bluuebunny/crossref_metadata_2025 huggingface dataset:
A New Calibration Method for Broadband Complex Resistivity Measurement System of Rocks and Ores
Authors: Zhang Haojie , Chen Rujun , Chun Shaoheng , Xu Chao
Published: February 2025

The complex resistivity (CR) measurement constitutes a practical methodology for investigating the internal structures of rocks and ores alongside their mineralogical compositions and the chemical properties of fluids. However, during complex resistivity testing, particularly at high frequencies, the leakage current caused by the distributed capacitance of the instrument’s acquisition channels reduces the measurement accuracy. Additionally, the contact impedance of the measuring devices and the electromagnetic coupling effects of the measurement cables further affect the complex resistivity test results of samples. To accurately characterize samples’ intrinsic induced polarization (IP) properties, we developed a broadband complex resistivity measurement system (1 mHz–100 kHz) for rocks and ores, comprising a complex resistivity analyzer and a sample holder, employing the four-electrode method. In this study, we establish a circuit model for the measurement system to analyze the influence of the distributed capacitance of the acquisition channels on the test results at elevated frequencies. We derive the error terms inherent in the instrument’s measurements across various circuit design configurations and propose a novel method for calculating the distributed capacitance of the instrument’s acquisition channels, the parasitic capacitance of the sampling resistor, and for calibrating data by reversing the polarity of the excitation signal. Furthermore, we investigate the effect of contact impedance within the measurement setup on test results and design two sample-testing devices. Through extensive testing on multiple circuit models and samples, the system achieves an accuracy of up to 1% within the 10 MΩ range. Its overall performance surpasses that of the Solartron 1260A impedance analyzer and traditional signal source forward connection calibration methods. This advancement holds significant implications for complex resistivity measurements and the study of rock physical properties.
Electronic Sensing Technologies in Food Quality Assessment: A Comprehensive Literature Review
Authors: Gil Marian , Rudy Mariusz , Duma-Kocan Paulina , Stanisławczyk Renata
Published: February 2025

This manuscript was prepared for the purpose of an in-depth analysis of the development of electronic sensors in food quality assessment. In this study, the following research question was asked: What are the arguments for the development of electronic sensors for food assessment? The aim of this work was to comprehensively review the current scientific literature presenting the discussed issues and their systematization, as well as to present the prospects, threats, and applications of electronic sensors in food quality testing. The greatest interest of researchers lies in the use of e-nose. In contrast, fewer publications concerned e-tongue applications, and the smallest number of works concerned e-eye application. The initial application of electronic sensors in the food industry progressed from research on the identification of single ingredients or properties to the creation of increasingly complex research instruments that comprehensively analyze areas of food characteristics. Specifically, e-sensor research has focused on individual e-nose, e-tongue, and e-eye devices and has not provided complete information about food. This is confirmed by the high accuracy of research results regarding the combined use of sensors in food quality assessment.
Bearing Fault Diagnosis Grounded in the Multi-Modal Fusion and Attention Mechanism
Authors: Yang Jianjian , Han Haifeng , Dong Xuan , Wang Guoyong , Zhang Shaocong
Published: February 2025

This paper proposes a novel method called Fusion Attention Network for Bearing Diagnosis (FAN-BD) to address the challenges in effectively extracting and fusing key information from current and vibration signals in traditional methods. The research is validated using the public dataset Vibration, Acoustic, Temperature, and Motor Current Dataset of Rotating Machines under Varying Operating Conditions for Fault Diagnosis. The method first converts current and vibration signals into two-dimensional grayscale images, extracts local features through multi-layer convolutional neural networks, and captures global information using the self-attention mechanism in the Vision Transformer (ViT). Furthermore, it innovatively introduces the Channel-Based Multi-Head Attention (CBMA) mechanism for the efficient fusion of features from different modalities, maximizing the complementarity between signals. The experimental results show that compared to mainstream algorithms such as Vision Transformer, Swin Transformer, and ConvNeXt, the Fusion Attention Network for Bearing Diagnosis (FAN-BD) achieves higher accuracy and robustness in fault diagnosis tasks, providing an efficient and reliable solution for bearing fault diagnosis.The proposed model outperforms ViT, Swin Transformer, ConvNeXt, and CBMA-ViT in terms of classification accuracy, achieving an accuracy of 97.5%. The comparative results clearly demonstrate that the proposed Fusion Attention Network for Bearing Diagnosis yields significant improvements in classification outcomes.
Potentials and Limitations of Using Sentinel Data for Power System Operation and Control: Case Study of Protection Against Forest Fires and Aerosol Contamination
Authors: Božiček Amalija , Filipović-Grčić Božidar , Franc Bojan , Škrlec Davor , Tomašević Frano
Published: February 2025

