bluuebunny/crossref_metadata_2025_split huggingface dataset:
Culturing primary neurons from rat hippocampus and cortex
Authors: Sahu Madhusmita Priyadarshini , Nikkilä Outi , Lågas Seija , Kolehmainen Sulo , Castrén Eero 
Published: December 2018

AbstractPrimary neurons from rodent brain hippocampus and cortex has served as great tools in biomedical research over the years. However, protocols for the preparation of primary neurons vary, which often leads to conflicting results. This report provides a robust and reliable protocol for the production of primary neuronal cultures from the cortex and hippocampus with minimal contribution of non-neuronal cells. The neurons were grown in serum free media and maintained for several weeks without any additional feeder cells. The neuronal cultures maintained according to this protocol differentiate and by three weeks develop extensive axonal and dendritic branching. The cultures produced by this method show excellent reproducibility and can be used for histological, molecular and biochemical methods.
“Homogenous subgroups of atypical meningiomas defined using oncogenic signatures: basis for a new grading system?”
Authors: Zador Zsolt , Landry Alexander , Saha Ashirbani , Cusimano Michael D. 
Published: December 2018

AbstractMeningiomas are the most common brain tumor with a prevalence of 3% in the population. Histological grading of meningiomas (1 through 3) has a major role in determining treatment choice and predicting outcome. While largely indolent grade 1 and the highly aggressive grade 3 meningiomas as considered mostly homogenous in clinical behavior, atypical or grade 2 meningiomas have highly diverse biological properties. Our aim was to identify homogenous subgroups of atypical meningiomas with the working hypothesis that these subgroups would share features with grade 1 and grade 3 counterparts. We carried out systems level analysis by gene module discovery using co-expression networks on the transcriptomics of 212 meningiomas. The newly identified subgroups were characterized in terms of recurrence rate and overlapping biological processes in gene ontology. We were able to reclassify 33 of 46 atypical meningiomas (72%) into a benign “grade 1-like” (14/46) and malignant “grade 3-like” (19/46) subgroup based on oncogenic signatures. Recurrence rates of “Grade 1-like” and “grade 3-like” tumors was 0% and 72% respectively. These two new subgroups showed similar recurrence rates and concordant biological processes with the respected grades. Our findings help resolve the heterogeneity/uncertainty around atypical meningioma biology and identify subgroups more homogenous than in prior studies. These results may help reshape prediction, follow-up planning, treatment decisions and recruitment protocols for future and ongoing clinical trials. The findings demonstrate the conceptual advantage of systems biology approaches and underpin the utility of molecular signatures as complements to the current histological grading system.
Environmental heterogeneity drives tsetse fly population dynamics
Authors: Cecilia Hélène , Arnoux Sandie , Picault Sébastien , Dicko Ahmadou , Seck Momar Talla , Sall Baba , Bassène Mireille , Vreysen Marc , Pagabeleguem Soumaïla , Bancé Augustin , Bouyer Jérémy , Ezanno Pauline 
Published: December 2018

AbstractA spatially and temporally heterogeneous environment may lead to unexpected population dynamics, and knowledge still is needed on which of the local environment properties favour population maintenance at larger scale. As regards pathogen vectors, such as tsetse flies transmitting human and animal African trypanosomosis, such a knowledge is crucial for proposing relevant management strategy. We developed an original mechanistic spatio-temporal model of tsetse fly population dynamics, accounting for combined effects of spatial complexity, density-dependence, and temperature on the age-structured population, and parametrized with field and laboratory data. We confirmed the strong impact of temperature and adult mortality on tsetse populations. We showed that patches with the lowest mean temperatures and lowest variations act as refuges when adult mortality is homogeneously increased. Our results highlighted the importance of baseline data collection to characterize the targeted ecosystem before any control measure is implemented to maximize its efficiency.
Heterogeneous progenitor cell behaviors underlie the assembly of neocortical cytoarchitecture
Authors: Llorca Alfredo , Ciceri Gabriele , Beattie Robert , Wong Fong K. , Diana Giovanni , Serafeimidou Eleni , Fernández-Otero Marian , Streicher Carmen , Arnold Sebastian J. , Meyer Martin , Hippenmeyer Simon , Maravall Miguel , Marín Oscar 
Published: December 2018

