bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Effect of Helicobacter Pylori Eradication on Paraoxonase Enzyme Activity
Authors: SACIKARA Muhammed , BULUR Oktay , POLAT Mehmet , NAZLIGUL Yaşar 
Published: June 2020

Purpose: Helicobacter pylori (H. pylori) infection is associated with gastrointestinal and extraintestinal diseases either directly via its special virulence factors or indirectly by increasing inflammation and oxidation. Paraoxonase-1 (PON–1) enzyme that is related to HDL cholesterol is responsible for the antioxidant and antiatherogenic effects of HDL cholesterol. PON–1 level is related to the risk of cardiovascular disease. We aimed to investigate the relation between H. pylori infection and PON-1 activity.
Material -Method: We prospectively evaluated 126 adult patients in a tertiary reference hospital in Ankara, Turkey. After H. pylori eradication therapy and checking for treatment success, 38 H. pylori-positive (17 male, 21 female) and 88 H. pylori-negative (43 male, 45 female ) patients were included in this study.
Results: PON–1 enzyme levels after H. pylori eradication therapy were 165,69U/L in H. pylori-negative and 131,68 U/L in H. pylori-positive groups. The difference in PON–1 enzyme levels after treatment in two groups was statistically significant (p=0,02).
Conclusion: Increased PON–1 enzyme levels after H. pylori eradication therapy might play a role in the antiatherosclerotic effect by reducing LDL oxidation.
Avaliações antioxidante e antifúngica dos óleos essenciais de Hymenaea stigonocarpa Mart. ex Hayne e Hymenaea courbaril L.
Authors: Menezes Filho Antonio Carlos Pereira de , Oliveira Filho Josemar Gonçalves de , Castro Carlos Frederico de Souza 
Published: June 2020

Hymenaea stigonocarpa e Hymenaea courbaril var. courbaril são espécies vegetais pertencentes a família Leguminosae, sendo encontrados no domínio Cerrado. Apresentam frutificação anual com frutos com casca densa e aromática. O trabalho teve por objetivo avaliar o rendimento, e as atividades antioxidante e antifúngica do óleo puro e mix (mistura de ambos os óleos em igual concentração). Para extração, foi utilizado equipamento tipo Clevenger, o rendimento foi determinado em porcentagem. A atividade antioxidante foi determinada em microplacas utilizando como modelo o radical DPPH nas seguintes concentrações, partindo do óleo puro, 50, 40, 30, 20, 10, 5, 2,5 e 1,25 µL mL-1. A atividade antifúngica foi avaliada por difusão em ágar utilizando sucessivas diluições de óleo essencial puro e nas concentrações 50, 25, 12,5, 6,25, 3,13 e 1,56 µL mL-1 e mix mistura de ambos os óleos em partes iguais em DMSO, sobre Sclerotinia sclerotiorum, Colletotrichum acutatum e gloeosporioides, e para Aspergillus flavus e niger. O rendimento foi de 0,04 e 0,06% para H. stigonocarpa e H. courbaril, respectivamente. A atividade antioxidante apresentou bons resultados, para ambos os óleos essenciais de H. stigonocarpa e H. courbaril com alta redução do radical DPPH para puro e nas concentrações 50 e 40 µL mL-1. Já para o mix a concentração 50 µL mL-1 taxa de 72% de redução. No experimento antifúngico foi observada alta eficiência no controle de crescimento das hifas para o óleo essencial de H. stigonocarpa com 83% sobre Sclerotinia sclerotiorum, 75% sobre C. acutatum, e para A. flavus com 55%, respectivamente. Para o óleo essencial de H. courbaril foi observada taxa de inibição de 100% para S. sclerotiorum, 100% para C. gloeosporioides e de 70% para A. flavus. Já para o mix de óleos essenciais foi observada redução no crecimento de 88% para S. sclerotiorum, 56% C. gloesporioides e de 42% para A. niger. Os óleos essenciais puros e mix apresentaram resultados promissores como agentes antioxidantes e antifúngicos naturais in vitro.
Incorporating Dynamic Production-Logging Data to the Permeability-Estimation Workflow Using Machine Learning
Authors: Guimaraes Ciro S. , Schirmer Luiz , Schardong Guilherme , Barreto Abelardo B. , Lopes Helio 
Published: June 2020