The power network is directly or indirectly exposed to various weather and climate conditions that can positively and negatively influence it. Forest fires and various aerosol contaminations may negatively affect the power network. Surface observations and measurements (e.g., weather stations) help protect against unfavorable influences, but the network is usually poor. That challenge may be solved by including satellite data in the power network planning, operation, and maintenance. This article presents the possibilities of using Sentinel mission’s data, at various temporal and spatial levels, for those purposes through examples of protection against forest fires and aerosol contamination. In the case of forest fires, satellite data enable a more-precise calculation of forest fire-spreading danger for areas with no installed weather stations, which may be used in the power system contingency analysis calculation. The analysis showed that aerosol contamination has a correlation with outage appearance in the 25 kV 50 Hz electric traction network. Sentinel 5p data may serve as a tool in a surface air-quality measurement data control to confirm/deny the high concentration of PM10 particles. Analysis showed that Sentinel data are favorable for power network operations on intra-day and day-ahead operations, as well as for long-term operations, which include planning and maintenance. The spatial resolution of Sentinel data is more than enough to fulfill the surface weather station network. Satellite data also enable the use of additional data that are not measured at ground stations.
High-Fold 3D Gaussian Splatting Model Pruning Method Assisted by Opacity
Authors: Qiu Shiyu , Wu Chunlei , Wan Zhenghao , Tong Siyuan
Published: February 2025

Recent advancements in 3D scene representation have underscored the potential of Neural Radiance Fields (NeRFs) for producing high-fidelity renderings of complex scenes. However, NeRFs are hindered by the significant computational burden of volumetric rendering. To address this, 3D Gaussian Splatting (3DGS) has emerged as an efficient alternative, utilizing Gaussian-based representations and rasterization techniques to achieve faster rendering speeds without sacrificing image quality. Despite these advantages, the large number of Gaussian points and associated internal parameters result in high storage demands. To address this challenge, we propose a pruning strategy applied during the Gaussian densification and pruning phases. Our approach integrates learnable Gaussian masks with a contribution-based pruning mechanism, further enhanced by an opacity update strategy to facilitate the pruning process. This method effectively eliminates redundant Gaussian points and those with minimal contributions to scene construction. Additionally, during the Gaussian parameter compression phase, we employ a combination of teacher–student models and vector quantization to compress the spherical harmonic coefficients. Extensive experimental results demonstrate that our approach reduces the storage requirements of original 3D Gaussian models by over 30 times, with only a minor degradation in rendering quality.
An Effective Energetic Application of Orange Waste in Multi-Component Co-Digestion with Municipal Sewage Sludge
Authors: Szaja Aleksandra , Czarnota Joanna , Masłoń Adam , Lebiocka Magdalena
Published: February 2025

A strategy allowing for the application of orange waste (OW) in anaerobic co-digestion with municipal sewage sludge (MSS) has been proposed. For this purpose, the introduction of an additional component represented by ice-cream processing waste (IPW) has been chosen. The experiment was conducted in batch mode at a temperature of 37 °C. Four series were conducted: S1—the mono-digestion of MSS; S2—two-component co-digestion of MSS and 1.5 g of OW; S3—two-component co-digestion of MSS and 1.0 g of IPW; and S4—three-component co-digestion of MSS, 1.0 g of IPW, and 1.5 g of OW. The obtained results indicate that the highest methane production was achieved in the presence of IPW in two- and three-component mixtures (S3 and S4). It was also accompanied by improved kinetics, enhanced organic removal, and stable process performance. The related methane yields were 407.6 and 401.6 mL/g VS in S3 and S4, respectively. In turn, in S1 and S2, this parameter was established at the level of 351.3 and 344.3 mL/g VS. Additionally, as compared to MSS mono-digestion (S1), the energy profit was enhanced by 54 and 62% in S3 and S4, respectively. The obtained results indicate the possibility of effective management of OW with energy recovery in the anaerobic digestion process (AD).
Perceived Brightness and Resolution of Holographic Augmented Reality Retinal Scan Glasses
Authors: Rutz Maximilian , Neuberger Pia , Pick Simon , Straßer Torsten
Published: February 2025

Augmented reality display performance depends strongly on features of the human visual system. This is especially true for retinal scan glasses, which use laser beam scanning and transparent holographic optical combiners. Human-centered approaches allow us to go beyond conventional optical metrology and evaluate display performance as it is perceived in actual augmented reality use cases. Here, we first present a theoretical formula for the retinal scan luminance and ambient contrast ratio calculated from optical powers, wavelengths, field of view, and human pupil diameter. As a promising insight, we found that the pupil diameter dependence is beneficial in assimilating the virtual image luminance to the ambient luminance. Second, we designed and performed a psychophysical experiment to assess perceived resolution in augmented reality settings using a fully functional retinal scan glasses prototype. We present the results of the trials and illustrate how this approach can be used in the further development of augmented reality smart glasses.
PLC-Controlled Intelligent Conveyor System with AI-Enhanced Vision for Efficient Waste Sorting
Authors: Almtireen Natheer , Reddy Viraj , Sutton Max , Nedvidek Alexander , Karn Caden , Ryalat Mutaz , Elmoaqet Hisham , Rawashdeh Nathir
Published: February 2025

Current waste sorting mechanisms, particularly those relying on manual processes, semi-automated systems, or technologies without Artificial Intelligence (AI) integration, are hindered by inefficiencies, inaccuracies, and limited scalability, reducing their effectiveness in meeting growing waste management demands. This study introduces a prototype waste sorting machine that integrates an AI-driven vision system with a Programmable Logic Controller (PLC) for high-accuracy automated waste sorting. The system, powered by the YOLOv8 deep learning model, achieved sorting accuracies of 88% for metal cans, 75% for paper, and 91% for plastic bottles, with an overall precision of 90%, a recall of 80%, and a mean average precision (mAP50) of 86%. The vision system provides real-time classification, while the PLC manages conveyor and actuator operations to ensure seamless sorting. Experimental results in a controlled environment validate the system’s high accuracy, minimal processing delays, and scalability for industrial recycling applications. This innovative integration of AI vision with PLC automation enhances sorting efficiency, reduces ecological impacts, and minimizes labor dependency. Furthermore, the system aligns with sustainable waste management practices, promoting circular economy principles and advancing the Sustainable Development Goals (SDGs).
State-of-the-Art Navigation Systems and Sensors for Unmanned Underwater Vehicles (UUVs)
Authors: Sagar Md Mainuddin , Konara Menaka , Picard Nate , Park Kihan
Published: February 2025

