bluuebunny/crossref_metadata_2025 huggingface dataset:
Machine Learning Approach with Harmonized Multinational Datasets for Enhanced Prediction of Hypothyroidism in Patients with Type 2 Diabetes
Authors: Adelson Robert P. , Garikipati Anurag , Zhou Yunfan , Ciobanu Madalina , Tawara Ken , Barnes Gina , Singh Navan Preet , Mao Qingqing , Das Ritankar
Published: May 2024

Type 2 diabetes (T2D) is a global health concern with increasing prevalence. Comorbid hypothyroidism (HT) exacerbates kidney, cardiac, neurological and other complications of T2D; these risks can be mitigated pharmacologically upon detecting HT. The current HT standard of care (SOC) screening in T2D is infrequent, delaying HT diagnosis and treatment. We present a first-to-date machine learning algorithm (MLA) clinical decision tool to classify patients as low vs. high risk for developing HT comorbid with T2D; the MLA was developed using readily available patient data from harmonized multinational datasets. The MLA was trained on data from NIH All of US (AoU) and UK Biobank (UKBB) (Combined dataset) and achieved a high negative predictive value (NPV) of 0.989 and an AUROC of 0.762 in the Combined dataset, exceeding AUROCs for the models trained on AoU or UKBB alone (0.666 and 0.622, respectively), indicating that increasing dataset diversity for MLA training improves performance. This high-NPV automated tool can supplement SOC screening and rule out T2D patients with low HT risk, allowing for the prioritization of lab-based testing for at-risk patients. Conversely, an MLA output that designates a patient to be at risk of developing HT allows for tailored clinical management and thereby promotes improved patient outcomes.
Enhancing IoT Security: Optimizing Anomaly Detection through Machine Learning
Authors: Balega Maria , Farag Waleed , Wu Xin-Wen , Ezekiel Soundararajan , Good Zaryn
Published: May 2024

As the Internet of Things (IoT) continues to evolve, securing IoT networks and devices remains a continuing challenge. Anomaly detection is a crucial procedure in protecting the IoT. A promising way to perform anomaly detection in the IoT is through the use of machine learning (ML) algorithms. There is a lack of studies in the literature identifying optimal (with regard to both effectiveness and efficiency) anomaly detection models for the IoT. To fill the gap, this work thoroughly investigated the effectiveness and efficiency of IoT anomaly detection enabled by several representative machine learning models, namely Extreme Gradient Boosting (XGBoost), Support Vector Machines (SVMs), and Deep Convolutional Neural Networks (DCNNs). Identifying optimal anomaly detection models for IoT anomaly detection is challenging due to diverse IoT applications and dynamic IoT networking environments. It is of vital importance to evaluate ML-powered anomaly detection models using multiple datasets collected from different environments. We utilized three reputable datasets to benchmark the aforementioned machine learning methods, namely, IoT-23, NSL-KDD, and TON_IoT. Our results show that XGBoost outperformed both the SVM and DCNN, achieving accuracies of up to 99.98%. Moreover, XGBoost proved to be the most computationally efficient method; the model performed 717.75 times faster than the SVM and significantly faster than the DCNN in terms of training times. The research results have been further confirmed by using our real-world IoT data collected from an IoT testbed consisting of physical devices that we recently built.
Fault Diagnosis Model for Bearings under Multiple Operating Conditions Based on Feature Parameterization Weighting
Authors: Meng Linghui , Xie Jinyang , Zhou Zhenwei , Chen Yiqiang
Published: May 2024

As a core component of automobile transmission, rolling bearings play a main role in the safety and reliability of vehicles. Existing diagnostic models often treat all features equally after feature extraction, without effectively distinguishing the importance of fault features, resulting in low accuracy and poor robustness in bearing fault diagnosis. To address this issue, a fault diagnosis model for bearings under multiple operating conditions based on feature parameterization weighting is proposed. The model utilizes a feature parameterization weighting module to categorize faults into two classes based on differences in means and implements different feature processing methods. The experimental results validate that the proposed feature parameterization weighting module effectively improves the diagnostic accuracy of the model by 8.95%. In terms of noise resistance, on two multi-condition datasets, the proposed diagnostic model achieves diagnostic accuracy of 98.79% and 98.36%. The diagnostic accuracy is improved by 15.7% and 22.48%, which indicates that the model has strong anti-noise ability.
Unveiling the Potential of Cryogenic Post-Combustion Carbon Capture: From Fundamentals to Innovative Processes
Authors: Luberti Mauro , Ballini Erika , Capocelli Mauro
Published: May 2024

Climate change necessitates urgent actions to mitigate carbon dioxide (CO2) emissions from fossil fuel-based energy generation. Among various strategies, the deployment of carbon capture and storage (CCS) solutions is critical for reducing emissions from point sources such as power plants and heavy industries. In this context, cryogenic carbon capture (CCC) via desublimation has emerged as a promising technology. While CCC offers high separation efficiency, minimal downstream compression work, and integration potential with existing industrial processes, challenges such as low operating temperatures and equipment costs persist. Ongoing research aims to address these hurdles in order to optimize the desublimation processes for widespread implementation. This review consolidates diverse works from the literature, providing insights into the strengths and limitations of CCC technology, including the latest pilot plant scale demonstrations. The transformative potential of CCC is first assessed on a theoretical basis, such as thermodynamic aspects and mass transfer phenomena. Then, recent advancements in the proposed process configurations are critically assessed and compared through key performance indicators. Furthermore, future research directions for this technology are clearly highlighted.
Validity and Reproducibility of Counter Electrodes for Linear Sweep Voltammetry Test in Microbial Electrolysis Cells
Authors: Chai Hyungwon , Koo Bonyoung , Son Sunghoon , Jung Sokhee Philemon
Published: May 2024

