Research Frontiers Research Articles

Bibliometrics analysis and knowledge mapping of pertussis vaccine research: trends from 1994 to 2023.

This study aims to use bibliometric methods to explore the evolving landscape, hotspots, and emerging frontiers of pertussis vaccine research, providing deeper insights into the current research landscape and guiding future vaccine development efforts. We conducted a comprehensive search of the Web of Science Core Collection database (WoSCC) from January 1, 1994, to December 31, 2023, employing search terms related to vaccination (vacc* or immun*) and pertussis (pertussis, Whooping Cough, Bordetella pertussis, B. pertussis, Bordetella pertussis infection, or B. pertussis infection) in the Title or Author keywords fields. Bibliometrics analysis of pertussis research was performed utilizing the bibliometrix-biblioshiny package in RStudio, alongside CiteSpace and VOSviewer software. In total, 2,623 records were analyzed, comprising 89.63% (n = 2,351) original research articles and 10.37% (n = 272) review articles. The study revealed that academic research on the pertussis vaccine was growing at a rate of 4.64% per year. The United States and Canada lead in the number of publications. GlaxoSmithKline and the Centers for Disease Control & Prevention- United States emerged as leading institutions, with Halperin SA and Locht C as the most active authors. Vaccine was the most influential journal. Most studies focused on vaccine effectiveness duration, vaccination schedules for high-risk groups, and people's attitudes toward vaccination. Our analysis showed increasing interest of researchers in pertussis literature, yet current research mainly emphasized expanding vaccine coverage and optimizing strategies, neglecting new vaccine development. This emphasized the need for prioritizing novel pertussis vaccines to tackle the resurgence challenge.

Analysis of the evolution of placental oxidative stress research from a bibliometric perspective.

Research on placental oxidative stress is pivotal for comprehending pregnancy-related physiological changes and disease mechanisms. Despite recent advancements, a comprehensive review of current status, hotspots, and trends remains challenging. This bibliometric study systematically analyzes the evolution of placental oxidative stress research, offering a reference for future studies. To conduct a comprehensive bibliometric analysis of the literature on placental oxidative stress to identify research hotspots, trends, and key contributors, thereby providing guidance for future research. Relevant data were retrieved from the Web of Science Core Collection database and analyzed using VOSviewer, CiteSpace, and the bibliometrix package. An in-depth analysis of 4,796 publications was conducted, focusing on publication year, country/region, institution, author, journal, references, and keywords. Data collection concluded on 29 April 2024. A total of 4,796 papers were retrieved from 1,173 journals, authored by 18,835 researchers from 4,257 institutions across 103 countries/regions. From 1991 to 2023, annual publications on placental oxidative stress increased from 7 to 359. The United States (1,222 publications, 64,158 citations), the University of Cambridge (125 publications, 13,562 citations), and Graham J. Burton (73 publications, 11,182 citations) were the most productive country, institution, and author, respectively. The journal Placenta had the highest number of publications (329) and citations (17,152), followed by the International Journal of Molecular Sciences (122 publications). The most frequent keywords were "oxidative stress," "expression," "pregnancy," "preeclampsia," and "lipid peroxidation." Emerging high-frequency keywords included "gestational diabetes mellitus," "health," "autophagy," "pathophysiology," "infection," "preterm birth," "stem cell," and "inflammation." Over the past 3decades, research has concentrated on oxidative stress processes, antioxidant mechanisms, pregnancy-related diseases, and gene expression regulation. Current research frontiers involve exploring pathophysiology and mechanisms, assessing emerging risk factors and environmental impacts, advancing cell biology and stem cell research, and understanding the complex interactions of inflammation and immune regulation. These studies elucidate the mechanisms of placental oxidative stress, offering essential scientific evidence for future intervention strategies, therapeutic approaches, and public health policies.

Ultrasound for breast cancer detection: A bibliometric analysis of global trends between 2004 and 2024.

