Feature Inference and the Causal Structure of Categories

ERIC Educational Resources Information Center

Rehder, B.; Burnett, R.C.

2005-01-01

The purpose of this article was to establish how theoretical category knowledge-specifically, knowledge of the causal relations that link the features of categories-supports the ability to infer the presence of unobserved features. Our experiments were designed to test proposals that causal knowledge is represented psychologically as Bayesian…

Structural features based genome-wide characterization and prediction of nucleosome organization

PubMed Central

2012-01-01

Background Nucleosome distribution along chromatin dictates genomic DNA accessibility and thus profoundly influences gene expression. However, the underlying mechanism of nucleosome formation remains elusive. Here, taking a structural perspective, we systematically explored nucleosome formation potential of genomic sequences and the effect on chromatin organization and gene expression in S. cerevisiae. Results We analyzed twelve structural features related to flexibility, curvature and energy of DNA sequences. The results showed that some structural features such as DNA denaturation, DNA-bending stiffness, Stacking energy, Z-DNA, Propeller twist and free energy, were highly correlated with in vitro and in vivo nucleosome occupancy. Specifically, they can be classified into two classes, one positively and the other negatively correlated with nucleosome occupancy. These two kinds of structural features facilitated nucleosome binding in centromere regions and repressed nucleosome formation in the promoter regions of protein-coding genes to mediate transcriptional regulation. Based on these analyses, we integrated all twelve structural features in a model to predict more accurately nucleosome occupancy in vivo than the existing methods that mainly depend on sequence compositional features. Furthermore, we developed a novel approach, named DLaNe, that located nucleosomes by detecting peaks of structural profiles, and built a meta predictor to integrate information from different structural features. As a comparison, we also constructed a hidden Markov model (HMM) to locate nucleosomes based on the profiles of these structural features. The result showed that the meta DLaNe and HMM-based method performed better than the existing methods, demonstrating the power of these structural features in predicting nucleosome positions. Conclusions Our analysis revealed that DNA structures significantly contribute to nucleosome organization and influence chromatin structure and gene expression regulation. The results indicated that our proposed methods are effective in predicting nucleosome occupancy and positions and that these structural features are highly predictive of nucleosome organization. The implementation of our DLaNe method based on structural features is available online. PMID:22449207

Linguistic Features and Schematic Textual Structure in Look-Good Advertisements in the Indian Print Media in English

ERIC Educational Resources Information Center

Singh, Sukhdev; Bedi, Navkiran Kaur

2013-01-01

Every text has a communicative purpose that it performs by dividing itself into generic stages. These stages are assigned specific goals and have differing linguistic structures. This paper makes an attempt to investigate whether there is a definable co-relation between linguistic features and stages in the genre of look-good advertisements. It…

Coastal Geographic Structures in Coastal-Marine Environmental Management

NASA Astrophysics Data System (ADS)

Baklanov, P. Ya.; Ganzei, K. S.; Ermoshin, V. V.

2018-01-01

It has been proposed to distinguish the coastal geographic structures consisting of a spatial combination of three interconnected and mutually conditioned parts (coastal-territorial, coastal, coastal-marine), which are interlinked with each other by the cumulative effect of real-energy flows. Distinguishing specific resource features of the coastal structures, by which they play a connecting role in the complex coastalmarine management, has been considered. The main integral resource feature of the coastal structures is their connecting functions, which form transitional parts mutually connecting the coastal-territorial and coastalmarine environmental management.

A deep learning framework for modeling structural features of RNA-binding protein targets

PubMed Central

Zhang, Sai; Zhou, Jingtian; Hu, Hailin; Gong, Haipeng; Chen, Ligong; Cheng, Chao; Zeng, Jianyang

2016-01-01

RNA-binding proteins (RBPs) play important roles in the post-transcriptional control of RNAs. Identifying RBP binding sites and characterizing RBP binding preferences are key steps toward understanding the basic mechanisms of the post-transcriptional gene regulation. Though numerous computational methods have been developed for modeling RBP binding preferences, discovering a complete structural representation of the RBP targets by integrating their available structural features in all three dimensions is still a challenging task. In this paper, we develop a general and flexible deep learning framework for modeling structural binding preferences and predicting binding sites of RBPs, which takes (predicted) RNA tertiary structural information into account for the first time. Our framework constructs a unified representation that characterizes the structural specificities of RBP targets in all three dimensions, which can be further used to predict novel candidate binding sites and discover potential binding motifs. Through testing on the real CLIP-seq datasets, we have demonstrated that our deep learning framework can automatically extract effective hidden structural features from the encoded raw sequence and structural profiles, and predict accurate RBP binding sites. In addition, we have conducted the first study to show that integrating the additional RNA tertiary structural features can improve the model performance in predicting RBP binding sites, especially for the polypyrimidine tract-binding protein (PTB), which also provides a new evidence to support the view that RBPs may own specific tertiary structural binding preferences. In particular, the tests on the internal ribosome entry site (IRES) segments yield satisfiable results with experimental support from the literature and further demonstrate the necessity of incorporating RNA tertiary structural information into the prediction model. The source code of our approach can be found in https://github.com/thucombio/deepnet-rbp. PMID:26467480

Non-familial hemophagocytic lymphohistiocytosis.

