Evaluation of a high-resolution regional climate simulation over Greenland

A simulation of the 1991 summer has been performed over south Greenland with a coupled atmosphere–snow regional climate model (RCM) forced by the ECMWF re-analysis. The simulation is evaluated with in-situ coastal and ice-sheet atmospheric and glaciological observations. Modelled air temperature, specific humidity, wind speed and radiative fluxes are in good agreement with the available observations, although uncertainties in the radiative transfer scheme need further investigation to improve the model’s performance. In the sub-surface snow-ice model, surface albedo is calculated from the simulated snow grain shape and size, snow depth, meltwater accumulation, cloudiness and ice albedo. The use of snow metamorphism processes allows a realistic modelling of the temporal variations in the surface albedo during both melting periods and accumulation events. Concerning the surface albedo, the main finding is that an accurate albedo simulation during the melting season strongly depends on a proper initialization of the surface conditions which mainly result from winter accumulation processes. Furthermore, in a sensitivity experiment with a constant 0.8 albedo over the whole ice sheet, the average amount of melt decreased by more than 60%, which highlights the importance of a correctly simulated surface albedo. The use of this coupled atmosphere–snow RCM offers new perspectives in the study of the Greenland surface mass balance due to the represented feedback between the surface climate and the surface albedo, which is the most sensitive parameter in energy-balance-based ablation calculations.Peer reviewe

Automated cardiovascular magnetic resonance image analysis with fully convolutional networks

Background: Cardiovascular magnetic resonance (CMR) imaging is a standard imaging modality for assessing cardiovascular diseases (CVDs), the leading cause of death globally. CMR enables accurate quantification of the cardiac chamber volume, ejection fraction and myocardial mass, providing information for diagnosis and monitoring of CVDs. However, for years, clinicians have been relying on manual approaches for CMR image analysis, which is time consuming and prone to subjective errors. It is a major clinical challenge to automatically derive quantitative and clinically relevant information from CMR images. Methods: Deep neural networks have shown a great potential in image pattern recognition and segmentation for a variety of tasks. Here we demonstrate an automated analysis method for CMR images, which is based on a fully convolutional network (FCN). The network is trained and evaluated on a large-scale dataset from the UK Biobank, consisting of 4,875 subjects with 93,500 pixelwise annotated images. The performance of the method has been evaluated using a number of technical metrics, including the Dice metric, mean contour distance and Hausdorff distance, as well as clinically relevant measures, including left ventricle (LV) end-diastolic volume (LVEDV) and end-systolic volume (LVESV), LV mass (LVM); right ventricle (RV) end-diastolic volume (RVEDV) and end-systolic volume (RVESV). Results: By combining FCN with a large-scale annotated dataset, the proposed automated method achieves a high performance in segmenting the LV and RV on short-axis CMR images and the left atrium (LA) and right atrium (RA) on long-axis CMR images. On a short-axis image test set of 600 subjects, it achieves an average Dice metric of 0.94 for the LV cavity, 0.88 for the LV myocardium and 0.90 for the RV cavity. The mean absolute difference between automated measurement and manual measurement was 6.1 mL for LVEDV, 5.3 mL for LVESV, 6.9 gram for LVM, 8.5 mL for RVEDV and 7.2 mL for RVESV. On long-axis image test sets, the average Dice metric was 0.93 for the LA cavity (2-chamber view), 0.95 for the LA cavity (4-chamber view) and 0.96 for the RA cavity (4-chamber view). The performance is comparable to human inter-observer variability. Conclusions: We show that an automated method achieves a performance on par with human experts in analysing CMR images and deriving clinically relevant measures

Does Diabetes Accelerate the Progression of Aortic Stenosis through Enhanced Inflammatory Response within Aortic valves?

Diabetes predisposes to aortic stenosis (AS). We aimed to investigate if diabetes affects the expression of selected coagulation proteins and inflammatory markers in AS valves. Twenty patients with severe AS and concomitant type 2 diabetes mellitus (DM) and 40 well-matched patients without DM scheduled for valve replacement were recruited. Valvular tissue factor (TF), TF pathway inhibitor (TFPI), prothrombin, C-reactive protein (CRP) expression were evaluated by immunostaining and TF, prothrombin, and CRP transcripts were analyzed by real-time PCR. DM patients had elevated plasma CRP (9.2 [0.74–51.9] mg/l vs. 4.7 [0.59–23.14] mg/l, p = 0.009) and TF (293.06 [192.32–386.12] pg/ml vs. 140 [104.17–177.76] pg/ml, p = 0.003) compared to non-DM patients. In DM group, TF−, TFPI−, and prothrombin expression within valves was not related to demographics, body mass index, and concomitant diseases, whereas increased expression related to DM was found for CRP on both protein (2.87 [0.5–9]% vs. 0.94 [0–4]%, p = 0.01) and transcript levels (1.3 ± 0.61 vs. 0.22 ± 0.43, p = 0.009). CRP-positive areas were positively correlated with mRNA TF (r = 0.84, p = 0.036). Diabetes mellitus is associated with enhanced inflammation within AS valves, measured by CRP expression, which may contribute to faster AS progression

Extracellular volume quantification in isolated hypertension - changes at the detectable limits?

