A Web Of Science-based Scientometric Analysis Of Mammalian Target Of A Rapamycin Signaling Pathway in Kidney Disease From 1986 To 2020 Part 1

Background

The mammalian target of the rapamycin (mTOR) signaling pathway is vital for the regulation of cell metabolism, growth, and proliferation in the kidney. This study aims to show current research focuses and predict future trends in the mTOR pathways in kidney disease using scientometric analysis. 

Methods

We referred to Web of ScienceTM Core Collection (WoSCC) Database publications. Carrot2, VOSviewer, and CiteSpace programs were applied to evaluate the distribution and contribution of authors, institutes, and countries/regions of extensive bibliographic metadata, show current research focuses, and predict future trends in kidney disease areas.

Results

Until July 10, 2020, there were 2,585 manuscripts about the mTOR signaling pathway in kidney disease in total, and every manuscript is cited 27.39 times on average. The big name of course is the United States. Research hot spots include “diabetic nephropathy”, “kidney transplantation”, “autosomal dominant polycystic kidney disease”, “tuberous sclerosis complex”, “renal cell carcinoma” and “autophagy”. Seven key clusters are detected, including “kidney transplantation”, “autosomal dominant polycystic kidney disease”, “renal transplantation”, “renal cell carcinoma”, “hamartin”, “autophagy” and “tuberous sclerosis complex”. 

Conclusions

Diabetic nephropathy, kidney transplantation, autosomal dominant polycystic kidney disease, tuberous sclerosis complex, renal cell carcinoma, and autophagy are future research hot spots by utilizing scientometric analysis. In the future, it is necessary to research these fields. 

Keywords

Bibliometrics; kidney diseases; TOR serine-threonine kinases; VOSviewer; CiteSpace

Introduction

The mammalian target of rapamycin is an evolutionarilyconserved serine-threonine kinase that senses and integrates various environmental factors to regulate cell growth, proliferation, and metabolism. Since the discovery of rapamycin’s primary target molecular mode of action and the functional biology effect, the mammalian target of rapamycin (mTOR) has been recognized to permeate many areas of medicine such as obesity (1,2), type 2 diabetes (3,4), genetic disorders (5), non-alcoholic fatty liver disease (6-8), neurological diseases (9-11) and insulin resistance (12). Increasing evidence indicates that mTOR pathway plays a significant role in transplantation, homeostasis, metabolism, and regeneration in the kidney (13-16). In addition, it is related to several diseases such as tuberous sclerosis complex (17), polycystic kidney disease (18), acute kidney injury (19), renal cell carcinoma (20), autosomal dominant polycystic kidney disease (21), and glomerular disease (22). 

Bibliometric is a new method for summarizing the statistical analysis of the publications in a specific discipline and subject area, and further identifying warm focus in a research field by creating information graphics. Social science and scientometric analysis use several biometric programs including VOSviewer (23), CitNetExplorer, CiteSpace (24), and HistCite. Even though considerable insights have been gained, many remain to endeavor regarding biomedicine. Schargus et al. identified the most frequently cited papers in dry eye research (25). Sugimoto et al. investigated sex-related factors in medical examinations between 2008 and 2016 (26). Fedewa et al. investigated the effect of exercise training on C reactive protein (27). The purpose of this study is to exploit bibliometric methods in order to analyze kinds of literature regarding mTOR signaling pathway in kidney disease. We investigate the contribution of authors, institutions, and countries/regions, the evolution of scientific ideas, research sub-themes, and milestone manuscripts in the specific research field by utilizing VOSviewer, CiteSpace, and other tools.

Methods

Data source and search strategy 

Relevant kinds of literature were extracted from the Web of ScienceTM Core Collection (WoSCC) Database (Clarivate Analysis, Boston, USA). We searched publications by exploiting the keywords “mTOR or mammalian target of rapamycin” and “kidney” from the WoSCC Database on July 10, 2020. No language restrictions were imposed. “Full record and cited references” were downloaded and raw data were transformed into TXT format which allowed for the analysis of bibliometric tools.

Statistical analysis and presentation 

Distribution and contribution of authors, institutes and countries/regions, and research areas of kinds of literature were analyzed, which was retrieved from WoSCC Database. We applied novel scientometric tools, including VOSviewer (Ludo Waltman, Leiden University of Centre for Science and Technology Studies, Netherlands), Carrot2 (Dawid Weiss, Poznan University of Technology, Poland) and CiteSpace (Chaomei Chen, Drexel University, USA) for comprehensive science mapping analysis of extensive bibliographic metadata.

CiteSpace (Version 5.6.R2 64-bit), which served as an indicator of the most active area of the scientific community research, was used to capture keywords with strong citation bursts, analyze the time trends of keywords, recognize cited authors/references, and develop visualization maps. Topical categories were analyzed by Carrot2. VOSviewer (Version 1.6.11) was utilized for recognizing associations among journals and constructing collaboration networks, which referred to term clustering, countries/regions/ institutions/authors, and quotation systems of cited authors/ journals.