PubMed

Cozzutto, C; Carbone, A; Comelli, A; Volpe, R

1989-03-01

A case of non-familial hemophagocytic lymphohistiocytosis (HLH) is described. The patient had a chronic course being alive and doing relatively well 3 years since onset. The specific pathological features of this disorder are discussed with emphasis on the fact that a remarkable loss of lymph node structure is sustained by a mature lymphohistiocytic infiltrate. Erythrophagocytosis is assessed as an important but not specific finding. Lymphocyte depletion is an important feature of the lesion. The presence of overlapping features in HLH, infection-associated hemophagocytic syndrome (IAHS) and X-linked recessive lymphoproliferative syndrome (XLS) is emphasized.

Feature Selection Using Information Gain for Improved Structural-Based Alert Correlation

PubMed Central

Siraj, Maheyzah Md; Zainal, Anazida; Elshoush, Huwaida Tagelsir; Elhaj, Fatin

2016-01-01

Grouping and clustering alerts for intrusion detection based on the similarity of features is referred to as structurally base alert correlation and can discover a list of attack steps. Previous researchers selected different features and data sources manually based on their knowledge and experience, which lead to the less accurate identification of attack steps and inconsistent performance of clustering accuracy. Furthermore, the existing alert correlation systems deal with a huge amount of data that contains null values, incomplete information, and irrelevant features causing the analysis of the alerts to be tedious, time-consuming and error-prone. Therefore, this paper focuses on selecting accurate and significant features of alerts that are appropriate to represent the attack steps, thus, enhancing the structural-based alert correlation model. A two-tier feature selection method is proposed to obtain the significant features. The first tier aims at ranking the subset of features based on high information gain entropy in decreasing order. The‏ second tier extends additional features with a better discriminative ability than the initially ranked features. Performance analysis results show the significance of the selected features in terms of the clustering accuracy using 2000 DARPA intrusion detection scenario-specific dataset. PMID:27893821

Influence of culture medium growth variables on Ganoderma lucidum exopolysaccharides structural features.

PubMed

Fraga, Irene; Coutinho, João; Bezerra, Rui M; Dias, Albino A; Marques, Guilhermina; Nunes, Fernando M

2014-10-13

In this work the effect of carbon and nitrogen levels and initial pH of the wheat extract culture medium of submerged culture of Ganoderma lucidum on the amount, purity and structural features of exopolysaccharides (EPS) were studied. A low peptone level (1.65 g L(-1)) favored mycelium biomass, EPS purity, but a higher supply of peptone (4.80 g L(-1)) is needed for maximum EPS production. The carbohydrate composition of the EPS and structural features also changed significantly according to the different growing conditions, being observed significant differences in the (1 → 3)/(1 → 4)-Glcp ratio and also on the branching degree of EPS. As the biological activities of EPS are highly dependent on the polysaccharide structural features, this variability can have implications on the EPS biological activities, but can also be used advantageously to produce tailor made polysaccharides with specific applications. Copyright © 2014 Elsevier Ltd. All rights reserved.

MultiLIS: A Description of the System Design and Operational Features.

ERIC Educational Resources Information Center

Kelly, Glen J.; And Others

1988-01-01

Describes development, hardware requirements, and features of the MultiLIS integrated library software package. A system profile provides pricing information, operational characteristics, and technical specifications. Sidebars discuss MultiLIS integration structure, incremental architecture, and NCR Tower Computers. (4 references) (MES)

Examining Brain Morphometry Associated with Self-Esteem in Young Adults Using Multilevel-ROI-Features-Based Classification Method

PubMed Central

Peng, Bo; Lu, Jieru; Saxena, Aditya; Zhou, Zhiyong; Zhang, Tao; Wang, Suhong; Dai, Yakang

