bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on Course-Changing Performance of a Large Ship with Spoiler Fins
Authors: Zhang Zedong , Hao Shuai , Wang Bin , Bo Xingdao , Zhang Xuning , Yu Yang
Published: November 2024

The poor maneuverability inherent to large ships is a non-negligible problem that restricts the development of the shipping industry, as large ships can only cruise at an excessively conservative speed when they encounter complicated traffic conditions; nevertheless, ship collision accidents still occasionally occur. In the present study, the novel concept of spoiler fins for modern large ships is proposed. In order to assess their effectiveness in enhancing ship maneuverability, a KRISO container ship (KCS) was selected to carry a pair of spoiler fins, after which a simplified simulation approach for saving the calculation resource was designed for ship collision avoidance conditions, and a full-scale numerical model, including the ship hull, fin, and fluid field domain, was established. Transient-state hydrodynamic forces were calculated during collision avoidance maneuvers using the CFD method; the pressure and velocity contours around the ship were demonstrated; and the ship motion trajectories under different initial ship speeds were simulated and predicted through the adoption of overset mesh and 6-DOF dynamic mesh techniques. Eventually, the improved course-changing performance, dependent on the spoiler fins, was validated.
Collaborative Scheduling of Mass Rescue Operations at Sea
Authors: Zhao Mengge , Pan Jiacai , Wang Qiaojie , Li Jun
Published: November 2024

The continued growth of the global cruise market has posed a major challenge to maritime search and rescue, as available rescue resources are limited compared to the scale of passenger ship disasters. To bridge the gap between the number of passengers in distress and the availability of rescue resources, this paper develops a two-stage Mass Rescue Operation (MRO) decision support model (MRO model) to fully utilize the available multiple rescue resources. Based on the combinatorial optimization theory, in the MRO model we consider the rescue capacity of multiple rescue resources and the synergy between them, the accident types and the marine environment conditions to optimize two objectives (rescue time and number of rescue resources dispatched) in two stages. In the first stage, the objective is to minimize the rescue time by Classical Selection Sort Algorithm. In the second stage, the rescue time and the number of rescue resources are simultaneously optimized by Simulated Annealing Arithmetic (SAA) integrated with Genetic Algorithm (GA). Furthermore, considering the actual role of helicopters in MROs, the MRO model is enhanced to schedule helicopters mandatorily or non-mandatorily. Finally, the MRO model was verified by simulating accidents in the Taiwan Strait. The simulation results show that compared with the first stage, the rescue time in the second stage model is saved by up to 16.18% and the number of rescue resources is reduced by up to 45.16%.
Nanotechnology-Enhanced Orthopaedic Surgery
Authors: Pang Alexander Shao-Rong , Liau Zi Qiang Glen , Oh Jacob Yoong-Leong , Srinivasan Dinesh Kumar
Published: November 2024

Nanomaterials hold significant promise for the future of orthopaedic implants due to their ability to mimic the nanoscale components of the bone, such as collagen fibrils and hydroxyapatite. Nanomaterials can regulate cell behaviour while offering mechanical strength and biocompatibility, making them ideal for bone repair and tissue regeneration. This comprehensive review explores the key existing and potential applications of nanotechnology in orthopaedics, including bone tissue engineering, drug delivery systems, systems combatting implant-related infections, and the surface preparation of implants to enhance osseointegration. These innovations are poised to revolutionise orthopaedic care by improving implant durability, reducing infection risks, and promoting bone regeneration to deliver personalised treatment and create better patient outcomes.
A New Genus Neotricholomopsis Gen. Nov and Description of Neotricholomopsis globispora Sp. Nov. (Phyllotopsidaceae, Agaricales) from Northwestern China Based on Phylogeny, Morphology, and Divergence Time
Authors: Fan Longfei , Wang Biyue , Zhong Xue , Zhou Hongmin , Yang Shunyi , Ji Xiaohong
Published: November 2024

While investigating macrofungi diversity in Gansu province, northwestern China, five fresh and fleshy specimens were collected, which are characterized by nearly white to buff hemispherical pileus with waved margins, a disc depressed with coral to brownish red fibrillose scales, adnate to sub-decurrent lamellae with four relatively regular rows of lamellulae, a stipe that is central, hollow, frequently straight to curved; basidiospores that are globose to subglobose, 5.0–6.0 × (3.5−) 4.0–5.0 (−5.5) μm, narrowly clavate cheilocystidia predominantly, pleurocystidia and caulocystidia not observed; and a cutis pileipellis, with hyphae slightly inflated in the KOH. The results of phylogeny analysis indicated that the species forms an independent lineage in Phyllotopsidaceae based on the ITS (ITS5/ITS4) and nLSU (LR0R/LR7) dataset. Molecular clock analyses suggested the common ancestor of Neotricholomopsis emerged later than upper Cretaceous with a mean crown age of 229.36 Mya (95% highest posterior density of 129.63–343.08 Mya). These five specimens were described as an unreported taxon based on the phylogeny analysis combined with morphological examination and ecological and geographical distribution. Detailed descriptions, illustrations, and phylogenetic trees to demonstrate the placement of this species and discussions with its related species are provided.
Advances in Land Consolidation and Land Ecology
Authors: Zhang Xiaobin , Ye Yanmei
Published: November 2024

