The barriers and facilitators to the design and delivery of sustainable healthcare across NHS Scotland: A forcefield analysis.

Healthcare systems around the world have set ambitious targets to design and deliver more environmentally sustainable healthcare. To achieve these targets, individuals, teams, organisations, and whole systems will have to change current attitudes, practices and processes. Change management theory advocates for early identification of the influencing forces to change, so that actions can be taken to overcome the barriers and strengthen the facilitators to increase the likelihood of success. This project undertook a forcefield analysis exercise to identify the barriers and facilitators to the design and delivery of sustainable healthcare in Scotland. The exercise identified 12 facilitators and 12 barriers to sustainable change and formulated ten recommendations to strengthen the former and overcome the latter. It is hoped that the results will raise awareness of the factors that influence the design and delivery of sustainable healthcare and will inform what actions can be taken to increase the likelihood of success.

foxg1a is required for hair cell development and regeneration in the zebrafish lateral line.

Mechanosensory hair cells located in the inner ear mediate the sensations of hearing and balance. If damaged, mammalian inner ear hair cells are unable to regenerate, resulting in permanent sensory deficits. Aquatic vertebrates like zebrafish (Danio rerio) have a specialized class of mechanosensory hair cells found in the lateral line system, allowing them to sense changes in water current. Unlike mammalian inner ear hair cells, lateral line hair cells can robustly regenerate following damage. In mammalian models, the transcription factor Foxg1 functions to promote normal development of the inner ear. Foxg1a is expressed in lateral line sensory organs in zebrafish larvae, but its function during lateral line development and regeneration has not been investigated. We find that loss of Foxg1a function results in reduced hair cell development and regeneration, as well as decreased cellular proliferation in the lateral line system. These data suggest that Foxg1 may be a valuable target for investigation of clinical hair cell regeneration. Summary statement: Our work demonstrates a role for Foxg1a in developing and regenerating new sensory cells through proliferation.

Long-Term Culture of Individual Caenorhabditis elegans on Solid Media for Longitudinal Fluorescence Monitoring and Aversive Interventions.

Caenorhabditis elegans are widely used to study aging biology. The standard practice in C. elegans aging studies is to culture groups of worms on solid nematode growth media (NGM), allowing the efficient collection of population-level data for survival and other physiological phenotypes, and periodic sampling of subpopulations for fluorescent biomarker quantification. Limitations to this approach are the inability to (1) follow individual worms over time to develop age trajectories for phenotypes of interest and (2) monitor fluorescent biomarkers directly in the context of the culture environment. Alternative culture approaches use liquid culture or microfluidics to monitor individual animals over time, in some cases including fluorescence quantification, with the tradeoff that the culture environment is contextually distinct from solid NGM. The WorMotel is a previously described microfabricated multi-well device for culturing isolated worms on solid NGM. Each worm is maintained in a well containing solid NGM surrounded by a moat filled with copper sulfate, a contact repellent for C. elegans, allowing longitudinal monitoring of individual animals. We find copper sulfate insufficient to prevent worms from fleeing when subjected to aversive interventions common in aging research, including dietary restriction, pathogenic bacteria, and chemical agents that induce cellular stress. The multi-well devices are also molded from polydimethylsiloxane, which produces high background artifacts in fluorescence imaging. This protocol describes a new approach for culturing isolated roundworms on solid NGM using commercially available polystyrene microtrays, originally designed for human leukocyte antigen (HLA) typing, allowing the measurement of survival, physiological phenotypes, and fluorescence across the lifespan. A palmitic acid barrier prevents worms from fleeing, even in the presence of aversive conditions. Each plate can culture up to 96 animals and easily adapts to a variety of conditions, including dietary restriction, RNAi, and chemical additives, and is compatible with automated systems for collecting lifespan and activity data.

