bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Sub-Chronic Exposure to Polystyrene Nanoplastics on Lipid and Antioxidant Metabolism in Sparus aurata
Authors: Okon Ekemini , Brandts Irene , Djafar Hayam , Tvarijonaviciute Asta , Balasch Joan Carles , Teles Mariana
Published: February 2025

Nanoplastics (NPs) can cross cellular membranes and affect cellular performance. This study aims to determine the effects of polystyrene NPs (PS-NPs, 44 nm) on gilthead seabream (Sparus aurata) exposed for 14 days to 100 μg/L PS-NPs. The results show that biometric indicators (weight, length, Fulton’s condition factor, and hepatosomatic index) were not affected after the experimental exposures. No significant effects were observed on white blood cell count, red blood cell count, mean corpuscular hemoglobin, or platelets compared to the control group. However, there was a significant decrease in hemoglobin concentration, hematocrit values, and mean corpuscular cell volume in fish exposed to PS-NPs. There were no significant effects on plasmatic cholesterol, triglyceride, alkaline phosphatase, or aspartate aminotransferase levels. The histological anatomy of both the gills and the intestine revealed no obvious signs of cellular damage, excessive mucous, or inflammation in the PS-NP group. The expression of transcripts related to lipid metabolism (pparα, pparβ), growth and development (igf1), detoxification (bche), and oxidative stress (sod, gpx1) were significantly downregulated in animals exposed to PS-NPs, indicating a slight impairment in lipid homeostasis and antioxidant response.
Interprofessional Therapeutic Drug Monitoring of Piperacillin/Tazobactam Enhances Care for Patients with Acute-on-Chronic Liver Failure in the ICU: A Retrospective Observational Pilot Study
Authors: Schmid Stephan , Zimmermann Katharina , Koch Chiara , Mester Patricia , Athanasoulas Georgios , Buttenschoen Jonas , Fleischmann Daniel , Schlosser-Hupf Sophie , Pavel Vlad , Schilling Tobias , Müller Martina , Kratzer Alexander
Published: February 2025

Background: Acute-on-chronic liver failure (ACLF) is a severe, rapidly progressing syndrome in patients with liver cirrhosis, often triggered by bacterial infections. Piperacillin/Tazobactam is a key antibiotic in this setting, and therapeutic drug monitoring (TDM) helps optimize its dosing. This study evaluates the impact of an interprofessional TDM strategy for Piperacillin/Tazobactam in ACLF patients in the ICU. Methods: This retrospective ICU study evaluated an interprofessional TDM approach for optimizing Piperacillin/Tazobactam dosing in critically ill ACLF patients. The team, consisting of physicians, clinical pharmacists, and staff nurses, engaged in shared decision making, collaboratively interpreting TDM results and adjusting the dosing accordingly. This study included 26 patients with ACLF who underwent initial TDM and 7 who received follow-up TDM. Piperacillin/Tazobactam dosing was modified based on TDM recommendations, with serum concentrations measured weekly. Adherence to and the implementation of interprofessional dosing recommendations were systematically analyzed to assess the impact of this approach. Results: The initial TDM showed that 30.8% of patients had Piperacillin/Tazobactam levels within the target range, while 53.8% were above and 15.4% below. The interprofessional team recommended dose reductions in seven patients, increases in three, and no change in eleven, with five requiring antibiotic modifications. At the first follow-up TDM, 20.0% reached target levels, while 80.0% remained above, with no subtherapeutic cases. The team recommended one further dose reduction and maintained dosing in four patients. All recommendations were fully implemented, demonstrating strong adherence to the collaborative protocol. Conclusions: The interprofessional TDM strategy optimized Piperacillin/Tazobactam dosing in ACLF patients with full adherence to the recommendations. This collaborative approach improves outcomes and supports global efforts to curb antibiotic resistance.
A Novel Methodology for Planning Urban Road Safety Interventions
Authors: Toraldo Emanuele , Novati Nicolò , Rossi Damiano , Ketabdari Misagh
Published: February 2025

Improving road safety is a major challenge for urban administrations due to the high frequency of accidents and their associated social costs. This study presents a methodology that combines historical accident data analysis with a proactive risk assessment approach to enhance decision-making in road safety planning. Using the International Road Assessment Programme (iRAP) and Geographic Information Systems (GIS), the proposed framework identifies high-risk locations and estimates the benefits of planned safety interventions. A key innovation of this methodology is the integration of cost–benefit analysis to prioritize interventions, ensuring optimal resource allocation. The approach was tested in a medium-sized Italian city where it helped identify critical areas and assess the potential impact of various safety measures, such as intersection redesign and traffic-calming strategies. The results demonstrated a significant potential to reduce accidents and associated social costs, offering a scalable model for urban road safety planning. By integrating data-driven insights with proactive evaluation, this methodology supports urban administrations in implementing effective, targeted interventions that contribute to Vision Zero goals.
MCDCNet: Mask Classification Combined with Adaptive Dilated Convolution for Image Semantic Segmentation
Authors: Wei Geng , Wang Junbo , Shi Bingxian , Zhu Xiaolin , Cao Bo , Liu Tong
Published: February 2025

