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Tropical Andean glaciers provide an important flux of freshwater to communities living both in high-altitude Cordillera and population centres downstream in countries such as Peru and Bolivia. Glacier recession threatens the sustainability of these water resources, and accurate modelling of future glacier behaviour is required to manage water stress in the region. These models must capture all processes contributing significantly to overall glacier mass budgets. Here we examine supraglacial pond and ice cliff development on three clean-ice glaciers in the Cordillera Vilcanota, Peru and their overall contribution to glacier mass balance. Whilst such features are common and well-studied on debris-covered glaciers, their development on debris-free glaciers has not been examined in detail. We use high-resolution contemporary and historical satellite imagery and repeat drone surveys to examine surface structure and geometry change over three glaciers during 1977–2024. We show how cliff and pond formation is driven by aspect-dependent surface melt of crevasse walls. These features act as ice loss hotspots, which enhance glacier net mass loss by ∼10% despite accounting for <5% glacier surface area. Incorporation of such amplified ice loss processes should be a priority for glacier model advances to achieve more accurate projections of future tropical glacier recession.
People with severe COVID anxiety have significant fears of contagion, physiological symptoms of anxiety in response to a COVID stimulus and employ often disproportionate safety behaviours at the expense of other life priorities.
Aims
To characterise the long-term trajectory of severe COVID anxiety, and the factors that influence recovery.
Method
This prospective cohort study followed 285 people with severe COVID anxiety in the UK over 18 months. A nested randomised feasibility trial tested an online cognitive–behavioural therapy (CBT)-based intervention (no. ISRCTN14973494). Descriptive statistics and linear regression models identified factors associated with change in COVID anxiety over 18 months.
Results
Most participants experienced major reductions in COVID anxiety over time (69.8% relative cohort mean decrease, P < 0.001), but a quarter of people (23.7%, 95% CI: 17.8–30.1) continued to worry about COVID every day, and for 13% symptoms remained severe even after the ending of all public health restrictions. Increasing age, being from a minority ethnic background that confers greater risk from COVID-19, and the persistence of high levels of health anxiety and depressive symptoms, predicted slower improvements in severe COVID anxiety after adjusting for other clinical and demographic factors. Neither a trial CBT-based intervention, nor contextual factors including daily case rates, vaccination status or having contracted COVID-19, appeared to affect the trajectory of severe COVID anxiety.
Conclusions
For most people severe COVID anxiety improves significantly with time. However, interventions treating depression and health anxiety, and targeting older people and those from greater-risk minority backgrounds, warrant further investigation in future pandemics.
Elastic turbulence can lead to increased flow resistance, mixing and heat transfer. Its control – either suppression or promotion – has significant potential, and there is a concerted ongoing effort by the community to improve our understanding. Here we explore the dynamics of uncertainty in elastic turbulence, inspired by an approach recently applied to inertial turbulence in Ge et al. (J. Fluid Mech., vol. 977, 2023, A17). We derive equations for the evolution of uncertainty measures, yielding insight on uncertainty growth mechanisms. Through numerical experiments, we identify four regimes of uncertainty evolution, characterised by (i) rapid transfer to large scales, with large-scale growth rates of $\tau ^{6}$ (where $\tau$ represents time), (ii) a dissipative reduction of uncertainty, (iii) exponential growth at all scales and (iv) saturation. These regimes are governed by the interplay between advective and polymeric contributions (which tend to increase uncertainty), viscous, relaxation and dissipation effects (which reduce uncertainty) and inertial contributions. In elastic turbulence, reducing Reynolds number increases uncertainty at short times, but does not significantly influence the growth of uncertainty at later times. At late times, the growth of uncertainty increases with Weissenberg number, with decreasing polymeric diffusivity and with the logarithm of the maximum length scale, as large flow features adjust the balance of advective and relaxation effects. These findings provide insight into the dynamics of elastic turbulence, offering a new approach for the analysis of viscoelastic flow instabilities.
