Bibliometric Analysis of Research on Telomere Length in Children: A Review of Scientific Literature

Association between telomere length and neuropsychological function at 4-5 years in children from the INMA project: a cross-sectional study

Shortened telomere length (TL) has been associated with lower cognitive performance, different neurological diseases in adults, and certain neurodevelopmental disorders in children. However, the evidence about the association between TL and neuropsychological developmental outcomes in children from the general population is scarce. Therefore, this study aimed to explore the association between TL and neuropsychological function in children 4-5 years of age. We included 686 children from the INMA Project, a population-based birth cohort in Spain. Leucocyte TL was determined by quantitative PCR method, and neuropsychological outcomes were measured using the McCarthy Scales of Children's Abilities (MCSA). Multiple linear regression models were used to estimate associations adjusted for potential confounding variables. Main findings showed that a longer TL was associated with a higher mean working memory score (β = 4.55; 95% CI = 0.39, 8.71). In addition, longer TL was associated with a higher mean global quantitative score (β = 3.85; 95% CI = -0.19, 7.89), although the association was marginally significant. To our knowledge, this is the first study that shows a positive association between TL and better neuropsychological outcomes in children. Although further research is required to confirm these results, this study supports the hypothesis that TL is essential in protecting and maintaining a child's health, including cognitive functions such as working memory.

Evaluating cluster analysis techniques in ChatGPT versus R-language with visualizations of author collaborations and keyword cooccurrences on articles in the Journal of Medicine (Baltimore) 2023: Bibliometric analysis

BACKGROUND

Analyses of author collaborations and keyword co-occurrences are frequently used in bibliographic research. However, no studies have introduced a straightforward yet effective approach, such as utilizing ChatGPT with Code Interpreter (ChatGPT_CI) or the R language, for creating cluster-oriented networks. This research aims to compare cluster analysis methods in ChatGPT_CI and R, visualize country-specific author collaborations, and then demonstrate the most effective approach.

METHODS

The research focused on articles and review pieces from Medicine (Baltimore) published in 2023. By August 20, 2023, we had gathered metadata for 1976 articles using the Web of Science core collections. The efficiency and effectiveness of cluster displays between ChatGPT_CI and R were compared by evaluating their time consumption. The best method was then employed to present a series of visualizations of country-specific author collaborations, rooted in social network and cluster analyses. Visualization techniques incorporating network charts, chord diagrams, circle bar plots, circle packing plots, heat dendrograms, dendrograms, and word clouds were demonstrated. We further highlighted the research profiles of 2 prolific authors using timeline visuals.

RESULTS

The research findings include that (1) the most active contributors were China, Nanjing Medical University (China), the Medical School Department, and Dr Chou from Taiwan when considering countries, institutions, departments, and individual authors, respectively; (2) the highest cited articles originated from Medicine (Baltimore) accounting for 4.53%: New England Journal of Medicine, PLOS ONE, LANCET, and The Journal of the American Medical Association, with respective contributions of 3.25%, 2.7%, 2.52%, and 1.54%; (3) visual cluster analysis in R proved to be more efficient and effective than ChatGPT_CI, reducing the time taken from 1 hour to just 3 minutes; (4) 7 cluster-focused networks were crafted using R on a custom platform; and (5) the research trajectories of 2 prominent authors (Dr Brin from the United States and Dr Chow from Taiwan) and articles themes in Medicine 2023 were depicted using timeline visuals.

CONCLUSIONS

This research highlighted the efficient and effective methods for conducting cluster analyses of author collaborations using R. For future related studies, such as keyword co-occurrence analysis, R is recommended as a viable alternative for bibliographic research.

A comprehensive approach for clustering analysis using follower-leading clustering algorithm (FLCA): Bibliometric analysis

BACKGROUND

There are 3 issues in bibliometrics that need to be addressed: The lack of a clear definition for author collaborations in cluster analysis that takes into account collaborations with and without self-connections; The need to develop a simple yet effective clustering algorithm for use in coword analysis, and; The inadequacy of general bibliometrics in regard to comparing research achievements and identifying articles that are worth reading and recommended for readers. The study aimed to put forth a clustering algorithm for cluster analysis (called following leader clustering [FLCA], a follower-leading clustering algorithm), examine the dissimilarities in cluster outcomes when considering collaborations with and without self-connections in cluster analysis, and demonstrate the application of the clustering algorithm in bibliometrics.

METHODS

The study involved a search for articles and review articles published in JMIR Medical Informatics between 2016 and 2022, conducted using the Web of Science core collections. To identify author collaborations (ACs) and themes over the past 7 years, the study utilized the FLCA algorithm. With the 3 objectives of; Comparing the results obtained from scenarios with and without self-connections; Applying the FLCA algorithm in ACs and themes, and; Reporting the findings using traditional bibliometric approaches based on counts and citations, and all plots were created using R.

