bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gene networks and expression quantitative trait loci associated with platinum-based chemotherapy response in high-grade serous ovarian cancer
Authors: Choi Jihoon , Tarnouskaya Anastasiya , Nesdoly Sean , Topouza Danai G. , Koti Madhuri , Duan Qing Ling 
Published: August 2019

AbstractBackgroundA major impediment in the treatment of ovarian cancer is the relapse of platinum-resistant tumors, which occurs in approximately 25% of patients. A better understanding of the biological mechanisms underlying platinum-based response will improve treatment efficacy through genetic testing and novel therapies.MethodsUsing data from high-grade serous ovarian carcinoma (HGSOC) patients in the Cancer Genome Atlas (TCGA), we classified those who remained progression-free for 12 months following platinum-based chemotherapy as “chemo-sensitive” (N=160) and those who had recurrence within six months as “chemo-resistant” (N=110). Univariate and multivariate analysis of expression microarrays identified differentially expressed genes and co-expression gene networks associated with chemotherapy response. Moreover, we integrated genomics data to determine expression quantitative trait loci (eQTL).ResultsDifferential expression of the Valosin-containing protein (VCP) gene and five co-expression gene networks were associated with chemotherapy response in HGSOC. VCP and the gene networks contribute to protein processing in the endoplasmic reticulum, which has been implicated in chemotherapy response. These findings were successfully replicated using independent replication cohort. Furthermore, 192 QTLs were associated with these gene networks and BRCA2 expression.ConclusionThis study implicates both known and novel genes as well as biological networks underlying response to platinum-based chemotherapy among HGSOC patients.
Trading Genome Vulnerability for Stable Genetic Inheritance: Active Retrotransposons Help Maintain Pericentromeric Heterochromatin Required for Faithful Cell Division
Authors: Hao Yajing , Wang Dongpeng , Wu Shuheng , Li Xiao , Shao Changwei , Zhang Peng , Chen Jia-Yu , Lim Do-Hwan , Fu Xiang-Dong , He Shunmin , Chen Runsheng 
Published: August 2019

ABSTRACTRetrotransposons are extensively populated in vertebrate genomes, which, when active, are thought to cause genome instability with potential benefit to genome evolution. Retrotransposon-derived RNAs are also known to give rise to small endo-siRNAs to help maintain heterochromatin at their sites of transcription; however, as not all heterochromatic regions are equally active in transcription, it remains unclear how heterochromatin is maintained across the genome. Here, we attack these problems by defining the origins of repeat-derived RNAs and their specific chromatin registers inDrosophilaS2 cells. We demonstrate that repeat RNAs are predominantly derived from active Gypsy elements, and upon their processing by Dicer-2, these endo-siRNAs act incisandtransto help maintain pericentromeric heterochromatin. Remarkably, we show that synthetic repeat-derived siRNAs are sufficient to rescue Dicer-2 deficiency-induced defects in heterochromatin formation in interphase and chromosome segregation during mitosis, thus demonstrating that active retrotransposons are actually required for stable genetic inheritance.
The Impact of Genetic Background and Cell Lineage on the Level and Pattern of Position Effect Variegation
Authors: Wang Sidney H. , Elgin Sarah C.R. 
Published: August 2019

AbstractBackgroundChromatin-based transcriptional silencing is often described as a stochastic process, largely because of the mosaic expression observed in position effect variegation (PEV), where a euchromatic reporter gene is juxtaposed with heterochromatin. Here we closely examine the impact of genetic background on PEV phenotypes in the fruit fly,Drosophila melanogaster.ResultsUsing consecutive generations of selective breeding, we isolated, from a single laboratory population, two inbred lines exhibiting contrasting degrees of variegation (A1: low expression, D1: high expression). Within each inbred population, remarkable similarity is observed in both the degree and the pattern of variegation. 89.63% of the differences between the two inbred lines in the degree of silencing can be explained by genotype, while a modest but significant sex effect is also observed. Further analyses of the PEV phenotype in the progeny of crosses between A1 and D1 suggest that the genotypic effect is the result of the combined effect of multiple independenttrans-acting loci. While the initial observations are based on a PEV phenotype scored in the fly eye (hsp70-whitereporter), similar degrees of silencing were observed using abeta-galreporter that can be scored across the whole fly. The pattern of variegatinghsp70-whiteexpression among individual flies becomes almost identical after five generations of inbreeding. Using a reporter inserted into the heterochromatic fourth chromosome, image analysis found significant enrichment of pigmentation in the ventral-posterior quadrant in both the A1 and D1 lines, and in the F1 and F2 progeny produced from a cross between A1 and D1, despite different degrees of expression.ConclusionsCombining these results with the spreading model for local heterochromatin formation, we propose an augmented stochastic model to describe PEV. In this model, the genetic background, which determines the overall level of silencing, works with the cell lineage specific regulatory environment to determine the on/ off probability at the reporter locus in each cell. This model acknowledges cell-type specific events, as well as the general impact of heterochromatin formation.
Anaerobic degradation of syringic acid by an adapted strain ofRhodopseudomonas palustris
Authors: Oshlag J. Zachary , Ma Yanjun , Morse Kaitlin , Burger Brian T. , Lemke Rachelle A. , Karlen Steven D. , Myers Kevin S. , Donohue Timothy J. , Noguera Daniel R. 
Published: August 2019

