bluuebunny/crossref_metadata_2025 huggingface dataset:
Bone Biomarkers Measured on Salivary Matrix: Study of Biological Variability in a Cohort of Young Subjects
Authors: Brescia Vincenzo , Cazzolla Angela Pia , Fontana Antonietta , Varraso Lucia , Capobianco Carmela , Lovero Roberto , Lo Muzio Lorenzo , Dioguardi Mario , Faienza Maria Felicia , Crincoli Vito , Di Serio Francesca , Ciavarella Domenico
Published: September 2023

Levels of bone turnover markers (BTM) can be measured using saliva. The aim of the present study was to determine the Biological Variability of BTM in young subjects, on serial biological salivary samples. Saliva samples of 20 apparently healthy young subjects (9 females and 11 males) have been analyzed. Samples collected using salivette with cotton swabs were obtained three times every 15 days. PTHrP; TRAcP-5b and P1NP have been assayed. The ANOVA test was used to calculate intra and interindividual variance (CVI and CVG). The individuality index (II) and reference change value (RCV) were evaluated for the clinically significant variation between two results in the same individual. CVI was highest for PTHrP and lowest for P1NP while CVG was highest for TRAcP-5b. RCV was maximum for PTHrP and minimum for P1NP. The critical difference (RCV) is of particular interest in evaluating variations in the concentrations of BMT on the salivary matrix during oral pathologies and/or dental treatments The salivary dosage of BMT during dental treatments could be fundamental to establishing establish the timing of the treatment and, in the case of orthodontic treatments, to evaluate the effectiveness of the applied forces.
An Improved Impact Damage Monitoring Method for High-Speed Trains Using Lamb Waves and Multi-Task Learning
Authors: Yang Jinsong , Gan Zhiqiang , Zhang Xiaozhen , Wang Tiantian , Xie Jingsong
Published: September 2023

High-speed trains may be subjected to various forms of physical impacts during long-term operation, causing structural damage and endangering driving safety. Therefore, impact damage monitoring remains a daunting challenge for the stable operation of high-speed train structures. The existing methods cannot simultaneously detect the location and severity of impact damage, which poses challenges to structural integrity assessment and preventive maintenance. This article proposes an impact damage monitoring method based on multi-task 2D-CNN. Sensor data fusion is performed using a 2D image processing method to convert a 1D impact damage signal into a 2D grayscale image. The fused grayscale image contains information related to the location and severity of impact damage. A damage detection framework was established using multi-task 2D-CNN for feature extraction, impact location classification, and impact energy quantification. This model can learn the commonalities and characteristics of each task by sharing network structure and parameters and can effectively improve the accuracy of each task. Compared with single-task learning, multi-task learning performs better on the metrics of the impact location task recognizing the impact energy task and reduces the training time by 30.83%. With a reduced number of samples, the performance of multi-task learning is more stable and can still effectively identify the location and severity of impact damage.
Deformation Characteristics of Mechanical Seal Face under Alternating Loads
Authors: Zhao Wenjing , Zheng Simin , Teng Liming , Jiang Jinbo , Wang Mengjiao , Peng Xudong
Published: September 2023

Taking the mechanical seal of the submersible as the object, a transient coupled heat transfer model was established, and the deformation of the seal face under stable and alternating conditions was investigated by considering the thermal–mechanical coupling effect. The deformation characteristics of the seal face under two different alternative forms of amplitude and period were analyzed. The morphology and wear characteristics of the seal face were measured and discussed based on the pseudo-real test of the mechanical seal under alternating loads. The results showed that the seal face tended to be squeezed near the inner diameter and a tapered convergent gap appeared at the outer diameter of the seal face under alternating loads. The deformation of the seal face presented obvious alternating transient characteristics under alternating loads, and the deformation under alternating rotational speed was greater than that of alternating medium pressure. The deformation of the seal face increased with the amplitude of the alternating loads, while the period of the alternating loads had little influence on it. The wear mechanism of the seal face under alternating conditions was mainly abrasive wear, and the wear caused by alternating rotational speed is more significant.
A Systematic Review on Earthworms in Soil Bioremediation
Authors: Tagliabue Francesca , Marini Enrica , De Bernardi Arianna , Vischetti Costantino , Casucci Cristiano
Published: September 2023

Bioremediation techniques are increasingly popular in addressing soil pollution. Despite this, using earthworms as first actors or adjuvants in decontamination is an open and little-discussed field. This paper focuses on vermiremediation effectiveness alone or combined with other bioremediation methods, such as phytoremediation and bioaugmentation. Literature was collected following the PRISMA criteria, setting the search with the following keywords: “(vermiremediation) AND (bioremediation OR phytoremediation OR plant*) AND (bioaugmentation OR bacteria)”. The investigation was performed on Google Scholar, Science Direct, SciFinder and Web of Science databases. The article data were collected, compared, elaborated, graphically summarised and discussed to assess if the earthworms’ activities play a critical role in tackling several soil pollutions. Furthermore, the review aimed to identify the most promising techniques in the function of the xenobiotic examined: organic, inorganic or both. Any gaps and criticism were highlighted to facilitate future research in this study area.
Set-Based Group Search Optimizer for Stochastic Many-Objective Optimal Power Flow
Authors: Zheng Jiehui , Tao Mingming , Li Zhigang , Wu Qinghua
Published: September 2023

