bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development and validation of a fast ultra‐high‐performance liquid chromatography tandem mass spectrometry method for determining carbonic anhydrase inhibitors and their metabolites in urine and hair
Authors: Lo Faro Alfredo Fabrizio , Tini Anastasio , Gottardi Massimo , Pirani Filippo , Sirignano Ascanio , Giorgetti Raffaele , Busardò Francesco Paolo 
Published: April 2021

AbstractA new, rapid, sensitive, and comprehensive ultra‐high‐performance liquid chromatography tandem mass spectrometry (UHPLC–MS/MS) method for quantifying diuretics (acetazolamide, brinzolamide, dorzolamide, and their metabolites) in human urine and hair was developed and fully validated. Twenty‐five milligrams of hair were incubated with 500‐μl M3® buffer reagent at 100°C for 1 h for complete digestion. After cooling, 1‐μl supernatant was injected onto chromatography system. Urine samples were simply diluted before injection. The chromatographic run time was short (8 min) through a column with a mobile phase gradient. The method was linear (determination coefficients always higher than 0.99) from limit of quantification (LOQ) to 500 ng/ml in urine and from LOQ to 10 ng/mg in hair. LOQs ranged from 0.07 to 1.16 ng/ml in urine and from 0.02 to 0.15 ng/mg in hair. No significant ion suppression due to matrix effect was observed, and process efficiency was always higher than 80%. Intra‐ and inter‐assay precision was lower than 15%. The suitability of the methods was tested with six urine and hair specimens from patients treated with acetazolamide, dorzolamide, or brinzolamide for ocular diseases or systemic hypertension. Average urine concentrations were 266.32 ng/ml for dorzolamide and 47.61 ng/ml for N‐deethyl‐dorzolamide (n = 3), 109.27 ng/ml for brinzolamide and 1.02 ng/ml for O‐desmethyl‐brinzolamide (n = 2), and finally, 12.63 ng/ml for acetazolamide. Average hair concentrations were 5.94 ng/mg for dorzolamide and 0.048 ng/mg for N‐deethyl‐dorzolamide (n = 3), 3.26 ng/mg for brinzolamide (n = 2), and 2.3 ng/mg for acetazolamide (n = 1). The developed method was simple and fast both in the extraction procedures making it eligible in high‐throughput analysis for clinical forensic and doping purposes.
Synergism between oral paracetamol and nefopam in a murine model of postoperative pain
Authors: Cabañero David , Maldonado Rafael 
Published: April 2021

AbstractBackgroundThe use of paracetamol or nefopam for postoperative pain control is limited by the need of high doses associated with unwanted effects. Previous works suggest positive interactions between both compounds that may be exploited to obtain potentiation of antinociception.MethodsMechanical and heat antinociception induced by oral doses of paracetamol, nefopam or their combination was studied by isobolographic analysis in a murine model of postsurgical pain. The effective doses that produced 50% antinociception (ED50) were calculated from the log dose–response curves for each compound. Subsequently, the effects of ED8.7s, ED12.5s, ED17.5s and ED35s of nefopam and paracetamol combined were assessed.ResultsOral paracetamol induced dose‐dependent relief of postoperative sensitivity and showed higher efficacy reducing mechanical hypersensitivity (ED50 177.3 ± 15.4 mg/kg) than heat hyperalgesia (ED50 278.6 ± 43 mg/kg). Oral nefopam induced dose‐dependent antinociception with similar efficacy for mechanical and heat hypersensitivity (ED50s 5.42 ± 0.81 vs. 5.83 ± 0.72). Combinations of increasing isoeffective doses revealed that combined ED17.5s (85.76 mg/kg paracetamol and 1.9 mg/kg nefopam) and ED35s (132.67 mg/kg and 3.73 mg/kg) showed synergistic effects leading to 75% and 90% mechanical antinociception, respectively. These mixtures were defined by interaction indexes of 0.43 and 0.41 and ratios 45:1 and 35:1 paracetamol:nefopam, respectively. The same combinations showed additive effects for the inhibition of incisional thermal hyperalgesia.Conclusions and limitationsThis work describes a synergistic antinociceptive interaction between low doses of nefopam and paracetamol for the treatment of postoperative hypersensitivity to peripheral stimuli. The promising results obtained on reflexive nociceptive responses of young male mice subjected to plantar surgery highlight the interest of further research evaluating the effects of this mixture on the affective‐motivational component of pain and in females and additional age groups. Confirmation of pain‐relieving efficacy and safety of this oral combination clinically available in European and Asian countries could provide a useful tool for postsurgical pain management.SignificanceEarly postoperative pain is currently undertreated and has been recognized as a relevant source of chronic postsurgical pain. Oral efficient treatments could facilitate fast‐track surgeries and patient recovery at home. Here, we identify in a mouse model of postoperative pain a potent synergistic oral combination consisting of low paracetamol and nefopam doses that provides relief of postsurgical hypersensitivity to mechanical and thermal stimuli. Oral multimodal paracetamol–nefopam mixtures represent a potential clinically available pharmacological strategy for the relief of incisional sensitivity and the promotion of patient recovery.
Energy analysis and simulation of PCM‐enhanced building envelopes in commercial buildings: A case study
Authors: Beiranvand Mostafa , Mohaghegh Mohammad Reza 
Published: April 2021

