bluuebunny/crossref_metadata_2025 huggingface dataset:
Study on Downhole Geomagnetic Suitability Problems Based on Improved Back Propagation Neural Network
Authors: Zhou Xu , Liu Jing , Men Huiwen , Ren Shangsheng , Guo Liwen
Published: June 2023

The analysis of geomagnetic suitability is the basis and premise of geomagnetic matching navigation and positioning. A geomagnetic suitability evaluation model using mixed sampling and an improved back propagation neural network (BPNN) based on the gray wolf optimization (GWO) algorithm by incorporating the dimension learning-based hunting (DLH) search strategy algorithm was proposed in this paper to accurately assess the geomagnetic suitability. Compared with the traditional geomagnetic suitability evaluation model, its generalization ability and accuracy were better improved. Firstly, the key indicators and matching labels used for geomagnetic suitability evaluation were analyzed, and an evaluation system was established. Then, a mixed sampling method based on the synthetic minority over-sampling technique (SMOTE) and Tomek Links was employed to extend the original dataset and construct a new dataset. Next, the dataset was divided into a training set and a test set, according to 7:3. The geomagnetic standard deviation, kurtosis coefficient, skewness coefficient, geomagnetic information entropy, geomagnetic roughness, variance of geomagnetic roughness, and correlation coefficient were used as input indicators and put into the DLH-GWO-BPNN model for model training with matching labels as output. Accuracy, recall, the ROC curve, and the AUC value were taken as evaluation indexes. Finally, PSO (Particle Swarm Optimization)-BPNN, WOA (Whale Optimization Algorithm)-BPNN, GA (Genetic Algorithm)-BPNN, and GWO-BPNN algorithms were selected as compared methods to verify the predictable ability of the DLH-GWO-BPNN. The accuracy ranking of the five models on the test set was as follows: PSO-BPNN (80.95 %) = WOA-BPNN (80.95%) < GA-BPNN (85.71%) = GWO-BPNN (85.71%) < DLH-GWO-BPNN (95.24%). The results indicate that the DLH-GWO-BPNN model can be used as a reliable method for underground geomagnetic suitability research, which can be applied to the research of geomagnetic matching navigation.
Inspection Algorithm of Welding Bead Based on Image Projection
Authors: Lee Jaeeun , Choi Hongseok , Kim Jongnam
Published: June 2023

The shear reinforcement of dual-anchorage (SRD) is used to enhance the safety of reinforced concrete structures in construction sites. In SRD, welding is used to create shear reinforcement, and after production, a quality inspection of the welding bead is required. Since the welding bead of SRD is inspected for quality by measuring both horizontal and vertical lengths, it is necessary to obtain this information for quality inspection. However, it is difficult to inspect the quality of welding beads using existing methods based on segmentation, due to the similarity in texture between the welding bead and the base material, as well as discoloration around the welded area after welding. In this paper, we propose an algorithm that detects the welding bead using an image projection algorithm for pixels and classifies the quality of the welding bead. This algorithm detects the position of welding beads using the brightness values of an image. The proposed algorithm reduces the amount of computation time by first specifying the region of interest and then performing the analysis. Results from experiments reveal that the algorithm accurately classifies welding beads into good or bad classes by obtaining all brightness values in the vertical and horizontal directions in the SRD image. Furthermore, comparison tests with conventional algorithms demonstrate that the classification accuracy of the proposed algorithm is the highest. The proposed algorithm will be helpful in the real-time welding bead inspection field where fast and accurate inspection is crucial.
Numerical Simulation on Transient Pressure Pulsations and Complex Flow Structures of a Ultra-High-Speed Centrifugal Pump at Stalled Condition
Authors: Zhou Zhenhua , Li Huacong , Chen Jinbo , Li Delin , Zhang Ning
Published: June 2023

A high-speed centrifugal pump is the key facility to deliver oil in an aero-engine. The stable operation is quite important to the safety of the engine. High-speed pump stability is essentially caused by the transient pressure pulsations excited by the complex flow within the pump, which needs to be clarified, especially for the pump under a rotating stall condition. In the current research, unsteady pressure pulsation and the corresponding flow distribution of the high-speed centrifugal pump are analyzed using the delayed detached-eddy simulation (DDES) method. Pressure signals within the pump are extracted by monitoring points. Results show that the dominant components in the pressure spectrum exhibit a significant difference at various flow rates, which locates at the blade passing frequency fBPF under the rated working condition and deviates to five times the shaft frequency (5fn) at the stalled condition. Such phenomenon is not observed in the normal centrifugal pump with low speed when using numerical and experiment methods, and usually the amplitude at fBPF reaches the maximum. Under the stalled condition, the component at 0.2fn is generated and considered as the rotating stall frequency, which is the same at different stalled flow rates. From velocity distribution, it is found that several blade channels are stalled as characterized by the large-scale separation bubbles, which are induced and triggered by the volute tongue.
Assessment of the Incentive Rate to Favor the Energy Retrofit of Public Buildings: A Comprehensive Approach for an Italian University Facility
Authors: Aruta Giuseppe , Ascione Fabrizio , Bianco Nicola , Iovane Teresa , Mastellone Margherita
Published: June 2023

