bluuebunny/crossref_metadata_2025_split huggingface dataset:
Local Connectome Phenotypes Predict Social, Health, and Cognitive Factors
Authors: Powell Michael A. , Garcia Javier O. , Yeh Fang-Cheng , Vettel Jean M. , Verstynen Timothy 
Published: April 2017

AbstractThe unique architecture of the human connectome is defined initially by genetics and subsequently sculpted over time with experience. Thus, similarities in predisposition and experience that lead to similarities in social, biological, and cognitive attributes should also be reflected in the local architecture of white matter fascicles. Here we employ a method known as local connectome fingerprinting that uses diffusion MRI to measure the fiber-wise characteristics of macroscopic white matter pathways throughout the brain. This fingerprinting approach was applied to a large sample (N=841) of subjects from the Human Connectome Project, revealing a reliable degree of between-subject correlation in the local connectome fingerprints, with a relatively complex, low-dimensional substructure. Using a cross-validated, high-dimensional regression analysis approach, we derived local connectome phenotype (LCP) maps that could reliably predict a subset of subject attributes measured, including demographic, health and cognitive measures. These LCP maps were highly specific to the attribute being predicted but also sensitive to correlations between attributes. Collectively, these results indicate that the local architecture of white matter fascicles reflects a meaningful portion of the variability shared between subjects along several dimensions.Author SummaryThe local connectome is the pattern of fiber systems (i.e., number of fibers, orientation, and size) within a voxel and reflects the proximal characteristics of white matter fascicles distributed throughout the brain. Here we show how variability in the local connectome is correlated in a principled way across individuals. This inter-subject correlation is reliable enough that unique phenotype maps can be learned to predict between-subject variability in a range of social, health, and cognitive attributes. This work shows, for the first time, how shared variability across individuals is reflected in the local connectome.
Intra-protein binding peptide fragments have specific and intrinsic sequence patterns
Authors: Wang Yuhong , Huang Junzhou , Li Wei , Wang Sheng , Ding Chuanfan 
Published: April 2017

AbstractThe key finding in the DNA double helix model is the specific pairing or binding between nucleotides A-T and C-G, and the pairing rules are the molecule basis of genetic code. Unfortunately, no such rules have been discovered for proteins. Here we show that similar rules and intrinsic sequence patterns between intra-protein binding peptide fragments do exist, and they can be extracted using a deep learning algorithm. Multi-millions of binding and non-binding peptide fragments from currently available protein X-ray structures are classified with an accuracy of up to 93%. This discovery has the potential in helping solve protein folding and protein-protein interaction problems, two open and fundamental problems in molecular biology.One Sentence SummaryClassification of binding and non-binding intra-protein peptide fragments using feed-forward neural network
Ultrasensitivity and Fluctuations in the Barkai-Leibler Model of Chemotaxis Receptors inEscherichia coli
Authors: Roy Ushasi , Gopalakrishnan Manoj 
Published: April 2017

AbstractA stochastic version of the Barkai-Leibler model of chemotaxis receptors inEscherichia coliis studied here with the goal of elucidating the effects of intrinsic network noise in their conformational dynamics. The model was originally proposed to explain the robust and near-perfect adaptation ofE. coliobserved across a wide range of spatially uniform attractant/repellent (ligand) concentrations. In the model, a receptor is either active or inactive and can stochastically switch between the two states. The enzyme CheR methylates inactive receptors while CheB demethylates active receptors and the probability for a receptor to be active depends on its level of methylation and ligand occupation. In a simple version of the model with two methylation sites per receptor (M= 2), we show rigorously, under a quasi-steady state approximation, that the mean active fraction of receptors is an ultrasensitive function of [CheR]/[CheB] in the limit of saturating receptor concentration. Hence the model shows zero-order ultrasensitivity (ZOU), similar to the classical two-state model of covalent modification studied by Goldbeter and Koshland (GK). We also find that in the limits of extremely small and extremely large ligand concentrations, the system reduces to two different two-state GK modules. A quantitative measure of the spontaneous fluctuations in activity is provided by the variancein the active fraction, which is estimated mathematically under linear noise approximation (LNA). It is found thatpeaks near the ZOU transition. The variance is a non-monotonic, but weak function of ligand concentration and a decreasing function of receptor concentration. Gillespie simulations are also performed in models withM= 2, 3 and 4. ForM= 2, simulations show excellent agreement with analytical results obtained under LNA. Numerical results forM= 3 andM= 4 are qualitatively similar to our mathematical results inM= 2; while all the models show ZOU in mean activity, the variance is found to be smaller for largerM. The magnitude of receptor noise deduced from available experimental data is consistent with our predictions. A simple analysis of the downstream signaling pathway shows that this noise is large enough to affect the motility of the organism, and may have a beneficial effect on it. The response of mean receptor activity to small time-dependent changes in the external ligand concentration is computed within linear response theory, and found to have a bilobe form, in agreement with earlier experimental observations.
The development of scientific consensus: analyzing conflict and concordance among Avian phylogenies
Authors: Brown Joseph W. , Wang Ning , Smith Stephen A. 
Published: April 2017

