bluuebunny/crossref_metadata_2025_split huggingface dataset:
Economic aspects of the deployment of fusion energy: the valley of death and the innovation cycle
Authors: Cardozo N. J. Lopes 
Published: February 2019

The speed at which fusion energy can be deployed is considered. Several economical factors are identified that impede this speed. Most importantly, the combination of an unprecedentedly high investment level needed for the proof of principle and the relatively long construction time of fusion plants precludes an effective innovation cycle. The valley of death is discussed, i.e. the period when a large investment is needed for the construction of early generations of fusion reactors, when there is no return yet. It is concluded that, within the mainstream scenario—a few DEMO reactors towards 2060 followed by generations of relatively large reactors—there is no realistic path to an appreciable contribution to the energy mix in the twenty-first century if economic constraints are applied. In other words, fusion will not contribute to the energy transition in the time frame of the Paris climate agreement. Within the frame of this analysis, the development of smaller, cheaper and most importantly, fast-to-build fusion plants could possibly represent an option to accelerate the introduction of fusion power. Whether this is possible is a technical question that is outside the scope of this paper, but this question is addressed in other contributions to the Royal Society workshop.
This article is part of a discussion meeting issue ‘Fusion energy using tokamaks: can development be accelerated?’.
Internalization of erythrocyte acylpeptide hydrolase is required for asexual replication ofPlasmodium falciparum
Authors: Elahi Rubayet , Dapper Christie , Klemba Michael 
Published: February 2019

ABSTRACTThe human malaria parasitePlasmodium falciparumcauses disease as it replicates within the host’s erythrocytes. We have found that an erythrocyte serine hydrolase, acylpeptide hydrolase (APEH), accumulates within developing asexual parasites. Internalization of APEH was associated with a proteolytic event that reduced the size of the catalytic polypeptide from 80 to 55 kDa, which suggests that the enzyme resides in the food vacuole. A triazole urea APEH inhibitor, termed AA74-1, was employed to characterize the role of parasite-internalized APEH.In vitro, AA74-1 was a potent and highly selective inhibitor of both host erythrocyte and parasite-internalized APEH. When added to cultures of parasite-infected erythrocytes, AA74-1 was a relatively poor inhibitor of replication over one asexual replication cycle; however, its potency increased dramatically after a second cycle. This enhancement of potency was not abrogated by the addition of exogenous isopentenyl pyrophosphate, which distinguishes it from the well-characterized “delayed death” phenomenon that is observed with inhibitors that target the parasite apicoplast. Analysis of inhibition by AA74-1in vivorevealed that a concentration of 100 nM was sufficient to quantitatively inhibit erythrocyte APEH. In contrast, the parasite-internalized APEH pool was inefficiently inhibited at concentrations up to 100-fold higher. Together, these findings provide evidence for an essential catalytic role for parasite-internalized APEH and suggest a model for AA74-1 growth inhibition whereby depletion of parasite APEH activity requires the internalization of inactive host cell APEH over two replication cycles.IMPORTANCENearly half a million deaths were attributed to malaria in 2017. Protozoan parasites of the genusPlasmodiumcause disease in humans while replicating asexually within the host’s erythrocytes, withP. falciparumresponsible for most of the mortality. Understanding howPlasmodiumspp. has adapted to its unique host erythrocyte environment is important for developing malaria control strategies. Here, we demonstrate thatP. falciparumco-opts a host erythrocyte serine hydrolase termed acylpeptide hydrolase. By showing that the parasite requires acylpeptide hydrolase activity for replication, we expand our knowledge of host cell factors that contribute to robust parasite growth.
Formal axioms in biomedical ontologies improve analysis and interpretation of associated data
Authors: Smaili Fatima Zohra , Gao Xin , Hoehndorf Robert 
Published: February 2019

