bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fibrinogen Level Predicts Prognosis of Patients with Acute Ischemic Stroke or TIA
Authors: Hou Huiqing , Xiang Xianglong , Pan Yuesong , Li Hao , Meng Xia , Wang Yongjun 
Published: August 2020

Abstract
Background: Fibrinogen is involved in acute stroke. This study aimed to investigate the association between fibrinogen and prognosis in patients with acute ischemic stroke or transient ischemic attack (TIA). Methods: Using data from the CNSR-Ⅲ (Third China National Stroke Registry), this sub-study included 10 518 (69%) consecutive patients who had fibrinogen levels measured. The primary outcome was a poor functional outcome defined as modified Rankin Scale score of 3 to 6 within 90 days. The secondary outcomes were stroke recurrence, ischemic stroke recurrence, composite vascular events, and poor functional outcome during the 1-year follow-up and a new vascular event at 90 days. Multivariate logistic regression and Cox regression analyses were used to assess the associations between fibrinogen and prognosis of patients. Results: In total, 1446 (13.9%) patients had a poor functional outcome at 90 days. High fibrinogen levels were associated with poor functional outcome (adjusted odds ratio [OR], 1.35; 95% confidence interval [CI], 1.12-1.64) at 90 days after adjustment for confounding risk factors. High fibrinogen levels also independently predicted poor functional outcome during the 1-year follow-up. Stroke recurrence occurred in 657 (6.3%) patients at 90 days. High fibrinogen levels were associated with stroke recurrence, ischemic stroke recurrence, and composite vascular events in the crude model, but further adjustment eliminated these associations in the multivariate models. Conclusion: Our study showed that high fibrinogen level was independently associated with poor functional outcome but not with stroke recurrence in patients with acute ischemic stroke or TIA.
Interfacial stabilization for inverted perovskite solar cells with long-term stability
Authors: He Zhubing , Chen Wei , Han Bing , Hu Qin , Gu Meng , Zhu Yudong , Yang Wenqiang , Zhou Yecheng , Luo Deying , Liu Fangzhou , Cheng Rui , Zhu Rui , Feng Shien-Ping , Djurišić Aleksandra , Russell Thomas 
Published: August 2020

Abstract
Perovskite solar cells (PSCs) commonly exhibit significant performance degradation due to ion migration through the top charge transport layer and ultimately metal electrode corrosion. Here, we demonstrate an interfacial management strategy using a boron chloride subphthalocyanine (Cl6SubPc)/fullerene electron-transport layer, which not only passivates the interfacial defects in the perovskite, but also suppresses halide diffusion as evidenced by multiple techniques, including visual element mapping by electron energy loss spectroscopy. As a result, we obtain inverted PSCs with an efficiency of 22.0% (21.3% certified), shelf life of 7000 hours, T80 of 816 h under damp heat stress (compared to less than 20 h without Cl6SubPc), and initial performance retention of 98% after 2000 hours at 80 oC in inert environment, 90% after 2034 h of illumination and MPP tracking in ambient for encapsulated devices and 95% after 1272 h outdoor testing ISOS-O-1, which is among the top device performance for the inverted PSCs.
DNA Methylation Changes in Endometrium and Correlation with Gene Expression During Ovarian Hyper-stimulation
Authors: Sun Bo , Ma Yujia , Wang Fang , Hu Linli , Dai Shanjun , Zhang Yile , Sun Yingpu 
Published: August 2020

Abstract
Persistent supraphysiological serum estradiol (E2) levels during controlled ovarian hyper-stimulation (COH) have a detrimental effect on endometrial receptivity. In this study, we explored RNA expression and DNA methylation profiles from patients’ endometrium. The patients were divided into two groups: the COH cycle (n=3, hCG+7) group and normal cycle group (n=3, LH+5). Quantitative RT-PCR was used to validate the expression of selected differentially expressed genes (DEGs). Comparing natural and stimulated endometrium transcriptome profiles revealed 640 DEGs, with a > 2-fold change (FC) and p < 0.01. The DEGs were reported to be involved in endometrial receptivity and epithelial-mesenchymal transition (EMT). The expression of IGFBP-1, MMP9, FGF9, LIF, WNT4, HAND2, and immune system-related genes were significantly up-regulated. By clustering and KEGG pathway analysis, molecules and pathways associated with endometrial receptivity (PI3K-Akt signaling pathway) were identified. DNA methylation was partially correlated to gene expression. In conclusion, RNA-seq COH affected endometrial receptivity and EMT/MET process by accelerated the decidualization process and broken the balance of estrogen and progesterone receptors expression. However, this was not associated with changes in DNA methylation.
Lesson by SARS-Cov 2 disease (COVID-19): whole body CT angiography detection of relevant and other/incidental systemic vascular findings
Authors: Rea Gaetano , Lassandro Francesco , Lieto Roberta , Bocchini Giorgio , Romano Federica , Sica Giacomo , Valente Tullio , Muto Emanuele , Murino Patrizia , Pinto Antonio , Montesarchio Vincenzo , Muto Maurizio , Pacella Daniela , Capitelli Ludovica , Bocchino Marialuisa 
Published: August 2020

