pH-induced structural switch of a parallel duplex to triplex-DNA at a BOLF1 gene segment of the human herpes virus 4 (HH4) genome.

ABSTRACT The 1990s was a decade where palaeontology was at the forefront of popular culture. The first two Jurassic Park films were massive summer blockbusters. At the same time, palaeontologists discovered important specimens and utilised new technology. All of this combined to make palaeontology an extremely newsworthy branch of science. This study is a content analysis of three major news organisations coverage of palaeontology. It documents how palaeontology was reported on in this decade by examining topic selection, commons tropes/metaphors and the visibility of certain palaeontologists. Furthermore, gendered depictions of palaeontologists and the presentation of scientists as rugged adventurers are also analysed. This study presents novel findings on print news media’s depiction of palaeontology and the agenda setting practices of the National Science Foundation.

The color of fruits is determined by the metabolic balance of chlorophyll, carotenoids and anthocyanins. This process is regulated in multiple ways and is closely related to human health, providing a theoretical basis for quality breeding and nutritional development. The external appearance of fruit serves as a direct visual manifestation of internally accumulated secondary metabolites, including anthocyanins, carotenoids, and chlorophylls, effectively acting as a "visual carrier" for these compounds. These pigments confer distinctive morphological characteristics to fruits, with their composition and concentration not only providing consumers with immediate cues regarding freshness and edibility but also closely correlating with fruit maturity and flavor quality. In recent years, the physiological activities associated with these pigments-such as antioxidant and anti-inflammatory effects-and their implications for human health have garnered significant attention within the fields of plant physiology, food science, and nutrition. This paper systematically elucidates the molecular mechanisms underlying fruit coloration, the regulatory networks involved, and the associated health benefits. Fruit color is primarily determined by the metabolic balance of pigments, including flavonoids (notably anthocyanins), carotenoids, and chlorophylls. Anthocyanin biosynthesis is precisely regulated by transcription factors such as the MYB-bHLH-WD40 (MBW) complex; carotenoid accumulation depends on the coordinated action of key enzymes like PSY and PDS alongside transcription factors including AP2/ERF and WRKY; meanwhile, chlorophyll degradation is modulated by factors such as ethylene and NAC proteins. Environmental stimuli and phytohormones influence pigment synthesis by modulating enzyme activities and gene expression, thereby participating in a complex network of genetic and environmental interactions that govern color regulation. The diversity of fruit coloration arises not only from variations in pigment types and concentrations-for example, red fruits are rich in anthocyanins, whereas orange-yellow fruits accumulate carotenoids-but also from the significant bioactive potential of these compounds in antioxidant, anti-inflammatory functions and in the prevention of metabolic diseases such as diabetes. This review seeks to identify molecular targets pertinent to the targeted breeding of fruit quality through an analysis of the genetic regulatory hierarchy governing pigment metabolism, environmental response mechanisms, and the correlation patterns between coloration and nutritional attributes. Furthermore, it aims to establish a theoretical framework to support the development and application of plant-derived bioactive compounds within the health industry.

The discovery of novel ferroelectric compounds and the modulation of polarization in established ferroelectric materials have persistently represented crucial and highly dynamic areas of research within the field of ferroelectric materials science. Here we demonstrate a structural templating strategy to reconfigure Aurivillius-phase oxides into metastable ferroelectric phases with tailored polarization. By stabilizing a metastable WO3 phase within a Bi2WO6 framework, we achieve robust out-of-plane polarization (10 µC/cm2) in textured WO3/Bi2WO6 films, contrasting the purely in-plane polarization of pristine Bi2WO6. First-principles calculations and atomic-resolution scanning transmission electron microscopy unveil a WO3 phase with oxygen displacement-driven ferroelectricity. Prototype ferroelectric field-effect transistors and memristors fabricated from these films exhibit robust switching ratios (>106) and thermal stability up to 350 °C. This work not only expands the family of binary ferroelectric oxides but also establishes a generalizable paradigm for overcoming polarization-directionality constraints in layered ferroelectrics.

ABSTRACT Objective To identify variables related to illicit drug use among graduate students. Participants 5,217 master’s and doctoral students completed an online survey in 2022. Method Logistic regression identified sociodemographic and academic predictors. Results 18.5% reported illicit drug use, mainly cannabinoids. Being aged 18–39, cisgender men, sexual and gender minorities, having no religion, having an income of up to 3 MW, no children, and living in Midwest, Southeast and South regions were associated with illicit drug use. Students in science and engineering fields, with scholarships, and who also work, were more likely to use illicit drugs. Conclusion Results indicate subgroups of graduate students more vulnerable to illicit drug use.

