bluuebunny/crossref_metadata_2025 huggingface dataset:
Occurrence of Antimicrobial Resistance in Canine and Feline Bacterial Pathogens in Germany under the Impact of the TÄHAV Amendment in 2018
Authors: Moerer Marianne , Lübke-Becker Antina , Bethe Astrid , Merle Roswitha , Bäumer Wolfgang
Published: July 2023

The occurrence of antimicrobial resistance due to the use of antimicrobials is considered to be a main cause for treatment failure of bacterial infections in humans and animals. The right of German veterinarians to use and prescribe medications such as antimicrobials is regulated by the Regulation of Veterinary Pharmacies (TÄHAV). The aim of this study was to investigate the impact of the second amendment to the TÄHAV in 2018 on the occurrence of antimicrobial resistance in selected bacterial pathogens isolated from dogs and cats in Germany. For this purpose, we analyzed antimicrobial susceptibility data from 38 German small animal practices gathered between 2015 and 2021 in cooperation with Laboklin (Labor für klinische Diagnostik GmbH & Co.KG, Bad Kissingen, Germany). Annual cumulative susceptibility data of eight bacterial species were analyzed and compared. The mean value of resistant isolates was determined for each year and supplemented by 95% confidence intervals. Encouraged by the amendment, an increase in sample submissions was observed in Germany. The highest resistance rates to the analyzed substances penicillin G, ampicillin, amoxicillin-clavulanic acid, cefovecin, and enrofloxacin were found for Staphylococcus pseudintermedius (S. pseudintermedius), S. aureus, and Escherichia coli (E. coli). In contrast, resistance rates were low for Pasteurella multocida (P. multocida) and β-hemolytic streptococci. Significant resistance trends (p < 0.05) assumed as influenced by the TÄHAV amendment could be the significant decreases in resistance rates of S. pseudintermedius against penicillin G to 67% (n = 322/479), and ampicillin to 63% (n = 286/453), as well as S. felis against amoxicillin-clavulanic acid and cefovecin to 2% (n = 2/109), furthermore, the reduction in the occurrence of resistance of S. aureus against enrofloxacin to 4% (n = 3/76) in 2021. Moreover, for all species, the efficacy against the analyzed substances was maintained over the study period.
Enhancement of Oxidative Stability of Deep-Fried Sunflower Oil by Addition of Essential Oil of Amomum villosum Lour.
Authors: Zhao Yunlong , Wu Haohao , Qu Mengrui , Liu Yuchen , Wang Dongying , Yang Haoduo , Wang Yingying , Wang Xuede , Blasi Francesca
Published: July 2023

In this study, the essential oil of the fruits of Amomum villosum Lour. (AVEO) was extracted through steam distillation and the components of the AVEO were analyzed using Gas Chromatography-Mass Spectrometry (GC-MS). Additionally, the antioxidant capacity in vitro of the AVEO was gauged using radical scavenging activity (DPPH, ABTS, superoxide anion) and ferric ion reducing antioxidant power (FRAP) assays; the antioxidant effect of a certain concentration of AVEO is even comparable to 0.08 mg/mL of butylated hydroxytoluene (BHT). Moreover, AVEO was applied to sunflower oil in a 30 h successive deep-frying experiment. Throughout the frying procedure, the sunflower oil-added antioxidant showed different degrees of benign changes in the physical and chemical parameters compared to the blank group, with 1 g/kg of AVEO being more consistent with 0.01 g/kg of tert-butyl hydroquinone (TBHQ), while 1.5 g/kg of essential oil revealed a stronger antioxidative capability. Meanwhile, the organoleptic characteristics of Chinese Maye, including its appearance, taste, flavor, and overall acceptability, were ameliorated when AVEO was added at 1.5 g/kg. Consequently, AVEO can be applied to substitute synthetic antioxidants as a natural antioxidant and flavoring agent during the deep-frying course of food.
Understanding the Photodynamic Therapy Induced Bystander and Abscopal Effects: A Review
Authors: Moloudi Kave , Sarbadhikary Paromita , Abrahamse Heidi , George Blassan P.
Published: July 2023

Photodynamic therapy (PDT) is a clinically approved minimally/non-invasive treatment modality that has been used to treat various conditions, including cancer. The bystander and abscopal effects are two well-documented significant reactions involved in imparting long-term systemic effects in the field of radiobiology. The PDT-induced generation of reactive oxygen and nitrogen species and immune responses is majorly involved in eliciting the bystander and abscopal effects. However, the results in this regard are unsatisfactory and unpredictable due to several poorly elucidated underlying mechanisms and other factors such as the type of cancer being treated, the irradiation dose applied, the treatment regimen employed, and many others. Therefore, in this review, we attempted to summarize the current knowledge regarding the non-targeted effects of PDT. The review is based on research published in the Web of Science, PubMed, Wiley Online Library, and Google Scholar databases up to June 2023. We have highlighted the current challenges and prospects in relation to obtaining clinically relevant robust, reproducible, and long-lasting antitumor effects, which may offer a clinically viable treatment against tumor recurrence and metastasis. The effectiveness of both targeted and untargeted PDT responses and their outcomes in clinics could be improved with more research in this area.
Experimental and Numerical Study of Nonlinear Vibration in Compressor Stator Blade with Holding Ring Structure Considering Contact Friction
Authors: Ma Jiaobin , Liu Zhufeng , Xie Yonghui , Zhang Di
Published: July 2023

