bluuebunny/crossref_metadata_2025_split huggingface dataset:
Lipidomic profiling of plasma extracellular vesicles as an effective means to evaluate the risk of preterm birth
Authors: Zhao Qianqian , Ma Zhen , Wang Xinran , Liang Minling , Wang Wenjing , Su Fengxia , Yang Huanming , Gao Ya , Ren Yan 
Published: June 2020

AbstractPreterm birth is the main cause of infant death worldwide and results in a high societal economic burden associated with newborn care. Recent studies have shown that extracellular vesicles play an important role in fetal development during pregnancy. Here, we fully investigated differences in lipids in plasma, microvesicles and exosomes between 27 preterm and 66 full-term pregnant women in the early second trimester (12-24 weeks) using an untargeted lipidomics approach. Independent of other characteristics of samples, we detected 97, 58 and 10 differential features (retention time (RT) and m/z) with identification by multivariate and univariate statistical analyses in plasma, microvesicles and exosomes, respectively. These altered lipids were involved in the formation of the bacterial cell wall and chronic low-level inflammation and oxidative stress. Furthermore, lipids in microvesicles could distinguish patients who experienced preterm labor from controls better than lipids in plasma and exosomes. The candidate lipid biomarkers in microvesicles were also validated by the pseudotargeted lipidomics method. The validation set included 41 preterm and 42 healthy pregnant women. PS (34:0) in microvesicles was able to distinguish preterm birth from healthy pregnancy with higher accuracy. Our study shows that differences in lipids in plasma, microvesicles and exosomes are useful for understanding the underlying mechanisms, early clinical diagnosis and intervention of preterm birth.
Closed-loop fMRI neurofeedback to reduce negative attentional bias in depression
Authors: Mennen Anne C. , Turk-Browne Nicholas B. , Wallace Grant , Seok Darsol , Jaganjac Adna , Stock Janet , deBettencourt Megan T. , Cohen Jonathan D. , Norman Kenneth A. , Sheline Yvette I. 
Published: June 2020

AbstractDepressed individuals show an attentional bias toward negatively valenced stimuli and thoughts. Here we present a novel closed-loop neurofeedback procedure that seeks to remediate this bias. Internal attentional states were detected by applying machine learning techniques to fMRI data in real-time, and externalized using a visually presented stimulus that the participant could learn to control. We trained 15 depressed and 12 healthy control participants over three fMRI sessions, preceded and followed by behavioral and clinical assessments. Initially, depressed participants were more likely than non-depressed participants to get “stuck” in negative attentional states, but this diminished with neurofeedback training relative to controls. Depression severity also decreased from pre- to post-training. These results demonstrate that our method is sensitive to the negative attentional bias in depressed individuals, and its reduction after training showcases the potential of this method as a treatment in the future.
scASK: A novel ensemble framework for classifying cell types based on single-cell RNA-seq data
Authors: Liu Bo , Wu Fang-Xiang , Zou Xiufen 
Published: June 2020

ABSTRACTThe Human Cell Atlas (HCA) is a large project that aims to identify all cell types in the human body. The dimension reduction and clustering for identification of cell types from single-cell RNA-sequencing (scRNA-seq) data have become foundational approaches to HCA. The major challenges of current computational analyses are of poor performance on large scale data and sensitive to initial data. We present a new ensemble framework called Adaptive Slice KNNs (scASK) to address the challenges for analysing scRNA-seq data with high dimensionality. scASK consists of three innovational modules, called DAS (Data Adaptive Slicing), MCS (Meta Classifiers Selecting) and EMS (Ensemble Mode Switching), respectively, which facilitate scASK to approximate a bias-variance tradeoff beyond classification. Thirteen real scRNA-seq datasets are used to evaluate the performance of scASK. Compared with five popular classification algorithms, our experimental results indicate that scASK achieves the best accuracy and robustness among all competing methods. In conclusion, adaptive slicing is an effective structural reduction procedure, and meanwhile scASK provides novel and robust ensemble framework especially for classifying cell types based on scRNA-seq data. scASK is publically available athttps://github.com/liubo2358/scASKcmd.
Mixture model investigation of the inner-outer asymmetry in visual crowding reveals a heavier weight towards the visual periphery
Authors: Shechter Adi , Yashar Amit 
Published: June 2020