The conventional optimal power flow (OPF) is confronted with challenges in tackling more than three objectives and the stochastic characteristics due to the uncertainty and intermittence of the RESs. However, there are few methods available that simultaneously address high-dimensional objective optimization and uncertainty handling. This paper proposes a set-based group search optimizer (SetGSO) to tackle the stochastic many-objective optimal power flow (MaOPF) of power systems penetrated with renewable energy sources. The proposed SetGSO depicts the original stochastic variables by set-based individuals under the evolutionary strategy of the basic GSO, without using repeated sampling or probabilistic information. Consequently, two metrics, hyper-volume and average imprecision, are introduced to transform the stochastic MaOPF into a deterministic bi-objective OPF, guaranteeing a much superior Pareto-optimal front. Finally, our method was evaluated on three modified bus systems containing renewable energy sources, and compared with the basic GSO using Monte Carlo sampling (GSO-MC) and a set-based genetic algorithm (SetGA) in solving the stochastic MaOPF. The numerical results demonstrate a saving of 90% of the computation time in the proposed SetGSO method compared to sampling-based approaches and it achieves improvements in both the hyper-volume and average imprecision indicators, with a maximum enhancement of approximately 30% and 7% compared to SetGA.
Stress Responses of Examiners during Ophthalmic Examination Practices in Healthy Young Students
Authors: Toda Haruo , Ubukata Hokuto , Kinoshita Naohiko , Abe Takuya , Morita Kunie
Published: September 2023

The stress reaction of trainees is an issue in the practices of medical-related examinations that involve real-time decision making based on the examiner–subject interactions. The Goldmann perimetry (GP) test is one of these examinations. To evaluate the students’ stress reactions in the practice of the GP test, the stress-related substances and heart rate variability were measured in forty students enrolled in the practice. While there was no significant increase in stress-related substances during the practice, significantly increased sympathetic activities were observed at the beginning of the tests. Moreover, the plasma cortisol measured before the tests showed a significant positive correlation to the students’ self-confidence scores, indicating the students, especially those with higher self-confidence scores, were anxious for upcoming tests with unfamiliar subjects. Once the tests began, they felt relieved in the procedures they had learned repeatedly. On the other hand, while the average plasma ACTH decreased significantly during the test, the ACTH secretion correlated positively to the test duration, indicating that the skillful participants had less stress during the test. In the medical-related practices, pre-training on how to deal with unfamiliar subjects may be helpful for reducing the stress of the trainees, in addition to the procedure itself.
Physics-Based Swab and Surge Simulations and the Machine Learning Modeling of Field Telemetry Swab Datasets
Authors: Mohammad Amir , Belayneh Mesfin , Davidrajuh Reggie
Published: September 2023

Drilling operations are the major cost factor for the oil industry. Appropriately designed operations are essential for successful drilling. Optimized drilling operations also enhance drilling performance and reduce drilling costs. This is achieved by increasing the bit life (minimizing premature bit wear), drilling more quickly, which reduces drilling time, and also reducing tripping operations. This paper is presented in two parts. The first part compares the parametric physics-based swab and surge simulation results obtained from the Bingham plastic, power law, and Robertson–Stiff models. The aim is to show how the model’s predictions deviate from each other. Two 80:20 oil/water ratio (OWR) oil-based drilling fluids and two 90:10 OWR oil-based drilling fluids, 1.96 sg and 2.0 sg, were considered in vertical and deviated wells. Analysis of the simulation results revealed that the deviations depend on the drilling fluid’s physical and rheological parameters as well as the well trajectory. Moreover, the model’s predictions were inconsistent. Data-driven machine learning (ML) modeling is the focus of the second section. Data-driven modeling was performed using both software-generated datasets and field datasets. The results show that the random forest regressor (RF), artificial neural network (ANN), long short-term memory (LSTM), LightGBM, XGBoost, and multivariate regression models predicted the training and test datasets with higher R-squared and minimum mean square error values. Deploying the ML model in real-time applications and the planning phase would lead to potential applications of artificial intelligence for well planning and optimization processes.
Enhancing Railway Network Safety by Reproducing Wheel–Rail Electrical Contact on a Laboratory Scale
Authors: Haydar Luna , Loete Florent , Houzé Frédéric , Choupin Tanguy , Guiche Fabien , Testé Philippe
Published: September 2023

Ensuring the safety of rail networks requires precise detection of a train’s position on a track section. This is achieved using a “track circuit” system, in which the wheel–rail electrical contact is the key to maintaining the system’s reliability. However, any degradation of this contact can lead to a track circuit malfunction known as “deshunting”, creating a serious safety risk for the rail network and for passengers. This paper presents a refined approach to this concern by implementing a laboratory-scale test bench. The main objective is to reproduce the wheel–rail electrical contact under controlled conditions to better understand the various aspects of this contact. The criteria governing the dimensioning of the test bench at reduced scale are based primarily on mechanical considerations. In this study, a series of tests were carried out to investigate the behavior of the electrical resistance as a function of various parameters such as load, current and time. An original homemade salt spray system was designed and used for obtaining controlled rail oxidation. Our preliminary results highlight the impact of these factors on the electrical resistance, providing valuable insights for future advances in rail safety technology.
A Systematic Review of Computer Vision and AI in Parking Space Allocation in a Seaport
Authors: Lee Hoon , Chatterjee Indranath , Cho Gyusung
Published: September 2023