At present, there are very few vibration test designs for compressor stator blades in damped blade test research, and there is a lack of consideration of the holding ring structure of the blade installation. In recent years, compressor designs have become more elaborate, and their structures have become more compact. For improving compressor stator blade design, it is necessary to study the blade vibration response considering contact and friction. In this paper, a compressor stator blade vibration test system with a holding ring structure is designed and built. The composition of the system and the flow of vibration are tested. Then, the nonlinear vibration rules of the model stator blades are experimentally studied through the built test bench. The experimental conditions include excitation forces of 1 N, 2 N, 3 N and 4 N, respectively. At the same time, the normal load of the outer holding ring and the blade contact surface includes 10 N, 20 N, 30 N and 40 N working conditions. The nonlinear vibration law of the test model blade considering contact friction is analyzed using a numerical method and experimental data. The experimental data agree well with the numerical analysis results, and the relative error of measurement is basically less than 5%. It is concluded that the damping vibration rule of the test model blade is related to the exciting force applied by the exciter and the contact surface normal load applied by the adjusting bolt. When these two parameters change, the movement behavior of the contact surface will switch between macro-slip, fretting slip and even a viscous state. Therefore, the amplitude of the blade will change and show nonlinear vibration characteristics. The experimental data in this paper can provide a reference for research on stator ring vibration safety in compressors.
The Detection of Fake News in Arabic Tweets Using Deep Learning
Authors: Alyoubi Shatha , Kalkatawi Manal , Abukhodair Felwa
Published: July 2023

Fake news has been around for a long time, but the rise of social networking applications over recent years has rapidly increased the growth of fake news among individuals. The absence of adequate procedures to combat fake news has aggravated the problem. Consequently, fake news negatively impacts various aspects of life (economical, social, and political). Many individuals rely on Twitter as a news source, especially in the Arab region. Mostly, individuals are reading and sharing regardless of the truth behind the news. Identifying fake news manually on these open platforms would be challenging as they allow anyone to build networks and publish the news in real time. Therefore, creating an automatic system for recognizing news credibility on social networks relying on artificial intelligence techniques, including machine learning and deep learning, has attracted the attention of researchers. Using deep learning methods has shown promising results in recognizing fake news written in English. Limited work has been conducted in the area of news credibility recognition for the Arabic language. This work proposes a deep learning-based model to detect fake news on Twitter. The proposed model utilizes the news content and social context of the user who participated in the news dissemination. In seeking an effective detection model for fake news, we performed extensive experiments using two deep learning algorithms with varying word embedding models. The experiments were evaluated using a self-created dataset. The experimental results revealed that the MARBERT with the convolutional neural network (CNN) model scores a superior performance in terms of accuracy and an F1-score of 0.956. This finding proves that the proposed model accurately detects fake news in Arabic Tweets relating to various topics.
Electrochemical Disinfection of Root Canals Bears No Risk of Damaging Periapical Tissues in a Dog Model
Authors: Koch Maximilian , Demmer Elena , Palarie Victor , Burkovski Andreas , Karl Matthias
Published: July 2023

Boron-doped diamond (BDD) electrodes have been advocated as a potential treatment alternative to the established methods for root canal disinfection. As healing of periapical tissue is important in this context, the associated risk of host tissue damage was to be evaluated. Following in vitro cell culture experiments (HeLa cells), root canal treatment was performed in an animal trial comparing BDD electrode application and the currently used rinsing media with respect to cell viability and host tissue damage. Statistical analyses comparing the size of radiolucency were based on Kruskal-Wallis and Nemenyi’s All Pairs tests (α = 0.05). The direct application of BDD electrodes had a time-dependent effect on cell viability comparable to H2O2, NaOCl, and CHX application. In contrast to the chemical treatment, the effect of BDD electrodes was transient. Conventionally treated teeth and teeth additionally treated with BDD electrodes did not significantly differ from each other with respect to the size of the periapical radiolucency as observed radiographically (vertical p = 0.998 and horizontal p = 0.878) and histologically (vertical p = 0.940 and horizontal p = 0.862). While showing greater disinfection efficiency, the application of BDD electrodes for the electrochemical disinfection of root canals does not have a greater risk of host tissue damage compared to the conventional treatment.
A Deep Model for Species-Specific Prediction of Ribonucleic-Acid-Binding Protein with Short Motifs
Authors: Wei Zhi-Sen , Rao Jun , Lin Yao-Jin
Published: July 2023