The electrode is a key component in a microbial electrolysis cell (MEC) that needs significant improvement for practical implementation. Accurate and reproducible analytical methods are substantial for the effective development of electrode technology. Linear sweep voltammetry (LSV) is an essential analytical method for evaluating electrode performance. In this study, inoculated carbon brush (IB), abiotic brush (AB), Pt wire (PtW), stainless steel wire (SSW), and mesh (SSM) were tested to find the most suitable counter electrode under different medium conditions. The coefficient of variation (Cv) of maximum current (Imax) was the most decisive indicator of the reproducibility test. This study shows that (i) the electrode used in operation is an appropriate counter electrode in an acetate-added condition, (ii) the anode LSV test should avoid the use of Pt wire as counter electrodes, and (iii) PtW is an appropriate counter electrode in cathode LSV in all conditions.
Economic Policy Uncertainty and Co-Control of Air Pollutants and CO2: Evidence from 282 Cities in China
Authors: Yang Xuan , Chen Geng , Qu Chunzi , Chen Zhixuan , Wen Yang , Shi Lei , Long Feng
Published: May 2024

China is currently focusing on the cooperative control of air pollution and CO2 emissions, as well as the mitigation of economic policy uncertainty (EPU). By using panel data from 282 cities spanning from 2003 to 2017 and a newly constructed city-level EPU index, a spatial Durbin, two-way fixed-effects model is employed, with the aim of estimating the impact of EPU on the synergistic emissions intensity (SEI) of air pollutants and CO2. Additionally, this paper investigates the potential channels through which EPU influences SEI. It also explores how pressures related to environmental protection and economic development affect the impact of EPU on SEI. The results indicate that a unit increase in EPU will result in a rise in the SEI of local cities, adjacent cities, and total cities by 930.9%, 69,162.7%, and 70,093.6%, respectively. Moreover, the channel analysis suggests that EPU exacerbates SEI by undermining the upgrading of the industrial structure, augmenting industrial structure distortion, and escalating labor market distortion. Furthermore, the effect of EPU on SEI may be lessened by an increase in environmental protection pressure, while an increase in economic development pressure may exert a positive influence. Finally, this paper concludes by recommending that policymakers should prioritize the maintenance and stability of economic policies, facilitate the advancement of the industrial structure, enhance the efficiency of labor resource allocation, and underscore the significance of managing urban air pollution and CO2 emissions.
A Distributed Harmonic Mitigation Strategy Based on Dynamic Points Incentive of Blockchain Communities
Authors: Wang Lei , Zhou Wen , Su Can , Fan Jiawen , Kong Weikuo , Li Pan
Published: May 2024

With the high proportion of renewable energy sources and power electronic devices accessed in the distribution network, the harmonic pollution problem has become increasingly serious. The traditional centralized harmonic mitigation strategy has difficulty in effectively dealing with these scattered and random harmonics. Therefore, a distributed harmonic mitigation strategy based on the dynamic points incentive of blockchain communities is proposed in this paper. Firstly, a comprehensive voltage sensitivity partitioning method with harmonic weight differentiation is proposed to realize the reasonable partitioning of each control node and controlled node in the distribution network concerning variability in harmonic components and their distribution. Then, a harmonic mitigation strategy based on the dynamic integral excitation of self-learning algorithms is constructed to promote self-organized optimization and active distributed coordinated control of mitigation devices. The strategy ensures that the total harmonic voltage distortion rate of each node meets the requirements by adjusting the partitioned collaboration to realize optimal harmonic mitigation. By setting optimized partitions in different scenarios and conducting simulation verification, the results demonstrate the effectiveness of the strategy in this paper. It stimulates synergy between devices through a dynamic incentive mechanism and significantly reduces the total harmonic voltage distortion rate across various test scenarios, reflecting the adaptability of the harmonic mitigation method presented.
Enhancing Sensor Data Imputation: OWA-Based Model Aggregation for Missing Values
Authors: Al-Amidie Muthana , Alzubaidi Laith , Islam Muhammad Aminul , Anderson Derek T.
Published: May 2024

Due to some limitations in the data collection process caused either by human-related errors or by collection electronics, sensors, and network connectivity-related errors, the important values at some points could be lost. However, a complete dataset is required for the desired performance of the subsequent applications in various fields like engineering, data science, statistics, etc. An efficient data imputation technique is desired to fill in the missing data values to achieve completeness within the dataset. The fuzzy integral is considered one of the most powerful techniques for multi-source information fusion. It has a wide range of applications in many real-world decision-making problems that often require decisions to be made with partially observable/available information. To address this problem, algorithms impute missing data with a representative sample or by predicting the most likely value given the observed data. In this article, we take a completely different approach to the information fusion task in the ordered weighted averaging (OWA) context. In particular, we empirically explore for different distributions how the weights/importance of the missing sources are distributed across the observed inputs/sources. The experimental results on the synthetic and real-world datasets demonstrate the applicability of the proposed methods.
Passive Control of Vortices in the Wake of a Bluff Body
Authors: Pátý Marek , Valášek Michael , Resta Emanuele , Marsilio Roberto , Ferlauto Michele
Published: May 2024