RESULTS

The study found a significant difference in cluster outcomes between the 2 scenarios with and without self-connections, with a 53.8% overlap (14 out of the top 20 countries in ACs). The top clusters were led by Yonsei University in South Korea, Grang Luo from the US, and model in institutes, authors, and themes over the past 7 years. The top entities with the most publications in JMIR Medical Informatics were the United States, Yonsei University in South Korea, Medical School, and Grang Luo from the US.

CONCLUSION

The FLCA algorithm proposed in this study offers researchers a comprehensive approach to exploring and comprehending the complex connections among authors or keywords. The study suggests that future research on ACs with cluster analysis should employ FLCA and R visualizations.

Global research trends in artificial intelligence for critical care with a focus on chord network charts: Bibliometric analysis

BACKGROUND

The field of critical care-related artificial intelligence (AI) research is rapidly gaining interest. However, there is still a lack of comprehensive bibliometric studies that measure and analyze scientific publications on a global scale. Network charts have traditionally been used to highlight author collaborations and coword phenomena (ACCP). It is necessary to determine whether chord network charts (CNCs) can provide a better understanding of ACCP, thus requiring clarification. This study aimed to achieve 2 objectives: evaluate global research trends in AI in intensive care medicine on publication outputs, coauthorships between nations, citations, and co-occurrences of keywords; and demonstrate the use of CNCs for ACCP in bibliometric analysis.

METHODS

The web of science database was searched for a total of 1992 documents published between 2013 and 2022. The document type was limited to articles and article reviews, and titles and abstracts were screened for eligibility. The characteristics of the publications, including preferred journals, leading research countries, international collaborations, top institutions, and major keywords, were analyzed using the category-journal rank-authorship-L-index score and trend analysis. The 100 most highly cited articles are also listed in detail.

RESULTS

Between 2018 and 2022, there was a sharp increase in publications, which accounted for 92.8% (1849/1992) of all papers included in the study. The United States and China were responsible for nearly 50% (936/1992) of the total publications. The leading countries, institutes, departments, authors, and journals in terms of publications were the US, Massachusetts Gen Hosp (US), Medical School, Zhongheng Zhang (China), and Science Reports. The top 3 primary keywords denoting research hotspots for AI in critically ill patients were mortality, model, and intensive care unit, with mortality having the highest burst strength (4.49). The keywords risk and system showed the highest growth trend (0.98) in counts over the past 4 years.

CONCLUSIONS

This study provides valuable insights into the potential for ACCP and future research opportunities. For AI-based clinical research to become widely accepted in critical care practice, collaborative research efforts are necessary to strengthen the maturity and robustness of AI-driven models using CNCs for display.

Analyzing author collaborations by developing a follower-leader clustering algorithm and identifying top co-authoring countries: Cluster analysis

BACKGROUND

This study aimed to explore suitable clustering algorithms for author collaborations (ACs) in bibliometrics and investigate which countries frequently coauthored with others in recent years. To achieve this, the study developed a method called the Follower-Leading Clustering Algorithm (FLCA) and used it to analyze ACs and cowords in the Journal of Medicine (Baltimore) from 2020 to 2022.

METHODS

This study extracted article metadata from the Web of Science and used the statistical software R to implement FLCA, enabling efficient and reproducible analysis of ACs and cowords in bibliometrics. To determine the countries that easily coauthored with other countries, the study observed the top 20 countries each year and visualized the results using network charts, heatmaps with dendrograms, and Venn diagrams. The study also used chord diagrams to demonstrate the use of FLCA on ACs and cowords in Medicine (Baltimore).

RESULTS

The study observed 12,793 articles, including 5081, 4418, and 3294 in 2020, 2021, and 2022, respectively. The results showed that the FLCA algorithm can accurately identify clusters in bibliometrics, and the USA, China, South Korea, Japan, and Spain were the top 5 countries that commonly coauthored with others during 2020 and 2022. Furthermore, the study identified China, Sichuan University, and diagnosis as the leading entities in countries, institutes, and keywords based on ACs and cowords, respectively. The study highlights the advantages of using cluster analysis and visual displays to analyze ACs in Medicine (Baltimore) and their potential application to coword analysis.

CONCLUSION

The proposed FLCA algorithm provides researchers with a comprehensive means to explore and understand the intricate connections between authors or keywords. Therefore, the study recommends the use of FLCA and visualizations with R for future research on ACs with cluster analysis.

The Impact of Foods, Nutrients, or Dietary Patterns on Telomere Length in Childhood and Adolescence: A Systematic Review

Environmental factors such as diet can affect telomere length (TL) dynamics. However, the role that children’s and adolescents’ diets play in maintaining TL is not well understood. Thus, we conducted a systematic review to examine the association between the intake of nutrients, foods, food groups, and/or dietary patterns and TL in childhood and adolescence. Following the PRISMA guidelines, we searched MEDLINE via PubMed, Embase, and Cochrane databases and additional registers and methods. The five selected studies were cross-sectional and conducted in children and adolescents aged 2 to 18 years. The main results suggest that a higher consumption of fish, nuts and seeds, fruits and vegetables, green leafy and cruciferous vegetables, olives, legumes, polyunsaturated fatty acids, and an antioxidant-rich diet might positively affect TL. On the contrary, a higher intake of dairy products, simple sugar, sugar-sweetened beverages, cereals, especially white bread, and a diet high in glycaemic load were factors associated with TL shortening. To our knowledge, this is the first systematic review examining the impact of dietary intake factors on TL in childhood and adolescence. Although limited, these results are consistent with previous studies in different adult populations. Further research is needed to ascertain potential nutritional determinants of TL in childhood and adolescence.

