bluuebunny/crossref_metadata_2025 huggingface dataset:
Acknowledgement to Reviewers of IJGI in 2020
Authors:   IJGI Editorial Office
Published: January 2021

Peer review is the driving force of journal development, and reviewers are gatekeepers who ensure that IJGI maintains its standards for the high quality of its published papers [...]
Carotenoid Biosynthesis and Plastid Development in Plants: The Role of Light
Authors: Quian-Ulloa Rocio , Stange Claudia
Published: January 2021

Light is an important cue that stimulates both plastid development and biosynthesis of carotenoids in plants. During photomorphogenesis or de-etiolation, photoreceptors are activated and molecular factors for carotenoid and chlorophyll biosynthesis are induced thereof. In fruits, light is absorbed by chloroplasts in the early stages of ripening, which allows a gradual synthesis of carotenoids in the peel and pulp with the onset of chromoplasts’ development. In roots, only a fraction of light reaches this tissue, which is not required for carotenoid synthesis, but it is essential for root development. When exposed to light, roots start greening due to chloroplast development. However, the colored taproot of carrot grown underground presents a high carotenoid accumulation together with chromoplast development, similar to citrus fruits during ripening. Interestingly, total carotenoid levels decrease in carrots roots when illuminated and develop chloroplasts, similar to normal roots exposed to light. The recent findings of the effect of light quality upon the induction of molecular factors involved in carotenoid synthesis in leaves, fruit, and roots are discussed, aiming to propose consensus mechanisms in order to contribute to the understanding of carotenoid synthesis regulation by light in plants.
Towards a Precision Medicine Approach Based on Machine Learning for Tailoring Medical Treatment in Alkaptonuria
Authors: Spiga Ottavia , Cicaloni Vittoria , Visibelli Anna , Davoli Alessandro , Paparo Maria Ausilia , Orlandini Maurizio , Vecchi Barbara , Santucci Annalisa
Published: January 2021

ApreciseKUre is a multi-purpose digital platform facilitating data collection, integration and analysis for patients affected by Alkaptonuria (AKU), an ultra-rare autosomal recessive genetic disease. It includes genetic, biochemical, histopathological, clinical, therapeutic resources and quality of life scores that can be shared among registered researchers and clinicians in order to create a Precision Medicine Ecosystem (PME). The combination of machine learning application to analyse and re-interpret data available in the ApreciseKUre shows the potential direct benefits to achieve patient stratification and the consequent tailoring of care and treatments to a specific subgroup of patients. In this study, we have developed a tool able to investigate the most suitable treatment for AKU patients in accordance with their Quality of Life scores, which indicates changes in health status before/after the assumption of a specific class of drugs. This fact highlights the necessity of development of patient databases for rare diseases, like ApreciseKUre. We believe this is not limited to the study of AKU, but it represents a proof of principle study that could be applied to other rare diseases, allowing data management, analysis, and interpretation.
T Cell Mediated Conversion of a Non-Anti-La Reactive B Cell to an Autoreactive Anti-La B Cell by Somatic Hypermutation
Authors: Bachmann Michael P. , Bartsch Tabea , Bippes Claudia C. , Bachmann Dominik , Puentes-Cala Edinson , Bachmann Jennifer , Bartsch Holger , Arndt Claudia , Koristka Stefanie , Loureiro Liliana R. , Kegler Alexandra , Laube Markus , Gross Joanne K. , Gross Tim , Kurien Biji T. , Scofield R. Hal , Farris A. Darise , James Judith A. , Schmitz Marc , Feldmann Anja
Published: January 2021

Since the first description of nuclear autoantigens in the late 1960s and early 1970s, researchers, including ourselves, have found it difficult to establish monoclonal antibodies (mabs) against nuclear antigens, including the La/SS-B (Sjögrens’ syndrome associated antigen B) autoantigen. To date, only a few anti-La mabs have been derived by conventional hybridoma technology; however, those anti-La mabs were not bona fide autoantibodies as they recognize either human La specific, cryptic, or post-translationally modified epitopes which are not accessible on native mouse La protein. Herein, we present a series of novel murine anti-La mabs including truly autoreactive ones. These mabs were elicited from a human La transgenic animal through adoptive transfer of T cells from non-transgenic mice immunized with human La antigen. Detailed epitope and paratope analyses experimentally confirm the hypothesis that somatic hypermutations that occur during T cell dependent maturation can lead to autoreactivity to the nuclear La/SS-B autoantigen.
The Protective Role of Sestrin2 in Atherosclerotic and Cardiac Diseases
Authors: Kishimoto Yoshimi , Kondo Kazuo , Momiyama Yukihiko
Published: January 2021