AbstractIntegrating phase change materials (PCMs) into the building envelopes is considered a promising solution to reduce the energy consumption in buildings. These materials, acting as thermal energy storage systems, delay the heat transfer from the building to out or in for several hours. The present research investigates the effect of PCM employed in the building envelopes on the building's energy‐saving. For this purpose, the central office building of the University of Torbat Heydarieh is simulated as the case study using DesignBuilder software in climatic conditions of East of Iran (dry climate with hot summer and cold winter). All materials are defined in the software, and a dynamic thermal model is developed to simulate the thermal loads of the building. The energy consumption of the building for cold seasons (from October to March) is simulated for the two scenarios of with and without PCM. The effect of the melting point is also investigated by considering three types of PCMs with different melting temperatures. After choosing the proper PCM according to weather conditions for this building, the effect of different combinations of PCMs applied to the south wall of the building on the reduction of the total energy consumption is investigated.
Front capturing by level set method for the reactive Euler equations
Authors: Xiao Min , Ni Guoxi , Wang Cheng , Yang Tonghui 
Published: April 2021

AbstractIn this article, we present a front capturing method for compressible reactive flows, where a shock tracking technique is applied with level set method. In stiff reaction problems, the difficulty arises when the time scale of the source term is significantly shorter than the time scale of the homogeneous conservation law. The spurious numerical phenomenon may occur due to the smeared out shock profiles. In order to overcome the difficulty, the detonation front is captured sharply by level set technique, and a modified finite volume scheme is developed at the computational cells cut by detonation front. The mass, momentum, and energy transitions are occurred on shock front for chemical reactive flows. In our method, the interface exchanges are calculated by considering a Riemann problem. Unlike the standard level set/ghost fluid method, our method can maintain the conservation on the shock discontinuity. One‐ and two‐dimensional numerical examples including stable and unstable detonation problems are illustrated to verify the good reliability and robustness of our method.
Social network size, loneliness, physical functioning and depressive symptoms among older adults: Examining reciprocal associations in four waves of the Longitudinal Aging Study Amsterdam (LASA)
Authors: Domènech‐Abella Joan , Mundó Jordi , Switsers Lise , van Tilburg Theo , Fernández Daniel , Aznar‐Lou Ignacio 
Published: April 2021

AbstractIntroductionPrevious research indicates that social isolation, loneliness, physical dysfunction and depressive symptoms are interrelated factors, little is known about the potential pathways among them. The aim of the study is to analyse simultaneously reciprocal relationships that could exist between the four factors to clarify potential mediation effects.MethodsWithin a large representative sample of older people in the Longitudinal Aging Study Amsterdam (LASA), participants aged 75 and over were followed up over a period of 11 years (four waves). We tested cross‐lagged and autoregressive longitudinal associations of social network size, loneliness, physical functioning and depressive symptoms using structural equation modelling (SEM).ResultsSeveral statistically significant cross‐lagged associations were found: decreasing physical functioning (Coef. = −0.03; p < 0.05), as well as social network size (Coef. = −0.02; p < 0.05), predicted higher levels of loneliness, which predicted an increase in depressive symptoms (Coef. = 0.17; p < 0.05) and further reduction of social network (Coef. = −0.20; p < 0.05). Decreasing physical functioning also predicted an increase in depressive symptoms (Coef. = −0.08; p < 0.05). All autoregressive associations were statistically significant.ConclusionInterventions focused on promoting social activities among older adults after negative life events, such as loss of social contacts or declining physical function, may alleviate feelings of loneliness and act as mental health protector.
Survival outcomes in patients with parotid gland carcinoma treated with postoperative therapies using risk stratification
Authors: Wei Zhi‐Gong , Peng Xing‐Chen , He Yan , Guan Hui , Wang Jing‐Jing , He Ling , Mu Xiao‐Li , Liu Zhe‐Ran , Li Rui‐Dan , Zhang Zhuang 
Published: April 2021

