bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genome Wide Epistasis Study of On-Statin Cardiovascular Events with Iterative Feature Reduction and Selection
Authors: Adams Solomon M. , Feroze Habiba , Nguyen Tara , Eum Seenae , Cornelio Cyrille K. , Harralson Arthur F. 
Published: April 2020

AbstractBackgroundPredicting risk for major adverse cardiovascular events (MACE) is an evidence-based practice that incorporates lifestyle, history, and other risk factors. Statins reduce risk for MACE by decreasing lipids, but it is difficult to stratify risk following initiation of a statin. Genetic risk determinants for on-statin MACE are low-effect size and impossible to generalize. Our objective was to determine high-level epistatic risk factors for on-statin MACE with GWAS-scale data.MethodsControlled-access data for 5,980 subjects taking a statin collected from Vanderbilt University Medical Center’s BioVU were obtained from dbGaP. We used Random Forest Iterative Feature Reduction and Selection (RF-IFRS) to select highly informative genetic and environmental features from a GWAS-scale dataset of patients taking statin medications. Variant-pairs were distilled into overlapping networks and assembled into individual decision trees to provide an interpretable set of variants and associated risk.Results1,718 cases who suffered MACE and 4,172 controls were obtained from dbGaP. Pathway analysis showed that variants in genes related to vasculogenesis (FDR=0.024), angiogenesis (FDR=0.019), and carotid artery disease (FDR=0.034) were related to risk for on-statin MACE. We identified six gene-variant networks that predicted odds of on-statin MACE. The most elevated risk was found in a small subset of patients carrying variants in COL4A2, TMEM178B, SZT2, and TBXAS1 (OR=4.53, p<0.001).ConclusionsThe RF-IFRS method is a viable method for interpreting complex “black-box” findings from machine-learning. In this study, it identified epistatic networks that could be applied to risk estimation for on-statin MACE. Further study will seek to replicate these findings in other populations.
Knowledge and Beliefs towards Universal Safety Precautions to flatten the curve during Novel Coronavirus Disease (nCOVID-19) Pandemic among general Public in India: Explorations from a National Perspective
Authors: Gudi Sai Krishna , Undela Krishna , Venkataraman Rajesh , Mateti Uday Venkat , Chhabra Manik , Nyamagoud Sanath , Tiwari Komal Krishna 
Published: April 2020

AbstractBackgroundThe novel Coronavirus disease (COVID-19) is being considered as the most serious health threat that the world has never witnessed in the recent times and significantly affecting the daily routine of mankind by emerging as a global pandemic. Yet, as there is no treatment nor a vaccine that was approved so far, universal safety precautions (USPs) and mitigating strategies are the only way to deal with this emergency crisis. However, knowledge and beliefs towards USPs among the general public in countries such as India with a large population are lacking.MethodsA prospective, cross-sectional, web-based online survey was conducted among the general public in India during March 2020. A 20-item self-administered survey questionnaire was developed and randomly distributed among the public using google document forms through social media networks. Descriptive statistics were used in representing the study characteristics, and the Chi-square test was used in assessing the associations among the study variables with a p-value of < 0.05 was considered as statistically significant.ResultsOf 1287 participants, 1117 have given their consent of willingness and completed the questionnaire with a response rate of 86.8%. The mean age of the study participants was 28.8 ± 10.9 years, where the majority of them belong to the age category <25 years, and sex was equally distributed. Based upon the socio-demographic information, the majority were post-graduates (32.9%), professional job holders (45%) and belonged to the upper-middle (40%) economic class. Overall, the knowledge and beliefs towards USPs and mitigating strategies among participants varied between moderate to high, with statistically significant associations with their socio-demographic characteristics.ConclusionsAlthough the knowledge and beliefs of the general public in India towards USPs are encouraging, there is a need for long-term educational interventions as the dynamics and severity of COVID-19 have been changing day-by-day rapidly. The findings of this study could guide the public health authorities in making and implementing decisions to combat this pandemic.
Risk of Secondary Malignancies in Patients with prostate cancer: A Systematic Review and Meta-analysis
Authors: Heydari Keyvan , Rismantab Sahar , Shamshirian Amir , Houshmand Pouya , Lotfi Parisa , Rafati Sajjad , Aref Amir , Saravi Ali , Shamshirian Danial , Zibaei Behdad , Alizadeh-Navaei Reza 
Published: April 2020

