Evaluation of different sources of uncertainty in climate change impact research using a hydro-climatic model ensemble

The international research project QBic3 (Quebec-Bavarian Collaboration on Climate Change) aims at investigating the potential impacts of climate change on the hydrology of regional scale catchments in Southern Quebec (Canada) and Bavaria (Germany). Yet, the actual change in river runoff characteristics during the next 70 years is highly uncertain due to a multitude of uncertainty sources. The so-called hydro-climatic ensemble that is constructed to describe the uncertainties of this complex model chain consists of four different global climate models, downscaled by three different regional climate models, an exchangeable bias correction algorithm, a separate method to scale RCM outputs to the hydrological model scale and several hydrological models of differing complexity to assess the impact of different hydro model concepts. This choice of models and scenarios allows for the inter-comparison of the uncertainty ranges of climate and hydrological models, of the natural variability of the climate system as well as of the impact of scaling and correction of climate data on mean, high and low flow conditions. A methodology to display the relative importance of each source of uncertainty is proposed and results for past runoff and potential future changes are presented

Clinical Indicators of Obstructive Sleep Apnea

Clinical indicators (e.g., sex, snoring severity, history of apnea, age, menopausal status, waist-to-hip ratio, body habitus) can predict OSA as diagnosed using overnight polysomnography or sleep study. (Strength of Recommendation: B, based on multiple cross-sectional studies.) There is insufficient evidence to specify which measure of body habitus (i.e., body mass index [BMI] or neck circumference) is more predictive of OSA

An ensemble approach to assess hydrological models’ contribution to uncertainties in the analysis of climate change impact on water resources

Over the recent years, several research efforts investigated the impact of climate change on water resources for different regions of the world. The projection of future river flows is affected by different sources of uncertainty in the hydro-climatic modelling chain. One of the aims of the QBic3 5 project (Que´bec-Bavarian International Collaboration on Climate Change) is to assess the contribution to uncertainty of hydrological models by using an ensemble of hydrological models presenting a diversity of structural complexity (i.e. lumped, semi distributed and distributed models). The study investigates two humid, mid-latitude catchments with natural flow conditions; one located in 10 Southern Que´bec (Canada) and one in Southern Bavaria (Germany). Daily flow is simulated with four different hydrological models, forced by outputs from regional climate models driven by a given number of GCMs’ members over a reference (1971–2000) and a future (2041–2070) periods. The results show that the choice of the hydrological model does strongly affect the climate change response of selected hydrological indicators, especially those related to low flows. Indicators related to high flows seem less sensitive on the choice of the hydrological model. Therefore, the computationally less demanding models (usually simple, lumped and conceptual) give a significant level of trust for high and overall mean flows

On the need for bias correction in regional climate scenarios to assess climate change impacts on river runoff

In climate change impact research, the assessment of future river runoff as well as the catchment scale water balance is impeded by different sources of modeling uncertainty. Some research has already been done in order to quantify the uncertainty of climate 5 projections originating from the climate models and the downscaling techniques as well as from the internal variability evaluated from climate model member ensembles. Yet, the use of hydrological models adds another layer of incertitude. Within the QBic3 project (Qu´ebec-Bavaria International Collaboration on Climate Change) the relative contributions to the overall uncertainty from the whole model chain (from global climate 10 models to water management models) are investigated using an ensemble of multiple climate and hydrological models. Although there are many options to downscale global climate projections to the regional scale, recent impact studies tend to use Regional Climate Models (RCMs). One reason for that is that the physical coherence between atmospheric and land-surface 15 variables is preserved. The coherence between temperature and precipitation is of particular interest in hydrology. However, the regional climate model outputs often are biased compared to the observed climatology of a given region. Therefore, biases in those outputs are often corrected to reproduce historic runoff conditions from hydrological models using them, even if those corrections alter the relationship between temperature and precipitation. So, as bias correction may affect the consistency between RCM output variables, the use of correction techniques and even the use of (biased) climate model data itself is sometimes disputed among scientists. For those reasons, the effect of bias correction on simulated runoff regimes and the relative change in selected runoff indicators is explored. If it affects the conclusion of climate change analysis in 25 hydrology, we should consider it as a source of uncertainty. If not, the application of bias correction methods is either unnecessary in hydro-climatic projections, or safe to use as it does not alter the change signal of river runoff. The results of the present paper highlight the analysis of daily runoff simulated with four different hydrological models in two natural-flow catchments, driven by different regional climate models for a reference and a future period. As expected, bias correction of climate model outputs is important for the reproduction of the runoff regime of the 5 past regardless of the hydrological model used. Then again, its impact on the relative change of flow indicators between reference and future period is weak for most indicators with the exception of the timing of the spring flood peak. Still, our results indicate that the impact of bias correction on runoff indicators increases with bias in the climate simulations

