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Background: Clinical practice guidelines for patients with primary biliary cholangitis (PBC) have been recently revised and implemented for well-established response criteria to standard first-line ursodeoxycholic acid (UDCA) therapy at 12 months after treatment initiation for the early identification of high-risk patients with inadequate treatment responses who may require treatment modification. However, there are only very limited data concerning the real-world clinical management of patients with PBC in Germany. Objective: The aim of this retrospective multicenter study was to evaluate response rates to standard first-line UDCA therapy and subsequent Second-line treatment regimens in a large cohort of well-characterized patients with PBC from 10 independent hepatological referral centers in Germany prior to the introduction of obeticholic acid as a licensed second-line treatment option. Methods: Diagnostic confirmation of PBC, standard first-line UDCA treatment regimens and response rates at 12 months according to Paris-I, Paris-II, and Barcelona criteria, the follow-up cut-off alkaline phosphatase (ALP) ≤ 1.67 × upper limit of normal (ULN) and the normalization of bilirubin (bilirubin ≤ 1 × ULN) were retrospectively examined between June 1986 and March 2017. The management and hitherto applied second-line treatment regimens in patients with an inadequate response to UDCA and subsequent response rates at 12 months were also evaluated. Results: Overall, 480 PBC patients were included in this study. The median UDCA dosage was 13.2 mg UDCA/kg bodyweight (BW)/d. Adequate UDCA treatment response rates according to Paris-I, Paris-II, and Barcelona criteria were observed in 91, 71.3, and 61.3% of patients, respectively. In 83.8% of patients, ALP ≤ 1.67 × ULN were achieved. A total of 116 patients (24.2%) showed an inadequate response to UDCA according to at least one criterion. The diverse second-line treatment regimens applied led to significantly higher response rates according to Paris-II (35 vs. 60%, p = 0.005), Barcelona (13 vs. 34%, p = 0.0005), ALP ≤ 1.67 × ULN and bilirubin ≤ 1 × ULN (52.1 vs. 75%, p = 0.002). The addition of bezafibrates appeared to induce the strongest beneficial effect in this cohort (Paris II: 24 vs. 74%, p = 0.004; Barcelona: 50 vs. 84%, p = 0.046; ALP < 1.67 × ULN and bilirubin ≤ 1 × ULN: 33 vs. 86%, p = 0.001). Conclusion: Our large retrospective multicenter study confirms high response rates following UDCA first-line standard treatment in patients with PBC and highlights the need for close monitoring and early treatment modification in high-risk patients with an insufficient response to UDCA since early treatment modification significantly increases subsequent response rates of these patients.
In the aftermath of the global financial crisis, the state of macroeconomicmodeling and the use of macroeconomic models in policy analysis has come under heavy criticism. Macroeconomists in academia and policy institutions have been blamed for relying too much on a particular class of macroeconomic models. This paper proposes a comparative approach to macroeconomic policy analysis that is open to competing modeling paradigms. Macroeconomic model comparison projects have helped produce some very influential insights such as the Taylor rule. However, they have been infrequent and costly, because they require the input of many teams of researchers and multiple meetings to obtain a limited set of comparative findings. This paper provides a new approach that enables individual researchers to conduct model comparisons easily, frequently, at low cost and on a large scale. Using this approach a model archive is built that includes many well-known empirically estimated models that may be used for quantitative analysis of monetary and fiscal stabilization policies. A computational platform is created that allows straightforward comparisons of models’ implications. Its application is illustrated by comparing different monetary and fiscal policies across selected models. Researchers can easily include new models in the data base and compare the effects of novel extensions to established benchmarks thereby fostering a comparative instead of insular approach to model development
In the aftermath of the global financial crisis, the state of macroeconomic modeling and the use of macroeconomic models in policy analysis has come under heavy criticism. Macroeconomists in academia and policy institutions have been blamed for relying too much on a particular class of macroeconomic models. This paper proposes a comparative approach to macroeconomic policy analysis that is open to competing modeling paradigms. Macroeconomic model comparison projects have helped produce some very influential insights such as the Taylor rule. However, they have been infrequent and costly, because they require the input of many teams of researchers and multiple meetings to obtain a limited set of comparative findings. This paper provides a new approach that enables individual researchers to conduct model comparisons easily, frequently, at low cost and on a large scale. Using this approach a model archive is built that includes many well-known empirically estimated models that may be used for quantitative analysis of monetary and fiscal stabilization policies. A computational platform is created that allows straightforward comparisons of models’ implications. Its application is illustrated by comparing different monetary and fiscal policies across selected models. Researchers can easily include new models in the data base and compare the effects of novel extensions to established benchmarks thereby fostering a comparative instead of insular approach to model development.