Researchers are currently conducting several studies in the field of navigation systems and sensors. Even in the past, there was a lot of research regarding the field of velocity sensors for unmanned underwater vehicles (UUVs). UUVs have various services and significance in the military, scientific research, and many commercial applications due to their autonomy mechanism. So, it’s very crucial for the proper maintenance of the navigation system. Reliable navigation of unmanned underwater vehicles depends on the quality of their state determination. There are so many navigation systems available, like position determination, depth information, etc. Among them, velocity determination is now one of the most important navigational criteria for UUVs. The key source of navigational aids for different deep-sea research projects is water currents. These days, many different sensors are available to monitor the UUV’s velocity. In recent times, there have been five primary types of sensors utilized for UUV velocity forecasts. These include Doppler Velocity Logger sensors, paddlewheel sensors, optical sensors, electromagnetic sensors, and ultrasonic sensors. The most popular sensing sensor for estimating velocity at the moment is the Doppler Velocity Logger (DVL) sensor. DVL sensor is the most fully developed sensor for UUVs in recent years. In this work, we offer an overview of the field of navigation systems and sensors (especially velocity) developed for UUVs with respect to their use with tidal current sensing in the UUV setting, including their history, evolution, current research initiatives, and anticipated future.
Pathogenic Yersinia enterocolitica’s Contamination of Cheeks, Tongues, and Other Pork Meats at Retail in France, 2023
Authors: Denis Martine , Felten Arnaud , Ducret Linda , Houard Emmanuelle , Tasset Manon , Novi Delphine , Chemaly Marianne
Published: February 2025

Pathogenic Y. enterocolitica’s contamination of cheeks, tongues, and other pork meats at retail was assessed in 2023, over 9 months. A total of 111 samples of cheeks, 104 of tongues, and 160 of fresh meat were taken at retail from the 13 regions of mainland France. The level of contamination was 16.0%, with a higher contamination in tongues (39.4%), followed by cheeks (16.4%). Only one meat sample was contaminated. Of the 128 isolated strains, 97.6% were of the BT4 biotype. Depending on the method used to check the presence of the plasmid—yadA-PCR, CR-MOX testing, or sequencing—the results were not consistent for some strains, but most of the strains (≥ to 65%) had the virulent plasmid pYV. All the BT4 strains (except two strains) carried the sequence ST18; they were distributed in 54 cgMLST genotypes. The genetic diversity of the strains was very high, whatever the typing method used, including cgMLST, wgMLST, and cgSNP. There was higher contamination in tongues and cheeks, and lower contamination in meat, suggesting that the head deboning step is riskier than the evisceration step for contamination by pathogenic Y. enterocolitica. This pathogen remains a zoonotic agent of public health importance to be monitored in pigs.
Analysis of the Odor Levels at the Closest Receptors Depending on the Stack Terminal Types
Authors: Bellasio Roberto , Bianconi Roberto
Published: February 2025

This paper presents the results of a numerical analysis for evaluating the effects of different stack terminal configurations on the odor levels estimated at the receptors located close to the plant. Stack terminals may be of different types, for example vertical unobstructed, vertical with rain cap, horizontal, gooseneck or with any slope with respect to the vertical. The comparison between CALPUFF and LAPMOD with vertical unobstructed stacks, rain capped stacks and different emission temperatures shows that the results are comparable, even though there is a tendency of LAPMOD to underpredict when vertical unobstructed stacks are used. A detailed numerical analysis has then been performed with the LAPMOD dispersion model, which adopts a numerical plume rise scheme capable to simulate releases with any orientation. Two different sites have been considered, both located in northern Italy: one with almost flat orography, and one with relatively complex orography. The results show that the choice of the stack terminal has important effects on the odor levels predicted at the closest receptors. The vertical unobstructed stack always has a smaller impact than all the other terminal types, particularly for low emission temperatures.
Exploring the Holiday Effect on Elevated Traffic-Related Air Pollution with Hyperlocal Measurements in Chengdu, China
Authors: Xiang Sheng , Yu Jiaojiao , Yu Yu Ting , Zhao Pengbo , Zheng Tie , Yue Jingsong , Yang Yuanyuan , Liu Haobing
Published: February 2025

