bluuebunny/crossref_metadata_2025_split huggingface dataset:
Safety and Efficacy of Laparoscopic Liver Resection for Lesions Located on Posterosuperior Segments: A Meta-Analysis of Short-term Outcomes
Authors: Machairas Nikolaos , Prodromidou Anastasia , Kostakis Ioannis D. , Spartalis Eleftherios , Sotiropoulos Georgios C. 
Published: August 2018

Introduction:
Laparoscopic liver resections (LLR) are currently acknowledged as safe and efficient procedures. LLR in posterosuperior (PS) segments are considered highly challenging procedures. The aim of our meta-analysis was to evaluate the effect of LLR versus open liver resection on short-term outcomes for PS segment lesions.

Materials and Methods:
A systematic search of Medline, Scopus, Google Scholar, Cochrane CENTRAL Register of Controlled Trials and Clinicaltrials.gov databases for articles was performed.

Results:
Five studies involving 531 patients who underwent resection for PS liver segments lesions were included. LLR were associated with reduced blood loss and overall complications. Operative time, blood transfusion, R0 resection, resection margin, hospital stay, and mortality were not found different among the 2 groups.

Conclusions:
Notwithstanding their highly demanding nature, LLR in PS segments are safe and efficient procedures in the hands of experienced surgeons. Further studies are mandatory to evaluate their effect in these challenging liver resections.
An integrative genomic analysis of the Longshanks selection experiment for longer limbs in mice
Authors: Castro João P. L. , Yancoskie Michelle N. , Marchini Marta , Belohlavy Stefanie , Kučka Marek , Beluch William H. , Naumann Ronald , Skuplik Isabella , Cobb John , Barton Nick H. , Rolian Campbell , Chan Yingguang Frank 
Published: August 2018

AbstractEvolutionary studies are often limited by missing data that are critical to understanding the history of selection. Selection experiments, which reproduce rapid evolution under controlled conditions, are excellent tools to study how genomes evolve under strong selection. Here we present a genomic dissection of the Longshanks selection experiment, in which mice were selectively bred over 20 generations for longer tibiae relative to body mass, resulting in 13% longer tibiae in two replicate lines. We synthesized evolutionary theory, genome sequences and molecular genetics to understand the selection response and found that it involved both polygenic adaptation and discrete loci of major effect, with the strongest loci likely to be selected in parallel between replicates. We show that selection may favor de-repression of bone growth through inactivation of two limb enhancers of an inhibitor,Nkx3-2. Our integrative genomic analyses thus show that it is possible to connect individual base-pair changes to the overall selection response.
Genomic Response to Selection for Diurnality and Nocturnality in Drosophila
Authors: Pegoraro Mirko , Flavell Laura M.M. , Menegazzi Pamela , Colombi Perrine , Dao Pauline , Helfrich-Förster Charlotte , Tauber Eran 
Published: August 2018

AbstractMost animals restrict their activity to a specific part of the day, being diurnal, nocturnal or crepuscular. The genetic basis underlying diurnal preference is largely unknown. Under laboratory conditions, Drosophila melanogaster is crepuscular, showing a bi-modal activity profile. However, a survey of strains derived from wild populations indicated that high variability among individuals exists, with diurnal and nocturnal flies being observed. Using a highly diverse population, we have carried out an artificial selection experiment, selecting flies with extreme diurnal or nocturnal preference. After 10 generations, we obtained highly diurnal and nocturnal strains. We used whole-genome expression analysis to identify differentially expressed genes in diurnal, nocturnal and crepuscular (control) flies. Other than one circadian clock gene (pdp1), most differentially expressed genes were associated with either clock output (pdf, to) or input (Rh3, Rh2, msn). This finding was congruent with behavioural experiments indicating that both light masking and the circadian pacemaker are involved in driving nocturnality. The diurnal and nocturnal selection strains provide us with a unique opportunity to understand the genetic architecture of diurnal preference.
Dissecting transcriptomic signatures of neuronal differentiation and maturation using iPSCs
Authors: Burke EE , Chenoweth JG , Shin JH , Collado-Torres L , Kim SK , Micali N , Wang Y , Straub RE , Hoeppner DJ , Chen HY , Lescure A , Shibbani K , Hamersky GR , Phan BN , Ulrich WS , Valencia C , Jaishankar A , Price AJ , Rajpurohit A , Semick SA , Bürli R , Barrow JC , Hiler DJ , Page SC , Martinowich K , Hyde TM , Kleinman JE , Berman KF , Apud JA , Cross AJ , Brandon NJ , Weinberger DR , Maher BJ , McKay RDG , Jaffe AE 
Published: August 2018

