bluuebunny/crossref_metadata_2025_split huggingface dataset:
Population of the temperate mosquito, Culex pipiens, decreases in response to habitat climatological changes in future
Authors: Watanabe K. , Fukui S. , Ohta S. 
Published: May 2017

AbstractPredictions of the temporal distribution of vector mosquitoes are an important issue for human health because the response of mosquito populations to climate change could have implications for the risk of vector‐borne diseases. To elucidate the effects of climate change on mosquito populations inhabiting temperate regions, we developed a Physiology‐based Climate‐driven Mosquito Population model for temperate regions. For accurately reproducing the temporal patterns observed in mosquito populations, the key factors were identified by implementing the combinations of factors into the model. We focused on three factors: the effect of diapause, the positive effect of rainfall on larval carrying capacity, and the negative effect of rainfall as the washout mortality on aquatic stages. For each model, parameters were calibrated using weekly observation data of a Culex pipiens adult population collected in Tokyo, Japan. Based on its likelihood value, the model incorporating diapause, constant carrying capacity, and washout mortality was the best to replicate the observed data. By using the selected model and applying global climate model data, our results indicated that the mosquito population would decrease and adults’ active season would be shortened under future climate conditions. We found that incorporating the washout effect in the model settings or not caused a difference in the temporal patterns in the projected mosquito populations. This suggested that water resources in mosquito habitats in temperate regions should be considered for predicting the risk of vector‐borne diseases in such regions.
Analysis on bioaccumulation of metals in aquatic environment of Beas River Basin: A case study from Kanjli wetland
Authors: Singh Navdeep , Kaur Manpreet , Katnoria Jatinder Kaur 
Published: May 2017

AbstractWetlands, the biological filters of the Earth, play an important role in biochemical transformation of various pollutants. Wetland plants, in this direction, help in accumulating various contaminants from aquatic bodies. Considering this, the present study was planned to estimate different metals (Cd, Cu, Cr, Co, Fe, Pb, Zn, and Mn) in water, sediment, soil, and plant (4 aquatic and 12 terrestrial) samples of Kanjli wetland, Kapurthala, Punjab (India), and a Ramsar site. It was observed that the contents of Cd and Pb in water samples were higher than limits prescribed by Bureau of Indian standards. Bioaccumulation and translocation factors for various metals were also calculated. Although all the plant species were found to be hyperaccumulator for one or the other metal studied, maximum six metals (Cd, Co, Fe, Mn, Pb, and Zn) were bioaccumulated inPanicum antidotaleamong aquatic plant species while (Cd, Cu, Fe, Mn, Pb, and Zn) inLantana camaraandAgeratum conyzoidsamong terrestrial plants species. It is evident that all these plants have potential to phytoremediate various inorganic pollutants and can act as bioindicators. The physicochemical characteristics revealed high biochemical oxygen demand (BOD) and nitrate (NO3) contents and low dissolved oxygen (DO) in water samples while the high content of phosphates in soil and sediment samples.
An application of principal component analysis to the interpretation of ionospheric current systems
Authors: Alken P. , Maute A. , Richmond A. D. , Vanhamäki H. , Egbert G. D. 
Published: May 2017

AbstractIonospheric currents are driven by several different physical processes and exhibit complex spatial and temporal structure. Magnetic field measurements of ionospheric sources are often spatially sparse, causing significant challenges in visualizing current flow at a specific time. Standard methods of fitting equivalent current models to magnetic observations, such as line currents, spherical harmonic analysis, spherical cap harmonic analysis, and spherical elementary current systems (SECS), are often unable to capture the full spatial complexity of the currents or require a large number of parameters which cannot be fully determined by the available data coverage. These methods rely on a set of generic basis functions which contain limited information about the geometries of the various ionospheric sources. In this study, we develop new basis functions for fitting ground and satellite measurements, which are derived from physics‐based ionospheric modeling combined with principal component analysis (PCA). The physics‐based modeling provides realistic current flow patterns for all of the primary ionospheric sources, including their daily and seasonal variability. The PCA technique extracts the most relevant spatial geometries of the currents from the model run into a small set of equivalent current modes. We fit these modes to magnetic measurements of the Swarm satellite mission at low and middle latitudes and compare the resulting model with independent measurements and with the SECS approach. We find that our PCA method accurately reproduces features of the equatorial electrojet and Sq current systems with only 10 modes and can predict ionospheric fields far from the data region.
Patient‐Reported Outcomes
Authors: Kammerman Lisa A. , Cappelleri Joseph C. , Bartlett Jonathan 
Published: May 2017

