bluuebunny/crossref_metadata_2025 huggingface dataset:
Predicting the Kinetic Coordination of Immune Response Dynamics in SARS-CoV-2 Infection: Implications for Disease Pathogenesis
Authors: Grebennikov Dmitry , Karsonova Antonina , Loguinova Marina , Casella Valentina , Meyerhans Andreas , Bocharov Gennady
Published: September 2022

A calibrated mathematical model of antiviral immune response to SARS-CoV-2 infection is developed. The model considers the innate and antigen-specific responses to SARS-CoV-2 infection. Recently published data sets from human challenge studies with SARS-CoV-2 were used for parameter evaluation. The calibration of the mathematical model of SARS-CoV-2 infection is based on combining the parameter guesses from our earlier study of influenza A virus infection, some recent quantitative models of SARS-CoV-2 infection and clinical data-based parameter estimation of a subset of the model parameters. Hence, the calibrated mathematical model represents a theoretical exploration type of study, i.e., ‘in silico patient’ with mild-to-moderate severity phenotype, rather than a completely validated quantitative model of COVID-19 with respect to all its state-space variables. Understanding the regulation of multiple intertwined reaction components of the immune system is necessary for linking the kinetics of immune responses with the clinical phenotypes of COVID-19. Consideration of multiple immune reaction components in a single calibrated mathematical model allowed us to address some fundamental issues related to the pathogenesis of COVID-19, i.e., the sensitivity of the peak viral load to the parameters characterizing the antiviral specific response components, the kinetic coordination of the individual innate and adaptive immune responses, and the factors favoring a prolonged viral persistence. The model provides a tool for predicting the infectivity of patients, i.e., the amount of virus which is transmitted via droplets from the person infected with SARS-CoV-2, depending on the time of infection. The thresholds for variations of the innate and adaptive response parameters which lead to a prolonged persistence of SARS-CoV-2 due to the loss of a kinetic response synchrony/coordination between them were identified.
CIST: Differentiating Concepts and Instances Based on Spatial Transformation for Knowledge Graph Embedding
Authors: Zhang Pengfei , Chen Dong , Fang Yang , Zhao Xiang , Xiao Weidong
Published: September 2022

Knowledge representation learning is representing entities and relations in a knowledge graph as dense low-dimensional vectors in the continuous space, which explores the features and properties of the graph. Such a technique can facilitate the computation and reasoning on the knowledge graphs, which benefits many downstream tasks. In order to alleviate the problem of insufficient entity representation learning caused by sparse knowledge graphs, some researchers propose knowledge graph embedding models based on instances and concepts, which utilize the latent semantic connections between concepts and instances contained in the knowledge graphs to enhance the knowledge graph embedding. However, they model instances and concepts in the same space or ignore the transitivity of isA relations, leading to inaccurate embeddings of concepts and instances. To address the above shortcomings, we propose a knowledge graph embedding model that differentiates concepts and instances based on spatial transformation—CIST. The model alleviates the gathering issue of similar instances or concepts in the semantic space by modeling them in different embedding spaces, and adds a learnable parameter to adjust the neighboring range for concept embedding to distinguish hierarchical information of different concepts, thus modeling the transitivity of isA relations. The above features of instances and concepts serve as auxiliary information so that thoroughly modeling them could alleviate the insufficient entity representation learning issue. For the experiments, we chose two tasks, i.e., link prediction and triple classification, and two real-life datasets: YAGO26K-906 and DB111K-174. Compared with state of the arts, CIST achieves an optimal performance in most cases. Specifically, CIST outperforms the SOTA model JOIE by 51.1% on Hits@1 in link prediction and 15.2% on F1 score in triple classification.
Multipurpose Aggregation in Risk Assessment
Authors: Kovács Zoltán , Csizmadia Tibor , Mihálcz István , Kosztyán Zsolt T.
Published: September 2022

Risk-mitigation decisions in risk-management systems are usually based on complex risk indicators. Therefore, aggregation is an important step during risk assessment. Aggregation is important when determining the risk of components or the overall risk of different areas or organizational levels. In this article, the authors identify different aggregation scenarios. They summarize the requirements of aggregation functions and characterize different aggregations according to these requirements. They critique the multiplication-based risk priority number (RPN) used in existing applications and propose the use of other functions in different aggregation scenarios. The behavior of certain aggregation functions in warning systems is also examined. The authors find that, depending on the aggregation location within the organization and the purpose of the aggregation, considerably more functions can be used to develop complex risk indicators. The authors use different aggregations and seriation and biclustering to develop a method for generating corrective and preventive actions. The paper provides contributions for individuals, organizations, and or policy makers to assess and mitigate the risks at all levels of the enterprise.
Pattern Dynamics of Cross Diffusion Predator–Prey System with Strong Allee Effect and Hunting Cooperation
Authors: Zhu Meng , Li Jing , Lian Xinze
Published: September 2022

