bluuebunny/crossref_metadata_2025 huggingface dataset:
New Protocol and Architecture for a Wastewater Treatment System Intended for Irrigation
Authors: Jimenez Jose M. , Parra Lorena , García Laura , Lloret Jaime , Mauri Pedro V. , Lorenz Pascal
Published: April 2021

Water quality may be affected by aspects such as pollution from industries, agricultural fertilizers and pesticides, and waste produced by humans. This contamination can affect the produce of the fields irrigated by untreated water. Therefore, it is necessary to add a treatment process in irrigation systems. In this paper, an architecture, communication protocol, and a data analysis algorithm for a wastewater treatment system intended for irrigation are presented. Our system includes a smart group-based wireless sensor network that is able to detect high salinity levels and pollution stains, such as oil spills. When contamination is detected, the water is led into auxiliary canals that perform the biosorption process to treat the water and dump it back into the main canal. Simulations were performed to assess the amount of data stored on the secure digital (SD) card, the consumed bandwidth, and the energy consumption of our proposal. The results show the system has a low bandwidth consumption with a maximum of 2.58 kbps for the setting of two daily data transmissions of the node in the last auxiliary canal. Furthermore, it can sustain the energy consumption in adverse conditions, where the node with the highest energy consumption reaches the lowest energy value of 12,320 mW/h.
Nano-Silver Particles Reduce Contaminations in Tissue Culture but Decrease Regeneration Rate and Slows Down Growth and Development of Aldrovanda vesiculosa Explants
Authors: Parzymies Marzena
Published: April 2021

Aldrovanda vesiculosa is a carnivorous water plant which is endangered by extinction worldwide. The number of natural stands and populations has decreased; therefore, there is a need for its active protection. The best method would be an in vitro culture. One of the main problems is disinfection of the explants. Therefore, it was decided that we should treat the explants with nano-silver particles. The explants were shoot fragments which were disinfected with sodium hypochlorite and then placed in a liquid 1/5 MS medium, supplemented with silver nanoparticles (AgNPs) at a concentration of 5 mg·dm−3. It was observed that AgNPs reduced the number of contaminations but also led to necrosis of the shoots. The shoots, which undertook regeneration in presence of AgNPs, were smaller and did not form traps; however, after being moved to fresh media twice, they started to develop normal leaves. Taking into consideration both disinfection and regeneration rates, it might be advisable to disinfect aldrovanda shoots in sodium hypochlorite only, without AgNPs. The results of the research might indicate a toxic activity of AgNPs towards water plants, which seems a big problem, as nanoparticles are commonly used in all the fields of life. However, the matter should be studied further.
A 6DOF Virtual Environment Space Docking Operation with Human Supervision
Authors: Copot Cosmin , Muresan Cristina I. , Beschi Manuel , Ionescu Clara M.
Published: April 2021

In this work, we present a synchronous co-simulation of a 6DOF (six degree of freedom) ball and plate platform and its 3D computer model. The co-simulation in the virtual environment is intended to mimic the rendezvous between a cargo vehicle such as the Falcon 9 from SpaceX and the ISS (International Space Station). The visual feedback sensing of the position of the 6DOF platform is implemented using a Kinect RGB-D device. The human in the loop acts as supervisory control for initiating the docking mechanism. This paper delivers an adaptive fractional order control solution which is easily tunable, implementable and validated on a laboratory benchmark. The results indicate that fractional order control can tackle large variability in the system dynamics and deliver specified performance at all times.
Identification of Synonyms Using Definition Similarities in Japanese Medical Device Adverse Event Terminology
Authors: Yagahara Ayako , Uesugi Masahito , Yokoi Hideto
Published: April 2021

Japanese medical device adverse events terminology, published by the Japan Federation of Medical Devices Associations (JFMDA terminology), contains entries for 89 terminology items, with each of the terminology entries created independently. It is necessary to establish and verify the consistency of these terminology entries and map them efficiently and accurately. Therefore, developing an automatic synonym detection tool is an important concern. Such tools for edit distances and distributed representations have achieved good performance in previous studies. The purpose of this study was to identify synonyms in JFMDA terminology and evaluate the accuracy using these algorithms. A total of 125 definition sentence pairs were created from the terminology as baselines. Edit distances (Levenshtein and Jaro–Winkler distance) and distributed representations (Word2vec, fastText, and Doc2vec) were employed for calculating similarities. Receiver operating characteristic analysis was carried out to evaluate the accuracy of synonym detection. A comparison of the accuracies of the algorithms showed that the Jaro–Winkler distance had the highest sensitivity, Doc2vec with DM had the highest specificity, and the Levenshtein distance had the highest value in area under the curve. Edit distances and Doc2vec makes it possible to obtain high accuracy in predicting synonyms in JFMDA terminology.
Detection and Classification of Human Activity for Emergency Response in Smart Factory Shop Floor
Authors: Nwakanma Cosmas Ifeanyi , Islam Fabliha Bushra , Maharani Mareska Pratiwi , Lee Jae-Min , Kim Dong-Seong
Published: April 2021

