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This study aims to study the distribution characteristics of antibiotic resistance in direct-eating food and analysis of Citrobacter freundii genome and pathogenicity. Residual antibiotics and antibiotic resistance genes (ARGs) in the environment severely threaten human health and the ecological environment. The diseases caused by foodborne pathogenic bacteria are increasing daily, and the enhancement of antibiotic resistance of pathogenic bacteria poses many difficulties in the treatment of disease.

In this study, six fresh fruits and vegetable samples were selected for isolation and identification of culturable bacteria and analysis of antibiotic resistance. The whole genome of Citrobacter freundii isolated from cucumber was sequenced and analyzed by Oxford Nanopore sequencing.

The results show that 270 strains of bacteria were identified in 6 samples. From 12 samples of direct food, 2 kinds of probiotics and 10 kinds of opportunistic pathogens were screened. The proportion of Citrobacter freundii screened from cucumber was significantly higher than that from other samples, and it showed resistance to a variety of antibiotics. Whole genome sequencing showed that Citrobacter freundii was composed of a circular chromosome containing signal peptides, transmembrane proteins and transporters that could induce antibiotic efflux, indicating that Citrobacter freundii had strong adaptability to the environment. The detection of genes encoding carbohydrate active enzymes is more beneficial to the growth and reproduction of Citrobacter freundii in crops. A total of 29 kinds of ARGs were detected in Citrobacter freundii, mainly conferring resistance to fluoroquinolones, aminoglycosides, carbapenem, cephalosporins and macrolides. The main mechanisms are the change in antibiotic targets and efflux pumps, the change in cell permeability and the inactivation of antibiotics and the detection of virulence factors and ARGs, further indicating the serious risk to human health.

The detection of genomic islands and prophages increases the risk of horizontal transfer of virulence factors and ARGs, which spreads the drug resistance of bacteria and pathogenic bacteria more widely.

This systematic review aimed to identify and categorize applications using Fast Healthcare Interoperability Resources (FHIR) to support activities outside of direct healthcare provision.

A systematic electronic search was performed, and 53 studies were included after the selection process.

The results show that FHIR is being used to support (1) clinical research (i.e. clinical research based on interventional trials, data interoperability to support clinical research and advanced communication services to support clinical research), (2) public health and (3) medical education. Despite the FHIR potential to support activities outside of direct healthcare provision, some barriers were identified, namely difficulties translating the proposed applications to clinical environments or FHIR technical issues that require further developments.

This study provided a broad review of how FHIR is being applied in clinical activities outside of direct clinical care and identified three major domains, that is, clinical research, public health and medical education, being the first and most representative in terms of number of publications.

Genetics, a discipline of biology, is one of the most recent and rapidly advancing disciplines in science. This study aims to present a bibliometric analysis of the genetics research output of Iranian authors, map the intellectual structure of these studies and investigate the development path of this literature and the interrelationships among the main topics.

This study searched the Web of Science database for documentation of Iranian-published genetics research published up to 2020. Further, this study used HistCite software to profile and analyze the most cited articles and references and to draw their historiographies.

A database search revealed 21,329 documents that created the study population. The highest cited publications based on the Global Citation Score (GCS) and Local Citation Score (LCS) achieved scores of 602 and 47, respectively. The publication growth rate study demonstrated consistent expansion over time. The scientific maps based on LCS and GCS had five and four clusters, respectively. Furthermore, journal articles emerged as the predominant type of publication.

The significance of this study is in its contribution to understanding the genetics research position in Iran, informing policymakers and researchers, helping scientific collaboration and its impact on public attitudes and quality of life. The results of the present study, with benefits for various groups of communities, such as policymakers, academic groups and public society, can bridge the gap between theoretical research and practical implications.

The results of this study, by helping future advancement in health care, medical genetics and disease prevention, may have a direct and indirect positive influence on the quality of life. Furthermore, it may lead to more informed discussions on health care and biotechnology as well as influencing public attitudes and perceptions.

