bluuebunny/crossref_metadata_2025 huggingface dataset:
Vibration and Derailment Analyses of Trains Moving on Curved and Cant Rails
Authors: Ju Shen-Haw , Ro Ti-Iaw
Published: June 2021

A moving axle finite element (FE) was developed to study the contact between a wheel and curved rail, where the FE can simulate multi-point contact with sticking, sliding, and separation modes. The possible contact region is inputted as a number of nodes along the wheel and rail surfaces, while the wheel nodes are simulated as cubic-splines. The rail node to wheel cubic-splines contact method is then used to find the normal and shear forces, where the normal and tangential stiffness values obtained from the three-dimensional (3D) FE analysis for an actual wheel and rail are used to model the force–displacement relationship. A simple theoretical solution for curved railways was used to validate the proposed FE in 3D analyses. The results show that good agreement with the theoretical and FE solutions for the contact normal force, shear force, wheel sliding, and wheel separation under various train speeds, curve radius, cant angles, and friction coefficients. This FE can be used in combination with other elements to simulate a train traveling on a curved track system, in which only the standard Newton–Raphson and Newmark’s methods are required in the FE main program.
Identification of Cost-Optimal Measures for Energy Renovation of Thermal Envelopes in Different Types of Public School Buildings in the City of Valencia
Authors: Liébana-Durán María Esther , Serrano-Lanzarote Begoña , Ortega-Madrigal Leticia
Published: June 2021

In order to achieve the EU emission reduction goals, it is essential to renovate the building stock, by improving energy efficiency and promoting total decarbonisation. According to the 2018/844/EU Directive, 3% of Public Administration buildings should be renovated every year. So as to identify the measures to be applied in those buildings and obtain the greatest reduction in energy consumption at the lowest cost, the Directive 2010/31/EU proposed a cost-optimisation-based methodology. The implementation of this allowed to carry out studies in detail in actual scenarios for the energy renovation of thermal envelopes of public schools in the city of Valencia. First, primary school buildings were analysed and classified into three representative types. For each type, 21 sets of measures for improving building thermal envelopes were proposed, considering the global cost, in order to learn about the savings obtained, the repayment term for the investment made, the percentage reduction in energy consumption and the level of compliance with regulatory requirements. The result and conclusions will help Public Administration in Valencia to draw up an energy renovation plan for public building schools in the city.
Semantic Web and Knowledge Graphs for Industry 4.0
Authors: Yahya Muhammad , Breslin John G. , Ali Muhammad Intizar
Published: June 2021

In recent years, due to technological advancements, the concept of Industry 4.0 (I4.0) is gaining popularity, while presenting several technical challenges being tackled by both the industrial and academic research communities. Semantic Web including Knowledge Graphs is a promising technology that can play a significant role in realizing I4.0 implementations. This paper surveys the use of the Semantic Web and Knowledge Graphs for I4.0 from different perspectives such as managing information related to equipment maintenance, resource optimization, and the provision of on-time and on-demand production and services. Moreover, to solve the challenges of limited depth and expressiveness in the current ontologies, we have proposed an enhanced reference generalized ontological model (RGOM) based on Reference Architecture Model for I4.0 (RAMI 4.0). RGOM can facilitate a range of I4.0 concepts including improved asset monitoring, production enhancement, reconfiguration of resources, process optimizations, product orders and deliveries, and the life cycle of products. Our proposed RGOM can be used to generate a knowledge graph capable of providing answers in response to any real-time query.
Three-Dimensional Reconstruction-Based Vibration Measurement of Bridge Model Using UAVs
Authors: Wu Zhihua , Chen Gongfa , Ding Qiong , Yuan Bing , Yang Xiaomei
Published: June 2021

This paper presents a measurement method of bridge vibration based on three-dimensional (3D) reconstruction. A video of bridge model vibration is recorded by an unmanned aerial vehicle (UAV), and the displacement of target points on the bridge model is tracked by the digital image correlation (DIC) method. Due to the UAV motion, the DIC-tracked displacement of the bridge model includes the absolute displacement caused by the excitation and the false displacement induced by the UAV motion. Therefore, the UAV motion must be corrected to measure the real displacement. Using four corner points on a fixed object plane as the reference points, the projection matrix for each frame of images can be estimated by the UAV camera calibration, and then the 3D world coordinates of the target points on the bridge model can be recovered. After that, the real displacement of the target points can be obtained. To verify the correctness of the results, the operational modal analysis (OMA) method is used to extract the natural frequencies of the bridge model. The results show that the first natural frequency obtained from the proposed method is consistent with the one obtained from the homography-based method. By further comparing with the homography-based correction method, it is found that the 3D reconstruction method can effectively overcome the limitation of the homography-based method that the fixed reference points and the target points must be coplanar.
Protection Strategy for Edge-Weighted Graphs in Disease Spread
Authors: Manríquez Ronald , Guerrero-Nancuante Camilo , Taramasco Carla
Published: June 2021

