bluuebunny/crossref_metadata_2025 huggingface dataset:
The Prevalence of Coxiella burnetii in Hard Ticks in Europe and Their Role in Q Fever Transmission Revisited—A Systematic Review
Authors: Körner Sophia , Makert Gustavo R. , Ulbert Sebastian , Pfeffer Martin , Mertens-Scholz Katja
Published: April 2021

The zoonosis Q fever is caused by the obligate intracellular bacterium Coxiella burnetii. Besides the main transmission route via inhalation of contaminated aerosols, ticks are discussed as vectors since the first isolation of the pathogen from a Dermacentor andersonii tick. The rare detection of C. burnetii in ticks and the difficult differentiation of C. burnetii from Coxiella-like endosymbionts (CLEs) are questioning the relevance of ticks in the epidemiology of Q fever. In this review, literature databases were systematically searched for recent prevalence studies concerning C. burnetii in ticks in Europe and experimental studies evaluating the vector competence of tick species. A total of 72 prevalence studies were included and evaluated regarding DNA detection methods and collection methods, country, and tested tick species. Specimens of more than 25 different tick species were collected in 23 European countries. Overall, an average prevalence of 4.8% was determined. However, in half of the studies, no Coxiella-DNA was detected. In Southern European countries, a significantly higher prevalence was observed, possibly related to the abundance of different tick species here, namely Hyalomma spp. and Rhipicephalus spp. In comparison, a similar proportion of studies used ticks sampled by flagging and dragging or tick collection from animals, under 30% of the total tick samples derived from the latter. There was no significant difference in the various target genes used for the molecular test. In most of the studies, no distinction was made between C. burnetii and CLEs. The application of specific detection methods and the confirmation of positive results are crucial to determine the role of ticks in Q fever transmission. Only two studies were available, which assessed the vector competence of ticks for C. burnetii in the last 20 years, demonstrating the need for further research.
CDKN2A Gene Expression as a Potential Aging Biomarker in Dogs
Authors: Sándor Sára , Tátrai Kitti , Czeibert Kálmán , Egyed Balázs , Kubinyi Enikő
Published: April 2021

Describing evolutionary conserved physiological or molecular patterns, which can reliably mark the age of both model organisms and humans or predict the onset of age-related pathologies has become a priority in aging research. The age-related gene-expression changes of the Cyclin Dependent Kinase Inhibitor 2A (CDKN2A) gene have been well-documented in humans and rodents. However, data is lacking from other relevant species, including dogs. Therefore, we quantified the CDKN2A mRNA abundance in dogs of different ages, in four tissue types: the frontal cortex of the brain, temporal muscle, skin, and blood. We found a significant, positive correlation between CDKN2A relative expression values and age in the brain, muscle, and blood; however, no correlation was detected in the skin. The strongest correlation was detected in the brain tissue (CDKN2A/GAPDH: r = 0.757, p < 0.001), similarly to human findings, while the muscle and blood showed weaker, but significant correlation. Our results suggest that CDKN2A might be a potential blood-borne biomarker of aging in dogs, although the validation and optimization will require further, more focused research. Our current results also clearly demonstrate that the role of CDKN2A in aging is conserved in dogs, regarding both tissue specificity and a pivotal role of CDKN2A in brain aging.
Analysis of Data Presented by Multisets Using a Linguistic Approach
Authors: Demidova Liliya A. , Sokolova Julia S.
Published: April 2021

The problem of the analysis of datasets formed by the results of group expert assessment of objects by a certain set of features is considered. Such datasets may contain mismatched, including conflicting values of object evaluations by the analyzed features. In addition, the values of the assessments for the features can be not only point, but also interval due to the incompleteness and inaccuracy of the experts’ knowledge. Taking into account all the results of group expert assessment of objects for a certain set of features, estimated pointwise, can be carried out using the multiset toolkit. To process interval values of assessments, it is proposed to use a linguistic approach which involves the use of a linguistic scale in order to describe various strategies for evaluating objects: conservative, neutral and risky, and implement various decision-making strategies in the problems of clustering, classification, and ordering of objects. The linguistic approach to working with objects assessed by a group of experts with setting interval values of assessments has been successfully applied to the analysis of the dataset presented by competitive projects. A herewith, for the dataset under consideration, using various assessment strategies, solutions of clustering, classification, and ordering problems were obtained with the study of the influence of the chosen assessment strategy on the results of solving the corresponding problem.
The Effects of Microbial Inoculants on Bacterial Communities of the Rhizosphere Soil of Maize
Authors: Shen Minchong , Li Jiangang , Dong Yuanhua , Zhang Zhengkun , Zhao Yu , Li Qiyun , Dang Keke , Peng Junwei , Liu Hong
Published: April 2021

