Neural underpinnings of the identifiable victim effect: affect shifts preferences for giving.

Science.gov (United States)

Genevsky, Alexander; Västfjäll, Daniel; Slovic, Paul; Knutson, Brian

2013-10-23

The "identifiable victim effect" refers to peoples' tendency to preferentially give to identified versus anonymous victims of misfortune, and has been proposed to partly depend on affect. By soliciting charitable donations from human subjects during behavioral and neural (i.e., functional magnetic resonance imaging) experiments, we sought to determine whether and how affect might promote the identifiable victim effect. Behaviorally, subjects gave more to orphans depicted by photographs versus silhouettes, and their shift in preferences was mediated by photograph-induced feelings of positive arousal, but not negative arousal. Neurally, while photographs versus silhouettes elicited activity in widespread circuits associated with facial and affective processing, only nucleus accumbens activity predicted and could statistically account for increased donations. Together, these findings suggest that presenting evaluable identifiable information can recruit positive arousal, which then promotes giving. We propose that affect elicited by identifiable stimuli can compel people to give more to strangers, even despite costs to the self.

Identifying the cutting tool type used in excavations using neural networks

Energy Technology Data Exchange (ETDEWEB)

Jonak, J.; Gajewski, J. [Lublin University of Technology, Lublin (Poland). Faculty of Mechanical Engineering

2006-03-15

The paper presents results of preliminary research on utilising neural networks to identify excavating cutting tool's type used in multi-tool excavating heads of mechanical coal miners. Such research is necessary to identify rock excavating process with a given head, and construct adaptation systems for control of excavating process with such a head.

A Proteomics Approach to Identify New Putative Cardiac Intercalated Disk Proteins.

Directory of Open Access Journals (Sweden)

Siddarth Soni

Full Text Available Synchronous beating of the heart is dependent on the efficient functioning of the cardiac intercalated disk (ID. The ID is composed of a complex protein network enabling electrical continuity and chemical communication between individual cardiomyocytes. Recently, several different studies have shed light on increasingly prevalent cardiac diseases involving the ID. Insufficient knowledge of its composition makes it difficult to study these disease mechanisms in more detail and therefore here we aim expand the ID proteome. Here, using a combination of general membrane enrichment, in-depth quantitative proteomics and an intracellular location driven bioinformatics approach, we aim to discover new putative ID proteins in rat ventricular tissue.General membrane isolation, enriched amongst others also with ID proteins as based on presence of the established markers connexin-43 and n-cadherin, was performed using centrifugation. By mass spectrometry, we quantitatively evaluated the level of 3455 proteins in the enriched membrane fraction (EMF and its counterpart, the soluble cytoplasmic fraction. These data were stringently filtered to generate a final set of 97 enriched, putative ID proteins. These included Cx43 and n-cadherin, but also many interesting novel candidates. We selected 4 candidates (Flotillin-2 (FLOT2, Nexilin (NEXN, Popeye-domain-containg-protein 2 (POPDC2 and thioredoxin-related-transmembrane-protein 2 (TMX2 and confirmed their co-localization with n-cadherin in the ID of human and rat heart cryo-sections, and isolated dog cardiomyocytes.The presented proteomics dataset of putative new ID proteins is a valuable resource for future research into this important molecular intersection of the heart.

Application of particle swarm optimization to identify gamma spectrum with neural network

International Nuclear Information System (INIS)

Shi Dongsheng; Di Yuming; Zhou Chunlin

2007-01-01

In applying neural network to identification of gamma spectra back propagation (BP) algorithm is usually trapped to a local optimum and has a low speed of convergence, whereas particle swarm optimization (PSO) is advantageous in terms of globe optimal searching. In this paper, we propose a new algorithm for neural network training, i.e. combined BP and PSO optimization, or PSO-BP algorithm. Practical example shows that the new algorithm can overcome shortcomings of BP algorithm and the neural network trained by it has a high ability of generalization with identification result of 100% correctness. It can be used effectively and reliably to identify gamma spectra. (authors)

Exome sequencing in 53 sporadic cases of schizophrenia identifies 18 putative candidate genes.

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Michel Guipponi

Full Text Available Schizophrenia (SCZ is a severe, debilitating mental illness which has a significant genetic component. The identification of genetic factors related to SCZ has been challenging and these factors remain largely unknown. To evaluate the contribution of de novo variants (DNVs to SCZ, we sequenced the exomes of 53 individuals with sporadic SCZ and of their non-affected parents. We identified 49 DNVs, 18 of which were predicted to alter gene function, including 13 damaging missense mutations, 2 conserved splice site mutations, 2 nonsense mutations, and 1 frameshift deletion. The average number of exonic DNV per proband was 0.88, which corresponds to an exonic point mutation rate of 1.7×10(-8 per nucleotide per generation. The non-synonymous-to-synonymous mutation ratio of 2.06 did not differ from neutral expectations. Overall, this study provides a list of 18 putative candidate genes for sporadic SCZ, and when combined with the results of similar reports, identifies a second proband carrying a non-synonymous DNV in the RGS12 gene.

Identifying thematic roles from neural representations measured by functional magnetic resonance imaging.

Science.gov (United States)

Wang, Jing; Cherkassky, Vladimir L; Yang, Ying; Chang, Kai-Min Kevin; Vargas, Robert; Diana, Nicholas; Just, Marcel Adam

2016-01-01

The generativity and complexity of human thought stem in large part from the ability to represent relations among concepts and form propositions. The current study reveals how a given object such as rabbit is neurally encoded differently and identifiably depending on whether it is an agent ("the rabbit punches the monkey") or a patient ("the monkey punches the rabbit"). Machine-learning classifiers were trained on functional magnetic resonance imaging (fMRI) data evoked by a set of short videos that conveyed agent-verb-patient propositions. When tested on a held-out video, the classifiers were able to reliably identify the thematic role of an object from its associated fMRI activation pattern. Moreover, when trained on one subset of the study participants, classifiers reliably identified the thematic roles in the data of a left-out participant (mean accuracy = .66), indicating that the neural representations of thematic roles were common across individuals.

EST mining identifies proteins putatively secreted by the anthracnose pathogen Colletotrichum truncatum

Directory of Open Access Journals (Sweden)

Vandenberg Albert

2011-06-01

Full Text Available Abstract Background Colletotrichum truncatum is a haploid, hemibiotrophic, ascomycete fungal pathogen that causes anthracnose disease on many economically important leguminous crops. This pathogen exploits sequential biotrophic- and necrotrophic- infection strategies to colonize the host. Transition from biotrophy to a destructive necrotrophic phase called the biotrophy-necrotrophy switch is critical in symptom development. C. truncatum likely secretes an arsenal of proteins that are implicated in maintaining a compatible interaction with its host. Some of them might be transition specific. Results A directional cDNA library was constructed from mRNA isolated from infected Lens culinaris leaflet tissues displaying the biotrophy-necrotrophy switch of C. truncatum and 5000 expressed sequence tags (ESTs with an average read of > 600 bp from the 5-prime end were generated. Nearly 39% of the ESTs were predicted to encode proteins of fungal origin and among these, 162 ESTs were predicted to contain N-terminal signal peptides (SPs in their deduced open reading frames (ORFs. The 162 sequences could be assembled into 122 tentative unigenes comprising 32 contigs and 90 singletons. Sequence analyses of unigenes revealed four potential groups: hydrolases, cell envelope associated proteins (CEAPs, candidate effectors and other proteins. Eleven candidate effector genes were identified based on features common to characterized fungal effectors, i.e. they encode small, soluble (lack of transmembrane domain, cysteine-rich proteins with a putative SP. For a selected subset of CEAPs and candidate effectors, semiquantitative RT-PCR showed that these transcripts were either expressed constitutively in both in vitro and in planta or induced during plant infection. Using potato virus X (PVX based transient expression assays, we showed that one of the candidate effectors, i. e. contig 8 that encodes a cerato-platanin (CP domain containing protein, unlike CP proteins

The Proteome of Biologically Active Membrane Vesicles from Piscirickettsia salmonis LF-89 Type Strain Identifies Plasmid-Encoded Putative Toxins

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Cristian Oliver

2017-09-01

Full Text Available Piscirickettsia salmonis is the predominant bacterial pathogen affecting the Chilean salmonid industry. This bacterium is the etiological agent of piscirickettsiosis, a significant fish disease. Membrane vesicles (MVs released by P. salmonis deliver several virulence factors to host cells. To improve on existing knowledge for the pathogenicity-associated functions of P. salmonis MVs, we studied the proteome of purified MVs from the P. salmonis LF-89 type strain using multidimensional protein identification technology. Initially, the cytotoxicity of different MV concentration purified from P. salmonis LF-89 was confirmed in an in vivo adult zebrafish infection model. The cumulative mortality of zebrafish injected with MVs showed a dose-dependent pattern. Analyses identified 452 proteins of different subcellular origins; most of them were associated with the cytoplasmic compartment and were mainly related to key functions for pathogen survival. Interestingly, previously unidentified putative virulence-related proteins were identified in P. salmonis MVs, such as outer membrane porin F and hemolysin. Additionally, five amino acid sequences corresponding to the Bordetella pertussis toxin subunit 1 and two amino acid sequences corresponding to the heat-labile enterotoxin alpha chain of Escherichia coli were located in the P. salmonis MV proteome. Curiously, these putative toxins were located in a plasmid region of P. salmonis LF-89. Based on the identified proteins, we propose that the protein composition of P. salmonis LF-89 MVs could reflect total protein characteristics of this P. salmonis type strain.

The Proteome of Biologically Active Membrane Vesicles from Piscirickettsia salmonis LF-89 Type Strain Identifies Plasmid-Encoded Putative Toxins.

Science.gov (United States)

Oliver, Cristian; Hernández, Mauricio A; Tandberg, Julia I; Valenzuela, Karla N; Lagos, Leidy X; Haro, Ronie E; Sánchez, Patricio; Ruiz, Pamela A; Sanhueza-Oyarzún, Constanza; Cortés, Marcos A; Villar, María T; Artigues, Antonio; Winther-Larsen, Hanne C; Avendaño-Herrera, Ruben; Yáñez, Alejandro J

2017-01-01

Piscirickettsia salmonis is the predominant bacterial pathogen affecting the Chilean salmonid industry. This bacterium is the etiological agent of piscirickettsiosis, a significant fish disease. Membrane vesicles (MVs) released by P. salmonis deliver several virulence factors to host cells. To improve on existing knowledge for the pathogenicity-associated functions of P. salmonis MVs, we studied the proteome of purified MVs from the P. salmonis LF-89 type strain using multidimensional protein identification technology. Initially, the cytotoxicity of different MV concentration purified from P. salmonis LF-89 was confirmed in an in vivo adult zebrafish infection model. The cumulative mortality of zebrafish injected with MVs showed a dose-dependent pattern. Analyses identified 452 proteins of different subcellular origins; most of them were associated with the cytoplasmic compartment and were mainly related to key functions for pathogen survival. Interestingly, previously unidentified putative virulence-related proteins were identified in P. salmonis MVs, such as outer membrane porin F and hemolysin. Additionally, five amino acid sequences corresponding to the Bordetella pertussis toxin subunit 1 and two amino acid sequences corresponding to the heat-labile enterotoxin alpha chain of Escherichia coli were located in the P. salmonis MV proteome. Curiously, these putative toxins were located in a plasmid region of P. salmonis LF-89. Based on the identified proteins, we propose that the protein composition of P. salmonis LF-89 MVs could reflect total protein characteristics of this P. salmonis type strain.

An artificial neural network system to identify alleles in reference electropherograms.

Science.gov (United States)

Taylor, Duncan; Harrison, Ash; Powers, David

2017-09-01

Electropherograms are produced in great numbers in forensic DNA laboratories as part of everyday criminal casework. Before the results of these electropherograms can be used they must be scrutinised by analysts to determine what the identified data tells them about the underlying DNA sequences and what is purely an artefact of the DNA profiling process. This process of interpreting the electropherograms can be time consuming and is prone to subjective differences between analysts. Recently it was demonstrated that artificial neural networks could be used to classify information within an electropherogram as allelic (i.e. representative of a DNA fragment present in the DNA extract) or as one of several different categories of artefactual fluorescence that arise as a result of generating an electropherogram. We extend that work here to demonstrate a series of algorithms and artificial neural networks that can be used to identify peaks on an electropherogram and classify them. We demonstrate the functioning of the system on several profiles and compare the results to a leading commercial DNA profile reading system. Copyright © 2017 Elsevier B.V. All rights reserved.

A comparison of neural tube defects identified by two independent routine recording systems for congenital malformations in Northern Ireland.

Science.gov (United States)

Nevin, N C; McDonald, J R; Walby, A L

1978-12-01

The efficiency of two systems for recording congenital malformations has been compared; one system, the Registrar General's Congenital Malformation Notification, is based on registering all malformed infants, and the other, the Child Health System, records all births. In Northern Ireland for three years [1974--1976], using multiple sources of ascertainment, a total of 686 infants with neural tube defects was identified among 79 783 live and stillbirths. The incidence for all neural tube defects in 8 60 per 1 000 births. The Registrar General's Congenital Malformation Notification System identified 83.6% whereas the Child Health System identified only 63.3% of all neural tube defects. Both systems together identified 86.2% of all neural tube defects. The two systems are suitable for monitoring of malformations and the addition of information from the Genetic Counselling Clinics would enhance the data for epidemiological studies.

Transcriptome Analysis of Mango (Mangifera indica L.) Fruit Epidermal Peel to Identify Putative Cuticle-Associated Genes

Science.gov (United States)

Tafolla-Arellano, Julio C.; Zheng, Yi; Sun, Honghe; Jiao, Chen; Ruiz-May, Eliel; Hernández-Oñate, Miguel A.; González-León, Alberto; Báez-Sañudo, Reginaldo; Fei, Zhangjun; Domozych, David; Rose, Jocelyn K. C.; Tiznado-Hernández, Martín E.

2017-04-01

Mango fruit (Mangifera indica L.) are highly perishable and have a limited shelf life, due to postharvest desiccation and senescence, which limits their global distribution. Recent studies of tomato fruit suggest that these traits are influenced by the expression of genes that are associated with cuticle metabolism. However, studies of these phenomena in mango fruit are limited by the lack of genome-scale data. In order to gain insight into the mango cuticle biogenesis and identify putative cuticle-associated genes, we analyzed the transcriptomes of peels from ripe and overripe mango fruit using RNA-Seq. Approximately 400 million reads were generated and de novo assembled into 107,744 unigenes, with a mean length of 1,717 bp and with this information an online Mango RNA-Seq Database (http://bioinfo.bti.cornell.edu/cgi-bin/mango/index.cgi) which is a valuable genomic resource for molecular research into the biology of mango fruit was created. RNA-Seq analysis suggested that the pathway leading to biosynthesis of the cuticle component, cutin, is up-regulated during overripening. This data was supported by analysis of the expression of several putative cuticle-associated genes and by gravimetric and microscopic studies of cuticle deposition, revealing a complex continuous pattern of cuticle deposition during fruit development and involving substantial accumulation during ripening/overripening.

The neural correlates of reciprocity are sensitive to prior experience of reciprocity.

Science.gov (United States)

Cáceda, Ricardo; Prendes-Alvarez, Stefania; Hsu, Jung-Jiin; Tripathi, Shanti P; Kilts, Clint D; James, G Andrew

2017-08-14

Reciprocity is central to human relationships and is strongly influenced by multiple factors including the nature of social exchanges and their attendant emotional reactions. Despite recent advances in the field, the neural processes involved in this modulation of reciprocal behavior by ongoing social interaction are poorly understood. We hypothesized that activity within a discrete set of neural networks including a putative moral cognitive neural network is associated with reciprocity behavior. Nineteen healthy adults underwent functional magnetic resonance imaging scanning while playing the trustee role in the Trust Game. Personality traits and moral development were assessed. Independent component analysis was used to identify task-related functional brain networks and assess their relationship to behavior. The saliency network (insula and anterior cingulate) was positively correlated with reciprocity behavior. A consistent array of brain regions supports the engagement of emotional, self-referential and planning processes during social reciprocity behavior. Published by Elsevier B.V.

A neural network to identify neutral mesons

International Nuclear Information System (INIS)

Lefevre, F.; Lautridou, P.; Marques, M.; Matulewicz, T.; Ostendorf, R.; Schutz, Y.

1994-01-01

Both π 0 and η mesons decay long before they can reach a detector. They predominantly decay by emission of two photons, and are identified by constructing the invariant mass of the photons. Misidentified mesons result from ambiguity in associating photons. Our work tries to select which pair is the most likely to be a physical one rather than a chance one. We first designed a Hopfield neural net, but all the activities converged rapidly towards zero except the highest one. To improve the solution we slew down the computation in order to let the network explore several states and to impose activities to converge towards one for all selected pairs. This was achieved by adding links connecting each cell to itself. The network performance is all the more interesting that the solid angle covered by the detector is greater than 15%. (D.L.). 5 refs

Identification and characterization of putative conserved IAM ...

African Journals Online (AJOL)

Available putative AMI sequences from a wide array of monocot and dicot plants were identified and the phylogenetic tree was constructed and analyzed. We identified in this tree, a clade that contained sequences from species across the plant kingdom suggesting that AMI is conserved and may have a primary role in plant ...

Identifying the relevant dependencies of the neural network response on characteristics of the input space

CERN Multimedia

CERN. Geneva

2018-01-01

This talk presents an approach to identify those characteristics of the neural network inputs that are most relevant for the response and therefore provides essential information to determine the systematic uncertainties.

The Putative Son's Attractiveness Alters the Perceived Attractiveness of the Putative Father.

Science.gov (United States)

Prokop, Pavol

2015-08-01

A body of literature has investigated female mate choice in the pre-mating context (pre-mating sexual selection). Humans, however, are long-living mammals forming pair-bonds which sequentially produce offspring. Post-mating evaluations of a partner's attractiveness may thus significantly influence the reproductive success of men and women. I tested herein the theory that the attractiveness of putative sons provides extra information about the genetic quality of fathers, thereby influencing fathers' attractiveness across three studies. As predicted, facially attractive boys were more frequently attributed to attractive putative fathers and vice versa (Study 1). Furthermore, priming with an attractive putative son increased the attractiveness of the putative father with the reverse being true for unattractive putative sons. When putative fathers were presented as stepfathers, the effect of the boy's attractiveness on the stepfather's attractiveness was lower and less consistent (Study 2). This suggests that the presence of an attractive boy has the strongest effect on the perceived attractiveness of putative fathers rather than on non-fathers. The generalized effect of priming with beautiful non-human objects also exists, but its effect is much weaker compared with the effects of putative biological sons (Study 3). Overall, this study highlighted the importance of post-mating sexual selection in humans and suggests that the heritable attractive traits of men are also evaluated by females after mating and/or may be used by females in mate poaching.

Study on the identifying of meat's visible spectrum based on BP artificial neural network

Science.gov (United States)

Li, Xiaotian; Zhang, Tieqiang; Li, Bo; Jiang, Yongheng; Liu, Binghui; Li, Zhaokai

2006-01-01

A method to identify different meat by the visible and reflected spectra of meat with BP artificial neural net (BP-ANN) was introduced in this paper. The visible and reflected spectra (from 420 to 535nm) of different meat (beef and pork) were measured with fiber sensor spectrometer. A kind of ANN with a double-hidden layer was created to identify the different meat automatically. Its right ratio reaches 92.71%.

Identifying Tmem59 related gene regulatory network of mouse neural stem cell from a compendium of expression profiles

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Guo Xiuyun

2011-09-01

Full Text Available Abstract Background Neural stem cells offer potential treatment for neurodegenerative disorders, such like Alzheimer's disease (AD. While much progress has been made in understanding neural stem cell function, a precise description of the molecular mechanisms regulating neural stem cells is not yet established. This lack of knowledge is a major barrier holding back the discovery of therapeutic uses of neural stem cells. In this paper, the regulatory mechanism of mouse neural stem cell (NSC differentiation by tmem59 is explored on the genome-level. Results We identified regulators of tmem59 during the differentiation of mouse NSCs from a compendium of expression profiles. Based on the microarray experiment, we developed the parallelized SWNI algorithm to reconstruct gene regulatory networks of mouse neural stem cells. From the inferred tmem59 related gene network including 36 genes, pou6f1 was identified to regulate tmem59 significantly and might play an important role in the differentiation of NSCs in mouse brain. There are four pathways shown in the gene network, indicating that tmem59 locates in the downstream of the signalling pathway. The real-time RT-PCR results shown that the over-expression of pou6f1 could significantly up-regulate tmem59 expression in C17.2 NSC line. 16 out of 36 predicted genes in our constructed network have been reported to be AD-related, including Ace, aqp1, arrdc3, cd14, cd59a, cds1, cldn1, cox8b, defb11, folr1, gdi2, mmp3, mgp, myrip, Ripk4, rnd3, and sncg. The localization of tmem59 related genes and functional-related gene groups based on the Gene Ontology (GO annotation was also identified. Conclusions Our findings suggest that the expression of tmem59 is an important factor contributing to AD. The parallelized SWNI algorithm increased the efficiency of network reconstruction significantly. This study enables us to highlight novel genes that may be involved in NSC differentiation and provides a shortcut to

Application of artificial neural networks to identify equilibration in computer simulations

Science.gov (United States)

Leibowitz, Mitchell H.; Miller, Evan D.; Henry, Michael M.; Jankowski, Eric

2017-11-01

Determining which microstates generated by a thermodynamic simulation are representative of the ensemble for which sampling is desired is a ubiquitous, underspecified problem. Artificial neural networks are one type of machine learning algorithm that can provide a reproducible way to apply pattern recognition heuristics to underspecified problems. Here we use the open-source TensorFlow machine learning library and apply it to the problem of identifying which hypothetical observation sequences from a computer simulation are “equilibrated” and which are not. We generate training populations and test populations of observation sequences with embedded linear and exponential correlations. We train a two-neuron artificial network to distinguish the correlated and uncorrelated sequences. We find that this simple network is good enough for > 98% accuracy in identifying exponentially-decaying energy trajectories from molecular simulations.

A strategy to discover new organizers identifies a putative heart organizer.

Science.gov (United States)

Anderson, Claire; Khan, Mohsin A F; Wong, Frances; Solovieva, Tatiana; Oliveira, Nidia M M; Baldock, Richard A; Tickle, Cheryll; Burt, Dave W; Stern, Claudio D

2016-08-25

Organizers are regions of the embryo that can both induce new fates and impart pattern on other regions. So far, surprisingly few organizers have been discovered, considering the number of patterned tissue types generated during development. This may be because their discovery has relied on transplantation and ablation experiments. Here we describe a new approach, using chick embryos, to discover organizers based on a common gene expression signature, and use it to uncover the anterior intestinal portal (AIP) endoderm as a putative heart organizer. We show that the AIP can induce cardiac identity from non-cardiac mesoderm and that it can pattern this by specifying ventricular and suppressing atrial regional identity. We also uncover some of the signals responsible. The method holds promise as a tool to discover other novel organizers acting during development.

ChloroP, a neural network-based method for predicting chloroplast transitpeptides and their cleavage sites

DEFF Research Database (Denmark)

Emanuelsson, O.; Nielsen, Henrik; von Heijne, Gunnar

1999-01-01

the cleavage sites given in SWISS-PROT. An analysis of 715 Arabidopsis thaliana sequences from SWISS-PROT suggests that the ChloroP method should be useful for the identification of putative transit peptides in genome-wide sequence data. The ChloroP predictor is available as a web-server at http......We present a neural network based method (ChloroP) for identifying chloroplast transit peptides and their cleavage sites. Using cross-validation, 88% of the sequences in our homology reduced training set were correctly classified as transit peptides or nontransit peptides. This performance level...

Alteration of putative amino acid levels and morphological findings in neural tissues of methylmercury-intoxicated mice

Energy Technology Data Exchange (ETDEWEB)

Hirayama, K.; Inouye, M.; Fujisaki, T.

1985-04-01

Methylmercury chloride was administered PO to male Kud:ddY mice at a dose of 5 mg/kg/day for 20 days. The contents of taurine, aspartate, glutamate, glycine, and ..gamma..-aminobutyric acid were determined in tissue and crude synaptosomal (P/sub 2/) fraction of cerebellum, cerebral cortex, and spinal cord of methylmercury-treated mice with or without ataxia. In the cerebellum of ataxic mice, increased levels of taurine and glycine were found in the tissue and P/sub 2/ fraction, and increased levels of glutamate were found in the P/sub 2/ fraction. In the cerebral cortex, the levels of ..gamma..-aminobutylic acid decreased in the tissue and in the P/sub 2/ fraction of ataxic mice, but increased levels were found in the tissue of non-ataxic mice. A decreased asparate level in the cerebral cortex of ataxic mice and an increased taurine level in the cerebral cortex of non-ataxic mice were also found. In the spinal cord of ataxic mice, taurine increased in the tissue and in the P/sub 2/ fraction. Glutamate level decreased in the spinal cord of ataxic mice, but increased in the P/sub 2/ fraction of non-ataxic mice. Increased glycine levels in the P/sub 2/ fraction of the spinal cord were also found in non-axtaxic mice. Histologically, some degenerative changes were demonstrated in the cerebral and cerebellar cortices of ataxic mice. Such changes were also present to a mild degree in non-ataxic mice. In conclusion, methylmercury treatment altered the levels of putative neurotransmitter amino acids in neutral tissue of mice. These alterations might be caused by specific neural cell dysfunction and could be related to the appearance of ataxia.

Differential Expression Patterns in Chemosensory and Non-Chemosensory Tissues of Putative Chemosensory Genes Identified by Transcriptome Analysis of Insect Pest the Purple Stem Borer Sesamia inferens (Walker)

OpenAIRE

Zhang, Ya-Nan; Jin, Jun-Yan; Jin, Rong; Xia, Yi-Han; Zhou, Jing-Jiang; Deng, Jian-Yu; Dong, Shuang-Lin

2013-01-01

BACKGROUND: A large number of insect chemosensory genes from different gene subfamilies have been identified and annotated, but their functional diversity and complexity are largely unknown. A systemic examination of expression patterns in chemosensory organs could provide important information. METHODOLOGY/PRINCIPAL FINDINGS: We identified 92 putative chemosensory genes by analysing the transcriptome of the antennae and female sex pheromone gland of the purple stem borer Sesamia inferens, am...

Identifying the neural substrates of intrinsic motivation during task performance.

Science.gov (United States)

Lee, Woogul; Reeve, Johnmarshall

2017-10-01

Intrinsic motivation is the inherent tendency to seek out novelty and challenge, to explore and investigate, and to stretch and extend one's capacities. When people imagine performing intrinsically motivating tasks, they show heightened anterior insular cortex (AIC) activity. To fully explain the neural system of intrinsic motivation, however, requires assessing neural activity while people actually perform intrinsically motivating tasks (i.e., while answering curiosity-inducing questions or solving competence-enabling anagrams). Using event-related functional magnetic resonance imaging, we found that the neural system of intrinsic motivation involves not only AIC activity, but also striatum activity and, further, AIC-striatum functional interactions. These findings suggest that subjective feelings of intrinsic satisfaction (associated with AIC activations), reward processing (associated with striatum activations), and their interactions underlie the actual experience of intrinsic motivation. These neural findings are consistent with the conceptualization of intrinsic motivation as the pursuit and satisfaction of subjective feelings (interest and enjoyment) as intrinsic rewards.

Morphological covariance in anatomical MRI scans can identify discrete neural pathways in the brain and their disturbances in persons with neuropsychiatric disorders.

Science.gov (United States)

Bansal, Ravi; Hao, Xuejun; Peterson, Bradley S

2015-05-01

We hypothesize that coordinated functional activity within discrete neural circuits induces morphological organization and plasticity within those circuits. Identifying regions of morphological covariation that are independent of morphological covariation in other regions therefore may therefore allow us to identify discrete neural systems within the brain. Comparing the magnitude of these variations in individuals who have psychiatric disorders with the magnitude of variations in healthy controls may allow us to identify aberrant neural pathways in psychiatric illnesses. We measured surface morphological features by applying nonlinear, high-dimensional warping algorithms to manually defined brain regions. We transferred those measures onto the surface of a unit sphere via conformal mapping and then used spherical wavelets and their scaling coefficients to simplify the data structure representing these surface morphological features of each brain region. We used principal component analysis (PCA) to calculate covariation in these morphological measures, as represented by their scaling coefficients, across several brain regions. We then assessed whether brain subregions that covaried in morphology, as identified by large eigenvalues in the PCA, identified specific neural pathways of the brain. To do so, we spatially registered the subnuclei for each eigenvector into the coordinate space of a Diffusion Tensor Imaging dataset; we used these subnuclei as seed regions to track and compare fiber pathways with known fiber pathways identified in neuroanatomical atlases. We applied these procedures to anatomical MRI data in a cohort of 82 healthy participants (42 children, 18 males, age 10.5 ± 2.43 years; 40 adults, 22 males, age 32.42 ± 10.7 years) and 107 participants with Tourette's Syndrome (TS) (71 children, 59 males, age 11.19 ± 2.2 years; 36 adults, 21 males, age 37.34 ± 10.9 years). We evaluated the construct validity of the identified covariation in morphology

Influence of putative exopolysaccharide genes on Pseudomonas putida KT2440 biofilm stability

DEFF Research Database (Denmark)

Nilsson, Martin; Chiang, Wen-Chi; Fazli, Mustafa

2011-01-01

We report a study of the role of putative exopolysaccharide gene clusters in the formation and stability of Pseudomonas putida KT2440 biofilm. Two novel putative exopolysaccharide gene clusters, pea and peb, were identified, and evidence is provided that they encode products that stabilize P....... putida KT2440 biofilm. The gene clusters alg and bcs, which code for proteins mediating alginate and cellulose biosynthesis, were found to play minor roles in P. putida KT2440 biofilm formation and stability under the conditions tested. A P. putida KT2440 derivative devoid of any identifiable...

Mode of effective connectivity within a putative neural network differentiates moral cognitions related to care and justice ethics.

Science.gov (United States)

Cáceda, Ricardo; James, G Andrew; Ely, Timothy D; Snarey, John; Kilts, Clinton D

2011-02-25

Moral sensitivity refers to the interpretive awareness of moral conflict and can be justice or care oriented. Justice ethics is associated primarily with human rights and the application of moral rules, whereas care ethics is related to human needs and a situational approach involving social emotions. Among the core brain regions involved in moral issue processing are: medial prefrontal cortex, anterior (ACC) and posterior (PCC) cingulate cortex, posterior superior temporal sulcus (pSTS), insula and amygdala. This study sought to inform the long standing debate of whether care and justice moral ethics represent one or two different forms of cognition. Model-free and model-based connectivity analysis were used to identify functional neural networks underlying care and justice ethics for a moral sensitivity task. In addition to modest differences in patterns of associated neural activity, distinct modes of functional and effective connectivity were observed for moral sensitivity for care and justice issues that were modulated by individual variation in moral ability. These results support a neurobiological differentiation between care and justice ethics and suggest that human moral behavior reflects the outcome of integrating opposing rule-based, self-other perspectives, and emotional responses.

Putative Risk Factors in Developmental Dyslexia: A Case-Control Study of Italian Children

Science.gov (United States)

Mascheretti, Sara; Marino, Cecilia; Simone, Daniela; Quadrelli, Ermanno; Riva, Valentina; Cellino, Maria Rosaria; Maziade, Michel; Brombin, Chiara; Battaglia, Marco

2015-01-01

Although dyslexia runs in families, several putative risk factors that cannot be immediately identified as genetic predict reading disability. Published studies analyzed one or a few risk factors at a time, with relatively inconsistent results. To assess the contribution of several putative risk factors to the development of dyslexia, we conducted…

Primary genome scan to identify putative quantitative trait loci for feedlot growth rate, feed intake, and feed efficiency of beef cattle.

Science.gov (United States)

Nkrumah, J D; Sherman, E L; Li, C; Marques, E; Crews, D H; Bartusiak, R; Murdoch, B; Wang, Z; Basarab, J A; Moore, S S

2007-12-01

Feed intake and feed efficiency of beef cattle are economically relevant traits. The study was conducted to identify QTL for feed intake and feed efficiency of beef cattle by using genotype information from 100 microsatellite markers and 355 SNP genotyped across 400 progeny of 20 Angus, Charolais, or Alberta Hybrid bulls. Traits analyzed include feedlot ADG, daily DMI, feed-to-gain ratio [F:G, which is the reciprocal of the efficiency of gain (G:F)], and residual feed intake (RFI). A mixed model with sire as random and QTL effects as fixed was used to generate an F-statistic profile across and within families for each trait along each chromosome, followed by empirical permutation tests to determine significance thresholds for QTL detection. Putative QTL for ADG (chromosome-wise P < 0.05) were detected across families on chromosomes 5 (130 cM), 6 (42 cM), 7 (84 cM), 11 (20 cM), 14 (74 cM), 16 (22 cM), 17 (9 cM), 18 (46 cM), 19 (53 cM), and 28 (23 cM). For DMI, putative QTL that exceeded the chromosome-wise P < 0.05 threshold were detected on chromosomes 1 (93 cM), 3 (123 cM), 15 (31 cM), 17 (81 cM), 18 (49 cM), 20 (56 cM), and 26 (69 cM) in the across-family analyses. Putative across-family QTL influencing F:G that exceeded the chromosome-wise P < 0.05 threshold were detected on chromosomes 3 (62 cM), 5 (129 cM), 7 (27 cM), 11 (16 cM), 16 (30 cM), 17 (81 cM), 22 (72 cM), 24 (55 cM), and 28 (24 cM). Putative QTL influencing RFI that exceeded the chromosome-wise P < 0.05 threshold were detected on chromosomes 1 (90 cM), 5 (129 cM), 7 (22 cM), 8 (80 cM), 12 (89 cM), 16 (41 cM), 17 (19 cM), and 26 (48 cM) in the across-family analyses. In addition, a total of 4, 6, 1, and 8 chromosomes showed suggestive evidence (chromosome-wise, P < 0.10) for putative ADG, DMI, F:G, and RFI QTL, respectively. Most of the QTL detected across families were also detected within families, although the locations across families were not necessarily the locations within families, which is

Putative Dementia Cases Fluctuate as a Function of Mini-Mental State Examination Cut-Off Points.

Science.gov (United States)

Rosa, Ilka M; Henriques, Ana G; Wiltfang, Jens; da Cruz E Silva, Odete A B

2018-01-01

As the population ages, there is a growing need to quickly and accurately identify putative dementia cases. Many cognitive tests are available; among those commonly used are the Cognitive Dementia Rating (CDR) and the Mini-Mental Status Examination (MMSE). The aim of this work was to compare the validity and reliability of these cognitive tests in a primary care based cohort (pcb-Cohort). The MMSE and the CDR were applied to 568 volunteers in the pcb-Cohort. Distinct cut-off points for the MMSE were considered, namely MMSE 27, MMSE 24, and MMSE PT (adapted for the Portuguese population). The MMSE 27 identified the greatest number of putative dementia cases, and, as determined by the ROC curve, it was the most sensitive and specific of the MMSE cut-offs considered. Putative predictive or risk factors identified included age, literacy, depression, and diabetes mellitus (DM). DM has previously been indicated as a risk factor for dementia and Alzheimer's disease. Comparatively, the MMSE 27 cut-off has the greatest sensibility (94.9%) and specificity (66.3%) when compared to MMSE PT and MMSE 24. Upon comparing MMSE and CDR scores, the latter identified a further 146 putative dementia cases, thus permitting one to propose that in an ideal situation, both tests should be employed. This increases the likelihood of identifying putative dementia cases for subsequent follow up work, thus these cognitive tests represent important tools in patient care. Further, this is a significant study for Portuguese populations, where few of these studies have been carried out.

Mode of effective connectivity within a putative neural network differentiates moral cognitions related to care and justice ethics.

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Ricardo Cáceda

Full Text Available BACKGROUND: Moral sensitivity refers to the interpretive awareness of moral conflict and can be justice or care oriented. Justice ethics is associated primarily with human rights and the application of moral rules, whereas care ethics is related to human needs and a situational approach involving social emotions. Among the core brain regions involved in moral issue processing are: medial prefrontal cortex, anterior (ACC and posterior (PCC cingulate cortex, posterior superior temporal sulcus (pSTS, insula and amygdala. This study sought to inform the long standing debate of whether care and justice moral ethics represent one or two different forms of cognition. METHODOLOGY/PRINCIPAL FINDINGS: Model-free and model-based connectivity analysis were used to identify functional neural networks underlying care and justice ethics for a moral sensitivity task. In addition to modest differences in patterns of associated neural activity, distinct modes of functional and effective connectivity were observed for moral sensitivity for care and justice issues that were modulated by individual variation in moral ability. CONCLUSIONS/SIGNIFICANCE: These results support a neurobiological differentiation between care and justice ethics and suggest that human moral behavior reflects the outcome of integrating opposing rule-based, self-other perspectives, and emotional responses.

Mode of Effective Connectivity within a Putative Neural Network Differentiates Moral Cognitions Related to Care and Justice Ethics

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Cáceda, Ricardo; James, G. Andrew; Ely, Timothy D.; Snarey, John; Kilts, Clinton D.

2011-01-01

Background Moral sensitivity refers to the interpretive awareness of moral conflict and can be justice or care oriented. Justice ethics is associated primarily with human rights and the application of moral rules, whereas care ethics is related to human needs and a situational approach involving social emotions. Among the core brain regions involved in moral issue processing are: medial prefrontal cortex, anterior (ACC) and posterior (PCC) cingulate cortex, posterior superior temporal sulcus (pSTS), insula and amygdala. This study sought to inform the long standing debate of whether care and justice moral ethics represent one or two different forms of cognition. Methodology/Principal Findings Model-free and model-based connectivity analysis were used to identify functional neural networks underlying care and justice ethics for a moral sensitivity task. In addition to modest differences in patterns of associated neural activity, distinct modes of functional and effective connectivity were observed for moral sensitivity for care and justice issues that were modulated by individual variation in moral ability. Conclusions/Significance These results support a neurobiological differentiation between care and justice ethics and suggest that human moral behavior reflects the outcome of integrating opposing rule-based, self-other perspectives, and emotional responses. PMID:21364916

Molecular profiling of aged neural progenitors identifies Dbx2 as a candidate regulator of age-associated neurogenic decline.

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Lupo, Giuseppe; Nisi, Paola S; Esteve, Pilar; Paul, Yu-Lee; Novo, Clara Lopes; Sidders, Ben; Khan, Muhammad A; Biagioni, Stefano; Liu, Hai-Kun; Bovolenta, Paola; Cacci, Emanuele; Rugg-Gunn, Peter J

2018-06-01

Adult neurogenesis declines with aging due to the depletion and functional impairment of neural stem/progenitor cells (NSPCs). An improved understanding of the underlying mechanisms that drive age-associated neurogenic deficiency could lead to the development of strategies to alleviate cognitive impairment and facilitate neuroregeneration. An essential step towards this aim is to investigate the molecular changes that occur in NSPC aging on a genomewide scale. In this study, we compare the transcriptional, histone methylation and DNA methylation signatures of NSPCs derived from the subventricular zone (SVZ) of young adult (3 months old) and aged (18 months old) mice. Surprisingly, the transcriptional and epigenomic profiles of SVZ-derived NSPCs are largely unchanged in aged cells. Despite the global similarities, we detect robust age-dependent changes at several hundred genes and regulatory elements, thereby identifying putative regulators of neurogenic decline. Within this list, the homeobox gene Dbx2 is upregulated in vitro and in vivo, and its promoter region has altered histone and DNA methylation levels, in aged NSPCs. Using functional in vitro assays, we show that elevated Dbx2 expression in young adult NSPCs promotes age-related phenotypes, including the reduced proliferation of NSPC cultures and the altered transcript levels of age-associated regulators of NSPC proliferation and differentiation. Depleting Dbx2 in aged NSPCs caused the reverse gene expression changes. Taken together, these results provide new insights into the molecular programmes that are affected during mouse NSPC aging, and uncover a new functional role for Dbx2 in promoting age-related neurogenic decline. © 2018 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd.

Identifying tau hadronic decay with neural network

International Nuclear Information System (INIS)

Chen Guoming; Chen Gang

1995-01-01

The identification of tau one prong hadronic decay using neural network is presented. Based on the identification, we measured the branching ratios: Br(π/Kν) = (12.18 +- 0.26 +- 0.42)%, Br(π/Kπ 0 ν) = (25.20 +-0.35 +- 0.50)%, Br(π/K2π 0 ν) = (8.88 +- 0.37 +- 0.38)%, Br(π/K3π 0 ν) = (1.70 +- 0.24 +- 0.39)%

Using c-Jun to identify fear extinction learning-specific patterns of neural activity that are affected by single prolonged stress.

Science.gov (United States)

Knox, Dayan; Stanfield, Briana R; Staib, Jennifer M; David, Nina P; DePietro, Thomas; Chamness, Marisa; Schneider, Elizabeth K; Keller, Samantha M; Lawless, Caroline

2018-04-02

Neural circuits via which stress leads to disruptions in fear extinction is often explored in animal stress models. Using the single prolonged stress (SPS) model of post traumatic stress disorder and the immediate early gene (IEG) c-Fos as a measure of neural activity, we previously identified patterns of neural activity through which SPS disrupts extinction retention. However, none of these stress effects were specific to fear or extinction learning and memory. C-Jun is another IEG that is sometimes regulated in a different manner to c-Fos and could be used to identify emotional learning/memory specific patterns of neural activity that are sensitive to SPS. Animals were either fear conditioned (CS-fear) or presented with CSs only (CS-only) then subjected to extinction training and testing. C-Jun was then assayed within neural substrates critical for extinction memory. Inhibited c-Jun levels in the hippocampus (Hipp) and enhanced functional connectivity between the ventromedial prefrontal cortex (vmPFC) and basolateral amygdala (BLA) during extinction training was disrupted by SPS in the CS-fear group only. As a result, these effects were specific to emotional learning/memory. SPS also disrupted inhibited Hipp c-Jun levels, enhanced BLA c-Jun levels, and altered functional connectivity among the vmPFC, BLA, and Hipp during extinction testing in SPS rats in the CS-fear and CS-only groups. As a result, these effects were not specific to emotional learning/memory. Our findings suggest that SPS disrupts neural activity specific to extinction memory, but may also disrupt the retention of fear extinction by mechanisms that do not involve emotional learning/memory. Copyright © 2017 Elsevier B.V. All rights reserved.

Weak correlations between hemodynamic signals and ongoing neural activity during the resting state

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Winder, Aaron T.; Echagarruga, Christina; Zhang, Qingguang; Drew, Patrick J.

2017-01-01

Spontaneous fluctuations in hemodynamic signals in the absence of a task or overt stimulation are used to infer neural activity. We tested this coupling by simultaneously measuring neural activity and changes in cerebral blood volume (CBV) in the somatosensory cortex of awake, head-fixed mice during periods of true rest, and during whisker stimulation and volitional whisking. Here we show that neurovascular coupling was similar across states, and large spontaneous CBV changes in the absence of sensory input were driven by volitional whisker and body movements. Hemodynamic signals during periods of rest were weakly correlated with neural activity. Spontaneous fluctuations in CBV and vessel diameter persisted when local neural spiking and glutamatergic input was blocked, and during blockade of noradrenergic receptors, suggesting a non-neuronal origin for spontaneous CBV fluctuations. Spontaneous hemodynamic signals reflect a combination of behavior, local neural activity, and putatively non-neural processes. PMID:29184204

Synchrotron- and focal plane array-based Fourier-transform infrared spectroscopy differentiates the basalis and functionalis epithelial endometrial regions and identifies putative stem cell regions of human endometrial glands.

Science.gov (United States)

Theophilou, Georgios; Morais, Camilo L M; Halliwell, Diane E; Lima, Kássio M G; Drury, Josephine; Martin-Hirsch, Pierre L; Stringfellow, Helen F; Hapangama, Dharani K; Martin, Francis L

2018-05-09

The cyclical process of regeneration of the endometrium suggests that it may contain a cell population that can provide daughter cells with high proliferative potential. These cell lineages are clinically significant as they may represent clonogenic cells that may also be involved in tumourigenesis as well as endometriotic lesion development. To determine whether the putative stem cell location within human uterine tissue can be derived using vibrational spectroscopy techniques, normal endometrial tissue was interrogated by two spectroscopic techniques. Paraffin-embedded uterine tissues containing endometrial glands were sectioned to 10-μm-thick parallel tissue sections and were floated onto BaF 2 slides for synchrotron radiation-based Fourier-transform infrared (SR-FTIR) microspectroscopy and globar focal plane array-based FTIR spectroscopy. Different spectral characteristics were identified depending on the location of the glands examined. The resulting infrared spectra were subjected to multivariate analysis to determine associated biophysical differences along the length of longitudinal and crosscut gland sections. Comparison of the epithelial cellular layer of transverse gland sections revealed alterations indicating the presence of putative transient-amplifying-like cells in the basalis and mitotic cells in the functionalis. SR-FTIR microspectroscopy of the base of the endometrial glands identified the location where putative stem cells may reside at the same time pointing towards ν s PO 2 - in DNA and RNA, nucleic acids and amide I and II vibrations as major discriminating factors. This study supports the view that vibration spectroscopy technologies are a powerful adjunct to our understanding of the stem cell biology of endometrial tissue. Graphical abstract ᅟ.

Synergic Functions of miRNAs Determine Neuronal Fate of Adult Neural Stem Cells

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Meritxell Pons-Espinal

2017-04-01

Full Text Available Summary: Adult neurogenesis requires the precise control of neuronal versus astrocyte lineage determination in neural stem cells. While microRNAs (miRNAs are critically involved in this step during development, their actions in adult hippocampal neural stem cells (aNSCs has been unclear. As entry point to address that question we chose DICER, an endoribonuclease essential for miRNA biogenesis and other RNAi-related processes. By specific ablation of Dicer in aNSCs in vivo and in vitro, we demonstrate that miRNAs are required for the generation of new neurons, but not astrocytes, in the adult murine hippocampus. Moreover, we identify 11 miRNAs, of which 9 have not been previously characterized in neurogenesis, that determine neurogenic lineage fate choice of aNSCs at the expense of astrogliogenesis. Finally, we propose that the 11 miRNAs sustain adult hippocampal neurogenesis through synergistic modulation of 26 putative targets from different pathways. : In this article, the authors demonstrate that Dicer-dependent miRNAs are required for the generation of new neurons, but not astrocytes, in the adult hippocampus in vivo and in vitro. The authors identify a new set of 11 miRNAs that synergistically converge on multiple targets in different pathways to sustain neurogenic lineage fate commitment in aNSCs. Keywords: mouse, hippocampus, neural stem cells, fate choice, adult neurogenesis, astrogliogenesis, DICER, microRNAs, synergy

Using neural networks with jet shapes to identify b jets in e+e- interactions

International Nuclear Information System (INIS)

Bellantoni, L.; Conway, J.S.; Jacobsen, J.E.; Pan, Y.B.; Wu Saulan

1991-01-01

A feed-forward neural network trained using backpropagation was used to discriminate between b and light quark jets in e + e - → Z 0 → qanti q events. The information presented to the network consisted of 25 jet shape variables. The network successfully identified b jets in two- and three-jet events modeled using a detector simulation. The jet identification efficiency for two-jet events was 61% and the probability to call a light quark jet a b jet equal to 20%. (orig.)

Identifying Jets Using Artifical Neural Networks

Science.gov (United States)

Rosand, Benjamin; Caines, Helen; Checa, Sofia

2017-09-01

We investigate particle jet interactions with the Quark Gluon Plasma (QGP) using artificial neural networks modeled on those used in computer image recognition. We create jet images by binning jet particles into pixels and preprocessing every image. We analyzed the jets with a Multi-layered maxout network and a convolutional network. We demonstrate each network's effectiveness in differentiating simulated quenched jets from unquenched jets, and we investigate the method that the network uses to discriminate among different quenched jet simulations. Finally, we develop a greater understanding of the physics behind quenched jets by investigating what the network learnt as well as its effectiveness in differentiating samples. Yale College Freshman Summer Research Fellowship in the Sciences and Engineering.

Genome-Wide Analysis of Corynespora cassiicola Leaf Fall Disease Putative Effectors.

Science.gov (United States)

Lopez, David; Ribeiro, Sébastien; Label, Philippe; Fumanal, Boris; Venisse, Jean-Stéphane; Kohler, Annegret; de Oliveira, Ricardo R; Labutti, Kurt; Lipzen, Anna; Lail, Kathleen; Bauer, Diane; Ohm, Robin A; Barry, Kerrie W; Spatafora, Joseph; Grigoriev, Igor V; Martin, Francis M; Pujade-Renaud, Valérie

2018-01-01

Corynespora cassiicola is an Ascomycetes fungus with a broad host range and diverse life styles. Mostly known as a necrotrophic plant pathogen, it has also been associated with rare cases of human infection. In the rubber tree, this fungus causes the Corynespora leaf fall (CLF) disease, which increasingly affects natural rubber production in Asia and Africa. It has also been found as an endophyte in South American rubber plantations where no CLF outbreak has yet occurred. The C. cassiicola species is genetically highly diverse, but no clear relationship has been evidenced between phylogenetic lineage and pathogenicity. Cassiicolin, a small glycosylated secreted protein effector, is thought to be involved in the necrotrophic interaction with the rubber tree but some virulent C. cassiicola isolates do not have a cassiicolin gene. This study set out to identify other putative effectors involved in CLF. The genome of a highly virulent C. cassiicola isolate from the rubber tree (CCP) was sequenced and assembled. In silico prediction revealed 2870 putative effectors, comprising CAZymes, lipases, peptidases, secreted proteins and enzymes associated with secondary metabolism. Comparison with the genomes of 44 other fungal species, focusing on effector content, revealed a striking proximity with phylogenetically unrelated species ( Colletotrichum acutatum, Colletotrichum gloesporioides, Fusarium oxysporum, nectria hematococca , and Botrosphaeria dothidea ) sharing life style plasticity and broad host range. Candidate effectors involved in the compatible interaction with the rubber tree were identified by transcriptomic analysis. Differentially expressed genes included 92 putative effectors, among which cassiicolin and two other secreted singleton proteins. Finally, the genomes of 35 C. cassiicola isolates representing the genetic diversity of the species were sequenced and assembled, and putative effectors identified. At the intraspecific level, effector

Genome-Wide Analysis of Corynespora cassiicola Leaf Fall Disease Putative Effectors

Directory of Open Access Journals (Sweden)

David Lopez

2018-03-01

Full Text Available Corynespora cassiicola is an Ascomycetes fungus with a broad host range and diverse life styles. Mostly known as a necrotrophic plant pathogen, it has also been associated with rare cases of human infection. In the rubber tree, this fungus causes the Corynespora leaf fall (CLF disease, which increasingly affects natural rubber production in Asia and Africa. It has also been found as an endophyte in South American rubber plantations where no CLF outbreak has yet occurred. The C. cassiicola species is genetically highly diverse, but no clear relationship has been evidenced between phylogenetic lineage and pathogenicity. Cassiicolin, a small glycosylated secreted protein effector, is thought to be involved in the necrotrophic interaction with the rubber tree but some virulent C. cassiicola isolates do not have a cassiicolin gene. This study set out to identify other putative effectors involved in CLF. The genome of a highly virulent C. cassiicola isolate from the rubber tree (CCP was sequenced and assembled. In silico prediction revealed 2870 putative effectors, comprising CAZymes, lipases, peptidases, secreted proteins and enzymes associated with secondary metabolism. Comparison with the genomes of 44 other fungal species, focusing on effector content, revealed a striking proximity with phylogenetically unrelated species (Colletotrichum acutatum, Colletotrichum gloesporioides, Fusarium oxysporum, nectria hematococca, and Botrosphaeria dothidea sharing life style plasticity and broad host range. Candidate effectors involved in the compatible interaction with the rubber tree were identified by transcriptomic analysis. Differentially expressed genes included 92 putative effectors, among which cassiicolin and two other secreted singleton proteins. Finally, the genomes of 35 C. cassiicola isolates representing the genetic diversity of the species were sequenced and assembled, and putative effectors identified. At the intraspecific level, effector

Identifying apple surface defects using principal components analysis and artifical neural networks

Science.gov (United States)

Artificial neural networks and principal components were used to detect surface defects on apples in near-infrared images. Neural networks were trained and tested on sets of principal components derived from columns of pixels from images of apples acquired at two wavelengths (740 nm and 950 nm). I...

Computational identification of putative cytochrome P450 genes in ...

African Journals Online (AJOL)

In this work, a computational study of expressed sequence tags (ESTs) of soybean was performed by data mining methods and bio-informatics tools and as a result 78 putative P450 genes were identified, including 57 new ones. These genes were classified into five clans and 20 families by sequence similarities and among ...

Alternative splicing events identified in human embryonic stem cells and neural progenitors.

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Gene W Yeo

2007-10-01

Full Text Available Human embryonic stem cells (hESCs and neural progenitor (NP cells are excellent models for recapitulating early neuronal development in vitro, and are key to establishing strategies for the treatment of degenerative disorders. While much effort had been undertaken to analyze transcriptional and epigenetic differences during the transition of hESC to NP, very little work has been performed to understand post-transcriptional changes during neuronal differentiation. Alternative RNA splicing (AS, a major form of post-transcriptional gene regulation, is important in mammalian development and neuronal function. Human ESC, hESC-derived NP, and human central nervous system stem cells were compared using Affymetrix exon arrays. We introduced an outlier detection approach, REAP (Regression-based Exon Array Protocol, to identify 1,737 internal exons that are predicted to undergo AS in NP compared to hESC. Experimental validation of REAP-predicted AS events indicated a threshold-dependent sensitivity ranging from 56% to 69%, at a specificity of 77% to 96%. REAP predictions significantly overlapped sets of alternative events identified using expressed sequence tags and evolutionarily conserved AS events. Our results also reveal that focusing on differentially expressed genes between hESC and NP will overlook 14% of potential AS genes. In addition, we found that REAP predictions are enriched in genes encoding serine/threonine kinase and helicase activities. An example is a REAP-predicted alternative exon in the SLK (serine/threonine kinase 2 gene that is differentially included in hESC, but skipped in NP as well as in other differentiated tissues. Lastly, comparative sequence analysis revealed conserved intronic cis-regulatory elements such as the FOX1/2 binding site GCAUG as being proximal to candidate AS exons, suggesting that FOX1/2 may participate in the regulation of AS in NP and hESC. In summary, a new methodology for exon array analysis was introduced

Search strings for the study of putative occupational determinants of disease

NARCIS (Netherlands)

Mattioli, Stefano; Zanardi, Francesca; Baldasseroni, Alberto; Schaafsma, Frederieke; Cooke, Robin M. T.; Mancini, Gianpiero; Fierro, Mauro; Santangelo, Chiara; Farioli, Andrea; Fucksia, Serenella; Curti, Stefania; Violante, Francesco S.; Verbeek, Jos

2010-01-01

To identify efficient PubMed search strategies to retrieve articles regarding putative occupational determinants of conditions not generally considered to be work related. Based on MeSH definitions and expert knowledge, we selected as candidate search terms the four MeSH terms describing

Surface electromyographic amplitude does not identify differences in neural drive to synergistic muscles.

Science.gov (United States)

Martinez-Valdes, Eduardo; Negro, Francesco; Falla, Deborah; De Nunzio, Alessandro Marco; Farina, Dario

2018-04-01

Surface electromyographic (EMG) signal amplitude is typically used to compare the neural drive to muscles. We experimentally investigated this association by studying the motor unit (MU) behavior and action potentials in the vastus medialis (VM) and vastus lateralis (VL) muscles. Eighteen participants performed isometric knee extensions at four target torques [10, 30, 50, and 70% of the maximum torque (MVC)] while high-density EMG signals were recorded from the VM and VL. The absolute EMG amplitude was greater for VM than VL ( P differences in EMG amplitude can be due to both differences in the neural drive and in the size of the MU action potentials, we indirectly inferred the neural drives received by the two muscles by estimating the synaptic inputs received by the corresponding motor neuron pools. For this purpose, we analyzed the increase in discharge rate from recruitment to target torque for motor units matched by recruitment threshold in the two muscles. This analysis indicated that the two muscles received similar levels of neural drive. Nonetheless, the size of the MU action potentials was greater for VM than VL ( P difference explained most of the differences in EMG amplitude between the two muscles (~63% of explained variance). These results indicate that EMG amplitude, even following normalization, does not reflect the neural drive to synergistic muscles. Moreover, absolute EMG amplitude is mainly explained by the size of MU action potentials. NEW & NOTEWORTHY Electromyographic (EMG) amplitude is widely used to compare indirectly the strength of neural drive received by synergistic muscles. However, there are no studies validating this approach with motor unit data. Here, we compared between-muscles differences in surface EMG amplitude and motor unit behavior. The results clarify the limitations of surface EMG to interpret differences in neural drive between muscles.

Cortical sensorimotor alterations classify clinical phenotype and putative genotype of spasmodic dysphonia

Science.gov (United States)

Battistella, Giovanni; Fuertinger, Stefan; Fleysher, Lazar; Ozelius, Laurie J.; Simonyan, Kristina

2017-01-01

Background Spasmodic dysphonia (SD), or laryngeal dystonia, is a task-specific isolated focal dystonia of unknown causes and pathophysiology. Although functional and structural abnormalities have been described in this disorder, the influence of its different clinical phenotypes and genotypes remains scant, making it difficult to explain SD pathophysiology and to identify potential biomarkers. Methods We used a combination of independent component analysis and linear discriminant analysis of resting-state functional MRI data to investigate brain organization in different SD phenotypes (abductor vs. adductor type) and putative genotypes (familial vs. sporadic cases) and to characterize neural markers for genotype/phenotype categorization. Results We found abnormal functional connectivity within sensorimotor and frontoparietal networks in SD patients compared to healthy individuals as well as phenotype- and genotype-distinct alterations of these networks, involving primary somatosensory, premotor and parietal cortices. The linear discriminant analysis achieved 71% accuracy classifying SD and healthy individuals using connectivity measures in the left inferior parietal and sensorimotor cortex. When categorizing between different forms of SD, the combination of measures from left inferior parietal, premotor and right sensorimotor cortices achieved 81% discriminatory power between familial and sporadic SD cases, whereas the combination of measures from the right superior parietal, primary somatosensory and premotor cortices led to 71% accuracy in the classification of adductor and abductor SD forms. Conclusions Our findings present the first effort to identify and categorize isolated focal dystonia based on its brain functional connectivity profile, which may have a potential impact on the future development of biomarkers for this rare disorder. PMID:27346568

Cortical sensorimotor alterations classify clinical phenotype and putative genotype of spasmodic dysphonia.

Science.gov (United States)

Battistella, G; Fuertinger, S; Fleysher, L; Ozelius, L J; Simonyan, K

2016-10-01

Spasmodic dysphonia (SD), or laryngeal dystonia, is a task-specific isolated focal dystonia of unknown causes and pathophysiology. Although functional and structural abnormalities have been described in this disorder, the influence of its different clinical phenotypes and genotypes remains scant, making it difficult to explain SD pathophysiology and to identify potential biomarkers. We used a combination of independent component analysis and linear discriminant analysis of resting-state functional magnetic resonance imaging data to investigate brain organization in different SD phenotypes (abductor versus adductor type) and putative genotypes (familial versus sporadic cases) and to characterize neural markers for genotype/phenotype categorization. We found abnormal functional connectivity within sensorimotor and frontoparietal networks in patients with SD compared with healthy individuals as well as phenotype- and genotype-distinct alterations of these networks, involving primary somatosensory, premotor and parietal cortices. The linear discriminant analysis achieved 71% accuracy classifying SD and healthy individuals using connectivity measures in the left inferior parietal and sensorimotor cortices. When categorizing between different forms of SD, the combination of measures from the left inferior parietal, premotor and right sensorimotor cortices achieved 81% discriminatory power between familial and sporadic SD cases, whereas the combination of measures from the right superior parietal, primary somatosensory and premotor cortices led to 71% accuracy in the classification of adductor and abductor SD forms. Our findings present the first effort to identify and categorize isolated focal dystonia based on its brain functional connectivity profile, which may have a potential impact on the future development of biomarkers for this rare disorder. © 2016 EAN.

Neural signal processing for identifying failed fuel rods in nuclear reactors

International Nuclear Information System (INIS)

Seixas, Jose M. de; Soares Filho, William; Pereira, Wagner C.A.; Teles, Claudio C.B.

2002-01-01

Ultrasonic pulses were used for automatic detection of failed nuclear fuel rods. For experimental tests of the proposed method, an assembly prototype of 16 x 16 rods was built by using genuine rods but without fuel inside (just air). Some rods were partially filled with water to simulate cracked rods. Using neural signal processing on the received echoes of the emitted ultrasonic pulses, a detection efficiency of 97% was obtained. Neural detection is shown to outperform other classical discriminating methods and can also reveal important features of the signal structure of the received echoes. (author)

Search strings for the study of putative occupational determinants of disease

NARCIS (Netherlands)

Mattioli, S.; Zanardi, F.; Baldasseroni, A.; Schaafsma, F.; Cooke, R.M.T.; Mancini, G.; Fierro, M.; Santangelo, C.; Farioli, A.; Fucksia, S.; Curti, S.; Violante, F.S.; Verbeek, J.

2010-01-01

Objective To identify efficient PubMed search strategies to retrieve articles regarding putative occupational determinants of conditions not generally considered to be work related. Methods Based on MeSH definitions and expert knowledge, we selected as candidate search terms the four MeSH terms

Bilingualism provides a neural reserve for aging populations.

Science.gov (United States)

Abutalebi, Jubin; Guidi, Lucia; Borsa, Virginia; Canini, Matteo; Della Rosa, Pasquale A; Parris, Ben A; Weekes, Brendan S

2015-03-01

It has been postulated that bilingualism may act as a cognitive reserve and recent behavioral evidence shows that bilinguals are diagnosed with dementia about 4-5 years later compared to monolinguals. In the present study, we investigated the neural basis of these putative protective effects in a group of aging bilinguals as compared to a matched monolingual control group. For this purpose, participants completed the Erikson Flanker task and their performance was correlated to gray matter (GM) volume in order to investigate if cognitive performance predicts GM volume specifically in areas affected by aging. We performed an ex-Gaussian analysis on the resulting RTs and report that aging bilinguals performed better than aging monolinguals on the Flanker task. Bilingualism was overall associated with increased GM in the ACC. Likewise, aging induced effects upon performance correlated only for monolinguals to decreased gray matter in the DLPFC. Taken together, these neural regions might underlie the benefits of bilingualism and act as a neural reserve that protects against the cognitive decline that occurs during aging. Copyright © 2015 Elsevier Ltd. All rights reserved.

Neural plasticity in functional and anatomical MRI studies of children with Tourette syndrome

DEFF Research Database (Denmark)

Eichele, Heike; Plessen, Kerstin J

2012-01-01

Background: Tourette syndrome (TS) is a neuropsychiatric disorder with childhood onset characterized by chronic motor and vocal tics. The typical clinical course of an attenuation of symptoms during adolescence in parallel with the emerging self-regulatory control during development suggests...... that plastic processes may play an important role in the development of tic symptoms. Methods: We conducted a systematic search to identify existing imaging studies (both anatomical and functional magnetic resonance imaging [fMRI]) in young persons under the age of 19 years with TS. Results: The final search...... compensatory pathways in children with TS. Along with alterations in regions putatively representing the origin of tics, deviations in several other regions most likely represent an activity-dependent neural plasticity that help to modulate tic severity, such as the prefrontal cortex, but also in the corpus...

Transcriptional Profiling of Hypoxic Neural Stem Cells Identifies Calcineurin-NFATc4 Signaling as a Major Regulator of Neural Stem Cell Biology

Science.gov (United States)

Moreno, Marta; Fernández, Virginia; Monllau, Josep M.; Borrell, Víctor; Lerin, Carles; de la Iglesia, Núria

2015-01-01

Summary Neural stem cells (NSCs) reside in a hypoxic microenvironment within the brain. However, the crucial transcription factors (TFs) that regulate NSC biology under physiologic hypoxia are poorly understood. Here we have performed gene set enrichment analysis (GSEA) of microarray datasets from hypoxic versus normoxic NSCs with the aim of identifying pathways and TFs that are activated under oxygen concentrations mimicking normal brain tissue microenvironment. Integration of TF target (TFT) and pathway enrichment analysis identified the calcium-regulated TF NFATc4 as a major candidate to regulate hypoxic NSC functions. Nfatc4 expression was coordinately upregulated by top hypoxia-activated TFs, while NFATc4 target genes were enriched in hypoxic NSCs. Loss-of-function analyses further revealed that the calcineurin-NFATc4 signaling axis acts as a major regulator of NSC self-renewal and proliferation in vitro and in vivo by promoting the expression of TFs, including Id2, that contribute to the maintenance of the NSC state. PMID:26235896

Novel Mutation of LRP6 Identified in Chinese Han Population Links Canonical WNT Signaling to Neural Tube Defects.

Science.gov (United States)

Shi, Zhiwen; Yang, Xueyan; Li, Bin-Bin; Chen, Shuxia; Yang, Luming; Cheng, Liangping; Zhang, Ting; Wang, Hongyan; Zheng, Yufang

2018-01-15

Neural tube defects (NTDs), the second most frequent cause of human congenital abnormalities, are debilitating birth defects due to failure of neural tube closure. It has been shown that noncanonical WNT/planar cell polarity (PCP) signaling is required for convergent extension (CE), the initiation step of neural tube closure (NTC). But the effect of canonical WNT//β-catenin signaling during NTC is still elusive. LRP6 (low density lipoprotein receptor related proteins 6) was identified as a co-receptor for WNT/β-catenin signaling, but recent studies showed that it also can mediate WNT/PCP signaling. In this study, we screened mutations in the LRP6 gene in 343 NTDs and 215 ethnically matched normal controls of Chinese Han population. Three rare missense mutations (c.1514A>G, p.Y505C); c.2984A>G, p.D995G; and c.4280C>A, p.P1427Q) of the LRP6 gene were identified in Chinese NTD patients. The Y505C mutation is a loss-of-function mutation on both WNT/β-catenin and PCP signaling. The D995G mutation only partially lost inhibition on PCP signaling without affecting WNT/β-catenin signaling. The P1427Q mutation dramatically increased WNT/β-catenin signaling but only mildly loss of inhibition on PCP signaling. All three mutations failed to rescue CE defects caused by lrp6 morpholino oligos knockdown in zebrafish. Of interest, when overexpressed, D995G did not induce any defects, but Y505C and P1427Q caused more severe CE defects in zebrafish. Our results suggested that over-active canonical WNT signaling induced by gain-of-function mutation in LRP6 could also contribute to human NTDs, and a balanced WNT/β-catenin and PCP signaling is probably required for proper neural tube development. Birth Defects Research 110:63-71, 2018. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Effect of the size of an artificial neural network used as pattern identifier

International Nuclear Information System (INIS)

Reynoso V, M.R.; Vega C, J.J.

2003-01-01

A novel way to extract relevant parameters associated with the outgoing ions from nuclear reactions, obtained by digitizing the signals provided by a Bragg curve spectrometer (BCS) is presented. This allowed the implementation of a more thorough pulse-shape analysis. Due to the complexity of this task, it was required to take advantage of new and more powerful computational paradigms. This was fulfilled using a back-propagation artificial neural network (ANN) as a pattern identifier. Over training of ANNs is a common problem during the training stage. In the performance of the ANN there is a compromise between its size and the size of the training set. Here, this effect will be illustrated in relation to the problem of Bragg Curve (BC) identification. (Author)

Effect of the size of an artificial neural network used as pattern identifier

Energy Technology Data Exchange (ETDEWEB)

Reynoso V, M.R.; Vega C, J.J. [ININ, 52045 Ocoyoacac, Estado de Mexico (Mexico)

2003-07-01

A novel way to extract relevant parameters associated with the outgoing ions from nuclear reactions, obtained by digitizing the signals provided by a Bragg curve spectrometer (BCS) is presented. This allowed the implementation of a more thorough pulse-shape analysis. Due to the complexity of this task, it was required to take advantage of new and more powerful computational paradigms. This was fulfilled using a back-propagation artificial neural network (ANN) as a pattern identifier. Over training of ANNs is a common problem during the training stage. In the performance of the ANN there is a compromise between its size and the size of the training set. Here, this effect will be illustrated in relation to the problem of Bragg Curve (BC) identification. (Author)

CLONING, SEQUENCE ANALYSIS, AND CHARACTERIZATION OF PUTATIVE BETA-LACTAMASE OF STENOTROPHOMONAS MALTOPHILIA

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Chong Seng Shueh

2012-10-01

Full Text Available The main objective of current study was to explore the function of chromosomal putative beta-lactamase gene (smlt 0115 in clinical Stenotrophomonas maltophilia. Antibiotic susceptibility test (AST screening for current antimicrobial drugs was done and Minimum Inhibitory Concentration (MIC level towards beta-lactams was determined by E-test. Putative beta-lactamase gene of S. maltophilia was amplified via PCR, with specific primers, then cloned into pET-15 expression plasmid and transformed into Escherichia coli BL21. The gene was sequenced and analyzed. The expressed protein was purified by affinity chromatography and the kinetic assay was performed. S. maltophilia ATCC 13637 was included in this experiment. Besides, a hospital strain which exhibited resistant to a series of beta-lactams including cefepime was identified via AST and MIC, hence it was named as S2 strain and was considered in this study. Sequencing result showed that putative beta-lactamase gene obtained from ATCC 13637 and S2 strains were predicted to have cephalosporinase activity by National Center for Biotechnology Information (NCBI blast program. Differences in the sequences of both ATCC 13637 and S2 strains were found via ClustalW alignment software. Kinetic assay proved a cephalosporinase characteristic produced by E. coli BL21 clone that overexpressed the putative beta-lactamase gene cloned under the control of an external promoter. Yet, expressed protein purified from S2 strain had high catalytic activity against beta-lactam antibiotics which was 14-fold higher than expressed protein purified from ATCC 13637 strain. This study represents the characterization analysis of putative beta-lactamase gene (smlt 0115 of S. maltophilia. The presence of the respective gene in the chromosome of S. maltophilia suggested that putative beta-lactamase gene (smlt 0115 of S. maltophilia plays a role in beta-lactamase resistance.

Zinc and glutamate dehydrogenase in putative glutamatergic brain structures.

Science.gov (United States)

Wolf, G; Schmidt, W

1983-01-01

A certain topographic parallelism between the distribution of histochemically (TIMM staining) identified zinc and putative glutamatergic structures in the rat brain was demonstrated. Glutamate dehydrogenase as a zinc containing protein is in consideration to be an enzyme synthesizing transmitter glutamate. In a low concentration range externally added zinc ions (10(-9) to 10(-7) M) induced an increase in the activity of glutamate dehydrogenase (GDH) originating from rat hippocampal formation, neocortex, and cerebellum up to 142.4%. With rising molarity of Zn(II) in the incubation medium, the enzyme of hippocampal formation and cerebellum showed a biphasic course of activation. Zinc ions of a concentration higher than 10(-6) M caused a strong inhibition of GDH. The effect of Zn(II) on GDH originating from spinal ganglia and liver led only to a decrease of enzyme activity. These results are discussed in connection with a functional correlation between zinc and putatively glutamatergic system.

Genome-wide characterization of genetic variants and putative regions under selection in meat and egg-type chicken lines.

Science.gov (United States)

Boschiero, Clarissa; Moreira, Gabriel Costa Monteiro; Gheyas, Almas Ara; Godoy, Thaís Fernanda; Gasparin, Gustavo; Mariani, Pilar Drummond Sampaio Corrêa; Paduan, Marcela; Cesar, Aline Silva Mello; Ledur, Mônica Corrêa; Coutinho, Luiz Lehmann

2018-01-25

Meat and egg-type chickens have been selected for several generations for different traits. Artificial and natural selection for different phenotypes can change frequency of genetic variants, leaving particular genomic footprints throghtout the genome. Thus, the aims of this study were to sequence 28 chickens from two Brazilian lines (meat and white egg-type) and use this information to characterize genome-wide genetic variations, identify putative regions under selection using Fst method, and find putative pathways under selection. A total of 13.93 million SNPs and 1.36 million INDELs were identified, with more variants detected from the broiler (meat-type) line. Although most were located in non-coding regions, we identified 7255 intolerant non-synonymous SNPs, 512 stopgain/loss SNPs, 1381 frameshift and 1094 non-frameshift INDELs that may alter protein functions. Genes harboring intolerant non-synonymous SNPs affected metabolic pathways related mainly to reproduction and endocrine systems in the white-egg layer line, and lipid metabolism and metabolic diseases in the broiler line. Fst analysis in sliding windows, using SNPs and INDELs separately, identified over 300 putative regions of selection overlapping with more than 250 genes. For the first time in chicken, INDEL variants were considered for selection signature analysis, showing high level of correlation in results between SNP and INDEL data. The putative regions of selection signatures revealed interesting candidate genes and pathways related to important phenotypic traits in chicken, such as lipid metabolism, growth, reproduction, and cardiac development. In this study, Fst method was applied to identify high confidence putative regions under selection, providing novel insights into selection footprints that can help elucidate the functional mechanisms underlying different phenotypic traits relevant to meat and egg-type chicken lines. In addition, we generated a large catalog of line-specific and common

Tracking Single Units in Chronic, Large Scale, Neural Recordings for Brain Machine Interface Applications

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Ahmed eEleryan

2014-07-01

Full Text Available In the study of population coding in neurobiological systems, tracking unit identity may be critical to assess possible changes in the coding properties of neuronal constituents over prolonged periods of time. Ensuring unit stability is even more critical for reliable neural decoding of motor variables in intra-cortically controlled brain-machine interfaces (BMIs. Variability in intrinsic spike patterns, tuning characteristics, and single-unit identity over chronic use is a major challenge to maintaining this stability, requiring frequent daily calibration of neural decoders in BMI sessions by an experienced human operator. Here, we report on a unit-stability tracking algorithm that efficiently and autonomously identifies putative single-units that are stable across many sessions using a relatively short duration recording interval at the start of each session. The algorithm first builds a database of features extracted from units' average spike waveforms and firing patterns across many days of recording. It then uses these features to decide whether spike occurrences on the same channel on one day belong to the same unit recorded on another day or not. We assessed the overall performance of the algorithm for different choices of features and classifiers trained using human expert judgment, and quantified it as a function of accuracy and execution time. Overall, we found a trade-off between accuracy and execution time with increasing data volumes from chronically implanted rhesus macaques, with an average of 12 seconds processing time per channel at ~90% classification accuracy. Furthermore, 77% of the resulting putative single-units matched those tracked by human experts. These results demonstrate that over the span of a few months of recordings, automated unit tracking can be performed with high accuracy and used to streamline the calibration phase during BMI sessions.

Identification of genomic variants putatively targeted by selection during dog domestication.

