bluuebunny/crossref_metadata_2025 huggingface dataset:
Aberrant Mitochondrial Morphology and Function in the BTBR Mouse Model of Autism Is Improved by Two Weeks of Ketogenic Diet
Authors: Ahn Younghee , Sabouny Rasha , Villa Bianca R. , Yee Nellie C. , Mychasiuk Richelle , Uddin Golam M. , Rho Jong M. , Shutt Timothy E.
Published: May 2020

Autism spectrum disorder (ASD) is a highly prevalent neurodevelopmental disorder that exhibits a common set of behavioral and cognitive impairments. Although the etiology of ASD remains unclear, mitochondrial dysfunction has recently emerged as a possible causative factor underlying ASD. The ketogenic diet (KD) is a high-fat, low-carbohydrate diet that augments mitochondrial function, and has been shown to reduce autistic behaviors in both humans and in rodent models of ASD. The aim of the current study was to examine mitochondrial bioenergetics in the BTBR mouse model of ASD and to determine whether the KD improves mitochondrial function. We also investigated changes in mitochondrial morphology, which can directly influence mitochondrial function. We found that BTBR mice had altered mitochondrial function and exhibited smaller more fragmented mitochondria compared to C57BL/6J controls, and that supplementation with the KD improved both mitochondrial function and morphology. We also identified activating phosphorylation of two fission proteins, pDRP1S616 and pMFFS146, in BTBR mice, consistent with the increased mitochondrial fragmentation that we observed. Intriguingly, we found that the KD decreased pDRP1S616 levels in BTBR mice, likely contributing to the restoration of mitochondrial morphology. Overall, these data suggest that impaired mitochondrial bioenergetics and mitochondrial fragmentation may contribute to the etiology of ASD and that these alterations can be reversed with KD treatment.
CRISPR/Cas9 Editing for Gaucher Disease Modelling
Authors: Pavan Eleonora , Ormazabal Maximiliano , Peruzzo Paolo , Vaena Emilio , Rozenfeld Paula , Dardis Andrea
Published: May 2020

Gaucher disease (GD) is an autosomal recessive lysosomal storage disorder caused by mutations in the acid β-glucosidase gene (GBA1). Besides causing GD, GBA1 mutations constitute the main genetic risk factor for developing Parkinson’s disease. The molecular basis of neurological manifestations in GD remain elusive. However, neuroinflammation has been proposed as a key player in this process. We exploited CRISPR/Cas9 technology to edit GBA1 in the human monocytic THP-1 cell line to develop an isogenic GD model of monocytes and in glioblastoma U87 cell lines to generate an isogenic GD model of glial cells. Both edited (GBA1 mutant) cell lines presented low levels of mutant acid β-glucosidase expression, less than 1% of residual activity and massive accumulation of substrate. Moreover, U87 GBA1 mutant cells showed that the mutant enzyme was retained in the ER and subjected to proteasomal degradation, triggering unfolded protein response (UPR). U87 GBA1 mutant cells displayed an increased production of interleukin-1β, both with and without inflammosome activation, α-syn accumulation and a higher rate of cell death in comparison with wild-type cells. In conclusion, we developed reliable, isogenic, and easy-to-handle cellular models of GD obtained from commercially accessible cells to be employed in GD pathophysiology studies and high-throughput drug screenings.
An Ultra-Sensitive Electrochemical Sensor for the Detection of Carcinogen Oxidative Stress 4-Nitroquinoline N-Oxide in Biologic Matrices Based on Hierarchical Spinel Structured NiCo2O4 and NiCo2S4; A Comparative Study
Authors: Chen Tse-Wei , Tamilalagan Elayappan , Chen Shen-Ming , Akilarasan Muthumariappan , Maheshwaran Selvarasu , Liu Xiaoheng
Published: May 2020

Various factors leads to cancer; among them oxidative damage is believed to play an important role. Moreover, it is important to identify a method to detect the oxidative damage. Recently, electrochemical sensors have been considered as the one of the most important techniques to detect DNA damage, owing to its rapid detection. However, electrode materials play an important role in the properties of electrochemical sensor. Currently, researchers have aimed to develop novel electrode materials for low-level detection of biomarkers. Herein, we report the facile hydrothermal synthesis of NiCo2O4 micro flowers (MFs) and NiCo2S4 micro spheres (Ms) and evaluate their electrochemical properties for the detection of carcinogen-causing biomarker 4-nitroquinoline n-oxide (4-NQO) in human blood serum and saliva samples. Moreover, as-prepared composites were fabricated on a glass carbon electrode (GCE), and its electrochemical activities for the determination of 4-NQO were investigated by using various electrochemical techniques. Fascinatingly, the NiCo2S4-Ms showed a very low detection limit of 2.29 nM and a wider range of 0.005 to 596.64 µM for detecting 4-NQO. Finally, the practical applicability of NiCo2S4-Ms in the 4-NQO spiked human blood serum and saliva samples were also investigated.
MicroRNA Profiling Reveals an Abundant miR-200a-3p Promotes Skeletal Muscle Satellite Cell Development by Targeting TGF-β2 and Regulating the TGF-β2/SMAD Signaling Pathway
Authors: Yin Huadong , He Haorong , Shen Xiaoxu , Tang Shuyue , Zhao Jing , Cao Xinao , Han Shunshun , Cui Can , Chen Yuqi , Wei Yuanhang , Wang Yan , Li Diyan , Zhu Qing
Published: May 2020