The bacterial community of rhizosphere soil maintains soil properties, regulates the microbiome, improves productivity, and sustains agriculture. However, the structure and function of bacterial communities have been interrupted or destroyed by unreasonable agricultural practices, especially the excessive use of chemical fertilizers. Microbial inoculants, regarded as harmless, effective, and environmentally friendly amendments, are receiving more attention. Herein, the effects of three microbial inoculants, inoculant M and two commercial inoculants (A and S), on bacterial communities of maize rhizosphere soil under three nitrogen application rates were compared. Bacterial communities treated with the inoculants were different from those of the non-inoculant control. The OTU (operational taxonomic unit) numbers and alpha diversity indices were decreased by three inoculants, except for the application of inoculant M in CF group. Beta diversity showed the different structures of bacterial communities changed by three inoculants compared with control. Furthermore, key phylotypes analyses exhibited the differences of biomarkers between different treatments visually. Overall, inoculant M had shared and unique abilities of regulating bacterial communities compared with the other two inoculants by increasing potentially beneficial bacteria and decreasing the negative. This work provides a theoretical basis for the application of microbial inoculants in sustainable agriculture.
New Neuroprotective Effect of Lemon IntegroPectin on Neuronal Cellular Model
Authors: Nuzzo Domenico , Picone Pasquale , Giardina Costanza , Scordino Miriana , Mudò Giuseppa , Pagliaro Mario , Scurria Antonino , Meneguzzo Francesco , Ilharco Laura M. , Fidalgo Alexandra , Alduina Rosa , Presentato Alessandro , Ciriminna Rosaria , Di Liberto Valentina
Published: April 2021

Lemon IntegroPectin obtained via hydrodynamic cavitation of organic lemon processing waste in water shows significant neuroprotective activity in vitro, as first reported in this study investigating the effects of both lemon IntegroPectin and commercial citrus pectin on cell viability, cell morphology, reactive oxygen species (ROS) production, and mitochondria perturbation induced by treatment of neuronal SH-SY5Y human cells with H2O2. Mediated by ROS, including H2O2 and its derivatives, oxidative stress alters numerous cellular processes, such as mitochondrial regulation and cell signaling, propagating cellular injury that leads to incurable neurodegenerative diseases. These results, and the absence of toxicity of this new pectic substance rich in adsorbed flavonoids and terpenes, suggest further studies to investigate its activity in preventing, retarding, or even curing neurological diseases.
QiOi: Performance Isolation for Hyperledger Fabric
Authors: Kim Jeongsu , Lee Kyungwoon , Yang Gyeongsik , Lee Kwanhoon , Im Jaemin , Yoo Chuck
Published: April 2021

This paper investigates the performance interference of blockchain services that run on cloud data centers. As the data centers offer shared computing resources to multiple services, the blockchain services can experience performance interference due to the co-located services. We explore the impact of the interference on Fabric performance and develop a new technique to offer performance isolation for Hyperledger Fabric, the most popular blockchain platform. First, we analyze the characteristics of the different components in Hyperledger Fabric and show that Fabric components have different impacts on the performance of Fabric. Then, we present QiOi, component-level performance isolation technique for Hyperledger Fabric. The key idea of QiOi is to dynamically control the CPU scheduling of Fabric components to cope with the performance interference. We implement QiOi as a user-level daemon and evaluate how QiOi mitigates the performance interference of Fabric. The evaluation results demonstrate that QiOi mitigates performance degradation of Fabric by 22% and improves Fabric latency by 2.5 times without sacrificing the performance of co-located services. In addition, we show that QiOi can support different ordering services and chaincodes with negligible overhead to Fabric performance.
Drone Ground Impact Footprints with Importance Sampling: Estimation and Sensitivity Analysis
Authors: Morio Jérôme , Levasseur Baptiste , Bertrand Sylvain
Published: April 2021

This paper addresses the estimation of accurate extreme ground impact footprints and probabilistic maps due to a total loss of control of fixed-wing unmanned aerial vehicles after a main engine failure. In this paper, we focus on the ground impact footprints that contains 95%, 99% and 99.9% of the drone impacts. These regions are defined here with density minimum volume sets and may be estimated by Monte Carlo methods. As Monte Carlo approaches lead to an underestimation of extreme ground impact footprints, we consider in this article multiple importance sampling to evaluate them. Then, we perform a reliability oriented sensitivity analysis, to estimate the most influential uncertain parameters on the ground impact position. We show the results of these estimations on a realistic drone flight scenario.
Modelling the Degree of Emotional Concern: COVID-19 Response in Social Media
Authors: Ortega Jose Moreno , Bernabé-Moreno Juan
Published: April 2021

The massive impact caused by the COVID-19 pandemic has left no one indifferent, becoming an unprecedented challenge. The use of protections such as sanitary masks has become increasingly common, restrictions in our daily lives, such as social distancing or confinements, have had serious consequences on the economy and our welfare state. Although the measures imposed throughout the world follow the same pattern, they have been applied with different criteria depending on the country. Over extended periods of time, people tend to change their perception of an event and its magnitude, or in other words, they stop being so concerned despite the seriousness of the matter. In this paper, we introduce a new metric to quantify the degree of emotional concern of people being affected by a topic, and we confirm how populations from different countries follow this trend of downplaying the effect of the pandemic and reach a state of indifference. To do this, we propose a method to analyze the social media stream over time extracting the different emotional states from the Russel Circumplex plane and computing the shifting created by the tragic event—the pandemic. We complete this metric by incorporating searching behavior to reflect not only push contents but also pull inquiries. The resulting metric establishes a relationship between the pandemic and the emotional response by defining the degree of Emotional Concern. Although the method can be applied to any location with a significant and varied amount of geo-localized social media streams, the scope of this paper covers the most representative cities in Europe.
Novel Coordinated Control Strategy of BESS and PMSG-WTG for Fast Frequency Response
Authors: Kim Hyunwook , Lee Junghun , Lee Jaehyeong , Jang Gilsoo
Published: April 2021

