bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fluoride releasing in polymer blends of poly(ethylene oxide) and poly(methyl methacrylate)
Authors: Wang Tianxiao , Li Menghong , Gu Ziyan , Qu Chengjuan , Segervald Jonas , Salh Roushdey , Wågberg Thomas , Wang Jia , Kou Wen 
Published: February 2024

Introduction: Polymethyl methacrylate is a polymer commonly used in clinical dentistry, including denture bases, occlusal splints and orthodontic retainers.Methods: To augment the polymethyl methacrylate-based dental appliances in counteracting dental caries, we designed a polymer blend film composed of polymethyl methacrylate and polyethylene oxide by solution casting and added sodium fluoride.Results: Polyethylene oxide facilitated the dispersion of sodium fluoride, decreased the surface average roughness, and positively influenced the hydrophilicity of the films. The blend film made of polymethyl methacrylate, polyethylene oxide and NaF with a mass ratio of 10: 1: 0.3 showed sustained release of fluoride ions and acceptable cytotoxicity. Antibacterial activity of all the films to Streptococcus mutans was negligible.Discussion: This study demonstrated that the polymer blends of polyethylene oxide and polymethyl methacrylate could realize the relatively steady release of fluoride ions with high biocompatibility. This strategy has promising potential to endow dental appliances with anti-cariogenicity.
The use of ChatGPT in teaching and learning: a systematic review through SWOT analysis approach
Authors: Mai Duong Thi Thuy , Da Can Van , Hanh Nguyen Van 
Published: February 2024

IntroductionThe integration of ChatGPT, an advanced AI-powered chatbot, into educational settings, has caused mixed reactions among educators. Therefore, we conducted a systematic review to explore the strengths and weaknesses of using ChatGPT and discuss the opportunities and threats of using ChatGPT in teaching and learning.MethodsFollowing the PRISMA flowchart guidelines, 51 articles were selected among 819 studies collected from Scopus, ERIC and Google Scholar databases in the period from 2022-2023.ResultsThe synthesis of data extracted from the 51 included articles revealed 32 topics including 13 strengths, 10 weaknesses, 5 opportunities and 4 threats of using ChatGPT in teaching and learning. We used Biggs’s Presage-Process-Product (3P) model of teaching and learning to categorize topics into three components of the 3P model.DiscussionIn the Presage stage, we analyzed how ChatGPT interacts with student characteristics and teaching contexts to ensure that the technology adapts effectively to diverse needs and backgrounds. In the Process stage, we analyzed how ChatGPT impacted teaching and learning activities to determine its ability to provide personalized, adaptive, and effective instructional support. Finally, in the Product stage, we evaluated how ChatGPT contributed to student learning outcomes. By carefully considering its application in each stage of teaching and learning, educators can make informed decisions, leveraging the strengths and addressing the weaknesses of ChatGPT to optimize its integration into teaching and learning processes.
Association between urinary organophosphate ester metabolite exposure and thyroid disease risk among US adults: National Health and Nutrition Examination Survey 2011-2014
Authors: Lin Yuxin , Lin Ruipeng , Wang Weikang , Xie Manling , Li Yun , Zhang Qian 
Published: February 2024

BackgroundOrganophosphate esters (OPEs) may interfere with thyroid function, but the relationship between OPEs and thyroid disease remains unclear. This study aims to elucidate the relationship between OPEs exposure and thyroid disease risk in the general population in the United States.MethodData were obtained from the 2011-2014 National Health and Nutrition Examination Survey cycle. All participants were tested for seven OPE metabolites in their urine and answered questions about whether they had thyroid disease through questionnaires. Logistic regression was employed to analyze the association between exposure to individual OPE metabolites and thyroid disease. Weighted Quantile Sum (WQS) regression modeling was utilized to assess exposure to mixed OPE metabolites and risk of thyroid disease. Bayesian kernel machine regression(BKMR) models to analyze the overall mixed effect of OPE metabolites.ResultA total of 2,449 participants were included in the study, 228 of whom had a history of thyroid disease. Bis(1,3-dichloro-2-propyl) phos (BDCPP), Diphenyl phosphate (DPHP) and Bis(2-chloroethyl) phosphate (BCEP) were the top three metabolites with the highest detection rates of 91.75%, 90.77% and 86.57%, respectively. In multivariate logistic regression models, after adjustment for confounding variables, individuals with the highest tertile level of BCEP were significantly and positively associated with increased risk of thyroid disease (OR=1.57, 95% CI=1.04-2.36), using the lowest tertile level as reference. In the positive WQS regression model, after correcting for confounding variables, mixed exposure to OPE metabolites was significantly positively associated with increased risk of thyroid disease (OR=1.03, 95% CI=1.01-1.06), with BCEP and DPHP having high weights. In the BKMR model, the overall effect of mixed exposure to OPE metabolites was not statistically significant, but univariate exposure response trends showed that the risk of thyroid disease decreased and then increased as BCEP exposure levels increased.ConclusionThe study revealed a significant association between exposure to OPE metabolites and an increased risk of thyroid disease, with BCEP emerging as the primary contributor. The risk of thyroid disease exhibits a J-shaped pattern, whereby the risk initially decreases and subsequently increases with rising levels of BCEP exposure. Additional studies are required to validate the association between OPEs and thyroid diseases.
Association between circulating immune cells and the risk of prostate cancer: a Mendelian randomization study
Authors: Hao Xuexue , Ren Congzhe , Zhou Hang , Li Muwei , Zhang Hao , Liu Xiaoqiang 
Published: February 2024