Abstract
Objectives: The aim of our study was to assess the frequency distribution of relevant and incidental vascular events in a retrospective cohort of 42 COVID-19 patients. Methods: All patients were studied by whole-body CT angiography.Twenty-three out of 42 patients were admitted to the intensive care unit (ICU). Results: Relevant vascular events were recorded in the 71.4% of the whole study population. Pulmonary embolism was the most frequent one both in ICU and no-ICU cases (56.5% vs10.5%, p=0.002). Ischemic infarction of other organs was affecting with an increasing prevalence the gut, the spleen, the liver, the brain and the kidney, with a simultaneous ischemic occurrence in some cases. Multi-focal venous thrombosis was also represented especially in ICU patients (p=0.005). Among incidental findings, splanchnic vessels little-size aneurysms were reported in the 40% of the whole population, with relative frequencies similarly distributed in ICU and no-ICU patients.Conclusions: Vascular involvement is not negligible in COVID-19 and should be carefully investigated as may significantly affect disease behavior and prognosis.
A Two-stage Panel Data Envelopment Analysis Models: Wallace-Hussain, Amemiya and Swamy-Arora
Authors: Shaik Saleem 
Published: August 2020

Abstract
This research presents two-stage panel data envelopment analysis (DEA) models for the estimation of efficiency measures. In the first stage, the variances of normal errors, v used in the transformation of the variables are recovered from pooled (Wallace-Hussain in 1969); within (Amemiya in 1971); or within, cross-sectional and time-series (Swamy-Arora in 1972) stochastic frontier analysis (SFA) models. The second stage involves estimating panel DEA efficiency measures using transformed data based on alternative two-way random effect econometric estimators in the first stage. The alternative panel DEA models might over- or under-estimate the pooled DEA model estimated efficiency measure due to the non-existence or existence of the spatial and temporal variations. An empirical application to 48 U.S. states from 1960 to 2004 suggests differences in the efficiency measure estimated by the pooled and panel DEA models. In addition, the efficiency measure estimated by the Swamy-Arora panel estimator is statistically different compared to the Wallace-Hussain and Amemiya panel estimator.
A Computational Framework to Quantify Host-Microbiome Interactions in Clostridioides Difficile&nbsp;Infection
Authors: Ke Shanlin , Pollock Nira R. , Wang Xu-wen , Chen Xinhua , Daugherty Kaitlyn , Lin Qianyun , Xu Hua , Garey Kevin W. , Gonzales-Luna Anne J. , Liu Yang-Yu , Kelly Ciarán P. 
Published: August 2020

Abstract
Background: Clostridioides difficile infection (CDI) is the most common cause of healthcare–associated infection and an important cause of morbidity and mortality among hospitalized patients. A comprehensive understanding of C. difficile infection (CDI) pathogenesis is crucial for disease diagnosis, treatment and prevention. To achieve that, a quantitative study of host-microbiome interactions in CDI is a prerequisite. Yet, an effective computational framework to quantify host-microbiome interactions in CDI was lacking. Methods: Here, we characterized gut microbial compositions and abroad panel of immunological markers in a comprehensive clinical cohort of 243 well-characterized human subjects with four different C. difficile infection/colonization statuses (CDI, Asymptomatic Carriage, Non-CDI Diarrhea, and Control). Based on microbial and immunological features, we developed a computational framework to detect CDI status using random forest and symbolic classification models.Results: First, by calculating the correlations between microbial compositions and the circulating levels of host immune markers for each of the four phenotype groups, we found that the interactions between gut microbiota and host immune markers are very sensitive to the status of C. difficile colonization and infection. Second, we demonstrated that incorporating both gut microbiome and host immune marker data into random forest classifiers can better distinguish CDI from other groups than can either type of data alone. Finally, we performed symbolic classification using selected features from random forest classifiers to derive simple mathematic formulas that explicitly model the interactions between gut microbiome and host immune markers.Conclusions: Overall, this study provides an effective computational framework to quantify the role of the intricate interactions between gut microbiota and host immune markers in CDI pathogenesis. This framework may inform the design of future diagnostic and therapeutic strategies.
Deep Learning Based Liver Cancer Segmentation from Computed Tomography Images
Authors: Ayalew Yodit Abebe , Fante Kinde Anlay , Aliy Mohammed 
Published: August 2020

