bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessing Land Cover Changes Using the LUCAS Database and Sentinel Imagery: A Comparative Analysis of Accuracy Metrics
Authors: Hejmanowska Beata , Kramarczyk Piotr
Published: December 2024

Classification of remote sensing images using machine learning models requires a large amount of training data. Collecting this data is both labor-intensive and time-consuming. In this study, the effectiveness of using pre-existing reference data on land cover gathered as part of the Land Use–Land Cover Area Frame Survey (LUCAS) database of the Copernicus program was analyzed. The classification was carried out in Google Earth Engine (GEE) using Sentinel-2 images that were specially prepared to account for the phenological development of plants. Classification was performed using SVM, RF, and CART algorithms in GEE, with an in-depth accuracy analysis conducted using a custom tool. Attention was given to the reliability of different accuracy metrics, with a particular focus on the widely used machine learning (ML) metric of “accuracy”, which should not be compared with the commonly used remote sensing metric of “overall accuracy”, due to the potential for significant artificial inflation of accuracy. The accuracy of LUCAS 2018 at Level-1 detail was estimated at 86%. Using the updated LUCAS dataset, the best classification result was achieved with the RF method, with an accuracy of 83%. An accuracy overestimation of approximately 10% was observed when reporting the average accuracy ACC metric used in ML instead of the overall accuracy OA metric.
Hypoplastic Modeling of Soil–Structure Contact Surface Considering Initial Anisotropy and Roughness
Authors: Yu Jingtao , Cao Junwang , Chen Zixuan , Zhu Jintao , Zhang Yulong , Yu Pengqiang
Published: December 2024

The development of a constitutive model for soil–structure contact surfaces remains a pivotal area of research within the field of soil–structure interaction. Drawing from the Gudehus–Bauer sand hypoplasticity model, this paper employs a technique that reduces the stress tensor and strain rate tensor components to formulate a hypoplastic model tailored for sand–structure interfaces. To capture the influence of initial anisotropy, a deposition direction peak stress coefficient is incorporated; meanwhile, a friction parameter is introduced to address the surface roughness of the contact. Consequently, a comprehensive hypoplastic constitutive model is developed that takes into account both initial anisotropy and roughness. Comparative analysis with experimental data from soils on contact surfaces with diverse boundary conditions and levels of roughness indicates that the proposed model accurately forecasts shear test outcomes across various contact surfaces. Utilizing the finite element software ABAQUS 2021, an FRIC subroutine was developed, which, through simulating direct shear tests on sand–structure contact surfaces, has proven its efficacy in predicting the shear behavior of these interfaces.
Innovative Use of Wood Ash for Fluoride Removal from Water: Comprehensive Experiments and Mechanism Insight
Authors: Lee Jae-In , Kang Jin-Kyu , Jeong Sanghyun , Lee Chang-Gu , Choi Joon-Weon , Park Seong-Jik
Published: December 2024

This study investigates the potential of wood ash (WA), a by-product of wood-based energy production, as an eco-friendly alternative for removing fluoride from water. Kinetic analysis revealed that WA enables rapid fluoride removal, reaching equilibrium within 1 h (112.09 ± 3.9 mg/g). Equilibrium analysis demonstrated that WA exhibits a Langmuir maximum capacity of 157.34 mg/g, indicating a high adsorption capacity that ranks within the top 10% of reported adsorbents (34th out of 328). According to thermodynamic analysis, the adsorption process appears to be both endothermic and spontaneous at elevated temperatures. pH dependence studies showed that while the fluoride adsorption capacity of WA peaked under acidic conditions, it remained relatively stable (116.01 ± 0.8 mg/g) over a wide range of pH levels (5 to 11). An optimal dosage of 6.67 g/L achieved a greater than 98% fluoride removal rate. Coexisting anions affected the fluoride adsorption capacity of WA, with the order of influence being PO43− > CO32− >> SO42− > NO3− ≈ Cl−. Mechanistic analyses confirmed the surface precipitation of CaF2 as the primary mechanism responsible for fluoride removal. With a Ca content of over 66 wt.%, WA facilitates enhanced fluoride removal. Overall, this study highlights the efficacy of WA as a sustainable adsorbent for the removal of fluoride from water, contributing to the valorization of WA in wastewater treatment applications.
Steering Assist Control for Bicycles with Variable Trail Effect
Authors: Kihara Takaatsu , Sugasawa Yuzuki , Kuriyama Keigo , Iwase Masami
Published: December 2024

The purpose of this study is to realize a power steering control that restores the maneuverability of the bicycle by assisting in handlebar operation during loading according to the analysis of the effect of loading children and luggage in the front basket on maneuverability. Placing baggage and child in the front basket of a bicycle causes an increase in the moment of inertia around the handlebar axis and a change in the position of the center of gravity, and leads to a decrease in the maneuverability of the bicycle. To solve the issue, previous studies have contributed to improve the maneuverability by applying the assist torque proportional to the user’s steering one by a power steering mechanism. However, in general, bicycle steering is affected not only by handlebar operation but also by the roll angle of the bicycle body through the trail effect. Therefore, in this study, we propose to design a control system to realize the variable trail effect, which is related to the roll angle of the bicycle body, and use it as the steering assist. To verify the effectiveness of the proposed method, we developed a bicycle equipped with the power steering mechanism and implemented the proposed control algorithm. The behavior of the experimental bicycle during straight-line and slalom biking has been analyzed, and it has been shown that the control system with the variable trail effect can recover maneuverability when a weight is placed in the front basket.
Artificial Intelligence in Oncology
Authors: Jeziorski Krzysztof , Olszewski Robert
Published: December 2024