ABSTRACTWhile lignin represents a major fraction of the carbon in plant biomass, biological strategies to convert the components of this heterogenous polymer into products of industrial and biotechnological value are lacking. Syringic acid (3,5-dimethoxy-4-hydroxybenzoic acid) is a byproduct of lignin degradation, appearing in lignocellulosic hydrolysates, deconstructed lignin streams, and other agricultural products.Rhodopseudomonas palustrisCGA009 is a known degrader of phenolic compounds under photoheterotrophic conditions, via the benzoyl-CoA degradation (BAD) pathway. However,R. palustrisCGA009 is reported to be unable to metabolizemeta-methoxylated phenolics such as syringic acid. We isolated a strain ofR. palustris(strain SA008.1.07), adapted from CGA009, which can grow on syringic acid under photoheterotrophic conditions, utilizing it as a sole source of organic carbon and reducing power. An SA008.1.07 mutant with an inactive benzoyl-CoA reductase structural gene was able to grow on syringic acid, demonstrating that the metabolism of this aromatic compound is not through the BAD pathway. Comparative gene expression analyses of SA008.1.07 implicated the involvement of products of thevanARBoperon (rpa3619-rpa3621), which has been described as catalyzing aerobic aromatic ring demethylation in other bacteria, in anaerobic syringic acid degradation. In addition, experiments with avanARBdeletion mutant demonstrated the involvement of thevanARBoperon in anaerobic syringic acid degradation. These observations provide new insights into the anaerobic degradation ofmeta-methoxylated and other aromatics byR. palustris.IMPORTANCELignin is the most abundant aromatic polymer on Earth and a resource that could eventually substitute for fossil fuels as a source of aromatic compounds for industrial and biotechnological applications. Engineering microorganisms for production of aromatic-based biochemicals requires detailed knowledge of metabolic pathways for the degradation of aromatics that are present in lignin. Our isolation and analysis of aRhodopseudomonas palustrisstrain capable of syringic acid degradation reveals a previously unknown metabolic route for aromatic degradation inR. palustris. This study highlights several key features of this pathway and sets the stage for a more complete understanding of the microbial metabolic repertoire to metabolize aromatic compounds from lignin and other renewable sources.
External quality assessment of bacterial identification and antimicrobial susceptibility testing in African national public health laboratories, 2011–2016
Authors: Perovic Olga , Yahaya Ali A. , Viljoen Crystal , Ndihokubwayo Jean-Bosco , Smith Marshagne , Coulibaly Sheick O. , De Gouveia Linda , Oxenford Christopher J. , Cognat Sebastien , Frean John 
Published: August 2019

