Search Results (339)

Non-viral vectors have gained recognition for their ability to enhance the safety of gene delivery processes. Among these, polyethyleneimine (PEI) stands out as the most widely utilized cationic polymer due to its accessibility. Traditional methods of modifying PEI, such as ligand conjugation, chemical derivatization, and cross-linking, are associated with intricate preparation procedures, limited transfection efficiency, and suboptimal biocompatibility. In this investigation, enhanced transfection efficiency was achieved through the straightforward physical blending of PEI carriers with spermine. Transfection assays explored the maximal enhancement potential conferred by spermine, alongside further methodological refinements aimed at optimizing transfection efficacy, showcasing a potential increase of up to 40.7%. Moreover, the attributes of resultant carriers, encompassing particle size, proton-buffering capacity, intermolecular interactions, and in vitro cytotoxicity, underwent comprehensive evaluation. Mechanistic inquiries into spermine’s augmentation of PEI carrier efficiency involved detailed investigations into cellular uptake mechanisms, lysosomal escape dynamics, and molecular simulation. Spermine has the capacity to augment the interaction between PEI and DNA, thereby engendering a system with reduced and more stable energy. These studies also disclosed that spermine augments the endosomal escape capability of PEI carriers without altering pathways involved in the cellular uptake of gene nanoparticles, thereby facilitating heightened gene expression. PEI-Sper emerges as a promising non-viral vector for gene delivery, distinguished by its simplicity in preparation, cost-effectiveness, and superior transfection efficiency. Full article

The use of the metaverse in educational environments has grown significantly in recent years, particularly following the shift of major tech companies towards virtual worlds and immersive technologies. Virtual reality and augmented reality technologies are employed to construct immersive learning environments. The metaverse is generally understood as a vast digital ecosystem or virtual space, facilitating the transition of individuals from physical to virtual environments, and is applicable to educational domains where practical experiments are challenging or fraught with risks, such as space exploration, chemical experimentation, and flight simulation training. In addition, the integration of artificial intelligence with the metaverse within educational contexts has significantly enriched the learning environment, giving rise to AI-driven teaching systems tailored to each student’s individual pace and learning modalities. As a result, a number of research articles have been conducted to explore the applications of the metaverse and artificial intelligence in education. This paper provides a systematic literature review following the PRISMA methodology to analyze and investigate the significance and impact of the metaverse in education, with a specific focus on the integration of AI with the metaverse. We address inquiries regarding the applications, challenges, academic disciplines, and effects of integrating AI and the metaverse in education that have not yet been explored in most research articles. Additionally, we study the AI techniques used in the metaverse in education and their roles. The review affirms that the integration of the metaverse in education, with the utilization of AI applications, will enrich education by improving students’ understanding and comprehension across diverse academic disciplines. Full article

Background/Objectives: The dual forces of structured inquiry and serendipitous discovery have long shaped neuropsychiatric research, with groundbreaking treatments such as lithium and ketamine resulting from unexpected discoveries. However, relying on chance is becoming increasingly insufficient to address the rising prevalence of mental health disorders like depression and schizophrenia, which necessitate precise, innovative approaches. Emerging technologies like artificial intelligence, induced pluripotent stem cells, and multi-omics have the potential to transform this field by allowing for predictive, patient-specific interventions. Despite these advancements, traditional methodologies such as animal models and single-variable analyses continue to be used, frequently failing to capture the complexities of human neuropsychiatric conditions. Summary: This review critically evaluates the transition from serendipity to precision-based methodologies in neuropsychiatric research. It focuses on key innovations such as dynamic systems modeling and network-based approaches that use genetic, molecular, and environmental data to identify new therapeutic targets. Furthermore, it emphasizes the importance of interdisciplinary collaboration and human-specific models in overcoming the limitations of traditional approaches. Conclusions: We highlight precision psychiatry’s transformative potential for revolutionizing mental health care. This paradigm shift, which combines cutting-edge technologies with systematic frameworks, promises increased diagnostic accuracy, reproducibility, and efficiency, paving the way for tailored treatments and better patient outcomes in neuropsychiatric care. Full article

Artificial intelligence (AI) holds tremendous potential for promoting equity and access to science, technology, engineering, and mathematics (STEM) education, particularly for students with disabilities. This conceptual review explores how AI can address the barriers faced by this underrepresented group by enhancing accessibility and supporting STEM practices like critical thinking, inquiry, and problem solving, as evidenced by tools like adaptive learning platforms and intelligent tutors. Results show that AI can positively influence student engagement, achievement, and motivation in STEM subjects. By aligning AI tools with Universal Design for Learning (UDL) principles, this paper highlights how AI can personalize learning, improve accessibility, and close achievement gaps in STEM content areas. Furthermore, the natural intersection of STEM principles and standards with the AI4K12 guidelines justifies the logical need for AI–STEM integration. Ethical concerns, such as algorithmic bias (e.g., unequal representation in training datasets leading to unfair assessments) and data privacy risks (e.g., potential breaches of sensitive student data), require critical attention to ensure AI systems promote equity rather than exacerbate disparities. The findings suggest that while AI presents a promising avenue for creating inclusive STEM environments, further research conducted with intentionality is needed to refine AI tools and ensure they meet the diverse needs of students with disabilities to access STEM. Full article

