bluuebunny/crossref_metadata_2025 huggingface dataset:
A Combined Windowing and Deep Learning Model for the Classification of Brain Disorders Based on Electroencephalogram Signals
Authors: Abooelzahab Dina , Zaher Nawal , Soliman Abdel Hamid , Chibelushi Claude
Published: February 2025

Background: The electroencephalogram (EEG) is essential for diagnosing and classifying brain disorders, enabling early medical intervention. Its ability to identify brain abnormalities has increased its clinical use in assessing changes in brain activity. Recent advancements in deep learning have introduced effective methods for interpreting EEG signals, utilizing large datasets for enhanced accuracy. Objective: This study presents a deep learning-based model designed to classify EEG data with better accuracy compared to existing approaches. Methods: The model consists of three key components: data selection, feature extraction, and classification. Data selection employs a windowing technique, while the feature extraction and classification stages use a deep learning framework combining a convolutional neural network (CNN) and a Long Short-Term Memory (LSTM) network. The resulting architecture includes up to 18 layers. The model was evaluated using the Temple University Hospital (TUH) dataset, comprising data from 2785 patients, ensuring its applicability to real-world scenarios. Results: Comparative performance analysis shows that this approach surpasses existing methods in accuracy, sensitivity, and specificity. Conclusions: This study highlights the potential of deep learning in enhancing EEG signal interpretation, offering a pathway to more accurate and efficient diagnoses of brain disorders for clinical applications.
Heterozygosity-Rich Regions in Canine Genome: Can They Serve as Indicators of Balancing Selection?
Authors: Halvoník Adrián , Moravčíková Nina , Vostrý Luboš , Vostra-Vydrova Hana , Mészáros Gábor , Demir Eymen , Chalupková Monika , Kasarda Radovan
Published: February 2025

Compared to the negative effect of directional selection on genetic diversity, balancing selection acts oppositely and maintains variability across the genome. This study aims to articulate whether balancing selection leads to heterozygosity-rich region islands (HRRIs) forming in the canine genome by investigating 1000 animals belonging to 50 dog breeds via 153,733 autosomal SNPs. A consecutive SNP-based approach was used to identify heterozygosity-rich regions (HRRs). Signals of balancing selection in the genome of studied breeds were then assessed with Tajima’s D statistics. A total of 72,062 HRRs with an average length of 324 kb were detected to be unevenly distributed across the genome. A total of 509 and 450 genomic regions were classified as HRRIs and balancing selection signals, respectively. Although the genome-wide distributions of HRRIs varied across breeds, several HRRIs were found in the same locations across multiple breeds. A total of 109 genomic regions were classified as both HRRIs and signals of balancing selection. Even though the genomic coordinates of HRRIs and balancing selection signals did not fully overlap across all genomic regions, balancing selection may play a significant role in maintaining diversity in regions associated with various cancer diseases, immune response, and bone, skin, and cartilage tissue development.
First Insights into the Home Range of an Adult Male Mediterranean Monk Seal Monachus monachus in the Ionian Sea, Greece, and Considerations About the Future Management of the Area
Authors: Panou Aliki , Tsoukalas Spyros , Anestis Anastasios , Bundone Luigi
Published: February 2025

From August 2021 to December 2023, one adult male Mediterranean monk seal was repeatedly registered, through a systematic monitoring camera system, frequenting a marine cave in southern Kefalonia Island, central Ionian Sea, Greece. The presence of the same adult seal in a series of caves and overhangs in a bay in northwestern Zakynthos, southern Ionian Sea, in September 2023 and May 2024 was verified through opportunistic surveys and citizen science. The two locations are ca. 15 km apart and each is located in a different marine NATURA 2000 site. Appropriate conservation measures need to take into consideration the fact that seals do move between Kefalonia and Zakynthos (and possibly also other Ionian islands) and that the entire area has to be considered as a single “conservation unit” rather than elaborating protection measures on a small scale around a couple of resting and pupping caves alone. A full network of marine caves under strict protection surrounded by a buffer zone, taking into account at least the species’ home range, is needed in order to substantially cover the monk seal’s critical terrestrial habitats throughout the Ionian Sea.
Research on Fitting and Denoising Subway Shield-Tunnel Cross-Section Point-Cloud Data Based on the Huber Loss Function
Authors: Bao Yan , Li Sixuan , Tang Chao , Sun Zhe , Yang Kun , Wang Yong
Published: February 2025

The expansion of tunnel scale has led to a massive demand for inspections. Light Detection And Ranging (LiDAR) has been widely applied in tunnel structure inspections due to its fast data acquisition speed and strong environmental adaptability. However, raw tunnel point-cloud data contain noise point clouds, such as non-structural facilities, which affect the detection of tunnel lining structures. Methods such as point-cloud filtering and machine learning have been applied to tunnel point-cloud denoising, but these methods usually require a lot of manual data preprocessing. In order to directly denoise the tunnel point cloud without preprocessing, this study proposes a comprehensive processing method for cross-section fitting and point-cloud denoising in subway shield tunnels based on the Huber loss function. The proposed method is compared with classical fitting denoising methods such as the least-squares method and random sample consensus (RANSAC). This study is experimentally verified with 40 m long shield-tunnel point-cloud data. Experimental results show that the method proposed in this study can more accurately fit the geometric parameters of the tunnel lining structure and denoise the point-cloud data, achieving a better denoising effect. Meanwhile, since coordinate system transformations are required during the point-cloud denoising process to handle the data, manual rotations of the coordinate system can introduce errors. This study simultaneously combines the Huber loss function with principal component analysis (PCA) and proposes a three-dimensional spatial coordinate system transformation method for tunnel point-cloud data based on the characteristics of data distribution.
Using Tablets to Teach Basic Literacy Skills to Kindergarten Students: A Case Study
Authors: Fokides Emmanuel , Klaoudatou Dionysia
Published: February 2025

