bluuebunny/crossref_metadata_2025 huggingface dataset:
Statistical and Ideal Convergences in Topology
Authors: Georgiou D. , Prinos G. , Sereti F.
Published: January 2023

The notion of convergence wins its own important part in the branch of Topology. Convergences in metric spaces, topological spaces, fuzzy topological spaces, fuzzy metric spaces, partially ordered sets (in short, posets), and fuzzy ordered sets (in short, fosets) develop significant chapters that attract the interest of many studies. In particular, statistical and ideal convergences play their own important role in all these areas. A lot of studies have been devoted to these special convergences, and many results have been proven. As a consequence, the necessity to produce and extend new results arises. Since there are many results on different kinds of convergences in different areas, we present a review paper on this research topic in order to collect the most essential results, which leads us to provide open questions for further investigation. More precisely, we present and gather definitions and results which have been proven for different kinds of convergences, mainly on statistical/ideal convergences, in metric spaces, topological spaces, fuzzy topological spaces, fuzzy metric spaces, posets, and fosets. Based on this presentation, we provide new open problems for further investigation on related topics. The study of these problems will create new “roads”, enriching the branch of convergences in the field of Topology.
An Alternative Lambert-Type Distribution for Bounded Data
Authors: Varela Héctor , Rojas Mario A. , Reyes Jimmy , Iriarte Yuri A.
Published: January 2023

In this article, we propose a new two-parameter distribution for bounded data such as rates, proportions, or percentages. The density function of the proposed distribution, presenting monotonic, unimodal, and inverse-unimodal shapes, tends to a positive finite value at the lower end of its support, which can lead to a better fit of the lower empirical quantiles. We derive some of the main structural properties of the new distribution. We make a description of the skewness and kurtosis of the distribution. We discuss the parameter estimation under the maximum likelihood method. We developed a simulation study to evaluate the behavior of the estimators. Finally, we present two applications to real data providing evidence that the proposed distribution can perform better than the popular beta and Kumaraswamy distributions.
Improved Least-Squares Progressive Iterative Approximation for Tensor Product Surfaces
Authors: Hu Qianqian , Wang Zhifang , Liang Ruyi
Published: January 2023

Geometric iterative methods, including progressive iterative approximation and geometric interpolation methods, are efficient for fitting a given data set. With the development of big data technology, the number of fitting data points has become massive, and the progressive iterative approximation for least-squares fitting (LSPIA) is generally applied to fit mass data. Combining the Schulz iterative method for calculating the Moore–Penrose generalized inverse matrix with the traditional LSPIA method, this paper presents an accelerated LSPIA method for tensor product surfaces and shows that the corresponding iterative surface sequence converged to the least-squares fitting surface of the given data set. The iterative format is that of a non-stationary iterative method, and the convergence rate increased rapidly as the iteration number increased. Some numerical examples are provided to illustrate that the proposed method has a faster convergence rate.
A New Alpha Power Cosine-Weibull Model with Applications to Hydrological and Engineering Data
Authors: Alghamdi Abdulaziz S. , Abd El-Raouf M. M.
Published: January 2023

Modifying the existing probability models in the literature and introducing new extensions of the existing probability models is a prominent and interesting research topic. However, in the most recent era, the extensions of the probability models via trigonometry methods have received great attention. This paper also offers a novel trigonometric version of the Weibull model called a new alpha power cosine-Weibull (for short, “NACos-Weibull”) distribution. The NACos-Weibull distribution is introduced by incorporating the cosine function. Certain distributional properties of the NACos-Weibull model are derived. The estimators of the NACos-Weibull model are derived by implementing the maximum likelihood approach. Three simulation studies are provided for different values of the parameters of the NACos-Weibull distribution. Finally, to demonstrate the effectiveness of the NACos-Weibull model, three applications from the hydrological and engineering sectors are considered.
Statistical Analysis of Descending Open Cycles of Collatz Function
Authors: Barghout Kamal , Hajji Wadii , Abu-Libdeh Nidal , Al-Jamal Mohammad
Published: January 2023

Collatz dynamic systems present a statistical space that can be studied rigorously. In a previous study, the author presented Collatz space in a unique dynamic numerical mode by tabulating a sequential correlation pattern of division by 2 of Collatz function’s even numbers until the numbers became odd with a consecutive occurrence, following an attribute of a 50:50 probability of division by 2 once (ascending behavior) as opposed to division by 2 more than once (descending behavior). In this paper, we describe the path of the Collatz function as sequences comprised of groups of the function’s iterates (open cycles) that end up with the first odd integer that is less than the starting odd integer. The descending behavior of the open cycles is attributed to a deterministic factor as observation of the cycles’ sequences shows. We do statistical analysis on 4 large samples of open cycles and orbits to 1. We define R(n) as the cycles’ deterministic variable defined as the ratio of division by 2 once to division by 2 more than once. We use statistical analysis to study the randomness of the orbits of the cycles’ starting odd positive integers as well as orbits to 1 up to 1,002,097,149.
Solar Energy Production Forecasting Based on a Hybrid CNN-LSTM-Transformer Model
Authors: Al-Ali Elham M. , Hajji Yassine , Said Yahia , Hleili Manel , Alanzi Amal M. , Laatar Ali H. , Atri Mohamed
Published: January 2023