With the advancement of computer technology and imaging equipment, ultrasound has emerged as a crucial tool in breast cancer diagnosis. To gain deeper insights into the research landscape of ultrasound in breast cancer diagnosis, this study employed bibliometric methods for a comprehensive analysis spanning from 2004 to 2024, analyzing 3523 articles from 2176 institutions in 82 countries/regions. Over this period, publications on ultrasound diagnosis of breast cancer showed a fluctuating growth trend from 2004 to 2024. Notably, China, Seoul National University and Kim EK emerged as leading contributors in ultrasound for breast cancer detection, with the most published and cited journals being Ultrasound Med Biol and Radiology. The research spots in this area included "breast lesion", "dense breast" and "breast-conserving surgery", while "machine learning", "ultrasonic imaging", "convolutional neural network", "case report", "pathological complete response", "deep learning", "artificial intelligence" and "classification" are anticipated to become future research frontiers. This groundbreaking bibliometric analysis and visualization of ultrasonic breast cancer diagnosis publications offer clinical medical professionals a reliable research focus and direction.

Learnable self-supervised support vector machine based individual selection strategy for multimodal multi-objective optimization

Multimodal multi-objective optimization problem (MMOP) is a frontier research problem, which can provide decision makers with more choices without making trade-offs. Many multimodal multi-objective evolutionary algorithms (MMOEAs) have been proposed to solve MMOP. However, most MMOEAs tend to prioritize the objective dominance of individuals in the process of individual selection, and only individuals with the same objective dominance will be considered the diversity, which leads to the loss of many promising solutions. To solve the above problem, this paper proposes a learnable self-supervised support vector machine (SVM) based multimodal multi-objective optimization algorithm (SVMEA). Support vector machine can learn the knowledge about distinguishing the advantages and disadvantages of individuals from the data in the existing training set and select individuals, in which the objective dominance of individuals is as important as diversity. Moreover, a crowding distance calculation method based on Manhattan distance is designed. Compared with the traditional method using Euclidean distance to calculate crowding distance, it can better evaluate the diversity of individuals in the decision space and assist the selection of elite solutions. Experimental results show that the proposed SVMEA is competitive with seven other advanced MMOEAs on 34 benchmark problems and a practical application problem.

Circularly Polarized Organic Ultralong Room‐Temperature Phosphorescence: Generation, Enhancement, and Application

AbstractCircularly polarized luminescent (CPL) materials have garnered tremendous attention owing to their expanded optical properties beyond emission wavelength and intensity. Among these, the emerging circularly polarized organic ultralong room‐temperature phosphorescence (CP‐OURTP) materialsdemonstrating elegant and distinct features are of significant importance for their extended emission lifetime, which represent a novel frontier in research with promising scientific and technological applications across diverse fields. This review systematically outlines the traditional strategies to achieve CP‐OURTP including organic crystals, copolymerization, host–guest doping, a combination of the copolymerization and host–guest doping, spinning and twisting technology, and supramolecular polymer assembly. Importantly, the recent significant progress of CP‐OURTP in the chiral soft materials, such as liquid crystals (LCs) involving lyotropic LCs (cellulose nanocrystals, CNCs) and chiral thermotropic LCs (cholesteric LCs and chiral LC elastomers), is showcased. Finally, the practical applications of CP‐OURTP materials are summarized, and the review concludes with the perspectives on the current challenges and future opportunities for CP‐OURTP materials. This review aims to inspire the further innovations in the fabrication of advanced CP‐OURTP materials and enrich their promising applications.

Forensic Diatom Analysis: Where Do We Stand and What Are the Latest Diagnostic Advances?

