bluuebunny/crossref_metadata_2025 huggingface dataset:
Study on the mechanism of dNK cells dysfunction resulting from the IDO downregulation in dMDSCs with Toxoplasma gondii infection
Authors: Hu Xuemei , Wang Yu , Zhao Xiaoyue , Li Zhidan , Wang Wenxiao , Jiang Yuzhu , Zhang Haixia , Liu Xianbing , Ren Yushan , Xu Xiaoyan
Published: October 2023

Myeloid-derived suppressor cells (MDSCs) play a crucial role in maintaining maternal-fetal tolerance for pregnancy by expressing immune suppressive molecules, such as indoleamine 2,3-dioxygenase (IDO), arginase-1 (Arg-1) and IL-10. The expression of IDO was downregulated in dDCs after Toxoplasma gondii (T. gondii) infection. However, whether T. gondii affected IDO expression in dMDSCs and then induced dNK cells dysfunction were still unclear. The human infected dMDSCs were co-cultured with purified dNK cells in vitro. Results showed that IDO expression in infected dMDSCs was significantly increased in the mRNA level but obviously decreased in the protein level. The transcriptional levels of IDO in dMDSCs were up-regulated through STAT3/p52-RelB pathway and IDO expression was decreased by degradation due to the increase of SOCS3 expression induced by T. gondii infection. In vivo, we found that adverse pregnancy outcomes of IDO−/− infected mice by T. gondii infection were more severe than those of WT mice and were significantly improved after treatment with exogenous kynurenine (Kyn). The reduction of IDO in dMDSCs induced by T. gondii infection lastly resulted in the downregulation of TGF-β and IL-10 expression in dNK cells through Kyn/AhR/SP1 signaling pathway, eventually leading to the dysfunction of dNK cells.
Global patterns of soil organic carbon dynamics in the 20–100 cm soil profile for different ecosystems: A global meta-analysis
Authors: Wang Haiyan , Yin Yulong , Cai Tingya , Tian Xingshuai , Chen Zhong , He Kai , Wang Zihan , Gong Haiqing , Miao Qi , Wang Yingcheng , Chu Yiyan , Zhang Qingsong , Zhuang Minghao , Cui Zhenling
Published: October 2023

Determining the dynamics of organic carbon in subsoil (SOC, depth of 20–100 cm) is important with respect to the global C cycle and warming mitigation. However, there is still a huge knowledge gap in the dynamics of spatiotemporal changes in SOC in this layer. We developed a new method to spatially resolve soil β values for global ecosystems (cropland, grassland, and forestland) and SOC dynamics at high resolution. We first quantified the spatial variability characteristics of these values and driving factors by analyzing 1221 soil profiles (0–1 m) of globally distributed field measurements and mapped the grid-level soil β values. Then we evaluated the SOC dynamics in different soil layers to determine the subsoil C stocks of various ecosystems. The subsoil SOC density values of cropland, grassland, and forestland were 63.8, 83.3, and 100.4 Mg ha–1, respectively. SOC density decreased with increasing depth, ranging from 5.6 to 30.8 Mg ha–1 for cropland, 7.5 to 40.0 Mg ha–1 for grassland, and 9.6 to 47.0 Mg ha–1 for forestland. The global subsoil SOC stock was 912 Pg C, in which an average of 54% resided in the top 0–100 cm of the soil profile. Our results provide insights into subsoil dynamics and the untapped potential to enhance global SOC sequestration in terrestrial ecosystems toward climate neutralization.
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

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

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

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

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

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

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

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

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

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

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

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

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

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.
Capitalist Diversity, Legal Origins, and Non-Independent Pasts: The Effects of Institutional Settings on Economic Performance
Authors: Halili Bernadette Louise , Gonzalez Carlos Rodriguez
Published: October 2023

This study explores the role of institutional settings, in their path dependence, stability and complementarity, in determining aggregate economic performance at the country-level. Cross-country differences in institutional design are operationalised in this study as national institutional settings: firstly as institutional configurations in the Varieties of Capitalism framework and secondly, as the interaction between formal institutions such as a modern capitalist state’s legal origins and informal institutions such as its non-independent past. Empirical findings from a panel data of 24 countries for the period 1995–2019 show that national institutional settings such as family market economies, mixed market economies, and the interaction between a country’s non-independent past and transplanted French legal origin, have significant and negative relationships with economic performance. Policy recommendations focus on addressing adverse macroeconomic consequences brought on by the predominance of entrenched elite groups, traditional patron-client relationships, and detrimental patronage networks.
JEL Classifications: F54 Colonialism; Imperialism; Postcolonialism, O43 Institutions and Growth, P16 Political Economy, P48 Political Economy; Legal Institutions; Property Rights; Natural Resources; Energy; Environment; Regional Studies
Cardiopulmonary Exercise Test to Detect Cardiac Dysfunction from Pulmonary Vascular Disease
Authors: Alotaibi Mona , Yang Jenny Z. , Papamatheakis Demosthenes G. , McGuire W. Cameron , Fernandes Timothy M. , Morris Timothy A.
Published: October 2023