BackgroundThere is still limited research on the association between immune cells and the risk of prostate cancer. Further investigations are warranted to comprehend the intricate associations at play.MethodsWe used a bidirectional two-sample Mendelian randomization (MR) analysis to investigate the causal relationship between immune cell phenotypes and prostate cancer. The summary data for immune cell phenotypes was derived from a study cohort, including 3,757 individuals from Sardinia with data on 731 immune cell phenotypes. The summary data for prostate cancer were obtained from the UK Biobank database. Sensitivity analyses were conducted, and the combination of MR-Egger and MR-Presso was used to assess horizontal pleiotropy. Cochran’s Q test was employed to evaluate heterogeneity, and the results were subjected to FDR correction.ResultsOur study identified two immune cell phenotypes significantly associated with the risk of prostate cancer, namely CD25 on naive-mature B cells (OR = 0.998, 95% CI, 0.997-0.999, P = 2.33E-05, FDR = 0.017) and HLA DR on CD14- CD16- cells (OR = 1.001, 95% CI, 1.000-1.002, P = 8.01E-05, FDR = 0.03). When adjusting FDR to 0.2, we additionally found six immune cell phenotypes influencing the incidence of prostate cancer. These include FSC-A on B cells (OR = 1.002, 95% CI, 1.001-1.002, P = 7.77E-04, FDR = 0.133), HLA DR on plasmacytoid dendritic cells (OR = 1.001, 95% CI, 1.000-1.001, P = 0.001, FDR = 0.133), CD14+ CD16- monocyte % monocytes (OR = 1.002, 95% CI, 1.001-1.003, P = 0.001, FDR = 0.133), and HVEM on effector memory CD4+ T cells (OR = 1.001, 95% CI, 1.000-1.002, P = 0.002, FDR = 0.169), which are positively correlated with the risk of prostate cancer. Conversely, CD25 on IgD+ B cells (OR = 0.998, 95% CI, 0.997-0.999, P = 0.002, FDR = 0.169) and Monocytic Myeloid-Derived Suppressor Cells AC (OR = 0.999, 95% CI, 0.999-1.000, P = 0.002, FDR = 0.17) are negatively correlated with the risk of prostate cancer.ConclusionThis study has revealed causal relationships between immune cell phenotypes and prostate cancer, supplying novel insights that might aid in identifying potential therapeutic targets of prostate cancer.
Coordinated operation and optimal sizing strategy of P2G—CNG trucks scheme on wind farm for participating in retail gas market
Authors: Salimu Athuman , Zhang Feng , Zhang Gang , Yang Libin 
Published: February 2024

