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Background The Obstetric Anal Sphincter Injury (OASI) Care Bundle comprises four primary and secondary prevention practices that target the rising rates of severe perineal tearing during childbirth, which can have severe debilitating consequences for women. The OASI Care Bundle was implemented in 16 maternity units in Britain in the OASI1 project (2017-2018), which demonstrated the care bundle’s effectiveness in reducing OASI rates. In OASI2, the care bundle will be scaled up to 20 additional National Health Service (NHS) maternity units in a hybrid effectiveness-implementation study that will examine the effectiveness of strategies used to introduce, implement and sustain the care bundle. Methods OASI2 is a two-arm cluster-randomised control trial (C-RCT) of maternity units in England, Scotland and Wales, with an additional non-randomised study arm. C-RCT arm 1 (peer support, n = 10 units) will be supported by ‘buddy’ units to implement the OASI Care Bundle. C-RCT arm 2 (lean implementation, n = 10 units) will implement without external support. The additional study arm (sustainability, n = 10 units) will include some original OASI1 units to evaluate the care bundle’s sustainability and OASI rates over time, from before OASI1 and through the end of OASI2. Units in all three study arms will receive an Implementation Toolkit with training resources and implementation support. The C-RCT arms will be compared in terms of OASI rate reduction (primary effectiveness outcome) and clinicians’ adoption of the care bundle (primary implementation outcome). Clinical data will be collated from maternity information systems; implementation data will be collected through validated surveys with women and clinicians, supplemented by qualitative methods. Descriptive statistics and regression modelling will be used for analysis. Emergent themes from the qualitative data will be assessed using framework analysis. Discussion OASI2 will study the impact of various implementation strategies used to introduce and sustain the OASI Care Bundle, and how these strategies affect the bundle’s clinical effectiveness. The study will generate insights into how to effectively scale-up and sustain uptake and coverage of similar interventions in maternity units. A locally adaptable ‘implementation blueprint’ will be produced to inform development of future guidelines to prevent perineal trauma. Trial registration ISRCTN26523605

Introduction Major surgery accounts for a substantial proportion of health service activity, due not only to the primary procedure, but the longer-term health implications of poor short-term outcome. Data from small studies or from outside the UK indicate that rates of complications and failure to rescue vary between hospitals, as does compliance with best practice processes. Within the UK, there is currently no system for monitoring postoperative complications (other than short-term mortality) in major non-cardiac surgery. Further, there is variation between national audit programmes, in the emphasis placed on quality assurance versus quality improvement, and therefore the principles of measurement and reporting which are used to design such programmes. Methods and analysis The PQIP patient study is a multi-centre prospective cohort study which recruits patients undergoing major surgery. Patient provide informed consent and contribute baseline and outcome data from their perspective using a suite of patient-reported outcome tools. Research and clinical staff complete data on patient risk factors and outcomes in-hospital, including two measures of complications. Longer-term outcome data are collected through patient feedback and linkage to national administrative datasets (mortality and readmissions). As well as providing a uniquely granular dataset for research, PQIP provides feedback to participating sites on their compliance with evidence-based processes and their patients’ outcomes, with the aim of supporting local quality improvement. Ethics and dissemination Ethical approval has been granted by the Health Research Authority in the UK. Dissemination of interim findings (non-inferential) will form a part of the improvement methodology and will be provided to participating centres at regular intervals, including near-real time feedback of key process measures. Inferential analyses will be published in the peer-reviewed literature, supported by a comprehensive multi-modal communications strategy including to patients, policy makers and academic audiences as well as clinicians.

