bluuebunny/crossref_metadata_2025 huggingface dataset:
Fd-CasBGRel: A Joint Entity–Relationship Extraction Model for Aquatic Disease Domains
Authors: Ye Hongbao , Lv Lijian , Zhou Chengquan , Sun Dawei
Published: July 2024

Entity–relationship extraction plays a pivotal role in the construction of domain knowledge graphs. For the aquatic disease domain, however, this relationship extraction is a formidable task because of overlapping relationships, data specialization, limited feature fusion, and imbalanced data samples, which significantly weaken the extraction’s performance. To tackle these challenges, this study leverages published books and aquatic disease websites as data sources to compile a text corpus, establish datasets, and then propose the Fd-CasBGRel model specifically tailored to the aquatic disease domain. The model uses the Casrel cascading binary tagging framework to address relationship overlap; utilizes task fine-tuning for better performance on aquatic disease data; trains on specialized aquatic disease corpora to improve adaptability; and integrates the BRC feature fusion module—which incorporates self-attention mechanisms, BiLSTM, relative position encoding, and conditional layer normalization—to leverage entity position and context for enhanced fusion. Further, it replaces the traditional cross-entropy loss function with the GHM loss function to mitigate category imbalance issues. The experimental results indicate that the F1 score of the Fd-CasBGRel on the aquatic disease dataset reached 84.71%, significantly outperforming several benchmark models. This model effectively addresses the challenges of ternary extraction’s low performance caused by high data specialization, insufficient feature integration, and data imbalances. The model achieved the highest F1 score of 86.52% on the overlapping relationship category dataset, demonstrating its robust capability in extracting overlapping data. Furthermore, We also conducted comparative experiments on the publicly available dataset WebNLG, and the model in this paper obtained the best performance metrics compared to the rest of the comparative models, indicating that the model has good generalization ability.
Investigation Lubricity Performance of Lubricating Oil Used in Marine Diesel Engine—Fuel Injection Pump
Authors: Kaminski Piotr
Published: July 2024

Diesel engines commonly suffer from oil contamination by fuel and other chemicals during operation and maintenance. This contamination alters the oil’s lubricating properties, leading to increased wear, corrosion, and other potential problems. Therefore, it is crucial to understand how oil degrades and becomes contaminated due to different replacement strategies is crucial for both engine operators and manufacturers. This study focuses on the impact of fuel dilution on specific properties of engine oil under real-world operating conditions in a marine diesel engine. Oil samples were collected regularly from the crankcase of the engine fuel injection pump and tribological tests were performed. These tests aimed to assess how marine gas oil affects the oil lubricity performance and how it maintains its useful life. The results confirm that diesel dilution primarily affects the oil lubricating abilities as well as overall performance.
Coordinated Control Method for Unequal-Cycle Adjacent Intersections Using Vehicle–Road Collaboration
Authors: Lian Peikun , Bao Riyong , Zhang Kangyi , Easa Said M. , Jiang Zhengyi , Chen Ning
Published: July 2024

In areas with significant changes in traffic demand and high vehicle dispersion at adjacent intersections, such as the surrounding roads of large shopping malls and schools, traffic problems are prone to occur. This is due to the unequal signal cycle lengths used at upstream and downstream intersections, which lead to periodic phase offsets as the cycles progress. To address this, we propose a multi-strategy integrated vehicle–road coordinated control method to tackle traffic flow operational issues caused by the offset characteristics of unequal-cycle adjacent intersections. A multi-strategy combined algorithm and control logic is established, which includes downstream intersection coordinated phase green extension, dynamic offset adjustment, and transitional queue speed guidance. The proposed method can substantially minimize the offset from falling into an incompatible threshold, effectively reducing queuing and early arrival of vehicles in the straight-through direction. It enables arriving vehicles to pass through the intersection without or with minimal stopping. Finally, the effectiveness of the method is validated using simulation experiments. A vehicle–road coordinated simulation verification platform was established, and comparative experiments were designed. The results indicate that the multi-strategy combined vehicle–road coordinated control method proposed in this paper, while ensuring the original through capacity for straight movements, can effectively reduce queue lengths, the number of stops, average vehicle delay, and travel time for single-direction straight lanes. This improvement enhances the efficiency of coordinated movements in the unequal–cycle adjacent intersections.
Research on Student Classroom Behavior Detection Based on the Real-Time Detection Transformer Algorithm
Authors: Lin Lihua , Yang Haodong , Xu Qingchuan , Xue Yanan , Li Dan
Published: July 2024