SummaryHuman induced pluripotent stem cells (hiPSCs) are a powerful model of neural differentiation and maturation. We present a hiPSC transcriptomics resource on corticogenesis from 5 iPSC donor and 13 subclonal lines across nine time points over 5 broad conditions: self-renewal, early neuronal differentiation, neural precursor cells (NPCs), assembled rosettes, and differentiated neuronal cells that were validated using electrophysiology. We identified widespread changes in the expression of individual transcript features and their splice variants, gene networks, and global patterns of transcription. We next demonstrated that co-culturing human NPCs with rodent astrocytes resulted in mutually synergistic maturation, and that cell type-specific expression data can be extracted using only sequencing read alignments without potentially disruptive cell sorting. We lastly developed and validated a computational tool to estimate the relative neuronal maturity of iPSC-derived neuronal cultures and human brain tissue, which were maturationally heterogeneous but contained subsets of cells most akin to adult human neurons.
ISO-RELEVANCE FUNCTIONS - A SYSTEMATIC APPROACH TO RANKING GENOMIC FEATURES BY DIFFERENTIAL EFFECT SIZE
Authors: Nayak Soumyashant , Lahens Nicholas F. , Kim Eun Ji , Ricciotti Emanuela , Paschos George , Tishkoff Sarah , Sarantopoulou Dimitra , Sengupta Shaon , Cooperman Barry , Grosser Tilo , Grant Gregory R. 
Published: August 2018

AbstractIt is common to measure large numbers of features to identify those differing between experimental conditions; for example using RNA-Seq to search for differentially expressed genes. Ranking by p-value allows for statistical control, but has well known issues: unreliability without many replicates; and significance of biologically irrelevant effect sizes. As a result prioritization is typically performed in conjunction with effect size; the canonical one being “fold-change” . However fold-change has several issues: division by zero, sensitivity to small values in the denominator, insensitivity to magnitude (1 over 2 equals 100 over 200). To mitigate these problems adding 1 to all values is a widely used heuristic; which we show using real and simulated data is typically highly sub-optimal, while the value 20 is nearly optimal in all cases. From another point of view, adding a fixed “pseudocount” to all values is essentially re-defining effect size from fold-change to something else. To explore this further, we axiomatize the concept of effect size and use this mathematical framework to study the problem in general. We also present the remarkable finding that pseudocounts strike a balance between sorting by fold-change and sorting by difference. Therefore, optimization is equivalent to finding the most harmonious balance between these two extremes. Lastly, the framework is illustrated on a fundamentally different type of problem, that of ranking di-codons by their differential abundance in the ORFeome of different species, where p-values are unavailable and one must solve the problem directly with effect sizes.
DNA Methylation Signatures of a Large Cohort Monozygotic Twins Clinically Discordant for Multiple Sclerosis
Authors: Souren Nicole Y. , Gerdes Lisa A. , Lutsik Pavlo , Gasparoni Gilles , Beltran Eduardo , Salhab Abdulrahman , Kümpfel Tania , Weichenhan Dieter , Plass Christoph , Hohlfeld Reinhard , Walter Jörn 
Published: August 2018