Background: diatoms are unicellular algae that have been used for more than a century for forensic purposes to diagnose drowning, with more or less success depending on the historical era. Although many years have passed, scientific research on diatoms has never ceased, which testifies to their enduring allure in forensics. Of course, diatom research has evolved and expanded over time, changing with the availability of new techniques and technologies. The volume of articles and their production over a period of many years has resulted in old, current, and new knowledge on diatoms being scattered over a large number of books and articles. Objectives: the purpose of this narrative literature review is, therefore, to summarize all this information and bring it together in a single work that can be useful for those who are studying diatoms and their usefulness for forensics for the first time, for those who are looking for proven methods of analysis, and finally for those who are interested in exploring new frontiers of research. Methods: a comprehensive literature search that included all studies dealing with the applications of diatoms in forensic science was performed in the most popular electronic databases. Results: traditional methods have been complemented by molecular and imaging methods and, more recently, by artificial intelligence. In addition, new biological substrates have been found for the analysis of diatoms. Conclusions: all this has led, on the one hand, to the consolidation of a whole body of knowledge on diatoms, on which this forensic analysis is still based, and, on the other hand, has opened up numerous new research directions.

Research trends in nutritional interventions for stroke: a bibliometric analysis and literature review.

Over the past 23 years, there has been a thorough analysis of literature concerning nutritional interventions, nutrients, and feeding approaches related to stroke. Furthermore, a scientific knowledge map was established, elucidating the current state of research, examining its development and trends, and offering new research viewpoints for the future. This study aimed to investigate global and emerging research trends in nutritional interventions for stroke from 2000 to 2023 through bibliometric analysis. A bibliometric analysis of literature from the Core Collection of Scientific Networks for the years 2000-2022 was conducted. CiteSpace, VOSviewer, and bibliometric graphical software were used to identify major contributors to publications, including authors, countries, institutions, journals, references, and keywords. The bibliometric analysis yielded a total of 464 publications. This is a gradually increasing number in terms of the number of publications during the study period. China had the highest number of publications. Clinical Nutrition" was the journal with the highest number of relevant publications, and the most commonly used keywords were "stroke," "nutrition" and "malnutrition." These analyses reveal research trends in nutritional therapy for stroke from 2000 to 2023 and point to prospective research frontiers. This study provides a deeper understanding of what nutritional treatment of stroke entails and provides guidance and support for future research in this area.

Visualising research trends and hotspots in ferroptosis: a decade of insights into iron-dependent cell death and clinical diseases

ObjectiveTo explore the research hotspots and frontier trends of ferroptosis and its association with clinical diseases both in China and internationally over the past decade.MethodsUtilizing the CNKI, PubMed, and Web of Science literature databases as data sources, we employed CiteSpace 6.2.R4 and VOSviewer software to visualize and analyze the authors, institutions, countries, and keywords related to ferroptosis and clinical diseases from 2013 to 2023.ResultsChina Medical University has published the highest number of studies in the field of ferroptosis and clinical diseases in China. Furthermore, China leads globally in attention to this research area. In 2022, domestic and international scholars exhibited the closest collaboration in this field. The year 2020 saw the most extensive range of sub-studies on ferroptosis and clinical diseases both at home and abroad. The keywords "cancer" and "long non-coding RNAs (LncRNAs)" emerged as the most prominent research topics in recent years.ConclusionFuture research on ferroptosis-related diseases, including cancer, heart failure, type 2 diabetes, and Alzheimer's disease, should further investigate the regulatory mechanisms linking ferroptosis with mitochondria, the Golgi apparatus, and multi-site LncRNA interactions. This could provide valuable insights for subsequent studies on cancer and other diseases in the context of ferroptosis.

Boosting Light-Matter Interactions in Plasmonic Nanogaps.

Plasmonic nanogaps in strongly coupled metal nanostructures can confine light to nanoscale regions, leading to huge electric field enhancement. This unique capability makes plasmonic nanogaps powerful platforms for boosting light-matter interactions, thereby enabling the rapid development of novel phenomena and applications. This review traces the progress of nanogap systems characterized by well-defined morphologies, controllable optical responses, and a focus on achieving extreme performance. The properties of plasmonic gap modes in far-field resonance and near-field enhancement are explored and a detailed comparative analysis of nanogap fabrication techniques down to sub-nanometer scales is provided, including bottom-up, top-down, and their combined approaches. Additionally, recent advancements and applications across various frontier research areas are highlighted, including surface-enhanced spectroscopy, plasmon-exciton strong coupling, nonlinear optics, optoelectronic devices, and other applications beyond photonics. Finally, the challenges and promising emerging directions in the field are discussed, such as light-driven atomic effects, molecular optomechanics, and alternative new materials.

