bluuebunny/crossref_metadata_2025_split huggingface dataset:
Acute Kidney Injury in COVID-19: clinical outcomes and risk factors
Authors: Jin Kui , Xie Tuxiu , Seery Sam , Ye Lu , Jiang Jie , Yang Weize , Luo Xiaomin , Wei Jie , Yin Lu , Fu Yangyang , Yu Shanshan , Zhang Lili , Xu Jun , lyu Jingjun 
Published: June 2020

Abstract
Background:Understanding of the incidence and effects of acute kidney injury (AKI) in patients diagnosed with COVID-19 is limited. The purpose of this study was to examine risk factors and related outcomes associated with AKI among patients diagnosed with COVID-19. Method: This is a retrospective cohort study of patients diagnosed with COVID-19 associated-pneumonia admitted to a tertiary hospital in Wuhan between January to February 2020. AKI was defined and staged according to the Kidney Disease: Improving Global Outcome (KDIGO) classification criteria. Cox’s multivariate regression and logistic regression modelling were used to assess the effects of AKI on hospital mortality and risk factors associated with occurrence of AKI. Primary outcomes were risk-adjusted in-hospital mortality.Results:342 patients were finally enrolled in this study. AKI occurred in 13.4% (n = 46), among them 7.0% (n = 24) developed stage 1AKI, and 6.4% (n = 22) developed stage 2 - 3 AKI. Overall 26.9% (n = 92) died during hospitalization. Among them 19.3% (57/296) of the non-AKI patients died, 62.5%(15/24) of stage 1 AKI patients, and 90.9% (20/22) of stage 2 - 3 AKI patients died. AKI was strongly associated with mortality (HR 2.52; 95% CI, 1.59-3.96; p＜0.001). Further analysis shows that progression to AKI stage 2 - 3 doubles the hazard ratio for death. Age, leukocytes number, fibrinogen concentration, C-reative protein level, and severity of pneumonia at admission were independent risk factors associated with the development of AKI. Conclusion:Acute kidney injury is common among hospitalized COVID-19 patients and strongly associated with increased mortality, early detection and prevention of the progression of AKI may be critical to reduce mortality of these patients.
Lymphocytopenia and neutrophilia deteriorate at the lowest oxygenation index timepoint in COVID-19 patient
Authors: Hong Wei-jun , Xu Yi-wen , Li Wei-ling , Xu Chun-qiang , Hu Xiao-fei , Zhang Mei-xian , Xu Hui-hui , Wang En , Ke Shao-fa , Jin Xiao-ping , Wu Gang , Liu Xi-chang 
Published: June 2020

Abstract
BackgroundCoronavirus disease 2019 (COVID-19) spread throughout the world and caused hundreds of thousands of infected people to death. However, the pathogenesis of severe acute respiratory syndrome coronavirus-2 (SARS COV-2) is poorly understood. The objective of this study is to retrospectively explore the pathogenesis of COVID-19 from clinical laboratory findings, taking disease progression into account.MethodsA single-centered, retrospective study was carried out, which included moderate (n=76) and severe COVID-19 cases (n=22). The difference of laboratory findings from blood routine examination and hepatorenal function test were retrospectively evaluated between the state of moderate and severe. The disease progression was indicated by oxygenation index.ResultsAge is a risk factor for disease progression from moderate to severe. Lymphocytopenia, neutrophilia, liver and kidney function decreasement occurred in severe patients on admission, compared with moderate patients. Lymphocytopenia and neutrophilia deteriorated at the lowest oxygenation index timepoint in the severe patients. And the oxygenation index was associated with ratio of lymphocyte and neutrophil in COVID-19 patients.ConclusionsLymphocytopenia and neutrophilia, which deteriorate in the progression of severe patients, are the main pathogenesis of COVID-19. More measures need to be taken to control lymphocytopenia and neutrophilia in severe COVID-19. Oxygenation index presented potentiality as predictor on the progression of COVID-19.
Modeling of spreading of the novel coronavirus based in the&nbsp;stochastic dynamic
Authors: Lima Leonardo S. 
Published: June 2020

