Scleromochlus and the early evolution of Pterosauromorpha

Pterosaurs, the first vertebrates to evolve powered flight, were key components of Mesozoic terrestrial ecosystems from their sudden appearance in the Late Triassic until their demise at the end of the Cretaceous1,2,3,4,5,6. However, the origin and early evolution of pterosaurs are poorly understood owing to a substantial stratigraphic and morphological gap between these reptiles and their closest relatives6, Lagerpetidae7. Scleromochlus taylori, a tiny reptile from the early Late Triassic of Scotland discovered over a century ago, was hypothesized to be a key taxon closely related to pterosaurs8, but its poor preservation has limited previous studies and resulted in controversy over its phylogenetic position, with some even doubting its identification as an archosaur9. Here we use microcomputed tomographic scans to provide the first accurate whole-skeletal reconstruction and a revised diagnosis of Scleromochlus, revealing new anatomical details that conclusively identify it as a close pterosaur relative1 within Pterosauromorpha (the lagerpetid + pterosaur clade). Scleromochlus is anatomically more similar to lagerpetids than to pterosaurs and retains numerous features that were probably present in very early diverging members of Avemetatarsalia (bird-line archosaurs). These results support the hypothesis that the first flying reptiles evolved from tiny, probably facultatively bipedal, cursorial ancestors1

Modified Needleman-Wunsch algorithm for clinical pathway clustering

Clinical pathways are used to guide clinicians to provide a standardised delivery of care. Because of their standardisation, the aim of clinical pathways is to reduce variation in both care process and patient outcomes. When learning clinical pathways from data through data mining, it is common practice to represent each patient pathway as a string corresponding to their movements through activities. Clustering techniques are popular methods for pathway mining, and therefore this paper focuses on distance metrics applied to string data for k-medoids clustering. The two main aims are to firstly, develop a technique that seamlessly integrates expert information with data and secondly, to develop a string distance metric for the purpose of process data. The overall goal was to allow for more meaningful clustering results to be found by adding context into the string similarity calculation. Eight common distance metrics and their applicability are discussed. These distance metrics prove to give an arbitrary distance, without consideration for context, and each produce different results. As a result, this paper describes the development of a new distance metric, the modified Needleman–Wunsch algorithm, that allows for expert interaction with the calculation by assigning groupings and rankings to activities, which provide context to the strings. This algorithm has been developed in partnership with UK’s National Health Service (NHS) with the focus on a lung cancer pathway, however the handling of the data and algorithm allows for application to any disease type. This method is contained within Sim.Pro.Flow, a publicly available decision support tool

Multifactor dimensionality reduction for graphics processing units enables genome-wide testing of epistasis in sporadic ALS

Motivation: Epistasis, the presence of gene–gene interactions, has been hypothesized to be at the root of many common human diseases, but current genome-wide association studies largely ignore its role. Multifactor dimensionality reduction (MDR) is a powerful model-free method for detecting epistatic relationships between genes, but computational costs have made its application to genome-wide data difficult. Graphics processing units (GPUs), the hardware responsible for rendering computer games, are powerful parallel processors. Using GPUs to run MDR on a genome-wide dataset allows for statistically rigorous testing of epistasis

Implementing psychological support for health and social care staff affected by the COVID-19 pandemic: a qualitative exploration of staff well-being hubs ('Resilience Hubs') using normalisation process theory

Objectives Evaluate the implementation of Hubs providing access to psychological support for health and social care keyworkers affected by the COVID-19 pandemic. Design Qualitative interviews informed by normalisation process theory to understand how the Hub model became embedded into normal practice, and factors that disrupted normalisation of this approach. Setting Three Resilience Hubs in the North of England. Participants Hub staff, keyworkers who accessed Hub support (Hub clients), keyworkers who had not accessed a Hub, and wider stakeholders involved in the provision of staff support within the health and care system (N=63). Results Hubs were generally seen as an effective way of supporting keyworkers, and Hub clients typically described very positive experiences. Flexibility and adaptability to local needs were strongly valued. Keyworkers accessed support when they understood the offer, valuing a confidential service that was separate from their organisation. Confusion about how Hubs differed from other support prevented some from enrolling. Beliefs about job roles, unsupportive managers, negative workplace cultures and systemic issues prevented keyworkers from valuing mental health support. Lack of support from managers discouraged keyworker engagement with Hubs. Black, Asian and minority ethnic keyworkers impacted by racism felt that the Hubs did not always meet their needs. Conclusions Hubs were seen as a valuable, responsive and distinct part of the health and care system. Findings highlight the importance of improving promotion and accessibility of Hubs, and continuation of confidential Hub support. Policy implications for the wider health and care sector include the central importance of genuine promotion of and value placed on mental health support by health and social care management, and the creation of psychologically safe work environments. Diversity and cultural competency training is needed to better reach under-represented communities. Findings are consistent with the international literature, therefore, likely to have applicability outside of the current context

HER2-HER3 heterodimer quantification by FRET-FILM and patient subclass analysis of the COIN colorectal trial