AbstractCrowding, the failure to identify a peripheral item in clutter, is an essential bottleneck in visual information processing. A hallmark characteristic of crowding is the inner-outer asymmetry in which the outer flanker (more eccentric) produces stronger interference than the inner one (closer to the fovea). We tested the contribution of the inner-outer asymmetry to the pattern of crowding errors in a typical radial crowding display in which both flankers are presented simultaneously on the horizontal meridian. In two experiments, observers were asked to estimate the orientation of a Gabor target. Instead of the target, observers reported the outer flanker much more frequently than the inner one. When the target was the outer Gabor, crowding was reduced. Furthermore, when there were four flankers, two on each side of the target, observers misreported the outer flanker adjacent to the target, not the outermost flanker. Model comparisons suggested that orientation crowding reflects sampling over a weighted sum of the represented features, in which the outer flanker is more heavily weighted compared to the inner one. Our findings reveal a counterintuitive phenomenon: in a radial arrangement of orientation crowding, within a region of selection, the outer item dominates appearance more than the inner one.
MTSplice predicts effects of genetic variants on tissue-specific splicing
Authors: Cheng Jun , Çelik Muhammed Hasan , Kundaje Anshul , Gagneur Julien 
Published: June 2020

AbstractTissue-specific splicing of exons plays an important role in determining tissue identity. However, computational tools predicting tissue-specific effects of variants on splicing are lacking. To address this issue, we developed MTSplice (Multi-tissue Splicing), a neural network which quantitatively predicts effects of human genetic variants on splicing of cassette exons in 56 tissues. MTSplice combines the state-of-the-art predictor MMSplice, which models constitutive regulatory sequences, with a new neural network which models tissue-specific regulatory sequences. MTSplice outperforms MMSplice on predicting effects associated with naturally occurring genetic variants in most tissues of the GTEx dataset. Furthermore, MTSplice predicts that autism-associated de novo mutations are enriched for variants affecting splicing specifically in the brain. MTSplice is provided free of use and open source at the model repository Kipoi. We foresee MTSplice to be useful for functional prediction and prioritization of variants associated with tissue-specific disorders.
Insights into the Binding Mechanism of Ascorbic Acid and Violaxanthin with Violaxanthin De-Epoxidase (VDE) and Chlorophycean Violaxanthin De-Epoxidase (CVDE) Enzymes: Docking, Molecular Dynamics, and Free Energy Analysis
Authors: Biswal Satyaranjan , Sen Gupta Parth Sarthi , Bhat Haamid Rasool , Rana Malay Kumar 
Published: June 2020

AbstractPhotosynthetic organisms have evolved to work under low and high lights in photoprotection, acting as a scavenger of reactive oxygen species. The light dependent xanthophyll cycle involved in this process is performed by a key enzyme (present in the thylakoid lumen) Violaxanthin De-Epoxidase (VDE) in the presence of violaxanthin and ascorbic acid substrates. Phylogenetically, VDE is found to be connected with an ancestral enzyme Chlorophycean Violaxanthin De-Epoxidase (CVDE) present in the green algae on the stromal side of the thylakoid membrane. However, the structure and functions of CVDE were not known. In search of functional similarities involving this cycle, the structure, binding conformation, stability, and interaction mechanism of CVDE are explored with the two substrates in comparison to VDE. The structure of CVDE was determined by homology modeling and validated. In-silico docking (of first-principles-optimized substrates) revealed it has a larger catalytic domain than VDE. A thorough analysis of the binding affinity and stability of four enzyme-substrate complexes are performed by computing free energies and its decomposition, the root-mean-square deviation (RMSD) and fluctuation (RMSF), the radius of gyration, salt-bridge and hydrogen bonding interactions in molecular dynamics. Based on these, violaxanthin interacts with CVDE to the similar extent as that of VDE, hence its role is expected to be the same for both the enzymes. On the contrary, ascorbic acid has a weaker interaction with CVDE than VDE. As these interactions drive epoxidation or de-epoxidation process in the xanthophyll cycle, it immediately discerns that either ascorbic acid does not take part in de-epoxidation or this process requires a different cofactor because of the weaker interaction of ascorbic acid with CVDE in comparison to VDE.
Phylogenetic comparative analyses of the determinants of anti-predator distraction behavior in shorebirds
Authors: Saijo Miki , Kutsukake Nobuyuki 
Published: June 2020