Background
Cardiac dysfunction from pulmonary vascular disease causes characteristic findings on cardiopulmonary exercise testing (CPET). We tested the accuracy of CPET for detecting inadequate stroke volume (SV) augmentation during exercise, a pivotal manifestation of cardiac limitation in patients with pulmonary vascular disease.
Methods
We reviewed patients with suspected pulmonary vascular disease in whom CPET and right heart catheterization (RHC) measurements were taken at rest and at anaerobic threshold (AT). We correlated CPET-determined O2·pulseAT/O2·pulserest with RHC-determined SVAT/SVrest. We evaluated the sensitivity and specificity of O2·pulseAT/O2·pulserest to detect SVAT/SVrest below the lower limit of normal (LLN). For comparison, we performed similar analyses comparing echocardiographically-measured peak tricuspid regurgitant velocity (TRVpeak) with SVAT/SVrest.
Results
From July 2018 through February 2023, 83 simultaneous RHC and CPET were performed. Thirty-six studies measured O2·pulse and SV at rest and at AT. O2·pulseAT/O2·pulserest correlated highly with SVAT/SVrest (r = 0.72, 95% CI 0.52, 0.85; p < 0.0001), whereas TRVpeak did not (r = -0.09, 95% CI -0.47, 0.33; p < 0.69). The AUROC to detect SVAT/SVrest below the LLN was significantly higher for O2·pulseAT/O2·pulserest (0.92, SE 0.04; p = 0.0002) than for TRVpeak (0.69, SE 0.10; p = 0.12). O2·pulseAT/O2·pulserest of less than 2.6 was 92.6% sensitive (95% CI 76.6%, 98.7%) and 66.7% specific (95% CI 35.2%, 87.9%) for deficient SVAT/SVrest.
Conclusions
CPET detected deficient SV augmentation more accurately than echocardiography. CPET-determined O2·pulseAT/O2·pulserest may have a prominent role for noninvasive screening of patients at risk for pulmonary vascular disease, such as patients with persistent dyspnea after pulmonary embolism.
Improving ML Accuracy in SQL Injection Detection using NLP and Feature Engineering.
Authors: Jaradat Majdi , Rattrout Amjad , Jayousi Rashid
Published: October 2023

This research proposes the DSQLIA model, which enhances the accuracy of machine learning (ML) algorithms in detecting SQL injection attacks. Traditional rule-based and signature-based methods face limitations in effectively identifying evolving attack techniques. To address this, DSQLIA employs feature engineering and Natural Language Processing (NLP). Relevant features capturing the unique characteristics of SQL injection attacks are identified and created through feature engineering. NLP techniques are applied to analyze the textual content of SQL queries and extract meaningful information for distinguishing between legitimate and malicious queries. The DSQLIA model evaluates different ML algorithms, including decision trees, support vector machines (SVM), and artificial neural networks (ANN), on a dataset. Various performance metrics such as accuracy, precision, recall, and F1-score are used to assess algorithm effectiveness. Results show that the SVM algorithm achieves the highest accuracy of 0.994, followed by the decision tree with 0.975, and the ANN with 0.966. This highlights the improved performance of SVM in accurately classifying SQL queries. By combining feature engineering and NLP techniques, the DSQLIA model enhances ML accuracy in SQL injection detection, offering a valuable approach to mitigating the risks posed by these vulnerabilities in web applications.
Disulfidptosis-related lncRNA signatures in lung adenocarcinoma: Predicting prognosis and evaluating the tumor immune microenvironment
Authors: Song Zipei , Cao Xincen , Wang Xiaokun , Li Yuting , Zhang Weiran , Wang Yuheng , Chen Liang
Published: October 2023

