bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring the Mechanism of Epimedium on Osteonecrosis of the Femoral Head through Network Pharmacology
Authors: Qi Yuxin , Hu Wei , Meng Chenyang , Jiang Enze , Ge Zhe , Wang Pei , Wang Jianzhong 
Published: October 2023

Abstract
BACKGROUND
Traditional Chinese Medicine (TCM) has consistently demonstrated promise in the prevention and management of ONFH. Epimedium, historically revered in Chinese medicinal recipes, has been utilized for mitigating conditions such as osteonecrosis and symptoms of kidney yang deficiency.
OBJECTIVE
This study aimed to forecast the drug targets and associated pathways through which Epimedium exerts its therapeutic effects against osteonecrosis of the femoral head. Additionally, we sought to delve deeper into its mechanism at the molecular level.
METHODS
In this study, we identified the active constituents and targets of Epimedium using the TCMSP database. The GEO database (with accession number GSE123568) was consulted to pinpoint targets associated with ONFH. Differential gene expression was visually represented through volcano and heat maps, crafted using the R software. GO and KEGG analyzes of these target genes were also subsequently performed using R software.
RESULTS
Five pivotal target genes were identified: PTGS2, KCNH2, BCL2L1, ABCG2, and E2F2. An exhaustive topological analysis was performed encompassing eight pathways and three genes.
CONCLUSION
This study elucidates the fundamental constituents, specific targets, and molecular pathways that underlie the effectiveness of Epimedium in the treatment of osteonecrosis of the femoral head.
Design of mock-ups for ultrasonic testing in civil engineering using numerical simulations
Authors: Dethof Fabian , Keßler Sylvia 
Published: October 2023

Abstract

The major objective when applying non-destructive testing (NDT) in civil engineering is the detection of defects such as honeycombs. Defects can impair the service life of structures and could lead in the worst case to fatal failures. All structures such as bridges, tunnels, locks etc. are unique objects with variation in geometry, dimensions, materials, environmental condition, load scenarios etc. Thus, the interpretation of NDT data is challenging and the validation of the NDT method, the training of inspectors and the reliability analysis of NDT rely on mock-ups with known defect situations mimicking the type of defect as realistic as possible. The considered defect sizes should cover the transition zone between detectable and non-detectable to properly evaluate the capability of the inspection system. However, knowledge about the limits of an inspection system is mostly non-existent. To overcome this limitation, this study applies numerical simulations for ultrasonic testing in reinforced concrete performed with the elastodynamic finite integration technique (EFIT) to identify this transition zone. First, the study shows the development and the validation of a numerical representation of concrete considering the implementation of a qualitatively realistic noise level. Additionally, the accurate representation of the sources during ultrasonic testing is confirmed by an investigation of the radiation characteristic for dry point contact ultrasonic transducers. The simulation outcome enabled the design of a mock-up for the detection of honeycombs applying ultrasonic testing considering major influencing factors. A case study completes the study demonstrating the applicability of the design scheme based on numerical simulation. In the real specimen, \(68\text{\%}\) of the implemented defects are detectable proving the effectiveness of the design method.
Absence of genetic structure among ecologically diverse populations indicate high plasticity in a pantropical seabird
Authors: Mazzochi Mariana Scain , Muraro Vitória , Fagundes Nelson Jurandi Rosa , Bugoni Leandro 
Published: October 2023

Abstract

Genotype and phenotype in mobile organisms can be defined by various factors such as environmental, biological and geographical. Brown noddies Anous stolidus are pan-tropical seabirds breeding at different times, with migratory and resident populations in six islands throughout 20° of latitude in the Southwestern Atlantic Ocean. If environmental heterogeneity plays a key role in their population biology, we would expect significant genetic structure and/or phenotypic variation among colonies. However, absence of genetic structure between phenotypically different populations could play a scenario of ecological plasticity. To test these hypotheses, we used a model-based integrative approach combining genetic (mtDNA and ultraconserved elements) and morphological data of the brown noddy (n = 122) along with environmental variables and isotopic niches. We uncovered low levels of genetic structure, with 16 haplotypes for mtDNA and a signal of an ancient population expansion. Ultraconserved elements indicated that all colonies belong to the same genetic population (K = 1) and revealed substantial endogamy. However, phenotype differed both by biometric measures and isotopic niches between most pairs of populations. Although individuals from the northernmost colony are larger than the others, they are genetically similar, indicating a wide reaction norm for this species. Our results indicate the Southwestern Atlantic populations of the brown noddy are panmictic, but ecologically and morphologically diverse.
Prognostic analysis of peritoneal washing cytology during interval debulking surgery in advanced ovarian cancer
Authors: Takasaki Kazuki , Ichinose Takayuki , Nishida Haruka , Miyagawa Yuko , Hashimoto Kei , Watanabe Saya , Takahashi Yuko , Hirano Mana , Hiraike Haruko , Sasajima Yuko , Nagasaka Kazunori 
Published: October 2023