Abstract
In this paper, one proposes a stochastic model based on Itô diffusion as mathematical model for time evolution of novel cases N(t) of the SARS-CoV-2 (COVID-19) in each day t. I propose a correspondent stochastic differential equation (SDE) analogous to classical differential equation for epidemic growing for some diseases as smallpox and typhoid fever. Furthermore, we made an analysis using the Fokker-Planck equation giving an estimating of the novel cases in the day t as the mean half-width of the distribution P(N,t) of novel cases. My results display that the model based on Itô diffusion fits well to the results supported by healthy Brazilian agencies due to large uncertainly in the official data generated by the low number of tests realized generating so a strong randomness in the official data.
A Network Pharmacology Based Analysis of The Potential Mechanisms of Compound Danshen Dripping Pill for Treatment of Diabetic Retinopathy
Authors: Zhang Xinyue , Wang Lizhen , Huang Xiaoying , Zheng Yanlin 
Published: June 2020

Abstract
Background: Diabetic retinopathy (DR) has become a worldwide concern in recent years because of the high prevalence and vision-threat. The limited therapies have been in stark contrast to its high prevalence. On top of that, almost all the treatments, like laser, are applied only at the end stage of this disease. However, with the development of network pharmacology, a traditional Chinese medicine (TCM), Compound Danshen Dripping Pill (CDDP), may bring some new insights into the early intervention of DR. Methods: The active compounds and potential targets of CDDP and DR-related targets were collected from the TCMSP, UniProt, GeneCards and OMIM databases. And protein-protein interactions (PPI) information was achieved from the STRING database. The gene enrichment analysis of GO and KEGG was carried out by “clusterProfiler” in R software. The collected data was then used to form network maps of compound-target and PPI, or visualized by the software of Cytoscape. Results: 54 compounds and 50 targets were identified for CDDP against DR. Among the predicted effective compounds, 29 tanshinones from Radix Salviae (Danshen) were identified. And the core targets might be estrogen receptor (ESR1), androgen receptor (AR), caspase-3 (CASP3), Interleukin-6 (IL6) and vascular endothelial growth factor A (VEGFA) in 50 targets. There were 266 significantly correlated biological processes such as steroid hormone response, oxidative stress and apoptosis enriched out. Besides, The 50 targets significantly participate in 97 pathways and mainly enriched in advanced glycation end products (AGE)-receptor for advanced glycation end products (RAGE), fluid shear stress and atherosclerosis, apoptosis and VEGF signal pathway et al.Conclusions: The mechanisms of CDDP for treating DR may involve multi-compound, multi-target and multi-pathway synergistic effects. It may participate in the regulation of steroid hormone response, oxidative stress, apoptosis and hemodynamics in diabetic retina. Tanshinones and luteolin from Radix Salviae were probably responsible for the effectiveness of CDDP on DR.
Performance of the QPLEXTM Alz Plus Assay, A Novel Multiplex Kit for Screening Cerebral Amyloid Deposition
Authors: Park Jong-Chan , Jung Keum Sim , Kim Jiyeong , Jang Ji Sung , Kwon Sunghoon , Byun Min Soo , Yi Dahyun , Byeon Gihwan , Jung Gijung , Kim Yu Kyeong , Lee Dong Young , Han Sun-Ho , Mook-Jung Inhee 
Published: June 2020

Abstract
Background: Alzheimer's disease (AD) is an irreversible neurodegenerative disease characterized by the hallmark finding of cerebral amyloid deposition. Many researchers have tried to predict the existence of cerebral amyloid deposition by using easily accessible blood plasma samples, but the effectiveness of such strategies remains controversial. Methods: We developed a new multiplex kit, the QPLEXTM Alz plus assay kit, which uses proteomics-based blood biomarkers to prescreen for cerebral amyloid deposition. A total of 300 participants who underwent Pittsburgh compound B (PiB)-positron emission tomography (PET) which allows imaging of cerebral amyloid deposition were included in this study. We compared the levels of QPLEXTM biomarkers between patients who were classified as PiB-negative or PiB-positive, regardless of their cognitive function. Logistic regression analysis followed by receiver operating characteristic (ROC) curve analysis was performed. The kit accuracy was tested using a randomized sample selection method.Results: The results obtained using our assay kit reached 89.1% area under curve (AUC) with 80.0% sensitivity and 83.0% specificity. Further validation of the QPLEXTM Alz plus assay kit using a randomized sample selection method showed an average accuracy of 81.5%.Conclusions: Our QPLEXTM Alz plus assay kit offers a highly effective way to predict cerebral amyloid deposition through a convenient blood test, and should enable easy prediction of AD in daily life.
A graph-based network for predicting chemical reaction pathways in solid-state materials synthesis
Authors: McDermott Matthew J. , Dwaraknath Shyam S. , Persson Kristin A. 
Published: June 2020