In this paper, we consider a Leslie–Gower cross diffusion predator–prey model with a strong Allee effect and hunting cooperation. We mainly investigate the effects of self diffusion and cross diffusion on the stability of the homogeneous state point and processes of pattern formation. Using eigenvalue theory and Routh–Hurwitz criterion, we analyze the local stability of positive equilibrium solutions. We give the conditions of Turing instability caused by self diffusion and cross diffusion in detail. In order to discuss the influence of self diffusion and cross diffusion, we choose self diffusion coefficient and cross diffusion coefficient as the main control parameters. Through a series of numerical simulations, rich Turing structures in the parameter space were obtained, including hole pattern, strip pattern and dot pattern. Furthermore, We illustrate the spatial pattern through numerical simulation. The results show that the dynamics of the model exhibits that the self diffusion and cross diffusion control not only form the growth of dots, stripes, and holes, but also self replicating spiral pattern growth. These results indicate that self diffusion and cross diffusion have important effects on the formation of spatial patterns.
On the Short Wave Instability of the Liquid/Gas Contact Surface in Porous Media
Authors: Shargatov Vladimir A. , Tsypkin George G. , Gorkunov Sergey V. , Kozhurina Polina I. , Bogdanova Yulia A.
Published: September 2022

We consider a problem of hydrodynamic stability of the liquid displacement by gas in a porous medium in the case when a light gas is located above the liquid. The onset of instability and the evolution of the small shortwave perturbations are investigated. We show that when using the Darcy filtration law, the onset of instability may take place at an infinitely large wavenumber when the normal modes method is inapplicable. The results of numerical simulation of the nonlinear problem indicate that the anomalous growth of the amplitude of shortwave small perturbations persists, but the growth rate of amplitude decreases significantly compared to the results of linear analysis. An analysis of the stability of the gas/liquid interface is also carried out using a network model of a porous medium. It is shown that the results of surface evolution calculations obtained using the network model are in qualitative agreement with the results of the continual approach, but the continual model predicts a higher velocity of the interfacial surfaces in the capillaries. The growth rate of perturbations in the network model also increases with decreasing perturbation wavelength at a constant amplitude.
Dynamic Model Selection Based on Demand Pattern Classification in Retail Sales Forecasting
Authors: E Erjiang , Yu Ming , Tian Xin , Tao Ye
Published: September 2022

Many forecasting techniques have been applied to sales forecasts in the retail industry. However, no one prediction model is applicable to all cases. For demand forecasting of the same item, the different results of prediction models often confuse retailers. For large retail companies with a wide variety of products, it is difficult to find a suitable prediction model for each item. This study aims to propose a dynamic model selection approach that combines individual selection and combination forecasts based on both the demand patterns and the out-of-sample performance for each item. Firstly, based on both metrics of the squared coefficient of variation (CV2) and the average inter-demand interval (ADI), we divide the demand patterns of items into four types: smooth, intermittent, erratic, and lumpy. Secondly, we select nine classical forecasting methods in the M-Competitions to build a pool of models. Thirdly, we design two dynamic weighting strategies to determine the final prediction, namely DWS-A and DWS-B. Finally, we verify the effectiveness of this approach by using two large datasets from an offline retailer and an online retailer in China. The empirical results show that these two strategies can effectively improve the accuracy of demand forecasting. The DWS-A method is suitable for items with the demand patterns of intermittent and lumpy, while the DWS-B method is suitable for items with the demand patterns of smooth and erratic.
Secure DNA-Coding Image Optical Communication Using Non-Degenerate Hyperchaos and Dynamic Secret-Key
Authors: Wen Heping , Liu Zhen , Lai Haowen , Zhang Chongfu , Liu Linhao , Yang Jieyi , Lin Yiting , Li Yunqi , Liao Yunlong , Ma Linchao , Chen Zefeng , Li Rui
Published: September 2022

With the aim of tackling insufficient security in the chaotic encryption algorithm for digital images in the Optical Access Network, a color image encryption scheme combining non-degenerate discrete hyperchaotic system and deoxyribonucleic acid (DNA) dynamic encoding is proposed. First, a new non-degenerate hyperchaotic system is constructed with all positive Lyapunov and more complex dynamic characteristics. Furthermore, the key sequence based on non-degenerate hyperchaotic system is generated using plaintext correlation to achieve the effect of a dynamic secret key. Next, a binary bit-planes permutation is performed on the image using one of the key sequences. Then, the chaotic key sequence is used to sequentially perform DNA encoding, obfuscation, and decoding. Finally, a binary bit-planes obfuscation is performed to obtain the final ciphertext. The research results show that the non-degenerate chaotic sequence can pass the NIST 800-22 test, and the corresponding encryption algorithm can resist various common attacks and has a strong anti-interference ability. In addition, the algorithm is verified on ARM-Embedded, which proves that the encryption system proposed in this paper is a feasible secure communication technology scheme. Therefore, the scheme proposed in this paper is helpful to provide new ideas for the design and application of high-security cryptosystem in optical access network.
Binarization Technique Comparisons of Swarm Intelligence Algorithm: An Application to the Multi-Demand Multidimensional Knapsack Problem
Authors: García José , Moraga Paola , Crawford Broderick , Soto Ricardo , Pinto Hernan
Published: September 2022