Vortices belong to the most important phenomena in fluid dynamics and play an essential role in many engineering applications. They can act detrimentally by harnessing the flow energy and reducing the efficiency of an aerodynamic device, whereas in other cases, their presence can be exploited to achieve targeted flow conditions. The control of the vortex parameters is desirable in both cases. In this paper, we introduce an optimization strategy for the control of vortices in the wake of a bluff body. Flow modelling is based on RANS and DES computations, validated by experimental data. The algorithm for vortex identification and characterization is based on the triple decomposition of motion. It produces a quantitative measure of vortex strength which is used to define the objective function in the optimization procedure. It is shown how the shape of an aerodynamic device can be altered to achieve the desired characteristics of vortices in its wake. The studied case is closely related to flame holders for combustion applications, but the conceptual approach has a general applicability to vortex control.
The Use of Ultraviolet Irradiation to Improve the Efficacy of Acids That Are Generally Recognized as Safe for Disinfecting Fresh Produce in the Ready-to-Eat Stage
Authors: Maimaitiyiming Ruxianguli , Yang Yuting , Mulati Ailikemu , Aihaiti Aihemaitijiang , Wang Jiayi
Published: May 2024

Fresh-cut produce is usually produced under standardized disinfection processes, which are unavailable at the ready-to-eat stage. Currently, chemical sanitizers are used for washing, but their disinfection efficacy is limited. In this study, UV-C (1.03 kJ/m2) was combined with organic acids that are generally recognized as safe (GRAS), including citric, malic, acetic, and lactic acids (LAs), to wash lettuce and cherry tomatoes that are contaminated with Escherichia coli O157:H7 and Salmonella Typhimurium. The results showed that LA was the most effective treatment among the single treatments, with a pathogen reduction and cross-contamination incidence of 2.0–2.3 log CFU/g and 28–35%, respectively. After combining with UV-C, the disinfection efficacy and cross-contamination prevention capacity of the four GRAS acids significantly improved. Among the combination treatments, the highest pathogen reduction (2.5–2.7 log CFU/g) and the lowest cross-contamination incidence (11–15%) were achieved by LA-UV. The analyses of ascorbic acid, chlorophyll, lycopene, antioxidant capacity, and ΔE indicated that neither the single nor combination treatments negatively affected the quality properties. These results provide a potential hurdle technology for fresh produce safety improvement at the ready-to-eat stage.
Improving Catalytic Efficiency of L-Arabinose Isomerase from Lactobacillus plantarum CY6 towards D-Galactose by Molecular Modification
Authors: Lu Chengyu , Chen Ziwei , Ravikumar Yuvaraj , Zhang Guoyan , Tang Xinrui , Zhang Yufei , Zhao Mei , Sun Wenjing , Qi Xianghui
Published: May 2024

L-Arabinose isomerase (L-AI) has been commonly used as an efficient biocatalyst to produce D-tagatose via the isomerization of D-galactose. However, it remains a significant challenge to efficiently synthesize D-tagatose using the native (wild type) L-AI at an industrial scale. Hence, it is extremely urgent to redesign L-AI to improve its catalytic efficiency towards D-galactose, and herein a structure-based molecular modification of Lactobacillus plantarum CY6 L-AI (LpAI) was performed. Among the engineered LpAI, both F118M and F279I mutants showed an increased D-galactose isomerization activity. Particularly, the specific activity of double mutant F118M/F279I towards D-galactose was increased by 210.1% compared to that of the wild type LpAI (WT). Besides the catalytic activity, the substrate preference of F118M/F279I was also largely changed from L-arabinose to D-galactose. In the enzymatic production of D-tagatose, the yield and conversion ratio of F118M/F279I were increased by 81.2% and 79.6%, respectively, compared to that of WT. Furthermore, the D-tagatose production of whole cells expressing F118M/F279I displayed about 2-fold higher than that of WT cell. These results revealed that the designed site-directed mutagenesis is useful for improving the catalytic efficiency of LpAI towards D-galactose.
Microbial Evolution in Artisanal Pecorino-like Cheeses Produced from Two Farms Managing Two Different Breeds of Sheep (Comisana and Lacaune)
Authors: Luziatelli Francesca , Abou Jaoudé Renée , Melini Francesca , Melini Valentina , Ruzzi Maurizio
Published: May 2024

“Pecorino” is a typical semi-hard cheese obtained with raw or heat-treated sheep milk using procedures to valorize the raw material’s chemical and microbiological properties. In the present study, using a high-throughput method of 16S rRNA gene sequencing, we assessed the evolution of the microbiome composition from milk to Pecorino-like cheese in artisanal processes using milk from Comisana and Lacaune sheep breeds. The comparative analysis of the bacterial community composition revealed significant differences in the presence and abundance of specific taxa in the milk microbiomes of the Comisana and Lacaune breeds. Next-Generation Sequencing (NGS) analysis also revealed differences in the curd microbiomes related to dairy farming practices, which have a relevant effect on the final structure of the Pecorino cheese microbiome.
Preparation and Regulation of Natural Amphiphilic Zein Nanoparticles by Microfluidic Technology
Authors: Liu Zhe , Ma Xiaojie , Ge Yanzheng , Hei Xue , Zhang Xinyu , Hu Hui , Zhu Jinjin , Adhari Benu , Wang Qiang , Shi Aimin
Published: May 2024

