChen, S.\u003cem\u003e et al.\u003c/em\u003e Publication trends and hot spots in postoperative cognitive dysfunction research: A 20-year bibliometric analysis. \u003cem\u003eJ\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Clin\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Anesth\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003cstrong\u003e67\u003c/strong\u003e, 110012. https://doi.org/10.1016/j.jclinane.2020.110012 (2020).\u003c/li\u003e\n\u003cli\u003evan Eck, N. J. \u0026amp; Waltman, L. Software survey: VOSviewer, a computer program for bibliometric mapping. \u003cem\u003eScientometrics\u003c/em\u003e \u003cstrong\u003e84\u003c/strong\u003e, 523-538. https://doi.org/10.1007/s11192-009-0146-3 (2010).\u003c/li\u003e\n\u003cli\u003eSynnestvedt, M. B., Chen, C. \u0026amp; Holmes, J. H. CiteSpace II: visualization and knowledge discovery in bibliographic databases. \u003cem\u003eAMIA Annu\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Symp\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Proc\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003cstrong\u003e2005\u003c/strong\u003e, 724-728 (2005).\u003c/li\u003e\n\u003cli\u003eTeles, R. H. G.\u003cem\u003e et al.\u003c/em\u003e Advances in Breast Cancer Management and Extracellular Vesicle Research, a Bibliometric Analysis. \u003cem\u003eCurr\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Oncol\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003cstrong\u003e28\u003c/strong\u003e, 4504-4520. https://doi.org/10.3390/curroncol28060382 (2021).\u003c/li\u003e\n\u003cli\u003eWu, H.\u003cem\u003e et al.\u003c/em\u003e Mapping Knowledge Structure and Themes Trends of Osteoporosis in Rheumatoid Arthritis: A Bibliometric Analysis. \u003cem\u003eFront\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Med (Lausanne)\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003cstrong\u003e8\u003c/strong\u003e, 787228. https://doi.org/10.3389/fmed.2021.787228 (2021).\u003c/li\u003e\n\u003cli\u003eChen, C. M. CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature. \u003cem\u003eJournal of the American Society for Information Science and Technology\u003c/em\u003e \u003cstrong\u003e57\u003c/strong\u003e, 359-377. https://doi.org/10.1002/asi.20317 (2006).\u003c/li\u003e\n\u003cli\u003eZheng, F., Wang, L., Zeng, Z. \u0026amp; Wu, S. International Technologies on Prevention and Treatment of Neurological and Psychiatric Diseases: Bibliometric Analysis of Patents. \u003cem\u003eJMIR Ment\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Health\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, e25238. https://doi.org/10.2196/25238 (2022).\u003c/li\u003e\n\u003cli\u003eWang, Y., Zhang, J., Zhang, Y. \u0026amp; Yao, J. Bibliometric analysis of global research profile on ketogenic diet therapies in neurological diseases: Beneficial diet therapies deserve more attention. \u003cem\u003eFront\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Endocrinol (Lausanne)\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, 1066785. https://doi.org/10.3389/fendo.2022.1066785 (2022).\u003c/li\u003e\n\u003cli\u003eScheller, J., Chalaris, A., Schmidt-Arras, D. \u0026amp; Rose-John, S. The pro- and anti-inflammatory properties of the cytokine interleukin-6. \u003cem\u003eBiochim\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Biophys\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Acta\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003cstrong\u003e1813\u003c/strong\u003e, 878-888. https://doi.org/10.1016/j.bbamcr.2011.01.034 (2011).\u003c/li\u003e\n\u003cli\u003eShi, L. Z.\u003cem\u003e et al.\u003c/em\u003e HIF1alpha-dependent glycolytic pathway orchestrates a metabolic checkpoint for the differentiation of TH17 and Treg cells. \u003cem\u003eJ\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Exp\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Med\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003cstrong\u003e208\u003c/strong\u003e, 1367-1376. https://doi.org/10.1084/jem.20110278 (2011).