Key Research Research Articles

Network Pharmacological Analysis and Experimental Validation of the Effects of Silybin on Proliferation, Migration, and Immunotherapy of Papillary Thyroid Cancer.

The study aimed to use network pharmacology research and in vitro experiments to investigate the material basis and molecular mechanisms of silybin in the treatment of papillary thyroid carcinoma. Papillary thyroid cancer (PTC) has a decent prognosis; however, recurrence and metastasis are the leading causes of death in patients with PTC. A key research focus in thyroid cancer treatment is the inhibition of PTC proliferation, invasion, and migration. Silybin, the major active element in the traditional Chinese herb silymarin, has been used to treat a range of diseases, including cancer, but no study has been undertaken to determine whether it can help prevent PTC. In this study, we attempted to determine through network pharmacology and in vitro experiments if silybin inhibits the development of papillary thyroid cancer by inhibiting cell cycle and invasive migration. To predict the probable targets and underlying mechanisms of silybin against PTC, a network pharmacology research was performed. In vitro experiments were conducted to further evaluate silybin's anti-cancer properties and priority targets against PTC. The datasets revealed a total of 489 silybin targets acting on PTC, and functional enrichment analysis suggested that the target genes were enriched in functions and pathways related to PTC development, invasion, migration, and immunotherapy. By constructing these target PPI networks, the seven hub genes, fibronectin 1 (FN1), tissue inhibitor of metalloproteinases 1 (TIMP1), N-cadherin (CDH2), collagen type III alpha 1 chain (COL3A1), cyclin D1 (CCND1), AP-1 transcription factor subunit (JUN), and hepatocyte growth factor receptor (MET) were found. These hub genes were determined to be highly linked to a worse clinicopathological form, a higher risk of metastatic recurrence, and a worse prognosis of PTC. The common immunological checkpoint gene expression levels were positively correlated with the expression levels of the hub genes. Silybin decreased the proliferative and metastatic capacity of PTC cells, according to in vitro investigations. When PTC was treated with silybin, the FN1/AKT signaling pathway was blocked, CCND1 expression was reduced, and CDH2, Vimentin, Snail, Slug and PD-L1 expressions were dramatically reduced, while E-cadherin expression was significantly elevated. These findings provide preliminary evidence that silybin inhibits PTC cell proliferation, metastasis, and invasion by altering the FN1/AKT signaling pathway and inhibiting the EMT process. Silybin can reverse immunosuppression in papillary thyroid cancer by affecting immunological checkpoint gene expression levels. These studies provide a theoretical and experimental scientific basis for the potential anticancer effects of silybin on PTC.

A Survey on Cyber Resilience: Key Strategies, Research Challenges, and Future Directions

Cyber resilience has become a major concern for both academia and industry due to the increasing number of data breaches caused by the expanding attack surface of existing IT infrastructure. Cyber resilience refers to an organisation’s ability to prepare for, absorb, recover from, and adapt to adverse effects typically caused by cyber-attacks that affect business operations. In this survey, we aim to identify the significant domains of cyber resilience and measure their effectiveness. We have selected these domains based on a literature review of frameworks, strategies, applications, tools, and technologies. We have outlined the cyber resilience requirements for each domain and explored solutions related to each requirement in detail. We have also compared and analysed different studies in each domain to find other ways of enhancing cyber resilience. Furthermore, we have compared cyber resilience frameworks and strategies based on technical requirements for various applications. We have also elaborated on techniques for improving cyber resilience. In the supplementary section, we have presented applications that have implemented cyber resilience. This survey comprehensively compares various popular cyber resilience tools to help researchers, practitioners, and organisations choose the best practices for enhancing cyber resilience. Finally, we have shared key findings, limitations, problems, and future directions.

