bluuebunny/crossref_metadata_2025 huggingface dataset:
Aptamer-Based Biosensors for the Analytical Determination of Bisphenol A in Foodstuffs
Authors: Schiano Marica Erminia , Abduvakhidov Avazbek , Varra Michela , Albrizio Stefania
Published: April 2022

Bisphenol A (BPA) is a synthetic compound utilized to manufacture plastics for Food Contact Materials (FCMs) or resins for the inside of food containers. Since it was recognized as an Endocrine-Disrupting Chemical (EDC), its implications in pathologies, such as cancer, obesity, diabetes, immune system alterations, and developmental and mental disorders, have been widely documented. Diet is considered the main source of exposure for humans to BPA. Consequently, continuous monitoring of the levels of BPA in foods is necessary to assess the risk associated with its consumption in one’s diet. So far, many reviews have been published on biosensors and aptamer-based biosensors, but none of them focus on their applications in their analyses of bisphenols in food matrices. With this review, the authors aim to fill this gap and to take a snapshot of the current state-of-the-art research on aptasensors designed to detect BPA in food matrices. Given that a new TDI value has recently been proposed by the EFSA (0.04 ng/kg), the search for new sensitive tools for the quantitative analysis of BPA is more topical and urgent than ever. From this perspective, aptasensors prove to be a good alternative to traditional analytical techniques for determining BPA levels in food.
Monitoring of Geomagnetic and Telluric Field Disturbances in the Russian Arctic
Authors: Kozyreva Olga V. , Pilipenko Vyacheslav A. , Marshalko Elena E. , Sokolova Elena Yu. , Dobrovolsky Mikhail N.
Published: April 2022

The influence of space factors on technological systems in the Arctic (power transmission lines, oil/gas pipelines) has become critically important. To examine in depth these effects, an archive of digital 1 min data from Soviet/Russian magnetic stations deployed along the Arctic coast was created, starting from 1983 to the present. All data from various sources were converted to daily files in standard IAGA-2002 format and supplemented with quick-look magnetograms. Some of these data are included already in the existing world magnetic field databases, but not all. Examples of disturbances known to excite intense geomagnetically induced currents in power transmission lines were presented: irregular Pi3 pulsations and magnetic perturbation events. The database was augmented with the global 3D model of the Earth’s conductivity structure. The given example showed how the combined usage of the geomagnetic field database and the conductivity model enables one to synthesize the geoelectric field response to geomagnetic variations, and to assess the distortions of the pipeline-soil potential. To determine regions most susceptible to geomagnetic hazard, a map with normalized telluric fields was created for a uniform sinusoidally varying magnetic disturbance. This map showed that the largest electrotelluric potentials and field are induced in regions with a high resistivity (e.g., Kola Peninsula and Ural Mountains). This database can be also a useful support for space missions in the magnetosphere. The database is publicly available on the anonymous FTP site.
Tunable Beam Splitter Based on Acoustic Binary Metagrating
Authors: Liu Zhengang , Ju Fangfang , Qian Shengyou , Liu Xiaojun
Published: April 2022

As an inversely designed artificial surface, acoustic metasurfaces usually consist of subwavelength unit cells in an array configuration, exhibiting exceptional abilities in acoustic wave manipulation. In contrast to metasurfaces with subwavelength units and complex configurations, we propose here a comprehensive concept of a beam splitter based on an acoustic binary metagrating (ABM), capable of splitting a given acoustic wave into two predesigned directions. The ABM is composed of only two kinds of elements, corresponding to the elements “0” and “1”, respectively. The diffraction orders in the ABM take a value of n = −1 (split beam 1) and n = 1 (split beam 2), and hence, the beam splitting occurs. We exemplify the ABM by etching only one straight-walled groove per period on a planar hard surface. In our design, the reflected angles of these two split beams can be readily controlled by setting a proper incident angle. Theoretical analysis and numerical simulations were undertaken to provide the proof of concept for the proposed acoustic beam splitter.
Generative Adversarial Networks for Zero-Shot Remote Sensing Scene Classification
Authors: Li Zihao , Zhang Daobing , Wang Yang , Lin Daoyu , Zhang Jinghua
Published: April 2022

Deep learning-based methods succeed in remote sensing scene classification (RSSC). However, current methods require training on a large dataset, and if a class does not appear in the training set, it does not work well. Zero-shot classification methods are designed to address the classification for unseen category images in which the generative adversarial network (GAN) is a popular method. Thus, our approach aims to achieve the zero-shot RSSC based on GAN. We employed the conditional Wasserstein generative adversarial network (WGAN) to generate image features. Since remote sensing images have inter-class similarity and intra-class diversity, we introduced classification loss, semantic regression module, and class-prototype loss to constrain the generator. The classification loss was used to preserve inter-class discrimination. We used the semantic regression module to ensure that the image features generated by the generator can represent the semantic features. We introduced class-prototype loss to ensure the intra-class diversity of the synthesized image features and avoid generating too homogeneous image features. We studied the effect of different semantic embeddings for zero-shot RSSC. We performed experiments on three datasets, and the experimental results show that our method performs better than the state-of-the-art methods in zero-shot RSSC in most cases.
The Association of Gender and Body Mass Index on the Values of Static and Dynamic Balance of University Students (A Cross-Sectional Design Study)
Authors: Mocanu George Danut , Murariu Gabriel
Published: April 2022

