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Contribution of an Online Intervention to Developing Communities of Practice: Mixed Methods Evaluation of an Online Safety Hub to Address Harmful Online Content in Relation to Self-Harm and Suicide.
No full textBACKGROUND: Online harm affects many people and has been associated with self-harm and suicidal ideation. Although there is an emerging body of evidence that addressing adverse online experiences should be part of the support offered to people who are at risk of self-harm and suicide, there has been little guidance to date on how this support might be provided and how safe conversations can be had on the subject. A UK charity dedicated to offering emotional support to anyone experiencing mental discomfort, having difficulty coping, or being at risk of suicide developed a digital intervention, the Online Safety Hub (the Hub), to address this shortfall. OBJECTIVE: The study aimed to evaluate the impact of the Hub on practitioners (people who provide support) and people with lived experiences of suicide and self-harm and to determine what learning environment is best suited to increase and maintain learning in the context of the Hub. METHODS: A sequential explanatory mixed methods evaluation comprised a rapid literature review, data collected from people with lived experience (n=6) and practitioners through an analysis of the Hub's activity data, 2 surveys (survey 1: n=45; survey 2: n=368), interviews (n=9), and focus groups (n=7). Surveys were analyzed for descriptive purposes only, and the interview and focus group analyses comprised coding of data and thematic analysis. The study design was informed by a panel of people with lived experience of online harm resulting in either self-harm and/or suicidal ideation. RESULTS: Initially, the evaluation found limited uptake of the Hub. Engagement with the Hub was impeded by a lack of clarity on the part of practitioners as to whether they were the intended audience. The evaluation process prompted the charity to design and deliver webinars to facilitate uptake of the Hub. Practitioners who engaged with the Hub via webinars found the content useful and were able to consider incorporating their learning into practice. The webinars offered a more social learning experience than individual engagement with the Hub, providing a community of practice for people with common interests across diverse organizational settings. Opportunities for shared learning and the supportive nature of the community of practice were valued when learning about the sensitive and difficult topic of online harm in relation to self-harm and suicide. The Hub contributed to awareness-raising and shared learning. CONCLUSIONS: Online resources alone may not be sufficient for an intervention to effectively raise awareness and change practice. Social learning facilitated through communities of practice can enhance engagement, uptake, and learning.</p
PRIMARY-AI: outcomes-based standards to safeguard primary care in the AI era.
No full textArtificial intelligence (AI) is being deployed at scale in primary care — from diagnostic support and risk stratification to triage and clinical documentation — without any agreed-upon outcomes-based framework for determining whether it strengthens or undermines continuity, coordination, comprehensiveness and people-centered care1. This is dangerous for the billions of people whose first contact with health systems is primary care.</p
DCFS: Continual Test-Time Adaptation via Dual Consistency of Feature and Sample
No full textContinual test-time adaptation aims to continuously adapt a pre-trained model to a stream of target domain data without accessing source data. Without access to source domain data, the model focuses solely on the feature characteristics of the target data. Relying exclusively on these features can lead to confusion and introduce learning biases. Currently, many existing methods generate pseudo-labels via model predictions. However, the quality of pseudo-labels cannot be guaranteed and the problem of error accumulation must be solved. To address these challenges, we propose DCFS, a novel CTTA framework that introduces dual-path feature consistency and confidence-aware sample learning. This framework disentangles the whole feature representation of the target data into semantic-related feature and domain-related feature using dual classifiers to learn distinct feature representations. By maintaining consistency between the sub-features and the whole feature, the model can comprehensively capture data features from multiple perspectives. Additionally, to ensure that the whole feature information of the target domain samples is not overlooked, we set a adaptive threshold and calculate a confidence score for each sample to carry out loss weighted self-supervised learning, effectively reducing the noise of pseudo-labels and alleviating the problem of error accumulation. The efficacy of our proposed method is validated through extensive experimentation across various datasets, including CIFAR10-C, CIFAR100-C, and ImageNet-C, demonstrating consistent performance in continual test-time adaptation scenarios.</p
Leadless Pacemakers: Clinical Advances, Outcomes, and Comparison With Conventional Systems
No full textLeadless cardiac pacemakers (L-PMs) represent a significant innovation in bradycardia management, offering an alternative to conventional transvenous pacemaker systems within a rapidly evolving, increasingly digital pacing landscape [1]. Unlike traditional pacemakers, which require a subcutaneous pulse generator and transvenous leads, L-PMs are self-contained, single-unit devices that are implanted entirely within the heart [2]. This editorial examines the clinical utility of L-PMs, recent advances in their design and delivery, their safety profile and complication rates, and their comparison with conventional pacemakers. A global perspective on their clinical adoption and regulatory approvals is also discussed.</p