Effectively classifying each pixel in an image is an important research topic in semantic segmentation. The Existing methods typically require the network to directly generate a feature map of the same size as the original image and classify each pixel, which makes it difficult for the network to fully leverage the representations from the backbone. To handle this challenge, this paper proposes a method named mask classification combined with an adaptive dilated convolution network (MCDCNet). Firstly, a Vision Transformer (ViT)-based module is employed to capture contextual features as the backbone. Secondly, the Spatial Extraction Module (SEM) is proposed to extract multi-scale spatial information through adaptive dilated convolution while preserving the original feature size. This spatial information is then integrated into the corresponding contextual features to enhance the representation. Finally, a novel inference process is proposed that incorporates the instance activation map (IAM)-based decoder for semantic segmentation, thereby enhancing the network’s capability to capture and comprehend semantic features. The experimental results demonstrate that our network significantly outperforms other per-pixel classification networks across several semantic segmentation datasets. In particular, on Cityscapes, MCDCNet achieves 80.3 mIoU with 11.8 M Params, demonstrating that the network is able to deliver a strong segmentation performance while maintaining a relatively low parameter count.
Exploring New Development Codes in an Era of “Land-Driven Development” Model Depletion via a Systematic Analysis of the Operational Mechanisms of Urban Land Property Rights
Authors: Tian Yingying , Jiang Guanghui , Wu Siduo
Published: February 2025

To promote the role of land property rights operation (LPRO) in urbanization and socioeconomic development, an optimization mechanism framework for LPRO is constructed to analyze how different variables related to the transfer, utilization, and supervision links within the LPRO system impact its macro effects. LPRO’s macro effects are promoted by the land price, advanced utilization level, land marketization level, public management land scale, residential land scale, and regulation of the upper and lower limits on the floor area ratio (FAR), with contributions of 38.18%, 22.62%, 4.78%, 3.11%, 2.43%, and 2.11%, respectively, whereas the low-quality land scale, commercial land proportion, change rate of the transfer scale, distance to the city center, and regulation of the upper limit on the FAR contribute negatively, by 6.63%, 3.14%, 2.82%, 2.65%, and 2.16%, respectively. Moreover, the role of the LPRO structure changes over time. The land marketization level has a single-threshold and increasingly positive contribution, the land price exhibits “U”-shaped double-threshold effects transforming from negative roles to positive roles, and the advanced utilization level shows double-threshold decreasing promotion effects. LPRO’s macro effects in central and western China operate similarly but differ from those in eastern China, highlighting the implementation of regionally differentiated guidance mechanisms. The results highlight the new code of “value-driven development” when the “land-driven development” model is weakening.
Analyzing Momentum Shifts in Tennis: A Machine-Learning Approach to Predicting Match Outcomes
Authors: Xia Yuean , Li Changfeng , Zhang Tanran
Published: February 2025

This study examines the impact of momentum dynamics on tennis match outcomes, addressing the limitations of traditional performance prediction methods. Using data from the 2023 Wimbledon men’s singles matches, a data-driven framework was developed to analyze factors influencing player performance. Factor analysis identified key independent variables, while a decision-tree model optimized through random-forest and genetic algorithm techniques was employed to predict match outcomes. Momentum was quantified using the Kendall consistency test, which revealed a significant correlation between momentum shifts and match results. The analysis highlighted that variations in momentum difference between players are crucial predictors, achieving a success rate of 78%. Visualizations further demonstrated that momentum fluctuations closely align with critical match events, offering a detailed understanding of performance dynamics. At the same time, the model has also been applied to the prediction of other tennis games and even table tennis games. It can adaptively adjust the K value and has a good fitting effect.Compared to conventional statistical methods, which often overlook the role of momentum, this model provides deeper insights into the interplay between momentum and match outcomes. While the framework shows strong applicability to tennis, its extension to other sports, such as table tennis, requires further exploration. These findings underscore the importance of momentum in competitive sports, offering new perspectives for match analysis, player training, and strategic planning and paving the way for future research into momentum dynamics across various sports disciplines.
Detection of Welding Defects Tracked by YOLOv4 Algorithm
Authors: Chen Yunxia , Wu Yan
Published: February 2025

The recall rate of the original YOLOv4 model for detecting internal defects in aluminum alloy welds is relatively low. To address this issue, this paper introduces an enhanced model, YOLOv4-cs1. The improvements include optimizing the stacking method of residual blocks, modifying the activation functions for different convolutional layers, and eliminating the downsampling layer in the PANet (Pyramid Attention Network) to preserve edge information. Building on these enhancements, the YOLOv4-cs2 model further incorporates an improved Spatial Pyramid Pooling (SPP) module after the third and fourth residual blocks. The experimental results demonstrate that the recall rates for pore and slag inclusion detection using the YOLOv4-cs1 and YOLOv4-cs2 models increased by 28.9% and 16.6%, and 45% and 25.2%, respectively, compared to the original YOLOv4 model. Additionally, the mAP values for the two models are 85.79% and 87.5%, representing increases of 0.98% and 2.69%, respectively, over the original YOLOv4 model.
An Evaluation of the Quantitative Concentration of Microplastic in Dendrobaena veneta and Lumbricus terrestris Tissues from Laboratory and Environmental Cultures
Authors: Klimasz Marek , Kacprzak Andrzej , Grobelak Anna
Published: February 2025