We all have a personality, whether or not we also have a mental health disorder, and for some people parts of our personality lead to problems with others, or in getting on in our lives. Indeed the same might be said of neurodevelopmental conditions, autism, intellectual disability, ADHD, of which we understand there to be a spectrum of degree, and which in unfavourable circumstances produces difficulty and dysfunction. The combination of personality and neurodevelopmental pathology is common, so too is misdiagnosis between them. This talk will describe the key theories to understand the overlap, tackle diagnostic uncertainty, and outlines the ways in which support can be offered for the combination of the two.
Chronic insomnia is prevalent in secondary care mental health populations and is associated with emotional distress, interpersonal impairment and reduced quality of life. In addition, it contributes to the aetiology of major mental health conditions and substance use. CBT for insomnia (CBTi) is a well-established evidence-based treatment approach for chronic insomnia and is recommended as the first-line treatment for adults in the UK by National Institute for Health and Care Excellence (NICE). Despite this, CBTi is not accessible for most secondary care mental health patients and therefore few benefit from this intervention.
Objectives
To examine the feasibility and effectiveness of a 6-week group CBTi programme for people using secondary care mental health and addictions services with chronic insomnia, using a case series design.
Methods
Each participant underwent an initial screening assessment to evaluate their suitability for the programme, the nature and impact of their sleep problem, and exclude other causes of insomnia. Self-reported measures of insomnia, personality functioning and depression were examined pre- and post-intervention using the Pittsburgh Sleep Quality Index (PSQI), Level of Personality Functioning Scale (LPFS) and Patient Health Questionnaire-9 (PHQ-9) respectively. PSQI was also re-assessed at 3-months’ follow-up.
Results
Of 42 people referred to the service (26 from mental health and 16 from addictions services), 25 attended baseline assessment, 19 started the group and 12 completed sessions. The most common primary diagnoses were Alcohol Use Disorder (n=8), Treatment Resistant Depression (n=5), Bipolar Affective Disorder (n=3) and Personality Disorder (n=3). There were 9 men and 16 women. The severity of sleep disturbance was high with a cohort average PSQI of 15.4 (s.d. 2.7, range 12-20). Additionally, the level of personality functioning was high (mean 31.0, s.d. 7.6 range 13-45) as well as depressive symptoms (PHQ-9 cohort mean 18.0, s.d. 5.5, range 7-26).
Among the completers, cohort mean PSQI score decreased from 14.1 to 12.0 (p=0.12). Of 10 patients with 3-month follow-up data, there was a relative reduction of 20.3% from baseline, to a cohort mean PSQI score of 11.5 (p=0.16). At 3-months other facets of sleep quality like total sleep time had improved in the cohort by 45 minutes, and onset latency reduced by 35 minutes. Post-group there were also reductions in cohort mean LPFS scores by a relative 10.3% (31.4 at baseline to 28.3 post-group, and in cohort mean PHQ-9 by 14.8% (16.4 to 13.8).
Conclusions
Group CBTi is a potentially scalable and feasible intervention that effectively treats chronic insomnia, depression and personality dysfunction in secondary care mental health and addictions populations. Further research should focus on replicating these findings in larger cohorts, and examine factors associated with uptake and completion of CBTi.
In the American Southwest and northern Mexico, it has long been argued that ceramic vessels with exterior surfaces that are covered with small nodes are Datura seed pod effigies. Datura is a genus of flowering plants containing psychoactive alkaloids that, when consumed, can induce hallucinations. Scholars have argued that these noded vessels were part of a ritual complex originating in Mexico and spreading throughout the Southwest. In his 2012 article, Lankford hypothesized that this ritual complex made its way into the southeastern United States based on the presence of the ceramic type Fortune Noded in the Mississippi River Valley. In this article, we evaluate three hypotheses suggested by Lankford. Our absorbed residue study did not support his first hypothesis that Fortune Noded vessels were directly related to Datura consumption. However, existing archaeological data do support the idea that a ritual complex including noded vessels moved through the Caddoan region to the Central Mississippi Valley. Those data also confirm Lankford’s final hypothesis that Datura was used in Mississippian period contexts in the Central Mississippi Valley. We conclude that Lankford’s hypothesis has merit and suggest that noded vessels and other ritual equipment be considered inalienable objects that moved through a network of ritual practitioners.
