bluuebunny/crossref_metadata_2025 huggingface dataset:
Multiobjective Optimization of Laser Polishing of Additively Manufactured Ti-6Al-4V Parts for Minimum Surface Roughness and Heat-Affected Zone
Authors: Solheid Juliana S. , Elkaseer Ahmed , Wunsch Torsten , Scholz Steffen , Seifert Hans J. , Pfleging Wilhelm
Published: May 2022

Metal parts produced by additive manufacturing often require postprocessing to meet the specifications of the final product, which can make the process chain long and complex. Laser post-processes can be a valuable addition to conventional finishing methods. Laser polishing, specifically, is proving to be a great asset in improving the surface quality of parts in a relatively short time. For process development, experimental analysis can be extensive and expensive regarding the time requirement and laboratory facilities, while computational simulations demand the development of numerical models that, once validated, provide valuable tools for parameter optimization. In this work, experiments and simulations are performed based on the design of experiments to assess the effects of the parametric inputs on the resulting surface roughness and heat-affected zone depths. The data obtained are used to create both linear regression and artificial neural network models for each variable. The models with the best performance are then used in a multiobjective genetic algorithm optimization to establish combinations of parameters. The proposed approach successfully identifies an acceptable range of values for the given input parameters (laser power, focal offset, axial feed rate, number of repetitions, and scanning speed) to produce satisfactory values of Ra and HAZ simultaneously.
Investigation on Structural Mapping Laws of Sensitive Geometric Errors Oriented to Remanufacturing of Three-Axis Milling Machine Tools
Authors: Ding Wenzheng , Song Zhanqun , Ding Shuang
Published: May 2022

Three-axis milling machine tools are widely used in manufacturing enterprises, and they have enormous potential demands for remanufacturing to improve their performance. During remanufacturing a three-axis milling machine tool, the structure needs to be reconstructed, so it is necessary to identify sensitive geometric errors of the remanufactured machine tool. In the traditional sensitive geometric error identification method, complex error modeling and analysis must be conducted. Therefore, professional knowledge is required, and the process of the identification is cumbersome. This paper focused on the quick identification of sensitive geometric errors for remanufacturing of three-axis milling machine tools. Firstly, sensitive geometric errors of a three-axis milling machine tool were identified based on the multi-body system theory and partial differential method. Then, mapping laws between the sensitive geometric errors and the machine tool structure were firstly presented. According to the proposed mapping laws, the sensitive geometric errors can be identified quickly and easily without complex error modeling and analysis. Finally, the simulation and experiment show that the straightness error of milling is improved up to 0.007 mm by compensating the sensitive geometric errors identified by the proposed mapping laws. The table lookup method based on the mapping laws can quickly identify the sensitive geometric errors of three-axis milling machine tools, which is beneficial for the efficiency and precision of remanufacturing of machine tools.
Fault Prediction of Rolling Element Bearings Using the Optimized MCKD–LSTM Model
Authors: Ma Leilei , Jiang Hong , Ma Tongwei , Zhang Xiangfeng , Shen Yong , Xia Lei
Published: May 2022

The reliability and safety of rotating equipment depend on the performance of bearings. For complex systems with high reliability and safety needs, effectively predicting the fault data in the use stage has important guiding significance for reasonably formulating reliability plans and carrying out reliability maintenance activities. Many methods have been used to solve the problem of reliability prediction. Due to its convenience and efficiency, the data-driven method is increasingly widely used in practical reliability prediction. In order to ensure the reliability of bearing operation, the main objective of the present study is to establish a novel model based on the optimized maximum correlation kurtosis deconvolution (MCKD) and long short-term memory (LSTM) recurrent neural network to realize early bearing fault warnings by predicting bearing fault time series. The proposed model is based on the lifecycle vibration signal of the bearing. In the first step, the cuckoo search (CS) is utilized to optimize the parameter filter length and deconvolution period of MCKD, considering the influence of periodic bearing time series, and to improve the fault impact component of the optimized MCKD deconvolution time series. Then the LSTM learning rate is selected according to the deconvolution time series. Finally, the dataset obtained through various preprocessing approaches is used to train and predict the LSTM model. The analyses performed using the XJTU-SY bearing dataset demonstrate that the prediction results are in good consistency with real fault data, and the average prediction accuracy of the optimized MCKD–LSTM model is 26% higher than that of the original time series.
Measurement and Modelling of a Cycloidal Gearbox in Actuator with Permanent Magnet Synchronous Machine
Authors: Šlapák Viktor , Ivan Jozef , Kyslan Karol , Hric Matúš , Ďurovský František , Paulišin Dušan , Kočiško Marek
Published: May 2022

Compact geared servo drives are a common part of modern industrial automation; thus, their proper modelling is a necessary part for the application and control design. The presented paper focuses on the mathematical model of the cycloidal gearbox, which is used in the compact actuator with a permanent magnet synchronous motor. A measurement procedure to obtain the necessary gearbox parameters is presented along with its mathematical model. A new approach was used to model the stiction and nonlinear gearbox friction behaviour in all four quadrants. A simulation of the actuator with the modelled gearbox is described and its results are compared with the real system measurement. Obtained results show a high match between simulation and experimental results and confirm the correctness of the simulation model.
Quantum Chemical Approaches to the Calculation of NMR Parameters: From Fundamentals to Recent Advances
Authors: Rusakova Irina L.
Published: May 2022