Fake news, viruses on computer systems or infectious diseases on communities are some of the problems that are addressed by researchers dedicated to study complex networks. The immunization process is the solution to these challenges and hence the importance of obtaining immunization strategies that control these spreads. In this paper, we evaluate the effectiveness of the DIL-Wα ranking in the immunization of nodes that are attacked by an infectious disease that spreads on an edge-weighted graph using a graph-based SIR model. The experimentation was done on real and scale-free networks and the results illustrate the benefits of this ranking.
Flexible Sample Environments for the Investigation of Soft Matter at the European Spallation Source: Part III—The Macroscopic Foam Cell
Authors: Kühnhammer Matthias , Widmann Tobias , Kreuzer Lucas P. , Schmid Andreas J. , Wiehemeier Lars , Frielinghaus Henrich , Jaksch Sebastian , Bögershausen Torsten , Barron Paul , Schneider Harald , Hiess Arno , Müller-Buschbaum Peter , Hellweg Thomas , von Klitzing Regine , Löhmann Oliver
Published: June 2021

The European Spallation Source (ESS), which is under construction in Lund (Sweden), will be the leading and most brilliant neutron source and aims at starting user operation at the end of 2023. Among others, two small angle neutron scattering (SANS) machines will be operated. Due to the high brilliance of the source, it is important to minimize the downtime of the instruments. For this, a collaboration between three German universities and the ESS was initialized to develop and construct a unified sample environment (SE) system. The main focus was set on the use of a robust carrier system for the different SEs, which allows setting up experiments and first prealignment outside the SANS instruments. This article covers the development and construction of a SE for SANS experiments with foams, which allows measuring foams at different drainage states and the control of the rate of foam formation, temperature, and measurement position. The functionality under ESS conditions was tested and neutron test measurement were carried out.
The Analysis of Periodic Order in Monolayers of Colloidal Superballs
Authors: Napel Daniël N. ten , Meijer Janne-Mieke , Petukhov Andrei V.
Published: June 2021

The characterization of periodic order in assemblies of colloidal particles can be complicated by the coincidence of Bragg diffraction peaks of the structure and minima in the form factor of the particles. Here, we demonstrate a general strategy to overcome this problem that is applicable to all low-dimensional structures. This approach is demonstrated in the application of small-angle X-ray scattering (SAXS) for the characterization of monolayers of colloidal silica superballs prepared using the unidirectional rubbing method. In this method, the ordering of the colloidal superballs is achieved by mechanically rubbing them onto a polydimethylsiloxane (PDMS)-coated surface. Using three differently shaped superballs, ranging from spherical to almost cubic, we show that certain Bragg peaks may not appear in the diffraction patterns due to the presence of minima in the form factor. We show that these missing Bragg peaks can be visualized by imaging the colloidal monolayers at various orientations. Moreover, we argue that the same strategy can be applied to other techniques, such as neutron scattering.
Predicting Electrokinetic Coupling and Electrical Conductivity in Fractured Media Using a Fractal Distribution of Tortuous Capillary Fractures
Authors: Thanh Luong Duy , Jougnot Damien , Do Phan Van , Hue Dang Thi Minh , Thuy Tran Thi Chung , Tuyen Vu Phi
Published: June 2021

Electrokinetics methods have attracted increasing interest to characterize hydrogeological processes in geological media, especially in complex hydrosystems such as fractured formations. In this work, we conceptualize fractured media as a bunch of parallel capillary fractures following the fractal size distribution. This conceptualization permits to obtain analytical models for both the electrical conductivity and the electrokinetic coupling in water saturated fractured media. We explore two different approaches to express the electrokinetic coupling. First, we express the streaming potential coupling coefficient as a function of the zeta potential and then we obtain the effective charge density in terms of macroscopic hydraulic and electrokinetic parameters of porous media. We show that when the surface electrical conductivity is negligible, the proposed models reduces to the previously proposed one based on a bundle of cylindrical capillaries. This model opens up a wide range of applications to monitor the water flow in fractured media.
Overset Grid Assembler and Flow Solver with Adaptive Spatial Load Balancing
Authors: Shibliyev Orxan , Sezai Ibrahim
Published: June 2021

An overset mesh approach is useful for unsteady flow problems which involve components moving relative to each other. Since the generation of a single mesh around all components is prone to mesh stretching due to the relative motion of bodies, using the overset grid methodology, an individual mesh can be generated for each component. In this study, a parallel overset grid assembler was developed to establish connectivity across component meshes. Connectivity information was transferred to the developed parallel flow solver. The assembler uses multiple methods such as alternating digital tree and stencil walking to reduce the time spent on domain connectivity. Both the assembler and solver were partitioned spatially so that overlapping mesh blocks reside in the same partitions. Spatial partitioning was performed using a 3D space partitioning structure, namely octree, to which mesh blocks are registered. The octree was refined adaptively until bins of octree could be evenly distributed to processors. The assembler and solver were tested on a generic helicopter configuration in terms of load balance, scalability, and memory usage.
Handgrip Strength Time Profile and Frailty: An Exploratory Study
Authors: Urbano Diana , Restivo Maria Teresa , Barbosa Manuel Romano , Fernandes Ângela , Abreu Paulo , Chousal Maria de Fátima , Coelho Tiago
Published: June 2021