Adverse events triggered by non-steroidal anti-inflammatory drugs (NSAIDs) are among the most common drug-related intolerance reactions in medicine; they are possibly related to inhibition of cyclooxygenase-1. Coxibs, preferentially inhibiting cyclooxygenase-2, may therefore represent safe alternatives in patients with NSAID intolerance. We reviewed the literature in a systematic and structured manner to identify and evaluate studies on the tolerance of coxibs in patients with NSAID intolerance. We searched MEDLINE (1966–2006), the COCHRANE LIBRARY (4th Issue 2006) and EMBASE (1966–2006) up to December 9, 2006, and analysed all publications included using a predefined evaluation sheet. Symptoms and severity of adverse events to coxibs were analysed based on all articles comprising such information. Subsequently, the probability for adverse events triggered by coxibs was determined on analyses of double-blind prospective trials only. Among 3,304 patients with NSAID intolerance, 119 adverse events occurred under coxib medication. All adverse events, except two, have been allergic/urticarial in nature; none was lethal, but two were graded as life-threatening (grade 4). The two non-allergic adverse events were described as a grade 1 upper respiratory tract haemorrhage, and a grade 1 gastrointestinal symptom, respectively. In 13 double-blind prospective studies comprising a total of 591 patients with NSAID intolerance, only 13 adverse reactions to coxib provocations were observed. The triggering coxibs were rofecoxib (2/286), celecoxib (6/208), etoricoxib (4/56), and valdecoxib (1/41). This review documents the good tolerability of coxibs in patients with NSAID intolerance, for whom access to this class of drugs for short-term treatment of pain and inflammation is advantageous.
The demand to develop convergent technology platforms, such as bio-functionalized medical devices, is rapidly increasing. However, the loss of biological function of the effector molecules during sterilization represents a significant and general problem. Therefore, we have developed and characterized a nano-coating (NC) formulation capable of maintaining the functionality of proteins on biological-device combination products. As a proof of concept, the NC preserved the structural and functional integrity of an otherwise highly fragile antibody immobilized on polyurethane during deleterious sterilizing irradiation (≥ 25 kGy). The NC procedure enables straight-forward terminal sterilization of bio-functionalized materials while preserving optimal conditioning of the bioactive surface.
Global water models (GWMs) simulate the terrestrial water cycle, on the global scale, and are used to assess the impacts of climate change on freshwater systems. GWMs are developed within different modeling frameworks and consider different underlying hydrological processes, leading to varied model structures. Furthermore, the equations used to describe various processes take different forms and are generally accessible only from within the individual model codes. These factors have hindered a holistic and detailed understanding of how different models operate, yet such an understanding is crucial for explaining the results of model evaluation studies, understanding inter-model differences in their simulations, and identifying areas for future model development. This study provides a comprehensive overview of how state-of-the-art GWMs are designed. We analyze water storage compartments, water flows, and human water use sectors included in 16 GWMs that provide simulations for the Inter-Sectoral Impact Model Intercomparison Project phase 2b (ISIMIP2b). We develop a standard writing style for the model equations to further enhance model improvement, intercomparison, and communication. In this study, WaterGAP2 used the highest number of water storage compartments, 11, and CWatM used 10 compartments. Seven models used six compartments, while three models (JULES-W1, Mac-PDM.20, and VIC) used the lowest number, three compartments. WaterGAP2 simulates five human water use sectors, while four models (CLM4.5, CLM5.0, LPJmL, and MPIHM) simulate only water used by humans for the irrigation sector. We conclude that even though hydrologic processes are often based on similar equations, in the end, these equations have been adjusted or have used different values for specific parameters or specific variables. Our results highlight that the predictive uncertainty of GWMs can be reduced through improvements of the existing hydrologic processes, implementation of new processes in the models, and high-quality input data.
Global water models (GWMs) simulate the terrestrial water cycle on the global scale and are used to assess the impacts of climate change on freshwater systems. GWMs are developed within different modelling frameworks and consider different underlying hydrological processes, leading to varied model structures. Furthermore, the equations used to describe various processes take different forms and are generally accessible only from within the individual model codes. These factors have hindered a holistic and detailed understanding of how different models operate, yet such an understanding is crucial for explaining the results of model evaluation studies, understanding inter-model differences in their simulations, and identifying areas for future model development. This study provides a comprehensive overview of how 16 state-of-the-art GWMs are designed. We analyse water storage compartments, water flows, and human water use sectors included in models that provide simulations for the Inter-Sectoral Impact Model Intercomparison Project phase 2b (ISIMIP2b). We develop a standard writing style for the model equations to enhance model intercomparison, improvement, and communication. In this study, WaterGAP2 used the highest number of water storage compartments, 11, and CWatM used 10 compartments. Six models used six compartments, while four models (DBH, JULES-W1, Mac-PDM.20, and VIC) used the lowest number, three compartments. WaterGAP2 simulates five human water use sectors, while four models (CLM4.5, CLM5.0, LPJmL, and MPI-HM) simulate only water for the irrigation sector. We conclude that, even though hydrological processes are often based on similar equations for various processes, in the end these equations have been adjusted or models have used different values for specific parameters or specific variables. The similarities and differences found among the models analysed in this study are expected to enable us to reduce the uncertainty in multi-model ensembles, improve existing hydrological processes, and integrate new processes.
