bluuebunny/crossref_metadata_2025_split huggingface dataset:
The novel and slowest arterial pressure waves: clinical implications in children with congenital heart disease following cardiovascular surgery
Authors: Ma Li , Yu Linyang , Liu Yingying , Lin Rouyi , Feng Jinqing , Cui Yanqin , Li Jianbin , Li Lijuan , Ning Shuyao , Zou Minghui , Huang Guodong , Wang Huanzhen , Chen Xinxin , Li Jia 
Published: October 2023

Abstract
Objective
Certain rhythmic arterial pressure waves in humans and animals have been noticed over one century. We found the noval and slowest arterial pressure waves in children following surgerical repair for congenital heart disease (CHD), and examined their characteristics and clinical implications.
Methods
We enrooled 212 children with 22 types of CHD during and in the first postoperative 48 hours. We monitored hemodynamics, including blood pressure, heart rate, cardiac cycle efficiency (CCE), and dP/dTmax using pressure recording analytical method by MostCare, and cerebral (ScO2) and renal (SrO2) oxygen saturation using near-infrared spectroscopy every 6 seconds. EEG was continuously monitored. Transcranial Doppler was used to measure the mean blood flow velocity (Vm) of the middle cerebral artery at the 24th hours.
Results
We found the waves with a frequency of ~ 90 seconds immediately following surgical repair in 46 patients in 12 types of CHD (21.7%), being most prevalent in patients with aortic arch abnormalities (Aorta Group, n = 24, 42.3%) or with ventricular septal defect (VSD) (VSD Group, n = 12, 23.5%). In Aorta and VSD Groups, the occurrence of the waves was asscoated with lower blood pressures, dP/dTmax, CCE, ScO2 and SrO2, Vm and worse EEG background abnormalities and higher number of EEG sharp waves, and serum lactate (Ps < 0.0001-0.07). The waves were accompanied with fluctuations of ScO2 and SrO2 in 80.6% and 69.6% of patients respectively.
Conclusions
The waves observed in children with CHD following cardiovascular surgery are the slowest ever reported, occurring most frequently in patients with aortic arch abnormalities or VSD. The presence of the waves was associated with worse and fluctuated ScO2 and SrO2, worse systemic hemodynamics and EEG abnormalities.
Comprehensive bioinformatic methods and machine learning algorithms to identify diagnostic biomarkers of coronary artery disease progression in pulmonary arterial hypertension
Authors: Lu Yang , Wang Zeyuan , Zhang Shuyuan , Wu Jiabo , Bai Ruilian , Wu Ming , Ren Xiaoyu , Gao Shiqi , Pan Ruokai , Fan Zhongjie , Tian Zhuang 
Published: October 2023

Abstract
Background Numerous fundamental and clinical investigations have showcased the correlation and interplay mechanism between coronary artery disease (CAD) and pulmonary arterial hypertension (PAH). We aimed to investigate diagnostic indicators and the correlation between immune response and diagnostic indicators.Methods To conduct additional differential expression analysis and weighted gene coexpression network analysis (WGCNA), we obtained CAD and PAH data from the Gene Expression Omnibus (GEO) database. Next, we employed shared genes to conduct enrichment analysis, construct a protein-protein interaction (PPI) network, and subsequently identify diagnostic biomarkers through the utilization of three machine learning algorithms. The diagnostic biomarkers were utilized for conducting logistic regression analysis and constructing a nomogram. Then, we compared the expression differences and their respective diagnostic effects. The evaluation of immune infiltration was conducted finally.Results By intersecting 671 genes that were differentially expressed in CAD and 2052 genes that were key module genes in PAH, we identified 67 genes that were common to both conditions. These shared genes were mainly enriched in signaling pathways associated with the activation of leukocytes and the regulation of inflammation. We further identified 26 genes through PPI network construction. Afterwards, three machine learning algorithms were utilized to choose two candidate biomarkers, namely DPYD and CPT1A. The two possible indicators showed improved diagnostic effectiveness and suggested a statistically significant positive correlation with macrophages in individuals with progressive CAD.Conclusion In this study, we have conducted the first research to identify early diagnostic biomarkers for the advancement of CAD in association with PAH. This was achieved by employing a variety of bioinformatic methods and machine learning algorithms. Possible therapeutic targets may exist due to the presence of a favorable correlation between diagnostic biomarkers and immune cells.
Untethered Bistable Origami Crawler for Confined Applications
Authors: Ren Hongliang , Cai Catherine , Huang Hui 
Published: October 2023