The aim of the article is to highlight the key role of artificial intelligence in modern oncology. The search for scientific publications was carried out through the following web search engines: PubMed, PMC, Web of Science, Scopus, Embase and Ebsco. Artificial intelligence plays a special role in oncology and is considered to be the future of oncology. The largest application of artificial intelligence in oncology is in diagnostics (more than 80%), particularly in radiology and pathology. This can help oncologists not only detect cancer at an early stage but also forecast the possible development of the disease by using predictive models. Artificial intelligence plays a special role in clinical trials. AI makes it possible to accelerate the discovery and development of new drugs, even if not necessarily successfully. This is done by detecting new molecules. Artificial intelligence enables patient recruitment by combining diverse demographic and medical patient data to match the requirements of a given research protocol. This can be done by reducing population heterogeneity, or by prognostic and predictive enrichment. The effectiveness of artificial intelligence in oncology depends on the continuous learning of the system based on large amounts of new data but the development of artificial intelligence also requires the resolution of some ethical and legal issues.
Graph Neural Networks for Analyzing Trauma-Related Brain Structure in Children and Adolescents: A Pilot Study
Authors: Jeong Harim , Kang Minjoo , McLeay Shanon , Blair R. J. R. , Chung Unsun , Hwang Soonjo
Published: December 2024

This study explores the potential of graph neural networks (GNNs) in analyzing brain networks of children and adolescents exposed to trauma, addressing limitations in traditional neuroimaging approaches. MRI-based brain data from trauma-exposed and control groups were modeled as whole-brain networks using regions-of-interest (ROIs), with GNNs applied to capture complex, non-linear connectivity patterns. Results revealed that the trauma-exposed group exhibited simplified network structures with higher importance in regions associated with cognitive and emotional regulation, such as the posterior cerebellum. In contrast, the control group demonstrated richer connectivity patterns, emphasizing regions related to motor and visual processing, such as the Right Lingual Gyrus. Compared to traditional t-test results highlighting regional density differences, the GNN approach uncovered deeper, network-level insights into the relationships between brain regions. These findings demonstrate the utility of GNNs in advancing neuroimaging research, offering new perspectives on trauma’s impact on brain connectivity and paving the way for future applications in understanding neural mechanisms and interventions.
Secrecy Rate Performance Analysis of Jammer-Aided Symbiotic Radio with Sensing Errors for Fifth Generation Wireless Networks
Authors: Onay Muhammed Yusuf
Published: December 2024

Symbiotic radio (SR), which has recently been introduced as an effective solution for 5G wireless networks, stands out with system models that include hybrid devices that share the frequency spectrum and transmit information to the same receiver. However, the low bit rate and the small amount of energy harvested in SR, where backscatter communication systems are integrated, make the system vulnerable to eavesdropping. To ensure security, the secrecy rate is defined as the difference between the number of bits transmitted to the receiver over the information channel and the number of bits reaching the eavesdropper (ED) over the wiretap channel. This paper is the first work that aims to maximize the secrecy rate for friendly jammer-aided SR networks with EDs over time allocation and power reflection coefficient in the presence of sensing errors. The proposed model consists of a base station (BS), a hybrid transmitter (HT) in symbiotic relationship with the BS, a WiFi access point used by the HT for energy harvesting, a jammer cooperating with the HT and BS, an information receiver, and EDs trying to access the information of the HT and BS. The simulation results provide valuable insights into the impact of system parameters on secrecy rate performance. Although taking the sensing error into account degrades the system performance, the real-world applicability of the system with sensing error is more realistic. It is also observed that the proposed system has higher performance compared to the wireless powered communication networks in the literature, which only use the energy harvest-then-transmit protocol and the power reflection coefficient is assumed to be zero.
Multi-Objective Optimal Trajectory Planning for Woodworking Manipulator and Worktable Based on the INSGA-II Algorithm
Authors: Yi Jiaping , Zhang Changqing , Chen Sihan , Dai Qinglong , Yu Hang , Yang Guang , Yu Leyuan
Published: December 2024

The manipulator has been widely used in the wood processing industry; the main problem currently faced is optimizing the motion trajectory to enhance the processing efficiency and operational stability of the woodworking manipulator and worktable. A 5-7-5 piecewise polynomial interpolation method is proposed to construct the spatial trajectories of each joint. An improved non-dominated sorting genetic algorithm (INSGA-II) is proposed to achieve a time–jerk multi-objective trajectory planning that can meet the dual requirements of minimal processing time and reduced motion impact. In order to address the limitations of the standard NSGA-II algorithm, which is prone to local optima and exhibits slow convergence, we propose a good point set method for multi-objective optimization population initialization and a linear ranking selection method to refine the parent selection process within the genetic algorithm. The improved NSGA-II algorithm markedly enhanced both the uniformity of the population distribution and convergence speed. In practical applications, selecting suitable weightings to construct a normalized weight function can identify the optimal solution from the Pareto frontier curve. A high-order continuous and smooth optimal trajectory without abrupt changes can be obtained. The simulation results demonstrated that the 5-7-5 piecewise polynomial interpolation curve effectively constructed a high-order smooth processing trajectory with continuous and smooth velocity, acceleration, and jerk, free from discontinuities. Moreover, the INSGA-II algorithm outperforms the original algorithm in terms of convergence and distribution, enabling the optimal time–jerk multi-objective trajectory planning that adheres to constraint conditions. Optimized by the improved NSGA-II algorithm, the optimal total running time is 4.5400 s, and the optimal jerk is 17.934 m(rad)/s3. This provides a novel approach to solving the inefficiencies and operational instability prevalent in traditional woodworking equipment.
Improving the Forecast Accuracy of PM2.5 Using SETAR-Tree Method: Case Study in Jakarta, Indonesia
Authors: Safira Dinda Ayu , Kuswanto Heri , Ahsan Muhammad
Published: December 2024

