bluuebunny/crossref_metadata_2025 huggingface dataset:
The Effect of the COVID-19 Pandemic on Outpatient Antibiotic Prescription Rates in Children and Adolescents—A Claims-Based Study in Germany
Authors: Akmatov Manas K. , Kohring Claudia , Dammertz Lotte , Heuer Joachim , Below Maike , Bätzing Jörg , Holstiege Jakob
Published: October 2022

The aim of the study was to examine whether the COVID-19 pandemic had any effect on antibiotic prescription rates in children in Germany. Using the nationwide outpatient prescription data from the Statutory Health Insurance from 2010 to 2021, changes in the monthly prescriptions of systemic antibiotics dispensed to children aged 0–14 years were examined (n = 9,688,483 in 2021). Interrupted time series analysis was used to assess the effect of mitigation measures against SARS-COV-2, introduced in March and November 2020, on antibiotic prescription rates. In the pre-pandemic period, the antibiotic prescription rates displayed a linear decrease from 2010 to 2019 (mean annual decrease, –6%). In 2020, an immediate effect of mitigation measures on prescription rates was observed; in particular, the rate decreased steeply in April (RR 0.24, 95% CI: 0.14–0.41) and November 2020 (0.44, 0.27–0.73). The decrease was observed in all ages and for all antibiotic subgroups. However, this effect was temporary. Regionally, prescription rates were highly correlated between 2019 and 2020/2021. Substantial reductions in antibiotic prescription rates following the mitigation measures may indicate limited access to medical care, changes in care-seeking behavior and/or a decrease of respiratory infections. Despite an all-time low of antibiotic use, regional variations remained high and strongly correlated with pre-pandemic levels.
Conditions Conducive to the Glutathionylation of Complex I Subunit NDUFS1 Augment ROS Production following the Oxidation of Ubiquinone Linked Substrates, Glycerol-3-Phosphate and Proline
Authors: Wang Kevin , Hirschenson Jonathan , Moore Amanda , Mailloux Ryan J.
Published: October 2022

Mitochondrial complex I can produce large quantities of reactive oxygen species (ROS) by reverse electron transfer (RET) from the ubiquinone (UQ) pool. Glutathionylation of complex I does induce increased mitochondrial superoxide/hydrogen peroxide (O2●−/H2O2) production, but the source of this ROS has not been identified. Here, we interrogated the glutathionylation of complex I subunit NDUFS1 and examined if its modification can result in increased ROS production during RET from the UQ pool. We also assessed glycerol-3-phosphate dehydrogenase (GPD) and proline dehydrogenase (PRODH) glutathionylation since both flavoproteins have measurable rates for ROS production as well. Induction of glutathionylation with disulfiram induced a significant increase in O2●−/H2O2 production during glycerol-3-phosphate (G3P) and proline (Pro) oxidation. Treatment of mitochondria with inhibitors for complex I (rotenone and S1QEL), complex III (myxothiazol and S3QEL), glycerol-3-phosphate dehydrogenase (iGP), and proline dehydrogenase (TFA) confirmed that the sites for this increase were complexes I and III, respectively. Treatment of liver mitochondria with disulfiram (50–1000 nM) did not induce GPD or PRODH glutathionylation, nor did it affect their activities, even though disulfiram dose-dependently increased the total number of protein glutathione mixed disulfides (PSSG). Immunocapture of complex I showed disulfiram incubations resulted in the modification of NDUFS1 subunit in complex I. Glutathionylation could be reversed by reducing agents, restoring the deglutathionylated state of NDUFS1 and the activity of the complex. Reduction of glutathionyl moieties in complex I also significantly decreased ROS production by RET from GPD and PRODH. Overall, these findings demonstrate that the modification of NDUFS1 can result in increased ROS production during RET from the UQ pool, which has implications for understanding the relationship between mitochondrial glutathionylation reactions and induction of oxidative distress in several pathologies
Phytochemical Screening and Bioactive Properties of Juglans regia L. Pollen
Authors: Żurek Natalia , Pycia Karolina , Pawłowska Agata , Kapusta Ireneusz Tomasz
Published: October 2022

Pollen is one of the major by-products of the walnut tree, yet it is poorly investigated. Thus, the aim of this study was to investigate the total phenolics, flavonoids, antioxidant, anticancer potential, and polyphenol profile of pollen obtained from male Juglans regia flowers. A total of 24 phenolic compounds were identified in Juglans regia pollen and all of them were reported for the first time for this raw material. The content of polyphenols was 408.03 mg/100 g dry weight (dw) and the most abundant components were quercetin 3-O-sophoroside and 4′,5,7-trihydroxy-3,6-dimethoxyflavone-7-O-beta-D-glucoside. The concentration of these compounds, as well as the total content of polyphenols and flavonoids, strongly determined the antioxidant and cytotoxic activity of Juglans regia pollen. Antioxidant action using the ABTS and CUPRAC methods had the values of 3.35 and 0.32 mmol TE/g dw, respectively. In turn, in the tests of chelating ability of ferrous ion, O2•− and OH− radical scavenging activity, of which the results were expressed as IC50, the values were equal to 335.01, 459.31, and 92.89 µg/mL, respectively. Among the six cancer cell lines, the strongest effect was demonstrated for Caco-2 (140.65 µg/mL) and MCF-7 (140.98 µg/mL) cells. The results provide valuable and previously unpublished data on the polyphenol composition and biological potential of Juglans regia pollen.
AT-CRF: A Chinese Reading Comprehension Algorithm Based on Attention Mechanism and Conditional Random Fields
Authors: Shi Nawei , Wang Huazhang , Cheng Yongqiang
Published: October 2022