Green energy is very important for developing new cities with high energy consumption, in addition to helping environment preservation. Integrating solar energy into a grid is very challenging and requires precise forecasting of energy production. Recent advances in Artificial Intelligence have been very promising. Particularly, Deep Learning technologies have achieved great results in short-term time-series forecasting. Thus, it is very suitable to use these techniques for solar energy production forecasting. In this work, a combination of a Convolutional Neural Network (CNN), a Long Short-Term Memory (LSTM) network, and a Transformer was used for solar energy production forecasting. Besides, a clustering technique was applied for the correlation analysis of the input data. Relevant features in the historical data were selected using a self-organizing map. The hybrid CNN-LSTM-Transformer model was used for forecasting. The Fingrid open dataset was used for training and evaluating the proposed model. The experimental results demonstrated the efficiency of the proposed model in solar energy production forecasting. Compared to existing models and other combinations, such as LSTM-CNN, the proposed CNN-LSTM-Transformer model achieved the highest accuracy. The achieved results show that the proposed model can be used as a trusted forecasting technique that facilitates the integration of solar energy into grids.
Behavior Cloning and Replay of Humanoid Robot via a Depth Camera
Authors: Wang Quantao , He Ziming , Zou Jialiang , Shi Haobin , Hwang Kao-Shing
Published: January 2023

The technique of behavior cloning is to equip a robot with the capability of learning control skills through observation, which can naturally perform human–robot interaction. Despite many related studies in the context of humanoid robot behavior cloning, the problems of the unnecessary recording of similar actions and more efficient storage forms than recording actions by joint angles or motor counts are still worth discussing. To reduce the storage burden on robots, we implemented an end-to-end humanoid robot behavior cloning system, which consists of three modules, namely action emulation, action memorization, and action replay. With the help of traditional machine learning methods, the system can avoid recording similar actions while storing actions in a more efficient form. A jitter problem in the action replay is also handled. In our system, an action is defined as a sequence of many pose frames. We propose a revised key-pose detection algorithm to keep minimal poses of each action to minimize storage consumption. Subsequently, a clustering algorithm for key poses is implemented to save each action in the form of identifiers series. Finally, a similarity equation is proposed to avoid the unnecessary storage of similar actions, in which the similarity evaluation of actions is defined as an LCS problem. Experiments on different actions have shown that our system greatly reduces the storage burden of the robot while ensuring that the errors are within acceptable limits. The average error of the revised key-pose detection algorithm is reduced by 69% compared to the original and 26% compared to another advanced algorithm. The storage consumption of actions is reduced by 97% eventually. Experimental results demonstrate that the system can efficiently memorize actions to complete behavioral cloning.
5G-Enabled Cyber-Physical Systems for Smart Transportation Using Blockchain Technology
Authors: Rajawat Anand Singh , Goyal S. B. , Bedi Pradeep , Verma Chaman , Ionete Eusebiu Ilarian , Raboaca Maria Simona
Published: January 2023

The physical world can be controlled directly over the Internet once a Cyber-Physical 1 System (CPS) infrastructure is established. The Intelligent Transportation System (ITS) encompasses Wireless Sensor Network (WSN), Vehicular ad hoc network (VANET), and 5G-enabled Internet of Things (IoT) solutions to transform traditional transportation into an ITS. This research investigates the option of running a blockchain-driven security assurance model to safeguard intelligent roads and smart vehicles as part of ITS. The proposed model considers a semi-distributed model in blockchain deployment to ensure satisfactory Internet of Vehicles (IoV) service while mining acceptable security assurance. The experimental outcomes on intelligent roads and smart parking management indicate that the proposed model achieves comparably good data delivery and reduced latency, paving the way to an innovative deployment of blockchain technologies in IoV for a dependable and trustworthy ITS.
Recent Advances in Stochastic Gradient Descent in Deep Learning
Authors: Tian Yingjie , Zhang Yuqi , Zhang Haibin
Published: January 2023

In the age of artificial intelligence, the best approach to handling huge amounts of data is a tremendously motivating and hard problem. Among machine learning models, stochastic gradient descent (SGD) is not only simple but also very effective. This study provides a detailed analysis of contemporary state-of-the-art deep learning applications, such as natural language processing (NLP), visual data processing, and voice and audio processing. Following that, this study introduces several versions of SGD and its variant, which are already in the PyTorch optimizer, including SGD, Adagrad, adadelta, RMSprop, Adam, AdamW, and so on. Finally, we propose theoretical conditions under which these methods are applicable and discover that there is still a gap between theoretical conditions under which the algorithms converge and practical applications, and how to bridge this gap is a question for the future.
A New Seminorm for d-Tuples of A-Bounded Operators and Their Applications
Authors: Altwaijry Najla , Feki Kais , Minculete Nicuşor
Published: January 2023

The aim of this paper was to introduce and investigate a new seminorm of operator tuples on a complex Hilbert space H when an additional semi-inner product structure defined by a positive (semi-definite) operator A on H is considered. We prove the equality between this new seminorm and the well-known A-joint seminorm in the case of A-doubly-commuting tuples of A-hyponormal operators. This study is an extension of a well-known result in [Results Math 75, 93(2020)] and allows us to show that the following equalities rA(T)=ωA(T)=∥T∥A hold for every A-doubly-commuting d-tuple of A-hyponormal operators T=(T1,…,Td). Here, rA(T),∥T∥A, and ωA(T) denote the A-joint spectral radius, the A-joint operator seminorm, and the A-joint numerical radius of T, respectively.
Analysis of Error and Stability of Nanofluid over Horizontal Channel with Heat/Mass Transfer and Nonlinear Thermal Conductivity
Authors: Zeeshan  , Ahammad N. Ameer , Shah Nehad Ali , Chung Jae Dong , Attaullah  , Rasheed Haroon Ur
Published: January 2023

