bluuebunny/crossref_metadata_2025_split huggingface dataset:
A single-cell RNA-seq Training and Analysis Suite using the Galaxy Framework
Authors: Tekman Mehmet , Batut Bérénice , Ostrovsky Alexander , Antoniewski Christophe , Clements Dave , Ramirez Fidel , Etherington Graham J , Hotz Hans-Rudolf , Scholtalbers Jelle , Manning Jonathan R , Bellenger Lea , Doyle Maria A , Heydarian Mohammad , Huang Ni , Soranzo Nicola , Moreno Pablo , Mautner Stefan , Papatheodorou Irene , Nekrutenko Anton , Taylor James , Blankenberg Daniel , Backofen Rolf , Grüning Björn 
Published: June 2020

AbstractBackgroundThe vast ecosystem of single-cell RNA-seq tools has until recently been plagued by an excess of diverging analysis strategies, inconsistent file formats, and compatibility issues between different software suites. The uptake of 10x Genomics datasets has begun to calm this diversity, and the bioinformatics community leans once more towards the large computing requirements and the statistically-driven methods needed to process and understand these ever-growing datasets.ResultsHere we outline several Galaxy workflows and learning resources for scRNA-seq, with the aim of providing a comprehensive analysis environment paired with a thorough user learning experience that bridges the knowledge gap between the computational methods and the underlying cell biology. The Galaxy reproducible bioinformatics framework provides tools, workflows and trainings that not only enable users to perform one-click 10x preprocessing, but also empowers them to demultiplex raw sequencing from custom tagged and full-length sequencing protocols. The downstream analysis supports a wide range of high-quality interoperable suites separated into common stages of analysis: inspection, filtering, normalization, confounder removal and clustering. The teaching resources cover an assortment of different concepts from computer science to cell biology. Access to all resources is provided at thesinglecell.usegalaxy.euportal.ConclusionsThe reproducible and training-oriented Galaxy framework provides a sustainable HPC environment for users to run flexible analyses on both 10x and alternative platforms. The tutorials from the Galaxy Training Network along with the frequent training workshops hosted by the Galaxy Community provide a means for users to learn, publish and teach scRNA-seq analysis.Key PointsSingle-cell RNA-seq has stabilised towards 10x Genomics datasets.Galaxy provides rich and reproducible scRNA-seq workflows with a wide range of robust tools.The Galaxy Training Network provides tutorials for the processing of both 10x and non-10x datasets.
The Impact of Restriction-Modification Systems on Mating inHaloferax volcanii
Authors: Ouellette Matthew , Makkay Andrea M. , Louyakis Artemis S. , Gophna Uri , Gogarten J. Peter , Papke R. Thane 
Published: June 2020

AbstractHalobacteria have been observed to be highly recombinogenic, frequently exchanging genetic material. Several barriers to mating in the Halobacteria have been examined, such as CRISPR-Cas, glycosylation, and archaeosortases, but these are low barriers that do not drastically reduce the recombination frequency. Another potential barrier could be restriction-modification (RM) systems, which cleave DNA that is not properly methylated, thus limiting the exchange of genetic material between cells which do not have compatible RM systems. In order to examine the role of RM systems on limiting recombination in the Halobacteria, the impact of RM systems on cell-to-cell mating inHaloferax volcanii, a well-characterized method of genetic exchange and recombination in a halobacterial species, was examined. Strains which possessed all naturally-occurring RM system genes inH. volcanii(RM+) and strains without these RM systems (ΔRM) were mated together to compare the efficiency of gene transfer between RM-compatible strains and RM-incompatible strains. The results indicated that mating RM-incompatible strains together resulted in a decrease in gene transfer efficiency compared to mating RM-compatible strains together, suggesting that RM systems limit mating inH. volcanii, but do not act as absolute barriers to recombination. Therefore, RM systems are low barriers to recombination in the Halobacteria, with RM-incompatible strains exchanging genetic material at a lower frequency than those with compatible RM systems, similar to other low recombination barriers in the Halobacteria.
Unique molecular characteristics of visceral afferents arising from different levels of the neuraxis: location of afferent somata predicts function and stimulus detection modalities
Authors: Meerschaert Kimberly A. , Adelman Peter C. , Friedman Robert L. , Albers Kathryn M. , Koerber H. R. , Davis Brian M. 
Published: June 2020

