bluuebunny/crossref_metadata_2025 huggingface dataset:
Band Topology of Bismuth Quantum Films
Authors: Chang Tay-Rong , Lu Qiangsheng , Wang Xiaoxiong , Lin Hsin , Miller T. , Chiang Tai-Chang , Bian Guang
Published: September 2019

Bismuth has been the key element in the discovery and development of topological insulator materials. Previous theoretical studies indicated that Bi is topologically trivial and it can transform into the topological phase by alloying with Sb. However, recent high-resolution angle-resolved photoemission spectroscopy (ARPES) measurements strongly suggested a topological band structure in pure Bi, conflicting with the theoretical results. To address this issue, we studied the band structure of Bi and Sb films by ARPES and first-principles calculations. The quantum confinement effectively enlarges the energy gap in the band structure of Bi films and enables a direct visualization of the

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topological invariant of Bi. We find that Bi quantum films in topologically trivial and nontrivial phases respond differently to surface perturbations. This way, we establish experimental criteria for detecting the band topology of Bi by spectroscopic methods.
Whipple Grossing in the Era of New Staging: Should We Standardize?
Authors: Shi Jiaqi , Basturk Olca
Published: September 2019

Whipple procedure, also known as pancreatoduodenectomy, is the most common surgery for the removal of tumors of the head of the pancreas, ampulla, distal common bile duct, or periampullary duodenum. It is also one of the most challenging resection specimens grossed by surgical pathologists. A thorough and consistent evaluation of the gross surgical specimen is the most critical first step for accurate diagnosis, determination of tumor origin, staging, and evaluation of margin status. However, there has been no standard grossing protocol for Whipple specimens, which has led to inaccurate diagnoses, staging, and inconsistent reporting. This issue has become even more challenging in the era of the size-based tumor staging systems recommended by the new 8th Edition of the American Joint Committee on Cancer (AJCC) Cancer Staging Manual. Moreover, new concerns have been raised regarding how to best evaluate margin status and lymph nodes. Studies have shown that different Whipple grossing methods can significantly impact margin assessment and lymph node yield and thus affect R0/R1 status and clinical stage. Other important issues under debate include nomenclature, definitions of margin (versus surface), and R1 status. Consistent Whipple grossing and standardization of reporting will provide better communication and more accurate diagnosis and staging, as well as prognostic prediction.
TOPSIS Method for Probabilistic Linguistic MAGDM with Entropy Weight and Its Application to Supplier Selection of New Agricultural Machinery Products
Authors: Lu Jianping , Wei Cun , Wu Jiang , Wei Guiwu
Published: September 2019

In multiple attribute group decision making (MAGDM) problems, uncertain decision information is well-represented by linguistic term sets (LTSs). These LTSs are easily converted into probabilistic linguistic sets (PLTSs). In this paper, a TOPSIS method is proposed for probabilistic linguistic MAGDM in which the attribute weights are completely unknown, and the decision information is in the form of probabilistic linguistic numbers (PLNs). First, the definition of the scoring function is used to solve the probabilistic linguistic entropy, which is then employed to objectively derive the attribute weights. Second, the optimal alternatives are determined by calculating the shortest distance from the probabilistic linguistic positive ideal solution (PLPIS) and on the other side the farthest distance of the probabilistic linguistic negative ideal solution (PLNIS). This proposed method extends the applications range of the traditional entropy-weighted method. Moreover, it doesn’t need the decision-maker to give the attribute weights in advance. Finally, a numerical example for supplier selection of new agricultural machinery products is used to illustrate the use of the proposed method. The result shows the approach is simple, effective and easy to calculate. The proposed method can contribute to the selection of suitable alternative successfully in other selection problems.
Hardware Support to Minimize the End-to-End Delay in Ethernet-Based Ring Networks
Authors: P. Corrêa Tomás , Almeida Luis
Published: September 2019

Ethernet is a popular networking technology in factory automation and industrial embedded systems, frequently using a ring topology for improved fault-tolerance. As many applications demand ever shorter cycle times and a higher number of nodes, the popular ring endure to remain as a valid topology. In this work, we discuss the factors that determine the ring network delay and show how they affect the network cycle time. Since increasing the link capacity has limited reach, we explore a time-triggered protocol that brings the nodes forwarding delay near to the physical layer delay. Additionally, we propose hardware accelerators based on FPGA technology that minimise the packet reception delay from physical reception to delivery to an application handler, preserving Ethernet layers and being compatible with its standard. This paper explains the accelerators concept and implementation, presents measurements using standard Media Access Control implementations, and shows the solution effectiveness with experimental results. We achieved a delay, from physical reception to the triggering of a user-level handler, of 1.1 µs independent of the packet length.
Review of the Comprehensive SAR Approach to Identify Scattering Mechanisms of Radar Backscatter from Vegetated Terrain
Authors: Arii Motofumi , Yamada Hiroyoshi , Kojima Shoichiro , Ohki Masato
Published: September 2019