AbstractMultiple sclerosis (MS) is an inflammatory demyelinating disease of the central nervous system with a modest concordance rate in monozygotic twins that strongly argues for involvement of epigenetic factors. We observe in 45 MS discordant monozygotic twins highly similar peripheral blood mononuclear cell-based methylomes. However, a few MS-associated differentially methylated positions (DMP) were identified and validated, including a region in theTMEM232promoter andZBTB16enhancer. In CD4+ T cells we observed an MS-associated differentially methylated region inFIRRE.In addition, many regions showed large methylation differences in individual pairs, but were not clearly associated with MS. Furthermore, epigenetic biomarkers for current interferon-beta treatment were identified, and extensive validation revealed theZBTB16DMP as a signature of prior glucocorticoid treatment. Altogether, our study represents an important reference for epigenomic MS studies. It identifies new candidate epigenetic markers, highlights treatment effects and genetic background as major confounders, and argues against some previously reported MS-associated epigenetic candidates.
Genetic and phenotypic differentiation of lumpfish (Cyclopterus lumpus) across the North Atlantic: implications for conservation and aquaculture
Authors: Whittaker Benjamin Alexander , Consuegra Sofia , Garcia de Leaniz Carlos 
Published: August 2018

ABSTRACTDemand for lumpfish (Cyclopterus lumpus) has increased exponentially over the last decade, both for their roe, which is used as a caviar substitute, and increasingly also as cleaner fish to control sea lice in salmon farming. The species is classified as Near Threatened by the UICN and there are growing concerns that over-exploitation of wild stocks and translocation of hatchery-reared lumpfish may compromise the genetic diversity of native populations. We carried a comparative analysis of genetic and phenotypic variation across the species’ range to estimate the level of genetic and phenotypic differentiation, and determined patterns of gene flow at spatial scales relevant to management. We found five genetically distinct groups located in the West Atlantic (USA, and Canada), Mid Atlantic (Iceland), East Atlantic (Faroe Islands, Ireland, Scotland, Norway, and Denmark), English Channel (England) and Baltic Sea (Sweden). Significant phenotypic differences were also found, with Baltic lumpfish growing more slowly, attaining a higher condition factor and maturing at a smaller size than North Atlantic lumpfish. Estimates of effective population size were consistently low across the NE Atlantic (Iceland, Faroe Islands, Norway), the area where most wild lumpfish are fished for their roe, and also for the aquaculture industry. Our study suggests that some lumpfish populations are very small and have low genetic diversity, which makes them particularly vulnerable to over-exploitation and genetic introgression. To protect them we advocate curtailing fishing effort, closing the breeding cycle of the species in captivity to reduce dependence on wild stocks, restricting the translocation of genetically distinct populations, and limiting the risk of farm escapes.
Universal cancer tasks, evolutionary tradeoffs, and the functions of driver mutations
Authors: Hausser Jean , Szekely Pablo , Bar Noam , Zimmer Anat , Sheftel Hila , Caldas Carlos , Alon Uri 
Published: August 2018

AbstractRecent advances have led to an appreciation of the vast molecular diversity of cancer. Detailed data has enabled powerful methods to sort tumors into groups with benefits for prognosis and treatment. We are still missing, however, a general theoretical framework to understand the diversity of tumor gene-expression and mutations. To address this, we present a framework based on multi-task evolution theory, using the fact that tumors evolve in the body, and that tumors are faced with multiple tasks that contribute to their fitness. In accordance with the theory, we find that tradeoff between tasks constrains tumor gene-expression to a continuum bounded by a polyhedron. The vertices of the polyhedron are gene-expression profiles each specializing in one task, allowing the tasks to be identified. We find five universal cancer tasks across tissue-types: cell-division, biomass & energy, lipogenesis, immune-interaction and invasion & tissue remodeling. Tumors whose gene-expression lies close to a vertex are task specialists. We find evidence that such specialists are more sensitive to drugs that interfere with this task. We find that driver mutations, but not passenger mutations, tune gene-expression towards specialization in specific tasks. This approach can integrate additional types of molecular data into a theoretically-based framework for understanding tumor diversity.
The role of control region mitochondrial DNA mutations in cardiovascular disease: stroke and myocardial infarction
Authors: Umbria Miriam , Ramos Amanda , Aluja Maria Pilar , Santos Cristina 
Published: August 2018

