bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ferroelectric Metal–Organic Framework as a Host Material for Sulfur to Alleviate the Shuttle Effect of Lithium–Sulfur Battery
Authors: Zhu Fulong , Tao Yanli , Bao Hongfei , Wu Xuesong , Qin Chao , Wang Xinlong , Su Zhongmin 
Published: June 2020

AbstractFerroelectricity has an excellent reversible polarization conversion behavior under an external electric field. Herein, we propose an interesting strategy to alleviate the shuttle effect of lithium–sulfur battery by utilizing ferroelectric metal–organic framework (FMOF) as a host material for the first time. Compared to other MOF with same structure but without ferroelectricity and commercial carbon black, the cathode based on FMOF exhibits a low capacity decay and high cycling stability. These results demonstrate that the polarization switching behaviors of FMOF under the discharge voltage of lithium–sulfur battery can effectively trap polysulfides by polar–polar interactions, decrease polysulfides shuttle and improve the electrochemical performance of lithium–sulfur battery.
Multicenter phase 2 trial of nintedanib in advanced nonpancreatic neuroendocrine tumors
Authors: Iyer Renuka V. , Konda Bhavana , Fountzilas Christos , Mukherjee Sarbajit , Owen Dwight , Attwood Kristopher , Wang Chong , Maguire Orla , Minderman Hans , Suffren Sheryl‐Ann , Hicks Karen , Wilton John , Bies Robert , Casucci Danielle , Reidy‐Lagunes Diane , Shah Manisha 
Published: June 2020

BackgroundAntiangiogenic‐targeting agents have low response rates in patients with nonpancreatic neuroendocrine tumors (NETs). Nintedanib is an oral antiangiogenic agent that has inhibitory effects on the fibroblast growth factor receptor, which is highly expressed in NETs. The authors hypothesized that nintedanib would be active in patients with nonpancreatic NETs.MethodsPatients with advanced, grade 1 or 2, nonpancreatic NETs who were receiving a stable dose of somatostatin analogue were enrolled. Nintedanib was administered at a dose of 200 mg twice daily in 28‐day cycles. The primary endpoint was progression‐free survival (PFS) at 16 weeks.ResultsThirty‐two patients were enrolled, and 30 were evaluable for the primary outcome. Most had radiographic disease progression within 12 months before enrollment. The 16‐week PFS rate was 83%, and the median PFS and overall survival were 11.0 months and 32.7 months, respectively. Nintedanib was well tolerated and delayed deterioration in quality of life. The baseline serotonin level had a strong, positive correlation with activated but exhausted T cells.ConclusionsNintedanib is active in nonpancreatic NETs. The immunosuppressive effect of serotonin should be targeted in future clinical trials.
A new method with hybrid direction for linear programming
Authors: Djeloud Khalil , Bentobache Mohand , Bibi Mohand Ouamer 
Published: June 2020

SummaryIn this work, we propose a new algorithm for solving linear programs. This algorithm starts by an initial support feasible solution, then it moves from one feasible point to a better one following a new hybrid direction. The constructed direction gives a better local improvement of the objective function than the direction of the adaptive method with hybrid direction (AMHD) algorithm proposed in Bibi MO, Bentobache M. A hybrid direction algorithm for solving linear programs. International Journal of Computer Mathematics, 2015; 92(2):200‐216. In order to stop the algorithm, a suboptimality criterion is used and the long step rule is developed for changing the current support. The proposed algorithm is implemented with C++, then a numerical study is conducted on randomly generated test problems and some instances of an optimal control problem. The obtained numerical results show that our algorithm is competitive with AMHD and the primal simplex algorithm of GNU linear programming kit (GLPK).
Imaging of Monoamine Neurotransmitters with Fluorescent Nanoscale Sensors
Authors: Dinarvand Meshkat , Elizarova Sofia , Daniel James , Kruss Sebastian 
Published: June 2020