This study aims to explore the use of force vs. time data obtained from an isometric handgrip test to match a frailty state based on the TFI score. BodyGrip, a novel prototype system, is used for handgrip strength over 10 s time interval tests. A cross-sectional study with a non-probabilistic sample of community-dwelling elderly women was conducted. The force/time data collected from the dominant handgrip strength test, together with the Tilburg Frailty Indicator (TFI) test results, were used to train artificial neural networks. Different models were tested, and the frailty matching of TFI scores reached a minimum accuracy of 75%. Despite the small sample size, the BodyGrip system appears to be a promising tool for exploring new frailty-related features. The adopted strategy foresees ultimately configuring the system to be used as an expedite mode for identifying individuals at risk, allowing an easy, quick, and frequent person-centered care approach. Additionally, it is suitable for following up of the elderly in particular, and it may assume a relevant role in the mitigation of the increase in frailty evolution during and after the imposed isolation of the COVID-19 pandemic. Further use of the system will improve the robustness of the artificial neural network algorithm.
Light Scattering and Absorption Complementarities to Neutron Scattering: In Situ FTIR and DLS Techniques at the High-Intensity and Extended Q-Range SANS Diffractometer KWS-2
Authors: Balacescu Livia , Brandl Georg , Kaneko Fumitoshi , Schrader Tobias Erich , Radulescu Aurel
Published: June 2021

Understanding soft and biological materials requires global knowledge of their microstructural features from elementary units at the nm scale up to larger complex aggregates in the micrometer range. Such a wide range of scale can be explored using the KWS-2 small-angle neutron (SANS) diffractometer. Additional information obtained by in situ complementary techniques sometimes supports the SANS analysis of systems undergoing structural modifications under external stimuli or which are stable only for short times. Observations at the local molecular level structure and conformation assists with an unambiguous interpretation of the SANS data using appropriate structural models, while monitoring of the sample condition during the SANS investigation ensures the sample stability and desired composition and chemical conditions. Thus, we equipped the KWS-2 with complementary light absorption and scattering capabilities: Fourier transform infrared (FTIR) spectroscopy can now be performed simultaneously with standard and time-resolved SANS, while in situ dynamic light scattering (DLS) became available for routine experiments, which enables the observation of either changes in the sample composition, due to sedimentation effects, or in size of morphologies, due to aggregation processes. The performance of each setup is demonstrated here using systems representative of those typically investigated on this beamline and benchmarked to studies performed offline.
A Learning-Based Methodology to Optimally Fit Short-Term Wind-Energy Bands
Authors: Risso Claudio , Guerberoff Gustavo
Published: June 2021

The increasing rate of penetration of non-conventional renewable energies is affecting the traditional assumption of controllability over energy sources. Power dispatch scheduling methods need to integrate the intrinsic randomness of some new sources, among which, wind energy is particularly difficult to treat. This work aims at the optimal construction of energy bands around wind energy forecasts. Complementarily, a remarkable fact of the proposed technique is that it can be extended to integrate multiple forecasts into a single one, whose band width is narrower at the same level of confidence. The work is based upon a real-world application case, developed for the Uruguayan Electricity Market, a world leader in the penetration of renewable energies.
Imperfect Wheat Grain Recognition Combined with an Attention Mechanism and Residual Network
Authors: Zhang Weiwei , Ma Huimin , Li Xiaohong , Liu Xiaoli , Jiao Jun , Zhang Pengfei , Gu Lichuan , Wang Qi , Bao Wenxia , Cao Shengnan
Published: June 2021

Intelligent detection of imperfect wheat grains based on machine vision is of great significance to correctly and rapidly evaluate wheat quality. There is little difference between the partial characteristics of imperfect and perfect wheat grains, which is a key factor limiting the classification and recognition accuracy of imperfect wheat based on a deep learning network model. In this paper, we propose a method for imperfect wheat grains recognition combined with an attention mechanism and residual network (ResNet), and verify its recognition accuracy by adding an attention mechanism module into different depths of residual network. Five residual networks with different depths (18, 34, 50, 101, and 152) were selected for the experiment, it was found that the recognition accuracy of each network model was improved with the attention mechanism, and the average recognition rate of ResNet-50 with the addition of the attention mechanism reached 96.5%. For ResNet-50 with the attention mechanism, the optimal learning rate was further screened as 0.0003. The average recognition accuracy reached 97.5%, among which the recognition rates of scab wheat grains, insect-damaged wheat grains, sprouted wheat grains, mildew wheat grains, broken wheat grains, and perfect wheat grains reached 97%, 99%, 99%, 95%, 96%, and 99% respectively. This work can provide guidance for the detection and recognition of imperfect wheat grains using machine vision.
Advances in Underground Energy Storage for Renewable Energy Sources
Authors: Menéndez Javier , Loredo Jorge
Published: June 2021

The use of fossil fuels (coal, fuel, and natural gas) to generate electricity has been reduced in the European Union during the last few years, involving a significant decrease in greenhouse gas emissions [...]
Learning the Parametric Transfer Function of Unitary Operations for Real-Time Evaluation of Manufacturing Processes Involving Operations Sequencing
Authors: Loreau Tanguy , Champaney Victor , Hascoët Nicolas , Mourgue Philippe , Duval Jean-Louis , Chinesta Francisco
Published: June 2021