The current investigation aims to analyze the nanofluid flow between two infinite rotating horizontal channels. The lower plate is porous and stretchable. The impact of physical parameters such as Hall current, thermal characteristics, heat source/sink, chemical reaction on velocity, temperature, and concentration profiles are discussed through graphs. The governing equations are transformed to ordinary differential equations using suitable transformations and then solved numerically using the RK4 approach along with the shooting technique. For varying values of the Schmidt number (SN) and the chemical reaction factor (CRF), the concentration profile declines, but decreases for the activation energy. It is observed that the velocity profile declines with the increasing values of the suction factor. The velocity profile increases when the values of the rotation factors are increased. The temperature field exhibits a rising behavior with increasing values of the thermophoresis factor, Brownian motion, and the thermal radiation factor. It is also observed that the heat transfer rate is significant at the lower wall with the increasing values of the Prandtl number (PN). For the numerical solution, the error estimation and the residue error are calculated for the stability and confirmation of the mathematical model. The novelty of the present work is to investigate the irregular heat source and chemical reaction over the porous rotating channel. A growing performance is revealed by the temperature field, with the increase in the Brownian motion (BM), thermophoresis factor (TF), thermal conductivity factor (TCF), and the radiation factor (RF).
CFD Study of MHD and Elastic Wall Effects on the Nanofluid Convection Inside a Ventilated Cavity Including Perforated Porous Object
Authors: Kolsi Lioua , Selimefendigil Fatih , Omri Mohamed , Rmili Hatem , Ayadi Badreddine , Maatki Chemseddine , Alshammari Badr M.
Published: January 2023

Cost-effective, lightweight design alternatives for the thermal management of heat transfer equipment are required. In this study, porous plate and perforated-porous plates are used for nanoliquid convection control in a flexible-walled vented cavity system under uniform magnetic field effects. The finite element technique is employed with the arbitrary Lagrangian–Eulerian (ALE) method. The numerical study is performed for different values of Reynolds number (200≤Re≤1000), Hartmann number (0≤Ha≤50), Cauchy number (10−8≤Ca≤10−4) and Darcy number (10−6≤Da≤0.1). At Re = 600, the average Nusselt number (Nu) is 6.3% higher by using a perforated porous plate in a cavity when compared to a cavity without a plate, and it is 11.2% lower at Re = 1000. At the highest magnetic field strength, increment amounts of Nu are in the range of 25.4–29.6% by considering the usage of plates. An elastic inclined wall provides higher Nu, while thermal performance improvements in the range of 3.6–6% are achieved when varying the elastic modulus of the wall. When using a perforated porous plate and increasing its permeability, 22.8% increments of average Nu are obtained. A vented cavity without a plate and elastic wall provides the highest thermal performance in the absence of a magnetic field, while using a porous plate with an elastic wall results in higher Nu when a magnetic field is used.
A Pell–Lucas Collocation Approach for an SIR Model on the Spread of the Novel Coronavirus (SARS CoV-2) Pandemic: The Case of Turkey
Authors: Yüzbaşı Şuayip , Yıldırım Gamze
Published: January 2023

In this article, we present a study about the evolution of the COVID-19 pandemic in Turkey. The modelling of a new virus named SARS-CoV-2 is considered by an SIR model consisting of a nonlinear system of differential equations. A collocation approach based on the Pell–Lucas polynomials is studied to get the approximate solutions of this model. First, the approximate solution in forms of the truncated Pell–Lucas polynomials are written in matrix forms. By utilizing the collocation points and the matrix relations, the considered model is converted to a system of the nonlinear algebraic equations. By solving this system, the unknown coefficients of the assumed Pell–Lucas polynomial solutions are determined, and so the approximate solutions are obtained. Secondly, two theorems about the error analysis are given and proved. The applications of the methods are made by using a code written in MATLAB. The parameters and the initial conditions of the model are determined according to the reported data from the Turkey Ministry of Health. Finally, the approximate solutions and the absolute error functions are visualized. To demonstrate the effectiveness of the method, our approximate solutions are compared with the approximate solutions obtained by the Runge–Kutta method. The reliable results are obtained from numerical results and comparisons. Thanks to this study, the tendencies of the pandemic can be estimated. In addition, the method can be applied to other countries after some necessary arrangements.
Parameter Estimation for a Kinetic Model of a Cellular System Using Model Order Reduction Method
Authors: Eshtewy Neveen Ali , Scholz Lena , Kremling Andreas
Published: January 2023