Machine reading comprehension (MRC) is an important research topic in the field of Natural Language Processing (NLP). However, traditional MRC models often face challenges of information loss, lack of capability to retain long-distance dependence, and inability to deal with unanswerable questions where answers are not available in given texts. In this paper, a Chinese reading comprehension algorithm, called the Attention and Conditional Random Filed (AT-CRF) Reader, is proposed to address the above challenges. Firstly, RoBERTa, a pre-trained language model, is introduced to obtain the embedding representations of input. Then, a depthwise separable convolution neural network and attention mechanisms are used to replace the recurrent neural network for encoding. Next, the attention flow and self-attention mechanisms are used to obtain the context–query internal relation. Finally, the conditional random field is used to handle unanswerable questions and predict the correct answer. Experiments were conducted on the two Chinese machine reading comprehension datasets, CMRC2018 and DuReader-checklist, and the results showed that, compared with the baseline model, the F1 scores achieved by our AT-CRF Reader model has improved by 2.65% and 2.68%, and the EM values increased by 4.45% and 3.88%.
VAPPD: Visual Analysis of Protein Pocket Dynamics
Authors: Guo Dongliang , Feng Li , Shi Chuanbao , Cao Lina , Li Yu , Wang Yanfen , Xu Ximing
Published: October 2022

Analyzing the intrinsic dynamic characteristics of protein pockets is a key aspect to understanding the functional mechanism of proteins, which is conducive to the discovery and development of drugs. At present, the research on the dynamic characteristics of pockets mainly focuses on pocket stability, similarity, and physicochemical properties. However, due to the high complexity and diversity of high-dimensional pocket data in dynamic processes, this work is challenging. In this paper, we explore the dynamic characteristics of protein pockets based on molecular dynamics (MD) simulation trajectories. First, a dynamic pocket shape representation method combining topological feature data is proposed to improve the accuracy of pocket similarity calculation. Secondly, a novel high-dimensional pocket similarity calculation method based on pocket to vector dynamic time warp (P2V-DTW) is proposed to solve the correlation calculation problem of unequal length sequences. Thirdly, a visual analysis system of protein dynamics (VAPPD) is proposed to help experts study the characteristics of high-dimensional dynamic pockets in detail. Finally, the efficiency of our approach is demonstrated in case studies of GPX4 and ACE2. By observing the characteristic changes of pockets under different spatiotemporal scales, especially the motion correlation between pockets, we can find the allosteric pockets. Experts in the field of biomolecules who cooperated with us confirm that our method is efficient and reliable, and has potential for high-dimensional dynamic pocket data analysis.
Risk Coupling Analysis of Deep Foundation Pits Adjacent to Existing Underpass Tunnels Based on Dynamic Bayesian Network and N–K Model
Authors: Jiang Jie , Liu Guangyang , Ou Xiaoduo
Published: October 2022

Because deep foundation pits and tunnels are deformation-sensitive structures, the safety of these projects is generally affected by coupled risks. In deep foundation pit construction, if the existing tunnel structure adjacent to the deposit is damaged, it can produce a severe group disaster. It is necessary to identify an efficient risk analysis model to study the dynamic coupled risk of deep foundation pit projects adjacent to existing underpass tunnels and to analyze the risk evolution law to achieve effective real-time safety control. This study proposes a coupled risk analysis model using the N–K model and dynamic Bayesian network to construct deep foundation pits in adjacent existing underpass tunnels. The model is predicated on association rules to explore the interrelationship between risk factors to build a dynamic Bayesian network structure. In addition, the N–K model is utilized to quantify coupled risks under such complex working conditions and to optimize the dynamic Bayesian network structure. The developed model clarifies the risk coupling mechanism of deep foundation pit construction adjacent to an existing underpass tunnel, finds the critical points in the risk transfer process, and conducts dynamic risk prediction and accident causation diagnosis for the coupled risk to realize the dynamic control of the coupled risk in the adjacent existing underpass tunnel construction. Taking the Nanning underground comprehensive utilization project as an example, the validity and applicability of the proposed approach were tested. The results showed that the model is feasible and has application potential, providing effective decision support for safety control while constructing deep foundation pits adjacent to existing tunnels.
Current-Feedback Instrumentation Amplifier Using Dual-Chopper Fill-In Technique
Authors: Choi Gyuri , Nam Kyeongsik , Yoo Mookyoung , Kang Sanggyun , Jin Byeongkwan , Kim Kyounghwan , Son Hyeoktae , Ko Hyoungho
Published: October 2022

In this study, we describe a dual-chopper glitch-reduction current-feedback instrumentation amplifier (CFIA) with a ripple reduction loop. The amplifier employs the chopping technique to reduce low-frequency noise, such as 1/f noise. A glitch caused by chopping occurs at each chopper clock edge and results in intermodulation distortion (IMD). Owing to the input offset, the chopping technique also produces ripples. In this study, the glitch-induced IMD was reduced using a fill-in technique whereby only neat signals were alternately used as outputs by avoiding the glitch section with dual-chopping channel CFIA. To avoid using a high-order, low-frequency filter, a ripple reduction loop was implemented to reduce the ripple generated by chopping. The CFIA is based on a low-noise chopper fully differential difference amplifier with a cascode stage and a Monticelli-class AB output stage, which can drive a larger load and increase power efficiency. The proposed dual-chopper CFIA was fabricated using a 0.18 µm CMOS standard process, and its current consumption with a 1.8-V power supply is 29.5 μA. The proposed CFIA has a gain of 51 V/V, input referred noise of 53.3 nV/√Hz at 1 Hz, and a noise efficiency factor of 4.48.
Model Test on Effect of Ground Fissure on the Behavior of Oblique Two-Section Subway Tunnel
Authors: Liu Lei , Ma Tao , Yan Jin-Kai , Wang Zhi-Hui
Published: October 2022

