bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Beryllium Addition on Microstructure, Mechanical and Corrosion Performance of Al-Mg-Li Alloys
Authors: Huang Yang , Li Weiwei , Wu Mingdong , Xiao Daihong , Huang Lanping , Liu Wensheng
Published: September 2023

The Al-Mg-Li alloy is ideal for ultra-lightweight aircraft components, and its further performance improvement is of great interest in the aerospace industry. In this study, the effects of various beryllium (Be) additions (Be-free, 0.1, 0.25, 0.50 wt.%) on the microstructure, mechanical, and corrosion performance of the Al-Mg-Li alloys were systematically investigated. The optimal tensile property was obtained in the alloy which added 0.1 wt.% Be with an ultimate tensile strength (UTS), yield strength (YS), and elongation (El) of 530 MPa, 370 MPa, and 9.2%, respectively. Trace Be addition promotes the grain refinement of the as-cast alloy ingot and contributes positive effects to the recrystallization, bringing improvement of the tensile property. Meanwhile, the best anti-corrosion behavior is also presented at 0.1 wt.% Be is added, due to its potential to reduce the width of precipitates free zone (PFZ). As the Be content increases to an excessive level, the comprehensive performance decreases. Therefore, it is strongly recommended that adding trace Be elements into Al-Mg-Li alloys has a positive effect on the comprehensive service performance.
Measuring Thermal Diffusivity of Azoheteroarene Thin Layers by Photothermal Beam Deflection and Photothermal Lens Methods
Authors: Mikaeeli Ameneh , Korte Dorota , Cabrera Humberto , Chomicki Dariusz , Dziczek Dariusz , Kharchenko Oksana , Song Peng , Liu Junyan , Wieck Andreas D. , Pawlak Michal
Published: September 2023

Measurement of thermal properties of thin films is challenging. In particular, thermal characterization is very difficult in semi-transparent samples. Here, we use two photothermal methods to obtain information about the thermal diffusivity as well as thermal conductivity of azoheteroarene functionalized polymer thin layers. The photothermal beam deflection (PBD) method is employed to gather data directly on thermal conductivity and thermal diffusivity, while the thermal lens (TL) method is employed to measure the effective thermal diffusivity. Consequently, the thermal diffusivity of the layers is indirectly estimated from the effective thermal diffusivity using a well-established theoretical relationship. Despite the utilization of distinct methods, our study reveals a remarkable consistency in the highly accurate results obtained from both approaches. This remarkable agreement reaffirms the reliability and mutual compatibility of the employed methods, highlighting their shared ability to provide accurate and congruent outcomes.
The Influence of Polyvinyl Alcohol Porogen Addition on the Nanostructural Characteristics of Hydroxyapatite
Authors: Novella Indrika , Rupaedah Bedah , Eddy Diana Rakhmawaty , Suryana  , Irwansyah Ferli Septi , Noviyanti Atiek Rostika
Published: September 2023

Hydroxyapatite (HA) is a porous material widely developed in various research fields because of its high biodegradability, biocompatibility, and low toxicity. In this research, HA was synthesized using a hydrothermal method with chicken eggshells as a calcium source and various concentrations of polyvinyl alcohol as a porogen (2.5%, 5.0%, and 7.5% by wt). The structure and morphology of HA were determined by X-ray diffraction (XRD) and scanning electron microscope (SEM), respectively. HA was obtained with varying concentrations of polyvinyl alcohol (PVA) porogen according to Inorganic Crystal Structure Database (ICSD) standard. Based on analysis using a refinement method, changes in unit cell parameters (cell volume and lattice strain) of HA synthesized using PVA porogen compared to the standard, the chi square (χ2) and index of R values were relatively low, validating the acceptable of the data. In addition, HA [Ca10(PO4)6(OH)2] with hexagonal structure and the P63/m space group was successfully obtained. Morphological analysis of HA by SEM found that HA has a spherical shape, and the porosity of HA increases with increasing concentrations of polyvinyl alcohol. The highest porosity was obtained with an addition of 5.0 wt% of PVA porogen (HAP3), reaching 69.53%.
Diffusion of Alloying Cobalt Oxide (II, III) into Electrical Steel
Authors: Elgamli Elmazeg , Anayi Fatih
Published: September 2023

This paper aims to reduce power loss in electrical steel by improving its surface resistivity. The proposed approach involves introducing additional alloying elements through diffusion once the steel sheet reaches the desired thickness. Various effective techniques have been suggested and tested to enhance the resistivity of the strip. The method entails creating a paste by combining powdered diffusing elements with specific solutions, which are then applied to the steel’s surface. After firing the sample, a successful transfer of certain elements to the steel surface is achieved. The amount and distribution of these elements can be controlled by adjusting the paste composition, modifying the firing parameters, and employing subsequent annealing procedures. This study specifically investigates the effectiveness of incorporating cobalt oxide (II, III) into non-oriented silicon iron to mitigate power loss. The experimental samples consist of non-oriented electrical steels with a composition of 2.4 wt% Si-Fe and dimensions of 0.305 mm × 300 mm × 30 mm. Power loss and permeability measurements are conducted using a single strip tester (SST) within a magnetic field range of 0.5 T to 1.7 T. These measurements are performed using an AC magnetic properties measurement system under controlled sinusoidal conditions at various frequencies. The research explores the impact of cobalt oxide (II, III) addition, observing successful diffusion into the steel through the utilization of a paste based on sodium silicate solution. This treatment results in a significant reduction in power loss in the non-oriented material, with power loss reductions of 14% at 400 Hz and 23% at 1 kHz attributed to the elimination of a porous layer containing a high concentration of the diffusing element. The formation of porosity in the cobalt addition was found to be particularly sensitive to firing temperature near the melting point. The diffusion process was examined through scanning electron microscopy (SEM) in combination with energy-dispersive X-ray spectroscopy (EDS). The results demonstrate improved power losses in the coated samples compared with the uncoated ones. In conclusion, this study establishes that the properties of non-oriented electrical steels can be enhanced through a safer process compared with the methods employed by previous researchers.
Thermal Conductivity and Microstructure of Novel Flaxseed-Gum-Filled Epoxy Resin Biocomposite: Analytical Models and X-ray Computed Tomography
Authors: Zaidi Mohammed , Baillis Dominique , Naouar Naim , Depriester Michael , Delattre François
Published: September 2023

