bluuebunny/crossref_metadata_2025_split huggingface dataset:
Auditory brainstem models: adapting cochlear nuclei improve spatial encoding by the medial superior olive in reverberation
Authors: Brughera Andrew , Mikiel-Hunter Jason , Dietz Mathias , McAlpine David 
Published: July 2019

AbstractListeners perceive sound-energy as originating from the direction of its source, even as direct sound is followed milliseconds later by reflected sound from multiple different directions. Early-arriving sound is emphasised in the ascending auditory pathway, including the medial superior olive (MSO) where binaural neurons encode the interaural time difference (ITD) cue for spatial location. Behaviourally, weighting of ITD conveyed during rising sound-energy is stronger at 600 Hz, a frequency with higher reverberant energy, than at 200 Hz where reverberant energy is lower. Here we computationally explore the combined effectiveness of adaptation before ITD-encoding, and excitatory binaural coincidence detection within MSO neurons, in emphasising ITD conveyed in early-arriving sound. With excitatory inputs from adapting model spherical bushy cells (SBCs) of the bilateral cochlear nuclei, a Hodgkin-Huxley-type model MSO neuron reproduces the frequency-dependent emphasis of rising vs. peak sound-energy in ITD-encoding. Maintaining the adaptation in model SBCs, and adjusting membrane speed in model MSO neurons, hemispheric populations of model SBCs and MSO neurons, with simplified membranes for computational efficiency, also reproduce the stronger weighting of ITD information conveyed during rising sound-energy at 600 Hz compared to 200 Hz. This hemispheric model further demonstrates a link between strong weighting of spatial information during rising sound-energy, and correct unambiguous lateralisation of reverberant speech.
Establishment of primary transgenic human airway epithelial cell cultures to study respiratory virus – host interactions
Authors: Jonsdottir Hulda R. , Marti Sabrina , Geerts Dirk , Rodriguez Regulo , Thiel Volker , Dijkman Ronald 
Published: July 2019

AbstractPrimary human airway epithelial cell (hAEC) cultures represent a universal platform to propagate respiratory viruses and characterize their host interactions in authentic target cells. To further elucidate specific interactions between human respiratory viruses and important host factors in airway epithelium, it is important to make hAEC cultures amenable to genetic modification. However, the short and finite lifespan of primary cells in cell culture creates a bottleneck for the genetic modification of these cultures. In the current study, we show that the incorporation of the Rho-associated protein kinase (ROCK) inhibitor (Y-27632) during cell propagation extends the life span of primary human cells in vitro and thereby facilitates the incorporation of lentivirus-based expression systems. Using fluorescent reporters for FACS-based sorting, we generated homogenously fluorescent hAEC cultures that differentiate normally after lentiviral transduction. As proof-of-principle, we demonstrate that host gene expression can be modulated post-differentiation via inducible short hairpin (sh)RNA-mediated knockdown. Importantly, functional characterization of these transgenic hAEC cultures with exogenous poly(I:C), as a proxy for virus infection, demonstrates that such modifications do not influence the host innate immune response. Moreover, the propagation kinetics of both human coronavirus 229E (HCoV-229E) and human respiratory syncytial virus (RSV) were not affected. Combined, these results validate our newly established protocol for the genetic modification of hAEC cultures thereby unlocking a unique potential for detailed molecular characterization of virus – host interactions in human respiratory epithelium.
A genetic pathway encoding double-stranded RNA transporters and interactors regulates growth and plasticity inCaenorhabditis elegans
Authors: Braukmann Fabian , Jordan David , Miska Eric Alexander 
Published: July 2019