With the rapid development of artificial intelligence and big data technology, intelligent education systems have become a key research focus in the field of modern educational technology. This study aims to enhance the intelligence level of educational systems by accurately detecting student behavior in the classroom using deep learning techniques. We propose a method for detecting student classroom behavior based on an improved RT DETR (Real-Time Detection Transformer) object detection algorithm. By combining actual classroom observation data with AI-generated data, we create a comprehensive and diverse student behavior dataset (FSCB-dataset). This dataset not only more realistically simulates the classroom environment but also effectively addresses the scarcity of datasets and reduces the cost of dataset construction. The study introduces MobileNetV3 as a lightweight backbone network, reducing the model parameters to one-tenth of the original while maintaining nearly the same accuracy. Additionally, by incorporating learnable position encoding and dynamic upsampling techniques, the model significantly improves its ability to recognize small objects and complex scenes. Test results on the FSCB-dataset show that the improved model achieves significant improvements in real-time performance and computational efficiency. The lightweight network is also easy to deploy on mobile devices, demonstrating its practicality in resource-constrained environments.
Hazardous High-Energy Seismic Event Discrimination Method Based on Region Division and Identification of Main Impact Factors: A Case Study
Authors: Liu Yaoqi , Cao Anye , Wang Qiang , Li Geng , Yang Xu , Wang Changbin
Published: July 2024

An investigation of risk factors has been identified as a crucial aspect of the routine management of rockburst. However, the identification methods for principal impact factors and the examination of the relationship between seismic energy and other source parameters have not been extensively explored to conduct dynamic risk management. This study aims to quantify impact risk factors and discriminate hazardous high-energy seismic events. The analytic hierarchy process (AHP) and entropy weight method (EWM) are utilized to ascertain the primary control factors based on geotechnical data and nearly two months of seismic data from a longwall panel. Furthermore, the distribution law and correlation relationship among seismic source parameters are systematically analyzed. Results show that the effect of coal depth, coal seam thickness, coal dip, and mining speed covers the entire mining process, while the fault is only prominent in localized areas. There are varying degrees of log-positive correlations between seismic energy and other source parameters, and this positive correlation is more pronounced for hazardous high-energy seismic events. Utilizing the linear logarithmic relationship between seismic energy and other source parameters, along with the impact weights of dynamic risks, the comprehensive energy index for evaluating high-energy seismic events is proposed. The comprehensive energy index identification method proves to be more accurate by comparing with the high-energy seismic events based on energy criteria. The limitations and improvements of this method are also synthesized to obtaining a wide range of applications.
Management of Plastic Wastes through Recent Advanced Pyrolysis Processes
Authors: Shareefdeen Zarook , ElGazar Aya Tarek
Published: July 2024

Plastics are predominant in numerous sectors like packaging, agriculture, hardware, electronics, and many others. Annual plastic demand has been rapidly growing in the last few decades because of the increasing dependency on plastics. As a consequence, massive amounts of plastic waste are being generated every year. These plastic wastes are non-biodegradable, and hence their disposal poses a serious threat to the ecosystem and causes significant environmental problems such as endangering the safety of marine life, wildlife, air, water, and soil, etc. A large portion of plastic waste ends up in landfills, and only a small fraction is recycled. The continuous dependence on landfills as the main disposal method for plastic waste is costly and ineffective. Common solutions to plastic waste management are incineration and recycling; however, incineration emits harmful pollutants and greenhouse gases that contribute to ozone layer depletion and global warming; moreover, recycling is expensive and inefficient. As an alternative to recycling and incineration, the pyrolysis process can convert plastic wastes into more valuable fuel products. Pyrolysis is a thermal process that converts raw material into pyrolysis liquid, solid wax, and non-condensable gases in the absence of oxygen. This process is attractive because it is economical and energy-efficient, and it can be used to convert various types of plastic waste into valuable products. In recent years, there have been significant developments in pyrolysis applications in liquid fuel production from plastic wastes. This work reviews recent advances in and challenges for the pyrolysis process for converting plastic wastes into a valuable alternative fuel, focusing on studies of advanced pyrolysis processes published over the last five years. The paper also highlights the numerical modeling of pyrolysis of plastic wastes and the potential impact of pyrolysis on the future of sustainable waste-management practices of plastics.
Entity-Alignment Interaction Model Based on Chinese RoBERTa
Authors: Feng Ping , Zhang Boning , Yang Lin , Feng Shiyu
Published: July 2024

Entity alignment aims to match entities with the same semantics from different knowledge graphs. Most existing studies use neural networks to combine graph-structure information and additional entity information (such as names, descriptions, images, and attributes) to achieve entity alignment. However, due to the heterogeneity of knowledge graphs, aligned entities often do not have the same neighbors, which makes it difficult to utilize the structural information from knowledge graphs and results in a decrease in alignment accuracy. Therefore, in this paper, we propose an interaction model that exploits only the additional information on entities. Our model utilizes names, attributes, and neighbors of entities for interaction and introduces attention interaction to extract features to further evaluate the matching scores between entities. Our model is applicable to Chinese datasets, and experimental results show that it has achieved good results on the Chinese medical datasets denoted MED-BBK-9K.
Layer Contour Geometric Characterization in MEX/P through CIS-Based Adaptive Edge Detection
Authors: Fernández Alejandro , Blanco David , Álvarez Braulio J. , Fernández Pedro , Zapico Pablo , Valiño Gonzalo
Published: July 2024