Abstract
Patient‐reported outcome (PRO) data present unique statistical challenges that may not be encountered with other types of endpoints used in randomized clinical trials. Statisticians, with their expertise in the design of clinical trials and the analysis of clinical trial data, contribute to the science of how studies can use PRO endpoints to provide data that are intended to support approval of medical products and PRO labeling claims. This article provides a brief regulatory history of PROs and highlights topics that statisticians who design and analyze clinical studies with PRO endpoints need to consider.
We discuss study design features that may help improve the likelihood of labeling claims for PRO data. Specification of the scientific question and estimand, definition of PRO endpoint, collection of data that aid PRO analyses and interpretation, and multiplicity adjustments are critical elements. In addition, PRO data have distinctive missing data considerations because PRO scores are typically constructed from many items and, often, from daily diary data. We discuss how missing items and missing diary days can affect efficacy analyses. Finally, we provide considerations for the interpretation of PRO results and suggest topics for further statistical research.
Theanine: Its Occurrence and Metabolism in Tea
Authors: Li Ning , de Silva Jacquie 
Published: May 2017

AbstractTea is the second most consumed beverage in the world, after water. It is widely regarded as a healthy beverage, associated with cancer prevention, boosting the immune system and mental alertness, although its popularity as a beverage probably has more to do with its pleasant taste and relaxation benefits. These qualities are attributed to a unique neurologically active non‐protein amino acid calledl‐theanine (γ‐ethylamino‐l‐glutamic acid). In this chapter, the authors review the properties of theanine, its occurrence and metabolism in tea. The possible role of theanine in nitrogen transport is discussed. The regulation of theanine levels is reviewed in the context of plant nitrogen metabolism. Particular emphasis is placed on the identification of enzymes involved in the synthesis and metabolism of theanine. Finally, the authors summarize the status of their endeavours to identify candidate genes contributing to the regulation of theanine levels in tea.
Metabolomics Approaches to Advance Understanding of Nitrogen Assimilation and Carbon–Nitrogen Interactions
Authors: Fait Aaron , Sienkiewicz‐Porzucek Agata , Fernie Alisdair R. 
Published: May 2017

AbstractIn the past 10 years, metabolomics has become an integrative and indispensable part of the post‐genomics approach to tackle questions on plant metabolism and its regulation in plants. Nonetheless, the dynamic range of the metabolic intermediates and their qualitative (chemical) diversity hampers the comprehensive analysis of the plant metabolome using one single platform. However, prompted by the increasing interest in routine analysis of the metabolic component, recent significant advances in experimental techniques, analytical technologies and tools for the elaboration of output data have been accomplished. Hence, our capability to identify an increasing number of metabolites and to integrate results from different approaches has greatly improved. Specific to the study of plant nitrogen metabolism, the introduction of metabolomics, alongside with transcriptomics, and metabolic flux analysis emphasized the complexity of the mechanisms regulating its assimilation and metabolism and the indissoluble interaction with carbon metabolism. In this chapter, we introduce the state of the art in metabolomics analytical tools and technologies as well as their employment to improve our understanding of nitrogen–carbon interaction in plants.
Metabolite Analysis and Metabolomics in the Study of Biotrophic Interactions between Plants and Microbes
Authors: Draper John , Rasmussen Susanne , Zubair Hassan 
Published: May 2017

