bluuebunny/crossref_metadata_2025 huggingface dataset:
Myocardial Strain Assessment for Early Duchenne Muscular Dystrophy Diagnosis in Pediatric Patients Using Cardiac MRI
Authors: Awadi Rania , Benameur Narjes , Hafsi Hassen , Younes Thouraya Ben , Arous Younes , Labidi Salam , Tavares João Manuel R. S.
Published: November 2024

Assessing myocardial strain remains challenging, particularly in the pediatric population, due to the smaller heart sizes, higher heart rates, and variability in strain parameters compared to adult populations. This study aimed to investigate the utility of myocardial strain measurements using cardiac magnetic resonance-feature tracking (CMR-FT) for early diagnosis of Duchenne muscular dystrophy (DMD) in pediatric patients. Twenty-eight DMD patients and 20 healthy controls were involved in this study. Global circumferential, longitudinal, and radial strain (GCS, GLS, and GRS) were measured for the left ventricle (LV) using CMR-FT. Segmental strain values only of the inferolateral and anterolateral LV segments in DMD patients without late gadolinium enhancement (LGE) and DMD patients with LGE were compared to the healthy controls. Strain measurements using CMR-FT in DMD patients were considerably lower than those of healthy controls, with all p-values lower than 0.001. DMD patients without LGE showed decreased inferolateral and anterolateral segmental values only relative to healthy controls. The same behavior was maintained for the LV geometry. Multivariable linear regression demonstrated that the end-systole (ES) wall thicknesses and thickening were associated with decreased GCS and GLS. CMR-FT is crucial in detecting cardiac abnormalities in patients with DMD. It represents an innovative imaging biomarker that can detect initial myocardial alterations in DMD cardiomyopathy without relying on gadolinium.
Estimating Motives for Renting Shared Bicycles Using Multinomial Logistic Regression: A Case Study from the Slovak Republic
Authors: Kubaľák Stanislav , Mazanec Jaroslav , Gogola Marián
Published: November 2024

This research aims to estimate the purposes for which bike-share users utilize shared bicycles from bike-sharing companies using selected predictors through multinomial logistic regression in Slovakia. The study seeks to provide a novel perspective on alternative transportation by addressing a gap in existing research, which has not previously focused on modeling the specific purposes of bicycle use. The final sample comprises 162 bike-share users out of more than 300 respondents. The results show that social status, bike-sharing company, and average distance are statistically significant input variables. Finally, we find that using shared bikes for recreation is more typical for employees with a traveled distance of up to 3 km from one of the two bike-sharing companies compared to the reference group (commuting to school). The paper contributes to better planning and management of bike-sharing systems.
The Mesoscopic Damage Mechanism of Jointed Sandstone Subjected to the Action of Dry–Wet Alternating Cycles
Authors: Zhang Liang , Wang Guilin , Wang Runqiu , Liu Bolong , Wang Ke
Published: November 2024

The effect of the dry–wet cycle, characterized by periodic water level changes in the Three Gorges Reservoir, will severely degrade the bearing performance of rock formations. In order to explore the effect of the dry–wet cycle on the mesoscopic damage mechanism of jointed sandstone, a list of meso-experiments was carried out on sandstone subjected to dry–wet cycles. The pore structure, throat features and mesoscopic damage evolution of jointed sandstone with the action of the dry–wet cycle were analyzed using a-low-field nuclear magnetic resonance (NMR) technique. Subsequently, the impact on the mineral content of dry–wet cycles was studied by small angle X-ray scattering (SAXS). Based on this, the mesoscopic damage mechanism of sandstone subjected to dry–wet cycles was revealed. The results show that the effects of the drying–wetting cycle can promote the development of porous channels within sandstone, resulting in cumulative damage. Besides, with an increase in dry–wet cycles, the proportion of small pores and pore throats decreased, while the proportion of medium and large pores and pore throats increased. The combined effects of extrusion crush, tensile fracture, chemical reaction and dissolution of minerals inside the jointed sandstone contributed to the development of mesoscopic pores, resulting in the increase of porosity and permeability of rock samples under the dry–wet cycles. The results provide an important reference value for the stability evaluation of rock mass engineering under long-term dry–wet alternation.
Analysis of the Impact of Selected Dynamic Parameters of a Motor Vehicle on CO2 Emissions Using Logistic Regression
Authors: Rykała Magdalena , Grzelak Małgorzata , Borucka Anna
Published: November 2024