Quantum chemical methods for the calculation of indirect NMR spin–spin coupling constants and chemical shifts are always in progress. They never stay the same due to permanently developing computational facilities, which open new perspectives and create new challenges every now and then. This review starts from the fundamentals of the nonrelativistic and relativistic theory of nuclear magnetic resonance parameters, and gradually moves towards the discussion of the most popular common and newly developed methodologies for quantum chemical modeling of NMR spectra.
Research on an Accuracy Optimization Algorithm of Kriging Model Based on a Multipoint Filling Criterion
Authors: Li Shande , Yuan Shuai , Liu Shaowei , Wen Jian , Huang Qibai
Published: May 2022

The optimization method based on the surrogate model has been widely used in the simulation and calculation process of complex engineering models. However, in this process, the low accuracy and computational efficiency of the surrogate model has always been an urgent problem that needs to be solved. Aimed at this problem, combined with the two characteristics of global search and local detection, a filling criterion with multiple points is firstly proposed named maximum of expected improvement & minimizing the predicted objective function & maximum of root mean squared error (EI&MP&RMSE) in this paper. Furthermore, the optimization procedure of the surrogate model based on EI&MP&RMSE is concluded. Meanwhile, the classical one-dimensional and two-dimensional functions are applied to verify the accuracy of the proposed method. The difference in the accuracy and mean square error of the surrogate model under different infill points criteria are analyzed. As expected, it shows that this method can effectively improve the accuracy of the surrogate model and reduce the number of iterations. It has extensive practicability and serviceability for the optimization of complex engineering structures.
The Effect of Bounded Rationality on Human Cooperation with Voluntary Participation
Authors: Yang Luhe , Yang Duoxing , Zhang Lianzhong
Published: May 2022

The evolution of human cooperation is an important issue concerning social science. A deep understanding of human bounded rationality is a prerequisite for promoting collective cooperation and solving social dilemmas. Here we construct an asymmetric micro-dynamic based on bounded rationality from a micro perspective by combining behavioral economics and cognitive psychology with evolutionary game theory. Asynchronously updated Monte Carlo simulations were conducted where individuals were located on a square lattice to play a voluntary public goods game. The results showed that “free riding” behaviors can be effectively suppressed in most situations. The cooperation level can be obviously enhanced in a population comprising easily satisfied cooperators and greedy defectors. Moreover, essential conditions for the stability of the system are further discussed at the microscopic level, and altruistic behavior can be explained that an individual with lower expectations for or underestimation of a single game is more likely to cooperate. We argue that, compared to traditional approaches, the integration of interdisciplinary ideas should be taken more seriously.
The Impact of Options on Investment Portfolios in the Short-Run and the Long-Run, with a Focus on Downside Protection and Call Overwriting
Authors: Buckle David
Published: May 2022

In this article, we analyse the impact of the introduction of options on an investment portfolio. Our first objective is to derive closed-form formulae for the standard measures of portfolio efficiency: risk premium, risk, Sharpe ratio, and beta, of any portfolio containing any combination of options. Using these formulae on three examples of simple option strategies (call overwriting, put protection, and collars), we show how these statistics are altered by the inclusion of an option overlay in a portfolio. Our second objective is to show that if an option strategy is repeated over multiple investment time periods, the long-run return becomes normally distributed. Our motivation is to provide investors with the mathematics to measure the impact of the introduction of options on portfolio efficiency and encourage a potential portfolio rebalance to account for this impact. Then, we highlight that whilst options can create asymmetric non-normal outcomes, their repeated use may not alter the long-run portfolio return in the desired way and thus to encourage investors to assess if an option overlay will deliver the desired long-run outcome.
Enhancing Firefly Algorithm with Dual-Population Topology Coevolution
Authors: Li Wei , Li Wangdong , Huang Ying
Published: May 2022

The firefly algorithm (FA) is a meta-heuristic swarm intelligence optimization algorithm. It simulates the social behavior of fireflies with their flash and attraction characteristics. Numerous researches showed that FA can successfully deal with some problems. However, too many attractions between the fireflies may result in high computational complexity, slow convergence, low solution accuracy and poor algorithm stability. To overcome these issues, this paper proposes an enhanced firefly algorithm with dual-population topology coevolution (DPTCFA). In DPTCFA, to maintain population diversity, a dual-population topology coevolution mechanism consisting of the scale-free and ring network topology is proposed. The scale-free network topology structure conforms to the distribution law between the optimal and potential individuals, and the ring network topology effectively reduces the attractions, and thereby has a low computational complexity. The Gauss map strategy is introduced in the scale-free network topology population to lower parameter sensitivity, and in the ring network topology population, a new distance strategy based on dimension difference is adopted to speed up the convergence. This paper improves a diversity neighborhood enhanced search strategy for firefly position update to increase the solution quality. In order to balance the exploration and exploitation, a staged balance mechanism is designed to enhance the algorithm stability. Finally, the performance of the proposed algorithm is verified via several well-known benchmark functions. Experiment results show that DPTCFA can efficiently improve the existing problems of FA to obtain better solutions.
Spread Option Pricing in Regime-Switching Jump Diffusion Models
Authors: Ramponi Alessandro
Published: May 2022

In this paper, we consider the problem of pricing a spread option when the underlying assets follow a bivariate regime-switching jump diffusion model. We exploit an approximation technique which is based on the univariate Fourier transform representation of the option price. The method proves to be computationally very effective with respect to benchmark Monte Carlo estimators and permits the use of several kinds of jump models other than the standard Gaussian setting. As a by-product, the exact price of an Exchange Option may be efficiently computed within this framework.
The Case of Small Prime Numbers Versus the Joye–Libert Cryptosystem
Authors: Teşeleanu George
Published: May 2022

