bluuebunny/crossref_metadata_2025_split huggingface dataset:
IL17A and IL23R gene polymorphisms affect the clinical features and prognosis of patients with multiple myeloma
Authors: Kasamatsu Tetsuhiro , Kimoto Mari , Takahashi Noriyuki , Minato Yusuke , Gotoh Nanami , Takizawa Makiko , Matsumoto Morio , Sawamura Morio , Yokohama Akihiko , Handa Hiroshi , Tsukamoto Norifumi , Saitoh Takayuki , Murakami Hirokazu 
Published: August 2017

AbstractSingle nucleotide polymorphisms (SNPs) in interleukin 17 (IL17A) and IL‐23 receptor (IL23R) are involved in the pathogenesis of many cancers and autoimmune diseases. We investigated the influence of IL17A and IL23R SNPs on the risk of developing multiple myeloma (MM) and its clinical features. We obtained genomic DNA from 120 patients with MM and 201 healthy controls and detected IL17A −197 G/A (rs2275913) and IL23R H3Q (rs1884444) genotypes using the polymerase chain reaction‐restriction fragment length polymorphism method. There were no significant differences in the genotype and allele frequencies of IL17A −197 G/A and IL23R H3Q between the controls and patients with MM. Compared with the GG and GA genotypes, the IL17A AA genotype was significantly associated with lower hemoglobin levels. The IL23R HH genotype was significantly associated with higher frequency of bone lesions and plasmacytoma than the HQ and QQ genotypes. We observed significant differences in overall survival (OS) between patients treated with thalidomide and/or bortezomib and those treated conventionally. Therefore, we also examined the effect of IL17A and IL23R polymorphisms on the clinical variables and OS in patients treated with thalidomide and/or bortezomib. We observed that the IL23R HH genotype was significantly associated with poor survival compared with the QH and HH genotypes in these patients. Our findings indicate that IL17A −197 G/A and IL23R H3Q are not associated with susceptibility to MM. However, IL‐17 and IL‐23R polymorphisms may affect severity, bone lesions, and extra‐medullary disease in patients with MM. Moreover, IL23R polymorphisms may contribute to poor prognosis in patients with MM treated with thalidomide and/or bortezomib.
Does an upper limit to river water temperature apply in all places?
Authors: Shaw Stephen B. 
Published: August 2017

AbstractThere remains continued use of non‐linear, logistic regression models for predicting water temperature from air temperature. A dominant feature of these non‐linear models is an upper bound on river water temperature. This upper bound is often attributed to a large increase in evaporative cooling at high air temperatures, but the exact conditions under which such an increase may occur have not been thoroughly explored. To better understand the appropriateness of the non‐linear model for predicting river water temperatures, it is essential to understand the physical basis for the upper bound and when it should and should not be included in the statistical model. This paper applies and validates an energy balance model against 8 river systems spread across different climate regions of the United States. The energy balance model is then used to develop a diagram relating vapour pressure deficit and air temperature to water temperature. With knowledge of present or future vapour pressure deficit (difference between saturation and actual vapour content in the atmosphere) conditions in a given climate, the diagram can be used to predict the likelihood of an upper bound in the air–water temperature relationship. This investigation offers a fundamental physical explanation of the most appropriate form of statistical models that should be used for predicting future water temperature from air temperature in different geographic regions with different climate conditions. In general, climatic regions that have only a slight increase in vapour pressure deficit with increasing air temperature (typically humid regions) would not be expected to have an upper bound. Conversely, climatic regions in which vapour pressure deficit sharply increases with increasing air temperature (typically arid regions) would be expected to have an upper bound.
Predicting dry‐season flows with a monthly rainfall–runoff model: Performance for gauged and ungauged catchments
Authors: Hamel Perrine , Guswa Andrew J. , Sahl Jake , Zhang Lu 
Published: August 2017

