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Bufalin is an anticancer drug extract from traditional Chinese medicine. Several articles about bufalin have been published. However, the literature on bufalin has not yet been systematically studied. This study aimed to identify the study status and knowledge structures of bufalin and to summarize the antitumor mechanism. Data were retrieved and downloaded from the PubMed database. The softwares of BICOMB, gCLUTO, Ucinet 6.0, and NetDraw2.084 were used to analyze these publications. The bufalin related genes were recognized and tagged by ABNER software. Then these BF-related genes were performed by Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis, and protein-protein interaction (PPI) network analysis. A total of 474 papers met the search criteria from 2000 to 2019. By biclustering clustering analysis, the 50 high-frequency main MeSH terms/subheadings were classified into 5 clusters. The clusters of drug therapy and the mechanism of bufalin were hotspot topics. A total of 50 genes were identified as BF-related genes. PPI network analysis showed that inducing apoptosis was the main effect of bufalin, and apoptosis-related gene Caspase 3 was the most reported by people. Bufalin could inhibit the proliferation, invasion, and metastasis of cancer cells through multiple signaling pathways, such as PI3K/AKT, Hedgehog, MAPK/JNK, Wnt/$\beta$-catenin, TGF-$\beta$/Smad, Integrin signaling pathway, and NF-KB signaling pathway via KEGG analysis. Through the quantitative analysis of bufalin literature, we revealed the research status and hot spots in this field and provided some guidance for further research.

The aim of this study was to analyze the research hotspots and mechanisms of luteolin in tumor-related fields using bibliometric and bioinformatic approaches to guide future research. We conducted a comprehensive screening of all articles on luteolin and tumors in Web of Science from 2008 to 2023. The extracted words from these publications were visualized using VOSviewer, Scimago Graphica, and CiteSpace. Public databases were used to collect luteolin and tumor-related targets. GO and KEGG analyses of luteolin antitumor-related genes were performed using Metascape. Protein interaction networks were built with Cytoscape and STRING, identifying hub targets of luteolin in antitumor activity. Subsequently, the binding capacity of luteolin to these hub targets was assessed using molecular docking technology. We found that China dominated this field, the Egyptian Knowledge Bank published the most articles, and Molecules had the highest number of related publications. Recently, network pharmacology, target, traditional Chinese medicine, and nanoparticles have become research hotspots in luteolin’s antitumor research. A total of 483 overlapping genes between luteolin and tumors were identified, and they were closely associated with the cancer-associated pathways, PI3K-Akt, and MAPK signaling pathways. Luteolin forms a complex network of antitumor-related genes, with TP53, TNF, STAT3, AKT1, JUN, IL6, and SRC playing key roles and showing strong binding affinity to luteolin. Computer technology is becoming increasingly integral to the discipline, and future research will focus on more precise antitumor mechanisms and effective clinical applications.

Population ageing and its influence on the economic growth has long been the focus of major concern. Using bibliometric techniques we found that: (1) although ageing has increasingly attracted more researchers within economics literature, the relative weight of ageing and economic growth related papers does not evidence a clear positive trend; (2) recent studies reveal the willingness of researchers to evaluate less immediate mechanisms relating ageing and economic growth; (3) the increase in the use of empirical methods reflects a trend to test economic phenomena with real-world data against the theory; (4) very few studies focus on developing and less developed countries.

The global financial crisis that followed Lehman Brothers’ declaration of bankruptcy in September 2008 critically highlighted the significance of research on systemic risk and macro-prudential supervision. Accordingly, this paper mainly analyzed the relationship between financial crises and the article output in financial crisis research through the application of bibliometrics. The occurrence of a financial crisis leads to changes in the output of articles on crisis and risks. Hence, we focused on bibliographic coupling (e.g., co-authorship, co-occurrence), data classification by risk type in this study (e.g., market risk, credit risk) and citation analysis (e.g., top 1% cited paper). Meanwhile, the analysis indicated the most relevant disciplines in financial crisis research. For example, the number of top 1% cited articles and citations, MARKET RISK documents and citations published the most papers. In other words, the market risk is valued in the financial risk literature.

The purpose of this paper is to retrieve and study the highly cited papers as well as the correlation between the citation frequency and the download frequency of the 20 traditional Chinese medicine journals in China, in order to provide the guidance for improving the influence and academic quality of these journals.

Bibliometric analyses were conducted on 1103 papers of 20 traditional Chinese medicine journals from 2011 to 2020 by retrieving for the China Academic Journal Network Publishing Database (CAJD) in China National Knowledge Infrastructure (CNKI). SPSS 17.0 software was used to analyze the correlation between the citation frequency and the download frequency via conducting regression fitting and establishing the mathematical models.