Earthworms play a key role in maintaining a healthy soil ecosystem by providing organic matter cycling and influencing the soil’s structure and physicochemical properties. In addition, they have also become the subject of research in the context of soil contamination by plastic particles or microplastics. In this article, two species of earthworms, Dendrobaena veneta and Lumbricus terrestris, were subjected to the influence of a mixed fraction of microplastics at different concentrations and studied to determine the possible correlation in tissue accumulation and to illustrate the possible structural changes in plastics under the influence of earthworm digestive enzymes. Using FTIR spectrometry and plastic fluorescence, the polymer content of the earthworm tissues was determined, and significant differences in the accumulation of plastic particles in the cultured earthworm tissues at the micro- and macroscales were documented.
Application of Short-Term Measurements to Estimate the Annual Mean Indoor Air Radon-222 Activity Concentration
Authors: Maringer Franz Josef , Blum Marius
Published: February 2025

A method was developed to estimate the average annual indoor radon activity concentration from three-week short-term measurements using active radon-222 measuring devices, taking into account the relevant influencing parameters (season, temperature difference, temporal air pressure gradient, etc.) during the short-term measurements. A total of 24 long-term measurements (6 months) and 50 short-term measurements (3 weeks) were carried out in 24 indoor spaces in private houses in four Austrian federal states between October 2022 and July 2023. At the same time as the short-term measurements, ambient parameters (outside and inside temperature, air pressure inside, outside, air humidity inside, outside, wind speed, wind direction, amount of precipitation) were also recorded to investigate their influence on the measured radon-222 activity concentrations. Building and usage data of the indoor spaces examined were also collected. Based on the evaluation of the radon-222 measurements carried out, a first guideline was developed for estimating the annual mean value of the radon-222 activity concentration from short-term measurements lasting around three weeks. The result shows that by applying the developed method, the approximation to the long-term average value can be significantly improved, at least by a factor of 2. This criterion is only valid for the 24 indoor spaces examined in this study. Generalisation requires a test and validation study of the method presented. It is planned to test and validate the developed method in other indoor spaces by means of further measurements and in-depth physical-statistical considerations, and to improve the functional relationships and the approximation to the long-term average value.
Certain Fixed-Point Results for (e,ψ,Φ)-Enriched Weak Contractions via Theoretic Order with Applications
Authors: Ishtiaq Umar , Din Muhammad , Rohen Yumnam , Alnowibet Khalid A. , Popa Ioan-Lucian
Published: February 2025

This paper aims to establish several fixed-point theorems within the framework of Banach spaces endowed with a binary relation. By utilizing enriched contraction principles involving two classes of altering-distance functions, the study encompasses various types of contractive mappings, including theoretic-order contractions, Picard–Banach contractions, weak contractions, and non-expansive contractions. A suitable Krasnoselskij iterative scheme is employed to derive the results. Many well-known fixed-point theorems (FPTs) can be obtained as special cases of these findings by assigning specific control functions in the main definitions or selecting an appropriate binary relation. To validate the theoretical results, numerous illustrative examples are provided. Furthermore, the paper demonstrates the applicability of the findings through applications to ordinary differential equations.
Methodology Development for Investigating Pathophysiological [18F]-FDG Muscle Uptake in Patients with Rheumatic Musculoskeletal Diseases
Authors: Sobejana Maia , Al Beiramani Mustafa , Zwezerijnen Gerben J. C. , van der Kooi Anneke , Raaphorst Joost , Meskers Carel G. M. , van der Esch Martin , van der Laken Conny J. , Steinz Maarten M.
Published: February 2025

Objectives: This retrospective study explored the qualitative and quantitative assessment of F18-fluordeoxyglucose ([18F]-FDG) positron emission tomography and computed tomography (PET/CT) scans to assess pathophysiological muscle glucose uptake in patients with a rheumatic musculoskeletal disease (RMD). [18F]-FDG PET/CT detects metabolic activity via glucose uptake in tissues. This study aimed to determine the feasibility of quantitative assessment of [18F]-FDG uptake in muscles across three different RMDs compared to controls. Methods: In this study we analysed whole-body [18F]-FDG PET/CT scans from patients with rheumatoid arthritis (RA; n = 11), osteoarthritis (OA; n = 10), and idiopathic inflammatory myositis (IIM; n = 10), and non-RMD controls (n = 11), focusing on muscle-tracer uptake in specific muscle groups. Qualitative assessment visually identified regions with high [18F]-FDG uptake, followed by quantitative assessment using two methods: fixed volume-of-interest (VOI) and hotspot VOI. In the fixed VOI method, a VOI was placed in the respective muscle at a fixed position (50% height from proximal to distal end) on PET/CT images. In the hotspot VOI method, the VOI was placed at the site of the highest [18F]-FDG uptake observed during qualitative assessment. Standardised uptake values (SUVs) were determined for different muscle groups between RMDs and controls. Results: Qualitative assessment revealed a heterogenous uptake pattern of [18F]-FDG that was found in 93% of quadriceps and hamstring muscles, while other muscles displayed either heterogenous or homogenous patterns. A Bland–Altman analysis showed that the hotspot VOI method had a higher sensitivity in detecting differential [18F]-FDG uptake in muscles. Across all muscle groups, patients with IIM had the highest [18F]-FDG uptake, followed by patients with OA and RA, respectively. Conclusions: [18F]-FDG PET/CT enables qualitative and quantitative differentiation of muscle glucose uptake in patients with RA, OA, and IIM, at both individual muscle and patient group levels. The hotspot method and SUVpeak are recommended for quantitative assessment. High [18F]-FDG uptake in multiple muscle groups suggests pathophysiological glucose metabolism in RMD-affected muscles.
Highlighting the Advanced Capabilities and the Computational Efficiency of DeepLabV3+ in Medical Image Segmentation: An Ablation Study
Authors: Prokopiou Ioannis , Spyridonos Panagiota
Published: February 2025