Nanozyme-enhanced enzyme control: Computational strategies for precise and sustained enzymatic activity in tissue engineering

Nanomaterials are revolutionizing tissue engineering by significantly enhancing enzyme-mediated chemical processes and cellular activities, thereby advancing the development of more effective therapeutic strategies. This research delves into the intricate dynamics of enzyme diffusion within tissue matrices, providing a comprehensive computational modeling framework aimed at optimizing enzyme concentration control in tissue scaffolds. Through advanced numerical algorithms and computational analysis, the study simulates optimal control strategies for regulating nanozyme levels, ensuring precise and sustained enzymatic activity within the scaffolds. A novel aspect of this work is the integration of videographic records, which offers an enriched understanding of the complex interactions between nanomaterials and biological tissues, providing detailed insights into the system’s operational dynamics. The study bridges the gap between experimental methodologies and theoretical models, aligning with the cutting-edge research in chemical physics and physical chemistry by offering novel approaches to tissue engineering challenges. The findings underscore the critical role of nanomaterials in achieving precise enzymatic control, which is pivotal for the development of advanced biomimetic systems and improved therapeutic outcomes. This work contributes to the ongoing frontier research in physical phenomena within chemistry, biology, and materials science, by providing significant new insights into enzyme delivery mechanisms and their application in biomedical contexts. The research not only highlights the importance of innovative methodologies in tissue engineering but also sets the stage for future experimental validations and potential clinical applications

Medical Education and Artificial Intelligence: Web of Science-Based Bibliometric Analysis (2013-2022).

Incremental advancements in artificial intelligence (AI) technology have facilitated its integration into various disciplines. In particular, the infusion of AI into medical education has emerged as a significant trend, with noteworthy research findings. Consequently, a comprehensive review and analysis of the current research landscape of AI in medical education is warranted. This study aims to conduct a bibliometric analysis of pertinent papers, spanning the years 2013-2022, using CiteSpace and VOSviewer. The study visually represents the existing research status and trends of AI in medical education. Articles related to AI and medical education, published between 2013 and 2022, were systematically searched in the Web of Science core database. Two reviewers scrutinized the initially retrieved papers, based on their titles and abstracts, to eliminate papers unrelated to the topic. The selected papers were then analyzed and visualized for country, institution, author, reference, and keywords using CiteSpace and VOSviewer. A total of 195 papers pertaining to AI in medical education were identified from 2013 to 2022. The annual publications demonstrated an increasing trend over time. The United States emerged as the most active country in this research arena, and Harvard Medical School and the University of Toronto were the most active institutions. Prolific authors in this field included Vincent Bissonnette, Charlotte Blacketer, Rolando F Del Maestro, Nicole Ledows, Nykan Mirchi, Alexander Winkler-Schwartz, and Recai Yilamaz. The paper with the highest citation was "Medical Students' Attitude Towards Artificial Intelligence: A Multicentre Survey." Keyword analysis revealed that "radiology," "medical physics," "ehealth," "surgery," and "specialty" were the primary focus, whereas "big data" and "management" emerged as research frontiers. The study underscores the promising potential of AI in medical education research. Current research directions encompass radiology, medical information management, and other aspects. Technological progress is expected to broaden these directions further. There is an urgent need to bolster interregional collaboration and enhance research quality. These findings offer valuable insights for researchers to identify perspectives and guide future research directions.

Scoping review of epigenetics on neurodegenerative diseases: research frontiers and publication status.