Abstract
Background: Liver cancer is the sixth most common cancer worldwide. According to WHO data in 2017, the liver cancer death in Ethiopia reached 1040 (0.16%) from all cancer deaths. Hepatocellular carcinoma (HCC), primary liver cancer causes the death of around 700,000 people each year worldwide and this makes it the third leading cause of cancer death. HCC is occurred due to cirrhosis and hepatitis B or C viruses. Liver cancer mostly diagnosed with a computed tomography (CT) scan. But, the detection of the tumor from the CT scan image is difficult since tumors have similar intensity with nearby tissues and may have a different appearance depending on their type, state, and equipment setting. Nowadays deep learning methods have been used for the segmentation of liver and its tumor from the CT scan images and they are more efficient than those traditional methods. But, they are computationally expensive and need many labeled samples for training, which are difficult in the case of biomedical images. Results: A deep learning-based segmentation algorithm is employed for liver and tumor segmentation from abdominal CT scan images. Three separate UNet models, one for liver segmentation and the others two for tumor segmentation from the segmented liver and directly from the abdominal CT scan image were used. A dice score of 0.96 was obtained for liver segmentation. And a dice score of 0.74 and 0.63 was obtained for segmentation of tumor from the liver and from abdominal CT scan image respectively. Conclusion: The research improves the liver tumor segmentation that will help the physicians in the diagnosis and detection of liver tumors and in designing a treatment plan for the patient. And for the patient, it increases the patients’ chance of getting treatment and decrease the mortality rate due to liver cancer.
SARS-CoV-2: Enhancement and Segmentation of High-ResolutionMicroscopy Images. Part I
Authors: Rodriguez Roberto , Mondeja Brian A. , Valdes Odalys , Resik Sonia , Vizcaino Ananayla , Acosta Emilio F. , González Yorexis , Kourí Vivian , Díaz Angelina , Guzmán María G. 
Published: August 2020

Abstract
Possibly, and due to poor eating habits and unhealthy lifestyle, many virus are transmitted to human people. Such is the case, of the novel coronavirus SARS-Cov-2, which has expanded of exponential way, practically, to whole world population. For this reason, the study of real microscopic images of this coronavirus is of great importance. The SARS-Cov-2 images were captured from nasopharyngeal samples of Cuban symptomatic individuals (RT-PCR positives for SARS-CoV-2), and processed via scanning electron microscopy. However, many times these microscopic images present some blurring problems, which are always susceptible to be improved. The aim of this work is to propose new computational methods to carry out enhancement and segmentation of SARS-Cov-2 high-resolution microscopic images. Moreover, due to the importance of the obtained results, this first work will be addressed to the application of the proposed algorithm. The proposed strategy obtained very satisfactory results, and we validated its performance, together with specialist physicians, on a set of 1005 images. A second paper will deeply analyze the theory related to these algorithms
Membrane Protein Metabolism in UNG-Activated NCAPH and RFC4 Subnetworks for Viral HCC|blood Cancer Development Via Inside-Out Microtubule Binding
Authors: Wang Lin , Chen Qingchun , Feng Haitao , Jiang Minghu , Huang Juxiang , Jiang Zhenfu 
Published: August 2020