MicroRNAs (miRNAs) are evolutionarily conserved, small noncoding RNAs that play critical post-transcriptional regulatory roles in skeletal muscle development. Chicken is an optimal model to study skeletal muscle formation because its developmental anatomy is similar to that of mammals. In this study, we identified potential miRNAs in the breast muscle of broilers and layers at embryonic day 10 (E10), E13, E16, and E19. We detected 1836 miRNAs, 233 of which were differentially expressed between broilers and layers. In particular, miRNA-200a-3p was significantly more highly expressed in broilers than layers at three time points. In vitro experiments showed that miR-200a-3p accelerated differentiation and proliferation of chicken skeletal muscle satellite cells (SMSCs) and inhibited SMSCs apoptosis. The transforming growth factor 2 (TGF-β2) was identified as a target gene of miR-200a-3p, and which turned out to inhibit differentiation and proliferation, and promote apoptosis of SMSCs. Exogenous TGF-β2 increased the abundances of phosphorylated SMAD2 and SMAD3 proteins, and a miR-200a-3p mimic weakened this effect. The TGF-β2 inhibitor treatment reduced the promotional and inhibitory effects of miR-200a-3p on SMSC differentiation and apoptosis, respectively. Our results indicate that miRNAs are abundantly expressed during embryonic skeletal muscle development, and that miR-200a-3p promotes SMSC development by targeting TGF-β2 and regulating the TGF-β2/SMAD signaling pathway.
Comparative Transcriptome Analysis Combining SMRT- and Illumina-Based RNA-Seq Identifies Potential Candidate Genes Involved in Betalain Biosynthesis in Pitaya Fruit
Authors: Wu Yawei , Xu Juan , Han Xiumei , Qiao Guang , Yang Kun , Wen Zhuang , Wen Xiaopeng
Published: May 2020

To gain more valuable genomic information about betalain biosynthesis, the full-length transcriptome of pitaya pulp from ‘Zihonglong’ (red pulp) and ‘Jinghonglong’ (white pulp) in four fruit developmental stages was analyzed using Single-Molecule Real-Time (SMRT) sequencing corrected by Illumina RNA-sequence (Illumina RNA-Seq). A total of 65,317 and 91,638 genes were identified in ‘Zihonglong’ and ‘Jinghonglong’, respectively. A total of 11,377 and 15,551 genes with more than two isoforms were investigated from ‘Zihonglong’ and ‘Jinghonglong’, respectively. In total, 156,955 genes were acquired after elimination of redundancy, of which, 120,604 genes (79.63%) were annotated, and 30,875 (20.37%) sequences without hits to reference database were probably novel genes in pitaya. A total of 31,169 and 53,024 simple sequence repeats (SSRs) were uncovered from the genes of ‘Zihonglong’ and ‘Jinghonglong’, and 11,650 long non-coding RNAs (lncRNAs) in ‘Zihonglong’ and 11,113 lncRNAs in ‘Jinghonglong’ were obtained herein. qRT-PCR was conducted on ten candidate genes, the expression level of six novel genes were consistent with the Fragments Per Kilobase of transcript per Million mapped reads (FPKM) values. In conclusion, we firstly undertook SMRT sequencing of the full-length transcriptome of pitaya, and the valuable resource that was acquired through this sequencing facilitated the identification of additional betalain-related genes. Notably, a list of novel putative genes related to the synthesis of betalain in pitaya fruits was assembled. This may provide new insights into betalain synthesis in pitaya.
Roles of Autophagy in Oxidative Stress
Authors: Yun Hyeong Rok , Jo Yong Hwa , Kim Jieun , Shin Yoonhwa , Kim Sung Soo , Choi Tae Gyu
Published: May 2020

Autophagy is a catabolic process for unnecessary or dysfunctional cytoplasmic contents by lysosomal degradation pathways. Autophagy is implicated in various biological processes such as programmed cell death, stress responses, elimination of damaged organelles and development. The role of autophagy as a crucial mediator has been clarified and expanded in the pathological response to redox signalling. Autophagy is a major sensor of the redox signalling. Reactive oxygen species (ROS) are highly reactive molecules that are generated as by-products of cellular metabolism, principally by mitochondria. Mitochondrial ROS (mROS) are beneficial or detrimental to cells depending on their concentration and location. mROS function as redox messengers in intracellular signalling at physiologically low level, whereas excessive production of mROS causes oxidative damage to cellular constituents and thus incurs cell death. Hence, the balance of autophagy-related stress adaptation and cell death is important to comprehend redox signalling-related pathogenesis. In this review, we attempt to provide an overview the basic mechanism and function of autophagy in the context of response to oxidative stress and redox signalling in pathology.
Oxidative Stress and Immune System Dysfunction in Autism Spectrum Disorders
Authors: Pangrazzi Luca , Balasco Luigi , Bozzi Yuri
Published: May 2020

