bluuebunny/crossref_metadata_2025_split huggingface dataset:
Decoding non-conscious thought representations during successful thought suppression
Authors: Koenig-Robert Roger , Pearson Joel 
Published: February 2020

AbstractControlling our own thoughts is central to mental wellbeing and its failure is at the crux of a number of mental disorders. Paradoxically, behavioural evidence shows that thought-suppression often fails. Despite the broad importance of understanding the mechanisms of thought control, little is known about the fate of neural representations of suppressed thoughts. Using functional MRI, we investigated the brain areas involved in controlling visual thoughts and tracked suppressed thought representations using multi-voxel pattern analysis (MVPA). Participants were asked to either visualize a vegetable/fruit or suppress any visual thoughts about those objects. Surprisingly, the content (object identity) of successfully suppressed thoughts was still decodable in visual and executive areas with algorithms trained on perception or imagery. This suggests that pictorial representations of the suppressed thoughts are still present despite individuals reporting they are not. Thought generation was associated with the left hemisphere, whereas thought suppression with right hemisphere engagement. Further, GLM analyses showed that subjective success in thought suppression was correlated with engagement of executive areas, while thought-suppression failure was associated with engagement of visual and memory related areas. These results reveal that the content of suppressed thoughts exist hidden from awareness, seemingly without an individual’s knowledge, providing a compelling reason why thought suppression is so ineffective. These data inform models of unconscious thought production and could be used to develop new treatment approaches to disorders involving maladaptive thoughts.
Algorithm for Extraction of Sub-Structure from Co-Crystallized PDB Ligand for Selective Targeting
Authors: Prakash Om 
Published: February 2020

ABSTRACTAn algorithm has been introduced for extraction of sub-structure from co-crystallized ligand of complex PDB file. Algorithm utilized location of atoms in 3D domain of complex of ligand & protein. It processed relative positioning of atoms for demarcation of influential part of ligand, which can provide potency to that ligand for binding with specific binding pocket of protein. Algorithm was validated with ligands co-crystallized with enzymes of different classes. Extracted sub-structures were validated (via evidence from database & literature) for selectivity towards one or more targets of same family.
Fluid flow-induced left-right asymmetric decay ofDand5mRNA in the mouse embryo requires Bicc1-Ccr4 RNA degradation complex
Authors: Minegishi Katsura , Rothé Benjamin , Komatsu Kaoru R. , Ono Hiroki , Ikawa Yayoi , Nishimura Hiromi , Miyashita Emi , Takaoka Katsuyoshi , Bando Kana , Kiyonari Hiroshi , Yamamoto Tadashi , Saito Hirohide , Constam Daniel B. , Hamada Hiroshi 
Published: February 2020

SUMMARYMolecular left-right (L-R) asymmetry is established at the node of the mouse embryo as a result of the sensing of a leftward fluid flow by immotile cilia of perinodal crown cells and the consequent degradation ofDand5mRNA on the left side. We here examined how the fluid flow inducesDand5mRNA decay. We found that the 3’ untranslated region (3’-UTR) ofDand5mRNA is necessary and sufficient for the left-sided decay and is responsive to the flow direction, loss of the cation channel Pkd2, and Ca2+. The 200-nucleotide proximal-most portion of the 3’-UTR, which is conserved among mammals, is essential for the asymmetric mRNA decay and binds Bicc1, an RNA binding protein specifically expressed at the node. Bicc1 preferentially recognizes GAC and GACR sequences in RNA, and these motifs are enriched in the 200-nucleotide region of theDand53’-UTR. The Cnot3 component of the Ccr4-Not deadenylase complex interacts with Bicc1 and is also required forDand5mRNA decay at the node. Our results thus suggest that leftward fluid flow induces binding of Bicc1 to the 3’-UTR ofDand5mRNA in crown cells on the left side of the node, and that consequent recruitment of Ccr4-Not mediates mRNA degradation.
Endogenous retroviruses drive KRAB zinc-finger family protein expression for tumor suppression
Authors: Ito Jumpei , Kimura Izumi , Soper Andrew , Coudray Alexandre , Koyanagi Yoshio , Nakaoka Hirofumi , Inoue Ituro , Turelli Priscilla , Trono Didier , Sato Kei 
Published: February 2020

