bluuebunny/crossref_metadata_2025 huggingface dataset:
The Reactive Species Interactome in Red Blood Cells: Oxidants, Antioxidants, and Molecular Targets
Authors: Cortese-Krott Miriam M.
Published: September 2023

Beyond their established role as oxygen carriers, red blood cells have recently been found to contribute to systemic NO and sulfide metabolism and act as potent circulating antioxidant cells. Emerging evidence indicates that reactive species derived from the metabolism of O2, NO, and H2S can interact with each other, potentially influencing common biological targets. These interactions have been encompassed in the concept of the reactive species interactome. This review explores the potential application of the concept of reactive species interactome to understand the redox physiology of RBCs. It specifically examines how reactive species are generated and detoxified, their interactions with each other, and their targets. Hemoglobin is a key player in the reactive species interactome within RBCs, given its abundance and fundamental role in O2/CO2 exchange, NO transport/metabolism, and sulfur species binding/production. Future research should focus on understanding how modulation of the reactive species interactome may regulate RBC biology, physiology, and their systemic effects.
Cybersecurity and Medical Imaging: A Simulation-Based Approach to DICOM Communication
Authors: Karagiannis Stylianos , Magkos Emmanouil , Ntantogian Christoforos , Cabecinha Ricardo , Fotis Theofanis
Published: September 2023

Medical imaging plays a crucial role in modern healthcare, providing essential information for accurate diagnosis and treatment planning. The Digital Imaging and Communications in Medicine (DICOM) standard has revolutionized the storage, transmission, and sharing of medical images and related data. Despite its advantages, implementation and deployment of the DICOM protocol often suffers from incomplete understanding, leading to vulnerabilities within the healthcare ecosystem. This research paper presents an implementation of DICOM communication and the development of a practical demonstration for simulation purposes The simulation can be used for conducting cybersecurity tests in the context of DICOM communication. Overall, the simulation provides a digital environment that can help in retrieving valuable insights into the practical aspects of DICOM communication and PACS integration, serving as a valuable resource for medical imaging professionals, researchers, and developers. These research results provide practical insights, and the DICOM simulation can be used in realistic contexts to showcase a variety of security scenarios.
Bayesian Network Demand-Forecasting Model Based on Modified Particle Swarm Optimization
Authors: Hu Shebiao , Li Kun
Published: September 2023

With the increasing variety of products, the increasing substitutability of products, and the trend of customized products, the volatility of market demand is increasing, which poses a challenge to make accurate demand forecasting. The Bayesian method is particularly promising and appealing when the data fluctuate greatly. This paper proposes a product-demand forecasting model based on multilayer Bayesian network, which introduces hidden layer variables and volatility factors to meet the time series connection and volatility of the demand data. However, most studies use sampling methods to estimate the parameters. We use Bayesian maximum a posteriori estimation to estimate the model parameters and introduce an improved particle swarm optimization algorithm (MPSO) to optimize the objective function. In order to increase the diversity of the particle population and accelerate the convergence, an adaptive particle velocity, position updating strategy, and nonlinear changing inertia weight are introduced in the algorithm. Finally, RMSE (Root Mean Square Error) and MAPE (Mean Absolute Percentage Error) are used as the evaluation criterion to conduct experiments on six different datasets, and the experimental results are compared with the results of the ARIMA (autoregressive integrated moving average model) method and PSO algorithm. The experimental results show that the method has a good prediction effect. It provides a new idea for demand forecasting in the supply chain.
Data Element Sharing in Convergence Media Ecology Based on Evolutionary Game
Authors: Hu Hongbin , Wang Yongbin , Song Guohui , Fan Weijian , Liu Chenming
Published: September 2023

As a new factor of production, data element has profoundly changed our mode of production, lifestyle and social governance style. The sharing of a data element in the convergence media ecology can greatly improve the circulation of a data element and enhance the value of a data element; however, it may face problems such as insufficient sharing willingness, incomplete sharing circulation mechanism and inadequate implementation of the incentive mechanism. To solve these problems, this paper introduced the evolutionary game theory in the convergence media ecology and established the data-sharing model according to the characteristics of nodes. We analyzed the ecological node evolution path, evolutionary stable strategy and the corresponding state conditions in the model. Furthermore, we carried out the sampling experiment simulation, which verified the effectiveness of the research content in this paper. At the end of the article, we summarize and give some key factors to increase the willingness to participate in sharing in convergence media ecology. This paper enriched the research field of data element sharing in convergence media and explored the willingness and tendency of the participants. The research results can provide targeted suggestions for promoting the sharing of data elements in convergence media ecology.
A New Influence Mechanism of Clocking Effect in Subsonic Compressor
Authors: Niu Han , Chen Jiang , Xiang Hang
Published: September 2023

