Efficacy and safety of lumacaftor/ivacaftor combination therapy in patients with cystic fibrosis homozygous for Phe508del CFTR by pulmonary function subgroup

Background Lumacaftor/ivacaftor combination therapy demonstrated clinical benefits inpatients with cystic fibrosis homozygous for the Phe508del CFTR mutation.Pretreatment lung function is a confounding factor that potentially impacts the efficacyand safety of lumacaftor/ivacaftor therapy. Methods Two multinational, randomised, double-blind, placebo-controlled, parallelgroupPhase 3 studies randomised patients to receive placebo or lumacaftor (600 mgonce daily [qd] or 400 mg every 12 hours [q12h]) in combination with ivacaftor (250 mgq12h) for 24 weeks. Prespecified analyses of pooled efficacy and safety data by lungfunction, as measured by percent predicted forced expiratory volume in 1 second(ppFEV1), were performed for patients with baseline ppFEV1 <40 (n=81) and ≥40(n=1016) and screening ppFEV1 <70 (n=730) and ≥70 (n=342). These studies wereregistered with ClinicalTrials.gov (NCT01807923 and NCT01807949). Findings The studies were conducted from April 2013 through April 2014.Improvements in the primary endpoint, absolute change from baseline at week 24 inppFEV1, were observed with both lumacaftor/ivacaftor doses in the subgroup withbaseline ppFEV1 <40 (least-squares mean difference versus placebo was 3∙7 and 3.3percentage points for lumacaftor 600 mg qd/ivacaftor 250 mg q12h and lumacaftor 400mg q12h/ivacaftor 250 mg q12h, respectively [p<0∙05] and in the subgroup with baselineppFEV1 ≥40 (3∙3 and 2∙8 percentage points, respectively [p<0∙001]). Similar absoluteimprovements versus placebo in ppFEV1 were observed in subgroups with screening 4ppFEV1 <70 (3∙3 and 3∙3 percentage points for lumacaftor 600 mg qd/ivacaftor 250 mgq12h and lumacaftor 400 mg q12h/ivacaftor 250 mg q12h, respectively [p<0∙001]) and≥70 (3∙3 and 1∙9 percentage points, respectively [p=0.002] and [p=0∙079]). Increases inBMI and reduction in number of pulmonary exacerbation events were observed in bothLUM/IVA dose groups vs placebo across all lung function subgroups. Treatment wasgenerally well tolerated, although the incidence of some respiratory adverse events washigher with active treatment than with placebo. Interpretation Lumacaftor/ivacaftor combination therapy benefits patients homozygousfor Phe508del CFTR who have varying degrees of lung function impairment. Funding Vertex Pharmaceuticals Incorporated.

Compositional data analysis of Holocene sediments from the West Bengal Sundarbans, India: Geochemical proxies for grain-size variability in a delta environment

This paper is part of a special issue of Applied Geochemistry focusing on reliable applications of compositional multivariate statistical methods. This study outlines the application of compositional data analysis (CoDa) to calibration of geochemical data and multivariate statistical modelling of geochemistry and grain-size data from a set of Holocene sedimentary cores from the Ganges-Brahmaputra (G-B) delta. Over the last two decades, understanding near-continuous records of sedimentary sequences has required the use of core-scanning X-ray fluorescence (XRF) spectrometry, for both terrestrial and marine sedimentary sequences. Initial XRF data are generally unusable in ‘raw-format’, requiring data processing in order to remove instrument bias, as well as informed sequence interpretation. The applicability of these conventional calibration equations to core-scanning XRF data are further limited by the constraints posed by unknown measurement geometry and specimen homogeneity, as well as matrix effects. Log-ratio based calibration schemes have been developed and applied to clastic sedimentary sequences focusing mainly on energy dispersive-XRF (ED-XRF) core-scanning. This study has applied high resolution core-scanning XRF to Holocene sedimentary sequences from the tidal-dominated Indian Sundarbans, (Ganges-Brahmaputra delta plain). The Log-Ratio Calibration Equation (LRCE) was applied to a sub-set of core-scan and conventional ED-XRF data to quantify elemental composition. This provides a robust calibration scheme using reduced major axis regression of log-ratio transformed geochemical data. Through partial least squares (PLS) modelling of geochemical and grain-size data, it is possible to derive robust proxy information for the Sundarbans depositional environment. The application of these techniques to Holocene sedimentary data offers an improved methodological framework for unravelling Holocene sedimentation patterns.

Least Squares Approach to Inverse Problems in Musculoskeletal Biomechanics

Inverse simulations of musculoskeletal models computes the internal forces such as muscle and joint reaction forces, which are hard to measure, using the more easily measured motion and external forces as input data. Because of the difficulties of measuring muscle forces and joint reactions, simulations are hard to validate. One way of reducing errors for the simulations is to ensure that the mathematical problem is well-posed. This paper presents a study of regularity aspects for an inverse simulation method, often called forward dynamics or dynamical optimization, that takes into account both measurement errors and muscle dynamics. The simulation method is explained in detail. Regularity is examined for a test problem around the optimum using the approximated quadratic problem. The results shows improved rank by including a regularization term in the objective that handles the mechanical over-determinancy. Using the 3-element Hill muscle model the chosen regularization term is the norm of the activation. To make the problem full-rank only the excitation bounds should be included in the constraints. However, this results in small negative values of the activation which indicates that muscles are pushing and not pulling. Despite this unrealistic behavior the error maybe small enough to be accepted for specific applications. These results is a starting point start for achieving better results of inverse musculoskeletal simulations from a numerical point of view.