AbstractCells use biomolecules to convey information. For instance, neurons communicate by releasing chemicals called neurotransmitters, including several monoamines. The information transmitted by neurons is, in part, coded in the type and amount of neurotransmitter released, the spatial distribution of release sites, the frequency of release events, and the diffusion range of the neurotransmitter. Therefore, quantitative information about neurotransmitters at the (sub)cellular level with high spatiotemporal resolution is needed to understand how complex cellular networks function. So far, various analytical methods have been developed and used to detect neurotransmitter secretion from cells. However, each method has limitations with respect to chemical, temporal and spatial resolution. In this review, we focus on emerging methods for optical detection of neurotransmitter release and discuss fluorescent sensors/probes for monoamine neurotransmitters such as dopamine and serotonin. We focus on the latest advances in near infrared fluorescent carbon nanotube‐based sensors and engineered fluorescent proteins for monoamine imaging, which provide high spatial and temporal resolution suitable for examining the release of monoamines from cells in cellular networks.
Applied use of alternate stable state modeling in restoration ecology
Authors: Zweig Christa L. , Newman Sue , Saunders Colin J. 
Published: June 2020

AbstractThe concept of alternate stable states is important in ecological theory and models, but the application and implementation of these models have the potential to make significant future advances in the field of patterned landscapes. The bistable ridge and slough landscape is a central feature of Everglades restoration and provides an important opportunity to test stable state theory with multistate transition models. We used these models to estimate environmental parameters associated with state changes (water depths, edaphic factors, etc.) and develop a quantitative method to measure resilience and stability. The multistate model indicates that long‐term, local hydrology (15‐yr mean maximums and 15‐yr mean amplitude) and edaphic factors control the local scale shifts between ridge and slough states. We show that multistate models can provide hydrologic envelopes for managers, produce a tool to help assess future water management scenarios, and address issues of sustainability, resilience, and restoration for any bistable system.
Diabetes mellitus exacerbates post‐myocardial infarction heart failure by reducing sarcolipin promoter methylation
Authors: Liu Zhongwei , Zhang Yong , Qiu Chuan , Zhu Haitao , Pan Shuo , Jia Hao , Kang Hongyan , Guan Gongchang , Hui Rutai , Zhu Ling , Wang Junkui 
Published: June 2020

AbstractAimsSarcolipin (SLN) is a key regulator of sarcoplasmic reticulum calcium‐ATPase (SERCA)2a, which handles intracellular calcium re‐uptake. This study was aimed to investigate the involvement of SLN in post‐myocardial infarction (MI) heart failure (HF) in diabetes.Methods and resultsDiabetes/MI rat models were established. Altered SLN expression in diabetic hearts was screened out by microarray. A myocardiotropic viral vector was used to deliver siRNA to silence SLN. DNA methylation was evaluated by bisulfite sequencing. Cardiac functions were evaluated by invasive haemodynamic examinations. The SERCA2a activity, cytoplasmic calcium concentration ([Ca2+]i), calcium spark, and myocyte contraction were detected. Correlation between HF and diabetes was analysed in a cohort consisted of 101 ST‐segment elevated myocardial infarction (STEMI) patients between 2017 and 2019 [53.54 ± 4.64 years old; 61.4% male gender; HbA1c% 6.15 ± 2.00; and left ventricular ejection fraction (LVEF%) 40.64 ± 3.20%]. SLN expression was evaluated in left ventricular tissue sample from six STEMI patients complicated with diabetes and six STEMI patients without diabetes. Expressions of DNA methyltransferase 1a and DNA methyltransferase 3 were reduced in diabetic hearts, leading to down‐regulation of SLN promoter methylation, resulting in increased SLN expression in rats. Impaired heart systolic functions were found in experimental diabetic MI rats, which were attenuated by SLN silencing. SERCA2a activity reduction and [Ca2+]i elevation were attenuated by SLN silencing in diabetic animal hearts and high‐glucose incubated primary myocytes. SLN silencing suppressed calcium sparks and improved contraction and sarcoplasmic reticulum calcium re‐uptake in high‐glucose incubated primary myocytes. Expression of SLN was up‐regulated in LV sampled from STEMI patients complicated with diabetes compared with non‐diabetic ones (P < 0.05). LVEF% was reduced in STEMI patients complicated with diabetes compared with non‐diabetic ones (P < 0.01). HbA1c% and LVEF% was related (r = −0.218, P = 0.028). Increased HbA1c% was correlated with reduced LVEF% after adjustment for age, sex, body mass index, cigarette smoking, creatinine, UA, low density lipoprotein, K+, Na+, and troponin I (adjusted odds ration = 0.75, 95% confidence interval 0.62–0.90, P = 0.002).ConclusionsDiabetes increases the vulnerability of STEMI patients to post‐MI HF by down‐regulating SLN promoter methylation, which further regulates SERCA2a activity via increasing cardiac SLN expression.
Recent advances of green pretreatment techniques for quality control of natural products
Authors: Du Kun‐ze , Sun A‐li , Yan Chaozhuo , Liang Chunxiao , Qi Lina , Wang Chenhong , Yang Rui , Cui Yan , Shang Ye , Li Jin , Chang Yan‐xu 
Published: June 2020