In a field of polarimetric synthetic aperture radar (SAR) remote sensing, various kinds of polarimetric decomposition techniques have been proposed. However, poor validations prevent them from operational applications. A true composition ratio of scattering mechanisms within a radar backscatter plays a key role. To overcome the issue, a novel comprehensive SAR approach to accurately identify a contribution of each scattering mechanism has been introduced. This is based on multiparametric SAR observation combined with a numerical model simulation. In this article, a comprehensive SAR approach is concisely reviewed to accelerate the research in this field. First, popular model-based polarimetric decompositions are introduced and their limitations are shown. Then, a behavior of scattering mechanisms is analyzed by the discrete scatterer model with some results using real multiparametric SAR data. A comprehensive SAR approach must be essential to realize an operational use of polarimetric SAR data.
Min-Max Predictive Control of a Five-Phase Induction Machine
Authors: Ramirez Daniel R. , Martin Cristina , Kowal G. Agnieszka , Arahal Manuel R.
Published: September 2019

In this paper, a fuzzy-logic based operator is used instead of a traditional cost function for the predictive stator current control of a five-phase induction machine (IM). The min-max operator is explored for the first time as an alternative to the traditional loss function. With this proposal, the selection of voltage vectors does not need weighting factors that are normally used within the loss function and require a cumbersome procedure to tune. In order to cope with conflicting criteria, the proposal uses a decision function that compares predicted errors in the torque producing subspace and in the x-y subspace. Simulations and experimental results are provided, showing how the proposal compares with the traditional method of fixed tuning for predictive stator current control.
Biodiesel Production from Reutealis Trisperma Oil Using KOH Impregnated Eggshell as a Heterogeneous Catalyst
Authors: Kusmiyati Kusmiyati , Prasetyoko Didik , Murwani Siwi , Nur Fadhilah Muthiah , Oetami Titie Prapti , Hadiyanto Hadiyanto , Widayat Widayat , Budiman Arief , Roesyadi Achmad
Published: September 2019

This research paper describes the synthesis of a heterogeneous catalyst (Potassium hydroxide (KOH)-impregnated eggshell) from waste chicken eggshell using the wet impregnation technique. In this experiment, the catalyst was derived from eggshell that was calcined at 800 °C for 5 h. It was impregnated with KOH at various KOH concentrations (10%, 15%, 20%, and 25%). The best catalyst was obtained by eggshell impregnated with 20% KOH concentration. This result was supported by the analysis of the catalyst characterization using Fourier-transform infrared spectrometry (FT-IR), which showed that the catalyst contained CaCO3 and CaOH groups. X-ray fluorescence analysis (XRF) was also used to analyze the types of mineral contained in the catalyst, including calcium, potassium, sulfur, and other impurities. It revealed that the optimum minerals were found in the KOH-impregnated eggshell (20%) catalyst of 94.42% calcium, 5.06% potassium, and a small amount of other impurities. These optimum minerals serve as active sites to increase the biodiesel yield. Scanning electron microscopy (SEM) showed that the catalyst samples appear as small, spherical, homogenous, and solid particles. The catalytic activity was investigated by the transesterification of Reutalism trisperma oil in various types of catalyst (KOH-impregnated eggshell, eggshell, and KOH-impregnated CaO), percentages of catalyst loading (weight of 1%, 3%, 5%, 7%, and 10%) and molar ratios (methanol to oil of 6:1, 8:1, 10:1, 12:1, and 15:1) for 60 min at 60 °C. The result indicated the optimum catalyst loading was 5 wt% with an 84.57% biodiesel yield. While the best molar ratio was 12:1 (methanol:oil) with a 97.95% biodiesel yield. The optimum condition was gained using a molar ratio of 12:1, 5 wt% catalyst loading, and KOH-impregnated eggshell with a 94% biodiesel yield.
Analysing the Energy Efficiency of EU Member States: The Potential of Energy Recovery from Waste in the Circular Economy
Authors: Halkos George , Petrou Kleoniki Natalia
Published: September 2019

This paper examines energy efficiency across 28 selected European Union (EU) Member States and reviews the potential for energy recovery from waste according to the efficiency scores obtained. The efficiencies are assessed through data envelopment analysis (DEA) and the following variables are used, inputs: final energy consumption, labour, capital, population density and outputs: gross domestic product (GDP), nitrogen oxide (NOx) emissions, sulphur oxide (SOx) emissions and greenhouse gas (GHG) emissions for the years 2008, 2010, 2012, 2014 and 2016. Results show that most countries maintain their efficiency scores with only a few marginally improving theirs and at the same time, it is noticed that most are decreasing after 2012. Based on these efficiency scores, this paper recommends moving towards waste-to-energy with two main objectives, namely sufficient and sustainable energy production and effective treatment of municipal solid waste (MSW). This option would enhance the circular economy, whereas prioritization needs to be given to prevention, preparation for reuse, recycling and energy recovery through to disposal. Together with the EU Commission’s competition strategy, these options would ensure reliable energy supplies at rational prices and with the least environmental impacts. Moreover the efficiency scores need to be examined along the financial crisis which has been affecting the EU since 2008, showing a decrease in those efficiency scores after 2012 under a more imminent crisis.
The Benefits of Variable Speed Operation in Hydropower Plants Driven by Francis Turbines
Authors: Bortoni Edson , Souza Zulcy de , Viana Augusto , Villa-Nova Helcio , Rezek Ângelo , Pinto Luciano , Siniscalchi Roberto , Bragança Rafael , Bernardes José
Published: September 2019