Microfluidic technology, as a continuous and mass preparation method of nanoparticles, has attracted much attention in recent years. In this study, zein nanoparticles (ZNPs) were continuously fabricated in a highly controlled manner by combining a microfluidics platform with the antisolvent method. The impact of ethanol content (60~95%, v/v) and flow rates of inner and outer phases in the microfluidics platform on particle properties were examined. Among all ZNPS, 90%-ZNPs have the highest solubility (32.83%) and the lowest hydrophobicity (90.43), which is the reverse point of the hydrophobicity of ZNPs. Moreover, when the inner phase flow rate was 1.5 mL/h, the particle size decreased significantly from 182.81 nm to 133.13 nm as the outer phase flow rate increased from 10 mL/h to 50 mL/h. The results revealed that ethanol content had significant impacts on hydrophilic–hydrophobic properties of ZNPs. The flow rates of ethanol–water solutions and deionized water (solvent and antisolvent) in the microfluidics platform significantly affected the particle size of ZNPs. These findings demonstrated that the combined application of a microfluidics platform and an antisolvent method could be an effective pathway for precisely controlling the fabrication process of protein nanoparticles and modulating their physicochemical properties.
Functional Biscuits, a Healthy Addition to Your Coffee Break—Evaluating Consumer Acceptability and Willingness to Pay
Authors: Blasi Emanuele , Rossi Eleonora Sofia , Pietrangeli Roberta , Nasso Marco , Cicatiello Clara , Palombieri Samuela , Sestili Francesco
Published: May 2024

An increasing number of individuals are eating out due to work and study commitments. This trend directly influences people’s food choices, especially those who frequently rely on snacks and pre-packaged foods. Consuming these foods can lead to long-term health consequences. Adding functional foods to vending machines could lead to healthier choices. Our aim is to evaluate the acceptability and willingness to pay (WTP) of workers and students for a snack pack of novel functional biscuits (FBs) made with high amylose contents. We found that the experimental flour used is effective in preventing various non-communicable diseases; two phases of analysis were carried out on 209 participants. The participants blindly tested the products and only after the sensory evaluation were they informed about the biscuits’ health contents. Firstly, the blind investigation highlighted the acceptability of the FBs compared to the conventional biscuits. Secondly, the finite mixture model on WTP revealed that some consumers are interested in the health benefits associated with high-amylose test blends and others are focused on hedonistic taste. The design of a communication strategy and industry approach should aim to assist consumers in comprehending the health benefits and sensory aspects of novel functional foods available on the market.
Reduced Order Modeling of System by Dynamic Modal Decom-Position with Fractal Dimension Feature Embedding
Authors: Zhang Mingming , Bai Simeng , Xia Aiguo , Tuo Wei , Lv Yongzhao
Published: May 2024

The balance between accuracy and computational complexity is currently a focal point of research in dynamical system modeling. From the perspective of model reduction, this paper addresses the mode selection strategy in Dynamic Mode Decomposition (DMD) by integrating an embedded fractal theory based on fractal dimension (FD). The existing model selection methods lack interpretability and exhibit arbitrariness in choosing mode dimension truncation levels. To address these issues, this paper analyzes the geometric features of modes for the dimensional characteristics of dynamical systems. By calculating the box counting dimension (BCD) of modes and the correlation dimension (CD) and embedding dimension (ED) of the original dynamical system, it achieves guidance on the importance ranking of modes and the truncation order of modes in DMD. To validate the practicality of this method, it is applied to the reduction applications on the reconstruction of the velocity field of cylinder wake flow and the force field of compressor blades. Theoretical results demonstrate that the proposed selection technique can effectively characterize the primary dynamic features of the original dynamical systems. By employing a loss function to measure the accuracy of the reconstruction models, the computed results show that the overall errors of the reconstruction models are below 5%. These results indicate that this method, based on fractal theory, ensures the model’s accuracy and significantly reduces the complexity of subsequent computations, exhibiting strong interpretability and practicality.
A High-Performance Fractional Order Controller Based on Chaotic Manta-Ray Foraging and Artificial Ecosystem-Based Optimization Algorithms Applied to Dual Active Bridge Converter
Authors: Ruiz Felipe , Pichardo Eduardo , Aly Mokhtar , Vazquez Eduardo , Avalos Juan G. , Sánchez Giovanny
Published: May 2024

Over the last decade, dual active bridge (DAB) converters have become critical components in high-frequency power conversion systems. Recently, intensive efforts have been directed at optimizing DAB converter design and control. In particular, several strategies have been proposed to improve the performance of DAB control systems. For example, fractional-order (FO) control methods have proven potential in several applications since they offer improved controllability, flexibility, and robustness. However, the FO controller design process is critical for industrializing their use. Conventional FO control design methods use frequency domain-based design schemes, which result in complex and impractical designs. In addition, several nonlinear equations need to be solved to determine the optimum parameters. Currently, metaheuristic algorithms are used to design FO controllers due to their effectiveness in improving system performance and their ability to simultaneously tune possible design parameters. Moreover, metaheuristic algorithms do not require precise and detailed knowledge of the controlled system model. In this paper, a hybrid algorithm based on the chaotic artificial ecosystem-based optimization (AEO) and manta-ray foraging optimization (MRFO) algorithms is proposed with the aim of combining the best features of each. Unlike the conventional MRFO method, the newly proposed hybrid AEO-CMRFO algorithm enables the use of chaotic maps and weighting factors. Moreover, the AEO and CMRFO hybridization process enables better convergence performance and the avoidance of local optima. Therefore, superior FO controller performance was achieved compared to traditional control design methods and other studied metaheuristic algorithms. An exhaustive study is provided, and the proposed control method was compared with traditional control methods to verify its advantages and superiority.
Cationic Glucan Dendrimer Gel-Mediated Local Delivery of Anti-OC-STAMP-siRNA for Treatment of Pathogenic Bone Resorption
Authors: Yamamoto Kenta , Sawada Shin-Ichi , Shindo Satoru , Nakamura Shin , Kwon Young M. , Kianinejad Nazanin , Vardar Saynur , Hernandez Maria , Akiyoshi Kazunari , Kawai Toshihisa
Published: May 2024

