bluuebunny/crossref_metadata_2025 huggingface dataset:
Real-Time Performance Measurement Application via Bluetooth Signals for Signalized Intersections
Authors: Yalçınlı Fuat , Akdemir Bayram , Durdu Akif
Published: September 2024

Improving the performance at signalized intersections can be achieved through different management styles or sensor technologies. It is crucial that we measure the real-time impact of these variables on intersection performance. This study introduces a Bluetooth-based real-time performance measurement system applicable to all signalized intersections. Additionally, the developed method serves as a feedback tool for adaptive intersection management systems, providing valuable data input for performance optimization. The method developed in the study is applied at the Refik Cesur Intersection in the Polatlı district of Ankara where delay values are calculated based on traffic flows and data from Bluetooth sensors positioned at strategic locations. Initially, the intersection operated under a fixed-time signaling system, followed by a fully adaptive signaling system the next day. The performance of these two systems is compared using the Bluetooth-based application. The results show that the average delay per vehicle per day is 58.1 seconds/vehicle for the fixed-time system and 45.3 seconds/vehicle for the adaptive system. To validate the Bluetooth-based performance measurement system, the intersection is modeled and simulated using Aimsun Simulation Software Next 20.0.4. The simulation results confirm the findings of the Bluetooth-based analysis, demonstrating the effectiveness of the adaptive signaling system in reducing delays.
Channel State Information (CSI) Amplitude Coloring Scheme for Enhancing Accuracy of an Indoor Occupancy Detection System Using Wi-Fi Sensing
Authors: Son Jaeseong , Park Jaesung
Published: September 2024

Indoor occupancy detection (IOD) via Wi-Fi sensing capitalizes on the varying patterns in CSI (Channel State Information) to estimate the number of people in a given area. However, the precision of such systems heavily depends on the quality of the CSI data, which can be degraded by noise and environmental factors. To address this issue, In this paper, we present a CSI preprocessing method to improve the accuracy of IOD systems using Wi-Fi sensing. Unlike existing preprocessing methods that use computationally complex signal processing or statistical techniques, we expand the dimension of CSI amplitude data into a three-channel vector through nonlinear transformation to amplify subtle differences between CSI data belonging to a different number of people. By drawing clearer boundaries between CSI data distributions belonging to a different number of people in a monitored area, our method improves the people-counting accuracy of a Wi-Fi sensing system. To ensure temporal consistency and improve data quality, we discretize the CSI measurements based on their transmission periods and aggregate consecutive measurements over a given time interval. These samples are then fed into a Convolutional Neural Network (CNN) specifically trained for the IOD task. Experimental results in diverse real-world scenarios verify that compared to the traditional methods, the enhanced feature representation capability of our approach leads to more accurate and robust sensing outcomes even in the most resource-constrained environment, where a commercial off-the-shelf CSI capture machine with only one antenna is used when a Wi-Fi sender with one transmit antenna sends packets periodically to the channel with the smallest Wi-Fi channel bandwidth.
THC Modelling of Bentonite Barrier of Geological Repository in Granite and Its Impact on Long-Term Safety
Authors: Narkuniene Asta , Grigaliuniene Dalia , Poskas Gintautas
Published: September 2024

As in any other industry, nuclear energy results in the accumulation of some waste, which needs to be managed safely and responsibly due to its radiotoxicity. In the case of highly radioactive waste, geological disposal in stable rock is considered a broadly accepted solution. For the evaluation of the long-term safety of a geological repository, the assessment of radionuclide transport needs to be carried out. Radionuclide transport through engineered and natural barriers of the repository will highly depend on the barriers’ transport-related properties, which will be determined by coupled thermal, hydraulic, chemical, mechanical, biological, and radiation processes taking place in those barriers. In this study, the thermo-hydro-chemical (THC) state of bentonite was analysed considering CO2 gas diffusion and temperature-dependent solubility in water. Reactive transport modelling of bentonite under non-isothermal conditions was performed with the COMSOL Multiphysics software (v6.0), coupled with the geochemical solver Phreeqc via the iCP interface. The modelling demonstrated that the consideration of chemical processes in bentonite had no significant influence on non-reactive Cl− transport; however, it would be important for other radionuclides whose sorption in porous media depends on the porewater pH. Based on the modelling results, changes in the bentonite mineralogical composition and, subsequently, porosity depend on the partial CO2 pressure at the bentonite–granite boundary. In the case of low CO2 partial pressure at the bentonite–granite interface, the calcite dissolution led to a slight porosity increase, while higher CO2 partial pressure led to decreased porosity near the interface.
3D Printed Microfluidic Separators for Solid/Liquid Suspensions
Authors: Marković Marijan-Pere , Žižek Krunoslav , Soldo Ksenija , Sunko Vjeran , Zrno Julijan , Vrsaljko Domagoj
Published: September 2024

