Search Results (4,391)

Background: Eating disorders (EDs) and self-harm (SH) are both associated with distress, poor psychosocial functioning, and increased risk of mortality. Much of the literature discusses the complex interplay between SH and ED behaviours where co-occurrence is common. The onset of both is typically seen during teenage years into early adulthood. A better understanding of the functions of these behaviours is needed to guide effective prevention and treatment, particularly during the crucial developmental years. An earlier review has explored the functions of self-harm, but an equivalent review for eating disorder behaviours does not appear to have been completed. Objectives: This evidence synthesis had two objectives. First, to identify and synthesise published first-hand accounts of the reasons why people engage in eating disorder behaviours with the view to develop a broad theoretical framework of functions. Second, to draw comparisons between the functions of eating disorder behaviours and self-harm. Methods: A qualitative evidence synthesis reporting first-hand accounts of the reasons for engaging in eating disorder behaviours. A ‘best fit’ framework synthesis, using the a priori framework from the review of self-harm functions, was undertaken with thematic analysis to categorise responses. Results: Following a systematic search and rigorous screening process, 144 studies were included in the final review. The most commonly reported functions of eating disorder behaviours were distress management (affect regulation) and interpersonal influence. This review identified significant overlap in functions between self-harm and eating disorder behaviours. Gender identity, responding to food insecurity, to delay growing up and responding to weight, shape, and body ideals were identified as functions more salient to eating disorder behaviours. Similarly, some self-harm functions were not identified in the eating disorder literature. These were experimenting, averting suicide, personal language, and exploring/maintaining boundaries. Conclusions: This evidence synthesis identified a prominent overlap between psychological functions of eating disorder behaviours and self-harm, specifically in relation to distress management (affect regulation). Despite clear overlap in certain areas, some functions were found to be distinct to each behaviour. The implications for delivering and adapting targeted interventions are discussed. Full article

To address the small-sample training bottleneck and inadequate convergence efficiency of Deep Reinforcement Learning (DRL)-based communication anti-jamming methods in complex electromagnetic environments, this paper proposes a Generative Adversarial Network-enhanced Deep Q-Network (GA-DQN) anti-jamming method. The method constructs a Generative Adversarial Network (GAN) to learn the time–frequency distribution characteristics of short-period jamming and to generate high-fidelity mixed samples. Furthermore, it screens qualified samples using the Pearson correlation coefficient to form a sample set, which is input into the DQN network model for pre-training to expand the experience replay buffer, effectively improving the convergence speed and decision accuracy of DQN. Our simulation results show that under periodic jamming, compared with the DQN algorithm, this algorithm significantly reduces the number of interference occurrences in the early communication stage and improves the convergence speed, to a certain extent. Under dynamic jamming and intelligent jamming, the algorithm significantly outperforms the DQN, Proximal Policy Optimization (PPO), and Q-learning (QL) algorithms. Full article

This paper introduces a novel system that utilizes OpenPose for skeleton estimation to enable a tabletop robot to interact with humans proactively. By accurately recognizing upper-body poses based on the skeleton information, the robot autonomously approaches individuals and initiates conversations. The contributions of this paper can be summarized into three main features. Firstly, we conducted a comprehensive data collection process, capturing five different table-front poses: looking down, looking at the screen, looking at the robot, resting the head on hands, and stretching both hands. These poses were selected to represent common interaction scenarios. Secondly, we designed the robot’s dialog content and movement patterns to correspond with the identified table-front poses. By aligning the robot’s responses with the specific pose, we aimed to create a more engaging and intuitive interaction experience for users. Finally, we performed an extensive evaluation by exploring the performance of three classification models—non-linear Support Vector Machine (SVM), Artificial Neural Network (ANN), and convolutional neural network (CNN)—for accurately recognizing table-front poses. We used an Asus Zenbo Junior robot to acquire images and leveraged OpenPose to extract 12 upper-body skeleton points as input for training the classification models. The experimental results indicate that the ANN model outperformed the other models, demonstrating its effectiveness in pose recognition. Overall, the proposed system not only showcases the potential of utilizing OpenPose for proactive human–robot interaction but also demonstrates its real-world applicability. By combining advanced pose recognition techniques with carefully designed dialog and movement patterns, the tabletop robot successfully engages with humans in a proactive manner. Full article

