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Background: To assess the state of neurological scientific research in Italy in the time interval 2020–2023. Methods: Elsevier's modular integrated platform "SciVal" was used to analyze bibliometric research products starting from scientific production data uploaded onto Scopus. We considered the research area "Neurology" in the 01/01/2020–14/06/2023 time interval, and the following variables were extracted: number of published studies, number of citations, Field-Weighted Citation Impact, and percentage of international collaborations. The contribution of Italian scientists to the neurological research was compared to that of the other nations. Results: Research identified 90,633 scientific papers in the neurological area worldwide, with a total of 472,750 citations. The products assigned to Italian groups were 6670 (53,587 citations, Field-Weighted Citation Impact 1.68, 41% international collaborations). Conclusions: According to the present study, Italian neurological research 2020 to 2023 ranks fifth globally and third in Europe. [ABSTRACT FROM AUTHOR]

The aim of this study is to analyze the publication trends on the psychological health of postmenopausal women by performing a bibliometric and visualization analysis that can be used as a foundation for understanding current and future research plans. Publications were retrieved from Dimensions database from 2012 to June 2022. VOSviewer software was used for data mining and visualization. A total of 1718 papers were selected by keyword search and delimiting criteria. To evaluate the productive nations, authors, journals, articles and frequent joint citations, citation analysis, author keyword co-occurrence analysis, co-authorship analysis and co-citation analysis were performed. Results depict that the USA contributed the most papers (n = 457). Maximum articles (n = 192) were published in 2021. The highest number of articles are published in Menopause: The Journal of the North American Menopause Society and Climacteric: The Journal of the International Menopause Society. Out of the top 10 contributing organizations in the field, six organizations were from the USA. R. Nappi of Italy is the most productive author with 20 articles and 1138 citations. From the point of average citations per article, H. Joffe has the highest score (71.5). The data reported in this analysis contribute to discussions about the development, growth and current state of psychological health of postmenopausal women as well as its impact. These findings offer helpful guidance for researchers in choosing their potential fields of study and integrating different approaches to solve complicated issues, finding potential co-authors and choosing the right institutions for supporting academic studies or collaborative research. [ABSTRACT FROM AUTHOR]

Team science refers to research initiatives considered in collaboration with scientists from different disciplines or fields. This paper presents a bibliometric analysis for visualization of global research activity concerning the combination of cancer and the COVID-19 pandemic using a team science approach. A bibliometric study was implemented using Web of Science from 2019 to 2021. We analyzed citations to identify description and citations analysis of results, most prolific countries, international research collaboration, most prolific institutions, research areas, most cited papers, and most productive journals. The preliminary data of 2,313 studies that adopted a team science approach were recorded and analyzed. Team science is becoming progressively popular in cancer research. The United States was the most active country, followed by Italy and China. The United States, the United Kingdom, and Italy had the highest level of cooperation with other countries. The most prolific institution was Harvard University, followed by University of London and the University of Texas System. Head and Neck Journal for the Sciences and Specialties of the Head and Neck, Frontiers in Oncology, and eCancerMedicalScience were the most productive journals. Governments, organizations, policymakers, and researchers should pay attention to team science approach at times of disasters such as cancer and COVID-19 to achieve the best strategies for controlling cancer that is currently a world problem. [ABSTRACT FROM AUTHOR]

Introduction: There is limited basic research on carbon dioxide (CO2) fractional laser, indicating blind spots in CO2 fractional laser treatment of certain diseases. This study aimed to organize previous literature, summarize the current research, and speculate on possible future development. Methods: We searched document data on fractional CO2 lasers from the Web of Science core collection database and retrieved 928 articles from 2004 to 2021. CiteSpace software was used to analyze the main institutions, authors, subject hotspots, and research frontiers in global CO2 fractional laser research. Results: The results revealed that 928 related papers were published in the past 18 years (2004–2021), and the number has increased annually. The publications were written by 3239 authors from 626 institutions in 60 countries/regions. The United States (US) dominates this field (312 documents), followed by Italy (289), and South Korea (88). Lasers in Surgery and Medicine is the journal with the most publications and citations, and Uebelhoer is the central author. The main research hotspots include vulvovaginal atrophy, fractional photothermolysis, keloids, drug delivery, gene expressions, facial acne scarring, resurfacing, vitiligo, and photo damage. Conclusion: Using CiteSpace, this paper draws a map of authors, institutions, and keywords in fractional CO2 laser from 2004 to 2021; summarizes the main authors, institutions, research hotspots, and cutting‐edge topics of global fractional CO2 laser technology in recent years; and summarizes the current application status of global fractional CO2 laser in disease treatment. It also provides new ideas for the future application and research of fractional CO2 lasers. [ABSTRACT FROM AUTHOR]