Epigenetics has significantly evolved and emerged as important players in the pathogenesis of neurodegenerative diseases. However, a scientometric synthesis of such changes over time is currently lacking. We conducted a comprehensive search of the Web of Science Core Collection from inception until November 5, 2022, using appropriate keywords. Our primary objective was to employ scientometric analysis to depict changes in keywords over time and to assess the structure and credibility of clusters. Additionally, we examined the network of research (countries, institutions, and authors) using CiteSpace and VOSviewer. We identified 25 clusters with well-structured networks (Q = 0.82) and highly credible clustering (S = 0.91) from 16,181 articles published between 1999 and 2022. Our findings are as follows: (a) the literature and research interest concerning the epigenetics of neurodegenerative diseases are continuously growing; (b) the three most productive countries are the USA, China, and Germany; (c) international collaborative relationships exist, alongside small, isolated collaboration networks of individual institutions. The number and impact of global publications on the epigenetics of neurodegenerative diseases have expanded rapidly over the past 20 years. This review provides valuable guidelines for researchers interested in neurodegenerative diseases research.

Global trends and performance of dry needling from 2004 to 2024: a bibliometric analysis.

Many doctors are incorporating dry needling into their clinical practice. Despite this growing trend, there has not been a comprehensive bibliometric analysis conducted in this field. Thus, this study aims to investigate the current research landscape, key research contributors, and popular research topics in dry needling, and to analyze the developmental trends within this area of study. The study utilized the Web of Science Core Collection (WoSCC) as the main data source. Scientific literature was gathered through title (TI) searches for original clinical research papers on dry needling published between 2004 and 2024, using 'dry needling' or 'dry needle' as the search term. Statistical analyses and visualizations of the literature information, such as keywords, countries, research institutions, and authors, were conducted using the bibliometric.com online platform and VOSviewer. This approach aimed to statistically analyze and visualize the key research entities, hotspots, and frontiers in dry needling research. Additionally, the study delved into collaborative networks, research outputs, hot topics, and trends within the field of dry needling. This investigation encompassed 468 publications, with the year 2021 topping the charts for the highest publication output, amassing a total of 271 articles. The journal "Acupuncture in Medicine" emerged as the most frequently cited publication. The most impactful article was titled "Acupuncture and dry-needling for low back pain: An updated systematic review within the framework of the Cochrane Collaboration." Spain took the lead as the most productive country in this domain, with the United States closely following. Cesar Fernández-de-las-Peñas emerged as the most prolific author in the field. The Universidad Rey Juan Carlos in Spain was recognized as the most productive institution for research in dry needling. As for journal keywords, "dry needling," "trigger point," and "myofascial pain syn-drome" were the triumvirate of terms most recurrently encountered. The field of dry needling research has witnessed significant growth in recent years, characterized by the emergence of novel trends such as comparative studies with acupuncture, exploration into the mechanisms of action, and a transition toward interdisciplinary approaches. As medical models evolve, the focus is expanding from the exclusive treatment of muscle pain to broader applications. Despite this progress, the domain is underscored by a paucity of large-scale, multicenter clinical trials and animal studies. There exists an imperative for enhanced collaboration among academic and research institutions. A more profound exploration and comprehensive research endeavors are essential to enhance our understanding and broaden the clinical application of dry needling techniques.

It’s time to celebrate! Linking genetic resources to the Mexican National Biological Collections custodied by the Institute of Biology of the National Autonomous University of Mexico

The Instituto de Biología of the Universidad Nacional Autónoma de México (IBUNAM) celebrates 95 years as a leading institution on biodiversity research. Besides developing frontier research, training of human resources, and public science communication, IBUNAM houses 10 National Zoological Collections and the National Herbarium of Mexico (MEXU). The specimens deposited in these collections are the foundation of numerous biological studies, from which ample genetic resources have been generated. Here we present an initial effort to link the specimens deposited at the National Biological Collections housed at IBUNAM to their public genetic resources, using MEXU’s Collection of Types of Vascular Plants as proof of concept. First, a list of the type specimens was retrieved from IBdata, the web system for consulting the records of the biological collections housed at IBUNAM. Then, the interface Entrez Programming Utilities of GenBank was used to search for the available genetic resources associated with the type specimens. New fields were incorporated into IBdata to facilitate access to the identified genetic resources. Future initiatives should promote access to the public metadata (e.g., molecular, morphological) associated to specimens of the biological collections housed at IBUNAM.

