bluuebunny/crossref_metadata_2025 huggingface dataset:
Secure Image Signal Transmission Scheme Using Poly-Polarization Filtering and Orthogonal Matrix
Authors: Luo Zhangkai , Pei Zhongmin , Yang Chengwei , Liu Zhengjun , Chen Hang
Published: February 2023

In this paper, a novel secure image signal transmission scheme was proposed in wireless systems, in which the poly-polarization filtering and the orthogonal matrix (PPF-OM) were combined to protect the image signal and eliminate the polarization dependent loss (PDL) at the same time, which was caused by the non-ideal wireless channel. This scheme divided the image information sequence into two parts in order to modulate and reshape the results into symbol matrices with the same size. Then, two sets of polarization states (PSs) and orthogonal matrices (OMs) were designed to process the symbols in order to enhance information protection and eliminate the PDL. Legitimate users were able to apply the shared PSs and OMs, step by step, so the information could be recovered. However, for eavesdroppers, the received signals were random symbols that were difficult to demodulate. Then, the bit error rate and the secrecy rate were derived to evaluate the performance of the PPF-OM scheme. Finally, the simulations demonstrated the superior performance of the PPF-OM scheme for enhancing the information security and eliminating the PDL.
Statistical Adaptation Loss Improved SMALL Sample Ship Detection Method Based on an Attention Mechanism and Data Enhancement
Authors: Gao Wei , Liu Yunqing , Zeng Yi , Li Qi , Liu Quanyang
Published: February 2023

Synthetic aperture radar (SAR) imagery is a promising data source for ocean activity detection. Ship target detection based on SAR images is widely used in maritime trade and the military. SAR image data are rare, and the amount of public data is small. For applications of SAR image ship target detection, a model with low data dependence, fast iteration and low training cost is needed. In this paper, the balanced positive and negative data enhancement method was used. Through statistical analysis of the training dataset, similar sea areas in the training set are filled with detection targets with comfortable size features. Increasing the proportion of positive samples in the data helps to improve the model detection effect. The regional attention preadaptation mechanism based on statistical analysis was implemented to extract information, and the scale-adaptive loss was combined to improve the detection accuracy of the model. Using the same data, our model exhibited better performance. When using 30% of the data, our model was stable in terms of accuracy and average precision (AP) and maintained detection results similar to the training results achieved using 100% of the dataset.
Virtual Reality Gaming in Rehabilitation after Musculoskeletal Injury—User Experience Pilot Study
Authors: Gouveia Élvio Rúbio , Campos Pedro , França Cristiano S. , Rodrigues Louis M. , Martins Francisco , França Cíntia , Gonçalves Frederica , Teixeira Fernando , Ihle Andreas , Gouveia Bruna R.
Published: February 2023

The purposes of this study were twofold: (1) to describe a new technological solution for the rehabilitation of musculoskeletal injuries based on virtual reality (VR) gaming, and (2) to analyze the variation in rated perceived exertion (RPE) and heart rate (HR) of the participants when undergoing a rehabilitation session based on different VR games. Thirty-seven participants aged 23.7 ± 7.0 years tested during five customized VR games to provide a complete rehabilitation session after a musculoskeletal injury. The results of the Friedman test indicated a statistically significant difference in RPE scale and HR across the five VR games throughout a complete rehabilitation session (χ2 (4, n = 35) = 75.59; p < 0.001 and χ2 (4, n = 35) = 27.75, p < 0.001, respectively). RPE and HR increased significantly from Game 1 to Game 2 (z = −5.16, p < 0.001), from Game 1 to Game 3 (z = −5.05, p < 0.001), from Game 1 to Game 4 (z = −4.87, p < 0.001), and from Game 1 to Game 5 (z = −3.61, p < 0.001). Moreover, the results showed a high perceived usability of the system, greater intrinsic motivation to perform the rehabilitation exercises, a high level of immersion, and a good experience in the VR gaming environment. Our study stimulates extended intervention programs following-up on this immersive virtual reality rehabilitation system to support soccer players recovering from musculoskeletal injuries.
Ultra-High-Cycle Fatigue Life Prediction of Metallic Materials Based on Machine Learning
Authors: Zhang Xuze , Liu Fang , Shen Min , Han Donggui , Wang Zilong , Yan Nu
Published: February 2023

The fatigue life evaluation of metallic materials plays an important role in ensuring the safety and long service life of metal structures. To further improve the accuracy and efficiency of the ultra-high-cycle fatigue life prediction of metallic materials, a new prediction method using machine learning was proposed. The training database contained the ultra-high-cycle fatigue life of different metallic materials obtained from fatigue tests, and two fatigue life prediction models were constructed based on the gradient boosting (GB) and random forest (RF) algorithms. The mean square error and the coefficient of determination were applied to evaluate the performance of the two models, and their advantages and application scenarios were also discussed. The ultra-high-cycle fatigue life of GCr15 bearing steel was predicted by the constructed models. It was found that only one datapoint of the GB model exceeded the triple error band, and the RF model had higher stability. The network model coefficient of determination and mean square error for the GB and RF models were 0.78, 0.79 and 0.69, 3.79, respectively. Both models could predict the ultra-high-cycle fatigue life of metallic materials quickly and effectively.
Development of Novel Electrochemical Biosensors Based on Horseradish Peroxidase for the Detection of Caffeic Acid
Authors: Trifan Andra Georgiana , Apetrei Irina Mirela
Published: February 2023