Background
As a novel form of regulated cell death (RCD), disulfidptosis has been reported recently, which brought the significant probability in better understanding for pathogenesis and therapeutic strategies of tumors. Long non-coding RNAs (LncRNAs) regulate the viability of tumor cells by engaging with a range of targets, including DNA, RNA, and proteins. Nonetheless, the understanding about the prognostic value of disulfidptosis-related LncRNAs (DRlncRNAs) in lung adenocarcinoma (LUAD) remains incomplete. Therefore, our study aimed at establishing a prognostic model for LUAD patients based on DRLncRNAs.
Methods
RNA-seq data and corresponding clinical information were acquired from The Cancer Genome Atlas (TCGA) database, enabling the identification of DRlncRNAs. Subsequently, a prognostic model was formulated for LUAD by utilizing a series of analyses including univariate COX, LASSO, and multivariate COX regression. Patients were then categorized into two groups with distinct level of DRLS score, and subsequently subjected to the consensus clustering analysis for assigning LUAD patients to distinct subtypes by employing the DRlncRNAs. Subsequent studies investigated disparities among groups with distinct risk and molecular subtypes in terms of overall survival (OS), functional enrichment, the tumor immune microenvironment (TIME), somatic mutations, and drug sensitivity. Finally, in vitro experiments were conducted to validate the LUAD cellular proliferation and migratory behavior upon GSEA knockdown.
Results
Using the prognostic model consists of 5 DRlncRNAs (AL365181.2, GSEC, AC093673.1, AC012615.1, AL606834.1), the low-risk group exhibited a markedly superior survival in comparison to the high-risk group. The significant differences were observed among patients from different risk groups in OS, immune cell infiltration, immune checkpoint expression, immunotherapy response, and mutation landscape. Experimental results from cellular studies demonstrate the knockdown of lncRNA GSEC leading to a significant reduction in the proliferation and migration abilities of LUAD cells.
Conclusion
Our prognostic model, constructed using 5 DRlncRNAs, exhibited the capacity to independently predict the survival of LUAD patients, providing the potentially significant assistance in prognosis prediction, and treatment effects optimization. Moreover, our study established a foundation for further research on disulfidptosis in LUAD and proposed new perspectives for the treatment of LUAD.
Hydraulic resistance of three-dimensional pial perivascular spaces in the brain
Authors: Boster Kimberly A. S. , Sun Jiatong , Shang Jessica K. , Kelley Douglas H. , Thomas John H.
Published: October 2023

Background Perivascular spaces (PVSs) carry cerebrospinal fluid (CSF) around the brain, facilitating healthy waste clearance. Measuring those flows in vivo is difficult, and often impossible, because PVSs are small, so accurate modeling is essential for understanding brain clearance. The most important parameter for modeling flow in a PVS is its hydraulic resistance, defined as the ratio of pressure drop to volume flow rate, which depends on its size and shape. In particular, the local resistance per unit length varies along a PVS and depends on variations in the local cross section.
Methods Using segmented, three-dimensional images of pial PVSs in mice, we performed fluid dynamical simulations to calculate the resistance per unit length. We applied extended lubrication theory to elucidate the difference between the calculated resistance and the expected resistance assuming a uniform flow. We tested four different approximation methods, and a novel correction factor to determine how to accurately estimate resistance per unit length with low computational cost. To assess the impact of assuming unidirectional flow, we also considered a circular duct whose cross-sectional area varied sinusoidally along its length.
Results We found that modeling a PVS as a series of short ducts with uniform flow, and numerically solving for the flow in each, yields good resistance estimates at low cost. If the second derivative of area with respect to axial location is less than 2, error is typically less than 15%, and can be reduced further with our correction factor. To make estimates with even lower cost, we found that instead of solving for the resistance numerically, the well-known resistance of a circular duct could be scaled by a shape factor. As long as the aspect ratio of the cross section was less than 0.7, the additional error was less than 10%.
Conclusions Neglecting off-axis velocity components underestimates the average resistance, but the error can be reduced with a simple correction factor. These results could increase the accuracy of future models of brain-wide and local CSF flow, enabling better prediction of clearance, for example, as it varies with age, brain state, and pathological conditions.
Microbiome characterization of biopsies from lesional skin in Spanish patients with hidradenitis suppurativa shows an abundance of Mycoplasma and a decrease in Cutibacterium species
Authors: Romaní Jorge , Rosés Carles , Fernández-Vela Javier , Muñoz-Santos Carlos , Barceló Anna , Guilabert Antonio
Published: October 2023