AbstractIMPORTANCEProstate cancer (PC) is the second most common cancer among males globally, however, the survival rate is favorable in most patients. In a small number of patients, who suffer from advanced or invasive cancer, various side effects such as secondary malignancies or treatment-related secondary malignancies (SMs) may be seen.OBJECTIVETo systematically asses the risk of secondary malignancies in patients with prostate cancer.DATA SOURCESWe have searched for longitudinal studies through databases of Web of Science, Scopus and PubMed for all available data up to September 2019.STUDY SELECTIONStudies with longitudinal design on prostate cancer patients that declared the results in SIR or those that the SIR could be calculated were eligible.DATA EXTRACTION AND SYNTHESISThe heterogeneity was evaluated using the I2 test. According to the results and in case of I2 ≥ 50%, the random effect model was used to combine the results. To identify the cause of heterogeneity in the studies, the analysis of sub-groups was performed based on the site of secondary malignancy, the treatment procedure, and duration of follow-up. Data were analyzed using STATA version 11.MAIN OUTCOMES AND MEASURESOverall SIR and based on treatment of prostate cancer and duration of follow-up.RESULTSTwenty-six studies involving more than 2223,704 patients with PC and more than 86034 cases of SMs were entered into this study. The meta-analysis showed that the risk of cancer after PC was 1.03 (95% CI 0.90 - 1.15) and the SIRs of some cancers such as the bladder 1.52 (1.06 - 1.99) and melanoma 1.32 (0.78 - 1.87) were higher than expected. While, malignancies such as rectum 0.92 (0.85 - 1.00), lung 0.85 (0.74 - 0.96) and liver 0.76 (0.54 - 0.98) showed lower incidence in compare to general population.CONCLUSIONS AND RELEVANCEThe overall risk of SMs in patients with prostate cancer is not significantly different from general population, and even in patients undergoing prostatectomy or brachytherapy, the risk is lower. But the incidence of some cancers such as melanoma, bladder, and urinary tract appears to be higher than the public in all types of treatment approaches.Key PointsQuestioIs the risk of secondary malignancy in patients with prostate cancer higher than the general population?FindingsThis systematic review and meta-analysis of 26 unique trials including 2223,704 patients, showed that the SIRs of some cancers such as the bladder and melanoma were higher than expected.MeaningThese findings suggest that the overall risk of some cancer such as bladder and melanoma in patients with prostate cancer were higher than the general population.
Parametric analysis of early data on COVID-19 expansion in selected European countries
Authors: Spousta Martin 
Published: April 2020

AbstractWe analyze the early data on COVID-19 expansion in selected European countries using an analytical parametric model. A description of the time dependence of the disease expansion and a method to evaluate trends of the expansion are proposed. Several features are observed in the data, namely a high predictability of the expansion of disease in Italy and a convergence of the “pushback” parameter towards a limiting value in all the countries where restrictive measures have been adopted. Basic predictions for the evolution of the disease expansion are made for selected countries with a stable evolution in the parametric space of the model. The findings presented here should contribute to the understanding of the behavior of the disease expansion and the role of the restrictive measures on the evolution of the expansion.
Mercury methylation trait dispersed across diverse anaerobic microbial guilds in a eutrophic sulfate-enriched lake
Authors: Peterson Benjamin D. , McDaniel Elizabeth A. , Schmidt Anna G. , Lepak Ryan F. , Tran Patricia Q. , Marick Robert A. , Ogorek Jacob M. , DeWild John F. , Krabbenhoft David P. , McMahon Katherine D. 
Published: April 2020