2017-01-01

Purpose: This study is to exam self-esteem related brain morphometry on brain magnetic resonance (MR) images using multilevel-features-based classification method. Method: The multilevel region of interest (ROI) features consist of two types of features: (i) ROI features, which include gray matter volume, white matter volume, cerebrospinal fluid volume, cortical thickness, and cortical surface area, and (ii) similarity features, which are based on similarity calculation of cortical thickness between ROIs. For each feature type, a hybrid feature selection method, comprising of filter-based and wrapper-based algorithms, is used to select the most discriminating features. ROI features and similarity features are integrated by using multi-kernel support vector machines (SVMs) with appropriate weighting factor. Results: The classification performance is improved by using multilevel ROI features with an accuracy of 96.66%, a specificity of 96.62%, and a sensitivity of 95.67%. The most discriminating ROI features that are related to self-esteem spread over occipital lobe, frontal lobe, parietal lobe, limbic lobe, temporal lobe, and central region, mainly involving white matter and cortical thickness. The most discriminating similarity features are distributed in both the right and left hemisphere, including frontal lobe, occipital lobe, limbic lobe, parietal lobe, and central region, which conveys information of structural connections between different brain regions. Conclusion: By using ROI features and similarity features to exam self-esteem related brain morphometry, this paper provides a pilot evidence that self-esteem is linked to specific ROIs and structural connections between different brain regions. PMID:28588470

Examining Brain Morphometry Associated with Self-Esteem in Young Adults Using Multilevel-ROI-Features-Based Classification Method.

PubMed

Peng, Bo; Lu, Jieru; Saxena, Aditya; Zhou, Zhiyong; Zhang, Tao; Wang, Suhong; Dai, Yakang

2017-01-01

Purpose: This study is to exam self-esteem related brain morphometry on brain magnetic resonance (MR) images using multilevel-features-based classification method. Method: The multilevel region of interest (ROI) features consist of two types of features: (i) ROI features, which include gray matter volume, white matter volume, cerebrospinal fluid volume, cortical thickness, and cortical surface area, and (ii) similarity features, which are based on similarity calculation of cortical thickness between ROIs. For each feature type, a hybrid feature selection method, comprising of filter-based and wrapper-based algorithms, is used to select the most discriminating features. ROI features and similarity features are integrated by using multi-kernel support vector machines (SVMs) with appropriate weighting factor. Results: The classification performance is improved by using multilevel ROI features with an accuracy of 96.66%, a specificity of 96.62%, and a sensitivity of 95.67%. The most discriminating ROI features that are related to self-esteem spread over occipital lobe, frontal lobe, parietal lobe, limbic lobe, temporal lobe, and central region, mainly involving white matter and cortical thickness. The most discriminating similarity features are distributed in both the right and left hemisphere, including frontal lobe, occipital lobe, limbic lobe, parietal lobe, and central region, which conveys information of structural connections between different brain regions. Conclusion: By using ROI features and similarity features to exam self-esteem related brain morphometry, this paper provides a pilot evidence that self-esteem is linked to specific ROIs and structural connections between different brain regions.

Juniper wood structure under the microscope.

PubMed

Bogolitsyn, Konstantin G; Zubov, Ivan N; Gusakova, Maria A; Chukhchin, Dmitry G; Krasikova, Anna A

2015-05-01

The investigations confirm the physicochemical nature of the structure and self-assembly of wood substance and endorse its application in plant species. The characteristic morphological features, ultra-microstructure, and submolecular structure of coniferous wood matrix using junipers as the representative tree were investigated by scanning electron (SEM) and atomic-force microscopy (AFM). Novel results on the specific composition and cell wall structure features of the common juniper (Juniperus Communis L.) were obtained. These data confirm the possibility of considering the wood substance as a nanobiocomposite. The cellulose nanofibrils (20-50 nm) and globular-shaped lignin-carbohydrate structures (diameter of 5-60 nm) form the base of such a nanobiocomposite.

Multi-Contrast Multi-Atlas Parcellation of Diffusion Tensor Imaging of the Human Brain

PubMed Central

Tang, Xiaoying; Yoshida, Shoko; Hsu, John; Huisman, Thierry A. G. M.; Faria, Andreia V.; Oishi, Kenichi; Kutten, Kwame; Poretti, Andrea; Li, Yue; Miller, Michael I.; Mori, Susumu