Background: In clinical practice, identifying the location and extent of tumors and lesions is crucial for disease diagnosis and treatment. Artificial intelligence, particularly deep neural networks, offers precise and automated segmentation, yet limited data and high computational demands often hinder its application. Transfer learning helps mitigate these challenges by significantly reducing computational costs, although applying these models can still be resource intensive. This study aims to present flexible and computationally efficient architecture that leverages transfer learning and delivers highly accurate results across various medical imaging problems. Methods: We evaluated three datasets with varying similarities to ImageNet: ISIC 2018 (skin lesions), CBIS-DDSM (breast masses), and the Shenzhen and Montgomery CXR Set (lung segmentation). An ablation study on ISIC 2018 tested various pre-trained backbones, architectures, and loss functions. Results: The optimal configuration—DeepLabV3+ with a pre-trained ResNet50 backbone and Log-Cosh Dice loss—was validated on the remaining datasets, achieving state-of-the-art results. Conclusion: Computationally simpler architectures can deliver robust performance without extensive resources, establishing DeepLabV3+ with the ResNet50 as a baseline for future studies. In the medical domain, enhancing data quality is more critical for improving segmentation accuracy than increasing model complexity.
Enhancing Motor Function and Quality of Life Combining Advanced Robotics and Biomechatronics in an Adult with Dystonic Spastic Tetraparesis: A Case Report
Authors: Leogrande Elisabetta , Piccoli Sara , Dell’Olio Francesco , Smania Nicola , Mazzoleni Stefano , Gandolfi Marialuisa
Published: February 2025

This case report explores the innovative integration of robotic and biomechatronic technologies, including the Motore and Ultra+ devices and neuro-suits, in a 10-session rehabilitation program for a young adult with dystonic spastic tetraparesis. Notable improvements were observed in upper limb motor function, coordination, and quality of life as measured by an increase of 18 pints on the Fugl-Meyer scale and a 25% improvement in the Bartle Index. Range of motion measurements showed consistent improvements, with task execution times improving by 10 s. These findings suggest the potential of combining wearable, robotic, and biomechatronic systems to enhance neurorehabilitation. Further refinement of these technologies might support clinicians in maximizing their integration in therapeutics, despite technical issues like synchronization issues that must be overcome.
Biophysical Modeling of Cardiac Cells: From Ion Channels to Tissue
Authors: Alonso Sergio , Alvarez-Lacalle Enrique , Bragard Jean , Echebarria Blas
Published: February 2025

Cardiovascular diseases have become the leading cause of death in developed countries. Among these, some are related to disruptions in the electrical synchronization of cardiac tissue leading to arrhythmias such as atrial flutter, ventricular tachycardia, or ventricular fibrillation. Their origin is diverse and involves several spatial and temporal scales, ranging from nanoscale ion channel dysfunctions to tissue-level fibrosis and ischemia. Mathematical models play a crucial role in elucidating the mechanisms underlying cardiac arrhythmias by simulating the electrical and physiological properties of cardiac tissue across different spatial scales. These models investigate the effects of genetic mutations, pathological conditions, and anti-arrhythmic interventions on heart dynamics. Despite their varying levels of complexity, they have proven to be important in understanding the triggers of arrhythmia, optimizing defibrillation protocols, and exploring the nonlinear dynamics of cardiac electrophysiology. In this work, we present diverse modeling approaches to the electrophysiology of cardiac cells and share examples from our own research where these approaches have significantly contributed to understanding cardiac arrhythmias. Although computational modeling of the electrical properties of cardiac tissue faces challenges in integrating data across multiple spatial and temporal scales, it remains an indispensable tool for advancing knowledge in cardiac biophysics and improving therapeutic strategies.
Equivalent Circuit Modeling and Analysis for Microfluidic Electrical Impedance Monitoring of Single-Cell Growth
Authors: Wang Yingying , Wu Haoran , Geng Yulu , Zhang Zhao , Fu Jiaming , Ouyang Jia , Zhu Zhen
Published: February 2025

Microfluidics has significantly advanced the field of single-cell analysis, particularly in studies related to cell growth, division, and heterogeneity. Electrical impedance spectroscopy (EIS), a label-free and non-invasive biosensing technique, has been integrated into microfluidic devices for high-throughput and long-term monitoring of single budding yeast cells. Accurate interpretation of EIS measurements of cell growth dynamics necessitates the establishment of theoretical equivalent circuit models for the single-cell sensing system. Here, we report on the development of equivalent circuit models of an in situ EIS sensing system to elucidate cell growth. Firstly, finite element modeling and simulation of an EIS measurement of cell growth in the EIS sensing unit were performed, guiding the fittings of electrical components for an established equivalent circuit model (ECM). From the ECM, we extracted an equivalent volume fraction applicable to various cell and sensing unit geometries to describe the geometry-dependent sensing characteristics corresponding to the electrical response in the model. Then, EIS measurements of an immobilized cell in a microfluidic device were conducted via peripheral circuits. A lumped parameter model for the entire EIS measurement system was established, with electrical components determined by fitting to experimental data. The rationality of the proposed theoretical model was validated through the long-term impedance variation induced by cell growth in experiments, demonstrating its feasibility in linking EIS data with the bio-physics underlying the experimental phenomenon.
Estimating the Minimum Sample Size for Neural Network Model Fitting—A Monte Carlo Simulation Study
Authors: Cheng Yongtian , Petrides Konstantinos Vassilis , Li Johnson
Published: February 2025