Transcriptomic Suppression of Immune and ECM stability in Skeletal Muscle of Patients with Chronic Kidney Disease
No full textBackgroundChronic kidney disease (CKD) is a growing public health emergency with a global prevalence of approximately 14%. Sarcopenia is a common complication of CKD contributing to functional decline and poor outcomes. However, the molecular mechanisms driving muscle wasting in CKD remain incompletely understood. This study aimed to characterise the transcriptomic profile in individuals with CKD compared to healthy control counterparts, to identify key pathways implicated in muscle dysfunction.MethodsVastus lateralis muscle biopsy samples were obtained from n = 10 people with CKD and n = 9 healthy controls matched for age, sex, ethnicity and physical activity. Bulk RNA sequencing was performed on all samples. Differential gene expression was assessed using DESeq2 and pathway enrichments analyses were conducted using Gene Ontology (GO) and KEGG databases.ResultsSeventy-six genes were differentially expressed in CKD muscle (FDR < 0.05, |log₂FC| ≥ 1), with 62 downregulated and 14 upregulated. he most consistent signature was suppression of immune-related and extracellular matrix transcripts, including CD163, C1QC, MPEG1, CXCL14, ITIH5, PODN, and CCDC80, suggesting attenuated immune surveillance and reduced ECM stability. In contrast, haemoglobin subunit genes (HBB, HBA1) were upregulated, potentially reflecting compensatory adaptation in oxygen transport. Several genes linked to regenerative processes (e.g., MEGF10, SOX4) were differentially expressed, but canonical myogenic and catabolic regulators remained unchanged, indicating that CKD muscle exists in a transcriptionally blunted state rather than one of overt inflammation or proteolysis.ConclusionsCKD skeletal muscle is characterised by suppression of immune and ECM regulatory programmes, with limited evidence for activation of classical inflammatory or degradative pathways. This distinct transcriptional profile suggests an immunologically and structurally quiescent state that may impair repair capacity and contribute to progressive sarcopenia. These findings refine current understanding of CKD-associated muscle dysfunction and highlight potential targets for mechanistic and therapeutic exploration.</p
The Effect of an Oblique Flow Entry on the Pressure Losses in Square Channels
No full textFlows in square channels are common in applications, such as automotive after-treatment systems and heat exchangers. Flows with axial flow entry are well understood, but for oblique flow entry, there is no clarity on the additional pressure loss magnitude or the flow regime. Laminar flow is often assumed, even though flow separation at the channel entrance can cause a transition to turbulence. Here, the impact of oblique flow entry on the flow is investigated using LES (large eddy simulation) and RANS (Reynolds averaged Navier–Stokes) models, and their advantages and limitations are identified. The LES simulations show that the shear layer at the channel entrance produces continuous shedding of eddies that persist downstream even at moderate channel Reynolds numbers ( 2000). The LES predicted pressure losses mostly agree with experimental data, and the differences observed are attributed to the difficulty of accurately replicating the experimental geometry. It is shown that both LES and RANS results are sensitive to the rounding of the leading edge (present in experiments). Including edge rounding improves the pressure predictions. RANS simulations mostly agree with experimens, but unlike LES did not predict transitional flow phenomena for sharp leading edge. This study provides insight into the flow structure and sources of pressure losses in square channels, highlights the importance of understanding key flow and geometric features when using LES to predict complex flows involving flow separation and shear layers, and indicates the need to further investigate the complex instability arising from interactions between secondary flow and shear-layer roll-up.</p
ANN-Based Online Parameter Correction for PMSM Control Using Sphere Decoding Algorithm
No full textThis work addresses parameter mismatch in Permanent Magnet Synchronous Motor (PMSM) drives, focusing on performance degradation caused by variations in flux linkage and inductance arising under realistic operating uncertainties. An artificial neural network (ANN) is trained to estimate these parameter shifts and update the controller model online. The procedure comprises three steps: (i) data generation using Sphere Decoding Algorithm-based Model Predictive Control (SDA-MPC) across a mismatch range of ±50%; (ii) offline ANN training to map measured features to parameter estimates; and (iii) online ANN deployment to update model parameters within the SDA-MPC loop. MATLAB /Simulink simulations show that ANN-based compensation can improve current tracking and THD under many mismatch conditions, although in some cases—particularly when inductance is overestimated—THD may increase relative to nominal operation. When parameters return to nominal values the ANN adapts accordingly, steering the controller back toward baseline performance. The data-driven adaptation enhances robustness with modest computational overhead. Future work includes hardware-in-the-loop (HIL) testing and explicit experimental study of temperature-dependent effects.</p
Elucidating the role of 3-hydroxykynurenine on neuronal physiology