In this study, biosensors based on two types of screen-printed carbon and Prussian blue-carbon electrodes, respectively, modified with peroxidase extracted from horseradish root for the sensitive and selective detection of caffeic acid were developed. The presence of the enzyme in the aqueous extract and the activity of peroxidase was demonstrated by spectrometric methods. The electrochemical technique used for the determination of caffeic acid with the biosensors was the cyclic voltammetry. Calibration of the biosensors towards caffeic acid was carried out in solutions of different concentrations, ranging from 5 to 74 μM. Suitable sensitivities and detection limits for practical applications were obtained, with the more sensitive (0.72 μA·μM−1) one being the biosensor containing Prussian blue as a mediator of the exchange between electrons with a detection limit of 0.9 μM. Caffeic acid was successfully determined and quantified in three food supplements using the Prussian blue-peroxidase-based biosensor. The method used to validate the results obtained with the biosensor in the food supplements was a comparison with the amounts indicated by the producers, with no differences between the results at a 99% confidence level.
Experimental Methods to Evaluate the Carbonation Degree in Concrete—State of the Art Review
Authors: Bui Huyen , Delattre Francois , Levacher Daniel
Published: February 2023

The carbonation action in concrete, in which carbonation reactions transform calcium hydroxide into calcium carbonate, is considered as a multi-phase physico-chemical process. Generally, carbonation in the cementitious composites has negative effects on the protection of reinforced bars due to the accelerated corrosion problem. The investigation of the carbonation degree is, therefore, necessary to evaluate the carbonation influence on the reinforced cementitious composites. In the present paper, experimental techniques to measure the carbonation degree in concrete are reviewed, including both qualitative and quantitative methods. It should be noted that, while qualitative technique focuses on the alterations in the concrete pore solution alkalinity which reflects the carbonation depth through the pH indicator, most quantitative methods could provide accurate determination of the CO2 penetration capacity during the carbonation process. The method used, for the practical phase, depends on the purpose of the carbonation degree measurement.
Optimizing the Parameters of Long Short-Term Memory Networks Using the Bees Algorithm
Authors: Alamri Nawaf Mohammad H. , Packianather Michael , Bigot Samuel
Published: February 2023

Improving the performance of Deep Learning (DL) algorithms is a challenging problem. However, DL is applied to different types of Deep Neural Networks, and Long Short-Term Memory (LSTM) is one of them that deals with time series or sequential data. This paper attempts to overcome this problem by optimizing LSTM parameters using the Bees Algorithm (BA), which is a nature-inspired algorithm that mimics the foraging behavior of honey bees. In particular, it was used to optimize the adjustment factors of the learning rate in the forget, input, and output gates, in addition to cell candidate, in both forward and backward sides. Furthermore, the BA was used to optimize the learning rate factor in the fully connected layer. In this study, artificial porosity images were used for testing the algorithms; since the input data were images, a Convolutional Neural Network (CNN) was added in order to extract the features in the images to feed into the LSTM for predicting the percentage of porosity in the sequential layers of artificial porosity images that mimic real CT scan images of products manufactured by the Selective Laser Melting (SLM) process. Applying a Convolutional Neural Network Long Short-Term Memory (CNN-LSTM) yielded a porosity prediction accuracy of 93.17%. Although using Bayesian Optimization (BO) to optimize the LSTM parameters mentioned previously did not improve the performance of the LSTM, as the prediction accuracy was 93%, adding the BA to optimize the same LSTM parameters did improve its performance in predicting the porosity, with an accuracy of 95.17% where a hybrid Bees Algorithm Convolutional Neural Network Long Short-Term Memory (BA-CNN-LSTM) was used. Furthermore, the hybrid BA-CNN-LSTM algorithm was capable of dealing with classification problems as well. This was shown by applying it to Electrocardiogram (ECG) benchmark images, which improved the test set classification accuracy, which was 92.50% for the CNN-LSTM algorithm and 95% for both the BO-CNN-LSTM and BA-CNN-LSTM algorithms. In addition, the turbofan engine degradation simulation numerical dataset was used to predict the Remaining Useful Life (RUL) of the engines using the LSTM network. A CNN was not needed in this case, as there was no feature extraction for the images. However, adding the BA to optimize the LSTM parameters improved the prediction accuracy in the testing set for the LSTM and BO-LSTM, which increased from 74% to 77% for the hybrid BA-LSTM algorithm.
A Study on the Optimization of the Louver Fin Heat Exchanger for Fuel Cell Electric Vehicle Using Genetic Algorithm
Authors: Kwon Hyeok , Park Sungyoung , Choi Jaeho , Han Jaeyoung
Published: February 2023

Fuel cell electric vehicles offer a short fuel charging time and high mileage, but require precise thermal management technology to ensure the durability and efficiency of the stack. Accordingly, the size and weight of the heat exchanger increase to ensure the performance of the heat exchanger. For this reason, a louver fin type heat exchanger requires optimal size and weight, as well as high performance. This paper optimally designs high-performance heat exchangers with reduced size and weight by applying genetic algorithms to solve this problem. The optimal result value was achieved by optimizing the design variables using concentrated variable modeling and a genetic algorithm, and the dynamic characteristics of the heat exchanger were analyzed by applying the driving cycle of the vehicle. In addition, 3D modeling was conducted to present the weight and practically applicable form. As a result, compared to the existing model, the heat transfer rate and effectiveness were improved by 5% and 1.6%, respectively, and the weight was also reduced by 5.8%. These results exceed the expected performance improvements of low size and weight. Moreover, it is expected that an improved heat exchanger optimization, as well as a design reflecting a drive cycle, could be conducted using the proposed genetic algorithm and be applied not only to a heat exchanger, but also to various components.
Influence of Dielectric Plate Parameters on the Reflection Coefficient of a Planar Aperture Antenna
Authors: Mandrić Vanja , Rupčić Slavko , Rimac-Drlje Snježana , Baxhaku Ismail
Published: February 2023