AbstractBiotrophic plant–microbe interactions depend on the establishment of a nutritional interface allowing nutrient trafficking between plants and microbial symbionts and pathogens. A global re‐programming of host and microbial metabolism is at the core of these interactions, and we summarise in this chapter studies on metabolome and, to add interpretational power, transcriptome changes associated with the establishment and maintenance of a range of plant–microbe associations. Pathogenic fungi of crops cause severe economic losses, and factors resulting in improved crop resistance against infection and disease spread are therefore the subject of extensive research projects. We focus in this chapter on three fungal examples, namelyMagnaporthe grisea(rice blast),Blumeria graminis(powdery mildew) andUstilago maydis(corn smut), and discuss how metabolomics technologies critically improve our understanding of resistant and susceptible interactions. Like pathogens, mutualistic symbionts are heterotrophic organisms and depend on nutrients from their hosts, but unlike pathogens these microbial symbionts rarely cause disease symptoms or host death. In contrast, they can improve plant fitness by providing valuable nutrients or protective metabolites to their hosts, and we present here insights from studies on three exemplar mutualistic interactions, namely nitrogen fixing legume‐rhizobial, phosphorus supplying plant root – arbuscular mycorrhizal and alkaloid‐producing plant shoot –Neotyphodiumspp. endophyte associations. We conclude this chapter with an analysis of similarities and differences of pathogenic and mutualistic interactions from a global metabolic viewpoint, and propose that improved spatial and temporal separation, as well as high‐throughput analytical techniques for low abundance metabolites (e.g. phytohormones), might overcome some current limitations.
Metabolomics of

A
rabidopsis Thaliana
Authors: Beale Michael H. , Sussman Michael R. 
Published: May 2017

Abstract

Since the publication of the complete genome sequence of the model plant
Arabidopsis thaliana,
the precision annotation of the exact function of each gene has become a major research activity. Metabolomic analysis has much to offer in this endeavour and the small physical size and generation time of Arabidopsis make it a particularly attractive system for large‐scale metabolomic data collection and analysis. In this review, we summarize the known phytochemistry of Arabidopsis, with particular emphasis on recent discoveries that indicate that the complexity of this plant's secondary metabolome is much greater than originally realized. We survey how the different analytical technologies, used in metabolomic analysis, are applied to quantify both primary and secondary metabolites of Arabidopsis. The use of isotope labelling to derive empirical formulae for unknown metabolites is highlighted, as is co‐expression analysis of transcriptome and metabolome data, as both of these technologies are well suited to this species. The application of the various techniques to study the molecular plant physiology, genetics and functional genomics of Arabidopsis is reviewed, with particular reference to the use of mutants and other genetic resources, such as recombinant inbred lines.
Progress in Chemometrics and Biostatistics for Plant Applications, or: A Good Red Wine is a Bad White Wine
Authors: Kopka Joachim , Walther Dirk , Allwood J. William , Goodacre Royston 
Published: May 2017

Abstract
In the hunt for novel chemometric and biostatistical tools suitable for the automated mining of large metabolite profiling and fingerprinting data sets, the application of well‐established statistical tools appears to have been neglected. Using a data set that aims to understand the contributions that the metabolome can make to the prediction of the enological quality of white wines from the Palatinate region of Germany, we exemplify the power of ‘simple’ statistical analyses for knowledge generation and repeatable data reduction without loss of relevant information. In view of the many and diverse experimental designs required in plant physiological studies, we emphasize that no generalized standard operation procedure for the statistical data mining of such experiments should be suggested. Instead, a well‐compiled toolbox of simple and enhanced statistical algorithms should be at hand, and this chemometrics ‘zoo’ can be applied in a case‐by‐case decision and sequence. Care should be taken to have more confidence in statistical significance analyses that estimate error probabilities rather than to focus on just a few sample classification tools, such as the omnipresent principal component (PCA) and hierarchical cluster analyses (HCA). These tools, HCA and PCA, are ideal and expertly employed if applied to the non‐biased search for differential or common trends among samples. These tools, however, are less suited for the search of metabolic markers and whilst partial least squares discriminant analysis is often used in metabolomics studies, a lot of studies have been performed in a less than optimal manner with respect to model validation. In this chapter, we discuss the use of the Wilcoxon test, the Kruskal–Wallis test and analyses of variance (ANOVA) for reproducible data reduction and exemplify the caveats of correlation and discriminant analyses. We are convinced that many novel but also already‐established statistical tools should be explored for metabolomic data mining. We suggest decision tree (DT) analyses as a potentially valuable tool for the deduction of classification rules and propose that DT analysis may improve our understanding of conditional interactions between physiological and metabolic responses.
Conductivity Enhancement of PEDOT:PSS via Addition of Chloroplatinic Acid and Its Mechanism
Authors: Wu Falin , Li Pengcheng , Sun Kuan , Zhou Yongli , Chen Wei , Fu Jiehao , Li Meng , Lu Shirong , Wei Dongshan , Tang Xiaosheng , Zang Zhigang , Sun Lidong , Liu Xixia , Ouyang Jianyong 
Published: May 2017