Urban expansion has ushered in a landscape of opportunities and challenges across housing, transportation, education, health, and the economy. In response to these evolving dynamics, the application of artificial intelligence (AI) and computer vision (CV) technologies has emerged as a transformative solution. While smart traffic monitoring and advanced parking distribution systems have eased urban pressures, optimizing mobility remains pivotal in the context of burgeoning smart cities. However, the seaport industry grapples with formidable issues in the efficient transport of containers. In light of this, the fusion of AI and CV technology holds promise as a solution. This study pioneers a systematic review, representing a novel exploration, delving into a comprehensive evaluation of the existing literature. It scrutinizes the profound advantages AI and CV offer in constructing sustainable, efficient parking ecosystems within seaports. Our methodological approach encompasses data collection, rigorous quality assessment, and meticulous exploration of the application of CV and AI in the realm of smart parking management. The findings underscore the pivotal role of AI and CV technologies in the development of efficient, sustainable transportation systems, particularly for optimizing container movement within seaports. This research presents a comprehensive analysis of the literature in the area of the application of AI and CV technologies in optimizing parking management at seaports, shedding light on the potential for sustainable transportation solutions in this critical domain. As these technologies usher in enhancements in traffic management, parking space allocation, and container logistics within seaports, this study represents a vital and timely contribution to the field, serving as a cornerstone for future innovations in seaport management and the broader context of smart cities.
AI Fairness in Data Management and Analytics: A Review on Challenges, Methodologies and Applications
Authors: Chen Pu , Wu Linna , Wang Lei
Published: September 2023

This article provides a comprehensive overview of the fairness issues in artificial intelligence (AI) systems, delving into its background, definition, and development process. The article explores the fairness problem in AI through practical applications and current advances and focuses on bias analysis and fairness training as key research directions. The paper explains in detail the concept, implementation, characteristics, and use cases of each method. The paper explores strategies to reduce bias and improve fairness in AI systems, reviews challenges and solutions to real-world AI fairness applications, and proposes future research directions. In addition, this study provides an in-depth comparative analysis of the various approaches, utilizing cutting-edge research information to elucidate their different characteristics, strengths, and weaknesses. The results of the comparison provide guidance for future research. The paper concludes with an overview of existing challenges in practical applications and suggests priorities and solutions for future research. The conclusions provide insights for promoting fairness in AI systems. The information reviewed in this paper is drawn from reputable sources, including leading academic journals, prominent conference proceedings, and well-established online repositories dedicated to AI fairness. However, it is important to recognize that research nuances, sample sizes, and contextual factors may create limitations that affect the generalizability of the findings.
Knowledge Repatriation: A Pilot Project about Making Cedar Root Baskets
Authors: Fortney Sharon M.
Published: September 2023

This paper describes the first phase of a Coast Salish Knowledge Repatriation Project being coordinated by the Curator of Indigenous Collections and Engagement at the Museum of Vancouver, within the unceded, ancestral territories of the xʷməθkʷəýəm (Musqueam), Sḵwx̱wú7mesh (Squamish), and səlilwətaɬ (Tsleil-Waututh) nations. The goal of this knowledge repatriation work is to support cultural revitalization and language renewal through activities that generate learning opportunities for community members. These activities pivot around knowledge that has been lost due to urbanization, forced assimilation efforts, and other colonial activities that may have restricted access to traditional lands and resources, preventing knowledge transmission. This work is about shifting the focus from extractive projects, that benefit external audiences, to one that supports capacity building and cultural renewal within communities. This essay describes a project to reintroduce coiled cedar root basketry into communities within the Greater Vancouver area in the province of British Columbia, Canada.
Experimental Campaign of Massive CO2 Atmospheric Releases in an Urban Area
Authors: Joubert Lauris , Leroy Guillaume , Claude Théo , Riahi Omar
Published: September 2023

Over recent decades, several campaigns have been carried out to collect data regarding the release and atmospheric dispersion of dense chemical products in an open field. All these experimental data are valuable information to challenge the predictions of numerical tools (Gaussian, integral-type, and CFD) and, if needed, to improve the code itself and the way we are using it. On the other hand, little attention has been paid to atmospheric dispersion releases with massive flow rates in a complex urban environment. To fill this gap, Ineris carried out an experimental campaign intended to study the atmospheric dispersion of massive CO2 releases on the CENZUB site (an action training center in an urban area located in Sissonne, France). Three CO2 releases were performed with mass flow rates of about 7 kg/s in three different configurations: one axial street release and two impacting releases (against a small and high-rise building). Several technologies of CO2 sensors were used to ensure better measurement accuracy. The main experimental campaign features and preliminary data analysis are presented. The results demonstrated the influence of the built environment on dispersion patterns.
Thrombin Generation Thresholds for Coagulation Initiation under Flow
Authors: Bouchnita Anass , Yadav Kanishk , Llored Jean-Pierre , Gurovich Alvaro , Volpert Vitaly
Published: September 2023