The results showed that the total citations of the 1103 papers were 93051 times and the average citations were 84.36 times per paper. The total downloads of the 1103 papers were 2058442 times, and the average downloads were 1866.22 times per paper. China Journal of Chinese Materia Medica ranked first according to the number of papers, total citations and total downloads. The citations of Journal of Chinese Medicinal Materials ranked first based on the number of citations per paper. One of Li’s paper had been cited the most (983 times). There were 629 (57.03%) papers whose first author was from universities. The scopes of the first authors were distributed in 29 regions and 2 special administrative regions (Macao, Hong Kong) in China. The authors from Beijing published 283 (25.66%) papers, ranking number one. The number of papers supported by funds was 882 (79.96%). The research results of correlation showed that the citation frequency and the download frequency of the highly cited papers had a highly positive correlation from both journal and paper level for whether the sample data of journals was normally distributed or nonnormally distributed. The correlation coefficients of the 20 journals at journal level and that at paper level were 0.9765 and 0.6677, respectively. The correlation was better at journal level than that at paper level, while the optimal regression fitting was all cubic polynomial. Among the 1103 papers, there were 684 (62.01%) research papers and 419 (37.99%) review papers. The main citation period of the top 15 papers was from the 2nd year to the 6th year after publication, accounting for 78.39%.

Papers on clinical therapeutics research, papers on the pharmacological effects and its mechanism of traditional Chinese medicine, and papers on traditional Chinese medicine and natural medicine were the main source of the highly cited papers of the traditional Chinese medicine journals. Editors of the journals should focus on the above-mentioned research areas to select manuscripts for exploiting the excellent sources extensively, while paying attention to review papers, focusing on national major or key projects, paying attention to network spreading, stabilizing authors with quality services, in order to improve the influence and the academic quality of journals.

Database Tomography (DT) is a textual database analysis system consisting of two major components: (1) algorithms for extracting multiword phrase frequencies and phrase proximities (physical closeness of the multiword technical phrases) from any type of large textual database, to augment (2) interpretative capabilities of the expert human analyst. DT was used to derive technical intelligence from a Nonlinear Dynamics database derived from the Science Citation Index/Social Science Citation Index (SCI). Phrase frequency analysis by the technical domain experts provided the pervasive technical themes of the Nonlinear Dynamics database, and the phrase proximity analysis provided the relationships among the pervasive technical themes. Bibliometric analysis of the Nonlinear Dynamics literature supplemented the DT results with author/journal/institution publication and citation data.

Database Tomography (DT) is a textual database analysis system consisting of two major components: (1) algorithms for extracting multi-word phrase frequencies and phrase proximities (physical closeness of the multi-word technical phrases) from any type of large textual database, to augment (2) interpretative capabilities of the expert human analyst. DT was used to obtain technical intelligence from a Fractals database derived from the Science Citation Index/Social Science Citation Index (SCI). Phrase frequency analysis by the technical domain experts provided the pervasive technical themes of the Fractals database, and the phrase proximity analysis provided the relationships among the pervasive technical themes. Bibliometric analysis of the Fractals literature supplemented the DT results with author/journal/institution publication and citation data.

In this paper, a bibliometric study of the computational intelligence field is presented. Bibliometric maps showing the associations between the main concepts in the field are provided for the periods 1996–2000 and 2001–2005. Both the current structure of the field and the evolution of the field over the last decade are analyzed. In addition, a number of emerging areas in the field are identified. It turns out that computational intelligence can best be seen as a field that is structured around four important types of problems, namely control problems, classification problems, regression problems, and optimization problems. Within the computational intelligence field, the neural networks and fuzzy systems subfields are fairly intertwined, whereas the evolutionary computation subfield has a relatively independent position.

Since the International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems published its first issue in 1993, it has made important contributions to the research field of computer science. In this study, based on the dataset of the publications published in this journal between 1993 and 2016 retrieved from Web of Science, a general overview of this journal is performed using bibliometric methods and visualized networks. First, the productive and influential publications, authors, institutions, countries/territories, and supraregions are analysed based on the total number of citations, publications, and different citation thresholds. Second, network visualization analysis is applied to illustrate the links and connections between terms by using the VOSviewer software. Moreover, the most cited journals and common author keywords of three continents, including North America, Europe, and Asia, are also presented. This paper will hopefully help researchers understand the research patterns of this journal.

The objective of this study was to provide an assessment of published studies on the wrist arthroscopy. The search was performed from the "Web of Science (WoS) Science Citation Expanded Database" with studies published between January 1, 1990 and March 31, 2011. For research we used the following terms: "Wrist arthroscopy" and "Arthroscopy of the wrist". We located a total of 426 studies about wrist arthroscopic, published in 89 journals over the study period. Of all the publications retrieved (426), original articles were 387 (90.84%), but only two (0.47%) were randomised controlled trials, level 1 of evidence.

