Research Hotspot Research Articles

Hotspots and trends of risk factors in gastric cancer: A visualization and bibliometric analysis

BACKGROUND The lack of specific symptoms of gastric cancer (GC) causes great challenges in its early diagnosis. Thus it is essential to identify the risk factors for early diagnosis and treatment of GC and to improve the survival rates. AIM To assist physicians in identifying changes in the output of publications and research hotspots related to risk factors for GC, constructing a list of key risk factors, and providing a reference for early identification of patients at high risk for GC. METHODS Research articles on risk factors for GC were searched in the Web of Science core collection, and relevant information was extracted after screening. The literature was analyzed using Microsoft Excel 2019, CiteSpace V, and VOSviewer 1.6.18. RESULTS A total of 2514 papers from 72 countries and 2507 research institutions were retrieved. China (n = 1061), National Cancer Center (n = 138), and Shoichiro Tsugane (n = 36) were the most productive country, institution, or author, respectively. The research hotspots in the study of risk factors for GC are summarized in four areas, namely: Helicobacter pylori (H. pylori ) infection, single nucleotide polymorphism, bio-diagnostic markers, and GC risk prediction models. CONCLUSION In this study, we found that H. pylori infection is the most significant risk factor for GC; single-nucleotide polymorphism (SNP) is the most dominant genetic factor for GC; bio-diagnostic markers are the most promising diagnostic modality for GC. GC risk prediction models are the latest current research hotspot. We conclude that the most important risk factors for the development of GC are H. pylori infection, SNP, smoking, diet, and alcohol.

Mapping the intellectual structure and emerging trends for the application of nanomaterials in gastric cancer: A bibliometric study

BACKGROUND Recent reviews have outlined the main nanomaterials used in relation to gastrointestinal tumors and described the basic properties of these materials. However, the research hotspots and trends in the application of nanomaterials in gastric cancer (GC) remain obscure. AIM To demonstrate the knowledge structure and evolutionary trends of research into the application of nanomaterials in GC. METHODS Publications related to the application of nanomaterials in GC were retrieved from the Web of Science Core Collection for this systematic review and bibliometric study. VOSviewer and CiteSpace were used for bibliometric and visualization analyses. RESULTS From 2000 to 2022, the application of nanomaterials in GC developed rapidly. The keyword co-occurrence analysis showed that the related research topics were divided into three clusters: (1) The application of nanomaterials in GC treatment; (2) The application and toxicity of nanomaterials in GC diagnosis; and (3) The effects of nanomaterials on the biological behavior of GC cells. Complexes, silver nanoparticles, and green synthesis are the latest high-frequency keywords that represent promising future research directions. CONCLUSION The application of nanomaterials in GC diagnosis and treatment and the mechanisms of their effects on GC cells have been major themes in this field over the past 23 years.

Polycytosine RNA-binding protein 1 regulates osteoblast function via a ferroptosis pathway in type 2 diabetic osteoporosis

BACKGROUND Recently, type 2 diabetic osteoporosis (T2DOP) has become a research hotspot for the complications of diabetes, but the specific mechanism of its occurrence and development remains unknown. Ferroptosis caused by iron overload is con-sidered an important cause of T2DOP. Polycytosine RNA-binding protein 1 (PCBP1), an iron ion chaperone, is considered a protector of ferroptosis. AIM To investigate the existence of ferroptosis and specific role of PCBP1 in the development of type 2 diabetes. METHODS A cell counting kit-8 assay was used to detect changes in osteoblast viability under high glucose (HG) and/or ferroptosis inhibitors at different concentrations and times. Transmission electron microscopy was used to examine the morphological changes in the mitochondria of osteoblasts under HG, and western blotting was used to detect the expression levels of PCBP1, ferritin, and the ferroptosis-related protein glutathione peroxidase 4 (GPX4). A lentivirus silenced and overexpressed PCBP1. Western blotting was used to detect the expression levels of the osteoblast functional proteins osteoprotegerin (OPG) and osteocalcin (OCN), whereas flow cytometry was used to detect changes in reactive oxygen species (ROS) levels in each group. RESULTS Under HG, the viability of osteoblasts was considerably decreased, the number of mitochondria undergoing atrophy was considerably increased, PCBP1 and ferritin expression levels were increased, and GPX4 expression was decreased. Western blotting results demonstrated that infection with lentivirus overexpressing PCBP1, increased the expression levels of ferritin, GPX4, OPG, and OCN, compared with the HG group. Flow cytometry results showed a reduction in ROS, and an opposite result was obtained after silencing PCBP1. CONCLUSION PCBP1 may protect osteoblasts and reduce the harm caused by ferroptosis by promoting ferritin expression under a HG environment. Moreover, PCBP1 may be a potential therapeutic target for T2DOP.