Bornite (Cu5FeS4) and digenite (Cu9–xFexS5; x = 0.4) have closely related cubic structures and are known for their range of superstructures derived from metal vacancies leading to larger unit cells expressed as n × a, where a = ∼5.5 Å and n is an integer. Such polymorphs can form during cooling from higher temperature bornite (Bn)–digenite (Dg) 1a solid solution (ss). The alleged basket-weave textures in natural bornite are investigated using high-angle annular dark field (HAADF) scanning transmission electron microscopy (STEM) imaging and energy-dispersive X-ray spectrometry. These techniques, combined with crystal modelling and STEM simulations, are suitable for depicting changes in phases related to crystal-structural modularity as they collectively better reproduce atomic distributions in real space. Bornite associated with either chalcocite or chalcopyrite from the Olympic Dam Cu-U-Au-Ag deposit, South Australia has non-stoichiometric Cu/Fe ratios and displays nanoscale basket-weave textures between the main components Bn2a and anilite (Cu7S4); Dg1a is preserved throughout, albeit as a minor phase. Anilite is a derivative of digenite, whereby a = b = √2aDg and c = 2aDg. Two intermediate phases, Dg3a and Bn2a4a, are documented and an additional phase, Bn2a6a, is tentatively suggested to occur in Fe-rich nanodomains within Bn2a. Considering the epitaxial relationships between all phases, we infer that basket-weave textures record phase transitions via polymorphic transformations of parent Bn2a and Dg1a during cooling. Observed phase assemblages are thus linked to cooling of Bn–Dgss in the range 70–87 mol.% Bn along a Cu6.18Fe1.26S5 – Cu9.12Fe0.89S5 tie-line defined from measured compositions. We depict three associations: Bn2a + Dg1a, Bn2a4a + Dg3a, and Bn2a4a/Bn2a6a + anilite, formed during cooling. Polymorph associations like these are relevant for enrichment of critical/precious metals in copper ores because Bi, Pb, Ag, Te and, probably also Au, if dissolved in Bn–Dgss, could be incorporated into superstructures during Cu-Fe-sulfide phase transitions.
Traditional legal scholarship has long focused on the exercise of discretion in all its forms; however, by borrowing from the analytical toolkit of science and technology studies (STS), we begin to take an ‘ontological turn’ into the courtroom by documenting a new tool of judicial discretion invoked by criminal justice adjudicators: what we call ontological discretion. By examining three objects from our own research – sleep, death, and intoxication—we show how their lack of a universal, singular ontology may necessitate that adjudicators use their discretion to either choose a coherent ontology in a given case, or else avoid opining on ‘what things are’ altogether. We therefore start to move beyond those important but now rather mainstream sociolegal inquiries into legal knowledges, instead shifting our focus toward what legal actors say the objects of their various knowledges actually are, as well as the widespread legal effects of the court’s ontological games.
Objectives/Goals: With qualitative interviews we aim to 1-Describe barriers and facilitators for post-transplant lymphoproliferative disease (PTLD) survivors’ access to late effects (LE) care. 2-Investigate clinicians’ perceptions of current and ideal PTLD LE care. Our long-term goal is to develop and pilot implementation strategies to standardize PTLD LE care. Methods/Study Population: Study population: We will recruit 20–25 PTLD survivors or their caregivers and 10–15 health care workers (HCW) from oncology, LE, and solid organ transplant (SOT) teams at St. Louis Children’s Hospital (SLCH). PTLD is a lymphoma-like cancer that occurs in solid organ transplant (SOT) recipients. PTLD survivors experience LE from cancer, yet many do not receive LE care. Research strategy: We will conduct qualitative semi-structured interviews based on the Consolidated Framework for Implementation Research (CFIR). A preliminary codebook will be based on CFIR and refined through transcript review. Team-based coding includes double coding and checking for intercoder reliability. We will generate coding reports to understand themes and identify barriers and facilitators of LE care. Results/Anticipated Results: We hypothesize survivors, caregivers, and HCWs will identify actionable factors to inform future studies to optimize LE care. We will examine the CFIR inner setting (resources, communication, and structural characteristics), outer setting (local attitudes and external pressures), innovation domain (adaptability, evidence base, and relative advantage), individuals domain (need, opportunity, and motivation), and implementation process domain. Our contribution will be novel. 1-This is the first assessment of barriers and facilitators for LE care in pediatric PTLD survivors. 2-We will consider input from HCWs across various disciplines delivering care to PTLD survivors. 3-We anticipate identifying unique contextual factors in PTLD survivors that will influence implementation of evidence-based LE care. Discussion/Significance of Impact: Pediatric cancer survivors experience LE. Coordinated care mitigates LE. PTLD survivors experience a high burden of LE, but less than 10% of PTLD survivors at SLCH follow in LE clinic. No studies have evaluated ideal delivery of LE care for PTLD survivors. Our findings will inform an implementation trial to improve delivery of LE care for PTLD survivors.
