bluuebunny/crossref_metadata_2025 huggingface dataset:
Salidroside Inhibits CCl4-Induced Liver Fibrosis in Mice by Reducing Activation and Migration of HSC Induced by Liver Sinusoidal Endothelial Cell-Derived Exosomal SphK1
Authors: Ye Qiannan , Zhou Yang , Zhao Changqing , Xu Lieming , Ping Jian
Published: May 2021

Sphingosine kinase 1 (SphK1)/Sphingosine-1-phosphate (S1P)/S1PRs signaling pathway is known to involve the advancement of liver fibrosis. Exosomal SphK1 promotes hepatic stellate cells (HSC) migration. Salidroside (Sal) inhibits liver fibrosis, but its mechanism is yet to be elucidated. This study was to explore the influences of Sal on the SphK/S1P/S1PRs signaling pathway in liver fibrosis induced by carbon tetrachloride (CCl4) in vivo, and investigated the mechanism of Sal affecting the migration and activation of HSC triggered by exosomal SphK1 in vitro. Our data showed that Sal reduced the activities of alanine transaminase (ALT), aspartate aminotransferase (AST) in serum, and hydroxyproline (Hyp) content in the liver tissue. Sal subdued the expression of α-smooth muscle actin (α-SMA), fibronectin (FN) and type I collagen (Col I) of the liver. Sal also reduced mitochondria-induced hepatocyte apoptosis and to inhibit JNK activation. Furthermore, Sal remarkably eradicated the influence of SphK1, SphK2, S1P, and S1PRs triggered by CCl4, whether stimulating or hindering. Compared with serum-derived exosomes from model group mice, serum-derived exosomes from Sal group mice expressed lower SphK1 and reduced JS 1 (mouse HSC cell line) migration. In addition, Sal was also observed to subdue Col I expression, AKT activation, and LX-2 migration induced by exosomal SphK1 from SK-HEP-1 (a kind of liver sinusoidal endothelial cells (LSEC) cell line). In conclusion, Sal could effectively alleviate liver injury, hepatocyte apoptosis, and liver fibrosis in vivo, providing supports that the protective effects of Sal might be realized by suppressing JNK activation and modulating the SphK/S1P/S1PRs axis. In vitro, it was observed that Sal might alleviate LX-2 migration and activation induced by exosomal SphK1 by inhibiting the AKT activation.
Diode-Pumped Fluorescence in Visible Range From Femtosecond Laser Inscribed Pr:LuAG Waveguides
Authors: Sun Lifei , Wang Chao , Cui Zemeng , Li Ruonan , Cai Yangjian , Ren Yingying , Mackenzie Mark D. , Kar Ajoy K.
Published: May 2021

Trivalent praseodymium (Pr3+) is the most established rare-earth ion for the direct generation of visible light. In our work, based on Pr-doped Lu3Al5O12 (LuAG) single crystal, cladding waveguides are fabricated by applying femtosecond laser inscription with different parameters. The main characteristics of the waveguides such as mode distributions, propagation losses are investigated. The investigations on confocal micro-photoluminescence enable us to illustrate femtosecond laser induced modifications in Pr:LuAG matrix. The waveguides are further pumped at a wavelength of 450 nm with an InGaN laser diode. Guided fluorescence emissions in visible range covering green, yellow-green, orange and red are obtained with a maximum slope efficiency of 4 × 10−4.
Computational Modeling for Antiarrhythmic Drugs for Atrial Fibrillation According to Genotype
Authors: Hwang Inseok , Jin Ze , Park Je-Wook , Kwon Oh-Seok , Lim Byounghyun , Hong Myunghee , Kim Min , Yu Hee-Tae , Kim Tae-Hoon , Uhm Jae-Sun , Joung Boyoung , Lee Moon-Hyoung , Pak Hui-Nam
Published: May 2021

Background: The efficacy of antiarrhythmic drugs (AAD) can vary in patients with atrial fibrillation (AF), and the PITX2 gene affects the responsiveness of AADs. We explored the virtual AAD (V-AAD) responses between wild-type and PITX2+/−-deficient AF conditions by realistic in silico AF modeling.

Methods: We tested the V-AADs in AF modeling integrated with patients' 3D-computed tomography and 3D-electroanatomical mapping, acquired in 25 patients (68% male, 59.8 ± 9.8 years old, 32.0% paroxysmal type). The ion currents for the PITX2+/− deficiency and each AAD (amiodarone, sotalol, dronedarone, flecainide, and propafenone) were defined based on previous publications.

Results: We compared the wild-type and PITX2+/− deficiency in terms of the action potential duration (APD90), conduction velocity (CV), maximal slope of restitution (Smax), and wave-dynamic parameters, such as the dominant frequency (DF), phase singularities (PS), and AF termination rates according to the V-AADs. The PITX2+/−-deficient model exhibited a shorter APD90 (p < 0.001), a lower Smax (p < 0.001), mean DF (p = 0.012), PS number (p < 0.001), and a longer AF cycle length (AFCL, p = 0.011). Five V-AADs changed the electrophysiology in a dose-dependent manner. AAD-induced AFCL lengthening (p < 0.001) and reductions in the CV (p = 0.033), peak DF (p < 0.001), and PS number (p < 0.001) were more significant in PITX2+/−-deficient than wild-type AF. PITX2+/−-deficient AF was easier to terminate with class IC AADs than the wild-type AF (p = 0.018).