AbstractHydrologic models are useful to understand the effects of climate and land‐use changes on dry‐season flows. In practice, there is often a trade‐off between simplicity and accuracy, especially when resources for catchment management are scarce. Here, we evaluated the performance of a monthly rainfall–runoff model (dynamic water balance model, DWBM) for dry‐season flow prediction under climate and land‐use change. Using different methods with decreasing amounts of catchment information to set the four model parameters, we predicted dry‐season flow for 89 Australian catchments and verified model performance with an independent dataset of 641 catchments in the United States. For the Australian catchments, model performance without catchment information (other than climate forcing) was fair; it increased significantly as the information to infer the four model parameters increased. Regressions to infer model parameters from catchment characteristics did not hold for catchments in the United States, meaning that a new calibration effort was needed to increase model performance there. Recognizing the interest in relative change for practical applications, we also examined how DWBM could be used to simulate a change in dry‐season flow following land‐use change. We compared results with and without calibration data and showed that predictions of changes in dry‐season flow were robust with respect to uncertainty in model parameters. Our analyses confirm that climate is a strong driver of dry‐season flow and that parsimonious models such as DWBM have useful management applications: predicting seasonal flow under various climate forcings when calibration data are available and providing estimates of the relative effect of land use on seasonal flow for ungauged catchments.
Sequentially testing polynomial model hypotheses using power transforms of regressors
Authors: Cho Jin Seo , Phillips Peter C. B. 
Published: August 2017

SummaryWe provide a methodology for testing a polynomial model hypothesis by generalizing the approach and results of Baek, Cho, and Phillips (Journal of Econometrics, 2015,187, 376–384; BCP), which test for neglected nonlinearity using power transforms of regressors against arbitrary nonlinearity. We use the BCP quasi‐likelihood ratio test and deal with the new multifold identification problem that arises under the null of the polynomial model. The approach leads to convenient asymptotic theory for inference, has omnibus power against general nonlinear alternatives, and allows estimation of an unknown polynomial degree in a model by way of sequential testing, a technique that is useful in the application of sieve approximations. Simulations show good performance in the sequential test procedure in both identifying and estimating unknown polynomial order. The approach, which can be used empirically to test for misspecification, is applied to a Mincer (Journal of Political Economy, 1958,66, 281–302;Schooling, Experience and Earnings, Columbia University Press, 1974) equation using data from Card (in Christofides, Grant, and Swidinsky (Eds.),Aspects of Labour Market Behaviour: Essays in Honour of John Vanderkamp, University of Toronto Press, 1995, 201‐222) and Bierens and Ginther (Empirical Economics, 2001,26, 307–324). The results confirm that the standard Mincer log earnings equation is readily shown to be misspecified. The applications consider different datasets and examine the impact of nonlinear effects of experience and schooling on earnings, allowing for flexibility in the respective polynomial representations.
Identifying contagion
Authors: Dungey Mardi , Renault Eric 
Published: August 2017

SummaryIdentifying contagion effects during periods of financial crisis is known to be complicated by the changing volatility of asset returns during periods of stress. To untangle this we propose a GARCH (generalized autoregressive conditional heteroskedasticity) common features approach, where systemic risk emerges from a common factor source (or indeed multiple factor sources) with contagion evident through possible changes in the factor loadings relating to the common factor(s). Within a portfolio mimicking factor framework this can be identified using moment conditions. We use this framework to identify contagion in three illustrations involving both single and multiple factor specifications: to the Asian currency markets in 1997–1998, to US sectoral equity indices in 2007–2009 and to the CDS (credit default swap) market during the European sovereign debt crisis of 2010–2013. The results reveal the extent to which contagion effects may be masked by not accounting for the sources of changed volatility apparent in simple measures such as correlation.
Review of the effects of manufactured nanoparticles on mammalian target organs
Authors: Wu Tianshu , Tang Meng 
Published: August 2017