In veins, clotting initiation displays a threshold response to flow intensity and injury size. Mathematical models can provide insights into the conditions leading to clot growth initiation under flow for specific subjects. However, it is hard to determine the thrombin generation curves that favor coagulation initiation in a fast manner, especially when considering a wide range of conditions related to flow and injury size. In this work, we propose to address this challenge by using a neural network model trained with the numerical simulations of a validated 2D model for clot formation. Our surrogate model approximates the results of the 2D simulations, reaching an accuracy of 94% on the test dataset. We used the trained artificial neural network to determine the threshold for thrombin generation parameters that alter the coagulation initiation response under varying flow speed and injury size conditions. Our model predictions show that increased levels of the endogenous thrombin potential (ETP) and peak thrombin concentration increase the likelihood of coagulation initiation, while an elevated time to peak decreases coagulation. The lag time has a small effect on coagulation initiation, especially when the injury size is small. Our surrogate model can be considered as a proof-of-concept of a tool that can be deployed to estimate the risk of bleeding in specific patients based on their Thrombin Generation Assay results.
Multi-Step Prediction of Typhoon Tracks Combining Reanalysis Image Fusion Using Laplacian Pyramid and Discrete Wavelet Transform with ConvLSTM
Authors: Lu Peng , Xu Mingyu , Chen Ming , Wang Zhenhua , Zheng Zongsheng , Yin Yixuan
Published: September 2023

Typhoons often cause huge losses, so it is significant to accurately predict typhoon tracks. Nowadays, researchers predict typhoon tracks with the single step, while the correlation of adjacent moments data is small in long-term prediction, due to the large step of time. Moreover, recursive multi-step prediction results in the accumulated error. Therefore, this paper proposes to fuse reanalysis images at the similarly historical moment and predicted images through Laplacian Pyramid and Discrete Wavelet Transform to reduce the accumulated error. That moment is determined according to the difference in the moving angle at predicted and historical moments, the color histogram similarity between predicted images and reanalysis images at historical moments and so on. Moreover, reanalysis images are weighted cascaded and input to ConvLSTM on the basis of the correlation between reanalysis data and the moving angle and distance of the typhoon. And, the Spatial Attention and weighted calculation of memory cells are added to improve the performance of ConvLSTM. This paper predicted typhoon tracks in 12 h, 18 h, 24 h and 48 h with recursive multi-step prediction. Their MAEs were 102.14 km, 168.17 km, 243.73 km and 574.62 km, respectively, which were reduced by 1.65 km, 5.93 km, 4.6 km and 13.09 km, respectively, compared with the predicted results of the improved ConvLSTM in this paper, which proved the validity of the model.
The Performance of a Deep Learning-Based Automatic Measurement Model for Measuring the Cardiothoracic Ratio on Chest Radiographs
Authors: Kim Donguk , Lee Jong Hyuk , Jang Myoung-jin , Park Jongsoo , Hong Wonju , Lee Chan Su , Yang Si Yeong , Park Chang Min
Published: September 2023

Objective: Prior studies on models based on deep learning (DL) and measuring the cardiothoracic ratio (CTR) on chest radiographs have lacked rigorous agreement analyses with radiologists or reader tests. We validated the performance of a commercially available DL-based CTR measurement model with various thoracic pathologies, and performed agreement analyses with thoracic radiologists and reader tests using a probabilistic-based reference. Materials and Methods: This study included 160 posteroanterior view chest radiographs (no lung or pleural abnormalities, pneumothorax, pleural effusion, consolidation, and n = 40 in each category) to externally test a DL-based CTR measurement model. To assess the agreement between the model and experts, intraclass or interclass correlation coefficients (ICCs) were compared between the model and two thoracic radiologists. In the reader tests with a probabilistic-based reference standard (Dawid–Skene consensus), we compared diagnostic measures—including sensitivity and negative predictive value (NPV)—for cardiomegaly between the model and five other radiologists using the non-inferiority test. Results: For the 160 chest radiographs, the model measured a median CTR of 0.521 (interquartile range, 0.446–0.59) and a mean CTR of 0.522 ± 0.095. The ICC between the two thoracic radiologists and between the model and two thoracic radiologists was not significantly different (0.972 versus 0.959, p = 0.192), even across various pathologies (all p-values > 0.05). The model showed non-inferior diagnostic performance, including sensitivity (96.3% versus 97.8%) and NPV (95.6% versus 97.4%) (p < 0.001 in both), compared with the radiologists for all 160 chest radiographs. However, it showed inferior sensitivity in chest radiographs with consolidation (95.5% versus 99.9%; p = 0.082) and NPV in chest radiographs with pleural effusion (92.9% versus 94.6%; p = 0.079) and consolidation (94.1% versus 98.7%; p = 0.173). Conclusion: While the sensitivity and NPV of this model for diagnosing cardiomegaly in chest radiographs with consolidation or pleural effusion were not as high as those of the radiologists, it demonstrated good agreement with the thoracic radiologists in measuring the CTR across various pathologies.
Machine Learning for Medical Image Translation: A Systematic Review
Authors: McNaughton Jake , Fernandez Justin , Holdsworth Samantha , Chong Benjamin , Shim Vickie , Wang Alan
Published: September 2023