This study investigates the fabrication of 3D-printed microfluidic devices for solid/liquid separation, focusing on additive manufacturing technologies. Stereolithography (SLA) and fused filament fabrication (FFF) were used to create microseparators with intricate designs optimized for separation efficiency. Model suspensions containing quartz sand, nano-calcium carbonate, and talc-based baby powder in water were prepared using an electric magnetic stirrer and conveyed into the microseparator via a peristaltic pump. Different flow rates were tested to evaluate their influence on the separation efficiency. The highest separation efficiency for the model systems was observed at a flow rate of 200 mL min−1. This was due to the increased turbulence at higher flow rates, which hindered the secondary flow perpendicular to the primary flow direction. The particle size distribution before and after separation was analyzed using sieve and laser diffraction, and particle morphology was inspected by scanning electron microscopy. The laser diffraction analysis revealed post-separation particle size distributions, indicating that Outlet 1 (external stream) consistently captured larger particles more effectively than Outlet 2 (internal stream). This work highlights the potential of additive manufacturing to produce customized microfluidic devices, enabling rapid prototyping and fine-tuning of complex geometries, thus enhancing separation efficiency across various industrial applications.
Study on Noise-Reduction Mechanism and Structural-Parameter Optimization of Ventilated Acoustic Metamaterial Labyrinth Plate
Authors: Zhang Dacheng , Tang Wanru , Sun Yumeng , Chen Changzheng , Su Xiaoming , Sun Xianming
Published: September 2024

In many noise scenarios, it is necessary to ensure ventilation and noise suppression. In this paper, a ventilated acoustic metamaterial labyrinth plate (VAMLP), formed by an array of labyrinth cells (LCs), is presented. Each labyrinth cell contains four labyrinth waveguide units (WUs). Based on the impedance series principle, an analytical model of the WU was developed and validated by a numerical model and impedance-tube experiments to determine the sound transmission loss of the WU and the LC. The mechanism of the influence of thermo-viscous loss was quantitatively analyzed, and it was clarified that the VAMLP produced sound absorption due to thermo-viscous loss. The change law of impedance at the entrance of the waveguide was analyzed, revealing the noise-reduction mechanism of the labyrinth unit. Combining a BP network and an improved sparrow search algorithm (ISSA), a BP–ISSA optimization model is proposed to optimize the ventilation capacity of the labyrinth cells. The BP-network model can accurately predict the resonance frequency from the structural parameters to form the fitness function. The ISSA optimization model was constructed using the fitness function as the constraint of an equation. Finally, the combination of structural parameters with optimal ventilation capacity was obtained for a given noise frequency.
Advancements in Semi-Active Automotive Suspension Systems with Magnetorheological Dampers: A Review
Authors: Wang Zunming , Liu Chi , Zheng Xu , Zhao Liang , Qiu Yi
Published: September 2024

Magnetorheological (MR) dampers have significantly advanced automotive suspension systems by providing adaptable damping characteristics in response to varying road conditions and driving dynamics. This review offers a comprehensive analysis of the evolution and integration of MR dampers in semi-active suspension systems. Semi-active systems present an optimal balance by integrating the simplicity inherent in passive systems with the adaptability characteristic of active systems, while mitigating the substantial energy consumption. The fundamental principles of MR technology, the design of MR dampers, and the diverse control strategies employed to optimize suspension performance were examined. The classical, modern, and intelligent control methods, along with the related research, were emphasized. Based on the above-mentioned methods, the benefits of MR semi-active control were highlighted, while the challenges and future research directions in MR damper technology were also addressed. Through a synthesis of recent research findings and practical applications, this paper underscores the advancements in MR-based semi-active suspension systems and their promising prospects in the automotive industry.
Nanoparticles Combining Gene Therapy and Chemotherapy as a Treatment for Gastrointestinal Tumors: A Systematic Review
Authors: Rodríguez-Criado Jorge , Quiñonero Francisco , Prados Jose , Melguizo Consolacion
Published: September 2024

Gastrointestinal cancer is one of the greatest challenges for biomedical research, accounting for one-quarter of diagnoses and one-third of deaths nowadays, due to the existence of drug resistance mechanisms that prevent therapeutic efficacy in advanced stages. Nanotechnology has been shown to be an effective strategy for the evasion of this phenomenon, and gene silencing by siRNA makes it possible to decrease the expression of certain genes involved in chemoresistance and tumor progression. Our review analyzed studies published during the last 5 years that combined siRNA gene inhibition and chemotherapy as treatment of different gastrointestinal tumors. This review was carried out by searching PubMed, SCOPUS and WoS databases, where 49 articles were finally selected. The results showed that simultaneous encapsulation of siRNA targeting different genes involved in cancer and chemotherapy were more effective at the preclinical level compared to the administration of both treatments individually. The cytotoxic effect was generated through increased induction of apoptosis derived from the dysregulation of chemoresistance-related pathways, producing a decrease in tumor volume and an increase in survival of mice in in vivo assays. Therefore, the combination of both therapies in the same nanoformulation appears to be an interesting therapeutic strategy for the treatment of gastrointestinal tumors.
Masked Style Transfer for Source-Coherent Image-to-Image Translation
Authors: Botti Filippo , Fontanini Tomaso , Bertozzi Massimo , Prati Andrea
Published: September 2024