Summary
The objective of this work is to develop and train feedforward artificial neural networks (ANNs) on the forecasting of layer permeability in heterogeneous reservoirs. The results are validated by comparing the model outputs with permeability curves computed from production logging data.
Production logs are used as targets to train the model. A flow-profile interpretation method is used to compute continuous permeability curves free of wellbore skin effects. In addition, segmentation techniques are applied to high-resolution ultrasonic image logs. These logs provide not only the image of the mega- and giga-pore system but can also identify the permeable facies along the reservoir. The image segmentation jointly with other borehole logs provides the necessary features for the network training process.
The proposed neural network focuses on delivering reliable and validated permeability curves. Its development accounts for formation skin factor, as well as nongeological noise usually found in ultrasonic image logs. The procedure is tested on both synthetic and field data sets. The estimations presented herein demonstrate the model's ability to learn nonlinear relationships between geological input variables and reservoir dynamic data even if the actual physical relationship is complex and not known a priori. Although the preprocessing stages of the procedure involve some expertise in data interpretation, the neural-network structure can be easily coded in any programming language, requiring no assumptions on physics in advance.
For the case studies presented in this work, the proposed procedure provides more accurate permeability curves than the ones obtained from conventional methods, which usually fail to predict the permeability measured on drill-stem tests conducted in dual-porosity reservoirs. The novelty of this work is to incorporate dynamic production-logging (PL) data into the permeability-estimation workflow.
Correction Notice: The preprint paper was updated from its originally published version to correct Fig. 17 on page 11. An erratum detailing the change is included in the Supporting Information section below.
A Protocol for Revealing Oral Neutrophil Heterogeneity by Single-Cell Immune Profiling in Human Saliva
Authors: Choudhury Saibyasachi N. , Novotny Mark , Aevermann Brian D , Lee Steven , Mandava Aishwarya , Qian Yu , Scheuermann Richard , Freire Marcelo 
Published: June 2020

Abstract
Neutrophils are the most abundant white blood cells in the human body responsible for fighting viral, bacterial and fungi infections. Out of the 100 billion neutrophils produced daily, it is estimated that 10 % of these cells end up in oral biofluids. Because saliva is a fluid accessible through non-invasive techniques, it is an optimal source of cells and molecule surveillance in health and disease. While neutrophils are abundant in saliva, scientific advancements in neutrophil biology have been hampered likely due to their short life span, inability to divide once terminally differentiated, sensitivity to physical stress, and low RNA content. Here, we devise a protocol aiming to understand neutrophil heterogeneity by improving isolation methods, single-cell RNA extraction, sequencing and bioinformatic pipelines. Advanced flow cytometry 3D analysis, and machine learning validated our gating system model, by including positive neutrophil markers and excluding other immune cells and uncovered neutrophil heterogeneity. Considering specific cell markers, unique mitochondrial content, stringent and less stringent filtering strategies, our transcriptome single cell findings unraveled novel neutrophil subpopulations. Collectively, this methodology accelerates the discovery of salivary immune landscapes, with the promise of improving the understanding of diversification mechanisms, clinical diagnostics in health and disease, and guide targeted therapies.
Prognostic Value of Neutrophil-to-Lymphocyte Ratio and Location in Patients With EGFR Mutant Metastatic Non-Small Cell Lung Cancer Treated with TKIs
Authors: Xie Xueqi , Li Xiaolin , Tang Wenjie , Chen Jinlong , Yu Jinming , Li Minghuan , Xie Peng 
Published: June 2020