Atherosclerotic disease, such as coronary artery disease (CAD), is known to be a chronic inflammatory disease, as well as an age-related disease. Excessive oxidative stress produced by reactive oxygen species (ROS) contributes to the pathogenesis of atherosclerosis. Sestrin2 is an anti-oxidant protein that is induced by various stresses such as hypoxia, DNA damage, and oxidative stress. Sestrin2 is also suggested to be associated with aging. Sestrin2 is expressed and secreted mainly by macrophages, endothelial cells, and cardiomyocytes. Sestrin2 plays an important role in suppressing the production and accumulation of ROS, thus protecting cells from oxidative damage. Since sestrin2 is reported to have anti-oxidant and anti-inflammatory properties, it may play a protective role against the progression of atherosclerosis and may be a potential therapeutic target for the amelioration of atherosclerosis. Regarding the association between blood sestrin2 levels and atherosclerotic disease, the blood sestrin2 levels in patients with CAD or carotid atherosclerosis were reported to be high. High blood sestrin2 levels in patients with such atherosclerotic disease may reflect a compensatory response to increased oxidative stress and may help protect against the progression of atherosclerosis. This review describes the protective role of sestrin2 against the progression of atherosclerotic and cardiac diseases.
USP2-Related Cellular Signaling and Consequent Pathophysiological Outcomes
Authors: Kitamura Hiroshi , Hashimoto Mayuko
Published: January 2021

Ubiquitin specific protease (USP) 2 is a multifunctional deubiquitinating enzyme. USP2 modulates cell cycle progression, and therefore carcinogenesis, via the deubiquitination of cyclins and Aurora-A. Other tumorigenic molecules, including epidermal growth factor and fatty acid synthase, are also targets for USP2. USP2 additionally prevents p53 signaling. On the other hand, USP2 functions as a key component of the CLOCK/BMAL1 complex and participates in rhythmic gene expression in the suprachiasmatic nucleus and liver. USP2 variants influence energy metabolism by controlling hepatic gluconeogenesis, hepatic cholesterol uptake, adipose tissue inflammation, and subsequent systemic insulin sensitivity. USP2 also has the potential to promote surface expression of ion channels in renal and intestinal epithelial cells. In addition to modifying the production of cytokines in immune cells, USP2 also modulates the signaling molecules that are involved in cytokine signaling in the target cells. Usp2 knockout mice exhibit changes in locomotion and male fertility, which suggest roles for USP2 in the central nervous system and male genital tract, respectively. In this review, we summarize the cellular events with USP2 contributions and list the signaling molecules that are upstream or downstream of USP2. Additionally, we describe phenotypic differences found in the in vitro and in vivo experimental models.
The Effect of an Anthropogenic Magnetic Field on the Early Developmental Stages of Fishes—A Review
Authors: Formicki Krzysztof , Korzelecka-Orkisz Agata , Tański Adam
Published: January 2021

The number of sources of anthropogenic magnetic and electromagnetic fields generated by various underwater facilities, industrial equipment, and transferring devices in aquatic environment is increasing. These have an effect on an array of fish life processes, but especially the early developmental stages. The magnitude of these effects depends on field strength and time of exposure and is species-specific. We review studies on the effect of magnetic fields on the course of embryogenesis, with special reference to survival, the size of the embryos, embryonic motor function, changes in pigment cells, respiration hatching, and directional reactions. We also describe the effect of magnetic fields on sperm motility and egg activation. Magnetic fields can exert positive effects, as in the case of the considerable extension of sperm capability of activation, or have a negative influence in the form of a disturbance in heart rate or developmental instability in inner ear organs.
Molecular Dynamics Simulations of Mitochondrial Uncoupling Protein 2
Authors: Škulj Sanja , Brkljača Zlatko , Kreiter Jürgen , Pohl Elena E. , Vazdar Mario
Published: January 2021

Molecular dynamics (MD) simulations of uncoupling proteins (UCP), a class of transmembrane proteins relevant for proton transport across inner mitochondrial membranes, represent a complicated task due to the lack of available structural data. In this work, we use a combination of homology modelling and subsequent microsecond molecular dynamics simulations of UCP2 in the DOPC phospholipid bilayer, starting from the structure of the mitochondrial ATP/ADP carrier (ANT) as a template. We show that this protocol leads to a structure that is impermeable to water, in contrast to MD simulations of UCP2 structures based on the experimental NMR structure. We also show that ATP binding in the UCP2 cavity is tight in the homology modelled structure of UCP2 in agreement with experimental observations. Finally, we corroborate our results with conductance measurements in model membranes, which further suggest that the UCP2 structure modeled from ANT protein possesses additional key functional elements, such as a fatty acid-binding site at the R60 region of the protein, directly related to the proton transport mechanism across inner mitochondrial membranes.
Polyhexamethylene Guanidine Phosphate Induces Apoptosis through Endoplasmic Reticulum Stress in Lung Epithelial Cells
Authors: Jeong Mi Ho , Jeon Mi Seon , Kim Ga Eun , Kim Ha Ryong
Published: January 2021