Emerging trends of environmental accounting research: a science mapping approach

Purpose This paper aims to provide a comprehensive knowledge structure for environmental accounting (EA) research by identifying research hotspots and frontiers and suggesting future trends for scholarly investigation. Design/methodology/approach Using the bibliometric method, the paper analyzed 321 academic articles and reviews in international journals from the Scopus database. Science mapping, including strategic diagrams, network analysis and thematic maps, was used to analyze the evolution of topics and to recommend future research trends. Findings EA research is an emerging trend. This study presents the landscape of EA research by constructing the “synthesis house of knowledge” in EA. Significant EA research areas were identified and future research trends were suggested based on the results. Practical implications This paper provides insights into the current state of EA research and identifies potential future research trends that can help scholars and experts develop and stimulate further advancement of the research in this field. Social implications Results may motivate policymakers and government agencies to formulate regulations to enforce appropriate corporate environmental strategies to better manage environmental costs and reduce community environmental impact. Originality/value The study provides an intellectually structured literature review of the EA research field; identifies the main themes through the innovative use of network analysis, strategic diagrams and thematic maps; highlights research gaps; and offers potential research questions and suggestions for future research. The novelty of this paper lies in the “synthesis house of knowledge” in EA and the research gaps and potential and specific research questions constructed from the findings.

Taking SCFAs produced by Lactobacillus reuteri orally reshapes gut microbiota and elicits antitumor responses

BackgroundColorectal cancer (CRC) incidence is increasing in recent years due to intestinal flora imbalance, making oral probiotics a hotspot for research. However, numerous studies related to intestinal flora regulation ignore its internal mechanisms without in-depth research.ResultsHere, we developed a probiotic microgel delivery system (L.r@(SA-CS)2) through the layer-by-layer encapsulation technology of alginate (SA) and chitosan (CS) to improve gut microbiota dysbiosis and enhance anti-tumor therapeutic effect. Short chain fatty acids (SCFAs) produced by L.r have direct anti-tumor effects. Additionally, it reduces harmful bacteria such as Proteobacteria and Fusobacteriota, and through bacteria mutualophy increases beneficial bacteria such as Bacteroidota and Firmicutes which produce butyric acid. By binding to the G protein-coupled receptor 109A (GPR109A) on the surface of colonic epithelial cells, butyric acid can induce apoptosis in abnormal cells. Due to the low expression of GPR109A in colon cancer cells, MK-6892 (MK) can be used to stimulate GPR109A. With increased production of butyrate, activated GPR109A is able to bind more butyrate, which further promotes apoptosis of cancer cells and triggers an antitumor response.ConclusionIt appears that the oral administration of L.r@(SA-CS)2 microgels may provide a treatment option for CRC by modifying the gut microbiota.