Osteoclast stimulatory transmembrane protein (OC-STAMP) plays a pivotal role in the promotion of cell fusion during osteoclast differentiation (osteoclastogenesis) in the context of pathogenic bone resorption. Thus, it is plausible that the suppression of OC-STAMP through a bioengineering approach could lead to the development of an effective treatment for inflammatory bone resorptive diseases with minimum side effects. Here, we synthesized two types of spermine-bearing (Spe) cationic glucan dendrimer (GD) gels (with or without C12) as carriers of short interfering RNA (siRNA) to silence OC-STAMP. The results showed that amphiphilic C12-GD-Spe gel was more efficient in silencing OC-STAMP than GD-Spe gel and that the mixture of anti-OC-STAMP siRNA/C12-GD-Spe significantly downregulated RANKL-induced osteoclastogenesis. Also, local injection of anti-OC-STAMP-siRNA/C12-GD-Spe could attenuate bone resorption induced in a mouse model of periodontitis. These results suggest that OC-STAMP is a promising target for the development of a novel bone regenerative therapy and that C12-GD-Spe gel provides a new nanocarrier platform of gene therapies for osteolytic disease.
Determinants of Health Status and Life Satisfaction among Older South Koreans
Authors: Lee Hyun-Chool , Repkine Alexandre
Published: May 2024

South Korea is a rapidly aging society with the lowest fertility rates among the OECD economies. It is projected to become a super-aged society in 2025, with the share of individuals older than 65 reaching twenty percent. These developments make it important to analyze the determinants of health outcomes in older individuals. In this study, we identified the determinants of subjective and objective health outcomes among senior individuals in South Korea. We used self-rated health and life satisfaction scores as the two subjective health status indicators, while the number of chronic diseases was the objective one. We ran Tobit multivariate regressions of all three indicators on a set of factors related to the older citizens’ physical, economic, and social characteristics. Active employment status and willingness to work in the future were positively related to self-rated health level but were not statistically related to life satisfaction, while income positively affected both subjective health status indicators. Age did not appear to affect satisfaction with life. Active leisure activities were positively related to both self-rated health and life satisfaction. In contrast, passive leisure, such as watching TV, was negatively related to both health status indicators while being associated with an increased number of chronic diseases. Our findings suggest that older South Koreans view employment primarily as a means of financial support rather than as an opportunity for active social engagement.
Understanding College Students’ Healthcare Avoidance: From Early Maladaptive Schemas, through Healthcare Institutional Betrayal and Betrayal Trauma Appraisal of Worst Healthcare Experiences
Authors: Rastegar Pedram J. , Langhinrichsen-Rohling Jennifer
Published: May 2024

Understanding healthcare avoidance among college students is critical. In this study, we consider two broad cognitive contributors to greater healthcare avoidance: specific early maladaptive schema and negative appraisals of students’ prior worst healthcare experiences. From schema theory, we proposed college students holding greater levels of two early maladaptive schema (disconnection/rejection and impaired autonomy/performance EMS) would be more likely to appraise their problematic healthcare experience as both containing healthcare institutional betrayal (HIB) behaviors and as traumatic and betrayal-inducing; both EMS and these appraisals would predict healthcare avoidance. Using a cross-sectional survey in a large, diverse college student sample (n = 1383, 61.1% female, 18.9% African American, 7.2% Asian, 6.4% Hispanic/Latino), as predicted, both EMS were significantly related to healthcare avoidance. Furthermore, a sequential mediation model was supported, indicating students holding greater EMS of disconnection/rejection or impaired autonomy/rejection reported more HIB in their worst healthcare experience, and appraised that experience as more betraying. Taken altogether, this model accounted for 23% of the variance in students’ reports of healthcare avoidance. Core beliefs formed early in life may be a foundational lens through which potentially traumatic healthcare experiences are processed in ways that can impact emerging adults’ future healthcare engagement. Findings also support the importance of addressing HIB actions and repairing trauma appraisals accrued during problematic healthcare experiences to prevent healthcare avoidance by emerging adults.
Two-Stage Path Planning for Long-Distance Off-Road Path Planning Based on Terrain Data
Authors: Zheng Xudong , Ma Mengyu , Zhong Zhinong , Yang Anran , Chen Luo , Jing Ning
Published: May 2024