The dynamic interaction between the ground fissure and an oblique two-section horseshoe-shaped subway tunnel under the subway dynamic load was investigated based on a series of model tests in this study. The results indicated that the subway subway-induced vibration attenuated in different degrees when propagating in the directions in the soil layer, while the ground fissure had an attenuation effect on subway vibration. Furthermore, the vibration of the soil layer below the tunnel near the ground fissure was stronger than that of the upper soil layer, and the vibration response at the tunnel bottom was stronger than that of the arch waist and the tunnel crown. The additional contact pressure between the tunnel bottom and the soil was relatively large when the ground fissure was not active, while the additional strain at the top and bottom of the tunnel caused by the excitation was small. Moreover, when the hanging wall of the ground fissure descended, the additional contact pressure at the tunnel crown in the hanging wall and the tunnel bottom in the footwall significantly increased, and a negative additional stain was identified at those two positions. Meanwhile, a positive additional stain was identified at the tunnel crown in the footwall and the tunnel crown in the hanging wall, increasing with the descent of the hanging wall.
Surgical Tool Detection in Open Surgery Videos
Authors: Fujii Ryo , Hachiuma Ryo , Kajita Hiroki , Saito Hideo
Published: October 2022

Detecting surgical tools is an essential task for analyzing and evaluating surgical videos. However, most studies focus on minimally invasive surgery (MIS) and cataract surgery. Mainly because of a lack of a large, diverse, and well-annotated dataset, research in the area of open surgery has been limited so far. Open surgery video analysis is challenging because of its properties: varied number and roles of people (e.g., main surgeon, assistant surgeons, and nurses), a complex interaction of tools and hands, various operative environments, and lighting conditions. In this paper, to handle these limitations and difficulties, we introduce an egocentric open surgery dataset that includes 15 open surgeries recorded with a head-mounted camera. More than 67k bounding boxes are labeled to 19k images with 31 surgical tool categories. Finally, we present a surgical tool detection baseline model based on recent advances in object detection. The results of our new dataset show that our presented dataset provides enough interesting challenges for future methods and that it can serve as a strong benchmark to address the study of tool detection in open surgery.
Complementary Strategies for Deciphering the Information Contained in Ancient Parchment Documentary Materials
Authors: Piñar Guadalupe , Cappa Federica , Vetter Wilfried , Schreiner Manfred , Miklas Heinz , Sterflinger Katja
Published: October 2022

This article reviews the complementary strategies that are used to decipher the valuable information that is contained in ancient parchment documentary materials. A new trend is molecular analysis, which has given rise to the emerging field of biocodicology, comprising protein and DNA analysis for the identification of the biological origin of the skins that are used for their manufacture. In addition, DNA analysis can identify the microbiome that is present in the object under investigation, which adds value by providing information on its history and state of preservation. In any case, it is important to complement the biomolecular investigations with microscopical and physicochemical analyses. Some of the complementary analytical techniques that are reviewed here, such as elemental analysis by X-ray fluorescence (XRF) with compound-specific analytical methods such as Fourier transform infrared (FTIR) and Raman spectroscopy are advantageous as they can be applied in a non-invasive way and without inducing any changes in the objects.
Trend and Representativeness of Acoustic Features of Broiler Chicken Vocalisations Related to CO2
Authors: Ginovart-Panisello Gerardo José , Iriondo Sanz Ignasi , Panisello Monjo Tesa , Riva Silvia , Garriga Dicuzzo Tomas , Abancens Escuer Eva , Alsina-Pagès Rosa Ma
Published: October 2022

The concentration of CO2 is relatively large in poultry farms and high accumulations of this gas reduce animal welfare. Good control of its concentration is crucial for the health of the animals. The vocalizations of the chickens can show their level of well-being linked to the presence of carbon dioxide. An audio recording system was implemented and audio raw data was processed to extract acoustical features from four cycles of forty days, three of them from the same farm. This research aims to find the most relevant acoustic features extracted from the broiler’s calls that are related to the CO2 concentration and that could help to automate procedures. The results are encouraging since MFCC 6, 9, 4 and 3 are the most important features that relate the vocalizations of the chickens to the gas concentration, furthermore there is a clear and more similar representativeness trend during birds’ life period from day 15 to day 40.
The Influence of Flight Direction and Camera Orientation on the Quality Products of UAV-Based SfM-Photogrammetry
Authors: Ahmed Shaker , El-Shazly Adel , Abed Fanar , Ahmed Wael
Published: October 2022