Abstract
Background: Our aim is to compute NCAPH and RFC4 subnetworks containing CDKN3 (feedback) for the novel molecular and cellular mechanisms of HCC (HBV or HCV) related cancer development from high UNG-activated upstream network.Methods: Non-SMC condensin I complex subunit H (NCAPH) and replication factor C subunit 4 (RFC4) common molecular and knowledge subnetworks containing cyclin-dependent kinase inhibitor 3-CDKN3 (feedback) related to cancer by references were identified in HCC (HBV or HCV), based on our established significant high expression uracil DNA glycosylase (UNG)-activated upstream Gene (protein) reconstruction network inference (GRNInfer) and Database for Annotation, Visualization and Integrated Discovery (DAVID).Results: Our results show the common molecules MAPT interaction with CDKN3 with RRM2 with HIST1H3H from UNG-activated upstream GRNInfer database; The common biological process and molecular function of MAPT as microtubule binding; HIST1H3H as cellular protein metabolic process from UNG-activated upstream DAVID database; The common cellular component of UNG, NCAPH, CDKN3, RRM2, HIST1H3H at nucleus; NCAPH, HIST1H3H at membrane; The common tissue distributions of NCAPH and RFC4 in Leukemiapromyelocytic(hl60), leukemialymphoblastic(molt4), etc.Conclusions: We propose and mutual positively verify membrane protein metabolism in UNG-activated NCAPH and RFC4 subnetworks for viral HCC|blood cancer development via inside-out microtubule binding.
New Records of Bartonella Spp. And Rickettsia Spp. In Lice Collected From Small Rodents
Authors: Aleksandravičienė Asta , Paulauskas Algimantas , Stanko Michal , Fričová Jana , Radzijevskaja Jana 
Published: August 2020

Abstract
Background: Lice are blood-sucking insects that are of medical and veterinary significance as parasites and vectors for various infectious agents. More than half of described blood-sucking lice species are found on rodents. Rodents are important hosts of several Bartonella and Rickettsia species and some of these pathogens are characterised as human pathogens in Europe. Rodent ectoparasites, such as fleas and ticks, are important vectors of Bartonella spp. and Rickettsia spp., but knowledge about the presence of these bacteria in lice is limited. The aim of this study was to determine the prevalence of Bartonella and Rickettsia bacteria in lice collected from rodents in Slovakia.Methods: The ectoparasites were collected from small rodents captured from 2010 to 2015 at four different sites in eastern Slovakia. The presence of Bartonella and Rickettsia pathogens in lice samples was screened by real-time PCR, targeting ssrA and gltA genes respectively. The molecular characterisation of the Bartonella strains was based on sequence analysis of partial rpoB and ITS genes, and of the Rickettsia species on sequence analysis of the gltA gene. Results: A total of 1074 lice of seven species were collected from six rodent species in Slovakia from 2010 to 2015. Bartonella DNA was detected in three species of lice Hoplopleura affinis (collected from Apodemus agrarius, A. flavicollis and Myodes glareolus), Polyplax serrata (from A. agrarius) and Hoplopleura sp. (from A. flavicollis). Sequence analysis revealed that the Bartonella strains belonged to the B. coopersplainsensis, B. tribocorum and B. taylorii genogroups. Rickettsia DNR was detected in H. affinis and P. serrata lice collected from A. agrarius. Sequence analysis revealed the presence of two Rickettsia species: R. helvetica and Rickettsia sp.Conclusions: To the best of the authors’ knowledge, this is the first report on the occurrence and diversity of Bartonella spp. and Rickettsia spp. in lice collected from small rodents in Europe. This study is also the first to detect B. coopersplainsensis in Slovakia.
3D Models Improve Understanding of Congenital Heart Disease
Authors: Awori Jonathan , Friedman Seth , Chan Titus , Howard Christopher , Seslar Stephen , Soriano Brian , Buddhe Sujatha 
Published: August 2020