Airway epithelial cell death contributes to the pathogenesis of lung fibrosis. Polyhexamethylene guanidine phosphate (PHMG-p), commonly used as a disinfectant, has been shown to be strongly associated with lung fibrosis in epidemiological and toxicological studies. However, the molecular mechanism underlying PHMG-p-induced epithelial cell death is currently unclear. We synthesized a PHMG-p–fluorescein isothiocyanate (FITC) conjugate and assessed its uptake into lung epithelial A549 cells. To examine intracellular localization, the cells were treated with PHMG-p–FITC; then, the cytoplasmic organelles were counterstained and observed with confocal microscopy. Additionally, the organelle-specific cell death pathway was investigated in cells treated with PHMG-p. PHMG-p–FITC co-localized with the endoplasmic reticulum (ER), and PHMG-p induced ER stress in A549 cells and mice. The ER stress inhibitor tauroursodeoxycholic acid (TUDCA) was used as a pre-treatment to verify the role of ER stress in PHMG-p-induced cytotoxicity. The cells treated with PHMG-p showed apoptosis, which was inhibited by TUDCA. Our results indicate that PHMG-p is rapidly located in the ER and causes ER-stress-mediated apoptosis, which is an initial step in PHMG-p-induced lung fibrosis.
Machine Learning Applied to the Analysis of Nonlinear Beam Dynamics Simulations for the CERN Large Hadron Collider and Its Luminosity Upgrade
Authors: Giovannozzi Massimo , Maclean Ewen , Montanari Carlo Emilio , Valentino Gianluca , Van der Veken Frederik F.
Published: January 2021

A Machine Learning approach to scientific problems has been in use in Science and Engineering for decades. High-energy physics provided a natural domain of application of Machine Learning, profiting from these powerful tools for the advanced analysis of data from particle colliders. However, Machine Learning has been applied to Accelerator Physics only recently, with several laboratories worldwide deploying intense efforts in this domain. At CERN, Machine Learning techniques have been applied to beam dynamics studies related to the Large Hadron Collider and its luminosity upgrade, in domains including beam measurements and machine performance optimization. In this paper, the recent applications of Machine Learning to the analyses of numerical simulations of nonlinear beam dynamics are presented and discussed in detail. The key concept of dynamic aperture provides a number of topics that have been selected to probe Machine Learning. Indeed, the research presented here aims to devise efficient algorithms to identify outliers and to improve the quality of the fitted models expressing the time evolution of the dynamic aperture.
Lightweight End-to-End Neural Network Model for Automatic Heart Sound Classification
Authors: Li Tao , Yin Yibo , Ma Kainan , Zhang Sitao , Liu Ming
Published: January 2021

Heart sounds play an important role in the initial screening of heart diseases. However, the accurate diagnosis with heart sound signals requires doctors to have many years of clinical experience and relevant professional knowledge. In this study, we proposed an end-to-end lightweight neural network model that does not require heart sound segmentation and has very few parameters. We segmented the original heart sound signal and performed a short-time Fourier transform (STFT) to obtain the frequency domain features. These features were sent to the improved two-dimensional convolutional neural network (CNN) model for features learning and classification. Considering the imbalance of positive and negative samples, we introduced FocalLoss as the loss function, verified our network model with multiple random verifications, and, hence, obtained a better classification result. Our main purpose is to design a lightweight network structure that is easy for hardware implementation. Compared with the results of the latest literature, our model only uses 4.29 K parameters, which is 1/10 of the size of the state-of-the-art work.
Prediction Method of Multiple Related Time Series Based on Generative Adversarial Networks
Authors: Wu Weijie , Huang Fang , Kao Yidi , Chen Zhou , Wu Qi
Published: January 2021

In multiple related time series prediction problems, the key is capturing the comprehensive influence of the temporal dependencies within each time series and the interactional dependencies between time series. At present, most time series prediction methods are difficult to capture the complex interaction between time series, which seriously affects the prediction results. In this paper, we propose a novel deep learning model Multiple Time Series Generative Adversarial Networks (MTSGAN) based on generative adversarial networks to solve this problem. MTSGAN is mainly composed of three components: interaction matrix generator, prediction generator, and time series discriminator. In our model, graph convolutional networks are used to extract interactional dependencies, and long short-term memory networks are used to extract temporal dependencies. Through the adversarial training between the generator and the discriminator, we enable the final prediction generator to generate prediction values that are very close to the true values. At last, we compare the prediction performance of the MTSGAN with other benchmarks on different datasets to prove the effectiveness of our proposed model, and we find that MTSGAN model consistently outperforms other state-of-the-art methods in the multiple related time series prediction problems.
Mechanisms of TTNtv-Related Dilated Cardiomyopathy: Insights from Zebrafish Models
Authors: Santiago Celine F. , Huttner Inken G. , Fatkin Diane
Published: January 2021

Dilated cardiomyopathy (DCM) is a common heart muscle disorder characterized by ventricular dilation and contractile dysfunction that is associated with significant morbidity and mortality. New insights into disease mechanisms and strategies for treatment and prevention are urgently needed. Truncating variants in the TTN gene, which encodes the giant sarcomeric protein titin (TTNtv), are the most common genetic cause of DCM, but exactly how TTNtv promote cardiomyocyte dysfunction is not known. Although rodent models have been widely used to investigate titin biology, they have had limited utility for TTNtv-related DCM. In recent years, zebrafish (Danio rerio) have emerged as a powerful alternative model system for studying titin function in the healthy and diseased heart. Optically transparent embryonic zebrafish models have demonstrated key roles of titin in sarcomere assembly and cardiac development. The increasing availability of sophisticated imaging tools for assessment of heart function in adult zebrafish has revolutionized the field and opened new opportunities for modelling human genetic disorders. Genetically modified zebrafish that carry a human A-band TTNtv have now been generated and shown to spontaneously develop DCM with age. This zebrafish model will be a valuable resource for elucidating the phenotype modifying effects of genetic and environmental factors, and for exploring new drug therapies.
Impact of Geometrical Imperfections on Estimation of Buckling and Limit Loads in a Silo Segment Using the Vibration Correlation Technique
Authors: Żmuda-Trzebiatowski Łukasz , Iwicki Piotr
Published: January 2021