Abstract
Background: Targeted therapy with the epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) has improved the field of metastatic non-small cell lung cancer treatment. Higher neutrophil-to-lymphocyte ratio (NLR) and lower relative lymphocyte counts as inflammatory indicators and associated with worse overall survival and progression free survival (PFS) in several tumor types. Few studies focused on these inflammation markers in field of TKIs eras. Methods: Patients with advanced EGFR mutation NSCLC treated with TKIs were included. Pre-treatment NLR means neutrophil to lymphocyte ratio measured in peripheral blood within one week before treating with TKIs. The baseline clinical characteristics of each group were compared by chi-square and t tests. Cox regression analyses were used to evaluate prognostic value of peripheral blood parameters on progression free survival (PFS). All prognostic factors were explored with multivariable regression. Results: We retrospectively analyzed 221 patients with metastatic NSCLC harboring exon 19 deletion, 21 L858R or rare mutation and receiving TKIs. Finally, a total of 190 patients were analyzed. The optimal cutoff values for pretreatment absolute lymphocyte count (Lym), lymphocyte percentage (Lym%), absolute neutrophil count (Neu), the percentage of neutrophil granulocytes (Neu%) and NLR were 1.625 B, 18.8%, 3.675a, 51.8% and 4.965, respectively. Patients with high neutrophil percent (18.8 months vs 13.0 months, P=0.003), absolute neutrophil counts (12.0 months vs 14.5 months, P=0.014) and NLR (7.0 months vs 15.2 months, P<0.001, one year PFS Rate, 38.4%, respectively) had worse PFS. In contrast, patients with high absolute lymphocyte counts (16.5 months vs 13.0 months, P=0.012) and lymphocyte percent (15.3 months vs 8.8 months, P<0.001) had a better progression-free-survival. Besides, tumor location is also an important factor for prognosis (14.3 months vs 11.6 months, P=0.003). On multivariate analysis, NLR and primary tumor location were both identified as independent and significantly risk indicators for worse PFS. Conclusion: NLR and primary location are both independent prognostic factors for PFS in patients with metastatic EGFR mutated lung tumor. Whether or not NLR and primary location could be useful markers in efficacy prediction of TKIs in advanced NSCLC calls for further investigation.
Spatiotemporal spread pattern of the COVID-19 cases in China
Authors: Feng Yongjiu , Li Qingmei , Tong Xiaohua , Wang Rong , Zhai Shuting , Gao Chen , Lei Zhenkun , Chen Shurui , Zhou Yilun , Wang Jiafeng , Yan Xiongfeng , Xie Huan , Chen Peng , Liu Shijie , Xv Xiong , Liu Sicong , Jin Yanmin , Wang C. , Hong Zhonghua , Luan Kuifeng , Wei Chao , Xu J. , Jiang Hua , Xiao Changjiang , Guo Yiyou 
Published: June 2020

Abstract
COVID-19 is currently spreading widely around the world, causing huge threats on public safety and global society. This study analyzes the spatiotemporal spread pattern of the COVID-19 in China, reveals China’s epicenters of the epidemic through spatial clustering, and delineates the substantial effect of distance to Wuhan on the COVID-19 spread. The results show that the daily new COVID-19 cases mostly occurred in and around Wuhan before March 6, and then moved to the Grand Bay Area (Shenzhen, Hong Kong and Macau). The total COVID-19 cases in China were mainly distributed in the east of the Huhuanyong Line, where the epicenters account for more than 60% of the country’s total on 24 January and 7 February, half on 31 January, and more than 70% from 14 February. The total cases finally stabilized around 84,000, and the inflection point for Wuhan was on 14 February, one week later than those of Hubei (outside Wuhan) and China (outside Hubei). The generalized additive model-based analysis shows that population density and distance to provincial cities significantly associated with the total number of the cases, while distances to prefecture cities and inter-city traffic stations, and population inflow from Wuhan after 24 January, had no strong relationships with the total number of cases. The results and findings should provide valuable insights for understanding the changes in the COVID-19 transmission and controlling the global COVID-19 spread.
Establishment of Multifactor Predictive Models for the Occurrence and Progression of Cervical Intraepithelial Neoplasia
Authors: Chen Mengjie , Wang He , Liang Yuejuan , Hu Mingmiao , Li Li 
Published: June 2020