AbstractBackgroundTo evaluate the role of postoperative treatment in parotid gland carcinoma (PGC) based on risk stratification.Material and MethodsA total of 301 PGC patients were retrospectively analyzed using risk stratification. The Kaplan–Meier method and Cox analysis were performed to conduct survival analysis.ResultsIn the high‐risk group, those treated with postoperative radiotherapy (RT) had a better 5‐year disease‐free survival (DFS) than those treated with surgery alone. In the low‐risk group, both surgery + RT and surgery +  chemotherapy (CT) significantly improved DFS when compared with surgery alone. Cox analysis showed that patients who underwent surgery + RT or surgery + CT had a lower risk of disease progression than those who underwent surgery alone in the low‐risk group. In the high‐risk group, patients who underwent surgery + RT had a lower risk of disease progression.ConclusionsPostoperative RT showed considerable benefit in improving disease control in patients with PGC, even in those without high‐risk factors.
Monitoring and modelling of hydrological processes in the semiarid region of Brazil: The Cariri experimental basins
Authors: S. Srinivasan Vajapeyam , M. de Alcântara Hugo , de O. Galvão Carlos , A. Bezerra Ulisses , E. de Brito Leite Cunha John 
Published: April 2021

AbstractCatchments have highly variable yields of runoff and soil erosion. The size, land use and the surface cover play a significant role and influence the catchment response and parameter values of simulation models. Two experimental basins—the Cariri basins—were equipped in a semi‐arid region of Brazil, for obtaining runoff and sediment yield at different catchment scales, as well as, to evaluate the influence of the land use and surface cover. In the first basin, located in the municipality of Sumé, the field studies were carried out at two different scales: four micro‐catchments with an area of around 0.5 ha and nine standard Wischmeier‐type erosion plots of 100 m2. The experimental units had varied vegetation and management. They were subjected only to natural rainfall events, and were monitored from 1982 to 1991. The total runoff and total sediment yield were determined for each of the events. The installations in the second basin, in the municipality of São João do Cariri, from 1999, include two erosion plots, three micro‐catchments, and two sub‐catchments of a small basin. These basins are still being monitored for runoff and sediment production. Among the micro‐catchments two are nested to detect any scale effect at the micro‐catchment level. Nearly 600 events of precipitation, that produced runoff in at least one of the experimental units, have been registered. These data have been used to evaluate the influence of various factors, including cultivation practices and to calibrate hydrological models for plots and micro‐catchments. Parameters have been tested by means of cross validations among micro‐catchments and sub‐catchments. The data sets are made available to all the catchment hydrology researchers and others at https://doi.org/10.5281/zenodo.4690886.
Snags in mobile money in developing economies
Authors: Kanobe Fredrick , Bwalya Kelvin Joseph 
Published: April 2021

AbstractLessening snags in the management of mobile money systems is a fundamental prerequisite. The study was motivated by the continuous mobile money management snags. Previous studies in developing economies focused mainly on technological algorithm for mobile money systems with untraceable attention given to management matters. The study aimed at lessening snags in the management of mobile money system. Underpinned by activity theory and guided by an interpretive paradigm, a qualitative inquiry was conducted. Semi‐structured interviews and internal document review formed the key data instruments. Expert purposive sampling was adopted, data thematically analyzed and themes mapped on activity theory nodes. The study revealed inadequate monitoring of the mobile money agents, insufficient confidentiality and privacy in financial transactions; use of general accounts for financial transactions, use of generic guidelines and polices, third party involvement in sensitive mobile money activities and weak staff recruitment policies as the key findings. Managerial implications for the study include online registration of customers, introduction of online transaction monitoring, online categorization of mobile money accounts, digital financial crime checks, digital validation of customer identities and continuous review and updates of mobile money guidelines.
In situ deposition of CdS on MoS2/rGO‐based nanocomposites for highly efficient photocatalytic H2 evolution reaction with visible light
Authors: Tan Bi‐yu , Song Xiao‐jie , Xian‐yang Shi 
Published: April 2021