The Renovation Wave for Europe highlighted the role of the public building stock for which Directive 2012/27/EU has set an annual renewal rate of 3%, which should rise to reach the goal of decarbonization by 2050. In this paper, the energy retrofit of an educational building—at the academic level—in Southern Italy was investigated. The aim was to evaluate the incentive share, which could accelerate the energy efficiency process, to achieve a cost-effective nZEB. The results show that the highest incentive rate is required for interventions on the opaque building envelope, which are also those that allow the least energy savings. An incentive rate of about 45% for the energy efficiency of the transparent envelope is necessary to reduce the payback time by about 7 years. The efficiency of the plants and the installation of a PV system are energetically and economically convenient even without forms of economic incentive. Finally, if the building is brought to high energy standards—a primary energy saving of 46% and energy class A3—an incentive rate of 40% is required to repay the intervention in about 10 years.
Analysis of a Two-Stage Magnetic Precession Gear Dynamics
Authors: Macyszyn Lukasz , Jedryczka Cezary , Mysinski Michal
Published: June 2023

The aim of this study was to carry out the investigation and analysis of two-stage magnetic precession gear dynamics and the determination of the resonance frequencies, which can be a cause of the powertrain system failures. Graphical interpretation of the two-stage precession gear is presented, and two equations of the dynamics of the movable elements of the presented gearbox were determined. On the basis of these equations, the stiffness coefficients and resonance frequencies of the presented gearbox were mathematically derived. The next step was to develop a numerical model of the magnetic precession gear dynamics in the environment of MATLAB Simulink. The elaborated model allowed us to analyze the influence of varying the input speed and the load torque on the operation of the magnetic precession gear. The performed analyses of the dynamics of the magnetic precession gear showed the occurrence of a resonance phenomenon under the influence of load torque ripples with a frequency close to the natural frequency of the studied system.
Identifying the Active Species in Li-Na Dual-Ion “Saltwater Battery” Based on Spinel Lithium Manganese Oxide, Sodium Titanium Phosphate and Aqueous Electrolyte
Authors: Schubert Jonathan , Grossmann Lukas , Seidlmayer Stefan , Pettinger Karl-Heinz , Gilles Ralph , Danzer Michael
Published: June 2023

The dual-ion “Saltwater Battery” based on aqueous electrolyte containing sodium ions and lithium ions is believed to be one of the safest and environmentally friendliest battery technologies. The anode consists of sodium titanium phosphate, whereas the cathode is spinel lithium manganese oxide. It has been reported that both materials can intercalate sodium and lithium ions depending on their availability in the electrolyte. This study aims to identify the dominant active species in “Saltwater Batteries” with dual-ion electrolyte. Therefore, cyclic voltammetry of single electrodes as well as full cell measurements are performed with electrolyte containing lithium sulfate, sodium sulfate or a mixture. Moreover, the study is complemented by ion analysis of the electrolyte, as well as X-ray diffraction of fresh and cycled electrodes at different states of charge. The results show that the cathode only (de)intercalates lithium ions, revealing that Li is the dominant active cathode species. The anode can react with both ions and undergoes a formation reaction accompanied by partial dissolution of sodium titanium phosphate. Nevertheless, cyclic voltammetry and full cell measurements indicate that lithium is also the dominant active species on the anode side. In conclusion, the dual-ion battery is dominated by lithium and shows a superior performance when removing sodium from electrolyte.
Business Models for Energy Community in the Aggregator Perspective: State of the Art and Research Gaps
Authors: Bertolini Marina , Morosinotto Gregorio
Published: June 2023

Distributed Energy Resources (DERs) are spreading under the pressure of climate change mitigation plans and the framework, recognized as the most suitable to exploit DER diffusion, is the Energy Community (EC). Understanding the role of energy companies, especially Aggregators, in this context, is still an open topic, as it is not clear how they can support members in the aggregation process and how they create value through their business. The aim of the study is therefore to revise whatever is currently present in the research agenda and consequently a systematic literature review has been carried out. The contribution of this work consists of illustrating the main features of Aggregators, pointing out how they implement their strategies in the energy markets, with which services they capture value, who their partners and customers are, what the financial aspects are of their activities with respect to the size of the aggregated clusters, and, in conclusion, which are the main business model structures currently deployed. Then, considerations are made concerning EC context, identifying the areas where an Aggregator could usefully support communities’ establishment and management, solving well-known hindrances, and what gaps future research should fill.
Initial-Productivity Prediction Method of Oil Wells for Low-Permeability Reservoirs Based on PSO-ELM Algorithm
Authors: Zhao Beichen , Ju Binshan , Wang Chaoxiang
Published: June 2023

Conventional numerical solutions and empirical formulae for predicting the initial productivity of oil wells in low-permeability reservoirs are limited to specific reservoirs and relatively simple scenarios. Moreover, the few influencing factors are less considered and the application model is more ideal. A productivity prediction method based on machine learning algorithms is established to improve the lack of application performance and incomplete coverage of traditional mathematical modelling for productivity prediction. A comprehensive analysis was conducted on the JY extra-low-permeability oilfield, considering its geological structure and various factors that may impact its extraction and production. The study collected 13 factors that influence the initial productivity of 181 wells. The Spearman correlation coefficient, ReliefF feature selection algorithm, and random forest selection algorithm were used in combination to rank the importance of these factors. The screening of seven main controlling factors was completed. The particle swarm optimization–extreme learning machine algorithm was adopted to construct the initial-productivity model. The primary control factors and the known initial productivity of 127 wells were used to train the model, which was then used to verify the initial productivity of the remaining 54 wells. In the particle swarm optimization–extreme learning machine (PSO-ELM) algorithm model, the root-mean-square error (RMSE) is 0.035 and the correlation factor (R2) is 0.905. Therefore, the PSO-ELM algorithm has a high accuracy and a fast computing speed in predicting the initial productivity. This approach will provide new insights into the development of initial-productivity predictions and contribute to the efficient production of low-permeability reservoirs.
Power Plant Transients including Hydraulic Short Circuit Operation Mode
Authors: Geiger Christoph , Riedelbauch Stefan
Published: June 2023