Predicting Domestic Abuse (Fairly) and Police Risk Assessment

Domestic abuse victim risk assessment is crucial for providing victims with the correct level of support. However, it has been shown that the approach currently taken by most UK police forces, the Domestic Abuse, Stalking, and Honour Based Violence (DASH) risk assessment, is not identifying the most vulnerable victims. Instead, we tested several machine learning algorithms and propose a predictive model, using logistic regression with elastic net as the best performing, that incorporates information readily available in police databases, and census-area-level statistics. We used data from a large UK police force including 350,000 domestic abuse incidents. Our models made significant improvement upon the predictive capacity of DASH, both for intimate partner violence (IPV; AUC = .748) and other forms of domestic abuse (non-IPV; AUC = .763). The most influential variables in the model were of the categories criminal history and domestic abuse history, particularly time since the last incident. We show that the DASH questions contributed almost nothing to the predictive performance. We also provide an overview of model fairness performance for ethnic and socioeconomic subgroups of the data sample. Although there were disparities between ethnic and demographic subgroups, everyone benefited from the increased accuracy of model-based predictions when compared with officer risk predictions. (AU)

La evaluación de riesgo de las víctimas de abuso doméstico es crucial para poder ofrecerle a las mismas el nivel adecuado de asistencia. No obstante, se ha demostrado que el enfoque predominante en casi todas las fuerzas policiales británicas, que descansa en el uso de DASH (las iniciales en inglés del instrumento de evaluación de abuso doméstico, acoso y violencia por cuestión de honor), no sirve para identificar a las víctimas más vulnerables. En su lugar, este artículo evalúa varios algoritmos de aprendizaje automático y propone un modelo predictivo, usando como algoritmo con un mejor rendimiento una regresión logística con red elástica, que utiliza como fuente de información variables normalmente disponibles en los archivos policiales, así como en el censo de la población. Para desarrollar y evaluar este modelo usamos datos de un departamento policial responsable de un área metropolitana en el Reino Unido que incluía 350,000 incidentes de abuso doméstico. Nuestros modelos mejoran significativamente la capacidad predictiva de DASH, tanto para la violencia en la relación de pareja (AUC = .748) como para otras formas de abuso doméstico (AUC = .763). Las variables más influyentes en el modelo fueron medidas del historial delictivo y de violencia doméstica previa, en particular el tiempo transcurrido desde el último incidente. El artículo demuestra que el cuestionario DASH prácticamente no contribuye nada al rendimiento predictivo de nuestro modelo. El artículo también ofrece una evaluación del rendimiento en términos de equidad para distintos grupos étnicos y socioeconómicos en nuestra muestra. Aunque había disparidad entre estos subgrupos, todos ellos se beneficiaban de la mayor precisión predictiva resultante de usar nuestros modelos en lugar de las clasificaciones policiales basadas en DASH. (AU)

Multi-disciplinary community respiratory team management of patients with chronic respiratory illness during the COVID-19 pandemic.

The Greater Glasgow & Clyde NHS Trust Community Respiratory Response Team was established to manage patients with chronic respiratory disease at home during the COVID-19 pandemic. The team aimed to avert hospital admission while maximally utilising remote consultations. This observational study analysed outcomes of the triage pathway used, use of remote consultations, hospital admissions and mortality among patients managed by the team. Patients' electronic health records were retrospectively reviewed. Rates of emergency department attendance, hospital admission and death within 28 days of referral were compared across triage pathways. Segmented linear regression was carried out for emergency admissions in Greater Glasgow and Clyde pre- and post- Community Respiratory Response Team implementation, using emergency admissions for chronic obstructive pulmonary disease in the rest of Scotland as control and adjusting for all-cause emergency admissions. The triage category correlated with hospital admission and death. The red pathway had the highest proportion attending the emergency department (21%), significantly higher than the amber and green pathways (p = 0.03 and p = 0.004, respectively). The highest number of deaths were in the blue "end-of-life" pathway (p < 0.001). 87% of interactions were undertaken remotely. Triage severity appropriately led to targeted home visits. No nosocomial COVID-19 infections occurred among patients or staff. The Community Respiratory Response Team was associated with a significant decrease in emergency admissions (RR = 0.96 for each additional month under the Poisson model) compared to the counterfactual if the service had not been in place, suggesting a benefit in reducing secondary care pressures. The Community Respiratory Response Team effectively managed patients with chronic respiratory disease in the community, with an associated reduction in secondary care pressures during the COVID-19 pandemic.