Traffic-related air pollutants (TRAPs) pose significant health risks in megacities, yet fixed monitoring sites often fail to capture their complexity. To characterize the TRAP concentrations which fixed sites cannot address, we employed a mobile platform to effectively capture real-time hyperlocal-scale TRAP variations in Chengdu, China. A 17-day sampling campaign was conducted covering the National Holiday of China and collected ~1.2 × 105 1 Hz paired data. We measured particle number concentration (PNC), black carbon (BC), and nitrogen oxides (NOx) across urban and rural freeway environments to assess the impact of reduced heavy-duty diesel vehicles (HDDVs) during the holiday (i.e., holiday effect). No clear impact of wind direction on TRAP concentrations was found in this study. However, substantial differences (two times) were observed when comparing non-holiday to holiday campaigns. Spearman correlations (0.21–0.56) between TRAPs persistently exceeded Pearson correlations (0.14–0.41), indicating non-linear relationships and suggesting the necessity for data transformations (e.g., logarithms) in TRAP analysis. The comparison of the background subtracted TRAPs concentrations between non-holiday and holidays, revealing approximately a 50% reduction in TRAPs across microenvironments. Among the TRAPs, NOx emerged as a reliable indicator of HDDV emissions. The study provides insights into vehicle fleet composition impacts, paving the way for enhanced exposure assessment strategies.
Experimental Study on Thermal Management of 5S7P Battery Module with Immersion Cooling Under High Charging/Discharging C-Rates
Authors: Tai Le Duc , Garud Kunal Sandip , Lee Moo-Yeon
Published: February 2025

In this study, the efficiency of an immersion cooling system for controlling the temperature of 5S7P battery modules at high charge and discharge C-rates was experimentally evaluated. The study was conducted in three main stages including the evaluation of different coolant oils followed by the proposition of an optimal volume flow rate (VFR) and cooling performance evaluation under high charging/discharging C-rates. In the first stage, three coolant oils, including Therminol D-12, Pitherm 150B, and BOT 2100, were compared. The Therminol D-12 achieved superior cooling performance, with the highest heat transfer coefficient (HTC) of 2171.93 W/m2⋅K and the ability to maintain the maximum temperature (Tmax) and temperature difference (∆T) of the battery module within the safe range. In the next stage, VFR was varied between 0.4 LPM and 1.0 LPM for the selected best coolant oil of Therminol D-12. The 0.8 LPM VFR was determined to be optimal with the highest HTC of 2445.73 W/m2⋅K and an acceptable pressure drop of 12,650 Pa, ensuring a balance between cooling performance and energy consumption. Finally, the cooling performance was evaluated at high charging/discharging C-rates from 1.5C to 3.0C for the proposed best coolant oil and VFR. The immersion cooling system with Therminol D-12 and a VFR of 0.8 LPM is an effective combination to achieve the desired performance of the battery module under extreme C-rate working conditions. The immersion cooling system with the proposed effective combination maintains the Tmax and ∆T at 38.6 °C and 4.3 °C under a charging rate of 3.0C and to 43.0 °C and 5.5 °C under a discharging rate of 3.0C.
The Role of Functional Beverages in Mitigating Cardiovascular Disease Risk Factors: A Focus on Their Antidiabetic and Hypolipidemic Properties
Authors: Scarcelli Eva , Iacopetta Domenico , Ceramella Jessica , Bonofiglio Daniela , Conforti Francesca Luisa , Aiello Francesca , Sinicropi Maria Stefania
Published: February 2025

The incidence and mortality rates of cardiovascular diseases (CVDs) are constantly increasing. Among the main risk factors, diabetes mellitus and hyperlipidaemia, which are equally widespread pathological conditions, stand out. Current preventive strategies are based on physical activity and a healthy, balanced diet. Primary therapies, on the other hand, are based on the administration of hypoglycaemic and cholesterol-lowering drugs. Given the increasing consumer demand for food products with healthy properties, functional beverages may represent a breakthrough in this field. Through a careful analysis of studies conducted over the past seven years, it has emerged that herbal teas, fruit and vegetable drinks, as well as milk- and plant-based beverages, can mitigate these two critical CVD risk factors, often linked to the presence of specific polyphenols or fermentation processes. The selection of in vivo, in vitro and clinical trials revealed the ability of such drinks to reduce the enzymatic activity of α-glucosidase and α-amylase, as well as to decrease circulating lipid levels, properties that were surprisingly also exhibited by beverages derived from food waste. Therefore, this review aims to highlight the possibility of employing these drinks as adjuvant therapy in the treatment of diabetes mellitus and hyperlipidaemia in order to reduce two potential CVD risk factors.
MWG-UNet++: Hybrid Transformer U-Net Model for Brain Tumor Segmentation in MRI Scans
Authors: Lyu Yu , Tian Xiaolin
Published: February 2025

The accurate segmentation of brain tumors from medical images is critical for diagnosis and treatment planning. However, traditional segmentation methods struggle with complex tumor shapes and inconsistent image quality which leads to suboptimal results. To address this challenge, we propose multiple tasking Wasserstein Generative Adversarial Network U-shape Network++ (MWG-UNet++) to brain tumor segmentation by integrating a U-Net architecture enhanced with transformer layers which combined with Wasserstein Generative Adversarial Networks (WGAN) for data augmentation. The proposed model called Residual Attention U-shaped Network (RAUNet) for brain tumor segmentation leverages the robust feature extraction capabilities of U-Net and the global context awareness provided by transformers to improve segmentation accuracy. Incorporating WGAN for data augmentation addresses the challenge of limited medical imaging datasets to generate high-quality synthetic images that enhance model training and generalization. Our comprehensive evaluation demonstrates that this hybrid model significantly improves segmentation performance. The RAUNet outperforms compared approaches by capturing long-range dependencies and considering spatial variations. The use of WGANs augments the dataset for resulting in robust training and improved resilience to overfitting. The average evaluation metric for brain tumor segmentation is 0.8965 which outperformed the compared methods.
Data-Driven Clustering of Plantar Thermal Patterns in Healthy Individuals: An Insole-Based Approach to Foot Health Monitoring
Authors: Borg Mark , Mizzi Stephen , Farrugia Robert , Mifsud Tiziana , Mizzi Anabelle , Bajada Josef , Falzon Owen
Published: February 2025