Within the XFLEX HYDRO project, the possibility of increasing the flexibility of hydro power plants to support the Electric Power System (EPS) is investigated. The flexibility of the pumped-storage power plant Frades 2, as the target, should increase by extending the operating range for each unit and by using the hydraulic short circuit (HSC) operation mode. Transient investigations of the additional plant conditions are performed to ensure the safety of the plant. With a 1D model of the entire hydro power plant including both pump-turbines, valves, surge tanks, and the water-bearing components, extensive calculations are carried out to verify the safety of the existing plant for extended operation conditions. In particular, the study focuses on the synchronous and asynchronous emergency shutdowns of the plant in the new operating conditions as well as other operation-related power plant transients regarding the HSC mode. With the results presented in this paper, the flexibility of the plant Frades 2 can be increased. Delayed emergency shutdowns are identified as particularly critical during the study and should always be given additional consideration in transient investigations.
Ocean Wave Energy Control Using Aquila Optimization Technique
Authors: Mishra Sunil Kumar , Jha Amitkumar V. , Appasani Bhargav , Bizon Nicu , Thounthong Phatiphat , Mungporn Pongsiri
Published: June 2023

This paper presents ocean wave energy control using the Aquila optimization (AO) technique. An oscillating water column (OWC)-type wave energy converter has been considered that is fitted with a Wells turbine and doubly fed induction generator (DFIG). To achieve maximum power point tracking (MPPT), the rotor speed of the DFIG must be controlled as per the MPPT law. The MPPT law is designed in such a way that the Wells turbine flow coefficient remains within the threshold limit. It avoids the turbine from stalling which generates the maximum power. The MPPT law provides the reference rotor speed which is followed by the actual rotor speed. For this, a backstepping controller (BSC)-based rotational speed control strategy has been designed using the Lyapunov stability theory. The BSC has unknown control parameters which should be selected such that tracking errors are minimum. Hence, the objective of this work is to find the unknown control parameters using an optimization approach. The optimization approach of selecting BSC control parameters for an OWC plant has not been explored yet. To achieve this, an integral square error (ISE)-type fitness function has been defined and minimized using the AO technique. The results achieved using the AO technique have been compared with particle swarm optimization (PSO) and a genetic algorithm (GA), validating its superior performance. The rotor speed error maximum peak overshoot is least for AO-BSC as compared to PSO-BSC and GA-BSC. The fitness function value for AO comes out to be least among all the optimization methods applied. However, all tested methods provide satisfactory results in terms of turbine flow coefficient, rotor speed and output power. The approach paves the way for future research on ocean wave energy control.
Exploring the Impact of Economic Growth on the Environment: An Overview of Trends and Developments
Authors: Ekonomou George , Halkos George
Published: June 2023

In our modern world, energy keeps the global economy running, and economic growth concerns are profoundly interrelated with environmental quality issues. Interestingly, scientists engage with empirical research to identify the impacts and causalities at the interface of economic activities, energy supply, and demand. The importance of the present study lies in a discussion of all contemporary research efforts bridging two strands of empirical literature in environmental economics: developments in energy growth nexus discussion and the environmental Kuznets curve. Furthermore, it highlights the inclusion of untested explanatory variables and the impacts on environmental degradation levels. In the context of the EKC hypothesis, the most popular indicators are greenhouse gas emissions (GHGs) and carbon dioxide emissions in conceptualizing environmental degradation. A review of relevant empirical studies disclosed additional research opportunities that can consider currently untested and less visible proxies of economic growth. For both strands in the literature, results differ based on the group of countries investigated, the econometric models adopted, the format of data, e.g., time series or panel analyses, the time frames due to data availability, and the proxies used to conceptualize energy, environmental degradation, and economic growth. Practical implications indicate that environmental degradation can be avoided or significantly limited within sustainable economic growth to reduce carbon dioxide emissions and increase the use of renewables in the energy mix. Furthermore, one particular implication is the concept of energy efficiency to reduce relevant demand to produce the same outcome or task.
Forecasting Electricity Demand in Turkey Using Optimization and Machine Learning Algorithms
Authors: Saglam Mustafa , Spataru Catalina , Karaman Omer Ali
Published: June 2023

Medium Neural Networks (MNN), Whale Optimization Algorithm (WAO), and Support Vector Machine (SVM) methods are frequently used in the literature for estimating electricity demand. The objective of this study was to make an estimation of the electricity demand for Turkey’s mainland with the use of mixed methods of MNN, WAO, and SVM. Imports, exports, gross domestic product (GDP), and population data are used based on input data from 1980 to 2019 for mainland Turkey, and the electricity demands up to 2040 are forecasted as an output value. The performance of methods was analyzed using statistical error metrics Root Mean Square Error (RMSE), Mean Absolute Error (MAE), R-squared, and Mean Square Error (MSE). The correlation matrix was utilized to demonstrate the relationship between the actual data and calculated values and the relationship between dependent and independent variables. The p-value and confidence interval analysis of statistical methods was performed to determine which method was more effective. It was observed that the minimum RMSE, MSE, and MAE statistical errors are 5.325 × 10−14, 28.35 × 10−28, and 2.5 × 10−14, respectively. The MNN methods showed the strongest correlation between electricity demand forecasting and real data among all the applications tested.
A Study on Spatial Distribution Extraction of Tidal Inundated Mangroves Based on High and Low Tide Level Images
Authors: You Haotian , You Qixu , Tang Xu , Liu Yao , Chen Jianjun , Wang Feng
Published: June 2023

