Coincident Fluorescence Burst Analysis of dUTP-Loaded Exosome-Mimetic Nanovesicles

The possibility of targeting functionality and low immunogenicity of exosomes and exosome-like nanovesicles makes them promising as drug-delivery carriers. To tap into this potential, accurate non-destructive methods to load them and characterize their contents are of utmost importance. However, the small size, polydispersity and aggregation of nanovesicles in solution, make quantitative characterizations of their loading particularly challenging. Here we develop an ad-hoc methodology based on burst analysis of dual-color confocal fluorescence microscopy experiments, suited for quantitative characterizations of exosome-like nanovesicles and of their loading. We apply it to study exosome-mimetic nanovesicles derived from animal extracellular-vesicles and human red blood cell detergent resistant membranes, loaded with dUTP cargo molecules. For both classes of nanovesicles we prove successful loading and by dual-color coincident fluorescence burst analysis, we retrieve size statistics and quantify the loading. The procedure affords single-vesicle characterizations well-suited for the investigation of a variety of cargo molecules and biological nanovesicle combinations besides the proof-of-principle demonstrations of this study. The results highlight a powerful characterization tool essential for the optimizing the loading process and for advanced engineering of biomimetic nanovesicles for therapeutic drug delivery.

Global population structure of Haemophilus influenzae serotype a (Hia) and emergence of invasive Hia disease: capsule switching or capsule replacement?

The population structure of Hia was examined by interrogation of the H. influenzae MLST website. There were 196 entries of Hia with 55 sequence types (STs) identified (as of September 3, 2020). BURST analysis clustered related STs into four complexes with ST-23, ST-4, ST-21 and ST-62 identified as their ancestral STs. The majority of Hia entries (73.4%) and STs (65.5%) were identified as clonal division I (ST-23 and the ST-4 complexes). Only 43 (21.9%) entries and 14 STs (25.5%) were identified as clonal division II (ST-62 and ST-21 complexes). Current data suggested most invasive Hia belonged to clonal division I and the ST-23 complex while most clonal division II Hia were respiratory isolates with the exception of ST-62 which was common among invasive Hia in the U.S. southwest. Comparison of the capsule bexABCD genes from clonal divisions I and II strains showed sequence diversity with variations following the pattern of clonal divisions. Evidence from the literature and the current study suggests recent emergence of invasive Hia might be related to capsule replacement subsequent to the implementation of the Hib conjugate vaccine and possibly exacerbated by other conjugate vaccines that may have altered the microbial flora of the human respiratory tract.

A Scientometric Review of Smart Construction Site in Construction Engineering and Management: Analysis and Visualization

With the extensive development and application of information technologies in construction engineering and management (CEM), the construction site is experiencing a rapid digital revolution and transformation. Since smart construction site has become the current research trend and one of the most hot topics, thus this study adopted an integrated bibliometric approach and quantitative analysis to explore the global research on smart construction site. As it is indicated in the content, the bibliometric and scientometric method-based literature review was carried out in this study. To be specific, the co-citation analysis in terms of author, document, and journal; the collaboration analysis in terms of authorship, institutions, and country/region; and category analysis, as well as cluster analysis and burst analysis were conducted based on 2206 peer-reviewed academic papers, which were published from January 2000 to February 2021. It is found that there has been an explosion of relevant publications especially in the past 10 years along with the changing of keywords from flexibility approach to information technologies, 3D reconstruction, IoT technologies, virtual reality, and others. Moreover, the results indicated that the collaborations and cooperation among different institutions, countries, and authors are not close enough, and the most significant research and development in smart construction occurred primarily in the USA, China, and England. Additionally, the smart construction site’s relevant research in terms of publication of quantity was doubled every five years. In addition, the smart construction site relevant research has gradually changed from the traditional project performance associated indicators to smart simulation applications and scenes. Lastly, implementation and management-related concerns about smart construction sites are discussed with seven topics. This study provides researchers and practitioners not merely with an in-depth understanding of the characters and also the trend of smart construction site research in the construction engineering and management field.

