bluuebunny/crossref_metadata_2025 huggingface dataset:
Neurological Complications of COVID-19: Underlying Mechanisms and Management
Authors: Shehata Ghaydaa A. , Lord Kevin C. , Grudzinski Michaela C. , Elsayed Mohamed , Abdelnaby Ramy , Elshabrawy Hatem A.
Published: April 2021

COVID-19 is a severe respiratory disease caused by the newly identified human coronavirus (HCoV) Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). The virus was discovered in December 2019, and in March 2020, the disease was declared a global pandemic by the World Health Organization (WHO) due to a high number of cases. Although SARS-CoV-2 primarily affects the respiratory system, several studies have reported neurological complications in COVID-19 patients. Headache, dizziness, loss of taste and smell, encephalitis, encephalopathy, and cerebrovascular diseases are the most common neurological complications that are associated with COVID-19. In addition, seizures, neuromuscular junctions’ disorders, and Guillain–Barré syndrome were reported as complications of COVID-19, as well as neurodegenerative and demyelinating disorders. However, the management of these conditions remains a challenge. In this review, we discuss the prevalence, pathogenesis, and mechanisms of these neurological sequelae that are secondary to SARS-CoV-2 infection. We aim to update neurologists and healthcare workers on the possible neurological complications associated with COVID-19 and the management of these disease conditions.
Sigma-1 Receptor (S1R) Interaction with Cholesterol: Mechanisms of S1R Activation and Its Role in Neurodegenerative Diseases
Authors: Zhemkov Vladimir , Geva Michal , Hayden Michael R. , Bezprozvanny Ilya
Published: April 2021

The sigma-1 receptor (S1R) is a 223 amino acid-long transmembrane endoplasmic reticulum (ER) protein. The S1R modulates the activity of multiple effector proteins, but its signaling functions are poorly understood. S1R is associated with cholesterol, and in our recent studies we demonstrated that S1R association with cholesterol induces the formation of S1R clusters. We propose that these S1R-cholesterol interactions enable the formation of cholesterol-enriched microdomains in the ER membrane. We hypothesize that a number of secreted and signaling proteins are recruited and retained in these microdomains. This hypothesis is consistent with the results of an unbiased screen for S1R-interacting partners, which we performed using the engineered ascorbate peroxidase 2 (APEX2) technology. We further propose that S1R agonists enable the disassembly of these cholesterol-enriched microdomains and the release of accumulated proteins such as ion channels, signaling receptors, and trophic factors from the ER. This hypothesis may explain the pleotropic signaling functions of the S1R, consistent with previously observed effects of S1R agonists in various experimental systems.
Development of a Topical Insulin Polymeric Nanoformulation for Skin Burn Regeneration: An Experimental Approach
Authors: Quitério Maria , Simões Sandra , Ascenso Andreia , Carvalheiro Manuela , Leandro Ana Paula , Correia Isabel , Viana Ana Silveira , Faísca Pedro , Ascensão Lia , Molpeceres Jesús , Gaspar Maria Manuela , Reis Catarina Pinto
Published: April 2021

Insulin is a peptide hormone with many physiological functions, besides its use in diabetes treatment. An important role of insulin is related to the wound healing process—however, insulin itself is too sensitive to the external environment requiring the protective of a nanocarrier. Polymer-based nanoparticles can protect, deliver, and retain the protein in the target area. This study aims to produce and characterize a topical treatment for wound healing consisting of insulin-loaded poly-DL-lactide/glycolide (PLGA) nanoparticles. Insulin-loaded nanoparticles present a mean size of approximately 500 nm and neutral surface charge. Spherical shaped nanoparticles are observed by scanning electron microscopy and confirmed by atomic force microscopy. SDS-PAGE and circular dichroism analysis demonstrated that insulin preserved its integrity and secondary structure after the encapsulation process. In vitro release studies suggested a controlled release profile. Safety of the formulation was confirmed using cell lines, and cell viability was concentration and time-dependent. Preliminary safety in vivo assays also revealed promising results.
Iron at the Interface of Hepatocellular Carcinoma
Authors: Paganoni Rossana , Lechel André , Vujic Spasic Maja
Published: April 2021

Cancer incidence and mortality are rapidly growing, with liver cancer being the sixth most diagnosed cancer worldwide and the third leading cause of cancer death in 2020. A number of risk factors have been identified that trigger the progression to hepatocellular carcinoma. In this review, we focus on iron as a potential risk factor for liver carcinogenesis. Molecules involved in the regulation of iron metabolism are often upregulated in cancer cells, in order to provide a supply of this essential trace element for all stages of tumor development, survival, proliferation, and metastasis. Thus, cellular and systemic iron levels must be tightly regulated to prevent or delay liver cancer progression. Disorders associated with dysregulated iron metabolism are characterized with increased susceptibility to hepatocellular carcinoma. This review discusses the association of iron with metabolic disorders such as hereditary hemochromatosis, non-alcoholic fatty liver disease, obesity, and type 2 diabetes, in the background of hepatocellular carcinoma.
Knockdown of RRM1 with Adenoviral shRNA Vectors to Inhibit Tumor Cell Viability and Increase Chemotherapeutic Sensitivity to Gemcitabine in Bladder Cancer Cells
Authors: Zhang Xia , Taoka Rikiya , Liu Dage , Matsuoka Yuki , Tohi Yoichiro , Kakehi Yoshiyuki , Sugimoto Mikio
Published: April 2021