Science.gov (United States)

Cagan, Alex; Blass, Torsten

2016-01-12

Dogs [Canis lupus familiaris] were the first animal species to be domesticated and continue to occupy an important place in human societies. Recent studies have begun to reveal when and where dog domestication occurred. While much progress has been made in identifying the genetic basis of phenotypic differences between dog breeds we still know relatively little about the genetic changes underlying the phenotypes that differentiate all dogs from their wild progenitors, wolves [Canis lupus]. In particular, dogs generally show reduced aggression and fear towards humans compared to wolves. Therefore, selection for tameness was likely a necessary prerequisite for dog domestication. With the increasing availability of whole-genome sequence data it is possible to try and directly identify the genetic variants contributing to the phenotypic differences between dogs and wolves. We analyse the largest available database of genome-wide polymorphism data in a global sample of dogs 69 and wolves 7. We perform a scan to identify regions of the genome that are highly differentiated between dogs and wolves. We identify putatively functional genomic variants that are segregating or at high frequency [> = 0.75 Fst] for alternative alleles between dogs and wolves. A biological pathways analysis of the genes containing these variants suggests that there has been selection on the 'adrenaline and noradrenaline biosynthesis pathway', well known for its involvement in the fight-or-flight response. We identify 11 genes with putatively functional variants fixed for alternative alleles between dogs and wolves. The segregating variants in these genes are strong candidates for having been targets of selection during early dog domestication. We present the first genome-wide analysis of the different categories of putatively functional variants that are fixed or segregating at high frequency between a global sampling of dogs and wolves. We find evidence that selection has been strongest

Neural Networks

International Nuclear Information System (INIS)

Smith, Patrick I.

2003-01-01

Physicists use large detectors to measure particles created in high-energy collisions at particle accelerators. These detectors typically produce signals indicating either where ionization occurs along the path of the particle, or where energy is deposited by the particle. The data produced by these signals is fed into pattern recognition programs to try to identify what particles were produced, and to measure the energy and direction of these particles. Ideally, there are many techniques used in this pattern recognition software. One technique, neural networks, is particularly suitable for identifying what type of particle caused by a set of energy deposits. Neural networks can derive meaning from complicated or imprecise data, extract patterns, and detect trends that are too complex to be noticed by either humans or other computer related processes. To assist in the advancement of this technology, Physicists use a tool kit to experiment with several neural network techniques. The goal of this research is interface a neural network tool kit into Java Analysis Studio (JAS3), an application that allows data to be analyzed from any experiment. As the final result, a physicist will have the ability to train, test, and implement a neural network with the desired output while using JAS3 to analyze the results or output. Before an implementation of a neural network can take place, a firm understanding of what a neural network is and how it works is beneficial. A neural network is an artificial representation of the human brain that tries to simulate the learning process [5]. It is also important to think of the word artificial in that definition as computer programs that use calculations during the learning process. In short, a neural network learns by representative examples. Perhaps the easiest way to describe the way neural networks learn is to explain how the human brain functions. The human brain contains billions of neural cells that are responsible for processing

Crystal structure and putative substrate identification for the Entamoeba histolytica low molecular weight tyrosine phosphatase.

Science.gov (United States)

Linford, Alicia S; Jiang, Nona M; Edwards, Thomas E; Sherman, Nicholas E; Van Voorhis, Wesley C; Stewart, Lance J; Myler, Peter J; Staker, Bart L; Petri, William A

2014-01-01

Entamoeba histolytica is a eukaryotic intestinal parasite of humans, and is endemic in developing countries. We have characterized the E. histolytica putative low molecular weight protein tyrosine phosphatase (LMW-PTP). The structure for this amebic tyrosine phosphatase was solved, showing the ligand-induced conformational changes necessary for binding of substrate. In amebae, it was expressed at low but detectable levels as detected by immunoprecipitation followed by immunoblotting. A mutant LMW-PTP protein in which the catalytic cysteine in the active site was replaced with a serine lacked phosphatase activity, and was used to identify a number of trapped putative substrate proteins via mass spectrometry analysis. Seven of these putative substrate protein genes were cloned with an epitope tag and overexpressed in amebae. Five of these seven putative substrate proteins were demonstrated to interact specifically with the mutant LMW-PTP. This is the first biochemical study of a small tyrosine phosphatase in Entamoeba, and sets the stage for understanding its role in amebic biology and pathogenesis. Copyright © 2014 Elsevier B.V. All rights reserved.

Single-Cell Transcriptomic Analysis Defines Heterogeneity and Transcriptional Dynamics in the Adult Neural Stem Cell Lineage

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Ben W. Dulken

2017-01-01

Full Text Available Neural stem cells (NSCs in the adult mammalian brain serve as a reservoir for the generation of new neurons, oligodendrocytes, and astrocytes. Here, we use single-cell RNA sequencing to characterize adult NSC populations and examine the molecular identities and heterogeneity of in vivo NSC populations. We find that cells in the NSC lineage exist on a continuum through the processes of activation and differentiation. Interestingly, rare intermediate states with distinct molecular profiles can be identified and experimentally validated, and our analysis identifies putative surface markers and key intracellular regulators for these subpopulations of NSCs. Finally, using the power of single-cell profiling, we conduct a meta-analysis to compare in vivo NSCs and in vitro cultures, distinct fluorescence-activated cell sorting strategies, and different neurogenic niches. These data provide a resource for the field and contribute to an integrative understanding of the adult NSC lineage.

Use of neural networks to identify transient operating conditions in nuclear power plants

International Nuclear Information System (INIS)

Uhrig, R.E.; Guo, Z.

1989-01-01

A technique using neural networks as a means of diagnosing specific abnormal conditions or problems in nuclear power plants is investigated and found to be feasible. The technique is based on the fact that each physical state of the plant can be represented by a unique pattern of instrument readings, which can be related to the condition of the plant. Neural networks are used to relate this pattern to the fault or problem. 3 refs., 2 figs., 4 tabs

Identification of EhTIF-IA: The putative E. histolytica orthologue of the ...

Indian Academy of Sciences (India)

2016-02-04

Feb 4, 2016 ... We have identified the E. histolytica equivalent of TIF-1A (EhTIF-IA) by homology search within ..... a putative EhTIF-IA with e-value (3e−25). Comparison of .... some biogenesis is correlated with altered rates of rDNA transcription ..... ylation by CK2 facilitates rDNA transcription by promoting dissociation of ...

Application of a Colorimetric Assay to Identify Putative Ribofuranosylaminobenzene 5'-Phosphate Synthase Genes Expressed with Activity in Escherichia coli

Directory of Open Access Journals (Sweden)

Bechard Matthew E.

2003-01-01

Full Text Available Tetrahydromethanopterin (H4MPT is a tetrahydrofolate analog originally discovered in methanogenic archaea, but later found in other archaea and bacteria. The extent to which H4MPT occurs among living organisms is unknown. The key enzyme which distinguishes the biosynthetic pathways of H4MPT and tetrahydrofolate is ribofuranosylaminobenzene 5'-phosphate synthase (RFAP synthase. Given the importance of RFAP synthase in H4MPT biosynthesis, the identification of putative RFAP synthase genes and measurement of RFAP synthase activity would provide an indication of the presence of H4MPT in untested microorganisms. Investigation of putative archaeal RFAP synthase genes has been hampered by the tendency of the resulting proteins to form inactive inclusion bodies in Escherichia coli. The current work describes a colorimetric assay for measuring RFAP synthase activity, and two modified procedures for expressing recombinant RFAP synthase genes to produce soluble, active enzyme. By lowering the incubation temperature during expression, RFAP synthase from Archaeoglobus fulgidus was produced in E. coli and purified to homogeneity. The production of active RFAP synthase from Methanothermobacter thermautotrophicus was achieved by coexpression of the gene MTH0830 with a molecular chaperone. This is the first direct biochemical identification of a methanogen gene that codes for an active RFAP synthase.

Application of a Colorimetric Assay to Identify Putative Ribofuranosylaminobenzene 5'-Phosphate Synthase Genes Expressed with Activity in Escherichia coli.

Science.gov (United States)

Bechard, Matthew E.; Chhatwal, Sonya; Garcia, Rosemarie E.; Rasche, Madeline E.

2003-01-01

Tetrahydromethanopterin (H(4)MPT) is a tetrahydrofolate analog originally discovered in methanogenic archaea, but later found in other archaea and bacteria. The extent to which H(4)MPT occurs among living organisms is unknown. The key enzyme which distinguishes the biosynthetic pathways of H(4)MPT and tetrahydrofolate is ribofuranosylaminobenzene 5'-phosphate synthase (RFAP synthase). Given the importance of RFAP synthase in H(4)MPT biosynthesis, the identification of putative RFAP synthase genes and measurement of RFAP synthase activity would provide an indication of the presence of H(4)MPT in untested microorganisms. Investigation of putative archaeal RFAP synthase genes has been hampered by the tendency of the resulting proteins to form inactive inclusion bodies in Escherichia coli. The current work describes a colorimetric assay for measuring RFAP synthase activity, and two modified procedures for expressing recombinant RFAP synthase genes to produce soluble, active enzyme. By lowering the incubation temperature during expression, RFAP synthase from Archaeoglobus fulgidus was produced in E. coli and purified to homogeneity. The production of active RFAP synthase from Methanothermobacter thermautotrophicus was achieved by coexpression of the gene MTH0830 with a molecular chaperone. This is the first direct biochemical identification of a methanogen gene that codes for an active RFAP synthase.

Genome-wide analysis of putative peroxiredoxin in unicellular and filamentous cyanobacteria

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Cui Hongli

2012-11-01

Full Text Available Abstract Background Cyanobacteria are photoautotrophic prokaryotes with wide variations in genome sizes and ecological habitats. Peroxiredoxin (PRX is an important protein that plays essential roles in protecting own cells against reactive oxygen species (ROS. PRXs have been identified from mammals, fungi and higher plants. However, knowledge on cyanobacterial PRXs still remains obscure. With the availability of 37 sequenced cyanobacterial genomes, we performed a comprehensive comparative analysis of PRXs and explored their diversity, distribution, domain structure and evolution. Results Overall 244 putative prx genes were identified, which were abundant in filamentous diazotrophic cyanobacteria, Acaryochloris marina MBIC 11017, and unicellular cyanobacteria inhabiting freshwater and hot-springs, while poor in all Prochlorococcus and marine Synechococcus strains. Among these putative genes, 25 open reading frames (ORFs encoding hypothetical proteins were identified as prx gene family members and the others were already annotated as prx genes. All 244 putative PRXs were classified into five major subfamilies (1-Cys, 2-Cys, BCP, PRX5_like, and PRX-like according to their domain structures. The catalytic motifs of the cyanobacterial PRXs were similar to those of eukaryotic PRXs and highly conserved in all but the PRX-like subfamily. Classical motif (CXXC of thioredoxin was detected in protein sequences from the PRX-like subfamily. Phylogenetic tree constructed of catalytic domains coincided well with the domain structures of PRXs and the phylogenies based on 16s rRNA. Conclusions The distribution of genes encoding PRXs in different unicellular and filamentous cyanobacteria especially those sub-families like PRX-like or 1-Cys PRX correlate with the genome size, eco-physiology, and physiological properties of the organisms. Cyanobacterial and eukaryotic PRXs share similar conserved motifs, indicating that cyanobacteria adopt similar catalytic

Genome-wide analysis of putative peroxiredoxin in unicellular and filamentous cyanobacteria.

Science.gov (United States)

Cui, Hongli; Wang, Yipeng; Wang, Yinchu; Qin, Song

2012-11-16

Cyanobacteria are photoautotrophic prokaryotes with wide variations in genome sizes and ecological habitats. Peroxiredoxin (PRX) is an important protein that plays essential roles in protecting own cells against reactive oxygen species (ROS). PRXs have been identified from mammals, fungi and higher plants. However, knowledge on cyanobacterial PRXs still remains obscure. With the availability of 37 sequenced cyanobacterial genomes, we performed a comprehensive comparative analysis of PRXs and explored their diversity, distribution, domain structure and evolution. Overall 244 putative prx genes were identified, which were abundant in filamentous diazotrophic cyanobacteria, Acaryochloris marina MBIC 11017, and unicellular cyanobacteria inhabiting freshwater and hot-springs, while poor in all Prochlorococcus and marine Synechococcus strains. Among these putative genes, 25 open reading frames (ORFs) encoding hypothetical proteins were identified as prx gene family members and the others were already annotated as prx genes. All 244 putative PRXs were classified into five major subfamilies (1-Cys, 2-Cys, BCP, PRX5_like, and PRX-like) according to their domain structures. The catalytic motifs of the cyanobacterial PRXs were similar to those of eukaryotic PRXs and highly conserved in all but the PRX-like subfamily. Classical motif (CXXC) of thioredoxin was detected in protein sequences from the PRX-like subfamily. Phylogenetic tree constructed of catalytic domains coincided well with the domain structures of PRXs and the phylogenies based on 16s rRNA. The distribution of genes encoding PRXs in different unicellular and filamentous cyanobacteria especially those sub-families like PRX-like or 1-Cys PRX correlate with the genome size, eco-physiology, and physiological properties of the organisms. Cyanobacterial and eukaryotic PRXs share similar conserved motifs, indicating that cyanobacteria adopt similar catalytic mechanisms as eukaryotes. All cyanobacterial PRX proteins

Expression of putative expansin genes in phylloxera (Daktulosphaira vitifoliae Fitch) induced root galls of Vitis spp.

Science.gov (United States)

Lawo, N C; Griesser, M; Forneck, A

Grape phylloxera ( Daktulosphaira vitifoliae Fitch) is a serious global pest in viticulture. The insects are sedentary feeders and require a gall to feed and reproduce. The insects induce their feeding site within the meristematic zone of the root tip, where they stay attached, feeding both intra- and intercellularly, and causing damage by reducing plant vigour. Several changes in cell structure and composition, including increased cell division and tissue swelling close to the feeding site, cause an organoid gall called a nodosity to develop. Because alpha expansin genes are involved in cell enlargement and cell wall loosening in many plant tissues it may be anticipated that they are also involved in nodosity formation. To identify expansin genes in Vitis vinifera cv. Pinot noir , we mined for orthologues genes in a comparative analysis. Eleven putative expansin genes were identified and shown to be present in the rootstock Teleki 5C ( V. berlandieri Planch. x V. riparia Michx.) using specific PCR followed by DNA sequencing. Expression analysis of young and mature nodosities and uninfested root tips were conducted via quantitative real time PCR (qRT-PCR). Up-regulation was measured for three putative expansin genes (VvEXPA15, -A17 and partly -A20) or down-regulation for three other putative genes (VvEXPA7, -A12, -A20) in nodosities. The present study clearly shows the involvement of putative expansin genes in the phylloxera-root interaction.

Distribution and morphology of cholinergic, putative catecholaminergic and serotonergic neurons in the brain of the Egyptian rousette flying fox, Rousettus aegyptiacus.

Science.gov (United States)

Maseko, Busisiwe C; Bourne, James A; Manger, Paul R

2007-11-01

Over the past decade much controversy has surrounded the hypothesis that the megachiroptera, or megabats, share unique neural characteristics with the primates. These observations, which include similarities in visual pathways, have suggested that the megabats are more closely related to the primates than to the other group of the Chiropteran order, the microbats, and suggests a diphyletic origin of the Chiroptera. To contribute data relevant to this debate, we used immunohistochemical techniques to reveal the architecture of the neuromodulatory systems of the Egyptian rousette (Rousettus aegypticus), an echolocating megabat. Our findings revealed many similarities in the nuclear parcellation of the cholinergic, putative catecholaminergic and serotonergic systems with that seen in other mammals including the microbat. However, there were 11 discrete nuclei forming part of these systems in the brain of the megabat studied that were not evident in an earlier study of a microbat. The occurrence of these nuclei align the megabat studied more closely with primates than any other mammalian group and clearly distinguishes them from the microbat, which aligns with the insectivores. The neural systems investigated are not related to such Chiropteran specializations as echolocation, flight, vision or olfaction. If neural characteristics are considered strong indicators of phylogenetic relationships, then the data of the current study strongly supports the diphyletic origin of Chiroptera and aligns the megabat most closely with primates in agreement with studies of other neural characters.

Analysis of Hydraulic Flood Control Structure at Putat Boro River

OpenAIRE

Ruzziyatno, Ruhban

2015-01-01

Putat Boro River is one of the main drainage systems of Surakarta city which drains into Bengawan Solo river. The primary problem when flood occur is the higher water level of Bengawan Solo than Boro River and then backwater occur and inundates Putat Boro River. The objective of the study is to obtain operational method of Putat Boro River floodgate to control both inflows and outflows not only during flood but also normal condition. It also aims to know the Putat Boro rivers floodgate op...

Application of a Colorimetric Assay to Identify Putative Ribofuranosylaminobenzene 5'-Phosphate Synthase Genes Expressed with Activity in Escherichia coli

OpenAIRE

Bechard, Matthew E.; Chhatwal, Sonya; Garcia, Rosemarie E.; Rasche, Madeline E.

2003-01-01

Tetrahydromethanopterin (H4MPT) is a tetrahydrofolate analog originally discovered in methanogenic archaea, but later found in other archaea and bacteria. The extent to which H4MPT occurs among living organisms is unknown. The key enzyme which distinguishes the biosynthetic pathways of H4MPT and tetrahydrofolate is ribofuranosylaminobenzene 5'-phosphate synthase (RFAP synthase). Given the importance of RFAP synthase in H4MPT biosynthesis, the identification of putative RFAP synthase genes and...

Incorporating deep learning with convolutional neural networks and position specific scoring matrices for identifying electron transport proteins.

Science.gov (United States)

Le, Nguyen-Quoc-Khanh; Ho, Quang-Thai; Ou, Yu-Yen

2017-09-05

In several years, deep learning is a modern machine learning technique using in a variety of fields with state-of-the-art performance. Therefore, utilization of deep learning to enhance performance is also an important solution for current bioinformatics field. In this study, we try to use deep learning via convolutional neural networks and position specific scoring matrices to identify electron transport proteins, which is an important molecular function in transmembrane proteins. Our deep learning method can approach a precise model for identifying of electron transport proteins with achieved sensitivity of 80.3%, specificity of 94.4%, and accuracy of 92.3%, with MCC of 0.71 for independent dataset. The proposed technique can serve as a powerful tool for identifying electron transport proteins and can help biologists understand the function of the electron transport proteins. Moreover, this study provides a basis for further research that can enrich a field of applying deep learning in bioinformatics. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Evaluation of neural networks to identify types of activity using accelerometers

NARCIS (Netherlands)

Vries, S.I. de; Garre, F.G.; Engbers, L.H.; Hildebrandt, V.H.; Buuren, S. van

2011-01-01

Purpose: To develop and evaluate two artificial neural network (ANN) models based on single-sensor accelerometer data and an ANN model based on the data of two accelerometers for the identification of types of physical activity in adults. Methods: Forty-nine subjects (21 men and 28 women; age range

Twenty putative palmitoyl-acyl transferase genes with distinct ...

African Journals Online (AJOL)

There are 20 genes containing DHHC domain predicted to encode putative palmitoyltransferase in Arabidopsis thaliana genome. However, little is known about their characteristics such as genetic relationship and expression profile. Here, we present an overview of the putative PAT genes in A. thaliana focusing on their ...

Differential expression patterns in chemosensory and non-chemosensory tissues of putative chemosensory genes identified by transcriptome analysis of insect pest the purple stem borer Sesamia inferens (Walker.

Directory of Open Access Journals (Sweden)

Ya-Nan Zhang

Full Text Available BACKGROUND: A large number of insect chemosensory genes from different gene subfamilies have been identified and annotated, but their functional diversity and complexity are largely unknown. A systemic examination of expression patterns in chemosensory organs could provide important information. METHODOLOGY/PRINCIPAL FINDINGS: We identified 92 putative chemosensory genes by analysing the transcriptome of the antennae and female sex pheromone gland of the purple stem borer Sesamia inferens, among them 87 are novel in this species, including 24 transcripts encoding for odorant binding proteins (OBPs, 24 for chemosensory proteins (CSPs, 2 for sensory neuron membrane proteins (SNMPs, 39 for odorant receptors (ORs and 3 for ionotropic receptors (IRs. The transcriptome analyses were validated and quantified with a detailed global expression profiling by Reverse Transcription-PCR for all 92 transcripts and by Quantitative Real Time RT-PCR for selected 16 ones. Among the chemosensory gene subfamilies, CSP transcripts are most widely and evenly expressed in different tissues and stages, OBP transcripts showed a clear antenna bias and most of OR transcripts are only detected in adult antennae. Our results also revealed that some OR transcripts, such as the transcripts of SNMP2 and 2 IRs were expressed in non-chemosensory tissues, and some CSP transcripts were antenna-biased expression. Furthermore, no chemosensory transcript is specific to female sex pheromone gland and very few are found in the heads. CONCLUSION: Our study revealed that there are a large number of chemosensory genes expressed in S. inferens, and some of them displayed unusual expression profile in non-chemosensory tissues. The identification of a large set of putative chemosensory genes of each subfamily from a single insect species, together with their different expression profiles provide further information in understanding the functions of these chemosensory genes in S. inferens as

Differential expression patterns in chemosensory and non-chemosensory tissues of putative chemosensory genes identified by transcriptome analysis of insect pest the purple stem borer Sesamia inferens (Walker).

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Zhang, Ya-Nan; Jin, Jun-Yan; Jin, Rong; Xia, Yi-Han; Zhou, Jing-Jiang; Deng, Jian-Yu; Dong, Shuang-Lin

2013-01-01

A large number of insect chemosensory genes from different gene subfamilies have been identified and annotated, but their functional diversity and complexity are largely unknown. A systemic examination of expression patterns in chemosensory organs could provide important information. We identified 92 putative chemosensory genes by analysing the transcriptome of the antennae and female sex pheromone gland of the purple stem borer Sesamia inferens, among them 87 are novel in this species, including 24 transcripts encoding for odorant binding proteins (OBPs), 24 for chemosensory proteins (CSPs), 2 for sensory neuron membrane proteins (SNMPs), 39 for odorant receptors (ORs) and 3 for ionotropic receptors (IRs). The transcriptome analyses were validated and quantified with a detailed global expression profiling by Reverse Transcription-PCR for all 92 transcripts and by Quantitative Real Time RT-PCR for selected 16 ones. Among the chemosensory gene subfamilies, CSP transcripts are most widely and evenly expressed in different tissues and stages, OBP transcripts showed a clear antenna bias and most of OR transcripts are only detected in adult antennae. Our results also revealed that some OR transcripts, such as the transcripts of SNMP2 and 2 IRs were expressed in non-chemosensory tissues, and some CSP transcripts were antenna-biased expression. Furthermore, no chemosensory transcript is specific to female sex pheromone gland and very few are found in the heads. Our study revealed that there are a large number of chemosensory genes expressed in S. inferens, and some of them displayed unusual expression profile in non-chemosensory tissues. The identification of a large set of putative chemosensory genes of each subfamily from a single insect species, together with their different expression profiles provide further information in understanding the functions of these chemosensory genes in S. inferens as well as other insects.

The Challenges of Neural Mind-reading Paradigms

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Oscar eVilarroya

2013-06-01

Full Text Available Neural mind-reading studies, based on multivariate pattern analysis (MVPA methods, are providing exciting new studies. Some of the results obtained with these paradigms have raised high expectations, such as the possibility of creating brain reading devices. However, such hopes are based on the assumptions that: a the BOLD signal is a marker of neural activity; b the BOLD pattern identified by a MVPA is a neurally sound pattern; c the MVPA’s feature space is a good mapping of the neural representation of a stimulus, and d the pattern identified by a MVPA corresponds to a representation. I examine here the challenges that still have to be met before fully accepting such assumptions.

The challenges of neural mind-reading paradigms.

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Vilarroya, Oscar

2013-01-01

Neural mind-reading studies, based on multivariate pattern analysis (MVPA) methods, are providing exciting new studies. Some of the results obtained with these paradigms have raised high expectations, such as the possibility of creating brain reading devices. However, such hopes are based on the assumptions that: (a) the BOLD signal is a marker of neural activity; (b) the BOLD pattern identified by a MVPA is a neurally sound pattern; (c) the MVPA's feature space is a good mapping of the neural representation of a stimulus, and (d) the pattern identified by a MVPA corresponds to a representation. I examine here the challenges that still have to be met before fully accepting such assumptions.

A Neural Network Approach for Identifying Particle Pitch Angle Distributions in Van Allen Probes Data

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Souza, V. M.; Vieira, L. E. A.; Medeiros, C.; Da Silva, L. A.; Alves, L. R.; Koga, D.; Sibeck, D. G.; Walsh, B. M.; Kanekal, S. G.; Jauer, P. R.;

Does bilingualism contribute to cognitive reserve? Cognitive and neural perspectives.

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Guzmán-Vélez, Edmarie; Tranel, Daniel

2015-01-01

Cognitive reserve refers to how individuals actively utilize neural resources to cope with neuropathology to maintain cognitive functioning. The present review aims to critically examine the literature addressing the relationship between bilingualism and cognitive reserve to elucidate whether bilingualism delays the onset of cognitive and behavioral manifestations of dementia. Potential neural mechanisms behind this relationship are discussed. PubMed and PsycINFO databases were searched (through January 2014) for original research articles in English or Spanish languages. The following search strings were used as keywords for study retrieval: "bilingual AND reserve," "reserve AND neural mechanisms," and "reserve AND multilingualism." Growing scientific evidence suggests that lifelong bilingualism contributes to cognitive reserve and delays the onset of Alzheimer's disease symptoms, allowing bilingual individuals affected by Alzheimer's disease to live an independent and richer life for a longer time than their monolingual counterparts. Lifelong bilingualism is related to more efficient use of brain resources that help individuals maintain cognitive functioning in the presence of neuropathology. We propose multiple putative neural mechanisms through which lifelong bilinguals cope with neuropathology. The roles of immigration status, education, age of onset, proficiency, and frequency of language use on the relationship between cognitive reserve and bilingualism are considered. Implications of these results for preventive practices and future research are discussed. PsycINFO Database Record (c) 2015 APA, all rights reserved.

Does Bilingualism Contribute to Cognitive Reserve? Cognitive and Neural Perspectives

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Guzmán-Vélez, Edmarie; Tranel, Daniel

2015-01-01

Objective Cognitive reserve refers to how individuals actively utilize neural resources to cope with neuropathology in order to maintain cognitive functioning. The present review aims to critically examine the literature addressing the relationship between bilingualism and cognitive reserve in order to elucidate whether bilingualism delays the onset of cognitive and behavioral manifestations of dementia. Potential neural mechanisms behind this relationship are discussed. Method Pubmed and PsychINFO databases were searched (through January 2014) for original research articles in English or Spanish languages. The following search strings were employed as keywords for study retrieval: ‘bilingual AND reserve’, ‘reserve AND neural mechanisms’, and ‘reserve AND multilingualism’. Results Growing scientific evidence suggests that lifelong bilingualism contributes to cognitive reserve and delays the onset of Alzheimer's disease symptoms, allowing bilingual individuals affected by Alzheimer's disease to live an independent and richer life for a longer time than their monolingual counterparts. Lifelong bilingualism is related to more efficient use of brain resources that help individuals maintain cognitive functioning in the presence of neuropathology. We propose multiple putative neural mechanisms through which lifelong bilinguals cope with neuropathology. The roles of immigration status, education, age of onset, proficiency and frequency of language use on the relationship between cognitive reserve and bilingualism are considered. Conclusions Implications of these results for preventive practices and future research are discussed. PMID:24933492

Neural Representations of Physics Concepts.

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Mason, Robert A; Just, Marcel Adam

2016-06-01

We used functional MRI (fMRI) to assess neural representations of physics concepts (momentum, energy, etc.) in juniors, seniors, and graduate students majoring in physics or engineering. Our goal was to identify the underlying neural dimensions of these representations. Using factor analysis to reduce the number of dimensions of activation, we obtained four physics-related factors that were mapped to sets of voxels. The four factors were interpretable as causal motion visualization, periodicity, algebraic form, and energy flow. The individual concepts were identifiable from their fMRI signatures with a mean rank accuracy of .75 using a machine-learning (multivoxel) classifier. Furthermore, there was commonality in participants' neural representation of physics; a classifier trained on data from all but one participant identified the concepts in the left-out participant (mean accuracy = .71 across all nine participant samples). The findings indicate that abstract scientific concepts acquired in an educational setting evoke activation patterns that are identifiable and common, indicating that science education builds abstract knowledge using inherent, repurposed brain systems. © The Author(s) 2016.

Neural mechanisms of selective attention in the somatosensory system.

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Gomez-Ramirez, Manuel; Hysaj, Kristjana; Niebur, Ernst

2016-09-01

Selective attention allows organisms to extract behaviorally relevant information while ignoring distracting stimuli that compete for the limited resources of their central nervous systems. Attention is highly flexible, and it can be harnessed to select information based on sensory modality, within-modality feature(s), spatial location, object identity, and/or temporal properties. In this review, we discuss the body of work devoted to understanding mechanisms of selective attention in the somatosensory system. In particular, we describe the effects of attention on tactile behavior and corresponding neural activity in somatosensory cortex. Our focus is on neural mechanisms that select tactile stimuli based on their location on the body (somatotopic-based attention) or their sensory feature (feature-based attention). We highlight parallels between selection mechanisms in touch and other sensory systems and discuss several putative neural coding schemes employed by cortical populations to signal the behavioral relevance of sensory inputs. Specifically, we contrast the advantages and disadvantages of using a gain vs. spike-spike correlation code for representing attended sensory stimuli. We favor a neural network model of tactile attention that is composed of frontal, parietal, and subcortical areas that controls somatosensory cells encoding the relevant stimulus features to enable preferential processing throughout the somatosensory hierarchy. Our review is based on data from noninvasive electrophysiological and imaging data in humans as well as single-unit recordings in nonhuman primates. Copyright © 2016 the American Physiological Society.

The Neural Basis of Vocal Pitch Imitation in Humans.

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Belyk, Michel; Pfordresher, Peter Q; Liotti, Mario; Brown, Steven

2016-04-01

Vocal imitation is a phenotype that is unique to humans among all primate species, and so an understanding of its neural basis is critical in explaining the emergence of both speech and song in human evolution. Two principal neural models of vocal imitation have emerged from a consideration of nonhuman animals. One hypothesis suggests that putative mirror neurons in the inferior frontal gyrus pars opercularis of Broca's area may be important for imitation. An alternative hypothesis derived from the study of songbirds suggests that the corticostriate motor pathway performs sensorimotor processes that are specific to vocal imitation. Using fMRI with a sparse event-related sampling design, we investigated the neural basis of vocal imitation in humans by comparing imitative vocal production of pitch sequences with both nonimitative vocal production and pitch discrimination. The strongest difference between these tasks was found in the putamen bilaterally, providing a striking parallel to the role of the analogous region in songbirds. Other areas preferentially activated during imitation included the orofacial motor cortex, Rolandic operculum, and SMA, which together outline the corticostriate motor loop. No differences were seen in the inferior frontal gyrus. The corticostriate system thus appears to be the central pathway for vocal imitation in humans, as predicted from an analogy with songbirds.

Brain Injury Expands the Numbers of Neural Stem Cells and Progenitors in the SVZ by Enhancing Their Responsiveness to EGF

Directory of Open Access Journals (Sweden)

Dhivyaa Alagappan

2009-04-01

Full Text Available There is an increase in the numbers of neural precursors in the SVZ (subventricular zone after moderate ischaemic injuries, but the extent of stem cell expansion and the resultant cell regeneration is modest. Therefore our studies have focused on understanding the signals that regulate these processes towards achieving a more robust amplification of the stem/progenitor cell pool. The goal of the present study was to evaluate the role of the EGFR [EGF (epidermal growth factor receptor] in the regenerative response of the neonatal SVZ to hypoxic/ischaemic injury. We show that injury recruits quiescent cells in the SVZ to proliferate, that they divide more rapidly and that there is increased EGFR expression on both putative stem cells and progenitors. With the amplification of the precursors in the SVZ after injury there is enhanced sensitivity to EGF, but not to FGF (fibroblast growth factor-2. EGF-dependent SVZ precursor expansion, as measured using the neurosphere assay, is lost when the EGFR is pharmacologically inhibited, and forced expression of a constitutively active EGFR is sufficient to recapitulate the exaggerated proliferation of the neural stem/progenitors that is induced by hypoxic/ischaemic brain injury. Cumulatively, our results reveal that increased EGFR signalling precedes that increase in the abundance of the putative neural stem cells and our studies implicate the EGFR as a key regulator of the expansion of SVZ precursors in response to brain injury. Thus modulating EGFR signalling represents a potential target for therapies to enhance brain repair from endogenous neural precursors following hypoxic/ischaemic and other brain injuries.

Abnormal neural activation patterns underlying working memory impairment in chronic phencyclidine-treated mice.

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Yosefu Arime

Full Text Available Working memory impairment is a hallmark feature of schizophrenia and is thought be caused by dysfunctions in the prefrontal cortex (PFC and associated brain regions. However, the neural circuit anomalies underlying this impairment are poorly understood. The aim of this study is to assess working memory performance in the chronic phencyclidine (PCP mouse model of schizophrenia, and to identify the neural substrates of working memory. To address this issue, we conducted the following experiments for mice after withdrawal from chronic administration (14 days of either saline or PCP (10 mg/kg: (1 a discrete paired-trial variable-delay task in T-maze to assess working memory, and (2 brain-wide c-Fos mapping to identify activated brain regions relevant to this task performance either 90 min or 0 min after the completion of the task, with each time point examined under working memory effort and basal conditions. Correct responses in the test phase of the task were significantly reduced across delays (5, 15, and 30 s in chronic PCP-treated mice compared with chronic saline-treated controls, suggesting delay-independent impairments in working memory in the PCP group. In layer 2-3 of the prelimbic cortex, the number of working memory effort-elicited c-Fos+ cells was significantly higher in the chronic PCP group than in the chronic saline group. The main effect of working memory effort relative to basal conditions was to induce significantly increased c-Fos+ cells in the other layers of prelimbic cortex and the anterior cingulate and infralimbic cortex regardless of the different chronic regimens. Conversely, this working memory effort had a negative effect (fewer c-Fos+ cells in the ventral hippocampus. These results shed light on some putative neural networks relevant to working memory impairments in mice chronically treated with PCP, and emphasize the importance of the layer 2-3 of the prelimbic cortex of the PFC.

Complete Genome Sequence of a Putative Densovirus of the Asian Citrus Psyllid, Diaphorina citri

OpenAIRE

Nigg, Jared C.; Nouri, Shahideh; Falk, Bryce W.

2016-01-01

Here, we report the complete genome sequence of a putative densovirus of the Asian citrus psyllid, Diaphorina citri. Diaphorina citri densovirus (DcDNV) was originally identified through metagenomics, and here, we obtained the complete nucleotide sequence using PCR-based approaches. Phylogenetic analysis places DcDNV between viruses of the Ambidensovirus and Iteradensovirus genera.

Affective neural response to restricted interests in autism spectrum disorders.

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Cascio, Carissa J; Foss-Feig, Jennifer H; Heacock, Jessica; Schauder, Kimberly B; Loring, Whitney A; Rogers, Baxter P; Pryweller, Jennifer R; Newsom, Cassandra R; Cockhren, Jurnell; Cao, Aize; Bolton, Scott

2014-01-01

Restricted interests are a class of repetitive behavior in autism spectrum disorders (ASD) whose intensity and narrow focus often contribute to significant interference with daily functioning. While numerous neuroimaging studies have investigated executive circuits as putative neural substrates of repetitive behavior, recent work implicates affective neural circuits in restricted interests. We sought to explore the role of affective neural circuits and determine how restricted interests are distinguished from hobbies or interests in typical development. We compared a group of children with ASD to a typically developing (TD) group of children with strong interests or hobbies, employing parent report, an operant behavioral task, and functional imaging with personalized stimuli based on individual interests. While performance on the operant task was similar between the two groups, parent report of intensity and interference of interests was significantly higher in the ASD group. Both the ASD and TD groups showed increased BOLD response in widespread affective neural regions to the pictures of their own interest. When viewing pictures of other children's interests, the TD group showed a similar pattern, whereas BOLD response in the ASD group was much more limited. Increased BOLD response in the insula and anterior cingulate cortex distinguished the ASD from the TD group, and parent report of the intensity and interference with daily life of the child's restricted interest predicted insula response. While affective neural network response and operant behavior are comparable in typical and restricted interests, the narrowness of focus that clinically distinguishes restricted interests in ASD is reflected in more interference in daily life and aberrantly enhanced insula and anterior cingulate response to individuals' own interests in the ASD group. These results further support the involvement of affective neural networks in repetitive behaviors in ASD. © 2013 The

Identifying beneficial task relations for multi-task learning in deep neural networks

DEFF Research Database (Denmark)

Bingel, Joachim; Søgaard, Anders

2017-01-01

Multi-task learning (MTL) in deep neural networks for NLP has recently received increasing interest due to some compelling benefits, including its potential to efficiently regularize models and to reduce the need for labeled data. While it has brought significant improvements in a number of NLP...

Bilingualism, dementia, cognitive and neural reserve.

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Perani, Daniela; Abutalebi, Jubin

2015-12-01

We discuss the role of bilingualism as a source of cognitive reserve and we propose the putative neural mechanisms through which lifelong bilingualism leads to a neural reserve that delays the onset of dementia. Recent findings highlight that the use of more than one language affects the human brain in terms of anatomo-structural changes. It is noteworthy that recent evidence from different places and cultures throughout the world points to a significant delay of dementia onset in bilingual/multilingual individuals. This delay has been reported not only for Alzheimer's dementia and its prodromal mild cognitive impairment phase, but also for other dementias such as vascular and fronto-temporal dementia, and was found to be independent of literacy, education and immigrant status. Lifelong bilingualism represents a powerful cognitive reserve delaying the onset of dementia by approximately 4 years. As to the causal mechanism, because speaking more than one language heavily relies upon executive control and attention, brain systems handling these functions are more developed in bilinguals resulting in increases of gray and white matter densities that may help protect from dementia onset. These neurocognitive benefits are even more prominent when second language proficiency and exposure are kept high throughout life.

Duplications and losses in gene families of rust pathogens highlight putative effectors.

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Pendleton, Amanda L; Smith, Katherine E; Feau, Nicolas; Martin, Francis M; Grigoriev, Igor V; Hamelin, Richard; Nelson, C Dana; Burleigh, J Gordon; Davis, John M

2014-01-01

Rust fungi are a group of fungal pathogens that cause some of the world's most destructive diseases of trees and crops. A shared characteristic among rust fungi is obligate biotrophy, the inability to complete a lifecycle without a host. This dependence on a host species likely affects patterns of gene expansion, contraction, and innovation within rust pathogen genomes. The establishment of disease by biotrophic pathogens is reliant upon effector proteins that are encoded in the fungal genome and secreted from the pathogen into the host's cell apoplast or within the cells. This study uses a comparative genomic approach to elucidate putative effectors and determine their evolutionary histories. We used OrthoMCL to identify nearly 20,000 gene families in proteomes of 16 diverse fungal species, which include 15 basidiomycetes and one ascomycete. We inferred patterns of duplication and loss for each gene family and identified families with distinctive patterns of expansion/contraction associated with the evolution of rust fungal genomes. To recognize potential contributors for the unique features of rust pathogens, we identified families harboring secreted proteins that: (i) arose or expanded in rust pathogens relative to other fungi, or (ii) contracted or were lost in rust fungal genomes. While the origin of rust fungi appears to be associated with considerable gene loss, there are many gene duplications associated with each sampled rust fungal genome. We also highlight two putative effector gene families that have expanded in Cqf that we hypothesize have roles in pathogenicity.

Complete Genome Sequence of a Putative Densovirus of the Asian Citrus Psyllid, Diaphorina citri.

Science.gov (United States)

Nigg, Jared C; Nouri, Shahideh; Falk, Bryce W

2016-07-28

Here, we report the complete genome sequence of a putative densovirus of the Asian citrus psyllid, Diaphorina citri Diaphorina citri densovirus (DcDNV) was originally identified through metagenomics, and here, we obtained the complete nucleotide sequence using PCR-based approaches. Phylogenetic analysis places DcDNV between viruses of the Ambidensovirus and Iteradensovirus genera. Copyright © 2016 Nigg et al.

An automated high throughput screening-compatible assay to identify regulators of stem cell neural differentiation.

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Casalino, Laura; Magnani, Dario; De Falco, Sandro; Filosa, Stefania; Minchiotti, Gabriella; Patriarca, Eduardo J; De Cesare, Dario

2012-03-01

The use of Embryonic Stem Cells (ESCs) holds considerable promise both for drug discovery programs and the treatment of degenerative disorders in regenerative medicine approaches. Nevertheless, the successful use of ESCs is still limited by the lack of efficient control of ESC self-renewal and differentiation capabilities. In this context, the possibility to modulate ESC biological properties and to obtain homogenous populations of correctly specified cells will help developing physiologically relevant screens, designed for the identification of stem cell modulators. Here, we developed a high throughput screening-suitable ESC neural differentiation assay by exploiting the Cell(maker) robotic platform and demonstrated that neural progenies can be generated from ESCs in complete automation, with high standards of accuracy and reliability. Moreover, we performed a pilot screening providing proof of concept that this assay allows the identification of regulators of ESC neural differentiation in full automation.

Identification-based chaos control via backstepping design using self-organizing fuzzy neural networks

International Nuclear Information System (INIS)

Peng Yafu; Hsu, C.-F.

2009-01-01

This paper proposes an identification-based adaptive backstepping control (IABC) for the chaotic systems. The IABC system is comprised of a neural backstepping controller and a robust compensation controller. The neural backstepping controller containing a self-organizing fuzzy neural network (SOFNN) identifier is the principal controller, and the robust compensation controller is designed to dispel the effect of minimum approximation error introduced by the SOFNN identifier. The SOFNN identifier is used to online estimate the chaotic dynamic function with structure and parameter learning phases of fuzzy neural network. The structure learning phase consists of the growing and pruning of fuzzy rules; thus the SOFNN identifier can avoid the time-consuming trial-and-error tuning procedure for determining the neural structure of fuzzy neural network. The parameter learning phase adjusts the interconnection weights of neural network to achieve favorable approximation performance. Finally, simulation results verify that the proposed IABC can achieve favorable tracking performance.

Direct adaptive control using feedforward neural networks

OpenAIRE

Cajueiro, Daniel Oliveira; Hemerly, Elder Moreira

2003-01-01

ABSTRACT: This paper proposes a new scheme for direct neural adaptive control that works efficiently employing only one neural network, used for simultaneously identifying and controlling the plant. The idea behind this structure of adaptive control is to compensate the control input obtained by a conventional feedback controller. The neural network training process is carried out by using two different techniques: backpropagation and extended Kalman filter algorithm. Additionally, the conver...

A putative hybrid swarm within Oonopsis foliosa (Asteraceae: Astereae)

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Hughes, J.F.; Brown, G.K.

2004-01-01

Oo??nopsis foliosa var. foliosa and var. monocephala are endemic to short-grass steppe of southeastern Colorado and until recently were considered geographically disjunct. The only known qualitative feature separating these 2 varieties is floral head type; var. foliosa has radiate heads, whereas var. monocephala heads are discoid. Sympatry between these varieties is restricted to a small area in which a range of parental types and intermediate head morphologies is observed. We used distribution mapping, morphometric analyses, chromosome cytology, and pollen stainability to characterize the sympatric zone. Morphometrics confirms that the only discrete difference between var. foliosa and var. monocephala is radiate versus discoid heads, respectively. The outer florets of putative hybrid individuals ranged from conspicuously elongated yet radially symmetric disc-floret corollas, to elongated radially asymmetric bilabiate- or deeply cleft corollas, to stunted ray florets with appendages remnant of corolla lobes. Chromosome cytology of pollen mother cells from both putative parental varieties and a series of intermediate morphological types collected at the sympatric zone reveal evidence of translocation heterozygosity. Pollen stainability shows no significant differences in viability between the parental varieties and putative hybrids. The restricted distribution of putative hybrids to a narrow zone of sympatry between the parental types and the presence of meiotic chromosome-pairing anomalies in these intermediate plants are consistent with a hybrid origin. The high stainability of putative-hybrid pollen adds to a growing body of evidence that hybrids are not universally unfit.

An Introduction to Neural Networks for Hearing Aid Noise Recognition.

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Kim, Jun W.; Tyler, Richard S.

1995-01-01

This article introduces the use of multilayered artificial neural networks in hearing aid noise recognition. It reviews basic principles of neural networks, and offers an example of an application in which a neural network is used to identify the presence or absence of noise in speech. The ability of neural networks to "learn" the…

Fine time course expression analysis identifies cascades of activation and repression and maps a putative regulator of mammalian sex determination.

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Steven C Munger

Full Text Available In vertebrates, primary sex determination refers to the decision within a bipotential organ precursor to differentiate as a testis or ovary. Bifurcation of organ fate begins between embryonic day (E 11.0-E12.0 in mice and likely involves a dynamic transcription network that is poorly understood. To elucidate the first steps of sexual fate specification, we profiled the XX and XY gonad transcriptomes at fine granularity during this period and resolved cascades of gene activation and repression. C57BL/6J (B6 XY gonads showed a consistent ~5-hour delay in the activation of most male pathway genes and repression of female pathway genes relative to 129S1/SvImJ, which likely explains the sensitivity of the B6 strain to male-to-female sex reversal. Using this fine time course data, we predicted novel regulatory genes underlying expression QTLs (eQTLs mapped in a previous study. To test predictions, we developed an in vitro gonad primary cell assay and optimized a lentivirus-based shRNA delivery method to silence candidate genes and quantify effects on putative targets. We provide strong evidence that Lmo4 (Lim-domain only 4 is a novel regulator of sex determination upstream of SF1 (Nr5a1, Sox9, Fgf9, and Col9a3. This approach can be readily applied to identify regulatory interactions in other systems.

Duplications and losses in gene families of rust pathogens highlight putative effectors

Directory of Open Access Journals (Sweden)

Amanda L. Pendleton

2014-06-01

Full Text Available Rust fungi are a group of fungal pathogens that cause some of the world’s most destructive diseases of trees and crops. A shared characteristic among rust fungi is obligate biotrophy, the inability to complete a lifecycle without a host. This dependence on a host species likely affects patterns of gene expansion, contraction, and innovation within rust pathogen genomes. The establishment of disease by biotrophic pathogens is reliant upon effector proteins that are encoded in the fungal genome and secreted from the pathogen into the host’s cell apoplast or within the cells. This study uses a comparative genomic approach to elucidate putative effectors and determine their evolutionary histories. We used OrthoMCL to identify nearly 20,000 gene families in proteomes of sixteen diverse fungal species, which include fifteen basidiomycetes and one ascomycete. We inferred patterns of duplication and loss for each gene family and identified families with distinctive patterns of expansion/contraction associated with the evolution of rust fungal genomes. To recognize potential contributors for the unique features of rust pathogens, we identified families harboring secreted proteins that: i arose or expanded in rust pathogens relative to other fungi, or ii contracted or were lost in rust fungal genomes. While the origin of rust fungi appears to be associated with considerable gene loss, there are many gene duplications associated with each sampled rust fungal genome. We also highlight two putative effector gene families that have expanded in Cqf that we hypothesize have roles in pathogenicity.

Neural Determinants of Task Performance during Feature-Based Attention in Human Cortex

Science.gov (United States)

Gong, Mengyuan

2018-01-01

Abstract Studies of feature-based attention have associated activity in a dorsal frontoparietal network with putative attentional priority signals. Yet, how this neural activity mediates attentional selection and whether it guides behavior are fundamental questions that require investigation. We reasoned that endogenous fluctuations in the quality of attentional priority should influence task performance. Human subjects detected a speed increment while viewing clockwise (CW) or counterclockwise (CCW) motion (baseline task) or while attending to either direction amid distracters (attention task). In an fMRI experiment, direction-specific neural pattern similarity between the baseline task and the attention task revealed a higher level of similarity for correct than incorrect trials in frontoparietal regions. Using transcranial magnetic stimulation (TMS), we disrupted posterior parietal cortex (PPC) and found a selective deficit in the attention task, but not in the baseline task, demonstrating the necessity of this cortical area during feature-based attention. These results reveal that frontoparietal areas maintain attentional priority that facilitates successful behavioral selection. PMID:29497703

Differential transcript abundance and genotypic variation of four putative allergen-encoding gene families in melting peach

NARCIS (Netherlands)

Yang, Z.; Ma, Y.; Chen, L.; Xie, R.; Zhang, X.; Zhang, B.; Lu, M.; Wu, S.; Gilissen, L.J.W.J.; Ree, van R.; Gao, Z.

2011-01-01

We analysed the temporal and spatial transcript expression of the panel of 18 putative isoallergens from four gene families (Pru p 1–4) in the peach fruit, anther and leaf of two melting cultivars, to gain insight into their expression profiles and to identify the key family members. Genotypic

Gene array analysis of neural crest cells identifies transcription factors necessary for direct conversion of embryonic fibroblasts into neural crest cells

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Tsutomu Motohashi

2016-03-01

Full Text Available Neural crest cells (NC cells are multipotent cells that emerge from the edge of the neural folds and migrate throughout the developing embryo. Although the gene regulatory network for generation of NC cells has been elucidated in detail, it has not been revealed which of the factors in the network are pivotal to directing NC identity. In this study we analyzed the gene expression profile of a pure NC subpopulation isolated from Sox10-IRES-Venus mice and investigated whether these genes played a key role in the direct conversion of Sox10-IRES-Venus mouse embryonic fibroblasts (MEFs into NC cells. The comparative molecular profiles of NC cells and neural tube cells in 9.5-day embryos revealed genes including transcription factors selectively expressed in developing trunk NC cells. Among 25 NC cell-specific transcription factor genes tested, SOX10 and SOX9 were capable of converting MEFs into SOX10-positive (SOX10+ cells. The SOX10+ cells were then shown to differentiate into neurons, glial cells, smooth muscle cells, adipocytes and osteoblasts. These SOX10+ cells also showed limited self-renewal ability, suggesting that SOX10 and SOX9 directly converted MEFs into NC cells. Conversely, the remaining transcription factors, including well-known NC cell specifiers, were unable to convert MEFs into SOX10+ NC cells. These results suggest that SOX10 and SOX9 are the key factors necessary for the direct conversion of MEFs into NC cells.

Dynamic decomposition of spatiotemporal neural signals.

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Luca Ambrogioni

2017-05-01

Full Text Available Neural signals are characterized by rich temporal and spatiotemporal dynamics that reflect the organization of cortical networks. Theoretical research has shown how neural networks can operate at different dynamic ranges that correspond to specific types of information processing. Here we present a data analysis framework that uses a linearized model of these dynamic states in order to decompose the measured neural signal into a series of components that capture both rhythmic and non-rhythmic neural activity. The method is based on stochastic differential equations and Gaussian process regression. Through computer simulations and analysis of magnetoencephalographic data, we demonstrate the efficacy of the method in identifying meaningful modulations of oscillatory signals corrupted by structured temporal and spatiotemporal noise. These results suggest that the method is particularly suitable for the analysis and interpretation of complex temporal and spatiotemporal neural signals.

Neural Mechanisms of Selective Visual Attention.

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Moore, Tirin; Zirnsak, Marc

2017-01-03

Selective visual attention describes the tendency of visual processing to be confined largely to stimuli that are relevant to behavior. It is among the most fundamental of cognitive functions, particularly in humans and other primates for whom vision is the dominant sense. We review recent progress in identifying the neural mechanisms of selective visual attention. We discuss evidence from studies of different varieties of selective attention and examine how these varieties alter the processing of stimuli by neurons within the visual system, current knowledge of their causal basis, and methods for assessing attentional dysfunctions. In addition, we identify some key questions that remain in identifying the neural mechanisms that give rise to the selective processing of visual information.

Putative periodontopathic bacteria and herpesviruses in pregnant women: a case-control study

OpenAIRE

Lu, Haixia; Zhu, Ce; Li, Fei; Xu, Wei; Tao, Danying; Feng, Xiping

2016-01-01

Little is known about herpesvirus and putative periodontopathic bacteria in maternal chronic periodontitis. The present case-control study aimed to explore the potential relationship between putative periodontopathic bacteria and herpesviruses in maternal chronic periodontitis.Saliva samples were collected from 36 pregnant women with chronic periodontitis (cases) and 36 pregnant women with healthy periodontal status (controls). Six putative periodontopathic bacteria (Porphyromonas gingivalis ...

Original and regenerating lizard tail cartilage contain putative resident stem/progenitor cells.

Science.gov (United States)

Alibardi, Lorenzo

2015-11-01

Regeneration of cartilaginous tissues is limited in mammals but it occurs with variable extension in lizards (reptiles), including in their vertebrae. The ability of lizard vertebrae to regenerate cartilaginous tissue that is later replaced with bone has been analyzed using tritiated thymidine autoradiography and 5BrdU immunocytochemistry after single pulse or prolonged-pulse and chase experiments. The massive cartilage regeneration that can restore broad vertebral regions and gives rise to a long cartilaginous tube in the regenerating tail, depends from the permanence of some chondrogenic cells within adult vertebrae. Few cells that retain tritiated thymidine or 5-bromodeoxy-uridine for over 35 days are mainly localized in the inter-vertebral cartilage and in sparse chondrogenic regions of the neural arch of the vertebrae, suggesting that they are putative resident stem/progenitor cells. The study supports previous hypothesis indicating that the massive regeneration of the cartilaginous tissue in damaged vertebrae and in the regenerating tail of lizards derive from resident stem cells mainly present in the cartilaginous areas of the vertebrae including in the perichondrium that are retained in adult lizards as growing centers for most of their lifetime. Copyright © 2015 Elsevier Ltd. All rights reserved.

Decentralized neural control application to robotics

CERN Document Server

Garcia-Hernandez, Ramon; Sanchez, Edgar N; Alanis, Alma y; Ruz-Hernandez, Jose A

2017-01-01

This book provides a decentralized approach for the identification and control of robotics systems. It also presents recent research in decentralized neural control and includes applications to robotics. Decentralized control is free from difficulties due to complexity in design, debugging, data gathering and storage requirements, making it preferable for interconnected systems. Furthermore, as opposed to the centralized approach, it can be implemented with parallel processors. This approach deals with four decentralized control schemes, which are able to identify the robot dynamics. The training of each neural network is performed on-line using an extended Kalman filter (EKF). The first indirect decentralized control scheme applies the discrete-time block control approach, to formulate a nonlinear sliding manifold. The second direct decentralized neural control scheme is based on the backstepping technique, approximated by a high order neural network. The third control scheme applies a decentralized neural i...

A Neural Network-Based Interval Pattern Matcher

Directory of Open Access Journals (Sweden)

Jing Lu

2015-07-01

Full Text Available One of the most important roles in the machine learning area is to classify, and neural networks are very important classifiers. However, traditional neural networks cannot identify intervals, let alone classify them. To improve their identification ability, we propose a neural network-based interval matcher in our paper. After summarizing the theoretical construction of the model, we take a simple and a practical weather forecasting experiment, which show that the recognizer accuracy reaches 100% and that is promising.

The challenges of neural mind-reading paradigms

OpenAIRE

Vilarroya, Oscar

2013-01-01

Neural mind-reading studies, based on multivariate pattern analysis (MVPA) methods, are providing exciting new studies. Some of the results obtained with these paradigms have raised high expectations, such as the possibility of creating brain reading devices. However, such hopes are based on the assumptions that: (a) the BOLD signal is a marker of neural activity; (b) the BOLD pattern identified by a MVPA is a neurally sound pattern; (c) the MVPA's feature space is a good mapping of the neura...

Identification of putative and potential cross-reactive chickpea (Cicer arietinum) allergens through an in silico approach.

Science.gov (United States)

Kulkarni, Anuja; Ananthanarayan, Laxmi; Raman, Karthik

2013-12-01

Allergy has become a key cause of morbidity worldwide. Although many legumes (plants in the Fabaceae family) are healthy foods, they may have a number of allergenic proteins. A number of allergens have been identified and characterized in Fabaceae family, such as soybean and peanut, on the basis of biochemical and molecular biological approaches. However, our understanding of the allergens from chickpea (Cicer arietinum L.), belonging to this family, is very limited. In this study, we aimed to identify putative and cross-reactive allergens from Chickpea (C. arietinum) by means of in silico analysis of the chickpea protein sequences and allergens sequences from Fabaceae family. We retrieved known allergen sequences in Fabaceae family from the IUIS Allergen Nomenclature Database. We performed a protein BLAST (BLASTp) on these sequences to retrieve the similar sequences from chickpea. We further analyzed the retrieved chickpea sequences using a combination of in silico tools, to assess them for their allergenicity potential. Following this, we built structure models using FUGUE: Sequence-structure homology; these models generated by the recognition tool were viewed in Swiss-PDB viewer. Through this in silico approach, we identified seven novel putative allergens from chickpea proteome sequences on the basis of similarity of sequence, structure and physicochemical properties with the known reported legume allergens. Four out of seven putative allergens may also show cross reactivity with reported allergens since potential allergens had common sequence and structural features with the reported allergens. The in silico proteomic identification of the allergen proteins in chickpea provides a basis for future research on developing hypoallergenic foods containing chickpea. Such bioinformatics approaches, combined with experimental methodology, will help delineate an efficient and comprehensive approach to assess allergenicity and pave the way for a better understanding of

Putative midkine family protein up-regulation in Patella caerulea (Mollusca, Gastropoda) exposed to sublethal concentrations of cadmium

International Nuclear Information System (INIS)

Vanucci, Silvana; Minerdi, Daniela; Kadomatsu, Kenji; Mengoni, Alessio; Bazzicalupo, Marco

2005-01-01

A cDNA sequence of a putative midkine (MK) family protein was identified and characterised in the mollusc Patella caerulea. The midkine family consists of two members, midkine and pleiotrophin (PTN), and it is one of the recently discovered cytokines. Our results show that this putative midkine protein is up-regulated in specimens of P. caerulea exposed to sublethal cadmium concentrations (i.e. 0.5 and 1 mg l -1 Cd) over a 10-day exposure period. Semiquantitative RT-PCR and quantitative Real time RT-PCR estimations indicate elevated expression of midkine mRNA in exposed specimens compared to controls. Moreover, RT-PCR Real time values were higher in the viscera (here defined as the part of the soft tissue including digestive gland plus gills) than in the foot (i.e. foot plus head plus heart) of the limpets. At present, information on the functional signalling significance of the midkine family proteins suggests that the up-regulation of P. caerulea putative midkine family protein is a distress signal likely with informative value on health status of the organism and with potential prognostic capability

Individual Identification Using Functional Brain Fingerprint Detected by Recurrent Neural Network.

Science.gov (United States)

Chen, Shiyang; Hu, Xiaoping P

2018-03-20

Individual identification based on brain function has gained traction in literature. Investigating individual differences in brain function can provide additional insights into the brain. In this work, we introduce a recurrent neural network based model for identifying individuals based on only a short segment of resting state functional MRI data. In addition, we demonstrate how the global signal and differences in atlases affect the individual identifiability. Furthermore, we investigate neural network features that exhibit the uniqueness of each individual. The results indicate that our model is able to identify individuals based on neural features and provides additional information regarding brain dynamics.

Identifying the Neural Substrates of Procrastination: a Resting-State fMRI Study.

Science.gov (United States)

Zhang, Wenwen; Wang, Xiangpeng; Feng, Tingyong

2016-09-12

Procrastination is a prevalent problematic behavior that brings serious consequences to individuals who suffer from it. Although this phenomenon has received increasing attention from researchers, the underpinning neural substrates of it is poorly studied. To examine the neural bases subserving procrastination, the present study employed resting-state fMRI. The main results were as follows: (1) the behavioral procrastination was positively correlated with the regional activity of the ventromedial prefrontal cortex (vmPFC) and the parahippocampal cortex (PHC), while negatively correlated with that of the anterior prefrontal cortex (aPFC). (2) The aPFC-seed connectivity with the anterior medial prefrontal cortex and the posterior cingulate cortex was positively associated with procrastination. (3) The connectivity between vmPFC and several other regions, such as the dorsomedial prefrontal cortex, the bilateral inferior prefrontal cortex showed a negative association with procrastination. These results suggested that procrastination could be attributed to, on the one hand, hyper-activity of the default mode network (DMN) that overrides the prefrontal control signal; while on the other hand, the failure of top-down control exerted by the aPFC on the DMN. Therefore, the present study unravels the biomarkers of procrastination and provides treatment targets for procrastination prevention.

Application of neural networks to multiple alarm processing and diagnosis in nuclear power plants

International Nuclear Information System (INIS)

Cheon, Se Woo; Chang Soon Heung; Chung, Hak Yeong

1992-01-01

This paper presents feasibility studies of multiple alarm processing and diagnosis using neural networks. The back-propagation neural network model is applied to the training of multiple alarm patterns for the identification of failure in a reactor coolant pump (RCP) system. The general mapping capability of the neural network enables to identify a fault easily. The case studies are performed with emphasis on the applicability of the neural network to pattern recognition problems. It is revealed that the neural network model can identify the cause of multiple alarms properly, even when untrained or sensor-failed alarm symptoms are given. It is also shown that multiple failures are easily identified using the symptoms of multiple alarms

Characterization of putative multidrug resistance transporters of the major facilitator-superfamily expressed in Salmonella Typhi

DEFF Research Database (Denmark)

Shaheen, Aqsa; Ismat, Fouzia; Iqbal, Mazhar

2015-01-01

Multidrug resistance mediated by efflux pumps is a well-known phenomenon in infectious bacteria. Although much work has been carried out to characterize multidrug efflux pumps in Gram-negative and Gram-positive bacteria, such information is still lacking for many deadly pathogens. The aim...... of this study was to gain insight into the substrate specificity of previously uncharacterized transporters of Salmonella Typhi to identify their role in the development of multidrug resistance. S. Typhi genes encoding putative members of the major facilitator superfamily were cloned and expressed in the drug......-hypersensitive Escherichia coli strain KAM42, and tested for transport of 25 antibacterial compounds, including representative antibiotics of various classes, antiseptics, dyes and detergents. Of the 15 tested putative transporters, STY0901, STY2458 and STY4874 exhibited a drug-resistance phenotype. Among these, STY4874...

Neural plasticity in functional and anatomical MRI studies of children with Tourette syndrome.

Science.gov (United States)

Eichele, Heike; Plessen, Kerstin J

2013-01-01

Tourette syndrome (TS) is a neuropsychiatric disorder with childhood onset characterized by chronic motor and vocal tics. The typical clinical course of an attenuation of symptoms during adolescence in parallel with the emerging self-regulatory control during development suggests that plastic processes may play an important role in the development of tic symptoms. We conducted a systematic search to identify existing imaging studies (both anatomical and functional magnetic resonance imaging [fMRI]) in young persons under the age of 19 years with TS. The final search resulted in 13 original studies, which were reviewed with a focus on findings suggesting adaptive processes (using fMRI) and plasticity (using anatomical MRI). Differences in brain activation compared to healthy controls during tasks that require overriding of prepotent responses help to understand compensatory pathways in children with TS. Along with alterations in regions putatively representing the origin of tics, deviations in several other regions most likely represent an activity-dependent neural plasticity that help to modulate tic severity, such as the prefrontal cortex, but also in the corpus callosum and the limbic system. Factors that potentially influence the development of adaptive changes in the brain of children with TS are age, comorbidity with other developmental disorders, medication use, IQ along with study-design or MRI techniques for acquisition, and analysis of data. The most prominent limitation of all studies is their cross-sectional design. Longitudinal studies extending to younger age groups and to children at risk for developing TS hopefully will confirm findings of neural plasticity in future investigations.

Secretome Characterization and Correlation Analysis Reveal Putative Pathogenicity Mechanisms and Identify Candidate Avirulence Genes in the Wheat Stripe Rust Fungus Puccinia striiformis f. sp. tritici.

Science.gov (United States)

Xia, Chongjing; Wang, Meinan; Cornejo, Omar E; Jiwan, Derick A; See, Deven R; Chen, Xianming

2017-01-01

Stripe (yellow) rust, caused by Puccinia striiformis f. sp. tritici ( Pst ), is one of the most destructive diseases of wheat worldwide. Planting resistant cultivars is an effective way to control this disease, but race-specific resistance can be overcome quickly due to the rapid evolving Pst population. Studying the pathogenicity mechanisms is critical for understanding how Pst virulence changes and how to develop wheat cultivars with durable resistance to stripe rust. We re-sequenced 7 Pst isolates and included additional 7 previously sequenced isolates to represent balanced virulence/avirulence profiles for several avirulence loci in seretome analyses. We observed an uneven distribution of heterozygosity among the isolates. Secretome comparison of Pst with other rust fungi identified a large portion of species-specific secreted proteins, suggesting that they may have specific roles when interacting with the wheat host. Thirty-two effectors of Pst were identified from its secretome. We identified candidates for Avr genes corresponding to six Yr genes by correlating polymorphisms for effector genes to the virulence/avirulence profiles of the 14 Pst isolates. The putative AvYr76 was present in the avirulent isolates, but absent in the virulent isolates, suggesting that deleting the coding region of the candidate avirulence gene has produced races virulent to resistance gene Yr76 . We conclude that incorporating avirulence/virulence phenotypes into correlation analysis with variations in genomic structure and secretome, particularly presence/absence polymorphisms of effectors, is an efficient way to identify candidate Avr genes in Pst . The candidate effector genes provide a rich resource for further studies to determine the evolutionary history of Pst populations and the co-evolutionary arms race between Pst and wheat. The Avr candidates identified in this study will lead to cloning avirulence genes in Pst , which will enable us to understand molecular mechanisms

A Meta-analysis of Multiple Myeloma Risk Regions in African and European Ancestry Populations Identifies Putatively Functional Loci.

Science.gov (United States)

Rand, Kristin A; Song, Chi; Dean, Eric; Serie, Daniel J; Curtin, Karen; Sheng, Xin; Hu, Donglei; Huff, Carol Ann; Bernal-Mizrachi, Leon; Tomasson, Michael H; Ailawadhi, Sikander; Singhal, Seema; Pawlish, Karen; Peters, Edward S; Bock, Cathryn H; Stram, Alex; Van Den Berg, David J; Edlund, Christopher K; Conti, David V; Zimmerman, Todd; Hwang, Amie E; Huntsman, Scott; Graff, John; Nooka, Ajay; Kong, Yinfei; Pregja, Silvana L; Berndt, Sonja I; Blot, William J; Carpten, John; Casey, Graham; Chu, Lisa; Diver, W Ryan; Stevens, Victoria L; Lieber, Michael R; Goodman, Phyllis J; Hennis, Anselm J M; Hsing, Ann W; Mehta, Jayesh; Kittles, Rick A; Kolb, Suzanne; Klein, Eric A; Leske, Cristina; Murphy, Adam B; Nemesure, Barbara; Neslund-Dudas, Christine; Strom, Sara S; Vij, Ravi; Rybicki, Benjamin A; Stanford, Janet L; Signorello, Lisa B; Witte, John S; Ambrosone, Christine B; Bhatti, Parveen; John, Esther M; Bernstein, Leslie; Zheng, Wei; Olshan, Andrew F; Hu, Jennifer J; Ziegler, Regina G; Nyante, Sarah J; Bandera, Elisa V; Birmann, Brenda M; Ingles, Sue A; Press, Michael F; Atanackovic, Djordje; Glenn, Martha J; Cannon-Albright, Lisa A; Jones, Brandt; Tricot, Guido; Martin, Thomas G; Kumar, Shaji K; Wolf, Jeffrey L; Deming Halverson, Sandra L; Rothman, Nathaniel; Brooks-Wilson, Angela R; Rajkumar, S Vincent; Kolonel, Laurence N; Chanock, Stephen J; Slager, Susan L; Severson, Richard K; Janakiraman, Nalini; Terebelo, Howard R; Brown, Elizabeth E; De Roos, Anneclaire J; Mohrbacher, Ann F; Colditz, Graham A; Giles, Graham G; Spinelli, John J; Chiu, Brian C; Munshi, Nikhil C; Anderson, Kenneth C; Levy, Joan; Zonder, Jeffrey A; Orlowski, Robert Z; Lonial, Sagar; Camp, Nicola J; Vachon, Celine M; Ziv, Elad; Stram, Daniel O; Hazelett, Dennis J; Haiman, Christopher A; Cozen, Wendy

2016-12-01

Genome-wide association studies (GWAS) in European populations have identified genetic risk variants associated with multiple myeloma. We performed association testing of common variation in eight regions in 1,318 patients with multiple myeloma and 1,480 controls of European ancestry and 1,305 patients with multiple myeloma and 7,078 controls of African ancestry and conducted a meta-analysis to localize the signals, with epigenetic annotation used to predict functionality. We found that variants in 7p15.3, 17p11.2, 22q13.1 were statistically significantly (P ancestry and persons of European ancestry, and the variant in 3p22.1 was associated in European ancestry only. In a combined African ancestry-European ancestry meta-analysis, variation in five regions (2p23.3, 3p22.1, 7p15.3, 17p11.2, 22q13.1) was statistically significantly associated with multiple myeloma risk. In 3p22.1, the correlated variants clustered within the gene body of ULK4 Correlated variants in 7p15.3 clustered around an enhancer at the 3' end of the CDCA7L transcription termination site. A missense variant at 17p11.2 (rs34562254, Pro251Leu, OR, 1.32; P = 2.93 × 10 -7 ) in TNFRSF13B encodes a lymphocyte-specific protein in the TNF receptor family that interacts with the NF-κB pathway. SNPs correlated with the index signal in 22q13.1 cluster around the promoter and enhancer regions of CBX7 CONCLUSIONS: We found that reported multiple myeloma susceptibility regions contain risk variants important across populations, supporting the use of multiple racial/ethnic groups with different underlying genetic architecture to enhance the localization and identification of putatively functional alleles. A subset of reported risk loci for multiple myeloma has consistent effects across populations and is likely to be functional. Cancer Epidemiol Biomarkers Prev; 25(12); 1609-18. ©2016 AACR. ©2016 American Association for Cancer Research.

A state space approach for piecewise-linear recurrent neural networks for identifying computational dynamics from neural measurements.

Directory of Open Access Journals (Sweden)

Daniel Durstewitz

2017-06-01

Full Text Available The computational and cognitive properties of neural systems are often thought to be implemented in terms of their (stochastic network dynamics. Hence, recovering the system dynamics from experimentally observed neuronal time series, like multiple single-unit recordings or neuroimaging data, is an important step toward understanding its computations. Ideally, one would not only seek a (lower-dimensional state space representation of the dynamics, but would wish to have access to its statistical properties and their generative equations for in-depth analysis. Recurrent neural networks (RNNs are a computationally powerful and dynamically universal formal framework which has been extensively studied from both the computational and the dynamical systems perspective. Here we develop a semi-analytical maximum-likelihood estimation scheme for piecewise-linear RNNs (PLRNNs within the statistical framework of state space models, which accounts for noise in both the underlying latent dynamics and the observation process. The Expectation-Maximization algorithm is used to infer the latent state distribution, through a global Laplace approximation, and the PLRNN parameters iteratively. After validating the procedure on toy examples, and using inference through particle filters for comparison, the approach is applied to multiple single-unit recordings from the rodent anterior cingulate cortex (ACC obtained during performance of a classical working memory task, delayed alternation. Models estimated from kernel-smoothed spike time data were able to capture the essential computational dynamics underlying task performance, including stimulus-selective delay activity. The estimated models were rarely multi-stable, however, but rather were tuned to exhibit slow dynamics in the vicinity of a bifurcation point. In summary, the present work advances a semi-analytical (thus reasonably fast maximum-likelihood estimation framework for PLRNNs that may enable to recover

Determination of the full-genome sequence of hepatitis E virus (HEV) SAAS-FX17 and use as a reference to identify putative HEV genotype 4 virulence determinants.

Science.gov (United States)

Zhu, Yumin; Yu, Xiaoming; Huang, Fenfen; Yu, Ruisong; Dong, Shijuan; Si, Fusheng; Zhang, Yuanshu; Li, Zhen

2012-11-08

Four major genotypes of hepatitis E virus (HEV), the causative agent of hepatitis E, have so far been recognized. While genotypes 3 and 4 are both zoonotic, the disease symptoms caused by the latter tend to be more severe. To examine if specific nucleotide/amino acid variations between genotypes 3 and 4 play a role in determining the severity of hepatitis E disease, the complete genome of one swine HEV genotype 4 isolate, SAAS-FX17, was determined and compared with other genotype 4 and genotype 3 genomes to identify putative HEV genotype 4 virulence determinants. A total of 42 conformable nt/aa variations between genotype 3 and 4 HEVs were detected, of which 19 were proposed to be potential disease severity determinants for genotype 4 strains. One potential determinant was located in each of the 5'-UTR and 3'-UTR, 3 and 12 within ORF1 and ORF2 respectively, and 2 in the junction region.

Could LC-NE-Dependent Adjustment of Neural Gain Drive Functional Brain Network Reorganization?

Directory of Open Access Journals (Sweden)

Carole Guedj

2017-01-01

Full Text Available The locus coeruleus-norepinephrine (LC-NE system is thought to act at synaptic, cellular, microcircuit, and network levels to facilitate cognitive functions through at least two different processes, not mutually exclusive. Accordingly, as a reset signal, the LC-NE system could trigger brain network reorganizations in response to salient information in the environment and/or adjust the neural gain within its target regions to optimize behavioral responses. Here, we provide evidence of the co-occurrence of these two mechanisms at the whole-brain level, in resting-state conditions following a pharmacological stimulation of the LC-NE system. We propose that these two mechanisms are interdependent such that the LC-NE-dependent adjustment of the neural gain inferred from the clustering coefficient could drive functional brain network reorganizations through coherence in the gamma rhythm. Via the temporal dynamic of gamma-range band-limited power, the release of NE could adjust the neural gain, promoting interactions only within the neuronal populations whose amplitude envelopes are correlated, thus making it possible to reorganize neuronal ensembles, functional networks, and ultimately, behavioral responses. Thus, our proposal offers a unified framework integrating the putative influence of the LC-NE system on both local- and long-range adjustments of brain dynamics underlying behavioral flexibility.

Identifying autism from neural representations of social interactions: neurocognitive markers of autism.

Science.gov (United States)

Just, Marcel Adam; Cherkassky, Vladimir L; Buchweitz, Augusto; Keller, Timothy A; Mitchell, Tom M

2014-01-01

Autism is a psychiatric/neurological condition in which alterations in social interaction (among other symptoms) are diagnosed by behavioral psychiatric methods. The main goal of this study was to determine how the neural representations and meanings of social concepts (such as to insult) are altered in autism. A second goal was to determine whether these alterations can serve as neurocognitive markers of autism. The approach is based on previous advances in fMRI analysis methods that permit (a) the identification of a concept, such as the thought of a physical object, from its fMRI pattern, and (b) the ability to assess the semantic content of a concept from its fMRI pattern. These factor analysis and machine learning methods were applied to the fMRI activation patterns of 17 adults with high-functioning autism and matched controls, scanned while thinking about 16 social interactions. One prominent neural representation factor that emerged (manifested mainly in posterior midline regions) was related to self-representation, but this factor was present only for the control participants, and was near-absent in the autism group. Moreover, machine learning algorithms classified individuals as autistic or control with 97% accuracy from their fMRI neurocognitive markers. The findings suggest that psychiatric alterations of thought can begin to be biologically understood by assessing the form and content of the altered thought's underlying brain activation patterns.