Abstract
Magnetically actuated miniature origami crawlers are capable of robust locomotion in confined environments due to their ability to overcome large environmental resistances. However, these devices are limited to passive functionalities as they are not able to utilize folding and unfolding for independent locomotion and active functionality. Here, we propose a bistable origami crawler that can shape-morph to access two separate regimes of folding degrees-of-freedoms that are separated by an energy barrier conferred by bistability. We employed the modified bistable V-fold origami crease pattern design as the fundamental unit of the origami crawler and incorporated internal permanent magnets to enable untethered shape-morphing for locomotion and reconfiguration. Specifically, by modulating the orientation of the external magnetic field, the origami crawler can reconfigure on-demand between an undeployed locomotion state, and a deployed load-bearing state. In the undeployed state, the origami crawler was able to actively deform to enable out-of-plane crawling for robust bi-directional locomotion and navigation in confined environments based on friction anisotropy. In the deployed state, the origami crawler was able to execute microneedle insertion in confined environments. Through this work, we demonstrated the potential of incorporating bistability into origami mechanisms to enable energy-dependent folding degrees-of-freedom, expanding the capabilities of origami devices in space-constraint applications.
Mechanisms and Energetics of Calcium Aluminosilicate Glass Dissolution through Ab initio Molecular Dynamics-Metadynamics Simulations
Authors: Ruiz Luis , Liu Meili 
Published: October 2023

Abstract
The dissolution of silicate glasses has implications in diverse fields ranging from the immobilization of radioactive waste to the development of sustainable alternatives to Portland cement. Here, we used ab initio molecular dynamics simulations coupled with well-tempered metadynamics to study Si-O-T bridge dissociation in calcium aluminosilicate glasses, crucial for understanding their dissolution processes. In a departure from the conventional Michalske-Freiman model, our findings reveal a nucleophilic substitution reaction mechanism characterized by a short-lived, 5-fold coordinated Si intermediate state with a near-trigonal bipyramidal geometry. We find that the reorganization energy introduces activation energy barriers that depend on the Si bridge coordination, with Si Q3 species serving as the rate-limiting step in the dissolution reaction. Our findings not only challenge long-standing theoretical models but also pave the way for more accurate and comprehensive frameworks for understanding the dissolution of silicate glasses in various applications.
Sugar-based drug-free systemic immunoregulating and imageable nanoparticles promote the efficacy of immune checkpoint inhibitors in aggressive cancer
Authors: Hsu Fei-Ting , Chen Ying-Tzu , Chin Yu‑Cheng , Chang Li-Chan , Chiang Shu-Chin , Yang Li-Xing , Liu Hua-Shan , Jen Long-Bin , Shyu Woei-Cherng , Hu Shang-Hsiu , Chiang I-Tsang , Liu Yu-Chang , Chiu Yi-Chun , Su Wen-Pin , Huang Chih-Chia 
Published: October 2023

Abstract
Poor drug delivery and an unresponsive tumor microenvironment (TME) hinder the treatment of glioblastoma (GBM) and pancreatic cancer (PC). Targeting macrophage polarization through nanoparticle (NP) internalization represents a promising approach to regulate the TME and enhance immunotherapy. Here, we introduce a galactose -based NP designed for monocarboxylate transporter 4 (MCT-4)-mediated transport in cells, promoting M2-to-M1 macrophage polarization and disrupting tumor cell mitochondrial function to trigger apoptosis. The CG-based NP promotes M1 macrophage accumulation, facilitates the M2-to-M1 transition, and exhibits the potential to overcome the obstacles in GBM and PC treatment. This approach enhances immune checkpoint inhibitor efficacy while overcoming the challenging TME. Additionally, incorporating Fe3O4 promotes ferroptosis and enables the use of these NPs in magnetic resonance imaging-based monitoring. Diverging from previous studies that focused on synthesizing nanomaterials, our work has pioneered a synthetic methodology that generates immune-stimulating NPs through a precursor-only hydrothermal reaction and galactose surface engineering. This approach can be meticulously tailored for precise immunotherapeutic applications, which is beneficial for targeting the intricacies of challenging cancers.
High-quality RNA isolation and cDNA library construction from Panama wilt resistant Musa paradisiaca cv. Malnad Rasbale for Next- Generation Sequencing
Authors: Sadarahalli Ullas Prasanna , Venkatarangaiah Krishna 
Published: October 2023