RRM1—an important DNA replication/repair enzyme—is the primary molecular gemcitabine (GEM) target. High RRM1-expression associates with gemcitabine-resistance in various cancers and RRM1 inhibition may provide novel cancer treatment approaches. Our study elucidates how RRM1 inhibition affects cancer cell proliferation and influences gemcitabine-resistant bladder cancer cells. Of nine bladder cancer cell lines investigated, two RRM1 highly expressed cells, 253J and RT112, were selected for further experimentation. An RRM1-targeting shRNA was cloned into adenoviral vector, Ad-shRRM1. Gene and protein expression were investigated using real-time PCR and western blotting. Cell proliferation rate and chemotherapeutic sensitivity to GEM were assessed by MTT assay. A human tumor xenograft model was prepared by implanting RRM1 highly expressed tumors, derived from RT112 cells, in nude mice. Infection with Ad-shRRM1 effectively downregulated RRM1 expression, significantly inhibiting cell growth in both RRM1 highly expressed tumor cells. In vivo, Ad-shRRM1 treatment had pronounced antitumor effects against RRM1 highly expressed tumor xenografts (p < 0.05). Moreover, combination of Ad-shRRM1 and GEM inhibited cell proliferation in both cell lines significantly more than either treatment individually. Cancer gene therapy using anti-RRM1 shRNA has pronounced antitumor effects against RRM1 highly expressed tumors, and RRM1 inhibition specifically increases bladder cancer cell GEM-sensitivity. Ad-shRRM1/GEM combination therapy may offer new treatment options for patients with GEM-resistant bladder tumors.
Thixotropic Hydrogels Composed of Self-Assembled Nanofibers of Double-Hydrophobic Elastin-Like Block Polypeptides
Authors: Sugioka Yusuke , Nakamura Jin , Ohtsuki Chikara , Sugawara-Narutaki Ayae
Published: April 2021

Physically crosslinked hydrogels with thixotropic properties attract considerable attention in the biomedical research field because their self-healing nature is useful in cell encapsulation, as injectable gels, and as bioinks for three-dimensional (3D) bioprinting. Here, we report the formation of thixotropic hydrogels containing nanofibers of double-hydrophobic elastin-like polypeptides (ELPs). The hydrogels are obtained with the double-hydrophobic ELPs at 0.5 wt%, the concentration of which is an order of magnitude lower than those for previously reported ELP hydrogels. Although the kinetics of hydrogel formation is slower for the double-hydrophobic ELP with a cell-binding sequence, the storage moduli G′ of mature hydrogels are similar regardless of the presence of a cell-binding sequence. Reversible gel–sol transitions are demonstrated in step-strain rheological measurements. The degree of recovery of the storage modulus G′ after the removal of high shear stress is improved by chemical crosslinking of nanofibers when intermolecular crosslinking is successful. This work would provide deeper insight into the structure–property relationships of the self-assembling polypeptides and a better design strategy for hydrogels with desired viscoelastic properties.
Exploring the Value of Nodes with Multicommunity Membership for Classification with Graph Convolutional Neural Networks
Authors: Hopwood Michael , Pho Phuong , Mantzaris Alexander V.
Published: April 2021

Sampling is an important step in the machine learning process because it prioritizes samples that help the model best summarize the important concepts required for the task at hand. The process of determining the best sampling method has been rarely studied in the context of graph neural networks. In this paper, we evaluate multiple sampling methods (i.e., ascending and descending) that sample based off different definitions of centrality (i.e., Voterank, Pagerank, degree) to observe its relation with network topology. We find that no sampling method is superior across all network topologies. Additionally, we find situations where ascending sampling provides better classification scores, showing the strength of weak ties. Two strategies are then created to predict the best sampling method, one that observes the homogeneous connectivity of the nodes, and one that observes the network topology. In both methods, we are able to evaluate the best sampling direction consistently.
Urinary Peptides as Potential Non-Invasive Biomarkers for Lupus Nephritis: Results of the Peptidu-LUP Study
Authors: Tailliar Maxence , Schanstra Joost , Dierckx Tim , Breuil Benjamin , Hanouna Guillaume , Charles Nicolas , Bascands Jean-Loup , Dussol Bertrand , Vazi Alain , Chiche Laurent , Siwy Justyna , Faguer Stanislas , Daniel Laurent , Daugas Eric , Jourde-Chiche Noémie ,   on behalf of the Groupe Coopératif sur le Lupus Rénal (GCLR)
Published: April 2021