AbstractVisceral organs receive neural innervation from sensory ganglia located adjacent to multiple levels of the brainstem and spinal cord. Here we examined whether molecular profiling could be used to identify functional clusters of colon afferents from thoracolumbar (TL), lumbosacral (LS), and nodose ganglia (NG) in the mouse. Profiling of TL and LS bladder afferents was also done. Visceral afferents were back-labeled using retrograde tracers injected into proximal and distal regions of colon or bladder, followed by single cell RT-qPCR and analysis via an automated hierarchical clustering method. Genes were chosen for assay (32 for bladder; 48 for colon) based on their established role in stimulus detection, regulation of sensitivity/function or neuroimmune interaction. A total of 132 colon afferents (from NG, TL and LS) and 128 bladder afferents (from TL and LS) were analyzed. Retrograde labeling from the colon showed NG and TL afferents innervate proximal and distal regions of the colon whereas 98% of LS afferents only project to distal regions. There were clusters of colon and bladder afferents, defined by mRNA profiling, that localized to either TL or LS ganglia. Mixed TL/LS clustering also was found. In addition, transcriptionally, NG colon afferents were almost completely segregated from colon DRG (TL or LS) neurons. These results indicate that populations of primary visceral afferents are functionally “tuned” to detect and interact with the internal environment and that information from all levels is integrated at higher (CNS) levels, not only for regulation of homeostatic functions, but for conscious visceral sensations including pain.Significance StatementVisceral organs are innervated by sensory neurons whose cell bodies are located in multiple ganglia associated with the brainstem and spinal cord. For the colon, this overlapping innervation is proposed to facilitate visceral sensation and homeostasis, where sensation and pain is mediated by spinal afferents and fear and anxiety (the affective aspects of visceral pain) are the domain of nodose afferents. Transcriptomic analysis performed here reveals that genes implicated in both homeostatic regulation and pain are found in afferents across all ganglia types, suggesting that conscious sensation and homeostatic regulation is the result of convergence, and not segregation, of sensory input.
Spontaneous variability predicts adaptive motor response in vocal pitch control
Authors: Tachibana Ryosuke O. , Xu Mingdi , Hashimoto Ryu-ichiro , Homae Fumitaka , Okanoya Kazuo 
Published: June 2020

AbstractOur motor system uses sensory feedback to keep behavioral performance in desired status. From this view, motor fluctuation is not simply ‘noise’ inevitably caused in the nervous system, but should provide a role in generating variations to explore better outcomes via their sensory feedback. Vocal control system offers a good model to investigate such adaptive sensory-motor interactions. The pitch, or fundamental frequency (FF), of voice is adaptively regulated by hearing its auditory feedback to compensate FF deviations. Animal studies, particularly for songbirds, have demonstrated that the variability in vocal features contributes to the adaptive control, although the same issue in human vocalizations has remained unclear. Here, we tested whether and how the motor variability contributes to adaptive control of vocal FF in humans. We measured the amount of compensatory vocal responses against FF shifts in the auditory feedback, and quantified the motor variability as amplitudes of spontaneous FF fluctuations during no shift vocalizations. The result showed a positive correlation between the ratio of compensation and the spontaneous vocal variability. Further analysis indicated that this correlation was due to slowly fluctuating components (<5 Hz) of the variability, but not fast fluctuations (6-30 Hz), which is likely to reflect controllability from the central nervous system. Moreover, the compensatory responses consisted of the same frequency range with the slow component in the spontaneous variability. These findings consistently demonstrated that the spontaneous motor variability predicts the adaptive control in vocal FF, supporting the motor exploration hypothesis.Significance statementWe regulate our own vocalization by hearing own voice. This fact is typically observed as canceling-out (compensatory) responses in vocalized pitch when artificial pitch shifts were induced in the auditory feedback of own voice. Interestingly, the amount of such compensation widely ranges among talkers from perfect cancellation to almost nothing. Here we demonstrated that participants who spontaneously exhibited larger fluctuations showed greater amounts of the compensation against feedbacked pitch shifts. Our in-depth analyses showed that slowly fluctuating components in spontaneous pitch variability are specifically correlated with the compensation ratios, and was shared in the compensatory response as a dominant component. These findings support the idea that such variability contributes to generating motor explorations to find better outcomes in motor controls.
Female and male plumage colour is linked to parental quality, pairing and extra-pair mating in a tropical passerine
Authors: Leitão Ana V. , Hall Michelle L. , Mulder Raoul A. 
Published: June 2020