No full textThe kynurenine pathway (KP) is the primary route for dietary tryptophan catabolism and culminates in NAD production. Several KP metabolites have neuromodulator functions and dysregulation of the KP is observed in a range of neurological disorders. Previous studies have suggested that the KP metabolite 3-hydroxykynurenine (3-HK) is a neurotoxin at supraphysiological levels in vitro (>100 μM). However, physiological levels of this metabolite in humans are much lower than these neurotoxic levels (~ 0.1 μM in healthy individuals and ~ 1 μM in disease). The present study examines the effects of 3-HK treatment on neuronal cells to better understand its role in disease by examining a range of cellular outcomes including mRNA expression profiles, cell viability, mitochondrial function and the release of extracellular vesicles (EVs).The neuroblastoma cell line SH-SY5Y was treated with 3-HK (0.1 M, 1 μM and 10 M) for 24 hours. Transcriptomic analysis revealed altered gene expression which was associated with RNA stability and protein modifications. Cell viability assays revealed that neuronal death occurred at concentrations one hundred times higher than that required for significant caspase-3/7 activation (1 μM). Mitochondria were imaged in live cells using confocal imaging and mitochondrial networks were analysed in FIJI. Mitochondrial fragmentation was observed at 10 μM 3-HK, alongside a significant increase in mitochondria number relative to other physiological concentrations. Interestingly, mitochondrial morphology was significantly altered by 0.1 μM 3-HK compared with the drug-naïve control. This suggested a dual, concentration dependent role for 3-HK in mitochondrial dynamics. Finally, EVs were isolated from serum-free conditioned media and analysed by nanoparticle tracking analysis which found increased EV diameter in cells treated with 3-HK.This study highlights the multifaceted role of 3-HK in neuronal function as treatment with physiological levels of 3-HK induced a variety of cellular responses that may be relevant for disease.</p
Targeting cell-cell communication systems of Streptococcus pneumoniae by molecularly imprinted polymers
No full textStreptococcus pneumoniae communicates through quorum sensing systems (QSS), which coordinate bacterial behaviour via pheromone signalling. Among peptide-mediated QSS, the regulatory gene family glycosyltransferase (Rgg) plays a crucial role in biofilm formation, virulence, bacteriocin production, and oxidative stress resistance, though its role in virulence and the possibility of being a drug target remain underexplored. This study investigated Rgg144 and Rgg1518, examining their regulatory interactions using isogenic mutants in growth studies, biochemical assays, and reporter gene analyses. The findings indicate that both Rggs contribute to mannose and galactose metabolism, as mutants exhibit attenuated growth and both systems were specifically induced by these sugars. Furthermore, full induction of each pathway required the presence of the other, indicating the inter-regulatory interactions between the two systems. Additionally, both Rggs play a significant role in protection against oxidative stress as evidence by the reduced expression of genes coding for superoxide dismutase (sodA) and thiol peroxidase (tpxD) in mutant strains and increased sensitivity to hydrogen peroxide and paraquat. Rgg144 and Rgg1518 were also implicated in pneumococcal colonisation and virulence, as mutant strains showed attenuated phenotypes in vivo. To disrupt pneumococcal communication, peptide-specific nano-molecularly imprinted polymers (nano-MIPs), shp144MIP and shp1518MIP, were synthesised. These nano-MIPs exhibited no toxicity in vivo (Galleria mellonella) or in vitro (S. pneumoniae growth) and effectively reduced disease progression, nasopharyngeal colonisation in a murine model, gene expression in reporter strains, and galactose utilisation. This study highlights the critical roles of Rgg144 and Rgg1518 in pneumococcal metabolism, oxidative stress response and colonisation, and introduces nano-MIPs as a promising therapeutic strategy to interfere with quorum sensing in Gram-positive bacterial infections, particularly S. pneumoniae.</p
A brain-driven neural circuit contributes to tissue regeneration in joint cartilage
No full textOBJECTIVES: Most mammalian tissues have limited regenerative capacity. It has been speculated that the brain might regulate tissue regeneration, while this concept has yet to be experimentally addressed. Using cartilage, a tissue with limited regenerative capacity as an example, we investigated this hypothesis. METHODS: We employed magnetic resonance imaging, polysynaptic retrograde tracing, chemogenetic/optogenetic manipulations, and single-cell RNA sequencing to characterise a functional brain-cartilage neural circuit regulating cartilage regeneration in human and mouse models. RESULTS: We found that fractional anisotropy and amplitude of low-frequency fluctuations values of the paraventricular nucleus (PVN) are elevated, and correlate with Western Ontario and McMaster Universities Arthritis Index scores and synovial fluid norepinephrine (NE) concentrations in patients with osteoarthritis. We further demonstrate the existence of a functional trans-neuronal circuit to regulate cartilage regeneration, which originates from PVNCRH neurons to sympathetic nerves in the synovium of joint. Inhibition of the circuit is sufficient to strongly promote the production of stable mature articular cartilage instead of fibrocartilage. This process fosters the regeneration of articular cartilage by inhibiting the pathways mediated by NE/articular cartilage via the β2-adrenergic receptor (ADRB2) in Proteoglycan 4+ cells. Furthermore, treatment with an ADRB2 inverse agonist prevented cartilage degradation in human articular cartilage explants. CONCLUSIONS: Our findings unveil a brain-cartilage circuit that regulates cartilage regeneration, providing valuable insights into the inherent limitations of tissue regeneration and suggesting a promising treatment strategy for enhancing cartilage regeneration.</p