Background: CT scans are often the first and only form of brain imaging that is performed to inform treatment plans for neurological patients due to its time- and cost-effective nature. However, MR images give a more detailed picture of tissue structure and characteristics and are more likely to pick up abnormalities and lesions. The purpose of this paper is to review studies which use deep learning methods to generate synthetic medical images of modalities such as MRI and CT. Methods: A literature search was performed in March 2023, and relevant articles were selected and analyzed. The year of publication, dataset size, input modality, synthesized modality, deep learning architecture, motivations, and evaluation methods were analyzed. Results: A total of 103 studies were included in this review, all of which were published since 2017. Of these, 74% of studies investigated MRI to CT synthesis, and the remaining studies investigated CT to MRI, Cross MRI, PET to CT, and MRI to PET. Additionally, 58% of studies were motivated by synthesizing CT scans from MRI to perform MRI-only radiation therapy. Other motivations included synthesizing scans to aid diagnosis and completing datasets by synthesizing missing scans. Conclusions: Considerably more research has been carried out on MRI to CT synthesis, despite CT to MRI synthesis yielding specific benefits. A limitation on medical image synthesis is that medical datasets, especially paired datasets of different modalities, are lacking in size and availability; it is therefore recommended that a global consortium be developed to obtain and make available more datasets for use. Finally, it is recommended that work be carried out to establish all uses of the synthesis of medical scans in clinical practice and discover which evaluation methods are suitable for assessing the synthesized images for these needs.
Multi-Parameter Auto-Tuning Algorithm for Mass Spectrometer Based on Improved Particle Swarm Optimization
Authors: Jia Mingzheng , Li Liang , Xiong Baolin , Feng Le , Cheng Wenbo , Dong Wen-Fei
Published: September 2023

Quadrupole mass spectrometers (QMS) are widely used for clinical diagnosis and chemical analysis. To obtain the best experimental results, mass spectrometers must be calibrated to an ideal setting before use. However, tuning the current QMS is challenging. Traditional tuning techniques possess low automation levels and rely primarily on skilled engineers. Therefore, in this study, we propose an innovative auto-tuning algorithm for QMS based on the improved particle swarm optimization (PSO) algorithm to automatically find the optimal solution of QMS parameters and make the QMS reach the optimal state. The improved PSO algorithm is combined with simulated annealing, multiple inertia weights, dynamic boundaries, and other methods to prevent the traditional PSO algorithm from the issue of a local optimal solution and premature convergence. According to the characteristics of the mass spectrum peaks, a termination function is proposed to simplify the termination conditions of the PSO algorithm and further improve the automation level of the mass spectrometer. The results of auto-calibration testing of resolution and mass axis show that both resolution and mass axis calibration could effectively meet the requirements of mass spectrometry experiments. By the experiment of auto-optimization testing of lens and ion source parameters, these parameters were all in the vicinity of the optimal solution, which achieved the expected performance. Through numerous experiments, the reproducibility of the algorithm was established as meeting the auto-tuning function of the QMS. The proposed method can automatically tune the mass spectrometer from its non-optimal condition to the optimal one, which can effectively reduce the tuning difficulty of QMS.
Analysis of High-Risk Neuroblastoma Transcriptome Reveals Gene Co-Expression Signatures and Functional Features
Authors: Martínez-Pacheco Mónica Leticia , Hernández-Lemus Enrique , Mejía Carmen
Published: September 2023

Neuroblastoma represents a neoplastic expansion of neural crest cells in the developing sympathetic nervous system and is childhood’s most common extracranial solid tumor. The heterogeneity of gene expression in different types of cancer is well-documented, and genetic features of neuroblastoma have been described by classification, development stage, malignancy, and progression of tumors. Here, we aim to analyze RNA sequencing datasets, publicly available in the GDC data portal, of neuroblastoma tumor samples from various patients and compare them with normal adrenal gland tissue from the GTEx data portal to elucidate the gene expression profile and regulation networks they share. Our results from the differential expression, weighted correlation network, and functional enrichment analyses that we performed with the count data from neuroblastoma and standard normal gland samples indicate that the analysis of transcriptome data from 58 patients diagnosed with high-risk neuroblastoma shares the expression pattern of 104 genes. More importantly, our analyses identify the co-expression relationship and the role of these genes in multiple biological processes and signaling pathways strongly associated with this disease phenotype. Our approach proposes a group of genes and their biological functions to be further investigated as essential molecules and possible therapeutic targets of neuroblastoma regardless of the etiology of individual tumors.
Modulation of the Cellular microRNA Landscape: Contribution to the Protective Effects of High-Density Lipoproteins (HDL)
Authors: Graham Annette
Published: September 2023

High-density lipoproteins (HDL) play an established role in protecting against cellular dysfunction in a variety of different disease contexts; however, harnessing this therapeutic potential has proved challenging due to the heterogeneous and relative instability of this lipoprotein and its variable cargo molecules. The purpose of this study is to examine the contribution of microRNA (miRNA; miR) sequences, either delivered directly or modulated endogenously, to these protective functions. This narrative review introduces the complex cargo carried by HDL, the protective functions associated with this lipoprotein, and the factors governing biogenesis, export and the uptake of microRNA. The possible mechanisms by which HDL can modulate the cellular miRNA landscape are considered, and the impact of key sequences modified by HDL is explored in diseases such as inflammation and immunity, wound healing, angiogenesis, dyslipidaemia, atherosclerosis and coronary heart disease, potentially offering new routes for therapeutic intervention.
Head-to-Head Comparison of Tissue Factor-Dependent Procoagulant Potential of Small and Large Extracellular Vesicles in Healthy Subjects and in Patients with SARS-CoV-2 Infection
Authors: Brambilla Marta , Frigerio Roberto , Becchetti Alessia , Gori Alessandro , Cretich Marina , Conti Maria , Mazza Antonella , Pengo Martino , Camera Marina
Published: September 2023

