bluuebunny/crossref_metadata_2025 huggingface dataset:
Shaking Table Tests of Lead Inserted Small-Sized Laminated Rubber Bearing for Nuclear Component Seismic Isolation
Authors: Koo Gyeong-Hoi , Shin Tae-Myung , Ma Sang-Jin
Published: May 2021

To assure seismic isolation performance against design and beyond design basis earthquakes in the nuclear facility components, the lead inserted small-sized laminated rubber bearings (LRB), which has a 10 kN vertical design load, have been designed and quasi-statically tested to validate their design mechanical properties in previous studies. Following this study, the seismic shaking tests of these full-scale LRBs are performed and discussed in this paper with the dummy mass system to investigate actual seismic isolation performance, dynamic characteristics of LRBs, consistency of the LRB’s quality, and so on. To study the seismic isolation performance, three beam structures (S1–S3) with different natural frequencies were installed both on the shaking table and the dummy mass supported by four LRBs: (1) S1: structure close to seismic isolation frequency; (2) S2: structure close to peak input spectral frequency; (3) S3: structure in the high-frequency region. The test results are described in various seismic levels of OBE (Operating Basis Earthquake), SSE (Safe Shutdown Earthquake), and BDBE (Beyond Design Basis Earthquake), and are compared with the analysis results to assure the seismic isolation performance and the LRB’s design parameters. From the results of the shaking table tests, it is confirmed that the lead inserted small-sized LRBs reveal an adequate seismic isolation performance and their dynamic characteristics as intended in the LRB design.
Combination of Permanent and Variable Load Is Dependent
Authors: Poutanen Tuomo , Pursiainen Sampsa , Länsivaara Tim
Published: May 2021

This study concerns the combination of the permanent and the variable loads in the structural design. The Eurocodes are used as a reference. Three new findings are presented: (1) In each physical structure, and in every load pair of the permanent load and the variable load, the maximum variable load is the service time load, the 50-year load, i.e., the high value of the variable load. Therefore, no load reduction should be applied in the combination. (2) The governing hypothesis is the independent load combination (ILC) with random load pairs and random single loads. However, the load pairs are not independent as normally one variable load occurs simultaneously in multiple structures and in multiple load pairs inducing correlation between the loads, ultimately full correlation, and the dependent load combination (DLC). (3) In the current Eurocodes, the design load combination applies to one load pair only. However, one design load combination virtually always applies to multiple load pairs which demands using the DLC. The authors have explained earlier that the permanent and variable loads should be combined dependently as the ILC contradicts the physics. The new findings support this conclusion. Changing the current codes towards the DLC approach would simplify them and eases their use in the structural design work.
Crack Propagation in the Tibia Bone within Total Knee Replacement Using the eXtended Finite Element Method
Authors: NGUYEN Ho-Quang , NGUYEN Trieu-Nhat-Thanh , PHAM Thinh-Quy-Duc , NGUYEN Van-Dung , TRAN Xuan Van , DAO Tien-Tuan
Published: May 2021

Understanding of fracture mechanics of the human knee structures within total knee replacement (TKR) allows a better decision support for bone fracture prevention. Numerous studies addressed these complex injuries involving the femur bones but the full macro-crack propagation from crack initiation to final failure and age-related effects on the tibia bone were not extensively studied. The present study aimed to develop a patient-specific model of the human tibia bone and the associated TKR implant, to study fatigue and fracture behaviors under physiological and pathological (i.e., age-related effect) conditions. Computed tomography (CT) data were used to develop a patient-specific computational model of the human tibia bone (cortical and cancellous) and associated implants. First, segmentation and 3D-reconstruction of the geometrical models of the tibia and implant were performed. Then, meshes were generated. The locations of crack initiation were identified using the clinical observation and the fatigue crack initiation model. Then, the propagation of the crack in the bone until final failure was investigated using the eXtended finite element method (X-FEM). Finally, the obtained outcomes were analyzed and evaluated to investigate the age-effects on the crack propagation behaviors of the bone. For fatigue crack initiation analysis, the stress amplitude–life S–N curve witnessed a decrease with increasing age. The maximal stress concentration caused by cyclic loading resulted in the weakening of the tibia bone under TKR. For fatigue crack propagation analysis, regarding simulation with the implant, the stress intensity factor and the energy release rate tended to decrease, as compared to the tibia model without the implant, from 0.15  ÷ 2.5 to 0.11 ÷ 1.9 (MPam) and from 10 ÷ 240 to 5 ÷ 133 (Jm−2), respectively. This led to the drop in crack propagation speed. This study provided, for the first time, a detailed view on the full crack path from crack initiation to final failure of the tibia bone within the TKR implant. The obtained outcomes also suggested that age (i.e., bone strength) also plays an important role in tibia crack and bone fracture. In perspective, patient-specific bone properties and dynamic loadings (e.g., during walking or running) are incorporated to provide objective and quantitative indicators for crack and fracture prevention, during daily activities.
Deep Reinforcement Learning-Based Multi-Hop State-Aware Routing Strategy for Wireless Sensor Networks
Authors: Zhang Aiqi , Sun Meiyi , Wang Jiaqi , Li Zhiyi , Cheng Yanbo , Wang Cheng
Published: May 2021