In this paper, we study the effect of using small prime numbers within the Joye–Libert public key encryption scheme. We introduce two novel versions and prove their security. We further show how to choose the system’s parameters such that the security results hold. Moreover, we provide a practical comparison between the cryptographic algorithms we introduced and the original Joye–Libert cryptosystem.
Performance Analysis of Regularized Convex Relaxation for Complex-Valued Data Detection
Authors: Alrashdi Ayed M. , Sifaou Houssem
Published: May 2022

In this work, we study complex-valued data detection performance in massive multiple-input multiple-output (MIMO) systems. We focus on the problem of recovering an n-dimensional signal whose entries are drawn from an arbitrary constellation K⊂C from m noisy linear measurements, with an independent and identically distributed (i.i.d.) complex Gaussian channel. Since the optimal maximum likelihood (ML) detector is computationally prohibitive for large dimensions, many convex relaxation heuristic methods have been proposed to solve the detection problem. In this paper, we consider a regularized version of this convex relaxation that we call the regularized convex relaxation (RCR) detector and sharply derive asymptotic expressions for its mean square error and symbol error probability. Monte-Carlo simulations are provided to validate the derived analytical results.
A Domain Adaptation-Based Method for Classification of Motor Imagery EEG
Authors: Li Changsheng , Chen Minyou , Zhang Li
Published: May 2022

Non-stationarity of EEG signals lead to high variability across sessions, which results in low classification accuracy. To reduce the inter-session variability, an unsupervised domain adaptation method is proposed. Arithmetic mean and covariance are exploited to represent the data distribution. First, overall mean alignment is conducted between the source and target data. Then, the data in the target domain is labeled by a classifier trained with the source data. The per-class mean and covariance of the target data are estimated based on the predicted labels. Next, an alignment from the source domain to the target domain is performed according to the covariance of each class in the target domain. Finally, per-class mean adaptation is required after covariance alignment to remove the shift of data distribution caused by covariance alignment. Two public BCI competition datasets, namely the BCI competition III dataset IVa and the BCI competition IV dataset IIa were used to evaluate the proposed method. On both datasets, the proposed method effectively improved classification accuracy.
Operational Calculus for the General Fractional Derivatives of Arbitrary Order
Authors: Al-Kandari Maryam , Hanna Latif A-M. , Luchko Yuri
Published: May 2022

In this paper, we deal with the general fractional integrals and the general fractional derivatives of arbitrary order with the kernels from a class of functions that have an integrable singularity of power function type at the origin. In particular, we introduce the sequential fractional derivatives of this type and derive an explicit formula for their projector operator. The main contribution of this paper is a construction of an operational calculus of Mikusiński type for the general fractional derivatives of arbitrary order. In particular, we present a representation of the m-fold sequential general fractional derivatives of arbitrary order as algebraic operations in the field of convolution quotients and derive some important operational relations.
TPBF: Two-Phase Bloom-Filter-Based End-to-End Data Integrity Verification Framework for Object-Based Big Data Transfer Systems
Authors: Kasu Preethika , Hamandawana Prince , Chung Tae-Sun
Published: May 2022

Computational science simulations produce huge volumes of data for scientific research organizations. Often, this data is shared by data centers distributed geographically for storage and analysis. Data corruption in the end-to-end route of data transmission is one of the major challenges in distributing the data geographically. End-to-end integrity verification is therefore critical for transmitting such data across data centers effectively. Although several data integrity techniques currently exist, most have a significant negative influence on the data transmission rate as well as the storage overhead. Therefore, existing data integrity techniques are not viable solutions in high performance computing environments where it is very common to transfer huge volumes of data across data centers. In this study, we propose a two-phase Bloom-filter-based end-to-end data integrity verification framework for object-based big data transfer systems. The proposed solution effectively handles data integrity errors by reducing the memory and storage overhead and minimizing the impact on the overall data transmission rate. We investigated the memory, storage, and data transfer rate overheads of the proposed data integrity verification framework on the overall data transfer performance. The experimental findings showed that the suggested framework had 5% and 10% overhead on the total data transmission rate and on the total memory usage, respectively. However, we observed significant savings in terms of storage requirements, when compared with state-of-the-art solutions.
Spatiotemporal Adaptive Fusion Graph Network for Short-Term Traffic Flow Forecasting
Authors: Yang Shumin , Li Huaying , Luo Yu , Li Junchao , Song Youyi , Zhou Teng
Published: May 2022

Traffic flow forecasting is challenging for us to analyze intricate spatial–temporal dependencies and obtain incomplete information of spatial–temporal connection. Existing frameworks mostly construct spatial and temporal modeling based on a fixed graph structure and given time series. However, a fixed adjacency matrix is limited to learn effective spatial–temporal correlations of the network because it represents incomplete information for missing genuine relation. To solve the difficulty, we design a novel spatial–temporal adaptive fusion graph network (STFAGN) for traffic prediction. First, our model combines fusion convolution layers with a novel adaptive dependency matrix by end-to-end training to capture the hidden spatial-temporal dependency on the data to complete incomplete information. Second, STFAGN could, in parallel, acquire hidden spatial–temporal dependencies by a fusion operation and temporal trend by fast-DTW. Meanwhile, we use ReZero connection as a simple change of deep residual networks to facilitate deep signal propagation and faster converge. Lastly, we conduct comparative experiments on two public traffic network datasets, whose results demonstrate the superiority of our algorithm compared to state-of-the-art baseline types. Ablation experiments also prove the rationality of the framework of STFAGN.
Volume, but Not the Location of Necrosis, Is Associated with Worse Outcomes in Acute Pancreatitis: A Prospective Study
Authors: Dekeryte Inga , Zviniene Kristina , Bieliuniene Edita , Dambrauskas Zilvinas , Ignatavicius Povilas
Published: May 2022