The goal of image-to-image translation (I2I) is to translate images from one domain to another while maintaining the content representations. A popular method for I2I translation involves the use of a reference image to guide the transformation process. However, most architectures fail to maintain the input’s main characteristics and produce images that are too similar to the reference during style transfer. In order to avoid this problem, we propose a novel architecture that is able to perform source-coherent translation between multiple domains. Our goal is to preserve the input details during I2I translation by weighting the style code obtained from the reference images before applying it to the source image. Therefore, we choose to mask the reference images in an unsupervised way before extracting the style from them. By doing so, the input characteristics are better maintained while performing the style transfer. As a result, we also increase the diversity in the generated images by extracting the style from the same reference. Additionally, adaptive normalization layers, which are commonly used to inject styles into a model, are substituted with an attention mechanism for the purpose of increasing the quality of the generated images. Several experiments are performed on the CelebA-HQ and AFHQ datasets in order to prove the efficacy of the proposed system. Quantitative results measured using the LPIPS and FID metrics demonstrate the superiority of the proposed architecture compared to the state-of-the-art methods.
Review on Assessment and Performance Mechanism Evaluation of Non-Structural Concrete Incorporating Waste Materials
Authors: Mashaan Nuha S. , De Silva Appuwa
Published: September 2024

This research seeks to solve the multi-faceted problem of waste disposal by analysing the application of waste plastic and tyre material within non-structural concrete to ensure more sustainability and less environmental degradation. The study focusses on material properties, including specific gravity, water absorption, and bulk density and characteristics of the concrete that is produced by the utilization of the above waste aggregates, including workability, compressive strength, flexural strength, and tensile strength. This paper employs results from published past research from the literature and MATLAB (R2021b) in the analysis of the findings, pointing to the fact that the mechanical properties reduce with the level of waste content yet emphasizing the green aspect of such materials. Thus, a complex and diverse effect is demonstrated by the life cycle assessments (LCA) for global warming, ozone depletion, terrestrial ecotoxicity, and acidification. Furthermore, the utilization of waste materials decreases the compressive, flexural, and tensile strength, but it provides distinct ecological benefits which prove the importance of proper mix proportions for concrete performance. The outcomes of this research will be useful for further investigation in the application of the concept as well as to call for the development of new ideas for the improvement of bonding of wastes to aggregates in concrete.
Biophilia and Adolescents’ Sense of Place in Australian Vertical Schools
Authors: Baber Tim , Cleveland Benjamin
Published: September 2024

This article describes the place relationships adolescents have with natural elements in recently developed ‘vertical schools’ in Australia: a relatively new school typology in the country, generally considered to be over four storeys high. Vertical schools are being built in Australia’s largest cities in response to the need for new schools where land is scarce. Drawing on qualitative research into the place relationships that adolescents have with their learning environments in two Australian vertical schools, this article explores the ways young people seek closer associations with nature in multi-storey educational settings. The research adopted a phenomenological approach to ‘place research’, asking what makes a place a place? Further, it recognised that places have the capacity to shape the ‘becoming’ of a person, that ‘becoming’ happens when there is a certain resonance between a place’s cycles, and that identity is created out of difference. As such, ‘place as complex adaptive assemblage theory’ was employed to study the interplay between location and experience in selected vertical schools, also drawing on the earlier theoretical work of Relph (1976), who suggested that the essence of a place lies in the unselfconscious intentionality that defines places as profound centres of human existence. Photovoice was employed as a method to elicit insights into the relationships adolescents have with their school as place. Students created photo essays to document their place relationships, revealing deeply insightful personal reflections on their school as place and the meanings they associate with it. Specifically, the article reports on what thirteen adolescent students communicated about the biophilic experiences afforded by their vertical school, including how it influenced their ‘becoming’. The findings demonstrated that the participating students not only valued relationships with natural elements, but actively sought biophilic experiences on a regular basis. The desire for more frequent and more significant interactions with natural materials and cycles was common across most students, indicating that the relatively limited biophilic experiences available to students in vertical schools is a challenge that should be addressed in future multi-level educational environments.
Application of Three-Dimensional Vision Technology in Dance
Authors: Zhong Yixun , Fu Xiao , Liang Zhihao , Ning Honglong
Published: September 2024

The development of science and technology constantly injects new vitality into dance performance and creation. Among them, three-dimensional (3D) vision technology provides novel ideas for the innovation and artistry of dance performances, expands the forms of dance performances and the way to present dance works, and brings a brand-new viewing experience to the audience. Nowadays, 3D vision technology in dance has been widely researched and applied. This review presents the background of the 3D vision technology application in the dance field, analyzes the main types of technology and working principles for realizing 3D vision, summarizes the research and application of the 3D vision technology in dance creation, perception, enhancement, and dance teaching, and finally looks forward to the development prospect of the 3D vision technology in the dance.
First Detections of Ionospheric Plasma Density Irregularities from GOES Geostationary GPS Observations during Geomagnetic Storms
Authors: Cherniak Iurii , Zakharenkova Irina , Gleason Scott , Hunt Douglas
Published: September 2024