ABSTRACTSexual selection has been proposed to drive the evolution of elaborate phenotypic traits in males, which often confer success in competition or mating. However, in many species both males and females display such traits, although studies reporting selection acting in both sexes are scarce. In this study, we investigated whether plumage ornamentation is sexually selected in female and male lovely fairy-wrensMalurus amabilis,a cooperatively breeding songbird. We found that female and male plumage colour was correlated with parental quality but did not incur survival costs. We also found evidence of positive assortative mating based on plumage colour. Microsatellite analyses of paternity indicated that the lovely fairywren has high levels of extra-pair paternity, with 53% of offspring resulting from extra-pair mating. Female and male plumage colour did not predict reproductive success and female proportion of extra-pair offspring in its own nest, but less colourful males obtained higher extra-pair paternity. We argue that plumage colour may be under sex-specific selection, highlighting the importance of looking at both sexes in studies of sexual selection and ornament evolution. The current findings together with previous study, suggest that plumage colour in female and male lovely fairy-wrens appears to be an honest signal relevant in both intra and inter-sexual competition contexts.
ORN: Extracting Latent Pathway Activities in Cancer with OR-gate Network
Authors: Liang Lifan , Zhu Kunju , Lu Songjian 
Published: June 2020

ABSTRACTPathway level understanding of cancer plays a key role in precision oncology. In this study, we developed a novel data-driven model, called the OR-gate Network (ORN), to simultaneously infer functional relationships among mutations, patient-specific pathway activities, and gene co-expression. In principle, logical OR gates agree with mutual exclusivity patterns in somatic mutations and bicluster patterns in transcriptomic profiles. In a trained ORN, the differential expression profiles of tumours can be explained by somatic mutations perturbing signalling pathways. We applied ORN to lower grade glioma (LLG) samples in TCGA and breast cancer samples from METABRIC. Both datasets have shown pathway patterns related to immune response and cell cycles. In LLG samples, ORN identified multiple metabolic pathways closely related to glioma development and revealed two pathways closely related to patient survival. Additional results from the METABRIC datasets showed that ORN could characterize key mechanisms of cancer and connect them to less studied somatic mutations (e.g., BAP1, MIR604, MICAL3, and telomere activities), which may generate novel hypothesis for targeted therapy.
Drug2ways: Reasoning over causal paths in biological networks for drug discovery
Authors: Rivas-Barragan Daniel , Mubeen Sarah , Bernat Francesc Guim , Hofmann-Apitius Martin , Domingo-Fernández Daniel 
Published: June 2020

AbstractElucidating the causal mechanisms responsible for disease can reveal potential therapeutic targets for pharmacological intervention and, accordingly, guide drug repositioning and discovery. In essence, the topology of a network can reveal the impact a drug candidate may have on a given biological state, leading the way for enhanced disease characterization and the design of advanced therapies. Network-based approaches, in particular, are highly suited for these purposes as they hold the capacity to identify the molecular mechanisms underlying disease. Here, we present drug2ways, a novel methodology that leverages multimodal causal networks for predicting drug candidates. Drug2ways implements an efficient algorithm which reasons over causal paths in large-scale biological networks to propose drug candidates for a given disease. We validate our approach using clinical trial information and demonstrate how drug2ways can be used for multiple applications to identify: i) single-target drug candidates, ii) candidates with polypharmacological properties that can optimize multiple targets, and iii) candidates for combination therapy. Finally, we make drug2ways available to the scientific community as a Python package that enables conducting these applications on multiple standard network formats.
Norepinephrine as a Spatial Memory Reset Signal
Authors: Grella Stephanie L. , Gomes Sarah M. , Lackie Rachel E. , Renda Briana , Marrone Diano F. 
Published: June 2020