Purification and crystallization of a putative transcriptional regulator of the benzoate oxidation pathway in Burkholderia xenovorans LB400

International Nuclear Information System (INIS)

Law, Adrienne M.; Bains, Jasleen; Boulanger, Martin J.

2009-01-01

The X-ray diffraction and preliminary phasing of the putative transcriptional regulator Bxe-C0898 from B. xenovorans LB400 are reported. Burkholderia xenovorans LB400 harbours two paralogous copies of the recently discovered benzoate oxidation (box) pathway. While both copies are functional, the paralogues are differentially regulated and flanked by putative transcriptional regulators from distinct families. The putative LysR-type transcriptional regulator (LTTR) adjacent to the megaplasmid-encoded box enzymes, Bxe-C0898, has been produced recombinantly in Escherichia coli and purified to homogeneity. Gel-filtration studies show that Bxe-C0898 is a tetramer in solution, consistent with previously characterized LTTRs. Bxe-C0898 crystallized with four molecules in the asymmetric unit of the P4 3 2 1 2/P4 1 2 1 2 unit cell with a solvent content of 61.19%, as indicated by processing of the X-ray diffraction data. DNA-protection assays are currently under way in order to identify potential operator regions for this LTTR and to define its role in regulation of the box pathway

Distribution and innervation of putative peripheral arterial chemoreceptors in the red-eared slider (Trachemys scripta elegans).

Science.gov (United States)

Reyes, Catalina; Fong, Angelina Y; Milsom, William K

2015-06-15

Peripheral arterial chemoreceptors have been isolated to the common carotid artery, aorta, and pulmonary artery of turtles. However, the putative neurotransmitters associated with these chemoreceptors have not yet been described. The goal of the present study was to determine the neurochemical content, innervations, and distribution of putative oxygen-sensing cells in the central vasculature of turtles and to derive homologies with peripheral arterial chemoreceptors of other vertebrates. We used tract tracing together with immunohistochemical markers for cholinergic cells (vesicular acetylcholine transporter [VAChT]), tyrosine hydroxylase (TH; the rate-limiting enzyme in catecholamine synthesis), and serotonin (5HT) to identify putative oxygen-sensing cells and to determine their anatomical relation to branches of the vagus nerve (Xth cranial nerve). We found potential oxygen-sensing cells in all three chemosensory areas innervated by branches of the Xth cranial nerve. Cells containing either 5HT or VAChT were found in all three sites. The morphology and size of these cells resemble glomus cells found in amphibians, mammals, tortoises, and lizards. Furthermore, we found populations of cholinergic cells located at the base of the aorta and pulmonary artery that are likely involved in efferent regulation of vessel resistance. Catecholamine-containing cells were not found in any of the putative chemosensitive areas. The presence of 5HT- and VAChT-immunoreactive cells in segments of the common carotid artery, aorta, and pulmonary artery appears to reflect a transition between cells containing the major neurotransmitters seen in fish (5HT) and mammals (ACh and adenosine). © 2015 Wiley Periodicals, Inc.

Anger in brain and body: the neural and physiological perturbation of decision-making by emotion.

Science.gov (United States)

Garfinkel, Sarah N; Zorab, Emma; Navaratnam, Nakulan; Engels, Miriam; Mallorquí-Bagué, Núria; Minati, Ludovico; Dowell, Nicholas G; Brosschot, Jos F; Thayer, Julian F; Critchley, Hugo D

2016-01-01

Emotion and cognition are dynamically coupled to bodily arousal: the induction of anger, even unconsciously, can reprioritise neural and physiological resources toward action states that bias cognitive processes. Here we examine behavioural, neural and bodily effects of covert anger processing and its influence on cognition, indexed by lexical decision-making. While recording beat-to-beat blood pressure, the words ANGER or RELAX were presented subliminally just prior to rapid word/non-word reaction-time judgements of letter-strings. Subliminal ANGER primes delayed the time taken to reach rapid lexical decisions, relative to RELAX primes. However, individuals with high trait anger were speeded up by subliminal anger primes. ANGER primes increased systolic blood pressure and the magnitude of this increase predicted reaction time prolongation. Within the brain, ANGER trials evoked an enhancement of activity within dorsal pons and an attenuation of activity within visual occipitotemporal and attentional parietal cortices. Activity within periaqueductal grey matter, occipital and parietal regions increased linearly with evoked blood pressure changes, indicating neural substrates through which covert anger impairs semantic decisions, putatively through its expression as visceral arousal. The behavioural and physiological impact of anger states compromises the efficiency of cognitive processing through action-ready changes in autonomic response that skew regional neural activity. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Purification and subunit structure of a putative K+-channel protein identified by its binding properties for dendrotoxin I

International Nuclear Information System (INIS)

Rehm, H.; Lazdunski, M.

1988-01-01

The binding protein for the K + -channel toxin dendrotoxin I was purified from a detergent extract of rat brain membranes. The purification procedure utilized chromatography on DEAE-Trisacryl, affinity chromatography on a dendrotoxin-I-Aca 22 column, and wheat germ agglutinin-Affigel 10 with a final 3,800- to 4,600-fold enrichment and a recovery of 8-16%. The high affinity (K d , 40-100 pM) and specificity of the binding site are retained throughout the purification procedure. Analysis of the purified material on silver-stained NaDodSO 4 /polyacrylamide gel revealed three bands of M r 76,000-80,000, 38,000 and 35,000. Interestingly, the binding site for 125 I-labeled mast cell degranulating peptide, another putative K + -channel ligand from bee venom, which induces long-term potentiation in hippocampus, seems to reside on the same protein complex, as both binding sites copurify through the entire purification protocol

Localization and expression of putative circadian clock transcripts in the brain of the nudibranch Melibe leonina.

Science.gov (United States)

Duback, Victoria E; Sabrina Pankey, M; Thomas, Rachel I; Huyck, Taylor L; Mbarani, Izhar M; Bernier, Kyle R; Cook, Geoffrey M; O'Dowd, Colleen A; Newcomb, James M; Watson, Winsor H

2018-09-01

The nudibranch, Melibe leonina, expresses a circadian rhythm of locomotion, and we recently determined the sequences of multiple circadian clock transcripts that may play a role in controlling these daily patterns of behavior. In this study, we used these genomic data to help us: 1) identify putative clock neurons using fluorescent in situ hybridization (FISH); and 2) determine if there is a daily rhythm of expression of clock transcripts in the M. leonina brain, using quantitative PCR. FISH indicated the presence of the clock-related transcripts clock, period, and photoreceptive and non-photoreceptive cryptochrome (pcry and npcry, respectively) in two bilateral neurons in each cerebropleural ganglion and a group of <10 neurons in the anterolateral region of each pedal ganglion. Double-label experiments confirmed colocalization of all four clock transcripts with each other. Quantitative PCR demonstrated that the genes clock, period, pcry and npcry exhibited significant differences in expression levels over 24 h. These data suggest that the putative circadian clock network in M. leonina consists of a small number of identifiable neurons that express circadian genes with a daily rhythm. Copyright © 2018 Elsevier Inc. All rights reserved.

Robustness of the ATLAS pixel clustering neural network algorithm

CERN Document Server

AUTHOR|(INSPIRE)INSPIRE-00407780; The ATLAS collaboration

2016-01-01

Proton-proton collisions at the energy frontier puts strong constraints on track reconstruction algorithms. In the ATLAS track reconstruction algorithm, an artificial neural network is utilised to identify and split clusters of neighbouring read-out elements in the ATLAS pixel detector created by multiple charged particles. The robustness of the neural network algorithm is presented, probing its sensitivity to uncertainties in the detector conditions. The robustness is studied by evaluating the stability of the algorithm's performance under a range of variations in the inputs to the neural networks. Within reasonable variation magnitudes, the neural networks prove to be robust to most variation types.

Neural Correlates of Intolerance of Uncertainty in Clinical Disorders.

Science.gov (United States)

Wever, Mirjam; Smeets, Paul; Sternheim, Lot

2015-01-01

Intolerance of uncertainty is a key contributor to anxiety-related disorders. Recent studies highlight its importance in other clinical disorders. The link between its clinical presentation and the underlying neural correlates remains unclear. This review summarizes the emerging literature on the neural correlates of intolerance of uncertainty. In conclusion, studies focusing on the neural correlates of this construct are sparse, and findings are inconsistent across disorders. Future research should identify neural correlates of intolerance of uncertainty in more detail. This may unravel the neurobiology of a wide variety of clinical disorders and pave the way for novel therapeutic targets.

Three neural network based sensor systems for environmental monitoring

International Nuclear Information System (INIS)

Keller, P.E.; Kouzes, R.T.; Kangas, L.J.

1994-05-01

Compact, portable systems capable of quickly identifying contaminants in the field are of great importance when monitoring the environment. One of the missions of the Pacific Northwest Laboratory is to examine and develop new technologies for environmental restoration and waste management at the Hanford Site. In this paper, three prototype sensing systems are discussed. These prototypes are composed of sensing elements, data acquisition system, computer, and neural network implemented in software, and are capable of automatically identifying contaminants. The first system employs an array of tin-oxide gas sensors and is used to identify chemical vapors. The second system employs an array of optical sensors and is used to identify the composition of chemical dyes in liquids. The third system contains a portable gamma-ray spectrometer and is used to identify radioactive isotopes. In these systems, the neural network is used to identify the composition of the sensed contaminant. With a neural network, the intense computation takes place during the training process. Once the network is trained, operation consists of propagating the data through the network. Since the computation involved during operation consists of vector-matrix multiplication and application of look-up tables unknown samples can be rapidly identified in the field

Identification of Putative Ortholog Gene Blocks Involved in Gestant and Lactating Mammary Gland Development: A Rodent Cross-Species Microarray Transcriptomics Approach

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Rodríguez-Cruz, Maricela; Coral-Vázquez, Ramón M.; Hernández-Stengele, Gabriel; Sánchez, Raúl; Salazar, Emmanuel; Sanchez-Muñoz, Fausto; Encarnación-Guevara, Sergio; Ramírez-Salcedo, Jorge

2013-01-01

The mammary gland (MG) undergoes functional and metabolic changes during the transition from pregnancy to lactation, possibly by regulation of conserved genes. The objective was to elucidate orthologous genes, chromosome clusters and putative conserved transcriptional modules during MG development. We analyzed expression of 22,000 transcripts using murine microarrays and RNA samples of MG from virgin, pregnant, and lactating rats by cross-species hybridization. We identified 521 transcripts differentially expressed; upregulated in early (78%) and midpregnancy (89%) and early lactation (64%), but downregulated in mid-lactation (61%). Putative orthologous genes were identified. We mapped the altered genes to orthologous chromosomal locations in human and mouse. Eighteen sets of conserved genes associated with key cellular functions were revealed and conserved transcription factor binding site search entailed possible coregulation among all eight block sets of genes. This study demonstrates that the use of heterologous array hybridization for screening of orthologous gene expression from rat revealed sets of conserved genes arranged in chromosomal order implicated in signaling pathways and functional ontology. Results demonstrate the utilization power of comparative genomics and prove the feasibility of using rodent microarrays to identification of putative coexpressed orthologous genes involved in the control of human mammary gland development. PMID:24288657

Semantic Congruence Accelerates the Onset of the Neural Signals of Successful Memory Encoding.

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Packard, Pau A; Rodríguez-Fornells, Antoni; Bunzeck, Nico; Nicolás, Berta; de Diego-Balaguer, Ruth; Fuentemilla, Lluís

2017-01-11

As the stream of experience unfolds, our memory system rapidly transforms current inputs into long-lasting meaningful memories. A putative neural mechanism that strongly influences how input elements are transformed into meaningful memory codes relies on the ability to integrate them with existing structures of knowledge or schemas. However, it is not yet clear whether schema-related integration neural mechanisms occur during online encoding. In the current investigation, we examined the encoding-dependent nature of this phenomenon in humans. We showed that actively integrating words with congruent semantic information provided by a category cue enhances memory for words and increases false recall. The memory effect of such active integration with congruent information was robust, even with an interference task occurring right after each encoding word list. In addition, via electroencephalography, we show in 2 separate studies that the onset of the neural signals of successful encoding appeared early (∼400 ms) during the encoding of congruent words. That the neural signals of successful encoding of congruent and incongruent information followed similarly ∼200 ms later suggests that this earlier neural response contributed to memory formation. We propose that the encoding of events that are congruent with readily available contextual semantics can trigger an accelerated onset of the neural mechanisms, supporting the integration of semantic information with the event input. This faster onset would result in a long-lasting and meaningful memory trace for the event but, at the same time, make it difficult to distinguish it from plausible but never encoded events (i.e., related false memories). Conceptual or schema congruence has a strong influence on long-term memory. However, the question of whether schema-related integration neural mechanisms occur during online encoding has yet to be clarified. We investigated the neural mechanisms reflecting how the active

Function of FEZF1 during early neural differentiation of human embryonic stem cells.

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Liu, Xin; Su, Pei; Lu, Lisha; Feng, Zicen; Wang, Hongtao; Zhou, Jiaxi

2018-01-01

The understanding of the mechanism underlying human neural development has been hampered due to lack of a cellular system and complicated ethical issues. Human embryonic stem cells (hESCs) provide an invaluable model for dissecting human development because of unlimited self-renewal and the capacity to differentiate into nearly all cell types in the human body. In this study, using a chemical defined neural induction protocol and molecular profiling, we identified Fez family zinc finger 1 (FEZF1) as a potential regulator of early human neural development. FEZF1 is rapidly up-regulated during neural differentiation in hESCs and expressed before PAX6, a well-established marker of early human neural induction. We generated FEZF1-knockout H1 hESC lines using CRISPR-CAS9 technology and found that depletion of FEZF1 abrogates neural differentiation of hESCs. Moreover, loss of FEZF1 impairs the pluripotency exit of hESCs during neural specification, which partially explains the neural induction defect caused by FEZF1 deletion. However, enforced expression of FEZF1 itself fails to drive neural differentiation in hESCs, suggesting that FEZF1 is necessary but not sufficient for neural differentiation from hESCs. Taken together, our findings identify one of the earliest regulators expressed upon neural induction and provide insight into early neural development in human.

The neural signature of emotional memories in serial crimes.

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Chassy, Philippe

2017-10-01

Neural plasticity is the process whereby semantic information and emotional responses are stored in neural networks. It is hypothesized that the neural networks built over time to encode the sexual fantasies that motivate serial killers to act should display a unique, detectable activation pattern. The pathological neural watermark hypothesis posits that such networks comprise activation of brain sites that reflect four cognitive components: autobiographical memory, sexual arousal, aggression, and control over aggression. The neural sites performing these cognitive functions have been successfully identified by previous research. The key findings are reviewed to hypothesise the typical pattern of activity that serial killers should display. Through the integration of biological findings into one framework, the neural approach proposed in this paper is in stark contrast with the many theories accounting for serial killers that offer non-medical taxonomies. The pathological neural watermark hypothesis offers a new framework to understand and detect deviant individuals. The technical and legal issues are briefly discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Identification and phylogenetic analysis of Tityus pachyurus and Tityus obscurus novel putative Na+-channel scorpion toxins.

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Jimmy A Guerrero-Vargas

Full Text Available Colombia and Brazil are affected by severe cases of scorpionism. In Colombia the most dangerous accidents are caused by Tityus pachyurus that is widely distributed around this country. In the Brazilian Amazonian region scorpion stings are a common event caused by Tityus obscurus. The main objective of this work was to perform the molecular cloning of the putative Na(+-channel scorpion toxins (NaScTxs from T. pachyurus and T. obscurus venom glands and to analyze their phylogenetic relationship with other known NaScTxs from Tityus species.cDNA libraries from venom glands of these two species were constructed and five nucleotide sequences from T. pachyurus were identified as putative modulators of Na(+-channels, and were named Tpa4, Tpa5, Tpa6, Tpa7 and Tpa8; the latter being the first anti-insect excitatory β-class NaScTx in Tityus scorpion venom to be described. Fifteen sequences from T. obscurus were identified as putative NaScTxs, among which three had been previously described, and the others were named To4 to To15. The peptides Tpa4, Tpa5, Tpa6, To6, To7, To9, To10 and To14 are closely related to the α-class NaScTxs, whereas Tpa7, Tpa8, To4, To8, To12 and To15 sequences are more related to the β-class NaScTxs. To5 is possibly an arthropod specific toxin. To11 and To13 share sequence similarities with both α and β NaScTxs. By means of phylogenetic analysis using the Maximum Parsimony method and the known NaScTxs from Tityus species, these toxins were clustered into 14 distinct groups.This communication describes new putative NaScTxs from T. pachyurus and T. obscurus and their phylogenetic analysis. The results indicate clear geographic separation between scorpions of Tityus genus inhabiting the Amazonian and Mountain Andes regions and those distributed over the Southern of the Amazonian rainforest. Based on the consensus sequences for the different clusters, a new nomenclature for the NaScTxs is proposed.

Tiered High-Throughput Screening Approach to Identify ...

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High-throughput screening (HTS) for potential thyroid–disrupting chemicals requires a system of assays to capture multiple molecular-initiating events (MIEs) that converge on perturbed thyroid hormone (TH) homeostasis. Screening for MIEs specific to TH-disrupting pathways is limited in the US EPA ToxCast screening assay portfolio. To fill one critical screening gap, the Amplex UltraRed-thyroperoxidase (AUR-TPO) assay was developed to identify chemicals that inhibit TPO, as decreased TPO activity reduces TH synthesis. The ToxCast Phase I and II chemical libraries, comprised of 1,074 unique chemicals, were initially screened using a single, high concentration to identify potential TPO inhibitors. Chemicals positive in the single concentration screen were retested in concentration-response. Due to high false positive rates typically observed with loss-of-signal assays such as AUR-TPO, we also employed two additional assays in parallel to identify possible sources of nonspecific assay signal loss, enabling stratification of roughly 300 putative TPO inhibitors based upon selective AUR-TPO activity. A cell-free luciferase inhibition assay was used to identify nonspecific enzyme inhibition among the putative TPO inhibitors, and a cytotoxicity assay using a human cell line was used to estimate the cellular tolerance limit. Additionally, the TPO inhibition activities of 150 chemicals were compared between the AUR-TPO and an orthogonal peroxidase oxidation assay using

Characterization of Putative cis-Regulatory Elements in Genes Preferentially Expressed in Arabidopsis Male Meiocytes

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Junhua Li

2014-01-01

Full Text Available Meiosis is essential for plant reproduction because it is the process during which homologous chromosome pairing, synapsis, and meiotic recombination occur. The meiotic transcriptome is difficult to investigate because of the size of meiocytes and the confines of anther lobes. The recent development of isolation techniques has enabled the characterization of transcriptional profiles in male meiocytes of Arabidopsis. Gene expression in male meiocytes shows unique features. The direct interaction of transcription factors (TFs with DNA regulatory sequences forms the basis for the specificity of transcriptional regulation. Here, we identified putative cis-regulatory elements (CREs associated with male meiocyte-expressed genes using in silico tools. The upstream regions (1 kb of the top 50 genes preferentially expressed in Arabidopsis meiocytes possessed conserved motifs. These motifs are putative binding sites of TFs, some of which share common functions, such as roles in cell division. In combination with cell-type-specific analysis, our findings could be a substantial aid for the identification and experimental verification of the protein-DNA interactions for the specific TFs that drive gene expression in meiocytes.

Putative bronchopulmonary flagellated protozoa in immunosuppressed patients.

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Kilimcioglu, Ali Ahmet; Havlucu, Yavuz; Girginkardesler, Nogay; Celik, Pınar; Yereli, Kor; Özbilgin, Ahmet

2014-01-01

Flagellated protozoa that cause bronchopulmonary symptoms in humans are commonly neglected. These protozoal forms which were presumed to be "flagellated protozoa" have been previously identified in immunosuppressed patients in a number of studies, but have not been certainly classified so far. Since no human cases of bronchopulmonary flagellated protozoa were reported from Turkey, we aimed to investigate these putative protozoa in immunosuppressed patients who are particularly at risk of infectious diseases. Bronchoalveolar lavage fluid samples of 110 immunosuppressed adult patients who were admitted to the Department of Chest Diseases, Hafsa Sultan Hospital of Celal Bayar University, Manisa, Turkey, were examined in terms of parasites by light microscopy. Flagellated protozoal forms were detected in nine (8.2%) of 110 cases. Metronidazole (500 mg b.i.d. for 30 days) was given to all positive cases and a second bronchoscopy was performed at the end of the treatment, which revealed no parasites. In conclusion, immunosuppressed patients with bronchopulmonary symptoms should attentively be examined with regard to flagellated protozoa which can easily be misidentified as epithelial cells.

Application of neural networks to connectional expert system for identification of transients in nuclear power plants

International Nuclear Information System (INIS)

Cheon, Se Woo; Kim, Wan Joo; Chang, Soon Heung; Roh, Myung Sub

1991-01-01

The Back-propagation Neural Network (BPN) algorithm is applied to connectionist expert system for the identification of BWR transients. Several powerful features of neural network-based expert systems over traditional rule-based expert systems are described. The general mapping capability of the neural networks enables to identify transients easily. A number of case studies were performed with emphasis on the applicability of the neural networks to the diagnostic domain. It is revealed that the BPN algorithm can identify transients properly, even when incomplete or untrained symptoms are given. It is also shown that multiple transients are easily identified

Identification and Characterization of Putative Integron-Like Elements of the Heavy-Metal-Hypertolerant Strains of Pseudomonas spp.

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Ciok, Anna; Adamczuk, Marcin; Bartosik, Dariusz; Dziewit, Lukasz

2016-11-28

Pseudomonas strains isolated from the heavily contaminated Lubin copper mine and Zelazny Most post-flotation waste reservoir in Poland were screened for the presence of integrons. This analysis revealed that two strains carried homologous DNA regions composed of a gene encoding a DNA_BRE_C domain-containing tyrosine recombinase (with no significant sequence similarity to other integrases of integrons) plus a three-component array of putative integron gene cassettes. The predicted gene cassettes encode three putative polypeptides with homology to (i) transmembrane proteins, (ii) GCN5 family acetyltransferases, and (iii) hypothetical proteins of unknown function (homologous proteins are encoded by the gene cassettes of several class 1 integrons). Comparative sequence analyses identified three structural variants of these novel integron-like elements within the sequenced bacterial genomes. Analysis of their distribution revealed that they are found exclusively in strains of the genus Pseudomonas .

Integrated evolutionary computation neural network quality controller for automated systems

Energy Technology Data Exchange (ETDEWEB)

Patro, S.; Kolarik, W.J. [Texas Tech Univ., Lubbock, TX (United States). Dept. of Industrial Engineering

1999-06-01

With increasing competition in the global market, more and more stringent quality standards and specifications are being demands at lower costs. Manufacturing applications of computing power are becoming more common. The application of neural networks to identification and control of dynamic processes has been discussed. The limitations of using neural networks for control purposes has been pointed out and a different technique, evolutionary computation, has been discussed. The results of identifying and controlling an unstable, dynamic process using evolutionary computation methods has been presented. A framework for an integrated system, using both neural networks and evolutionary computation, has been proposed to identify the process and then control the product quality, in a dynamic, multivariable system, in real-time.

Functional neural networks underlying response inhibition in adolescents and adults.

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Stevens, Michael C; Kiehl, Kent A; Pearlson, Godfrey D; Calhoun, Vince D

2007-07-19

This study provides the first description of neural network dynamics associated with response inhibition in healthy adolescents and adults. Functional and effective connectivity analyses of whole brain hemodynamic activity elicited during performance of a Go/No-Go task were used to identify functionally integrated neural networks and characterize their causal interactions. Three response inhibition circuits formed a hierarchical, inter-dependent system wherein thalamic modulation of input to premotor cortex by fronto-striatal regions led to response suppression. Adolescents differed from adults in the degree of network engagement, regional fronto-striatal-thalamic connectivity, and network dynamics. We identify and characterize several age-related differences in the function of neural circuits that are associated with behavioral performance changes across adolescent development.

Phloem proteomics reveals new lipid-binding proteins with a putative role in lipid-mediated signaling

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Allison Marie Barbaglia

2016-04-01

Full Text Available Global climate changes inversely affect our ability to grow the food required for an increasing world population. To combat future crop loss due to abiotic stress, we need to understand the signals responsible for changes in plant development and the resulting adaptations, especially the signaling molecules traveling long-distance through the plant phloem. Using a proteomics approach, we had identified several putative lipid-binding proteins in the phloem exudates. Simultaneously, we identified several complex lipids as well as jasmonates. These findings prompted us to propose that phloem (phospho- lipids could act as long-distance developmental signals in response to abiotic stress, and that they are released, sensed, and moved by phloem lipid-binding proteins (Benning et al., 2012. Indeed, the proteins we identified include lipases that could release a signaling lipid into the phloem, putative receptor components, and proteins that could mediate lipid-movement. To test this possible protein-based lipid-signaling pathway, three of the proteins, which could potentially act in a relay, are characterized here: (I a putative GDSL-motif lipase (II a PIG-P-like protein, with a possible receptor-like function; (III and PLAFP (phloem lipid-associated family protein, a predicted lipid-binding protein of unknown function. Here we show that all three proteins bind lipids, in particular phosphatidic acid (PtdOH, which is known to participate in intracellular stress signaling. Genes encoding these proteins are expressed in the vasculature, a prerequisite for phloem transport. Cellular localization studies show that the proteins are not retained in the endoplasmic reticulum but surround the cell in a spotted pattern that has been previously observed with receptors and plasmodesmatal proteins. Abiotic signals that induce the production of PtdOH also regulate the expression of GDSL-lipase and PLAFP, albeit in opposite patterns. Our findings suggest that while

Identifying time-delayed gene regulatory networks via an evolvable hierarchical recurrent neural network.

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Kordmahalleh, Mina Moradi; Sefidmazgi, Mohammad Gorji; Harrison, Scott H; Homaifar, Abdollah

2017-01-01

The modeling of genetic interactions within a cell is crucial for a basic understanding of physiology and for applied areas such as drug design. Interactions in gene regulatory networks (GRNs) include effects of transcription factors, repressors, small metabolites, and microRNA species. In addition, the effects of regulatory interactions are not always simultaneous, but can occur after a finite time delay, or as a combined outcome of simultaneous and time delayed interactions. Powerful biotechnologies have been rapidly and successfully measuring levels of genetic expression to illuminate different states of biological systems. This has led to an ensuing challenge to improve the identification of specific regulatory mechanisms through regulatory network reconstructions. Solutions to this challenge will ultimately help to spur forward efforts based on the usage of regulatory network reconstructions in systems biology applications. We have developed a hierarchical recurrent neural network (HRNN) that identifies time-delayed gene interactions using time-course data. A customized genetic algorithm (GA) was used to optimize hierarchical connectivity of regulatory genes and a target gene. The proposed design provides a non-fully connected network with the flexibility of using recurrent connections inside the network. These features and the non-linearity of the HRNN facilitate the process of identifying temporal patterns of a GRN. Our HRNN method was implemented with the Python language. It was first evaluated on simulated data representing linear and nonlinear time-delayed gene-gene interaction models across a range of network sizes and variances of noise. We then further demonstrated the capability of our method in reconstructing GRNs of the Saccharomyces cerevisiae synthetic network for in vivo benchmarking of reverse-engineering and modeling approaches (IRMA). We compared the performance of our method to TD-ARACNE, HCC-CLINDE, TSNI and ebdbNet across different network

Comparative analysis of the predicted secretomes of Rosaceae scab pathogens Venturia inaequalis and V. pirina reveals expanded effector families and putative determinants of host range.

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Deng, Cecilia H; Plummer, Kim M; Jones, Darcy A B; Mesarich, Carl H; Shiller, Jason; Taranto, Adam P; Robinson, Andrew J; Kastner, Patrick; Hall, Nathan E; Templeton, Matthew D; Bowen, Joanna K

2017-05-02

Fungal plant pathogens belonging to the genus Venturia cause damaging scab diseases of members of the Rosaceae. In terms of economic impact, the most important of these are V. inaequalis, which infects apple, and V. pirina, which is a pathogen of European pear. Given that Venturia fungi colonise the sub-cuticular space without penetrating plant cells, it is assumed that effectors that contribute to virulence and determination of host range will be secreted into this plant-pathogen interface. Thus the predicted secretomes of a range of isolates of Venturia with distinct host-ranges were interrogated to reveal putative proteins involved in virulence and pathogenicity. Genomes of Venturia pirina (one European pear scab isolate) and Venturia inaequalis (three apple scab, and one loquat scab, isolates) were sequenced and the predicted secretomes of each isolate identified. RNA-Seq was conducted on the apple-specific V. inaequalis isolate Vi1 (in vitro and infected apple leaves) to highlight virulence and pathogenicity components of the secretome. Genes encoding over 600 small secreted proteins (candidate effectors) were identified, most of which are novel to Venturia, with expansion of putative effector families a feature of the genus. Numerous genes with similarity to Leptosphaeria maculans AvrLm6 and the Verticillium spp. Ave1 were identified. Candidates for avirulence effectors with cognate resistance genes involved in race-cultivar specificity were identified, as were putative proteins involved in host-species determination. Candidate effectors were found, on average, to be in regions of relatively low gene-density and in closer proximity to repeats (e.g. transposable elements), compared with core eukaryotic genes. Comparative secretomics has revealed candidate effectors from Venturia fungal plant pathogens that attack pome fruit. Effectors that are putative determinants of host range were identified; both those that may be involved in race-cultivar and host

Identification of Putative Coffee Rust Mycoparasites via Single-Molecule DNA Sequencing of Infected Pustules.

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James, Timothy Y; Marino, John A; Perfecto, Ivette; Vandermeer, John

2016-01-15

The interaction of crop pests with their natural enemies is a fundament to their control. Natural enemies of fungal pathogens of crops are poorly known relative to those of insect pests, despite the diversity of fungal pathogens and their economic importance. Currently, many regions across Latin America are experiencing unprecedented epidemics of coffee rust (Hemileia vastatrix). Identification of natural enemies of coffee rust could aid in developing management strategies or in pinpointing species that could be used for biocontrol. In the present study, we characterized fungal communities associated with coffee rust lesions by single-molecule DNA sequencing of fungal rRNA gene bar codes from leaf discs (≈28 mm(2)) containing rust lesions and control discs with no rust lesions. The leaf disc communities were hyperdiverse in terms of fungi, with up to 69 operational taxonomic units (putative species) per control disc, and the diversity was only slightly reduced in rust-infected discs, with up to 63 putative species. However, geography had a greater influence on the fungal community than whether the disc was infected by coffee rust. Through comparisons between control and rust-infected leaf discs, as well as taxonomic criteria, we identified 15 putative mycoparasitic fungi. These fungi are concentrated in the fungal family Cordycipitaceae and the order Tremellales. These data emphasize the complexity of diverse fungi of unknown ecological function within a leaf that might influence plant disease epidemics or lead to the development of species for biocontrol of fungal disease. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Influence of neural adaptation on dynamics and equilibrium state of neural activities in a ring neural network

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Takiyama, Ken

2017-12-01

How neural adaptation affects neural information processing (i.e. the dynamics and equilibrium state of neural activities) is a central question in computational neuroscience. In my previous works, I analytically clarified the dynamics and equilibrium state of neural activities in a ring-type neural network model that is widely used to model the visual cortex, motor cortex, and several other brain regions. The neural dynamics and the equilibrium state in the neural network model corresponded to a Bayesian computation and statistically optimal multiple information integration, respectively, under a biologically inspired condition. These results were revealed in an analytically tractable manner; however, adaptation effects were not considered. Here, I analytically reveal how the dynamics and equilibrium state of neural activities in a ring neural network are influenced by spike-frequency adaptation (SFA). SFA is an adaptation that causes gradual inhibition of neural activity when a sustained stimulus is applied, and the strength of this inhibition depends on neural activities. I reveal that SFA plays three roles: (1) SFA amplifies the influence of external input in neural dynamics; (2) SFA allows the history of the external input to affect neural dynamics; and (3) the equilibrium state corresponds to the statistically optimal multiple information integration independent of the existence of SFA. In addition, the equilibrium state in a ring neural network model corresponds to the statistically optimal integration of multiple information sources under biologically inspired conditions, independent of the existence of SFA.

Neural networks and their application to nuclear power plant diagnosis

International Nuclear Information System (INIS)

Reifman, J.

1997-01-01

The authors present a survey of artificial neural network-based computer systems that have been proposed over the last decade for the detection and identification of component faults in thermal-hydraulic systems of nuclear power plants. The capabilities and advantages of applying neural networks as decision support systems for nuclear power plant operators and their inherent characteristics are discussed along with their limitations and drawbacks. The types of neural network structures used and their applications are described and the issues of process diagnosis and neural network-based diagnostic systems are identified. A total of thirty-four publications are reviewed

SACE_5599, a putative regulatory protein, is involved in morphological differentiation and erythromycin production in Saccharopolyspora erythraea.

Science.gov (United States)

Kirm, Benjamin; Magdevska, Vasilka; Tome, Miha; Horvat, Marinka; Karničar, Katarina; Petek, Marko; Vidmar, Robert; Baebler, Spela; Jamnik, Polona; Fujs, Štefan; Horvat, Jaka; Fonovič, Marko; Turk, Boris; Gruden, Kristina; Petković, Hrvoje; Kosec, Gregor

2013-12-17

Erythromycin is a medically important antibiotic, biosynthesized by the actinomycete Saccharopolyspora erythraea. Genes encoding erythromycin biosynthesis are organized in a gene cluster, spanning over 60 kbp of DNA. Most often, gene clusters encoding biosynthesis of secondary metabolites contain regulatory genes. In contrast, the erythromycin gene cluster does not contain regulatory genes and regulation of its biosynthesis has therefore remained poorly understood, which has for a long time limited genetic engineering approaches for erythromycin yield improvement. We used a comparative proteomic approach to screen for potential regulatory proteins involved in erythromycin biosynthesis. We have identified a putative regulatory protein SACE_5599 which shows significantly higher levels of expression in an erythromycin high-producing strain, compared to the wild type S. erythraea strain. SACE_5599 is a member of an uncharacterized family of putative regulatory genes, located in several actinomycete biosynthetic gene clusters. Importantly, increased expression of SACE_5599 was observed in the complex fermentation medium and at controlled bioprocess conditions, simulating a high-yield industrial fermentation process in the bioreactor. Inactivation of SACE_5599 in the high-producing strain significantly reduced erythromycin yield, in addition to drastically decreasing sporulation intensity of the SACE_5599-inactivated strains when cultivated on ABSM4 agar medium. In contrast, constitutive overexpression of SACE_5599 in the wild type NRRL23338 strain resulted in an increase of erythromycin yield by 32%. Similar yield increase was also observed when we overexpressed the bldD gene, a previously identified regulator of erythromycin biosynthesis, thereby for the first time revealing its potential for improving erythromycin biosynthesis. SACE_5599 is the second putative regulatory gene to be identified in S. erythraea which has positive influence on erythromycin yield. Like bld

Dynamic Neural State Identification in Deep Brain Local Field Potentials of Neuropathic Pain.

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Luo, Huichun; Huang, Yongzhi; Du, Xueying; Zhang, Yunpeng; Green, Alexander L; Aziz, Tipu Z; Wang, Shouyan

2018-01-01

In neuropathic pain, the neurophysiological and neuropathological function of the ventro-posterolateral nucleus of the thalamus (VPL) and the periventricular gray/periaqueductal gray area (PVAG) involves multiple frequency oscillations. Moreover, oscillations related to pain perception and modulation change dynamically over time. Fluctuations in these neural oscillations reflect the dynamic neural states of the nucleus. In this study, an approach to classifying the synchronization level was developed to dynamically identify the neural states. An oscillation extraction model based on windowed wavelet packet transform was designed to characterize the activity level of oscillations. The wavelet packet coefficients sparsely represented the activity level of theta and alpha oscillations in local field potentials (LFPs). Then, a state discrimination model was designed to calculate an adaptive threshold to determine the activity level of oscillations. Finally, the neural state was represented by the activity levels of both theta and alpha oscillations. The relationship between neural states and pain relief was further evaluated. The performance of the state identification approach achieved sensitivity and specificity beyond 80% in simulation signals. Neural states of the PVAG and VPL were dynamically identified from LFPs of neuropathic pain patients. The occurrence of neural states based on theta and alpha oscillations were correlated to the degree of pain relief by deep brain stimulation. In the PVAG LFPs, the occurrence of the state with high activity levels of theta oscillations independent of alpha and the state with low-level alpha and high-level theta oscillations were significantly correlated with pain relief by deep brain stimulation. This study provides a reliable approach to identifying the dynamic neural states in LFPs with a low signal-to-noise ratio by using sparse representation based on wavelet packet transform. Furthermore, it may advance closed-loop deep

Neural and Fuzzy Adaptive Control of Induction Motor Drives

International Nuclear Information System (INIS)

Bensalem, Y.; Sbita, L.; Abdelkrim, M. N.

2008-01-01

This paper proposes an adaptive neural network speed control scheme for an induction motor (IM) drive. The proposed scheme consists of an adaptive neural network identifier (ANNI) and an adaptive neural network controller (ANNC). For learning the quoted neural networks, a back propagation algorithm was used to automatically adjust the weights of the ANNI and ANNC in order to minimize the performance functions. Here, the ANNI can quickly estimate the plant parameters and the ANNC is used to provide on-line identification of the command and to produce a control force, such that the motor speed can accurately track the reference command. By combining artificial neural network techniques with fuzzy logic concept, a neural and fuzzy adaptive control scheme is developed. Fuzzy logic was used for the adaptation of the neural controller to improve the robustness of the generated command. The developed method is robust to load torque disturbance and the speed target variations when it ensures precise trajectory tracking with the prescribed dynamics. The algorithm was verified by simulation and the results obtained demonstrate the effectiveness of the IM designed controller

Modeling and Speed Control of Induction Motor Drives Using Neural Networks

Directory of Open Access Journals (Sweden)

V. Jamuna

2010-08-01

Full Text Available Speed control of induction motor drives using neural networks is presented. The mathematical model of single phase induction motor is developed. A new simulink model for a neural network-controlled bidirectional chopper fed single phase induction motor is proposed. Under normal operation, the true drive parameters are real-time identified and they are converted into the controller parameters through multilayer forward computation by neural networks. Comparative study has been made between the conventional and neural network controllers. It is observed that the neural network controlled drive system has better dynamic performance, reduced overshoot and faster transient response than the conventional controlled system.

Gut Microbiome and Putative Resistome of Inca and Italian Nobility Mummies.

Science.gov (United States)

Santiago-Rodriguez, Tasha M; Fornaciari, Gino; Luciani, Stefania; Toranzos, Gary A; Marota, Isolina; Giuffra, Valentina; Cano, Raul J

2017-11-07

Little is still known about the microbiome resulting from the process of mummification of the human gut. In the present study, the gut microbiota, genes associated with metabolism, and putative resistome of Inca and Italian nobility mummies were characterized by using high-throughput sequencing. The Italian nobility mummies exhibited a higher bacterial diversity as compared to the Inca mummies when using 16S ribosomal (rRNA) gene amplicon sequencing, but both groups showed bacterial and fungal taxa when using shotgun metagenomic sequencing that may resemble both the thanatomicrobiome and extant human gut microbiomes. Identification of sequences associated with plants, animals, and carbohydrate-active enzymes (CAZymes) may provide further insights into the dietary habits of Inca and Italian nobility mummies. Putative antibiotic-resistance genes in the Inca and Italian nobility mummies support a human gut resistome prior to the antibiotic therapy era. The higher proportion of putative antibiotic-resistance genes in the Inca compared to Italian nobility mummies may support the hypotheses that a greater exposure to the environment may result in a greater acquisition of antibiotic-resistance genes. The present study adds knowledge of the microbiome resulting from the process of mummification of the human gut, insights of ancient dietary habits, and the preserved putative human gut resistome prior the antibiotic therapy era.

A Functional Assay for Putative Mouse and Human Definitive Endoderm using Chick Whole-Embryo Cultures

DEFF Research Database (Denmark)

Johannesson, Martina; Semb, Tor Henrik; Serup, Palle

2012-01-01

. Thus, the purpose of this study is to describe a method whereby the in vivo functionality of DE derived from ESCs can be assessed. Methods: By directed differentiation, putative DE was derived from human and mouse ESCs. This putative DE was subsequently transplanted into the endoderm of chick embryos...... to determine any occurrence of integration. Putative DE was analyzed by gene and protein expression prior to transplantation and 48 h post transplantation. Results: Putative DE, derived from mouse and human ESCs, was successfully integrated within the chick endoderm. Endoderm-specific genes were expressed...... result show that putative DE integrates with the chick endoderm and participate in the development of the chicken gut, indicating the generation of functional DE from ESCs. This functional assay can be used to assess the generation of functional DE derived from both human and mouse ESCs and provides...

Nonequilibrium landscape theory of neural networks

Science.gov (United States)

Yan, Han; Zhao, Lei; Hu, Liang; Wang, Xidi; Wang, Erkang; Wang, Jin

2013-01-01

The brain map project aims to map out the neuron connections of the human brain. Even with all of the wirings mapped out, the global and physical understandings of the function and behavior are still challenging. Hopfield quantified the learning and memory process of symmetrically connected neural networks globally through equilibrium energy. The energy basins of attractions represent memories, and the memory retrieval dynamics is determined by the energy gradient. However, the realistic neural networks are asymmetrically connected, and oscillations cannot emerge from symmetric neural networks. Here, we developed a nonequilibrium landscape–flux theory for realistic asymmetrically connected neural networks. We uncovered the underlying potential landscape and the associated Lyapunov function for quantifying the global stability and function. We found the dynamics and oscillations in human brains responsible for cognitive processes and physiological rhythm regulations are determined not only by the landscape gradient but also by the flux. We found that the flux is closely related to the degrees of the asymmetric connections in neural networks and is the origin of the neural oscillations. The neural oscillation landscape shows a closed-ring attractor topology. The landscape gradient attracts the network down to the ring. The flux is responsible for coherent oscillations on the ring. We suggest the flux may provide the driving force for associations among memories. We applied our theory to rapid-eye movement sleep cycle. We identified the key regulation factors for function through global sensitivity analysis of landscape topography against wirings, which are in good agreements with experiments. PMID:24145451

Nonequilibrium landscape theory of neural networks.

Science.gov (United States)

Yan, Han; Zhao, Lei; Hu, Liang; Wang, Xidi; Wang, Erkang; Wang, Jin

2013-11-05

The brain map project aims to map out the neuron connections of the human brain. Even with all of the wirings mapped out, the global and physical understandings of the function and behavior are still challenging. Hopfield quantified the learning and memory process of symmetrically connected neural networks globally through equilibrium energy. The energy basins of attractions represent memories, and the memory retrieval dynamics is determined by the energy gradient. However, the realistic neural networks are asymmetrically connected, and oscillations cannot emerge from symmetric neural networks. Here, we developed a nonequilibrium landscape-flux theory for realistic asymmetrically connected neural networks. We uncovered the underlying potential landscape and the associated Lyapunov function for quantifying the global stability and function. We found the dynamics and oscillations in human brains responsible for cognitive processes and physiological rhythm regulations are determined not only by the landscape gradient but also by the flux. We found that the flux is closely related to the degrees of the asymmetric connections in neural networks and is the origin of the neural oscillations. The neural oscillation landscape shows a closed-ring attractor topology. The landscape gradient attracts the network down to the ring. The flux is responsible for coherent oscillations on the ring. We suggest the flux may provide the driving force for associations among memories. We applied our theory to rapid-eye movement sleep cycle. We identified the key regulation factors for function through global sensitivity analysis of landscape topography against wirings, which are in good agreements with experiments.

Purification and subunit structure of a putative K sup + -channel protein identified by its binding properties for dendrotoxin I

Energy Technology Data Exchange (ETDEWEB)

Rehm, H.; Lazdunski, M. (Centre National de la Recherche Scientifique, Nice (France))

1988-07-01

The binding protein for the K{sup +}-channel toxin dendrotoxin I was purified from a detergent extract of rat brain membranes. The purification procedure utilized chromatography on DEAE-Trisacryl, affinity chromatography on a dendrotoxin-I-Aca 22 column, and wheat germ agglutinin-Affigel 10 with a final 3,800- to 4,600-fold enrichment and a recovery of 8-16%. The high affinity (K{sub d}, 40-100 pM) and specificity of the binding site are retained throughout the purification procedure. Analysis of the purified material on silver-stained NaDodSO{sub 4}/polyacrylamide gel revealed three bands of M{sub r} 76,000-80,000, 38,000 and 35,000. Interestingly, the binding site for {sup 125}I-labeled mast cell degranulating peptide, another putative K{sup +}-channel ligand from bee venom, which induces long-term potentiation in hippocampus, seems to reside on the same protein complex, as both binding sites copurify through the entire purification protocol.

Lim homeobox genes in the Ctenophore Mnemiopsis leidyi: the evolution of neural cell type specification

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Simmons David K

2012-01-01

Full Text Available Abstract Background Nervous systems are thought to be important to the evolutionary success and diversification of metazoans, yet little is known about the origin of simple nervous systems at the base of the animal tree. Recent data suggest that ctenophores, a group of macroscopic pelagic marine invertebrates, are the most ancient group of animals that possess a definitive nervous system consisting of a distributed nerve net and an apical statocyst. This study reports on details of the evolution of the neural cell type specifying transcription factor family of LIM homeobox containing genes (Lhx, which have highly conserved functions in neural specification in bilaterian animals. Results Using next generation sequencing, the first draft of the genome of the ctenophore Mnemiopsis leidyi has been generated. The Lhx genes in all animals are represented by seven subfamilies (Lhx1/5, Lhx3/4, Lmx, Islet, Lhx2/9, Lhx6/8, and LMO of which four were found to be represented in the ctenophore lineage (Lhx1/5, Lhx3/4, Lmx, and Islet. Interestingly, the ctenophore Lhx gene complement is more similar to the sponge complement (sponges do not possess neurons than to either the cnidarian-bilaterian or placozoan Lhx complements. Using whole mount in situ hybridization, the Lhx gene expression patterns were examined and found to be expressed around the blastopore and in cells that give rise to the apical organ and putative neural sensory cells. Conclusion This research gives us a first look at neural cell type specification in the ctenophore M. leidyi. Within M. leidyi, Lhx genes are expressed in overlapping domains within proposed neural cellular and sensory cell territories. These data suggest that Lhx genes likely played a conserved role in the patterning of sensory cells in the ancestor of sponges and ctenophores, and may provide a link to the expression of Lhx orthologs in sponge larval photoreceptive cells. Lhx genes were later co-opted into patterning more

Complete nucleotide sequence and genome organization of Olive latent virus 3, a new putative member of the family Tymoviridae.

Science.gov (United States)

Alabdullah, Abdulkader; Minafra, Angelantonio; Elbeaino, Toufic; Saponari, Maria; Savino, Vito; Martelli, Giovanni P

2010-09-01

The complete nucleotide sequence and the genome organization were determined of a putative new member of the family Tymoviridae, tentatively named Olive latent virus 3 (OLV-3), recovered in southern Italy from a symptomless olive tree. The sequenced ssRNA genome comprises 7148 nucleotides excluding the poly(A) tail and contains four open reading frames (ORFs). ORF1 encodes a polyprotein of 221.6kDa in size, containing the conserved signatures of the methyltransferase (MTR), papain-like protease (PRO), helicase (HEL) and RNA-dependent RNA polymerase (RdRp) domains of the replication-associated proteins of positive-strand RNA viruses. ORF2 overlaps completely ORF1 and encodes a putative protein of 43.33kDa showing limited sequence similarity with the putative movement protein of Maize rayado fino virus (MRFV). ORF3 codes for a protein with predicted molecular mass of 28.46kDa, identified as the coat protein (CP), whereas ORF4 overlaps ORF3 and encodes a putative protein of 16kDa with sequence similarity to the p16 and p31 proteins of Citrus sudden death-associated virus (CSDaV) and Grapevine fleck virus (GFkV), respectively. Within the family Tymoviridae, OLV-3 genome has the closest identity level (49-52%) with members of the genus Marafivirus, from which, however, it differs because of the diverse genome organization and the presence of a single type of CP subunits. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Face recognition based on improved BP neural network

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Yue Gaili

2017-01-01

Full Text Available In order to improve the recognition rate of face recognition, face recognition algorithm based on histogram equalization, PCA and BP neural network is proposed. First, the face image is preprocessed by histogram equalization. Then, the classical PCA algorithm is used to extract the features of the histogram equalization image, and extract the principal component of the image. And then train the BP neural network using the trained training samples. This improved BP neural network weight adjustment method is used to train the network because the conventional BP algorithm has the disadvantages of slow convergence, easy to fall into local minima and training process. Finally, the BP neural network with the test sample input is trained to classify and identify the face images, and the recognition rate is obtained. Through the use of ORL database face image simulation experiment, the analysis results show that the improved BP neural network face recognition method can effectively improve the recognition rate of face recognition.

The neural code for face orientation in the human fusiform face area.

Science.gov (United States)

Ramírez, Fernando M; Cichy, Radoslaw M; Allefeld, Carsten; Haynes, John-Dylan

2014-09-03

Humans recognize faces and objects with high speed and accuracy regardless of their orientation. Recent studies have proposed that orientation invariance in face recognition involves an intermediate representation where neural responses are similar for mirror-symmetric views. Here, we used fMRI, multivariate pattern analysis, and computational modeling to investigate the neural encoding of faces and vehicles at different rotational angles. Corroborating previous studies, we demonstrate a representation of face orientation in the fusiform face-selective area (FFA). We go beyond these studies by showing that this representation is category-selective and tolerant to retinal translation. Critically, by controlling for low-level confounds, we found the representation of orientation in FFA to be compatible with a linear angle code. Aspects of mirror-symmetric coding cannot be ruled out when FFA mean activity levels are considered as a dimension of coding. Finally, we used a parametric family of computational models, involving a biased sampling of view-tuned neuronal clusters, to compare different face angle encoding models. The best fitting model exhibited a predominance of neuronal clusters tuned to frontal views of faces. In sum, our findings suggest a category-selective and monotonic code of face orientation in the human FFA, in line with primate electrophysiology studies that observed mirror-symmetric tuning of neural responses at higher stages of the visual system, beyond the putative homolog of human FFA. Copyright © 2014 the authors 0270-6474/14/3412155-13$15.00/0.

Toddlers' Duration of Attention toward Putative Threat

Science.gov (United States)

Kiel, Elizabeth J.; Buss, Kristin A.

2011-01-01

Although individual differences in reactions to novelty in the toddler years have been consistently linked to risk of developing anxious behavior, toddlers' attention toward a novel, putatively threatening stimulus while in the presence of other enjoyable activities has rarely been examined as a precursor to such risk. The current study examined…

H-1 and N-15 resonance assignment of the second fibronectin type III module of the neural cell adhesion molecule

DEFF Research Database (Denmark)

Kiselyov, Vladislav V; Berezin, Vladimir; Bock, Elisabeth

2008-01-01

We report here the NMR assignment of the second fibronectin type III module of the neural cell adhesion molecule (NCAM). This module has previously been shown to interact with the fibroblast growth factor receptor (FGFR), and the FGFR-binding site was mapped by NMR to the FG-loop region of the mo......We report here the NMR assignment of the second fibronectin type III module of the neural cell adhesion molecule (NCAM). This module has previously been shown to interact with the fibroblast growth factor receptor (FGFR), and the FGFR-binding site was mapped by NMR to the FG-loop region...... of the module. The FG-loop region also contains a putative nucleotide-binding motif, which was shown by NMR to interact with ATP. Furthermore, ATP was demonstrated to inhibit binding of the second F3 module of NCAM to FGFR....

Neural networks in continuous optical media

International Nuclear Information System (INIS)

Anderson, D.Z.

1987-01-01

The authors' interest is to see to what extent neural models can be implemented using continuous optical elements. Thus these optical networks represent a continuous distribution of neuronlike processors rather than a discrete collection. Most neural models have three characteristic features: interconnections; adaptivity; and nonlinearity. In their optical representation the interconnections are implemented with linear one- and two-port optical elements such as lenses and holograms. Real-time holographic media allow these interconnections to become adaptive. The nonlinearity is achieved with gain, for example, from two-beam coupling in photorefractive media or a pumped dye medium. Using these basic optical elements one can in principle construct continuous representations of a number of neural network models. The authors demonstrated two devices based on continuous optical elements: an associative memory which recalls an entire object when addressed with a partial object and a tracking novelty filter which identifies time-dependent features in an optical scene. These devices demonstrate the potential of distributed optical elements to implement more formal models of neural networks

VISLISI trial, a prospective clinical study allowing identification of a new metalloprotease and putative virulence factor from Staphylococcus lugdunensis.

Science.gov (United States)

Argemi, X; Prévost, G; Riegel, P; Keller, D; Meyer, N; Baldeyrou, M; Douiri, N; Lefebvre, N; Meghit, K; Ronde Oustau, C; Christmann, D; Cianférani, S; Strub, J M; Hansmann, Y

2017-05-01

Staphylococcus lugdunensis is a coagulase-negative staphylococcus that displays an unusually high virulence rate close to that of Staphylococcus aureus. It also shares phenotypic properties with S. aureus and several studies found putative virulence factors. The objective of the study was to describe the clinical manifestations of S. lugdunensis infections and investigate putative virulence factors. We conducted a prospective study from November 2013 to March 2016 at the University Hospital of Strasbourg. Putative virulence factors were investigated by clumping factor detection, screening for proteolytic activity, and sequence analysis using tandem nano-liquid chromatography-mass spectrometry. In total, 347 positive samples for S. lugdunensis were collected, of which 129 (37.2%) were from confirmed cases of S. lugdunensis infection. Eighty-one of these 129 patients were included in the study. Bone and prosthetic joints (PJI) were the most frequent sites of infection (n=28; 34.6%) followed by skin and soft tissues (n=23; 28.4%). We identified and purified a novel protease secreted by 50 samples (61.7%), most frequently associated with samples from deep infections and PJI (pr 0.97 and pr 0.91, respectively). Protease peptide sequencing by nano-liquid chromatography-mass spectrometry revealed a novel protease bearing 62.42% identity with ShpI, a metalloprotease secreted by Staphylococcus hyicus. This study confirms the pathogenicity of S. lugdunensis, particularly in bone and PJI. We also identified a novel metalloprotease called lugdulysin that may contribute to virulence. Copyright © 2016 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

Influence of the Training Set Value on the Quality of the Neural Network to Identify Selected Moulding Sand Properties

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Jakubski J.

2013-06-01

Full Text Available Artificial neural networks are one of the modern methods of the production optimisation. An attempt to apply neural networks for controlling the quality of bentonite moulding sands is presented in this paper. This is the assessment method of sands suitability by means of detecting correlations between their individual parameters. This paper presents the next part of the study on usefulness of artificial neural networks to support rebonding of green moulding sand, using chosen properties of moulding sands, which can be determined fast. The effect of changes in the training set quantity on the quality of the network is presented in this article. It has been shown that a small change in the data set would change the quality of the network, and may also make it necessary to change the type of network in order to obtain good results.

Neural Network Approach to Locating Cryptography in Object Code

Energy Technology Data Exchange (ETDEWEB)

Jason L. Wright; Milos Manic

2009-09-01

Finding and identifying cryptography is a growing concern in the malware analysis community. In this paper, artificial neural networks are used to classify functional blocks from a disassembled program as being either cryptography related or not. The resulting system, referred to as NNLC (Neural Net for Locating Cryptography) is presented and results of applying this system to various libraries are described.

Neural Activity Patterns in the Human Brain Reflect Tactile Stickiness Perception

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Kim, Junsuk; Yeon, Jiwon; Ryu, Jaekyun; Park, Jang-Yeon; Chung, Soon-Cheol; Kim, Sung-Phil

2017-01-01

Our previous human fMRI study found brain activations correlated with tactile stickiness perception using the uni-variate general linear model (GLM) (Yeon et al., 2017). Here, we conducted an in-depth investigation on neural correlates of sticky sensations by employing a multivoxel pattern analysis (MVPA) on the same dataset. In particular, we statistically compared multi-variate neural activities in response to the three groups of sticky stimuli: A supra-threshold group including a set of sticky stimuli that evoked vivid sticky perception; an infra-threshold group including another set of sticky stimuli that barely evoked sticky perception; and a sham group including acrylic stimuli with no physically sticky property. Searchlight MVPAs were performed to search for local activity patterns carrying neural information of stickiness perception. Similar to the uni-variate GLM results, significant multi-variate neural activity patterns were identified in postcentral gyrus, subcortical (basal ganglia and thalamus), and insula areas (insula and adjacent areas). Moreover, MVPAs revealed that activity patterns in posterior parietal cortex discriminated the perceptual intensities of stickiness, which was not present in the uni-variate analysis. Next, we applied a principal component analysis (PCA) to the voxel response patterns within identified clusters so as to find low-dimensional neural representations of stickiness intensities. Follow-up clustering analyses clearly showed separate neural grouping configurations between the Supra- and Infra-threshold groups. Interestingly, this neural categorization was in line with the perceptual grouping pattern obtained from the psychophysical data. Our findings thus suggest that different stickiness intensities would elicit distinct neural activity patterns in the human brain and may provide a neural basis for the perception and categorization of tactile stickiness. PMID:28936171

FUZZY NEURAL NETWORK FOR OBJECT IDENTIFICATION ON INTEGRATED CIRCUIT LAYOUTS

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A. A. Doudkin

2015-01-01

Full Text Available Fuzzy neural network model based on neocognitron is proposed to identify layout objects on images of topological layers of integrated circuits. Testing of the model on images of real chip layouts was showed a highеr degree of identification of the proposed neural network in comparison to base neocognitron.

A putative autonomous 20.5 kb-CACTA transposon insertion in an F3'H allele identifies a new CACTA transposon subfamily in Glycine max

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Vodkin Lila

2008-12-01

Full Text Available Abstract Background The molecular organization of very few genetically defined CACTA transposon systems have been characterized thoroughly as those of Spm/En in maize, Tam1 of Antirrhinum majus Candystripe1 (Cs1 from Sorghum bicolor and CAC1 from Arabidopsis thaliana, for example. To date, only defective deletion derivatives of CACTA elements have been described for soybean, an economically important plant species whose genome sequence will be completed in 2008. Results We identified a 20.5 kb insertion in a soybean flavonoid 3'-hydroxylase (F3'H gene representing the t* allele (stable gray trichome color whose origin traces to a single mutable chimeric plant displaying both tawny and gray trichomes. This 20.5 kb insertion has the molecular structure of a putative autonomous transposon of the CACTA family, designated Tgmt*. It encodes a large gene that was expressed in two sister isolines (T* and tm of the stable gray line (t* from which Tgmt* was isolated. RT-PCR derived cDNAs uncovered the structure of a large precursor mRNA as well as alternatively spliced transcripts reminiscent of the TNPA-mRNA generated by the En-1 element of maize but without sequence similarity to the maize TNPA. The larger mRNA encodes a transposase with a tnp2 and TNP1-transposase family domains. Because the two soybean lines expressing Tgmt* were derived from the same mutable chimeric plant that created the stable gray trichome t* allele line from which the element was isolated, Tgmt* has the potential to be an autonomous element that was rapidly inactivated in the stable gray trichome t* line. Comparison of Tgmt* to previously described Tgm elements demonstrated that two subtypes of CACTA transposon families exist in soybean based on divergence of their characteristic subterminal repeated motifs and their transposases. In addition, we report the sequence and annotation of a BAC clone containing the F3'H gene (T locus which was interrupted by the novel Tgmt* element

Gut Microbiome and Putative Resistome of Inca and Italian Nobility Mummies

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Tasha M. Santiago-Rodriguez

2017-11-01

Full Text Available Little is still known about the microbiome resulting from the process of mummification of the human gut. In the present study, the gut microbiota, genes associated with metabolism, and putative resistome of Inca and Italian nobility mummies were characterized by using high-throughput sequencing. The Italian nobility mummies exhibited a higher bacterial diversity as compared to the Inca mummies when using 16S ribosomal (rRNA gene amplicon sequencing, but both groups showed bacterial and fungal taxa when using shotgun metagenomic sequencing that may resemble both the thanatomicrobiome and extant human gut microbiomes. Identification of sequences associated with plants, animals, and carbohydrate-active enzymes (CAZymes may provide further insights into the dietary habits of Inca and Italian nobility mummies. Putative antibiotic-resistance genes in the Inca and Italian nobility mummies support a human gut resistome prior to the antibiotic therapy era. The higher proportion of putative antibiotic-resistance genes in the Inca compared to Italian nobility mummies may support the hypotheses that a greater exposure to the environment may result in a greater acquisition of antibiotic-resistance genes. The present study adds knowledge of the microbiome resulting from the process of mummification of the human gut, insights of ancient dietary habits, and the preserved putative human gut resistome prior the antibiotic therapy era.

Ten Putative Contributors to the Obesity Epidemic

Science.gov (United States)

McAllister, Emily J.; Dhurandhar, Nikhil V.; Keith, Scott W.; Aronne, Louis J.; Barger, Jamie; Baskin, Monica; Benca, Ruth M.; Biggio, Joseph; Boggiano, Mary M.; Eisenmann, Joe C.; Elobeid, Mai; Fontaine, Kevin R.; Gluckman, Peter; Hanlon, Erin C.; Katzmarzyk, Peter; Pietrobelli, Angelo; Redden, David T.; Ruden, Douglas M.; Wang, Chenxi; Waterland, Robert A.; Wright, Suzanne M.; Allison, David B.

2010-01-01

The obesity epidemic is a global issue and shows no signs of abating, while the cause of this epidemic remains unclear. Marketing practices of energy-dense foods and institutionally-driven declines in physical activity are the alleged perpetrators for the epidemic, despite a lack of solid evidence to demonstrate their causal role. While both may contribute to obesity, we call attention to their unquestioned dominance in program funding and public efforts to reduce obesity, and propose several alternative putative contributors that would benefit from equal consideration and attention. Evidence for microorganisms, epigenetics, increasing maternal age, greater fecundity among people with higher adiposity, assortative mating, sleep debt, endocrine disruptors, pharmaceutical iatrogenesis, reduction in variability of ambient temperatures, and intrauterine and intergenerational effects, as contributing factors to the obesity epidemic are reviewed herein. While the evidence is strong for some contributors such as pharmaceutical-induced weight gain, it is still emerging for other reviewed factors. Considering the role of such putative etiological factors of obesity may lead to comprehensive, cause specific, and effective strategies for prevention and treatment of this global epidemic. PMID:19960394

Estimation of neural energy in microelectrode signals

Science.gov (United States)

Gaumond, R. P.; Clement, R.; Silva, R.; Sander, D.

2004-09-01

We considered the problem of determining the neural contribution to the signal recorded by an intracortical electrode. We developed a linear least-squares approach to determine the energy fraction of a signal attributable to an arbitrary number of autocorrelation-defined signals buried in noise. Application of the method requires estimation of autocorrelation functions Rap(tgr) characterizing the action potential (AP) waveforms and Rn(tgr) characterizing background noise. This method was applied to the analysis of chronically implanted microelectrode signals from motor cortex of rat. We found that neural (AP) energy consisted of a large-signal component which grows linearly with the number of threshold-detected neural events and a small-signal component unrelated to the count of threshold-detected AP signals. The addition of pseudorandom noise to electrode signals demonstrated the algorithm's effectiveness for a wide range of noise-to-signal energy ratios (0.08 to 39). We suggest, therefore, that the method could be of use in providing a measure of neural response in situations where clearly identified spike waveforms cannot be isolated, or in providing an additional 'background' measure of microelectrode neural activity to supplement the traditional AP spike count.

Transcriptome analysis of Spodoptera frugiperda Sf9 cells reveals putative apoptosis-related genes and a preliminary apoptosis mechanism induced by azadirachtin.

Science.gov (United States)

Shu, Benshui; Zhang, Jingjing; Sethuraman, Veeran; Cui, Gaofeng; Yi, Xin; Zhong, Guohua

2017-10-16

As an important botanical pesticide, azadirachtin demonstrates broad insecticidal activity against many agricultural pests. The results of a previous study indicated the toxicity and apoptosis induction of azadirachtin in Spodoptera frugiperda Sf9 cells. However, the lack of genomic data has hindered a deeper investigation of apoptosis in Sf9 cells at a molecular level. In the present study, the complete transcriptome data for Sf9 cell line was accomplished using Illumina sequencing technology, and 97 putative apoptosis-related genes were identified through BLAST and KEGG orthologue annotations. Fragments of potential candidate apoptosis-related genes were cloned, and the mRNA expression patterns of ten identified genes regulated by azadirachtin were examined using qRT-PCR. Furthermore, Western blot analysis showed that six putative apoptosis-related proteins were upregulated after being treated with azadirachtin while the protein Bcl-2 were downregulated. These data suggested that both intrinsic and extrinsic apoptotic signal pathways comprising the identified potential apoptosis-related genes were potentially active in S. frugiperda. In addition, the preliminary results revealed that caspase-dependent or caspase-independent apoptotic pathways could function in azadirachtin-induced apoptosis in Sf9 cells.

A nuclear magnetic resonance based approach to accurate functional annotation of putative enzymes in the methanogen Methanosarcina acetivorans

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Nikolau Basil J

2011-06-01

Full Text Available Abstract Background Correct annotation of function is essential if one is to take full advantage of the vast amounts of genomic sequence data. The accuracy of sequence-based functional annotations is often variable, particularly if the sequence homology to a known function is low. Indeed recent work has shown that even proteins with very high sequence identity can have different folds and functions, and therefore caution is needed in assigning functions by sequence homology in the absence of experimental validation. Experimental methods are therefore needed to efficiently evaluate annotations in a way that complements current high throughput technologies. Here, we describe the use of nuclear magnetic resonance (NMR-based ligand screening as a tool for testing functional assignments of putative enzymes that may be of variable reliability. Results The target genes for this study are putative enzymes from the methanogenic archaeon Methanosarcina acetivorans (MA that have been selected after manual genome re-annotation and demonstrate detectable in vivo expression at the level of the transcriptome. The experimental approach begins with heterologous E. coli expression and purification of individual MA gene products. An NMR-based ligand screen of the purified protein then identifies possible substrates or products from a library of candidate compounds chosen from the putative pathway and other related pathways. These data are used to determine if the current sequence-based annotation is likely to be correct. For a number of case studies, additional experiments (such as in vivo genetic complementation were performed to determine function so that the reliability of the NMR screen could be independently assessed. Conclusions In all examples studied, the NMR screen was indicative of whether the functional annotation was correct. Thus, the case studies described demonstrate that NMR-based ligand screening is an effective and rapid tool for confirming or

Neural network post-processing of grayscale optical correlator

Science.gov (United States)

Lu, Thomas T; Hughlett, Casey L.; Zhoua, Hanying; Chao, Tien-Hsin; Hanan, Jay C.

2005-01-01

In this paper we present the use of a radial basis function neural network (RBFNN) as a post-processor to assist the optical correlator to identify the objects and to reject false alarms. Image plane features near the correlation peaks are extracted and fed to the neural network for analysis. The approach is capable of handling large number of object variations and filter sets. Preliminary experimental results are presented and the performance is analyzed.

Identification of Putative Precursor Genes for the Biosynthesis of Cannabinoid-Like Compound in Radula marginata

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Tajammul Hussain

2018-05-01

Full Text Available The liverwort Radula marginata belongs to the bryophyte division of land plants and is a prospective alternate source of cannabinoid-like compounds. However, mechanistic insights into the molecular pathways directing the synthesis of these cannabinoid-like compounds have been hindered due to the lack of genetic information. This prompted us to do deep sequencing, de novo assembly and annotation of R. marginata transcriptome, which resulted in the identification and validation of the genes for cannabinoid biosynthetic pathway. In total, we have identified 11,421 putative genes encoding 1,554 enzymes from 145 biosynthetic pathways. Interestingly, we have identified all the upstream genes of the central precursor of cannabinoid biosynthesis, cannabigerolic acid (CBGA, including its two first intermediates, stilbene acid (SA and geranyl diphosphate (GPP. Expression of all these genes was validated using quantitative real-time PCR. We have characterized the protein structure of stilbene synthase (STS, which is considered as a homolog of olivetolic acid in R. marginata. Moreover, the metabolomics approach enabled us to identify CBGA-analogous compounds using electrospray ionization mass spectrometry (ESI-MS/MS and gas chromatography mass spectrometry (GC-MS. Transcriptomic analysis revealed 1085 transcription factors (TF from 39 families. Comparative analysis showed that six TF families have been uniquely predicted in R. marginata. In addition, the bioinformatics analysis predicted a large number of simple sequence repeats (SSRs and non-coding RNAs (ncRNAs. Our results collectively provide mechanistic insights into the putative precursor genes for the biosynthesis of cannabinoid-like compounds and a novel transcriptomic resource for R. marginata. The large-scale transcriptomic resource generated in this study would further serve as a reference transcriptome to explore the Radulaceae family.

Therapeutic physical exercise in neural injury: friend or foe?

Science.gov (United States)

Park, Kanghui; Lee, Seunghoon; Hong, Yunkyung; Park, Sookyoung; Choi, Jeonghyun; Chang, Kyu-Tae; Kim, Joo-Heon; Hong, Yonggeun

2015-12-01

[Purpose] The intensity of therapeutic physical exercise is complex and sometimes controversial in patients with neural injuries. This review assessed whether therapeutic physical exercise is beneficial according to the intensity of the physical exercise. [Methods] The authors identified clinically or scientifically relevant articles from PubMed that met the inclusion criteria. [Results] Exercise training can improve body strength and lead to the physiological adaptation of skeletal muscles and the nervous system after neural injuries. Furthermore, neurophysiological and neuropathological studies show differences in the beneficial effects of forced therapeutic exercise in patients with severe or mild neural injuries. Forced exercise alters the distribution of muscle fiber types in patients with neural injuries. Based on several animal studies, forced exercise may promote functional recovery following cerebral ischemia via signaling molecules in ischemic brain regions. [Conclusions] This review describes several types of therapeutic forced exercise and the controversy regarding the therapeutic effects in experimental animals versus humans with neural injuries. This review also provides a therapeutic strategy for physical therapists that grades the intensity of forced exercise according to the level of neural injury.

Identification and adaptive neural network control of a DC motor system with dead-zone characteristics.

Science.gov (United States)

Peng, Jinzhu; Dubay, Rickey

2011-10-01

In this paper, an adaptive control approach based on the neural networks is presented to control a DC motor system with dead-zone characteristics (DZC), where two neural networks are proposed to formulate the traditional identification and control approaches. First, a Wiener-type neural network (WNN) is proposed to identify the motor DZC, which formulates the Wiener model with a linear dynamic block in cascade with a nonlinear static gain. Second, a feedforward neural network is proposed to formulate the traditional PID controller, termed as PID-type neural network (PIDNN), which is then used to control and compensate for the DZC. In this way, the DC motor system with DZC is identified by the WNN identifier, which provides model information to the PIDNN controller in order to make it adaptive. Back-propagation algorithms are used to train both neural networks. Also, stability and convergence analysis are conducted using the Lyapunov theorem. Finally, experiments on the DC motor system demonstrated accurate identification and good compensation for dead-zone with improved control performance over the conventional PID control. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

Geochemical characterization of oceanic basalts using artificial neural network

Digital Repository Service at National Institute of Oceanography (India)

Das, P.; Iyer, S.D.

method is specifically needed to identify the OFB as normal (N-MORB), enriched (E-MORB) and ocean island basalts (OIB). Artificial Neural Network (ANN) technique as a supervised Learning Vector Quantisation (LVQ) is applied to identify the inherent...

Evolvable synthetic neural system

Science.gov (United States)

Curtis, Steven A. (Inventor)

2009-01-01

An evolvable synthetic neural system includes an evolvable neural interface operably coupled to at least one neural basis function. Each neural basis function includes an evolvable neural interface operably coupled to a heuristic neural system to perform high-level functions and an autonomic neural system to perform low-level functions. In some embodiments, the evolvable synthetic neural system is operably coupled to one or more evolvable synthetic neural systems in a hierarchy.

Neural electrical activity and neural network growth.

Science.gov (United States)

Gafarov, F M

2018-05-01

The development of central and peripheral neural system depends in part on the emergence of the correct functional connectivity in its input and output pathways. Now it is generally accepted that molecular factors guide neurons to establish a primary scaffold that undergoes activity-dependent refinement for building a fully functional circuit. However, a number of experimental results obtained recently shows that the neuronal electrical activity plays an important role in the establishing of initial interneuronal connections. Nevertheless, these processes are rather difficult to study experimentally, due to the absence of theoretical description and quantitative parameters for estimation of the neuronal activity influence on growth in neural networks. In this work we propose a general framework for a theoretical description of the activity-dependent neural network growth. The theoretical description incorporates a closed-loop growth model in which the neural activity can affect neurite outgrowth, which in turn can affect neural activity. We carried out the detailed quantitative analysis of spatiotemporal activity patterns and studied the relationship between individual cells and the network as a whole to explore the relationship between developing connectivity and activity patterns. The model, developed in this work will allow us to develop new experimental techniques for studying and quantifying the influence of the neuronal activity on growth processes in neural networks and may lead to a novel techniques for constructing large-scale neural networks by self-organization. Copyright © 2018 Elsevier Ltd. All rights reserved.

Neural Network Machine Learning and Dimension Reduction for Data Visualization

Science.gov (United States)

Liles, Charles A.

2014-01-01

Neural network machine learning in computer science is a continuously developing field of study. Although neural network models have been developed which can accurately predict a numeric value or nominal classification, a general purpose method for constructing neural network architecture has yet to be developed. Computer scientists are often forced to rely on a trial-and-error process of developing and improving accurate neural network models. In many cases, models are constructed from a large number of input parameters. Understanding which input parameters have the greatest impact on the prediction of the model is often difficult to surmise, especially when the number of input variables is very high. This challenge is often labeled the "curse of dimensionality" in scientific fields. However, techniques exist for reducing the dimensionality of problems to just two dimensions. Once a problem's dimensions have been mapped to two dimensions, it can be easily plotted and understood by humans. The ability to visualize a multi-dimensional dataset can provide a means of identifying which input variables have the highest effect on determining a nominal or numeric output. Identifying these variables can provide a better means of training neural network models; models can be more easily and quickly trained using only input variables which appear to affect the outcome variable. The purpose of this project is to explore varying means of training neural networks and to utilize dimensional reduction for visualizing and understanding complex datasets.

Identifying endogenous neural stem cells in the adult brain in vitro and in vivo: novel approaches.

