Morbidität und Mortalität der HIV-Infektion

Zusammenfassung: Morbidität und Mortalität von HIV-infizierten Menschen haben seit 1996 aufgrund der antiretroviralen Kombinationstherapie (cART) dramatisch abgenommen. Die HIV-Infektion wurde somit zu einer chronischen, ambulant behandelbaren und meist asymptomatischen Krankheit mit praktisch normaler Lebenserwartung. Ein Hauptgrund der verbleibenden Morbidität und Sterblichkeit ist, dass die HIV-Infektion in etwa 20% der Fälle spät diagnostiziert bzw. therapiert wird. Oft liegt zu diesem Zeitpunkt die CD4-Zellzahl bereits unter der Schwelle von 200Zellen/µl und/oder AIDS-definierende Krankheiten haben sich manifestiert. Weitere Gründe für die verbleibende Morbidität und Mortalität sind Komorbiditäten, insbesondere die Koinfektion mit einer viralen Hepatitis und Tumoren bei älteren Patienten. Durch die verbesserte Prognose nimmt das Alter HIV-infizierter Menschen zu. Dies bedeutet aufgrund von Komorbiditäten und sozioökonomischen Kosten eine erhebliche Herausforderung für die Zukunf

The metastatic potential of seminomatous germ cell tumours is associated with a specific microRNA pattern

Background Seminomatous germ cell tumours (SGCT) are the most frequent malignancy in young men. Reliable prognostic biomarkers for the prediction of metastasis at diagnosis and the risk of relapse in clinical stage I (CSI) are lacking. Adjuvant therapies carry a risk of overtreatment, whereas salvage therapies have a risk of high toxicities. Thus, the identification of reliable prognostic biomarkers is highly desirable to identify patients who will benefit from early adjuvant treatment. MicroRNAs (miRNAs) regulate tumour development and progression, and their potential as biomarkers has already been proven in a variety of malignancies. Objectives The aim of our study was to define a specific miRNA expression pattern that discriminates metastatic from non‐metastatic primary SGCT. Materials and methods Total RNA was isolated from 24 formalin‐fixed paraffin‐embedded (FFPE) primary SGCT tumours (10 non‐metastatic, five metachronously and nine synchronously metastatic) and from 10 normal testicular tissue samples. Microarray analysis was performed for global miRNA expression profiling. The results were validated by quantitative real‐time polymerase chain reaction (qRT‐PCR). Statistical analysis was performed using SPSS. Results Microarray analyses revealed a specific miRNA pattern that distinguishes metastatic from non‐metastatic SGCT. Sixty‐three miRNAs were differentially expressed in metastatic compared to non‐metastatic tumours (P < .01). Microarray results were confirmed by qRT‐PCR for three out of five selected miRNAs (miR‐29c‐5p, miR‐506‐3p and miR‐371a‐5p; P < .05). All five miRNAs (miR‐29c‐5p, miR‐506‐3p, miR‐1307‐5p, miR‐371a‐5p and miR‐371a‐3p) showed differential expression between tumour and normal tissues (P < .05). Conclusion Metastatic primary SGCTs are characterized by a specific miRNA expression pattern. Therefore, specific miRNAs could represent a new tool to predict the metastatic potential in SGCT patients

miRNA Expression Characterizes Histological Subtypes and Metastasis in Penile Squamous Cell Carcinoma

Although microRNAs are described as promising biomarkers in many tumor types, little is known about their role in PSCC. Thus, we attempted to identify miRNAs involved in tumor development and metastasis in distinct histological subtypes considering the impact of HPV infection. In a first step, microarray analyses were performed on RNA from formalin-fixed, paraffin-embedded tumor (22), and normal (8) tissue samples. Microarray data were validated for selected miRNAs by qRT-PCR on an enlarged cohort, including 27 tumor and 18 normal tissues. We found 876 significantly differentially expressed miRNAs (p ≤ 0.01) between HPV-positive and HPV-negative tumor samples by microarray analysis. Although no significant differences were detected between normal and tumor tissue in the whole cohort, specific expression patterns occurred in distinct histological subtypes, such as HPV-negative usual PSCC (95 differentially expressed miRNAs, p ≤ 0.05) and HPV-positive basaloid/warty subtypes (247 differentially expressed miRNAs, p ≤ 0.05). Selected miRNAs were confirmed by qRT-PCR. Furthermore, microarray data revealed 118 miRNAs (p ≤ 0.01) that were significantly differentially expressed in metastatic versus non-metastatic usual PSCC. The lower expression levels for miR-137 and miR-328-3p in metastatic usual PSCC were validated by qRT-PCR. The results of this study confirmed that specific miRNAs could serve as potential diagnostic and prognostic markers in single PSCC subtypes and are associated with HPV-dependent pathways

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

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

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

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

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