The relative contribution of small (sEVs) and large extracellular vesicles (lEVs) to the total plasma procoagulant potential is not yet well defined. Thus, we compared total and TFpos-sEVs and -lEVs isolated from healthy subjects and COVID-19 patients during the acute phase of the infection and after symptom remission in terms of (1) vesicle enumeration using nanoparticle tracking assay, imaging flow cytometry, and TF immunofluorescence localization in a single-vesicle analysis using microarrays; (2) cellular origin; and (3) TF-dependent Xa generation capacity, as well as assessing the contribution of the TF inhibitor, TFPI. In healthy subjects, the plasma concentration of CD9/CD63/CD81pos sEVs was 30 times greater than that of calceinpos lEVs, and both were mainly released by platelets. Compared to lEVs, the levels of TFpos-sEVs were 2-fold higher. The TF-dependent Xa generation capacity of lEVs was three times greater than that of sEVs, with the latter being hindered by TFPI. Compared to HSs, the amounts of total and TFpos-sEVs and -lEVs were significantly greater in acute COVID-19 patients, which reverted to the physiological values at the 6-month follow-up. Interestingly, the FXa generation of lEVs only significantly increased during acute infection, with that of sEV being similar to that of HSs. Thus, in both healthy subjects and COVID-19 patients, the TF-dependent procoagulant potential is mostly sustained by large vesicles.
Comprehensive Genome and Transcriptome Analysis Identifies SLCO3A1 Associated with Aggressive Behavior in Pigs
Authors: Zhang Chunlei , Yang Huan , Xu Qinglei , Liu Mingzheng , Chao Xiaohuan , Chen Jiahao , Zhou Bo , Liu Yang
Published: September 2023

Copy number variation (CNV) represents a significant reservoir of genetic diversity within the genome and exhibits a strong association with economically valuable traits in livestock. The manifestation of aggressive behavior in pigs has detrimental effects on production efficiency, immune competency, and meat quality. Nevertheless, the impact of CNV on the aggressive behavior of pigs remains elusive. In this investigation, we employed an integrated analysis of genome and transcriptome data to investigate the interplay between CNV, gene expression changes, and indicators of aggressive behavior in weaned pigs. Specifically, a subset of pigs comprising the most aggressive pigs (MAP, n = 12) and the least aggressive pigs (LAP, n = 11) was purposefully selected from a herd of 500 weaned pigs following a mixing procedure based on their composite aggressive score (CAS). Subsequently, we thoroughly analyzed copy number variation regions (CNVRs) across the entire genome using next-generation sequencing techniques, ultimately revealing the presence of 6869 CNVRs. Using genome-wide association study (GWAS) analysis and evaluating variance-stabilizing transformation (VST) values, we successfully identified distinct CNVRs that distinguished the MAP and LAP counterparts. Among the prioritized CNVRs, CNVR-4962 (designated as the top-ranked p-value and VST value, No. 1) was located within the Solute Carrier Organic Anion Transporter Family Member 3A1 (SLCO3A1) gene. The results of our analyses indicated a significantly higher (p < 0.05) copy number of SLCO3A1 in the MAP compared to the LAP. Furthermore, this increased copy number exhibited a positive correlation with the CAS of the pigs (p < 0.05). Furthermore, we integrated genomic data with transcriptomic data from the temporal lobe to facilitate the examination of expression quantitative trait loci (eQTL). Importantly, these observations were consistent with the mRNA expression pattern of SLCO3A1 in the temporal lobe of both MAP and LAP (p < 0.05). Consequently, our findings strongly suggest that CNVs affecting SLCO3A1 may influence gene expression through a dosage effect. These results highlight the potential of SLCO3A1 as a candidate gene associated with aggressive traits in pig breeding programs.
Epigenetic Regulation of Fibroblasts and Crosstalk between Cardiomyocytes and Non-Myocyte Cells in Cardiac Fibrosis
Authors: Chu Liangyu , Xie Daihan , Xu Dachun
Published: September 2023

