bluuebunny/crossref_metadata_2025_split huggingface dataset:
Vasculature-staining with lipophilic dyes in tissue-cleared brains assessed by deep learning
Authors: Henriksen Beatriche L. E. , Jensen Kristian H. R. , Berg Rune W. 
Published: May 2020

Visualization of the vasculature in three dimensions (3D) has become attractive, particularly in stroke models. 3D-reconstruction is aided by tissue-clearing, where the transparency allows imaging of fluorescent probes in deeper structures. The vasculature is commonly stained by fluorescent lipophilic dyes that are incorporated into the wall during transcardial perfusion. Nevertheless, tissue clearing involves extracting the light-scattering lipids, and hence also the lipid-appended dyes. The wash-out likely depends on dye and its aldehyde-fixability. Fixation secures cross-linking to proteins and hence retainment in the tissue. However, the compatibility of various types of dyes is largely unknown. We tested and compared 9 different dyes for vasculature staining and tolerance to lipid clearing, which was quantified using deep learning image segmentation. Among the dyes, we found a subset that is both cost-effective and compatible with tissue lipid clearing. We suggest these dyes will provide a valuable tool for future investigations.HighlightsSize, alkyl-chains and aldehyde-fixable groups improve dye retention and performance.Cost-effective dyes in specific liposomes result in optimal vessel staining.SP-DiIC18 is compatible with CLARITY and BrainFilm and advantageous for most studies.We recommend, SP-DiI and R18, cost-effective dyes, for vessel-painting with CLARITY.Abstract Figure
Sex differences and effects of estrous stage on hippocampal-prefrontal theta communications
Authors: Schoepfer Kristin J. , Xu Yiqi , Wilber Aaron A. , Wu Wei , Kabbaj Mohamed 
Published: May 2020

ABSTRACTEffective communication between the mammalian hippocampus and neocortex is essential to certain cognitive-behavioral tasks critical to survival in a changing environment. Notably, functional synchrony between local field potentials (LFPs) of the ventral hippocampus (vHPC) and the medial prefrontal cortex (mPFC) within the theta band (4-12 Hz) underlies innate avoidance behavior during approach-avoidance conflict tasks in male rodents. However, the physiology of vHPC-mPFC communications in females remains unestablished. Furthermore, little is known about how mPFC subdivisions functionally interact in the theta band with hippocampal subdivisions in both sexes in the absence of task demands. Given the established roles of biological sex and gonadal hormone status on innate avoidance behaviors and neuronal excitability, here, we characterize the effects of biological sex and female estrous stage on hippocampal-prefrontal theta signaling in freely-moving female and male rats. LFPs from vHPC, dorsal hippocampus (dHPC), mPFC-prelimbic (PrL), and mPFC-infralimbic (IL) were simultaneously recorded during spontaneous exploration of a familiar arena. Data suggest that theta phase and power in vHPC preferentially synchronize with PrL; conversely, dHPC and IL preferentially synchronize. Males displayed greater vHPC-PrL theta synchrony than females, despite similar regional frequency band power and inter-regional coherence. Additionally, several significant estrous-linked changes in hippocampal-prefrontal theta dynamics were observed. These findings support the hypothesis that biological sex and female estrous stage can both affect hippocampal-prefrontal theta signaling in a familiar environment. These findings establish novel research avenues concerning sexual dimorphisms and effects of gonadal hormone status in HPC-mPFC network activity pertaining to threat evaluation biomarkers.SIGNIFICANCE STATEMENTEffective signaling between subregions of the hippocampus and the prefrontal cortex underlies several cognitive-behavioral processes necessary for survival. Theta-frequency synchrony between the local fields of the ventral hippocampus and the prefrontal cortex regulates innate avoidance behavior in male rodents. However, this circuit remains understudied in females, despite its potential utility in research modeling the neurobiology of anxiety disorders (and sex differences therein). Here, we demonstrate that both biological sex and female hormone status have multifaceted effects on hippocampal-prefrontal theta-frequency signaling in freely-moving rats during exploration of a familiar arena. These findings provide insight into how biological sex and female estrous stage shape the way in which these circuits may represent the potential for threat.
Towards a unifying diversity-area relationship (DAR) of species- and gene-diversity
Authors: Ma Zhanshan (Sam) , Ellison Aaron M. 
Published: May 2020