AbstractNanotechnology had matured significantly during the last two decades as it has transitioned from bench top science to applied technology. Even though the issue of safety of nanotechnology has been raised nearly one decade ago, the rapid progress in development and use of nanomaterials has not yet been matched by toxicological investigations. Many recent studies have simply outlined the toxic effects of nanoparticles (NPs), but few have systematically addressed their potentially adverse biological effects on target organs. Some animal models have shown that NPs could be accumulated in various organs. These accumulations can access the vasculature and target other organs, resulting in a potential health risks. After the brief description of current knowledge on the wide applications of several common NPs, their applications and the toxicokinetics, this review focused on effects of NPs on organ functions and mammal health after acute or chronic exposure, and potential mechanisms of action. Due to their physical properties, the liver, kidneys and lung are the main target organs of NPs. Most of NPs show slight toxicity when exposed to animals, while certain toxic effects like oxidative stress generation, inflammation and DNA damage are commonly observed. The severity of NPs toxicity is dependent upon several factors, including exposure dose and administration, NPs chemistry, size, shape, agglomeration state, and electromagnetic properties, which could provide useful information necessary to control the toxicity of NPs. Finally, the safety evaluation of nanotoxicity was addressed.
SH3BP1‐induced Rac‐Wave2 pathway activation regulates cervical cancer cell migration, invasion, and chemoresistance to cisplatin
Authors: Wang Jingjing , Feng Yeqian , Chen Xishan , Du Zheng , Jiang Shaijun , Ma Shuyun , Zou Wen 
Published: August 2017

AbstractCervical cancer still remains the fourth most common cancer, affecting women worldwide with large geographic variations in cervical cancer incidence and mortality rates. SH3‐domain binding protein‐1 (SH3BP1) specifically inactivating Rac1 and its target Wave2 is required for cell motility, thus regarded as an essential regulator of cancer cell metastasis. However, the exact effects and molecular mechanisms of SH3BP1 in cervical cancer progression are still unknown. The present study is aimed to investigate the mechanism of SH3BP1 in regulation of cervical cancer cell metastasis and chemoresistance. In the present study, we demonstrated a high SH3BP1 expression in cervical cancer tissues; a higher SH3BP1 expression is also correlated with a shorter overall survival of patients with cervical cancer. Further, we revealed that SH3BP1 overexpression promoted the invasion, migration, and chemoresistance of cervical cancer cell through increasing Rac1 activity and Wave2 protein level. The promotive effect of SH3BP1 could be partially reversed by a Rac1 inhibitor, NSC 23766. In cisplatin‐resistant cervical cancer tissues, SH3BP1, Rac1, and Wave2 mRNA expression was significantly up‐regulated compared to that of the cisplatin‐sensitive cervical cancer tissues. Taken together, SH3BP1/Rac1/Wave2 pathway may potentially act as an effective therapeutic target combined with traditional cisplatin‐based chemotherapy for cervical cancer.
Integrated process development ‐ quality by design compliant evaluation of upstream variations at the microscale level
Authors: Walther Cornelia , Boras Dario , Demmel Lars , Berkemeyer Matthias , Brocard Cécile , Dürauer Astrid 
Published: August 2017

AbstractBACKGROUNDEvaluation of optimized upstream conditions is often solely based on titers that do not reflect the downstream process and, consequently, the final purity and yield. This is especially critical for proteins expressed as inclusion bodies (IBs) because the subsequent downstream process is more complex than for soluble proteins. A miniaturized process development platform representing the entire downstream process at a microscale level combined with a multi‐fermenter system for bioprocess screening enables fast investigation, using quality by design (QbD) measures, of the quality of feedstock compositions that are altered by upstream conditions.RESULTSHigh‐throughput methods were integrated for an entire process chain, including upstream and downstream processing, for production of a recombinant protein as IBs. The miniaturized process chain consisted of cell disruption, IB harvesting, solubilization, refolding, and chromatographic purification. This enables processing and evaluation of 16 different fermentation conditions within 7 days. Only 2 g of initial biomass was required for evaluation of an individual fermentation. This resulted in a 15‐fold reduction of time and a 100‐fold reduction of material compared with common bench scale experiments.CONCLUSIONThis microscale process chain mimics the bench process and is able to differentiate purity variations as low as 2%. © 2017 Society of Chemical Industry
Using a combined oxygen‐supply and substrate‐feeding strategy to improve 2,3‐butanediol production by metabolically engineered Klebsiella oxytoca KMS005
Authors: Chan Sitha , Kanchanatawee Sunthorn , Jantama Sirima Suvarnakuta , Jantama Kaemwich , Joannis‐Cassan Claire , Taillandier Patricia 
Published: August 2017