Applications of artificial intelligence in the AEC industry: a review and future outlook

ABSTRACT In the context of “Industry 4.0,” the construction industry is undergoing a continuous process of digital transformation. In recent years, with the rapid development of artificial intelligence (AI) technology, AI has been successfully applied across various domains within the construction sector. This paper conducts a comprehensive review based on scientific bibliometric analysis and systematic evaluation to provide an overview of AI applications and developments in the architecture, engineering, and construction (AEC) industry, as well as to discuss future research trends. Firstly, a bibliometric analysis was carried out on 3,410 journal articles published between 2003 and 2022. This analysis examined characteristics such as annual publication trends, key researchers and their affiliations, countries of origin, collaborative relationships, prominent journals, and keyword clustering. Subsequently, through systematic review, three critical themes in the field were identified and analyzed: performance prediction, intelligent optimization, and engineering safety and risk. To gain a deeper understanding of cutting-edge AI technologies and their potential applications in the AEC sector, potential future research directions were discussed, including digital twins, blockchain, augmented reality, and virtual reality, all aimed at driving the intelligent and digital transformation of the AEC industry.

Философия как призвание и профессия: история становления философа в России, рассказанная от первого лица

This essay is a recollection of my years of study at Moscow State University and the beginning of work at the Higher School of Economics, as well as a reflection on the current period and state of philosophy in Russia in general. The purpose of this essay is an attempt to reflect on one’s belonging to a certain generation of philosophers, comparing it with past and future generations, as well as an attempt to trace the successive thread of generations. Using the example of my own apprenticeship, as well as teaching, the distinctive features of each new stage in the formation of philosophy in Russia are shown. Based on personal experience, the similarities and differences between Russian and foreign practice of teaching philosophy, as well as working in the academy as a professional philosopher, are thought through. The influence of the most significant and key studies and researchers on my philosophical perception, as well as on the formation of my generation of philosophers, is traced. The names and faces represent the characteristic spirit of a certain philosophical era, the most valuable and defining relationships for the author with colleagues and friends, the most important and promising projects and joint endeavors are recalled.

Application of AI in Sepsis: Citation Network Analysis and Evidence Synthesis.

Artificial intelligence (AI) has garnered considerable attention in the context of sepsis research, particularly in personalized diagnosis and treatment. Conducting a bibliometric analysis of existing publications can offer a broad overview of the field and identify current research trends and future research directions. The objective of this study is to leverage bibliometric data to provide a comprehensive overview of the application of AI in sepsis. We conducted a search in the Web of Science Core Collection database to identify relevant articles published in English until August 31, 2023. A predefined search strategy was used, evaluating titles, abstracts, and full texts as needed. We used the Bibliometrix and VOSviewer tools to visualize networks showcasing the co-occurrence of authors, research institutions, countries, citations, and keywords. A total of 259 relevant articles published between 2014 and 2023 (until August) were identified. Over the past decade, the annual publication count has consistently risen. Leading journals in this domain include Critical Care Medicine (17/259, 6.6%), Frontiers in Medicine (17/259, 6.6%), and Scientific Reports (11/259, 4.2%). The United States (103/259, 39.8%), China (83/259, 32%), United Kingdom (14/259, 5.4%), and Taiwan (12/259, 4.6%) emerged as the most prolific countries in terms of publications. Notable institutions in this field include the University of California System, Emory University, and Harvard University. The key researchers working in this area include Ritankar Das, Chris Barton, and Rishikesan Kamaleswaran. Although the initial period witnessed a relatively low number of articles focused on AI applications for sepsis, there has been a significant surge in research within this area in recent years (2014-2023). This comprehensive analysis provides valuable insights into AI-related research conducted in the field of sepsis, aiding health care policy makers and researchers in understanding the potential of AI and formulating effective research plans. Such analysis serves as a valuable resource for determining the advantages, sustainability, scope, and potential impact of AI models in sepsis.

A comprehensive value-based method for new nuclear medical service pricing: with case study of radium [223Ra] bone metastases treatment