This paper investigates the clocking effect in subsonic compressor element stages and the influence of design parameters on the flow mechanism. We focus on the relationship between the wake-induced separation loss and wake mixing loss and the unsteady mechanism in the wake flow process without considering the transition through several steady and unsteady numerical simulations aimed at a series of subsonic compressor element stages. The simulation results indicate that the performance difference at various indexing positions depends on the relationship between wake mixing loss and wake-induced separation loss for different compressor designs and operating conditions. Furthermore, the pressure transport caused by the negative jet of the Stator 0 wake in Rotor 1 creates a local acceleration region called SFAF, and a decrease in its absolute flow angle reduces the Stator 1 separation. Sufficient rim work of the rotor at highly loaded operating conditions is the basis for generating an effective SFAF. Furthermore, the fore-loading blade of Rotor 1 significantly reduces suction surface pressure drop, and a small angle between the stagger angles of Stator 0 and Rotor 1 increases the unsteady rotor load caused by the upstream wake to the total rotor load, both of which enhance SFAF.
Characteristics and Evolution of the Response of the Lower Atmosphere to the Tonga Volcanic Eruption
Authors: Ke Fuyang , Hu Xiangxiang , Hong Guan , Ming Lulu , Song Bao
Published: September 2023

Research concerning the response characteristics of lower atmosphere to volcanic eruption is a key and hot topic in the field of volcanic environment research. Against the background of a submarine volcano in the South Pacific island country of Hunga Tonga–Hunga Ha’apai (HTHH) on 15 January 2022, this paper explores the response characteristics of this volcanic eruption on environmental factors in the lower atmosphere region using a priori data such as ERA5 reanalysis data, water vapor data from GNSS inversion and surface temperature data from Landsat inversion for the Tonga Islands region. Among them, (1) The amount of precipitable water (PWV) in Tonga was abnormally high on 15 January. (2) The water vapor flux was mainly in the lower space below 850 hPa. (3) The average surface temperature in December 2021 was higher. In February 2022, the average surface temperature was lower. (4) There was a low-pressure center near 30° S on the south side of Tonga volcano on 14 January, and a new low-pressure center was formed on the east side of Tonga volcano after the eruption of Tonga volcano on 15 January. Furthermore, the precipitation area of Tonga increased in January and decreased in February 2022. The PWV values, water vapor fluxes, temperature and circulation response characteristics, and precipitation characteristics show that the volcanic eruption affected part of the atmospheric and oceanic circulation, and water vapor was transported to the low-pressure center along the direction of atmospheric circulation. With the continuous water vapor transport, precipitation formed in Tonga, and the intensity and area of precipitation in Tonga increased significantly in January. Thus, the volcanic eruption could have significantly triggered the response between the low-pressure center, PWV, precipitation and surface temperature in the lower atmosphere, which influenced the environmental characteristics of this eruption.
Tamed Warping Network for High-Resolution Semantic Video Segmentation
Authors: Li Songyuan , Feng Junyi , Li Xi
Published: September 2023

Recent approaches for fast semantic video segmentation have reduced redundancy by warping feature maps across adjacent frames, greatly speeding up the inference phase. However, the accuracy drops seriously owing to the errors incurred by warping. In this paper, we propose a novel framework and design a simple and effective correction stage after warping. Specifically, we build a non-key-frame CNN, fusing warped context features with current spatial details. Based on the feature fusion, our context feature rectification (CFR) module learns the model’s difference from a per-frame model to correct the warped features. Furthermore, our residual-guided attention (RGA) module utilizes the residual maps in the compressed domain to help CRF focus on error-prone regions. Results on Cityscapes show that the accuracy significantly increases from 67.3% to 71.6%, and the speed edges down from 65.5 FPS to 61.8 FPS at a resolution of 1024×2048. For non-rigid categories, e.g., “human” and “object”, the improvements are even higher than 18 percentage points.
Research on the Reconfiguration Method of Space-Based Exploration Satellite Constellations for Moving Target Tracking at Sea
Authors: Wang Yao , Luo Junren , Gu Xueqiang , Zhang Wanpeng
Published: September 2023

In addressing the challenge of tracking moving targets at sea, our focus has been directed towards the development of a reconstruction methodology founded upon satellite orbital manoeuvres. This endeavour has led us to devise a predictive model for manoeuvres within a geographic coordinate system, alongside the creation of a three-phase orbital manoeuvre model. A Non-dominant Sorting Adaptive Memetic (NSAM) algorithm is proposed in this paper, which is a two-layer multi-objective optimization algorithm that retains the advantages of evolutionary algorithms based on the population’s evolution and has an excellent local optimization ability of local search algorithms. The proposed algorithm can be used to solve multi-objective optimization problems. By comparing the target observation results before and after the satellite reconstruction simulation, it can be concluded that the orbital manoeuvring can effectively improve the observation probability and observation duration of the target at a certain speed. The orbital manoeuvre model created in this paper provides a certain methodical support for the tracking problem of moving targets at sea.
Comparative Analysis of Cooling Methods for Dynamic Infrared Thermography (DIRT)-Based Skin Cancer Diagnosis
Authors: Verstockt Jan , Thiessen Filip E. F. , Hoorens Isabelle , Brochez Lieve , Steenackers Gunther
Published: September 2023

