Bibliometric analysis of research trends and topic areas in traditional Chinese medicine therapy for lymphoma

CONTEXT

Traditional Chinese Medicine (TCM) is effective as a cancer treatment modality. However, this is the first bibliometric analysis of TCM in lymphoma treatment.

OBJECTIVE

This study explores the current trends and research topics of TCM in treating lymphoma from 2000 to 2023.

MATERIALS AND METHODS

We searched within the Web of Science Core Collection (WoSCC) for publications on TCM in lymphoma treatment, spanning 2000 to 2023. Subsequently, we employed a comprehensive approach utilizing CiteSpace software and VOSviewer to visually analyze research trends, authors, institutions, co-cited references, and keywords.

RESULTS

From January 1, 2000, to August 31, 2023, annual scientific publications on TCM for lymphoma treatment have steadily increased. Among the leading institutions in this field, the Beijing University of Chinese Medicine and the Fujian Medical University occupied the top positions. Regarding the authors, Jun Peng, Jiumao Lin, and Hongwei Chen emerged as the top three contributors. In the co-citation analysis of references, the top three co-cited references were authored by Hanahan D, Elmore S, and Livak KJ with citations numbered 13, 14, and 17, respectively. In particular, keywords reflecting current emerging trends included 'pathway', 'traditional Chinese medicine', 'oxidative stress', and 'macrophage polarization'.

DISCUSSION AND CONCLUSIONS

This bibliometric analysis provides a comprehensive overview of TCM for lymphoma treatment. This analysis identified the predominant trends and research topics in the field. The findings are expected to be of significant value for researchers who focus on TCM in lymphoma treatment, helping them better understand the development of this field.

Uncovering the building blocks of rural entrepreneurship: A comprehensive framework for mapping the components of rural entrepreneurial ecosystems

Entrepreneurship is a crucial driver of economic growth, especially in rural areas. Understanding the unique components that contribute to the success of rural entrepreneurial ecosystems is essential. This study presents a cutting-edge approach to uncover the essential components of rural entrepreneurial ecosystems that support rural entrepreneurship. We employ bibliometric techniques that enable us to leverage the Scopus database's academic paper metadata related to entrepreneurial ecosystems. Through citation analysis, we identify a core network of studies related to entrepreneurial ecosystems. Co-occurrence analysis visualizes the clusters of the most prominent components in both general and rural entrepreneurial ecosystems. We interpret the results based on a literature review. Our study categorizes the essential components into two: actor (academics, business, government, and community) and non-actor (human capital, network, entrepreneurial culture, financial systems, governance systems, infrastructure, environmental resources, and market) components. Environmental resources are critical in distinguishing the conditions of an entrepreneurial ecosystem in rural areas. This component represents the uniqueness and local economic potential of smaller areas, whereas in general entrepreneurial ecosystem studies, this component might not be a concern. By uncovering the components of rural entrepreneurial ecosystems, our study provides insights that can help policymakers, practitioners, and academics better support rural entrepreneurship and promote economic growth in rural areas.

Applications of artificial intelligence and machine learning in the financial services industry: A bibliometric review

This bibliometric review examines the research state of artificial intelligence (AI) and machine learning (ML) applications in the Banking, Financial Services, and Insurance (BFSI) sector. The study focuses on Scopus-indexed articles to identify key research clusters. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol, 39,498 articles were screened, resulting in 1045 articles meeting the inclusion criteria. N-gram analysis identified 177 unique terms in the article titles and abstracts. Co-occurrence analysis revealed nine distinct clusters covering fintech, risk management, anti-money laundering, and actuarial science, among others. These clusters offer a comprehensive overview of the multifaceted research landscape. The identified clusters can guide future research and inform study design. Policymakers, researchers, and practitioners in the BFSI sector can benefit from the study's findings, which identify research gaps and opportunities. This study contributes to the growing literature on bibliometrics, providing insights into AI and ML applications in the BFSI sector. The findings have practical implications, advancing our understanding of AI and ML's role in benefiting academia and industry.

Neuroimaging Investigations of Obesity: a Review of the Treatment of Sex from 2010

PURPOSE OF REVIEW

To summarize the results of adult obesity neuroimaging studies (structural, resting-state, task-based, diffusion tensor imaging) published from 2010, with a focus on the treatment of sex as an important biological variable in the analysis, and identify gaps in sex difference research.

RECENT FINDINGS

Neuroimaging studies have shown obesity-related changes in brain structure, function, and connectivity. However, relevant factors such as sex are often not considered. We conducted a systematic review and keyword co-occurrence analysis. Literature searches identified 6281 articles, of which 199 met inclusion criteria. Among these, only 26 (13%) considered sex as an important variable in the analysis, directly comparing the sexes (n = 10; 5%) or providing single-sex/disaggregated data (n = 16, 8%); the remaining studies controlled for sex (n = 120, 60%) or did not consider sex in the analysis (n = 53, 27%). Synthesizing sex-based results, obesity-related parameters (e.g., body mass index, waist circumference, obese status) may be generally associated with more robust morphological alterations in men and more robust structural connectivity alterations in women. Additionally, women with obesity generally expressed increased reactivity in affect-related regions, while men with obesity generally expressed increased reactivity in motor-related regions; this was especially true under a fed state. The keyword co-occurrence analysis indicated that sex difference research was especially lacking in intervention studies. Thus, although sex differences in the brain associated with obesity are known to exist, a large proportion of the literature informing the research and treatment strategies of today has not specifically examined sex effects, which is needed to optimize treatment.

