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Statistical models of the relationship between precipitation and topography are key elements for the spatial interpolation of rain-gauge measurements in high-mountain regions. This study investigates several extensions of the classical precipitation–height model in a direct comparison and within two popular interpolation frameworks, namely linear regression and kriging with external drift. The models studied include predictors of topographic height and slope at several spatial scales, a stratification by types of a circulation classification, and a predictor for wind-aligned topographic gradients. The benefit of the modeling components is investigated for the interpolation of seasonal mean and daily precipitation using leave-one-out cross-validation. The study domain is a north–south cross section of the European Alps (154 km × 187 km) that is inclined towards dense rain-gauge measurements (approx. 440 stations, 1971–2008). The significance of the topographic predictors was found to strongly depend on the interpolation framework. In linear regression, predictors of slope and at multiple scales reduce interpolation errors substantially. But with as many as nine predictors, the resulting interpolation still poorly replicates the across-ridge variation of climatological mean precipitation. Kriging with external drift (KED) leads to much smaller interpolation errors than linear regression, but this is achieved with a single predictor (local topographic height), whereas the incorporation of more extended predictor sets brings only marginal further improvement. Furthermore, the stratification by circulation types and the wind-aligned gradient predictor do not improve over the single predictor KED model. As for daily precipitation, interpolation accuracy improves considerably with KED and the use of a single predictor field (the distribution of seasonal mean precipitation) as compared to ordinary kriging (i.e., without any predictor). Nonetheless, information from circulation types did not improve interpolation accuracy. Our results confirm that the consideration of topography effects is important for spatial interpolation of precipitation in high-mountain regions. But a single predictor may be sufficient and taking appropriate account of the spatial autocorrelation (by kriging) can be more effective than the development of elaborate predictor sets within a regression model. Our results also question a popular practice of using linear regression for predictor selection in spatial interpolation; however they support the common practice of using a climatological mean field as a background in the interpolation of daily precipitation.

BackgroundInternational guidelines on the prevention and treatment of parastomal hernias are lacking. The European Hernia Society therefore implemented a Clinical Practice Guideline development project.MethodsThe guidelines development group consisted of general, hernia and colorectal surgeons, a biostatistician and a biologist, from 14 European countries. These guidelines conformed to the AGREE II standards and the GRADE methodology. The databases of MEDLINE, CINAHL, CENTRAL and the gray literature through OpenGrey were searched. Quality assessment was performed using Scottish Intercollegiate Guidelines Network checklists. The guidelines were presented at the 38th European Hernia Society Congress and each key question was evaluated in a consensus voting of congress participants.ResultsEnd colostomy is associated with a higher incidence of parastomal hernia, compared to other types of stomas. Clinical examination is necessary for the diagnosis of parastomal hernia, whereas computed tomography scan or ultrasonography may be performed in cases of diagnostic uncertainty. Currently available classifications are not validated; however, we suggest the use of the European Hernia Society classification for uniform research reporting. There is insufficient evidence on the policy of watchful waiting, the route and location of stoma construction, and the size of the aperture. The use of a prophylactic synthetic non-absorbable mesh upon construction of an end colostomy is strongly recommended. No such recommendation can be made for other types of stomas at present. It is strongly recommended to avoid performing a suture repair for elective parastomal hernia. So far, there is no sufficient comparative evidence on specific techniques, open or laparoscopic surgery and specific mesh types. However, a mesh without a hole is suggested in preference to a keyhole mesh when laparoscopic repair is performed.ConclusionAn evidence-based approach to the diagnosis and management of parastomal hernias reveals the lack of evidence on several topics, which need to be addressed by multicenter trials. Parastomal hernia prevention using a prophylactic mesh for end colostomies reduces parastomal herniation. Clinical outcomes should be audited and adverse events must be reported.

Brain-derived neurotrophic factor (BDNF) is a member of the nerve growth factor family which has been extensively studied for its roles in neural development, long-term memory, brain injury, and neurodegenerative diseases. BDNF signaling through tropomyosin receptor kinase B (TrkB) stimulates neuronal cell survival. For this reason, small molecule TrkB agonists are under pre-clinical develoment for the treatment of a range of neurodegenerative diseases and injuries. Our laboratory recently reported BDNF is secreted by pro-regenerative endothelial progenitor cells (EPCs) which support hematopoietic reconstitution following total body irradiation (TBI). Here we report BDNF-TrkB signaling plays a novel regenerative role in bone marrow and thymic regeneration following radiation injury. Exogenous administration of BDNF or TrkB agonist 7,8-dihydroxyflavone (7,8-DHF) following myelosuppressive radiation injury promoted faster recovery of mature blood cells and hematopoietic stem cells capable of multi-lineage reconstitution. BDNF promotes hematopoietic regeneration via activation of PDGFRα + bone marrow mesenchymal stem cells (MSCs) which increase secretion of hematopoietic cytokines interleukin 6 (IL-6) and leukemia inhibitory factor (LIF) in response to TrkB activation. These data suggest pharmacologic activation of the BDNF pathway with either BDNF or 7,8-DHF may be beneficial for treatment of radiation or chemotherapy induced myelosuppression.