This study explores how aristolochic acid I (AAI) drives hepatocellular carcinoma (HCC). We first employ network toxicology and machine learning to map the key molecular target genes. Next, our research utilizes molecular docking to evaluate how AAI binds to these targets, and finally confirms the stability and dynamics of the resulting complexes through molecular dynamics simulations. We identified 193 overlapping target genes between AAI and HCC through databases such as PubChem, OMIM, and ChEMBL. Machine learning algorithms (SVM-RFE, random forest, and LASSO regression) were employed to screen 11 core genes. LASSO serves as a rapid dimension-reduction tool, SVM-RFE recursively eliminates the features with the smallest weights, and Random Forest achieves ensemble learning through decision trees. Protein–protein interaction networks were constructed using Cytoscape 3.9.1, and key genes were validated through GO and KEGG enrichment analyses, an immune infiltration analysis, a drug sensitivity analysis, and a survival analysis. Molecular-docking experiments showed that AAI binds to each of the core targets with a binding affinity stronger than −5 kcal mol⁻¹, and subsequent molecular dynamics simulations verified that these complexes remain stable over time. This study determined the potential molecular mechanisms underlying AAI-induced HCC and identified key genes (CYP1A2, ESR1, and AURKA) as potential therapeutic targets, providing valuable insights for developing targeted strategies to mitigate the health risks associated with AAI exposure. Full article

Late-spring frost events severely damage low-chill peach blossoms, causing significant yield losses. Although 5-aminolevulinic acid (ALA) enhances cold tolerance through the PpC3H37-PpWRKY18 module, the regulatory mechanism of ALA on PpC3H37 remains to be elucidated. Using yeast one-hybrid screening with the PpC3H37 promoter as bait, we identified PpDof9 as a key interacting transcription factor. A genome-wide analysis revealed 25 PpDof genes in peaches (Prunus persica). These genes exhibited variable physicochemical properties, with most proteins predicted as nuclear-localized. Subcellular localization experiments in tobacco revealed that PpDof9 was localized to the nucleus, consistent with predictions. A synteny analysis indicated nine segmental duplication pairs and tandem duplications on chromosomes 5 and 6, suggesting duplication events drove family expansion. A conserved motif analysis confirmed universal presence of the Dof domain (Motif 1). Promoter cis-element screening identified low-temperature responsive (LTR) elements in 12 PpDofs, including PpDof1, PpDof8, PpDof9, and PpDof25. The quantitative real-time PCR (qRT-PCR) results showed that PpDof1, PpDof8, PpDof9, PpDof15, PpDof16, and PpDof25 were significantly upregulated under low-temperature stress, and this upregulation was further enhanced by ALA pretreatment. Our findings demonstrate ALA-mediated modulation of specific PpDof TFs in cold response and provide candidates (PpDof1, PpDof9, PpDof8, PpDof25) for enhancing floral frost tolerance in peaches. Full article

Concern over the presence of pharmaceutical waste in the environment has prompted research into the management of emerging organic micropollutants (EOMs). In response, sustainable technologies have been applied as alternatives to reduce the effects of these contaminants. This study investigated the capacity of filamentous fungi isolated from iron mine soil in the Amazon region to biodegrade the drug chloroquine diphosphate. An initial screening assessed the growth of four fungal strains on solid media containing chloroquine diphosphate: Trichoderma pseudoasperelloides CBMAI 2752, Penicillium rolfsii CBMAI 2753, Talaromyces verruculosus CBMAI 2754, and Penicillium sp. cf. guaibinense CBMAI 2758. Among them, Penicillium sp. cf. guaibinense CBMAI 2758 was selected for further testing in liquid media. A Box–Behnken factorial design was applied with three variables, pH (5, 7, and 9), incubation time (5, 10, and 15 days), and chloroquine diphosphate concentration (50, 75, and 100 mg·L⁻¹), totaling 15 experiments. The samples were analyzed by gas chromatography–mass spectrometry (GC-MS). The most effective conditions for chloroquine biodegradation were pH 7, 100 mg·L⁻¹ concentration, and 10 days of incubation. Four metabolites were identified: one resulting from N-deethylation M1 (N4-(7-chloroquinolin-4-yl)-N1-ethylpentane-1,4-diamine), two from carbon–carbon bond cleavage M2 (7-chloro-N-ethylquinolin-4-amine) and M3 (N1,N1-diethylpentane-1,4-diamine), and one from aromatic deamination M4 (N1-ethylbutane-1,4-diamine) by enzymatic reactions. The toxicity analysis showed that the products obtained from the biodegradation of chloroquine were less toxic than the commercial formulation of this compound. These findings highlight the biotechnological potential of Amazonian fungi for drug biodegradation and decontamination. Full article