Climate change and environmental degradation has resulted in a reduction in water inflow at hydropower plants, as well as a decrease in reservoir levels. Existing hydropower plants suffer from water head reduction, mainly with decrease in efficiency of energy conversion in hydro turbines. This paper showcases the benefits of operations with variable speed in existing hydropower plants, when working at a lower water head than the rated one. Theoretical analyses and tests were performed in a special constructed laboratorial setup aiming at evaluating the amount of efficiency recovery with variable speed operation. Connection alternatives for a constant frequency grid and applications of the learned concepts in an existent hydropower plant are presented. The investigations were applied to the Furnas hydropower plant. The results point out that economic feasibility of the application can be achieved.
DBSCAN Clustering Algorithms for Non-Uniform Density Data and Its Application in Urban Rail Passenger Aggregation Distribution
Authors: Li Xiaolu , Zhang Peng , Zhu Guangyu
Published: September 2019

With the emergence of all kinds of location services applications, massive location data are collected in real time. A hierarchical fast density clustering algorithm, DBSCAN(density based spatial clustering of applications with noise) algorithm based on Gauss mixture model, is proposed to detect clusters and noises of arbitrary shape in location data. First, the gaussian mixture model is used to fit the probability distribution of the dataset to determine different density levels; then, based on the DBSCAN algorithm, the subdatasets with different density levels are locally clustered, and at the same time, the appropriate seeds are selected to complete the cluster expansion; finally, the subdatasets clustering results are merged. The method validates the clustering effect of the proposed algorithm in terms of clustering accuracy, different noise intensity and time efficiency on the test data of public data sets. The experimental results show that the clustering effect of the proposed algorithm is better than traditional DBSCAN. In addition, the passenger flow data of the night peak period of the actual site is used to identify the uneven distribution of passengers in the station. The result of passenger cluster identification is beneficial to the optimization of service facilities, passenger organization and guidance, abnormal passenger flow evacuation.
A New Bursting Liability Evaluation Index for Coal –The Effective Elastic Strain Energy Release Rate
Authors: LU Zhiguo , JU Wenjun , GAO Fuqiang , FENG Youliang , SUN Zhuoyue , WANG Hao , YI Kang
Published: September 2019

Because both faults and cleats exist in coal, sharp stress drops occur during loading when coal is deformed. These drops occur during the pre-peak stage and are accompanied by sudden energy releases. After a stress drop, the stress climbs slowly following a zigzag path and the energy accumulated during the pre-peak stage is unstable. A stress–strain curve is the basic tool used to evaluate the bursting liability of coal. Based on energy accumulation in an unsteady state, the pre-peak stress–strain curve is divided into three stages: pre-extreme, stress drop, and re-rising stage. The energy evolution of the specimen during each stage is analyzed. In this paper, an index called the effective elastic strain energy release rate (EESERR) index is proposed and used to evaluate the coal’s bursting liability. The paper shows that the propagation and coalescence of cracks is accompanied by energy release. The stress climb following a zigzag path prolongs the plastic deformation stage. This causes a significant difference between the work done by a hydraulic press during a laboratory uniaxial compression experiment and the elastic strain energy stored in the specimen during the experiment, so the evaluation result of the burst energy index would be too high. The determination of bursting liability is a comprehensive evaluation of the elastic strain energy accumulated in coal that is released when the specimen is damaged. The index proposed in this paper fully integrates the energy evolution of coal samples being damaged by loading, the amount of elastic strain energy released during the sample failure divided by the failure time is the energy release rate. The calculation method is simplified so that the uniaxial compressive strength and elastic modulus are included which makes the new index more universal and comprehensive. Theoretical analysis and physical compression experiments validate the reliability of the evaluation.
Submission of a WECC DFIG Wind Turbine Model to Spanish Operation Procedure 12.3
Authors: Jiménez-Buendía Francisco , Villena-Ruiz Raquel , Honrubia-Escribano Andrés , Molina-García Ángel , Gómez-Lázaro Emilio
Published: September 2019

Power systems are currently witnessing a high wind-power penetration due to the development and commissioning of an increasing number of wind-power plants. This new scenario inevitably changes the way power systems are operated, mainly due to the uncertainties associated with wind, with the proper integration of this renewable energy source into the grid emerging as a new challenge. Unlike other highly flexible energy sources that can be used on demand according to the market needs, wind energy production is intermittent and non-dispatchable. In this context, transient stability analyses through the dynamic simulation of wind-turbine models and wind-power plants must be carried out. Moreover, as many countries have their own grid codes, the compliance requirements to connect wind farms to the network may be significantly different, depending on the specific region. In light of the above, this paper addresses the submission to Spanish Operation Procedure 12.3 (PO 12.3), for the first time, of one of the most advanced wind-turbine models, the generic Type 3 or doubly fed induction generator defined by the Western Electricity Coordinating Council (WECC) Second-Generation guidelines. The results show, on the one hand, the notable effect of the transformer inrush current, which influences the accuracy of the behavior of the generic wind-turbine model, and, on the other hand, the inability of the generic model to represent the transient periods of actual wind turbines. However, when the validation criteria is applied at the low-voltage measurement point, the WECC model fully complies with Spanish grid code PO 12.3.
Polymer Gels Made with Functionalized Organo-Silica Nanomaterials for Conformance Control
Authors: Najafiazar Bahador , Wessel-Berg Dag , Bergmo Per Eirik , Simon Christian Rone , Yang Juan , Torsæter Ole , Holt Torleif
Published: September 2019