Chronically high blood glucose (hyperglycemia) leads to diabetes and fatty liver disease. Obesity is a major risk factor for hyperglycemia, but the underlying mechanism is unknown. Here, we show that a high-fat diet (HFD) in mice causes early loss of expression of the glycolytic enzyme Hexokinase 2 (HK2) specifically in adipose tissue. Adipose-specific knockout of Hk2 reduced glucose disposal and lipogenesis and enhanced fatty acid release in adipose tissue. In a non-cell-autonomous manner, Hk2 knockout also promoted glucose production in liver. Furthermore, we observed reduced hexokinase activity in adipose tissue of obese and diabetic patients, and identified a loss-of-function mutation in the hk2 gene of naturally hyperglycemic Mexican cavefish. Mechanistically, HFD in mice led to loss of HK2 by inhibiting translation of Hk2 mRNA. Our findings identify adipose HK2 as a critical mediator of local and systemic glucose homeostasis, and suggest that obesity-induced loss of adipose HK2 is an evolutionarily conserved mechanism for the development of selective insulin resistance and thereby hyperglycemia.

The first purpose of our paper is to show how Hooley’s celebrated method leading to his conditional proof of the Artin conjecture on primitive roots can be combined with the Hardy–Littlewood circle method. We do so by studying the number of representations of an odd integer as a sum of three primes, all of which have prescribed primitive roots. The second purpose is to analyse the singular series. In particular, using results of Lenstra, Stevenhagen and Moree, we provide a partial factorisation as an Euler product and prove that this does not extend to a complete factorisation.

A statistical framework is presented for the assessment of climatological trends in the frequency of rare and extreme weather events. The methodology applies to long-term records of event counts and is based on the stochastic concept of binomial distributed counts. It embraces logistic regression for trend estimation and testing, and includes a quantification of the potential/limitation to discriminate a trend from the stochastic fluctuations in a record. This potential is expressed in terms of a detection probability, which is calculated from Monte Carlo–simulated surrogate records, and determined as a function of the record length, the magnitude of the trend and the average return period (i.e., the rarity) of events. Calculations of the detection probability for daily events reveal a strong sensitivity upon the rarity of events: in a 100-yr record of seasonal counts, a frequency change by a factor of 1.5 can be detected with a probability of 0.6 for events with an average return period of 30 days; however, this value drops to 0.2 for events with a return period of 100 days. For moderately rare events the detection probability decreases rapidly with shorter record length, but it does not significantly increase with longer record length when very rare events are considered. The results demonstrate the difficulty to determine trends of very rare events, underpin the need for long period data for trend analyses, and point toward a careful interpretation of statistically nonsignificant trend results. The statistical method is applied to examine seasonal trends of heavy daily precipitation at 113 rain gauge stations in the Alpine region of Switzerland (1901–94). For intense events (return period: 30 days) a statistically significant frequency increase was found in winter and autumn for a high number of stations. For strong precipitation events (return period larger than 100 days), trends are mostly statistically nonsignificant, which does not necessarily imply the absence of a trend.

Obesity is a major risk factor for insulin resistance and type 2 diabetes. In adipose tissue, obesity-mediated insulin resistance correlates with the accumulation of proinflammatory macrophages and inflammation. However, the causal relationship of these events is unclear. Here, we report that obesity-induced insulin resistance in mice precedes macrophage accumulation and inflammation in adipose tissue. Using a mouse model that combines genetically induced, adipose-specific insulin resistance (mTORC2-knockout) and diet-induced obesity, we found that insulin resistance causes local accumulation of proinflammatory macrophages. Mechanistically, insulin resistance in adipocytes results in production of the chemokine monocyte chemoattractant protein 1 (MCP1), which recruits monocytes and activates proinflammatory macrophages. Finally, insulin resistance (high homeostatic model assessment of insulin resistance [HOMA-IR]) correlated with reduced insulin/mTORC2 signaling and elevated MCP1 production in visceral adipose tissue from obese human subjects. Our findings suggest that insulin resistance in adipose tissue leads to inflammation rather than vice versa.