AbstractBackgroundIn 2002, the World Health Organization (WHO) launched a regional microbiology external quality assessment (EQA) programme for national public health laboratories in the African region, initially targeting priority epidemic-prone bacterial diseases, and later including other common bacterial pathogens.ObjectivesThe aim of this study was to analyse the efficacy of an EQA programme as a laboratory quality system evaluation tool.MethodsWe analysed the proficiency of laboratories’ performance of bacterial identification and AST for the period 2011–2016. Overall, 81 laboratories from 45 countries participated.The National Institute for Communicable Diseases of South Africa provided technical coordination following an agreement with WHO, and supplied EQA samples of selected bacterial organisms for microscopy (Gram stain), identification, and antimicrobial susceptibility testing (AST). National public health laboratories, as well as laboratories involved in the Invasive Bacterial Diseases Surveillance Network, were enrolled by the WHO Regional Office for Africa to participate in the EQA programme.ResultsWe analysed participants’ results of 41 surveys, which included the following organisms sent as challenges: Streptococcus pneumonia, Haemophilus influenza, Neisseria meningitidis, Salmonella Typhi, Salmonella Enteritidis, Shigella flexneri, Staphylococcus aureus, Streptococcus agalactiae, Streptococcus anginosus, Enterococcus faecium, Serratia marcescens, Acinetobacter baumannii, and Enterobacter cloacae. Overall, 76% of participants obtained acceptable scores for identification, but a substantial proportion of AST scores were not in the acceptable range.ConclusionIn the African Region, implementation of diagnostic stewardship in clinical bacteriology is generally suboptimal. This report illustrates that AST is poorly done compared to microscopy and identification. It is critically important to make the case for implementation of quality assurance in AST, as it is the cornerstone for antimicrobial resistance surveillance reporting and implementation of the Global Antimicrobial Resistance Surveillance System.
Identification of immunoreactive linear epitopes ofBorrelia miyamotoi
Authors: Tokarz Rafal , Tagliafierro Teresa , Caciula Adrian , Mishra Nischay , Thakkar Riddhi , Chauhan Lokendra V , Sameroff Stephen , Delaney Shannon , Wormser Gary P. , Marques Adriana , Lipkin W. Ian 
Published: August 2019

AbstractBorrelia miyamotoiis an emerging tick-borne spirochete transmitted byIxodidticks. Current serologic assays forB. miyamotoiare impacted by genetic similarities to otherBorreliaand limited understanding of optimal antigenic targets. In this study, we employed the TBD-Serochip, a peptide array platform, to identify new linear targets for serologic detection ofB. miyamotoi. We examined a wide range of suspectedB. miyamotoiantigens and identified 352 IgM and 91 IgG reactive peptides, with the majority mapping to variable membrane proteins. These included peptides within conserved fragments of variable membrane proteins that may have greater potential for differential diagnosis. We also identified reactive regions on FlaB, and demonstrate crossreactivity ofB. burgdorferiC6 with aB. miyamotoiC6-like peptide. The panel of linear peptides identified in this study can be used to enhance serodiagnosis ofB. miyamotoi.
Motion Coherence and Luminance Contrast Interact in Driving Visual Gamma-Band Activity
Authors: Pellegrini Franziska , Hawellek David J , Pape Anna-Antonia , Hipp Joerg F , Siegel Markus 
Published: August 2019

AbstractSynchronized neuronal population activity in the gamma-frequency range (> 30 Hz) correlates with the bottom-up drive of various visual features. It has been hypothesized that gamma-band synchronization enhances the gain of neuronal representations, yet evidence remains sparse. We tested a critical prediction of the gain hypothesis, which is that features that drive synchronized gamma-band activity interact super-linearly. To test this prediction, we employed whole-head magnetencephalography (MEG) in human subjects and investigated if the strength of visual motion (motion coherence) and luminance contrast interact in driving gamma-band activity in visual cortex. We found that gamma-band activity (64 to 128 Hz) monotonically increased with coherence and contrast while lower frequency activity (8 to 32 Hz) decreased with both features. Furthermore, as predicted for a gain mechanism, we found a multiplicative interaction between motion coherence and contrast in their joint drive of gamma-band activity. The lower frequency activity did not show such an interaction. Our findings provide evidence, that gamma-band activity acts as a cortical gain mechanism that nonlinearly combines the bottom-up drive of different visual features in support of visually guided behavior.
Epigenetic mechanism of carbohydrate sulfotransferase 3 (CHST3) downregulation in the aging brain
Authors: Baidoe-Ansah David , Sadman Sakib M , Jia Shaobo , Fischer Andre , Kaushik Rahul , Dityatev Alexander 
Published: August 2019