Conclusions: The computational modeling-guided AAD test was feasible for evaluating the efficacy of multiple AADs in patients with AF. AF wave-dynamic and electrophysiological characteristics are different among the PITX2-deficient and the wild-type genotype models.
An Interpretable Hand-Crafted Feature-Based Model for Atrial Fibrillation Detection
Authors: Rouhi Rahimeh , Clausel Marianne , Oster Julien , Lauer Fabien
Published: May 2021

Atrial Fibrillation (AF) is the most common type of cardiac arrhythmia. Early diagnosis of AF helps to improve therapy and prognosis. Machine Learning (ML) has been successfully applied to improve the effectiveness of Computer-Aided Diagnosis (CADx) systems for AF detection. Presenting an explanation for the decision made by an ML model is considerable from the cardiologists' point of view, which decreases the complexity of the ML model and can provide tangible information in their diagnosis. In this paper, a range of explanation techniques is applied to hand-crafted features based ML models for heart rhythm classification. We validate the impact of the techniques by applying feature selection and classification to the 2017 CinC/PhysioNet challenge dataset. The results show the effectiveness and efficiency of SHapley Additive exPlanations (SHAP) technique along with Random Forest (RF) for the classification of the Electrocardiogram (ECG) signals for AF detection with a mean F-score of 0.746 compared to 0.706 for a technique based on the same features based on a cascaded SVM approach. The study also highlights how this interpretable hand-crafted feature-based model can provide cardiologists with a more compact set of features and tangible information in their diagnosis.
Transforming Growth Factor-β and Long Non-coding RNA in Renal Inflammation and Fibrosis
Authors: Gu Yue-Yu , Dou Jing-Yun , Huang Xiao-Ru , Liu Xu-Sheng , Lan Hui-Yao
Published: May 2021

Renal fibrosis is one of the most characterized pathological features in chronic kidney disease (CKD). Progressive fibrosis eventually leads to renal failure, leaving dialysis or allograft transplantation the only clinical option for CKD patients. Transforming growth factor-β (TGF-β) is the key mediator in renal fibrosis and is an essential regulator for renal inflammation. Therefore, the general blockade of the pro-fibrotic TGF-β may reduce fibrosis but may risk promoting renal inflammation and other side effects due to the diverse role of TGF-β in kidney diseases. Long non-coding RNAs (lncRNAs) are RNA transcripts with more than 200 nucleotides and have been regarded as promising therapeutic targets for many diseases. This review focuses on the importance of TGF-β and lncRNAs in renal inflammation, fibrogenesis, and the potential applications of TGF-β and lncRNAs as the therapeutic targets and biomarkers in renal fibrosis and CKD are highlighted.
Genetic Effects and Expression Patterns of the Nitrate Transporter (NRT) Gene Family in Populus tomentosa
Authors: Zhao Lei , Chen Panfei , Liu Peng , Song Yuepeng , Zhang Deqiang
Published: May 2021

Nitrate is an important source of nitrogen for poplar trees. The nitrate transporter (NRT) gene family is generally responsible for nitrate absorption and distribution. However, few analyses of the genetic effects and expression patterns of NRT family members have been conducted in woody plants. Here, using poplar as a model, we identified and characterized 98 members of the PtoNRT gene family. We calculated the phylogenetic and evolutionary relationships of the PtoNRT family and identified poplar-specific NRT genes and their expression patterns. To construct a core triple genetic network (association - gene expression - phenotype) for leaf nitrogen content, a candidate gene family association study, weighted gene co-expression network analysis (WGCNA), and mapping of expression quantitative trait nucleotides (eQTNs) were combined, using data from 435 unrelated Populus. tomentosa individuals. PtoNRT genes exhibited distinct expression patterns between twelve tissues, circadian rhythm points, and stress responses. The association study showed that genotype combinations of allelic variations of three PtoNRT genes had a strong effect on leaf nitrogen content. WGCNA produced two co-expression modules containing PtoNRT genes. We also found that four PtoNRT genes defined thousands of eQTL signals. WGCNA and eQTL provided comprehensive analysis of poplar nitrogen-related regulatory factors, including MYB17 and WRKY21. NRT genes were found to be regulated by five plant hormones, among which abscisic acid was the main regulator. Our study provides new insights into the NRT gene family in poplar and enables the exploitation of novel genetic factors to improve the nitrate use efficiency of trees.
Psychological Distress, Early Behavioral Response, and Perception Toward the COVID-19 Pandemic Among Health Care Workers in North Shoa Zone, Oromiya Region
Authors: Jemal Kemal , Deriba Berhanu Senbeta , Geleta Tinsae Abeya
Published: May 2021

Background: The coronavirus disease 2019 (COVID-19) pandemic has had a significant psychological impact on health care workers (HCWs). Therefore, this study inspects the mental health status, behavioral response, and perception among HCWs (nurses, physicians, and medical laboratory workers) during the COVID-19 pandemic in public health care facilities.

