bluuebunny/crossref_metadata_2025_split huggingface dataset:
Discovery of Novel Muscarinic Receptor Modulators by Integrating a Natural Product Framework and a Bioactive Molecule
Authors: Varkhedkar Rajesh , Dogra Shalini , Tiwari Divya , Hussain Yusuf , Yadav Prem Narayan , Pandey Ganesh 
Published: January 2018

AbstractMuscarinic acetylcholine receptors (mAChRs) are important therapeutic targets for several diseases of the central nervous system and periphery. However, the lack of subtype‐selective ligands for these receptors is a major challenge. A novel approach involving the integration of a natural product framework with a bioactive molecule (iNPBM) by using gephyrotoxin and the isoindoline framework is demonstrated for the discovery of new and selective mAChR modulators. We established a scalable and versatile synthetic scheme to enable the synthesis of various analogues that provided the first structure–activity relationship study of this class of compounds. Pharmacological profiling of these compounds demonstrated several ligands with high affinity and selectivity for mAChRs. Specifically, RG‐06 and RG‐09 were found to be antagonists of M3‐mAChR, whereas RG‐02 was found to be an agonist at M2‐mAChR. Furthermore, RG‐02 exhibited salutary effects in an established pharmacological model of a cognitive deficit in mice.
Clinical Bioavailability of the Novel BACE1 Inhibitor Lanabecestat (AZD3293): Assessment of Tablet Formulations Versus an Oral Solution and the Impact of Gastric pH on Pharmacokinetics
Authors: Ye Naidong , Monk Scott A. , Daga Pankaj , Bender David M. , Rosen Laura B. , Mullen Jamie , Minkwitz Margaret C. , Kugler Alan R. 
Published: January 2018

AbstractThe relative bioavailability of lanabecestat administered as 2 tablet formulations versus an oral solution was investigated. This phase 1 single‐center, open‐label, randomized, 3‐period crossover study involved healthy male and nonfertile female subjects aged 18–55 years (NCT02039180). Subjects received a single 50‐mg lanabecestat dose as solution, tablet A, or tablet B on day 1 of each crossover period; 14 of 16 subjects completed the study. Relative bioavailability based on plasma lanabecestat AUC0–∞ (area under the plasma drug concentration–time curve from zero to infinity) geometric mean ratio versus oral solution (primary variable) was: tablet A, 1.052 (90% confidence interval [CI], 1.001–1.106); tablet B, 1.040 (0.989–1.093). These 90%CIs for geometric mean ratios are within accepted standard bioequivalence boundaries for all other pharmacokinetic (PK) parameters for both lanabecestat and metabolite (AZ13569724). All 3 formulations had similar plasma lanabecestat concentration–time profiles. Six adverse events were reported by 6 subjects (37.5%, all mild). GastroPlus modeling predicted a negligible impact of gastric pH changes on systemic PK (up to pH 7.4). Both tablet formulations fall within standard accepted bioequivalence criteria versus the oral solution. A single 50‐mg lanabecestat dose was well tolerated as a solution or tablet formulation in this population.
A data‐driven approach to modeling power consumption for a hybrid supercomputer
Authors: Sîrbu Alina , Babaoglu Ozalp 
Published: January 2018