Hidradenitis suppurativa (HS) is a chronic inflammatory skin disorder characterized by nodules, abscesses, and tunnels. Understanding the role of the skin microbiome in HS pathogenesis is crucial for developing targeted therapies. Previous studies have reported dysbiosis in HS-affected skin. This study aimed to investigate the microbiome in lesional skin biopsies of HS patients compared to perilesional healthy skin and healthy controls. Additionally, we sought to identify potential differences in the microbiome based on disease endotype, clinical variables, and lesion type. We collected skin samples from 30 HS patients and 20 healthy controls. Participants were categorized into follicular and inflammatory endotypes. Skin biopsies were obtained from lesional and perilesional areas of patients, and from anatomically matched areas in healthy controls. The microbiome was characterized using 16S rRNA gene sequencing. Clinical variables were recorded, including age, sex, body mass index, smoking habit, age of disease onset, family history, and lesion type. The microbiome composition differed significantly between lesional, perilesional, and healthy skin. Lesional skin showed higher abundance of Mycoplasma (P = 0,013) and Bacillus (p < 0,01), while Propionibacterium was more prevalent in healthy controls (p < 0,01). No significant differences were observed in the microbiome composition based on endotypes or lesion types. However, the severity of HS was associated with decreased Propionibacterium abundance. Our study provides novel insights into the microbiome variations in HS-affected skin in a Mediterranean population. The dysbiosis observed, particularly the higher abundance of Mycoplasma, may play a role in the inflammatory process of HS. Understanding the microbiome's impact on HS pathogenesis could lead to innovative treatments aimed at restoring microbiological balance and controlling inflammation. Propionibacterium's lower abundance in severe HS suggests its potential as a therapeutic target. Further investigations into microbiome manipulation as a potential therapeutic approach are warranted, particularly in early-stage lesions with potential for reversibility.
Predicting Highlights in Badminton Matches: A Knowledge- Aware Model Analysis of Rally-by-Rally Statistics
Authors: Liu Xingyu , Ren Hao , Chen Tao
Published: October 2023

In the realm of sports analytics, predicting highlights in badminton matches plays a crucial role in enhancing fan engagement and broadcasting. This study introduces a Knowledge-Aware Model (KAM) that integrates domain-specific knowledge and data-driven techniques to predict game highlights. Analyzing an extensive dataset from the 2017 World Championships and the 2018 Thomas Cup, comprising over 5,180 individual rallies from 140 singles matches, the KAM considers serving and receiving zones, technical stroke nuances, total strokes, rally time and point outcomes. Comparative evaluations against baseline models and state-of-the-art approaches demonstrate the KAM's superiority, achieving an F1-score of 0.793. By combining comprehensive match statistics with rally-specific data, the KAM offers an innovative approach to predicting highlights, with implications extending beyond badminton to multimedia analysis and recommendation systems. This research presents a pivotal step towards more precise and engaging sports analytics.
Microtubule Affinity-Regulating Kinase family members differently affect tau phosphorylation and toxicity in a Drosophila model
Authors: Sultanakhmetov Grigorii , Kato Iori , Asada Akiko , Saito Taro , Ando Kanae
Published: October 2023

Accumulation of abnormally phosphorylated tau is thought to cause neuronal loss in Alzheimer's disease (AD) and related neurodegenerative disorders. Tau phosphorylation at Ser262 and Ser356 in the KXGS motifs of microtubule-binding repeats plays a critical role in its physiological function and AD pathogenesis. Members of the Microtubule Affinity-Regulating Kinase family (MARK1-4) phosphorylate these residues and are considered potential therapeutic targets for AD. However, whether and how each member affects tau toxicity in vivo is unclear. By using a Drosophila model of tau toxicity, we compared the effect on tau-induced neurodegeneration among MARKs. We found that MARK4, but not other MARKs, promotes tau accumulation. All MARKs increased tau phosphorylation at Ser262, and MARK1, MARK2, and MARK4 increased tau phosphorylation at Ser356. The levels of AT8-tau were decreased with co-expression of MARK2 and MARK3 but not with MARK1 and MARK4, and tau phosphorylation at Ser396 was elevated only with MARK4. MARK4 enhanced tau-induced neurodegeneration more than other MARKs. Our results suggest that MARK4 promotes tau accumulation via enhancing additional phosphorylation and that inhibition of MARK4 may be an effective treatment for AD and related tauopathies.
Incorporating space in hierarchical capture mark recapture models: can we better capture variance?
Authors: Drift Anne-Merel R. van der , Leirs Herwig , Mariën Joachim , Sabuni Christopher , Mulungu Loth , Kirkpatrick Lucinda
Published: October 2023