Methods: A facilities-based cross-sectional study was conducted in July 2020. A simple random sampling technique was used to select study participants. Data were collected by self-report administered questionnaires using Patient Health Questionnaire-9 (PHQ-9) for depression, General Anxiety Disorder-7 (GAD-7) for anxiety, Insomnia Severity Index (ISI) for insomnia, Impact of Event Scale-Revised (IES-R) for psychological distress, Perceived Threat Scale for perception, and Behavioral Response Inquiry for the behavioral response. Moreover, bivariable and multivariable logistic regressions analysis was used to identify the association between dependent and independent variables at p-value <0.05.

Results: A total of 417 (98.6%) HCWs responded to a self-administered questionnaire. The proportion of HCWs who had moderate to severe symptoms of psychological distress, depression, anxiety, and insomnia during the COVID-19 pandemic were 58, 16.3, 30.7, and 15.9%, respectively. Three-fifth of the nurses, medical laboratory professionals (62.2%), and physicians (59.2%) had reported good behavioral responses toward the COVID-19 pandemic. More than three-fifths of the nurses had reported poor perception toward the COVID-19 pandemic. Conversely, 61.2% of physicians and three-fourths (75.5%) of medical laboratory professionals had reported good perception toward the COVID-19 pandemic. Female and married participants, those working in the emergency unit, those with poor behavioral responses, and those with poor perception toward the COVID-19 pandemic were significantly associated with symptoms of psychological distress, depression, anxiety, and insomnia.

Conclusions: Psychological impacts among physicians, nurses, and medical laboratory professionals are high during the COVID-19 pandemic. The Ethiopian Federal Ministry of Health should aim to protect all HCWs' psychological well-being during the COVID-19 pandemic with appropriate interventions and accurate information response.
Emotional Comparison Between Semantic Dementia and Alzheimer's Disease
Authors: Wang Ping , Zhao Qianhua , Zhou Yan , Hong Zhen , Guo Qihao , Liu Jianren
Published: May 2021

Background: Previous studies have suggested that Alzheimer's disease (AD) and semantic dementia (SD) are both associated with emotional processing impairment. However, the degree and type of emotional symptoms between the two types of dementia have not been previously compared.

Method: We used the Apathy Evaluation Scale (AES), the Toronto Empathy Questionnaire (TEQ), the Geriatric Depression Scale (GDS) and the Self-rating Anxiety Scale (SAS) to examine apathy, empathy, depression and anxiety, respectively.

Results: Between mild AD and mild SD, moderate-to-severe AD and moderate-to-severe SD, the total scores of TEQ are significantly different, but the total scores of GDS, SAS and AES have no significant differences. In addition, normal individuals, AD and SD patients got the similar scores in SAS and GDS.

Conclusions: Empathy emotion in SD patients is more severe than that in AD patients. However, apathy, depression and anxiety emotion is similar between the two groups.
Smokeless Tobacco Point of Sale Advertising, Placement and Promotion: Associations With Store and Neighborhood Characteristics
Authors: James Shirley A. , Heller John G. , Hartman Chantel J. , Schaff Andrew C. , Mushtaq Nasir , Beebe Laura A.
Published: May 2021

Introduction: Objectives of this study were to determine retail and neighborhood characteristics associated with smokeless tobacco (ST) product promotion, price promotion, and storefront advertising among retailers in Oklahoma.

Methods: In this statewide point-of-sale study, we collected data from 1,354 ST retailers. Using store characteristics and census tract information, we estimated summary statistics and adjusted prevalence ratios during 2019–2020.

Results: Of ST retailers audited, 11.0% demonstrated ST youth promotion, 43.0% ST price promotions, and 19.6% ST storefront advertising. The adjusted prevalence ratio (aPR) for convenience stores was higher for all three ST strategies: youth promotion (aPR = 3.4, 95% CI 1.9, 6.2), price promotion (aPR = 3.8, 95% CI 2.9, 5.0), and storefront advertising (aPR=16.4, 95% CI 6.7, 40.3) compared to other store types. Metropolitan tobacco retailers had higher aPRs for youth promotion (aPR = 1.7, 95% CI 1.12 2.6) and storefront advertising (aPR = 1.5, 95% CI 1.2, 1.9).

Conclusions: Findings of this study suggest there are currently ample opportunities for youth and adults at risk for tobacco initiation to be exposed to ST products in the retail environment. Convenience stores, more likely to be found and utilized in rural areas compared to metropolitan areas, are disproportionately more likely to engage in marketing strategies that could lure youth into trying smokeless tobacco.
Unknown Disease Outbreaks Detection: A Pilot Study on Feature-Based Knowledge Representation and Reasoning Model
Authors: Feng Rui , Hu Qiping , Jiang Yingan
Published: May 2021

Background:The outbreak of COVID-19 in 2019 has rapidly swept the world, causing irreparable loss to human beings. The pandemic has shown that there is still a delay in the early response to disease outbreaks and needs a method for unknown disease outbreak detection. The study's objective is to establish a new medical knowledge representation and reasoning model, and use the model to explore the feasibility of unknown disease outbreak detection.

Methods:The study defined abnormal values with diagnostic significances from clinical data as the Features, and defined the Features as the antecedents of inference rules to match with knowledge bases, achieved in detecting known or emerging infectious disease outbreaks. Meanwhile, the study built a syndromic surveillance base to capture the target cases' Features to improve the reliability and fault-tolerant ability of the system.