A majority of mangroves are located in the coastal intertidal zone and are subject to tidal periodic inundation. However, the previous vegetation indices used for extracting the spatial distribution of mangroves were not able to effectively extract submerged mangroves, and the applicability of the vegetation indices used on different spatial resolution images obtained from different sensors was not verified. In this study, a new vegetation index, namely the intertidal mangrove identification indices (IMIIs), was proposed, based on GF-2 images of high and low tide levels. Meanwhile, other commonly used vegetation indices were also extracted. All the vegetation indices were used to extract the spatial distribution of mangroves under tidal inundation, and applicability tests of the vegetation indices were conducted on Sentinel-2 images in three different regions. It was found that the IMIIs proposed based on GF-2 images of high and low tide levels can extract submerged mangroves relatively well, and the spatial distribution extraction results of mangroves are better than those of other vegetation indices, with IMII2 outperforming IMII1. At the same time, IMIIs have good applicability in medium resolution Sentinel-2 images, and there are relatively large differences in the extraction results of mangrove spatial distribution among different vegetation indices in areas with significant impact of tidal inundation. Among all vegetation indices, the extraction results of IMIIs are relatively superior. In most cases, multi variables collaborative application can improve the accuracy of mangrove spatial distribution extraction results. Based on the results of this study, it was concluded that the IMIIs proposed in this study can accurately extract the spatial distribution of mangroves inundated by tides from both medium- and high-resolution images, providing accurate basic data for effective management and scientific protection of mangrove resources.
Influence of Wood Knots of Chinese Weeping Cypress on Selected Physical Properties
Authors: Lyu Jianhua , Qu Hongyue , Chen Ming
Published: June 2023

The effects of wood knots of Chinese weeping cypress (Cupressus funebris Endl.) wood on selected physical and color properties were investigated. Thirty samples of live knots, dead knots, and clear wood groups were selected for experiments to determine the physical properties of wood density, wood shrinkage, wood swelling, and wood color. The experimental analysis results showed that the wood density values are in the order: dead knots > live knots > clear wood, with a significant difference in wood density between different groups (p < 0.01). In addition, the values of the air-dry volumetric wood shrinkage, air-dry volumetric wood swelling, oven-dry volumetric wood shrinkage, and oven-dry volumetric wood swelling ratios are in the order: dead knots > live knots > clear wood, being consistent with a variation in wood density. Three groups of wood colors were provided: the color of clear wood is light, the color of live knots is reddish, and the color of live knots is blackish, in relative terms. The chromatic aberration between the three groups can be identified, and the wood color difference resulted from the discrepancy in the lightness index.
Future Range Dynamics Suggest Increasing Threats of Grey Squirrels (Sciurus carolinensis) against Red Squirrels (Sciurus vulgaris) in Europe: A Perspective on Climatic Suitability
Authors: Nie Peixiao , Yang Rujing , Feng Jianmeng
Published: June 2023

Interactions between the introduced gray squirrel (Sciurus carolinensis) and the native red squirrel (S. vulgaris) play an important role in the ecological equilibrium of European forest ecosystems. However, the range dynamics of the grey squirrel and red squirrel under future climate change scenarios remain unknown. The present study examined the range dynamics of grey squirrels and red squirrels in Europe and their range overlap now and in the future based on climate change. Under the most optimistic climate change scenario (SSP126), expansion of the grey squirrel’s range was mainly predicted in Germany, France, Croatia, Serbia, and Bulgaria. Under the most pessimistic climate change scenario (SSP585), expansion of the grey squirrel’s range was predicted in vast and scattered regions. Additionally, France, Italy, and Germany were overlapping ranges for the grey squirrel and red squirrel in the future under the SSP126 scenario but not under the current conditions, suggesting that there will be new regions where grey squirrels may threaten red squirrels in the future under SSP126. The range overlaps under the SSP585 scenario but not under the current conditions were vast and scattered, suggesting that there will be new regions in the future where grey squirrel may displace red squirrels under SSP585. Despite considerable variation, we detected expansions in the grey squirrel and red squirrel ranges and an increase in overlapping ranges between grey squirrels and red squirrels in the future. Therefore, our prediction suggests increasing threats of grey squirrels toward red squirrels in Europe in the future under climate change, which may impact the ecological equilibrium of European forest ecosystems.
Genetic Determinants of Atherogenic Indexes
Authors: Texis Tomas , Rivera-Mancía Susana , Colín-Ramírez Eloisa , Cartas-Rosado Raul , Koepsell David , Rubio-Carrasco Kenneth , Rodríguez-Dorantes Mauricio , Gonzalez-Covarrubias Vanessa
Published: June 2023