Factory shop floor workers are exposed to threats and accidents due to their encounters with tools, equipment, and toxic materials. There are cases of occupational accidents resulting in injuries to workers and precipitating lawsuits, which on the other hand affect company’s operational cost. To ensure the safety of workers within the shop floor, there is a need for proactive activity monitoring. Such activities include detection of falling objects, abnormal vibration, and movement of humans within an acceptable area of the factory floor. Breathing sensor-based monitoring of workers in the smart factory shop floor can also be implemented. This is for the detection of human activity, especially in cases where workers are in isolation with no available emergency assistance. Internet of Things (IoT), Industrial Internet of Things (IIoT), and machine learning (ML) have enabled so many possibilities in this area. In this study, we present a simple test-bed, which is made up of a vibration sensor, a breathing and movement sensor, and a Light Detection and Ranging (LIDAR) sensor. These sensors were used to gather normal and abnormal data of human activities at the factory. We developed a dataset based on possible real-life situations and it is made up of about 10,000 data points. The data was split with a ratio of 75:25 for training and testing the model. We investigated the performance of different ML algorithms, including support vector machine (SVM), linear regression, naive Bayes (NB), K-nearest neighbor (KNN), and convolutional neural network (CNN). From our experiments, the CNN model outperformed other algorithms with an accuracy of 99.45%, 99.78%,100%, and 100%, respectively, for vibration, movement, breathing, and distance. We have also successfully developed a dataset to assist the research community in this field.
Automatic Symbol Resolution on Embedded Platforms by the Example of Smart TV Device
Authors: Majchrowicz Michał , Duch Piotr
Published: April 2021

Smart TV devices are gaining increasingly more popularity. Due to their nature, Smart TVs can access a lot of sensitive data. This is one of the reasons why the Smart TV has become a popular target of hacking recently. Manufacturers try to make such attacks more difficult, and one of the methods they use is the removal of symbols from the firmware. In principle, this would prevent or significantly hinder the preparation of malwares or homebrew that could run on different firmware versions. This article is focused on developing algorithms for automatic symbol resolution. We proposed two automatic symbol resolution methods designed for Smart TVs. Presented methods were tested on the firmwares of the most popular Smart TV manufacturers’, Samsung and LG, devices. Furthermore, an original framework is presented, which automatically locates the desired function in the binaries based on characteristic strings used in or near searched function. The developed framework is commonly used by homebrew developers (e.g., SamyGO) and releases developers from hardcoding function’s addresses for different firmwares.
Quantitative Assessment of Cybersecurity Risks for Mitigating Data Breaches in Business Systems
Authors: Algarni Abdullah M. , Thayananthan Vijey , Malaiya Yashwant K.
Published: April 2021

The evaluation of data breaches and cybersecurity risks has not yet been formally addressed in modern business systems. There has been a tremendous increase in the generation, usage and consumption of industrial and business data as a result of smart and computational intensive software systems. This has resulted in an increase in the attack surface of these cyber systems. Consequently, there has been a consequent increase in the associated cybersecurity risks. However, no significant studies have been conducted that examine, compare, and evaluate the approaches used by the risk calculators to investigate the data breaches. The development of an efficient cybersecurity solution allows us to mitigate the data breaches threatened by the cybersecurity risks such as cyber-attacks against database storage, processing and management. In this paper, we develop a comprehensive, formal model that estimates the two components of security risks: breach cost and the likelihood of a data breach within 12 months. The data used in this model are taken from the industrial business report, which provides the necessary information collected and the calculators developed by the major organizations in the field. This model integrated with the cybersecurity solution uses consolidated factors that have a significant impact on the data breach risk. We propose mathematical models of how the factors impact the cost and the likelihood. These models allow us to conclude that results obtained through the models mitigate the data breaches in the potential and future business system dynamically.
Attainable Moment Set Optimization to Support Configuration Design: A Required Moment Set Based Approach
Authors: Zhang Jiannan , Söpper Max , Holzapfel Florian
Published: April 2021

In this paper, we discuss an attainable moment set (AMS) optimization methodology considering a system’s required moment set (RMS). The AMS describes the achievable moments from a system, given its input limits. An RMS, like an AMS, is a convex set in the moment space, describing the required moments for a system to meet the designed mission profile and disturbance rejection requirements. Given the configuration of a system, its mission requirements, and the derived RMS, the proposed optimization maximizes coverage of the AMS onto the RMS, thus ensuring the system possesses the guaranteed controllability to fulfill its required missions from a design level. To achieve this goal, the variables to optimize are chosen as effector settings, such as the installation position and angle of propellers and control surfaces, which effectively change the AMS without a vast impact on major design parameters, such as mass and moment of inertia. Since the optimization includes massive geometry operations of rays intersecting polyhedron, an efficient intersection solver is proposed to speed up the optimization process. The described method is applied to an electric-vertical-take-of-landing vehicle (eVTOL) with eight hover propellers, which delivers a highly improved coverage of the RMS compared to its initial design.
Employing Finite Element Analysis and Robust Control Concepts in Mechatronic System Design-Flexible Manipulator Case Study
Authors: Goubej Martin , Königsmarková Jana , Kampinga Ronald , Nieuwenkamp Jakko , Paquay Stéphane
Published: April 2021