The article analyzes the impact of selected operational parameters of internal combustion engine vehicles on CO2 emissions. The study was preceded by a detailed analysis of the issues related to CO2 emissions in the EU, with a focus on Poland, where the tests were conducted. The key scientific assumption is that individual vehicle users’ behaviors significantly impact global CO2 emissions. Daily use of private vehicles, driving style, and attention to fuel efficiency contribute to cumulative effects that can drive the transformation toward more sustainable transport. Therefore, the study was conducted using real-time empirical data obtained from the vehicles’ OBD (On-Board Diagnostics) diagnostic systems. This approach enabled the creation of a diagnostic tool allowing each vehicle user to assess CO2 emissions and ultimately manage its levels, which is the biggest innovation of the work. Two levels of CO2 emissions were identified as categorical variables in the model, considered either ecological or non-ecological from the perspective of sustainable transport. The CO2 emission threshold of 200 g/km was adopted based on the average age of vehicles in Poland (14.5 years) and Regulation (EC) No 443/2009 of the European Parliament and of the Council. Three models of logistic regression dedicated to different driving cycle phases—starting, urban driving, and highway driving—were proposed and compared. This study demonstrated that during vehicle starting, the most significant factors influencing the probability of ecological driving are vehicle velocity, relative engine load, and relative throttle position, while for the other two types of movement, engine power and torque should also be considered. The logistic regression model for vehicle start-up obtained a value of sensitivity at about 82% and precision at about 85%. In the case of urban driving, the values of the discussed parameters reach significantly higher levels, with sensitivity at around 96% and precision at about 92%. In turn, the model related to highway driving achieved the highest values among the created models, with sensitivity at around 97% and precision at about 93%.
Convolutional Neural Network for Interface Defect Detection in Adhesively Bonded Dissimilar Structures
Authors: Smagulova Damira , Samaitis Vykintas , Jasiuniene Elena
Published: November 2024

This study presents an ultrasonic non-destructive method with convolutional neural networks (CNN) used for the detection of interface defects in adhesively bonded dissimilar structures. Adhesive bonding, as the weakest part of such structures, is prone to defects, making their detection challenging due to various factors, including surface curvature, which causes amplitude variations. Conventional non-destructive methods and processing algorithms may be insufficient to enhance detectability, as some influential factors cannot be fully eliminated. Even after aligning signals reflected from the sample surface and interface, in some cases, due to non-parallel interfaces, persistent amplitude variations remain, significantly affecting defect detectability. To address this problem, a proposed method that integrates ultrasonic NDT and CNN, and which is able to recognize complex patterns and non-linear relationships, is developed in this work. Traditional ultrasonic pulse-echo testing was performed on adhesive structures to collect experimental data and generate C-scan images, covering the time gate from the first interface reflection to the time point where the reflections were attenuated. Two classes of datasets, representing defective and defect-free areas, were fed into the neural network. One subset of the dataset was used for model training, while another subset was used for model validation. Additionally, data collected from a different sample during an independent experiment were used to evaluate the generalization and performance of the neural network. The results demonstrated that the integration of a CNN enabled high prediction accuracy and automation of the analysis process, enhancing efficiency and reliability in detecting interface defects.
Two-Stage Optimization of Mobile Energy Storage Sizing, Pre-Positioning, and Re-Allocation for Resilient Networked Microgrids with Dynamic Boundaries
Authors: Lei Hongtao , Jiang Bo , Liu Yajie , Zhu Cheng , Zhang Tao
Published: November 2024

Networked microgrids (NMGs) enhance the resilience of power systems by enabling mutual support among microgrids via dynamic boundaries. While previous research has optimized the locations of mobile energy storage (MES) devices, the critical aspect of MES capacity sizing has been largely neglected, despite its direct impact on costs. This paper introduces a two-stage optimization framework for MES sizing, pre-positioning, and re-allocation within NMGs. In the first stage, the capacity sizing and pre-positioning of MES devices are optimized before a natural disaster. In the second stage, the re-allocation and active power output of MES devices are adjusted post-disaster, with boundary switches operated based on the damage scenarios. The framework restores unserved loads by either forming isolated microgrids using MES or re-establishing connections between microgrids via smart switches. The proposed framework is modeled mathematically and solved using a customized progressive hedging algorithm. Extensive experiments on modified IEEE 33-node and 69-node systems demonstrate the model’s effectiveness and applicability in improving system resilience.
Emergency Dispatch Strategy Considering Spatiotemporal Evolution of Power Grid Failures Under Typhoon Conditions
Authors: Ren Bixing , Wang Dajiang , Wang Chenggen , Li Qiang , Hu Yingjie , Jia Yongyong
Published: November 2024

The increasing climate-change-induced tropical cyclone phenomena expose the power grid to significant operation risks by disrupting the normal operation of grid components. This paper considers the failure mechanism with respect to critical grid components and reveals a novel spatiotemporal revolution of grid failures during the passage of typhoons. Based on the spatiotemporal evolution of grid failures, a threshold-based emergency scenario set and the corresponding two-stage robust optimization-based emergency dispatch model are developed. The robust emergency dispatch strategy is obtained using a column-and-constraint generation (C&CG) algorithm. The simulation results show that the proposed robust emergency dispatch strategy can guarantee a considerable degree of robustness under multiple emergency scenarios driven by uncertain typhoon conditions.
A Measurement Device for the Normal Spectral Emissivity of Materials Under Low-Temperature and Vacuum Conditions
Authors: Liu Xufeng , Zhang Zhenyuan , Feng Guojin
Published: November 2024

Based on parallel light, a device for measuring sample emissivity under vacuum and low temperature was established. In this paper, a new emissivity measurement formula was designed, which replaces the derivation of Kirchhoff’s law of thermal radiation. The device is designed with a light-weight blackbody, an improved cooling speed, and an improved PID temperature control system to achieve a good temperature stability, close to 1 mK. The device is capable of measuring within a wavelength range of 4 μm to 16 μm. The results of the uncertainty assessment show that the uncertainty of the normal emissivity is better than 1.6% in the range of 4 μm to 7 μm, and better than 0.6% in the range of 7 μm to 14 μm (k = 1) at 0 °C.
Pseudo-Labeling and Time-Series Data Analysis Model for Device Status Diagnostics in Smart Agriculture
Authors: Jung Minwoo , Kim Dae-Young
Published: November 2024