Erianin inhibits the progression of triple-negative breast cancer by suppressing SRC-mediated cholesterol metabolism

Triple-negative breast cancer (TNBC) is highly malignant and lacks effective biotherapeutic targets. The development of efficient anticancer drugs with low toxicity and few side effects is a hotspot in TNBC treatment research. Although erianin is known to have potent antitumor activity, its regulatory mechanism and target in TNBC have not been fully elucidated, hampering further drug development. This study showed that erianin can significantly inhibit TNBC cell proliferation and migration, promote cell apoptosis, and inhibit the growth of transplanted tumors in mice. Mechanistically, through network pharmacology analysis, molecular docking and cellular thermal shift assays, we preliminarily identified SRC as the cellular target of erianin. Erianin potently inhibited the expression of SRC, which mediated the anticancer effect of erianin in TNBC. Moreover, erianin can downregulate the expression of genes related to cholesterol synthesis and uptake by targeting SRC, interfering with cholesterol levels in TNBC, thereby inhibiting the progression of TNBC in vivo and in vitro. Taken together, our results suggest that erianin may inhibit the progression of TNBC by suppressing SRC-mediated cholesterol metabolism, and erianin has the great potential to be an effective treatment for TNBC patients.

Global trends in research on aging associated with periodontitis from 2002 to 2023: a bibliometric analysis

BackgroundAging has been implicated in many chronic inflammatory diseases, including periodontitis. Periodontitis is an inflammatory disease caused by long-term irritation of the periodontal tissues by the plaque biofilm on the surface of the teeth. However, only a few bibliometric analyses have systematically studied this field to date. This work sought to visualize research hot spots and trends in aging associated with periodontitis from 2002 to 2023 through bibliometric approaches.MethodsGraphpad prism v8.0.2 was used to analyse and plot annual papers, national publication trends and national publication heat maps. In addition, CtieSpace (6.1.6R (64-bit) Advanced Edition) and VOSviewer (version 1.6.18) were used to analyse these data and visualize the scientific knowledge graph.ResultsThe number of documents related to aging associated with periodontitis has steadily increased over 21 years. With six of the top ten institutions in terms of publications coming from the US, the US is a major driver of research in this area. journal of periodontology is the most published journal in the field. Tonetti MS is the most prolific authors and co-cited authors in the field. Journal of Periodontology and Journal of Clinical Periodontology are the most popular journals in the field with the largest literature. Periodontitis, Alzheimer’s disease, and peri-implantitis are current hot topics and trends in the field. Inflammation, biomarkers, oxidative stress cytokines are current research hotspots in this field.ConclusionOur research found that global publications regarding research on aging associated with periodontitis increased dramatically and were expected to continue increasing. Inflammation and aging, and the relationship between periodontitis and systemic diseases, are topics worthy of attention.

Global trends and hotspots in research on acupuncture for neurodegenerative diseases over the last decade: a bibliometric and visualization analysis

ObjectivesThis study aimed to explore the current status and trends of acupuncture for neurodegenerative diseases (NDs) in the last decade and provide new insights for researchers in future studies.MethodsThe publications concerning acupuncture treatment for NDs published between 2014 and 2023 were extracted from the Web of Science Core Collection. We used CiteSpace and VOSviewer to analyze data on numbers of annual publications, countries, institutions, cited journals, cited authors, cited references, keywords, and citation bursts about acupuncture for NDs.ResultsA total of 635 publications were obtained from 2014 to 2023. We identified the most prolific journals, countries, institutions, authors, patterns of authorship, and the main direction of future research in the field of acupuncture for NDs in the last decade. The country, institution, and journal with the most publications are China (389 articles), Beijing University of Chinese Medicine (56 articles), and Evidence Based Complementary and Alternative Medicine (42 articles), respectively. The high-frequency keywords focused on “Alzheimer's disease,” “Parkinson's disease,” “acupuncture,” “dementia,” and “electroacupuncture.” The top five keywords in terms of centrality were “cerebral ischemia,” “acupuncture stimulation,” “fMRI,” “apoptosis,” and “deep brain stimulation.”ConclusionThe results from this bibliometric study provide insight into the research trends in acupuncture therapy for NDs, and the current status and trends of the past decade, which may help researchers confirm the current status, hotspots, and frontier trends in this field.