In this study, we present the first results of detecting ionospheric irregularities using non-typical GPS observations recorded onboard the Geostationary Operational Environmental Satellites (GOES) mission operating at ~35,800 km altitude. Sitting above the GPS constellation, GOES can track GPS signals only from GPS transmitters on the opposite side of the Earth in a rather unique geometry. Although GPS receivers onboard GOES are primarily designed for navigation and were not configured for ionospheric soundings, these GPS measurements along links that traverse the Earth’s ionosphere can be used to retrieve information about ionospheric electron density. Using the radio occultation (RO) technique applied to GPS measurements from the GOES–16, we analyzed variations in the ionospheric total electron content (TEC) on the links between the GPS transmitter and geostationary GOES GPS receiver. For case-studies of major geomagnetic storms that occurred in September 2017 and August 2018, we detected and analyzed the signatures of storm-induced ionospheric irregularities in novel and promising geostationary GOES GPS observations. We demonstrated that the presence of ionospheric irregularities near the GOES GPS RO sounding field of view during geomagnetic disturbances was confirmed by ground-based GNSS observations. The use of RO observations from geostationary orbit provides new opportunities for monitoring ionospheric irregularities and ionospheric density.
On Extending the Applicability of Iterative Methods for Solving Systems of Nonlinear Equations
Authors: Bate Indra , Murugan Muniyasamy , George Santhosh , Senapati Kedarnath , Argyros Ioannis K. , Regmi Samundra
Published: September 2024

In this paper, we present a technique that improves the applicability of the result obtained by Cordero et al. in 2024 for solving nonlinear equations. Cordero et al. assumed the involved operator to be differentiable at least five times to extend a two-step p-order method to order p+3. We obtained the convergence order of Cordero et al.’s method by assuming only up to the third-order derivative of the operator. Our analysis is in a more general commutative Banach algebra setting and provides a radius of the convergence ball. Finally, we validate our theoretical findings with several numerical examples. Also, the concept of basin of attraction is discussed with examples.
Impacts of Curing-Induced Phase Segregation in Silicon Nanoparticle-Based Electrodes
Authors: Huey Zoey , Carroll G. Michael , Coyle Jaclyn , Walker Patrick , Neale Nathan R. , DeCaluwe Steven , Jiang Chunsheng
Published: September 2024

We report the investigation of silicon nanoparticle composite anodes for Li-ion batteries, using a combination of two nm-scale atomic force microscopy-based techniques: scanning spreading resistance microscopy for electrical conduction mapping and contact resonance and force volume for elastic modulus mapping, along with scanning electron microscopy-based energy dispersion spectroscopy, nanoindentation, and electrochemical analysis. Thermally curing the composite anode—made of polyethylene oxide-treated Si nanoparticles, carbon black, and polyimide binder—reportedly improves the anode electrochemical performance significantly. This work demonstrates phase segregation resulting from thermal curing, where alternating bands of carbon and silicon active material are observed. This electrode morphology is retained after extensive cycling, where the electrical conduction of the carbon-rich bands remains relatively unchanged, but the mechanical modulus of the bands decreases distinctly. These electrical and mechanical factors may contribute to performance improvement, with carbon bands serving as a mechanical buffer for Si deformation and providing electrical conduction pathways. This work motivates future efforts to engineer similar morphologies for mitigating capacity loss in silicon electrodes.
A Comparative Study of Sentiment Classification Models for Greek Reviews
Authors: Michailidis Panagiotis D.
Published: September 2024

In recent years, people have expressed their opinions and sentiments about products, services, and other issues on social media platforms and review websites. These sentiments are typically classified as either positive or negative based on their text content. Research interest in sentiment analysis for text reviews written in Greek is limited compared to that in English. Existing studies conducted for the Greek language have focused more on posts collected from social media platforms rather than on consumer reviews from e-commerce websites and have primarily used traditional machine learning (ML) methods, with little to no work utilizing advanced methods like neural networks, transfer learning, and large language models. This study addresses this gap by testing the hypothesis that modern methods for sentiment classification, including artificial neural networks (ANNs), transfer learning (TL), and large language models (LLMs), perform better than traditional ML models in analyzing a Greek consumer review dataset. Several classification methods, namely, ML, ANNs, TL, and LLMs, were evaluated and compared using performance metrics on a large collection of Greek product reviews. The empirical findings showed that the GreekBERT and GPT-4 models perform significantly better than traditional ML classifiers, with BERT achieving an accuracy of 96% and GPT-4 reaching 95%, while ANNs showed similar performance to ML models. This study confirms the hypothesis, with the BERT model achieving the highest classification accuracy.
AI-Powered Synthesis of Structured Multimodal Breast Ultrasound Reports Integrating Radiologist Annotations and Deep Learning Analysis
Authors: Azhar Khadija , Lee Byoung-Dai , Byon Shi Sub , Cho Kyu Ran , Song Sung Eun
Published: September 2024