Order reduction methods are important tools for systems engineering and can be used, for example, for parameter estimation of kinetic models for systems biology applications. In particular, the Proper Orthogonal Decomposition (POD) method produces a reduced-order model of a system that is used for solving inverse problems (parameter estimation). POD is an intrusive model order reduction method that is aimed to obtain a lower-dimensional system for a high-dimensional system while preserving the main features of the original system. We use a singular value decomposition (SVD) to compute a reduced basis as it is usually numerically more robust to compute the singular values of the snapshot matrix instead of the eigenvalues of the corresponding correlation matrix. The reduced basis functions are then used to construct a data-fitting function that fits a known experimental data set of system substance concentrations. The method is applied to calibrate a kinetic model of carbon catabolite repression (CCR) in Escherichia coli, where the regulatory mechanisms on the molecular side are well understood and experimental data for a number of state variables is available. In particular, we show that the method can be used to estimate the uptake rate constants and other kinetic parameters of the CCR model.
A New Accelerated Algorithm Based on Fixed Point Method for Convex Bilevel Optimization Problems with Applications
Authors: Thongsri Piti , Panyanak Bancha , Suantai Suthep
Published: January 2023

A new accelerated common fixed point algorithm is introduced and analyzed for a countable family of nonexpansive mappings and then we apply it to solve some convex bilevel optimization problems. Then, under some suitable conditions, we prove a strong convergence result of the proposed algorithm. As an application, we employ the proposed algorithm for regression and classification problems. Moreover, we compare the performance of our algorithm with others. By numerical experiments, we found that our algorithm has a better performance than the others.
A Novel CDMA-Based Secret Message Multiplexing Scheme by Image Data Hiding
Authors: Lee Chih-Hung , Sun Kun-Sheng , Horng Ji-Hwei , Chang Chin-Chen
Published: January 2023

In this paper, based on the concept of Code Division Multiple Access (CDMA), we propose an innovative secret message multiplexing scheme by digital image data hiding. Multiple secret messages distributed for several participants are encoded into a CDMA codeword through CDMA multiplexing and then embedded into a grayscale image. At the receiving side, each intended recipient will be assigned a distinct spreading code as the secret key for data extraction. In this way, even the authorized user can only extract his or her own secret message using an exclusive secret key and has no knowledge about other user’s secret. This characteristic helps to ensure data security. Experimental results demonstrate that the scheme is also resistant to Gaussian noise attack, salt-and-pepper noise attack, and cropping attacks. Those merits sustain the feasibility of the proposed scheme.
Micro-Thrust, Low-Fuel Consumption, and High-Precision East/West Station Keeping Control for GEO Satellites Based on Synovial Variable Structure Control
Authors: Liu Fucheng , Ye Lijun , Liu Chunyang , Wang Jingji , Yin Haining
Published: January 2023

Aiming at the shortcomings of non-optimal fuel consumption and low accuracy of Geosynchronous orbit (GEO) satellites in the east/west station keeping (EWSK) at the current stage, a micro-thrust EWSK algorithm for GEO satellites based on a single-synovial surface is proposed. This algorithm has the characteristics of low fuel consumption and high control precision. However, when this algorithm performs GEO station switching under the condition of limited velocity increment, the mean longitude capture path may not be optimal, the capture time of the mean longitude is too long, and the engineering applicability is not good. In view of the above problems, a micro-thrust EWSK for GEO satellites based on dual synovial surfaces is proposed. Through the advance planning of the mean longitude, the control lag caused by the limited velocity increment is eliminated, the optimal path-planning problem of the mean longitude is solved, and the capture time of the mean longitude is greatly shortened. The two EWSK algorithms proposed in this paper have the advantages of small calculation amount, optimal fuel consumption, high precision and strong stability, which have good engineering application value.
A Periodically Rotating Distributed Forcing of Flow over a Sphere for Drag Reduction
Authors: Son Donggun , Lee Jungil
Published: January 2023

In the present study, we propose a periodically rotating distributed forcing for turbulent flow over a sphere for its drag reduction. The blowing/suction forcing is applied on a finite slot of the sphere surface near the flow separation, and unsteady sinusoidal forcing velocities are azimuthally distributed on the sphere surface. This forcing profile periodically rotates in the azimuthal direction over time with a forcing frequency, satisfying the instantaneous zero net mass flux. The Reynolds number considered is Re=104 and large eddy simulations are conducted to assess the control performance. It is shown that the drag reduction performance varies with the forcing frequency, and the control results are classified into low-frequency ineffective, effective drag reduction, and high-frequency saturation regimes. With forcing frequencies in the effective drag reduction regime, a helical vortex is generated from the forcing on the sphere and evolves in the shear layer, and this vortex is responsible for the separation delay and flow reattachment resulting in the base pressure recovery and drag reduction. The maximum drag reduction is about 44% with the forcing frequency in the effective drag reduction regime, while controls in other regimes do not produce a drag reduction.
Dynamic Candidate Solution Boosted Beluga Whale Optimization Algorithm for Biomedical Classification
Authors: Houssein Essam H. , Sayed Awny
Published: January 2023