Background and Objectives: The course and clinical outcomes of acute pancreatitis (AP) are highly variable. Up to 20% of patients develop pancreatic necrosis. Extent and location of it might affect the clinical course and management. The aim was to determine the clinical relevance of the extent and location of pancreatic necrosis in patients with AP. Materials and Methods: A cohort of patients with necrotizing AP was collected from 2012 to 2018 at the Hospital of Lithuanian University of Health Sciences. Patients were allocated to subgroups according to the location (entire pancreas, left and right sides of pancreas) and extent (<30%, 30–50%, >50%) of pancreatic necrosis. Patients were reviewed for demographic features, number of performed surgical interventions, local and systemic complications, hospital stay and mortality rate. All contrast enhanced computed tomography (CECT) scans were evaluated by at least two experienced abdominal radiologists. All patients were treated according to the standard treatment protocol based on current international guidelines. Results: The study included 83 patients (75.9% males (n = 63)) with a mean age of 53 ± 1.7. The volume of pancreatic necrosis exceeded 50% in half of the patients (n = 42, 51%). Positive blood culture (n = 14 (87.5%)), multiple organ dysfunction syndrome (n = 17 (73.9%)) and incidences of respiratory failure (n = 19 (73.1%)) were significantly more often diagnosed in patients with pancreatic necrosis exceeding 50% (p < 0.05). Patients with >50% of necrosis were significantly (p < 0.05) more often diagnosed with moderately severe (n = 24 (41.4%)) and severe (n = 18 (72%)) AP. The number of surgical interventions (n = 18 (72%)) and ultrasound-guided interventions (n = 26 (65%)) was also significantly higher. In patients with whole-pancreas necrosis, incidence of renal insufficiency (n = 11 (64.7%)) and infected pancreatic necrosis (n = 19 (57.6%)) was significantly higher (p < 0.05). Conclusions: The clinical course and outcome were worse in the case of pancreatic necrosis exceeding 50%, rendering the need for longer and more complex treatment.
Current Knowledge on Exosome Biogenesis, Cargo-Sorting Mechanism and Therapeutic Implications
Authors: Xie Shenmin , Zhang Qin , Jiang Li
Published: May 2022

Extracellular vesicles (EVs) are nanoscale membrane vesicles released by donor cells that can be taken up by recipient cells. The study of EVs has the potential to identify unknown cellular and molecular mechanisms in intercellular communication and disease. Exosomes, with an average diameter of ≈100 nanometers, are a subset of EVs. Different molecular families have been shown to be involved in the formation of exosomes and subsequent secretion of exosomes, which largely leads to the complexity of the form, structure and function of exosomes. In addition, because of their low immunogenicity and ability to transfer a variety of bioactive components to recipient cells, exosomes are regarded as effective drug delivery systems. This review summarizes the known mechanisms of exosomes biogenesis, cargo loading, exosomes release and bioengineering, which is of great importance for further exploration into the clinical applications of EVs.
Numerical Simulation of Microstructure Evolution of Large GCr15 Bar during Multi-Pass Rough Rolling
Authors: Han Huaibin , Zhao Xianming , Ding Haochen , Zhang Chi , Yu Xueqing , Wang Wei
Published: May 2022

Severe temperature gradients and inhomogeneous strain distribution exist in the large cross-section of GCr15 bearing steel during the hot bar rolling process, resulting in a complex microstructure evolution in the bar. To promote the performance of the bar, a thermal-mechanical coupled finite element (FE) model was developed to capture the variations in temperature and deformation strain. A subroutine, considering the dynamic recrystallization (DRX), meta-dynamic recrystallization (MDRX), static recrystallization (SRX), and grain growth (GG) of austenite grains of GCr15 steel, was developed and coupled to the FE model to predict the microstructure’s evolution during rough rolling. The simulation implies that the inner part of the bloom is deformed at high temperatures due to the heat generated by plastic deformation and slow heat conduction, while the surface temperature decreases along with the passes. The heavy reduction design with 11 passes was found to introduce higher strains at the center regions than those of the same rough rolling reduction divided into 13 passes. The higher strains at the center regions refined the grain size and promoted microstructure homogeneity. The observation of the microstructures after hot bar rolling confirmed the refinement of the heavy reduction design for rough rolling. Furthermore, the heavy rough rolling reduction was found to be beneficial for alleviating the macrosegregation of the casting bloom.
Engineering of Escherichia coli Glyceraldehyde-3-Phosphate Dehydrogenase with Dual NAD+/NADP+ Cofactor Specificity for Improving Amino Acid Production
Authors: Slivinskaya Ekaterina A. , Plekhanova Natalia S. , Altman Irina B. , Yampolskaya Tatiana A.
Published: May 2022

Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is a key enzyme in the central metabolism of microbial cells. GAPDHs differ in cofactor specificity and use NAD+, NADP+, or both cofactors, reducing them to NADH and NADPH, respectively. Sufficient NADPH supply is one of the critical factors required for synthesis of the amino acids l-lysine, l-threonine, and l-proline in industrially important Escherichia coli-based producer strains. E. coli cells have NAD+-dependent glycolytic GAPDH. One reasonable approach to increase NADPH formation in cells is to change the specificity of the GAPDH from NAD+ to NADP+. In this study, we modified the cofactor specificity of E. coli GAPDH by amino acid substitutions at positions 34, 188 and 189. Several mutant enzymes with dual NAD+/NADP+ cofactor specificity were obtained, and their kinetic parameters were determined. Overexpression of the genes encoding the resulting mutant GAPDHs with dual cofactor specificity in cells of l-lysine-, l-threonine-, and l-proline-producing E. coli strains led to a marked increase in the accumulation of the corresponding amino acid in the culture medium. This effect was more pronounced when cultivating on xylose as a carbon source. Other possible applications of the mutant enzymes are discussed.
Optimization of Lipopeptide Biosurfactant Production by Salibacterium sp. 4CTb in Batch Stirred-Tank Bioreactors
Authors: Márquez-Villa José Martín , Mateos-Díaz Juan Carlos , Rodríguez-González Jorge Alberto , Camacho-Ruíz Rosa María
Published: May 2022

Halophilic microorganisms are potentially capable as platforms to produce low-cost biosurfactants. However, the robustness of bioprocesses is still a challenge and, therefore, it is essential to understand the effects of microbiological culture conditions through bioreactor engineering. Based on a design of experiments (DOE) and a response surface methodology (RSM) tailored and taken from the literature, the present work focuses on the evaluation of a composite central design (CCD) under batch cultures in stirred-tank bioreactors with the halophilic bacteria Salibacterium sp. 4CTb in order to determine the operative conditions that favor mass transfer and optimize the production of a lipopeptide. The results obtained showed profiles highlighting the most favorable culture conditions, which lead to an emulsification index (E24%) higher than 70%. Moreover, through the behavior of dissolved oxygen (DO), it was possible to experimentally evaluate the higher volumetric coefficient of mass transfer in the presence of lipopeptide (kLa = 31 1/h) as a key criterion for the synthesis of the biosurfactant on further cell expansion.
The StkSR Two-Component System Influences Colistin Resistance in Acinetobacter baumannii
Authors: Giles Sarah K. , Stroeher Uwe H. , Papudeshi Bhavya , Edwards Robert A. , Carlson-Jones Jessica AP. , Roach Michael , Brown Melissa H.
Published: May 2022

Acinetobacter baumannii is an opportunistic human pathogen responsible for numerous severe nosocomial infections. Genome analysis on the A. baumannii clinical isolate 04117201 revealed the presence of 13 two-component signal transduction systems (TCS). Of these, we examined the putative TCS named here as StkSR. The stkR response regulator was deleted via homologous recombination and its progeny, ΔstkR, was phenotypically characterized. Antibiogram analyses of ΔstkR cells revealed a two-fold increase in resistance to the clinically relevant polymyxins, colistin and polymyxin B, compared to wildtype. PAGE-separation of silver stained purified lipooligosaccharide isolated from ΔstkR and wildtype cells ruled out the complete loss of lipooligosaccharide as the mechanism of colistin resistance identified for ΔstkR. Hydrophobicity analysis identified a phenotypical change of the bacterial cells when exposed to colistin. Transcriptional profiling revealed a significant up-regulation of the pmrCAB operon in ΔstkR compared to the parent, associating these two TCS and colistin resistance. These results reveal that there are multiple levels of regulation affecting colistin resistance; the suggested ‘cross-talk’ between the StkSR and PmrAB two-component systems highlights the complexity of these systems.
Development, Characterization, and Antimicrobial Evaluation of Ampicillin-Loaded Nanoparticles Based on Poly(maleic acid-co-vinylpyrrolidone) on Resistant Staphylococcus aureus Strains
Authors: Salamanca Constain H. , Barrera-Ocampo Álvaro , Oñate-Garzón Jose
Published: May 2022

This study was focused on synthesizing, characterizing, and evaluating the antimicrobial effect of polymer nanoparticles (NPs) loaded with ampicillin. For this, the NPs were produced through polymeric self-assembly in aqueous media assisted by high-intensity sonication, using anionic polymers corresponding to the sodium salts of poly(maleic acid-co-vinylpyrrolidone) and poly(maleic acid-co-vinylpyrrolidone) modified with decyl-amine, here named as PMA-VP and PMA-VP-N10, respectively. The polymeric NPs were analyzed and characterized through the formation of polymeric pseudo-phases utilizing pyrene as fluorescent probe, as well as by measurements of particle size, zeta potential, polydispersity index, and encapsulation efficiency. The antimicrobial effect was evaluated by means of the broth microdilution method employing ampicillin sensitive and resistant Staphylococcus aureus strains. The results showed that PMA-VP and PMA-VP-N10 polymers can self-assemble, forming several types of hydrophobic pseudo-phases with respect to the medium pH and polymer concentration. Likewise, the results described that zeta potential, particle size, polydispersity index, and encapsulation efficiency are extremely dependent on the medium pH, whereas the antimicrobial activity displayed an interesting recovery of antibiotic activity when ampicillin is loaded in the polymeric NPs.
Lycorine Alkaloid and Crinum americanum L. (Amaryllidaceae) Extracts Display Antifungal Activity on Clinically Relevant Candida Species
Authors: Silva Lorene Coelho , Correia Amabel Fernandes , Gomes João Victor Dutra , Romão Wanderson , Motta Larissa Campos , Fagg Christopher William , Magalhães Pérola Oliveira , Silveira Dâmaris , Fonseca-Bazzo Yris Maria
Published: May 2022