Prostate cancer is among the most prevalent malignancies in men worldwide, underscoring the need for early and accurate diagnostic tools. This study presents a proof-of-concept and pilot clinical validation of a novel bioelectric impedance-based biosensor for the detection of prostate-specific antigen (PSA) in human serum. The system integrates Molecular Identification through Membrane Engineering (MIME) with the xCELLigence real-time cell analysis platform, employing Vero cells electroinserted with anti-PSA antibodies. Optimization experiments identified 15,000 cells/well as the optimal configuration for impedance response. The biosensor exhibited specific, concentration-dependent changes in impedance upon exposure to PSA standard solutions and demonstrated significant differentiation between PSA-positive and PSA-negative human serum samples relative to the clinical threshold of 4 ng/mL. The biosensor offered rapid results within one minute, unlike standard immunoradiometric assay (IRMA), while showing strong diagnostic agreement. The system’s specificity, sensitivity, and reproducibility support its potential for integration into point-of-care screening workflows. This bioelectric assay represents one of the fastest PSA detection approaches reported to date and offers a promising solution for reducing overdiagnosis while improving clinical decision-making and patient outcomes. Full article

Developing ultra-high-temperature geothermal resources is challenging, as traditional drilling fluids, including foam systems, lack thermal stability above 160 °C. To address this key technical bottleneck, this study delves into the screening principles for high-temperature-resistant foaming agents and foam stabilizers. Through high-temperature aging experiments (foaming performance evaluated up to 240 °C and rheological/filtration properties evaluated after aging at 200 °C), specific additives were selected that still exhibit good foaming and foam-stabilizing performance under high-temperature and high-salinity conditions. Building on this, the foam drilling fluid system formulation was optimized using an orthogonal experimental design. The optimized formulations were systematically evaluated for their density, volume, rheological properties (apparent viscosity and plastic viscosity), and filtration properties (API fluid loss and HTHP fluid loss) before and after high-temperature aging (at 200 °C). The research results indicate that specific formulation systems exhibit excellent high-temperature stability and particularly outstanding performance in filtration control, with the selected foaming agent FP-1 maintaining good performance up to 240 °C and optimized formulations demonstrating excellent HTHP fluid loss control at 200 °C. This provides an important theoretical basis and technical support for further research and field application of foam drilling fluid systems for deep high-temperature geothermal energy development. Full article

Atmospheric and oceanic turbulence can severely degrade the orbital angular momentum (OAM) mode purity of vortex beams in cross-media optical links. Here, we propose a hybrid correction framework that fuses multiscale phase-screen modeling with a lightweight U-Net predictor for phase-distortion—driven solely by measured optical intensity—and augments it with a feed-forward, Gaussian-reference subtraction scheme for iterative compensation. In our experiments, this approach boosts the l = 3 mode purity from 38.4% to 98.1%. Compared to the Gerchberg–Saxton algorithm, the Gaussian-reference feed-forward method achieves far lower computational complexity and greater robustness, making real-time phase recovery feasible for OAM-based communications over heterogeneous channels. Full article

