bluuebunny/crossref_metadata_2025_split huggingface dataset:
Diversity and Gradient Analysis of Common Yew (Taxus Baccata L.) Communities in Eastern Hyrcanian Forests, Northern Iran
Authors: Esmailzadeh Omid , Soofi Meysam , Karami Pari 
Published: August 2020

Abstract
Aims: To outline syntaxonomical synthesis of yew (Taxus baccata L.) in the eastern of Hyrcanian forest and to identify their main environmental gradients. Location: Jahan-Nama protected area (JNPA) as a unique yew population with heterogeneous floristically composition in the east of Hyrcanian forests, Northern Iran. Methods: Vegetation units were classified using modified TWINSPAN and were translated into syntaxonomic system. Syntaxa were determined by re-arrangement of each relevé based on diagnostic species occurrences and expert knowledge with the aim to increase the floristic distinctiveness of vegetation units. Syntaxa were finally evaluated by diagnostic species and environmental parameters according to phi- values and ANOVA, respectively. DCA was used to visualize the dissimilarity of syntaxa and their relationships with the environmental factors. We also used species combination concept for determining diagnostic species in the second association. Results: The classification of JNPA yew forests resulted in 6 Vegetation unites. These patterns were translated into four associations, two sub-associations and two variants. (Asso.1) Fago orientalis-Taxetum baccatae is found in northern aspects with lower slopes and higher soil depth; (Asso.2) Aceri velutini-Taxetum baccatae is occurring in the moderate but rocky slopes. Asso.1 and Asso.2 are the same in altitude and involving Carpinus betulus as a co-dominant. (Asso.3) Carpino betuli-Carpino orientale-Taxetum baccatae developed in the intermediate slopes. (Asso.4) Carpino orientale -Taxetum baccatae appeared in the highest slope of northeast and northwest aspects with shallow soil depth. The main factors determining the species composition of the JNPA syntaxa are slope, eastness, elevation and clay content. Conclusions: Our study provides the first syntaxonomic of yew communities in east of Hyrcanian forests and it also used the concept of species combination for exploring diagnostic species for proposing Carpino betuli- Carpino orientale- Taxetum baccatae association. We also showed that yew could be associated with different plant species which are distributing in different site suitability. It caused to have various yew syntaxa in JNPA and considerably reiterate high floristically and ecologically capacity of this area.
Diagnostic value of bronchoalveolar lavage-fluid soluble triggering receptor expressed on myeloid cells-1 (sTREM-1) concentration for neonatal ventilator-associated pneumonia
Authors: Zhou Jian , Zhou Jingqian , Hong Yan , Wang Youcheng , Lin Hailong , Huang Leting 
Published: August 2020

Abstract
Background: Soluble triggering receptor expressed on myeloid cells-1 (sTREM-1) has regarded as a biological marker of infection. We aimed to evaluate the diagnostic value of bronchoalveolar lavage (BAL)-sTREM-1 concentration in neonatal ventilator-associated pneumonia (NVAP). Methods: In this multicenter, controlled clinical trial of 60 preterm and 33 full-term neonates on mechanical ventilators, we measured concentrations of BAL-fluid and serum sTREM-1, serum C-reactive protein, and serum procalcitonin, as well as white blood cell count. We initially divided cases into eight groups, based on three categories: preterm of full-term; NVAP or non-NVAP; and extrapulmonary infection present or absent. Groups were compared, and logistic regression analysis and receiver operating characteristic (ROC) analysis was performed to determine diagnostic value. Results: The mean gestational age (± standard deviation) of preterm and full-term neonates was 28.9±2.2 weeks and 39.5±1.7 weeks, respectively, and 32/60 were male. The BAL-fluid sTREM-1 concentration was higher in NVAP cases than in non-NVAP cases, irrespective of extrapulmonary infection. ROC analysis revealed that BAL-fluid sTREM-1 concentration had an area under the curve (AUC) of 0.986 and a cutoff value of 228.0 pg/ml (sensitivity, 94.3%; specificity, 96%) in preterm neonates; the same values in full-term neonates were 0.938 and 245.5 pg/ml (sensitivity, 100%; specificity, 93.7%), respectively. The optimal combination of indicators was BAL-fluid sTREM-1 and serum C-reactive protein concentration. All indicators were present at lower levels on days 8 and 10 of ventilation in neonates who ultimately recovered than in those who did not. Conclusion: BAL-fluid sTREM-1 and serum C-reactive protein concentrations may be useful for the diagnosis of NVAP.
Bisindolylmaleimide IX: A novel anti-SARS-CoV2 agent targeting viral main protease 3CLpro demonstrated by virtual screening and in vitro assays
Authors: Gupta Yash , Maciorowski Dawid , Zak Samantha E. , Jones Krysten A. , Kathayat Rahul S. , Azizi Saara-Anne , Mathur Raman , Pearce Catherine M. , Ilc David J. , Husein Hamza , Herbert Andrew S. , Bharti Ajay , Rathi Brijesh , Durvasula Ravi , Becker Daniel P. , Dickinson Bryan C. , Dye John M. , Kempaiah Prakasha 
Published: August 2020