Abstract
Protocol standardized for high-quality RNA isolation for gene expression analysis in Foc race 4 resistant banana cv. Malnad Rasbale. Malnad Rasbale was produced by co-cultivating the micropropagated and Foc race 4 infected banana clones with Trichoderma strains isolated from banana farmyards. Existing protocols for RNA extraction from banana cultivars need high-yield and good-quality tissue are perplexing due to manifestation of polysaccharides and polyphenols as major contaminants which hamper RNA isolation. The methodology is based on the CTAB method using a high amount of PVP and β-mercaptoethanol in the extraction buffer. The RNA isolated from resistant banana clones showed high-quality and RIN values in control, Foc race 4 infected and Trichoderma co-cultivated resistant clones were 7.8, 7.6, and 7.6 respectively. cDNA library studies revealed a good calibrated base pair size of 318, 366, and 361 respectively.This investigation is applicable for the molecular aspects of Malnad Rasbale to isolate high-quality RNA, RNA-seq, and cDNA library construction for NGS analysis. CTAB methodology yielded high-quality RNA with RIN value > 7 and good calibrated base pair with > 310 in Malnad Rasbale plants co-cultured with Trichoderma strains in in-vitro developed conditions. This protocol is deciphered for RNA isolation, RNA-Seq, and cDNA library construction.
Nexus between prevalence of Taenia solium (Cysticercus cellulosae) cysticercosis in pigs and human cysticercosis cases in hospitals in Benin
Authors: Tassou Wassiou Abdou , Attindéhou Sabbas , Gbati Oubri Bassa , Adjassin Josias Steve , Salifou Sahidou 
Published: October 2023

Abstract
The cysticercosis is a major zoonotic disease in many developing countries. This study was carried out to determine the prevalence of porcine cysticercosis and to identify potential risk factors associated and their seroprevalence as well in Benin. The tongue palpation was performed on 4150 pigs from the pig farmers were randomly selected to diagnose cysticercosis and to assess the risk factors associated. In slaughterhouses, 792 pigs were inspected. Serum samples from 460 pigs were tested of the presence of Taenia solium cysticercosis using the HP10 antigen-ELISA (Ag-ELISA). A logistic regression model with a 95% confidence interval was used to analyse the main risk factors associated. The tongue palpation revealed a prevalence of 4.79% at the level of slaughterhouses versus 7.82% in the post-mortem inspection. The Ag-ELISA revealed that more than 40% of the pigs were positive. The risk factors identified were the origin area of pigs, the history of cysticercosis in the farms, the presence or absence of a latrine, the pig-farming systems, the age class of pigs and the source of watering. In addition, 34.48% individuals was tested for taenia versus 13.79% for cysticercosis in the hospitals surveyed. Our results showed the major revelation of porcine cysticercosis and its very high level of risk for a public health in all departments of Benin. Therefore, this study suggests the need to continue epidemiological and sociological surveys with a "One Health" approach in order to design and implement effective control measures in this country of high consumption of pigs.
Investigation of the awareness of specialist physicians in Iran hospitals regarding treatment costs in 2022
Authors: Ebrahimipour Hosein , Yousefi Mehdi , Varmaghani Mehdi , Khoshkhou Mehdi , Mojtabaeian Seyyed Morteza 
Published: October 2023