The balance of the body conditions the quality and efficiency of the movements in daily and sports activities, its impairment generating problems in the manifestation of motor skills for all age groups. The aim of this study is to analyze how the gender and BMI values of university students influence the results of the static and dynamic balance tests applied. The investigated group consists of 195 undergraduate students, from various specializations of the Dunărea de Jos University in Galați (99 males and 96 females, ages = 20.16 ± 1.98, BMI = 24.15 ± 5.68). The independent variables gender and BMI levels (underweight, normal weight and overweight/obese) were defined. The participants were evaluated in May 2019 using a series of 7 tests: one leg standing test with eyes closed, stork test, flamingo test, Bass test, functional reach test, walk and turn field sobriety test and Fukuda test. The results provided using multivariate analysis (MANOVA) indicate balanced performance for the gender variable, but with significantly better values for women in the one leg standing test, flamingo test and functional reach test (F values are associated with thresholds p < 0.05). Men obtain slightly better, but statistically insignificant (p > 0.05), performances on the stork test, Bass test and Fukuda test. The BMI step comparison confirms the difficulties of the overweight group in assessing balance, with the lowest scores in maintaining static positions and the most errors in dynamic balance tests, with significant differences from normal and underweight in most tests (p < 0.05). An interesting aspect is the slightly superior performance of the underweight compared to the normal weight group, for the one leg standing test, flamingo test and walk and turn field sobriety test. The analysis of Spearman correlation coefficients indicates a number of significant associations between elevated BMI values and decreased performance on balance tests.
Structural Behaviour of Axially Loaded Concrete-Filled Steel Tube Columns during the Top-Down Construction Method
Authors: Lazovic Radovanovic Marija M. , Nikolic Jelena Z. , Radovanovic Janko R. , Kostic Svetlana M.
Published: April 2022

The paper discusses the structural behaviour of concrete-filled steel tube columns (CFT) when applied to the top-down construction method as temporary internal supports for ceilings. Their ultimate capacity to take into account the actual boundary conditions of the column is essential for successful application in construction. The paper presents the full-scale in situ testing of four slender specimens with variable D/t ratios under concentric axial loading. The CFT columns were supported on the previously jacked concrete piles. In addition, detailed finite element numerical models in ABAQUS and PLAXIS computer programs were developed. The models include the nonlinear behaviour of materials and the nonlinear behaviour of soil. The soil–pile–column interaction and impact of the CFT column–pile connection stiffness on global column stability were considered. The numerical model was validated by comparison with the experimental results. In conclusion, the coefficient for the effective buckling length of the studied columns is proposed. Finally, the experimental results of the critical buckling forces were compared with widely used international design codes Eurocode 4-EC4, American standard-ACI and the Australian standard-AS.
Continuous Estimation of Finger and Wrist Joint Angles Using a Muscle Synergy Based Musculoskeletal Model
Authors: He Zixun , Qin Zixuan , Koike Yasuharu
Published: April 2022

Recently, many muscle synergy-based human motion prediction models and algorithms have been proposed. In this study, the muscle synergies extracted from electromyography (EMG) data were used to construct a musculoskeletal model (MSM) to predict the joint angles of the wrist, thumb, index finger, and middle finger. EMG signals were analyzed using independent component analysis to reduce signal noise and task-irrelevant artifacts. The weights of each independent component (IC) were converted into a heat map related to the motion pattern and compared with human anatomy to find a different number of ICs matching the motion pattern. Based on the properties of the MSM, non-negative matrix factorization was used to extract muscle synergies from selected ICs that represent the extensor and flexor muscle groups. The effects of these choices on the prediction accuracy was also evaluated. The performance of the model was evaluated using the correlation coefficient (CC) and normalized root-mean-square error (NRMSE). The proposed method has a higher prediction accuracy than those of traditional methods, with an average CC of 92.0% and an average NRMSE of 10.7%.
A Novel Data Augmentation-Based Brain Tumor Detection Using Convolutional Neural Network
Authors: Alsaif Haitham , Guesmi Ramzi , Alshammari Badr M. , Hamrouni Tarek , Guesmi Tawfik , Alzamil Ahmed , Belguesmi Lamia
Published: April 2022

Brain tumor is a severe cancer and a life-threatening disease. Thus, early detection is crucial in the process of treatment. Recent progress in the field of deep learning has contributed enormously to the health industry medical diagnosis. Convolutional neural networks (CNNs) have been intensively used as a deep learning approach to detect brain tumors using MRI images. Due to the limited dataset, deep learning algorithms and CNNs should be improved to be more efficient. Thus, one of the most known techniques used to improve model performance is Data Augmentation. This paper presents a detailed review of various CNN architectures and highlights the characteristics of particular models such as ResNet, AlexNet, and VGG. After that, we provide an efficient method for detecting brain tumors using magnetic resonance imaging (MRI) datasets based on CNN and data augmentation. Evaluation metrics values of the proposed solution prove that it succeeded in being a contribution to previous studies in terms of both deep architectural design and high detection success.
Deep Learning Algorithm for Heart Valve Diseases Assisted Diagnosis
Authors: Flores-Alonso Santiago Isaac , Tovar-Corona Blanca , Luna-García René
Published: April 2022