AbstractBACKGROUNDThere is much demand for and extensive application for 2,3‐butanediol (2,3‐BD) in various fields, and micro‐aerobic and substrate‐feeding conditions greatly affect microbial growth and production. The theoretical maximum of 2,3‐BD fermentative yield has rarely been reported. Therefore, our study aimed to develop an efficient combined oxygen‐supply and substrate‐feeding strategy to improve 2,3‐BD production yield in metabolically engineered Klebsiella oxytoca KMS005.RESULTSThe optimized oxygen consumption for 2,3‐BD production by strain KMS005 was demonstrated at 9.2 g for 1 L working volume corresponding to KLa of 25.2 h−1. During fed‐batch, a glucose feeding rate of 2 g h−1 starting at the end of the growth phase for 48 h followed by a final batch phase of 40 h was found likely to be satisfactory for 2,3‐BD production by the strain KMS005. A final 2,3‐BD concentration was obtained at 74.7 g L−1 with few by‐products formation. A theoretical maximum of 2,3‐BD production yield of 0.5 g g−1 substrate used was also approached.CONCLUSIONOur oxygen‐supply strategy with the specific feeding pattern developed in this study allowed the highest fermentative production yield of 2,3‐BD ever reported. The KMS005 strain may be used as a biocatalyst for cost‐effective 2,3‐BD production from renewable substrates. In addition, the outcome might bring a message for further developments of simple fed‐batch fermentation under micro‐aeration conditions into larger scales for 2,3‐BD production by K. oxytoca KMS005 or even other microorganisms. © 2017 Society of Chemical Industry
Numerical framework for the simulation of dielectric heating using finite and boundary element method
Authors: Grabmaier Sebastian , Jüttner Matthias , Vögeli Desirée , Rucker Wolfgang M. , Göhner Peter 
Published: August 2017

SummaryThis paper presents the latest development towards a software agent–based numerical framework for interdisciplinary coupled problems. The software agent framework is capable to incorporate multiple physical effects and combine multiple numerical methods through the usage of a neutral abstraction layer. The principles of software agent–based programming and the application in a numerical example are discussed. This paper focuses on dielectric heating and different methods for solving the time harmonic Maxwell equation. By reusing state of the art finite element method (FEM) and boundary element method (BEM) software tools and managing the interface between the different tools, this approach solves complicated and realistic three‐dimensional problems. The functionality and efficiency of the framework are demonstrated on the dielectric heating inside a human head due to electromagnetic waves. A proper iterative coupling formulation for FEM and BEM is derived and numerically validated. The FEM‐BEM coupling separates from existing approaches, because it takes advantage of new developments in the FEM, namely, the perfect handling of infinite domains through perfectly matched layers. Moreover, the simplicity and flexibility of the coupling method allow implementation in existing numerical codes.
Future Caribbean temperature and rainfall extremes from statistical downscaling
Authors: Stennett‐Brown Roxann K. , Jones Jhordanne J. P. , Stephenson Tannecia S. , Taylor Michael A. 
Published: August 2017