AbstractNumerous genes are aberrantly expressed in tumors, but its cause remains unclear. Human endogenous retroviruses (HERVs) are repetitive elements in the genome and have a potential to work as enhancers modulating adjacent genes. Since numerous HERVs are activated epigenetically in tumors, their activation could alter gene expression globally in tumors and change the tumor characteristics. Here, we show the HERV activation in tumors is associated with the upregulation of hundreds of transcriptional suppressors, Krüppel-associated box domain-containing zinc-finger family proteins (KZFPs). KZFP genes are preferentially encoded nearby the activated HERVs in tumors and transcriptionally regulated by the adjacent HERVs. Increased HERV and KZFP expression in tumors was associated with better disease conditions. Many KZFPs could suppress the progressive characteristics of cancer cells by downregulating genes related to the cell cycle and cell-matrix adhesion. Our data suggest that HERV activation in tumors drives the concerted expression of KZFP genes for tumor suppression.
Candidate gene prioritization using graph embedding
Authors: Do Quan , Larmande Pierre 
Published: February 2020

AbstractCandidate genes prioritization allows to rank among a large number of genes, those that are strongly associated with a phenotype or a disease. Due to the important amount of data that needs to be integrate and analyse, gene-to-phenotype association is still a challenging task. In this paper, we evaluated a knowledge graph approach combined with embedding methods to overcome these challenges. We first introduced a dataset of rice genes created from several open-access databases. Then, we used the Translating Embedding model and Convolution Knowledge Base model, to vectorize gene information. Finally, we evaluated the results using link prediction performance and vectors representation using some unsupervised learning techniques.
A geometric basis for surface habitat complexity and biodiversity
Authors: Torres-Pulliza Damaris , Dornelas Maria A. , Pizarro Oscar , Bewley Michael , Blowes Shane A. , Boutros Nader , Brambilla Viviana , Chase Tory J. , Frank Grace , Friedman Ariell , Hoogenboom Mia O. , Williams Stefan , Zawada Kyle J. A. , Madin Joshua S. 
Published: February 2020

AbstractStructurally complex habitats tend to contain more species and higher total abundances than simple habitats. This ecological paradigm is grounded in first principles: species richness scales with area, and surface area and niche density increase with three-dimensional complexity. Here we present a geometric basis for surface habitats that unifies ecosystems and spatial scales. The theory is framed by fundamental geometric constraints among three structure descriptors—surface height, rugosity and fractal dimension—and explains 98% of surface variation in a structurally complex test system: coral reefs. We then show how coral biodiversity metrics (species richness, total abundance and probability of interspecific encounter) vary over the theoretical structure descriptor plane, demonstrating the value of the theory for predicting the consequences of natural and human modifications of surface structure.
Categorizing SHR and WKY rats by chi2 algorithm and decision tree
Authors: Tsai Ping-Rui , Chen Kun-Huang , Hong Tzay-Ming , Wang Fu-Nien , Huang Teng-Yi 
Published: February 2020

ABSTRACTIn the past two decades neuroscience has offered many popular methods for the analysis of mental disorder, such as seed-based analysis, ICA, and graph methods. They are widely used in the study of brain network. We offer a new procedure that can simplify the analysis and has a high ROC index over 0.9. This method uses the graph theory to build a connectivity network, which is characterized by degrees and measures the number of effective links for each voxel. When the degree is ranked from low to high, the network equation can be fit by the power-law distribution. It has been proposed that distinct and yet robust exponents of the power law can differentiate human behavior. Using the mentally disordered SHR and WKY rats as samples, we employ chi2 algorithm and Decision Tree to classify different states of mental disorder by analyzing different traits in degree of connectivity.
The properties of buried ion pairs are governed by the propensity of proteins to reorganize
Authors: Kougentakis Christos M. , Skerritt Lauren , Majumdar Ananya , Schlessman Jamie L. , García-Moreno E. Bertrand 
Published: February 2020