Atherogenesis and dyslipidemia increase the risk of cardiovascular disease, which is the leading cause of death in developed countries. While blood lipid levels have been studied as disease predictors, their accuracy in predicting cardiovascular risk is limited due to their high interindividual and interpopulation variability. The lipid ratios, atherogenic index of plasma (AIP = log TG/HDL-C) and the Castelli risk index 2 (CI2 = LDL-C/HDL-C), have been proposed as better predictors of cardiovascular risk, but the genetic variability associated with these ratios has not been investigated. This study aimed to identify genetic associations with these indexes. The study population (n = 426) included males (40%) and females (60%) aged 18–52 years (mean 39 years); the Infinium GSA array was used for genotyping. Regression models were developed using R and PLINK. AIP was associated with variation on APOC3, KCND3, CYBA, CCDC141/TTN, and ARRB1 (p-value < 2.1 × 10−6). The three former were previously associated with blood lipids, while CI2 was associated with variants on DIPK2B, LIPC, and 10q21.3 rs11251177 (p-value 1.1 × 10−7). The latter was previously linked to coronary atherosclerosis and hypertension. KCND3 rs6703437 was associated with both indexes. This study is the first to characterize the potential link between genetic variation and atherogenic indexes, AIP, and CI2, highlighting the relationship between genetic variation and dyslipidemia predictors. These results also contribute to consolidating the genetics of blood lipid and lipid indexes.
Analysis of Dispersivity in Marine Clays of Cartagena de Indias, Colombia
Authors: Acuña Cristian , Betancur Juan , Baldovino Jair Arrieta , Barboza Guilliam , Saba Manuel
Published: June 2023

This study assessed the dispersivity of soils extracted from the northern region of Cartagena de Indias (Colombia) using the pinhole test, crumb test, and chemical–microstructural analyses. Dispersive soils are susceptible to erosive phenomena upon contact with water, yet they have not been adequately characterized in the city. To evaluate the dispersivity degree of different deformed and undisturbed soil samples, soil characterization tests included particle size analysis, chemical composition, Atterberg limits, specific gravity, and compaction. The results showed that the soils are highly plastic clays (i.e., CH) with a slight to moderate dispersivity level (i.e., ND3) according to the pinhole test and a moderate degree of dispersivity confirmed by the crumb test. The extracted soil sample sodium levels ranged from 0.72% to 1.94%, and the soil had an optimal moisture content of 26% and a maximum apparent dry unit weight of 13.87 kN/m3. According to standards and results, Cartagena de Indias’s studied marine clays are unsuitable for civil construction due to the degree of uncertainty in their behavior.
Etiology of Anemia and Risk Factors of Mortality among Hospitalized Patients: A Real-Life Retrospective Study in a Tertiary Center in Greece
Authors: Ioannou Petros , Papazachariou Andria , Tsafaridou Maria , Koutroubakis Ioannis E. , Kofteridis Diamantis P.
Published: June 2023

Anemia is a prominent global health issue with a wide variety of causes and can be associated with decreased quality of life, increased hospitalization, and higher mortality, especially in older individuals. Therefore, studies further shedding light on the causes and the risk factors of this condition should be performed. The aim of the present study was to examine the causes of anemia in hospitalized patients in a tertiary hospital in Greece and identify risk factors related to higher mortality. In total, 846 adult patients with a diagnosis of anemia were admitted during the study period. The median age was 81 years, and 44.8% were male. The majority of patients had microcytic anemia, with the median mean corpuscular volume (MCV) being 76.3 fL and the median hemoglobin being 7.1 g/dL. Antiplatelets were used by 28.6% of patients, while 28.4% were using anticoagulants at the time of diagnosis. At least one unit of packed red blood cells (PRBCs) was transfused in 84.6% of patients, and a median of two PRBCs was used per patient. A gastroscopy was performed in 55%, and a colonoscopy was performed in 39.8% of patients in the present cohort. Anemia was considered to be multifactorial in almost half the cases, while the most commonly identified cause was iron deficiency anemia, more commonly with positive endoscopic findings. Mortality was relatively low, at 4.1%. Multivariate logistic regression analysis identified higher B12 levels and longer duration of hospital stay to be independently positively associated with mortality.
Khosta: A Genetic and Structural Point of View of the Forgotten Virus
Authors: Scarpa Fabio , Imperia Elena , Ciccozzi Alessandra , Pascarella Stefano , Quaranta Miriana , Giovanetti Marta , Borsetti Alessandra , Petrosillo Nicola , Ciccozzi Massimo
Published: June 2023

Bats are well-known to be natural reservoirs of various zoonotic coronaviruses, which have caused outbreaks of severe acute respiratory syndrome (SARS) and the COVID-19 pandemic in 2002 and 2019, respectively. In late 2020, two new Sarbecoviruses were found in Russia, isolated in Rhinolophus bats, i.e., Khosta-1 in R. ferrumequinum and Khosta-2 in R. hipposideros. The potential danger associated with these new species of Sarbecovirus is that Khosta-2 has been found to interact with the same entry receptor as SARS-CoV-2. Our multidisciplinary approach in this study demonstrates that Khosta-1 and -2 currently appear to be not dangerous with low risk of spillover, as confirmed by prevalence data and by phylogenomic reconstruction. In addition, the interaction between Khosta-1 and -2 with ACE2 appears weak, and furin cleavage sites are absent. While the possibility of a spillover event cannot be entirely excluded, it is currently highly unlikely. This research further emphasizes the importance of assessing the zoonotic potential of widely distributed batborne CoV in order to monitor changes in genomic composition of viruses and prevent spillover events (if any).
Special Issue on Whole Genome Amplification
Authors: Jäger Richard
Published: June 2023

