bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modulation of Individual Alpha Frequency with tACS shifts Time Perception
Authors: Mioni G. , Shelp A. , Stanfield-Wiswell C. T. , Gladhill K. A. , Bader F. , Wiener M. 
Published: July 2020

ABSTRACTPrevious studies have linked brain oscillation and timing, with evidence suggesting that alpha oscillations (10Hz) may serve as a “sample rate” for the visual system. However, direct manipulation of alpha oscillations and time perception has not yet been demonstrated. Eighteen subjects performed a time generalization task with visual stimuli. Participants first learned the standard intervals (600 ms) and then were required to judge the new temporal intervals if they were equal or different compared to the standard. Additionally, we had previously recorded resting-state EEG from each subject and calculated their Individual Alpha Frequency (IAF), estimated as the peak frequency from the mean spectrum over posterior electrodes between 8 and 13 Hz. After learning the standard interval, participants performed the time generalization task while receiving occipital transcranial Alternating Current Stimulation (tACS). Crucially, for each subject, tACS was administered at their IAF or at off-peak alpha frequencies (IAF±2 Hz). Results demonstrated a linear shift in the psychometric function indicating a modification of perceived duration, such that progressively “faster” alpha stimulation led to longer perceived intervals. These results provide the first evidence that direct manipulations of alpha oscillations can shift perceived time in a manner consistent with a clock speed effect.
A termination-independent role of Rat1 in cotranscriptional splicing
Authors: Dhoondia Zuzer , Elewa Hesham , Malik Marva , Arif Zahidur , Pique-Regi Roger , Ansari Athar 
Published: July 2020

AbstractThe yeast termination factor Rat1, and its human homolog Xrn2, have been implicated in multiple nuclear processes. Here we report a novel role of Rat1 in mRNA splicing. Rat1 mutants display increased levels of unspliced transcripts. Accumulation of unspliced transcripts was not due to a failure to degrade unspliced mRNA, disruption of termination or an increased elongation rate in Rat1 mutants. ChIP-Seq analysis revealed Rat1 crosslinking to the introns of a subset of yeast genes. Mass spectrometry and coimmunoprecipitation revealed interaction of Rat1 with the Clf1, Isy1, Yju2, Prp43, and Sub2 splicing factors. Furthermore, recruitment of the Prp2 splicing factor on the intron was compromised in the Rat1 mutant. Based on these findings we propose that Rat1 has a novel role in splicing of a subset of mRNA in budding yeast.
Lineage specific transcription factor waves reprogram neuroblastoma from self-renewal to differentiation
Authors: Banerjee Deblina , Gryder Berkley , Bagchi Sukriti , Liu Zhihui , Chen Hsien-Chao , Xu Man , Sun Ming , Vaksman Zalman , Diskin Sharon J. , Khan Javed , Thiele Carol J 
Published: July 2020

AbstractTemporal regulation of super-enhancer (SE) driven lineage specific transcription factors (TFs) underlies normal developmental programs. Neuroblastoma (NB) arises from an inability of sympathoadrenal progenitors to exit a self-renewal program and terminally differentiate. To identify critical SEs driving TF regulators of NB, we utilized NB cells in which all-trans retinoic acid (ATRA) induces growth arrest and differentiation. H3K27ac ChIP-seq paired with RNA-seq over a time course of ATRA treatment revealed SEs moving in a coordinated manner with four distinct temporal patterns (clusters). SEs that decreased with ATRA linked to 24 TFs involved in stem cell development/specialization (MYCN, GATA3, SOX11)along withLMO1, a transcriptional coregulator and oncogene identified via a genome-wide association study (GWAS) of NB. H3K27ac levels and GATA3 binding at the NB-associated rs2168101 site of the LMO1 SE were reduced with ATRA treatment, resulting in 1.46 fold decreasedLMO1expression. The SOX11 SE was lost coincident with a 50% decrease in mRNA after 8 days of ATRA treatment. CRISPR-Cas9 screening and siRNA inhibition showed a dependency on SOX11 for cell growth in NB cell lines. Silencing of the SOX11 SE using dCAS9-KRAB targeted guides caused a 40% decrease inSOX11mRNA and inhibited cell growth. Three other TF SE clusters had sequential waves of activation at 2, 4 and 8 days of ATRA treatment and involved TFs regulating neural development (GATA2andSOX4). Silencing of the gained SOX4 SE using dCAS9-KRAB targeting, caused a 50% decrease in SOX4 expression and attenuated expression of ATRA-induced differentiation genes. Our study has identified candidate oncogenic lineage drivers of NB self-renewal and TFs critical for implementing a differentiation program.
Immuno-informatics approach for multi-epitope vaccine designing against SARS-CoV-2
Authors: Banerjee Souvik , Majumder Kaustav , Gutierrez Gerardo Jose , Gupta Debkishore , Mittal Bharti 
Published: July 2020