Background: Lupus nephritis (LN) is a severe manifestation of Systemic Lupus Erythematosus (SLE). The therapeutic strategy relies on kidney biopsy (KB) results. We tested whether urinary peptidome analysis could non-invasively differentiate active from non-active LN. Design: Urinary samples were collected from 93 patients (55 with active LN and 38 with non-active LN), forming a discovery (n = 42) and an independent validation (n = 51) cohort. Clinical characteristics were collected at inclusion and prospectively for 24 months. The urinary peptidome was analyzed by capillary-electrophoresis coupled to mass-spectrometry, comparing active LN to non-active LN, and assessing chronic lesions and response to therapy. The value of previously validated prognostic (CKD273) and differential diagnostic (LN172) signatures was evaluated. Results: Urinary peptides could not discriminate between active and non-active LN or predict early response to therapy. Tubulo-interstitial fibrosis was correlated to the CKD273. The LN172 score identified 92.5% of samples as LN. Few patients developed new-onset CKD. Conclusions: We validated the CKD273 and LN172 classifiers but did not identify a robust signature that could predict active LN and replace KB. The value of urinary peptidome to predict long-term CKD, or renal flares in SLE, remains to be evaluated.
Lipid and Lipoprotein Dysregulation in Sepsis: Clinical and Mechanistic Insights into Chronic Critical Illness
Authors: Barker Grant , Leeuwenburgh Christiaan , Brusko Todd , Moldawer Lyle , Reddy Srinivasa , Guirgis Faheem
Published: April 2021

In addition to their well-characterized roles in metabolism, lipids and lipoproteins have pleiotropic effects on the innate immune system. These undergo clinically relevant alterations during sepsis and acute inflammatory responses. High-density lipoprotein (HDL) plays an important role in regulating the immune response by clearing bacterial toxins, supporting corticosteroid release, decreasing platelet aggregation, inhibiting endothelial cell apoptosis, reducing the monocyte inflammatory response, and inhibiting expression of endothelial cell adhesion molecules. It undergoes quantitative as well as qualitative changes which can be measured using the HDL inflammatory index (HII). Pro-inflammatory, or dysfunctional HDL (dysHDL) lacks the ability to perform these functions, and we have also found it to independently predict adverse outcomes and organ failure in sepsis. Another important class of lipids known as specialized pro-resolving mediators (SPMs) positively affect the escalation and resolution of inflammation in a temporal fashion. These undergo phenotypic changes in sepsis and differ significantly between survivors and non-survivors. Certain subsets of sepsis survivors go on to have perilous post-hospitalization courses where this inflammation continues in a low grade fashion. This is associated with immunosuppression in a syndrome of persistent inflammation, immunosuppression, and catabolism syndrome (PICS). The continuous release of tissue damage-related patterns and viral reactivation secondary to immunosuppression feed this chronic cycle of inflammation. Animal data indicate that dysregulation of endogenous lipids and SPMs play important roles in this process. Lipids and their associated pathways have been the target of many clinical trials in recent years which have not shown mortality benefit. These results are limited by patient heterogeneity and poor animal models. Considerations of sepsis phenotypes and novel biomarkers in future trials are important factors to be considered in future research. Further characterization of lipid dysregulation and chronic inflammation during sepsis will aid mortality risk stratification, detection of sepsis, and inform individualized pharmacologic therapies.
Ecological Momentary Assessment of the Relationship between Positive Outcome Expectancies and Gambling Behaviour
Authors: Dowling Nicki A. , Merkouris Stephanie S. , Spence Kimberley
Published: April 2021

Relapse prevention models suggest that positive outcome expectancies can constitute situational determinants of relapse episodes that interact with other factors to determine the likelihood of relapse. The primary aims were to examine reciprocal relationships between situational positive gambling outcome expectancies and gambling behaviour and moderators of these relationships. An online survey and a 28 day Ecological Momentary Assessment (EMA) were administered to 109 past-month gamblers (84% with gambling problems). EMA measures included outcome expectancies (enjoyment/arousal, self-enhancement, money), self-efficacy, craving, negative emotional state, interpersonal conflict, social pressure, positive emotional state, financial pressures, and gambling behaviour (episodes, expenditure). Pre-EMA measures included problem gambling severity, motives, psychological distress, coping strategies, and outcome expectancies. No reciprocal relationships between EMA outcome expectancies and gambling behaviour (episodes, expenditure) were identified. Moderations predicting gambling episodes revealed: (1) cravings and problem gambling exacerbated effects of enjoyment/arousal expectancies; (2) positive emotional state and positive reframing coping exacerbated effects of self-enhancement expectancies; and (3) instrumental social support buffered effects of money expectancies. Positive outcome expectancies therefore constitute situational determinants of gambling behaviour, but only when they interact with other factors. All pre-EMA expectancies predicted problem gambling severity (OR = 1.61–3.25). Real-time interventions addressing gambling outcome expectancies tailored to vulnerable gamblers are required.
A Velocity Obstacle-Based Real-Time Regional Ship Collision Risk Analysis Method
Authors: Chen Pengfei , Li Mengxia , Mou Junmin
Published: April 2021

Maritime accidents such as ship collisions pose continuous risks to individuals and society with due to their severe consequences on human life, economic and environmental losses, etc. Supervising the maritime traffic in the different regions and maintaining its safety level is an essential task for stakeholders such as maritime safety administrations. In this research, a new ship collision risk analysis method is developed with the utilisation of AIS (Automatic Identification System) data. A velocity obstacle-based risk measurement is applied to measure the risk of collision between multiple ships from the velocity perspective, based on which, the collision risk and the complexity of the encounter situation are obtained at the same time. Secondly, a density-based clustering technique is introduced to identify the hotspots of ship traffic in the region as an indicator for maritime safety operators. A case study using historical AIS data was implemented to verify the effectiveness of the proposed approach in a manner that simulates the real-time data scenario. Furthermore, a comparison between existing risk analysis method is conducted to validate the proposed method.
The Effects of Installation on the Elastic Stiffness Coefficients of Spudcan Foundations
Authors: Lin Wen-Long , Wang Zhen , Liu Fei , Yi Jiang-Tao
Published: April 2021