A total of 2,585 kinds of literature were extracted from WoSCC Database. According to the definition of CiteSpace, visualization knowledge maps were composed of nodes and links. Different nodes in figures represent elements such as countries/regions and authors, and links between nodes indicate relationships of co-citations or collaboration/ cooccurrence. And publications were analyzed to construct the cluster analysis, co-citation network, dual-map overlays, and the time zone or timeline view. We employed the process of “clustering” of CiteSpace to identify different subtopics among all articles about “mTOR in kidney disease”. VOSviewer was utilized to perform journal co-citation density analysis. And “Circles visualization” was created to excerpt significant keywords and reveal the relative influence of every keyword by Carrot2.

Results

Annual publications and trend 

Data is input in the flow diagram (Figure 1). Based on the WoSCC, a total of 2,585 manuscripts are published. The first literature about mTOR which met the search terms was published in 1999. Only after 2005 did the articles on mTOR reach at least a double-digit number annually. And the number of publications was an ever-increasing activity per year. In the past 20 years, the proportion of mTOR pathways in the overall research of kidneys showed an upward trend (Figure 2A). In 2019, the annual kinds of literature grew to 291 (Figure 2A). These papers have been cited 70,795 times and every article was on averagely cited 27.39 times.

Figure 1 Scientometric analysis of mTOR signaling pathway in kidney disease revealed in the flow diagram. K, scale factor; Z, z-sore, a standard score of the number of appearances of keywords. mTOR, mammalian target of rapamycin.

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Distribution and contribution of global countries/regions and institutions 

Seventy countries/regions in total have published research on mTOR signaling pathways in kidney disease. It happened that one piece of literature was published by authors from diverse countries/regions. The top 15 most productive countries/ regions produced 2,860 papers (Figure 2B). Papers about mTOR in kidney disease originated mainly in the United States. And the number of papers in the United States was a lot higher than in the other countries/regions. The USA published 923 articles, followed by China (n=373), Germany (n=297), Italy (n=199), France (n=194), Spain (n=181), Japan (n=126), England (n=108), and Switzerland (n=94) (Figure 2B). According to the heat map made by VOSviewer, the USA, Germany, Italy, and China had the most intense publication density (Figure 2C).

In order to obtain a better understanding of the contributions of each country/region to the mTOR in kidney disease and the collaborations between countries/ regions, we analyzed the WoSCC Database as data. According to these data, we focused more on international collaborations, the number of citations, and the times each country/region cites the work of another. USA (n=32,984) and Germany (n=8,579) ranked top two in regard to total citation numbers (Figure 2D). Although the USA, China, Germany, Italy, and France have the highest numbers of mTOR-related publications, the average citation number per document of Switzerland and the Netherlands is much higher than the other countries (Figure 2D). China, Japan, and some European nations, such as Germany, England, and the Netherlands, had the largest publications concentrated between 2008 and 2010, while Italy, Poland, Canada, Switzerland, and Spain are mainly published from 2013 to 2015 (Figure 2E).

A total of 2,882 institutions have published kinds of literature. The citation network among these institutions was analyzed by the VOSviewer program. Table 1 revealed the top 10 institutions with the most publications. Among these organizations, five belong to the United States, two to Germany, two to Spain, and one to France. Harvard University mainly researched mTOR in kidney disease in 2012–2013 (Figure 2F). On average, papers from the University Freiburg were cited 68.16 times, which was much higher than the others (Figure 2G, H).

Figure 2 Countries/regions involved in mTOR signaling pathway in kidney disease research. (A) Number and percentage of publications. (B) The top 15 countries/regions with the largest publications. (C) Heat map of publications in countries/regions. (D) Average citations per paper and total citation number of the top 15 countries/regions with the largest production. (E) The number of articles in 70 countries/ regions. (F) The number of manuscripts in different institutions. (G) Publication number and citation per paper of top 20 most productive institutions. (H) Collaboration between institutions. mTOR, mammalian target of rapamycin.

Manuscript distribution among journals

The 2,585 articles were extracted from 730 SCI-E recorded journals. The total publication number and the citation network among these journals were analyzed by the VOSviewer program. The minimum number of documents of journals was set higher than 5 to visualize a map of 100 journals (Figure 3A). The top 20 most productive journals published 850 kinds of literature, which was one out of three of the total publication number. The top three magazines with the most evaluated number of distributed articles were Transplantation Proceedings, Transplantation, and the American Journal of Transplantation. Eighteen of these journals were established in the UK (n=5) and the United States (n=13) (Table 2). New England Journal of Medicine (74.699), Nature Medicine (36.13), Nature Reviews Nephrology (20.711), Annals of Oncology (18.274), and European Urology (17.947) were the top 5 journals with the highest impact factor. Since Nature had only published one related literature: Termination of autophagy and reformation of lysosomes regulated by mTOR (28), even if the citation number reached 783, the VOSviewer program did not select the magazine. The same research area of journals had a tendency to be within the same cluster. The node on the graph represents a magazine and links between nodes indicate a co-citation relationship with each other (Figure 3A). There existed three clusters in the network visualization map and items in different clusters have different colors (Figure 3B). 

Figure 3 Citation networks and collaboration among organizations and authors. (A) The top 100 highly cited journals with network visualization. (B) The top 100 highly cited journals with citation network. (C) The co-authorship among the top 70 highly cited authors. (D) The top 70 highly cited authors with network visualization. (E) The top 20 strongest citation bursts of references. (F) A co-citation network of references.

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