AbstractAimThe microbiome as a biogeographic entity can be investigated, to the minimum, from two perspectives: one is the spatial/temporal distribution of species (or any level of the operational taxonomic unit or OTU) diversity, and another is the spatial/temporal distribution of metagenomic gene diversity. Both are necessary for comprehensive understanding of the taxonomical, ecological, evolutionary and functional aspects of the microbiome biogeography. Here we propose to investigate the metagenomic diversity-area relationship (m-DAR), which is a transformation of the species-DAR (s-DAR) that extended the classic SAR (species-area relationship) by replacing the species richness with general species diversity measured in Hill numbers.InnovationThem-DAR ands-DAR, using the same mathematical models, offer a unifying tool for investigating the biogeography of microbiome from ecological, metagenomic and functional perspectives. Specifically, we investigatem-DAR of the human gut metagenome in terms of the MG (metagenomic gene) and MFGC (metagenome functional gene cluster) respectively, by sketching out the DAR-profile, PDO (pair-wise diversity overlap) profile, MAD (maximal accrual diversity) profile, and RIP (ratio of individual- to population-diversity) profile at each scale. These profiles constitute our unifying DAR toolset and can be applied to any microbiomes beyond the human gut microbiome.Main conclusionsWe demonstrate the construction and applications of them-DAR and its associated four profiles with six large datasets of the human gut metagenomes including three microbiome-associated diseases (obesity, diabetes, IBD) and their healthy controls, supported with randomization tests to determine the differences between healthy and diseased treatments in theirm-DAT parameters. Theoretically, our study presents a successful case to demonstrate the feasibility of unifying systematic biogeographyvs. evolutionary biogeography, of an inclusive biogeography of plants, animal and microbes. Practically, our approach offers an important tool for investigating the spatial scaling of human metagenome diversity in a population (cohort) and its relationship with individual-level diversity.
Advancing Divide-and-Conquer Phylogeny Estimation using Robinson-Foulds Supertrees
Authors: Yu Xilin , Le Thien , Christensen Sarah A. , Molloy Erin K. , Warnow Tandy 
Published: May 2020

AbstractOne of the Grand Challenges in Science is the construction of theTree of Life, an evolutionary tree containing several million species, spanning all life on earth. However, the construction of the Tree of Life is enormously computationally challenging, as all the current most accurate methods are either heuristics forNP-hard optimization problems or Bayesian MCMC methods that sample from tree space. One of the most promising approaches for improving scalability and accuracy for phylogeny estimation uses divide-and-conquer: a set of species is divided into overlapping subsets, trees are constructed on the subsets, and then merged together using a “supertree method”. Here, we present Exact-RFS-2, the first polynomial-time algorithm to find an optimal supertree of two trees, using the Robinson-Foulds Supertree (RFS) criterion (a major approach in supertree estimation that is related to maximum likelihood supertrees), and we prove that finding the RFS of three input trees isNP-hard. We also present GreedyRFS (a greedy heuristic that operates by repeatedly using Exact-RFS-2 on pairs of trees, until all the trees are merged into a single supertree). We evaluate Exact-RFS-2 and GreedyRFS, and show that they have better accuracy than the current leading heuristic for RFS. Exact-RFS-2 and GreedyRFS are available in open source form on Github atgithub.com/yuxilin51/GreedyRFS.
INSCT: Integrating millions of single cells using batch-aware triplet neural networks
Authors: Simon Lukas M. , Wang Yin-Ying , Zhao Zhongming 
Published: May 2020