Vertebrate growth plasticity in response to variation in a mutualistic interaction.

Vertebrate growth can be phenotypically plastic in response to predator-prey and competitive interactions. It is unknown however, if it can be plastic in response to mutualistic interactions. Here we investigate plasticity of vertebrate growth in response to variation in mutualistic interactions, using clown anemonefish and their anemone hosts. In the wild, there is a positive correlation between the size of the fish and the size of the anemone, but the cause of this correlation is unknown. Plausible hypotheses are that fish exhibit growth plasticity in response to variation in food or space provided by the host. In the lab, we pair individuals with real anemones of various sizes and show that fish on larger anemones grow faster than fish on smaller anemones. By feeding the fish a constant food ration, we exclude variation in food availability as a cause. By pairing juveniles with artificial anemones of various sizes, we exclude variation in space availability as a single cause. We argue that variation in space availability in conjunction with host cues cause the variability in fish growth. By adjusting their growth, anemonefish likely maximize their reproductive value given their anemone context. More generally, we demonstrate vertebrate growth plasticity in response to variation in mutualistic interactions.

The Diffusion Mechanism of Ge During Oxidation of Si/SiGe Nanofins.

A recently discovered, enhanced Ge diffusion mechanism along the oxidizing interface of Si/SiGe nanostructures has enabled the formation of single-crystal Si nanowires and quantum dots embedded in a defect-free, single-crystal SiGe matrix. Here, we report oxidation studies of Si/SiGe nanofins aimed at gaining a better understanding of this novel diffusion mechanism. A superlattice of alternating Si/Si0.7Ge0.3 layers was grown and patterned into fins. After oxidation of the fins, the rate of Ge diffusion down the Si/SiO2 interface was measured through the analysis of HAADF-STEM images. The activation energy for the diffusion of Ge down the sidewall was found to be 1.1 eV, which is less than one-quarter of the activation energy previously reported for Ge diffusion in bulk Si. Through a combination of experiments and DFT calculations, we propose that the redistribution of Ge occurs by diffusion along the Si/SiO2 interface followed by a reintroduction into substitutional positions in the crystalline Si.

A biological classification of Huntington's disease: the Integrated Staging System.

The current research paradigm for Huntington's disease is based on participants with overt clinical phenotypes and does not address its pathophysiology nor the biomarker changes that can precede by decades the functional decline. We have generated a new research framework to standardise clinical research and enable interventional studies earlier in the disease course. The Huntington's Disease Integrated Staging System (HD-ISS) comprises a biological research definition and evidence-based staging centred on biological, clinical, and functional assessments. We used a formal consensus method that involved representatives from academia, industry, and non-profit organisations. The HD-ISS characterises individuals for research purposes from birth, starting at Stage 0 (ie, individuals with the Huntington's disease genetic mutation without any detectable pathological change) by using a genetic definition of Huntington's disease. Huntington's disease progression is then marked by measurable indicators of underlying pathophysiology (Stage 1), a detectable clinical phenotype (Stage 2), and then decline in function (Stage 3). Individuals can be precisely classified into stages based on thresholds of stage-specific landmark assessments. We also demonstrated the internal validity of this system. The adoption of the HD-ISS could facilitate the design of clinical trials targeting populations before clinical motor diagnosis and enable data standardisation across ongoing and future studies.

Huntington's Disease Regulatory Science Consortium: Accelerating Medical Product Development.

Huntington's disease (HD) is a devastating neurodegenerative disorder that urgently needs disease-modifying therapeutics. To this end, collaboration to standardize clinical research practices in the field and drive progress in addressing drug development challenges is paramount. At a meeting in 2017 organized by CHDI Foundation and the Critical Path Institute, stakeholders across the pharmaceutical industry, academia, regulatory agencies, and patient advocacy groups discussed the need for and potential impact of a consortium dedicated to HD regulatory science. Consequently, the Huntington's Disease Regulatory Science Consortium (HD-RSC) was formed, a precompetitive consortium that is dedicated to building a regulatory strategy to expedite the approval of HD therapeutics.