SummaryPower consumption of current High Performance Computing systems has to be reduced by at least one order of magnitude before they can be scaled up towards ExaFLOP performance. While we can expect novel hardware technologies and architectures to contribute towards this goal, significant advances have to come also from software technologies such as proactive and power‐aware scheduling, resource allocation, and fault‐tolerant computing. Development of these software technologies in turn relies heavily on our ability to model and accurately predict power consumption in large computing systems. In this paper, we present a data‐driven model of power consumption for a hybrid supercomputer (which held the top spot in the Green500 ranking in June 2013) that combines CPU, GPU, and MIC technologies to achieve high levels of energy efficiency. Our model takes as input workload characteristics—the number and location of resources that are used by each job at a certain time—and calculates a predicted power consumption at the system level. The model is application‐code‐agnostic and is based solely on a data‐driven predictive approach, where log data describing the past jobs in the system are employed to estimate future power consumption. For this, three different model components are developed and integrated. The first employs support vector regression to predict power usage for jobs before these are started. The second uses a simple heuristic to predict the length of jobs, again before they start. The two predictions are then combined to estimate power consumption due to the job at all computational elements in the system. The third component is a linear model that takes as input the power consumption at the computing units and predicts system‐wide power consumption. Our method achieves highly‐accurate predictions starting solely from workload information and user histories. The model can be applied to power‐aware scheduling and power capping: alternative workload dispatching configurations can be evaluated from a power perspective and more efficient ones can be selected. The methodology outlined here can be easily adapted to other HPC systems where the same types of log data are available.
Short time Fourier transformation and deep neural networks for motor imagery brain computer interface recognition
Authors: Wang Zijian , Cao Lei , Zhang Zuo , Gong Xiaoliang , Sun Yaoru , Wang Haoran 
Published: January 2018

SummaryMotor imagery (MI) is an important control paradigm in the field of brain‐computer interface (BCI), which enables the recognition of personal intention. So far, numerous methods have been designed to classify EEG signal features for MI task. However, deep neural networks have been seldom applied to analyze EEG signals. In this study, two novel kinds of deep learning schemes based on convolutional neural networks (CNN) and Long Short‐Term Memory (LSTM) were proposed for MI‐classification. The frequency domain representations of EEG signals were obtained using short time Fourier transform (STFT) to train models. Classification results were compared between conventional algorithm, CNN, and LSTM models. Compared with two other methods, CNN algorithms had shown better performance. These conclusions verified that CNN method was promising for MI‐based BCIs.
Towards Sustainable Production of Formic Acid
Authors: Bulushev Dmitri A. , Ross Julian R. H. 
Published: January 2018

AbstractFormic acid is a widely used commodity chemical. It can be used as a safe, easily handled, and transported source of hydrogen or carbon monoxide for different reactions, including those producing fuels. The review includes historical aspects of formic acid production. It briefly analyzes production based on traditional sources, such as carbon monoxide, methanol, and methane. However, the main emphasis is on the sustainable production of formic acid from biomass and biomass‐derived products through hydrolysis and oxidation processes. New strategies of low‐temperature synthesis from biomass may lead to the utilization of formic acid for the production of fuel additives, such as methanol; upgraded bio‐oil; γ‐valerolactone and its derivatives; and synthesis gas used for the Fischer–Tropsch synthesis of hydrocarbons. Some technological aspects are also considered.
An efficient load balancing method for ad hoc networks
Authors: Singh Jaspreet , Rai C. S. 
Published: January 2018

SummaryRouting is the most basic and essential operation of any ad hoc network. A mobile ad hoc network presents many challenges, because of the severe resource limitations such as dynamic and varying topology, lack of centralized control, insecure medium, and limited battery power, among others. Therefore, optimization and conservation is the key to success of any ad hoc network operation. In this paper, we propose and define 2 new metrics for ad hoc networks: bandwidth utilization ratio and load index. These metrics can be used as an indicator to measure and monitor the network usability and to improve its efficiency by efficient load distribution. They can be used to predict the additional load that can be accommodated in the network, without causing any congestion or overflows. We also propose a new load balancing routing scheme for ad hoc networks, called efficient load balancing method. This method tries to offset the load on different paths using load index as a metric. Load index is defined as a measure of a node's degree of involvement in the message routing process, which is indicative of its load. To make this algorithm efficient, we limit our routes to a few efficient ones only. This number of alternate routes used, out of the pool of all available routes, is defined as degree of distribution. Simulation results adequately prove the efficiency of proposed method, vis‐à‐vis 2 other load balancing approaches, and these are verified statistically at 99% confidence interval. A p × q factorial design is used to verify that simulation results are the actual measurements and not due to some unknown errors.
Genotyping strategy matters when analyzing hypervariable major histocompatibility complex‐Experience from a passerine bird
Authors: Rekdal Silje L. , Anmarkrud Jarl Andreas , Johnsen Arild , Lifjeld Jan T. 
Published: January 2018