This study proposes an automated data-labeling model that combines a pseudo-labeling algorithm with waveform segmentation based on Long Short-Term Memory (LSTM) to effectively label time-series data in smart agriculture. This model aims to address the inefficiency of manual labeling for large-scale data generated by agricultural systems, enhancing the performance and scalability of predictive models. Our proposed method leverages key features of time-series data to automatically generate labels for new data, thereby improving model accuracy and streamlining data processing. By automating the labeling process, we reduce dependence on manual labeling, which is often labor-intensive and prone to errors in large datasets. This approach enables the efficient preparation of labeled data for applications such as anomaly detection, pattern recognition, and predictive modeling in smart agriculture. Experimental results demonstrate that the automated labeling model achieves 89% accuracy in agricultural environments and reduces data processing time by 30%. Future research will focus on extending the model’s applicability to diverse agricultural settings, enhancing generalization performance, and improving real-time processing capabilities, thereby advancing intelligent and sustainable smart agriculture systems.
A Parallel Monte Carlo Algorithm for the Life Cycle Asset Allocation Problem
Authors: Yang Xueying , Li Chen , Li Xu , Lu Zhonghua
Published: November 2024

Life cycle asset allocation is a crucial aspect of financial planning, especially for pension funds. Traditional methods often face challenges in computational efficiency and applicability to different market conditions. This study aimed to innovatively transplant an algorithm from reinforcement learning that enhances the efficiency and accuracy of life cycle asset allocation. We synergized tabular methods with Monte Carlo simulations to solve the pension problem. This algorithm was designed to correspond states in reinforcement learning to key variables in the pension model: wealth, labor income, consumption level, and proportion of risky assets. Additionally, we used cleaned and modeled survey data from Chinese consumers to validate the model’s optimal decision-making in the Chinese market. Furthermore, we optimized the algorithm using parallel computing to significantly reduce computation time. The proposed algorithm demonstrated superior efficiency compared to the traditional value iteration method. Serial execution of our algorithm took 29.88 min, while parallel execution reduced this to 1.42 min, compared to the 41.15 min required by the value iteration method. These innovations suggest significant potential for improving pension fund management strategies, particularly in the context of the Chinese market.
Case Study of an Integrated Design and Technical Concept for a Scalable Hyperloop System
Authors: Radeck Domenik , Janke Florian , Gatta Federico , Nicolau João , Semino Gabriele , Hofmann Tim , König Nils , Kleikemper Oliver , Hsu Felix He-Mao , Rink Sebastian , Achenbach Felix , Jocher Agnes
Published: November 2024

This paper presents the design process and resulting technical concept for an integrated hyperloop system, aimed at realizing efficient high-speed ground transportation. This study integrates various functions into a coherent and technically feasible solution, with key design decisions that optimize performance and cost-efficiency. An iterative design process with domain-specific experts, regular reviews, and a dataset with a single source of truth were employed to ensure continuous and collective progress. The proposed hyperloop system features a maximum speed of 600 kmh and a capacity of 21 passengers per pod (vehicle). It employs air docks for efficient boarding, electromagnetic suspension (EMS) combined with electrodynamic suspension (EDS) for high-speed lane switching, and short stator motor technology for propulsion. Cooling is managed through water evaporation at an operating pressure of 10 mbar, while a 300 kW inductive power supply (IPS) provides onboard power. The design includes a safety system that avoids emergency exits along the track and utilizes separated safety-critical and high-bandwidth communication. With prefabricated concrete parts used for the tube, construction costs can be reduced and scalability improved. A dimensioned cross-sectional drawing, as well as a preliminary pod mass budget and station layout, are provided, highlighting critical technical systems and their interactions. Calculations of energy consumption per passenger kilometer, accounting for all functions, demonstrate a distinct advantage over existing modes of transportation, achieving greater efficiency even at high speeds and with smaller vehicle sizes. This work demonstrates the potential of a well-integrated hyperloop system to significantly enhance transportation efficiency and sustainability, positioning it as a promising extension to existing modes of travel. The findings offer a solid framework for future hyperloop development, encouraging further research, standardization efforts, and public dissemination for continued advancements.
Nocturnal Ozone Enhancement Induced by Sea-Land Breezes During Summertime in Northern Coastal City Qingdao, China
Authors: Meng He , Liu Jiahong , Wang Lu , Shi Laiyuan , Li Jianjun
Published: November 2024