Autism Spectrum Disorders (ASDs) represent a group of neurodevelopmental disorders associated with social and behavioral impairments. Although dysfunctions in several signaling pathways have been associated with ASDs, very few molecules have been identified as potentially effective drug targets in the clinic. Classically, research in the ASD field has focused on the characterization of pathways involved in neural development and synaptic plasticity, which support the pathogenesis of this group of diseases. More recently, immune system dysfunctions have been observed in ASD. In addition, high levels of reactive oxygen species (ROS), which cause oxidative stress, are present in ASD patients. In this review, we will describe the major alterations in the expression of genes coding for enzymes involved in the ROS scavenging system, in both ASD patients and ASD mouse models. In addition, we will discuss, in the context of the most recent literature, the possibility that oxidative stress, inflammation and immune system dysfunction may be connected to, and altogether support, the pathogenesis and/or severity of ASD. Finally, we will discuss the possibility of novel treatments aimed at counteracting the interplay between ROS and inflammation in people with ASD.
The 15q11.2 BP1-BP2 Microdeletion (Burnside–Butler) Syndrome: In Silico Analyses of the Four Coding Genes Reveal Functional Associations with Neurodevelopmental Disorders
Authors: Rafi Syed K. , Butler Merlin G.
Published: May 2020

The 15q11.2 BP1-BP2 microdeletion (Burnside–Butler) syndrome is emerging as the most frequent pathogenic copy number variation (CNV) in humans associated with neurodevelopmental disorders with changes in brain morphology, behavior, and cognition. In this study, we explored functions and interactions of the four protein-coding genes in this region, namely NIPA1, NIPA2, CYFIP1, and TUBGCP5, and elucidate their role, in solo and in concert, in the causation of neurodevelopmental disorders. First, we investigated the STRING protein-protein interactions encompassing all four genes and ascertained their predicted Gene Ontology (GO) functions, such as biological processes involved in their interactions, pathways and molecular functions. These include magnesium ion transport molecular function, regulation of axonogenesis and axon extension, regulation and production of bone morphogenetic protein and regulation of cellular growth and development. We gathered a list of significantly associated cardinal maladies for each gene from searchable genomic disease websites, namely MalaCards.org: HGMD, OMIM, ClinVar, GTR, Orphanet, DISEASES, Novoseek, and GeneCards.org. Through tabulations of such disease data, we ascertained the cardinal disease association of each gene, as well as their expanded putative disease associations. This enabled further tabulation of disease data to ascertain the role of each gene in the top ten overlapping significant neurodevelopmental disorders among the disease association data sets: (1) Prader–Willi Syndrome (PWS); (2) Angelman Syndrome (AS); (3) 15q11.2 Deletion Syndrome with Attention Deficit Hyperactive Disorder & Learning Disability; (4) Autism Spectrum Disorder (ASD); (5) Schizophrenia; (6) Epilepsy; (7) Down Syndrome; (8) Microcephaly; (9) Developmental Disorder, and (10) Peripheral Nervous System Disease. The cardinal disease associations for each of the four contiguous 15q11.2 BP1-BP2 genes are NIPA1- Spastic Paraplegia 6; NIPA2—Angelman Syndrome and Prader–Willi Syndrome; CYFIP1—Fragile X Syndrome and Autism; TUBGCP5—Prader–Willi Syndrome. The four genes are individually associated with PWS, ASD, schizophrenia, epilepsy, and Down syndrome. Except for TUBGCP5, the other three genes are associated with AS. Unlike the other genes, TUBGCP5 is also not associated with attention deficit hyperactivity disorder and learning disability, developmental disorder, or peripheral nervous system disease. CYFIP1 was the only gene not associated with microcephaly but was the only gene associated with developmental disorders. Collectively, all four genes were associated with up to three-fourths of the ten overlapping neurodevelopmental disorders and are deleted in this most prevalent known pathogenic copy number variation now recognized among humans with these clinical findings.
Electrospun Nano-Fibers for Biomedical and Tissue Engineering Applications: A Comprehensive Review
Authors: Parham Shokoh , Kharazi Anousheh Zargar , Bakhsheshi-Rad Hamid Reza , Ghayour Hamid , Ismail Ahmad Fauzi , Nur Hadi , Berto Filippo
Published: May 2020

Pharmaceutical nano-fibers have attracted widespread attention from researchers for reasons such as adaptability of the electro-spinning process and ease of production. As a flexible method for fabricating nano-fibers, electro-spinning is extensively used. An electro-spinning unit is composed of a pump or syringe, a high voltage current supplier, a metal plate collector and a spinneret. Optimization of the attained nano-fibers is undertaken through manipulation of the variables of the process and formulation, including concentration, viscosity, molecular mass, and physical phenomenon, as well as the environmental parameters including temperature and humidity. The nano-fibers achieved by electro-spinning can be utilized for drug loading. The mixing of two or more medicines can be performed via electro-spinning. Facilitation or inhibition of the burst release of a drug can be achieved by the use of the electro-spinning approach. This potential is anticipated to facilitate progression in applications of drug release modification and tissue engineering (TE). The present review aims to focus on electro-spinning, optimization parameters, pharmacological applications, biological characteristics, and in vivo analyses of the electro-spun nano-fibers. Furthermore, current developments and upcoming investigation directions are outlined for the advancement of electro-spun nano-fibers for TE. Moreover, the possible applications, complications and future developments of these nano-fibers are summarized in detail.
Justification of the Lugiato-Lefever Model from a Damped Driven ϕ4 Equation
Authors: Akbar Fiki Taufik , Gunara Bobby Eka , Susanto Hadi
Published: May 2020