The paper examines effectiveness of the vibration correlation technique which allows determining the buckling or limit loads by means of measured natural frequencies of structures. A steel silo segment with a corrugated wall, stiffened with cold-formed channel section columns was analysed. The investigations included numerical analyses of: linear buckling, dynamic eigenvalue and geometrically static non-linear problems. Both perfect and imperfect geometries were considered. Initial geometrical imperfections included first and second buckling and vibration mode shapes with three amplitudes. The vibration correlation technique proved to be useful in estimating limit or buckling loads. It was very efficient in the case of small and medium imperfection magnitudes. The significant deviations between the predicted and calculated buckling and limit loads occurred when large imperfections were considered.
Detector Response to D-D Neutrons and Stability Measurements with 4H Silicon Carbide Detectors
Authors: Kushoro Matteo Hakeem , Rebai Marica , Tardocchi Marco , Altana Carmen , Cazzaniga Carlo , De Marchi Eliana , La Via Francesco , Meda Laura , Meli Alessandro , Parisi Miriam , Perelli Cippo Enrico , Pillon Mario , Trotta Antonio , Tudisco Salvo , Gorini Giuseppe
Published: January 2021

The use of wide-band-gap solid-state neutron detectors is expanding in environments where a compact size and high radiation hardness are needed, such as spallation neutron sources and next-generation fusion machines. Silicon carbide is a very promising material for use as a neutron detector in these fields because of its high resistance to radiation, fast response time, stability and good energy resolution. In this paper, measurements were performed with neutrons from the ISIS spallation source with two different silicon carbide detectors together with stability measurements performed in a laboratory under alpha-particle irradiation for one week. Some consideration to the impact of the casing of the detector on the detector’s counting rate is given. In addition, the detector response to Deuterium-Deuterium (D-D) fusion neutrons is described by comparing neutron measurements at the Frascati Neutron Generator with a GEANT4 simulation. The good stability measurements and the assessment of the detector response function indicate that such a detector can be used as both a neutron counter and spectrometer for 2–4 MeV neutrons. Furthermore, the absence of polarization effects during neutron and alpha irradiation makes silicon carbide an interesting alternative to diamond detectors for fast neutron detection.
Comparison of Foam Glass-Ceramics with Different Composition Derived from Ark Clamshell (ACS) and Soda Lime Silica (SLS) Glass Bottles Sintered at Various Temperatures
Authors: Hisham Noor Aizat Noor , Zaid Mohd Hafiz Mohd , Aziz Sidek Hj Ab , Muhammad Farah Diana
Published: January 2021

Soda lime silica (SLS) waste as the source of silica (SiO2) and ark clamshell (ACS) as the foaming agent has been utilized to fabricate the low-cost and lightweight foam glass-ceramics. A series of 1 and 6 wt% foam glass-ceramics were successfully prepared by the conventional solid-state sintering method at various sintering temperatures for 60 min. The bulk density of the samples has achieved minimum density (1.014 g/cm3) with maximum expansion (62.31%) at 6 wt% of the ACS content sintered at 800 °C for 60 min. The bulk density increases while the linear shrinkage and total porosity decrease with the progression of ACS contents and sintering temperature, where the results correspond with the FESEM micrograph. The result of XRD and FTIR transmittance spectra have shown that the formation of wollastonite crystal has occurred starting at 6 wt% of the ACS content sintered at 800 °C for 30 min. The highest mechanical performance (3.90 MPa) with an average total porosity (8.04%) is observed for the sample containing 1 wt% of ACS. It can be concluded that the composition of foam glass-ceramics (1 and 6 wt%) and sintering temperatures give significant results to the structural, physical, and mechanical properties of the fabricated foam glass-ceramics.
Use of a Handheld X-ray Fluorescence Analyser to Quantify Chloride Ions In Situ: A Case Study of Structural Repair
Authors: Chinchón-Payá Servando , Torres Martín Julio E. , Rebolledo Ramos Nuria , Sánchez Montero Javier
Published: January 2021

To ensure that a structure will last throughout its service life, repairing reinforced concrete entails, among others, correctly marking off the area affected by aggressive agents that may deteriorate both the concrete and the steel. Chloride, the most damaging source of reinforcement corrosion, may diffuse to a greater or lesser distance from the surface depending on the ease of penetration. In this study, we calibrated a handheld X-ray fluorescence analyser (hXRF) and used it to quantify the chloride concentration in cement-based materials. The findings were verified against a series of samples of known concentration to establish a suitable correction factor. Chloride ions were quantified precisely and accurately with the hXRF instrument, and we calculated a correction factor of 1.16. The instrument and the information recorded were used to quantify the chloride ion content in different parts of an existing structure. The analyser identified apparently healthy areas that could, nonetheless, pose oxidation problems in the near future due to significant chloride concentration. Chloride quantification data at different depths can be used to draw diffusion or penetration profiles and to determine whether ion concentration around the reinforcement is within the recommended limits. The method developed can be applied in situ to quickly locate the most critical areas.
Correction: Wang, F., et al. Effect of Low-Frequency Electromagnetic Casting on Micro-Structure and Macro-Segregation of 5A90 Alloy Ingots. Materials 2020, 13, 2720
Authors: Wang Fuyue , Wang Xiangjie , Cui Jianzhong
Published: January 2021