Skin cancer is a significant global health issue, placing a growing burden on individuals and society. Conventional diagnostic methods like visual examination and biopsy have limitations in invasiveness and accuracy. As a result, alternative tools such as infrared thermography have gained attention in skin cancer diagnosis. Tissue-mimicking phantoms have been instrumental in facilitating research in this field, offering controlled environments. While they do not fully replicate human skin complexity, physical skin models provide stability, ease of fabrication, and control over properties. Agarose phantoms are employed in this study. This research focused on testing and comparing cooling techniques for human skin in the context of skin cancer diagnosis using dynamic infrared thermography. Six cooling methods were investigated: a cool pack, an aluminum medal, ice, alcohol, a vortex cooler and a Zimmer Cryo 6 cooler. The experimental setup involved an infrared camera (Optris Xi400) with microscope optics positioned above an agar phantom mimicking flat skin and an ulcerating skin lesion. Based on experiments conducted on the skin phantom, it was observed that convective cooling methods offered more consistent and uniform cooling. Conversely, conductive methods proved effective for flat objects but posed challenges in achieving uniform cooling for bulging skin or ulcerated lesions. Ice or alcohol were deemed unsuitable due to artifacts influencing the infrared radiation and thermal camera view. A decision matrix assessed cooling techniques based on criteria such as uniformity, repeatability, view obstruction, efficiency, workload, patient comfort, clinical suitability, noise exposure, consumables, additional equipment, and price. The Zimmer Cryo 6 cooler emerged as the most suitable cooling method after evaluating various factors.
Correlation between Neck Muscle Endurance Tests, Ultrasonography, and Self-Reported Outcomes in Women with Low Cervical Disability and Neck Pain
Authors: Pardos-Aguilella Pilar , Ceballos-Laita Luis , Cabanillas-Barea Sara , Pérez-Guillén Silvia , Ciuffreda Gianluca , Jiménez-del-Barrio Sandra , Carrasco-Uribarren Andoni
Published: September 2023

Background: Neck pain (NP) is a frequent condition in women, characterized by exhibiting distinct clinical manifestations such as the presence of deep neck (DN) muscle weakness. Endurance and ultrasonography of the DN muscles, and patient-reported outcome measures, are commonly used outcomes in clinical practice. The aim of this study is to assess and correlate the endurance of the DN muscles and their morphological characteristics with pain intensity, neck disability and headache impact. Methods: An observational and correlational study was carried out. Eighty-two women were recruited, and endurance tests of neck flexor and extensor (chin tuck flexion test and neck extensor muscles endurance test), ultrasonography of the DN muscles, pain intensity, disability (neck disability index) and headache impact (HIT-6) were measured. Spearman’s rho was used to evaluate the correlation between the outcome variables, and a simple linear regression analysis was carried out to explain the model in detail. Results: Statistically significant negative correlations between the chin tuck neck flexion test and neck disability index (NDI) (r = −0.38; p < 0.001) and HIT-6 (r = −0.26; p = 0.02) were found. The neck extensor muscles endurance test showed a negative correlation with NDI (r = −0.27; p = 0.01) and HIT-6 (r = −0.26; p = 0.02). The simple linear regression analysis showed an R squared of 26.7% and was statistically significant (NDI: R squared = 0.267; F = 3.13; p = 0.004) for NDI. Conclusion: A negative correlation between deep neck muscle endurance test results and self-reported outcome measures in women with low cervical disability and neck pain were observed. This suggests that lower endurance in the deep neck muscles may be associated with poorer self-reported symptoms and functionality in these patients. The chin tuck neck flexion test and deep extensor muscles endurance test could predict self-perceived neck disability in women with low cervical disability and NP.
Cloudscapes over the Baltic Sea–Cloud Motifs in Finnish, Swedish, German, Russian, Polish, Lithuanian, and Latvian Symbolic Landscape Painting around 1900
Authors: Konopka Emiliana
Published: September 2023

The cloud motif, a significant one in the landscape painting of the 1890s and early 1900s, has been usually marginalized by scholars despite the fact that during this (Symbolist) period clouds became independent subjects of landscape painting in many European countries, especially in the Baltic Sea Region. Cloud imagery makes a robust appearance in Scandinavian, Russian, Polish, Lithuanian, and Latvian art during the decades around 1900. The variety of symbolic meanings and possible interpretations of cloudscapes was impacted by cultural and literary associations that emerged with European Symbolism. There is a surprising resemblance of cloudscapes executed within the Baltic Sea Region, an examination of which reveals the complexity of artistic influence and the presence and wandering of motifs among artists.
Fermatean Fuzzy Fairly Aggregation Operators with Multi-Criteria Decision-Making
Authors: Mateen Muhammad Haris , Al-Dayel Ibrahim , Alsuraiheed Turki
Published: September 2023