Predicting Domestic Abuse (Fairly) and Police Risk Assessment.

Domestic abuse victim risk assessment is crucial for providing victims with the correct level of support. However, it has been shown that the approach currently taken by most UK police forces, the Domestic Abuse, Stalking, and Honour Based Violence (DASH) risk assessment, is not identifying the most vulnerable victims. Instead, we tested several machine learning algorithms and propose a predictive model, using logistic regression with elastic net as the best performing, that incorporates information readily available in police databases, and census-area-level statistics. We used data from a large UK police force including 350,000 domestic abuse incidents. Our models made significant improvement upon the predictive capacity of DASH, both for intimate partner violence (IPV; AUC = .748) and other forms of domestic abuse (non-IPV; AUC = .763). The most influential variables in the model were of the categories criminal history and domestic abuse history, particularly time since the last incident. We show that the DASH questions contributed almost nothing to the predictive performance. We also provide an overview of model fairness performance for ethnic and socioeconomic subgroups of the data sample. Although there were disparities between ethnic and demographic subgroups, everyone benefited from the increased accuracy of model-based predictions when compared with officer risk predictions.

La evaluación de riesgo de las víctimas de abuso doméstico es crucial para poder ofrecerle a las mismas el nivel adecuado de asistencia. No obstante, se ha demostrado que el enfoque predominante en casi todas las fuerzas policiales británicas, que descansa en el uso de DASH (las iniciales en inglés del instrumento de evaluación de abuso doméstico, acoso y violencia por cuestión de honor), no sirve para identificar a las víctimas más vulnerables. En su lugar, este artículo evalúa varios algoritmos de aprendizaje automático y propone un modelo predictivo, usando como algoritmo con un mejor rendimiento una regresión logística con red elástica, que utiliza como fuente de información variables normalmente disponibles en los archivos policiales, así como en el censo de la población. Para desarrollar y evaluar este modelo usamos datos de un departamento policial responsable de un área metropolitana en el Reino Unido que incluía 350,000 incidentes de abuso doméstico. Nuestros modelos mejoran significativamente la capacidad predictiva de DASH, tanto para la violencia en la relación de pareja (AUC = .748) como para otras formas de abuso doméstico (AUC = .763). Las variables más influyentes en el modelo fueron medidas del historial delictivo y de violencia doméstica previa, en particular el tiempo transcurrido desde el último incidente. El artículo demuestra que el cuestionario DASH prácticamente no contribuye nada al rendimiento predictivo de nuestro modelo. El artículo también ofrece una evaluación del rendimiento en términos de equidad para distintos grupos étnicos y socioeconómicos en nuestra muestra. Aunque había disparidad entre estos subgrupos, todos ellos se beneficiaban de la mayor precisión predictiva resultante de usar nuestros modelos en lugar de las clasificaciones policiales basadas en DASH.

Recommendations to Optimize the Use of Volumetric MRI in Huntington's Disease Clinical Trials.

Volumetric magnetic resonance imaging (vMRI) has been widely studied in Huntington's disease (HD) and is commonly used to assess treatment effects on brain atrophy in interventional trials. Global and regional trajectories of brain atrophy in HD, with early involvement of striatal regions, are becoming increasingly understood. However, there remains heterogeneity in the methods used and a lack of widely-accessible multisite, longitudinal, normative datasets in HD. Consensus for standardized practices for data acquisition, analysis, sharing, and reporting will strengthen the interpretation of vMRI results and facilitate their adoption as part of a pathobiological disease staging system. The Huntington's Disease Regulatory Science Consortium (HD-RSC) currently comprises 37 member organizations and is dedicated to building a regulatory science strategy to expedite the approval of HD therapeutics. Here, we propose four recommendations to address vMRI standardization in HD research: (1) a checklist of standardized practices for the use of vMRI in clinical research and for reporting results; (2) targeted research projects to evaluate advanced vMRI methodologies in HD; (3) the definition of standard MRI-based anatomical boundaries for key brain structures in HD, plus the creation of a standard reference dataset to benchmark vMRI data analysis methods; and (4) broad access to raw images and derived data from both observational studies and interventional trials, coded to protect participant identity. In concert, these recommendations will enable a better understanding of disease progression and increase confidence in the use of vMRI for drug development.