This study investigated the influence of sea–land breezes on nocturnal spatial and temporal distribution of ozone (O3) and its potential effects on particulate nitrate formation in Qingdao, a coastal city in northern China. Observation campaigns were conducted to measure surface air pollutants and meteorological factors during a typical sea–land breezes event from 22 to 23 July 2022. A coherent Doppler lidar (CDL) system was employed to continuously detect three-dimensional wind fields. The results revealed that nocturnal ozone levels were enhanced by a conversion of sea–land breezes. Initially, the prevailing northerly land breeze transported high concentrations of O3 and other air pollutants from downtown to the Yellow Sea. As the sea breeze developed in the afternoon, the sea breeze front advanced northward, resulting in a flow of high O3 concentrations back into inland areas. This penetration of the sea breeze front led to a notable spike in O3 concentrations between 16:00 on 22 July and 02:00 on 23 July across downtown areas, with an average increase of over 70 μg/m3 within 10 min. Notably, a time lag in peak O3 concentration was observed with southern downtown areas peaking before northern rural areas. During this period, combined pollution of O3 and PM2.5 was also observed. These findings indicated that the nighttime increase in O3 concentrations, coupled with enhanced atmospheric oxidation, would likely promote the secondary conversion of gaseous precursors into PM2.5.
Automatic Segmentation and Evaluation of Mitral Regurgitation Using Doppler Echocardiographic Images
Authors: Liu Guorong , Wang Yulong , Cheng Hanlin , Shi Zhongqing , Qi Zhanru , Yao Jing , Luo Shouhua , Chen Gong
Published: November 2024

Background: Mitral Regurgitation (MR) is a common heart valve disease. Severe MR can lead to pulmonary hypertension, cardiac arrhythmia, and even death. Therefore, early diagnosis and assessment of MR severity are crucial. In this study, we propose a deep learning-based method for segmenting MR regions, aiming to improve the efficiency of MR severity classification and diagnosis. Methods: We enhanced the Efficient Multi-Scale Attention (EMA) module to capture multi-scale features more effectively, thereby improving its segmentation performance on MR regions, which vary widely in size. A total of 367 color Doppler echocardiography images were acquired, with 293 images used for model training and 74 images for testing. To fully validate the capability of the improved EMA module, we use ResUNet as the backbone, partially integrating the enhanced EMA module into the decoder’s upsampling process. The proposed model is then compared with classic models like Deeplabv3+ and PSPNet, as well as UNet, ResUNet, ResUNet with the original EMA module added, and UNet with the improved EMA module added. Results: The experimental results demonstrate that the model proposed in this study achieved the best performance for the segmentation of the MR region on the test dataset: Jaccard (84.37%), MPA (92.39%), Recall (90.91%), and Precision (91.9%). In addition, the classification of MR severity based on the segmentation mask generated by our proposed model also achieved acceptable performance: Accuracy (95.27%), Precision (88.52%), Recall (91.13%), and F1-score (90.30%). Conclusion: The model proposed in this study achieved accurate segmentation of MR regions, and based on its segmentation mask, automatic and accurate assessment of MR severity can be realized, potentially assisting radiologists and cardiologists in making decisions about MR.
DGNMDA: Dual Heterogeneous Graph Neural Network Encoder for miRNA-Disease Association Prediction
Authors: Lu Daying , Zhang Qi , Zheng Chunhou , Li Jian , Yin Zhe
Published: November 2024

In recent years, numerous studies have highlighted the pivotal importance of miRNAs in personalized healthcare, showcasing broad application prospects. miRNAs hold significant potential in disease diagnosis, prognosis assessment, and therapeutic target discovery, making them an integral part of precision medicine. They are expected to enable precise disease subtyping and risk prediction, thereby advancing the development of precision medicine. GNNs, a class of deep learning architectures tailored for graph data analysis, have greatly facilitated the advancement of miRNA-disease association prediction algorithms. However, current methods often fall short in leveraging network node information, particularly in utilizing global information while neglecting the importance of local information. Effectively harnessing both local and global information remains a pressing challenge. To tackle this challenge, we propose an innovative model named DGNMDA. Initially, we constructed various miRNA and disease similarity networks based on authoritative databases. Subsequently, we creatively design a dual heterogeneous graph neural network encoder capable of efficiently learning feature information between adjacent nodes and similarity information across the entire graph. Additionally, we develop a specialized fine-grained multi-layer feature interaction gating mechanism to integrate outputs from the neural network encoders to identify novel associations connecting miRNAs with diseases. We evaluate our model using 5-fold cross-validation and real-world disease case studies, based on the HMDD V3.2 dataset. Our method demonstrates superior performance compared to existing approaches in various tasks, confirming the effectiveness and potential of DGNMDA as a robust method for predicting miRNA-disease associations.
Systemic Lipid Metabolism Dysregulation as a Possible Driving Force of Fracture Non-Unions?
Authors: Grgurević Lovorka , Novak Ruđer , Jambrošić Lucija , Močibob Marko , Jaganjac Morana , Halasz Mirna , Salai Grgur , Hrkač Stela , Milošević Milan , Vlahović Tomislav , Romić Jeronim , Matičić Dražen , Vidović Dinko
Published: November 2024