Bibliometric and visualized analysis of global research on microRNAs in gastric cancer: from 2013 to 2023

Gastric cancer (GC) imposes a heavy burden on global public health, and microRNAs (miRNAs) play a crucial role in the diagnosis and treatment of GC. Therefore, it is necessary to clarify the hotspots and frontiers in the field of miRNAs in GC to guide future research. A total of 2,051 publications related to miRNAs in GC from January 2013 to December 2023 were searched from the Web of Science Core Collection database. CiteSpace was used to identify research hotspots and delineate developmental trends. In the past decade, China, Nanjing Medical University, and Ba Yi were the most contributing research country, institute, and author in this field, respectively. The role of miRNAs as biomarkers in GC, the mechanism of miRNAs in the progression of GC, and the impact of the mutual effects between miRNAs and Helicobacter pylori on GC have been regarded as the research hotspots. The mechanisms of miRNAs on glucose metabolism and the application of the roles of circular RNAs as miRNA sponges in GC treatment will likely be frontiers. Overall, this study called for strengthened cooperation to identify targets and therapeutic regimes for local specificity and high-risk GC types, and to promote the translation of research results into clinical practice.

Emerging contaminants in water environments: progress, evolution, and prospects

ABSTRACT This article employs bibliometric tools like VOSviewer, Bibliometrix, and CiteSpace for a comprehensive visual analysis of 1,612 documents on Emerging Contaminants in Waters from the Web of Science database. The objective is to elucidate the historical development, research hotspots, and trends in international studies of this field, offering valuable insights and guidance for future research directions. The analysis reveals a consistent increase in publications from 2003 to 2023, with the United States, China, and Spain being the most prolific contributors. A detailed examination of keyword co-occurrence and cluster analysis shows a predominant focus on themes such as pollutant detection, risk assessment, and biogeochemical cycling. Furthermore, the study underscores the significance of forming interdisciplinary networks among authors and institutions, highlighting its critical role in enhancing the quality and innovation of scientific research. The findings of this study not only chart the progression and focal points of research in this domain but also underscore the pivotal role of international collaboration, serving as an indispensable reference for shaping future research trajectories and fostering global cooperation.

Advances in sequencing and omics studies in prostate cancer: unveiling molecular pathogenesis and clinical applications

BackgroundProstate cancer (PCa) is one of the most threatening health problems for the elderly males. However, our understanding of the disease has been limited by the research technology for a long time. Recently, the maturity of sequencing technology and omics studies has been accelerating the studies of PCa, establishing themselves as an essential impetus in this field.MethodsWe assessed Web of Science (WoS) database for publications of sequencing and omics studies in PCa on July 3rd, 2023. Bibliometrix was used to conduct ulterior bibliometric analysis of countries/affiliations, authors, sources, publications, and keywords. Subsequently, purposeful large amounts of literature reading were proceeded to analyze research hotspots in this field.Results3325 publications were included in the study. Research associated with sequencing and omics studies in PCa had shown an obvious increase recently. The USA and China were the most productive countries, and harbored close collaboration. CHINNAIYAN AM was identified as the most influential author, and CANCER RESEARCH exhibited huge impact in this field. Highly cited publications and their co-citation relationships were used to filtrate literatures for subsequent literature reading. Based on keyword analysis and large amounts of literature reading, ‘the molecular pathogenesis of PCa’ and ‘the clinical application of sequencing and omics studies in PCa’ were summarized as two research hotspots in the field.ConclusionSequencing technology had a deep impact on the studies of PCa. Sequencing and omics studies in PCa helped researchers reveal the molecular pathogenesis, and provided new possibilities for the clinical practice of PCa.

