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The landscape of photoaging: From bench to bedside in a bibliometric analysis

BACKGROUND: Bibliometric software exists as a platform providing multiple algorithms to process the data to suffice diverse goals. Interpretation of the result must be based on insight into the meaning of the original data and the algorithm used. Medical Subject Headings (MeSH) terms represent the m...

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Detalles Bibliográficos
Autores principales: Sun, Pei Hong, Yan, Wei Tong, Tian, Rui Feng, Sun, Yan, Wu, Yan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9633272/
https://www.ncbi.nlm.nih.gov/pubmed/36339199
http://dx.doi.org/10.3389/fpubh.2022.972766
Descripción
Sumario:BACKGROUND: Bibliometric software exists as a platform providing multiple algorithms to process the data to suffice diverse goals. Interpretation of the result must be based on insight into the meaning of the original data and the algorithm used. Medical Subject Headings (MeSH) terms represent the macro-level meaning of topics, keywords that commonly reflect the micro-level aspects. OBJECTIVE: This study attempts to investigate the landscape of photoaging in the recent two decades by using bibliometric analysis. METHODS: Published studies of photoaging were obtained from PubMed and Web of Science Core Collection (WoSCC) from 2000 to 2020. Basic bibliometric information was generated by WoSCC. Major MeSH terms were performed in cluster analysis and displayed as a hierarchical form to induce knowledge structure, detection algorithm on keywords was presented as a timeline form to obtain hotspots, and institutional clusters were labeled with keywords to achieve institutional characteristics. RESULTS: A total of 2,727 and 2,705 studies were identified in PubMed and WoSCC, respectively. The number of photoaging-related studies at 3-year intervals grew steadily. The studies were performed in about 80 countries/regions. The highly frequent major MeSH terms were distributed in seven clusters, reflecting the etiology, pathophysiology, treatment, and prevention of photoaging. The hotspots changed as time went on, and the hotspots in recent 5 years were mitogen-activated protein kinase (MAPK), nuclear factor erythroid-derived 2-like 2 (Nrf2), and antioxidant activity. The highly productive institutions labeling in the top four clusters were Seoul National University, University of Michigan, China Medical University, and Harvard University, with corresponding keywords of UVB, retinoic acid, Nrf2, and rejuvenation. CONCLUSIONS: This study built a knowledge structure of pathophysiology, treatment and prevention of photoaging, and identified recent hotspots of MAPK, Nrf2, and antioxidant activity. We provide a landscape of photoaging, from the bench (pathophysiology) to bedside (treatment, prevention), and pave the way for future research.