In order to minimize execution times, improve the quality of solutions, and address more extensive target situations, optimization techniques, particularly metaheuristics, are continually improved. Hybridizing procedures are one of these noteworthy strategies due to their wide range of applications. This article describes a hybrid algorithm that combines the k-means method to produce a binary version of the cuckoo search and sine cosine algorithms. The binary algorithms are applied on the NP-hard multi-demand multidimensional knapsack problem. This problem is of particular interest because it has two types of constraints. The first group of constraints is related to the capacity of the knapsacks, and a second type is associated with the demand that must be met. Experiments were undertaken to acquire insight into the contribution of the k-means technique and the local search operator to the final results. Additionally, a comparison is made with two other types of binarization, the first based on a random method and the second based on the percentile concept. The results reveal that the k-means hybrid algorithm consistently provides superior results in most cases studied. In particular, incorporating the local search operator improved the results by an average of 0.23%. On the other hand, when comparing the results with 100 items and 30-30 restrictions, k-means was 1.06% better on average than the random operator.
Semantic Protocol and Resource Description Framework Query Language: A Comprehensive Review
Authors: Houssein Essam H. , Ibrahem Nahed , Zaki Alaa M. , Sayed Awny
Published: September 2022

This review presents various perspectives on converting user keywords into a formal query. Without understanding the dataset’s underlying structure, how can a user input a text-based query and then convert this text into semantic protocol and resource description framework query language (SPARQL) that deals with the resource description framework (RDF) knowledge base? The user may not know the structure and syntax of SPARQL, a formal query language and a sophisticated tool for the semantic web (SEW) and its vast and growing collection of interconnected open data repositories. As a result, this study examines various strategies for turning natural language into formal queries, their workings, and their results. In an Internet search engine from a single query, such as on Google, numerous matching documents are returned, with several related to the inquiry while others are not. Since a considerable percentage of the information retrieved is likely unrelated, sophisticated information retrieval systems based on SEW technologies, such as RDF and web ontology language (OWL), can help end users organize vast amounts of data to address this issue. This study reviews this research field and discusses two different approaches to show how users with no knowledge of the syntax of semantic web technologies deal with queries.
Efficient Ontology Meta-Matching Based on Interpolation Model Assisted Evolutionary Algorithm
Authors: Xue Xingsi , Wu Qi , Ye Miao , Lv Jianhui
Published: September 2022

Ontology is the kernel technique of the Semantic Web (SW), which models the domain knowledge in a formal and machine-understandable way. To ensure different ontologies’ communications, the cutting-edge technology is to determine the heterogeneous entity mappings through the ontology matching process. During this procedure, it is of utmost importance to integrate different similarity measures to distinguish heterogeneous entity correspondence. The way to find the most appropriate aggregating weights to enhance the ontology alignment’s quality is called ontology meta-matching problem, and recently, Evolutionary Algorithm (EA) has become a great methodology of addressing it. Classic EA-based meta-matching technique evaluates each individual through traversing the reference alignment, which increases the computational complexity and the algorithm’s running time. For overcoming this drawback, an Interpolation Model assisted EA (EA-IM) is proposed, which introduces the IM to predict the fitness value of each newly generated individual. In particular, we first divide the feasible region into several uniform sub-regions using lattice design method, and then precisely evaluate the Interpolating Individuals (INIDs). On this basis, an IM is constructed for each new individual to forecast its fitness value, with the help of its neighborhood. For testing EA-IM’s performance, we use the Ontology Alignment Evaluation Initiative (OAEI) Benchmark in the experiment and the final results show that EA-IM is capable of improving EA’s searching efficiency without sacrificing the solution’s quality, and the alignment’s f-measure values of EA-IM are better than OAEI’s participants.
Deployment of the Microeconomic Consumer Theory in the Artificial Neural Networks Modelling: Case of Organic Food Consumption
Authors: Jajić Ivan , Herceg Tomislav , Pejić Bach Mirjana
Published: September 2022

Organic food consumption has become a significant trend in consumer behaviour, determined by various motives, among which the price does not play a major role, thus reflecting the Lancaster approach to the microeconomic consumer theory. Additionally, artificial neural networks (ANNs) have proven to have significant potential in providing accurate and efficient models for predicting consumer behaviour. Considering these two trends, this study aims to deploy the Lancaster approach in the emerging area of artificial intelligence. The paper aims to develop the ANN-based predictive model to investigate the relationship between organic food consumption, demographic characteristics, and health awareness attitudes. Survey research has been conducted on a sample of Croatian inhabitants, and ANN models have been used to assess the importance of various determinants for organic food consumption. A Three-layer Multilayer Perceptron Neural Networks (MLPNN) structure has been constructed and validated to select the optimal number of neurons and transfer functions. One layer is used as the first input, while the other two are hidden layers (the first covers the radially symmetrical input, sigmoid function; the second covers the output, softmax function). Three versions of the testing, training, and holdout data structures were used to develop ANNs. The highest accuracy was achieved with a 7-2-1 partition. The best ANN model was determined as the model that was showing the smallest percent of incorrect predictions in the holdout stage, the second-lowest cross-entropy error, the correct classification rate, and the area under the ROC curve. The research results show that the availability of healthy food shops and consumer awareness of these shops strongly impacts organic food consumption. Using the ANN methodology, this analysis confirmed the validity of the Lancaster approach, stating that the characteristics or attributes of goods are defined by the consumer and not by the product itself.
A Novel Surrogate Model-Based Solving Framework for the Black-Box Dynamic Co-Design and Optimization Problem in the Dynamic System
Authors: Zhang Qi , Wu Yizhong , Lu Li
Published: September 2022