AbstractGenotyping of classical major histocompatibility complex (MHC) genes is challenging when they are hypervariable and occur in multiple copies. In this study, we used several different approaches to genotype the moderately variable MHC class I exon 3 (MHCIe3) and the highly polymorphic MHC class II exon 2 (MHCIIβe2) in the bluethroat (Luscinia svecica). Two family groups (eight individuals) were sequenced in replicates at both markers using Ion Torrent technology with both a single‐ and a dual‐indexed primer structure. Additionally, MHCIIβe2 was sequenced on Illumina MiSeq. Allele calling was conducted by modifications of the pipeline developed by Sommer et al. (BMC Genomics, 14, 2013, 542) and the software AmpliSAS. While the different genotyping strategies gave largely consistent results for MHCIe3, with a maximum of eight alleles per individual, MHCIIβe2 was remarkably complex with a maximum of 56 MHCIIβe2 alleles called for one individual. Each genotyping strategy detected on average 50%–82% of all MHCIIβe2 alleles per individual, but dropouts were largely allele‐specific and consistent within families for each strategy. The discrepancies among approaches indicate PCR biases caused by the platform‐specific primer tails. Further, AmpliSAS called fewer alleles than the modified Sommer pipeline. Our results demonstrate that allelic dropout is a significant problem when genotyping the hypervariable MHCIIβe2. As these genotyping errors are largely nonrandom and method‐specific, we caution against comparing genotypes across different genotyping strategies. Nevertheless, we conclude that high‐throughput approaches provide a major advance in the challenging task of genotyping hypervariable MHC loci, even though they may not reveal the complete allelic repertoire.
Evolution of a key trait greatly affects underground community assembly process through habitat adaptation in earthworms
Authors: Ikeda Hiroshi , Fukumori Kayoko , Shoda‐Kagaya Etsuko , Takahashi Masamichi , Ito Masamichi T. , Sakai Yoshimi , Matsumoto Kazuma 
Published: January 2018

AbstractUnderground community assemblies have not been studied well compared with aboveground communities, despite their importance for our understanding of whole ecosystems. To investigate underground community assembly over evolutionary timescales, we examined terrestrial earthworm communities (Oligochaeta: Haplotaxida) in conserved mountainous primary forests in Japan as a model system. We collected 553 earthworms mostly from two dominant families, the Megascolecidae and the Lumbricidae, from 12 sites. We constructed a molecular taxonomic unit tree based on the analysis of three genes to examine the effects of a biogeographic factor (dispersal ability) and an evolutionary factor (habitat adaptation) on the earthworm community assembly process. The phylogenetic distance of the earthworm communities among sites was positively correlated with geographic distance when intraspecific variation was included, indicating that the divergence within species was affected by biogeographic factors. The community assembly process in the Megascolecidae has also been affected by environmental conditions in relation to an evolutionary relationship between habitat environment and intestinal cecum type, a trait closely related to habitat depth and diet, whereas that in the Lumbricidae has not been affected as such. Intestinal cecum type showed a pattern of niche conservatism in the Megascolecidae lineage. Our results suggest that investigating the evolution of a key trait related to life history can lead to the clear description of community assembly process over a long timescale and that the community assembly process can differ greatly among related lineages even though they live sympatrically.
Stable and Sensitive Amperometric Determination of Endocrine Disruptor Bisphenol A at Residual Metal Impurities Within SWCNT
Authors: Kanagavalli Pandiyaraj , Senthil Kumar Shanmugam 
Published: January 2018