Textile waste water treatment: analysis of mapping knowledge domains

Textile waste water contains dyes and chemicals that produce harmful vapors and exhaust gases, which is hazardous to the environment and public health. Therefore, it must be carefully treated before discharged. To understand the research evolution in the research area of textile waste water treatment, based on bibliometrics, an in-depth analysis of the publications and hotspots in this area was presented in this paper. For the analysis, totally 6774 papers related to the research area that are published between the year 1964 and 2023 were collected from the Web of Science Core Collection. Using CiteSpace and VOSviewer as bibliometric analysis tools, the collaboration of countries, regions, and organizations was investigated. Besides, an analysis for citation and co-citation of journals, authors, references, and co-occurrence of keywords was performed. The evolution of research hotspots in the three major research directions related to degradation, oxidation, and adsorption is also analyzed in this paper. The analysis results show that researches related to oxidation and adsorption are active in recent years, while nanocomposite adsorbents and graphene oxide are the current research hotspots.

A review of research on driving distraction based on bibliometrics and co-occurrence: Focus on driving distraction recognition methods

INTRODUCTION

The existing selection of driving distraction recognition methods is based on a specific research perspective and does not provide comprehensive information on the entire field of view.

METHOD

We conducted a systematic review of previous studies, aiming to come up with appropriate research methods to identify the driver's distraction state. First, this article selects four sets of search keywords related to driving distraction discrimination from five databases (Web of Science, ScienceDirect, Springer Link, IEEE, and TRID) and identifies 1,620 peer-reviewed documents from 2000 to 2020; these 1,620 documents underwent bibliographic analysis and co-occurrence network analysis. The co-occurrence coupling relationship is analyzed from the aspects of time, country, publication, author and keywords. Second, 37 papers published were screened, and the driving distraction recognition methods proposed by these 37 papers were summarized and analyzed.

RESULTS

The results show that this field has been prevalent since 2013; countries such as the United States, Britain, Germany, Australia, China, and Canada are in the forefront of research in this field, and the cooperation between related countries is relatively close. The cooperation between authors is characterized by aggregation, and the mobile phone as the main keyword is almost connected to other keyword nodes; the recognition model of deep learning algorithm based on video surveillance data sources has become the mainstream hot spot distraction recognition method. The recognition model of machine learning algorithm based on vehicle dynamics data, driver physiology, and eye movement data sources has specific advantages and disadvantages.

PRACTICAL APPLICATIONS

The results can help people to understand the current situation of driving distraction comprehensively and systematically, provide better theoretical support for researchers to choose the subsequent driving distraction recognition model, and provide research direction for driving distraction recognition in the future.

Antibiotic resistance genes and their links with bacteria and environmental factors in three predominant freshwater aquaculture modes

Rapid development of aquaculture industry and increasing demand of various inputs (especially antibiotics), are suspected to promote the occurrence and spread of ARGs in aquaculture related environments. However, the occurrences of ARGs under different freshwater aquaculture practices are rarely known. Here, we investigated the seasonal profiles of the main ARGs, intI1 and bacteria in waters from three kinds of predominant freshwater aquaculture practices around the Honghu Lake (China), as well as their co-occurrences and interrelationships with antibiotics, heavy metals and general water quality. The results indicate that quinolone resistance genes (qnrB), tetracycline resistance genes (tetB and tetX) and sulfonamide resistance genes (sul1 and sul2) were the top five predominant ARGs with seasonal variations of abundance. Fish ponds were of the highest absolute abundances of tested ARGs than the other two modes. Crayfish ponds and their adjacent ditches shared similar ARGs profile. Different subtypes of ARGs belonging to the same class of resistance were varied in abundances. Some bacteria were predicted to carry different ARGs, which indicating multi-antibiotic resistances. Moreover, the combined environmental factors (antibiotics, heavy metals and water quality) partially shaped the profiles of ARGs and bacteria composition. Overall, this study provides new comprehensive understanding on the characterization of ARGs contamination in different freshwater aquaculture practices from the perspectives of environmental chemistry, microbiology and ecology. The results would benefit the optimization of aquaculture practices toward environmental integrity and sustainability.