Background/Objectives: Cancer suffers from unresolved therapeutic challenges owing to the lack of targeted therapies and heightened recurrence risk. This study aimed to investigate the new series of hydroxamate by structurally modifying the pharmacophore of vorinostat. Methods: The present work involves the synthesis of 15 differently substituted 2H-1,2,3-triazole-based hydroxamide analogs by employing triazole ring as a cap with varied linker fragments. The compounds were evaluated for their anticancer effect, especially their anti-breast cancer response. Molecular docking and molecular dynamics simulations were conducted to examine binding interactions. Results: Results indicated that among all synthesized hybrids, the molecule VI(i) inhibits the growth of MCF-7 and A-549 cells (GI₅₀ < 10 μg/mL) in an antiproliferative assay. Compound VI(i) was also tested for cytotoxic activity by employing an MTT assay against A549, MCF-7, and MDA-MB-231 cell lines, and the findings indicate its potent anticancer response, especially against MCF-7 cells with IC₅₀ of 60 µg/mL. However, it experiences minimal toxicity towards the normal cell line (HEK-293). Mechanistic studies revealed a dual-pathway activation: first, apoptosis (17.18% of early and 10.22% of late apoptotic cells by annexin V/PI analysis); second, cell cycle arrest at the S and G2/M phases. It also promotes ROS generation in a concentration-dependent manner. The HDAC–inhibitory assay, extended in silico molecular docking, and MD simulation experiments further validated its significant binding affinity towards HDAC 1 and 6 isoforms. DFT and ADMET screening further support the biological proclivity of the title compounds. The notable biological contribution of VI(i) highlights it as a potential candidate, especially against breast cancer cells. Full article

Background: Exocrine pancreatic insufficiency (EPI or PEI) may be prevalent in as many as 3 of 10 people with diabetes due to exocrine pancreatic function being reduced as early as the time of diagnosis. EPI can be treated with pancreatic enzyme replacement therapy (PERT), but the symptom burden of EPI remains high and improved screening and diagnosis methods are needed. Methods: An online survey (n = 324) evaluated the gastrointestinal symptom experiences of people with (n = 155) and without (n = 169) EPI using a novel symptom tool, the Exocrine Pancreatic Insufficiency Symptom Score (EPI/PEI-SS). A large sub-group (n = 120) of people with diabetes with EPI (Type 1, n = 14, Type 2, n = 20) or without EPI (Type 1, n = 78; Type 2; n = 6) was characterized and compared to those without diabetes (n = 204) in a sub-analysis of the larger EPI/PEI-SS study. Results: The symptom burden of EPI is similar, irrespective of diabetes. Like those without diabetes, people with type 1 diabetes with EPI had a statistically significant (p < 0.001) higher mean score (range 0–225) on the EPI/PEI-SS (100.86, SD: 48.92) than people with T1D without EPI (31.59, SD: 28.25), distinct from other GI conditions (p < 0.001). Similar patterns occurred in those with T2D. Conclusions: High EPI/PEI-SS scores seem to distinguish between likely EPI and other GI conditions among people with diabetes, and the EPI/PEI-SS should be further studied as a possible screening method for EPI at a population level. It should also be evaluated as a tool to aid individuals with diabetes in tracking changes to EPI symptoms over time based on PERT titration. Full article

Background and Aim: Artificial intelligence (AI) is among the most promising innovations for transforming nursing education, making it more interactive, personalized, and competency-based. However, its integration also raises significant ethical and practical concerns. This scoping review aims to analyze and summarize key studies on the application of AI in university-level nursing education, focusing on its benefits, challenges, and future prospects. Methods: A scoping review was conducted using the Population, Concept, and Context (PCC) framework, targeting nursing students and educators in academic settings. A comprehensive search was carried out across the PubMed, Scopus, and Web of Science databases. Only peer-reviewed original studies published in English were included. Two researchers independently screened the studies, resolving any disagreements through team discussion. Data were synthesized narratively. Results: Of the 569 articles initially identified, 11 original studies met the inclusion criteria. The findings indicate that AI-based tools—such as virtual simulators and ChatGPT—can enhance students’ learning experiences, communication skills, and clinical preparedness. Nonetheless, several challenges were identified, including increased simulation-related anxiety, potential misuse, and ethical concerns related to data quality, privacy, and academic integrity. Conclusions: AI offers significant opportunities to enhance nursing education; however, its implementation must be approached with critical awareness and responsibility. It is essential that students develop both digital competencies and ethical sensitivity to fully leverage AI’s potential while ensuring high-quality education and responsible nursing practice. Full article