Epigenetic mechanisms and cell crosstalk have been shown to play important roles in the initiation and progression of cardiac fibrosis. This review article aims to provide a thorough overview of the epigenetic mechanisms involved in fibroblast regulation. During fibrosis, fibroblast epigenetic regulation encompasses a multitude of mechanisms, including DNA methylation, histone acetylation and methylation, and chromatin remodeling. These mechanisms regulate the phenotype of fibroblasts and the extracellular matrix composition by modulating gene expression, thereby orchestrating the progression of cardiac fibrosis. Moreover, cardiac fibrosis disrupts normal cardiac function by imposing myocardial mechanical stress and compromising cardiac electrical conduction. This review article also delves into the intricate crosstalk between cardiomyocytes and non-cardiomyocytes in the heart. A comprehensive understanding of the mechanisms governing epigenetic regulation and cell crosstalk in cardiac fibrosis is critical for the development of effective therapeutic strategies. Further research is warranted to unravel the precise molecular mechanisms underpinning these processes and to identify potential therapeutic targets.
Exploring the Link between Plasma Levels of PCSK9, Immune Dysregulation and Atherosclerosis in Patients with Primary Sjögren’s Syndrome
Authors: Bianconi Vanessa , Cafaro Giacomo , Mannarino Massimo Raffaele , Perricone Carlo , Cosentini Elena , Bistoni Onelia , Paltriccia Rita , Lombardini Rita , Gerli Roberto , Pirro Matteo , Bartoloni Elena
Published: September 2023

Proprotein convertase subtilisin/kexin type 9 (PCSK9) regulates lipid metabolism contributing to cardiovascular (CV) risk in the general population. The relationship between PCSK9 and CV risk in systemic autoimmune diseases has been poorly explored. We investigated the association between plasma PCSK9, measures of immune–inflammatory status and markers of atherosclerosis in 52 consecutive patients with primary Sjögren’s syndrome (pSS) in comparison to healthy controls (HCs). Median plasma PCSK9 levels were significantly higher in pSS patients versus HCs (162 (79–255) vs. 53 (39–99) ng/mL). Significantly higher prevalence of subclinical atherosclerosis and lower of dyslipidaemia (61% vs. 85%, p = 0.042) characterized pSS patients versus HCs. In pSS, no significant correlation emerged between PCSK9 and disease activity, atherosclerosis and lipid levels. In HCs, PCSK9 significantly correlated with lipid levels and atherosclerosis. Interestingly, significantly higher PCSK9 levels were found in HCs with high-to-very-high as compared to low-to-moderate CV risk (p = 0.018) while a non-significant trend towards higher PCSK9 levels was detected in pSS patients with low-to-moderate as compared to high-to-very-high CV risk (p = 0.060). This is the first demonstration that pSS patients, despite lower prevalence of dyslipidaemia and higher CV risk profile, are characterized by a 3-fold increase in PCSK9 levels in comparison to HCs. As PCSK9 does not correlate with measures of CV risk, its role in CV morbidity in pSS needs further investigation.
ROS-Mediated Fragmentation Alters the Effects of Hyaluronan on Corneal Epithelial Wound Healing
Authors: Lin Xiao , Moreno Isabel Y. , Nguyen Lawrence , Gesteira Tarsis F. , Coulson-Thomas Vivien J.
Published: September 2023

A buildup of reactive oxygen species (ROS) occurs in virtually all pathological conditions. Hyaluronan (HA) is a major extracellular matrix component and is susceptible to oxidation by reactive oxygen species (ROS), yet the precise chemical structures of oxidized HA products (oxHA) and their physiological properties remain largely unknown. This study characterized the molecular weight (MW), structures, and physiological properties of oxHA. For this, high-molecular-weight HA (HMWHA) was oxidized using increasing molar ratios of hydrogen peroxide (H2O2) or hypochlorous acid (HOCl). ROS lead to the fragmentation of HA, with the oxHA products produced by HOCl exhibiting an altered chemical structure while those produced by H2O2 do not. HMWHA promotes the viability of human corneal epithelial cells (hTCEpi), while low MWHA (LMWHA), ultra-LMWHA (ULMWHA), and most forms of oxHA do not. HMWHA and LMWHA promote hTCEpi proliferation, while ULMWHA and all forms of oxHA do not. LMWHA and some forms of oxHA promote hTCEpi migration, while HMWHA does not. Finally, all native forms of HA and oxHA produced by HOCl promote in vivo corneal wound healing, while oxHA produced by H2O2 does not. Taken together, our results show that HA fragmentation by ROS can alter the physiological activity of HA by altering its MW and structure.
Inhaled Exosomes Genetically Manipulated to Overexpress CD24 (EXO-CD24) as a Compassionate Use in Severe ARDS Patients
Authors: Green Orr , Shenberg Gil , Baruch Roni , Argaman Lihi , Levin Talya , Michelson Ian , Hadary Ruthy , Isakovich Boris , Golos Miri , Schwartz Reut , MacLoughlin Ronan , Adi Nimrod , Arber Nadir , Shapira Shiran
Published: September 2023