The industrial adoption of material extrusion of polymers (MEX/P) is hindered by the geometric quality of manufactured parts. Contact image sensors (CISs), commonly used in flatbed scanners, have been proposed as a suitable technology for layer-wise characterization of contour deviations, paving the way for the application of corrective measures. Nevertheless, despite the high resolution of CIS digital images, the accurate characterization of layer contours in MEX/P is affected by contrast patterns between the layer and the background. Conventional edge-recognition algorithms struggle to comprehensively characterize layer contours, thereby diminishing the reliability of deviation measurements. In this work, we introduce a novel approach to precisely locate contour points in the context of MEX/P based on evaluating the similarity between the grayscale pattern near a particular tentative contour point and a previously defined gradient reference pattern. Initially, contrast patterns corresponding to various contour orientations and layer-to-background distances are captured. Subsequently, contour points are identified and located in the images, with coordinate measuring machine (CMM) verification serving as a ground truth. This information is then utilized by an adaptive edge-detection algorithm (AEDA) designed to identify boundaries in manufactured layers. The proposed method has been evaluated on test targets produced through MEX/P. The results indicate that the average deviation of point position compared to that achievable with a CMM in a metrology laboratory ranges from 8.02 µm to 13.11 µm within the experimental limits. This is a substantial improvement in the reliability of contour reconstruction when compared to previous research, and it could be crucial for implementing routines for the automated detection and correction of geometric deviations in AM parts.
Borehole Breakout Prediction Based on Multi-Output Machine Learning Models Using the Walrus Optimization Algorithm
Authors: Zhang Rui , Zhou Jian , Tao Ming , Li Chuanqi , Li Pingfeng , Liu Taoying
Published: July 2024

Borehole breakouts significantly influence drilling operations’ efficiency and economics. Accurate evaluation of breakout size (angle and depth) can enhance drilling strategies and hold potential for in situ stress magnitude inversion. In this study, borehole breakout size is approached as a complex nonlinear problem with multiple inputs and outputs. Three hybrid multi-output models, integrating commonly used machine learning algorithms (artificial neural networks ANN, random forests RF, and Boost) with the Walrus optimization algorithm (WAOA) optimization techniques, are developed. Input features are determined through literature research (friction angle, cohesion, rock modulus, Poisson’s ratio, mud pressure, borehole radius, in situ stress), and 501 related datasets are collected to construct the borehole breakout size dataset. Model performance is assessed using the Pearson Correlation Coefficient (R2), Mean Absolute Error (MAE), Variance Accounted For (VAF), and Root Mean Squared Error (RMSE). Results indicate that WAOA-ANN exhibits excellent and stable prediction performance, particularly on the test set, outperforming the single-output ANN model. Additionally, SHAP sensitivity analysis conducted on the WAOA-ANN model reveals that maximum horizontal principal stress (σH) is the most influential parameter in predicting both the angle and depth of borehole breakout. Combining the results of the studies and analyses conducted, WAOA-ANN is considered to be an effective hybrid multi-output model in the prediction of borehole breakout size.
A Novel Technosol Formulation for Sustainable Landfill Top Covers Using Non-Hazardous Wastes
Authors: Fernández-Caliani Juan Carlos , Álvarez-Lozano Julia , García-Navarro Encarnación , Fernández-Landero Sandra , Cantero Cristóbal , Giráldez María Inmaculada
Published: July 2024

This study explores the potential of non-hazardous wastes for crafting an engineered soil-like material (Technosol) suitable for landfill capping applications. Three distinct materials—waste foundry sand (WFS), washing aggregate sludge (WAS), and composted biosolids (CBS)—were strategically combined to develop this innovative Technosol. The formulation process involved a comprehensive analysis of their physical–chemical properties, mineral composition, leachate quality, and a series of geotechnical assessments to ensure compliance with landfill top cover construction standards. The blend 90WFS/10WAS showed optimal geotechnical properties for constructing a protective layer, including maximum dry density (1.77 g cm−3), void ratio (0.4), CBR index (23.2), cohesive strength (40 kPa), internal friction (ϕ = 30°), and permeability coefficient (k = 1.48 × 10−6 cm s−1). Further enhancement was achieved by adding 10% CBS, resulting in the development of a functional organo-mineral topsoil horizon (81WFS/9WAS/10CBS). Importantly, leachate analysis confirmed the negligible environmental footprint of this Technosol. Moreover, a pot-based experiment with Brassica juncea planting validated its capacity to support plant growth and establish a vegetative cover on the landfill surface.
Postcards and Emotions: Modernist Architecture in the Films of Pedro Almodóvar and Woody Allen
Authors: Romero Santos Rubén , Mejón Ana , Herrero Bernal Begoña , Ciller Carmen
Published: July 2024

Modernism has emerged as the preeminent iconic representation of Barcelona. However, the process through which this peculiar style has attained its iconic status is an arduous and multifaceted endeavor. This paper examines the challenges inherent in the categorization and periodization of Modernisme, followed by a succinct review of its initial filmic representations, culminating in a comprehensive analysis of two films in which Modernisme assumes a pivotal role: All About My Mother (Pedro Almodóvar 1999) and Vicky Cristina Barcelona (Woody Allen 2008). We conclude that Modernisme’s transformation into a cultural brand is largely attributable to the erosion of its ideological component in favor of a touristic and globalizing gaze.
Modeling Data with Extreme Values Using Three-Spliced Distributions
Authors: Bâcă Adrian , Vernic Raluca
Published: July 2024