Abstract
Accelerated synthesis of inorganic materials remains a significant challenge in the search for novel, functional materials. Many of the chemical principles which enable "synthesis by design" in synthetic organic chemistry do not exist in solid-state chemistry, despite extensive computed/experimental thermochemistry data. We present a chemical reaction network model constructed from thermochemistry databases that captures features of the thermodynamic phase space which synthesis reactions traverse. Directed edges in the network are assigned weights via a transformation that maps reaction parameters to costs. We devise a computationally tractable approach for suggesting likely reaction pathways via application of pathfinding algorithms and linear combination of lowest-cost paths in the network. We demonstrate initial success of the reaction network in predicting a complex metathesis reaction pathway toward yttrium manganese oxide YMnO3. The reaction network presents new opportunities for enabling reaction pathway prediction, rapid iteration between experimental/theoretical results, and ultimately, control of synthesis of solid-state materials.
Defining the Extracellular Matrix of Rhabdomyosarcoma
Authors: Lian Xiaolei , Bond J. Steffan , Bharathy Narendra , Boudko Sergei P. , Pokidysheva Elena , Shern Jack F. , Lathara Melvin , Settelmeyer Teagan , Cleary Megan M. , Bajwa Ayeza , Sriniv Ganapati , Hartley Christopher P. , Bächinger Hans Peter , Mansoor Atiya , Gultekin Sakir H. , Berlow Noah E. , Keller Charles 
Published: June 2020

Abstract
Background: Rhabdomyosarcoma (RMS) is the most common soft-tissue sarcoma of childhood with a propensity to metastasize. Current treatment for patients with RMS includes conventional systemic chemotherapy, radiation therapy and surgical resection; nevertheless, little to no improvement in long term survival has been achieved in decades – underlining the need for target discovery and new therapeutic approaches to targeting tumor cells or the tumor microenvironment.Methods:To evaluate cross-species sarcoma extracellular matrix production, we have used murine models which feature knowledge of the myogenic cell-of-origin. With focus on the RMS/undifferentiated pleomorphic sarcoma (UPS) continuum, we have constructed tissue microarrays of 48 murine and 4 human sarcomas to analyze expression of 7 different collagens, fibrillins and collagen-modifying proteins, with cross-correlation to RNA deep sequencing.Results:We have uncovered that RMS produces increased expression of type XVIII collagen alpha 1 (COL18A1), which is clinically associated with decreased long-term survival. We have also identified significantly increased RNA expression of COL4A1, FBN2, PLOD1 and PLOD2 in human RMS relative to normal skeletal muscle.Conclusion:These results complement recent studies investigating whether soft tissue sarcomas utilize collagens, fibrillins and collagen-modifying enzymes to alter the structural integrity of surrounding host extracellular matrix/collagen quaternary structure resulting in improved ability to improve the ability to invade regionally and metastasize, for which therapeutic targeting is possible.
Identification of the active substances and mechanisms of ginger for the treatment of colon cancer based on network pharmacology and molecular docking
Authors: Zhang MengMeng , Wang Dan , Lu Feng , Zhao Rong , Ye Xun , He Lin , ai li , Wu ChunJie 
Published: June 2020

Abstract
Background: Colon cancer is increasing recently but the high cost and adverse side effects experienced always leads to treatment drop out. Zingiber officinale, commonly known as ginger, is a popular herbal medicine and this study was aimed to identify the active compounds from ginger and to investigate its anti-cancer mechanisms through network pharmacology construction. Results: Ginger compounds were discerned through the TCMSP, which were filtered by the metrics of oral bioavailability and drug likeness, and its related targets were searched. After that, the targets interacting with colon cancer were collected using Genecards, OMIM, and Drugbank databases. Six potential active compounds, 288 interacting targets in addition to 1356 disease-related targets were collected, of which 114 intersection targets were obtained. The PPI network showed that 32 targets including SRC, PIK3R1, and TP53 were identified as key targets. These targets were mainly associated with the biological processes like transmembrane receptor protein tyrosine kinase signaling pathway, regulation of cellular protein localization, cellular response to oxidative stress. KEGG enrichment manifested that ginger probably produced preventive effects against colon cancer by regulating significant signaling pathway like pathway in cancer, hepatitis B, and estrogen signaling pathway. TP53, HSP90AA1, MAPK8, JAK2, CASP3, and ERBB2 could be viewed as the most potential target proteins, which were validated by molecular docking simulation.Conclusion: This study demonstrated the multi-component, multi-target, and multi-pathway characteristics of ginger, providing novel insight for ginger compounds developed as new drug for anti-colon cancer.
Recombinant Bacteriophage LysKB317 Endolysin Mitigates Lactobacillus Infection of Corn Mash Fermentations
Authors: Lu Shao- Yeh , Bischoff Kenneth M. , Rich Joseph O. , Liu Siqing , Skory Christopher D. 
Published: June 2020