The health of our planet’s ecosystems is deeply linked to how we manage land resources [...]
The Measurement of Intra-Distributional Mobility: An Investigation of District Long-Term Housing Vacancies
Authors: Gray David
Published: November 2024

It is not unusual for government reports to place spatial inequalities into a league table, highlighting poorly performing jurisdictions in some form of yardstick competition. A case in point is long-term dwelling vacancies. Action on Empty Homes, which works closely with local governments in the UK, provides commentary about poor performance, including recording persistently higher rates in certain regions and mentioning the worst rankings at the local level. How the distribution of vacant dwellings changes is not well explored. How rigid this league is has been a feature of a discussion in the growth literature. A useful dynamic policy measure in this regard is how far the average jurisdiction changes its league position over a given period. A type of convergence proposed here, implied by Sala-i-Martin, features the time for the initial rankings to become discordant with the current order. One could see this sort of measure being used widely, wherever performances are judged relatively as a means of highlighting good practice. Using English data on vacant dwellings, this paper shows that there is a ‘long memory’ in long-term vacancy rates, both at the local and regional levels. The industrial and housing inheritances of districts in the North of England, evident in the league table in 2004, remain influential after 18 years, even with general population growth. Although the use of incentives to bring dwellings back into use is thought to be successful, it is suggested that the role of the buy-to-let investor may have been overlooked. Changes in the treatment of their rewards appear to coincide with a rise in long-term vacancies.
Investigating Ecosystem Service Trade-Offs and Synergies: The Need for Correlations and Driving Factors in the Upper Fen River Basin of Shanxi Province, China
Authors: Ding Zhongyi , Wang Yuxin , Ma Liang , Yang Jintan , Hou Huping , Wang Jing , Xiong Jinting , Zhang Shaoliang
Published: November 2024

This research provides an overview of the trade-offs and synergies among ecosystem services (ESs) within the upper Fen River Basin (uFRB) that are crucial for informed land management and regional ecological protection. We utilized methodologies, including the dynamic equivalent factor method and spatial autocorrelation analysis, to track ES and driving factors from 1990 to 2020. This study revealed a 13.27% increase in overall ES value, with notable growth in forest land and water areas. Initially, synergies were dominant, but trade-offs became evident over time, particularly with food production. This study identified road proximity and the Normalized Difference Vegetation Index (NDVI) as primary drivers of ES values, with their impact evolving annually. The analysis also highlighted the importance of considering the temporal dynamics in ES relationships and the influence of driving factors on these services. We propose incorporating socio-ecological factors and ES bundles into spatial planning. This is crucial as it will allow us to optimize multi-ES objectives, thus balancing trade-offs and enhancing synergies for sustainable land use.
Development and Evaluation of Machine Learning Models for Air-to-Land Temperature Conversion Using the Newly Established Kunlun Mountain Gradient Observation System
Authors: Li Yongkang , He Qing , Liu Yongqiang , Maituerdi Amina , Yan Yang , Tan Jiao
Published: November 2024

Mountainous land types are characterized by a scarcity of observational data, particularly in remote areas such as the Kunlun Mountains, where conventional Automatic Weather Stations (AWSs) typically do not record land surface temperature (LST) data. This study aims to develop and evaluate models for converting air temperature (TA) to LST using newly established meteorological station data from the Kunlun Mountain Gradient Observation System, thereby providing time-continuous LST data for AWSs. We constructed a conceptual model to explore the relationship between 1.5 m TA and LST and instantiated it using three machine learning algorithms: Support Vector Machine (SVR), Convolutional Neural Network (CNN), and CatBoost. The results demonstrated that the CatBoost algorithm outperformed the others under complex terrain and climatic conditions, achieving a coefficient of determination (R2) of 0.997 and the lowest root mean square error (RMSE) of 0.627 °C, indicating superior robustness and accuracy. Consequently, CatBoost was selected as the optimal model. Additionally, this study analyzed the spatiotemporal distribution characteristics of cloud cover in the Kunlun Mountain region using the MOD11A1 product and assessed the uncertainties introduced by the 8-day average compositing method of the MOD11A2 product. The results revealed significant discrepancies between the monthly average LST derived from polar-orbiting satellites and the hourly composite monthly LST measured on-site or under ideal cloud-free conditions. These differences were particularly pronounced in high-altitude regions (4000 m and above), with the greatest differences occurring in winter, reaching up to 10.2 °C. These findings emphasize the importance of hourly LST calculations based on AWSs for accurately assessing the spatiotemporal characteristics of LST in the Kunlun Mountains, thus providing more precise spatiotemporal support for remote sensing applications in high-altitude regions.
To Impose or Not Impose Penalty Conditions Following Professional Misconduct: What Factors Are Cited by Three Professional Disciplinary Tribunals in New Zealand?
Authors: Surgenor Lois , Diesfeld Kate , Rychert Marta , Kelly Olivia , Kersey Kate
Published: November 2024

