bluuebunny/crossref_metadata_2025 huggingface dataset:
Chestnut Honey Is Effective against Mixed Biofilms at Different Stages of Maturity
Authors: Koloh Regina , Balázs Viktória L. , Nagy-Radványi Lilla , Kocsis Béla , Kerekes Erika Beáta , Kocsis Marianna , Farkas Ágnes
Published: March 2024

The irresponsible overuse of antibiotics has increased the occurrence of resistant bacterial strains, which represents one of the biggest patient safety risks today. Due to antibiotic resistance and biofilm formation in bacteria, it is becoming increasingly difficult to suppress the bacterial strains responsible for various chronic infections. Honey was proven to inhibit bacterial growth and biofilm development, offering an alternative solution in the treatment of resistant infections and chronic wounds. Our studies included chestnut honey, valued for its high antibacterial activity, and the bacteria Pseudomonas aeruginosa, methicillin-resistant Staphylococcus aureus, and S. epidermidis, known to form multi-species biofilm communities. Minimum inhibitory concentrations (MIC) of chestnut honey were determined for each bacterial strain. Afterwards, the mixed bacterial biofilms were treated with chestnut honey at different stages of maturity (incubation times: 2, 4, 6, 12, 24 h). The extent of biofilm inhibition was measured with a crystal violet assay and demonstrated by scanning electron microscopy (SEM). As the incubation time increased and the biofilm became more mature, inhibition rates decreased gradually. The most sensitive biofilm was the combination MRSA-S. epidermidis, with a 93.5% inhibition rate after 2 h of incubation. Our results revealed that chestnut honey is suitable for suppressing the initial and moderately mature stages of mixed biofilms.
Microbiological Quality and Safety of Fresh Rabbit Meat with Special Reference to Methicillin-Resistant S. aureus (MRSA) and ESBL-Producing E. coli
Authors: da Silva Guedes Jessica , Velilla-Rodriguez David , González-Fandos Elena
Published: March 2024

The purpose of this investigation was to evaluate the microbial quality and safety of rabbit meat. A total of 49 rabbit meat samples were taken at the retail level. The mesophiles, staphylococci, Enterobacterales, and Pseudomonas spp. counts were 4.94 ± 1.08, 2.59 ± 0.70, 2.82 ± 0.67, and 3.23 ± 0.76 log CFU/g, respectively. Campylobacter spp. were not detected in any sample. Listeria monocytogenes was isolated from one sample (2.04%) at levels below 1.00 log CFU/g. Multi-resistant S aureus was found in seven samples (14.9%). Methicillin-resistant S. aureus, S. epidermidis, S. haemolyticus, M. caseolyticus, and M. sciuri were found in a sample each (10.20%), and all of them were multi-resistant. Multi-resistant ESBL-producing E. coli were detected in two samples from the same retailer (4.08%). The high resistance found in methicillin-resistant staphylococci and ESBL-producing E. coli is of particular concern, and suggests that special measures should be taken in rabbit meat.
Effects of Aspirin Eugenol Ester on Liver Oxidative Damage and Energy Metabolism in Immune-Stressed Broilers
Authors: Zhong Jiale , Zhen Wenrui , Bai Dongying , Hu Xiaodi , Zhang Haojie , Zhang Ruilin , Ito Koichi , Zhang Yi , Zhang Bingkun , Ma Yanbo
Published: March 2024

The aim of this study was to investigate the effects of aspirin eugenol ester (AEE) on liver oxidative damage and energy metabolism in immune-stressed broilers. In total, 312 broilers were divided into 4 groups (saline, LPS, SAEE, and LAEE). Broilers in the saline and LPS groups were fed a basal diet; the SAEE and LAEE groups had an added 0.01% AEE in their diet. Broilers in the LPS and LAEE groups were injected with lipopolysaccharides, while the saline and SAEE groups were injected with saline. Results showed that AEE increased the body weight, average daily gain, and average daily feed intake, as well as decreasing the feed conversion ratio of immune-stressed broilers. AEE protects against oxidative damage in immune-stressed broiler livers by elevating the total antioxidant capacity, superoxide dismutase activity, and glutathione S-transferase alpha 3 (GSTA3) and glutaredoxin 2 (GLRX2) expression, while decreasing malondialdehyde content. AEE lessened inflammation by reducing prostaglandin-F2α production and prostaglandin-endoperoxide synthase 2 (PTGS2) and interleukin-1beta (IL-1β) expression. AEE decreased oxidative phosphorylation rates by increasing succinic acid levels and lowering both adenosine diphosphate (ADP) levels and ceroid lipofuscinosis neuronal 5 (CLN5) expression. AEE modulated the metabolism of phenylalanine, tyrosine, lipids, and cholesterol by reducing the phenyllactate and L-arogenate levels, lowering dopachrome tautomerase (DCT) and apolipoprotein A4 (APOA4) expression, and increasing phenylpyruvic acid and dopa decarboxylase (DDC) expression. In summary, AEE can effectively alleviate liver oxidative damage and energy metabolism disorders in immune-stressed broilers.
Evaluating the Neuroprotective Potential of Caffeinated Coffee in the Context of Aluminum-Induced Neurotoxicity: Insights from a PC12 Cell Culture Model
Authors: Rodak Kamil , Bęben Dorota , Birska Monika , Siwiela Oliwia , Kokot Izabela , Moreira Helena , Radajewska Anna , Szyjka Anna , Kratz Ewa Maria
Published: March 2024