The growing awareness of the environment and sustainable development has prompted the search for solutions involving the development of bio-based composite materials for insulating applications, offering an alternative to traditional synthetic materials such as glass- and carbon-reinforced composites. In this study, we investigate the thermal and microstructural properties of new biocomposite insulating materials derived from flaxseed-gum-filled epoxy, with and without the inclusion of reinforced flax fibers. A theoretical approach is proposed to estimate the thermal conductivity, while the composite’s microstructure is characterized using X-ray Computed Tomography and image analysis. The local thermal conductivity of the flax fibers and the flaxseed gum matrix is identified by using effective thermal conductivity measurements and analytical models. This study provides valuable insight into the thermal behavior of these biocomposites with varying compositions of flaxseed gum and epoxy resin. The results obtained could not only contribute to a better understanding the thermal properties of these materials but are also of significant interest for advanced numerical modeling applications.
Alternative to Conventional Solutions in the Development of Membranes and Hydrogen Evolution Electrocatalysts for Application in Proton Exchange Membrane Water Electrolysis: A Review
Authors: Perović Klara , Morović Silvia , Jukić Ante , Košutić Krešimir
Published: September 2023

Proton exchange membrane water electrolysis (PEMWE) represents promising technology for the generation of high-purity hydrogen using electricity generated from renewable energy sources (solar and wind). Currently, benchmark catalysts for hydrogen evolution reactions in PEMWE are highly dispersed carbon-supported Pt-based materials. In order for this technology to be used on a large scale and be market competitive, it is highly desirable to better understand its performance and reduce the production costs associated with the use of expensive noble metal cathodes. The development of non-noble metal cathodes poses a major challenge for scientists, as their electrocatalytic activity still does not exceed the performance of the benchmark carbon-supported Pt. Therefore, many published works deal with the use of platinum group materials, but in reduced quantities (below 0.5 mg cm−2). These Pd-, Ru-, and Rh-based electrodes are highly efficient in hydrogen production and have the potential for large-scale application. Nevertheless, great progress is needed in the field of water electrolysis to improve the activity and stability of the developed catalysts, especially in the context of industrial applications. Therefore, the aim of this review is to present all the process features related to the hydrogen evolution mechanism in water electrolysis, with a focus on PEMWE, and to provide an outlook on recently developed novel electrocatalysts that could be used as cathode materials in PEMWE in the future. Non-noble metal options consisting of transition metal sulfides, phosphides, and carbides, as well as alternatives with reduced noble metals content, will be presented in detail. In addition, the paper provides a brief overview of the application of PEMWE systems at the European level and related initiatives that promote green hydrogen production.
An Adaptive Shift Schedule Design Method for Multi-Gear AMT Electric Vehicles Based on Dynamic Programming and Fuzzy Logical Control
Authors: Liu Xiaodong , Du Juan , Cheng Xingqun , Zhu Yan , Ma Jian
Published: September 2023

This paper proposes an adaptive shift schedule design framework based on dynamic programming (DP) algorithm and fuzzy logical control to promote the shift schedule’s adaptability whilst improving the comprehensive performance of the multi-gear automated manual transmission (AMT) electric vehicles in real-time application. First, the DP algorithm is employed to extract an offline optimal gear-shift schedule based on a set of driving conditions, including 11 groups of typical driving cycles. Second, a fuzzy logical controller is formulated considering the variation in the vehicle load and acceleration, where a velocity increment is exported online to adjust the gear-shift velocity of the predesigned DP-based schedule to develop a Fuzzy-DP shift schedule. In addition, multi-objective particle swarm optimization (MOPSO) is utilized to construct a comprehensive shift schedule by simultaneously considering the dynamic and economic performance of the vehicle. Then, the dynamic and economic shift schedules are deployed as the benchmark to examine the performance of the proposed shift schedule. Finally, the effectiveness of the Fuzzy-DP shift schedule is evaluated by comparison with others under various combined driving cycles (including vehicle load and velocity). The comparisons demonstrate the remarkable promotion in the adaptability of the Fuzzy-DP shift schedule in terms of acceleration time, energy-saving potential, and shift frequency. The most significant improvements in the dynamic, economic, and shift frequency can reach 8.86%, 10.12%, and 8.56%, respectively, in contrast to the MOPSO-based shift schedule.
Using Noisy Evaluation to Accelerate Parameter Optimization of Medical Image Segmentation Ensembles
Authors: Tóth János , Tomán Henrietta , Hajdu Gabriella , Hajdu András
Published: September 2023