Introduction: Non-unions are fractures that do not heal properly, resulting in a false joint formation at the fracture site. This condition leads to major health issues and imposes a burden on national healthcare systems. The etiology of non-unions is still not fully understood; therefore, we aimed to identify potential systemic factors that may contribute to their formation. Materials and methods: We conducted a cross-sectional concomitant proteomic and metabolomic pilot study of blood plasma in patients with non-unions (N = 11) and compared them with patients with bone fracture in the normal active healing phase (N = 12). Results: We found five significantly upregulated proteins in the non-union group: immunoglobulin heavy variable 3–74, immunoglobulin lambda variable 2–18, low-density lipoprotein receptor-related protein 4, zinc-alpha-2-glycoprotein, and serum amyloid A-1 protein; and we found one downregulated protein: cystatin-C. The metabolomic study found differences in alanine, aspartate and glutamate metabolism pathways between two groups. Conclusions: The combined results of proteomic and metabolomic analyses suggest that the dysregulation of lipid metabolism may contribute to non-union formation.
Adverse Effects of Aβ1-42 Oligomers: Impaired Contextual Memory and Altered Intrinsic Properties of CA1 Pyramidal Neurons
Authors: Min-Kaung-Wint-Mon  , Kida Hiroyuki , Kanehisa Itsuki , Kurose Masahiko , Ishikawa Junko , Sakimoto Yuya , Paw-Min-Thein-Oo  , Kimura Ryoichi , Mitsushima Dai
Published: November 2024

Aβ1-42 (amyloid beta) oligomers, the major neurotoxic culprits in Alzheimer’s disease, initiate early pathophysiological events, including neuronal hyperactivity, that underlie aberrant network activity and cognitive impairment. Although several synaptotoxic effects have been extensively studied, neuronal hyperexcitability, which may also contribute to cognitive deficits, is not fully understood. Here, we found several adverse effects of in vivo injection of Aβ1-42 oligomers on contextual memory and intrinsic properties of CA1 pyramidal neurons. Male rats underwent behavioral and electrophysiological studies 1 week after microinjections into the dorsal CA1 region, followed by histological analysis. After 1 week, Aβ1-42 oligomers impaired contextual learning without affecting basic physiological functions and triggered training-induced neuronal excitability. Furthermore, riluzole, a persistent sodium current (INaP) blocker, dose-dependently reduced Aβ1-42 oligomer-induced hyperexcitability. Congo red staining, which detects insoluble amyloid deposits, further identified labeling of CA1 pyramidal neurons while immunohistochemistry with lecanemab, which detects soluble Aβ oligomers, revealed immunoreactivity of both pyramidal and non-pyramidal cells in the target area. Therefore, our study suggests that a single injection of Aβ1-42 oligomers resulted in contextual memory deficits along with concomitant neuronal hyperexcitability and amyloid deposition in the CA1 region after 1 week.
Common Genetic Factors May Play a Role in the Relationships Between Body Composition, Adipokines, and Low-Back-Pain-Related Disability
Authors: Tarabeih Nader , Kalinkovich Alexander , Ashkenazi Shai , Shalata Adel , Livshits Gregory
Published: November 2024

In this study, we evaluated the contribution of the putative genetic factors into the established associations between selected circulating adipokine levels, body composition measurements, and low-back-pain-related disability scores (LBP_DS). A total of 1078 individuals from 98 nuclear families (with 1 to 11 siblings per family) were examined. A detailed self-report questionnaire was used to collect LBP disability data; body composition (fat, skeletal muscle mass, and extracellular water (ECW)) was assessed using the bioimpedance method; plasma levels of adipokines were measured by ELISA. Pedigree-based statistical analysis methods were used, including family-based variance component analysis (VCA) and principal phenotype analysis (PPA), to estimate the contribution of potential genetic and environmental factors. The VCA revealed a significant additive genetic component in LBP_DS and for the selected body composition phenotypes and adipokines. The study also revealed that both adipokines (GDF-15, chemerin, and follistatin) and body composition variables (BMI, fat mass/weight, waist circumference, and ECW) were genetically correlated with LBP_DS. Next, PPA generated two synthetic phenotypes: PPCT (combining cytokines) and PPBC (combining body composition variables). There was no significant correlation between the putative genetic factors underlying the created PPs. However, each of them displayed a significant genetic correlation with LBP_DS. These findings indicate that genetic factors that are assumingly common for several adipokine variations and several body composition measurements, respectively, presumably have a pleotropic genetic influence on the LBP_DS variation, independently from one another. This, in turn, suggests that the alleged genetic factors employing pleiotropic effects on LBP_DS have a complex and probably non-overlapping composition.
Comparison of Different Keratinocyte Cell Line Models for Analysis of NLRP1 Inflammasome Activation
Authors: Wang Tian , Yazdi Amir S. , Panayotova-Dimitrova Diana
Published: November 2024

The NLRP1 (nucleotide-binding domain, leucine-rich-containing family, pyrin domain-containing-1) inflammasome is the most important inflammasome in human keratinocytes. It plays a crucial role in regulating innate immunity in the skin. This study aimed to evaluate NLRP1 inflammasome activation and the corresponding levels of detection in different keratinocyte cell lines to identify a suitable in vitro model for analyzing inflammasome activation in keratinocytes. We compared NLRP1 inflammasome activation, expression, and cell death among primary keratinocytes and immortalized keratinocyte cell lines HaCaT, HaSKpw, and SVTERT upon stimulation with ultraviolet B (UVB) irradiation or talabostat. The effects of both NLRP1 inducers on cell death and the modification of NLRP1 molecules were examined using fluorescence-activated cell sorting analysis, Western blotting, and an enzyme-linked immunosorbent assay. The key inflammasome components had varied expression levels among the keratinocyte cell models, with the highest expression observed in primary keratinocytes. Moreover, our data showed that both UVB and talabostat triggered cell death, and NLRP1 inflammasome activation was readily detected in primary keratinocytes but not in the analyzed immortalized keratinocyte cell lines. Therefore, we do not recommend the use of the immortalized keratinocyte cell lines HaCaT, HaSKpw, and SVTERT for analyzing inflammasome activation in keratinocytes; we strongly recommend the use of primary keratinocytes for these studies.
Estrogen Regulates Ca2+ to Promote Mitochondrial Function Through G-Protein-Coupled Estrogen Receptors During Oocyte Maturation
Authors: Liu Qingyang , Li Jingmei , Li Yanxue , Cheng Ming , Zhang Hui , Ma Baohua
Published: November 2024

