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Train motion prognostics and classification from multi-source decentralised sensors using unsupervised data-driven technology
No full textThis study proposes a novel scenario to recognize railway train motions using K-means clustering and data collected by smartphone sensors. Traditional methods often depend on high-cost and maintenance intensive sensors. These methods face financial and logistical challenges which limit their widespread application. This study collects train acceleration using smartphones onboard and uses K-means to classify different train motions from the extracted features in both time- and frequency- domains. The result demonstrates that this approach not only addresses the latency with the traditional methods but also enhances the accuracy of train motion classification. This successful endeavor underscores the potential of integrating machine learning with smartphones to efficiently address railway motion classification challenges which enhances real-time monitoring and predictive maintenance
Leveraging Digital Advanced Manufacturing to Enable Polymer Electrolyte Fuel Cells With Ultrahigh Gravimetric Power Density
Full text linkThe integration of hydrogen fuel cells into aerospace and mobility applications is limited by the weight and volume of fuel cell system, where bipolar plates alone account for up to 80% of the fuel cell stack mass and 60% of its volume. This study addresses this challenge by developing a new class of lightweight and compact porous distributors engineered through computational modeling that enable ultrahigh power densities. The research begins with a graphene-coated nickel foam porous distributor, which enhances reactants transport and interfacial conductivity, achieving a peak power density of 1.52 W/cm², representing a ~50% improvement over conventional designs. To further boost gravimetric power density, titanium was adopted as a base material, and porous architectures were optimized using CFD-driven design and flow control. Two advanced manufacturing techniques - laser powder bed fusion (LPBF) and laser micromachining - were employed to fabricate titanium-based porous distributors with tailored geometry. While the optimised LPBF lattice structure reached 1.18 W/cm², the laser-patterned non-homogeneous titanium architecture demonstrated a breakthrough performance of 1.71 W/cm², translating to volumetric and gravimetric power densities of 12 kW/L and 9 kW/kg, respectively. These values surpass current commercial benchmarks and even exceed EU 2030 targets. This work demonstrates how integrating digital design, flow control, and advanced materials/manufacturing enables a transformative leap in fuel cell power density, with implications extending to electrolysers, heat exchangers, and batteries
Access and engagement with maternity, social care and mental health services for perinatal migrant women with no recourse to public funds and irregular status:A cross-sectional study using the eLIXIR born in South London, UK, maternity-child data linkage
Full text linkObjectivesIn the UK, an estimated two million migrants are irregular or subject to No Recourse to Public Funds (NRPF) visa conditions, restricting welfare access and often requiring payment for NHS maternity care. The impact on maternity and perinatal service use remains poorly quantified.Study designRetrospective cross-sectional study.MethodsWe used linked electronic health records from maternity, neonatal, and mental health services in South London (eLIXIR-BiSL cohort). The sample included 56,690 women with 67,308 pregnancies (Oct 2018–Oct 2023). Migration status was categorised as UK-born, migrants with recourse to public funds, NRPF, or unknown visa status. Adjusted risk ratios (aRRs) were estimated using generalised linear models, controlling for sociodemographic and clinical characteristics.ResultsCompared with UK-born women, migrants, particularly those with NRPF, had lower engagement with services. Women with NRPF were less likely to access early antenatal care (aRR 0.36 [0.33–0.38]), attend maternity triage (0.89 [0.82–0.96]), or birth in midwife-led settings (0.51 [0.36–0.71]). They were more likely to access care late (3.61 [3.33–3.92]), receive inadequate antenatal care (1.41 [1.30–1.53]), transfer providers (1.54 [1.36–1.74]), and experience prolonged postnatal stays (1.38 [1.21–1.57]). Women with NRPF had lower mental health care contact before (0.05 [0.03–0.08]) and during pregnancy (0.51 [0.37–0.69]), and reduced engagement with social care (0.36 [0.17–0.70]) and the criminal justice system (0.30 [0.19–0.44]).ConclusionsMigrants with NRPF or unknown visa status face persistent barriers to maternity and mental health care. Inclusive reforms are needed to address inequity
ChemGenXplore:an interactive tool for exploring and analysing chemical genomic data
Full text linkMotivation: Chemical genomics is a powerful high-throughput approach to systematically link phenotypes to genotypes. However, the vast datasets generated remain challenging to explore due to the lack of integrated, interactive tools for visualization and analysis. Existing workflows often require multiple independent software tools, limiting data accessibility and collaboration. Therefore, we created a user-friendly platform that enables efficient exploration and sharing of chemical genomics data. Results: We developed ChemGenXplore, a web-based Shiny application designed to streamline the visualization and analysis of chemical genomic screens. It offers two primary functionalities: one for exploring pre-implemented datasets and another for analysing user-uploaded datasets. ChemGenXplore enables users to visualize phenotypic profiles, assess gene–gene and condition–condition correlations, perform GO and KEGG enrichment analysis, and generate customizable, interactive heatmaps. To further support collaborative research, ChemGenXplore also facilitates the comparative analysis of chemical genomic and other omics datasets. By consolidating these features into a single interactive and accessible tool, ChemGenXplore facilitates data sharing, enhances reproducibility, and promotes collaboration within the research community. Availability and implementation: ChemGenXplore is freely accessible as a web application at https://chemgenxplore.kaust.edu.sa/. Source code and documentation, including instructions for local installation, are provided on GitHub (https://github.com/Hudaahmadd/ChemGenXplore). A Docker image is also available on DockerHub (https://hub.docker.com/r/hudaahmad/chemgenxplore) to ensure reproducibility and simplify installation