ImportanceInnovative nuclear medicine services offer substantial clinical value to patients. However, these advancements often come with high costs. Traditional payment strategies do not incentivize medical institutes to provide new services nor determine the fair price for payers. A shift towards a value-based pricing strategy is imperative to address these challenges. Such a strategy would reconcile the cost of innovation with incentives, foster transparent allocation of healthcare resources, and expedite the accessibility of essential medical services.ObjectiveThis study aims to develop and present a comprehensive, value-based pricing model for new nuclear medicine services, illustrated explicitly through a case study of the radium [223Ra] treatment for bone metastases. In constructing the pricing model, we have considered three primary value determinants: the cost of the new service, associated service risk, and the difficulty of the service provision. Our research can help healthcare leaders design an evidence-based Fee-For-Service (FFS) payment reference pricing with nuclear medicine services and price adjustments.Design, setting and participantsThis multi-center study was conducted from March 2021 to February 2022 (including consultation meetings) and employed both qualitative and quantitative methodologies. We organized focus group consultations with physicians from nuclear medicine departments in Beijing, Chongqing, Guangzhou, and Shanghai to standardize the treatment process for radium [223Ra] bone metastases. We used a specially designed ‘Radium Nuclide [223Ra] Bone Metastasis Data Collection Form’ to gather nationwide resource consumption data to extract information from local databases. Four interviews with groups of experts were conducted to determine the add-up ratio, based on service risk and difficulty. The study organized consultation meeting with key stakeholders, including policymakers, service providers, clinical researchers, and health economists, to finalize the pricing equation and the pricing result of radium [223Ra] bone metastases service.Main outcomes and measuresWe developed and detailed a pricing equation tailored for innovative services in the nuclear medicine department, illustrating its application through a step-by-step guide. A standardized service process was established to ensure consistency and accuracy. Adhering to best practice guidelines for health cost data analysis, we emphasized the importance of cross-validation of data, where validated data demonstrated less variation. However, it required a more advanced health information system to manage and analyze the data inputs effectively.ResultsThe standardized service of radium [223Ra] bone metastases includes: pre-injection assessment, treatment plan, administration, post-administration monitoring, waste disposal and monitoring. The average duration for each stage is 104 min, 39 min, 25 min, 72 min and 56 min. A standardized monetary value for medical consumables is 54.94 yuan ($7.6), and the standardised monetary value (medical consumables cost plus human input) is 763.68 yuan ($109.9). Applying an agreed value add-up ratio of 1.065, the standardized value is 810.19 yuan ($116.9). Feedback from a consultation meeting with policymakers and health economics researchers indicates a consensus that the pricing equation developed was reasonable and well-grounded.ConclusionThis research is the first study in the field of nuclear medicine department pricing methodology. We introduce a comprehensive value-based nuclear medical service pricing method and use radium[223Ra] bone metastases treatment pricing in China as a case study. This study establishes a novel pricing framework and provides practical instructions on its implementation in a real-world healthcare setting.

Trust, risk perception, and intention to use autonomous vehicles: an interdisciplinary bibliometric review

AbstractAutonomous vehicles (AV) offer promising benefits to society in terms of safety, environmental impact and increased mobility. However, acute challenges persist with any novel technology, inlcuding the perceived risks and trust underlying public acceptance. While research examining the current state of AV public perceptions and future challenges related to both societal and individual barriers to trust and risk perceptions is emerging, it is highly fragmented across disciplines. To address this research gap, by using the Web of Science database, our study undertakes a bibliometric and performance analysis to identify the conceptual and intellectual structures of trust and risk narratives within the AV research field by investigating engineering, social sciences, marketing, and business and infrastructure domains to offer an interdisciplinary approach. Our analysis provides an overview of the key research area across the search categories of ‘trust’ and ‘risk’. Our results show three main clusters with regard to trust and risk, namely, behavioural aspects of AV interaction; uptake and acceptance; and modelling human–automation interaction. The synthesis of the literature allows a better understanding of the public perception of AV and its historical conception and development. It further offers a robust model of public perception in AV, outlining the key themes found in the literature and, in turn, offers critical directions for future research.