AbstractBACKGROUNDThe development of advanced and inexpensive photocatalytic systems exhibiting high efficiency is highly desired for hydrogen (H2) production. In this work, a hydrothermal and in situ growth method was employed for the construction of CdS/MoS2/rGO nanocomposites by coupling MoS2/rGO with CdS to produce H2. The stability and photocatalytic properties of the nanocomposites for H2 evolution at different CdS content were investigated.RESULTSIt was found that CdS/MoS2/rGO nanocomposites with 0.35 wt% CdS displayed the highest H2 evolution rate of 11 331.65 μmol h−1 g−1. This corresponded to the apparent quantum efficiency of 10.4% at 420 nm, which was approximately 46 times higher than that of pure CdS. The CdS/MoS2/rGO nanocomposites showed excellent stability in 6‐run recycling experiments. Additionally, a plausible H2 production mechanism was proposed.CONCLUSIONThe remarkable photocatalytic activity was attributed to the high electron–hole pair separation efficiency upon the introduction of MoS2/rGO. This work provides new insights for enhancing the photocatalytic H2 evolution activity. © 2021 Society of Chemical Industry (SCI).
Evaluation of automated segmentation algorithms for neurons in macaque cerebral microscopic images
Authors: You Zhenzhen , Jiang Ming , Shi Zhenghao , Ning Xiaojuan , Shi Cheng , Du Shuangli , Hérard Anne‐Sophie , Jan Caroline , Souedet Nicolas , Delzescaux Thierry 
Published: April 2021

AbstractAccurate cerebral neuron segmentation is required before neuron counting and neuron morphological analysis. Numerous algorithms for neuron segmentation have been published, but they are mainly evaluated using limited subsets from a specific anatomical region, targeting neurons of clear contrast and/or neurons with similar staining intensity. It is thus unclear how these algorithms perform on cerebral neurons in diverse anatomical regions. In this article, we introduce and reliably evaluate existing machine learning algorithms using a data set of microscopy images of macaque brain. This data set highlights various anatomical regions (e.g., cortex, caudate, thalamus, claustrum, putamen, hippocampus, subiculum, lateral geniculate, globus pallidus, etc.), poor contrast, and staining intensity differences of neurons. The evaluation was performed using 10 architectures of six classic machine learning algorithms in terms of typical Recall, Precision, F‐score, aggregated Jaccard index (AJI), as well as a performance ranking of algorithms. F‐score of most of the algorithms is superior to 0.7. Deep learning algorithms facilitate generally higher F‐scores. U‐net with suitable layer depth has been evaluated to be excellent classifiers with F‐score of 0.846 and 0.837 when performing cross validation. The evaluation and analysis indicate the performance gap among algorithms in various anatomical regions and the strengths and limitations of each algorithm. The comparative result highlights at the same time the importance and difficulty of neuron segmentation and provides clues for future improvement. To the best of our knowledge, this work is the first comprehensive study for neuron segmentation in such large‐scale anatomical regions.
Neuron segmentation plays a critical role in extracting cerebral information, such as neuron counting and neuron morphological analysis.
Accurate automated cerebral neuron segmentation is a challenging task due to different kinds, poor contrast, staining intensity differences, and fuzzy boundaries of neurons.
The comprehensive evaluation and analysis of performance among existing machine learning algorithms in diverse anatomical regions allows to make clear of the strengths and limitations of state‐of‐the‐art algorithm.
The comprehensive study provides clues for future improvement and creation of automated methods.
Synthesis of julolidines via one‐pot cascade three component Povarov reaction in the presence of silica sulfuric acid
Authors: Kaboudin Babak , Sohrabi Masoumeh , Kazemi Foad 
Published: April 2021

AbstractIn this report, synthesis of julolidines via one‐pot cascade reaction of aniline derivatives with a mixture of styrene and formaldehyde in the presence of silica sulfuric acid as an efficient catalyst has been studied under aerobic condition. By presented method, various julolidines are obtained under mild and transition metal‐free conditions. The reaction is proceeded with imine formation and followed by an Aza‐Diels‐Alder cycloaddition with styrene gave julolidine derivatives. The catalyst can be recycled and reused multiple times to catalyze the reaction.
Identifying the primary meteorological factors affecting the growth and development of Tartary buckwheat and a comprehensive landrace evaluation using a multi‐environment phenotypic investigation
Authors: Li Jing , Feng Shan , Qu Yang , Gong Xiangwei , Luo Yan , Yang Qinghua , Zhang Yuchuan , Dang Ke , Gao Xiaoli , Feng Baili 
Published: April 2021