Heart sounds are mainly the expressions of the opening and closing of the heart valves. Some sounds are produced by the interruption of laminar blood flow as it turns into turbulent flow, which is explained by abnormal functioning of the valves. The analysis of the phonocardiographic signals has made it possible to indicate that the normal and pathological records differ from each other concerning both temporal and spectral features. The present work describes the design and implementation based on deep neural networks and deep learning for the binary and multiclass classification of four common valvular pathologies and normal heart sounds. For feature extraction, three different techniques were considered: Discrete Wavelet Transform, Continuous Wavelet Transform and Mel Frequency Cepstral Coefficients. The performance of both approaches reached F1 scores higher than 98% and specificities in the “Normal” class of up to 99%, which considers the cases that can be misclassified as normal. These results place the present work as a highly competitive proposal for the generation of systems for assisted diagnosis.
Causality in Control Systems Based on Data-Driven Oscillation Identification
Authors: Falkowski Michał J. , Domański Paweł D. , Pawłuszewicz Ewa
Published: April 2022

This paper addresses the subject of causality analysis using simulation data and data collected from a real control system. Simulated data includes Gaussian and Cauchy noise signals. Real-time series include various, mostly unknown distortions, like trends, oscillations, and noises. Presented research focuses on the oscillatory component in data and its propagation in multi-loop control systems. Oscillation identification is based on a deep decomposition process for control error time series. Identified periodic signals are used for further causality processing. The analysis uses the Transfer Entropy approach. This method belongs to the group of model-free methods. The determination of information pathways is conducted without any model or a priori process knowledge. The research investigates the impact of the oscillation time-series component on the Transfer Entropy causality analysis. The summary shows the observations obtained for given simulated datasets and those collected from real processes. The obtained results show that simulated analysis works properly. On the contrary, the direct application of the oscillation decomposition in real industrial cases may be misleading. Large datasets demand modification in the methodology. Different variants are tested. They show that oscillation propagation is biased in real systems and, therefore, the decomposition should be applied with caution. Furthermore, it is important to remember that the algorithm transition from simulated data to real industrial ones is demanding and should be done with the utmost care.
From Teachers’ Perspective: Can an Online Digital Competence Certification System Be Successfully Implemented in Schools?
Authors: Balaban Igor , Sobodić Aleksandra
Published: April 2022

This study aims to assess the implementation effectiveness of the online platform for digital competence (DC) certification in schools. The testing platform was a prototype of a DC certification system developed and piloted during 2019 in primary and secondary schools in six European countries involving more than 800 teachers and 6000 students. The study resulted in positive proof that the effective integration and evaluation of the DC acquisition, evaluation, and certification within formal curricula in primary and secondary schools is possible. In addition, it was confirmed that information quality is a significant predictor of the impact on the platform end-users. In contrast, the quality of service is not a significant predictor of a successful implementation of the cloud-based platform with an intuitive user interface and proper online help, i.e., massive open online courses (MOOCs). Furthermore, the developed instrument can help schools implement and assess platforms for DC certification and help policymakers pursue and monitor the implementation of such platforms in schools.
Digestate-Derived Ammonium Fertilizers and Their Blends as Substitutes to Synthetic Nitrogen Fertilizers
Authors: Saju Amrita , Ryan Demi , Sigurnjak Ivona , Germaine Kieran , Dowling David N. , Meers Erik
Published: April 2022

Nutrient recovery from biomass streams generates novel recycling-derived fertilizers (RDFs). The effect of RDFs depends on their nutrient content and variability, which can aid or hinder their use by end-users. Detailed characterization of RDFs can help in evaluating product properties, whereas blending RDFs can optimize their nutrient ratios and reduce nutrient variability. This study assesses ammonium nitrate (AN) from stripping-scrubbing, ammonium water (AW) and concentrate (CaE) from evaporation, and two tailor-made blends (AN + CaE and AW + CaE), for their potential as nitrogen (N) fertilizers in the pot cultivation of lettuce. Parallelly, a soil incubation experiment was conducted to investigate the N release dynamics of the tested RDFs. The RDFs were compared against the commercial calcium ammonium nitrate (CAN) and an unfertilized control. AN and AW fertilization resulted in a similar crop yield and N uptake to the CAN treatment. CaE and blends exhibited poor yield and N uptake, possibly due to the sodium toxicity detected. AN and AW displayed N fertilizer replacement values above 100%, whereas CaE and blends exhibited poor results in the current experiments. The soil incubation experiment showed a positive soil priming effect in AN and AW treatment, as their N release was over 100%. Further research under uncontrolled field conditions utilizing AN and AW for diverse crop types can validate their N replacement potential.
Load-Carrying Capacity of Bailey Bridge in Civil Applications
Authors: Prokop Jozef , Odrobiňák Jaroslav , Farbák Matúš , Novotný Vladimír
Published: April 2022

