bluuebunny/crossref_metadata_2025_split huggingface dataset:
Integrated bioinformatics analysis reveals novel key biomarkers and potential candidate small molecule drugs in diabetic nephropathy
Authors: Joshi Harish , Vastrad Basavaraj , Joshi Nidhi , Tengli Anandkumar , Vastrad Chanabasayya , Kotturshetti Iranna 
Published: March 2021

Abstract
The underlying molecular mechanisms of diabetic nephropathy (DN) have yet not been investigated clearly. In this investigation, we aimed to identify key genes involved in the pathogenesis and prognosis of DN. We selected expression profiling by high throughput sequencing dataset GSE142025 from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) between DN and normal control samples were analyzed with limma package. Gene ontology (GO) and REACTOME enrichment analysis were performed using ToppGene. Then we established the protein-protein interaction (PPI) network, miRNA-DEG regulatory network and TF-DEG regulatory network. The diagnostic values of hub genes were performed through receiver operating characteristic (ROC) curve analysis. Finally, the candidate small molecules as potential drugs to treat DM were predicted using molecular docking studies. Through expression profiling by high throughput sequencing dataset, a total of 549 DEGs were detected including 275 up regulated and 274 down regulated genes. Biological process analysis of functional enrichment showed these DEGs were mainly enriched in cell activation, response to hormone, cell surface, integral component of plasma membrane, signaling receptor binding, lipid binding, immunoregulatory interactions between a lymphoid and a non-lymphoid cell and biological oxidations. DEGs with high degree of connectivity (MDFI, LCK, BTK, IRF4, PRKCB, EGR1, JUN, FOS, ALB and NR4A1) were selected as hub genes from protein-protein interaction (PPI) network, miRNA-DEG regulatory network and TF-DEG regulatory network. The ROC curve analysis confirmed that hub genes were high diagnostic values. Finally, the significant small molecules were obtained based on molecular docking studies. Our results indicated that MDFI, LCK, BTK, IRF4, PRKCB, EGR1, JUN, FOS, ALB and NR4A1 could be the potential novel biomarkers for GC diagnosis prognosis and the promising therapeutic targets. The present study may be crucial to understanding the molecular mechanism of DN initiation and progression.
Hub Genes and Key Pathway Identification in Wilms Tumor Based on Bioinformatics Analysis
Authors: Vastrad Basavaraj , Vastrad Chanabasayya , Kotturshetti Iranna 
Published: March 2021

Abstract
Wilms tumor (WT) is a childhood kidney cancer with unknown etiology. Gene expression analysis has become very essential in WT. Thus, we performed an integrated analysis of gene expression data to identify new molecular mechanisms and key functional genes in WT. Gene expression (GSE60850) dataset was downloaded from Gene Expression Omnibus. Differentially expressed genes (DEGs) were identified using limma. Pathway and Gene Ontology (GO) enrichment analyses were performed for the DEGs by ToppGene database. Then, protein–protein interaction (PPI) networks and modules were established by the Mentha database and PEWCC1, and visualized by Cytoscape software. Target gene - miRNA regulatory network and target gene - TF regulatory network were established by the Network Analyst database and visualized by Cytoscape software. Finally, survival analysis, expression analysis, stage analysis, mutation analysis, immunohistochemical (IHC) analysis, receiver operating characteristic (ROC), reverse transcription polymerase chain reaction (RT-PCR) and immune infiltration analysis of hub genes was performed. We identified 988 DEGs ultimately including 502 up regulated genes and 486 down regulated genes. Pathway and GO enrichment analysis revealed that DEGs were mainly enriched in D-myo-inositol (3,4,5,6)-tetrakisphosphate biosynthesis, platelet activation, cholesterol biosynthesis III, and complement, coagulation cascades, embryo development, cell surface, DNA-binding transcription factor activity, carboxylic acid metabolic process, extracellular space and signaling receptor binding. FN1, AURKA, TRIM41, NFKBIA, TXNDC5, SIN3A, MAGI1, GPRASP2, UCHL1 and FXYD6 were filtrated as the hub genes. These identified DEGs and hub genes facilitate our knowledge of the underlying molecular mechanism of WT and have the potential to be used as diagnostic and prognostic biomarkers or therapeutic targets for WT.
Epidemiology, pathogens distribution, antibiotic susceptibility and the risk factors for mortality of patients with central nervous system infections: a retrospective study from 2012 to 2019 in a teaching hospital in China
Authors: Zhang Zheng , Song Yan , Kang Jianbang , Duan Surong , Li Qi , Feng Fuqiang , Duan Jinju 
Published: March 2021