Profession-related disciplinary tribunals consider a range of factors when determining penalties following findings of professional misconduct. Penalties that impose conditions on practice hold the potential to facilitate practitioners’ rehabilitation back to safe practice. This study explores the use of penalty conditions by three disciplinary tribunals in New Zealand (the Lawyers and Conveyancers Tribunal [LCDT]; the Health Practitioners Disciplinary Tribunal [HPDT]; and the Teachers Disciplinary Tribunal [TDT]). Disciplinary decisions published between 2018 and 2022 (N = 538) were analysed, coding the explicit reasons cited for imposing or not imposing conditions and if rehabilitation was cited as a penalty principle. Conditions were imposed in 58.6% of the cases, though tribunals varied. All of the tribunals commonly referred to the concepts of remorse/insight, or lack of it, as reasons for ordering or not ordering conditions, and they often considered the seriousness of the misconduct. Reasons for not ordering conditions were more varied between tribunals, as was citing rehabilitation as a penalty principle. The findings suggest that tribunals give substantial consideration to the decision of imposing conditions, drawing on both objective (e.g., past misconduct) and subjective (e.g., cognitive and psychological) phenomena. The reasons did align with concepts found in broad sentencing guidelines from some other jurisdictions (e.g., criminal justice response), though future research on defining and measuring these concepts may help understand their predictive and protective utility.
Effect of Variation in Viscosity on Static and Dynamic Characteristics of Rough Porous Journal Bearings with Micropolar Fluid Squeeze Film Lubrication
Authors: Naduvinamani Neminath Bhujappa , Koppa Bhagyashri Kotreppa
Published: November 2024

In the present study, an effort was made to determine the effects of a porous matrix with different viscosities on the dynamic and static behaviors of rough short journal bearings taking into account the action of a squeezing film under varying loads without journal rotation. The micropolar fluid was regarded as a lubricant that contained microstructure additives in both the porous region and the film region. By applying Darcy’s law for micropolar fluids through a porous matrix and stochastic theory related to uneven surfaces, a standardized Reynolds-type equation was extrapolated. Two scenarios with a stable and an alternating applied load were analyzed. The impacts of variations in viscosity, the porous medium, and roughness on a short journal bearing were examined. We inspected the dynamic and static behaviors of the journal bearing. We found that the velocity of the journal center with a micropolar fluid decreased when there was a cyclic load, and the impact of variations in the viscosity and porous matrix diminished the load capacity and pressure in the squeeze film and increased the velocity of the journal center.
Redispersible Acrylic Ester Polymers: Effect of Polymer Property Changes Due to Polymerization Method Modification and Functional Additives on the Performance of Polymer Cement Mortar
Authors: Lee Jeong-Bae
Published: November 2024

This paper presents an experimental study aimed at improving the performance of polymer cement mortar by evaluating the properties of acrylic ester redispersible polymers, synthesized using a change in polymerization method from emulsion monomer to monomer dropwise addition methods, along with the use of a functional additive in the form of a foaming agent. To achieve the research objectives, a polymer with a glass transition temperature of −11 °C was synthesized by fixing the monomer ratio, particle-size distribution, and glass transition temperature, and the physical properties of the polymer cement mortar were assessed. The results showed that polymers synthesized using the modified polymerization method increased elongation at break and possessed a 35% smaller average particle size. The use of the foaming agent also resulted in enhanced tensile strength. The polymer cement mortars made with these respective polymers demonstrated improvements in compressive strength 11~25%, flexural strength 53~77%, bond strength 78~113%, volumetric changes 65~88%, and water absorption 30~70%. These findings suggest that changes in the polymerization method and the incorporation of functional additives influence the average particle size and air entrainment control properties of the polymers, thereby positively impacting the performance of the cement hydrates.
Atmosphere Effects in Laser Powder Bed Fusion: A Review
Authors: Brown Ben , Lough Cody , Wilson Davis , Newkirk Joseph , Liou Frank
Published: November 2024

The use of components fabricated by laser powder bed fusion (LPBF) requires the development of processing parameters that can produce high-quality material. Manipulating the most commonly identified critical build parameters (e.g., laser power, laser scan speed, and layer thickness) on LPBF equipment can generate acceptable parts for established materials and moderately intricate part geometries. The need to fabricate increasingly complex parts from unique materials drives the limited research into LPBF process control using underutilized parameters, such as atmosphere composition and pressure. As presented in this review, manipulating atmosphere composition and pressure in laser beam welding has been shown to expand processing windows and produce higher-quality welds. The similarities between laser beam welding and laser-based AM processes suggest that this atmosphere control research could be effectively adapted for LPBF, an area that has not been widely explored. Tailoring this research for LPBF has significant potential to reveal novel processing regimes. This review presents the current state of the art in atmosphere research for laser beam welding and LPBF, with a focus on studies exploring cover gas composition and pressure, and concludes with an outlook on future LPBF atmosphere control systems.
Classification-Based Parameter Optimization Approach of the Turning Process
Authors: Yang Lei , Jiang Yibo , Yang Yawei , Zeng Guowen , Zhu Zongzhi , Chen Jiaxi
Published: November 2024