AbstractBACKGROUNDTartary buckwheat (Fagopyrum tataricum) is a traditional edible and medicinal crop and has been praised as one of the green foods for humans in the 21st century. However, its production and promotion are restricted by the low yields of current varieties. The interaction of genotype and environment could lead to inconsistent phenotypic performance of genotypes across different environments. Climate change has intensified these effects and poses a substantial threat to crop production.RESULTSIn the present study, the effects of meteorological factors on the phenotypic traits of 200 Tartary buckwheat landraces across four macro‐environments were investigated. Overall, the phenotypic performance of these Tartary buckwheat landraces was markedly varied across the different environments. Also, the average daily temperature and precipitation had relatively higher impacts on phenotypic performance. The results also revealed the negative impacts of relative humidity on the yield‐related traits. Twenty‐five Tartary buckwheat landraces were ultimately identified as having good overall phenotypic performance and high yield stability.CONCLUSIONUnderstanding the impacts of meteorological factors on the phenotypic performance of crops can guide appropriate measures and facilitate germplasm selection for yield enhancement in the context of climate change. The landraces selected comprehensively in this study could be used as parents or intermediate materials for breeding high‐quality Tartary buckwheat varieties in the future. The methods used could also be extended to other crops for breeding and germplasm innovation. © 2021 Society of Chemical Industry.
Prediction of soft tissue sarcoma response to radiotherapy using longitudinal diffusion MRI and a deep neural network with generative adversarial network‐based data augmentation
Authors: Gao Yu , Ghodrati Vahid , Kalbasi Anusha , Fu Jie , Ruan Dan , Cao Minsong , Wang Chenyang , Eilber Fritz C. , Bernthal Nicholas , Bukata Susan , Dry Sarah M. , Nelson Scott D. , Kamrava Mitchell , Lewis John , Low Daniel A. , Steinberg Michael , Hu Peng , Yang Yingli 
Published: April 2021

PurposeThe goal of this study was to predict soft tissue sarcoma response to radiotherapy (RT) using longitudinal diffusion‐weighted MRI (DWI). A novel deep‐learning prediction framework along with generative adversarial network (GAN)‐based data augmentation was investigated for the response prediction.MethodsThirty soft tissue sarcoma patients who were treated with five‐fraction hypofractionated radiation therapy (RT, 6Gy×5) underwent diffusion‐weighted MRI three times throughout the RT course using an MR‐guided radiotherapy system. Pathologic treatment effect (TE) scores, ranging from 0‐100%, were obtained from the post‐RT surgical specimen as a surrogate of patient treatment response. Patients were divided into three classes based on the TE score (TE ≤ 20%, 20% < TE < 90%, TE ≥ 90%). Apparent diffusion coefficient (ADC) maps of the tumor from the three time points were combined as 3‐channel images. An auxiliary classifier generative adversarial network (ACGAN) was trained on 20 patients to augment the data size. A total of 15,000 synthetic images were generated for each class. A prediction model based on a previously described VGG‐19 network was trained using the synthesized data, validated on five unseen validation patients, and tested on the remaining five test patients. The entire process was repeated seven times, each time shuffling the training, validation, and testing datasets such that each patient was tested at least once during the independent test stage. Prediction performance for slice‐based prediction and patient‐based prediction was evaluated.ResultsThe average training and validation accuracies were 86.5% ± 1.6% and 84.8% ± 1.8%, respectively, indicating that the generated samples were good representations of the original patient data. Among the seven rounds of testing, slice by slice prediction accuracy ranged from 81.6% to 86.8%. The overall accuracy of the independent test sets was 83.3%. For patient‐based prediction, 80% was achieved in one round and 100% was achieved in the remaining six rounds. The mean accuracy was 97.1%.ConclusionThis study demonstrated the potential to use deep learning to predict the pathologic treatment effect from longitudinal DWI. Accuracies of 83.3% and 97.1% were achieved on independent test sets for slice‐based and patient‐based prediction respectively.