In the era of machine learning, many psychological studies use machine learning methods. Specifically, neural networks, a set of machine learning methods that exhibit exceptional performance in various tasks, have been used on psychometric datasets for supervised model fitting. From the computer scientist’s perspective, psychometric independent variables are typically ordinal and low-dimensional—characteristics that can significantly impact model performance. To our knowledge, there is no guidance about the sample planning suggestion for this task. Therefore, we conducted a simulation study to test the performance of an NN with different sample sizes and the simulation of both linear and nonlinear relationships. We proposed the minimum sample size for the neural network model fitting with two criteria: the performance of 95% of the models is close to the theoretical maximum, and 80% of the models can outperform the linear model. The findings of this simulation study show that the performance of neural networks can be unstable with ordinal variables as independent variables, and we suggested that neural networks should not be used on ordinal independent variables with at least common nonlinear relationships in psychology. Further suggestions and research directions are also provided.
Cognitive Mechanisms Underlying the Influence of Facial Information Processing on Estimation Performance
Authors: Huang Xinqi , Zhou Xiaofan , Xu Mingyi , Liu Zhihao , Ma Yilin , Zhu Chuanlin , Kou Dongquan
Published: February 2025

This study aimed to investigate the roles of facial information processing and math anxiety in estimation performance. Across three experiments, participants completed a two-digit multiplication estimation task under the conditions of emotion judgment (Experiment 1), identity judgment (Experiment 2), and combined emotion and identity judgment (Experiment 3). In the estimation task, participants used either the down-up or up-down problem to select approximate answers. In Experiment 1, we found that negative emotions impair estimation performance, while positive and consistent emotions have a facilitating effect on estimation efficiency. In Experiment 2, we found that emotion and identity consistency interact with each other, and negative emotions actually promote estimation efficiency when identity is consistent. In Experiment 3, we found that emotion, identity consistency, and emotional consistency have complex interactions on estimation performance. Moreover, in most face-processing conditions, participants’ estimation performance is not affected by their level of math anxiety. However, in a small number of cases, mean proportions under happy and fearful conditions are negatively correlated with math anxiety.
Flexural Performance of RC Beams Strengthened with High-Strength Steel Wire Mesh and UHPC
Authors: Zhu Chao , Du Chunlin , Qi Yanxin , Jiang Zhimei , Zhang Zhongya , Yang Jun , Li Yinbin , Cheng Jun
Published: February 2025

This study proposes a strengthening technique comprising a combination of high-strength steel wire mesh and ultra-high performance concrete (UHPC) to address the challenge of the insufficient bearing capacity of existing structures. The tensile performance of high-strength wire mesh and the crack resistance of UHPC were comprehensively considered in this technique. To evaluate the influence of the steel fiber volume ratio and the high-strength steel mesh strengthening ratio on the axial tensile performance, uniaxial tensile tests were carried out on two sets of dumbbell-shaped specimens. A constitutive model of the wire mesh UHPC that matched the experimental results was established. The finite element analysis of RC beams strengthened with high-strength wire mesh and UHPC was carried out, based on this constitutive model. The experimental results indicated the following: (a) The crack resistance and ultimate strength of the specimen reinforced with the high-strength steel wire mesh were effectively enhanced, with enhancement ratios of 97.8% and 124.8%, respectively. (b) The embedded interactions between the steel wire mesh and UHPC were simulated by considering the material nonlinearity. The finite element modeling of RC beams strengthened with wire mesh UHPC was achieved. (c) Positive correlations were observed between the thickness of the UHPC layer, the steel fiber volume ratio, and the high-strength wire mesh layer with the flexural capacity of the strengthened beams. The cracking and ultimate moments were maximally enhanced by 96.2% and 99.4%, respectively.
Dynamic Amplification Analysis of the Main Girder of Cable-Stayed Bridges After Cable Rupture Using the Modal Superposition Method
Authors: Liu Haikuan , Li Jie , Zhang Junfeng , Luo Jun
Published: February 2025

This study investigates the dynamic amplification effect of the main girder of cable-stayed bridges after cable rupture. The expression for the dynamic amplification effect is derived using the modal superposition method, and the influence of the duration of cable rupture on the dynamic amplification effect is investigated. The results indicate that, for a single-degree-of-freedom (SDOF) system without damping, the displacement dynamic amplification factor (DAF) can reach a maximum of 2.0. For the main girder of cable-stayed bridges, the dynamic amplification factor can exceed 2.0 and is related to the weight of the projection components of the response on the mode shapes. Using the modal superposition method of calculation, the higher-order modes have the greatest influence on shear force, followed by the bending moment, while they have the least influence on displacement. The theoretical derivation is validated using a simplified model, and it is shown that the commonly used equivalent static load calculation method with a factor of 2.0 for the static cable force poses potential safety risks. Furthermore, this study shows that the shorter the duration of cable rupture, the more pronounced the dynamic amplification effect. It is recommended that the duration of the cable rupture should not exceed 0.01 times the fundamental period of the structure when the maximum impact effect is calculated to ensure the rationality of the calculation results.
How 3D Printers for Houses Can Reduce CO2 Emissions
Authors: Palazzo Andrea
Published: February 2025