Subjected to pre-load, spudcan foundations, widely utilized to support offshore jack-up rigs, may penetrate in a few diameters into soft clays before mobilizing sufficient resistance from soil. While its stress–strain behavior is known to be affected by the embedment condition and soil backflow, the small-strain calculation with wished-in-place assumption was previously adopted to analyze its elastic stiffness coefficients. This study takes advantage of a recently developed dual-stage Eulerian–Lagrangian (DSEL) technique to re-evaluate the elastic stiffness coefficients of spudcans after realistically modelling the deep, continuous spudcan penetration. A numerical parametric exercise is conducted to investigate the effects of strength non-homogeneity, embedment depths, and the spudcan’s size on the elastic stiffness. On these bases, an expression is provided such that the practicing engineers can conveniently factor the installation effects into the estimation of elastic stiffness coefficients of spudcans.
Molecular Phylogeny of Endophytic Fungi from Rattan (Calamus castaneus Griff.) Spines and Their Antagonistic Activities against Plant Pathogenic Fungi
Authors: Azuddin Nurul Farizah , Mohd Masratul Hawa , Rosely Nik Fadzly N. , Mansor Asyraf , Zakaria Latiffah
Published: April 2021

Calamus castaneus is a common rattan palm species in the tropical forests of Peninsular Malaysia and is noticeable by the yellow-based spines that cover the stems. This study aimed to determine the prevalence of fungal endophytes within C. castaneus spines and whether they inhibit the growth of fungal pathogens. Twenty-one genera with 40 species of fungal endophytes were isolated and identified from rattan palm spines. Based on molecular identification, the most common isolates recovered from the spines were Colletotrichum (n = 19) and Diaporthe spp. (n = 18), followed by Phyllosticta spp., Xylaria sp., Trichoderma spp., Helminthosporium spp., Penicillium spp., Fusarium spp., Neopestalotiopsis spp., Arthrinium sp., Cyphellophora sp., Cladosporium spp., Curvularia sp., Bionectria sp., and Acremonium spp. Non-sporulating fungi were also identified, namely Nemania primolutea, Pidoplitchkoviella terricola, Muyocopron laterale, Acrocalymma fici, Acrocalymma medicaginis, and Endomelanconiopsis endophytica. The isolation of these endophytes showed that the spines harbor endophytic fungi. Most of the fungal endophytes inhibited the growth of several plant pathogenic fungi, with 68% of the interactions resulting in mutual inhibition, producing a clear inhibition zone of <2 mm. Our findings demonstrate the potential of the fungal endophytes from C. castaneus spines as biocontrol agents.
Random Transfer of Ogataea polymorpha Genes into Saccharomyces cerevisiae Reveals a Complex Background of Heat Tolerance
Authors: Seike Taisuke , Narazaki Yuki , Kaneko Yoshinobu , Shimizu Hiroshi , Matsuda Fumio
Published: April 2021

Horizontal gene transfer, a process through which an organism acquires genes from other organisms, is a rare evolutionary event in yeasts. Artificial random gene transfer can emerge as a valuable tool in yeast bioengineering to investigate the background of complex phenotypes, such as heat tolerance. In this study, a cDNA library was constructed from the mRNA of a methylotrophic yeast, Ogataea polymorpha, and then introduced into Saccharomyces cerevisiae. Ogataea polymorpha was selected because it is one of the most heat-tolerant species among yeasts. Screening of S. cerevisiae populations expressing O. polymorpha genes at high temperatures identified 59 O. polymorpha genes that contribute to heat tolerance. Gene enrichment analysis indicated that certain S. cerevisiae functions, including protein synthesis, were highly temperature-sensitive. Additionally, the results confirmed that heat tolerance in yeast is a complex phenotype dependent on multiple quantitative loci. Random gene transfer would be a useful tool for future bioengineering studies on yeasts.
Phenotyping Rare CFTR Mutations Reveal Functional Expression Defects Restored by TRIKAFTATM
Authors: Laselva Onofrio , Ardelean Maria C. , Bear Christine E.
Published: April 2021

The rare Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) mutations, c.1826A > G (H609R) and c.3067_3072delATAGTG (I1023_V1024del), are associated with severe lung disease. Despite the existence of four CFTR targeted therapies, none have been approved for individuals with these mutations because the associated molecular defects were not known. In this study we examined the consequences of these mutations on protein processing and channel function in HEK293 cells. We found that, similar to F508del, H609R and I1023_V1024del-CFTR exhibited reduced protein processing and altered channel function. Because the I1023_V1024del mutation can be linked with the mutation, I148T, we also examined the protein conferred by transfection of a plasmid bearing both mutations. Interestingly, together with I148T, there was no further reduction in channel function exhibited by I1023-V1024del. Both H609R and I1023_V1024del failed to exhibit significant correction of their functional expression with lumacaftor and ivacaftor. In contrast, the triple modulator combination found in TRIKAFTATM, i.e., tezacaftor, elexacaftor and ivacaftor rescued trafficking and function of both of these mutants. These in-vitro findings suggest that patients harbouring H609R or I1023_V1024del, alone or with I148T, may benefit clinically from treatment with TRIKAFTATM.
Compound Haplotype Variants in CFH and CD46 Genes Determine Clinical Outcome of Atypical Hemolytic Uremic Syndrome (aHUS)—A Series of Cases from a Single Family
Authors: Furmańczyk-Zawiska Agnieszka , Kubiak-Dydo Anna , Użarowska-Gąska Ewelina , Kotlarek-Łysakowska Marta , Salata Katarzyna , Kolanowska Monika , Świerniak Michał , Gaj Paweł , Leszczyńska Beata , Daniel Maria , Jażdżewski Krystian , Durlik Magdalena , Wójcicka Anna
Published: April 2021