The paper presents an extensive study aimed to determine the applicability of the demountable Bailey bridge (BB) system on construction sites or in other temporary conditions while meeting the regulations for the design and assessment of steel bridges. The analysis is focused on whether and to what extent the BB system with spans between 12 and 36 m is usable for on-site freight transport with conventional lorries with a total weight of up to 22–28 tons. At the same time, the BB system within these spans should be utilized for construction vehicles with a total weight of up to 32–40 tons. To calculate the load-carrying capacity, spatial numerical models were analysed using FEM and procedures of actual design codes were utilized. In the case of the main girders, analysis is focused on the out-of-plane stability of their compressed chords. Recommendations for the use of this bridge system in different arrangements of the main girder and bridge deck are then summarized and discussed.
A Deadbeat Current and Flux Vector Control for IPMSM Drive with High Dynamic Performance
Authors: Ton That-Dong , Hsieh Min-Fu
Published: April 2022

In this paper, a new deadbeat stator current and flux linkage vector control (DB-CFVC) scheme for interior permanent magnet synchronous machines (IPMSM) is proposed. The control structure is simplified by implementing the proposed flux linkage vector control method in the α-β stationary coordinate. Unlike conventional deadbeat methods, the dynamic performance of the proposed DB-CFVC can be enhanced while voltage command saturation and over output current are avoided. This is achieved with a “reinforced” phase angle reference of stator flux linkage vector by considering rotor speed error and maximum voltage to properly enhance the quality of the calculated flux phase angle command. By predicting stator flux linkage and current in the stationary coordinate, the deadbeat direct flux linkage vector control based on the one-step delay compensation strategy becomes straightforward and exhibits low sensitivity to motor parameters compared to conventional methods performed in the rotating frame. Then, by developing a practical and robust hybrid flux linkage observer, the proposed DB-CFVC method can work more reliably and effectively than conventional methods. Simulations and experiments are conducted in a drive system for an IPMSM to evaluate the effectiveness and reliability of the proposed method.
GNSS Signal Distortion Estimation: A Comparative Analysis of L5 Signal from GPS II and GPS III
Authors: Wang Meng , Lu Xiaochun , Rao Yongnan
Published: April 2022

The nonlinear navigation payload transmission channel introduces errors at a system level, resulting in a distortion of the received signal and affecting differential positioning users. This work models the transmission channel of the navigation payload and uses the joint estimation algorithm to calculate the digital distortion and analog channel response of the transmission channel from the received signal. On the above basis, the algorithm and model are verified by GPS-L5 measured data, and the channel characteristics of GPS II and GPS III are deeply analyzed. The results show that the existing GPS IIF satellites have a digital distortion, which is negligible in GPS III satellites. Regarding the analog channel response, GPS III has better amplitude and group delay consistency than GPS II. Lastly, the ranging bias caused by the transmission channel of the navigation payload is provided to the user for reference, and GPS III is improved by approximately 0.02 m compared with GPS II. This study provides support for adjusting the satellite signal pre-distortion and enriches subsequent GNSS signal quality assessment work; it can also be used as a reference for differential positioning users.
Measuring the Critical Influence Factors for Predicting Carbon Dioxide Emissions of Expanding Megacities by XGBoost
Authors: Zhang Jianxun , Zhang He , Wang Rui , Zhang Mengxiao , Huang Yazhe , Hu Jiahui , Peng Jingyi
Published: April 2022

CO2 is the main greenhouse gas. Urban spatial development, land use, and so on may be affected by CO2 and climate change. The main questions studied in this paper are as follows: What are the drivers of CO2 emissions of expanding megacities? How can they be analyzed from different perspectives? Do the results differ for megacities at different stages of development? Based on the XGBoost model, this paper explored the complex factors affecting CO2 emissions by using data of four Chinese megacities, Beijing, Tianjin, Shanghai, and Chongqing, from 2003 to 2017. The main findings are as follows: The XGBoost model has better applicability and accuracy in predicting carbon emissions of expanding megacities, with root mean square error (RMSE) as low as 0.036. Under the synergistic effect of multiple factors, population, land size, and gross domestic product are still the primary driving forces of CO2 emissions. Population density and population become more important in the single-factor analysis. The key drivers of CO2 emissions in megacities at respective developmental stages are different. This paper provides methods and tools for accurately predicting CO2 emissions and measuring the critical drivers. Furthermore, it could provide decision support for megacities to make targeted carbon-emission-reduction strategies based on their own developmental stages.
Extreme Rainfall Simulations with Changing Resolution of Orography Based on the Yin-He Global Spectrum Model: A Case Study of the Zhengzhou 20·7 Extreme Rainfall Event
Authors: Wang Yingjie , Wu Jianping , Peng Jun , Yang Xiangrong , Liu Dazheng
Published: April 2022