A Fermatean fuzzy set (FRFS) is the extension of a fuzzy set, an intuitionistic fuzzy set, and a Pythagorean fuzzy set, and is used in different fields. Unlike other fuzzy structures, the sum of cubes of membership grades in FRFSs approximates a unit interval, increasing uncertainty. In this study, we intend to provide unique operational rules and aggregation operators (AOs) inside a Fermatean fuzzy environment. To develop a fair remedy for the membership degree and non-membership degree features of “Fermatean fuzzy numbers (FRFNs)”, our solution introduces new neutral or fair operating principles, which include the concept of proportional distribution. Based on the suggested operating principles, we provide the “Fermatean fuzzy fairly weighted average operator and the Fermatean fuzzy fairly ordered weighted averaging operator”. Our suggested AOs provide more generalized, reliable, and exact data than previous techniques. Combining the recommended AOs with multiple decision-makers and partial weight information under FRFSs, we also devised a technique for “multi-criteria decision-making”. To illustrate the application of our novel method, we provide an example of the algorithm’s effectiveness in addressing decision-making challenges.
Determining the Relationship between Mechanical Properties and Quantitative Magnetic Resonance Imaging of Joint Soft Tissues Using Patient-Specific Templates
Authors: Hananouchi Takehito , Satake Shinji , Sakao Kei , Katsuda Hiroshi , Shimada Nagakazu , Dorthe Erik W. , D’Lima Darryl D.
Published: September 2023

To determine whether the mechanical properties of joint soft tissues such as cartilage can be calculated from quantitative magnetic resonance imaging (MRI) data, we investigated whether the mechanical properties of articular cartilage and meniscus scheduled to be resected during arthroplasty are correlated with the T2 relaxation time on quantitative MRI at the same location. Six patients who had undergone knee arthroplasty and seven who had undergone hip arthroplasty were examined. For the knee joint, the articular cartilage and lateral meniscus of the distal lateral condyle of the femur and proximal lateral tibia were examined, while for the hip joint, the articular cartilage above the femoral head was studied. We investigated the relationship between T2 relaxation time by quantitative MRI and stiffness using a hand-made compression tester at 235 locations. The patient-individualized template technique was used to align the two measurement sites. The results showed a negative correlation (from −0.30 to −0.35) in the less severely damaged articular cartilage and meniscus. This indicates that tissue mechanical properties can be calculated from T2 relaxation time, suggesting that quantitative MRI is useful in determining when to start loading after interventional surgery on cartilage tissue and in managing the health of elderly patients.
Investigation on Flavescence Dorée in North-Western Italy Identifies Map-M54 (16SrV-D/Map-FD2) as the Only Phytoplasma Genotype in Vitis vinifera L. and Reveals the Presence of New Putative Reservoir Plants
Authors: Rigamonti Ivo Ercole , Salvetti Martino , Girgenti Paola , Bianco Piero Attilio , Quaglino Fabio
Published: September 2023

Flavescence dorée (FD) is the most important phytoplasma-associated disease of the grapevine yellows complex in Europe. Recent studies highlighted a great genetic diversity within FD phytoplasma (FDp) strains and demonstrated that their diffusion is not related exclusively to the pathosystem including Vitis vinifera L. and Scaphoideus titanus but involves additional vectors and reservoir plants. This study aimed to investigate FD epidemiology in north-western Italy, with a particular focus on FDp hosts. During field surveys, leaf samples were collected from symptomatic grapevines and other symptomless plant species, and insects were collected within and around vineyards. Phytoplasmas belonging to the ribosomal group 16SrV were detected and typed using nested-PCR-based amplification and nucleotide sequence analyses of the map gene. All symptomatic grapevines were found to be infected by the FDp genotype M54, prevalent in S. titanus and also identified in other known and newly reported hosts. Interestingly, other FDp strains (M38, M50, M51, M121) and FDp-related strains (M39, M43, M48), never detected in grapevines, were largely identified in several known and newly reported host plants and insects including S. titanus. Such evidence confirmed the complexity of FD ecology, expanding the knowledge on the range of FDp host plants putatively involved in the disease spread.
The Expression of Trace Amine-Associated Receptors (TAARs) in Breast Cancer Is Coincident with the Expression of Neuroactive Ligand–Receptor Systems and Depends on Tumor Intrinsic Subtype
Authors: Vaganova Anastasia N. , Maslennikova Daria D. , Konstantinova Valeria V. , Kanov Evgeny V. , Gainetdinov Raul R.
Published: September 2023

Currently, the contribution of trace amine-associated receptors (TAARs) to breast cancer (BC) is recognized, but their associations with various pathological characteristics are not yet understood. There is accumulated transcriptomic data for BC tumors, which are represented in publicly accessible databases. We estimated TAARs’ (including TAAR1, TAAR2, TAAR5, TAAR6, TAAR8, and TAAR9) associations with BC stage, grade, and molecular subtypes in these data and identified that the expression of all TAARs was associated with more unfavorable cancer subtypes, including basal-like and HER2-positive tumors. Also, the significant upregulation of all TAARs was demonstrated in circulating tumor cells compared to the metastatic lesions. Considering that co-expressed genes are more likely to be involved in the same biologic processes, we analyzed genes that are co-expressed with TAARs in BC. These gene sets were enriched with the genes of the olfactory transduction pathway and neuroactive ligand–receptor interaction participants. TAARs are co-expressed with G-protein-coupled receptors of monoamine neurotransmitters including dopamine, norepinephrine, and serotonin as well as with other neuroactive ligand-specific receptors. Since TAAR1 is able to modulate the activity of monoamine receptors that are involved in the regulation of BC growth, TAAR1 and potentially other TAARs may be regarded as prospective therapeutic targets for breast cancer.
Advances of Osteosarcoma Models for Drug Discovery and Precision Medicine
Authors: Tan Linyun , Wang Yitian , Hu Xin , Du Guifeng , Tang Xiaodi , Min Li
Published: September 2023