Science.gov (United States)

Rueger, Maria Adele; Androutsellis-Theotokis, Andreas

2013-01-01

In the 1960s, Joseph Altman reported that the adult mammalian brain is capable of generating new neurons. Today it is understood that some of these neurons are derived from uncommitted cells in the subventricular zone lining the lateral ventricles, and the dentate gyrus of the hippocampus. The first area generates new neuroblasts which migrate to the olfactory bulb, whereas hippocampal neurogenesis seems to play roles in particular types of learning and memory. A part of these uncommitted (immature) cells is able to divide and their progeny can generate all three major cell types of the nervous system: neurons, astrocytes, and oligodendrocytes; these properties define such cells as neural stem cells. Although the roles of these cells are not yet clear, it is accepted that they affect functions including olfaction and learning/memory. Experiments with insults to the central nervous system also show that neural stem cells are quickly mobilized due to injury and in various disorders by proliferating, and migrating to injury sites. This suggests a role of endogenous neural stem cells in disease. New pools of stem cells are being discovered, suggesting an even more important role for these cells. To understand these cells and to coax them to contribute to tissue repair it would be very useful to be able to image them in the living organism. Here we discuss advances in imaging approaches as well as new concepts that emerge from stem cell biology with emphasis on the interface between imaging and stem cells.

Cracking the Neural Code for Sensory Perception by Combining Statistics, Intervention, and Behavior.

Science.gov (United States)

Panzeri, Stefano; Harvey, Christopher D; Piasini, Eugenio; Latham, Peter E; Fellin, Tommaso

2017-02-08

The two basic processes underlying perceptual decisions-how neural responses encode stimuli, and how they inform behavioral choices-have mainly been studied separately. Thus, although many spatiotemporal features of neural population activity, or "neural codes," have been shown to carry sensory information, it is often unknown whether the brain uses these features for perception. To address this issue, we propose a new framework centered on redefining the neural code as the neural features that carry sensory information used by the animal to drive appropriate behavior; that is, the features that have an intersection between sensory and choice information. We show how this framework leads to a new statistical analysis of neural activity recorded during behavior that can identify such neural codes, and we discuss how to combine intersection-based analysis of neural recordings with intervention on neural activity to determine definitively whether specific neural activity features are involved in a task. Copyright © 2017 Elsevier Inc. All rights reserved.

Gender effects and sexual-orientation impact on androstadienone-evoked behavior and neural processing

Directory of Open Access Journals (Sweden)

Jacqueline eKrajnik

2014-07-01

Full Text Available In humans, the most established and investigated substance acting as a chemosignal, i.e., a substance that is excreted from the body, is 4,16-androstadien-3-one (AND. AND, which is found in sweat and saliva, is known to be responsible for influencing several variables, such as psychophysiological status, behavior, as well as cortical processing. The aim of the present review is to give insight into the variety of AND effects, with special regard to specific cross-sexual characteristics of this putative human chemosignal, emphasizing the neural activation patterns and factors such as contextual conditions. This review highlights the importance of including those contributing factors into the analysis of behavioral as well as brain-related studies.

Neural Interfaces for Intracortical Recording: Requirements, Fabrication Methods, and Characteristics.

Science.gov (United States)

Szostak, Katarzyna M; Grand, Laszlo; Constandinou, Timothy G

2017-01-01

Implantable neural interfaces for central nervous system research have been designed with wire, polymer, or micromachining technologies over the past 70 years. Research on biocompatible materials, ideal probe shapes, and insertion methods has resulted in building more and more capable neural interfaces. Although the trend is promising, the long-term reliability of such devices has not yet met the required criteria for chronic human application. The performance of neural interfaces in chronic settings often degrades due to foreign body response to the implant that is initiated by the surgical procedure, and related to the probe structure, and material properties used in fabricating the neural interface. In this review, we identify the key requirements for neural interfaces for intracortical recording, describe the three different types of probes-microwire, micromachined, and polymer-based probes; their materials, fabrication methods, and discuss their characteristics and related challenges.

Deciphering Neural Codes of Memory during Sleep

Science.gov (United States)

Chen, Zhe; Wilson, Matthew A.

2017-01-01

Memories of experiences are stored in the cerebral cortex. Sleep is critical for consolidating hippocampal memory of wake experiences into the neocortex. Understanding representations of neural codes of hippocampal-neocortical networks during sleep would reveal important circuit mechanisms on memory consolidation, and provide novel insights into memory and dreams. Although sleep-associated ensemble spike activity has been investigated, identifying the content of memory in sleep remains challenging. Here, we revisit important experimental findings on sleep-associated memory (i.e., neural activity patterns in sleep that reflect memory processing) and review computational approaches for analyzing sleep-associated neural codes (SANC). We focus on two analysis paradigms for sleep-associated memory, and propose a new unsupervised learning framework (“memory first, meaning later”) for unbiased assessment of SANC. PMID:28390699

Nonlinear identification of process dynamics using neural networks

International Nuclear Information System (INIS)

Parlos, A.G.; Atiya, A.F.; Chong, K.T.

1992-01-01

In this paper the nonlinear identification of process dynamics encountered in nuclear power plant components is addressed, in an input-output sense, using artificial neural systems. A hybrid feedforward/feedback neural network, namely, a recurrent multilayer perceptron, is used as the model structure to be identified. The feedforward portion of the network architecture provides its well-known interpolation property, while through recurrency and cross-talk, the local information feedback enables representation of temporal variations in the system nonlinearities. The standard backpropagation learning algorithm is modified, and it is used for the supervised training of the proposed hybrid network. The performance of recurrent multilayer perceptron networks in identifying process dynamics is investigated via the case study of a U-tube steam generator. The response of representative steam generator is predicted using a neural network, and it is compared to the response obtained from a sophisticated computer model based on first principles. The transient responses compare well, although further research is warranted to determine the predictive capabilities of these networks during more severe operational transients and accident scenarios

The systematic functional analysis of plasmodium protein kinases identifies essential regulators of mosquito transmission

KAUST Repository

Tewari, Rita; Straschil, Ursula; Bateman, Alex; Bö hme, Ulrike; Cherevach, Inna; Gong, Peng; Pain, Arnab; Billker, Oliver

2010-01-01

Although eukaryotic protein kinases (ePKs) contribute to many cellular processes, only three Plasmodium falciparum ePKs have thus far been identified as essential for parasite asexual blood stage development. To identify pathways essential for parasite transmission between their mammalian host and mosquito vector, we undertook a systematic functional analysis of ePKs in the genetically tractable rodent parasite Plasmodium berghei. Modeling domain signatures of conventional ePKs identified 66 putative Plasmodium ePKs. Kinomes are highly conserved between Plasmodium species. Using reverse genetics, we show that 23 ePKs are redundant for asexual erythrocytic parasite development in mice. Phenotyping mutants at four life cycle stages in Anopheles stephensi mosquitoes revealed functional clusters of kinases required for sexual development and sporogony. Roles for a putative SR protein kinase (SRPK) in microgamete formation, a conserved regulator of clathrin uncoating (GAK) in ookinete formation, and a likely regulator of energy metabolism (SNF1/KIN) in sporozoite development were identified. 2010 Elsevier Inc.

The systematic functional analysis of plasmodium protein kinases identifies essential regulators of mosquito transmission

KAUST Repository

Tewari, Rita

2010-10-21

Although eukaryotic protein kinases (ePKs) contribute to many cellular processes, only three Plasmodium falciparum ePKs have thus far been identified as essential for parasite asexual blood stage development. To identify pathways essential for parasite transmission between their mammalian host and mosquito vector, we undertook a systematic functional analysis of ePKs in the genetically tractable rodent parasite Plasmodium berghei. Modeling domain signatures of conventional ePKs identified 66 putative Plasmodium ePKs. Kinomes are highly conserved between Plasmodium species. Using reverse genetics, we show that 23 ePKs are redundant for asexual erythrocytic parasite development in mice. Phenotyping mutants at four life cycle stages in Anopheles stephensi mosquitoes revealed functional clusters of kinases required for sexual development and sporogony. Roles for a putative SR protein kinase (SRPK) in microgamete formation, a conserved regulator of clathrin uncoating (GAK) in ookinete formation, and a likely regulator of energy metabolism (SNF1/KIN) in sporozoite development were identified. 2010 Elsevier Inc.

Altered Synchronizations among Neural Networks in Geriatric Depression.

Science.gov (United States)

Wang, Lihong; Chou, Ying-Hui; Potter, Guy G; Steffens, David C

2015-01-01

Although major depression has been considered as a manifestation of discoordinated activity between affective and cognitive neural networks, only a few studies have examined the relationships among neural networks directly. Because of the known disconnection theory, geriatric depression could be a useful model in studying the interactions among different networks. In the present study, using independent component analysis to identify intrinsically connected neural networks, we investigated the alterations in synchronizations among neural networks in geriatric depression to better understand the underlying neural mechanisms. Resting-state fMRI data was collected from thirty-two patients with geriatric depression and thirty-two age-matched never-depressed controls. We compared the resting-state activities between the two groups in the default-mode, central executive, attention, salience, and affective networks as well as correlations among these networks. The depression group showed stronger activity than the controls in an affective network, specifically within the orbitofrontal region. However, unlike the never-depressed controls, geriatric depression group lacked synchronized/antisynchronized activity between the affective network and the other networks. Those depressed patients with lower executive function has greater synchronization between the salience network with the executive and affective networks. Our results demonstrate the effectiveness of the between-network analyses in examining neural models for geriatric depression.

Detection of putatively thermophilic anaerobic methanotrophs in diffuse hydrothermal vent fluids.

Science.gov (United States)

Merkel, Alexander Y; Huber, Julie A; Chernyh, Nikolay A; Bonch-Osmolovskaya, Elizaveta A; Lebedinsky, Alexander V

2013-02-01

The anaerobic oxidation of methane (AOM) is carried out by a globally distributed group of uncultivated Euryarchaeota, the anaerobic methanotrophic arachaea (ANME). In this work, we used G+C analysis of 16S rRNA genes to identify a putatively thermophilic ANME group and applied newly designed primers to study its distribution in low-temperature diffuse vent fluids from deep-sea hydrothermal vents. We found that the G+C content of the 16S rRNA genes (P(GC)) is significantly higher in the ANME-1GBa group than in other ANME groups. Based on the positive correlation between the P(GC) and optimal growth temperatures (T(opt)) of archaea, we hypothesize that the ANME-1GBa group is adapted to thrive at high temperatures. We designed specific 16S rRNA gene-targeted primers for the ANME-1 cluster to detect all phylogenetic groups within this cluster, including the deeply branching ANME-1GBa group. The primers were successfully tested both in silico and in experiments with sediment samples where ANME-1 phylotypes had previously been detected. The primers were further used to screen for the ANME-1 microorganisms in diffuse vent fluid samples from deep-sea hydrothermal vents in the Pacific Ocean, and sequences belonging to the ANME-1 cluster were detected in four individual vents. Phylotypes belonging to the ANME-1GBa group dominated in clone libraries from three of these vents. Our findings provide evidence of existence of a putatively extremely thermophilic group of methanotrophic archaea that occur in geographically and geologically distinct marine hydrothermal habitats.

Distribution of Mast Cells and Locations, Depths, and Sizes of the Putative Acupoints CV 8 and KI 16

Directory of Open Access Journals (Sweden)

Sharon Jiyoon Jung

2017-01-01

Full Text Available The anatomical locations and sizes of acupuncture points (APs are identified in traditional Chinese medicine by using the cun measurement method. More precise knowledge of those locations and sizes to submillimeter precision, along with their cytological characterizations, would provide significant contributions both to scientific investigations and to precise control of the practice of acupuncture. Over recent decades, researchers have come to realize that APs in the skin of rats and humans have more mast cells (MCs than neighboring nonacupoints. In this work, the distribution of MCs in the ventral skin of mice was studied so that it could be used to infer the locations, depths from the epidermis, and sizes of three putative APs. The umbilicus was taken as the reference point, and a transversal cross section through it was studied. The harvested skins from 8-week-old mice were stained with toluidine blue, and the MCs were recognized by their red-purple stains and their metachromatic granules. The three putative APs, CV 8 and the left and the right KI 16 APs, were identified based on their high densities of MCs. These findings also imply that acupuncture may stimulate, through MCs, an immune response to allergic inflammation.

ESTs Analysis of Putative Genes Engaged in Polyporus umbellatus Sclerotial Development

Directory of Open Access Journals (Sweden)

Chao Song

2014-09-01

Full Text Available Polyporus umbellatus is one of the most widely used and precious medicinal fungi and the underground sclerotia are known to be with great medicinal value. However, the molecular mechanisms involved in sclerotial development are poorly understood. In the present study, we constructed a forward suppression subtractive hybridization (SSH cDNA library of Polyporus umbellatus to identify genes expressing differently between mycelium and sclerotia. In this library, a total of 1202 clones were sequenced, assembled into 222 contigs and 524 singletons which were further searched against the NCBI nonredundant (NR protein database (E-value cutoff, 10−5. Based on sequence similarity with known proteins, 378 sequences between mycelium and sclerotial were identified and classified into different functional categories through Gene Ontology (GO, Clusters of orthologous Groups of proteins (COGs. We have finally identified a majority of differentially expressed genes (constituting 5.6% of the present library between the two different periods. An expression level of 32 selected expressed sequence tags (ESTs generated from the above SSH cDNA library was studied through RT-PCR. This study provides the first global overview of genes putatively involved in Polyporus umbellatus sclerotial development and provides a preliminary basis for further functional research in terms of regulated gene expression in sclerotial production.

Handedness is related to neural mechanisms underlying hemispheric lateralization of face processing

Science.gov (United States)

Frässle, Stefan; Krach, Sören; Paulus, Frieder Michel; Jansen, Andreas

2016-06-01

While the right-hemispheric lateralization of the face perception network is well established, recent evidence suggests that handedness affects the cerebral lateralization of face processing at the hierarchical level of the fusiform face area (FFA). However, the neural mechanisms underlying differential hemispheric lateralization of face perception in right- and left-handers are largely unknown. Using dynamic causal modeling (DCM) for fMRI, we aimed to unravel the putative processes that mediate handedness-related differences by investigating the effective connectivity in the bilateral core face perception network. Our results reveal an enhanced recruitment of the left FFA in left-handers compared to right-handers, as evidenced by more pronounced face-specific modulatory influences on both intra- and interhemispheric connections. As structural and physiological correlates of handedness-related differences in face processing, right- and left-handers varied with regard to their gray matter volume in the left fusiform gyrus and their pupil responses to face stimuli. Overall, these results describe how handedness is related to the lateralization of the core face perception network, and point to different neural mechanisms underlying face processing in right- and left-handers. In a wider context, this demonstrates the entanglement of structurally and functionally remote brain networks, suggesting a broader underlying process regulating brain lateralization.

Neural Interfaces for Intracortical Recording: Requirements, Fabrication Methods, and Characteristics

Directory of Open Access Journals (Sweden)

Katarzyna M. Szostak

2017-12-01

Full Text Available Implantable neural interfaces for central nervous system research have been designed with wire, polymer, or micromachining technologies over the past 70 years. Research on biocompatible materials, ideal probe shapes, and insertion methods has resulted in building more and more capable neural interfaces. Although the trend is promising, the long-term reliability of such devices has not yet met the required criteria for chronic human application. The performance of neural interfaces in chronic settings often degrades due to foreign body response to the implant that is initiated by the surgical procedure, and related to the probe structure, and material properties used in fabricating the neural interface. In this review, we identify the key requirements for neural interfaces for intracortical recording, describe the three different types of probes—microwire, micromachined, and polymer-based probes; their materials, fabrication methods, and discuss their characteristics and related challenges.

Phylogenetic and comparative gene expression analysis of barley (Hordeum vulgare)WRKY transcription factor family reveals putatively retained functions betweenmonocots and dicots

Energy Technology Data Exchange (ETDEWEB)

Mangelsen, Elke; Kilian, Joachim; Berendzen, Kenneth W.; Kolukisaoglu, Uner; Harter, Klaus; Jansson, Christer; Wanke, Dierk

2008-02-01

WRKY proteins belong to the WRKY-GCM1 superfamily of zinc finger transcription factors that have been subject to a large plant-specific diversification. For the cereal crop barley (Hordeum vulgare), three different WRKY proteins have been characterized so far, as regulators in sucrose signaling, in pathogen defense, and in response to cold and drought, respectively. However, their phylogenetic relationship remained unresolved. In this study, we used the available sequence information to identify a minimum number of 45 barley WRKY transcription factor (HvWRKY) genes. According to their structural features the HvWRKY factors were classified into the previously defined polyphyletic WRKY subgroups 1 to 3. Furthermore, we could assign putative orthologs of the HvWRKY proteins in Arabidopsis and rice. While in most cases clades of orthologous proteins were formed within each group or subgroup, other clades were composed of paralogous proteins for the grasses and Arabidopsis only, which is indicative of specific gene radiation events. To gain insight into their putative functions, we examined expression profiles of WRKY genes from publicly available microarray data resources and found group specific expression patterns. While putative orthologs of the HvWRKY transcription factors have been inferred from phylogenetic sequence analysis, we performed a comparative expression analysis of WRKY genes in Arabidopsis and barley. Indeed, highly correlative expression profiles were found between some of the putative orthologs. HvWRKY genes have not only undergone radiation in monocot or dicot species, but exhibit evolutionary traits specific to grasses. HvWRKY proteins exhibited not only sequence similarities between orthologs with Arabidopsis, but also relatedness in their expression patterns. This correlative expression is indicative for a putative conserved function of related WRKY proteins in mono- and dicot species.

Morphological neural networks

Energy Technology Data Exchange (ETDEWEB)

Ritter, G.X.; Sussner, P. [Univ. of Florida, Gainesville, FL (United States)

1996-12-31

The theory of artificial neural networks has been successfully applied to a wide variety of pattern recognition problems. In this theory, the first step in computing the next state of a neuron or in performing the next layer neural network computation involves the linear operation of multiplying neural values by their synaptic strengths and adding the results. Thresholding usually follows the linear operation in order to provide for nonlinearity of the network. In this paper we introduce a novel class of neural networks, called morphological neural networks, in which the operations of multiplication and addition are replaced by addition and maximum (or minimum), respectively. By taking the maximum (or minimum) of sums instead of the sum of products, morphological network computation is nonlinear before thresholding. As a consequence, the properties of morphological neural networks are drastically different than those of traditional neural network models. In this paper we consider some of these differences and provide some particular examples of morphological neural network.

Diabetic retinopathy screening using deep neural network.

Science.gov (United States)

Ramachandran, Nishanthan; Hong, Sheng Chiong; Sime, Mary J; Wilson, Graham A

2017-09-07

There is a burgeoning interest in the use of deep neural network in diabetic retinal screening. To determine whether a deep neural network could satisfactorily detect diabetic retinopathy that requires referral to an ophthalmologist from a local diabetic retinal screening programme and an international database. Retrospective audit. Diabetic retinal photos from Otago database photographed during October 2016 (485 photos), and 1200 photos from Messidor international database. Receiver operating characteristic curve to illustrate the ability of a deep neural network to identify referable diabetic retinopathy (moderate or worse diabetic retinopathy or exudates within one disc diameter of the fovea). Area under the receiver operating characteristic curve, sensitivity and specificity. For detecting referable diabetic retinopathy, the deep neural network had an area under receiver operating characteristic curve of 0.901 (95% confidence interval 0.807-0.995), with 84.6% sensitivity and 79.7% specificity for Otago and 0.980 (95% confidence interval 0.973-0.986), with 96.0% sensitivity and 90.0% specificity for Messidor. This study has shown that a deep neural network can detect referable diabetic retinopathy with sensitivities and specificities close to or better than 80% from both an international and a domestic (New Zealand) database. We believe that deep neural networks can be integrated into community screening once they can successfully detect both diabetic retinopathy and diabetic macular oedema. © 2017 Royal Australian and New Zealand College of Ophthalmologists.

Involvement of a putative intercellular signal-recognizing G protein-coupled receptor in the engulfment of Salmonella by the protozoan Tetrahymena

Directory of Open Access Journals (Sweden)

P.N. Agbedanu

2013-07-01

Full Text Available In an effort to investigate the molecular basis of protozoa engulfment-mediated hypervirulence of Salmonella in cattle, we evaluated protozoan G protein-coupled receptors (GPCRs as transducers of Salmonella engulfment by the model protozoan Tetrahymena. Our laboratory previously demonstrated that non-pathogenic protozoa (including Tetrahymena engulf Salmonella and then exacerbate its virulence in cattle, but the mechanistic details of the phenomenon are not fully understood. GPCRs were investigated since these receptors facilitate phagocytosis of particulates by Tetrahymena, and a GPCR apparently modulates bacterial engulfment for the pathogenic protozoan Entamoeba histolytica. A database search identified three putative Tetrahymena GPCRs, based on sequence homologies and predicted transmembrane domains, that were the focus of this study. Salmonella engulfment by Tetrahymena was assessed in the presence of suramin, a non-specific GPCR inhibitor. Salmonella engulfment was also assessed in Tetrahymena in which expression of putative GPCRs was knocked-down using RNAi. A candidate GPCR was then expressed in a heterologous yeast expression system for further characterization. Our results revealed that Tetrahymena were less efficient at engulfing Salmonella in the presence of suramin. Engulfment was reduced concordantly with a reduction in the density of protozoa. RNAi-based studies revealed that knock-down of one the Tetrahymena GPCRs caused diminished engulfment of Salmonella. Tetrahymena lysates activated this receptor in the heterologous expression system. These data demonstrate that the Tetrahymena receptor is a putative GPCR that facilitates bacterial engulfment by Tetrahymena. Activation of the putative GPCR seemed to be related to protozoan cell density, suggesting that its cognate ligand is an intercellular signaling molecule.

Application of artificial neural network to identify nuclear materials

International Nuclear Information System (INIS)

Xu Peng; Wang Zhe; Li Tiantuo

2005-01-01

Applying the neutral network, the article studied the technology of identifying the gamma spectra of the nuclear material in the nuclear components. In the article, theory of the network identifying the spectra is described, and the results of identification of gamma spectra are given.(authors)

The neural basis of financial risk taking.

Science.gov (United States)

Kuhnen, Camelia M; Knutson, Brian

2005-09-01

Investors systematically deviate from rationality when making financial decisions, yet the mechanisms responsible for these deviations have not been identified. Using event-related fMRI, we examined whether anticipatory neural activity would predict optimal and suboptimal choices in a financial decision-making task. We characterized two types of deviations from the optimal investment strategy of a rational risk-neutral agent as risk-seeking mistakes and risk-aversion mistakes. Nucleus accumbens activation preceded risky choices as well as risk-seeking mistakes, while anterior insula activation preceded riskless choices as well as risk-aversion mistakes. These findings suggest that distinct neural circuits linked to anticipatory affect promote different types of financial choices and indicate that excessive activation of these circuits may lead to investing mistakes. Thus, consideration of anticipatory neural mechanisms may add predictive power to the rational actor model of economic decision making.

Deep Neural Network Detects Quantum Phase Transition

Science.gov (United States)

Arai, Shunta; Ohzeki, Masayuki; Tanaka, Kazuyuki

2018-03-01

We detect the quantum phase transition of a quantum many-body system by mapping the observed results of the quantum state onto a neural network. In the present study, we utilized the simplest case of a quantum many-body system, namely a one-dimensional chain of Ising spins with the transverse Ising model. We prepared several spin configurations, which were obtained using repeated observations of the model for a particular strength of the transverse field, as input data for the neural network. Although the proposed method can be employed using experimental observations of quantum many-body systems, we tested our technique with spin configurations generated by a quantum Monte Carlo simulation without initial relaxation. The neural network successfully identified the strength of transverse field only from the spin configurations, leading to consistent estimations of the critical point of our model Γc = J.

Patterns recognition of electric brain activity using artificial neural networks

Science.gov (United States)

Musatov, V. Yu.; Pchelintseva, S. V.; Runnova, A. E.; Hramov, A. E.

2017-04-01

An approach for the recognition of various cognitive processes in the brain activity in the perception of ambiguous images. On the basis of developed theoretical background and the experimental data, we propose a new classification of oscillating patterns in the human EEG by using an artificial neural network approach. After learning of the artificial neural network reliably identified cube recognition processes, for example, left-handed or right-oriented Necker cube with different intensity of their edges, construct an artificial neural network based on Perceptron architecture and demonstrate its effectiveness in the pattern recognition of the EEG in the experimental.

Particle identification with neural networks using a rotational invariant moment representation

International Nuclear Information System (INIS)

Sinkus, R.

1997-01-01

A feed-forward neural network is used to identify electromagnetic particles based upon their showering properties within a segmented calorimeter. The novel feature is the expansion of the energy distribution in terms of moments of the so-called Zernike functions which are invariant under rotation. The multidimensional input distribution for the neural network is transformed via a principle component analysis and rescaled by its respective variances to ensure input values of the order of one. This results is a better performance in identifying and separating electromagnetic from hadronic particles, especially at low energies. (orig.)

Pax7 lineage contributions to the mammalian neural crest.

Directory of Open Access Journals (Sweden)

Barbara Murdoch

Full Text Available Neural crest cells are vertebrate-specific multipotent cells that contribute to a variety of tissues including the peripheral nervous system, melanocytes, and craniofacial bones and cartilage. Abnormal development of the neural crest is associated with several human maladies including cleft/lip palate, aggressive cancers such as melanoma and neuroblastoma, and rare syndromes, like Waardenburg syndrome, a complex disorder involving hearing loss and pigment defects. We previously identified the transcription factor Pax7 as an early marker, and required component for neural crest development in chick embryos. In mammals, Pax7 is also thought to play a role in neural crest development, yet the precise contribution of Pax7 progenitors to the neural crest lineage has not been determined.Here we use Cre/loxP technology in double transgenic mice to fate map the Pax7 lineage in neural crest derivates. We find that Pax7 descendants contribute to multiple tissues including the cranial, cardiac and trunk neural crest, which in the cranial cartilage form a distinct regional pattern. The Pax7 lineage, like the Pax3 lineage, is additionally detected in some non-neural crest tissues, including a subset of the epithelial cells in specific organs.These results demonstrate a previously unappreciated widespread distribution of Pax7 descendants within and beyond the neural crest. They shed light regarding the regionally distinct phenotypes observed in Pax3 and Pax7 mutants, and provide a unique perspective into the potential roles of Pax7 during disease and development.

Replicable Expansion and Differentiation of Neural Precursors from Adult Canine Skin

Directory of Open Access Journals (Sweden)

Thomas Duncan

2017-08-01

Full Text Available Repopulation of brain circuits by neural precursors is a potential therapeutic strategy for neurodegenerative disorders; however, choice of cell is critical. Previously, we introduced a two-step culture system that generates a high yield of neural precursors from small samples of adult canine skin. Here, we probe their gene and protein expression profiles in comparison with dermal fibroblasts and brain-derived neural stem cells and characterize their neuronal potential. To date, we have produced >50 skin-derived neural precursor (SKN lines. SKNs can be cultured in a highly replicable fashion and uniformly express a panel of identifying markers. Upon differentiation, they self-upregulate neural specification genes, generating neurons with basic electrophysiological functionality. This unique population of neural precursors, derived from mature skin, overcomes many of the practical issues that have limited clinical translation of alternative cell types. Easily accessible, neuronally committed, and patient specific, SKNs may have potential for the treatment of brain disorders.

Putative Lineage of Novel African Usutu Virus, Central Europe

Centers for Disease Control (CDC) Podcasts

2015-10-15

Sarah Gregory reads an abridged version of "Putative Lineage of Novel African Usutu Virus, Central Europe.".  Created: 10/15/2015 by National Center for Emerging and Zoonotic Infectious Diseases (NCEZID).   Date Released: 10/15/2015.

Neural Based Orthogonal Data Fitting The EXIN Neural Networks

CERN Document Server

Cirrincione, Giansalvo

2008-01-01

Written by three leaders in the field of neural based algorithms, Neural Based Orthogonal Data Fitting proposes several neural networks, all endowed with a complete theory which not only explains their behavior, but also compares them with the existing neural and traditional algorithms. The algorithms are studied from different points of view, including: as a differential geometry problem, as a dynamic problem, as a stochastic problem, and as a numerical problem. All algorithms have also been analyzed on real time problems (large dimensional data matrices) and have shown accurate solutions. Wh

Iris double recognition based on modified evolutionary neural network

Science.gov (United States)

Liu, Shuai; Liu, Yuan-Ning; Zhu, Xiao-Dong; Huo, Guang; Liu, Wen-Tao; Feng, Jia-Kai

2017-11-01

Aiming at multicategory iris recognition under illumination and noise interference, this paper proposes a method of iris double recognition based on a modified evolutionary neural network. An equalization histogram and Laplace of Gaussian operator are used to process the iris to suppress illumination and noise interference and Haar wavelet to convert the iris feature to binary feature encoding. Calculate the Hamming distance for the test iris and template iris , and compare with classification threshold, determine the type of iris. If the iris cannot be identified as a different type, there needs to be a secondary recognition. The connection weights in back-propagation (BP) neural network use modified evolutionary neural network to adaptively train. The modified neural network is composed of particle swarm optimization with mutation operator and BP neural network. According to different iris libraries in different circumstances of experimental results, under illumination and noise interference, the correct recognition rate of this algorithm is higher, the ROC curve is closer to the coordinate axis, the training and recognition time is shorter, and the stability and the robustness are better.

Identification of generalized state transfer matrix using neural networks

International Nuclear Information System (INIS)

Zhu Changchun

2001-01-01

The research is introduced on identification of generalized state transfer matrix of linear time-invariant (LTI) system by use of neural networks based on LM (Levenberg-Marquart) algorithm. Firstly, the generalized state transfer matrix is defined. The relationship between the identification of state transfer matrix of structural dynamics and the identification of the weight matrix of neural networks has been established in theory. A singular layer neural network is adopted to obtain the structural parameters as a powerful tool that has parallel distributed processing ability and the property of adaptation or learning. The constraint condition of weight matrix of the neural network is deduced so that the learning and training of the designed network can be more effective. The identified neural network can be used to simulate the structural response excited by any other signals. In order to cope with its further application in practical problems, some noise (5% and 10%) is expected to be present in the response measurements. Results from computer simulation studies show that this method is valid and feasible

Comparative Analysis of Putative Orthologues of Mitochondrial Import Motor Subunit: Pam18 and Pam16 in Plants

OpenAIRE

Chen, Xuejin; Ghazanfar, Bushra; Khan, Abdul Rehman; Hayat, Sikandar; Cheng, Zhihui

2013-01-01

Pam18/Tim14 and Pam16/Tim16, highly conserved proteins among eukaryotes, are two essential subunits of protein import motors localized in the inner mitochondrial membrane. The heterodimer formed by Pam18 and Pam16 via their J-type domains serves a regulatory function in protein translocation. Here, we report that thirty-one Pam18 and twenty-six Pam16 putative orthologues in twelve plant species were identified and analyzed through bioinformatics strategy. Results data revealed that Pam18 and ...

Identifying temporal and causal contributions of neural processes underlying the Implicit Association Test (IAT

Directory of Open Access Journals (Sweden)

Chad Edward Forbes

2012-11-01

Full Text Available The Implicit Association Test (IAT is a popular behavioral measure that assesses the associative strength between outgroup members and stereotypical and counterstereotypical traits. Less is known, however, about the degree to which the IAT reflects automatic processing. Two studies examined automatic processing contributions to a gender-IAT using a data driven, social neuroscience approach. Performance on congruent (e.g., categorizing male names with synonyms of strength and incongruent (e.g., categorizing female names with synonyms of strength IAT blocks were separately analyzed using EEG (event-related potentials, or ERPs, and coherence; Study 1 and lesion (Study 2 methodologies. Compared to incongruent blocks, performance on congruent IAT blocks was associated with more positive ERPs that manifested in frontal and occipital regions at automatic processing speeds, occipital regions at more controlled processing speeds and was compromised by volume loss in the anterior temporal lobe, insula and medial PFC. Performance on incongruent blocks was associated with volume loss in supplementary motor areas, cingulate gyrus and a region in medial PFC similar to that found for congruent blocks. Greater coherence was found between frontal and occipital regions to the extent individuals exhibited more bias. This suggests there are separable neural contributions to congruent and incongruent blocks of the IAT but there is also a surprising amount of overlap. Given the temporal and regional neural distinctions, these results provide converging evidence that stereotypic associative strength assessed by the IAT indexes automatic processing to a degree.

Molecular cloning and characterization of a putative OGG_N domain ...

African Journals Online (AJOL)

Molecular cloning and characterization of a putative OGG_N domain from the camel, Camelus dromedarius. Farid Shokry Ataya, Mohammad Saud Alanazi, Dalia Fouad, Hehsam Mahmoud Saeed, Mohammad Bazzi ...

Applications of neural networks in training science.

Science.gov (United States)

Pfeiffer, Mark; Hohmann, Andreas

2012-04-01

Training science views itself as an integrated and applied science, developing practical measures founded on scientific method. Therefore, it demands consideration of a wide spectrum of approaches and methods. Especially in the field of competitive sports, research questions are usually located in complex environments, so that mainly field studies are drawn upon to obtain broad external validity. Here, the interrelations between different variables or variable sets are mostly of a nonlinear character. In these cases, methods like neural networks, e.g., the pattern recognizing methods of Self-Organizing Kohonen Feature Maps or similar instruments to identify interactions might be successfully applied to analyze data. Following on from a classification of data analysis methods in training-science research, the aim of the contribution is to give examples of varied sports in which network approaches can be effectually used in training science. First, two examples are given in which neural networks are employed for pattern recognition. While one investigation deals with the detection of sporting talent in swimming, the other is located in game sports research, identifying tactical patterns in team handball. The third and last example shows how an artificial neural network can be used to predict competitive performance in swimming. Copyright © 2011 Elsevier B.V. All rights reserved.

Molecular annotation of integrative feeding neural circuits.

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Pérez, Cristian A; Stanley, Sarah A; Wysocki, Robert W; Havranova, Jana; Ahrens-Nicklas, Rebecca; Onyimba, Frances; Friedman, Jeffrey M

2011-02-02

The identity of higher-order neurons and circuits playing an associative role to control feeding is unknown. We injected pseudorabies virus, a retrograde tracer, into masseter muscle, salivary gland, and tongue of BAC-transgenic mice expressing GFP in specific neural populations and identified several CNS regions that project multisynaptically to the periphery. MCH and orexin neurons were identified in the lateral hypothalamus, and Nurr1 and Cnr1 in the amygdala and insular/rhinal cortices. Cholera toxin β tracing showed that insular Nurr1(+) and Cnr1(+) neurons project to the amygdala or lateral hypothalamus, respectively. Finally, we show that cortical Cnr1(+) neurons show increased Cnr1 mRNA and c-Fos expression after fasting, consistent with a possible role for Cnr1(+) neurons in feeding. Overall, these studies define a general approach for identifying specific molecular markers for neurons in complex neural circuits. These markers now provide a means for functional studies of specific neuronal populations in feeding or other complex behaviors. Copyright © 2011 Elsevier Inc. All rights reserved.

The neural optimal control hierarchy for motor control

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DeWolf, T.; Eliasmith, C.

2011-10-01

Our empirical, neuroscientific understanding of biological motor systems has been rapidly growing in recent years. However, this understanding has not been systematically mapped to a quantitative characterization of motor control based in control theory. Here, we attempt to bridge this gap by describing the neural optimal control hierarchy (NOCH), which can serve as a foundation for biologically plausible models of neural motor control. The NOCH has been constructed by taking recent control theoretic models of motor control, analyzing the required processes, generating neurally plausible equivalent calculations and mapping them on to the neural structures that have been empirically identified to form the anatomical basis of motor control. We demonstrate the utility of the NOCH by constructing a simple model based on the identified principles and testing it in two ways. First, we perturb specific anatomical elements of the model and compare the resulting motor behavior with clinical data in which the corresponding area of the brain has been damaged. We show that damaging the assigned functions of the basal ganglia and cerebellum can cause the movement deficiencies seen in patients with Huntington's disease and cerebellar lesions. Second, we demonstrate that single spiking neuron data from our model's motor cortical areas explain major features of single-cell responses recorded from the same primate areas. We suggest that together these results show how NOCH-based models can be used to unify a broad range of data relevant to biological motor control in a quantitative, control theoretic framework.

The Putative Chemosignal Androstadienone Makes Women More Generous.

Science.gov (United States)

Perrotta, Valentina; Graffeo, Michele; Bonini, Nicolao; Gottfried, Jay A

2016-06-01

Putative human chemosignals have been shown to influence mood states and emotional processing, but the connection between these effects and higher-order cognitive processing is not well established. This study utilized an economic game (Dictator Game) to test whether androstadienone (AND), an odorous compound derived from testosterone, impacts on altruistic behavior. We predicted that the female participants would act more generously in the AND condition, exhibiting a significant interaction effect between gender and AND on Dictator Game contributions. We also expected that the presence of AND should increase the positive mood of the female participants, compared to a control odor condition and also compared to the mood of the male participants. The results confirm our hypotheses: for women the subliminal perception of AND led to larger monetary donations, compared to a control odor, and also increased positive mood. These effects were absent or significantly weaker in men. Our findings highlight the capacity of human putative chemosignals to influence emotions and higher cognitive processes - in particular the processes used in the context of economic decisions - in a gender-specific way.

Characteristics of functional enrichment and gene expression level of human putative transcriptional target genes.

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Osato, Naoki

2018-01-19

Transcriptional target genes show functional enrichment of genes. However, how many and how significantly transcriptional target genes include functional enrichments are still unclear. To address these issues, I predicted human transcriptional target genes using open chromatin regions, ChIP-seq data and DNA binding sequences of transcription factors in databases, and examined functional enrichment and gene expression level of putative transcriptional target genes. Gene Ontology annotations showed four times larger numbers of functional enrichments in putative transcriptional target genes than gene expression information alone, independent of transcriptional target genes. To compare the number of functional enrichments of putative transcriptional target genes between cells or search conditions, I normalized the number of functional enrichment by calculating its ratios in the total number of transcriptional target genes. With this analysis, native putative transcriptional target genes showed the largest normalized number of functional enrichments, compared with target genes including 5-60% of randomly selected genes. The normalized number of functional enrichments was changed according to the criteria of enhancer-promoter interactions such as distance from transcriptional start sites and orientation of CTCF-binding sites. Forward-reverse orientation of CTCF-binding sites showed significantly higher normalized number of functional enrichments than the other orientations. Journal papers showed that the top five frequent functional enrichments were related to the cellular functions in the three cell types. The median expression level of transcriptional target genes changed according to the criteria of enhancer-promoter assignments (i.e. interactions) and was correlated with the changes of the normalized number of functional enrichments of transcriptional target genes. Human putative transcriptional target genes showed significant functional enrichments. Functional

From sensation to perception: Using multivariate classification of visual illusions to identify neural correlates of conscious awareness in space and time.

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Hogendoorn, Hinze

2015-01-01

An important goal of cognitive neuroscience is understanding the neural underpinnings of conscious awareness. Although the low-level processing of sensory input is well understood in most modalities, it remains a challenge to understand how the brain translates such input into conscious awareness. Here, I argue that the application of multivariate pattern classification techniques to neuroimaging data acquired while observers experience perceptual illusions provides a unique way to dissociate sensory mechanisms from mechanisms underlying conscious awareness. Using this approach, it is possible to directly compare patterns of neural activity that correspond to the contents of awareness, independent from changes in sensory input, and to track these neural representations over time at high temporal resolution. I highlight five recent studies using this approach, and provide practical considerations and limitations for future implementations.

An evaluation of neural networks for identification of system parameters in reactor noise signals

International Nuclear Information System (INIS)

Miller, L.F.

1991-01-01

Several backpropagation neural networks for identifying fundamental mode eigenvalues were evaluated. The networks were trained and tested on analytical data and on results from other numerical methods. They were then used to predict first mode break frequencies for noise data from several sources. These predictions were, in turn, compared with analytical values and with results from alternative methods. Comparisons of results for some data sets suggest that the accuracy of predictions from neural networks are essentially equivalent to results from conventional methods while other evaluations indicate that either method may be superior. Experience gained from these numerical experiments provide insight for improving the performance of neural networks relative to other methods for identifying parameters associated with experimental data. Neural networks may also be used in support of conventional algorithms by providing starting points for nonlinear minimization algorithms

Forecasting Flare Activity Using Deep Convolutional Neural Networks

Science.gov (United States)

Hernandez, T.

2017-12-01

Current operational flare forecasting relies on human morphological analysis of active regions and the persistence of solar flare activity through time (i.e. that the Sun will continue to do what it is doing right now: flaring or remaining calm). In this talk we present the results of applying deep Convolutional Neural Networks (CNNs) to the problem of solar flare forecasting. CNNs operate by training a set of tunable spatial filters that, in combination with neural layer interconnectivity, allow CNNs to automatically identify significant spatial structures predictive for classification and regression problems. We will start by discussing the applicability and success rate of the approach, the advantages it has over non-automated forecasts, and how mining our trained neural network provides a fresh look into the mechanisms behind magnetic energy storage and release.

Tinnitus and neural plasticity of the brain

NARCIS (Netherlands)

Bartels, Hilke; Staal, Michiel J.; Albers, Frans W. J.

Objective: To describe the current ideas about the manifestations of neural plasticity in generating tinnitus. Data Sources: Recently published source articles were identified using MEDLINE, PubMed, and Cochrane Library according to the key words mentioned below. Study Selection: Review articles and

Complete Genome Sequence of Diaphorina citri-associated C virus, a Novel Putative RNA Virus of the Asian Citrus Psyllid, Diaphorina citri

OpenAIRE

Nouri, Shahideh; Salem, Nid?; Falk, Bryce W.

2016-01-01

We present here the complete nucleotide sequence and genome organization of a novel putative RNA virus identified in field populations of the Asian citrus psyllid, Diaphorina citri, through sequencing of the transcriptome followed by reverse transcription-PCR (RT-PCR). We tentatively named this virus Diaphorina citri-associated C virus (DcACV). DcACV is an unclassified positive-sense RNA virus.

Search strings for the study of putative occupational determinants of disease

Science.gov (United States)

Mattioli, Stefano; Zanardi, Francesca; Baldasseroni, Alberto; Schaafsma, Frederieke; Cooke, Robin MT; Mancini, Gianpiero; Fierro, Mauro; Santangelo, Chiara; Farioli, Andrea; Fucksia, Serenella; Curti, Stefania; Verbeek, Jos

2010-01-01

Objective To identify efficient PubMed search strategies to retrieve articles regarding putative occupational determinants of conditions not generally considered to be work related. Methods Based on MeSH definitions and expert knowledge, we selected as candidate search terms the four MeSH terms describing ‘occupational disease’, ‘occupational exposure’, ‘occupational health’ and ‘occupational medicine’ (DEHM) alongside 22 other promising terms. We first explored overlaps between the candidate terms in PubMed. Using random samples of abstracts retrieved by each term, we estimated the proportions of articles containing potentially pertinent information regarding occupational aetiology in order to formulate two search strategies (one more ‘specific’, one more ‘sensitive’). We applied these strategies to retrieve information on the possible occupational aetiology of meningioma, pancreatitis and atrial fibrillation. Results Only 20.3% of abstracts were retrieved by more than one DEHM term. The more ‘specific’ search string was based on the combination of terms that yielded the highest proportion (40%) of potentially pertinent abstracts. The more ‘sensitive’ string was based on the use of broader search fields and additional coverage provided by other search terms under study. Using the specific string, the numbers of abstracts needed to read to find one potentially pertinent article were 1.2 for meningioma, 1.9 for pancreatitis and 1.8 for atrial fibrillation. Using the sensitive strategy, the numbers needed to read were 4.4 for meningioma, 8.9 for pancreatitis and 10.5 for atrial fibrillation. Conclusions The proposed strings could help health care professionals explore putative occupational aetiology for diseases that are not generally thought to be work related. PMID:19819858

Design and Implementation of Behavior Recognition System Based on Convolutional Neural Network

Directory of Open Access Journals (Sweden)

Yu Bo

2017-01-01

Full Text Available We build a set of human behavior recognition system based on the convolution neural network constructed for the specific human behavior in public places. Firstly, video of human behavior data set will be segmented into images, then we process the images by the method of background subtraction to extract moving foreground characters of body. Secondly, the training data sets are trained into the designed convolution neural network, and the depth learning network is constructed by stochastic gradient descent. Finally, the various behaviors of samples are classified and identified with the obtained network model, and the recognition results are compared with the current mainstream methods. The result show that the convolution neural network can study human behavior model automatically and identify human’s behaviors without any manually annotated trainings.

Neural networks

International Nuclear Information System (INIS)

Denby, Bruce; Lindsey, Clark; Lyons, Louis

1992-01-01

The 1980s saw a tremendous renewal of interest in 'neural' information processing systems, or 'artificial neural networks', among computer scientists and computational biologists studying cognition. Since then, the growth of interest in neural networks in high energy physics, fueled by the need for new information processing technologies for the next generation of high energy proton colliders, can only be described as explosive

Neural correlates of the food/non-food visual distinction.

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Tsourides, Kleovoulos; Shariat, Shahriar; Nejati, Hossein; Gandhi, Tapan K; Cardinaux, Annie; Simons, Christopher T; Cheung, Ngai-Man; Pavlovic, Vladimir; Sinha, Pawan

2016-03-01

An evolutionarily ancient skill we possess is the ability to distinguish between food and non-food. Our goal here is to identify the neural correlates of visually driven 'edible-inedible' perceptual distinction. We also investigate correlates of the finer-grained likability assessment. Our stimuli depicted food or non-food items with sub-classes of appealing or unappealing exemplars. Using data-classification techniques drawn from machine-learning, as well as evoked-response analyses, we sought to determine whether these four classes of stimuli could be distinguished based on the patterns of brain activity they elicited. Subjects viewed 200 images while in a MEG scanner. Our analyses yielded two successes and a surprising failure. The food/non-food distinction had a robust neural counterpart and emerged as early as 85 ms post-stimulus onset. The likable/non-likable distinction too was evident in the neural signals when food and non-food stimuli were grouped together, or when only the non-food stimuli were included in the analyses. However, we were unable to identify any neural correlates of this distinction when limiting the analyses only to food stimuli. Taken together, these positive and negative results further our understanding of the substrates of a set of ecologically important judgments and have clinical implications for conditions like eating-disorders and anhedonia. Copyright © 2016 Elsevier B.V. All rights reserved.

Information processing in micro and meso-scale neural circuits during normal and disease states

Science.gov (United States)

Luongo, Francisco

Neural computation can occur at multiple spatial and temporal timescales. The sum total of all of these processes is to guide optimal behaviors within the context of the constraints imposed by the physical world. How the circuits of the brain achieves this goal represents a central question in systems neuroscience. Here I explore the many ways in which the circuits of the brain can process information at both the micro and meso scale. Understanding the way information is represented and processed in the brain could shed light on the neuropathology underlying complex neuropsychiatric diseases such as autism and schizophrenia. Chapter 2 establishes an experimental paradigm for assaying patterns of microcircuit activity and examines the role of dopaminergic modulation on prefrontal microcircuits. We find that dopamine type 2 (D2) receptor activation results in an increase in spontaneous activity while dopamine type 1 (D1) activation does not. Chapter 3 of this dissertation presents a study that illustrates how cholingergic activation normally produces what has been suggested as a neural substrate of attention; pairwise decorrelation in microcircuit activity. This study also shows that in two etiologicall distinct mouse models of autism, FMR1 knockout mice and Valproic Acid exposed mice, this ability to decorrelate in the presence of cholinergic activation is lost. This represents a putative microcircuit level biomarker of autism. Chapter 4 examines the structure/function relationship within the prefrontal microcircuit. Spontaneous activity in prefrontal microcircuits is shown to be organized according to a small world architecture. Interestingly, this architecture is important for one concrete function of neuronal microcircuits; the ability to produce temporally stereotyped patterns of activation. In the final chapter, we identify subnetworks in chronic intracranial electrocorticographic (ECoG) recordings using pairwise electrode coherence and dimensionality reduction

Genomic characterization of putative allergen genes in peach/almond and their synteny with apple

Science.gov (United States)

Chen, Lin; Zhang, Shuiming; Illa, Eudald; Song, Lijuan; Wu, Shandong; Howad, Werner; Arús, Pere; Weg, Eric van de; Chen, Kunsong; Gao, Zhongshan

2008-01-01

Background Fruits from several species of the Rosaceae family are reported to cause allergic reactions in certain populations. The allergens identified belong to mainly four protein families: pathogenesis related 10 proteins, thaumatin-like proteins, lipid transfer proteins and profilins. These families of putative allergen genes in apple (Mal d 1 to 4) have been mapped on linkage maps and subsequent genetic study on allelic diversity and hypoallergenic traits has been carried out recently. In peach (Prunus persica), these allergen gene families are denoted as Pru p 1 to 4 and for almond (Prunus dulcis)Pru du 1 to 4. Genetic analysis using current molecular tools may be helpful to establish the cause of allergenicity differences observed among different peach cultivars. This study was to characterize putative peach allergen genes for their genomic sequences and linkage map positions, and to compare them with previously characterized homologous genes in apple (Malus domestica). Results Eight Pru p/du 1 genes were identified, four of which were new. All the Pru p/du 1 genes were mapped in a single bin on the top of linkage group 1 (G1). Five Pru p/du 2 genes were mapped on four different linkage groups, two very similar Pru p/du 2.01 genes (A and B) were on G3, Pru p/du 2.02 on G7,Pru p/du 2.03 on G8 and Pru p/du 2.04 on G1. There were differences in the intron and exon structure in these Pru p/du 2 genes and in their amino acid composition. Three Pru p/du 3 genes (3.01–3.03) containing an intron and a mini exon of 10 nt were mapped in a cluster on G6. Two Pru p/du 4 genes (Pru p/du 4.01 and 4.02) were located on G1 and G7, respectively. The Pru p/du 1 cluster on G1 aligned to the Mal d 1 clusters on LG16; Pru p/du 2.01A and B on G3 to Mal d 2.01A and B on LG9; the Pru p/du 3 cluster on G6 to Mal d 3.01 on LG12; Pru p/du 4.01 on G1 to Mal d 4.03 on LG2; and Pru p/du 4.02 on G7 to Mal d 4.02 on LG2. Conclusion A total of 18 putative peach/almond allergen genes have

Genomic characterization of putative allergen genes in peach/almond and their synteny with apple

Directory of Open Access Journals (Sweden)

Weg Eric

2008-11-01

Full Text Available Abstract Background Fruits from several species of the Rosaceae family are reported to cause allergic reactions in certain populations. The allergens identified belong to mainly four protein families: pathogenesis related 10 proteins, thaumatin-like proteins, lipid transfer proteins and profilins. These families of putative allergen genes in apple (Mal d 1 to 4 have been mapped on linkage maps and subsequent genetic study on allelic diversity and hypoallergenic traits has been carried out recently. In peach (Prunus persica, these allergen gene families are denoted as Pru p 1 to 4 and for almond (Prunus dulcisPru du 1 to 4. Genetic analysis using current molecular tools may be helpful to establish the cause of allergenicity differences observed among different peach cultivars. This study was to characterize putative peach allergen genes for their genomic sequences and linkage map positions, and to compare them with previously characterized homologous genes in apple (Malus domestica. Results Eight Pru p/du 1 genes were identified, four of which were new. All the Pru p/du 1 genes were mapped in a single bin on the top of linkage group 1 (G1. Five Pru p/du 2 genes were mapped on four different linkage groups, two very similar Pru p/du 2.01 genes (A and B were on G3, Pru p/du 2.02 on G7,Pru p/du 2.03 on G8 and Pru p/du 2.04 on G1. There were differences in the intron and exon structure in these Pru p/du 2 genes and in their amino acid composition. Three Pru p/du 3 genes (3.01–3.03 containing an intron and a mini exon of 10 nt were mapped in a cluster on G6. Two Pru p/du 4 genes (Pru p/du 4.01 and 4.02 were located on G1 and G7, respectively. The Pru p/du 1 cluster on G1 aligned to the Mal d 1 clusters on LG16; Pru p/du 2.01A and B on G3 to Mal d 2.01A and B on LG9; the Pru p/du 3 cluster on G6 to Mal d 3.01 on LG12; Pru p/du 4.01 on G1 to Mal d 4.03 on LG2; and Pru p/du 4.02 on G7 to Mal d 4.02 on LG2. Conclusion A total of 18 putative peach

Identifying phenomenal consciousness.

Science.gov (United States)

Schier, Elizabeth

2009-03-01

This paper examines the possibility of finding evidence that phenomenal consciousness is independent of access. The suggestion reviewed is that we should look for isomorphisms between phenomenal and neural activation spaces. It is argued that the fact that phenomenal spaces are mapped via verbal report is no problem for this methodology. The fact that activation and phenomenal space are mapped via different means does not mean that they cannot be identified. The paper finishes by examining how data addressing this theoretical question could be obtained.

In Vivo Recording of Neural and Behavioral Correlates of Anesthesia Induction, Reversal, and Euthanasia in Cephalopod Molluscs

Directory of Open Access Journals (Sweden)

Hanna M. Butler-Struben

2018-02-01

Full Text Available Cephalopod molluscs are among the most behaviorally and neurologically complex invertebrates. As they are now included in research animal welfare regulations in many countries, humane and effective anesthesia is required during invasive procedures. However, currently there is no evidence that agents believed to act as anesthetics produce effects beyond immobility. In this study we demonstrate, for the first time, that two of the most commonly used agents in cephalopod general anesthesia, magnesium chloride and ethanol, are capable of producing strong and reversible blockade of afferent and efferent neural signal; thus they are genuine anesthetics, rather than simply sedating agents that render animals immobile but not insensible. Additionally, we demonstrate that injected magnesium chloride and lidocaine are effective local anesthetic agents. This represents a considerable advance for cephalopod welfare. Using a reversible, minimally invasive recording procedure, we measured activity in the pallial nerve of cuttlefish (Sepia bandensis and octopus (Abdopus aculeatus, Octopus bocki, during induction and reversal for five putative general anesthetic and two local anesthetic agents. We describe the temporal relationship between loss of behavioral responses (immobility, loss of efferent neural signal (loss of “consciousness” and loss of afferent neural signal (anesthesia for general anesthesia, and loss of afferent signal for local anesthesia. Both ethanol and magnesium chloride were effective as bath-applied general anesthetics, causing immobility, complete loss of behavioral responsiveness and complete loss of afferent and efferent neural signal. Cold seawater, diethyl ether, and MS-222 (tricaine were ineffective. Subcutaneous injection of either lidocaine or magnesium chloride blocked behavioral and neural responses to pinch in the injected area, and we conclude that both are effective local anesthetic agents for cephalopods. Lastly, we

In Vivo Recording of Neural and Behavioral Correlates of Anesthesia Induction, Reversal, and Euthanasia in Cephalopod Molluscs.

Science.gov (United States)

Butler-Struben, Hanna M; Brophy, Samantha M; Johnson, Nasira A; Crook, Robyn J

2018-01-01

Cephalopod molluscs are among the most behaviorally and neurologically complex invertebrates. As they are now included in research animal welfare regulations in many countries, humane and effective anesthesia is required during invasive procedures. However, currently there is no evidence that agents believed to act as anesthetics produce effects beyond immobility. In this study we demonstrate, for the first time, that two of the most commonly used agents in cephalopod general anesthesia, magnesium chloride and ethanol, are capable of producing strong and reversible blockade of afferent and efferent neural signal; thus they are genuine anesthetics, rather than simply sedating agents that render animals immobile but not insensible. Additionally, we demonstrate that injected magnesium chloride and lidocaine are effective local anesthetic agents. This represents a considerable advance for cephalopod welfare. Using a reversible, minimally invasive recording procedure, we measured activity in the pallial nerve of cuttlefish ( Sepia bandensis ) and octopus ( Abdopus aculeatus, Octopus bocki ), during induction and reversal for five putative general anesthetic and two local anesthetic agents. We describe the temporal relationship between loss of behavioral responses (immobility), loss of efferent neural signal (loss of "consciousness") and loss of afferent neural signal (anesthesia) for general anesthesia, and loss of afferent signal for local anesthesia. Both ethanol and magnesium chloride were effective as bath-applied general anesthetics, causing immobility, complete loss of behavioral responsiveness and complete loss of afferent and efferent neural signal. Cold seawater, diethyl ether, and MS-222 (tricaine) were ineffective. Subcutaneous injection of either lidocaine or magnesium chloride blocked behavioral and neural responses to pinch in the injected area, and we conclude that both are effective local anesthetic agents for cephalopods. Lastly, we demonstrate that a

Anomaly detection in an automated safeguards system using neural networks

International Nuclear Information System (INIS)

Whiteson, R.; Howell, J.A.

1992-01-01

An automated safeguards system must be able to detect an anomalous event, identify the nature of the event, and recommend a corrective action. Neural networks represent a new way of thinking about basic computational mechanisms for intelligent information processing. In this paper, we discuss the issues involved in applying a neural network model to the first step of this process: anomaly detection in materials accounting systems. We extend our previous model to a 3-tank problem and compare different neural network architectures and algorithms. We evaluate the computational difficulties in training neural networks and explore how certain design principles affect the problems. The issues involved in building a neural network architecture include how the information flows, how the network is trained, how the neurons in a network are connected, how the neurons process information, and how the connections between neurons are modified. Our approach is based on the demonstrated ability of neural networks to model complex, nonlinear, real-time processes. By modeling the normal behavior of the processes, we can predict how a system should be behaving and, therefore, detect when an abnormality occurs

Hybrid Neural Network Approach Based Tool for the Modelling of Photovoltaic Panels

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Antonino Laudani

2015-01-01

Full Text Available A hybrid neural network approach based tool for identifying the photovoltaic one-diode model is presented. The generalization capabilities of neural networks are used together with the robustness of the reduced form of one-diode model. Indeed, from the studies performed by the authors and the works present in the literature, it was found that a direct computation of the five parameters via multiple inputs and multiple outputs neural network is a very difficult task. The reduced form consists in a series of explicit formulae for the support to the neural network that, in our case, is aimed at predicting just two parameters among the five ones identifying the model: the other three parameters are computed by reduced form. The present hybrid approach is efficient from the computational cost point of view and accurate in the estimation of the five parameters. It constitutes a complete and extremely easy tool suitable to be implemented in a microcontroller based architecture. Validations are made on about 10000 PV panels belonging to the California Energy Commission database.

A common neural code for perceived and inferred emotion.

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Skerry, Amy E; Saxe, Rebecca

2014-11-26

Although the emotions of other people can often be perceived from overt reactions (e.g., facial or vocal expressions), they can also be inferred from situational information in the absence of observable expressions. How does the human brain make use of these diverse forms of evidence to generate a common representation of a target's emotional state? In the present research, we identify neural patterns that correspond to emotions inferred from contextual information and find that these patterns generalize across different cues from which an emotion can be attributed. Specifically, we use functional neuroimaging to measure neural responses to dynamic facial expressions with positive and negative valence and to short animations in which the valence of a character's emotion could be identified only from the situation. Using multivoxel pattern analysis, we test for regions that contain information about the target's emotional state, identifying representations specific to a single stimulus type and representations that generalize across stimulus types. In regions of medial prefrontal cortex (MPFC), a classifier trained to discriminate emotional valence for one stimulus (e.g., animated situations) could successfully discriminate valence for the remaining stimulus (e.g., facial expressions), indicating a representation of valence that abstracts away from perceptual features and generalizes across different forms of evidence. Moreover, in a subregion of MPFC, this neural representation generalized to trials involving subjectively experienced emotional events, suggesting partial overlap in neural responses to attributed and experienced emotions. These data provide a step toward understanding how the brain transforms stimulus-bound inputs into abstract representations of emotion. Copyright © 2014 the authors 0270-6474/14/3315997-12$15.00/0.

A Neural Signature Encoding Decisions under Perceptual Ambiguity.

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Sun, Sai; Yu, Rongjun; Wang, Shuo

2017-01-01

People often make perceptual decisions with ambiguous information, but it remains unclear whether the brain has a common neural substrate that encodes various forms of perceptual ambiguity. Here, we used three types of perceptually ambiguous stimuli as well as task instructions to examine the neural basis for both stimulus-driven and task-driven perceptual ambiguity. We identified a neural signature, the late positive potential (LPP), that encoded a general form of stimulus-driven perceptual ambiguity. In addition to stimulus-driven ambiguity, the LPP was also modulated by ambiguity in task instructions. To further specify the functional role of the LPP and elucidate the relationship between stimulus ambiguity, behavioral response, and the LPP, we employed regression models and found that the LPP was specifically associated with response latency and confidence rating, suggesting that the LPP encoded decisions under perceptual ambiguity. Finally, direct behavioral ratings of stimulus and task ambiguity confirmed our neurophysiological findings, which could not be attributed to differences in eye movements either. Together, our findings argue for a common neural signature that encodes decisions under perceptual ambiguity but is subject to the modulation of task ambiguity. Our results represent an essential first step toward a complete neural understanding of human perceptual decision making.

Development of nuclear power plant diagnosis technique using neural networks

International Nuclear Information System (INIS)

Horiguchi, Masahiro; Fukawa, Naohiro; Nishimura, Kazuo

1991-01-01

A nuclear power plant diagnosis technique has been developed, called transient phenomena analysis, which employs neural network. The neural networks identify malfunctioning equipment by recognizing the pattern of main plant parameters, making it possible to locate the cause of an abnormality when a plant is in a transient state. In a case where some piece of equipment shows abnormal behavior, many plant parameters either directly or indirectly related to that equipment change simultaneously. When an abrupt change in a plant parameter is detected, changes in the 49 main plant parameters are classified into three types and a characteristic change pattern consisting of 49 data is defined. The neural networks then judge the cause of the abnormality from this pattern. This neural-network-based technique can recognize 100 patterns that are characterized by the causes of plant abnormality. (author)

High-Throughput Screening to Identify Compounds That Increase Fragile X Mental Retardation Protein Expression in Neural Stem Cells Differentiated From Fragile X Syndrome Patient-Derived Induced Pluripotent Stem Cells.

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Kumari, Daman; Swaroop, Manju; Southall, Noel; Huang, Wenwei; Zheng, Wei; Usdin, Karen

2015-07-01

: Fragile X syndrome (FXS), the most common form of inherited cognitive disability, is caused by a deficiency of the fragile X mental retardation protein (FMRP). In most patients, the absence of FMRP is due to an aberrant transcriptional silencing of the fragile X mental retardation 1 (FMR1) gene. FXS has no cure, and the available treatments only provide symptomatic relief. Given that FMR1 gene silencing in FXS patient cells can be partially reversed by treatment with compounds that target repressive epigenetic marks, restoring FMRP expression could be one approach for the treatment of FXS. We describe a homogeneous and highly sensitive time-resolved fluorescence resonance energy transfer assay for FMRP detection in a 1,536-well plate format. Using neural stem cells differentiated from an FXS patient-derived induced pluripotent stem cell (iPSC) line that does not express any FMRP, we screened a collection of approximately 5,000 known tool compounds and approved drugs using this FMRP assay and identified 6 compounds that modestly increase FMR1 gene expression in FXS patient cells. Although none of these compounds resulted in clinically relevant levels of FMR1 mRNA, our data provide proof of principle that this assay combined with FXS patient-derived neural stem cells can be used in a high-throughput format to identify better lead compounds for FXS drug development. In this study, a specific and sensitive fluorescence resonance energy transfer-based assay for fragile X mental retardation protein detection was developed and optimized for high-throughput screening (HTS) of compound libraries using fragile X syndrome (FXS) patient-derived neural stem cells. The data suggest that this HTS format will be useful for the identification of better lead compounds for developing new therapeutics for FXS. This assay can also be adapted for FMRP detection in clinical and research settings. ©AlphaMed Press.

Application of artificial neural network for medical image recognition and diagnostic decision making

International Nuclear Information System (INIS)

Asada, N.; Eiho, S.; Doi, K.; MacMahon, H.; Montner, S.M.; Giger, M.L.

1989-01-01

An artificial neural network has been applied for pattern recognition and used as a tool in an expert system. The purpose of this study is to examine the potential usefulness of the neural network approach in medical applications for image recognition and decision making. The authors designed multilayer feedforward neural networks with a back-propagation algorithm for our study. Using first-pass radionuclide ventriculograms, we attempted to identify the right and left ventricles of the heart and the lungs by training the neural network from patterns of time-activity curves. In a preliminary study, the neural network enabled identification of the lungs and heart chambers once the network was trained sufficiently by means of repeated entries of data from the same case

Exploring universal partnerships and putative marriages as tools for ...

African Journals Online (AJOL)

Following upon the Supreme Court of Appeal's judgment in Butters v Mncora 2012 4 SA 1 (SCA), which broadened the criteria and consequences of universal partnerships in cohabitation relationships, this article investigates the potential of universal partnerships and putative marriages to allocate rights to share in ...

A new putative deltapartitivirus recovered from Dianthus amurensis.

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An, Hongliu; Tan, Guanlin; Xiong, Guihong; Li, Meirong; Fang, Shouguo; Islam, Saif Ul; Zhang, Songbai; Li, Fan

2017-09-01

Two double stranded RNAs (dsRNA), likely representing the genome of a novel deltapartitivirus, provisionally named carnation cryptic virus 3 (CCV3), were recovered from Dianthus amurensis. The two dsRNAs were 1,573 (dsRNA1) and 1,561 (dsRNA2) bp in size, each containing a single open reading frame (ORF) encoding a 475- and 411-aa protein, respectively. The 475-aa protein contains a conserved RNA dependent RNA polymerase (RdRp) domain which shows significant homology to RdRps of established or putative partitiviruses, particularly those belonging to the genus Deltapartitivirus. However, it shares an amino acid identity of 75% with its closest relative, the RdRp of the deltapartitivirus beet cryptic virus 2 (BCV2), and is <62% identical to the RdRps of other partitiviruses. In a phylogenetic tree constructed with RdRps of selected partitiviruses, CCV3 clustered with BCV2 and formed a well-supported monophyletic clade with known or putative deltapartitiviruses.

Putative chemosensory receptors of the codling moth, Cydia pomonella, identified by antennal transcriptome analysis.

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Jonas M Bengtsson

Full Text Available The codling moth, Cydia pomonella, is an important fruit pest worldwide. As nocturnal animals, adults depend to a large extent on olfactory cues for detection of food and mates, and, for females, oviposition sites. In insects, odor detection is mediated by odorant receptors (ORs and ionotropic receptors (IRs, which ensure the specificity of the olfactory sensory neuron responses. In this study, our aim was to identify chemosensory receptors in the codling moth as a means to uncover new targets for behavioral interference. Using next-generation sequencing techniques, we identified a total of 43 candidate ORs, one gustatory receptor and 15 IRs in the antennal transcriptome. Through Blast and sequence similarity analyses we annotated the insect obligatory co-receptor ORco, five genes clustering in a conserved clade containing sex pheromone receptors, one homolog of the Bombyx mori female-enriched receptor BmorOR30 (but no homologs of the other B. mori female-enriched receptors and one gene clustering in the sugar receptor family. Among the candidate IRs, we identified homologs of the two highly conserved co-receptors IR8a and IR25a, and one homolog of an IR involved in phenylethyl amine detection in Drosophila. Our results open for functional characterization of the chemosensory receptors of C. pomonella, with potential for new or refined applications of semiochemicals for control of this pest insect.

De novo assembly of the Indo-Pacific humpback dolphin leucocyte transcriptome to identify putative genes involved in the aquatic adaptation and immune response.

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Duan Gui

Full Text Available BACKGROUND: The Indo-Pacific humpback dolphin (Sousa chinensis, a marine mammal species inhabited in the waters of Southeast Asia, South Africa and Australia, has attracted much attention because of the dramatic decline in population size in the past decades, which raises the concern of extinction. So far, this species is poorly characterized at molecular level due to little sequence information available in public databases. Recent advances in large-scale RNA sequencing provide an efficient approach to generate abundant sequences for functional genomic analyses in the species with un-sequenced genomes. PRINCIPAL FINDINGS: We performed a de novo assembly of the Indo-Pacific humpback dolphin leucocyte transcriptome by Illumina sequencing. 108,751 high quality sequences from 47,840,388 paired-end reads were generated, and 48,868 and 46,587 unigenes were functionally annotated by BLAST search against the NCBI non-redundant and Swiss-Prot protein databases (E-value<10(-5, respectively. In total, 16,467 unigenes were clustered into 25 functional categories by searching against the COG database, and BLAST2GO search assigned 37,976 unigenes to 61 GO terms. In addition, 36,345 unigenes were grouped into 258 KEGG pathways. We also identified 9,906 simple sequence repeats and 3,681 putative single nucleotide polymorphisms as potential molecular markers in our assembled sequences. A large number of unigenes were predicted to be involved in immune response, and many genes were predicted to be relevant to adaptive evolution and cetacean-specific traits. CONCLUSION: This study represented the first transcriptome analysis of the Indo-Pacific humpback dolphin, an endangered species. The de novo transcriptome analysis of the unique transcripts will provide valuable sequence information for discovery of new genes, characterization of gene expression, investigation of various pathways and adaptive evolution, as well as identification of genetic markers.

Augmenting intracortical brain-machine interface with neurally driven error detectors

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Even-Chen, Nir; Stavisky, Sergey D.; Kao, Jonathan C.; Ryu, Stephen I.; Shenoy, Krishna V.

2017-12-01

Objective. Making mistakes is inevitable, but identifying them allows us to correct or adapt our behavior to improve future performance. Current brain-machine interfaces (BMIs) make errors that need to be explicitly corrected by the user, thereby consuming time and thus hindering performance. We hypothesized that neural correlates of the user perceiving the mistake could be used by the BMI to automatically correct errors. However, it was unknown whether intracortical outcome error signals were present in the premotor and primary motor cortices, brain regions successfully used for intracortical BMIs. Approach. We report here for the first time a putative outcome error signal in spiking activity within these cortices when rhesus macaques performed an intracortical BMI computer cursor task. Main results. We decoded BMI trial outcomes shortly after and even before a trial ended with 96% and 84% accuracy, respectively. This led us to develop and implement in real-time a first-of-its-kind intracortical BMI error ‘detect-and-act’ system that attempts to automatically ‘undo’ or ‘prevent’ mistakes. The detect-and-act system works independently and in parallel to a kinematic BMI decoder. In a challenging task that resulted in substantial errors, this approach improved the performance of a BMI employing two variants of the ubiquitous Kalman velocity filter, including a state-of-the-art decoder (ReFIT-KF). Significance. Detecting errors in real-time from the same brain regions that are commonly used to control BMIs should improve the clinical viability of BMIs aimed at restoring motor function to people with paralysis.

[Segmentation of whole body bone SPECT image based on BP neural network].

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Zhu, Chunmei; Tian, Lianfang; Chen, Ping; He, Yuanlie; Wang, Lifei; Ye, Guangchun; Mao, Zongyuan

2007-10-01

In this paper, BP neural network is used to segment whole body bone SPECT image so that the lesion area can be recognized automatically. For the uncertain characteristics of SPECT images, it is hard to achieve good segmentation result if only the BP neural network is employed. Therefore, the segmentation process is divided into three steps: first, the optimal gray threshold segmentation method is employed for preprocessing, then BP neural network is used to roughly identify the lesions, and finally template match method and symmetry-removing program are adopted to delete the wrongly recognized areas.

Conserved gene regulatory module specifies lateral neural borders across bilaterians.

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Li, Yongbin; Zhao, Di; Horie, Takeo; Chen, Geng; Bao, Hongcun; Chen, Siyu; Liu, Weihong; Horie, Ryoko; Liang, Tao; Dong, Biyu; Feng, Qianqian; Tao, Qinghua; Liu, Xiao

2017-08-01

The lateral neural plate border (NPB), the neural part of the vertebrate neural border, is composed of central nervous system (CNS) progenitors and peripheral nervous system (PNS) progenitors. In invertebrates, PNS progenitors are also juxtaposed to the lateral boundary of the CNS. Whether there are conserved molecular mechanisms determining vertebrate and invertebrate lateral neural borders remains unclear. Using single-cell-resolution gene-expression profiling and genetic analysis, we present evidence that orthologs of the NPB specification module specify the invertebrate lateral neural border, which is composed of CNS and PNS progenitors. First, like in vertebrates, the conserved neuroectoderm lateral border specifier Msx/vab-15 specifies lateral neuroblasts in Caenorhabditis elegans Second, orthologs of the vertebrate NPB specification module ( Msx/vab-15 , Pax3/7/pax-3 , and Zic/ref-2 ) are significantly enriched in worm lateral neuroblasts. In addition, like in other bilaterians, the expression domain of Msx/vab-15 is more lateral than those of Pax3/7/pax-3 and Zic/ref- 2 in C. elegans Third, we show that Msx/vab-15 regulates the development of mechanosensory neurons derived from lateral neural progenitors in multiple invertebrate species, including C. elegans , Drosophila melanogaster , and Ciona intestinalis We also identify a novel lateral neural border specifier, ZNF703/tlp-1 , which functions synergistically with Msx/vab- 15 in both C. elegans and Xenopus laevis These data suggest a common origin of the molecular mechanism specifying lateral neural borders across bilaterians.

Complete Genome Sequence of Diaphorina citri-associated C virus, a Novel Putative RNA Virus of the Asian Citrus Psyllid, Diaphorina citri.

Science.gov (United States)

Nouri, Shahideh; Salem, Nidà; Falk, Bryce W

2016-07-21

We present here the complete nucleotide sequence and genome organization of a novel putative RNA virus identified in field populations of the Asian citrus psyllid, Diaphorina citri, through sequencing of the transcriptome followed by reverse transcription-PCR (RT-PCR). We tentatively named this virus Diaphorina citri-associated C virus (DcACV). DcACV is an unclassified positive-sense RNA virus. Copyright © 2016 Nouri et al.

Isolating Discriminant Neural Activity in the Presence of Eye Movements and Concurrent Task Demands

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Jon Touryan

2017-07-01

Full Text Available A growing number of studies use the combination of eye-tracking and electroencephalographic (EEG measures to explore the neural processes that underlie visual perception. In these studies, fixation-related potentials (FRPs are commonly used to quantify early and late stages of visual processing that follow the onset of each fixation. However, FRPs reflect a mixture of bottom-up (sensory-driven and top-down (goal-directed processes, in addition to eye movement artifacts and unrelated neural activity. At present there is little consensus on how to separate this evoked response into its constituent elements. In this study we sought to isolate the neural sources of target detection in the presence of eye movements and over a range of concurrent task demands. Here, participants were asked to identify visual targets (Ts amongst a grid of distractor stimuli (Ls, while simultaneously performing an auditory N-back task. To identify the discriminant activity, we used independent components analysis (ICA for the separation of EEG into neural and non-neural sources. We then further separated the neural sources, using a modified measure-projection approach, into six regions of interest (ROIs: occipital, fusiform, temporal, parietal, cingulate, and frontal cortices. Using activity from these ROIs, we identified target from non-target fixations in all participants at a level similar to other state-of-the-art classification techniques. Importantly, we isolated the time course and spectral features of this discriminant activity in each ROI. In addition, we were able to quantify the effect of cognitive load on both fixation-locked potential and classification performance across regions. Together, our results show the utility of a measure-projection approach for separating task-relevant neural activity into meaningful ROIs within more complex contexts that include eye movements.

Evolvable Neural Software System

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Curtis, Steven A.