BACKGROUND: The phase 3 MRC COIN trial showed no statistically significant benefit from adding the EGFR-target cetuximab to oxaliplatin-based chemotherapy in first-line treatment of advanced colorectal cancer. This study exploits additional information on HER2-HER3 dimerization to achieve patient stratification and reveal previously hidden subgroups of patients who had differing disease progression and treatment response. METHODS: HER2-HER3 dimerization was quantified by 'FLIM Histology' in primary tumor samples from 550 COIN trial patients receiving oxaliplatin and fluoropyrimidine chemotherapy +/-cetuximab. Bayesian latent class analysis (LCA) and covariate reduction was performed to analyze the effects of HER2-HER3 dimer, RAS mutation and cetuximab on progression-free survival (PFS) and overall survival (OS). All statistical tests were two-sided. RESULTS: LCA on a cohort of 398 patients revealed two patient subclasses with differing prognoses (median OS: 1624 days [95%CI=1466-1816] vs 461 [95%CI=431-504]): Class 1 (15.6%) showed a benefit from cetuximab in OS (HR = 0.43 [95%CI=0.25-0.76]; p = 0.004). Class 2 showed an association of increased HER2-HER3 with better OS (HR = 0.64 [95%CI=0.44-0.94]; p = 0.02). A class prediction signature was formed and tested on an independent validation cohort (N = 152) validating the prognostic utility of the dimer assay. Similar subclasses were also discovered in full trial dataset (N = 1,630) based on 10 baseline clinicopathological and genetic covariates. CONCLUSIONS: Our work suggests that the combined use of HER dimer imaging and conventional mutation analyses will be able to identify a small subclass of patients (>10%) who will have better prognosis following chemotherapy. A larger prospective cohort will be required to confirm its utility in predicting the outcome of anti-EGFR treatment

A service mapping exercise of four health and social care staff mental health and wellbeing services, Resilience Hubs, to describe health service provision and interventions

Background: NHS England funded 40 Mental Health and Wellbeing Hubs to support health and social care staff affected by the COVID-19 pandemic. We aimed to document variations in how national guidance was adapted to the local contexts of four Hubs in the North of England.Methods: We used a modified version of Price’s (2019) service mapping methodology. Service level data were used to inform the analysis. A mapping template was adapted from a range of tools, including the European Service Mapping Schedule, and reviewed by Hub leads. Key data included service model; staffing; and interventions. Data were collected between March 2021 – March 2022 by site research assistants. Findings were accuracy-checked by Hub leads, and a logic model developed to theorise how the Hubs may effect change.Results: Hub goals and service models closely reflected guidance; offering: proactive outreach; team-based support; clinical assessment; onward referral, and rapid access to mental health support (in-house and external). Implementation reflected a service context of a client group with high mental health need, and high waiting times at external mental health services. Hubs were predominantly staffed by experienced clinicians, to manage these mental health presentations and organisational working. Formulation-based psychological assessment and the provision of direct therapy were not core functions of the NHS England model, however all Hubs incorporated these adaptations into their service models in response to local contexts, such as extensive waiting lists within external services, and/or client presentations falling between gaps in existing service provision. Finally, a standalone clinical records system was seen as important to reassure Hub users of confidentiality. Other more nuanced variation depended on localised contexts.Conclusion: This study provides a map for setting up services, emphasising early understandings of how new services will integrate within existing systems. Local and regional contexts led to variation in service configuration. Whilst additional Hub functions are supported by available literature, further research is needed to determine whether these functions should comprise essential components of staff wellbeing services moving forward. Future research should also determine the comparative effectiveness of service components, and the limits of permissible variation.Study registration: researchregistry6303.</p

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Proper Watering by Earl P. Grey (page 1) Soil Structure and Plant Feeding for Trees and Shrubs on the Golf Course by William Teece (2) Power Golf Carts: A Blessing or a Curse by David Dunlavey (3) A Comparison by Paul White (3) Trees on a Golf Course by Oliver Leech (5) Turf Management Majors Want a Golf Team by Richard Rossiter (6) Class Will of \u2766 (7)Famous Last Words from 1966 (8) Turf Heating with Electric Cables by J.R. Barrett, Jr. and W.H. Daniel (A-1) Poa Annua Restriction by C. F. Kerr and W.H. Daniel (A-9) Phosphorus by Marvin H. Ferguson (A-14) Role of Potassium in Turf Grass management by R. E. Wagner (A-16) Role of Minor Elements in Turfgrass Management by Alexander Radko (A-22) Rhizoctonia Brown patch and Pythium Diseas by Malcolm C. Shurtleff (A-27) Sclerotinia Dollar Spot and Snow Mold by Noel Jackson (A-32) Fusarium Blight - Disease of Turf Grasses by George A. Bean (A-35) Observing the Weather - Old and New Techniques by Robert C. Copeland (A-39) Water Supply by Allan Grieve Jr. (A-41) Establishment and Maintenance of Campus Turf by William A. Lambert (A-51) Athletic Field Management by J. T. Williams (A-56