Breast cancer is the most prevalent cancer among women worldwide. B-mode ultrasound (US) is essential for early detection, offering high sensitivity and specificity without radiation exposure. This study introduces a semi-automatic method to streamline breast US report generation, aiming to reduce the burden on radiologists. Our method synthesizes comprehensive breast US reports by combining the extracted information from radiologists’ annotations during routine screenings with the analysis results from deep learning algorithms on multimodal US images. Key modules in our method include image classification using visual features (ICVF), type classification via deep learning (TCDL), and automatic report structuring and compilation (ARSC). Experiments showed that the proposed method reduced the average report generation time to 3.8 min compared to manual processes, even when using relatively low-spec hardware. Generated reports perfectly matched ground truth reports for suspicious masses without a single failure on our evaluation datasets. Additionally, the deep-learning-based algorithm, utilizing DenseNet-121 as its core model, achieved an overall accuracy of 0.865, precision of 0.868, recall of 0.847, F1-score of 0.856, and area under the receiver operating characteristics of 0.92 in classifying tissue stiffness in breast US shear-wave elastography (SWE-mode) images. These improvements not only streamline the report generation process but also allow radiologists to dedicate more time and focus on patient care, ultimately enhancing clinical outcomes and patient satisfaction.
A Rapid Head Organ Localization System Based on Clinically Realistic Images: A 3D Two Step Progressive Registration Method with CVH Anatomical Knowledge Mapping
Authors: Sun Changjin , Tong Fei , Luo Junjie , Wang Yuting , Ou Mingwen , Wu Yi , Qiu Mingguo , Wu Wenjing , Gong Yan , Luo Zhongwen , Qiao Liang
Published: September 2024

Rapid localization of ROI (Region of Interest) for tomographic medical images (TMIs) is an important foundation for efficient image reading, computer-aided education, and well-informed rights of patients. However, due to the multimodality of clinical TMIs, the complexity of anatomy, and the deformation of organs caused by diseases, it is difficult to have a universal and low-cost method for ROI organ localization. This article focuses on actual concerns of TMIs from medical students, engineers, interdisciplinary researchers, and patients, exploring a universal registration method between the clinical CT/MRI dataset and CVH (Chinese Visible Human) to locate the organ ROI in a low-cost and lightweight way. The proposed method is called Two-step Progressive Registration (TSPR), where the first registration adopts “eye–nose triangle” features to determine the spatial orientation, and the second registration adopts the circular contour to determine the spatial scale, ultimately achieving CVH anatomical knowledge automated mapping. Through experimentation with representative clinical TMIs, the registration results are capable of labeling the ROI in the images well and can adapt to the deformation problem of ROI, as well as local extremum problems that are prone to occur in inter-subject registration. Unlike the ideal requirements for TMIs’ data quality in laboratory research, TSPR has good adaptability to incomplete and non-thin-layer quality in real clinical data in a low-cost and lightweight way. This helps medical students, engineers, and interdisciplinary researchers independently browse images, receive computer-aided education, and provide patients with better access to well-informed services, highlighting the potential of digital public health and medical education.
Roles of Toll-like Receptor Signaling in Inflammatory Bone Resorption
Authors: Tominari Tsukasa , Matsumoto Chiho , Tanaka Yuki , Shimizu Kensuke , Takatoya Masaru , Sugasaki Moe , Karouji Kento , Kasuga Urara , Miyaura Chisato , Miyata Shinji , Itoh Yoshifumi , Hirata Michiko , Inada Masaki
Published: September 2024

Toll-like receptors (TLRs) are pattern recognition receptors expressed in immune cells, including neutrophils, macrophages, and dendritic cells. Microbe-associated molecular patterns, including bacterial components, membranes, nucleic acids, and flagella are recognized by TLRs in inflammatory immune responses. Periodontal disease is an inflammatory disease known to cause local infections associated with gingival inflammation, subsequently leading to alveolar bone resorption. Prostaglandin E2 (PGE2) is a key mediator of TLR-induced inflammatory bone resorption. We previously reported that membrane-bound PGE synthase (mPGES-1)-deficient mice failed to induce bone resorption by lipopolysaccharide (LPS), a major pathogenic factor involved in periodontal bone resorption. Further experiments exploring specific pathogen-promoting osteoclast differentiation revealed that various TLR ligands induced osteoclast differentiation in a co-culture model. The ligands for TLR2/1, TLR2/6, TLR3, and TLR5, as well as TLR4, induce osteoclast differentiation associated with the production of PGE2 and the receptor activator of nuclear factor-kappa B ligand (RANKL), an inevitable inducer of osteoclast differentiation in osteoblasts. In vivo, local injection of TLR ligands, including TLR2/1, TLR2/6, and TLR3, resulted in severe alveolar bone resorption. This review summarizes the latest findings on TLR-mediated osteoclast differentiation and bone resorption in inflammatory diseases, such as periodontal diseases.
Prospects and Current Challenges of Extracellular Vesicle-Based Biomarkers in Cancer
Authors: Lawrence Samuel R. , Shah Karan M.
Published: September 2024

