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Intermolecular Sp<sup>3</sup>C─H Metalation of Non-Nucleophilic Brønsted Bases Using Simple Lewis Acids
No full text2,6-Di-tert-butyl substituted pyridines (tBu2-py) are widely used non-nucleophilic Brønsted bases. Their ubiquity is due to their highly hindered basic site and chemically robust nature. Herein we report that simple M2X6 Lewis acids (M═Al or Ga, X═Cl, Br or I) effect intermolecular sp3C─H metalation of tBu2-py bases under mild conditions. The sp3C─H metalated products can be converted in situ into ─BPin, ─iodo, ─bromo and ─hydroxy derivatives for further elaboration. Mechanistic investigations indicate that: i) a frustrated Lewis pair effects sp3C─H heterolysis to form the C─M bond and a protonated pyridine; ii) C─H metalation requires singly halide-bridged super-electrophilic M2X6 dimers for sufficiently low barriers. Finally, sp3C─H metalation using M2X6 is not limited to tBu2-py bases. Thus, it is important to be aware of this facile sp3C─H functionalisation when using a range of non-nucleophilic Brønsted bases.</p
Multiregional blood-brain barrier phenotyping identifies the prefrontal cortex as the most vulnerable region to ageing in mice
No full textAge-associated vascular alterations make the brain more vulnerable to neuropathologies. Research in humans and rodents have demonstrated structural, molecular, and functional alterations of the aged brain vasculature that suggest blood-brain barrier (BBB) dysfunction. However, these studies focused on particular features of the BBB and specific brain regions. Thus, it remains unclear if and which BBB age-associated phenotypes are conserved across brain areas. Moreover, there is very limited information about how BBB dysfunction and cell-specific phenotypes relate to each other. In this manuscript, we use immunofluorescence, transmission electron microscopy (TEM), and permeability assays to assess how age-associated BBB molecular, structural, and functional phenotypes correlate between the BBB cell types at three brain regions (prefrontal cortex, hippocampus, and corpus callosum) during mouse early ageing. We discovered that at 18-20 months of age, changes to the mouse BBB are subtle. The prefrontal cortex BBB is the most affected by age, with alterations in brain endothelial cell protein expression, BBB permeability, basement membrane thickness, and astrocyte endfoot size when compared to young mice. Here, we deliver a detailed multicellular characterisation of region-dependent BBB changes at early stages of ageing. Our data paves the way for future studies to investigate how region-specific BBB dysfunction may contribute to disease-associated regional vulnerability
Integrated investment, retrofit and abandonment planning of energy systems with short-term and long-term uncertainty using enhanced Benders decomposition
Get PDFWe propose the REORIENT (REnewable resOuRce Investment for the ENergy Transition) model for energy systems planning with the following novelties: (1) integrating capacity expansion, retrofit and abandonment planning, and (2) using multi-horizon stochastic mixed-integer linear programming with multi-timescale uncertainty. We apply the model to the European energy system considering: (a) investment in new hydrogen infrastructures, (b) capacity expansion of the European power system, (c) retrofitting oil and gas infrastructures in the North Sea region for hydrogen production and distribution, and abandoning existing infrastructures, and (d) long-term uncertainty in oil and gas prices and short-term uncertainty in time series parameters. We utilise the structure of multi-horizon stochastic programming and propose a stabilised adaptive Benders decomposition to solve the model efficiently. We first conduct a sensitivity analysis on retrofitting costs of oil and gas infrastructures. We then compare the REORIENT model with a conventional investment planning model regarding costs and investment decisions. Finally, the computational performance of the algorithm is presented. The results show that: (1) when the retrofitting cost is below 20% of the cost of building new ones, retrofitting is economical for most of the existing pipelines, (2) platform clusters keep producing oil due to the massive profit, and the clusters are abandoned in the last investment stage, (3) compared with a traditional investment planning model, the REORIENT model yields 24% lower investment cost in the North Sea region, and (4) the enhanced Benders algorithm is up to 6.8 times faster than the level method stabilised adaptive Benders.</p
Obstructive Coronary Artery Disease Improved Prediction by the COME-CCT Pretest Probability Calculator With Cardiac CT
Get PDFBackground: Combining pretest probability (PTP) with computed tomography angiography (CTA) for diagnosing obstructive coronary artery disease (CAD) has not yet been determined. Objectives: The purpose of this study was to evaluate the accuracy of PTP calculation alone and with CTA for diagnosing CAD. Methods: A total of 65 prospective diagnostic accuracy studies of patients clinically referred to invasive coronary angiography with stable chest pain were included in this international collaborative individual patient data Collaborative Meta-Analysis of Cardiac CT (COME-CCT) meta-analysis. Mixed-effects logistic regression with a data set–specific random intercept for clustering was applied to 4 models: the traditional Diamond-Forrester models, a PTP model based on the COME-CCT data (termed COME-CCT-PTP calculator), a CTA alone model, and a combined COME-CCT-PTP with CTA model. Results: Individual patient data from 5,332 patients with clinically indicated invasive coronary angiography from 22 countries were included. The COME-CCT-PTP calculator was more accurate than the original Diamond-Forrester model (AUC: 0.68; 95% CI: 0.66-0.69 vs 0.63; 95% CI: 0.62-0.65). The COME-CCT-PTP with CTA model significantly improved accuracy compared with either model alone (AUC: 0.86; 95% CI: 0.85-0.87 vs 0.81; 95% CI: 0.80-0.82). The improved prediction was consistent in decision curve analysis with an increased net benefit for all chest pain subtypes and was almost equally seen in patients with typical or atypical angina (0.85; 95% CI: 0.84-0.86) and nonanginal or other chest discomfort (0.88; 95% CI: 0.86-0.89). Conclusions: Combining the COME-CCT-PTP calculator with CTA provides more accurate prediction than the PTP or CTA alone for the diagnosis of obstructive CAD, for all chest pain subtypes.</p