2014-01-01

In this paper, we propose a novel method for parcellating the human brain into 193 anatomical structures based on diffusion tensor images (DTIs). This was accomplished in the setting of multi-contrast diffeomorphic likelihood fusion using multiple DTI atlases. DTI images are modeled as high dimensional fields, with each voxel exhibiting a vector valued feature comprising of mean diffusivity (MD), fractional anisotropy (FA), and fiber angle. For each structure, the probability distribution of each element in the feature vector is modeled as a mixture of Gaussians, the parameters of which are estimated from the labeled atlases. The structure-specific feature vector is then used to parcellate the test image. For each atlas, a likelihood is iteratively computed based on the structure-specific vector feature. The likelihoods from multiple atlases are then fused. The updating and fusing of the likelihoods is achieved based on the expectation-maximization (EM) algorithm for maximum a posteriori (MAP) estimation problems. We first demonstrate the performance of the algorithm by examining the parcellation accuracy of 18 structures from 25 subjects with a varying degree of structural abnormality. Dice values ranging 0.8–0.9 were obtained. In addition, strong correlation was found between the volume size of the automated and the manual parcellation. Then, we present scan-rescan reproducibility based on another dataset of 16 DTI images – an average of 3.73%, 1.91%, and 1.79% for volume, mean FA, and mean MD respectively. Finally, the range of anatomical variability in the normal population was quantified for each structure. PMID:24809486

[A family of short retroposons (Squaml) from squamate reptiles (Reptilia: Squamata): structure, evolution and correlation with phylogeny].

PubMed

Kosushkin, S A; Borodulina, O R; Solov'eva, E N; Grechko, V V

2008-01-01

We have isolated and characterised sequences of a SINE family specific for squamate reptiles from a genome of lacertid lizard that we called Squam1. Copies are 360-390 bp in length and share a significant similarity with tRNA gene sequence on its 5'-end. This family was also detected by us in DNA of representatives of varanids, iguanids (anolis), gekkonids, and snakes. No signs of it were found in DNA of mammals, birds, amphibians, and crocodiles. Detailed analysis of primary structure of the retroposons obtained by us from genomic libraries or GenBank sequences was carried out. Most taxa possess 2-3 subfamilies of the SINE in their genomes with specific diagnostic features in their primary structure. Individual variability of copies in different families is about 85% and is just slightly lower on the genera level. Comparison of consensus sequences on family level reveals a high degree of structural similarity with a number of specific apomorphic features which makes it a useful marker of phylogeny for this group of reptiles. Snakes do not show specific affinity to varanids when compared to other lizards, as it was suggested earlier.

Structural and phylogenetic analysis of Rhodobacter capsulatus NifF: uncovering general features of nitrogen-fixation (nif)-flavodoxins.

PubMed

Pérez-Dorado, Inmaculada; Bortolotti, Ana; Cortez, Néstor; Hermoso, Juan A

2013-01-09

Analysis of the crystal structure of NifF from Rhodobacter capsulatus and its homologues reported so far reflects the existence of unique structural features in nif flavodoxins: a leucine at the re face of the isoalloxazine, an eight-residue insertion at the C-terminus of the 50's loop and a remarkable difference in the electrostatic potential surface with respect to non-nif flavodoxins. A phylogenetic study on 64 sequences from 52 bacterial species revealed four clusters, including different functional prototypes, correlating the previously defined as "short-chain" with the firmicutes flavodoxins and the "long-chain" with gram-negative species. The comparison of Rhodobacter NifF structure with other bacterial flavodoxin prototypes discloses the concurrence of specific features of these functional electron donors to nitrogenase.

Extracting physicochemical features to predict protein secondary structure.

PubMed

Huang, Yin-Fu; Chen, Shu-Ying

2013-01-01

We propose a protein secondary structure prediction method based on position-specific scoring matrix (PSSM) profiles and four physicochemical features including conformation parameters, net charges, hydrophobic, and side chain mass. First, the SVM with the optimal window size and the optimal parameters of the kernel function is found. Then, we train the SVM using the PSSM profiles generated from PSI-BLAST and the physicochemical features extracted from the CB513 data set. Finally, we use the filter to refine the predicted results from the trained SVM. For all the performance measures of our method, Q 3 reaches 79.52, SOV94 reaches 86.10, and SOV99 reaches 74.60; all the measures are higher than those of the SVMpsi method and the SVMfreq method. This validates that considering these physicochemical features in predicting protein secondary structure would exhibit better performances.

Extracting Physicochemical Features to Predict Protein Secondary Structure

PubMed Central

Chen, Shu-Ying

2013-01-01

We propose a protein secondary structure prediction method based on position-specific scoring matrix (PSSM) profiles and four physicochemical features including conformation parameters, net charges, hydrophobic, and side chain mass. First, the SVM with the optimal window size and the optimal parameters of the kernel function is found. Then, we train the SVM using the PSSM profiles generated from PSI-BLAST and the physicochemical features extracted from the CB513 data set. Finally, we use the filter to refine the predicted results from the trained SVM. For all the performance measures of our method, Q 3 reaches 79.52, SOV94 reaches 86.10, and SOV99 reaches 74.60; all the measures are higher than those of the SVMpsi method and the SVMfreq method. This validates that considering these physicochemical features in predicting protein secondary structure would exhibit better performances. PMID:23766688

Seeking instructional specificity: An example from analogical instruction

NASA Astrophysics Data System (ADS)

Kuo, Eric; Wieman, Carl E.

