SummaryBackgroundThe management of people with multiple chronic conditions challenges health-care systems designed around single conditions. There is international consensus that care for multimorbidity should be patient-centred, focus on quality of life, and promote self-management towards agreed goals. However, there is little evidence about the effectiveness of this approach. Our hypothesis was that the patient-centred, so-called 3D approach (based on dimensions of health, depression, and drugs) for patients with multimorbidity would improve their health-related quality of life, which is the ultimate aim of the 3D intervention.MethodsWe did this pragmatic cluster-randomised trial in general practices in England and Scotland. Practices were randomly allocated to continue usual care (17 practices) or to provide 6-monthly comprehensive 3D reviews, incorporating patient-centred strategies that reflected international consensus on best care (16 practices). Randomisation was computer-generated, stratified by area, and minimised by practice deprivation and list size. Adults with three or more chronic conditions were recruited. The primary outcome was quality of life (assessed with EQ-5D-5L) after 15 months' follow-up. Participants were not masked to group assignment, but analysis of outcomes was blinded. We analysed the primary outcome in the intention-to-treat population, with missing data being multiply imputed. This trial is registered as an International Standard Randomised Controlled Trial, number ISRCTN06180958.FindingsBetween May 20, 2015, and Dec 31, 2015, we recruited 1546 patients from 33 practices and randomly assigned them to receive the intervention (n=797) or usual care (n=749). In our intention-to-treat analysis, there was no difference between trial groups in the primary outcome of quality of life (adjusted difference in mean EQ-5D-5L 0·00, 95% CI −0·02 to 0·02; p=0·93). 78 patients died, and the deaths were not considered as related to the intervention.InterpretationTo our knowledge, this trial is the largest investigation of the international consensus about optimal management of multimorbidity. The 3D intervention did not improve patients' quality of life.FundingNational Institute for Health Research.

Predictions of marine ice-sheet behaviour require models that are able to robustly simulate grounding line migration. We present results of an intercomparison exercise for marine ice-sheet models. Verification is effected by comparison with approximate analytical solutions for flux across the grounding line using simplified geometrical configurations (no lateral variations, no effects of lateral buttressing). Unique steady state grounding line positions exist for ice sheets on a downward sloping bed, while hysteresis occurs across an overdeepened bed, and stable steady state grounding line positions only occur on the downward-sloping sections. Models based on the shallow ice approximation, which does not resolve extensional stresses, do not reproduce the approximate analytical results unless appropriate parameterizations for ice flux are imposed at the grounding line. For extensional-stress resolving "shelfy stream" models, differences between model results were mainly due to the choice of spatial discretization. Moving grid methods were found to be the most accurate at capturing grounding line evolution, since they track the grounding line explicitly. Adaptive mesh refinement can further improve accuracy, including fixed grid models that generally perform poorly at coarse resolution. Fixed grid models, with nested grid representations of the grounding line, are able to generate accurate steady state positions, but can be inaccurate over transients. Only one full-Stokes model was included in the intercomparison, and consequently the accuracy of shelfy stream models as approximations of full-Stokes models remains to be determined in detail, especially during transients

Objective: Supporting patients' self care could have a major effect on the management of long-term conditions, which has led to worldwide interest in effective self care interventions. In England, self care support is being developed through the ''Expert Patients Programme'', which provides lay-led generic courses to improve patients' self care skills. However, the clinical and cost effectiveness of such courses remains unclear. Methods: Two-arm pragmatic randomised controlled trial design with waiting list control in community settings in England. 629 patients with a wide range of self-defined long-term conditions were studied. The lay-led self care support group involved 6-weekly sessions to teach self care skills. Primary outcomes were self-efficacy, reported energy and routine health services utilisation at 6 months. A cost-effectiveness analysis was also conducted. Results: Patients receiving immediate course access reported considerably greater self-efficacy and energy at 6-month follow-up, but reported no statistically significant reductions in routine health services utilisation over the same time period. The cost-effectiveness analysis showed that patients receiving immediate course access reported considerably greater health related quality of life, and a small reduction in costs. If a quality adjusted life year was valued at £20 000 ($39 191; J30 282), there was a 70% probability that the intervention was cost effective. Conclusions: Lay-led self care support groups are effective in improving self-efficacy and energy levels among patients with long-term conditions, and are likely to be cost effective over 6 months at conventional values of a decision-maker's willingness to pay. They may be a useful addition to current services in the management of long-term conditions.