Abstract
Background Commercial ethanol fermentation facilities traditionally rely on antibiotics for bacterial contamination control. Here we demonstrate an alternative approach to treat contamination using a novel peptidoglycan hydrolase (LysKB317) isolated from a bacteriophage, EcoSau. This endolysin was specially selected against Lactobacillus strains that were isolated as contaminants from a fuel ethanol plant. The LysKB317 gene was recombinantly expressed in Escherichia coli as a 33 kDa purified enzyme. Results In turbidity reduction assays, the recombinant enzyme was subjected to a panel of 32 bacterial strains and was active against 28 bacterial strains representing one species of Acetobacter, eight species of Lactobacillus, one species of Pediococcus, three species of Streptococcus, and one species of Weissella. The activity of LysKB317 was optimal around pH 6, but it has broad activity and stability from pH 4.5 – 7.5 up to at least 48 h. Maximum activity was observed at 50°C up to at least 72 h. In addition, LysKB317 was stable in 30% ethanol up to at least 72 h. In experimentally infected corn mash fermentations, 1 µM endolysin reduced bacterial load by 4-log fold change, while 0.01 µM reduced bacteria by 2-log fold change. Concentration of fermentation products (ethanol, residual glucose, lactic acid, and acetic acids) for infected cultures treated with ≥ 0.01 µM LysKB317 were similar to uncontaminated controls. Conclusion Exogenously added LysKB317 endolysin is functional in conditions typically found in fuel ethanol fermentations tanks and may be developed as an alternative to antibiotics for contamination control during fuel ethanol fermentations.
Comparison of Obesity-Related Parameters as Predictors of High Pulse Wave Velocity in Middle-Aged and Elderly People in China: A Multicenter Cross-Sectional Community-Based Study
Authors: Sun Ting , Xie Hui , Ma Zuchang 
Published: June 2020

Abstract
Background: The association between fat-related parameters and occurrence of high pulse wave velocity (PWV) in Chinese middle-aged and elderly people is unknown, especially when booy composition indicators are compared.Methods: A total of 3219 middle-aged and elderly subjects who were recruited from 6 community health service centers located in Hefei, Bengbu, and Chuzhou met the inclusion criteria and had valid data. E-health promotion system was used to collect health basic data, and brachial-ankle pulse wave (baPWV) and body composition of each subject were measured. Partial correlation and binary logistic regression analyses were performed to identify associations between fat-related parameters and high PWV, and receiver operating characteristic curves were analyzed for optimal cutoff values and predictive capacity for high PWV.Results: The highest partial correlation coefficients (adjusted for age) for waist-to-height ratio (WHtR) were in middle-aged women and elderly men (range, 0.1-0.31); and that for waist circumference (WC) were in elderly women and middle-aged men (range, 0.12-0.29). WHtR explained the largest proportion of variation for dependent variables, with an R2 value ranging from 0.088 to 0.216 in Model 1; the beta of WC was slightly higher than that of WHtR in elderly women in Models 2 and 3. The predictive capacities of these parameters were lower in men. The area under the receiver operating characteristic curve was higher for WHtR (0.573–0.693) than for the other parameters in both men and women, with optimal cutoff values of 0.51-0.54.Conclusions: WHtR and WC may be useful for community-based screening of women ≥40 years as a secondary preventative measure for high PWV. These 2 parameters can be used in conjunction with others (eg., body composition index) to predict the risk of high PWV based on region, age, and sex.
Generation and Characterization of Skeletal Muscle Cell based Model for GNE Myopathy: Implications in Actin Dynamics
Authors: Devi Shamulailatpam Shreedarshanee , Yadav Rashmi , Mashangva Fluencephila , Chaudhary Priyanka , Sharma Shweta , Arya Ranjana 
Published: June 2020