For better designing manufacturing processes, surrogate models were widely considered in the past, where the effect of different material and process parameters was considered from the use of a parametric solution. The last contains the solution of the model describing the system under study, for any choice of the selected parameters. These surrogate models, also known as meta-models, virtual charts or computational vademecum, in the context of model order reduction, were successfully employed in a variety of industrial applications. However, they remain confronted to a major difficulty when the number of parameters grows exponentially. Thus, processes involving trajectories or sequencing entail a combinatorial exposition (curse of dimensionality) not only due to the number of possible combinations, but due to the number of parameters needed to describe the process. The present paper proposes a promising route for circumventing, or at least alleviating that difficulty. The proposed technique consists of a parametric transfer function that, as soon as it is learned, allows for, from a given state, inferring the new state after the application of a unitary operation, defined as a step in the sequenced process. Thus, any sequencing can be evaluated almost in real time by chaining that unitary transfer function, whose output becomes the input of the next operation. The benefits and potential of such a technique are illustrated on a problem of industrial relevance, the one concerning the induced deformation on a structural part when printing on it a series of stiffeners.
Industry 4.0 Maturity Model Assessing Environmental Attributes of Manufacturing Company
Authors: Zoubek Michal , Poor Peter , Broum Tomas , Basl Josef , Simon Michal
Published: June 2021

The primary purpose of this article is to present a maturity model dealing with environmental manufacturing processes in a company. According to some authors, Industry 4.0 is based on characteristics that have already been the focus of “lean and green” concepts. The goal of the article was to move from resource consumption, pollutant emissions, and more extensive manufacturing towards environmentally responsible manufacturing (ERM). Using environmental materials and methods reduces energy consumption, which generates cost savings and higher profits. Here, value stream mapping (VSM) was applied to identify core processes with environmental potential. This paper provides an understanding of the role of environmental manufacturing in the era of the Fourth Industrial Revolution.
Thermo-Viscoelastic Response of Protein-Based Hydrogels
Authors: Drozdov Aleksey D. , deClaville Christiansen Jesper
Published: June 2021

Because of the bioactivity and biocompatibility of protein-based gels and the reversible nature of bonds between associating coiled coils, these materials demonstrate a wide spectrum of potential applications in targeted drug delivery, tissue engineering, and regenerative medicine. The kinetics of rearrangement (association and dissociation) of the physical bonds between chains has been traditionally studied in shear relaxation tests and small-amplitude oscillatory tests. A characteristic feature of recombinant protein gels is that chains in the polymer network are connected by temporary bonds between the coiled coil complexes and permanent cross-links between functional groups of amino acids. A simple model is developed for the linear viscoelastic behavior of protein-based gels. Its advantage is that, on the one hand, the model only involves five material parameters with transparent physical meaning and, on the other, it correctly reproduces experimental data in shear relaxation and oscillatory tests. The model is applied to study the effects of temperature, the concentration of proteins, and their structure on the viscoelastic response of hydrogels.
Understanding Emotions: Origins and Roles of the Amygdala
Authors: Šimić Goran , Tkalčić Mladenka , Vukić Vana , Mulc Damir , Španić Ena , Šagud Marina , Olucha-Bordonau Francisco E. , Vukšić Mario , R. Hof Patrick
Published: June 2021

Emotions arise from activations of specialized neuronal populations in several parts of the cerebral cortex, notably the anterior cingulate, insula, ventromedial prefrontal, and subcortical structures, such as the amygdala, ventral striatum, putamen, caudate nucleus, and ventral tegmental area. Feelings are conscious, emotional experiences of these activations that contribute to neuronal networks mediating thoughts, language, and behavior, thus enhancing the ability to predict, learn, and reappraise stimuli and situations in the environment based on previous experiences. Contemporary theories of emotion converge around the key role of the amygdala as the central subcortical emotional brain structure that constantly evaluates and integrates a variety of sensory information from the surroundings and assigns them appropriate values of emotional dimensions, such as valence, intensity, and approachability. The amygdala participates in the regulation of autonomic and endocrine functions, decision-making and adaptations of instinctive and motivational behaviors to changes in the environment through implicit associative learning, changes in short- and long-term synaptic plasticity, and activation of the fight-or-flight response via efferent projections from its central nucleus to cortical and subcortical structures.
Cannabinoid Activity—Is There a Causal Connection to Spasmolysis in Clinical Studies?
Authors: Joseph Daniel , Schulze Johannes
Published: June 2021