AbstractThe environment and genes shape the development, physiology and behaviour of organisms. Many animal species can take-up double-stranded RNA (dsRNA) from the environment. Environmental dsRNA changes gene expression through RNA interference (RNAi). While environmental RNAi is used as a laboratory tool, e.g. in nematodes, planaria and insects, its biological role remains enigmatic. Here we characterise the environmental dsRNA receptor SID-2 to understand the biological function of dsRNA uptake inCaenorhabditis elegans. First we determine that SID-2 localises to the apical membrane and the trans-Golgi-network (TGN) in the intestine, implicating the TGN as a central cellular compartment for environmental dsRNA uptake. We demonstrate that SID-2 is irrelevant for nucleotide uptake from the environment as a nutritional (nitrogen) source. Instead RNA profiling and high-resolution live imaging revealed a new biological function forsid-2in growth and phenotypic plasticity. Surprisingly, lack of the ability to uptake environmental RNA reduces plasticity of gene expression. Furthermore, using genetic analyses we show that the dsRNA pathway genessid-2, sid-1andrde-4together regulate growth. This work suggest that environmental RNA affects morphology and plasticity through gene regulation.
Activity of epigenetic inhibitors against Plasmodium falciparum asexual and sexual blood stages
Authors: Vanheer Leen , Kafsack Björn F.C. 
Published: July 2019

AbstractRegulation of gene expression by epigenetic processes is critical for malaria parasite survival in multiple life stages. To evaluate the suitability of targeting these pathways we screened 350 epigenetic inhibitors against asexual blood stages and gametocytes of P. falciparum. We observed ≥90% inhibition at 10 µM for 28% of compounds, of which a third retained ≥90% inhibition at 1 µM. These results suggest epigenetic regulation as a promising target for the development of new multi-stage anti-malarials.
Explicit strategies in force field adaptation
Authors: Schween Raphael , McDougle Samuel D. , Hegele Mathias , Taylor Jordan A. 
Published: July 2019

AbstractIn recent years, it has become increasingly clear that a number of learning processes are at play in visuomotor adaptation tasks. In addition to the presumed formation of an internal model of the perturbation, learners can also develop explicit knowledge allowing them to select better actions in responding to a given perturbation. Advances in visuomotor rotation experiments have underscored the important role that such “explicit learning” plays in shaping adaptation to kinematic perturbations. Yet, in adaptation to dynamic perturbations, its contribution has been largely overlooked, potentially because compensation of a viscous force field, for instance, is difficult to assess by commonly-used verbalization-based approaches. We therefore sought to assess the contribution of explicit learning in learners adapting to a dynamic perturbation by two novel modifications of a force field experiment. First, via an elimination approach, we asked learners to abandon any cognitive strategy before selected force channel trials to expose consciously accessible parts of overall learning. Learners indeed reduced compensatory force compared to standard Catch channels. Second, via a manual reporting approach, we instructed a group of learners to mimic their right hand’s adaptation by moving with their naïve left hand. While a control group displayed negligible left-hand force compensation, the Mimic group reported forces that approximated right-hand adaptation but appeared to under-report the velocity component of the force field in favor of a more position-based component. We take these results to clearly demonstrate the contribution of explicit learning to force adaptation, underscoring its relevance to motor learning in general.New & NoteworthyWhile the role of explicit learning has recently been appreciated in visuomotor adaptation tasks, their contribution to force field adaptation has not been as widely acknowledged. To address this issue, we employed two novel methods to assay explicit learning in force field adaptation tasks and found that learners can voluntarily control aspects of force production and manually report them with their untrained limb. This suggests that an explicit component contributes to force field adaptation and may provide alternative explanations to behavioral phenomena commonly thought to reveal a complex organization of internal models in the brain.
Development of a PC12 cell-based assay forin vitroscreening of catechol-O-methyltransferase inhibitors
Authors: Zhang Gongliang , Buchler Ingrid P. , DePasquale Michael , Wormald Michael , Liao Gangling , Wei Huijun , Barrow James C. , Carr Gregory V. 
Published: July 2019

ABSTRACTThe male rat adrenal pheochromocytoma cell-originated PC12 cell line can synthesize and release catecholamine neurotransmitters, and it has been widely used as a model system in cell biology and toxicology research. Catechol-O-methyltransferase (COMT) is involved in the inactivation of the catecholamine neurotransmitters, and it is particularly important for theregulation of dopamine. In this study, we explored the feasibility of using PC12 cells as anin vitrodrug screening platform to compare the activity of multiple COMT inhibitors. Incubation of PC12 cells with tolcapone, a highly potent and selective COMT inhibitor, increased the concentrations of dopamine and its metabolite 3,4-dihydroxyphenylacetic acid (DOPAC) while reducing the metabolites 3-methoxytyramine (3-MT) and homovanillic acid (HVA) in the cell culture medium. LIBD-3, a novel, non-nitrocatechol COMT inhibitor produced similar effects compared to tolcapone. LIBD-4, a less potent inhibitor, exhibited the expected right-shift in functional inhibition in the assay. These results match the knownin vivoeffects of COMT inhibition in rodents. Together, these data support the continued use of PC12 cells as anin vitroscreen that bridges cell-free enzyme assays and more costlyin vivoassays.
Visualizing the periodic Ribo-seq reads with RiboPlotR
Authors: Wu Hsin-Yen Larry , Hsu Polly Yingshan 
Published: July 2019