AbstractRecent developments in phylogenetic methods and data acquisition have allowed for the construction of large and comprehensive phylogenetic relationships. Published phylogenies represent an enormous resource that not only facilitate the resolution of questions related to comparative biology, but also provide a resource on which to gauge the development of consensus across the tree of life. From the Open Tree of Life, we gathered 290 avian phylogenies representing all major groups that have been published over the last few decades and analyzed how concordance and conflict develop among these trees through time. Nine large scale backbone trees (including a new synthetic tree from this study) were used for the consensus assessment. We found that conflicts were over-represented both along the backbone (higher-level neoavian relationships) and within the oscine Passeriformes. Importantly, although we have made major strides in our knowledge of major clades, recent published comprehensive trees, as well as trees of individual clades, continue to contribute significantly to the resolution of clades in the avian phylogeny. These findings are somewhat unexpected, given that birds constitute a relatively well-studied and small clade of the tree of life (i.e., Aves). Therefore, our analysis highlights that much work is still needed before we can confidently resolve the less well studied areas of the tree of life.
Bidirectional and context-dependent changes in theta and gamma oscillatory brain activity in noradrenergic cell-specificHypocretin/Orexin receptor 1-KO mice
Authors: Li Sha , Franken Paul , Vassalli Anne 
Published: April 2017

AbstractNoradrenaline (NA) and hypocretins/orexins (HCRT), and their receptors, dynamically modulate the circuits that configure behavioral states, and their associated oscillatory activities. Salient stimuli activate spiking of locus coeruleus noradrenergic (NALC) cells, inducing NA release and brain-wide noradrenergic signalling, thus resetting network activity, and mediating an orienting response. Hypothalamic HCRT neurons provide one of the densest input to NALCcells. To functionally address the HCRT-to-NA connection, we selectively disrupted theHcrtr1gene in NA neurons, and analyzed resulting (Hcrtr1Dbh-CKO) mice’, and their control littermates’ electrocortical response in several contexts of enhanced arousal. Under enforced wakefulness (EW), or after cage change (CC),Hcrtr1Dbh-CKOmice exhibited a weakened ability to lower infra-θ frequencies (1-7 Hz), and mount a robust, narrow-bandwidth, high-frequency θ rhythm (~8.5 Hz). A fast-γ (55-80 Hz) response, whose dynamics closely parallelled θ, also diminished, while β/slow-γ activity (15-45 Hz) increased. Furthermore, EW-associated locomotion was lower. Surprisingly, nestbuilding-associated wakefulness, inversely, featured enhanced θ and fast-γ activities. Thus HCRT-to-NA signalling may fine-tune arousal, up in alarming conditions, and down during self-motivated, goal-driven behaviors. Lastly, slow-wave-sleep following EW and CC, but not nestbuilding, was severely deficient in slow-δ waves (0.75-2.25 Hz), suggesting that HCRT-to-NA signalling regulates the slow-δ rebound characterizing sleep after stress-associated arousal.
Unbiased definition of a shared T-cell receptor motif enables population-based studies of tuberculosis
Authors: DeWitt W. S. , Quan K. K. , Wilburn D. , Sherwood A. , Vignali M. , De Rosa S. C. , Day C. L. , Scriba T. J. , Robins H. S. , Swanson W. , Emerson R. O. , Seshadri C. 
Published: April 2017