With the development of wireless sensor network technology, the routing strategy has important significance in the Internet of Things. An efficient routing strategy is one of the fundamental technologies to ensure the correct and fast transmission of wireless sensor networks. In this paper, we study how to combine deep learning technology with routing technology to propose an efficient routing strategy to cope with network topology changes. First, we use the recurrent neural network combined with the deep deterministic policy gradient method to predict the network traffic distribution. Second, the multi-hop node state is considered as the input of a double deep Q network. Therefore, the nodes can make routing decisions according to the current state of the network. Multi-hop state-aware routing strategy based on traffic flow forecasting (MHSA-TFF) is proposed. Simulation results show that the MHSA-TFF can improve transmission delay, average routing length, and energy efficiency.
A Human-Inspired Control Strategy for Improving Seamless Robot-To-Human Handovers
Authors: Neranon Paramin , Sutiphotinun Tanapong
Published: May 2021

One of the challenging aspects of robotics research is to successfully establish a human-like behavioural control strategy for human–robot handover, since a robotic controller is further complicated by the dynamic nature of the human response. This paper consequently highlights the development of an appropriate set of behaviour-based control for robot-to-human object handover by first understanding an equivalent human–human handover. The optimized hybrid position and impedance control was implemented to ensure good stability, adaptability and comfort of the robot in the object handover tasks. Moreover, a questionnaire technique was employed to gather information from the participants concerning their evaluations of the developed control system. The results demonstrate that the quantitative measurement of performance of the human-inspired control strategy can be considered acceptable for seamless human–robot handovers. This also provided significant satisfaction with the overall control performance in the robotic control system, in which the robot can dexterously pass the object to the receiver in a timely and natural manner without the risk of harm or injury by the robot. Furthermore, the survey responses were in agreement with the parallel test outcomes, demonstrating significant satisfaction with the overall performance of the robot–human interaction, as measured by an average rating of 4.20 on a five-point scale.
Influence of Wind Power on Modeling of Bidding Strategy in a Promising Power Market with a Modified Gravitational Search Algorithm
Authors: Singh Satyendra , Fozdar Manoj , Malik Hasmat , Fernández Moreno Maria del Valle , García Márquez Fausto Pedro
Published: May 2021

It is expected that large-scale producers of wind energy will become dominant players in the future electricity market. However, wind power output is irregular in nature and it is subjected to numerous fluctuations. Due to the effect on the production of wind power, producing a detailed bidding strategy is becoming more complicated in the industry. Therefore, in view of these uncertainties, a competitive bidding approach in a pool-based day-ahead energy marketplace is formulated in this paper for traditional generation with wind power utilities. The profit of the generating utility is optimized by the modified gravitational search algorithm, and the Weibull distribution function is employed to represent the stochastic properties of wind speed profile. The method proposed is being investigated and simplified for the IEEE-30 and IEEE-57 frameworks. The results were compared with the results obtained with other optimization methods to validate the approach.
Estrogen Signaling in Bone
Authors: Lara-Castillo Nuria
Published: May 2021

Estrogen plays important roles in bone homeostasis throughout a person’s life, including longitudinal bone growth, bone healing, and adaptation to mechanical forces. Estrogen exerts its action by binding to its multiple receptors in the cell membrane and cytoplasm. Until now at least three estrogen receptors (ER) have been reported: ER alpha (ERα), ER beta (ERβ), and G-protein coupled estrogen receptor 1 (GPER1) also known as GP30. Recently it has been observed that estrogen crosstalk with other signaling pathways helping to understand its wide effects in bone homeostasis. Abrupt loss of estrogen production experienced by menopausal women is associated with the rapid loss of bone mass ultimately leading to osteoporosis. The detrimental results during its absence with aging and the increased life expectancy of current and future generations make it of high importance to fully understand its mechanism of action. This review article aims to update on (1) the molecular mechanism of action of estrogen in the skeletal system, (2) ERs expression in different bone cells, (3) recent reported ER mutations resulting in pathological human conditions, and (4) role of estrogen signaling during bone healing.
Cooperative Spectrum Sensing Based on Convolutional Neural Networks
Authors: Tan Youheng , Jing Xiaojun
Published: May 2021

Cooperative spectrum sensing (CSS) is an important topic due to its capacity to solve the issue of the hidden terminal. However, the sensing performance of CSS is still poor, especially in low signal-to-noise ratio (SNR) situations. In this paper, convolutional neural networks (CNN) are considered to extract the features of the observed signal and, as a consequence, improve the sensing performance. More specifically, a novel two-dimensional dataset of the received signal is established and three classical CNN (LeNet, AlexNet and VGG-16)-based CSS schemes are trained and analyzed on the proposed dataset. In addition, sensing performance comparisons are made between the proposed CNN-based CSS schemes and the AND, OR, majority voting-based CSS schemes. The simulation results state that the sensing accuracy of the proposed schemes is greatly improved and the network depth helps with this.
Asymptotic Analytical Solution on Lamb Waves in Functionally Graded Nano Copper Layered Wafer
Authors: Hu Yifeng , Cao Xiaoshan , Niu Yi , Ru Yan , Shi Junping
Published: May 2021