\u003c/li\u003e\n\u003cli\u003eSetoguchi, R., Hori, S., Takahashi, T. \u0026amp; Sakaguchi, S. Homeostatic maintenance of natural Foxp3(+) CD25(+) CD4(+) regulatory T cells by interleukin (IL)-2 and induction of autoimmune disease by IL-2 neutralization. \u003cem\u003eJ\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Exp\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Med\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003cstrong\u003e201\u003c/strong\u003e, 723-735. https://doi.org/10.1084/jem.20041982 (2005).\u003c/li\u003e\n\u003cli\u003eLee, Y. K., Menezes, J. S., Umesaki, Y. \u0026amp; Mazmanian, S. K. Proinflammatory T-cell responses to gut microbiota promote experimental autoimmune encephalomyelitis. \u003cem\u003eProc\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Natl\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Acad\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Sci\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e USA\u003c/em\u003e \u003cstrong\u003e108 Suppl 1\u003c/strong\u003e, 4615-4622. https://doi.org/10.1073/pnas.1000082107 (2011).\u003c/li\u003e\n\u003cli\u003eWang, M.\u003cem\u003e et al.\u003c/em\u003e Role of tumor microenvironment in tumorigenesis. \u003cem\u003eJ\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Cancer\u003c/em\u003e \u003cstrong\u003e8\u003c/strong\u003e, 761-773. https://doi.org/10.7150/jca.17648 (2017).\u003c/li\u003e\n\u003cli\u003eLakhan, S. E., Kirchgessner, A. \u0026amp; Hofer, M. Inflammatory mechanisms in ischemic stroke: therapeutic approaches. \u003cem\u003eJ\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Transl\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Med\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003cstrong\u003e7\u003c/strong\u003e, 97. https://doi.org/10.1186/1479-5876-7-97 (2009).\u003c/li\u003e\n\u003cli\u003eKarussis, D.\u003cem\u003e et al.\u003c/em\u003e Safety and immunological effects of mesenchymal stem cell transplantation in patients with multiple sclerosis and amyotrophic lateral sclerosis. \u003cem\u003eArch\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Neurol\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003cstrong\u003e67\u003c/strong\u003e, 1187-1194. https://doi.org/10.1001/archneurol.2010.248 (2010).\u003c/li\u003e\n\u003cli\u003eHaroon, E., Raison, C. L. \u0026amp; Miller, A. H. Psychoneuroimmunology meets neuropsychopharmacology: translational implications of the impact of inflammation on behavior. \u003cem\u003eNeuropsychopharmacology\u003c/em\u003e \u003cstrong\u003e37\u003c/strong\u003e, 137-162. https://doi.org/10.1038/npp.2011.205 (2012).\u003c/li\u003e\n\u003cli\u003eLiesz, A.\u003cem\u003e et al.\u003c/em\u003e Regulatory T cells are key cerebroprotective immunomodulators in acute experimental stroke. \u003cem\u003eNat\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Med\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003cstrong\u003e15\u003c/strong\u003e, 192-199. https://doi.org/10.1038/nm.1927 (2009).\u003c/li\u003e\n\u003cli\u003eViglietta, V., Baecher-Allan, C., Weiner, H. L. \u0026amp; Hafler, D. A. Loss of functional suppression by CD4+CD25+ regulatory T cells in patients with multiple sclerosis. \u003cem\u003eJ\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Exp\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Med\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003cstrong\u003e199\u003c/strong\u003e, 971-979. https://doi.org/10.1084/jem.20031579 (2004).\u003c/li\u003e\n\u003cli\u003eReynolds, A. D., Banerjee, R., Liu, J., Gendelman, H. E. \u0026amp; Mosley, R. L. Neuroprotective activities of CD4+CD25+ regulatory T cells in an animal model of Parkinson\u0026apos;s disease. \u003cem\u003eJ\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Leukoc\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Biol\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003cstrong\u003e82\u003c/strong\u003e, 1083-1094. https://doi.org/10.1189/jlb.0507296 (2007).