Abstract

Background
Interval debulking surgery (IDS) following neoadjuvant chemotherapy is a treatment option for advanced ovarian cancer. Optimal surgery is required for better survival; however, while peritoneal washing cytology (PWC) has been identified as a prognostic factor, its comprehensive assessment during IDS remains unexplored. Therefore, we aimed to evaluate PWC efficacy during IDS, alongside other factors including residual disease and the modeled CA-125 ELIMination rate constant K (KELIM), by retrospectively reviewing the medical records of 25 patients with advanced ovarian cancer underwent neoadjuvant chemotherapy and IDS between January 2017 to June 2023.
Results
Twelve (48.0%) patients were PWC-positive, and the remainder were PWC-negative. PWC was performed at laparotomy during IDS, after which five (41.7%) PWC-positive and four (30.8%) PWC-negative patients received bevacizumab, an anti-VEGF monoclonal antibody, for maintenance treatment. Four (33.3%) PWC-positive and 10 (76.9%) PWC-negative patients received poly ADP-ribose polymerase inhibitors. In patients who received bevacizumab and poly ADP-ribose polymerase inhibitors, overall survival and progression-free survival did not significantly differ between those who were PWC-positive and PWC-negative (p = 0.27 and 0.20, respectively). Progression-free survival significantly differed between those with favorable and unfavorable CA-125 KELIM (p = 0.02). Multivariate analysis indicated that optimal surgery and favorable CA-125 KELIM were associated with better progression-free survival (p < 0.01 and 0.02, respectively), with only optimal surgery associated with better overall survival (p = 0.04).
Conclusions
A positive PWC at IDS was not associated with survival in advanced ovarian cancer. Our findings indicate that although PWC status at IDS should be one of the factors determining survival in patients with advanced ovarian cancer, CA-125 KELIM may be a more useful prognostic factor than PWC status due to recent improvements in maintenance treatment. Further studies are needed to validate these results, highlighting the potential importance of maintenance treatment after IDS and the need for further research to validate the clinical significance of a positive PWC.
Vascular endothelial growth factor receptor tyrosine kinase inhibitors associated hepatotoxicity: An Analysis of the FDA Adverse Event Reporting System
Authors: Zheng Hanrui , Zhou Kexun , Zheng Zhuoya , Xiao Min , Wen Feng , Wu Fengbo , Wu Bin 
Published: October 2023

Abstract
Vascular endothelial growth factor tyrosine kinase inhibitors (VEGFR-TKIs) are widely used in cancer. Despite the growing number of reported cases of hepatotoxicity resulting from the use of these drugs, there is a lack of information regarding the specific features and severity of hepatotoxicity associated with VEGFR-TKIs. We conducted disproportionality analyses using the Food and Drug Administration Adverse Event Reporting System (FAERS) to evaluate the potential association between hepatotoxicity and ten VEGFR-TKIs. The reporting odds ratios (ROR) and the information component (IC) were calculated to determine the presence of signals for severe liver injury. A total of 10,236 hepatotoxicity events cases with VEGF-TKIs as primary suspected drugs were collected. Apatinib, axitinib, cabozantinib, lenvatinib, pazopanib, regorafenib, sorafenib and sunitinib generated significant signals for liver injury. Significant signals indicating severe liver injury were detected with sorafenib, regorafenib, pazopanib, sunitinib and lenvatinib. The prognosis of drug-related liver injury was poor, sometimes resulting in death.
Epithelioid Hemangioma of the Nasal Cavity: A Diagnostic Challenge
Authors: Khan Adil Aziz , Ahuja Sana , Zaheer Sufian 
Published: October 2023