In many fields, complicated issues can now be solved with the help of Artificial Intelligence (AI) and Machine Learning (ML). One of the more modern Metaheuristic (MH) algorithms used to tackle numerous issues in various fields is the Beluga Whale Optimization (BWO) method. However, BWO has a lack of diversity, which could lead to being trapped in local optimaand premature convergence. This study presents two stages for enhancing the fundamental BWO algorithm. The initial stage of BWO’s Opposition-Based Learning (OBL), also known as OBWO, helps to expedite the search process and enhance the learning methodology to choose a better generation of candidate solutions for the fundamental BWO. The second step, referred to as OBWOD, combines the Dynamic Candidate Solution (DCS) and OBWO based on the k-Nearest Neighbor (kNN) classifier to boost variety and improve the consistency of the selected solution by giving potential candidates a chance to solve the given problem with a high fitness value. A comparison study with present optimization algorithms for single-objective bound-constraint optimization problems was conducted to evaluate the performance of the OBWOD algorithm on issues from the 2022 IEEE Congress on Evolutionary Computation (CEC’22) benchmark test suite with a range of dimension sizes. The results of the statistical significance test confirmed that the proposed algorithm is competitive with the optimization algorithms. In addition, the OBWOD algorithm surpassed the performance of seven other algorithms with an overall classification accuracy of 85.17% for classifying 10 medical datasets with different dimension sizes according to the performance evaluation matrix.
Laser-Induced Porcine Model of Experimental Retinal Vein Occlusion: An Optimized Reproducible Approach
Authors: Mæng Mads Odgaard , Roshanth Nirrooja , Kruse Anders , Nielsen Jonas Ellegaard , Kjærgaard Benedict , Honoré Bent , Vorum Henrik , Cehofski Lasse Jørgensen
Published: January 2023

Retinal vein occlusion (RVO) is a frequent visually disabling condition. The management of RVO continues to challenge clinicians. Macular edema secondary to RVO is often recurrent, and patients typically require intravitreal injections for several years. Understanding molecular mechanisms in RVO is a key element in improving the treatment of the condition. Studying the molecular mechanisms in RVO at the retinal level is possible using animal models of experimental RVO. Most studies of experimental RVO have been sporadic, using only a few animals per experiment. Here, we report on 10 years of experience of the use of argon laser-induced experimental RVO in 108 porcine eyes from 65 animals, including 65 eyes with experimental branch retinal vein occlusion (BRVO) and 43 eyes with experimental central retinal vein occlusion (CRVO). Reproducibility and methods for evaluating and controlling ischemia in experimental RVO are reviewed. Methods for studying protein changes in RVO are discussed in detail, including proteomic analysis, Western blotting, and immunohistochemistry. Experimental RVO has brought significant insights into molecular changes in RVO. Testing intravitreal interventions in experimental RVO may be a significant step in developing personalized therapeutic approaches for patients with RVO.
Prevention and Treatment of Chemotherapy-Induced Peripheral Neuropathy (CIPN) with Non-Pharmacological Interventions: Clinical Recommendations from a Systematic Scoping Review and an Expert Consensus Process
Authors: Klafke Nadja , Bossert Jasmin , Kröger Birgit , Neuberger Petra , Heyder Ute , Layer Monika , Winkler Marcela , Idler Christel , Kaschdailewitsch Elke , Heine Rolf , John Heike , Zielke Tatjana , Schmeling Beeke , Joy Sosamma , Mertens Isabel , Babadag-Savas Burcu , Kohler Sara , Mahler Cornelia , Witt Claudia M. , Steinmann Diana , Voiss Petra , Stolz Regina
Published: January 2023

Background: Most individuals affected by cancer who are treated with certain chemotherapies suffer of CIPN. Therefore, there is a high patient and provider interest in complementary non-pharmacological therapies, but its evidence base has not yet been clearly pointed out in the context of CIPN. Methods: The results of a scoping review overviewing the published clinical evidence on the application of complementary therapies for improving the complex CIPN symptomatology are synthesized with the recommendations of an expert consensus process aiming to draw attention to supportive strategies for CIPN. The scoping review, registered at PROSPERO 2020 (CRD 42020165851), followed the PRISMA-ScR and JBI guidelines. Relevant studies published in Pubmed/MEDLINE, PsycINFO, PEDro, Cochrane CENTRAL, and CINAHL between 2000 and 2021 were included. CASP was used to evaluate the methodologic quality of the studies. Results: Seventy-five studies with mixed study quality met the inclusion criteria. Manipulative therapies (including massage, reflexology, therapeutic touch), rhythmical embrocations, movement and mind–body therapies, acupuncture/acupressure, and TENS/Scrambler therapy were the most frequently analyzed in research and may be effective treatment options for CIPN. The expert panel approved 17 supportive interventions, most of them were phytotherapeutic interventions including external applications and cryotherapy, hydrotherapy, and tactile stimulation. More than two-thirds of the consented interventions were rated with moderate to high perceived clinical effectiveness in therapeutic use. Conclusions: The evidence of both the review and the expert panel supports a variety of complementary procedures regarding the supportive treatment of CIPN; however, the application on patients should be individually weighed in each case. Based on this meta-synthesis, interprofessional healthcare teams may open up a dialogue with patients interested in non-pharmacological treatment options to tailor complementary counselling and treatments to their needs.
Metabolomics Analysis of Different Tissues of Lonicera japonica Thunb. Based on Liquid Chromatography with Mass Spectrometry
Authors: Wang Yan , Li Lili , Ji Wenhua , Liu Shuang , Fan Jiali , Lu Heng , Wang Xiao
Published: January 2023