Innovative strategies for characterizing and managing huanglongbing in citrus.

Huanglongbing is a severe citrus disease that causes significant tree and crop losses worldwide. It is caused by three Candidatus liberibacter species and spread by psyllids and infected budwood. Various methods have been used to diagnose and understand HLB, including recent advances in molecular and biochemical assays that explore the pathogen's mode of action and its impact on the host plant. Characterization is essential for developing sustainable HLB management strategies. Nanotechnology, particularly nano sensors and metal nanoparticles, shows potential for precise disease diagnosis and control. Additionally, antibiotics, nanomaterials, and genetic engineering techniques like transgenesis offer promising avenues for mitigating HLB. These diverse approaches, from conventional to cutting-edge, contribute to developing integrated HLB management strategies for sustainable citrus cultivation. The review highlights the significant advancements in conventional and advanced molecular and biochemical characterization of HLB, aiding in early detection and understanding of the infection mechanism. It emphasizes the multidimensional efforts required to characterize disease and devise innovative management strategies. As the citrus industry faces unprecedented challenges, exploring new frontiers in HLB research provides hope for sustainable solutions and a resilient future for global citrus cultivation.

Past, Present, and Future of Liver-Brain Axis in Alzheimer's Disease: ABibliometric Review.

No effective drugs currently exist to cure Alzheimer's disease (AD) due to its complexity and the lack of understanding of the involved molecular signaling and pathways. The relationship between liver health and AD is now widely recognized. Still, molecular links and shared pathways between the liver and brain remain unclear, making the liver-brain axis in AD therapies a new area for exploration. However, bibliometric studies on this topic are lacking. This study aims to review the liver-brain axis in AD and identify future research hotspots and trends through bibliometric analysis. Articles and reviews related to AD and liver and its related diseases were searched in the Web of Science Core Collection (WoSCC) database up to 2024. Data were processed and visually analyzed using VOSviewer, CiteSpace, and Pajek. We collected 1,777 articles on AD and liver and its related diseases from 2,517 institutions across 80 countries. Keyword cluster analysis identified 11 clusters, with 'insulin resistance,' 'amyloid-beta,' 'apolipoprotein-E,' 'oxidative stress,' and 'inflammation' appearing most frequently, and exhibiting strong total link strength. These results indicate that these topics have been the primary focus of research on the liver-brain axis in AD. This study is the first to comprehensively analyze the liver-brain axis in AD using bibliometric methods. The research results identify recent research frontiers and hotspots, aiding scholars in gaining a deeper understanding of the correlation between AD and the liver.

Triboelectric Nanogenerator for Self-Powered Gas Sensing.

With the continuous acceleration of industrialization, gas sensors are evolving to become portable, wearable and environmentally friendly. However, traditional gas sensors rely on external power supply, which severely limits their applications in various industries. As an innovative and environmentally adaptable power generation technology, triboelectric nanogenerators (TENGs) can be integrated with gas sensors to leverage the benefits of both technologies for efficient and environmentally friendly self-powered gas sensing. This paper delves into the basic principles and current research frontiers of the TENG-based self-powered gas sensor, focusing particularly on innovative applications in environmental safety monitoring, healthcare, as well as emerging fields such as food safety assurance and smart agriculture. It emphasizes the significant advantages of TENG-based self-powered gas sensor systems in promoting environmental sustainability, achieving efficient sensing at room temperature, and driving technological innovations in wearable devices. It also objectively analyzes the technical challenges, including issues related to performance enhancement, theoretical refinement, and application expansion, and provides targeted strategies and future research directions aimed at paving the way for continuous progress and widespread applications in the field of self-powered gas sensors.