Tablets have long been employed across a variety of educational domains. Given the ongoing debate regarding their effect on skill and knowledge development, especially among very young learners, a study was conducted to evaluate their effectiveness against conventional educational materials. The study involved 76 kindergarten students, employing a between-subjects design to investigate basic literacy skills. These skills included letter name identification and letter sound recognition. To measure knowledge acquisition, evaluation tests were administered, and questionnaires were used to collect data on students’ motivation, engagement, and enjoyment. The findings revealed that tablets significantly enhanced the targeted skills compared to conventional materials. Tablets were also rated higher in enjoyment, engagement, and motivation. Importantly, these factors significantly impacted learning outcomes with tablets, while they had no effect in the case of conventional materials.
Performance-Based Seismic Design
Authors: Nastri Elide , Pisapia Alessandro
Published: February 2025

The increasing complexity of modern structures, combined with the pressing demand for resilient and sustainable structures, has driven significant advancements in earthquake engineering [...]
Improved Autocollimator for Roll Angle Measurement with an Enlarged Measuring Range
Authors: Guo Yan , Zhang Yu , Ji Jiali , Yan Qing , Di Huige , Wang Li , Hua Dengxin
Published: February 2025

An autocollimator is a goniometer established according to the principle of autocollimation, but it is ineffective for measuring the roll angle. This paper proposes an improved autocollimator available for large-range roll angle measurement, which maintains the optical structure of the classic one while incorporating a wedge prism (WP) working in transmissive mode as a roll angle sensing element to dissociate the collimated beam into two beams. According to the moving paths of the two light spots focused on the photodetector, the roll angle of the WP can be solved. The measuring method is expounded, and the calibration results reveal that the improved autocollimator has an accuracy of ±13.55 arcsec over a range of 360°, confirming its feasibility for roll angle measurement where a large measuring range is required.
Seismic Shear Strength Prediction of Reinforced Concrete Shear Walls by Stacking Multiple Machine Learning Models
Authors: Tian Siming , Ni Xiangyong , Wang Yang
Published: February 2025

Reinforced concrete shear walls (RCSWs) are complicated to compute their shear capacity due to their large cross-sectional height-to-thickness ratios and the fact that they are subjected to vertical loads. Numerous factors influence RCSWs’ shear strength capacity, and the analytical models find it challenging to fully account for each factor’s impact on RCSWs’ shear-bearing capacity. Machine learning (ML) technology can deeply capture the mapping relationship between each input feature and the target value, and provide a more flexible and effective prediction method for RCSW shear-bearing capacity. To this end, a shear capacity test database containing 583 RCSW specimens was first established and characterized, and then the database was employed to train single, ensemble, and deep learning models for the shear strength of shear walls and combined with hyper-parameter tuning to enhance each model’s prediction performance, after which the prediction performance of each model was compared. Then, the ML models were contrasted with conventional techniques founded on the mechanical premise. Finally, in order to improve the prediction accuracy and reliability of the ML methods, the individually trained models were integrated into a stacking model using the stacking method, and the stacking model’s prediction performance was assessed. The results of this study show that in the single model, the test set R2 of the decision tree (DT) reaches 0.94, showing good trend-capturing ability. Among the ensemble models, Gradient Boosting (GB) performs the best and is comparable to DT in terms of RMSE and R2 and significantly outperforms other ensemble methods, such as Random Forest (RF) and Bagging. Deep Neural Networks (DNNs) show the strongest predictive ability among all models, with the lowest RMSE (263 kN) and a test R2 of 0.95, which is much better than the majority of ensemble models. The ML models show high accuracy and reliability compared to the traditional RC shear wall shear capacity models. The stacking model has an R2 of 0.98 and a CoV of 0.147 in the test set, and it is much better than other independent ML models (R2 = 0.88~0.95, CoV = 0.179~0.651).
Inadvertent Dural Puncture Causing Low Pressure Headache and Peripheral Vestibular Bilateral Damage
Authors: Longridge N. S. , Mallinson A. I. , Robinson R. G.
Published: February 2025

Introduction: This edition of the Audiology Research journal is dedicated to Dr. John Epley. For this reason, we would like to present a very unusual case involving the development of a bilateral abnormality of the otolith organs. The otoliths are the structures from which calcium particles detach to induce benign paroxysmal positional vertigo, the disorder for which Dr. Epley is famous for managing. Case report: This case report outlines an unusual presentation of vestibular pathology involving the otoliths. Discussion: We suggest that the atypical presentation may be related to a bilaterally asymmetrical insult to the otoliths. Conclusions: The central insult suffered by this patient resulted in bilateral peripheral otolithic pathology.
Enumerating the Number of Spanning Trees of Pyramid Graphs Based on Some Nonahedral Graphs
Authors: Asiri Ahmad , Daoud Salama Nagy
Published: February 2025