2015-12-01

Broad instructional methods like "interactive engagement" have been shown to be effective, but such general characterization provides little guidance on the details of how to structure instructional materials. In this study, we seek instructional specificity by comparing two ways of using an analogy to learn a target physical principle: (i) applying the analogy to the target physical domain on a case-by-case basis and (ii) using the analogy to create a general rule in the target physical domain. In the discussion sections of a large, introductory physics course (N =2 3 1 ), students who sought a general rule were better able to discover and apply a correct physics principle than students who analyzed the examples case by case. The difference persisted at a reduced level after subsequent direct instruction. We argue that students who performed case-by-case analyses were more likely to focus on idiosyncratic problem-specific features rather than the deep structural features. This study provides an example of investigations into how the specific structure of instructional materials can be consequential for what is learned.

Quantifying site-specific physical heterogeneity within an estuarine seascape

USGS Publications Warehouse

Kennedy, Cristina G.; Mather, Martha E.; Smith, Joseph M.

2017-01-01

Quantifying physical heterogeneity is essential for meaningful ecological research and effective resource management. Spatial patterns of multiple, co-occurring physical features are rarely quantified across a seascape because of methodological challenges. Here, we identified approaches that measured total site-specific heterogeneity, an often overlooked aspect of estuarine ecosystems. Specifically, we examined 23 metrics that quantified four types of common physical features: (1) river and creek confluences, (2) bathymetric variation including underwater drop-offs, (3) land features such as islands/sandbars, and (4) major underwater channel networks. Our research at 40 sites throughout Plum Island Estuary (PIE) provided solutions to two problems. The first problem was that individual metrics that measured heterogeneity of a single physical feature showed different regional patterns. We solved this first problem by combining multiple metrics for a single feature using a within-physical feature cluster analysis. With this approach, we identified sites with four different types of confluences and three different types of underwater drop-offs. The second problem was that when multiple physical features co-occurred, new patterns of total site-specific heterogeneity were created across the seascape. This pattern of total heterogeneity has potential ecological relevance to structure-oriented predators. To address this second problem, we identified sites with similar types of total physical heterogeneity using an across-physical feature cluster analysis. Then, we calculated an additive heterogeneity index, which integrated all physical features at a site. Finally, we tested if site-specific additive heterogeneity index values differed for across-physical feature clusters. In PIE, the sites with the highest additive heterogeneity index values were clustered together and corresponded to sites where a fish predator, adult striped bass (Morone saxatilis), aggregated in a related acoustic tracking study. In summary, we have shown general approaches to quantifying site-specific heterogeneity.

Structural Feature Ions for Distinguishing N- and O-Linked Glycan Isomers by LC-ESI-IT MS/MS

NASA Astrophysics Data System (ADS)

Everest-Dass, Arun V.; Abrahams, Jodie L.; Kolarich, Daniel; Packer, Nicolle H.; Campbell, Matthew P.

2013-06-01

Glycomics is the comprehensive study of glycan expression in an organism, cell, or tissue that relies on effective analytical technologies to understand glycan structure-function relationships. Owing to the macro- and micro-heterogeneity of oligosaccharides, detailed structure characterization has required an orthogonal approach, such as a combination of specific exoglycosidase digestions, LC-MS/MS, and the development of bioinformatic resources to comprehensively profile a complex biological sample. Liquid chromatography-electrospray ionization-mass spectrometry (LC-ESI-MS/MS) has emerged as a key tool in the structural analysis of oligosaccharides because of its high sensitivity, resolution, and robustness. Here, we present a strategy that uses LC-ESI-MS/MS to characterize over 200 N- and O-glycans from human saliva glycoproteins, complemented by sequential exoglycosidase treatment, to further verify the annotated glycan structures. Fragment-specific substructure diagnostic ions were collated from an extensive screen of the literature available on the detailed structural characterization of oligosaccharides and, together with other specific glycan structure feature ions derived from cross-ring and glycosidic-linkage fragmentation, were used to characterize the glycans and differentiate isomers. The availability of such annotated mass spectrometric fragmentation spectral libraries of glycan structures, together with such substructure diagnostic ions, will be key inputs for the future development of the automated elucidation of oligosaccharide structures from MS/MS data.

Event-related potentials to structural familiar face incongruity processing.