AbstractMotivationThere are now over 500 ontologies in the life sciences. Over the past years, significant resources have been invested into formalizing these biomedical ontologies. Formal axioms in ontologies have been developed and used to detect and ensure ontology consistency, find unsatisfiable classes, improve interoperability, guide ontology extension through the application of axiom-based design patterns, and encode domain background knowledge. At the same time, ontologies have extended their amount of human-readable information such as labels and definitions as well as other meta-data. As a consequence, biomedical ontologies now form large formalized domain knowledge bases and have a potential to improve ontology-based data analysis by providing background knowledge and relations between biological entities that are not otherwise connected.ResultsWe evaluate the contribution of formal axioms and ontology meta-data to the ontology-based prediction of protein-protein interactions and gene–disease associations. We find that the formal axioms that have been created for the Gene Ontology and several other ontologies significantly improve ontology-based prediction models through provision of domain-specific background knowledge. Furthermore, we find that the labels, synonyms and definitions in ontologies can also provide background knowledge that may be exploited for prediction. The axioms and meta-data of different ontologies contribute in varying degrees to improving data analysis. Our results have major implications on the further development of formal knowledge bases and ontologies in the life sciences, in particular as machine learning methods are more frequently being applied. Our findings clearly motivate the need for further development, and the systematic, application-driven evaluation and improvement, of formal axioms in ontologies.Availabilityhttps://github.com/bio-ontology-research-group/tsoeContactrobert.hoehndorf@kaust.edu.sa, xin.gao@kaust.edu.sa
Profiling embryonic stem cell differentiation by MALDI-MS: development of a reproducible and robust sample preparation workflow
Authors: Heap Rachel E. , Segarra-Fas Anna , Findlay Greg M. , Trost Matthias 
Published: February 2019

ABSTRACTMALDI-TOF mass spectrometry (MS) is widely used to characterize and biotype bacterial samples, but a complimentary method for profiling of mammalian cells is still underdeveloped. Current approaches vary dramatically in their sample preparation methods and are not suitable for high-throughput studies. In this work, we present a universal workflow for mammalian cell MALDI-TOF MS analysis and apply it to distinguish ground-state naïve and differentiating mouse embryonic stem cells (mESCs), which can be used as a model for drug discovery. We employed a systematic approach testing many parameters to evaluate how efficiently and reproducibly each method extracted unique mass features from four different human cell lines. This data enabled us to develop a unique mammalian cell MALDI-TOF workflow involving a freeze-thaw cycle, methanol fixing and CHCA matrix to generate spectra that yield maximum information and are highly reproducible. We applied our optimized workflow to distinguish naïve and differentiating populations using multivariate analysis and reproducibly identifying unique features. Consequently, our MALDI-TOF MS profiling method enables identification of unique biomarkers and robust phenotyping of mESC differentiation. This method can in the future be applied to profile other cell types and expanded towards cellular MALDI-TOF MS screening assays.
Predicting educational achievement from genomic measures and socioeconomic status
Authors: von Stumm Sophie , Smith-Woolley Emily , Ayorech Ziada , McMillan Andrew , Rimfeld Kaili , Dale Philip S. , Plomin Robert 
Published: February 2019

ABSTRACTThe two best predictors of children’s educational achievement available from birth are parents’ socioeconomic status (SES) and, recently, children’s inherited DNA differences that can be aggregated in genome-wide polygenic scores (GPS). Here we chart for the first time the developmental interplay between these two predictors of educational achievement at ages 7, 11, 14 and 16 in a sample of almost 5,000 UK school children. We show that the prediction of educational achievement from both GPS and SES increases steadily throughout the school years. Using latent growth curve models, we find that GPS and SES not only predict educational achievement in the first grade but they also account for systematic changes in achievement across the school years. At the end of compulsory education at age 16, GPS and SES respectively predict 14% and 23% of the variance of educational achievement; controlling for genetic influence on SES reduces its predictive power to 16%. Analyses of the extremes of GPS and SES highlight their influence and interplay: In children who have high GPS and come from high SES families, 77% go to university, whereas 21% of children with low GPS and from low SES backgrounds attend university. We find that the effects of GPS and SES are primarily additive, suggesting that their joint impact is particularly dramatic for children at the extreme ends of the distribution.
Reconstructing and Analysing The Genome of The Last Eukaryote Common Ancestor to Better Understand the Transition from FECA to LECA
Authors: Newman David , Whelan Fiona J. , Moore Matthew , Rusilowicz Martin , McInerney James O. 
Published: February 2019