E-GOVERNANCE IN REVENUE COLLECTION AND CUSTOMS ADMINISTRATION IN SIERRA LEONE – A SURVEY

The willingness of taxpayers to comply with their obligations depends to a large extent upon the perception that the funds collected are put to good use. It also depends on how easy and convenient it is for the taxpayer to comply. Hence getting taxpayers to voluntarily pay their correct taxes at the right time is the dream of every government. The four key research objectives are: to find out whether the implementation of ICT will improve the performance of public enterprises; to investigate whether there is a link between the tax filing system and revenue collection; to determine the significance of tax compliance and performance of the National Revenue Authority (NRA) and to examine the relationship between tax administration and revenue collection. Data was collected through questionnaires from selected tax administrators and taxpayers in Freetown and two provincial locations, Bo and Makeni, using convenience sampling. Descriptive statistical analysis techniques were employed for data analysis. Findings from the study revealed that a vast majority of the respondents believe that the implementation of ICT results in better performance of public enterprises; and that there is a link between the tax filing system and revenue collection which allows refunds to be deposited directly into taxpayers' bank accounts; the level of tax compliance is significant to the performance of the National Revenue Authority; and adoption of ICT has positive impact on a country’s tax collection rate. The paper recommends that the Government of Sierra Leone should embark on public sensitisation on the benefits of the adoption and use of ICT infrastructure that aids easy tax administration and collection in the other rural regions of the country.<p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/soc/0758/a.php" alt="Hit counter" /></p>

Renewable Energy Potentials and Roadmap in Brazil, Austria, and Germany

The emerging energy transition is particularly described as a move towards a cleaner, lower-carbon system. In the context of the global shift towards sustainable energy sources, this paper reviews the potential and roadmap for hydrogen energy as a crucial component of the clean energy landscape. The primary objective is to present a comprehensive literature overview, illuminating key themes, trends, and research gaps in the scientific discourse concerning hydrogen production and energy policy. This review focuses particularly on specified geographic contexts, with an emphasis on understanding the unique energy policies related to renewable energy in Brazil, Austria, and Germany. Given their distinct social systems and developmental stages, this paper aims to delineate the nuanced approaches these countries adopt in their pursuit of renewable energy and the integration of hydrogen within their energy frameworks. Brazil exhibits vast renewable energy potential, particularly in wind and solar energy sectors, positioning itself for substantial growth in the coming years. Germany showcases a regulatory framework that promotes innovation and technological expansion, reflecting its highly developed social system and commitment to transitioning away from fossil fuels. Austria demonstrates dedication to decarbonization, particularly through the exploration of biomethane for residential heating and cooling.

Adaptive Force Field Parameter Optimization for Expanding Reaction Simulations within Wide-Ranged Temperature.

Large-scale and long-term simulation of chemical reactions are key research topics in computational chemistry. However, there are still difficulties in simulating high-temperature reactions, such as polymer thermal decomposition. Herein, we introduce an adaptive potential parameter optimization framework designed to automatically fine-tune parameters, and the application of it to optimize ReaxFF parameters enhances the accuracy of chemical reaction simulations conducted at experimental temperatures. To achieve this, we leverage the power of Random Forests and interpretable machine learning techniques that enable the identification and selection of parameters that exert a substantial influence on the target attribute. By training deep neural network (NN) models, we established optimized parameter associations with reference properties. We train deep neural network (NN) models to establish the relationship between the optimized parameters and reference properties. We employ a Genetic Algorithm (GA) to utilize the surrogate NN model and the quantum mechanical targets to speed up the search for the optimal parameters. Our simulation results of resin pyrolysis show that the adaptive optimized ReaxFF can predict the peak temperature more accurately and obtain reasonable product composition under conditions that more closely resemble experimental scenarios. This work facilitates advances in force field parameter optimization for more accurate and universal reaction simulations.

Crafting Creative Melodies: A User-Centric Approach for Symbolic Music Generation

Composing coherent and structured music is one of the main challenges in symbolic music generation. Our research aims to propose a user-centric framework design that promotes a collaborative environment between users and knowledge agents. The primary objective is to improve the music creation process by actively involving users who provide qualitative feedback and emotional assessments. The proposed framework design constructs an abstract format in which a musical piece is represented as a sequence of musical samples. It consists of multiple agents that embody the dynamics of musical creation, emphasizing user-driven creativity and control. This user-centric approach can benefit individuals with different musical backgrounds, encouraging creative exploration and autonomy in personalized, adaptive environments. To guide the design of this framework, we investigate several key research questions, including the optimal balance between system autonomy and user involvement, the extraction of rhythmic and melodic features through musical sampling, and the effectiveness of topological and hierarchical data representations. Our discussion will highlight the different aspects of the framework in relation to the research questions, expected outcomes, and its potential effectiveness in achieving objectives. Through establishing a theoretical foundation and addressing the research questions, this work has laid the groundwork for future empirical studies to validate the framework and its potential in symbolic music generation.