In this article, an aperture antenna excited by a waveguide with a circular cross-section and covered with a dielectric plate was analyzed via simulation calculation and verified via measurements. The influence of the geometrical and electromagnetic parameters of the dielectric plate on the reflection coefficient S11 of the antenna opening was systematically analyzed. The geometrical parameters taken in this analysis are the thickness d and the width/length h1/h2 of the dielectric plate. The electromagnetic parameters used in this analysis are the real and the imaginary part of permittivity (εr, tan δ) and the electrical conductivity of the dielectric plate (σ). The simulation calculation and analysis included other structural and electromagnetic parameters of the dielectric plate (density of the radome material, relative permeability, and magnetic loss tangent (ρ, µr, and tan δµ, respectively)), but the results show that in the range of real values of these parameters for the materials used for the dielectric plate, they had no significant influence on the reflection coefficient. The results show that impedance-matched antennas with very low values of the reflection coefficients S11 at the resonant frequency can be realized by changing the geometrical and electromagnetic parameters of the dielectric plate material. The results are presented for a circular aperture antenna on a planar grounded plane with a dielectric plate on the opening, and the achieved lowest values of the S11 parameter were −45.17 dB (simulated) and −43.93 dB (measured) at the frequencies of 1.7820 GHz and 1.7550 GHz, respectively. The estimated values of the dielectric plate parameters in this case are thickness d = 11.08 mm (0.67 λ); width × length of grounded plane and dielectric plate h1 × h2 = 423 × 450 mm2 (2.51 × 2.67 λ); relative permittivity 2.5, tan δ = 0.09, μr = 1, tan δμ = 0.00, ρ = 1200 kg·m−3; and electrical conductivity σ = 0 S/m. The simulation calculation results were verified by measuring the reflection coefficient S11 on the created laboratory model of the aperture antenna with the dielectric plate and showed a very good match.
Damage Diagnosis of Frame Structure Based on Convolutional Neural Network with SE-Res2Net Module
Authors: Fu Wenmei , Liu Zhiqiang , Cai Chaozhi , Xue Yingfang , Ren Jianhua
Published: February 2023

The complex application environments of frame structures and the similar vibration signals between different locations make it difficult to accurately diagnose damage using traditional methods. Based on modifying the parameters and configuration of the convolution neural network with training interference (TICNN), this paper proposes a new model for damage diagnosis of frame structures by implanting a squeeze-and-excitation neural network (SENet) and Res2Net modules. Taking the frame structure model from the University of British Columbia as the research object, the proposed damage diagnosis model was used to diagnose its damage type. The proposed new model was compared with other models in terms of accuracy and anti-noise ability. The experimental results show that the accuracy of the proposed model was 99.44% when the training epoch was 30 and 99.78% when training epoch was 100. It is superior to other similar models in terms of convergence speed and accuracy. At the same time, the proposed model also has an excellent advantage in anti-noise ability. Therefore, the proposed damage diagnosis model has the advantages of fast convergence and higher damage diagnosis accuracy under a strong noise environment. It can realize the accurate damage diagnosis of structural frames.
A Study on the Improvement of Filter Performance to Remove Indoor Air Pollution
Authors: Kim Yong-Sun , Kim Hong-Gun , Kwac Lee-Ku , Ko Sang-Cheol
Published: February 2023

This study carried out a simplified baffle filter shape study on the over the range (OTR) filter used in a general kitchen. In order to improve the filter’s efficiency, the simulation was performed using ANSYS FLUENT and COMSOL Multiphysics, and a wind tunnel test apparatus was manufactured to minimize the error rate of dust collection efficiency in the experiment. In the case of a physical filter, it was confirmed through a theoretical review that dust is collected in the filter by the inertial collision method, and the flow velocity must be increased to increase the dust collection efficiency. To increase the flow velocity and increase the filter contact area, the use of sub-filters and the Coanda effect was proposed and simulated. When only the Coanda effect was applied, the collection efficiency increased by about 7–15% compared to the original filter, and when the three types of sub-filters were proposed, and among them, a circular sub-filter was applied, it increased by 25%. When applying the sub-filter and the Coanda effect at the same time, it was confirmed that the sub-filter was more efficient than the Coanda effect. However, in the case of a physical filter, since it cannot collect particles less than PM2.5, the electric dust collection method was proposed and a simulation was conducted. The possibility of removing ultrafine dust below PM2.5 was secured by using an electric dust-collection filter simulation, and it is expected that the reliability will be secured by using experimental devices and products in the future.
Essential Oils and Bacteriocin-Based Active Edible Coating: An Innovative, Natural and Sustainable Approach for the Control of Listeria monocytogenes in Seafoods
Authors: Iseppi Ramona , Camellini Stefania , Zurlini Chiara , Cigognini Ilaria Maria , Cannavacciuolo Mariarosaria , Messi Patrizia
Published: February 2023