SUMMARYThe cerebral cortex contains multiple hierarchically organized areas with distinctive cytoarchitectonical patterns, but the cellular mechanisms underlying the emergence of this diversity remain unclear. Here, we have quantitatively investigated the neuronal output of individual progenitor cells in the ventricular zone of the developing mouse neocortex using a combination of methods that together circumvent the biases and limitations of individual approaches. We found that individual cortical progenitor cells show a high degree of stochasticity and generate pyramidal cell lineages that adopt a wide range of laminar configurations. Mathematical modelling these lineage data suggests that a small number of progenitor cell populations, each generating pyramidal cells following different stochastic developmental programs, suffice to generate the heterogenous complement of pyramidal cell lineages that collectively build the complex cytoarchitecture of the neocortex.
Large-scale analyses of human microbiomes reveal thousands of small, novel genes and their predicted functions
Authors: Sberro Hila , Greenfield Nicholas , Pavlopoulos Georgios , Kyrpides Nikos , Bhatt Ami S. 
Published: December 2018

AbstractSmall proteins likely abound in prokaryotes, and may mediate much of the communication that occurs between organisms within a microbiome and their host. Unfortunately, small proteins are traditionally overlooked in biology, in part due to the computational and experimental difficulties in detecting them. To systematically identify novel small proteins, we carried out a large comparative genomics study on 1,773 HMP human-associated metagenomes from four different body sites (mouth, gut, skin and vagina). We describe more than four thousand conserved protein families, the majority of which are novel; ~30% of these protein families are predicted to be secreted or transmembrane. Over 90% of the small protein families have no known domain, and almost half are not represented in reference genomes, emphasizing the incompleteness of knowledge in this space. Our analysis exposes putative novel ‘housekeeping’ small protein families, including a potential novel ribosomally associated protein, as well as ‘mammalian-specific’ or ‘human-specific’ protein families. By analyzing the genomic neighborhood of small genes, we pinpoint a subset of families that are potentially associated with defense against bacteriophage. Finally, we identify families that may be subject to horizontal transfer and are thus potentially involved in adaptation of bacteria to the changing human environment. Our study suggest that small proteins are highly abundant and that those of the human microbiome, in particular, may perform diverse functions that have not been previously reported.
Novel Computational Method to Define RNA PSRs Explains Influenza A Virus Nucleotide Conservation
Authors: Chursov Andrey , Fridlyand Nathan , Sufianov Albert A. , Kiselev Oleg I. , Baranovskaya Irina , Vasin Andrey , Yewdell Jonathan W. , Shneider Alexander 
Published: December 2018

ABSTRACTRNA molecules often fold into evolutionarily selected functional structures. Yet, the literature offers neither a satisfactory definition for “structured RNA regions”, nor a computational method to accurately identify such regions. Here, we define structured RNA regions based on the premise that both stems and loops in functional RNA structures should be conserved among RNA molecules sharing high sequence homology. In addition, we present a computational approach to identify RNA regions possessing evolutionarily conserved secondary structures, RNA ISRAEU (RNA Identification of Structured Regions As Evolutionary Unchanged). Applying this method to H1N1 influenza mRNAs revealed previously unknown structured RNA regions that are potentially essential for viral replication and/or propagation. Evolutionary conservation of RNA structural elements may explain, in part, why mutations in some nucleotide positions within influenza mRNAs occur significantly more often than in others. We found that mutations occurring in conserved nucleotide positions may be more disruptive for structured RNA regions than single nucleotide polymorphisms in positions that are more prone to changes. Finally, we predicted computationally a previously unknown stem-loop structure and demonstrated that oligonucleotides complementing the stem (but not the loop or unrelated sequences) reduce viral replicationin vitro.These results contribute to understanding influenza A virus evolution and can be applied to rational design of attenuated vaccines and/or drug designs based on disrupting conserved RNA structural elements.AUTHOR SUMMARYRNA structures play key biological roles. However, the literature offers neither a satisfactory definition for “structured RNA regions” nor the computational methodology to identify such regions. We define structured RNA regions based on the premise that functionally relevant RNA structures should be evolutionarily conserved, and devise a computational method to identify RNA regions possessing evolutionarily conserved secondary structural elements. Applying this method to influenza virus mRNAs of pandemic and seasonal H1N1 influenza A virus generated Predicted Structured Regions (PSRs), which were previously unknown. This explains the previously mysterious sequence conservation among evolving influenza strains. Also, we have experimentally supported existence of a computationally predicted stem-loop structure predicted computationally. Our approach may be useful in designing live attenuated influenza vaccines and/or anti-viral drugs based on disrupting necessary conserved RNA structures.
Unpredictable effects of the genetic background of transgenic lines in physiological quantitative traits
Authors: Evangelou Amalia , Ignatiou Anastasia , Antoniou Chloi , Kalanidou Sofia , Chatzimatthaiou Sotiroula , Shianiou Gavriella , Ellina Soteroulla , Athanasiou Rafaella , Panagi Myrofora , Apidianakis Yiorgos , Pitsouli Chrysoula 
Published: December 2018