The paper deals with development of a methodology for mechatronic system design using state-of-the-art model-based system engineering methods. A simple flexible robotic arm is considered as a benchmark problem for the evaluation of various techniques used in the phases of modelling, analysis, control system design, validation, and implementation. The flexible nature of the mechanical structure introduces inherently oscillatory dynamics in the target bandwidth range, which complicates all the above-mentioned design steps. This paper demonstrates the process of deriving a complex nonlinear model of the flexible arm setup. An initial idea about the plant dynamics is acquired from analytical modelling using the Euler–Bernoulli beam theory. A more thorough understanding is subsequently acquired from finite element analysis. Linearisation and order reduction are the next steps necessary for the derivation of a simplified control-relevant model. A time-dependent variable parameter of load mass position is considered and a robust controller is subsequently designed in order to fulfil certain performance criteria for all the admissible plant configurations. This is performed using a recent H-infinity loop shaping method for fixed structure controller design. The results are validated by means of a physical plant, comparing the experimental data with the model predictions.
Research on Energy Storage Optimization Operation Schedule in an Island System
Authors: Chen Yu-Tung , Kuo Cheng-Chien , Jhan Jia-Zhang
Published: April 2021

This paper proposes a 24-h ahead unit commitment for a diesel-photovoltaic (PV)-battery system using mixed-integer linear programming (MILP) to minimize the operating cost which includes the power storage system (PSS) in the reserve capacity. Considering the Kinmen island’s winter peak load case of 20 MW, and summer peak load case of 60 MW, a 24-h schedule for the diesel-PV-battery system island system for these two scenarios was optimized that allows the PSS to perform both as an additional reserve capacity and peak-shaving auxiliary device. The results show that the addition of PSS in the dispatch decision can allow the flexibility of the systems, especially in the reserve allocation, to up to twice the value of the PSS capacity. In this way, the PSS reduces the early startup and late shutdown of high-cost units while maintaining the system reserve, thereby, reducing the operating cost of the system.
Clustering Moving Object Trajectories: Integration in CROSS-CPP Analytic Toolbox
Authors: Blazquez-Herranz Alberto , Caballero-Garzon Juan-Ignacio , Zilverberg Albert , Wolff Christian , Rodríguez-Gonzalez Alejandro , Menasalvas Ernestina
Published: April 2021

Mobile devices equipped with sensors are generating an amount of geo-spatial related data that, properly analyzed can be used for future applications. In particular, being able to establish similar trajectories is crucial to analyze events on common points in the trajectories. CROSS-CPP is a European project whose main aim is to provide tools to store data in a data market and to have a toolbox to analyze the data. As part of these analytic tools, a set of functionalities has been developed to cluster trajectories. Based on previous work on clustering algorithms we present in this paper a Quickbundels algorithm adaptation to trajectory clustering . Experiments using different distance measures show that Quickbundles outperforms spectral clustering, with the WS84 geodesic distance being the one that provides the best results.
Path Planning Based on Obstacle-Dependent Gaussian Model Predictive Control for Autonomous Driving
Authors: Pae Dong-Sung , Kim Geon-Hee , Kang Tae-Koo , Lim Myo-Taeg
Published: April 2021

Path planning research plays a vital role in terms of safety and comfort in autonomous driving systems. This paper focuses on safe driving and comfort riding through path planning in autonomous driving applications and proposes autonomous driving path planning through an optimal controller integrating obstacle-dependent Gaussian (ODG) and model prediction control (MPC). The ODG algorithm integrates the information from the sensors and calculates the risk factors in the driving environment. The MPC function finds vehicle control signals close to the objective function under limited conditions, such as the structural shape of the vehicle and road driving conditions. The proposed method provides safe control and minimizes vehicle shaking due to the tendency to respond to avoid obstacles quickly. We conducted an experiment using mobile robots, similar to an actual vehicle, to verify the proposed algorithm performance. The experimental results show that the average safety metric is 72.34%, a higher ISO-2631 comport score than others, while the average processing time is approximately 14.2 ms/frame.
Intelligent Scheduling with Reinforcement Learning
Authors: Cunha Bruno , Madureira Ana , Fonseca Benjamim , Matos João
Published: April 2021

In this paper, we present and discuss an innovative approach to solve Job Shop scheduling problems based on machine learning techniques. Traditionally, when choosing how to solve Job Shop scheduling problems, there are two main options: either use an efficient heuristic that provides a solution quickly, or use classic optimization approaches (e.g., metaheuristics) that take more time but will output better solutions, closer to their optimal value. In this work, we aim to create a novel architecture that incorporates reinforcement learning into scheduling systems in order to improve their overall performance and overcome the limitations that current approaches present. It is also intended to investigate the development of a learning environment for reinforcement learning agents to be able to solve the Job Shop scheduling problem. The reported experimental results and the conducted statistical analysis conclude about the benefits of using an intelligent agent created with reinforcement learning techniques. The main contribution of this work is proving that reinforcement learning has the potential to become the standard method whenever a solution is necessary quickly, since it solves any problem in very few seconds with high quality, approximate to the optimal methods.
Verification and Optimization of an Ultra-Low Volume (ULV) Sprayer Used for the Inactivation of Indoor Total Bacteria
Authors: Choi Yun-Hee , Huh Da-An , Lee Ju-Yeon , Choi Ji Yoon , Moon Kyong Whan
Published: April 2021