The management of osteosarcoma (OS) patients presents a significant clinical challenge. Despite progress in conventional and targeted therapies, the survival rate of OS patients remains limited largely due to therapy resistance and the high metastatic potential of the disease. OS models that accurately reflect the fundamental characteristics are vital to the innovation and validation of effective therapies. This review provides an insight into the advances and challenges in OS drug development, focusing on various preclinical models, including cell lines, 3D culture models, murine models, and canine models. The relevance, strengths, and limitations of each model in OS research are explored. In particular, we highlight a range of potential therapeutics identified through these models. These instances of successful drug development represent promising pathways for personalized OS treatment.
Wave-like Robotic Locomotion between Highly Flexible Surfaces and Comparison to Worm Robot Locomotion
Authors: Shachaf Dan , Katz Rotem , Zarrouk David
Published: September 2023

In a recent study, we developed a minimally actuated robot that utilizes wave-like locomotion and analyzed its kinematics. In this paper, we present an analysis of the robot’s locomotion between two highly flexible surfaces. Initially, we created a simulation model of the robot between two surfaces and determined its speed and the conditions of locomotion based on the flexibility of the surface, the geometrical parameters, and the coefficient of friction for horizontal locomotion and climbing at different angles. Our findings indicate that wave locomotion is capable of consistently advancing along the surface, even when the surface is highly flexible. Next, we developed an experimental setup and conducted multiple experiments to validate the accuracy of our simulation. The results indicate an average relative difference of approximately 11% between the speed and advance ratio of the wave crawling between the two surfaces of our simulation model and the experimental results were performed using an actual robot. Lastly, we compared the wave locomotion results to those of the worm locomotion and discovered that wave locomotion outperforms worm locomotion, especially at a higher surface flexibility.
A Methylene Blue-Enhanced Nanostructured Electrochemical Immunosensor for H-FABP Myocardial Injury Biomarker
Authors: Prado Cecília Maciel , Burgos Ferreira Paula Angélica , Alves de Lima Lucas , Gomes Trindade Erika Ketlem , Fireman Dutra Rosa
Published: September 2023

A sensitive electrochemical immunosensor for the detection of the heart-type fatty acid binding protein (HFABP), an earlier biomarker for acute myocardial infarction than Troponins, is described. The sensing platform was enhanced with methylene blue (MB) redox coupled to carbon nanotubes (CNT) assembled on a polymer film of polythionine (PTh). For this strategy, monomers of thionine rich in amine groups were electrosynthesized by cyclic voltammetry on the immunosensor’s gold surface, forming an electroactive film with excellent electron transfer capacity. Stepwise sensor surface preparation was electrochemically characterized at each step and scanning electronic microscopy was carried out showing all the preparation steps. The assembled sensor platform combines MB and PTh in a synergism, allowing sensitive detection of the H-FABP in a linear response from 3.0 to 25.0 ng∙mL−1 with a limit of detection of 1.47 ng∙mL−1 HFABP that is similar to the clinical level range for diagnostics. H-FABP is a newer powerful biomarker for distinguishing between unstable angina and acute myocardial infarction.
Dynamic Properties of Timber–Concrete Composite Beams with Crossed Inclined Coach Screw Connections: Experimental and Theoretical Investigations
Authors: Wen Bo , Tao Haotian , Shi Benkai , Yang Huifeng
Published: September 2023

Due to the low density and stiffness of wood, traditional timber floor systems are prone to producing large vibration responses. By combining timber beams with concrete floors, timber–concrete composite (TCC) floor systems show stronger bearing capacity, higher bending stiffness, and better thermal and sound insulation behaviors when compared with traditional timber floor systems. In this study, the vibration performance of TCC beams with crossed inclined coach screw connectors was investigated using dynamic tests. The influence of the screw diameters and slab dimensions on the dynamic performance of the composite beams was evaluated. The test results demonstrated that TCC beams show good dynamic performance when used as a floor component and meet the preliminary requirements of floor vibration comfort for fundamental frequency. The fundamental frequency and damping ratio of TCC beams decreases with the increase in slab dimensions. The bending stiffness and natural frequency of TCC beams decrease smoothly when reducing the screw diameter from 16 to 12 mm. Additionally, two theoretical models were used to predict the natural frequencies of the TCC beams, and the predicted values show good consistency with the measured ones.
GPER1 Activation Exerts Anti-Tumor Activity in Multiple Myeloma
Authors: Gallo Cantafio Maria Eugenia , Torcasio Roberta , Scionti Francesca , Mesuraca Maria , Ronchetti Domenica , Pistoni Mariaelena , Bellizzi Dina , Passarino Giuseppe , Morelli Eugenio , Neri Antonino , Viglietto Giuseppe , Amodio Nicola
Published: September 2023