AbstractPredation risk exerts a strong selective pressure on anti-predator behavior, resulting in behaviors to achieve defense of offspring and the individual. In shorebirds, some species perform distraction behavior that is attracting the attention of a predator. This behavior evolved, and were lost multiple times, independently and the behavioral repertoire varies among species. Although defense of offspring is critical for parents, the determinants of inter-specific variation in the distraction behavior remain unstudied. We surveyed the literature and conducted phylogenetic comparative analyses (n = 169 species) to test predictions regarding nest site, body mass, and coloniality. We found that small species were more likely to perform distraction behavior than large species. Solitary species were more likely to perform distraction behavior than colonial nesting species. Previous studies suggested that colonial nesting and large species commonly perform aggressive anti-predator behavior, implying that distraction behavior is an alternative anti-predator strategy to aggressive ones.
Computational Support, Not Primacy, Distinguishes Compensatory Memory Reorganization in Epilepsy
Authors: Tracy Joseph I. , Chaudhary Kapil , Modi Shilpi , Crow Andrew , Kumar Ashith , Weinstein David , Sperling Michael R. 
Published: June 2020

AbstractTemporal lobe epilepsy (TLE) is associated with impairment in episodic memory. A substantial sub-group, however, is able to maintain adequate memory despite temporal lobe pathology. What has been missing from prior work in the cognitive reorganization is a direct comparison of TLE patients with intact/compensated status from those who are memory impaired and uncompensated. Little is known about the particular regional activations, functional connectivities (FC’s), and/or network reconfigurations that implement changes in the primary computations or the support functions that drive adaptive plasticity and compensated memory. We utilized task fMRI on 54 unilateral TLE patients and 24 matched healthy controls (HC) during performance of a paired-associate memory (PAM) task to address three questions: 1) what regions implement PAM in TLE, and do such regions vary as a function of good versus poor performance, 2) are there unique FC’s present during memory encoding that accounts for intact status through the preservation of primary memory computations or the supportive computations that allow for compensated memory responses, and 3) what features during memory encoding are most distinctive: is it the magnitude and location of regional activations, or the presence of enhanced functional connections to key structures such as the hippocampus? Results revealed a unique profile of non-ictal, non-dominant hemisphere regions (e.g., right posterior temporal regions) were most important to intact/compensated status in LTLE, involving both increased regional activity and increased modulatory communication with the hippocampi, all feature that was missing in impaired/uncompensated LTLE. The profile involved areas that are neither contralateral homologues to left hemisphere memory areas, nor regions traditionally considered computationally primary for episodic memory. None of these areas of increased activation or functional connectivity were associated with advantaged memory in HC’s. Our emphasis on different performance levels yielded insight into two forms of cognitive reorganization. Computational primacy, where LTLE showed little change relative to HC’s, and computational support where Intact/Compensated LTLE patients showed adaptive abnormalities. The analyses isolated the unique regional activations and mediating FC’s that implement truly compensatory reorganization in LTLE. The results provided a new perspective on memory deficits by making clear that memory deficits arise not just from knockout of a functional hub, but from the failure to instantiate a complex set of reorganization responses. Such responses provided computational support to ensure successful memory. The findings demonstrated that by keeping track of performance levels, we can increase our understanding of adaptive brain responses and neuroplasticity in epilepsy.
Dispersal evolution diminishes the negative density dependence in dispersal
Authors: Mishra Abhishek , Chakraborty Partha Pratim , Dey Sutirth 
Published: June 2020