In this study, the feasibility of using Lamb waves in functionally graded (FG) nano copper layered wafers in nondestructive evaluation is evaluated. The elastic parameters and mass densities of these wafers vary with thickness due to the variation in grain size. The power series technique is used to solve the governing equations with variable coefficients. To analyze multilayered structures, of which the material parameters are continuous but underivable, a modified transfer matrix method is proposed and combined with the power series method. Results show that multiple modes of Lamb waves exist in FG nano copper wafers. Moreover, the gradient property leads to a decrease in phase velocity, and the absolute value of the phase velocity variation is positively correlated with the gradient coefficient. The phase velocity variation and variation rate in Mode 2 are smaller than those in other modes. The findings indicate that Mode 4 is recommended for nondestructive evaluation. However, if the number of layers is greater than four, the dispersion curves of the Lamb waves in the multilayer structures tend to coincide with those in the equivalent uniform structures. The results of this study provide theoretical guidance for the nondestructive evaluation of FG nanomaterial layered structures.
Financial Context News Sentiment Analysis for the Lithuanian Language
Authors: Štrimaitis Rokas , Stefanovič Pavel , Ramanauskaitė Simona , Slotkienė Asta
Published: May 2021

Financial area analysis is not limited to enterprise performance analysis. It is worth analyzing as wide an area as possible to obtain the full impression of a specific enterprise. News website content is a datum source that expresses the public’s opinion on enterprise operations, status, etc. Therefore, it is worth analyzing the news portal article text. Sentiment analysis in English texts and financial area texts exist, and are accurate, the complexity of Lithuanian language is mostly concentrated on sentiment analysis of comment texts, and does not provide high accuracy. Therefore in this paper, the supervised machine learning model was implemented to assign sentiment analysis on financial context news, gathered from Lithuanian language websites. The analysis was made using three commonly used classification algorithms in the field of sentiment analysis. The hyperparameters optimization using the grid search was performed to discover the best parameters of each classifier. All experimental investigations were made using the newly collected datasets from four Lithuanian news websites. The results of the applied machine learning algorithms show that the highest accuracy is obtained using a non-balanced dataset, via the multinomial Naive Bayes algorithm (71.1%). The other algorithm accuracies were slightly lower: a long short-term memory (71%), and a support vector machine (70.4%).
Algorithm for Designing Reconfigurable Equipment to Enable Industry 4.0 and Circular Economy-Driven Manufacturing Systems
Authors: Brad Emilia , Brad Stelian
Published: May 2021

In the paradigm of industry 4.0, manufacturing enterprises need a high level of agility to adapt fast and with low costs to small batches of diversified products. They also need to reduce the environmental impact and adopt the paradigm of the circular economy. In the configuration space defined by this duality, manufacturing systems must embed a high level of reconfigurability at the level of their equipment. Finding the most appropriate concept of each reconfigurable equipment that composes an eco-smart manufacturing system is challenging because every system is unique in the context of an enterprise’s business model and technological focus. To reduce the entropy and to minimize the loss function in the design process of reconfigurable equipment, an evolutionary algorithm is proposed in this paper. It combines the particle swarm optimization (PSO) method with the theory of inventive problem-solving (TRIZ) to systematically guide the creative potential of design engineers towards the definition of the optimal concept over equipment’s lifecycle: what and when you need, no more, no less. The algorithm reduces the number of iterations in designing the optimal solution. An example for configuration design of a reconfigurable machine tool with adjustable functionality is included to demonstrate the effectiveness of the proposed algorithm.
Effect of Semi-Continuous Anaerobic Digestion on the Substrate Solubilisation of Lignin-Rich Steam-Exploded Ludwigia grandiflora
Authors: Bhatia Pranshu , Fujiwara Masaaki , Salangsang Maria Cecilia D. , Qian Jun , Liu Xin , Ban Syuhei , Myojin Mitsuyuki , Toda Tatsuki
Published: May 2021

In this study, semi-continuous anaerobic digestion of lignin-rich steam-exploded Ludwigia grandiflora (Lignin = 25.22% ± 4.6% total solids) was performed to understand better the effect of steam explosion on the substrate solubilisation and inhibitors formation during the process. Steam explosion pretreatment was performed at 180 °C for 30 min at a severity factor of 3.8 to enhance the biogas yield of the lignocellulosic biomass. The semi-continuous anaerobic digestion was performed in a continuously stirred tank reactor for 98 days at an initial hydraulic retention time of 30 days and an organic loading rate of 0.9 g-VS L−1 day−1. The performed steam explosion pretreatment caused biomass solubilisation, resulting in enhanced biogas production during the process. During the anaerobic digestion process, the average biogas yield was 265 mL g-VS−1, and the pH throughout the operation was in the optimum range of 6.5–8.2. Due to fluctuations in the biogas yield, the hydraulic retention time and organic loading rate were changed on day 42 (50 days and 0.5 g-VS L−1 day−1) and on day 49 (40 days and 0.7 g-VS L−1 day−1), and 1 M of NaOH was added to the liquid fraction of the steam-exploded L. grandiflora during the latter part of the operation to maintain the stability in the reactor. Therefore, the steam explosion pretreatment helped in the degradation of L. grandiflora by breaking the lignocellulose structure. In addition, changes in the operating conditions of the anaerobic digestion led to an increase in the biogas production towards the end of the process, leading to the stability in the CSTR.
Which Reanalysis Dataset Should We Use for Renewable Energy Analysis in Ireland?
Authors: Doddy Clarke Eadaoin , Griffin Seánie , McDermott Frank , Monteiro Correia João , Sweeney Conor
Published: May 2021