Readily obtained highly conductive, transparent, and flexible poly(3,4‐ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) films is urgently needed in printing of flexible transparent electrodes. A simple and facile method to enhance the electrical conductivity of PEDOT:PSS films is reported. The conductivity is increased by four orders of magnitude after adding solid chloroplatinic acid (H2PtCl6) into the pristine PEDOT:PSS solution. The H2PtCl6‐doped PEDOT:PSS film exhibits a sheet resistance of 44 ± 5 Ω □‐1 and a transmittance of 84 ± 1% at 550 nm, corresponding to a figure of merit of 47 ± 4. Comparative study shows addition of solid acid like H2PtCl6 is more effective in conductivity enhancement than addition of polar organic solvents, such as dimethyl sulfoxide or ethylene glycol. The mechanism for the conductivity enhancement is attributed to both in situ doping and phase separation of PEDOT:PSS. PEDOT is oxidized and doped by Pt4+ of H2PtCl6, which is reduced simultaneously to Pt2+. Proton transfer from H2PtCl6 to PSS− of PEDOT:PSS causes formation of neutral PSSH, leading to phase separation between insulating PSS and conducting PEDOT. Such a phase separation results in conformational changes of PEDOT chains and reduction in energy barrier for charge hopping.
Correlates of resistance and relapse during blinatumomab therapy for relapsed/refractory acute lymphoblastic leukemia
Authors: Aldoss Ibrahim , Song Joo , Stiller Tracey , Nguyen Tina , Palmer Joycelynne , O'Donnell Margaret , Stein Anthony S. , Marcucci Guido , Forman Stephen , Pullarkat Vinod 
Published: May 2017

AbstractWe retrospectively analyzed 65 patients with refractory/relapsed (r/r) ALL who were treated with blinatumomab for predictors of leukemia response as well as clinical patterns of relapse and resistance with particular focus on downregulation of CD19 expression and extramedullary disease (EM‐ALL). The complete remission (CR) rate was 51%, and 15 (45%) responders underwent allogeneic hematopoietic cell transplantation (HCT) in CR. High leukemia burden (bone marrow blasts >50%) (P = .02), history of prior EM‐ALL (P = .005), and active EM‐ALL at the time of initiating blinatumomab (P = .05) predicted lower CR rate. Among refractory cases, 13 (41%) had evidence of EM‐ALL progression, and CD19 expression was negative or dim in 18% and 23%, respectively. Among responders, 20 (61%) subsequently relapsed among whom EM‐ALL relapse occurred in 8 (40%) patients, and CD19 expression was negative or dim in 35 and 6% of evaluable cases, respectively. Pretreatment moderate/strong CD19 expression (P = .01) and history of prior EM‐ALL during ALL course (P = .04) were risk factors for developing EM‐ALL at progression/relapse. However, no pretreatment factors predicted progression/relapse with CD19‐negative ALL. Overall‐survival (OS) and even‐free survival were improved for patients underwent allogeneic HCT compared to responders who did not. Furthermore, OS was superior for patients responded to blinatumomab compared to those who did not. Extramedullary and CD19‐negative disease are common during blinatumomab failure in r/r ALL. In addition to high leukemia burden, concurrent or prior history EM‐ALL were associated with lower response to blinatumomab. Higher CD19 expression as well as prior history of EM‐ALL were associated with EM‐ALL at the time of blinatumomab failure.
Local integrals of motion in many‐body localized systems
Authors: Imbrie John Z. , Ros Valentina , Scardicchio Antonello 
Published: May 2017