The anti-Listeria monocytogenes activity of four essential oils (EOs) (Salvia officinalis, Citrus limon, Mentha piperita and Thymus vulgaris) and bacteriocin bacLP17, added alone or in mixture in active edible coatings, was determined in artificially contaminated shrimps. The minimal inhibitory concentration (MIC) values of the EOs were determined against the NCTC 10888 strain of L. monocytogenes by using the broth microdilution method. The checkerboard method was carried out in tryptic soy broth (TSB), using microdilution to obtain the Fractional Inhibitory Concentration Index (FIC-Index) for six associations of EOs, chosen based on the best MIC results. All the EOs confirmed their anti-Listeria activity, both “in vitro” and inside the coatings. The coating matrix was suitable for use in the food field, allowing a gradual release of the EOs in packaged food. When the EOs were used in association (EO/EO) they were demonstrated to act synergistically, leading to a significant reduction in the amount (10–20 times) of EOs needing to be used, and consequently a decrease in the strong smell on the food. This effect was also confirmed when the compounds were incorporated into the coatings. The inclusion of the EOs within the coating not only ensured the anti-Listeria activity by increasing the shelf-life of food products, but also further mitigated the strong smell of the EOs, improving the organoleptic impact on the food and its sensory properties.
Basic Properties for Certain Subclasses of Meromorphic p-Valent Functions with Connected q-Analogue of Linear Differential Operator
Authors: El-Deeb Sheza M. , Cotîrlă Luminiţa-Ioana
Published: February 2023

In this paper, we define three subclasses Mp,αn,q(η,A,B),Ip,αn(λ,μ,γ),, Rpn,q(λ,μ,γ) connected with a q-analogue of linear differential operator Dα,p,Gn,q which consist of functions F of the form F(ζ)=ζ−p+∑j=1−p∞ajζj(p∈N) satisfying the subordination condition p−1ηζDα,p,Gn,qF(ζ)′Dα,p,Gn,qF(ζ)+p≺p1+Aζ1+Bζ.Also, we study the various properties and characteristics of this subclass Mp,αn,q,∗(η,A,B) such as coefficients estimate, distortion bounds and convex family. Also the concept of δneighborhoods and partial sums of analytic functions to the class Mp,αn,q(η,A,B).
COVID-19 Classification through Deep Learning Models with Three-Channel Grayscale CT Images
Authors: Sufian Maisarah Mohd , Moung Ervin Gubin , Hijazi Mohd Hanafi Ahmad , Yahya Farashazillah , Dargham Jamal Ahmad , Farzamnia Ali , Sia Florence , Mohd Naim Nur Faraha
Published: February 2023

COVID-19, an infectious coronavirus disease, has triggered a pandemic that has claimed many lives. Clinical institutes have long considered computed tomography (CT) as an excellent and complementary screening method to reverse transcriptase-polymerase chain reaction (RT-PCR). Because of the limited dataset available on COVID-19, transfer learning-based models have become the go-to solutions for automatic COVID-19 detection. However, CT images are typically provided in grayscale, thus posing a challenge for automatic detection using pre-trained models, which were previously trained on RGB images. Several methods have been proposed in the literature for converting grayscale images to RGB (three-channel) images for use with pre-trained deep-learning models, such as pseudo-colorization, replication, and colorization. The most common method is replication, where the one-channel grayscale image is repeated in the three-channel image. While this technique is simple, it does not provide new information and can lead to poor performance due to redundant image features fed into the DL model. This study proposes a novel image pre-processing method for grayscale medical images that utilize Histogram Equalization (HE) and Contrast Limited Adaptive Histogram Equalization (CLAHE) to create a three-channel image representation that provides different information on each channel. The effectiveness of this method is evaluated using six other pre-trained models, including InceptionV3, MobileNet, ResNet50, VGG16, ViT-B16, and ViT-B32. The results show that the proposed image representation significantly improves the classification performance of the models, with the InceptionV3 model achieving an accuracy of 99.60% and a recall (also referred as sensitivity) of 99.59%. The proposed method addresses the limitation of using grayscale medical images for COVID-19 detection and can potentially improve the early detection and control of the disease. Additionally, the proposed method can be applied to other medical imaging tasks with a grayscale image input, thus making it a generalizable solution.
Whole-Body Vibration Training on Oxidative Stress Markers, Irisin Levels, and Body Composition in Women with Fibromyalgia: A Randomized Controlled Trial
Authors: dos Santos Jousielle Márcia , Taiar Redha , Ribeiro Vanessa Gonçalves César , da Silva Lage Vanessa Kelly , Scheidt Figueiredo Pedro Henrique , Costa Henrique Silveira , Pereira Lima Vanessa , Sañudo Borja , Bernardo-Filho Mário , Sá-Caputo Danúbia da Cunha de , Dias Peixoto Marco Fabrício , Mendonça Vanessa Amaral , Rapin Amandine , Lacerda Ana Cristina Rodrigues
Published: February 2023