Cannabinoid drugs are registered for postoperative nausea and emesis, Tourette syndrome and tumor-related anorexia, but are also used for spasticity and pain relief, among other conditions. Clinical studies for spasmolysis have been equivocal and even conclusions from meta-analyses were not consistent. This may be due to uncertainty in diagnostic criteria as well as a lack of direct spasmolytic activity (direct causality). In this review we used the Hill criteria to investigate whether a temporal association is causal or spurious. Methods: A systematic literature search was performed to identify all clinical trials of cannabinoids for spasticity. Studies were evaluated for dose dependency and time association; all studies together were analyzed for reproducibility, coherence, analogy and mechanistic consistency. A Funnel plot was done for all studies to identify selection or publication bias. Results: Twenty-seven studies were included in this meta-analysis. The spasmolytic activity (effect strength) was weak, with a nonsignificant small effect in most studies and a large effect only in a few studies (“enriched” studies, low patient numbers). No dose dependency was seen and plotting effect size vs. daily dose resulted in a slope of 0.004. Most studies titrated the cannabinoid to the optimum dose, e.g., 20 mg/d THC. The effect decreased with longer treatment duration (3–4 months). The spasmolytic effect is consistent for different European countries but not always within a country, nor is the effect specific for an etiology (multiple sclerosis, spinal cord injury, others). For other criteria like plausibility, coherence or analogous effects, no data exist to support or refute them. In most studies, adverse effects were frequently reported indicating a therapeutic effect only at high doses with relevant side effects. Conclusions: Current data do not support a specific spasmolytic effect; a general decrease in CNS activity analogous to benzodiazepines appears more likely. Whether individual patients or specific subgroups benefit from cannabinoids is unclear. Further studies should compare cannabinoids with other, nonspecific spasmolytic drugs like benzodiazepines.
Targeting the Proteasome in Advanced Renal Cell Carcinoma: Complexity and Limitations of Patient-Individualized Preclinical Drug Discovery
Authors: Li Jielin , Pohl Laura , Schüler Julia , Korzeniewski Nina , Reimold Philipp , Kaczorowski Adam , Hou Weibin , Zschäbitz Stefanie , Nientiedt Cathleen , Jäger Dirk , Hohenfellner Markus , Duensing Anette , Duensing Stefan
Published: June 2021

Background: Systemic treatment options for metastatic renal cell carcinoma (RCC) have significantly expanded in recent years. However, patients refractory to tyrosine kinase and immune checkpoint inhibitors still have limited treatment options and patient-individualized approaches are largely missing. Patients and Methods: In vitro drug screening of tumor-derived short-term cultures obtained from seven patients with clear cell RCC was performed. For one patient, a patient-derived xenograft (PDX) mouse model was established for in vivo validation experiments. Drug effects were further investigated in established RCC cell lines. Results: The proteasome inhibitor carfilzomib was among the top hits identified in three of four patients in which an in vitro drug screening could be performed successfully. Carfilzomib also showed significant acute and long-term cytotoxicity in established RCC cell lines. The in vivo antitumoral activity of carfilzomib was confirmed in a same-patient PDX model. The cytotoxicity of carfilzomib was found to correlate with the level of accumulation of ubiquitinated proteins. Conclusions: In this proof-of-concept study, we show that patient-individualized in vitro drug screening and preclinical validation is feasible. However, the fact that carfilzomib failed to deliver a clinical benefit in RCC patients in a recent phase II trial unrelated to the present study underscores the complexities and limitations of this strategy.
MyD88 Is Not Required for Muscle Injury-Induced Endochondral Heterotopic Ossification in a Mouse Model of Fibrodysplasia Ossificans Progressiva
Authors: Lyu Huili , Elkins Cody M. , Pierce Jessica L. , Serezani C. Henrique , Perrien Daniel S.
Published: June 2021

Excess inflammation and canonical BMP receptor (BMPR) signaling are coinciding hallmarks of the early stages of injury-induced endochondral heterotopic ossification (EHO), especially in the rare genetic disease fibrodysplasia ossificans progressiva (FOP). Multiple inflammatory signaling pathways can synergistically enhance BMP-induced Smad1/5/8 activity in multiple cell types, suggesting the importance of pathway crosstalk in EHO and FOP. Toll-like receptors (TLRs) and IL-1 receptors mediate many of the earliest injury-induced inflammatory signals largely via MyD88-dependent pathways. Thus, the hypothesis that MyD88-dependent signaling is required for EHO was tested in vitro and in vivo using global or Pdgfrα-conditional deletion of MyD88 in FOP mice. As expected, IL-1β or LPS synergistically increased Activin A (ActA)-induced phosphorylation of Smad 1/5 in fibroadipoprogenitors (FAPs) expressing Alk2R206H. However, conditional deletion of MyD88 in Pdgfrα-positive cells of FOP mice did not significantly alter the amount of muscle injury-induced EHO. Even more surprisingly, injury-induced EHO was not significantly affected by global deletion of MyD88. These studies demonstrate that MyD88-dependent signaling is dispensable for injury-induced EHO in FOP mice.
EvoSeg: Automated Electron Microscopy Segmentation through Random Forests and Evolutionary Optimization
Authors: Zumbado-Corrales Manuel , Esquivel-Rodríguez Juan
Published: June 2021

Electron Microscopy Maps are key in the study of bio-molecular structures, ranging from borderline atomic level to the sub-cellular range. These maps describe the envelopes that cover possibly a very large number of proteins that form molecular machines within the cell. Within those envelopes, we are interested to find what regions correspond to specific proteins so that we can understand how they function, and design drugs that can enhance or suppress a process that they are involved in, along with other experimental purposes. A classic approach by which we can begin the exploration of map regions is to apply a segmentation algorithm. This yields a mask where each voxel in 3D space is assigned an identifier that maps it to a segment; an ideal segmentation would map each segment to one protein unit, which is rarely the case. In this work, we present a method that uses bio-inspired optimization, through an Evolutionary-Optimized Segmentation algorithm, to iteratively improve upon baseline segments obtained from a classical approach, called watershed segmentation. The cost function used by the evolutionary optimization is based on an ideal segmentation classifier trained as part of this development, which uses basic structural information available to scientists, such as the number of expected units, volume and topology. We show that a basic initial segmentation with the additional information allows our evolutionary method to find better segmentation results, compared to the baseline generated by the watershed.
The Differential Effects of the Amount of Training on Sensitivity of Distinct Actions to Reward Devaluation
Authors: Bar Or Maya , Klavir Oded
Published: June 2021