Abstract
Background
To study the risk factors involved in the occurrence and progression of cervical intraepithelial neoplasia (CIN) and to establish predictive models.
Methods
Genemania was used to build a gene network. Then, the core gene-related pathways associated with the occurrence and progression of CIN were screened in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Real-time fluorescence quantitative polymerase chain reaction (RT-qPCR) experiments were performed to verify the differential expression of the identified genes in different tissues. R language was used for predictive model establishment.
Results
A total of 10 genes were investigated in this study. A total of 30 cases of cervical squamous cell cancer (SCC), 52 cases of CIN and 38 cases of normal cervix were enrolled in. Compared to CIN cases, the age of patients in the SCC group was older, the number of parities was greater, and the percentage of patients diagnosed with CINII + by TCT was higher. The expression of TGFBR2, CSKN1A1, PRKCI and CTBP2 was significantly higher in the SCC groups. Compared to patients with normal cervix tissue, the percentage of patients who were HPV positive and were diagnosed with CINII + by TCT was significantly higher. FOXO1 expression was significantly higher in CIN tissue, but TGFBR2 and CTBP2 expression was significantly lower in CIN tissue. The significantly different genes and clinical factors were included in the models.
Conclusions
Combination of clinical and significant genes to establish the random forest models can provide references to predict the occurrence and prediction of CIN.
A Comprehensive RNA Handling and Transcriptomics Guide for High-Throughput Processing of Plasmodium Blood-Stage Samples.
Authors: Kucharski Michal , Tripathi Jaishree , Nayak Sourav , Zhu Lei , Wirjanata Grennady , Pluijm Rob W. van der , Dhorda Mehul , Dondorp Arjen , Bozdech Zbynek 
Published: June 2020

Abstract
BackgroundSequencing technology advancements opened new opportunities to use transcriptomics for studying malaria pathology and epidemiology. Even though in recent years the study of whole parasite transcriptome proved to be essential in understanding parasite biology there is no compiled up-to-date reference protocol for the efficient generation of transcriptome data from growing number of samples. Here, we present a comprehensive methodology on how to preserve, extract, amplify, and sequence full-length mRNA transcripts from Plasmodium-infected blood samples that can be fully streamlined for high-throughput studies.Results We evaluated the utility of various commercially available RNA-preserving reagents in a range of storage conditions. Similarly, we compared several RNA extraction protocols and established the one most suitable for the extraction of high-quality total RNA from low-parasitemia and low-volume blood samples. Furthermore, we updated the criteria needed to evaluate the quality and integrity of Plasmodium RNA in the presence of human RNA. Optimization of SMART-seq2 amplification method to better suit AT-rich P. falciparum RNA samples allowed us to generate high-quality transcriptomes from as little as 10ng of total RNA and a lower parasitemia limit of 0.05%. Finally, we designed a modified method for depletion of unwanted human hemoglobin transcripts using in vitro CRISPR-Cas9 treatment, thus improving parasite transcriptome coverage in low parasitemia samples. To prove the functionality of the pipeline for both laboratory and field strains, we generated the highest 2-hour resolution RNA-seq transcriptome for Plasmodium falciparum 3D7 intraerythrocytic lifecycle available up-to-date and also applied the entire protocol to create the largest transcriptome data from Southeast Asian field isolates.ConclusionsOverall, our methodology presents an inclusive pipeline for generation of good quality transcriptomic data from a diverse range of Plasmodium-infected blood samples with varying parasitemia and RNA inputs. The flexibility of this pipeline to be adapted to robotic handling will facilitate both small and large scale future transcriptomic studies in the field of malaria.
Geography Matters for Sanitation! Spatial Heterogeneity of the District-level Correlates of Open Defecation in India
Authors: Chakraborty Saurav , Novotný Josef , Das Jadab , Bardahn Aditi , Roy Srijanee , Mondal Swikriti , Patel Priyank Pravin , Santra Sneha , Maity Indranil , Biswas Rimi , Maji Aparajita , Pramanik Suvamoy 
Published: June 2020

Abstract
Background: Sanitation interventions often fail in meeting the desired expectations. A prominent reason is the ecological nature of sanitation phenomena that inherently associates with its high dependence on contextual specifics. This also constrains the generalization of research findings in this domain and substantiates the need to supplement most prevalent micro-level evidence with wider population-level (ecological) studies. This paper thus provides the first quantitative analysis of the spatial heterogeneity of the district-level correlates of open defecation in India. It focuses on a contiguous region of 266 districts (their rural parts) comprising of seven northern and eastern Indian states, all of which had comparatively high open defecation rates in 2011.Methods: We employ standard non-spatial regression, spatially explicit regressions and multi-scale geographically weighted regression to compare the stability of the measurable correlates of open defecation across these different methods as well as across the analyzed spatial units. Results: Attributes like the ownership of household assets, drinking water inaccessibility and prevalent literacy rates were identified as the most stable district-level correlates of open defecation in this region. A higher share of Muslims in the population positively correlated with lower open defecation rates, while this relationship was amplified by the population density. This finding support hypotheses about the positive sanitation externalities stemming from the spatial co-concentrations of Muslim and non-Muslim populations. Conclusions: Our analyses demonstrate notable spatial clustering and significant spatial non-stationarity of the examined variables. Therefore, research findings that ignore the spatial heterogeneity of sanitation drivers possibly provide incomplete information for practice.
Climate Signals in River Flood Damages Emerge under Sound Regional Disaggregation
Authors: Sauer Inga , Reese Ronja , Otto Christian , Geiger Tobias , Willner Sven N. , Guillod Benoit , Bresch David , Frieler Katja 
Published: June 2020