AbstractIt is still a matter of debate whether the First Eukaryote Common Ancestor (FECA) arose from the merger of an archaeal host with an alphaproteobacterium, or was a proto-eukaryote with significant eukaryotic characteristics way before endosymbiosis occurred. The Last Eukaryote Common Ancestor (LECA) as its descendant is thought to be an entity that possessed functional and cellular complexity comparable to modern organisms. The precise nature and physiology of both of these organisms has been a long-standing, unanswered question in evolutionary and cell biology. Recently, a much broader diversity of eukaryotic genomes has become available and this means we can reconstruct early eukaryote evolution with a greater deal of precision. Here, we reconstruct a hypothetical genome for LECA from modern eukaryote genomes. The constituent genes were mapped onto 454 pathways from the KEGG database covering cellular, genetic, and metabolic processes across six model species to provide functional insights into it’s capabilities. We reconstruct a LECA that was a facultatively anaerobic, single-celled organism, similar to a modern Protist possessing complex predatory and sexual behaviour. We go on to examine how much of these capabilities arose along the FECA-to-LECA transition period. We see a at least 1,554 genes gained by FECA during this evolutionary period with extensive remodelling of pathways relating to lipid metabolism, cellular processes, genetic information processing, protein processing, and signalling. We extracted the BRITE classifications for the genes from the KEGG database, which arose during the transition from FECA-to-LECA and examine the types of genes that saw the most gains and what novel classifications were introduced. Two-thirds of our reconstructed LECA genome appears to be prokaryote in origin and the remaining third consists of genes with functional classifications that originate from prokaryote homologs in our LECA genome. Signal transduction and Post Translational Modification elements stand out as the primary novel classes of genes developed during this period. These results suggest that largely the eukaryote common ancestors achieved the defining characteristics of modern eukaryotes by primarily expanding on prokaryote biology and gene families.
Assessment of the effects of aerobic fitness on cerebrovascular function in young adults using multiple inversion time arterial spin labelling MRI
Authors: Foster Catherine , Steventon Jessica J , Helme Daniel , Tomassini Valentina , Wise Richard G. 
Published: February 2019

AbstractThe cross-sectional study investigated the effects of aerobic fitness on cerebrovascular function in the healthy brain. We quantified grey matter (GM) cerebral blood flow (CBF) and cerebrovascular reactivity (CVR), in a sample of young adults within a normal fitness range. Based on existing TCD and fMRI evidence, we predicted a positive relationship between fitness and resting GM CBF, and CVR. Exploratory hypotheses that higher peak would be associated with higher GM volume and cognitive performance were also investigated.20 adults underwent a peak test and a battery of cognitive tests. All subjects underwent an MRI scan where multiple inversion time (MTI) pulsed arterial spin labelling (PASL) was used to quantify resting CBF and CVR to 5% CO2.ROI analysis showed a non-significant negative correlation between whole-brain GM CBF and peak; r=-0.4, p=0.08, corrected p (p’) =0.16 and a significant positive correlation between peak and voxelwise whole-brain GM CVR; r=0.62, p=0.003, p’ =0.006. Voxelwise analysis revealed a significant inverse association between peak and resting CBF in the left and right thalamus, brainstem, right lateral occipital cortex, left intracalcarine cortex and cerebellum. The results of this study suggest that aerobic fitness is associated with lower CBF and greater CVR in young adults.
Episodic diversifying selection and intragenomic interactions shape the evolution of DNA and RNA viruses
Authors: Aris-Brosou Stéphane , Parent Louis , Ibeh Neke 
Published: February 2019