When encountering the black-box dynamic co-design and optimization (BDCDO) problem in the multidisciplinary dynamic system, the finite difference technique is inefficient or even infeasible to provide approximate numerical gradient information for the optimization algorithm since it requires numerous original expensive evaluations. Therefore, a solving framework based on the surrogate model of the state equation is introduced to optimize BDCDO. To efficiently construct the surrogate model, a sequential sampling method is presented on the basis of the successive relative improvement ratio. Meanwhile, a termination criterion is suggested to quantify the convergence of the solution. Ultimately, the newly proposed sampling strategy and termination criterion are incorporated into the BDCDO solving framework to optimize two numerical examples and two engineering examples. The results demonstrate that the framework integrating the proposed sampling strategy and termination criterion has the best performance in terms of the accuracy, efficiency, and computational budget compared to the existing methods.
In-Situ Sludge Reduction Performance and Mechanism in Sulfidogenic Anoxic–Oxic–Anoxic Membrane Bioreactors
Authors: Li Chengyue , Maqbool Tahir , Kang Hongyu , Zhang Zhenghua
Published: September 2022

The excess sludge generated from the activated sludge process remains a big issue. Sustainable approaches that achieve in situ sludge reduction with satisfactory effluent quality deserve attention. This study explored the sludge reduction performance of sulfidogenic anoxic–oxic–anoxic (AOA) membrane bioreactors. The dynamics of the microbial community and metabolic pathways were further analyzed to elucidate the internal mechanism of sludge reduction. Compared with the conventional anoxic–oxic–oxic membrane bioreactor (MBRcontrol), AOAS150 (150 mg/L SO42− in the membrane tank) and AOAS300 (300 mg/L SO42− in the membrane tank) reduced biomass production by 40.39% and 47.45%, respectively. The sulfide reduced from sulfate could enhance the sludge decay rate and decrease sludge production. Extracellular polymeric substances (EPSs) destruction and aerobic lysis contributed to sludge reduction in AOA bioreactors. The relative abundance of Bacteroidetes (phylum), sulfate-reducing bacteria (SRB, genus), and Ignavibacterium (genus) increased in AOA bioreactors compared with MBRcontrol. Our metagenomic analysis indicated that the total enzyme-encoding genes involved in glycolysis, denitrification, and sulfate-reduction processes decreased over time in AOAS300 and were lower in AOAS300 than AOAS150 at the final stage of operation. The excess accumulation of sulfide in AOAS300 may inactive the functional bacteria, and sulfide inhibition induced sludge reduction.
A Study on the Design of Bending Process According to the Shape of Initial Billets for Bi-Metal Elbow
Authors: Ha Seonghun , Cho Daehwan , Park Joonhong , Kim Seongjae
Published: September 2022

Studies have been steadily conducted on the forming process of the bending pipe that enables the transport of underground resources. Recently, it has been suggested that bent pipes for transport withstand high pressure during the forming process, but it is judged that the research on methods able to overcome the limitations of non-uniform dimensional distribution due to the difference in the mechanical properties and thickness of the outer and inner pipes is insufficient. This study proposes a new precision forging method called the cut-forged-joint process (CFJP) for the manufacture of bent pipe containing bi-metal. The initial billet and mandrel were designed considering the standard dimensions of bent pipes, and pre-simulation was performed applied to the designed models. The results of dimensional accuracy obtained by forging experiments and the computational forming simulation were compared with each other to verify the reliability. As a final outcome, it was confirmed that it is possible to secure the dimensional accuracy of bi-metal bent pipes by applying the newly proposed CFJP.
Influence of Yttrium on the Phase Composition of the Ti-Al System Obtained by the ‘Hydride Technology’
Authors: Karakchieva Natalia , Artemenko Alina , Lepakova Olga , Sachkov Victor , Kurzina Irina
Published: September 2022

In this study, the influence of yttrium on the formation of the structural-phase state of the Ti-Al alloy, obtained by the “hydride technology” (GT) method, has been analyzed. Using transmission electron microscopy (TEM) and X-ray spectral microanalysis, the authors of the work have established the following phases formed in the sample volume and on the surface: Ti3Al, TiAl, Al, α-Ti, Ti3Al5, Y2Al, Y5Al3, YAl3, YAl, and Y6Ti4Al43. The lamellar structure has been formed in the alloy volume. The average width of the Al-rich lamellae was 0.36 µm and that of the Ti-rich lamellae was 0.21 µm. The formation of a triple Y6Ti4Al43 phase, which is localized along the boundaries of the lamellar structure, has been recorded. The localization scheme of the formed phases of the TAY alloy has been proposed.
Solute Effect on Grain Refinement of Al- and Mg-Alloys: An Overview of the Recent Advances Made by the LiME Research Hub
Authors: Gao Feng , Fan Zhongyun
Published: September 2022