The Lugiato-Lefever equation is a damped and driven version of the well-known nonlinear Schrödinger equation. It is a mathematical model describing complex phenomena in dissipative and nonlinear optical cavities. Within the last two decades, the equation has gained much attention as it has become the basic model describing microresonator (Kerr) frequency combs. Recent works derive the Lugiato-Lefever equation from a class of damped driven ϕ 4 equations closed to resonance. In this paper, we provide a justification of the envelope approximation. From the analysis point of view, the result is novel and non-trivial as the drive yields a perturbation term that is not square integrable. The main approach proposed in this work is to decompose the solutions into a combination of the background and the integrable component. This paper is the first part of a two-manuscript series.
A Group Law on the Projective Plane with Applications in Public Key Cryptography
Authors: Durán Díaz Raúl , Hernández Encinas Luis , Muñoz Masqué Jaime
Published: May 2020

In the context of new threats to Public Key Cryptography arising from a growing computational power both in classic and in quantum worlds, we present a new group law defined on a subset of the projective plane F P 2 over an arbitrary field F , which lends itself to applications in Public Key Cryptography and turns out to be more efficient in terms of computational resources. In particular, we give explicitly the number of base field operations needed to perform the mentioned group law. Based on it, we present a Diffie-Hellman-like key agreement protocol. We analyze the computational difficulty of solving the mathematical problem underlying the proposed Abelian group law and we prove that the security of our proposal is equivalent to the discrete logarithm problem in the multiplicative group of the cubic extension of the finite field considered. We present an experimental setup in order to show real computation times along a comparison with the group operation in the group of points of an elliptic curve. Based on current state-of-the-art algorithms, we provide parameter ranges suitable for real world applications. Finally, we present a promising variant of the proposed group law, by moving from the base field F to the ring Z / p q Z , and we explain how the security becomes enhanced, though at the cost of a longer key length.
An Investigation into Video Game Addiction in Pre-Adolescents and Adolescents: A Cross-Sectional Study
Authors: Esposito Maria Rosaria , Serra Nicola , Guillari Assunta , Simeone Silvio , Sarracino Franca , Continisio Grazia Isabella , Rea Teresa
Published: May 2020

Background and Objectives: Game addiction is an emerging problem in public health. A gaming disorder is characterized by a pattern of persistent or recurrent gaming behavior. The behavioral pattern is severe enough to implicate a significant involvement of family, social, educational, professional, or other relationships. Therefore, greater attention needs to be paid to potential addictive behaviors in terms of video games in order to identify both pre-adolescents and adolescents at risk and to provide them with adequate assistance. Materials and Methods: A random sample of 622 students including pre-adolescents and adolescents were enrolled from September 1st to October 31th 2016, and the Game Addiction Scale (GAS) interview was used to identify pathological students with both Monothetic and Polythetic analysis. Results: This study shows the presence of pathological students is equal to 1.93%, with 37.46% and 4.50% obtained with Monothetic and Polythetic analysis (global and partial), respectively. In our sample, the most frequent were students with a gaming time of 1 or 2 h, and students with a day gaming frequency of 1, 2, or 3 times a day. The items with more pathological students were Item 2 (i.e., Tolerance) and 4 (i.e., Withdrawal). Every item was positively correlated with Daily gaming time (hours) and Daily game frequency, excluding Item 4 (i.e., Withdrawal). Finally, the Monothetic GAS score was positively correlated with Daily gaming time while the Polythetic Global GAS was positively correlated with Daily game frequency and negatively with Education level; instead, the Polythetic Partial GAS score was positively correlated with only Daily gaming time. Conclusion: Males are pathological gamblers more so than females and spend more time playing video games. An increase in Daily game frequency or Daily gaming time implicates an increase in video game addictions, while an increase in Education level, which generally corresponds to a greater age, implicates a decrease in game addiction. Finally, we observed that the correlations obtained between the Polythetic Partial GAS score with the independent variables such as Age, Gender, Education level, Daily gaming time (hours), and Daily game frequency were analogous to the significant correlations obtained with the Monothetic GAS score, while these correlations were different for the Polythetic Global GAS and the independent variables. These results suggest that the use of the original Polythetic scale should not be neglected.
Deep Contact Strength of Surface Hardened Gears
Authors: Beskopylny Alexey , Meskhi Besarion , Onishkov Nikolay , Kotelnitskaya Lubov , Ananova Oxana
Published: May 2020

This article is devoted to the analysis methods for assessing the load capacity of gears hardened by surface chemical-thermal treatment (CTT), which are characterized by structural and chemical heterogeneity. The leading type of failure is determined by several factors, the main of which are the surface and deep layer properties of the material, which fundamentally differ in the energy and structural state. Intercrystalline fracture mechanisms predominate in the surface layers and transcrystalline in the core. For these cases, the classical failure criteria of Mohr, Tresca, and Mises lead to significant errors. Therefore, the bearing capacity of the layer component is investigated by the generalized criterion of the limit state of the Pisarenko-Lebedev structurally inhomogeneous material, considering changes in its plastic properties due to surface hardening. The reliability of predicting the level of bearing capacity of surface hardened steel parts, such as gears, was significantly improved. The influence of the plasticity parameter on the level of bearing capacity for various types of CTT is estimated. Calculations using the presented model show that for alloy steels with a Ni content up to 1%, the safety coefficient can be limited to 1.2, which will increase the bearing capacity by 25–27%.
Characterization of Postprandial Effects on CSF Metabolomics: A Pilot Study with Parallel Comparison to Plasma
Authors: Saito Kosuke , Hattori Kotaro , Andou Tomohiro , Satomi Yoshinori , Gotou Masamitsu , Kobayashi Hiroyuki , Hidese Shinsuke , Kunugi Hiroshi
Published: May 2020