Air pollution in Jakarta, one of the most polluted cities globally, has reached critical levels, with PM2.5 concentrations exceeding the WHO guidelines and posing significant health risks. Accurate forecasting of PM2.5 is crucial for effective air quality management and public health interventions. PM2.5 exhibits significant nonlinear fluctuations; thus, this study employed two machine learning approaches: self-exciting threshold autoregressive tree (SETAR-Tree) and long short-term memory (LSTM). The SETAR-Tree model integrates regime-switching capabilities with decision tree principles to capture nonlinear patterns, while LSTM models long-term dependencies in time-series data. The results showed that: (1) SETAR-Tree outperformed LSTM, achieving lower RMSE (0.1691 in-sample, 0.2159 out-sample) and MAPE (2.83% in-sample, 2.98% out-sample) compared to LSTM’s RMSE (0.2038 in-sample, 0.2399 out-sample) and MAPE (3.48% in-sample, 4.05% out-sample); (2) SETAR-Tree demonstrated better responsiveness to sudden regime changes, capturing complex pollution patterns influenced by meteorological and anthropogenic factors; (3) PM2.5 in Jakarta often exceeds the WHO limits, highlighting this study’s importance in supporting strategic planning and providing an early warning system to reduce outdoor activity during extreme pollution.
Wind Field Characteristics of the 13 June 2014 Downburst Event in Beijing Based on Meteorological Tower Records
Authors: Zhang Shi , Wang Yibo , Qian Zengzhi , Guo Kexin , Xu Xiaoda , Zhou Daxing , Cao Qing
Published: December 2024

Understanding the characteristics of downburst wind fields is crucial for studying structural resistance to downbursts. Based on measured data from the 325 m meteorological tower in Beijing, this paper investigates the spatiotemporal evolution of mean and fluctuating winds during a non-stationary downburst. Key wind field parameters such as the mean wind speed, turbulence intensity, turbulence integral length scale, probability density function, power spectral density, evolutionary power spectral density, and gust factor are statistically analyzed. The results show that the wind speed of downburst undergoes rapid changes, with wind direction significantly influenced by outflow vortices at low altitudes and relatively stable at higher altitudes. When the event happens, the temperature decreases sharply. The mean wind speeds and turbulence integral length scale of the downburst exhibit pronounced “nose-shaped” profile characteristics at the moment when peak wind speed occurs. The turbulence intensity at lower altitudes predominantly exceeds that at higher altitudes. The probability density distribution function of the reduced fluctuating wind speed matches the standard Gaussian distribution curve. The fluctuating wind speeds of the downburst exhibit significant non-stationary characteristics, with their energy mainly distributing in the period of rapid change of wind speed in the time domain and concentrating in the vicinity of 0–0.1 Hz in the frequency domain. The gust factor reaches its maximum at the moment when the peak wind speed occurs.
Assessing Thermal Comfort and Indoor Air Quality: In an Educational Facility of a Semi-Arid Climate Zone
Authors: Parmaksiz Kemalettin , Yesilnacar Mehmet Irfan , Karabulut Abdullah Izzeddin
Published: December 2024

There are three main approaches to human thermal comfort; a psychological approach, a thermo-physiological approach, and an approach based on human energy balance. According to the ISO 7730 and ASHRAE Standard 55-2023 standards, the psychological approach defines thermal comfort as a mental state in which individuals feel satisfied with their surrounding environment. According to this definition, thermal comfort is very subjective and may vary between individuals, as well as according to the environment and climate. This study aimed to evaluate the thermal comfort levels of students in primary and high school classrooms situated within the semi-arid climatic conditions of Şanlıurfa. For this purpose, 15 Temmuz Şehitleri Secondary School, Kadir Evliyaoğlu College, and TOBB Science High School in Şanlıurfa were chosen as fieldwork locations. Within the scope of the study, the climatic conditions (classroom temperature, air velocity, humidity, radiant temperature, Tw, Tg carbon dioxide) were measured, and how the students felt under the thermal conditions of these classrooms was evaluated. The study encompasses both the heating season (winter) and the non-heating season (summer). Based on the findings obtained from the study, PMV (Predicted Mean Vote) and PPD (Predicted Percentage Dissatisfied) values and whether they are suitable thermal comfort for the people in these places tried to be determined by mathematical modeling and standards such as ASHRAE Standard 55-2023. While PMV values ranged between −0.58 (North) and 2.53 (East+South+West), PPD values were observed between 5% (South and some North facades) and 94% (East+South+West). While the South facade offers values close to the comfort range of 0.01–0.02 in terms of PMV, the East+South+West facade shows serious thermal discomfort with a PMV value of 2.53 and a PPD value of 94%.
Analysis of Bulk Queueing Model with Load Balancing and Vacation
Authors: Niranjan Subramani Palani , Latha Suthanthiraraj Devi , Vlase Sorin , Scutaru Maria Luminita
Published: December 2024