Abstract
Introduction
In the current economic situation, where financing in healthcare services has become a major problem, awareness of costs and cost-effective decision-making has become more important than ever. Many factors are involved in healthcare spending, but physicians play the most important role. This study aimed to determine the level of awareness of specialist physicians working in Iran hospitals regarding treatment costs.
Method
This cross-sectional and analytical study was conducted in all public-educational hospitals in Mashhad. The data collection tool in this study was a researcher-made checklist, through which participants were asked to estimate the cost of 25 items of services and expenses. The questionnaire is a checklist of the most expensive items and services extracted by specialty. Data were analyzed using STATA version 14 software after collection.
Results
The awareness level of all groups of specialist participants in this study was evaluated as weak regarding treatment costs. In this study, the most accurate estimate of treatment costs was related to emergency medicine specialists (21.5%) and the weakest estimate was related to internal medicine and obstetrics and gynecology specialists (12.4%). All participating specialists in this study tended to estimate treatment costs higher than the actual cost. This study shows that the participating specialists had the highest accuracy in estimating the costs of imaging (22.9%) and the lowest accuracy in estimating the costs of consumables (11.6%). Also, more than 93% of respondents in this study stated that they have not passed any relevant courses on healthcare economics.
Conclusion
The low accuracy of physicians' estimates as the most important factor in managing healthcare costs is the main challenge identified in this section. Displaying item costs and monthly expenses in appropriate places, providing physicians with cost information, developing computer programs capable of displaying costs when physicians write orders, and including retraining programs on healthcare economics can improve physicians' awareness of treatment costs.
Impact of climatic anomalies and reservoir induced seismicity on earthquake generation using Federated Learning
Authors: Tehseen Rabia , Omer Uzma , Mehr Maham , Javaid Rubab , Saqib Shazia 
Published: October 2023

Abstract

In this article, earthquake forecasting model using federated learning (FL) technique has been proposed. Federated Learning is the most advanced technique of machine learning (ML) that guarantees data privacy, ensures data availability, promises data security, and handles network latency trials inherent in prediction of earthquakes by prohibiting data to be transferred over the network for model training. The main objective of this study is to determine the impact of artificial stresses and climatic anomalies on regional seismicity. Experimental verification has been carried out within 100 km radial area from 34.708o N, 72.5478o E in Western Himalayan region. Regional data of atmospheric temperature, air pressure, rainfall, water level of reservoir and seismicity has been collected on hourly bases from 1985 till 2022. In this research, four client stations at different points within the selected area have been established to train local models by calculating time lag correlation between multiple data parameters. These local models are transmitted to central server where global model is trained for generating earthquake alert with ten days lead time, towards a specific client where high correlation among all parameters have been reported.
Densification of fast-growing paulownia wood for tough composites with stab resistance property
Authors: Chen changjie , Shen Leiming , Sun Ye , Bao Limin , Wang Xinhou 
Published: October 2023

Abstract
Paulownia wood, a fast-growing wood native to China, has limited application due to its loose texture. However, the mechanical properties of materials can be improved by densification after delignification. In this study, paulownia wood was treated with sodium hydroxide and hydrogen peroxide to remove most of the lignin, then densified by hot pressing. The influence of the densification process of paulownia wood/epoxy composite on the mechanical properties, especially stab resistance, was discussed. The results show that densification after delignification significantly improves the mechanical properties of the materials. The densification improves the fracture strength and modulus of the materials, reching 171.98 MPa and 14.55 GPa. Hybrid composites made of densified wood/carbon fiber/epoxy resin have good stab resistance. The punch strength per unit area density and puncture worker unit area density of these hybrid composites are superior to carbon fiber reinforced composites.
Analysis of The Travelling Time According to Weather Conditions Using Machine Learning Algorithms
Authors: CANBULUT Gülçin 
Published: October 2023

Abstract
Nowadays, a large part of the world’s population lives in urban areas. The increase in the population living in cities makes it difficult to live in cities.Local administrators seek solutions to these problems in order to make cities more livable. In order to increase the quality of transportation, which is among the important issues for local governments, studies are carried out to establish smart transportation systems for public transportation companies. Estimating travel times is an important tool in managing transportation operations. In addition, operations managers use these forecasts to coordinate future transportation operations. The public transport travel time prediction has been a well-researched topic; various researchers have predicted travel time using mathematical, statistical, and machine learning based models. Researchers also have compared the performance of these models. It can be seen that studies in this field can be divided into statistical methods and machine learning methods. And number of researchers use one of these methods. But in this study, we use both statistical and machine learning techniques together. Also, the parameters of this study are different from the other studies in this literature. The effect of the weather on the travel time will be analyzed. In this respect it is thought that the study will contribute to the literature. In the study, in addition to model tuning, sensitivity analyzes are also carried out according to the change of the k value in the KNN algorithm and the change of the threshold values used to determine outliers. we can say that, as can be seen from the analysis, the Catboost algorithm appears to be the algorithm that gives the best results in almost every situation.
Fog Based IoT-enabled system security forElectrical Vehicles in the Smart Grids
Authors: sonker Sanjay Kumar Sonker sanjay , Sagar Bharat Bhushan , C Ramesh C. Bansal Ramesh 
Published: October 2023