In recent years, the study of numerical weather prediction (NWP) in complex orographic areas has attracted a great deal of attention. Complex orography plays an important role in the occurrence and development of extreme rainfall events. In this study, the Yin–He Global Spectrum Model (YHGSM) was used, and the wave number truncation method was employed to decompose the orographic data to different resolutions. The obtained orographic data with different resolutions were used to simulate the extreme rainfall in Zhengzhou, Henan Province, China, to discuss the degree of influence and mechanism of the different orographic resolutions on the extreme rainfall. The results show that the simulation results of the YHGSM with high-resolution orography are better than those of the low-resolution orography in terms of the rainfall intensity and range. When the rainfall intensity is higher, the results of the low-resolution orography simulated the rainfall range of big heavy rainfall better. The orography mainly affected the rainfall by affecting the velocity of the updraft, but it had a limited influence on the maximum height that the updraft could reach. A strong updraft is one of the key factors leading to extreme rainfall in Henan Province. When the orographic resolution changes, the sensitivity of the vertical velocity of the updraft to the orographic resolution is the greatest, the sensitivity of the upper-air divergence and low-level vorticity to the orographic resolution is lower than that of the vertical velocity. In conclusion, the high-resolution orography is helpful in improving the model’s prediction of extreme rainfall, and when predicting extreme rainfall in complex orographic areas, forecasters may need to artificially increase rainfall based on model results.
Two Open Problems on CA-Groupoids and Cancellativities of T2CA-Groupoids
Authors: An Xiaogang , Zhang Xiaohong , Ma Zhirou
Published: April 2022

Cyclic associative groupoids (CA-groupoids) and Type-2 cyclic associative groupoids (T2CA-groupoids) are two types of non-associative groupoids which satisfy cyclic associative law and type-2 cyclic associative law, respectively. In this paper, we prove two theorems that weak cancellativity is cancellativity and right quasi-cancellativity is left quasi-cancellativity in a CA-groupoid, thus successfully solving two open problems. Moreover, the relationships among separativity, quasi-cancellativity and commutativity in a CA-groupoid are discussed. Finally, we study the various cancellativities of T2CA-groupoids such as power cancellativity, quasi-cancellativity and cancellativity. By determining the relationships between them, we can illuminate the structure of T2CA-groupoids.
Application of Loop-Mediated Isothermal Amplification (LAMP) in Sex Identification of Parrots Bred in Egypt
Authors: Elnomrosy Sara M. , Hagag Naglaa M. , AbdAllah Mohamed I. , Kolenda Rafał , Zacharski Maciej
Published: April 2022

Over 400 of the 3800 tropical avian species are endangered or threatened. One of many solutions to conserve animal biodiversity is breeding animals in zoos or private animal farms. Animal breeding programs are difficult to implement in species with sexual monomorphism, such as parrots. Molecular biology methods offer a solution to determine the sex of these species. Therefore, in this study, we aimed to test the performance of PCR and LAMP techniques on sex identification for 21 parrot species belonging to three families, i.e., Psittacidae, Cacatuidae, and Psittaculidae. We established a protocol for DNA isolation from feathers in our laboratory and found optimal conditions for PCR and LAMP. We showed that the LAMP method with the use of the PSI-W primers set, developed by Centeno-Cuadros, functions in 17 previously untested species. Moreover, we found that further improvements are required in universal LAMP primers for the detection of parrot DNA, which are necessary for confirmation of the male sex. The LAMP method also proved to be more sensitive for female sex identification in contrast to the reference PCR test. Therefore, we conclude that LAMP is a suitable method for the routine diagnostic sex identification of parrots.
Drosophila Wing Integration and Modularity: A Multi-Level Approach to Understand the History of Morphological Structures
Authors: Benítez Hugo A. , Püschel Thomas A. , Suazo Manuel J.
Published: April 2022

Static, developmental, and evolutionary variation are different sources of morphological variation which can be quantified using morphometrics tools. In the present study we have carried out a comparative multiple level study of integration (i.e., static, developmental, and evolutionary) to acquire insight about the relationships that exist between different integration levels, as well as to better understand their involvement in the evolutionary processes related to the diversification of Drosophila’s wing shape. This approach was applied to analyse wing evolution in 59 species across the whole genus in a large dataset (~10,000 wings were studied). Static integration was analysed using principal component analysis, thus providing an integration measurement for overall wing shape. Developmental integration was studied between wing parts by using a partial least squares method between the anterior and posterior compartments of the wing. Evolutionary integration was analysed using independent contrasts. The present results show that all Drosophila species exhibit strong morphological integration at different levels. The strong integration and overall similarities observed at multiple integration levels suggest a shared mechanism underlying this variation, which could result as consequence of genetic drift acting on the wing shape of Drosophila.
Metabolic Changes Induced by Cerebral Ischemia, the Effect of Ischemic Preconditioning, and Hyperhomocysteinemia
Authors: Baranovicova Eva , Hnilicova Petra , Kalenska Dagmar , Kaplan Peter , Kovalska Maria , Tatarkova Zuzana , Tomascova Anna , Lehotsky Jan
Published: April 2022