On the settling and clustering behaviour of polydisperse gas–solid flows
Get PDFSedimenting flows occur in a range of society-critical systems, such as circulating fluidised bed reactors and pyroclastic density currents (PDCs), the most hazardous volcanic process. In these systems, mass loading is sufficiently high ( ≫O(1) ) and momentum coupling between the phases gives rise to mesoscale behaviour, such as formation of coherent structures capable of generating and sustaining turbulence in the carrier phase and directly impacting large-scale quantities of interest, such as settling time. While contemporary work has explored the physical processes underpinning these multiphase phenomena for monodispersed particles, polydispersed behaviour has been largely understudied. Since all real-world flows are polydisperse, understanding the role of polydispersity in gas–solid systems is critical for informing closures that are accurate and robust. This work characterises the sedimentation behaviour of two polydispersed gas–solid flows, with properties of the particles sampled from historical PDC ejecta. Highly resolved data at two volume fractions (1 % and 10 %) are collected using an EulerLagrange framework and is compared with monodisperse configurations of particles with diameters equivalent to the arithmetic mean of the polydisperse configurations. From these data, we find that polydispersity has an important impact on cluster formation and structure and that this is most pronounced for dilute flows. At higher volume fraction, the effect of polydispersity is reduced. We also propose a new metric for predicting the degree of clustering, termed ‘surface loading’, and a model for the coefficient of drag that accurately captures the settling velocity observed in the high-fidelity data
A digital intervention to improve mental health and interpersonal resilience for young people who have experienced online sexual abuse:The i-Minds non-randomised feasibility clinical trial and nested qualitative study
Get PDFBackgroundNo evidence-based support for young people who have experienced technology-assisted sexual abuse exists. The project’s aims were to develop a digital intervention that improves mentalisation (the ability to understand the minds of oneself and others that underlies behaviour) to reduce the risk for revictimisation and future harm and improve young people’s resilience.ObjectivesTo co-design a mentalisation-based digital intervention; determine its feasibility, acceptability, safety and usability; and determine how to best integrate this into practice.MethodsA mixed-methods, non-randomised study in young people aged 12–18 years exposed to technology-assisted sexual abuse across two United Kingdom sites. We adapted an existing mentalisation-based therapy manual and co-designed a digital health intervention (app) using participatory methods. Recommendations from our pre-trial qualitative work with healthcare professionals supporting young people with technology-assisted sexual abuse and lived experience consultation informed app development and trial procedures. The primary outcome was the feasibility and acceptability of delivering the digital intervention measured against relevant fields of the Consolidated Standards of Reporting Trials statement for feasibility studies. Intervention safety was reported against an adverse events procedure. Usability was guided by the framework for analysing and measuring usage and engagement data in digital interventions. Acceptability was examined using qualitative methods. The planned sample size of the feasibility clinical trial was 60 young people.ResultsBetween May 2022 and March 2023, 147 young people were screened for eligibility for the feasibility clinical trial; 72 referrals were made and 43 young people were allocated to receive the intervention. We found that it was possible to recruit and retain participants to this trial. Quantitative and qualitative data showed that the i-Minds app was safe, acceptable and associated with promising signals of efficacy on valuable outcomes post treatment, including technology-assisted-sexual-abuse-related post-traumatic symptoms, resilience, internalising symptoms and reflective functioning. Most participants accessed or completed app modules. User feedback indicated that participants had a positive experience using the app, positively increasing their knowledge/understanding of their own mental health and their motivation to address their mental health difficulties. Practitioners identified the barriers to implementing i-Minds into routine practice as not being involved in its design at the outset, possible impact on workload and whether digital health interventions might replace routine care. Facilitators included the distinct nature and specificity of the i-Minds app for the target group and its ability to support young people on service waiting lists
Examining the cognitive underpinnings of functional decline in prodromal Alzheimer’s disease:Insights from the Details of Functions of Everyday Life (DoFEL) Scale