In the original article [...]
Laboratory Evaluation of the Properties of Asphalt Mixture with Wood Ash Filler
Authors: Dimter Sanja , Šimun Miroslav , Zagvozda Martina , Rukavina Tatjana
Published: January 2021

Today, the road construction profession is more than ever facing limited and increasingly expensive resources for component materials of asphalt mixtures, which has also led to the need for continuous research on the use of waste materials. One such potentially usable waste material is ash obtained by the combustion of wood biomass that is used to produce heat and electricity. The goal of this paper is to ascertain the possibility of using wood ash (WA) as the filler in asphalt concrete mixtures for the base-wearing layers of a pavement. The properties of Marshall stability (MS), quotient (MQ) and deformations, and the indirect tensile strength of water-conditioned samples and dry samples were tested on asphalt samples of an AC16 surf mixture with different contents of wood ash as the filler. The obtained values of MS and MQ indicate that a 50% content of bio ash in the filler results in an increase in asphalt’s resistance to the appearance of plastic deformations and greater tensile strength and in good asphalt resistance to the action of water.
Stressing State Analysis of Reinforced Concrete Beam Strengthened by CFRP Sheet with Anchoring Device
Authors: Luo Liang , Lai Jie , Shi Jun , Sun Guorui , Huang Jie , Yuan Maoguo
Published: January 2021

This paper investigates the working performance of reinforcement concrete (RC) beams strengthened by Carbon-Fiber-Reinforced Plastic (CFRP) with different anchoring under bending moment, based on the structural stressing state theory. The measured strain values of concrete and Carbon-Fiber-Reinforced Plastic (CFRP) sheet are modeled as generalized strain energy density (GSED), to characterize the RC beams’ stressing state. Then the Mann–Kendall (M–K) criterion is applied to distinguish the characteristic loads of structural stressing state from the curve, updating the definition of structural failure load. In addition, for tested specimens with middle anchorage and end anchorage, the torsion applied on the anchoring device and the deformation width of anchoring device are respectively set parameters to analyze their effects on the reinforcement performance of CFRP sheet through comparing the strain distribution pattern of CFRP. Finally, in order to further explore the strain distribution of the cross-section and analyze the stressing-state characteristics of the RC beam, the numerical shape function (NSF) method is proposed to reasonably expand the limited strain data. The research results provide a new angle of view to conduct structural analysis and a reference to the improvement of reinforcement effect of CFRP.
Spectroscopic Ellipsometry Characterization of As-Deposited and Annealed Non-Stoichiometric Indium Zinc Tin Oxide Thin Film
Authors: Janicek Petr , Putri Maryane , Kim Ki Hwan , Lee Hye Ji , Bouska Marek , Šlang Stanislav , Lee Hee Young
Published: January 2021

A spectroscopic ellipsometry study on as-deposited and annealed non-stoichiometric indium zinc tin oxide thin films of four different compositions prepared by RF magnetron sputtering was conducted. Multi-sample analysis with two sets of samples sputtered onto glass slides and silicon wafers, together with the analysis of the samples onto each substrate separately, was utilized for as-deposited samples. Annealed samples onto the glass slides were also analyzed. Spectroscopic ellipsometry in a wide spectral range (0.2–6 eV) was used to determine optical constants (refractive index n and extinction coefficient k) of these films. Parameterized semiconductor oscillator function, together with Drude oscillator, was used as a model dielectric function. Geometrical parameters (layer thickness and surface roughness) and physical parameters (direct optical bandgap, free carrier concentration, mobility, and specific electrical resistivity) were determined from spectroscopic ellipsometry data modeling. Specific electrical resistivity determined from the Drude oscillator corresponds well with the results from electrical measurements. Change in the optical bandgap, visible especially for annealed samples, corresponds with the change of free carrier concentration (Moss–Burstein effect). Scanning electron microscope did not reveal any noticeable annealing-induced change in surface morphology.
Development of Intelligent Information System for Digital Cultural Contents
Authors: Hur Yuna , Jo Jaechoon
Published: January 2021

A significant amount of digital cultural contents is shared online, but learners do not know where subject matter content is or how to find it. Therefore, there is a need for a service to improve educational quality by effectively providing relevant information in response to searches for content that is useful to learners. This study developed and tested the usability and utility of an intelligent information system that effectively searches and visualizes digital cultural contents. The system collects data on digital cultural contents, automatically classifies them, and creates content triple data to automatically display the results with a 3D timeline, knowledge network map, and keyword relation network map through content search, triple search, and keyword search. We also conducted a survey and in-depth interviews to verify users’ satisfaction with respect to the use and utility of the system. For the experiment, we developed survey questions to measure user satisfaction and conducted in-depth interviews regarding the system’s utility with a total of 65 subjects. The results show that the response for satisfaction with regard to the use and utility was generally “satisfied”. In addition, the system stability was evaluated as “high”.
Identifying Decisive Socio-Political Sustainability Barriers in the Supply Chain of Banking Sector in India: Causality Analysis Using ISM and MICMAC
Authors: Chen Wen-Kuo , Nalluri Venkateswarlu , Lin Man-Li , Lin Ching-Torng
Published: January 2021