ABSTRACTIn many organisms, dispersal varies with the local population density. Such patterns of density-dependent dispersal (DDD) are expected to shape the dynamics, spatial spread and invasiveness of populations. Despite their ecological importance, empirical evidence for the evolution of DDD patterns remains extremely scarce. This is especially relevant because rapid evolution of dispersal traits has now been empirically confirmed in several taxa. Changes in DDD of dispersing populations could help clarify not only the role of DDD in dispersal evolution, but also the possible pattern of subsequent range expansion. Here, we investigate the relationship between dispersal evolution and DDD using a long-term experimental evolution study onDrosophila melanogaster. We compared the DDD patterns of four dispersal-selected populations and their non-selected controls. The control populations showed negative DDD, which was stronger in females than in males. In contrast, the dispersal-selected populations showed density-independent dispersal, where neither males nor females exhibited DDD. We compare our results with previous evolutionary predictions that focused largely on positive DDD, and highlight how the direction of evolutionary change depends on the initial DDD pattern of a population. Finally, we discuss the implications of DDD evolution for spatial ecology and evolution.
Nitric oxide, KATPchannels and endothelin-1 modulate brain pericyte function, vascular tone and neurovascular coupling
Authors: Zambach Stefan Andreas , Cai Changsi , Cederberg Helms Hans Christian , Hald Bjørn Olav , Fordsmann Jonas Christoffer , Nielsen Reena Murmu , Lønstrup Micael , Brodin Birger , Lauritzen Martin Johannes 
Published: June 2020

ABSTRACTNeurotransmitter-mediated signaling correlates strongly to changes in cerebral blood flow (CBF), and functional neuroimaging relies on the robust coupling between activity and CBF, i.e. neurovascular coupling (NVC). We here reveal that key endothelial signaling molecules, nitric oxide (eNO) and endothelin-1 (ET1), modulate pericyte contractility and that pericyte ATP-sensitive potassium (KATP) channels interact with endothelial factors to modulate vascular tone and NVC. We show that NVC requires local synthesis of cGMP, but not NO derived from endothelial cells. The potent endothelial vasoconstrictor ET1 contracted pericytes by IP3receptor mediated Ca2+release and blocked NVC. In comparison, pericyte KATPchannel openers increased the diameter of capillaries by deactivation of L-type Ca2+channels while KATPblockers shortened the NVC response. All vasoactive stimuli produced the largest diameter changes at the first capillary that branches off from the penetrating arteriole. Our results reveal that three different signaling pathways mediate the effects of NO, ET1 and KATPchannels on brain pericytes and capillary blood flow by mechanisms similar to vascular smooth muscle despite great differences in morphology.
Unsupervised Neural Tracing in Densely Labeled Multispectral Brainbow Images
Authors: Duan Bin , Walker Logan A , Roossien Douglas H , Shen Fred Y , Cai Dawen , Yan Yan 
Published: June 2020

AbstractReconstructing neuron morphology is central to uncovering the complexity of the nervous system. That is because the morphology of a neuron essentially provides the physical constraints to its intrinsic electrophysiological properties and its connectivity. Recent advances in imaging technologies generated large quantities of high-resolution 3D images of neurons in the brain. Furthermore, the multispectral labeling technology, Brainbow permits unambiguous differentiation of neighboring neurons in a densely labeled brain, therefore enables for the first time the possibility of studying the connectivity between many neurons from a light microscopy image. However, lack of reliable automated neuron morphology reconstruction makes data analysis the bottleneck of extracting rich informatics in neuroscience. Supervoxel-based neuron segmentation methods have been proposed to solve this problem, however, the use of previous approaches has been impeded by the large numbers of errors which arise in the final segmentation. In this paper, we present a novel unsupervised approach to trace neurons from multispectral Brainbow images, which prevents segmentation errors and tracing continuity errors using two innovations. First, we formulate a Gaussian mixture model-based clustering strategy to improve the separation of segmented color channels that provides accurate skeletonization results for the following steps. Next, a skeleton graph approach is proposed to allow the identification and correction of discontinuities in the neuron tree topology. We find that these innovations allow our approach to outperform current state-of-the-art approaches, which results in more accurate neuron tracing as a tree representation close to human expert annotation.
Genome-wide analysis of the cupin superfamily in cowpea (Vigna unguiculata)
Authors: Rocha Antônio J. , de Oliveira Barsottini Mario Ramos , Paiva Ana Luiza Sobral , Costa José Hélio , Grangeiro Thalles Barbosa 
Published: June 2020