Atypical hemolytic uremic syndrome (aHUS) is a rare disease triggered by dysregulation of the alternative complement pathway, consisting of a characteristic triad of nonimmune hemolytic anemia, thrombocytopenia, and renal failure. The risk of aHUS onset, recurrence, and allograft loss depends on the genetic background of a patient. We show a series of cases from a single family whose five members were affected by aHUS and presented distinct clinical outcomes. Next-generation sequencing revealed combined mutations in both complement factor H and membrane cofactor protein CD46. Out of eight siblings, aHUS affected three adult brothers, and, subsequently, affected two children of an unaffected sister. The first patient died due to aHUS, and two other brothers underwent successful kidney transplantation with no aHUS recurrence. The younger, 10-month-old child presented with a severe course of the disease with cardiac involvement and persistent hemolytic anemia limited by eculizumab, while the 2-year-old recovered completely on eculizumab. The study shows a highly variable disease penetrance.
What Crowdsourcing Platforms Do for Solvers in Problem-Solving Contests: A Content Analysis of Their Websites
Authors: Zhang Xuefeng , Du Lin
Published: April 2021

Solvers’ wide and continuous participation is imperative for the sustainable development of online crowdsourcing platforms (OCPs). Prior studies have deeply investigated what and how solvers’ motives and demographics, task attributes, requester attributes, and platform designs influence solvers’ participation. However, to our knowledge, few studies concentrated on what these OCPs do for solvers in practices that are concerned with solvers and thus influence their decision to participate. To fill this gap, this study conducted a content analysis of 25 typical OCPs focusing on problem-solving contests to identify service measures that they presented for solvers. Consequently, 14 major service measures that are related to contest management, solver management, and requester management were identified. Thereafter, we discussed the roles of these service measures in solvers’ participation. They are activating solvers to participate, providing solvers opportunities to participate, and supporting solvers to participate. Our analysis, on the one hand, presents a comprehensive list of service measures for solvers distributed on these OCPs separately and on the other hand aids the OCPs to improve their solver service and for solvers to compare and analyze their preferred OCPs as a reference.
Behavior of Chemokine Receptor 6 (CXCR6) in Complex with CXCL16 Soluble form Chemokine by Molecular Dynamic Simulations: General Protein‒Ligand Interaction Model and 3D-QSAR Studies of Synthetic Antagonists
Authors: Aguilera-Durán Giovanny , Romo-Mancillas Antonio
Published: April 2021

The CXCR6‒CXCL16 axis is involved in several pathological processes, and its overexpression has been detected in different types of cancer, such as prostate, breast, ovary, and lung cancer, along with schwannomas, in which it promotes invasion and metastasis. Moreover, this axis is involved in atherosclerosis, type 1 diabetes, primary immune thrombocytopenia, vitiligo, and other autoimmune diseases, in which it is responsible for the infiltration of different immune system cells. The 3D structure of CXCR6 and CXCL16 has not been experimentally resolved; therefore, homology modeling and molecular dynamics simulations could be useful for the study of this signaling axis. In this work, a homology model of CXCR6 and a soluble form of CXCL16 (CXCR6‒CXCL16s) are reported to study the interactions between CXCR6 and CXCL16s through coarse-grained molecular dynamics (CG-MD) simulations. CG-MD simulations showed the two activation steps of CXCR6 through a decrease in the distance between the chemokine and the transmembrane region (TM) of CXCR6 and transmembrane rotational changes and polar interactions between transmembrane segments. The polar interactions between TM3, TM5, and TM6 are fundamental to functional conformation and the meta-active state of CXCR6. The interactions between D77-R280 and T243-TM7 could be related to the functional conformation of CXCR6; alternatively, the interaction between Q195-Q244 and N248 could be related to an inactive state due to the loss of this interaction, and an arginine cage broken in the presence of CXCL16s allows the meta-active state of CXCR6. A general protein‒ligand interaction supports the relevance of TM3‒TM5‒TM6 interactions, presenting three relevant pharmacophoric features: HAc (H-bond acceptor), HDn (H-bond donator), and Hph (hydrophobic), distributed around the space between extracellular loops (ECLs) and TMs. The HDn feature is close to TM3 and TM6; likewise, the HAc and Hph features are close to ECL1 and ECL2 and could block the rotation and interactions between TM3‒TM6 and the interactions of CXCL16s with the ECLs. Tridimensional quantitative structure-activity relationships (3D-QSAR) models show that the positive steric (VdW) and electrostatic fields coincide with the steric and positive electrostatic region of the exo-azabicyclo[3.3.1]nonane scaffold in the best pIC50 ligands. This substructure is close to the E274 residue and therefore relevant to the activity of CXCR6. These data could help with the design of new molecules that inhibit chemokine binding or antagonize the receptor based on the activation mechanism of CXCR6 and provoke a decrease in chemotaxis caused by the CXCR6‒CXCL16 axis.
Calculation of Dynamic Viscosity in Concentrated Cementitious Suspensions: Probabilistic Approximation and Bayesian Analysis
Authors: De La Rosa Ángel , Ruiz Gonzalo , Castillo Enrique , Moreno Rodrigo
Published: April 2021