Exposure to aluminum (Al) and its compounds is an environmental factor that induces neurotoxicity, partially through oxidative stress, potentially leading to the development of neurodegenerative diseases. Components of the diet, such as caffeinated coffee, may play a significant role in preventing these diseases. In the present study, an experimental model of PC12 cells (rat pheochromocytoma tumor cells) was developed to investigate the influence of caffeine and caffeinated coffee on neurotoxicity induced by Al compounds and/or oxidative stress. For the induction of neurotoxicity, aluminum maltolate (Almal) and H2O2 were used. The present study demonstrates that 100 μM Almal reduced cell survival, while caffeinated coffee with caffeine concentrations of 5 μg/mL and 80 μg/mL reversed this effect, resulting in a higher than fivefold increase in PC12 cell survival. However, despite the observed antioxidant properties typical for caffeine and caffeinated coffee, it is unlikely that they are the key factors contributing to cell protection against neurotoxicity induced by both oxidative stress and Al exposure. Moreover, the present study reveals that for coffee to exert its effects, it is possible that Al must first activate certain mechanisms within the cell. Therefore, various signaling pathways are discussed, and modifications of these pathways might significantly decrease the risk of Al-induced neurotoxicity.
Voice-Controlled Robotics in Early Education: Implementing and Validating Child-Directed Interactions Using a Collaborative Robot and Artificial Intelligence
Authors: Aguilera Cristhian A. , Castro Angela , Aguilera Cristhian , Raducanu Bogdan
Published: March 2024

This article introduces a voice-controlled robotic system for early education, enabling children as young as four to interact with robots using natural voice commands. Recognizing the challenges posed by programming languages and robot theory for young learners, this study leverages recent advancements in artificial intelligence, such as large language models, to make robots more intelligent and easier to use. This innovative approach fosters a natural and intuitive interaction between the child and the robot, effectively removing barriers to access and expanding the educational possibilities of robotics in the classroom. In this context, a software pipeline is proposed that translates voice commands into robot actions. Each component is tested using different deep learning models and cloud services to determine their suitability, with the best ones being selected. Finally, the chosen setup is validated through an integration test involving children aged 4 to 6 years. Preliminary results demonstrate the system’s capability to accurately recognize and execute voice commands, highlighting its potential as a valuable educational tool for early education.
A Boundary Scan Test Vectors Optimization Method Based on Improved GA-AO* Approach Considering Fault Probability Model
Authors: Su Yuanzhang , Guo Xinfeng , Luo Hang , Wang Jingyuan , Liu Zhen
Published: March 2024

The generation of test vectors is a key technique that affects the efficiency and fault detection rate of the boundary scan test. Aiming at the local optimal solution problem of the current common test vectors generation algorithm, this paper proposes a test vectors generation algorithm based on improved GA-AO* model, through which the test vectors are generated by using the idea of heuristic search and backtracking correction. In order to speed up the heuristic search, this paper designed a heuristic function with both prior and posterior parameters to describe the influence of typical faults on the failure probability index of the test vectors. At the same time, this paper used a genetic algorithm (GA) to determine the specific values of the posterior parameters iteratively. Finally, through theoretical analysis and physical verification, compared with the test vector generated by the traditional method, the test vector generated by this method is optimized on the prior failure probability index and performs better in the physical experiment.
Numerical Simulation of Surface Subsidence and Fracture Evolution Caused by Pulang Copper Mine Mining
Authors: Li Zhengrong , Hou Kepeng , Li Tong , Tang Jingtian , Lu Guangyin
Published: March 2024

Subsidence of the earth’s surface induced by mining activities has always been a critical concern in the relevant research fields. This subsidence disrupts the original geological structures and can lead to secondary geological hazards, environmental degradation, and threats to human lives and property. An in-depth investigation of this issue led to us using the three-dimensional finite-difference numerical simulation software FLAC3D 6.0 in this study. The research focuses on the Prang Copper Mine subsidence area in Yunnan Province, China, with a particular emphasis on the comprehensive analysis of the formation mechanisms of a large-scale crack appearing on the south side of the subsidence area. The study also includes a predictive analysis of the future development trends of this crack. The simulation results indicate that the crack formation was a consequence of the combined effects of uneven surface subsidence induced by underground structural interfaces and underground mining activities. As mining activities continued, the non-uniform subsidence of the surface intensified. The northward (Y-axis) displacement difference of characteristic points A and B on both sides of the crack continuously increased, signifying the widening of the crack. Mining activities also influence the displacement in the X-axis direction, potentially posing risks to support structures on either side of existing drainage channels. Therefore, effective control measures are warranted. Furthermore, this study highlights the possibility that new mining activities may further exacerbate subsidence on the south side of the subsidence area. This research provides valuable insights into the complexity of surface subsidence and its associated risks, offering guidance for mining activity planning and safety measures.
Research on the Impact of a Fluid Field on an Acoustic Field in Herschel–Quincke Tube
Authors: Ma Congcong , Niu Pingping , Zhu Hanhao , Zou Hongyu
Published: March 2024