1H Nuclear Magnetic Resonance (NMR) metabolomics is one of the fundamental tools in the fast-developing metabolomics field. It identifies and quantifies the most abundant metabolites, alterations of which can describe energy metabolism, activated immune response, protein synthesis and catabolism, neurotransmission, and many other factors. This paper summarizes our results of the 1H NMR metabolomics approach to characterize the distribution of relevant metabolites and their alterations induced by cerebral ischemic injury or its combination with hyperhomocysteinemia in the affected tissue and blood plasma in rodents. A decrease in the neurotransmitter pool in the brain tissue likely follows the disordered feasibility of post-ischemic neurotransmission. This decline is balanced by the increased tissue glutamine level with the detected impact on neuronal health. The ischemic injury was also manifested in the metabolomic alterations in blood plasma with the decreased levels of glycolytic intermediates, as well as a post-ischemically induced ketosis-like state with increased plasma ketone bodies. As the 3-hydroxybutyrate can act as a likely neuroprotectant, its post-ischemic increase can suggest its supporting role in balancing ischemic metabolic dysregulation. Furthermore, the 1H NMR approach revealed post-ischemically increased 3-hydroxybutyrate in the remote organs, such as the liver and heart, as well as decreased myocardial glutamate. Ischemic preconditioning, as a proposed protective strategy, was manifested in a lower extent of metabolomic changes and/or their faster recovery in a longitudinal study. The paper also summarizes the pre- and post-ischemic metabolomic changes in the rat hyperhomocysteinemic models. Animals are challenged with hyperglycemia and ketosis-like state. A decrease in several amino acids in plasma follows the onset and progression of hippocampal neuropathology when combined with ischemic injury. The 1H NMR metabolomics approach also offers a high potential for metabolites in discriminatory analysis in the search for potential biomarkers of ischemic injury. Based on our results and the literature data, this paper presents valuable findings applicable in clinical studies and suggests the precaution of a high protein diet, especially foods which are high in Met content and low in B vitamins, in the possible risk of human cerebrovascular neuropathology.
Did Homocysteine Take Part in the Start of the Synthesis of Peptides on the Early Earth?
Authors: Youssef-Saliba Sparta , Milet Anne , Vallée Yannick
Published: April 2022

Unlike its shorter analog, cysteine, and its methylated derivative, methionine, homocysteine is not today a proteinogenic amino acid. However, this thiol containing amino acid is capable of forming an activated species intramolecularly. Its thiolactone could have made it an interesting molecular building block at the origin of life on Earth. Here we study the cyclization of homocysteine in water and show theoretically and experimentally that in an acidic medium the proportion of thiolactone is significant. This thiolactone easily reacts with amino acids to form dipeptides. We envision that these reactions may help interpret why a methionine residue is introduced at the start of all protein synthesis.
Long COVID-19 in Children: From the Pathogenesis to the Biologically Plausible Roots of the Syndrome
Authors: Piazza Michele , Di Cicco Maria , Pecoraro Luca , Ghezzi Michele , Peroni Diego , Comberiati Pasquale
Published: April 2022

Long Coronavirus disease-19 (COVID-19) refers to the persistence of symptoms related to the infection with severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). This condition is described as persistent and can manifest in various combinations of signs and symptoms, such as fatigue, headache, dyspnea, depression, cognitive impairment, and altered perception of smells and tastes. Long COVID-19 may be due to long-term damage to different organs—such as lung, brain, kidney, and heart—caused by persisting viral-induced inflammation, immune dysregulation, autoimmunity, diffuse endothelial damage, and micro thrombosis. In this review, we discuss the potential and biologically plausible role of some vitamins, essential elements, and functional foods based on the hypothesis that an individual’s dietary status may play an important adjunctive role in protective immunity against COVID-19 and possibly against its long-term consequences.
A Review of Electrochemical Sensors for the Detection of Glycated Hemoglobin
Authors: Zhan Zhikun , Li Yang , Zhao Yuliang , Zhang Hongyu , Wang Zhen , Fu Boya , Li Wen Jung
Published: April 2022

Glycated hemoglobin (HbA1c) is the gold standard for measuring glucose levels in the diagnosis of diabetes due to the excellent stability and reliability of this biomarker. HbA1c is a stable glycated protein formed by the reaction of glucose with hemoglobin (Hb) in red blood cells, which reflects average glucose levels over a period of two to three months without suffering from the disturbance of the outside environment. A number of simple, high-efficiency, and sensitive electrochemical sensors have been developed for the detection of HbA1c. This review aims to highlight current methods and trends in electrochemistry for HbA1c monitoring. The target analytes of electrochemical HbA1c sensors are usually HbA1c or fructosyl valine/fructosyl valine histidine (FV/FVH, the hydrolyzed product of HbA1c). When HbA1c is the target analyte, a sensor works to selectively bind to specific HbA1c regions and then determines the concentration of HbA1c through the quantitative transformation of weak electrical signals such as current, potential, and impedance. When FV/FVH is the target analyte, a sensor is used to indirectly determine HbA1c by detecting FV/FVH when it is hydrolyzed by fructosyl amino acid oxidase (FAO), fructosyl peptide oxidase (FPOX), or a molecularly imprinted catalyst (MIC). Then, a current proportional to the concentration of HbA1c can be produced. In this paper, we review a variety of representative electrochemical HbA1c sensors developed in recent years and elaborate on their operational principles, performance, and promising future clinical applications.
Elimination Reaction-Based Benzimidazole Probe for Cysteine Detection and Its Application in Serum Sample Analysis
Authors: Song In-ho , Yeom Gyu Seong , Kuwar Anil , Nimse Satish Balasaheb
Published: April 2022