ABSTRACTContextual information is represented in the hippocampus (HPC) partially through the recruitment of distinct neuronal ensembles. It is believed that reactivation of these ensembles underlies memory retrieval processes. Recently, we showed that norepinephrine (NE) input from phasic locus coeruleus (LC) activation induces hippocampal plasticity resulting in the recruitment of new neurons and a disengagement from previously established representations. We hypothesize that NE may provide a neuromodulatory, mnemonic switch signaling the HPC to move from a state of retrieval to encoding in the presence of novelty, and therefore, plays a role in memory updating. Here, we tested whether bilateral dorsal dentate gyrus (DG) infusions of the β-adrenergic receptor (BAR) agonist isoproterenol (ISO), administered prior to encoding or retrieval, would impair spatial working and reference memory by reverting the system to encoding (thereby recruiting new neurons) potentially interfering with retrieval of the previously established spatial ensemble. We also investigated whether dDG infusions of ISO could promote cognitive flexibility by switching the system to encoding when it is adaptive (i.e. when new information is presented e.g. reversal learning). We found that intra-dDG infusions of ISO given prior to retrieval caused deficits in working and reference memory which was blocked by pre-treatment with the BAR-antagonist, propranolol (PRO). In contrast, ISO administered prior to reversal learning led to improved performance. These data support our hypothesis that NE serves as a novelty signal to update HPC contextual representations via BAR activation-facilitated recruitment of new neurons. This can be both maladaptive and adaptive depending on the situation.SIGNIFICANCE STATEMENTThe current work highlights the involvement of hippocampal BARs in determining the flexibility of contextual representations to promote new learning in a way that supports adaptive behavior. This work builds upon previous work showing that noradrenergic input to the hippocampus is involved in recruiting new neurons resulting in new contextual representations and may be involved in the underlying neural mechanisms that support memory updating. These data suggest targets for anxiety disorders such as PTSD, which are characterized by noradrenergic dysregulation, and may also involve impairments in memory updating mechanisms where the incorporation of new information is not effectively encoded. The further understanding of the neurobiological mechanisms involved in updating memories may provide insight into novel treatment strategies.
Temporal transcriptome profiling ofMicrochloropsis gaditanaCCMP526 under hyper-saline conditions
Authors: Karthikaichamy Anbarasu , Beardall John , Coppel Ross , Noronha Santosh , Srivastava Sanjeeva , Bulach Dieter 
Published: June 2020

ABSTRACTMicroalgae can tolerate a wide range of environmental conditions and have been exploited for their lipid and carbohydrate accumulating properties. The utility of this process could be further enhanced through understanding the critical gene regulatory networks that govern the acclimatization process. Advancements in systems biology and sequencing tools now enable us to obtain a genome-wide overview of gene expression under particular conditions of interest. Under salinity stress,Microchloropsis gaditanaCCMP526, a commercially important alga has been previously reported to accumulate carbohydrate and lipid. To understand the mechanism of acclimatization, here we report a temporal transcriptomic analysis ofM. gaditanaunder two different salinity levels (55 and 100 PSU). The short term (0, 1 and 6 h) and long term (24 and 72 h) responses of the salt-induced transcript pool were used to identify salinity-inducible genes using correspondence analysis. The transcript abundance of genes involved in triacylglycerol biosynthesis, membrane lipid modification, carbon assimilation and shunting, and osmolyte biosynthesis indicated thatM. gaditanaemploys a two-stage acclimatization strategy during hypersaline conditions.
Double Emulsion Picoreactors for High-Throughput Single-Cell Encapsulation and Phenotyping via FACS
Authors: Brower Kara K. , Khariton Margarita , Suzuki Peter H. , Still Chris , Kim Gaeun , Calhoun Suzanne G. K. , Qi Lei S. , Wang Bo , Fordyce Polly M. 
Published: June 2020