The banking sector often plays a crucial role in the improvement of infrastructure and economy of any country. In many emerging economies, it is apparent that a wide variety of social and political issues are related to the associated supply chain sustainability of financial service firms. Although such sustainability and its implementation issues have largely been addressed in existing research literature and in practice for many years, the attention towards socio-political sustainability aspects has been quite limited. Thus, this study attempted to explore the determinants for improving socio-political sustainability in financial service firms. Through adopting the fuzzy Delphi method (FDM), performing an exhaustive literature review, and conducting semi-structured interviews with the decision-makers of the service firms, nine key barriers for socio-political sustainability were first identified in this study. Then, the influence relationships of the key barriers were assessed by 15 experts. During the assessment process, the interrelationships and their dependence powers among key barriers were analyzed using the interpretive structural modelling (ISM) approach and cross-impact matrix multiplication applied to classification (MICMAC) methods. The assessment results show that among the studied barriers, “antisocial considerations”, “unstable political climate”, and “lack of political coherence” are the decisive barriers that affect the socio-political sustainability in the supply chain of financial service firms. The knowledge in understanding and reducing these decisive barriers can provide service sector practitioners, especially those with limited resources, the enhanced capability to conduct better planning and designing of effective and continuous improvement programs, so as to win over new consumers and retain existing clients by offering sustainable services.
High-Performance Tracking for Piezoelectric Actuators Using Super-Twisting Algorithm Based on Artificial Neural Networks
Authors: Napole Cristian , Barambones Oscar , Derbeli Mohamed , Calvo Isidro , Silaa Mohammed Yousri , Velasco Javier
Published: January 2021

Piezoelectric actuators (PEA) are frequently employed in applications where nano-Micr-odisplacement is required because of their high-precision performance. However, the positioning is affected substantially by the hysteresis which resembles in an nonlinear effect. In addition, hysteresis mathematical models own deficiencies that can influence on the reference following performance. The objective of this study was to enhance the tracking accuracy of a commercial PEA stack actuator with the implementation of a novel approach which consists in the use of a Super-Twisting Algorithm (STA) combined with artificial neural networks (ANN). A Lyapunov stability proof is bestowed to explain the theoretical solution. Experimental results of the proposed method were compared with a proportional-integral-derivative (PID) controller. The outcomes in a real PEA reported that the novel structure is stable as it was proved theoretically, and the experiments provided a significant error reduction in contrast with the PID.
Marine Biotechnology: Challenges and Development Market Trends for the Enhancement of Biotic Resources in Industrial Pharmaceutical and Food Applications. A Statistical Analysis of Scientific Literature and Business Models
Authors: Daniotti Sara , Re Ilaria
Published: January 2021

Biotechnology is an essential tool for the sustainable exploitation of marine resources, although the full development of their potential is complicated by a series of cognitive and technological limitations. Thanks to an innovative systematic approach that combines the meta-analysis of 620 articles produced worldwide with 29 high TRL (Technology Readiness Level) European funded projects, the study provides an assessment of the growth prospects of blue biotechnologies, with a focus on pharmaceutical and food applications, and the most promising technologies to overcome the main challenges in the commercialization of marine products. The results show a positive development trend, with publications more than doubled from 2010 (36) to 2019 (70). Biochemical and molecular characterization, with 150 studies, is the most widely used technology. However, the emerging technologies in basic research are omics technologies, pharmacological analysis and bioinformatics, which have doubled the number of publications in the last five years. On the other hand, technologies for optimizing the conditions of cultivation, harvesting and extraction are central to most business models with immediate commercial exploitation (65% of high-TRL selected projects), especially in food and nutraceutical applications. This research offers a starting point for future research to overcome all those obstacles that restrict the marketing of products derived from organisms.
Acknowledgment to Reviewers of Metabolites in 2020
Authors:   Metabolites Editorial Office
Published: January 2021

Peer review is the driving force of journal development, and reviewers are gatekeepers who ensure that Metabolites maintains its standards for the high quality of its published papers [...]
The Diabetic Lung: Insights into Pulmonary Changes in Children and Adolescents with Type 1 Diabetes
Authors: Mameli Chiara , Ghezzi Michele , Mari Alessandra , Cammi Giulia , Macedoni Maddalena , Redaelli Francesca Chiara , Calcaterra Valeria , Zuccotti Gianvincenzo , D’Auria Enza
Published: January 2021

Historically, the lung was not listed and recognized as a major target organ of diabetic injury. The first evidence of diabetic lung involvement was published fifty years ago, with a study conducted in a population of young adults affected by type 1 diabetes (T1D). In recent years, there has been mounting evidence showing that the lung is a target organ of diabetic injury since the beginning of the disease—at the pediatric age. The deeply branched vascularization of the lungs and the abundance of connective tissue, indeed, make them vulnerable to the effects of hyperglycemia, in a way similar to other organs affected by microvascular complications. In this review, we focus on pulmonary function impairment in children and adolescents affected by T1D. We also cover controversial aspects regarding available studies and future perspectives in this field.
The Correctness of the Simplified Bernoulli Trial (SBT) Collision Scheme of Calculations of Two-Dimensional Flows
Authors: Shterev Kiril
Published: January 2021

