151398 research outputs found
Sort by
Agomelatine 3D-printed microneedles as a potential drug delivery system for the treatment of depression
No full textMicroneedles (MNs) are small devices that help to overcome the skin barrier and, thus, increase the effectiveness of transdermal drug delivery. This approach could be beneficial, especially for drugs characterised by low oral bioavailability, such as the antidepressant agomelatine (AGM), which is now only available on the market as an oral tablet. The aim of this study was to obtain agomelatine-loaded microneedle systems for potential use in the treatment of depression, using the 3D-printing methods. 3D-printing is an emerging technology enabling the manufacture of drug dosage forms or devices in a personalised, fast, and cost-efficient manner. Three 3D-printing techniques, different drug loading methods, and various shapes of microneedles were investigated along with the mechanical and physicochemical evaluation, release, stability, and toxicity studies of the obtained samples. Masked Stereolithography (MSLA) and PolyJet methods were successful in obtaining good-quality microneedle systems. Additionally, the MSLA method allowed for easy combining of the resin with the drug. The presence of the drug in the product was confirmed, and the drug release pattern depended on the loading method. Mechanical testing showed that Pyramid and Cone geometries were the most promising in puncture tests, and stability testing revealed the need for light- and moisture-resistant packaging. The formulations selected based on the obtained results will be further investigated on the way to create a transdermal alternative to agomelatine oral tablets and increase the effectiveness of depression treatment
Beyond the spotlight: unveiling self-presentation strategies of elite Turkish female athletes on Instagram
No full textThis study aims to reveal the self-presentation strategies of elite Turkish female athletes on Instagram. Drawing on Goffman’s self-presentation theory, the research also explores how gender typing across different sports may shape athletes’ self-presentation strategies. By examining the use of social media by 44 elite Turkish female athletes in 15 different sports, this study provides clear evidence that elite athletes utilise Instagram for both front-stage and back-stage presentations by employing six self-presentation strategies (information-sharing, match or competition-related information-sharing, behind-the-scenes, interaction, self-promotion, and opinion-sharing) when sharing content on the platform to convey these different aspects of their athletic lives. The research findings also reveal that, in ‘masculine’ sports, female athletes tend to share more back-stage performance footage, whereas within ‘feminine’ branches of athletics, there appears to be a notable inclination towards higher utilisation of the front-stage category.<br/
Error performance characterization of LoRa-based direct-to-satellite IoT
No full textRecently, Long-Range (LoRa)-based direct-to-satellite Internet-of-Things (DtS-IoT) has garnered widespread attention from both academia and industry due to its capability to provide pervasive connectivity in an energy-efficient and cost-effective manner. A rigorous error performance analysis of such a new paradigm is quite essential for future green IoT communications. In this paper, we provide a novel analytical framework to characterize the error performance of LoRa-based DtS-IoT systems by leveraging an empirically-verified satellite-to-ground channel model. To enable a practical performance analysis, non-coherent detection is considered in the presence of interference along with the relative time and frequency offsets, where the corresponding decision metrics are theoretically derived. Based on this, closed-form symbol and bit error rate expressions are obtained by approximating the impact of the overall interference distributed within the decision metrics by that of the peak interference. Moreover, the impact of some key system parameters, such as the spreading factor (SF), bandwidth, and the end-device’s (ED’s) location, on the error performance is thoroughly investigated. The validity of our theoretical analysis is substantiated by extensive numerical simulations, where further insights are obtained into the error performance improvements of LoRa-based DtS-IoT systems
Time of day of cardiac surgery and postoperative outcomes in the UK: a secondary analysis of linked national datasets
No full textIntroductionUncertainty remains regarding whether the time of day that cardiac surgery is performed affects postoperative outcomes or if the observed variation can be explained by patient or surgical factors.MethodsA secondary analysis of prospectively collected data was conducted to examine the association between time of cardiac surgery and clinical outcomes. Data were derived from four linked UK datasets: the National Adult Cardiac Surgery Audit; the Case Mix Programme; Hospital Episode Statistics; and Office for National Statistics mortality records. The primary outcomes were hazard of death due to cardiovascular disease and time to hospital readmission for myocardial infarction or acute heart failure. Secondary outcomes included duration of postoperative hospital stay; occurrence of major cardiovascular events; and all-cause mortality.ResultsLinked data for 24,068 patients were identified. Surgeries performed in late morning (10:00 to 11:59) had the highest mean (SD) predicted risk of death (3.7% (4.6)), compared with 3.2% (3.7) for early morning (07:00 to 09:59), 2.8% (3.4) for early afternoon (12:00 to 13:59) and 3.1% (3.6) for late afternoon (14:00 to 19:59) surgeries, respectively. The primary outcome measures showed an increased hazard of death from cardiovascular disease in the late morning (adjusted hazard ratio 1.18, 95%CI 1.00–1.39), with no difference in hazard of readmission for myocardial infarction or acute heart failure (adjusted hazard ratio 0.97, 95%CI 0.85–1.11). There were no differences in the secondary outcome measures.DiscussionTime-of-day variation in postoperative death due to cardiovascular disease following cardiac surgery was observed, with the highest risk seen in late morning procedures. These findings suggest that intra-operative or organisational factors specific to this period may influence outcomes. Future research should explore whether individual circadian phenotypes or chronotypes contribute to this variation, supporting a move towards precision and personalised scheduling of cardiac surgery to optimise patient outcomes
Critical review of recent advances in AI-enhanced SEM and EDS techniques for metallic microstructure characterization