The COVID-19 pandemic significantly changed patterns of human interaction, including in the educational sector, which was forced to transform relationships among students, families, and the academic community. The present study sought to establish the interrelationships between performance on cognitive tests during the preschool stage and the perceptions of parents about remote education in school children during the pandemic. The study included 100 preschool children from socially vulnerable sectors who underwent remote and distance learning in 2020 and 2021. The reliability of the applied questionnaire was determined through a confirmatory factor analysis. A structural equation model was constructed to determine the perceptions of parents about remote education based on cognitive performance during the preschool stage. The model fit yielded favorable results for predictive variables (χ2 = 7.734, DF = 9 [p = 0.561], the comparative goodness-of-fit index [CFI] = 1.000, root mean square error of approximation [RMSEA] = 0.000, standardized mean square residual [SRMR] = 0.069), and executive function (χ2 = 3.711, DF = 5 [p > 0.592], CFI = 1.000, RMSEA = 0.000, SRMR = 0.039) as latent variables that affected parents’ perceptions. These results indicate that parents’ perceptions of remote education are mediated by predictive aspects of learning and executive function during the preschool stage.

Background The Tommy’s Clinical Decision Support Tool is a web-based application that is used to assess risk of preterm birth and placental dysfunction. Utilising validated algorithms and rule engines, which are more accurate than current checklist methods, the Tool instantly recommends best evidenced-based care pathways. This personalisation of assessment and decision support could reduce preterm birth and stillbirth, whilst also addressing variation in care. This study aimed to develop the intervention and assess feasibility of implementation in four NHS maternity services to inform a planned cluster randomised controlled trial. We aimed to investigate barriers and facilitators to implementation; reach (whether particular groups are excluded and why), fidelity (degree to which the intervention is delivered as intended), and unintended consequences. Methods The NASSS framework (Non-adoption or Abandonment of technology by individuals and difficulties achieving Scale-up, Spread and Sustainability) informed analysis. We used online surveys, semi-structured interviews and focus groups to investigate maternity service user and healthcare professional (HCP) experience. Results One thousand one hundred eighty-one maternity service users and 112 HCPs participated, completing 1260 online surveys, 8 focus groups and 29 semi-structured interviews (women: n = 24; HCPs: n = 23). Overall, the Tool appears acceptable and easy-to-use for both pregnant and HCP users, although the burden of introducing a novel intervention within an already overstretched service was identified as a potential barrier to successful implementation. Findings influenced developments of the device and implementation strategy ahead of the trial. Lessons learned highlighted the importance of: availability of the Tool to guide care for all, including pregnant users unable, or choosing not to engage with it; top-level and multidisciplinary buy-in; dedicated resources; preparation for transitional period; local champions across professions and settings; clarity in purpose, scope, potential benefits and evidence-base; mitigation of double data entry; IT infrastructure optimisation; flexibility in training and accessibility of implementation resources. Further refinements will include non-English translation of the pregnant user interface. Conclusions Tommy’s Tool has the potential to make providing optimal maternity care easier for health professionals, which could reduce variation in care and ultimately improve outcomes. This study gave us the opportunity to evaluate implementation processes and identify potential barriers to successful implementation. By addressing these barriers, ahead of the trial, we have maximised the chance of the trial results being conclusive. Trial registration this study was prospectively registered on ISRCTN:ID13498237, on 31/01/2022.

Desmoid tumors represent a rare entity of monoclonal origin characterized by locally aggressive behavior and inability to metastasize. Most cases present in a sporadic pattern and are characterized by a mutation in the CTNNB1 gene; while 5–15% show a hereditary pattern associated with APC gene mutation, both resulting in abnormal β-catenin accumulation within the cell. The most common sites of presentation are the extremities and the thoracic wall, whereas FAP associated cases present intra-abdominally or in the abdominal wall. Histopathological diagnosis is mandatory, and evaluation is guided with imaging studies ranging from ultrasound, computed tomography or magnetic resonance. Current approaches advocate for an initial active surveillance period due to the stabilization and even regression capacity of desmoid tumors. For progressive, symptomatic, or disabling cases, systemic treatment, radiotherapy or surgery may be used. This is a narrative review of this uncommon disease; we present current knowledge about molecular pathogenesis, diagnosis and treatment.