Objectives/Goals: This study aims to evaluate the performance of a third-party artificial intelligence (AI) product in predicting diagnosis-related groups (DRGs) in a community healthcare system. We highlight a use case illustrating how clinical practice leverages AI-predicted information in unexpected yet advantageous ways and assess the AI predictions accuracy and practical application. Methods/Study Population: DRGs are crucial for hospital reimbursement under the prospective payment model. The Mayo Clinic Health System (MCHS), a network of clinics and hospitals serving a substantial rural population in Minnesota and Wisconsin, has recently adopted an AI algorithm developed by Xsolis (an AI-focused healthcare solution provider). This algorithm, a 1D convolutional neural network, predicts DRGs based on clinical documentation. To assess the accuracy of AI-generated DRG predictions for inpatient discharges, we analyzed data from 930 patients hospitalized at MCHS Mankato between March 2 and May 13, 2024. The Xsolis platform provided the top three DRG predictions for the first 48 hours of each inpatient stay. The accuracy of these predictions was then compared against the final billed DRG codes from the hospital’s records. Results/Anticipated Results: In our validation set, Xsolis achieved a top-3 DRG prediction accuracy of 71% at 24 hours and 81% at 48 hours, which is lower than the originally reported accuracy of 81.1% and 83.3%, respectively. Interestingly, discussions with clinical practice leaders revealed that the most valuable information derived from the AI predictions was the expected geometric mean length of stay (GMLOS), which Xsolis was perceived to predict accurately. In the Medicare system, each DRG is associated with an expected GMLOS, a critical factor for efficient hospital flow planning. A subsequent analysis comparing predicted GMLOS with the actual length of stay showed variances of -0.10 days on day 1 and 0.14 days on day 2, indicating a high degree of accuracy and aligning with clinical practice perceptions. Discussion/Significance of Impact: Our research underscores that clinical practice can leverage AI predictions in unexpected yet beneficial ways. While initially focused on DRG prediction, the associated GMLOS emerged as more significant. This suggests that AI algorithm validation should be tailored to specific clinical needs rather than relying solely on generalized benchmarks.
Quantum field theory predicts a nonlinear response of the vacuum to strong electromagnetic fields of macroscopic extent. This fundamental tenet has remained experimentally challenging and is yet to be tested in the laboratory. A particularly distinct signature of the resulting optical activity of the quantum vacuum is vacuum birefringence. This offers an excellent opportunity for a precision test of nonlinear quantum electrodynamics in an uncharted parameter regime. Recently, the operation of the high-intensity Relativistic Laser at the X-ray Free Electron Laser provided by the Helmholtz International Beamline for Extreme Fields has been inaugurated at the High Energy Density scientific instrument of the European X-ray Free Electron Laser. We make the case that this worldwide unique combination of an X-ray free-electron laser and an ultra-intense near-infrared laser together with recent advances in high-precision X-ray polarimetry, refinements of prospective discovery scenarios and progress in their accurate theoretical modelling have set the stage for performing an actual discovery experiment of quantum vacuum nonlinearity.