Shifting between goal-directed and habitual behaviors is essential for daily functioning. An inability to do so is associated with various clinical conditions, such as obsessive–compulsive disorder (OCD). Here we developed a new behavioral model in mice allowing us to produce and examine the development of different behaviors under goal-directed or habitual control. By using overtraining of instrumental associations between two levers and two rewards, and later devaluating one of the rewards, we differentiate and explore the motivational control of behaviors within the task which consequentially promotes what seems like excessive irrational behavior. Using our model, we found that the ability of instrumental behavior, to adapt to a change in the value of a known reward, is a function of practice. Once an instrumental action was practiced extensively it becomes habitual and, thus, under S–R control and could not be amended, not even when resulting in a noxious outcome. However, direct consummatory or Pavlovian actions, such as licking or checking, responds immediately to the change in value. This imbalance could render an instrumental behavior excessive and unresponsive to changes in outcome while the direct change in consumption implies that the change was in fact registered. This could suggest a system that, when out of balance, can create excessive behaviors, not adapting to an acknowledged change.
Statistical and Machine Learning Link Selection Methods for Brain Functional Networks: Review and Comparison
Authors: Ivanoska Ilinka , Trivodaliev Kire , Kalajdziski Slobodan , Zanin Massimiliano
Published: June 2021

Network-based representations have introduced a revolution in neuroscience, expanding the understanding of the brain from the activity of individual regions to the interactions between them. This augmented network view comes at the cost of high dimensionality, which hinders both our capacity of deciphering the main mechanisms behind pathologies, and the significance of any statistical and/or machine learning task used in processing this data. A link selection method, allowing to remove irrelevant connections in a given scenario, is an obvious solution that provides improved utilization of these network representations. In this contribution we review a large set of statistical and machine learning link selection methods and evaluate them on real brain functional networks. Results indicate that most methods perform in a qualitatively similar way, with NBS (Network Based Statistics) winning in terms of quantity of retained information, AnovaNet in terms of stability and ExT (Extra Trees) in terms of lower computational cost. While machine learning methods are conceptually more complex than statistical ones, they do not yield a clear advantage. At the same time, the high heterogeneity in the set of links retained by each method suggests that they are offering complementary views to the data. The implications of these results in neuroscience tasks are finally discussed.
Non-Invasive Biomarkers for Earlier Detection of Pancreatic Cancer—A Comprehensive Review
Authors: Brezgyte Greta , Shah Vinay , Jach Daria , Crnogorac-Jurcevic Tatjana
Published: June 2021

Pancreatic ductal adenocarcinoma (PDAC) carries a deadly diagnosis, due in large part to delayed presentation when the disease is already at an advanced stage. CA19-9 is currently the most commonly utilized biomarker for PDAC; however, it lacks the necessary accuracy to detect precursor lesions or stage I PDAC. Novel biomarkers that could detect this malignancy with improved sensitivity (SN) and specificity (SP) would likely result in more curative resections and more effective therapeutic interventions, changing thus the present dismal survival figures. The aim of this study was to systematically and comprehensively review the scientific literature on non-invasive biomarkers in biofluids such as blood, urine and saliva that were attempting earlier PDAC detection. The search performed covered a period of 10 years (January 2010—August 2020). Data were extracted using keywords search in the three databases: MEDLINE, Web of Science and Embase. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool was applied for study selection based on establishing the risk of bias and applicability concerns in Patient Selection, Index test (biomarker assay) and Reference Standard (standard-of-care diagnostic test). Out of initially over 4000 published reports, 49 relevant studies were selected and reviewed in more detail. In addition, we discuss the present challenges and complexities in the path of translating the discovered biomarkers into the clinical setting. Our systematic review highlighted several promising biomarkers that could, either alone or in combination with CA19-9, potentially improve earlier detection of PDAC. Overall, reviewed biomarker studies should aim to improve methodological and reporting quality, and novel candidate biomarkers should be investigated further in order to demonstrate their clinical usefulness. However, challenges and complexities in the path of translating the discovered biomarkers from the research laboratory to the clinical setting remain and would have to be addressed before a more realistic breakthrough in earlier detection of PDAC is achieved.
A Collaborative Model to Implement Flexible, Accessible and Efficient Oncogenetic Services for Hereditary Breast and Ovarian Cancer: The C-MOnGene Study
Authors: Lapointe Julie , Dorval Michel , Chiquette Jocelyne , Joly Yann , Guertin Jason Robert , Laberge Maude , Gekas Jean , Hébert Johanne , Pomey Marie-Pascale , Cruz-Marino Tania , Touhami Omar , Blanchet Saint-Pierre Arnaud , Gagnon Sylvain , Bouchard Karine , Rhéaume Josée , Boisvert Karine , Brousseau Claire , Castonguay Lysanne , Fortier Sylvain , Gosselin Isabelle , Lachapelle Philippe , Lavoie Sabrina , Poirier Brigitte , Renaud Marie-Claude , Ruizmangas Maria-Gabriela , Sebastianelli Alexandra , Roy Stéphane , Côté Madeleine , Racine Marie-Michelle , Roy Marie-Claude , Côté Nathalie , Brisson Carmen , Charette Nelson , Faucher Valérie , Leblanc Josianne , Dubeau Marie-Ève , Plante Marie , Desbiens Christine , Beaumont Martin , Simard Jacques , Nabi Hermann
Published: June 2021