In the face of increasing demands for tasks such as mountain rescue, geological exploration, and military operations in complex wilderness environments, planning an efficient walking route is crucial. To address the inefficiency of traditional two-dimensional path planning, this paper proposes a two-stage path planning algorithm. First, an improved Probabilistic Roadmap (PRM) algorithm is used to quickly and roughly determine the initial path. Then, the morphological dilation is applied to process the grid points of the initial path, retaining the surrounding area of the initial path for a precise positioning of the search range. Finally, the idea of the A∗ algorithm is applied to achieve precise path planning in the refined search range. During the process of constructing the topology map, we utilized parallelization acceleration strategies to expedite the graph construction. In order to verify the effectiveness of the algorithm, we used terrain data to construct a wilderness environment model, and tests were conducted on off-road path planning tasks with different terrains and distances. The experimental results show a substantial enhancement in the computational efficiency of the proposed algorithm relative to the conventional A∗ algorithm by 30 to 60 times.
Equine Endothelial Cells Show Pro-Angiogenic Behaviours in Response to Fibroblast Growth Factor 2 but Not Vascular Endothelial Growth Factor A
Authors: Finding Elizabeth J. T. , Faulkner Ashton , Nash Lilly , Wheeler-Jones Caroline P. D.
Published: May 2024

Understanding the factors which control endothelial cell (EC) function and angiogenesis is crucial for developing the horse as a disease model, but equine ECs remain poorly studied. In this study, we have optimised methods for the isolation and culture of equine aortic endothelial cells (EAoECs) and characterised their angiogenic functions in vitro. Mechanical dissociation, followed by magnetic purification using an anti-VE-cadherin antibody, resulted in EC-enriched cultures suitable for further study. Fibroblast growth factor 2 (FGF2) increased the EAoEC proliferation rate and stimulated scratch wound closure and tube formation by EAoECs on the extracellular matrix. Pharmacological inhibitors of FGF receptor 1 (FGFR1) (SU5402) or mitogen-activated protein kinase (MEK) (PD184352) blocked FGF2-induced extracellular signal-regulated kinase 1/2 (ERK1/2) phosphorylation and functional responses, suggesting that these are dependent on FGFR1/MEK-ERK signalling. In marked contrast, vascular endothelial growth factor-A (VEGF-A) had no effect on EAoEC proliferation, migration, or tubulogenesis and did not promote ERK1/2 phosphorylation, indicating a lack of sensitivity to this classical pro-angiogenic growth factor. Gene expression analysis showed that unlike human ECs, FGFR1 is expressed by EAoECs at a much higher level than both VEGF receptor (VEGFR)1 and VEGFR2. These results suggest a predominant role for FGF2 versus VEGF-A in controlling the angiogenic functions of equine ECs. Collectively, our novel data provide a sound basis for studying angiogenic processes in horses and lay the foundations for comparative studies of EC biology in horses versus humans.
Effects of Fucoidans on Activated Retinal Microglia
Authors: Dörschmann Philipp , Hunger Florentine , Schroth Hannah , Chen Sibei , Kopplin Georg , Roider Johann , Klettner Alexa
Published: May 2024

Sulfated marine polysaccharides, so-called fucoidans, have been shown to exhibit anti-inflammatory and immunomodulatory activities in retinal pigment epithelium (RPE). In this study, we tested the effects of different fucoidans (and of fucoidan-treated RPE cells) on retinal microglia to investigate whether its anti-inflammatory effect can be extrapolated to the innate immune cells of the retina. In addition, we tested whether fucoidan treatment influenced the anti-inflammatory effect of RPE cells on retinal microglia. Three fucoidans were tested (FVs from Fucus vesiculosus, Fuc1 and FucBB04 from Laminaria hyperborea) as well as the supernatant of primary porcine RPE treated with fucoidans for their effects on inflammatory activated (using lipopolysaccharide, LPS) microglia cell line SIM-A9 and primary porcine retinal microglia. Cell viability was detected with a tetrazolium assay (MTT), and morphology by Coomassie staining. Secretion of tumor necrosis factor alpha (TNFα), interleukin 1 beta (IL1β) and interleukin 8 (IL8) was detected with ELISA, gene expression (NOS2 (Nitric oxide synthase 2), and CXCL8 (IL8)) with qPCR. Phagocytosis was detected with a fluorescence assay. FucBB04 and FVs slightly reduced the viability of SIM-A9 and primary microglia, respectively. Treatment with RPE supernatants increased the viability of LPS-treated primary microglia. FVs and FucBB04 reduced the size of LPS-activated primary microglia, indicating an anti-inflammatory phenotype. RPE supernatant reduced the size of LPS-activated SIM-A9 cells. Proinflammatory cytokine secretion and gene expression in SIM-A9, as well as primary microglia, were not significantly affected by fucoidans, but RPE supernatants reduced the secretion of LPS-induced proinflammatory cytokine secretion in SIM-A9 and primary microglia. The phagocytosis ability of primary microglia was reduced by FucBB04. In conclusion, fucoidans exhibited only modest effects on inflammatorily activated microglia by maintaining their cell size under stimulation, while the anti-inflammatory effect of RPE cells on microglia irrespective of fucoidan treatment could be confirmed, stressing the role of RPE in regulating innate immunity in the retina.
PACSAB Server: A Web-Based Tool for the Study of Aggregation and the Conformational Ensemble of Disordered and Folded Proteins
Authors: Emperador Agustí
Published: May 2024