(1) Background: Mitochondrial dysfunction and redox imbalance seem to be involved in fibromyalgia (FM) pathogenesis. The results of our previous studies suggest that whole-body vibration training (WBVT) would improve redox status markers, increase blood irisin levels, and ameliorate the body composition of women with FM. (2) Objective: The current study aimed to investigate WBVT on oxidative stress markers, plasma irisin levels, and body composition in women with FM. (3) Methods: Forty women with FM were randomized into WBVT or untrained (UN) groups. Before and after 6 weeks of WBVT, body composition was assessed by dual-energy radiological absorptiometry (DXA), and inflammatory marker activities were measured by enzymatic assay. (4) Results: Body composition, blood irisin levels, and oxidative stress markers were similar between UN and WBVT groups before the intervention. After 6 weeks of intervention, the WBVT group presented higher irisin levels (WBVT: 316.98 ± 109.24 mg·dL³, WBVT: 477.61 ± 267.92 mg·dL³, p = 0.01) and lower TBARS levels (UN: 0.39 ± 0.02 nmol MDA/mg protein, WBVT: 0.24 ± 0.06 nmol MDA/mg protein, p = 0.001) and visceral adipose tissue mass (UN: 1.37 ± 0.49 kg, WBVT: 0.69 ± 0.54 kg, p = 0.001) compared to the UN group. (5) Conclusions: Six weeks of WBVT improves blood redox status markers, increases irisin levels, and reduces visceral adipose tissue mass, favoring less cell damage and more outstanding oxidative balance in women with FM.
Curcumin Release from Biomaterials for Enhanced Tissue Regeneration Following Injury or Disease
Authors: Hamilton Adelle E. , Gilbert Ryan J.
Published: February 2023

Curcumin, a bioactive phenol derived from turmeric, is an antioxidant, anti-inflammatory, and antibacterial molecule. Although curcumin exhibits beneficial effects in its innate form, it is highly hydrophobic, which leads to poor water solubility and, consequently, low bioavailability. The lack of bioavailability limits curcumin’s effectiveness as a treatment and restricts its use in clinical applications. Furthermore, to achieve beneficial, clinically relevant results, high doses of curcumin are required for systemic administration. Many researchers have utilized biomaterial carriers, including electrospun fibers, nanoparticles, hydrogels, and composite scaffolds, to overcome curcumin’s principle therapeutic limitation of low bioavailability. By using biomaterials to deliver curcumin directly to injury sites, researchers have harnessed the beneficial natural properties of curcumin while providing scaffolding to support tissue regeneration. This review will provide an in-depth overview of the literature that utilizes biomaterial delivery of curcumin for tissue regeneration in injury and disease models.
Changes in Community Composition and Functional Traits of Bumblebees in an Alpine Ecosystem Relate to Climate Warming
Authors: Scharnhorst Victor Sebastian , Thierolf Katharina , Neumayer Johann , Becsi Benedikt , Formayer Herbert , Lanner Julia , Ockermüller Esther , Mirwald Alina , König Barbara , Kriechbaum Monika , Meimberg Harald , Meyer Philipp , Rupprecht Christina , Pachinger Bärbel
Published: February 2023

Climate warming has been observed as the main cause of changes in diversity, community composition, and spatial distribution of different plant and invertebrate species. Due to even stronger warming compared to the global mean, bumblebees in alpine ecosystems are particularly exposed to these changes. To investigate the effects of climate warming, we sampled bumblebees along an elevational gradient, compared the records with data from 1935 and 1936, and related our results to climate models. We found that bumblebee community composition differed significantly between sampling periods and that increasing temperatures in spring were the most plausible factor explaining these range shifts. In addition, species diversity estimates were significantly lower compared to historical records. The number of socio-parasitic species was significantly higher in the historical communities, while recent communities showed increases in climate generalists and forest species at lower elevations. Nevertheless, no significant changes in community-weighted means of a species temperature index (STI) or the number of cold-adapted species were detected, likely due to the historical data resolution. We conclude that the composition and functionality of bumblebee communities in the study area have been significantly affected by climate warming, with changes in land use and vegetation cover likely playing an additional important role.
Schizophrenia Animal Modeling with Epidermal Growth Factor and Its Homologs: Their Connections to the Inflammatory Pathway and the Dopamine System
Authors: Sotoyama Hidekazu , Namba Hisaaki , Tohmi Manavu , Nawa Hiroyuki
Published: February 2023

Epidermal growth factor (EGF) and its homologs, such as neuregulins, bind to ErbB (Her) receptor kinases and regulate glial differentiation and dopaminergic/GABAergic maturation in the brain and are therefore implicated in schizophrenia neuropathology involving these cell abnormalities. In this review, we summarize the biological activities of the EGF family and its neuropathologic association with schizophrenia, mainly overviewing our previous model studies and the related articles. Transgenic mice as well as the rat/monkey models established by perinatal challenges of EGF or its homologs consistently exhibit various behavioral endophenotypes relevant to schizophrenia. In particular, post-pubertal elevation in baseline dopaminergic activity may illustrate the abnormal behaviors relevant to positive and negative symptoms as well as to the timing of this behavioral onset. With the given molecular interaction and transactivation of ErbB receptor kinases with Toll-like receptors (TLRs), EGF/ErbB signals are recruited by viral infection and inflammatory diseases such as COVID-19-mediated pneumonia and poxvirus-mediated fibroma and implicated in the immune–inflammatory hypothesis of schizophrenia. Finally, we also discuss the interaction of clozapine with ErbB receptor kinases as well as new antipsychotic development targeting these receptors.
Metabolic Activation of PARP as a SARS-CoV-2 Therapeutic Target—Is It a Bait for the Virus or the Best Deal We Could Ever Make with the Virus? Is AMBICA the Potential Cure?
Authors: Puthanveetil Prasanth
Published: February 2023