A study concerning the influence of flow on the Herschel–Quincke duct is presented here, which includes the numerical model, the acoustic source and the absorption condition called the Perfectly Matched Layer. For the excitation of a sound field, a normal mode wave is placed at the inlet of the tube. The function of PML is to simulate the infinite tube and avoid the reflection of acoustic wave. To investigate the influence of flow field on sound field, a coupled calculation method combining the finite element method and computational fluid dynamics is used to solve the linearized Euler equation, named the Galbrun equation. Firstly, the influence of the cross-section of the tube on the acoustic field is considered. Secondly, the effects of flow on the acoustic field is also investigated. Lastly, a comparative analysis of the simulation results reveals the influence of flow and other parameters of the tube on sound propagation. Both the Mach number and the cross-section ratio have an influence on the acoustic resonance, and the resonance frequency decreases with the increase in the cross-section ratio.
Investigating Semantic Differences in User-Generated Content by Cross-Domain Sentiment Analysis Means
Authors: Ploscă Traian-Radu , Curiac Christian-Daniel , Curiac Daniel-Ioan
Published: March 2024

Sentiment analysis of domain-specific short messages (DSSMs) raises challenges due to their peculiar nature, which can often include field-specific terminology, jargon, and abbreviations. In this paper, we investigate the distinctive characteristics of user-generated content across multiple domains, with DSSMs serving as the central point. With cross-domain models on the rise, we examine the capability of the models to accurately interpret hidden meanings embedded in domain-specific terminology. For our investigation, we utilize three different community platform datasets: a Jira dataset for DSSMs as it contains particular vocabulary related to software engineering, a Twitter dataset for domain-independent short messages (DISMs) because it holds everyday speech type of language, and a Reddit dataset as an intermediary case. Through machine learning techniques, we thus explore whether software engineering short messages exhibit notable differences compared to regular messages. For this, we utilized the cross-domain knowledge transfer approach and RoBERTa sentiment analysis technique to prove the existence of efficient models in addressing DSSMs challenges across multiple domains. Our study reveals that DSSMs are semantically different from DISMs due to F1 score differences generated by the models.
Lessons Learnt from the Influencing Factors of Forested Areas’ Vulnerability under Climatic Change and Human Pressure in Arid Areas: A Case Study of the Thiès Region, Senegal
Authors: Faye Bonoua , Du Guoming , Li Quanfeng , Faye Hélène Véronique Marie Thérèse , Diéne Jeanne Colette , Mbaye Edmée , Seck Henri Marcel
Published: March 2024

Understanding the factors influencing the vulnerability of forested areas is crucial for human well-being and effective governance of ecosystem supply and demand. Based on remote sensing data, this study also considered ten natural and human variables as indexes to explore the main influencing factors that may impact the vulnerability of the Thies region’s forested areas. The 2005, 2010, 2015, and 2020 satellite image data were processed using ArcGIS 10.6 and ENVI 5.1 software. The methodology includes using the transfer matrix approach and calculating the geographic landscape index to describe the dominant morphology of forested areas. Furthermore, a mixed linear regression model was built to establish the connection between forested areas and the potential contributing components. Our study revealed that the forested areas led to relative fragmentation, with an average of 88 patches for Aggregation Index (AI), 3.25 for Largest Patch Index (LPI), 2.50 for Patch Density (PD), and 112 for Landscape Shape Index (LSI) between 2005 and 2020. In addition, the transfer matrix indicated that the loss of forestry areas was about −78.8 km2 for agricultural land, −127.8 km2 for bare land, and −65.3 km2 for artificial surfaces. The most critical factors that influenced forested areas were agricultural and manufactural added value, rainfall (p < 0.05), slope, distance to the road, and agricultural sown area (p < 0.001). Overall, this investigation has revealed that the effective management of forested areas in the Thies region requires an understandable assessment. It was observed that both human anthropogenic and natural factors significantly contribute to the decline in forested areas.
Phenolic Profiles and Antitumor Activity against Colorectal Cancer Cells of Seeds from Selected Ribes Taxa
Authors: Lyashenko Svetlana , López-Ruiz Rosalía , García-Cervantes Ana Minerva , Rodríguez-García Ignacio , Yunusova Svetlana , Guil-Guerrero José Luis
Published: March 2024

Seeds from several Ribes taxa were surveyed for phenolic compounds and in vitro antiproliferative activity against HT-29 colorectal cancer cells. Total phenolic compounds were analyzed through the Folin–Ciocalteu procedure, while LC coupled to a single mass spectrometer (MS) Orbitrap using an electrospray interface (ESI) was performed to determine the phenolic profiles. Antitumor effects were established using the MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay. Total phenolics ranged from 11.4 in R. alpinum to 94.8 mg of caffeic acid equivalents (CAE)/g in R. nigrum ‘Koksa’. Concerning phenolic compounds, four were hydroxylated benzoic acids, four cinnamic acid derivatives, eight flavonoids, and nine flavonoid glycosides. The growth inhibition against HT-29 cancer cells was exercised much better by R. nigrum ‘Koksa’ and Ribes ‘Erkeeni’ (GI50 37 and 42 µg/mL). All Ribes extracts, except for R. nigrum ‘Hara katarlik’, showed higher activity than R. rubrum (GI50 at 72 h: 99 µg/mL). Interestingly, the extract from Ribes ‘Erkeeni’, which exhibited high bioactivity, contains all detected phenolic compounds, unlike R. nigrum ‘Koksa’, which lacks only populnin. Therefore, the high bioactivity found for such extracts could be due to a synergy of all detected compounds. This work constitutes a comprehensive action for expanding knowledge on the phenolic profiles and antitumor activity of GLA-rich Ribes seeds.
Machine Learning Prediction Techniques in the Optimization of Diagnostic Laboratories’ Network Operations
Authors: Regulski Krzysztof , Opaliński Andrzej , Swadźba Jakub , Sitkowski Piotr , Wąsowicz Paweł , Kwietniewska-Śmietana Agnieszka
Published: March 2024