The enumeration of spanning trees in various graph forms has been made easier by the study of electrically equivalent transformations, which was motivated by Kirchhoff’s work on electrical networks. In this work, using knowledge of difference equations, the electrically equivalent transformations and rules of weighted generating function are used to calculate the explicit formulas of the number of spanning trees of novel pyramid graph types based on some nonahedral graphs. Lastly, we compare our graphs’ entropy with that of other average-degree graphs that have been researched.
Convergence Analysis for Cayley Variational Inclusion Problem Involving XOR and XNOR Operations
Authors: Arifuzzaman  , Irfan Syed Shakaib , Ahmad Iqbal
Published: February 2025

In this article, we introduce and study a generalized Cayley variational inclusion problem incorporating XOR and XNOR operations. We establish an equivalent fixed-point formulation and demonstrate the Lipschitz continuity of the generalized Cayley approximation operator. Furthermore, we analyze the existence and convergence of the proposed problem using an implicit iterative algorithm. The iterative algorithm and numerical results presented in this study significantly enhance previously known findings in this domain. Finally, a numerical result is provided to support our main result and validate the proposed algorithm using MATLAB programming.
Dupilumab for Chronic Obstructive Pulmonary Disease: A Systematic Review
Authors: Young Julia , Spisany Taylor , Guidry Corey M. , Hong Jisoo , Le Jessica , El Rassi Edward , Boylan Paul M.
Published: February 2025

Background/Objectives: Dupilumab was recently approved to treat eosinophilic phenotypes of chronic obstructive pulmonary disease (COPD). This systematic review aimed to collect and appraise the efficacy and safety of dupilumab to treat patients with COPD. Methods: Databases searched included Ovid Medline, Embase, Web of Science, Directory of Open Access Journals, and International Pharmaceutical Abstracts. Experimental and observational studies, including case reports/series, were eligible for inclusion. Reports were independently screened, appraised, and extracted by three investigators; disagreements were resolved through discussion and agreement. Quality appraisal was conducted using the Cochrane Risk of Bias Tool 2.0, Newcastle–Ottawa Scale, and JBI Checklist for experimental, observational, and case studies, respectively. Results: A total of 307 unique reports were identified, of which 17 were included in this systematic review. The majority (n = 11, 64.7%) of reports presented evidence from the BOREAS and NOTUS trials, the landmark trials serving as the basis for dupilumab’s approval to treat refractory eosinophilic COPD. The results from this systematic review found that dupilumab reduced exacerbations of COPD in patients treated with inhaled triple therapy and it was well tolerated. Conclusions: When added to inhaled triple therapy, dupilumab may decrease patients’ risk for acute exacerbations of COPD. Additional research is necessary to substantiate these findings for broader generalizability, including populations with non-eosinophilic COPD phenotypes.
Targeting Atherosclerosis via NEDD4L Signaling—A Review of the Current Literature
Authors: Laurindo Lucas Fornari , Dogani Rodrigues Victória , de Lima Enzo Pereira , Leme Boaro Beatriz , Mendes Peloi Julia Maria , Ferraroni Sanches Raquel Cristina , Penteado Detregiachi Cláudia Rucco , José Tofano Ricardo , Angelica Miglino Maria , Sloan Katia Portero , Sloan Lance Alan , Barbalho Sandra Maria
Published: February 2025

Cardiovascular diseases are the primary cause of mortality worldwide. In this scenario, atherosclerotic cardiovascular outcomes dominate since their incidence increases as populations grow and age. Atherosclerosis is a chronic inflammatory disease that affects arteries. Although its pathophysiology is heterogeneous, some genes are indissociably associated with its occurrence, and understanding their effects on the disease’s occurrence could undoubtedly define effective screening and treatment strategies. One such gene is NEDD4L. The NEDD4L gene is related to ubiquitin ligase enzyme activities. It is essential to regulate vascular inflammation, atherosclerosis plaque stability, endothelial and vascular smooth cell function, and lipid metabolism, particularly in controlling cholesterol levels. However, the evidence is dubious, and no review has yet synthesized the effects of targeting NEDD4L on atherosclerosis. Therefore, our review aims to fill this gap by analyzing the literature on NEDD4L concerning atherosclerosis occurrence. To achieve this goal, we performed a systematic literature search of reputable databases, including PubMed, Google Scholar, Web of Science, Scopus, and Embase. The inclusion criteria comprised peer-reviewed original studies using in vitro and animal models due to the unavailability of relevant clinical studies. Systematic reviews, meta-analyses, and articles that did not focus on the relationship between NEDD4L and atherosclerosis and those unrelated to this health condition were excluded. Studies not written in the English language were also excluded. The search strategy included studies from January 2000 to January 2025 in the final analysis to capture recent advancements. Following screening, five studies were included. Most of the included studies underscored NEDD4L’s role in increasing atherosclerosis plaque formation, but other studies indicated that stimulating NEDD4L may positively counter atherosclerosis plaque formation. Therefore, future research endeavors must address several limitations, which have been tentatively highlighted throughout the manuscript, for more informative research based on preclinical studies and to successfully translate the findings into clinical trials.
Metabolic Response After a Single Maximal Exercise Session in Physically Inactive Young Adults (EASY Study): Relevancy of Adiponectin Isoforms
Authors: Cano-Montoya Johnattan , Bentes Amanda , Pavez Yanara , Rubilar Paola , Lavoz Carolina , Ehrenfeld Pamela , Sandoval Viviana , Martínez-Huenchullán Sergio
Published: February 2025