Abstract
Background: Central nervous system (CNS) infections are relatively rare but associated with high mortality worldwide. Empirical antimicrobial therapy is crucial for the prognosis of patients with CNS infections, which should be based on the knowledge of pathogens distribution and antibiotic sensitivities. China is a vast country, and the pathogens distribution varies nationwide. The aim of this study is to investigate the features of pathogens in patients with CNS infections in north China and we tried to evaluate the risk factors for mortality.Methods: We retrospectively analyzed the patients with positive cerebrospinal fluid (CSF) culture in a teaching hospital between January 2012 and December 2019. The following information were collected: demographic characteristics, laboratory data, causative organisms and antimicrobial susceptibility results. Univariate analysis and binary logistic regression analysis were performed to identify the risk factors for mortality.Results: In this eight-year retrospective study, a total of 72 patients were diagnosed with CNS infections and 86 isolates were identified. Among all the microorganisms detected, Gram-positive strains consisted of 59.3%, Gram-negative bacteria of 30.2% and fungi of 10.5%. The predominant Gram-positive isolate was coagulase-negative staphylococci. Acinetobacter baumannii, Escherichia coli and Klebsiella were the common Gram-negative strains. Compared to 2012-2015 years, the proportion of Gram-negative bacteria increased markedly during 2016-2019 years. Vancomycin, teicoplanin and linezolid were still 100% sensitive to Gram-positive bacteria. For the multidrug-resistant Gram-negative bacteria, only tigecycline was the 100% sensitive antibiotics. The mortality of the 72 patients was 30.6%. In the multivariate analysis, age >50 years, combined pulmonary infection and CSF glucose < normal value were associated with poor prognosis. Conclusions: CNS infections cause high mortality worldwide. Although Gram-positive bacteria are still the primary pathogen of CNS infections, Gram-negative bacteria had increased in recent years and should be considered in the choice of empirical antibiotic treatment. Special attention should be given to older patients and those combined pulmonary infection and with low CSF glucose level.
Processes and Mechanisms of Phosphorus Mobility Among Sediment, Water and Cyanobacteria Under Hydrodynamic Conditions
Authors: Ren Lingxiao , Ding Keqiang , Hu Zhixin , Wang Huiya , Qi Ning , Xu Wei 
Published: March 2021

Abstract
Phosphorus (P) has an important role in eutrophication and it is essential to explore the processes and mechanisms of P mobility in natural waters. In this study, laboratory experiments were conducted to simulate the SW system (sediment and water) and SAW system (sediment, algae and water) under four hydrodynamic intensity conditions (static control, 50 rpm, 125 rpm and 200 rpm treatments), to investigate P mobility. Results in SW system showed that, sediment was an important source of P for overlying water, and the released total P (TP) increased with stronger hydrodynamic intensity, when P associated with metal pools (redox-sensitive P [BD-P] and meta-oxides bound P [NaOH-P]) were the most unstable and easier to migrate into the overlying water. Stronger hydrodynamic disturbances could enhance the processes including sediment resuspension, dissolution of particles, and release of P, when P mobility had a close relationship with redox conditions near sediment-water interface (SWI). Therefore, the release of TP, BD-P and NaOH-P from sediment increased and decreased in the control and 50-200 rpm treatments over time. In SAW system, the release of TP significantly increased from sediment comparing to SW system, and the growth of Microcystis aeruginosa could selectively enhance the release of BD-P, NaOH-P, and organic P (OP). Meanwhile, the released P from sediment was quickly accumulated by algal cells. The maximum accumulation ability of P by cells, the highest photosynthetic efficiency and the best growth of M. aeruginosa were observed in 125 rpm treatment. But with excessively strong hydrodynamic intensity (200 rpm treatment), the accumulation ability of P and alkaline phosphatase activity (APA) of M. aeruginosa was suppressed, which might hinder algal utilization of P and inhibit algal growth. Overall, our findings demonstrated the patterns of P mobility in natural ecosystems and could contribute to the understanding of P cycling.
Geochemical monitoring of deionized seawater injected underground during construction of an LPG rock cavern in Namikata, Japan, for the safety water curtain system
Authors: Ueda Akira , Ozawa Akiko , Kusakabe Yasushi , Furukawa Takafumi , Yamaguchi Kohei , Yageta Masayuki , Otake Takeshi 
Published: March 2021