ABSTRACTPhysiological, fitness and disease phenotypes are complex traits exhibiting continuous variation in natural populations. To understand complex trait gene functions transgenic lines of undefined genetic background are often combined to assess quantitative phenotypes ignoring the impact of genetic polymorphisms. Here, we used inbred wild-type strains of theDrosophilaGenetics Reference Panel to assess the phenotypic variation of six physiological and fitness traits, namely, female fecundity, survival and intestinal mitosis upon oral infection, defecation rate and fecal pH upon oral infection, and terminal tracheal cell branching in hypoxia. We found continuous variation in the approximately 150 strains tested for each trait, with extreme values differing by more than four standard deviations for all traits. In addition, we assessed the effects of commonly usedDrosophila UAS-RNAitransgenic strains and their backcrossed isogenized counterparts, in the same traits plus baseline intestinal mitosis and tracheal branching in normoxia, in heterozygous conditions, when only half of the genetic background was different among strains. We tested 20 non-isogenic strains (10 KK and 10 GD) from the ViennaDrosophilaResource Center and their isogenized counterparts without Gal4 induction. Survival upon infection and female fecundity exhibited differences in 50% and 40% of the tested isogenic vs. non-isogenic pairs, respectively, whereas all other traits were affected in only 10-25% of the cases. Upon Gal4-inducedUAS-RNAiexpression, 4 out of 11 isogenic vs. non-isogenic pairs tested exhibited differences in survival to infection. Andvice versa, crossing a singleUAS-RNAiline with a Gal4 transgene inserted in different genetic backgrounds exhibited quantitative variations that were unpredictable on the basis of pure line performance. Thus, irrespective of the trait of interest, the genetic background of commonly used transgenic strains needs to be considered carefully during experimentation.
Data from an electronic health informatics pipeline to describe clearance dynamics of Hepatitis B surface antigen (HBsAg) and e-Antigen (HBeAg) in chronic HBV infection
Authors: Downs Louise , Smith David , Lumley Sheila F , Patel Meha , McNaughton Anna L , Mokaya Jolynne , Ansari M Azim , Salih Hizni , Várnai Kinga A , Freeman Oliver , Cripps Sarah , Phillips Jane , Collier Jane , Woods Kerrie , Channon Keith , Davies Jim , Barnes Eleanor , Jeffery Katie , Matthews Philippa C 
Published: December 2018