Grain refinement is of importance for metallic materials since it provides multiple benefits, such as improved castability, reduced casting defects and improved mechanical properties. From extensive research carried out in the past decades, it has been widely accepted that solute is one of the crucial factors for achieving grain refinement. However, grain refinement is a complex phenomenon, depending on not only solutes in the melt to provide growth restriction but also the physical and chemical nature of the nucleant particles (either endogenous or exogenous). Although significant progress has been made on the subject, some critical questions still remain open, and a comprehensive understanding of the mechanisms of solute effect on grain refinement is still desirable. In this paper, we present an overview of the solute effect on grain refinement based on our recent advances made in the LiME Research Hub. This covers the effect of solute on nucleation potency of nucleant particles due to interfacial segregation, columnar to equiaxed transition (CET), growth restriction and eventually on the overall grain refinement.
Genomic Comparative Analysis of Cordyceps pseudotenuipes with Other Species from Cordyceps
Authors: Lu Yingling , Wang Yi , Yuan Xiaolong , Huang Ou , Dong Quanying , Li Dandan , Ding Shujin , Ma Fuxian , Yu Hong
Published: September 2022

The whole genome of Cordyceps pseudotenuipes was sequenced, annotated, and compared with three related species to characterize the genome. The antibiotics and Secondary Metabolites Analysis Shell (antiSMASH) and local BLAST analysis were used to explore the secondary metabolites (SMs) and biosynthesis gene clusters (BGCs) of the genus Cordyceps. The genome-wide basic characteristics of C. pseudotenuipes, C. tenuipes, C. cicadae, and C. militaris revealed unequal genome size, with C. cicadae as the largest (34.11 Mb), followed by C. militaris (32.27 Mb). However, the total gene lengths of C. pseudotenuipes and C. tenuipes were similar (30.1 Mb and 30.06 Mb). The GC contents of C. pseudotenuipes, C. tenuipes, C. cicadae, and C. militaris genomes differed slightly (51.40% to 54.11%). AntiSMASH and local BLAST analysis showed that C. pseudotenuipes, C. tenuipes, C. cicadae, and C. militaris had 31, 28, 31, and 29 putative SM BGCs, respectively. The SM BGCs contained different quantities of polyketide synthetase (PKS), nonribosomal peptide synthetase (NRPS), terpene, hybrid PKS + NRPS, and hybrid NRPS + Other. Moreover, C. pseudotenuipes, C. tenuipes, C. cicadae, and C. militaris had BGCs for the synthesis of dimethylcoprogen. C. pseudotenuipes, C. tenuipes, and C. cicadae had BGCs for the synthesis of leucinostatin A/B, neosartorin, dimethylcoprogen, wortmanamide A/B, and beauvericin. In addition, the SM BGCs unique to C. pseudotenuipes were clavaric acid, communesin, and deoxynivalenol. Synteny analysis indicated that the scaffolds where the SM BGC was located were divided into more than 70 collinear blocks, and there might be rearrangements. Altogether, these findings improved our understanding of the molecular biology of the genus Cordyceps and will facilitate the discovery of new biologically active SMs from the genus Cordyceps using heterologous expression and gene knockdown methods.
NMR-Based Metabolomic Analysis of Plasma in Patients with Adult Congenital Heart Disease and Associated Pulmonary Arterial Hypertension: A Pilot Study
Authors: Xu Beizhu , Huang Caihua , Zhang Caojin , Lin Donghai , Wu Weifeng
Published: September 2022

Patients with unrepaired congenital heart disease (CHD) are prone to pulmonary arterial hypertension (PAH). The ovine pulmonary arterial smooth muscle cells exposed to increased pulmonary blood flow (PBF) exhibited hyperproliferation and metabolic alterations, but the metabolic disorders of patients with CHD and associated PAH (PAH-CHD) have not yet been fully understood. Adult CHD patients were prospectively included and divided into the PAH-CHD group (n = 24) and CHD group (n = 38), while healthy adults were included as healthy control (HC) group (n = 29). Plasma from each subject was prepared for nuclear magnetic resonance (NMR) detection. 1H-NMR spectra were acquired using 850 MHz NMR spectrometer. A total of 28 metabolites were identified from the NMR spectra and their relative concentrations were calculated and analyzed by multivariate and univariate statistical analyses and metabolic pathway analysis. Receiver operating characteristic (ROC) curve analysis and correlation analysis were performed to identify potential biomarkers and assess their roles in clinical assessment. Multivariate statistical analysis showed that the metabolic profile of PAH-CHD was altered relative to CHD or HC, while that of CHD was altered relative to HC. The identified characteristic metabolites were alanine, glucose, glycine, threonine and lactate, and the areas under the ROC curves (AUCs) were 0.769, 0.808, 0.711, 0.842 and 0.817, respectively. Multivariate ROC curve analysis showed AUCs ranging from 0.895 to 0.955 for the combination of these characteristic metabolites. The correlation analysis indicated that lactate and threonine were significantly correlated with mean pulmonary arterial pressure, pulmonary vascular resistance and N-terminal pro-B-type natriuretic peptide. The increased PBF could trigger global metabolic alterations in patients with CHD, which were more severe in patients with PAH-CHD. The characteristic metabolites have the potential to be biomarkers of PAH-CHD, which could be used for its noninvasive diagnosis, severity and prognosis assessment, thereby improving the management of PAH-CHD.
A Protocol for Fabrication and on-Chip Cell Culture to Recreate PAH-Afflicted Pulmonary Artery on a Microfluidic Device
Authors: Sarkar Tanoy , Nguyen Trieu , Moinuddin Sakib M. , Stenmark Kurt R. , Nozik Eva S. , Saha Dipongkor , Ahsan Fakhrul
Published: September 2022