Abstract
An underground liquified petroleum gas (LPG) storage facility was constructed between 1998 and 2006 in Namikata, Imabari City, Ehime Prefecture, Japan, to increase domestic LPG stockpiles. The most important issue during construction and operation of this facility is gas leakage prevention. To thwart water leakage, the water curtain system was constructed according to design standards, and a large amount of deionized seawater (seal water) was continuously injected into the rock mass around the cavern to keep the water level constant during both construction and operation. It is possible to distinguish three end member waters (existing groundwater, seawater or fossil seawater, and seal water) using the salinity and isotope (δ18O) difference because seal water injected underground has almost the same δ18O value as seawater. In this study, continuous observation is carried out using the geochemical techniques for flow analysis with a mixing ratio of three end members in the initial construction period (April 2005 to March 2006) of the LPG underground storage facility. It is determined that existing groundwater and seawater originally distributed in this region are partly replaced by seal water in the cavern.
High expression of eIF4E regulates immune cell infiltration and leads to poor prognosis in breast cancer
Authors: Li Fan , Sun Huizhi , Li Yue , Bai Xiaoyu , Dong Xueyi , Zhao Nan , Meng Jie , Sun Baocun , Zhang Danfang 
Published: March 2021

Abstract
Background

The expression and activation of Eukaryotic translation initiation factor 4E (eIF4E) is related to tumor transformation and genesis, but the functional role and the mechanism whereby it drives immune infiltration in breast cancer remain uncertain.
Methods

Multiple databases were used for assessing the expression and clinic-pathological features of eIF4E, after which ImmuCellAI and TIMER database were used to explore the relationship between eIF4E and immune infiltration and clinicopathological information were collected from clinical cases of breast cancer. Finally, the genes co-expressed with eIF4E were identified by LinkedOmics. These genes were analyzed protein interaction network and TF-miRNA interaction network by Networkanalyst, and enriched by GO and KEGG. The key genes of immune markers were functionally annotated.
Results

High expression of eIF4E was associated with poor overall survival (OS) and relapse-free survival (RFS) in breast cancer samples from multiple databases. It is notable that the expression of eIF4E is positively correlated with the infiltration of CD8+T cells, macrophages, neutrophils and dendritic cells. The expression of eIF4E is closely related to many immune markers in breast cancer. Immunohistochemical analysis showed that the patients with high expression of eIF4E related macrophage marker (CD68+) and M2 type marker (CD163+) in tumor stroma(TS) were significantly correlated with poor prognosis (P < 0.05). High infiltration density of CD163+ had significant difference in TNM staging compared with those with low(P < 0.05).Functional analysis of co-expressed genes showed that they were involved in the biological process of human immune response. GO analysis showed that co-expressed immune marker genes were involved in human immune response, adaptive immune response, macrophage activation, extracellular structure organization and regulation of DNA metabolism process. KEGG enrichment showed that it was involved in inflammatory bowel disease, cell adhesion molecule pathway, JAK-STAT signal pathway, T cell receptor signal pathway and so on.
Conclusions

These results suggest that high expression of eIF4E regulates immune cell infiltration, especially promotes macrophage M2 polarization by JAK/STAT6 and PI3K/AKT pathway, which is associated with poor prognosis of breast cancer patients. It is a valuable prognostic biomarker for breast cancer patients, and may be a potential therapeutic target in the future.
Joint of Modeling Techniques and Life Cycle Assessment for Prediction of Yield, Economic Profit, and Global Warming Potential for Wheat Farms
Authors: Ghasemi-Mobtaker Hassan , Kaab Ali , Rafiee Shahin 
Published: March 2021