We review the current (as of Fall 2016) status of the studies on the emergent integrability in many‐body localized models. We start by explaining how the phenomenology of fully many‐body localized systems can be recovered if one assumes the existence of a complete set of (quasi)local operators which commute with the Hamiltonian (local integrals of motions, or LIOMs). We describe the evolution of this idea from the initial conjecture, to the perturbative constructions, to the mathematical proof given for a disordered spin chain. We discuss the proposed numerical algorithms for the construction of LIOMs and the status of the debate on the existence and nature of such operators in systems with a many‐body mobility edge, and in dimensions larger than one.
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The Dynamic Multisite Interactions between Two Intrinsically Disordered Proteins
Authors: Wu Shaowen , Wang Dongdong , Liu Jin , Feng Yitao , Weng Jingwei , Li Yu , Gao Xin , Liu Jianwei , Wang Wenning 
Published: May 2017

AbstractProtein interactions involving intrinsically disordered proteins (IDPs) comprise a variety of binding modes, from the well‐characterized folding upon binding to dynamic fuzzy complexes. To date, most studies concern the binding of an IDP to a structured protein, while the interaction between two IDPs is poorly understood. In this study, NMR, smFRET, and molecular dynamics (MD) simulation are combined to characterize the interaction between two IDPs, the C‐terminal domain (CTD) of protein 4.1G and the nuclear mitotic apparatus (NuMA) protein. It is revealed that CTD and NuMA form a fuzzy complex with remaining structural disorder. Multiple binding sites on both proteins were identified by molecular dynamics and mutagenesis studies. This study provides an atomic scenario in which two IDPs bearing multiple binding sites interact with each other in dynamic equilibrium. The combined approach employed here could be widely applicable for investigating IDPs and their dynamic interactions.
High‐k dielectric composites of poly(2‐cyanoethyl vinyl ether) and barium titanate for flexible electronics
Authors: Piana Francesco , Pfleger Jiří , Jambor Roman , Řičica Tomáš , Macak Jan M. 
Published: May 2017

ABSTRACTHigh‐k dielectric composite material for electronic applications was obtained by mixing a polymer with high dielectric constant, poly(2‐cyanoethyl vinyl ether) (CEPVA), and highly crystalline barium titanate (BT). Barium titanate nanoparticles of a size in the range 40–90 nm were prepared by the solvothermal method. By optimizing the reaction conditions, the formation of carbonate impurities and the agglomeration of formed nanoparticles were significantly reduced compared to state‐of‐the‐art procedures. Dielectric spectroscopy was measured in the range of 0.01 Hz to 10 MHz and showed the dielectric constant to be ɛ′ ∼ 35–40 with only 30 vol % content of BT in the composite. Extrapolating to 100% BT nanoparticle concentration and using the Lichtenecker model, the dielectric constant ɛ′ = 365 ± 27 at 10 kHz was obtained. The relaxation and electrical properties were investigated in depth, and a new relaxation phenomenon was revealed. CEPVA/BT composite is considered suitable for electronic applications, in which high ɛ′ together with a good mechanical flexibility are required, such as organic field effect transistors. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017, 134, 45236.
Physico‐optical properties of a crosslinked hyaluronic acid scaffold for biomedical applications
Authors: Lepore Maria , Portaccio Marianna , Delfino Ines , Sironi Laura , La Gatta Annalisa , D'Agostino Antonella , Izzo E. , Schiraldi Chiara 
Published: May 2017

ABSTRACTOptical techniques are increasingly employed for monitoring cell–matrix interactions in suitably prepared 3D scaffolds. The ability of designing and realizing synthetic extracellular matrix with well‐controlled optical properties is a crucial need in this field. For this purpose, a crosslinked hyaluronic acid (HA) scaffold is prepared. Fourier transform infrared and ultraviolet–visible spectroscopies enable to monitor the scaffold preparation process and to evidence scaffold high transparency and low fluorescence in the visible range. 3D optical characteristics of the HA scaffold are tested by two‐photon microscopy (TPM) imaging of embedded fluorescent microbeads and alive keratinocytes labeled with vital PKH67 dye at different depths from the scaffold surface. Some useful indications about the potentiality of TPM measurements for the determination of attenuation coefficient of turbid media are also reported. Moreover, the use of the presented HA scaffold for preparing tissue phantoms for fluorescence imaging or diffuse imaging is proposed. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017, 134, 45243.