No full textThis critical review explores the transformative impact of artificial intelligence (AI), particularly machine learning (ML) and computer vision (CV), on scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) for metallic microstructure analysis, spanning research from 2010 to 2025. It critically evaluates how AI techniques balance automation, accuracy, and scalability, analysing why certain methods (e.g., Vision Transformers for complex microstructures) excel in specific contexts and how trade-offs in data availability, computational resources, and interpretability shape their adoption. The review examines AI-driven techniques, including semantic segmentation, object detection, and instance segmentation, which automate the identification and characterisation of microstructural features, defects, and inclusions, achieving enhanced accuracy, efficiency, and reproducibility compared to traditional manual methods. It introduces the Microstructure Analysis Spectrum, a novel framework categorising techniques by task complexity and scalability, providing a new lens to understand AI’s role in materials science. The paper also evaluates AI’s role in chemical composition analysis and predictive modelling, facilitating rapid forecasts of mechanical properties such as hardness and fracture strain. Practical applications in steelmaking (e.g., automated inclusion characterisation) and case studies on high-entropy alloys and additively manufactured metals underscore AI’s benefits, including reduced analysis time and improved quality control. Extending prior reviews, this work incorporates recent advancements like Vision Transformers, 3D Convolutional Neural Networks (CNNs), and Generative Adversarial Networks (GANs). Key challenges—data scarcity, model interpretability, and computational demands—are critically analysed, with representative trade-offs from the literature highlighted (e.g., GANs can substantially augment effective dataset size through synthetic data generation, typically at the cost of significantly increased training time)
Exploring spirituality in palliative care services: an All-Ireland survey
No full textBackgroundSpirituality and spiritual care are recognised as integral components of palliative care practice. Because of the diverse nature of this unique part of humanity, it may be challenging to describe what spirituality is or to ensure that spiritual care is delivered consistently in palliative care settings. However, failure to address the spiritual needs of a person and those who are important to them, who are in receipt of palliative care, can contribute to unnecessary distress.MethodologyThis study employed a mixed-method design. Using a purposefully selected non-probability sampling method, an adapted survey was specifically developed and conducted across the island of Ireland among healthcare professionals working in palliative and end-of-life care services. Data analysis included the use of a computer software programme (IBM SPSS Statistics, Version 28), qualitative data was analysed using Braun and Clarke’s (2022) six step approach to thematic analysis.ResultsCompleted surveys were received from a wide range of health care professionals (152 responses). Results showed that 113 (74.8%) had been working in palliative care for at least 6 years, and 109 (72.1%) respondents reported frequent/very frequent engagement in this aspect of care. Four themes emerged from the qualitative data relating to the concept of spiritual care (1) linked to holistic care which was seen as fundamental to palliative care, (2) closely linked to supporting someone in their search for meaning, which was often associated with existential issues, (3) it required practitioners to recognise that people often expressed their spirituality and spiritual needs within the context of the individual’s values & beliefs, (4) a form of accompaniment, closely related to a journey that included supporting someone as they moved towards death.ConclusionThe findings from this study show that many members of the palliative care team are actively engaged in supporting people with life-limiting illness and their families with their spiritual needs and concerns. Respondents were able to offer a rich insight into what they believed spiritual care is and the important role it plays in delivering palliative care. There was a clear recognition of the need for further support and training. It is hoped that the findings from this study will contribute to further discussion, learning and research, and encourage more members of the palliative care team to engage in this component of person-centred care
Bronchial epithelial cell-derived extracellular vesicles drive inflammasome activation and NTHi infection in COPD
No full textExtracellular vesicles (EVs) are lipid-membrane bound vesicles that can be beneficial or detrimental depending on the content they carry. As epithelial cells are the first line of defense against harmful particles, this work explored the role of bronchial epithelial cell-derived EVs (CepEVs) in the pathogenesis and progression of chronic obstructive pulmonary disease (COPD). RNA sequencing of macrophages stimulated with CepEVs revealed the upregulation of various inflammasome-related genes, alongside significant IL-1b and IL-18 release, which could be attenuated with caspase-1 or NLRP3 inhibition. The proteome of CepEVs was also assessed, which highlighted a significant reduction in antibacterial proteins compared to healthy EVs (HepEVs). When functionally assessed in NTHi infection of THP-1 cells, pre-incubation with HepEVs stimulated NTHi clearance and reduced pro-inflammatory cytokine release by macrophages, which was reduced in CepEV-stimulated cells. This study shows for the first time that CepEVs are able to both prime and activate the inflammasome in healthy macrophages, and highlights EV-induced inflammasome inhibition as a potential therapeutic target for the dysregulated inflammation seen in COPD. Alongside the inflammasome, we were also able to show that CepEVs are deficient for multiple antibacterial proteins, and that one or more of these proteins are essential in mounting an immune response against NTHi in macrophages. This finding contributes to a potential therapeutic pipeline through the supplementation of the depleted antibacterial proteins in CepEVs, allowing for efficient bacterial clearance and reduced consequential inflammatory burden. CepEV co-incubation resulted in a persistent state of inflammation and infection. Both sets of findings contribute to the overall knowledge of COPD pathogenesis, and highlight epithelial EVs as key players in the propagation of inflammation and susceptibility to infection