Results:The study combined the method with Severe Acute Respiratory Syndrome (SARS), Middle East Respiratory Syndrome (MERS), and early COVID-19 outbreaks as empirical studies. The results showed that with suitable surveillance guidelines, the method proposed in this study was capable to detect outbreaks of SARS, MERS, and early COVID-19 pandemics. The quick matching accuracies of confirmed infection cases were 89.1, 26.3–98%, and 82%, and the syndromic surveillance base would capture the Features of the remaining cases to ensure the overall detection accuracies. Based on the early COVID-19 data in Wuhan, this study estimated that the median time of the early COVID-19 cases from illness onset to local authorities' responses could be reduced to 7.0–10.0 days.

Conclusions:This study offers a new solution to transfer traditional medical knowledge into structured data and form diagnosis rules, enables the representation of doctors' logistic thinking and the knowledge transmission among different users. The results of empirical studies demonstrate that by constantly inputting medical knowledge into the system, the proposed method will be capable to detect unknown diseases from existing ones and perform an early response to the initial outbreaks.
Unitarity and Information in Quantum Gravity: A Simple Example
Authors: Amadei Lautaro , Liu Hongguang , Perez Alejandro
Published: May 2021

In approaches to quantum gravity, where smooth spacetime is an emergent approximation of a discrete Planckian fundamental structure, any effective smooth field theoretical description would miss part of the fundamental degrees of freedom and thus break unitarity. This is applicable also to trivial gravitational field (low energy) idealizations realized by the use of Minkowski background geometry which, as with any other spacetime geometry, corresponds, in the fundamental description, to infinitely many different and closely degenerate discrete microstates. The existence of such microstates provides a large reservoir q-bit for information to be coded at the end of black hole evaporation and thus opens the way to a natural resolution of the black hole evaporation information puzzle. In this paper we show that these expectations can be made precise in a simple quantum gravity model for cosmology motivated by loop quantum gravity. Concretely, even when the model is fundamentally unitary, when microscopic degrees of freedom irrelevant to low-energy cosmological observers are suitably ignored, pure states in the effective description evolve into mixed states due to decoherence with the Planckian microscopic structure. Moreover, in the relevant physical regime these hidden degrees of freedom do not carry any “energy” and thus realize, in a fully quantum gravitational context, the idea (emphasized before by Unruh and Wald) that decoherence can take place without dissipation, now in a concrete gravitational model strongly motivated by quantum gravity. All this strengthens the perspective of a quite conservative and natural resolution of the black hole evaporation puzzle where information is not destroyed but simply degraded (made unavailable to low-energy observers) into correlations with the microscopic structure of the quantum geometry at the Planck scale.
Theoretical Predictions of Surface Light Element Abundances in Protostellar and Pre-Main Sequence Phase
Authors: Tognelli E. , Degl’Innocenti S. , Prada Moroni P. G. , Lamia L. , Pizzone R. G. , Tumino A. , Spitaleri C. , Chiavassa A.
Published: May 2021

Theoretical prediction of surface stellar abundances of light elements–lithium, beryllium, and boron–represents one of the most interesting open problems in astrophysics. As well known, several measurements of 7Li abundances in stellar atmospheres point out a disagreement between predictions and observations in different stellar evolutionary phases, rising doubts about the capability of present stellar models to precisely reproduce stellar envelope characteristics. The problem takes different aspects in the various evolutionary phases; the present analysis is restricted to protostellar and pre-Main Sequence phases. Light elements are burned at relatively low temperatures (T from ≈2 to ≈5 million degrees) and thus in the early evolutionary stages of a star they are gradually destroyed at different depths of stellar interior mainly by (p, α) burning reactions, in dependence on the stellar mass. Their surface abundances are strongly influenced by the nuclear cross sections, as well as by the extension toward the stellar interior of the convective envelope and by the temperature at its bottom, which depend on the characteristics of the star (mass and chemical composition) as well as on the energy transport in the convective stellar envelope. In recent years, a great effort has been made to improve the precision of light element burning cross sections. However, theoretical predictions surface light element abundance are challenging because they are also influenced by the uncertainties in the input physics adopted in the calculations as well as the efficiency of several standard and non-standard physical processes active in young stars (i.e. diffusion, radiative levitation, magnetic fields, rotation). Moreover, it is still not completely clear how much the previous protostellar evolution affects the pre-Main Sequence characteristics and thus the light element depletion. This paper presents the state-of-the-art of theoretical predictions for protostars and pre-Main Sequence stars and their light element surface abundances, discussing the role of (p, α) nuclear reaction rates and other input physics on the stellar evolution and on the temporal evolution of the predicted surface abundances.
A Pneumatic Generator Based on Gas-Liquid Reversible Transition for Soft Robots
Authors: Zhang Guolong , Yang Guilin , Deng Yimin , Zheng Tianjiang , Fang Zaojun , Zhang Hao , Jiang Xiongyu
Published: May 2021

