bluuebunny/crossref_metadata_2025_split huggingface dataset:
Digital Health Literacy About COVID-19 as a Factor Mediating the Association Between the Importance of Online Information Search and Subjective Well-Being Among University Students in Vietnam
Authors: Nguyen Linh Hoang Thuy , Vo Man Thi Hue , Tran Lien Thi Mai , Dadaczynski Kevin , Okan Orkan , Murray Linda , Van Vo Thang 
Published: September 2021

Introduction: Digital health literacy (DHL) has recently been proposed as a means of enabling healthy decisions for protective behavior, preventive measures, and adherence with COVID-19 policies and recommendations especially in the era of the “infodemic”. This study aimed to (1) identify COVID-19 related DHL and its association with online information seeking; (2) to elucidate COVID-19 related DHL as a mediator predictor between the importance of online information search and its association with subjective well-being among Vietnamese university students.Methods: A cross-sectional web-based survey was used to elicit the responses of Vietnamese students over 2 consecutive weeks (from April 25 to May 9, 2020, n = 1,003, 70.1% female students, mean age 21.4 ± 3.1). The online survey questionnaire collected data on the sociodemographic characteristics of participants, DHL about COVID-19, information seeking behavior, and subjective well-being. Mediation analysis was conducted using the importance of searching COVID-19 related information as independent variables, subjective well-being as a dependent variable, and DHL as a mediator variable.Results: Among 1,003 students, the mean (SD) of DHL related to COVID-19 was 2.87 ± 0.32. In the survey, 87.2% of the students reported sufficient well-being, while almost 13% reported low or very low well-being. The findings also indicated that search engines were the most popular platform for information seeking by Vietnamese students (95.3%) and 92.8% of participants had searched for information related to the current spread of COVID-19. Not searching for hygiene regulation as part of infection control and an average level of information satisfaction were associated with limited DHL (p &lt; 0.05). The importance of online information searching related to COVID-19 increased the subjective well-being of students significantly and limited DHL (p &lt; 0.05). DHL was found to mediate the relationship between the importance of online information searching and the subjective well-being of students.Conclusion: The finding provides insight into DHL about COVID-19 among university students, and their ability to find, understand, appraise, and use online health related information during lockdown throughout the first COVID-19 pandemic wave. DHL should be highlighted as a mediating factor that enhances the positive effect of the importance of information seeking on psychological well-being. However, further studies are needed to better define the mediating role of DHL across other factors.
Endometrial Thickness Is a Risk Factor for Singleton Low Birth Weight From Single Blastocyst Transfer: A Retrospective Cohort Study
Authors: Du Mingze , Zhang Junwei , Liu Manman , Guan Yichun , Wang Xingling 
Published: September 2021

ObjectiveTo explore whether endometrial thickness (EMT) ≤7.5 mm is associated with singleton low birth weight (LBW) from single fresh blastocyst transfer.MethodsThis was a retrospective cohort study. Only women ≤ 40 years old who underwent single fresh blastocyst transfer and had singleton live births were included in the study. LBW was the primary outcome of this study. Neonatal malformation was the secondary outcome. Logistic regression was used to evaluate the association between (EMT) ≤7.5 mm and singleton LBW.ResultsA total number of 2847 women met the study inclusion criteria. The neonatal birthweight in the EMT ≤7.5 mm group was significantly lower than that in the EMT 7.6~12.0 mm and EMT &gt;12.0 mm group (P&lt;0.001). The rate of LBW in the EMT ≤7.5 mm group was 24.9%, which was significantly higher than the 4.0% in the EMT 7.6~12.0 mm group and the 5.3% in the EMT &gt;12.0 mm group (P&lt;0.001). The total neonatal malformation rate was similar between the groups (1.1%, 0.8% and 1.5%, P=0.21). After logistic regression analysis, EMT ≤7.5 mm was found to be an independent risk factor for LBW (adjusted odds ratio [AOR]: 4.39, 95% CI: 1.85˜10.46, P&lt;0.001).ConclusionEMT ≤7.5 mm on the hCG trigger day is an independent risk factor for LBW in singleton pregnancies from single fresh blastocyst transfer. The neonatal birthweight in the EMT ≤7.5 mm group was significantly lower than that in the EMT 7.6~12.0 mm and EMT &gt;12.0 mm groups. The total neonatal malformation rate was comparable between the groups.
The Carcinogenic and Non-Carcinogenic Health Risks of Metal(oid)s Bioaccumulation in Leafy Vegetables: A Consumption Advisory
Authors: Alsafran Mohammed , Usman Kamal , Rizwan Muhammad , Ahmed Talaat , Al Jabri Hareb 
Published: September 2021