Cancer continues to impose a substantial global health burden, particularly among the elderly, where the ongoing global demographic shift towards an ageing population underscores the growing need for early cancer detection. This is essential for enabling personalised cancer care and optimised treatment throughout the disease course to effectively mitigate the increasing societal impact of cancer. Liquid biopsy has emerged as a promising strategy for cancer diagnosis and treatment monitoring, offering a minimally invasive method for the isolation and molecular profiling of circulating tumour-derived components. The expansion of the liquid biopsy approach to include the detection of tumour-derived extracellular vesicles (tdEVs) holds significant therapeutic opportunity. Evidence suggests that tdEVs carry cargo reflecting the contents of their cell-of-origin and are abundant within the blood, exhibiting superior stability compared to non-encapsulated tumour-derived material, such as circulating tumour nucleic acids and proteins. However, despite theoretical promise, several obstacles hinder the translation of extracellular vesicle-based cancer biomarkers into clinical practice. This critical review assesses the current prospects and challenges facing the adoption of tdEV biomarkers in clinical practice, offering insights into future directions and proposing strategies to overcome translational barriers. By addressing these issues, EV-based liquid biopsy approaches could revolutionise cancer diagnostics and management.
Screening of Anti-Prion Compounds Using the Protein Misfolding Cyclic Amplification Technology
Authors: Pritzkow Sandra , Schauer Isaac , Tupaki-Sreepurna Ananya , Morales Rodrigo , Soto Claudio
Published: September 2024

Prion diseases are 100% fatal infectious neurodegenerative diseases affecting the brains of humans and other mammals. The disease is caused by the formation and replication of prions, composed exclusively of the misfolded prion protein (PrPSc). We invented and developed the protein misfolding cyclic amplification (PMCA) technology for in vitro prion replication, which allow us to replicate the infectious agent and it is commonly used for ultra-sensitive prion detection in biological fluids, tissues and environmental samples. In this article, we studied whether PMCA can be used to screen for chemical compounds that block prion replication. A small set of compounds previously shown to have anti-prion activity in various systems, mostly using cells infected with murine prions, was evaluated for their ability to prevent the replication of prions. Studies were conducted simultaneously with prions derived from 4 species, including human, cattle, cervid and mouse. Our results show that only one of these compounds (methylene blue) was able to completely inhibit prion replication in all species. Estimation of the IC50 for methylene blue inhibition of human prions causing variant Creutzfeldt-Jakob disease (vCJD) was 7.7 μM. Finally, we showed that PMCA can be used for structure-activity relationship studies of anti-prion compounds. Interestingly, some of the less efficient prion inhibitors altered the replication of prions in some species and not others, suggesting that PMCA is useful for studying the differential selectivity of potential drugs.
Effects of Aging on Patellofemoral Joint Stress during Stair Negotiation on Challenging Surfaces
Authors: Hunt Nicholas L. , Holcomb Amy E. , Fitzpatrick Clare K. , Brown Tyler N.
Published: September 2024

This study examined the effect of age and surface on patellofemoral joint (PFJ) stress magnitude and waveform during stair ascent and descent tasks. A total of 12 young and 12 older adults had knee biomechanics quantified while they ascended and descended stairs on normal, slick, and uneven surfaces. The peak of stance (0–100%) PFJ stress and associated components were submitted to a two-way repeated measures ANOVA, while the PFJ stress waveform was submitted to statistical parametric mapping two-way ANOVA. During stair ascent, older adults exhibited greater PFJ stress waveforms, from 55 to 59% and 74 to 84% of stance (p < 0.001) as well as greater PFJ stress–time integral across stance (p = 0.003), and later peak PFJ stress, than young adults (p = 0.002). When ascending on the uneven surface, participants exhibited smaller PFJ stress from 9 to 24% of stance compared to the normal surface, but greater PFJ stress from 75 to 88% and from 63 to 68% of stance (p < 0.001) as well as greater PFJ stress–time integrals compared to normal and slick surfaces (p < 0.032). During stair descent, older adults exhibited a smaller PFJ contact area range (p = 0.034) and peak knee flexion angle (p = 0.022) than young adults. When descending on the slick surface, participants exhibited smaller PFJ stress from 5 to 18% of stance, but greater stress, from 92 to 98% of stance (both: p < 0.001), compared to the normal surface. Negotiating slick and uneven stairs may produce knee biomechanics that increase PFJ stress, and the larger, later PFJ stress exhibited by older adults may further increase their risk of PFJ pain.
Confronting Accelerating Global Antimicrobial Resistance and the Associated Increase in Deaths
Authors: Amsterdam Daniel
Published: September 2024

Although advances in contemporary medical care have broadened access to healthcare and extended the human life span, deaths resulting from antimicrobial-resistant pathogens continue to increase. This minireview summarizes the evidence that AI and machine learning, coupled with precision medicine and alternative therapies, such as repurposing non-antibiotic drugs and the use of bacteriophages, has promise to halt this advance.
Kawasaki Disease Diagnosis and Treatment in over 1000 Patients: A Continuum of Dysregulated Inflammatory Responses
Authors: Netea Stejara A. , Biesbroek Giske , van Stijn Diana , Nagelkerke Sietse Q. ,   Kawasaki Study Group,   CAHAL Group,   KIRI Group, Kuipers Irene M. , Kuijpers Taco W.
Published: September 2024