Ultimately, this study concludes that despite the proliferation of publications in terms of quantity and complexity, especially in areas such as disease diagnosis, prevention and treatment, there remains a need for more attention to other facets of genetics such as biology and biotechnology. Iranian publications are most related to population genetics, human genetics, molecular genetics, medical genetics, genomics, developmental genetics and evolutionary genetics out of 10 branches of genetics. This study reveals patterns in scientific outputs and authorship collaborations and plays an alternative and innovative role in revealing Iranian research trends in genetics.

This study aims to clarify influencing factors of overcapacity of new energy enterprises in China and accurately predict whether these enterprises have overcapacity.

Based on relevant data including the experience and evidence from the capital market in China, the research establishes a generic univariate selection-comparative machine learning model to study relevant factors that affect overcapacity of new energy enterprises from five dimensions. These include the governmental intervention, market demand, corporate finance, corporate governance and corporate decision. Moreover, the bridging approach is used to strengthen findings from quantitative studies via the results from qualitative studies.

The authors' results show that the overcapacity of new energy enterprises in China is brought out by the combined effect of governmental intervention corporate governance and corporate decision. Governmental interventions increase the overcapacity risk of new energy enterprises mainly by distorting investment behaviors of enterprises. Corporate decision and corporate governance factors affect the overcapacity mainly by regulating the degree of overconfidence of the management team and the agency cost. Among the eight comparable integrated models, generic univariate selection-bagging exhibits the optimal comprehensive generalization performance and its area under the receiver operating characteristic curve Area under curve (AUC) accuracy precision and recall are 0.719, 0.960, 0.975 and 0.983, respectively.

The proposed integrated model analyzes causes and predicts presence of overcapacity of new energy enterprises to help governments to formulate appropriate strategies to deal with overcapacity and new energy enterprises to optimize resource allocation. Ten main features which affect the overcapacity of new energy enterprises in China are identified through generic univariate selection model. Through the bridging approach, the impact of the main features on the overcapacity of new energy enterprises and the mechanism of the influence are analyzed.

This study aims to give a glimpse of the existing blockchain applications across industries and add to a complete knowledge of the blockchain’s properties.

Systematic literature review is used as the research strategy for this investigation and other aspects of the preferred reporting items for systematic reviews and meta-analyses framework have been incorporated to create a scholarly publications evaluation of the blockchain-based application in the financial arena and its future. The research looks at 86 studies published between 2018 and 2022.

There has been a steady but noticeable increase in the study of blockchain’s potential in many application domains over the past few of years. This rising tendency illustrates the newness and potential of blockchain technology, as well as the increasing attention from academics. According to the findings, blockchain is an appropriate solution for processing transactions using cryptocurrencies; nevertheless, it still has significant technical issues and limits that require to be exploring and solving before it can be considered a viable option. It is therefore, necessary to have a high level of reliability for payments and confidentiality, in addition to maintaining the anonymity of nodes, to stop assaults and efforts to disrupt transactions in the blockchain.

This study has several important theoretical and practical implications. First, it adds to the body of knowledge on blockchain and Fintech, focusing on the transaction side. While much blockchain research has focused on how the technology may affect strategic choices, this study has shed light on its potential from the perspective of financial reporting. Second, by highlighting the importance of the demand for the prompt identification of losses, this work adds to the body of knowledge on the factors that influence transaction frauds involving paper money. Additionally, by establishing the link between transparency and virtual transactions, the author backs up the asymmetric responses of investors to different investment possibilities. It looks at the evolution of financial technology (Fintech) and shows how it can be used to take the advantage of unique opportunities.

The study is different and novel from the previously published literature on this topic mainly because of its comprehensiveness, as it revolves around all industrial and commercial areas. The three main lines of research have been outlined, namely, classifying the many blockchain-based innovations that will alter the financial landscape in many industries; identifying whether these industries are a good fit for blockchain’s wealth creation potential; and directing researchers by outlining prospective study pathways.