Benzimidazole-based compound 2-(p-tolyl)-1H-benzo[d]imidazole (3) and its derivative probe A-B have been synthesized for the highly selective detection and quantification of Cys in human serum. The photophysical properties of A-B and compound 3 were evaluated by UV-vis absorption and fluorescence spectroscopy. A-B showed high selectivity and sensitivity for Cys among tested analytes, including amino acids, anions, and cations. A-B selectively reacts with Cys and results in compound 3 with fluorescence turn-on effect. A-B did not show any interference from the components in the serum matrix for Cys detection in the human serum sample. A-B detects Cys in serum samples with 2.3–5.4-fold better LOD than reported methods. The detection limit of 86 nM and 43 nM in HEPES buffer using UV-visible and fluorescence spectroscopy, respectively, makes A-B an excellent chemosensor for Cys detection.
Meta-Analysis of the Performance of Pervious Concrete with Cement and Aggregate Replacements
Authors: Anwar Faiz Habib , El-Hassan Hilal , Hamouda Mohamed , Hinge Gilbert , Mo Kim Hung
Published: April 2022

In recent years, pervious concrete (PC) has gained much attention as one of the strategies for low-impact development (LID) in pavements due to its structural, economic, and road-user benefits. This study sought to review and evaluate changes in the mechanical, hydraulic, and durability performance of PC produced with cement and aggregate replacements. A meta-analysis was conducted to elucidate the feasible range of the replacement percentage and the number of materials that could be used to replace cement and aggregates; single or binary replacements were considered. Results indicated that cement-replacing materials, industrial wastes (IWA), and recycled aggregates (RA) met the minimum requirement for the mechanical, hydraulic, and durability properties of PC. The use of a single cement replacement material provided PC with better performance than when cement was replaced with two or more materials or when cement alone was used. Industrial waste was found to be a better replacement to aggregates than RA. The combined replacement of cement and aggregates with IWA and other cement-replacing materials was the most effective method for improving the mechanical, hydraulic, and durability performance of PC. Replacements of up to 40% was considered viable for cement replacement, while up to 50% replacement was considered practical for aggregate and combined replacement. PC incorporating different cement-replacing materials exhibited equivalent or improved mechanical properties and maintained hydraulic performance compared to cement-based PC. Nonetheless, limited studies are available on the durability performance of PC made with cement and/or replacements. Thus, the durability of PC coupled with the applicability of replacement materials acquired from different locations need to be evaluated to address the viability of producing more durable PC with the use of replacements.
A P-I Diagram Approach for Predicting Dynamic Response and Damage Assessment of Reactive Power Concrete Columns Subjected to Blast Loading
Authors: Rong Qin , Zhao Zhonghui , Hou Xiaomeng , Jiang Zhizhong
Published: April 2022

Reactive power concrete (RPC) possesses high compressive strength, toughness, and durability, and it is increasingly being used in important buildings. The column is an important load-bearing member of a building, and its failure under blast loading results in building collapse. Based on these attributes, the dynamic response and the degree of damage to the RPC column are critical in assessing building performance. Due to the lack of methods, the progress of the study is relatively slow. In order to solve these issues, the dynamic response of the RPC column is studied based on the equivalent single-degree-of-freedom method and P-I curve in this paper. During the model validation phase, the deformation of the RPC column predicted using the ESDOF approach correlates well with the explosion simulation and test results. The P-I curves of the typical RPC column were also determined, and some data were analyzed to evaluate the influence of different key parameters, such as slenderness ratio, cross-sectional dimension, and axial compression ratio. The results show that the RPC column is susceptible to shear, bending, and bending-shear failure in the impulse load region, quasi-static load region, and dynamic load region, respectively. The cross-sectional dimension and slenderness ratio exhibit the greatest influence on P-I curves among the five parameters. With the increasing cross-sectional dimension and slenderness ratio, the overpressure asymptote of bending response increases by 4.2 times and decreases by about 57.3%. Furthermore, combined with the P-I curve features, it is found that reasonably increasing the cross-sectional dimensions and RPC strength could simultaneously improve the comprehensive anti-blast performance of RPC columns. This study was carried out to obtain the effect of the five parameters mentioned above on the degree of damage under different blast loading, which can provide a valuable reference for the dynamic response of RPC columns.
Suppression of the ABCA1 Cholesterol Transporter Impairs the Growth and Migration of Epithelial Ovarian Cancer
Authors: Gao Jixuan , Jung MoonSun , Williams Rebekka T. , Hui Danica , Russell Amanda J. , Naim Andrea J. , Kamili Alvin , Clifton Molly , Bongers Angelika , Mayoh Chelsea , Ho Gwo , Scott Clare L. , Jessup Wendy , Haber Michelle , Norris Murray D. , Henderson Michelle J. ,   on behalf of Australian Ovarian Cancer Study
Published: April 2022