This study showed there are a large number of studies on wrist arthroscopy, but the level of methodological evidence is low.

Image engineering is a discipline that includes image processing, image analysis, image understanding, and the applications of these techniques. To promote its development and evolvement, this paper provides a well-regulated explanation of the definition of image engineering, as well as its intention and extension. It also introduces a new classification of the theories of image engineering, and the applications of image technology. A thorough statistical survey on the publications in this discipline is carried out, and an analysis and discussion of the statistics from the classification results are presented. This work shows a general and an up-to-date picture of the status, progress, trends and application areas of image engineering.

Objective: This study used CiteSpace to look at the current state of research on epilepsy and synaptic plasticity and to point out the hotspots and frontiers. Method: We searched Web of Science (WoS) for studies related to epilepsy and synaptic plasticity. CiteSpace was used to construct network maps of cooperation across countries, institutions, and authors to identify frontiers and hotspots in epilepsy and synaptic plasticity research. Results: A total of 1700 studies on epilepsy and synaptic plasticity were retrieved from the WoS. The United States and Baylor College of Medicine were the most prolific nation and institution in this field with 680 and 28 publications, respectively. The most prolific author (11 articles) was Xuefeng Wang. The Journal of Neuroscience published the most articles (71, 6.71%) and had the most co-citations (1557, 4.57%). In this paper, the interaction and mechanism between epilepsy and synaptic plasticity, as well as future research hotspots, are highlighted. Conclusion: CiteSpace can reveal the institutions, leaders, journals, cited papers, and research hotspots involved in epilepsy and synaptic plasticity. To the best of our knowledge, this is the first study that visualizes the relationship between epilepsy and synaptic plasticity and provides references for future research directions.

Evolutionary studies of cultural complexity often assume that group members select the best information available in the group, effectively diffusing the best innovations, whose advantages are subsequently passed on to the next generation. This would seem to describe the ideal of the scientific process — each cohort of papers in a field surfacing the best innovations, refining them and passing on to the next “layer” or cohort of scientific works. Here, we use academic journal databases to explore this “forking” (branching) process in the evolution of a scientific paradigm. We apply citation network visualization and Latent Dirichlet allocation topic analysis to three different paradigms defined pragmatically as the set of papers citing a highly influential paper in each respective case. Our three case studies indicate a founder effect in how the seminal paper is highly-embedded in the citation network, and yet peripheral to the evolution of topics in subsequent “layers” of publications within the paradigm. This and additional evidence suggest certain topics are selected and followed, while others are left behind. From these case studies, we discuss how hitherto undeveloped ideas of the past might be located in the topic space of seminal works of the same fruitful time period.

A recent highly publicized study [Park, M., Leahey, E. and Funk, R. J., Papers and patents are becoming less disruptive over time, Nature613 (2023) 138–144] claiming that science has become less disruptive over recent decades represents an extraordinary achievement but with deceptive results. The measure of disruption, CD₅, in this study does not account for differences in citation amid decades of exponential growth in publication rate. In order to account for both the exponential growth as well as the differential impact of research works over time, here we apply a weighted disruption index to the same dataset. We find that, among research papers in the dataset, this weighted disruption index has been close to its expected neutral value over the last fifty years and has even increased modestly since 2000. We also show how the proportional decrease in unique words is expected in an exponentially growing corpus. Finding little evidence for recent decrease in disruption, we suggest that it is actually increasing. Future research should investigate improved definitions of disruption.

Bibliometric studies based on the Web of Science (WOS) database have become an increasingly popular method for analyzing the structure of scientific research. So do network approaches, which, based on empirical data, make it possible to characterize the emergence of topological structures over time and across multiple research areas. Our paper is a contribution to interweaving these two lines of research that have progressed in separate ways but whose common applications have been increasingly frequent. Among other attributes, Author Keywords and Keywords Plus® are used as units of analysis that enable us to identify changes in the topics of interest and related bibliography. By considering the co-occurrence of those keywords with the Author Keyword Complexity, we provide an overview of the evolution of studies on Complexity Sciences, and compare this evolution in seven social and natural scientific fields. The results show a considerable increase in the number of papers dealing with complexity, as well as a general tendency across different disciplines for this literature to move from a more foundational, general and conceptual to a more applied, specific and empirical set of co-occurring keywords. Moreover, we provide evidence of changing topologies of networks of co-occurring keywords, which are described through the computation of some topological coefficients. In so doing, we emphasize the distinguishing structures that characterize the networks of the seven research areas.