AbstractThe novel Corona Virus Disease 2019 (COVID-19) pandemic has set the fatality rates ablaze across the world. So, to combat this disease, we have designed a multi-epitope vaccine from various proteins of Severe Acute Respiratory Syndrome Corona virus 2 (SARS-CoV-2) with an immuno-informatics approach, validated in silico to be stable, non-allergic and antigenic. Cytotoxic T-cell, helper T-cell, and B-cell epitopes were computationally predicted from six conserved protein sequences among four viral strains isolated across the world. The T-cell epitopes, overlapping with the B-cell epitopes, were included in the vaccine construct to assure the humoral and cell-mediated immune response. The beta-subunit of cholera toxin was added as an adjuvant at the N-terminal of the construct to increase immunogenicity. Interferon-gamma inducing epitopes were even predicted in the vaccine. Molecular docking and binding energetics studies revealed strong interactions of the vaccine with immune-stimulatory toll-like receptors (TLR) −2, 3, 4. Molecular dynamics simulation of the vaccine ensured in vivo stability in the biological system. The immune simulation of vaccine evinced elevated immune response. The efficient translation of the vaccine in an expression vector was assured utilizing in silico cloning approach. Certainly, such a vaccine construct could reliably be effective against COVID-19.
Annotation of Chromatin States in 66 Complete Mouse Epigenomes During Development
Authors: van der Velde Arjan , Fan Kaili , Tsuji Junko , Moore Jill , Purcaro Michael , Pratt Henry , Weng Zhiping 
Published: July 2020

ABSTRACTThe morphologically and functionally distinct cell types of a multicellular organism are maintained by epigenomes and gene expression programs. Phase III of the ENCODE Project profiled 66 mouse epigenomes across twelve tissues at daily intervals from embryonic day 10.5 to birth. Applying the ChromHMM algorithm to these epigenomes, we annotated eighteen chromatin states with characteristics of promoters, enhancers, transcribed regions, repressed regions, and quiescent regions throughout the developmental time course. Our integrative analyses delineate the tissue specificity and developmental trajectory of the loci in these chromatin states. Approximately 0.3% of each epigenome is assigned to a bivalent chromatin state, which harbors both active marks and the repressive mark H3K27me3. Highly evolutionarily conserved, these loci are enriched in silencers bound by Polycomb Repressive Complex proteins and the transcription start sites of their silenced target genes. This collection of chromatin state assignments provides a useful resource for studying mammalian development.
Decreasing alertness modulates perceptual decision-making
Authors: Jagannathan Sridhar R. , Bareham Corinne A. , Bekinschtein Tristan A. 
Published: July 2020

ABSTRACTThe ability to make decisions based on external information, prior knowledge and evidence, is a crucial aspect of cognition and may determine the success and survival of an organism. Despite extensive work on decision-making mechanisms/models, understanding the effects of alertness on neural and cognitive processes remain limited. Here we use electroencephalography and behavioural modelling to characterise cognitive and neural dynamics of perceptual decision-making in awake/low alertness periods in humans (14 male, 18 female) and characterise the compensatory mechanisms as alertness decreases. Well-rested human participants, changing between full-wakefulness and low alertness, performed an auditory tone-localisation task and its behavioural dynamics was quantified with psychophysics, signal detection theory and drift-diffusion modelling, revealing slower reaction times, inattention to the left side of space, and a lower rate of evidence accumulation in periods of low alertness. Unconstrained multivariate pattern analysis (decoding) showed a ~280ms delayed onset driven by low alertness of the neural signatures differentiating between left and right decision, with a spatial reconfiguration from centro-parietal to lateral frontal regions 150-360ms. To understand the neural compensatory mechanisms with decreasing alertness, we connected the evidence-accumulation behavioural parameter to the neural activity, showing in the early periods (125-325ms) a shift in the associated patterns from right parietal regions in awake, to right fronto-parietal during low alertness. This change in the neurobehavioural dynamics for central accumulation related cognitive processes define a clear reconfiguration of the brain networks’ regions and dynamics needed for the implementation of decision-making, revealing mechanisms of resilience of cognition when challenged by decreased alertness.Significance statementMost living organisms make multiple daily decisions and these require a degree of evidence from both the environment and the internal milieu. Such decisions are usually studied under sequential sampling models and involve making a behavioural choice based on sensory encoding, central accumulation, and motor implementation processes. Since there is little research on how decreasing alertness affects such cognitive processes, this study has looked at the cognitive and neural dynamics of perceptual decision-making in people while fully awake and in drowsy periods. Using computational modelling of behaviour and neural dynamics on human participants performing an auditory tone-localisation task, we reveal how low alertness modulates evidence accumulation related processes and its corresponding compensatory neural signatures.
Vast amounts of encoded items nullify but do not reverse the effect of sleep on declarative memory
Authors: Kolibius Luca D. , Born Jan , Feld Gordon B. 
Published: July 2020