Background: Epithelial ovarian cancer (EOC) is the most lethal gynaecological malignancy with over 80% of cases already disseminated at diagnosis and facing a dismal five-year survival rate of 35%. EOC cells often spread to the greater omentum where they take-up cholesterol. Excessive amounts of cholesterol can be cytocidal, suggesting that cholesterol efflux through transporters may be important to maintain homeostasis, and this may explain the observation that high expression of the ATP-binding cassette A1 (ABCA1) cholesterol transporter has been associated with poor outcome in EOC patients. Methods: ABCA1 expression was silenced in EOC cells to investigate the effect of inhibiting cholesterol efflux on EOC biology through growth and migration assays, three-dimensional spheroid culture and cholesterol quantification. Results: ABCA1 suppression significantly reduced the growth, motility and colony formation of EOC cell lines as well as the size of EOC spheroids, whilst stimulating expression of ABCA1 reversed these effects. In serous EOC cells, ABCA1 suppression induced accumulation of cholesterol. Lowering cholesterol levels using methyl-B-cyclodextrin rescued the effect of ABCA1 suppression, restoring EOC growth. Furthermore, we identified FDA-approved agents that induced cholesterol accumulation and elicited cytocidal effects in EOC cells. Conclusions: Our data demonstrate the importance of ABCA1 in maintaining cholesterol balance and malignant properties in EOC cells, highlighting its potential as a therapeutic target for this disease.
Cancer Evolution in Precision Medicine Era
Authors: Karagiannis Dimitris , Rampias Theodoros
Published: April 2022

Recent advances in our understanding of cancer, driven mainly by the emergence of new technologies have highlighted that heterogeneity shapes not only the genetic profile of tumors but also their epigenetic and gene expression profile [...]
Blood Plasma Stabilized Gold Nanoclusters for Personalized Tumor Theranostics
Authors: Jarockyte Greta , Poderys Vilius , Barzda Virginijus , Karabanovas Vitalijus , Rotomskis Ricardas
Published: April 2022

Personalized cancer theranostics has a potential to increase efficiency of early cancer diagnostics and treatment, and to reduce negative side-effects. Protein-stabilized gold nanoclusters may serve as theranostic agents. To make gold nanoclusters personalized and highly biocompatible, the clusters were stabilized with human plasma proteins. Optical properties of synthesized nanoclusters were investigated spectroscopically, and possible biomedical application was evaluated using standard cell biology methods. The spectroscopic investigations of human plasma proteins stabilized gold nanoclusters revealed that a wide photoluminescence band in the optical tissue window is suitable for cancer diagnostics. High-capacity generation of singlet oxygen and other reactive oxygen species was also observed. Furthermore, the cluster accumulation in cancer cells and the photodynamic effect were evaluated. The results demonstrate that plasma proteins stabilized gold nanoclusters that accumulate in breast cancer cells and are non-toxic in the dark, while appear phototoxic under irradiation with visible light. The results positively confirm the utility of plasma protein stabilized gold nanoclusters for the use in cancer diagnostics and treatment.
Physical Exercise Restrains Cancer Progression through Muscle-Derived Factors
Authors: Papadopetraki Argyro , Maridaki Maria , Zagouri Flora , Dimopoulos Meletios-Athanasios , Koutsilieris Michael , Philippou Anastassios
Published: April 2022

A growing body of in vitro and in vivo studies suggests that physical activity offers important benefits against cancer, in terms of both prevention and treatment. However, the exact mechanisms implicated in the anticancer effects of exercise remain to be further elucidated. Muscle-secreted factors in response to contraction have been proposed to mediate the physical exercise-induced beneficial effects and be responsible for the inter-tissue communications. Specifically, myokines and microRNAs (miRNAs) constitute the most studied components of the skeletal muscle secretome that appear to affect the malignancy, either directly by possessing antioncogenic properties, or indirectly by mobilizing the antitumor immune responses. Moreover, some of these factors are capable of mitigating serious, disease-associated adverse effects that deteriorate patients’ quality of life and prognosis. The present review summarizes the myokines and miRNAs that may have potent anticancer properties and the expression of which is induced by physical exercise, while the mechanisms of secretion and intercellular transportation of these factors are also discussed.
Fabrication of Ni2P Cocatalyzed CdS Nanorods with a Well-Defined Heterointerface for Enhanced Photocatalytic H2 Evolution
Authors: Cai Mengdie , Cao Siyu , Zhuo Zhenzhen , Wang Xue , Shi Kangzhong , Cheng Qin , Xue Zhaoming , Du Xi , Shen Cheng , Liu Xianchun , Wang Rui , Shi Lu , Sun Song
Published: April 2022

Developing non-noble metal photocatalysts for efficient photocatalytic hydrogen evolution is crucial for exploiting renewable energy. In this study, a photocatalyst of Ni2P/CdS nanorods consisting of cadmium sulfide (CdS) nanorods (NRs) decorated with Ni2P nanoparticles (NPs) was fabricated using an in-situ solvothermal method with red phosphor (P) as the P source. Ni2P NPs were tightly anchored on the surface of CdS NRs to form a core-shell structure with a well-defined heterointerface, aiming to achieve a highly efficient photocatalytic H2 generation. The as-synthesized 2%Ni2P/CdS NRs photocatalyst exhibited the significantly improved photocatalytic H2 evolution rate of 260.2 μmol∙h−1, more than 20 folds higher than that of bare CdS NRs. Moreover, the as-synthesized 2%Ni2P/CdS NRs photocatalyst demonstrated an excellent stability, even better than that of Pt/CdS NRs. The photocatalytic performance enhancement was ascribed to the core-shell structure with the interfacial Schottky junction between Ni2P NPs and CdS NRs and the accompanying fast and effective photogenerated charge carriers’ separation and transfer. This work provides a new strategy for designing non-noble metal photocatalysts to replace the noble catalysts for photocatalytic water splitting.