ABSTRACTBackgroundRibo-seq has revolutionized the study of mRNA translation in a genome-wide scale. High-quality Ribo-seq data display strong 3-nucleotide (nt) periodicity, which corresponds to translating ribosomes decipher three nucleotides each time. While the 3-nt periodicity has been widely used to study novel translation events and identify small open reading frames on presumed non-coding RNAs, tools which allow the visualization of those events remain underdeveloped.FindingsRiboPlotR is a visualization package written in R that presents both RNA-seq coverage and Ribo-seq reads for all annotated transcript isoforms in a context of a given gene. In particular, RiboPlotR plots Ribo-seq reads mapped in three reading frames using three colors for one isoform model at a time. Moreover, RiboPlotR shows Ribo-seq reads on upstream ORFs, 5’ and 3’ untranslated regions and introns, which is critical for observing new translation events and potential regulatory mechanisms.ConclusionsRiboPlotR is freely available (https://github.com/hsinyenwu/RiboPlotR) and allows the visualization of the translating features in Ribo-seq data.
Expression Profiling, Downstream Signaling and Subunit Interactions of GPA2/GPB5 in the Adult MosquitoAedes aegypti
Authors: Rocco David A. , Paluzzi Jean-Paul V. 
Published: July 2019

AbstractGPA2/GPB5 and its receptor constitute a glycoprotein hormone-signalling system native to the genomes of most vertebrate and invertebrate organisms, including humans and mosquitoes. Unlike the well-studied gonadotropins and thyrotropin, the exact function of GPA2/GPB5 is unclear, and whether it elicits its functions as heterodimers, homodimers or as independent monomers remains unknown. Here, the glycoprotein hormone signalling system was investigated in adult mosquitoes, where GPA2 and GPB5 subunit transcripts co-localized to bilateral pairs of neuroendocrine cells within the first five abdominal ganglia of the central nervous system. Unlike human GPA2/GPB5 that demonstrated strong heterodimerization between subunits, the GPA2/GPB5 subunits inA. aegyptilacked evidence of heterodimerization when heterologously expressed. Interestingly, cross-linking analysis to determine subunit interactions revealedA. aegyptiandH. sapiensGPA2 and GPB5 subunits form homodimers, and treatments with independent subunits did not activateA. aegyptiLGR1 orH. sapiensTSH receptor, respectively. Since mosquito GPA2/GPB5 heterodimers were not evident by heterologous expression of independent subunits, a tethered construct was generated for expression of the subunits as a single polypeptide chain to improve heterodimer formation. Our findings revealedA. aegyptiLGR1 elicited constitutive activity that elevated levels of cAMP as determined by increased cAMP-dependent luminescence. However, upon treatment with recombinant tethered GPA2/GPB5 heterodimers, an inhibitory G protein (Gi) signalling cascade is initiated and forskolin-induced cAMP production is inhibited. These results provide evidence towards the functional deorphanization of LGR1 and, moreover, further support the notion that GPA2/GPB5 heterodimerization is a requirement for glycoprotein hormone receptor activation.
DeepMicrobes: taxonomic classification for metagenomics with deep learning
Authors: Liang Qiaoxing , Bible Paul W. , Liu Yu , Zou Bin , Wei Lai 
Published: July 2019