Data center architecture plays an important role in effective server management network systems. Load balancing is one such data architecture used to efficiently distribute network traffic to the server. In this paper, we incorporated the load-balancing technique used in cloud computing with power business intelligence (BI) and cloud load based on the queueing theoretic approach. This model examines a bulk arrival and batch service queueing system, incorporating server overloading and underloading based on the queue length. In a batch service system, customers are served in groups following a general bulk service rule with the server operating between the minimum value ‘a’ and the maximum value ‘b’. But in certain situations, maintaining the same extreme values of the server is difficult, and it needs to be changed according to the service request. In this paper, server load balancing is introduced for a batch service queueing model, which is the capacity of the server that can be adjusted, either increased or decreased, based upon the service request by the customer. On service completion, if the service request is not enough to start any of the services, the server will be assigned to perform a secondary job (vacation). After vacation completion based upon the service request, the server will start regular service, overload or underload. Cloud computing using power BI can be analyzed based on server load balancing. The function that determines the probability of the queue size at any given time is derived for the specified queueing model using the supplementary variable technique with the remaining time as the supplementary variable. Additionally, various system characteristics are calculated and illustrated with suitable numerical examples.
Definition of Triangular Norms and Triangular Conorms on Subfamilies of Type-2 Fuzzy Sets
Authors: Hernández-Varela Pablo , Talavera Francisco Javier , Cubillo Susana , Torres-Blanc Carmen , Elorza Jorge
Published: December 2024

In certain stages of the application of a type-2 fuzzy logic system, it is necessary to perform operations between input or output fuzzy variables in order to compute the union, intersection, aggregation, complement, and so forth. In this context, operators that satisfy the axioms of t-norms and t-conorms are of particular significance, as they are applied to model intersection and union, respectively. Furthermore, the existence of a range of these operators allows for the selection of the t-norm or t-conorm that offers the optimal performance, in accordance with the specific context of the system. In this paper, we obtain new t-norms and t-conorms on some important subfamilies of the set of functions from [0,1] to [0,1]. The structure of these families provides a more solid algebraic foundation for the applications. In particular, we define these new operators on the subsets of the functions that are convex, normal, and normal and convex, as well as the functions taking only the values 0 or 1 and the subset of functions whose support is a finite union of closed intervals. These t-norms and t-conorms are generalized to the type-2 fuzzy set framework.
Mappings of a Bounded Dirichlet Integral: The Modulus Method
Authors: Cristea Mihai
Published: December 2024

We study the geometric properties of some classes of mappings for which an inverse Poletsky modular inequality holds. In these classes of mappings, we give some extensions of the theorems of Lindelőf and Fatou from the classical complex analysis. We also find some conditions for the existence of injective minimizers for mappings of biconformal energy.
Optimized Production of Fungal Polygalacturonase Using Cupuaçu (Theobroma grandiflorum) Peel as Substrate and Its Effect on Clarification of Cupuaçu Juice
Authors: Falcão Lucas de S. , Monteiro Trisha E. de A. , do Amaral Thaís S. , Azevedo Sthéfanny C. M. , Batista Bárbara N. , Jordão António M. , Albuquerque Patrícia M.
Published: December 2024

Pectinolytic enzymes play a key role in many beverages manufacturing processes, improving their clarification and filtration steps. Fungal pectinases are considered promising green catalysts for industrial applications, and they can be produced using fruit-processing residues as substrate. In this study, we investigated the optimal conditions to produce polygalacturonase from Aspergillus brasiliensis in a solid-phase bioprocess, using cupuaçu (Theobroma grandiflorum) peel as substrate. Then, the pectinolytic extract was applied in the clarification of cupuaçu juice. A central composite design was used to determine the optimal fungal cultivation conditions. Thus, the optimal fungal cultivation (maximum production of 11.81 U/g of polygalacturonase) was obtained using cupuaçu peel with 80% moisture, at 34 °C, for 7 days in a medium containing 4.2% phosphorus and 2.6% nitrogen. The enzymatic extract showed greater activity at 60 °C and stability at a pH range between 5.0 and 7.0. The pectinolytic extract was able to clarify the cupuaçu juice, causing a 53.95% reduction in its turbidity and maintaining its antioxidant activity. Our results demonstrate that the cupuaçu peel can be used as a substrate to produce polygalacturonase, and the enzymatic extract produced can be applied in the cupuaçu juice processing, contributing to the circular economy.
Automated Measurements of Tooth Size and Arch Widths on Cone-Beam Computerized Tomography and Scan Images of Plaster Dental Models
Authors: Nguyen Thong Phi , Ahn Jang-Hoon , Lim Hyun-Kyo , Kim Ami , Yoon Jonghun
Published: December 2024

