Harmondunlap9655

In 2008, Vian reported an increasing interest in understanding how corruption affects healthcare outcomes and asked what could be done to combat corruption in the health sector. Eleven years later, corruption is seen as a heterogeneous mix of activity, extensive and expensive in terms of loss of productivity, increasing inequity and costs, but with few examples of programmes that have successfully tackled corruption in low-income or middle-income countries. The commitment, by multilateral organisations and many governments to the Sustainable Development Goals and Universal Health Coverage has renewed an interest to find ways to tackle corruption within health systems. These efforts must, however, begin with a critical assessment of the existing theoretical models and approaches that have underpinned action in the health sector in the past and an assessment of the potential of innovations from anticorruption work developed in sectors other than health. To that end, this paper maps the key debates and theoretical frameworks that have dominated research on corruption in health. It examines their limitations, the blind spots that they create in terms of the questions asked, and the capacity for research to take account of contextual factors that drive practice. It draws on new work from heterodox economics which seeks to target anticorruption interventions at practices that have high impact and which are politically and economically feasible to address. We consider how such approaches can be adopted into health systems and what new questions need to be addressed by researchers to support the development of sustainable solutions to corruption. We present a short case study from Bangladesh to show how such an approach reveals new perspectives on actors and drivers of corruption practice. We conclude by considering the most important areas for research and policy.This paper introduces a framework for conducting and disseminating mixed methods research on positive outlier countries that successfully improved their health outcomes and systems. We provide guidance on identifying exemplar countries, assembling multidisciplinary teams, collecting and synthesising pre-existing evidence, undertaking qualitative and quantitative analyses, and preparing dissemination products for various target audiences. Through a range of ongoing research studies, we illustrate application of each step of the framework while highlighting key considerations and lessons learnt. We hope uptake of this comprehensive framework by diverse stakeholders will increase the availability and utilisation of rigorous and comparable insights from global health success stories.

In recognition of our increasingly globalised world, global health is now a required component of the medical school curriculum in the UK. We review the current provision of global health education (GHE) in UK medical schools to identify gaps in compulsory teaching.

We conducted a review of the literature to inform a two-part electronic survey of global health compulsory teaching, optional teaching and pre-elective training. Surveys were sent to all 33 UK medical schools for completion by the faculty lead on global health and the nominated final year student representative.

Surveys were returned by 29 (88%) medical school faculty and 15 (45%) medical student representatives; 24 (83%) faculty and 10 (67%) students reported including GHE in the core curriculum; however, there was wide variation in the learning outcomes covered. On average 75% of faculty and 82% of students reported covering recommended global health themes 'global burden of disease', 'socioeconomic and environmental determinants of healthmprove access to fundamental GHE for all medical students.Muscle-invasive bladder cancer (MIBC) frequently harbors mutations in the CDKN1A gene, which encodes the tumor suppressor protein p21, with the majority of alterations truncating the peptide. The effect of these mutations is poorly understood. We hypothesized that after DNA-damaging events, cells deficient in p21 would be unable to halt the cell cycle and efficiently repair DNA damage, thus proceeding down the apoptotic pathway. We used synthetic CRISPR guide RNAs to ablate the whole peptide (sg12, targeting the 12th amino acid) or the C-terminal proliferating cell nuclear antigen (PCNA)-binding domain (sg109) to mimic different p21-truncating mutations compared with a negative control (sgGFP) in bladder cancer cell lines. Loss of detectable p21 and a stable truncated p21 peptide were identified in sg12 and sg109 single-cell clones, respectively. We found that p21-deficient cells (sg12) were sensitized to cisplatin, while cells harboring distally truncated p21 (sg12 clones) demonstrated enhanced cisplatin resistance. p21-deficient sg12 clones demonstrated less repair of DNA-platinum adducts and increased γ-H2AX foci after cisplatin exposure, suggesting there was persistent DNA damage after p21 loss. p21-deficient sg12 clones were also unable to prevent the activation of CDK1 after DNA damage, and therefore, continued through the cell cycle, resulting in replication fork collapse, potentially explaining the observed cisplatin sensitization. AT7867 clinical trial sg109 clones were neither unable to sequester PCNA nor localize p21 to the nucleus after DNA damage, potentially explaining the chemoresistant phenotype. Our findings suggest that different CDKN1A truncations have different and perhaps disparate biology, and that there may be a duality of effect on cisplatin sensitivity depending on mutation context. IMPLICATIONS Some truncating CDKN1A mutations generate a retained peptide that may have neomorphic functions and affect cisplatin sensitivity in patients with bladder cancer.As the most complex organ of the human body, the brain is composed of diverse regions, each consisting of distinct cell types and their respective cellular interactions. Human brain development involves a finely tuned cascade of interactive events. These include spatiotemporal gene expression changes and dynamic alterations in cell-type composition. However, our understanding of this process is still largely incomplete owing to the difficulty of brain spatiotemporal transcriptome collection. In this study, we developed a tensor-based approach to impute gene expression on a transcriptome-wide level. After rigorous computational benchmarking, we applied our approach to infer missing data points in the widely used BrainSpan resource and completed the entire grid of spatiotemporal transcriptomics. Next, we conducted deconvolutional analyses to comprehensively characterize major cell-type dynamics across the entire BrainSpan resource to estimate the cellular temporal changes and distinct neocortical areas across development.