High levels of metal(oid)s in soil or food pose a severe health risk to humans. The potential toxicants find their way into the living systems via the food chain, following bioaccumulation in edible plants, including leafy vegetables grown in or irrigated with contaminated soil or water, respectively. The current study determines the levels of vanadium (V), chromium (Cr), nickel (Ni), copper (Cu), arsenic (As), lead (Pb), and cadmium (Cd) in leafy vegetables (rocca, coriander, and parsley) grown in different open irrigated farms in Qatar and investigates their potential human health risks (carcinogenic and noncarcinogenic). The mean concentrations of V, Cr, Ni, Cu, As, Cd, and Pb in rocca are 17.09, 6.41, 1.70, 13.04, 14.72, 0.90, and 6.36 mg/kg, respectively; in coriander are 15.91, 6.03, 1.38, 15.30, 16.86, 0.43, and 5.00 mg/kg, respectively; and in parsley are 16.25, 6.26, 2.19, 17.97, 16.60, 0.51, and 5.46 mg/kg, respectively. The mean levels of V, Cr, As, Cd, and Pb were observed to be higher than the recommended World Health Organization (WHO)/Food and Agriculture Organization (FAO) values. The target hazard quotient (THQ) values of Cu and As were found to be greater than 1 for the adult population. For the two elements (i.e., Cu and As), the THQ varied from 1.03 to 1.42 and 1.17 to 1.44 in men. In women, the values ranged from 1.20 to 1.65 and 1.35 to 1.55, for Cu and As, respectively. The hazard index (HI) of rocca, coriander, and parsley was 3.99, 4.10, and 4.43, respectively, in men, 4.64, 4.76, and 5.14, respectively, among women. The carcinogenic risk (CR) of Cr, Ni, and As ranged from 7.16 × 10−4 to 7.61 × 10−4, 5.57 × 10−4 to 8.85 × 10−4, and 5.24 × 10−3 to 6.01 × 10−3, respectively, in men. In women, it ranged from 8.31 × 10−4 to 8.83 × 10−4, 6.47 × 10−4 to 1.03 × 10−3, and 6.09 × 10−3 to 6.97 × 10−3, respectively, in all vegetables. In crux, the consumption of rocca, coriander, and parsley grown in selected farms in Qatar poses a major health risk (both noncarcinogenic and carcinogenic) to the consumer. As a result, we recommend that vegetables grown in the studied areas be closely monitored to protect consumer health.
Associations of the miRNA-146a rs2910164 and the miRNA-499a rs3746444 Polymorphisms With Plasma Lipid Levels: A Meta-Analysis
Authors: Liu Fuqiang , Wang Shengping , Luo Zhi 
Published: September 2021

Background: The studies of miRNAs are vibrant and remain at the forefront in the cardiovascular system. Emerging studies indicate that the genetic polymorphisms of the miRNA gene may affect lipid metabolism; this study aims to clarify the specific correlations between the rs2910164 and rs3746444 polymorphisms and lipid levels.Methods and Results: A comprehensive search of literature was performed from December 31, 2020, to May 31, 2021, by searching of the PubMed and the Cochrane databases. The standardized mean difference (SMD) and 95% confidence interval (CI) were used to evaluate the differences in lipid levels between the genotypes. rs2910164, a functional polymorphism in the miRNA-146a gene, was associated with increased triglycerides (TG) (SMD = 0.35, 95% CI = 0.15–0.54, p &lt; 0.001), total cholesterol (TC) (SMD = 0.43, 95% CI = 0.16–0.70, p &lt; 0.001), and low-density lipoprotein cholesterol (LDL-C) (SMD = 0.37, 95% CI = 0.11–0.63, p = 0.01) as well as decreased high-density lipoprotein cholesterol (HDL-C) (SMD = −0.27, 95% CI = −0.47−0.07, p = 0.01) levels. rs3746444, a functional polymorphism in the miRNA-499a gene, was only correlated with decreased TG (SMD = −0.09, 95% CI = −0.17−0.01, P = 0.03) levels.Conclusions: The miRNA-146a rs2910164 polymorphism is significantly associated with atherogenic dyslipidemia.
Unsupervised Clustering Reveals Distinct Subtypes of Biliary Atresia Based on Immune Cell Types and Gene Expression
Authors: Pang Xiuqing , Cao Jing , Chen Shuru , Gao Zhiliang , Liu Guangjian , Chong Yutian , Chen Zhuanggui , Gong Jiao , Li Xinhua 
Published: September 2021