The study aims to add to the body of knowledge of open source tangible product management (also called open design). The objective is also to develop a guideline for efficient open source tangible product development and adoption.

The exploratory research design using secondary data (like newspapers, magazines, research articles, bogs, papers, etc.) is used to analyze open source tangible product design challenges and enablers. The success stories of Open Source Software projects (OSS) were studied for identification of critical success factors and further their relevancy was tested in the two popular cases of open source drug discovery (malaria and tuberculosis)

Open innovation has become a part of competitive strategy of current businesses. It requires an efficient intellectual property protection regime for its implementation. However, in a market dominated by proprietary benefits, the open source technology development can serve as remedy for innovation needs of neglected sectors. The OSS literature revealed managing two classes of factors, namely technology sponsor level factors and environmental factors for efficiency and effectiveness. The case study analysis in the context of applicability of these OSS critical factors showed their limitations in open source tangible products, and highlighted understanding additional challenges and remedies.

Open source innovation is a collaborative effort involving inputs from various/diverse players, hence monitoring the effort and motivation level of the contributors is a cumbersome task. Only the information that is available online and in print media is taken as research inputs in this work. Also the data taken were from two case studies; a lot more case studies in the open design domain can progress the theory. The implications of this study are far-reaching in the areas where profit motivated proprietary efforts lack in addressing societal need. It provides guidelines for addressing those unmet needs by developing products in a collaborative way without intellectual property hurdles.

The essence of open design is becoming more vital, and there is a pressing need to build theory to support it, which still is elusive and dispersed. The study fills the gap using secondary data and case study approach.

This paper investigates school library services in the digital age for students with dyslexia and explores the impact of current library services on students’ learning.

A qualitative study with semi-structured interviews was designed according to the LAFE (Look and listen, Assistance and accessibility, Format and fit, and Environment) framework for learners with dyslexia and the 5E instructional model and conducted with 11 school librarians.

Results indicated that participants lacked knowledge of dyslexia for appropriate library services. Awareness, IT skills, school administration, funding and parental attitudes would influence the library’s tailored services to dyslexic children, despite the rich resources in these participants’ libraries, including paperbacks, digital resources and electronic devices. Adaptations are necessary to provide accessible services, especially by applying digital technologies, and school libraries can positively impact students’ reading interests, promote knowledge inquiry and strengthen information literacy skills.

While students with dyslexia spend significant time in schools, limited studies focus on school library services in the digital age, especially in Asia. This study fills the gap by systematically exploring the issue with the 5E instructional model.

In this study, the research question posed was: What are the defining characteristics, limitations, and potential opportunities in the research on heterogeneity within ASD?

This scoping review used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses methodology to address the research question: “What are the defining characteristics, limitations, and potential opportunities in the research on heterogeneity within ASD?” A comprehensive literature search was conducted across databases including MEDLINE/PubMed, SciVerse Scopus and Springer Link, with keywords such as autism, autism spectrum disorder (ASD), heterogeneity and neurodevelopment. Inclusion criteria covered original research, reviews and protocols published since 1990, while irrelevant or out-of-date works were excluded. Thematic analysis was applied to collected data to identify common patterns, trends and key characteristics, leading to a narrative synthesis. Ethical review board approval was not required due to the nature of the review.

The scoping review underscored the multifaceted nature of ASD, emphasizing its clinical, methodological and investigational complexities. ASD’s diverse behavioral, social and biological characteristics challenged its classification as a uniform entity. To address this, the review examined strategies like stricter clinical criteria, categorization into functional subgroups, and larger, diverse sample sizes. Moreover, it highlighted the transformative role of Big Data and machine learning in advancing the comprehension of ASD’s manifold manifestations. This research contributed valuable insights and innovative approaches for addressing the intrinsic heterogeneity of ASD, reshaping the understanding of this complex condition.