This study investigated how different remote sensing techniques can be combined to accurately monitor mangroves. In this paper, we present a framework to use drone imagery to calculate correction factors which can improve the accuracy of satellite-based mangrove extent. We focus on semi-arid dwarf mangroves of Baja California Sur, Mexico, where the mangroves tend to be stunted in height and found in small patches, as well as larger forests. Using a DJI Phantom 4 Pro, we imaged mangroves and labeled the extent by manual classification in QGIS. Using ArcGIS, we compared satellite-based mangrove extent maps from Global Mangrove Watch (GMW) in 2016 and Mexico’s national government agency (National Commission for the Knowledge and Use of Biodiversity, CONABIO) in 2015, with extent maps generated from in situ drone studies in 2018 and 2019. We found that satellite-based extent maps generally overestimated mangrove coverage compared to that of drone-based maps. To correct this overestimation, we developed a method to derive correction factors for GMW mangrove extent. These correction factors correspond to specific pixel patterns generated from a convolution analysis and mangrove coverage defined from drone imagery. We validated our model by using repeated k-fold cross-validation, producing an accuracy of 98.3% ± 2.1%. Overall, drones and satellites are complementary tools, and the rise of machine learning can help stakeholders further leverage the strengths of the two tools, to better monitor mangroves for local, national, and international management.

Group-IV color centers in diamond are a promising light-matter interface for quantum networking devices. The negatively charged tin-vacancy center (SnV) is particularly interesting, as its large spin-orbit coupling offers strong protection against phonon dephasing and robust cyclicity of its optical transitions toward spin-photon-entanglement schemes. Here, we demonstrate multiaxis coherent control of the SnV spin qubit via an all-optical stimulated Raman drive between the ground and excited states. We use coherent population trapping and optically driven electronic spin resonance to confirm coherent access to the qubit at 1.7 K and obtain spin Rabi oscillations at a rate of Ω/2π=19.0(1) MHz. All-optical Ramsey interferometry reveals a spin dephasing time of T₂^(*)=1.3(3) μs, and four-pulse dynamical decoupling already extends the spin-coherence time to T₂=0.30(8) ms. Combined with transform-limited photons and integration into photonic nanostructures, our results make the SnV a competitive spin-photon building block for quantum networks.

Abstract The energetic demands of proliferating cells during tumorigenesis require close coordination between the cell cycle and metabolism. While CDK4 is known for its role in cell proliferation, its metabolic function in cancer, particularly in triple-negative breast cancer (TNBC), remains unclear. Our study, using genetic and pharmacological approaches, reveals that CDK4 inactivation only modestly impacts TNBC cell proliferation and tumor formation. Notably, CDK4 depletion or long-term CDK4/6 inhibition confers resistance to apoptosis in TNBC cells. Mechanistically, CDK4 enhances mitochondria-endoplasmic reticulum contact (MERCs) formation, promoting mitochondrial fission and ER-mitochondrial calcium signaling, which are crucial for TNBC metabolic flexibility. Phosphoproteomic analysis identified CDK4’s role in regulating PKA activity at MERCs. In this work, we highlight CDK4’s role in mitochondrial apoptosis inhibition and suggest that targeting MERCs-associated metabolic shifts could enhance TNBC therapy.

Isocitrate dehydrogenase 1 and 2 (IDH1 and IDH2) are key metabolic enzymes that are mutated in a variety of cancers to confer a gain-of-function activity resulting in the accumulation of an oncometabolite, D-2-hydroxyglutarate (2-HG). Accumulation of 2-HG can result in epigenetic dysregulation and a block in cellular differentiation, suggesting these mutations play a role in neoplasia. Based on its potential as a cancer target, a number of small molecule inhibitors have been developed to specifically inhibit mutant forms of IDH (mIDH1 and mIDH2). We present a comprehensive suite of in vitro preclinical drug development assays that can be used as a tool-box to identify lead compounds for mIDH drug discovery programs, as well as what we believe is the most comprehensive publically available dataset on the top mIDH inhibitors. This involved biochemical, cell-based, and tier-one ADME techniques.