Measurements of tooth size for estimating inter-arch tooth size discrepancies and inter-tooth distances, essential for orthodontic diagnosis and treatment, are primarily done using traditional methods involving plaster models and calipers. These methods are time-consuming and labor-intensive, requiring multiple steps. With advances in cone-beam computerized tomography (CBCT) and intraoral scanning technology, these processes can now be automated through computer analyses. This study proposes a multi-step computational method for measuring mesiodistal tooth widths and inter-tooth distances, applicable to both CBCT and scan images of plaster models. The first step involves 3D segmentation of the upper and lower teeth using CBCT, combining results from sagittal and panoramic views. For intraoral scans, teeth are segmented from the gums. The second step identifies the teeth based on an adaptively estimated jaw midline using maximum intensity projection. The third step uses a decentralized convolutional neural network to calculate key points representing the parameters. The proposed method was validated against manual measurements by orthodontists using plaster models, achieving an intraclass correlation coefficient of 0.967 and a mean absolute error of less than 1 mm for all tooth types. An analysis of variance test confirmed the statistical consistency between the method’s measurements and those of human experts.
Antibacterial Potential of Honeybee Venom and Monascus purpureus Extracellular Metabolites Against Multidrug-Resistant Pathogenic Bacteria
Authors: Teiba Islam I. , Mazrou Yasser S. A. , Makhlouf Abeer H. , Nehela Yasser , Mohamed Abdallah E. , Abbas Ahmed M. , Mamdouh Islam , El-Bilawy Emad H.
Published: December 2024

Antimicrobial resistance (AMR) poses a critical global health threat, driving the search for alternative treatments to conventional antibiotics. In this study, the antibacterial properties of honeybee venom (BV) and fungal Monascus purpureus red dye (RD) were evaluated against three multidrug-resistant bacterial pathogens. Extracts of BV and RD exhibited dose-dependent antibacterial activity against the three tested bacteria, with their strongest effectiveness against S. aureus (minimum inhibitory concentrations [MIC] = 3.18 and 6.315 μg·mL−1, respectively). Although the three bacterial strains were resistant to the antibiotic ampicillin-sulbactam (10/10 µg), both extracts exhibited superior antibacterial activity against the three bacterial strains compared to five standard antibiotics, especially RD extract, which produced the largest inhibition zone (20 ± 0.20 mm) against S. aureus. The larger inhibition zones against S. aureus suggest its high sensitivity, whereas E. coli and E. faecalis exhibited smaller inhibition zones, indicating less sensitivity to BV and RD extracts. Differences in the inhibition zones suggest the variations in antimicrobial activity between the two extracts and their strain-specific effectiveness. Scanning electron microscopy (SEM) revealed that BV and RD extracts disrupted the bacterial plasma membrane, suggesting that the bioactive compounds penetrate the bacterial cell wall and alter its integrity. Furthermore, GC–MS-based analysis revealed that the chemical composition of BV and RD extracts exhibited highly diverse structures, including complex polycyclic systems, porphyrins, steroids, and esters. For instance, 42 metabolites were identified in the BV extract, which mainly were organic and metal–organic compounds; however, only 23 molecules were identified in RD extract, which mainly were fatty acids and their derivatives. The diversity in the chemical compositions of both extracts highlights their potential applications in pharmaceuticals, materials, and biochemistry fields. Collectively, these findings indicate that honeybee venom and the red dye from M. purpureus have promising antibacterial properties and warrant further investigation as potential alternatives to conventional antibiotics. Further multi-ligand docking-based virtual screening studies are required to identify the most promising detected metabolite(s) within both BV and RD extracts.
The Role of the Gastrointestinal Microbiota in Parkinson’s Disease
Authors: Gabrielli Maurizio , Zileri Dal Verme Lorenzo , Zocco Maria Assunta , Nista Enrico Celestino , Ojetti Veronica , Gasbarrini Antonio
Published: December 2024

Background/Objectives: Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by the loss of dopaminergic neurons leading to debilitating motor and non-motor symptoms. Beyond its well-known neurological features, emerging evidence underscores the pivotal role of the gut–brain axis and gastrointestinal microbiota in PD pathogenesis. Dysbiosis has been strongly linked to PD and is associated with increased intestinal permeability, chronic inflammation, and the production of neurotoxic metabolites that may exacerbate neuronal damage. Methods: This review delves into the complex interplay between PD and dysbiosis, shedding light on two peculiar subsets of dysbiosis, Helicobacter pylori infection and small-intestinal bacterial overgrowth. These conditions may not only contribute to PD progression but also influence therapeutic responses such as L-dopa efficacy. Conclusions: The potential to modulate gut microbiota through probiotics, prebiotics, and synbiotics; fecal microbiota transplantation; and antibiotics represents a promising frontier for innovative PD treatments. Despite this potential, the current evidence is limited by small sample sizes and methodological variability across studies. Rigorous, large-scale, randomized placebo-controlled trials with standardized treatments in terms of composition, dosage, and duration are urgently needed to validate these findings and pave the way for microbiota-based therapeutic strategies in PD management.
Congenital Zika Syndrome: Insights from Integrated Proteomic and Metabolomic Analysis
Authors: Gomes-de-Pontes Leticia , Barreiros Lucila Akune , Gomes Lillian Nunes , Salgado Ranieri Coelho , da Silva Napoleão Sarah Maria , Soeiro-Pereira Paulo V. , Passos Saulo Duarte , Condino-Neto Antonio
Published: December 2024