An increase in inverter-based resources (IBRs) can lower the inertia of a power system, which may adversely affect the power system by causing changes such as a frequency nadir reduction or an increased initial rate of change of frequency (RoCoF). To prevent this, an ancillary service called fast frequency response (FFR) helps the inertia response by using IBRs. The main resources used in FFR are variable-speed wind turbine generators (VSWTGs) or energy storage systems (ESSs), which can respond quickly through converter control. The control is applied to the frequency regulation service faster than the primary frequency response, so the second frequency nadir may fall below the first frequency nadir. This study proposed a novel coordinated control strategy to efficiently utilize energy to improve the frequency nadir through coordinated control of wind turbines based on permanent magnetic synchronous generators (PMSGs) and battery energy storage systems (BESSs). The simulation results confirmed that the two-bus test system was composed of PSCAD/EMTDC, and the frequency nadir increased by utilizing the same amount of energy as in traditional control systems.
Spatial-Temporal Changes in Removal of Fecal Indicators and Diversity of Bacterial Communities in a Constructed Wetland with Ornamental Plants
Authors: Calheiros Cristina S. C. , Pereira Sofia I. A. , Franco Albina R. , Castro Paula M. L.
Published: April 2021

The present study was undertaken in a constructed wetland (CW), setup in a tourism house, for domestic wastewater treatment. The influence of season variations on the abundance of fecal indicator organisms (total coliforms and Escherichia coli) in the wastewater and in the substrate and the roots of plants inhabiting the inlet and outlet zones of the CW was evaluated along three consecutive years. The structure and diversity of bacterial communities associated to the CW’s substrate of inlet and outlet zones was also analyzed overtime. Wastewater was characterized for physicochemical and microbiological parameters and the bacterial communities colonizing the substrate surface, were analyzed by Denaturing Gradient Gel Electrophoresis (DGGE). The CW was effective in removing COD, BOD5, TSS, PO43−, NH4+, NO3−, and NO2−. It was also effective in removing fecal indicators, with a generalized decrease of total coliforms and E. coli in the substrate and in the wastewater from inlet to outlet of up to 2–3 log. The structure and composition of bacterial communities associated with the substrate was mainly influenced by the year rather than by the season or the CW zone.
An Application of the Associate Hopfield Network for Pattern Matching in Chart Analysis
Authors: Mai Weiming , Lee Raymond S. T.
Published: April 2021

Chart patterns are significant for financial market behavior analysis. Lots of approaches have been proposed to detect specific patterns in financial time series data, most of them can be categorized as distance-based or training-based. In this paper, we applied a trainable continuous Hopfield Neural Network for financial time series pattern matching. The Perceptually Important Points (PIP) segmentation method is used as the data preprocessing procedure to reduce the fluctuation. We conducted a synthetic data experiment on both high-level noisy data and low-level noisy data. The result shows that our proposed method outperforms the Template Based (TB) and Euclidean Distance (ED) and has an advantage over Dynamic Time Warping (DTW) in terms of the processing time. That indicates the Hopfield network has a potential advantage over other distance-based matching methods.
Development of Shear Resistance Formula for the Y-Type Perfobond Rib Shear Connector Considering Probabilistic Characteristics
Authors: Kim Sang-Hyo , Batbold Tuvshintur , Shah Syed Haider Ali , Yoon Suro , Han Oneil
Published: April 2021

A design shear resistance formula for Y-type perfobond rib shear connectors is proposed with the various reduction factors, which can be selected depending on the target safety level. The nominal shear resistance formula is improved based on the systematic sensitivity analysis as well as the regression fit test based on 84 push-out test results, including 15 additional push-out tests to extend the application ranges and reduce the estimation errors, compared to the formula proposed in previous studies. Some design variables are additionally included in the proposed design formula: the yield strengths of rebar and rib plate. The basic design variables in the proposed design formula are (1) number of ribs and transverse rebars, (2) concrete compressive strength, (3) rebar diameter and yield strength, and (4) rib thickness, width, height, and yield strength. The application ranges of the basic design variables are recommended for the proposed design formula. The various shear resistance reduction factors are proposed based on the probabilistic ultimate shear resistance model of Y-type perfobond rib shear connectors. The proposed procedure may be recommended to develop the design formula for shear connectors with various shapes.
Negation Detection on Mexican Spanish Tweets: The T-MexNeg Corpus
Authors: Bel-Enguix Gemma , Gómez-Adorno Helena , Pimentel Alejandro , Ojeda-Trueba Sergio-Luis , Aguilar-Vizuet Brian
Published: April 2021