Background: Osteoarthritis, a common degenerative osteochondral disease, has a close relationship between its mechanism of occurrence and oxidative stress. However, there are relatively few relevant studies in this field, and a more mature research system has not yet been formed. Methods: By searching the Web of Science (WOS) database, we obtained 1 412 publications in the field of osteoarthritis and oxidative stress. The search results were then analyzed bibliometrically using Citespace and VOSviewer, including a study of publication trends in the field, analysis of core authors, analysis of countries and institutions with high contributions, analysis of core journals, and to identify research trends and hot spots in the field, we performed keyword clustering. Results: We collected 1 412 publications on the field of osteoarthritis and oxidative stress from 1998–2022. By analyzing the publication trends in the field, we noted an exponential increase in the number of publications per year since 2014. We then identified the core authors in the field (Blanco, Francisco J., Loeser, Richard F., Vaamonde-garcia, et.al) as well as the countries (China, USA, Italy et.al) and institutions (Xi An Jiao Tong Univ, Wenzhou Med Univ, Zhejiang Univ et.al). The OSTEOARTHRITIS AND CARTILAGE and INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES contain a large number of research papers in this field, and through keyword co-occurrence analysis, we counted 3 227 keywords appearing in the field of osteoarthritis and oxidative stress. These keywords were clustered into 9 groups, representing 9 different research hotspots. Conclusions: Research in the field of osteoarthritis and oxidative stress has been developing since 1998 and is now maturing, but there is an urgent need to strengthen international academic exchanges and discuss the future focus of research development in the field of osteoarthritis and oxidative stress. [ABSTRACT FROM AUTHOR]

SUMMARY: Advances in olive oil research have blossomed in recent years, and articles on olive oil have been widely recorded. However, a comprehensive and systematic bibliometric analysis of olive oil research has not been completed. Through a systematic literature search, we consolidated 7003 papers from the Web of Science Core Collection database. This bibliometric analysis was carried out to examine the article growth, geographical distribution, and analysis of journals/research areas/authors/keywords. The results revealed the following: (1) Exponential growth was shown in the annual number of publications (R2 = 0.9791). The geographical distribution is biased to a few countries, especially Spain, Italy, and Greece in the Mediterranean region, placing a larger focus on olive oil research. (2) Quality analysis‐related research acted as a link between keyword groups, the disease prevention and treatment‐related research of olive oil received decreasing interest, while authentication and quality analysis‐related research of olive oil showed the opposite trend, by‐products‐related research of olive oil got waving interests over the whole period. (3) Improvement is needed in the degree of olive oil with international collaboration. This is the first time that hotspots and trends in olive oil research have been shown. [ABSTRACT FROM AUTHOR]