Deep placement of gel in waterflooded hydrocarbon reservoirs may block channels with high water flow and may divert the water into other parts of the reservoir, resulting in higher oil production. In order to get the gel constituents to the right reservoir depths, a delay in the gelling time in the order of weeks at elevated temperatures will be necessary. In this work, a methodology for controlled gelation of partially hydrolyzed polyacrylamide using hybrid nanomaterials with functional groups as cross-linkers was developed. Two delay mechanisms with hybrid materials and polyelectrolyte complexes were designed and tested. Both mechanisms could significantly delay the gelation rate, giving gelling times ranging from several days to several weeks in synthetic sea water at 80 °C. Gelling experiments in sandstone cores showed that gel strength increased with aging time. For long aging times, strong gels were formed which resulted in almost no water permeability. A series of coreflooding experiments with polymer and deactivated nanomaterial were performed. In addition to differential pressures and concentration profiles, the experiments enabled calculation of retention and inaccessible pore volumes. A novel numerical model of 1D two-phase flow has been developed and tested with results from core flooding experiments. The model can track the age distribution and concentrations of the nanomaterial (and therefore water viscosity) throughout the porous medium at every time step. The model generated a good fit of experimental results.
Identifying Biases in Global Tree Cover Products: A Case Study in Costa Rica
Authors: Cunningham Daniel , Cunningham Paul , Fagan Matthew E.
Published: September 2019

Global tree cover products are widely used in analyses of deforestation, fragmentation, and connectivity, but are rarely critically assessed. Inaccuracies in these products could have consequences for future decision making, especially in data-poor regions like the tropics. In this study, potential biases in global and regional tree cover products were assessed across a diverse tropical country, Costa Rica. Two global tree cover products and one regional national forest cover map were evaluated along biophysical gradients in elevation, precipitation, and agricultural land cover. To quantify product accuracy and bias, freely available high-resolution imagery was used to validate tree and land cover across these gradients. Although the regional forest cover map was comparable in accuracy to a widely-used global forest map (the Global Forest Change of Hansen et al., also known as the GFC), another global forest map (derived from a cropland dataset) had the highest accuracy. Both global and regional forest cover products showed small to severe biases along biophysical gradients. Unlike the regional map, the global GFC map strongly underestimated tree cover (>10% difference) below 189 mm of precipitation and at elevations above 2000 m, with a larger bias for precipitation. All map products misclassified agricultural fields as forest, but the GFC product particularly misclassified row crops and perennial erect crops (banana, oil palm, and coffee), with maximum tree cover in agricultural fields of 89%–100% across all crops. Our analysis calls into further question the utility of the GFC product for global forest monitoring outside humid regions, indicating that, in tropical regions, the GFC product is most accurate in areas with high, aseasonal rainfall, low relief, and low cropland area. Given that forest product errors are spatially distributed along biophysical gradients, researchers should account for these spatial biases when attempting to analyze or generate forest map products.
Learning (Not) to Evade Taxes
Authors: Prinz Aloys
Published: September 2019

In this paper, lab experiments on tax compliance were theoretically investigated with dynamic and stochastic methods. It is well known from experimental games that learning allows a better understanding of participants’ behavior. However, it has not been explicitly applied so far in the theoretical analysis of tax compliance experiments. In this paper, it was shown that two decision-making processes may be distinguished: a discrete process in which all options are regarded and an all-or-nothing process in which either the respective tax is paid fully or not at all. The corresponding variant of the learning model was either a stochastic or a deterministic one, with the stochastic version as the more general model. In the additional empirical part of the paper, it was shown that tax payments decline in trend over the rounds of the considered experiment. This negative trend was interpreted as a learning effect, in accordance with the stochastic version of the theoretical model. However, the alternative interpretation that the observed behavior was driven by a tiring effect cannot be completely excluded.
Integration of Bioinformatics Resources Reveals the Therapeutic Benefits of Gemcitabine and Cell Cycle Intervention in SMAD4-Deleted Pancreatic Ductal Adenocarcinoma
Authors: Hsieh Yao-Yu , Liu Tsang-Pai , Chou Chia-Jung , Chen Hsin-Yi , Lee Kuen-Haur , Yang Pei-Ming
Published: September 2019