Towards Sustainable Modes for Remote Monitoring in Waste Management: A Study of Marginalized Urban Areas in Romania

Implementing circular and carbon-neutral waste management practices is essential for promoting environmental sustainability and public health. This is particularly critical in marginalized areas, where effective waste management strategies play a pivotal role in addressing environmental challenges, promoting community well-being, and fostering sustainable development. The article will explore waste management in marginalized urban areas in an integrated manner, exploring key European research domains: waste management, housing in informal settlements, and spatial information. We examined 37 Local Development Strategies (LDSs) for marginalized urban areas (MUAs) in Romania to determine whether they incorporate waste management measures. In addition, we used QGIS along with imagery accessible on the European Space Agency’s platform. This supplies Copernicus Sentinel-2 satellite data. We referred to a specific urban area, namely the Municipality of Turda, selected from the endorsed LDS, where the illegal landfills are present. Based on the data presented in the LDS and confirmed with the in situ verification or remotely using street view platforms, we have determined that the identified areas indeed contain illegal waste deposits. To validate these findings, the methodology employed, along with observations and results from the Turda study area, can be extended to other territories and marginalized urban areas.

Use of Practice-Based Research Networks in Massage Therapy Research.

Massage therapy is a profession, not simply an intervention, and pathways are needed to connect all key massage therapy profession components-clinicians, patient/clients, and the work-to the scholarship and research that describes, investigates, and shapes practice. While the volume of massage-related research has grown over the past few decades, much of the growing massage evidence base is not reflective of real-world massage therapy, nor is research typically conducted through the clinical lens of the massage therapy discipline. This situation reflects the unfortunate disconnect between massage therapy research and massage therapy practice, while magnifying a key research infrastructure deficiency within the massage therapy discipline: the who and where research is conducted is disconnected from the who and where massage therapy is practiced. Practice-based research networks (PBRNs) are a staple of primary care and other health professions research reflecting real life, discipline-focused practice that seeks to address the needs of the discipline's practitioners and patients. The PBRN model fits well with the directional need of massage therapy research. This paper presents a commentary on the use of PBRNs in massage therapy research, and the current state of PBRN research within the field of massage therapy, namely the recently launched MassageNet PBRN.

Exploring the nutritional landscape and emerging trends in kidney stone research: visualization and bibliometric analysis

BackgroundKidney stones, or renal nephrolithiasis, are common and dangerous, increasing the risk of chronic kidney disease. Dietary manipulation is essential for the prevention and recurrence of kidney stones. Research into nutrition and kidney stones lacks library analysis, making it difficult to identify new trends. This bibliometric study was conducted to explore the current landscape of research on nutrition and kidney stones worldwide. This paper also emphasizes significant research trends in this area over the past two decades, aiming to assist researchers in understanding the current research status and identifying potential future directions.MethodsThe scholarly literature pertaining to diet and kidney stones was systematically explored utilizing SciVerse Scopus to identify pertinent research articles released from 2003 to 2022. The examination encompassed an assessment of publication patterns, key contributors, focal areas of research, prevalent themes, influential articles, and emerging research avenues. Following data extraction to Excel, analyses, including frequencies, percentages, and linear regression, were conducted. Visual exploration was facilitated through the use of the VOSviewer program version 1.6.19.ResultsBetween 2003 and 2022, 697 publications on nutrition and kidney stones were identified. There were 478 original articles (68.58%), 120 reviews (17.22%) and 99 other types of publications (14.20%). The United States is the most productive country, with significant growth in research in the fields of nutrition and kidney stones. The United States has demonstrated the strongest partnerships between researchers’ networks from various countries. Cluster analysis revealed three major research themes: sex differences in kidney stone disease, the correlation between increased dietary acid consumption and calcium oxide kidney stones, and nephrolithiasis associated with a ketogenic diet.ConclusionsThis study offers a thorough examination of nutrition and kidney stone research, encompassing key research domains, collaborative networks, and emerging patterns. The findings can aid researchers in gaining insight into the present landscape of the discipline and determining future research directions.