Roadway mortality increased during COVID-19, reversing a multi-decade downward trend. The Fatality Analysis Reporting System (FARS) was used to examine contributing factors pre-COVID-19 and in the COVID-19 era using the five pillars of the Safe System framework: (1) road users; (2) vehicles; (3) roadways; (4) speed; and (5) post-crash care. Two study time periods were matched to control for seasonality differences pre-COVID-19 (n = 1725, 1 April 2018–31 December 2019) and in the COVID-19 era (n = 2010, 1 April 2020–31 December 2021) with a three-month buffer period between the two time frames excluded. Four of the five pillars of the safe system had road safety indicators that worsened during the pandemic. Mortality was 19.7% higher for motor vehicle occupants and 45.1% higher for riders of motorized two-wheeled vehicles. In adjusted analyses, failure to use safety equipment (safety belts/helmets) was associated with 44% higher mortality. Two road user groups, non-motorized bicyclists and pedestrians, did not contribute significantly to higher mortality. Urban roadway crashes were higher compared to rural crashes. Additional scientific inquiry into factors associated with COVID-19-era mortality using the Safe System framework yielded important scientific insights to inform prevention efforts. Motorized two-wheeled vehicles contribute disproportionately to pandemic-era higher mortality and constitute an emerging road safety issue that deserves further attention. Full article

Meteorites have intrigued humanity for centuries, representing our enduring pursuit of knowledge and exploration of the cosmos’ enigmas. These celestial objects have not only influenced artistic expression and the formation of myths but have also fostered scientific inquiry. In this regard, meteorites are crucial to space research, offering valuable information about the early solar system, the formation of planets, and the development of organic compounds. Their analysis aids in deciphering cosmic processes and identifying resources that may support future space missions, making them essential for advancing planetary sciences. Meteorites are also cultural heritage items, with most known samples preserved in natural history museums. This paper deals with the Martian meteorites collected to date, focusing on NWA 16788, the largest individual Martian meteorite recovered so far. Full article

Florida’s population is projected to grow by 8.8 million residents over the next 25 years. This increase places demands on the transportation system, particularly for mobility-vulnerable populations, potentially impacting equitable transportation options and access for all users. Developing transit solutions for mobility-vulnerable populations may enhance economic activity, health, and well-being. Inquiry is needed to explore transportation stakeholders’ strategies and perspectives on the challenges and opportunities of the existing transportation system. Therefore, this study examined stakeholders’ views on strategies to address user needs, related challenges, and opportunities while identifying gaps, strengths, weaknesses, and threats relevant to addressing transportation among mobility-vulnerable populations. The team conducted 13 semi-structured interviews with city planners, transportation employees, industry stakeholders, and state representatives. Findings indicate gaps in the transportation system, particularly available funding and limited common goals among stakeholders. Participants emphasized the need for enhanced educational resources and collaboration with community members. They identified strengths like a willingness to pilot innovative transit technologies, weaknesses such as unreliable options, opportunities for innovation, and threats, including COVID-19′s impact on transportation use. Understanding transportation stakeholders’ shared challenges and opportunities is crucial for identifying transit needs and developing strategies to reduce disparities for mobility-vulnerable populations. Full article

This research is motivated by the arbitrary nature of decision-making environments and the dynamic changes in decision patterns, particularly in international dispute resolution. These challenges introduce uncertainties that could be effectively managed by fuzzy logic, which provides a robust framework for evaluating alternatives under multiple criteria. In this study, an Interval-Valued Type-2 Fuzzy TOPSIS approach is proposed to assess various dispute resolution methods, including negotiation, good offices, mediation, international inquiry, conciliation, international organization, arbitration, and international jurisdiction. Common criteria are determined by examining academic literature and by interviewing relevant experts.—cost-efficiency, duration, impartiality, binding nature, and generalizability are considered essential in determining the best resolution method. The proposed method allows for a nuanced evaluation by incorporating both primary and secondary levels of uncertainty, enabling decision-makers to determine the best alternative solution more reliably. This method’s application extends not only to the international law field but also to industrial engineering, where complex, uncertain decision environments require similarly sophisticated multicriteria decision-making tools. By systematically analyzing these resolution methods, this study aims to provide a structured, quantifiable approach that enhances the decision-making process for both international legal practitioners and engineers working with uncertain and dynamic systems. The results of this study ultimately contribute to improved decision-making outcomes and greater efficiency in multidisciplinary problem solving. The assessments of experts in international law, international relations, and political science in their respective fields of expertise have been gathered to form a consensus. This study contributes to the literature as it is the pioneering application of fuzzy multicriteria decision-making techniques in the field of international law. The results of this study imply that the best option from the different decision-maker evaluations is international jurisdiction. Consequently, the utilization of multicriteria decision-making tools can result in more informed and effective decisions in complex and uncertain situations, which is advantageous to both legal practitioners and engineers. Additionally, incorporating different disciplines can help streamline the decision-making process and improve overall efficiency in solving multidisciplinary problems. Full article