Rationale: Acute respiratory distress syndrome (ARDS) is a major global health concern with a significant unmet need. EXO-CD24 is delivered via inhalation-reduced cytokines and chemokine secretion and lung injury in ARDS and improved survival in mice models of ARDS, influenza, and sepsis. Objectives: This clinical paper aims to evaluate the potential of EXO-CD24, a novel immunomodulatory treatment, in the compassionate care of critically ill, intubated patients with post-infection-induced acute respiratory distress syndrome (ARDS). Methods: Eleven critically ill patients diagnosed with post-infection ARDS (10 with COVID-19 and one with an adenovirus-associated infection) were administered EXO-CD24 in four medical centers across Israel. The patients had multiple co-morbidities, including cancer, hypertension, diabetes, and ischemic heart disease, and met the criteria for severe ARDS according to the Berlin classification. EXO-CD24 was administered via inhalation, and adverse events related to its use were carefully monitored. Measurements and Main Results: The administration of EXO-CD24 did not result in any recorded adverse events. The median hospitalization duration was 11.5 days, and the overall mortality rate was 36%. Notably, patients treated at the Tel Aviv Medical Center (TASMC) showed a lower mortality rate of 12.5%. The WBC and CRP levels decreased in comparison to baseline levels at hospitalization, and rapid responses occurred even in patients with kidney transplants who were off the ventilator within a few days and discharged shortly thereafter. The production of cytokines and chemokines was significantly suppressed in all patients, including those who died. Among the patients at TASMC, four had kidney transplants and were on immunosuppressive drugs, and all of them fully recovered and were discharged from the hospital. Conclusions: EXO-CD24 holds promise as a potential therapeutic agent for all stages of ARDS, even in severe intubated cases. Importantly, EXO-CD24 demonstrated a favorable safety profile without any apparent side effects with promising efficacy. Furthermore, the potential of EXO-CD24 as a platform for addressing hyper-inflammatory states warrants exploration. Further research and larger-scale clinical trials are warranted to validate these preliminary findings.
Enantioselective Biomimetic Structures Inspired by Oxi-Dase-Type Metalloenzymes, Utilizing Polynuclear Compounds Containing Copper (II) and Manganese (II) Ions as Building Blocks
Authors: Gómez Didier , Acosta Jorge , López-Sandoval Horacio , Torres-Palma Ricardo A. , Ávila-Torres Yenny
Published: September 2023

This study focuses on developing and evaluating two novel enantioselective biomimetic models for the active centers of oxidases (ascorbate oxidase and catalase). These models aim to serve as alternatives to enzymes, which often have limited action and a delicate nature. For the ascorbate oxidase (AO) model (compound 1), two enantiomers, S,S(+)cpse and R,R(−)cpse, were combined in a crystalline structure, resulting in a racemic compound. The analysis of their magnetic properties and electrochemical behavior revealed electronic transfer between six metal centers. Compound 1 effectively catalyzed the oxidation of ascorbic to dehydroascorbic acid, showing a 45.5% yield for the racemic form. This was notably higher than the enantiopure compounds synthesized previously and tested in the current report, which exhibited yields of 32% and 28% for the S,S(+)cpse and R,R(-)cpse enantiomers, respectively. This outcome highlights the influence of electronic interactions between metal ions in the racemic compound compared to pure enantiomers. On the other hand, for the catalase model (compound 2), both the compound and its enantiomer displayed polymeric properties and dimeric behavior in the solid and solution states, respectively. Compound 2 proved to be effective in catalyzing the oxidation of hydrogen peroxide to oxygen with a yield of 64.7%. In contrast, its enantiomer (with R,R(-)cpse) achieved only a 27% yield. This further validates the functional nature of the prepared biomimetic models for oxidases. This research underscores the importance of understanding and designing biomimetic models of metalloenzyme active centers for both biological and industrial applications. These models show promising potential as viable alternatives to natural enzymes in various processes.
Treadmill Training Plus Semi-Immersive Virtual Reality in Parkinson’s Disease: Results from a Pilot Study
Authors: Pullia Massimo , Ciatto Laura , Andronaco Giuseppe , Donato Concetta , Aliotta Rosario Ermes , Quartarone Angelo , De Cola Maria Cristina , Bonanno Mirjam , Calabrò Rocco Salvatore , Cellini Roberta
Published: September 2023

Parkinson’s disease (PD) is one of the most common neurodegenerative disorders that causes postural instability and gait alterations, such as reduced walking speed, shorter step length, and gait asymmetry, exposing patients to a higher risk of falling. Recently, virtual reality (VR) was added to a treadmill, in order to promote motor functional recovery and neuroplastic processes. Twenty PD patients were enrolled and randomly assigned to two groups: the experimental group (EG) and the control group (CG). In particular, patients in the EG were trained with the C-Mill, an innovative type of treadmill, which is equipped with semi-immersive VR, whereas the CG performed conventional physiotherapy. Patients in both groups were evaluated through a specific motor assessment battery at baseline (T0) and after the training (T1). Comparing pre-(T0) and post-(T1) treatment scores, in the EG, we found statistical significances in the following outcome measures: 6 Minutes Walking Test (6MWT) (p < 0.0005), Timed up and go (TUG right) (p < 0.03), Berg Balance Scale (BBS) (p < 0.006), Tinetti Scale (TS) (p < 0.002), Falls Efficacy Scale- International (FES-I), (p < 0.03) Unified PD Rating Scale-III (UPDRS) (p < 0.002), and Functional Independence Measure (FIM) (p < 0.004). Also, the CG showed statistical significances after the training. Between-group (EG and CG) analysis showed significative statistical differences in 6MWT (p < 0.006), BBS (p < 0.006), TS (p < 0.008), FES-I (p < 0.01), and FIM (p < 0.009). From our results it emerges that both groups (EG and CG) achieved better outcome scores after the treatment, suggesting that both physiotherapy interventions were effective. However, the EG training using VR seemed to have induced more improvements, especially in gait and balance skills. Then, C-Mill could be a valid adjunctive treatment in the context of gait and balance disturbances, which are very common in the PD population.