Electronic journal databases allow efficient retrieval and processing of bibliometric data, making possible enhanced literature reviews called research profiling studies. We have conducted such a research profiling study of Multiple Criteria Decision Making (MCDM) using the ISI Web of Science. The ISI database covers close to 9000 publications, mainly journals. We report statistics regarding how the MCDM field has developed based on variations of a set of rather broad search words. We have also produced detailed correlation maps based on most cited authors for different decades, showing the birth and evolution of different schools of thought. We seek to provide the "big picture" of MCDM. Our study shows that the field has experienced exponential growth. At the same time it has penetrated other neighboring domains of knowledge, such as Information and Communication Technologies and engineering.

Multi-criteria decision making (MCDM) is a sub-discipline of operations research aimed at evaluating alternatives in consideration of various criteria. It is used by practically everyone in their daily lives and professional settings. Seeing the great value of MCDM, we conduct a comprehensive review to propel its innovation and development forward. Compared with any other reviews, we do not focus on introducing its methods, but on tracing its evolution and characteristics. As a general rule, every discipline has its own developing laws. They can be understood on various levels and can point out the direction the discipline is heading for. We firmly believe that our work can bring insight into MCDM’s frontiers and trend, which can eventually provide guidance on how to conduct the future research. In the first half of the paper, we investigate MCDM’s paradigm through literature review and colloquially divide its story into four stages: the Stone Age, the Iron Age, the Industrial Age and the New Stage. The first three stages symbolise its debut, growth and prosperity. Each one has distinctive thoughts, techniques and application, and to some extent hints the major works of the next stage. Since the turn of the 21st century, the paradigm has been once again experiencing dramatic changes, suggesting that it is on the threshold of a new era. Thus, in the second half of the work, a bibliometric analysis of the present stage ensues. Put simply, we take a global view of the stage by visualizing the stage’s publication quantity, publication distribution, and research categories. Then we design a snowballing co-citation method to explore its movements. The results demonstrate that MCDM is a dynamic, worldwide study for which China is the most productive country and the USA plays a pivot role in scholar communication. Method reviews, straightforward methods and MCDM-oriented fuzzy sets are predominant frontiers. The application, however, always changes with the requirements of the times. Now, it mainly refers to energy, environment, and supplier selection, while issues like sociology, tourism, education, etc. also emerge at a fast speed. Apart from this, experts have gradually shaken off the fetters of the traditional research style and are increasingly willing to structure methods and select application areas with a more personal touch. In the future, how to improve reviews, methods and fuzzy sets, how to understand and draw inspirations from society needs, and how experts can tailor MCDM to accommodate specific problems might be the pressing concerns.

The International Journal of Information Technology and Decision Making (IJITDM) was launched in 2002 to study how the information technology and decision-making technique affect each other. To summarize the progress of the journal in the latest 11 years, a bibliometric overview of the IJITDM publications from 2012 to 2022 is provided to identify the conceptual evolution and development situation of the journal during this time slot. To do this, first, the publication and citation structures of the publications in this journal is presented. Then, the scientific network map analysis, including keywords analysis, co-authorship analysis and co-citation analysis, is performed in details. Furthermore, the development trends of information technologies and decision-making methods are discussed to dig out factors that influence the evolution of topics in IJITDM publications. Finally, conclusions of this study are offered. It is found that the IJITDM grew significantly from 2012 to 2022. The work presented in this paper will help scholars to obtain systematic knowledge and structured understanding of the research hotspots and development trends of the journal.

In 2002, Tom Wilson argued about knowledge management (KM) "that the bandwagon lacks wheels". In the same issue of the same journal, Leonard Ponzi and Michael Koenig posited that KM was perhaps "in the process of establishing itself as a new aspect of management". Who was correct? This article examines bibliographic evidence to conclude that the latter interpretation was correct, that KM has firmly established itself as a major, and to the extent that permanence can be established in this rapidly changing world, permanent component of management. It then argues that the reasons for KM's permanence all fundamentally derive from the common sense of KM.

This paper aims to represent the bibliometric characteristics of the American Historical Review (AHR) in an attempt to highlight the journal's contribution to the field of History as one of the leading journals in Journal Citation Reports (JCR). AHR has the highest impact factor among the other journals in its field, and has been bringing together scholars from all over the world since 1895. Although the field of History is known as localized and non-interdisciplinarity, the present study's findings reveal that AHR has different characteristics compared to traditional contributions to the field of History by other journals. In addition, the results show that approximately three quarters of AHR citations, from 67 different categories, are gathered by articles. This indicates that AHR has an increased degree of convergence with other disciplines. These findings may be interpreted as an indication that traditional historical scholarly communication is increasingly changing toward interdisciplinarity. However, it would be problematic to generalize these findings for all history literature, based on a single journal evaluation. This study suggests that AHR has become increasingly diversified and consequently no longer reflects the main characteristics of the field of History. Future studies of more History journals are needed to validate the results and reveal possible changes in the field.