Attention should always be given to which reanalysis dataset to use when preparing analysis for a project. The accuracies of three reanalysis datasets, two global (ERA5 and MERRA-2) and one high-resolution regional reanalysis (MÉRA), are assessed by comparison with observations at seven weather observing stations around Ireland. Skill scores are calculated for the weather variables at these stations that are most relevant to the renewable energy sector: 10 m wind for wind power; surface shortwave radiation (SW) and 2 m temperature for photovoltaic power generation. The choice of which reanalysis dataset to use is important when future planning depends on this data. The newer ERA5 generally outperforms the other two reanalyses. However, this is not always true, and the best performing reanalysis dataset often depends on the variable of interest and location. As errors are significant for these reanalysis datasets, consideration should also be given to datasets specifically tailored to renewable energy resource modelling.
On the Left Ventricular Remodeling of Patients with Stenotic Aortic Valve: A Statistical Shape Analysis
Authors: Cutugno Salvatore , Ingrassia Tommaso , Nigrelli Vincenzo , Pasta Salvatore
Published: May 2021

The left ventricle (LV) constantly changes its shape and function as a response to pathological conditions, and this process is known as remodeling. In the presence of aortic stenosis (AS), the degenerative process is not limited to the aortic valve but also involves the remodeling of LV. Statistical shape analysis (SSA) offers a powerful tool for the visualization and quantification of the geometrical and functional patterns of any anatomic changes. In this paper, a SSA method was developed to determine shape descriptors of the LV under different degrees of AS and thus to shed light on the mechanistic link between shape and function. A total of n=86 patients underwent computed tomography (CT) for the evaluation of valvulopathy were segmented to obtain the LV surface and then were automatically aligned to a reference template by rigid registrations and transformations. Shape modes of the anatomical LV variation induced by the degree of AS were assessed by principal component analysis (PCA). The first shape mode represented nearly 50% of the total variance of LV shape in our patient population and was mainly associated to a spherical LV geometry. At Pearson’s analysis, the first shape mode was positively correlated to both the end-diastolic volume (p<0.01, R=0.814) and end-systolic volume (p<0.01, and R=0.922), suggesting LV impairment in patients with severe AS. A predictive model built with PCA-related shape modes achieved better performance in stratifying the occurrence of adverse events with respect to a baseline model using clinical demographic data as risk predictors. This study demonstrated the potential of SSA approaches to detect the association of complex 3D shape features with functional LV parameters.
Variants in Maternal Effect Genes and Relaxed Imprinting Control in a Special Placental Mesenchymal Dysplasia Case with Mild Trophoblast Hyperplasia
Authors: Huang Tien-Chi , Chang Kung-Chao , Chang Jen-Yun , Tsai Yi-Shan , Yang Yao-Jong , Chang Wei-Chun , Mo Chu-Fan , Yu Pei-Hsiu , Chiang Chun-Ting , Lin Shau-Ping , Kuo Pao-Lin
Published: May 2021

Placental mesenchymal dysplasia (PMD) and partial hydatidiform mole (PHM) placentas share similar characteristics, such as placental overgrowth and grape-like placental tissues. Distinguishing PMD from PHM is critical because the former can result in normal birth, while the latter diagnosis will lead to artificial abortion. Aneuploidy and altered dosage of imprinted gene expression are implicated in the pathogenesis of PHM and also some of the PMD cases. Diandric triploidy is the main cause of PHM, whereas mosaic diploid androgenetic cells in the placental tissue have been associated with the formation of PMD. Here, we report a very special PMD case also presenting with trophoblast hyperplasia phenotype, which is a hallmark of PHM. This PMD placenta has a normal biparental diploid karyotype and is functionally sufficient to support normal fetal growth. We took advantage of this unique case to further dissected the potential common etiology between these two diseases. We show that the differentially methylated region (DMR) at NESP55, a secondary DMR residing in the GNAS locus, is significantly hypermethylated in the PMD placenta. Furthermore, we found heterozygous mutations in NLRP2 and homozygous variants in NLRP7 in the mother’s genome. NLRP2 and NLRP7 are known maternal effect genes, and their mutation in pregnant females affects fetal development. The variants/mutations in both genes have been associated with imprinting defects in mole formation and potentially contributed to the mild abnormal imprinting observed in this case. Finally, we identified heterozygous mutations in the X-linked ATRX gene, a known maternal–zygotic imprinting regulator in the patient. Overall, our study demonstrates that PMD and PHM may share overlapping etiologies with the defective/relaxed dosage control of imprinted genes, representing two extreme ends of a spectrum.
Weighted Gene Co-Expression Network Analysis Reveals Key Genes and Potential Drugs in Abdominal Aortic Aneurysm
Authors: Kan Ke-Jia , Guo Feng , Zhu Lei , Pallavi Prama , Sigl Martin , Keese Michael
Published: May 2021