Three-dimensional printing technology for building construction is rapidly emerging as a transformative force, offering innovative and sustainable solutions to reduce the environmental impact of the construction sector. Unlike traditional methods, this technology significantly lowers CO2 emissions by enabling the use of sustainable materials such as geopolymers and recycled aggregates. Moreover, it minimizes waste, labor requirements, and the need for extensive on-site equipment, thereby reducing the overall carbon footprint of building projects. Studies indicate that adopting 3D printing in construction can cut CO2 emissions by up to 70%, depending on the materials used. By enhancing precision and integrating automation, 3D printing optimizes material consumption, reduces transportation needs, and minimizes energy-intensive activities. This research highlights the pivotal role of 3D printing in reshaping the construction process, quantifying its potential to drive sustainability and innovation, both directly and indirectly, at multiple stages of the building lifecycle.
Surgical Techniques for Non-Small-Cell Lung Cancer After Neoadjuvant Chemo-Immunotherapy: State of Art and Review of the Literature
Authors: Trabalza Marinucci Beatrice , Mancini Massimiliano , Siciliani Alessandra , Messa Fabiana , Piccioni Giorgia , D’Andrilli Antonio , Maurizi Giulio , Ciccone Anna Maria , Menna Cecilia , Vanni Camilla , Tiracorrendo Matteo , Rendina Erino Angelo , Ibrahim Mohsen
Published: February 2025

Non-small-cell lung cancer (NSCLC) accounts for 80–85% of all lung cancers. Approximately 20% of patients with NSCLC are diagnosed with stage IIIA–IIIB disease, for which the optimal treatment remains unclear. Meta-analyses reveal that neoadjuvant/perioperative ICI–chemotherapy significantly improves pathological complete response (pCR), overall survival (OS), major pathological response (MPR), and R0 rate compared to standard neoadjuvant chemotherapy. Resectability is achieved when R0 resection can be performed after surgery. Radiographic downstaging often does not correspond to surgical downstaging. In fact, intra-operative fibrosis due to chemo-immunotherapy (synonymous with ICI–chemotherapy) can create adhesions and consequent difficult planes for dissection. Thus, pneumonectomy cannot be avoided. Even the suspicion of N2 after neoadjuvant treatment is considered a limitation of upfront surgery because of the risk of pneumonectomy. The aim of this review is to explore the literature on the technical strategies for surgical excision of NSCLC after chemo-immunotherapy, addressing even the most challenging scenarios.
The Application of Surface Luminance Distribution Measurements to the Evaluation of Neoplastic Lesions of the Prostate Gland
Authors: Tereszkiewicz Krzysztof , Aebisher David , Wachta Henryk , Kulig Łukasz , Osuchowski Michał , Kaznowska Ewa , Domka Wojciech , Polar Mateusz , Myśliwiec Angelika , Dynarowicz Klaudia , Bartusik-Aebisher Dorota
Published: February 2025

Prostate cancer is one of the most commonly diagnosed malignancies in men [...]
Identification of the Interacting Domains Between Tissue Factor and β1-Integrin and the Signalling Properties of the Two Fibronectin-like Domains of Tissue Factor
Authors: Featherby Sophie J. , Faulkner Eamon C. , Maraveyas Anthony , Ettelaie Camille
Published: February 2025

Background: Interactions between tissue factor (TF) and β1-integrin induce cell signals, but the molecular mechanisms are not completely understood. The extracellular domain of TF and EGF4-βTD domains of β1-integrin were hypothesised to be the most likely domains involved in the interaction. Additionally, the interaction may induce a conformational change in β1-integrin, which results in changes in signalling. Methods: Peptide constructs corresponding to the upper (residues 1–110; UED), lower (residues 106–219; LED) or combined extracellular domain (residues 1–219; TED) of TF were produced, as well as peptides corresponding to EGF4-βTD or EGF4 domains of β1-integrin. These constructs were expressed in TF-rich MDA-MB-231 cells and TF-deficient primary endothelial cells. The association of the peptides with endogenous-TF or β1-integrin was assessed by a proximity ligation assay and co-immunoprecipitation. Additionally, the influence of the constructs on β1-integrin conformation and the outcome on ERK1/2 activation, cyclin D expression and cell proliferation was analysed. Results: In MDA-MB-231 cells, all TF-constructs were associated with β1-integrin whilst LED was co-immunopurified with β1-integrin. EGF4-βTD was associated with and co-immunopurified with endogenous TF. Additionally, the expression of UED or EGF4-βTD reduced ERK phosphorylation and cyclin D expression and suppressed proliferation. In endothelial cells, the expression of UED, and to a lesser extent, LED, reduced the proportion of β1-integrin in the active conformation and induced ERK1/2 phosphorylation but did not induce cyclin D expression or proliferation. Conclusions: Collectively, these data indicate the extracellular domains of TF function together, with the lower domain forming a robust interaction with the βTD of β1-integrin and the upper domain inducing cell signalling by regulating β1-integrin conformation.
NON-SMALL-CELL LUNG CANCER: Real-World Population-Based Cohorts’ Study
Authors: Buja Alessandra , Rugge Massimo , Bortolami Alberto , Zorzi Manuel , Rea Federico , Zanovello Anna , Scroccaro Giovanna , Conte Pierfranco , Pasello Giulia , Guarneri Valentina ,   on behalf of Rete Oncologica Veneta,   Periplo Foundation
Published: February 2025