The COVID-19 pandemic has had a great impact on global health and is an economic burden. Even with vaccines and anti-viral medications we are still scrambling to get a balance. In this perspective, we have shed light upon an extremely feasible approach by which we can control the SARS-CoV-2 infection and the associated complications, bringing some solace to this ongoing turmoil. We are providing some insights regarding an ideal agent which could prevent SARS-CoV-2 multiplication. If we could identify an agent which is an activator of metabolism and is also bioactive, we could prevent corona activation (AMBICA). Some naturally occurring lipid molecules best fit this identity as an agent which has the capacity to replenish our host cells, specifically immune cells, with ATP. It could also act as a source for providing a substrate for host cell PARP family members for MARylation and PARylation processes, leading to manipulation of the viral macro domain function, resulting in curbing the virulence and propagation of SARS-CoV-2. Identification of the right lipid molecule or combination of lipid molecules will fulfill the criteria. This perspective has focused on a unique angle of host-pathogen interaction and will open up a new dimension in treating COVID-19 infection.
Progression of Thoracic Aortic Dissection Is Aggravated by the hsa_circ_0007386/miR-1271-5P/IGF1R/AKT Axis via Induction of Arterial Smooth Muscle Cell Apoptosis
Authors: Xie Xinsheng , Hong Xiang , Hong Shichai , Huang Yulong , Chen Gang , Chen Yihui , Lin Yue , Lu Weifeng , Fu Weiguo , Wang Lixin
Published: February 2023

Background: The molecular mechanisms associated with thoracic aortic dissection (TAD) remain poorly understood. A comprehensive high-throughput sequencing-based analysis of the circRNA–miRNA–mRNA competitive endogenous RNA (ceRNA) regulatory network in TAD has not been conducted. The purpose of this study is to identify and verify the key ceRNA networks which may have crucial biological functions in the pathogenesis of TAD. Methods: Gene expression profiles of the GSE97745, GSE98770, and GSE52093 datasets were acquired from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified using the GEO2R tools. Protein–protein interaction (PPI) networks of the hub genes were constructed using STRING; the hub genes and modules were identified by MCODE and CytoHubba plugins of the Cytoscape. We analyzed the hub genes using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. The functions of these hub genes were assessed using Cytoscape software. Our data—along with data from GSE97745, GSE98770, and GSE52093—were used to verify the findings. Results: Upon combined biological prediction, a total of 11 ce-circRNAs, 11 ce-miRNAs, and 26 ce-mRNAs were screened to construct a circRNA–miRNA–mRNA ceRNA network. PPI network and module analysis identified four hub nodes, including IGF1R, JAK2, CSF1, and GAB1. Genes associated with the Ras and PI3K-Akt signaling pathways were clustered in the four hub node modules in TAD. The node degrees were most significant for IGF1R, which were also the most significant in the two modules (up module and hub module). IGF1R was selected as a key gene, and the hsa_circ_0007386/miR-1271–5P/IGF1R/AKT regulatory axis was established. The relative expression levels of the regulatory axis members were confirmed by RT-PCR in 12 samples, including TAD tissues and normal tissues. Downregulation of IGF1R expression in smooth muscle cells (SMCs) was found to induce apoptosis by regulating the AKT levels. In addition, IGF1R showed high diagnostic efficacy in both AD tissue and blood samples. Conclusions: The hsa_circ_0007386/miR-1271-5P/IGF1R/AKT axis may aggravate the progression of TAD by inducing VSMCs apoptosis. CeRNA networks could provide new insights into the underlying molecular mechanisms of TAD. In addition, IGF1R showed high diagnostic efficacy in both tissue and plasma samples in TAD, which can be considered as a diagnostic marker for TAD.
Brain Degeneration in Synucleinopathies Based on Analysis of Cognition and Other Nonmotor Features: A Multimodal Imaging Study
Authors: Lucas-Jiménez Olaia , Ibarretxe-Bilbao Naroa , Diez Ibai , Peña Javier , Tijero Beatriz , Galdós Marta , Murueta-Goyena Ane , Del Pino Rocío , Acera Marian , Gómez-Esteban Juan Carlos , Gabilondo Iñigo , Ojeda Natalia
Published: February 2023

Background: We aimed to characterize subtypes of synucleinopathies using a clustering approach based on cognitive and other nonmotor data and to explore structural and functional magnetic resonance imaging (MRI) brain differences between identified clusters. Methods: Sixty-two patients (n = 6 E46K-SNCA, n = 8 dementia with Lewy bodies (DLB) and n = 48 idiopathic Parkinson’s disease (PD)) and 37 normal controls underwent nonmotor evaluation with extensive cognitive assessment. Hierarchical cluster analysis (HCA) was performed on patients’ samples based on nonmotor variables. T1, diffusion-weighted, and resting-state functional MRI data were acquired. Whole-brain comparisons were performed. Results: HCA revealed two subtypes, the mild subtype (n = 29) and the severe subtype (n = 33). The mild subtype patients were slightly impaired in some nonmotor domains (fatigue, depression, olfaction, and orthostatic hypotension) with no detectable cognitive impairment; the severe subtype patients (PD patients, all DLB, and the symptomatic E46K-SNCA carriers) were severely impaired in motor and nonmotor domains with marked cognitive, visual and bradykinesia alterations. Multimodal MRI analyses suggested that the severe subtype exhibits widespread brain alterations in both structure and function, whereas the mild subtype shows relatively mild disruptions in occipital brain structure and function. Conclusions: These findings support the potential value of incorporating an extensive nonmotor evaluation to characterize specific clinical patterns and brain degeneration patterns of synucleinopathies.
Could Long Non-Coding RNA MEG3 and PTENP1 Interact with miR-21 in the Pathogenesis of Non-Alcoholic Fatty Liver Disease?
Authors: Erdem Mustafa Genco , Unlu Ozge , Demirci Mehmet
Published: February 2023