Pulmonary arterial hypertension (PAH) is a rare pulmonary vascular disease that affects people of all ethnic origins and age groups including newborns. In PAH, pulmonary arteries and arterioles undergo a series of pathological changes including remodeling of the entire pulmonary vasculatures and extracellular matrices, mis-localized growth of pulmonary arterial cells, and development of glomeruloid-like lesions called plexiform lesions. Traditionally, various animal and cellular models have been used to understand PAH pathophysiology, investigate sex-disparity in PAH and monitor therapeutic efficacy of PAH medications. However, traditional models can only partially capture various pathological features of PAH, and they are not adaptable to combinatorial study design for deciphering intricately intertwined complex cellular processes implicated in PAH pathogenesis. While many microfluidic chip-based models are currently available for major diseases, no such disease-on-a-device model is available for PAH, an under investigated disease. In the absence of any chip-based models of PAH, we recently proposed a five-channel polydimethylsiloxane (PDMS)-based microfluidic device that can emulate major pathological features of PAH. However, our proposed model can make a bigger impact on the PAH field only when the larger scientific community engaged in PAH research can fabricate the device and develop the model in their laboratory settings. With this goal in mind, in this study, we have described the detailed methodologies for fabrication and development of the PAH chip model including a thorough explanation of scientific principles for various steps for chip fabrication, a detailed list of reagents, tools and equipment along with their source and catalogue numbers, description of laboratory setup, and cautionary notes. Finally, we explained the methodologies for on-chip cell seeding and application of this model for studying PAH pathophysiology. We believe investigators with little or no training in microfluidic chip fabrication can fabricate this eminently novel PAH-on-a-chip model. As such, this study will have a far-reaching impact on understanding PAH pathophysiology, unravelling the biological mystery associated with sexual dimorphism in PAH, and developing PAH therapy based on patient sex and age.
NO2 Sensing Behavior of Compacted Chemically Treated Multi-Walled Carbon Nanotubes
Authors: Lapekin Nikita I. , Golovakhin Valeriy V. , Kim Ekaterina Yu. , Bannov Alexander G.
Published: September 2022

This article is devoted to the investigation of the sensing behavior of chemically treated multi-walled carbon nanotubes (MWNTs) at room temperature. Chemical treatment of MWNTs was carried out with a solution of either sulfuric or chromic acids. The materials obtained were investigated by transmission electron microscopy, scanning electron microscopy, Raman-spectroscopy, X-ray diffraction, and Fourier transform infrared spectroscopy. The active layer of chemiresistive gas sensors was obtained by cold pressing (compaction) at 11 MPa of powders of bare and treated multi-walled carbon nanotubes. The sensing properties of pellets were investigated using a custom dynamic type of station at room temperature (25 ± 2 °C). Detection of NO2 was performed in synthetic air (79 vol% N2, 21 vol% O2). It was found that the chemical treatment significantly affects the sensing properties of multi-walled carbon nanotubes, which is indicated by increasing the response of the sensors toward 100–500 ppm NO2 and lower concentrations.
Quorum Sensing and Quorum Quenching with a Focus on Cariogenic and Periodontopathic Oral Biofilms
Authors: Wright Patricia P. , Ramachandra Srinivas Sulugodu
Published: September 2022

Numerous in vitro studies highlight the role of quorum sensing in the pathogenicity and virulence of biofilms. This narrative review discusses general principles in quorum sensing, including Gram-positive and Gram-negative models and the influence of flow, before focusing on quorum sensing and quorum quenching in cariogenic and periodontopathic biofilms. In cariology, quorum sensing centres on the role of Streptococcus mutans, and to a lesser extent Candida albicans, while Fusobacterium nucleatum and the red complex pathogens form the basis of the majority of the quorum sensing research on periodontopathic biofilms. Recent research highlights developments in quorum quenching, also known as quorum sensing inhibition, as a potential antimicrobial tool to attenuate the pathogenicity of oral biofilms by the inhibition of bacterial signalling networks. Quorum quenchers may be synthetic or derived from plant or bacterial products, or human saliva. Furthermore, biofilm inhibition by coating quorum sensing inhibitors on dental implant surfaces provides another potential application of quorum quenching technologies in dentistry. While the body of predominantly in vitro research presented here is steadily growing, the clinical value of quorum sensing inhibitors against in vivo oral polymicrobial biofilms needs to be ascertained.
Synthetic Peptides against Plant Pathogenic Bacteria
Authors: Badosa Esther , Planas Marta , Feliu Lidia , Montesinos Laura , Bonaterra Anna , Montesinos Emilio
Published: September 2022