ABSTRACTHBsAg and HBeAg have gained traction as biomarkers of control and clearance during monitoring of chronic hepatitis B virus infection (CHB). An improved understanding of the correlates of clearance of these proteins could help inform improvements in patient-stratified care and advance insights into the underlying mechanisms of disease control, thus underpinning new cure strategies. We collected electronic clinical data via an electronic pipeline supported by the National Institute for Health Research Health Informatics Collaborative (NIHR-HIC), adopting an unbiased approach to generating a robust longitudinal dataset for adults testing HBsAg-positive from a large UK teaching hospital over a six year period (2011-2016 inclusive). From 553 individuals with CHB, longitudinal data were available for 319, representing >107,000 weeks of clinical follow-up. Among these 319 individuals, 13 (4%) cleared HBsAg completely. HBsAg clearance rate was similar in individuals on NA therapy (n=4, median clearance time 150 weeks) vs those not on NA therapy (n=9, median clearance time 157 weeks). Those who cleared HBsAg were significantly older, and less likely to be on NA therapy compared to non-clearers (p=0.003 and p=0.001, respectively). Chinese ethnicity was associated with HBeAg positivity (p=0.025). HBeAg clearance occurred both on NA therapy (n=24, median time 49 weeks) and off NA therapy (n=19, median time 52 weeks). Improved insights into the dynamics of these biomarkers can underpin better prognostication and patient-stratified care. Our systematised approach to data collection paves the way for scaling up efforts to harness clinical data to address research questions and underpin improvements in clinical care provision.IMPORTANCEAdvances in the diagnosis, monitoring and treatment of hepatitis B virus (HBV) infection are urgently required if we are to meet international targets for elimination by the year 2030. Here we demonstrate how routine clinical data can be harnessed through an unbiased electronic pipeline, showcasing the significant potential for amassing large clinical datasets that can help to inform advances in patient care, and provide clues that inform new cure strategies. Our cohort from a large UK hospital includes adults from diverse ethnic groups that have previously been under-represented in the literature. Tracking two protein biomarkers that are used to monitor chronic HBV infection, we provide new insights into the timelines of HBV clearance, both on and off treatment. These results contribute to improvements in individualised clinical care and may provide important clues into the immune events that underpin disease control.
Biophysical and physiological causes of coral reef microbialization
Authors: Silveira Cynthia B. , Roach Ty N. F. , Villela Helena , Barno Adam , Reyes Brandon , Rubio-Portillo Esther , Le Tram , Mead Spencer , Hatay Mark , Luque Antoni , Wegley-Kelly Linda , Vermeij Mark , Bailey Barbara , Takeshita Yui , Haas Andreas , Rohwer Forest 
Published: December 2018

AbstractCoral reefs are declining globally as their primary producer communities shift from stony coral to fleshy macroalgae dominance. Previously, we have shown that the rise of fleshy macroalgae produces dissolved organic carbon (DOC) that lead to microbialization and coral death. Here we test the hypothesis that the biophysical cause of bacterial biomass accumulation is a relative decrease in electron acceptors relative to electron donors due to O2loss from macroalgae. We show that 37 % of photosynthetic O2produced by reef fleshy macroalgae is lost in the form of gas through ebullition from algae surfaces. O2loss increases DOC:O2ratios, decoupling the photosynthetically fixed carbon from oxidative potential for respiration. This biogeochemical environment drives heterotrophic microbes to increase cell-specific DOC consumption and cell sizes, accumulating biomass. In contrast, corals do not lose oxygen and support the growth of smaller and fewer bacteria.In situbiomass and metagenomic analyses of 87 reefs across the Pacific and Caribbean show that on algae-dominated reefs bacteria accumulate organic carbon through a Warburg-like increase in aerobic glycolytic metabolism. Because of its biophysical basis, microbialization is predicted to occur in other marine ecosystems shifting primary producer assemblages, such as planktonic communities in warming and acidifying conditions.
The Bellerophon pipeline, improving de novo transcriptomes and removing chimeras
Authors: Kerkvliet Jesse , de Fouchier Arthur , van Wijk Michiel , Groot Astrid T. 
Published: December 2018

AbstractTranscriptome quality control is an important step in RNA-seq experiments. However, the quality of de novo assembled transcriptomes is difficult to assess, due to the lack of reference genome to compare the assembly to. We developed a method to assess and improve the quality of de novo assembled transcriptomes by focusing on the removal of chimeric sequences. These chimeric sequences can be the result of faulty assembled contigs, merging two transcripts into one. The developed method is incorporated into a pipeline, that we named Bellerophon, which is broadly applicable and easy to use. Bellerophon first uses the quality-assessment tool TransRate to indicate the quality, after which it uses a Transcripts Per Million (TPM) filter to remove lowly expressed contigs and CD-HIT-EST to remove highly identical contigs. To validate the quality of this method, we performed three benchmark experiments: 1) a computational creation of chimeras, 2) identification of chimeric contigs in a transcriptome assembly, 3) a simulated RNAseq experiment using a known reference transcriptome. Overall, the Bellerophon pipeline was able to remove between 40 to 91.9% of the chimeras in transcriptome assemblies and removed more chimeric than non-chimeric contigs. Thus, the Bellerophon sequence of filtration steps is a broadly applicable solution to improve transcriptome assemblies.
The impact of stroma on the discovery of molecular subtypes and prognostic gene signatures in serous ovarian cancer
Authors: Schwede Matthew , Waldron Levi , Mok Samuel C. , Wei Wei , Basunia Azfar , Merritt Melissa A. , Parmigiani Giovanni , Harrington David , Quackenbush John , Birrer Michael J. , Culhane Aedín C. 
Published: December 2018