Aggressive neuroendocrine lung cancers, including small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC), represent an understudied tumor subset that accounts for approximately 40,000 new lung cancer cases per year in the United States. No targeted therapy exists for these tumors. We determined that achaetescute homolog 1 (ASCL1), a transcription factor required for proper development of pulmonary neuroendocrine cells, is essential for the survival of a majority of lung cancers (both SCLC and NSCLC) with neuroendocrine features. By combining whole-genome microarray expression analysis performed on lung cancer cell lines with ChIPSeq data designed to identify conserved transcriptional targets of ASCL1, we discovered an ASCL1 target 72-gene expression signature that (i) identifies neuroendocrine differentiation in NSCLC cell lines, (ii) is predictive of poor prognosis in resected NSCLC specimens from three datasets, and (iii) represents novel "druggable" targets. Among these druggable targets is B-cell CLL/lymphoma 2, which when pharmacologically inhibited stops ASCL1-dependent tumor growth in vitro and in vivo and represents a proof-of-principle ASCL1 downstream target gene. Analysis of downstream targets of ASCL1 represents an important advance in the development of targeted therapy for the neuroendocrine class of lung cancers, providing a significant step forward in the understanding and therapeutic targeting of the molecular vulnerabilities of neuroendocrine lung cancer.ASCL1 transcriptome | target discovery | personalized therapy G ene expression signatures from large cohorts of lung tumors suggest that cancers with neuroendocrine features appear in ∼10% of pathologically diagnosed non-small cell lung cancers (NSCLCs) (1, 2), whereas small cell lung cancers (SCLCs) compose 15-20% of all lung cancer cases (3). In the United States, this represents nearly 40,000 patients per year presenting with a high-grade neuroendocrine lung tumor. Molecular and functional characterization of these aggressive tumors, along with the development of relevant preclinical models, is needed to rationally develop and test new targeted therapies.A highly expressed gene in the class of neuroendocrine lung cancers is the lineage-specific transcription factor achaete-scute homolog 1 (ASCL1) (4, 5). ASCL1 is required to establish the lineage of pulmonary neuroendocrine cells (6) and is necessary for the continued survival of SCLCs (7, 8). ASCL1's appearance in an NSCLC subset, neuroendocrine NSCLC (NE-NSCLC), is a recent and unexplained finding (9), and, importantly, its role as a potential lineage oncogene in lung tumors has been heretofore unexplored. The lineage addiction hypothesis in cancer suggests that certain tumors arise from dysregulation of genes involved in normal development. Hijacking these genes, which are involved in numerous facets of growth, cell division, and differentiation, provides a budding precancerous cell with the framework within which to progress to full tumorigenicity. The transcription factors...

Background Distress is an expected emotional response to a negative life event. Experiences common in later life may trigger distress such as bereavement or loss of physical mobility. Distress is considered to be distinct to anxiety and/or depression and is not diagnostically labelled as a mental health problem. Older adults will often manage their own distress. Previous literature has focused on how younger adults self-manage mental health problems, however little research has explored the self-management strategies used by older people. There is a need to clarify the role of primary care in the context of distressed older adults who may consult healthcare services. This study seeks to address these gaps through qualitative methods. Methods This study was approved by Keele University's ethical review panel. Older adults who selfidentified as distressed were recruited from community groups in North Staffordshire, England. Data were generated through semi-structured interviews and analysed thematically using constant comparison methods. A patient and public involvement and engagement group contributed to development of the research questions and methods, and offered their perspectives on the findings. Results Data saturation was achieved after 18 interviews. Key themes were: experiences of distress, actions taken, help-seeking from healthcare services and perceptions of treatments offered in primary care. Various forms of loss contributed to participants' distress. Participants initiated their own selfmanagement strategies which included: pursuing independent activities, seeking social support and attending community groups and church. Five participants reported having consulted a GP when distressed but described a lack of acceptable treatments offered. Conclusions To support older adults who are distressed, healthcare professionals in primary care should consider exploring how patients currently manage their mood problems, provide a broad range of information about potential management options and consider sign-posting older adults to community resources.

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Abstract. Earlier large-scale Greenland ice sheet sea-level projections (e.g. those run during the ice2sea and SeaRISE initiatives) have shown that ice sheet initial conditions have a large effect on the projections and give rise to important uncertainties. The goal of this initMIP-Greenland intercomparison exercise is to compare, evaluate, and improve the initialisation techniques used in the ice sheet modelling community and to estimate the associated uncertainties in modelled mass changes. initMIP-Greenland is the first in a series of ice sheet model intercomparison activities within ISMIP6 (the Ice Sheet Model Intercomparison Project for CMIP6), which is the primary activity within the Coupled Model Intercomparison Project Phase 6 (CMIP6) focusing on the ice sheets. Two experiments for the large-scale Greenland ice sheet have been designed to allow intercomparison between participating models of (1) the initial present-day state of the ice sheet and (2) the response in two idealised forward experiments. The forward experiments serve to evaluate the initialisation in terms of model drift (forward run without additional forcing) and in response to a large perturbation (prescribed surface mass balance anomaly); they should not be interpreted as sea-level projections. We present and discuss results that highlight the diversity of data sets, boundary conditions, and initialisation techniques used in the community to generate initial states of the Greenland ice sheet. We find good agreement across the ensemble for the dynamic response to surface mass balance changes in areas where the simulated ice sheets overlap but differences arising from the initial size of the ice sheet. The model drift in the control experiment is reduced for models that participated in earlier intercomparison exercises.

Abstract. The Greenland ice sheet is one of the largest contributors to global mean sea-level rise today and is expected to continue to lose mass as the Arctic continues to warm. The two predominant mass loss mechanisms are increased surface meltwater run-off and mass loss associated with the retreat of marine-terminating outlet glaciers. In this paper we use a large ensemble of Greenland ice sheet models forced by output from a representative subset of the Coupled Model Intercomparison Project (CMIP5) global climate models to project ice sheet changes and sea-level rise contributions over the 21st century. The simulations are part of the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6). We estimate the sea-level contribution together with uncertainties due to future climate forcing, ice sheet model formulations and ocean forcing for the two greenhouse gas concentration scenarios RCP8.5 and RCP2.6. The results indicate that the Greenland ice sheet will continue to lose mass in both scenarios until 2100, with contributions of 90±50 and 32±17 mm to sea-level rise for RCP8.5 and RCP2.6, respectively. The largest mass loss is expected from the south-west of Greenland, which is governed by surface mass balance changes, continuing what is already observed today. Because the contributions are calculated against an unforced control experiment, these numbers do not include any committed mass loss, i.e. mass loss that would occur over the coming century if the climate forcing remained constant. Under RCP8.5 forcing, ice sheet model uncertainty explains an ensemble spread of 40 mm, while climate model uncertainty and ocean forcing uncertainty account for a spread of 36 and 19 mm, respectively. Apart from those formally derived uncertainty ranges, the largest gap in our knowledge is about the physical understanding and implementation of the calving process, i.e. the interaction of the ice sheet with the ocean.