1. Capture mark recapture (CMR) models allow the estimation of various components of animal populations, such as survival and recapture probabilities and often assume homogenous detection of individuals. However, individual detection probability is not heterogeneous for a range of different reasons, for example due to the location and environmental context of traps within an individual’s home range or individual characteristics such as age. Spatial CMR models incorporate this heterogeneity by including the spatial coordinates of traps, data which is often already collected in standard CMR approaches. 2. We compared how the inclusion of spatial data changed estimations of survival, detection probability, and the probability of seroconversion to an arenavirus, in the multimammate mouse. We used a Bayesian framework to develop non spatial, partially spatial and fully spatial models alongside multievent CMR models and used simulations to test whether parameters were sensitive to starting parameters. 3. We found that bias and precision were similar for all three different model types, with simulations always returning estimates within the 95% credible intervals. When applied to field data, our models predicted a lower survival of individuals exposed to Morogoro virus (MORV) in non spatial models while survival was similar in spatially explicit models. 4. We suggest that spatial coordinates of traps should always be recorded when carrying out CMR and spatially explicit analysis should be used whenever possible, particularly as incorporating spatial variation may capture ecological processes without the need for additional data collection that can be challenging to acquire with wild animals.
Prognostic and Immunotherapeutic Potential of Regulatory T Cell- Associated Signature in Ovarian Cancer
Authors: Liu Yinglei , Shan Feng , Sun Ying , Kai Haili , Cao Yang , Huang Menghui , Liu Jinhui , Zhang Pengpeng , Zheng Yanli
Published: October 2023

Background: Immunosuppression is a key feature of cancer, promoting tumor growth and progression. Regulatory T cells (Tregs) are a specialized subset of T lymphocytes that mediate immunosuppression in cancer. However, the role of Treg-related genes in ovarian cancer (OC) remains largely unexplored.
Methods: To identify marker genes related to Tregs in OC, we utilized scRNA-seq analysis. Treg scores were then constructed using single-sample gene set enrichment analysis (ssGSEA) based on these markers. To identify gene modules with the strongest correlation with Treg scores in bulk RNA-seq data, we employed the Weighted Gene Co-expression Network Analysis (WGCNA) algorithm. Multiple machine learning algorithms were then used to construct risk models with superior predictive performance, which were validated using external independent datasets. A risk score was developed for each OC sample based on the optimal model to evaluate differences in prognosis, immune infiltration, pathway activity, and immunotherapy between high and low-risk groups.
Results: We identified 365 genes governing Treg functionality utilizing the WGCNA algorithm, and determined that 70 of these genes were linked to the prognosis of OC based on univariate Cox analysis. By employing a fusion of the Random Survival Forest (RSF) and Lasso algorithms, we developed a risk model showcasing the most elevated c-index derived from the allocated risk scores. The model's efficacy was substantiated through the utilization of four external datasets. Our analysis unveiled that the low-risk cohort exhibited a more favorable prognosis, augmented infiltration of immune cells, elevated expression of immune checkpoints, as well as noteworthy disparities in pathway enrichment and immunotherapy efficacy among the distinct risk groups.
Conclusion: Our findings provide new insights into the role of Treg cells in the development and progression of OC and highlight the potential for developing novel Treg-targeted therapies for the treatment of this disease.
Virtual Reality, Face-To-Face, and 2D Video Conferencing in Group Work: A Comparative Study on Fatigue, Creativity, Flow, and Interactions
Authors: Macchi Gregorio , De Pisapia Nicola
Published: October 2023

This study investigates the impact of different interaction settings— two-dimensional Video Conferencing (VC), Face-To-Face (FTF), and Virtual Reality (VR)—on group dynamics, cognitive performance, and aspects of well-being in a professional context. Utilizing a sample of 40 participants from a large Italian electricity transmission company, the study employs a within-subjects design to explore various metrics, including flow, creativity, fatigue and aspects of interaction. The results indicate that FTF interactions are optimal for idea generation and task absorption. VR, although initially more fatiguing for first-time users, fosters a more collaborative and peaceful environment, encouraging participants to engage more openly with each other. VC was found to be the least fatiguing, but also the least engaging in terms of task absorption and idea generation. Additionally, age-related differences were observed, particularly in the perception of motivational and emotional fatigue in the VR setting. The study provides empirical evidence supporting the integration of VR in professional settings for specific types of meetings, while also highlighting the limitations and areas for future research. These findings have implications for organizational well-being, cognitive ergonomics, and the evolving landscape of remote work technologies.