Microbial interactions enhanced environmental fitness and expanded ecological niches under dibutyl phthalate and cadmium co-contamination

Co-contamination of organic pollutants and heavy metals is universal in the natural environment. Dibutyl phthalate (DBP), a typical plasticizer, frequently coexists with cadmium (Cd) in nature. However, little attention has been given to the impacts of co-contamination by DBP and Cd on microbial communities or the responses of microbes. To address this, a microcosm experiment was conducted by supplying the exogenous DBP-degrading bacterium Glutamicibacter nicotianae ZM05 to investigate the interplay among DBP-Cd co-contamination, the exogenous DBP-degrading bacterium G. nicotianae ZM05, and indigenous microorganisms. To adapt to co-contamination stress, microbial communities adjust their diversity, interactions, and functions. The stability of the microbial community decreased under co-contamination, as evidenced by lower diversity, simpler network, and fewer ecological niches. Microbial interactions were strengthened, as evidenced by enriched pathways related to microbial communications. Meanwhile, interactions between microorganisms enhanced the environmental fitness of the exogenous DBP-degrading bacterium ZM05. Based on co-occurrence network prediction and coculture experiments, metabolic interactions between the non-DBP-degrading bacterium Cupriavidus metallidurans ZM16 and ZM05 were proven. Strain ZM16 utilized protocatechuic acid, a DBP downstream metabolite, to relieve acid inhibition and adsorbed Cd to relieve toxic stress. These findings help to explain the responses of bacterial and fungal communities to DBP-Cd co-contamination and provide new insights for the construction of degrading consortia for bioremediation.

Network and meta-omics reveal the cooperation patterns and mechanisms in an efficient 1,4-dioxane-degrading microbial consortium

1,4-Dioxane is an emerging wastewater contaminant with probable human carcinogenicity. Our current understanding of microbial interactions during 1,4-dioxane biodegradation process in mixed cultures is limited. Here, we applied metagenomic, metatranscriptomic and co-occurrence network analyses to unraveling the microbial cooperation between degrader and non-degraders in an efficient 1,4-dioxane-degrading microbial consortium CH1. A 1,4-dioxane-degrading bacterium, Ancylobacter polymorphus ZM13, was isolated from CH1 and had a potential of being one of the important degraders due to its high relative abundance, highly expressed monooxygenase genes tmoABCDEF and high betweenness centrality of networks. The strain ZM13 cooperated obviously with 6 bacterial genera in the network, among which Xanthobacter and Mesorhizobium could be involved in the intermediates metabolism with responsible genes encoding alcohol dehydrogenase (adh), aldehyde dehydrogenase (aldh), glycolate oxidase (glcDEF), glyoxylate carboligase (gcl), malate synthase (glcB) and 2-isopropylmalate synthase (leuA) differentially high-expressed. Also, 1,4-dioxane facilitated the shift of biodiversity and function of CH1, and those cooperators cooperated with ZM13 in the way of providing amino acids or fatty acids, as well as relieving environmental stresses to promote biodegradation. These results provide new insights into our understandings of the microbial interactions during 1,4-dioxane degradation, and have important implications for predicting microbial cooperation and constructing efficient and stable synthetic 1,4-dioxane-degrading consortia for practical remediation.

Free-living nematodes of Mediterranean ports: A mandatory contribution for their use in ecological quality assessment

Free-living nematodes were investigated in three Mediterranean commercial ports (Ancona and Trieste, Italy; Koper, Slovenia) in terms of abundance, diversity and functionality. Results indicated that r-strategist genera were dominant in all ports and that a more diverse assemblage characterized Trieste, despite the high contamination levels, suggesting a potential adaptation to long-standing contamination. The main environmental factor that shaped the assemblage in all ports were Total Polycyclic Aromatic Hydrocarbons, while Total Organic Carbon and the grain-size were less relevant. A co-occurrence analysis was applied for identifying which genera cohesively respond to site-specific environmental conditions in order to recalibrate and implement the sets of bioindicator genera in relation to their different opportunistic behaviour. Finally, we provided some suggestions for a proper application of the nematode indices (Maturity Index, Index of Trophic Diversity, Shannon diversity) in order to encourage the use of free-living nematodes for the environmental quality assessment of commercial ports.

(Micro) nanoplastics promote the risk of antibiotic resistance gene propagation in biological phosphorus removal system

Microplastics (MPs), nanoplastics (NPs) and antibiotic resistance genes (ARGs), as emerging pollutants, have been frequently detected in wastewater treatment plants. However, the behavior of phosphorus and ARGs under MP and NP (MP/NP) pressure in biological phosphorus removal (BPR) system is still unknown. This study investigated the effects of MP/NPs on phosphorus removal and ARGs propagation in BPR system. Results showed that MP/NPs had no influence on phosphorus removal, but significantly promoted the amplification of tetracycline resistance genes (TRGs). Moreover, the TRG abundance were more facilitated by MPs than NPs, and the TRGs of efflux pump and enzymatic modification mechanism were mainly enriched. Meanwhile, MP/NPs increased the transmission risk of multiple resistance genes and mobile gene elements (MGEs). Microbial communities demonstrated the main polyphosphate accumulating organisms shifted from Acinetobacter to unclassified_Gammaproteobacteria, which explained why phosphorus removal efficiency was unaffected with MP/NP addition. Correlation analysis revealed there was no significant correlation between ARGs and MGEs (intI1 and intI2), but the abundances of potential hosts of ARGs were significantly increased with MP/NP addition, implying microbial community structure changes rather than gene horizontal transfer was the main factor promoting ARG propagation under MP/NP pressure.