The article presents an outline of the concept of a prototype system allowing for the optimization of inventory management in a diagnostic laboratory on the basis of patients results. The effectiveness of laboratory diagnostics depends largely on the appropriate management of resources and the quality of tests. A functional quality management system is an integral element of every diagnostic laboratory, ensuring reliability and appropriate work standards. This system includes maintaining correct and reliable analytical test results as well as the optimal use of the laboratory equipment’s processing capacity and the appropriate organization of the supply chain—both analytical material and reagents. It is extremely important to avoid situations in which tests cannot be performed due to a lack of reagents, the overloading of analyzers, or improper calibration. Therefore, the accurate prediction of the number of orders is crucial to optimize the laboratory’s operations, both in the short term—for the next few hours and minutes—and in the longer term, even monthly, which will allow for the appropriate planning of reagent stock. As part of the research presented in this article, machine learning methods were used to implement the above functionalities, which allowed for the development of a prototype of a laboratory optimization system using patient test results as a basis.
Wiener Filter Using the Conjugate Gradient Method and a Third-Order Tensor Decomposition
Authors: Benesty Jacob , Paleologu Constantin , Stanciu Cristian-Lucian , Costea Ruxandra-Liana , Dogariu Laura-Maria , Ciochină Silviu
Published: March 2024

In linear system identification problems, the Wiener filter represents a popular tool and stands as an important benchmark. Nevertheless, it faces significant challenges when identifying long-length impulse responses. In order to address the related shortcomings, the solution presented in this paper is based on a third-order tensor decomposition technique, while the resulting sets of Wiener–Hopf equations are solved with the conjugate gradient (CG) method. Due to the decomposition-based approach, the number of coefficients (i.e., the parameter space of the filter) is greatly reduced, which results in operating with smaller data structures within the algorithm. As a result, improved robustness and accuracy can be achieved, especially in harsh scenarios (e.g., limited/incomplete sets of data and/or noisy conditions). Besides, the CG-based solution avoids matrix inversion operations, together with the related numerical and complexity issues. The simulation results are obtained in a network echo cancellation scenario and support the performance gain. In this context, the proposed iterative Wiener filter outperforms the conventional benchmark and also some previously developed counterparts that use matrix inversion or second-order tensor decompositions.
Applications of Machine Learning and Computer Vision in Industry 4.0
Authors: Haffner Oto , Kučera Erik , Rosinová Danica
Published: March 2024

Among the most important economic activities of humankind is industry [...]
Multistage Mixed-Attention Unsupervised Keyword Extraction for Summary Generation
Authors: Wu Di , Cheng Peng , Zheng Yuying
Published: March 2024

Summary generation is an important research direction in natural language processing. Aimed at the problems of redundant information processing difficulties and an inability to generate high-quality summaries from long text in existing summary generation models, BART is the backbone model, an N + 1 coarse–fine-grained multistage summary generation framework is constructed, and a multistage mixed-attention unsupervised keyword extraction summary generation model is proposed (multistage mixed-attention unsupervised keyword extraction for summary generation, MSMAUKE-SummN). In the N-coarse-grained summary generation stages, a sentence filtering layer (PureText) is constructed to remove redundant information in long text. A mixed-attention unsupervised approach is used to iteratively extract keywords, assisting summary inference and enriching the global semantic information of coarse-grained summaries. In the 1-fine-grained summary generation stage, a self-attentive keyword selection module (KeywordSelect) is designed to obtain keywords with higher weights and enhance the local semantic representation of fine-grained summaries. Tandem N-coarse-grained and 1-fine-grained summary generation stages are used to obtain long text summaries through a multistage generation approach. The experimental results show that the model improves the ROUGE-1, ROUGE-2, and ROUGE-L metrics by a minimum of 0.75%, 1.48%, and 1.25% over the HMNET, TextRank, HAT-BART, DDAMS, and SummN models on summarized datasets such as AMI, ICSI, and QMSum.
Quantitative Evaluation of the View of the Landscape Using a Visibility Analysis Optimization Algorithm
Authors: Li Zhijie , An Junfan , Zhang Jie , Shi Haoqi , Gao Yuan , Xue Jingyu , Li Changhua , Mohi-ud-din Ghulam
Published: March 2024

Visual evaluation of the landscape is an important way to judge landscape quality. In this study, by optimizing the vertical angle and relative slope parameters of a visibility analysis algorithm, we intuitively and quantitatively display visibility grid data on the landscape based on tourists’ viewpoints and realize the transformation from making calculations only for the visible area to quantitatively evaluating the quality of visually experiencing the landscape considering parallax. We consider a variety of landscape visual influence factors (visible area, landscape water system distribution, number of landscape resources) to construct an index system for evaluating landscape visual effects. Finally, a set of improved landscape visual evaluation methods is proposed by integrating the analytic hierarchy process (AHP) and an optimization algorithm into the visibility analysis. Validation of the case study of the ancient town Fenghuang shows that these methods can effectively distinguish good and bad landscape viewpoints in a scenic area and support planning and design decisions on the related spatial layout and viewing platform. This study provides a new perspective for developing a quantitative, intelligent digital landscape analysis system.
Controlled Nickel Nanoparticles: A Review on How Parameters of Synthesis Can Modulate Their Features and Properties
Authors: e Silva Felipe , Salim Vera , Rodrigues Thenner
Published: March 2024