AbstractSleep strengthens memories by repeatedly reactivating associated neuron ensembles. Our studies show that although long-term memory for a medium number of word-pairs (160) benefits from sleep, a large number (320) does not. This suggest an upper limit to the amount of information that has access to sleep-dependent declarative memory consolidation, which is possibly linked to the availability of reactivation opportunities. Due to competing processes of global forgetting that are active during sleep, we hypothesised that even larger amounts of information would enhance the proportion of information that is actively forgotten during sleep. In the present study, we aimed to induce such forgetting by challenging the sleeping brain with vast amounts of to be remembered information. For this, 80 participants learned a very large number of 640 word-pairs over the course of an entire day and then either slept or stayed awake during the night. Recall was tested after another night of regular sleep. Results revealed comparable retention rates between the sleep and wake groups. Although this null-effect can be reconciled the concept of limited capacities available for sleep-dependent consolidation, it contradicts our hypothesis that sleep would increase forgetting compared to the wake group. Additional exploratory analyses relying on equivalence testing and Bayesian statistics reveal that there is evidence against sleep having a detrimental effect on the retention of declarative memory at high information loads. We argue that forgetting occurs in both wake and sleep states through different mechanisms, i.e., through increased interference and through global synaptic downscaling, respectively. Both of these processes might scale similarly with information load.
ZNF416 is a pivotal transcriptional regulator of fibroblast mechano-activation
Authors: Jones Dakota L. , Meridew Jeffrey A. , Ducharme Merrick T. , Lydon Katherine L. , Choi Kyoung Moo , Caporarello Nunzia , Tan Qi , Link Patrick A. , Espinosa Ana Maria Diaz , Xiong Yuning , Lee Jeong-Heon , Ye Zhenqing , Yan Huihuang , Ordog Tamas , Ligresti Giovanni , Varelas Xaralabos , Tschumperlin Daniel J. 
Published: July 2020

AbstractMatrix stiffness is a central regulator of fibroblast function. However, the transcriptional mechanisms linking matrix stiffness to changes in fibroblast phenotype are incompletely understood. Here, we evaluated the effect of matrix stiffness on genome-wide chromatin accessibility in freshly-isolated lung fibroblasts using assay for transposase-accessible chromatin followed by sequencing (ATAC-seq). We found higher matrix stiffness profoundly increased global chromatin accessibility relative to lower matrix stiffness, and these alterations were in close genomic proximity to known pro-fibrotic gene programs. Motif analysis of these regulated genomic loci identified ZNF416 as a putative mediator of fibroblast stiffness responses. Similarly, motif analysis of the promoters of differentially expressed genes observed in freshly sorted fibroblasts from an experimental bleomycin lung fibrosis model also identified ZNF416 as a putative mediator ofin vivofibroblast activation. Genome occupancy analysis using chromatin-immunoprecipitation followed by sequencing (ChIP-seq) confirmed that ZNF416 occupies a broad range of genes implicated in fibroblast activation and tissue-fibrosis, with relatively little overlap in genomic occupancy with other mechanoresponsive and pro-fibrotic transcriptional regulators. Using loss and gain of function studies we demonstrated that ZNF416 plays a critical role in fibroblast proliferation, extracellular matrix synthesis and contractile function. Together these observations identify ZNF416 as novel mechano-activated transcriptional regulator of fibroblast biology.
Reconstructing feedback representations in ventral visual pathway with a generative adversarial autoencoder
Authors: Al-Tahan Haider , Mohsenzadeh Yalda 
Published: July 2020