Background: In this study, we investigated the role of extracellular vesicles (EVs) in the pathogenesis of Congenital Zika Syndrome (CZS). Previous studies have highlighted the role of EVs in intercellular communication and the modulation of biological processes during viral infections, motivating our in-depth analysis. Our objective was to identify specific molecular signatures in the EVs of patients with CZS, focusing on their potential as biomarkers and on cellular pathways affected by the infection. Methods: We conducted advanced proteomic and metabolomic analyses using mass spectrometry for protein and metabolite identification. EVs were isolated from CZS patient samples and control groups using Izon qEV size-exclusion chromatography columns. Results: The analyzed EVs presented distinct molecular profiles in patients with CZS. Proteomic analysis revealed significant alterations in specific proteins, suggesting involvement in the PI3K-AKT-mTOR pathway, while metabolomics highlighted metabolites related to critical processes in Zika virus pathogenesis. These findings suggest a key role for the PI3K-AKT-mTOR pathway in regulating cellular processes during infection and indicate the involvement of EVs in intercellular communication. Additionally, the results identified potential biomarkers capable of aiding early diagnosis and assessing disease progression. Conclusions: This study demonstrates that EVs play a crucial role in intercellular communication during Zika virus infection. The identification of specific alterations in the PI3K-AKT-mTOR pathway highlights a possible therapeutic target, providing new opportunities for the development of more effective treatment strategies for CZS. Our findings significantly advance the understanding of CZS and underscore the need for further investigations using advanced techniques to validate and explore these potential molecular targets.
VDAC1: A Key Player in the Mitochondrial Landscape of Neurodegeneration
Authors: Argueti-Ostrovsky Shirel , Barel Shir , Kahn Joy , Israelson Adrian
Published: December 2024

Voltage-Dependent Anion Channel 1 (VDAC1) is a mitochondrial outer membrane protein that plays a crucial role in regulating cellular energy metabolism and apoptosis by mediating the exchange of ions and metabolites between mitochondria and the cytosol. Mitochondrial dysfunction and oxidative stress are central features of neurodegenerative diseases. The pivotal functions of VDAC1 in controlling mitochondrial membrane permeability, regulating calcium balance, and facilitating programmed cell death pathways, position it as a key determinant in the delicate balance between neuronal viability and degeneration. Accordingly, increasing evidence suggests that VDAC1 is implicated in the pathophysiology of neurodegenerative diseases, including Alzheimer’s disease (AD), Parkinson’s disease (PD), amyotrophic lateral sclerosis (ALS), and others. This review summarizes the current findings on the contribution of VDAC1 to neurodegeneration, focusing on its interactions with disease-specific proteins, such as amyloid-β, α-synuclein, and mutant SOD1. By unraveling the complex involvement of VDAC1 in neurodegenerative processes, this review highlights potential avenues for future research and drug development aimed at alleviating mitochondrial-related neurodegeneration.
Disease-Associated Dopamine Receptor D2 Variants Exhibit Functional Consequences Depending on Different Heterotrimeric G-Protein Subunit Combinations
Authors: Niebrügge Nele , Trovato Olga , Praschberger Roman , Lieb Andreas
Published: December 2024

Background: Dopamine receptors (DRs) are G-protein-coupled receptors (GPCRs) found in the central nervous system (CNS). DRs are essential for mediating various downstream signaling cascades and play a critical role in regulating the dopaminergic nigrostriatal pathway, which is involved in motor control. Recently, mutations in DRD2 (WT), p.Ile212Phe (I212F), and p.Met345Arg (M345R) have been associated with hyperkinetic movement disorders and shown to alter heterotrimeric G-protein complex signaling and β-arrestin recruitment. Methods: To conduct a detailed investigation of the I212F and M345R functional phenotypes, we used the TRansdUcer PATHway (TRUPATH) assay to study heterotrimeric G-protein recruitment and the Parallel Receptorome Expression and Screening via Transcriptional Output (PRESTO-Tango) assay to evaluate transcriptional activation following arrestin translocation for β-arrestin recruitment. Results: In our study, we could confirm the reported mutant’s loss-of-function phenotype in β-arrestin 2 recruitment (reduced agonist potency and decreased maximal signaling efficacy in comparison to the WT). However, a detailed analysis of basal/constitutive activity also revealed a gain-of-function phenotype for mutant M345R. For a more comprehensive investigation of heterotrimeric G-protein complex signaling, we investigated the impact of WT mutants in combination with (i) a specifically suggested assay, and (ii) the most abundantly expressed heterotrimeric G-protein complex combinations in WT receptor-enriched regions. We were able to confirm the reported gain-of-function phenotype by Rodriguez-Contreras et al. and extend it by the use of the most abundant heterotrimeric G-protein subunits, GαoA and Gαi1, β1 and β2, and γ3 and γ7, in mouse and human basal ganglia. Conclusions: Although our results indicate that the interaction of the two variants with the most highly expressed heterotrimeric G-protein complex subunit combinations also results in a gain-of-function phenotype, they also clearly demonstrate that the phenotype can be significantly altered, dependent on heterotrimeric G-protein complex expression.
Exploring the Molecular Modalities in the Pathogenesis of Diabetic Kidney Disease with a Focus on the Potential Therapeutic Implications
Authors: Gaydarski Lyubomir , Petrova Kristina , Angushev Ivan , Stanchev Stancho , Iliev Alexandar , Stamenov Nikola , Kirkov Vidin , Landzhov Boycho
Published: December 2024