Abstract
Wireless sensor networks (WSN) have dependability, integrity, and confidentiality issues because of their extensive use. An efficient defensive line for WSN is provided by intrusion detection, a crucial active defence technology. Given the uniqueness of WSN, it is necessary to strike a balance between precise data transmission and constrained sensor energy, as well as between the detecting effect and a lack of network resources. In this study, we suggested a fog computing-based intrusion detection system (IDS) for a smart power grid. This article's main objective is to explain how to use IDS in a smart grid setting. We introduce a stacked model based on the ensemble learning algorithm, which can accurately portray the connections among fog nodes that are vulnerable to cyber-attacks. We conclude by conducting a series of comparative experiments using the KDD CUP 99 dataset with cross-validation, and determine that the Fog-IDS and Stacking-based approaches are more effective in enhancing the performance of the IDS. By conducting simulations, we confirm that our approach effectively analysis fog nodes using the deployed IDS can predict the energy requirement refill station. With an accuracy rate of over 99.837%, MCC rate 99.73%, and F1-Score rate 99.827%.
GABA induced by sleep disorders promotes the proliferation and migration of colon tumors through miR-223-3p endogenous pathway and exosome pathway
Authors: Bao Haijun , Peng Zuojie , Cheng Xukai , Jian Chenxing , Li Xianguo , Shi Yongping , Zhu Wenzhong , Hu Yuan , Jiang Mi , Song Jia , Fang Feifei , Chen Jinhuang , Shu Xiaogang 
Published: October 2023

Abstract
Background: Research has indicated that long-term sleep disorders can lead to immune dysfunction and participate in the occurance and progression of tumors. However, the relationship between sleep disorders and colon cancer remains unclear. This study explored the specific mechanism through which sleep disorders promotes the proliferation and migration of colon cancer, with a focus on the neurotransmitter GABA.
Methods:Chronic sleep suppression mice model were used to investigate the effect of sleep disorder on tumors. We detected neurotransmitter levels in the peripheral blood of mice using ELISA. CCK-8 assay, colony formation assay, wound healing assay, and transwell assay were performed to investigate the effect of GABA on colon cancer cells, while immunofluorescence showed the distribution of macrophages in lung metastatic tissues. We isolated exosomes from a GABA-induced culture medium to explore the effects of GABA-induced colon cancer cells on macrophages. Gain- and loss-of-function experiments, luciferase report analysis, immunohistochemistry, and cytokine detection were performed to reveal the crosstalk between colon cancer cells and macrophages.
Results: Sleep disorders promote peripheral blood GABA level and colon cancer cell proliferation and migration. Immunofluorescence analysis revealed that GABA-induced colon cancer metastasis is associated with enhanced recruitment of macrophages in the lungs. The co-culture results showed that GABA intensified M2 polarization of macrophage induced by colon cancer cells. This effect is due to the activation of the macrophage MAPK pathway by tumor-derived exosomal miR-223-3p. Furthermore, M2-like macrophages promote tumor proliferation and migration by secreting IL-17. We also identified an endogenous miR-223-3p downregulation of the E3 ligase CBLB, which enhances the stability of cMYC protein and augments colon cancer cells proliferation and migration ability. Notably, cMYC acts as a transcription factor and can also regulate the expression of miR-223-3p.
Conclusion: Our results suggest that sleep disorders can promote the expression of miR-223-3p in colon cancer cells through GABA, leading to downregulation of the E3 ligase CBLB and inhibition of cMYC ubiquitination. Simultaneously, extracellular miR-223-3p promotes M2-like macrophage polarization, which leads to the secretion of IL-17, further enhancing the proliferation and migration of colon cancer cells.