The development of whole-genome amplification (WGA) techniques has opened up new avenues for genetic analysis and genome research, in particular by facilitating the genome-wide analysis of few or even single copies of genomic DNA, such as from single cells (prokaryotic or eukaryotic) or virions [...]
Magnesium Nutrient Application Induces Metabolomics and Physiological Responses in Mulberry (Morus alba) Plants
Authors: Jin Xin , Ackah Michael , Wang Lei , Amoako Frank Kwarteng , Shi Yisu , Essoh Lionnelle Gyllye , Li Jianbin , Zhang Qiaonan , Li Haonan , Zhao Weiguo
Published: June 2023

Mulberry (Morus alba) is a significant plant with numerous economic benefits; however, its growth and development are affected by nutrient levels. A high level of magnesium (Mg) or magnesium nutrient starvation are two of the significant Mg factors affecting plant growth and development. Nevertheless, M. alba’s metabolic response to different Mg concentrations is unclear. In this study, different Mg concentrations, optimal (3 mmol/L), high (6 mmol/L and 9 mmol/L), or low (1 and 2 mmol/L) and deficient (0 mmol/L), were applied to M. alba for three weeks to evaluate their effects via physiological and metabolomics (untargeted; liquid chromatography–mass spectrometry (LC-MS)) studies. Several measured physiological traits revealed that Mg deficiency and excess Mg altered net photosynthesis, chlorophyll content, leaf Mg content and fresh weight, leading to remarkable reductions in the photosynthetic efficiency and biomass of mulberry plants. Our study reveals that an adequate supply of the nutrient Mg promoted the mulberry’s physiological response parameters (net photosynthesis, chlorophyll content, leaf and root Mg content and biomass). The metabolomics data show that different Mg concentrations affect several differential metabolite expressions (DEMs), particularly fatty acyls, flavonoids, amino acids, organic acid, organooxygen compounds, prenol lipids, coumarins, steroids and steroid derivatives, cinnamic acids and derivatives. An excessive supply of Mg produced more DEMs, but negatively affected biomass production compared to low and optimum supplies of Mg. The significant DEMs correlated positively with mulberry’s net photosynthesis, chlorophyll content, leaf Mg content and fresh weight. The mulberry plant’s response to the application of Mg used metabolites, mainly amino acids, organic acids, fatty acyls, flavonoids and prenol lipids, in the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways. These classes of compounds were mainly involved in lipid metabolism, amino acid metabolism, energy metabolism, the biosynthesis of other secondary metabolites, the biosynthesis of other amino acids, the metabolism of cofactors and vitamin pathways, indicating that mulberry plants respond to Mg concentrations by producing a divergent metabolism. The supply of Mg nutrition was an important factor influencing the induction of DEMs, and these metabolites were critical in several metabolic pathways related to magnesium nutrition. This study provides a fundamental understanding of DEMs in M. alba’s response to Mg nutrition and the metabolic mechanisms involved, which may be critical to the mulberry genetic breeding program.
The Endogenous Dual Retinoid Receptor Agonist Alitretinoin Exhibits Immunoregulatory Functions on Antigen-Presenting Cells
Authors: Kislat Andreas , Olah Peter , Kuchner Marcus , Gerber Peter Arne , Schrader Jürgen , Meller Stephan , Homey Bernhard
Published: June 2023

Retinoids are a frequently used class of drugs in the treatment of inflammatory as well as malignant skin diseases. Retinoids have differential affinity for the retinoic acid receptor (RAR) and/or the retinoid X receptor (RXR). The endogenous dual RAR and RXR agonist alitretinoin (9-cis retinoic acid) demonstrated remarkable efficacy in the treatment of chronic hand eczema (CHE) patients; however, detailed information on the mechanisms of action remains elusive. Here, we used CHE as a model disease to unravel immunomodulatory pathways following retinoid receptor signaling. Transcriptome analyses of skin specimens from alitretinoin-responder CHE patients identified 231 significantly regulated genes. Bioinformatic analyses indicated keratinocytes as well as antigen presenting cells as cellular targets of alitretinoin. In keratinocytes, alitretinoin interfered with inflammation-associated barrier gene dysregulation as well as antimicrobial peptide induction while markedly inducing hyaluronan synthases without affecting hyaluronidase expression. In monocyte-derived dendritic cells, alitretinoin induced distinct morphological and phenotypic characteristics with low co-stimulatory molecule expression (CD80 and CD86), the increased secretion of IL-10 and the upregulation of the ecto-5′-nucleotidase CD73 mimicking immunomodulatory or tolerogenic dendritic cells. Indeed, alitretinoin-treated dendritic cells demonstrated a significantly reduced capacity to activate T cells in mixed leukocyte reactions. In a direct comparison, alitretinoin-mediated effects were significantly stronger than those observed for the RAR agonist acitretin. Moreover, longitudinal monitoring of alitretinoin-responder CHE patients could confirm in vitro findings. Taken together, we demonstrate that the dual RAR and RXR agonist alitretinoin targets epidermal dysregulation and demonstrates strong immunomodulatory effects on antigen presenting cell functions.
Untargeted Metabolomics Identifies Biomarkers for MCADD Neonates in Dried Blood Spots
Authors: Sebaa Rajaa , AlMogren Maha , Alseraty Wafaa , Abdel Rahman Anas
Published: June 2023