Medical genetic services are facing an unprecedented demand for counseling and testing for hereditary breast and ovarian cancer (HBOC) in a context of limited resources. To help resolve this issue, a collaborative oncogenetic model was recently developed and implemented at the CHU de Québec-Université Laval; Quebec; Canada. Here, we present the protocol of the C-MOnGene (Collaborative Model in OncoGenetics) study, funded to examine the context in which the model was implemented and document the lessons that can be learned to optimize the delivery of oncogenetic services. Within three years of implementation, the model allowed researchers to double the annual number of patients seen in genetic counseling. The average number of days between genetic counseling and disclosure of test results significantly decreased. Group counseling sessions improved participants’ understanding of breast cancer risk and increased knowledge of breast cancer and genetics and a large majority of them reported to be overwhelmingly satisfied with the process. These quality and performance indicators suggest this oncogenetic model offers a flexible, patient-centered and efficient genetic counseling and testing for HBOC. By identifying the critical facilitating factors and barriers, our study will provide an evidence base for organizations interested in transitioning to an oncogenetic model integrated into oncology care; including teams that are not specialized but are trained in genetics.
Tissue-Specific Warburg Effect in Breast Cancer and Cancer-Associated Adipose Tissue—Relationship between AMPK and Glycolysis
Authors: Kalezic Andjelika , Udicki Mirjana , Srdic Galic Biljana , Aleksic Marija , Korac Aleksandra , Jankovic Aleksandra , Korac Bato
Published: June 2021

Typical features of the breast malignant phenotype rely on metabolic reprogramming of cancer cells and their interaction with surrounding adipocytes. Obesity is strongly associated with breast cancer mortality, yet the effects of obesity on metabolic reprogramming of cancer and cancer-associated adipose tissue remain largely unknown. Paired biopsies of breast tumor tissue and adipose tissue from premenopausal women were divided according to pathohistological analyses and body mass index on normal-weight and overweight/obese with benign or malignant tumors. We investigated the protein expression of key regulatory enzymes of glycolysis, pentose phosphate pathway (PPP), and glycogen synthesis. Breast cancer tissue showed a simultaneous increase in 5′-AMP-activated protein kinase (AMPK) protein expression with typical features of the Warburg effect, including hexokinase 2 (HK 2) overexpression and its association with mitochondrial voltage-dependent anion-selective channel protein 1, associated with an overexpression of rate-limiting enzymes of glycolysis (phosphofructokinase 1—PFK-1) and pentose phosphate pathway (glucose-6-phosphate dehydrogenase—G6PDH). In parallel, cancer-associated adipose tissue showed increased AMPK protein expression with overexpression of HK 2 and G6PDH in line with increased PPP activity. Moreover, important obesity-associated differences in glucose metabolism were observed in breast cancer tissue showing prominent glycogen deposition and higher glycogen synthase kinase-3 protein expression in normal-weight women and higher PFK-1 and glyceraldehyde 3-phosphate dehydrogenase (GAPDH) protein expression in overweight/obese women. In conclusion, metabolic reprogramming of glycolysis contributes to tissue-specific Warburg effect in breast cancer and cancer-associated adipose tissue.
Is Emodin with Anticancer Effects Completely Innocent? Two Sides of the Coin
Authors: Akkol Esra Küpeli , Tatlı Iffet Irem , Karatoprak Gökçe Şeker , Ağar Osman Tuncay , Yücel Çiğdem , Sobarzo-Sánchez Eduardo , Capasso Raffaele
Published: June 2021

Many anticancer active compounds are known to have the capacity to destroy pathologically proliferating cancer cells in the body, as well as to destroy rapidly proliferating normal cells. Despite remarkable advances in cancer research over the past few decades, the inclusion of natural compounds in researches as potential drug candidates is becoming increasingly important. However, the perception that the natural is reliable is an issue that needs to be clarified. Among the various chemical classes of natural products, anthraquinones have many biological activities and have also been proven to exhibit a unique anticancer activity. Emodin, an anthraquinone derivative, is a natural compound found in the roots and rhizomes of many plants. The anticancer property of emodin, a broad-spectrum inhibitory agent of cancer cells, has been detailed in many biological pathways. In cancer cells, these molecular mechanisms consist of suppressing cell growth and proliferation through the attenuation of oncogenic growth signaling, such as protein kinase B (AKT), mitogen-activated protein kinase (MAPK), HER-2 tyrosine kinase, Wnt/-catenin, and phosphatidylinositol 3-kinase (PI3K). However, it is known that emodin, which shows toxicity to cancer cells, may cause kidney toxicity, hepatotoxicity, and reproductive toxicity especially at high doses and long-term use. At the same time, studies of emodin, which has poor oral bioavailability, to transform this disadvantage into an advantage with nano-carrier systems reveal that natural compounds are not always directly usable compounds. Consequently, this review aimed to shed light on the anti-proliferative and anti-carcinogenic properties of emodin, as well as its potential toxicities and the advantages of drug delivery systems on bioavailability.
Exercise Inhibits Doxorubicin-Induced Damage to Cardiac Vessels and Activation of Hippo/YAP-Mediated Apoptosis
Authors: Tao Rong-Hua , Kobayashi Masato , Yang Yuanzheng , Kleinerman Eugenie S.
Published: June 2021