This paper gives definitions of terms which have become critical in ensuring that Anglican churches minimize the risk of harm to all who are involved as practitioners or recipients of its ministries. This imperative is rooted in Scripture, not just the recent history or pronouncements of the Lambeth Conference 2022. The terms ‘Safeguarding’, ‘Safe Ministry’ and ‘Safe Church’ (SC) are set out with reference to the ‘Lambeth Calls’. This paper explores why such terms have come to the forefront of current theological praxis, notes historical iterations of such matters and asks why some Anglican churches or provinces may resist adopting this Lambeth Call. It offers both an apologetic for the universal adoption of SC practices and a scriptural and dominical mandate for them. The paper identifies theological and scriptural principles on which SC theory and practice might be grounded. Anglican churches and provinces are encouraged to develop a theory and practice of SC pertinent to their environment rather than adhere to abstract universal prescriptions which risk irrelevance amidst cultural and contextual particularity.
A generalization of a cognitive probability model is proposed utilizing the serial position effect to account for decay in probability of recall. The general nature of the model permits the incorporation of almost any of the recent free-recall serial position curve results. Two examples, hypothesizing different serial position curves, are given.
England's primary care service for psychological therapy (Improving Access to Psychological Therapies [IAPT]) treats anxiety and depression, with a target recovery rate of 50%. Identifying the characteristics of patients who achieve recovery may assist in optimizing future treatment. This naturalistic cohort study investigated pre-therapy characteristics as predictors of recovery and improvement after IAPT therapy.
Methods
In a cohort of patients attending an IAPT service in South London, we recruited 263 participants and conducted a baseline interview to gather extensive pre-therapy characteristics. Bayesian prediction models and variable selection were used to identify baseline variables prognostic of good clinical outcomes. Recovery (primary outcome) was defined using (IAPT) service-defined score thresholds for both depression (Patient Health Questionnaire [PHQ-9]) and anxiety (Generalized Anxiety Disorder [GAD-7]). Depression and anxiety outcomes were also evaluated as standalone (PHQ-9/GAD-7) scores after therapy. Prediction model performance metrics were estimated using cross-validation.
Results
Predictor variables explained 26% (recovery), 37% (depression), and 31% (anxiety) of the variance in outcomes, respectively. Variables prognostic of recovery were lower pre-treatment depression severity and not meeting criteria for obsessive compulsive disorder. Post-therapy depression and anxiety severity scores were predicted by lower symptom severity and higher ratings of health-related quality of life (EuroQol questionnaire [EQ5D]) at baseline.
Conclusion
Almost a third of the variance in clinical outcomes was explained by pre-treatment symptom severity scores. These constructs benefit from being rapidly accessible in healthcare services. If replicated in external samples, the early identification of patients who are less likely to recover may facilitate earlier triage to alternative interventions.
In response to the COVID-19 pandemic, we rapidly implemented a plasma coordination center, within two months, to support transfusion for two outpatient randomized controlled trials. The center design was based on an investigational drug services model and a Food and Drug Administration-compliant database to manage blood product inventory and trial safety.
Methods:
A core investigational team adapted a cloud-based platform to randomize patient assignments and track inventory distribution of control plasma and high-titer COVID-19 convalescent plasma of different blood groups from 29 donor collection centers directly to blood banks serving 26 transfusion sites.
Results:
We performed 1,351 transfusions in 16 months. The transparency of the digital inventory at each site was critical to facilitate qualification, randomization, and overnight shipments of blood group-compatible plasma for transfusions into trial participants. While inventory challenges were heightened with COVID-19 convalescent plasma, the cloud-based system, and the flexible approach of the plasma coordination center staff across the blood bank network enabled decentralized procurement and distribution of investigational products to maintain inventory thresholds and overcome local supply chain restraints at the sites.
Conclusion:
The rapid creation of a plasma coordination center for outpatient transfusions is infrequent in the academic setting. Distributing more than 3,100 plasma units to blood banks charged with managing investigational inventory across the U.S. in a decentralized manner posed operational and regulatory challenges while providing opportunities for the plasma coordination center to contribute to research of global importance. This program can serve as a template in subsequent public health emergencies.