Nickel nanoparticles have wide-ranging applications in diverse fields, including electronics, catalysis, and biomedicine. The unique properties of these nanoparticles depend on their physical and chemical attributes. Consequently, there is a growing interest in understanding the performance relationships through a nuanced comprehension of their controlled synthesis. This review explores the advancements related to precisely defined nickel nanoparticles, with a specific focus on unraveling the connections between performance and their physical/chemical characteristics. The emphasis is on elucidating how manipulating synthetic parameters, such as precursor concentration, reductant agent properties, temperature, time, and the presence of stabilizing agents, can provide additional avenues for refining the performance in terms of size and morphology. Through the analysis of each variable, we illustrate the methodology for synthesizing well-controlled nickel nanoparticles, showcasing the ability to exert precision over their composition, size, and surface morphology.
Influence of Various Urban Morphological Parameters on Urban Canopy Ventilation: A Parametric Numerical Study
Authors: Zeng Liyue , Zhang Xuelin , Lu Jun , Li Yongcai , Hang Jian , Hua Jiajia , Zhao Bo , Ling Hong
Published: March 2024

Numerical simulation is vital for evaluating urban ventilation. However, accurate urban-scale ventilation modeling requires extensive building surface simulation for computational demand. The distributed drag force approach simplifies the urban canopy by modeling buildings as a porous volume that accounts for momentum and turbulence. This method is a practical solution for simulating urban airflow. The drag force coefficient (Cd) is a crucial aerodynamic parameter in this approach. This study examines how Cd varies with urban design parameters such as plan area density (λp), average building height (H), frontal area density (λf), floor aspect ratio (AR), and sky view factor (SVF). Employing extensive numerical simulations conducted under neutral atmospheric conditions, we explore ranges of λp = 0.04–0.07 and λf = 0.1–1.2. The numerical model has been validated against existing wind tunnel data. The results show that Cd is insensitive to the model scale and background wind speed. We discover a nonlinear relationship between Cd and the parameters λp, λf, and SVF. For urban layouts with cubic-shaped buildings, Cd peaks at different λp within the range of 0.2~0.8. When λp and H are constant, Cd has a linear relationship with AR and λf. It is recommended to use λp, SVF, and AR as predictors for Cd across various urban configurations.
ℤ2 × ℤ2 Equivariant Quantum Neural Networks: Benchmarking against Classical Neural Networks
Authors: Dong Zhongtian , Comajoan Cara Marçal , Dahale Gopal Ramesh , Forestano Roy T. , Gleyzer Sergei , Justice Daniel , Kong Kyoungchul , Magorsch Tom , Matchev Konstantin T. , Matcheva Katia , Unlu Eyup B.
Published: March 2024

This paper presents a comparative analysis of the performance of Equivariant Quantum Neural Networks (EQNNs) and Quantum Neural Networks (QNNs), juxtaposed against their classical counterparts: Equivariant Neural Networks (ENNs) and Deep Neural Networks (DNNs). We evaluate the performance of each network with three two-dimensional toy examples for a binary classification task, focusing on model complexity (measured by the number of parameters) and the size of the training dataset. Our results show that the Z2×Z2 EQNN and the QNN provide superior performance for smaller parameter sets and modest training data samples.
Translational Regular Variability and the Index Function
Authors: Fatić Danica , Djurčić Dragan , Kočinac Ljubiša D. R.
Published: March 2024

This paper deals with translational regular and rapid variations. By using a new method of proving the Galambos–Bojanić-Seneta type theorems, we prove two theorems of this type for translationally regularly varying and translationally rapidly varying functions and sequences, important objects in the asymptotic analysis of divergent processes. Also, we introduce and study the index functions for translationally regularly varying functions and sequences. For example, we prove that the index function of a translationally regularly varying function is also in the same class of functions.
Flavonoids and Flavonoid-Based Nanoparticles for Osteoarthritis and Rheumatoid Arthritis Management
Authors: Wahnou Hicham , Limami Youness , Oudghiri Mounia
Published: March 2024

Arthritis, a global health burden comprising osteoarthritis and rheumatoid arthritis, demands advanced therapeutic approaches. In this context, flavonoids, a diverse group of naturally occurring compounds abundant in fruits, vegetables, and medicinal plants, have emerged as promising candidates for mitigating the inflammatory processes associated with arthritic conditions. This review aims, first, to provide a comprehensive exploration of the potential of flavonoids, focusing on specific compounds such as quercetin, epigallocatechin-3-gallate (EGCG), apigenin, luteolin, fisetin, silibinin, kaempferol, naringenin, and myricetin. The second section of this review delves into the anti-arthritic activities of these flavonoids, drawing insights from clinical trials and scientific studies. Each flavonoid is scrutinized individually to elucidate its mechanisms of action and therapeutic efficacy in the context of both osteoarthritis and rheumatoid arthritis. The third section of this review highlights the challenges associated with harnessing flavonoids for anti-inflammatory purposes. Bioavailability limitations pose a significant hurdle, prompting the exploration of innovative strategies such as the use of nanoparticles as delivery vehicles. In response to these challenges, the fourth section focuses on the emerging field of flavonoid-based nanoparticles. This includes detailed discussions on quercetin, EGCG, fisetin, and naringenin-based nanoparticles, highlighting formulation strategies and preclinical evidence supporting their potential in arthritis management. The targeted delivery to inflammatory sites and the exploration of synergistic combinations with other compounds are also discussed as promising avenues to enhance the therapeutic impact of flavonoids. This review consolidates current knowledge on flavonoids and their nanoformulations as potential therapeutic interventions for osteoarthritis and rheumatoid arthritis. By addressing challenges and presenting future research directions, this review aims to contribute to the advancement of innovative and effective strategies for alleviating the global burden of arthritis.
Gait Recognition and Assistance Parameter Prediction Determination Based on Kinematic Information Measured by Inertial Measurement Units
Authors: Xiang Qian , Wang Jiaxin , Liu Yong , Guo Shijie , Liu Lei
Published: March 2024