The turning process is a widely used machining process, and its productivity has a significant impact on the cost and profit in industrial enterprises. Currently, it is difficult to effectively determine the optimum process parameters under complex conditions. To address this issue, a classification-based parameter optimization approach of the turning process is proposed in this paper, which aims to provide feasible optimization suggestions of process parameters and consists of a classification model and several optimization strategies. Specifically, the classification model is used to separate the whole complex process into different substages to reduce difficulties of the further optimization, and it achieves high accuracy and strong anti-interference in the identification of substages by integrating the advantages of an encoder-decoder framework, attention mechanism, and major voting. Additionally, during the optimization process of each substage, Dynamic Time Warping (DTW) and K-Nearest Neighbor (KNN) are utilized to eliminate the negative impact of cutting tool wear status on optimization results at first. Then, the envelope curve strategy and boxplot method succeed in the adaptive calculation of a parameter threshold and the detection of optimizable items. According to these optimization strategies, the proposed approach performs well in the provision of effective optimization suggestions. Ultimately, the proposed approach is verified by a bearing production line. Experimental results demonstrate that the proposed approach achieves a significant productivity improvement of 23.43% in the studied production line.
RETRACTED: Ossicini, A. On the Nature of Some Euler’s Double Equations Equivalent to Fermat’s Last Theorem. Mathematics 2022, 10, 4471
Authors: Ossicini Andrea
Published: November 2024

The Mathematics Editorial Office retracts the article entitled “On the Nature of Some Euler’s Double Equations Equivalent to Fermat’s Last Theorem [...]
Efficient Quantum Private Comparison with Unitary Operations
Authors: Hou Min , Wu Yue
Published: November 2024

Quantum private comparison (QPC) is a crucial component of quantum multiparty computing (QMPC), allowing parties to compare their private inputs while ensuring that no sensitive information is disclosed. Many existing QPC protocols that utilize Bell states encounter efficiency challenges. In this paper, we present a novel and efficient QPC protocol that capitalizes on the distinct characteristics of Bell states to enable secure comparisons. Our method transforms private inputs into unitary operations on shared Bell states, which are then returned to a third party to obtain the comparison results. This approach enhances efficiency and decreases the reliance on complex quantum resources. A single Bell state can compare two classical bits, achieving a qubit efficiency of 100%. We illustrate the feasibility of the protocol through a simulation on the IBM Quantum Cloud Platform. The security analysis confirms that our protocol is resistant to both eavesdropping and attacks from participants.
Asymptotic and Oscillatory Analysis of Second-Order Differential Equations with Distributed Deviating Arguments
Authors: Alqahtani Zuhur , Qaraad Belgees , Almuneef Areej , Ramos Higinio
Published: November 2024

This paper focuses on studying the oscillatory properties of a distinctive class of second-order advanced differential equations with distributed deviating arguments in a noncanonical case. Utilizing the Riccati method and the comparison method with first-order equations, in addition to other analytical methods, we have established criteria to test whether the solutions of the studied equation exhibit oscillatory behavior. To verify the validity of the results we obtained and determine their applicability, we present some examples to confirm the strength and accuracy of our proposed criteria.
Fixed-Time Event-Triggered Control of Nonholonomic Mobile Robots with Uncertain Dynamics and Preassigned Transient Performance
Authors: Wang Yong , Ji Yunfeng , Li Wei , Fang Xi
Published: November 2024

In this paper, a novel adaptive control scheme is proposed for the path-following problem of a nonholonomic mobile robot with uncertain dynamics based on barrier functions. To optimize communication resources, we integrate an event-triggered mechanism that avoids Zeno behavior and ensures that the tracking error of the closed-loop system converges to a small neighborhood around zero within a fixed time, while consistently satisfying predefined transient performance requirements. Extensive simulation studies demonstrate the effectiveness of the proposed approach and validate the theoretical results.
Nonlinear Analysis of the Multi-Layered Nanoplates
Authors: Sadeghian Mostafa , Palevicius Arvydas , Griskevicius Paulius , Janusas Giedrius
Published: November 2024

This text investigates the bending/buckling behavior of multi-layer asymmetric/symmetric annular and circular graphene plates through the application of the nonlocal strain gradient model. Additionally, the static analysis of multi-sector nanoplates is addressed. By considering the van der Waals interactions among the layers, the higher-order shear deformation theory (HSDT), and the nonlocal strain gradient theory, the equilibrium equations are formulated in terms of generalized displacements and rotations. The mathematical nonlinear equations are solved utilizing either the semi-analytical polynomial method (SAPM) and the differential quadrature method (DQM). Also, the available references are used to validate the results. Investigations are conducted to examine the effect of small-scale factors, the van der Waals interaction value among the layers, boundary conditions, and geometric factors.
Abelian Theorems for the Real Weierstrass Transform over Compactly Supported Distributions
Authors: González Benito J. , Negrín Emilio Ramón , Maan Jeetendrasingh
Published: November 2024

This paper explores Abelian theorems associated with the real Weierstrass transform over distributions of compact support. This study contributes to both mathematical analysis and distribution theory by offering new insights into the interaction between integral transforms and compactly supported distributions.
Advanced Trans-BiGRU-QA Fusion Model for Atmospheric Mercury Prediction
Authors: Shih Dong-Her , Chung Feng-I. , Wu Ting-Wei , Wang Bo-Hao , Shih Ming-Hung
Published: November 2024