Unmanned aerial vehicles (UAVs) can provide valuable spatial information products for many projects across a wide range of applications. One of the major challenges in this discipline is the quality of positioning accuracy of the resulting mapping products in professional photogrammetric projects. This is especially true when using low-cost UAV systems equipped with GNSS receivers for navigation. In this study, the influence of UAV flight direction and camera orientation on positioning accuracy in an urban area on the west bank of the Euphrates river in Iraq was investigated. Positioning accuracy was tested in this study with different flight directions and camera orientation settings using a UAV autopilot app (Pix4Dcapture software (Ver. 4.11.0)). The different combinations of these two main parameters (camera orientation and flight direction) resulted in 11 different flight cases for which individual planimetric and vertical accuracies were evaluated. Eleven flight sets of dense point clouds, DEMs, and ortho-imagery were created in this way to compare the achieved positional accuracies. One set was created using the direct georeferencing method (without using GCPs), while the other ten sets were created using the indirect georeferencing approach based on ground truth measurements of five artificially created GCPs. Positional accuracy was found to vary depending on the user-defined flight plan settings, despite an approximately constant flight altitude. However, it was found that the horizontal accuracy achieved was better than the vertical accuracy for all flight sets. This study revealed that combining multiple sets of images with different flight directions and camera orientations can significantly improve the overall positional accuracy to reach several centimeters.
Predictive Modeling of Employee Churn Analysis for IoT-Enabled Software Industry
Authors: Naz Komal , Siddiqui Isma Farah , Koo Jahwan , Khan Mohammad Ali , Qureshi Nawab Muhammad Faseeh
Published: October 2022

Employee churn analytics is the process of assessing employee turnover rate and predicting churners in a corporate company. Due to the rapid requirement of experts in the industries, an employee may switch workplaces, and the company then has to look for a substitute with the training to deal with the tasks. This has become a bottleneck and the corporate sector suffers with additional cost overheads to restore the work routine in the organization. In order to solve this issue in a timely manner, we identify several ML techniques that examine an employee’s record and assess factors in generalized ways to assess whether the resource will remain to continue working or may leave the workplace with the passage of time. However, sensor-based information processing is not much explored in the corporate sector. This paper presents an IoT-enabled predictive strategy to evaluate employee churn count and discusses the factors to decrease this issue in the organizations. For this, we use filter-based methods to analyze features and perform classification to identify firm future churners. The performance evaluation shows that the proposed technique efficiently identifies the future churners with 98% accuracy in the IoT-enabled corporate sector organizations.
Nanotechnology-Based Strategies for Treatment of Obesity, Cancer and Anti-microbial Resistance: Highlights of the Department of Science and Innovation/Mintek Nanotechnology Innovation Centre Biolabels Research Node at the University of the Western Cape
Authors: Sibuyi Nicole Remaliah Samantha , Moabelo Koena Leah , Meyer Samantha , Skepu Amanda , Onani Martin Opiyo , Madiehe Abram Madimabe , Meyer Mervin
Published: October 2022

Nanotechnology has recently received much interest in various fields, including medicine. South Africa (SA) was the first country in Africa to adopt the technology with the aim of enhancing the national bio-economy and global competitiveness by using innovative nanotechnology-based solutions. Since its inception in 2005 in SA, researchers have seized opportunities to increase and develop niche areas for its application in the health, energy, food, agriculture, and water sectors. We ventured into this field and have performed pioneering work on nanotechnology-based treatment strategies over the years. This perspective highlights the journey, with associated successes over the years, in order to display the impact of our nanotechnology research in health. The focus is on the nanotechnology outputs that have emanated from the Department of Science and Innovation (DSI)/Mintek Nanotechnology Innovation Centre (NIC) Biolabels Research Node (BRN) at the University of the Western Cape (UWC). BRN’s research interests were on nano-enabled materials for developing therapeutic agents, photothermal sensitizers, and targeted drug-delivery systems for treatment of chronic diseases and antimicrobial resistance.
Effective Data Utilization in the Context of Industry 4.0 Technology Integration
Authors: Janík Samuel , Szabó Peter , Mĺkva Miroslava , Mareček-Kolibiský Martin
Published: October 2022

We are part of the digital transformation of society and industry. The digital transformation of industry is based on new technologies brought about by the fourth industrial revolution. The Internet of Things (IoT), Cloud Computing, Cyber–Physical Systems (CPS) and Big Data provide the digital link between machines and individuals in processes. This completely new system is based on efficient data collection, data analysis and immediate interventions in organizational processes based on the results of the analysis. Smart organizations are driven by data and not by models. By working efficiently with the vast amounts of data available, the smart organizations of the future can ensure business sustainability, increase competitiveness through process optimization and reduce costs. In general, the aim of this paper was to identify the means to achieve a paradigm shift from traditional organizations to smart organizations through the use of data in the context of integrating Industry 4.0 technologies. The aim of the research was to determine the extent to which different Industry 4.0 technologies are applied in the effective use of data from specific activities/processes in industrial organizations to bring about a paradigm shift from traditional organizations to smart organizations. The first part of the paper describes the theoretical background of the transition from traditional to smart organizations using selected Industry 4.0 technologies. The second part of the paper characterizes the research objective, the methods used in the paper and the basic statistics used to determine the research questions and hypotheses. The next section evaluates the research questions and hypotheses that were used to meet the research objective. The last part of the paper is a summary of the obtained results, based on which we conclude that the primary challenge for organizations in the Slovak Republic is to learn how to work with the collected data, the need for their appropriate structuring and subsequent archiving, which is manifested by the need for training and application of data analysts in a broader context.
Research on the Obstacle-Avoidance Steering Control Strategy of Tracked Inspection Robots
Authors: Wang Chuanwei , Wang Saisai , Ma Hongwei , Zhang Heng , Xue Xusheng , Tian Haibo , Zhang Lei
Published: October 2022