An important concern with regard to the ensembles of algorithms is that using the individually optimal parameter settings of the members does not necessarily maximize the performance of the ensemble itself. In this paper, we propose a novel evaluation method for simulated annealing that combines dataset sampling and image downscaling to accelerate the parameter optimization of medical image segmentation ensembles. The scaling levels and sample sizes required to maintain the convergence of the search are theoretically determined by adapting previous results for simulated annealing with imprecise energy measurements. To demonstrate the efficiency of the proposed method, we optimize the parameters of an ensemble for lung segmentation in CT scans. Our experimental results show that the proposed method can maintain the solution quality of the base method with significantly lower runtime. In our problem, optimization with simulated annealing yielded an F1 score of 0.9397 and an associated MCC of 0.7757. Our proposed method maintained the solution quality with an F1 score of 0.9395 and MCC of 0.7755 while exhibiting a 42.01% reduction in runtime. It was also shown that the proposed method is more efficient than simulated annealing with only sampling-based evaluation when the dataset size is below a problem-specific threshold.
Fuzzy CNN Autoencoder for Unsupervised Anomaly Detection in Log Data
Authors: Gorokhov Oleg , Petrovskiy Mikhail , Mashechkin Igor , Kazachuk Maria
Published: September 2023

Currently, the task of maintaining cybersecurity and reliability in various computer systems is relevant. This problem can be solved by detecting anomalies in the log data, which are represented as a stream of textual descriptions of events taking place. For these purposes, reduction to a One-class classification problem is used. Standard One-class classification methods do not achieve good results. Deep learning approaches are more effective. However, they are not robust to outliers and require a lot of computational effort. In this paper, we propose a new robust approach based on a convolutional autoencoder using fuzzy clustering. The proposed approach uses a parallel convolution operation to feature extraction, which makes it more efficient than the currently popular Transformer architecture. In the course of the experiments, the proposed approach showed the best results for both the cybersecurity and the reliability problems compared to existing approaches. It was also shown that the proposed approach is robust to outliers in the training set.
Regularized Normalization Methods for Solving Linear and Nonlinear Eigenvalue Problems
Authors: Liu Chein-Shan , Kuo Chung-Lun , Chang Chih-Wen
Published: September 2023

To solve linear and nonlinear eigenvalue problems, we develop a simple method by directly solving a nonhomogeneous system obtained by supplementing a normalization condition on the eigen-equation for the uniqueness of the eigenvector. The novelty of the present paper is that we transform the original homogeneous eigen-equation to a nonhomogeneous eigen-equation by a normalization technique and the introduction of a simple merit function, the minimum of which leads to a precise eigenvalue. For complex eigenvalue problems, two normalization equations are derived utilizing two different normalization conditions. The golden section search algorithms are employed to minimize the merit functions to locate real and complex eigenvalues, and simultaneously, we can obtain precise eigenvectors to satisfy the eigen-equation. Two regularized normalization methods can accelerate the convergence speed for two extensions of the simple method, and a derivative-free fixed-point Newton iterative scheme is developed to compute real eigenvalues, the convergence speed of which is ten times faster than the golden section search algorithm. Newton methods are developed for solving two systems of nonlinear regularized equations, and the efficiency and accuracy are significantly improved. Over ten examples demonstrate the high performance of the proposed methods. Among them, the two regularization methods are better than the simple method.
Application of Wavelet Transform to Urysohn-Type Equations
Authors: Lukianenko V. , Kozlova M. , Belozub V.
Published: September 2023

This paper deals with convolution-type Urysohn equations of the first kind. Finding a solution for such equations is an ill-posed problem. For it to be solved, regularization algorithms and the continuous wavelet transform are used. Similar to the Fourier transform, the continuous wavelet transform is applied to convolution-type equations (based on the Fourier and wavelet transforms) and to Urysohn equations with unknown shift. The wavelet transform is preferable for the cases with approximated right-hand sides and for type 1 equations. We demonstrated that the application of the wavelet transform to Urysohn-type equations with unknown shift translates into a solution of a nonlinear equation with an oscillating kernel. Depending on the availability of a priori information, a combination of regularization and iterative algorithms with the use of close equations are effective for solving convolution-type equations based on the continuous wavelet transform and Urysohn equation.
Robustness of the cμ-Rule for an Unreliable Single-Server Two-Class Queueing System with Constant Retrial Rates
Authors: Efrosinin Dmitry , Stepanova Natalia , Sztrik Janos
Published: September 2023

We study the robustness of the cμ-rule for the optimal allocation of a resource consisting of one unreliable server to parallel queues with two different classes of customers. The customers in queues can be served with respect to a FIFO retrial discipline, when the customers at the heads of queues repeatedly try to occupy the server at a random time. It is proved that for scheduling problems in the system without arrivals, the cμ-rule minimizes the total average cost. For the system with arrivals, it is difficult directly to prove the optimality of the same policy with explicit relations. We derived for an infinite-buffer model a static control policy that also prescribes the service for certain values of system parameters exclusively for the class-i customers if both of the queues are not empty, with the aim to minimize the average cost per unit of time. It is also shown that in a finite buffer case, the cμ-rule fails.
An Ensemble of Long Short-Term Memory Networks with an Attention Mechanism for Upper Limb Electromyography Signal Classification
Authors: Alotaibi Naif D. , Jahanshahi Hadi , Yao Qijia , Mou Jun , Bekiros Stelios
Published: September 2023