AbstractMercury (Hg) methylation is a microbially mediated process that converts inorganic Hg into the bioaccumulative neurotoxin methylmercury (MeHg). Exploring the diversity and metabolic potential of the dominant Hg-methylating microorganisms can provide insights into how biogeochemical cycles and water quality parameters underlie MeHg production. However, our understanding of the ecophysiology of methylators in natural ecosystems is still limited. Here, we used shotgun metagenomics paired with biogeochemical data to identify likely hotspots for MeHg production in a lake with elevated sulfate levels and characterize the microbial methylators and the flanking microbial community. Identified putative methylators were dominated by hgcA sequences divergent from those in canonical, experimentally confirmed methylators. Using genome-resolved metagenomics, these sequences were identified within genomes associated with Bacteroidetes and the recently described phylum Kiritimatiellaeota. Over half of the hgcA abundance comes from genomes corresponding to obligately fermentative organisms, many of which have a large number of glucoside hydrolases for polysaccharide degradation. Sulfate-reducing genomes encoding hgcA were also identified, but only accounted for 22% of the abundance of hgcA+ genomes. This work highlights the diverse dispersal of the methylation trait across the microbial anoxic food web.
Epigenomic Diversity of Cortical Projection Neurons in the Mouse Brain
Authors: Zhang Zhuzhu , Zhou Jingtian , Tan Pengcheng , Pang Yan , Rivkin Angeline , Kirchgessner Megan A. , Williams Elora , Lee Cheng-Ta , Liu Hanqing , Franklin Alexis D. , Miyazaki Paula Assakura , Bartlett Anna , Aldridge Andrew , Vu Minh , Boggeman Lara , Fitzpatrick Conor , Nery Joseph R. , Castanon Rosa G. , Rashid Mohammad , Jacobs Matthew , Ito Tony , Dominguez Bertha , Niu Sheng-Yong , Smith Jared B. , O’Connor Carolyn , Lee Kuo-Fen , Jin Xin , Mukamel Eran A. , Behrens M. Margarita , Ecker Joseph R. , Callaway Edward M. 
Published: April 2020

SummaryNeuronal cell types are classically defined by their molecular properties, anatomy, and functions. While recent advances in single-cell genomics have led to high-resolution molecular characterization of cell type diversity in the brain, neuronal cell types are often studied out of the context of their anatomical properties. To better understand the relationship between molecular and anatomical features defining cortical neurons, we combined retrograde labeling with single-nucleus DNA methylation sequencing to link epigenomic properties of cell types to neuronal projections. We examined 11,827 single neocortical neurons from 63 cortico-cortical (CC) and cortico-subcortical long-distance projections. Our results revealed unique epigenetic signatures of projection neurons that correspond to their laminar and regional location and projection patterns. Based on their epigenomes, intra-telencephalic (IT) cells projecting to different cortical targets could be further distinguished, and some layer 5 neurons projecting to extra-telencephalic targets (L5-ET) formed separate subclusters that aligned with their axonal projections. Such separation varied between cortical areas, suggesting area-specific differences in L5-ET subtypes, which were further validated by anatomical studies. Interestingly, a population of CC projection neurons clustered with L5-ET rather than IT neurons, suggesting a population of L5-ET cortical neurons projecting to both targets (L5-ET+CC). We verified the existence of these neurons by labeling the axon terminals of CC projection neurons and observed clear labeling in ET targets including thalamus, superior colliculus, and pons. These findings highlight the power of single-cell epigenomic approaches to connect the molecular properties of neurons with their anatomical and projection properties.
Translational neurophysiological biomarkers of N-methyl-D-aspartate receptor dysfunction in serine racemase knockout mice
Authors: Balla Andrea , Ginsberg Stephen , Abbas Atheir I. , Sershen Henry , Javitt Daniel C. 
Published: April 2020

AbstractAlterations in glutamatergic function are well established in schizophrenia (Sz), but new treatment development is hampered by the lack of translational pathophysiological and target engagement biomarkers as well as by the lack of animal models that recapitulate the pathophysiological features of Sz. Here, we evaluated the rodent auditory steady state response (ASSR) and long-latency auditory event-related potential (aERP) as potential translational markers. These biomarkers were assessed for their sensitivity to both the N-methyl-D-aspartate receptor (NMDAR) antagonist phencyclidine (PCP) and to knock-out (KO) of Serine Racemase (SR), which is known to lead to Sz-like alterations in function of parvalbumin (PV)-type cortical interneurons. Both PCP and SRKO led to significant increases of ASSR, consistent with PV interneuron effects. Similar effects were observed in mice with selective NMDAR KO on PV interneurons. By contrast, PCP but not SRKO reduced the amplitude of the rodent analog of the human N1 potential. Overall, these findings support use of rodent ASSR and long-latency aERP, along with previously described measures such as mismatch negativity (MMN), as translational biomarkers, and support SRKO mice as a potential rodent model for PV interneuron dysfunction in Sz.
Precise electronic control of redox reactions insideEscherichia coliusing a genetic module
Authors: Baruch Moshe , Tejedor-Sanz Sara , Su Lin , Ajo-Franklin Caroline M. 
Published: April 2020