We present a new focus for the Krieger–Dougherty equation from a probabilistic point of view. This equation allows the calculation of dynamic viscosity in suspensions of various types, like cement paste and self-compacting mortar/concrete. The physical meaning of the parameters that intervene in the equation (maximum packing fraction of particles and intrinsic viscosity), together with the random nature associated with these systems, make the application of the Bayesian analysis desirable. This analysis permits the transformation of parametric-deterministic models into parametric-probabilistic models, which improves and enriches their results. The initial limitations of the Bayesian methods, due to their complexity, have been overcome by numerical methods (Markov Chain Monte Carlo and Gibbs Sampling) and the development of specific software (OpenBUGS). Here we use it to compute the probability density functions that intervene in the Krieger–Dougherty equation applied to the calculation of viscosity in several cement pastes, self-compacting mortars, and self-compacting concretes. The dynamic viscosity calculations made with the Bayesian distributions are significantly better than those made with the theoretical values.
Challenges in the Fabrication of Biodegradable and Implantable Optical Fibers for Biomedical Applications
Authors: Gierej Agnieszka , Geernaert Thomas , Van Vlierberghe Sandra , Dubruel Peter , Thienpont Hugo , Berghmans Francis
Published: April 2021

The limited penetration depth of visible light in biological tissues has encouraged researchers to develop novel implantable light-guiding devices. Optical fibers and waveguides that are made from biocompatible and biodegradable materials offer a straightforward but effective approach to overcome this issue. In the last decade, various optically transparent biomaterials, as well as different fabrication techniques, have been investigated for this purpose, and in view of obtaining fully fledged optical fibers. This article reviews the state-of-the-art in the development of biocompatible and biodegradable optical fibers. Whilst several reviews that focus on the chemical properties of the biomaterials from which these optical waveguides can be made have been published, a systematic review about the actual optical fibers made from these materials and the different fabrication processes is not available yet. This prompted us to investigate the essential properties of these biomaterials, in view of fabricating optical fibers, and in particular to look into the issues related to fabrication techniques, and also to discuss the challenges in the use and operation of these optical fibers. We close our review with a summary and an outline of the applications that may benefit from these novel optical waveguides.
Elevated-Temperature Performance, Combustibility and Fire Propagation Index of Fly Ash-Metakaolin Blend Geopolymers with Addition of Monoaluminium Phosphate (MAP) and Aluminum Dihydrogen Triphosphate (ATP)
Authors: Zulkifly Khairunnisa , Cheng-Yong Heah , Yun-Ming Liew , Bayuaji Ridho , Abdullah Mohd Mustafa Al Bakri , Ahmad Shamsul Bin , Stachowiak Tomasz , Szmidla Janusz , Gondro Joanna , Jeż Bartłomiej , Khalid Mohd Suhaimi Bin , Garus Sebastian , Shee-Ween Ong , Wan-En Ooi , Hui-Teng Ng
Published: April 2021

Thermal performance, combustibility, and fire propagation of fly ash-metakaolin (FA-MK) blended geopolymer with the addition of aluminum triphosphate, ATP (Al(H2PO4)3), and monoaluminium phosphate, MAP (AlPO4) were evaluated in this paper. To prepare the geopolymer mix, fly ash and metakaolin with a ratio of 1:1 were added with ATP and MAP in a range of 0–3% by weight. The fire/heat resistance was evaluated by comparing the residual compressive strengths after the elevated temperature exposure. Besides, combustibility and fire propagation tests were conducted to examine the thermal performance and the applicability of the geopolymers as passive fire protection. Experimental results revealed that the blended geopolymers with 1 wt.% of ATP and MAP exhibited higher compressive strength and denser geopolymer matrix than control geopolymers. The effect of ATP and MAP addition was more obvious in unheated geopolymer and little improvement was observed for geopolymer subjected to elevated temperature. ATP and MAP at 3 wt.% did not help in enhancing the elevated-temperature performance of blended geopolymers. Even so, all blended geopolymers, regardless of the addition of ATP and MAP, were regarded as the noncombustible materials with negligible (0–0.1) fire propagation index.
Establishing the Relationship between Cutting Speed and Output Parameters in Belt Grinding on Steels, Aluminum and Nickel Alloys: Development of Recommendations
Authors: Syreyshchikova Nelli Vladimirovna , Pimenov Danil Yurievich , Gupta Munish Kumar , Nadolny Krzysztof , Giasin Khaled , Sharma Shubham
Published: April 2021