2009-01-01

The Evolvable Neural Software System (ENSS) is composed of sets of Neural Basis Functions (NBFs), which can be totally autonomously created and removed according to the changing needs and requirements of the software system. The resulting structure is both hierarchical and self-similar in that a given set of NBFs may have a ruler NBF, which in turn communicates with other sets of NBFs. These sets of NBFs may function as nodes to a ruler node, which are also NBF constructs. In this manner, the synthetic neural system can exhibit the complexity, three-dimensional connectivity, and adaptability of biological neural systems. An added advantage of ENSS over a natural neural system is its ability to modify its core genetic code in response to environmental changes as reflected in needs and requirements. The neural system is fully adaptive and evolvable and is trainable before release. It continues to rewire itself while on the job. The NBF is a unique, bilevel intelligence neural system composed of a higher-level heuristic neural system (HNS) and a lower-level, autonomic neural system (ANS). Taken together, the HNS and the ANS give each NBF the complete capabilities of a biological neural system to match sensory inputs to actions. Another feature of the NBF is the Evolvable Neural Interface (ENI), which links the HNS and ANS. The ENI solves the interface problem between these two systems by actively adapting and evolving from a primitive initial state (a Neural Thread) to a complicated, operational ENI and successfully adapting to a training sequence of sensory input. This simulates the adaptation of a biological neural system in a developmental phase. Within the greater multi-NBF and multi-node ENSS, self-similar ENI s provide the basis for inter-NBF and inter-node connectivity.

Religious beliefs influence neural substrates of self-reflection in Tibetans.

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Wu, Yanhong; Wang, Cheng; He, Xi; Mao, Lihua; Zhang, Li

2010-06-01

Previous transcultural neuroimaging studies have shown that the neural substrates of self-reflection can be shaped by different cultures. There are few studies, however, on the neural activity of self-reflection where religion is viewed as a form of cultural expression. The present study examined the self-processing of two Chinese ethnic groups (Han and Tibetan) to investigate the significant role of religion on the functional anatomy of self-representation. We replicated the previous results in Han participants with the ventral medial prefrontal cortex and left anterior cingulate cortex showing stronger activation in self-processing when compared with other-processing conditions. However, no typical self-reference pattern was identified in Tibetan participants on behavioral or neural levels. This could be explained by the minimal subjective sense of 'I-ness' in Tibetan Buddhists. Our findings lend support to the presumed role of culture and religion in shaping the neural substrate of self.

N-Myc and GCN5 regulate significantly overlapping transcriptional programs in neural stem cells.

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Verónica Martínez-Cerdeño

Full Text Available Here we examine the functions of the Myc cofactor and histone acetyltransferase, GCN5/KAT2A, in neural stem and precursor cells (NSC using a conditional knockout approach driven by nestin-cre. Mice with GCN5-deficient NSC exhibit a 25% reduction in brain mass with a microcephaly phenotype similar to that observed in nestin-cre driven knockouts of c- or N-myc. In addition, the loss of GCN5 inhibits precursor cell proliferation and reduces their populations in vivo, as does loss of N-myc. Gene expression analysis indicates that about one-sixth of genes whose expression is affected by loss of GCN5 are also affected in the same manner by loss of N-myc. These findings strongly support the notion that GCN5 protein is a key N-Myc transcriptional cofactor in NSC, but are also consistent with recruitment of GCN5 by other transcription factors and the use by N-Myc of other histone acetyltransferases. Putative N-Myc/GCN5 coregulated transcriptional pathways include cell metabolism, cell cycle, chromatin, and neuron projection morphogenesis genes. GCN5 is also required for maintenance of histone acetylation both at its putative specific target genes and at Myc targets. Thus, we have defined an important role for GCN5 in NSC and provided evidence that GCN5 is an important Myc transcriptional cofactor in vivo.

Breast Cancer Diagnosis using Artificial Neural Networks with Extreme Learning Techniques

OpenAIRE

Chandra Prasetyo Utomo; Aan Kardiana; Rika Yuliwulandari

2014-01-01

Breast cancer is the second cause of dead among women. Early detection followed by appropriate cancer treatment can reduce the deadly risk. Medical professionals can make mistakes while identifying a disease. The help of technology such as data mining and machine learning can substantially improve the diagnosis accuracy. Artificial Neural Networks (ANN) has been widely used in intelligent breast cancer diagnosis. However, the standard Gradient-Based Back Propagation Artificial Neural Networks...

Chaotic diagonal recurrent neural network

International Nuclear Information System (INIS)

Wang Xing-Yuan; Zhang Yi

2012-01-01

We propose a novel neural network based on a diagonal recurrent neural network and chaos, and its structure and learning algorithm are designed. The multilayer feedforward neural network, diagonal recurrent neural network, and chaotic diagonal recurrent neural network are used to approach the cubic symmetry map. The simulation results show that the approximation capability of the chaotic diagonal recurrent neural network is better than the other two neural networks. (interdisciplinary physics and related areas of science and technology)

Computational modeling of neural plasticity for self-organization of neural networks.

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Chrol-Cannon, Joseph; Jin, Yaochu

2014-11-01

Self-organization in biological nervous systems during the lifetime is known to largely occur through a process of plasticity that is dependent upon the spike-timing activity in connected neurons. In the field of computational neuroscience, much effort has been dedicated to building up computational models of neural plasticity to replicate experimental data. Most recently, increasing attention has been paid to understanding the role of neural plasticity in functional and structural neural self-organization, as well as its influence on the learning performance of neural networks for accomplishing machine learning tasks such as classification and regression. Although many ideas and hypothesis have been suggested, the relationship between the structure, dynamics and learning performance of neural networks remains elusive. The purpose of this article is to review the most important computational models for neural plasticity and discuss various ideas about neural plasticity's role. Finally, we suggest a few promising research directions, in particular those along the line that combines findings in computational neuroscience and systems biology, and their synergetic roles in understanding learning, memory and cognition, thereby bridging the gap between computational neuroscience, systems biology and computational intelligence. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

The Neuroeconomics of Tobacco Demand: An Initial Investigation of the Neural Correlates of Cigarette Cost-Benefit Decision Making in Male Smokers.

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Gray, Joshua C; Amlung, Michael T; Owens, Max; Acker, John; Brown, Courtney L; Brody, Gene H; Sweet, Lawrence H; MacKillop, James

2017-02-03

How the brain processes cigarette cost-benefit decision making remains largely unknown. Using functional magnetic resonance imaging (fMRI), this study investigated the neural correlates of decisions for cigarettes (0-10 cigarettes) at varying levels of price during a Cigarette Purchase Task (CPT) in male regular smokers (N = 35). Differential neural activity was examined between choices classified as inelastic, elastic, and suppressed demand, operationalized as consumption unaffected by cost, partially suppressed by cost, and entirely suppressed by cost, respectively. Decisions reflecting elastic demand, putatively the most effortful decisions, elicited greater activation in regions associated with inhibition and planning (e.g., middle frontal gyrus and inferior frontal gyrus), craving and interoceptive processing (anterior insula), and conflict monitoring (e.g., anterior cingulate cortex). Exploratory examination in a harmonized dataset of both cigarette and alcohol demand (N = 59) suggested common neural activation patterns across commodities, particularly in the anterior insula, caudate, anterior cingulate, medial frontal gyrus, and dorsolateral prefrontal cortex. Collectively, these findings provide initial validation of a CPT fMRI paradigm; reveal the interplay of brain regions associated with executive functioning, incentive salience, and interoceptive processing in cigarette decision making; and add to the literature implicating the insula as a key brain region in addiction.

Identification of neural outgrowth genes using genome-wide RNAi.

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Katharine J Sepp

2008-07-01

Full Text Available While genetic screens have identified many genes essential for neurite outgrowth, they have been limited in their ability to identify neural genes that also have earlier critical roles in the gastrula, or neural genes for which maternally contributed RNA compensates for gene mutations in the zygote. To address this, we developed methods to screen the Drosophila genome using RNA-interference (RNAi on primary neural cells and present the results of the first full-genome RNAi screen in neurons. We used live-cell imaging and quantitative image analysis to characterize the morphological phenotypes of fluorescently labelled primary neurons and glia in response to RNAi-mediated gene knockdown. From the full genome screen, we focused our analysis on 104 evolutionarily conserved genes that when downregulated by RNAi, have morphological defects such as reduced axon extension, excessive branching, loss of fasciculation, and blebbing. To assist in the phenotypic analysis of the large data sets, we generated image analysis algorithms that could assess the statistical significance of the mutant phenotypes. The algorithms were essential for the analysis of the thousands of images generated by the screening process and will become a valuable tool for future genome-wide screens in primary neurons. Our analysis revealed unexpected, essential roles in neurite outgrowth for genes representing a wide range of functional categories including signalling molecules, enzymes, channels, receptors, and cytoskeletal proteins. We also found that genes known to be involved in protein and vesicle trafficking showed similar RNAi phenotypes. We confirmed phenotypes of the protein trafficking genes Sec61alpha and Ran GTPase using Drosophila embryo and mouse embryonic cerebral cortical neurons, respectively. Collectively, our results showed that RNAi phenotypes in primary neural culture can parallel in vivo phenotypes, and the screening technique can be used to identify many new

Identification of putative regulatory motifs in the upstream regions of co-expressed functional groups of genes in Plasmodium falciparum

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Joshi NV

2009-01-01

Full Text Available Abstract Background Regulation of gene expression in Plasmodium falciparum (Pf remains poorly understood. While over half the genes are estimated to be regulated at the transcriptional level, few regulatory motifs and transcription regulators have been found. Results The study seeks to identify putative regulatory motifs in the upstream regions of 13 functional groups of genes expressed in the intraerythrocytic developmental cycle of Pf. Three motif-discovery programs were used for the purpose, and motifs were searched for only on the gene coding strand. Four motifs – the 'G-rich', the 'C-rich', the 'TGTG' and the 'CACA' motifs – were identified, and zero to all four of these occur in the 13 sets of upstream regions. The 'CACA motif' was absent in functional groups expressed during the ring to early trophozoite transition. For functional groups expressed in each transition, the motifs tended to be similar. Upstream motifs in some functional groups showed 'positional conservation' by occurring at similar positions relative to the translational start site (TLS; this increases their significance as regulatory motifs. In the ribonucleotide synthesis, mitochondrial, proteasome and organellar translation machinery genes, G-rich, C-rich, CACA and TGTG motifs, respectively, occur with striking positional conservation. In the organellar translation machinery group, G-rich motifs occur close to the TLS. The same motifs were sometimes identified for multiple functional groups; differences in location and abundance of the motifs appear to ensure different modes of action. Conclusion The identification of positionally conserved over-represented upstream motifs throws light on putative regulatory elements for transcription in Pf.

Similar patterns of neural activity predict memory function during encoding and retrieval.

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Kragel, James E; Ezzyat, Youssef; Sperling, Michael R; Gorniak, Richard; Worrell, Gregory A; Berry, Brent M; Inman, Cory; Lin, Jui-Jui; Davis, Kathryn A; Das, Sandhitsu R; Stein, Joel M; Jobst, Barbara C; Zaghloul, Kareem A; Sheth, Sameer A; Rizzuto, Daniel S; Kahana, Michael J

2017-07-15

Neural networks that span the medial temporal lobe (MTL), prefrontal cortex, and posterior cortical regions are essential to episodic memory function in humans. Encoding and retrieval are supported by the engagement of both distinct neural pathways across the cortex and common structures within the medial temporal lobes. However, the degree to which memory performance can be determined by neural processing that is common to encoding and retrieval remains to be determined. To identify neural signatures of successful memory function, we administered a delayed free-recall task to 187 neurosurgical patients implanted with subdural or intraparenchymal depth electrodes. We developed multivariate classifiers to identify patterns of spectral power across the brain that independently predicted successful episodic encoding and retrieval. During encoding and retrieval, patterns of increased high frequency activity in prefrontal, MTL, and inferior parietal cortices, accompanied by widespread decreases in low frequency power across the brain predicted successful memory function. Using a cross-decoding approach, we demonstrate the ability to predict memory function across distinct phases of the free-recall task. Furthermore, we demonstrate that classifiers that combine information from both encoding and retrieval states can outperform task-independent models. These findings suggest that the engagement of a core memory network during either encoding or retrieval shapes the ability to remember the past, despite distinct neural interactions that facilitate encoding and retrieval. Copyright © 2017 Elsevier Inc. All rights reserved.

Advances in Artificial Neural Networks – Methodological Development and Application

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Yanbo Huang

2009-08-01

Full Text Available Artificial neural networks as a major soft-computing technology have been extensively studied and applied during the last three decades. Research on backpropagation training algorithms for multilayer perceptron networks has spurred development of other neural network training algorithms for other networks such as radial basis function, recurrent network, feedback network, and unsupervised Kohonen self-organizing network. These networks, especially the multilayer perceptron network with a backpropagation training algorithm, have gained recognition in research and applications in various scientific and engineering areas. In order to accelerate the training process and overcome data over-fitting, research has been conducted to improve the backpropagation algorithm. Further, artificial neural networks have been integrated with other advanced methods such as fuzzy logic and wavelet analysis, to enhance the ability of data interpretation and modeling and to avoid subjectivity in the operation of the training algorithm. In recent years, support vector machines have emerged as a set of high-performance supervised generalized linear classifiers in parallel with artificial neural networks. A review on development history of artificial neural networks is presented and the standard architectures and algorithms of artificial neural networks are described. Furthermore, advanced artificial neural networks will be introduced with support vector machines, and limitations of ANNs will be identified. The future of artificial neural network development in tandem with support vector machines will be discussed in conjunction with further applications to food science and engineering, soil and water relationship for crop management, and decision support for precision agriculture. Along with the network structures and training algorithms, the applications of artificial neural networks will be reviewed as well, especially in the fields of agricultural and biological

A Tensor-Product-Kernel Framework for Multiscale Neural Activity Decoding and Control

Science.gov (United States)

Li, Lin; Brockmeier, Austin J.; Choi, John S.; Francis, Joseph T.; Sanchez, Justin C.; Príncipe, José C.

2014-01-01

Brain machine interfaces (BMIs) have attracted intense attention as a promising technology for directly interfacing computers or prostheses with the brain's motor and sensory areas, thereby bypassing the body. The availability of multiscale neural recordings including spike trains and local field potentials (LFPs) brings potential opportunities to enhance computational modeling by enriching the characterization of the neural system state. However, heterogeneity on data type (spike timing versus continuous amplitude signals) and spatiotemporal scale complicates the model integration of multiscale neural activity. In this paper, we propose a tensor-product-kernel-based framework to integrate the multiscale activity and exploit the complementary information available in multiscale neural activity. This provides a common mathematical framework for incorporating signals from different domains. The approach is applied to the problem of neural decoding and control. For neural decoding, the framework is able to identify the nonlinear functional relationship between the multiscale neural responses and the stimuli using general purpose kernel adaptive filtering. In a sensory stimulation experiment, the tensor-product-kernel decoder outperforms decoders that use only a single neural data type. In addition, an adaptive inverse controller for delivering electrical microstimulation patterns that utilizes the tensor-product kernel achieves promising results in emulating the responses to natural stimulation. PMID:24829569

A Particle Swarm Optimization Algorithm for Neural Networks in Recognition of Maize Leaf Diseases

Directory of Open Access Journals (Sweden)

Zhiyong ZHANG

2014-03-01

Full Text Available The neural networks have significance on recognition of crops disease diagnosis? but it has disadvantage of slow convergent speed and shortcoming of local optimum. In order to identify the maize leaf diseases by using machine vision more accurately, we propose an improved particle swarm optimization algorithm for neural networks. With the algorithm, the neural network property is improved. It reasonably confirms threshold and connection weight of neural network, and improves capability of solving problems in the image recognition. At last, an example of the emulation shows that neural network model based on recognizes significantly better than without optimization. Model accuracy has been improved to a certain extent to meet the actual needs of maize leaf diseases recognition.

Neural Parallel Engine: A toolbox for massively parallel neural signal processing.

Science.gov (United States)

Tam, Wing-Kin; Yang, Zhi

2018-05-01

Large-scale neural recordings provide detailed information on neuronal activities and can help elicit the underlying neural mechanisms of the brain. However, the computational burden is also formidable when we try to process the huge data stream generated by such recordings. In this study, we report the development of Neural Parallel Engine (NPE), a toolbox for massively parallel neural signal processing on graphical processing units (GPUs). It offers a selection of the most commonly used routines in neural signal processing such as spike detection and spike sorting, including advanced algorithms such as exponential-component-power-component (EC-PC) spike detection and binary pursuit spike sorting. We also propose a new method for detecting peaks in parallel through a parallel compact operation. Our toolbox is able to offer a 5× to 110× speedup compared with its CPU counterparts depending on the algorithms. A user-friendly MATLAB interface is provided to allow easy integration of the toolbox into existing workflows. Previous efforts on GPU neural signal processing only focus on a few rudimentary algorithms, are not well-optimized and often do not provide a user-friendly programming interface to fit into existing workflows. There is a strong need for a comprehensive toolbox for massively parallel neural signal processing. A new toolbox for massively parallel neural signal processing has been created. It can offer significant speedup in processing signals from large-scale recordings up to thousands of channels. Copyright © 2018 Elsevier B.V. All rights reserved.

Putative periodontopathic bacteria and herpesviruses in pregnant women: a case-control study.

Science.gov (United States)

Lu, Haixia; Zhu, Ce; Li, Fei; Xu, Wei; Tao, Danying; Feng, Xiping

2016-06-15

Little is known about herpesvirus and putative periodontopathic bacteria in maternal chronic periodontitis. The present case-control study aimed to explore the potential relationship between putative periodontopathic bacteria and herpesviruses in maternal chronic periodontitis.Saliva samples were collected from 36 pregnant women with chronic periodontitis (cases) and 36 pregnant women with healthy periodontal status (controls). Six putative periodontopathic bacteria (Porphyromonas gingivalis [Pg], Aggregatibacer actinomycetemcomitans [Aa], Fusobacterium nucleatum [Fn], Prevotella intermedia [Pi], Tannerella forsythia [Tf], and Treponema denticola [Td]) and three herpesviruses (Epstein-Barr virus [EBV], human cytomegalovirus [HCMV], and herpes simplex virus [HSV]) were detected. Socio-demographic data and oral health related behaviors, and salivary estradiol and progesterone levels were also collected. The results showed no significant differences in socio-demographic background, oral health related behaviors, and salivary estradiol and progesterone levels between the two groups (all P > 0.05). The detection rates of included periodontopathic microorganisms were not significantly different between the two groups (all P > 0.05), but the coinfection rate of EBV and Pg was significantly higher in the case group than in the control group (P = 0.028). EBV and Pg coinfection may promote the development of chronic periodontitis among pregnant women.

Neural chips, neural computers and application in high and superhigh energy physics experiments

International Nuclear Information System (INIS)

Nikityuk, N.M.; )

2001-01-01

Architecture peculiarity and characteristics of series of neural chips and neural computes used in scientific instruments are considered. Tendency of development and use of them in high energy and superhigh energy physics experiments are described. Comparative data which characterize the efficient use of neural chips for useful event selection, classification elementary particles, reconstruction of tracks of charged particles and for search of hypothesis Higgs particles are given. The characteristics of native neural chips and accelerated neural boards are considered [ru

Differential proteomic analysis of Aspergillus fumigatus morphotypes reveals putative drug targets.

Science.gov (United States)

Kubitschek-Barreira, Paula H; Curty, Nathalia; Neves, Gabriela W P; Gil, Concha; Lopes-Bezerra, Leila M

2013-01-14

Aspergillus fumigatus is the main etiological agent of invasive aspergillosis, an important opportunistic infection for neutropenic patients. The main risk groups are patients with acute leukemia and bone marrow transplantation recipients. The lack of an early diagnostic test together with the limited spectrum of antifungal drugs remains a setback to the successful treatment of this disease. During invasive infection the inhaled fungal conidia enter the morphogenic cycle leading to angioinvasive hyphae. This work aimed to study differentially expressed proteins of A. fumigatus during morphogenesis. To achieve this goal, a 2D-DIGE approach was applied to study surface proteins extractable by reducing agents of two A. fumigatus morphotypes: germlings and hyphae. Sixty-three differentially expressed proteins were identified by MALDI-ToF/MS. We observed that proteins associated with biosynthetic pathways and proteins with multiple functions (miscellaneous) were over-expressed in the early stages of germination, while in hyphae, the most abundant proteins detected were related to metabolic processes or have unknown functions. Among the most interesting proteins regulated during morphogenesis, two putative drug targets were identified, the translational factor, eEF3 and the CipC-like protein. Neither of these proteins are present in mammalian cells. Copyright © 2012 Elsevier B.V. All rights reserved.

Empirical modeling of nuclear power plants using neural networks

International Nuclear Information System (INIS)

Parlos, A.G.; Atiya, A.; Chong, K.T.

1991-01-01

A summary of a procedure for nonlinear identification of process dynamics encountered in nuclear power plant components is presented in this paper using artificial neural systems. A hybrid feedforward/feedback neural network, namely, a recurrent multilayer perceptron, is used as the nonlinear structure for system identification. In the overall identification process, the feedforward portion of the network architecture provides its well-known interpolation property, while through recurrency and cross-talk, the local information feedback enables representation of time-dependent system nonlinearities. The standard backpropagation learning algorithm is modified and is used to train the proposed hybrid network in a supervised manner. The performance of recurrent multilayer perceptron networks in identifying process dynamics is investigated via the case study of a U-tube steam generator. The nonlinear response of a representative steam generator is predicted using a neural network and is compared to the response obtained from a sophisticated physical model during both high- and low-power operation. The transient responses compare well, though further research is warranted for training and testing of recurrent neural networks during more severe operational transients and accident scenarios

Identification of Complex Dynamical Systems with Neural Networks (2/2)

CERN Multimedia

CERN. Geneva

2016-01-01

The identification and analysis of high dimensional nonlinear systems is obviously a challenging task. Neural networks have been proven to be universal approximators but this still leaves the identification task a hard one. To do it efficiently, we have to violate some of the rules of classical regression theory. Furthermore we should focus on the interpretation of the resulting model to overcome its black box character. First, we will discuss function approximation with 3 layer feedforward neural networks up to new developments in deep neural networks and deep learning. These nets are not only of interest in connection with image analysis but are a center point of the current artificial intelligence developments. Second, we will focus on the analysis of complex dynamical system in the form of state space models realized as recurrent neural networks. After the introduction of small open dynamical systems we will study dynamical systems on manifolds. Here manifold and dynamics have to be identified in parall...

Identification of Complex Dynamical Systems with Neural Networks (1/2)

CERN Multimedia

CERN. Geneva

2016-01-01

The identification and analysis of high dimensional nonlinear systems is obviously a challenging task. Neural networks have been proven to be universal approximators but this still leaves the identification task a hard one. To do it efficiently, we have to violate some of the rules of classical regression theory. Furthermore we should focus on the interpretation of the resulting model to overcome its black box character. First, we will discuss function approximation with 3 layer feedforward neural networks up to new developments in deep neural networks and deep learning. These nets are not only of interest in connection with image analysis but are a center point of the current artificial intelligence developments. Second, we will focus on the analysis of complex dynamical system in the form of state space models realized as recurrent neural networks. After the introduction of small open dynamical systems we will study dynamical systems on manifolds. Here manifold and dynamics have to be identified in parall...

Neural tissue-spheres

DEFF Research Database (Denmark)

Andersen, Rikke K; Johansen, Mathias; Blaabjerg, Morten

2007-01-01

By combining new and established protocols we have developed a procedure for isolation and propagation of neural precursor cells from the forebrain subventricular zone (SVZ) of newborn rats. Small tissue blocks of the SVZ were dissected and propagated en bloc as free-floating neural tissue...... content, thus allowing experimental studies of neural precursor cells and their niche...

Radioactivity nuclide identification based on BP and LM algorithm neural network

International Nuclear Information System (INIS)

Wang Jihong; Sun Jian; Wang Lianghou

2012-01-01

The paper provides the method which can identify radioactive nuclide based on the BP and LM algorithm neural network. Then, this paper compares the above-mentioned method with FR algorithm. Through the result of the Matlab simulation, the method of radioactivity nuclide identification based on the BP and LM algorithm neural network is superior to the FR algorithm. With the better effect and the higher accuracy, it will be the best choice. (authors)

Modification of surface/neuron interfaces for neural cell-type specific responses: a review

International Nuclear Information System (INIS)

Chen, Cen; Kong, Xiangdong; Lee, In-Seop

2016-01-01

Surface/neuron interfaces have played an important role in neural repair including neural prostheses and tissue engineered scaffolds. This comprehensive literature review covers recent studies on the modification of surface/neuron interfaces. These interfaces are identified in cases both where the surfaces of substrates or scaffolds were in direct contact with cells and where the surfaces were modified to facilitate cell adhesion and controlling cell-type specific responses. Different sources of cells for neural repair are described, such as pheochromocytoma neuronal-like cell, neural stem cell (NSC), embryonic stem cell (ESC), mesenchymal stem cell (MSC) and induced pluripotent stem cell (iPS). Commonly modified methods are discussed including patterned surfaces at micro- or nano-scale, surface modification with conducting coatings, and functionalized surfaces with immobilized bioactive molecules. These approaches to control cell-type specific responses have enormous potential implications in neural repair. (paper)

Utility of Phox2b immunohistochemical stain in neural crest tumours and non-neural crest tumours in paediatric patients.

Science.gov (United States)

Warren, Mikako; Matsuno, Ryosuke; Tran, Henry; Shimada, Hiroyuki

2018-03-01

This study evaluated the utility of Phox2b in paediatric tumours. Previously, tyrosine hydroxylase (TH) was the most widely utilised sympathoadrenal marker specific for neural crest tumours with neuronal/neuroendocrine differentiation. However, its sensitivity is insufficient. Recently Phox2b has emerged as another specific marker for this entity. Phox2b immunohistochemistry (IHC) was performed on 159 paediatric tumours, including (group 1) 65 neural crest tumours with neuronal differentiation [peripheral neuroblastic tumours (pNT)]: 15 neuroblastoma undifferentiated (NB-UD), 10 NB poorly differentiated (NB-PD), 10 NB differentiating (NB-D), 10 ganglioneuroblastoma intermixed (GNBi), 10 GNB nodular (GNBn) and 10 ganglioneuroma (GN); (group 2) 23 neural crest tumours with neuroendocrine differentiation [pheochromocytoma/paraganglioma (PCC/PG)]; (group 3) 27 other neural crest tumours including one composite rhabdomyosarcoma/neuroblastoma; and (group 4) 44 non-neural crest tumours. TH IHC was performed on groups 1, 2 and 3. Phox2b was expressed diffusely in pNT (n = 65 of 65), strongly in NB-UD and NB-PD and with less intensity in NB-D, GNB and GN. Diffuse TH was seen in all NB-PD, NB-D, GNB and GN, but nine of 15 NB-UD and a nodule in GNBn did not express TH (n = 55 of 65). PCC/PG expressed diffuse Phox2b (n = 23 of 23) and diffuse TH, except for one tumour (n = 22 of 23). In composite rhabdomyosarcoma, TH was expressed only in neuroblastic cells and Phox2b was diffusely positive in neuroblastic cells and focally in rhabdomyosarcoma. All other tumours were negative for Phox2b (n = none of 44). Phox2b was a specific and sensitive marker for pNT and PCC/PG, especially useful for identifying NB-UD often lacking TH. Our study also presented a composite rhabdomyosarcoma/neuroblastoma of neural crest origin. © 2017 John Wiley & Sons Ltd.

Pattern Recognition and Classification of Fatal Traffic Accidents in Israel A Neural Network Approach

DEFF Research Database (Denmark)

Prato, Carlo Giacomo; Gitelman, Victoria; Bekhor, Shlomo

2011-01-01

on 1,793 fatal traffic accidents occurred during the period between 2003 and 2006 and applies Kohonen and feed-forward back-propagation neural networks with the objective of extracting from the data typical patterns and relevant factors. Kohonen neural networks reveal five compelling accident patterns....... Feed-forward back-propagation neural networks indicate that sociodemographic characteristics of drivers and victims, accident location, and period of the day are extremely relevant factors. Accident patterns suggest that countermeasures are necessary for identified problems concerning mainly vulnerable...

Regulation of Arabidopsis Early Anther Development by Putative Cell-Cell Signaling Molecules and Transcriptional Regulators

Institute of Scientific and Technical Information of China (English)

Yu-Jin Sun; Carey LH Hord; Chang-Bin Chen; Hong Ma

2007-01-01

Anther development in flowering plants involves the formation of several cell types, including the tapetal and pollen mother cells. The use of genetic and molecular tools has led to the identification and characterization of genes that are critical for normal cell division and differentiation in Arabidopsis early anther development. We review here several recent studies on these genes, including the demonstration that the putative receptor protein kinases BAM1 and BAM2 together play essential roles in the control of early cell division and differentiation. In addition, we discuss the hypothesis that BAM1/2 may form a positive-negative feedback regulatory loop with a previously identified key regulator, SPOROCYTELESS (also called NOZZLE),to control the balance between sporogenous and somatic cell types in the anther. Furthermore, we summarize the isolation and functional analysis of the DYSFUNCTIONAL TAPETUM1 (DYT1) gene in promoting proper tapetal cell differentiation. Our finding that DYT1 encodes a putative transcription factor of the bHLH family, as well as relevant expression analyses, strongly supports a model that DYT1 serves as a critical link between upstream factors and downstream target genes that are critical for normal tapetum development and function. These studies, together with other recently published works, indicate that cell-cell communication and transcriptional control are key processes essential for cell fate specification in anther development.

Searching for Cross-Diagnostic Convergence: Neural Mechanisms Governing Excitation and Inhibition Balance in Schizophrenia and Autism Spectrum Disorders.

Science.gov (United States)

Foss-Feig, Jennifer H; Adkinson, Brendan D; Ji, Jie Lisa; Yang, Genevieve; Srihari, Vinod H; McPartland, James C; Krystal, John H; Murray, John D; Anticevic, Alan

2017-05-15

Recent theoretical accounts have proposed excitation and inhibition (E/I) imbalance as a possible mechanistic, network-level hypothesis underlying neural and behavioral dysfunction across neurodevelopmental disorders, particularly autism spectrum disorder (ASD) and schizophrenia (SCZ). These two disorders share some overlap in their clinical presentation as well as convergence in their underlying genes and neurobiology. However, there are also clear points of dissociation in terms of phenotypes and putatively affected neural circuitry. We highlight emerging work from the clinical neuroscience literature examining neural correlates of E/I imbalance across children and adults with ASD and adults with both chronic and early-course SCZ. We discuss findings from diverse neuroimaging studies across distinct modalities, conducted with electroencephalography, magnetoencephalography, proton magnetic resonance spectroscopy, and functional magnetic resonance imaging, including effects observed both during task and at rest. Throughout this review, we discuss points of convergence and divergence in the ASD and SCZ literature, with a focus on disruptions in neural E/I balance. We also consider these findings in relation to predictions generated by theoretical neuroscience, particularly computational models predicting E/I imbalance across disorders. Finally, we discuss how human noninvasive neuroimaging can benefit from pharmacological challenge studies to reveal mechanisms in ASD and SCZ. Collectively, we attempt to shed light on shared and divergent neuroimaging effects across disorders with the goal of informing future research examining the mechanisms underlying the E/I imbalance hypothesis across neurodevelopmental disorders. We posit that such translational efforts are vital to facilitate development of neurobiologically informed treatment strategies across neuropsychiatric conditions. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights

Puzzle Pieces: Neural Structure and Function in Prader-Willi Syndrome

Science.gov (United States)

Manning, Katherine E.; Holland, Anthony J.

2015-01-01

Prader-Willi syndrome (PWS) is a neurodevelopmental disorder of genomic imprinting, presenting with a behavioural phenotype encompassing hyperphagia, intellectual disability, social and behavioural difficulties, and propensity to psychiatric illness. Research has tended to focus on the cognitive and behavioural investigation of these features, and, with the exception of eating behaviour, the neural physiology is currently less well understood. A systematic review was undertaken to explore findings relating to neural structure and function in PWS, using search terms designed to encompass all published articles concerning both in vivo and post-mortem studies of neural structure and function in PWS. This supported the general paucity of research in this area, with many articles reporting case studies and qualitative descriptions or focusing solely on the overeating behaviour, although a number of systematic investigations were also identified. Research to date implicates a combination of subcortical and higher order structures in PWS, including those involved in processing reward, motivation, affect and higher order cognitive functions, with both anatomical and functional investigations indicating abnormalities. It appears likely that PWS involves aberrant activity across distributed neural networks. The characterisation of neural structure and function warrants both replication and further systematic study. PMID:28943631

Puzzle Pieces: Neural Structure and Function in Prader-Willi Syndrome

Directory of Open Access Journals (Sweden)

Katherine E. Manning

2015-12-01

Full Text Available Prader-Willi syndrome (PWS is a neurodevelopmental disorder of genomic imprinting, presenting with a behavioural phenotype encompassing hyperphagia, intellectual disability, social and behavioural difficulties, and propensity to psychiatric illness. Research has tended to focus on the cognitive and behavioural investigation of these features, and, with the exception of eating behaviour, the neural physiology is currently less well understood. A systematic review was undertaken to explore findings relating to neural structure and function in PWS, using search terms designed to encompass all published articles concerning both in vivo and post-mortem studies of neural structure and function in PWS. This supported the general paucity of research in this area, with many articles reporting case studies and qualitative descriptions or focusing solely on the overeating behaviour, although a number of systematic investigations were also identified. Research to date implicates a combination of subcortical and higher order structures in PWS, including those involved in processing reward, motivation, affect and higher order cognitive functions, with both anatomical and functional investigations indicating abnormalities. It appears likely that PWS involves aberrant activity across distributed neural networks. The characterisation of neural structure and function warrants both replication and further systematic study.

Whole-transcriptome survey of the putative ATP-binding cassette (ABC) transporter family genes in the latex-producing laticifers of Hevea brasiliensis.

Science.gov (United States)

Zhiyi, Nie; Guijuan, Kang; Yu, Li; Longjun, Dai; Rizhong, Zeng

2015-01-01

The ATP-binding cassette (ABC) proteins or transporters constitute a large protein family in plants and are involved in many different cellular functions and processes, including solute transportation, channel regulation and molecular switches, etc. Through transcriptome sequencing, a transcriptome-wide survey and expression analysis of the ABC protein genes were carried out using the laticiferous latex from Hevea brasiliensis (rubber tree). A total of 46 putative ABC family proteins were identified in the H. brasiliensis latex. These consisted of 12 'full-size', 21 'half-size' and 13 other putative ABC proteins, and all of them showed strong conservation with their Arabidopsis thaliana counterparts. This study indicated that all eight plant ABC protein paralog subfamilies were identified in the H. brasiliensis latex, of which ABCB, ABCG and ABCI were the most abundant. Real-time quantitative reverse transcription-polymerase chain reaction assays demonstrated that gene expression of several latex ABC proteins was regulated by ethylene, jasmonic acid or bark tapping (a wound stress) stimulation, and that HbABCB15, HbABCB19, HbABCD1 and HbABCG21 responded most significantly of all to the abiotic stresses. The identification and expression analysis of the latex ABC family proteins could facilitate further investigation into their physiological involvement in latex metabolism and rubber biosynthesis by H. brasiliensis.

Putative golden proportions as predictors of facial esthetics in adolescents.

NARCIS (Netherlands)

Kiekens, R.M.A.; Kuijpers-Jagtman, A.M.; Hof, M.A. van 't; Hof, B.E. van 't; Maltha, J.C.

2008-01-01

INTRODUCTION: In orthodontics, facial esthetics is assumed to be related to golden proportions apparent in the ideal human face. The aim of the study was to analyze the putative relationship between facial esthetics and golden proportions in white adolescents. METHODS: Seventy-six adult laypeople

Dengue Virus Infection of Aedes aegypti Requires a Putative Cysteine Rich Venom Protein.

Directory of Open Access Journals (Sweden)

Berlin Londono-Renteria

2015-10-01

Full Text Available Dengue virus (DENV is a mosquito-borne flavivirus that causes serious human disease and mortality worldwide. There is no specific antiviral therapy or vaccine for DENV infection. Alterations in gene expression during DENV infection of the mosquito and the impact of these changes on virus infection are important events to investigate in hopes of creating new treatments and vaccines. We previously identified 203 genes that were ≥5-fold differentially upregulated during flavivirus infection of the mosquito. Here, we examined the impact of silencing 100 of the most highly upregulated gene targets on DENV infection in its mosquito vector. We identified 20 genes that reduced DENV infection by at least 60% when silenced. We focused on one gene, a putative cysteine rich venom protein (SeqID AAEL000379; CRVP379, whose silencing significantly reduced DENV infection in Aedes aegypti cells. Here, we examine the requirement for CRVP379 during DENV infection of the mosquito and investigate the mechanisms surrounding this phenomenon. We also show that blocking CRVP379 protein with either RNAi or specific antisera inhibits DENV infection in Aedes aegypti. This work identifies a novel mosquito gene target for controlling DENV infection in mosquitoes that may also be used to develop broad preventative and therapeutic measures for multiple flaviviruses.

Motion control of servo cylinder using neural network

International Nuclear Information System (INIS)

Hwang, Un Kyoo; Cho, Seung Ho

2004-01-01

In this paper, a neural network controller that can be implemented in parallel with a PD controller is suggested for motion control of a hydraulic servo cylinder. By applying a self-excited oscillation method, the system design parameters of open loop transfer function of servo cylinder system are identified. Based on system design parameters, the PD gains are determined for the desired closed loop characteristics. The neural network is incorporated with PD control in order to compensate the inherent nonlinearities of hydraulic servo system. As an application example, a motion control using PD-NN has been performed and proved its superior performance by comparing with that of a PD control

On the nature and evolution of the neural bases of human language

Science.gov (United States)

Lieberman, Philip

2002-01-01

The traditional theory equating the brain bases of language with Broca's and Wernicke's neocortical areas is wrong. Neural circuits linking activity in anatomically segregated populations of neurons in subcortical structures and the neocortex throughout the human brain regulate complex behaviors such as walking, talking, and comprehending the meaning of sentences. When we hear or read a word, neural structures involved in the perception or real-world associations of the word are activated as well as posterior cortical regions adjacent to Wernicke's area. Many areas of the neocortex and subcortical structures support the cortical-striatal-cortical circuits that confer complex syntactic ability, speech production, and a large vocabulary. However, many of these structures also form part of the neural circuits regulating other aspects of behavior. For example, the basal ganglia, which regulate motor control, are also crucial elements in the circuits that confer human linguistic ability and abstract reasoning. The cerebellum, traditionally associated with motor control, is active in motor learning. The basal ganglia are also key elements in reward-based learning. Data from studies of Broca's aphasia, Parkinson's disease, hypoxia, focal brain damage, and a genetically transmitted brain anomaly (the putative "language gene," family KE), and from comparative studies of the brains and behavior of other species, demonstrate that the basal ganglia sequence the discrete elements that constitute a complete motor act, syntactic process, or thought process. Imaging studies of intact human subjects and electrophysiologic and tracer studies of the brains and behavior of other species confirm these findings. As Dobzansky put it, "Nothing in biology makes sense except in the light of evolution" (cited in Mayr, 1982). That applies with as much force to the human brain and the neural bases of language as it does to the human foot or jaw. The converse follows: the mark of evolution on

Mechanisms to medicines: elucidating neural and molecular substrates of fear extinction to identify novel treatments for anxiety disorders.

Science.gov (United States)

Bukalo, Olena; Pinard, Courtney R; Holmes, Andrew

2014-10-01

The burden of anxiety disorders is growing, but the efficacy of available anxiolytic treatments remains inadequate. Cognitive behavioural therapy for anxiety disorders focuses on identifying and modifying maladaptive patterns of thinking and behaving, and has a testable analogue in rodents in the form of fear extinction. A large preclinical literature has amassed in recent years describing the neural and molecular basis of fear extinction in rodents. In this review, we discuss how this work is being harnessed to foster translational research on anxiety disorders and facilitate the search for new anxiolytic treatments. We begin by summarizing the anatomical and functional connectivity of a medial prefrontal cortex (mPFC)-amygdala circuit that subserves fear extinction, including new insights from optogenetics. We then cover some of the approaches that have been taken to model impaired fear extinction and associated impairments with mPFC-amygdala dysfunction. The principal goal of the review is to evaluate evidence that various neurotransmitter and neuromodulator systems mediate fear extinction by modulating the mPFC-amygdala circuitry. To that end, we describe studies that have tested how fear extinction is impaired or facilitated by pharmacological manipulations of dopamine, noradrenaline, 5-HT, GABA, glutamate, neuropeptides, endocannabinoids and various other systems, which either directly target the mPFC-amygdala circuit, or produce behavioural effects that are coincident with functional changes in the circuit. We conclude that there are good grounds to be optimistic that the progress in defining the molecular substrates of mPFC-amygdala circuit function can be effectively leveraged to identify plausible candidates for extinction-promoting therapies for anxiety disorders. © 2014 The British Pharmacological Society.

Heterologous expression and characterization of a putative glycoside hydrolase family 43 arabinofuranosidase from Clostridium thermocellum B8

NARCIS (Netherlands)

Camargo, de Brenda R.; Claassens, Nico J.; Quirino, Betania Ferraz; Noronha, Eliane F.; Kengen, Servé W.M.

2018-01-01

An extensive list of putative cellulosomal enzymes from C. thermocellum is now available in the public databanks, however, most of these remain unvalidated with regard to their activity and expression control mechanisms. This is particularly true of those enzymes putatively involved in hemicellulose

Estimation of break location and size for loss of coolant accidents using neural networks

International Nuclear Information System (INIS)

Na, Man Gyun; Shin, Sun Ho; Jung, Dong Won; Kim, Soong Pyung; Jeong, Ji Hwan; Lee, Byung Chul

2004-01-01

In this work, a probabilistic neural network (PNN) that has been applied well to the classification problems is used in order to identify the break locations of loss of coolant accidents (LOCA) such as hot-leg, cold-leg and steam generator tubes. Also, a fuzzy neural network (FNN) is designed to estimate the break size. The inputs to PNN and FNN are time-integrated values obtained by integrating measurement signals during a short time interval after reactor scram. An automatic structure constructor for the fuzzy neural network automatically selects the input variables from the time-integrated values of many measured signals, and optimizes the number of rules and its related parameters. It is verified that the proposed algorithm identifies very well the break locations of LOCAs and also, estimate their break size accurately

The fundamentals of fuzzy neural network and application in nuclear monitoring

International Nuclear Information System (INIS)

Feng Diqing; Lei Ming

1995-01-01

The authors presents a fuzzy modeling method using fuzzy neural network with the back-propagation algorithm. The new method can identify the fuzzy model of a nonlinear system automatically. Fuzzy neural network is used to generate fuzzy rules and membership functions. The feasibility and inferential statistic of the method is examined by using numerical data and XOR problem. The FNN improves accuracy and reliability, reduces design time and minimizes system cost of fuzzy design. The FNN can be used for estimation of human injury in nuclear explosions and can be simplified to a rule neural network (RNN), which is used for pole extraction of signal. Preliminary simulation show that FNN has vest vistas in nuclear monitoring

Multimodal neural correlates of cognitive control in the Human Connectome Project.

Science.gov (United States)

Lerman-Sinkoff, Dov B; Sui, Jing; Rachakonda, Srinivas; Kandala, Sridhar; Calhoun, Vince D; Barch, Deanna M

2017-12-01

Cognitive control is a construct that refers to the set of functions that enable decision-making and task performance through the representation of task states, goals, and rules. The neural correlates of cognitive control have been studied in humans using a wide variety of neuroimaging modalities, including structural MRI, resting-state fMRI, and task-based fMRI. The results from each of these modalities independently have implicated the involvement of a number of brain regions in cognitive control, including dorsal prefrontal cortex, and frontal parietal and cingulo-opercular brain networks. However, it is not clear how the results from a single modality relate to results in other modalities. Recent developments in multimodal image analysis methods provide an avenue for answering such questions and could yield more integrated models of the neural correlates of cognitive control. In this study, we used multiset canonical correlation analysis with joint independent component analysis (mCCA + jICA) to identify multimodal patterns of variation related to cognitive control. We used two independent cohorts of participants from the Human Connectome Project, each of which had data from four imaging modalities. We replicated the findings from the first cohort in the second cohort using both independent and predictive analyses. The independent analyses identified a component in each cohort that was highly similar to the other and significantly correlated with cognitive control performance. The replication by prediction analyses identified two independent components that were significantly correlated with cognitive control performance in the first cohort and significantly predictive of performance in the second cohort. These components identified positive relationships across the modalities in neural regions related to both dynamic and stable aspects of task control, including regions in both the frontal-parietal and cingulo-opercular networks, as well as regions

Neural-net based real-time economic dispatch for thermal power plants

Energy Technology Data Exchange (ETDEWEB)

Djukanovic, M.; Milosevic, B. [Inst. Nikola Tesla, Belgrade (Yugoslavia). Dept. of Power Systems; Calovic, M. [Univ. of Belgrade (Yugoslavia). Dept. of Electrical Engineering; Sobajic, D.J. [Electric Power Research Inst., Palo Alto, CA (United States)

1996-12-01

This paper proposes the application of artificial neural networks to real-time optimal generation dispatch of thermal units. The approach can take into account the operational requirements and network losses. The proposed economic dispatch uses an artificial neural network (ANN) for generation of penalty factors, depending on the input generator powers and identified system load change. Then, a few additional iterations are performed within an iterative computation procedure for the solution of coordination equations, by using reference-bus penalty-factors derived from the Newton-Raphson load flow. A coordination technique for environmental and economic dispatch of pure thermal systems, based on the neural-net theory for simplified solution algorithms and improved man-machine interface is introduced. Numerical results on two test examples show that the proposed algorithm can efficiently and accurately develop optimal and feasible generator output trajectories, by applying neural-net forecasts of system load patterns.

Development of an accident diagnosis system using a dynamic neural network for nuclear power plants

International Nuclear Information System (INIS)

Lee, Seung Jun; Kim, Jong Hyun; Seong, Poong Hyun

2004-01-01

In this work, an accident diagnosis system using the dynamic neural network is developed. In order to help the plant operators to quickly identify the problem, perform diagnosis and initiate recovery actions ensuring the safety of the plant, many operator support system and accident diagnosis systems have been developed. Neural networks have been recognized as a good method to implement an accident diagnosis system. However, conventional accident diagnosis systems that used neural networks did not consider a time factor sufficiently. If the neural network could be trained according to time, it is possible to perform more efficient and detailed accidents analysis. Therefore, this work suggests a dynamic neural network which has different features from existing dynamic neural networks. And a simple accident diagnosis system is implemented in order to validate the dynamic neural network. After training of the prototype, several accident diagnoses were performed. The results show that the prototype can detect the accidents correctly with good performances

Real-space mapping of topological invariants using artificial neural networks

Science.gov (United States)

Carvalho, D.; García-Martínez, N. A.; Lado, J. L.; Fernández-Rossier, J.

2018-03-01

Topological invariants allow one to characterize Hamiltonians, predicting the existence of topologically protected in-gap modes. Those invariants can be computed by tracing the evolution of the occupied wave functions under twisted boundary conditions. However, those procedures do not allow one to calculate a topological invariant by evaluating the system locally, and thus require information about the wave functions in the whole system. Here we show that artificial neural networks can be trained to identify the topological order by evaluating a local projection of the density matrix. We demonstrate this for two different models, a one-dimensional topological superconductor and a two-dimensional quantum anomalous Hall state, both with spatially modulated parameters. Our neural network correctly identifies the different topological domains in real space, predicting the location of in-gap states. By combining a neural network with a calculation of the electronic states that uses the kernel polynomial method, we show that the local evaluation of the invariant can be carried out by evaluating a local quantity, in particular for systems without translational symmetry consisting of tens of thousands of atoms. Our results show that supervised learning is an efficient methodology to characterize the local topology of a system.

Neural networks for aircraft control

Science.gov (United States)

Linse, Dennis

1990-01-01

Current research in Artificial Neural Networks indicates that networks offer some potential advantages in adaptation and fault tolerance. This research is directed at determining the possible applicability of neural networks to aircraft control. The first application will be to aircraft trim. Neural network node characteristics, network topology and operation, neural network learning and example histories using neighboring optimal control with a neural net are discussed.

Supplementary data: Variation in the PTEN-induced putative kinase ...

Indian Academy of Sciences (India)

Variation in the PTEN-induced putative kinase 1 gene associated with the increase risk of type 2 diabetes in northern Chinese. Yanchun Qu, Liang Sun, Ze Yang and Ruifa Han. J. Genet. 90, 125–128. Table 1. Clinical characteristics of cases and controls. Phenotype. T2DM. Controls. P value. Age (years). 49.5 ± 11.1. 50.4 ± ...

Parameter diagnostics of phases and phase transition learning by neural networks

Science.gov (United States)

Suchsland, Philippe; Wessel, Stefan

2018-05-01

We present an analysis of neural network-based machine learning schemes for phases and phase transitions in theoretical condensed matter research, focusing on neural networks with a single hidden layer. Such shallow neural networks were previously found to be efficient in classifying phases and locating phase transitions of various basic model systems. In order to rationalize the emergence of the classification process and for identifying any underlying physical quantities, it is feasible to examine the weight matrices and the convolutional filter kernels that result from the learning process of such shallow networks. Furthermore, we demonstrate how the learning-by-confusing scheme can be used, in combination with a simple threshold-value classification method, to diagnose the learning parameters of neural networks. In particular, we study the classification process of both fully-connected and convolutional neural networks for the two-dimensional Ising model with extended domain wall configurations included in the low-temperature regime. Moreover, we consider the two-dimensional XY model and contrast the performance of the learning-by-confusing scheme and convolutional neural networks trained on bare spin configurations to the case of preprocessed samples with respect to vortex configurations. We discuss these findings in relation to similar recent investigations and possible further applications.

A negative modulatory role for rho and rho-associated kinase signaling in delamination of neural crest cells

Directory of Open Access Journals (Sweden)

Kalcheim Chaya

2008-10-01

Full Text Available Abstract Background Neural crest progenitors arise as epithelial cells and then undergo a process of epithelial to mesenchymal transition that precedes the generation of cellular motility and subsequent migration. We aim at understanding the underlying molecular network. Along this line, possible roles of Rho GTPases that act as molecular switches to control a variety of signal transduction pathways remain virtually unexplored, as are putative interactions between Rho proteins and additional known components of this cascade. Results We investigated the role of Rho/Rock signaling in neural crest delamination. Active RhoA and RhoB are expressed in the membrane of epithelial progenitors and are downregulated upon delamination. In vivo loss-of-function of RhoA or RhoB or of overall Rho signaling by C3 transferase enhanced and/or triggered premature crest delamination yet had no effect on cell specification. Consistently, treatment of explanted neural primordia with membrane-permeable C3 or with the Rock inhibitor Y27632 both accelerated and enhanced crest emigration without affecting cell proliferation. These treatments altered neural crest morphology by reducing stress fibers, focal adhesions and downregulating membrane-bound N-cadherin. Reciprocally, activation of endogenous Rho by lysophosphatidic acid inhibited emigration while enhancing the above. Since delamination is triggered by BMP and requires G1/S transition, we examined their relationship with Rho. Blocking Rho/Rock function rescued crest emigration upon treatment with noggin or with the G1/S inhibitor mimosine. In the latter condition, cells emigrated while arrested at G1. Conversely, BMP4 was unable to rescue cell emigration when endogenous Rho activity was enhanced by lysophosphatidic acid. Conclusion Rho-GTPases, through Rock, act downstream of BMP and of G1/S transition to negatively regulate crest delamination by modifying cytoskeleton assembly and intercellular adhesion.

Galectin-1 is expressed in early-type neural progenitor cells and down-regulates neurogenesis in the adult hippocampus

Directory of Open Access Journals (Sweden)

Imaizumi Yoichi

2011-01-01

Full Text Available Abstract Background In the adult mammalian brain, neural stem cells (NSCs proliferate in the dentate gyrus (DG of the hippocampus and generate new neurons throughout life. A multimodal protein, Galectin-1, is expressed in neural progenitor cells (NPCs and implicated in the proliferation of the NPCs in the DG. However, little is known about its detailed expression profile in the NPCs and functions in adult neurogenesis in the DG. Results Our immunohistochemical and morphological analysis showed that Galectin-1 was expressed in the type 1 and 2a cells, which are putative NSCs, in the subgranular zone (SGZ of the adult mouse DG. To study Galectin-1's function in adult hippocampal neurogenesis, we made galectin-1 knock-out mice on the C57BL6 background and characterized the effects on neurogenesis. In the SGZ of the galectin-1 knock-out mice, increased numbers of type 1 cells, DCX-positive immature progenitors, and NeuN-positive newborn neurons were observed. Using triple-labeling immunohistochemistry and morphological analyses, we found that the proliferation of the type-1 cells was increased in the SGZ of the galectin-1 knock-out mice, and we propose that this proliferation is the mechanism for the net increase in the adult neurogenesis in these knock-out mice DG. Conclusions Galectin-1 is expressed in the neural stem cells and down-regulates neurogenesis in the adult hippocampus.

Amplification of tumor inducing putative cancer stem cells (CSCs) by vitamin A/retinol from mammary tumors

Energy Technology Data Exchange (ETDEWEB)

Sharma, Rohit B. [Department of Microbiology and Molecular Genetics, University of Pittsburgh, PA 15261 (United States); Wang, Qingde [Department of Surgery, University of Pittsburgh, PA 15261 (United States); Khillan, Jaspal S., E-mail: khillan@pitt.edu [Department of Microbiology and Molecular Genetics, University of Pittsburgh, PA 15261 (United States)

2013-07-12

Highlights: •Vitamin A supports self renewal of putative CSCs from mammary tumors. •These cells exhibit impaired retinol metabolism into retinoic acid. •CSCs from mammary tumors differentiate into mammary specific cell lineages. •The cells express mammary stem cell specific CD29 and CD49f markers. •Putative CSCs form highly metastatic tumors in NOD SCID mouse. -- Abstract: Solid tumors contain a rare population of cancer stem cells (CSCs) that are responsible for relapse and metastasis. The existence of CSC however, remains highly controversial issue. Here we present the evidence for putative CSCs from mammary tumors amplified by vitamin A/retinol signaling. The cells exhibit mammary stem cell specific CD29{sup hi}/CD49f{sup hi}/CD24{sup hi} markers, resistance to radiation and chemo therapeutic agents and form highly metastatic tumors in NOD/SCID mice. The cells exhibit indefinite self renewal as cell lines. Furthermore, the cells exhibit impaired retinol metabolism and do not express enzymes that metabolize retinol into retinoic acid. Vitamin A/retinol also amplified putative CSCs from breast cancer cell lines that form highly aggressive tumors in NOD SCID mice. The studies suggest that high purity putative CSCs can be isolated from solid tumors to establish patient specific cell lines for personalized therapeutics for pre-clinical translational applications. Characterization of CSCs will allow understanding of basic cellular and molecular pathways that are deregulated, mechanisms of tumor metastasis and evasion of therapies that has direct clinical relevance.

Applications of Mesenchymal Stem Cells and Neural Crest Cells in Craniofacial Skeletal Research

Directory of Open Access Journals (Sweden)

Satoru Morikawa

2016-01-01

Full Text Available Craniofacial skeletal tissues are composed of tooth and bone, together with nerves and blood vessels. This composite material is mainly derived from neural crest cells (NCCs. The neural crest is transient embryonic tissue present during neural tube formation whose cells have high potential for migration and differentiation. Thus, NCCs are promising candidates for craniofacial tissue regeneration; however, the clinical application of NCCs is hindered by their limited accessibility. In contrast, mesenchymal stem cells (MSCs are easily accessible in adults, have similar potential for self-renewal, and can differentiate into skeletal tissues, including bones and cartilage. Therefore, MSCs may represent good sources of stem cells for clinical use. MSCs are classically identified under adherent culture conditions, leading to contamination with other cell lineages. Previous studies have identified mouse- and human-specific MSC subsets using cell surface markers. Additionally, some studies have shown that a subset of MSCs is closely related to neural crest derivatives and endothelial cells. These MSCs may be promising candidates for regeneration of craniofacial tissues from the perspective of developmental fate. Here, we review the fundamental biology of MSCs in craniofacial research.

Alkenenitrile Transmissive Olefination: Synthesis of the Putative Lignan "Morinol I"

Science.gov (United States)

Fleming, Fraser F.; Liu, Wang; Yao, Lihua; Pitta, Bhaskar; Purzycki, Matthew; Ravikumar, P. C.

2012-01-01

Grignard reagents trigger an addition-elimination with α'-hydroxy acrylonitriles to selectively generate Z-alkenenitriles. The modular assembly of Z-alkenenitriles from a Grignard reagent, acrylonitrile, and an aldehyde is ideal for stereoselectively synthesizing alkenes as illustrated in the synthesis of the putative lignan "morinol I." PMID:22545004

A Neural Region of Abstract Working Memory

Science.gov (United States)

Cowan, Nelson; Li, Dawei; Moffitt, Amanda; Becker, Theresa M.; Martin, Elizabeth A.; Saults, J. Scott; Christ, Shawn E.

2011-01-01

Over 350 years ago, Descartes proposed that the neural basis of consciousness must be a brain region in which sensory inputs are combined. Using fMRI, we identified at least one such area for working memory, the limited information held in mind, described by William James as the trailing edge of consciousness. Specifically, a region in the left…

Dissociable neural representations of reinforcement and belief prediction errors underlie strategic learning.

Science.gov (United States)

Zhu, Lusha; Mathewson, Kyle E; Hsu, Ming

2012-01-31

Decision-making in the presence of other competitive intelligent agents is fundamental for social and economic behavior. Such decisions require agents to behave strategically, where in addition to learning about the rewards and punishments available in the environment, they also need to anticipate and respond to actions of others competing for the same rewards. However, whereas we know much about strategic learning at both theoretical and behavioral levels, we know relatively little about the underlying neural mechanisms. Here, we show using a multi-strategy competitive learning paradigm that strategic choices can be characterized by extending the reinforcement learning (RL) framework to incorporate agents' beliefs about the actions of their opponents. Furthermore, using this characterization to generate putative internal values, we used model-based functional magnetic resonance imaging to investigate neural computations underlying strategic learning. We found that the distinct notions of prediction errors derived from our computational model are processed in a partially overlapping but distinct set of brain regions. Specifically, we found that the RL prediction error was correlated with activity in the ventral striatum. In contrast, activity in the ventral striatum, as well as the rostral anterior cingulate (rACC), was correlated with a previously uncharacterized belief-based prediction error. Furthermore, activity in rACC reflected individual differences in degree of engagement in belief learning. These results suggest a model of strategic behavior where learning arises from interaction of dissociable reinforcement and belief-based inputs.

The Neural Border: Induction, Specification and Maturation of the territory that generates Neural Crest cells.

Science.gov (United States)

Pla, Patrick; Monsoro-Burq, Anne H

2018-05-28

The neural crest is induced at the edge between the neural plate and the nonneural ectoderm, in an area called the neural (plate) border, during gastrulation and neurulation. In recent years, many studies have explored how this domain is patterned, and how the neural crest is induced within this territory, that also participates to the prospective dorsal neural tube, the dorsalmost nonneural ectoderm, as well as placode derivatives in the anterior area. This review highlights the tissue interactions, the cell-cell signaling and the molecular mechanisms involved in this dynamic spatiotemporal patterning, resulting in the induction of the premigratory neural crest. Collectively, these studies allow building a complex neural border and early neural crest gene regulatory network, mostly composed by transcriptional regulations but also, more recently, including novel signaling interactions. Copyright © 2018. Published by Elsevier Inc.

Neural network based automated algorithm to identify joint locations on hand/wrist radiographs for arthritis assessment

International Nuclear Information System (INIS)

Duryea, J.; Zaim, S.; Wolfe, F.

2002-01-01

Arthritis is a significant and costly healthcare problem that requires objective and quantifiable methods to evaluate its progression. Here we describe software that can automatically determine the locations of seven joints in the proximal hand and wrist that demonstrate arthritic changes. These are the five carpometacarpal (CMC1, CMC2, CMC3, CMC4, CMC5), radiocarpal (RC), and the scaphocapitate (SC) joints. The algorithm was based on an artificial neural network (ANN) that was trained using independent sets of digitized hand radiographs and manually identified joint locations. The algorithm used landmarks determined automatically by software developed in our previous work as starting points. Other than requiring user input of the location of nonanatomical structures and the orientation of the hand on the film, the procedure was fully automated. The software was tested on two datasets: 50 digitized hand radiographs from patients participating in a large clinical study, and 60 from subjects participating in arthritis research studies and who had mild to moderate rheumatoid arthritis (RA). It was evaluated by a comparison to joint locations determined by a trained radiologist using manual tracing. The success rate for determining the CMC, RC, and SC joints was 87%-99%, for normal hands and 81%-99% for RA hands. This is a first step in performing an automated computer-aided assessment of wrist joints for arthritis progression. The software provides landmarks that will be used by subsequent image processing routines to analyze each joint individually for structural changes such as erosions and joint space narrowing

Characterization of ERAS, a putative novel human oncogene, in skin and breast

Energy Technology Data Exchange (ETDEWEB)

Peña Avalos, B.L. de la

2014-07-01

Most human tumors have mutations in genes of the RAS small GTPase protein family. RAS works as a molecular switch for signaling pathways that modulate many aspects of cell behavior, including proliferation, differentiation, motility and death. Oncogenic mutations in RAS prevent GTP hydrolysis, locking RAS in a permanently active state, being the most common mutations in HRAS, KRAS and NRAS. The human RAS family consists of at least 36 different genes, many of which have been scarcely studied. One of these relatively unknown genes is ERAS (ES cell-expressed RAS), which is a constitutively active RAS protein, localized in chromosome X and expressed only in embryonic cells, being undetectable in adult tissues. New high throughput technologies have made it possible to screen complete cancer genomes for identification of mutations associated to cancer. Using the Sleeping Beauty (SB) transposon system, ERAS was identified as a putative novel oncogene in non-melanoma skin and breast cancers. The major aim of this project is to determine the general characteristics of ERAS as a putative novel human oncogene in skin and breast cells. Forced expression of ERAS results in drastic changes in cell shape, proliferation and motility. When ERAS is overexpressed in skin and breast human cells it is mainly localized in the cytoplasmic membrane. ERAS activates the phosphatidylinositol-3-OH kinase (PI3K) pathway but not the mitogen-activated protein kinase (MAPK) pathway. ERAS-expressing cells suffer spontaneous morphologic and phenotypic EMT-like changes, including cytoskeleton reorganization, vimentin and N-cadherin up-regulation and down-regulation of E-cadherin, which can be associated with increased malignancy, and invasive and metastatic potential. Our results suggest that inappropriate expression of ERAS lead to transformation of human cells. (Author)

Analyses of germline variants associated with ovarian cancer survival identify functional candidates at the 1q22 and 19p12 outcome loci

DEFF Research Database (Denmark)

Glubb, Dylan M; Johnatty, Sharon E; Quinn, Michael C J

2017-01-01

We previously identified associations with ovarian cancer outcome at five genetic loci. To identify putatively causal genetic variants and target genes, we prioritized two ovarian outcome loci (1q22 and 19p12) for further study. Bioinformatic and functional genetic analyses indicated that MEF2D...... and ZNF100 are targets of candidate outcome variants at 1q22 and 19p12, respectively. At 19p12, the chromatin interaction of a putative regulatory element with the ZNF100 promoter region correlated with candidate outcome variants. At 1q22, putative regulatory elements enhanced MEF2D promoter activity...... and haplotypes containing candidate outcome variants modulated these effects. In a public dataset, MEF2D and ZNF100 expression were both associated with ovarian cancer progression-free or overall survival time. In an extended set of 6,162 epithelial ovarian cancer patients, we found that functional candidates...

Effect of specific amino acid substitutions in the putative fusion peptide of structural glycoprotein E2 on Classical Swine Fever Virus replication

International Nuclear Information System (INIS)

Fernández-Sainz, I.J.; Largo, E.; Gladue, D.P.; Fletcher, P.; O’Donnell, V.; Holinka, L.G.; Carey, L.B.; Lu, X.; Nieva, J.L.; Borca, M.V.

2014-01-01

E2, along with E rns and E1, is an envelope glycoprotein of Classical Swine Fever Virus (CSFV). E2 is involved in several virus functions: cell attachment, host range susceptibility and virulence in natural hosts. Here we evaluate the role of a specific E2 region, 818 CPIGWTGVIEC 828 , containing a putative fusion peptide (FP) sequence. Reverse genetics utilizing a full-length infectious clone of the highly virulent CSFV strain Brescia (BICv) was used to evaluate how individual amino acid substitutions within this region of E2 may affect replication of BICv. A synthetic peptide representing the complete E2 FP amino acid sequence adopted a β-type extended conformation in membrane mimetics, penetrated into model membranes, and perturbed lipid bilayer integrity in vitro. Similar peptides harboring amino acid substitutions adopted comparable conformations but exhibited different membrane activities. Therefore, a preliminary characterization of the putative FP 818 CPIGWTGVIEC 828 indicates a membrane fusion activity and a critical role in virus replication. - Highlights: • A putative fusion peptide (FP) region in CSFV E2 protein was shown to be critical for virus growth. • Synthetic FPs were shown to efficiently penetrate into lipid membranes using an in vitro model. • Individual residues in the FP affecting virus replication were identified by reverse genetics. • The same FP residues are also responsible for mediating membrane fusion

Effect of specific amino acid substitutions in the putative fusion peptide of structural glycoprotein E2 on Classical Swine Fever Virus replication

Energy Technology Data Exchange (ETDEWEB)

Fernández-Sainz, I.J. [Plum Island Animal Disease Center, ARS, USDA (United States); Largo, E. [Biophysics Unit (CSIC-UPV/EHU), Department of Biochemistry and Molecular Biology, University of the Basque Country (UPV/EHU), P.O. Box 644, 48080 Bilbao (Spain); Gladue, D.P.; Fletcher, P. [Plum Island Animal Disease Center, ARS, USDA (United States); O’Donnell, V. [Plum Island Animal Disease Center, ARS, USDA (United States); Plum Island Animal Disease Center, DHS, Greenport, NY 11944 (United States); Holinka, L.G. [Plum Island Animal Disease Center, ARS, USDA (United States); Carey, L.B. [Department of Experimental and Health Sciences, Universitat Pompeu Fabra (UPF), E-08003 Barcelona (Spain); Lu, X. [Plum Island Animal Disease Center, DHS, Greenport, NY 11944 (United States); Nieva, J.L. [Biophysics Unit (CSIC-UPV/EHU), Department of Biochemistry and Molecular Biology, University of the Basque Country (UPV/EHU), P.O. Box 644, 48080 Bilbao (Spain); Borca, M.V., E-mail: manuel.borca@ars.usda.gov [Plum Island Animal Disease Center, ARS, USDA (United States)

2014-05-15

E2, along with E{sup rns} and E1, is an envelope glycoprotein of Classical Swine Fever Virus (CSFV). E2 is involved in several virus functions: cell attachment, host range susceptibility and virulence in natural hosts. Here we evaluate the role of a specific E2 region, {sup 818}CPIGWTGVIEC{sup 828}, containing a putative fusion peptide (FP) sequence. Reverse genetics utilizing a full-length infectious clone of the highly virulent CSFV strain Brescia (BICv) was used to evaluate how individual amino acid substitutions within this region of E2 may affect replication of BICv. A synthetic peptide representing the complete E2 FP amino acid sequence adopted a β-type extended conformation in membrane mimetics, penetrated into model membranes, and perturbed lipid bilayer integrity in vitro. Similar peptides harboring amino acid substitutions adopted comparable conformations but exhibited different membrane activities. Therefore, a preliminary characterization of the putative FP {sup 818}CPIGWTGVIEC{sup 828} indicates a membrane fusion activity and a critical role in virus replication. - Highlights: • A putative fusion peptide (FP) region in CSFV E2 protein was shown to be critical for virus growth. • Synthetic FPs were shown to efficiently penetrate into lipid membranes using an in vitro model. • Individual residues in the FP affecting virus replication were identified by reverse genetics. • The same FP residues are also responsible for mediating membrane fusion.

Neural network regulation driven by autonomous neural firings

Science.gov (United States)

Cho, Myoung Won

2016-07-01

Biological neurons naturally fire spontaneously due to the existence of a noisy current. Such autonomous firings may provide a driving force for network formation because synaptic connections can be modified due to neural firings. Here, we study the effect of autonomous firings on network formation. For the temporally asymmetric Hebbian learning, bidirectional connections lose their balance easily and become unidirectional ones. Defining the difference between reciprocal connections as new variables, we could express the learning dynamics as if Ising model spins interact with each other in magnetism. We present a theoretical method to estimate the interaction between the new variables in a neural system. We apply the method to some network systems and find some tendencies of autonomous neural network regulation.

Automated Understanding of Financial Statements Using Neural Networks and Semantic Grammars

OpenAIRE

Markovitch, J. S.

1995-01-01

This article discusses how neural networks and semantic grammars may be used to locate and understand financial statements embedded in news stories received from on-line news wires. A neural net is used to identify where in the news story a financial statement appears to begin. A grammar then is applied to this text in an effort to extract specific facts from the financial statement. Applying grammars to financial statements presents unique parsing problems since the dollar amounts of financi...

Discrimination of ex-core neutron noise signatures using artificial neural networks

International Nuclear Information System (INIS)

Alguindigue, I.E.; Uhrig, R.E.; Cai, M.; Trenty, A.

1993-01-01

The vibratory behavior of the internals in a Pressurized Water Reactor, PWR, can be identified and monitored using ex-core neutron noise data from power detectors located at ionization chambers outside the vessel. The signatures collected from these sensors provide information regarding presence of contacts between the core barrel and the pressure vessel, and more importantly, a means of verifying the integrity of components in the system. This report describes a neural-network-based methodology for identifying the vibration mode of the core barrel, and for detecting a particular family of mechanical failures. Features are extracted from the neutron noise spectra and used for training neural network models to identify the different states of vibratory behavior typically exhibited by PWR'S. The technique was tested on data from twenty eight 900MW pressurized water reactors in France, and the results achieved are over 98% accurate

Measures of Coupling between Neural Populations Based on Granger Causality Principle.

Science.gov (United States)

Kaminski, Maciej; Brzezicka, Aneta; Kaminski, Jan; Blinowska, Katarzyna J

2016-01-01

This paper shortly reviews the measures used to estimate neural synchronization in experimental settings. Our focus is on multivariate measures of dependence based on the Granger causality (G-causality) principle, their applications and performance in respect of robustness to noise, volume conduction, common driving, and presence of a "weak node." Application of G-causality measures to EEG, intracranial signals and fMRI time series is addressed. G-causality based measures defined in the frequency domain allow the synchronization between neural populations and the directed propagation of their electrical activity to be determined. The time-varying G-causality based measure Short-time Directed Transfer Function (SDTF) supplies information on the dynamics of synchronization and the organization of neural networks. Inspection of effective connectivity patterns indicates a modular structure of neural networks, with a stronger coupling within modules than between them. The hypothetical plausible mechanism of information processing, suggested by the identified synchronization patterns, is communication between tightly coupled modules intermitted by sparser interactions providing synchronization of distant structures.

Dynamics of neural cryptography.

Science.gov (United States)

Ruttor, Andreas; Kinzel, Wolfgang; Kanter, Ido

2007-05-01

Synchronization of neural networks has been used for public channel protocols in cryptography. In the case of tree parity machines the dynamics of both bidirectional synchronization and unidirectional learning is driven by attractive and repulsive stochastic forces. Thus it can be described well by a random walk model for the overlap between participating neural networks. For that purpose transition probabilities and scaling laws for the step sizes are derived analytically. Both these calculations as well as numerical simulations show that bidirectional interaction leads to full synchronization on average. In contrast, successful learning is only possible by means of fluctuations. Consequently, synchronization is much faster than learning, which is essential for the security of the neural key-exchange protocol. However, this qualitative difference between bidirectional and unidirectional interaction vanishes if tree parity machines with more than three hidden units are used, so that those neural networks are not suitable for neural cryptography. In addition, the effective number of keys which can be generated by the neural key-exchange protocol is calculated using the entropy of the weight distribution. As this quantity increases exponentially with the system size, brute-force attacks on neural cryptography can easily be made unfeasible.

Dynamics of neural cryptography

International Nuclear Information System (INIS)

Ruttor, Andreas; Kinzel, Wolfgang; Kanter, Ido

2007-01-01

Synchronization of neural networks has been used for public channel protocols in cryptography. In the case of tree parity machines the dynamics of both bidirectional synchronization and unidirectional learning is driven by attractive and repulsive stochastic forces. Thus it can be described well by a random walk model for the overlap between participating neural networks. For that purpose transition probabilities and scaling laws for the step sizes are derived analytically. Both these calculations as well as numerical simulations show that bidirectional interaction leads to full synchronization on average. In contrast, successful learning is only possible by means of fluctuations. Consequently, synchronization is much faster than learning, which is essential for the security of the neural key-exchange protocol. However, this qualitative difference between bidirectional and unidirectional interaction vanishes if tree parity machines with more than three hidden units are used, so that those neural networks are not suitable for neural cryptography. In addition, the effective number of keys which can be generated by the neural key-exchange protocol is calculated using the entropy of the weight distribution. As this quantity increases exponentially with the system size, brute-force attacks on neural cryptography can easily be made unfeasible

Dynamics of neural cryptography

Science.gov (United States)

Ruttor, Andreas; Kinzel, Wolfgang; Kanter, Ido

2007-05-01

Synchronization of neural networks has been used for public channel protocols in cryptography. In the case of tree parity machines the dynamics of both bidirectional synchronization and unidirectional learning is driven by attractive and repulsive stochastic forces. Thus it can be described well by a random walk model for the overlap between participating neural networks. For that purpose transition probabilities and scaling laws for the step sizes are derived analytically. Both these calculations as well as numerical simulations show that bidirectional interaction leads to full synchronization on average. In contrast, successful learning is only possible by means of fluctuations. Consequently, synchronization is much faster than learning, which is essential for the security of the neural key-exchange protocol. However, this qualitative difference between bidirectional and unidirectional interaction vanishes if tree parity machines with more than three hidden units are used, so that those neural networks are not suitable for neural cryptography. In addition, the effective number of keys which can be generated by the neural key-exchange protocol is calculated using the entropy of the weight distribution. As this quantity increases exponentially with the system size, brute-force attacks on neural cryptography can easily be made unfeasible.

Adipose stromal cells contain phenotypically distinct adipogenic progenitors derived from neural crest.