Monitoring plantar foot temperatures is essential for assessing foot health, particularly in individuals with diabetes at increased risk of complications. Traditional thermographic imaging measures foot temperatures in unshod individuals lying down, which may not reflect thermal characteristics of feet in shod, active, real-world conditions. These controlled settings limit understanding of dynamic foot temperatures during daily activities. Recent advancements in wearable technology, such as insole-based sensors, overcome these limitations by enabling continuous temperature monitoring. This study leverages a data-driven clustering approach, independent of pre-selected foot regions or models like the angiosome concept, to explore normative thermal patterns in shod feet with insole-based sensors. Data were collected from 27 healthy participants using insoles embedded with 21 temperature sensors. The data were analysed using clustering algorithms, including k-means, fuzzy c-means, OPTICS, and hierarchical clustering. The clustering algorithms showed a high degree of similarity, with variations primarily influenced by clustering granularity. Six primary thermal patterns were identified, with the “butterfly pattern” (elevated medial arch temperatures) predominant, representing 51.5% of the dataset, aligning with findings in thermographic studies. Other patterns, like the “medial arch + metatarsal area” pattern, were also observed, highlighting diverse yet consistent thermal distributions. This study shows that while normative thermal patterns observed in thermographic imaging are reflected in insole data, the temperature distribution within the shoe may better represent foot behaviour during everyday activities, particularly when enclosed in a shoe. Unlike thermal imaging, the proposed in-shoe system offers the potential to capture dynamic thermal variations during ambulatory activities, enabling richer insights into foot health in real-world conditions.
Selectively Blocking Small Conductance Ca2+-Activated K+ Channels Improves Cognition in Aged Mice
Authors: Ong Jessie , Heller H. Craig , Pittaras Elsa
Published: February 2025

Aging is associated with decreased neuronal sensitivity and activity that creates deficits in cognitive processes, including learning, memory, motivation, general activity, and other behaviors. These effects are due in part to decreased intracellular Ca2+ homeostasis, increasing hyperpolarization of the resting potential in aged neurons and therefore decreasing their excitability. To reduce hyperpolarization in aged mice, we used apamin, a selective small conductance Ca2+-activated K+ (sKCa) channel blocker. By blocking the sKCa channels, apamin decreases the egress of the K+ out of the cell, reducing its hyperpolarization and causing it to be closer to threshold potential. As a result, neurons should be more sensitive to excitatory stimuli and more active. We evaluated the performance of aged mice in a selection of cognitive and behavioral tests prior to and after systemic applications of apamin or the vehicle saline. Apamin improved performance in short-term memory, increased attention to tasks, and decreased anhedonia. Apamin had no significant effect on long-term spatial and recognition memory, risk-taking behavior, sociability, and anxiety. Our results are compatible with the known effects of sKCa channel blockade on neuronal sensitivity and activity; however, these short-term effects were not reflected in longer-term alterations of neural plasticity responsible for long-term spatial and recognition memory or other more complex cognitive processes we evaluated.
The Role of Umbilical Cord Mesenchymal Stem Cell-Derived Extracellular Vesicles in Modulating Dermal Fibroblast Activity: A Pathway to Enhanced Tissue Regeneration
Authors: Barathan Muttiah , Ham Kow Jack , Wong Hui Yin , Law Jia Xian
Published: February 2025

Extracellular vesicles (EVs) secreted by umbilical cord-derived mesenchymal stem cells (UC-MSCs) hold significant promise as therapeutic agents in regenerative medicine. This study investigates the effects of UC-MSC-derived EVs on dermal fibroblast function, and their potential in wound healing applications. EVs were characterized by nanoparticle tracking analysis and transmission electron microscopy, revealing a mean size of 118.6 nm, consistent with exosomal properties. Dermal fibroblasts were treated with varying concentrations of EVs (25–100 µg/mL), and their impacts on cellular metabolism, mitochondrial activity, reactive oxygen species (ROS) production, wound closure, inflammatory cytokine secretion, growth factor production, and extracellular matrix (ECM) gene expression were evaluated. At lower concentrations (25–50 µg/mL), EVs significantly enhanced fibroblast metabolic and mitochondrial activity. However, higher concentrations (≥75 µg/mL) increased ROS levels, suggesting potential hormetic effects. EVs also modulated inflammation by reducing pro-inflammatory cytokines (IL-6, TNF-α) while promoting pro-regenerative cytokines (IL-33, TGF-β). Treatment with 50 µg/mL of EVs optimally stimulated wound closure and growth factor secretion (VEGF, BDNF, KGF, IGF), and upregulated ECM-related gene expression (type I and III collagen, fibronectin). These findings demonstrate that UC-MSC-derived EVs exert multifaceted effects on dermal fibroblast function, including enhanced cellular energetics, stimulation of cell migration, regulation of inflammation, promotion of growth factor production, and increased ECM synthesis. This study highlights the potential of EVs as a novel therapeutic strategy for wound healing and tissue regeneration, emphasizing the importance of optimizing EV concentration for maximal therapeutic efficacy.
Chronic Coronary Artery Disease: Wall Disease vs. Lumenopathy
Authors: Paraskevaidis Ioannis , Kourek Christos , Tsougos Elias
Published: February 2025

