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Developing programme theories to address unmet needs of people experiencing homelessness and severe mental illness: protocol for a realist review [version 1; peer review: 1 approved with reservations]
Get PDFMental Health Advice on TikTok
No full textIn this paper, we provide the first, large-scale corpus-pragmatic analysis of mental health advice by social media influencers on TikTok. We identify advice-giving in large datasets focusing on if-conditionals as a specific form that allows us to analyse how the audience is positioned relative to a need and the solution which is then proposed. To identify the different ways in which mental health issues are presented, we use an adapted version of the 'mental health quotient' (Newson and Thiagarajan, 2020), as a linguistically informed framework for differentiating between lay discussions of mental health and those that invoke specific disorders. We sample a corpus of over 27,000 TikTok videos from 85 mental health influencers, using corpus-scale identification to extract and analyse if-conditionals produced by mental health professionals and wellness influencers. Our analysis of the protasis shows how these two types of influencers use prompts that share some similarities but also rely on fundamentally different models of healthcare. The relationship between these prompts and the information and recommendations in the apodosis show how health professionals rely on diagnostic information and therapeutic advice, while wellness influencers recommend embodied practice and products to treat mental health issues. These findings set out the distinctive ecosystem of healthcare which is emerging within the algorithmically driven contexts of sites like TikTok
Design, Synthesis, and Characterization of Novel, Subtype-Selective Fluorescent Antagonists Targeting the Nociceptin/Orphanin FQ Opioid Peptide Receptor
Get PDFThe nociceptin/orphanin FQ opioid peptide receptor (NOPr) is a member of the opioid receptor family under investigation for the treatment of depression, Parkinson’s disease, addiction, and pain. Opioid analgesics such as morphine act through μ-opioid receptor (MOPr) activation but cause MOPr-driven side effects that include respiratory depression, tolerance, addiction, and constipation. Bivalent NOPr/MOPr agonists have been shown to confer effective analgesia with an improved side effect profile. However, the development of new NOPr-targeting drugs is challenged by a paucity of pharmacological tools to characterize NOPr-ligands and visualize receptor expression. We report the design, synthesis, and pharmacological evaluation of the first high affinity small molecule NOPr-targeting fluorescent ligands, based on the antagonist: (2R)-1-(phenylmethyl)-N-(3-spiro[1H-2-benzofuran-3,4′-piperidine]-1′-ylpropyl)pyrrolidine-2-carboxamide (C24). These ligands display excellent selectivity for the NOPr against MOPr, δ (DOPr), and κ (KOPr) opioid receptors and are effective tracers for competition binding assays to evaluate NOPr-ligand affinity and in live cell imaging to visualize NOPr expression
NLRP3 Inflammasome and Polycystic Ovary Syndrome (PCOS): A Novel Profile in Adipose Tissue
Get PDFPolycystic ovary syndrome (PCOS) is a common endocrine disorder characterized by chronic low-grade inflammation. The NLRP3 inflammasome has been implicated in various inflammatory conditions, but its role in PCOS remains unclear. This study aimed to investigate whether the NLRP3 inflammasome and its associated components, IL-1β, CASP-1, and PYCARD, are involved in the pathogenesis of PCOS. Gene and protein expression levels of NLRP3, IL-1β, CASP-1, and PYCARD were assessed in adipose tissue samples (visceral and subcutaneous) from women with and without PCOS using qPCR and Western blotting. Contrary to our initial hypothesis, CASP-1 gene expression was significantly higher in non-PCOS participants across all adipose depots examined. Similarly, NLRP3 protein levels were significantly upregulated in visceral adipose tissue (VAT) and in combined adipose samples from the non-PCOS group. No significant group differences were observed in the gene expression of NLRP3, IL-1β, or PYCARD. These findings suggest a more complex role for the NLRP3 inflammasome in PCOS than previously assumed. The elevated CASP-1 and NLRP3 levels in non-PCOS participants may reflect compensatory regulation, subclinical inflammation in controls, or technical variability. Further research is needed to explore alternative inflammasome pathways and the influence of metabolic factors, such as insulin, on inflammasome regulation in PCOS
AI Data-Driven Framework for Optimal Electrical Machine Design in Aerospace Application