Micro-electromechanical systems (MEMS) have developed rapidly in recent years in various technical fields that have increased their interest in the Direct Simulation Monte Carlo (DSMC) method. In this paper, we present a simple representation of the DSMC collision scheme and investigate the correctness of the Simplified Bernoulli Trial (SBT) collision scheme for the calculation of two-dimensional flows. The first part of the collision scheme, which determines collision pairs, is presented following the derivation of the expression for the mean free path and using the cumulative distribution function. Approaches and conclusions based on one-dimensional flows are not always directly applicable to two- and three-dimensional flows. We investigated SBT correctness by using the two-dimensional pressure-driven gas flow of monoatomic gas as a test case. We studied the influence of shuffling of the list of particles per cell (PPC) before the collision scheme’s execution, as well as the minimal and maximal number of PPC, on the correctness of the solution. The investigation showed that shuffling and the number of PPC played an important role in the correctness of SBT. Our recommendations are straightforwardly applicable to three-dimensional flows. Finally, we considered the mixing of two gases and compared the results available in the literature.
Next-Generation Diamond Electrodes for Neurochemical Sensing: Challenges and Opportunities
Authors: Purcell Erin , Becker Michael , Guo Yue , Hara Seth , Ludwig Kip , McKinney Collin , Monroe Elizabeth , Rechenberg Robert , Rusinek Cory , Saxena Akash , Siegenthaler James , Sortwell Caryl , Thompson Cort , Trevathan James , Witt Suzanne , Li Wen
Published: January 2021

Carbon-based electrodes combined with fast-scan cyclic voltammetry (FSCV) enable neurochemical sensing with high spatiotemporal resolution and sensitivity. While their attractive electrochemical and conductive properties have established a long history of use in the detection of neurotransmitters both in vitro and in vivo, carbon fiber microelectrodes (CFMEs) also have limitations in their fabrication, flexibility, and chronic stability. Diamond is a form of carbon with a more rigid bonding structure (sp3-hybridized) which can become conductive when boron-doped. Boron-doped diamond (BDD) is characterized by an extremely wide potential window, low background current, and good biocompatibility. Additionally, methods for processing and patterning diamond allow for high-throughput batch fabrication and customization of electrode arrays with unique architectures. While tradeoffs in sensitivity can undermine the advantages of BDD as a neurochemical sensor, there are numerous untapped opportunities to further improve performance, including anodic pretreatment, or optimization of the FSCV waveform, instrumentation, sp2/sp3 character, doping, surface characteristics, and signal processing. Here, we review the state-of-the-art in diamond electrodes for neurochemical sensing and discuss potential opportunities for future advancements of the technology. We highlight our team’s progress with the development of an all-diamond fiber ultramicroelectrode as a novel approach to advance the performance and applications of diamond-based neurochemical sensors.
Influence of Characteristics of Thermoplastic Polyurethane on Graphene-Thermoplastic Polyurethane Composite Film
Authors: Zhou Zhi-Min , Wang Ke , Lin Kai-wen , Wang Yue-Hui , Li Jing-Ze
Published: January 2021

Graphene-thermoplastic polyurethane (G-TPU) composite films were fabricated by traditional blending method and tape casting process with commercial graphene sheets as functional fillers and TPU masterbatches of four different melting points as matrix, respectively. The effects of matrix on the distribution of graphene, the electrical conductivity, and infrared (IR) light thermal properties of the G-TPU composite films were investigated. The experimental results reveal that the characteristics of TPU has little influence on the electrical conductivity of the G-TPU composite films, although the four TPU solutions have different viscosities. However, under the same graphene mass content, the thermal conductivity of four G-TPU composite films with different melting points is significantly different. The four kinds of G-TPU composite films have obvious infrared (IR) thermal effect. There is little difference in the temperatures between the composite films prepared by TPU with melting a point of 100 °C, 120 °C, and 140 °C, respectively; however, when the content of graphene is less than 5 wt%, the temperature of the composite film prepared by TPU with a melting point of 163 °C is obviously lower than that of the other three composite films. The possible reason for this phenomenon is related to the structure of TPU.
Surface Modification of PDMS-Based Microfluidic Devices with Collagen Using Polydopamine as a Spacer to Enhance Primary Human Bronchial Epithelial Cell Adhesion
Authors: Dabaghi Mohammadhossein , Shahriari Shadi , Saraei Neda , Da Kevin , Chandiramohan Abiram , Selvaganapathy Ponnambalam Ravi , Hirota Jeremy A.
Published: January 2021