Background: Cardiac involvement is common in Fabry disease (FD) and typically manifests with left ventricular hypertrophy (LVH). Patients with FD are frequently misdiagnosed, and this is mainly related to the lack of disease awareness among clinicians. The aim of this study was to determine whether providing a targeted educational intervention on FD may enhance FD diagnosis. Methods. This research was designed as a single-arm before-and-after intervention study and evaluated the impact of providing a specific training on FD to cardiologists from different Italian centers, without experience in rare diseases. In the 12-month period after the educational intervention, the rate of FD screening and diagnosis was assessed and compared with those conducted in the two years preceding the study initiation. Results: Fifteen cardiologists participated to this study, receiving a theoretical and practical training on FD. In the two previous two years, they conducted 12 FD screening (6/year), and they did not detect any cases of FD. After the training, they performed 45 FD screenings, with an eight-fold rise in the annual screening rate. The screened population (age: 61 ± 11 years, men: 82%) was mainly composed of patients with unexplained LVH (n = 43). There were four new FD diagnoses and, among of them, three had a late-onset GLA variant. After the cascade genetic screening, 11 affected relatives and 8 heterozygous carriers were also detected. Conclusions: A targeted educational intervention for cardiologists allowed the identification of four new families with FD. Enhancing FD awareness is helpful to reduce the diagnostic and therapeutic delay. Full article

History tools facilitate iterative analysis data by allowing users to view, retrieve, and revisit visualization states. However, traditional history tools are constrained by screen space limitations, which restrict the user’s ability to fully understand historical states and make it challenging to provide an intuitive preview of these states. Most immersive history tools, in contrast, operate independently of screen space and fail to consider their integration. This paper proposes HybridFilm, an innovative mixed-reality history tool that seamlessly integrates screen space and immersive reality. First, it expands the user’s understanding of historical states through a multi-source spatial fusion approach. Second, it proposes a “focus + context”-based multi-source spatial historical data visualization and interaction scheme. Furthermore, we assessed the usability and utility of HybridFilm through experimental evaluation. In comparison to traditional history tools, HybridFilm offers a more intuitive and immersive experience while maintaining a comparable level of interaction comfort and fluency. Full article

Background and Objectives: Emerging evidence indicates that individuals exposed to adverse childhood experiences (ACEs) face elevated risks for various chronic illnesses. However, the association between ACEs and osteoporosis risk remains underexplored, particularly regarding potential modifications by genetic susceptibility. This prospective cohort study aims to examine the relationship of ACEs with incident osteoporosis and investigate interactions with polygenic risk score (PRS). Materials and Methods: This study analyzed 124,789 UK Biobank participants initially free of osteoporosis. Cumulative ACE burden (emotional neglect, emotional abuse, physical neglect, physical abuse, sexual abuse) was ascertained through validated questionnaires. Multivariable-adjusted Cox proportional hazards models assessed osteoporosis risk during a median follow-up of 12.8 years. Moderation analysis examined genetic susceptibility interactions using a standardized PRS incorporating osteoporosis-related SNPs. Results: Among 2474 incident osteoporosis cases, cumulative ACEs showed dose–response associations with osteoporosis risk (adjusted hazard ratio [HR]_{per one-unit increase} = 1.07, 95% confidence interval [CI] 1.04–1.11; high ACEs [≥3 types] vs. none: HR = 1.26, 1.10–1.43). Specifically, emotional neglect (HR = 1.14, 1.04–1.25), emotional abuse (HR = 1.14, 1.03–1.27), physical abuse (HR = 1.17, 1.05–1.30), and sexual abuse (HR = 1.15, 1.01–1.31) demonstrated comparable effect sizes. Sex-stratified analysis revealed stronger associations in women. Joint exposure to high ACEs/high PRS tripled osteoporosis risk (HR = 3.04, 2.46–3.76 vs. low ACEs/low PRS) although G × E interaction was nonsignificant (P-interaction = 0.10). Conclusions: These results suggest that ACEs conferred incremental osteoporosis risk independent of genetic predisposition. These findings support the inclusion of ACE screening in osteoporosis prevention strategies and highlight the need for targeted bone health interventions for youth exposed to ACEs. Full article