Abstract
Introduction: Understanding congenital heart disease (CHD) is vital for medical personnel and parents of affected children. While traditional 2D schematics serve as the typical approach used, several studies have shown these models to be suboptimal. Recent world-emphasis has shifted to 3D printed models to bridge knowledge and create new opportunities for experiential learning. We sought to systematically compare 3D digital and physical models for medical personnel and parent education compared to traditional methods.Methods: 3D printed and digital models were made out of MRI and CT data for 20 common CHD. Fellows and nurse practitioners used these models to explore intra-cardiac pathologies following traditional teaching. The models were also used for parent education in outpatient settings after traditional education. The participants were then asked to fill out a Likert scale questionnaire to assess their understanding and satisfaction with different teaching techniques. These ratings were compared using paired t-tests and Pearson’s correlation. Results: Twenty-five medical personnel (18 fellows; 2 nurses; 4 nurse practitioners and one attending) and twenty parents participated in the study. The diagnosis varied from simple mitral valve pathology to complex single ventricle palliation. Parent and medical personnel understanding with digital models was significantly higher than traditional (p = 0.01). Subjects also felt that physical models were overall more useful than digital ones (p=0.001). Physicians using models for parent education also perceived the models to be useful, not significantly impacting their clinical workflow.Conclusions: 3D models, both digital and printed, enhance medical personnel and parental understanding of CHD.
Effect of novel coronavirus disease 2019 infection on chronic kidney disease G1-G5, G5 Dialysis and G5 Transplantation
Authors: Amiri Fateme Shamekhi 
Published: August 2020

Abstract
Background: The pneumonia caused by the 2019 novel coronavirus (SARS-CoV-2) is a highly infectious disease that causes lethal disease and multiorgan failure. The aim of this research is to investigate association between covid-19 infection and kidney dysfunction.Methods and materials: In this retrospective study, sixty-eight patients with kidney dysfunction and covid-19 infection were investigated. Clinical features, laboratory data at initial presentation, management and outcomes were collected.The paper has written based on searching PubMed Central and Google Scholar to identify potentially relevant articles. Median, percentage, mean ± standard deviation (SD), two-tailed t and chi-square and Cohen᾽s-d tests were used for statistical analyses. Moreover, relative risk, odds ratio, pearson᾽s correlation for statistical analyses were used. Results: The average age of patients at time of diagnosis in covid-19 nephropathy was 52.04 ± 14.42 years (ranging from 24 years to 88 years). There was not statistical significance correlation between lymphocytopenia and serum creatinine (SCr) in covid-19 nephropathy (R2=0.063; p-value= 0.33). Effect size of elevated IL-6 on decreased estimated glomerular filtration rate (eGFR) in covid-19 nephropathy was assessed 0.656 (medium effect size). Relative risk and odds ratio of acute kidney disease (AKD) in covid-19 nephropathy were assessed 0.57 and 0.4, respectively (p-value: 0.422). Correlation between SCr changes and time of emergent AKI (acute kidney injury), AKD and chronic kidney disease (CKD) was assessed with R2 of 0.0003 and p-value of 0.94 (not significant). Conclusion: The present study revealed medium effect size of elevated IL-6 on decreased eGFR. Future clinical research is required for investigating novel unknown findings in covid-19 nephropathy.
Circular RNA circANKS1B as the Sponge of miR-152-3p Promotes Prostate Cancer Progression by up-Regulating TGF-α Expression
Authors: Tao Liangjun , Pan Xinyuan , Wang Jiawei , Zhang Li , Tao Lingsong , Liang Chaozhao 
Published: August 2020

Abstract
Background: Growing studies indicate that circRNAs play critical roles in human diseases, and show great potential as biomarkers and therapeutic targets. This study aims to investigate the expression and function of circANKS1B in prostate cancer (PC).Methods: The expression of circANKS1B and miRNA-152-3p were determined by real-time qRT-PCR. The cell migration and invasion were measured by transwell assay. The interaction between circANKS1B and miR-152-3p was confirmed by dual-luciferase reporter gene assay. Rescue experiments were conducted to demonstrate whether circANKS1B regulated the migration and invasion of PC cells by the circANKS1B-miR-152-3p-TGF-α pathway.Results: The expression of circANKS1B was dramatically up-regulated both in PC cells and tissues. Moreover, high circANKS1B expression was associated with a poor prognosis of PC patients. Dual-luciferase reporter assay indicated that circABKS1B directly bound to miRNA-152-3p. Furthermore, circANKS1B negatively regulated miR-152-3p expression. Knockdown of circANKS1B remarkably suppressed PC cells invasion and TGF-α expression, while the effects of circANKS1B silencing were reversed by miR-152-3p deficiency. In addition, the impact of miR-152-3p silencing on PC cell invasion was also abrogated by TGF-α deficiency. In all, circANKS1B as the sponge of miR-152-3p promotes prostate cancer progression by up-regulating TGF-α expression.Conclusion: Our findings reveal that circANKS1B could be a potential prognostic biomarker and therapeutic target of PC.