The increase in wind penetration and the stochastic nature of wind can cause some wind power to be curtailed, leading to a loss of revenue. Wind farm owners can invest in power to gas (P2G)—compressed natural gas (CNG) truck systems to utilize the curtailed wind power that would otherwise have been wasted. This paper proposes a coordinated operation and optimal sizing strategy of P2G and CNG trucks. P2G derives its power from curtailed wind power and also purchases electricity at low prices to facilitate methane (natural gas) production. The methane is directly stored in CNG trucks, which are used as temporary storage and as a means of transporting the gas, thereby reducing costs by eliminating storage tank. Firstly, a coordinated operation strategy for P2G and CNG trucks considering curtailed wind power and electricity purchased from the grid is presented. Secondly, an optimal sizing optimization model to determine the capacity of P2G and the number of CNG trucks using particle swarm optimization is presented, considering the coordinated operation strategy and operation constraints to maximize profit when the proposed system participates in the retail gas market. Finally, case studies were conducted to verify the viability of the proposed strategy using curtailed wind power data, electricity price data, and gas price data. Result show that optimal capacity of the P2G plant is 9.9 MW, and the optimal number of CNG trucks is 2. There is a 19.8% cost reduction with a payback period of 5.728 years compared to the conventional strategy with a payback period of 8.52 years. 89.74% of curtailed wind power is utilized, while only 10.26% of curtailed wind power is unutilized. Higher utilization of curtailed wind power that would otherwise have been wasted is achieved. The system earns a profit by selling the produced natural gas to a retail gas market.
Regional disparities in antenatal care utilization among pregnant women and its determinants in Ethiopia
Authors: Awoke Nefsu , Ababulgu Sabit Abazinab , Hanfore Lolemo Kelbiso , Gebeyehu Eyasu Gambura , Wake Senahara Korsa 
Published: February 2024

BackgroundAntenatal care primarily focuses on health care checkups, the provision of advice on healthy behaviors, and the delivery of psychological, social, and emotional support for women with pregnancy. The national target set by the Ethiopian government is to achieve 95% of at least four ANC visits. Nevertheless, 43.11% of women had four or more checkups, according to the 2019 Ethiopian Demographic and Health Survey. Despite this achievement, antenatal care visits differ significantly between Ethiopian regions. Consequently, the purpose of this study was to assess regional disparities in pregnant women's utilization of antenatal care and its determinants in Ethiopia.MethodsWe have used 2019 intermediate Ethiopian Demographic and Health Survey data for analysis. The analysis comprised a total of 3,917 weighted women age 15–49 who had a live birth in the 5 years preceding the survey. Poisson regression analysis was done using SAS software version 9.4. To show the strength and direction of the association, an incidence rate ratio with a 95% confidence interval was used. Variables with a p-value &lt;0.05 were declared as significant factors associated with the number of ANC visits.ResultsIn Ethiopia, the number of ANC visits differs between regions. With a mean of 4.74 (95% CI: 4.49, 4.99), Addis Ababa reported the highest percentage of ANC visits (82.7%), while the Somali Region reported the lowest percentage (11.3%) with a mean of 0.73 (95% CI: 0.57, 0.88). Maternal age, educational level, religion, household wealth index, place of delivery, and household size show significant associations with the number of antenatal care visits.ConclusionsIn Ethiopia, there is the highest regional disparity in the number of ANC visits. The number of ANC visits was influenced by the mother's age, education, religion, household wealth index, place of delivery, and household size. Regarding the ANC visits, there should be initiatives that address the demands of pastoralist and agro-pastoralist communities to increase ANC utilization. As with many other health outcomes, education and low socio-economic status were associated with low ANC visit but these are tied to the overall social development of a country and are not immediately amenable to public health interventions
An exosome-derived lncRNA signature identified by machine learning associated with prognosis and biomarkers for immunotherapy in ovarian cancer
Authors: Cui Yongjia , Zhang Weixuan , Lu Wenping , Feng Yaogong , Wu Xiaoqing , Zhuo Zhili , Zhang Dongni , Zhang Yichi 
Published: February 2024