Tracked inspection robots possess prominent advantages in dealing with severe environment rescue, safety inspection, and other important tasks, and have been used widely. However, tracked robots are affected by skidding and slipping, so it is difficult to achieve accurate control. For example, the control parameters of a tracked robot are the same during driving, but the pressure, shear force and steering resistance of the robot on the road surface are different, which affects the steering characteristics of the robot on complex terrain. Based on analysis of the structural parameters and steering radius of the robot, the traction force and resistance torque models of the tracked robot were established, and the plane dynamics of the robot’s steering were analyzed and solved. The corresponding relationships between the road parameters, relative steering radius, and lateral relative offset of the robot on three typical roads were obtained. Mathematical models of the robot’s track speed and relative steering radius with and without skid and slip were established. Through simulation analysis of Matlab software, the corresponding relationship between the relative steering radius of the robot and the velocity difference of the two tracks were obtained. Taking angular obstacles as an example, three obstacle-avoidance steering control strategies, once turning in situ center, twice turning in situ center, and large-radius steering were developed. The tracked robot and obstacle multi-body dynamic simulation models were constructed using ADAMS simulation software. The simulation results show that all three methods can complete the steering tasks according to the requirements; however, under the influence of skid and slip, the trajectory of the robot deviates from the ideal trajectory, which has a great impact on large-radius steering, even though the large-radius obstacle-avoidance steering control strategy has the advantages of a smooth trajectory, fast steering speed, and high efficiency. The obstacle-avoidance steering experiments were completed by the robot prototype, which verifies the rationality of robot steering theory, which could provide the corresponding theoretical basis for autonomous obstacle-avoidance navigation control of a tracked robot.
The Conditional Probability of Correlating East Pacific Earthquakes with NOAA Electron Bursts
Authors: Fidani Cristiano
Published: October 2022

A correlation between low L-shell 30–100 keV electrons precipitating into the atmosphere and M ≥ 6 earthquakes in West Pacific was presented in past works where ionospheric events anticipated earthquakes by 1.5–3.5 h. This was a statistical result obtained from the Medium Energy Protons Electrons Detector on board the NOAA-15 satellite, which was analyzed for 16.5 years. The present analysis, utilizing the same database, translated into adiabatic coordinates during geomagnetic quiet periods, lead to another significant correlation regarding East Pacific strong earthquakes. This new correlation is still observed between high energy precipitating electrons detected by the NOAA-15 0° telescope and M ≥ 6 events of another very dangerous seismic region of the Pacific ring of fire. The particle precipitation that contributed to this correlation was characterized by electron L-shell, pitch-angle, possible disturbance altitudes, and geographical locations. This correlation occurred circa 57 h prior to the East Pacific earthquakes, according to past single cases of reports. The conditional probability corresponding to the cross-correlation peak of 0.024 per binary events reached a value of 0.011. A probability gain of 2 was calculated for earthquakes after an independent L-shell EBs detection, it is therefore applicable for future earthquake forecasting experiments. Moreover, a time-dependent probability gain approaching the correlation peak was estimated.
Health Risks Associated with Polycyclic Aromatic Hydrocarbons (PAHs) in Dustfall Collected from Universities in Wuhan, China
Authors: Liu Ying , Mao Yao , Xu Jun , Chen Wenmin , Hu Tianpeng , Xu Chengyan , Liu Weijie , Qu Chengkai , Chen Wei , Zhang Jiaquan , Xing Xinli , Qi Shihua
Published: October 2022

Atmospheric dustfall samples from the libraries and dormitories of 14 universities in Wuhan, China, were collected and analyzed for 16 priority polycyclic aromatic hydrocarbons (PAHs). The results showed that the levels of Σ16PAHs in the dustfall from libraries varied from 2.45 to 13.4 μg·g−1, with an average value of 5.06 μg·g−1, while that of dormitories ranged from 2.61 to 10.6 μg·g−1, with an average of 5.19 μg·g−1. The compositions of PAHs in library and dormitory dustfall were similar, and they were dominated by high molecular weight PAHs (HMW-PAHs) (including fluoranthene, benzo(b)fluoranthene, and chrysene), which accounted for 79.2% of the total PAHs. Spatially, the higher levels of PAHs contamination were mainly distributed in areas with high population density and heavy traffic, which suggests that anthropogenic activities made an important contribution to the PAHs emissions. The diagnostic ratios and principal component analyses (PCA) indicated that combustion-related anthropogenic sources, such as petroleum, coal, and biomass combustion, as well as vehicular traffic emission, were the main sources of PAHs bound to dustfall. The toxic equivalent concentrations (BaPeq) of dustfall-bound PAHs ranged from 271 to 2510 μg·kg−1. According to the health risk assessment results, dermal contact was the predominant exposure pathway, followed by ingestion and inhalation. The incremental lifetime cancer risks (ILCRs) of exposure to PAHs in dustfall was 1.230 × 10−6−1.140 × 10−5, which indicates that there are low potential carcinogenic risks in the universities.
Numerical Investigation on the Influence of Class Number and Wavelength on the Performance of Curved Vane Demisters
Authors: Cai Zhen , Wang Pengfei , Luo Xiangyu , Huang Jin , Qin Zhenqi , Mei Jinna , Zhao Wensheng
Published: October 2022