\u003c/li\u003e\n\u003cli\u003eReynolds, A. D.\u003cem\u003e et al.\u003c/em\u003e Regulatory T cells attenuate Th17 cell-mediated nigrostriatal dopaminergic neurodegeneration in a model of Parkinson\u0026apos;s disease. \u003cem\u003eJ\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Immunol\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003cstrong\u003e184\u003c/strong\u003e, 2261-2271. https://doi.org/10.4049/jimmunol.0901852 (2010).\u003c/li\u003e\n\u003cli\u003eIadecola, C. \u0026amp; Anrather, J. The immunology of stroke: from mechanisms to translation. \u003cem\u003eNat\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Med\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003cstrong\u003e17\u003c/strong\u003e, 796-808. https://doi.org/10.1038/nm.2399 (2011).\u003c/li\u003e\n\u003cli\u003eHori, S., Nomura, T. \u0026amp; Sakaguchi, S. Control of regulatory T cell development by the transcription factor Foxp3. \u003cem\u003eScience\u003c/em\u003e \u003cstrong\u003e299\u003c/strong\u003e, 1057-1061. https://doi.org/10.1126/science.1079490 (2003).\u003c/li\u003e\n\u003cli\u003eFontenot, J. D., Gavin, M. A. \u0026amp; Rudensky, A. Y. Foxp3 programs the development and function of CD4+CD25+ regulatory T cells. \u003cem\u003eNat\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Immunol\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003cstrong\u003e4\u003c/strong\u003e, 330-336. https://doi.org/10.1038/ni904 (2003).\u003c/li\u003e\n\u003cli\u003eSakaguchi, S., Yamaguchi, T., Nomura, T. \u0026amp; Ono, M. Regulatory T cells and immune tolerance. \u003cem\u003eCell\u003c/em\u003e \u003cstrong\u003e133\u003c/strong\u003e, 775-787. https://doi.org/10.1016/j.cell.2008.05.009 (2008).\u003c/li\u003e\n\u003cli\u003eBettelli, E.\u003cem\u003e et al.\u003c/em\u003e Reciprocal developmental pathways for the generation of pathogenic effector T(H)17 and regulatory T cells. \u003cem\u003eNature\u003c/em\u003e \u003cstrong\u003e441\u003c/strong\u003e, 235-238. https://doi.org/10.1038/nature04753 (2006).\u003c/li\u003e\n\u003cli\u003eLiddelow, S. A.\u003cem\u003e et al.\u003c/em\u003e Neurotoxic reactive astrocytes are induced by activated microglia. \u003cem\u003eNature\u003c/em\u003e \u003cstrong\u003e541\u003c/strong\u003e, 481-487. https://doi.org/10.1038/nature21029 (2017).\u003c/li\u003e\n\u003cli\u003eWang, M.\u003cem\u003e et al.\u003c/em\u003e Regulatory T lymphocytes as a therapy for ischemic stroke. \u003cem\u003eSemin\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Immunopathol\u003c/em\u003e. https://doi.org/10.1007/s00281-022-00975-z (2022).\u003c/li\u003e\n\u003cli\u003eBell, L., Lenhart, A., Rosenwald, A., Monoranu, C. M. \u0026amp; Berberich-Siebelt, F. Lymphoid Aggregates in the CNS of Progressive Multiple Sclerosis Patients Lack Regulatory T Cells. \u003cem\u003eFront\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Immunol\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, 3090. https://doi.org/10.3389/fimmu.2019.03090 (2019).\u003c/li\u003e\n\u003cli\u003eChwojnicki, K.\u003cem\u003e et al.\u003c/em\u003e Administration of CD4(+)CD25(high)CD127(-)FoxP3(+) Regulatory T Cells for Relapsing-Remitting Multiple Sclerosis: A Phase 1 Study. \u003cem\u003eBioDrugs\u003c/em\u003e \u003cstrong\u003e35\u003c/strong\u003e, 47-60. https://doi.org/10.1007/s40259-020-00462-7 (2021).\u003c/li\u003e\n\u003cli\u003eSommer, A.\u003cem\u003e et al.\u003c/em\u003e Th17 Lymphocytes Induce Neuronal Cell Death in a Human iPSC-Based Model of Parkinson\u0026apos;s Disease. \u003cem\u003eCell Stem Cell\u003c/em\u003e \u003cstrong\u003e23\u003c/strong\u003e, 123-131.e126. https://doi.org/10.1016/j.stem.2018.06.015 (2018).\u003c/li\u003e\n\u003cli\u003eBi, Y.\u003cem\u003e et al.