In this paper, we introduce the T-MexNeg corpus of Tweets written in Mexican Spanish. It consists of 13,704 Tweets, of which 4895 contain negation structures. We performed an analysis of negation statements embedded in the language employed on social media. This research paper aims to present the annotation guidelines along with a novel resource targeted at the negation detection task. The corpus was manually annotated with labels of negation cue, scope, and, event. We report the analysis of the inter-annotator agreement for all the components of the negation structure. This resource is freely available. Furthermore, we performed various experiments to automatically identify negation using the T-MexNeg corpus and the SFU ReviewSP-NEG for training a machine learning algorithm. By comparing two different methodologies, one based on a dictionary and the other based on the Conditional Random Fields algorithm, we found that the results of negation identification on Twitter are lower when the model is trained on the SFU ReviewSP-NEG Corpus. Therefore, this paper shows the importance of having resources built specifically to deal with social media language.
The Limitations of 5f Delocalization and Dispersion
Authors: Tobin J. G. , Nowak S. , Yu S. W. , Alonso-Mori R. , Kroll T. , Nordlund D. , Weng T. C. , Sokaras D.
Published: April 2021

Delocalization in the 5f states of the actinides is an important phenomenon, but poorly quantified. Here, the fundamental limitations of 5f dispersion measurements using angle and momentum resolved variants of photoelectron spectroscopy will be discussed. A novel approach will be suggested, based on a theoretical projection, which should circumvent these limitations: M4,5 X-ray emission spectroscopy. This analysis will utilize the case study of U metal, which can be considered to be the paramount example of 5f dispersion.
Examining Attention Mechanisms in Deep Learning Models for Sentiment Analysis
Authors: Kardakis Spyridon , Perikos Isidoros , Grivokostopoulou Foteini , Hatzilygeroudis Ioannis
Published: April 2021

Attention-based methods for deep neural networks constitute a technique that has attracted increased interest in recent years. Attention mechanisms can focus on important parts of a sequence and, as a result, enhance the performance of neural networks in a variety of tasks, including sentiment analysis, emotion recognition, machine translation and speech recognition. In this work, we study attention-based models built on recurrent neural networks (RNNs) and examine their performance in various contexts of sentiment analysis. Self-attention, global-attention and hierarchical-attention methods are examined under various deep neural models, training methods and hyperparameters. Even though attention mechanisms are a powerful recent concept in the field of deep learning, their exact effectiveness in sentiment analysis is yet to be thoroughly assessed. A comparative analysis is performed in a text sentiment classification task where baseline models are compared with and without the use of attention for every experiment. The experimental study additionally examines the proposed models’ ability in recognizing opinions and emotions in movie reviews. The results indicate that attention-based models lead to great improvements in the performance of deep neural models showcasing up to a 3.5% improvement in their accuracy.
A Study on Distance Measurement Module for Driving Vehicle Velocity Estimation in Multi-Lanes Using Drones
Authors: Lee Kwan-Hyeong
Published: April 2021

A method of estimating driving vehicle information usually uses a speed gun and a fixed speed camera. Estimating vehicle information using the speed gun has a high risk of traffic accidents by the operator and the fixed speed camera is not efficient in terms of installation cost and maintenance. The existing driving vehicle information estimation method can only measure each lane’s driving vehicle information, so it is impossible to measure multi-lanes simultaneously with a single measuring device. This study develops a distance measurement module that can acquire driving vehicle information in multi-lanes simultaneously with a single system using a drone. The distance measurement module is composed of two LiDAR sensors to detect the driving vehicle in one lane. The drone is located above the edge of the road and each LiDAR sensor emits the front/rear point of the road measuring point to detect the driving vehicle. The driving vehicle velocity is estimated by detecting the driving vehicle’s detection distance and transit time through radiation, with the drone LiDAR sensor placed at two measurement points on the road. The drone LiDAR sensor radiates two measuring points on the road and estimates the velocity based on driving vehicle’s detection distance and driving time. As an experiment, the velocity accuracy of the drone driving vehicle is compared with the speed gun measurement. The vehicle velocity RMSE for the first and second lanes using drones is 0.75 km/h and 1.3 km/h, respectively. The drone and the speed gun’s average error probabilities are 1.2% and 2.05% in the first and second lanes, respectively. The developed drone is more efficient than existing driving vehicle measurement equipment because it can acquire information on the driving vehicle in a dark environment and a person’s safety.
Applying Automatic Translation for Optical Music Recognition’s Encoding Step
Authors: Ríos-Vila Antonio , Esplà-Gomis Miquel , Rizo David , Ponce de León Pedro J. , Iñesta José M.
Published: April 2021

Optical music recognition is a research field whose efforts have been mainly focused, due to the difficulties involved in its processes, on document and image recognition. However, there is a final step after the recognition phase that has not been properly addressed or discussed, and which is relevant to obtaining a standard digital score from the recognition process: the step of encoding data into a standard file format. In this paper, we address this task by proposing and evaluating the feasibility of using machine translation techniques, using statistical approaches and neural systems, to automatically convert the results of graphical encoding recognition into a standard semantic format, which can be exported as a digital score. We also discuss the implications, challenges and details to be taken into account when applying machine translation techniques to music languages, which are very different from natural human languages. This needs to be addressed prior to performing experiments and has not been reported in previous works. We also describe and detail experimental results, and conclude that applying machine translation techniques is a suitable solution for this task, as they have proven to obtain robust results.
Technological Development and Application of Photo and Video Theodolites
Authors: Paar Rinaldo , Roić Miodrag , Marendić Ante , Miletić Stjepan
Published: April 2021