Lonicera japonica Thunb. (LJT) has been widely used as medicines or food additives in Asian countries for thousands of years. The flower buds are often medicinally used, and the other tissues are ignored. However, flowers, leaves and stems have also been reported to have antimicrobial, anti-inflammatory and antioxidant effects. In the current study, un-targeted metabolomics analysis was performed to investigate the metabolic difference among different tissues (flowers, flower buds, stems and leaves) of LJT based on liquid chromatography with mass spectrometry. A total of 171 metabolites were identified, including 28 flavonoids, 35 phenolic acids, 43 iridoids, 9 amino acids, 6 nucleotides, 16 fatty acids, 22 lipids and 12 others. Four new secondary metabolites were discovered. Some flavonoids and iridoids were not detected in leaves and stems. Principal component analysis showed significant differences among four different tissues. Some 27, 81, 113 differential metabolites were found between flowers/flower buds, leaves/flower buds, stems/flower buds, respectively. Primary metabolites showed a higher content in the flowers and flower buds. For the flavonoids, flavones were mainly accumulated in the leaves, flavonols were mainly accumulated in the flower buds, and acylated flavonol glucosides were mainly accumulated in the flowers. Most phenolic acids showed a higher content in the flowers or flower buds, while phenolic acid-glucosides showed significantly higher content in the flower buds. The most abundant iridoids in the LJT also showed a higher content in the flowers and flower buds. These results can provide new insights into the understanding of the metabolites changes in different tissues, and lay a theoretical foundation for the comprehensive utilization of LJT.
Analysis of Whole-Genome Sequences of Pathogenic Gram-Positive and Gram-Negative Isolates from the Same Hospital Environment to Investigate Common Evolutionary Trends Associated with Horizontal Gene Exchange, Mutations and DNA Methylation Patterning
Authors: Korotetskiy Ilya S. , Shilov Sergey V. , Kuznetsova Tatyana , Kerimzhanova Bahkytzhan , Korotetskaya Nadezhda , Ivanova Lyudmila , Zubenko Natalya , Parenova Raikhan , Reva Oleg N.
Published: January 2023

Hospital-acquired infections are a generally recognized problem for healthcare professionals. Clinical variants of Gram-negative and Gram-positive pathogens are characterized with enhanced antibiotic resistance and virulence due to mutations and the horizontal acquisition of respective genetic determinants. In this study, two Escherichia coli, two Klebsiella pneumoniae, three Pseudomonas aeruginosa, two Staphylococcus aureus, one Staphylococcus epidermidis and one Streptococcus pneumoniae showing broad spectra of antibiotic resistance were isolated from patients suffering from nosocomial infections in a local hospital in Almaty, Kazakhstan. The aim of the study was to compare general and species-specific pathways of the development of virulence and antibiotic resistance through opportunistic pathogens causing hospital-acquired infections. The whole-genome PacBio sequencing of the isolates allowed for the genotyping and identification of antibiotic resistance and virulence genetic determinants located in the chromosomes, plasmids and genomic islands. It was concluded that long-read sequencing is a useful tool for monitoring the epidemiological situation in hospitals. Marker antibiotic resistance mutations common for different microorganisms were identified, which were acquired due to antibiotic-selective pressure in the same clinical environment. The genotyping and identification of strain-specific DNA methylation motifs were found to be promising in estimating the risks associated with hospital infection outbreaks and monitoring the distribution and evolution of nosocomial pathogens.
In Vitro Screen of Lactobacilli Strains for Gastrointestinal and Vaginal Benefits
Authors: Anglenius Heli , Mäkivuokko Harri , Ahonen Ilmari , Forssten Sofia D. , Wacklin Pirjo , Mättö Jaana , Lahtinen Sampo , Lehtoranta Liisa , Ouwehand Arthur C.
Published: January 2023

Traditional probiotics comprise mainly lactic acid bacteria that are safe for human use, tolerate acid and bile, and adhere to the epithelial lining and mucosal surfaces. In this study, one hundred commercial and non-commercial strains that were isolated from human feces or vaginal samples were tested with regards to overall growth in culture media, tolerance to acid and bile, hydrogen peroxide (H2O2) production, and adhesion to vaginal epithelial cells (VECs) and to blood group antigens. As a result, various of the tested lactobacilli strains were determined to be suitable for gastrointestinal or vaginal applications. Commercial strains grew better than the newly isolated strains, but tolerance to acid was a common property among all tested strains. Tolerance to bile varied considerably between the strains. Resistance to bile and acid correlated well, as did VEC adhesion and H2O2 production, but H2O2 production was not associated with resistance to bile or acid. Except for L. iners strains, vaginal isolates had better overall VEC adhesion and higher H2O2 production. Species- and strain-specific differences were evident for all parameters. Rank-ordered clustering with nine clusters was used to identify strains that were suitable for gastrointestinal or vaginal health, demonstrating that the categorization of strains for targeted health indications is possible based on the parameters that were measured in this study.
Diversity of Bacterial Soft Rot-Causing Pectobacterium Species Affecting Cabbage in Serbia
Authors: Jelušić Aleksandra , Mitrović Petar , Marković Sanja , Iličić Renata , Milovanović Predrag , Stanković Slaviša , Popović Milovanović Tatjana
Published: January 2023