RNA-binding proteins (RBPs) play an important role in the synthesis and degradation of ribonucleic acid (RNA) molecules. The rapid and accurate identification of RBPs is essential for understanding the mechanisms of cell activity. Since identifying RBPs experimentally is expensive and time-consuming, computational methods have been explored to predict RBPs directly from protein sequences. In this paper, we developed an RBP prediction method named CnnRBP based on a convolution neural network. CnnRBP derived a sparse high-dimensional di- and tripeptide frequency feature vector from a protein sequence and then reduced this vector to a low-dimensional one using the Light Gradient Boosting Machine (LightGBM) algorithm. Then, the low-dimensional vectors derived from both RNA-binding proteins and non-RNA-binding proteins were fed to a multi-layer one-dimensional convolution network. Meanwhile, the SMOTE algorithm was used to alleviate the class imbalance in the training data. Extensive experiments showed that the proposed method can extract discriminative features to identify RBPs effectively. With 10-fold cross-validation on the training datasets, CnnRBP achieved AUC values of 99.98%, 99.69% and 96.72% for humans, E. coli and Salmonella, respectively. On the three independent datasets, CnnRBP achieved AUC values of 0.91, 0.96 and 0.91, outperforming the recent tripeptide-based method (i.e., TriPepSVM) by 8%, 4% and 5%, respectively. Compared with the state-of-the-art CNN-based predictor (i.e., iDRBP_MMC), CnnRBP achieved MCC values of 0.67, 0.68 and 0.73 with significant improvements by 6%, 6% and 15%, respectively. In addition, the cross-species testing shows that CnnRBP has a robust generalization performance for cross-species RBP prediction between close species.
A Machine-Learning-Based Software for the Simulation of Regional Characteristic Ground Motion
Authors: Hu Jinjun , Ding Yitian , Lin Shibin , Zhang Hui , Jin Chaoyue
Published: July 2023

Ground-motion simulations provide input time history data required for designing and assessing structures; however, the simulations conducted by the currently available tools only match the design spectrum without verifying if the statistical characteristics of the spectrum and duration are satisfied. A ground-motion simulation software was developed to resolve these issues. The developed software employs machine learning methods to match the amplitude, spectrum, and duration features of the target region. Principal component analysis is employed to extract features from the actual ground-motion database to detect characteristic ground motions and predict the target acceleration amplitude, response spectrum, and duration, based on the response spectrum and duration prediction equations. The results show that the simulated ground motion can match the amplitude, spectrum, and duration characteristics well. Therefore, the simulated ground motion can provide more reasonable input for the structure. Moreover, the developed software provides visualization functions that enable the user to determine the target area and obtain the amplitude field intuitively.
Renewable-Based Microgrids: Design, Control and Optimization
Authors: Tostado-Véliz Marcos , Arévalo Paul , Kamel Salah , El-Sehiemy Ragab A. , Senjyu Tomonobu
Published: July 2023

To achieve carbon neutrality by 2050, additional measures must be taken, including the extensive incorporation of renewable energy sources (RESs) [...]
Cross-Modal Images Matching Based Enhancement to MEMS INS for UAV Navigation in GNSS Denied Environments
Authors: Han Songlai , Zhao Mingcun , Wang Kai , Dong Jing , Su Ang
Published: July 2023

A new cross-modal image matching method is proposed to solve the problem that unmanned aerial vehicles (UAVs) are difficult to navigate in GPS-free environment and night environment. In this algorithm, infrared image or visible image is matched with satellite visible image. The matching process is divided into two steps, namely, coarse matching and fine alignment. Based on the dense structure features, the coarse matching algorithm can realize the position update above 10 Hz with a small amount of computation. Based on the end-to-end matching network, the fine alignment algorithm can align the multi-sensor image with the satellite image under the condition of interference. In order to obtain the position and heading information with higher accuracy, the fusion of the information after visual matching with the inertial information can restrain the divergence of the inertial navigation position error. The experiment shows that it has the advantages of strong anti-interference ability, strong reliability, and low requirements on hardware, which is expected to be applied in the field of unmanned navigation.
Vibration-Based Detection of Bearing Damages in a Planetary Gearbox Using Convolutional Neural Networks
Authors: Scholtyssek Julia , Bislich Luka Josephine , Cordes Felix , Krieger Karl-Ludwig
Published: July 2023

Tapered roller bearings are used partly in very rough and highly stressful environmental conditions. Therefore, the need for condition monitoring is increasing. This study is intended to provide an approach for monitoring bearings in a two-stage planetary gearbox based on vibration analysis. In total, the data of six damage phenomena and one healthy bearing are collected. A convolutional neural network (CNN) is trained and evaluated by using the balanced accuracy. Mainly, it is investigated how many damage severities can be detected. In addition, the robustness of the model regarding unknown speeds and damage phenomena should be proven. The results show a very good differentiation up to all of the presented damage phenomena. The classifier reaches an averaged balanced accuracy of 0.96. Also, samples collected at unknown speeds can be classified well for speed values within the known range. For unknown damage phenomena, the classifier shows limits so that a reliable classification is only applicable with a binary classifier, which differentiates between healthy and damaged. The investigations therefore show that a reliable detection of bearing damage is possible in a two-stage planetary gear. Furthermore, the transferability of the model is successfully tested and implemented for the binary classifier.
Patient Satisfaction with Anterior Interim CAD-CAM Rehabilitations Designed by CAD Technician versus Trained Dentist—A Clinical Preliminary Study
Authors: Cuschieri Laura , Casha Amy , No-Cortes Juliana , Ferreira Lima Jacqueline , Cortes Arthur
Published: July 2023

