bluuebunny/crossref_metadata_2025_split huggingface dataset:
Emotion suppression failures are associated with local increases in sleep-like activity
Authors: Avvenuti Giulia , Bertelloni Davide , Lettieri Giada , Ricciardi Emiliano , Cecchetti Luca , Pietrini Pietro , Bernardi Giulio 
Published: August 2020

AbstractEmotion self-regulation relies both on cognitive and behavioral strategies implemented to modulate the subjective experience and/or the behavioral expression of a given emotion. While it is known that a network encompassing fronto-cingulate and parietal brain areas is engaged during successful emotion regulation, the functional mechanisms underlying failures in emotion suppression are still unclear. In order to investigate this issue, we analyzed video and high-density EEG recordings of nineteen healthy adult subjects during an emotion suppression (ES) and a free expression (FE) task performed on two consecutive days. Changes in facial expression during ES, but not FE, were preceded by local increases in sleep-like activity (1-4Hz) in in brain areas responsible for emotional suppression, including bilateral anterior insula and anterior cingulate cortex, and in right middle/inferior frontal gyrus (p<0.05, corrected). Moreover, shorter sleep duration the night prior to the ES experiment correlated with the number of behavioral errors (p=0.01) and tended to be associated with higher frontal sleep-like activity during emotion suppression failures (p=0.05). These results indicate that local sleep-like activity may represent the cause of emotion suppression failures in humans, and may offer a functional explanation for previous observations linking lack of sleep, changes in frontal activity and emotional dysregulation.
Frequency-specific transcranial neuromodulation of oscillatory alpha power alters and predicts human visuospatial attention performance
Authors: Kemmerer S. K. , Sack A.T. , de Graaf T.A. , ten Oever S. , De Weerd P. , Schuhmann T. 
Published: August 2020

AbstractUnilateral transcranial alternating current stimulation (tACS) at alpha frequency modulates the locus of spatial attention. However, the neural mechanisms by which tACS influences spatial attention remain poorly understood. Here, we applied high-definition tACS at the individual alpha frequency (IAF), two control frequencies (IAF+/-2Hz) and sham to the left posterior parietal cortex and measured its effects on visuospatial attention performance as well as alpha power (using electroencephalography, EEG). Our results revealed a leftward lateralization of alpha power relative to sham. At a high value of leftward alpha lateralization, we also observed a leftward attention bias, which differed from sham. Moreover, the magnitude of the alpha lateralization effect predicted the attention bias. These effects occurred for tACS at IAF but not for the control frequencies. This suggests that tACS operates through oscillatory interactions with ongoing brain rhythms in line with the synchronization theory. Our results also highlight the importance of personalized stimulation protocols, especially in potential clinical settings.
Estimation of Laminar BOLD Activation Profiles using Deconvolution with a Physiological Point Spread Function
Authors: Markuerkiaga Irati , Marques José P. , Gallagher Tara E. , Norris David G. 
Published: August 2020

AbstractBackgroundThe specificity of gradient echo (GE)-BOLD laminar fMRI activation profiles is degraded by intracortical veins that drain blood from lower to upper cortical layers, propagating activation signal in the same direction. This work describes an approach to obtain layer specific profiles by deconvolving the measured profiles with a physiological Point Spread Function (PSF).New MethodIt is shown that the PSF can be characterised by a TE-dependent peak to tail (p2t) value that is independent of cortical depth and can be estimated by simulation. An experimental estimation of individual p2t values and the sensitivity of the deconvolved profiles to variations in p2t is obtained using laminar data measured with a multi-echo 3D-FLASH sequence. These profiles are echo time dependent, but the underlying neuronal response is the same, allowing a data-based estimation of the PSF.ResultsThe deconvolved profiles are highly similar to the gold-standard obtained from extremely high resolution 3D-EPI data, for a range of p2t values of 5-9, which covers both the empirically determined value (7.1) and the value obtained by simulation (6.3).Comparison with Existing Method(s)Corrected profiles show a flatter shape across the cortex and a high level of similarity with the gold-standard, defined as a subset of profiles that are unaffected by intracortical veins.ConclusionsWe conclude that deconvolution is a robust approach for removing the effect of signal propagation through intracortical veins. This makes it possible to obtain profiles with high laminar specificity while benefitting from the higher sensitivity and efficiency of GE-BOLD sequences.
Real-time, low-latency closed-loop feedback using markerless posture tracking
Authors: Kane Gary , Lopes Gonçalo , Saunders Jonny L. , Mathis Alexander , Mathis Mackenzie W. 
Published: August 2020