Medium-chain acyl-CoA dehydrogenase deficiency (MCADD) is the most common inherited mitochondrial metabolic disease of fatty acid β-oxidation, especially in newborns. MCADD is clinically diagnosed using Newborn Bloodspot Screening (NBS) and genetic testing. Still, these methods have limitations, such as false negatives or positives in NBS and the variants of uncertain significance in genetic testing. Thus, complementary diagnostic approaches for MCADD are needed. Recently, untargeted metabolomics has been proposed as a diagnostic approach for inherited metabolic diseases (IMDs) due to its ability to detect a wide range of metabolic alterations. We performed an untargeted metabolic profiling of dried blood spots (DBS) from MCADD newborns (n = 14) and healthy controls (n = 14) to discover potential metabolic biomarkers/pathways associated with MCADD. Extracted metabolites from DBS samples were analyzed using UPLC-QToF-MS for untargeted metabolomics analyses. Multivariate and univariate analyses were used to analyze the metabolomics data, and pathway and biomarker analyses were also performed on the significantly identified endogenous metabolites. The MCADD newborns had 1034 significantly dysregulated metabolites compared to healthy newborns (moderated t-test, no correction, p-value ≤ 0.05, FC 1.5). A total of 23 endogenous metabolites were up-regulated, while 84 endogenous metabolites were down-regulated. Pathway analyses showed phenylalanine, tyrosine, and tryptophan biosynthesis as the most affected pathways. Potential metabolic biomarkers for MCADD were PGP (a21:0/PG/F1alpha) and glutathione, with an area under the curve (AUC) of 0.949 and 0.898, respectively. PGP (a21:0/PG/F1alpha) was the first oxidized lipid in the top 15 biomarker list affected by MCADD. Additionally, glutathione was chosen to indicate oxidative stress events that could happen during fatty acid oxidation defects. Our findings suggest that MCADD newborns may have oxidative stress events as signs of the disease. However, further validations of these biomarkers are needed in future studies to ensure their accuracy and reliability as complementary markers with established MCADD markers for clinical diagnosis.
Mechanisms of Resistance to Antibody-Drug Conjugates
Authors: Khoury Rita , Saleh Khalil , Khalife Nadine , Saleh Mohamad , Chahine Claude , Ibrahim Rebecca , Lecesne Axel
Published: June 2023

The treatment of cancer patients has dramatically changed over the past decades with the advent of monoclonal antibodies, immune-checkpoint inhibitors, bispecific antibodies, and innovative T-cell therapy. Antibody-drug conjugates (ADCs) have also revolutionized the treatment of cancer. Several ADCs have already been approved in hematology and clinical oncology, such as trastuzumab emtansine (T-DM1), trastuzumab deruxtecan (T-DXd), and sacituzumab govitecan (SG) for the treatment of metastatic breast cancer, and enfortumab vedotin (EV) for the treatment of urothelial carcinoma. The efficacy of ADCs is limited by the emergence of resistance due to different mechanisms, such as antigen-related resistance, failure of internalization, impaired lysosomal function, and other mechanisms. In this review, we summarize the clinical data that contributed to the approval of T-DM1, T-DXd, SG, and EV. We also discuss the different mechanisms of resistance to ADCs, as well as the ways to overcome this resistance, such as bispecific ADCs and the combination of ADCs with immune-checkpoint inhibitors or tyrosine-kinase inhibitors.
Genetic Targeting of dSAMTOR, A Negative dTORC1 Regulator, during Drosophila Aging: A Tissue-Specific Pathology
Authors: Katarachia Stamatia A. , Markaki Sophia P. , Velentzas Athanassios D. , Stravopodis Dimitrios J.
Published: June 2023

mTORC1 regulates mammalian cell metabolism and growth in response to diverse environmental stimuli. Nutrient signals control the localization of mTORC1 onto lysosome surface scaffolds that are critically implicated in its amino acid-dependent activation. Arginine, leucine and S-adenosyl-methionine (SAM) can serve as major mTORC1-signaling activators, with SAM binding to SAMTOR (SAM + TOR), a fundamental SAM sensor, preventing the protein’s (SAMTOR’s) inhibitory action(s) against mTORC1, thereby triggering its (mTORC1) kinase activity. Given the lack of knowledge regarding the role of SAMTOR in invertebrates, we have identified the Drosophila SAMTOR homologue (dSAMTOR) in silico and have, herein, genetically targeted it through the utilization of the GAL4/UAS transgenic tool. Survival profiles and negative geotaxis patterns were examined in both control and dSAMTOR-downregulated adult flies during aging. One of the two gene-targeted schemes resulted in lethal phenotypes, whereas the other one caused rather moderate pathologies in most tissues. The screening of head-specific kinase activities, via PamGene technology application, unveiled the significant upregulation of several kinases, including the dTORC1 characteristic substrate dp70S6K, in dSAMTOR-downregulated flies, thus strongly supporting the inhibitory dSAMTOR action(s) upon the dTORC1/dp70S6K signaling axis in Drosophila brain settings. Importantly, genetic targeting of the Drosophila BHMT bioinformatics counterpart (dBHMT), an enzyme that catabolizes betaine to produce methionine (the SAM precursor), led to severe compromises in terms of fly longevity, with glia-, motor neuron- and muscle-specific dBHMT downregulations exhibiting the strongest effects. Abnormalities in wing vein architectures were also detected in dBHMT-targeted flies, thereby justifying their notably reduced negative geotaxis capacities herein observed mainly in the brain–(mid)gut axis. In vivo adult fly exposure to clinically relevant doses of methionine revealed the mechanistic synergism of decreased dSAMTOR and increased methionine levels in pathogenic longevity, thus rendering (d)SAMTOR an important component in methionine-associated disorders, including homocystinuria(s).
Dry Reforming of Methane over 5%Ni/Ce1-xTixO2 Catalysts Obtained via Synthesis in Supercritical Isopropanol
Authors: Smal Ekaterina , Bespalko Yulia , Arapova Marina , Fedorova Valeria , Valeev Konstantin , Eremeev Nikita , Sadovskaya Ekaterina , Krieger Tamara , Glazneva Tatiana , Sadykov Vladislav , Simonov Mikhail
Published: June 2023