Analysis of the Market Potential of Syrian Organic Fruit and Vegetables for Exports to Germany

Syria has been a major producer and exporter of fresh fruit and vegetables (FFV) in the Arabic region. Prior to 2011, Syrian FFV were mainly exported to the neighbouring countries, the Gulf States and Northern Africa as well as to Eastern European countries. Although the EU is potentially one of the most profitable markets of high quality FFV (such as organic ones) in the world, Syrian exports of FFV to Western European countries like Germany have been small. It could be a lucrative opportunity for Syrian growers and exporters of FFV to export organic products to markets such as Germany, where national production is limited to a few months due to climatic conditions. Yet, the organic sector in Syria is comparatively young and only a very small area of FFV is certified according to EU organic regulations. Up to the author’s knowledge, little was known about Syrian farmers’ attitudes towards organic FFV production. There was also no study so far that explored and analysed the determining factors for organic FFV adoption among Syrian farmers as well as the exports of these products to the EU markets. The overarching aim of the present dissertation focused on exploring and identifying the market potential of Syrian exports of organic FFV to Germany. The dissertation was therefore concerned with three main objectives: (i) to explore if German importers and wholesalers of organic FFV see market opportunities for Syrian organic products and what requirements in terms of quality and quantity they have, (ii) to determine the obstacles Syrian producers and exporters face when exporting agricultural products to Germany, and (iii) to investigate whether Syrian farmers of FFV can imagine converting their farms to organic production as well as the underlying reasons why they do so or not. A twofold methodological approach with expert interviews and a farmer survey were used in this dissertation to address the abovementioned objectives. While expert interviews were conducted with German and Syrian wholesalers of (organic) FFV in 2011 (9 interviews each), the farmer survey was administrated with 266 Syrian farmers of FFV in the main region for the production of FFV (i.e. the coastal region) from November 2012 till May 2013. For modelling farmers’ decisions to adopt organic farming, the Theory of Planned Behaviour as theoretical framework and Partial Least Squares Structural Equation Modelling as the main method for data analysis were used in this study. The findings of this dissertation yield implications for the different stakeholders (governmental institutions and NGOs, farmers, exporters, wholesalers, etc.) who are interested in prompting the Syrian export of organic products. Based on the empirical results and a literature review, an action plan to promote Syrian production and export of organic products was developed which can help in the post-war period in Syria at improving the organic sector.

On the Capital Structure of Real Estate Firms

The leverage and debt maturity choices of real estate companies are interdependent, and are not made separately as is often assumed in the literature. We use three-stage least squares (3SLS) regression analysis to explore this interdependence for a sample of listed U.S. real estate companies and Real Estate Investment Trusts (REITs) traded between 1973 and 2006.We find substantial differences in the nature of the relationship between leverage and maturity for the two firm types. Leverage is a determinant of maturity for non-REITs, whereas maturity is a determinant of leverage for REITs. We also find that the drivers of capital structure choices in real estate companies and REITs clearly reflect the effects of the REIT regulation.

Increasing the power of genome wide association studies in natural populations using repeated measures : evaluation and implementation

1. Genomewide association studies (GWAS) enable detailed dissections of the genetic basis for organisms' ability to adapt to a changing environment. In long-term studies of natural populations, individuals are often marked at one point in their life and then repeatedly recaptured. It is therefore essential that a method for GWAS includes the process of repeated sampling. In a GWAS, the effects of thousands of single-nucleotide polymorphisms (SNPs) need to be fitted and any model development is constrained by the computational requirements. A method is therefore required that can fit a highly hierarchical model and at the same time is computationally fast enough to be useful. 2. Our method fits fixed SNP effects in a linear mixed model that can include both random polygenic effects and permanent environmental effects. In this way, the model can correct for population structure and model repeated measures. The covariance structure of the linear mixed model is first estimated and subsequently used in a generalized least squares setting to fit the SNP effects. The method was evaluated in a simulation study based on observed genotypes from a long-term study of collared flycatchers in Sweden. 3. The method we present here was successful in estimating permanent environmental effects from simulated repeated measures data. Additionally, we found that especially for variable phenotypes having large variation between years, the repeated measurements model has a substantial increase in power compared to a model using average phenotypes as a response. 4. The method is available in the R package RepeatABEL. It increases the power in GWAS having repeated measures, especially for long-term studies of natural populations, and the R implementation is expected to facilitate modelling of longitudinal data for studies of both animal and human populations.

Job-demand for Learning and Job-related Learning: the Mediating Effect of Job Performance Improvement Initiatives

This study examined whether job-performance-improvementinitiatives mediate the relationship between individuals’ job-demand for learning and job-related learning. Data were obtained from 115 full-time employees in a diverse range of occupations. A partial least squares analysis revealed that job-performance-improvement-initiatives mediate partially the effects of job-demand for learning on job-related learning. Several implications for future research and policy are drawn from the findings.