Flipped classrooms are student-centered and encourage students to engage in self-directed learning actively. The WSQ (Watch–Summary–Question) is an effective learning model for guiding students’ self-directed learning. However, for students who do not know how to take notes or have low self-efficacy, the WSQ learning model may become a mere formality, leading to passive learning. The POE (Prediction–Observation–Explanation) is an inquiry-based learning model that inspires students to learn through active inquiry. By integrating the WSQ with the POE, this study proposes the POEWSQ learning model. Through POE activities, students make predictions about the content before learning, actively explore it, and then engage in WSQ activities to deepen their understanding. This study develops a multimedia learning system for the POEWSQ learning model to guide students in learning programming. Students predict the content, draw a flowchart (Prediction), then watch the instructional video (Watch/Observation), and complete guided notes (Summary). Next, students explain the differences between the flowcharts (Explanation), complete the unit test (Assessment), and, finally, ask a question (Question). The results showed that learners using the flipped classroom integrated with the POEWSQ learning model have significantly higher learning effectiveness, motivation, self-efficacy, reflective ability, and attitudes toward programmed learning than those with the WSQ learning model. Full article

Hymenoptera, which includes honeybees, wasps, bumblebees, and hornets, is an order of the class Insecta, whose venom can induce anaphylactic reactions in dogs. While several studies have investigated the natural histories and risk factors of Hymenoptera venom allergy (HVA) in humans, only limited information is available on canine patients. Therefore, the aim of this study was to identify risk factors leading to severe systemic reactions (SSRs) and to explore the natural history of these patients. This was achieved with an inquiry into the case histories of 178 dogs that were stung by Hymenoptera and presented to the Vetsuisse Faculty Animal Hospital of the University of Zurich between 2018 and 2022. Dogs under two years old, dogs that weighed under 10 kg, purebred dogs, and dogs that were stung in the oral cavity were at a greater risk of developing SSRs. Almost two thirds of patients with SSRs experienced the same or worse symptoms after subsequent stings and >40% of patients with local reactions developed SSRs when stung again. Next to providing valuable clinical information about HVA in dogs, these findings strongly support the recommendation of venom immunotherapy (VIT) for patients with HVA. Full article

Although interdisciplinary research has garnered extensive attention in academia, its core knowledge structure has yet to be systematically explored. To address this gap, this study aims to uncover the underlying core knowledge topics within interdisciplinary research, enabling researchers to gain a deeper understanding of the knowledge framework, improve research efficiency, and offer insights for future inquiries. Based on the Web of Science (WoS) database, this study collected 153 highly cited papers and employed the LDA topic model to identify latent topics and extract the knowledge structure within interdisciplinary research. The findings indicate that the core knowledge topics of interdisciplinary research can be categorized into four major areas: the knowledge framework and social impact of interdisciplinary research, multidisciplinary approaches in cancer treatment and patient care, Covid-19 multidisciplinary care and rehabilitation, and multidisciplinary AI and optimization in industrial applications. Moreover, the study reveals that AI-related interdisciplinary research topics are rapidly emerging. Through an in-depth analysis of these topics, the study discusses potential future directions for interdisciplinary research, including the cultivation and development of interdisciplinary talent, evaluation systems and policy support for interdisciplinary research, international cooperation and interdisciplinary globalization, and AI and interdisciplinary research optimization. This study not only uncovers the core knowledge structure of interdisciplinary research but also demonstrates the effectiveness of the LDA topic model as a data mining tool for revealing key topics and trends, providing practical tools for future research. However, this study has two main limitations: the time lag of highly cited papers and the dynamic evolution of interdisciplinary research. Future research should address these limitations to further enhance the understanding of interdisciplinary research. Full article