Curved vane demisters with high efficiency are widely used in power, chemical, and gas industries. To reveal the relationship between the separation performance and the basic geometric parameters used in the steam generator. In this paper, the influence of wavelength on droplet separation performance has been numerically studied. Additionally, the pressure drops, friction factor, and separation efficiency of the two-phase flow are numerically analyzed. Then, grade separation efficiency is numerically investigated, and the overall separation efficiency is obtained to evaluate the separation performance. It is found that a prolonged wavelength L can initially increase and thereafter decrease the separation efficiency. However, when the wavelength increases to a high level, continuously increasing the wavelength decreases the droplet re-entrainment mass source.
Development of a Data-Driven Method for Online Battery Remaining-Useful-Life Prediction
Authors: Hell Sebastian Matthias , Kim Chong Dae
Published: October 2022

Remaining-useful-life (RUL) prediction of Li-ion batteries is used to provide an early indication of the expected lifetime of the battery, thereby reducing the risk of failure and increasing safety. In this paper, a detailed method is presented to make long-term predictions for the RUL based on a combination of gated recurrent unit neural network (GRU NN) and soft-sensing method. Firstly, an indirect health indicator (HI) was extracted from the charging processes using a soft-sensing method that can accurately describe power degradation instead of capacity. Then, a GRU NN with a sliding window was applied to learn the long-term performance development. The method also uses a dropout and early stopping method to prevent overfitting. To build the models and validate the effectiveness of the proposed method, a real-world NASA battery data set with various battery measurements was used. The results show that the method can produce a long-term and accurate RUL prediction at each position of the degradation progression based on several historical battery data sets.
Current Technologies to Accelerate the Aging Process of Alcoholic Beverages: A Review
Authors: Krüger Roselini Trapp , Alberti Aline , Nogueira Alessandro
Published: October 2022

The aging process contributes to the sensory evolution of alcoholic beverages, producing changes in the color and flavor of the final product. Traditionally, aging has occurred by storing beverages in wooden barrels for several months or years. To meet the demand for aged beverages, there is a need for large storage areas, a large number of wooden barrels, and, consequently, large volumes of stored product. Evaporation losses can also occur. In addition to the reactions of the beverage itself, there is also a transfer of wood compounds to the drink, which is later modified by successive oxidation reactions. This study addresses the alternative methods for accelerating the aging stage of beverages. These include the use of wood fragments, ultrasound, micro-oxygenation, pulsed electric field, high hydrostatic pressure, and microwave and gamma irradiation. These methods can be applied to optimize the process of extracting wood compounds, promote free radical formation, reduce oxidation reaction time, and accelerate yeast autolysis time. This study provides examples of some of the aforementioned methods. These technologies add value to the aging process, since they contribute to the reduction of production costs and, consequently, can increase commercial competitiveness.
Drug-Disease Association Prediction Using Heterogeneous Networks for Computational Drug Repositioning
Authors: Kim Yoonbee , Jung Yi-Sue , Park Jong-Hoon , Kim Seon-Jun , Cho Young-Rae
Published: October 2022

Drug repositioning, which involves the identification of new therapeutic indications for approved drugs, considerably reduces the time and cost of developing new drugs. Recent computational drug repositioning methods use heterogeneous networks to identify drug–disease associations. This review reveals existing network-based approaches for predicting drug–disease associations in three major categories: graph mining, matrix factorization or completion, and deep learning. We selected eleven methods from the three categories to compare their predictive performances. The experiment was conducted using two uniform datasets on the drug and disease sides, separately. We constructed heterogeneous networks using drug–drug similarities based on chemical structures and ATC codes, ontology-based disease–disease similarities, and drug–disease associations. An improved evaluation metric was used to reflect data imbalance as positive associations are typically sparse. The prediction results demonstrated that methods in the graph mining and matrix factorization or completion categories performed well in the overall assessment. Furthermore, prediction on the drug side had higher accuracy than on the disease side. Selecting and integrating informative drug features in drug–drug similarity measurement are crucial for improving disease-side prediction.
Construction and Analysis of an Enzyme-Constrained Metabolic Model of Corynebacterium glutamicum
Authors: Niu Jinhui , Mao Zhitao , Mao Yufeng , Wu Ke , Shi Zhenkun , Yuan Qianqian , Cai Jingyi , Ma Hongwu
Published: October 2022

The genome-scale metabolic model (GEM) is a powerful tool for interpreting and predicting cellular phenotypes under various environmental and genetic perturbations. However, GEM only considers stoichiometric constraints, and the simulated growth and product yield values will show a monotonic linear increase with increasing substrate uptake rate, which deviates from the experimentally measured values. Recently, the integration of enzymatic constraints into stoichiometry-based GEMs was proven to be effective in making novel discoveries and predicting new engineering targets. Here, we present the first genome-scale enzyme-constrained model (ecCGL1) for Corynebacterium glutamicum reconstructed by integrating enzyme kinetic data from various sources using a ECMpy workflow based on the high-quality GEM of C. glutamicum (obtained by modifying the iCW773 model). The enzyme-constrained model improved the prediction of phenotypes and simulated overflow metabolism, while also recapitulating the trade-off between biomass yield and enzyme usage efficiency. Finally, we used the ecCGL1 to identify several gene modification targets for l-lysine production, most of which agree with previously reported genes. This study shows that incorporating enzyme kinetic information into the GEM enhances the cellular phenotypes prediction of C. glutamicum, which can help identify key enzymes and thus provide reliable guidance for metabolic engineering.
Differential Effects of Beta-Hydroxybutyrate Enantiomers on Induced Pluripotent Stem Derived Cardiac Myocyte Electrophysiology
Authors: Klos Matthew L. , Hou Wanqing , Nsengimana Bernard , Weng Shiwang , Yan Chuyun , Xu Suowen , Devaney Eric , Han Shuxin
Published: October 2022