Cerebrospinal fluid (CSF) metabolites reflect biochemical diffusion/export from the brain and possibly serve as biomarkers related to brain disease severity, pathophysiology, and therapeutic efficacy/toxicity. Metabolomic studies using blood matrices have demonstrated interindividual and preanalytical variation of blood metabolites, whereas those of CSF metabolites remain unclear. In this study, we aimed to delineate the postprandial effects on CSF metabolites because fasting of patients with brain-related disorders is challenging. We collected pre- and postprandial (1.5, 3, and 6 h) plasma and CSF from nine healthy subjects. Using a mass-spectrometry-based global metabolomics approach, 150 and 130 hydrophilic metabolites and 263 and 340 lipids were detected in CSF and plasma, respectively. Principal component analysis of CSF hydrophilic metabolites and lipids primarily classified individual subjects at any time point, suggesting that the postprandial effects had a lower impact than interindividual variations on CSF metabolites. Individually, less than 10% of the CSF metabolites were putatively altered by postprandial effects (with either significant differences or over 2-fold changes, but not both) at any time point. Thus, global CSF metabolite levels are not directly associated with food intake, and except for several putatively altered CSF metabolites, postprandial effects are not a major concern when applying CSF metabolomics to screen biomarkers.
Complex Geophysical Investigations under Extreme P,T–Conditions at Zentralinstitut für Physik der Erde (ZIPE) (1970–1990)
Authors: Mueller Hans J. , Vollstädt Heiner
Published: May 2020

The development of the geophysical high pressure research in the former German Democratic Republic (GDR) is described here. The GDR was a German state established in 1949 at the territory of the Soviet occupation zone. The different experimental investigations under extreme pressure and temperature conditions and their industrial applications, including the pilot manufacture of synthetic diamonds are explained. A review of the research topics pursued including experiments on lunar material and Earth core/mantle material is described.
Repurposing Zileuton as a Depression Drug Using an AI and In Vitro Approach
Authors: Kubick Norwin , Pajares Marta , Enache Ioana , Manda Gina , Mickael Michel-Edwar
Published: May 2020

Repurposing drugs to target M1 macrophages inflammatory response in depression constitutes a bright alternative for commonly used antidepressants. Depression is a significant type of mood disorder, where patients suffer from pathological disturbances associated with a proinflammatory M1 macrophage phenotype. Presently, the most commonly used antidepressants such as Zoloft and Citalopram can reduce inflammation, but suffer from dangerous side effects without offering specificity toward macrophages. We employed a new strategy for drug repurposing based on the integration of RNA-seq analysis and text mining using deep neural networks. Our system employs a Google semantic AI universal encoder to compute sentences embedding. Sentences similarity is calculated using a sorting function to identify drug compounds. Then sentence relevance is computed using a custom-built convolution differential network. Our system highlighted the NRF2 pathway as a critical drug target to reprogram M1 macrophage response toward an anti-inflammatory profile (M2). Using our approach, we were also able to predict that lipoxygenase inhibitor drug zileuton could modulate NRF2 pathway in vitro. Taken together, our results indicate that reorienting zileuton usage to modulate M1 macrophages could be a novel and safer therapeutic option for treating depression.
New Oxindole-Bridged Acceptors for Organic Sensitizers: Substitution and Performance Studies in Dye-Sensitized Solar Cells
Authors: Tingare Yogesh S. , Su Chaochin , Shen Ming-Tai , Tsai Sheng-Han , Ho Shih-Yu , Li Wen-Ren
Published: May 2020

New D-π-A configured organic sensitizers featuring halogen-substituted oxindole-bridged acceptor units have been synthesized for dye-sensitized solar cells applications. Among fluorine, bromine, and iodine substitution, the cell based on bromine incorporated dye exhibited the highest efficiency. The oxindoles in these sensitizers were found to assist the electron injection through the chelation of their amide carbonyl groups to the TiO2 surface. This study provides an alternate approach for future rational dye design to gain excellent DSSC performance.
Simplified Procedure for General Synthesis of Monosubstituted Piperazines—From a Batch Reaction Vessel to a Flow (Microwave) Reactor
Authors: Němečková Dana , Havránková Eva , Šimbera Jan , Ševčík Richard , Pazdera Pavel
Published: May 2020

We reported a novel simplified synthetic procedure for the preparation of monosubstituted piperazine derivatives which can now be easily prepared in a one-pot-one-step way from a protonated piperazine with no need of introduction of a protecting group. Reactions, proceeding either at room or higher temperatures in common solvents, involve heterogeneous catalysis by metal ions supported on commercial polymeric resins. A general synthetic scheme was successfully applied to afford a wide range of monosubstituted piperazines. Furthermore, we picked up a set of piperazine derivatives and studied the possibilities of microwave acceleration of given synthetic reactions to make them even more efficient. Our research proceeded from a simple batch technique to the construction of a flow microwave reactor prototype and resulted in promising findings which are summarized and discussed in the article.
Characterization of Micronutrients, Bioaccessibility and Antioxidant Activity of Prickly Pear Cladodes as Functional Ingredient
Authors: Missaoui Meriam , D’Antuono Isabella , D’Imperio Massimiliano , Linsalata Vito , Boukhchina Sadok , Logrieco Antonio F. , Cardinali Angela
Published: May 2020