AbstractViruses are known to have some of the highest and most diverse mutation rates found in any biological replicator, topped by single-stranded (ss) RNA viruses, while double-stranded (ds) DNA viruses have rates approaching those of bacteria. As mutation rates are tightly and negatively correlated with genome size, selection is a clear driver of viral evolution. However, the role of intragenomic interactions as drivers of viral evolution is less well documented. To understand how these two processes affect viral evolution, we systematically surveyed ssRNA, ssDNA, dsRNA, and dsDNA viruses, to find which virus type and which functions show evidence for episodic diversifying selection and correlated evolution. We show that while evidence for selection is mostly found in single stranded viruses, and correlated evolution is more prevalent in DNA viruses, the genes that are affected by both processes are involved in key aspects of their life cycle, favoring viral stability over proliferation. We further show that both evolutionary processes are intimately linked at the amino acid level, which suggests that selection alone does not explain the whole evolutionary —and epidemiological— potential of viruses.
CAN TRANSCRANIAL DIRECT CURRENT STIMULATION OVER THE DORSOLATERAL PREFRONTAL CORTEX ENHANCE PROPRIOCEPTION?
Authors: Beck Eric N. , Narayanan Sankirtana Shankar , McDermott Rian , Witney Alice G. 
Published: February 2019

ABSTRACTIntroductionProprioception (perception of one’s limb position) is critical for accurate and consistent movement, and is processed by the sensorimotor cortex. Increased prefrontal activity is associated with improved proprioception and motor performance. Anodal transcranial direct current stimulation (tDCS) of the left dorsolateral prefrontal cortex (DLPFC) has been found to increase activity of the sensorimotor cortex. Thus, this study aimed to investigate whether anodal tDCS of the DLPFC may enhance proprioception measured with a target task. It was hypothesized that tDCS over the left DLPFC would improve motor performance (error and variability) on a target task completed without vision.DesignSingle blind, within-participant, sham-controlled trial.MethodsFifteen healthy young adults (M:F=6:9, age=23.3 years) completed 18 trials of a computerized target task (manipulating a mouse) with their non-dominant upper-limb, with and without vision, before and after (pre/post assessment) 20-minutes of stimulation (anodal tDCS of the left DLPFC) and sham conditions. Averages and coefficient of variation (CV, variability between trials) of spatio-temporal parameters associated with the movement were measured. Stimulation/ sham sessions were counterbalanced (stimulation first session, n=8), with each session separated by one week. Repeated-measures ANOVA and pairwise comparisons (95% confidence intervals [CI]) were conducted.ResultsRegarding distance travelled CV, a significant interaction between condition and assessment (F(1,14)=5.09, p=0.041) demonstrated that variability was significantly less post-stimulation compared to pre (p=0.003). A significant interaction between assessment and vision (F(1,14)=30.08, p<0.001) regarding distance travelled CV showed that without vision, variability was significantly less at post compared to pre (p<0.001), and this decrease was found after the stimulation condition only (95% CI = Δ 7.4 +/− 1.6 [4.0 to 10.9]).ConclusionSince variability of distance travelled during the target task without vision was lower post-stimulation compared to pre, consistency of movement without vision, and therefore proprioception, may have been enhanced by anodal tDCS of the DLPFC. This improvement could be due to modulation of fronto-striatal-thalamic circuits. These findings may be the first step in developing tDCS methods as an effective adjunct therapy for dysfunctional proprioception in various disorders, such as Parkinson’s disease.
Ecological origins of perceptual grouping principles in the auditory system
Authors: Młynarski Wiktor , McDermott Josh H. 
Published: February 2019