AbstractWhile vision evokes a dense network of feedforward and feedback neural processes in the brain, visual processes are primarily modeled with feedforward hierarchical neural networks, leaving the computational role of feedback processes poorly understood. Here, we developed a generative autoencoder neural network model and adversarially trained it on a categorically diverse data set of images. We hypothesized that the feedback processes in the ventral visual pathway can be represented by reconstruction of the visual information performed by the generative model. We compared representational similarity of the activity patterns in the proposed model with temporal (magnetoencephalography) and spatial (functional magnetic resonance imaging) visual brain responses. The proposed generative model identified two segregated neural dynamics in the visual brain. A temporal hierarchy of processes transforming low level visual information into high level semantics in the feedforward sweep, and a temporally later dynamics of inverse processes reconstructing low level visual information from a high level latent representation in the feedback sweep. Our results append to previous studies on neural feedback processes by presenting a new insight into the algorithmic function and the information carried by the feedback processes in the ventral visual pathway.Author summaryIt has been shown that the ventral visual cortex consists of a dense network of regions with feedforward and feedback connections. The feedforward path processes visual inputs along a hierarchy of cortical areas that starts in early visual cortex (an area tuned to low level features e.g. edges/corners) and ends in inferior temporal cortex (an area that responds to higher level categorical contents e.g. faces/objects). Alternatively, the feedback connections modulate neuronal responses in this hierarchy by broadcasting information from higher to lower areas. In recent years, deep neural network models which are trained on object recognition tasks achieved human-level performance and showed similar activation patterns to the visual brain. In this work, we developed a generative neural network model that consists of encoding and decoding sub-networks. By comparing this computational model with the human brain temporal (magnetoencephalography) and spatial (functional magnetic resonance imaging) response patterns, we found that the encoder processes resemble the brain feedforward processing dynamics and the decoder shares similarity with the brain feedback processing dynamics. These results provide an algorithmic insight into the spatiotemporal dynamics of feedforward and feedback processes in biological vision.
Development of non-transgenic glyphosate tolerant wheat by TILLING
Authors: Moehs Charles P. , Austill William J. , Facciotti Daniel , Holm Aaron , Loeffler Dayna , Lu Zhongjin , Mullenberg Jessica C. , Slade Ann J. , Steine Michael N. , van Boxtel Jos , McGuire Cate 
Published: July 2020

AbstractGlyphosate (N-phosphonomethyl-glycine) is the world’s most widely used broad spectrum, post-emergence herbicide. It inhibits the chloroplast-targeted enzyme 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS; EC 2.5.1.19), a component of the plant and microorganism-specific shikimate pathway and a key catalyst in the production of aromatic amino acids. Variants of EPSPS that are not inhibited by glyphosate due to particular amino acid alterations in the active site of the enzyme are known. Some of these variants have been identified in weed species that have developed resistance to glyphosate because of the strong selective pressure of continuous, heavy glyphosate use. We have used TILLING (Targeting Induced Local Lesions in Genomes), a non-transgenic, target-selected, reverse genetics mutation breeding technique, and conventional genetic crosses, to identify and combine, through two rounds of mutagenesis, wheat lines having both T102I and P106S (so-called TIPS enzyme) mutations in both the A and the D sub-genome homoeologous copies of the wheat EPSPS gene. The combined effects of the T102I and P106S mutations are known from previous work in multiple species to minimize the binding of the herbicide while maintaining the affinity of the catalytic site for its native substrates. These novel wheat lines exhibit substantial tolerance to commercially relevant levels of glyphosate.
Protein sequence design by explicit energy landscape optimization
Authors: Norn Christoffer , Wicky Basile I. M. , Juergens David , Liu Sirui , Kim David , Koepnick Brian , Anishchenko Ivan , Players Foldit , Baker David , Ovchinnikov Sergey 
Published: July 2020

AbstractThe protein design problem is to identify an amino acid sequence which folds to a desired structure. Given Anfinsen’s thermodynamic hypothesis of folding, this can be recast as finding an amino acid sequence for which the lowest energy conformation is that structure. As this calculation involves not only all possible amino acid sequences but also all possible structures, most current approaches focus instead on the more tractable problem of finding the lowest energy amino acid sequence for the desired structure, often checking by protein structure prediction in a second step that the desired structure is indeed the lowest energy conformation for the designed sequence, and discarding the in many cases large fraction of designed sequences for which this is not the case. Here we show that by backpropagating gradients through the trRosetta structure prediction network from the desired structure to the input amino acid sequence, we can directly optimize over all possible amino acid sequences and all possible structures, and in one calculation explicitly design amino acid sequences predicted to fold into the desired structure and not any other. We find that trRosetta calculations, which consider the full conformational landscape, can be more effective than Rosetta single point energy estimations in predicting folding and stability of de novo designed proteins. We compare sequence design by landscape optimization to the standard fixed backbone sequence design methodology in Rosetta, and show that the results of the former, but not the latter, are sensitive to the presence of competing low-lying states. We show further that more funneled energy landscapes can be designed by combining the strengths of the two approaches: the low resolution trRosetta model serves to disfavor alternative states, and the high resolution Rosetta model, to create a deep energy minimum at the design target structure.SignificanceComputational protein design has primarily focused on finding sequences which have very low energy in the target designed structure. However, what is most relevant during folding is not the absolute energy of the folded state, but the energy difference between the folded state and the lowest lying alternative states. We describe a deep learning approach which captures the entire folding landscape, and show that it can enhance current protein design methods.