The control of plant diseases caused by bacteria that seriously compromise crop productivity around the world is still one of the most important challenges in food security. Integrated approaches for disease control generally lack plant protection products with high efficacy and low environmental and health adverse effects. Functional peptides, either from natural sources or synthetic, are considered as novel candidates to develop biopesticides. Synthetic peptides can be obtained based on the structure of natural compounds or de novo designed, considering the features of antimicrobial peptides. The advantage of this approach is that analogues can be conveniently prepared, enabling the identification of sequences with improved biological properties. Several peptide libraries have been designed and synthetized, and the best sequences showed strong bactericidal activity against important plant pathogenic bacteria, with a good profile of biodegradability and low toxicity. Among these sequences, there are bacteriolytic or antibiofilm peptides that work against the target bacteria, plant defense elicitor peptides, and multifunctional peptides that display several of these properties. Here, we report the research performed by our groups during the last twenty years, as well as our ongoing work. We also highlight those peptides that can be used as candidates to develop novel biopesticides, and the main challenges and prospects.
Improving the Shelf-Life of Fish Burgers Made with a Mix of Sea Bass and Sea Bream Meat by Bioprotective Cultures
Authors: Iacumin Lucilla , Pellegrini Michela , Sist Alice , Tabanelli Giulia , Montanari Chiara , Bernardi Cristian , Comi Giuseppe
Published: September 2022

Seafood products are one of the most perishable foods, and their shelf life is limited by enzymatic and microbial spoilage. Developing methods to extend the shelf life of fresh fish could reduce food waste in the fishery industry, retail stores, and private households. In recent decades, the application of lactic acid bacteria (LAB) as bioprotective cultures has become a promising tool. In this study, we evaluated the use of four starter cultures, previously selected for their properties as bioprotective agents, for sea bass and sea bream burgers biopreservation. Starter cultures impacted the microbial populations, biochemical parameters (pH, TVB-N), and sensory properties of fish burgers, during 10 days of storage at 4 °C and then 20 days at 8 °C in modified atmosphere packaging (MAP). Also, storage time influenced the microbial and physicochemical characteristics of all the tested samples, except for TVB-N values, which were significantly higher in the uninoculated burgers. The volatilome changed in the different treatments, and in particular, the samples supplemented with starter presented a profile that described their rapid growth and colonization, with the production of typical molecules derived from their metabolism. The addition of bioprotective cultures avoided bloating spoilage and improved the sensory parameters of the burgers. The shelf life of the fish burgers supplemented with starter cultures could be extended up to 12 days.
Effect of Phthalates and Their Substitutes on the Physiology of Pseudomonas aeruginosa
Authors: Louis Mélissande , Tahrioui Ali , Verdon Julien , David Audrey , Rodrigues Sophie , Barreau Magalie , Manac’h Maëliss , Thiroux Audrey , Luton Baptiste , Dupont Charly , Calvé Marie Le , Bazire Alexis , Crépin Alexandre , Clabaut Maximilien , Portier Emilie , Taupin Laure , Defontaine Florian , Clamens Thomas , Bouffartigues Emeline , Cornelis Pierre , Feuilloley Marc , Caillon Jocelyne , Dufour Alain , Berjeaud Jean-Marc , Lesouhaitier Olivier , Chevalier Sylvie
Published: September 2022

Phthalates are used in a variety of applications—for example, as plasticizers in polyvinylchloride products to improve their flexibility—and can be easily released into the environment. In addition to being major persistent organic environmental pollutants, some phthalates are responsible for the carcinogenicity, teratogenicity, and endocrine disruption that are notably affecting steroidogenesis in mammals. Numerous studies have thus focused on deciphering their effects on mammals and eukaryotic cells. While multicellular organisms such as humans are known to display various microbiota, including all of the microorganisms that may be commensal, symbiotic, or pathogenic, few studies have aimed at investigating the relationships between phthalates and bacteria, notably regarding their effects on opportunistic pathogens and the severity of the associated pathologies. Herein, the effects of phthalates and their substitutes were investigated on the human pathogen, Pseudomonas aeruginosa, in terms of physiology, virulence, susceptibility to antibiotics, and ability to form biofilms. We show in particular that most of these compounds increased biofilm formation, while some of them enhanced the bacterial membrane fluidity and altered the bacterial morphology.
Molecular Epidemiology of Multidrug-Resistant Pseudomonas aeruginosa Acquired in a Spanish Intensive Care Unit: Using Diverse Typing Methods to Identify Clonal Types
Authors: Adelantado Lacasa Marta , Portillo Maria Eugenia , Lobo Palanco Joaquin , Chamorro Judith , Ezpeleta Baquedano Carmen
Published: September 2022

The increasing number of infections from multidrug-resistant P. aeruginosa (MDRPA) has compromised the selection of appropriate treatment in critically ill patients. Recent investigations have shown the existence of MDRPA global clones that have been disseminated in hospitals worldwide. We aimed to describe the molecular epidemiology and genetic diversity of the MDRPA acquired by Intensive Care Units (ICU) patients in our hospital. We used phenotypic methods to define the MDRPA and molecular methods were used to illustrate the presence of carbapenemase encoding genes. To characterize the MDRPA isolates, we used MALDI-TOF biomarker peaks, O-antigen serotyping, and multi-locus sequence typing analyses. Our data show that the most widely distributed MDRPA clone in our ICU unit was the ST175 strain. These isolates were further investigated by the whole-genome sequencing technique to determine the resistome profile and phylogenetic relationships, which showed, as previously described, that the MDR profile was due to the intrinsic resistance mechanisms and not the carbapenemase encoding genes. In addition, this study suggests that the combination of environmental focus and cross-transmission are responsible for the spread of MDRPA clones within our ICU unit. Serotyping and MALDI-TOF analyses are useful tools for the early detection of the most prevalent MDRPA clones in our hospital. Using these methods, semi-directed treatments can be introduced at earlier stages and healthcare professionals can actively search for environmental foci as possible sources of outbreaks.
Recovery of Rare Earth Elements Minerals in Complex Low-Grade Saprolite Ore by Froth Flotation
Authors: Abaka-Wood George Blankson , Johnson Bob , Addai-Mensah Jonas , Skinner William
Published: September 2022