BackgroundOvarian cancer (OC) has the highest mortality rate among gynecological malignancies. Current treatment options are limited and ineffective, prompting the discovery of reliable biomarkers. Exosome lncRNAs, carrying genetic information, are promising new markers. Previous studies only focused on exosome-related genes and employed the Lasso algorithm to construct prediction models, which are not robust.Methods420 OC patients from the TCGA datasets were divided into training and validation datasets. The GSE102037 dataset was used for external validation. LncRNAs associated with exosome-related genes were selected using Pearson analysis. Univariate COX regression analysis was used to filter prognosis-related lncRNAs. The overlapping lncRNAs were identified as candidate lncRNAs for machine learning. Based on 10 machine learning algorithms and 117 algorithm combinations, the optimal predictor combinations were selected according to the C index. The exosome-related LncRNA Signature (ERLS) model was constructed using multivariate COX regression. Based on the median risk score of the training datasets, the patients were divided into high- and low-risk groups. Kaplan-Meier survival analysis, the time-dependent ROC, immune cell infiltration, immunotherapy response, and immune checkpoints were analyzed.Results64 lncRNAs were subjected to a machine-learning process. Based on the stepCox (forward) combined Ridge algorithm, 20 lncRNA were selected to construct the ERLS model. Kaplan-Meier survival analysis showed that the high-risk group had a lower survival rate. The area under the curve (AUC) in predicting OS at 1, 3, and 5 years were 0.758, 0.816, and 0.827 in the entire TCGA cohort. xCell and ssGSEA analysis showed that the low-risk group had higher immune cell infiltration, which may contribute to the activation of cytolytic activity, inflammation promotion, and T-cell co-stimulation pathways. The low-risk group had higher expression levels of PDL1, CTLA4, and higher TMB. The ERLS model can predict response to anti-PD1 and anti-CTLA4 therapy. Patients with low expression of PDL1 or high expression of CTLA4 and low ERLS exhibited significantly better survival prospects, whereas patients with high ERLS and low levels of PDL1 or CTLA4 exhibited the poorest outcomes.ConclusionOur study constructed an ERLS model that can predict prognostic risk and immunotherapy response, optimizing clinical management for OC patients.
MGMT unmethylation and high levels of CD47 and TIGIT indicate a poor prognosis in adult diffuse gliomas
Authors: Ma Lingbo , Shi Yi , Li Chang , Deng Bin , Jiang Jinfang , Cao Yuwen , Wang Lianghai , Li Hongyan 
Published: February 2024

IntroductionIn 2021, the World Health Organization published a new classification system for central nervous system tumors. This study reclassified the adult diffuse glioma (ADG) into astrocytoma, oligodendroglioma, and glioblastoma (GBM) according to the new tumor classification.MethodsThe association of TERT promoter (pTERT) mutation, MGMT methylation, and CD47/TIGIT expression with patient prognosis was investigated.ResultsImmunohistochemical analysis showed that the expression levels of CD47 and TIGIT in tumor tissues were significantly higher than those in normal brain tissues. CD47 levels were higher in GBM and grade 4 astrocytoma tissues. TIGIT expression was also higher in patients with GBM. The high expressions of CD47, TIGIT, and CD47/TIGIT were positively correlated with MGMT unmethylation but not pTERT mutation. Moreover, MGMT unmethylation was associated with poor overall survival in astrocytoma. High CD47, TIGIT, and CD47/TIGIT levels were associated with significantly reduced survival in ADG and GBM. GBM, MGMT unmethylation, and high CD47 expression were independent prognostic factors for overall survival in ADG.DiscussionCollectively, these results showed that the MGMT unmethylation and high levels of CD47 and TIGIT are associated with a poor prognosis in ADG. Patients with high CD47 and TIGIT expression may benefit from anti-CD47 and TIGIT immunotherapy.
TNFα: TNFR1 signaling inhibits maturation and maintains the pro-inflammatory programming of monocyte-derived macrophages in murine chronic granulomatous disease
Authors: Gibbings Sophie L. , Haist Kelsey C. , Redente Elizabeth F. , Henson Peter M. , Bratton Donna L. 
Published: February 2024

IntroductionLoss of NADPH oxidase activity results in proinflammatory macrophages that contribute to hyperinflammation in Chronic Granulomatous Disease (CGD). Previously, it was shown in a zymosan-induced peritonitis model that gp91phox-/- (CGD) monocyte-derived macrophages (MoMacs) fail to phenotypically mature into pro-resolving MoMacs characteristic of wild type (WT) but retain the ability to do so when placed in the WT milieu. Accordingly, it was hypothesized that soluble factor(s) in the CGD milieu thwart appropriate programming.MethodsWe sought to identify key constituents using ex vivo culture of peritoneal inflammatory leukocytes and their conditioned media. MoMac phenotyping was performed via flow cytometry, measurement of efferocytic capacity and multiplex analysis of secreted cytokines. Addition of exogenous TNFα, TNFα neutralizing antibody and TNFR1-/- MoMacs were used to study the role of TNFα: TNFR1 signaling in MoMac maturation.ResultsMore extensive phenotyping defined normal MoMac maturation and demonstrated failure of maturation of CGD MoMacs both ex vivo and in vivo. Protein components, and specifically TNFα, produced and released by CGD neutrophils and MoMacs into conditioned media was identified as critical to preventing maturation. Exogenous addition of TNFα inhibited WT MoMac maturation, and its neutralization allowed maturation of cultured CGD MoMacs. TNFα neutralization also reduced production of IL-1β, IL-6 and CXCL1 by CGD cells though these cytokines played no role in MoMac programming. MoMacs lacking TNFR1 matured more normally in the CGD milieu both ex vivo and following adoptive transfer in vivo.DiscussionThese data lend mechanistic insights into the utility of TNFα blockade in CGD and to other diseases where such therapy has been shown to be beneficial.
Mannose-binding lectin gene polymorphism in psoriasis and vitiligo: an observational study and computational analysis
Authors: Behairy Mohammed Y. , Tawfik Noha Z. , Eid Refaat A. , Nasser Binjawhar Dalal , Alshaya Dalal Sulaiman , Fayad Eman , Elkhatib Walid F. , Abdallah Hoda Y. 
Published: February 2024