Probabilistic co-occurrence assessment for suites of listed species

Section 7 of the Endangered Species Act requires the US Environmental Protection Agency (US EPA) to consult with the Services (US Fish and Wildlife Service and National Marine Fisheries Service) over potential pesticide impacts on federally listed species. Consultation is complicated by the large number of pesticide products and listed species, as well as by lack of consensus on best practices for conducting co-occurrence analyses. Previous work demonstrates that probabilistic estimates of species' ranges and pesticide use patterns improve these analyses. Here we demonstrate that such estimates can be made for suites of sympatric listed species. Focusing on two watersheds, one in Iowa and the other in Mississippi, we obtained distribution records for 13 species of terrestrial and aquatic listed plants and animals occurring therein. We used maximum entropy modeling and bioclimatic, topographic, hydrographic, and land cover variables to predict species' ranges at high spatial resolution. We constructed probabilistic spatial models of use areas for two pesticides based on the US Department of Agriculture Cropland Data Layer and reduced classification errors by incorporating information on the relationships between individual pixels and their neighbors using object-based images analysis. We then combined species distribution and crop footprint models to derive overall probability of co-occurrence of listed species and pesticide use. For aquatic species, we also integrated an estimate of downstream residue transport. We report each separate species-by-use-area co-occurrence estimate and also combine these modeled co-occurrence probabilities across species within watersheds to produce an overall metric of potential pesticide exposure risk for these listed species at the watershed level. We propose that the consultation process between US EPA and the Services be based on such batched estimation of probabilistic co-occurrence for multiple listed species at a regional scale. Integr Environ Assess Manag 2022;18:1088-1100. © 2021 SETAC.

Research on Gambling in Young People: A Co-Occurrence Analysis

Gambling as a risk factor in youth development, particularly its causes and consequences, has been the subject of a growing number of studies. However, the literature relating to young people has yet to be compiled in a systematic form. The present study adopts a descriptive bibliometric approach to map global research on gambling in young people using metadata from the Web of Science database. The results show that research on gambling in young people at a country level has increased in recent years, though some regions are underrepresented. Co-occurrence analysis revealed the frequent use of several terms. It is hoped that these findings will assist in future research on the subject.

Gamification in education: A scientometric, content and co-occurrence analysis of systematic review and meta-analysis articles

This study seeks scientometric, content and co-occurrence analysis of systematic review and Meta-analysis articles in the field of gamification in education. In terms of purpose, this is an applied study and regarding type, it is a scientometric and co-occurrence analysis. The researchers conducted a search in WoS, Scopus and PubMed databases. The abstract and full text of 25 out of 71 articles were selected to be included in the study. Then, the citation and altmetrics indicators were investigated. In addition, VOSviewer software was utilized to analyze and visualize keywords and map of articles. Finally, the full texts of all articles were analyzed to be provided more information about the types of analyses in these articles. The findings showed that 25 articles were published between 2016 and 2021. Co-occurrence map of articles showed that the three variables of motivation, learning, and engagement have been considered in gamified education studies and most studies have examined gamification in the e-learning environment. Finally, the content analysis of the articles showed that 344 articles were included and analyzed in these 25 systematic reviews and meta-analyses. The types of analyzes performed on these 344 articles categorized them in 7 categories including Country/Territory, Duration of intervention, Lessons/content and the level of gamified educational course, the number of learners, platforms, the game elements and the theories. The results of the study illustrate that different dimensions of the gamification in articles in the field of Education have been considered by the researchers.

Research trends in cybercrime victimization during 2010-2020: a bibliometric analysis

Research on cybercrime victimization is relatively diversified; however, no bibliometric study has been found to introduce the panorama of this subject. The current study aims to address this research gap by performing a bibliometric analysis of 387 Social Science Citation Index articles relevant to cybercrime victimization from Web of Science database during the period of 2010-2020. The purpose of the article is to examine the research trend and distribution of publications by five main fields, including time, productive authors, prominent sources, active institutions, and leading countries/regions. Furthermore, this study aims to determine the global collaborations and current gaps in research of cybercrime victimization. Findings indicated the decidedly upward trend of publications in the given period. The USA and its authors and institutions were likely to connect widely and took a crucial position in research of cybercrime victimization. Cyberbullying was identified as the most concerned issue over the years and cyber interpersonal crimes had the large number of research comparing to cyber-dependent crimes. Future research is suggested to concern more about sample of the elder and collect data in different countries which are not only European countries or the USA. Cross-nation research in less popular continents in research map was recommended to be conducted more. This paper contributed an overview of scholarly status of cybercrime victimization through statistical evidence and visual findings; assisted researchers to optimize their own research direction; and supported authors and institutions to build strategies for research collaboration.