AbstractMicroorganisms regulate the redox state of different biomolecules to precisely control biological processes. These processes can be modulated by electrochemically coupling intracellular biomolecules to an external electrode, but current approaches afford only limited control and specificity. Here we describe specific electrochemical control of the reduction of intracellular biomolecules inEscherichia colithrough introduction of a heterologous electron transfer pathway.E. coliexpressingmtrCABfromShewanella oneidensisMR-1 consumed electrons directly from a cathode when fumarate or nitrate, both intracellular electron acceptors, were present. The fumarate-triggered current consumption occurred only when fumarate reductase was present, indicating all the electrons passed through this enzyme. Moreover, MtrCAB-expressingE. coliused current to stoichiometrically produce ammonia. Thus, our work introduces a modular genetic tool to reduce a specific intracellular redox molecule with an electrode, opening the possibility of electronically controlling biological processes such as biosynthesis and growth in any microorganism.
Integrative Network Fusion: a multi-omics approach in molecular profiling
Authors: Chierici Marco , Bussola Nicole , Marcolini Alessia , Francescatto Margherita , Zandonà Alessandro , Trastulla Lucia , Agostinelli Claudio , Jurman Giuseppe , Furlanello Cesare 
Published: April 2020

ABSTRACTRecent technological advances and international efforts, such as The Cancer Genome Atlas (TCGA), have made available several pan-cancer datasets encompassing multiple omics layers with detailed clinical information in large collection of samples. The need has thus arisen for the development of computational methods aimed at improving cancer subtyping and biomarker identification from multi-modal data. Here we apply the Integrative Network Fusion (INF) pipeline, which combines multiple omics layers exploiting Similarity Network Fusion (SNF) within a machine learning predictive framework. INF includes a feature ranking scheme (rSNF) on SNF-integrated features, used by a classifier over juxtaposed multi-omics features (juXT). In particular, we show instances of INF implementing Random Forest (RF) and linear Support Vector Machine (LSVM) as the classifier, and two baseline RF and LSVM models are also trained on juXT. A compact RF model, called rSNFi, trained on the intersection of top-ranked biomarkers from the two approaches juXT and rSNF is finally derived. All the classifiers are run in a 10×5-fold cross-validation schema to warrant reproducibility, following the guidelines for an unbiased Data Analysis Plan by the US FDA-led initiatives MAQC/SEQC. INF is demonstrated on four classification tasks on three multi-modal TCGA oncogenomics datasets. Gene expression, protein abundances and copy number variants are used to predict estrogen receptor status (BRCA-ER, N=381) and breast invasive carcinoma subtypes (BRCA-subtypes, N=305), while gene expression, miRNA expression and methylation data is used as predictor layers for acute myeloid leukemia and renal clear cell carcinoma survival (AML-OS, N=157; KIRC-OS, N=181). In test, INF achieved similar Matthews Correlation Coefficient (MCC) values and 97% to 83% smaller feature sizes (FS), compared with juXT for BRCA-ER (MCC: 0.83 vs 0.80; FS: 56 vs 1801) and BRCA-subtypes (0.84 vs 0.80; 302 vs 1801), improving KIRC-OS performance (0.38 vs 0.31; 111 vs 2319). INF predictions are generally more accurate in test than one-dimensional omics models, with smaller signatures too, where transcriptomics consistently play the leading role. Overall, the INF framework effectively integrates multiple data levels in oncogenomics classification tasks, improving over the performance of single layers alone and naive juxtaposition, and provides compact signature sizes1.
Morphological estimation of Cellularity on Neo-adjuvant treated breast cancer histological images
Authors: Ortega-Ruiz Mauricio Alberto , Karabağ Cefa , García Garduño Victor , Reyes-Aldasoro Constantino Carlos 
Published: April 2020