The integration of artificial intelligence (AI) into education quickly transforms education and training, especially in the fields of science and mathematics. This study investigated the impact of AI-based educational tools based on conceptual understanding of mathematics among first-year teachers at private education facilities in Rwanda. Using a quasi-experimental mixed-methods design, 14 participants were intentionally assigned to the experimental group (n = 7). This used AI-based tools and traditionally directed control groups (n = 7). The purpose of this study is to compare conceptual understandings between groups. Results show that the experimental group showed significantly higher learning results (mean amplification = 33.5%) compared to the control group (mean amplification = 18.5%), indicating that 71.4% of AI users reached excellence (post-test > 80%) compared to 28.6% of traditional group. Statistical analysis confirmed a significant difference in the index after testing (t = 3.24, p = 0.007). Furthermore, a strong positive correlation was found between the frequency of AI usage and conceptual increase (r = 0.85, p = 0.017), indicating the importance of sustainable interactions. The results of the research based on the technology adoption model showed that participants had a positive attitude towards AI tools and identified improvements in their usefulness, ease of use, and interaction. A significant correlation between perceived ease of use and utility (r = 0.78, p = 0.023) highlighted the important factors affecting adoption. This study concludes that AI-based tools significantly improve conceptual understanding of mathematics that is significantly integrated into educational education. These results provide valuable information to teachers who use AI to support future teacher skills and seek to support training in training.

The aim of this work is to provide an overview of the modern applications of artificial intelligence (AI) in professional sports, using football as an example. We will discuss modern approaches to injury prediction and the requirements for implementing these systems in a club setting. The methodology includes a scoping review of publications from 2015 to 2025 in the fields of sports medicine, sports science, and computer vision, as well as an analysis of industry standards for data quality. As a result, key classes of AI tasks have been systematized, including tracking, scouting, and decision support by headquarters. Typical data and model architectures have been identified, as well as critical sources of information bias and leakage. Requirements for validation and implementation have also been highlighted. It has been demonstrated that injury risk models in football show potential in prospective studies with high-quality «time-loss» labeling and strict time partitioning. However, their practical value depends not only on AUC, but also on calibration, resistance to data drift, and integration into the training process and recovery measures. The practical significance of the results is in the development of a practical framework for creating an «AI club system». This includes standardizing data, creating an ethical and legal framework, selecting metrics, establishing a monitoring protocol, and developing a set of preventive measures supported by models. The value of this work lies in its focus on sports scientists, analysts, and coaching staff, as well as its emphasis on the reproducibility and risk management of AI implementation.

At present, the evaluation of science, technology, engineering, arts, and mathematics (STEAM) education in college English teaching is still in the exploratory stage. Current research has focused solely on student learning and has addressed only that aspect of STEAM learning. To address this gap, this study integrates deep learning (DL) within the context of cognitive psychology to examine English teaching behavior at a private university. DL originates from the concept of “deep learning” in the fields of education and learning sciences. In this context, DL emphasizes learners' deep understanding, meaning construction, and transfer application of knowledge in the learning process, focusing on cognitive engagement, emotional experience, learning strategies, and the development of higher-order thinking. It is a learning orientation centered on learning quality and learning process. First, the concepts of cognitive psychology, DL, and STEAM education are introduced. Second, in line with cognitive psychology, DL is strategically designed and incorporated into the evaluation of STEAM education. Finally, based on STEAM education, the study explores the current state of English teaching at private universities and uses data from a questionnaire to analyze this situation.

As communication scholars become increasingly interested in studying virtual reality (VR) as a communication channel it will be important to establish useful measures related to perceptual variables in virtual environments. One such variable is physical fidelity: the degree to which virtual environments replicate or resemble places in the physical world. Often in computer science and other fields interested in VR, this variable is measured as reaction time within the system. However, for social scientific VR scholars, it can be important to understand how much the user perceives the environment to have physical fidelity. In the existing literature when physical fidelity is measured as a perceptual variable, it is often conflated with measures of immersion or spatial presence. This paper presents a confirmatory factor analysis approach to establishing a well-fitting scale of perceptual physical fidelity over three separate samples as well as delineating the conceptual and operational differences between physical fidelity, immersion, and spatial presence.

