151398 research outputs found
Sort by
CAPA: continuous-aperture arrays for revolutionizing 6G wireless communications
No full textIn this article, a novel continuous-aperture array (CAPA)-based wireless communication architecture is proposed, which relies on an electrically large aperture with a continuous current distribution. First, an existing prototype of CAPA is reviewed, followed by the potential benefits and key motivations for employing CAPAs in wireless communications. Then, three practical hardware implementation approaches for CAPAs are introduced based on electronic, optical, and acoustic materials. Furthermore, several beamforming approaches are proposed to optimize the continuous current distributions of CAPAs, which are fundamentally different from those used for conventional spatially discrete arrays (SPDAs). Numerical results are provided to demonstrate their key features in low complexity and near-optimality. Based on these proposed approaches, the performance gains of CAPAs over SPDAs are revealed in terms of channel capacity as well as diversity-multiplexing gains. Finally, several open research problems in CAPA are highlighted.<br/
A generalised -Core concept for normal form games
No full textWe develop a generalisation of the -Core solution for non-cooperative games in normal form. We show that this generalised -Core is non-empty for the class of separable games that admit a socially optimal Nash equilibrium. Examples are provided that indicate that non-emptiness of the generalised -Core cannot be expected for large classes of normal form games
Enhancing patient rehabilitation predictions with a hybrid anomaly detection model: Density-based clustering and interquartile range methods
No full textIn recent years, there has been a concerted effort to improve anomaly detection techniques, particularly in the context of high-dimensional, distributed clinical data. Analysing patient data within clinical settings reveals a pronounced focus on refining diagnostic accuracy, personalising treatment plans, and optimising resource allocation to enhance clinical outcomes. Nonetheless, this domain faces unique challenges, such as irregular data collection, inconsistent data quality, and patient-specific structural variations. This paper proposed a novel hybrid approach that integrates heuristic and stochastic methods for anomaly detection in patient clinical data to address these challenges. The strategy combines HPO-based optimal Density-Based Spatial Clustering of Applications with Noise for clustering patient exercise data, facilitating efficient anomaly identification. Subsequently, a stochastic method based on the Interquartile Range filters unreliable data points, ensuring that medical tools and professionals receive only the most pertinent and accurate information. The primary objective of this study is to equip healthcare professionals and researchers with a robust tool for managing extensive, high-dimensional clinical datasets, enabling effective isolation and removal of aberrant data points. Furthermore, a sophisticated regression model has been developed using Automated Machine Learning (AutoML) to assess the impact of the ensemble abnormal pattern detection approach. Various statistical error estimation techniques validate the efficacy of the hybrid approach alongside AutoML. Experimental results show that implementing this innovative hybrid model on patient rehabilitation data leads to a notable enhancement in AutoML performance, with an average improvement of 0.041 in the (Formula presented.) score, surpassing the effectiveness of traditional regression models.</p
Barriers and facilitators in implementing clinical practice guidelines among nurses in emergency departments and critical care units: a systematic review
No full textAimThis systematic review explored the barriers and facilitators to the implementation of clinical practice guidelines (CPGs) among nurses in emergency departments (EDs) and critical care units (CCUs).DesignSystematic review.MethodA systematic review was performed using both qualitative and quantitative studies from five databases (CINAHL, Web of Science, Embase, Scopus and PubMed). The literature search was conducted in May 2024. The PRISMA framework was used to guide the review process. Findings were subject to a narrative, thematic analysis and critical appraisal.ResultsEighteen studies were identified that met the inclusion criteria, yielding three themes related to barriers and facilitators of guideline implementation: individual-level, guideline-level and organisational-level. Key barriers included lack of awareness of guidelines, lack of