Identification of data mining research frontier based on conference papers

Purpose Identifying the frontiers of a specific research field is one of the most basic tasks in bibliometrics and research published in leading conferences is crucial to the data mining research community, whereas few research studies have focused on it. The purpose of this study is to detect the intellectual structure of data mining based on conference papers. Design/methodology/approach This study takes the authoritative conference papers of the ranking 9 in the data mining field provided by Google Scholar Metrics as a sample. According to paper amount, this paper first detects the annual situation of the published documents and the distribution of the published conferences. Furthermore, from the research perspective of keywords, CiteSpace was used to dig into the conference papers to identify the frontiers of data mining, which focus on keywords term frequency, keywords betweenness centrality, keywords clustering and burst keywords. Findings Research showed that the research heat of data mining had experienced a linear upward trend during 2007 and 2016. The frontier identification based on the conference papers showed that there were five research hotspots in data mining, including clustering, classification, recommendation, social network analysis and community detection. The research contents embodied in the conference papers were also very rich. Originality/value This study detected the research frontier from leading data mining conference papers. Based on the keyword co-occurrence network, from four dimensions of keyword term frequency, betweeness centrality, clustering analysis and burst analysis, this paper identified and analyzed the research frontiers of data mining discipline from 2007 to 2016.

The landscape of academic literature in quantum technologies

In this study, we investigated the academic literature on quantum technologies (QT) using bibliometric tools. We used a set of 49,823 articles obtained from the Web of Science (WoS) database using a search query constructed through expert opinion. Analysis of this revealed that QT is deeply rooted in physics, and the majority of the articles are published in physics journals. Keyword analysis revealed that the literature could be clustered into three distinct sets, which are (i) quantum communication/cryptography, (ii) quantum computation, and (iii) physical realizations of quantum systems. We performed a burst analysis that showed the emergence and fading away of certain key concepts in the literature. This is followed by co-citation analysis on the “highly cited” articles provided by the WoS, using these we devised a set of core corpus of 34 publications. Comparing the most highly cited articles in this set with respect to the initial set we found that there is a clear difference in most cited subjects. Finally, we performed co-citation analyses on country and organization levels to find the central nodes in the literature. Overall, the analyses of the datasets allowed us to cluster the literature into three distinct sets, construct the core corpus of the academic literature in QT, and to identify the key players on country and organization levels, thus offering insight into the current state of the field. Search queries and access to figures are provided in the appendix.

Trends and developments in oral health literacy: a scientometric research study (1991–2020)

Objective This study aimed to establish the current situation, intellectual base, hotspots, development trends, and frontiers of oral health literacy (OHL) from the literature. Methods We analyzed 1505 bibliographic records dated between January 1990 and December 2020 retrieved from the Web of Science Core Collection and the Scopus database. We used CiteSpace for word frequency analysis, co-occurrence analysis, co-citation analysis, clustering analysis, and burst analysis. Results The total number of publications increased year-on-year, with the majority of publications coming from the USA. Most studies focused on the relationship between (oral) health literacy and oral health, and the development of OHL instruments. The top 10 keywords by frequency were “health literacy”, “oral health”, “attitude to health”, “dental caries”, “adult”, “children”, “dental care”, “knowledge”, “questionnaire”, and “adolescent”. The keyword with the highest burst intensity was “dental health education”. Conclusions OHL research is a thriving field. The field is focused on the development of an OHL instrument and health promotion practice. Strategic cooperation among countries, institutions, authors, hospitals, and communities will be important to encourage further OHL research and address oral health problems.

Predictive Maintenance and Intelligent Sensors in Smart Factory: Review

With the arrival of new technologies in modern smart factories, automated predictive maintenance is also related to production robotisation. Intelligent sensors make it possible to obtain an ever-increasing amount of data, which must be analysed efficiently and effectively to support increasingly complex systems’ decision-making and management. The paper aims to review the current literature concerning predictive maintenance and intelligent sensors in smart factories. We focused on contemporary trends to provide an overview of future research challenges and classification. The paper used burst analysis, systematic review methodology, co-occurrence analysis of keywords, and cluster analysis. The results show the increasing number of papers related to key researched concepts. The importance of predictive maintenance is growing over time in relation to Industry 4.0 technologies. We proposed Smart and Intelligent Predictive Maintenance (SIPM) based on the full-text analysis of relevant papers. The paper’s main contribution is the summary and overview of current trends in intelligent sensors used for predictive maintenance in smart factories.