NAFLD is the most common cause of chronic liver disease worldwide. The miRNAs and lncRNAs are important endogenous ncRNAs families that can regulate molecular mechanisms. The aim of this study was to analyze the miRNA and lncRNA expression profiles in serum samples of NAFLD patients with different types of hepatosteatosis compared to healthy controls by the qPCR method. A total of180 NAFLD patients and 60 healthy controls were included. miRCURY LNA miRNA miRNome PCR human panel I + II kit and LncProfiler qPCR Array Kit were used to detect miRNA and lncRNA expression, respectively. DIANA miRPath and DIANA-lncBase web servers were used for interaction analysis. As a result, 75 miRNA and 24 lncRNA expression changes were determined. For miRNAs and lncRNAs, 30 and 5 were downregulated and 45 and 19 were upregulated, respectively. hsa-miR-21 was upregulated 2-fold whereas miR-197 was downregulated 0.25-fold. Among lncRNAs, NEAT1 was upregulated 2.9-fold while lncRNA MEG3 was downregulated 0.41-fold. A weak correlation was found between hsa-miR-122 and lncRNA MALAT1. As a conclusion, it is clear that lncRNA–miRNA interaction is involved in the molecular mechanisms of the emergence of NAFLD. The lncRNAs MEG3 and PTENP1 interacted with hsa-miR-21. It was thought that this interaction should be investigated as a biomarker for the development of NAFLD.
Spacer-Supported Thermal Ablation to Prevent Carbonisation and Improve Ablation Size: A Proof of Concept Study
Authors: Mankertz Fiona , Gemeinhardt Ole , Felbor Ute , Hadlich Stefan , Hosten Norbert
Published: February 2023

Thermal ablation offers a minimally invasive alternative in the treatment of hepatic tumours. Several types of ablation are utilised with different methods and indications. However, to this day, ablation size remains limited due to the formation of a central non-conductive boundary layer. In thermal ablation, this boundary layer is formed by carbonisation. Our goal was to prevent or delay carbonisation, and subsequently increase ablation size. We used bovine liver to compare ablation diameter and volume, created by a stand-alone laser applicator, with those created when utilising a spacer between laser applicator and hepatic tissue. Two spacer variants were developed: one with a closed circulation of cooling fluid and one with an open circulation into hepatic tissue. We found that the presence of a spacer significantly increased ablation volume up to 75.3 cm3, an increase of a factor of 3.19 (closed spacer) and 3.02 (open spacer) when compared to the stand-alone applicator. Statistical significance between spacer variants was also present, with the closed spacer producing a significantly larger ablation volume (p < 0.001, MDiff = 3.053, 95% CI[1.612, 4.493]) and diameter (p < 0.001, MDiff = 4.467, 95% CI[2.648, 6.285]) than the open spacer. We conclude that the presence of a spacer has the potential to increase ablation size.
Association of Antihistamine Use with Increased Risk of Esophageal Squamous Cell Carcinoma: A Nationwide, Long-Term Follow-Up Study Using Propensity Score Matching
Authors: Peng Jhao-Yang , Yu Ying-Hui , Chen Wan-Ming , Shia Ben-Chang , Chen Mingchih , Wu Szu-Yuan
Published: February 2023

Esophageal cancer is a common and aggressive cancer, with a five-year survival rate of approximately 20%. Therefore, identifying safe and effective medications that can reduce the risk of esophageal cancer is of great importance. Objective: To examine the association between H1-antihistamines (AHs) use and the incidence of esophageal squamous cell carcinoma (ESCC) in a head-to-head propensity score matching (PSM) comparative study. Design: Retrospective cohort study. Setting: Nationwide population-based study in Taiwan. Participants: 1289,526 adults from the National Health Insurance Research Database from 2008 to 2018. Exposures: AH use. Main Outcomes and Measures: Incidence rates (IRs), incidence rate ratios (IRRs), and adjusted hazard ratios (aHRs) of ESCC in AH users compared with nonusers. Results: AH users had a significantly higher IR of ESCC than nonusers (1.47 vs. 1.36 per 100,000 person-years). The IRR (95% CI) for ESCC was 1.18 (1.08–1.28) in AH users compared with nonusers. After adjustment for age, sex, income levels, urbanization, cigarettes smoking, alcoholic related diseases, comorbidities, medication use, and Charlson Comorbidity Index scores, the aHR (95% CI) for ESCC was 1.22 (1.12–1.33) in AH users compared with nonusers. A dose–response relationship was also observed, with aHRs for AH use at 28–182, 183–488, 489–1043, and >1043 cumulative defined daily doses (cDDDs) of 1.12, 1.20, 1.25, and 1.37, respectively, compared with <28 cDDDs. Conclusions and Relevance: Our study found a significant association between AH use and the increased risk of ESCC, with a dose–response relationship. This study suggests that AH use may increase the risk of ESCC, especially at high doses, and highlights the importance of caution when prescribing AHs.
Antitumor Potential of Antiepileptic Drugs in Human Glioblastoma: Pharmacological Targets and Clinical Benefits
Authors: Stella Manuela , Baiardi Giammarco , Pasquariello Stefano , Sacco Fabio , Dellacasagrande Irene , Corsaro Alessandro , Mattioli Francesca , Barbieri Federica
Published: February 2023