One limitation of this scoping review is that it primarily relied on existing literature and did not involve primary data collection. While the review synthesized and analyzed a substantial body of research, the absence of original data collection may limit the depth of insights into specific aspects of ASD heterogeneity. Future research could benefit from incorporating primary data collection methods, such as surveys or interviews with individuals with ASD and their families, to gain more nuanced perspectives on the condition’s heterogeneity.

The reliance on existing literature in this scoping review highlights the need for further empirical studies exploring ASD’s heterogeneity. Researchers should consider conducting primary data collection to capture real-world experiences and variations within the ASD population. This approach could provide more comprehensive and context-specific insights, ultimately informing the development of tailored interventions and support strategies for individuals with ASD and their families.

This paper offers a fresh perspective on understanding ASD by examining its clinical, methodological and investigational implications in light of its inherent heterogeneity. Rather than viewing ASD as a uniform condition, this study explores strategies such as stricter clinical criteria, subcategorization based on functionality and diverse sample sizes to address its complexity. In addition, this study highlights the innovative use of Big Data and machine learning to gain deeper insights into ASD’s diverse manifestations. This approach contributes new insights and promising directions for future research, challenging the conventional understanding of ASD as a singular entity.

Additive manufacturing (AM), also known as three-dimensional (3D) printing technology, has been used in the health-care industry for over two decades. It is in high demand in the health-care industry due to its strength to manufacture custom-designed and personalized 3D constructs. Recently, AM technologies are being explored to develop personalized drug delivery systems, such as personalized oral dosages, implants and others due to their potential to design and develop systems with complex geometry and programmed controlled release profile. Furthermore, in 2015, the US Food and Drug Administration approved the first AM medication, Spritam® (Apprecia Pharmaceuticals) which has led to tremendous interest in exploring this technology as a bespoke solution for patient-specific drug delivery systems. The purpose of this study is to provide a comprehensive overview of AM technologies applied to the development of personalized drug delivery systems, including an analysis of the commercial status of AM based drugs and delivery devices.

This review paper provides a detailed understanding of how AM technologies are used to develop personalized drug delivery systems. Different AM technologies and how these technologies can be chosen for a specific drug delivery system are discussed. Different types of materials used to manufacture personalized drug delivery systems are also discussed here. Furthermore, recent preclinical and clinical trials are discussed. The challenges and future perceptions of personalized medicine and the clinical use of these systems are also discussed.

Substantial works are ongoing to develop personalized medicine using AM technologies. Understanding the regulatory requirements is needed to establish this area as a point-of-care solution for patients. Furthermore, scientists, engineers and regulatory agencies need to work closely to successfully translate the research efforts to clinics.

This review paper highlights the recent efforts of AM-based technologies in the field of personalized drug delivery systems with an insight into the possible future direction.

The purpose of this study focused on a global longitudinal bibliometric mapping of research in the field of health biotechnology between 1990 and 2023 to determine who is leading this field of knowledge and to estimate the sub-disciplines that are emerging and project those that will prevail in the future.

The study identified the most relevant countries, institutions and researchers, as well as the type of scientific collaborations. The applied steps applied in the study were the following: identification and selection of keyword terms by a panel of experts; design and application of an algorithm to identify these selected keywords in titles, abstracts and keywords using Web of Science terms to contrast them; performance of JCR data processing during 2023 using R, Python and VOSviewer.

Among the most relevant conclusions of the study are the following exponential growth has been observed in the study period; new branches of knowledge have emerged in which the subjects have been acquiring their own autonomous capabilities; and R&D in this field is still concentrated in a small group of core countries, and the trend is for it to remain so due to the capacity needs required.

This contribution seeks to systematize the existing scientific knowledge in the field of biotechnology, specifically in the area of health, using the technique of scientific mapping based on a logical model of indicators that aims to determine potential thematic ramifications.