AbstractEfficient integration of heterogeneous and increasingly large single cell RNA sequencing (scRNA-seq) data poses a major challenge for analysis and in particular, comprehensive atlasing efforts. Here, we developed a novel deep learning algorithm to overcome batch effects using batch-aware triplet neural networks, called INSCT (“Insight”). Using simulated and real data, we demonstrate that INSCT generates an embedding space which accurately integrates cells across experiments, platforms and species. Our benchmark comparisons with current state-of-the-art scRNA-seq integration methods revealed that INSCT outperforms competing methods in scalability while achieving comparable accuracies. Moreover, using INSCT in semi-supervised mode enables users to classify unlabeled cells by projecting them into a reference collection of annotated cells. To demonstrate scalability, we applied INSCT to integrate more than 2.6 million transcriptomes from four independent studies of mouse brains in less than 1.5 hours using less than 25 gigabytes of memory. This feature empowers researchers to perform atlasing scale data integration in a typical desktop computer environment. INSCT is freely available athttps://github.com/lkmklsmn/insct.HighlightsINSCT accurately integrates multiple scRNA-seq datasetsINSCT accurately predicts cell types for an independent scRNA-seq datasetEfficient deep learning framework enables integration of millions of cells on a personal computer
Back to feedback: aberrant sensorimotor control in music performance under pressure
Authors: Furuya Shinichi , Ishimaru Reiko , Oku Takanori , Nagata Noriko 
Published: May 2020

ABSTRACTPrecisely timed production of dexterous actions is often destabilized in anxiogenic situations. Previous studies demonstrated that cognitive functions such as attention and working memory as well as autonomic nervous functions are susceptible to induced anxiety in skillful performance while playing sports or musical instruments. However, it is not known whether the degradation of motor functions, sensory perception, or sensorimotor control underlies such a compromise of skillful performance due to psychophysiological distress. Here, we addressed this issue through a series of behavioral experiments, which provided no evidence supporting for detrimental effects of the stress on the perceptual accuracy and precision of the finger movements in pianists. By contrast, after transiently delaying the timing of tone production while playing the piano, the local tempo was abnormally disrupted only under pressure. The results suggest that psychological stress degraded the temporal stability of movement control due to an abnormal increase in sensory feedback gain but not temporal perception or motor precision. A learning experiment further demonstrated that the temporal instability of auditory-motor control under pressure was alleviated after practicing piano while ignoring delayed auditory feedback but not after practicing while compensating for the delayed feedback. Together, these findings suggest an abnormal transition from feedforward to feedback control in expert piano performance in anxiogenic situations, which can be mitigated through specialized sensorimotor training that involves piano practice while volitionally ignoring the artificially delayed provision of auditory feedback.
BrainGNN: Interpretable Brain Graph Neural Network for fMRI Analysis
Authors: Li Xiaoxiao , Zhou Yuan , Dvornek Nicha , Zhang Muhan , Gao Siyuan , Zhuang Juntang , Scheinost Dustin , Staib Lawrence , Ventola Pamela , Duncan James 
Published: May 2020

AbstractUnderstanding which brain regions are related to a specific neurological disorder or cognitive stimuli has been an important area of neuroimaging research. We propose BrainGNN, a graph neural network (GNN) framework to analyze functional magnetic resonance images (fMRI) and discover neurological biomarkers. Considering the special property of brain graphs, we design novel ROI-aware graph convolutional (Ra-GConv) layers that leverage the topological and functional information of fMRI. Motivated by the need for transparency in medical image analysis, our BrainGNN contains ROI-selection pooling layers (R-pool) that highlight salient ROIs (nodes in the graph), so that we can infer which ROIs are important for prediction. Furthermore, we propose regularization terms—unit loss, topK pooling (TPK) loss and group-level consistency (GLC) loss—on pooling results to encourage reasonable ROI-selection and provide flexibility to encourage either fully individual- or patterns that agree with group-level data. We apply the BrainGNN framework on two independent fMRI datasets: an Autism Spectrum Disorder (ASD) fMRI dataset and data from the Human Connectome Project (HCP) 900 Subject Release. We investigate different choices of the hyper-parameters and show that BrainGNN outperforms the alternative fMRI image analysis methods in terms of four different evaluation metrics. The obtained community clustering and salient ROI detection results show a high correspondence with the previous neuroimaging-derived evidence of biomarkers for ASD and specific task states decoded for HCP. We will make BrainGNN codes public available after acceptance.
Metagenomic identification of diverse animal hepaciviruses and pegiviruses
Authors: Porter Ashleigh F. , Pettersson John H.-O. , Chang Wei-Shan , Harvey Erin , Rose Karrie , Shi Mang , Eden John-Sebastian , Buchmann Jan , Moritz Craig , Holmes Edward C. 
Published: May 2020