AbstractRecent studies associated certain type of cardiovascular disease (CVD) with specific mitochondrial DNA (mtDNA) defects, mainly driven by the central role of mitochondria in cellular metabolism. Considering the importance of the control region (CR) on the regulation of the mtDNA gene expression, the aim of the present study was to investigate the role of the mtDNA CR mutations in two CVDs: stroke and myocardial infarction (MI). Both, fixed and heteroplasmy mutations of the mtDNA CR in two population samples of demographically-matched case and controls, were analysed using 154 stroke cases, 211 MI cases and their corresponding control individuals. Significant differences were found between cases and controls, reporting the m.16145G>A and m.16311T>C as a potential genetic risk factors for stroke (conditional logistic regression: p=0.038 and p=0.018, respectively), whereas the m.72T>C, m.73A>G and m.16356T>C could act as possible beneficial genetic factors for MI (conditional logistic regression: p=0.001, p=0.009 and p=0.016, respectively). Furthermore, our findings also showed a high percentage of point heteroplasmy in MI controls (logistic regression: p=0.046; OR= 0.209, 95% CI [0.045-0.972]). These results demonstrate the possible role of mtDNA mutations in the CR on the pathogenesis of stroke and MI, and show the importance of including this regulatory region in genetic association studies.Author SummaryGiven the association between cardiovascular disease and specific mitochondrial DNA (mtDNA) defects and considering the importance of the control region of this genome on the regulation of mtDNA gene expression, here, we investigate the role of mutations in mitochondrial DNA control region in two cardiovascular diseases: stroke and myocardial infarction. In this study we found five mitochondrial genetic variants related to cardiovascular disease, based on single nucleotide polymorphisms (SNPs), which are located in the control region of mtDNA. Despite the abundance of work on the role of mitochondrial DNA in relation to cardiovascular disease, little literature has been published on the variation that this genome expresses in relation to this disease. For this reason, our study provides significant insight of the genetic variability that determines normality or pathology in relation to the genetic risk of cardiovascular disease. The results obtained demonstrate the possible role of mtDNA mutations in the control region on the pathogenesis of stroke and myocardial infarction, and show the importance of including this regulatory region in genetic association studies.
Exploring the prediction of emotional valence and pharmacologic effect across fMRI studies of antidepressants
Authors: Barron Daniel , Salehi Mehraveh , Browning Michael , Harmer Catherine J , Constable R. Todd , Duff Eugene 
Published: August 2018

ABSTRACTBackgroundClinically approved antidepressants modulate the brain’s emotional valence circuits, suggesting that the response of these circuits could serve as a biomarker for screening candidate antidepressant drugs. However, it is necessary that these modulations can be reliably detected. Here, we apply a cross-validated predictive model to classify emotional valence and pharmacologic effect across eleven task-based fMRI datasets (n=306) exploring the effect of antidepressant administration on emotional face processing.MethodsWe created subject-level contrast of parameter estimates of the emotional faces task and used the Shen whole-brain parcellation scheme to define 268 subject-level features that trained a cross-validated gradient-boosting machine protocol to classify emotional valence (fearful vs happy face visual conditions) and pharmacologic effect (drug vs placebo administration) within and across studies.ResultsWe found patterns of brain activity that classify emotional valence with a statistically significant level of accuracy (70% across-all-subjects; range from 50-87% across-study). Our classifier failed to consistently discriminate drug from placebo. Subject population (healthy or unhealthy), treatment group (drug or placebo), and drug administration protocol (dose and duration) affected this accuracy with similar populations better predicting one another.ConclusionsWe found limited evidence that antidepressants modulated brain response in a consistent manner, however found a consistent signature for emotional valence. Variable functional patterns across studies suggest that predictive modeling can inform biomarker development in mental health and in pharmacotherapy development. Our results suggest that case-controlled designs and more standardized protocols are required for functional imaging to provide robust biomarkers for drug development.
Multifaceted integration - memory for faces is subserved by widespread connections between visual, memory, social and auditory networks
Authors: Ramot Michal , Walsh Catherine , Martin Alex 
Published: August 2018