Physical and chemical cleaning for the removal of indoor microorganisms, which can cause allergic reactions and respiratory diseases, is labor-intensive and time-consuming. An ultra-low volume (ULV) sprayer, a newly introduced device to inactivate pathogenic microorganisms, allows the disinfectant particles to reach hard-to-reach spaces indoors and is more cost-effective than the existing methods. However, few studies have been conducted to verify the efficiency of the ULV sprayer. Here, we verified the disinfection efficiency of the ULV sprayer for inactivating total bacteria present on indoor surfaces, considering the factors affecting bacteria inactivation, and presented the optimal ULV sprayer usage conditions to achieve the highest disinfection efficiency depending on room size. The total bacteria removal efficiency was high (range: 0.56–2.46 log10 reductions), including hard-to-reach spaces. A response surface model was developed to identify the individual and interactive effects of the disinfectant concentration, spray amount, and room size on total bacteria disinfection efficiency. These three variables had interactive effects on the total bacteria disinfection efficiency. The experimental data were fitted to a second-order polynomial model, with high coefficients of determination (R2) for all models (R2 > 0.82). The optimum conditions were a spray amount of 3.08–6.40 L in 160 m3, 3.78–7.22 L in 230 m3, and 5.68–8 L in 300 m3 surface area when using dilution rates of 100 times. These conditions predicted a bacterial disinfection efficiency of >1.10 log10 reductions (92%) on all surfaces. Our results clearly indicate that the ULV sprayer effectively inactivates total bacteria present on indoor surfaces.
Conventional and Enzyme-Assisted Extraction of Rosemary Leaves (Rosmarinus officinalis L.): Toward a Greener Approach to High Added-Value Extracts
Authors: Pontillo Antonella Rozaria Nefeli , Papakosta-Tsigkri Lydia , Lymperopoulou Theopisti , Mamma Diomi , Kekos Dimitris , Detsi Anastasia
Published: April 2021

The effect of different extraction methods of rosemary leaves on the total phenolic content (TPC), and the antioxidant activity of the extracts was herein investigated. Firstly, the solid-liquid conventional extraction (CEM) and microwave-assisted extraction (MAE) were implemented in an effort to identify the effect of the solvent and of microwave irradiation on the extract quality. The extract obtained from CEM at room temperature, using ethanol/water 95:5 v/v, showed the highest antioxidant activity (IC50 = 12.1 μg/mL). MAE using ethanol/water 50:50 v/v provided an extract with TPC and DPPH radical scavenging ability in a significantly shorter extraction time (1 h for MAE and 24 h for CEM). Enzyme-assisted extraction (EAE) using five commercial enzyme formulations was implemented, and the kinetic equation was calculated. Finally, the effect of EAE as a pretreatment method to CEM was examined. Pretreatment of the plant material with pectinolytic enzymes for 1 h prior to a 24 h CEM with 50% hydroethanolic solvent was found to be the optimum conditions for the extraction of rosemary leaves, providing an extract with higher DPPH radical scavenging ability (IC50 14.3 ± 0.8 μg/mL) and TPC (15.2 ± 0.3 mgGAE/grosemary) than the corresponding extract without the enzyme pretreatment.
Erratum: Hussein et al. Indoor Particle Concentrations, Size Distributions, and Exposures in Middle Eastern Microenvironments. Atmosphere 2020, 11, 41
Authors: Hussein Tareq , Alameer Ali , Jaghbeir Omar , Albeitshaweesh Kolthoum , Malkawi Mazen , Boor Brandon E. , Koivisto Antti Joonas , Löndahl Jakob , Alrifai Osama , Al-Hunaiti Afnan
Published: April 2021

The authors would like to correct the published article [...]
Snow Processes and Climate Sensitivity in an Arid Mountain Region, Northern Chile
Authors: Jara Francisco , Lagos-Zúñiga Miguel , Fuster Rodrigo , Mattar Cristian , McPhee James
Published: April 2021

Seasonal snow and glaciers in arid mountain regions are essential in sustaining human populations, economic activity, and ecosystems, especially in their role as reservoirs. However, they are threatened by global atmospheric changes, in particular by variations in air temperature and their effects on precipitation phase, snow dynamics and mass balance. In arid environments, small variations in snow mass and energy balance can produce large changes in the amount of available water. This paper provides insights into the impact of global warming on the mass balance of the seasonal snowpack in the mountainous Copiapó river basin in northern Chile. A dataset from an experimental station was combined with reanalysis data to run a physically based snow model at site and catchment scales. The basin received an average annual precipitation of approximately 130 mm from 2001 to 2016, with sublimation losses higher than 70% of the snowpack. Blowing snow sublimation presented an orographic gradient resultant from the decreasing air temperature and windy environment in higher elevations. Under warmer climates, the snowpack will remain insensitive in high elevations (>4000 m a.s.l.), but liquid precipitation will increase at lower heights.
GeoLOD: A Spatial Linked Data Catalog and Recommender
Authors: Kopsachilis Vasilis , Vaitis Michail
Published: April 2021