The Opuntia ficus indica (L.) (OFI) is used as a nutritional and pharmaceutical agent in various dietary and value added products. This study underlines the possible use of native prickly pear cladode powder as a functional ingredient for health-promoting food production. To summarise, chemical characterization of polyphenols, minerals and soluble dietary fibre was performed; furthermore, the antioxidant activity and bioaccessibility of polyphenols and minerals were assessed. Eleven compounds between phenolic acids and flavonoids were identified, with piscidic acid and isorhamnetin derivatives being the most abundant. Opuntia’s dietary fibre was mainly constituted of mucilage and pectin, and was composed of arabinose, galactose, glucose, mannose, rhamnose, and xylose sugars. The polyphenols’ bioaccessibility was very high: piscidic acid at 200%, eucomic and ferulic acids >110% and flavonoids from 89% to 100%. The prickly pear cladode powder is also a source of minerals, as cations (calcium, sodium, potassium and magnesium) and anions (sulphate and chloride), with high magnesium bioaccessibilty (93%). OFI powder showed good capacity of radical scavenging measured by DPPH and ABTS methods, with 740 and 775 μmol Trolox/100 g OFI, respectively. Finally, the presented results allow the consideration of this natural product as a source of several essential nutrients, with a possible use in the food industry as a functional ingredient.
Artificial Intelligence Based Methods for Asphaltenes Adsorption by Nanocomposites: Application of Group Method of Data Handling, Least Squares Support Vector Machine, and Artificial Neural Networks
Authors: Mazloom Mohammad Sadegh , Rezaei Farzaneh , Hemmati-Sarapardeh Abdolhossein , Husein Maen M. , Zendehboudi Sohrab , Bemani Amin
Published: May 2020

Asphaltenes deposition is considered a serious production problem. The literature does not include enough comprehensive studies on adsorption phenomenon involved in asphaltenes deposition utilizing inhibitors. In addition, effective protocols on handling asphaltenes deposition are still lacking. In this study, three efficient artificial intelligent models including group method of data handling (GMDH), least squares support vector machine (LSSVM), and artificial neural network (ANN) are proposed for estimating asphaltenes adsorption onto NiO/SAPO-5, NiO/ZSM-5, and NiO/AlPO-5 nanocomposites based on a databank of 252 points. Variables influencing asphaltenes adsorption include pH, temperature, amount of nanocomposites over asphaltenes initial concentration (D/C0), and nanocomposites characteristics such as BET surface area and volume of micropores. The models are also optimized using nine optimization techniques, namely coupled simulated annealing (CSA), genetic algorithm (GA), Bayesian regularization (BR), scaled conjugate gradient (SCG), ant colony optimization (ACO), Levenberg–Marquardt (LM), imperialistic competitive algorithm (ICA), conjugate gradient with Fletcher-Reeves updates (CGF), and particle swarm optimization (PSO). According to the statistical analysis, the proposed RBF-ACO and LSSVM-CSA are the most accurate approaches that can predict asphaltenes adsorption with average absolute percent relative errors of 0.892% and 0.94%, respectively. The sensitivity analysis shows that temperature has the most impact on asphaltenes adsorption from model oil solutions.
One-Step Three-Dimensional Phase Unwrapping Approach Based on Small Baseline Subset Interferograms
Authors: Esch Christina , Köhler Joël , Gutjahr Karlheinz , Schuh Wolf-Dieter
Published: May 2020

One of the most critical steps in a multitemporal D-InSAR analysis is the resolution of the phase ambiguities in the context of phase unwrapping. The Extended Minimum Cost Flow approach is one of the potential phase unwrapping algorithms used in the Small Baseline Subset analysis. In a first step, each phase gradient is unwrapped in time using a linear motion model and, in a second step, the spatial phase unwrapping is individually performed for each interferogram. Exploiting the temporal and spatial information is a proven method, but the two-step procedure is not optimal. In this paper, a method is presented which solves both the temporal and spatial phase unwrapping in one single step. This requires some modifications regarding the estimation of the motion model and the choice of the weights. Furthermore, the problem of temporal inconsistency of the data, which occurs with spatially filtered interferograms, must be considered. For this purpose, so called slack variables are inserted. To verify the method, both simulated and real data are used. The test region is the Lower-Rhine-Embayment in the southwest of North Rhine-Westphalia, a very rural region with noisy data. The studies show that the new approach leads to more consistent results, so that the deformation time series of the analyzed pixels can be improved.
Entropy of Real-World Gait in Parkinson’s Disease Determined from Wearable Sensors as a Digital Marker of Altered Ambulatory Behavior
Authors: Coates Lucy , Shi Jian , Rochester Lynn , Del Din Silvia , Pantall Annette
Published: May 2020