Acute and chronic coronary artery disease (CAD) are interconnected, representing two facets of the same condition. Chronic CAD exhibits a dynamic nature, manifesting as stable or acute ischemia, or both. Myocardial ischemia can be transient and reversible. The genesis of CAD involves diverse anatomical and functional mechanisms, including endothelial dysfunction, arteriolar remodeling, capillary rarefaction, and perivascular fibrosis, though no single factor explains its heterogeneity. Chronic CAD is often stable but may present as symptomatic or asymptomatic (e.g., in diabetes) and affect various coronary compartments (epicardial or microcirculation). This complexity necessitates a reappraisal of our approach, as pathophysiological mechanisms vary and often overlap. A comprehensive exploration of these mechanisms using advanced diagnostic techniques can aid in identifying the dynamic processes underlying CAD. The disease may present as obstructive or non-obstructive, stable or unstable, underscoring its diversity. The primary source of CAD lies in the arterial wall, emphasizing the need for research on its components, such as the endothelium and vascular smooth muscle cells, and factors disrupting arterial homeostasis. Shifting focus from arterial luminal status to the arterial wall can provide insights into the genesis of atheromatous plaques, enabling earlier interventions to prevent their development and progression.
Heavy Chalcogen Properties of Sulfur and Selenium Enhance Nucleic Acid-Based Therapeutics
Authors: Dansereau Stephen J. , Sheng Jia
Published: February 2025

The Group 16 elements of the periodic table have a characteristic valence shell configuration instrumental to their chemical properties and reactivities. The electrostatic potentials of these so-called chalcogens have been exploited in the design of materials that require the efficient passage of electrons including supermagnets, photocatalytic dyes, and solar panels. Likewise, the incorporation of the heavy chalcogen selenium into organic frameworks has been shown to increase the reactivities of double bonds and heterocyclic rings, while its interactions with aromatic side chains in the hydrophobic core of proteins via selenomethionine impart a stabilizing effect. Typically present in the active site, the hypervalence of selenocysteine enables it to further stabilize the folded protein and mediate electron transfer. Selenium’s native occurrence in bacterial tRNA maintains base pair fidelity, most notably during oxidative stress, through its electronic and steric effects. Such native modifications at the positions 2 and 5 of uridine render these sites relevant in the design of RNA-based therapeutics. Innocuous selenium substitution for oxygen in the former and the standard methods of selenium-derivatized oligonucleotide synthesis and detection have led to the establishment of a novel class of therapeutics. In this review, we summarize some progress in this area.
A Neuroprotective Peptide Modulates Retinal cAMP Response Element-Binding Protein (CREB), Synapsin I (SYN1), and Growth-Associated Protein 43 (GAP43) in Rats with Silicone Oil-Induced Ocular Hypertension
Authors: Johnson Gretchen A. , Krishnamoorthy Raghu R. , Nagaraj Ram H. , Stankowska Dorota L.
Published: February 2025

This study evaluated the neuroprotective potential of peptain-1 conjugated to a cell-penetrating peptide (CPP-P1) in an ocular hypertension model of glaucoma. Brown Norway (BN) rats were subjected to intraocular pressure (IOP) elevation via intracameral injection of silicone oil (SO), with concurrent intravitreal injections of either CPP-P1 or a vehicle. Retinal cross-sections were analyzed for markers of neuroprotection, including cAMP response element-binding protein (CREB), phosphorylated CREB (p-CREB), growth-associated protein-43 (GAP43), synapsin-1 (SYN1), and superoxide dismutase 2 (SOD2). Hematoxylin and eosin staining was used to assess retinal-layer thickness. SO-treated rats exhibited significant reductions in the thickness of the inner nuclear layer (INL, 41%, p = 0.016), inner plexiform layer (IPL, 52%, p = 0.0002), and ganglion cell layer (GCL, 57%, p = 0.001). CPP-P1 treatment mitigated these reductions, preserving INL thickness by 32% (p = 0.059), IPL by 19% (p = 0.119), and GCL by 31% (p = 0.057). Increased levels of CREB (p = 0.17) and p-CREB (p = 0.04) were observed in IOP-elevated, CPP-P1-treated retinas compared to IOP-elevated, vehicle-treated retinas. Although overall GAP43 levels were low, there was a modest increase in expression within the IPL and GCL in SO- and CPP-P1-treated retinas (p = 0.15 and p = 0.09, respectively) compared to SO- and vehicle-treated retinas. SO injection reduced SYN1 expression in both IPL and GCL (p = 0.01), whereas CPP-P1 treatment significantly increased SYN1 levels in the IPL (p = 0.03) and GCL (p = 0.002). While SOD2 expression in the GCL was minimal across all groups, a trend toward increased expression was observed in CPP-P1-treated animals (p = 0.16). The SO model was replicated with SO removal after 7 days and monitored for 21 days followed by retinal flat-mount preparation to assess retinal ganglion cell (RGC) survival. A 42% loss in RGCs (p = 0.009) was observed in SO-injected eyes, which were reduced by approximately 37% (p = 0.03) with CPP-P1 treatment. These findings suggest that CPP-P1 is a promising neuroprotective agent that promotes retinal ganglion cell survival and the preservation of other retinal neurons, potentially through enhanced CREB signaling in a rat model of SO-induced ocular hypertension.
Nonlinear Gait Variability Increases with Age in Children from 2–10 Years Old
Authors: Applequist Bryon C. , Motz Zachary L. , Kyvelidou Anastasia
Published: February 2025