Candida species are the main fungal agents causing infectious conditions in hospital patients. The development of new drugs with antifungal potential, increased efficacy, and reduced toxicity is essential to face the challenge of fungal resistance to standard treatments. The aim of this study is to evaluate the in vitro antifungal effects of two crude extracts of Crinum americanum L., a rich alkaloid fraction and lycorine alkaloid, on the Candida species. As such, we used a disk diffusion susceptibility test, determined the minimum inhibitory concentration (MIC), and characterized the components of the extracts using Electrospray Ionization Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (ESI FT-ICR MS). The extracts were found to have antifungal activity against various Candida species. The chemical characterization of the extracts indicated the presence of alkaloids such as lycorine and crinine. The Amaryllidaceae family has a promising antifungal potential. Furthermore, it was found that the alkaloid lycorine directly contributes to the effects that were observed for the extracts and fraction of C. americanum.
Nano-Drug Delivery Systems Based on Different Targeting Mechanisms in the Targeted Therapy of Colorectal Cancer
Authors: Wang Ke , Shen Ruoyu , Meng Tingting , Hu Fuqiang , Yuan Hong
Published: May 2022

Colorectal cancer (CRC) is a usual digestive tract malignancy and the third main cause of cancer death around the world, with a high occurrence rate and mortality rate. Conventional therapies for CRC have certain side effects and restrictions. However, the exciting thing is that with the rapid development of nanotechnology, nanoparticles have gradually become more valuable drug delivery systems than traditional therapies because of their capacity to control drug release and target CRC. This also promotes the application of nano-drug targeted delivery systems in the therapy of CRC. Moreover, to make nanoparticles have a better colon targeting effect, many approaches have been used, including nanoparticles targeting CRC and in response to environmental signals. In this review, we focus on various targeting mechanisms of CRC-targeted nanoparticles and their latest research progress in the last three years, hoping to give researchers some inspiration on the design of CRC-targeted nanoparticles.
Insight of the Functional and Biological Activities of Coconut (Cocos nucifera L.) Protein by Proteomics Analysis and Protein-Based Bioinformatics
Authors: Ma Jingrong , Pan Chuang , Chen Haiming , Chen Weijun , Chen Wenxue , Zhang Ming , Zhong Qiuping
Published: May 2022

Coconut (Cocos nucifera L.) is one of the most critical economic crops in the tropics and sub-tropics. Although coconut protein has attracted more and more attention due to its nutritional potential, the lack of proteomic information has limited its practical application. The present study aimed to investigate the coconut meat proteome by shotgun proteomics and protein-based bioinformatic analysis. A grand total of 1686 proteins were identified by searching the National Center for Biotechnology Information (NCBI) protein database and self-constructed C. nucifera transcriptome repository. Among them, 17 and 9 proteins were identified as antioxidant proteins and globulins, respectively. Network analysis of the globulins referred to the sub-works of Cupin and Oleosin, and the antioxidant proteins were related to the sub-networks of glutathione metabolism and peroxisome. The bioactive peptides acquired by in-silico digestion of the targeted proteins have the potential to be applied as antioxidants and emulsifiers for both healthcare and food stabilization.
Synthesis, X-ray Structure and Biological Studies of New Self-Assembled Cu(II) Complexes Derived from s-Triazine Schiff Base Ligand
Authors: Khalil Tarek , Dahlous Kholood , Soliman Saied , Khalil Nessma , El-Faham Ayman , El-Dissouky Ali
Published: May 2022

The two ligands 2-(1-(2-(4,6-dimorpholino-1,3,5-triazin-2-yl)hydrazono)ethyl)aniline (DMAT) and 2-(1-(2-(4,6-dimorpholino-1,3,5-triazin-2-yl)hydrazono)ethyl)phenol (DMOHT) were used to synthesize three heteroleptic Cu(II) complexes via a self-assembly technique. The structure of the newly synthesized complexes was characterized using elemental analysis, FTIR and X-ray photoelectron spectroscopy (XPS) to be [Cu(DMAT)(H2O)(NO3)]NO3.C2H5OH (1), [Cu(DMOT)(CH3COO)] (2) and [Cu(DMOT)(NO3)] (3). X-ray single-crystal structure of complex 1 revealed a hexa-coordinated Cu(II) ion with one DMAT as a neutral tridentate NNN-chelate, one bidentate nitrate group and one water molecule. In the case of complex 2, the Cu(II) is tetra-coordinated with one DMOT as an anionic tridentate NNO-chelate and one monodentate acetate group. The antimicrobial, antioxidant and anticancer activities of the studied compounds were examined. Complex 1 had the best anticancer activity against the lung carcinoma A-549 cell line (IC50 = 5.94 ± 0.58 µM) when compared to cis-platin (25.01 ±2.29 µM). The selectivity index (SI) of complex 1 was the highest (6.34) when compared with the free ligands (1.3–1.8), and complexes 2 (0.72) and 3 (2.97). The results suggested that, among those compounds studied, complex 1 is the most promising anticancer agent against the lung carcinoma A-549 cell line. In addition, complex 1 had the highest antioxidant activity (IC50 = 13.34 ± 0.58 µg/mL) which was found to be comparable to the standard ascorbic acid (IC50 = 10.62 ± 0.84 µg/mL). Additionally, complex 2 showedbroad-spectrum antimicrobial action against the microbes studied. The results revealed it to possess the strongest action of all the three complexes against B. subtilis. The MIC values found are 39.06, 39.06 and 78.125 μg/mL for complexes 1–3, respectively.
The Essential Oil Derived from Perilla frutescens (L.) Britt. Attenuates Imiquimod–Induced Psoriasis-like Skin Lesions in BALB/c Mice
Authors: Xu Yani , Shi Yaohui , Huang Jingxia , Gu Hongtao , Li Chunlian , Zhang Lanyue , Liu Guanting , Zhou Wei , Du Zhiyun
Published: May 2022