ABSTRACTPeptide-specific T cells that are restricted by highly polymorphic major histocompatibility complex (MHC) proteins express diverse T-cell receptors (TCRs) that are rarely shared among unrelated individuals. T-cells can also recognize bacterial lipid antigens that bind the relatively non-polymorphic CD1 family of proteins. However, genetic variation in human CD1 genes and TCR diversity expressed by CD1-restricted T-cells have not been quantitatively determined. Here, we show that CD1B is nearly nucleotide-identical across all five continental ancestry groups, providing evidence for purifying selection during human evolution. We used CD1B tetramers loaded with a mycobacterial glycolipid antigen to isolate T-cells from four genetically unrelated South African adults and cataloged thousands of TCRs fromin-vitroexpanded T-cells using immunosequencing. We identified highly conserved motifs that were co-expressed as a functional heterodimer and significantly enriched among tetramer-positive T-cells sorted directly from peripheral blood. Finally, we show that frequencies of these TCR motifs are increased in the blood of patients with active tuberculosis compared to uninfected controls, a finding that is confirmed by ex-vivo frequencies of tetramer-positive T-cells determined by flow cytometry. These data provide a framework for unbiased definition of TCRs targeting lipid antigens, which can be tested for clinical associations independently of host genetic background.Brief SummaryWe used human genetics and immunosequencing to define a shared T-cell receptor motif that is specific for a mycobacterial lipid antigen and associated with tuberculosis independently of host genetic background.
The Virtual Mouse Brain: a computational neuroinformatics platform to study whole mouse brain dynamics
Authors: Melozzi Francesca , Woodman Marmaduke M. , Jirsa Viktor K. , Bernard Christophe 
Published: April 2017

AbstractConnectome-based modeling of large-scale brain network dynamics enables causal in silico interrogation of the brain’s structure-function relationship, necessitating the close integration of diverse neuroinformatics fields.Here we extend the open-source simulation software The Virtual Brain to whole mouse brain network modeling based on individual diffusion Magnetic Resonance Imaging (dMRI)-based or tracer-based detailed mouse connectomes. We provide practical examples on how to use The Virtual Mouse Brain to simulate brain activity, such as seizure propagation and the switching behavior of the resting state dynamics in health and disease.The Virtual Mouse Brain enables theoretically driven experimental planning and ways to test predictions in the numerous strains of mice available to study brain function in normal and pathological conditions.
Progressive Multiple Sequence Alignment with the Poisson Indel Process
Authors: Maiolo Massimo , Zhang Xiaolei , Gil Manuel , Anisimova Maria 
Published: April 2017

AbstractSequence alignment lies at the heart of many evolutionary and comparative genomics studies. However, the optimal alignment of multiple sequences is NP-hard, so that exact algorithms become impractical for more than a few sequences. Thus, state of the art alignment methods employ progressive heuristics, breaking the problem into a series of pairwise alignments guided by a phylogenetic tree. Changes between homologous characters are typically modelled by a continuous-time Markov substitution model. In contrast, the dynamics of insertions and deletions (indels) are not modelled explicitly, because the computation of the marginal likelihood under such models has exponential time complexity in the number of taxa. Recently, Bouchard-Côté and Jordan [PNAS (2012) 110(4):1160–1166] have introduced a modification to a classical indel model, describing indel evolution on a phylogenetic tree as a Poisson process. The model termed PIP allows to compute the joint marginal probability of a multiple sequence alignment and a tree in linear time. Here, we present an new dynamic programming algorithm to align two multiple sequence alignments by maximum likelihood in polynomial time under PIP, and apply it a in progressive algorithm. To our knowledge, this is the first progressive alignment method using a rigorous mathematical formulation of an evolutionary indel process and with polynomial time complexity.
Giantin knockout models reveal a feedback loop between Golgi function and glycosyltransferase expression
Authors: Stevenson Nicola L. , Bergen Dylan J. M. , Skinner Roderick E.H. , Kague Erika , Martin-Silverstone Elizabeth , Robson Brown Kate A. , Hammond Chrissy L. , Stephens David J. 
Published: April 2017