Beta-hydroxybutyrate (βOHB), along with acetoacetate and acetone, are liver-produced ketone bodies that are increased after fasting or prolonged exercise as an alternative fuel source to glucose. βOHB, as the main circulating ketone body, is not only a G-protein coupled receptor ligand but also a histone deacetylases inhibitor, prompting the reexamination of its role in health and disease. In this study, we compared the effects of two commercial βOHB formulations an enantiomer R βOHB and a racemic mixture ±βOHB on induced pluripotent stem cell cardiac myocytes (iPS-CMs) electrophysiology. Cardiac myocytes were cultured in R βOHB or ±βOHB for at least ten days after lactate selection. Flouvolt or Fluo-4 was used to assay iPS-CMs electrophysiology. We found that while both formulations increased the optical potential amplitude, R βOHB prolonged the action potential duration but ±βOHB shortened the action potential duration. Moreover, ±βOHB increased the peak calcium transient but R βOHB reduced the peak calcium transient. Co-culturing with glucose or fatty acids did not ameliorate the effects, suggesting that βOHB was more than a fuel source. The effect of βOHB on iPS-CMs electrophysiology is most likely stereoselective, and care must be taken to evaluate the role of exogenous βOHB in health and disease.
Blood Adipokines/Cytokines in Young People with Chronic Bronchitis and Abdominal Obesity
Authors: Khudiakova Alena Dmitrievna , Polonskaya Yana Vladimirovna , Shramko Victoria Sergeevna , Shcherbakova Lilia Valeryevna , Striukova Evgeniia Vitalievna , Kashtanova Elena Vladimirovna , Ragino Yulia Igorevna
Published: October 2022

The pathogenesis of the development of chronic lung diseases assumes the participation of systemic inflammation factors, as well as hormone-like substances produced by adipose tissue. The aim of this study was to evaluate the associations of certain adipokines/cytokines and chronic bronchitis against the background of abdominal obesity in young people. The study included 1415 people aged 25−44. In total, 115 people were selected by the random numbers method, who were divided into two subgroups: those with chronic bronchitis and abdominal obesity and those with chronic bronchitis without abdominal obesity. A control group of patients with comparable gender and age was also selected. In the group of patients with chronic bronchitis, adiponectin, TNFa and GIP levels were 1.4 times higher. The levels of C-peptide, MCP-1 and PP in the group of chronic bronchitis were 1.3 times higher compared to the control. Adipsin, lipocalin-2, IL-6 and resistin were significantly higher in the group with chronic bronchitis. Glucagon, amylin and ghrelin were 2.2, 2.3 and 3.2 times lower, respectively, in the group of patients with chronic bronchitis. Against the background of abdominal obesity, the probability of having chronic bronchitis increased with an increase in the level of lipocalin-2 and GIP and TNFa.
Pancreatic Cancer Research beyond DNA Mutations
Authors: Sato Hiromichi , Sasaki Kazuki , Hara Tomoaki , Tsuji Yoshiko , Arao Yasuko , Otsuka Chihiro , Hamano Yumiko , Ogita Mirei , Kobayashi Shogo , di Luccio Eric , Hirotsu Takaaki , Doki Yuichiro , Eguchi Hidetoshi , Satoh Taroh , Uchida Shizuka , Ishii Hideshi
Published: October 2022

Pancreatic ductal adenocarcinoma (PDAC) is caused by genetic mutations in four genes: KRAS proto-oncogene and GTPase (KRAS), tumor protein P53 (TP53), cyclin-dependent kinase inhibitor 2A (CDKN2A), and mothers against decapentaplegic homolog 4 (SMAD4), also called the big 4. The changes in tumors are very complex, making their characterization in the early stages challenging. Therefore, the development of innovative therapeutic approaches is desirable. The key to overcoming PDAC is diagnosing it in the early stages. Therefore, recent studies have investigated the multifaced characteristics of PDAC, which includes cancer cell metabolism, mesenchymal cells including cancer-associated fibroblasts and immune cells, and metagenomics, which extend to characterize various biomolecules including RNAs and volatile organic compounds. Various alterations in the KRAS-dependent as well as KRAS-independent pathways are involved in the refractoriness of PDAC. The optimal combination of these new technologies is expected to help treat intractable pancreatic cancer.
News about Structure and Function of Synapses: Health and Diseases
Authors: Meldolesi Jacopo
Published: October 2022

During the last century, synapses have been intensely investigated as the most interesting sites of neuroscience development [...]
The Effect of Citicoline on the Expression of Matrix Metalloproteinase-2 (MMP-2), Transforming Growth Factor-β1 (TGF-β1), and Ki-67, and on the Thickness of Scleral Tissue of Rat Myopia Model
Authors: Wahyuningsih Eka , Wigid Dimas , Dewi Astrid , Moehariadi Hariwati , Sujuti Hidayat , Anandita Nanda
Published: October 2022