AbstractTaxonomic classification is a crucial step for metagenomics applications including disease diagnostics, microbiome analyses, and outbreak tracing. Yet it is unknown what deep learning architecture can capture microbial genome-wide features relevant to this task. We report DeepMicrobes (https://github.com/MicrobeLab/DeepMicrobes), a computational framework that can perform large-scale training on > 10,000 RefSeq complete microbial genomes and accurately predict the species-of-origin of whole metagenome shotgun sequencing reads. We show the advantage of DeepMicrobes over state-of-the-art tools in precisely identifying species from microbial community sequencing data. Therefore, DeepMicrobes expands the toolbox of taxonomic classification for metagenomics and enables the development of further deep learning-based bioinformatics algorithms for microbial genomic sequence analysis.
STARRPeaker: Uniform processing and accurate identification of STARR-seq active regions
Authors: Lee Donghoon , Shi Manman , Moran Jennifer , Wall Martha , Zhang Jing , Liu Jason , Fitzgerald Dominic , Kyono Yasuhiro , Ma Lijia , White Kevin P , Gerstein Mark 
Published: July 2019

AbstractBackgroundHigh-throughput reporter assays, such as self-transcribing active regulatory region sequencing (STARR-seq), allow for unbiased and quantitative assessment of enhancers at a genome-wide scale. Recent advances in STARR-seq technology have employed progressively more complex genomic libraries and increased sequencing depths, to assay larger sized regions, up to the entire human genome. These advances necessitate a reliable processing pipeline and peak-calling algorithm.ResultsMost STARR-seq studies have relied on chromatin immunoprecipitation sequencing (ChIP-seq) processing pipelines. However, there are key differences in STARR-seq versus ChIP-seq. First, STARR-seq uses transcribed RNA to measure the activity of an enhancer, making an accurate determination of the basal transcription rate important. Second, STARR-seq coverage is highly non-uniform, overdispersed, and often confounded by sequencing biases, such as GC content and mappability. Lastly, here, we observed a clear correlation between RNA thermodynamic stability and STARR-seq readout, suggesting that STARR-seq may be sensitive to RNA secondary structure and stability. Considering these findings, we developed a negative-binomial regression framework for uniformly processing STARR-seq data, called STARRPeaker. In support of this, we generated whole-genome STARR-seq data from the HepG2 and K562 human cell lines and applied STARRPeaker to call enhancers.ConclusionsWe show STARRPeaker can unbiasedly detect active enhancers from both captured and whole-genome STARR-seq data. Specifically, we report ∼33,000 and ∼20,000 candidate enhancers from HepG2 and K562, respectively. Moreover, we show that STARRPeaker outperforms other peak callers in terms of identifying known enhancers with fewer false positives. Overall, we demonstrate an optimized processing framework for STARR-seq experiments can identify putative enhancers while addressing potential confounders.
A Comparison of Drug Delivery into Skin Using Topical Solutions, Needle Injections and Jet Injections
Authors: Cu Katharina , Bansal Ruchi , Mitragotri Samir , Rivas David Fernandez 
Published: July 2019

AbstractDrug diffusion within the skin with a needle-free micro-jet injection (NFI) device was compared with two well-established delivery methods: topical application and solid needle injection. A permanent make-up (PMU) machine, normally used for dermal pigmentation, was utilized as a solid needle injection method. For NFIs a continuous wave (CW) laser diode was used to create a bubble inside a microfluidic device containing a light absorbing solution. Each method delivered two different solutions intoex-vivoporcine skin. The first solution consisted of a red dye (direct red 81) and rhodamine B in water. The second solution was direct red 81 and rhodamine B in water and glycerol. For PMU experiments, the skin samples were kept stationary and the diffusion depth, width and surface area were measured. The NFI has a higher vertical dispersion velocity of 3 × 105μm/s compared to topical (0.1 μm/s) and needle injection (53μm/s). The limitations and advantages of each method are discussed, and we conclude that the micro-jet injector represents a fast and minimally invasive injection method, while the solid needle injector causes notably tissue damage. In contrast, the topical method had the slowest diffusion rate but causes no visible damage to the skin.
Effects of prey turnover on poison frog toxins: a landscape ecology approach to assess how biotic interactions affect species phenotypes
Authors: Prates Ivan , Paz Andrea , Brown Jason L. , Carnaval Ana C. 
Published: July 2019

