Everolimus after failure of one prior VEGF-targeted therapy in metastatic renal cell carcinoma : Final results of the MARC-2 trial

MARC-2, a prospective, multicenter phase IV trial, aimed to investigate clinical outcomes in patients with metastatic renal cell carcinoma (mRCC) treated with everolimus after failure of one initial vascular endothelial growth factor receptor tyrosine kinase inhibitor (VEGFR-TKI) therapy and to identify subgroups benefiting most, based on clinical characteristics and biomarkers. Patients with clear cell mRCC failing one initial VEGFR-TKI received everolimus until progression or unacceptable toxicity. Primary endpoint was 6-month progression-free survival rate (6moPFS). Secondary endpoints were overall response rate (ORR), PFS, overall survival (OS), and safety. Between 2011 and 2015, 63 patients were enrolled. Median age was 65.4 years (range 43.3-81.1). 6moPFS was 39.3% (95% confidence interval [CI], 27.0-51.3) overall, 54.4% (95% CI, 35.2-70.1) vs 23.7% (95% CI, 10.5-39.9) for patients aged ≥65 vs 25 vs ≤25 kg/m2. A Cox proportional hazards model confirmed a longer PFS for patients aged ≥65 years (hazard ratio [HR] 0.46; 95% CI, 0.26-0.80) and a longer OS for patients with BMI >25 kg/m2 (HR 0.36; 95% CI, 0.18-0.71). Median PFS and median OS were 3.8 months (95% CI, 3.2-6.2) and 16.8 months (95% CI, 14.3-24.3). ORR was 7.9% and disease control rate was 60.3%. No new safety signals emerged. Most common adverse events were stomatitis (31.7%), fatigue (31.7%), and anemia (30.2%). One patient died from treatment-related upper gastrointestinal hemorrhage. Everolimus remains a safe and effective treatment option for mRCC patients after one prior VEGFR-TKI therapy. Patients aged ≥65 years and patients with BMI >25 kg/m2 benefited most

Thrombospondin-2 and LDH Are Putative Predictive Biomarkers for Treatment with Everolimus in Second-Line Metastatic Clear Cell Renal Cell Carcinoma (MARC-2 Study)

There is an unmet need for predictive biomarkers in metastatic renal cell carcinoma (mRCC) therapy. The phase IV MARC-2 trial searched for predictive blood biomarkers in patients with predominant clear cell mRCC who benefit from second-line treatment with everolimus. In an exploratory approach, potential biomarkers were assessed employing proteomics, ELISA, and polymorphism analyses. Lower levels of angiogenesis-related protein thrombospondin-2 (TSP-2) at baseline (≤665 parts per billion, ppb) identified therapy responders with longer median progressionfree survival (PFS; ≤665 ppb at baseline: 6.9 months vs. 1.8, p = 0.005). Responders had higher lactate dehydrogenase (LDH) levels in serum two weeks after therapy initiation (>27.14 nmol/L), associated with a longer median PFS (3.8 months vs. 2.2, p = 0.013) and improved overall survival (OS; 31.0 months vs. 14.0 months, p < 0.001). Baseline TSP-2 levels had a stronger relation to PFS (HR 0.36, p = 0.008) than baseline patient parameters, including IMDC score. Increased serum LDH levels two weeks after therapy initiation were the best predictor for OS (HR 0.21, p < 0.001). mTOR polymorphisms appeared to be associated with therapy response but were not significant. Hence, we identified TSP-2 and LDH as promising predictive biomarkers for therapy response on everolimus after failure of one VEGF-targeted therapy in patients with clear cell mRCC

What is the importance of climate model bias when projecting the impacts of climate change on land surface processes?