Diabetic kidney disease (DKD) is a leading cause of chronic kidney disease (CKD) and end-stage renal disease worldwide, affecting approximately 40% of individuals with type 2 diabetes (T2DM) and 30% of those with type 1 diabetes (T1DM). As the prevalence of diabetes continues to rise, the burden of DKD is expected to grow correspondingly. This review explores the roles of key molecular pathways, including the apelinergic system, vascular endothelial growth factor (VEGF)/VEGF receptor (VEGFR) axis, and nitric oxide (NO)/nitric oxide synthase (NOS) signaling, in DKD pathogenesis and potential therapeutic applications. The apelinergic system, involving apelin and its receptor (APLNR), influences endothelial function, glucose metabolism, and renal health. Preclinical studies highlight its dual role in renal protection and injury through anti-inflammatory and antioxidant pathways, while other evidence suggests that it may exacerbate DKD through podocyte damage and angiogenesis. Similarly, the VEGF/VEGFR axis demonstrates a complex contribution to DKD, where VEGF-A promotes pathological angiogenesis and glomerular damage, but its inhibition requires careful modulation to prevent adverse effects. The NO/NOS system, integral to vascular and renal homeostasis, also exhibits altered activity in DKD, with reduced bioavailability linked to oxidative stress and inflammation. This review underscores the intricate interplay between these pathways in DKD, revealing both challenges and opportunities in their therapeutic targeting. Further research is essential to refine strategies and develop effective interventions for DKD management.
The Identification of Molecular Ploidy Status of Abnormal Pronuclear Zygotes Reveals a Significant Number of Euploid Blastocysts Available for Conception
Authors: McCallie Blair R. , Haywood Mary E. , Henry Lauren N. , Lee Rachel M. , Schoolcraft William B. , Katz-Jaffe Mandy G.
Published: December 2024

Objective: Abnormally fertilized embryos are often discarded during in vitro fertilization due to the fact that known chromosomal ploidy abnormalities lead to implantation failure or pregnancy loss. The objective of this study was to determine if pronuclear numeration (PN) observed at fertilization check is representative of the true ploidy status of the subsequent developing blastocyst in order to maximize the number of viable embryos available for infertility patients and increase their chances of conception. Methods: Upon successful fertilization, pronuclear numeration was noted, and zygotes were cultured to the blastocyst stage. Biopsied trophectoderm cells were then lysed, and the isolated DNA was whole-genome amplified followed by library preparation. Next-generation sequencing was performed for PGT-A, and excess whole-genome amplified DNA was utilized for single nucleotide polymorphism beadchip array analysis. Results: At the time of fertilization check on day 1 of embryo development, when there were no visible pronuclei (n = 291), 56% of these 0PN blastocysts were confirmed to be diploid and normally fertilized. The remaining 41.9% were aneuploid, and 2.1% of the 0PN blastocysts contained only 23 haploid chromosomes. Upon analysis of the 1PN blastocysts (n = 217), just over a third (36.4%) only contained 23 haploid chromosomes (23XO), with another third (31.8%) identified as aneuploid, and surprisingly, the remaining third (31.8%) confirmed to be diploid and normally fertilized. In contrast, 50% of the 3PN blastocysts (n = 172) showed the presence of a third set of 23 parental chromosomes and were confirmed to be triploid (69XXY = 59.3% and 69XXX = 40.7%), with 41.9% identified as aneuploid and, interestingly, a small percentage (8.1%) confirmed to be diploid with normal fertilization. A very small proportion of biopsied blastocysts (0.63%) displaying the correct number of pronuclei for normal fertilization (2PN) were also identified as triploid with a third set of 23 parental chromosomes. To date, there have been 74 euploid embryo transfers from zygotes originally identified with an alternate pronuclear numeration, resulting in 16 ongoing pregnancies and 32 healthy live births, rates that match those typically observed with normally fertilized 2PN zygotes (>60%). Conclusions: A surprising number of blastocysts that were identified to have alternate pronuclear numeration at fertilization check on day 1 of embryo development were actually determined to be diploid with normal fertilization after molecular analysis. Accurate identification of haploid and tripoid zygotes is critical to prevent implantation failure and pregnancy loss and allows for the identification of all euploid embryos in a cohort, which has the potential to increase cumulative live birth rates for infertility patients.
Association of Circulating Neprilysin with BMI, Cardiovascular Health, and Kidney Function in High-Risk Pregnancies: A Pilot Study
Authors: Hasani Kaltrina Kutllovci , Kulovic-Sissawo Azra , Saloň Adam , Stern Christina , Mayer-Pickel Karoline , Cervar-Zivkovic Mila , Goswami Nandu , Fluhr Herbert , Hiden Ursula
Published: December 2024