The past, present, and future of crowdsourcing and innovation: A bibliometric analysis and future research agenda

This research article addresses the current status and emerging trends in the literature at the intersection of crowdsourcing and innovation. While separate reviews exist for crowdsourcing and innovation individually, a comprehensive literature review specific to their intersection is lacking. Therefore, this study conducts a bibliometric meta-analysis of the extensive body of literature in the field of innovation and crowdsourcing, aiming to fill this research gap. The analysis encompasses all articles in Elsevier's Scopus database that incorporate relevant terms in their titles, abstracts, or keywords, resulting in a sample of 180 articles. VosViewer and Bibliometrix package in R are employed for the analysis. The analysis reveals three key research clusters, including the role of crowdsourcing in fostering organizational innovation, crowdsourcing-based social capital formation and its impact on organizational value creation, and the role of crowdsourcing platforms in facilitating engagement between the crowd and the organization. Adopting a holistic perspective, this research contributes new insights into the interconnections between crowdsourcing and innovation research fields. Additionally, the analysis provides clarity on research content, evolutionary context, and reveals emerging research trends in this domain.

Sampling business process event logs with guarantees

SummaryEvent log sampling has emerged as a key research focus in the field of process mining, aiming to enhance the efficiency of various process mining tasks, including model discovery, conformance checking, and process prediction. However, current log sampling techniques often fail to ensure high‐quality sample logs. This paper introduces a novel framework to support efficient event log sampling without compromising the quality of the sample log compared to the original one. The approach revolves around the consideration of directly‐follows relation (DFR) among business tasks as the fundamental behavior unit of an event log. By ensuring the DFR equivalence between the original and sample logs, the proposed technique addresses the challenge of sample log quality from the model discovery point of view. The framework is instantiated by seven distinct sampling strategies each has its own specialty and is fully implemented in the open‐source process mining tool platform ProM. To validate its effectiveness, we conducted a comprehensive experimental evaluation using 12 publicly available real‐life event logs against state‐of‐the‐art sampling techniques. The results clearly demonstrate that our technique significantly improves model discovery efficiency while upholding high quality of the discovered models.

Bibliometric Mapping of Academic Research Focusing on Animal Production and Climate Change in Association with Methane Emissions and Animal Productivity

Climate change is a pressing global challenge, and animal production is a major contributor to methane emissions. This study examines the academic landscape of research on CH4 emissions and animal productivity, with a focus on cattle, sheep, and goats. Using a bibliometric analysis of 2500 documents published between 1987 and 2023, the study finds that research on this topic has increased significantly over time, with a record high in 2022. The leading countries in terms of research output are the United States, China, Brazil, Canada, and Italy. The study identifies several key research themes, including the impact of CH4 emissions on animal productivity parameters, the development of mitigation strategies, and the assessment of trade-offs and synergies between CH4 emissions reduction and other sustainability goals. The study concludes by highlighting the importance of continued research on CH4 emissions and animal productivity to develop and implement effective mitigation strategies. This study has important implications for policymakers, researchers, and the livestock industry. Policymakers can use the findings to inform the development of policies and regulations that support the reduction of CH4 emissions from animal production. Researchers can use the findings to identify gaps in the existing knowledge base and to develop new research directions. The livestock industry can use the findings to develop more sustainable production practices. By working together, policymakers, researchers, and the livestock industry can develop and implement effective mitigation strategies that reduce greenhouse gas emissions, protect the environment, and support sustainable food production.

The global distribution and the risk prediction of relapsing fever group Borrelia: a data review with modelling analysis