The metabolic response to a maximal exercise test in physically inactive adults remains poorly understood, particularly regarding the role of adiponectin, an adipokine with insulin-sensitizing and anti-inflammatory properties. Adiponectin circulates in three isoforms—low (LMW), medium (MMW), and high-molecular-weight (HMW)—with differing bioactivities. While exercise is known to influence adiponectin levels, evidence is conflicting, and few studies have explored isoform-specific changes. This study aimed to evaluate the effects of a single maximal exercise session on circulating adiponectin isoforms and their associations with metabolic and kidney function markers in physically inactive young adults. In this quasi-experimental study, twenty-one physically inactive participants (mean age 24.6 ± 2.1 years, 85.7% women) completed a progressive cycle ergometer test. Circulating levels of LMW and MMW adiponectin, metabolic outcomes (e.g., cholesterol, triglycerides, fibroblast growth factor 21 (FGF21)), and kidney function markers (e.g., creatinine, proteinuria) were assessed before and after exercise using biochemical assays and Western blotting. Comparisons between pre- and post-exercise values were made with the Wilcoxon test. Exercise increased lipid metabolism markers (total cholesterol, triglycerides, HDL) and kidney stress indicators (albuminuria, proteinuria) (p < 0.05). LMW and MMW adiponectin levels showed no significant overall changes, but LMW adiponectin positively correlated with changes in total cholesterol and FGF21, while MMW adiponectin negatively correlated with creatinine and proteinuria (p < 0.05). HMW adiponectin was undetectable by our methods. A single maximal exercise session revealed isoform-specific associations between adiponectin and metabolic or kidney stress markers, emphasizing the complex role of adiponectin in exercise-induced metabolic responses. Future research should explore mechanisms underlying these differential associations to optimize exercise interventions for metabolic health improvement.
An Enhanced Misinformation Detection Model Based on an Improved Beluga Whale Optimization Algorithm and Cross-Modal Feature Fusion
Authors: Mu Guangyu , Ju Xiaoqing , Yan Hongduo , Li Jiaxue , Gao He , Li Xiurong
Published: February 2025

The proliferation of multimodal misinformation on social media has become a critical concern. Although detection methods have advanced, feature representation and cross-modal semantic alignment challenges continue to hinder the effective use of multimodal data. Therefore, this paper proposes an IBWO-CASC detection model that integrates an improved Beluga Whale Optimization algorithm with cross-modal attention feature fusion. Firstly, the Beluga Whale Optimization algorithm is enhanced by combining adaptive search mechanisms with batch parallel strategies in the feature space. Secondly, a feature alignment method is designed based on supervised contrastive learning to establish semantic consistency. Then, the model incorporates a Cross-modal Attention Promotion mechanism and global–local interaction learning pattern. Finally, a multi-task learning framework is built based on classification and contrastive objectives. The empirical analysis shows that the proposed IBWO-CASC model achieves a detection accuracy of 97.41% on our self-constructed multimodal misinformation dataset. Compared with the average accuracy of the existing six baseline models, the accuracy of this model is improved by 4.09%. Additionally, it demonstrates enhanced robustness in handling complex multimodal scenarios.
STXBP1 Syndrome: Biotechnological Advances, Challenges, and Perspectives in Gene Therapy, Experimental Models, and Translational Research
Authors: Ruano-Rodríguez Silvestre , Navarro-Alonso Mar , Domínguez-Velasco Benito , Álvarez-Dolado Manuel , Esteban Francisco J.
Published: February 2025

STXBP1 syndrome is a severe early-onset epileptic encephalopathy characterized by developmental delay and intellectual disability. This review addresses key challenges in STXBP1 syndrome research, focusing on advanced therapeutic approaches and experimental models. We explore gene therapy strategies, including CRISPR-Cas9, adeno-associated viral (AAV) vectors, and RNA therapies such as antisense oligonucleotides (ASOs), aimed at correcting STXBP1 genetic dysfunctions. This review presents in vivo and in vitro models, highlighting their contributions to understanding disease mechanisms. Additionally, we provide a proposal for a detailed bioinformatic analysis of a Spanish cohort of 41 individuals with STXBP1-related disorders, offering insights into specific mutations and their biological implications. Clinical and translational perspectives are discussed, emphasizing the potential of personalized medicine approaches. Future research directions and key challenges are outlined, including the identification of STXBP1 interactors, unexplored molecular pathways, and the need for clinically useful biomarkers. This comprehensive review underscores the complexity of STXBP1-related infantile epileptic encephalopathy and opens new avenues for advancing the understanding and treatment of this heterogeneous disease.
Elastic Body Spring Method (EBSM) for the Stability Analysis of the Global Vipassana Pagoda in Mumbai, India
Authors: Gandolfi Alessandro , Pingaro Natalia , Milani Gabriele
Published: February 2025