Abstract
The emergence of SARS/MERS drug-resistant COVID-19 with high transmission and mortality has recently been declared a pandemic. Like all coronaviruses, SARS-CoV-2 is a relatively large virus consisting of several enzymes with essential functions within its proteome. Here, we focused on repurposing approved and investigational drugs by identifying potential drugs that are predicted to effectively inhibit critical enzymes. We targeted seven proteins with enzymatic activities known to be essential at different stages of the virus life cycle; PLpro, 3CLpro, RdRP, Helicase, ExoN, NendoU, and 2’-O-MT. For virtual screening, the energy minimization of a crystal structure of the modeled protein was carried out using the Protein Preparation Wizard1. Following active site selection based on data mining and COACH predictions, we performed a high-throughput virtual screen of drugs (n=5903) that are approved by worldwide regulatory bodies. The screening was performed against viral targets using three sequential docking modes (i.e. HTVS, SP, and XP). Our in-silico virtual screening identified ~290 potential drugs based on the criteria of energy, docking parameters, ligand, and binding site strain and score. Drugs specific to each target protein were further analyzed for binding free energy perturbation by molecular mechanics (prime MM-GBSA) and pruning the hits to the top 32 candidates. Top lead from each target pool was further subjected to molecular dynamics simulation using the Desmond module. Herein we report the evaluation of in-vitro efficacy of selected hit drug molecules on SARS-CoV-2 virus inhibition. Among eight molecules included in our evaluation, we found the micromolar inhibitor of protein kinase C isoforms, Bisindolylmaleimide IX (BIM IX), as the most potent inhibitor of SARS-CoV-2 in-vitro. Further, in-silico predicted target validation through enzymatic assays confirmed its interaction with 3CLpro to be the target. Therefore, our data support advancing BIM IX for clinical evaluation as a potential treatment for COVID-19. This is the first study that has showcased the possibility of using bisindolylmaleimide IX to treat COVID-19 through this pipeline.
Shift in the Spatio-Temporal Natural Fruiting of Boletes in West African Woodlands: the Key Role of the Soil Moisture
Authors: Badou Akotchayé Sylvestre , Houdanon Roel D. , Tchan Kassim I. , Hègbè D.M.T. Apollon , Yorou Nourou Soulemane 
Published: August 2020

Abstract
Background: The ectomycorrhizal fungi display strong fluctuations during the mycological season. However, how abiotic parameters affect the fruiting sequences of ectomycorrhizal fungi and also the direction and extent of this effect are not yet tapped adequately. The present study seeks to assess the microclimate effect on the natural production of boletes. Nine permanent plots of 2500 m2 (50m x 50m) split into 25 subplots of 100 m2 (10m x 10m) were installed in three different vegetation dominated respectively by Isoberlinia doka, Isoberlinia tomentosa and Uapaca togoensis. Microclimatic parameters were recorded each 30 minutes throughout by mean of a Micro Station Data Logger - H21-002 the mycological seasons. Each plot was surveyed twice a week (from May to October) over three years (2015, 2016 and 2017) to record the presence/absence of fruit bodies and fresh biomass of boletes. To evaluate the effect of time and microclimate variables on natural production, we used mixed effects and generalized linear models using R version 3.5.3. Results: In total, during the three years (2015, 2016 and 2017), we recorded 14 species of boletes. Species richness does not change over time (P > 0.05). In addition, fresh biomass varies within years and vegetation (P < 0.05). The combination of year and month of collection has a significant effect on the number of fruit bodies (P < 0.05). Only the soil moisture has a significant positive influence on the species richness of boletes (P > 0.05). Conclusions: When the soil moisture decreases by four units, the number of fruit bodies of ectomycorrhizal fungi is significantly reduced by one unit. Therefore, above 0.25 m3 / m3 and below 0.05 m3 / m3 there is a decrease in the number of fruit bodies.
Increasing Risk of Wild Swings between Droughts and Floods over Global Land Areas
Authors: Cheng Linyin , Liu Zhiyong , Chen Xiaohong , Lin Kairong 
Published: August 2020