AbstractThe RNA virus familyFlaviviridaeharbours several important pathogens of humans and other animals, including Zika virus, dengue virus and hepatitis C virus. TheFlaviviridaeare currently divided into four genera -Hepacivirus,Pegivirus,PestivirusandFlavivirus– each of which have a diverse host range. Members of the genusHepacivirusare associated with a diverse array of animal species, including humans and non-human primates, other mammalian species, as well as birds and fish, while the closely related pegiviruses have been identified in a variety of mammalian taxa including humans. Using a combination of meta-transcriptomic and whole genome sequencing we identified four novel hepaciviruses and one novel variant of a known virus, in five species of native Australian wildlife, expanding our knowledge of the diversity in this important group of RNA viruses. The infected hosts comprised native Australian marsupials and birds, as well as a native gecko (Gehyra lauta). The addition of these novel viruses led to the identification of a distinct marsupial clade within the hepacivirus phylogeny that also included an engorgedIxodes holocyclustick collected while feeding on Australian long-nosed bandicoots (Perameles nasuta). Gecko and avian associated hepacivirus lineages were also identified. In addition, by mining the short-read archive (SRA) database we identified another five novel members ofFlaviviridae, comprising three new hepaciviruses from avian and primate hosts, as well as two primate-associated pegiviruses. The large-scale phylogenetic analysis of these novel hepacivirus and pegivirus genomes provides additional support for virus-host co-divergence over evolutionary time-scales.
Transcriptome analysis reveals infection strategies employed byFusarium graminearumas a root pathogen
Authors: Ding Yi , Gardiner Donald M , Kazan Kemal 
Published: May 2020

AbstractThe fungal pathogenFusarium graminearuminfect both heads and roots of cereal crops causing several economically important diseases such as head blight, seedling blight, crown rot and root rot. Trichothecene mycotoxins such as deoxynivalenol (DON), a well-known virulence factor, produced byF. graminearum(Fg) during disease development is also an important health concern. Although howF. graminearuminfects above-ground tissues is relatively well studied, very little is known about molecular processes employed by the pathogen during below-ground infection. Also unknown is the role of DON during root infection. In the present study, we analyzed the transcriptome ofF. graminearumduring root infection of the model cerealBrachypodium distachyon.We also compared ourFgtranscriptome data during root infection with those reported during wheat head infection. These analyses suggested that both shared and unique infection strategies employed by the pathogen during colonization of different host tissues. Several metabolite biosynthesis genes induced inF. graminearumduring root infection could be linked to phytohormone production, implying that the pathogen likely interferes root specific defenses. In addition, to understand the role of DON inFgroot infection, we analyzed the transcriptome of the DON deficientTri5mutant. These analyses showed that the absence of DON had a significant effect on fungal transcriptional responses. Although DON was produced in infected roots, this mycotoxin did not act as a virulence factor during root infection. Our results reveal new mechanistic insights into the below-ground strategies employed byF. graminearumthat may benefit the development of new genetic tools to combat this important cereal pathogen.
Lipoic acid biosynthesis is essential forPlasmodium falciparumtransmission and influences redox response and carbon metabolism of parasite asexual blood stages
Authors: Biddau Marco , Kumar T.R. Santha , Henrich Philipp , Laine Larissa M. , Blackburn Gavin J. , Chokkathukalam Achuthanunni , Li Tao B , Sim Kim Lee , Hoffman Stephen L , Barrett Michael P. , Coombs Graham H. , McFadden Geoffrey I. , Fidock David A. , Müller Sylke , Sheiner Lilach 
Published: May 2020