This paper presents an innovative procedure for the stability assessment of masonry domes, aiming at simplifying the modelling and the computational stages of structural analysis. It exploits a macroscopic approach to discretise masonry, specifically using elastic bodies linked by nonlinear interfaces. The latter are made by axial and, when needed, tangential trusses—in turn characterised by an elastic perfectly plastic/brittle behaviour—which constitute the joints connecting homogenised elastic macroblocks. The objective is—by employing low-cost commercial Finite Element software—to predict the behaviour of a masonry curved structure up to failure, maintaining the computational complexity low and the approach accessible to a common user. The process enables not only the quantification of damage at failure but also the tracking of its evolution within the structure, by examining axial forces found in the trusses at each load step. The method allows the modelling of the response of any kind of masonry structure under imposed loads or displacements. Its efficacy is proven on a paradigmatic dome (Global Vipassana Pagoda, Mumbai, India) by comparing the results with limit analysis precedent studies. Finally, the major reliability of a 3D approach is demonstrated.
AI Model for Predicting Anti-PD1 Response in Melanoma Using Multi-Omics Biomarkers
Authors: Gschwind Axel , Ossowski Stephan
Published: February 2025

Background: Immune checkpoint inhibitors (ICIs) have demonstrated significantly improved clinical efficacy in a minority of patients with advanced melanoma, whereas non-responders potentially suffer from severe side effects and delays in other treatment options. Predicting the response to anti-PD1 treatment in melanoma remains a challenge because the current FDA-approved gold standard, the nonsynonymous tumor mutation burden (nsTMB), offers limited accuracy. Methods: In this study, we developed a multi-omics-based machine learning model that integrates genomic and transcriptomic biomarkers to predict the response to anti-PD1 treatment in patients with advanced melanoma. We employed least absolute shrinkage and selection operator (LASSO) regression with 49 biomarkers extracted from tumor–normal whole-exome and RNA sequencing as input features. The performance of the multi-omics AI model was thoroughly compared to that of nsTMB alone and to models that use only genomic or transcriptomic biomarkers. Results: We used publicly available DNA and RNA-seq datasets of melanoma patients for the training and validation of our model, forming a meta-cohort of 449 patients for which the outcome was recorded as a RECIST score. The model substantially improved the prediction of anti-PD1 outcomes compared to nsTMB alone, with an ROC AUC of 0.7 in the training set and an ROC AUC of 0.64 in the test set. Using SHAP values, we demonstrated the explainability of the model’s predictions on a per-sample basis. Conclusions: We demonstrated that models using only RNA-seq or multi-omics biomarkers outperformed nsTMB in predicting the response of melanoma patients to ICI. Furthermore, our machine learning approach improves clinical usability by providing explanations of its predictions on a per-patient basis. Our findings underscore the utility of multi-omics data for selecting patients for treatment with anti-PD1 drugs. However, to train clinical-grade AI models for routine applications, prospective studies collecting larger melanoma cohorts with consistent application of exome and RNA sequencing are required.
Threading the Needle: Navigating Novel Immunotherapeutics in Pancreatic Ductal Adenocarcinoma
Authors: Demir Tarik , Moloney Carolyn , Mahalingam Devalingam
Published: February 2025

Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy with a poor prognosis. Currently, chemotherapy is the only option for most patients with advanced-stage PDAC. Further, conventional immunotherapies and targeted therapies improve survival outcomes only in rare PDAC patient subgroups. To date, combinatory immunotherapeutic strategies to overcome the immune-hostile PDAC tumor microenvironment (TME) have resulted in limited efficacy in clinical studies. However, efforts are ongoing to develop new treatment strategies for patients with PDAC with the evolving knowledge of the TME, molecular characterization, and immune resistance mechanisms. Further, the growing arsenal of various immunotherapeutic agents, including novel classes of immune checkpoint inhibitors and oncolytic, chimeric antigen receptor T cell, and vaccine therapies, reinforces these efforts. This review will focus on the place of immunotherapy and future possible strategies in PDAC.
Enhanced Effect of SO2-Induced Pt/CeZrTiO2 on the Catalytic Oxidation of C2H6
Authors: Hou Changming , Hu Jiangliang , Hou Jiancai , Wu Dongxia , Shiliu Jiabao , Bao Weiren
Published: February 2025

The role of SO2 in the catalytic oxidation of light hydrocarbons remains controversial, especially in terms of its effects on catalyst performance and reaction pathways. In this study, the Pt/CeZrTiO2 catalyst was synthesized to explore the influence of SO2 during the catalytic combustion of ethane. The results revealed two distinct roles of SO2: (1) SO2 interacts with the catalyst, forming new active structures that facilitate C-H bond cleavage, alter the ethane oxidation pathway, and enhance low-temperature C2H6 conversion. (2) SO2 participates in the reaction process, replenishing active sites and maintaining a balance between two ethane oxidation pathways, leading to improved high-temperature C2H6 conversion and enhanced catalytic combustion efficiency. This study provides new insights into the role of SO2 in modulating catalyst properties and reaction pathways for efficient light hydrocarbon combustion.
Atrophic C2C12 Myotubes Activate Inflammatory Response of Macrophages In Vitro
Authors: Wu Cong , Tong Yishan , Huang Jiapeng , Wang Shuo , Kobori Haruki , Zhang Ziwei , Suzuki Katsuhiko
Published: February 2025