With the deepening of the Industrial Revolution and the rapid development of the chemical industry, the large-scale emissions of corrosive dust and gases from numerous factories have become a significant source of air pollution. Mercury in the atmosphere, identified by the United Nations Environment Programme (UNEP) as one of the globally concerning air pollutants, has been proven to pose a threat to the human environment with potential carcinogenic risks. Therefore, accurately predicting atmospheric mercury concentration is of critical importance. This study proposes a novel advanced model—the Trans-BiGRU-QA hybrid—designed to predict the atmospheric mercury concentration accurately. Methodology includes feature engineering techniques to extract relevant features and applies a sliding window technique for time series data preprocessing. Furthermore, the proposed Trans-BiGRU-QA model is compared to other deep learning models, such as GRU, LSTM, RNN, Transformer, BiGRU, and Trans-BiGRU. This study utilizes air quality data from Vietnam to train and test the models, evaluating their performance in predicting atmospheric mercury concentration. The results show that the Trans-BiGRU-QA model performed exceptionally well in terms of Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and R-squared (R2), demonstrating high accuracy and robustness. Compared to other deep learning models, the Trans-BiGRU-QA model exhibited significant advantages, indicating its broad potential for application in environmental pollution prediction.
Dynamic-Max-Value ReLU Functions for Adversarially Robust Machine Learning Models
Authors: Sooksatra Korn , Rivas Pablo
Published: November 2024

The proliferation of deep learning has transformed artificial intelligence, demonstrating prowess in domains such as image recognition, natural language processing, and robotics. Nonetheless, deep learning models are susceptible to adversarial examples, well-crafted inputs that can induce erroneous predictions, particularly in safety-critical contexts. Researchers actively pursue countermeasures such as adversarial training and robust optimization to fortify model resilience. This vulnerability is notably accentuated by the ubiquitous utilization of ReLU functions in deep learning models. A previous study proposed an innovative solution to mitigate this vulnerability, presenting a capped ReLU function tailored to bolster neural network robustness against adversarial examples. However, the approach had a scalability problem. To address this limitation, a series of comprehensive experiments are undertaken across diverse datasets, and we introduce the dynamic-max-value ReLU function to address the scalability problem.
Finite-Time Partial Component Consensus for Nonlinear Leader-Following Multi-Agent Systems
Authors: Yan Zhaolei , Yang Baibin , Luo Manman , Hu Manfeng
Published: November 2024

The problem of finite-time partial component consensus (FTPCC) for first-order nonlinear multi-agent systems (MASs) is investigated in this paper for the first time. By incorporating the permutation matrix approach, we derive a novel error system for identical components, which facilitates stability analysis. Leveraging partial variable stability theory and related foundational knowledge, we devise two adaptable protocols. These protocols are tailored to achieve FTPCC in nonlinear MASs, one for systems without disturbances and another for those with bounded disturbances. To validate our findings, numerical examples are provided, demonstrating the effectiveness of the proposed results.
Chaetomorpha linum Extract as a Source of Antimicrobial Compounds: A Circular Bioeconomy Approach
Authors: Barletta Roberta , Trezza Alfonso , Geminiani Michela , Frusciante Luisa , Olmastroni Tommaso , Sannio Filomena , Docquier Jean-Denis , Santucci Annalisa
Published: November 2024

The circular bioeconomy is currently a promising model for repurposing natural sources; these sources include plants due to their abundance of bioactive compounds. This study evaluated the antimicrobial properties of a Chaetomorpha linum extract. Chaetomorpha linum is an invasive macroalga from the Orbetello Lagoon (Tuscany, Italy), which grows in nutrient-rich environments and has been forming extended mats since 2005. The biomass is mechanically harvested and treated as waste, consuming considerable manpower and financial resources. As a potential way to increase the value of such waste, this study found that C. linum extract (CLE) is a source of antimicrobial compounds. The phytochemical characterization of the extract revealed the predominant presence of palmitic acid, a fatty acid with known antimicrobial activity. Based on such findings, four bacterial species of high clinical relevance (Enterococcus faecalis, Staphylococcus aureus, Pseudomonas aeruginosa, and Escherichia coli) were tested, revealing a notable antibacterial activity of the extract on Enterococcus faecalis (MIC, 32 μg/mL). Computational analyses identified a potential Enterococcus faecalis molecular target for palmitic acid, offering molecular insights on the interaction. This study presents a comprehensive in vitro and in silico approach for drug and target discovery studies by repurposing C. linum as a source of antimicrobial bioactive compounds.
A Target to Combat Antibiotic Resistance: Biochemical and Biophysical Characterization of 3-Dehydroquinate Dehydratase from Methicillin-Resistant Staphylococcus aureus
Authors: Téllez-Valencia Alfredo , Oria-Hernández Jesús , Castillo-Villanueva Adriana , Sierra-Campos Erick , Valdez-Solana Mónica , Cisneros-Martínez Jorge , Avitia-Domínguez Claudia
Published: November 2024