The gait recognition of exoskeletons includes motion recognition and gait phase recognition under various road conditions. The recognition of gait phase is a prerequisite for predicting exoskeleton assistance time. The estimation of real-time assistance time is crucial for the safety and accurate control of lower-limb exoskeletons. To solve the problem of predicting exoskeleton assistance time, this paper proposes a gait recognition model based on inertial measurement units that combines the real-time motion state recognition of support vector machines and phase recognition of long short-term memory networks. A recognition validation experiment was conducted on 30 subjects to determine the reliability of the gait recognition model. The results showed that the accuracy of motion state and gait phase were 99.98% and 98.26%, respectively. Based on the proposed SVM-LSTM gait model, exoskeleton assistance time was predicted. A test was conducted on 10 subjects, and the results showed that using assistive therapy based on exercise status and gait stage can significantly improve gait movement and reduce metabolic costs by an average of more than 10%.
Postbiotics of Naturally Fermented Synbiotic Mixture of Rice Water Aids in Promoting Colonocyte Health
Authors: Anbalagan Charumathi , Nandabalan Sangeetha Kadapakkam , Sankar Pavithra , Rajaram Prasanna Srinivasan , Govindaraj Karthick , Rupert Secunda , Sathyanesan Jeswanth
Published: March 2024

The eubiotic state of the gut microbiota is primarily brought about by various probiotic species that colonize the gut. It is becoming very clear that the probiotic-metabolite mixtures in the gut luminal milieu is central in establishing cross-kingdom signalling networks to maintain gut-multi-organ axes health. Culturally, different fermented foods and beverages have been regional staples since ancient times, and are known to be enriched with probiotics. However, regional variations including the environment, the staple food source (prebiotics), and fermentation methods, among other factors, influence the fermenting probiotic species. Fermented rice water (FRW), an economical, easy to make, simple beverage is a rich source of synbiotics. Therefore, consumption of fermented rice water allows for the intake of a variety of region-specific live probiotics. The secondary metabolites (postbiotics) present in such symbiotic mixtures may also contribute toward maintaining normal intestinal cellular functions. In this study, we highlight that regional staples such as rice consumed in their fermented form may hold promise in alleviating gut-related diseases. Our results show that simple overnight fermentation of cooked edible rice enables the growth of probiotic bacterial species belonging to the Lactic Acid Bacteria group (Leuconostoc lactis, Weisella confusa, Weisella cibacria, Lactococcus lactis, lactococcus taiwanensis, Lactobacillus fermentum, Lactobacillus nagelii, and Lactobacillus delbrueckii ssp. indicus). Metabolomic analysis of the overnight fermented and over two-nights fermented rice water identified more than 200 postbiotic metabolites. Our results show that postbiotics contributing to energy metabolism, gut-multiorgan axes, and microbial paraprobiotics are enriched in the overnight (~10 h) fermented rice water as compared to the over two-nights fermented rice water. Functional analysis via gene expression studies for nutrient absorption (mct-1 and mct-2) and barrier integrity (occludin and zo-1) reveals significant upregulation of these genes upon FRW treatment of HT29 colon cells. This study is a first-of-its-kind to demonstrate the proof-of-principle that postbiotics of naturally fermented rice water positively modulates colonocyte health.
The AP2/ERF Transcription Factor PgERF120 Regulates Ginsenoside Biosynthesis in Ginseng
Authors: Jiang Yang , Zhang Qi , Zeng Zixia , Wang Yi , Zhao Mingzhu , Wang Kangyu , Zhang Meiping
Published: March 2024