Get PDFNowadays, a permanent magnet synchronous motor (PMSM) has emerged as a potential alternative for aerospace actuator applications. The PMSM is a high-power-to-weight-ratio electrical machine and can provide reliable operation within the required thermal limits. An electrical machine designer applies multiphysics optimization techniques to optimize the parameters of an electrical machine. The optimization process is combined with electromagnetic and thermal finite element analysis (FEA) to generate feasible machine designs. FEA is computationally expensive and time-consuming, which makes it difficult to analyze over varied geometrical parameters and increases the likelihood of selecting a suboptimal electrical machine design. This work introduces the application of AI in machine design & selection of optimal machine dimensions, which reduces the requirement of FEA for an increased number of variations in geometric parameters. Three AI models have been developed for this purpose. The first AI model has been developed to predict the output parameter based on nine types of geometric input parameters. The output parameters are treated as input for the second AI model to predict whether this configuration is feasible or non-feasible. The third AI data-driven model uses clustering of the output parameters of feasible machines to identify the most suitable machine according to user requirements. The application of AI achieved an improvement of 31% in the torque density of PMSM. The selected optimal electrical machine has been prototyped and validated through experimental tests. Multiple design is also possible to obtain using the same framework. To showcase additional design through the framework, two additional machine design having different geometries for increase in torque, & decrease in total weight and decrease in torque ripple, & magnet weight have been presented
Overview of DC Distribution System in Low-Carbon Building–Part I: Configuration, Architectures and Applications
Get PDFThe building sector consumes approximately 32% of global energy and generates 34% of carbon dioxide emissions. Consequently, advancing energy conservation and emission reduction within this sector plays a critical role in mitigating the global climate crisis. Integrating photovoltaic (PV) generation, combined electrical and thermal energy storage systems, direct current (DC) distribution, and flexible load management technologies within buildings, synergistically optimized across the power source, energy conversion, and demand sides, creates pathways for decarbonizing the building sector. This review begins by elucidating the system's key configuration: building PV, energy storage systems (ESS), DC distribution systems and flexible loads, elaborating on their specific configurations and applications within the building environment. Subsequently, the paper reviews and analyzes low-voltage direct current (LVDC) voltage levels from the perspectives of existing standards and DC load demands. Focusing on DC distribution network topologies, this paper introduces unipolar and bipolar DC systems along with relevant studies, and reviews typical network configurations applicable to single buildings and building clusters. Following this, twelve global application case studies are presented and discussed, along with their key operational parameters. Finally, this paper discusses directions for technical standardization and future development trends
Changing the Multiple Sclerosis Diagnostic Pathway: Insights From Stakeholders on Implementing Novel Radiological Biomarkers
Get PDFBackground: The multiple sclerosis (MS) diagnostic process can be lengthy and result in psychological distress and treatment delays. The 2024 revised McDonald diagnostic criteria incorporate the central vein sign (CVS) and paramagnetic rim lesions (PRL), radiological biomarkers that offer the potential to improve the diagnostic pathway.Methods: The study aims were to: (1) investigate the experiences of people with MS and health care professionals (HCPs) regarding the current diagnostic process, and (2) identify the barriers and facilitators to implementing the revised diagnostic criteria. Semistructured individual interviews and focus groups were conducted with 10 HCPs and 9 people with MS. Framework analysis, applying normalization process theory, was employed.Results: Interviews revealed 4 themes: current challenges for the diagnostic pathway, CVS/PRL implementation barriers, the benefits of CVS/PRL implementation, and suggestions for overcoming implementation barriers and improving the diagnostic pathway . Challenges to implementation include pathway inefficiencies, care delivery inequality, insufficient communication, financial constraints, capacity limitations, and clinician hesitancy with the revised criteria. Suggested strategies for implementation and improvement included HCP training, enhancing interdisciplinary collaboration, evaluating implemented changes, and delivering emotional and practical support during diagnosis. Benefits for CVS/PRL implementation included reduced reliance on lumbar punctures, improved patient experience, cost-effectiveness, and enhanced diagnostic accuracy.Conclusions: Despite patient enthusiasm, implementing the revised diagnostic criteria will be challenging and possibly delayed unless HCP concerns are appropriately addressed