Background: Linear methods of analysis of variability are concerned with the magnitude of variability and often consider deviations from a central mean as errors. The utilization of nonlinear tools to examine variability allows for the exploration and measurement of the patterns of variability displayed by the system. This methodology explores the deterministic properties of biological signals, in this case, gait, or how previous iterations within the gait cycle influence subsequent and future iterations. The nonlinear analysis of gait variability of the joint angle time series has not been investigated in developing children. Methods: We collected 3 min of treadmill walking data for 28 children between the ages of 2 and 10 years old and analyzed their joint angle time series using nonlinear methods of analysis (sample entropy, largest Lyapunov exponent, and recurrence quantification analysis). Results: Our results indicate that the nonlinear variability of children’s gait increases as children age. Interestingly, this contrasts with the findings from our previous work that showed a decrease in linear variability as children age. The combination of a decrease in linear variability, or a refined and improved stability of gait, as well as an increase in nonlinear variability, or an increase in the sophistication and quality of movement patterns, suggest an overall maturation of the neuromuscular system. Conclusions: Our study indicate that there is a refining of gait with age and motor maturation. This refining speaks to the overall multifaceted organization of systems that defines the maturation of gait.
Peritoneal Endometriosis Impairs Ovarian Reserve and Increases Atresia in a Rat Model
Authors: Ricci Analía , Bengochea Tatiana , Olivares Carla , del Valle Sofía , Simone Julieta , Gemzell-Danielsson Kristina , Barañao Rosa Inés , Meresman Gabriela , Bilotas Mariela
Published: February 2025

Background/Objectives: Endometriosis has a marked impact on fertility, although the mechanisms behind this relationship remain poorly understood, particularly in cases without significant anatomical distortions or in the context of ovarian endometriomas. This study aimed to investigate the effect of peritoneal endometriosis on ovarian function by assessing ovarian reserve and apoptosis. Methods: Peritoneal endometriosis was surgically induced in Sprague Dawley rats through the autotransplantation of uterine fragments onto the bowel mesothelium. One month post-surgery, ovarian structures were counted, follicle and corpora lutea apoptosis was evaluated by TUNEL, and apoptotic-related protein expression in ovaries was assessed by Western blot. Additionally, a co-culture system using 12Z endometriotic and KGN granulosa cell lines was utilized to evaluate gene expression by RT-qPCR. Results: Rats with peritoneal endometriosis exhibited a significant reduction in ovarian structures characterized by a low number of total follicles, particularly primordial, primary, preantral, and late-antral follicles. Consistently, AMH protein expression was decreased in ovaries in the presence of endometriosis. In addition, this disease led to a significant increase in late-antral follicles that were TUNEL-positive and in the number of apoptotic cells in corpora lutea, indicating higher apoptosis in endometriosis ovaries. Concomitantly, the altered expression of apoptosis-related proteins was observed, with increased procaspase 3 and decreased BCL-2 expression. In addition, KGN granulosa cells co-cultured with 12Z endometriotic cells displayed reduced KITLG mRNA expression and increased AMHR2 mRNA expression. Conclusions: Peritoneal endometriosis significantly impairs ovarian health by disrupting folliculogenesis, reducing ovarian reserve, and increasing apoptosis, potentially accelerating ovarian aging and contributing to infertility. These results underscore the need for further research to identify the molecular pathways involved and to develop targeted therapeutic strategies.
Obesity as a Risk Factor for Hyperglycemia, Electrolyte Disturbances, and Acute Kidney Injury in the Emergency Department
Authors: Crintea Iulia Najette , Cindrea Alexandru Cristian , Mederle Ovidiu Alexandru , Fulga Teodor Florin , Marza Adina Maria , Petrica Alina , Trebuian Cosmin Iosif , Timar Romulus
Published: February 2025

Background/Objectives: Obesity is a global health challenge linked to a higher risk of metabolic and cardiovascular complications. This study investigates the role of cardiovascular markers in predicting metabolic crises in obese patients, focusing on the prevalence and clinical implications of these markers. Methods: This retrospective cohort study included 433 patients presenting with metabolic crises at the Emergency Department of Timișoara Municipal Emergency Hospital between 2019 and 2024. Patients were classified into obese (n = 161) and non-obese (n = 272) groups, with obesity further stratified into four grades based on body mass index (BMI). Cardiovascular markers, including NT-proBNP, troponin I, CRP, CK-MB, and D-dimer, alongside metabolic parameters, were analyzed. Results: Metabolic crises were significantly more prevalent in obese patients in all metabolic emergencies: hyperglycemia (27.9% vs. 11.0%, p < 0.001), electrolyte imbalance (23.6% vs. 9.2%, p < 0.001), and acute kidney injury (AKI) (12.4% vs. 5.5%, p = 0.01). NT-proBNP levels independently predicted AKI in obese patients (adjusted OR: 1.14 per 1000 pg/mL, 95% CI: 1.10–1.19, p < 0.001), with excellent discriminatory power (AUC: 0.88). Troponin I and D-dimer were higher in hyperglycemia and electrolyte imbalance, respectively, emphasizing the role of cardiac stress and pro-thrombotic states. Inflammatory markers such as CRP were significantly associated with metabolic disturbances, supporting the contribution of systemic inflammation. Comorbidities, particularly heart failure and atrial fibrillation, further increased the risk of metabolic crises. Conclusions: Cardiovascular markers suggest potential utility for early risk stratification of metabolic crises in obese patients. However, further studies are needed to validate their clinical applicability and to establish standardized approaches for integrating these biomarkers into routine practice, especially in patients with advanced obesity grades.
Systematic Review of Self-Assessment Scales for Negative Symptoms in Schizophrenia
Authors: Métivier Lucie , Dollfus Sonia
Published: February 2025