Parkinson’s disease (PD) is a common age-related neurodegenerative disease. Gait impairment is frequent in the later stages of PD contributing to reduced mobility and quality of life. Digital biomarkers such as gait velocity and step length are predictors of motor and cognitive decline in PD. Additional gait parameters may describe different aspects of gait and motor control in PD. Sample entropy (SampEnt), a measure of signal predictability, is a nonlinear approach that quantifies regularity of a signal. This study investigated SampEnt as a potential biomarker for PD and disease duration. Real-world gait data over a seven-day period were collected using an accelerometer (Axivity AX3, York, UK) placed on the low back and gait metrics extracted. SampEnt was determined for the stride time, with vector length and threshold parameters optimized. People with PD had higher stride time SampEnt compared to older adults, indicating reduced gait regularity. The range of SampEnt increased over 36 months for the PD group, although the mean value did not change. SampEnt was associated with dopaminergic medication dose but not with clinical motor scores. In conclusion, this pilot study indicates that SampEnt from real-world data may be a useful parameter reflecting clinical status although further research is needed involving larger populations.
Smartwatch-Derived Data and Machine Learning Algorithms Estimate Classes of Ratings of Perceived Exertion in Runners: A Pilot Study
Authors: Davidson Padraig , Düking Peter , Zinner Christoph , Sperlich Billy , Hotho Andreas
Published: May 2020

The rating of perceived exertion (RPE) is a subjective load marker and may assist in individualizing training prescription, particularly by adjusting running intensity. Unfortunately, RPE has shortcomings (e.g., underreporting) and cannot be monitored continuously and automatically throughout a training sessions. In this pilot study, we aimed to predict two classes of RPE (≤15 “Somewhat hard to hard” on Borg’s 6–20 scale vs. RPE > 15 in runners by analyzing data recorded by a commercially-available smartwatch with machine learning algorithms. Twelve trained and untrained runners performed long-continuous runs at a constant self-selected pace to volitional exhaustion. Untrained runners reported their RPE each kilometer, whereas trained runners reported every five kilometers. The kinetics of heart rate, step cadence, and running velocity were recorded continuously ( 1 Hz ) with a commercially-available smartwatch (Polar V800). We trained different machine learning algorithms to estimate the two classes of RPE based on the time series sensor data derived from the smartwatch. Predictions were analyzed in different settings: accuracy overall and per runner type; i.e., accuracy for trained and untrained runners independently. We achieved top accuracies of 84.8 % for the whole dataset, 81.8 % for the trained runners, and 86.1 % for the untrained runners. We predict two classes of RPE with high accuracy using machine learning and smartwatch data. This approach might aid in individualizing training prescriptions.
An Energy-Efficient Evolutionary Clustering Technique for Disaster Management in IoT Networks
Authors: Biabani Morteza , Fotouhi Hossein , Yazdani Nasser
Published: May 2020

Wireless Sensor Networks (WSNs) are key elements of Internet of Things (IoT) networks which provide sensing and wireless connectivity. Disaster management in smart cities is classified as a safety-critical application. Thus, it is important to ensure system availability by increasing the lifetime of WSNs. Clustering is one of the routing techniques that benefits energy efficiency in WSNs. This paper provides an evolutionary clustering and routing method which is capable of managing the energy consumption of nodes while considering the characteristics of a disaster area. The proposed method consists of two phases. First, we present a model with improved hybrid Particle Swarm Optimization (PSO) and Harmony Search Algorithm (HSA) for cluster head (CH) selection. Second, we design a PSO-based multi-hop routing system with enhanced tree encoding and a modified data packet format. The simulation results for disaster scenarios prove the efficiency of the proposed method in comparison with the state-of-the-art approaches in terms of the overall residual energy, number of live nodes, network coverage, and the packet delivery ratio.
An Intelligent Non-Invasive Real-Time Human Activity Recognition System for Next-Generation Healthcare
Authors: Taylor William , Shah Syed Aziz , Dashtipour Kia , Zahid Adnan , Abbasi Qammer H. , Imran Muhammad Ali
Published: May 2020

Human motion detection is getting considerable attention in the field of Artificial Intelligence (AI) driven healthcare systems. Human motion can be used to provide remote healthcare solutions for vulnerable people by identifying particular movements such as falls, gait and breathing disorders. This can allow people to live more independent lifestyles and still have the safety of being monitored if more direct care is needed. At present wearable devices can provide real-time monitoring by deploying equipment on a person’s body. However, putting devices on a person’s body all the time makes it uncomfortable and the elderly tend to forget to wear them, in addition to the insecurity of being tracked all the time. This paper demonstrates how human motions can be detected in a quasi-real-time scenario using a non-invasive method. Patterns in the wireless signals present particular human body motions as each movement induces a unique change in the wireless medium. These changes can be used to identify particular body motions. This work produces a dataset that contains patterns of radio wave signals obtained using software-defined radios (SDRs) to establish if a subject is standing up or sitting down as a test case. The dataset was used to create a machine learning model, which was used in a developed application to provide a quasi-real-time classification of standing or sitting state. The machine-learning model was able to achieve 96.70% accuracy using the Random Forest algorithm using 10 fold cross-validation. A benchmark dataset of wearable devices was compared to the proposed dataset and results showed the proposed dataset to have similar accuracy of nearly 90%. The machine-learning models developed in this paper are tested for two activities but the developed system is designed and applicable for detecting and differentiating x number of activities.
Lensless Computational Imaging Technology Using Deep Convolutional Network
Authors: Chen Peidong , Su Xiuqin , Liu Muyuan , Zhu Wenhua
Published: May 2020