G protein-coupled estrogen receptor 1 (GPER1) activation is emerging as a promising therapeutic strategy against several cancer types. While GPER targeting has been widely studied in the context of solid tumors, its effect on hematological malignancies remains to be fully understood. Here, we show that GPER1 mRNA is down-regulated in plasma cells from overt multiple myeloma (MM) and plasma cell leukemia patients as compared to normal donors or pre-malignant conditions (monoclonal gammopathy of undetermined significance and smoldering MM); moreover, lower GPER1 expression associates with worse overall survival of MM patients. Using the clinically applicable GPER1-selective agonist G-1, we demonstrate that the pharmacological activation of GPER1 triggered in vitro anti-MM activity through apoptosis induction, also overcoming the protective effects exerted by bone marrow stromal cells. Noteworthy, G-1 treatment reduced in vivo MM growth in two distinct xenograft models, even bearing bortezomib-resistant MM cells. Mechanistically, G-1 upregulated the miR-29b oncosuppressive network, blunting an established miR-29b-Sp1 feedback loop operative in MM cells. Overall, this study highlights the druggability of GPER1 in MM, providing the first preclinical framework for further development of GPER1 agonists to treat this malignancy.
Non-Alcoholic Fatty Liver Disease Is Associated with a Decreased Catalase (CAT) Level, CT Genotypes and the T Allele of the -262 C/T CAT Polymorphism
Authors: Kosmalski Marcin , Szymczak-Pajor Izabela , Drzewoski Józef , Śliwińska Agnieszka
Published: September 2023

Background: It is well known that oxidative stress plays an important role in the development of non-alcoholic fatty liver disease (NAFLD). It has been suggested that an insufficient antioxidant defense system composed of antioxidant enzymes, including catalase (CAT) and nonenzymatic molecules, is a key factor triggering oxidative damage in the progression of liver disease. Therefore, the aim of our study was to assess whether the level of CAT and -262 C/T polymorphism in the promoter of CAT (rs1001179) are associated with NAFLD. Methods: In total, 281 adults (152/129 female/male, aged 65.61 ± 10.44 years) were included in the study. The patients were assigned to an NAFLD group (n = 139) or a group without NAFLD (n = 142) based on the results of an ultrasound, the Hepatic Steatosis Index, and the Fatty Liver Index (FLI). CAT levels were determined using an ELISA test, and genomic DNA was extracted via the standard phenol/chloroform-based method and genotyped via RFLP-PCR. Results: The CAT level was decreased in NAFLD patients (p < 0.001), and an ROC analysis revealed that a CAT level lower than 473.55 U/L significantly increases the risk of NAFLD. In turn, genotyping showed that the CT genotype and the T allele of -262 C/T CAT polymorphism elevate the risk of NAFLD. The diminished CAT level in the NAFLD group correlated with increased FLI, waist circumference and female gender. Conclusion: The obtained results support observations that oxidative damage associated with NAFLD may be the result of a decreased CAT level as a part of the antioxidant defense system.
Electric Field Effects on Brain Activity: Implications for Epilepsy and Burst Suppression
Authors: Doubovikov Evan D. , Serdyukova Natalya A. , Greenberg Steven B. , Gascoigne David A. , Minhaj Mohammed M. , Aksenov Daniil P.
Published: September 2023

Electric fields are now considered a major mechanism of epileptiform activity. However, it is not clear if another electrophysiological phenomenon, burst suppression, utilizes the same mechanism for its bursting phase. Thus, the purpose of this study was to compare the role of ephaptic coupling—the recruitment of neighboring cells via electric fields—in generating bursts in epilepsy and burst suppression. We used local injections of the GABA-antagonist picrotoxin to elicit epileptic activity and a general anesthetic, sevoflurane, to elicit burst suppression in rabbits. Then, we applied an established computational model of pyramidal cells to simulate neuronal activity in a 3-dimensional grid, with an additional parameter to trigger a suppression phase based on extra-cellular calcium dynamics. We discovered that coupling via electric fields was sufficient to produce bursting in scenarios where inhibitory control of excitatory neurons was sufficiently low. Under anesthesia conditions, bursting occurs with lower neuronal recruitment in comparison to seizures. Our model predicts that due to the effect of electric fields, the magnitude of bursts during seizures should be roughly 2–3 times the magnitude of bursts that occur during burst suppression, which is consistent with our in vivo experimental results. The resulting difference in magnitude between bursts during anesthesia and epileptiform bursts reflects the strength of the electric field effect, which suggests that burst suppression and epilepsy share the same ephaptic coupling mechanism.
Simulation of the Inductor Structure to Improve FZ Thermal Fields
Authors: Ai Xingtian , Sun Chenguang , Zhang Hui , Sun Jian , Xie Luxiao , Liu Guodong , Chen Guifeng
Published: September 2023

The floating zone (FZ) is one of the important methods for pulling silicon single crystals, but there are still problems of an unstable thermal field and crystallization difficulties. They will directly affect the growth of single crystals, resulting in defects and even fractures, seriously reducing production efficiency. Based on this, the effect of the modified inductor structure on the FZ thermal field is investigated in this paper. Using COMSOL 6.0 simulation software, 2D and 3D FZ models are established. The inductor steps under the 2D model and the inductor slits under the 3D model are compared to analyze the effects of steps and slits on the 8-inch FZ thermal field and melt flow. The distributions of temperature fields and melt flow in the melting zone under the action of the axial magnetic field are calculated by finite element analysis. The results show that the melt under the introduction of steps in the 2D model and the cross-slit structure in the 3D model is the most stable and favorable for crystal growth, which matches the actual production.
Opinion Formation in Online Public Debates Structured in Information Cascades: A System-Theoretic Viewpoint
Authors: Kozitsin Ivan V.
Published: September 2023