PubMed

Jemel, B; George, N; Olivares, E; Fiori, N; Renault, B

1999-07-01

Thirty scalp sites were used to investigate the specific topography of the event-related potentials (ERPs) related to face associative priming when masked eyes of familiar faces were completed with either the proper features or incongruent ones. The enhanced negativity of N210 and N350, due to structural incongruity of faces, have a "category specific" inferotemporal localization on the scalp. Additional analyses support the existence of multiple ERP features within the temporal interval typically associated with N400 (N350 and N380), involving occipitotemporal and centroparietal areas. Seven reliable dipole locations have been evidenced using the brain electrical source analysis algorithm. Some of these localizations (fusiform, parahippocampal) are already known to be involved in face recognition, the other ones being related to general cognitive processes related to the task's demand. Because of their specific topography, the observed effects suggest that the face structural congruency process might involve early specialized neocortical areas in parallel with cortical memory circuits in the integration of perceptual and cognitive face processing.

2.4 Å resolution crystal structure of human TRAP1NM, the Hsp90 paralog in the mitochondrial matrix.

PubMed

Sung, Nuri; Lee, Jungsoon; Kim, Ji Hyun; Chang, Changsoo; Tsai, Francis T F; Lee, Sukyeong

2016-08-01

TRAP1 is an organelle-specific Hsp90 paralog that is essential for neoplastic growth. As a member of the Hsp90 family, TRAP1 is presumed to be a general chaperone facilitating the late-stage folding of Hsp90 client proteins in the mitochondrial matrix. Interestingly, TRAP1 cannot replace cytosolic Hsp90 in protein folding, and none of the known Hsp90 co-chaperones are found in mitochondria. Thus, the three-dimensional structure of TRAP1 must feature regulatory elements that are essential to the ATPase activity and chaperone function of TRAP1. Here, the crystal structure of a human TRAP1NM dimer is presented, featuring an intact N-domain and M-domain structure, bound to adenosine 5'-β,γ-imidotriphosphate (ADPNP). The crystal structure together with epitope-mapping results shows that the TRAP1 M-domain loop 1 contacts the neighboring subunit and forms a previously unobserved third dimer interface that mediates the specific interaction with mitochondrial Hsp70.

PSSP-RFE: accurate prediction of protein structural class by recursive feature extraction from PSI-BLAST profile, physical-chemical property and functional annotations.

PubMed

Li, Liqi; Cui, Xiang; Yu, Sanjiu; Zhang, Yuan; Luo, Zhong; Yang, Hua; Zhou, Yue; Zheng, Xiaoqi

2014-01-01

Protein structure prediction is critical to functional annotation of the massively accumulated biological sequences, which prompts an imperative need for the development of high-throughput technologies. As a first and key step in protein structure prediction, protein structural class prediction becomes an increasingly challenging task. Amongst most homological-based approaches, the accuracies of protein structural class prediction are sufficiently high for high similarity datasets, but still far from being satisfactory for low similarity datasets, i.e., below 40% in pairwise sequence similarity. Therefore, we present a novel method for accurate and reliable protein structural class prediction for both high and low similarity datasets. This method is based on Support Vector Machine (SVM) in conjunction with integrated features from position-specific score matrix (PSSM), PROFEAT and Gene Ontology (GO). A feature selection approach, SVM-RFE, is also used to rank the integrated feature vectors through recursively removing the feature with the lowest ranking score. The definitive top features selected by SVM-RFE are input into the SVM engines to predict the structural class of a query protein. To validate our method, jackknife tests were applied to seven widely used benchmark datasets, reaching overall accuracies between 84.61% and 99.79%, which are significantly higher than those achieved by state-of-the-art tools. These results suggest that our method could serve as an accurate and cost-effective alternative to existing methods in protein structural classification, especially for low similarity datasets.

Multiple conformations of the cytidine repressor DNA-binding domain coalesce to one upon recognition of a specific DNA surface.

PubMed

Moody, Colleen L; Tretyachenko-Ladokhina, Vira; Laue, Thomas M; Senear, Donald F; Cocco, Melanie J

2011-08-09

The cytidine repressor (CytR) is a member of the LacR family of bacterial repressors with distinct functional features. The Escherichia coli CytR regulon comprises nine operons whose palindromic operators vary in both sequence and, most significantly, spacing between the recognition half-sites. This suggests a strong likelihood that protein folding would be coupled to DNA binding as a mechanism to accommodate the variety of different operator architectures to which CytR is targeted. Such coupling is a common feature of sequence-specific DNA-binding proteins, including the LacR family repressors; however, there are no significant structural rearrangements upon DNA binding within the three-helix DNA-binding domains (DBDs) studied to date. We used nuclear magnetic resonance (NMR) spectroscopy to characterize the CytR DBD free in solution and to determine the high-resolution structure of a CytR DBD monomer bound specifically to one DNA half-site of the uridine phosphorylase (udp) operator. We find that the free DBD populates multiple distinct conformations distinguished by up to four sets of NMR peaks per residue. This structural heterogeneity is previously unknown in the LacR family. These stable structures coalesce into a single, more stable udp-bound form that features a three-helix bundle containing a canonical helix-turn-helix motif. However, this structure differs from all other LacR family members whose structures are known with regard to the packing of the helices and consequently their relative orientations. Aspects of CytR activity are unique among repressors; we identify here structural properties that are also distinct and that might underlie the different functional properties. © 2011 American Chemical Society

