Global transcriptome sequencing identifies chlamydospore specific markers in Candida albicans and Candida dubliniensis.

Candida albicans and Candida dubliniensis are pathogenic fungi that are highly related but differ in virulence and in some phenotypic traits. During in vitro growth on certain nutrient-poor media, C. albicans and C. dubliniensis are the only yeast species which are able to produce chlamydospores, large thick-walled cells of unknown function. Interestingly, only C. dubliniensis forms pseudohyphae with abundant chlamydospores when grown on Staib medium, while C. albicans grows exclusively as a budding yeast. In order to further our understanding of chlamydospore development and assembly, we compared the global transcriptional profile of both species during growth in liquid Staib medium by RNA sequencing. We also included a C. albicans mutant in our study which lacks the morphogenetic transcriptional repressor Nrg1. This strain, which is characterized by its constitutive pseudohyphal growth, specifically produces masses of chlamydospores in Staib medium, similar to C. dubliniensis. This comparative approach identified a set of putatively chlamydospore-related genes. Two of the homologous C. albicans and C. dubliniensis genes (CSP1 and CSP2) which were most strongly upregulated during chlamydospore development were analysed in more detail. By use of the green fluorescent protein as a reporter, the encoded putative cell wall related proteins were found to exclusively localize to C. albicans and C. dubliniensis chlamydospores. Our findings uncover the first chlamydospore specific markers in Candida species and provide novel insights in the complex morphogenetic development of these important fungal pathogens.

Predicting community and ecosystem outcomes of mycorrhizal responses to global change.

Mycorrhizal symbioses link the biosphere with the lithosphere by mediating nutrient cycles and energy flow though terrestrial ecosystems. A more mechanistic understanding of these plant-fungal associations may help ameliorate anthropogenic changes to C and N cycles and biotic communities. We explore three interacting principles: (1) optimal allocation, (2) biotic context and (3) fungal adaptability that may help predict mycorrhizal responses to carbon dioxide enrichment, nitrogen eutrophication, invasive species and land-use changes. Plant-microbial feedbacks and thresholds are discussed in light of these principles with the goal of generating testable hypotheses. Ideas to develop large-scale collaborative research efforts are presented. It is our hope that mycorrhizal symbioses can be effectively integrated into global change models and eventually their ecology will be understood well enough so that they can be managed to help offset some of the detrimental effects of anthropogenic environmental change.

Changing Religiosity, Changing Politics? The Influence of 'Belonging' and 'Believing' on Political Attitudes in Switzerland

Starting from theories of secularization and of religious individualization, we propose a two-dimensional typology of religiosity and test its impact on political attitudes. Unlike classic conceptions of religiosity used in political studies, our typology simultaneously accounts for an individual's sense of belonging to the church (institutional dimension) and his/her personal religious beliefs (spiritual dimension). Our analysis, based on data from the World Values Survey in Switzerland (1989-2007), shows two main results. First, next to evidence of religious decline, we also find evidence of religious change with an increase in the number of people who "believe without belonging." Second, non-religious individuals and individuals who believe without belonging are significantly more permissive on issues of cultural liberalism than followers of institutionalized forms of religiosity.

Local-global splitting for spatiotemporal-adaptive multiscale methods

We present a novel spatiotemporal-adaptive Multiscale Finite Volume (MsFV) method, which is based on the natural idea that the global coarse-scale problem has longer characteristic time than the local fine-scale problems. As a consequence, the global problem can be solved with larger time steps than the local problems. In contrast to the pressure-transport splitting usually employed in the standard MsFV approach, we propose to start directly with a local-global splitting that allows to locally retain the original degree of coupling. This is crucial for highly non-linear systems or in the presence of physical instabilities. To obtain an accurate and efficient algorithm, we devise new adaptive criteria for global update that are based on changes of coarse-scale quantities rather than on fine-scale quantities, as it is routinely done before in the adaptive MsFV method. By means of a complexity analysis we show that the adaptive approach gives a noticeable speed-up with respect to the standard MsFV algorithm. In particular, it is efficient in case of large upscaling factors, which is important for multiphysics problems. Based on the observation that local time stepping acts as a smoother, we devise a self-correcting algorithm which incorporates the information from previous times to improve the quality of the multiscale approximation. We present results of multiphase flow simulations both for Darcy-scale and multiphysics (hybrid) problems, in which a local pore-scale description is combined with a global Darcy-like description. The novel spatiotemporal-adaptive multiscale method based on the local-global splitting is not limited to porous media flow problems, but it can be extended to any system described by a set of conservation equations.

Turnaround across diverse global supply chains using shared metrics and change methodology: The Case of Amer Sports Corporation

Purpose - The purpose of this paper is to document the outcome of a global three-year long supply chain improvement initiative at a multi-national producer of branded sporting goods that is transforming from a holding structure to an integrated company. The case company is comprised of seven internationally well-known sport brands, which form a diverse set of independent sub-cases, on which the same supply chain metrics and change project approach was applied to improve supply chain performance. Design/methodology/approach - By using in-depth case study and statistical analysis the paper analyzes across the brands how supply chain complexity (SKU count), supply chain type (make or buy) and seasonality affect completeness and punctuality of deliveries, and inventory as the change project progresses. Findings - Results show that reduction in supply chain complexity improves delivery performance, but has no impact on inventory. Supply chain type has no impact on service level, but brands with in-house production are better in improving inventory than those with outsourced production. Non-seasonal business units improve service faster than seasonal ones, yet there is no impact on inventory. Research limitations/implications - The longitudinal data used for the analysis is biased with the general business trend, yet the rich data from different cases and three-years of data collection enables generalizations to a certain level. Practical implications - The in-depth case study serves as an example for other companies on how to initiate a supply chain improvement project across business units with tangible results. Originality/value - The seven sub-cases with their different characteristics on which the same improvement initiative was applied sets a unique ground for longitudinal analysis to study supply chain complexity, type and seasonality.