This paper presents the research results of one of the main technological parameters of belt grinding, i.e., the cutting speed while machining corrosion- and heat-resistant, structural carbon and structural alloy steels, aluminum, and heat-resistant nickel alloys. Experimental and analytical methods are used to establish the dependence of the output parameters of surface belt grinding on the cutting speed and tool characteristics. An analytical model, considering the physical and mechanical properties of the grinding belt (strength depending on the base and bond; the thermal conductivity; the type of grinding operation) and the machined material, is created to determine the belt grinding speed. The output parameters, such as the arithmetic mean of the surface roughness (Ra) and the material removal rate (MRR) during the belt grinding of steels, heat-resistant and light alloys, have been studied. Based on the empirical dependencies of the belt grinding parameters, the model was developed for the selection and setting of the cutting speed of belt grinding for the aforementioned alloys, taking into account the type of operation, the type of the machined material, and the main characteristics of the sanding belt.
Nanosensors for Visual Detection of Glucose in Biofluids: Are We Ready for Instrument-Free Home-Testing?
Authors: Boselli Luca , Pomili Tania , Donati Paolo , Pompa Pier P.
Published: April 2021

Making frequent large-scale screenings for several diseases economically affordable would represent a real breakthrough in healthcare. One of the most promising routes to pursue such an objective is developing rapid, non-invasive, and cost-effective home-testing devices. As a first step toward a diagnostic revolution, glycemia self-monitoring represents a solid base to start exploring new diagnostic strategies. Glucose self-monitoring is improving people’s life quality in recent years; however, current approaches still present vast room for improvement. In most cases, they still involve invasive sampling processes (i.e., finger-prick), quite discomforting for frequent measurements, or implantable devices which are costly and commonly dedicated to selected chronic patients, thus precluding large-scale monitoring. Thanks to their unique physicochemical properties, nanoparticles hold great promises for the development of rapid colorimetric devices. Here, we overview and analyze the main instrument-free nanosensing strategies reported so far for glucose detection, highlighting their advantages/disadvantages in view of their implementation as cost-effective rapid home-testing devices, including the potential use of alternative non-invasive biofluids as samples sources.
A Model Procedure for Catalytic Conversion of Waste Cotton into Useful Chemicals
Authors: Binczarski Michal J. , Malinowska Justyna , Stanishevsky Andrei , Severino Courtney J. , Yager Riley , Cieslak Malgorzata , Witonska Izabela A.
Published: April 2021

Cotton is grown in about 90 countries and accounts for 24% of the fibers used in the global production of textiles. In 2018/2019, 25.8 Mt of cotton were produced around the world. Since this natural product consists mainly of cellulose, it can be used as a raw material in the so-called “sugar economy”. This paper discusses a model procedure for thermally assisted acidic hydrolysis of cotton into glucose and subsequent oxidation of the glucose into calcium gluconate over Pd-Au/SiO2 catalyst. In the first step, H2SO4 was used as a catalyst for hydrolysis. The cotton hydrolysates were neutralized using CaCO3 and applied as a substrate in the second step, where glucose was oxidized over Pd-Au/SiO2 prepared by ultrasound assisted co-impregnation. With the appropriate Au/Pd molar ratio, small crystallites of palladium and gold were created which were active and selective towards the formation of gluconate ions. This approach to the transformation of glucose represents as a viable alternative to biological processes using fungal and bacterial species, which are sensitive to the presence of inhibitors such as furfurals and levulinic acid in hydrolysates.
Supervised Learning Methods for Modeling Concrete Compressive Strength Prediction at High Temperature
Authors: Ahmad Mahmood , Hu Ji-Lei , Ahmad Feezan , Tang Xiao-Wei , Amjad Maaz , Iqbal Muhammad Junaid , Asim Muhammad , Farooq Asim
Published: April 2021

Supervised learning algorithms are a recent trend for the prediction of mechanical properties of concrete. This paper presents AdaBoost, random forest (RF), and decision tree (DT) models for predicting the compressive strength of concrete at high temperature, based on the experimental data of 207 tests. The cement content, water, fine and coarse aggregates, silica fume, nano silica, fly ash, super plasticizer, and temperature were used as inputs for the models’ development. The performance of the AdaBoost, RF, and DT models are assessed using statistical indices, including the coefficient of determination (R2), root mean squared error-observations standard deviation ratio (RSR), mean absolute percentage error, and relative root mean square error. The applications of the above-mentioned approach for predicting the compressive strength of concrete at high temperature are compared with each other, and also to the artificial neural network and adaptive neuro-fuzzy inference system models described in the literature, to demonstrate the suitability of using the supervised learning methods for modeling to predict the compressive strength at high temperature. The results indicated a strong correlation between experimental and predicted values, with R2 above 0.9 and RSR lower than 0.5 during the learning and testing phases for the AdaBoost model. Moreover, the cement content in the mix was revealed as the most sensitive parameter by sensitivity analysis.
3D Parametric and Nonparametric Description of Surface Topography in Manufacturing Processes
Authors: Królczyk Grzegorz , Kacalak Wojciech , Wieczorowski Michał
Published: April 2021

Surface topography has a profound influence on the function of a surface [...]
Overview of HSS Steel Grades Development and Study of Reheating Condition Effects on Austenite Grain Size Changes
Authors: Kvackaj Tibor , Bidulská Jana , Bidulský Róbert
Published: April 2021