BackgroundBiliary atresia (BA) is a severe cholangiopathy of early infancy that destroys cholangiocytes, obstructs ductular pathways and if left untreated, culminates to liver cirrhosis. Mechanisms underlying the etiological heterogeneity remain elusive and few studies have attempted phenotyping BA. We applied machine learning to identify distinct subtypes of BA which correlate with the underlying pathogenesis.MethodsThe BA microarray dataset GSE46995 was downloaded from the Gene Expression Omnibus (GEO) database. Unsupervised hierarchical cluster analysis was performed to identify BA subtypes. Then, functional enrichment analysis was applied and hub genes identified to explore molecular mechanisms associated with each subtype. An independent dataset GSE15235 was used for validation process.ResultsBased on unsupervised cluster analysis, BA patients can be classified into three distinct subtypes: Autoimmune, Viral and Embryonic subtypes. Functional analysis of Subtype 1 correlated with Fc Gamma Receptor (FCGR) activation and hub gene FCGR2A, suggesting an autoimmune response targeting bile ducts. Subtype 2 was associated with immune receptor activity, cytokine receptor, signaling by interleukins, viral protein interaction, suggesting BA is associated with viral infection. Subtype 3 was associated with signaling and regulation of expression of Robo receptors and hub gene ITGB2, corresponding to embryonic BA. Moreover, Reactome pathway analysis showed Neutrophil degranulation pathway enrichment in all subtypes, suggesting it may result from an early insult that leads to biliary stasis.ConclusionsThe classification of BA into different subtypes improves our current understanding of the underlying pathogenesis of BA and provides new insights for future studies.
Applying Deep Learning to Accelerated Clinical Brain Magnetic Resonance Imaging for Multiple Sclerosis
Authors: Mani Ashika , Santini Tales , Puppala Radhika , Dahl Megan , Venkatesh Shruthi , Walker Elizabeth , DeHaven Megan , Isitan Cigdem , Ibrahim Tamer S. , Wang Long , Zhang Tao , Gong Enhao , Barrios-Martinez Jessica , Yeh Fang-Cheng , Krafty Robert , Mettenburg Joseph M. , Xia Zongqi 
Published: September 2021

Background: Magnetic resonance (MR) scans are routine clinical procedures for monitoring people with multiple sclerosis (PwMS). Patient discomfort, timely scheduling, and financial burden motivate the need to accelerate MR scan time. We examined the clinical application of a deep learning (DL) model in restoring the image quality of accelerated routine clinical brain MR scans for PwMS.Methods: We acquired fast 3D T1w BRAVO and fast 3D T2w FLAIR MRI sequences (half the phase encodes and half the number of slices) in parallel to conventional parameters. Using a subset of the scans, we trained a DL model to generate images from fast scans with quality similar to the conventional scans and then applied the model to the remaining scans. We calculated clinically relevant T1w volumetrics (normalized whole brain, thalamic, gray matter, and white matter volume) for all scans and T2 lesion volume in a sub-analysis. We performed paired t-tests comparing conventional, fast, and fast with DL for these volumetrics, and fit repeated measures mixed-effects models to test for differences in correlations between volumetrics and clinically relevant patient-reported outcomes (PRO).Results: We found statistically significant but small differences between conventional and fast scans with DL for all T1w volumetrics. There was no difference in the extent to which the key T1w volumetrics correlated with clinically relevant PROs of MS symptom burden and neurological disability.Conclusion: A deep learning model that improves the image quality of the accelerated routine clinical brain MR scans has the potential to inform clinically relevant outcomes in MS.
Periodic Limb Movements Syndrome in Patients With Cerebral Small Vessel Disease: Protocol for a Prospective Observational Study
Authors: Spektor Ekaterina , Fietze Ingo , Poluektov Mikhail G. 
Published: September 2021