The increasing availability of linked data poses new challenges for the identification and retrieval of the most appropriate data sources that meet user needs. Recent dataset catalogs and recommenders provide advanced methods that facilitate linked data search, but none exploits the spatial characteristics of datasets. In this paper, we present GeoLOD, a web catalog of spatial datasets and classes and a recommender for spatial datasets and classes possibly relevant for link discovery processes. GeoLOD Catalog parses, maintains and generates metadata about datasets and classes provided by SPARQL endpoints that contain georeferenced point instances. It offers text and map-based search functionality and dataset descriptions in GeoVoID, a spatial dataset metadata template that extends VoID. GeoLOD Recommender pre-computes and maintains, for all identified spatial classes in the Web of Data (WoD), ranked lists of classes relevant for link discovery. In addition, the on-the-fly Recommender allows users to define an uncatalogued SPARQL endpoint, a GeoJSON or a Shapefile and get class recommendations in real time. Furthermore, generated recommendations can be automatically exported in SILK and LIMES configuration files in order to be used for a link discovery task. In the results, we provide statistics about the status and potential connectivity of spatial datasets in the WoD, we assess the applicability of the recommender, and we present the outcome of a system usability study. GeoLOD is the first catalog that targets both linked data experts and geographic information systems professionals, exploits geographical characteristics of datasets and provides an exhaustive list of WoD spatial datasets and classes along with class recommendations for link discovery.
Identification of Differential N-Glycan Compositions in the Serum and Tissue of Colon Cancer Patients by Mass Spectrometry
Authors: Coura Marcelo de M.A. , Barbosa Eder A. , Brand Guilherme D. , Bloch Carlos , de Sousa Joao B.
Published: April 2021

Colorectal cancer (CRC) ranks second as the leading cause of cancer-related deaths worldwide. N-glycosylation is one of the most common posttranslational protein modifications. Therefore, we studied the total serum N-glycome (TSNG) of 13 colon cancer patients compared to healthy controls using MALDI-TOF/MS and LC-MS. N-glycosylation of cancer tumor samples from the same cohort were further quantified using a similar methodology. In total, 23 N-glycan compositions were down-regulated in the serum of colon cancer patients, mostly galactosylated forms whilst the mannose-rich HexNAc2Hex7, the fucosylated bi-antennary glycan HexNAc4Hex5Fuc1NeuAc2, and the tetra-antennary HexNAc6Hex7NeuAc3 were up-regulated in serum. Hierarchical clustering analysis of TSNG correctly singled out 85% of the patients from controls. Albeit heterogenous, N-glycosylation of tumor samples showed overrepresented oligomannosidic, bi-antennary hypogalactosylated, and branched compositions related to normal colonic tissue, in both MALDI-TOF/MS and LC-MS analysis. Moreover, compositions found upregulated in tumor tissue were mostly uncorrelated to compositions in serum of cancer patients. Mass spectrometry-based N-glycan profiling in serum shows potential in the discrimination of patients from healthy controls. However, the compositions profile in serum showed no parallel with N-glycans in tumor microenvironment, which suggests a different origin of compositions found in serum of cancer patients.
SARS-CoV-2 Mpro: A Potential Target for Peptidomimetics and Small-Molecule Inhibitors
Authors: Citarella Andrea , Scala Angela , Piperno Anna , Micale Nicola
Published: April 2021

The uncontrolled spread of the COVID-19 pandemic caused by the new coronavirus SARS-CoV-2 during 2020–2021 is one of the most devastating events in the history, with remarkable impacts on the health, economic systems, and habits of the entire world population. While some effective vaccines are nowadays approved and extensively administered, the long-term efficacy and safety of this line of intervention is constantly under debate as coronaviruses rapidly mutate and several SARS-CoV-2 variants have been already identified worldwide. Then, the WHO’s main recommendations to prevent severe clinical complications by COVID-19 are still essentially based on social distancing and limitation of human interactions, therefore the identification of new target-based drugs became a priority. Several strategies have been proposed to counteract such viral infection, including the repurposing of FDA already approved for the treatment of HIV, HCV, and EBOLA, inter alia. Among the evaluated compounds, inhibitors of the main protease of the coronavirus (Mpro) are becoming more and more promising candidates. Mpro holds a pivotal role during the onset of the infection and its function is intimately related with the beginning of viral replication. The interruption of its catalytic activity could represent a relevant strategy for the development of anti-coronavirus drugs. SARS-CoV-2 Mpro is a peculiar cysteine protease of the coronavirus family, responsible for the replication and infectivity of the parasite. This review offers a detailed analysis of the repurposed drugs and the newly synthesized molecules developed to date for the treatment of COVID-19 which share the common feature of targeting SARS-CoV-2 Mpro, as well as a brief overview of the main enzymatic and cell-based assays to efficaciously screen such compounds.
Relationship between Oxidative Stress and Imatinib Resistance in Model Chronic Myeloid Leukemia Cells
Authors: Głowacki Sylwester , Synowiec Ewelina , Szwed Marzena , Toma Monika , Skorski Tomasz , Śliwiński Tomasz
Published: April 2021