We present in this article the PACSAB server, which is designed to provide information about the structural ensemble and interactions of both stable and disordered proteins to researchers in the field of molecular biology. The use of this tool does not require any computational skills as the user just needs to upload the structure of the protein to be studied; the server runs a simulation with the PACSAB model, a highly accurate coarse-grained model that is much more efficient than standard molecular dynamics for the exploration of the conformational space of multiprotein systems. The trajectories generated by the simulations based on this model reveal the propensity of the protein under study for aggregation, identify the residues playing a central role in the aggregation process, and reproduce the whole conformational space of disordered proteins. All of this information is shown and can be downloaded from the web page.
Inflammatory and Cardiovascular Biomarkers to Monitor Fabry Disease Progression
Authors: Alonso-Núñez Adrián , Pérez-Márquez Tania , Alves-Villar Marta , Fernández-Pereira Carlos , Fernández-Martín Julián , Rivera-Gallego Alberto , Melcón-Crespo Cristina , San Millán-Tejado Beatriz , Ruz-Zafra Aurora , Garofano-López Remedios , Sánchez-Martínez Rosario , García-Payá Elena , López-Mendoza Manuel , Martín-Suárez Ignacio , Ortolano Saida
Published: May 2024

Fabry disease is an invalidating multisystemic disorder affecting α-Galactosidase, a rate-limiting hydrolase dedicated to lipid catabolism. Non-metabolized substrates, such as Globotriaosylceramide and its derivatives trigger the direct or indirect activation of inflammatory events and endothelial dysfunction. In spite of the efficacy demonstrated by enzyme replacement therapy or pharmacological chaperones in delaying disease progression, few studies have analyzed whether these treatments can improve the pro-inflammatory state of FD patients. Therefore, the aim of this work was to assess cytokines and cardiovascular risk-related proteins detectable in plasma from FD patients, whether treated or not with ERT, to evaluate the reliability of these markers in monitoring disease stage and treatment effects. We identified inflammatory and endothelial dysfunction markers (ADAMTS-13, TNF-α, GDF-15, MIP-1β, VEGFA, MPO, and MIC-1) that cooperate in a common pathway and are increased in FD patients’ plasma samples. As shown by the assessment of these proteins over time, they can help to evaluate the risk of higher severity in FD, as well as ERT effects. Even though the analyzed proteins cannot be considered as proper biomarkers due to their non-specificity to FD, taken together they can provide a signature of reference molecules with prognostic value for early diagnosis, and evaluation of disease progression and treatment efficacy, using blood samples.
Anticancer Effect of Hemin through ANO1 Inhibition in Human Prostate Cancer Cells
Authors: Park So-Hyeon , Lee Yechan , Jeon Hyejin , Park Junghwan , Kim Jieun , Kang Mincheol , Namkung Wan
Published: May 2024

Anoctamin1 (ANO1), a calcium-activated chloride channel, is overexpressed in a variety of cancer cells, including prostate cancer, and is involved in cancer cell proliferation, migration, and invasion. Inhibition of ANO1 in these cancer cells exhibits anticancer effects. In this study, we conducted a screening to identify novel ANO1 inhibitors with anticancer effects using PC-3 human prostate carcinoma cells. Screening of 2978 approved and investigational drugs revealed that hemin is a novel ANO1 inhibitor with an IC50 value of 0.45 μM. Notably, hemin had no significant effect on intracellular calcium signaling and cystic fibrosis transmembrane conductance regulator (CFTR), a cyclic AMP (cAMP)-regulated chloride channel, and it showed a weak inhibitory effect on ANO2 at 3 μM, a concentration that completely inhibits ANO1. Interestingly, hemin also significantly decreased ANO1 protein levels and strongly inhibited the cell proliferation and migration of PC-3 cells in an ANO1-dependent manner. Furthermore, it strongly induced caspase-3 activation, PARP degradation, and apoptosis in PC-3 cells. These findings suggest that hemin possesses anticancer properties via ANO1 inhibition and could be considered for development as a novel treatment for prostate cancer.
Intestinal Microbiota and Derived Metabolites in Myocardial Fibrosis and Postoperative Atrial Fibrillation
Authors: Nenna Antonio , Laudisio Alice , Taffon Chiara , Fogolari Marta , Spadaccio Cristiano , Ferrisi Chiara , Loreni Francesco , Giacinto Omar , Mastroianni Ciro , Barbato Raffaele , Rose David , Salsano Antonio , Santini Francesco , Angeletti Silvia , Crescenzi Anna , Antonelli Incalzi Raffaele , Chello Massimo , Lusini Mario
Published: May 2024

The high incidence of atrial fibrillation (AFib) following cardiac surgery (postoperative atrial fibrillation, POAF) relies on specific surgical features. However, in the setting of POAF, the role of the microbiome in the modulation of cardiac fibrosis is still not clear. This study aimed to analyze the effect of the microbiome and its main metabolic product (trimethylamine-N-oxide, TMAO) in the fibrosis of myocardial tissue, to investigate its role in POAF. Patients undergoing elective cardiac surgery with cardiopulmonary bypass, central atrio-caval cannulation and no history of AFib, were included. A fragment of the right atrium was analyzed for qualitative and mRNA-quantitative evaluation. A preoperative blood sample was analyzed with enzyme-linked immunosorbent assay (ELISA). A total of 100 patients have been included, with POAF occurring in 38%. Histologically, a higher degree of fibrosis, angiogenesis and inflammation has been observed in POAF. Quantitative evaluation showed increased mRNA expression of collagen-1, collagen-3, fibronectin, and transforming growth factor beta (TGFb) in the POAF group. ELISA analysis showed higher levels of TMAO, lipopolysaccharide and TGFb in POAF, with similar levels of sP-selectin and zonulin. TMAO ≥ 61.8 ng/mL (odds ratio, OR 2.88 [1.35–6.16], p = 0.006), preoperative hemoglobin < 13.1 g/dL (OR 2.37 [1.07–5.24], p = 0.033) and impaired right ventricular function (OR 2.38 [1.17–4.83], p = 0.017) were independent predictors of POAF. Also, TMAO was significantly associated with POAF by means of increased fibrosis. Gut microbiome product TMAO is crucial for myocardial fibrosis, which is a key factor for POAF. Patients in preoperative sinus rhythm who will develop POAF have increased genetic expression of pro-fibrotic genes and enhanced fibrosis in histological staining. Elevated TMAO level (≥61.8 ng/mL) is an independent risk factor for POAF.
Shear Stress-Induced AMP-Activated Protein Kinase Modulation in Endothelial Cells: Its Role in Metabolic Adaptions and Cardiovascular Disease
Authors: Hauger Philipp C. , Hordijk Peter L.
Published: May 2024