AbstractEvents and objects in the world must be inferred from sensory signals to support behavior. Because sensory measurements are temporally and spatially local, the estimation of an object or event can be viewed as the grouping of these measurements into representations of their common causes. Per-ceptual grouping is believed to reflect internalized regularities of the natural environment, yet grouping cues have traditionally been identified using informal observation, and investigated using artificial stim-uli. The relationship of grouping to natural signal statistics has thus remained unclear, and additional or alternative cues remain possible. Here we derive auditory grouping cues by measuring and summarizing statistics of natural sound features. Feature co-occurrence statistics reproduced established cues but also revealed previously unappreciated grouping principles. The results suggest that auditory grouping is adapted to natural stimulus statistics, show how these statistics can reveal novel grouping phenomena, and provide a framework for studying grouping in natural signals.
Scalable and Accurate Drug–target Prediction Based on Heterogeneous Bio-linked Network Mining
Authors: Zong Nansu , Wong Rachael Sze Nga , Ngo Victoria , Yu Yue , Li Ning 
Published: February 2019

AbstractMotivationDespite the existing classification- and inference-based machine learning methods that show promising results in drug-target prediction, these methods possess inevitable limitations, where: 1) results are often biased as it lacks negative samples in the classification-based methods, and 2) novel drug-target associations with new (or isolated) drugs/targets cannot be explored by inference-based methods. As big data continues to boom, there is a need to study a scalable, robust, and accurate solution that can process large heterogeneous datasets and yield valuable predictions.ResultsWe introduce a drug-target prediction method that improved our previously proposed method from the three aspects: 1) we constructed a heterogeneous network which incorporates 12 repositories and includes 7 types of biomedical entities (#20,119 entities, # 194,296 associations), 2) we enhanced the feature learning method with Node2Vec, a scalable state-of-art feature learning method, 3) we integrate the originally proposed inference-based model with a classification model, which is further fine-tuned by a negative sample selection algorithm. The proposed method shows a better result for drug–target association prediction: 95.3% AUC ROC score compared to the existing methods in the 10-fold cross-validation tests. We studied the biased learning/testing in the network-based pairwise prediction, and conclude a best training strategy. Finally, we conducted a disease specific prediction task based on 20 diseases. New drug-target associations were successfully predicted with AUC ROC in average, 97.2% (validated based on the DrugBank 5.1.0). The experiments showed the reliability of the proposed method in predicting novel drug-target associations for the disease treatment.
Hallucinations both in and out of context: An Active Inference Account
Authors: Benrimoh David , Parr Thomas , Adams Rick A. , Friston Karl 
Published: February 2019

ABSTRACTHallucinations, including auditory verbal hallucinations (AVH), occur in both the healthy population and in psychotic conditions such as schizophrenia (often developing after a prodromal period). In addition, hallucinations can be in-context (they can be consistent with the environment, such as when one hallucinates the end of a sentence that has been repeated many times), or out-of-context (such as the bizarre hallucinations associated with schizophrenia). In previous work, we introduced a model of hallucinations as false (positive) inferences based on a (Markov decision process) formulation of active inference. In this work, we extend this model to include content – to disclose the computational mechanisms behind in- and out-of-context hallucinations. In active inference, sensory information is used to disambiguate alternative hypotheses about the causes of sensations. Sensory information is balanced against prior beliefs, and when this balance is tipped in the favor of prior beliefs, hallucinations can occur. We show that in-context hallucinations arise when (simulated) subjects cannot use sensory information to correct prior beliefs about hearing a voice, but beliefs about content (i.e. the sequential order of a sentence) remain accurate. When hallucinating subjects also have inaccurate beliefs about state transitions, out-of-context hallucinations occur; i.e. their hallucinated speech content is disordered. Furthermore, subjects with inaccurate beliefs about state transitions but an intact ability to use sensory information do not hallucinate and are reminiscent of prodromal patients. This work demonstrates the different computational mechanisms that may underlie the spectrum of hallucinatory experience – from the healthy population to psychotic states.