Chronic myeloid leukemia (CML) develops due to the presence of the BCR-ABL1 protein, a target of tyrosine kinase inhibitors (TKIs), such as imatinib (IM), used in a CML therapy. CML eradication is a challenge due to developing resistance to TKIs. BCR-ABL1 induces endogenous oxidative stress leading to genomic instability and development of TKI resistance. Model CML cells susceptible or resistant to IM, as well as wild-type, non-cancer cells without the BCR-ABL1 protein were treated with IM, hydrogen peroxide (H2O2) as a model trigger of external oxidative stress, or with IM+H2O2. Accumulation of reactive oxygen species (ROS), DNA damage, activity of selected antioxidant enzymes and glutathione (GSH), and mitochondrial potential (MMP) were assessed. We observed increase in ROS accumulation in BCR-ABL1 positive cells and distinct levels of ROS accumulation in IM-susceptible cells when compared to IM-resistant ones, as well as increased DNA damage caused by IM action in sensitive cells. Depletion of GSH levels and a decreased activity of glutathione peroxidase (GPx) in the presence of IM was higher in the cells susceptible to IM. IM-resistant cells showed an increase of catalase activity and a depletion of MMP. BCR-ABL1 kinase alters ROS metabolism, and IM resistance is accompanied by the changes in activity of GPx, catalase, and alterations in MMP.
In Vitro Investigation of Vascular Permeability in Endothelial Cells from Human Artery, Vein and Lung Microvessels at Steady-State and Anaphylactic Conditions
Authors: Callesen Katrine T. , Yuste-Montalvo Alma , Poulsen Lars K. , Jensen Bettina M. , Esteban Vanesa
Published: April 2021

Human anaphylactic reactions largely involve an increase in vascular permeability, which is mainly controlled by endothelial cells (ECs). Due to the acute and serious nature of human anaphylaxis, in vivo studies of blood vessels must be replaced or supplemented with in vitro models. Therefore, we used a macromolecular tracer assay (MMTA) to investigate the EC permeability of three phenotypes of human ECs: artery (HAECs), vein (HSVECs) and microvessels from lung (HMLECs). ECs were stimulated with two fast-acting anaphylactic mediators (histamine and platelet-activating factor (PAF)) and one longer-lasting mediator (thrombin). At steady-state conditions, HSVEC monolayers were the most permeable and HMLEC the least (15.8% and 8.3% after 60 min, respectively). No response was found in ECs from artery or vein to any stimuli. ECs from microvessels reacted to stimulation with thrombin and also demonstrated a tendency of increased permeability for PAF. There was no reaction for histamine. This was not caused by missing receptor expression, as all three EC phenotypes expressed receptors for both PAF and histamine. The scarce response to fast-acting mediators illustrates that the MMTA is not suitable for investigating EC permeability to anaphylactic mediators.
Artificially Induced Pluripotent Stem Cell-Derived Whole-Brain Organoid for Modelling the Pathophysiology of Metachromatic Leukodystrophy and Drug Repurposing
Authors: Esmail Sally , Danter Wayne R.
Published: April 2021

Metachromatic leukodystrophy (MLD) is a rare neurodegenerative disease that results from a deficiency of the lysosomal enzyme arylsulfatase A (ARSA). Worldwide, there are between one in 40,000 and one in 160,000 people living with the disease. While there are currently no effective treatments for MLD, induced pluripotent stem cell-derived brain organoids have the potential to provide a better understanding of MLD pathogenesis. However, developing brain organoid models is expensive, time consuming and may not accurately reflect disease progression. Using accurate and inexpensive computer simulations of human brain organoids could overcome the current limitations. Artificially induced whole-brain organoids (aiWBO) have the potential to greatly expand our ability to model MLD and guide future wet lab research. In this study, we have upgraded and validated our artificially induced whole-brain organoid platform (NEUBOrg) using our previously validated machine learning platform, DeepNEU (v6.2). Using this upgraded NEUBorg, we have generated aiWBO simulations of MLD and provided a novel approach to evaluate factors associated with MLD pathogenesis, disease progression and new potential therapeutic options.
Corticospinal Excitability during a Perspective Taking Task as Measured by TMS-Induced Motor Evoked Potentials
Authors: Murray Elizabeth , Brenya Janet , Chavarria Katherine , Kelly Karen J. , Fierst Anjel , Ahmad Nathira , Anton Caroline , Shaffer Layla , Kapila Kairavi , Driever Logan , Weaver Kayla , Dial Caroline , Crawford Maya , Hartman Iso , Infantino Tommy , Butler Fiona , Straus Abigail , Walker Shakeera L. , Balugas Brianna , Pardillo Mathew , Goncalves Briana , Keenan Julian Paul
Published: April 2021

Only by understanding the ability to take a third-person perspective can we begin to elucidate the neural processes responsible for one’s inimitable conscious experience. The current study examined differences in hemispheric laterality during a first-person perspective (1PP) and third-person perspective (3PP) taking task, using transcranial magnetic stimulation (TMS). Participants were asked to take either the 1PP or 3PP when identifying the number of spheres in a virtual scene. During this task, single-pulse TMS was delivered to the motor cortex of both the left and right hemispheres of 10 healthy volunteers. Measures of TMS-induced motor-evoked potentials (MEPs) of the contralateral abductor pollicis brevis (APB) were employed as an indicator of lateralized cortical activation. The data suggest that the right hemisphere is more important in discriminating between 1PP and 3PP. These data add a novel method for determining perspective taking and add to the literature supporting the role of the right hemisphere in meta representation.
Quantitative EEG in Cognitive Neuroscience
Authors: Höller Yvonne
Published: April 2021