Background: Approximately half of all women develop palpitations during pregnancy, with a quarter experiencing arrhythmias. While most presentations are benign, some cases can result in sudden cardiac death or serious symptom development. Considering such clinical presentation, healthcare providers must acquire knowledge in this area to provide comprehensive prenatal, perinatal, and postnatal care. However, no study could be located that focused on women’s life experiences of such complications during or in the post-pregnancy period. Objectives: The study aims to share the results of a study that explored the life experience of one woman who developed non-sustained ventricular tachycardia during her third pregnancy that lasted into the postpartum period. Methods: Using narrative inquiry self-study methodology, a woman’s experiences were explored to uncover the challenges she faced in coping with such complications during a period of transition for herself and her family. This methodology allowed for an in-depth understanding of how these complications could affect all aspects of her life. Results: Four narrative threads were produced: (1) diagnostic challenges and delayed recognition; (2) impact on maternal identity and family dynamics; (3) navigating healthcare systems and treatment decisions; and (4) long-term adaptation and resilience. Conclusions: The intention was to add to this topic area to ensure future researchers, current and future healthcare providers, and patients have literature they can refer to when studying, providing care for, or experiencing similar health complications. Acquiring this knowledge can aid healthcare professionals to ensure appropriate care is provided, risks are minimized, and their recovery is well supported. Full article

Recent research indicates the significant potential of artificial intelligence (AI) in enhancing teachers’ instructional practices in areas such as lesson planning, personalized teacher intervention and feedback, and performance assessment. To fully realize the potential of AI in teaching, it is crucial to understand how teachers innovatively apply and critically evaluate AI applications in their teaching practices. However, there is a research gap in investigating how teachers use various features of an AI-enabled system and their perceptions of AI integration in teaching to promote teachers’ effective AI integration practices. Employing an exploratory case study design, we investigated how six science teachers utilized an AI-enabled inquiry intelligent tutoring system (Inq-ITS) within their teaching and examined their perceptions of AI integration. Classroom observations and teacher interview data were collected. When using Inq-ITS functionalities, two teachers with a pedagogical orientation of teacher-guided scientific inquiry mainly engaged with its virtual tutor and teacher report summary features. Conversely, four teachers, practicing the pedagogical orientation of AI-guided scientific inquiry, relied on the AI system to guide student learning, interacting intensively with its features, particularly real-time teacher alerts and teacher inquiry practice support. Regardless of the differences in using Inq-ITS features, all teachers recognized the potential benefits of pedagogical change and encountered various challenges. This analysis also revealed that teachers exhibited distinct perceptions regarding the role of Inq-ITS integration in their teaching. Teachers who adopted a teacher-guided pedagogical orientation perceived the Inq-ITS as a supporting tool that enhanced traditional teaching methods. In contrast, those with an AI-guided pedagogical orientation viewed the Inq-ITS as akin to a teaching assistant and a pedagogical collaborator. The findings underscored the importance of enhancing teachers’ realization of the pedagogical affordance of AI in teaching through their use of AI functionalities. It is essential to consider teachers’ diverse perceptions of AI integration when promoting their integration of AI into teaching practices. Full article

This review explores how intuitive processes drive innovation, which we define as novel ideas, inventions, or artistic creations that cannot be logically derived from existing knowledge or sensory data. Although intuitive processes are not yet fully recognized as a formal area of scientific research, this paper examines current approaches to their study and modeling. It highlights the necessity of integrating unconventional modeling methods with neuroscience to gain deeper insights into these processes. Key experimental studies investigating extrasensory abilities—such as remote viewing, precognition, and telepathy—are reviewed, emphasizing their potential relevance to innovation. We propose that combining these unconventional modeling approaches with insights from systems neurology can provide new perspectives on the neural mechanisms underpinning intuition and creativity. This review emphasizes the critical need for further research into intuitive processes to address complex global challenges. It calls for a more open, interdisciplinary approach to scientific inquiry, promoting the exploration of unconventional forms of knowledge generation and their neural correlates. Full article

The scourge of food waste (FW) is a significant global challenge, impacting climate change, food security, and the sustainability of agrifood systems. The objective of this paper is to identify, analyze, and understand the factors influencing household consumer behaviors in Romania regarding the reduction of FW. Three primary research objectives were established to assess food consumption behaviors within households, to explore attitudes toward FW, and to understand the motivations for reducing FW along with the measures implemented by households to address this issue. Methodology: Data were collected through an online self-administered questionnaire, designed to investigate consumer behaviors related to the avoidance of FW. A descriptive statistical analysis was performed, and a linear regression model was developed to evaluate a composite index measuring Romanian consumers’ behavior towards FW reduction. Results: The resulting model identifies key predictors that drive concrete actions to minimize FW, including the desire to mitigate the environmental impact, household conversations about FW and strategies to reduce it, established food routines, the influence of one’s social circle, individual ecological and social responsibility, and the effectiveness of awareness campaigns addressing the consequences of FW. Practical and social implications: The findings highlight the necessity of education and awareness initiatives to shift attitudes and behaviors concerning FW. Future research is warranted to deepen understanding and enhance interventions. Originality: This study represents a pioneering and innovative inquiry into FW behavior in Romania, filling a gap in the existing literature and contributing to the broader discourse on this pressing environmental issue. Full article