Psoriasis is reported to be a common chronic immune-mediated skin disease characterized by abnormal keratinocytes and cell proliferation. Perilla leaves are rich in essential oils, fatty acids, and flavonoids, which are recognized for their antioxidant and anti-inflammatory effects. In this study, the alleviating effect of essential oil (PO) extracted from Perilla frutescens stems and leaves on imiquimod (IMQ) -induced psoriasis-like lesions in BALB/c mice were investigated. Results showed that PO ameliorated psoriasis-like lesions in vivo, reduced the expression of lymphocyte antigen 6 complex locus G6D (Ly-6G), which is a marker of neutrophil activation, and inhibited the expression of inflammatory factors interleukin 1 (IL-1), interleukin 6 (IL-6), inducible nitric oxide synthase (iNOS), and cyclooxygenase 2 (COX2). In addition, PO significantly decreased the expression of cytokines such as IL-6, IL-1, interleukin 23 (IL-23), interleukin 17 (IL-17), and nuclear factor kappa-B (NF-κB). Furthermore, the down-regulation of mRNA levels of psoriasis-related pro-inflammatory cytokines, such as IL-17, interleukin 22 (IL-22), IL-23, interferon-α (IFN-α), and Interferon-γ (IFN-γ) was observed with the treatment of PO. All results show a concentration dependence of PO, with low concentrations showing the best results. These results suggest that PO effectively alleviated psoriasis-like skin lesions and down-regulated inflammatory responses, which indicates that PO could potentially be used for further studies on inflammation-related skin diseases such as psoriasis and for the treatment of psoriasis such as psoriasis natural plant essential oil resources.
Different Effects of Cigarette Smoke, Heated Tobacco Product and E-Cigarette Vapour on Orbital Fibroblasts in Graves’ Orbitopathy; a Study by Real Time Cell Electronic Sensing
Authors: Aranyosi Janos , Galgoczi Erika , Erdei Annamaria , Katko Monika , Fodor Mariann , Ujhelyi Zoltan , Bacskay Ildiko , Nagy Endre , Ujhelyi Bernadett
Published: May 2022

Thyroid autoimmunity in Graves’ disease (GD) is accompanied by Graves’ orbitopathy (GO) in 40% of the cases. Orbital fibroblasts (OF) play a key role in the pathogenesis and cigarette smoking is a known deteriorating factor. Alongside conventional cigarettes (CC) new alternatives became available for smokers, including heated tobacco products (HTP) and E-cigarettes (ECIG). We aimed to study the cellular effects of smoke extracts (SE) in orbital fibroblasts. Primary OF cultures from GO and NON-GO orbits were exposed to different concentrations of SE (1%, 50%) and the changes were followed using Real Time Cell Electronic Sensing (RT-CES). Untreated GO and NON-GO cells had different maximum cell index (CI) values of 3.3 and 2.79 respectively (p < 0.0001). CC, HTP and ECIG treated NON-GO fibroblasts exhibited peak CIs of 2.62, 3.32 and 3.41 while treated GO cells’ CIs were higher, 5.38, 6.25 and 6.33, respectively (p < 0.0001). The metabolic activity (MTT) decreased (p < 0.001) and hyaluronan production doubled (p < 0.02) after 50% of CC SE treatment in all cell cultures. GO fibroblasts were more sensitive to low concentration SE then NON-GO fibroblasts (p < 0.0001). The studied SEs exerted different effects. RT-CES is a sensitive technique to detect the effects of very low concentration of SE on fibroblasts.
Isolation, Structural Elucidation, Antioxidant and Hypoglycemic Activity of Polysaccharides of Brassica rapa L.
Authors: Cao Wenyang , Wang Chenxi , Mayhesumu Xiayidan , Pan Le , Dang Yan , Yili Abulimiti , Abuduwaili Aytursun , Mansur Sanawar
Published: May 2022

The aim of this study was to investigate the effects of microwave ultrasonic-assisted extraction (MUAE) on the content, structure, and biological functions of Brassica rapa L. polysaccharide (BRP). Response surface methodology (RSM) was used to optimize the parameters of MUAE, and it obtained a polysaccharide with yield of 21.802%. Then, a neutral polysaccharide named BRP-1-1 with a molecular weight of 31.378 kDa was isolated and purified from BRP using DEAE-650 M and Sephadex G-100. The structures of the BRP-1-1 were elucidated through a combination of FT-IR, GC-MS, NMR, and methylation analysis. The results showed that BRP-1 consisted of mannose (Man) and glucose (Glu) in a molar ratio of 7.62:1. The backbone of BRP-1-1 mainly consisted of →6)-α-D-Glup-(1→4-β-D-Glup-(1→2)-α-D-Manp-(1→2)-α-D-Glup-(1→, the branch was [T-α-D-Manp-(1]n→. BRP-1-1 intervention significantly inhibited α-glucosidase activity; an inhibition rate of 44.623% was achieved at a concentration of 0.5 mg/mL. The results of the in vitro biological activity showed that BRP-1-1 has good antioxidant and hypoglycemic activity, suggesting that BRP-1-1 could be developed as a functional medicine.
Survey of Dipeptidyl Peptidase III Inhibitors: From Small Molecules of Microbial or Synthetic Origin to Aprotinin
Authors: Abramić Marija , Agić Dejan
Published: May 2022