Introduction: This retrospective follow-up study evaluates patient outcomes and treatment costs in two cohorts of incident NSCLC patients recorded in the population-based cancer registry of the Veneto Region in 2017 and 2019. Methods: This study examines two cohorts of incident NSCLC patients recorded by the Regional Veneto cancer registry in 2017 (493 patients) and 2019 (557 patients). Cancer patients were followed for three years after diagnosis to assess the disease’s outcomes and analyze the overall treatment-related costs. Overall survival and cancer-specific mortality were evaluated using Cox regression models. The log-transformed overall treatment costs for the 3 years following diagnosis were analyzed using linear regression. Results: The overall mortality risk significantly lowered in the 2019 cohort (HR 0.84; 95% CI 0.72–0.98, p = 0.024). Stage III patients were not associated with a significant overall survival rate (HR 0.71; 95% CI 0.50–1.02; p = 0.065) but were associated with significantly higher cancer-specific survival (HR 0.61; 95% CI 0.41–0.91; p = 0.015). Overall, the 2019 cohort showed significantly higher costs (coefficient 0.16; 95% CI 0.02–0.30, p = 0.025), particularly as a result of increases in the costs of drug administration, outpatient services, and medical devices. However, during the same 3-year follow-up period, this cohort featured lower average costs for hospice care and hospitalizations. Conclusions: These results revealed notable differences in clinical outcomes and patient-related costs in incident NSCLCs in 2017 and 2019. The study highlights the importance of monitoring clinical outcomes and management costs in real-world oncology practice.
Immune Checkpoint Inhibitors and Targeted Therapies in Early-Stage Non-Small-Cell Lung Cancer: State-of-the-Art and Future Perspectives
Authors: Barcellini Lucrezia , Nardin Simone , Sacco Gianluca , Ferrante Michele , Rossi Giovanni , Barletta Giulia , Bennicelli Elisa , Dellepiane Chiara , Tagliamento Marco , Ramella Pollone Beatrice , Lucente Luca , Coco Simona , Marconi Silvia , Santamaria Sara , Pariscenti Gian Luca , Genova Carlo
Published: February 2025

Background: Approximately 25–30% of non-small-cell lung cancer (NSCLC) patients are diagnosed when the disease is still resectable, although the risk of recurrence is significant. Recently, approaches based on targeted agents or immune checkpoint inhibitors (ICIs) have modified the management of such patients. However, some questions remain unanswered. Objectives: Our aim is to assess the current evidence on approaches involving targeted agents and ICIs in resectable NSCLC, to provide an up-to-date overview of the subject, and to identify areas of current debate, Methods: We analyzed randomized trials on ICIs and targeted therapies in early-stage NSCLC, published or presented at international oncology meetings throughout the last 5 years. Results: Osimertinib and alectinib have shown robust results in the adjuvant setting for molecularly identified patient subgroups, while ICIs have achieved robust data in the neoadjuvant/perioperative setting, with less consistent data on the pure adjuvant approach. Circulating tumor DNA levels may offer a possible biomarker for therapeutic decisions, albeit more prospective data are needed. Conclusions: Targeted agents and ICIs are revolutionizing early-stage NSCLC, similarly to what was observed in advanced disease. Prospective studies designed to compare neoadjuvant, adjuvant, and perioperative approaches and to assess the role of circulating biomarkers are warranted.
Autophagy in Tissue Repair and Regeneration
Authors: Moreno-Blas Daniel , Adell Teresa , González-Estévez Cristina
Published: February 2025

Autophagy is a cellular recycling system that, through the sequestration and degradation of intracellular components regulates multiple cellular functions to maintain cellular homeostasis and survival. Dysregulation of autophagy is closely associated with the development of physiological alterations and human diseases, including the loss of regenerative capacity. Tissue regeneration is a highly complex process that relies on the coordinated interplay of several cellular processes, such as injury sensing, defense responses, cell proliferation, differentiation, migration, and cellular senescence. These processes act synergistically to repair or replace damaged tissues and restore their morphology and function. In this review, we examine the evidence supporting the involvement of the autophagy pathway in the different cellular mechanisms comprising the processes of regeneration and repair across different regenerative contexts. Additionally, we explore how modulating autophagy can enhance or accelerate regeneration and repair, highlighting autophagy as a promising therapeutic target in regenerative medicine for the development of autophagy-based treatments for human diseases.
Molecular Mechanisms of Immune Regulation: A Review
Authors: Arneth Borros
Published: February 2025