Pancreatic ductal adenocarcinoma (PDAC) is the most common and aggressive type of pancreatic cancer. The five-year survival rate of PDAC is very low (less than 8%), which is associated with the late diagnosis, high metastatic potential, and resistance to therapeutic agents. The identification of better prognostic or therapeutic biomarker may have clinical benefits for PDAC treatment. SMAD4, a central mediator of transforming growth factor beta (TGFβ) signaling pathway, is considered a tumor suppressor gene. SMAD4 inactivation is frequently found in PDAC. However, its role in prognosis and therapeutics of PDAC is still unclear. In this study, we applied bioinformatics approaches, and integrated publicly available resources, to investigate the role of SMAD4 gene deletion in PDAC. We found that SMAD4 deletion was associated with poorer disease-free, but not overall, survival in PDAC patients. Cancer hallmark enrichment and pathway analysis suggested that the upregulation of cell cycle-related genes in SMAD4-deleted PDAC. Chemotherapy response profiling of PDAC cell lines and patient-derived organoids revealed that SMAD4-deleted PDAC was sensitive to gemcitabine, the first-line treatment for PDAC, and specific cell cycle-targeting drugs. Taken together, our study provides an insight into the prognostic and therapeutic roles of SMAD4 gene deletion in PDAC, and SMAD4 gene copy numbers may be used as a therapeutic biomarker for PDAC treatment.
Integrating Geovisual Analytics with Machine Learning for Human Mobility Pattern Discovery
Authors: Zhang Tong , Wang Jianlong , Cui Chenrong , Li Yicong , He Wei , Lu Yonghua , Qiao Qinghua
Published: September 2019

Understanding human movement patterns is of fundamental importance in transportation planning and management. We propose to examine complex public transit travel patterns over a large-scale transit network, which is challenging since it involves thousands of transit passengers and massive data from heterogeneous sources. Additionally, efficient representation and visualization of discovered travel patterns is difficult given a large number of transit trips. To address these challenges, this study leverages advanced machine learning methods to identify time-varying mobility patterns based on smart card data and other urban data. The proposed approach delivers a comprehensive solution to pre-process, analyze, and visualize complex public transit travel patterns. This approach first fuses smart card data with other urban data to reconstruct original transit trips. We use two machine learning methods, including a clustering algorithm to extract transit corridors to represent primary mobility connections between different regions and a graph-embedding algorithm to discover hierarchical mobility community structures. We also devise compact and effective multi-scale visualization forms to represent the discovered travel behavior dynamics. An interactive web-based mapping prototype is developed to integrate advanced machine learning methods with specific visualizations to characterize transit travel behavior patterns and to enable visual exploration of transit mobility patterns at different scales and resolutions over space and time. The proposed approach is evaluated using multi-source big transit data (e.g., smart card data, transit network data, and bus trajectory data) collected in Shenzhen City, China. Evaluation of our prototype demonstrates that the proposed visual analytics approach offers a scalable and effective solution for discovering meaningful travel patterns across large metropolitan areas.
The Role of Adipokines as Circulating Biomarkers in Critical Illness and Sepsis
Authors: Loosen Sven H. , Koch Alexander , Tacke Frank , Roderburg Christoph , Luedde Tom
Published: September 2019

Sepsis represents a major global health burden. Early diagnosis of sepsis as well as guiding early therapeutic decisions in septic patients still represent major clinical challenges. In this context, a whole plethora of different clinical and serum-based markers have been tested regarding their potential for early detection of sepsis and their ability to stratify patients according to their probability to survive critical illness and sepsis. Adipokines represent a fast-growing class of proteins that have gained an increasing interest with respect to their potential to modulate immune responses in inflammatory and infectious diseases. We review current knowledge on the role of different adipokines in diagnostic work-up and risk stratification of sepsis as well as critical illness. We discuss recent data from animal models as well as from clinical studies and finally highlight the limitations of these analyses that currently prevent the use of adipokines as biomarkers in daily practice.
Skin Doctor: Machine Learning Models for Skin Sensitization Prediction that Provide Estimates and Indicators of Prediction Reliability
Authors: Wilm Anke , Stork Conrad , Bauer Christoph , Schepky Andreas , Kühnl Jochen , Kirchmair Johannes
Published: September 2019

The ability to predict the skin sensitization potential of small organic molecules is of high importance to the development and safe application of cosmetics, drugs and pesticides. One of the most widely accepted methods for predicting this hazard is the local lymph node assay (LLNA). The goal of this work was to develop in silico models for the prediction of the skin sensitization potential of small molecules that go beyond the state of the art, with larger LLNA data sets and, most importantly, a robust and intuitive definition of the applicability domain, paired with additional indicators of the reliability of predictions. We explored a large variety of molecular descriptors and fingerprints in combination with random forest and support vector machine classifiers. The most suitable models were tested on holdout data, on which they yielded competitive performance (Matthews correlation coefficients up to 0.52; accuracies up to 0.76; areas under the receiver operating characteristic curves up to 0.83). The most favorable models are available via a public web service that, in addition to predictions, provides assessments of the applicability domain and indicators of the reliability of the individual predictions.
Anti-Myocardial Infarction Effects of Radix Aconiti Lateralis Preparata Extracts and Their Influence on Small Molecules in the Heart Using Matrix-Assisted Laser Desorption/Ionization–Mass Spectrometry Imaging
Authors: Wu Hao , Liu Xi , Gao Ze-yu , Dai Zhen-feng , Lin Ming , Tian Fang , Zhao Xin , Sun Yi , Pu Xiao-ping
Published: September 2019