The objective of this study was to assess the impact of digital waxing expertise on patient satisfaction with anterior interim computer-aided design and computer-aided manufacturing (CAD-CAM) prosthetic rehabilitations designed either by a CAD and dental technician or by a dental clinician with basic CAD-CAM training. This in vivo preliminary study was conducted on a total of 18 patients receiving anterior CAD-CAM rehabilitations (at least from canine to canine) with fixed bridges and/or single crowns. Only patients that had conventional chairside temporary restorations were enrolled. Three within-patient groups were defined at different time points: group CONTROL refers to all 18 patients at their first appointment, when they were using their initial temporary conventional prostheses; group DENT refers to all patients immediately after trying in a set of CAD-CAM prostheses designed by a dental clinician (with basic one-week CAD-CAM training); and group CAD refers to all patients after trying in a set of CAD-CAM prostheses for the same tooth elements but designed by an experienced CAD technician (who was also an experienced dental prosthetic technician). All CAD-CAM restorations were milled in polymethyl methacrylate (PMMA) with high translucency and strength properties (Prime, Zirkonzahn). Satisfaction with comfort and esthetics was assessed for all patients for the three different time points (groups CONTROL, DENT and CAD). Statistically significant differences among groups were assessed with the Friedmann’s test. Group CAD significantly outperformed the other groups in both assessed variables (p = 0.001). The group DENT, in turn, outperformed group CONTROL for satisfaction with esthetics (p = 0.006) but not for comfort (p > 0.05). In conclusion, CAD operator background and expertise level significantly affect patient self-reported outcomes for anterior CAD-CAM rehabilitations. Single crowns and fixed bridges digitally designed by an experienced professional trained in both CAD-CAM and dental technology will likely offer high satisfaction and comfort to patients receiving anterior prosthetic rehabilitations.
Relationship between Effective Duration and Intelligibility of Japanese Monosyllables in Individuals with Sensorineural Hearing Loss
Authors: Akasaka Sakie , Nishimura Tadashi , Shimokura Ryota , Kitahara Tadashi , Hosoi Hiroshi
Published: July 2023

Among the temporal elements in the autocorrelation function, the effective duration (τe) is a useful indicator of speech recognition for patients with sensorineural hearing impairment. We assessed the influence of speech recognition performance on the relationship between the percentage of accurately perceived articulation and the median τe (τe-med) and the relationship between monosyllabic confusion and the τe-med. Significant correlations were observed between the articulation percentage and the average τe-med in groups with high, middle, and low speech recognition scores (SRSs). Two-factor mixed analysis of variance revealed significant main effects for the condition (presentation/response). There was no significant main effect for group (high-, middle-, or low-SRS) scores and no significant interaction between the groups. The average τe-med of the response was significantly longer than that of the presentation in all three groups. Monosyllables with short τe-med values tended to be misheard as monosyllables with a long τe-med when confusion occurred. The τe-med was useful for estimating monosyllables that patients with sensorineural hearing impairment find easy to listen to, independent of speech recognition performance.
Application of the Kinematic Assessment of Multi-Faced Slopes Using Stereographic Projection: The Case Study of a Planar Failure on the Spondylus Coast, Ecuador
Authors: Borja Bernal Cesar Patricio , Jordá Bordehore Luis
Published: July 2023

This manuscript presents a relevant practical application of the stability analysis of multi-face slopes that uses the concept of the restricted daylight envelope in multi-faced slopes (MFS). The methodology was applied to the back analysis of a case study of a failed slope in mudstones and sandstones on the Spondylus coast in Ecuador. The instabilities analyzed included several rock cliffs with dihedral rock faces in mudstones. It is interesting to analyze the failure mechanism of these natural coastal slopes because, on the Spondylus coast, several hotels and tourist spots are located near the upper parts of some similar regions. The stereographic projection methodology can simulate complex geometries and simplify the analysis.
Numerical Modeling and Simulation of Non-Invasive Acupuncture Therapy Utilizing Near-Infrared Light-Emitting Diode
Authors: Singh Sundeep , Escobar Andres , Wang Zexi , Zhang Zhiyi , Ramful Chundra , Xu Chang-Qing
Published: July 2023

Acupuncture is one of the most extensively used complementary and alternative medicine therapies worldwide. In this study, we explore the use of near-infrared light-emitting diodes (LEDs) to provide acupuncture-like physical stimulus to the skin tissue, but in a completely non-invasive way. A computational modeling framework has been developed to investigate the light-tissue interaction within a three-dimensional multi-layer model of skin tissue. Finite element-based analysis has been conducted, to obtain the spatiotemporal temperature distribution within the skin tissue, by solving Pennes’ bioheat transfer equation, coupled with the Beer-Lambert law. The irradiation profile of the LED has been experimentally characterized and imposed in the numerical model. The experimental validation of the developed model has been conducted through comparing the numerical model predictions with those obtained experimentally on the agar phantom. The effects of the LED power, treatment duration, LED distance from the skin surface, and usage of multiple LEDs on the temperature distribution attained within the skin tissue have been systematically investigated, highlighting the safe operating power of the selected LEDs. The presented information about the spatiotemporal temperature distribution, and critical factors affecting it, would assist in better optimizing the desired thermal dosage, thereby enabling a safe and effective LED-based photothermal therapy.
A New Fuzzy-Based Classification Method for Use in Smart/Precision Medicine
Authors: Zaitseva Elena , Levashenko Vitaly , Rabcan Jan , Kvassay Miroslav
Published: July 2023