Background: Skeletal muscle wasting is commonly observed in aging, immobility, and chronic diseases. In pathological conditions, the impairment of skeletal muscle and immune system often occurs simultaneously. Recent studies have highlighted the initiative role of skeletal muscle in interactions with immune cells. However, the impact of skeletal muscle wasting on macrophage inflammatory responses remains poorly understood. Methods: To investigate the effect of atrophic myotubes on the inflammatory response of macrophages, we established two in vitro models to induce myotube atrophy: one induced by D-galactose and the other by starvation. Conditioned medium (CM) from normal and atrophic myotubes were collected and administered to bone marrow-derived macrophages (BMDMs) from mice. Subsequently, lipopolysaccharide (LPS) stimulation was applied, and the expression of inflammatory cytokines was measured via RT-qPCR. Results: Both D-galactose and starvation treatments reduced myotube diameter and upregulated muscle atrophy-related gene expression. CM from both atrophic myotubes models augmented the gene expression of pro-inflammatory factors in BMDMs following LPS stimulation, including Il6, Il1b, and Nfkb1. Notably, CM from starvation-induced atrophic myotubes also enhanced Il12b, Tnf, and Nos2 expression in BMDMs after stimulation, a response not observed in D-galactose-induced atrophic myotubes. Conclusions: These findings suggest that CM from atrophic myotubes enhanced the expression of LPS-induced pro-inflammatory mediators in macrophages.
Evaluation of Reminder App for Optimization of Bladder Filling Status During Hypo-Fractionated Irradiation for Prostate Cancer: Protocol of REFILL-PAC-HYPO Trial
Authors: Rades Dirk , Küter Jan-Dirk , von Staden Michael , Al-Salool Ahmed , Ziemann Christian , Janssen Stefan , Koeck Julia , Domschikowski Justus , Kristiansen Charlotte , Madsen Christine Vestergård , Duma Marciana N. , Bartscht Tobias , Cacicedo Jon , Cremers Florian
Published: February 2025

Background/Objectives: During radiotherapy for prostate cancer, the risk of radiation cystitis is increased if the volume of the bladder is small. According to previous studies, it is important that bladder volumes are ≥200 mL. Drinking protocols may be helpful in this context. Adherence to such protocols can be challenging, and may be improved by an app reminding patients before each session of radiotherapy to drink a certain amount of water. Our prospective phase 2 trial (REFILL-PAC-HYPO, NCT06784115) evaluates the impact of a reminder app on bladder filling in prostate cancer patients treated with hypo-fractionated radiotherapy. Methods: Twenty-seven patients need to be recruited for the REFILL-PAC-HYPO trial. Radiotherapy, preferably with volumetric-modulated arc therapy, uses hypo-fractionation with 20 × 3.0 Gy over four weeks. An app reminds patients to drink water (300 mL) 45 min before each session of hypo-fractionated irradiation. On the last day of their treatment, patients are asked about their satisfaction with the app. In the case of a dissatisfaction rate of >20%, the app requires modifications. If this rate is >40%, the app is considered not useful. Additionally, patients are asked about the impact of their participation in the trial and using the app on their general attitude towards health technology. Furthermore, the phase 2 cohort is compared to a historical control group treated with hypo-fractionated radiotherapy during recent years but not supported by an app. The REFILL-PAC-HYPO trial will contribute to identifying the potential value of a reminder app for bladder filling during hypo-fractionated radiotherapy for prostate cancer.
The Regenerative Potential of Rice Bran Oil Incorporated into Nanofibers: An In Vitro Study
Authors: Bispo-dos-Santos Karina , Trevisan Ingrid Mayara Cavalcante , Rapôso Catarina , Velho Paulo Eduardo Neves Ferreira , Ricci Leonardi Gislaine
Published: February 2025

Background/Objectives: Rice bran oil (RBO) is rich in phytochemical compounds and has many pharmaceutical applications. This work evaluated the regenerative potential of nanofibers incorporating RBO, focusing on their efficacy in tissue engineering and dermatological formulations. The main objective was to investigate the impact of RBO on SK-MEL-28 melanoma cell migration and wound closure through an in vitro healing assay. In addition, the biocompatibility and cell adhesion properties of the nanofibers were examined. Methods: The study employed cell culture techniques and field emission gun scanning electron microscopy (FEG-SEM) investigation. RBO was tested at different concentrations (0.5%, 1%, 5%, or 10%), both in isolation and incorporated into nanofibers. Cell migration was assessed through a wound-healing assay, while cell adhesion to the nanofibers was assessed using FEG-SEM. Statistical analyses were conducted to assess the significance of the findings. Results: Higher cell migration was achieved with 5% (p < 0.002) and 10% (p < 0.05) RBO nanofibers compared to the control and isolated RBO. The biocompatibility study found cell adhesion capability, highlighting the potential of these nanofibers for tissue engineering applications. Conclusions: Our results showed enhanced SK-MEL-28 cell migration and wound closure with RBO-incorporated nanofibers compared to isolated RBO. Biocompatibility was confirmed, suggesting potential for tissue engineering. Our findings indicate that the incorporation of RBO into nanofibers improves their oxidative stability, which is essential for preserving their phytochemical compounds and their beneficial effects on human skin cells in vitro.
Is Frailty Associated with Worse Outcomes After Major Liver Surgery? An Observational Case–Control Study
Authors: Lunca Sorinel , Morarasu Stefan , Ivanov Andreea Antonina , Clancy Cillian , O’Brien Luke , Zaharia Raluca , Musina Ana Maria , Roata Cristian Ene , Dimofte Gabriel Mihail
Published: February 2025