Abstract
Climate variability is nothing new. Of rising concern is the consecutive occurrence of reversed weather patterns — droughts followed by severe floods, which tip a precarious balance with lasting impacts on human and natural systems. Here we examined changes in the likelihood and spatial distribution of dry-to-wet precipitation events over global land surface using climate model projections. We find anthropogenic climate change is likely to stress more widespread regions with rapid see-saw changes from dry to wet spells by the end of the 21st Century, increasing the threat to water security. Additionally, Eastern North America, South and East Asia, and Eastern Africa are emerging future hotspots of extreme drought-deluge swings by yielding marked enhancements in the events’ occurrence probability and spatial coverage. This study can provide useful information for policy makers to develop integrated approach to drought and flood management, while broadening the scope of research on compound climate extremes.
Early Diagnostic Value of Spectral Domain-optical Coherence Tomography for Optic Nerve Injury in Sellar-occupied Patients
Authors: Zhang Li , Yang Xiaowei , Zhang Wei , Han Muyuan , Zhao Wenshuai , Li Xiaohao 
Published: August 2020

Abstract
Background: To investigate the value of spectral domain-optical coherence tomography (SD-OCT) in the early diagnosis of optic nerve injury in patients with occupying lesion in sellar region. Methods: A case-control study was conducted for patients who were diagnosed as the occupying lesion in sellar region in the Department of Ophthalmology. The general routine examination and visual field examination were performed in the ophthalmology department. A total of 22 patients(44 eyes) with no abnormalities were selected, and 22 healthy controls (44 eyes) were enrolled. SD-OCT was used to detect the average thickness of peripapillary retinal nerve fiber layer (pRNFL) and the thickness of four quadrants and the thickness of each layer of macular ganglion cell complex (mGCC). The results were compared to evaluate the damage of the optic nerve. The area under the receiver operating characteristic (ROC) curve (AUC) was evaluated by SD-OCT to detect the diagnostic efficacy of pRNFL and mGCC for sellar-occupying optic nerve damage. Results: The average thickness of pRNFL was significantly different from that of healthy controls (P<0.01). The mean thickness of mGCC, macular retinal nerve fiber layer (mRNFL) and GCL+ were significantly different from those of healthy controls (P<0.05). The AUC values ​​of pRNFL, mRNFL, ganglion cell layer (GCL) + and mGCC were 0.757, 0.643, 0.702 and 0.688, respectively. The diagnostic value was pRNFL> GCL+ > mGCC > mRNFL. Conclusion: The thickness of pRNFL and mGCC detected by SD-OCT has clinical value in the diagnosis of optic nerve injury in early patients with occupying lesion in sellar region. The change of pRNFL thickness is more effective than mGCC thickness in the early sellar-occupying optic nerve injury.
Weyl-triplons in SrCu2(BO3)2
Authors: Sengupta Pinaki , BHOWMICK DHIMAN 
Published: August 2020

Abstract
Presence of Weyl node, nodal line or nodal surface in the band structure is a signature of topological gapless phase in a three-dimensional(3D) material. Here, we propose that Weyl triplons are expected to appear in the low energy magnetic excitations in the canonical Shastry-Sutherland compound, \ce{SrCu2(BO3)2}, a quasi-2D quantum magnet. Our results show that whena minimal, realistic inter-layer coupling is added to the well-established microscopicmodel describing the excitation spectrum of the individual layers,the Dirac points that appears in the zero-field triplon spectrum of the 2D modelsplits into two pairs of Weyl points along the Kz direction. Varying the strength of the inter-layer Dzyaloshinskii–Moriya(DM) interaction and applying asmall longitudinal magnetic field results in a range of band topologytransitions accompanied by changing numbers of Weyl points. We propose inelastic neutron scattering along with thermal Hall effect as the experimental techniques to detect the presence of Weyl-node in the triplon spectrum of this material.
The Landscape of Gene Co-Expression Modules Correlating with Prognostic Genetic Abnormalities in AML
Authors: Guo Chao , Gao Ya-yue , Ju Qian-qian , Zhang Chun-xia , Gong Ming , Li Zhen-ling 
Published: August 2020