Transmission of mitochondrial DNA following assisted reproduction and nuclear transfer

Review of the articleMitochondria are the organelles responsible for producing the majority of a cell's ATP and also play an essential role in gamete maturation and embryo development. ATP production within the mitochondria is dependent on proteins encoded by both the nuclear and the mitochondrial genomes, therefore co-ordination between the two genomes is vital for cell survival. To assist with this co-ordination, cells normally contain only one type of mitochondrial DNA (mtDNA) termed homoplasmy. Occasionally, however, two or more types of mtDNA are present termed heteroplasmy. This can result from a combination of mutant and wild-type mtDNA molecules or from a combination of wild-type mtDNA variants. As heteroplasmy can result in mitochondrial disease, various mechanisms exist in the natural fertilization process to ensure the maternal-only transmission of mtDNA and the maintenance of homoplasmy in future generations. However, there is now an increasing use of invasive oocyte reconstruction protocols, which tend to bypass mechanisms for the maintenance of homoplasmy, potentially resulting in the transmission of either form of mtDNA heteroplasmy. Indeed, heteroplasmy caused by combinations of wild-type variants has been reported following cytoplasmic transfer (CT) in the human and following nuclear transfer (NT) in various animal species. Other techniques, such as germinal vesicle transfer and pronuclei transfer, have been proposed as methods of preventing transmission of mitochondrial diseases to future generations. However, resulting embryos and offspring may contain mtDNA heteroplasmy, which itself could result in mitochondrial disease. It is therefore essential that uniparental transmission of mtDNA is ensured before these techniques are used therapeutically

Ultra-sensitive magnetometry based on free precession of nuclear spins

We discuss the design and performance of a very sensitive low-field magnetometer based on the detection of free spin precession of gaseous, nuclear polarized 3He or 129Xe samples with a SQUID as magnetic flux detector. The device will be employed to control fluctuating magnetic fields and gradients in a new experiment searching for a permanent electric dipole moment of the neutron as well as in a new type of 3He/129Xe clock comparison experiment which should be sensitive to a sidereal variation of the relative spin precession frequency. Characteristic spin precession times T_2 of up to 60h could be measured. In combination with a signal-to-noise ratio of > 5000:1, this leads to a sensitivity level of deltaB= 1fT after an integration time of 220s and to deltaB= 10^(-4)fT after one day. Even in that sensitivity range, the magnetometer performance is statistically limited, and noise sources inherent to the magnetometer are not limiting. The reason is that free precessing 3He (129Xe) nuclear spins are almost completely decoupled from the environment. That makes this type of magnetometer in particular attractive for precision field measurements where a long-term stability is required

Identification of Novel SNPs in Glioblastoma Using Targeted Resequencing

High-throughput sequencing opens avenues to find genetic variations that may be indicative of an increased risk for certain diseases. Linking these genomic data to other “omics” approaches bears the potential to deepen our understanding of pathogenic processes at the molecular level. To detect novel single nucleotide polymorphisms (SNPs) for glioblastoma multiforme (GBM), we used a combination of specific target selection and next generation sequencing (NGS). We generated a microarray covering the exonic regions of 132 GBM associated genes to enrich target sequences in two GBM tissues and corresponding leukocytes of the patients. Enriched target genes were sequenced with Illumina and the resulting reads were mapped to the human genome. With this approach we identified over 6000 SNPs, including over 1300 SNPs located in the targeted genes. Integrating the genome-wide association study (GWAS) catalog and known disease associated SNPs, we found that several of the detected SNPs were previously associated with smoking behavior, body mass index, breast cancer and high-grade glioma. Particularly, the breast cancer associated allele of rs660118 SNP in the gene SART1 showed a near doubled frequency in glioblastoma patients, as verified in an independent control cohort by Sanger sequencing. In addition, we identified SNPs in 20 of 21 GBM associated antigens providing further evidence that genetic variations are significantly associated with the immunogenicity of antigens