The development of information technology has had a significant impact on various areas of human activity, including medicine. It has led to the emergence of the phenomenon of Industry 4.0, which, in turn, led to the development of the concept of Medicine 4.0. Medicine 4.0, or smart medicine, can be considered as a structural association of such areas as AI-based medicine, telemedicine, and precision medicine. Each of these areas has its own characteristic data, along with the specifics of their processing and analysis. Nevertheless, at present, all these types of data must be processed simultaneously, in order to provide the most complete picture of the health of each individual patient. In this paper, after a brief analysis of the topic of medical data, a new classification method is proposed that allows the processing of the maximum number of data types. The specificity of this method is its use of a fuzzy classifier. The effectiveness of this method is confirmed by an analysis of the results from the classification of various types of data for medical applications and health problems. In this paper, as an illustration of the proposed method, a fuzzy decision tree has been used as the fuzzy classifier. The accuracy of the classification in terms of the proposed method, based on a fuzzy classifier, gives the best performance in comparison with crisp classifiers.
Human Patient-Derived Brain Tumor Models to Recapitulate Ependymoma Tumor Vasculature
Authors: Tang-Schomer Min D. , Bookland Markus J. , Sargent Jack E. , N. Jackvony Taylor
Published: July 2023

Despite in vivo malignancy, ependymoma lacks cell culture models, thus limiting therapy development. Here, we used a tunable three-dimensional (3D) culture system to approximate the ependymoma microenvironment for recapitulating a patient’s tumor in vitro. Our data showed that the inclusion of VEGF in serum-free, mixed neural and endothelial cell culture media supported the in vitro growth of all four ependymoma patient samples. The growth was driven by Nestin and Ki67 double-positive cells in a putative cancer stem cell niche, which was manifested as rosette-looking clusters in 2D and spheroids in 3D. The effects of extracellular matrix (ECM) such as collagen or Matrigel superseded that of the media conditions, with Matrigel resulting in the greater enrichment of Nestin-positive cells. When mixed with endothelial cells, the 3D co-culture models developed capillary networks resembling the in vivo ependymoma vasculature. The transcriptomic analysis of two patient cases demonstrated the separation of in vitro cultures by individual patients, with one patient’s culture samples closely clustered with the primary tumor tissue. While VEGF was found to be necessary for preserving the transcriptomic features of in vitro cultures, the presence of endothelial cells shifted the gene’s expression patterns, especially genes associated with ECM remodeling. The homeobox genes were mostly affected in the 3D in vitro models compared to the primary tumor tissue and between different 3D formats. These findings provide a basis for understanding the ependymoma microenvironment and enabling the further development of patient-derived in vitro ependymoma models for personalized medicine.
A Molecular Analysis of the Aminopeptidase P-Related Domain of PID-5 from Caenorhabditis elegans
Authors: Lloyd Anna C. , Gregory Kyle S. , Isaac R. Elwyn , Acharya K. Ravi
Published: July 2023

A novel protein, PID-5, has been shown to be a requirement for germline immortality and has recently been implicated in RNA-induced epigenetic silencing in the Caenorhabditis elegans embryo. Importantly, it has been shown to contain both an eTudor and aminopeptidase P-related domain. However, the silencing mechanism has not yet been fully characterised. In this study, bioinformatic tools were used to compare pre-existing aminopeptidase P molecular structures to the AlphaFold2-predicted aminopeptidase P-related domain of PID-5 (PID-5 APP-RD). Structural homology, metal composition, inhibitor-bonding interactions, and the potential for dimerisation were critically assessed through computational techniques, including structural superimposition and protein-ligand docking. Results from this research suggest that the metallopeptidase-like domain shares high structural homology with known aminopeptidase P enzymes and possesses the canonical ‘pita-bread fold’. However, the absence of conserved metal-coordinating residues indicates that only a single Zn2+ may be bound at the active site. The PID-5 APP-RD may form transient interactions with a known aminopeptidase P inhibitor and may therefore recognise substrates in a comparable way to the known structures. However, loss of key catalytic residues suggests the domain will be inactive. Further evidence suggests that heterodimerisation with C. elegans aminopeptidase P is feasible and therefore PID-5 is predicted to regulate proteolytic cleavage in the silencing pathway. PID-5 may interact with PID-2 to bring aminopeptidase P activity to the Z-granule, where it could influence WAGO-4 activity to ensure the balanced production of 22G-RNA signals for transgenerational silencing. Targeted experiments into APPs implicated in malaria and cancer are required in order to build upon the biological and therapeutic significance of this research.
The Potential of Fasting-Mimicking Diet as a Preventive and Curative Strategy for Alzheimer’s Disease
Authors: Boccardi Virginia , Pigliautile Martina , Guazzarini Anna Giulia , Mecocci Patrizia
Published: July 2023