AbstractMalaria is still one of the most important global infectious diseases. Emergence of drug resistance and a shortage of new efficient anti-malarials continue to hamper a malaria eradication agenda. Malaria parasites are highly sensitive to changes in redox environment. Understanding the mechanisms regulating parasite redox could contribute to the design of new drugs. Malaria parasites have a complex network of redox regulatory systems housed in their cytosol, in their mitochondrion and in their plastid (apicoplast). While the roles of enzymes of the thioredoxin and glutathione pathways in parasite survival have been explored, the antioxidant role of α-lipoic acid (LA) produced in the apicoplast has not been tested. We analysed the effects of LA depletion on mutantPlasmodium falciparumlacking the apicoplast lipoic acid protein ligase B (lipB). Our results showed a change in expression of redox regulators in the apicoplast and the cytosol. We further detected a change in parasite central carbon metabolism, with LA depletion influencing glycolysis and tricarboxylic acid cycle activity. Importantly, abrogation of LipB impactedP. falciparummosquito development, preventing oocyst maturation and production of infectious sporozoite stages, thus flagging LA biosynthesis as a potential target for the development of new transmission drugs.
Morphological and genetic confirmation of the millipedeChordeuma sylvestreC. L. Koch, 1847 new to Ireland
Authors: Gaul Willson , Tighe Andrew J 
Published: May 2020

AbstractWe report the millipedeChordeuma sylvestreC. L. Koch, 1847 for the first time from Ireland. We used morphology of male gonopods and DNA barcoding of the COI gene from two individuals to confirm the identification of one male and one female collected from the campus of University College Dublin. DNA barcoding revealed two mitochondrial haplotypes, implying that colonization was from multiple females or eggs from multiple females. To evaluate how likely it is thatC. sylvestrearrived relatively recently in Ireland, we used species richness estimates and species accumulation curves to evaluate the completeness of the species list compiled during two previous periods of intensive millipede recording going back to 1971. Millipede recording in Ireland was far from complete during the period 1971 – 1984, with multiple species present but undetected. Recording was more complete during the period 1986 – 2005. The area within 20 km of the newC. sylvestrerecords was poorly recorded during the period 1986 – 2005, so we cannot rule out the possibility thatC. sylvestrehas been in Dublin for at least a few decades. However, the disjunct location of the current records compared to the species’s known native range in northern France, the urban location of the current site, and the lack of records from the relatively intensive millipede recording in Ireland between 1986 and 2005 suggest thatC. sylvestreis a recent anthropogenic introduction in Ireland.
Kmer2SNP: reference-free SNP calling from raw reads based on matching
Authors: Li Yanbo , Lin Yu 
Published: May 2020

AbstractThe development of DNA sequencing technologies provides the opportunity to call heterozygous SNPs for each individual. SNP calling is a fundamental problem of genetic analysis and has many applications, such as gene-disease diagnosis, drug design, and ancestry inference. Reference-based SNP calling approaches generate highly accurate results, but they face serious limitations especially when high-quality reference genomes are not available for many species. Although reference-free approaches have the potential to call SNPs without using the reference genome, they have not been widely applied on large and complex genomes because existing approaches suffer from low recall/precision or high runtime.We develop a reference-free algorithm Kmer2SNP to call SNP directly from raw reads. Kmer2SNP first computes the k-mer frequency distribution from reads and identifies potential heterozygous k-mers which only appear in one haplotype. Kmer2SNP then constructs a graph by choosing these heterozygous k-mers as vertices and connecting edges between pairs of heterozygous k-mers that might correspond to SNPs. Kmer2SNP further assigns a weight to each edge using overlapping information between heterozygous k-mers, computes a maximum weight matching and finally outputs SNPs as edges between k-mer pairs in the matching.We benchmark Kmer2SNP against reference-free methods including hybrid (assembly-based) and assembly-free methods on both simulated and real datasets. Experimental results show that Kmer2SNP achieves better SNP calling quality while being an order of magnitude faster than the state-of-the-art methods. Kmer2SNP shows the potential of calling SNPs only using k-mers from raw reads without assembly. The source code is freely available athttps://github.com/yanboANU/Kmer2SNP.