AbstractA simple and attentive method was attempted for the determination of endocrine disruptor molecule, Bisphenol A (BPA) using residual metal impurity act as a reactant present in as received SWCNT. The electrochemical behavior of BPA oxidation and its reaction mechanism was investigated by cyclic voltammetry using “as received SWCNT modified on glassy carbon electrode” (SWCNT/GCE) and the obtained results were compared with bare GCE. The SWCNT/GCE showed high electrocatalytic activity, sensitivity, stability and more importantly not much surface fouling compared with bare GCE. This is because of the formation of electroactive quinone and catechol as byproducts on SWCNT/GCE during electro‐oxidation of BPA. More interestingly, the electrochemically acid treated SWCNT/GCE not showed any characteristic oxidation and reduction peaks during electro‐oxidation of BPA which indicates that the presence of a residual metal impurity in SWCNT plays a vital role in electro‐oxidation of BPA. The amperometric detection of BPA oxidation on SWCNT/GCE showed excellent stability and good linear response from the wide range of concentration of 10–100 μM. The limit of detection and sensitivity of BPA electro‐oxidation on SWCNT/GCE is to be 7.3 μM (S/N=3) and 0.6494 μA/μM cm2 respectively. Finally, the fabricated sensor using SWCNT/GCE was successfully applied for the detection of BPA in plastic water bottles with excellent recovery range from 98–102 %.
An O2 Tolerant Polymer/Glucose Oxidase Based Bioanode as Basis for a Self‐powered Glucose Sensor
Authors: Lopez Francesca , Zerria Sarra , Ruff Adrian , Schuhmann Wolfgang 
Published: January 2018

AbstractThe development of O2 tolerant glucose sensors based on the highly active and robust enzyme glucose oxidase is still a major challenge because of the competition between the natural electron acceptor O2 and free‐diffusing or polymer‐bound artificial electron acceptors. We report the fabrication of a glucose oxidase based bioanode that operates under ambient conditions. Combination of this bioanode with a bilirubin oxidase based biocathode enabled the fabrication of a glucose/O2 powered biofuel cell as integrated power source for a self‐powered device. Glucose oxidase at the anode was electrically wired via a low‐potential redox polymer, i. e. a Toluidine Blue‐modified poly(methacrylate) based polymer, that ensures a high open‐circuit voltage of the biofuel cell but also catalytically reduces O2 and hence requires a protection shield for measurements under ambient conditions. The sensing layer was deposited by means of potential pulse‐assisted co‐deposition of glucose oxidase within the redox polymer and was protected from O2 by a newly proposed lactate oxidase/catalase based O2 removal layer that was immobilized within a hydrophilic redox‐silent polymer on top of the sensing layer. The protection layer was powered by lactate, a natural component in human blood. The biofuel cell exhibited an OCV of ca. 650 mV and the power output was dependent on the glucose concentration without any interference from oxygen providing that lactate was available in the analyte solution.
An improved design to capture magnetic microparticles for capillary electrophoresis based immobilized microenzyme reactors
Authors: Ramana Pranov , Schejbal Jan , Houthoofd Kristof , Martens Johan , Adams Erwin , Augustijns Patrick , Glatz Zdenĕk , Van Schepdael Ann 
Published: January 2018

AbstractIn this paper, we demonstrate the effectiveness of a new 3D printed magnet holder that enables capture of magnetic microparticles in commercially available capillary electrophoresis equipment with a liquid or air based coolant system. The design as well as the method to capture magnetic microparticles inside the capillary are discussed. This setup was tested at temperature and pH values suitable for performing enzymatic reactions. To demonstrate its applicability in CE‐ immobilized microenzyme reactors (IMER) development, human flavin‐containing monooxygenase 3 and bovine serum albumin were immobilized on amino functionalized magnetic microparticles using glutaraldehyde. These microparticles were subsequently used to perform in‐line capillary electrophoresis with clozapine as a model substrate. This setup could be used further to establish CE‐IMERs of other drug metabolic enzymes in a commercially available liquid based capillary coolant system. The CE‐IMER setup was successful, although a subsequent decrease in enzyme activity was observed on repeated runs.
Accurate automated assessment of gully cross‐section geometry using the photogrammetric interface FreeXSapp
Authors: Castillo C. , Marín‐Moreno V.J. , Pérez R. , Muñoz‐Salinas R. , Taguas E.V. 
Published: January 2018