Pregnancy outcomes in women at high risk of preterm birth receiving a vaginal cervical cerclage with, or without, progesterone:A retrospective, secondary analysis of the C-STICH randomised controlled trial data
Full text linkBackground: Vaginal cervical cerclage and progesterone are established treatments for prevention of pregnancy loss and prematurity. There is limited data to assess the effect of these treatments in combination. The objective of this study was to investigate the association between progesterone and no progesterone treatment on pregnancy outcomes in women at high risk of preterm birth who had received a vaginal cervical cerclage. Methods and findings: This is a secondary post-hoc analysis of women recruited to the C-STICH randomised controlled trial, which recruited in 75 obstetric units in the UK between 2015 and 2021. In the C-STICH trial, women with a singleton pregnancy, receiving a vaginal cervical cerclage due to a history of pregnancy loss or premature birth, or if indicated by ultrasound, were randomised to cerclage with braided or monofilament suture, with a primary outcome of pregnancy loss, defined as miscarriage, stillbirth, or neonatal death in the first week of life. In this secondary analysis, the primary outcome was pregnancy loss, defined as miscarriage and perinatal mortality, including any stillbirth or neonatal death in the first week of life. Secondary maternal outcomes included miscarriage and previable neonatal death; stillbirth; gestational age at delivery; preterm pre labour rupture of membranes, and sepsis. Secondary neonatal outcomes included early/late neonatal death and sepsis. For each outcome, regression models were fitted adjusting for prespecified prognostic variables. From the 2,048 women recruited to C-STICH, 1943 (95%) women had a vaginal cerclage placed and available progesterone data. Of these, 834 (43%) women received progesterone and 1,109 (57%) did not receive progesterone. In women with primary outcome data available, in our predefined analysis pregnancy loss occurred in 49 (5.9%) of 832 women who received progesterone and 91 (8.3%) of 1,103 women who did not receive progesterone (adjusted* risk ratio 0.70 (95% confidence interval (CI) [0.50, 0.99]); adjusted risk difference −0.02 (95% CI [−0.04, −0.001], *adjusted for indication, obstetric history, surgical technique, and maternal age). Further exploratory analysis excluding women who had termination of pregnancy for foetal anomaly demonstrated a nonsignificant reduction in the risk of pregnancy loss. Key limitations of this study include a nonrandomised trial design and unknown confounding relating to variation in progesterone use. Conclusion: In women with a vaginal cervical cerclage and concomitant progesterone there appears to be an association with a reduced risk of pregnancy loss. This combination therapy may be an important opportunity to further reduce the risk of pregnancy loss in this high-risk cohort
Implementation outcomes of a symptom management intervention in ambulatory oncology practices evaluated using a cluster randomized stepped-wedge trial design
Full text linkObjective: To test a package of clinician- and system-level implementation strategies on the adoption and reach of an electronic health record (EHR)-integrated cancer symptom assessment and management program, called cPRO, within a large academic healthcare system. Methods: This hybrid type 2 effectiveness-implementation study used a cluster randomized stepped-wedge trial design to test a package of strategies targeting system operations, clinician practices, and patient experience to support implementation of cPRO. Six clusters, comprised by 26 oncology clinic sites, were randomly allocated to one of six sequences which dictated the time at which each cluster underwent a 6-month implementation preparation period followed by a transition to the post-implementation phase in which 46 discrete implementation strategies were deployed. The primary implementation outcome was patient adoption of cPRO, measured by the proportion of patients completing cPRO assessments. Secondary outcomes included the reach of patient enrollment in the cPRO system and clinician adoption of referrals using an EHR “dot phrase” (snippets of text that can be quickly inserted into patient charts for referrals, orders, etc.) triggered by elevated cPRO scores. Data were analyzed using a cluster-period level analysis (generalized least squares linear regression with fixed cluster effects and adjustment for calendar time). Results: The study included 34,643 unique outpatients receiving cancer treatment at 26 clinics between October 2020 and March 2024. The primary analysis showed no significant difference between the pre- and post-implementation periods on the mean difference in the proportion of patients who complete the assessments (25% vs. 40%). Secondary outcomes indicated that the implementation strategy package did not significantly improve the reach of cPRO enrollment among patients (RR = 1.00, CI: 0.78 to 1.27). Clinician adoption of referrals in response to elevated cPRO symptom scores showed a marginal positive, alebeit non-statistically significant association with the implementation strategy package (RR = 1.66, CI: 0.79 to 3.48), although this varied over time. Conclusions: The implementation strategies tested did not significantly alter patient adoption rates of cPRO when comparing pre- and post-implementation periods, but might improve clinician adoption of the EHR dot phrase function. Future studies should explore strategies to enhance the integration of digital symptom management systems into routine cancer care to improve patient outcomes. Trial registration: ClinicalTrials.gov NCT03988543; registered 8 May 2019 https://clinicaltrials.gov/study/NCT03988543?term=NCT03988543&rank=1