Advancing cutting-edge techniques to accurately classify electromyography (EMG) signals are of paramount importance given their extensive implications and uses. While recent studies in the literature present promising findings, a significant potential still exists for substantial enhancement. Motivated by this need, our current paper introduces a novel ensemble neural network approach for time series classification, specifically focusing on the classification of upper limb EMG signals. Our proposed technique integrates long short-term memory networks (LSTM) and attention mechanisms, leveraging their capabilities to achieve accurate classification. We provide a thorough explanation of the architecture and methodology, considering the unique characteristics and challenges posed by EMG signals. Furthermore, we outline the preprocessing steps employed to transform raw EMG signals into a suitable format for classification. To evaluate the effectiveness of our proposed technique, we compare its performance with a baseline LSTM classifier. The obtained numerical results demonstrate the superiority of our method. Remarkably, the method we propose attains an average accuracy of 91.5%, with all motion classifications surpassing the 90% threshold.
Rapid Prediction of Hot-Air Temperature of Kalugin Top Combustion Hot Blast Stove by Means of Computational Fluid Dynamics Numerical Simulation
Authors: Zhao Ming , Pan Yuhua , Meng Fanxu , Ma Ping
Published: September 2023

Based on the three-dimensional (3D) steady-state CFD numerical simulations conducted previously on an industrial Kalugin top combustion hot blast stove, a two-dimensional (2D) transient CFD numerical model for a single channel (hole) of a column of checker bricks in the regenerator of the same hot stove was established in the present work. The average mass flowrate and temperature of the flue gas flowing into the checker brick holes during the combustion period predicted by the 3D model were used as the inlet boundary conditions of the 2D model. Inside the hole of the checker bricks, processes of fluid flow and heat transfer of the flue gas during the combustion period and those of cold air during the hot-air-supply period were simulated using the 2D model for multiple operation cycles (combustion and hot-air-supply periods) of the hot stove, enabling rapid predictions of hot-air temperature under different operating conditions. The simulation results show that when the fuel gas flowrate and air consumption coefficient during the combustion period are controlled within the range of 80,000–100,000 Nm3/h and 1.02–1.28, respectively, a hot-air temperature in the range from 1273 °C to 1295 °C can be obtained during the hot-air-supply period. Applying this optimized operating condition to the industrial hot stove investigated in this study can achieve significant effects of reducing fuel gas flowrate by 8.6% and increasing hot-air temperature by 32 °C. In addition, a regression analysis on the numerical simulation results and the data measured from the industrial hot stove yields a roughly linear relationship between the dome temperature during the combustion period and the hot-air temperature during the hot-air-supply period, that is, the hot-air temperature would be increased by about 16 °C for every increment of 10 °C in the dome temperature, for instance. Therefore, the influences of the operating parameters on heat transfer characteristics in the regenerator and on hot-air temperature obtained in the present work provide a useful reference for guiding the hot stove operation optimization to achieve significant energy saving and emission reduction through facilitating more efficient combustion to minimize fuel gas consumption in steel plants.
Dietary Effects on Gut Microbial Metabolism and Intestinal Inflammation in Mammals
Authors: Gao Bei , Liu Haoyu
Published: September 2023

Growing evidence has proven that the gut microbiota has a tremendous impact on mammalian health [...]
Design and Mixing Analysis of a Passive Micromixer Based on Curly Baffles
Authors: Juraeva Makhsuda , Kang Dong-Jin
Published: September 2023

A novel passive micromixer based on curly baffles is proposed and optimized through the signal-to-noise analysis of various design parameters. The mixing performance of the proposed design was evaluated across a wide Reynolds number range, from 0.1 to 80. Through the analysis, the most influential parameter was identified, and its value was found to be constant regardless of the mixing mechanism. The optimized design, refined using the signal-to-noise analysis, demonstrated a significant enhancement of mixing performance, particularly in the low Reynolds number range (Re< 10). The design set obtained at the diffusion dominance range shows the highest degree of mixing (DOM) in the low Reynolds number range of Re< 10, while the design set optimized for the convection dominance range exhibited the least pressure drop across the entire Reynolds number spectrum (Re< 80). The present design approach proved to be a practical tool for identifying the most influential design parameter and achieving excellent mixing and pressure drop characteristics. The enhancement is mainly due to the curvature of the most influential design parameter.
Response Surface Methodology Application for Bacteriophage–Antibiotic Antibiofilm Activity Optimization
Authors: Grygorcewicz Bartłomiej , Gliźniewicz Marta , Olszewska Patrycja , Miłek Dominika , Czajkowski Artur , Serwin Natalia , Cecerska-Heryć Elżbieta , Rakoczy Rafał
Published: September 2023