Application of non parametric Bayesian methods in high dimensional data

With the development of technology and the widespread collection of data, high-dimensional data analysis has become a research hotspot in many fields. Traditional parameter methods often face problems such as dimensional disasters in high-dimensional data analysis. Non parametric methods have broad application prospects in high-dimensional data because they do not rely on specific parameter distribution assumptions. The Bayesian rule is more suitable for dealing with noise and outliers in high-dimensional data because it takes uncertainty into account. Therefore, it is of great significance to combine non parametric methods with Bayesian methods for application research in high-dimensional data analysis. In this paper, the nonparametric Bayesian method was applied to the analysis of high-dimensional data, and the Dirichlet process Mixture model was used to cluster high-dimensional data. The regression analysis of high-dimensional data was carried out through the prediction model of nonparametric Bayesian regression. In this paper, the nonparametric Bayesian method based on Bayesian sparse linear model was used for feature selection of high-dimensional data. In order to determine the superiority of nonparametric Bayesian methods in high-dimensional data analysis, this paper conducted experiments on nonparametric Bayesian methods and traditional parametric methods in high-dimensional data analysis from five aspects of cluster analysis, classification analysis, regression analysis, feature selection and anomaly detection, and evaluated them through multiple indicators. This article explored the application of non parametric Bayesian methods in high-dimensional data analysis from these aspects through simulation experiments. The experimental results show that the clustering accuracy of the non parametric Bayesian clustering algorithm was 0.93, and the accuracy of the non parametric Bayesian classification algorithm was between 0.93 and 0.99; the coefficient of determination of nonparametric Bayesian regression algorithm was 0.98; the F1 values of non parametric Bayesian methods in anomaly detection ranged from 0.86 to 0.91, which was superior to traditional methods. Non parametric Bayesian methods have broad application prospects in high-dimensional data analysis, and can be applied in multiple fields such as clustering, classification, regression, etc.

Themes and trends in marathon performance research: a comprehensive bibliometric analysis from 2009 to 2023

Background: When marathon runners break the 2-h barrier at the finishing line, it attracts global attention. This study is aimed to conduct a bibliometric analysis of publications in the field of marathon running, analyze relevant research contributors, and visualize the historical trends of marathon performance research over the past 15 years.Methods: On 8 December 2023, we extracted high-quality publication data from the Web of Science Core Collection spanning from 1 January 2009 to 30 November 2023. We conducted bibliometric analysis and research history visualization using the R language packages biblioshiny, VOSviewer, and CiteSpace.Results: A total of 1,057 studies were published by 3,947 authors from 1,566 institutions across 63 countries/regions. USA has the highest publication and citation volume, while, the University of Zurich being the most prolific research institution. Keywords analysis revealed several hotspots in marathon research over the past 3 years: (1) physiology of the elite marathon runners, (2) elite marathon training intensity and pacing strategies, (3) nutritional strategies for elite marathon runners, (4) age and sex differences in marathon performance, (5) recovery of inflammatory response and muscle damage.Conclusion: This study presents the first comprehensive bibliometric analysis of marathon performance research over the past 15 years. It unveils the key contributors to marathon performance research, visually represents the historical developments in the field, and highlights the recent topical frontiers. The findings of this study will guide future research by identifying potential hotspots and frontiers.

Global research trends in nursing leadership from 1985 to 2022: a bibliometric analysis.

Developing nursing leadership has become a key policy priority to achieve universal health coverage. This study aims to explore the current status, developing trends and research frontiers in the field of nursing leadership. In total, 1,137 articles and reviews on nursing leadership from 1985 to 2022 were retrieved from the Web of Science Core Collection database. Trends of publications, journals, countries/regions, institutions, documents and keywords were visualized and analyzed using Microsoft Excel and CiteSpace software. Nursing leadership research showed an overall increase in number despite slight fluctuations in annual publications. The USA was the leading country in nursing leadership research, and the University of Alberta was the most productive institution. The Journal of Nursing Management was the most widely published journal that focused on nursing leadership, followed by the Journal of Nursing Administration. Keyword analysis showed that the main research hotspots of nursing leadership are improvement, practice and impact of nursing leadership. This article summarizes the current state and frontiers of nursing leadership for researchers, managers and policy makers, as well as follow-up, development and implementation of nursing leadership. More research is needed that focuses on the improvement, practice and impact of nursing leadership, which are cyclical, complementary and mutually reinforcing. Longitudinal and intervention studies of nursing leadership, especially on patient prognosis, are also particularly needed.