Glioblastoma (GBM) is characterized by fast-growing cells, genetic and phenotypic heterogeneity, and radio-chemo-therapy resistance, contributing to its dismal prognosis. Various medical comorbidities are associated with the natural history of GBM. The most disabling and greatly affecting patients’ quality of life are neurodegeneration, cognitive impairment, and GBM-related epilepsy (GRE). Hallmarks of GBM include molecular intrinsic mediators and pathways, but emerging evidence supports the key role of non-malignant cells within the tumor microenvironment in GBM aggressive behavior. In this context, hyper-excitability of neurons, mediated by glutamatergic and GABAergic imbalance, contributing to GBM growth strengthens the cancer-nervous system crosstalk. Pathogenic mechanisms, clinical features, and pharmacological management of GRE with antiepileptic drugs (AEDs) and their interactions are poorly explored, yet it is a potentially promising field of research in cancer neuroscience. The present review summarizes emerging cooperative mechanisms in oncogenesis and epileptogenesis, focusing on the neuron-to-glioma interface. The main effects and efficacy of selected AEDs used in the management of GRE are discussed in this paper, as well as their potential beneficial activity as antitumor treatment. Overall, although still many unclear processes overlapping in GBM growth and seizure onset need to be elucidated, this review focuses on the intriguing targeting of GBM-neuron mutual interactions to improve the outcome of the so challenging to treat GBM.
The Serum Brain-Derived Neurotrophic Factor Increases in Serotonin Reuptake Inhibitor Responders Patients with First-Episode, Drug-Naïve Major Depression
Authors: Yoshimura Reiji , Okamoto Naomichi , Chibaatar Enkmurun , Natsuyama Tomoya , Ikenouchi Atsuko
Published: February 2023

Brain-derived neurotrophic factor (BDNF) is a growth factor synthesized in the cell bodies of neurons and glia, which affects neuronal maturation, the survival of nervous system, and synaptic plasticity. BDNF play an important role in the pathophysiology of major depression (MD). The serum BDNF levels changed over time, or with the improvement in depressive symptoms. However, the change of serum BDNF during pharmacotherapy remains obscure in MDD. In particular, the changes in serum BDNF associated with pharmacotherapy have not yet been fully elucidated. The present study aimed to compare the changes in serum BDNF concentrations in first-episode, drug-naive patients with MD treated with antidepressants between treatment-response and treatment-nonresponse groups. The study included 35 inpatients and outpatients composed of 15 males and 20 females aged 36.7 ± 6.8 years at the Department of Psychiatry of our University Hospital. All patients met the DSM-5 diagnostic criteria for MD. The antidepressants administered included paroxetine, duloxetine, and escitalopram. Severity of depressive state was assessed using the 17-item HAMD before and 8 weeks after drug administration. Responders were defined as those whose total HAMD scores at 8 weeks had decreased by 50% or more compared to those before drug administration, while non-responders were those whose total HAMD scores had decreased by less than 50%. Here we showed that serum BDNF levels were not significantly different at any point between the two groups. The responder group, but not the non-responder group, showed statistically significant changes in serum BDNF 0 and serum BDNF 8. The results suggest that the changes of serum BDNF might differ between the two groups. The measurement of serum BDNF has the potential to be a useful predictor of pharmacotherapy in patients with first-episode, drug-naïve MD.
Spread of the Optical Power Emission of Three Units Each of Two Different Laser Therapy Devices Used in Sports Medicine, Which Cannot Be Assessed by the Users, Shown by Means of High-Fidelity Laser Measurement Technology
Authors: Kaub Leon , Schmitz Christoph
Published: February 2023

Laser therapy devices (LTDs) operating with near-infrared laser light are increasingly being used in sports medicine. For several reasons, users cannot evaluate whether or not such devices emit laser beams according to the specifications provided by the manufacturer and the settings of the device. In this study, the laser beams from two different LTDs that can be used in sports medicine were thoroughly characterized by measuring the emitted power, pulse shapes and lengths and spatial intensity distributions using professional, high-fidelity laser measurement technology. This was repeated for three units of each LDT independently to distinguish problems of individual units from potential intrinsic instrument design errors. The laser beams from the units of one LTD agreed with the settings of the device, with the measured average power for these units being within 3.3% of the set power. In contrast, the laser beams from the units of the other LTD showed large deviations between the settings and the actual emitted light. This device came with three laser diodes that could be used independently and simultaneously. The average power differed greatly between the units as well as between the laser diodes within each unit. Some laser diodes emitted essentially no light, which could lead to a lack of treatment for patients. Other laser diodes emitted much more power than set at the device (up to 230%), which could result in skin irritations or burning of patients. These findings indicate a need for better standardization and consistency of therapeutic laser light sources.