Methicillin-resistant Staphylococcus aureus (MRSA) is associated with the acquisition of nosocomial infections, community-acquired infections, and infections related to livestock animals. In the pursuit of molecular targets in the development process of antibacterial drugs, enzymes within the shikimate pathway, such as 3-dehydroquinate dehydratase (DHQD), are regarded as promising targets. Therefore, through biochemical and biophysical techniques, in the present work, the characterization of DHQD from MRSA (SaDHQD) was performed. The kinetic results showed that the enzyme had a Vmax of 107 μmol/min/mg, a Km of 54 μM, a kcat of 48 s−1, and a catalytic efficiency of 0.9 μM−1 s−1. Within the biochemical parameters, the enzyme presented an optimal temperature of 55 °C and was thermostable at temperatures from 10 to 20 °C, being completely inactivated at 60 °C in 10 min. Furthermore, SaDHQD showed an optimal pH of 8.0 and was inactivated at pH 4.0 and 12.0. Moreover, the activity of the enzyme was affected by the presence of ions, surfactants, and chelating agents. The thermodynamic data showed that the rate of inactivation of the enzyme was a temperature-dependent process. Furthermore, the enthalpy change, entropy change, and Gibbs free energy change of inactivation were positive and practically constant, which suggested that the inactivation of SaDHQD by temperature was driven principally by enthalpic contributions. These results provide, for the first time, valuable information that contributes to the knowledge of this enzyme and will be useful in the search of SaDHQD inhibitors that can serve as leads to design a new drug against MRSA to combat antibiotic resistance.
The Antiviral Effects of Heat-Killed Lactococcus lactis Strain Plasma Against Dengue, Chikungunya, and Zika Viruses in Humans by Upregulating the IFN-α Signaling Pathway
Authors: Low Zhao Xuan , Kanauchi Osamu , Tiong Vunjia , Sahimin Norhidayu , Lani Rafidah , Tsuji Ryohei , AbuBakar Sazaly , Hassandarvish Pouya
Published: November 2024

The growing risk of contracting viral infections due to high-density populations and ecological disruptions, such as climate change and increased population mobility, has highlighted the necessity for effective antiviral treatment and preventive measures against Dengue virus (DENV), Chikungunya virus (CHIKV), and Zika virus (ZIKV). Recently, there has been increasing attention on the use of probiotics as a potential antiviral option to reduce virus infections. The present study aimed to assess the immunomodulatory effects of heat-killed Lactococcus lactis strain plasma (LC-Plasma) on peripheral blood mononuclear cells (PBMCs) and its subsequent antiviral response against DENV, CHIKV, and ZIKV. To evaluate the immunomodulatory effects of LC-Plasma on PBMCs isolated from healthy individuals, PBMCs were cultured at a density of 2 × 105 cells/well and stimulated with 10 µg/mL of LC-Plasma. LC-plasma-stimulated PBMCs demonstrated elevated interferon-alpha (IFN-α) production and cluster of differentiation 86 (CD86) and human leukocyte antigen-DR isotype (HLA-DR) upregulation, potentially linked to plasmacytoid dendritic cell (pDC) activation. The replication of DENV, CHIKV, and ZIKV was dose-dependently inhibited when Huh-7 cells were stimulated with LC-Plasma-stimulated PBMC supernatant (LCP Sup). IFN-stimulated gene (ISG) expression, including IFN-stimulated gene 15 (ISG15), IFN-stimulated exonuclease gene 20 (ISG20), IFN-induced transmembrane protein 1 (IFITM-1), myxovirus resistance protein A (MxA), and radical S-adenosyl methionine domain-containing protein 2 (RSAD2), was significantly upregulated in LCP Sup-stimulated Huh-7 cells. Findings from this study indicate that LC-Plasma has the potential to induce IFN-α production, leading to an enhancement in the expression of ISGs and contributing to a broad-spectrum antiviral response. Thus, LC-Plasma may serve as a rational adjunctive treatment to ameliorate viral diseases, warranting future clinical trials.
Therapeutic Effect of Lactiplantibacillus plantarun HFY11 Isolated from Naturally Fermented Yak Yogurt on Lincomycin Hydrochloride–Induced Diarrhea in Mice
Authors: Tan Fang , Ren Lixuan , Kong Chang-Suk
Published: November 2024

This study aimed to observe the therapeutic effect of Lactiplantibacillus plantarun HFY11 (LP-HFY11) on lincomycin hydrochloride-induced diarrhea in mice. The results showed that LP-HFY11 alleviated weight loss and intestinal and colon tissue lesions caused by diarrhea. The serum assay showed that LP-HFY11 decreased interleukin 17A (IL-17A), IL-6, 5-hydroxytryptamine, and malondialdehyde levels and increased total antioxidant capacity in mice with diarrhea. LP-HFY11 also downregulated the mRNA expression of cystic fibrosis transmembrane conductance regulator (CFTR), epidermal growth factor receptor (EGFR), and transforming growth factor beta 1 (TGFβ1) and upregulated the expression of recombinant sodium/hydrogen exchanger 1 (NHE1) and NHE4 in the colon tissues of mice with diarrhea. In conclusion, the study showed that LP-HFY11 could effectively inhibit diarrhea, and the effect was better than that of the drug Bifidobacterium tetragenous viable bacteria tablets (Bifidobacterium-TVBT).
Investigation of Antibiotic Resistance of E. coli Associated with Farm Animal Feces with Participation of Citizen Scientists
Authors: Timofeeva Anna M. , Galyamova Maria R. , Krivosheev Dmitriy M. , Karabanov Sergey Yu. , Sedykh Sergey E.
Published: November 2024