Abstract
Forecasting crop yield and its environmental effects can help increase agricultural energy efficiency and reduce environmental impacts. This study provides mathematical, adaptive network-based fuzzy inference system (ANFIS) and neural networks (ANNs) techniques for forecast yield, economic profit, and global warming of wheat production. For this purpose, 75 wheat farms located in the central area of Hamadan province were selected randomly and data were gathered through oral interview. Then, computed the input and output energy, life cycle assessment (LCA) was utilized to specify the environmental effects of wheat cultivation. The calculations displayed that the averages of inputs and outputs energy were about 43055 MJ ha−1 and 117407 MJ ha−1, respectively. The LCA results demonstrated that wheat cultivation cause to the emissions of 624.29 kg CO2 eq. ton−1. ANN structures for predicting yield, economic profit and global warming in wheat production with two hidden layers were the best topologies. ANFIS model results indicated that in the 3-level ANFIS model, the highest R2 is found for net return (0.962). The results comparison showed that ANN and ANFIS models outperform linear models to predict yield, economic profit, and global warming of wheat production.
Tool Wear Prediction Using a Hybrid of Tool Chip Image and Evolutionary Fuzzy Neural Network
Authors: Lin Cheng-Jian , Jhang Jyun-Yu , Chen Shao-Hsien 
Published: March 2021

Abstract
This paper proposed an evolutionary fuzzy neural network (EFNN) for tool wear prediction. The material chip is affected by cutting conditions during the cutting process. The different tool wear status causes different chip color which means the color of material chip can be an important factor for tool wear prediction. In this study, an industrial camera is used to capture chip image and convert it into CIE xy chromaticity features through a color conversion model. In addition, to improve the prediction accuracy, a dynamic group cooperative particle swarm optimization (DGCPSO) is proposed to optimize the EFNN parameters. The cutting time and CIE xy value are used as the input of the EFNN, and the output is predicted tool wear value. The experimental results show that the mean absolute percentage error (MAPE) of the proposed EFNN is 2.83% better than other methods.
Multimodal characterization of macular telangiectasia type 2 and correlation with multifocal electroretinogram
Authors: Ayachit Apoorva , Reddy Lakshmipriya Uday , Joshi Shrinivas , Ayachit Guruprasad 
Published: March 2021

Abstract
1. Purpose: To study the correlation of multimodal imaging in macular telangiectasia (Mac Tel) with foveal function on multifocal electroretinogram (mfERG)2. Methods: Eyes with non- proliferative Mac Tel diagnosed based on clinical examination, optical coherence tomography (OCT), autofluorescence (AF), fluorescein angiography (FA), OCT angiography (OCTA). Control group with normal eye exam included for multifocal electroretinogram.Staging of OCT, OCTA, AF and FA done in Mac Tel subjects. mfERG done in study subjects and controls. Correlation of imaging modalities and P1 amplitudes at fovea (ring 1) studied in terms of correlation co-efficient.3. Results: Twenty nine eyes of 16 patients of Mac Tel and 25 eyes of 19 controls were included. BCVA was 0.38 ± 0.266 in study eyes and 0 in control eyes. On OCT it was observed that 41.4% Mac Tel eyes (n = 12) belonged to stage 3, 37.9%(n = 11)) eyes belonged to stage 2 and 20.7% (n = 6) eyes belonged to stage 1. AF- Stage 3 comprised of 75.9% eyes (n = 22); 4 eyes belonged to stage 2 and 3 eyes to stage 1. On FA, 18 eyes belonged to stage 3 (62.1%); stage 2 was seen in 1 (3.4%) eye and stage 1 was seen in 10 (34.5%) eyes. There was decrease in P1 amplitudes from R1(p < 0.001), R2( 0.001), R3 (< 0.001) and R4 (0.001) in Mac Tel eyes compared to control eyes but not in R5 (p 0.785). SD- OCT had positive correlation with FAF (CC 0.747,p < 0.001) FFA (CC 0.775, p < 0.001) and R1P1 (CC 0.682, p < 0.001). With OCTA there was no significant correlation (CC 0.318, p 0.093). There was positive and significant correlation of OCT (0.682,<0.001), OCTA (0.379,p 0.042) AF ( 0.635, p < 0.001) and FA (0.495, p < 0.006) with R1P1.4. Conclusions: Existing multimodal imaging systems can be reliable indicators of foveal function as on mfERG.
Combination of XGBoost Analysis and Rule-Based Method for Intrapartum Cardiotocograph Classification
Authors: Kuo Pao-Lin , Lim Bee Yen , Du Yi-Chun , Chen Po-Fan , Tsai Pei-Yin 
Published: March 2021