Directory of Open Access Journals (Sweden)

Yoshihiro Sowa

Full Text Available Recent studies have shown that adipose-derived stromal/stem cells (ASCs contain phenotypically and functionally heterogeneous subpopulations of cells, but their developmental origin and their relative differentiation potential remain elusive. In the present study, we aimed at investigating how and to what extent the neural crest contributes to ASCs using Cre-loxP-mediated fate mapping. ASCs harvested from subcutaneous fat depots of either adult P0-Cre/or Wnt1-Cre/Floxed-reporter mice contained a few neural crest-derived ASCs (NCDASCs. This subpopulation of cells was successfully expanded in vitro under standard culture conditions and their growth rate was comparable to non-neural crest derivatives. Although NCDASCs were positive for several mesenchymal stem cell markers as non-neural crest derivatives, they exhibited a unique bipolar or multipolar morphology with higher expression of markers for both neural crest progenitors (p75NTR, Nestin, and Sox2 and preadipocytes (CD24, CD34, S100, Pref-1, GATA2, and C/EBP-delta. NCDASCs were able to differentiate into adipocytes with high efficiency but their osteogenic and chondrogenic potential was markedly attenuated, indicating their commitment to adipogenesis. In vivo, a very small proportion of adipocytes were originated from the neural crest. In addition, p75NTR-positive neural crest-derived cells were identified along the vessels within the subcutaneous adipose tissue, but they were negative for mural and endothelial markers. These results demonstrate that ASCs contain neural crest-derived adipocyte-restricted progenitors whose phenotype is distinct from that of non-neural crest derivatives.

Face Recognition using Artificial Neural Network | Endeshaw | Zede ...

African Journals Online (AJOL)

Face recognition (FR) is one of the biometric methods to identify the individuals by the features of face. Two Face Recognition Systems (FRS) based on Artificial Neural Network (ANN) have been proposed in this paper based on feature extraction techniques. In the first system, Principal Component Analysis (PCA) has been ...

Butterfly Classification by HSI and RGB Color Models Using Neural Networks

Directory of Open Access Journals (Sweden)

Jorge E. Grajales-Múnera

2013-11-01

Full Text Available This study aims the classification of Butterfly species through the implementation of Neural Networks and Image Processing. A total of 9 species of Morpho genre which has blue as a characteristic color are processed. For Butterfly segmentation we used image processing tools such as: Binarization, edge processing and mathematical morphology. For data processing RGB values are obtained for every image which are converted to HSI color model to identify blue pixels and obtain the data to the proposed Neural Networks: Back-Propagation and Perceptron. For analysis and verification of results confusion matrix are built and analyzed with the results of neural networks with the lowest error levels. We obtain error levels close to 1% in classification of some Butterfly species.

Fault diagnosis system of electromagnetic valve using neural network filter

International Nuclear Information System (INIS)

Hayashi, Shoji; Odaka, Tomohiro; Kuroiwa, Jousuke; Ogura, Hisakazu

2008-01-01

This paper is concerned with the gas leakage fault detection of electromagnetic valve using a neural network filter. In modern plants, the ability to detect and identify gas leakage faults is becoming increasingly important. The main difficulty in detecting gas leakage faults by sound signals lies in the fact that the practical plants are usually very noisy. To solve this difficulty, a neural network filter is used to eliminate background noise and raise the signal noise ratio of the sound signal. The background noise is assumed as a dynamic system, and an accurate mathematical model of the dynamic system can be established using a neural network filter. The predicted error between predicted values and practical ones constitutes the output of the filter. If the predicted error is zero, then there is no leakage. If the predicted error is greater than a certain value, then there is a leakage fault. Through application to practical pneumatic systems, it is verified that the neural network filter was effective in gas leakage detection. (author)

Implementing Signature Neural Networks with Spiking Neurons.

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Carrillo-Medina, José Luis; Latorre, Roberto

2016-01-01

Spiking Neural Networks constitute the most promising approach to develop realistic Artificial Neural Networks (ANNs). Unlike traditional firing rate-based paradigms, information coding in spiking models is based on the precise timing of individual spikes. It has been demonstrated that spiking ANNs can be successfully and efficiently applied to multiple realistic problems solvable with traditional strategies (e.g., data classification or pattern recognition). In recent years, major breakthroughs in neuroscience research have discovered new relevant computational principles in different living neural systems. Could ANNs benefit from some of these recent findings providing novel elements of inspiration? This is an intriguing question for the research community and the development of spiking ANNs including novel bio-inspired information coding and processing strategies is gaining attention. From this perspective, in this work, we adapt the core concepts of the recently proposed Signature Neural Network paradigm-i.e., neural signatures to identify each unit in the network, local information contextualization during the processing, and multicoding strategies for information propagation regarding the origin and the content of the data-to be employed in a spiking neural network. To the best of our knowledge, none of these mechanisms have been used yet in the context of ANNs of spiking neurons. This paper provides a proof-of-concept for their applicability in such networks. Computer simulations show that a simple network model like the discussed here exhibits complex self-organizing properties. The combination of multiple simultaneous encoding schemes allows the network to generate coexisting spatio-temporal patterns of activity encoding information in different spatio-temporal spaces. As a function of the network and/or intra-unit parameters shaping the corresponding encoding modality, different forms of competition among the evoked patterns can emerge even in the absence

Bioprinting for Neural Tissue Engineering.

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Knowlton, Stephanie; Anand, Shivesh; Shah, Twisha; Tasoglu, Savas

2018-01-01

Bioprinting is a method by which a cell-encapsulating bioink is patterned to create complex tissue architectures. Given the potential impact of this technology on neural research, we review the current state-of-the-art approaches for bioprinting neural tissues. While 2D neural cultures are ubiquitous for studying neural cells, 3D cultures can more accurately replicate the microenvironment of neural tissues. By bioprinting neuronal constructs, one can precisely control the microenvironment by specifically formulating the bioink for neural tissues, and by spatially patterning cell types and scaffold properties in three dimensions. We review a range of bioprinted neural tissue models and discuss how they can be used to observe how neurons behave, understand disease processes, develop new therapies and, ultimately, design replacement tissues. Copyright © 2017 Elsevier Ltd. All rights reserved.

Identification of a putative nuclear export signal motif in human NANOG homeobox domain

International Nuclear Information System (INIS)

Park, Sung-Won; Do, Hyun-Jin; Huh, Sun-Hyung; Sung, Boreum; Uhm, Sang-Jun; Song, Hyuk; Kim, Nam-Hyung; Kim, Jae-Hwan

2012-01-01

Highlights: ► We found the putative nuclear export signal motif within human NANOG homeodomain. ► Leucine-rich residues are important for human NANOG homeodomain nuclear export. ► CRM1-specific inhibitor LMB blocked the potent human NANOG NES-mediated nuclear export. -- Abstract: NANOG is a homeobox-containing transcription factor that plays an important role in pluripotent stem cells and tumorigenic cells. To understand how nuclear localization of human NANOG is regulated, the NANOG sequence was examined and a leucine-rich nuclear export signal (NES) motif ( 125 MQELSNILNL 134 ) was found in the homeodomain (HD). To functionally validate the putative NES motif, deletion and site-directed mutants were fused to an EGFP expression vector and transfected into COS-7 cells, and the localization of the proteins was examined. While hNANOG HD exclusively localized to the nucleus, a mutant with both NLSs deleted and only the putative NES motif contained (hNANOG HD-ΔNLSs) was predominantly cytoplasmic, as observed by nucleo/cytoplasmic fractionation and Western blot analysis as well as confocal microscopy. Furthermore, site-directed mutagenesis of the putative NES motif in a partial hNANOG HD only containing either one of the two NLS motifs led to localization in the nucleus, suggesting that the NES motif may play a functional role in nuclear export. Furthermore, CRM1-specific nuclear export inhibitor LMB blocked the hNANOG potent NES-mediated export, suggesting that the leucine-rich motif may function in CRM1-mediated nuclear export of hNANOG. Collectively, a NES motif is present in the hNANOG HD and may be functionally involved in CRM1-mediated nuclear export pathway.

Encoding sensory and motor patterns as time-invariant trajectories in recurrent neural networks.

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Goudar, Vishwa; Buonomano, Dean V

2018-03-14

Much of the information the brain processes and stores is temporal in nature-a spoken word or a handwritten signature, for example, is defined by how it unfolds in time. However, it remains unclear how neural circuits encode complex time-varying patterns. We show that by tuning the weights of a recurrent neural network (RNN), it can recognize and then transcribe spoken digits. The model elucidates how neural dynamics in cortical networks may resolve three fundamental challenges: first, encode multiple time-varying sensory and motor patterns as stable neural trajectories; second, generalize across relevant spatial features; third, identify the same stimuli played at different speeds-we show that this temporal invariance emerges because the recurrent dynamics generate neural trajectories with appropriately modulated angular velocities. Together our results generate testable predictions as to how recurrent networks may use different mechanisms to generalize across the relevant spatial and temporal features of complex time-varying stimuli. © 2018, Goudar et al.

Finding strong lenses in CFHTLS using convolutional neural networks

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Jacobs, C.; Glazebrook, K.; Collett, T.; More, A.; McCarthy, C.

2017-10-01

We train and apply convolutional neural networks, a machine learning technique developed to learn from and classify image data, to Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) imaging for the identification of potential strong lensing systems. An ensemble of four convolutional neural networks was trained on images of simulated galaxy-galaxy lenses. The training sets consisted of a total of 62 406 simulated lenses and 64 673 non-lens negative examples generated with two different methodologies. An ensemble of trained networks was applied to all of the 171 deg2 of the CFHTLS wide field image data, identifying 18 861 candidates including 63 known and 139 other potential lens candidates. A second search of 1.4 million early-type galaxies selected from the survey catalogue as potential deflectors, identified 2465 candidates including 117 previously known lens candidates, 29 confirmed lenses/high-quality lens candidates, 266 novel probable or potential lenses and 2097 candidates we classify as false positives. For the catalogue-based search we estimate a completeness of 21-28 per cent with respect to detectable lenses and a purity of 15 per cent, with a false-positive rate of 1 in 671 images tested. We predict a human astronomer reviewing candidates produced by the system would identify 20 probable lenses and 100 possible lenses per hour in a sample selected by the robot. Convolutional neural networks are therefore a promising tool for use in the search for lenses in current and forthcoming surveys such as the Dark Energy Survey and the Large Synoptic Survey Telescope.

Characterization of a putative cis-regulatory element that controls transcriptional activity of the pig uroplakin II gene promoter

International Nuclear Information System (INIS)

Kwon, Deug-Nam; Park, Mi-Ryung; Park, Jong-Yi; Cho, Ssang-Goo; Park, Chankyu; Oh, Jae-Wook; Song, Hyuk; Kim, Jae-Hwan; Kim, Jin-Hoi

2011-01-01

Highlights: → The sequences of -604 to -84 bp of the pUPII promoter contained the region of a putative negative cis-regulatory element. → The core promoter was located in the 5F-1. → Transcription factor HNF4 can directly bind in the pUPII core promoter region, which plays a critical role in controlling promoter activity. → These features of the pUPII promoter are fundamental to development of a target-specific vector. -- Abstract: Uroplakin II (UPII) is a one of the integral membrane proteins synthesized as a major differentiation product of mammalian urothelium. UPII gene expression is bladder specific and differentiation dependent, but little is known about its transcription response elements and molecular mechanism. To identify the cis-regulatory elements in the pig UPII (pUPII) gene promoter region, we constructed pUPII 5' upstream region deletion mutants and demonstrated that each of the deletion mutants participates in controlling the expression of the pUPII gene in human bladder carcinoma RT4 cells. We also identified a new core promoter region and putative negative cis-regulatory element within a minimal promoter region. In addition, we showed that hepatocyte nuclear factor 4 (HNF4) can directly bind in the pUPII core promoter (5F-1) region, which plays a critical role in controlling promoter activity. Transient cotransfection experiments showed that HNF4 positively regulates pUPII gene promoter activity. Thus, the binding element and its binding protein, HNF4 transcription factor, may be involved in the mechanism that specifically regulates pUPII gene transcription.

Mechanisms to medicines: elucidating neural and molecular substrates of fear extinction to identify novel treatments for anxiety disorders

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Bukalo, Olena; Pinard, Courtney R; Holmes, Andrew

2014-01-01

The burden of anxiety disorders is growing, but the efficacy of available anxiolytic treatments remains inadequate. Cognitive behavioural therapy for anxiety disorders focuses on identifying and modifying maladaptive patterns of thinking and behaving, and has a testable analogue in rodents in the form of fear extinction. A large preclinical literature has amassed in recent years describing the neural and molecular basis of fear extinction in rodents. In this review, we discuss how this work is being harnessed to foster translational research on anxiety disorders and facilitate the search for new anxiolytic treatments. We begin by summarizing the anatomical and functional connectivity of a medial prefrontal cortex (mPFC)–amygdala circuit that subserves fear extinction, including new insights from optogenetics. We then cover some of the approaches that have been taken to model impaired fear extinction and associated impairments with mPFC–amygdala dysfunction. The principal goal of the review is to evaluate evidence that various neurotransmitter and neuromodulator systems mediate fear extinction by modulating the mPFC–amygdala circuitry. To that end, we describe studies that have tested how fear extinction is impaired or facilitated by pharmacological manipulations of dopamine, noradrenaline, 5-HT, GABA, glutamate, neuropeptides, endocannabinoids and various other systems, which either directly target the mPFC–amygdala circuit, or produce behavioural effects that are coincident with functional changes in the circuit. We conclude that there are good grounds to be optimistic that the progress in defining the molecular substrates of mPFC–amygdala circuit function can be effectively leveraged to identify plausible candidates for extinction-promoting therapies for anxiety disorders. Linked Articles This article is part of a themed section on Animal Models in Psychiatry Research. To view the other articles in this section visit http://dx.doi.org/10.1111/bph.2014

In silico Prediction, in vitro Antibacterial Spectrum, and Physicochemical Properties of a Putative Bacteriocin Produced by Lactobacillus rhamnosus Strain L156.4

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Letícia de C. Oliveira

2017-05-01

Full Text Available A bacteriocinogenic Lactobacillus rhamnosus L156.4 strain isolated from the feces of NIH mice was identified by 16S rRNA gene sequencing and MALDI-TOF mass spectrometry. The entire genome was sequenced using Illumina, annotated in the PGAAP, and RAST servers, and deposited. Conserved genes associated with bacteriocin synthesis were predicted using BAGEL3, leading to the identification of an open reading frame (ORF that shows homology with the L. rhamnosus GG (ATCC 53103 prebacteriocin gene. The encoded protein contains a conserved protein motif associated a structural gene of the Enterocin A superfamily. We found ORFs related to the prebacteriocin, immunity protein, ABC transporter proteins, and regulatory genes with 100% identity to those of L. rhamnosus HN001. In this study, we provide evidence of a putative bacteriocin produced by L. rhamnosus L156.4 that was further confirmed by in vitro assays. The antibacterial activity of the substances produced by this strain was evaluated using the deferred agar-spot and spot-on-the lawn assays, and a wide antimicrobial activity spectrum against human and foodborne pathogens was observed. The physicochemical characterization of the putative bacteriocin indicated that it was sensitive to proteolytic enzymes, heat stable and maintained its antibacterial activity in a pH ranging from 3 to 9. The activity against Lactobacillus fermentum, which was used as an indicator strain, was detected during bacterial logarithmic growth phase, and a positive correlation was confirmed between bacterial growth and production of the putative bacteriocin. After a partial purification from cell-free supernatant by salt precipitation, the putative bacteriocin migrated as a diffuse band of approximately 1.0–3.0 kDa by SDS-PAGE. Additional studies are being conducted to explore its use in the food industry for controlling bacterial growth and for probiotic applications.

In silico Prediction, in vitro Antibacterial Spectrum, and Physicochemical Properties of a Putative Bacteriocin Produced by Lactobacillus rhamnosus Strain L156.4

Science.gov (United States)

Oliveira, Letícia de C.; Silveira, Aline M. M.; Monteiro, Andréa de S.; dos Santos, Vera L.; Nicoli, Jacques R.; Azevedo, Vasco A. de C.; Soares, Siomar de C.; Dias-Souza, Marcus V.; Nardi, Regina M. D.

2017-01-01

A bacteriocinogenic Lactobacillus rhamnosus L156.4 strain isolated from the feces of NIH mice was identified by 16S rRNA gene sequencing and MALDI-TOF mass spectrometry. The entire genome was sequenced using Illumina, annotated in the PGAAP, and RAST servers, and deposited. Conserved genes associated with bacteriocin synthesis were predicted using BAGEL3, leading to the identification of an open reading frame (ORF) that shows homology with the L. rhamnosus GG (ATCC 53103) prebacteriocin gene. The encoded protein contains a conserved protein motif associated a structural gene of the Enterocin A superfamily. We found ORFs related to the prebacteriocin, immunity protein, ABC transporter proteins, and regulatory genes with 100% identity to those of L. rhamnosus HN001. In this study, we provide evidence of a putative bacteriocin produced by L. rhamnosus L156.4 that was further confirmed by in vitro assays. The antibacterial activity of the substances produced by this strain was evaluated using the deferred agar-spot and spot-on-the lawn assays, and a wide antimicrobial activity spectrum against human and foodborne pathogens was observed. The physicochemical characterization of the putative bacteriocin indicated that it was sensitive to proteolytic enzymes, heat stable and maintained its antibacterial activity in a pH ranging from 3 to 9. The activity against Lactobacillus fermentum, which was used as an indicator strain, was detected during bacterial logarithmic growth phase, and a positive correlation was confirmed between bacterial growth and production of the putative bacteriocin. After a partial purification from cell-free supernatant by salt precipitation, the putative bacteriocin migrated as a diffuse band of approximately 1.0–3.0 kDa by SDS-PAGE. Additional studies are being conducted to explore its use in the food industry for controlling bacterial growth and for probiotic applications. PMID:28579977

The putative Leishmania telomerase RNA (LeishTER undergoes trans-splicing and contains a conserved template sequence.

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Elton J R Vasconcelos

Full Text Available Telomerase RNAs (TERs are highly divergent between species, varying in size and sequence composition. Here, we identify a candidate for the telomerase RNA component of Leishmania genus, which includes species that cause leishmaniasis, a neglected tropical disease. Merging a thorough computational screening combined with RNA-seq evidence, we mapped a non-coding RNA gene localized in a syntenic locus on chromosome 25 of five Leishmania species that shares partial synteny with both Trypanosoma brucei TER locus and a putative TER candidate-containing locus of Crithidia fasciculata. Using target-driven molecular biology approaches, we detected a ∼2,100 nt transcript (LeishTER that contains a 5' spliced leader (SL cap, a putative 3' polyA tail and a predicted C/D box snoRNA domain. LeishTER is expressed at similar levels in the logarithmic and stationary growth phases of promastigote forms. A 5'SL capped LeishTER co-immunoprecipitated and co-localized with the telomerase protein component (TERT in a cell cycle-dependent manner. Prediction of its secondary structure strongly suggests the existence of a bona fide single-stranded template sequence and a conserved C[U/C]GUCA motif-containing helix II, representing the template boundary element. This study paves the way for further investigations on the biogenesis of parasite TERT ribonucleoproteins (RNPs and its role in parasite telomere biology.

The F-box protein Cdc4/Fbxw7 is a novel regulator of neural crest development in Xenopus laevis

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Hartley Rebecca S

2010-01-01

Full Text Available Abstract Background The neural crest is a unique population of cells that arise in the vertebrate ectoderm at the neural plate border after which they migrate extensively throughout the embryo, giving rise to a wide range of derivatives. A number of proteins involved in neural crest development have dynamic expression patterns, and it is becoming clear that ubiquitin-mediated protein degradation is partly responsible for this. Results Here we demonstrate a novel role for the F-box protein Cdc4/Fbxw7 in neural crest development. Two isoforms of Xenopus laevis Cdc4 were identified, and designated xCdc4α and xCdc4β. These are highly conserved with vertebrate Cdc4 orthologs, and the Xenopus proteins are functionally equivalent in terms of their ability to degrade Cyclin E, an established vertebrate Cdc4 target. Blocking xCdc4 function specifically inhibited neural crest development at an early stage, prior to expression of c-Myc, Snail2 and Snail. Conclusions We demonstrate that Cdc4, an ubiquitin E3 ligase subunit previously identified as targeting primarily cell cycle regulators for proteolysis, has additional roles in control of formation of the neural crest. Hence, we identify Cdc4 as a protein with separable but complementary functions in control of cell proliferation and differentiation.

Noncoding RNA in the Transcriptional Landscape of Human Neural Progenitor Cell Differentiation

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Patrick eHecht

2015-10-01

Full Text Available Increasing evidence suggests that noncoding RNAs play key roles in cellular processes, particularly in the brain. The present study used RNA sequencing to identify the transcriptional landscape of two human neural progenitor cell lines, SK-N-SH and ReNcell CX, as they differentiate into human cortical projection neurons. Protein coding genes were found to account for 54.8% and 57.0% of expressed genes, respectively, and alignment of RNA sequencing reads revealed that only 25.5-28.1% mapped to exonic regions of the genome. Differential expression analysis in the two cell lines identified altered gene expression in both protein coding and noncoding RNAs as they undergo neural differentiation with 222 differentially expressed genes observed in SK-N-SH cells and 19 differentially expressed genes in ReNcell CX. Interestingly, genes showing differential expression in SK-N-SH cells are enriched in genes implicated in autism spectrum disorder, but not in gene sets related to cancer or Alzheimer’s disease. Weighted gene co-expression network analysis (WGCNA was used to detect modules of co-expressed protein coding and noncoding RNAs in SK-N-SH cells and found four modules to be associated with neural differentiation. These modules contain varying levels of noncoding RNAs ranging from 10.7% to 49.7% with gene ontology suggesting roles in numerous cellular processes important for differentiation. These results indicate that noncoding RNAs are highly expressed in human neural progenitor cells and likely hold key regulatory roles in gene networks underlying neural differentiation and neurodevelopmental disorders.

Probabilistic neural network algorithm for using radon emanations as an earthquake precursor

International Nuclear Information System (INIS)

Gupta, Dhawal; Shahani, D.T.

2014-01-01

The investigation throughout the world in past two decades provides evidence which indicate that significance variation of radon and other soil gases occur in association with major geophysical events such as earthquake. The traditional statistical algorithm includes regression to remove the effect of the meteorological parameters from the raw radon and anomalies are calculated either taking the periodicity in seasonal variations or periodicity computed using Fast Fourier Transform. In case of neural networks the regression step is avoided. A neural network model can be found which can learn the behavior of radon with respect to meteorological parameter in order that changing emission patterns may be adapted to by the model on its own. The output of this neural model is the estimated radon values. This estimated radon value is used to decide whether anomalous behavior of radon has occurred and a valid precursor may be identified. The neural network model developed using Radial Basis function network gave a prediction rate of 87.7%. The same was accompanied by huge false alarms. The present paper deals with improved neural network algorithm using Probabilistic Neural Networks that requires neither an explicit step of regression nor use of any specific period. This neural network model reduces the false alarms to zero and gave same prediction rate as RBF networks. (author)

Neural correlates and neural computations in posterior parietal cortex during perceptual decision-making

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Alexander eHuk

2012-10-01

Full Text Available A recent line of work has found remarkable success in relating perceptual decision-making and the spiking activity in the macaque lateral intraparietal area (LIP. In this review, we focus on questions about the neural computations in LIP that are not answered by demonstrations of neural correlates of psychological processes. We highlight three areas of limitations in our current understanding of the precise neural computations that might underlie neural correlates of decisions: (1 empirical questions not yet answered by existing data; (2 implementation issues related to how neural circuits could actually implement the mechanisms suggested by both physiology and psychology; and (3 ecological constraints related to the use of well-controlled laboratory tasks and whether they provide an accurate window on sensorimotor computation. These issues motivate the adoption of a more general encoding-decoding framework that will be fruitful for more detailed contemplation of how neural computations in LIP relate to the formation of perceptual decisions.

Sall1 regulates cortical neurogenesis and laminar fate specification in mice: implications for neural abnormalities in Townes-Brocks syndrome

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Susan J. Harrison

2012-05-01

Progenitor cells in the cerebral cortex undergo dynamic cellular and molecular changes during development. Sall1 is a putative transcription factor that is highly expressed in progenitor cells during development. In humans, the autosomal dominant developmental disorder Townes-Brocks syndrome (TBS is associated with mutations of the SALL1 gene. TBS is characterized by renal, anal, limb and auditory abnormalities. Although neural deficits have not been recognized as a diagnostic characteristic of the disease, ∼10% of patients exhibit neural or behavioral abnormalities. We demonstrate that, in addition to being expressed in peripheral organs, Sall1 is robustly expressed in progenitor cells of the central nervous system in mice. Both classical- and conditional-knockout mouse studies indicate that the cerebral cortex is particularly sensitive to loss of Sall1. In the absence of Sall1, both the surface area and depth of the cerebral cortex were decreased at embryonic day 18.5 (E18.5. These deficiencies are associated with changes in progenitor cell properties during development. In early cortical progenitor cells, Sall1 promotes proliferative over neurogenic division, whereas, at later developmental stages, Sall1 regulates the production and differentiation of intermediate progenitor cells. Furthermore, Sall1 influences the temporal specification of cortical laminae. These findings present novel insights into the function of Sall1 in the developing mouse cortex and provide avenues for future research into potential neural deficits in individuals with TBS.

Neural correlates of sad feelings in healthy girls.

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Lévesque, J; Joanette, Y; Mensour, B; Beaudoin, G; Leroux, J-M; Bourgouin, P; Beauregard, M

2003-01-01

Emotional development is indisputably one of the cornerstones of personality development during infancy. According to the differential emotions theory (DET), primary emotions are constituted of three distinct components: the neural-evaluative, the expressive, and the experiential. The DET further assumes that these three components are biologically based and functional nearly from birth. Such a view entails that the neural substrate of primary emotions must be similar in children and adults. Guided by this assumption of the DET, the present functional magnetic resonance imaging study was conducted to identify the neural correlates of sad feelings in healthy children. Fourteen healthy girls (aged 8-10) were scanned while they watched sad film excerpts aimed at externally inducing a transient state of sadness (activation task). Emotionally neutral film excerpts were also presented to the subjects (reference task). The subtraction of the brain activity measured during the viewing of the emotionally neutral film excerpts from that noted during the viewing of the sad film excerpts revealed that sad feelings were associated with significant bilateral activations of the midbrain, the medial prefrontal cortex (Brodmann area [BA] 10), and the anterior temporal pole (BA 21). A significant locus of activation was also noted in the right ventrolateral prefrontal cortex (BA 47). These results are compatible with those of previous functional neuroimaging studies of sadness in adults. They suggest that the neural substrate underlying the subjective experience of sadness is comparable in children and adults. Such a similitude provides empirical support to the DET assumption that the neural substrate of primary emotions is biologically based.

Distinctive and common neural underpinnings of major depression, social anxiety, and their comorbidity.

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Hamilton, J Paul; Chen, Michael C; Waugh, Christian E; Joormann, Jutta; Gotlib, Ian H

2015-04-01

Assessing neural commonalities and differences among depression, anxiety and their comorbidity is critical in developing a more integrative clinical neuroscience and in evaluating currently debated categorical vs dimensional approaches to psychiatric classification. Therefore, in this study, we sought to identify patterns of anomalous neural responding to criticism and praise that are specific to and common among major depressive disorder (MDD), social anxiety disorder (SAD) and comorbid MDD-SAD. Adult females who met formal diagnostic criteria for MDD, SAD or MDD-SAD and psychiatrically healthy participants underwent functional magnetic resonance imaging as they listened to statements directing praise or criticism at them or at another person. MDD groups showed reduced responding to praise across a distributed cortical network, an effect potentially mediated by thalamic nuclei undergirding arousal-mediated attention. SAD groups showed heightened anterior insula and decreased default-mode network response to criticism. The MDD-SAD group uniquely showed reduced responding to praise in the dorsal anterior cingulate cortex. Finally, all groups with psychopathology showed heightened response to criticism in a region of the superior frontal gyrus implicated in attentional gating. The present results suggest novel neural models of anhedonia in MDD, vigilance-withdrawal behaviors in SAD, and poorer outcome in MDD-SAD. Importantly, in identifying unique and common neural substrates of MDD and SAD, these results support a formulation in which common neural components represent general risk factors for psychopathology that, due to factors that are present at illness onset, lead to distinct forms of psychopathology with unique neural signatures. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Deep Learning Neural Networks and Bayesian Neural Networks in Data Analysis

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Chernoded Andrey

2017-01-01

Full Text Available Most of the modern analyses in high energy physics use signal-versus-background classification techniques of machine learning methods and neural networks in particular. Deep learning neural network is the most promising modern technique to separate signal and background and now days can be widely and successfully implemented as a part of physical analysis. In this article we compare Deep learning and Bayesian neural networks application as a classifiers in an instance of top quark analysis.

Neural correlates of affective influence on choice.

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Piech, Richard M; Lewis, Jade; Parkinson, Caroline H; Owen, Adrian M; Roberts, Angela C; Downing, Paul E; Parkinson, John A

2010-03-01

Making the right choice depends crucially on the accurate valuation of the available options in the light of current needs and goals of an individual. Thus, the valuation of identical options can vary considerably with motivational context. The present study investigated the neural structures underlying context dependent evaluation. We instructed participants to choose from food menu items based on different criteria: on their anticipated taste or on ease of preparation. The aim of the manipulation was to assess which neural sites were activated during choice guided by incentive value, and which during choice based on a value-irrelevant criterion. To assess the impact of increased motivation, affect-guided choice and cognition-guided choice was compared during the sated and hungry states. During affective choice, we identified increased activity in structures representing primarily valuation and taste (medial prefrontal cortex, insula). During cognitive choice, structures showing increased activity included those implicated in suppression and conflict monitoring (lateral orbitofrontal cortex, anterior cingulate). Hunger influenced choice-related activity in the ventrolateral prefrontal cortex. Our results show that choice is associated with the use of distinct neural structures for the pursuit of different goals. Published by Elsevier Inc.

Neural Tube Defects

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Neural tube defects are birth defects of the brain, spine, or spinal cord. They happen in the ... that she is pregnant. The two most common neural tube defects are spina bifida and anencephaly. In ...

Putative Biomarkers and Targets of Estrogen Receptor Negative Human Breast Cancer

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Stephen W. Byers

2011-07-01

Full Text Available Breast cancer is a progressive and potentially fatal disease that affects women of all ages. Like all progressive diseases, early and reliable diagnosis is the key for successful treatment and annihilation. Biomarkers serve as indicators of pathological, physiological, or pharmacological processes. Her2/neu, CA15.3, estrogen receptor (ER, progesterone receptor (PR, and cytokeratins are biomarkers that have been approved by the Food and Drug Administration for disease diagnosis, prognosis, and therapy selection. The structural and functional complexity of protein biomarkers and the heterogeneity of the breast cancer pathology present challenges to the scientific community. Here we review estrogen receptor-related putative breast cancer biomarkers, including those of putative breast cancer stem cells, a minor population of estrogen receptor negative tumor cells that retain the stem cell property of self renewal. We also review a few promising cytoskeleton targets for ER alpha negative breast cancer.

A Fault Diagnosis Approach for the Hydraulic System by Artificial Neural Networks

OpenAIRE

Xiangyu He; Shanghong He

2014-01-01

Based on artificial neural networks, a fault diagnosis approach for the hydraulic system was proposed in this paper. Normal state samples were used as the training data to develop a dynamic general regression neural network (DGRNN) model. The trained DGRNN model then served as the fault determinant to diagnose test faults and the work condition of the hydraulic system was identified. Several typical faults of the hydraulic system were used to verify the fault diagnosis approach. Experiment re...

Cardiac autonomic imbalance by social stress in rodents: understanding putative biomarkers

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Susan K Wood, Phd

2014-08-01

Full Text Available Exposure to stress or traumatic events can lead to the development of depression and anxiety disorders. In addition to the debilitating consequences on mental health, patients with psychiatric disorders also suffer from autonomic imbalance, making them susceptible to a variety of medical disorders. Emerging evidence utilizing spectral analysis of heart rate variability (HRV, a reliable noninvasive measure of cardiovascular autonomic regulation, indicates that patients with depression and various anxiety disorders (i.e., panic, social, generalized anxiety disorders, and post traumatic stress disorder are characterized by decreased HRV. Social stressors in rodents are ethologically relevant experimental stressors that recapitulate many of the dysfunctional behavioral and physiological changes that occur in psychological disorders. In this review, evidence from clinical studies and preclinical stress models identify putative biomarkers capable of precipitating the comorbidity between disorders of the mind and autonomic dysfunction. Specifically, the role of corticotropin releasing factor, neuropeptide Y and inflammation are investigated. The impetus for this review is to highlight stress-related biomarkers that may prove critical in the development of autonomic imbalance in stress -related psychiatric disorders.

Sequence analysis of putative swrW gene required for surfactant ...

African Journals Online (AJOL)

owner

2012-07-17

Jul 17, 2012 ... These nucleotide and protein sequence analysis of the putative swrW gene provides vital information on the versatility .... chain reaction (PCR) products were stored at 4°C. Presence of ... identical to the same gene with an E-value of 0.0. .... The Prokaryotes-A Handbook on the Biol. of Bacteria:Ecophysiol.

Noise-enhanced categorization in a recurrently reconnected neural network

International Nuclear Information System (INIS)

Monterola, Christopher; Zapotocky, Martin

2005-01-01

We investigate the interplay of recurrence and noise in neural networks trained to categorize spatial patterns of neural activity. We develop the following procedure to demonstrate how, in the presence of noise, the introduction of recurrence permits to significantly extend and homogenize the operating range of a feed-forward neural network. We first train a two-level perceptron in the absence of noise. Following training, we identify the input and output units of the feed-forward network, and thus convert it into a two-layer recurrent network. We show that the performance of the reconnected network has features reminiscent of nondynamic stochastic resonance: the addition of noise enables the network to correctly categorize stimuli of subthreshold strength, with optimal noise magnitude significantly exceeding the stimulus strength. We characterize the dynamics leading to this effect and contrast it to the behavior of a more simple associative memory network in which noise-mediated categorization fails

Noise-enhanced categorization in a recurrently reconnected neural network

Science.gov (United States)

Monterola, Christopher; Zapotocky, Martin

2005-03-01

We investigate the interplay of recurrence and noise in neural networks trained to categorize spatial patterns of neural activity. We develop the following procedure to demonstrate how, in the presence of noise, the introduction of recurrence permits to significantly extend and homogenize the operating range of a feed-forward neural network. We first train a two-level perceptron in the absence of noise. Following training, we identify the input and output units of the feed-forward network, and thus convert it into a two-layer recurrent network. We show that the performance of the reconnected network has features reminiscent of nondynamic stochastic resonance: the addition of noise enables the network to correctly categorize stimuli of subthreshold strength, with optimal noise magnitude significantly exceeding the stimulus strength. We characterize the dynamics leading to this effect and contrast it to the behavior of a more simple associative memory network in which noise-mediated categorization fails.

On-line plant-wide monitoring using neural networks

International Nuclear Information System (INIS)

Turkcan, E.; Ciftcioglu, O.; Eryurek, E.; Upadhyaya, B.R.

1992-06-01

The on-line signal analysis system designed for a multi-level mode operation using neural networks is described. The system is capable of monitoring the plant states by tracking different number of signals up to 32 simultaneously. The data used for this study were acquired from the Borssele Nuclear Power Plant (PWR type), and using the on-line monitoring system. An on-line plant-wide monitoring study using a multilayer neural network model is discussed in this paper. The back-propagation neural network algorithm is used for training the network. The technique assumes that each physical state of the power plant can be represented by a unique pattern of instrument readings which can be related to the condition of the plant. When disturbance occurs, the sensor readings undergo a transient, and form a different set of patterns which represent the new operational status. Diagnosing these patterns can be helpful in identifying this new state of the power plant. To this end, plant-wide monitoring with neutral networks is one of the new techniques in real-time applications. (author). 9 refs.; 5 figs

Long Noncoding RNA-1604 Orchestrates Neural Differentiation through the miR-200c/ZEB Axis.

Science.gov (United States)

Weng, Rong; Lu, Chenqi; Liu, Xiaoqin; Li, Guoping; Lan, Yuanyuan; Qiao, Jing; Bai, Mingliang; Wang, Zhaojie; Guo, Xudong; Ye, Dan; Jiapaer, Zeyidan; Yang, Yiwei; Xia, Chenliang; Wang, Guiying; Kang, Jiuhong

2018-03-01

Clarifying the regulatory mechanisms of embryonic stem cell (ESC) neural differentiation is helpful not only for understanding neural development but also for obtaining high-quality neural progenitor cells required by stem cell therapy of neurodegenerative diseases. Here, we found that long noncoding RNA 1604 (lncRNA-1604) was highly expressed in cytoplasm during neural differentiation, and knockdown of lncRNA-1604 significantly repressed neural differentiation of mouse ESCs both in vitro and in vivo. Bioinformatics prediction and mechanistic analysis revealed that lncRNA-1604 functioned as a novel competing endogenous RNA of miR-200c and regulated the core transcription factors ZEB1 and ZEB2 during neural differentiation. Furthermore, we also demonstrated the critical role of miR-200c and ZEB1/2 in mouse neural differentiation. Either introduction of miR-200c sponge or overexpression of ZEB1/2 significantly reversed the lncRNA-1604 knockdown-induced repression of mouse ESC neural differentiation. Collectively, these findings not only identified a previously unknown role of lncRNA-1604 and ZEB1/2 but also elucidated a new regulatory lncRNA-1604/miR-200c/ZEB axis in neural differentiation. Stem Cells 2018;36:325-336. © 2017 AlphaMed Press.

Putative and unique gene sequence utilization for the design of species specific probes as modeled by Lactobacillus plantarum

Science.gov (United States)

The concept of utilizing putative and unique gene sequences for the design of species specific probes was tested. The abundance profile of assigned functions within the Lactobacillus plantarum genome was used for the identification of the putative and unique gene sequence, csh. The targeted gene (cs...

A targeted sequencing panel identifies rare damaging variants in multiple genes in the cranial neural tube defect, anencephaly.

Science.gov (United States)

Ishida, M; Cullup, T; Boustred, C; James, C; Docker, J; English, C; Lench, N; Copp, A J; Moore, G E; Greene, N D E; Stanier, P

2018-04-01

Neural tube defects (NTDs) affecting the brain (anencephaly) are lethal before or at birth, whereas lower spinal defects (spina bifida) may lead to lifelong neurological handicap. Collectively, NTDs rank among the most common birth defects worldwide. This study focuses on anencephaly, which despite having a similar frequency to spina bifida and being the most common type of NTD observed in mouse models, has had more limited inclusion in genetic studies. A genetic influence is strongly implicated in determining risk of NTDs and a molecular diagnosis is of fundamental importance to families both in terms of understanding the origin of the condition and for managing future pregnancies. Here we used a custom panel of 191 NTD candidate genes to screen 90 patients with cranial NTDs (n = 85 anencephaly and n = 5 craniorachischisis) with a targeted exome sequencing platform. After filtering and comparing to our in-house control exome database (N = 509), we identified 397 rare variants (minor allele frequency, MAF < 1%), 21 of which were previously unreported and predicted damaging. This included 1 frameshift (PDGFRA), 2 stop-gained (MAT1A; NOS2) and 18 missense variations. Together with evidence for oligogenic inheritance, this study provides new information on the possible genetic causation of anencephaly. © 2017 The Authors. Clinical Genetics published by John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Neural Network Target Identification System for False Alarm Reduction

Science.gov (United States)

Ye, David; Edens, Weston; Lu, Thomas T.; Chao, Tien-Hsin

2009-01-01

A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feed forward back propagation neural network (NN) is then trained to classify each feature vector and remove false positives. This paper discusses the test of the system performance and parameter optimizations process which adapts the system to various targets and datasets. The test results show that the system was successful in substantially reducing the false positive rate when tested on a sonar image dataset.

An S/T-Q cluster domain census unveils new putative targets under Tel1/Mec1 control

Directory of Open Access Journals (Sweden)

Cheung Hannah C

2012-11-01

Full Text Available Abstract Background The cellular response to DNA damage is immediate and highly coordinated in order to maintain genome integrity and proper cell division. During the DNA damage response (DDR, the sensor kinases Tel1 and Mec1 in Saccharomyces cerevisiae and ATM and ATR in human, phosphorylate multiple mediators which activate effector proteins to initiate cell cycle checkpoints and DNA repair. A subset of kinase substrates are recognized by the S/T-Q cluster domain (SCD, which contains motifs of serine (S or threonine (T followed by a glutamine (Q. However, the full repertoire of proteins and pathways controlled by Tel1 and Mec1 is unknown. Results To identify all putative SCD-containing proteins, we analyzed the distribution of S/T-Q motifs within verified Tel1/Mec1 targets and arrived at a unifying SCD definition of at least 3 S/T-Q within a stretch of 50 residues. This new SCD definition was used in a custom bioinformatics pipeline to generate a census of SCD-containing proteins in both yeast and human. In yeast, 436 proteins were identified, a significantly larger number of hits than were expected by chance. These SCD-containing proteins did not distribute equally across GO-ontology terms, but were significantly enriched for those involved in processes related to the DDR. We also found a significant enrichment of proteins involved in telophase and cytokinesis, protein transport and endocytosis suggesting possible novel Tel1/Mec1 targets in these pathways. In the human proteome, a wide range of similar proteins were identified, including homologs of some SCD-containing proteins found in yeast. This list also included high concentrations of proteins in the Mediator, spindle pole body/centrosome and actin cytoskeleton complexes. Conclusions Using a bioinformatic approach, we have generated a census of SCD-containing proteins that are involved not only in known DDR pathways but several other pathways under Tel1/Mec1 control suggesting new

Identification of a novel group of putative Arabidopsis thaliana beta-(1,3)-galactosyltransferases

DEFF Research Database (Denmark)

Qu, Yongmei; Egelund, Jack; Gilson, Paul R

2008-01-01

To begin biochemical and molecular studies on the biosynthesis of the type II arabinogalactan chains on arabinogalactan-proteins (AGPs), we adopted a bioinformatic approach to identify and systematically characterise the putative galactosyltransferases (GalTs) responsible for synthesizing the beta......-(1,3)-Gal linkage from CAZy GT-family-31 from Arabidopsis thaliana. These analyses confirmed that 20 members of the GT-31 family contained domains/motifs typical of biochemically characterised beta-(1,3)-GTs from mammalian systems. Microarray data confirm that members of this family are expressed......,3)-GalT activity. This bioinformatic/molecular study of CAZy GT-family-31 was validated by the recent report of Strasser et al. (Plant Cell 19:2278-2292, 2007) that another member of this family (At1g26810; GALT1) encodes a beta-(1,3)-GalT involved in the biosynthesis of the Lewis a epitope of N...

Neural representations of emotion are organized around abstract event features.

Science.gov (United States)

Skerry, Amy E; Saxe, Rebecca

2015-08-03

Research on emotion attribution has tended to focus on the perception of overt expressions of at most five or six basic emotions. However, our ability to identify others' emotional states is not limited to perception of these canonical expressions. Instead, we make fine-grained inferences about what others feel based on the situations they encounter, relying on knowledge of the eliciting conditions for different emotions. In the present research, we provide convergent behavioral and neural evidence concerning the representations underlying these concepts. First, we find that patterns of activity in mentalizing regions contain information about subtle emotional distinctions conveyed through verbal descriptions of eliciting situations. Second, we identify a space of abstract situation features that well captures the emotion discriminations subjects make behaviorally and show that this feature space outperforms competing models in capturing the similarity space of neural patterns in these regions. Together, the data suggest that our knowledge of others' emotions is abstract and high dimensional, that brain regions selective for mental state reasoning support relatively subtle distinctions between emotion concepts, and that the neural representations in these regions are not reducible to more primitive affective dimensions such as valence and arousal. Copyright © 2015 Elsevier Ltd. All rights reserved.

Cramp-fasciculation syndrome in patients with and without neural autoantibodies.

Science.gov (United States)

Liewluck, Teerin; Klein, Christopher J; Jones, Lyell K

2014-03-01

We investigated the clinical, electrophysiological and neural autoantibody characteristics in cramp-fasciculation syndrome (CFS) patients. We reviewed Mayo Clinic records from 2000 to 2011 to identify clinically defined CFS patients who underwent neural autoantibody testing. Stored sera of patients who tested positive for antibodies to voltage-gated potassium channel complex (VGKC complex) were analyzed further for leucine-rich glioma-inactivated 1 (LGI1) or contactin-associated protein-2 immunoglobulin G (CASPR2-IgG) antibodies. Thirty-seven patients were identified. Twelve were seropositive for neural autoantibodies. Clinical manifestations were similar in seropositive and seronegative patients, although central and autonomic neuronal hyperexcitability symptoms were more common in seropositive cases. No patients had a malignancy. Repetitive tibial nerve stimulation at 10 Hz revealed longer afterdischarges in seropositive patients. Two of 7 patients with VGKC-complex autoimmunity demonstrated LGI1 or CASPR2-IgG antibodies. Only 2 of 12 seropositive patients required immunotherapy. VGKC-complex autoimmunity occurs in a minority of CFS patients. Antibody positivity was associated with extramuscular manifestations, typically without malignancy. Target antigens within the VGKC complex remain unknown in most patients. Published 2013 by Wiley Periodicals, Inc. This article is a US Government work and, as such, is in the public domain in the United States of America.

Putative contact ketoconazole shampoo-triggered pemphigus foliaceus in a dog.

Science.gov (United States)

Sung, Hyun-Jeong; Yoon, In-Hwa; Kim, Jung-Hyun

2017-09-01

A 10-year-old spayed female cocker spaniel dog was referred for an evaluation of acute-onset generalized pustular cutaneous lesions following application of ketoconazole shampoo. Cytologic and histopathologic examinations of the lesions revealed intra-epidermal pustules with predominantly neutrophils and acantholytic cells. This is the first description of putative contact ketoconazole shampoo-triggered pemphigus foliaceus in a dog.

Differential expressions of putative genes in various floral organs of ...

African Journals Online (AJOL)

STORAGESEVER

2009-06-03

Jun 3, 2009 ... Full Length Research Paper. Differential expressions of putative genes in various floral organs of the Pigeon orchid (Dendrobium crumenatum) using GeneFishing. Faridah, Q. Z.1, 2, Ng, B. Z.3, Raha, A. R.4, Umi, K. A. B.5 and Khosravi, A. R.2*. 1Department of Biology, Faculty Science, University Putra ...

Neural Representation. A Survey-Based Analysis of the Notion

Directory of Open Access Journals (Sweden)

Oscar Vilarroya

2017-08-01

Full Text Available The word representation (as in “neural representation”, and many of its related terms, such as to represent, representational and the like, play a central explanatory role in neuroscience literature. For instance, in “place cell” literature, place cells are extensively associated with their role in “the representation of space.” In spite of its extended use, we still lack a clear, universal and widely accepted view on what it means for a nervous system to represent something, on what makes a neural activity a representation, and on what is re-presented. The lack of a theoretical foundation and definition of the notion has not hindered actual research. My aim here is to identify how active scientists use the notion of neural representation, and eventually to list a set of criteria, based on actual use, that can help in distinguishing between genuine or non-genuine neural-representation candidates. In order to attain this objective, I present first the results of a survey of authors within two domains, place-cell and multivariate pattern analysis (MVPA research. Based on the authors’ replies, and on a review of neuroscientific research, I outline a set of common properties that an account of neural representation seems to require. I then apply these properties to assess the use of the notion in two domains of the survey, place-cell and MVPA studies. I conclude by exploring a shift in the notion of representation suggested by recent literature.

Particle identification with neural networks using a rotational invariant moment representation

Science.gov (United States)

Sinkus, Ralph; Voss, Thomas

1997-02-01

A feed-forward neural network is used to identify electromagnetic particles based upon their showering properties within a segmented calorimeter. A preprocessing procedure is applied to the spatial energy distribution of the particle shower in order to account for the varying geometry of the calorimeter. The novel feature is the expansion of the energy distribution in terms of moments of the so-called Zernike functions which are invariant under rotation. The distributions of moments exhibit very different scales, thus the multidimensional input distribution for the neural network is transformed via a principal component analysis and rescaled by its respective variances to ensure input values of the order of one. This increases the sensitivity of the network and thus results in better performance in identifying and separating electromagnetic from hadronic particles, especially at low energies.

Particle identification with neural networks using a rotational invariant moment representation

International Nuclear Information System (INIS)

Sinkus, R.

1997-01-01

A feed-forward neural network is used to identify electromagnetic particles based upon their showering properties within a segmented calorimeter. A preprocessing procedure is applied to the spatial energy distribution of the particle shower in order to account for the varying geometry of the calorimeter. The novel feature is the expansion of the energy distribution in terms of moments of the so-called Zernike functions which are invariant under rotation. The distributions of moments exhibit very different scales, thus the multidimensional input distribution for the neural network is transformed via a principal component analysis and rescaled by its respective variances to ensure input values of the order of one. This increases the sensitivity of the network and thus results in better performance in identifying and separating electromagnetic from hadronic particles, especially at low energies. (orig.)

Image Finder Mobile Application Based on Neural Networks

Directory of Open Access Journals (Sweden)

Nabil M. Hewahi

2017-04-01

Full Text Available Nowadays taking photos via mobile phone has become a very important part of everyone’s life. Almost each and every person who has a smart phone also has thousands of photos in their mobile device. At times it becomes very difficult to find a particular photo from thousands of photos, and it takes time. This research was done to come up with an innovative solution that could solve this problem. The solution will allow the user to find the required photo by simply drawing a sketch on the objects in the required picture, for example a tree or car, etc. Two types of supervised Artificial Neural Networks are used for this purpose; one is trained to identify the handmade sketches and other is trained to identify the images. The proposed approach introduces a mechanism to relate the sketches with the images by matching them after training. The experimentation results for testing the trained neural networks reached 100% for the sketches, and 84% for the images of two objects as a case study.

Characterization of a putative grapevine Zn transporter, VvZIP3, suggests its involvement in early reproductive development in Vitis vinifera L

Directory of Open Access Journals (Sweden)

Gainza-Cortés Felipe

2012-07-01

Full Text Available Abstract Background Zinc (Zn deficiency is one of the most widespread mineral nutritional problems that affect normal development in plants. Because Zn cannot passively diffuse across cell membranes, it must be transported into intracellular compartments for all biological processes where Zn is required. Several members of the Zinc-regulated transporters, Iron-regulated transporter-like Protein (ZIP gene family have been characterized in plants, and have shown to be involved in metal uptake and transport. This study describes the first putative Zn transporter in grapevine. Unravelling its function may explain an important symptom of Zn deficiency in grapevines, which is the production of clusters with fewer and usually smaller berries than normal. Results We identified and characterized a putative Zn transporter from berries of Vitis vinifera L., named VvZIP3. Compared to other members of the ZIP family identified in the Vitis vinifera L. genome, VvZIP3 is mainly expressed in reproductive tissue - specifically in developing flowers - which correlates with the high Zn accumulation in these organs. Contrary to this, the low expression of VvZIP3 in parthenocarpic berries shows a relationship with the lower Zn accumulation in this tissue than in normal seeded berries where its expression is induced by Zn. The predicted protein sequence indicates strong similarity with several members of the ZIP family from Arabidopsis thaliana and other species. Moreover, VvZIP3 complemented the growth defect of a yeast Zn-uptake mutant, ZHY3, and is localized in the plasma membrane of plant cells, suggesting that VvZIP3 has the function of a Zn uptake transporter. Conclusions Our results suggest that VvZIP3 encodes a putative plasma membrane Zn transporter protein member of the ZIP gene family that might play a role in Zn uptake and distribution during the early reproductive development in Vitis vinifera L., indicating that the availability of this micronutrient

A neural flow estimator

DEFF Research Database (Denmark)

Jørgensen, Ivan Harald Holger; Bogason, Gudmundur; Bruun, Erik

1995-01-01

This paper proposes a new way to estimate the flow in a micromechanical flow channel. A neural network is used to estimate the delay of random temperature fluctuations induced in a fluid. The design and implementation of a hardware efficient neural flow estimator is described. The system...... is implemented using switched-current technique and is capable of estimating flow in the μl/s range. The neural estimator is built around a multiplierless neural network, containing 96 synaptic weights which are updated using the LMS1-algorithm. An experimental chip has been designed that operates at 5 V...

Hidden neural networks

DEFF Research Database (Denmark)

Krogh, Anders Stærmose; Riis, Søren Kamaric

1999-01-01

A general framework for hybrids of hidden Markov models (HMMs) and neural networks (NNs) called hidden neural networks (HNNs) is described. The article begins by reviewing standard HMMs and estimation by conditional maximum likelihood, which is used by the HNN. In the HNN, the usual HMM probability...... parameters are replaced by the outputs of state-specific neural networks. As opposed to many other hybrids, the HNN is normalized globally and therefore has a valid probabilistic interpretation. All parameters in the HNN are estimated simultaneously according to the discriminative conditional maximum...... likelihood criterion. The HNN can be viewed as an undirected probabilistic independence network (a graphical model), where the neural networks provide a compact representation of the clique functions. An evaluation of the HNN on the task of recognizing broad phoneme classes in the TIMIT database shows clear...

NeuroMEMS: Neural Probe Microtechnologies

Directory of Open Access Journals (Sweden)

Sam Musallam

2008-10-01

Full Text Available Neural probe technologies have already had a significant positive effect on our understanding of the brain by revealing the functioning of networks of biological neurons. Probes are implanted in different areas of the brain to record and/or stimulate specific sites in the brain. Neural probes are currently used in many clinical settings for diagnosis of brain diseases such as seizers, epilepsy, migraine, Alzheimer’s, and dementia. We find these devices assisting paralyzed patients by allowing them to operate computers or robots using their neural activity. In recent years, probe technologies were assisted by rapid advancements in microfabrication and microelectronic technologies and thus are enabling highly functional and robust neural probes which are opening new and exciting avenues in neural sciences and brain machine interfaces. With a wide variety of probes that have been designed, fabricated, and tested to date, this review aims to provide an overview of the advances and recent progress in the microfabrication techniques of neural probes. In addition, we aim to highlight the challenges faced in developing and implementing ultralong multi-site recording probes that are needed to monitor neural activity from deeper regions in the brain. Finally, we review techniques that can improve the biocompatibility of the neural probes to minimize the immune response and encourage neural growth around the electrodes for long term implantation studies.

Experiments in Neural-Network Control of a Free-Flying Space Robot

Science.gov (United States)

Wilson, Edward

1995-01-01

Four important generic issues are identified and addressed in some depth in this thesis as part of the development of an adaptive neural network based control system for an experimental free flying space robot prototype. The first issue concerns the importance of true system level design of the control system. A new hybrid strategy is developed here, in depth, for the beneficial integration of neural networks into the total control system. A second important issue in neural network control concerns incorporating a priori knowledge into the neural network. In many applications, it is possible to get a reasonably accurate controller using conventional means. If this prior information is used purposefully to provide a starting point for the optimizing capabilities of the neural network, it can provide much faster initial learning. In a step towards addressing this issue, a new generic Fully Connected Architecture (FCA) is developed for use with backpropagation. A third issue is that neural networks are commonly trained using a gradient based optimization method such as backpropagation; but many real world systems have Discrete Valued Functions (DVFs) that do not permit gradient based optimization. One example is the on-off thrusters that are common on spacecraft. A new technique is developed here that now extends backpropagation learning for use with DVFs. The fourth issue is that the speed of adaptation is often a limiting factor in the implementation of a neural network control system. This issue has been strongly resolved in the research by drawing on the above new contributions.

Experiments in Neural-Network Control of a Free-Flying Space Robot

National Research Council Canada - National Science Library

Wilson, Edward

1995-01-01

Four important generic issues are identified and addressed in some depth in this thesis as part of the development of an adaptive neural network based control system for an experimental free flying space robot prototype...

Identification of putative QTLs for seedling stage phosphorus starvation response in finger millet (Eleusine coracana L. Gaertn. by association mapping and cross species synteny analysis.

Directory of Open Access Journals (Sweden)

M Ramakrishnan

Full Text Available A germplasm assembly of 128 finger millet genotypes from 18 countries was evaluated for seedling-stage phosphorus (P responses by growing them in P sufficient (Psuf and P deficient (Pdef treatments. Majority of the genotypes showed adaptive responses to low P condition. Based on phenotype behaviour using the best linear unbiased predictors for each trait, genotypes were classified into, P responsive, low P tolerant and P non-responsive types. Based on the overall phenotype performance under Pdef, 10 genotypes were identified as low P tolerants. The low P tolerant genotypes were characterised by increased shoot and root length and increased root hair induction with longer root hairs under Pdef, than under Psuf. Association mapping of P response traits using mixed linear models revealed four quantitative trait loci (QTLs. Two QTLs (qLRDW.1 and qLRDW.2 for low P response affecting root dry weight explained over 10% phenotypic variation. In silico synteny analysis across grass genomes for these QTLs identified putative candidate genes such as Ser-Thr kinase and transcription factors such as WRKY and basic helix-loop-helix (bHLH. The QTLs for response under Psuf were mapped for traits such as shoot dry weight (qHSDW.1 and root length (qHRL.1. Putative associations of these QTLs over the syntenous regions on the grass genomes revealed proximity to cytochrome P450, phosphate transporter and pectin methylesterase inhibitor (PMEI genes. This is the first report of the extent of phenotypic variability for P response in finger millet genotypes during seedling-stage, along with the QTLs and putative candidate genes associated with P starvation tolerance.

Identification of putative QTLs for seedling stage phosphorus starvation response in finger millet (Eleusine coracana L. Gaertn.) by association mapping and cross species synteny analysis.

Science.gov (United States)

Ramakrishnan, M; Ceasar, S Antony; Vinod, K K; Duraipandiyan, V; Ajeesh Krishna, T P; Upadhyaya, Hari D; Al-Dhabi, N A; Ignacimuthu, S

2017-01-01

A germplasm assembly of 128 finger millet genotypes from 18 countries was evaluated for seedling-stage phosphorus (P) responses by growing them in P sufficient (Psuf) and P deficient (Pdef) treatments. Majority of the genotypes showed adaptive responses to low P condition. Based on phenotype behaviour using the best linear unbiased predictors for each trait, genotypes were classified into, P responsive, low P tolerant and P non-responsive types. Based on the overall phenotype performance under Pdef, 10 genotypes were identified as low P tolerants. The low P tolerant genotypes were characterised by increased shoot and root length and increased root hair induction with longer root hairs under Pdef, than under Psuf. Association mapping of P response traits using mixed linear models revealed four quantitative trait loci (QTLs). Two QTLs (qLRDW.1 and qLRDW.2) for low P response affecting root dry weight explained over 10% phenotypic variation. In silico synteny analysis across grass genomes for these QTLs identified putative candidate genes such as Ser-Thr kinase and transcription factors such as WRKY and basic helix-loop-helix (bHLH). The QTLs for response under Psuf were mapped for traits such as shoot dry weight (qHSDW.1) and root length (qHRL.1). Putative associations of these QTLs over the syntenous regions on the grass genomes revealed proximity to cytochrome P450, phosphate transporter and pectin methylesterase inhibitor (PMEI) genes. This is the first report of the extent of phenotypic variability for P response in finger millet genotypes during seedling-stage, along with the QTLs and putative candidate genes associated with P starvation tolerance.

Segmentation of Drosophila Heart in Optical Coherence Microscopy Images Using Convolutional Neural Networks

OpenAIRE

Duan, Lian; Qin, Xi; He, Yuanhao; Sang, Xialin; Pan, Jinda; Xu, Tao; Men, Jing; Tanzi, Rudolph E.; Li, Airong; Ma, Yutao; Zhou, Chao

2018-01-01

Convolutional neural networks are powerful tools for image segmentation and classification. Here, we use this method to identify and mark the heart region of Drosophila at different developmental stages in the cross-sectional images acquired by a custom optical coherence microscopy (OCM) system. With our well-trained convolutional neural network model, the heart regions through multiple heartbeat cycles can be marked with an intersection over union (IOU) of ~86%. Various morphological and dyn...

The two putative comS homologs of the biotechnologically important Bacillus licheniformis do not contribute to competence development.

Science.gov (United States)

Jakobs, Mareike; Hoffmann, Kerstin; Liesegang, Heiko; Volland, Sonja; Meinhardt, Friedhelm

2015-03-01

In Bacillus subtilis, natural genetic competence is subject to complex genetic regulation and quorum sensing dependent. Upon extracellular accumulation of the peptide-pheromone ComX, the membrane-bound sensor histidine kinase ComP initiates diverse signaling pathways by activating-among others-DegQ and ComS. While DegQ favors the expression of extracellular enzymes rather than competence development, ComS is crucial for competence development as it prevents proteolytic degradation of ComK, the key transcriptional activator of all genes required for the uptake and integration of DNA. In Bacillus licheniformis, ComX/ComP sensed cell density negatively influences competence development, suggesting differences from the quorum-sensing-dependent control mechanism in Bacillus subtilis. Here, we show that each of six investigated strains possesses both of two different, recently identified putative comS genes. When expressed from an inducible promoter, none of the comS candidate genes displayed an impact on competence development neither in B. subtilis nor in B. licheniformis. Moreover, disruption of the genes did not reduce transformation efficiency. While the putative comS homologs do not contribute to competence development, we provide evidence that the degQ gene as for B. subtilis negatively influences genetic competency in B. licheniformis.

Learning in Artificial Neural Systems

Science.gov (United States)

Matheus, Christopher J.; Hohensee, William E.

1987-01-01

This paper presents an overview and analysis of learning in Artificial Neural Systems (ANS's). It begins with a general introduction to neural networks and connectionist approaches to information processing. The basis for learning in ANS's is then described, and compared with classical Machine learning. While similar in some ways, ANS learning deviates from tradition in its dependence on the modification of individual weights to bring about changes in a knowledge representation distributed across connections in a network. This unique form of learning is analyzed from two aspects: the selection of an appropriate network architecture for representing the problem, and the choice of a suitable learning rule capable of reproducing the desired function within the given network. The various network architectures are classified, and then identified with explicit restrictions on the types of functions they are capable of representing. The learning rules, i.e., algorithms that specify how the network weights are modified, are similarly taxonomized, and where possible, the limitations inherent to specific classes of rules are outlined.

Spatially Compact Neural Clusters in the Dorsal Striatum Encode Locomotion Relevant Information.

Science.gov (United States)

Barbera, Giovanni; Liang, Bo; Zhang, Lifeng; Gerfen, Charles R; Culurciello, Eugenio; Chen, Rong; Li, Yun; Lin, Da-Ting

2016-10-05

An influential striatal model postulates that neural activities in the striatal direct and indirect pathways promote and inhibit movement, respectively. Normal behavior requires coordinated activity in the direct pathway to facilitate intended locomotion and indirect pathway to inhibit unwanted locomotion. In this striatal model, neuronal population activity is assumed to encode locomotion relevant information. Here, we propose a novel encoding mechanism for the dorsal striatum. We identified spatially compact neural clusters in both the direct and indirect pathways. Detailed characterization revealed similar cluster organization between the direct and indirect pathways, and cluster activities from both pathways were correlated with mouse locomotion velocities. Using machine-learning algorithms, cluster activities could be used to decode locomotion relevant behavioral states and locomotion velocity. We propose that neural clusters in the dorsal striatum encode locomotion relevant information and that coordinated activities of direct and indirect pathway neural clusters are required for normal striatal controlled behavior. VIDEO ABSTRACT. Published by Elsevier Inc.

Emotion identification and aging: Behavioral and neural age-related changes.

Science.gov (United States)

Gonçalves, Ana R; Fernandes, Carina; Pasion, Rita; Ferreira-Santos, Fernando; Barbosa, Fernando; Marques-Teixeira, João

2018-05-01

Aging is known to alter the processing of facial expressions of emotion (FEE), however the impact of this alteration is less clear. Additionally, there is little information about the temporal dynamics of the neural processing of facial affect. We examined behavioral and neural age-related changes in the identification of FEE using event-related potentials. Furthermore, we analyze the relationship between behavioral/neural responses and neuropsychological functioning. To this purpose, 30 younger adults, 29 middle-aged adults and 26 older adults identified FEE. The behavioral results showed a similar performance between groups. The neural results showed no significant differences between groups for the P100 component and an increased N170 amplitude in the older group. Furthermore, a pattern of asymmetric activation was evident in the N170 component. Results also suggest deficits in facial feature decoding abilities, reflected by a reduced N250 amplitude in older adults. Neuropsychological functioning predicts P100 modulation, but does not seem to influence emotion identification ability. The findings suggest the existence of a compensatory function that would explain the age-equivalent performance in emotion identification. The study may help future research addressing behavioral and neural processes involved on processing of FEE in neurodegenerative conditions. Copyright © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Isolating neural correlates of conscious perception from neural correlates of reporting one’s perception

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Michael A Pitts

2014-10-01

Full Text Available To isolate neural correlates of conscious perception (NCCs, a standard approach has been to contrast neural activity elicited by identical stimuli of which subjects are aware versus unaware. Because conscious experience is private, determining whether a stimulus was consciously perceived requires subjective report: e.g., button-presses indicating detection, visibility ratings, verbal reports, etc. This reporting requirement introduces a methodological confound when attempting to isolate NCCs: The neural processes responsible for accessing and reporting one’s percept are difficult to distinguish from those underlying the conscious percept itself. Here, we review recent attempts to circumvent this issue via a modified inattentional blindness paradigm (Pitts, Martinez, & Hillyard, 2012 and present new data from a backward masking experiment in which task-relevance and visual awareness were manipulated in a 2x2 crossed design. In agreement with our previous inattentional blindness results, stimuli that were consciously perceived yet not immediately accessed for report (aware, task-irrelevant condition elicited a mid-latency posterior ERP negativity (~200-240ms, while stimuli that were accessed for report (aware, task-relevant condition elicited additional components including a robust P3b (~380-480ms subsequent to the mid-latency negativity. Overall, these results suggest that some of the NCCs identified in previous studies may be more closely linked with accessing and maintaining perceptual information for reporting purposes than with encoding the conscious percept itself. An open question is whether the remaining NCC candidate (the ERP negativity at 200-240ms reflects visual awareness or object-based attention.

Periostin is identified as a putative metastatic marker in breast cancer-derived exosomes.

Science.gov (United States)

Vardaki, Ioulia; Ceder, Sophia; Rutishauser, Dorothea; Baltatzis, George; Foukakis, Theodoros; Panaretakis, Theocharis

2016-11-15

Breast cancer (BrCa) is the most frequent cancer type in women and a leading cause of cancer related deaths in the world. Despite the decrease in mortality due to better diagnostics and palliative care, there is a lack of prognostic markers of metastasis. Recently, the exploitation of liquid biopsies and in particular of the extracellular vesicles has shown promise in the identification of such prognostic markers. In this study we compared the proteomic content of exosomes derived from metastatic and non-metastatic human (MCF7 and MDA-MB-231) and mouse (67NR and 4T1) cell lines. We found significant differences not only in the amount of secreted exosomes but most importantly in the protein content of exosomes secreted from metastatic versus non-metastatic ones. We identified periostin as a protein that is enriched in exosomes secreted by metastatic cells and validated its presence in a pilot cohort of breast cancer patient samples with localized disease or lymph node (LN) metastasis.

Use of neural network techniques to identify cosmic ray electrons and positrons during the 1993 balloon flight of the NMSU/Wizard-TS93 instrument

Energy Technology Data Exchange (ETDEWEB)

Bellotti, R.; Castellano, M. [Bari Univ. (Italy)]|[INFN, Bari (Italy); Candusso, M.; Casolino, M.; Morselli, A.; Picozza, P. [Rome Univ. `Tor Vergata` (Italy)]|[INFN, Rome (Italy); Aversa, F.; Boezio, M. [Trieste Univ. (Italy)]|[INFN, Trieste (Italy); Barbiellini, G. [Trieste Univ. (Italy)]|[INFN, Trieste (Italy); Basini, G. [INFN, Laboratori Nazionali di Frascati, Rome (Italy)

1995-09-01

The detectors used in the TS93 balloon flight produced a large volume of information for each cosmic ray trigger. Some of the data was visual in nature, other portions contained energy deposition and timing information. The data sets are amenable to conventional analysis techniques but there is no assurance that conventional techniques make full use of subtle correlations and relations amongst the detector responses. With the advent of neural network technologies, particularly adept at classification of complex phenomena, it would seem appropriate to explore the utility of neural network techniques to classify particles observed with the instruments. In this paper neural network based methodology for signal/background discrimination in a cosmic ray space experiment is discussed. Results are presented for electron and positron classification in the TS93 flight data set and will be compared to conventional analyses.

Application of artificial neural networks to evaluate weld defects of nuclear components

International Nuclear Information System (INIS)

Amin, E.S.

2007-01-01

Artificial neural networks (ANNs) are computational representations based on the biological neural architecture of the brain. ANNs have been successfully applied to a wide range of engineering and scientific applications, such as signal, image processing and data analysis. Although Radiographic testing is widely used for welding defects, it is unsuccessful in identifying some welding defects because of the nature of image formation and quality. Neoteric algorithms have been used for the purpose of weld defects identifications in radiographic images to replace the expert knowledge. The application of artificial neural networks in noise detection of radiographic films is used. Radial Basis (RB) and learning vector quantization (LVQ) were applied. The method shows good performance in weld defects recognition and classification problems.

The neural bases for valuing social equality.

Science.gov (United States)

Aoki, Ryuta; Yomogida, Yukihito; Matsumoto, Kenji

2015-01-01

The neural basis of how humans value and pursue social equality has become a major topic in social neuroscience research. Although recent studies have identified a set of brain regions and possible mechanisms that are involved in the neural processing of equality of outcome between individuals, how the human brain processes equality of opportunity remains unknown. In this review article, first we describe the importance of the distinction between equality of outcome and equality of opportunity, which has been emphasized in philosophy and economics. Next, we discuss possible approaches for empirical characterization of human valuation of equality of opportunity vs. equality of outcome. Understanding how these two concepts are distinct and interact with each other may provide a better explanation of complex human behaviors concerning fairness and social equality. Copyright © 2014 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

CONSTRUCTION COST PREDICTION USING NEURAL NETWORKS

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Smita K Magdum

2017-10-01

Full Text Available Construction cost prediction is important for construction firms to compete and grow in the industry. Accurate construction cost prediction in the early stage of project is important for project feasibility studies and successful completion. There are many factors that affect the cost prediction. This paper presents construction cost prediction as multiple regression model with cost of six materials as independent variables. The objective of this paper is to develop neural networks and multilayer perceptron based model for construction cost prediction. Different models of NN and MLP are developed with varying hidden layer size and hidden nodes. Four artificial neural network models and twelve multilayer perceptron models are compared. MLP and NN give better results than statistical regression method. As compared to NN, MLP works better on training dataset but fails on testing dataset. Five activation functions are tested to identify suitable function for the problem. ‘elu' transfer function gives better results than other transfer function.

Classification of data patterns using an autoassociative neural network topology

Science.gov (United States)

Dietz, W. E.; Kiech, E. L.; Ali, M.

1989-01-01

A diagnostic expert system based on neural networks is developed and applied to the real-time diagnosis of jet and rocket engines. The expert system methodologies are based on the analysis of patterns of behavior of physical mechanisms. In this approach, fault diagnosis is conceptualized as the mapping or association of patterns of sensor data to patterns representing fault conditions. The approach addresses deficiencies inherent in many feedforward neural network models and greatly reduces the number of networks necessary to identify the existence of a fault condition and estimate the duration and severity of the identified fault. The network topology used in the present implementation of the diagnostic system is described, as well as the training regimen used and the response of the system to inputs representing both previously observed and unknown fault scenarios. Noise effects on the integrity of the diagnosis are also evaluated.

Study on automatic ECT data evaluation by using neural network

International Nuclear Information System (INIS)

Komatsu, H.; Matsumoto, Y.; Badics, Z.; Aoki, K.; Nakayasu, F.; Hashimoto, M.; Miya, K.

1994-01-01

At the in--service inspection of the steam generator (SG) tubings in Pressurized Water Reactor (PWR) plant, eddy current testing (ECT) has been widely used at each outage. At present, ECT data evaluation is mainly performed by ECT data analyst, therefore it has the following problems. Only ECT signal configuration on the impedance trajectory is used in the evaluation. It is an enormous time consuming process. The evaluation result is influenced by the ability and experience of the analyst. Especially, it is difficult to identify the true defect signal hidden in background signals such as lift--off noise and deposit signals. In this work, the authors performed the study on the possibility of the application of neural network to ECT data evaluation. It was demonstrated that the neural network proved to be effective to identify the nature of defect, by selecting several optimum input parameters to categorize the raw ECT signals

Measures of coupling between neural populations based on Granger causality principle

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Maciej Kaminski

2016-10-01

Full Text Available This paper shortly reviews the measures used to estimate neural synchronization in experimental settings. Our focus is on multivariate measures of dependence based on the Granger causality (G-causality principle, their applications and performance in respect of robustness to noise, volume conduction, common driving, and presence of a weak node. Application of G-causality measures to EEG, intracranial signals and fMRI time series is addressed. G-causality based measures defined in the frequency domain allow the synchronization between neural populations and the directed propagation of their electrical activity to be determined. The time-varying G-causality based measure Short-time Directed Transfer Function (SDTF supplies information on the dynamics of synchronization and the organization of neural networks. Inspection of effective connectivity patterns indicates a modular structure of neural networks, with a stronger coupling within modules than between them. The hypothetical plausible mechanism of information processing, suggested by the identified synchronization patterns, is communication between tightly coupled modules intermitted by sparser interactions providing synchronization of distant structures.

Homology and homoplasy of swimming behaviors and neural circuits in the Nudipleura (Mollusca, Gastropoda, Opisthobranchia)

Science.gov (United States)

Newcomb, James M.; Sakurai, Akira; Lillvis, Joshua L.; Gunaratne, Charuni A.; Katz, Paul S.

2012-01-01

How neural circuit evolution relates to behavioral evolution is not well understood. Here the relationship between neural circuits and behavior is explored with respect to the swimming behaviors of the Nudipleura (Mollusca, Gastropoda, Opithobranchia). Nudipleura is a diverse monophyletic clade of sea slugs among which only a small percentage of species can swim. Swimming falls into a limited number of categories, the most prevalent of which are rhythmic left–right body flexions (LR) and rhythmic dorsal–ventral body flexions (DV). The phylogenetic distribution of these behaviors suggests a high degree of homoplasy. The central pattern generator (CPG) underlying DV swimming has been well characterized in Tritonia diomedea and in Pleurobranchaea californica. The CPG for LR swimming has been elucidated in Melibe leonina and Dendronotus iris, which are more closely related. The CPGs for the categorically distinct DV and LR swimming behaviors consist of nonoverlapping sets of homologous identified neurons, whereas the categorically similar behaviors share some homologous identified neurons, although the exact composition of neurons and synapses in the neural circuits differ. The roles played by homologous identified neurons in categorically distinct behaviors differ. However, homologous identified neurons also play different roles even in the swim CPGs of the two LR swimming species. Individual neurons can be multifunctional within a species. Some of those functions are shared across species, whereas others are not. The pattern of use and reuse of homologous neurons in various forms of swimming and other behaviors further demonstrates that the composition of neural circuits influences the evolution of behaviors. PMID:22723353

Neural System Prediction and Identification Challenge

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Ioannis eVlachos

2013-12-01

Full Text Available Can we infer the function of a biological neural network (BNN if we know the connectivity and activity of all its constituent neurons? This question is at the core of neuroscience and, accordingly, various methods have been developed to record the activity and connectivity of as many neurons as possible. Surprisingly, there is no theoretical or computational demonstration that neuronal activity and connectivity are indeed sufficient to infer the function of a BNN. Therefore, we pose the Neural Systems Identification and Prediction Challenge (nuSPIC. We provide the connectivity and activity of all neurons and invite participants (i to infer the functions implemented (hard-wired in spiking neural networks (SNNs by stimulating and recording the activity of neurons and, (ii to implement predefined mathematical/biological functions using SNNs. The nuSPICs can be accessed via a web-interface to the NEST simulator and the user is not required to know any specific programming language. Furthermore, the nuSPICs can be used as a teaching tool. Finally, nuSPICs use the crowd-sourcing model to address scientific issues. With this computational approach we aim to identify which functions can be inferred by systematic recordings of neuronal activity and connectivity. In addition, nuSPICs will help the design and application of new experimental paradigms based on the structure of the SNN and the presumed function which is to be discovered.