Abstract
Background: The heterogenous cytogenetic and molecular variations were harbored by AML patients, some of which are related with AML pathogenesis and clinical outcomes. We aimed to uncover the intrinsic expression profiles correlating with prognostic genetic abnormalities by WGCNA.Methods: We downloaded the clinical and expression dataset from BeatAML, TCGA and GEO database. Using R (version 4.0.2) and ‘WGCNA’ package, the co-expression modules correlating with the ELN2017 prognostic markers were identified (R2 ≥ 0.4, p < 0.01). ORA detected the enriched pathways for the key co-expression modules. The patients in TCGA cohort were randomly assigned into the training set (50%) and testing set (50%). The LASSO penalized regression analysis was employed to build the prediction model, fitting OS to the expression level of hub genes by ‘glmnet’ package. Then the testing and 2 independent validation sets (GSE12417 and GSE37642) were used to validate the diagnostic utility and accuracy of the model. Results: A total of 37 gene co-expression modules and 973 hub genes were identified for the BeatAML cohort. We found that 3 modules were significantly correlated with genetic markers (the ‘lightyellow’ module for NPM1 mutation, the ‘saddlebrown’ module for RUNX1 mutation, the ‘lightgreen’ module for TP53 mutation). ORA revealed that the ‘lightyellow’ module was mainly enriched in DNA-binding transcription factor activity and activation of HOX genes. The ‘saddlebrown’ module was enriched in immune response process. And the ‘lightgreen’ module was predominantly enriched in mitosis cell cycle process. The LASSO- regression analysis identified 6 genes (NFKB2, NEK9, HOXA7, APRC5L, FAM30A and LOC105371592) with non-zero coefficients. The risk score generated from the 6-gene model, was associated with ELN2017 risk stratification, relapsed disease, and prior MDS history. The 5-year AUC for the model was 0.822 and 0.824 in the training and testing sets, respectively. Moreover, the diagnostic utility of the model was robust when it was employed in 2 validation sets (5-year AUC 0.743-0.79).Conclusions: We established the co-expression network signature correlated with the ELN2017 recommended prognostic genetic abnormalities in AML. The 6-gene prediction model for AML survival was developed and validated by multiple datasets.
Machine learning prediction on number of patient due to conjunctivitis based on air pollutants: A preliminary study
Authors: Chen Juan , Cheng Yong-ran , Feng Zhan-hui , Zhou Meng-Yun , Wang Nan , Ye Lan , Wang Mingwei , Yao Jin 
Published: August 2020

Abstract
Background: Accurate prediction of the number of patients with conjunctivitis plays an important role in providing adequate treatment at the hospital, but such accurate predictive model currently does not exist. The current study sought to use machine learning (ML) prediction based on past patient for conjunctivitis and several air pollutants. The optimal machine learning prediction model was selected to predict conjunctivitis-related number patients.Methods: The average daily air pollutants concentrations (CO, O3, NO2, SO2, PM10, PM2.5) and weather data (highest and lowest temperature) were collected. Data were randomly divided into training dataset and test dataset, and normalized mean square error (NMSE) was calculated by 10 fold cross validation, comparing between the ability of seven ML methods to predict the number of patient due to conjunctivitis (Lasso penalized liner model, Decision tree, Boosting regression, Bagging regression, Random forest, Support vector, and Neural network). According to the accuracy of impact prediction, the important air and weather factors that affect conjunctivitis were identified.Results: A total of 84977 cases to treat conjunctivitis were obtained from the ophthalmology center of the Affiliated Hospital of Hangzhou Normal University. For all patients together, the NMSE of the different methods were as follows: Lasso penalized liner regression: 0.755, Decision tree: 0.710, Boosting regression: 0.616, Bagging regression: 0.615, Random forest: 0.392, Support vectors: 0.688, and Neural network: 0.476. Further analyses, stratified by gender and age at diagnosis, supported Random forest as being superior to others ML methods. The main factors affecting conjunctivitis were: O3, NO2, SO2 and air temperature.Conclusion: Machine learning algorithm can predict number of patients due to conjunctivitis, among which, the Random forest algorithm had the highest accuracy. Machine learning algorithm could provide accurate information for hospitals dealing with conjunctivitis caused by air factors.
Molecular characteristics of carbapenem-resistant Enterobacteriaceae isolated from clinical infection and fecal survey samples in Southern China
Authors: Duan Xiaonv , Qin Yingcheng , Peng Yuan , Rui YongYu 
Published: August 2020