Ginseng (Panax ginseng C.A. Meyer) is a perennial herb belonging to the family Araliaceae and has been used for thousands of years in East Asia as an essential traditional medicine with a wide range of pharmacological activities of its main active ingredient, ginsenosides. The AP2/ERF gene family, widely present in plants, is a class of transcription factors capable of responding to ethylene regulation that has an influential role in regulating the synthesis of major active ingredients in medicinal plants and in response to biotic and abiotic stresses, which have not been reported in Panax ginseng. In this study, the AP2/ERF gene was localized on the ginseng chromosome, and an AP2/ERF gene duplication event was also discovered in Panax ginseng. The expression of seven ERF genes and three key enzyme genes related to saponin synthesis was measured by fluorescence quantitative PCR using ethylene treatment of ginseng hairy roots, and it was observed that ethylene promoted the expression of genes related to the synthesis of ginsenosides, among which the PgERF120 gene was the most sensitive to ethylene. We analyzed the sequence features and expression patterns of the PgERF120 gene and found that the expression of the PgERF120 gene was specific in time and space. The PgERF120 gene was subsequently cloned, and plant overexpression and RNA interference vectors were constructed. Ginseng adventitious roots were transformed using the Agrobacterium tumefaciens-mediated method to obtain transgenic ginseng hairy roots, and the gene expression, ginsenoside content and malondialdehyde content in overexpression-positive hairy roots were also analyzed. This study preliminarily verified that the PgERF120 gene can be involved in the regulation of ginsenoside synthesis, which provides a theoretical basis for the study of functional genes in ginseng and a genetic resource for the subsequent use of synthetic biology methods to improve the yield of ginsenosides.
Neuroprotective Effects of Krypton Inhalation on Photothrombotic Ischemic Stroke
Authors: Antonova Viktoriya V. , Silachev Denis N. , Plotnikov Egor Y. , Pevzner Irina B. , Yakupova Elmira I. , Pisarev Mikhail V. , Boeva Ekaterina A. , Tsokolaeva Zoya I. , Lyubomudrov Maxim A. , Shumov Igor V. , Grechko Andrey V. , Grebenchikov Oleg A.
Published: March 2024

This is the first in vivo study to investigate the neuroprotective effects of krypton on focal cerebral ischemia. The aim of the study was to analyze the effect of 2 h of inhalation of a krypton–oxygen mixture (Kr 70%/O2 30%) on the recovery of neurological functions and the degree of brain damage in rats after photoinduced ischemic stroke (PIS) and to investigate the possible mechanisms responsible for this neuroprotection. Experiments were performed on male Wistar rats weighing 250–300 g (n = 32). Animals were randomized into four groups. Two groups (n = 20) underwent photoinduced ischemic stroke, followed by 2 h of inhalation of krypton–oxygen mixture consisting of Kr 70%/O2 30% or a nitrogen–oxygen breathing mixture consisting of N2 70%/O2 30%, followed by neurological examinations on days 3 and 7. The other two groups (n = 12) received only gas mixtures of the same concentration and exposure duration as in those in the PIS groups, then Western blot analysis of the potential molecular mechanisms was performed. The results of the study show that treatment with the krypton–oxygen mixture consisting of Kr 70%/O2 30% improves the neurological status on day 7 of observation, reduces the lesion volume according to the MRI examination and the number of Iba-1- and caspase-3-positive cells in the damaged area, promotes the activation of neoangiogenesis (an increase in the von Willebrand factor), and reduces the penumbra area and the number of NeuN-positive cells in it on day 14 of observation. Inhalation of the krypton–oxygen mixture also significantly increases the levels of phosphorylated AKT kinase (protein kinase B) and glycogen synthase kinase 3b (pGSK3b) and promotes the expression of transcription factor Nrf2, which was accompanied by the lowered expression of transcription factor NFkB (p50). Thus, we showed pronounced neuroprotection induced by krypton inhalation after stroke and identified the signaling pathways that may be responsible for restoring neurological functions and reducing damage.
Laboratory Puzzle of Oxidative Stress, Parameters of Hemostasis and Inflammation in Hospitalized Patients with COVID-19
Authors: Djordjevic Jelena , Ignjatovic Vesna , Vukomanovic Vladimir , Vuleta Katarina , Ilic Nevenka , Slovic Zivana , Stanojevic Pirkovic Marijana , Mihaljevic Olgica
Published: March 2024

Bearing in mind that coronavirus disease (COVID-19) is associated with a wide range of laboratory abnormalities, the aim of this study was to examine the importance of determining the parameters of oxidative stress and antioxidant protection as well as markers of inflammation and hemostasis in hospitalized patients with COVID-19. The study population included 105 patients with severe COVID-19 and 65 healthy control subjects. The parameters of oxidative stress and the activity of enzymes of the antioxidant system were determined from the obtained samples using spectrophotometric methods. Standard laboratory methods were performed for the determination of the biochemical and hematological parameters. Patients with COVID-19 showed a significantly higher level of pro-oxidative parameters (hydrogen peroxide (H2O2) and the index of lipid peroxidation in the form of thiobarbituric acid-reactive substances (TBARSs)) and a significantly lower activity of the antioxidant system (catalase (CAT)). Patients with COVID-19 had significantly higher values of inflammation parameters (C-reactive protein (CRP), procalcitonin (PCT), ratio of the number of neutrophils to lymphocytes (NLR), and ratio of the number of platelets to lymphocytes (PLR)) and parameters of hemostasis (activated partial thromboplastin time (aPTT), prothrombin time (PT), D-dimer, fibrinogen) than the control healthy subjects. In addition, changes in hemostatic parameters correlated positively with inflammatory markers in the group of patients with COVID-19. The early determination of hemostasis parameters and the parameters of inflammation can help in the prediction of poor prognosis in COVID-19 patients.
Electroretinographical Analysis of the Effect of BGP-15 in Eyedrops for Compensating Global Ischemia–Reperfusion in the Eyes of Sprague Dawley Rats
Authors: Takács Barbara , Szilágyi Anna , Priksz Dániel , Bombicz Mariann , Szabó Adrienn Mónika , Pelles-Taskó Beáta , Rusznyák Ágnes , Haimhoffer Ádám , Gesztelyi Rudolf , Szilvássy Zoltán , Juhász Béla , Varga Balázs
Published: March 2024