The soft robots actuated by pressure, cables, thermal, electrosorption, combustion and smart materials are usually faced with the problems of poor portability, noise, weak load capacity, small deformation and high driving voltages. In this paper, a novel pneumatic generator for soft robots based on the gas-liquid reversible transition is proposed, which has the advantages of large output force, easy deformation, strong load capacity and high flexibility. The pressure of the pneumatic generator surges or drops flexibly through the reversible transformation between liquid and gas phase, making the soft actuator stretch or contract regularly, without external motors, compressors and pressure-regulating components. The gas-liquid reversible-transition actuation process is modeled to analyze its working mechanism and characteristics. The pressure during the pressurization stage increases linearly with a rate regulated by the heating power and gas volume. It decreases exponentially with the exponential term as a quadratic function of time at the fast depressurization stage, while with the exponential term as a linear function of time at the slow depressurization stage. The drop rate can be adjusted by changing the gas volume and cooling conditions. Furthermore, effectiveness has been verified through experiments of the prototype. The pressure reaches 25 bar with a rising rate of +3.935 bar/s when 5 mL weak electrolyte solution is heated at 800 W, and the maximum depressurization rate in air cooling is –3.796 bar/s. The soft finger actuated by the pneumatic generator can bend with an angular displacement of 67.5°. The proposed pneumatic generator shows great potential to be used for the structure, driving and sensing integration of artificial muscles.
Animal Welfare Policies and Human Rights in the Context of Slaughter Procedures
Authors: Bozzo Giancarlo , Barrasso Roberta , Ferorelli Davide , Gassi Vito , Russo Roberto , Celentano Francesco Emanuele
Published: May 2021

Human rights, such as to non-discrimination and freedom of religion, are internationally recognized. In the meantime, the so-called global animal law is becoming more and more important. In this context, religious slaughter is increasingly becoming a matter for debate as a number of special procedures, which avoid stunning methods, may lead to greater suffering for animals. Such procedures are common to Judaism and Islam and involve 25% of the global population, almost 2 billion people. Considering that about 94% of European public opinion in 2015 expressed concern over animal welfare, it is time to evaluate the legal perspective of these special treatments. Indeed, although they seem to violate animal welfare policies, at the same time states have a duty to uphold religious freedom (and its forms of expression) under International and European law. The aim of this study is to evaluate, through a multidisciplinary approach, the complex balance between human rights in general and animal welfare policies, which are gaining importance especially in the European Continent’s legal framework.
Assessment of the Relationship between Postpartum Health and Mid-Lactation Performance, Behavior, and Feed Efficiency in Holstein Dairy Cows
Authors: Martin Malia J. , Weigel Kent A. , White Heather M.
Published: May 2021

The objective of this study was to investigate the relationships between postpartum health disorders and mid-lactation performance, feed efficiency, and sensor-derived behavioral traits. Multiparous cows (n = 179) were monitored for health disorders for 21 days postpartum and enrolled in a 45-day trial between 50 to 200 days in milk, wherein feed intake, milk yield and components, body weight, body condition score, and activity, lying, and feeding behaviors were recorded. Feed efficiency was measured as residual feed intake and the ratio of fat- or energy-corrected milk to dry matter intake. Cows were classified as either having hyperketonemia (HYK; n = 72) or not (n = 107) and grouped by frequency of postpartum health disorders: none (HLT; n = 94), one (DIS; n = 63), or ≥2 (DIS+; n = 22). Cows that were diagnosed with HYK had higher mid-lactation yields of fat- and energy-corrected milk. No differences in feed efficiency were detected between HYK or health status groups. Highly active mid-lactation time was higher in healthy animals, and rumination time was lower in ≥4th lactation cows compared with HYK or DIS and DIS+ cows. Differences in mid-lactation behaviors between HYK and health status groups may reflect the long-term impacts of health disorders. The lack of a relationship between postpartum health and mid-lactation feed efficiency indicates that health disorders do not have long-lasting impacts on feed efficiency.
Seconeolitsine, the Novel Inhibitor of DNA Topoisomerase I, Protects against Invasive Pneumococcal Disease Caused by Fluoroquinolone-Resistant Strains
Authors: Tirado-Vélez Jose Manuel , Carreño David , Sevillano David , Alou Luis , Yuste José , de la Campa Adela G.
Published: May 2021

Antibiotic resistance in Streptococcus pneumoniae has increased worldwide, making fluoroquinolones an alternative therapeutic option. Fluoroquinolones inhibit the type II DNA topoisomerases (topoisomerase IV and gyrase). In this study we have evaluated the in vivo activity of seconeolitsine, an inhibitor of topoisomerase I. Levofloxacin (12.5 to 50 mg/kg) or seconeolitsine (5 to 40 mg/kg) were administered every 12 h during two days in mice infected with a serotype 8-resistant strain. At 48 h, a 70% protection was obtained with seconeolitsine (40 mg/kg; p < 0.001). However, survival with levofloxacin was 20%, regardless of the dose. In addition, seconeolitsine decreased bacteremia efficiently. Levofloxacin had higher levels in serum than seconeolitsine (Cmax of 14.7 vs. 1.6; p < 0.01) and higher values of area under the serum concentration-time curve (AUC0-12h of 17.3 vs. 5; p < 0.01). However, seconeolitsine showed higher levels of time to peak concentration and elimination half-life. This is consistent with the higher binding of seconeolitsine to plasma proteins (40% and 80% when used at 1 µg/mL and 50 µg/mL, respectively) in comparison to levofloxacin (12% at 5 µg/mL and 33% at 50 µg/mL). Our results suggest that seconeolitsine would be a promising therapeutic alternative against pneumococcal isolates with high fluoroquinolone resistance levels.
Prediction of Arrival Time of Vessels Considering Future Weather Conditions
Authors: Ogura Takahiro , Inoue Teppei , Uchihira Naoshi
Published: May 2021