AbstractA few advancing technologies for natural product analysis have been widely proposed, which focus on decreasing energy consumption and developing an environmentally sustainable manner. These green sample pretreatment and analysis methods following the green Analytical Chemistry (GAC) criteria have the advantage of improving the strategy of chemical analyses, promoting sustainable development to analytical laboratories, and reducing the negative effects of analysis experiments on the environment. A few minimized extraction methodologies have been proposed for replacing the traditional methods in the quality evaluation of natural products, mainly including solid‐phase microextraction (SPME) and liquid phase microextraction (LPME). These procedures not only have no need for large numbers of samples and toxic reagent, but also spend a small amount of extraction and analytical time. This overview aims to list out the main green strategies on the application of quality evaluation and control for natural products in the past 3 years.
A new perspective to the conventional solar pond technology to increase the thermal efficiency
Authors: Sogukpinar Haci 
Published: June 2020

AbstractIn this study, a new perspective was introduced to conventional solar pond technology to spread its commercial application. In order to make it more useful with preserving energy efficiency, the brine layers were replaced with the normal freshwater by using a separated transparent partition. Structurally modified three different solar ponds were proposed and numerical investigations were conducted by using discrete ordinate method (DOM). For this, four types of solar ponds were modeled, the first one is the conventional salt‐gradient solar pond and three others are modified versions which are named as “Pure Water Solar Pond.” For all models, a comprehensive finite element method was developed to investigate the daily performance of solar ponds by using commercial software COMSOL. Salt‐gradient solar pond consists of seven layers where one layer is the heat storage zone, five layers are nonconvective zone, and one is the upper convective zone. However, in the modified models, solar ponds consist of two glass layers and one to three pure water zones depending on the model types. The numerical method includes a novel approach to calculate all the zone where absorption, emission, scattering, transmission, convection, and radiation are taken into account. Numerical results for all models were compared with an experiment to correlate the numerical accuracy of the DOM with anisotropic scattering phase function. Results indicate there is a good correlation between these four model approach and the experiment.
Primary Sources of Polycyclic Aromatic Hydrocarbons to Streambed Sediment in Great Lakes Tributaries Using Multiple Lines of Evidence
Authors: Baldwin Austin K. , Corsi Steven R. , Oliver Samantha K. , Lenaker Peter L. , Nott Michelle A. , Mills Marc A. , Norris Gary A. , Paatero Pentti 
Published: June 2020

Abstract
Polycyclic aromatic hydrocarbons (PAHs) are among the most widespread and potentially toxic contaminants in Great Lakes (USA/Canada) tributaries. The sources of PAHs are numerous and diverse, and identifying the primary source(s) can be difficult. The present study used multiple lines of evidence to determine the likely sources of PAHs to surficial streambed sediments at 71 locations across 26 Great Lakes Basin watersheds. Profile correlations, principal component analysis, positive matrix factorization source-receptor modeling, and mass fractions analysis were used to identify potential PAH sources, and land-use analysis was used to relate streambed sediment PAH concentrations to different land uses. Based on the common conclusion of these analyses, coal-tar–sealed pavement was the most likely source of PAHs to the majority of the locations sampled. The potential PAH-related toxicity of streambed sediments to aquatic organisms was assessed by comparison of concentrations with sediment quality guidelines. The sum concentration of 16 US Environmental Protection Agency priority pollutant PAHs was 7.4–196 000 µg/kg, and the median was 2600 µg/kg. The threshold effect concentration was exceeded at 62% of sampling locations, and the probable effect concentration or the equilibrium partitioning sediment benchmark was exceeded at 41% of sampling locations. These results have important implications for watershed managers tasked with protecting and remediating aquatic habitats in the Great Lakes Basin. Environ Toxicol Chem 2020;39:1392–1408. © 2020 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.
Abstract
Comparison of US Environmental Protection Agency 16 priority pollutant polycyclic aromatic hydrocarbon compound (ΣPAH16) concentrations in select sediments around the world. Bar = mean; whisker = maximum.
Multiple Linear Regression Modeling Predicts the Effects of Surface Water Chemistry on Acute Vanadium Toxicity to Model Freshwater Organisms
Authors: Gillio Meina Esteban , Niyogi Som , Liber Karsten 
Published: June 2020