Retinal vascular diseases and consequential metabolic disturbances in the eye are major concerns for healthcare systems all around the world. BGP-15, a drug candidate small-molecule [O-(3-piperidino-2-hydroxy-1-propyl) nicotinic amidoxime dihydrochloride], has been formerly demonstrated by our workgroup to be retinoprotective both in the short and long term. Based on these results, the present study was performed to investigate the efficacy of BGP in an eyedrop formulation containing sulfobutylether-β-cyclodextrin (SBECD), which is a solubility enhancer as well. Electroretinographical evaluations were carried out and BGP was demonstrated to improve both scotopic and photopic retinal a- and b-waves, shorten their implicit times and restore oscillatory potentials after ischemia–reperfusion. It was also observed to counteract retinal thinning after ischemia–reperfusion in the eyes of Sprague Dawley rats. This small-molecule drug candidate is able to compensate for experimental global eye ischemia–reperfusion injury elicited by ligation of blood vessels in rats. We successfully demonstrated that BGP is able to exert its protective effects on the retina even if administered in the form of eyedrops.
MAPT Mutations V337M and N297K Alter Organelle Trafficking in Frontotemporal Dementia Patient-Specific Motor Neurons
Authors: Hartmann Christiane , Anskat Marie , Ehrlich Marc , Sterneckert Jared , Pal Arun , Hermann Andreas
Published: March 2024

Frontotemporal dementia (FTD) is a neurodegenerative disease characterized by the progressive loss of neurons mainly in the frontal and temporal lobes of the brain. Mutations (e.g., V337M, N297K) in the microtubule-associated protein TAU (MAPT) are responsible 5–20% of familial FTD cases and have been associated with defects in organelle trafficking that plays a critical role in the proper function of cells, including transport of essential molecules and degradation of waste products. Due to the critical role of TAU mutations in microtubule stabilization and organelle transportation, it is of great interest to study these molecular mechanisms to develop effective therapeutic strategies. Therefore, herein, we analyzed mitochondrial and lysosomal trafficking in disease-specific spinal motor neurons by using live cell imaging in undirected (uncompartmentalized) and directed (compartmentalized) cell culture systems. While V337M neurons only expressed 3R TAU, the N297K mutant neurons expressed both 3R and 4R TAU. Axonal trafficking was affected differentially in V337M and N297 MAPT mutated neurons. These findings suggest that the MAPT mutations V337M and N297K impaired axon physiology differentially, which highlights the need for mutation- and/or 3R/4R TAU-specific therapeutic approaches.
Flavonoids as CYP3A4 Inhibitors In Vitro
Authors: Kondža Martin , Brizić Ivica , Jokić Stela
Published: March 2024

Flavonoids, a diverse group of polyphenolic compounds found abundantly in fruits, vegetables, and beverages like tea and wine, offer a plethora of health benefits. However, they have a potential interaction with drug metabolism, particularly through the inhibition of the cytochrome P450 3A4 enzyme, the most versatile and abundant enzyme in the liver. CYP3A4 is responsible for metabolizing approximately 50% of clinically prescribed drugs across diverse therapeutic classes, so these interactions have raised concerns about potential adverse effects. This review delves into the scientific evidence surrounding flavonoid-mediated CYP3A4 inhibition, exploring the inhibitory potential of investigated flavonoids and future implications. Kusehnol I, chrysin, leachianone A, and sophoraflavone G showed the largest inhibitory potentials and lowest IC50 values. While the clinical significance of flavonoid-mediated CYP3A4 inhibition in dietary contexts is generally considered low due to moderate intake and complex interactions, it poses a potential concern for individuals consuming high doses of flavonoid supplements or concurrently taking medications metabolized by CYP3A4. This can lead to increased drug exposure, potentially triggering adverse reactions or reduced efficacy.
A Two-Layer Self-Organizing Map with Vector Symbolic Architecture for Spatiotemporal Sequence Learning and Prediction
Authors: Kempitiya Thimal , Alahakoon Damminda , Osipov Evgeny , Kahawala Sachin , De Silva Daswin
Published: March 2024

We propose a new nature- and neuro-science-inspired algorithm for spatiotemporal learning and prediction based on sequential recall and vector symbolic architecture. A key novelty is the learning of spatial and temporal patterns as decoupled concepts where the temporal pattern sequences are constructed using the learned spatial patterns as an alphabet of elements. The decoupling, motivated by cognitive neuroscience research, provides the flexibility for fast and adaptive learning with dynamic changes to data and concept drift and as such is better suited for real-time learning and prediction. The algorithm further addresses several key computational requirements for predicting the next occurrences based on real-life spatiotemporal data, which have been found to be challenging with current state-of-the-art algorithms. Firstly, spatial and temporal patterns are detected using unsupervised learning from unlabeled data streams in changing environments; secondly, vector symbolic architecture (VSA) is used to manage variable-length sequences; and thirdly, hyper dimensional (HD) computing-based associative memory is used to facilitate the continuous prediction of the next occurrences in sequential patterns. The algorithm has been empirically evaluated using two benchmark and three time-series datasets to demonstrate its advantages compared to the state-of-the-art in spatiotemporal unsupervised sequence learning where the proposed ST-SOM algorithm is able to achieve 45% error reduction compared to HTM algorithm.