This paper presents the findings of a large-scale study on antibiotic resistance in bacteria found in farm animal feces across Russia. The study included 6578 samples of farm animal manure from 13 regions in Russia, with the help of citizen scientists. Molecular and microbiological methods were used to analyze 1111 samples of E. coli. The microbiological analysis focused on culturing the microorganisms present in the fecal samples on selective media for E. coli and evaluating the sensitivity of the bacteria to different antibiotics, including ampicillin, tetracycline, chloramphenicol, cefotaxime, and ciprofloxacin. The molecular analysis involved isolating the genomic DNA of the bacteria and conducting PCR assays to detect the vanA, vanB, and mcr-1 antibiotic resistance genes. The results demonstrated significant differences in antibiotic sensitivity of the samples that are morphologically identical to E. coli from different regions. For example, 98.0% and 82.5% of E. coli and other fecal bacterial isolates from the Omsk and Vologda regions lacked antibiotic resistance genes, while 97.7% of samples from the Voronezh region possessed three resistance genes simultaneously. The phenotypic antibiotic sensitivity test also revealed regional differences. For instance, 98.1% of fecal bacterial samples from cattle in the Udmurt Republic were sensitive to all five antibiotics tested, whereas 92.8% of samples from the Voronezh region showed resistance to all five antibiotics. The high level of antibiotic resistance observed may be attributed to their use in farming practices. The distinctive feature of our research is that comprehensive geographical coverage was achieved by using a citizen science platform. Citizen scientists, specifically students from colleges and universities, were responsible for the collection and initial analysis of samples. The project attracted 3096 student participants, enabling the collection and analysis of a significant number of samples from various locations in Russia.
Biofilm Inhibition Activity of Fennel Honey, Fennel Essential Oil and Their Combination
Authors: Nagy-Radványi Lilla , Ormai Edit , Koloh Regina , Ángyán Virág Diána , Kocsis Béla , Bencsik-Kerekes Erika , Szabó Péter , Csikós Eszter , Farkas Ágnes , Horváth Györgyi , Kocsis Marianna , Balázs Viktória Lilla
Published: November 2024

The eradication of bacterial biofilms remains a persistent challenge in medicine, particularly because an increasing number of biofilms exhibit resistance to conventional antibiotics. This underscores the importance of searching for novel compounds that present antibacterial and biofilm inhibition activity. Various types of honey and essential oil were proven to be effective against a number of biofilm-forming bacterial strains. The current study demonstrated the effectiveness of the relatively unexplored fennel honey (FH), fennel essential oil (FEO), and their combination against biofilm-forming bacterial strains Pseudomonas aeruginosa, methicillin-resistant Staphylococcus aureus, and Escherichia coli, with a series of in vitro experiments. The authenticity of FH and FEO was checked with light microscopy and gas chromatography-mass spectrometry, respectively. Minimum inhibitory concentrations were determined using the microdilution method, and antibiofilm activity was assessed with crystal violet assay. Structural changes in bacterial cells and biofilms, induced by the treatments, were monitored with scanning electron microscopy. FEO and FH inhibited the biofilm formation of each bacterial strain, with FEO being more effective compared to FH. Their combination was the most effective, with inhibitory rates ranging between 87 and 92%, depending on the bacterial strain. The most sensitive bacterium was E. coli, while P. aeruginosa was the most resistant. These results provide justification for the combined use of honey and essential oil to suppress bacterial biofilms and can serve as a starting point to develop an effective surface disinfectant with natural ingredients.
In Vitro and In Vivo Antitumor Activity of Lophocereus marginatus (DC.) S. Arias & Terrazas Endophytic Aspergillus versicolor and Metarhizium anisopliae Extracts Against the Murine Lymphoma L5178Y-R
Authors: Clark-Pérez Diana Laura , Romo-Sáenz César Iván , Ramírez-Villalobos Jesica María , Tamez-Guerra Patricia , Caballero-Hernández Diana , Delgado-Miranda Ana Laura , García Andrés , Elizondo-Luevano Joel Horacio , Rodríguez-Padilla Cristina , Gomez-Flores Ricardo
Published: November 2024

Cancer belongs to a group of diseases characterized by uncontrolled cell growth. The search for new effective treatments for cancer has led to the discovery of different molecules from plants, bacteria, and fungi with pharmacological use. Plant endophytic fungi are large producers of metabolites with antitumor properties. We aimed to evaluate the in vitro and in vivo antitumor potential of extracts from Lophocereus marginatus endophytic fungi. We obtained ethyl acetate and hexane extracts from the L. marginatus endophytes Metarhizium anisopliae and Aspergillus versicolor and evaluated their antitumor activity against murine L5178Y-R lymphoma cells and human peripheral blood mononuclear cells, using the 3-(4,5-dimethylthiazol-2-yl)-2-diphenyltetrazolium bromide reduction colorimetric technique. M. anisopliae and A. versicolor ethyl acetate extracts showed IC50 values of 9.168 ± 1.21 μg/mL and 13.51 ± 1.62, respectively, and selectivity indices > 30. We also observed that the maximum tolerated dose (100 mg/kg) of ethyl acetate extracts and the vehicle in BALB/c mice did not cause hepatotoxicity. In addition, we evaluated the effects of ethyl acetate extracts on survival and tumor volume in the L5178Y-R lymphoma tumor model. An increase in survival (17 d) was observed in mice treated with A. versicolor extract. Furthermore, it did not increase tumor volume during 10 d, as compared with the control groups without treatment, vehicle, and M. anisopliae extract, which had a maximum survival of 10 d. A. versicolor ethyl acetate extract showed in vitro and in vivo antitumor activity against lymphoma L5178Y-R, increasing mice survival.
A Ratiometric Fluorescence Probe for Visualized Detection of Heavy Metal Cadmium and Application in Water Samples and Living Cells
Authors: Xu Qijiang , Qin Wen , Qin Yanfei , Hu Guiying , Xing Zhiyong , Liu Yatong
Published: November 2024