Abstract
Epithelioid hemangioma also known as angio-lymphoid hyperplasia with eosinophilia is a rare benign vascular neoplasm of unknown etiology. It always poses a diagnostic challenge for clinicians and is usually misdiagnosed as Kimura’s, IgG4-related disease or malignant vascular tumors. The present case report describes an extremely rare presentation of epithelioid hemangioma inside the left nasal cavity causing complete obstruction and nasal septal deviation towards the right side in a young male. The case highlights a non-conventional presentation of epithelioid hemangioma and the importance of histo-morphological features in the diagnosis of this entity.
Perspectives of key interest groups regarding Supervised Consumption Sites (SCS) and novel Mobile Overdose Response Services (MORS): A qualitative Canadian study.
Authors: Seo Boogyung , Rioux William , Teare Adrian , Rider Nathan , Jones Stephanie , Taplay Pamela , Ghosh Sumantra Monty 
Published: October 2023

Abstract

Background
Supervised consumption sites (SCS) are proven effective for preventing drug poisoning deaths during the opioid epidemic. Despite their successes, SCS still contend with structural and logistical barriers that limit their accessibility. Mobile Overdose Response Services (MORS) are novel technologies reminiscent of informal “spotting” methods that may address some of the limitations of SCS. Here, we strove to qualitatively examine the factors that may encourage or deter utilization of MORS compared to SCS.
Methods
A total of 52 participants across Canada were recruited using convenience, purposive, and snowball methods. A semi-structured interview was conducted by evaluators from a third-party research organization. Inductive thematic analysis informed by grounded theory was utilized to identify the major themes.
Results
Participants viewed MORS as an opportunity to consume substances without being hindered by fear of apprehension/criminalization, stigma, and invasion of privacy. They also noted that MORS provided more flexibility for clients who could not easily access the physical sites (e.g., due to location, weather concerns, time of day). There was some ambivalence as to whether MORS or physical sites provided more social connection and relationship building. Some viewed physical SCSs to be safer due to perceived shorter overdose response times.
Conclusion
In sum, participants viewed SCS and MORS as filling different needs and gaps. This study adds to a growing body of literature which informs how virtual services can serve as useful adjunct services to SCS.
Multilayer Meta-Surface Low-Profile Antenna Using Artificial Intelligence Processing for 5G and optical Communication
Authors: Rentapalli Vanitha Rani , Roy Bappadittya 
Published: October 2023

Abstract
In this article, a low-profile high-gain meta-surface artificial intelligence process-based broadband microstrip patch antenna, for 5G wireless communications is presented. The FR4 epoxy substrate material with a dielectric constant of 4.4 and a thickness of 1.6, is used for the antenna to operate at a 20 GHz resonating frequency. The proposed antenna is simulated using the HFSS to design a simple antenna with a low profile and proper operational characteristics. Moreover, a new type of meta surface antenna with a modified patch is elongated on the surface of the antenna. The simulation of the proposed antenna highlights that the studied antenna has a maximum reflection coefficient of -34 dB, with a bandwidth of 17GHz to 23GHz. The perfect results, with a low profile and antenna size of 1.33λ0 × 1.33λ0 × 0.106 λ0, were measured and fabricated. The meta surface appeared in the form of a mesh type of structure, fed by a microstrip patch antenna with coaxial feed cells, revealing a good arrangement with the simulated one. Moreover, the meta surface with artificial technology has empowered the arrival of new ideas and explanations in the strategy of antennas for the control of electromagnetic waves. The measured results show that the proposed antenna has the perfect axial ratio, along with a 10dB impedance bandwidth achieved with a valued stable gain of 9 to 10 dBi.
A novel Magnetic Fe-Co-Zn composite as an effective and recyclable adsorbent for dyes adsorption from wastewater
Authors: Ren Zongli , Zhang Weiwei , Ma Xin , Yang Xuan , Fang Yali 
Published: October 2023