Background: IL28B gene polymorphism is the best baseline predictor of response to interferon alfa-based antiviral therapies in chronic hepatitis C. Recently, a new IFN-L4 polymorphism was identified as first potential functional variant for induction of IL28B expression. Individualization of interferon alfa-based therapies based on a combination of IL28B/IFN-L4 polymorphisms may help to optimize virologic outcome and economic resources.
Methods: Optimization of treatment outcome prediction was assessed by combination of different IL28B and IFN-L4 polymorphisms in patients with chronic HCV genotype 1 (n = 385), 2/3 (n = 267), and 4 (n = 220) infection treated with pegylated interferon alfa (PEG-IFN) and ribavirin with (n = 79) or without telaprevir. Healthy people from Germany (n = 283) and Egypt (n = 96) served as controls.
Results: Frequencies of beneficial IL28B rs12979860 C/C genotypes were lower in HCV genotype 1/4 infected patients in comparison to controls (20–35% vs. 46–47%) this was also true for ss469415590 TT/TT (20–35% vs. 45–47%). Single interferon-lambda SNPs (rs12979860, rs8099917, ss469415590) correlated with sustained virologic response (SVR) in genotype 1, 3, and 4 infected patients while no association was observed for genotype 2. Interestingly, in genotype 3 infected patients, best SVR prediction was based on IFN-L4 genotype. Prediction of SVR with high accuracy (71–96%) was possible in genotype 1, 2, 3 and 4 infected patients who received PEG-IFN/ribavirin combination therapy by selection of beneficial IL28B rs12979860 C/C and/or ss469415590 TT/TT genotypes (p<0.001). For triple therapy with first generation protease inhibitors (PIs) (boceprevir, telaprevir) prediction of high SVR (90%) rates was based on the presence of at least one beneficial genotype of the 3 IFN-lambda SNPs.
Conclusion: IFN-L4 seems to be the best single predictor of SVR in genotype 3 infected patients. For optimized prediction of SVR by treatment with dual combination or first generation PI triple therapies, grouping of interferon-lambda haplotypes may be helpful with positive predictive values of 71–96%.
Large-scale genetic census of an elusive carnivore, the European wildcat (Felis s. silvestris)
(2016)
The European wildcat, Felis silvestris silvestris, serves as a prominent target species for the reconnection of central European forest habitats. Monitoring of this species, however, appears difficult due to its elusive behaviour and the ease of confusion with domestic cats. Recently, evidence for multiple wildcat occurrences outside its known distribution has accumulated in several areas across Central Europe, questioning the validity of available distribution data for this species. Our aim was to assess the fine-scale distribution and genetic status of the wildcat in its central European distribution range. We compiled and analysed genetic samples from roadkills and hundreds of recent hair-trapping surveys and applied phylogenetic and genetic clustering methods to discriminate wild and domestic cats and identify population subdivision. 2220 individuals were confirmed as either wildcat (n = 1792) or domestic cat (n = 342), and the remaining 86 (3.9 %) were identified as hybrids between the two. Remarkably, genetic distinction of domestic cats, wildcats and their hybrids was only possible when taking into account the presence of two highly distinct genetic lineages of wildcats, with a suture zone in central Germany. 44 % of the individual wildcats where sampled outside the previously published distribution. Our analyses confirm a relatively continuous spatial presence of wildcats across large parts of the study area in contrast to previous analyses indicating a highly fragmented distribution. Our results suggest that wildcat conservation and management should take advantage of the higher than previously assumed dispersal potential of wildcats, which may use wildlife corridors very efficiently.
High-throughput protein localization studies require multiple strategies. Mass spectrometric analysis of defined cellular fractions is one of the complementary approaches to a diverse array of cell biological methods. In recent years, the protein content of different cellular (sub-)compartments was approached. Despite of all the efforts made, the analysis of membrane fractions remains difficult, in that the dissection of the proteomes of the envelope membranes of chloroplasts or mitochondria is often not reliable because sample purity is not always warranted. Moreover, proteomic studies are often restricted to single (model) species, and therefore limited in respect to differential individual evolution. In this study we analyzed the chloroplast envelope proteomes of different plant species, namely, the individual proteomes of inner and outer envelope (OE) membrane of Pisum sativum and the mixed envelope proteomes of Arabidopsis thaliana and Medicago sativa. The analysis of all three species yielded 341 identified proteins in total, 247 of them being unique. 39 proteins were genuine envelope proteins found in at least two species. Based on this and previous envelope studies we defined the core envelope proteome of chloroplasts. Comparing the general overlap of the available six independent studies (including ours) revealed only a number of 27 envelope proteins. Depending on the stringency of applied selection criteria we found 231 envelope proteins, while less stringent criteria increases this number to 649 putative envelope proteins. Based on the latter we provide a map of the outer and inner envelope core proteome, which includes many yet uncharacterized proteins predicted to be involved in transport, signaling, and response. Furthermore, a foundation for the functional characterization of yet unidentified functions of the inner and OE for further analyses is provided.