Endothelial cells (ECs) line the inner surface of all blood vessels and form a barrier that facilitates the controlled transfer of nutrients and oxygen from the circulatory system to surrounding tissues. Exposed to both laminar and turbulent blood flow, ECs are continuously subject to differential mechanical stimulation. It has been well established that the shear stress associated with laminar flow (LF) is atheroprotective, while shear stress in areas with turbulent flow (TF) correlates with EC dysfunction. Moreover, ECs show metabolic adaptions to physiological changes, such as metabolic shifts from quiescence to a proliferative state during angiogenesis. The AMP-activated protein kinase (AMPK) is at the center of these phenomena. AMPK has a central role as a metabolic sensor in several cell types. Moreover, in ECs, AMPK is mechanosensitive, linking mechanosensation with metabolic adaptions. Finally, recent studies indicate that AMPK dysregulation is at the center of cardiovascular disease (CVD) and that pharmacological targeting of AMPK is a promising and novel strategy to treat CVDs such as atherosclerosis or ischemic injury. In this review, we summarize the current knowledge relevant to this topic, with a focus on shear stress-induced AMPK modulation and its consequences for vascular health and disease.
Integrated Transcriptomic and Metabolomic Analysis Reveals the Molecular Regulatory Mechanism of Flavonoid Biosynthesis in Maize Roots under Lead Stress
Authors: Guo Zhaolai , Yuan Xinqi , Li Ting , Wang Sichen , Yu Yadong , Liu Chang’e , Duan Changqun
Published: May 2024

Flavonoids are secondary metabolites that play important roles in the resistance of plants to abiotic stress. Despite the widely reported adverse effects of lead (Pb) contamination on maize, the effects of Pb on the biosynthetic processes of flavonoids in maize roots are still unknown. In the present work, we employed a combination of multi-omics and conventional assay methods to investigate the effects of two concentrations of Pb (40 and 250 mg/kg) on flavonoid biosynthesis in maize roots and the associated molecular regulatory mechanisms. Analysis using conventional assays revealed that 40 and 250 mg/kg Pb exposure increased the lead content of maize root to 0.67 ± 0.18 mg/kg and 3.09 ± 0.02 mg/kg, respectively, but they did not result in significant changes in maize root length. The multi-omics results suggested that exposure to 40 mg/kg of Pb caused differential expression of 33 genes and 34 metabolites related to flavonoids in the maize root system, while 250 mg/kg of Pb caused differential expression of 34 genes and 31 metabolites. Not only did these differentially expressed genes and metabolites participate in transferase activity, anthocyanin-containing compound biosynthetic processes, metal ion binding, hydroxyl group binding, cinnamoyl transferase activity, hydroxycinnamoyl transferase activity, and flavanone 4-reductase activity but they were also significantly enriched in the flavonoid, isoflavonoid, flavone, and flavonol biosynthesis pathways. These results show that Pb is involved in the regulation of maize root growth by interfering with the biosynthesis of flavonoids in the maize root system. The results of this study will enable the elucidation of the mechanisms of the effects of lead on maize root systems.
Nerve Growth Factor Signaling Modulates the Expression of Glutaminase in Dorsal Root Ganglion Neurons during Peripheral Inflammation
Authors: Gujar Vikramsingh , Pande Radhika D. , Hardas Bhalchandra M. , Das Subhas
Published: May 2024

Glutamate functions as the major excitatory neurotransmitter for primary sensory neurons and has a crucial role in sensitizing peripheral nociceptor terminals producing sensitization. Glutaminase (GLS) is the synthetic enzyme that converts glutamine to glutamate. GLS-immunoreactivity (-ir) and enzyme activity are elevated in dorsal root ganglion (DRG) neuronal cell bodies during chronic peripheral inflammation, but the mechanism for this GLS elevation is yet to be fully characterized. It has been well established that, after nerve growth factor (NGF) binds to its high-affinity receptor tropomyosin receptor kinase A (TrkA), a retrograde signaling endosome is formed. This endosome contains the late endosomal marker Rab7GTPase and is retrogradely transported via axons to the cell soma located in the DRG. This complex is responsible for regulating the transcription of several critical nociceptive genes. Here, we show that this retrograde NGF signaling mediates the expression of GLS in DRG neurons during the process of peripheral inflammation. We disrupted the normal NGF/TrkA signaling in adjuvant-induced arthritic (AIA) Sprague Dawley rats by the pharmacological inhibition of TrkA or blockade of Rab7GTPase, which significantly attenuated the expression of GLS in DRG cell bodies. The results indicate that NGF/TrkA signaling is crucial for the production of glutamate and has a vital role in the development of neurogenic inflammation. In addition, our pain behavioral data suggest that Rab7GTPase can be a potential target for attenuating peripheral inflammatory pain.