When data exhibit a high frequency of small to medium values and a low frequency of large values, fitting a classical distribution might fail. This is why spliced models defined from different distributions on distinct intervals are proposed in the literature. In contrast to the intensive study of two-spliced distributions, the case with more than two components is scarcely approached. In this paper, we focus on three-spliced distributions and on their ability to improve the modeling of extreme data. For this purpose, we consider a popular insurance data set related to Danish fire losses, to which we fit several three-spliced distributions; moreover, the results are compared to the best-fitted two-spliced distributions from previous studies.
Stability of Fixed Points of Partial Contractivities and Fractal Surfaces
Authors: Navascués María A.
Published: July 2024

In this paper, a large class of contractions is studied that contains Banach and Matkowski maps as particular cases. Sufficient conditions for the existence of fixed points are proposed in the framework of b-metric spaces. The convergence and stability of the Picard iterations are analyzed, giving error estimates for the fixed-point approximation. Afterwards, the iteration proposed by Kirk in 1971 is considered, studying its convergence, stability, and error estimates in the context of a quasi-normed space. The properties proved can be applied to other types of contractions, since the self-maps defined contain many others as particular cases. For instance, if the underlying set is a metric space, the contractions of type Kannan, Chatterjea, Zamfirescu, Ćirić, and Reich are included in the class of contractivities studied in this paper. These findings are applied to the construction of fractal surfaces on Banach algebras, and the definition of two-variable frames composed of fractal mappings with values in abstract Hilbert spaces.
On Some New Dynamic Hilbert-Type Inequalities across Time Scales
Authors: Zakarya Mohammed , Saied Ahmed I. , Al-Thaqfan Amirah Ayidh I , Ali Maha , Rezk Haytham M.
Published: July 2024

In this article, we present some novel dynamic Hilbert-type inequalities within the framework of time scales T. We achieve this by utilizing Hölder’s inequality, the chain rule, and the mean inequality. As specific instances of our findings (when T=N and T=R), we obtain the discrete and continuous analogues of previously established inequalities. Additionally, we derive other inequalities for different time scales, such as T=qN0 for q>1, which, to the best of the authors’ knowledge, is a largely novel conclusion.
Comparison of Transcranial Magnetic Stimulation Dosimetry between Structured and Unstructured Grids Using Different Solvers
Authors: Camera Francesca , Merla Caterina , De Santis Valerio
Published: July 2024

In recent years, the interest in transcranial magnetic stimulation (TMS) has surged, necessitating deeper understanding, development, and use of low-frequency (LF) numerical dosimetry for TMS studies. While various ad hoc dosimetric models exist, commercial software tools like SimNIBS v4.0 and Sim4Life v7.2.4 are preferred for their user-friendliness and versatility. SimNIBS utilizes unstructured tetrahedral mesh models, while Sim4Life employs voxel-based models on a structured grid, both evaluating induced electric fields using the finite element method (FEM) with different numerical solvers. Past studies primarily focused on uniform exposures and voxelized models, lacking realism. Our study compares these LF solvers across simplified and realistic anatomical models to assess their accuracy in evaluating induced electric fields. We examined three scenarios: a single-shell sphere, a sphere with an orthogonal slab, and a MRI-derived head model. The comparison revealed small discrepancies in induced electric fields, mainly in regions of low field intensity. Overall, the differences were contained (below 2% for spherical models and below 12% for the head model), showcasing the potential of computational tools in advancing exposure assessment required for TMS protocols in different bio-medical applications.
Effect of Sextant Fixating Angle of Spiral Clavicle Plate on Biomechanical Stability—A Preliminary Finite Element Study
Authors: Hu Ming-Hsien , Su Po-Feng , Lin Kun-Jhih , Chen Wen-Chuan , Wang Shun-Ping
Published: July 2024

Introduction: A spiral clavicle plate has been accepted for its superior multidirectional compatibility in the treatment of midshaft clavicle fractures from a biomechanical perspective. However, the influence of the sextant angle (spiral level) definition on biomechanical performance has not been clarified. A conceptual finite element analysis was conducted to identify the advantages and drawbacks of spiral clavicle plates with various sextant angle definitions. Methods: Conventional superior and three different conceptual spiral plates with sextant angle definitions ranging from 45 to 135 degrees were constructed to restore an OTA 15-B1.3 midshaft clavicle fracture model. Three major loading scenarios (cantilever downward bending, axial compression, and axial torsion) were simulated to evaluate the reconstructed structural stiffness and the stress on the clavicle plate and bone screws. Results: The spiral clavicle plate demonstrated greater capability in resisting cantilever downward bending with an increase in sextant angle and showed comparable structural stiffness and implant stress compared to the superior clavicle plate. However, weakened resistance to axial compression load was noted for the spiral clavicle plate, with lowered stiffness and increased stress on the clavicle plate and screws as the spiral level increased. Conclusion: The spiral clavicle plate has been reported to offer multidirectional compatibility for the treatment of midshaft clavicle fractures, as well as geometric advantages in anatomical matching and reduced skin prominence after surgery. The current study supports that remarkable cantilever bending strength can be achieved with this plate. However, users must consider the potential drawback of lowered axial compression resistance in safety considerations.
Discriminant Input Processing Scheme for Self-Assisted Intelligent Healthcare Systems
Authors: Medani Mohamed , Alsubai Shtwai , Min Hong , Dutta Ashit Kumar , Anjum Mohd
Published: July 2024