The recent discovery of emerging relapsing fever group Borrelia (RFGB) species, such as Borrelia miyamotoi, poses a growing threat to public health. However, the global distribution and associated risk burden of these species remain uncertain. We aimed to map the diversity, distribution, and potential infection risk of RFGB. We searched PubMed, Web of Science, GenBank, CNKI, and eLibrary from Jan 1, 1874, to Dec 31, 2022, for published articles without language restriction to extract distribution data for RFGB detection in vectors, animals, and humans, and clinical information about human patients. Only articles documenting RFGB infection events were included in this study, and data for RFGB detection in vectors, animals, or humans were composed into a dataset. We used three machine learning algorithms (boosted regression trees, random forest, and least absolute shrinkage and selection operator logistic regression) to assess the environmental, ecoclimatic, biological, and socioeconomic factors associated with the occurrence of four major RFGB species: Borrelia miyamotoi, Borrelia lonestari, Borrelia crocidurae, and Borrelia hermsii; and mapped their worldwide risk level. We retrieved 13 959 unique studies, among which 697 met the selection criteria and were used for data extraction. 29 RFGB species have been recorded worldwide, of which 27 have been identified from 63 tick species, 12from 61 wild animals, and ten from domestic animals. 16 RFGB species caused human infection, with a cumulative count of 26 583 cases reported from Jan 1, 1874, to Dec 31, 2022. Borrelia recurrentis (17 084 cases) and Borrelia persica (2045 cases) accounted for the highest proportion of human infection. B miyamotoi showed the widest distribution among all RFGB, with a predicted environmentally suitable area of 6·92 million km2, followed by Blonestari (1·69 million km2), B crocidurae (1·67 million km2), and B hermsii (1·48 million km2). The habitat suitability index of vector ticks and climatic factors, such as the annual mean temperature, have the most significant effect among all predictive models for the geographical distribution of the four major RFGB species. The predicted high-risk regions are considerably larger than in previous reports. Identification, surveillance, and diagnosis of RFGB infections should be prioritised in high-risk areas, especially within low-income regions. National Key Research and Development Program of China.

The development and diversity of religious cognition and behavior: Protocol for Wave 1 data collection with children and parents by the Developing Belief Network.

The Developing Belief Network is a consortium of researchers studying human development in diverse social-cultural settings, with a focus on the interplay between general cognitive development and culturally specific processes of socialization and cultural transmission in early and middle childhood. The current manuscript describes the study protocol for the network's first wave of data collection, which aims to explore the development and diversity of religious cognition and behavior. This work is guided by three key research questions: (1) How do children represent and reason about religious and supernatural agents? (2) How do children represent and reason about religion as an aspect of social identity? (3) How are religious and supernatural beliefs transmitted within and between generations? The protocol is designed to address these questions via a set of nine tasks for children between the ages of 4 and 10 years, a comprehensive survey completed by their parents/caregivers, and a task designed to elicit conversations between children and caregivers. This study is being conducted in 39 distinct cultural-religious groups (to date), spanning 17 countries and 13 languages. In this manuscript, we provide detailed descriptions of all elements of this study protocol, give a brief overview of the ways in which this protocol has been adapted for use in diverse religious communities, and present the final, English-language study materials for 6 of the 39 cultural-religious groups who are currently being recruited for this study: Protestant Americans, Catholic Americans, American members of the Church of Jesus Christ of Latter-day Saints, Jewish Americans, Muslim Americans, and religiously unaffiliated Americans.

Research overview on the genetic mechanism underlying the biosynthesis of polysaccharide in tuber plants.

Tuber plants are of great significance in the world as human food crops. Polysaccharides, important metabolites in tuber plants, also serve as a source of innovative drugs with significant pharmacological effects. These drugs are particularly known for their immunomodulation and antitumor properties. To fully exploit the potential value of tuber plant polysaccharides and establish a synthetic system for their targeted synthesis, it is crucial to dissect their metabolic processes and genetic regulatory mechanisms. In this article, we provide a comprehensive summary of the basic pathways involved in the synthesis of various types of tuber plant polysaccharides. We also outline the key research progress that has been made in this area in recent years. We classify the main types and functions of tuber plant polysaccharides and analyze the biosynthetic processes and genetic regulation mechanisms of key enzymes involved in the metabolic pathways of starch, cellulose, pectin, and fructan in tuber plants. We have identified hexokinase and glycosyltransferase as the key enzymes involved in the polysaccharide synthesis process. By elucidating the synthesis pathway of polysaccharides in tuber plants and understanding the underlying mechanism of action of key enzymes in the metabolic pathway, we can provide a theoretical framework for enhancing the yield of polysaccharides and other metabolites in plant culture cells. This will ultimately lead to increased production efficiency.