The application of multimodal AI large model in the green supply chain of energy industry

With the accelerated advancements in artificial intelligence and the increasing emphasis on sustainable supply chain management, the integration of multimodal artificial intelligence (AI) into green supply chains has emerged as a critical research frontier. This study delves into the synergistic potential and challenges of combining multimodal AI, which leverages diverse data types such as text, images, and numerical data, to enhance decision-making processes in green supply chains. Through the meticulous design of a data strategy and model framework, this research establishes a sophisticated and efficient data processing and model training pipeline. The experimental results reveal that the comprehensive analysis and fusion of multimodal data significantly improve the prediction accuracy of key supply chain metrics, with observed increases in accuracy and recall rates by 12.4% and 9.8%, respectively. Additionally, the model's limitations are critically assessed, and targeted improvement strategies are proposed. The practical implications of this study are profound, offering actionable insights for the application of multimodal AI in real-world energy sector scenarios. The findings underscore the potential of this technology to optimize operations, reduce environmental impact, and drive sustainable growth in the energy industry.

Artificial intelligence alphafold model for molecular biology and drug discovery: a machine-learning-driven informatics investigation.

AlphaFold model has reshaped biological research. However, vast unstructured data in the entire AlphaFold field requires further analysis to fully understand the current research landscape and guide future exploration. Thus, this scientometric analysis aimed to identify critical research clusters, track emerging trends, and highlight underexplored areas in this field by utilizing machine-learning-driven informatics methods. Quantitative statistical analysis reveals that the AlphaFold field is enjoying an astonishing development trend (Annual Growth Rate = 180.13%) and global collaboration (International Co-authorship = 33.33%). Unsupervised clustering algorithm, time series tracking, and global impact assessment point out that Cluster 3 (Artificial Intelligence-Powered Advancements in AlphaFold for Structural Biology) has the greatest influence (Average Citation = 48.36 ± 184.98). Additionally, regression curve and hotspot burst analysis highlight "structure prediction" (s = 12.40, R2 = 0.9480, p = 0.0051), "artificial intelligence" (s = 5.00, R2 = 0.8096, p = 0.0375), "drug discovery" (s = 1.90, R2 = 0.7987, p = 0.0409), and "molecular dynamics" (s = 2.40, R2 = 0.8000, p = 0.0405) as core hotspots driving the research frontier. More importantly, the Walktrap algorithm further reveals that "structure prediction, artificial intelligence, molecular dynamics" (Relevance Percentage[RP] = 100%, Development Percentage[DP] = 25.0%), "sars-cov-2, covid-19, vaccine design" (RP = 97.8%, DP = 37.5%), and "homology modeling, virtual screening, membrane protein" (RP = 89.9%, DP = 26.1%) are closely intertwined with the AlphaFold model but remain underexplored, which implies a broad exploration space. In conclusion, through the machine-learning-driven informatics methods, this scientometric analysis offers an objective and comprehensive overview of global AlphaFold research, identifying critical research clusters and hotspots while prospectively pointing out underexplored critical areas.

Bibliometric analysis of chondrocyte apoptosis in knee osteoarthritis.

Apoptosis, a form of programmed cell death, plays a significant role in osteoarthritis; however, bibliometric studies in this field remain scarce. Bibliometrics provides a visual representation of research outcomes and trends, guiding future investigations. Journal data from January 1, 2013, to December 31, 2023, in this field were obtained from the Web of Science (WOS) core database. Analysis was conducted using VOSviewer and CiteSpace. Analysis revealed that over the past decade, 794 articles were published in 299 journals by 4447 authors from 49 countries and 877 institutions. The top contributors were China, the United States, and the United Kingdom. Zhuang Chao emerged as the most prolific author, and "osteoarthritis and cartilage" ranked as the most frequently cited journal. Keyword clustering focused on mechanisms, inflammation, and cartilage. The most-cited article was "chondrocyte apoptosis in the pathogenesis of osteoarthritis" in the "International Journal of Molecular Sciences." Burst word analysis highlighted extracellular matrix, circular RNA, micro RNA, indicating current research hotspots. Utilizing bibliometrics and visual analysis, we explored the hotspots and trends in the field of chondrocyte apoptosis in osteoarthritis. Extracellular matrix, Circular RNA, Micro RNA, among others, are likely to become future research focal points and frontiers.