Abstract
Multiple linear regression (MLR) modeling has been successfully used to predict how water chemistry variables influence the toxicity of cationic metals to aquatic organisms, but no MLR model exists for vanadium (V). Recent research has indicated that an increase in pH (from 6 to 9), or high concentrations of sodium (473 mg Na+/L), increase V toxicity to Daphnia pulex. In contrast, increases in alkalinity (&gt;100 mg as CaCO3) and sulfate (&gt;100 mg SO42–/L) reduce V toxicity. How these variables influence V toxicity to Oncorhynchus mykiss (rainbow trout) was still unknown. Our results show that increasing pH from 6.2 to 8.9 tended to decrease the 96-h median lethal concentration (LC50) for V toxicity to O. mykiss by 9.6 mg V/L. An alkalinity increase from 71 to 330 mg/L as CaCO3 tended to increase the 96-h LC50 by 3.3 mg V/L, whereas when SO42− rose from 150 to 250 mg/L, the LC50 significantly increased by 0.3 mg V/L followed by a significant decrease of 1 mg V/L when SO42− was &gt;250 mg/L. Sodium (between 100 and 336 mg/L) showed no effect on V toxicity to O. mykiss. The toxicity patterns for O. mykiss were similar to those observed for D. pulex, except for that of SO42−, potentially indicating different mechanisms of V uptake or regulation in the 2 species. The LC50s and associated water chemistry were combined to develop an MLR model for O. mykiss and D. pulex. Alkalinity and pH modified V toxicity to both species, whereas SO42− influenced V toxicity to D. pulex. Overall, MLR models should be considered for creating new local benchmarks or water quality guidelines for V. Environ Toxicol Chem 2020;39:1737–1745. © 2020 SETAC
ECBCM: A prestige‐based edge computing blockchain security consensus model
Authors: Xuan Shichang , Chen Zhiyu , Chung Ilyong , Tan Haowen , Man Dapeng , Du Xiaojiang , Yang Wu , Guizani Mohsen 
Published: June 2020

AbstractThe explosive growth of data in the network has brought huge burdens and challenges to traditional centralized cloud computing data processing. To solve this problem, edge computing technology came into being. Because the edge is closer to the user, processing part of the data at the edge can also bring a faster response to the user and improve their experience. However, the existing edge computing platforms have problems such as data storage security and multiparty data mutual trust. Blockchain technology has become an important means to solve the above data storage and sharing problems due to its excellent characteristics. The core of blockchain technology is consensus, and its speed and security will directly affect the efficiency and stability of the blockchain system. Therefore, this study uses the consensus mechanism as an entry point to reduce the resource consumption of the edge computing blockchain system and improve its security. In order to reduce the resource consumption of traditional consensus algorithms, improve their adaptability in the edge computing environment, and solve the security problem caused by the concentration of node rights, a prestige‐based edge computing blockchain security consensus model (ECBCM) is proposed. ECBCM is a general model based on prestige rewards and penalties. It also introduces a node replacement mechanism to ensure the fault tolerance of the consensus process. According to the results of multiple sets of performance comparison experiments and security verification experiments after embedding the existing consensus algorithm, the validity of the consensus model is confirmed.
Humanized mouse model: Hematopoietic stemcell transplantation and tracking using short tandem repeat technology
Authors: Walcher Lia , Hilger Nadja , Wege Anja K. , Lange Franziska , Tretbar U. Sandy , Blaudszun André‐René , Fricke Stephan 
Published: June 2020