knowledge and skills, attitudes towards guidelines, resource limitations, lack of perceived support, complexity of guidelines and lack of training. Facilitators to guideline use included colleague support, adequate training, effective leadership and refinement of guidelines to ensure relevance, local adaptation and user-friendly content.DiscussionNumerous barriers to nurse implementation of CPGs exist in ED and CCU settings, reflecting a complex interplay of individual, CPG-related and organisational factors. To facilitate CPG implementation, it is important for staff to be educated and trained in their use, supported to implement (including resource allocation) and that CPGs are designed to be easily implemented in practice.ConclusionThis systematic review highlights risk factors for poor CPG implementation and highlights the importance of addressing awareness, knowledge, resources and support for CPG use through targeted training, leadership and CPG design.Relevance to Clinical PracticeAn analysis of barriers and facilitators to CPG implementation among nurses in ED and CCU settings provides an important opportunity to address a gap in the literature, facilitating the development of strategies to promote CPG use and enhance care quality among nurses in these specific contexts.<br/
Continuous processing strategies for amorphous solid dispersions of itraconazole: impact of polymer selection and manufacturing techniques
No full textBackground: The limited aqueous solubility of BCS Class II drugs, exemplified by itraconazole (ITR), continues to hinder their bioavailability and therapeutic performance following oral administration. The present study investigated the development of amorphous solid dispersions (ASDs) of ITR via continuous manufacturing technologies, such as hot melt extrusion (HME) and spray drying (SD), to improve drug release. Methods: Polymer selection was guided by Hansen solubility parameter (HSP) analysis, film casting, and molecular modeling, leading to the identification of aminoalkyl methacrylate copolymer type A (Eudragit® EPO), polyvinyl caprolactam–polyvinyl acetate–polyethylene glycol graft copolymer (Soluplus®), and hypromellose acetate succinate HG (AQOAT® AS-HG) as suitable carriers. ASDs were prepared at drug-to-polymer ratios of 1:1, 1:2, and 2:1. Comprehensive characterization was performed using ATR-FTIR, NMR, DSC, PXRD, SEM, PLM, and contact angle analysis. Results: HME demonstrated higher process efficiency, solvent-free operation, and superior dissolution enhancement compared to SD. Optimized HME-based ASDs were formulated into tablets. The ITR–Eudragit® EPO formulation achieved 95.88% drug release within 2 h (Weibull model, R2 > 0.99), while Soluplus® and AQOAT® AS-HG systems achieved complete release, best described by the Peppas–Sahlin model. Molecular modeling confirmed favorable drug–polymer interactions, correlating with the formation of stable complex and enhanced release performance. Conclusions: HME-based continuous manufacturing provides a scalable and robust strategy for improving the oral delivery of poorly water-soluble drugs. Integrating predictive modeling with experimental screening enables the rational design of ASD formulations with optimized dissolution behavior, offering potential for improved therapeutic outcomes in BCS Class II drug delivery.<br/
Healthcare costs and health outcomes analysis of Neoadjuvant Trastuzumab therapy for HER2 positive breast cancer
No full textBackgroundGlobally, the incidence of breast cancer continues to rise; however, mortality rates are declining due to the growing effectiveness of targeted therapies and treatments. Overexpression of human epidermal growth factor receptor 2 (HER2) is seen in ∼15% of breast cancers (termed HER2+). Trastuzumab is the standard HER2-targeted therapy for HER2+ breast cancers in the adjuvant setting, and is increasingly being used as a neoadjuvant chemotherapy treatment (NACT or NAC). However, as well as the clinical impact, using drugs in a different treatment setting (including neoadjuvant) has a financial impact. Economic evaluation of novel chemotherapeutic strategies can assess both clinical utility and cost-effectiveness, thereby informing and guiding healthcare resource allocation decisions. Currently, the cost, clinical outcomes, and cost-effectiveness of single-agent neoadjuvant Trastuzumab remain underexplored. In this study, we evaluated the cost-effectiveness of Trastuzumab administered as neoadjuvant therapy, adjuvant therapy, or a combination of both regimens (NACT/ACT).MethodsA 3-year retrospective observational comparative analysis was conducted to examine costs