IntroductionPsoriasis and vitiligo are inflammatory autoimmune skin disorders with remarkable genetic involvement. Mannose-binding lectin (MBL) represents a significant immune molecule with one of its gene variants strongly linked to autoimmune diseases. Therefore, in this study, we investigated the role of the MBL variant, rs1800450, in psoriasis and vitiligo disease susceptibility.MethodsThe study comprised performing in silico analysis, performing an observational study regarding psoriasis patients, and performing an observational study regarding vitiligo patients. Various in silico tools were used to investigate the impact of the selected mutation on the function, stability, post-translational modifications (PTMs), and secondary structures of the protein. In addition, a total of 489 subjects were enrolled in this study, including their demographic and clinicopathological data. Genotyping analysis was performed using real-time PCR for the single nucleotide polymorphism (SNP) rs1800450 on codon 54 of the MBL gene, utilizing TaqMan genotyping technology. In addition, implications of the studied variant on disease susceptibility and various clinicopathological data were analyzed.ResultsComputational analysis demonstrated the anticipated effects of the mutation on MBL protein. Furthermore, regarding the observational studies, rs1800450 SNP on codon 54 displayed comparable results in our population relative to global frequencies reported via the 1,000 Genomes Project. This SNP showed no significant association with either psoriasis or vitiligo disease risk in all genetic association models. Furthermore, rs1800450 SNP did not significantly correlate with any of the demographic or clinicopathological features of both psoriasis and vitiligo.DiscussionOur findings highlighted that the rs1800450 SNP on the MBL2 gene has no role in the disease susceptibility to autoimmune skin diseases, such as psoriasis and vitiligo, among Egyptian patients. In addition, our analysis advocated the notion of the redundancy of MBL and revealed the lack of significant impact on both psoriasis and vitiligo disorders.
Fluid mechanics of aortic valve incompetence in the dilated left ventricle
Authors: Vu Vi , May-Newman Karen 
Published: February 2024

Introduction: Aortic insufficiency (AI) occurs when the aortic valve fails to close completely, allowing backward blood flow into the left ventricle (LV). The progression of AI can lead to ventricular dysfunction and congestive heart failure, setting off a self-perpetuating cycle that worsens these conditions. This study employed models of repeatable and reversible AI within a simulated circulatory loop to analyze vortex dynamics, AI parameters, and gain insights into the efficiency of ventricular washout.Method: A transparent silicone model of an LV with an ejection fraction of 17% served as the baseline, simulating a condition without AI. Mild, moderate, and severe AI were induced using 3D-printed stents, obstructing the complete closure of the aortic valve while allowing unimpeded forward blood flow. Midplane velocity fields were analyzed to compute AI and vortex properties, energy dissipation rate, blood residence time, and shear activation potential.Results and discussion: With increasing AI severity, the regurgitant jet expanded, impeding the development and trajectory of mitral inflow. The inefficiency in fluid transport became apparent through a declining ratio of total kinetic energy rate to energy dissipation rate and an increasing residence time. Impaired ventricular washout resulted in the accumulation of fluid with elevated shear activation potential in the LV. These findings suggested that AI progressively induces abnormal intraventricular flow, heightening the thromboembolic risk in heart failure patients. The study also advocates for the potential application of mock circulatory system to explore the effects of various AI configurations, especially when combined with other cardiac implants like artificial heart valve or left ventricular assist device.