AbstractThe Golgi is the cellular hub for complex glycosylation, controlling accurate processing of complex proteoglycans, receptors, ligands, and glycolipids. Its structure and organisation is dependent on golgins, which tether cisternal membranes and incoming transport vesicles. Here we show that knockout of the largest golgin, giantin, leads to substantial changes in gene expression despite only limited effects on Golgi structure. Notably, 22 Golgi-resident glycosyltransferases, but not glycan processing enzymes or the ER glycosylation machinery, are differentially expressed following giantin ablation. This includes near-complete loss-of-function of GALNT3 in both mammalian cell and zebrafish models. Giantin knockout zebrafish exhibit hyperostosis and ectopic calcium deposits, recapitulating phenotypes of hyperphosphatemic familial tumoral calcinosis, a disease caused by mutations in GALNT3. These data reveal a new feature of Golgi homeostasis, the ability to regulate glycosyltransferase expression to generate a functional proteoglycome.Summary statementKnockout of giantin in a genome-engineered cell line and zebrafish models reveals the capacity of the Golgi to control its own biochemistry through changes in gene expression.
Single-Cell Genome Dynamics in Early Embryo Development: A Statistical Thermodynamics Approach
Authors: Giuliani Alessandro , Tsuchiya Masa , Yoshikawa Kenichi 
Published: April 2017

AbstractA statistical thermodynamics approach to the temporal development of biological regulation provides a phenomenological description of the dynamical behavior of genome expression in terms of autonomous self-organization with a critical transition (Self-Organized Criticality: SOC). In early mouse embryo development, the dynamical change in the self-organization of overall expression determineshow and whenreprogramming of the genome-expression state occurs. Reprogramming occurs via a transition state (climbing over an epigenetic landscape), where the critical-regulation pattern of the zygote state disappears. A critical transition is well captured in terms of the bimodality of expression ensembles, which reflects distinct thermodynamic states (critical states). These critical states exhibit a genome avalanche pattern: competition between order (scaling) and disorder (divergence) around a critical point. The genome avalanche in mouse embryo development, which is committed to erase a previous ordered state, reveals that the direction of early embryo single-cell development traverses the same steps as in differentiation, but in the opposite order of self-organization.
Scc2-mediated loading of cohesin onto chromosomes in G1 yeast cells is insufficient to build cohesion during S phase
Authors: Nasmyth Kim A 
Published: April 2017

SummarySister chromatids are held together from their replication until mitosis. Sister chromatid cohesion is mediated by the ring-shaped cohesin complex and it is thought that cohesin holds sister chromatids together by entrapping sister DNAs within the cohesin ring (Haering et al., 2008). However, how this occurs is not well understood. Because cohesin binds to DNA prior to replication it is possible that the replication fork passes through the lumen of the ring thereby placing replicated sisters inside cohesin rings. If this is the case, loading of cohesin in the G1 phase may be sufficient to build cohesion.We show here that Scc2, a cohesin subunit required for loading cohesin onto chromosomesde novo, is necessary for establishment of cohesion even after Scc2-mediated loading has already taken place during late G1 or early S phase. Our results challenge a previous conclusion based on related experiments whereby Scc2 was found not to be required for cohesion establishment during S phase (Lengronne et al., 2006).
Spatial structure of synchronized inhibition in the olfactory bulb
Authors: Arnson Hannah A. , Strowbridge Ben W. 
Published: April 2017