International logistics is becoming increasingly active. Marine transportation, in particular, accounts for approximately 90% of the total volume managed in international logistics and plays a vital role in the supply chains of many companies. However, en route factors, such as weather conditions, often delay scheduled arrivals at destination ports, and an accurate prediction of the arrival time is required for supply chain efficiency. The arrival time has been predicted in previous studies by calculating the route to the destination port and the en route voyage speed without considering the influence of future weather conditions. Hence, the prediction accuracy may decrease when weather conditions change. In this study, we propose a prediction method that identifies the route from the voyage results of vessels whose weather condition is similar to the future one and uses Bayesian learning to calculate the voyage speed in consideration of future weather conditions. Consequently, future changes in weather conditions are reflected in the prediction results. The prediction accuracy of the proposed method is projected to be 28% higher than that from previous studies based on historical operational data of vessels carrying home appliance and automobile industry cargoes.
Effects of Velocity and Permeability on Tracer Dispersion in Porous Media
Authors: Yang Yulong , Liu Tongjing , Li Yanyue , Li Yuqi , You Zhenjiang , Zuo Mengting , Diwu Pengxiang , Wang Rui , Zhang Xing , Liang Jinhui
Published: May 2021

During micro-scale tracer flow in porous media, the permeability and fluid velocity significantly affect the fluid dispersion properties of the media. However, the relationships between the dispersion coefficient, permeability, and fluid velocity in core samples are still not clearly understood. Two sets of experiments were designed to study the effects of tracer fluid flow velocity and porous medium permeability on the dispersion phenomenon in a core environment, using natural and sand-filled cores, respectively. From experimental data-fitting by a mathematical model, the relationship between the dispersion coefficient, flow velocity, and permeability was identified, allowing the analysis of the underlying mechanism behind this phenomenon. The results show that a higher volumetric flow rate and lower permeability cause a delay in the tracer breakthrough time and an increase in the dispersion coefficient. The core experimental results show that the dispersion coefficient is negatively correlated with the permeability and positively correlated with the superficial velocity. The corresponding regression equations indicate linear relations between the dispersion coefficient, core permeability, and fluid velocity, resulting from the micron scale of grain diameters in cores. The combination of high velocity and low permeability yields a large dispersion coefficient. The effects of latitudinal dispersion in porous media cannot be ignored in low-permeability cores or formations. These findings can help to improve the understanding of tracer flow in porous media, the design of injection parameters, and the interpretation of tracer concentration distribution in inter-well tracer tests.
Multi-Step Traffic Speed Prediction Based on Ensemble Learning on an Urban Road Network
Authors: Feng Bin , Xu Jianmin , Zhang Yonggang , Lin Yongjie
Published: May 2021

Short-term traffic speed prediction plays an important role in the field of Intelligent Transportation Systems (ITS). Usually, traffic speed forecasting can be divided into single-step-ahead and multi-step-ahead. Compared with the single-step method, multi-step prediction can provide more future traffic condition to road traffic participants for guidance decision-making. This paper proposes a multi-step traffic speed forecasting by using ensemble learning model with traffic speed detrending algorithm. Firstly, the correlation analysis is conducted to determine the representative features by considering the spatial and temporal characteristics of traffic speed. Then, the traffic speed time series is split into a trend set and a residual set via a detrending algorithm. Thirdly, a multi-step residual prediction with direct strategy is formulated by the ensemble learning model of stacking integrating support vector machine (SVM), CATBOOST, and K-nearest neighbor (KNN). Finally, the forecasting traffic speed can be reached by adding predicted residual part to the trend one. In tests that used field data from Zhongshan, China, the experimental results indicate that the proposed model outperforms the benchmark ones like SVM, CATBOOST, KNN, and BAGGING.
Prediction of Long-Term Health Risk from Radiocesium Deposited on Ground with Consideration of Land-Surface Properties
Authors: Yasuda Hiroshi
Published: May 2021

After the Fukushima Daiichi accident, there have been long controversial discussions on “how safe is safe?” between the authorities and the residents in the affected area. This controversy was partly attributable to the way the authorities made a judgement based on the annual effective dose rate; meanwhile, many of the local residents have serious concerns about future consequences for their health caused by chronic radiation exposure, particularly of small children. To settle this controversy, the author presents an approach based on long-term cancer risk projections of female infants, i.e., the most radiosensitive group, following land contamination by radiocesium deposition into ground with different surface conditions; the land was classified into three categories on the basis of decaying patterns of radiation dose rate: “Fast”, “Middle”, and “Slow”. From the results of analyses with an initial dose rate of 20 mGy per year, it was predicted that the integrated lifetime attributable risk (LAR) of cancer mortality of a female person ranged by a factor of 2 from 1.8% (for the Fast area) to 3.6% (for the Slow area) that were clearly higher than the nominal risk values derived from effective dose estimates with median values of environmental model parameters. These findings suggest that accurate site-specific information on the behavioral characteristics of radionuclides in the terrestrial environment are critically important for adequate decision making for protecting people when there is an event accompanied by large-scale radioactive contamination.
Analysis on the Exhaust Air Recirculation of the Ventilation System in Multi-Story Building
Authors: Park Seonghyun , Park Hyungyu , Seo Janghoo
Published: May 2021