Online information cascades (tree-like structures formed by posts, comments, likes, replies, etc.) constitute the spine of the public online information environment, reflecting its various trends, evolving with it and, importantly, affecting its development. While users participate in online discussions, they display their views and thus contribute to the growth of cascades. At the same time, users’ opinions are influenced by cascades’ elements. The current paper aims to advance our knowledge regarding these social processes by developing an agent-based model in which agents participate in a discussion around a post on the Internet. Agents display their opinions by writing comments on the post and liking them (i.e., leaving positive assessments). The result of these processes is dual: on the one hand, agents develop an information cascade; on the other hand, they update their views. Our purpose is to understand how agents’ activity, openness to influence, and cognitive constraints (that condition the amount of information individuals are able to proceed with) affect opinion dynamics in a three-party society. More precisely, we are interested in what opinion will dominate in the long run and how this is moderated by the aforementioned factors, the social contagion effect (when people’ perception of a message may depend not only on the message’s opinion, but also on how other individuals perceive this object, with more positive evaluations increasing the probability of adoption), and ranking algorithms that steer the order in which agents learn new messages. Among other things, we demonstrated that replies to disagreeable opinions are extremely effective for promoting your own position. In contrast, various forms of like activity have a tiny effect on this issue.
Voxel Extraction and Multiclass Classification of Identified Brain Regions across Various Stages of Alzheimer’s Disease Using Machine Learning Approaches
Authors: Shahzadi Samra , Butt Naveed Anwer , Sana Muhammad Usman , Pascual Iñaki Elío , Urbano Mercedes Briones , Díez Isabel de la Torre , Ashraf Imran
Published: September 2023

This study sought to investigate how different brain regions are affected by Alzheimer’s disease (AD) at various phases of the disease, using independent component analysis (ICA). The study examines six regions in the mild cognitive impairment (MCI) stage, four in the early stage of Alzheimer’s disease (AD), six in the moderate stage, and six in the severe stage. The precuneus, cuneus, middle frontal gyri, calcarine cortex, superior medial frontal gyri, and superior frontal gyri were the areas impacted at all phases. A general linear model (GLM) is used to extract the voxels of the previously mentioned regions. The resting fMRI data for 18 AD patients who had advanced from MCI to stage 3 of the disease were obtained from the ADNI public source database. The subjects include eight women and ten men. The voxel dataset is used to train and test ten machine learning algorithms to categorize the MCI, mild, moderate, and severe stages of Alzheimer’s disease. The accuracy, recall, precision, and F1 score were used as conventional scoring measures to evaluate the classification outcomes. AdaBoost fared better than the other algorithms and obtained a phenomenal accuracy of 98.61%, precision of 99.00%, and recall and F1 scores of 98.00% each.
Thyroid Nodule Detection and Region Estimation in Ultrasound Images: A Comparison between Physicians and an Automated Decision Support System Approach
Authors: Gomes Ataide Elmer Jeto , Jabaraj Mathews S. , Schenke Simone , Petersen Manuela , Haghghi Sarvar , Wuestemann Jan , Illanes Alfredo , Friebe Michael , Kreissl Michael C.
Published: September 2023

Background: Thyroid nodules are very common. In most cases, they are benign, but they can be malignant in a low percentage of cases. The accurate assessment of these nodules is critical to choosing the next diagnostic steps and potential treatment. Ultrasound (US) imaging, the primary modality for assessing these nodules, can lack objectivity due to varying expertise among physicians. This leads to observer variability, potentially affecting patient outcomes. Purpose: This study aims to assess the potential of a Decision Support System (DSS) in reducing these variabilities for thyroid nodule detection and region estimation using US images, particularly in lesser experienced physicians. Methods: Three physicians with varying levels of experience evaluated thyroid nodules on US images, focusing on nodule detection and estimating cystic and solid regions. The outcomes were compared to those obtained from a DSS for comparison. Metrics such as classification match percentage and variance percentage were used to quantify differences. Results: Notable disparities exist between physician evaluations and the DSS assessments: the overall classification match percentage was just 19.2%. Individually, Physicians 1, 2, and 3 had match percentages of 57.6%, 42.3%, and 46.1% with the DSS, respectively. Variances in assessments highlight the subjectivity and observer variability based on physician experience levels. Conclusions: The evident variability among physician evaluations underscores the need for supplementary decision-making tools. Given its consistency, the CAD offers potential as a reliable “second opinion” tool, minimizing human-induced variabilities in the critical diagnostic process of thyroid nodules using US images. Future integration of such systems could bolster diagnostic precision and improve patient outcomes.
Effect of Cuff Inflation on Blood Pressure, Arousals, Sleep Efficiency, and Desaturations: Sub-Analysis of the VAST Pilot Study
Authors: Socrates Thenral , Krisai Philipp , Meienberg Andrea , Mayr Michael , Burkard Thilo , Vischer Annina S.
Published: September 2023