A series of 5%Ni/Ce1-xTixO2 catalysts was prepared with nickel impregnation of mixed Ce–Ti oxides obtained via synthesis in supercritical isopropanol. All oxides have a cubic fluorite phase structure. Ti is incorporated into the fluorite structure. Small amounts of impurities of TiO2 or mixed Ce–Ti oxides appear with Ti introduction. Supported Ni is presented as the NiO or NiTiO3 perovskite phase. Ti introduction increases total samples reducibility and results in stronger interaction of supported Ni with the oxide support. The fraction of rapidly replaced oxygen and the average tracer diffusion coefficient also increase. The number of metallic nickel sites decreased with increasing Ti content. All catalysts except Ni-CeTi0.45 demonstrate close activity in tests of dry reforming of methane. The lower activity of Ni-CeTi0.45 can be connected to Ni decoration with species of the oxide support. The incorporation of Ti prevents detachment of Ni particles from the surface and their sintering during dry reforming of methane.
BS148 Reduces the Aggressiveness of Metastatic Melanoma via Sigma-2 Receptor Targeting
Authors: Sorbi Claudia , Belluti Silvia , Atene Claudio Giacinto , Marocchi Federica , Linciano Pasquale , Roy Neena , Paradiso Elia , Casarini Livio , Ronsisvalle Simone , Zanocco-Marani Tommaso , Brasili Livio , Lanfrancone Luisa , Imbriano Carol , Di Rocco Giulia , Franchini Silvia
Published: June 2023

The management of advanced-stage melanoma is clinically challenging, mainly because of its resistance to the currently available therapies. Therefore, it is important to develop alternative therapeutic strategies. The sigma-2 receptor (S2R) is overexpressed in proliferating tumor cells and represents a promising vulnerability to target. Indeed, we have recently identified a potent S2R modulator (BS148) that is effective in melanoma. To elucidate its mechanism of action, we designed and synthesized a BS148 fluorescent probe that enters SK-MEL-2 melanoma cells as assessed using confocal microscopy analysis. We show that S2R knockdown significantly reduces the anti-proliferative effect induced by BS148 administration, indicating the engagement of S2R in BS148-mediated cytotoxicity. Interestingly, BS148 treatment showed similar molecular effects to S2R RNA interference-mediated knockdown. We demonstrate that BS148 administration activates the endoplasmic reticulum stress response through the upregulation of protein kinase R-like ER kinase (PERK), activating transcription factor 4 (ATF4) genes, and C/EBP homologous protein (CHOP). Furthermore, we show that BS148 treatment downregulates genes related to the cholesterol pathway and activates the MAPK signaling pathway. Finally, we translate our results into patient-derived xenograft (PDX) cells, proving that BS148 treatment reduces melanoma cell viability and migration. These results demonstrate that BS148 is able to inhibit metastatic melanoma cell proliferation and migration through its interaction with the S2R and confirm its role as a promising target to treat cancer.
Nanoarchitectonics of Three-Dimensional Carbon Nanofiber-Supported Hollow Copper Sulfide Spheres for Asymmetric Supercapacitor Applications
Authors: Shin Miyeon , Awasthi Ganesh Prasad , Sharma Krishna Prasad , Pandey Puran , Park Mira , Ojha Gunendra Prasad , Yu Changho
Published: June 2023

Three-dimensional carbon nanofiber (3D-CNF)-supported hollow copper sulfide (HCuS) spheres were synthesized by the facile hydrothermal method. The morphology of the as-synthesized HCuS@3D-CNF composite clearly revealed that the 3D-CNFs act as a basement for HCuS spheres. The electrochemical performance of as-synthesized HCuS@3D-CNFs was evaluated by cyclic voltammetry (CV) tests, gravimetric charge–discharge (GCD) tests, and Nyquist plots. The obtained results revealed that the HCuS@3D-CNFs exhibited greater areal capacitance (4.6 F/cm2) compared to bare HCuS (0.64 F/cm2) at a current density of 2 mA/cm2. Furthermore, HCuS@3D-CNFs retained excellent cyclic stability of 83.2% after 5000 cycles. The assembled asymmetric device (HCuS@3D-CNFs//BAC) exhibits an energy density of 0.15 mWh/cm2 with a working potential window of 1.5 V in KOH electrolyte. The obtained results demonstrate that HZnS@3D-CNF nanoarchitectonics is a potential electrode material for supercapacitor applications.
Carbonic Anhydrase and Biomarker Research: New Insights
Authors: Lionetto Maria Giulia
Published: June 2023

Carbonic anhydrase (CA) is a widespread metalloenzyme with eight genetically distinct families catalyzing the reversible hydration of CO2 to HCO3− and H+ [...]