Get PDFAvailable assessments for early-stage Alzheimer's disease (AD) identify neuropsychological and functional impairments, which rarely correlate in the early disease stages. The ability to bind information in memory declines in preclinical AD stages. However, it is unclear whether such cognitive deficits underlie functional impairment in prodromal AD stages. This study investigates whether incorporating memory binding, a function that is a sensitive cognitive marker for early-stage AD, into a functional assessment tool can reveal the cognitive underpinnings of daily activities. The Details of Function of Everyday Life (DoFEL) scale was revised, and its latent structure was explored through principal axis factoring in a nonclinical sample ( n = 559). Dementia professionals subsequently reviewed the revised DoFEL for content validity, followed by confirmatory factor analysis in another nonclinical sample ( n = 135). Additionally, 49 participants with mild cognitive impairment (MCI) and 33 healthy controls completed the DoFEL, Addenbrooke's Cognitive Examination-Revised (ACE-R) and a Visual Short-Term Memory Binding Task (VSTMBT). Correlation analysis and binomial regression were used to examine the relationship between DoFEL scores and cognitive measures and to assess its ability to differentiate between healthy controls and MCI patients. The revised DoFEL showed satisfactory structural and construct validity, although some items lacked content validity. Significant negative associations were found between DoFEL scores and ACE-R ( r = -0.66, p < 0.001) as well as VSTMBT ( r = -0.52, p=0.003) performances. Binomial regression demonstrated the DoFEL's effectiveness in distinguishing healthy controls from MCI patients (AUC = 0.95). These findings suggest that linking memory binding with functional performance could enhance functional assessment in early-stage AD. </p
Decolonizing religion:Engaging indigenous knowledge and transformative theological Praxis amidst global instability
Get PDFThe perceived binary between "world religions" and indigenous traditions is a colonial construct. This editorial asserts that dismantling this oppositional framework is essential for decolonizing religion and enabling constructive conversations with local and indigenous epistemes and practices. The five articles in this issue demonstrate that engagement with local practices and indigenous knowledge creates space for resilience, relationality, and ecological stewardship. Such a decolonial approach offers a crucial framework for responding to contemporary global challenges, including the climate crisis, economic precarity, and systemic injustice. Ultimately, this editorial calls for a more holistic religious practice and alternative socio-ethical imaginations
Leveraging expert input for robust and explainable AI-assisted lung cancer detection in chest X-rays
Get PDFDeep learning models show significant potential for advancing AI-assisted medical diagnostics, particularly in detecting lung cancer through medical image modalities such as chest X-rays. However, the black-box nature of these models poses challenges to their interpretability and trustworthiness, limiting their adoption in clinical practice. This study examines both the interpretability and robustness of a high-performing lung cancer detection model based on InceptionV3, utilizing a public dataset of chest X-rays and radiological reports. We evaluate the clinical utility of multiple explainable AI (XAI) techniques, including both post-hoc and ante-hoc approaches, and find that existing methods often fail to provide clinically relevant explanations, displaying inconsistencies and divergence from expert radiologist assessments. To address these limitations, we collaborated with a radiologist to define diagnosis-specific clinical concepts and developed ClinicXAI, an expert-driven approach leveraging the concept bottleneck methodology. ClinicXAI generated clinically meaningful explanations which closely aligned with the practical requirements of clinicians while maintaining high diagnostic accuracy. We also assess the robustness of ClinicXAI in comparison to the original InceptionV3 model by subjecting both to a series of widely utilized adversarial attacks. Our analysis demonstrates that ClinicXAI exhibits significantly greater resilience to adversarial perturbations. These findings underscore the importance of incorporating domain expertise into the design of interpretable and robust AI systems for medical diagnostics, paving the way for more trustworthy and effective AI solutions in healthcare
Can we tackle the inverse care law in general practice?
Get PDFThe inverse care law (ICL), as described by Julian Tudor Hart in his seminal 1971 Lancet article, is the observation that ‘The availability of good medical care tends to vary inversely with the need for it in the population served.’ 1 Tudor Hart’s main target was the threat of marketisation in health care, made clear in the second (less quoted) part of the ICL: ‘This inverse care law operates more completely where medical care is most exposed to market forces, and less so where such exposure is reduced.’Whether or not you agree with Tudor Hart’s thesis on market forces, it is clear that the distribution of general practice resources is not targeted to areas of greatest need. A 2022 report from The Health Foundation found that there were fewer GPs, despite higher health needs, in the most socioeconomically disadvantaged areas of England.2 We conducted a similar analysis of the general practice workforce in Scotland and found that, not only were there fewer GPs in the most deprived areas, but there were also fewer non-GP clinical staff (for example, practice nurses) and fewer non-clinical staff.3In our systematic scoping review, we found that, since Scottish devolution in 1999, a range of policies and interventions have sought to address health inequalities in general practice, with varying success and sustainability;4 only 2 of the 20 interventions — community links workers and financial advisers — have been rolled out nationally, though sustainability is uncertain. In this editorial, we discuss a range of developments to improve the volume and quality of general practice in the most socioeconomically deprived areas, and what more can be done.<br/
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