ABSTRACTThe Statistical Downscaling Model (SDSM) is used to investigate future projections of daily minimum and maximum temperature extremes for 45 stations and rainfall extremes for 39 stations across the Caribbean and neighbouring regions. Models show good skill in reproducing the monthly climatology of the mean daily temperatures and the frequencies of warm days, warm nights, cool days and cool nights between 1961 and 2001. Models for rainfall exhibit lower skill but generally capture the monthly climatology of mean daily rainfall and the spatial distribution of the mean annual maximum number of consecutive dry days (CDD) and mean annual count of days with daily rainfall above 10 mm (R10). Future projections suggest an increase (decrease) in warm (cool) days and nights by 2071–2099 under the A2 and B2 scenarios relative to 1961–1990. An increase in CDD is suggested for most stations except some eastern Caribbean stations and Bahamas. Decreases in RX1 (monthly maximum 1‐day precipitation), R10 and R95p (annual total rainfall above the 95th percentile) are also suggested for some northern Caribbean locations and Belize under the A2 scenario, compared to a mixture of increases and decreases for the eastern Caribbean. Atmospheric predictors used in SDSM correlate well with known oceanic and atmospheric drivers of Caribbean climate, e.g. the Atlantic Multidecadal Oscillation (AMO) on a seasonal timescale. Atlantic sea surface temperatures and the Caribbean low level jet appear to have significant influence on Caribbean temperature and rainfall extremes.
EURO‐CORDEX regional climate model simulation of precipitation on Scottish islands (1971–2000): model performance and implications for decision‐making in topographically complex regions
Authors: Foley Aideen , Kelman Ilan 
Published: August 2017

ABSTRACTDue to their scale and complex topography, islands such as the Hebrides and Shetland Islands are not completely resolved by global climate models, which may impact the quality of data that can be provided about future climate in such locations. In principle, dynamical downscaling may provide helpful additional detail about future local climate. However, there is also the potential for error and uncertainty to cascade through to the regional simulation. Here, we evaluate the simulative skill of the EURO‐CORDEX regional climate model ensemble on regional and local scales in the Hebrides and Shetland Islands, and consider the potential for such models to aid decision‐making in island settings, and other locations characterized by complex topography. Several precipitation indices (accumulated precipitation amount, mean daily precipitation amount, max 1‐day and 5‐day precipitation amounts, simple daily intensity, number of heavy and very heavy precipitation days) are used to assess model performance and identify bias relative to observations. Models are compared regionally, and at specific locations, namely Stornoway in the Hebrides and Lerwick in Shetland, for the period 1971–2000. Regional evaluation utilizes the UKCP09 gridded observational data set and local evaluation at Stornoway Airport and Lerwick utilizes observed mean precipitation and extreme indices from the European Climate Assessment & Dataset project. While no models perform skilfully across all the metrics studied, some models capture aspects of the precipitation climate at each location particularly well. Differences in model performance between the two case study sites highlight the value of evaluating models on multiple spatial scales. The implications of model uncertainty for decision‐making are also discussed.
Seasonal and interannual variability of land–atmosphere coupling across the Southern Great Plains of North America using the North American regional reanalysis
Authors: Basara Jeffrey B. , Christian Jordan I. 
Published: August 2017

ABSTRACTThe purpose of this study was to investigate the seasonal to interannual variability of the temporal and spatial distributions of land–atmosphere coupling (LAC) at the mesoscale within the Southern Great Plains (SGP) of the United States. The North American Regional Reanalysis data set from 1979 to 2014 was used to complete this study. To further expand the relationship between soil moisture and precipitation, LAC was examined for the effects of soil moisture variability on latent heat flux (SM‐E) and the impact of latent heat flux variability on precipitation (E‐P). Results revealed that within the SGP there is a temporal and spatial seasonal evolution of the SM‐E relationship and dry boreal summer month (June, July and August, JJA) periods exhibit a stronger E‐P relationship relative to pluvial boreal summer month periods. Further, the variability of coupling was large both within‐season (i.e. JJA) as well as at the interannual scale while the interannual spatial and temporal coherence was such that no specific locations showed consistent coupling within the domain. Thus, the results indicate that while the SGP domain is sensitive to coupling, the location of preferred coupling is likely due to non‐local factors at the mesoscale embedded within synoptic conditions as well as the regional climate.