AbstractThe ability to control a behavioral task or stimulate neural activity based on animal behavior in real-time is an important tool for experimental neuroscientists. Ideally, such tools are noninvasive, low-latency, and provide interfaces to trigger external hardware based on posture. Recent advances in pose estimation with deep learning allows researchers to train deep neural networks to accurately quantify a wide variety of animal behaviors. Here we provide a newDeepLabCut-Live!package that achieves low-latency real-time pose estimation (within 15 ms, >100 FPS), with an additional forward-prediction module that achieves zero-latency feedback, and a dynamic-cropping mode that allows for higher inference speeds. We also provide three options for using this tool with ease: (1) a stand-alone GUI (calledDLC-Live! GUI), and integration into (2)Bonsaiand (3)AutoPilot. Lastly, we benchmarked performance on a wide range of systems so that experimentalists can easily decide what hardware is required for their needs.
Distinguishing Critical, Beneficial, Neutral and Harmful Mutations Uncovered in the Directed Evolution of a Yeast Membrane Receptor
Authors: Adeniran Adebola , Tyo Keith E.J. 
Published: August 2020

AbstractWe present a reversion analysis of mutations introduced during the directed evolution of the yeast G-protein coupled receptor (GPCR) Ste2p to detect a peptide biomarker of chronic kidney disease. Two mutated receptors are analyzed in this study. Mutations acquired during directed evolution were reverted one at a time to the wild-type residue to assess the mutation’s contribution to receptor function. Mutations in the first and fifth transmembrane regions, the second intracellular loop and a truncation were found to be crucial for sensitive detection of the peptide biomarker. Some mutations acquired during directed evolution were found to be neutral to or harmful for biomarker detection. Mutations were also assessed for their contributions to increasing basal activity of the evolved receptors. A similar set of crucial mutations were found in the two receptors, implying a similar mechanism detection. The mutations are reasoned to appear to give the ability to detect a smaller sized peptide, affect interaction with the G-protein and allow for prolonged signaling after stimulation. These data should provide guidance for further engineering of Ste2p and other GPCRs.
A Deep Learning Framework for Predicting Human Essential Genes by Integrating Sequence and Functional data
Authors: Zhang Xue , Xiao Weijia , Xiao Wangxin 
Published: August 2020

ABSTRACTEssential genes are necessary to the survival or reproduction of a living organism. The prediction and analysis of gene essentiality can advance our understanding to basic life and human diseases, and further boost the development of new drugs. Wet lab methods for identifying essential genes are often costly, time consuming, and laborious. As a complement, computational methods have been proposed to predict essential genes by integrating multiple biological data sources. Most of these methods are evaluated on model organisms. However, prediction methods for human essential genes are still limited and the relationship between human gene essentiality and different biological information still needs to be explored. In addition, exploring suitable deep learning techniques to overcome the limitations of traditional machine learning methods and improve the prediction accuracy is also important and interesting. We propose a deep learning based method, DeepSF, to predict human essential genes. DeepSF integrates sequence features derived from DNA and protein sequence data with features extracted or learned from different types of functional data, such as gene ontology, protein complex, protein domain, and protein-protein interaction network. More than 200 features from these biological data are extracted/learned which are integrated together to train a cost-sensitive deep neural network by utilizing multiple deep leaning techniques. The experimental results of 10-fold cross validation show that DeepSF can accurately predict human gene essentiality with an average AUC of 95.17%, the area under precision-recall curve (auPRC) of 92.21%, the accuracy of 91.59%, and the F1 measure about 78.71%. In addition, the comparison experimental results show that DeepSF significantly outperforms several popular traditional machine learning models (SVM, Random Forest, and Adaboost), and performs slightly better than a recent deep learning model (DeepHE). We have demonstrated that the proposed method, DeepSF, is effective for predicting human essential genes. Deep learning techniques are promising at both feature learning and classification levels for the task of essential gene prediction.
Pregnancy success in mice requires appropriate cannabinoid receptor signaling for primary decidua formation
Authors: Li Yingju , Dewar Amanda , Kim Yeonsun , Dey Sudhansu K. , Sun Xiaofei 
Published: August 2020