Abstract
Background: The identified rate of carbapenem-resistant Enterobacteriaceae (CRE) have been increasingly in the clinical infections. Here, a study of analysing the relationship of clinical infectious CRE and fecal carried CRE was performed.Methods: Clinical CRE and fecal CRE were collected from hosiptal in China. Polymerase chain reaction (PCR)-based amplification and sequencing were performed to analyse the carriage of drug-resistant genes and mobile genetic elements (MGEs), Enterobacterial Repetitive Intergenic Consensus (ERIC) technology and whole genome sequencing (WGS) were used to analysis the characteristic of genetic structure of CRE isolates.Results: 99 clinical CRE and 30 fecal CRE were collected, respectively. The top three strains present in the highest proportions were K. pneumoniae (86; 66.67%), E. cloacae (22; 17.05%), and E. coli (11; 8.53%). Most of the isolates were susceptible to colistin (98.45%) and tigecycline (98.45%). blaKPC−2 (96.03%) was the dominant carbapenemase gene in clinical CRE and fecal CRE, followed by blaNDM (52.7%); co-existence of the blaKPC−2 and blaNDM genes was detected in 63 (50.00%) strains. One K. pneumoniae isolate co-producing NDM-5 and mcr-1, and one E. coli isolate co-producing KPC-2, IMP-4, and mcr-1 were detected. Two novel gene cassettes of intI2 were dectected. ERIC genotyping and genomic analysis revealed that K. pneumoniae isolated from clinical infections and fecal survey samples were same clone.Conclusions: This is the first report of comparing the molecular characteristics of CRE isolated from clinical infection and fecal survey samples. we found that fecal carried CRE were closely related to CRE which caused infections.
Associations of co-exposure to metals with serum uric acid and hyperuricemia: A cross-sectional study
Authors: Jiang Shunli , Zhou Shuang , Liu Huimin , Peng Cheng , Zhang Xu , Zhou Hao , Wang Zhihong , Lu Qing 
Published: August 2020

Abstract
While lead exposure is associated with hyperuricemia, there is scarce evidence about whether other metals are associated with serum uric acid (SUA) levels and hyperuricemia, and whether joint effects among metals existed. We conducted a cross-sectional study in 1950 eligible participants with 20 metals measured in urine. We used multivariable linear and logistic regression models to investigate the associations of metals exposure with SUA levels and hyperuricemia risk. We found that urinary vanadium and arsenic concentrations were associated with increased SUA levels in both sexes while urinary selenium concentrations were inversely associated with SUA levels in males. Each doubling of vanadium, arsenic, and selenium concentrations was associated with an adjusted odds ratio of 1.17 (95% CI: 1.03, 1.33), 1.22 (95% CI: 0.99, 1.50), and 0.67 (95% CI: 0.50, 0.88) for hyperuricemia in males, respectively. In addition, under the exposure of vanadium and arsenic, only if high selenium content existed, no significantly increased SUA levels and hyperuricemia risk in both sexes can be found. Vanadium and arsenic exposure were suggested to be associated with elevated SUA levels and hyperuricemia risk with sex difference while high selenium status might counteract their detrimental effects.
Predictors of Modern Contraceptive Use Among Married Women in Angola: A Population Based Study
Authors: Zegeye Betregiorgis Hailu , Garedew Gashaw Woldeamanuel , Negash Wassie , Asegidew Balkew Tegegn 
Published: August 2020

Abstract
Background: Maternal mortality is unacceptability high in Sub-Saharan-African countries including Angola. Despite family planning is one of the vital intervention to reduce maternal death, the coverage of modern contraceptive use in Angola is extremely low and there is a paucity of evidence regarding current factors associated with contraceptive use in Angola. Therefore, this study aimed at investigating predictors of contraceptive use among married women in Angola using nationally representative data.Methods: The data were extracted from 2015/16 Angola Multiple Indicator and Health Survey for this study and approximately 8,033 married women aged 15 - 49 years were participated. Bivariate and multivariate logistic regression were performed using STATA version 14 software to identify the predictors, and p-value less than 0.05 was considered as statistically significant.Results: The coverage of modern contraceptive use among married women was 8.9%. Maternal age, women’s educational level, maternal occupation, place of residence, media exposure, number of living children, desire for more children and subnational region were main predictors for modern contraceptive use.Conclusion: Modern contraceptive use among married women in Angola was very low. Married women who were educated, wealthiest, exposed for media, who had living children, interested to have child after 2 years and those who were not interested to have at all were more likely to use contraceptive. Therefore, the government of Angola and other concerned bodies need to emphasize in empowering women through education and economy as well as dissemination of contraceptive related information through media especially for women’s living in rural settings.