In South Korea, the installation of a mechanical ventilation system is mandatory for the management of indoor air quality, and various studies concerning the ventilation rate and performance of the ventilation system have been conducted. However, only a few studies have been conducted regarding the recirculation rate of the ventilation system. If the appropriate arrangement of intake and exhaust vents in the ventilation system is not considered, the pollutants emitted from the circulation movement may be recirculated into the indoor environment and cause the degradation of the performance of the ventilation system. Therefore, this study aimed to quantitatively analyze the recirculation rate of pollutants emitted from a kindergarten building with an installed mechanical ventilation system in Seoul, South Korea, using computational fluid dynamics (CFD) analysis, and analyze the effectiveness of the guide panel installed for the prevention of the pollutants’ recirculation. The number of cases for the CFD analysis was set to a total of ten based on the ventilation rate in a mechanical ventilation system, external wind direction, and the existence of the guide panel for preventing the recirculation of exhaust air. The maximum recirculation rate of exhaust air without the installation of a guide panel was shown to be 20.0%. The maximum recirculation rate in the case where the external wind speed, direction of wind, and the ventilation rate were assumed to be identical to the other case but the guide panel for preventing the recirculation of exhaust air was assumed to be installed was 7.7%, 12.3% lower compared with the case with maximum recirculation rate.
A Fast Calculation Method of Far-Field Intensity Distribution with Point Spread Function Convolution for High Energy Laser Propagation
Authors: Ma Huimin , Zhang Pengfei , Zhang Jinghui , Liu Haiqiu , Fan Chengyu , Qiao Chunhong , Zhang Weiwei , Li Xiaohong
Published: May 2021

The turbulence effect, thermal blooming effect, laser beam aberration, platform jitter, and other effects in the process of high energy laser propagation in the atmosphere will cause serious degradation of laser beam quality, which will have a negative impact on the actual application of laser propagation engineering. It is important in the engineering application of high-energy laser propagation to evaluate the far-field intensity distribution quickly. Based on the optical transfer function (OTF) theory of imaging system, the propagation process of high-energy lasers is modeled as the imaging process of point source. By using the convolution of point spread function (PSF) of jitter, turbulence, thermal blooming, and aberration of emission system, fast calculation of the far-field intensity distribution of high energy laser is realized. The calculation results are compared with those obtained by the 4D wave optics simulation program in different propagation scenarios. The results show that the calculated facula distribution and encircled energy of this method are in good agreement with the simulation results of wave optics, which can realize the fast and accurate evaluation of the far-field intensity distribution of high-energy laser propagation and provide a reference for practical engineering application.
Impact of Black Carbon on Surface Ozone in the Yangtze River Delta from 2015 to 2018
Authors: Tan Yue , Zhao Delong , Wang Honglei , Zhu Bin , Bai Dongping , Liu Ankang , Shi Shuangshuang , Dai Qihang
Published: May 2021

Despite the yearly decline in PM2.5 in China, surface ozone has been rapidly increasing recently, which makes it imperative to coordinate and control both PM2.5 and ozone in the atmosphere. This study utilized the data of pollutant concentrations and meteorological elements during 2015 to 2018 in Nanjing, China to analyze the daily correlation between black carbon and ozone (CBO), and the distribution of the pollutant concentrations under different levels of CBO. Besides, the diurnal variations of pollutant concentrations and meteorological elements under high positive and negative CBO were discussed and compared. The results show that the percentage of positive CBO had been increasing at the average rate of 7.1%/year, and it was 38.7% in summer on average, nearly twice of that in other seasons (19.2%). The average black carbon (BC), PM2.5 and NO2 under positive CBO was lower than those under negative CBO. It is noticeable that the surface ozone began to ascend when CBO was up to 0.2, with PM2.5 and NO2 decreasing and BC remaining steady. Under negative CBO, pollutant concentrations and meteorological elements showed obvious diurnal variations: BC showed a double-peak pattern and surface ozone, PM2.5, SO2 and CO showed single-peak patterns and NO2 showed a trough from 10:00 to 19:00. Wind speed and visibility showed a single-peak pattern with little seasonal difference. Relative humidity rose first, then it lowered and then it rose. Under positive CBO, the patterns of diurnal variations became less obvious, and some of them even showed no patterns, but just fluctuated at a certain level.
Hydroxylapatite and Related Minerals in Bone and Dental Tissues: Structural, Spectroscopic and Mechanical Properties from a Computational Perspective
Authors: Ulian Gianfranco , Moro Daniele , Valdrè Giovanni
Published: May 2021

Hard tissues (e.g., bone, enamel, dentin) in vertebrates perform various and different functions, from sustaining the body to haematopoiesis. Such complex and hierarchal tissue is actually a material composite whose static and dynamic properties are controlled by the subtle physical and chemical interplay between its components, collagen (main organic part) and hydroxylapatite-like mineral. The knowledge needed to fully understand the properties of bony and dental tissues and to develop specific applicative biomaterials (e.g., fillers, prosthetics, scaffolds, implants, etc.) resides mostly at the atomic scale. Among the different methods to obtains such detailed information, atomistic computer simulations (in silico) have proven to be both corroborative and predictive tools in this subject. The authors have intensively worked on quantum mechanical simulations of bioapatite and the present work reports a detailed review addressed to the crystal-chemical, physical, spectroscopic, mechanical, and surface properties of the mineral phase of bone and dental tissues. The reviewed studies were conducted at different length and time scales, trying to understand the features of hydroxylapatite and biological apatite models alone and/or in interaction with simplified collagen-like models. The reported review shows the capability of the computational approach in dealing with complex biological physicochemical systems, providing accurate results that increase the overall knowledge of hard tissue science.
Mapping the Featural and Holistic Face Processing of Bad and Good Face Recognizers
Authors: Marzi Tessa , Gronchi Giorgio , Turano Maria Teresa , Giovannelli Fabio , Giganti Fiorenza , Rebai Mohamed , Viggiano Maria Pia
Published: May 2021