Within the framework of Internet of Things or when constrained in limited space, lensless imaging technology provides effective imaging solutions with low cost and reduced size prototypes. In this paper, we proposed a method combining deep learning with lensless coded mask imaging technology. After replacing lenses with the coded mask and using the inverse matrix optimization method to reconstruct the original scene images, we applied FCN-8s, U-Net, and our modified version of U-Net, which is called Dense-U-Net, for post-processing of reconstructed images. The proposed approach showed supreme performance compared to the classical method, where a deep convolutional network leads to critical improvements of the quality of reconstruction.
A Model to Predict Children’s Reaction Time at Signalized Intersections
Authors: Ištoka Otković Irena
Published: May 2020

Traffic accident statistics in urban areas, both locally in Croatia and at the European level, identify children as a group of vulnerable road users. The analysis of the parameters that influence the interaction of child pedestrians and other road users requires special attention. This paper presents the results of research about the reaction time of children, measured both in laboratory conditions, via a computer reaction time test, and in actual traffic conditions. The results of the reaction time test in a situation with expected stimuli (a computer test) of children aged 6 to 10 years were compared with the results of the reaction time of adult traffic participants, drivers, who also took part in the computer test. Standard deviations of the reaction times between the control group (drivers, adults) and each subgroup of children were significantly different (p < 0.05). The results suggest that the largest developmental jump occurs between preschool children and first-grade children. In actual traffic conditions, the reaction time of children aged 4 to 16 years at the signalized intersection was measured. The model for predicting the reaction time of children in real traffic conditions was created using a neural network. The model prediction results matched well with the values measured in actual traffic conditions, for the observed intersection (correlation coefficient is 94.56%) and for the validation intersection (correlation coefficient is 92.29%). Parameters influencing children’s reaction times in real traffic conditions were identified by applying both statistical analysis and the neural network model developed. Using both methods, the same key distractors were identified—the movement of children in the group and the use of mobile phones. The case study was conducted at selected signalized intersections in the city of Osijek, Croatia.
The Evolutionary Trajectory of the Agile Concept Viewed from a Management Fashion Perspective
Authors: Madsen Dag Øivind
Published: May 2020

Agile is one of the most popular contemporary management concepts and buzzwords. This paper provides an in-depth examination of the influence of the Agile concept on the discourse, thinking and practices of organizations worldwide. The paper traces the emergence and evolution of the Agile concept from inception to the present by synthesizing findings from a wide range of academic and practitioner-oriented sources. Overall, the picture that emerges from the analysis is that the Agile concept has grown considerably in popularity and has become one of the most dominant concepts in public management discourse. The popularization of Agile has, to a large extent, been driven by an active supply-side made up of actors such as consultants, coaches, and trainers. Another finding is that the Agile concept has evolved considerably over time, from its initial presentation as a narrow and specialized concept rooted in the software development community to a much broader and general approach applicable across nearly all types of organizations and industries. The broadening of the concept has led to neologisms such as Agile Marketing, Agile Government, and Agile Management. The paper ends with reflections on the current status of Agile and some speculation about the concept’s likely future trajectory.
Is There Visual Lateralisation of the Sun Compass in Homing Pigeons?
Authors: Griffiths Charlotte , Holland Richard , Gagliardo Anna
Published: May 2020

Functional lateralisation in the avian visual system can be easily studied by testing monocularly occluded birds. The sun compass is a critical source of navigational information in birds, but studies of visual asymmetry have focussed on cues in a laboratory rather than a natural setting. We investigate functional lateralisation of sun compass use in the visual system of homing pigeons trained to locate food in an outdoor octagonal arena, with a coloured beacon in each sector and a view of the sun. The arena was rotated to introduce a cue conflict, and the experimental groups, a binocular treatment and two monocular treatments, were tested for their directional choice. We found no significant difference in test orientation between the treatments, with all groups showing evidence of both sun compass and beacon use, suggesting no complete functional lateralisation of sun compass use within the visual system. However, reduced directional consistency of binocular vs. monocular birds may reveal a conflict between the two hemispheres in a cue conflict condition. Birds using the right hemisphere were more likely to choose the intermediate sector between the training sector and the shifted training beacon, suggesting a possible asymmetry in favour of the left eye/right hemisphere (LE/RH) when integrating different cues.
Delayed Onset Scleromalacia and Conjunctival Bleb Formation Following Intraoperative Mitomycin C Application during Conjunctival Melanoma Excision
Authors: Ahmed Syed Naqib , Shahid Syed Mohammed , Nanavaty Mayank A.
Published: May 2020

Purpose: To present a case of delayed onset scleromalacia and conjunctival bleb formation one year after conjunctival melanoma excision with intraoperative use of mitomycin-C (MMC) and double-freeze-thaw technique. Methods: Case report. Results: A 69-year-old woman had a conjunctival melanoma excised by the ‘no touch technique’ with intraoperative application of 0.02% MMC for 3 min on bare sclera, freeze-thaw cryotherapy and amniotic membrane transplant performed elsewhere. Three months later, she presented to us with a red, sore and painful right eye. Examination revealed severe scleritis. She was treated with lubricants and oral steroids for 6 weeks. She settled well with no recurrence of melanoma. At one year, she developed scleromalacia and conjunctival blebs in the inferonasal quadrant of right eye. She remains under closer observation as she is at high risk of perforation. Conclusion: Caution should be exercised with intraoperative use of MMC on bare sclera during excision and cryotherapy of conjunctival melanoma. As published in the literature, when using MMC, it is recommended to use the lowest dose topically in the form of eye drops in the postoperative period for the shortest time to avoid any sight-threatening complications.