Participatory system dynamics modeling:advancing equity through contextualized implementation science in global health
Full text linkImplementation science is central to advancing health equity in low- and middle-income countries (LMICs), yet many interventions continue to fall short of sustained impact. These failures are not merely technical or logistical; rather, they stem from a deeper epistemic gap: the inability of dominant implementation approaches to account meaningfully for contextual complexity. By treating “context” as a static backdrop or checklist of barriers and facilitators, existing approaches overlook how dynamic interactions, institutional logics, and local power relations shape implementation outcomes over time. We argue that Participatory System Dynamics Modeling (PSD) offers a transformative shift. Unlike conventional methods, PSD integrates diverse sources of evidence, including administrative data, prior research, expert insight, and lived experiences, into a logically consistent, interactive simulation model. PSD invites stakeholders to co-create these models, surfacing feedback loops, time delays, trade-offs, and unintended consequences that traditional frameworks often miss. We outline how PSD enables researchers and practitioners to move beyond linear planning and surface-level stakeholder consultation by co-creating dynamic models that reflect local complexity, power dynamics, and feedback loops. Drawing from examples across LMICs, we illustrate how PSD strengthens implementation by aligning with local realities and enabling systemic reflection. We recommend embedding PSD into health planning, research, and training infrastructures as a capacity-building pathway to advance its methodological uptake in implementation science and strengthen the global capacity to deliver health interventions that are context-responsive, system-informed, and grounded in LMIC realities
Cytoplasmic NAD/H synthesis via NRK1 regulates inflammatory capacity and promotes survival of CD4<sup>+</sup> T cells.
Full text linkT cell metabolism increases upon activation, underpinning immune effector functions. Nicotinamide adenine dinucleotide (NAD/H) is an essential redox cofactor for glycolysis and mitochondrial substrate oxidation. It's phosphorylation to NADP/H regulates reactive oxygen species (ROS) abundance. NAD/H levels increase upon T cell activation, but synthesis pathways and implications are not fully characterised. Here, we interrogate the role of the NAD/H-synthesis enzyme nicotinamide riboside kinase 1 (NRK1), the expression of which increases upon stimulation of both human and murine CD4+ T cells. Functionally, NRK1 activity restrains activation and cytokine production of CD4+ T cells while promoting survival. These activities are linked to increased NRK1 expression in the cytoplasm, where it locally raises NAD/H levels. This supports glycolysis, but more profoundly impacts cytoplasmic NADP/H generation, thereby controlling ROS abundance and nuclear NFAT translocation. During fungal and viral infection, T-cell-intrinsic NRK1 maintains effector CD4+ T cell abundance within affected tissues and draining lymph nodes, supporting infection control. Taken together, these data confirm that subcellular regulation of immune cell metabolism determines immune responses at the level of whole organism. </p
Enhancing comparability in idiopathic intracranial hypertension research through standardised outcome measures:In reply to: Outcomes of venous sinus stenting versus ventriculoperitoneal shunting for fulminant idiopathic intracranial hypertension: a dual-center analysis
No full textMaking use of avacopan in clinical practice
Full text linkAnti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is a severe multisystem autoimmune disease in which renal involvement is common and often progresses, without timely intervention, to end-stage kidney disease. Standard remission induction therapy combines high-dose glucocorticoids (GCs) with cyclophosphamide or rituximab. While effective, cumulative GC exposure drives substantial treatment-related morbidity, including infection, diabetes, osteoporosis and cardiovascular complications, highlighting the urgent need for GC-sparing strategies. Avacopan, an oral selective C5a receptor antagonist, represents a novel therapeutic approach targeting the alternative complement pathway, a key mediator of neutrophil activation and vascular injury in AAV. The pivotal phase 3 ADVOCATE trial demonstrated that avacopan achieved non-inferior remission at 26 weeks and superior sustained remission at 52 weeks compared with a standard GC taper, while reducing GC-related toxicity and improving renal recovery, particularly in patients with advanced kidney impairment. Since approval in 2021, real-world studies and case series have given further confidence in avacopan’s efficacy across diverse patient subgroups, including those with severe renal disease, diffuse alveolar haemorrhage and refractory manifestations. However, real-world data also highlight variability in GC tapering practices and safety signals, particularly hepatotoxicity in Japanese cohorts. Several unanswered questions remain, including the long-term safety, clinical benefit of treatment beyond 1 year and optimal GC concomitant use or even the feasibility of complete GC avoidance. Ongoing large-scale studies and international real-world evidence will be essential to define avacopan’s optimal role in clinical practice, ensuring equitable access for patients with AAV
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