\u003c/em\u003e Human Adipose Tissue-Derived Mesenchymal Stem Cells in Parkinson\u0026apos;s Disease: Inhibition of T Helper 17 Cell Differentiation and Regulation of Immune Balance Towards a Regulatory T Cell Phenotype. \u003cem\u003eClin\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Interv\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Aging\u003c/em\u003e \u003cstrong\u003e15\u003c/strong\u003e, 1383-1391. https://doi.org/10.2147/cia.S259762 (2020).\u003c/li\u003e\n\u003cli\u003eShi, L.\u003cem\u003e et al.\u003c/em\u003e Treg cell-derived osteopontin promotes microglia-mediated white matter repair after ischemic stroke. \u003cem\u003eImmunity\u003c/em\u003e \u003cstrong\u003e54\u003c/strong\u003e, 1527-1542.e1528. https://doi.org/10.1016/j.immuni.2021.04.022 (2021).\u003c/li\u003e\n\u003cli\u003eQu, G.\u003cem\u003e et al.\u003c/em\u003e Current status and perspectives of regulatory T cell-based therapy. \u003cem\u003eJ\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Genet\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Genomics\u003c/em\u003e \u003cstrong\u003e49\u003c/strong\u003e, 599-611. https://doi.org/10.1016/j.jgg.2022.05.005 (2022).\u003c/li\u003e\n\u003cli\u003eParodi, B. \u0026amp; Kerlero de Rosbo, N. The Gut-Brain Axis in Multiple Sclerosis. Is Its Dysfunction a Pathological Trigger or a Consequence of the Disease? \u003cem\u003eFront\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Immunol\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 718220. https://doi.org/10.3389/fimmu.2021.718220 (2021).\u003c/li\u003e\n\u003cli\u003eHaase, S., Haghikia, A., Wilck, N., M\u0026uuml;ller, D. N. \u0026amp; Linker, R. A. Impacts of microbiome metabolites on immune regulation and autoimmunity. \u003cem\u003eImmunology\u003c/em\u003e \u003cstrong\u003e154\u003c/strong\u003e, 230-238. https://doi.org/10.1111/imm.12933 (2018).\u003c/li\u003e\n\u003cli\u003eCekanaviciute, E.\u003cem\u003e et al.\u003c/em\u003e Gut bacteria from multiple sclerosis patients modulate human T cells and exacerbate symptoms in mouse models. \u003cem\u003eProc\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Natl\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Acad\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Sci\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e USA\u003c/em\u003e \u003cstrong\u003e114\u003c/strong\u003e, 10713-10718. https://doi.org/10.1073/pnas.1711235114 (2017).\u003c/li\u003e\n\u003cli\u003eMangalam, A.\u003cem\u003e et al.\u003c/em\u003e Human Gut-Derived Commensal Bacteria Suppress CNS Inflammatory and Demyelinating Disease. \u003cem\u003eCell Rep\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003cstrong\u003e20\u003c/strong\u003e, 1269-1277. https://doi.org/10.1016/j.celrep.2017.07.031 (2017).\u003c/li\u003e\n\u003cli\u003eChen, P. \u0026amp; Tang, X. Gut Microbiota as Regulators of Th17/Treg Balance in Patients With Myasthenia Gravis. \u003cem\u003eFront\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Immunol\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 803101. https://doi.org/10.3389/fimmu.2021.803101 (2021).\u003c/li\u003e\n\u003cli\u003eLi, J., Zhang, Z., Du, S. \u0026amp; Guo, Q. Interleukin 2 Ameliorates Autoimmune Neuroinflammation by Modulating the Balance of T Helper 17 Cells and Regulatory T Cells in Mouse. \u003cem\u003eAnn\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Clin\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Lab\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Sci\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003cstrong\u003e51\u003c/strong\u003e, 529-534 (2021).\u003c/li\u003e\n\u003cli\u003eGiovannelli, I.\u003cem\u003e et al.\u003c/em\u003e Amyotrophic lateral sclerosis transcriptomics reveals immunological effects of low-dose interleukin-2. \u003cem\u003eBrain Commun\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003cstrong\u003e3\u003c/strong\u003e, fcab141. https://doi.org/10.1093/braincomms/fcab141 (2021).