Theodolites are fundamental geodetic measuring instruments for all practical geodetic tasks, as well as for experimental geodetic scientific purposes. Their development has a long history. Photo and video theodolites represent the advanced development of classic theodolites. Development started in 19th century, but only in the last 15 years has commercial application been achieved in the geodetic profession. The latest development, called image-assisted total stations (IATS), is a theodolite which consists of a classic robotic total station (RTS) with integrated image sensors. It was introduced in the early 2000s. With the development of theodolites, their application became much wider; today, they can be used for structural and geo-monitoring, i.e., for the determination of static and dynamic displacements and deformations of civil engineering structures such as bridges, dams, wind turbines, and high buildings, as well as natural structures, such as mountain slopes. They can be implemented in geodetic monitoring systems, which are an integral part of engineering structural diagnosis, and they provide essential information about the current condition of the structure. This paper describes the technological development of photo and video theodolites divided into phases according to the main innovations in their development. The application of modern video theodolites (i.e., IATS) is presented through several experimental studies that were performed. The procedure of conducting measurements with this kind of instrument, as well as the analysis of acquired data and achieved results, is elaborated. Lastly, the authors conclude, according to the achieved results, that IATS can today be used for determination of quasi-static and dynamic displacements with small and high amplitudes.
Mathematical Modelling of a Static Concentrating Photovoltaic: Simulation and Experimental Validation
Authors: Muhammad-Sukki Firdaus , Farooq Haroon , Abu-Bakar Siti Hawa , Ardila-Rey Jorge Alfredo , Sellami Nazmi , Kilpatrick Ciaran , Muhtazaruddin Mohd Nabil , Bani Nurul Aini , Zulkipli Muhammad
Published: April 2021

For the past twenty years, there has been increasing interest and investment in solar photovoltaic (PV) technology. One particular area of interest is the development of concentrating PV (CPV), especially for use in building integration. Many CPV designs have been developed and investigated. This paper aims at producing a mathematical modelling using MATLAB programme to predict the current-voltage (I-V) and power-voltage (P-V) characteristics of a static CPV. The MATLAB programme could also simulate the angular response of the CPV designs-which has never been explored in the previous literature. In this paper, a CPV known as the rotationally asymmetrical dielectric totally internally reflecting concentrator (RADTIRC) was analysed. A specific RADTIRC design that has an acceptance angle of ±40° was investigated in this paper. A mathematical modelling was used to simulate the angular characteristics of the RADTIRC from −50° to 50° with an increment 5°. For any CPV, we propose that the value of opto-electronic gain, Copto-e needs to be included in the mathematical model, which were obtained from experiments. The range of incident angle (±50°) was selected to demonstrate that the RADTIRC is capable of capturing the sun rays within its acceptance angle of ±40°. In each simulation, the I-V and P-V characteristics were produced, and the short circuit current (Isc), the open-circuit voltage (Voc), the maximum power (Pmax), the fill factor (FF) and the opto-electronic gain (Copto-e) were determined and recorded. The results from the simulations were validated via experiments. It was found that the simulation model is able to predict the I-V and P-V characteristics of the RADTIRC as well as its angular response, with the highest error recorded for the Isc, Voc, Pmax, FF and Copto-e was 2.1229%, 5.3913%, 9.9681%, 4.4231% and 0.0000% respectively when compared with the experiment.
Model of an Artificial Neural Network for Solving the Problem of Controlling a Genetic Algorithm Using the Mathematical Apparatus of the Theory of Petri Nets
Authors: Petrosov David Aregovich , Lomazov Vadim Alexsandrovich , Petrosova Nataliy Vladimirovna
Published: April 2021

The aim of the study was to increase the speed, quantity and quality of solutions in intelligent systems aimed at solving the problem of structural–parametric synthesis of models of large discrete systems with a given behavior. As a hypothesis, it was assumed that the adapted model of an artificial neural network is able to control changes in the parameters of the functioning of the operators of the genetic algorithm directly in the process of solving the problem of intelligent structural–parametric synthesis of models of large discrete systems. To solve the problem of managing the process of intelligent search for solutions based on a genetic algorithm, an artificial neural network, which is used as an add-in, must dynamically change the “destructive” ability of operators based on data about the current and/or historical state of the population. In the article, the theory of Petri nets is used as a single mathematical device capable of modeling the work of evolutionary procedures. This mathematical tool is able to simulate the operation of a genetic algorithm adapted to solving the problem of structural–parametric synthesis of models of large discrete systems with a given behavior; simulate the operation and training of an artificial neural network; combine the genetic algorithm with a control add-in based on an artificial neural network to prevent attenuation and premature convergence; simulate the process of recognizing the state of the population; and simulate the operation of the models obtained as a result of the synthesis. As an example of the functioning of the proposed approach, the article presents the results of a computational experiment, which considers the problem of structural–parametric synthesis of computer technology based on the developed models of the element base-RS, D and T triggers that are capable of processing a given input vector into the required (reference) output. In the software implementation of the proposed approach, calculations on the CPU and CPU+GPGPU technologies were used.
Electrospun Janus Beads-On-A-String Structures for Different Types of Controlled Release Profiles of Double Drugs
Authors: Li Ding , Wang Menglong , Song Wen-Liang , Yu Deng-Guang , Bligh Sim Wan Annie
Published: April 2021