Background: Cerebrovascular diseases are the leading cause of cognitive decline and dementia. Therefore, the investigation of the potential ways to slow down the disease progression is an important research field. Periodic limb movements in sleep (PLMS) are known to be associated with transient changes in heart rate and blood pressure. These changes might influence the course of cerebral small vessel disease (cSVD). Nevertheless, the clinical significance of PLMS, particularly its influence on cardiovascular diseases course, is still controversial and underinvestigated.Methods/design: Patients from 60 to 75 years old diagnosed with cSVD will undergo nocturnal polysomnography. Subjects with apnea/hypopnea index under 5 will be enrolled. Sleep quality and daytime functioning will be assessed at baseline with self-reported questionnaires. Brain MRI and cognitive assessment will be performed at baseline and in the 2-year follow-up. Progression of cSVD markers and cognitive dysfunction will be compared between patients with PLMS index (PLMI) equal to or more than 15 movements per hour of sleep and controls (PLMI &lt;15/h).Discussion: The negative role of PLMS in cSVD progression and related cognitive decline is expected. We suppose that patients with PLMS tend to worsen in cognitive performance more rapidly than age-, gender-, and comorbidity-matched controls. We also expect them to have more rapid white matter hyperintensities and other cSVD marker progression. The limitations of the study protocol are the short follow-up period, the absence of a treatment group, and inability to make a conclusion about causality.
An Adaptive Transfer-Learning-Based Deep Cox Neural Network for Hepatocellular Carcinoma Prognosis Prediction
Authors: Chai Hua , Xia Long , Zhang Lei , Yang Jiarui , Zhang Zhongyue , Qian Xiangjun , Yang Yuedong , Pan Weidong 
Published: September 2021

BackgroundPredicting hepatocellular carcinoma (HCC) prognosis is important for treatment selection, and it is increasingly interesting to predict prognosis through gene expression data. Currently, the prognosis remains of low accuracy due to the high dimension but small sample size of liver cancer omics data. In previous studies, a transfer learning strategy has been developed by pre-training models on similar cancer types and then fine-tuning the pre-trained models on the target dataset. However, transfer learning has limited performance since other cancer types are similar at different levels, and it is not trivial to balance the relations with different cancer types.MethodsHere, we propose an adaptive transfer-learning-based deep Cox neural network (ATRCN), where cancers are represented by 12 phenotype and 10 genotype features, and suitable cancers were adaptively selected for model pre-training. In this way, the pre-trained model can learn valuable prior knowledge from other cancer types while reducing the biases.ResultsATRCN chose pancreatic and stomach adenocarcinomas as the pre-training cancers, and the experiments indicated that our method improved the C-index of 3.8% by comparing with traditional transfer learning methods. The independent tests on three additional HCC datasets proved the robustness of our model. Based on the divided risk subgroups, we identified 10 HCC prognostic markers, including one new prognostic marker, TTC36. Further wet experiments indicated that TTC36 is associated with the progression of liver cancer cells.ConclusionThese results proved that our proposed deep-learning-based method for HCC prognosis prediction is robust, accurate, and biologically meaningful.
Identification of N6-Methylandenosine-Related lncRNAs for Subtype Identification and Risk Stratification in Gastric Adenocarcinoma
Authors: Huang Yuancheng , Yang Zehong , Huang Chaoyuan , Jiang Xiaotao , Yan Yanhua , Zhuang Kunhai , Wen Yi , Liu Fengbin , Li Peiwu 
Published: September 2021

