Bibliometric and visualization analysis of mesenchymal stem cells and rheumatoid arthritis (from 2012 to 2021)

Current situation and trend of non-coding RNA in rheumatoid arthritis: a review and bibliometric analysis

Background

Rheumatoid arthritis (RA) is a chronic, systemic autoimmune disease that affects multiple joints and has adverse effects on various organs throughout the body, often leading to a poor prognosis. Recent studies have shown significant progress in the research of non-coding RNAs (ncRNAs) in RA. Therefore, this study aims to comprehensively assess the current status and research trends of ncRNAs in RA through a bibliometric analysis.

Methods

This study retrieved articles relevant to ncRNAs and RA from the Science Citation Index Expanded Database of the Web of Science Core Collection between January 1st, 2003, and July 31st, 2023. The relevant articles were screened based on the inclusion criteria. VOSviewer and CiteSpace are utilized for bibliometric and visual analysis.

Results

A total of 1697 publications were included in this study, and there was a noticeable increase in annual publications from January 1st, 2003, to July 31st, 2023. China, the United States, and the United Kingdom were the most productive countries in this field, contributing to 43.81%, 13.09%, and 3.87% of the publications. Anhui Medical University and Lu Qianjin were identified as the most influential institution and author. Frontiers In Immunology stood out as the most prolific journal, while Arthritis & Rheumatology was the most co-cited journal. Additionally, the research related to "circular RNA", "oxidative stress", "proliferation", and "migration" have emerged as new hotspots in the field.

Conclusion

In this study, we have summarized the publication characteristics related to ncRNA and RA and identified the most productive countries, institutions, authors, journals, hot topics, and trends.

Hypercoagulability in Rheumatoid Arthritis: A Bibliometric Analysis and Retrospective Data Mining Study

BACKGROUND

Rheumatoid arthritis (RA) is an autoimmune disease characterized by chronic systemic inflammation, leading to joint deformities and functional loss. RA progression is accompanied by abnormalities in the coagulation-fibrinolysis system, clinically manifested as a hypercoagulable state. However, there are currently no bibliometrics or visualization analysis in this field.

OBJECTIVE

The present study aims to reveal the knowledge structure, research status, and research trends related to hypercoagulability in RA through bibliometric analysis and to evaluate the utility of inflammatory and coagulation markers in RA disease activity through retrospective data mining.

METHODS

English articles and reviews on RA hypercoagulability published from 2010 to 2023 were extracted from the Web of Science Core Collection (WoSCC) database on March 1, 2023. VOSviewer and CiteSpace software were used for knowledge mapping analysis of the included papers in terms of countries/regions, institutions, journals, authors, keywords, research hotspots, and frontiers. A retrospective analysis was conducted on the general information on RA patients. The demographic and clinical indicators of all participants were collected to determine the correlation of inflammatory and coagulation markers with the Chinese patient-reported activity index for rheumatoid arthritis (CPRI-RA).

RESULTS

A total of 957 papers were retrieved. The United States was the most productive country in this field and had the highest h-index, and the most prolific institution was the Karolinska Institute. The Annals of the Rheumatic Diseases was the journal with the most publications, and KLARESKOG L. was the most productive author. From keyword analysis, it could be seen that "inflammation", "activation", "disease-activity", and "risk" had long been the focuses of RA hypercoagulability research. "Criteria", "validation", "coagulation", "target", and "anemia" were the latest popular keywords in the past 5 years. Retrospective data mining revealed that the levels of inflammation (RF, ESR, and CRP) and coagulation (PLT and DD) were significantly increased in RA patients. FBG, CRP, and ESR were significantly correlated with CPRI-RA. Additionally, ESR, CRP, and FBG were identified as independent risk factors for CPRI-RA.

CONCLUSION

The mechanism and application of hypercoagulability in RA have been research hotspots in recent years. Inflammation and coagulation markers are independent risk factors for CPRI-RA.