Volumetric MRI-Based Biomarkers in Huntington's Disease: An Evidentiary Review.

Huntington's disease (HD) is an autosomal-dominant inherited neurodegenerative disorder that is caused by expansion of a CAG-repeat tract in the huntingtin gene and characterized by motor impairment, cognitive decline, and neuropsychiatric disturbances. Neuropathological studies show that disease progression follows a characteristic pattern of brain atrophy, beginning in the basal ganglia structures. The HD Regulatory Science Consortium (HD-RSC) brings together diverse stakeholders in the HD community-biopharmaceutical industry, academia, nonprofit, and patient advocacy organizations-to define and address regulatory needs to accelerate HD therapeutic development. Here, the Biomarker Working Group of the HD-RSC summarizes the cross-sectional evidence indicating that regional brain volumes, as measured by volumetric magnetic resonance imaging, are reduced in HD and are correlated with disease characteristics. We also evaluate the relationship between imaging measures and clinical change, their longitudinal change characteristics, and within-individual longitudinal associations of imaging with disease progression. This analysis will be valuable in assessing pharmacodynamics in clinical trials and supporting clinical outcome assessments to evaluate treatment effects on neurodegeneration.

Controlled Formation of Stacked Si Quantum Dots in Vertical SiGe Nanowires.

We demonstrate the ability to fabricate vertically stacked Si quantum dots (QDs) within SiGe nanowires with QD diameters down to 2 nm. These QDs are formed during high-temperature dry oxidation of Si/SiGe heterostructure pillars, during which Ge diffuses along the pillars' sidewalls and encapsulates the Si layers. Continued oxidation results in QDs with sizes dependent on oxidation time. The formation of a Ge-rich shell that encapsulates the Si QDs is observed, a configuration which is confirmed to be thermodynamically favorable with molecular dynamics and density functional theory. The type-II band alignment of the Si dot/SiGe pillar suggests that charge trapping on the Si QDs is possible, and electron energy loss spectra show that a conduction band offset of at least 200 meV is maintained for even the smallest Si QDs. Our approach is compatible with current Si-based manufacturing processes, offering a new avenue for realizing Si QD devices.

Baclofen therapeutics, toxicity, and withdrawal: A narrative review.

Baclofen is an effective therapeutic for the treatment of spasticity related to multiple sclerosis, spinal cord injuries, and other spinal cord pathologies. It has been increasingly used off-label for the management of several disorders, including musculoskeletal pain, gastroesophageal reflux disease, and alcohol use disorder. Baclofen therapy is associated with potential complications, including life-threatening toxicity and withdrawal syndrome. These disorders require prompt recognition and a high index of suspicion. While these complications can develop following administration of either oral or intrathecal baclofen, the risk is greater with the intrathecal route. The management of baclofen toxicity is largely supportive while baclofen withdrawal syndrome is most effectively treated with re-initiation or supplementation of baclofen dosing. Administration of other pharmacologic adjuncts may be required to effectively treat associated withdrawal symptoms. This narrative review provides an overview of the historical and emerging uses of baclofen, offers practical dosing recommendations for both oral and intrathecal routes of administration, and reviews the diagnosis and management of both baclofen toxicity and withdrawal.

Effective Data Sharing as a Conduit for Advancing Medical Product Development.