Adult-onset Still's disease is a nonfamilial, or sporadic, systemic autoinflammatory disorder accompanied by peak fever ≥ 39 °C, arthralgia or arthritis, skin rashes, leukocytosis (≥ 10,000 cells/mm3) with neutrophils ≥ 80%, and other clinical symptoms. This study aimed to analyze the quantity and quality of publications, and to exhibit the current global status and trend of adult-onset Still's disease research. Searched with the search term 'Adult onset Still disease' on the Web of Science for time limited to 2011–2020. Original articles and reviews were selected. A total of 537 articles were retrieved from 44 countries, of which 13 met the criteria of major active countries. High-income countries contributed 378 articles (70.39%). The number of articles annually increased significantly in the 10-year period (P < 0.001). China (n = 90, 16.76%), Japan (n = 79, 14.71%), Italy (n = 59, 10.99%), the United States (n = 52, 9.68%) and South Korea (n = 45, 8.38%) are the five most productive countries. Adjusted by population, Italy led the top list, followed by South Korea and Israel. According to gross domestic product analysis, Italy ranked first, followed by Portugal and Turkey. A significant correlation was detected between average citations and AAS (P = 0.002), MRC (P < 0.001). From 2011 to 2020, the number of global articles was increasing rapidly. Most papers came from high-income countries. The relationship between the bibliometric and altmetric analyses are basically consistent, therefore the two can prove/complement each other. [ABSTRACT FROM AUTHOR]

The spiraling growth of the world's population and unregulated urbanization have resulted in many environmental problems, including poor quality of air, which is associated with a wide range of health issues. Machine learning approaches have been extensively employed to predict air quality, attracting the attention of the scientific community worldwide. Bibliometric studies provide a useful means by which to visualize and analyze published works, helping researchers to make novel scientific contributions by filling existing knowledge gaps in the research. To acquire an in-depth understanding of the topic, this paper presents a bibliometric analysis of all published articles on the use of machine learning networks to predict air quality found in the Web of Science (WoS) search engine from 1992 to 2021. S-curve analysis and social network analysis were used to identify the temporal distribution of articles, productivity by countries/continents, research institutions, and scientific metrics of journal productivity. This study indicated that maximum expansion of the literature witnessed during 2017–2021 (second phase) which represents an expansion or growth stage of machine learning and air quality prediction research. The number of published works increased significantly with 1432 articles accounting for 68.51% of all publications. As a result of the increased interest in machine learning-based prediction tools, the number of articles grew 2.17-fold compared to the 1992–2016 (first phase). In terms of international collaboration impact, Italy emerged as the most successful country (43.44), followed by Greece (31.22) and Spain (23.29). Author keywords analysis was employed to explore and evaluate the emerging research trends on the subject of air quality using machine learning models. Keywords that appear most frequently in this study are 'air pollution', 'air quality', 'machine learning', and 'forecasting'. Citation burst analysis, research productivity analysis, highly influential and highly cited works were also employed to examine various research themes and questions. In this study we also discussed how conventional methods were transformed into machine learning approaches. It is expected that this paper will provide technical guidelines, research priorities, and future opportunities for the precise prediction of air quality and emergency management of air pollution globally. • Interest in air quality prediction through machine learning model is expanding. • China and US were found productive countries in terms of countries collaboration. • Big data, Internet of Things, and Smart city are emerging topic for future research. • Significant difference between citations, funded and non-funded research. • Ensemble modeling is popular in air quality prediction research. [ABSTRACT FROM AUTHOR]

The spiraling growth of the world's population and unregulated urbanization have resulted in many environmental problems, including poor quality of air, which is associated with a wide range of health issues. Machine learning approaches have been extensively employed to predict air quality, attracting the attention of the scientific community worldwide. Bibliometric studies provide a useful means by which to visualize and analyze published works, helping researchers to make novel scientific contributions by filling existing knowledge gaps in the research. To acquire an in-depth understanding of the topic, this paper presents a bibliometric analysis of all published articles on the use of machine learning networks to predict air quality found in the Web of Science (WoS) search engine from 1992 to 2021. S-curve analysis and social network analysis were used to identify the temporal distribution of articles, productivity by countries/continents, research institutions, and scientific metrics of journal productivity. This study indicated that maximum expansion of the literature witnessed during 2017–2021 (second phase) which represents an expansion or growth stage of machine learning and air quality prediction research. The number of published works increased significantly with 1432 articles accounting for 68.51% of all publications. As a result of the increased interest in machine learning-based prediction tools, the number of articles grew 2.17-fold compared to the 1992–2016 (first phase). In terms of international collaboration impact, Italy emerged as the most successful country (43.44), followed by Greece (31.22) and Spain (23.29). Author keywords analysis was employed to explore and evaluate the emerging research trends on the subject of air quality using machine learning models. Keywords that appear most frequently in this study are 'air pollution', 'air quality', 'machine learning', and 'forecasting'. Citation burst analysis, research productivity analysis, highly influential and highly cited works were also employed to examine various research themes and questions. In this study we also discussed how conventional methods were transformed into machine learning approaches. It is expected that this paper will provide technical guidelines, research priorities, and future opportunities for the precise prediction of air quality and emergency management of air pollution globally. • Interest in air quality prediction through machine learning model is expanding. • China and US were found productive countries in terms of countries collaboration. • Big data, Internet of Things, and Smart city are emerging topic for future research. • Significant difference between citations, funded and non-funded research. • Ensemble modeling is popular in air quality prediction research. [ABSTRACT FROM AUTHOR]