AbstractFace memory abilities are at the core of human social interaction, yet these vary widely within the general population, ranging from developmental prosopagnosia to “super-recognizers”. Previous work has focused mainly on the contribution of the well described face network to this variance. However, given the nature of the face memory task, and the social context in which it takes place, we were interested in exploring how the collaboration between different networks outside the face network (measured through resting state connectivity) affects performance on face memory tasks. We discovered that face recognition memory is supported by a wide network of connections between the face patches, memory regions, auditory regions and social networks. Moreover, this network was selective for memory for faces, and did not predict memory for other visual objects, such as cars.
Elysium: RNA-seq Alignment in the Cloud
Authors: Lachmann Alexander , Xie Zhuorui , Ma’ayan Avi 
Published: August 2018

MotivationRNA-sequencing (RNA-seq) is currently the leading technology for genome-wide transcript quantification. Mapping the raw reads to transcript and gene level counts can be achieved by a variety of aligners and pipelines. The diversity of processing options reduces interoperability. In addition, the alignment step requires significant computational resources and basic programming knowledge. Elysium enables users of all skill levels to perform a uniform and free RNA-seq alignment in the cloud.ResultsThe Elysium infrastructure is comprised of four components: A file upload API that enables storage of FASTQ files on Amazon S3 without Amazon credentials; an API to handle the cloud alignment job scheduling for uploaded files; and a graphical user interface (GUI) to provide intuitive access to users that do not have command-line access skills.AvailabilityThe Elysium source code is available under the Apache Licence 2.0 on GitHub at: https://github.com/maayanlab/elysiumThe service of cloud based RNA-seq alignment is freely accessible through the Elysium GUI at: http://elysium.cloud
Density-dependent resistance protectsLegionella pneumophilafrom its own antimicrobial metabolite, HGA
Authors: Levin Tera C. , Goldspiel Brian P. , Malik Harmit S. 
Published: August 2018

AbstractTo persist in the extracellular state, the bacterial pathogenLegionella pneumophilamust withstand competition from neighboring bacteria. Here, we find thatL. pneumophilacan antagonize the growth of neighboringLegionellaspecies using a secreted inhibitor: HGA (homogentisic acid), the unstable, redox-active precursor molecule toL. pneumophila’s brown-black pigment. Unexpectedly, we find thatL. pneumophilacan itself be inhibited by HGA secreted from neighboring, isogenic strains. Our genetic approaches further identifylpg1681as a gene that modulatesL. pneumophilasusceptibility to HGA. We find thatL. pneumophilasensitivity to HGA is density-dependent and cell intrinsic. This resistance is not mediated by the stringent response nor the previously describedLegionellaquorum-sensing pathway. Instead, we find thatL. pneumophilacells secrete HGA only when they are conditionally HGA-resistant, which allows these bacteria to produce a potentially self-toxic molecule while restricting the opportunity for self-harm. We speculate that establishedLegionellacommunities may deploy molecules such as HGA as an unusual public good that can protect against invasion by low-density competitors.
ShinyAIM: Shiny-based Application of Interactive Manhattan Plots for Longitudinal Genome-Wide Association Studies
Authors: Hussain Waseem , Campbell Malachy , Walia Harkamal , Morota Gota 
Published: August 2018

AbstractDue to advancements in sensor-based, non-destructive phenotyping platforms, researchers are increasingly collecting data with higher temporal resolution. These phenotypes collected over several time points are cataloged as longitudinal traits and used for genome-wide association studies (GWAS). Longitudinal GWAS typically yield a large number of output files, posing a significant challenge for data interpretation and visualization. Efficient, dynamic, and integrative data visualization tools are essential for the interpretation of longitudinal GWAS results for biologists but are not widely available to the community. We have developed a flexible and user-friendly Shiny-based online application, ShinyAIM, to dynamically view and interpret temporal GWAS results. The main features of the application include (i) an interactive Manhattan plots for single time points, (ii) a grid plot to view Manhattan plots for all time points simultaneously, (iii) dynamic scatter plots for p-value-filtered selected markers to investigate co-localized genomic regions across time points, (iv) and interactive phenotypic data visualization to capture variation and trends in phenotypes. The application is written entirely in the R language and can be used with limited programming experience. ShinyAIM is deployed online as a Shiny web server application at https://chikudaisei.shinyapps.io/shinyaim/, enabling easy access for users without installation. The application can also be launched on the local machine in RStudio.