Morphometry Based on Effective and Accurate Correspondences of Localized Patterns (MEACOLP)

PubMed Central

Wang, Hu; Ren, Yanshuang; Bai, Lijun; Zhang, Wensheng; Tian, Jie

2012-01-01

Local features in volumetric images have been used to identify correspondences of localized anatomical structures for brain morphometry. However, the correspondences are often sparse thus ineffective in reflecting the underlying structures, making it unreliable to evaluate specific morphological differences. This paper presents a morphometry method (MEACOLP) based on correspondences with improved effectiveness and accuracy. A novel two-level scale-invariant feature transform is used to enhance the detection repeatability of local features and to recall the correspondences that might be missed in previous studies. Template patterns whose correspondences could be commonly identified in each group are constructed to serve as the basis for morphometric analysis. A matching algorithm is developed to reduce the identification errors by comparing neighboring local features and rejecting unreliable matches. The two-sample t-test is finally adopted to analyze specific properties of the template patterns. Experiments are performed on the public OASIS database to clinically analyze brain images of Alzheimer's disease (AD) and normal controls (NC). MEACOLP automatically identifies known morphological differences between AD and NC brains, and characterizes the differences well as the scaling and translation of underlying structures. Most of the significant differences are identified in only a single hemisphere, indicating that AD-related structures are characterized by strong anatomical asymmetry. In addition, classification trials to differentiate AD subjects from NC confirm that the morphological differences are reliably related to the groups of interest. PMID:22540000

Using a Word Association Test for the Assessment of High School Students' Cognitive Structures on Dissolution

ERIC Educational Resources Information Center

Derman, Aysegul; Eilks, Ingo

2016-01-01

Understanding students' cognitive structures in a specific knowledge domain helps to determine the ''what, how and why'' features of such knowledge, so that we can take these structures into consideration in teaching. The purpose of the present study was to identify students' cognitive structures about solution and dissolution concepts. The study…

Structural health monitoring feature design by genetic programming

NASA Astrophysics Data System (ADS)

Harvey, Dustin Y.; Todd, Michael D.

2014-09-01

Structural health monitoring (SHM) systems provide real-time damage and performance information for civil, aerospace, and other high-capital or life-safety critical structures. Conventional data processing involves pre-processing and extraction of low-dimensional features from in situ time series measurements. The features are then input to a statistical pattern recognition algorithm to perform the relevant classification or regression task necessary to facilitate decisions by the SHM system. Traditional design of signal processing and feature extraction algorithms can be an expensive and time-consuming process requiring extensive system knowledge and domain expertise. Genetic programming, a heuristic program search method from evolutionary computation, was recently adapted by the authors to perform automated, data-driven design of signal processing and feature extraction algorithms for statistical pattern recognition applications. The proposed method, called Autofead, is particularly suitable to handle the challenges inherent in algorithm design for SHM problems where the manifestation of damage in structural response measurements is often unclear or unknown. Autofead mines a training database of response measurements to discover information-rich features specific to the problem at hand. This study provides experimental validation on three SHM applications including ultrasonic damage detection, bearing damage classification for rotating machinery, and vibration-based structural health monitoring. Performance comparisons with common feature choices for each problem area are provided demonstrating the versatility of Autofead to produce significant algorithm improvements on a wide range of problems.

Principles for Predicting RNA Secondary Structure Design Difficulty.