The aim of this work was to identify and characterize the pectolytic bacteria responsible for the emergence of bacterial soft rot on two summer cabbage hybrids (Cheers F1 and Hippo F1) grown in the Futog locality (Bačka, Vojvodina), known for the five-century-long tradition of cabbage cultivation in Serbia. Symptoms manifesting as soft lesions on outer head leaves were observed during August 2021, while the inner tissues were macerated, featuring cream to black discoloration. As the affected tissue decomposed, it exuded a specific odor. Disease incidence ranged from 15% to 25%. A total of 67 isolates producing pits on crystal violet pectate (CVP) medium were characterized for their phenotypic and genotypic features. The pathogenicity was confirmed on cabbage heads. Findings yielded by the repetitive element palindromic-polymerase chain reaction (rep-PCR) technique confirmed interspecies diversity between cabbage isolates, as well as intraspecies genetic diversity within the P. carotovorum group of isolates. Based on multilocus sequence typing (MLST) using genes dnaX, mdh, icdA, and proA, five representative isolates were identified as Pectobacterium carotovorum (Cheers F1 and Hippo F1), while two were identified as Pectobacterium versatile (Hippo F1) and Pectobacterium odoriferum (Hippo F1), respectively, indicating the presence of diverse Pectobacterium species even in combined infection in the same field. Among the obtained isolates, P. carotovorum was the most prevalent species (62.69%), while P. versatile and P. odoriferum were less represented (contributing by 19.40% and 17.91%, respectively). Multilocus sequence analysis (MLSA) performed with concatenated sequences of four housekeeping genes (proA, dnaX, icdA, and mdh) and constructed a neighbor-joining phylogenetic tree enabled insight into the phylogenetic position of the Serbian cabbage Pectobacterium isolates. Bacterium P. odoriferum was found to be the most virulent species for cabbage, followed by P. versatile, while all three species had comparable virulence with respect to potato. The results obtained in this work provide a better understanding of the spreading routes and abundance of different Pectobacterium spp. in Serbia.
Genomic Characterization of Three Novel Bartonella Strains in a Rodent and Two Bat Species from Mexico
Authors: Gonçalves-Oliveira Jonathan , Gutierrez Ricardo , Schlesener Cory Lee , Jaffe David A. , Aguilar-Setién Alvaro , Boulouis Henri-Jean , Nachum-Biala Yaarit , Huang Bihua C. , Weimer Bart C. , Chomel Bruno B. , Harrus Shimon
Published: January 2023

Rodents and bats are the most diverse mammal group that host Bartonella species. In the Americas, they were described as harboring Bartonella species; however, they were mostly characterized to the genotypic level. We describe here Bartonella isolates obtained from blood samples of one rodent (Peromyscus yucatanicus from San José Pibtuch, Yucatan) and two bat species (Desmodus rotundus from Progreso, and Pteronotus parnellii from Chamela-Cuitzmala) from Mexico. We sequenced and described the genomic features of three Bartonella strains and performed phylogenomic and pangenome analyses to decipher their phylogenetic relationships. The mouse-associated genome was closely related to Bartonella vinsonii. The two bat-associated genomes clustered into a single distinct clade in between lineages 3 and 4, suggesting to be an ancestor of the rodent-associated Bartonella clade (lineage 4). These three genomes showed <95% OrthoANI values compared to any other Bartonella genome, and therefore should be considered as novel species. In addition, our analyses suggest that the B. vinsonii complex should be revised, and all B. vinsonii subspecies need to be renamed and considered as full species. The phylogenomic clustering of the bat-associated Bartonella strains and their virulence factor profile (lack of the Vbh/TraG conjugation system remains of the T4SS) suggest that it should be considered as a new lineage clade (L5) within the Bartonella genus.
Antibiofilm Potential of Coelomic Fluid and Paste of Earthworm Pheretima posthuma (Clitellata, Megascolecidae) against Pathogenic Bacteria
Authors: Hussain Mudassar , Liaqat Iram , Zafar Urooj , Saleem Sadiah , Aftab Muhammad Nauman , Khalid Awais , Modafer Yosra , Alshammari Fahdah Ayed , Mashraqi Abdullah , El-Mansi Ahmed A.
Published: January 2023

Antibiotic drug resistance is a global public health issue that demands new and novel therapeutic molecules. To develop new agents, animal secretions or products are used as an alternative agent to overcome this problem. In this study, earthworm (Pheretima posthuma) coelomic fluid (PCF), and body paste (PBP) were used to analyze their effects as antibiofilm agents against four bacterial isolates MH1 (Pseudomonas aeruginosa MT448672), MH2 (Escherichia coli MT448673), MH3 (Staphylococcus aureus MT448675), and MH4 (Klebsiella pneumoniae MT448676). Coelomic fluid extraction and body paste formation were followed by minimum inhibitory concentrations (MICs), biofilm formation time kinetics, and an antibiofilm assay, using heat and cold shock, sunlight exposure auto-digestion, and test tube methods. The results showed that the MIC values of PCF and PBP against S. aureus, P. aeruginosa, K. pneumoniae, and E. coli bacterial isolates ranged from 50 to 100 μg/mL, while, the results related to biofilm formation for P. aeruginosa, S. aureus, and K. pneumoniae strains were observed to be highly significantly increased (p < 0.005) after 72 h. E. coli produced a significant (p < 0.004) amount of biofilm after 48 h. Following time kinetics, the antibiofilm activity of PCF and PBP was tested at different concentrations (i.e., 25–200 μg/mL) against the aforementioned four strains (MH1–MH4). The findings of this study revealed that both PBP (5.61 ± 1.0%) and PCF (5.23 ± 1.5%) at the lowest concentration (25 μg/mL) showed non-significant (p > 0.05) antibiofilm activity against all the selected strains (MH1-MH4). At 50 μg/mL concentration, both PCF and PBP showed significant (p < 0.05) biofilm inhibition (<40%) for all isolates. Further, the biofilm inhibitory potential was also found to be more significant (p < 0.01) at 100 μg/mL of PCF and PBP, while it showed highly significant (p < 0.001) biofilm inhibition at 150 and 200 μg/mL concentrations. Moreover, more than 90% biofilm inhibition was observed at 200 μg/mL of PCF, while in the case of the PBP, <96% biofilm reduction (i.e., 100%) was also observed by all selected strains at 200 μg/mL. In conclusion, earthworm body fluid and paste have biologically active components that inhibit biofilm formation by various pathogenic bacterial strains. For future investigations, there is a need for further study to explore the potential bioactive components and investigate in depth their molecular mechanisms from a pharmaceutical perspective for effective clinical utilization.
Nur77 Serves as a Potential Prognostic Biomarker That Correlates with Immune Infiltration and May Act as a Good Target for Prostate adenocarcinoma
Authors: Hu Qiong-Ying , Liu Jie , Zhang Xiao-Kun , Yang Wan-Ting , Tao Yu-Tian , Chen Ce , Qian Ye-He , Tang Jin-Shan , Yao Xin-Sheng , Xu Ying-He , Wang Jing-Hui
Published: January 2023