\u003c/li\u003e\n\u003cli\u003eLee, P. W., Severin, M. E. \u0026amp; Lovett-Racke, A. E. TGF-\u0026beta; regulation of encephalitogenic and regulatory T cells in multiple sclerosis. \u003cem\u003eEur\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e J\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Immunol\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003cstrong\u003e47\u003c/strong\u003e, 446-453. https://doi.org/10.1002/eji.201646716 (2017).\u003c/li\u003e\n\u003cli\u003eKimura, A. \u0026amp; Kishimoto, T. IL-6: regulator of Treg/Th17 balance. \u003cem\u003eEur\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e J\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Immunol\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003cstrong\u003e40\u003c/strong\u003e, 1830-1835. https://doi.org/10.1002/eji.201040391 (2010).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-3234444/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3234444/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis bibliometric study aimed to summarize and visualize the current research status, emerging trends and research hotspots of regulatory T (Treg) cells in neurological diseases. Relevant documents were retrieved from the Web of Science Core Collection. Tableau Public, VOSviewer and CiteSpace software were applied to perform bibliometric analysis and network visualization. A total of 2739 documents were included, and research on Treg cells in neurological diseases is still in a prolific period. The documents included in the research were sourced from 85 countries/regions, with the majority of them originating from the United States, and 2811 organizations, with a significant proportion of them coming from Harvard Medical School. Despite being the most prolific author in this research area, Gendelman HE had relatively few collaborations with researchers from other organizations. Considering the number of documents and citations, impact factors and JCR partitions, \u003cem\u003eFrontiers in Immunology\u003c/em\u003e was the most popular journal in this research area. Keywords \u0026ldquo;multiple sclerosis\u0026rdquo;, \u0026ldquo;inflammation\u0026rdquo;, \u0026ldquo;regulatory T cells\u0026rdquo;, \u0026ldquo;neuroinflammation\u0026rdquo;, \u0026ldquo;autoimmunity\u0026rdquo;, \u0026ldquo;cytokines\u0026rdquo; and \u0026ldquo;immunomodulation\u0026rdquo; were identified as high frequency keywords. Additionally, \u0026ldquo;gut microbiota\u0026rdquo; has recently emerged as a new topic of interest. The study of Treg cells in neurological diseases continues to be a hot topic. Immunomodulation, gut microbiota, and cytokines represent the current research hotspots and frontiers in this field. Treg cell-based immunomodulatory approaches have shown immense potential in the treatment of neurological diseases. Modifying gut microbiota or regulating cytokines to boost the numbers and functions of Treg cells represents a promising therapeutic strategy for neurological diseases.\u003c/p\u003e","manuscriptTitle":"Bibliometric analysis of global research trends on regulatory T cells in neurological diseases","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-08-10 15:00:30","doi":"10.21203/rs.3.rs-3234444/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a76ee93a-474e-48c0-9c95-86bb80dc70d0","owner":[],"postedDate":"August 10th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":23837949,"name":"Biological sciences/Immunology"},{"id":23837950,"name":"Health sciences/Diseases"},{"id":23837951,"name":"Health sciences/Molecular medicine"},{"id":23837952,"name":"Health sciences/Neurology"}],"tags":[],"updatedAt":"2023-10-09T13:29:37+00:00","versionOfRecord":[],"versionCreatedAt":"2023-08-10 15:00:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3234444","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3234444","identity":"rs-3234444","version":["v1"]},"buildId":"cBFmMYwuxLRRLfASyISRj","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}