Contemporary economic growth relies on infrastructure. However, post-growth scholarship has only recently begun to grapple with infrastructure as a specific object of analysis and often reduces it to little more than a set of barriers to be overcome or a means to essential service provision. This article challenges such limited perspectives by developing a holistic framework through which to understand post-growth infrastructure, how it works and how it can change. Building on the insights of infrastructural analysis conducted in the fields of Science and Technology Studies (STS), geography and anthropology, we advance a relational understanding of post-growth infrastructure, which we define as those that foster social practices that satisfy situated needs, limit consumption and resist capitalist co-optation. Furthermore, we examine the logics that both explain the social dominance of infrastructure and represent pathways for its transformation; that is, as a phenomenon that simultaneously coerces and seduces individuals to adopt certain practices, yet remains suggestive of and open to other uses. We argue that, in order to explain post-growth transformations, post-growth studies must engage with these logics. Finally, we identify strategies for post-growth infrastructural transformation: appropriating growth infrastructure, reconstructing it in line with a post-growth agenda and ensuring its maintenance in the face of capitalist pressures. In this way, our framework represents an important step towards a larger body of research on post-growth infrastructure.

The field of developmental science is increasingly interested in conducting research that is more representative, equitable, inclusive and generalizable. One way to achieve these aims is to conduct research that positions communities as key collaborators and central contributors to our scientific inquiries. These principles are evident in community science approaches like community-based participatory research (CBPR) and participatory action research (PAR). We argue that CBPR and PAR can be implemented by developmental scientists. Here, we describe two initiatives that utilized CBPR and PAR. The first initiative is Playful Learning Landscapes (PLL). PLL embeds research from the learning sciences into public spaces to offer playful learning opportunities for children and families, and community science practices are leveraged throughout the process. The second initiative is the Galápagos Education and Research Alliance (GERA). GERA harnesses the tools of community science by working directly with communities in the fragile environment of Galápagos to gather data about ecosystem health and build community-based plans for climate change adaptation. Together, these two initiatives offer rich examples of how CBPR and PAR principles engender active participation from the community throughout the design and evaluation of a research project. We discuss the opportunities and challenges of using community-centred approaches.

Cuproptosis, a copper-dependent regulated cell death pathway formally characterized in 2022, has rapidly attracted scientific interest in cancer metabolism and mitochondrial biology. The accelerated growth of related publications warrants systematic bibliometric assessment to clarify research focus, thematic evolution, and early translational relevance within this emerging field. This study mapped the global landscape of cuproptosis research using bibliometric methods, with emphasis on publication trends, thematic structure, collaboration patterns, and citation networks. A total of 1469 Scopus-indexed original research articles published between 2022 and 2025 were analyzed using Bibliometrix for performance indicators, Bradford's and Lotka's laws, and thematic mapping; VOSviewer for keyword co-occurrence and collaboration networks; and CiteSpace for reference co-citation analysis. Results demonstrated rapid publication growth characteristic of an early-stage scientific field, with 33.4% of articles concentrated in 13 core journals. Research output was highly geographically concentrated, with Chinese institutions contributing 89.8% of publications, while international collaboration remained limited (14.7%). Keyword and co-citation analyses revealed a thematic shift from foundational mechanistic studies toward prognostic modeling, copper ionophore exploration (e.g., elesclomol and disulfiram), immune-related analyses, and bioinformatics-driven patient stratification. Ferredoxin 1 (FDX1) emerged as a central regulatory node in co-citation networks, reflecting its role in defining the molecular framework of cuproptosis rather than validated drug development. Overall, cuproptosis research remains largely mechanistic and preclinical, with only early indications of translational relevance. The strong geographic concentration of publications and limited international collaboration highlight structural imbalances in knowledge production and the need for broader global validation. This bibliometric mapping clarifies the field's early developmental stage and identifies priorities for future research, including cross-regional collaboration, experimental standardization, and cautious advancement toward clinical application.

The results of the 2022 PISA indicate that science skills and interest in Indonesia are still low. One way to increase interest in science is by introducing inventor figure of science and techonology. However, alternative learning media that are communicative and relevant to adolescents' media consumption habits are needed. Therefore, this study aims to design a character design for an inventor in the field of science and technology for a Webtoon comic as an educational tool for adolescents aged 15–18. This study used qualitative and quantitative methods. The qualitative method was used to understand the needs and interests of the target audience and to gather information from the literature for scientific sources in designing the inventor character. The quantitative method was used as one of the character design evaluation criteria, based on voting results by adolescents aged 15–18. The character design used Marika Nieminen's principles: demographics, silhouette and shape, color, and characteristics. Several alternatives were used to generate character designs, which were then evaluated to determine the final design. The character design evaluation will be assessed using several variables within an evaluation framework.