AbstractThis paper describes a methodology that extracts morphological features from histological breast cancer images stained for Hematoxilyn and Eosin (H&E). Cellularity was estimated and the correlation between features and the residual tumour size cellularity after a Neo-Adjuvant treatment (NAT) was examined. Images from whole slide imaging (WSI) were processed automatically with traditional computer vision methods to extract twenty two morphological parameters from the nuclei, epithelial region and the global image. The methodology was applied to a set of images from breast cancer under NAT. The data came from the BreastPathQ Cancer Cellularity Challenge 2019, and consisted of 2579 patches of 255×255 pixels of H&E histopatological samples from NAT treatment patients. The methodology automatically implements colour separation, segmentation and morphological analysis using traditional algorithms (K-means grouping, watershed segmentation, Otsu’s binarisation). Linear regression methods were applied to determine strongest correlation between the parameters and the cancer cellularity. The morphological parameters showed correlation with the residual tumour cancer cellularity. The strongest correlations corresponded to the stroma concentration value (r = −0.9786) and value from HSV image colour space (r = −0.9728), both from a global image parameters.
A versatile high throughput strategy for cloning the env gene of HIV-1
Authors: Mishra Nitesh , Dobhal Ayushman , Sharma Shaifali , Luthra Kalpana 
Published: April 2020

AbstractThe trimeric envelope glycoprotein (gp120/gp41)3of human immunodeficiency virus-1 (HIV-1) mediates viral and host cell membrane fusion, initiated by binding of viral envelope gp120 protein to the CD4 receptor on host immune cells. Functional env genes from infected individuals have been widely used as templates for vaccine design, for setting up viral neutralization assays and to study the viral evolution and pathogenesis. Traditional topoisomerase or T4 DNA polymerase mediated approaches for cloning single genome amplified (SGA) env genes are labor-intensive, cost-ineffective with low-throughput, thereby enabling functional analysis of only a limited number of env genes from the diverse circulating quasispecies in infected individuals. Herein, we report an efficient, easy to optimize and high-throughput approach for cloning diverse HIV-1 env genes. Multiple env/rev gene cassettes, derived from infected infants, were subjected to SGA using Phusion polymerase and utilized as megaprimers in overlap extension PCR mediated cloning (OEC), circumventing the requirement for novel enzymes. Furthermore, utilization of Phusion polymerase for both the amplification of env/rev cassettes and OEC allows convenient monitoring and optimization, thereby providing much greater flexibility and versatility for analysis of env genes from HIV-1 infected individuals.
Accumulation of mutations in genes associated with sexual reproduction contributed to the domestication of a vegetatively propagated staple crop, enset
Authors: Tesfamicael Kiflu Gebramicael , Gebre Endale , March Timothy J , Sznajder Beata , Mather Diane E. , Marcelino Rodriguez Lopez Carlos 
Published: April 2020

AbstractEnset (Ensete ventricosum(Welw.) Cheesman) is a drought tolerant, vegetatively propagated crop that was domesticated in Ethiopia. It is a staple food for more than 20 million people in Ethiopia. Despite its current importance and immense potential, enset is among the most genetically understudied and underexploited food crops. We collected 230 enset wild and cultivated accessions across the main enset producing regions in Ethiopia and applied amplified fragment length polymorphism and genotype by sequencing (GBS) methods to these accessions. Wild and cultivated accessions were clearly separated from each other, with 89 genes found to harbour SNPs that separated wild from cultivated accessions. Among these, 17 genes are thought to be involved in flower initiation and seed development. Among cultivated accessions, differentiation was mostly associated with geographical location and with proximity to wild populations. Our results indicate that vegetative propagation of elite clones has favoured capacity for vegetative growth at the expense of capacity for sexual reproduction. This is consistent with previous reports that cultivated enset tends to produce non-viable seeds and flowers less frequent than wild enset.