INTRODUCTION: Patient-level data sharing has the potential to significantly impact the lives of patients by optimizing and improving the medical product development process. In the product development setting, successful data sharing is defined as data sharing that is actionable and facilitates decision making during the development and review of medical products. This often occurs through the creation of new product development tools or methodologies, such as novel clinical trial design and enrichment strategies, predictive pre-clinical and clinical models, clinical trial simulation tools, biomarkers, and clinical outcomes assessments, and more. METHODS: To be successful, extensive partnerships must be established between all relevant stakeholders, including industry, academia, research institutes and societies, patient-advocacy groups, and governmental agencies, and a neutral third-party convening organization that can provide a pre-competitive space for data sharing to occur. CONCLUSIONS: Data sharing focused on identified regulatory deliverables that improve the medical product development process encounters significant challenges that are not seen with data sharing aimed at advancing clinical decision making and requires the commitment of all stakeholders. Regulatory data sharing challenges and solutions, as well as multiple examples of previous successful data sharing initiatives are presented and discussed in the context of medical product development.

Standardized Data Structures in Rare Diseases: CDISC User Guides for Duchenne Muscular Dystrophy and Huntington's Disease.

Interest in drug development for rare diseases has expanded dramatically since the Orphan Drug Act was passed in 1983, with 40% of new drug approvals in 2019 targeting orphan indications. However, limited quantitative understanding of natural history and disease progression hinders progress and increases the risks associated with rare disease drug development. Use of international data standards can assist in data harmonization and enable data exchange, integration into larger datasets, and a quantitative understanding of disease natural history. The US Food and Drug Administration (FDA) requires the use of Clinical Data Interchange Consortium (CDISC) Standards in new drug submissions to help the agency efficiently and effectively receive, process, review, and archive submissions, as well as to help integrate data to answer research questions. Such databases have been at the core of biomarker qualification efforts and fit-for-purpose models endorsed by the regulators. We describe the development of CDISC therapeutic area user guides for Duchenne muscular dystrophy and Huntington's disease through Critical Path Institute consortia. These guides describe formalized data structures and controlled terminology to map and integrate data from different sources. This will result in increased standardization of data collection and allow integration and comparison of data from multiple studies. Integration of multiple data sets enables a quantitative understanding of disease progression, which can help overcome common challenges in clinical trial design in these and other rare diseases. Ultimately, clinical data standardization will lead to a faster path to regulatory approval of urgently needed new therapies for patients.

An enormous sulfur isotope excursion indicates marine anoxia during the end-Triassic mass extinction.

The role of ocean anoxia as a cause of the end-Triassic marine mass extinction is widely debated. Here, we present carbonate-associated sulfate δ34S data from sections spanning the Late Triassic-Early Jurassic transition, which document synchronous large positive excursions on a global scale occurring in ~50 thousand years. Biogeochemical modeling demonstrates that this S isotope perturbation is best explained by a fivefold increase in global pyrite burial, consistent with large-scale development of marine anoxia on the Panthalassa margin and northwest European shelf. This pyrite burial event coincides with the loss of Triassic taxa seen in the studied sections. Modeling results also indicate that the pre-event ocean sulfate concentration was low (<1 millimolar), a common feature of many Phanerozoic deoxygenation events. We propose that sulfate scarcity preconditions oceans for the development of anoxia during rapid warming events by increasing the benthic methane flux and the resulting bottom-water oxygen demand.

Wet-chemical etching of FIB lift-out TEM lamellae for damage-free analysis of 3-D nanostructures.

Reducing ion beam damage from the focused ion beam (FIB) during fabrication of cross sections is a well-known challenge for materials characterization, especially cross sectional characterization of nanostructures. To address this, a new method has been developed for cross section fabrication enabling high resolution transmission electron microscopy (TEM) analysis of 3-D nanostructures free of surrounding material and free of damage detectable by TEM analysis. Before FIB processing, nanopillars are encapsulated in a sacrificial oxide which acts as a protective layer during FIB milling. The cross sectional TEM lamella containing the nanopillars is then mounted and thinned with some modifications to conventional FIB sample preparation that provide stability for the lamella during the following wet-chemical dip etch. The wet-chemical etch of the TEM lamella removes the sacrificial oxide layer, freeing the nanopillars from any material that would obscure TEM imaging. Both high resolution TEM and aberration corrected scanning TEM images of Si/SiGe pillars with diameters down to 30 nm demonstrate the successful application of this approach.