AbstractDuring recent years, 3‐D techniques such as LiDAR and Structure‐from‐Motion (SfM) photogrammetry have been increasingly used for gully erosion assessment. However, innovative image‐based approaches based on these advances may also be used to provide accurate cross‐sectional measurements which are less expensive and time‐demanding. In this work, we present the FreeXSapp methodology, a new piece of freely‐available software based on existing SfM tools (MicMac and PMVS2) and augmented‐reality targets (ArUco markers) which performs the automated 3‐D reconstruction, scaling, orientation and analysis of gully cross‐sections (XSs) from images taken from the gully margin using a smartphone camera. As a field application, the volume of a 60‐m‐long medium‐size gully was evaluated, where a total of 10 XSs were measured and analyzed in approximately 30 min. The relative accuracy in estimating width and depth dimensions was in the order of 0.5%, with a precision ratio (relative to the camera–XS distance) of ~1500. Overall, using this methodology showed excellent performance in terms of time and cost requirements when compared with typical 3‐D and conventional 2‐D techniques. The FreeXSapp interface is downloadable for free for Windows operating systems at http://www.uco.es/users/ccastillo/freexsapp. Copyright © 2018 John Wiley & Sons, Ltd.
Terrestrial toxicity model for nickel: Comparison of culture method and modeling approaches
Authors: Jiang Yang , Zhao Xiaopeng , Gu Xueyuan , Gu Cheng , Wang Xiaorong 
Published: January 2018

Abstract

In metal toxicity model studies of soil–plant systems, hydroponic culture is often employed to simulate soil conditions, but the validity of this approach has not been examined. The present study evaluated Ni toxicity to wheat root elongation using models developed in hydroponic and sand cultures and then compared the results with those obtained from real soils. Three mechanism toxicity models were examined: the free ion activity model, the biotic ligand model (BLM), and the Gouy-Chapman-Stern model. After being developed in hydroponic and sand culture bioassays, the models were validated with 18 soils from across China. The results showed that more accurate predictions were obtained with sand rather than hydroponic bioassays. Dissolved organic matter exerted only a limited effect on Ni toxicity, whereas an important role was found for osmotic effects. Of the 3 models, the sand-based BLM best predicted Ni toxicity to wheat root elongation (root-mean-square error = 16.2% and R2 = 0.79) and was as good as the BLM estimated directly from soils. The present study shows that sand is a better matrix than solution for root elongation bioassays of Ni toxicity and that osmotic effects must be taken into account in evaluating soil conditions. Environ Toxicol Chem 2018;37:1349–1358. © 2018 SETAC
Abstract
Optimization of physicochemical and textural properties of pizza cheese fortified with soybean oil and carrot extract
Authors: Motevalizadeh Ehsan , Mortazavi Seyed Ali , Milani Elnaz , Hooshmand‐Dalir Moosa Al‐Reza 
Published: January 2018

AbstractResponse surface methodology (RSM) was used to optimize pizza cheese containing carrot extract. The effects of two important independent variables including soybean oil (5%–20%) and carrot extract (5%–20%) were studied on physicochemical and textural properties of pizza cheese containing carrot extract. According to the results, RSM was successfully used for optimizing formulation of pizza cheese containing carrot juice. Results of this study revealed that oil (A), carrot (B), AB, square term of carrot (B2), B, AB, square term of oil (A2), B2, AB, AB, A2B, A2, A2, A, A2, A2, AB, and AB2 had the most effect on moisture, acidity, stretch, L*, a*, b*, hardness, meltability, springiness, peroxide value (PV), cohesiveness, chewiness, gumminess, fracture force, adhesiveness force, stiffness, flavor, and overall acceptability, respectively. A formulation upon 20% oil and 10.88% carrot extract was found as the optimal formulation for pizza cheese containing carrot extract. At the optimal formulation, PV, L*, a*, b*, meltability, stretch, cohesiveness, springiness, gumminess, chewiness, adhesive force, flavor, texture, and overall acceptability at the optimum formulation were measured 2.23, 82.51, −3.69, 18.05, 17.86, 85.61, 0.41, 7.874, 23.7, 0.27, 0.61, 3.50, 3.95, and 3.65, respectively.