ObjectivesThe purpose of this study was to investigate the role of m6A-related lncRNAs in gastric adenocarcinoma (STAD) and to determine their prognostic value.MethodsGene expression and clinicopathological data were obtained from The Cancer Genome Atlas (TCGA) database. Correlation analysis and univariate Cox regression analysis were conducted to identify m6A-related prognostic lncRNAs. Subsequently, different clusters of patients with STAD were identified via consensus clustering analysis, and a prognostic signature was established by least absolute shrinkage and selection operator (LASSO) Cox regression analyses. The clinicopathological characteristics, tumor microenvironment (TME), immune checkpoint genes (ICGs) expression, and the response to immune checkpoint inhibitors (ICIs) in different clusters and subgroups were explored. The prognostic value of the prognostic signature was evaluated using the Kaplan-Meier method, receiver operating characteristic curves, and univariate and multivariate regression analyses. Additionally, Gene Set Enrichment Analysis (GSEA), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and Gene Ontology (GO) analysis were performed for biological functional analysis.ResultsTwo clusters based on 19 m6A-related lncRNAs were identified, and a prognostic signature comprising 14 m6A-related lncRNAs was constructed, which had significant value in predicting the OS of patients with STAD, clinicopathological characteristics, TME, ICGs expression, and the response to ICIs. Biological processes and pathways associated with cancer and immune response were identified.ConclusionsWe revealed the role and prognostic value of m6A-related lncRNAs in STAD. Together, our finding refreshed the understanding of m6A-related lncRNAs and provided novel insights to identify predictive biomarkers and immunotherapy targets for STAD.
Influence of the Weakening Effect of Drilling Fluid on Wellbore Stability in Anisotropic Shale Formation
Authors: Zhang Fan , Liu Hou-Bin , Cui Shuai , Meng Ying-Feng , Wang Jia-Jun 
Published: September 2021

For horizontal wells in Longmaxi Formation, oil-based drilling fluid that soaks for a long time is more likely to cause a wellbore collapse. Therefore, in this paper, the downhole core method of shale formation, in Longmaxi Formation, was adopted. First, rock samples were selected from different sampling angles and soaked with field drilling fluid. Second, a triaxial mechanics experiment was carried out. Based on the anisotropic wellbore stress distribution model, the stability of shale wellbore was calculated and analyzed. The results show that the compressive strength and cohesion of the shale are reduced after soaking in the drilling fluid. Hence, the reduction range of various sampling angles obviously differs as well. Shear failure occurs in vertical stratification; shear slip failure occurs along the weak plane, showing strong anisotropy. Combined with the experimental results, the collapse pressure is calculated, and it is found that the weakening effect of drilling fluid makes the overall collapse pressure rise by about 0.2 g/cm3. Finally, the shale bedding dip and dip direction have a great influence on the collapse pressure. The lower critical mud weight always takes the minimum value when the borehole axis is perpendicular to the bedding.
Latent Profile Analysis of Perceptions and Attitudes Towards COVID-19 in a Sample of Chinese People
Authors: Niu Zhimin , Li Li , Li Hongying , Mei Songli , Jiang Hui , Deng Zhiyong , Xin Jun 
Published: September 2021

Background: The novel coronavirus-2019 (COVID-19) disease has spread quickly throughout China and around the world, endangering human health and life. Individuals' perceptions and attitudes as well as related health education measures may affect disease progression and prognosis during the COVID-19 outbreak. To promote and implement health education, research must focus on the perceptions and attitudes towards COVID-19 among Chinese people. The present study aimed to examine the profiles and predictive factors of the perceptions and attitudes towards COVID-19 in a sample of Chinese people.Methods: A sample of 2,663 Chinese people comprising medical staff and members of the general public completed an online survey on Wenjuanxing. The survey measured demographic variables (e.g., gender, age, education level, and place of residence) and perceptions and attitudes towards COVID-19.Results: Two profiles of perceptions and attitudes towards COVID-19 (positive and negative perceptions and attitudes) were identified in the sample. Place of residence during the COVID-19 pandemic and first response to COVID-19 were found to be independent predictive factors for COVID-19 related perceptions and attitudes.Conclusion: In addition to drug therapy and mental health services, the perceptions and attitudes of Chinese people towards COVID-19 should be considered when promoting health education during the COVID-19 pandemic.