Background: Kawasaki disease (KD) is a pediatric vasculitis, leading to coronary artery aneurysms (CAAs) in ~4–14%. Attention to the etiology and course of KD was generated by the close mimic of a SARS-CoV-2-induced phenotype, called multisystem inflammatory syndrome in children (MIS-C). Methods: A total of 1179 cases were collected from 2012 with ~50% of cases retrospectively included. Clinical characteristics were described and risk factors for CAA (persistence) were investigated. Phenotypic patterns of the prospectively included KD patients were evaluated. These patterns were also compared to the seronegative KD and seropositive MIS-C cases identified during the SARS-CoV-2 pandemic. Results: KD mostly affected boys and children < 5 years. IVIG resistance, CAAs, and giant CAAs occurred in 24.5%, 21.4%, and 6.6%, respectively. Giant CAAs were significantly more likely to normalize to a normal Z score in patients that were younger than 2.5 years old at the time of initial giant CAA (χ2 test p = 0.02). In our prospective (SARS-CoV-2-seronegative) KD series, there was a diminishing male predominance over time, whereas the proportions of incomplete presentations (p < 0.001) and patients with circulatory shock (p = 0.04) increased since the COVID-19 pandemic. Pre- and post-pandemic KD cases presented with different levels of C-reactive protein, thrombocyte counts, and hemoglobin levels over the years. Compared to pandemic KD, SARS-CoV-2-seropositive MIS-C patients were older (p < 0.001), and more often required intensive care admission (p < 0.001), with a gradual decrease over time between 2020 and 2022 (p = 0.04). KD carried a substantial risk of CAA development in contrast to MIS-C. Conclusion: the phenotypic changes seen over the last twelve years of our prospective follow-up study suggest a spectrum of hyperinflammatory states with potentially different triggering events within this clinical entity.
Interleukin-37 Inhibits Interleukin-1β-Induced Articular Chondrocyte Apoptosis by Suppressing Reactive Oxygen Species
Authors: Kim Seong-Kyu , Kim Boyoung , Choe Jung-Yoon , Kim Ji-Won , Park Ki-Yeun
Published: September 2024

Objective: Chondrocyte apoptosis has been considered a crucial mechanism that is responsible for cartilage destruction in osteoarthritis (OA). The mechanism of interleukin-37 (IL-37) on chondrocyte apoptosis has not been clearly determined in the pathogenesis of OA. Here, we explored the role of IL-37 in the regulation of cellular apoptosis in rat chondrocytes stimulated by IL-1β. Methods: Rat chondrocytes were used in in vitro study, and were stimulated with IL-1β (10 ng/mL) and/or recombinant IL-37 (rIL-37; 100 ng/mL) after cytotoxicity assessments using these cytokines were conducted. After rIL-37 treatment of chondrocytes stimulated with IL-1β, the cell proliferation assay, apoptosis assays, including expression of mitochondrial apoptosis-related markers, flow cytometry analysis of annexin V-FITC/propidium iodide (PI), cell cycle analysis, and Hoechst 33342 staining, and reactive oxygen species (ROS) measurement were used. Results: IL-1β induced expression of inflammatory cytokines and triggered degradation of the extracellular matrix of rat chondrocytes, but this effect was significantly attenuated by rIL-37 treatment. Enhanced ROS generation following IL-1β stimulation was reduced in a dose-dependent manner after stimulation with rIL-37. IL-1β induced pro-apoptotic markers and suppressed anti-apoptotic markers in rat chondrocytes. Flow cytometry using annexin V-FITC/PI revealed that IL-1β increased the apoptosis rate of rat chondrocytes, and that this effect was markedly reversed by treatment with rIL-37. Conclusions: IL-37 potently attenuated IL-1β-mediated apoptosis of rat chondrocytes by blocking ROS production. This study suggests that IL-37 can serve as a novel anti-cytokine therapy in OA by blocking chondrocyte apoptosis.
How Multifunctioning Joints Produce Highly Agile Limbs in Animals with Lessons for Robotics
Authors: Burgess Stuart C.
Published: September 2024

This paper reviews how multifunctioning joints produce highly agile limbs in animals with lessons for robotics. One of the key reasons why animals are so fast and agile is that they have multifunctioning joints in their limbs. The multifunctioning joints lead to a high degree of compactness which then leads to a host of benefits such as low mass, low moment of inertia and low drag. This paper presents three case studies of multifunctioning joints—the human wrist joint, knee joint and foot joints—in order to identify how multifunctioning is achieved and what lessons can be learned for robotics. It also reviews the multifunctioning nature of muscle which plays an important role in joint actuation. A key finding is that multifunctioning is achieved through various means: multiple degrees of freedom, multifunctioning parts, over-actuation and reconfiguration. In addition, multifunctioning is achieved through highly sophisticated layouts with high levels of integration and fine-tuning. Muscle also makes an important contribution to animal agility by performing multiple functions including providing shape, protection and heat. The paper reviews progress in achieving multifunctioning in robot joints particularly for the wrist, knee and foot. Whilst there has been some progress in creating multifunctioning robotic joints, there is still a large gap between the performance of animal and robotic joints. There is an opportunity to improve the agility of robots by using multifunctioning to reduce the size and mass of robotic joints.
Mussel-Inspired Multifunctional Polyethylene Glycol Nanoparticle Interfaces
Authors: Casagualda Carolina , López-Moral Alba , Alfonso-Triguero Paula , Lorenzo Julia , Alibés Ramon , Busqué Félix , Ruiz-Molina Daniel
Published: September 2024