Phage–antibiotic combination-based protocols are presently under heightened investigation. This paradigm extends to engagements with bacterial biofilms, necessitating novel computational approaches to comprehensively characterize and optimize the outcomes achievable via these combinations. This study aimed to explore the Response Surface Methodology (RSM) in optimizing the antibiofilm activity of bacteriophage–antibiotic combinations. We employ a combination of antibiotics (gentamicin, meropenem, amikacin, ceftazidime, fosfomycin, imipenem, and colistin) alongside the bacteriophage vB_AbaP_AGC01 to combat Acinetobacter baumannii biofilm. Based on the conducted biofilm challenge assays analyzed using the RSM, the optimal points of antibiofilm activity efficacy were effectively selected by applying this methodology, enabling the quantifiable mathematical representations. Subsequent optimization showed the synergistic potential of the anti-biofilm that arises when antibiotics are judiciously combined with the AGC01 bacteriophage, reducing biofilm biomass by up to 80% depending on the antibiotic used. The data suggest that the phage–imipenem combination demonstrates the highest efficacy, with an 88.74% reduction. Notably, the lower concentrations characterized by a high maximum reduction in biofilm biomass were observed in the phage–amikacin combination at cA = 0.00195 and cP = 0.38 as the option that required minimum resources. It is worth noting that only gentamicin antagonism between the phage and the antibiotic was detected.
Impact of Sleeve Gastrectomy on Fecal Microbiota in Individuals with Morbid Obesity
Authors: Tedjo Danyta I. , Wilbrink Jennifer A. , Boekhorst Jos , Timmerman Harro M. , Nienhuijs Simon W. , Stronkhorst Arnold , Savelkoul Paul H. M. , Masclee Ad A. M. , Penders John , Jonkers Daisy M. A. E.
Published: September 2023

Background: The intestinal microbiota plays an important role in the etiology of obesity. Sleeve gastrectomy (SG) is a frequently performed and effective therapy for morbid obesity. Objective: To investigate the effect of sleeve gastrectomy on the fecal microbiota of individuals with morbid obesity and to examine whether shifts in microbiota composition are associated with markers of inflammation and intestinal barrier function. Methods: Fecal and blood samples of healthy individuals (n = 27) and morbidly obese individuals pre-SG (n = 24), and at 2 months (n = 13) and 6 months post-SG (n = 9) were collected. The 16SrRNA gene was sequenced to assess microbiota composition. Fecal calprotectin, plasma inflammatory markers and intestinal permeability markers (multi-sugar test) were determined. Results: Fecal microbiota composition between morbidly obese and lean individuals was significantly different. The fecal microbiota composition changed significantly 2 and 6 months post-SG (p = 0.008) compared to pre-SG but not towards a more lean profile. The post-SG microbiota profile was characterized by an increase in facultative anaerobic bacteria, characteristic for the upper gastrointestinal tract. No correlations were found between inflammatory markers, intestinal permeability and microbial profile changes. Conclusions: Fecal microbiota composition in morbidly obese individuals changed significantly following SG. This change might be explained by functional changes induced by the SG procedure.
A Whole-Genome Sequencing-Based Approach for the Characterization of Klebsiella pneumoniae Co-Producing KPC and OXA-48-like Carbapenemases Circulating in Sardinia, Italy
Authors: Del Rio Arcadia , Fox Valeria , Muresu Narcisa , Sechi Illari , Cossu Andrea , Palmieri Alessandra , Scutari Rossana , Alteri Claudia , Sotgiu Giovanni , Castiglia Paolo , Piana Andrea
Published: September 2023

Background: Whole-genome sequencing (WGS) provides important information for the characterization, surveillance, and monitoring of antimicrobial resistance (AMR) determinants, particularly in cases of multi- and extensively drug-resistant microorganisms. We reported the results of a WGS analysis carried out on carbapenemases-producing Klebsiella pneumoniae, which causes hospital-acquired infections (HAIs) and is characterized by a marked resistance profile. Methods: Clinical, phenotypic, and genotypic data were collected for the AMR surveillance screening program of the University Hospital of Sassari (Italy) during 2020–2021. Genomic DNA was sequenced using the Illumina Nova Seq 6000 platform. Final assemblies were manually curated and carefully verified for the detection of antimicrobial resistance genes, porin mutations, and virulence factors. A phylogenetic analysis was performed using the maximum likelihood method. Results: All 17 strains analyzed belonged to ST512, and most of them carried the blaKPC-31 variant blaOXA-48-like, an OmpK35 truncation, and an OmpK36 mutation. Phenotypic analysis showed a marked resistance profile to all antibiotic classes, including β-lactams, carbapenems, aminoglycosides, fluoroquinolone, sulphonamides, and novel β-lactam/β-lactamase inhibitors (BL/BLI). Conclusion: WGS characterization revealed the presence of several antibiotic resistance determinants and porin mutations in highly resistant K. pneumoniae strains responsible for HAIs. The detection of blaKPC-31 in our hospital wards highlights the importance of genomic surveillance in hospital settings to monitor the emergence of new clones and the need to improve control and preventive strategies to efficiently contrast AMR.
Concurrent Brain Subregion Microgliosis in an HLA-II Mouse Model of Group A Streptococcal Skin Infection
Authors: Nookala Suba , Mukundan Santhosh , Grove Bryon , Combs Colin
Published: September 2023