A side-by-side electrospinning process characterized by a home-made eccentric spinneret was established to produce the Janus beads-on-a-string products. In this study, ketoprofen (KET) and methylene blue (MB) were used as model drugs, which loaded in Janus beads-on-a-string products, in which polyvinylpyrrolidone K90 (PVP K90) and ethyl cellulose (EC) were exploited as the polymer matrices. From SEM images, distinct nanofibers and microparticles in the Janus beads-on-a-string structures could be observed clearly. X-ray diffraction demonstrated that all crystalline drugs loaded in Janus beads-on-a-string products were transferred into the amorphous state. ATR-FTIR revealed that the components of prepared Janus nanostructures were compatibility. In vitro dissolution tests showed that Janus beads-on-a-string products could provide typical double drugs controlled-release profiles, which provided a faster immediate release of MB and a slower sustained release of KET than the electrospun Janus nanofibers. Drug releases from the Janus beads-on-a-string products were controlled through a combination of erosion mechanism (linear MB-PVP sides) and a typical Fickian diffusion mechanism (bead KET-EC sides). This work developed a brand-new approach for the preparation of the Janus beads-on-a-string nanostructures using side-by-side electrospinning, and also provided a fresh idea for double drugs controlled release and the potential combined therapy.
Development of Optical Biosensor Using Protein A-Conjugated Chitosan–Gold Nanoparticles for Diagnosis of Cystic Echinococcosis
Authors: Safarpour Hanie , Majdi Hasan , Masjedi Ali , Pagheh Abdol Sattar , Pereira Maria de Lourdes , Rodrigues Oliveira Sonia M. , Ahmadpour Ehsan
Published: April 2021

Human echinococcosis is a serious parasitic diseasethat still affects millions of people in many parts of the world. Since it can offer a critical threat to people’s health, it is important to discover a rapid, convenient, and economical method for detection. Herein, we propose a novel point of care assay, namely, an enhanced immuno-dot-blot assay for diagnosis of cystic echinococcosis (hydatidosis). This method is based on the formation of a sandwich complex between a goldnanoprobe (chitosan–gold nanoparticleprotein A) and hydatid cyst antigen (Ag B), which holds anti-Ag B antibodies. Briefly, protein A was conjugated to chitosan–gold nanoparticles via glutaraldehyde chemistry. Then, Ag B was immobilized on the surface of a nitrocellulose membrane, which was followed by the addition of the sera sample and gold nanoprobes. The positive signals were easily detectable by naked eye. The signal intensity of this biosensor was proportional to the concentration of active anti-Echinococcus granulosus antibodies on the surface of the nanoparticles, titer of antibodies in the sera samples, and concentration of Ag B coated on the nitrocellulose membrane. The minimum concentration to use the protein A for conjugation to detect titer of anti-Echinococcus IgGand the concentration of Ag B coated in nitrocellulose membrane were 0.5 and 0.3 mg/mL, respectively. This enhanced immuno-dot-blot assay offers a simple diagnostic technique withoutthe need for expensive equipment for diagnosis of echinococcosis.
Platinum Complexes in Colorectal Cancer and Other Solid Tumors
Authors: Köberle Beate , Schoch Sarah
Published: April 2021

Cisplatin is one of the most commonly used drugs for the treatment of various solid neoplasms, including testicular, lung, ovarian, head and neck, and bladder cancers. Unfortunately, the therapeutic efficacy of cisplatin against colorectal cancer is poor. Various mechanisms appear to contribute to cisplatin resistance in cancer cells, including reduced drug accumulation, enhanced drug detoxification, modulation of DNA repair mechanisms, and finally alterations in cisplatin DNA damage signaling preventing apoptosis in cancer cells. Regarding colorectal cancer, defects in mismatch repair and altered p53-mediated DNA damage signaling are the main factors controlling the resistance phenotype. In particular, p53 inactivation appears to be associated with chemoresistance and poor prognosis. To overcome resistance in cancers, several strategies can be envisaged. Improved cisplatin analogues, which retain activity in resistant cancer, might be applied. Targeting p53-mediated DNA damage signaling provides another therapeutic strategy to circumvent cisplatin resistance. This review provides an overview on the DNA repair pathways involved in the processing of cisplatin damage and will describe signal transduction from cisplatin DNA lesions, with special attention given to colorectal cancer cells. Furthermore, examples for improved platinum compounds and biochemical modulators of cisplatin DNA damage signaling will be presented in the context of colon cancer therapy.
Treatment and Outcome Analysis of 639 Relapsed Non-Hodgkin Lymphomas in Children and Adolescents and Resulting Treatment Recommendations
Authors: Burkhardt Birgit , Taj Mary , Garnier Nathalie , Minard-Colin Veronique , Hazar Volkan , Mellgren Karin , Osumi Tomoo , Fedorova Alina , Myakova Natalia , Verdu-Amoros Jaime , Andres Mara , Kabickova Edita , Attarbaschi Andishe , Chiang Alan Kwok Shing , Bubanska Eva , Donska Svetlana , Hjalgrim Lisa Lyngsie , Wachowiak Jacek , Pieczonka Anna , Uyttebroeck Anne , Lazic Jelena , Loeffen Jan , Buechner Jochen , Niggli Felix , Csoka Monika , Krivan Gergely , Palma Julia , Burke G. A. Amos , Beishuizen Auke , Koeppen Kristin , Mueller Stephanie , Herbrueggen Heidi , Woessmann Wilhelm , Zimmermann Martin , Balduzzi Adriana , Pillon Marta
Published: April 2021