AbstractCowpea [Vigna unguiculata(L.)Walp.] is an essential food crop that is cultivated in many important arid and semi-arid regions of the world. In this study the genome-wide database of cowpea genes was accessed in search of genomic sequences coding for globulins, specifically members of the cupin superfamily, a well-documented multigenic family belonging to the globulin protein class. A total of seventy-seven genes belonging to the cupin superfamily were found and divided into six families. We classifyV. unguiculatagenes into two subgroups: classical cupins with one cupin domain (fifty-nine proteins) and bicupins with two cupin domains (eighteen members). In addition, a search for cupin members in other closely related species of the fabaceae family [V. angularis, V. radiatamandPhaseolus vulgaris(common bean)] was performed. Based on those data, a detailed characterization and comparison of the cupin genes on these species was performed with the aim to better understand the connection and functions of cupin proteins from different, but related, plant species. This study was the first attempt to investigate the cupin superfamily inV. unguiculata, allowing the identification of six cupins families and better understand the structural features of those proteins, such as number of domains alternative splicing.
Genomics of OcularChlamydia trachomatisafter 5 years of SAFE interventions for trachoma in Amhara, Ethiopia
Authors: Pickering Harry , Chernet Ambahun , Sata Eshetu , Zerihun Mulat , Williams Charlotte A. , Breuer Judith , Nute Andrew W. , Haile Mahiteme , Zeru Taye , Tadesse Zerihun , Bailey Robin L. , Callahan E. Kelly , Holland Martin J. , Nash Scott D. 
Published: June 2020

AbstractBackgroundTo eliminate trachoma as a public health problem, the WHO recommends the SAFE strategy. As part of the SAFE strategy in the Amhara Region, Ethiopia, the Trachoma Control Program distributed over 124 million doses of antibiotic between 2007 and 2015. Despite these interventions, trachoma remained hyperendemic in many districts and a considerable level ofChlamydia trachomatis(Ct) infection was evident.MethodsWe utilised residual material from Abbott m2000Ctdiagnostic tests to sequence 99 ocularCtsamples from Amhara and investigated the role ofCtgenomic variation in the continued transmission ofCtfollowing 5 years of SAFE.FindingsSequences were typical of ocularCt, at the whole-genome level and in tissue tropism-associated genes. There was no evidence of macrolide-resistance in thisCtpopulation. Polymorphism in a region aroundompAgene was associated with village-level TF prevalence. Additionally, greaterompAdiversity at the district-level was associated with increasedCtinfection prevalence.InterpretationWe found no evidence forCtgenomic variation contributing to continued transmission ofCtafter treatment, adding to previous evidence that azithromycin does not drive acquisition of macrolide resistance alleles inCt. IncreasedCtinfection in villages and in districts with moreompAvariants requires longitudinal investigation to understand what impact this may have on treatment success and host immunity.FundingEuropean Commission; Neglected Tropical Disease Support Center; International Trachoma Initiative
Measuring Neuronal Signals with Microelectrode Arrays: A Finite Element Analysis
Authors: Bestel R , van Rienen U , Thielemann C , Appali R 
Published: June 2020

AbstractObjectiveMeasuring neuronal cell activity using microelectrode arrays reveals a great variety of derived signal shapes within extracellular recordings. However, possible mechanisms responsible for this variety have not yet been entirely determined, which might hamper any subsequent analysis of the recorded neuronal data. For an investigation of this issue, we propose a computational model based on the finite element method describing the electrical coupling between an electrically active neuron and an extracellular recording electrode in detail. This allows for a systematic study of possible parameters that may play an essential role in defining or altering the shape of the measured electrode potential. Our results indicate that neuronal geometry and neurite structure, as well as the actual pathways of input potentials that evoke action potential generation, have a significant impact on the shape of the resulting extracellular electrode recording and explain most of the known signal shape variety.