The broad range of clinical manifestations and life-threatening infections caused by the Gram-positive bacterium, Streptococcus pyogenes or Group A Streptococcus (GAS), remains a significant concern to public health, with a subset of individuals developing neurological complications. Here, we examined the concurrent neuroimmune effects of subcutaneous GAS infections in an HLA-Class II (HLA) transgenic mouse model of subcutaneous GAS infection. To investigate changes in the skin–brain axis, HLA-DQ8 (DQA1*0301/DQB1*0302) mice (DQ8) were randomly divided into three groups: uninfected controls (No Inf), GAS infected and untreated (No Tx), and GAS infected with a resolution by clindamycin (CLN) treatment (CLN Tx) (10 mg/kg/5 days) and were monitored for 16 days post-infection. While the skin GAS burden was significantly reduced by CLN, the cortical and hippocampal GAS burden in the male DQ8 mice was not significantly reduced with CLN. Immunoreactivity to anti-GAS antibody revealed the presence of GAS bacteria in the vicinity of the neuronal nucleus in the neocortex of both No Tx and CLN Tx male DQ8 mice. GAS infection-mediated cortical cytokine changes were modest; however, compared to No Inf or No Tx groups, a significant increase in IL-2, IL-13, IL-22, and IL-10 levels was observed in CLN Tx females despite the lack of GAS burden. Western blot analysis of cortical and hippocampal homogenates showed significantly higher ionized calcium-binding adaptor-1 (Iba-1, microglia marker) protein levels in No Tx females and males and CLN Tx males compared to the No Inf group. Immunohistochemical analysis showed that Iba-1 immunoreactivity in the hippocampal CA3 and CA1 subregions was significantly higher in the CLN Tx males compared to the No Tx group. Our data support the possibility that the subcutaneous GAS infection communicates to the brain and is characterized by intraneuronal GAS sequestration, brain cytokine changes, Iba-1 protein levels, and concurrent CA3 and CA1 subregion-specific microgliosis, even without bacteremia.
The Role of Fusobacterium nucleatum in Oral and Colorectal Carcinogenesis
Authors: Pignatelli Pamela , Nuccio Federica , Piattelli Adriano , Curia Maria Cristina
Published: September 2023

In recent years, several studies have suggested a strong association of microorganisms with several human cancers. Two periodontopathogenic species in particular have been mentioned frequently: Fusobacterium nucleatum (F. nucleatum) and Porphyromonas gingivalis. Chronic periodontal disease has been reported to be a risk factor for oral squamous cell carcinoma (OSCC), colorectal cancer (CRC) and pancreatic cancer. F. nucleatum is a Gram-negative anaerobic bacterium that lives in the oral cavity, urogenital, intestinal and upper digestive tract. It plays a significant role as a co-aggregation factor, with almost all bacterial species that participate in oral plaque formation acting as a bridge between early and late colonizers. F. nucleatum, gives an important inflammatory contribution to tumorigenesis progression and is associated with epithelial-derived malignancies, such as OSCC and CRC. F. nucleatum produces an adhesion protein, FadA, which binds to VE-cadherin on endothelial cells and to E-cadherins on epithelial cells. The last binding activates oncogenic pathways, such as Wnt/βcatenin, in oral and colorectal carcinogenesis. F. nucleatum also affects immune response because its Fap2 protein interacts with an immune receptor named TIGIT present on some T cells and natural killer cells inhibiting immune cells activities. Morover, F. nucleatum release outer membrane vesicles (OMVs), which induce the production of proinflammatory cytokines and initiating inflammation. F. nucleatum migrates from the oral cavity and reaches the colon hematogenously but it is not known if in the bloodstream it reaches the CRC as free, erythrocyte-bound bacteria or in OMV. F. nucleatum abundance in CRC tissue has been inversely correlated with overall survival (OS). The prevention and treatment of periodontal disease through the improvement of oral hygiene should be included in cancer prevention protocols. FadA virulence factors may also serve as novel targets for therapeutic intervention of oral and colorectal cancer.
Clinopyroxene Compositions of E-MORB-Type Gabbro from Bingdaban Ophiolites in Central Tianshan, NW China: Insights into the Evolution of the Magmatic System and Geodynamic Setting
Authors: Song Yujia , Liu Xijun , Xiao Yao , Liu Xiao , Tian Hao
Published: September 2023

Clinopyroxene, one of the primary rock-forming minerals in mafic rocks, is the major host of lithophile elements in the mantle lithosphere and plays a crucial role in understanding mantle evolution and rock petrogenesis. Taking the Bingdaban ophiolite as an example, this study employed electron probe microanalysis and in situ trace element analysis to investigate the geochemistry of clinopyroxene in gabbros to determine the magma series and evolution, constrain the physicochemical conditions of the magmatic processes and explore the petrogenesis and tectonic setting. Representative gabbro samples were subjected to zircon U–Pb isotopic analysis, yielding an age of 424.3 ± 5.9 Ma. Geochemical investigations revealed that the Bingdaban gabbros exhibit tholeiitic composition, suggesting a genesis associated with enriched mid-ocean ridge basalt (E-MORB). Mineralogical analyses indicated that the clinopyroxene in the gabbros was Mg-rich, Fe-poor, and alkali-poor, representing a subalkaline series. The compositional end members of clinopyroxene were calculated as Wo38.9–48.0En30.9–48.1Fs10.4–24.4, indicating a predominance of diopside with a minor amount of augite. Temperature–pressure conditions imply that these rocks formed in a high-temperature, low-pressure, and shallow-source environment. Compositional estimates of the melt in equilibrium with clinopyroxene are consistent with the overall characteristics of the host rock, reflecting an E-MORB setting. The Bingdaban gabbro likely originated from an initially depleted mantle source that later received an input of enriched mantle material, indicating formation in either an initial oceanic or immature back-arc basin tectonic setting.
Exposure of Rats to Multi-Walled Carbon Nanotubes: Correlation of Inhalation Exposure to Lung Burden, Bronchoalveolar Lavage Fluid Findings, and Lung Morphology
Authors: Kasai Tatsuya , Fukushima Shoji
Published: September 2023