This review examines the potential of fasting-mimicking diets (FMDs) in preventing and treating Alzheimer’s disease (AD). FMDs are low-calorie diets that mimic the physiological and metabolic effects of fasting, including the activation of cellular stress response pathways and autophagy. Recent studies have shown that FMDs can reduce amyloid-beta accumulation, tau phosphorylation, and inflammation, as well as improve cognitive function in animal models of AD. Human studies have also reported improvements in AD biomarkers, cognitive functions, and subjective well-being measures following FMDs. However, the optimal duration and frequency of FMDs and their long-term safety and efficacy remain to be determined. Despite these uncertainties, FMDs hold promise as a non-pharmacological approach to AD prevention and treatment, and further research in this area is warranted.
Regulation of Bone by Mechanical Loading, Sex Hormones, and Nerves: Integration of Such Regulatory Complexity and Implications for Bone Loss during Space Flight and Post-Menopausal Osteoporosis
Authors: Hart David A.
Published: July 2023

During evolution, the development of bone was critical for many species to thrive and function in the boundary conditions of Earth. Furthermore, bone also became a storehouse for calcium that could be mobilized for reproductive purposes in mammals and other species. The critical nature of bone for both function and reproductive needs during evolution in the context of the boundary conditions of Earth has led to complex regulatory mechanisms that require integration for optimization of this tissue across the lifespan. Three important regulatory variables include mechanical loading, sex hormones, and innervation/neuroregulation. The importance of mechanical loading has been the target of much research as bone appears to subscribe to the “use it or lose it” paradigm. Furthermore, because of the importance of post-menopausal osteoporosis in the risk for fractures and loss of function, this aspect of bone regulation has also focused research on sex differences in bone regulation. The advent of space flight and exposure to microgravity has also led to renewed interest in this unique environment, which could not have been anticipated by evolution, to expose new insights into bone regulation. Finally, a body of evidence has also emerged indicating that the neuroregulation of bone is also central to maintaining function. However, there is still more that is needed to understand regarding how such variables are integrated across the lifespan to maintain function, particularly in a species that walks upright. This review will attempt to discuss these regulatory elements for bone integrity and propose how further study is needed to delineate the details to better understand how to improve treatments for those at risk for loss of bone integrity, such as in the post-menopausal state or during prolonged space flight.
The Enigmatic CA2: Exploring the Understudied Region of the Hippocampus and Its Involvement in Parkinson’s Disease
Authors: Zhao Fang , Behnisch Thomas
Published: July 2023

Parkinson’s disease (PD) is a neurodegenerative disease that affects both motor and non-motor functions. Although motor impairment is a prominent clinical sign of PD, additional neurological symptoms may also occur, particularly in the preclinical and prodromal stages. Among these symptoms, social cognitive impairment is common and detrimental. This article aims to review non-motor symptoms in PD patients, focusing on social cognitive deficits. It also examines the specific characteristics of the CA2 region and its involvement in social behavior, highlighting recent advances and perspectives. Additionally, this review provides critical insights into and analysis of research conducted in rodents and humans, which may help improve the understanding of the current status of putative therapeutic strategies for social cognitive dysfunction in PD and potential avenues related to the function of the hippocampal CA2 region.
Fusion Protein of RBP and Albumin Domain III Reduces Lung Fibrosis by Inactivating Lung Stellate Cells
Authors: Choi Jaeho , Son Yuna , Moon Ji Wook , Park Dae Won , Kim Young-Sik , Oh Junseo
Published: July 2023

Activated stellate cells play a role in fibrosis development in the liver, pancreas, and kidneys. The fusion protein R-III, which consists of retinol-binding protein and albumin domain III, has been demonstrated to attenuate liver and renal fibrosis by suppressing stellate cell activation. In this study, we investigated the efficacy of R-III against bleomycin-induced lung fibrosis in mice. R-III reduced lung fibrosis and primarily localized in autofluorescent cells in the lung tissue. Furthermore, we isolated lung stellate cells (LSCs) from rat lungs using the isolation protocol employed for hepatic stellate cells (HSCs). LSCs shared many characteristics with HSCs, including the presence of vitamin A-containing lipid droplets and the expression of alpha-smooth muscle actin and collagen type I, markers for activated HSCs/myofibroblasts. LSCs spontaneously transdifferentiated into myofibroblasts in in vitro culture, which was inhibited by R-III. These findings suggest that R-III may reduce lung fibrosis by inactivating LSCs and could be a promising treatment for extrahepatic fibrosis.
Design and Simulation of a Hierarchical Parallel Distributed Processing Model for Orientation Selection Based on Primary Visual Cortex
Authors: Wei Hui , Ye Jingyong , Li Jiaqi , Wang Yun
Published: July 2023

The study of the human visual system not only helps to understand the mechanism of the visual system but also helps to develop visual aid systems to help the visually impaired. As the systematic study of neural signal processing mechanisms in early biological vision continues, the hierarchical structure of the visual system is gradually being dissected, bringing the possibility of building brain-like computational models from a bionic perspective. In this paper, we follow the objective facts of neurobiology and propose a parallel distributed processing computational model of primary visual cortex orientation selection with reference to the complex process of visual signal processing and transmission between the retina to the primary visual cortex, the hierarchical receptive field structure between cells in each layer, and the very fine-grained parallel distributed characteristics of cortical visual computation, which allow for high speed and efficiency. We approach the design from a brain-like chip perspective, map our network model on the field programmable gate array (FPGA), and perform simulation experiments. The results verify the possibility of implementing our proposed model with programmable devices, which can be applied to small wearable devices with low power consumption and low latency.
COVID-19-Related Stress and Its Association with Intimate Partner Violence Perpetration and Victimization
Authors: Keilholtz Brooke , Spencer Chelsea , Vail Summer , Palmer Megan
Published: July 2023