Background: The rate of morbidity after liver surgery is estimated at 30% and can be even higher when considering higher-risk subgroups of patients. Frailty is believed to better predict surgical outcomes by showcasing the patient’s ability to withstand major surgical stress and selecting frail ones. Methods: This is a single-centre, observational case–control study on patients diagnosed with liver malignancies who underwent liver resections between 2013 and 2024. The five-item modified Frailty Index (mFI-5) was used to split patients into frail and non-frail. The two groups were compared in terms of preoperative, operative and postoperative outcomes using a chi-squared and logistic regression model. Results: A total of 230 patients were included and split into two groups: non-frail, NF, n = 90, and frail patients, F, n = 140. Overall, F patients had a higher rate of morbidity (p = 0.04) but with similar mortality and length of stay. When considering only major liver resections, F patients had a higher probability of posthepatectomy liver failure (LR 6.793, p = 0.009), postoperative bleeding (LR 9.541, p = 0.002) and longer ICU stay (LR 8.666, p = 0.003), with similar rates of bile leak, surgical site infections, length of stay and mortality. Conclusions: Frailty seems to be a solid predictor of posthepatectomy liver failure in patients undergoing major liver resections and is associated with a longer ICU stay. However, mortality and surgical morbidity seem to be comparable between frail and non-frail patients.
Proposal for Diet Supplementation to Prevent Knee Osteoarthritis in Female Soccer Players
Authors: Caballero-García Alberto , Noriega-González David C. , Caballero-Castillo Aurora , Roche Enrique
Published: February 2025

Soccer is a widely practiced and highly mediatic sport discipline. For this reason, the incidence of injuries associated with the game is an active area of research. High-impact actions occur during the game, affecting the knee joint and resulting in osteoarthritis. In this line, knee osteoarthritis results from mechanical and biological stress due to lesions that are not adequately repaired, resulting in an inflammatory process. This occurs because the degradation of extracellular matrix predominates over synthesis by chondrocytes. Therefore, in soccer players, knee osteoarthritis results from joint traumatic actions, displaying a degenerative evolution. Osteoarthritis occurs in up to 32% of male soccer players, 3 times more than in the male general population. On the other hand, female soccer players are a main target population to suffer from knee osteoarthritis, with a higher significant incidence observed compared to men. In this context, certain diet supplements have an instrumental potential in the prevention and/or treatment of knee osteoarthritis. Therefore, the aim of this narrative review is to present possible research lines to implement treatments for knee osteoarthritis in female soccer players.
Impact of Incorporating Nanoparticles to Adhesive Resin on the Demineralization of Enamel: A Systematic Review
Authors: Almosa Naif
Published: February 2025

Background/Objective: Many novel solutions for a range of dental problems are emerging as a result of the quick development of nanotechnology and nanocomplex synthetic techniques. The effectiveness, quality, and negative consequences of these advancements are occasionally debatable, though. This systematic review sought to better summarize the existing additions of nanoparticles to dental adhesive systems in order to improve their performance and properties, evaluate their quality, and examine the results that have been published. Materials and methods: The present systematic review was carried out according to PRISMA guidelines. The search was carried out on PubMed central, Cochrane collaboration, Science direct and Scopus scientific engines. Selected MeSH keywords (nanoparticles, adhesive resin, enamel demineralization) were used for data extraction. A total of 13 full-text original articles were included in the final analysis, and these articles were based on adding nanoparticles to the adhesive resin to evaluate their effects on enamel demineralization. Results: The literature search resulted in a total of 13 original studies/articles up until November 2024. The text articles comprised in vitro studies with robust inclusion and exclusion criteria. The review included various types of adhesives and nanoparticles, with amorphous calcium phosphate (ACP) being the most common. Other nanoparticles included polydopamine–Ag, bioactive glass, and silver. Most studies assessed the effects of nanoparticles on adhesive shear bond strength (SBS), microbial growth, and microhardness. Only three studies investigated the effects of nanoparticles on microhardness using Vickers tests. Conclusions: The review found that adding nanoparticles to orthodontic dental adhesives enhances their antibacterial and anticariogenic properties without affecting the shear bond strength. This could prevent enamel demineralization during orthodontic therapy. Future research could benefit from these positive properties, necessitating an interdisciplinary approach.
Validation of Quantitative Light-Induced Fluorescence Digital Analysis for Assessing Early Dental Caries Depth: A Micro-Computed Tomography-Based In Vitro Study
Authors: Min Ji-Hyun
Published: February 2025