A systematic characterization of factors that regulate Drosophila segmentation via a bacterial one-hybrid system

Specificity data for groups of transcription factors (TFs) in a common regulatory network can be used to computationally identify the location of cis-regulatory modules in a genome. The primary limitation for this type of analysis is the paucity of specificity data that is available for the majority of TFs. We describe an omega-based bacterial one-hybrid system that provides a rapid method for characterizing DNA-binding specificities on a genome-wide scale. Using this system, 35 members of the Drosophila melanogaster segmentation network have been characterized, including representative members of all of the major classes of DNA-binding domains. A suite of web-based tools was created that uses this binding site dataset and phylogenetic comparisons to identify cis-regulatory modules throughout the fly genome. These tools allow specificities for any combination of factors to be used to perform rapid local or genome-wide searches for cis-regulatory modules. The utility of these factor specificities and tools is demonstrated on the well-characterized segmentation network. By incorporating specificity data on an additional 66 factors that we have characterized, our tools utilize ∼14% of the predicted factors within the fly genome and provide an important new community resource for the identification of cis-regulatory modules

Biosynthesis of Salmonella enterica [NiFe]-hydrogenase-5 : probing the roles of system-specific accessory proteins

A subset of bacterial [NiFe]-hydrogenases have been shown to be capable of activating dihydrogen-catalysis under aerobic conditions; however, it remains relatively unclear how the assembly and activation of these enzymes is carried out in the presence of air. Acquiring this knowledge is important if a generic method for achieving production of O2-resistant [NiFe]-hydrogenases within heterologous hosts is to be developed. Salmonella enterica serovar Typhimurium synthesizes the [NiFe]-hydrogenase-5 (Hyd-5) enzyme under aerobic conditions. As well as structural genes, the Hyd-5 operon also contains several accessory genes that are predicted to be involved in different stages of biosynthesis of the enzyme. In this work, deletions in the hydF, hydG, and hydH genes have been constructed. The hydF gene encodes a protein related to Ralstonia eutropha HoxO, which is known to interact with the small subunit of a [NiFe]-hydrogenase. HydG is predicted to be a fusion of the R. eutropha HoxQ and HoxR proteins, both of which have been implicated in the biosynthesis of an O2-tolerant hydrogenase, and HydH is a homologue of R. eutropha HoxV, which is a scaffold for [NiFe] cofactor assembly. It is shown here that HydG and HydH play essential roles in Hyd-5 biosynthesis. Hyd-5 can be isolated and characterized from a ΔhydF strain, indicating that HydF may not play the same vital role as the orthologous HoxO. This study, therefore, emphasises differences that can be observed when comparing the function of hydrogenase maturases in different biological systems

An ensemble approach to assess hydrological models' contribution to uncertainties in the analysis of climate change impact on water resources

Over the recent years, several research efforts investigated the impact of climate change on water resources for different regions of the world. The projection of future river flows is affected by different sources of uncertainty in the hydro-climatic modelling chain. One of the aims of the QBic<sup>3</sup> project (Québec-Bavarian International Collaboration on Climate Change) is to assess the contribution to uncertainty of hydrological models by using an ensemble of hydrological models presenting a diversity of structural complexity (i.e., lumped, semi distributed and distributed models). The study investigates two humid, mid-latitude catchments with natural flow conditions; one located in Southern Québec (Canada) and one in Southern Bavaria (Germany). Daily flow is simulated with four different hydrological models, forced by outputs from regional climate models driven by global climate models over a reference (1971–2000) and a future (2041–2070) period. The results show that, for our hydrological model ensemble, the choice of model strongly affects the climate change response of selected hydrological indicators, especially those related to low flows. Indicators related to high flows seem less sensitive on the choice of the hydrological model