Despite poor survival, controversies remain in the treatment for refractory or relapsed pediatric non-Hodgkin lymphoma (r/r NHL). The current project aimed to collect international experience on the re-induction treatment of r/r NHL, hematopoietic stem cell transplantation (HSCT), risk factors associated with outcome, and to suggest treatment recommendations. Inclusion criteria were (i) refractory disease, disease progression or relapse of any NHL subtype except anaplastic large cell lymphoma, (ii) age < 18 years at initial diagnosis, (iii) diagnosis in/after January 2000. Data from 639 eligible patients were evaluable. The eight-year probability of overall survival was 34 ± 2% with highly significant differences according to NHL subtypes: 28 ± 3% for 254 Burkitt lymphoma/leukemia, 50 ± 6% for 98 diffuse large B-cell lymphomas, 57 ± 8% for 41 primary mediastinal large B-cell lymphomas, 27 ± 3% for 177 T-lymphoblastic lymphomas, 52 ± 10% for 34 precursor-B-cell lymphoblastic lymphomas and 30 ± 9% for 35 patients with rare NHL subtypes. Subtype-specific factors associated with survival and treatment recommendations are suggested. There were no survivors without HSCT, except in few very small subgroups. Conclusions: There is an urgent need to further improve survival in r/r NHL. The current study provides the largest real-world series, which underlines the role of HSCT and suggests treatment recommendations.
Role of Circulating Tumor DNA in Hematological Malignancy
Authors: Ogawa Miho , Yokoyama Kazuaki , Imoto Seiya , Tojo Arinobu
Published: April 2021

With the recent advances in noninvasive approaches for cancer diagnosis and surveillance, the term “liquid biopsy” has become more familiar to clinicians, including hematologists. Liquid biopsy provides a variety of clinically useful genetic data. In this era of personalized medicine, genetic information is critical to early diagnosis, aiding risk stratification, directing therapeutic options, and monitoring disease relapse. The validity of circulating tumor DNA (ctDNA)-mediated liquid biopsies has received increasing attention. This review summarizes the current knowledge of liquid biopsy ctDNA in hematological malignancies, focusing on the feasibility, limitations, and key areas of clinical application. We also highlight recent advances in the minimal residual disease monitoring of leukemia using ctDNA. This article will be useful to those involved in the clinical practice of hematopoietic oncology.
Immune Cell Infiltrates and Neutrophil-to-Lymphocyte Ratio in Relation to Response to Chemotherapy and Prognosis in Laryngeal and Hypopharyngeal Squamous Cell Carcinomas
Authors: Sánchez-Canteli Mario , Juesas Luis , Redin Esther , Calvo Alfonso , López Fernando , Astudillo Aurora , Montuenga Luis M. , García-Pedrero Juana M. , Rodrigo Juan P.
Published: April 2021

Our goal was to assess the correlation of immune parameters with the response to induction chemotherapy (ICT) in head and neck squamous cell carcinoma (HNSCC) patients. Pretreatment biopsies from 64 patients with HNSCC that received ICT were assessed for PD-L1 protein expression and density of CD8+ and FOXP3+ tumor infiltrating lymphocytes (TIL). In addition, the neutrophil-to-lymphocyte ratio (NLR) was calculated from pretreatment whole blood counts. In total, 55% of cases exhibited PD-L1 combined proportion score (CPS) positivity (≥1% stained cells). PD-L1 CPS positivity correlated with a high density of both CD8+ (p = 0.01) and FOXP3+ (p < 0.001) TILs. There was no correlation between PD-L1 expression or TIL density and NLR values. In univariate analyses, the absence of PD-L1 CPS expression (p = 0.042) and a high NLR (p = 0.034) were significantly correlated with response to ICT. Neither CD8+ TIL (p = 0.99) nor FOXP3+ TIL densities (p = 0.71) were associated with response to ICT. In multivariate analysis, only a high NLR was associated with response to ICT (HR = 4.06, 95% CI = 1.06–15.5, p = 0.04). In addition, a high NLR was also independently associated with lower disease-specific (p = 0.03) and overall survival rates (p = 0.04), particularly in the subset of patients who received definitive surgical treatment. These results suggest that NLR could emerge as a predictive biomarker of response to ICT.
Mouse Models for Deciphering the Impact of Homologous Recombination on Tumorigenesis
Authors: Matos-Rodrigues Gabriel , Martini Emmanuelle , Lopez Bernard S.
Published: April 2021