Background/Objectives: This study aimed to evaluate the analytical validity of micro-computed tomography (µCT) and compare it with quantitative light-induced fluorescence digital (QLFD) for assessing early dental caries (EDC) lesion depth (LD). This study was conducted in a destructive in vitro setting. Methods: EDC lesions were artificially induced in 28 bovine tooth specimens for 10, 20, 30, 40, 50, 60, and 70 days, respectively. The lesions were analyzed using µCT and QLFD, with grayscale intensity thresholds set at 90% and 95%. A Pearson correlation analysis was performed to evaluate the relationship between lesion depths measured using micro-computed tomography (LDµCT) and quantitative light-induced fluorescence digital (LDQLFD) across different demineralization periods. Additionally, a Bland–Altman analysis was conducted to assess agreement between the two methods and identify systematic differences and potential bias. A regression analysis was further conducted with LDQLFD as the independent variable and LDµCT as the dependent variable. Results: LDµCT was consistently lower than LDQLFD across all demineralization periods. The Pearson correlation analysis demonstrated a strong correlation between LDµCT and LDQLFD (r = 0.898–0.977, p < 0.001). The Bland–Altman analysis demonstrated a high level of agreement, with most data points falling within the 95% limit of agreement. Furthermore, the regression analysis suggested that QLFD may serve as a reliable complementary tool for lesion depth assessment. Conclusions: Although µCT and QLFD operate based on different principles, the findings of this study, along with the cost-effectiveness and ease of use of QLFD, suggest that QLFD may serve as a complementary tool to µCT in experimental research.
Seismic Data Acquisition Utilizing a Group of UAVs
Authors: Timoshenko Artem , Yashin Grigoriy , Serpiva Valerii , Hamadov Rustam , Fedotov Dmitry , Kartashova Mariia , Golikov Pavel
Published: February 2025

Seismic exploration in hard-to-reach hazardous environments like deserts is a very expensive and time-consuming process that involves a lot of human resources and equipment. These difficulties can be overcome with the implementation of robots, providing flexible mission design, safe operation, and high precision data acquisition. This work presents an autonomous robotic system to assist seismic crews in advanced data acquisition for near-surface characterization, shallow cavity detection, and acquisition grid infill. The developed system consists of a swarm control station and a swarm of unmanned aerial vehicles (UAVs) equipped with seismic sensors. The architecture of the swarm control station, its individual blocks, features of UAV exploitation for seismic data acquisition tasks, hardware and software tool limitations are considered. Algorithms for planning UAV swarm flight paths, their comparison and trajectory examples are presented. Experiments utilizing 9 and 16 UAVs to record 171 and 144 target points, respectively, in harsh desert conditions are described. The results demonstrate the feasibility of the proposed system for seismic data acquisition. The developed robotic system offers flexibility in seismic survey design and planning, enabling efficient coverage of vast areas and facilitating comprehensive data acquisition, which enhances the accuracy and resolution of subsurface seismic imaging.
Determination of the Band Gap Energy of SnO2 and ZnO Thin Films with Different Crystalline Qualities and Doping Levels
Authors: Guillén Cecilia
Published: February 2025

This research is on the structural, optical, and electrical properties of SnO2 and ZnO thin films, which are increasingly used in many electronic devices, including gas sensors, light-emitting diodes, and solar cells. For the various applications, it is essential to accurately determine the band gap energy, as it controls the optical and electrical behavior of the material. However, there is no single method for its determination; rather, different approximations depend on the crystalline quality and the doping level because these modify the energy band structure of the semiconductor. With the aim of analyzing the various approaches, SnO2 and ZnO films were prepared by sputtering on unheated glass substrates and subsequently annealed in N2 at various temperatures between 250 °C and 450 °C. These samples showed different crystallite sizes, absorption coefficients, and free carrier concentrations depending on the material and the annealing temperature. Analysis of the results shows that the expression developed for amorphous materials underestimates the band gap value, and the so-called unified method tends to overestimate it, while the equations for perfect or heavily doped crystals give band gap energies more consistent with the doping level, regardless of the crystalline quality of the films.
Robust Regression and Redundant Measurement Noise Estimation Adaptive Filtering for Localization in Urban Environments
Authors: Zha Li , Zhang Hai , Wang Aiping , Tao Cancan
Published: February 2025

This paper focuses on a solution of target self-positioning when a Global Navigation Satellite System (GNSS) is denied. It is composed of Inertial Navigation Systems (INS), Signals of Opportunities (SOPs), and a navigation prototype. One of the options for navigation via SOP (NAVSOP) is to utilize cellular signals, such as Long Time Evolution (LTE). When the prior information is insufficient, the location of the base station (BS) is obtained by collecting the demodulation of the downlink signal, and the synchronization signal is used for static time offset correction. In view of the large positioning error of the trilateral positioning method based on Received Signal Strength (RSS), a multi-station positioning optimization method is proposed by introducing the robust regression. Monte Carlo simulation experiments indicate that the method has improved the positioning failure and insufficient accuracy. Aiming at the influence of the state estimation errors on filtering results, the Second Order Mutual Difference (SOMD) method with the noise covariance R, which is independent of the existing Extended Kalman Filter (EKF) framework and combined with Redundant Measurement Noise Covariance Estimation (RMNCE), is applied to the model. The simulation results show that the average error of the robust model is 10.28 m, which is better than the EKF method. Finally, a vehicle test in constant speed has been carried out. The results show that the proposed model can realize self-positioning with limited BS location information, and the positioning accuracy can reach 11.68 m over a 283 m trajectory.