Worldwide trends on molar incisor and deciduous molar hypomineralisation research: a bibliometric analysis over a 19-year period

AIM

To identify the worldwide trends in scientific evidence and gaps in knowledge regarding molar incisor hypomineralisation (MIH) and deciduous molar hypomineralisation/hypomineralised second primary molars (DMH/HSPM), exploring the contribution of authors and countries, possible etiological factors and proposed treatments, in order to guide future research in the area.

METHODS

Searches were conducted in MEDLINE, Scopus, Web of Science, Cochrane Library, Lilacs/BBO, Embase and Google Scholar. Studies employing the terms MIH, DMH/HSPM and their linguistic variations were included. The following data were extracted: title, authors, year and journal of publication and first author's affiliation country. Studies were categorized according to topic, dentition, study design, etiological factors and types of treatments. Categories were analysed in relation to their distribution, co-occurrence, cross-correlation and/or autocorrelation.

RESULTS

Five hundred and three studies were included. The most published authors were Manton D (n = 47), de Souza JF (n = 22) and Ghanim A (n = 22) and four main collaboration clusters have been identified. Most of the studies were conducted on permanent dentition (MIH) (87.4%); with observational design (57.2%). The "European Archives of Paediatric Dentistry" was the most published journal (13.3%) and a significant increase in the number of publications was observed in the last decade. MIH was most studied in relation to prevalence/incidence, systemic factors involved in its aetiology and treatment with composite restorations, while a gap in knowledge was observed for extraction and sealants. Less studies were published on DMH/HSPM and most of them evaluated risk factors or prevalence/incidence. The gap of knowledge was observed in relation to treatments and patient's quality of life.

CONCLUSIONS

This bibliometric review provided a comprehensive overview of research in MIH and DMH/HSPM over the past 19 years. Within the limitations of the present study, the following conclusions can be drawn: global trends point to an increasing peak of scientific publication, especially in the last decade, while there is a shortage of clinical studies on treatments, mainly evaluating tooth extractions. Finally the multifactorial nature should be further explored, considering environmental and systemic factors together.

Bibliometric Analysis of Global Research Productivity on Vitamin D and Bone Metabolism (2001-2020): Learn from the Past to Plan Future

Vitamin D has long been known for preserving bone and non-skeletal health. Despite its magnitude of impact, scarce literature has explored the evolution of the relevant published literature. This study aimed at evaluating the trends and performance of Vitamin D and bone metabolism-related publications (2001−2020). All pertinent English language 16,887 articles were searched and extracted from the Web of Science (WoS) database and “R-Bibliometrix” was used for comprehensive analysis. Around 60,149 authors contributed from 114 countries, showing the USA on top with >1/4th of all articles, followed by Japan, China, and the United Kingdom. For authors, Cooper C, Dawson-Hughes B, and Holick MF were found to have written the most articles, citations and highest h-index, respectively. Corresponding authors from the top 20 countries collectively were responsible for around 84% of the articles. Among 2735 sources, Osteoporosis International (632), Journal of Bone and Mineral Research (569), and Bone (448) were foremost. Most prominent sources showed recent declining contributions. The increasing trend of publications with a higher spike from 2008 to 2014, followed by a gradual increase till 2017, was observed. Leading countries, affiliations, and authors showed collaborative publications and were mostly from developed countries with limited contributions, particularly from low- and middle-income countries.

Therapeutic Effects of Melatonin on Ocular Diseases: Knowledge Map and Perspective

Melatonin plays a critical role in the pathophysiological process including circadian rhythm, apoptosis, and oxidative stress. It can be synthesized in ocular tissues, and its receptors are also found in the eye, triggering more investigations concentrated on the role of melatonin in the eye. In the past decades, the protective and therapeutic potentials of melatonin for ocular diseases have been widely revealed in animal models. Herein, we construct a knowledge map of melatonin in treating ocular diseases through bibliometric analysis and review its current understanding and clinical evidence. The overall field could be divided into twelve topics through keywords co-occurrence analysis, in which the glaucoma, myopia, and retinal diseases were of greatest research interests according to the keywords burst detection. The existing clinical trials of melatonin in ocular diseases mainly focused on the glaucoma, and more research should be promoted, especially for various diseases and drug administration. We also discuss its bioavailability and further research topics including developing melatonin sensors for personalized medication, acting as stem cell therapy assistant drug, and consuming food-derived melatonin for facilitating its clinical transformation.