Regional climate change impact (CCI) studies have widely involved downscaling and bias correcting (BC) global climate model (GCM)-projected climate for driving land surface models. However, BC may cause uncertainties in projecting hydrologic and biogeochemical responses to future climate due to the impaired spatiotemporal covariance of climate variables and a breakdown of physical conservation principles. Here we quantify the impact of BC on simulated climate-driven changes in water variables (evapotranspiration (ET), runoff, snow water equivalent (SWE), and water demand for irrigation), crop yield, biogenic volatile organic compounds (BVOC), nitric oxide (NO) emissions, and dissolved inorganic nitrogen (DIN) export over the Pacific Northwest (PNW) region. We also quantify the impacts on net primary production (NPP) over a small watershed in the region (HJ-Andrews). Simulation results from the coupled ECHAM5–MPI-OM model with A1B emission scenario were first dynamically downscaled to 12 km resolution with the WRF model. Then a quantile-mapping-based statistical downscaling model was used to downscale them into 1/16° resolution daily climate data over historical and future periods. Two climate data series were generated, with bias correction (BC) and without bias correction (NBC). Impact models were then applied to estimate hydrologic and biogeochemical responses to both BC and NBC meteorological data sets. These impact models include a macroscale hydrologic model (VIC), a coupled cropping system model (VIC-CropSyst), an ecohydrological model (RHESSys), a biogenic emissions model (MEGAN), and a nutrient export model (Global-NEWS). Results demonstrate that the BC and NBC climate data provide consistent estimates of the climate-driven changes in water fluxes (ET, runoff, and water demand), VOCs (isoprene and monoterpenes) and NO emissions, mean crop yield, and river DIN export over the PNW domain. However, significant differences rise from projected SWE, crop yield from dry lands, and HJ-Andrews's ET between BC and NBC data. Even though BC post-processing has no significant impacts on most of the studied variables when taking PNW as a whole, their effects have large spatial variations and some local areas are substantially influenced. In addition, there are months during which BC and NBC post-processing produces significant differences in projected changes, such as summer runoff. Factor-controlled simulations indicate that BC post-processing of precipitation and temperature both substantially contribute to these differences at regional scales. We conclude that there are trade-offs between using BC climate data for offline CCI studies versus directly modeled climate data. These trade-offs should be considered when designing integrated modeling frameworks for specific applications; for example, BC may be more important when considering impacts on reservoir operations in mountainous watersheds than when investigating impacts on biogenic emissions and air quality, for which VOCs are a primary indicator

О перспективе извлечения йода из продукта утилизации окислителя ракетного топлива

Crop models are essential tools for assessing the threat of climate change to local and global food production. Present models used to predict wheat grain yield are highly uncertain when simulating how crops respond to temperature. Here we systematically tested 30 different wheat crop models of the Agricultural Model Intercomparison and Improvement Project against field experiments in which growing season mean temperatures ranged from 15 degrees C to 32 degrees C, including experiments with artificial heating. Many models simulated yields well, but were less accurate at higher temperatures. The model ensemble median was consistently more accurate in simulating the crop temperature response than any single model, regardless of the input information used. Extrapolating the model ensemble temperature response indicates that warming is already slowing yield gains at a majority of wheat-growing locations. Global wheat production is estimated to fall by 6% for each degree C of further temperature increase and become more variable over space and time

The International Heat Stress Genotype Experiment for modeling wheat response to heat: field experiments and AgMIP-Wheat multi-model simulations

The data set contains a portion of the International Heat Stress Genotype Experiment (IHSGE) data used in the AgMIP-Wheat project to analyze the uncertainty of 30 wheat crop models and quantify the impact of heat on global wheat yield productivity. It includes two spring wheat cultivars grown during two consecutive winter cropping cycles at hot, irrigated, and low latitude sites in Mexico (Ciudad Obregon and Tlaltizapan), Egypt (Aswan), India (Dharwar), the Sudan (Wad Medani), and Bangladesh (Dinajpur). Experiments in Mexico included normal (November-December) and late (January-March) sowing dates. Data include local daily weather data, soil characteristics and initial soil conditions, crop measurements (anthesis and maturity dates, anthesis and final total above ground biomass, final grain yields and yields components), and cultivar information. Simulations include both daily in-season and end-of-season results from 30 wheat models

Assessing the danger of self-sustained HIV epidemics in heterosexuals by population based phylogenetic cluster analysis.