Prostate adenocarcinoma (PRAD) is the most frequent malignancy, and is the second leading cause of death due to cancer in men. Thus, new prognostic biomarkers and drug targets for PRAD are urgently needed. As we know, nuclear receptor Nur77 is important in cancer development and changes in the tumor microenvironment; whereas, the function of Nur77 in PRAD remains to be elucidated. The TCGA database was used to explore the Nur77 expression and its role in the prognosis of PRAD. It was shown that Nur77 was down regulated in PRAD, and low Nur77 expression was correlated with advanced clinical pathologic characteristics (high grade, histological type, age) and poor prognosis. Furthermore, key genes screening was examined by univariate Cox analysis and Kaplan-Meier survival. Additionally, Nur77 was closely related to immune infiltration and some anti-tumor immune functions. The differentially expressed genes (DEGs) were presented by protein-protein interaction (PPI) network analysis. Therefore, the expression level of Nur77 might help predict the survival of PRAD cases, which presents a new insight and a new target for the treatment of PRAD. In vitro experiments verified that natural product malayoside targeting Nur77 exhibited significant therapeutic effects on PRAD and largely induced cell apoptosis by up-regulating the expression of Nur77 and its mitochondrial localization. Taken together, Nur77 is a prognostic biomarker for patients with PRAD, which may refresh the profound understanding of PRAD individualized treatment.
Advances in the Study of Probiotics for Immunomodulation and Intervention in Food Allergy
Authors: Huang Yan-Yan , Liang Yan-Tong , Wu Jia-Min , Wu Wei-Tong , Liu Xin-Tong , Ye Ting-Ting , Chen Xiao-Rong , Zeng Xin-An , Manzoor Muhammad Faisal , Wang Lang-Hong
Published: January 2023

Food allergies are a serious food safety and public health issue. Soybean, dairy, aquatic, poultry, and nut products are common allergens inducing allergic reactions and adverse symptoms such as atopic dermatitis, allergic eczema, allergic asthma, and allergic rhinitis. Probiotics are assumed as an essential ingredient in maintaining intestinal microorganisms’ composition. They have unique physiological roles and therapeutic effects in maintaining the mucosal barrier, immune function, and gastrointestinal tract, inhibiting the invasion of pathogenic bacteria, and preventing diarrhea and food allergies. Multiple pieces of evidence reveal a significant disruptive effect of probiotics on food allergy pathology and progression mechanisms. Thus, this review describes the allergenic proteins as an entry point and briefly describes the application of probiotics in allergenic foods. Then, the role of probiotics in preventing and curing allergic diseases by regulating human immunity through intestinal flora and intestinal barrier, modulating host immune active cells, and improving host amino acid metabolism are described in detail. The anti-allergic role of probiotics in the function and metabolism of the gastrointestinal tract has been comprehensively explored to furnish insights for relieving food allergy symptoms and preventing food allergy.
Exploring the Co-Crystallization of Kojic Acid with Silver(I), Copper(II), Zinc(II), and Gallium(III) for Potential Antibacterial Applications
Authors: Sun Renren , Casali Lucia , Turner Raymond J. , Braga Dario , Grepioni Fabrizia
Published: January 2023

Co-crystallization of kojic acid (HKA) with silver(I), copper(II), zinc(II), or gallium(III) salts yielded three 1D coordination polymers and one 0D complex in which kojic acid was present as a neutral or anionic terminal or bridging ligand. All reactions were conducted mechanochemically via ball milling and manual grinding, or via slurry. All solids were fully characterized via single-crystal and/or powder X-ray diffraction. As kojic acid is a mild antimicrobial compound that is widely used in cosmetics, and the metal cations possess antibacterial properties, their combinations were tested for potential antibacterial applications. The minimal inhibition concentrations (MICs) and minimal biocidal concentrations (MBCs) for all compounds were measured against standard strains of the bacteria P. aeruginosa, S. aureus, and E. coli. All compounds exerted appreciable antimicrobial activity in the order of silver, zinc, copper, and gallium complexes.