Estrogen is a steroid hormone that plays a key role in regulating many physiological processes, such as follicle activation and development and oocyte maturation in mammals. Ca2+ is crucial in oogenesis, oocyte maturation, ovulation, and fertilization. However, the mechanism by which estrogen regulates Ca2+ during oocyte maturation in mice has not been reported. This study revealed that Ca2+ levels in oocytes significantly increase during the 4–12 h period in vitro. Oocytes treated with 0.1 µM estrogen and 1 µM G1, a G-protein-coupled estrogen receptor (GPER) agonist, showed significantly increased Ca2+ levels, while treatment with 1 µM G15, an antagonist of GPER, significantly decreased Ca2+ levels. Notably, estrogen regulates Ca2+ in oocytes through the GPER pathway and promotes the expression of the Ca2+-producing protein EPAC1. In addition, estrogen alleviates the inhibitory effect of the Ca2+ chelator BAPTA-AM during oocyte maturation by promoting Ca2+ production. Furthermore, estrogen can promote the expression of the mitochondrial generation-associated protein SIRT1 through the GPER pathway, alleviate mitochondrial oxidative damage caused by BAPTA-AM, and restore the mitochondrial membrane potential level. Collectively, this study demonstrates that estrogen can regulate Ca2+ through the GPER-EPAC1 pathway and promote the expression of SIRT1, which promotes oocyte mitochondrial function during oocyte maturation.
Differential Lipid Signatures of Lumbar and Cisternal Cerebrospinal Fluid
Authors: Toft-Bertelsen Trine L. , Andreassen Søren Norge , Norager Nicolas H. , Simonsen Anja Hviid , Hasselbalch Steen Gregers , Juhler Marianne , MacAulay Nanna
Published: November 2024

Background: The molecular composition of cerebrospinal fluid (CSF) is often used as a key indicator of biochemical alterations within distinct brain and spinal cord fluid compartments. The CSF protein content in lumbar CSF samples is widely employed as a biomarker matrix for diagnosing brain-related pathological conditions. CSF lipid profiles may serve as promising complementary diagnostics, but it remains unresolved if the lipid distribution is consistent along the neuroaxis. Methods: The lipid composition was determined with liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) in cisternal CSF obtained from healthy subjects undergoing preventive surgery of an unruptured aneurism (n = 11) and lumbar CSF obtained from individuals referred for the clinical evaluation of cognitive dysfunction but subsequently cleared and deemed healthy (n = 19). Results: We reveal discernible variations in lipid composition along the neuroaxis, with a higher overall lipid concentration in cisternal CSF, although with different relative distributions of the various lipid classes in the two compartments. The cisternal CSF contained elevated levels of most lipid classes, e.g., sphingomyelins, lysophosphatidylcholines, plasmenylphosphatidylcholines, phosphatidic acids, and triacylglycerols, whereas a few select lipids from the classes of fatty acids, phosphatidylcholines, amides and plasmenylphosphatidylethanolamines were, oppositely, elevated in the lumbar CSF pool. Conclusions: The distinct lipid distribution along the neuroaxis illustrates that the molecular constituents in these two CSF compartments are not uniform. These findings emphasize the necessity of establishing a lumbar lipid index for the accurate interpretation of the cranial CSF lipid profile.
Unraveling the Immune Web: Advances in SMI Capsular Fibrosis from Molecular Insights to Preclinical Breakthroughs
Authors: Schoberleitner Ines , Faserl Klaus , Lackner Michaela , Coraça-Huber Débora C. , Augustin Angela , Imsirovic Anja , Sigl Stephan , Wolfram Dolores
Published: November 2024

Breast implant surgery has evolved significantly, yet challenges such as capsular contracture remain a persistent concern. This review presents an in-depth analysis of recent advancements in understanding the immune mechanisms and clinical implications associated with silicone mammary implants (SMIs). The article systematically examines the complex interplay between immune responses and capsular fibrosis, emphasizing the pathophysiological mechanisms of inflammation in the etiology of this fibrotic response. It discusses innovations in biomaterial science, including the development of novel anti-biofilm coatings and immunomodulatory surfaces designed to enhance implant integration and minimize complications. Emphasis is placed on personalized risk assessment strategies, leveraging molecular insights to tailor interventions and improve patient outcomes. Emerging therapeutic targets, advancements in surgical techniques, and the refinement of post-operative care are also explored. Despite notable progress, challenges such as the variability in immune responses, the long-term efficacy of new interventions, and ethical considerations remain. Future research directions are identified, focusing on personalized medicine, advanced biomaterials, and bridging preclinical findings with clinical applications. As we advance from bench to bedside, this review illuminates the path forward, where interdisciplinary collaboration and continued inquiry weave together to enhance the art and science of breast implant surgery, transforming patient care into a realm of precision and excellence.
Loss of Sterol Biosynthesis in Economically Important Plant Pests and Pathogens: A Review of a Potential Target for Pest Control
Authors: Dahlin Paul , Ruthes Andrea Caroline
Published: November 2024