Assessing the danger of transition of HIV transmission from a concentrated to a generalized epidemic is of major importance for public health. In this study, we develop a phylogeny-based statistical approach to address this question. As a case study, we use this to investigate the trends and determinants of HIV transmission among Swiss heterosexuals. We extract the corresponding transmission clusters from a phylogenetic tree. To capture the incomplete sampling, the delayed introduction of imported infections to Switzerland, and potential factors associated with basic reproductive number R0, we extend the branching process model to infer transmission parameters. Overall, the R0 is estimated to be 0.44 (95%-confidence interval 0.42-0.46) and it is decreasing by 11% per 10 years (4%-17%). Our findings indicate rather diminishing HIV transmission among Swiss heterosexuals far below the epidemic threshold. Generally, our approach allows to assess the danger of self-sustained epidemics from any viral sequence data

A Generic Bio-Economic Farm Model for Environmental and Economic Assessment of Agricultural Systems

Bio-economic farm models are tools to evaluate ex-post or to assess ex-ante the impact of policy and technology change on agriculture, economics and environment. Recently, various BEFMs have been developed, often for one purpose or location, but hardly any of these models are re-used later for other purposes or locations. The Farm System Simulator (FSSIM) provides a generic framework enabling the application of BEFMs under various situations and for different purposes (generating supply response functions and detailed regional or farm type assessments). FSSIM is set up as a component-based framework with components representing farmer objectives, risk, calibration, policies, current activities, alternative activities and different types of activities (e.g., annual and perennial cropping and livestock). The generic nature of FSSIM is evaluated using five criteria by examining its applications. FSSIM has been applied for different climate zones and soil types (criterion 1) and to a range of different farm types (criterion 2) with different specializations, intensities and sizes. In most applications FSSIM has been used to assess the effects of policy changes and in two applications to assess the impact of technological innovations (criterion 3). In the various applications, different data sources, level of detail (e.g., criterion 4) and model configurations have been used. FSSIM has been linked to an economic and several biophysical models (criterion 5). The model is available for applications to other conditions and research issues, and it is open to be further tested and to be extended with new components, indicators or linkages to other models

Incident Hepatitis C Virus Infections in the Swiss HIV Cohort Study : changes in treatment uptake and outcomes between 1991 and 2013

Background: The hepatitis C virus (HCV) epidemic is evolving rapidly in patients infected with human immunodeficiency virus (HIV). We aimed to describe changes in treatment uptake and outcomes of incident HCV infections before and after 2006, the time-point at which major changes in HCV epidemic became apparent. Methods.  We included all adults with an incident HCV infection before June 2012 in the Swiss HIV Cohort Study, a prospective nationwide representative cohort of individuals infected with HIV. We assessed the following outcomes by time period: the proportion of patients starting an HCV therapy, the proportion of treated patients achieving a sustained virological response (SVR), and the proportion of patients with persistent HCV infection during follow-up. Results.  Of 193 patients with an HCV seroconversion, 106 were diagnosed before and 87 after January 2006. The proportion of men who have sex with men increased from 24% before to 85% after 2006 (P &lt; .001). Hepatitis C virus treatment uptake increased from 33% before 2006 to 77% after 2006 (P &lt; .001). Treatment was started during early infection in 22% of patients before and 91% after 2006 (P &lt; .001). An SVR was achieved in 78% and 29% (P = .01) of patients treated during early and chronic HCV infection. The probability of having a detectable viral load 5 years after diagnosis was 0.67 (95% confidence interval [CI], 0.58-0.77) in the group diagnosed before 2006 and 0.24 (95% CI, 0.16-0.35) in the other group (P &lt; .001). Conclusions. In recent years, increased uptake and earlier initiation of HCV therapy among patients with incident infections significantly reduced the proportion of patients with replicating HCV