AbstractCharges are incompatible with the hydrophobic interior of proteins, yet proteins use buried charges, often in pairs or networks, to drive energy transduction processes, catalysis, pH-sensing, and ion transport. The structural adaptations necessary to accommodate interacting charges in the protein interior are not well understood. According to continuum electrostatic calculations, the Coulomb interaction between two buried charges cannot offset the highly unfavorable penalty of dehydrating two charges. This was investigated experimentally with two variants of staphylococcal nuclease (SNase) with Glu:Lys or Lys:Glu pairs introduce at internal i, i+4 positions on an α-helix. Contrary to expectations from previous theoretical and experimental studies, the proteins tolerated the charged ion pairs in both orientations. Crystal structures and NMR spectroscopy studies showed that in both variants, side chains or backbone are reorganized. This leads to the exposure of at least one of the two buried groups to water. Comparison of these ion pairs with a highly stable buried ion pair in SNase shows that the location and the amplitude of structural reorganization can vary dramatically between ion pairs buried in the same general region of the protein. The propensity of the protein to populate alternative conformation states in which internal charges can contact water appears to be the factor that governs the magnitude of electrostatic effects in hydrophobic environments. The net effect of structural reorganization is to weaken the Coulomb interactions between charge pairs; however, the reorganized protein no longer has to pay the energetic penalty for burying charges. These results provide the framework necessary to understand the interplay between the dehydration of charges, Coulomb interactions and protein reorganization that tunes the functional properties of proteins.
Equivolumetric protocol generates library sizes proportional to total microbial load in next-generation sequencing
Authors: Cruz Giuliano Netto Flores , Christoff Ana Paula , de Oliveira Luiz Felipe Valter 
Published: February 2020

AbstractNext-generation sequencing (NGS) has been extensively employed to perform microbiome characterization worldwide. As a culture-independent methodology, it has allowed high-level profiling of sample microbial composition. However, most studies are limited to information regarding relative bacterial abundances, ignoring scenarios in which sample microbe biomass can vary widely. Here, we develop an equivolumetric protocol for amplicon library preparation capable of generating NGS data responsive to input DNA, recovering proportionality between observed read counts and absolute bacterial abundances. Under specified conditions, we argue that the estimation of colony-forming units (CFU), the most common unit of bacterial abundance in classical microbiology, is challenged mostly by resolution and taxon-to-taxon variation. We propose Bayesian cumulative probability models to address such issues. Our results indicate that predictive errors vary consistently below one order of magnitude for observed bacteria. We also demonstrate our approach has the potential to generalize to previously unseen bacteria, but predictive performance is hampered by specific taxa of uncommon profile. Finally, it remains clear that NGS data are not inherently restricted to relative information only, and microbiome science can indeed meet the working scales of traditional microbiology.
Quantitative trait loci mapped for TCF21 binding, chromatin accessibility and chromosomal looping in coronary artery smooth muscle cells reveal molecular mechanisms of coronary disease loci
Authors: Zhao Quanyi , Dacre Michael , Nguyen Trieu , Pjanic Milos , Liu Boxiang , Iyer Dharini , Cheng Paul , Wirka Robert , Brian Kim Juyong , Fraser Hunter B , Quertermous Thomas 
Published: February 2020