Microbial characteristics in anaerobic membrane bioreactor treating domestic sewage: Effects of HRT and process performance

Two anaerobic membrane bioreactors (AnMBRs) equipped with different membrane pore size (0.4 or 0.05 µm) were operated at 25˚C and fed with domestic wastewater. The hydraulic retention time (HRT) of the reactors was shortened. The microbial communities of the two AnMBRs were investigated by 16S rRNA gene amplicon sequencing to see the effects of HRT. The predominant Archaea was an aceticlastic methanogen Methanosaeta. The composition of hydrogenotrophic methanogens changed with the HRTs: the population of Methanobacterium was higher for longer HRTs, whereas the population of unclassified Methanoregulaceae was higher for shorter HRTs. The Anaerolineae, Bacteroidia and Clostridia bacteria were dominant in both of the reactors, with a combined relative abundance of over 55%. The relative abundance of Anaerolineae was proportional to the biogas production performance. The change in the population of hydrogenotrophic methanogens or Anaerolineae can be used as an indicator for process monitoring. The sum of the relative abundance of Anaerolineae and Clostridia fluctuated slightly with changes in the HRT in both AnMBRs when the reactor was stably operated. The co-occurrence analysis revealed the relative abundance of the operational taxonomic units belonging to Anaerolineae and Clostridia was functionally equivalent during the treatment of real domestic sewage. A principal coordination analysis revealed that the changes in the microbial community in each reactor were consistent with the change of HRT. In addition, both the HRT and the stability of the process are important factors for maintaining microbial community structures.

Coupling beach ecology and macroplastics litter studies: Current trends and the way ahead

As sites of floating marine material deposition, sandy beaches accumulate marine litter. While research and assessment on beach litter is increasing and involves various actors (scientists, society and NGOs), there is the need to assess current and future dominant trends, directions and priorities in that research. As such, a textural co-occurrence analysis was applied to published scientific literature. Words were considered both singly and as part of compound terms related to concepts relevant to sandy beach ecology: morphodynamic state; Littoral Active Zone; indicator fauna. Litter as a compound term was also included. The main co-occurrences were found within compounds, with scarce interaction of "morphodynamic state" with the others, indicating the need for further integration of beach ecology paradigms into beached plastics studies. Three approaches are proposed to overcome the research limits highlighted: the unequivocation of terms, the consideration of adequate scales, and the attention to dynamics rather than just patterns.

Comparative evaluation of simultaneous nitritation/denitritation and energy recovery in air-cathode microbial fuel cells (ACMFCs) treating low C/N ratio wastewater

Air-cathode microbial fuel cells (ACMFCs) can extract available electrons from the low C/N ratio wastewater (LCNW) for pollutant degradation and power generation. However, the multiple effects of operating parameters and their relationship between the performances and parameters are still lacking. In this study, several ACMFCs for simultaneous nitritation/denitritation (SND) and energy recovery were constructed and evaluated in terms of chemical oxygen demand (COD), NH₄⁺-N, C/N ratio, phosphate buffer solution (PBS), and external resistance (R_ext), and several derived parameters (e.g., organic loading rate (OLR), nitrogen loading rate (NLR)). Results indicated that ACMFCs could be used to treat LCNW successfully with high pollutant removal rates and sustainable current generation. Maximum removal efficiencies of 94% COD, 92% NH₄⁺-N, and 92% total nitrogen (TN) were achieved. A maximum power density of 1400 mW m^-2 and columbic efficiency of 69.2% were also obtained at a low C/N ratio of 1.7-2.6. Low C/N ratios promoted SND by balancing nitritation and denitritation. The microbial community and their predicated function results showed considerable nitrifiers and denitrificans were enriched in the ACMFCs, contributing to SND and power recovery. Further analyses showed that the NH₄⁺-N could inhibit SND, but PBS and R_ext had no obvious effects on this outcome. Co-occurrence network analysis demonstrated that power is positively correlated with COD and R_ext; strong correlations between organic removal and COD, and between nitrogen removal and ammonia, conductivity, and C/N ratio were also noted. Overall, the appropriate control of such parameters is necessary to achieve efficient SND in ACMFCs for LCNW treatment.

Systematic and bibliographic review of sustainability indicators for contaminated site remediation: Comparison between China and western nations

Sustainable remediation, which promotes the use of more sustainable practices during environmental clean-up activities, is an area of intense international development. While numerous indicators related to sustainable remediation assessment have been utilized and published in related academic literature, they are difficult to unify and vary in emphasis between countries. Following literature retrieval from CNKI, Springer, ScienceDirect, and Wiley Online databases, we present a systematic and bibliometric analysis of relevant national and international literature to define the most frequently considered indicators of sustainability, which play important roles in selecting remediation technologies or site management methods from a sustainability perspective. Following the application of co-occurrence analysis and social network analysis, the results indicate that 1) environmental criteria are most commonly used in evaluating remediation technologies, with significantly less emphasis on social criteria in Chinese publications in particular; 2) with an increasing number of publications in the last 20 years, sustainable remediation has gone through an initial stage, rising stage, and burst or wider adoption stage, characterized by a transformation of the research theme from a predominantly risk-based management approach to a sustainability-based one, with risk management as an underpinning principle; 3) health, resource, cost, and time are the most widely used indicators in terms of social, environmental, economic, and technical criteria, respectively; 4) clear differences exist between China and other nations, particularly in the frequency of usage of each indicator, the application of social criteria, and preferred stakeholders. Nevertheless, China has made significant progress and now makes increasing contributions to sustainable remediation at an international level.