Polydimethylsiloxane (PDMS) is a silicone-based synthetic material used in various biomedical applications due to its properties, including transparency, flexibility, permeability to gases, and ease of use. Though PDMS facilitates and assists the fabrication of complicated geometries at micro- and nano-scales, it does not optimally interact with cells for adherence and proliferation. Various strategies have been proposed to render PDMS to enhance cell attachment. The majority of these surface modification techniques have been offered for a static cell culture system. However, dynamic cell culture systems such as organ-on-a-chip devices are demanding platforms that recapitulate a living tissue microenvironment’s complexity. In organ-on-a-chip platforms, PDMS surfaces are usually coated by extracellular matrix (ECM) proteins, which occur as a result of a physical and weak bonding between PDMS and ECM proteins, and this binding can be degraded when it is exposed to shear stresses. This work reports static and dynamic coating methods to covalently bind collagen within a PDMS-based microfluidic device using polydopamine (PDA). These coating methods were evaluated using water contact angle measurement and atomic force microscopy (AFM) to optimize coating conditions. The biocompatibility of collagen-coated PDMS devices was assessed by culturing primary human bronchial epithelial cells (HBECs) in microfluidic devices. It was shown that both PDA coating methods could be used to bind collagen, thereby improving cell adhesion (approximately three times higher) without showing any discernible difference in cell attachment between these two methods. These results suggested that such a surface modification can help coat extracellular matrix protein onto PDMS-based microfluidic devices.
Towards Iron-Titanium Oxide Nanostructures from Ecuadorian Black Mineral Sands
Authors: Lagos Karina J. , Marinkovic Bojan A. , Debut Alexis , Vizuete Karla , Guerrero Víctor H. , Pardo Emilio , Pontón Patricia I.
Published: January 2021

Ecuadorian black mineral sands were used as starting material for the production of iron-titanium oxide nanostructures. For this purpose, two types of mineral processing were carried out, one incorporating a pre-treatment before conducting an alkaline hydrothermal synthesis (NaOH 10 M at 180 °C for 72 h), and the other prescinding this first step. Nanosheet-assembled flowers and nanoparticle agglomerates were obtained from the procedure including the pre-treatment. Conversely, nanobelts and plate-like particles were prepared by the single hydrothermal route. The nanoscale features of the product morphologies were observed by scanning electron microscopy (SEM) and transmission electron microscopy (TEM) analyses. The ilmenite and hematite molar fractions, within the ilmenite-hematite solid solution, in the as-synthetized samples were estimated by Brown’s approach using the computed values of unit-cell volumes from Le Bail adjustments of X-ray powder diffraction (XRPD) patterns. The resulting materials were mainly composed of Fe-rich ilmenite-hematite solid solutions (hematite molar contents ≥0.6). Secondary phases, which possibly belong to lepidocrocite-like or corrugated titanate structures, were also identified. The current study demonstrated the feasibility of employing Ecuadorian mineral resources as low-cost precursors to synthesize high-added-value nanostructures with promising applications in several fields.
The Pharmaceutical Industry in 2020. An Analysis of FDA Drug Approvals from the Perspective of Molecules
Authors: de la Torre Beatriz G. , Albericio Fernando
Published: January 2021

Although the pharmaceutical industry will remember 2020 as the year of COVID-19, it is important to highlight that this year has been the second-best—together with 1996—in terms of the number of drugs accepted by the US Food and Drug Administration (FDA). Each of these two years witnessed the authorization of 53 drugs—a number surpassed only in 2018 with 59 pharmaceutical agents. The 53 approvals in 2020 are divided between 40 new chemical entities and 13 biologic drugs (biologics). Of note, ten monoclonal antibodies, two antibody–drug conjugates, three peptides, and two oligonucleotides have been approved in 2020. Close inspection of the so-called small molecules reveals the significant presence of fluorine atoms and/or nitrogen aromatic heterocycles. This report analyzes the 53 new drugs of the 2020 harvest from a strictly chemical perspective, as it did for those authorized in the previous four years. On the basis of chemical structure alone, the drugs that received approval in 2020 are classified as the following: biologics (antibodies, antibody-drug conjugates, and proteins); TIDES (peptide and oligonucleotides); natural products; fluorine-containing molecules; nitrogen aromatic heterocycles; and other small molecules.
Analyzing Kinase Similarity in Small Molecule and Protein Structural Space to Explore the Limits of Multi-Target Screening
Authors: Schmidt Denis , Scharf Magdalena M. , Sydow Dominique , Aßmann Eva , Martí-Solano Maria , Keul Marina , Volkamer Andrea , Kolb Peter
Published: January 2021

While selective inhibition is one of the key assets for a small molecule drug, many diseases can only be tackled by simultaneous inhibition of several proteins. An example where achieving selectivity is especially challenging are ligands targeting human kinases. This difficulty arises from the high structural conservation of the kinase ATP binding sites, the area targeted by most inhibitors. We investigated the possibility to identify novel small molecule ligands with pre-defined binding profiles for a series of kinase targets and anti-targets by in silico docking. The candidate ligands originating from these calculations were assayed to determine their experimental binding profiles. Compared to previous studies, the acquired hit rates were low in this specific setup, which aimed at not only selecting multi-target kinase ligands, but also designing out binding to anti-targets. Specifically, only a single profiled substance could be verified as a sub-micromolar, dual-specific EGFR/ErbB2 ligand that indeed avoided its selected anti-target BRAF. We subsequently re-analyzed our target choice and in silico strategy based on these findings, with a particular emphasis on the hit rates that can be expected from a given target combination. To that end, we supplemented the structure-based docking calculations with bioinformatic considerations of binding pocket sequence and structure similarity as well as ligand-centric comparisons of kinases. Taken together, our results provide a multi-faceted picture of how pocket space can determine the success of docking in multi-target drug discovery efforts.