Neural system prediction and identification challenge.

Science.gov (United States)

Vlachos, Ioannis; Zaytsev, Yury V; Spreizer, Sebastian; Aertsen, Ad; Kumar, Arvind

2013-01-01

Can we infer the function of a biological neural network (BNN) if we know the connectivity and activity of all its constituent neurons?This question is at the core of neuroscience and, accordingly, various methods have been developed to record the activity and connectivity of as many neurons as possible. Surprisingly, there is no theoretical or computational demonstration that neuronal activity and connectivity are indeed sufficient to infer the function of a BNN. Therefore, we pose the Neural Systems Identification and Prediction Challenge (nuSPIC). We provide the connectivity and activity of all neurons and invite participants (1) to infer the functions implemented (hard-wired) in spiking neural networks (SNNs) by stimulating and recording the activity of neurons and, (2) to implement predefined mathematical/biological functions using SNNs. The nuSPICs can be accessed via a web-interface to the NEST simulator and the user is not required to know any specific programming language. Furthermore, the nuSPICs can be used as a teaching tool. Finally, nuSPICs use the crowd-sourcing model to address scientific issues. With this computational approach we aim to identify which functions can be inferred by systematic recordings of neuronal activity and connectivity. In addition, nuSPICs will help the design and application of new experimental paradigms based on the structure of the SNN and the presumed function which is to be discovered.

The V-ATPase a2-subunit as a putative endosomal pH-sensor.

Science.gov (United States)

Marshansky, V

2007-11-01

V-ATPase (vesicular H(+)-ATPase)-driven intravesicular acidification is crucial for vesicular trafficking. Defects in vesicular acidification and trafficking have recently been recognized as essential determinants of various human diseases. An important role of endosomal acidification in receptor-ligand dissociation and in activation of lysosomal hydrolytic enzymes is well established. However, the molecular mechanisms by which luminal pH information is transmitted to the cytosolic small GTPases that control trafficking events such as budding, coat formation and fusion are unknown. Here, we discuss our recent discovery that endosomal V-ATPase is a pH-sensor regulating the degradative pathway. According to our model, V-ATPase is responsible for: (i) the generation of a pH gradient between vesicular membranes; (ii) sensing of intravesicular pH; and (iii) transmitting this information to the cytosolic side of the membrane. We also propose the hypothetical molecular mechanism involved in function of the V-ATPase a2-subunit as a putative pH-sensor. Based on extensive experimental evidence on the crucial role of histidine residues in the function of PSPs (pH-sensing proteins) in eukaryotic cells, we hypothesize that pH-sensitive histidine residues within the intra-endosomal loops and/or C-terminal luminal tail of the a2-subunit could also be involved in the pH-sensing function of V-ATPase. However, in order to identify putative pH-sensitive histidine residues and to test this hypothesis, it is absolutely essential that we increase our understanding of the folding and transmembrane topology of the a-subunit isoforms of V-ATPase. Thus the crucial role of intra-endosomal histidine residues in pH-dependent conformational changes of the V-ATPase a2-isoform, its interaction with cytosolic small GTPases and ultimately in its acidification-dependent regulation of the endosomal/lysosomal protein degradative pathway remain to be determined.

Regulatory elements of the floral homeotic gene AGAMOUS identified by phylogenetic footprinting and shadowing.

Energy Technology Data Exchange (ETDEWEB)

Hong, R. L., Hamaguchi, L., Busch, M. A., and Weigel, D.

2003-06-01

OAK-B135 In Arabidopsis thaliana, cis-regulatory sequences of the floral homeotic gene AGAMOUS (AG) are located in the second intron. This 3 kb intron contains binding sites for two direct activators of AG, LEAFY (LFY) and WUSCHEL (WUS), along with other putative regulatory elements. We have used phylogenetic footprinting and the related technique of phylogenetic shadowing to identify putative cis-regulatory elements in this intron. Among 29 Brassicaceae, several other motifs, but not the LFY and WUS binding sites previously identified, are largely invariant. Using reporter gene analyses, we tested six of these motifs and found that they are all functionally important for activity of AG regulatory sequences in A. thaliana. Although there is little obvious sequence similarity outside the Brassicaceae, the intron from cucumber AG has at least partial activity in A. thaliana. Our studies underscore the value of the comparative approach as a tool that complements gene-by-gene promoter dissection, but also highlight that sequence-based studies alone are insufficient for a complete identification of cis-regulatory sites.

A Strategy for Identifying Quantitative Trait Genes Using Gene Expression Analysis and Causal Analysis

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Akira Ishikawa

2017-11-01

Full Text Available Large numbers of quantitative trait loci (QTL affecting complex diseases and other quantitative traits have been reported in humans and model animals. However, the genetic architecture of these traits remains elusive due to the difficulty in identifying causal quantitative trait genes (QTGs for common QTL with relatively small phenotypic effects. A traditional strategy based on techniques such as positional cloning does not always enable identification of a single candidate gene for a QTL of interest because it is difficult to narrow down a target genomic interval of the QTL to a very small interval harboring only one gene. A combination of gene expression analysis and statistical causal analysis can greatly reduce the number of candidate genes. This integrated approach provides causal evidence that one of the candidate genes is a putative QTG for the QTL. Using this approach, I have recently succeeded in identifying a single putative QTG for resistance to obesity in mice. Here, I outline the integration approach and discuss its usefulness using my studies as an example.

A Strategy for Identifying Quantitative Trait Genes Using Gene Expression Analysis and Causal Analysis.

Science.gov (United States)

Ishikawa, Akira

2017-11-27

Large numbers of quantitative trait loci (QTL) affecting complex diseases and other quantitative traits have been reported in humans and model animals. However, the genetic architecture of these traits remains elusive due to the difficulty in identifying causal quantitative trait genes (QTGs) for common QTL with relatively small phenotypic effects. A traditional strategy based on techniques such as positional cloning does not always enable identification of a single candidate gene for a QTL of interest because it is difficult to narrow down a target genomic interval of the QTL to a very small interval harboring only one gene. A combination of gene expression analysis and statistical causal analysis can greatly reduce the number of candidate genes. This integrated approach provides causal evidence that one of the candidate genes is a putative QTG for the QTL. Using this approach, I have recently succeeded in identifying a single putative QTG for resistance to obesity in mice. Here, I outline the integration approach and discuss its usefulness using my studies as an example.

Inhibitory Synaptic Plasticity - Spike timing dependence and putative network function.

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Tim P Vogels

2013-07-01

Full Text Available While the plasticity of excitatory synaptic connections in the brain has been widely studied, the plasticity of inhibitory connections is much less understood. Here, we present recent experimental and theoretical □ndings concerning the rules of spike timing-dependent inhibitory plasticity and their putative network function. This is a summary of a workshop at the COSYNE conference 2012.

Neural Networks: Implementations and Applications

OpenAIRE

Vonk, E.; Veelenturf, L.P.J.; Jain, L.C.

1996-01-01

Artificial neural networks, also called neural networks, have been used successfully in many fields including engineering, science and business. This paper presents the implementation of several neural network simulators and their applications in character recognition and other engineering areas

Neural analysis of bovine ovaries ultrasound images in the identification process of the corpus luteum

Science.gov (United States)

Górna, K.; Jaśkowski, B. M.; Okoń, P.; Czechlowski, M.; Koszela, K.; Zaborowicz, M.; Idziaszek, P.

2017-07-01

The aim of the paper is to shown the neural image analysis as a method useful for identifying the development stage of the domestic bovine corpus luteum on digital USG (UltraSonoGraphy) images. Corpus luteum (CL) is a transient endocrine gland that develops after ovulation from the follicle secretory cells. The aim of CL is the production of progesterone, which regulates many reproductive functions. In the presented studies, identification of the corpus luteum was carried out on the basis of information contained in ultrasound digital images. Development stage of the corpus luteum was considered in two aspects: just before and middle of domination phase and luteolysis and degradation phase. Prior to the classification, the ultrasound images have been processed using a GLCM (Gray Level Co-occurence Matrix). To generate a classification model, a Neural Networks module implemented in the STATISTICA was used. Five representative parameters describing the ultrasound image were used as learner variables. On the output of the artificial neural network was generated information about the development stage of the corpus luteum. Results of this study indicate that neural image analysis combined with GLCM texture analysis may be a useful tool for identifying the bovine corpus luteum in the context of its development phase. Best-generated artificial neural network model was the structure of MLP (Multi Layer Perceptron) 5:5-17-1:1.

A Sequence and Structure Based Method to Predict Putative Substrates, Functions and Regulatory Networks of Endo Proteases

Science.gov (United States)

Venkatraman, Prasanna; Balakrishnan, Satish; Rao, Shashidhar; Hooda, Yogesh; Pol, Suyog

2009-01-01

Background Proteases play a central role in cellular homeostasis and are responsible for the spatio- temporal regulation of function. Many putative proteases have been recently identified through genomic approaches, leading to a surge in global profiling attempts to characterize their function. Through such efforts and others it has become evident that many proteases play non-traditional roles. Accordingly, the number and the variety of the substrate repertoire of proteases are expected to be much larger than previously assumed. In line with such global profiling attempts, we present here a method for the prediction of natural substrates of endo proteases (human proteases used as an example) by employing short peptide sequences as specificity determinants. Methodology/Principal Findings Our method incorporates specificity determinants unique to individual enzymes and physiologically relevant dual filters namely, solvent accessible surface area-a parameter dependent on protein three-dimensional structure and subcellular localization. By incorporating such hitherto unused principles in prediction methods, a novel ligand docking strategy to mimic substrate binding at the active site of the enzyme, and GO functions, we identify and perform subjective validation on putative substrates of matriptase and highlight new functions of the enzyme. Using relative solvent accessibility to rank order we show how new protease regulatory networks and enzyme cascades can be created. Conclusion We believe that our physiologically relevant computational approach would be a very useful complementary method in the current day attempts to profile proteases (endo proteases in particular) and their substrates. In addition, by using functional annotations, we have demonstrated how normal and unknown functions of a protease can be envisaged. We have developed a network which can be integrated to create a proteolytic world. This network can in turn be extended to integrate other regulatory

GWAS of clinically defined gout and subtypes identifies multiple susceptibility loci that include urate transporter genes

NARCIS (Netherlands)

Nakayama, A.; Nakaoka, H.; Yamamoto, K.; Sakiyama, M.; Shaukat, A.; Toyoda, Y.; Okada, Y.; Kamatani, Y.; Nakamura, T.; Takada, T.; Inoue, K.; Yasujima, T.; Yuasa, H.; Shirahama, Y.; Nakashima, H.; Shimizu, S.; Higashino, T.; Kawamura, Y.; Ogata, H.; Kawaguchi, M.; Ohkawa, Y.; Danjoh, I.; Tokumasu, A.; Ooyama, K.; Ito, T.; Kondo, T.; Wakai, K.; Stiburkova, B.; Pavelka, K.; Stamp, L.K.; Dalbeth, N.; Sakurai, Y.; Suzuki, H; Hosoyamada, M.; Fujimori, S.; Yokoo, T.; Hosoya, T.; Inoue, I.; Takahashi, A.; Kubo, M.; Ooyama, H.; Shimizu, T.; Ichida, K.; Shinomiya, N.; Merriman, T.R.; Matsuo, H.; Andres, M; Joosten, L.A.; Janssen, M.C.H.; Jansen, T.L.; Liote, F.; Radstake, T.R.; Riches, P.L.; So, A.; Tauches, A.K.

2017-01-01

OBJECTIVE: A genome-wide association study (GWAS) of gout and its subtypes was performed to identify novel gout loci, including those that are subtype-specific. METHODS: Putative causal association signals from a GWAS of 945 clinically defined gout cases and 1213 controls from Japanese males were

SiNC: Saliency-injected neural codes for representation and efficient retrieval of medical radiographs.

Directory of Open Access Journals (Sweden)

Jamil Ahmad

Full Text Available Medical image collections contain a wealth of information which can assist radiologists and medical experts in diagnosis and disease detection for making well-informed decisions. However, this objective can only be realized if efficient access is provided to semantically relevant cases from the ever-growing medical image repositories. In this paper, we present an efficient method for representing medical images by incorporating visual saliency and deep features obtained from a fine-tuned convolutional neural network (CNN pre-trained on natural images. Saliency detector is employed to automatically identify regions of interest like tumors, fractures, and calcified spots in images prior to feature extraction. Neuronal activation features termed as neural codes from different CNN layers are comprehensively studied to identify most appropriate features for representing radiographs. This study revealed that neural codes from the last fully connected layer of the fine-tuned CNN are found to be the most suitable for representing medical images. The neural codes extracted from the entire image and salient part of the image are fused to obtain the saliency-injected neural codes (SiNC descriptor which is used for indexing and retrieval. Finally, locality sensitive hashing techniques are applied on the SiNC descriptor to acquire short binary codes for allowing efficient retrieval in large scale image collections. Comprehensive experimental evaluations on the radiology images dataset reveal that the proposed framework achieves high retrieval accuracy and efficiency for scalable image retrieval applications and compares favorably with existing approaches.

Identifying pathogenicity genes in the rubber tree anthracnose fungus Colletotrichum gloeosporioides through random insertional mutagenesis.

Science.gov (United States)

Cai, Zhiying; Li, Guohua; Lin, Chunhua; Shi, Tao; Zhai, Ligang; Chen, Yipeng; Huang, Guixiu

2013-07-19

To gain more insight into the molecular mechanisms of Colletotrichum gloeosporioides pathogenesis, Agrobacterium tumefaciens-mediated transformation (ATMT) was used to identify mutants of C. gloeosporioides impaired in pathogenicity. An ATMT library of 4128 C. gloeosporioides transformants was generated. Transformants were screened for defects in pathogenicity with a detached copper brown leaf assay. 32 mutants showing reproducible pathogenicity defects were obtained. Southern blot analysis showed 60.4% of the transformants had single-site T-DNA integrations. 16 Genomic sequences flanking T-DNA were recovered from mutants by thermal asymmetric interlaced PCR, and were used to isolate the tagged genes from the genome sequence of wild-type C. gloeosporioides by Basic Local Alignment Search Tool searches against the local genome database of the wild-type C. gloeosporioides. One potential pathogenicity genes encoded calcium-translocating P-type ATPase. Six potential pathogenicity genes had no known homologs in filamentous fungi and were likely to be novel fungal virulence factors. Two putative genes encoded Glycosyltransferase family 28 domain-containing protein and Mov34/MPN/PAD-1 family protein, respectively. Five potential pathogenicity genes had putative function matched with putative protein of other Colletotrichum species. Two known C. gloeosporioides pathogenicity genes were also identified, the encoding Glomerella cingulata hard-surface induced protein and C. gloeosporioides regulatory subunit of protein kinase A gene involved in cAMP-dependent PKA signal transduction pathway. Copyright © 2013 Elsevier GmbH. All rights reserved.

Proteinaceous Pheromone Homologs Identified from the Cloacal Gland Transcriptome of a Male Axolotl, Ambystoma mexicanum.

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Kevin W Hall

Full Text Available Pheromones play an important role in modifying vertebrate behavior, especially during courtship and mating. Courtship behavior in urodele amphibians often includes female exposure to secretions from the cloacal gland, as well as other scent glands. The first vertebrate proteinaceous pheromone discovered, the decapeptide sodefrin, is a female attracting pheromone secreted by the cloacal gland of male Cynops pyrrhogaster. Other proteinaceous pheromones in salamanders have been shown to elicit responses from females towards conspecific males. The presence and levels of expression of proteinaceous pheromones have not been identified in the family Ambystomatidae, which includes several important research models. The objective of this research was therefore to identify putative proteinaceous pheromones from male axolotls, Ambystoma mexicanum, as well as their relative expression levels. The results indicate that axolotls possess two different forms of sodefrin precursor-like factor (alpha and beta, as well as a putative ortholog of plethodontid modulating factor. The beta form of sodefrin precursor-like factor was amongst the most highly expressed transcripts within the cloacal gland. The ortholog of plethodontid modulating factor was expressed at a level equivalent to the beta sodefrin precursor-like factor. The results are from a single male axolotl; therefore, we are unable to assess how representative our results may be. Nevertheless, the presence of these highly expressed proteinaceous pheromones suggests that male axolotls use multiple chemical cues to attract female conspecifics. Behavioral assays would indicate whether the putative protein pheromones elicit courtship activity from female axolotls.

Proteinaceous Pheromone Homologs Identified from the Cloacal Gland Transcriptome of a Male Axolotl, Ambystoma mexicanum.

Science.gov (United States)

Hall, Kevin W; Eisthen, Heather L; Williams, Barry L

2016-01-01

Pheromones play an important role in modifying vertebrate behavior, especially during courtship and mating. Courtship behavior in urodele amphibians often includes female exposure to secretions from the cloacal gland, as well as other scent glands. The first vertebrate proteinaceous pheromone discovered, the decapeptide sodefrin, is a female attracting pheromone secreted by the cloacal gland of male Cynops pyrrhogaster. Other proteinaceous pheromones in salamanders have been shown to elicit responses from females towards conspecific males. The presence and levels of expression of proteinaceous pheromones have not been identified in the family Ambystomatidae, which includes several important research models. The objective of this research was therefore to identify putative proteinaceous pheromones from male axolotls, Ambystoma mexicanum, as well as their relative expression levels. The results indicate that axolotls possess two different forms of sodefrin precursor-like factor (alpha and beta), as well as a putative ortholog of plethodontid modulating factor. The beta form of sodefrin precursor-like factor was amongst the most highly expressed transcripts within the cloacal gland. The ortholog of plethodontid modulating factor was expressed at a level equivalent to the beta sodefrin precursor-like factor. The results are from a single male axolotl; therefore, we are unable to assess how representative our results may be. Nevertheless, the presence of these highly expressed proteinaceous pheromones suggests that male axolotls use multiple chemical cues to attract female conspecifics. Behavioral assays would indicate whether the putative protein pheromones elicit courtship activity from female axolotls.

Germinal Center Optimization Applied to Neural Inverse Optimal Control for an All-Terrain Tracked Robot

Directory of Open Access Journals (Sweden)

Carlos Villaseñor

2017-12-01

Full Text Available Nowadays, there are several meta-heuristics algorithms which offer solutions for multi-variate optimization problems. These algorithms use a population of candidate solutions which explore the search space, where the leadership plays a big role in the exploration-exploitation equilibrium. In this work, we propose to use a Germinal Center Optimization algorithm (GCO which implements temporal leadership through modeling a non-uniform competitive-based distribution for particle selection. GCO is used to find an optimal set of parameters for a neural inverse optimal control applied to all-terrain tracked robot. In the Neural Inverse Optimal Control (NIOC scheme, a neural identifier, based on Recurrent High Orden Neural Network (RHONN trained with an extended kalman filter algorithm, is used to obtain a model of the system, then, a control law is design using such model with the inverse optimal control approach. The RHONN identifier is developed without knowledge of the plant model or its parameters, on the other hand, the inverse optimal control is designed for tracking velocity references. Applicability of the proposed scheme is illustrated using simulations results as well as real-time experimental results with an all-terrain tracked robot.

Novel Adaptive Forward Neural MIMO NARX Model for the Identification of Industrial 3-DOF Robot Arm Kinematics

OpenAIRE

Ho Pham Huy Anh; Nguyen Thanh Nam

2012-01-01

In this paper, a novel forward adaptive neural MIMO NARX model is used for modelling and identifying the forward kinematics of an industrial 3‐DOF robot arm system. The nonlinear features of the forward kinematics of the industrial robot arm drive are thoroughly modelled based on the forward adaptive neural NARX model‐based identification process using experimental input‐output training data. This paper proposes a novel use of a back propagation (BP) algorithm to generate the forward neural M...

Vector neural net identifying many strongly distorted and correlated patterns

Science.gov (United States)

Kryzhanovsky, Boris V.; Mikaelian, Andrei L.; Fonarev, Anatoly B.

2005-01-01

We suggest an effective and simple algorithm providing a polynomial storage capacity of a network of the form M ~ N2s+1, where N is the dimension of the stored binary patterns. In this problem the value of the free parameter s is restricted by the inequalities N >> slnN >= 1. The algorithm allows us to identify a large number of highly distorted similar patterns. The negative influence of correlations of the patterns is suppressed by choosing a sufficiently large value of the parameter s. We show the efficiency of the algorithm by the example of a perceptron identifier, but it also can be used to increase the storage capacity of full connected systems of associative memory.

Cloning and sequence analysis of putative type II fatty acid synthase ...

Indian Academy of Sciences (India)

Prakash

Cloning and sequence analysis of putative type II fatty acid synthase genes from Arachis hypogaea L. ... acyl carrier protein (ACP), malonyl-CoA:ACP transacylase, β-ketoacyl-ACP .... Helix II plays a dominant role in the interaction ... main distinguishing features of plant ACPs in plastids and ..... synthase component; J. Biol.

Neurophysiology and neural engineering: a review.

Science.gov (United States)

Prochazka, Arthur

2017-08-01

Neurophysiology is the branch of physiology concerned with understanding the function of neural systems. Neural engineering (also known as neuroengineering) is a discipline within biomedical engineering that uses engineering techniques to understand, repair, replace, enhance, or otherwise exploit the properties and functions of neural systems. In most cases neural engineering involves the development of an interface between electronic devices and living neural tissue. This review describes the origins of neural engineering, the explosive development of methods and devices commencing in the late 1950s, and the present-day devices that have resulted. The barriers to interfacing electronic devices with living neural tissues are many and varied, and consequently there have been numerous stops and starts along the way. Representative examples are discussed. None of this could have happened without a basic understanding of the relevant neurophysiology. I also consider examples of how neural engineering is repaying the debt to basic neurophysiology with new knowledge and insight. Copyright © 2017 the American Physiological Society.

Putative golden proportions as predictors of facial esthetics in adolescents.

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Kiekens, Rosemie M A; Kuijpers-Jagtman, Anne Marie; van 't Hof, Martin A; van 't Hof, Bep E; Maltha, Jaap C

2008-10-01

In orthodontics, facial esthetics is assumed to be related to golden proportions apparent in the ideal human face. The aim of the study was to analyze the putative relationship between facial esthetics and golden proportions in white adolescents. Seventy-six adult laypeople evaluated sets of photographs of 64 adolescents on a visual analog scale (VAS) from 0 to 100. The facial esthetic value of each subject was calculated as a mean VAS score. Three observers recorded the position of 13 facial landmarks included in 19 putative golden proportions, based on the golden proportions as defined by Ricketts. The proportions and each proportion's deviation from the golden target (1.618) were calculated. This deviation was then related to the VAS scores. Only 4 of the 19 proportions had a significant negative correlation with the VAS scores, indicating that beautiful faces showed less deviation from the golden standard than less beautiful faces. Together, these variables explained only 16% of the variance. Few golden proportions have a significant relationship with facial esthetics in adolescents. The explained variance of these variables is too small to be of clinical importance.

Fast and Efficient Asynchronous Neural Computation with Adapting Spiking Neural Networks

NARCIS (Netherlands)

D. Zambrano (Davide); S.M. Bohte (Sander)

2016-01-01

textabstractBiological neurons communicate with a sparing exchange of pulses - spikes. It is an open question how real spiking neurons produce the kind of powerful neural computation that is possible with deep artificial neural networks, using only so very few spikes to communicate. Building on

Boosted Jet Tagging with Jet-Images and Deep Neural Networks

International Nuclear Information System (INIS)

Kagan, Michael; Oliveira, Luke de; Mackey, Lester; Nachman, Benjamin; Schwartzman, Ariel

2016-01-01

Building on the jet-image based representation of high energy jets, we develop computer vision based techniques for jet tagging through the use of deep neural networks. Jet-images enabled the connection between jet substructure and tagging with the fields of computer vision and image processing. We show how applying such techniques using deep neural networks can improve the performance to identify highly boosted W bosons with respect to state-of-the-art substructure methods. In addition, we explore new ways to extract and visualize the discriminating features of different classes of jets, adding a new capability to understand the physics within jets and to design more powerful jet tagging methods

Neuron's eye view: Inferring features of complex stimuli from neural responses.

Directory of Open Access Journals (Sweden)

Xin Chen

2017-08-01

Full Text Available Experiments that study neural encoding of stimuli at the level of individual neurons typically choose a small set of features present in the world-contrast and luminance for vision, pitch and intensity for sound-and assemble a stimulus set that systematically varies along these dimensions. Subsequent analysis of neural responses to these stimuli typically focuses on regression models, with experimenter-controlled features as predictors and spike counts or firing rates as responses. Unfortunately, this approach requires knowledge in advance about the relevant features coded by a given population of neurons. For domains as complex as social interaction or natural movement, however, the relevant feature space is poorly understood, and an arbitrary a priori choice of features may give rise to confirmation bias. Here, we present a Bayesian model for exploratory data analysis that is capable of automatically identifying the features present in unstructured stimuli based solely on neuronal responses. Our approach is unique within the class of latent state space models of neural activity in that it assumes that firing rates of neurons are sensitive to multiple discrete time-varying features tied to the stimulus, each of which has Markov (or semi-Markov dynamics. That is, we are modeling neural activity as driven by multiple simultaneous stimulus features rather than intrinsic neural dynamics. We derive a fast variational Bayesian inference algorithm and show that it correctly recovers hidden features in synthetic data, as well as ground-truth stimulus features in a prototypical neural dataset. To demonstrate the utility of the algorithm, we also apply it to cluster neural responses and demonstrate successful recovery of features corresponding to monkeys and faces in the image set.

Artificial neural networks in NDT

International Nuclear Information System (INIS)

Abdul Aziz Mohamed

2001-01-01

Artificial neural networks, simply known as neural networks, have attracted considerable interest in recent years largely because of a growing recognition of the potential of these computational paradigms as powerful alternative models to conventional pattern recognition or function approximation techniques. The neural networks approach is having a profound effect on almost all fields, and has been utilised in fields Where experimental inter-disciplinary work is being carried out. Being a multidisciplinary subject with a broad knowledge base, Nondestructive Testing (NDT) or Nondestructive Evaluation (NDE) is no exception. This paper explains typical applications of neural networks in NDT/NDE. Three promising types of neural networks are highlighted, namely, back-propagation, binary Hopfield and Kohonen's self-organising maps. (Author)

A neural network for the Bragg synthetic curves recognition

International Nuclear Information System (INIS)

Reynoso V, M.R.; Vega C, J.J.; Fernandez A, J.; Belmont M, E.; Policroniades R, R.; Moreno B, E.

1996-01-01

A ionization chamber was employed named Bragg curve spectroscopy. The Bragg peak amplitude is a monotone growing function of Z, which permits to identify elements through their measurement. A better technique for this measurement is to improve the use of neural networks with the purpose of the identification of the Bragg curve. (Author)

A neural network device for on-line particle identification in cosmic ray experiments

International Nuclear Information System (INIS)

Scrimaglio, R.; Finetti, N.; D'Altorio, L.; Rantucci, E.; Raso, M.; Segreto, E.; Tassoni, A.; Cardarilli, G.C.

2004-01-01

On-line particle identification is one of the main goals of many experiments in space both for rare event studies and for optimizing measurements along the orbital trajectory. Neural networks can be a useful tool for signal processing and real time data analysis in such experiments. In this document we report on the performances of a programmable neural device which was developed in VLSI analog/digital technology. Neurons and synapses were accomplished by making use of Operational Transconductance Amplifier (OTA) structures. In this paper we report on the results of measurements performed in order to verify the agreement of the characteristic curves of each elementary cell with simulations and on the device performances obtained by implementing simple neural structures on the VLSI chip. A feed-forward neural network (Multi-Layer Perceptron, MLP) was implemented on the VLSI chip and trained to identify particles by processing the signals of two-dimensional position-sensitive Si detectors. The radiation monitoring device consisted of three double-sided silicon strip detectors. From the analysis of a set of simulated data it was found that the MLP implemented on the neural device gave results comparable with those obtained with the standard method of analysis confirming that the implemented neural network could be employed for real time particle identification

Anosmin-1 is essential for neural crest and cranial placodes formation in Xenopus.

Science.gov (United States)

Bae, Chang-Joon; Hong, Chang-Soo; Saint-Jeannet, Jean-Pierre

2018-01-15

During embryogenesis vertebrates develop a complex craniofacial skeleton associated with sensory organs. These structures are primarily derived from two embryonic cell populations the neural crest and cranial placodes, respectively. Neural crest cells and cranial placodes are specified through the integrated action of several families of signaling molecules, and the subsequent activation of a complex network of transcription factors. Here we describe the expression and function of Anosmin-1 (Anos1), an extracellular matrix protein, during neural crest and cranial placodes development in Xenopus laevis. Anos1 was identified as a target of Pax3 and Zic1, two transcription factors necessary and sufficient to generate neural crest and cranial placodes. Anos1 is expressed in cranial neural crest progenitors at early neurula stage and in cranial placode derivatives later in development. We show that Anos1 function is required for neural crest and sensory organs development in Xenopus, consistent with the defects observed in Kallmann syndrome patients carrying a mutation in ANOS1. These findings indicate that anos1 has a conserved function in the development of craniofacial structures, and indicate that anos1-depleted Xenopus embryos represent a useful model to analyze the pathogenesis of Kallmann syndrome. Copyright © 2017. Published by Elsevier Inc.

High-Content Screening in hPSC-Neural Progenitors Identifies Drug Candidates that Inhibit Zika Virus Infection in Fetal-like Organoids and Adult Brain.

Science.gov (United States)

Zhou, Ting; Tan, Lei; Cederquist, Gustav Y; Fan, Yujie; Hartley, Brigham J; Mukherjee, Suranjit; Tomishima, Mark; Brennand, Kristen J; Zhang, Qisheng; Schwartz, Robert E; Evans, Todd; Studer, Lorenz; Chen, Shuibing

2017-08-03

Zika virus (ZIKV) infects fetal and adult human brain and is associated with serious neurological complications. To date, no therapeutic treatment is available to treat ZIKV-infected patients. We performed a high-content chemical screen using human pluripotent stem cell-derived cortical neural progenitor cells (hNPCs) and found that hippeastrine hydrobromide (HH) and amodiaquine dihydrochloride dihydrate (AQ) can inhibit ZIKV infection in hNPCs. Further validation showed that HH also rescues ZIKV-induced growth and differentiation defects in hNPCs and human fetal-like forebrain organoids. Finally, HH and AQ inhibit ZIKV infection in adult mouse brain in vivo. Strikingly, HH suppresses viral propagation when administered to adult mice with active ZIKV infection, highlighting its therapeutic potential. Our approach highlights the power of stem cell-based screens and validation in human forebrain organoids and mouse models in identifying drug candidates for treating ZIKV infection and related neurological complications in fetal and adult patients. Copyright © 2017 Elsevier Inc. All rights reserved.

An efficient cDNA-AFLP-based strategy for the identification of putative pathogenicity factors from the potato cyst nematode Globodera rostochiensis.

Science.gov (United States)

Qin, L; Overmars, H; Helder, J; Popeijus, H; van der Voort, J R; Groenink, W; van Koert, P; Schots, A; Bakker, J; Smant, G

2000-08-01

A new strategy has been designed to identify putative pathogenicity factors from the dorsal or subventral esophageal glands of the potato cyst nematode Globodera rostochiensis. Three independent criteria were used for selection. First, genes of interest should predominantly be expressed in infective second-stage juveniles, and not, or to a far lesser extent, in younger developmental stages. For this, gene expression profiles from five different developmental stages were generated with cDNA-AFLP (amplified fragment length polymorphism). Secondly, the mRNA corresponding to such a putative pathogenicity factor should predominantly be present in the esophageal glands of pre-parasitic juveniles. This was checked by in situ hybridization. As a third criterion, these proteinaceous factors should be preceded by a signal peptide for secretion. Expression profiles of more than 4,000 genes were generated and three up-regulated, dorsal gland-specific proteins preceded by signal peptide for secretion were identified. No dorsal gland genes have been cloned before from plant-parasitic nematodes. The partial sequence of these three factors, A4, A18, and A41, showed no significant homology to any known gene. Their presence in the dorsal glands of infective juveniles suggests that these proteins could be involved in feeding cell initiation, and not in migration in the plant root or in protection against plant defense responses. Finally, the applicability of this new strategy in other plant-microbe interactions is discussed.

Fractional Hopfield Neural Networks: Fractional Dynamic Associative Recurrent Neural Networks.

Science.gov (United States)

Pu, Yi-Fei; Yi, Zhang; Zhou, Ji-Liu

2017-10-01

This paper mainly discusses a novel conceptual framework: fractional Hopfield neural networks (FHNN). As is commonly known, fractional calculus has been incorporated into artificial neural networks, mainly because of its long-term memory and nonlocality. Some researchers have made interesting attempts at fractional neural networks and gained competitive advantages over integer-order neural networks. Therefore, it is naturally makes one ponder how to generalize the first-order Hopfield neural networks to the fractional-order ones, and how to implement FHNN by means of fractional calculus. We propose to introduce a novel mathematical method: fractional calculus to implement FHNN. First, we implement fractor in the form of an analog circuit. Second, we implement FHNN by utilizing fractor and the fractional steepest descent approach, construct its Lyapunov function, and further analyze its attractors. Third, we perform experiments to analyze the stability and convergence of FHNN, and further discuss its applications to the defense against chip cloning attacks for anticounterfeiting. The main contribution of our work is to propose FHNN in the form of an analog circuit by utilizing a fractor and the fractional steepest descent approach, construct its Lyapunov function, prove its Lyapunov stability, analyze its attractors, and apply FHNN to the defense against chip cloning attacks for anticounterfeiting. A significant advantage of FHNN is that its attractors essentially relate to the neuron's fractional order. FHNN possesses the fractional-order-stability and fractional-order-sensitivity characteristics.

Forecasting solar proton event with artificial neural network

Science.gov (United States)

Gong, J.; Wang, J.; Xue, B.; Liu, S.; Zou, Z.

Solar proton event (SPE), relatively rare but popular in solar maximum, can bring hazard situation to spacecraft. As a special event, SPE always accompanies flare, which is also called proton flare. To produce such an eruptive event, large amount energy must be accumulated within the active region. So we can investigate the character of the active region and its evolving trend, together with other such as cm radio emission and soft X-ray background to evaluate the potential of SEP in chosen area. In order to summarize the omen of SPEs in the active regions behind the observed parameters, we employed AI technology. Full connecting neural network was chosen to fulfil this job. After constructing the network, we train it with 13 parameters that was able to exhibit the character of active regions and their evolution trend. More than 80 sets of event parameter were defined to teach the neural network to identify whether an active region was potential of SPE. Then we test this model with a data base consisting SPE and non-SPE cases that was not used to train the neural network. The result showed that 75% of the choice by the model was right.

Changes in neural network homeostasis trigger neuropsychiatric symptoms.

Science.gov (United States)

Winkelmann, Aline; Maggio, Nicola; Eller, Joanna; Caliskan, Gürsel; Semtner, Marcus; Häussler, Ute; Jüttner, René; Dugladze, Tamar; Smolinsky, Birthe; Kowalczyk, Sarah; Chronowska, Ewa; Schwarz, Günter; Rathjen, Fritz G; Rechavi, Gideon; Haas, Carola A; Kulik, Akos; Gloveli, Tengis; Heinemann, Uwe; Meier, Jochen C

2014-02-01

The mechanisms that regulate the strength of synaptic transmission and intrinsic neuronal excitability are well characterized; however, the mechanisms that promote disease-causing neural network dysfunction are poorly defined. We generated mice with targeted neuron type-specific expression of a gain-of-function variant of the neurotransmitter receptor for glycine (GlyR) that is found in hippocampectomies from patients with temporal lobe epilepsy. In this mouse model, targeted expression of gain-of-function GlyR in terminals of glutamatergic cells or in parvalbumin-positive interneurons persistently altered neural network excitability. The increased network excitability associated with gain-of-function GlyR expression in glutamatergic neurons resulted in recurrent epileptiform discharge, which provoked cognitive dysfunction and memory deficits without affecting bidirectional synaptic plasticity. In contrast, decreased network excitability due to gain-of-function GlyR expression in parvalbumin-positive interneurons resulted in an anxiety phenotype, but did not affect cognitive performance or discriminative associative memory. Our animal model unveils neuron type-specific effects on cognition, formation of discriminative associative memory, and emotional behavior in vivo. Furthermore, our data identify a presynaptic disease-causing molecular mechanism that impairs homeostatic regulation of neural network excitability and triggers neuropsychiatric symptoms.

Fluctuation-Driven Neural Dynamics Reproduce Drosophila Locomotor Patterns.

Directory of Open Access Journals (Sweden)

Andrea Maesani

2015-11-01

Full Text Available The neural mechanisms determining the timing of even simple actions, such as when to walk or rest, are largely mysterious. One intriguing, but untested, hypothesis posits a role for ongoing activity fluctuations in neurons of central action selection circuits that drive animal behavior from moment to moment. To examine how fluctuating activity can contribute to action timing, we paired high-resolution measurements of freely walking Drosophila melanogaster with data-driven neural network modeling and dynamical systems analysis. We generated fluctuation-driven network models whose outputs-locomotor bouts-matched those measured from sensory-deprived Drosophila. From these models, we identified those that could also reproduce a second, unrelated dataset: the complex time-course of odor-evoked walking for genetically diverse Drosophila strains. Dynamical models that best reproduced both Drosophila basal and odor-evoked locomotor patterns exhibited specific characteristics. First, ongoing fluctuations were required. In a stochastic resonance-like manner, these fluctuations allowed neural activity to escape stable equilibria and to exceed a threshold for locomotion. Second, odor-induced shifts of equilibria in these models caused a depression in locomotor frequency following olfactory stimulation. Our models predict that activity fluctuations in action selection circuits cause behavioral output to more closely match sensory drive and may therefore enhance navigation in complex sensory environments. Together these data reveal how simple neural dynamics, when coupled with activity fluctuations, can give rise to complex patterns of animal behavior.

Barratt Impulsivity and Neural Regulation of Physiological Arousal.

Directory of Open Access Journals (Sweden)

Sheng Zhang

Full Text Available Theories of personality have posited an increased arousal response to external stimulation in impulsive individuals. However, there is a dearth of studies addressing the neural basis of this association.We recorded skin conductance in 26 individuals who were assessed with Barratt Impulsivity Scale (BIS-11 and performed a stop signal task during functional magnetic resonance imaging. Imaging data were processed and modeled with Statistical Parametric Mapping. We used linear regressions to examine correlations between impulsivity and skin conductance response (SCR to salient events, identify the neural substrates of arousal regulation, and examine the relationship between the regulatory mechanism and impulsivity.Across subjects, higher impulsivity is associated with greater SCR to stop trials. Activity of the ventromedial prefrontal cortex (vmPFC negatively correlated to and Granger caused skin conductance time course. Furthermore, higher impulsivity is associated with a lesser strength of Granger causality of vmPFC activity on skin conductance, consistent with diminished control of physiological arousal to external stimulation. When men (n = 14 and women (n = 12 were examined separately, however, there was evidence suggesting association between impulsivity and vmPFC regulation of arousal only in women.Together, these findings confirmed the link between Barratt impulsivity and heightened arousal to salient stimuli in both genders and suggested the neural bases of altered regulation of arousal in impulsive women. More research is needed to explore the neural processes of arousal regulation in impulsive individuals and in clinical conditions that implicate poor impulse control.

Barratt Impulsivity and Neural Regulation of Physiological Arousal.

Science.gov (United States)

Zhang, Sheng; Hu, Sien; Hu, Jianping; Wu, Po-Lun; Chao, Herta H; Li, Chiang-shan R

2015-01-01

Theories of personality have posited an increased arousal response to external stimulation in impulsive individuals. However, there is a dearth of studies addressing the neural basis of this association. We recorded skin conductance in 26 individuals who were assessed with Barratt Impulsivity Scale (BIS-11) and performed a stop signal task during functional magnetic resonance imaging. Imaging data were processed and modeled with Statistical Parametric Mapping. We used linear regressions to examine correlations between impulsivity and skin conductance response (SCR) to salient events, identify the neural substrates of arousal regulation, and examine the relationship between the regulatory mechanism and impulsivity. Across subjects, higher impulsivity is associated with greater SCR to stop trials. Activity of the ventromedial prefrontal cortex (vmPFC) negatively correlated to and Granger caused skin conductance time course. Furthermore, higher impulsivity is associated with a lesser strength of Granger causality of vmPFC activity on skin conductance, consistent with diminished control of physiological arousal to external stimulation. When men (n = 14) and women (n = 12) were examined separately, however, there was evidence suggesting association between impulsivity and vmPFC regulation of arousal only in women. Together, these findings confirmed the link between Barratt impulsivity and heightened arousal to salient stimuli in both genders and suggested the neural bases of altered regulation of arousal in impulsive women. More research is needed to explore the neural processes of arousal regulation in impulsive individuals and in clinical conditions that implicate poor impulse control.

Bidirectional neural interface: Closed-loop feedback control for hybrid neural systems.

Science.gov (United States)

Chou, Zane; Lim, Jeffrey; Brown, Sophie; Keller, Melissa; Bugbee, Joseph; Broccard, Frédéric D; Khraiche, Massoud L; Silva, Gabriel A; Cauwenberghs, Gert

2015-01-01

Closed-loop neural prostheses enable bidirectional communication between the biological and artificial components of a hybrid system. However, a major challenge in this field is the limited understanding of how these components, the two separate neural networks, interact with each other. In this paper, we propose an in vitro model of a closed-loop system that allows for easy experimental testing and modification of both biological and artificial network parameters. The interface closes the system loop in real time by stimulating each network based on recorded activity of the other network, within preset parameters. As a proof of concept we demonstrate that the bidirectional interface is able to establish and control network properties, such as synchrony, in a hybrid system of two neural networks more significantly more effectively than the same system without the interface or with unidirectional alternatives. This success holds promise for the application of closed-loop systems in neural prostheses, brain-machine interfaces, and drug testing.

A new perspective on behavioral inconsistency and neural noise in aging: Compensatory speeding of neural communication

Directory of Open Access Journals (Sweden)

S. Lee Hong

2012-09-01

Full Text Available This paper seeks to present a new perspective on the aging brain. Here, we make connections between two key phenomena of brain aging: 1 increased neural noise or random background activity; and 2 slowing of brain activity. Our perspective proposes the possibility that the slowing of neural processing due to decreasing nerve conduction velocities leads to a compensatory speeding of neuron firing rates. These increased firing rates lead to a broader distribution of power in the frequency spectrum of neural oscillations, which we propose, can just as easily be interpreted as neural noise. Compensatory speeding of neural activity, as we present, is constrained by the: A availability of metabolic energy sources; and B competition for frequency bandwidth needed for neural communication. We propose that these constraints lead to the eventual inability to compensate for age-related declines in neural function that are manifested clinically as deficits in cognition, affect, and motor behavior.

Transcriptional profiling of adult neural stem-like cells from the human brain.

Directory of Open Access Journals (Sweden)

Cecilie Jonsgar Sandberg

Full Text Available There is a great potential for the development of new cell replacement strategies based on adult human neural stem-like cells. However, little is known about the hierarchy of cells and the unique molecular properties of stem- and progenitor cells of the nervous system. Stem cells from the adult human brain can be propagated and expanded in vitro as free floating neurospheres that are capable of self-renewal and differentiation into all three cell types of the central nervous system. Here we report the first global gene expression study of adult human neural stem-like cells originating from five human subventricular zone biopsies (mean age 42, range 33-60. Compared to adult human brain tissue, we identified 1,189 genes that were significantly up- and down-regulated in adult human neural stem-like cells (1% false discovery rate. We found that adult human neural stem-like cells express stem cell markers and have reduced levels of markers that are typical of the mature cells in the nervous system. We report that the genes being highly expressed in adult human neural stem-like cells are associated with developmental processes and the extracellular region of the cell. The calcium signaling pathway and neuroactive ligand-receptor interactions are enriched among the most differentially regulated genes between adult human neural stem-like cells and adult human brain tissue. We confirmed the expression of 10 of the most up-regulated genes in adult human neural stem-like cells in an additional sample set that included adult human neural stem-like cells (n = 6, foetal human neural stem cells (n = 1 and human brain tissues (n = 12. The NGFR, SLITRK6 and KCNS3 receptors were further investigated by immunofluorescence and shown to be heterogeneously expressed in spheres. These receptors could potentially serve as new markers for the identification and characterisation of neural stem- and progenitor cells or as targets for manipulation of cellular

Parameter estimation in space systems using recurrent neural networks

Science.gov (United States)

Parlos, Alexander G.; Atiya, Amir F.; Sunkel, John W.

1991-01-01

The identification of time-varying parameters encountered in space systems is addressed, using artificial neural systems. A hybrid feedforward/feedback neural network, namely a recurrent multilayer perception, is used as the model structure in the nonlinear system identification. The feedforward portion of the network architecture provides its well-known interpolation property, while through recurrency and cross-talk, the local information feedback enables representation of temporal variations in the system nonlinearities. The standard back-propagation-learning algorithm is modified and it is used for both the off-line and on-line supervised training of the proposed hybrid network. The performance of recurrent multilayer perceptron networks in identifying parameters of nonlinear dynamic systems is investigated by estimating the mass properties of a representative large spacecraft. The changes in the spacecraft inertia are predicted using a trained neural network, during two configurations corresponding to the early and late stages of the spacecraft on-orbit assembly sequence. The proposed on-line mass properties estimation capability offers encouraging results, though, further research is warranted for training and testing the predictive capabilities of these networks beyond nominal spacecraft operations.

Neural bases of ingroup altruistic motivation in soccer fans.

Science.gov (United States)

Bortolini, Tiago; Bado, Patrícia; Hoefle, Sebastian; Engel, Annerose; Zahn, Roland; de Oliveira Souza, Ricardo; Dreher, Jean-Claude; Moll, Jorge

2017-11-23

Humans have a strong need to belong to social groups and a natural inclination to benefit ingroup members. Although the psychological mechanisms behind human prosociality have extensively been studied, the specific neural systems bridging group belongingness and altruistic motivation remain to be identified. Here, we used soccer fandom as an ecological framing of group membership to investigate the neural mechanisms underlying ingroup altruistic behaviour in male fans using event-related functional magnetic resonance. We designed an effort measure based on handgrip strength to assess the motivation to earn money (i) for oneself, (ii) for anonymous ingroup fans, or (iii) for a neutral group of anonymous non-fans. While overlapping valuation signals in the medial orbitofrontal cortex (mOFC) were observed for the three conditions, the subgenual cingulate cortex (SCC) exhibited increased functional connectivity with the mOFC as well as stronger hemodynamic responses for ingroup versus outgroup decisions. These findings indicate a key role for the SCC, a region previously implicated in altruistic decisions and group affiliation, in dovetailing altruistic motivations with neural valuation systems in real-life ingroup behaviour.

RBF Neural Network Approach for Identification and Control of DC Motors

Directory of Open Access Journals (Sweden)

EA Feilat

2012-12-01

Full Text Available In this paper, a neural network approach for the identification and control of a separately excited direct (DC motor (SEDCM driving a centrifugal pump load is applied. In this application, two radial basis function neural networks (RBFNN are used: The first is a RBFNN identifier trained offline to emulate the dynamic performance of the DC motor-load system. The second is a RBFNN controller, which is trained to make the motor speed follow a selected reference signal. Two RBFNN control schemes are proposed using direct inverse and internal model control schemes. The performance of the RBFNN identifier and controller is investigated in terms of step response, sharp changes in speed trajectory, and sudden load change, as well as changes in motor parameters. The performance of RBFNN in system identification and control has been compared with the performance of the well-known back-propagation neural network (BPNN. The simulation results show that both of the BPNN and RBFNN controllers exhibit excellent dynamic response, adapt well to changes in speed trajectory and load connected to the motor, and adapt to the variations of motor parameters. Furthermore, the simulation results show that the step response of RBFNN internal model and direct inverse controllers are identical.

Development of the disable software reporting system on the basis of the neural network

Science.gov (United States)

Gavrylenko, S.; Babenko, O.; Ignatova, E.

2018-04-01

The PE structure of malicious and secure software is analyzed, features are highlighted, binary sign vectors are obtained and used as inputs for training the neural network. A software model for detecting malware based on the ART-1 neural network was developed, optimal similarity coefficients were found, and testing was performed. The obtained research results showed the possibility of using the developed system of identifying malicious software in computer systems protection systems

Sequential neural models with stochastic layers

DEFF Research Database (Denmark)

Fraccaro, Marco; Sønderby, Søren Kaae; Paquet, Ulrich

2016-01-01

How can we efficiently propagate uncertainty in a latent state representation with recurrent neural networks? This paper introduces stochastic recurrent neural networks which glue a deterministic recurrent neural network and a state space model together to form a stochastic and sequential neural...... generative model. The clear separation of deterministic and stochastic layers allows a structured variational inference network to track the factorization of the model's posterior distribution. By retaining both the nonlinear recursive structure of a recurrent neural network and averaging over...

Memory-guided sensory comparisons in the prefrontal cortex: contribution of putative pyramidal cells and interneurons.

Science.gov (United States)

Hussar, Cory R; Pasternak, Tatiana

2012-02-22

Comparing two stimuli that occur at different times demands the coordination of bottom-up and top-down processes. It has been hypothesized that the dorsolateral prefrontal (PFC) cortex, the likely source of top-down cortical influences, plays a key role in such tasks, contributing to both maintenance and sensory comparisons. We examined this hypothesis by recording from the PFC of monkeys comparing directions of two moving stimuli, S1 and S2, separated by a memory delay. We determined the contribution of the two principal cell types to these processes by classifying neurons into broad-spiking (BS) putative pyramidal cells and narrow-spiking (NS) putative local interneurons. During the delay, BS cells were more likely to exhibit anticipatory modulation and represent the remembered direction. While this representation was transient, appearing at different times in different neurons, it weakened when direction was not task relevant, suggesting its utility. During S2, both putative cell types showed comparison-related activity modulations. These modulations were of two types, each carried by different neurons, which either preferred trials with stimuli moving in the same direction or trials with stimuli of different directions. These comparison effects were strongly correlated with choice, suggesting their role in circuitry underlying decision making. These results provide the first demonstration of distinct contributions made by principal cell types to memory-guided perceptual decisions. During sensory stimulation both cell types represent behaviorally relevant stimulus features contributing to comparison and decision-related activity. However in the absence of sensory stimulation, putative pyramidal cells dominated, carrying information about the elapsed time and the preceding direction.

In silico analysis to identify vaccine candidates common to multiple serotypes of Shigella and evaluation of their immunogenicity

KAUST Repository

Pahil, Sapna

2017-08-02

Shigellosis or bacillary dysentery is an important cause of diarrhea, with the majority of the cases occurring in developing countries. Considering the high disease burden, increasing antibiotic resistance, serotype-specific immunity and the post-infectious sequelae associated with shigellosis, there is a pressing need of an effective vaccine against multiple serotypes of the pathogen. In the present study, we used bio-informatics approach to identify antigens shared among multiple serotypes of Shigella spp. This approach led to the identification of many immunogenic peptides. The five most promising peptides based on MHC binding efficiency were a putative lipoprotein (EL PGI I), a putative heat shock protein (EL PGI II), Spa32 (EL PGI III), IcsB (EL PGI IV) and a hypothetical protein (EL PGI V). These peptides were synthesized and the immunogenicity was evaluated in BALB/c mice by ELISA and cytokine assays. The putative heat shock protein (HSP) and the hypothetical protein elicited good humoral response, whereas putative lipoprotein, Spa32 and IcsB elicited good T-cell response as revealed by increased IFN-γ and TNF-α cytokine levels. The patient sera from confirmed cases of shigellosis were also evaluated for the presence of peptide specific antibodies with significant IgG and IgA antibodies against the HSP and the hypothetical protein, bestowing them as potential future vaccine candidates. The antigens reported in this study are novel and have not been tested as vaccine candidates against Shigella. This study offers time and cost-effective way of identifying unprecedented immunogenic antigens to be used as potential vaccine candidates. Moreover, this approach should easily be extendable to find new potential vaccine candidates for other pathogenic bacteria.

In silico analysis to identify vaccine candidates common to multiple serotypes of Shigella and evaluation of their immunogenicity.

Science.gov (United States)

Pahil, Sapna; Taneja, Neelam; Ansari, Hifzur Rahman; Raghava, G P S

2017-01-01

Shigellosis or bacillary dysentery is an important cause of diarrhea, with the majority of the cases occurring in developing countries. Considering the high disease burden, increasing antibiotic resistance, serotype-specific immunity and the post-infectious sequelae associated with shigellosis, there is a pressing need of an effective vaccine against multiple serotypes of the pathogen. In the present study, we used bio-informatics approach to identify antigens shared among multiple serotypes of Shigella spp. This approach led to the identification of many immunogenic peptides. The five most promising peptides based on MHC binding efficiency were a putative lipoprotein (EL PGI I), a putative heat shock protein (EL PGI II), Spa32 (EL PGI III), IcsB (EL PGI IV) and a hypothetical protein (EL PGI V). These peptides were synthesized and the immunogenicity was evaluated in BALB/c mice by ELISA and cytokine assays. The putative heat shock protein (HSP) and the hypothetical protein elicited good humoral response, whereas putative lipoprotein, Spa32 and IcsB elicited good T-cell response as revealed by increased IFN-γ and TNF-α cytokine levels. The patient sera from confirmed cases of shigellosis were also evaluated for the presence of peptide specific antibodies with significant IgG and IgA antibodies against the HSP and the hypothetical protein, bestowing them as potential future vaccine candidates. The antigens reported in this study are novel and have not been tested as vaccine candidates against Shigella. This study offers time and cost-effective way of identifying unprecedented immunogenic antigens to be used as potential vaccine candidates. Moreover, this approach should easily be extendable to find new potential vaccine candidates for other pathogenic bacteria.

In silico analysis to identify vaccine candidates common to multiple serotypes of Shigella and evaluation of their immunogenicity

KAUST Repository

Pahil, Sapna; Taneja, Neelam; Ansari, Hifzur Rahman; Raghava, G. P. S.

2017-01-01

Shigellosis or bacillary dysentery is an important cause of diarrhea, with the majority of the cases occurring in developing countries. Considering the high disease burden, increasing antibiotic resistance, serotype-specific immunity and the post-infectious sequelae associated with shigellosis, there is a pressing need of an effective vaccine against multiple serotypes of the pathogen. In the present study, we used bio-informatics approach to identify antigens shared among multiple serotypes of Shigella spp. This approach led to the identification of many immunogenic peptides. The five most promising peptides based on MHC binding efficiency were a putative lipoprotein (EL PGI I), a putative heat shock protein (EL PGI II), Spa32 (EL PGI III), IcsB (EL PGI IV) and a hypothetical protein (EL PGI V). These peptides were synthesized and the immunogenicity was evaluated in BALB/c mice by ELISA and cytokine assays. The putative heat shock protein (HSP) and the hypothetical protein elicited good humoral response, whereas putative lipoprotein, Spa32 and IcsB elicited good T-cell response as revealed by increased IFN-γ and TNF-α cytokine levels. The patient sera from confirmed cases of shigellosis were also evaluated for the presence of peptide specific antibodies with significant IgG and IgA antibodies against the HSP and the hypothetical protein, bestowing them as potential future vaccine candidates. The antigens reported in this study are novel and have not been tested as vaccine candidates against Shigella. This study offers time and cost-effective way of identifying unprecedented immunogenic antigens to be used as potential vaccine candidates. Moreover, this approach should easily be extendable to find new potential vaccine candidates for other pathogenic bacteria.

In silico analysis to identify vaccine candidates common to multiple serotypes of Shigella and evaluation of their immunogenicity.

Directory of Open Access Journals (Sweden)

Sapna Pahil

Full Text Available Shigellosis or bacillary dysentery is an important cause of diarrhea, with the majority of the cases occurring in developing countries. Considering the high disease burden, increasing antibiotic resistance, serotype-specific immunity and the post-infectious sequelae associated with shigellosis, there is a pressing need of an effective vaccine against multiple serotypes of the pathogen. In the present study, we used bio-informatics approach to identify antigens shared among multiple serotypes of Shigella spp. This approach led to the identification of many immunogenic peptides. The five most promising peptides based on MHC binding efficiency were a putative lipoprotein (EL PGI I, a putative heat shock protein (EL PGI II, Spa32 (EL PGI III, IcsB (EL PGI IV and a hypothetical protein (EL PGI V. These peptides were synthesized and the immunogenicity was evaluated in BALB/c mice by ELISA and cytokine assays. The putative heat shock protein (HSP and the hypothetical protein elicited good humoral response, whereas putative lipoprotein, Spa32 and IcsB elicited good T-cell response as revealed by increased IFN-γ and TNF-α cytokine levels. The patient sera from confirmed cases of shigellosis were also evaluated for the presence of peptide specific antibodies with significant IgG and IgA antibodies against the HSP and the hypothetical protein, bestowing them as potential future vaccine candidates. The antigens reported in this study are novel and have not been tested as vaccine candidates against Shigella. This study offers time and cost-effective way of identifying unprecedented immunogenic antigens to be used as potential vaccine candidates. Moreover, this approach should easily be extendable to find new potential vaccine candidates for other pathogenic bacteria.

Neural networks for genetic epidemiology: past, present, and future

Directory of Open Access Journals (Sweden)

Motsinger-Reif Alison A

2008-07-01

Full Text Available Abstract During the past two decades, the field of human genetics has experienced an information explosion. The completion of the human genome project and the development of high throughput SNP technologies have created a wealth of data; however, the analysis and interpretation of these data have created a research bottleneck. While technology facilitates the measurement of hundreds or thousands of genes, statistical and computational methodologies are lacking for the analysis of these data. New statistical methods and variable selection strategies must be explored for identifying disease susceptibility genes for common, complex diseases. Neural networks (NN are a class of pattern recognition methods that have been successfully implemented for data mining and prediction in a variety of fields. The application of NN for statistical genetics studies is an active area of research. Neural networks have been applied in both linkage and association analysis for the identification of disease susceptibility genes. In the current review, we consider how NN have been used for both linkage and association analyses in genetic epidemiology. We discuss both the successes of these initial NN applications, and the questions that arose during the previous studies. Finally, we introduce evolutionary computing strategies, Genetic Programming Neural Networks (GPNN and Grammatical Evolution Neural Networks (GENN, for using NN in association studies of complex human diseases that address some of the caveats illuminated by previous work.

Parallel consensual neural networks.

Science.gov (United States)

Benediktsson, J A; Sveinsson, J R; Ersoy, O K; Swain, P H

1997-01-01

A new type of a neural-network architecture, the parallel consensual neural network (PCNN), is introduced and applied in classification/data fusion of multisource remote sensing and geographic data. The PCNN architecture is based on statistical consensus theory and involves using stage neural networks with transformed input data. The input data are transformed several times and the different transformed data are used as if they were independent inputs. The independent inputs are first classified using the stage neural networks. The output responses from the stage networks are then weighted and combined to make a consensual decision. In this paper, optimization methods are used in order to weight the outputs from the stage networks. Two approaches are proposed to compute the data transforms for the PCNN, one for binary data and another for analog data. The analog approach uses wavelet packets. The experimental results obtained with the proposed approach show that the PCNN outperforms both a conjugate-gradient backpropagation neural network and conventional statistical methods in terms of overall classification accuracy of test data.

Creative-Dynamics Approach To Neural Intelligence

Science.gov (United States)

Zak, Michail A.

1992-01-01

Paper discusses approach to mathematical modeling of artificial neural networks exhibiting complicated behaviors reminiscent of creativity and intelligence of biological neural networks. Neural network treated as non-Lipschitzian dynamical system - as described in "Non-Lipschitzian Dynamics For Modeling Neural Networks" (NPO-17814). System serves as tool for modeling of temporal-pattern memories and recognition of complicated spatial patterns.

Crystallization and preliminary crystallographic analysis of a putative glucokinase/hexokinase from Thermus thermophilus

International Nuclear Information System (INIS)

Nakamura, Tsutomu; Kashima, Yasuhiro; Mine, Shouhei; Oku, Takashi; Uegaki, Koichi

2011-01-01

In this study, a putative glucokinase/hexokinase from T. thermophilus was purified and crystallized. Diffraction data were collected and processed to 2.02 Å resolution. Glucokinase/hexokinase catalyzes the phosphorylation of glucose to glucose 6-phosphate, which is the first step of glycolysis. The open reading frame TTHA0299 of the extreme thermophile Thermus thermophilus encodes a putative glucokinase/hexokinase which contains the consensus sequence for proteins from the repressors, open reading frames and sugar kinases family. In this study, the glucokinase/hexokinase from T. thermophilus was purified and crystallized using polyethylene glycol 8000 as a precipitant. Diffraction data were collected and processed to 2.02 Å resolution. The crystal belonged to space group P2 1 , with unit-cell parameters a = 70.93, b = 138.14, c = 75.16 Å, β = 95.41°

Neural Network Based Sensory Fusion for Landmark Detection

Science.gov (United States)

Kumbla, Kishan -K.; Akbarzadeh, Mohammad R.

1997-01-01

NASA is planning to send numerous unmanned planetary missions to explore the space. This requires autonomous robotic vehicles which can navigate in an unstructured, unknown, and uncertain environment. Landmark based navigation is a new area of research which differs from the traditional goal-oriented navigation, where a mobile robot starts from an initial point and reaches a destination in accordance with a pre-planned path. The landmark based navigation has the advantage of allowing the robot to find its way without communication with the mission control station and without exact knowledge of its coordinates. Current algorithms based on landmark navigation however pose several constraints. First, they require large memories to store the images. Second, the task of comparing the images using traditional methods is computationally intensive and consequently real-time implementation is difficult. The method proposed here consists of three stages, First stage utilizes a heuristic-based algorithm to identify significant objects. The second stage utilizes a neural network (NN) to efficiently classify images of the identified objects. The third stage combines distance information with the classification results of neural networks for efficient and intelligent navigation.

Application of neural networks to software quality modeling of a very large telecommunications system.

Science.gov (United States)

Khoshgoftaar, T M; Allen, E B; Hudepohl, J P; Aud, S J

1997-01-01

Society relies on telecommunications to such an extent that telecommunications software must have high reliability. Enhanced measurement for early risk assessment of latent defects (EMERALD) is a joint project of Nortel and Bell Canada for improving the reliability of telecommunications software products. This paper reports a case study of neural-network modeling techniques developed for the EMERALD system. The resulting neural network is currently in the prototype testing phase at Nortel. Neural-network models can be used to identify fault-prone modules for extra attention early in development, and thus reduce the risk of operational problems with those modules. We modeled a subset of modules representing over seven million lines of code from a very large telecommunications software system. The set consisted of those modules reused with changes from the previous release. The dependent variable was membership in the class of fault-prone modules. The independent variables were principal components of nine measures of software design attributes. We compared the neural-network model with a nonparametric discriminant model and found the neural-network model had better predictive accuracy.

Evaluation of surveillance of dengue fever cases in the public health centre of Putat Jaya based on attribute surveillance

Directory of Open Access Journals (Sweden)

Zumaroh Zumaroh

2015-01-01

Full Text Available Dengue Hemorrhagic Fever (DHF is a public health problem in the village of Putat Jaya which is an endemic area. Surveilans activity in DHF control program is the most important activity in controlling and monitoring disease progression. The program is expected to achieve incidence rate 55/100.000 population. This study aimed to evaluate the implementation of case surveilans in health centre of putat jaya based on attribute surveillance. Attribute surveillance is an indicator that describes the characteristics of the surveillance system. This research was an evaluation research with descriptive study design. As informants were clinic staff who deal specifically with cases of dengue hemorrhagic fever and laboratory workers. The techniques of data collection by interviews and document study. The variables of this study were simplicity, flexibility, acceptability, sensitivity, positive predictive value, representativeness, timeliness, data quality and data stability. It could be seen from Incidence Rate in 2013 has reached 133/100.00 population. The activity of surveilance in the village of Putat Jaya reviewed from disease contol program management was not succeed into decrease incidence rate of DHF. Therefore, dengue control programs in health centers Putat Jaya need to do cross-sector cooperation and cross-program cooperation, strengthening the case reporting system by way increasing in the utilization of information and communication technology electromedia. Keywords: case surveillance, dengue hemorrhagic fever, evaluation, attribute surveillance, Putat Jaya

The mouse that roared: neural mechanisms of social hierarchy.

Science.gov (United States)

Wang, Fei; Kessels, Helmut W; Hu, Hailan

2014-11-01

Hierarchical social status greatly influences behavior and health. Human and animal studies have begun to identify the brain regions that are activated during the formation of social hierarchies. They point towards the prefrontal cortex (PFC) as a central regulator, with brain areas upstream of the PFC conveying information about social status, and downstream brain regions executing dominance behavior. This review summarizes our current knowledge on the neural circuits that control social status. We discuss how the neural mechanisms for various types of dominance behavior can be studied in laboratory rodents by selective manipulation of neuronal activity or synaptic plasticity. These studies may help in finding the cause of social stress-related mental and physical health problems. Copyright © 2014 Elsevier Ltd. All rights reserved.