Radix Aconiti Lateralis Preparata (fuzi) is the processed product of Aconitum carmichaelii Debeaux tuber, and has great potential anti-myocardial infarction effects, including improving myocardial damage and energy metabolism in rats. However, the effects of Radix Aconiti Lateralis Preparata extracts in a rat model of myocardial infarction have not yet been fully illustrated. Herein, Radix Aconiti Lateral Preparata was used to prepare Radix Aconiti Lateralis Preparata extract (RAE), fuzi polysaccharides (FPS), and fuzi total alkaloid (FTA). Then, we aimed to compare the effects of RAE, FPS, and FTA in MI rats and further explore their influence on small molecules in the heart. We reported that Radix Aconiti Lateralis Preparata extract (RAE) and fuzi total alkaloid (FTA) significantly improved left ventricular function and structure, and reduced myocardial damage and infarct size in rats with myocardial infarction by the left anterior descending artery ligation. In contrast, fuzi polysaccharides (FPS) was less effective than RAE and FTA, indicating that alkaloids might play a major role in the treatment of myocardial infarction. Moreover, via matrix-assisted laser desorption/ionization–mass spectrometry imaging (MALDI–MSI), we further showed that RAE and FTA containing alkaloids as the main common components regulated myocardial energy metabolism-related molecules and phospholipids levels and distribution patterns against myocardial infarction. In particular, it was FTA, not RAE, that could also regulate potassium ions and glutamine to play a cardioprotective role in myocardial infarction, which revealed that an appropriate dose of alkaloids generated more obvious cardiotonic effects. These findings together suggested that Radix Aconiti Lateralis Preparata extracts containing an appropriate dose of alkaloids as its main pharmacological active components exerted protective effects against myocardial infarction by improving myocardial energy metabolism abnormalities and changing phospholipids levels and distribution patterns to stabilize the cardiomyocyte membrane structure. Thus, RAE and FTA extracted from Radix Aconiti Lateralis Preparata are potential candidates for the treatment of myocardial infarction.
Analysis of Interacting Proteins of Aluminum Toxicity Response Factor ALS3 and CAD in Citrus
Authors: Wu Yan-Mei , Wang Yan-Yu , Zhou Yang-Fei , Meng Xin , Huang Zeng-Rong , Chen Li-Song , Yang Lin-Tong
Published: September 2019

Aluminum (Al) treatment significantly decreased the dry weight (DW) of stem, shoot and whole plant of both Citrus sinensis and C. grandis, but did not change that of root. Al significantly decreased leaf DW of C. grandis, increased the ratio of root to shoot and the lignin content in roots of both species. The higher content of Al in leaves and stems and lignin in roots of C. grandis than that of C. sinensis might be due to the over-expression of Al sensitive 3 (ALS3) and cinnamyl alcohol deaminase (CAD) in roots of C. grandis, respectively. By using yeast-two-hybridazation (Y2H) and bimolecular fluorescence complementation (BiFC) techniques, we obtained the results that glutathione S-transferase (GST), vacuolar-type proton ATPase (V-ATPase), aquaporin PIP2 (PIP2), ubiquitin carboxyl-terminal hydrolase 13 (UCT13), putative dicyanin blue copper protein (DCBC) and uncharacterized protein 2 (UP2) were interacted with ALS3 and GST, V-ATPase, Al sensitive 3 (ALS3), cytochrome P450 (CP450), PIP2, uncharacterized protein 1 (UP1) and UP2 were interacted with CAD. Annotation analysis revealed that these proteins were involved in detoxification, cellular transport, post-transcriptional modification and oxidation-reduction homeostasis or lignin biosynthesis in plants. Real-time quantitative PCR (RT-qPCR) analysis further revealed that the higher gene expression levels of most of these interacting proteins in C. grandis roots than that in C. sinensis ones were consistent with the higher contents of lignin in C. grandis roots and Al absorbed by C. grandis. In conclusion, our study identified some key interacting components of Al responsive proteins ALS3 and CAD, which could further help us to understand the molecular mechanism of Al tolerance in citrus plants and provide new information to the selection and breeding of tolerant cultivars, which are cultivated in acidic areas.
MYB Gene Family in Potato (Solanum tuberosum L.): Genome-Wide Identification of Hormone-Responsive Reveals Their Potential Functions in Growth and Development
Authors: Sun Wenjun , Ma Zhaotang , Chen Hui , Liu Moyang
Published: September 2019

As an important nongrain crop, the growth and yield of potato (Solanum tuberosum L.) is often affected by an unfavorable external environment in the process of cultivation. The MYB family is one of the largest and most important gene families, participating in the regulation of plant growth and development and response to abiotic stresses. Several MYB genes in potato that regulate anthocyanin synthesis and participate in abiotic stress responses have been identified. To identify all Solanum tuberosum L. MYB (StMYB) genes involved in hormone or stress responses to potentially regulate potato growth and development, we identified the MYB gene family at the genome-wide level. In this work, 158 StMYB genes were found in the potato genome. According to the amino acid sequence of the MYB domain and gene structure, the StMYB genes were divided into R2R3-MYB and R1R2R3-MYB families, and the R2R3-MYB family was divided into 20 subgroups (SGs). The expression of 21 StMYB genes from different SGs in roots, stems, leaves, flowers, shoots, stolons, young tubers, and mature tubers was determined by quantitative real-time polymerase chain reaction (qRT-PCR). The expression patterns of StMYB genes in potatoes treated with abscisic acid (ABA), indole-3-acetic acid (IAA), gibberellin acid 3 (GA3), NaCl, mannitol, and heat were also measured. We have identified several potential candidate genes that regulate the synthesis of potato flavonoids or participate in hormone or stress responses. This work provides a comprehensive understanding of the MYB family in potato and will lay a foundation for the future investigation of the potential functions of StMYB genes in the growth and development of potato.
Protective Role of Leaf Variegation in Pittosporum tobira under Low Temperature: Insights into the Physio-Biochemical and Molecular Mechanisms
Authors: Zhang Zhilu , Liu Zhonghua , Song Haina , Chen Minghui , Cheng Shiping
Published: September 2019