The funding source (British Heart Foundation and UK National Institute for Health Research) provided salaries for research training (FZ, TT, DS, SW), but had no role in study design, collection, analysis, interpretation, writing, or decisions with regard to publication. This work was undertaken at University College London Hospital, which received a proportion of funding from the UK Department of Health National Institute for Health Research Biomedical Research Centres funding scheme. We are grateful to King’s College London Laboratories for processing the collagen biomarker panel

The Role of B-cells and IgM Antibodies in Parasitemia, Anemia, and VSG Switching in Trypanosoma brucei–Infected Mice

African trypanosomes are extracellular parasitic protozoa, predominantly transmitted by the bite of the haematophagic tsetse fly. The main mechanism considered to mediate parasitemia control in a mammalian host is the continuous interaction between antibodies and the parasite surface, covered by variant-specific surface glycoproteins. Early experimental studies have shown that B-cell responses can be strongly protective but are limited by their VSG-specificity. We have used B-cell (µMT) and IgM-deficient (IgM−/−) mice to investigate the role of B-cells and IgM antibodies in parasitemia control and the in vivo induction of trypanosomiasis-associated anemia. These infection studies revealed that that the initial setting of peak levels of parasitemia in Trypanosoma brucei–infected µMT and IgM−/− mice occurred independent of the presence of B-cells. However, B-cells helped to periodically reduce circulating parasites levels and were required for long term survival, while IgM antibodies played only a limited role in this process. Infection-associated anemia, hypothesized to be mediated by B-cell responses, was induced during infection in µMT mice as well as in IgM−/− mice, and as such occurred independently from the infection-induced host antibody response. Antigenic variation, the main immune evasion mechanism of African trypanosomes, occurred independently from host antibody responses against the parasite's ever-changing antigenic glycoprotein coat. Collectively, these results demonstrated that in murine experimental T. brucei trypanosomiasis, B-cells were crucial for periodic peak parasitemia clearance, whereas parasite-induced IgM antibodies played only a limited role in the outcome of the infection

Blood Stage Malaria Vaccine Eliciting High Antigen-Specific Antibody Concentrations Confers No Protection to Young Children in Western Kenya

The antigen, falciparum malaria protein 1 (FMP1), represents the 42-kDa C-terminal fragment of merozoite surface protein-1 (MSP-1) of the 3D7 clone of P. falciparum. Formulated with AS02 (a proprietary Adjuvant System), it constitutes the FMP1/AS02 candidate malaria vaccine. We evaluated this vaccine's safety, immunogenicity, and efficacy in African children.A randomised, double-blind, Phase IIb, comparator-controlled trial.The trial was conducted in 13 field stations of one mile radii within Kombewa Division, Nyanza Province, Western Kenya, an area of holoendemic transmission of P. falciparum. We enrolled 400 children aged 12-47 months in general good health.Children were randomised in a 1ratio1 fashion to receive either FMP1/AS02 (50 microg) or Rabipur(R) rabies vaccine. Vaccinations were administered on a 0, 1, and 2 month schedule. The primary study endpoint was time to first clinical episode of P. falciparum malaria (temperature >/=37.5 degrees C with asexual parasitaemia of >/=50,000 parasites/microL of blood) occurring between 14 days and six months after a third dose. Case detection was both active and passive. Safety and immunogenicity were evaluated for eight months after first immunisations; vaccine efficacy (VE) was measured over a six-month period following third vaccinations.374 of 400 children received all three doses and completed six months of follow-up. FMP1/AS02 had a good safety profile and was well-tolerated but more reactogenic than the comparator. Geometric mean anti-MSP-1(42) antibody concentrations increased from1.3 microg/mL to 27.3 microg/mL in the FMP1/AS02 recipients, but were unchanged in controls. 97 children in the FMP1/AS02 group and 98 controls had a primary endpoint episode. Overall VE was 5.1% (95% CI: -26% to +28%; p-value = 0.7).FMP1/AS02 is not a promising candidate for further development as a monovalent malaria vaccine. Future MSP-1(42) vaccine development should focus on other formulations and antigen constructs.Clinicaltrials.gov NCT00223990