AbstractAn early event after implantation is stromal cell transformation to decidual cells (decidualization) that support embryo development. In mice, this process begins at the antimesometrial (AM) pole with differentiation of stromal cells into epithelial-like cells (epithelioid cells) surrounding the implantation chamber. This is an avascular zone called the primary decidual zone (PDZ), and considered to function as a transient, size-dependent permeable barrier to protect the embryo from maternal circulating harmful agents, including immunoglobulins, immune cells, microorganisms and other noxious agents. This zone forms on day 5 afternoon and becomes fully established on day 6 with the loss of the crypt epithelium. The PDZ gradually degenerates with the appearance of the secondary decidual zone (SDZ) around the PDZ that peaks on day 8 in mice. Decidualization is critical for early pregnancy in mice and humans. We show that cannabinoid/endocannabinoid signaling influences decidualization in early pregnancy. Mice deficient in two major cannabinoid receptors, CB1 and CB2, show compromised PDZ. We found that angiogenic factors are dysregulated inCnr1-/-Cnr2-/-mice with defective PDZs, resulting in the abnormal presence of blood vessels and macrophages in this zone; disruption of the PDZ compromises pregnancy outcomes. Using anin vitrodecidualization model, we found thatCnr1levels increase in mouse stromal cells and human uterine fibroblast (Huf) cells undergoing decidualization and that limiting CB1 signaling in these cell types suppresses decidualizationin vitro. Since endothelial cells expressCnr2and decidual cells expressCnr1, we hypothesize that angiogenic events driven by CB2 are integrated with CB1 in decidual cells, leading to proper PDZ formation, a critical step for pregnancy success.
Differential expression of starch and sucrose metabolic genes linked to varying biomass yield inMiscanthushybrids
Authors: De Vega Jose J , Peel Ned , Purdy Sarah J , Hawkins Sarah , Donnison Iain , Dyer Sarah , Farrar Kerrie 
Published: August 2020

ABSTRACTMiscanthusis a commercial lignocellulosic biomass crop owing to its high biomass productivity and low chemical input requirements. InterspecificMiscanthushybrids with high biomass yield were shown to have low concentrations of starch and sucrose but high concentrations of fructose. We performed a transcriptional RNA-seq analysis between selectedMiscanthushybrids with contrasting values for these phenotypes to clarify how these phenotypes are genetically controlled. We observed that genes directly involved in the synthesis and degradation of starch and sucrose were down-regulated in high yieldingMiscanthushybrids. At the same time, glycolysis and export of triose phosphates were up-regulated in high yieldingMiscanthushybrids. Our results evidence a direct relationship between high expression of essential enzymatic genes in the starch and sucrose pathways, high starch concentrations, and lower biomass production. The strong interconnectivity between genotype, chemotype and agronomic traits opens the door to use the expression of well-characterised genes in the starch and sucrose pathway for the early selection of high biomass yielding genotypes from largeMiscanthuspopulations.
Temperature Effect on Polymerase Fidelity
Authors: Xue Yuan , Braslavsky Ido , Quake Stephen R. 
Published: August 2020