Leaf variegation has been demonstrated to have adaptive functions such as cold tolerance. Pittosporum tobira is an ornamental plant with natural leaf variegated cultivars grown in temperate regions. Herein, we investigated the role of leaf variegation in low temperature responses by comparing variegated “Variegatum” and non-variegated “Green Pittosporum” cultivars. We found that leaf variegation is associated with impaired chloroplast development in the yellow sector, reduced chlorophyll content, strong accumulation of carotenoids and high levels of ROS. However, the photosynthetic efficiency was not obviously impaired in the variegated leaves. Also, leaf variegation plays low temperature protective function since “Variegatum” displayed strong and efficient ROS-scavenging enzymatic systems to buffer cold (10 °C)-induced damages. Transcriptome analysis under cold conditions revealed 309 differentially expressed genes between both cultivars. Distinctly, the strong cold response observed in “Variegatum” was essentially attributed to the up-regulation of HSP70/90 genes involved in cellular homeostasis; up-regulation of POD genes responsible for cell detoxification and up-regulation of FAD2 genes and subsequent down-regulation of GDSL genes leading to high accumulation of polyunsaturated fatty acids for cell membrane fluidity. Overall, our results indicated that leaf variegation is associated with changes in physiological, biochemical and molecular components playing low temperature protective function in P. tobira.
CDDO-Me Attenuates Vasogenic Edema and Astroglial Death by Regulating NF-κB p65 Phosphorylations and Nrf2 Expression Following Status Epilepticus
Authors: Kim Min-Ju , Park Hana , Choi Seo-Hyeon , Kong Min-Jeong , Kim Ji-Eun , Kang Tae-Cheon
Published: September 2019

2-Cyano-3,12-dioxo-oleana-1,9(11)-dien-28-oic acid methyl ester (CDDO-Me) is a triterpenoid analogue of oleanolic acid that has anti-inflammatory, antioxidant, and neuroprotective activities. In the present study, we evaluate the effects of CDDO-Me on serum extravasation and astroglial death in the rat piriform cortex (PC) induced by status epilepticus (a prolonged seizure activity, SE) in order to propose an underlying pharmacological mechanism of CDDO-Me and its availability for treatment of vasogenic edema. CDDO-Me effectively mitigated serum extravasation and a massive astroglial loss in the PC following SE. CDDO-Me abrogated tumor necrosis factor-α (TNF-α) synthesis in activated microglia by inhibiting nuclear factor-κB (NF-κB) p65 serine 276 phosphorylation. CDDO-Me also abolished NF-κB threonine 435 phosphorylation in endothelial cells and TNF-α-mediated-phosphatidylinositol-3-kinase (PI3K)/AKT/endothelial nitric oxide synthase (eNOS) signaling cascades, which trigger vasogenic edema following SE. Furthermore, CDDO-Me increased astroglial viability via the up-regulation of nuclear factor-erythroid 2-related factor 2 (Nrf2) expression. Therefore, our findings suggest that CDDO-Me may ameliorate SE-induced vasogenic edema formation by regulating NF-κB p65 phosphorylations in microglia as well as endothelial cells and enhancing Nrf2 expression in astrocytes, respectively.
Polymeric Systems as Antimicrobial or Antifouling Agents
Authors: Francolini Iolanda , Piozzi Antonella
Published: September 2019

The rapid increase in the emergence of antibiotic-resistant bacterial strains combined with a dwindling rate of discovery of novel antibiotic molecules has lately created an alarming issue worldwide [...]
Human Leukocyte Antigen and Red Blood Cells Impact Umbilical Cord Blood CD34+ Cell Viability after Thawing
Authors: Vanegas Diana , Galindo Cristian-Camilo , Páez-Gutiérrez Iván-Aurelio , González-Acero Lorena-Xiomara , Medina-Valderrama Pavel-Tiberio , Lozano Juan-Camilo , Camacho-Rodríguez Bernardo , Perdomo-Arciniegas Ana-María
Published: September 2019

Hematopoietic progenitor cell (HPC) transplantation is a treatment option for malignant and nonmalignant diseases. Umbilical cord blood (UCB) is an important HPC source, mainly for pediatric patients. It has been demonstrated that human leukocyte antigen (HLA) matching and cell dose are the most important features impacting clinical outcomes. However, UCB matching is performed using low resolution HLA typing and it has been demonstrated that the unnoticed mismatches negatively impact the transplant. Since we found differences in CD34+ viability after thawing of UCB units matched for two different patients (p = 0.05), we presumed a possible association between CD34+ cell viability and HLA. We performed a multivariate linear model (n = 67), comprising pre-cryopreservation variables and high resolution HLA genotypes separately. We found that pre-cryopreservation red blood cells (RBC), granulocytes, and viable CD34+ cell count significantly impacted CD34+ viability after thawing, along with HLA-B or -C (R2 = 0.95, p = 0.01; R2 = 0.56, p = 0.007, respectively). Although HLA-B*40:02 may have a negative impact on CD34+ cell viability, RBC depletion significantly improves it.
Multivariate Maps—A Glyph-Placement Algorithm to Support Multivariate Geospatial Visualization
Authors: McNabb Liam , Laramee Robert S.
Published: September 2019