This study presented the first in a series of investigations currently underway to develop efficacious, cost-effective, and benign processing opportunities to produce rare earth elements (REE)–rich concentrate from an Australian complex low–grade saprolite ore [1.14% total rare earth oxides (TREO) grade], which is primarily exploited for its gold and copper values. This work specifically presented a preliminary flotation investigation carried out on the ore using sodium oleate as a collector. The relative effects of pulp pH, desliming, and depressants were investigated to ascertain any chance of recovering and upgrading REE minerals in saprolite ore using three different processing configurations. Based on the experimental results, flotation processes carried out on raw feed allowed the recovery of the majority of REE minerals (>50%), but the process was unselective, where clay and silicate gangue minerals reported into the flotation concentrate along with the REE minerals. However, desliming before flotation in the presence of depressants (starch and sodium silicate) improved REE minerals flotation selectivity, which produced concentrates assaying 5.87% and 4.22% TREO grades, with corresponding recoveries of 45% and 50% at pulp pH 9 and 10.5, respectively. Mineralogical analysis conducted on selected flotation concentrate indicated that silicate and clay gauge minerals were recovered via the synergistic act of surface activation and entrainment due to their fine to ultrafine nature. A comparison of all the test results revealed a haphazard grade–recovery relationship suggesting that there is an opportunity to further maximize both REE recovery and grade through further flotation studies where other process parameters may be investigated and optimized. The prospect of using magnetic separation has also been suggested.
Development of Direct Immobilization Technique of Ag Nanoparticles on Resin Substrates Imparting High Antibacterial and Antiviral Activities
Authors: Seino Satoshi , Ohkubo Yuji , Magara Tomonari , Enomoto Hiroki , Nakajima Eri , Nishida Tomoki , Imoto Yasuo , Nakagawa Takashi
Published: September 2022

A new method has been developed to impart the antimicrobial activity of silver nanoparticles to resin substrates. A resin substrate immersed in an aqueous solution of silver nitrate was irradiated with gamma ray or high energy electron beams. Silver nanoparticles were successfully immobilized on the resin surface directly by chemical reactions induced by ionizing radiation. It was experimentally confirmed that various resin materials, such as acrylonitrile-butadiene-styrene, polyethylene, polypropylene, polyvinyl chloride, and polycarbonate, were applicable for this process. The effects of gamma ray or electron beam irradiation on resin substrates were almost negligible since the irradiation dose was equal or less than that used for sterilization. Despite the small amount of Ag loadings, the obtained samples showed high antibacterial and antiviral activities.
Removal of Benzene and Toluene from Synthetic Wastewater by Adsorption onto Magnetic Zeolitic Imidazole Framework Nanocomposites
Authors: Kyzas George Z. , McKay Gordon , Al-Musawi Tariq J. , Salehi Sabereh , Balarak Davoud
Published: September 2022

Considering the risk associated with exposure to benzene and toluene in water resources, researchers have been motivated to conduct studies to remove them from aqueous solutions. Thus, by performing the present study, the potential of Fe3O4/zeolite imidazolate framework nanoparticles (Fe3O4@ZIF-8) was evaluated for the adsorption of benzene and toluene. Accordingly, the solution pH, Fe3O4@ZIF-8 dosage, mixing time, concentration of benzene and toluene, and temperature, were the parameters considered for conducting the batch experiments, for which their effect on adsorption efficiency was evaluated. Our conducted experiments introduced the neutral pH as the best pH range to obtain the maximum removal. Fitting the adsorption data into the various models revealed the aptness of the Langmuir isotherm equation in describing experimental information and highest adsorption capacity; for benzene it was 129.4, 134.2, 137.3, and 148.2 mg g−1, but for toluene it was 118.4, 125.2, 129.6, and 133.1 mg g−1, for temperature 20, 30, 40, and 50 °C, respectively. Using obtained optimal conditions, the adsorption efficiencies of benzene and toluene were obtained to be 98.4% and 93.1%, respectively. Kinetic studies showed acceptable coefficients for PSO kinetics and confirmed its suitability. Also, the recyclability results showed that for six consecutive periods of the adsorption-desorption process, the percentage of removal decreased by only 6% for benzene and toluene. Moreover, calculating thermodynamic parameter changes for benzene and toluene removal confirmed the favorability and spontaneity of the studied process and its endothermic nature. Considering the above findings, Fe3O4@ZIF-8 was found to be an operative adsorbent for removing pollutants.