Intimate partner violence (IPV) is a pervasive issue, and during the COVID-19 pandemic, it has been speculated that the prevalence rates of IPV increased. This paper aims to understand how pandemic-specific distress was related to experiencing and perpetrating IPV. Using self-reported survey data from 371 individuals living in the United States, this study used multiple logistic regressions to examine how reports of distress related to working from home, working outside the home, isolation, stay-at-home orders, mask mandates, physical and mental health, finances, interpersonal relationships, taking care of children, and online learning for children, as well as reports of partner conflict regarding COVID-19, were associated with physical, psychological, and sexual IPV perpetration and victimization. Our results indicated that distress related to family relationships, taking care of children, and COVID-19 as a source of conflict were all associated with an increased risk of IPV victimization, while distress related to mask mandates and friendships was associated with a decreased risk. Distress related to physical health, family relationships, taking care of children, and COVID-19 being a source of conflict were associated with an increased risk of IPV perpetration, while distress related to mental health and friendships was associated with a decreased risk. Implications for researchers and clinicians are discussed.
Investigation of Sensible Cooling Performance in the Case of an Air Handling Unit System with Indirect Evaporative Cooling: Indirect Evaporative Cooling Effects for the Additional Cooling System of Buildings
Authors: Kostyák Attila , Szekeres Szabolcs , Csáky Imre
Published: July 2023

Previous studies have shown that the amount of energy consumed by mechanical cooling can be significantly reduced by the indirect evaporative cooling (IEC) process. By increasing the heat recovery efficiency of air handling units (AHUs), sensible cooling performance can be achieved with the IEC process for a significant part of the cooling season. This study determined the sensible cooling performance under which outdoor air conditions can be achieved. With IEC, the indoor humidity load cannot be adequately managed and must be solved by a supplementary cooling system, which may require additional cooling energy. This study shows the effect of the set indoor humidity on the amount of cooling energy required. The increase in energy consumption of the supplementary cooling system has been determined by simulation and for which indoor air conditions the amount of cooling energy used can be optimized if only IEC cooling is used in the air handling unit.
Study on the Liquefaction Mechanism of Mixed-Size Tailings Material Based on Grain Contact State Theory
Authors: Jiang Chunlin , Wang Guangjin , Zhang Yanbo , Liang Jinglong
Published: July 2023

Tailings ponds serve as high-potential energy structures designed to store waste tailings and other industrial materials. However, they can give rise to significant environmental pollution and pose a substantial threat to social and economic development, as well as the safety of people’s lives and property. Seismic disasters can cause liquefaction of tailings, leading to destabilization and dam failure of tailings ponds, and the evolution of dynamic pore pressure of tailings can indirectly reflect the destabilization process of tailings ponds. Fine grain content is one of the main factors affecting the dynamic strength and pore pressure development of tailings. This article studies the microscopic characteristics of tailings material through microscopic observation, triaxial testing, discrete element simulation, and grain contact state theory, aiming to analyze the influence mechanism of fine grain content on the micromechanics of tailings. Based on the grain contact state theory, the tailings with different fine grain contents are classified into three types: coarse grain tailings, intermediate-size grain tailings, and fine grain tailings, and the grain contact is classified into four different states. In contact state 1, the vibration pore pressure exhibits a “fast-stable” development mode with increasing vibrations. In contact state 2 or 3, the vibration pore pressure develops linearly with vibrations. For contact state 4, the development of vibration pore pressure presents a “fast-stable-sharp” development mode. The effect of fine grain content (FC) on the liquefication of the tailings studied in the present work is as follows. When the fine grain content is FC<30%, the liquefaction resistance of the tailings decreases with the increase of FC. When FC>30%, the liquefaction resistance increases with the increase of FC. When FC=30%, the liquefaction resistance is the lowest, indicating that the critical threshold of the fine grain content of the tailings studied in the present work is FCth=30%.
Improvement in the Seismic Performance of a Super-Long-Span Concrete-Filled Steel-Tube-Arch Bridge
Authors: Ye Dan , Tong Yijin , Gan Lijun , Tang Zhuoran , Zhang Ruijie
Published: July 2023