Abstract
Cardiotocograph (CTG) contains uterine contraction (UC) and fetal heart rate (FHR) signals, which is an important information of clinical pregnant woman care. National Institute of Child Health and Human Development (NICHD) is one of the reference guides for clinical care and it classified pregnant woman into three categories including I, II, and III to evaluate the status of fetus. However, when it comes to manual interpretation was time-consuming and not easy to observe the slight differences. In this study, we combined rule-based method and eXtreme Gradient Boosting (XGBoost) analysis for intrapartum cardiotocograph classification. Because the category II of NICHD is defined unknown status, XGBoost analysis was used to classify the category II into IIa and IIb, and analyze their probability of fetal distress (FD). From the clinical trial of 68 pregnant women, the results of three categories (I, II and III) were consistent and no statistical difference with the clinicians’ interpretation and the average Kappa was about 0.72. The results also indicated that the probability of FD was 28.8% and 71.2% in category IIa and IIb, respectively. It shows the proposed method has potential to provide a clinical assistant tool for pregnant women care.
A new uncertain linear regression model based on equation deformation
Authors: Wang Shuai , Ning Yufu , Shi Hongmei 
Published: March 2021

Abstract
When the observed data are imprecise, the uncertain regression model is more suitable for the linear regression analysis. Least squares estimate can fully consider the given data and minimize the sum of squares of residual error, and can effectively solve the linear regression equation of imprecisely observed data. On the basis of uncertainty theory, this paper presents an equation deformation method for solving unknown parameters in uncertain linear regression equations. We first establish the equation deformation method of one-dimensional linear regression model, and then extend it to the case of multiple linear regression model. We also combine the equation deformation method with Cramer's rule and matrix, and propose the Cramer's rule and matrix elementary transformation method to solve the unknown parameters of the uncertain linear regression equation. Numerical examples show that the equation deformation method can effectively solve the unknown parameters of the uncertain linear regression equation.
Psychometric Validation of the EORTC QLQ-HCC18 in Patients with Previously Treated Unresectable Hepatocellular Carcinoma
Authors: Serrano Daniel , Podger Lauren , Barnes Gisoo , Song James , Tang Boxiong 
Published: March 2021

Abstract
Purpose: Demonstrate the measurement properties of the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Hepatocellular Carcinoma 18-question module (EORTC QLQ-HCC18) within a previously treated, unresectable HCC clinical trial population that was distinct from the published QLQ-HCC18 validation population. Methods: Analyses were conducted using data from BGB-A317-208, an open label, international, clinical trial of the monoclonal antibody tislelizumab in adult HCC patients. The EORTC Quality of Life Questionnaire Core 30 (EORTC QLQ-C30) and QLQ-HCC18 were assessed at baseline as well as weeks 3 and 9. Psychometric validation of the QLQ-HCC18 included reliability, construct validity, ability to detect change, and meaningful within-patient change (MWPC). Known-groups validity and MWPC analyses were also stratified on several pre-defined subpopulations. Results: A total of 248 patients were included. The QLQ-HCC18 fatigue, nutrition, and index domains demonstrated acceptable internal consistency; acceptable test-retest reliability was found for fatigue, body image, nutrition, pain, sexual interest, and index domains. The QLQ-HCC18 fatigue domain achieved acceptable concurrent validity for 13 of 16 correlations; the index domain achieved acceptable concurrent validity for 15 of 16 correlations. Clear differentiation of the QLQ-HCC18 change scores between improvement and maintenance anchor groups were observed for body image, fatigue, pain, and index domains. Differentiation between deterioration and maintenance anchor groups were observed for fever and fatigue domains. MWPC point estimates defining improvement for the QLQ-HCC18 fatigue and index domains were -7.18 and -4.07, respectively; MWPC point estimates defining deterioration were 5.34 and 3.16, respectively. Conclusions: The EORTC QLQ-HCC18 fatigue and index domains consistently demonstrated robust psychometric properties, supporting the use of these domains as suitable patient-reported endpoints within a previously treated, unresectable HCC patient population.