Modern technology and analysis of emotions play a crucial role in enabling intelligent healthcare systems to provide diagnostics and self-assistance services based on observation. However, precise data predictions and computational models are critical for these systems to perform their jobs effectively. Traditionally, healthcare monitoring has been the primary emphasis. However, there were a couple of negatives, including the pattern feature generating the method’s scalability and reliability, which was tested with different data sources. This paper delves into the Discriminant Input Processing Scheme (DIPS), a crucial instrument for resolving challenges. Data-segmentation-based complex processing techniques allow DIPS to merge many emotion analysis streams. The DIPS recommendation engine uses segmented data characteristics to sift through inputs from the emotion stream for patterns. The recommendation is more accurate and flexible since DIPS uses transfer learning to identify similar data across different streams. With transfer learning, this study can be sure that the previous recommendations and data properties will be available in future data streams, making the most of them. Data utilization ratio, approximation, accuracy, and false rate are some of the metrics used to assess the effectiveness of the advised approach. Self-assisted intelligent healthcare systems that use emotion-based analysis and state-of-the-art technology are crucial when managing healthcare. This study improves healthcare management’s accuracy and efficiency using computational models like DIPS to guarantee accurate data forecasts and recommendations.
The Effects of Khat Chewing among Djiboutians: Dental Chemical Studies, Gingival Histopathological Analyses and Bioinformatics Approaches
Authors: Mohamed Abdoul-Latif Fatouma , Ainane Ayoub , Merito Ali , Houmed Aboubaker Ibrahim , Mohamed Houda , Cherroud Sanaa , Ainane Tarik
Published: July 2024

This study examined the effects of khat chewing on oral gingival conditions by adopting a targeted process which combined physicochemical analyses of the teeth, histopathological examinations of the gums, and bioinformatics modeling. The physicochemical evaluation of teeth in khat consumers compared to non-consumers was carried out using specific analytical techniques; hence, the results of this initial investigation revealed significant erosion of the tooth enamel due to khat chewing, as well as an alteration of the essential chemical composition of the teeth. Additionally, the histopathological analyses complemented preliminary studies by showing severe inflammation of the gums and oral mucosa in khat users. The understanding of these studies was enriched by bioinformatics analysis, where modeling was carried out via computational methods. This analytical phase examined molecular docking mechanisms, including the interaction between cathinone, the main alkaloid of khat, and the protein receptors involved in the protection of gingival tissues against infections. In summary, this multidisciplinary research provided an in-depth view of the oral health issues related to khat chewing, combining experimental studies with bioinformatics perspectives.
The Utility of the Koala Scat: A Scoping Review
Authors: Johnston Stephen D. , Hulse Lyndal , Keeley Tamara , Mucci Albano , Seddon Jennifer , Maynard Sam
Published: July 2024

The use of samples or scats to provide important ecological, genetic, disease and physiology details on free-range populations is gaining popularity as an alternative non-invasive methodology. Koala populations in SE Queensland and NSW have recently been listed as endangered and continue to face anthropomorphic and stochastic environmental impacts that could potentially lead to their extinction. This scoping review examines the current and potential utility of the koala scat to contribute data relevant to the assessment of koala conservation status and decision making. Although we demonstrate that there is great potential for this methodology in providing details for both individual wild animal and population biology (distribution, abundance, sex ratio, immigration/emigration, genetic diversity, evolutionary significant unit, disease epidemiology, nutrition, reproductive status and stress physiology), the calibre of this information is likely to be a function of the quality of the scat that is sampled.
Metformin Restrains the Proliferation of CD4+ T Lymphocytes by Inducing Cell Cycle Arrest in Normo- and Hyperglycemic Conditions
Authors: Cartes-Velásquez Ricardo , Vera Agustín , Antilef Bárbara , Sanhueza Sergio , Lamperti Liliana , González-Ortiz Marcelo , Nova-Lamperti Estefanía
Published: July 2024