Quantitative electroencephalography (EEG) distinguishes itself from clinical EEG by the application of mathematical approaches and computer scientific methods [...]
Differentiating Real-World Autobiographical Experiences without Recourse to Behaviour
Authors: Erez Jonathan , Gagnon Marie-Eve , Owen Adrian M.
Published: April 2021

Investigating human consciousness based on brain activity alone is a key challenge in cognitive neuroscience. One of its central facets, the ability to form autobiographical memories, has been investigated through several fMRI studies that have revealed a pattern of activity across a network of frontal, parietal, and medial temporal lobe regions when participants view personal photographs, as opposed to when they view photographs from someone else’s life. Here, our goal was to attempt to decode when participants were re-experiencing an entire event, captured on video from a first-person perspective, relative to a very similar event experienced by someone else. Participants were asked to sit passively in a wheelchair while a researcher pushed them around a local mall. A small wearable camera was mounted on each participant, in order to capture autobiographical videos of the visit from a first-person perspective. One week later, participants were scanned while they passively viewed different categories of videos; some were autobiographical, while others were not. A machine-learning model was able to successfully classify the video categories above chance, both within and across participants, suggesting that there is a shared mechanism differentiating autobiographical experiences from non-autobiographical ones. Moreover, the classifier brain maps revealed that the fronto-parietal network, mid-temporal regions and extrastriate cortex were critical for differentiating between autobiographical and non-autobiographical memories. We argue that this novel paradigm captures the true nature of autobiographical memories, and is well suited to patients (e.g., with brain injuries) who may be unable to respond reliably to traditional experimental stimuli.
Behavioral and Attitudinal Correlates of Trusted Sources of COVID-19 Vaccine Information in the US
Authors: Latkin Carl A. , Dayton Lauren , Miller Jacob R. , Yi Grace , Jaleel Afareen , Nwosu Chikaodinaka C. , Yang Cui , Falade-Nwulia Oluwaseun
Published: April 2021

There is a critical need for the public to have trusted sources of vaccine information. A longitudinal online study assessed trust in COVID-19 vaccine information from 10 sources. A factor analysis for data reduction revealed two factors. The first factor contained politically conservative sources (PCS) of information. The second factor included eight news sources representing mainstream sources (MS). Multivariable logistic regression models were used. Trust in Dr. Fauci was also examined. High trust in MS was associated with intention to encourage family members to get COVID-19 vaccines, altruistic beliefs that more vulnerable people should have vaccine priority, and belief that racial minorities with higher rates of COVID-19 deaths should have priority. High trust in PCS was associated with intention to discourage friends from getting vaccinated. Higher trust in PCS was also associated with participants more likely to disagree that minorities with higher rates of COVID-19 deaths should have priority for a vaccine. High trust in Dr. Fauci as a source of COVID-19 vaccine information was associated with factors similar to high trust in MS. Fair, equitable, and transparent access and distribution are essential to ensure trust in public health systems’ abilities to serve the population.
Telomere Architecture Correlates with Aggressiveness in Multiple Myeloma
Authors: Rangel-Pozzo Aline , Yu Pak , LaL Sadhana , Asbaghi Yasmin , Sisdelli Luiza , Tammur Pille , Tamm Anu , Punab Mari , Klewes Ludger , Louis Sherif , Knecht Hans , Olujohungbe Adebayo , Mai Sabine
Published: April 2021

The prognosis of multiple myeloma (MM), an incurable B-cell malignancy, has significantly improved through the introduction of novel therapeutic modalities. Myeloma prognosis is essentially determined by cytogenetics, both at diagnosis and at disease progression. However, for a large cohort of patients, cytogenetic analysis is not always available. In addition, myeloma patients with favorable cytogenetics can display an aggressive clinical course. Therefore, it is necessary to develop additional prognostic and predictive markers for this disease to allow for patient risk stratification and personalized clinical decision-making. Genomic instability is a prominent characteristic in MM, and we have previously shown that the three-dimensional (3D) nuclear organization of telomeres is a marker of both genomic instability and genetic heterogeneity in myeloma. In this study, we compared in a longitudinal prospective study blindly the 3D telomeric profiles from bone marrow samples of 214 initially treatment-naïve patients with either monoclonal gammopathy of undetermined significance (MGUS), smoldering multiple myeloma (SMM), or MM, with a minimum follow-up of 5 years. Here, we report distinctive 3D telomeric profiles correlating with disease aggressiveness and patient response to treatment in MM patients, and also distinctive 3D telomeric profiles for disease progression in smoldering multiple myeloma patients. In particular, lower average intensity (telomere length, below 13,500 arbitrary units) and increased number of telomere aggregates are associated with shorter survival and could be used as a prognostic factor to identify high-risk SMM and MM patients.
Towards Targeted Alpha Therapy with Actinium-225: Chelators for Mild Condition Radiolabeling and Targeting PSMA—A Proof of Concept Study
Authors: Reissig Falco , Bauer David , Zarschler Kristof , Novy Zbynek , Bendova Katerina , Ludik Marie-Charlotte , Kopka Klaus , Pietzsch Hans-Jürgen , Petrik Milos , Mamat Constantin
Published: April 2021