and health outcomes using clinicopathological data (treatment type, surgical procedure, breast cancer subtype) from a public hospital in Ireland. Overall, 192 non-metastatic, non-palliative HER2+ breast cancer patients (Luminal B HER2, and HER2+ [non-luminal]) were selected (151 adjuvant Trastuzumab treated, 28 neoadjuvant Trastuzumab treated, 13 NACT/ACT Trastuzumab treated). The analysis estimated the cost of treatment (chemotherapy regimen, surgery type) and health outcomes, which were evaluated by analysis of survival data, and by calculating quality-adjusted life years (QALYs) and average cost-effectiveness ratios (ACERs). Multivariate regression analysis, using survival regression model techniques, was performed to evaluate associations between treatment types and total costs- adjusted by age, stage, grade, and subtype. A Cox proportional hazard model estimated the effect of treatment alternatives for time to disease-free survival (DFS).ResultsMultivariate analysis demonstrated no significant difference in treatment cost (p=0.318), surgery cost (p=0.951), or DFS (p=0.236) between the adjuvant and neoadjuvant Trastuzumab treatment groups. A significantly increased cost of treatment was observed in older patients (p=0.011) and patients with Grade 3 tumours (p=0.037). No significant difference in cost was found between the HER2 subtype groups (p=0.129) or between disease stages (p=0.71). No significant difference in QALY was observed between adjuvant and neoadjuvant treatment groups (p=0.296).ConclusionOverall, while adjuvant Trastuzumab remains the most cost-effective strategy for patients with HER2+ breast cancer, adopting a neoadjuvant Trastuzumab approach does not appear to pose a significant economic disadvantage. Notably, higher treatment costs were observed among older patients, a finding with important financial implications for healthcare systems. These results highlight the need for careful evaluation to inform forthcoming age-related cancer policy updates
Single-shot reconstruction of electron beam longitudinal phase space in a laser wakefield accelerator
No full textWe report on a single-shot longitudinal phase-space reconstruction diagnostic for electron beams in a laser wakefield accelerator via the experimental observation of distinct periodic modulations in the angularly resolved spectra. Such modulated angular spectra arise as a result of the direct interaction between the ultrarelativistic electron beam and the laser driver in the presence of the wakefield. A constrained theoretical model for the coupled oscillator, assisted by a genetic algorithm, can recreate the experimental electron spectra and, thus, fully reconstructs the longitudinal phase-space distribution of the electron beam with a temporal resolution of approximately 1.3 fs. In particular, it reveals the slice energy spread of the electron beam, which is important to measure for applications such as x-ray free electron lasers. In our experiment, the root-mean-square slice energy spread retrieved is bounded at 9.9 MeV, corresponding to a 0.9%–3.0% relative spread, despite the overall GeV energy beam having approximately 100% relative energy spread
Polygenic risk scores for eGFR are associated with age at kidney failure
No full textBackgroundThe genetic architecture of chronic kidney disease (CKD) is complex, including monogenic and polygenic contributions. CKD progression to kidney failure is influenced by factors including male sex, baseline estimated glomerular filtration rate (eGFR), hypertension, diabetes, proteinuria, and the underlying kidney disease. These traits all have strong genetic components, which can be partially quantified using polygenic risk scores. This paper examines the association between polygenic risk scores for CKD-related traits and age at kidney failure development.MethodsGenome-wide genotype data from 10,586 patients with kidney failure were compiled from 12 cohorts. Polygenic risk scores for hypertension, albuminuria, rapid decline in eGFR, decreased total kidney volume, and decreased eGFR were calculated using weights from published independent population-scale genome-wide association studies. The association between each polygenic risk score and age at kidney failure was investigated using logistic regression models. The association between polygenic risk score and age at kidney failure was also investigated separately for each primary kidney disease.ResultsIndividuals in the highest 10% of polygenic risk score for decreased eGFR developed kidney failure 2 years earlier than those in the bottom 90% (49.9 years and 47.9 years, P = 5e-5). A standard deviation increase in decreased eGFR polygenic risk score was associated with increased odds of developing kidney failure before the age of 60 years (Odds ratio (OR) = 1.05; 95% CI 1.01–1.10; P = 0.01), as was high decreased eGFR polygenic risk score (OR = 1.26; 95% CI 1.08–1.46; P = 0.003).ConclusionsWe conclude that decreased eGFR polygenic risk score explains a portion of the variation in age at development of kidney failure