In recent years, numerous publications have emerged claiming that animals possess consciousness. Moreover, neurophysiological literature has discussed the possible existence of consciousness in artificial intelligence (AI). Both ideas stem from analyses of the behavior of animals and AI systems. Here, I argue that it is impossible to draw conclusions about animal consciousness based solely on their behavior. Addressing the question of animal consciousness requires an understanding of its neuronal mechanisms, and the challenge lies in whether these mechanisms can be understood. Views on this issue diverge widely, ranging from Cartesian dualism, which denies any neuronal mechanisms of consciousness, to the opposing position that consciousness is one of cognitive functions whose underlying mechanisms can be understood. Here, I support the latter view. In contrast, the problem of AI consciousness belongs to the field of computer science rather than neurophysiology. Even if artificial intelligence were to acquire consciousness in the future, it would be an AI-specific form of consciousness bearing little relation to human consciousness. Consequently, insights into the mechanisms underlying AI consciousness are unlikely to advance our understanding of human consciousness.

The study of neuroanatomy is fundamental in many scientific fields. Despite this, it is a challenging subject for students. As technology evolves, it is being increasingly incorporated into educational methods, including the teaching of neuroanatomy. Three-dimensional (3D) visualizations are well suited for displaying neuroanatomy. Tools enabling interaction with these visualizations allow students to engage and explore in a personalized way. While such tools are becoming more popular, there is uneven access to them, as well as limited evaluation of their educational impacts. In this work, a 3D neuroanatomy visualization was created through magnetic resonance imaging and appropriate post-processing. The visualization was integrated into two interactive platforms: a Spanish-language web-based tool (https://3dviewer.lavis.unam.mx/projects/neuroinmersa/) and an immersive virtual reality tool called a CAVE (Cave Automatic Virtual Environment) based in Latin America (Mexico). The tools were included in the study plan of a neuroanatomy-related undergraduate course, and their impact was analyzed through student grades and student or faculty questionnaire responses. The tools were well received by faculty and students alike, with high scores for enjoyment, usefulness, and potential for supporting self-study. Student grades showed improvement, which could be associated with the introduction of this resource (pre- vs. post-implementation: p = 0.05, Cohen's d = 0.44), although larger controlled studies are required. For the virtual environment, the importance of "simulator sickness" is highlighted, as it impacted user enjoyment. The creation of these tools enabled preliminary analysis of their impact in an educational setting, while beginning to fill the gap of interactive neuroanatomy education tools in Latin America.

Nanomaterials are gaining increasing importance in various scientific and technological fields, including ecological strategies for environmental remediation, such as the treatment of soils contaminated with petroleum hydrocarbons. This study aimed to evaluate the effectiveness of hydrocarbon-contaminated soil remediation using graphene oxide nanoparticles (GO-NPs) and zinc oxide nanoparticles (ZnO-NPs) in combination with bacterial consortium inoculation and phytoremediation with Lolium perenne. The study was conducted in two stages: laboratory-scale biodegradation experiments and semi-technical scale phytoremediation. The laboratory stage determined optimal nanomaterial doses based on respirometric and chromatographic analyses. During phytoremediation, the contents of total petroleum hydrocarbons (TPHs) and polycyclic aromatic hydrocarbons (PAHs) in soil, roots, and shoots were monitored. Biomass growth was recorded, and environmental toxicity was assessed using Phytotoxkit, Microtox, and Ostracodtoxkit tests. The addition of nanomaterials significantly enhanced soil remediation, with improvements in TPH and PAHs removal resulting from microbial biodegradation in both stages and, additionally, in the phytoremediation stage, from phytoextraction by plants. TPH biodegradation reached up to 81.85% in GO-NP variants and 80.9% in ZnO-NP treatments, while PAHs reached 73.19% and 70.66%, respectively. The biomass of Lolium perenne increased by 28.63% in GO-NP variants and by 22.21% in ZnO-NP treatments compared to the control. Total accumulation of TPH increased by 80.86% and 74.15%, and PAHs by 71.26% and 65.35%. Nanomaterial-amended variants also showed a reduction in toxicity units to 2.50-3.30. These results indicate that combining nanomaterials with bioaugmentation significantly enhances phytoremediation efficiency while reducing soil toxicity.