A [Co5] cluster‐based organic framework as fluorescent detection platform toward quinolone antibiotics

The detection of quinolone antibiotics is an important research hotspot for protecting human health. Herein, a three‐dimensional metal–organic framework with the formula of {[Co5(TPT)2(BPDC)3(μ3‐O)2(H2O)4]·8MeCN·3DMF}n (NS‐3, TPT = tris(4‐pyridyl)‐1,3,5‐triazin, H2BPDC = 1,4‐benzenedicarboxylic acid) has been successfully prepared through solvothermal method. Single‐crystal X‐ray diffraction analysis revealed that three‐dimensional NS‐3 can be viewed as an eight‐connected sqc4 net with pentanuclear [Co5(μ3‐O)2]6+ cluster as metal nodes. Importantly, when norfloxacin, ofloxacin, and enrofloxacin were added in NS‐3 ethanol suspension, the luminescence intensity of NS‐3 at 333 nm was obviously decreased while new emission peaks clearly emerged, indicating that NS‐3 can be a potential rare fluorescent detection to recognize quinolone antibiotics in ethanol. Additionally, NS‐3 exhibits high sensitivity to norfloxacin, ofloxacin, and enrofloxacin with a limit of detection of 43, 34, and 139 nM, respectively, which is superior to most of the reported metal–organic frameworks.

Knowledge mapping of graph neural networks for drug discovery: a bibliometric and visualized analysis

IntroductionIn recent years, graph neural network has been extensively applied to drug discovery research. Although researchers have made significant progress in this field, there is less research on bibliometrics. The purpose of this study is to conduct a comprehensive bibliometric analysis of graph neural network applications in drug discovery in order to identify current research hotspots and trends, as well as serve as a reference for future research.MethodsPublications from 2017 to 2023 about the application of graph neural network in drug discovery were collected from the Web of Science Core Collection. Bibliometrix, VOSviewer, and Citespace were mainly used for bibliometric studies.Results and DiscussionIn this paper, a total of 652 papers from 48 countries/regions were included. Research interest in this field is continuously increasing. China and the United States have a significant advantage in terms of funding, the number of publications, and collaborations with other institutions and countries. Although some cooperation networks have been formed in this field, extensive worldwide cooperation still needs to be strengthened. The results of the keyword analysis clarified that graph neural network has primarily been applied to drug-target interaction, drug repurposing, and drug-drug interaction, while graph convolutional neural network and its related optimization methods are currently the core algorithms in this field. Data availability and ethical supervision, balancing computing resources, and developing novel graph neural network models with better interpretability are the key technical issues currently faced. This paper analyzes the current state, hot spots, and trends of graph neural network applications in drug discovery through bibliometric approaches, as well as the current issues and challenges in this field. These findings provide researchers with valuable insights on the current status and future directions of this field.

A review and bibliometric analysis of global research on proton radiotherapy.

Proton beam therapy (PBT) has great advantages as tumor radiotherapy and is progressively becoming a more prevalent choice for individuals undergoing radiation therapy. The objective of this review is to pinpoint collaborative efforts among countries and institutions, while also exploring the hot topics and future outlook in the field of PBT. Data from publications were downloaded from the Web of Science Core Collection. CiteSpace and Excel 2016 were used to conduct the bibliometric and knowledge map analysis. A total of 6516 publications were identified, with the total number of articles steadily increasing and the United States being the most productive country. Harvard University took the lead in contributing the highest number of publications. Paganetti Harald published the most articles and had the most cocitations. PHYS MED BIOL published the greatest number of PBT-related articles, while INT J RADIAT ONCOL received the most citations. Paganetti Harald, 2012, PHYS MED BIOL can be classified as classic literature due to its high citation rate. We believe that research on technology development, dose calculation and relative biological effectiveness were the knowledge bases in this field. Future research hotspots may include clinical trials, flash radiotherapy, and immunotherapy.

Knowledge mapping of chronic insomnia: a bibliometric analysis (2000-2023).