Maps are one of the most conventional types of visualization used when conveying information to both inexperienced users and advanced analysts. However, the multivariate representation of data on maps is still considered an unsolved problem. We present a multivariate map that uses geo-space to guide the position of multivariate glyphs and enable users to interact with the map and glyphs, conveying meaningful data at different levels of detail. We develop an algorithm pipeline for this process and demonstrate how the user can adjust the level-of-detail of the resulting imagery. The algorithm features a unique combination of guided glyph placement, level-of-detail, dynamic zooming, and smooth transitions. We present a selection of user options to facilitate the exploration process and provide case studies to support how the application can be used. We also compare our placement algorithm with previous geo-spatial glyph placement algorithms. The result is a novel glyph placement solution to support multi-variate maps.
Morphology and Structural Stability of Bismuth-Gadolinium Co-Doped Ceria Electrolyte Nanopowders
Authors: Accardo Grazia , Spiridigliozzi Luca , Dell’Agli Gianfranco , Yoon Sung Pil , Frattini Domenico
Published: September 2019

The reduction of the sintering temperature of doped ceria ceramics remains an open challenge for their real exploitation as electrolytes for intermediate temperature solid oxide fuel cell (IT-SOFCs) at the industrial level. In this work, we have used Bi (0.5 and 2 mol %) as the sintering aid for Gd (20 mol %)-doped ceria. Nano-sized powders of Bi/Gd co-doped ceria were easily synthesized via a simple and cheap sol-gel combustion synthesis. The obtained powders showed high sinterability and very good electrochemical properties. More importantly, even after prolonged annealing at 700 °C, both of the powders and of the sintered pellets, no trace of structural modifications, phase instabilities, or Bi segregation appeared. Therefore, the use of a small amount of Bi can be taken into account for preparing ceria-based ceramic electrolytes at low sintering temperatures.
The Association between Adult Weight Gain and Insulin Resistance at Middle Age: Mediation by Visceral Fat and Liver Fat
Authors: Verkouter Inge , Noordam Raymond , le Cessie Saskia , van Dam Rob M. , Lamb Hildo J. , Rosendaal Frits R. , van Heemst Diana , de Mutsert Renée
Published: September 2019

We aimed to investigate the role of the amount of visceral fat and liver fat in the association between adult weight change and insulin resistance at middle age. In the Netherlands Epidemiology of Obesity study, adult weight change was calculated with recalled body weight at age 20 years and measured body weight at middle age. Measures of insulin resistance were calculated using both fasting and postprandial glucose and insulin concentrations. Visceral fat was assessed by magnetic resonance (MR) imaging and liver fat by proton-MR spectroscopy (N = 1758). We examined the association between adult weight change and insulin resistance with linear regression, adjusted for confounding factors. To investigate mediation, we additionally adjusted for total body fat, visceral fat, and liver fat. In participants who gained ≥50% of body weight during adulthood, homeostatic model assessment for insulin resistance (HOMA-IR) was 3.22 (95% CI 2.76; 3.77) times higher than in weight maintainers. In a joint model, total body fat mediated this association for 8.1% (95% CI −9.2; 25.4), visceral fat for 32.0% (18.6; 45.4%) and liver fat for 22.5% (15.0; 30.1). The association between adult weight gain and insulin resistance at middle age is largely mediated by both visceral fat and liver fat.
Excellent Islet Yields after 18-h Porcine Pancreas Preservation by Ductal Injection, Pancreas Preservation with MK Solution, Bottle Purification, and Islet Purification Using Iodixanol with UW Solution and Iodixanol with MK Solution
Authors: Kuwae Kazuho , Miyagi-Shiohira Chika , Hamada Eri , Tamaki Yoshihito , Nishime Kai , Sakai Mayuko , Yonaha Tasuku , Makishi Erika , Saitoh Issei , Watanabe Masami , Noguchi Hirofumi
Published: September 2019

Successful islet isolation is the key to successful islet transplantation. Our group recently modified the islet isolation protocol to include pancreatic ductal injection of the preservation solution, pancreas storage in modified extracellular-type trehalose-containing Kyoto (MK) solution, and use of an iodixanol-based purification solution and bottle purification. In this study, we applied these methods to porcine islet isolation after 18-h pancreas preservation and compared two solutions with different compositions in bottle purification. Islet yield before purification was 651,661 ± 157,719 islet equivalents (IE) and 5576 ± 1538 IE/g pancreas weight. An IU solution was made by adding iodixanol to University of Wisconsin solution and an IK solution was made by adding iodixanol to MK solution. The efficacy of the two solutions for islet isolation was compared. There were no significant differences between the two purification methods with regard to islet yield, survival rate, purity, score, or stimulation index. These results indicate that our isolation protocol produces efficient islet yields from prolonged cold-stored pancreas and that IU and IK solutions are equally useful for islet purification.