Currently, targeted alpha therapy is one of the most investigated topics in radiopharmaceutical cancer management. Especially, the alpha emitter 225Ac has excellent nuclear properties and is gaining increasing popularity for the treatment of various tumor entities. We herein report on the synthesis of two universal 225Ac-chelators for mild condition radiolabeling and binding to conjugate molecules of pharmacological interest via the copper-mediated click chemistry. A convenient radiolabeling procedure was investigated as well as the complex stability proved for both chelators and two PSMA (prostate-specific membrane antigen)-targeting model radioconjugates. Studies regarding affinity and cell survival were performed on LNCaP cells followed by biodistribution studies, which were performed using LNCaP tumor-bearing mice. High efficiency radiolabeling for all conjugates was demonstrated. Cell binding studies revealed a fourfold lower cell affinity for the PSMA radioconjugate with one targeting motif compared to the radioconjugate owing two targeting motifs. Additionally, these differences were verified by in vitro cell survival evaluation and biodistribution studies, both showing a higher cell killing efficiency for the same dose, a higher tumor uptake (15%ID/g) and a rapid whole body clearance after 24 h. The synthesized chelators will overcome obstacles of lacking stability and worse labeling needs regarding 225Ac complexation using the DOTA (1,4,7,10-tetraazacyclododecane-1,4,7,10-tetrayl)tetraacetic acid) chelator. Moreover, the universal functionalization expands the coverage of these chelators in combination with any sensitive bio(macro)molecule, thus improving treatment of any addressable tumor target.
Profiling of Adipose and Skeletal Muscle in Human Pancreatic Cancer Cachexia Reveals Distinct Gene Profiles with Convergent Pathways
Authors: Narasimhan Ashok , Zhong Xiaoling , Au Ernie P. , Ceppa Eugene P. , Nakeeb Atilla , House Michael G. , Zyromski Nicholas J. , Schmidt C. Max , Schloss Katheryn N. H. , Schloss Daniel E. I. , Liu Yunlong , Jiang Guanglong , Hancock Bradley A. , Radovich Milan , Kays Joshua K. , Shahda Safi , Couch Marion E. , Koniaris Leonidas G. , Zimmers Teresa A.
Published: April 2021

The vast majority of patients with pancreatic ductal adenocarcinoma (PDAC) suffer cachexia. Although cachexia results from concurrent loss of adipose and muscle tissue, most studies focus on muscle alone. Emerging data demonstrate the prognostic value of fat loss in cachexia. Here we sought to identify the muscle and adipose gene profiles and pathways regulated in cachexia. Matched rectus abdominis muscle and subcutaneous adipose tissue were obtained at surgery from patients with benign conditions (n = 11) and patients with PDAC (n = 24). Self-reported weight loss and body composition measurements defined cachexia status. Gene profiling was done using ion proton sequencing. Results were queried against external datasets for validation. 961 DE genes were identified from muscle and 2000 from adipose tissue, demonstrating greater response of adipose than muscle. In addition to known cachexia genes such as FOXO1, novel genes from muscle, including PPP1R8 and AEN correlated with cancer weight loss. All the adipose correlated genes including SCGN and EDR17 are novel for PDAC cachexia. Pathway analysis demonstrated shared pathways but largely non-overlapping genes in both tissues. Age related muscle loss predominantly had a distinct gene profiles compared to cachexia. This analysis of matched, externally validate gene expression points to novel targets in cachexia.
Risk of Pharmacological or Hospital Treatment for Depression in Patients with Colorectal Cancer–Associations with Pre-Cancer Lifestyle, Comorbidity and Clinical Factors
Authors: Kjaer Trille Kristina , Moustsen-Helms Ida Rask , Albieri Vanna , Larsen Signe Benzon , Degett Thea Helene , Tjønneland Anne , Johansen Christoffer , Kjaer Susanne K. , Gogenur Ismail , Dalton Susanne Oksbjerg
Published: April 2021

We investigated the risk of depression in colorectal cancer (CRC) patients and associated risk factors. The 1324 patients with CRC and 6620 matched cancer-free participants from the Diet, Cancer and Health study were followed for up to 16 years for either a first hospitalization for depression or antidepressant prescription after diagnosis of CRC cancer or study entry date. Information on the outcome and covariates was retrieved from the Danish Colorectal Cancer Group database, the national health registries and questionnaires. Cumulative incidence of depression was estimated, and Cox regression models were used to evaluate the association between risk factors and depression incidence. During follow-up, 191 (14.4%) patients with CRC and 175 (2.6%) cancer-free comparison persons experienced depression. After adjustments, in the first year after cancer diagnosis, patients with CRC had a 12-fold higher hazard compared with the cancer-free population (HR, 12.01; 95% CI, 7.89–18.28). The risk decreased during follow-up but remained significantly elevated with an HR of 2.65 (95% CI, 1.61–4.36) after five years. Identified risk factors were presence of comorbidities, advanced disease stage and use of radiotherapy, while life style factors (pre-cancer or at diagnosis) and chemotherapy did not seem to contribute to the increased risk.