The progress and trend of pro-environmental behavior research: a bibliometrics-based visualization analysis

Pro-environmental behavior (PEB) has always been a hot topic in academic and practical, and it is highly necessary to explore the research progress and development trend of PEB. Based on 1038 relevant literatures published and the Web of Science core database, this paper used citation analysis, co-word analysis and cluster analysis methods to systematically analyze the dynamic evolution process of PEB's research topics, knowledge base and subject areas. The results show that PEB research is currently in a period of rapid growth. And PEB research presents typical multidisciplinary characteristics, mainly focuses on Psychology-Education-Social, Economics-Economic-Political, Environmental-Toxicology-Nutrition and other disciplines. Then, this study also finds that the PEB research hotspots mainly concentrated in seven directions such as "Environmental cognition, emotion and motivation process", etc., which can be further classified into three horizontal levels and three vertical levels. This study will provide valuable theoretical and practical reference for the future research of PEB.

Global distribution of publications in anesthesiology : A bibliometric analysis from 1999 to 2018

PURPOSE

Only few studies have analyzed the global distribution of anesthesia research. This study was designed to reveal the current global research status of anesthesiology.

METHODS

Articles published between 1999 and 2018 in international journals in the field of anesthesiology were retrieved from the PubMed database. The top 20 ranked countries were identified. The gross domestic product (GDP) of each country was also retrieved to reveal the correlation between research outputs and the economy. The total outputs and outputs per 10 million inhabitants in each country were calculated and compared. To analyze the quality of publications among the top 10 ranked countries, the impact factor (IF), article influence score (AIS), and immediacy index (ImI) were calculated and analyzed. In addition, the keywords of publications were retrieved to conduct co-occurrence analysis in order to determine the research focus in anesthesiology.

RESULTS

A total of 112,918 articles were published in 30 selected journals from 1999 to 2018. There was a positive correlation between research outputs and GDP of 10 countries (p < 0.001, r = 0.825). The USA ranked 1st with 21,703 articles, followed by the UK (8393 articles) and Germany (6504 articles). Canada had the highest number of publications per 10 million inhabitants in 2018. The UK had the highest average IF (4.70), average AIS (1.16), and average ImI (1.64) among the 10 countries. The research highlights in the field of anesthesiology included "mechanism and management of pain", "cardiac anesthesia", "pediatric anesthesia and airway management", "analgesia" and "anesthetic agents".

CONCLUSION

Regarding quantity trend, the output of global production in anesthesiology increased continuously as the number of articles from the high-output countries showed an increasing trend; however, there was still a gap between developing and developed countries in research quality. High-quality research should be encouraged in developing countries.

Patterns and drivers of microeukaryotic distribution along the North Equatorial Current from the Central Pacific Ocean to the South China Sea

Microeukaryotes have been recognized as highly abundant and diverse both in form and function, however, data on their diversity and distribution along marine currents remain scarce. Herein, the distribution of microeukaryotes in surface seawaters was analyzed along a 9000 km stretch of the North Equatorial Current (NEC) and its bifurcation using high throughput DNA sequencing. Significant distance-decay patterns were detected, and the microeukaryote communities were further divided into Central Pacific Ocean (CPO), Western Pacific Ocean (WPO), and South China Sea (SCS) groups. Statistical analyses suggested that the microeukaryotic assembly in the WPO is maintained by the CPO community transported via the NEC. Environmental selection contributed more to community variations than spatial processes did. Temperature and salinity were the two most important environmental factors to shape the examined communities. Altogether, characterizing the microeukaryotic diversity and distribution along the NEC provided an insight into the drivers of their distribution in open oceans.

[Visual analysis of research progress on emotional labor of medical staff in China]

Objective: To summarize the research progress of medical emotional labor in China, and provide data reference for medical workers in the field of emotional labor. Methods: In March 2020, we searched the research content of emotional labor of medical workers through CNKI system, and analyzed it by using CiteSpace software. We visualized the topic of emotional labor of medical workers by using the knowledge map formed by keyword co-occurrence and keyword clustering, as well as the emergent words and time zone map. The analysis contents include the basic information characteristics of the selected literature, research hotspots and topics, research trends and frontiers. Results: The first related literature was published in 2008, and 126 related literatures were retrieved. Research hotspots include 'emotional labor', 'nurse', 'work burnout', 'medical staff' and 'work satisfaction', etc. Topics can be divided into three categories: research objects, variables affecting factors and medical workplace. There are 24 emergent words. In 2008, 2011, 2013, and 2015, important turning points for research changes exist. Conclusion: In the future, researchers in China can try to broaden the scope of medical subjects and influencing factors, etc., and be closely linked to the results of existing studies.