Abdominal aortic aneurysm (AAA) is a prevalent aortic disease that causes high mortality due to asymptomatic gradual expansion and sudden rupture. The underlying molecular mechanisms and effective pharmaceutical therapy for preventing AAA progression have not been fully identified. In this study, we identified the key modules and hub genes involved in AAA growth from the GSE17901 dataset in the Gene Expression Omnibus (GEO) database through the weighted gene co-expression network analysis (WGCNA). Key genes were further selected and validated in the mouse dataset (GSE12591) and human datasets (GSE7084, GSE47472, and GSE57691). Finally, we predicted drug candidates targeting key genes using the Drug–Gene Interaction database. Overall, we identified key modules enriched in the mitotic cell cycle, GTPase activity, and several metabolic processes. Seven key genes (CCR5, ADCY5, ADCY3, ACACB, LPIN1, ACSL1, UCP3) related to AAA progression were identified. A total of 35 drugs/compounds targeting the key genes were predicted, which may have the potential to prevent AAA progression.
Molecular Imprinting on Nanozymes for Sensing Applications
Authors: Cardoso Ana R. , Frasco Manuela F. , Serrano Verónica , Fortunato Elvira , Sales Maria Goreti Ferreira
Published: May 2021

As part of the biomimetic enzyme field, nanomaterial-based artificial enzymes, or nanozymes, have been recognized as highly stable and low-cost alternatives to their natural counterparts. The discovery of enzyme-like activities in nanomaterials triggered a broad range of designs with various composition, size, and shape. An overview of the properties of nanozymes is given, including some examples of enzyme mimics for multiple biosensing approaches. The limitations of nanozymes regarding lack of selectivity and low catalytic efficiency may be surpassed by their easy surface modification, and it is possible to tune specific properties. From this perspective, molecularly imprinted polymers have been successfully combined with nanozymes as biomimetic receptors conferring selectivity and improving catalytic performance. Compelling works on constructing imprinted polymer layers on nanozymes to achieve enhanced catalytic efficiency and selective recognition, requisites for broad implementation in biosensing devices, are reviewed. Multimodal biomimetic enzyme-like biosensing platforms can offer additional advantages concerning responsiveness to different microenvironments and external stimuli. Ultimately, progress in biomimetic imprinted nanozymes may open new horizons in a wide range of biosensing applications.
Fast and Sensitive Determination of the Fungicide Carbendazim in Fruit Juices with an Immunosensor Based on White Light Reflectance Spectroscopy
Authors: Koukouvinos Georgios , Karachaliou Chrysoula-Evangelia , Raptis Ioannis , Petrou Panagiota , Livaniou Evangelia , Kakabakos Sotirios
Published: May 2021

Carbendazim is a systemic benzimidazole-type fungicide with broad-spectrum activity against fungi that undermine food products safety and quality. Despite its effectiveness, carbendazim constitutes a major environmental pollutant, being hazardous to both humans and animals. Therefore, fast and reliable determination of carbendazim levels in water, soil, and food samples is of high importance for both food industry and public health. Herein, an optical biosensor based on white light reflectance spectroscopy (WLRS) for fast and sensitive determination of carbendazim in fruit juices is presented. The transducer is a Si/SiO2 chip functionalized with a benzimidazole conjugate, and determination is based on a competitive immunoassay format. Thus, for the assay, a mixture of an in-house developed rabbit polyclonal anti-carbendazim antibody with the standards or samples is pumped over the chip, followed by biotinylated secondary antibody and streptavidin. The WLRS platform allows for real-time monitoring of biomolecular interactions carried out onto the Si/SiO2 chip by transforming the shift in the reflected interference spectrum caused by the immunoreaction to effective biomolecular adlayer thickness. The sensor is able to detect 20 ng/mL of carbendazim in fruit juices with high accuracy and precision (intra- and inter-assay CVs ≤ 6.9% and ≤9.4%, respectively) in less than 30 min, applying a simple sample treatment that alleviates any “matrix-effect” on the assay results and a 60 min preincubation step for improving assay sensitivity. Excellent analytical characteristics and short analysis time along with its small size render the proposed WLRS immunosensor ideal for future on-the-spot determination of carbendazim in food and environmental samples.
Executive Function Improves Following Acute Exercise in Adults with Down Syndrome
Authors: Ringenbach Shannon , Arnold Nathanial , Myer Brandon , Hayes Claire , Nam Kahyun , Chen Chih-Chia
Published: May 2021

The influence of exercise on brain function is an important topic, especially in persons with intellectual deficits. The aim of this study is to determine the effect of an acute bout of resistance training (RT) compared to assisted cycle therapy (ACT) and no training (NT) in adults with DS on cognitive function. Fourteen participants attended four sessions: a baseline assessment, an assisted cycling therapy (ACT) session, a resistance training (RT) session, and a session of no training (NT). In the RT session, the leg press, chest press, seated row, leg curl, shoulder press, and latissimus pulldown were performed. The ACT session consisted of 30 min of cycling and in NT session consisted of 20 min of board games. Inhibition was measured by the Erikson flanker task and cognitive planning was measured by the Tower of London test and both were administered prior to (pretest) and after each intervention (posttest). Our results showed that inhibition time improved more following RT and ACT than NT. There was also a significant difference between ACT and NT. For cognitive planning, improvements were seen following ACT and NT. In conclusion, an acute session of ACT demonstrated a significant trend towards improvements in executive functions in adults with DS which we interpreted using a model of neural changes and the cognitive stimulation hypothesis.
Italian Version of the Pittsburgh Rehabilitation Participation Scale: Psychometric Analysis of Validity and Reliability
Authors: Iosa Marco , Galeoto Giovanni , De Bartolo Daniela , Russo Valentina , Ruotolo Ilaria , Spitoni Grazia , Ciancarelli Irene , Tramontano Marco , Antonucci Gabriella , Paolucci Stefano , Morone Giovanni
Published: May 2021