To evaluate lung toxicity due to inhalation of multi-walled carbon nanotubes (MWCNTs) in rats, we developed a unique MWCNT aerosol generator based on dry aerosolization using the aerodynamic cyclone principle. Rats were exposed to MWNT-7 (also known as Mutsui-7 and MWCNT-7) aerosolized using this device. We report here an analysis of previously published data and additional unpublished data obtained in 1-day, 2-week, 13-week, and 2-year inhalation exposure studies. In one-day studies, it was found that approximately 50% of the deposited MWNT-7 fibers were cleared the day after the end of exposure, but that clearance of the remaining fibers was markedly reduced. This is in agreement with the premise that the rapidly cleared fibers were deposited in the ciliated airways while the slowly cleared fibers were deposited beyond the ciliated airways in the respiratory zone. Macrophage clearance of MWNT-7 fibers from the alveoli was limited. Instead of macrophage clearance from the alveoli, containment of MWNT-7 fibers within induced granulomatous lesions was observed. The earliest changes indicative of pulmonary toxicity were seen in the bronchoalveolar lavage fluid. Macrophage-associated inflammation persisted from the one-day exposure to MWNT-7 to the end of the two-year exposure period. Correlation of lung tumor development with MWNT-7 lung burden required incorporating the concept of area under the curve for the duration of the study; the development of lung tumors induced by MWNT-7 correlated with lung burden and the duration of MWNT-7 residence in the lung.
The Effect of Nanobubbles on Transdermal Applications
Authors: Mitropoulos Athanasios Ch. , Pappa Christina , Kosheleva Ramonna I. , Kyzas George Z.
Published: September 2023

In the present work, a new method for dermal delivery using nanobubbles (NBs) is investigated. Oxygen NBs are generated in deionized water and used to produce cosmetic formulations with hyaluronic acid as an active ingredient. Nanobubbles result in the improvement of the effect and penetration of the active ingredient through Strat-M, a synthetic membrane that resembles human skin. Experiments conducted with the Franz Cell device confirm the greater penetration of the active ingredient into Strat-M due to NBs, compared to cosmetic formulations that do not contain NBs. The effect of NBs was further examined by measuring UV-Vis and FTIR spectra. A possible mechanism was outlined, too. It was also found that NBs do not change the pH or the FTIR spectrum of the cosmetic serum indicating non-toxicity.
Comment on Xiang et al. Association between the Triglyceride-Glucose Index and Vitamin D Status in Type 2 Diabetes Mellitus. Nutrients 2023, 15, 639
Authors: Mahat Roshan Kumar , Rathore Vedika
Published: September 2023

We read with great interest the article entitled “Association between the Triglyceride-Glucose Index and Vitamin D Status in Type 2 Diabetes Mellitus” by Xiang Q et al. [...]
Associations between Milk Intake and Sleep Disorders in Chinese Adults: A Cross-Sectional Study
Authors: Xu Jinzhong , Lao Jiaying , Jiang Qingxi , Lin Wenhui , Chen Xiyi , Zhu Chongrong , He Shencong , Xie Wenbo , Wang Fan , Yang Bo , Liu Yanlong
Published: September 2023

We aimed to examine the association of milk intake with sleep disorders and their specific indicators. The current study included 768 adults aged 28–95 from Wenling, China. Milk intake was assessed using a food frequency questionnaire with ten food items, while sleep disorders were measured using the Pittsburgh Sleep Quality Index (PSQI), with higher scores indicating poorer sleep. The participants were divided into two groups according to the average intake of milk per week: rare intake (≤62.5 mL/week) and regular intake (>62.5 mL/week). Primary measurements were multivariate-adjusted odds ratios (ORs) with 95% confidence intervals (CIs) for the prevalence of sleep disorders concerning regular milk intake compared with rare intake. In secondary analyses, linear regression analyses were performed to assess the effects of milk intake on sleep disorders and their specific dimensions. Regular intake of milk did not have a significant association with sleep disorders compared with rare intake (adjusted OR: 0.72, 95%; CI: 0.51, 1.03), but this association was found to be pronounced with sleep disturbances (OR: 0.49, 95%; CI: 0.28, 0.87). Increased intake of milk was significantly associated with the lower scores of PSQI for sleep quality (β: −0.045, 95%; CI: −0.083, −0.007) and sleep disturbances (β: −0.059, 95%; CI: −0.090, −0.029), respectively. When stratified by age and gender, the benefits of milk intake for sleep disorders and sleep disturbances were more significant in older adults (≥65) and men than in younger persons and women. In summary, regular milk intake benefits sleep quality, which may contribute to nutritional psychiatric support for prevention against sleep disorders.
Effects of Whey Protein Supplementation on Inflammatory Marker Concentrations in Older Adults
Authors: Adler Samuel , Olsen Wyatt , Rackerby Bryna , Spencer Rachel , Dallas David C.
Published: September 2023