Sterol biosynthesis is a crucial metabolic pathway in plants and various plant pathogens. Their vital physiological role in multicellular organisms and their effects on growth and reproduction underline their importance as membrane compounds, hormone precursors, and signaling molecules. Insects, nematodes, and oomycetes of the Peronosporales group, which harbor important agricultural pests and pathogens, have lost the ability to synthesize their own sterols. These organisms rely on the acquisition of sterols from their host and are dependent on the sterol composition of the host. It is thought that sterol-synthesizing enzymes were lost during co-evolution with the hosts, which provided the organisms with sufficient amounts of the required sterols. To meet the essential requirements of these organisms, some sterol auxotrophs retained a few remaining sterol-modifying enzymes. Several molecular and biochemical investigations have suggested promising avenues for pest and pathogen control by targeting host sterol composition, sterol uptake, or sterol modification in organisms that have lost the ability to biosynthesize sterol de novo. This review examines the loss of sterol biosynthesis de novo in insects, nematodes, and oomycetes with the aim of investigating the sterol metabolic constraints and sterol acquisition of these organisms. This will shed light on its potential as a control target for the management of sterol-dependent organisms in a comprehensive agronomic approach.
Extracellular DNA and Deoxyribonuclease Activity as Prognostic Markers in Sepsis
Authors: Janíková Monika , Pribulová Nikola , Kmeťová Katarína , Macáková Kristína , Dobišová Anna , Kopčová Michaela , Bucová Mária , Vlková Barbora , Celec Peter
Published: November 2024

Background/Objectives: Sepsis is characterized by a dysregulated immune response to infection and is associated with high lethality. Extracellular DNA (ecDNA) has drawn significant interest as a damage-associated molecular pattern because of its potential involvement in the pathophysiology of sepsis. Methods: In this study, we examined the ecDNA concentration in 27 adult patients admitted to the intensive care unit. Fluorometry and quantitative PCR were used for the assessment of ecDNA. In addition, deoxyribonuclease activity was measured as a potential modulator of ecDNA. Results: Our findings reveal nearly 5-fold higher concentrations of ecDNA in non-survivors, suggesting its potential as a prognostic indicator for sepsis outcomes on day 7. Interestingly, the subcellular origin of ecDNA was similar between patients diagnosed with systemic inflammatory response syndrome, sepsis, and septic shock. Deoxyribonuclease activity, implicated in the cleavage of ecDNA, was comparable across all patient groups. Conclusions: To establish the prognostic value of ecDNA as a biomarker, further investigations within a larger patient cohort are needed. Nevertheless, our results suggest that high ecDNA in sepsis patients represents a negative prognostic biomarker.
Controlled Coffee Intake Enhances Erythrocyte Deformability, Na,K-ATPase Activity, and GSH/GSSG Ratio in Healthy Young Adults
Authors: Radosinska Dominika , Jasenovec Tomas , Golianova Alzbeta , Szadvari Ivan , Vazan Rastislav , Kovacicova Ivona , Snurikova Denisa , Vrbjar Norbert , Radosinska Jana
Published: November 2024

Background: Published studies suggest that regular coffee consumption may reduce the risk of various diseases. However, many of these studies relied on questionnaire-based data, limiting their ability to identify the specific biological mechanisms behind the observed effects. This study focuses on controlled coffee consumption among healthy young adults to clarify its effects on erythrocyte properties. The functional condition of erythrocytes is important as it affects both macro- and microcirculation. Additionally, since erythrocytes are not true cells, they are particularly sensitive to biochemical and biophysical changes when exposed to biologically active substances. Methods: After a washout period, 33 healthy young volunteers were asked to consume a standardized dose of a coffee beverage daily for 3 weeks. Basic hematological and body composition parameters were recorded before and after the intervention. Erythrocyte functional status was evaluated based on the following measurements: deformability, osmotic resistance, Na,K-ATPase activity, and nitric oxide production, along with monitoring oxidative stress markers. Results: After a coffee consumption period, both erythrocyte count and hematocrit value increased, while body composition remained unchanged. Erythrocyte deformability improved across a range of shear stress values typical of human circulation. This improvement was accompanied with enhanced Na,K-ATPase activity in erythrocyte membranes in the wide range of sodium ion concentrations, as well as increased nitric oxide production by erythrocytes. Additionally, a higher GSH/GSSG ratio, indicating a shift towards a more favorable antioxidant balance, was observed in erythrocytes following the coffee intake period. Conclusions: The results of this study suggest that controlled coffee intake in healthy young adults can positively influence various indices of erythrocyte functional status. Although the observed statistically significant changes were modest, the findings consistently indicate a positive modulation of erythrocyte properties—cell deformability, oxidative resilience, and active membrane transport of cations—following coffee consumption.
Preliminary Investigation of a Potential Optical Biosensor Using the Diamond™ Nucleic Acid Dye Applied to DNA and Friction Ridge Analysis from Fingerprint Traces
Authors: Czarnomska Martyna , Lewkowicz Aneta , Gruszczyńska Emilia , Walczewska-Szewc Katarzyna , Gryczyński Zygmunt , Bojarski Piotr , Steinborn Sławomir
Published: November 2024