Homologous recombination (HR) is a fundamental evolutionarily conserved process that plays prime role(s) in genome stability maintenance through DNA repair and through the protection and resumption of arrested replication forks. Many HR genes are deregulated in cancer cells. Notably, the breast cancer genes BRCA1 and BRCA2, two important HR players, are the most frequently mutated genes in familial breast and ovarian cancer. Transgenic mice constitute powerful tools to unravel the intricate mechanisms controlling tumorigenesis in vivo. However, the genes central to HR are essential in mammals, and their knockout leads to early embryonic lethality in mice. Elaborated strategies have been developed to overcome this difficulty, enabling one to analyze the consequences of HR disruption in vivo. In this review, we first briefly present the molecular mechanisms of HR in mammalian cells to introduce each factor in the HR process. Then, we present the different mouse models of HR invalidation and the consequences of HR inactivation on tumorigenesis. Finally, we discuss the use of mouse models for the development of targeted cancer therapies as well as perspectives on the future potential for understanding the mechanisms of HR inactivation-driven tumorigenesis in vivo.
Facile Synthesis of Potassium-Doped Titanium Oxide Nanostructure (KTiOxs)/AlO(OH) Composites for Enhanced Photocatalytic Performance
Authors: Lee So Yoon , Matsubara Tatsuya , Numata Daiki , Serizawa Ai
Published: April 2021

Generally, nanoparticles (NPs) are used as photocatalysts, which sometimes results in difficulties in the separation and recycling of photocatalysts from suspensions after their application in water and wastewater treatment, which hinders industrial applications of NPs that are too fine to be removed by gravitational settling. This can be solved by using support NPs to overcome these problems. -OH enrich AlO(OH), which is produced by a steam coating process, has been could be used as a possible support, because the -OH groups on the surface can interact with foreign molecules; thus, various composite functional materials can be prepared. Potassium doped titanium oxide NPs, which are produced by a wet corrosion process, namely KTiOxs, have been selected as photocatalysts, because KTiOxs have sufficient K+ ions, thereby expecting the chemical bonding with -OH group from AlO(OH). This study fabricated a novel photocataysis system made by combining KTiOxs as catalysts and AlO(OH) as the catalysts’ support, namely KTiOxs/AlO(OH) composites. The KTiOxs nanowires, obtained from 10 mol/L of a KOH solution treated with Ti and AlO(OH) at 280 °C for 24 h through a steam coating process, yielded the highest surface area and the highest photocatalytic performance.
Transduction of Pig Small Airway Epithelial Cells and Distal Lung Progenitor Cells by AAV4
Authors: Chen Oliver G. , Mather Steven E. , Brommel Christian M. , Hamilton Bradley A. , Ehler Annie , Villacreses Raul , Girgis Reda E. , Abou Alaiwa Mahmoud , Stoltz David A. , Zabner Joseph , Li Xiaopeng
Published: April 2021

Cystic fibrosis (CF) is caused by genetic mutations of the CF transmembrane conductance regulator (CFTR), leading to disrupted transport of Cl− and bicarbonate and CF lung disease featuring bacterial colonization and chronic infection in conducting airways. CF pigs engineered by mutating CFTR develop lung disease that mimics human CF, and are well-suited for investigating CF lung disease therapeutics. Clinical data suggest small airways play a key role in the early pathogenesis of CF lung disease, but few preclinical studies have focused on small airways. Efficient targeted delivery of CFTR cDNA to small airway epithelium may correct the CFTR defect and prevent lung infections. Adeno-associated virus 4 (AAV4) is a natural AAV serotype and a safe vector with lower immunogenicity than other gene therapy vectors such as adenovirus. Our analysis of AAV natural serotypes using cultured primary pig airway epithelia showed that AAV4 has high tropism for airway epithelia and higher transduction efficiency for small airways compared with large airways. AAV4 mediated the delivery of CFTR, and corrected Cl− transport in cultured primary small airway epithelia from CF pigs. Moreover, AAV4 was superior to all other natural AAV serotypes in transducing ITGα6β4+ pig distal lung progenitor cells. In addition, AAV4 encoding eGFP can infect pig distal lung epithelia in vivo. This study demonstrates AAV4 tropism in small airway progenitor cells, which it efficiently transduces. AAV4 offers a novel tool for mechanistical study of the role of small airway in CF lung pathogenesis in a preclinical large animal model.
Sensory Stimulation in the NICU Environment: Devices, Systems, and Procedures to Protect and Stimulate Premature Babies
Authors: Vitale Francesco Massimo , Chirico Gaetano , Lentini Carmen
Published: April 2021

Prematurity deprives infants of the prenatal sensory stimulation essential to their correct development; in addition, the stressful environment of the NICU impacts negatively on their growth. The purpose of this review was to investigate the effects of NICU noise pollution on preterm infants and parents. We focused on the systems and projects used to control and modulate sounds, as well as on those special devices and innovative systems used to deliver maternal sounds and vibrations to this population. The results showed beneficial effects on the preterm infants in different areas such as physiological, autonomic, and neurobehavioral development. Although most of these studies highlight positive reactions, there is also a general acknowledgement of the current limits: small and heterogeneous groups, lack of structured variable measurements, systematic control groups, longitudinal studies, and normative values. The mother’s presence is always preferred, but the use of music therapy and the devices analyzed, although not able to replace her presence, aim to soften her absence through familiar and protective stimuli, which is a very powerful aid during the COVID-19 pandemic.