Individual abilities in face recognition (good versus bad recognizers) were explored by means of event-related potentials (ERPs). The adaptation response profile of the N170 component to whole faces, eyes and mouths was used in order to highlight the crucial role of individual abilities in identity repetition processes for unfamiliar faces. The main point of this study is to underline the importance of characterizing the performance (bad or good) of the participants and to show that behaviorally selected groups might reveal neural differences. Good recognizers showed selective right hemisphere N170 repetition effects for whole faces and not for features. On the contrary, bad recognizers showed a general repetition effect not specifically related to faces and more pronounced processing for features. These findings suggest a different contribution of holistic and featural analysis in bad and good performers. In conclusion, we propose that the N170 might be used as a tool to tease apart face encoding processes as a function of individual differences.
Genetic Variation and Immunohistochemical Localization of the Glucocorticoid Receptor in Breast Cancer Cases from the Breast Cancer Care in Chicago Cohort
Authors: Al-Alem Umaima , Mahmoud Abeer M. , Batai Ken , Shah-Williams Ebony , Gann Peter H. , Kittles Rick , Rauscher Garth H.
Published: May 2021

Background: Glucocorticoid, one of the primary mediators of stress, acts via its receptor, the glucocorticoid receptor (GCR/NR3C1), to regulate a myriad of physiological processes. We measured the genetic variation and protein expression of GCR, and the genes that regulate GCR function or response and examined whether these alterations were associated with breast cancer clinicopathological characteristics. Method: We used samples from a multiracial cohort of breast cancer patients to assess the association between breast cancer characteristics and the genetic variants of single nucleotide polymorphisms (SNPs) in GCR/NR3C1, FKBP5, Sgk1, IL-6, ADIPOQ, LEPR, SOD2, CAT, and BCL2. Results: Several SNPs were associated with breast cancer characteristics, but statistical significance was lost after adjustment for multiple comparisons. GCR was detected in all normal breast tissues and was predominantly located in the nuclei of the myoepithelial cell layer, whereas the luminal layer was negative for GCR. GCR expression was significantly decreased in all breast cancer tissue types, compared to nontumor tissue, but was not associated with breast cancer characteristics. We found that high nuclear GCR expression was associated with basal cell marker cytokeratin 5/6 positivity. Conclusion: GCR expression is reduced in breast cancer tissue and correlates with the basal cell marker CK5/6.
Molecular Biology of Pediatric and Adult Male Germ Cell Tumors
Authors: Pinto Mariana Tomazini , Cárcano Flavio Mavignier , Vieira Ana Glenda Santarosa , Cabral Eduardo Ramos Martins , Lopes Luiz Fernando
Published: May 2021

Cancer is a leading cause of death by disease in children and the second most prevalent of all causes in adults. Testicular germ cell tumors (TGCTs) make up 0.5% of pediatric malignancies, 14% of adolescent malignancies, and are the most common of malignancies in young adult men. Although the biology and clinical presentation of adult TGCTs share a significant overlap with those of the pediatric group, molecular evidence suggests that TGCTs in young children likely represent a distinct group compared to older adolescents and adults. The rarity of this cancer among pediatric ages is consistent with our current understanding, and few studies have analyzed and compared the molecular basis in childhood and adult cancers. Here, we review the major similarities and differences in cancer genetics, cytogenetics, epigenetics, and chemotherapy resistance between pediatric and adult TGCTs. Understanding the biological and molecular processes underlying TGCTs may help improve patient outcomes, and fuel further investigation and clinical research in childhood and adult TGCTs.
Targeting Wnt Signaling in Endometrial Cancer
Authors: Fatima Iram , Barman Susmita , Rai Rajani , Thiel Kristina W. , Chandra Vishal
Published: May 2021

This review presents new findings on Wnt signaling in endometrial carcinoma and implications for possible future treatments. The Wnt proteins are essential mediators in cell signaling during vertebrate embryo development. Recent biochemical and genetic studies have provided significant insight into Wnt signaling, in particular in cell cycle regulation, inflammation, and cancer. The role of Wnt signaling is well established in gastrointestinal and breast cancers, but its function in gynecologic cancers, especially in endometrial cancers, has not been well elucidated. Development of a subset of endometrial carcinomas has been attributed to activation of the APC/β-catenin signaling pathway (due to β-catenin mutations) and downregulation of Wnt antagonists by epigenetic silencing. The Wnt pathway also appears to be linked to estrogen and progesterone, and new findings implicate it in mTOR and Hedgehog signaling. Therapeutic interference of Wnt signaling remains a significant challenge. Herein, we discuss the Wnt-activating mechanisms in endometrial cancer and review the current advances and challenges in drug discovery.