AbstractNeural extracellular matrix (ECM) is a complex molecular meshwork surrounding neurons and glial cells in the extracellular space. Structural and functional state of ECM in the brain is tightly regulated by various components of neural ECM such as hyaluronic acid, chondroitin sulfate proteoglycans, link proteins, tenascins, various matrix-modifying enzymes such as chondroitin sulfate synthases and carbohydrate sulfotransferase together with matrix-degrading enzymes. Age-dependent accumulation of ECM molecules is implicated in the age-associated decline in synaptic and cognitive functions. Understanding age-associated changes in the expression of genes involved in regulating various components of ECM can provide an insight into the role of ECM in the aging brain. Hence, in this study, we compared the expression levels of ECM regulating genes in three groups of mice: 2-3 months old mice (2-3M), 22- to 26-month-old mice (22-26M) and more than 30-month-old mice (>30M). Using qPCR, we discovered that in the hippocampus of >30M old mice, the majority of ECM related genes are downregulated, while genes related to neuroinflammation are highly upregulated. This pattern was accompanied by a decrease in cognitive performance of the >30M old mice and was most correlated among ECM-related genes with the downregulation of carbohydrate sulfotransferase 3 (CHST3) gene expression. Interestingly, in 24-26M mice, no general decrease in the expression of ECM related genes was observed, although we still found the upregulation in neuroinflammatory genes and downregulation ofCHST3. Further analysis of epigenetic mechanisms revealed a decrease in H3K4me3, three methyl groups at the lysine 4 on the histone H3 proteins, associated with the promoter region ofCHST3gene in non-neuronal (NeuN-negative) but not in neuronal (NeuN-positive) cells. We conclude that in 22-26 M old brains there are minor changes in expression of the studiedbona fideneural ECM genes but there is a prominent epigenetic dysregulation of theCHST3gene responsible for 6-sulfation of chondroitin sulfates, which may lead to impaired brain plasticity and cognitive decline.
Staging Alzheimer’s disease in the brain and retina of B6.APP/PS1 mice by transcriptional profiling
Authors: Chintapaludi Sumana R. , Uyar Asli , Jackson Harriet M. , Acklin Casey J. , Wang Xulong , Sasner Michael , Carter Gregory W. , Howell Gareth R. 
Published: August 2019

ABSTRACTAlzheimer’s disease (AD) is a common form of dementia characterized by amyloid plaque deposition, TAU pathology, neuroinflammation and neurodegeneration. Mouse models recapitulate some key features of AD. For instance, the B6.APP/PS1 model (carrying human transgenes for mutant forms of APP and PSEN1) shows plaque deposition and associated neuroinflammatory responses involving both astrocytes and microglia beginning around 6 months of age. However, in our colony, TAU pathology, significant neurodegeneration and cognitive decline are not apparent in this model even at older ages. Therefore, this model is ideal for studying neuroinflammatory responses to amyloid deposition. Here, RNA sequencing of brain and retinal tissue, generalized linear modeling (GLM), functional annotation followed by validation by immunofluorescence (IF) was performed in B6.APP/PS1 mice to determine the earliest molecular changes prior to and around the onset of plaque deposition (2-6 months of age). Multiple pathways were shown to be activated in response to amyloid deposition including the JAK/STAT and NALFD pathways. Putative, cell-specific targets of STAT3, a central component of the JAK/STAT pathway, were identified that we propose provide more precise options for assessing the potential for targeting activation of the JAK/STAT pathway as a treatment for human AD. In the retina, GLM predicted activation of vascular-related pathways. However, many of the gene expression changes comparing B6 with B6.APP/PS1 retina samples occurred prior to plaque onset (2 months of age). This suggests retinal changes in B6.APP/PS1 mice may be an artefact of overexpression of mutant forms of APP and PSEN1 providing limited translatability to human AD. Therefore, caution should be taken when using this mouse model to assess the potential of using the eye as a window to the brain for AD.
Chromatin 3D structure reconstruction with consideration of adjacency relationship among genomic loci
Authors: Li Fang-Zhen , Liu Zhi-E , Li Xiu-Yuan , Bu Li-Mei , Bu Hong-Xia , Liu Hui , Zhang Cai-Ming 
Published: August 2019