The knowledge domain and emerging trends in phytoremediation: a scientometric analysis with CiteSpace

As a cost-effective, environmentally friendly remediation technology, phytoremediation is defined as the use of green plants to remove pollutants from the environment or render them harmless and has been applied to a variety of contaminated sites throughout the world. There is a prominent phenomenon in which publications about phytoremediation increase each year and involve an increasing number of subject categories. This paper adopts the scientometric analysis method to assess the current state and explore the trends of phytoremediation research based on the bibliographic records retrieved from the Web of Science Core Collection (WoSCC). The results of this paper clearly answer the following questions. (1) What are the publishing characteristics of research on the topic of phytoremediation? What are the characteristics of academic collaboration in phytoremediation research? (2) What are the characteristics and development trends of phytoremediation research? (3) What are the hotspots and frontiers of phytoremediation research? Overall, the research method provides a new approach for the assessment of the performance of phytoremediation research. These results may help new researchers quickly integrate into the field of phytoremediation, as they can easily grasp the frontiers of phytoremediation research and obtain more valuable scientific information. This study also provides references for the follow-up research of relevant researchers.

A Probabilistic Co-Occurrence Approach for Estimating Likelihood of Spatial Overlap Between Listed Species Distribution and Pesticide Use Patterns

Characterizing potential spatial overlap between federally threatened and endangered ("listed") species distributions and registered pesticide use patterns is important for accurate risk assessment of threatened and endangered species. Because accurate range information for such rare species is often limited and agricultural pesticide use patterns are dynamic, simple spatial co-occurrence methods may overestimate or underestimate overlap and result in decisions that benefit neither listed species nor the regulatory process. Here, we demonstrate a new method of co-occurrence analysis that employs probability theory to estimate spatial distribution of rare species populations and areas of pesticide use to determine the likelihood of potential exposure. Specifically, we 1) describe a probabilistic method to estimate pesticide use based on crop production patterns; 2) construct species distribution models for 2 listed insect species whose ranges were previously incompletely described, the rusty-patched bumble bee (Bombus affinis) and the Poweshiek skipperling (Oarisma poweshiek); and 3) develop a probabilistic co-occurrence methodology and assessment framework. Using the principles of the Bayes' theorem, we constructed probabilistic spatial models of pesticide use areas by integrating information from land-cover spatial data, agriculture statistics, and remote-sensing data. We used maximum entropy methods to build species distribution models for 2 listed insects based on species collection and observation records and predictor variables relevant to the species' biogeography and natural history. We further developed novel methods for refinement of these models at spatial scales relevant to US Fish and Wildlife Service (FWS) regulatory priorities (e.g., critical habitat areas). Integrating both probabilistic assessments and focusing on USFWS priority management areas, we demonstrate that spatial overlap (i.e., potential for exposure) is not deterministic but instead a function of both species distribution and land use patterns. Our work serves as a framework to enhance the accuracy and efficiency of threatened and endangered species assessments using a data-driven likelihood analysis of species co-occurrence. Integr Environ Assess Manag 2019;00:1-12. © 2019 SETAC.

Worldwide co-occurrence analysis of 17 species of the genus Brachypodium using data mining

The co-occurrence of plant species is a fundamental aspect of plant ecology that contributes to understanding ecological processes, including the establishment of ecological communities and its applications in biological conservation. A priori algorithms can be used to measure the co-occurrence of species in a spatial distribution given by coordinates. We used 17 species of the genus Brachypodium, downloaded from the Global Biodiversity Information Facility data repository or obtained from bibliographical sources, to test an algorithm with the spatial points process technique used by Silva et al. (2016), generating association rules for co-occurrence analysis. Brachypodium spp. has emerged as an effective model for monocot species, growing in different environments, latitudes, and elevations; thereby, representing a wide range of biotic and abiotic conditions that may be associated with adaptive natural genetic variation. We created seven datasets of two, three, four, six, seven, 15, and 17 species in order to test the algorithm with four different distances (1, 5, 10, and 20 km). Several measurements (support, confidence, lift, Chi-square, and p-value) were used to evaluate the quality of the results generated by the algorithm. No negative association rules were created in the datasets, while 95 positive co-occurrences rules were found for datasets with six, seven, 15, and 17 species. Using 20 km in the dataset with 17 species, we found 16 positive co-occurrences involving five species, suggesting that these species are coexisting. These findings are corroborated by the results obtained in the dataset with 15 species, where two species with broad range distributions present in the previous dataset are eliminated, obtaining seven positive co-occurrences. We found that B. sylvaticum has co-occurrence relations with several species, such as B. pinnatum, B. rupestre, B. retusum, and B. phoenicoides, due to its wide distribution in Europe, Asia, and north of Africa. We demonstrate the utility of the algorithm implemented for the analysis of co-occurrence of 17 species of the genus Brachypodium, agreeing with distributions existing in nature. Data mining has been applied in the field of biological sciences, where a great amount of complex and noisy data of unseen proportion has been generated in recent years. Particularly, ecological data analysis represents an opportunity to explore and comprehend biological systems with data mining and bioinformatics tools.