Many climate impact assessments require high-resolution precipitation time series that have a spatio-temporal correlation structure consistent with observations, for simulating either current or future climate conditions. In this respect, weather generators (WGs) designed and calibrated for multiple sites are an appealing statistical downscaling technique to stochastically simulate multiple realisations of possible future time series consistent with the local precipitation characteristics and their expected future changes. In this study, we present the implementation and validation of a multi-site daily precipitation generator re-built after the methodology described in Wilks (1998). The generator consists of several Richardson-type WGs run with spatially correlated random number streams. This study aims at investigating the capabilities, the added value and the limitations of the precipitation generator for a typical Alpine river catchment in the Swiss Alpine region under current climate. The calibrated multi-site WG is skilful at individual sites in representing the annual cycle of the precipitation statistics, such as mean wet day frequency and intensity as well as monthly precipitation sums. It reproduces realistically the multi-day statistics such as the frequencies of dry and wet spell lengths and precipitation sums over consecutive wet days. Substantial added value is demonstrated in simulating daily areal precipitation sums in comparison to multiple WGs that lack the spatial dependency in the stochastic process. Limitations are seen in reproducing daily and multi-day extreme precipitation sums, observed variability from year to year and in reproducing long dry spell lengths. Given the performance of the presented generator, we conclude that it is a useful tool to generate precipitation series consistent with the mean climatic aspects and likely helpful to be used as a downscaling technique for climate change scenarios.

Modelling spatial covariance is an essential part of all geostatistical methods. Traditionally, parametric semivariogram models are fit from available data. More recently, it has been suggested to use nonparametric correlograms obtained from spatially complete data fields. Here, both estimation techniques are compared. Nonparametric correlograms are shown to have a substantial negative bias. Nonetheless, when combined with the sample variance of the spatial field under consideration, they yield an estimate of the semivariogram that is unbiased for small lag distances. This justifies the use of this estimation technique in geostatistical applications. Various formulations of geostatistical combination (Kriging) methods are used here for the construction of hourly precipitation grids for Switzerland based on data from a sparse realtime network of raingauges and from a spatially complete radar composite. Two variants of Ordinary Kriging (OK) are used to interpolate the sparse gauge observations. In both OK variants, the radar data are only used to determine the semivariogram model. One variant relies on a traditional parametric semivariogram estimate, whereas the other variant uses the nonparametric correlogram. The variants are tested for three cases and the impact of the semivariogram model on the Kriging prediction is illustrated. For the three test cases, the method using nonparametric correlograms performs equally well or better than the traditional method, and at the same time offers great practical advantages. Furthermore, two variants of Kriging with external drift (KED) are tested, both of which use the radar data to estimate nonparametric correlograms, and as the external drift variable. The first KED variant has been used previously for geostatistical radar-raingauge merging in Catalonia (Spain). The second variant is newly proposed here and is an extension of the first. Both variants are evaluated for the three test cases as well as an extended evaluation period. It is found that both methods yield merged fields of better quality than the original radar field or fields obtained by OK of gauge data. The newly suggested KED formulation is shown to be beneficial, in particular in mountainous regions where the quality of the Swiss radar composite is comparatively low. An analysis of the Kriging variances shows that none of the methods tested here provides a satisfactory uncertainty estimate. A suitable variable transformation is expected to improve this.

The structure of a putative molybdate transporter (ModB 2 C 2 ) is presented in complex with its cognate binding protein ModA. These results help provide the structural basis for the ATP-driven transport mechanism of both clinically relevant multi-drug ABC exporters and of ABC importers facilitating bacterial nutrient uptake. ATP-binding cassette (ABC) transporter proteins carry diverse substrates across cell membranes 1 . Whereas clinically relevant ABC exporters are implicated in various diseases or cause multidrug resistance of cancer cells 2 , 3 , bacterial ABC importers are essential for the uptake of nutrients 4 , including rare elements such as molybdenum. A detailed understanding of their mechanisms requires direct visualization at high resolution and in distinct conformations. Our recent structure of the multidrug ABC exporter Sav1866 has revealed an outward-facing conformation of the transmembrane domains coupled to a closed conformation of the nucleotide-binding domains, reflecting the ATP-bound state 5 . Here we present the 3.1 Å crystal structure of a putative molybdate transporter (ModB 2 C 2 ) from Archaeoglobus fulgidus in complex with its binding protein (ModA). Twelve transmembrane helices of the ModB subunits provide an inward-facing conformation, with a closed gate near the external membrane boundary. The ATP-hydrolysing ModC subunits reveal a nucleotide-free, open conformation, whereas the attached binding protein aligns the substrate-binding cleft with the entrance to the presumed translocation pathway. Structural comparison of ModB 2 C 2 A with Sav1866 suggests a common alternating access and release mechanism, with binding of ATP promoting an outward-facing conformation and dissociation of the hydrolysis products promoting an inward-facing conformation.