AbstractThe discovery of extremophiles helped enable the development of groundbreaking technology such as polymerase chain reaction. Temperature variation is often an essential step of these technology platforms, but the effect of temperature on the error rate of polymerases from different origins is under-explored. Here, we applied high-throughput sequencing to profile the error rates of DNA polymerases from psychrophilic, mesophilic, and thermophilic origins with single-molecule resolution. We found that reaction temperature substantially increases substitution and deletion error rates of psychrophilic and mesophilic DNA polymerases. Our motif analysis shows that the substitution error profiles cluster according to phylogenetic similarity of polymerases, not reaction temperature, thus suggesting that reaction temperature increases global error rate of polymerases independent of sequence context. Intriguingly, we also found that the DNA polymerase I of a psychrophilic bacteria exhibits higher polymerization activity than its mesophilic ortholog across all temperature ranges, including down to −19°C which is well below the freezing temperature of water. Our results provide a useful reference for how reaction temperature, a crucial parameter of biochemistry, can affect DNA polymerase fidelity in organisms adapted to a wide range of thermal environments.
Phenological displacement is uncommon among sympatric angiosperms
Authors: Park Daniel S. , Breckheimer Ian K. , Ellison Aaron M. , Lyra Goia M. , Davis Charles C. 
Published: August 2020

AbstractInteractions between species can influence access to resources and successful reproduction. One possible outcome of such interactions is reproductive character displacement. Here, the similarity of reproductive traits – such as flowering time – among close relatives growing in sympatry differ more so than when growing apart. However, evidence for the overall prevalence and direction of this phenomenon, or the stability of such differences under environmental change, remains untested across large taxonomic and spatial scales. We apply data from tens of thousands of herbarium specimens to examine character displacement in flowering time across 110 animal-pollinated angiosperm species in the eastern USA. We demonstrate that the degree and direction of phenological displacement among co-occurring closely related species pairs varies tremendously. Overall, flowering time displacement in sympatry is not common. However, displacement is generally greater among species pairs that flower close in time, regardless of direction. We additionally identify that future climate change may alter the nature of phenological displacement among many of these species pairs. On average, flowering times of closely related species were predicted to shift further apart by the mid-21st century, which may have significant future consequences for species interactions and gene flow.
An elasticity-curvature illusion decouples cutaneous and proprioceptive cues in active exploration of soft objects
Authors: Xu Chang , Wang Yuxiang , Gerling Gregory J. 
Published: August 2020

AbstractOur sense of touch helps us encounter the richness of our natural world. Across a myriad of contexts and repetitions, we have learned to deploy certain exploratory movements in order to elicit perceptual cues that are optimal and efficient. Such cues help us assess an object’s roughness, or stickiness, or as in this case, its softness. Leveraging empirical experiments combined with computational modeling of skin deformation, we develop a perceptual illusion for softness, or compliance, where small-compliant and large-stiff spheres are indiscriminable. The elasticity-curvature illusion, however, becomes readily discriminable when explored volitionally. This tactile illusion is unique because it naturally decouples proprioceptive cues from those involving identical, cutaneous contact attributes. Furthermore, the illusion sheds light into exactly how we explore soft objects, i.e., by volitionally controlling force, to optimally elicit and integrate proprioceptive cues amidst illusory cutaneous contact.
An Efficient Vector-based CRISPR/Cas9 System in anOreochromis mossambicusCell Line using Endogenous Promoters
Authors: Hamar Jens , Kültz Dietmar 
Published: August 2020