Patient’s active participation in therapy is a key component of successful rehabilitation. In fact, low participation has been shown to be a prognostic factor of poor outcome; however, participation is rarely assessed in clinical settings. The Pittsburgh Rehabilitation Participation Scale (PRPS) is a validated, quick, and accurate measure of participation, relying on clinicians’ observation, and not requiring any self-report by patients. The aim of this study was to validate an Italian version of the PRPS. Following forward and back-translation of PRPS into Italian, the translated version was validated in a total of 640 therapy sessions, related to a cohort of 32 patients admitted to an Italian hospital. It was tested for concurrent validity, finding significant correlations with Barthel Index (R > 0.58, p < 0.001) and SF-36 Physical and Mental Health (R > 0.4, p < 0.02), for predictive validity, finding significant correlation with the effectiveness of rehabilitation (R = 0.358, p = 0.045), and for inter-rater and intra-rater reliability, computing an Intra-class correlation coefficient (ICC = 0.926 and 0.756, respectively). These psychometric properties results were similar to those of the original version of this scale. The proposed PRPS can be helpful for Italian clinicians in the assessment of patient’s participation during rehabilitation.
Similar Theory of Mind Deficits in Community Dwelling Older Adults with Vascular Risk Profile and Patients with Mild Cognitive Impairment: The Case of Paradoxical Sarcasm Comprehension
Authors: Tsentidou Glykeria , Moraitou Despina , Tsolaki Magda
Published: May 2021

Recent studies deal with disorders and deficits caused by vascular syndrome in efforts for prediction and prevention. Cardiovascular health declines with age due to vascular risk factors, and this leads to an increasing risk of cognitive decline. Mild cognitive impairment (MCI) is defined as the negative cognitive changes beyond what is expected in normal aging. The purpose of the study was to compare older adults with vascular risk factors (VRF), MCI patients, and healthy controls (HC) in social cognition and especially in theory of mind ability (ToM). The sample comprised a total of 109 adults, aged 50 to 85 years (M = 66.09, SD = 9.02). They were divided into three groups: (a) older adults with VRF, (b) MCI patients, and (c) healthy controls (HC). VRF and MCI did not differ significantly in age, educational level or gender as was the case with HC. Specifically, for assessing ToM, a social inference test was used, which was designed to measure sarcasm comprehension. Results showed that the performance of the VRF group and MCI patients is not differentiated, while HC performed higher compared to the other two groups. The findings may imply that the development of a vascular disorder affecting vessels of the brain is associated from its “first steps” to ToM decline, at least regarding specific aspects of it, such as paradoxical sarcasm understanding.
Design of Robot-Inclusive Vertical Green Landscape
Authors: Yeo Matthew S. K. , Samarakoon S. M. Bhagya P. , Ng Qi Boon , Muthugala M. A. Viraj J. , Elara Mohan Rajesh
Published: May 2021

Vertical gardens have emerged alongside the increase in urban density and land scarcity to reintegrate greenery in the built environment. Existing maintenance for vertical gardens is labour-intensive, time-consuming and is being increasingly complemented by robotic applications. While research has been focused on enhancing robot design to improve productivity, minimal effort has been done on ‘design for robots’ in creating suitable environments for optimal robot deployments. This paper proposed a multi-disciplinary approach that brings together architects, designers, and roboticians to adapt the design of the vertical garden infrastructure to counteract the limitations of the maintenance robot. A case study on an existing plant maintenance robot ‘Urodela’ was conducted to determine the limitations encountered by robotic aid during operation. A robot-inclusive modular design for vertical gardens is proposed based on robot-inclusive principles, namely manipulability and safety, along with architectural design considerations. Design explorations for different configurations of track layouts of the proposed robot-inclusive modular design for vertical gardens is further analysed to validate its applicability and scalability.
Challenges of Neoantigen Targeting in Lynch Syndrome and Constitutional Mismatch Repair Deficiency Syndrome
Authors: Abidi Asima , Gorris Mark A. J. , Brennan Evan , Jongmans Marjolijn C. J. , Weijers Dilys D. , Kuiper Roland P. , de Voer Richarda M. , Hoogerbrugge Nicoline , Schreibelt Gerty , de Vries I. Jolanda M.
Published: May 2021