CD4+ T lymphocytes play a key role in the modulation of the immune response by orchestrating both effector and regulatory functions. The effect of metformin on the immunometabolism of CD4+ T lymphocytes has been scarcely studied, and its impact under high glucose conditions, particularly concerning effector responses and glucose metabolism, remains unknown. This study aims to evaluate the effect of metformin on the modulation of the effector functions and glucose metabolism of CD4+ T lymphocytes under normo- and hyperglycemic conditions. CD4+ T lymphocytes, obtained from peripheral blood from healthy volunteers, were anti-CD3/CD28-activated and cultured for 4 days with three concentrations of metformin (0.1 mM, 1 mM, and 5 mM) under normoglycemic (5.5 mM) and hyperglycemic (25 mM) conditions. Effector functions such as proliferation, cell count, cell cycle analysis, activation markers and cytokine secretion were analyzed by flow cytometry. Glucose uptake was determined using the 2-NBDG assay, and levels of glucose, lactate, and phosphofructokinase (PFK) activity were assessed by colorimetric assays. Metformin at 5 mM restrained the cell counts and proliferation of CD4+ T lymphocytes by arresting the cell cycle in the S/G2 phase at the beginning of the cell culture, without affecting cell activation, cytokine production, and glucose metabolism. In fact, CD69 expression and IL4 secretion by CD4+ T lymphocytes was higher in the presence of 5 mM than the untreated cells in both glucose conditions. Overall, metformin inhibited proliferation through mechanisms associated with cell cycle arrest, leading to an increase in the S/G2 phases at the expense of G1 in activated CD4+ T lymphocytes in normo- and hyperglycemic conditions. Despite the cell cycle arrest, activated CD4+ T lymphocytes remained metabolically, functionally, and phenotypically activated.
Blood-Derived Extracellular Vesicles as a Promising Liquid Biopsy Diagnostic Tool for Early Cancer Detection
Authors: He Dan , Cui Bozhou , Lv Hongkai , Lu Shuxian , Zhu Yuan , Cheng Yuqiang , Dang Lin , Zhang Hong
Published: July 2024

Cancer poses a significant public health challenge worldwide, and timely screening has the potential to mitigate cancer progression and reduce mortality rates. Currently, early identification of most tumors relies on imaging techniques and tissue biopsies. However, the use of low-cost, highly sensitive, non-invasive detection methods for early cancer screening has become more attractive. Extracellular Vesicles (EVs) released by all living cells contain distinctive biological components, such as nucleic acids, proteins, and lipids. These vesicles play crucial roles in the tumor microenvironment and intercellular communication during tumor progression, rendering liquid biopsy a particularly suitable method for diagnosis. Nevertheless, challenges related to purification methods and validation of efficacy currently hinder its widespread clinical implementation. These limitations underscore the importance of refining isolation techniques and conducting comprehensive investigations on EVs. This study seeks to evaluate the potential of liquid biopsy utilizing blood-derived EVs as a practical, cost-effective, and secure approach for early cancer detection.
Hepatic Gene Expression and Metabolite Profiles of Androstenone and Skatole Relative to Plasma Estrone Sulfate Levels in Boars
Authors: Bone Christine , Squires E. James
Published: July 2024

Testicular steroids can alter the activity and expression of enzymes within the liver and may influence the metabolism of skatole and androstenone, which are responsible for boar taint. Plasma levels of estrone sulfate (E1S) are indicative of the steroidogenic capacity of the boar and are variable between animals of similar live weights at slaughter. This study aimed to characterize the relationship between steroidogenic capacity and the metabolism of boar taint compounds by relating plasma E1S levels at slaughter weight to the expression levels of genes regulating the metabolism of androstenone and skatole, along with their respective metabolite profiles. RT-qPCR was used to evaluate gene expression in the liver. Hepatocytes were also isolated and treated with androstenone or skatole, with metabolite levels in the incubation media quantified by high-performance liquid chromatography. Plasma E1S levels ranged from 2.2–108.5 ng/mL and were positively correlated with overall skatole metabolism (p = 0.038), the production of metabolites 3-methyloxindole (p = 0.026) and 3-hydroxy-3-methyloxindole (p = 0.036), and expression levels of key genes involved in skatole metabolism, specifically CYP2C33 (p = 0.0042), CYP2C49 (p = 0.022), and CYB5R1 (p = 0.017). There was no association between androstenone metabolism and plasma E1S concentrations; however, there was evidence of possible co-regulation amongst genes involved in the metabolism of androstenone, skatole, and estrogens. These findings indicate that steroidogenic capacity is related to the rate of skatole, but not androstenone metabolism, in slaughter-weight boars.
Assessment of Antimicrobial and Cytotoxic Activities of Liposomes Loaded with Curcumin and Lippia origanoides Essential Oil
Authors: Bedoya-Agudelo Juan Pablo , López-Carvajal Jhon Esteban , Quiguanás-Guarín Edwin Stiven , Cardona Nestor , Padilla-Sanabria Leonardo , Castaño-Osorio Jhon Carlos
Published: July 2024

(1) Introduction: Curcumin and Lippia origanoides essential oils have a broad spectrum of biological activities; however, their physicochemical instability, low solubility, and high volatility limit their therapeutic use. Encapsulation in liposomes has been reported as a feasible approach to increase the physicochemical stability of active substances, protect them from interactions with the environment, modulate their release, reduce their volatility, improve their bioactivity, and reduce their toxicity. To date, there are no reports on the co-encapsulation of curcumin and Lippia origanoides essential oils in liposomes. Therefore, the objective of this work is to prepare and physiochemical characterize liposomes loaded with the mixture of these compounds and to evaluate different in vitro biological activities. (2) Methods: Liposomes were produced using the thin-layer method and physiochemical characteristics were calculated. The antimicrobial and cytotoxic activities of both encapsulated and non-encapsulated compounds were evaluated. (3) Results: Empty and loaded nanometric-sized liposomes were obtained that are monodisperse and have a negative zeta potential. They inhibited the growth of Staphylococcus aureus and did not exhibit cytotoxic activity against mammalian cells. (4) Conclusions: Encapsulation in liposomes was demonstrated to be a promising strategy for natural compounds possessing antimicrobial activity.
Recent Advances in Gene Therapy for Hemophilia: Projecting the Perspectives
Authors: Chernyi Nikita , Gavrilova Darina , Saruhanyan Mane , Oloruntimehin Ezekiel S. , Karabelsky Alexander , Bezsonov Evgeny , Malogolovkin Alexander
Published: July 2024