AbstractCRISPR/Cas9 gene editing is effective in manipulating genetic loci in mammalian cell cultures and whole fish but efficient platforms applicable to fish cell lines are currently limited. Our initial attempts to employ this technology in fish cell lines using heterologous promoters or a ribonucleoprotein approach failed to indicate genomic alteration at targeted sites in a tilapia brain cell line (OmB). For potential use in a DNA vector approach, endogenous tilapia beta Actin (OmbAct), EF1 alpha (OmEF1a), and U6 (TU6) promoters were isolated. The strongest candidate promoter determined by EGFP reporter assay, OmEF1a, was used to drive constitutive Cas9 expression in a modified OmB cell line (Cas9-OmB1). Cas9-OmB1 cell transfection with vectors expressing gRNAs driven by the TU6 promoter achieved mutational efficiencies as high as 81% following hygromycin selection. Mutations were not detected using human and zebrafish U6 promoters demonstrating the phylogenetic proximity of U6 promoters as critical when used for gRNA expression. Sequence alteration to TU6 improved mutation rate and cloning efficiency. In conclusion, we report new tools for ectopic expression and a highly efficient, economical system for manipulation of genomic loci and evaluation of their causal relationship with adaptive cellular phenotypes by CRISPR/Cas9 gene editing in fish cells.
CIVET-Macaque: an automated pipeline for MRI-based cortical surface generation and cortical thickness in macaques
Authors: Lepage Claude , Wagstyl Konrad , Jung Benjamin , Seidlitz Jakob , Sponheim Caleb , Ungerleider Leslie , Wang Xindi , Evans Alan C. , Messinger Adam 
Published: August 2020

AbstractThe MNI CIVET pipeline for automated extraction of cortical surfaces and evaluation of cortical thickness fromin-vivohuman MRI has been extended for processing macaque brains. Processing is performed based on the NIMH Macaque Template (NMT), as the reference template, with the anatomical parcellation of the surface following the D99 and CHARM atlases. The modifications needed to adapt CIVET to the macaque brain are detailed. Results have been obtained using CIVET-macaque to process the anatomical scans of the 31 macaques used to generate the NMT and another 95 macaques from the PRIME-DE initiative. It is anticipated that the open usage of CIVET-macaque will promote collaborative efforts in data collection and processing, sharing, and automated analyses from which the non-human primate brain imaging field will advance.
Characterization of extracellular vesicles and synthetic nanoparticles with four orthogonal single-particle analysis platforms
Authors: Arab Tanina , Mallick Emily R. , Huang Yiyao , Dong Liang , Liao Zhaohao , Zhao Zezhou , Gololobova Olesia , Smith Barbara , Haughey Norman J. , Pienta Kenneth J. , Slusher Barbara S. , Tarwater Patrick M. , Tosar Juan Pablo , Zivkovic Angela M. , Vreeland Wyatt N. , Paulaitis Michael E. , Witwer Kenneth W. 
Published: August 2020

ABSTRACTWe compared four orthogonal technologies for sizing, counting, and phenotyping of extracellular vesicles (EVs) and synthetic particles. The platforms were: single-particle interferometric reflectance imaging sensing (SP-IRIS) with fluorescence, nanoparticle tracking analysis (NTA) with fluorescence, microfluidic resistive pulse sensing (MRPS), and nanoflow cytometry measurement (NFCM). EVs from the human T lymphocyte line H9 (high CD81, low CD63) and the promonocytic line U937 (low CD81, high CD63) were separated from culture conditioned medium (CCM) by differential ultracentrifugation (dUC) or a combination of ultrafiltration (UF) and size exclusion chromatography (SEC) and characterized by transmission electron microscopy (TEM) and Western blot (WB). Mixtures of synthetic particles (silica and polystyrene spheres) with known sizes and/or concentrations were also tested. MRPS and NFCM returned similar particle counts, while NTA detected counts approximately one order of magnitude lower for EVs, but not for synthetic particles. SP-IRIS events could not be used to estimate particle concentrations. For sizing, SP-IRIS, MRPS, and NFCM returned similar size profiles, with smaller sizes predominating (per power law distribution), but with sensitivity typically dropping off below diameters of 60 nm. NTA detected a population of particles with a mode diameter greater than 100 nm. Additionally, SP-IRIS, MRPS, and NFCM were able to identify at least three of four distinct size populations in a mixture of silica or polystyrene nanoparticles. Finally, for tetraspanin phenotyping, the SP-IRIS platform in fluorescence mode was able to detect at least two markers on the same particle, while NFCM detected either CD81 or CD63. Based on the results of this study, we can draw conclusions about existing single-particle analysis capabilities that may be useful for EV biomarker development and mechanistic studies.