ABSTRACT The science, technology, engineering, and mathematics (STEM) fields are seen as driving economic expansion and innovation. Nevertheless, students of colour and students from low socio-economic status families remain underrepresented in both STEM education and careers. In the present study, we utilised the High School Longitudinal Study of 2008 to examine the relationship between Algebra I and students’ subsequent interest and likelihood of pursuing a STEM major in postsecondary years. Our findings indicate that students who had taken Algebra I by the eighth grade show a higher tendency to have an intention and to declare a STEM major in college. However, the advantageous relationships tend to weaken among Hispanic students. Additionally, such positive associations between early algebra taking and the STEM outcomes are greater among students with higher socio-economic backgrounds. These results underscore the significance of taking Algebra I in the early years in shaping students’ STEM pathways.

The development of flexible smart textiles urgently requires conductive fibers with high elasticity, wide strain response, and environmental stability. Conventional polyaniline (PANI)-based composite conductive fibers suffer from low production scalability, inconsistent nanostructure control, and compromised electromechanical properties, severely limiting their practical application in smart textiles. Herein, an innovative online in situ polymerization microfluidic spinning (OIPMS) strategy was proposed. This approach integrated solvent-exchange-induced phase separation for fiber solidification with in situ oxidative polymerization of aniline within a confined space. It enabled continuous growth of tunable PANI nanostructures on the surface of PANI/thermoplastic polyurethane (TPU) composite fibers in a single step, such as PANI nanoparticles, nanorods, nanowires, and nanosheets. Notably, PANI nanowires (PNWs) formed a densely entangled network on the fiber surface. The resulting PANI/TPU@PNW fibers exhibited optimized overall electrical, mechanical, and strain sensing properties: conductivity of 36.21 S/m, breaking elongation > 400%, breaking strength of 0.19 cN/dtex, coupled with a wide strain range (0-300%), high sensitivity (gauge factor = 24.2), excellent linearity (R2 = 0.984), and rapid response times (200 and 300 ms). The PANI/TPU@PNW fibers also demonstrated multimodal sensing capabilities for detecting bending and pressure, while maintaining stability after 5000 stretching cycles and 30 machine washes. The excellent sensing performance mechanism stemmed from the multidimensional synergistic conductive network of matrix enhancement, surface cracking, and outer layer bridging. These fibers could also be sewn into smart textiles and were further integrated into smart dancewear, smart camouflage sleeve, and smart varicose vein stocking, demonstrating significant application potential in the fields of sports science, military communication, and medical monitoring.

With the rapid advancement of the information age, electromagnetic waves have brought convenience to people while also posing numerous problems and challenges. Developing absorptive materials that combine strong absorption, wide bandwidth, low density, and high stability has become a core research direction in the field of materials science. Using the hydrothermal method, a flower-like zinc oxide/multi-walled carbon nanotube nanocomposite was synthesized with hydroxylated multi-walled carbon nanotubes as the carrier. This was achieved by selecting different solvents and varying concentrations of zinc precursor solutions. The composite was then blended with 50 wt% paraffin wax to investigate its electromagnetic parameters and absorptive properties. Results indicate optimal absorption performance occurs in a mixed solvent of deionized water: anhydrous ethanol = 1:1, with a zinc oxide precursor concentration of 0.2 mol/L. At a sample thickness of 2.5 mm, the minimum reflection loss reaches −40.15 dB, and the effective absorption bandwidth spans 2.88 GHz (8.00–10.88 GHz). The synergistic design strategy of “hydroxylated carrier-flower-like structure-mixed solvent” provides an innovative and practical new pathway for preparing high-performance zinc oxide/multi-walled carbon nanotube absorber materials.

The concept of chemical bonds and the detailed knowledge of how and where the breaking/formation processes occur are perhaps the central research fields in chemical sciences. However, the exact mechanisms underlying these processes still deserve an in-depth explanation. This perspective article systematically describes how the electronic distribution changes along the reaction pathway using Bonding Evolution Theory (BET) and Non-Covalent Interaction (NCI) analysis, highlighting their crucial role in the study of reaction mechanisms. Both methods enable on-the-fly topological classification for understanding how old bonds are broken and new bonds are formed. Specifically, the curly arrow representation is used to provide a detailed description of the molecular mechanism of chemical rearrangements based on the movements of electrons from the reactants to the products via the corresponding transition structures and possible intermediates. Furthermore, this review examines various illustrative studies that offer the classic examples of internal proton transfer reaction, decarbonylation of unsaturated cyclic ketones, Mannich-type reactions, and thio-Claisen rearrangement. The analysis of the actual mechanism of these chemical reactions highlights the power of the ELF and NCI analysis to provide a physical basis for electron rearrangements along the reaction pathway. Finally, we address the current challenges and present perspectives for advancing the theoretical understanding and practical applications in this rapidly developing field.