Research hotspots and trends of artificial intelligence in rheumatoid arthritis: A bibliometric and visualized study

Artificial intelligence (AI) applications on rheumatoid arthritis (RA) are becoming increasingly popular. In this bibliometric study, we aimed to analyze the characteristics of publications relevant to the research of AI in RA, thereby developing a thorough overview of this research topic. Web of Science was used to retrieve publications on the application of AI in RA from 2003 to 2022. Bibliometric analysis and visualization were performed using Microsoft Excel (2019), R software (4.2.2) and VOSviewer (1.6.18). The overall distribution of yearly outputs, leading countries, top institutions and authors, active journals, co-cited references and keywords were analyzed. A total of 859 relevant articles were identified in the Web of Science with an increasing trend. USA and China were the leading countries in this field, accounting for 71.59% of publications in total. Harvard University was the most influential institution. Arthritis Research & Therapy was the most active journal. Primary topics in this field focused on estimating the risk of developing RA, diagnosing RA using sensor, clinical, imaging and omics data, identifying the phenotype of RA patients using electronic health records, predicting treatment response, tracking the progression of the disease and predicting prognosis and developing new drugs. Machine learning and deep learning algorithms were the recent research hotspots and trends in this field. AI has potential applications in various fields of RA, including the risk assessment, screening, early diagnosis, monitoring, prognosis determination, achieving optimal therapeutic outcomes and new drug development for RA patients. Incorporating machine learning and deep learning algorithms into real-world clinical practice will be a future research hotspot and trend for AI in RA. Extensive collaboration to improve model maturity and robustness will be a critical step in the advancement of AI in healthcare.

Bibliometric and visual analysis of microglia-related neuropathic pain from 2000 to 2021

Background

Microglia has gradually gained researchers' attention in the past few decades and has shown its promising prospect in treating neuropathic pain. Our study was performed to comprehensively evaluate microglia-related neuropathic pain via a bibliometric approach.

Methods

We retrospectively reviewed publications focusing on microglia-related neuropathic pain from 2000 to 2021 in WoSCC. VOS viewer software and CiteSpace software were used for statistical analyses.

Results

A total of 2,609 articles were finally included. A steady increase in the number of relevant publications was observed in the past two decades. China is the most productive country, while the United States shares the most-cited and highest H-index country. The University of London, Kyushu University, and the University of California are the top 3 institutions with the highest number of publications. Molecular pain and Pain are the most productive and co-cited journals, respectively. Inoue K (Kyushu University) is the most-contributed researcher and Ji RR (Duke University) ranks 1st in both average citations per article and H-index. Keywords analyses revealed that pro-inflammatory cytokines shared the highest burst strength. Sex differences, neuroinflammation, and oxidative stress are the emerging keywords in recent years.

Conclusion

In the field of microglia-related neuropathic pain, China is the largest producer and the United States is the most influential country. The signaling communication between microglia and neurons has continued to be vital in this field. Sexual dimorphism, neuroinflammation, and stem-cell therapies might be emerging trends that should be closely monitored.

Global Trends and Future Research Directions for Temporomandibular Disorders and Stem Cells

Temporomandibular disorder (TMD) is an umbrella term used to describe various conditions that affect temporomandibular joints, masticatory muscles, and associated structures. Although the most conservative and least invasive treatment is preferable, more invasive therapies should be employed to refractory patients. Tissue engineering has been presented as a promising therapy. Our study aimed to investigate trends and point out future research directions on TMD and stem cells. A comprehensive search was carried out in the Web of Science Core Collection (WoS-CC) in October 2022. The bibliometric parameters were analyzed through descriptive statistics and graphical mapping. Thus, 125 papers, published between 1992 and 2022 in 65 journals, were selected. The period with the highest number of publications and citations was between 2012 and 2022. China has produced the most publications on the subject. The most frequently used keywords were "cartilage", "temporomandibular joint", "mesenchymal stem cells", and "osteoarthritis". Moreover, the primary type of study was in vivo. It was noticed that using stem cells to improve temporomandibular joint repair and regeneration is a significant subject of investigation. Nonetheless, a greater understanding of the biological interaction and the benefits of using these cells in patients with TMD is required.