Nanoparticles (NPs) are receiving increasing interest in biomedical applications. However, due to their large surface area, in physiological environments, they tend to interact with plasma proteins, inducing their agglomeration and ultimately resulting in a substantial efficiency decrease in diagnostic and therapeutic applications. To overcome such problems, NPs are typically coated with a layer of hydrophilic and biocompatible polymers, such as PEG chains. However, few examples exist in which this property could be systematically fine-tuned and combined with added properties, such as emission. Herein, we report a novel mussel-inspired catechol-based strategy to obtain biocompatible and multifunctional coatings, using a previously developed polymerization methodology based on the formation of disulfide bridges under mild oxidative conditions. Two families of NPs were selected as the proof of concept: mesoporous silica NPs (MSNPs), due to their stability and known applications, and magnetite NPs (Fe3O4 NPs), due to their small size (<10 nm) and magnetic properties. The PEG coating confers biocompatibility on the NPs and can be further functionalized with bioactive molecules, such as glucose units, through the end carboxylic acid moieties. Once we demonstrated the feasibility of our approach to obtaining PEG-based coatings on different families of NPs, we also obtained multifunctional coatings by incorporating fluorescein functionalities. The resulting coatings not only confer biocompatibility and excellent cell internalization, but also allow for the imaging and tracking of NPs within cells.
Movement-Based Prosthesis Control with Angular Trajectory Is Getting Closer to Natural Arm Coordination
Authors: Segas Effie , Leconte Vincent , Doat Emilie , Cattaert Daniel , de Rugy Aymar
Published: September 2024

Traditional myoelectric controls of trans-humeral prostheses fail to provide intuitive coordination of the necessary degrees of freedom. We previously showed that by using artificial neural network predictions to reconstruct distal joints, based on the shoulder posture and movement goals (i.e., position and orientation of the targeted object), participants were able to position and orient an avatar hand to grasp objects with natural arm performances. However, this control involved rapid and unintended prosthesis movements at each modification of the movement goal, impractical for real-life scenarios. Here, we eliminate this abrupt change using novel methods based on an angular trajectory, determined from the speed of stump movement and the gap between the current and the ‘goal’ distal configurations. These new controls are tested offline and online (i.e., involving participants-in-the-loop) and compared to performances obtained with a natural control. Despite a slight increase in movement time, the new controls allowed twelve valid participants and six participants with trans-humeral limb loss to reach objects at various positions and orientations without prior training. Furthermore, no usability or workload degradation was perceived by participants with upper limb disabilities. The good performances achieved highlight the potential acceptability and effectiveness of those controls for our target population.
Preparation of Aluminum-Based Superhydrophobic Surfaces for Fog Collection by Bioinspired Sarracenia Microstructures
Authors: Guo Yunjie , Li Jie , Ma Lisheng , Shi Wentian , Wang Yuke , Fu Shuo , Lu Yanning
Published: September 2024

Freshwater shortage is a growing problem. Inspired by the Sarracenia trichome fog-trapping and ultrafast water-transport structure, a series of hierarchical textured surfaces with high-low ribs with different wettabilities was prepared based on laser processing combined with dip modification. Through fog-collection performance tests, it was found that the samples with superhydrophobicity and low adhesion had the best fog-collection effect. In addition, it was observed that the fog-collection process of different microstructured samples was significantly different, and it was analysed that the fog-collection process was composed of two aspects: directional condensation and directional transport of droplets, which were affected by the low ribs number and rib height ratio. A design parameter was given to create the Sarracenia trichome-like structure to achieve a fast water transport mode. This study provides a good reference for the development and preparation of fog-collection surfaces.
Evaluation of Existing Reinforced Concrete Buildings for Seismic Retrofit through External Stiffening: Limit Displacement Method
Authors: Maidi Moab , Shufrin Igor
Published: September 2024

This study introduces an alternative approach to the assessment of the earthquake resistance of existing buildings and the evaluation of the requirements for seismic retrofit through external stiffening. Instead of assessing individual structural components, we evaluate the entire building using a nonlinear static pushover analysis. Earthquake resistance of the building is defined as a ratio between the total energy that the existing structure can absorb and the energy at its ideal (upgraded) state estimated using the capacity curves obtained from the pushover analysis. The required retrofitting can then be assessed as the stiffness needed to be added to achieve the desired resistance. The study establishes the definition for the ideal capacity of an existing structure, safe displacement limits, and a procedure for deriving the target capacity curves and earthquake-resistance factors. The proposed procedure is applied to a benchmark example, demonstrating that upgrading sub-standard RC structures can be achieved by adding external stiffening members without strengthening individual components. The study also shows that traditional assessment procedures have limited capability to evaluate earthquake resistance in existing buildings with low ductility. The developed procedure provides an essential tool for comparative assessments of retrofitting scenarios and profitability evaluations.