Recently, significant scientific research breakthroughs have been witnessed in the treatment of chronic insomnia. However, it seems that there is currently no bibliometric analysis of this. Therefore, we hope to comprehensively review and analyze the scholarly system and research focus in the field of chronic insomnia treatment through bibliometric methods. Between 2000 and 2023, we explored various papers in relation to the treatment of chronic insomnia in the Web of Science Core Collection(WOSCC) database. Subsequently, the collected papers were subjected to bibliometric analysis utilizing CiteSpace, VOSviewer, and the "bibliometric" package in R language. With China and the United States(USA) among them, a total of 2937 papers were published across 49 countries. Publications related to the treatment of chronic insomnia were increasing year by year. The Laval University, Washington University, Pittsburgh University, and Stanford University were key research institutions. The journal Sleep was widely popular in the field and was also one of the most cited journals. These papers came from 148 authors, with Morin, Charles M., Roth, Thomas, Espie, Colin A., Harvey, Allison G., and Buysse, Daniel J. publishing the most papers and Morin, cm being co-cited the most. The treatment process of chronic insomnia can be divided into three main stages: drug intervention, diseases related to chronic insomnia, and cognitive behavioral therapy and mental health. Keywords such as "children and adolescents", "novel coronavirus pneumonia" (COVID-19), "mental health" and "heart failure" have become the focus of current research. We carried out a detailed bibliometric review of the development trends and research results of chronic insomnia research through this study for the first time. The information it provides reveals recent research hotspots and cutting-edge issues, providing valuable reference materials for researchers focusing on the treatment of chronic insomnia.

Bibliometric analysis on the structure and function of IL17

BackgroundInterleukin17 (IL17) is an important cytokine in host defense at mucosal surfaces and also mediates many autoimmune diseases, including rheumatoid arthritis (RA). In recent years, many types of research relevant to the structure and function of IL17 have been identified. However, there is no bibliometric analysis in this research field. This study aims to explore the history, research hotspots, and emerging trends of IL17 from the perspective of the structure and function dynamics.MethodsArticles relevant to IL17 in the last two decades were retrieved through the Web of Science Core Collection (WoSCC) database. The bibliometric analysis was performed by VOSview.ResultsA total of 882 papers in this research were analyzed from 65 countries, and the rate of published articles has increased from 2008 annually, with the USA, China, and Germany leading the research effort. Frontiers in Immunology has significantly impacted research in this field and the University of Pittsburgh was the leading institution. Gaffen, Sarah L. from the University of Pittsburgh was the most productive researcher in this field and Papp Ka from the Probity Medical Research Incorporate of Canada is the most co-cited author. The analysis of keywords showed that inflammation, expression, Th17 cells, and cytokines were the main hotspots and frontier directions of IL17. The trend of clinical application in the future is the development of new therapy drugs based on the structure of IL17 or IL17 signaling pathway molecular.ConclusionsOur research summarized the developments and research trends of IL17 and would help researchers understand the research status of IL17 and provide a reference for future researchers as soon as possible.

Research Progress of Heavy-Metal-Free Quantum Dot Light-Emitting Diodes

At present, heavy-metal-free quantum dot light-emitting diodes (QLEDs) have shown great potential as a research hotspot in the field of optoelectronic devices. This article reviews the research on heavy-metal-free quantum dot (QD) materials and light-emitting diode (LED) devices. In the first section, we discussed the hazards of heavy-metal-containing quantum dots (QDs), such as environmental pollution and human health risks. Next, the main representatives of heavy-metal-free QDs were introduced, such as InP, ZnE (E=S, Se and Te), CuInS2, Ag2S, and so on. In the next section, we discussed the synthesis methods of heavy-metal-free QDs, including the hot injection (HI) method, the heat up (HU) method, the cation exchange (CE) method, the successful ionic layer adsorption and reaction (SILAR) method, and so on. Finally, important progress in the development of heavy-metal-free QLEDs was summarized in three aspects (QD emitter layer, hole transport layer, and electron transport layer).