Background/Objectives: Inadequate cardiovascular adaptation during pregnancy impairs endothelial function and vascular resistance, contributing to complications such as pre-eclampsia (PE) and gestational hypertension (GH). Neprilysin (NEP), a protease involved in vascular regulation, has been linked to PE, but its role in endothelial function and vascular adaptation remains unclear. This pilot study investigates the associations between soluble neprilysin (sNEP) and markers of vascular and renal function in high-risk pregnancies without PE. Methods: Observed parameters were analyzed in 29 high-risk pregnant women across early, mid-, and late pregnancy. sNEP levels were analyzed alongside body mass index (BMI), endothelial dysfunction (ADMA), arterial stiffness (pulse wave velocity, PWV), retinal microvasculature (central retinal arteriolar and venular equivalents, CRAE and CRVE), and kidney function markers. The impact of gestational hypertension (GH) and prior smoking on sNEP levels was also evaluated. Results: In early and mid-pregnancy, sNEP was inversely associated with BMI. During mid-pregnancy, sNEP showed a positive correlation with CRAE and an inverse correlation with PWV, suggesting reduced arterial stiffness. By late pregnancy, sNEP was positively associated with glomerular filtration rate and inversely correlated with creatinine and protein levels, reflecting improved kidney function. Women with GH exhibited elevated sNEP, while former smokers had lower sNEP levels in early pregnancy. Conclusions: These findings suggest that sNEP plays a role in vascular and renal adaption during pregnancy, offering new perspectives on vascular tone regulation in high-risk pregnancies. Further research is needed to clarify these mechanisms and their clinical relevance.
High-Performance Photocatalytic Multifunctional Material Based on Bi4Ti3O12-Supported Ag and Ti3C2Tx for Organic Degradation and Antibacterial Applications
Authors: Zhang Kexi , Yan Bingdong , Wang Xiaohong , Cao Yang , Hao Wanjun , Tu Jinchun
Published: December 2024

With the rapid development of modern science and technology and the diversification of social needs, traditional single-performance materials struggle to meet the complex and changeable application scenarios. To address the multifaceted requirements of biomedical applications, such as disease diagnosis and treatment, scientists are dedicated to developing new multifunctional biomaterials with multiple activities. Bi4Ti3O12 (BTO), despite its versatility and application potential, has insufficient photocatalytic performance. Silver nanoparticles (Ag) and Ti3C2Tx are particularly effective as antibacterial materials but they have relatively single functions. In this study, BTO/Ag/Ti3C2Tx biomultifunctional materials were constructed by combining BTO with Ag and Ti3C2Tx. We discovered that the addition of Ag and Ti3C2Tx effectively optimized the visible light absorption characteristics of BTO, reduced the electron transfer resistance, and increased the carrier concentration, thus significantly improving the photocatalytic performance of composite material, thereby markedly improving the composite’s photocatalytic performance and its efficacy in photochemical sensing and photodegradation. At the same time, BTO, as a carrier, effectively avoids Ag and Ti3C2Tx agglomeration and gives full play to its antibacterial properties. In the specific performance studies, ascorbic acid and MB were used as the subjects of photochemical sensing and photodegradation properties, while Escherichia coli and Staphylococcus aureus were tested for antibacterial properties. The BTO/Ag/Ti3C2Tx composite showed remarkable results in all assessments, demonstrating its potential as a versatile antibacterial and photocatalytic material.
Role of Virtual iMRI in Glioblastoma Surgery: Advantages, Limitations, and Correlation with iCT and Brain Shift
Authors: Grasso Erica , Certo Francesco , Ganau Mario , Bonomo Giulio , Fiumanò Giuseppa , Buscema Giovanni , Maugeri Andrea , Agodi Antonella , Barbagallo Giuseppe M. V.
Published: December 2024

Background: Elastic image fusion (EIF) using an intraoperative CT (iCT) scan may enhance neuronavigation accuracy and compensate for brain shift. Objective: To evaluate the safety and reliability of the EIF algorithm (Virtual iMRI Cranial 4.5, Brainlab AG, Munich Germany, for the identification of residual tumour in glioblastoma surgery. Moreover, the impact of brain shift on software reliability is assessed. Methods: This ambispective study included 80 patients with a diagnosis of glioblastoma. Pre-operative MRI was elastically fused with an intraoperative CT scan (BodyTom; Samsung-Neurologica, Danvers, MA, USA) acquired at the end of the resection. Diagnostic specificity and the sensitivity of each tool was determined. The impact of brain shift on residual tumour was statistically analysed. An analysis of accuracy was performed through Target Registration Error (TRE) measurement after rigid image fusion (RIF) and EIF. A qualitative evaluation of each Virtual MRI image (VMRI) was performed. Results: VMRI identified residual tumour in 26/80 patients (32.5%), confirmed by post-operative MRI (true positive). Of these, 5 cases were left intentionally due to DES-positive responses, 8 cases underwent near maximal or subtotal resection, and 13 cases were not detected by iCT. However, in the other 27/80 cases (33.8%), VMRI reported residual tumour that was present neither on iCT nor on post-operative MRI (false positive). i-CT showed a sensitivity of 56% and specificity of 100%; VMRI demonstrated a sensitivity of 100% and specificity of 50%. Spearman correlation analysis showed a moderate correlation between pre-operative volume and VMRI tumour residual. Moreover, tumour involving insula or infiltrating more than one lobe displayed higher median values (p = 0.023) of virtual residual tumour. A statistically significant reduction towards lower TRE values after EIF was observed for test structures. Conclusions: Virtual iMRI was proven to be a feasible option to detect residual tumour. Its integration within a multimodal imaging protocol may provide neurosurgeons with intraoperatively updated imaging.