AbstractPurposeRecent efforts to improve outcomes for high-grade serous ovarian cancer, a leading cause of cancer death in women, have focused on identifying molecular subtypes and prognostic gene signatures, but existing subtypes have poor cross-study robustness. We tested the contribution of cell admixture in published ovarian cancer molecular subtypes and prognostic gene signatures.Experimental DesignPublic gene expression data, two molecular subtype classifications, and 61 published gene signatures of ovarian cancer were examined. Using microdissected data, we developed gene signatures of ovarian tumor and stroma. Computational simulations of increasing stromal cell proportion were performed by mixing gene expression profiles of paired microdissected ovarian tumor and stroma.ResultsEstablished ovarian cancer molecular subtypes are strongly associated with the cell admixture. Tumors were classified as different molecular subtypes in simulations, when the percentage of stromal cells increased. Stromal gene expression in bulk tumor was weakly prognostic, and in one dataset, increased stroma was associated with anatomic sampling location. Five published prognostic gene signatures were no longer prognostic in a multivariate model that adjusted for stromal content alone.ConclusionsThe discovery that molecular subtypes of high grade serous ovarian cancer is influenced by cell admixture, and stromal cell gene expression is crucial for interpretation and reproduction of ovarian cancer molecular subtypes and gene signatures derived from bulk tissue. Single cell analysis may be required to refine the molecular subtypes of high grade serous ovarian cancer. Because stroma proportion was weakly prognostic, elucidating the role of the tumor microenvironment’s components will be important.Translational relevanceOvarian cancer is a leading cause of cancer death in women in the United States. Although the tumor responds to standard therapy for the majority of patients, it frequently recurs and becomes drug-resistant. Recent efforts have focused on identifying molecular subtypes and prognostic gene signatures of ovarian cancer in order to tailor therapy and improve outcomes. This study demonstrates that molecular subtype identification depends on the ratio of tumor to stroma within the specimen. We show that the specific anatomic location of the biopsy may influence the proportion of stromal involvement and potentially the resulting gene expression pattern. It will be crucial for these factors to be taken into consideration when interpreting and reproducing ovarian cancer molecular subtypes and gene signatures derived using bulk tissue and single cells. Furthermore, it will be important to define the relative proportions of stromal cells and model their prognostic importance in the tumor microenvironment.
Inference of Nonlinear Spatial Subunits in Primate Retina with Spike-Triggered Clustering
Authors: Shah Nishal P. , Brackbill Nora , Rhoades Colleen E. , Kling Alexandra , Goetz Georges , Litke Alan , Sher Alexander , Simoncelli Eero P. , Chichilnisky E.J. 
Published: December 2018

AbstractIntegration of rectified synaptic inputs is a widespread nonlinear motif in sensory neuroscience. We present a novel method for maximum likelihood estimation of nonlinear subunits by soft-clustering spike-triggered stimuli. Subunits estimated from parasol ganglion cells recorded in macaque retina partitioned the receptive field into compact regions, likely representing bipolar cell inputs. Joint clustering with multiple RGCs revealed shared subunits in neighboring cells, producing a parsimonious population model. Closed-loop subunit validation was then performed by projecting white noise into the null space of the linear receptive field. Responses to these null stimuli were more accurately explained by a model with multiple subunits, and were stronger in OFF cells than ON cells. Presentation of natural stimuli containing jittering edges and textures also revealed greater response prediction accuracy with the subunit model. Finally, the generality of the approach was demonstrated by application to V1 data.