The last ten years have witnessed an increase in publications focusing on bioeconomy as a proposal to confront the global challenges of climate change, depletion of non-renewable resources and ecosystem degradation. This paper investigates the scientific literature on issues related agricultural bioeconomy by applying a bibliometric network analysis. Bibliometric analysis is applied to the publications of the Scopus database during the period 2010–2020 in order to provide an overview of the main aspects that characterize agricultural bioeconomy. The results showed that out of a total of 1100 scientific papers, only 2.45% were published in 2010, while the corresponding share in 2020 was 20.81%. In the five years of 2016–2020, cumulatively, 70.63% of the publications were made, showing the dynamic evolution of bioeconomy. In addition, out of 85 countries in total, Germany and Italy are the two countries with most publications, while the fragmentation of research is evident with the creation of two main nodes, the European and the American. Moreover, keyword analysis showed that biomass and sustainability are two main recurring concepts, confirming that, currently, bioeconomy operates at three different levels: energy demand, land demand, and governance. It is apparent that to boost the development of agricultural bioeconomy, the following aspects should be assessed: the effective use of resources, an understanding of the key drivers of agricultural bioeconomy, and a clear perception of their associations. There is still no consensus as to which are the key factors that will accelerate its sustainable development. Our pursuit is to use the tools of bibliometric analysis to reach more critical conclusions regarding the agricultural bioeconomy, rather than approach it in a static way. [ABSTRACT FROM AUTHOR]

Historically, essential oils and their lead molecules have been extensively recognised for their anti-infective properties. In this context, certain volatile phenolics (VPs) have emerged as important antimicrobial compounds with excellent inhibitory activity against pathogenic bacteria and fungi, which further extends to drug-resistant and biofilm-forming micro-organisms. In this review, we aim to collate and discuss a number of published papers on the anti-infective activities of naturally occurring VPs with special emphasis on eugenol, isoeugenol, thymol and carvacrol, using Scopus Web of Science and PubMed databases. The biosynthesis and extraction of these VPs are discussed, while particular attention is given to their broad-spectrum antimicrobial activity and the mechanisms of action. We highlight combinational studies of the VPs with other phytocompounds and with commercially available drugs, which may be a promising and a rewarding future approach to combat antimicrobial resistance. These VPs alone, or concomitantly with other compounds or drugs, have the potential to be incorporated into different formulations for biomedical applications. An in-depth assessment of 2310 articles retrieved from the Scopus database spanning a 35-year period indicated 23.1% increase in global publication growth in VPs anti-infective research, with authors from Italy, Portugal and Austria dominating the research landscape. The dominant areas of investigations are identified as antimicrobial activity, antibacterial mechanism of action, antifungal mechanism of action, extraction methods and phytochemistry, use in the food industry, and for oral and dental anti-infective activity. Specific research areas, which require future attention include; antituberculosis research, nanoparticle formulation of antimicrobial active VP molecules, preclinical and clinical trials. The antimicrobial testing of isoeugenol was found to be the least studied of the VPs and this requires further attention. [Display omitted] • A bibliometric analysis of four volatile phenolics over 35-year period is presented. • Thymol, carvacrol, eugenol and isoeugenol reviewed, isoeugenol requires future attention. • Antimicrobial mechanistic actions and combination studies are explored. [ABSTRACT FROM AUTHOR]