This review paper concerns the development of the chemical compositions and controlled processes of rolling and cooling steels to increase their mechanical properties and reduce weight and production costs. The paper analyzes the basic differences among high-strength steel (HSS), advanced high-strength steel (AHSS) and ultra-high-strength steel (UHSS) depending on differences in their final microstructural components, chemical composition, alloying elements and strengthening contributions to determine strength and mechanical properties. HSS is characterized by a final single-phase structure with reduced perlite content, while AHSS has a final structure of two-phase to multiphase. UHSS is characterized by a single-phase or multiphase structure. The yield strength of the steels have the following value intervals: HSS, 180–550 MPa; AHSS, 260–900 MPa; UHSS, 600–960 MPa. In addition to strength properties, the ductility of these steel grades is also an important parameter. AHSS steel has the best ductility, followed by HSS and UHSS. Within the HSS steel group, high-strength low-alloy (HSLA) steel represents a special subgroup characterized by the use of microalloying elements for special strength and plastic properties. An important parameter determining the strength properties of these steels is the grain-size diameter of the final structure, which depends on the processing conditions of the previous austenitic structure. The influence of reheating temperatures (TReh) and the holding time at the reheating temperature (tReh) of C–Mn–Nb–V HSLA steel was investigated in detail. Mathematical equations describing changes in the diameter of austenite grain size (dγ), depending on reheating temperature and holding time, were derived by the authors. The coordinates of the point where normal grain growth turned abnormal was determined. These coordinates for testing steel are the reheating conditions TReh = 1060 °C, tReh = 1800 s at the diameter of austenite grain size dγ = 100 μm.
The Influence of Fear Effect to a Discrete-Time Predator-Prey System with Predator Has Other Food Resource
Authors: Chen Jialin , He Xiaqing , Chen Fengde
Published: April 2021

A discrete-time predator–prey system incorporating fear effect of the prey with the predator has other food resource is proposed in this paper. The trivial equilibrium and the predator free equilibrium are both unstable. A set of sufficient conditions for the global attractivity of prey free equilibrium and interior equilibrium are established by using iteration scheme and the comparison principle of difference equations. Our study shows that due to the fear of predation, the prey species will be driven to extinction while the predator species tends to be stable since it has other food resource, i.e., the prey free equilibrium may be globally stable under some suitable conditions. Numeric simulations are provided to illustrate the feasibility of the main results.
Boolean Networks Models in Science and Engineering
Authors: Aledo Juan A. , Martinez Silvia , Valverde Jose C.
Published: April 2021

As a generalization of other notions like cellular automata or Kauffman networks appeared in the last quarter of the twentieth century, the notion of Boolean networks has undergone a special development in recent decades [...]
A Conceptual Probabilistic Framework for Annotation Aggregation of Citizen Science Data
Authors: Cerquides Jesus , Mülâyim Mehmet Oğuz , Hernández-González Jerónimo , Ravi Shankar Amudha , Fernandez-Marquez Jose Luis
Published: April 2021

Over the last decade, hundreds of thousands of volunteers have contributed to science by collecting or analyzing data. This public participation in science, also known as citizen science, has contributed to significant discoveries and led to publications in major scientific journals. However, little attention has been paid to data quality issues. In this work we argue that being able to determine the accuracy of data obtained by crowdsourcing is a fundamental question and we point out that, for many real-life scenarios, mathematical tools and processes for the evaluation of data quality are missing. We propose a probabilistic methodology for the evaluation of the accuracy of labeling data obtained by crowdsourcing in citizen science. The methodology builds on an abstract probabilistic graphical model formalism, which is shown to generalize some already existing label aggregation models. We show how to make practical use of the methodology through a comparison of data obtained from different citizen science communities analyzing the earthquake that took place in Albania in 2019.
Improving EDLC Device Performance Constructed from Plasticized Magnesium Ion Conducting Chitosan Based Polymer Electrolytes via Metal Complex Dispersion
Authors: Aziz Shujahadeen B. , Dannoun Elham M. A. , Hamsan M. H. , Abdulwahid Rebar T. , Mishra Kuldeep , Nofal Muaffaq M. , Kadir M. F. Z.
Published: April 2021

The current work shows the preparation of plasticized chitosan-magnesium acetate Mg(CH3COO)2-based polymer electrolyte dispersed with nickel (Ni) metal complexes via solution casting. Investigations of electrical and electrochemical properties of the prepared polymer composite electrolyte were carried out. The structural and optical properties of the samples were studied using X-ray diffraction (XRD) and UV-Vis spectroscopy techniques. The structural and optical outcomes revealed a clear enhancement in both absorbance and amorphous nature of the samples upon the addition of Ni metal complexes. Through the simulation of impedance data, various ion transport parameters were calculated. The electrochemical performance of the sample was examined by means of transference number measurement (TNM), linear sweep voltammetry (LSV) and cyclic voltammetry (CV) measurements. The TNM analysis confirmed the dominance of ions as the main charge carrier in the electrolyte with tion of (0.96) compared to only (0.04) for tel. The present electrolyte was stable in the range of 0 V to 2.4 V, which was obtained from linear sweep voltammetry (LSV). A result from CV proved that the electrical double-layer capacitor (EDLC) has a capacitive behavior as no redox peaks could be observed. The presence of Ni improved the charge–discharge cycle of the EDLC due to its amorphous behavior. The average performances of the EDLC were recorded as 41.7 F/g, 95%, 5.86 Wh/kg and 628 W/kg for specific capacitance, coulombic efficiency, energy and power densities, respectively. The fabricated EDLC device was found to be stable up to 1000 cycles.