AI for tobacco control: identifying tobacco-promoting social media content using large language models
No full textIntroductionTobacco companies use social media to bypass marketing restrictions. Studies show that exposure to tobacco promotion on social media influences subsequent smoking behavior, yet it is challenging to monitor such content. We developed an artificial intelligence that can automatically identify tobacco-promoting content on social media.Aims and MethodsIn this mixed methods study, 177,684 tobacco-related tweets published on Twitter in Turkish were collected. Through inductive content analysis of a sample of 200 tweets, the main mechanisms by which tobacco is promoted on social media were identified. Then, a sample of 5000 tweets was deductively analyzed and labeled based on those mechanisms. A pre-trained transformer-based Large Language Model was fine-tuned using the labeled dataset. Then, tobacco promotion in all tweets was predicted using this model.ResultsThe main mechanisms of tobacco promotion on social media included modeling the behavior, expressing positive attitudes, recommending use, and marketing brands or vendors. The developed model identified tobacco-promoting social media content with 87.8% recall and 81.1% precision. The utility of the model was demonstrated in the analysis of tobacco promotion in tweets for a period of a month.ConclusionsThis tool makes it possible to monitor tobacco promotion in social media and creates new opportunities for tobacco control policy and practice, not only in surveillance and enforcement but also in health promotion.ImplicationsTobacco promotion in social media is a well-known yet hard-to-addressed problem due to the nature of social media. This study leverages a cutting-edge AI approach, Large Language Models, to identify tobacco promotion in social media content automatically and precisely. The developed model offers better prediction performance than previously proposed techniques. The study enables surveillance of tobacco-promoting content both for research purposes and enforcement of tobacco control measures. Furthermore, we suggest a range of health promotion opportunities this tool can help with from developing personal skills to creating supportive environments and strengthening community actions.<br/
3D-printing of dipyridamole/thermoplastic polyurethane materials for bone regeneration
No full textTissue engineering combines biology and engineering to develop constructs for repairing or replacing damaged tissues. Over the last few years, this field has seen significant advancements, particularly in bone tissue engineering. 3D printing has revolutionised this field, allowing the fabrication of patient- or defect-specific scaffolds to enhance bone regeneration, thus providing a personalised approach that offers unique control over the shape, size, and structure of 3D-printed constructs. Accordingly, thermoplastic polyurethane (TPU)-based 3D-printed scaffolds loaded with dipyridamole (DIP) were manufactured to evaluate their in vitro osteogenic capacity. The fabricated DIP-loaded TPU-based scaffolds were fully characterised, and their physical and mechanical properties analysed. Moreover, the DIP release profile, the biocompatibility of scaffolds with murine calvaria-derived pre-osteoblastic cells, and the intracellular alkaline phosphatase (ALP) assay to verify osteogenic ability were evaluated. The results suggested that these materials offered an attractive option for preparing bone scaffolds due to their mechanical properties. Indeed, the addition of DIP in concentrations up to 10% did not influence the compression modulus. Moreover, DIP-loaded scaffolds containing the highest DIP cargo (10% w/w) were able to provide sustained drug release for up to 30 days. Furthermore, cell viability, proliferation, and osteogenesis of MC3T3-E1 cells were significantly increased with the highest DIP cargo (10% w/w) compared to the control samples. These promising results suggest that DIP-loaded TPU-based scaffolds may enhance bone regeneration. Combined with the flexibility of 3D printing, this approach has the potential to enable the creation of customized scaffolds tailored to patients’ needs at the point of care in the future.<br/