Abstract
Removal of pollutants from wastewater has always been a concern. Adsorbent materials formed on the basis of activated carbon are promising adsorbents for the removal of organic pollutants from the aqueous phase as a result of their rich pore structure and high chemical activity. However, the majority of ACs exist as micro-crystalline powders, making them complicated to segregate and recycle. Therefore, in this paper, a new magnetic adsorbent (AC-CN-Fe-Co-Zn) doped with iron, cobalt and zinc was prepared by impregnation and calcination for the adsorption of Methylene blue (MB) and Acid blue (AB80). The prepared AC-CN-Fe-Co-Zn was characterized by SEM, TEM, XRD, BET, and Raman. For the ensuing series of experiments, the effects of pH, binding time, temperature and initial concentration on the adsorption behaviors of MB and AB80 by AC-CN-Fe-Co-Zn were investigated. The results demonstrate that the inorganic ions in the magnetic material display excellent dispersion on the surface of carbon material and the pseudo-second-order kinetic model is an accurate representation of the adsorption data. The thermodynamic adsorption curves are consistent with the Langmuir model. The adsorption mechanism involves the critical contribution of hydrogen bonding interaction, π-π interaction, pore adsorption, and electrostatic attraction. The maximum adsorption capacities of MB and AB80 were 83.40 mg/g and 35.36 mg/g respectively. Following 5 iterations of utilization, the eradication effectiveness for MB and AB80 were 79.82% and 61.54% respectively. The results confirmed that the comprehensive properties of AC-CN-Fe-Co-Zn make it an excellent and efficient adsorbent for the removal of dyes. This paper provides a new sight on the synthesis of high efficiency adsorbents for dyes pollutant separation.
Assessment of the health impacts of air pollution exposure in East African Countries
Authors: Baharane Valérien , Shatalov Andrey Borisovich 
Published: October 2023

Abstract
The health effects of air pollution remain a public concern worldwide. Using data from the Global Burden of Disease 2019 report, we statistically analysed total mortality, Disability-Adjusted Life Years (DALY), and Years of Life Lost (YLL) attributable to air pollution in eight East African countries between 1990 and 2019. We acquired ambient ozone (O3), PM2.5 concentrations and Household Air Pollution (HAP) from the solid fuel from the State of Global Air report. The multilinear regression model was used to evaluate the predictability of YLLs by the air pollutants. We estimated the ratio rate for each health burden attributable to air pollution to compare the country's efforts in the reduction of air pollution health burden. This study found that the total number of deaths attributable to air pollution decreased by 14.26% for 30 years. The drop came from the reduction of 43.09% in mortality related to Lower Respiratory tract Infection (LRI). However, only five out of eight countries managed to decrease the total number of deaths attributable to air pollution with the highest decrease observed in Ethiopia (40.90%), and the highest increase in Somalia (67.49%). The linear regression model showed that HAP is the pollutant of the most concern in the region, with a 1% increase in HAP resulting in a 31.06% increase in regional YLL (R2 = 0.93; p < 0.05). With the increasing ground-level ozone, accompanied by the lack of adequate measures to reduce particulate pollutants, the health burdens attributable to air pollution are still a threat in the region.
An Ensemble Novel Deep Learning Technique for Chest Radiograph-Based Pneumonia Prediction
Authors: J PREMALATHA , D KAYETHRI 
Published: October 2023

Abstract
Pneumonia continues to be a prominent treatable cause of global mortality, stressing the importance of early identification to enable prompt intervention. Chest X-rays (CXRs) are an essential diagnostic tool, however determining their exact interpretation is still very difficult. By addressing both medical experts and individuals who are new to the area, the proposed work aims to improve prediction of pneumonia. The Synthetic Minority Over-sampling Technique has been utilised to cope with imbalanced dataset because the used dataset does not have balanced distribution among all classes. A pneumonia prediction model that makes use of convolutional neural networks including CustomVGG19, CustomResNet-50 and CustomDenseNet121 and the proposed ensemble model to improve diagnosis of pneumonia has been proposed. These models are trained and improved in experiments. The optimization of each model's performance was achieved through the systematic exploration of diverse configurations and hyperparameters. The ultimate outcomes were derived by employing the ensemble technique, which involved amalgamating the predictions of CNN models during the analysis. Results demonstrate the superiority of the proposed model, which achieved a 97.68% prediction accuracy.
A hybrid Gaussian Mixture/DSMC approach to study the Fourier thermal problem
Authors: Nejad Shahin Mohammad , Peters Frank , Nedea Silvia , Frijns Arjan , Smeulders David 
Published: October 2023