AbstractOlfactory sensory input is detected by receptor neurons in the nose which then send information to the olfactory bulb, the first brain region for processing olfactory information. Within the olfactory bulb, many local circuit interneurons, including axonless granule cells, function to facilitate fine odor discrimination. How interneurons interact with principal cells to affect bulbar processing is not known though the mechanism is likely to be different than in sensory cortical regions since the olfactory bulb lacks an obvious topographical organization; neighboring glomerular columns, representing inputs from different receptor neuron subtypes, typically have different odor tuning. Determining the spatial scale over which interneurons such as granule cells can affect principal cells is a critical step towards understanding how the olfactory bulb operates. We addressed this question by assaying inhibitory synchrony using intracellular recordings from pairs of principal cells with different inter-somatic spacing. We find that in acute rat olfactory bulb slices, inhibitory synchrony is evident in the spontaneous synaptic input in mitral cells separated up to 300μm. At all inter-somatic spacing assayed, inhibitory synchrony was dependent on fast Na+channels, suggesting that action potentials in granule cells function to coordinate GABA release at relatively distant dendrodendritic synapses formed throughout the the dendritic arbor. Our results suggest that individual granule cells are able to influence relatively large groups of mitral and tufted cells belonging to clusters of at least 15 glomerular modules, providing a potential mechanism to integrate signals reflecting a wide variety of odorants.
Monitoring of thermal stresses in pressure components using inverse heat conduction methods
Authors: Taler Jan , Weglowski Bohdan , Pilarczyk Marcin 
Published: April 2017

Purpose
The purpose of this paper is to present a method for monitoring transient thermal stresses. This paper also presents the analysis of thermal stresses of boiler pressure element heating during the start-up in real conditions. The inverse methods are used to determine the wall temperature, whereas the commercial software ANSYS is used to determine the thermal stresses in the pressure component.

Design/methodology/approach
The method is based on the solution of the inverse heat conduction problem. Thermal stresses are determined indirectly taking into account the measured temperature values at selected points on the outer wall of a pressure component. First, the transient temperature distribution in the entire pressure element is calculated, and then, thermal stresses are determined by the finite element method. Measured pressure changes are used to determine the stresses resultant from the internal pressure.

Findings
The obtained stresses and temperature in the thick-walled pipe are illustrated and compared with experimental data. Satisfactory agreement was found between computational and experimental results.

Originality/value
The method can be used in the monitoring of thermal and mechanical stresses during the boiler’s start-up and shut-down. Because the temperature distribution at each time level is determined, it can be applied as a thermal load during the structural analysis.
Identification of the cancer ablation parameters during RF hyperthermia using gradient, evolutionary and hybrid algorithms
Authors: Paruch Marek 
Published: April 2017

Purpose
The purpose of this study is to show that the methods of the numerical simulation can be a very effective tool for a proper choice of control parameters of artificial hyperthermia. An electromagnetic field induced by two external electrodes and a temperature field resulting from electrodes action in a 3D domain of biological tissue is considered. An important problem is the appropriate directing of heat in the region of tumor, so as to avoid damaging healthy cells surrounding the tumor. Recently, to concentrate the heat on the tumor, magnetic nanoparticles, which are introduced into the tumor, were used. The nanoparticles should be made of material that ensures appropriate magnetic properties and has a high biocompatibility with the biological tissue. External electric field causes the heat generation in the tissue domain.

Design/methodology/approach
The distribution of electric potential in the domain considered is described by the Laplace system of equations, while the temperature field is described by the Pennes’ system of equations. These problems are coupled by source function being the additional component in the Pennes’ equation and resulting from the electric field action. The boundary element method is applied to solve the coupled problem connected with the heating of biological tissues.

Findings
The aim of investigations is to determine an electric potential of external electrodes and the number of nanoparticles introduced to a tumor region to obtain the artificial hyperthermia state. The tests performed showed that the proposed tool to solve the inverse problem provides correct results.

Research limitations/implications
In the paper the steady state bioheat transfer problem is considered, so the thermal damage is a function of the temperature only. Therefore, the solution can be considered as the maximum ablation zone of cancer. Additionally, the choice of appropriate parameters will be affected on the position and shape of the tumor and the electrodes.

Originality/value
In the paper the inverse problem has been solved using the evolutionary algorithm, gradient method and hybrid algorithm which is a combination of the two previous.