Specific Syndecan-1 Domains Regulate Mesenchymal Tumor Cell Adhesion, Motility and Migration

Malignant mesothelioma is an asbestos induced cancer that is difficult to diagnose. Several studies have combined biomarkers to improve mesothelioma diagnosis, but with moderate success, and there is a need for new mesothelioma biomarkers. The tumour is often resistant to treatment and most patients will survive less than a year. An indicator of patient survival is the tumours growth pattern, which in turn is influenced by expressed proteoglycans. In this thesis work, we aim to improve the possibilities to diagnose malignant mesothelioma by combining biomarkers and by identifying new ones. We also investigate tumour driving mechanisms with focus on one of these suggested biomarkers, the cell-bound proteoglycan syndecan-1. We were able to construct a diagnostic two-step model based on biomarkers in patient material. By implementing a cut-off level and thereafter focusing on unresolved patients we combined hyaluronan and N-ERC/mesothelin (paper I), which significantly increased the diagnostic accuracy for malignant mesothelioma. To further improve diagnosis, we used mass spectrometry to find new biomarkers. We identified and validated galectin-1, which was excellent in discriminating mesotheliomas from adenocarcinomas (paper II). In the same study, we were also the first to describe aldo-keto reductase 1B10 as a novel prognostic mesothelioma biomarker. Syndecan-1 has been indicated as a marker for carcinomas. In paper I we describe how higher levels of syndecan-1 indicate the presence of a carcinoma over a mesothelioma. This was verified in paper II when syndecan-1 was identified as downregulated in fluids from mesothelioma patients compared to lung cancer patients. Paper III and paper IV focus on this proteoglycan. Malignant cell lines transfected with syndecan-1 and various truncated forms of syndecan-1 affected adhesion and migration, which are key features of cancer invasion (paper III). The results showed a domain- and cell type specific effect on the cells’ motility. Regulating syndecan-1 levels and analysing the global gene expression of mesothelioma cells made it evident that this proteoglycan has a strong influence on transforming growth factor β signalling and several growth factor pathways (paper IV). Links to cell migration and proliferation were furthermore identified, along with glycosaminoglycan modifying enzymes. These results can shed light on the complex role of syndecan-1 in invasion and growth of malignant mesenchymal cells. Taken together, this thesis work describes a complement to conventional mesothelioma diagnosis and identifies novel biomarkers. Furthermore, the potential biomarker syndecan-1 was shown to have an effect on cell motility and proliferation. These results increase our understanding of this aggressive malignancy

Stepped care targeting psychological distress in head and neck and lung cancer patients: a randomized clinical trial

<p>Abstract</p> <p>Background</p> <p>Psychological distress is common in cancer survivors. Although there is some evidence on effectiveness of psychosocial care in distressed cancer patients, referral rate is low. Lack of adequate screening instruments in oncology settings and insufficient availability of traditional models of psychosocial care are the main barriers. A stepped care approach has the potential to improve the efficiency of psychosocial care. The aim of the study described herein is to evaluate efficacy of a stepped care strategy targeting psychological distress in cancer survivors.</p> <p>Methods/design</p> <p>The study is designed as a randomized clinical trial with 2 treatment arms: a stepped care intervention programme versus care as usual. Patients treated for head and neck cancer (HNC) or lung cancer (LC) are screened for distress using OncoQuest, a computerized touchscreen system. After stratification for tumour (HNC vs. LC) and stage (stage I/II vs. III/IV), 176 distressed patients are randomly assigned to the intervention or control group. Patients in the intervention group will follow a stepped care model with 4 evidence based steps: 1. Watchful waiting, 2. Guided self-help via Internet or a booklet, 3. Problem Solving Treatment administered by a specialized nurse, and 4. Specialized psychological intervention or antidepressant medication. In the control group, patients receive care as usual which most often is a single interview or referral to specialized intervention. Primary outcome is the Hospital Anxiety and Depression Scale (HADS). Secondary outcome measures are a clinical level of depression or anxiety (CIDI), quality of life (EQ-5D, EORTC QLQ-C30, QLQ-HN35, QLQ-LC13), patient satisfaction with care (EORTC QLQ-PATSAT), and costs (health care utilization and work loss (TIC-P and PRODISQ modules)). Outcomes are evaluated before and after intervention and at 3, 6, 9 and 12 months after intervention.</p> <p>Discussion</p> <p>Stepped care is a system of delivering and monitoring treatments, such that effective, yet least resource-intensive, treatment is delivered to patients first. The main aim of a stepped care approach is to simplify the patient pathway, provide access to more patients and to improve patient well-being and cost reduction by directing, where appropriate, patients to low cost (self-)management before high cost specialist services.</p> <p>Trial registration</p> <p>NTR1868</p