Abstract
Climate change highly affects precipitation patterns. Here, we address the question whether the signal of climate change is already detectable in time series of reported damages caused by fluvial floods. Building on hazard indicators from process-based hydrological simulations, we develop an empirical model to reconstruct reported damages and quantify individual contributions of climate-induced changes in hazard, exposure, and vulnerability to observed trends. Across nine world regions, trends in damages are generally dominated by increasing exposure and decreasing vulnerability, with the latter being most pronounced in less developed regions. However, accounting for heterogeneity in changes of hazard frequency and magnitude within a region, a climate signal is detectable, especially in South and Sub-Saharan Africa as well as in Latin America. Damages in most regions are subject to a monotonous trend even after accounting for natural variability where an effect of long-term global warming can not yet be distinguished from a potential influence from multidecadal oscillations.
Melatonin Maintains Macrophage M1 Phenotype to Reverse LPS-stimulated Tumor Immune Tolerance
Authors: Lin Yukun , Zhang Mengdi , Zhou Lin , Wang Yuehua , Wang Mengqi , Du Jincheng , Kui Fuguang , Gu Wenwen , Lin Haihong , Li Hong , Cen Shihong , Du Gangjun 
Published: June 2020

Abstract
Background: Lipopolysaccharide (LPS) is a potent trigger of macrophage-mediated inflammation and its repeated stimulation results in immune tolerance. This study is to explore the cellular mechanisms of LPS-mediated tumor immune tolerance and to investigate whether melatonin can reverse this tolerance. Methods: The effect of melatonin and LPS on macrophages was assessed by cell proliferation, morphological changes, phagocytosis and autophagy in vitro. The tumor-preventing effect of melatonin and LPS were evaluated in the urethane-induced lung carcinoma model and in the H22 liver cancer allograft model. Immunofluorescence, immunohistochemistry and ELISA were used to examine protein expression. The related targets and pathways of melatonin were predicted by comprehensive bioinformatics, and the clinical association of bacterial infections and survival was evaluated in cancer patients by meta-analysis.Results: In vitro，Raw264.7 macrophages were polarized toward the M1 phenotype by single LPS administration but toward the M2 phenotype by repeated LPS administration. Interestingly, combination treatment with repeated LPS and 10 µM melatonin prevented macrophage polarization toward the M2-like phenotype and exerted lasting antitumor efficacy. In the urethane-induced lung carcinoma model, repeated LPS administration stimulated macrophage polarization toward the M2 phenotype and promoted lung carcinogenesis, which was abrogated by macrophage depletion, while melatonin alone or in combination with repeated LPS challenge restored M1-like macrophages and prevented carcinogenesis. In the H22 liver cancer allograft model, melatonin maintained the macrophage phenotype and promoted the tumor-suppressing effect of repeated LPS challenge. Furthermore, we found that macrophages repeatedly stimulated with LPS had a high level of surface lipid rafts that mediated PI3K/AKT and JAK2/STAT3 signaling and prevented both LPS sensitivity and immune response by self-expression of PD-L1 and surface expression of PD-1 receptor on NK cells, whereas melatonin decreased surface lipid rafts and PI3K/AKT and JAK2/STAT3 signaling. Finally, we conducted a comprehensive bioinformatics analysis of melatonin-relevant targets and pathways involved in M2 macrophage polarization and evaluated the clinical associations of bacterial infections and survival in cancer patients. Conclusions: This study suggests a function of melatonin in regulating macrophage polarization to maintain LPS-stimulated tumor immune surveillance.