Dose-related cardiomyopathy is a major side effect following doxorubicin (Dox). To investigate whether exercise (Ex)-induced vasculogenesis plays a role in reducing Dox-induced cardiotoxicity, GFP+ bone marrow (BM) cells from GFP transgenic mice were transplanted into wild-type mice. Transplanted mice were treated with Dox, Ex, Dox+Ex, or control. We found Dox therapy resulted in decreased systolic and diastolic blood flow, decreased ejection fraction and fractional shortening, and decreased vascular endothelial cells and pericytes. These abnormalities were not seen in Dox+Ex hearts. Heart tissues from control-, Ex-, or Dox-treated mice showed a small number of GFP+ cells. By contrast, the Dox+Ex-treated hearts had a significant increase in GFP+ cells. Further analyses demonstrated these GFP+ BM cells had differentiated into vascular endothelial cells (GFP+CD31+) and pericytes (GFP+NG2+). Decreased cardiomyocytes were also seen in Dox-treated but not Dox+Ex-treated hearts. Ex induced an increase in GFP+c-Kit+ cells. However, these c-Kit+ BM stem cells had not differentiated into cardiomyocytes. Dox therapy induced phosphorylation of MST1/2, LATS1, and YAP; a decrease in total YAP; and cleavage of caspase-3 and PARP in the heart tissues. Dox+Ex prevented these effects. Our data demonstrated Dox-induced cardiotoxicity is mediated by vascular damage resulting in decreased cardiac blood flow and through activation of Hippo-YAP signaling resulting in cardiomyocyte apoptosis. Furthermore, Ex inhibited these effects by promoting migration of BM stem cells into the heart to repair the cardiac vessels damaged by Dox and through inhibiting Dox-induced Hippo-YAP signaling-mediated apoptosis. These data support the concept of using exercise as an intervention to decrease Dox-induced cardiotoxicity.
Thyroid Hormone Enhances Angiogenesis and the Warburg Effect in Squamous Cell Carcinomas
Authors: Miro Caterina , Nappi Annarita , Cicatiello Annunziata Gaetana , Di Cicco Emery , Sagliocchi Serena , Murolo Melania , Belli Valentina , Troiani Teresa , Albanese Sandra , Amiranda Sara , Zavacki Ann Marie , Stornaiuolo Mariano , Mancini Marcello , Salvatore Domenico , Dentice Monica
Published: June 2021

Cancer angiogenesis is required to support energetic demand and metabolic stress, particularly during conditions of hypoxia. Coupled to neo-vasculogenesis, cancer cells rewire metabolic programs to sustain growth, survival and long-term maintenance. Thyroid hormone (TH) signaling regulates growth and differentiation in a variety of cell types and tissues, thus modulating hyper proliferative processes such as cancer. Herein, we report that TH coordinates a global program of metabolic reprogramming and induces angiogenesis through up-regulation of the VEGF-A gene, which results in the enhanced proliferation of tumor endothelial cells. In vivo conditional depletion of the TH activating enzyme in a mouse model of cutaneous squamous cell carcinoma (SCC) reduces the concentration of TH in the tumoral cells and results in impaired VEGF-A production and attenuated angiogenesis. In addition, we found that TH induces the expression of the glycolytic genes and fosters lactate production, which are key traits of the Warburg effect. Taken together, our results reveal a TH–VEGF-A–HIF1α regulatory axis leading to enhanced angiogenesis and glycolytic flux, which may represent a target for SCC therapy.
Circular RNAs: Emerging Regulators of the Major Signaling Pathways Involved in Cancer Progression
Authors: Papatsirou Maria , Artemaki Pinelopi I. , Karousi Paraskevi , Scorilas Andreas , Kontos Christos K.
Published: June 2021

Signal transduction is an essential process that regulates and coordinates fundamental cellular processes, such as development, immunity, energy metabolism, and apoptosis. Through signaling, cells are capable of perceiving their environment and adjusting to changes, and most signaling cascades ultimately lead to alterations in gene expression. Circular RNAs (circRNAs) constitute an emerging type of endogenous transcripts with regulatory roles and unique properties. They are stable and expressed in a tissue-, cell-, and developmental stage-specific manner, while they are involved in the pathogenesis of several diseases, including cancer. Aberrantly expressed circRNAs can mediate cancer progression through regulation of the activity of major signaling cascades, such as the VEGF, WNT/β-catenin, MAPK, PI3K/AKT, and Notch signaling pathways, as well as by interfering with signaling crosstalk. Deregulated signaling can then function to induce angiogenesis, promote invasion, migration, and metastasis, and, generally, modulate the hallmarks of cancer. In this review article, we summarize the most recently described and intriguing cases of circRNA-mediated signaling regulation that are involved in cancer progression, and discuss the biomarker potential of circRNAs, as well as future therapeutic applications.