A neural network clustering algorithm for the ATLAS silicon pixel detector

CERN Document Server

Aad, Georges; Abdallah, Jalal; Abdel Khalek, Samah; Abdinov, Ovsat; Aben, Rosemarie; Abi, Babak; Abolins, Maris; AbouZeid, Ossama; Abramowicz, Halina; Abreu, Henso; Abreu, Ricardo; Abulaiti, Yiming; Acharya, Bobby Samir; Adamczyk, Leszek; Adams, David; Adelman, Jahred; Adomeit, Stefanie; Adye, Tim; Agatonovic-Jovin, Tatjana; Aguilar-Saavedra, Juan Antonio; Agustoni, Marco; Ahlen, Steven; Ahmadov, Faig; Aielli, Giulio; Akerstedt, Henrik; Åkesson, Torsten Paul Ake; Akimoto, Ginga; Akimov, Andrei; Alberghi, Gian Luigi; Albert, Justin; Albrand, Solveig; Alconada Verzini, Maria Josefina; Aleksa, Martin; Aleksandrov, Igor; Alexa, Calin; Alexander, Gideon; Alexandre, Gauthier; Alexopoulos, Theodoros; Alhroob, Muhammad; Alimonti, Gianluca; Alio, Lion; Alison, John; Allbrooke, Benedict; Allison, Lee John; Allport, Phillip; Almond, John; Aloisio, Alberto; Alonso, Alejandro; Alonso, Francisco; Alpigiani, Cristiano; Altheimer, Andrew David; Alvarez Gonzalez, Barbara; Alviggi, Mariagrazia; Amako, Katsuya; Amaral Coutinho, Yara; Amelung, Christoph; Amidei, Dante; Amor Dos Santos, Susana Patricia; Amorim, Antonio; Amoroso, Simone; Amram, Nir; Amundsen, Glenn; Anastopoulos, Christos; Ancu, Lucian Stefan; Andari, Nansi; Andeen, Timothy; Anders, Christoph Falk; Anders, Gabriel; Anderson, Kelby; Andreazza, Attilio; Andrei, George Victor; Anduaga, Xabier; Angelidakis, Stylianos; Angelozzi, Ivan; Anger, Philipp; Angerami, Aaron; Anghinolfi, Francis; Anisenkov, Alexey; Anjos, Nuno; Annovi, Alberto; Antonaki, Ariadni; Antonelli, Mario; Antonov, Alexey; Antos, Jaroslav; Anulli, Fabio; Aoki, Masato; Aperio Bella, Ludovica; Apolle, Rudi; Arabidze, Giorgi; Aracena, Ignacio; Arai, Yasuo; Araque, Juan Pedro; Arce, Ayana; Arguin, Jean-Francois; Argyropoulos, Spyridon; Arik, Metin; Armbruster, Aaron James; Arnaez, Olivier; Arnal, Vanessa; Arnold, Hannah; Arratia, Miguel; Arslan, Ozan; Artamonov, Andrei; Artoni, Giacomo; Asai, Shoji; Asbah, Nedaa; Ashkenazi, Adi; Åsman, Barbro; Asquith, Lily; Assamagan, Ketevi; Astalos, Robert; Atkinson, Markus; Atlay, Naim Bora; Auerbach, Benjamin; Augsten, Kamil; Aurousseau, Mathieu; Avolio, Giuseppe; Azuelos, Georges; Azuma, Yuya; Baak, Max; Baas, Alessandra; Bacci, Cesare; Bachacou, Henri; Bachas, Konstantinos; Backes, Moritz; Backhaus, Malte; Backus Mayes, John; Badescu, Elisabeta; Bagiacchi, Paolo; Bagnaia, Paolo; Bai, Yu; Bain, Travis; Baines, John; Baker, Oliver Keith; Balek, Petr; Balli, Fabrice; Banas, Elzbieta; Banerjee, Swagato; Bannoura, Arwa A E; Bansal, Vikas; Bansil, Hardeep Singh; Barak, Liron; Baranov, Sergei; Barberio, Elisabetta Luigia; Barberis, Dario; Barbero, Marlon; Barillari, Teresa; Barisonzi, Marcello; Barklow, Timothy; Barlow, Nick; Barnett, Bruce; Barnett, Michael; Barnovska, Zuzana; Baroncelli, Antonio; Barone, Gaetano; Barr, Alan; Barreiro, Fernando; Barreiro Guimarães da Costa, João; Bartoldus, Rainer; Barton, Adam Edward; Bartos, Pavol; Bartsch, Valeria; Bassalat, Ahmed; Basye, Austin; Bates, Richard; Batkova, Lucia; Batley, Richard; Battaglia, Marco; Battistin, Michele; Bauer, Florian; Bawa, Harinder Singh; Beau, Tristan; Beauchemin, Pierre-Hugues; Beccherle, Roberto; Bechtle, Philip; Beck, Hans Peter; Becker, Anne Kathrin; Becker, Sebastian; Beckingham, Matthew; Becot, Cyril; Beddall, Andrew; Beddall, Ayda; Bedikian, Sourpouhi; Bednyakov, Vadim; Bee, Christopher; Beemster, Lars; Beermann, Thomas; Begel, Michael; Behr, Katharina; Belanger-Champagne, Camille; Bell, Paul; Bell, William; Bella, Gideon; Bellagamba, Lorenzo; Bellerive, Alain; Bellomo, Massimiliano; Belotskiy, Konstantin; Beltramello, Olga; Benary, Odette; Benchekroun, Driss; Bendtz, Katarina; Benekos, Nektarios; Benhammou, Yan; Benhar Noccioli, Eleonora; Benitez Garcia, Jorge-Armando; Benjamin, Douglas; Bensinger, James; Benslama, Kamal; Bentvelsen, Stan; Berge, David; Bergeaas Kuutmann, Elin; Berger, Nicolas; Berghaus, Frank; Beringer, Jürg; Bernard, Clare; Bernat, Pauline; Bernius, Catrin; Bernlochner, Florian Urs; Berry, Tracey; Berta, Peter; Bertella, Claudia; Bertoli, Gabriele; Bertolucci, Federico; Bertsche, David; Besana, Maria Ilaria; Besjes, Geert-Jan; Bessidskaia, Olga; Bessner, Martin Florian; Besson, Nathalie; Betancourt, Christopher; Bethke, Siegfried; Bhimji, Wahid; Bianchi, Riccardo-Maria; Bianchini, Louis; Bianco, Michele; Biebel, Otmar; Bieniek, Stephen Paul; Bierwagen, Katharina; Biesiada, Jed; Biglietti, Michela; Bilbao De Mendizabal, Javier; Bilokon, Halina; Bindi, Marcello; Binet, Sebastien; Bingul, Ahmet; Bini, Cesare; Black, Curtis; Black, James; Black, Kevin; Blackburn, Daniel; Blair, Robert; Blanchard, Jean-Baptiste; Blazek, Tomas; Bloch, Ingo; Blocker, Craig; Blum, Walter; Blumenschein, Ulrike; Bobbink, Gerjan; Bobrovnikov, Victor; Bocchetta, Simona Serena; Bocci, Andrea; Bock, Christopher; Boddy, Christopher Richard; Boehler, Michael; Boek, Thorsten Tobias; Bogaerts, Joannes Andreas; Bogdanchikov, Alexander; Bogouch, Andrei; Bohm, Christian; Bohm, Jan; Boisvert, Veronique; Bold, Tomasz; Boldea, Venera; Boldyrev, Alexey; Bomben, Marco; Bona, Marcella; Boonekamp, Maarten; Borisov, Anatoly; Borissov, Guennadi; Borri, Marcello; Borroni, Sara; Bortfeldt, Jonathan; Bortolotto, Valerio; Bos, Kors; Boscherini, Davide; Bosman, Martine; Boterenbrood, Hendrik; Boudreau, Joseph; Bouffard, Julian; Bouhova-Thacker, Evelina Vassileva; Boumediene, Djamel Eddine; Bourdarios, Claire; Bousson, Nicolas; Boutouil, Sara; Boveia, Antonio; Boyd, James; Boyko, Igor; Bracinik, Juraj; Brandt, Andrew; Brandt, Gerhard; Brandt, Oleg; Bratzler, Uwe; Brau, Benjamin; Brau, James; Braun, Helmut; Brazzale, Simone Federico; Brelier, Bertrand; Brendlinger, Kurt; Brennan, Amelia Jean; Brenner, Richard; Bressler, Shikma; Bristow, Kieran; Bristow, Timothy Michael; Britton, Dave; Brochu, Frederic; Brock, Ian; Brock, Raymond; Bromberg, Carl; Bronner, Johanna; Brooijmans, Gustaaf; Brooks, Timothy; Brooks, William; Brosamer, Jacquelyn; Brost, Elizabeth; Brown, Jonathan; Bruckman de Renstrom, Pawel; Bruncko, Dusan; Bruneliere, Renaud; Brunet, Sylvie; Bruni, Alessia; Bruni, Graziano; Bruschi, Marco; Bryngemark, Lene; Buanes, Trygve; Buat, Quentin; Bucci, Francesca; Buchholz, Peter; Buckingham, Ryan; Buckley, Andrew; Buda, Stelian Ioan; Budagov, Ioulian; Buehrer, Felix; Bugge, Lars; Bugge, Magnar Kopangen; Bulekov, Oleg; Bundock, Aaron Colin; Burckhart, Helfried; Burdin, Sergey; Burghgrave, Blake; Burke, Stephen; Burmeister, Ingo; Busato, Emmanuel; Büscher, Daniel; Büscher, Volker; Bussey, Peter; Buszello, Claus-Peter; Butler, Bart; Butler, John; Butt, Aatif Imtiaz; Buttar, Craig; Butterworth, Jonathan; Butti, Pierfrancesco; Buttinger, William; Buzatu, Adrian; Byszewski, Marcin; Cabrera Urbán, Susana; Caforio, Davide; Cakir, Orhan; Calafiura, Paolo; Calandri, Alessandro; Calderini, Giovanni; Calfayan, Philippe; Calkins, Robert; Caloba, Luiz; Calvet, David; Calvet, Samuel; Camacho Toro, Reina; Camarda, Stefano; Cameron, David; Caminada, Lea Michaela; Caminal Armadans, Roger; Campana, Simone; Campanelli, Mario; Campoverde, Angel; Canale, Vincenzo; Canepa, Anadi; Cano Bret, Marc; Cantero, Josu; Cantrill, Robert; Cao, Tingting; Capeans Garrido, Maria Del Mar; Caprini, Irinel; Caprini, Mihai; Capua, Marcella; Caputo, Regina; Cardarelli, Roberto; Carli, Tancredi; Carlino, Gianpaolo; Carminati, Leonardo; Caron, Sascha; Carquin, Edson; Carrillo-Montoya, German D; Carter, Janet; Carvalho, João; Casadei, Diego; Casado, Maria Pilar; Casolino, Mirkoantonio; Castaneda-Miranda, Elizabeth; Castelli, Angelantonio; Castillo Gimenez, Victoria; Castro, Nuno Filipe; Catastini, Pierluigi; Catinaccio, Andrea; Catmore, James; Cattai, Ariella; Cattani, Giordano; Caughron, Seth; Cavaliere, Viviana; Cavalli, Donatella; Cavalli-Sforza, Matteo; Cavasinni, Vincenzo; Ceradini, Filippo; Cerio, Benjamin; Cerny, Karel; Santiago Cerqueira, Augusto; Cerri, Alessandro; Cerrito, Lucio; Cerutti, Fabio; Cerv, Matevz; Cervelli, Alberto; Cetin, Serkant Ali; Chafaq, Aziz; Chakraborty, Dhiman; Chalupkova, Ina; Chang, Philip; Chapleau, Bertrand; Chapman, John Derek; Charfeddine, Driss; Charlton, Dave; Chau, Chav Chhiv; Chavez Barajas, Carlos Alberto; Cheatham, Susan; Chegwidden, Andrew; Chekanov, Sergei; Chekulaev, Sergey; Chelkov, Gueorgui; Chelstowska, Magda Anna; Chen, Chunhui; Chen, Hucheng; Chen, Karen; Chen, Liming; Chen, Shenjian; Chen, Xin; Chen, Yujiao; Cheng, Hok Chuen; Cheng, Yangyang; Cheplakov, Alexander; Cherkaoui El Moursli, Rajaa; Chernyatin, Valeriy; Cheu, Elliott; Chevalier, Laurent; Chiarella, Vitaliano; Chiefari, Giovanni; Childers, John Taylor; Chilingarov, Alexandre; Chiodini, Gabriele; Chisholm, Andrew; Chislett, Rebecca Thalatta; Chitan, Adrian; Chizhov, Mihail; Chouridou, Sofia; Chow, Bonnie Kar Bo; Chromek-Burckhart, Doris; Chu, Ming-Lee; Chudoba, Jiri; Chwastowski, Janusz; Chytka, Ladislav; Ciapetti, Guido; Ciftci, Abbas Kenan; Ciftci, Rena; Cinca, Diane; Cindro, Vladimir; Ciocio, Alessandra; Cirkovic, Predrag; Citron, Zvi Hirsh; Citterio, Mauro; Ciubancan, Mihai; Clark, Allan G; Clark, Philip James; Clarke, Robert; Cleland, Bill; Clemens, Jean-Claude; Clement, Christophe; Coadou, Yann; Cobal, Marina; Coccaro, Andrea; Cochran, James H; Coffey, Laurel; Cogan, Joshua Godfrey; Coggeshall, James; Cole, Brian; Cole, Stephen; Colijn, Auke-Pieter; Collot, Johann; Colombo, Tommaso; Colon, German; Compostella, Gabriele; Conde Muiño, Patricia; Coniavitis, Elias; Conidi, Maria Chiara; Connell, Simon Henry; Connelly, Ian; Consonni, Sofia Maria; Consorti, Valerio; Constantinescu, Serban; Conta, Claudio; Conti, Geraldine; Conventi, Francesco; Cooke, Mark; Cooper, Ben; Cooper-Sarkar, Amanda; Cooper-Smith, Neil; Copic, Katherine; Cornelissen, Thijs; Corradi, Massimo; Corriveau, Francois; Corso-Radu, Alina; Cortes-Gonzalez, Arely; Cortiana, Giorgio; Costa, Giuseppe; Costa, María José; Costanzo, Davide; Côté, David; Cottin, Giovanna; Cowan, Glen; Cox, Brian; Cranmer, Kyle; Cree, Graham; Crépé-Renaudin, Sabine; Crescioli, Francesco; Cribbs, Wayne Allen; Crispin Ortuzar, Mireia; Cristinziani, Markus; Croft, Vince; Crosetti, Giovanni; Cuciuc, Constantin-Mihai; Cuhadar Donszelmann, Tulay; Cummings, Jane; Curatolo, Maria; Cuthbert, Cameron; Czirr, Hendrik; Czodrowski, Patrick; Czyczula, Zofia; D'Auria, Saverio; D'Onofrio, Monica; Da Cunha Sargedas De Sousa, Mario Jose; Da Via, Cinzia; Dabrowski, Wladyslaw; Dafinca, Alexandru; Dai, Tiesheng; Dale, Orjan; Dallaire, Frederick; Dallapiccola, Carlo; Dam, Mogens; Daniells, Andrew Christopher; Dano Hoffmann, Maria; Dao, Valerio; Darbo, Giovanni; Darmora, Smita; Dassoulas, James; Dattagupta, Aparajita; Davey, Will; David, Claire; Davidek, Tomas; Davies, Eleanor; Davies, Merlin; Davignon, Olivier; Davison, Adam; Davison, Peter; Davygora, Yuriy; Dawe, Edmund; Dawson, Ian; Daya-Ishmukhametova, Rozmin; De, Kaushik; de Asmundis, Riccardo; De Castro, Stefano; De Cecco, Sandro; De Groot, Nicolo; de Jong, Paul; De la Torre, Hector; De Lorenzi, Francesco; De Nooij, Lucie; De Pedis, Daniele; De Salvo, Alessandro; De Sanctis, Umberto; De Santo, Antonella; De Vivie De Regie, Jean-Baptiste; Dearnaley, William James; Debbe, Ramiro; Debenedetti, Chiara; Dechenaux, Benjamin; Dedovich, Dmitri; Deigaard, Ingrid; Del Peso, Jose; Del Prete, Tarcisio; Deliot, Frederic; Delitzsch, Chris Malena; Deliyergiyev, Maksym; Dell'Acqua, Andrea; Dell'Asta, Lidia; Dell'Orso, Mauro; Della Pietra, Massimo; della Volpe, Domenico; Delmastro, Marco; Delsart, Pierre-Antoine; Deluca, Carolina; Demers, Sarah; Demichev, Mikhail; Demilly, Aurelien; Denisov, Sergey; Derendarz, Dominik; Derkaoui, Jamal Eddine; Derue, Frederic; Dervan, Paul; Desch, Klaus Kurt; Deterre, Cecile; Deviveiros, Pier-Olivier; Dewhurst, Alastair; Dhaliwal, Saminder; Di Ciaccio, Anna; Di Ciaccio, Lucia; Di Domenico, Antonio; Di Donato, Camilla; Di Girolamo, Alessandro; Di Girolamo, Beniamino; Di Mattia, Alessandro; Di Micco, Biagio; Di Nardo, Roberto; Di Simone, Andrea; Di Sipio, Riccardo; Di Valentino, David; Dias, Flavia; Diaz, Marco Aurelio; Diehl, Edward; Dietrich, Janet; Dietzsch, Thorsten; Diglio, Sara; Dimitrievska, Aleksandra; Dingfelder, Jochen; Dionisi, Carlo; Dita, Petre; Dita, Sanda; Dittus, Fridolin; Djama, Fares; Djobava, Tamar; Barros do Vale, Maria Aline; Do Valle Wemans, André; Doan, Thi Kieu Oanh; Dobos, Daniel; Doglioni, Caterina; Doherty, Tom; Dohmae, Takeshi; Dolejsi, Jiri; Dolezal, Zdenek; Dolgoshein, Boris; Donadelli, Marisilvia; Donati, Simone; Dondero, Paolo; Donini, Julien; Dopke, Jens; Doria, Alessandra; Dova, Maria-Teresa; Doyle, Tony; Dris, Manolis; Dubbert, Jörg; Dube, Sourabh; Dubreuil, Emmanuelle; Duchovni, Ehud; Duckeck, Guenter; Ducu, Otilia Anamaria; Duda, Dominik; Dudarev, Alexey; Dudziak, Fanny; Duflot, Laurent; Duguid, Liam; Dührssen, Michael; Dunford, Monica; Duran Yildiz, Hatice; Düren, Michael; Durglishvili, Archil; Dwuznik, Michal; Dyndal, Mateusz; Ebke, Johannes; Edson, William; Edwards, Nicholas Charles; Ehrenfeld, Wolfgang; Eifert, Till; Eigen, Gerald; Einsweiler, Kevin; Ekelof, Tord; El Kacimi, Mohamed; Ellert, Mattias; Elles, Sabine; Ellinghaus, Frank; Ellis, Nicolas; Elmsheuser, Johannes; Elsing, Markus; Emeliyanov, Dmitry; Enari, Yuji; Endner, Oliver Chris; Endo, Masaki; Engelmann, Roderich; Erdmann, Johannes; Ereditato, Antonio; Eriksson, Daniel; Ernis, Gunar; Ernst, Jesse; Ernst, Michael; Ernwein, Jean; Errede, Deborah; Errede, Steven; Ertel, Eugen; Escalier, Marc; Esch, Hendrik; Escobar, Carlos; Esposito, Bellisario; Etienvre, Anne-Isabelle; Etzion, Erez; Evans, Hal; Ezhilov, Alexey; Fabbri, Laura; Facini, Gabriel; Fakhrutdinov, Rinat; Falciano, Speranza; Falla, Rebecca Jane; Faltova, Jana; Fang, Yaquan; Fanti, Marcello; Farbin, Amir; Farilla, Addolorata; Farooque, Trisha; Farrell, Steven; Farrington, Sinead; Farthouat, Philippe; Fassi, Farida; Fassnacht, Patrick; Fassouliotis, Dimitrios; Favareto, Andrea; Fayard, Louis; Federic, Pavol; Fedin, Oleg; Fedorko, Wojciech; Fehling-Kaschek, Mirjam; Feigl, Simon; Feligioni, Lorenzo; Feng, Cunfeng; Feng, Eric; Feng, Haolu; Fenyuk, Alexander; Fernandez Perez, Sonia; Ferrag, Samir; Ferrando, James; Ferrari, Arnaud; Ferrari, Pamela; Ferrari, Roberto; Ferreira de Lima, Danilo Enoque; Ferrer, Antonio; Ferrere, Didier; Ferretti, Claudio; Ferretto Parodi, Andrea; Fiascaris, Maria; Fiedler, Frank; Filipčič, Andrej; Filipuzzi, Marco; Filthaut, Frank; Fincke-Keeler, Margret; Finelli, Kevin Daniel; Fiolhais, Miguel; Fiorini, Luca; Firan, Ana; Fischer, Adam; Fischer, Julia; Fisher, Wade Cameron; Fitzgerald, Eric Andrew; Flechl, Martin; Fleck, Ivor; Fleischmann, Philipp; Fleischmann, Sebastian; Fletcher, Gareth Thomas; Fletcher, Gregory; Flick, Tobias; Floderus, Anders; Flores Castillo, Luis; Florez Bustos, Andres Carlos; Flowerdew, Michael; Formica, Andrea; Forti, Alessandra; Fortin, Dominique; Fournier, Daniel; Fox, Harald; Fracchia, Silvia; Francavilla, Paolo; Franchini, Matteo; Franchino, Silvia; Francis, David; Franklin, Melissa; Franz, Sebastien; Fraternali, Marco; French, Sky; Friedrich, Conrad; Friedrich, Felix; Froidevaux, Daniel; Frost, James; Fukunaga, Chikara; Fullana Torregrosa, Esteban; Fulsom, Bryan Gregory; Fuster, Juan; Gabaldon, Carolina; Gabizon, Ofir; Gabrielli, Alessandro; Gabrielli, Andrea; Gadatsch, Stefan; Gadomski, Szymon; Gagliardi, Guido; Gagnon, Pauline; Galea, Cristina; Galhardo, Bruno; Gallas, Elizabeth; Gallo, Valentina Santina; Gallop, Bruce; Gallus, Petr; Galster, Gorm Aske Gram Krohn; Gan, KK; Gandrajula, Reddy Pratap; Gao, Jun; Gao, Yongsheng; Garay Walls, Francisca; Garberson, Ford; García, Carmen; García Navarro, José Enrique; Garcia-Sciveres, Maurice; Gardner, Robert; Garelli, Nicoletta; Garonne, Vincent; Gatti, Claudio; Gaudio, Gabriella; Gaur, Bakul; Gauthier, Lea; Gauzzi, Paolo; Gavrilenko, Igor; Gay, Colin; Gaycken, Goetz; Gazis, Evangelos; Ge, Peng; Gecse, Zoltan; Gee, Norman; Geerts, Daniël Alphonsus Adrianus; Geich-Gimbel, Christoph; Gellerstedt, Karl; Gemme, Claudia; Gemmell, Alistair; Genest, Marie-Hélène; Gentile, Simonetta; George, Matthias; George, Simon; Gerbaudo, Davide; Gershon, Avi; Ghazlane, Hamid; Ghodbane, Nabil; Giacobbe, Benedetto; Giagu, Stefano; Giangiobbe, Vincent; Giannetti, Paola; Gianotti, Fabiola; Gibbard, Bruce; Gibson, Stephen; Gilchriese, Murdock; Gillam, Thomas; Gillberg, Dag; Gilles, Geoffrey; Gingrich, Douglas; Giokaris, Nikos; Giordani, MarioPaolo; Giordano, Raffaele; Giorgi, Filippo Maria; Giorgi, Francesco Michelangelo; Giraud, Pierre-Francois; Giugni, Danilo; Giuliani, Claudia; Giulini, Maddalena; Gjelsten, Børge Kile; Gkaitatzis, Stamatios; Gkialas, Ioannis; Gladilin, Leonid; Glasman, Claudia; Glatzer, Julian; Glaysher, Paul; Glazov, Alexandre; Glonti, George; Goblirsch-Kolb, Maximilian; Goddard, Jack Robert; Godfrey, Jennifer; Godlewski, Jan; Goeringer, Christian; Goldfarb, Steven; Golling, Tobias; Golubkov, Dmitry; Gomes, Agostinho; Gomez Fajardo, Luz Stella; Gonçalo, Ricardo; Goncalves Pinto Firmino Da Costa, Joao; Gonella, Laura; González de la Hoz, Santiago; Gonzalez Parra, Garoe; Gonzalez-Sevilla, Sergio; Goossens, Luc; Gorbounov, Petr Andreevich; Gordon, Howard; Gorelov, Igor; Gorini, Benedetto; Gorini, Edoardo; Gorišek, Andrej; Gornicki, Edward; Goshaw, Alfred; Gössling, Claus; Gostkin, Mikhail Ivanovitch; Gouighri, Mohamed; Goujdami, Driss; Goulette, Marc Phillippe; Goussiou, Anna; Goy, Corinne; Gozpinar, Serdar; Grabas, Herve Marie Xavier; Graber, Lars; Grabowska-Bold, Iwona; Grafström, Per; Grahn, Karl-Johan; Gramling, Johanna; Gramstad, Eirik; Grancagnolo, Sergio; Grassi, Valerio; Gratchev, Vadim; Gray, Heather; Graziani, Enrico; Grebenyuk, Oleg; Greenwood, Zeno Dixon; Gregersen, Kristian; Gregor, Ingrid-Maria; Grenier, Philippe; Griffiths, Justin; Grillo, Alexander; Grimm, Kathryn; Grinstein, Sebastian; Gris, Philippe Luc Yves; Grishkevich, Yaroslav; Grivaz, Jean-Francois; Grohs, Johannes Philipp; Grohsjean, Alexander; Gross, Eilam; Grosse-Knetter, Joern; Grossi, Giulio Cornelio; Groth-Jensen, Jacob; Grout, Zara Jane; Guan, Liang; Guescini, Francesco; Guest, Daniel; Gueta, Orel; Guicheney, Christophe; Guido, Elisa; Guillemin, Thibault; Guindon, Stefan; Gul, Umar; Gumpert, Christian; Gunther, Jaroslav; Guo, Jun; Gupta, Shaun; Gutierrez, Phillip; Gutierrez Ortiz, Nicolas Gilberto; Gutschow, Christian; Guttman, Nir; Guyot, Claude; Gwenlan, Claire; Gwilliam, Carl; Haas, Andy; Haber, Carl; Hadavand, Haleh Khani; Haddad, Nacim; Haefner, Petra; Hageböck, Stephan; Hajduk, Zbigniew; Hakobyan, Hrachya; Haleem, Mahsana; Hall, David; Halladjian, Garabed; Hamacher, Klaus; Hamal, Petr; Hamano, Kenji; Hamer, Matthias; Hamilton, Andrew; Hamilton, Samuel; Hamnett, Phillip George; Han, Liang; Hanagaki, Kazunori; Hanawa, Keita; Hance, Michael; Hanke, Paul; Hanna, Remie; Hansen, Jørgen Beck; Hansen, Jorn Dines; Hansen, Peter Henrik; Hara, Kazuhiko; Hard, Andrew; Harenberg, Torsten; Hariri, Faten; Harkusha, Siarhei; Harper, Devin; Harrington, Robert; Harris, Orin; Harrison, Paul Fraser; Hartjes, Fred; Hasegawa, Satoshi; Hasegawa, Yoji; Hasib, A; Hassani, Samira; Haug, Sigve; Hauschild, Michael; Hauser, Reiner; Havranek, Miroslav; Hawkes, Christopher; Hawkings, Richard John; Hawkins, Anthony David; Hayashi, Takayasu; Hayden, Daniel; Hays, Chris; Hayward, Helen; Haywood, Stephen; Head, Simon; Heck, Tobias; Hedberg, Vincent; Heelan, Louise; Heim, Sarah; Heim, Timon; Heinemann, Beate; Heinrich, Lukas; Hejbal, Jiri; Helary, Louis; Heller, Claudio; Heller, Matthieu; Hellman, Sten; Hellmich, Dennis; Helsens, Clement; Henderson, James; Henderson, Robert; Heng, Yang; Hengler, Christopher; Henrichs, Anna; Henriques Correia, Ana Maria; Henrot-Versille, Sophie; Hensel, Carsten; Herbert, Geoffrey Henry; Hernández Jiménez, Yesenia; Herrberg-Schubert, Ruth; Herten, Gregor; Hertenberger, Ralf; Hervas, Luis; Hesketh, Gavin Grant; Hessey, Nigel; Hickling, Robert; Higón-Rodriguez, Emilio; Hill, Ewan; Hill, John; Hiller, Karl Heinz; Hillert, Sonja; Hillier, Stephen; Hinchliffe, Ian; Hines, Elizabeth; Hirose, Minoru; Hirschbuehl, Dominic; Hobbs, John; Hod, Noam; Hodgkinson, Mark; Hodgson, Paul; Hoecker, Andreas; Hoeferkamp, Martin; Hoffman, Julia; Hoffmann, Dirk; Hofmann, Julia Isabell; Hohlfeld, Marc; Holmes, Tova Ray; Hong, Tae Min; Hooft van Huysduynen, Loek; Hostachy, Jean-Yves; Hou, Suen; Hoummada, Abdeslam; Howard, Jacob; Howarth, James; Hrabovsky, Miroslav; Hristova, Ivana; Hrivnac, Julius; Hryn'ova, Tetiana; Hsu, Catherine; Hsu, Pai-hsien Jennifer; Hsu, Shih-Chieh; Hu, Diedi; Hu, Xueye; Huang, Yanping; Hubacek, Zdenek; Hubaut, Fabrice; Huegging, Fabian; Huffman, Todd Brian; Hughes, Emlyn; Hughes, Gareth; Huhtinen, Mika; Hülsing, Tobias Alexander; Hurwitz, Martina; Huseynov, Nazim; Huston, Joey; Huth, John; Iacobucci, Giuseppe; Iakovidis, Georgios; Ibragimov, Iskander; Iconomidou-Fayard, Lydia; Ideal, Emma; Iengo, Paolo; Igonkina, Olga; Iizawa, Tomoya; Ikegami, Yoichi; Ikematsu, Katsumasa; Ikeno, Masahiro; Ilchenko, Iurii; Iliadis, Dimitrios; Ilic, Nikolina; Inamaru, Yuki; Ince, Tayfun; Ioannou, Pavlos; Iodice, Mauro; Iordanidou, Kalliopi; Ippolito, Valerio; Irles Quiles, Adrian; Isaksson, Charlie; Ishino, Masaya; Ishitsuka, Masaki; Ishmukhametov, Renat; Issever, Cigdem; Istin, Serhat; Iturbe Ponce, Julia Mariana; Iuppa, Roberto; Ivarsson, Jenny; Iwanski, Wieslaw; Iwasaki, Hiroyuki; Izen, Joseph; Izzo, Vincenzo; Jackson, Brett; Jackson, Matthew; Jackson, Paul; Jaekel, Martin; Jain, Vivek; Jakobs, Karl; Jakobsen, Sune; Jakoubek, Tomas; Jakubek, Jan; Jamin, David Olivier; Jana, Dilip; Jansen, Eric; Jansen, Hendrik; Janssen, Jens; Janus, Michel; Jarlskog, Göran; Javadov, Namig; Javůrek, Tomáš; Jeanty, Laura; Jejelava, Juansher; Jeng, Geng-yuan; Jennens, David; Jenni, Peter; Jentzsch, Jennifer; Jeske, Carl; Jézéquel, Stéphane; Ji, Haoshuang; Ji, Weina; Jia, Jiangyong; Jiang, Yi; Jimenez Belenguer, Marcos; Jin, Shan; Jinaru, Adam; Jinnouchi, Osamu; Joergensen, Morten Dam; Johansson, Erik; Johansson, Per; Johns, Kenneth; Jon-And, Kerstin; Jones, Graham; Jones, Roger; Jones, Tim; Jongmanns, Jan; Jorge, Pedro; Joshi, Kiran Daniel; Jovicevic, Jelena; Ju, Xiangyang; Jung, Christian; Jungst, Ralph Markus; Jussel, Patrick; Juste Rozas, Aurelio; Kaci, Mohammed; Kaczmarska, Anna; Kado, Marumi; Kagan, Harris; Kagan, Michael; Kajomovitz, Enrique; Kalderon, Charles William; Kama, Sami; Kamenshchikov, Andrey; Kanaya, Naoko; Kaneda, Michiru; Kaneti, Steven; Kantserov, Vadim; Kanzaki, Junichi; Kaplan, Benjamin; Kapliy, Anton; Kar, Deepak; Karakostas, Konstantinos; Karastathis, Nikolaos; Karnevskiy, Mikhail; Karpov, Sergey; Karpova, Zoya; Karthik, Krishnaiyengar; Kartvelishvili, Vakhtang; Karyukhin, Andrey; Kashif, Lashkar; Kasieczka, Gregor; Kass, Richard; Kastanas, Alex; Kataoka, Yousuke; Katre, Akshay; Katzy, Judith; Kaushik, Venkatesh; Kawagoe, Kiyotomo; Kawamoto, Tatsuo; Kawamura, Gen; Kazama, Shingo; Kazanin, Vassili; Kazarinov, Makhail; Keeler, Richard; Kehoe, Robert; Keil, Markus; Keller, John; Kempster, Jacob Julian; Keoshkerian, Houry; Kepka, Oldrich; Kerševan, Borut Paul; Kersten, Susanne; Kessoku, Kohei; Keung, Justin; Khalil-zada, Farkhad; Khandanyan, Hovhannes; Khanov, Alexander; Khodinov, Alexander; Khomich, Andrei; Khoo, Teng Jian; Khoriauli, Gia; Khoroshilov, Andrey; Khovanskiy, Valery; Khramov, Evgeniy; Khubua, Jemal; Kim, Hee Yeun; Kim, Hyeon Jin; Kim, Shinhong; Kimura, Naoki; Kind, Oliver; King, Barry; King, Matthew; King, Robert Steven Beaufoy; King, Samuel Burton; Kirk, Julie; Kiryunin, Andrey; Kishimoto, Tomoe; Kisielewska, Danuta; Kiss, Florian; Kittelmann, Thomas; Kiuchi, Kenji; Kladiva, Eduard; Klein, Max; Klein, Uta; Kleinknecht, Konrad; Klimek, Pawel; Klimentov, Alexei; Klingenberg, Reiner; Klinger, Joel Alexander; Klioutchnikova, Tatiana; Klok, Peter; Kluge, Eike-Erik; Kluit, Peter; Kluth, Stefan; Kneringer, Emmerich; Knoops, Edith; Knue, Andrea; Kobayashi, Dai; Kobayashi, Tomio; Kobel, Michael; Kocian, Martin; Kodys, Peter; Koevesarki, Peter; Koffas, Thomas; Koffeman, Els; Kogan, Lucy Anne; Kohlmann, Simon; Kohout, Zdenek; Kohriki, Takashi; Koi, Tatsumi; Kolanoski, Hermann; Koletsou, Iro; Koll, James; Komar, Aston; Komori, Yuto; Kondo, Takahiko; Kondrashova, Nataliia; Köneke, Karsten; König, Adriaan; König, Sebastian; Kono, Takanori; Konoplich, Rostislav; Konstantinidis, Nikolaos; Kopeliansky, Revital; Koperny, Stefan; Köpke, Lutz; Kopp, Anna Katharina; Korcyl, Krzysztof; Kordas, Kostantinos; Korn, Andreas; Korol, Aleksandr; Korolkov, Ilya; Korolkova, Elena; Korotkov, Vladislav; Kortner, Oliver; Kortner, Sandra; Kostyukhin, Vadim; Kotov, Vladislav; Kotwal, Ashutosh; Kourkoumelis, Christine; Kouskoura, Vasiliki; Koutsman, Alex; Kowalewski, Robert Victor; Kowalski, Tadeusz; Kozanecki, Witold; Kozhin, Anatoly; Kral, Vlastimil; Kramarenko, Viktor; Kramberger, Gregor; Krasnopevtsev, Dimitriy; Krasny, Mieczyslaw Witold; Krasznahorkay, Attila; Kraus, Jana; Kravchenko, Anton; Kreiss, Sven; Kretz, Moritz; Kretzschmar, Jan; Kreutzfeldt, Kristof; Krieger, Peter; Kroeninger, Kevin; Kroha, Hubert; Kroll, Joe; Kroseberg, Juergen; Krstic, Jelena; Kruchonak, Uladzimir; Krüger, Hans; Kruker, Tobias; Krumnack, Nils; Krumshteyn, Zinovii; Kruse, Amanda; Kruse, Mark; Kruskal, Michael; Kubota, Takashi; Kuday, Sinan; Kuehn, Susanne; Kugel, Andreas; Kuhl, Andrew; Kuhl, Thorsten; Kukhtin, Victor; Kulchitsky, Yuri; Kuleshov, Sergey; Kuna, Marine; Kunkle, Joshua; Kupco, Alexander; Kurashige, Hisaya; Kurochkin, Yurii; Kurumida, Rie; Kus, Vlastimil; Kuwertz, Emma Sian; Kuze, Masahiro; Kvita, Jiri; La Rosa, Alessandro; La Rotonda, Laura; Lacasta, Carlos; Lacava, Francesco; Lacey, James; Lacker, Heiko; Lacour, Didier; Lacuesta, Vicente Ramón; Ladygin, Evgueni; Lafaye, Remi; Laforge, Bertrand; Lagouri, Theodota; Lai, Stanley; Laier, Heiko; Lambourne, Luke; Lammers, Sabine; Lampen, Caleb; Lampl, Walter; Lançon, Eric; Landgraf, Ulrich; Landon, Murrough; Lang, Valerie Susanne; Lankford, Andrew; Lanni, Francesco; Lantzsch, Kerstin; Laplace, Sandrine; Lapoire, Cecile; Laporte, Jean-Francois; Lari, Tommaso; Lassnig, Mario; Laurelli, Paolo; Lavrijsen, Wim; Law, Alexander; Laycock, Paul; Le, Bao Tran; Le Dortz, Olivier; Le Guirriec, Emmanuel; Le Menedeu, Eve; LeCompte, Thomas; Ledroit-Guillon, Fabienne Agnes Marie; Lee, Claire Alexandra; Lee, Hurng-Chun; Lee, Jason; Lee, Shih-Chang; Lee, Lawrence; Lefebvre, Guillaume; Lefebvre, Michel; Legger, Federica; Leggett, Charles; Lehan, Allan; Lehmacher, Marc; Lehmann Miotto, Giovanna; Lei, Xiaowen; Leight, William Axel; Leisos, Antonios; Leister, Andrew Gerard; Leite, Marco Aurelio Lisboa; Leitner, Rupert; Lellouch, Daniel; Lemmer, Boris; Leney, Katharine; Lenz, Tatjana; Lenzen, Georg; Lenzi, Bruno; Leone, Robert; Leone, Sandra; Leonhardt, Kathrin; Leonidopoulos, Christos; Leontsinis, Stefanos; Leroy, Claude; Lester, Christopher; Lester, Christopher Michael; Levchenko, Mikhail; Levêque, Jessica; Levin, Daniel; Levinson, Lorne; Levy, Mark; Lewis, Adrian; Lewis, George; Leyko, Agnieszka; Leyton, Michael; Li, Bing; Li, Bo; Li, Haifeng; Li, Ho Ling; Li, Lei; Li, Liang; Li, Shu; Li, Yichen; Liang, Zhijun; Liao, Hongbo; Liberti, Barbara; Lichard, Peter; Lie, Ki; Liebal, Jessica; Liebig, Wolfgang; Limbach, Christian; Limosani, Antonio; Lin, Simon; Lin, Tai-Hua; Linde, Frank; Lindquist, Brian Edward; Linnemann, James; Lipeles, Elliot; Lipniacka, Anna; Lisovyi, Mykhailo; Liss, Tony; Lissauer, David; Lister, Alison; Litke, Alan; Liu, Bo; Liu, Dong; Liu, Jianbei; Liu, Kun; Liu, Lulu; Liu, Miaoyuan; Liu, Minghui; Liu, Yanwen; Livan, Michele; Livermore, Sarah; Lleres, Annick; Llorente Merino, Javier; Lloyd, Stephen; Lo Sterzo, Francesco; Lobodzinska, Ewelina; Loch, Peter; Lockman, William; Loddenkoetter, Thomas; Loebinger, Fred; Loevschall-Jensen, Ask Emil; Loginov, Andrey; Loh, Chang Wei; Lohse, Thomas; Lohwasser, Kristin; Lokajicek, Milos; Lombardo, Vincenzo Paolo; Long, Brian Alexander; Long, Jonathan; Long, Robin Eamonn; Lopes, Lourenco; Lopez Mateos, David; Lopez Paredes, Brais; Lopez Paz, Ivan; Lorenz, Jeanette; Lorenzo Martinez, Narei; Losada, Marta; Loscutoff, Peter; Lou, XinChou; Lounis, Abdenour; Love, Jeremy; Love, Peter; Lowe, Andrew; Lu, Feng; Lubatti, Henry; Luci, Claudio; Lucotte, Arnaud; Luehring, Frederick; Lukas, Wolfgang; Luminari, Lamberto; Lundberg, Olof; Lund-Jensen, Bengt; Lungwitz, Matthias; Lynn, David; Lysak, Roman; Lytken, Else; Ma, Hong; Ma, Lian Liang; Maccarrone, Giovanni; Macchiolo, Anna; Machado Miguens, Joana; Macina, Daniela; Madaffari, Daniele; Madar, Romain; Maddocks, Harvey Jonathan; Mader, Wolfgang; Madsen, Alexander; Maeno, Mayuko; Maeno, Tadashi; Magradze, Erekle; Mahboubi, Kambiz; Mahlstedt, Joern; Mahmoud, Sara; Maiani, Camilla; Maidantchik, Carmen; Maier, Andreas Alexander; Maio, Amélia; Majewski, Stephanie; Makida, Yasuhiro; Makovec, Nikola; Mal, Prolay; Malaescu, Bogdan; Malecki, Pawel; Maleev, Victor; Malek, Fairouz; Mallik, Usha; Malon, David; Malone, Caitlin; Maltezos, Stavros; Malyshev, Vladimir; Malyukov, Sergei; Mamuzic, Judita; Mandelli, Beatrice; Mandelli, Luciano; Mandić, Igor; Mandrysch, Rocco; Maneira, José; Manfredini, Alessandro; Manhaes de Andrade Filho, Luciano; Manjarres Ramos, Joany Andreina; Mann, Alexander; Manning, Peter; Manousakis-Katsikakis, Arkadios; Mansoulie, Bruno; Mantifel, Rodger; Mapelli, Livio; March, Luis; Marchand, Jean-Francois; Marchiori, Giovanni; Marcisovsky, Michal; Marino, Christopher; Marjanovic, Marija; Marques, Carlos; Marroquim, Fernando; Marsden, Stephen Philip; Marshall, Zach; Marti, Lukas Fritz; Marti-Garcia, Salvador; Martin, Brian; Martin, Brian Thomas; Martin, Tim; Martin, Victoria Jane; Martin dit Latour, Bertrand; Martinez, Homero; Martinez, Mario; Martin-Haugh, Stewart; Martyniuk, Alex; Marx, Marilyn; Marzano, Francesco; Marzin, Antoine; Masetti, Lucia; Mashimo, Tetsuro; Mashinistov, Ruslan; Masik, Jiri; Maslennikov, Alexey; Massa, Ignazio; Massol, Nicolas; Mastrandrea, Paolo; Mastroberardino, Anna; Masubuchi, Tatsuya; Mättig, Peter; Mattmann, Johannes; Maurer, Julien; Maxfield, Stephen; Maximov, Dmitriy; Mazini, Rachid; Mazzaferro, Luca; Mc Goldrick, Garrin; Mc Kee, Shawn Patrick; McCarn, Allison; McCarthy, Robert; McCarthy, Tom; McCubbin, Norman; McFarlane, Kenneth; Mcfayden, Josh; Mchedlidze, Gvantsa; McMahon, Steve; McPherson, Robert; Meade, Andrew; Mechnich, Joerg; Medinnis, Michael; Meehan, Samuel; Mehlhase, Sascha; Mehta, Andrew; Meier, Karlheinz; Meineck, Christian; Meirose, Bernhard; Melachrinos, Constantinos; Mellado Garcia, Bruce Rafael; Meloni, Federico; Mengarelli, Alberto; Menke, Sven; Meoni, Evelin; Mercurio, Kevin Michael; Mergelmeyer, Sebastian; Meric, Nicolas; Mermod, Philippe; Merola, Leonardo; Meroni, Chiara; Merritt, Frank; Merritt, Hayes; Messina, Andrea; Metcalfe, Jessica; Mete, Alaettin Serhan; Meyer, Carsten; Meyer, Christopher; Meyer, Jean-Pierre; Meyer, Jochen; Middleton, Robin; Migas, Sylwia; Mijović, Liza; Mikenberg, Giora; Mikestikova, Marcela; Mikuž, Marko; Milic, Adriana; Miller, David; Mills, Corrinne; Milov, Alexander; Milstead, David; Milstein, Dmitry; Minaenko, Andrey; Minashvili, Irakli; Mincer, Allen; Mindur, Bartosz; Mineev, Mikhail; Ming, Yao; Mir, Lluisa-Maria; Mirabelli, Giovanni; Mitani, Takashi; Mitrevski, Jovan; Mitsou, Vasiliki A; Mitsui, Shingo; Miucci, Antonio; Miyagawa, Paul; Mjörnmark, Jan-Ulf; Moa, Torbjoern; Mochizuki, Kazuya; Mohapatra, Soumya; Mohr, Wolfgang; Molander, Simon; Moles-Valls, Regina; Mönig, Klaus; Monini, Caterina; Monk, James; Monnier, Emmanuel; Montejo Berlingen, Javier; Monticelli, Fernando; Monzani, Simone; Moore, Roger; Moraes, Arthur; Morange, Nicolas; Moreno, Deywis; Moreno Llácer, María; Morettini, Paolo; Morgenstern, Marcus; Morii, Masahiro; Moritz, Sebastian; Morley, Anthony Keith; Mornacchi, Giuseppe; Morris, John; Morvaj, Ljiljana; Moser, Hans-Guenther; Mosidze, Maia; Moss, Josh; Motohashi, Kazuki; Mount, Richard; Mountricha, Eleni; Mouraviev, Sergei; Moyse, Edward; Muanza, Steve; Mudd, Richard; Mueller, Felix; Mueller, James; Mueller, Klemens; Mueller, Thibaut; Mueller, Timo; Muenstermann, Daniel; Munwes, Yonathan; Murillo Quijada, Javier Alberto; Murray, Bill; Musheghyan, Haykuhi; Musto, Elisa; Myagkov, Alexey; Myska, Miroslav; Nackenhorst, Olaf; Nadal, Jordi; Nagai, Koichi; Nagai, Ryo; Nagai, Yoshikazu; Nagano, Kunihiro; Nagarkar, Advait; Nagasaka, Yasushi; Nagel, Martin; Nairz, Armin Michael; Nakahama, Yu; Nakamura, Koji; Nakamura, Tomoaki; Nakano, Itsuo; Namasivayam, Harisankar; Nanava, Gizo; Narayan, Rohin; Nattermann, Till; Naumann, Thomas; Navarro, Gabriela; Nayyar, Ruchika; Neal, Homer; Nechaeva, Polina; Neep, Thomas James; Nef, Pascal Daniel; Negri, Andrea; Negri, Guido; Negrini, Matteo; Nektarijevic, Snezana; Nelson, Andrew; Nelson, Timothy Knight; Nemecek, Stanislav; Nemethy, Peter; Nepomuceno, Andre Asevedo; Nessi, Marzio; Neubauer, Mark; Neumann, Manuel; Neves, Ricardo; Nevski, Pavel; Newman, Paul; Nguyen, Duong Hai; Nickerson, Richard; Nicolaidou, Rosy; Nicquevert, Bertrand; Nielsen, Jason; Nikiforou, Nikiforos; Nikiforov, Andriy; Nikolaenko, Vladimir; Nikolic-Audit, Irena; Nikolics, Katalin; Nikolopoulos, Konstantinos; Nilsson, Paul; Ninomiya, Yoichi; Nisati, Aleandro; Nisius, Richard; Nobe, Takuya; Nodulman, Lawrence; Nomachi, Masaharu; Nomidis, Ioannis; Norberg, Scarlet; Nordberg, Markus; Novgorodova, Olga; Nowak, Sebastian; Nozaki, Mitsuaki; Nozka, Libor; Ntekas, Konstantinos; Nunes Hanninger, Guilherme; Nunnemann, Thomas; Nurse, Emily; Nuti, Francesco; O'Brien, Brendan Joseph; O'grady, Fionnbarr; O'Neil, Dugan; O'Shea, Val; Oakham, Gerald; Oberlack, Horst; Obermann, Theresa; Ocariz, Jose; Ochi, Atsuhiko; Ochoa, Ines; Oda, Susumu; Odaka, Shigeru; Ogren, Harold; Oh, Alexander; Oh, Seog; Ohm, Christian; Ohman, Henrik; Ohshima, Takayoshi; Okamura, Wataru; Okawa, Hideki; Okumura, Yasuyuki; Okuyama, Toyonobu; Olariu, Albert; Olchevski, Alexander; Olivares Pino, Sebastian Andres; Oliveira Damazio, Denis; Oliver Garcia, Elena; Olszewski, Andrzej; Olszowska, Jolanta; Onofre, António; Onyisi, Peter; Oram, Christopher; Oreglia, Mark; Oren, Yona; Orestano, Domizia; Orlando, Nicola; Oropeza Barrera, Cristina; Orr, Robert; Osculati, Bianca; Ospanov, Rustem; Otero y Garzon, Gustavo; Otono, Hidetoshi; Ouchrif, Mohamed; Ouellette, Eric; Ould-Saada, Farid; Ouraou, Ahmimed; Oussoren, Koen Pieter; Ouyang, Qun; Ovcharova, Ana; Owen, Mark; Ozcan, Veysi Erkcan; Ozturk, Nurcan; Pachal, Katherine; Pacheco Pages, Andres; Padilla Aranda, Cristobal; Pagáčová, Martina; Pagan Griso, Simone; Paganis, Efstathios; Pahl, Christoph; Paige, Frank; Pais, Preema; Pajchel, Katarina; Palacino, Gabriel; Palestini, Sandro; Palka, Marek; Pallin, Dominique; Palma, Alberto; Palmer, Jody; Pan, Yibin; Panagiotopoulou, Evgenia; Panduro Vazquez, William; Pani, Priscilla; Panikashvili, Natalia; Panitkin, Sergey; Pantea, Dan; Paolozzi, Lorenzo; Papadopoulou, Theodora; Papageorgiou, Konstantinos; Paramonov, Alexander; Paredes Hernandez, Daniela; Parker, Michael Andrew; Parodi, Fabrizio; Parsons, John; Parzefall, Ulrich; Pasqualucci, Enrico; Passaggio, Stefano; Passeri, Antonio; Pastore, Fernanda; Pastore, Francesca; Pásztor, Gabriella; Pataraia, Sophio; Patel, Nikhul; Pater, Joleen; Patricelli, Sergio; Pauly, Thilo; Pearce, James; Pedersen, Maiken; Pedraza Lopez, Sebastian; Pedro, Rute; Peleganchuk, Sergey; Pelikan, Daniel; Peng, Haiping; Penning, Bjoern; Penwell, John; Perepelitsa, Dennis; Perez Codina, Estel; Pérez García-Estañ, María Teresa; Perez Reale, Valeria; Perini, Laura; Pernegger, Heinz; Perrino, Roberto; Peschke, Richard; Peshekhonov, Vladimir; Peters, Krisztian; Peters, Yvonne; Petersen, Brian; Petersen, Troels; Petit, Elisabeth; Petridis, Andreas; Petridou, Chariclia; Petrolo, Emilio; Petrucci, Fabrizio; Pettersson, Nora Emilia; Pezoa, Raquel; Phillips, Peter William; Piacquadio, Giacinto; Pianori, Elisabetta; Picazio, Attilio; Piccaro, Elisa; Piccinini, Maurizio; Piegaia, Ricardo; Pignotti, David; Pilcher, James; Pilkington, Andrew; Pina, João Antonio; Pinamonti, Michele; Pinder, Alex; Pinfold, James; Pingel, Almut; Pinto, Belmiro; Pires, Sylvestre; Pitt, Michael; Pizio, Caterina; Plazak, Lukas; Pleier, Marc-Andre; Pleskot, Vojtech; Plotnikova, Elena; Plucinski, Pawel; Poddar, Sahill; Podlyski, Fabrice; Poettgen, Ruth; Poggioli, Luc; Pohl, David-leon; Pohl, Martin; Polesello, Giacomo; Policicchio, Antonio; Polifka, Richard; Polini, Alessandro; Pollard, Christopher Samuel; Polychronakos, Venetios; Pommès, Kathy; Pontecorvo, Ludovico; Pope, Bernard; Popeneciu, Gabriel Alexandru; Popovic, Dragan; Poppleton, Alan; Portell Bueso, Xavier; Pospisil, Stanislav; Potamianos, Karolos; Potrap, Igor; Potter, Christina; Potter, Christopher; Poulard, Gilbert; Poveda, Joaquin; Pozdnyakov, Valery; Pralavorio, Pascal; Pranko, Aliaksandr; Prasad, Srivas; Pravahan, Rishiraj; Prell, Soeren; Price, Darren; Price, Joe; Price, Lawrence; Prieur, Damien; Primavera, Margherita; Proissl, Manuel; Prokofiev, Kirill; Prokoshin, Fedor; Protopapadaki, Eftychia-sofia; Protopopescu, Serban; Proudfoot, James; Przybycien, Mariusz; Przysiezniak, Helenka; Ptacek, Elizabeth; Puddu, Daniele; Pueschel, Elisa; Puldon, David; Purohit, Milind; Puzo, Patrick; Qian, Jianming; Qin, Gang; Qin, Yang; Quadt, Arnulf; Quarrie, David; Quayle, William; Queitsch-Maitland, Michaela; Quilty, Donnchadha; Qureshi, Anum; Radeka, Veljko; Radescu, Voica; Radhakrishnan, Sooraj Krishnan; Radloff, Peter; Rados, Pere; Ragusa, Francesco; Rahal, Ghita; Rajagopalan, Srinivasan; Rammensee, Michael; Randle-Conde, Aidan Sean; Rangel-Smith, Camila; Rao, Kanury; Rauscher, Felix; Rave, Tobias Christian; Ravenscroft, Thomas; Raymond, Michel; Read, Alexander Lincoln; Readioff, Nathan Peter; Rebuzzi, Daniela; Redelbach, Andreas; Redlinger, George; Reece, Ryan; Reeves, Kendall; Rehnisch, Laura; Reisin, Hernan; Relich, Matthew; Rembser, Christoph; Ren, Huan; Ren, Zhongliang; Renaud, Adrien; Rescigno, Marco; Resconi, Silvia; Rezanova, Olga; Reznicek, Pavel; Rezvani, Reyhaneh; Richter, Robert; Ridel, Melissa; Rieck, Patrick; Rieger, Julia; Rijssenbeek, Michael; Rimoldi, Adele; Rinaldi, Lorenzo; Ritsch, Elmar; Riu, Imma; Rizatdinova, Flera; Rizvi, Eram; Robertson, Steven; Robichaud-Veronneau, Andree; Robinson, Dave; Robinson, James; Robson, Aidan; Roda, Chiara; Rodrigues, Luis; Roe, Shaun; Røhne, Ole; Rolli, Simona; Romaniouk, Anatoli; Romano, Marino; Romero Adam, Elena; Rompotis, Nikolaos; Roos, Lydia; Ros, Eduardo; Rosati, Stefano; Rosbach, Kilian; Rose, Matthew; Rosendahl, Peter Lundgaard; Rosenthal, Oliver; Rossetti, Valerio; Rossi, Elvira; Rossi, Leonardo Paolo; Rosten, Rachel; Rotaru, Marina; Roth, Itamar; Rothberg, Joseph; Rousseau, David; Royon, Christophe; Rozanov, Alexandre; Rozen, Yoram; Ruan, Xifeng; Rubbo, Francesco; Rubinskiy, Igor; Rud, Viacheslav; Rudolph, Christian; Rudolph, Matthew Scott; Rühr, Frederik; Ruiz-Martinez, Aranzazu; Rurikova, Zuzana; Rusakovich, Nikolai; Ruschke, Alexander; Rutherfoord, John; Ruthmann, Nils; Ryabov, Yury; Rybar, Martin; Rybkin, Grigori; Ryder, Nick; Saavedra, Aldo; Sacerdoti, Sabrina; Saddique, Asif; Sadeh, Iftach; Sadrozinski, Hartmut; Sadykov, Renat; Safai Tehrani, Francesco; Sakamoto, Hiroshi; Sakurai, Yuki; Salamanna, Giuseppe; Salamon, Andrea; Saleem, Muhammad; Salek, David; Sales De Bruin, Pedro Henrique; Salihagic, Denis; Salnikov, Andrei; Salt, José; Salvachua Ferrando, Belén; Salvatore, Daniela; Salvatore, Pasquale Fabrizio; Salvucci, Antonio; Salzburger, Andreas; Sampsonidis, Dimitrios; Sanchez, Arturo; Sánchez, Javier; Sanchez Martinez, Victoria; Sandaker, Heidi; Sandbach, Ruth Laura; Sander, Heinz Georg; Sanders, Michiel; Sandhoff, Marisa; Sandoval, Tanya; Sandoval, Carlos; Sandstroem, Rikard; Sankey, Dave; Sansoni, Andrea; Santoni, Claudio; Santonico, Rinaldo; Santos, Helena; Santoyo Castillo, Itzebelt; Sapp, Kevin; Sapronov, Andrey; Saraiva, João; Sarrazin, Bjorn; Sartisohn, Georg; Sasaki, Osamu; Sasaki, Yuichi; Sauvage, Gilles; Sauvan, Emmanuel; Savard, Pierre; Savu, Dan Octavian; Sawyer, Craig; Sawyer, Lee; Saxon, David; Saxon, James; Sbarra, Carla; Sbrizzi, Antonio; Scanlon, Tim; Scannicchio, Diana; Scarcella, Mark; Scarfone, Valerio; Schaarschmidt, Jana; Schacht, Peter; Schaefer, Douglas; Schaefer, Ralph; Schaepe, Steffen; Schaetzel, Sebastian; Schäfer, Uli; Schaffer, Arthur; Schaile, Dorothee; Schamberger, R. Dean; Scharf, Veit; Schegelsky, Valery; Scheirich, Daniel; Schernau, Michael; Scherzer, Max; Schiavi, Carlo; Schieck, Jochen; Schillo, Christian; Schioppa, Marco; Schlenker, Stefan; Schmidt, Evelyn; Schmieden, Kristof; Schmitt, Christian; Schmitt, Christopher; Schmitt, Sebastian; Schneider, Basil; Schnellbach, Yan Jie; Schnoor, Ulrike; Schoeffel, Laurent; Schoening, Andre; Schoenrock, Bradley Daniel; Schorlemmer, Andre Lukas; Schott, Matthias; Schouten, Doug; Schovancova, Jaroslava; Schramm, Steven; Schreyer, Manuel; Schroeder, Christian; Schuh, Natascha; Schultens, Martin Johannes; Schultz-Coulon, Hans-Christian; Schulz, Holger; Schumacher, Markus; Schumm, Bruce; Schune, Philippe; Schwanenberger, Christian; Schwartzman, Ariel; Schwegler, Philipp; Schwemling, Philippe; Schwienhorst, Reinhard; Schwindling, Jerome; Schwindt, Thomas; Schwoerer, Maud; Sciacca, Gianfranco; Scifo, Estelle; Sciolla, Gabriella; Scott, Bill; Scuri, Fabrizio; Scutti, Federico; Searcy, Jacob; Sedov, George; Sedykh, Evgeny; Seidel, Sally; Seiden, Abraham; Seifert, Frank; Seixas, José; Sekhniaidze, Givi; Sekula, Stephen; Selbach, Karoline Elfriede; Seliverstov, Dmitry; Sellers, Graham; Semprini-Cesari, Nicola; Serfon, Cedric; Serin, Laurent; Serkin, Leonid; Serre, Thomas; Seuster, Rolf; Severini, Horst; Sfiligoj, Tina; Sforza, Federico; Sfyrla, Anna; Shabalina, Elizaveta; Shamim, Mansoora; Shan, Lianyou; Shang, Ruo-yu; Shank, James; Shapiro, Marjorie; Shatalov, Pavel; Shaw, Kate; Shehu, Ciwake Yusufu; Sherwood, Peter; Shi, Liaoshan; Shimizu, Shima; Shimmin, Chase Owen; Shimojima, Makoto; Shiyakova, Mariya; Shmeleva, Alevtina; Shochet, Mel; Short, Daniel; Shrestha, Suyog; Shulga, Evgeny; Shupe, Michael; Shushkevich, Stanislav; Sicho, Petr; Sidiropoulou, Ourania; Sidorov, Dmitri; Sidoti, Antonio; Siegert, Frank; Sijacki, Djordje; Silva, José; Silver, Yiftah; Silverstein, Daniel; Silverstein, Samuel; Simak, Vladislav; Simard, Olivier; Simic, Ljiljana; Simion, Stefan; Simioni, Eduard; Simmons, Brinick; Simoniello, Rosa; Simonyan, Margar; Sinervo, Pekka; Sinev, Nikolai; Sipica, Valentin; Siragusa, Giovanni; Sircar, Anirvan; Sisakyan, Alexei; Sivoklokov, Serguei; Sjölin, Jörgen; Sjursen, Therese; Skottowe, Hugh Philip; Skovpen, Kirill; Skubic, Patrick; Slater, Mark; Slavicek, Tomas; Sliwa, Krzysztof; Smakhtin, Vladimir; Smart, Ben; Smestad, Lillian; Smirnov, Sergei; Smirnov, Yury; Smirnova, Lidia; Smirnova, Oxana; Smith, Kenway; Smizanska, Maria; Smolek, Karel; Snesarev, Andrei; Snidero, Giacomo; Snyder, Scott; Sobie, Randall; Socher, Felix; Soffer, Abner; Soh, Dart-yin; Solans, Carlos; Solar, Michael; Solc, Jaroslav; Soldatov, Evgeny; Soldevila, Urmila; Solfaroli Camillocci, Elena; Solodkov, Alexander; Soloshenko, Alexei; Solovyanov, Oleg; Solovyev, Victor; Sommer, Philip; Song, Hong Ye; Soni, Nitesh; Sood, Alexander; Sopczak, Andre; Sopko, Bruno; Sopko, Vit; Sorin, Veronica; Sosebee, Mark; Soualah, Rachik; Soueid, Paul; Soukharev, Andrey; South, David; Spagnolo, Stefania; Spanò, Francesco; Spearman, William Robert; Spettel, Fabian; Spighi, Roberto; Spigo, Giancarlo; Spousta, Martin; Spreitzer, Teresa; Spurlock, Barry; St Denis, Richard Dante; Staerz, Steffen; Stahlman, Jonathan; Stamen, Rainer; Stanecka, Ewa; Stanek, Robert; Stanescu, Cristian; Stanescu-Bellu, Madalina; Stanitzki, Marcel Michael; Stapnes, Steinar; Starchenko, Evgeny; Stark, Jan; Staroba, Pavel; Starovoitov, Pavel; Staszewski, Rafal; Stavina, Pavel; Steinberg, Peter; Stelzer, Bernd; Stelzer, Harald Joerg; Stelzer-Chilton, Oliver; Stenzel, Hasko; Stern, Sebastian; Stewart, Graeme; Stillings, Jan Andre; Stockton, Mark; Stoebe, Michael; Stoicea, Gabriel; Stolte, Philipp; Stonjek, Stefan; Stradling, Alden; Straessner, Arno; Stramaglia, Maria Elena; Strandberg, Jonas; Strandberg, Sara; Strandlie, Are; Strauss, Emanuel; Strauss, Michael; Strizenec, Pavol; Ströhmer, Raimund; Strom, David; Stroynowski, Ryszard; Stucci, Stefania Antonia; Stugu, Bjarne; Styles, Nicholas Adam; Su, Dong; Su, Jun; Subramania, Halasya Siva; Subramaniam, Rajivalochan; Succurro, Antonella; Sugaya, Yorihito; Suhr, Chad; Suk, Michal; Sulin, Vladimir; Sultansoy, Saleh; Sumida, Toshi; Sun, Xiaohu; Sundermann, Jan Erik; Suruliz, Kerim; Susinno, Giancarlo; Sutton, Mark; Suzuki, Yu; Svatos, Michal; Swedish, Stephen; Swiatlowski, Maximilian; Sykora, Ivan; Sykora, Tomas; Ta, Duc; Taccini, Cecilia; Tackmann, Kerstin; Taenzer, Joe; Taffard, Anyes; Tafirout, Reda; Taiblum, Nimrod; Takahashi, Yuta; Takai, Helio; Takashima, Ryuichi; Takeda, Hiroshi; Takeshita, Tohru; Takubo, Yosuke; Talby, Mossadek; Talyshev, Alexey; Tam, Jason; Tan, Kong Guan; Tanaka, Junichi; Tanaka, Reisaburo; Tanaka, Satoshi; Tanaka, Shuji; Tanasijczuk, Andres Jorge; Tannenwald, Benjamin Bordy; Tannoury, Nancy; Tapprogge, Stefan; Tarem, Shlomit; Tarrade, Fabien; Tartarelli, Giuseppe Francesco; Tas, Petr; Tasevsky, Marek; Tashiro, Takuya; Tassi, Enrico; Tavares Delgado, Ademar; Tayalati, Yahya; Taylor, Frank; Taylor, Geoffrey; Taylor, Wendy; Teischinger, Florian Alfred; Teixeira Dias Castanheira, Matilde; Teixeira-Dias, Pedro; Temming, Kim Katrin; Ten Kate, Herman; Teng, Ping-Kun; Teoh, Jia Jian; Terada, Susumu; Terashi, Koji; Terron, Juan; Terzo, Stefano; Testa, Marianna; Teuscher, Richard; Therhaag, Jan; Theveneaux-Pelzer, Timothée; Thomas, Juergen; Thomas-Wilsker, Joshuha; Thompson, Emily; Thompson, Paul; Thompson, Peter; Thompson, Stan; Thomsen, Lotte Ansgaard; Thomson, Evelyn; Thomson, Mark; Thong, Wai Meng; Thun, Rudolf; Tian, Feng; Tibbetts, Mark James; Tikhomirov, Vladimir; Tikhonov, Yury; Timoshenko, Sergey; Tiouchichine, Elodie; Tipton, Paul; Tisserant, Sylvain; Todorov, Theodore; Todorova-Nova, Sharka; Toggerson, Brokk; Tojo, Junji; Tokár, Stanislav; Tokushuku, Katsuo; Tollefson, Kirsten; Tomlinson, Lee; Tomoto, Makoto; Tompkins, Lauren; Toms, Konstantin; Topilin, Nikolai; Torrence, Eric; Torres, Heberth; Torró Pastor, Emma; Toth, Jozsef; Touchard, Francois; Tovey, Daniel; Tran, Huong Lan; Trefzger, Thomas; Tremblet, Louis; Tricoli, Alessandro; Trigger, Isabel Marian; Trincaz-Duvoid, Sophie; Tripiana, Martin; Triplett, Nathan; Trischuk, William; Trocmé, Benjamin; Troncon, Clara; Trottier-McDonald, Michel; Trovatelli, Monica; True, Patrick; Trzebinski, Maciej; Trzupek, Adam; Tsarouchas, Charilaos; Tseng, Jeffrey; Tsiareshka, Pavel; Tsionou, Dimitra; Tsipolitis, Georgios; Tsirintanis, Nikolaos; Tsiskaridze, Shota; Tsiskaridze, Vakhtang; Tskhadadze, Edisher; Tsukerman, Ilya; Tsulaia, Vakhtang; Tsuno, Soshi; Tsybychev, Dmitri; Tudorache, Alexandra; Tudorache, Valentina; Tuna, Alexander Naip; Tupputi, Salvatore; Turchikhin, Semen; Turecek, Daniel; Turk Cakir, Ilkay; Turra, Ruggero; Tuts, Michael; Tykhonov, Andrii; Tylmad, Maja; Tyndel, Mike; Uchida, Kirika; Ueda, Ikuo; Ueno, Ryuichi; Ughetto, Michael; Ugland, Maren; Uhlenbrock, Mathias; Ukegawa, Fumihiko; Unal, Guillaume; Undrus, Alexander; Unel, Gokhan; Ungaro, Francesca; Unno, Yoshinobu; Urbaniec, Dustin; Urquijo, Phillip; Usai, Giulio; Usanova, Anna; Vacavant, Laurent; Vacek, Vaclav; Vachon, Brigitte; Valencic, Nika; Valentinetti, Sara; Valero, Alberto; Valery, Loic; Valkar, Stefan; Valladolid Gallego, Eva; Vallecorsa, Sofia; Valls Ferrer, Juan Antonio; Van Den Wollenberg, Wouter; Van Der Deijl, Pieter; van der Geer, Rogier; van der Graaf, Harry; Van Der Leeuw, Robin; van der Ster, Daniel; van Eldik, Niels; van Gemmeren, Peter; Van Nieuwkoop, Jacobus; van Vulpen, Ivo; van Woerden, Marius Cornelis; Vanadia, Marco; Vandelli, Wainer; Vanguri, Rami; Vaniachine, Alexandre; Vankov, Peter; Vannucci, Francois; Vardanyan, Gagik; Vari, Riccardo; Varnes, Erich; Varol, Tulin; Varouchas, Dimitris; Vartapetian, Armen; Varvell, Kevin; Vazeille, Francois; Vazquez Schroeder, Tamara; Veatch, Jason; Veloso, Filipe; Veneziano, Stefano; Ventura, Andrea; Ventura, Daniel; Venturi, Manuela; Venturi, Nicola; Venturini, Alessio; Vercesi, Valerio; Verducci, Monica; Verkerke, Wouter; Vermeulen, Jos; Vest, Anja; Vetterli, Michel; Viazlo, Oleksandr; Vichou, Irene; Vickey, Trevor; Vickey Boeriu, Oana Elena; Viehhauser, Georg; Viel, Simon; Vigne, Ralph; Villa, Mauro; Villaplana Perez, Miguel; Vilucchi, Elisabetta; Vincter, Manuella; Vinogradov, Vladimir; Virzi, Joseph; Vivarelli, Iacopo; Vives Vaque, Francesc; Vlachos, Sotirios; Vladoiu, Dan; Vlasak, Michal; Vogel, Adrian; Vogel, Marcelo; Vokac, Petr; Volpi, Guido; Volpi, Matteo; von der Schmitt, Hans; von Radziewski, Holger; von Toerne, Eckhard; Vorobel, Vit; Vorobev, Konstantin; Vos, Marcel; Voss, Rudiger; Vossebeld, Joost; Vranjes, Nenad; Vranjes Milosavljevic, Marija; Vrba, Vaclav; Vreeswijk, Marcel; Vu Anh, Tuan; Vuillermet, Raphael; Vukotic, Ilija; Vykydal, Zdenek; Wagner, Peter; Wagner, Wolfgang; Wahlberg, Hernan; Wahrmund, Sebastian; Wakabayashi, Jun; Walder, James; Walker, Rodney; Walkowiak, Wolfgang; Wall, Richard; Waller, Peter; Walsh, Brian; Wang, Chao; Wang, Chiho; Wang, Fuquan; Wang, Haichen; Wang, Hulin; Wang, Jike; Wang, Jin; Wang, Kuhan; Wang, Rui; Wang, Song-Ming; Wang, Tan; Wang, Xiaoxiao; Wanotayaroj, Chaowaroj; Warburton, Andreas; Ward, Patricia; Wardrope, David Robert; Warsinsky, Markus; Washbrook, Andrew; Wasicki, Christoph; Watkins, Peter; Watson, Alan; Watson, Ian; Watson, Miriam; Watts, Gordon; Watts, Stephen; Waugh, Ben; Webb, Samuel; Weber, Michele; Weber, Stefan Wolf; Webster, Jordan S; Weidberg, Anthony; Weigell, Philipp; Weinert, Benjamin; Weingarten, Jens; Weiser, Christian; Weits, Hartger; Wells, Phillippa; Wenaus, Torre; Wendland, Dennis; Weng, Zhili; Wengler, Thorsten; Wenig, Siegfried; Wermes, Norbert; Werner, Matthias; Werner, Per; Wessels, Martin; Wetter, Jeffrey; Whalen, Kathleen; White, Andrew; White, Martin; White, Ryan; White, Sebastian; Whiteson, Daniel; Wicke, Daniel; Wickens, Fred; Wiedenmann, Werner; Wielers, Monika; Wienemann, Peter; Wiglesworth, Craig; Wiik-Fuchs, Liv Antje Mari; Wijeratne, Peter Alexander; Wildauer, Andreas; Wildt, Martin Andre; Wilkens, Henric George; Will, Jonas Zacharias; Williams, Hugh; Williams, Sarah; Willis, Christopher; Willocq, Stephane; Wilson, Alan; Wilson, John; Wingerter-Seez, Isabelle; Winklmeier, Frank; Winter, Benedict Tobias; Wittgen, Matthias; Wittig, Tobias; Wittkowski, Josephine; Wollstadt, Simon Jakob; Wolter, Marcin Wladyslaw; Wolters, Helmut; Wosiek, Barbara; Wotschack, Jorg; Woudstra, Martin; Wozniak, Krzysztof; Wright, Michael; Wu, Mengqing; Wu, Sau Lan; Wu, Xin; Wu, Yusheng; Wulf, Evan; Wyatt, Terry Richard; Wynne, Benjamin; Xella, Stefania; Xiao, Meng; Xu, Da; Xu, Lailin; Yabsley, Bruce; Yacoob, Sahal; Yamada, Miho; Yamaguchi, Hiroshi; Yamaguchi, Yohei; Yamamoto, Akira; Yamamoto, Kyoko; Yamamoto, Shimpei; Yamamura, Taiki; Yamanaka, Takashi; Yamauchi, Katsuya; Yamazaki, Yuji; Yan, Zhen; Yang, Haijun; Yang, Hongtao; Yang, Un-Ki; Yang, Yi; Yanush, Serguei; Yao, Liwen; Yao, Weiming; Yasu, Yoshiji; Yatsenko, Elena; Yau Wong, Kaven Henry; Ye, Jingbo; Ye, Shuwei; Yen, Andy L; Yildirim, Eda; Yilmaz, Metin; Yoosoofmiya, Reza; Yorita, Kohei; Yoshida, Rikutaro; Yoshihara, Keisuke; Young, Charles; Young, Christopher John; Youssef, Saul; Yu, David Ren-Hwa; Yu, Jaehoon; Yu, Jiaming; Yu, Jie; Yuan, Li; Yurkewicz, Adam; Yusuff, Imran; Zabinski, Bartlomiej; Zaidan, Remi; Zaitsev, Alexander; Zaman, Aungshuman; Zambito, Stefano; Zanello, Lucia; Zanzi, Daniele; Zeitnitz, Christian; Zeman, Martin; Zemla, Andrzej; Zengel, Keith; Zenin, Oleg; Ženiš, Tibor; Zerwas, Dirk; Zevi della Porta, Giovanni; Zhang, Dongliang; Zhang, Fangzhou; Zhang, Huaqiao; Zhang, Jinlong; Zhang, Lei; Zhang, Xueyao; Zhang, Zhiqing; Zhao, Zhengguo; Zhemchugov, Alexey; Zhong, Jiahang; Zhou, Bing; Zhou, Lei; Zhou, Ning; Zhu, Cheng Guang; Zhu, Hongbo; Zhu, Junjie; Zhu, Yingchun; Zhuang, Xuai; Zhukov, Konstantin; Zibell, Andre; Zieminska, Daria; Zimine, Nikolai; Zimmermann, Christoph; Zimmermann, Robert; Zimmermann, Simone; Zimmermann, Stephanie; Zinonos, Zinonas; Ziolkowski, Michael; Zobernig, Georg; Zoccoli, Antonio; zur Nedden, Martin; Zurzolo, Giovanni; Zutshi, Vishnu; Zwalinski, Lukasz

2014-09-15

A novel technique to identify and split clusters created by multiple charged particles in the ATLAS pixel detector using a set of artificial neural networks is presented. Such merged clusters are a common feature of tracks originating from highly energetic objects, such as jets. Neural networks are trained using Monte Carlo samples produced with a detailed detector simulation. This technique replaces the former clustering approach based on a connected component analysis and charge interpolation. The performance of the neural network splitting technique is quantified using data from proton-proton collisions at the LHC collected by the ATLAS detector in 2011 and from Monte Carlo simulations. This technique reduces the number of clusters shared between tracks in highly energetic jets by up to a factor of three. It also provides more precise position and error estimates of the clusters in both the transverse and longitudinal impact parameter resolution.

Novel Adaptive Forward Neural MIMO NARX Model for the Identification of Industrial 3-DOF Robot Arm Kinematics

Directory of Open Access Journals (Sweden)

Ho Pham Huy Anh

2012-10-01

Full Text Available In this paper, a novel forward adaptive neural MIMO NARX model is used for modelling and identifying the forward kinematics of an industrial 3-DOF robot arm system. The nonlinear features of the forward kinematics of the industrial robot arm drive are thoroughly modelled based on the forward adaptive neural NARX model-based identification process using experimental input-output training data. This paper proposes a novel use of a back propagation (BP algorithm to generate the forward neural MIMO NARX (FNMN model for the forward kinematics of the industrial 3-DOF robot arm. The results show that the proposed adaptive neural NARX model trained by a Back Propagation learning algorithm yields outstanding performance and perfect accuracy.

The Use of Artificial Neural Networks in Prediction of Congenital CMV Outcome from Sequence Data

Directory of Open Access Journals (Sweden)

Ravit Arav-Boger

2008-01-01

Full Text Available A large number of CMV strains has been reported to circulate in the human population, and the biological significance of these strains is currently an active area of research. The analysis of complex genetic information may be limited using conventional phylogenetic techniques. We constructed artificial neural networks to determine their feasibility in predicting the outcome of congenital CMV disease (defined as presence of CMV symptoms at birth based on two data sets: 54 sequences of CMV gene UL144 obtained from 54 amniotic fluids of women who contracted acute CMV infection during their pregnancy, and 80 sequences of 4 genes (US28, UL144, UL146 and UL147 obtained from urine, saliva or blood of 20 congenitally infected infants that displayed different outcomes at birth. When data from all four genes was used in the 20-infants’ set, the artificial neural network model accurately identified outcome in 90% of cases. While US28 and UL147 had low yield in predicting outcome, UL144 and UL146 predicted outcome in 80% and 85% respectively when used separately. The model identified specific nucleotide positions that were highly relevant to prediction of outcome. The artificial neural network classified genotypes in agreement with classic phylogenetic analysis. We suggest that artificial neural networks can accurately and efficiently analyze sequences obtained from larger cohorts to determine specific outcomes.The ANN training and analysis code is commercially available from Optimal Neural Informatics (Pikesville, MD.

Hypothetical Pattern Recognition Design Using Multi-Layer Perceptorn Neural Network For Supervised Learning

Directory of Open Access Journals (Sweden)

Md. Abdullah-al-mamun

2015-08-01

Full Text Available Abstract Humans are capable to identifying diverse shape in the different pattern in the real world as effortless fashion due to their intelligence is grow since born with facing several learning process. Same way we can prepared an machine using human like brain called Artificial Neural Network that can be recognize different pattern from the real world object. Although the various techniques is exists to implementation the pattern recognition but recently the artificial neural network approaches have been giving the significant attention. Because the approached of artificial neural network is like a human brain that is learn from different observation and give a decision the previously learning rule. Over the 50 years research now a days pattern recognition for machine learning using artificial neural network got a significant achievement. For this reason many real world problem can be solve by modeling the pattern recognition process. The objective of this paper is to present the theoretical concept for pattern recognition design using Multi-Layer Perceptorn neural networkin the algorithm of artificial Intelligence as the best possible way of utilizing available resources to make a decision that can be a human like performance.

Fibrous dysplasia of the cranial vault: quantitative analysis based on neural networks

International Nuclear Information System (INIS)

Arana, E.; Marti-Bonmati, L.; Paredes, R.; Molla, E.

1998-01-01

To assess the utility of statistical analysis and neural networks in the quantitative analysis of fibrous dysplasia of the cranial vault. Ten patients with fibrous dysplasia (six women and four men with a mean age of 23.60±17.85 years) were selected from a series of 167 patients with lesions of the cranial vault evaluated by plain radiography and computed tomography (CT). Nineteen variables were taken from their medical records and radiological study. Their characterization was based on statistical analysis and neural network, and was validated by means of the leave-one-out method. The performance of the neural network was estimated by means of receiver operating characteristics (ROC) curves, using as a parameter the area under the curve A z . Bivariate analysis identified age, duration of symptoms, lytic and sclerotic patterns, sclerotic margin, ovoid shape, soft-tissue mas and periosteal reaction as significant variables. The area under the neural network curve was 0.9601±0.0435. The network selected the matrix and soft-tissue mass a variables that were indispensable for diagnosis. The neural network presents a high performance in the characterization of fibrous dysplasia of the cranial vault, disclosing occult interactions among the variables. (Author) 24 refs

Oscillatory neural representations in the sensory thalamus predict neuropathic pain relief by deep brain stimulation.

Science.gov (United States)

Huang, Yongzhi; Green, Alexander L; Hyam, Jonathan; Fitzgerald, James; Aziz, Tipu Z; Wang, Shouyan

2018-01-01

Understanding the function of sensory thalamic neural activity is essential for developing and improving interventions for neuropathic pain. However, there is a lack of investigation of the relationship between sensory thalamic oscillations and pain relief in patients with neuropathic pain. This study aims to identify the oscillatory neural characteristics correlated with pain relief induced by deep brain stimulation (DBS), and develop a quantitative model to predict pain relief by integrating characteristic measures of the neural oscillations. Measures of sensory thalamic local field potentials (LFPs) in thirteen patients with neuropathic pain were screened in three dimensional feature space according to the rhythm, balancing, and coupling neural behaviours, and correlated with pain relief. An integrated approach based on principal component analysis (PCA) and multiple regression analysis is proposed to integrate the multiple measures and provide a predictive model. This study reveals distinct thalamic rhythms of theta, alpha, high beta and high gamma oscillations correlating with pain relief. The balancing and coupling measures between these neural oscillations were also significantly correlated with pain relief. The study enriches the series research on the function of thalamic neural oscillations in neuropathic pain and relief, and provides a quantitative approach for predicting pain relief by DBS using thalamic neural oscillations. Copyright © 2017 Elsevier Inc. All rights reserved.

Recognition of underground nuclear explosion and natural earthquake based on neural network

International Nuclear Information System (INIS)

Yang Hong; Jia Weimin

2000-01-01

Many features are extracted to improve the identified rate and reliability of underground nuclear explosion and natural earthquake. But how to synthesize these characters is the key of pattern recognition. Based on the improved Delta algorithm, features of underground nuclear explosion and natural earthquake are inputted into BP neural network, and friendship functions are constructed to identify the output values. The identified rate is up to 92.0%, which shows that: the way is feasible

Genome-wide identification and characterization of putative lncRNAs in the diamondback moth, Plutella xylostella (L.).

Science.gov (United States)

Wang, Yue; Xu, Tingting; He, Weiyi; Shen, Xiujing; Zhao, Qian; Bai, Jianlin; You, Minsheng

2018-01-01

Long non-coding RNAs (lncRNAs) are of particular interest because of their contributions to many biological processes. Here, we present the genome-wide identification and characterization of putative lncRNAs in a global insect pest, Plutella xylostella. A total of 8096 lncRNAs were identified and classified into three groups. The average length of exons in lncRNAs was longer than that in coding genes and the GC content was lower than that in mRNAs. Most lncRNAs were flanked by canonical splice sites, similar to mRNAs. Expression profiling identified 114 differentially expressed lncRNAs during the DBM development and found that majority were temporally specific. While the biological functions of lncRNAs remain uncharacterized, many are microRNA precursors or competing endogenous RNAs involved in micro-RNA regulatory pathways. This work provides a valuable resource for further studies on molecular bases for development of DBM and lay the foundation for discovery of lncRNA functions in P. xylostella. Copyright © 2017 Elsevier Inc. All rights reserved.

Distribution of putative virulence genes and antimicrobial drug resistance in Vibrio harveyi

Digital Repository Service at National Institute of Oceanography (India)