ABSTRACTIn the past five years, droplet microfluidic techniques have unlocked new opportunities for the high-throughput genome-wide analysis of single cells, transforming our understanding of cellular diversity and function. However, the field lacks an accessible method to screen and sort droplets based on cellular phenotype upstream of genetic analysis, particularly for large and complex cells. To meet this need, we developed Dropception, a robust, easy-to-use workflow for precise single-cell encapsulation into picoliter-scale double emulsion droplets compatible with high-throughput phenotyping via fluorescence-activated cell sorting (FACS). We demonstrate the capabilities of this method by encapsulating five standardized mammalian cell lines of varying size and morphology as well as a heterogeneous cell mixture of a whole dissociated flatworm (5 - 25 μm in diameter) within highly monodisperse double emulsions (35 μm in diameter). We optimize for preferential encapsulation of single cells with extremely low multiple-cell loading events (<2% of cell-containing droplets), thereby allowing direct linkage of cellular phenotype to genotype. Across all cell lines, cell loading efficiency approaches the theoretical limit with no observable bias by cell size. FACS measurements reveal the ability to discriminate empty droplets from those containing cells with good agreement to single-cell occupancies quantified via microscopy, establishing robust droplet screening at single-cell resolution. High-throughput FACS phenotyping of cellular picoreactors has the potential to shift the landscape of single-cell droplet microfluidics by expanding the repertoire of current nucleic acid droplet assays to include functional screening.ABSTRACT FIGURE
Functional and cognitive outcomes after COVID-19 delirium
Authors: Mcloughlin Benjamin C , Miles Amy , Webb Thomas , Knopp Paul , Eyres Clodagh , Fabbri Ambra , Humphries Fiona , Davis Daniel 
Published: June 2020

AbstractPurposeTo ascertain delirium prevalence and outcomes in COVID-19.MethodsWe conducted a point-prevalence study in a cohort of COVID-19 inpatients at University College Hospital. Delirium was defined by DSM-IV criteria. The primary outcome was all-cause mortality at 4 weeks; secondary outcomes were physical and cognitive function.ResultsIn 71 patients, 31 (42%) had delirium, of which only 19 had been recognised by the clinical team. At 4 weeks, 20 (28%) had died, 26 (36%) were interviewed by telephone and 21 (30%) remained as inpatients. Physical function was substantially worse in people after delirium (−39 points on functional scale/166, 95% CI −92 to −21, p=0.01) (Table 2). Mean cognitive scores at follow-up were similar and delirium was not associated with mortality in this sample.ConclusionsOur findings indicate that delirium is common, yet under-recognised. Delirium is associated with functional impairments in the medium-term.Key summary pointsAimTo investigate functional and cognitive outcomes among patients with delirium in COVID-19.FindingsDelirium in COVID-19 was prevalent (42%) but only a minority had been recognised by the clinical team. At 4-week follow-up, delirium was significantly associated with worse functional outcomes, independent of pre-morbid frailty. Cognitive outcomes were not appreciably worse.MessageThe presence of delirium is a significant factor in predicting worse functional outcomes in patients with COVID-19.
Who dies from COVID-19? Post-hoc explanations of mortality prediction models using coalitional game theory, surrogate trees, and partial dependence plots
Authors: Yang Russell 
Published: June 2020

AbstractAs of early June, 2020, approximately 7 million COVID-19 cases and 400,000 deaths have been reported. This paper examines four demographic and clinical factors (age, time to hospital, presence of chronic disease, and sex) and utilizes Shapley values from coalitional game theory and machine learning to evaluate their relative importance in predicting COVID-19 mortality. The analyses suggest that out of the 4 factors studied, age is the most important in predicting COVID-19 mortality, followed by time to hospital. Sex and presence of chronic disease were both found to be relatively unimportant, and the two global interpretation techniques differed in ranking them. Additionally, this paper creates partial dependence plots to determine and visualize the marginal effect of each factor on COVID-19 mortality and demonstrates how local interpretation of COVID-19 mortality prediction can be applicable in a clinical setting. Lastly, this paper derives clinically applicable decision rules about mortality probabilities through a parsimonious 3-split surrogate tree, demonstrating that high-accuracy COVID-19 mortality prediction can be achieved with simple, interpretable models.