Mind the gaps: overlooking inaccessible regions confounds statistical testing in genome analysis

Background

The current versions of reference genome assemblies still contain gaps represented by stretches of Ns. Since high throughput sequencing reads cannot be mapped to those gap regions, the regions are depleted of experimental data. Moreover, several technology platforms assay a targeted portion of the genomic sequence, meaning that regions from the unassayed portion of the genomic sequence cannot be detected in those experiments. We here refer to all such regions as inaccessible regions, and hypothesize that ignoring these regions in the null model may increase false findings in statistical testing of colocalization of genomic features.

Results

Our explorative analyses confirm that the genomic regions in public genomic tracks intersect very little with assembly gaps of human reference genomes (hg19 and hg38). The little intersection was observed only at the beginning and end portions of the gap regions. Further, we simulated a set of synthetic tracks by matching the properties of real genomic tracks in a way that nullified any true association between them. This allowed us to test our hypothesis that not avoiding inaccessible regions (as represented by assembly gaps) in the null model would result in spurious inflation of statistical significance. We contrasted the distributions of test statistics and p-values of Monte Carlo-based permutation tests that either avoided or did not avoid assembly gaps in the null model when testing colocalization between a pair of tracks. We observed that the statistical tests that did not account for assembly gaps in the null model resulted in a distribution of the test statistic that is shifted to the right and a distribution of p-values that is shifted to the left (indicating inflated significance). We observed a similar level of inflated significance in hg19 and hg38, despite assembly gaps covering a smaller proportion of the latter reference genome.

Conclusion

We provide empirical evidence demonstrating that inaccessible regions, even when covering only a few percentages of the genome, can lead to a substantial amount of false findings if not accounted for in statistical colocalization analysis.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2438-1) contains supplementary material, which is available to authorized users.

Bacterial Succession Decreases Network Complexity During Plant Material Decomposition in Mangroves

In this study, 16S rRNA gene amplicon sequencing was used to assess bacterial diversity and dynamics throughout different stages of leaves decomposition of three plant species (Rhizophora mangle, Laguncularia racemosa, and Avicennia schaueriana) in three distinct mangroves of São Paulo state, Brazil. The experiments were conducted in microcosms. Phylogenetic diversity (Faiths' PD) index showed differences between samples and suggested that some treatments like R. mangle increased their bacterial diversity through time. Principal coordinate analysis revealed that community's profile varied based on mangroves, followed by plant species and time. A clear succession patterns was observed in this study, i.e., some microorganisms with low abundance in the initial phases gradually became dominant (e.g., Alphaproteobacteria), whereas microbes that were initially predominant became low (e.g., Gammaproteobacteria). Co-occurrence analyses were performed for all times of plant degradation aiming to better understand the relationships between bacterial populations. The c-score index was done to test the randomness of the community assemblage during the stages of decomposition. For all degradation time points, the values of the observed c-score were higher than the values of the simulated c-score. This result indicated that during plant decomposition, the bacterial communities presented less co-occurrence than expected by chance and that these communities were not randomly assembled but instead they are driven by species interactions. Network analyses results showed that in the conditions presented in this experiment, the initial stages of leaf decomposition formed more connected and complex networks than the later stages. These results suggest that resource competition was a determinant in these specific mangroves during plant degradation, mainly in the initial periods.

Behavioral responses to emotional challenges in female rats living in a seminatural environment: The role of estrogen receptors

Estrogen receptors (ERs) are involved in sexual as well as non-sexual behaviors. In the present study we assessed the effects of stimuli inducing positive or negative affect on sociosexual, exploratory and fear-related behaviors of female rats housed in groups (4 females, 3 males) in a seminatural environment. Ovariectomized females were treated with oil, 17β‑estradiol benzoate (EB, 18 μg/kg), the ERα agonist propylpyrazoletriol (PPT), or the ERβ agonist diarylpropionitrile (DPN) (both 2 × 10 mg/rat). On the test day, the females were exposed to a sequence of events consisting of lavender odor, Mozart's Sonata for Two Pianos K448, chocolate pellets, white noise and fox odor (2,3,5‑Trimethyl‑3‑thiazoline, TMT). All these events are known to induce positive or negative affect. Behavior was carefully observed from the video record. White noise suppressed sexual behaviors and reduced the time spent in the open area of the environment. TMT had no consistent effect whereas exposure to music caused avoidance of the open area. Exposure to chocolate increased exploratory and social behavior. Lavender odor enhanced exploratory behavior. PPT and EB stimulated sexual behaviors, whereas DPN was ineffective. Co-occurrence analyses of the sequence of behavioral patterns revealed that PPT and EB consistently belonged to clusters different from oil and DPN, whereas DPN was separate from oil only under fear-inducing experimental conditions. These data, from a procedure with external validity, confirm that the ERα is crucial for sexual behaviors, that these behaviors are reduced under stressful conditions, and that the ERβ may have some role in fear-related behaviors.