Lynch syndrome (LS) and constitutional mismatch repair deficiency (CMMRD) are hereditary disorders characterised by a highly increased risk of cancer development. This is due to germline aberrations in the mismatch repair (MMR) genes, which results in a high mutational load in tumours of these patients, including insertions and deletions in genes bearing microsatellites. This generates microsatellite instability and cause reading frameshifts in coding regions that could lead to the generation of neoantigens and opens up avenues for neoantigen targeting immune therapies prophylactically and therapeutically. However, major obstacles need to be overcome, such as the heterogeneity in tumour formation within and between LS and CMMRD patients, which results in considerable variability in the genes targeted by mutations, hence challenging the choice of suitable neoantigens. The machine-learning methods such as NetMHC and MHCflurry that predict neoantigen- human leukocyte antigen (HLA) binding affinity provide little information on other aspects of neoantigen presentation. Immune escape mechanisms that allow MMR-deficient cells to evade surveillance combined with the resistance to immune checkpoint therapy make the neoantigen targeting regimen challenging. Studies to delineate shared neoantigen profiles across patient cohorts, precise HLA binding algorithms, additional therapies to counter immune evasion and evaluation of biomarkers that predict the response of these patients to immune checkpoint therapy are warranted.
Comprehensive Assessment of Incidence, Risk Factors, and Mechanisms of Impaired Medical and Psychosocial Health Outcomes among Adolescents and Young Adults with Cancer: Protocol of the Prospective Observational COMPRAYA Cohort Study
Authors: Husson Olga , Ligtenberg Marjolijn J. L. , van de Poll-Franse Lonneke V. , Prins Judith B. , van den Bent Martin J. , van Eenbergen Mies C. , Fles Renske , Manten-Horst Eveliene , Gietema Jourik A. , van der Graaf Winette T. A.
Published: May 2021

Adolescent and young adult (AYA) cancer patients suffer from delay in diagnosis, and lack of centralized cancer care, age-adjusted expertise, and follow-up care. This group presents with a unique spectrum of cancers, distinct tumor biology, cancer risk factors, developmental challenges, and treatment regimens that differ from children and older adults. It is imperative for advances in the field of AYA oncology to pool data sources across institutions and create large cohorts to address the many pressing questions that remain unanswered in this vulnerable population. We will create a nationwide infrastructure (COMPRAYA) for research into the incidence, predictive/prognostic markers, and underlying mechanisms of medical and psychosocial outcomes for AYA between 18–39 years diagnosed with cancer. A prospective, observational cohort of (n = 4000), will be established. Patients will be asked to (1) complete patient-reported outcome measures; (2) donate a blood, hair, and stool samples (to obtain biochemical, hormonal, and inflammation parameters, and germline DNA); (3) give consent for use of routinely archived tumor tissue and clinical data extraction from medical records and registries; (4) have a clinic visit to assess vital parameters. Systematic and comprehensive collection of patient and tumor characteristics of AYA will support the development of evidence-based AYA care programs and guidelines.
Beyond Abscopal Effect: A Meta-Analysis of Immune Checkpoint Inhibitors and Radiotherapy in Advanced Non-Small Cell Lung Cancer
Authors: Fiorica Francesco , Tebano Umberto , Gabbani Milena , Perrone Mariasole , Missiroli Sonia , Berretta Massimiliano , Giuliani Jacopo , Bonetti Andrea , Remo Andrea , Pigozzi Eva , Tontini Andrea , Napoli Giuseppe , Luca Nicoletta , Grigolato Daniela , Pinton Paolo , Giorgi Carlotta
Published: May 2021

Background: Immune checkpoint inhibitors (ICI) plus radiotherapy (RT) have been suggested as an emerging combination in non-small cell lung cancer (NSCLC) patients. However, little is known about the magnitude of its benefits and potential clinical predictors. Objective: To assess the effects of this combination on the increase in overall and progression-free survival. Data sources: The MEDLINE and CANCERLIT (1970–2020) electronic databases were searched, and the reference lists of included studies were manually searched. Study selection: Studies were included if they were comparative studies between combination ICI-RT and ICI or RT alone in advanced or metastatic NSCLC patients. Overall survival (OS) was analyzed according to the treatment strategy. Data extraction: Data on population, intervention, and outcomes were extracted from each study, in accordance with the intention-to-treat method, by two independent observers and combined using the DerSimonian method and Laird method. Results: Compared to ICI or RT alone, ICI-RT significantly increased the 1-year and 3-year OS RR by 0.75 (95% CI 0.64–0.88; p = 0.0003) and 0.85 (95% CI 0.78–0.93; p = 0.0006), respectively. Furthermore, there was a statistically significant benefit on 1- and 3-year progression-free survival (RR 0.73 (95% CI, 0.61–0.87; p = 0.0005) and RR 0.82 (95% CI 0.67–0.99; p = 0.04), respectively). Conclusions: In patients with advanced or metastatic NSCLC, combination ICI-RT increases 1- and 3-year OS and progression-free survival compared to ICI or RT alone.
Estrogen Receptor-α Suppresses Liver Carcinogenesis and Establishes Sex-Specific Gene Expression
Authors: O’Brien Mara H. , Pitot Henry C. , Chung Sang-Hyuk , Lambert Paul F. , Drinkwater Norman R. , Bilger Andrea
Published: May 2021