Background: The immune system must carefully balance fighting pathogens with minimization of inflammation and avoidance of autoimmune responses. Over the past ten years, researchers have extensively studied the mechanisms regulating this delicate balance. Comprehending these mechanisms is essential for developing treatments for inflammatory conditions. Aim: This review aims to synthesize knowledge of immunoregulatory processes published from 2014–2024 and to highlight discoveries that provide fresh perspectives on this complex balance. Methods: The keywords “molecular mechanisms”, “immune regulation”, “immune signaling pathways”, and “immune homeostasis” were used to search PubMed for articles published between 2014 and 2024, with a preference for articles published in the past three years. Results: Recent research has pinpointed the impact of factors such as cytokine signaling, T-cell regulation, epigenetic regulation, and immunometabolism on immune function. Discussion: New research highlights the intricate interactions between the immune system and other molecular elements. A key area of interest is the impact of non-coding RNAs and metabolic pathways on the regulation of immune responses. Conclusions: Exploring the mechanisms by which the immune system is regulated will provide new avenues for developing treatments to address autoimmune and inflammatory conditions.
Arterial Stiffness and Subclinical Inflammation in Children with Familial Mediterranean Fever: A Comprehensive Analysis
Authors: Sav Nadide Melike , Altinsoy Hasan Baki , Turen Betul , Gökçe Ayşe
Published: February 2025

Background/Objectives: Familial Mediterranean fever (FMF) is a chronic autoinflammatory disease. Throughout the disease, subclinical inflammation persists into the remission period. It is known that chronic inflammation causes endothelial dysfunction and, as a consequence, arterial stiffness occurs. In this study, carotid and aortic intima–media thicknesses (IMT) and arterial stiffness were measured in FMF patients to evaluate the risk of possible vascular damage due to chronic inflammation. Methods: The study included pediatric patients with FMF who had been in remission for a minimum of 3 months. Carotid and aortic IMT and arterial stiffness measurements were conducted using sonoelastography. The acute-phase reactants were also evaluated in all participants. Results: Carotid artery stiffness measurements by strain elastography were significantly higher in the patient group than in the control group. However, the aortic and carotid IMT were similar between the two groups. The acute-phase reactants were significantly higher in the patient group than in the control group. Conclusions: This study demonstrated that arterial stiffness increased in pediatric FMF patients. According to the results of the present study, the effects of chronic inflammation on arterial tissues may lead to atherosclerotic changes in the later stages of the disease and may pose a risk for coronary diseases. Arterial ultrasonographic and elastographic measurements to be performed periodically in children with FMF are noninvasive methods that can be used to evaluate the course of endothelial damage. We aimed to show that arterial stiffness may be a marker of early cardiovascular disease.
Mechanism and Applications of Vagus Nerve Stimulation
Authors: Chen Zhen , Liu Kezhou
Published: February 2025

Over the past three decades, vagus nerve stimulation (VNS) has emerged as a promising rehabilitation therapy for a diverse range of conditions, demonstrating substantial clinical potential. This review summarizes the in vivo biological mechanisms activated by VNS and their corresponding clinical applications. Furthermore, it outlines the selection of parameters and equipment for VNS implementation. VNS exhibits anti-inflammatory effects, modulates neurotransmitter release, enhances neural plasticity, inhibits apoptosis and autophagy, maintains blood–brain barrier integrity, and promotes angiogenesis. Clinically, VNS has been utilized in the treatment of epilepsy, depression, headache, stroke, and obesity. Its potential applications extend to anti-inflammatory treatment and the management of cardiovascular and cerebrovascular diseases and various brain disorders. However, further experiments are required to definitively establish the efficacy of VNS’s various mechanisms. Additionally, there is a need to explore and identify optimal rehabilitation treatment parameters for different diseases.
High-Temperature Steam- and CO2-Assisted Gasification of Oil Sludge and Petcoke
Authors: Frolov Sergey M. , Smetanyuk Viktor A. , Sadykov Ilyas A. , Silantiev Anton S. , Frolov Fedor S. , Popkova Vera Ya. , Hasiak Jaroslav K. , Buyanovskaya Anastasiya G. , Takazova Rina U. , Dudareva Tatiana V. , Bekeshev Valentin G. , Vorobyov Alexey B. , Inozemtsev Alexey V. , Inozemtsev Jaroslav O.
Published: February 2025

A new high-temperature allothermal gasification technology is used to process three types of oil waste: ground oil sludge (GOS), tank oil sludge (TOS), and petcoke. The gasifying agent (GA), mainly composed of H2O and CO2 at a temperature above 2300 K and atmospheric pressure, is produced by pulsed detonations of a near-stochiometric methane-oxygen mixture. The gasification experiments show that the dry off-gas contains 80–90 vol.% combustible gas composed of 40–45 vol.% CO, 28–33 vol.% H2, 5–10 vol.% CH4, and 4–7 vol.% noncondensable C2–C3 hydrocarbons. The gasification process is accompanied by the removal of mass from a flow gasifier in the form of fine solid ash particles with a size of about 1 μm. The ash particles have a mesoporous structure with a specific surface area ranging from 3.3 to 15.2 m2/g and pore sizes ranging from 3 to 50 nm. The measured wall temperatures of the gasifier are in reasonable agreement with the calculated value of the thermodynamic equilibrium temperature of the off-gas. The measured CO content in the off-gas is in good agreement with the thermodynamic calculations. The reduced H2 content and elevated contents of CH4, CO2, and CxHy are apparently associated with the nonuniform distribution of the waste/GA mass ratio in the gasifier. To increase the H2 yield, it is necessary to improve the mixing of waste with the GA. It is proposed to mix crushed petcoke with oil sludge to form a paste and feed the combined waste into the gasifier using a specially designed feeder.