AbstractEcological studies of species pairs demonstrated that biotic interactions promote phenotypic change and eco-evolutionary feedbacks. However, we have a limited understanding of how phenotypes respond to interactions with multiple taxa. We investigate how interactions with a network of prey species contribute to spatially structured variation in the skin toxins of the Neotropical poison frog Oophaga pumilio. Specifically, we assess how beta-diversity of alkaloid-bearing arthropod prey assemblages (68 ant species) and evolutionary divergence among populations (from a neutral genetic marker) contribute to frog poison dissimilarity (toxin profiles composed of 230 different lipophilic alkaloids sampled from 934 frogs at 46 sites). We show that ant assemblage turnover predicts alkaloid turnover and unique toxin combinations across the range of O. pumilio. By contrast, evolutionary relatedness is barely correlated with toxin variation. We discuss how the analytical framework proposed here can be extended to other multi-trophic systems, coevolutionary mosaics, microbial assemblages, and ecosystem services.
Molecular insights from conformational ensembles via machine learning
Authors: Fleetwood O. , Kasimova M.A. , Westerlund A.M. , Delemotte L. 
Published: July 2019

ABSTRACTBiomolecular simulations are intrinsically high dimensional and generate noisy datasets of ever increasing size. Extracting important features in the data is crucial for understanding the biophysical properties of molecular processes, but remains a big challenge. Machine learning (ML) provides powerful dimensionality reduction tools. However, such methods are often criticized to resemble black boxes with limited human-interpretable insight.We use methods from supervised and unsupervised ML to efficiently create interpretable maps of important features from molecular simulations. We benchmark the performance of several methods including neural networks, random forests and principal component analysis, using a toy model with properties reminiscent of macromolecular behavior. We then analyze three diverse biological processes: conformational changes within the soluble protein calmodulin, ligand binding to a G protein-coupled receptor and activation of an ion channel voltage-sensor domain, unravelling features critical for signal transduction, ligand binding and voltage sensing. This work demonstrates the usefulness of ML in understanding biomolecular states and demystifying complex simulations.STATEMENT OF SIGNIFICANCEUnderstanding how biomolecules function requires resolving the ensemble of structures they visit. Molecular dynamics simulations compute these ensembles and generate large amounts of data that can be noisy and need to be condensed for human interpretation. Machine learning methods are designed to process large amounts of data, but are often criticized for their black-box nature and have historically been modestly used in the analysis of biomolecular systems. We demonstrate how machine learning tools can provide an interpretable overview of important features in a simulation dataset. We develop a protocol to quickly perform data-driven analysis of molecular simulations. This protocol is applied to identify the molecular basis of ligand binding to a receptor and of voltage sensitivity of an ion channel.
Construction of High-Resolution RAD-Seq Based Linkage Map, Anchoring Reference Genome, and QTL Mapping of the Sex Chromosome in the Marine Medaka Oryzias melastigma
Authors: Lee Bo-Young , Kim Min-Sub , Choi Beom-Soon , Nagano Atsushi J. , Ting Au Doris Wai , Sun Wu Rudolf Shiu , Takehana Yusuke , Lee Jae-Seong 
Published: July 2019

ABSTRACTMedaka (Oryzias spp.) is an important fish species in ecotoxicology and considered as a model species due to its biological features including small body size and short generation time. Since Japanese medaka Oryzias latipes is a freshwater species with access to an excellent genome resources, the marine medaka Oryzias melastigma is also applicable for marine ecotoxicology. In genome era, a high-density genetic linkage map is a very useful resource in genomic research, providing a means for comparative genomic analysis and verification of de novo genome assembly. In this study, we developed a high-density genetic linkage map for O. melastigma using restriction-site associated DNA sequencing (RAD-seq). The genetic map consisted of 24 linkage groups with 2,481 RAD-tag markers. The total map length was 1,784 cM with an average marker space of 0.72 cM. The genetic map was integrated with the reference-assisted chromosome assembly (RACA) of O. melastigma, which anchored 90.7% of the assembled sequence onto the linkage map. The values of complete Benchmarking Universal Single-Copy Orthologs (BUSCO) were similar to RACA assembly but N50 (23.74 Mb; total genome length 779.4 Mb; gap 5.29%) increased to 29.99 Mb (total genome length 778.7 Mb; gap 5.2%). Using MapQTL analysis with a single nucleotide polymorphism markers, we identified a major quantitative trait locus for sex traits on the Om10. The integration of the genetic map with the reference genome of marine medaka will serve as a good resource for studies in molecular toxicology, genomics, CRISPR/Cas9, and epigenetics.