Heavy metal cadmium (II) residuals have inflicted severe damage to human health and ecosystems. It has become imperative to devise straightforward and highly selective sensing methods for the detection of Cd2+. In this work, a ratiometric benzothiazole-based fluorescence probe (BQFA) was effortlessly synthesized and characterized using standard optical techniques for the visual detection of Cd2+ with a change in color from blue to green, exhibiting a significant Stokes shift. Moreover, the binding ratio of BQFA to Cd2+ was established as 1:1 by the Job’s plot and was further confirmed by FT-IR and 1HNMR titrations. The ratiometric fluorescence response via the ICT mechanism was confirmed by DFT calculations. Furthermore, the limit of detection for detecting Cd2+ was determined to be 68 nM. Furthermore, it is noteworthy that BQFA showed good performance in real water samples, paper strips, smartphone colorimetric identification, and cell imaging.
Enhancing Cannabinoid Bioavailability in Pain Management: The Role of Cyclodextrins
Authors: Ribeiro Adriana , Loureiro Rui , Cabral-Marques Helena
Published: November 2024

Chronic pain (CP), including pain related to cancer, affects approximately 2 billion people worldwide, significantly diminishing quality of life and imposing socio-economic burdens. Current treatments often provide limited relief and may cause adverse effects, demanding more effective alternatives. Natural compounds from Cannabis sativa L., particularly cannabinoids like THC and CBD, exhibit analgesic and anti-inflammatory properties, but their therapeutic use is restricted by poor solubility and low bioavailability. Cyclodextrins (CDs) and cyclic oligosaccharides may encapsulate hydrophobic drugs in order to enhance their solubility and stability, offering a promising solution to these challenges. This study explores the formation of CD inclusion complexes with cannabinoids and specific terpenes, such as D-limonene (LIM), beta-caryophyllene (BCP), and gamma-terpinene (γ-TPN), aiming to improve pharmacokinetic profiles and therapeutic efficacy. We discuss analytical techniques for characterizing these complexes and their mechanisms of action, highlighting the potential of CDs to optimize drug formulations. The integration of CDs in cannabinoid therapies may enhance patient compliance and treatment outcomes in CP management. Future research should focus on innovative formulations and delivery systems to maximize the clinical applications of those compounds.
Shape-Controlled Growth and In Situ Characterization of CdS Nanocrystals via Liquid Cell Transmission Electron Microscopy
Authors: Wei Wei , Sun Xinyu , Sun Jun , Hao Cen
Published: November 2024

Controlling the growth, structure, and shape of CdS nanocrystals is crucial for harnessing their unique physicochemical properties across diverse applications. This control can be achieved by introducing chemical additives into the synthesis reaction mixture. However, precise manipulation of nanocrystal synthesis necessitates a thorough understanding of the formation mechanisms under various chemical conditions, a task that remains challenging. In this study, we employed in situ liquid cell transmission electron microscopy (TEM) to investigate the growth mechanisms of CdS nanocrystals in a reaction solution of cadmium chloride and thiourea, with sodium citrate serving as a structure-directing agent. We observed that CdS nanocrystals evolve through two distinct growth modes: (1) in the absence of sodium citrate, spherical nanocrystals isotropically transform into CdS nanocubes, and (2) in the presence of sodium citrate, cuboid nanocrystals preferentially extend along the {011} direction and anisotropically into CdS triangular nanoplates. Theoretical analysis has confirmed that the adsorption energy of sodium citrate on different crystal facets significantly influences the morphology of the CdS nanocrystals. Our findings not only provide a method for synthesizing CdS nanocrystals based on electron beam induction but also elucidate the intricate nanoscale growth mechanisms, offering insights that could inform the future rational design of nanocrystals with tailored morphologies.
Multifunctional Dy3+ Complexes with Triphenylmethanolates: Structural Diversity, Luminescence, and Magnetic Relaxation
Authors: Félix Gautier , Tolpygin Aleksei O. , Larquey Aurore , Gogolev Ilia A. , Nelyubina Yulia V. , Guari Yannick , Larionova Joulia , Trifonov Alexander A.
Published: November 2024

The coordination environment of magneto-luminescent Dy3+-based Single-Molecule Magnets (SMM) is a crucial factor influencing both magnetic and luminescent properties. In this work, we explore how triphenylmethanolate (Ph3CO−), in combination with other ligands, can modulate the structure and, therefore, the magnetic properties of Dy3+-based SMM. Using triphenylmethanolate in combination with THF and pyridine (Py) as co-ligands, we synthesized a series of mononuclear cis-[Dy(OCPh3)2(THF)4][BPh4]·(2,6-Me2C5H3N) (1), trans-Dy(OCPh3)3(THF)2 (2), fac-Dy(OCPh3)3(py)3 (3) and dinuclear [(Ph3CO)Dy(THF){(μ2–Cl)2Li(THF)2}μ2–Cl]2 (4) complexes where the Dy3+ ion presents five- or six-coordinate geometries. Dinuclear compound 4 exhibits a genuine SMM behavior with a relatively high energy barrier of 421 cm−1, while mononuclear complexes 1–3 are field-induced SMM. These complexes also present Dy3+-characteristic luminescence, highlighting their multifunctional character.