Citicoline, presumed to be involved in the dopaminergic pathway, might play a role as a candidate agent in controlling myopia. However, its study with respect to myopia is limited. The aim of this study is to demonstrate the effect of citicoline on the expression of MMP-2, TGF-β1, and Ki-67, and on the thickness of scleral tissue of a rat myopia model. Immunohistochemistry was performed to evaluate the expression of MMP-2, TGF-β1, and Ki-67 as the markers for fibroblast proliferation. Hematoxylin and eosin staining were used to evaluate scleral thickness. An electronic digital caliper was used to evaluate the axial length. The treatment group administered with 200 mg/kg BW/day had the lowest mean MMP-2 expression, axial elongation, and fibroblast proliferation, but it had the highest mean scleral thickness. The treatment group administered with 300 mg/kg BW/day had the highest mean TGF-β1 expression. Citicoline is able to decrease MMP-2 expression and fibroblast proliferation and increase TGF-β1 expression and scleral tissue thickness significantly in the scleral tissue of rat models for myopia.
Evidence of Renin–Angiotensin System Receptors in Deep Fascia: A Role in Extracellular Matrix Remodeling and Fibrogenesis?
Authors: Pirri Carmelo , Caroccia Brasilina , Angelini Andrea , Petrelli Lucia , Piazza Maria , Biz Carlo , Ruggieri Pietro , De Caro Raffaele , Stecco Carla
Published: October 2022

Recent studies have shown that fascial fibroblasts are sensitive to different stimuli (biochemical or biophysical), promoting extracellular matrix remodeling, as well as synthetic activity. Moreover, the extensive literature on the renin–angiotensin system (RAS) reported its involvement in tissue remodeling. This study aimed to investigate the presence of RAS components in the deep fascia. Thoracolumbar fascia specimens were collected from 13 patients (age range: 25–75 years; seven males and five females) who had undergone elective spinal surgical procedures at the Orthopedic Clinic of the University of Padova. Gene expression analysis was performed to investigate the expression of Ang II type 1 receptor (AT1R), Ang II type 2 receptor (AT2R), MAS receptor (MasR), angiotensinogen, angiotensin-converting enzyme 2 (ACE2) and angiotensin-converting enzyme 1 (ACE1). AT1R and ACE2 were also measured with immunoblot. AT1R was the most expressed angiotensin receptor subtype (300.2 ± 317 copies/25 ng of mRNA), followed by MasR (37.1 ± 39.56 copies/25 ng of mRNA) and AT2R (147 ± 122 copies/25 ng of mRNA). The amounts of angiotensinogen, ACE1 and ACE2 were hardly detectable. These findings demonstrate that RAS system receptors are present in the deep fascia, with a greater expression of AT1R, suggesting their involvement in fascial remodeling and fibrogenesis.
Semiconductor Multimaterial Optical Fibers for Biomedical Applications
Authors: Shen Lingyu , Teng Chuanxin , Wang Zhuo , Bai Hongyi , Kumar Santosh , Min Rui
Published: October 2022

Integrated sensors and transmitters of a wide variety of human physiological indicators have recently emerged in the form of multimaterial optical fibers. The methods utilized in the manufacture of optical fibers facilitate the use of a wide range of functional elements in microscale optical fibers with an extensive variety of structures. This article presents an overview and review of semiconductor multimaterial optical fibers, their fabrication and postprocessing techniques, different geometries, and integration in devices that can be further utilized in biomedical applications. Semiconductor optical fiber sensors and fiber lasers for body temperature regulation, in vivo detection, volatile organic compound detection, and medical surgery will be discussed.
Detection of SARS-CoV-2 Neutralizing Antibodies in Vaccinated Pregnant Women and Neonates by Using a Lateral Flow Immunoassay Coupled with a Spectrum-Based Reader
Authors: Chen Wei-Chun , Lin Yen-Pin , Cheng Chao-Min , Shen Ching-Fen , Li Chang-Wei , Wang Yu-Kuo , Shih Ting-Ying , Hong Chitsung , Chang Ting-Chang , Shen Ching-Ju
Published: October 2022

The focus of this study was to investigate the detection of neutralizing antibodies (Nabs) in maternal serum and cord blood as the targeted samples by employing a lateral flow immunoassay combined with a spectrum reader (LFI-SR) and the correlation of Nab protection against different types of SARS-CoV-2. We enrolled 20 pregnant women who were vaccinated with the Moderna (mRNA-1273) vaccine during pregnancy and collected 40 samples during delivery. We used an LFI-SR for the level of spike protein receptor binding domain antibody (SRBD IgG) as Nabs and examined the correlation of the SRBD IgG concentration and Nab inhibition rates (NabIR) via enzyme-linked immunosorbent assays (ELISA). The LFI-SR had high confidence for the SRBD IgG level (p < 0.0001). Better NabIR were found in wild-type SARS-CoV-2 (WT) compared to Delta-type (DT) and Omicron-type (OT). Women with two-dose vaccinations demonstrated greater NabIR than those with a single dose. The cut-off value of the SRBD IgG level by the LFI-SR for NabIR to DT (≥30%; ≥70%) was 60.15 and 150.21 ng/mL for mothers (both p = 0.005), and 156.31 (p = 0.011) and 230.20 ng/mL (p = 0.006) for babies, respectively. An additional vaccine booster may be considered for those mothers with SRBD IgG levels < 60.15 ng/mL, and close protection should be given for those neonates with SRBD IgG levels < 150.21 ng/mL, since there is no available vaccine for them.