Background/Objectives: Negative symptoms (NSs) significantly impair the outcome of schizophrenia, primarily due to their effect on quality of life and their resistance to pharmacological treatments. Several scales have been developed to assess the various dimensions of NSs, including avolition, anhedonia, alogia, social withdrawal, and blunted affect. While observer-rated scales are the most commonly used, self-assessment tools remain underutilized. However, self-assessments offer a promising approach for gaining insights into the personal experiences of individuals. The objective of this review was to identify and report the psychometric properties of self-assessment scales for NSs that are relevant for both research and clinical practice, with a focus on tools that assess multiple domains of NSs in order to support comprehensive evaluations and tailored therapeutic strategies. Methods: We conducted an exhaustive literature review following PRISMA guidelines to identify self-evaluation scales that evaluate several domains of NSs in the MEDLINE and Web of Science databases. The COSMIN checklist was used to assess the methodological quality of each tool. Results: Our review identified five self-assessment scales. Among these, two scales received a Grade A recommendation for use in clinical or research practice: the Self-evaluation Negative Symptom (SNS), which assesses the five domains of NSs, and the Motivation And Pleasure Scale Self-report (MAP-SR), which evaluates anhedonia, avolition, and social withdrawal. Conclusions: The SNS and the MAP-SR are the only tools with sufficient psychometric properties, making them reliable for use in both research and clinical practice. Despite the development of self-assessment tools for NSs, their integration into research and clinical settings remains limited, highlighting the need for increased utilization to enhance the understanding and management of these symptoms.
Eye-Tracking Metrics as a Digital Biomarker for Neurocognitive Disorders in Multiple Sclerosis: A Scoping Review
Authors: Cecchetti Sonja , Duchowski Andrew T. , Cavallo Marco
Published: February 2025

Multiple sclerosis (MS) is an autoimmune disease classified as neurodegenerative because it can be associated with the more or less progressive development of neurological symptoms and cognitive deficits. In recent years, various studies have started to investigate eye movements in relation to cognitive impairment in persons with MS by means of eye-tracking equipment. However, the high heterogeneity of the paradigms used in different studies, as well as the different methodologies included, makes it difficult to provide a complete and precise picture of this important research and clinical issue. The purpose of the present in-depth scoping review was to map the existing literature in this field to determine which metrics may be relevant when dealing with the neurocognitive profile of people with MS. From the analyses of the included studies, the anti-saccade latency and errors were the most frequently proposed metrics. Correlation analyses between these metrics and cognitive measures showed significant associations between them, calling for a deeper investigation of this promising research and clinical field. The results of the present scoping review strongly suggest that eye tracking may play a crucial role in clinical practice during the early detection of neurocognitive disorders. There is a great need for primary research that addresses the full complexity of MS in its different phenotypes and the disease-related variables from a multidisciplinary perspective. Future research should clarify whether oculomotor dysfunction in MS follows or precedes cognitive deficits.
Vinpocetine, a Phosphodiesterase Type 1 Inhibitor, Mitigates Locomotor Hyperactivity in Female Mice Exposed to Lead During Development
Authors: Araujo Ulisses C. , Nunes Fernanda , Gonçalves Bruno S. , Gomes Regina A. A. , Moreira Maria de Fátima R. , Nunes-Freitas Andre , Krahe Thomas E. , Abreu-Villaça Yael de , Manhães Alex C. , Filgueiras Cláudio C.
Published: February 2025

Background/Objectives Studies in rodents indicate that disruptions in both cyclic adenosine monophosphate (cAMP) and cyclic guanosine monophosphate (cGMP) signaling pathways are involved in the development of hyperactive behavior. We examined whether vinpocetine, a phosphodiesterase type 1 inhibitor that enhances brain cAMP and cGMP levels, could mitigate locomotor hyperactivity in mice exposed to lead during early development. Methods Swiss mice were exposed to 90 ppm of lead in their drinking water throughout gestation and the first ten postnatal days. At postnatal day 10 (PN10), blood lead levels (BLLs) were about 30 µg/dL. At PN30, animals either received vinpocetine (20 mg/kg, i.p.) or a vehicle 4 h before the evaluation of locomotor activity in the open field. Results Lead-exposed males did not display differences in locomotor activity compared to controls, while lead-exposed females showed a significant increase in locomotion. Vinpocetine treatment significantly reversed the lead-induced hyperactivity in females. Conclusions These findings suggest that the cAMP and cGMP signaling pathways play a role in the hyperactivity induced by lead exposure.