Root segmentation beyond species boundaries: A generalizable framework for anatomical analysis
Get PDFRoot anatomical features are critical for plant performance characterization, yet phenotyping at the anatomical scale remains limited by the extreme annotation burden of cellular segmentation. We present a two-stage segmentation framework that greatly reduces annotation requirements while maintaining high accuracy across diverse plant species and imaging conditions. Our approach decomposes multi-class segmentation into species-agnostic tissue identification followed by tissue type classification. By designing robust input representations invariant to imaging artifacts and morphological variations, our framework enables rapid adaptation to new species with fewer than 40 labeled images. Additionally, the first stage automatically generates tissue boundaries, transforming tedious manual tracing into simple tissue labeling. We validate our method on pearl millet, and sorghum root cross-sections from different imaging protocols, achieving state-of-the-art performance while dramatically reducing deployment time. This efficiency breakthrough enables scalable root phenotyping across diverse crop species, accelerating the development of climate-resilient varieties for global food security
Interactive effects of multiple types of exogenous uncertainty and prior experience on strategic investment decisions: A real options perspective
Get PDFReal Options Theory (ROT) is recognized as a powerful framework to understand strategic investment decisions under exogenous uncertainty. While ROT has studied multiple types of exogenous uncertainty, whether those have interacting effects has not been systematically addressed. We propose that ROT should start incorporating interactions between multiple exogenous uncertainties in its explanations of strategic investment decisions. In addition, our proposal accounts for direct and indirect paths by which exogenous uncertainty may exert influence as well as for the role of prior experience of making similar strategic investments. We chose patenting to illustrate our proposal to extend ROT. We empirically test our predictions using a sample of Chinese listed firms. Our findings confirm our proposal that different types of exogenous uncertainty can affect a strategic investment decision in distinct ways. Thus, ROT research can be enhanced by considering interactions between distinct types of exogenous uncertainty
Exploring the Use of Hybrid Closed‐Loop Systems in People With Type 1 Diabetes and Their Partners: A Qualitative Evaluation From the NHS England Pilot
Get PDFAims: The NHS England hybrid closed-loop (HCL) insulin pump pilot offered people living with Type 1 diabetes (PWT1Ds) access to HCL therapy. Outcomes demonstrated the glycaemic benefits of HCL. Our study explored the views, experiences and impact of HCL on users and their partners′ daily life. Methods: A total of 14 PWT1Ds and 12 partners of PWT1Ds who participated in the NHS HCL pilot took part in semistructured interviews via telephone/video call. Topics explored included the effect of the HCL system on glucose levels, time spent managing diabetes, daily life and challenges with the systems. Interviews were audio-recorded and transcribed. Data was analysed using inductive thematic analysis and then mapped onto an adapted Optimal Health Wheel (OHW) framework encompassing four relevant domains: (i) emotional, (ii) intellectual, (iii) social and (iv) physical. Results: Ten subthemes relating to the impact or experience of using HCL emerged—knowledge and previous experience, time/trial and error, building trust, impact on mental wellbeing, impact on physical health, impact on diabetes management, impact on lifestyle, impact on work, impact on relationships and need for support. PWT1Ds and partners reported multifaceted physiological and psychosocial benefits of using HCL systems. While technical difficulties and initial learning hurdles were acknowledged as barriers to HCL use, facilitators such as previous experience and trial and error helped overcome these issues. Conclusions: PWT1Ds and their partners endorsed the use of HCL systems, despite challenges, due to the impactful benefits to their lives. To ensure future successful implementation of HCL, users should be offered appropriate training and access to support to help build trust. These findings underscore the potential of HCL systems in T1D treatment
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