Global scientific trends update on macrophage polarization in rheumatoid arthritis: A bibliometric and visualized analysis from 2000 to 2022

The role of YAP/TAZ on joint and arthritis

Osteoarthritis (OA) and rheumatoid arthritis (RA) are two common forms of arthritis with undefined etiology and pathogenesis. Yes-associated protein (YAP) and its homolog transcriptional coactivator with PDZ-binding motif (TAZ), which act as sensors for cellular mechanical and inflammatory cues, have been identified as crucial players in the regulation of joint homeostasis. Current studies also reveal a significant association between YAP/TAZ and the pathogenesis of OA and RA. The objective of this review is to elucidate the impact of YAP/TAZ on different joint tissues and to provide inspiration for further studying the potential therapeutic implications of YAP/TAZ on arthritis. Databases, such as PubMed, Cochran Library, and Embase, were searched for all available studies during the past two decades, with keywords "YAP," "TAZ," "OA," and "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.