One of the well-known X-linked genetic disorders is hemophilia, which could be hemophilia A as a result of a mutation in the F8 (factor VIII) gene or hemophilia B as a result of a mutation in the F9 (factor IX) gene, leading to insufficient levels of the proteins essential for blood coagulation cascade. In patients with severe hemophilia, factor VIII or factor IX activities in the blood plasma are considerably low, estimated to be less than 1%. This is responsible for spontaneous or post-traumatic bleeding episodes, or both, leading to disease complications and death. Current treatment of hemophilia relies on the prevention of bleeding, which consists of expensive lifelong replacement infusion therapy of blood plasma clotting factors, their recombinant versions, or therapy with recombinant monoclonal antibodies. Recently emerged gene therapy approaches may be a potential game changer that could reshape the therapeutic outcomes of hemophilia A or B using a one-off vector in vivo delivery and aim to achieve long-term endogenous expression of factor VIII or IX. This review examines both traditional approaches to the treatment of hemophilia and modern methods, primarily focusing on gene therapy, to update knowledge in this area. Recent technological advances and gene therapeutics in the pipeline are critically reviewed and summarized. We consider gene therapy to be the most promising method as it may overcome the problems associated with more traditional treatments, such as the need for constant and expensive infusions and the presence of an immune response to the antibody drugs used to treat hemophilia.
Ischemic Neuroprotection by Insulin with Down-Regulation of Divalent Metal Transporter 1 (DMT1) Expression and Ferrous Iron-Dependent Cell Death
Authors: Fenaroli Francesca , Valerio Alessandra , Ingrassia Rosaria
Published: July 2024

Background: The regulation of divalent metal transporter-1 (DMT1) by insulin has been previously described in Langerhans cells and significant neuroprotection was found by insulin and insulin-like growth factor 1 treatment during experimental cerebral ischemia in acute ischemic stroke patients and in a rat 6-OHDA model of Parkinson’s disease, where DMT1 involvement is described. According to the regulation of DMT1, previously described as a target gene of NF-kB in the early phase of post-ischemic neurodegeneration, both in vitro and in vivo, and because insulin controls the NFkB signaling with protection from ischemic cell death in rat cardiomyocytes, we evaluated the role of insulin in relation to DMT1 expression and function during ischemic neurodegeneration. Methods: Insulin neuroprotection is evaluated in differentiated human neuroblastoma cells, SK-N-SH, and in primary mouse cortical neurons exposed to oxygen glucose deprivation (OGD) for 8 h or 3 h, respectively, with or without 300 nM insulin. The insulin neuroprotection during OGD was evaluated in both cellular models in terms of cell death, and in SK-N-SH for DMT1 protein expression and acute ferrous iron treatment, performed in acidic conditions, known to promote the maximum DMT1 uptake as a proton co-transporter; and the transactivation of 1B/DMT1 mouse promoter, already known to be responsive to NF-kB, was analyzed in primary mouse cortical neurons. Results: Insulin neuroprotection during OGD was concomitant to the down-regulation of both DMT1 protein expression and 1B/DMT1 mouse promoter transactivation. We also showed the insulin-dependent protection from cell death after acute ferrous iron treatment. In conclusion, although preliminary, this evaluation highlights the peculiar role of DMT1 as a possible pharmacological target, involved in neuroprotection by insulin during in vitro neuronal ischemia and acute ferrous iron uptake.
Spasmolytic Activity of 1,3-Disubstituted 3,4-Dihydroisoquinolines
Authors: Milusheva Miglena , Stoyanova Mihaela , Gledacheva Vera , Stefanova Iliyana , Todorova Mina , Nikolova Stoyanka
Published: July 2024

This article concerns the spasmolytic activities of some novel 1,3-disubstituted 3,4-dihydroisoquinolines. These compounds can be evaluated as potential therapeutic candidates according to Lipinski’s rule of five, showing high gastrointestinal absorption and the ability to cross the blood–brain barrier, which is a very important parameter in the drug discovery processes. In silico simulation predicted smooth muscle relaxant activity for all the compounds. Since smooth muscle contractile failure is a characteristic feature of many disorders, in the current paper, we concentrate on the parameters of the spontaneous contractile responses of smooth muscle (SM) cells compared to the well-known drug mebeverine. Two of the newly synthesized substances can be identified as essential modulating regulators and potentially used as therapeutic molecules. One of these molecules also showed significant DPPH antioxidant activity compared to rutin.
A Rapid and Reliable Spectrofluorimetric Method to Measure the Urinary Lactulose/Mannitol Ratio for Dysbiosis Assessment
Authors: Marino Cerrato Lorenzo , Schiano Elisabetta , Iannuzzo Fortuna , Tenore Gian Carlo , Summa Vincenzo , Daglia Maria , Novellino Ettore , Stornaiuolo Mariano
Published: July 2024