Abstract
In rarefied gas dynamics scattering kernels deserve special attention since they contain all the essential information about the effects of physical and chemical properties of the gas-solid surface interface on the gas scattering process. However, to study the impact of the gas-surface interactions on the large-scale behavior of fluid flows, these scattering kernels need to be integrated in larger-scale models like Direct Simulation Monte Carlo (DSMC). In this work, the Gaussian mixture (GM) model, an unsupervised machine learning approach, is utilized to establish a scattering kernel for monoatomic (Ar) and diatomic (H\textsubscript{2}) gases directly from Molecular Dynamics (MD) simulations data. The GM scattering kernel is coupled to a pure DSMC solver to study isothermal and non-isothermal rarefied gas flows in a system with two parallel walls. To fully examine the coupling mechanism between the GM scattering kernel and the DSMC approach, a one-to-one correspondence between MD and DSMC particles is considered here. Benchmarked by MD results, the performance of the GM-DSMC is assessed against the Cercignani-Lampis-Lord (CLL) kernel incorporated into DSMC simulation (CLL-DSMC). The comparison of various physical and stochastic parameters shows the better performance of the GM-DSMC approach. Especially for the diatomic system, the GM-DSMC outperforms the CLL-DSMC approach. The fundamental superiority of the GM-DSMC approach confirms its potential as a multi-scale simulation approach for accurately measuring flow field properties in systems with highly nonequilibrium conditions.
Spillover effects of COVID-19 on USA Education Group stocks
Authors: Fernandes Leonardo H S , de Araujo Fernando H. A. , Silva José W. L. , Leite Urbanno P. S. , Muniz Lucas M. , Fernandes José P. V. , Paiva Ranilson O. A. , Pinto Ibsen M. B. S. , Taba Benjamin Miranda 
Published: October 2023

Abstract

We explore the price dynamics of 16 representative records of USA Education Group stocks, encompassing two non-overlapping periods (before, during and after COVID-19). Based on information theory and cluster analysis techniques, our study provides insights into the disorder, predictability, efficiency, similarity and resilience/weakness considering the most diverse financial stakeholders. Our results show that nine assets were weak during the COVID-19 crisis (AACG, APEI, ATGE, CHG, LINC, LRN, PRDO, STRA and UTI). In this way, the most significant negative impact on their price dynamics was AACG (−6.617%), followed by LINC (−5.236%). Otherwise, the most significant positive effects on their price dynamics resulting from the COVID-19 crisis were TWOU (5.973%) and EDU (2.612%). Our findings contribute significantly to understanding price dynamics in the education sector, encompassing non-crisis and crisis periods and provide valuable information for financial risk management, highlighting the importance of considering financial assets’ efficiency and resilience/weakness during economic turbulence, such as the COVID-19 crisis.
Outcome of Remdesivir on Mortality in Patients with COVID-19 Pneumonia
Authors: Yayan Josef , Rasche Kurt , Windisch Wolfram , Franke Karl-Josef 
Published: October 2023

Abstract
Introduction:
Coronavirus disease 2019 (COVID-19) pneumonia, caused by SARS-CoV-2, has become a major health issue worldwide. Of all the available antiviral agents, remdesivir, an antiviral nucleoside analog, has the highest anti-SARS-CoV-2 activity. However, relevant studies have reported that remdesivir provides only minor additional benefits in patients with COVID-19 pneumonia. Here, we assessed the effectiveness of remdesivir on the survival of patients with COVID-19 pneumonia.
Methods
In this single-center, retrospective study, we evaluated data of patients hospitalized for COVID-19 pneumonia at the Lüdenscheid Clinic in Germany from January 1, 2020, to December 31, 2020. Specifically, we compared mortality, length of hospital stay, intensive care unit use, laboratory test results, symptoms, and comorbidities among COVID-19 pneumonia patients who received and did not receive remdesivir.
Results
Throughout 2020, 154 patients with COVID-19 pneumonia were hospitalized at the study hospital. Of these, 38 (24.7%) were treated with remdesivir; these patients were also significantly (approximately 10 years) older than those who did not receive remdesivir (P = 0.0011). Of all 26 deaths, only 10 (38.5%) were noted in remdesivir recipients; this indicated that remdesivir effectiveness is 73.7% in patients with COVID-19 pneumonia. Remdesivir significantly reduced the length of hospital stay until 1 week after treatment initiation (P = 0.0041). Compared with nonrecipients, remdesivir recipients had a significantly higher respiratory distress prevalence (21.4%; P = 0.0288) as well as a significantly higher prevalence of neurological disorders (n = 9; P = 0.0025) and mental (n = 6; P = 0.0048) disorders.
Conclusion
In patients with COVID-19 pneumonia, remdesivir has low (73.7%) effectiveness against mortality.