Estrogen protects females from hepatocellular carcinoma (HCC). To determine whether this protection is mediated by classic estrogen receptors, we tested HCC susceptibility in estrogen receptor-deficient mice. In contrast to a previous study, we found that diethylnitrosamine induces hepatocarcinogenesis to a significantly greater extent when females lack Esr1, which encodes Estrogen Receptor-α. Relative to wild-type littermates, Esr1 knockout females developed 9-fold more tumors. Deficiency of Esr2, which encodes Estrogen Receptor-β, did not affect liver carcinogenesis in females. Using microarrays and QPCR to examine estrogen receptor effects on hepatic gene expression patterns, we found that germline Esr1 deficiency resulted in the masculinization of gene expression in the female liver. Six of the most dysregulated genes have previously been implicated in HCC. In contrast, Esr1 deletion specifically in hepatocytes of Esr1 conditional null female mice (in which Cre was expressed from the albumin promoter) resulted in the maintenance of female-specific liver gene expression. Wild-type adult females lacking ovarian estrogen due to ovariectomy, which is known to make females susceptible to HCC, also maintained female-specific expression in the liver of females. These studies indicate that Esr1 mediates liver cancer risk, and its control of sex-specific liver gene expression involves cells other than hepatocytes.
Viroids as a Tool to Study RNA-Directed DNA Methylation in Plants
Authors: Wassenegger Michael , Dalakouras Athanasios
Published: May 2021

Viroids are plant pathogenic, circular, non-coding, single-stranded RNAs (ssRNAs). Members of the Pospiviroidae family replicate in the nucleus of plant cells through double-stranded RNA (dsRNA) intermediates, thus triggering the host’s RNA interference (RNAi) machinery. In plants, the two RNAi pillars are Post-Transcriptional Gene Silencing (PTGS) and RNA-directed DNA Methylation (RdDM), and the latter has the potential to trigger Transcriptional Gene Silencing (TGS). Over the last three decades, the employment of viroid-based systems has immensely contributed to our understanding of both of these RNAi facets. In this review, we highlight the role of Pospiviroidae in the discovery of RdDM, expound the gradual elucidation through the years of the diverse array of RdDM’s mechanistic details and propose a revised RdDM model based on the cumulative amount of evidence from viroid and non-viroid systems.
B Cell Activation and Escape of Tolerance Checkpoints: Recent Insights from Studying Autoreactive B Cells
Authors: Bonasia Carlo G. , Abdulahad Wayel H. , Rutgers Abraham , Heeringa Peter , Bos Nicolaas A.
Published: May 2021

Autoreactive B cells are key drivers of pathogenic processes in autoimmune diseases by the production of autoantibodies, secretion of cytokines, and presentation of autoantigens to T cells. However, the mechanisms that underlie the development of autoreactive B cells are not well understood. Here, we review recent studies leveraging novel techniques to identify and characterize (auto)antigen-specific B cells. The insights gained from such studies pertaining to the mechanisms involved in the escape of tolerance checkpoints and the activation of autoreactive B cells are discussed. In addition, we briefly highlight potential therapeutic strategies to target and eliminate autoreactive B cells in autoimmune diseases.
Novel Roles of SH2 and SH3 Domains in Lipid Binding
Authors: Sipeki Szabolcs , Koprivanacz Kitti , Takács Tamás , Kurilla Anita , László Loretta , Vas Virag , Buday László
Published: May 2021

Signal transduction, the ability of cells to perceive information from the surroundings and alter behavior in response, is an essential property of life. Studies on tyrosine kinase action fundamentally changed our concept of cellular regulation. The induced assembly of subcellular hubs via the recognition of local protein or lipid modifications by modular protein interactions is now a central paradigm in signaling. Such molecular interactions are mediated by specific protein interaction domains. The first such domain identified was the SH2 domain, which was postulated to be a reader capable of finding and binding protein partners displaying phosphorylated tyrosine side chains. The SH3 domain was found to be involved in the formation of stable protein sub-complexes by constitutively attaching to proline-rich surfaces on its binding partners. The SH2 and SH3 domains have thus served as the prototypes for a diverse collection of interaction domains that recognize not only proteins but also lipids, nucleic acids, and small molecules. It has also been found that particular SH2 and SH3 domains themselves might also bind to and rely on lipids to modulate complex assembly. Some lipid-binding properties of SH2 and SH3 domains are reviewed here.
Extracellular Soluble Membranes from Retinal Pigment Epithelial Cells Mediate Apoptosis in Macrophages
Authors: Sanjiv Nayan , Osathanugrah Pawarissara , Fraser Emma , Ng Tat Fong , Taylor Andrew W.
Published: May 2021

A central characterization of retinal immunobiology is the prevention of proinflammatory activity by macrophages. The retinal pigment epithelial cells (RPEs) are a major source of soluble anti-inflammatory factors. This includes a soluble factor that induces macrophage apoptosis when the activity of the immunomodulating neuropeptide alpha-melanocyte-stimulating hormone (α-MSH) is neutralized. In this manuscript, isolated extracellular soluble membranes (ESMs) from primary RPE were assayed to see if they could be the soluble mediator of apoptosis. Our results demonstrated that RPE ESMs mediated the induction of macrophage apoptosis that was suppressed by α-MSH. In contrast, the RPE line ARPE-19, cultured under conditions that induce similar anti-inflammatory activity to primary RPEs, did not activate apoptosis in the macrophages. Moreover, only the ESMs from primary RPE cultures, and not those from the ARPE-19 cell cultures, expressed mFasL. The results demonstrate that RPE ESMs are a soluble mediator of apoptosis and that this may be a mechanism by which the RPEs select for the survival of α-MSH-induced suppressor cells.