AbstractBackgroundTo investigate the epigenetic and transcriptional mechanisms of coronary artery disease (CAD) risk, as well as the functional regulation of chromatin structure and function, we have created a catalog of genetic variants associated with three stages of transcriptionalcis-regulation in primary human coronary artery vascular smooth muscle cells (HCASMC).ResultsTo this end, we have used a pooling approach with HCASMC lines to map regulatory variation that mediates binding of the CAD associated transcription factor TCF21 with ChIPseq studies (bQTLs), variation that regulates chromatin accessibility with ATACseq studies (caQTLs), and chromosomal looping with HiC methods (clQTLs). We show significant overlap of the QTLs, and their relationship to smooth muscle specific genes and the binding of smooth muscle transcription factors. Further, we use multiple analyses to show that these QTLs are highly associated with CAD GWAS loci and correlated to lead SNPs in these loci where they show allelic effects. We have verified with genome editing that identified functional variants can regulate both chromatin accessibility and chromosomal looping, providing new insights into functional mechanisms regulating chromatin state and chromosomal structure. Finally, we directly link the disease associatedTGFβ1-SMAD3pathway to the CAD associatedFN1gene through a response QTL that modulates both chromatin accessibility and chromosomal looping.ConclusionsTogether, these studies represent the most thorough mapping of multiple QTL types in a highly disease relevant primary cultured cell type, and provide novel insights into their functional overlap and mechanisms that underlie these genomic features and their relationship to disease risk.
Re-evaluating the conventional wisdom about binding assays
Authors: Wilson Brandon D. , Soh H. Tom 
Published: February 2020

AbstractAnalytical technologies based on binding assays have evolved substantially since their inception nearly 60 years ago, but our conceptual understanding of molecular recognition has not kept pace. Indeed, contemporary technologies such as single-molecule and digital measurements have challenged, or even rendered obsolete, core aspects of the conventional wisdom related to binding assay design. Here, we explore the fundamental principles underlying molecular recognition systems, which we consider in terms of signals generated through concentration-dependent shifts in equilibrium. We challenge certain orthodoxies related to binding-based detection assays, including the primary importance of a lowKDand the extent to which this parameter constrains dynamic range and limit of detection. Lastly, we identify key principles for designing binding assays optimally suited for a given detection application.
Changes in the tumor microenvironment and treatment outcome in glioblastoma: A pilot study
Authors: Ali Sehar , Borin Thaiz F , Piranlioglu Raziye , Ara Roxan , Lebedyeva Iryna , Angara Kartik , Achyut Bhagelu R , Arbab Ali S. , Rashid Mohammad H 
Published: February 2020

AbstractGlioblastoma (GBM) is a hypervascular and aggressive primary malignant tumor of the central nervous system. Recent investigations showed that traditional therapies along with antiangiogenic therapies failed due to the development of post-therapy resistant and recurrent GBM. Our investigations show that there are changes in the cellular and metabolic compositions in the tumor microenvironment (TME). It can be said that tumor cell-directed therapies are ineffective and we need to rethink how to treat GBM.We hypothesize that the composition of TME-associated cells will be different based on the therapy and therapeutic agents, and TME-targeting therapy will be better to decrease recurrence and improve survival. Therefore, the purpose of this study is to determine the changes in the TME in respect of T-cell population, M1 and M2 macrophage polarization status, and MDSC population following different treatments in a syngeneic model of GBM. In addition to these parameters, tumor growth and survival were also studied following different treatments.The results showed that changes in the TME-associated cells were dependent on the therapeutic agents and the TME-targeting therapy improved the survival of the GBM bearing animals.The current GBM therapies should be revisited to add agents to prevent the accumulation of bone marrow-derived cells in the TME or to prevent the effect of immune-suppressive myeloid cells in causing alternative neovascularization, the revival of glioma stem cells, and recurrence. Instead of concurrent therapy, a sequential strategy would be best to target TME-associated cells.
Internally generated population activity in cortical networks hinders information transmission
Authors: Huang Chengcheng , Pouget Alexandre , Doiron Brent 
Published: February 2020