Developments in science and technology lead to an increasing use of scientific evidence in litigation. Interdisciplinary research can improve current procedures and introduce new ones for the disclosure and examination of evidence. The dactyloscopic trace is used for personal identification by matching minutiae (the minimum required may vary by country) or for extracting DNA material from the trace under investigation. The research presented in this article aims to propose the merging of two currently used personal identification methods, DNA analysis and dactyloscopic trace analysis, which are currently treated as separate forensic traces found at a crime scene. Namely, the forensic trace to be analyzed is the dactyloscopic trace containing DNA, and both sources of information needed for identification are examined as one. Promega’s Diamond™ Nucleic Acid Dye, presented as a safe alternative to ethidium bromide, works by binding to single- and double-stranded DNA and is used to visualize the separation of material in a gel and to detect DNA in forensic samples. Spectroscopic studies as absorption and emission spectra and fluorescence microscopy observations presented in our research confirm that Diamond™ Nucleic Acid Dye can also be used to visualize fingerprints on non-absorbent surfaces and that combining the two methods into one can significantly increase the evidential value and contribute to the design of an innovative fast-acting optical biosensor.
Lasting Deficiencies in Vergence Eye Movements in Patients with Peripheral or Central Vertigo: Improvements After Four Sessions of REMOBI Neurotraining and Associated Functional Benefits
Authors: Kapoula Zoï , Aakash Ganesan , Rèmi Guèrin , Bauwens Alain , Martiat Benoit , Leonard Valentine
Published: November 2024

The vestibular function is in synergism with the oculomotor vergence. Vertigo may be related to vergence disorders and conversely, vestibular pathologies may affect vergence. To consolidate this hypothesis, we conducted a study at the vestibular orthoptic clinic of the Bastogne Hospital. Fourteen patients with vertigo history appearing 2 weeks to 8 years ago, aged 30 to 65 years were studied; at the moment of the eye movement study, no patient had acute attack of vertigo. The origin of vertigo varied (Meniere’s disease, organic pathology, sensitivity to visual movement). An assessment with objective measurement of vergence (single-step protocol) was carried out with the REMOBI technology coupled with binocular video-oculography in sitting and standing positions. Four neuro-rehabilitation sessions of vergence eye movements were performed with the double-step in-depth protocol, alternating sitting and standing positions to involve different postural and vestibular functions. An assessment of vergence was done again 1 to 2 months later. The initial assessment revealed problems of magnitude and/or speed or variability of vergence for 11 of the patients relative to controls (published by the group in previous studies). After neuro-rehabilitation, an improvement was observed in eight patients. Patients reported a clear improvement of their self confidence in moving in the space. Posture measures done before rehabilitation comparing eyes fixating or closed or while making near–far vergence eye movements indicated lower medio-lateral acceleration when doing vergence eye movements in patients with vertigo history of functional origin. The results are in favor of the hypothesis of a symbiosis between vergence and vestibular function and the interest of diagnosis and rehabilitation of the vergence disorder in patients with vertigo history in the absence of acute vertigo attack.
Natural Semantic Networks: The Concept of Mistreatment and Good Treatment in Students of Health Careers
Authors: Ortega-Bastidas Javiera , Baquedano-Rodríguez Marjorie , Bastías-Vega Nancy , Pérez-Villalobos Cristhian , Schilling-Norman Mary Jane , Parra-Ponce Paula , Martín Ricardo Arteaga-San , Hechenleitner-Carvallo Marcela , Ríos-Teillier María Isabel , Paredes-Villarroel Ximena , Peralta-Camposano José , Ricouz-Moya Alejandra , Soto-Faúndes Catherine , Williams-Oyarce Carolina
Published: November 2024

Natural semantic networks (NSNs) provide an approach to understanding concepts in terms of their density and strength. The objective of this study was to conceptualize mistreatment and good treatment among health science students in Chile, according to gender and training cycle. Methods: A mixed-methods study with a relational scope was conducted, involving 994 health science students. The present study is exploratory and combines both qualitative and quantitative analysis. We utilized the NSN technique, applying a questionnaire via SurveyMonkey after obtaining informed consent. Results: A total of 4386 defining words for mistreatment were identified, with the most relevant being ‘aggression’, ‘abuse’, and ‘violence’. In the case of good treatment, a total of 4146 defining words were obtained, with ‘respect’, ‘empathy’, and ‘kindness’ standing out. For good treatment, a statistically significant relationship was observed between the defining words and the variables of gender (χ2 = 41.158; p < 0.05) and training cycle (χ2 = 28.698; p < 0.05). For mistreatment, a statistically significant relationship was found only with training cycle (χ2 = 35.858; p < 0.05). Conclusions: Exploring the meanings associated with mistreatment and good treatment has a theoretical implication in the way in which two highly polysemic aspects of the educational environment can be understood.