Gut microbiota plays a crucial role in human health homeostasis, and the result of its alteration, known as dysbiosis, leads to several pathologies (e.g., inflammatory bowel disease, metabolic syndrome, and Crohn’s disease). Traditional methods used to assess dysbiosis include the dual sugar absorption test and the urinary lactulose/mannitol ratio (LMR) measurement using mass spectrometry. Despite its precision, this approach is costly and requires specialized equipment. Hence, we developed a rapid and reliable spectrofluorimetric method for measuring LMR in urine, offering a more accessible alternative. This spectrofluorimetric assay quantifies the fluorescence of nicotinamide adenine dinucleotide (NADH) and nicotinamide adenine dinucleotide phosphate (NADPH) produced during the enzymatic oxidation of mannitol and lactulose, respectively. The assay requires 100 µL of urine samples and detects LMR values lower (eubiosis) and higher (dysbiosis) than 0.05, ultimately being amenable to high-throughput screening and automatization, making it practical for clinical and research settings. A validation of the method demonstrated its high precision, accuracy, and robustness. Additionally, this study confirmed analyte stability under various storage conditions, ensuring reliable results even with delayed analysis. Overall, this spectrofluorimetric technique reduces costs, time, and the environmental impact associated with traditional mass spectrometry methods, making it a viable option for widespread use in the assessment of dysbiosis.
Molecular Changes in the Ischemic Brain as Non-Invasive Brain Stimulation Targets—TMS and tDCS Mechanisms, Therapeutic Challenges, and Combination Therapies
Authors: Markowska Aleksandra , Tarnacka Beata
Published: July 2024

Ischemic stroke is one of the leading causes of death and disability. As the currently used neurorehabilitation methods present several limitations, the ongoing research focuses on the use of non-invasive brain stimulation (NIBS) techniques such as transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS). NIBS methods were demonstrated to modulate neural excitability and improve motor and cognitive functioning in neurodegenerative diseases. However, their mechanisms of action are not fully elucidated, and the clinical outcomes are often unpredictable. This review explores the molecular processes underlying the effects of TMS and tDCS in stroke rehabilitation, including oxidative stress reduction, cell death, stimulation of neurogenesis, and neuroprotective phenotypes of glial cells. A highlight is put on the newly emerging therapeutic targets, such as ferroptotic and pyroptotic pathways. In addition, the issue of interindividual variability is discussed, and the role of neuroimaging techniques is investigated to get closer to personalized medicine. Furthermore, translational challenges of NIBS techniques are analyzed, and limitations of current clinical trials are investigated. The paper concludes with suggestions for further neurorehabilitation stroke treatment, putting the focus on combination and personalized therapies, as well as novel protocols of brain stimulation techniques.
Air Pollution Increases Risk of Occurrence of Intracerebral Haemorrhage but Not of Subarachnoid Haemorrhage: Time-Series Cross-Sectional Study
Authors: Czernych Radosław , Kozera Grzegorz , Badyda Artur Jerzy , Bieniaszewski Leszek , Zagożdżon Paweł
Published: July 2024

(1) Background: Haemorrhagic strokes (HS), including intracerebral (ICH) and subarachnoid haemorrhages (SAH), account for approximately 10–15% of strokes worldwide but are associated with worse functional outcomes and higher rates of mortality, and financial burden than ischemic stroke. There is evidence that confirmed poor air quality may increase the incidence of haemorrhagic strokes. The aim of our study was to evaluate the association between individual ambient air pollutants and the risk of haemorrhagic stroke in an urban environment without high levels of air pollution. (2) Methods: A time-series cross-sectional study design was used. A daily air pollution concentration (Agency of Regional Air Quality Monitoring in the Gdansk Metropolitan Area) and incidence of haemorrhagic strokes (National Health Fund) were obtained and covered the time period from 1 January 2014 to 31 December 2018. A generalised additive model with Poisson regression was used to estimate the associations between 24-h mean concentrations of SO2, NO, NO2, NOx, CO, PM10, PM2.5, and O3 and a daily number of haemorrhagic strokes. (3) Results: The single-day lag model results showed that NO2, NO and NOx exposure was associated with increased risk of ICH (88% events) with RR of 1.059 (95% CI: 1.015–1.105 for lag0), 1.033 (95% CI: 1.007–1.060 for lag0) and 1.031 (95% CI: 1.005–1.056 for lag0), but not for SAH (12% events). Exposure to CO was related to a substantial and statistically significant increase in incidence for 1.031 (95% CI: 1.002–1.061 for lag0) but not for SAH. Higher SO2, PM10, PM2.5, and O3 exposures were not significantly related to both ISC and SAH. (4) Conclusions: In this time-series cross-sectional study, we found strong evidence that supports the hypothesis that transient elevations in ambient NO2, NO and CO are associated with a higher relative risk of intracerebral but not subarachnoid haemorrhage.