Abstract
UDP-N-acetyl glucosamine-2 epimerase/ N-acetyl mannosamine kinase (GNE) catalyzes key enzymatic reactions in the biosynthesis of sialic acid. Mutation in GNE gene causes GNE-Myopathy characterized by adult onset muscle weakness and degeneration. GNE is involved in different cellular processes like adhesion, apoptosis, ER stress and autophagy. Lack of appropriate model system limits drug and treatment options for GNE Myopathy as GNE knock out was found to be embryonically lethal. In the present study, we have generated L6 rat skeletal muscle cell-based model system for GNE Myopathy where GNE gene is knocked out at exon 3 using AAV mediated SEPT homology recombination. The cell line was heterozygous for GNE gene with one wild type and one truncated allele as confirmed by sequencing. The phenotype showed reduced GNE epimerase activity with little reduction in sialic acid content. In addition, the GNE knock out cell line revealed altered cytoskeletal organization with disrupted actin filament. The signaling cascade regulating actin dynamics such as Rho A, Cofilin, FAK and Src were altered leading to reduced cell migration in GNE heterozygous cells. Our study indicates possible role of GNE in regulating actin dynamics and cell migration of skeletal muscle cell. The skeletal muscle cell based system offers great potential in understanding pathomechanism and target identification for GNE Myopathy.
New Methods for Stress Concentration Factor Calculation in Butt Welded Joints: A Comparative Study
Authors: Randic Miroslav , Pavletić Duško , Fabić Marko 
Published: June 2020

Abstract
Surface cracks in butt-welded joints usually occur in places with increased stress concentrations. The stress concentration factor (SCF) can be calculated using an empirical equation, with five geometric parameters of a butt-welded joint (thickness of the base material, toe radius, weld toe angle, weld width, and reinforcement height). However, in anindustrial environment, it is impractical and sometimes even impossible to measure all five geometric parameters with sufficient accuracy. In this study, eight experiments on butt-welded joints were performed. All samples were scanned with a 3D scanner, and the geometric sizes of the welded joints were measured using computer software. A modified empirical expression proposed by Ushirokawa and Nakayama was used to calculate the SCF; the expression was adjusted in such a way that the SCF was calculated by knowing only the toe radius. In addition, four new expressions were proposed for the calculation of the SCF by knowing the toe radius in relation to the weld toe angle; the expressions were then compared and analysed. Additionally, the values of the stress concentrations in the butt-welded joints were obtained using afinite element method (FEM). The SCFs calculated using the four methods were compared and further discussed. Our data suggested a new accurate and straightforward approach for calculating the SCF by knowing only the weld toe radius.
Lifestyle-associated health risk indicators across a wide range of occupational groups: a cross-sectional analysis in 72 855 workers
Authors: Väisänen Daniel , Kallings Lena V , Andersson Gunnar , Wallin Peter , Hemmingsson Erik , Ekblom-Bak Elin 
Published: June 2020

Abstract
ObjectivesIdentify and compare health risk indicators for common chronic diseases between different occupational groups. Methods A total of 72,855 participants (41% women) participating in an occupational health servicescreening in 2014–2019 were included. Occupation was defined by the Swedish Standard Classification of Occupation, and divided into nine major and additionally eight sub-major groups. These were analysed separately, as white- and blue-collar occupations and as low- and high-skilled occupations. Seven health risk indicators were self-reported: exercise, physical work situation, sitting at work and leisure, smoking, diet, and perceived health, whereas cardiorespiratory fitness, BMI and blood pressure were measured. These were further dichotomized (yes/no) and as clustering of risk indicators (≥3 vs. <3).ResultsThe greatest variation in OR across sub-major and major occupational groups were seen for daily smoking (OR=0.68 to OR=5.12), physically demanding work (OR=0.55 to OR=45.74) and high sitting at work (OR=0.04 to OR=1.86). For clustering of health risk indicators, blue-collar workers had significantly higher clustering of health risks (OR: 1.80; 95% CI 1.71-1.90) compared to white-collar workers (reference). Compared to high-skilled white-collar workers, low-skilled white-collar workers had similar OR (2.00; 1.88-2.13) as high-skilled blue-collar workers (1.98; 1.86-2.12), with low-skilled blue-collar workers having the highest clustered risk (2.32; 2.17-2.48).ConclusionThere were large differences in health risk indicators across occupational groups, mainly between high-skilled white-collar occupations and the other occupations, with important variations also between major and sub-major occupational groups. Future health interventions should target the occupational groups identified with the highest risk for effective disease prevention.