Although whey protein isolate (WPI) has been shown to be immunomodulatory, its ability to modulate production of a broad array of inflammatory markers has not previously been investigated in healthy adults. We investigated the effects of daily supplementation with 35 g of WPI for 3 weeks on inflammatory marker concentrations in the blood serum and feces of 14 older adult subjects (mean age: 59). Serum was analyzed using a multiplex assay to quantify the cytokines IFN-γ, IL-1β, IL-1RA, IL-2, IL-3, IL-4, IL-5, IL-6, IL-7, IL-8, IL-9, IL-10, IL-12p70, IL-13, IL-17A and TNF-α. Fecal samples were analyzed using an ELISA for the inflammatory markers calprotectin and lactoferrin. Our results yielded high inter-subject variability and a significant proportion of cytokine concentrations that were below our method’s limit of quantification. We observed decreases in serum IL-12p70 in the washout phase compared with baseline, as well as the washout stage for fecal lactoferrin relative to the intervention stage. Serum IL-13 was also significantly reduced during the intervention and washout stages. Our data suggest that whey protein supplementation did not significantly alter most inflammatory markers measured but can alter concentrations of some inflammatory markers in healthy older adults. However, our study power of 35% suggests the number of participants was too low to draw strong conclusions from our data.
Comparison of CD4+/CD8+ Lymphocytic Subpopulations Pre- and Post-Antituberculosis Treatment in Patients with Diabetes and Tuberculosis
Authors: Rendón Ramírez Erick J. , Rosas-Taraco Adrián G. , Soto-Monciváis Berenice , Colunga-Pedraza Perla R. , Salazar-Riojas Rosario , Méndez-Ramírez Nereida , Arce-Mendoza Alma Yolanda , Muñiz-Buenrostro Antonio , Llaca-Díaz Jorge , Gomez-Almaguer David , Rendón Adrián
Published: September 2023

Is there a CD4+ and CD8+ immunity alteration in patients with pulmonary tuberculosis (TB) and diabetes (DM) that does not recover after antituberculosis treatment? This prospective comparative study evaluated CD4+ and CD8+ lymphocytic subpopulations and antituberculosis antibodies in patients with diabetes and tuberculosis (TB-DM), before and after antituberculosis treatment. CD4+ T cell counts were lower in patients with TB-DM compared to those with only TB or only DM, and these levels remained low even after two months of anti-TB treatment. Regarding the CD8+ T cell analysis, we identified higher blood values in the DM-only group, which may be explained by the high prevalence of latent tuberculosis (LTBI) in patients with DM. IgM antituberculosis antibodies levels were elevated in patients with only TB at baseline, and 2 months post-anti-TB treatment, IgG did not express any relevant alterations. Our results suggest an alteration in CD4+ immunity in patients with TB-DM that did not normalize after antituberculosis treatment.
Phylogenetic Investigations of Dengue 2019–2021 Outbreak in Guadeloupe and Martinique Caribbean Islands
Authors: Garcia--Van Smévoorde Margot , Piorkowski Géraldine , Emboulé Loic , Dos Santos Georges , Loraux Cécile , Guyomard-Rabenirina Stéphanie , Joannes Marie-Odile , Fagour Laurence , Najioullah Fatiha , Cabié André , de Lamballerie Xavier , Vega-Rúa Anubis , Césaire Raymond , Calvez Elodie
Published: September 2023

Dengue fever has been a public health problem in the Caribbean region since 1981, when it first reappeared in Cuba. In 1989, it was reported in Martinique and Guadeloupe (two French islands 200 km apart); since then, DENV has caused several epidemics locally. In 2019–2021, DENV-1, DENV-2, and DENV-3 were detected. Serotype distribution was differentiated, with DENV-2 and DENV-3 predominating in Guadeloupe and Martinique, respectively. Complete genome sequencing was carried out on 32 specimens, and phylogenic analysis identified the circulation of genotype V for DENV-1, cosmopolitan genotype for DENV-2, and genotype III for DENV-3. However, two distinct circulating groups were identified for DENV-1 and DENV-3, suggesting independent introductions. Overall, despite the context of the COVID-19 pandemic and the associated travel restrictions, these results confirm the active circulation of DENV and specific epidemiological features on each of the two islands. Such differences may be linked to the founder effect of the various introduction events, and to local factors such as the population immunity and the transmission capacity of the vectors. Further genomic and epidemiological characterization of DENV strains remains essential to understand how dengue spreads in each specific geographical context and to prevent future epidemics.
Non-Structural Proteins (Nsp): A Marker for Detection of Human Coronavirus Families
Authors: Tamayo-Ordóñez María Concepción , Rosas-García Ninfa María , Ayil-Gutiérrez Benjamín Abraham , Bello-López Juan Manuel , Tamayo-Ordóñez Francisco Alberto , Anguebes-Franseschi Francisco , Damas-Damas Siprian , Tamayo-Ordóñez Yahaira de Jesús
Published: September 2023

SARS-CoV-2 was the cause of the global pandemic that caused a total of 14.9 million deaths during the years 2020 and 2021, according to the WHO. The virus presents a mutation rate between 10−5 and 10−3 substitutions per nucleotide site per cell infection (s/n/c). Due to this, studies aimed at knowing the evolution of this virus could help us to foresee (through the future development of new detection strategies and vaccines that prevent the infection of this virus in human hosts) that a pandemic caused by this virus will be generated again. In this research, we performed a functional annotation and identification of changes in Nsp (non-structural proteins) domains in the coronavirus genome. The comparison of the 13 selected coronavirus pangenomes demonstrated a total of 69 protein families and 57 functions associated with the structural domain’s differentials between genomes. A marked evolutionary conservation of non-structural proteins was observed. This allowed us to identify and classify highly pathogenic human coronaviruses into alpha, beta, gamma, and delta groups. The designed Nsp cluster provides insight into the trajectory of SARS-CoV-2, demonstrating that it continues to evolve rapidly. An evolutionary marker allows us to discriminate between phylogenetically divergent groups, viral genotypes, and variants between the alpha and betacoronavirus genera. These types of evolutionary studies provide a window of opportunity to use these Nsp as targets of viral therapies.