The applicability of current seismic-performance-improvement technologies needs to be studied. This research took a super-long-span CFST arch bridge with a total length of 788 m as the object on which to perform a non-linear time-history analysis and a seismic-check calculation according to the seismic response, so as to reveal the seismic weak points of the arch bridge. After the completion of the bridge’s construction, we arranged and utilized the stayed buckle cables (SBCs) reasonably. The seismic performance of the super-long-span CFST arch bridge was improved through friction-pendulum bearings (FPBs) and SBCs. The research shows that FPBs can solve the problem of the insufficient shear resistance of bearings, and SBCs can address the problem whereby the compressive stress of the transverse connection of the main arch exceeds the allowable stress. Moreover, SBCs can increase the transverse stiffness of arch bridges and reduce their seismic responses. Finally, a combination of FPBs and SBCs was adopted to improve the overall seismic performance of the arch bridge and obtain the best seismic-performance-improvement effect.
Improved Recognition Accuracy of Myrrh Decoction Pieces by Electronic Nose Technology Using GC-MS Analysis and Sensor Selection
Authors: Zhou Gailian , He Ting , Xie Xueting , Qin Jianfeng , Wei Wei , Zhang Yujing , Hao Erwei
Published: July 2023

The quality of myrrh decoction pieces can be influenced by factors such as origin, source, and processing methods. The quality of myrrh in the market varies greatly, and adulteration is a serious issue, highlighting the urgent need for improved quality control measures. This study explores the integration of GC–MS analysis and sensor selection in electronic nose technology for the improved classification of myrrh decoction pieces. GC–MS analysis revealed the presence of 130 volatile compounds in the six myrrh samples, primarily composed of alkene compounds, and each sample exhibited variations in composition. An electronic nose system was designed using a sensor array consisting of six sensors selected from twelve sensors capable of detecting volatile compounds consistent with myrrh composition, including WO3 quantum dots, Fe2O3 hollow nanorods, ZnFe2O4 nanorods, SnO2 nanowires, and two commercially available sensors. The sensors exhibited distinct response patterns to the myrrh samples, indicating their suitability for myrrh analysis. Various sensor parameters, including response, response and recovery time, integral area, and slope, were computed to characterize the sensors’ performance. These parameters provided valuable insight into the sensor–gas interactions and the unique chemical profiles of the myrrh samples. The LDA model demonstrated high accuracy in differentiating between the myrrh types, utilizing the discriminative features captured by the sensor array, with a classification accuracy of 90% on the testing set. This research provides a comprehensive evaluation method for the quality control of myrrh pieces and a scientific basis for the development and utilization of myrrh.
Symptom Profiles of Children and Young People 12 Months after SARS-CoV-2 Testing: A National Matched Cohort Study (The CLoCk Study)
Authors: Pinto Pereira Snehal M. , Nugawela Manjula D. , McOwat Kelsey , Dalrymple Emma , Xu Laila , Ladhani Shamez N. , Simmons Ruth , Chalder Trudie , Swann Olivia , Ford Tamsin , Heyman Isobel , Segal Terry , Semple Malcolm G. , Rojas Natalia K. , CLoCk Consortium  , Shafran Roz , Stephenson Terence
Published: July 2023

Background: Although 99% of children and young people have been exposed to SARS-CoV-2, the long-term prevalence of post-COVID-19 symptoms in young people is unclear. The aim of this study is to describe symptom profiles 12 months after SARS-CoV-2 testing. Method: A matched cohort study of a national sample of 20,202 children and young people who took a SARS-CoV-2 PCR test between September 2020 and March 2021. Results: 12 months post-index-test, there was a difference in the number of symptoms reported by initial negatives who never tested positive (NN) compared to the other three groups who had at least one positive test (p < 0.001). Similarly, 10.2% of the NN group described five-plus symptoms at 12 months compared to 15.9–24.0% in the other three groups who had at least one positive test. The most common symptoms were tiredness, sleeping difficulties, shortness of breath, and headaches for all four groups. For all these symptoms, the initial test positives with subsequent reports of re-infection had higher prevalences than other positive groups (p < 0.001). Symptom profiles, mental health, well-being, fatigue, and quality of life did not vary by vaccination status. Conclusions: Following the pandemic, many young people, particularly those that have had multiple SARS-CoV-2 positive tests, experience a range of symptoms that warrant consideration and potential investigation and intervention.
Potentiality of Charcoal as a Dendrochronological and Paleoclimatic Archive: Case Study of Archaeological Charcoal from Southeastern Altai, Russia
Authors: Agatova Anna , Nepop Roman , Myglan Vladimir , Barinov Valentin , Tainik Anna , Filatova Maja
Published: July 2023

Archaeological charcoal from ancient nomad iron-smelting furnaces collected in the highland southeastern Russian Altai has great potential as a material for tree ring analysis. Dendrochronological dating was applied to 355 viable samples (>80% of the 448 collected ones), prepared using a new protocol. Individual tree ring series of 155 (~43%) samples were used to construct nine floating chronologies from 76 to 290 rings long. The archaeological and radiocarbon data on charcoal that fueled the hearths of the Kosh-Agach type bracket the floating tree ring chronologies between the second and tenth centuries AD. The results demonstrate that long tree ring “steppe” chronologies can be obtained for intermontane basins in the arid zone of Southern Siberia, using the analysis of charcoal samples. A strong climate signal imprinted in the annual growth of trees allowed for crossdating samples with relatively few rings. The revealed common climate signal for larches from different locations indicates similar paleoclimate conditions of their growth despite the strong modern southeastward aridization trend in the region, which was not so pronounced ca. 1.5 ka ago. The further matching of these chronologies to the calendar timeline will provide reference for the precise comparison of climatic conditions in the floors of intermontane basins and in the flanking mountains.