AbstractHow neuronal variability impacts neuronal codes is a central question in systems neuroscience, often with complex and model dependent answers. Most population models are parametric, with a tacitly assumed structure of neuronal tuning and population-wide variability. While these models provide key insights, they purposely divorce any mechanistic relationship between trial average and trial variable neuronal activity. By contrast, circuit based models produce activity with response statistics that are reflection of the underlying circuit structure, and thus any relations between trial averaged and trial variable activity are emergent rather than assumed. In this work, we study information transfer in networks of spatially ordered spiking neuron models with strong excitatory and inhibitory interactions, capable of producing rich population-wide neuronal variability. Motivated by work in the visual system we embed a columnar stimulus orientation map in the network and measure the population estimation of an orientated input. We show that the spatial structure of feedforward and recurrent connectivity are critical determinants for population code performance. In particular, when network wiring supports stable firing rate activity then with a sufficiently large number of decoded neurons all available stimulus information is transmitted. However, if the inhibitory projections place network activity in a pattern forming regime then the population-wide dynamics compromise information flow. In total, network connectivity determines both the stimulus tuning as well as internally generated population-wide fluctuations and thereby dictates population code performance in complicated ways where modeling efforts provide essential understanding.
Dissimilarity in sulcal width patterns in the cortex can be used to identify patients with schizophrenia with extreme deficits in cognitive performance
Authors: Janssen Joost , Díaz-Caneja Covadonga M. , Alloza Clara , Schippers Anouck , de Hoyos Lucía , Santonja Javier , Gordaliza Pedro M. , Buimer Elizabeth E.L. , van Haren Neeltje E.M. , Cahn Wiepke , Arango Celso , Kahn René S. , Hulshoff Pol Hilleke E. , Schnack Hugo G. 
Published: February 2020

AbstractSchizophrenia is a biologically complex disorder with multiple regional deficits in cortical brain morphology. In addition, interindividual heterogeneity of cortical morphological metrics is larger in patients with schizophrenia when compared to healthy controls. Exploiting interindividual differences in severity of cortical morphological deficits in patients instead of focusing on group averages may aid in detecting biologically informed homogeneous subgroups. The Person-Based Similarity Index (PBSI) of brain morphology indexes an individual’s morphometric similarity across numerous cortical regions amongst a sample of healthy subjects. We extended the PBSI such that it indexes morphometric similarity of an independent individual (e.g., a patient) with respect to healthy control subjects. By employing a normative modeling approach on longitudinal data, we determined an individual’s degree of morphometric dissimilarity to the norm. We calculated the PBSI for sulcal width (PBSI-SW) in patients with schizophrenia and healthy control subjects (164 patients, 164 healthy controls; 656 MRI scans) and associated it with cognitive performance and cortical sulcation index. A subgroup of patients with markedly deviant PBSI-SW showed extreme deficits in cognitive performance and cortical sulcation. Progressive reduction of PBSI-SW in the schizophrenia group relative to healthy controls was driven by these deviating individuals. By explicitly leveraging interindividual differences in severity of PBSI-SW deficits, neuroimaging-driven subgrouping of patients is feasible. As such, our results pave the way for future applications of morphometric similarity indices for subtyping of clinical populations.
Optoacoustic flow-cytometry with light scattering referencing
Authors: Seeger Markus , Stiel Andre C. , Ntziachristos Vasilis 
Published: February 2020

AbstractIn analogy to the development of fluorescent proteins, innovative tools for screening optoacoustic cell labels could lead to tailored protein labels for OA, imparting novel ways to visualize biological structure and function. Optoacoustic imaging emerges towards a highly promising modality for life sciences and medical practise with advantageous capabilities such as great accessible depth, and 3D studying of living tissue. The development of novel labels with molecular specificity could significantly enhance the optoacoustic contrast, specificity, and sensitivity and allow optoacoustic to interrogate tissues not amenable to the fluorescence method. We report on an optoacoustic flow cytometer (OAFC) prototype, developed for screening optoacoustic reporter genes. The cytometer concurrently records light scattering for referencing purposes. Since recording light scattering is completely independent from OA, we believe it to be a more reliable referencing method than e.g. fluorescence or ultrasound-backscatter. Precise characterization of our OAFC prototype showcases its ability to optoacoustically characterize objects in-flow that are in the size range of single cells. We apply the OAFC to distinguish individualE. colicells based on optoacoustic properties of their expressed chromoproteins read in-flow using microfluidic arrangements and achieved precisions over 90%. We discuss how the light scattering referenced OAFC method offers a critical step towards routine measurement of optoacoustic properties of single-cells and could pave the way for identifying genetically encoded optoacoustic reporters, by transferring working concepts of the fluorescence field.