Dipeptidyl peptidase III (DPP III) was originally thought to be a housekeeping enzyme that contributes to intracellular peptide catabolism. More specific roles for this cytosolic metallopeptidase, in the renin-angiotensin system and oxidative stress regulation, were confirmed, or recognized, only recently. To prove indicated (patho)physiological functions of DPP III in cancer progression, cataract formation and endogenous pain modulation, or to reveal new ones, selective and potent inhibitors are needed. This review encompasses natural and synthetic compounds with experimentally proven inhibitory activity toward mammalian DPP III. Except for the polypeptide aprotinin, all others are small molecules and include flavonoids, coumarin and benzimidazole derivatives. Presented are current strategies for the discovery or development of DPP III inhibitors, and mechanisms of inhibitory actions. The most potent inhibitors yet reported (propioxatin A and B, Tyr-Phe- and Phe-Phe-NHOH, and JMV-390) are active in low nanomolar range and contain hydroxamic acid moiety. High inhibitory potential possesses oligopeptides from the hemorphin group, valorphin and tynorphin, which are poor substrates of DPP III. The crystal structure of human DPP III-tynorphin complex enabled the design of the transition-state peptidomimetics inhibitors, effective in low micromolar concentrations. A new direction in the field is the development of fluorescent inhibitor for monitoring DPP III activity.
Hyperoside: A Review of Its Structure, Synthesis, Pharmacology, Pharmacokinetics and Toxicity
Authors: Xu Sijin , Chen Shuaipeng , Xia Wenxin , Sui Hong , Fu Xueyan
Published: May 2022

Hyperoside is an active ingredient in plants, such as Hypericum monogynum in Hypericaceae, Crataegus pinnatifida in Rosaceae and Polygonum aviculare in Polygonaceae. Its pharmacologic effects include preventing cancer and protecting the brain, neurons, heart, kidneys, lung, blood vessels, bones, joints and liver, among others. Pharmacokinetic analysis of hyperoside has revealed that it mainly accumulates in the kidney. However, long-term application of high-dose hyperoside should be avoided in clinical practice because of its renal toxicity. This review summarises the structure, synthesis, pharmacology, pharmacokinetics and toxicity of hyperoside.
Seasonal Variability of Volatilome from Dictyota dichotoma
Authors: Radman Sanja , Čagalj Martina , Šimat Vida , Jerković Igor
Published: May 2022

Dictyotaceae, the large family of brown algae with the genus Dictyota as the richest one among them, produce a significant number of secondary metabolites, like diterpenes. The aim of this study was to investigate the variations in the composition of the volatile organic compounds (VOCs) of the brown alga Dictyota dichotoma collected from the Adriatic Sea. For the first time, both seasonal changes and the impact of air drying were examined. Headspace solid-phase microextraction (HS-SPME) on two fibres with different polarities and hydrodistillation (HD), followed by gas chromatography and mass spectrometry (GC-MS) analysis, was performed on both fresh (FrDd) and air-dried (DrDd) D. dichotoma. The major compounds of HS-FrDd were pentadecane and oct-1-en-3-ol. The percentage of pentadecane in HS-DrDd was increased up to 7.8 times in comparison with HS-FrDd. Principal component analysis (PCA) identified differences between the variability of data among fresh and dried samples over months and clearly dissociated the fresh May samples from the others in the HS-SPME results. The most abundant group of VOCs in HD were terpenes, with diterpenes isopachydictyol A and cembra-4,7,11,15-tetraen-3-ol as the major compounds. Diterpene pachydictyol A was also found and among sesquiterpenes and gleenol was the most abundant. Based on the dominant compound analyses, the PCA showed distinct separation of the fresh and dried samples, indicating similarities between the samples and allowing the establishment of typical VOCs significant for the chemotaxonomy of D. dichotoma.
Effects of the Bark Resin Extract of Garcinia nigrolineata on Chronic Stress-Induced Memory Deficit in Mice Model and the In Vitro Monoamine Oxidases and β-Amyloid Aggregation Inhibitory Activities of Its Prenylated Xanthone Constituents
Authors: Khamphukdee Charinya , Turkmani Ibrahim , Chotritthirong Yutthana , Chulikhit Yaowared , Boonyarat Chantana , Sekeroglu Nazim , Silva Artur M. S. , Monthakantirat Orawan , Kijjoa Anake
Published: May 2022

The present study describes investigation of the effects of the bark resin extract of Garcinia nigrolineata (Clusiaceae) on the cognitive function and the induction of oxidative stress in both frontal cortex and hippocampus by unpredictable chronic mild stress (UCMS). By using behavioral mouse models, i.e., the Y-maze test, the Novel Object Recognition Test (NORT), and the Morris Water Maze Test (MWMT), it was found that the negative impact of repeated mild stress-induced learning and memory deficit through brain oxidative stress in the UCMS mice was reversed by treatment with the bark resin extract G. nigrolineata. Moreover, the prenylated xanthones viz. cowagarcinone C, cowaxanthone, α-mangostin, cowaxanthone B, cowanin, fuscaxanthone A, fuscaxanthone B, xanthochymusxanthones A, 7-O-methylgarcinone E, and cowagarcinone A, isolated from the bark resin of G. nigrolineata, were assayed for their inhibitory activities against β-amyloid (Aβ) aggregation and monoamine oxidase enzymes (MAOs).