AbstractIntroductionModels of mice carrying a human immune system, so‐called humanized mice, are used increasingly as preclinical models to bridge the gap between model organisms and human beings. Challenges of the humanized mouse model include finding suitable sources for human hematopoietic stem cells (HSC) and reaching sufficient engraftment of these cells in immunocompromised mice.MethodsIn this study, we compared the use of CD34+ HSC from cord blood (CB) vs HSC from adult mobilized peripheral blood. Furthermore, we developed a simple and highly specific test for donor identification in humanized mice by applying the detection method of short tandem repeats (STR).ResultsIt was found that, in vitro, CB‐derived and adult HSC show comparable purity, viability, and differentiation potential in colony‐forming unit assays. However, in vivo, CB‐derived HSC engrafted to a significantly higher extent in NOD.Cg‐PrkdcscidIL2rγtm1Wjl/SzJ (NSG) mice than adult HSC. Increasing the cell dose of adult HSC or using fresh cells without cryopreservation did not improve the engraftment rate. Interestingly, when using adult HSC, the percentage of human cells in the bone marrow was significantly higher than that in the peripheral blood. Using the STR‐based test, we were able to identify and distinguish human cells from different donors in humanized mice and in a humanized allogeneic transplantation model.ConclusionFrom these findings, we conclude that adult mobilized HSC are less suitable for generating a humanized immune system in mice than CB‐derived cells.
Thromboembolic events after high‐intensity training during cisplatin‐based chemotherapy for testicular cancer: Case reports and review of the literature
Authors: Thorsen Lene , Haugnes Hege S. , Fosså Sophie D. , Brydøy Marianne , Tandstad Torgrim , Wisløff Torbjørn , Gjerset Gunhild M. , Edvardsen Elisabeth , Larsen Karl‐Otto , Sandset Per Morten , Henriksson Carola E. , Raastad Truls , Negaard Helene F. S. 
Published: June 2020

AbstractThe randomized “Testicular cancer and Aerobic and Strength Training trial” (TAST‐trial) aimed to evaluate the effect of high‐intensity interval training (HIIT) on cardiorespiratory fitness during cisplatin‐based chemotherapy (CBCT) for testicular cancer (TC). Here, we report on an unexpected high number of thromboembolic (TE) events among patients randomized to the intervention arm, and on a review of the literature on TE events in TC patients undergoing CBCT. Patients aged 18 to 60 years with a diagnosis of metastatic germ cell TC, planned for 3 to 4 CBCT cycles, were randomized to a 9 to 12 weeks exercise intervention, or to a single lifestyle counseling session. The exercise intervention included two weekly HIIT sessions, each with 2 to 4 intervals of 2 to 4 minutes at 85% to 95% of peak heart rate. The study was prematurely discontinued after inclusion of 19 of the planned 94 patients, with nine patients randomized to the intervention arm and 10 to the control arm. Three patients in the intervention arm developed TE complications; two with pulmonary embolism and one with myocardial infarction. All three patients had clinical stage IIA TC. No TE complications were observed among patients in the control arm. Our observations indicate that high‐intensity aerobic training during CBCT might increase the risk of TE events in TC patients, leading to premature closure of the TAST‐trial.
A Proposed Novel Hybrid Intelligent Model Based on ANFIS Integrated with Firefly Algorithm for Forecasting Discharge Coefficient of Side Weirs on Converging Canals*
Authors: Heydari Majeid , Shabanlou Saeid 
Published: June 2020

AbstractSide weirs are widely used to measure and control flows passing through main canals. In this study, a hybrid model is developed to approximate the discharge coefficient of side weirs located on converging canals for the first time, meaning that the adaptive neuro‐fuzzy inference system (ANFIS) network is optimized by means of the firefly algorithm. After that, six ANFIS and adaptive neuro‐fuzzy inference system‐firefly algorithm (ANFIS‐FA) models are introduced using input parameters. In addition, in this study, Monte Carlo simulation is employed to study the modelling accuracy. Furthermore, the k‐fold cross‐validation approach is implemented to validate the modelling results. Analysing the modelled results demonstrates that the hybrid models are more accurate than the ANFIS ones. The superior model simulates the discharge coefficient values with reasonable accuracy. For example, the values of the determination coefficient (R2), the mean absolute error (MAE) and the root mean square error (RMSE) for the superior model are calculated as 0.993, 0.011 and 0.015, respectively. Also, about 98% of the superior model results have errors less than 12%. According to the uncertainty analysis results, the superior model has an overestimated performance. A sensitivity analysis indicates that the flow Froude number at the side weir downstream is the most effective input parameter. © 2020 John Wiley & Sons, Ltd.