The influence of cuff inflations on night-time measurements during 24 h ambulatory blood pressure (BP) measurements is unknown. We investigated the potential effect of cuff inflations on sleep parameters using measurements taken simultaneously with a cuffless device using pulse-transit-time (PTT). On the first day of measurement, standard cuff-based 24 h BP and cuffless measurements were simultaneously performed on the right and left arms (CUFF/PTT-D). In this experiment, 1–2 days after the first measurement, the cuffless device was worn alone (PTT-D). Only data from the cuffless device were analyzed. The following mean sleep parameters were analyzed: mean systolic and diastolic BP, arousals, sleep efficiency, total arousals, arousal per hour, and desaturations. In total, 21 individuals were prospectively enrolled. The mean (SD) age was 47 (±15) years, and 57% were female. The mean systolic asleep BP during CUFF/PTT-D and during PTT-D were 131 (±21) and 131 (±26) mmHg, respectively. The mean diastolic asleep BP values during CUFF/PTT-D and during PTT-D were 80 (±14) and 84 (±14) mmHg, respectively (p = 0.860, p = 0.100, respectively). Systolic and diastolic asleep mean difference was 0.1 (±18.0) and −3.6 (±9.8) mmHg, respectively. There were significantly more total arousals during PTT-D (p = 0.042). There were no significant differences seen in sleep efficiency (p = 0.339) or desaturations (p = 0.896) between the two measurement periods. We could not show any significant impact from cuff inflations during sleep, as documented by PTT-D measurements.
Prognostic Assessment of Gastropancreatic Neuroendocrine Neoplasm: Prospects and limits of Radiomics
Authors: De Muzio Federica , Pellegrino Fabio , Fusco Roberta , Tafuto Salvatore , Scaglione Mariano , Ottaiano Alessandro , Petrillo Antonella , Izzo Francesco , Granata Vincenza
Published: September 2023

Neuroendocrine neoplasms (NENs) are a group of lesions originating from cells of the diffuse neuroendocrine system. NENs may involve different sites, including the gastrointestinal tract (GEP-NENs). The incidence and prevalence of GEP-NENs has been constantly rising thanks to the increased diagnostic power of imaging and immuno–histochemistry. Despite the plethora of biochemical markers and imaging techniques, the prognosis and therapeutic choice in GEP-NENs still represents a challenge, mainly due to the great heterogeneity in terms of tumor lesions and clinical behavior. The concept that biomedical images contain information about tissue heterogeneity and pathological processes invisible to the human eye is now well established. From this substrate comes the idea of radiomics. Computational analysis has achieved promising results in several oncological settings, and the use of radiomics in different types of GEP-NENs is growing in the field of research, yet with conflicting results. The aim of this narrative review is to provide a comprehensive update on the role of radiomics on GEP-NEN management, focusing on the main clinical aspects analyzed by most existing reports: predicting tumor grade, distinguishing NET from other tumors, and prognosis assessment.
Information and Media Literacy in the Age of AI: Options for the Future
Authors: Tiernan Peter , Costello Eamon , Donlon Enda , Parysz Maria , Scriney Michael
Published: September 2023

The concepts of information and media literacy have been central components of digital literacy since the digitization of information began. However, the increasing influence of artificial intelligence on how individuals locate, evaluate, and create content has significant implications for what it means to be information and media literate. This paper begins by exploring the role artificial intelligence plays at the various stages of information retrieval and creation processes. Following this, the paper reviews existing digital literacy frameworks to ascertain their definitions of information and media literacy and the potential impact of artificial intelligence on them. We find that digital literacy frameworks have been slow to react to artificial intelligence and its repercussions, and we recommend a number of strategies for the future. These strategies center around a more agile, responsive, and participatory approach to digital literacy framework development and maintenance.
Flame and Smoke Semantic Dataset: Indoor Fire Detection with Deep Semantic Segmentation Model
Authors: Hou Feifei , Rui Xiyue , Chen Yuanheng , Fan Xinyu
Published: September 2023

Indoor fires can easily cause property damage and especially serious casualties. Early and timely fire detection helps firefighters make scientific judgments on the cause of fires, thereby effectively controlling fire accidents. However, most of the existing computer-vision-based fire detection methods are only able to detect a single case of flame or smoke. In this paper, a tailored deep-learning-based scheme is designed to simultaneously detect flame and smoke objects in indoor scenes. We adopt the semantic segmentation architecture DeepLabv3+ as the main model, which is an encoder-decoder architecture for both the detection and segmentation of fire objects. Within this, the key module, e.g., atrous convolution, is integrated into the architecture to improve image resolution and accurately locate targets. In addition, to solve the question of an insufficient indoor fire dataset, we prepare and construct a new annotated dataset named the ‘Flame and Smoke Semantic Dataset (FSSD)’, which includes extensive semantic information of fire objects and is collected from real indoor scenes and other fire sources. Experiments conducted on our FSSD database and the comparisons with state-of-the-art methods (FCN, PSPNet, and DeepLabv3), confirm the high performance of the proposed scheme with 91.53% aAcc, 89.67% mAcc, and 0.8018 mIoU, respectively.