AbstractChromatin 3D conformation plays important roles in regulating gene or protein functions. High-throughout chromosome conformation capture (3C)-based technologies, such as Hi-C, have been exploited to acquire the contact frequencies among genomic loci at genome-scale. Various computational tools have been proposed to recover the underlying chromatin 3D structures from in situ Hi-C contact map data. As connected residuals in a polymer, neighboring genomic loci have intrinsic mutual dependencies in building a 3D conformation. However, current methods seldom take this feature into account. We present a method called ShNeigh, which combines the classical MDS technique with local dependence of neighboring loci modelled by a Gaussian formula, to infer the best 3D structure from noisy and incomplete contact frequency matrices. The results obtained on simulations and real Hi-C data showed, while keeping the high-speed nature of classical MDS, ShNeigh is more accurate and robust than existing methods, especially for sparse contact maps. A Matlab implementation of the proposed method is available at https://github.com/fangzhen-li/ShNeigh.Author summaryWe propose a new method to infer a consensus 3D genome structure from a Hi-C contact map. The novelty of our method is that it takes into accounts the adjacency of genomic loci along chromosomes. Specifically, the proposed method penalizes the optimization problem of the classical multidimensional scaling method with a smoothness constraint weighted by a function of the genomic distance between the pairs of genomic loci. We demonstrate this optimization problem can still be solved efficiently by a classical multidimensional scaling method. We then show that the method can recover stable structures in high noise settings. We also show that it can reconstruct similar structures from data obtained using different restriction enzymes.
Housing laboratory mice deficient for Nod2 and Atg16l1 in a natural environment uncovers genetic and environmental contributions to immune variation
Authors: Lin Jian-Da , Devlin Joseph C. , Yeung Frank , McCauley Caroline , Leung Jacqueline M. , Chen Ying-Han , Cronkite Alex , Hansen Christina , Drake-Dunn Charlotte , Ruggles Kelly V. , Cadwell Ken , Graham Andrea L. , Loke P’ng 
Published: August 2019

SUMMARYThe relative contributions of genetic and environmental factors to variation in immune responses are still poorly understood. Here, we performed a deep phenotypic analysis of immunological parameters of laboratory mice released into an outdoor enclosure, carrying susceptibility genes (Nod2 and Atg16l1) implicated in the development of inflammatory bowel diseases. Variations of immune cell populations were largely driven by environment, whereas cytokine production in response to stimulation was affected more by genetic mutations. Multi-omic models identified transcriptional signatures associated with differences in T cell populations. Subnetworks associated with responses against Clostridium perfringens, Candida albicans and Bacteroides vulgatus were also coupled with rewilding. Hence, exposing laboratory mice carrying different genetic mutations to a natural environment uncovered important contributors to immune variation.One sentence summaryNatural environment exposure in laboratory mice primarily promotes variation in population frequencies of immune cells, whereas cytokine responses to stimulation are affected more by genetic susceptibility to inflammatory bowel disease.
Predicting 30-day Hospital Readmissions Using Artificial Neural Networks with Medical Code Embedding
Authors: Liu Wenshuo , Singh Karandeep , Ryan Andrew M. , Sukul Devraj , Mahmoudi Elham , Waljee Akbar K. , Stansbury Cooper M. , Zhu Ji , Nallamothu Brahmajee K. 
Published: August 2019

ABSTRACTReducing unplanned readmissions is a major focus of current hospital quality efforts. In order to avoid unfair penalization, administrators and policymakers use prediction models to adjust for the performance of hospitals from healthcare claims data. Regression-based models are a commonly utilized method for such risk-standardization across hospitals; however, these models often suffer in accuracy. In this study we, compare four prediction models for unplanned patient readmission for patients hospitalized with acute myocardial infarction (AMI), congestive health failure (HF), and pneumonia (PNA) within the Nationwide Readmissions Database in 2014. We evaluated hierarchical logistic regression and compared its performance with gradient boosting and two models that utilize artificial neural network. We show that unsupervised Global Vector for Word Representations embedding representations of administrative claims data combined with artificial neural network classification models significantly improves prediction of 30-day readmission. Our best models increased the AUC for prediction of 30-day readmissions from 0.68 to 0.72 for AMI, 0.60 to 0.64 for HF, and 0.63 to 0.68 for PNA compared to hierarchical logistic regression. Furthermore, risk-standardized hospital readmission rates calculated from our artificial neural network model that employed embeddings led to reclassification of approximately 10% of hospitals across categories of hospital performance. This finding suggests that prediction models that incorporate new methods classify hospitals differently than traditional regression-based approaches and that their role in assessing hospital performance warrants further investigation.