PubMed

Anderson-Lee, Jeff; Fisker, Eli; Kosaraju, Vineet; Wu, Michelle; Kong, Justin; Lee, Jeehyung; Lee, Minjae; Zada, Mathew; Treuille, Adrien; Das, Rhiju

2016-02-27

Designing RNAs that form specific secondary structures is enabling better understanding and control of living systems through RNA-guided silencing, genome editing and protein organization. Little is known, however, about which RNA secondary structures might be tractable for downstream sequence design, increasing the time and expense of design efforts due to inefficient secondary structure choices. Here, we present insights into specific structural features that increase the difficulty of finding sequences that fold into a target RNA secondary structure, summarizing the design efforts of tens of thousands of human participants and three automated algorithms (RNAInverse, INFO-RNA and RNA-SSD) in the Eterna massive open laboratory. Subsequent tests through three independent RNA design algorithms (NUPACK, DSS-Opt and MODENA) confirmed the hypothesized importance of several features in determining design difficulty, including sequence length, mean stem length, symmetry and specific difficult-to-design motifs such as zigzags. Based on these results, we have compiled an Eterna100 benchmark of 100 secondary structure design challenges that span a large range in design difficulty to help test future efforts. Our in silico results suggest new routes for improving computational RNA design methods and for extending these insights to assess "designability" of single RNA structures, as well as of switches for in vitro and in vivo applications. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

In vivo, label-free, three-dimensional quantitative imaging of liver surface using multi-photon microscopy

NASA Astrophysics Data System (ADS)

Zhuo, Shuangmu; Yan, Jie; Kang, Yuzhan; Xu, Shuoyu; Peng, Qiwen; So, Peter T. C.; Yu, Hanry

2014-07-01

Various structural features on the liver surface reflect functional changes in the liver. The visualization of these surface features with molecular specificity is of particular relevance to understanding the physiology and diseases of the liver. Using multi-photon microscopy (MPM), we have developed a label-free, three-dimensional quantitative and sensitive method to visualize various structural features of liver surface in living rat. MPM could quantitatively image the microstructural features of liver surface with respect to the sinuosity of collagen fiber, the elastic fiber structure, the ratio between elastin and collagen, collagen content, and the metabolic state of the hepatocytes that are correlative with the pathophysiologically induced changes in the regions of interest. This study highlights the potential of this technique as a useful tool for pathophysiological studies and possible diagnosis of the liver diseases with further development.

In vivo, label-free, three-dimensional quantitative imaging of liver surface using multi-photon microscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhuo, Shuangmu, E-mail: shuangmuzhuo@gmail.com, E-mail: hanry-yu@nuhs.edu.sg; Institute of Laser and Optoelectronics Technology, Fujian Normal University, Fuzhou 350007; Yan, Jie

2014-07-14

Various structural features on the liver surface reflect functional changes in the liver. The visualization of these surface features with molecular specificity is of particular relevance to understanding the physiology and diseases of the liver. Using multi-photon microscopy (MPM), we have developed a label-free, three-dimensional quantitative and sensitive method to visualize various structural features of liver surface in living rat. MPM could quantitatively image the microstructural features of liver surface with respect to the sinuosity of collagen fiber, the elastic fiber structure, the ratio between elastin and collagen, collagen content, and the metabolic state of the hepatocytes that are correlativemore » with the pathophysiologically induced changes in the regions of interest. This study highlights the potential of this technique as a useful tool for pathophysiological studies and possible diagnosis of the liver diseases with further development.« less

iFeature: a python package and web server for features extraction and selection from protein and peptide sequences.

PubMed

Chen, Zhen; Zhao, Pei; Li, Fuyi; Leier, André; Marquez-Lago, Tatiana T; Wang, Yanan; Webb, Geoffrey I; Smith, A Ian; Daly, Roger J; Chou, Kuo-Chen; Song, Jiangning

2018-03-08

Structural and physiochemical descriptors extracted from sequence data have been widely used to represent sequences and predict structural, functional, expression and interaction profiles of proteins and peptides as well as DNAs/RNAs. Here, we present iFeature, a versatile Python-based toolkit for generating various numerical feature representation schemes for both protein and peptide sequences. iFeature is capable of calculating and extracting a comprehensive spectrum of 18 major sequence encoding schemes that encompass 53 different types of feature descriptors. It also allows users to extract specific amino acid properties from the AAindex database. Furthermore, iFeature integrates 12 different types of commonly used feature clustering, selection, and dimensionality reduction algorithms, greatly facilitating training, analysis, and benchmarking of machine-learning models. The functionality of iFeature is made freely available via an online web server and a stand-alone toolkit. http://iFeature.erc.monash.edu/; https://github.com/Superzchen/iFeature/. jiangning.song@monash.edu; kcchou@gordonlifescience.org; roger.daly@monash.edu. Supplementary data are available at Bioinformatics online.

An ensemble-of-classifiers based approach for early diagnosis of Alzheimer's disease: classification using structural features of brain images.

PubMed

Farhan, Saima; Fahiem, Muhammad Abuzar; Tauseef, Huma

2014-01-01

Structural brain imaging is playing a vital role in identification of changes that occur in brain associated with Alzheimer's disease. This paper proposes an automated image processing based approach for the identification of AD from MRI of the brain. The proposed approach is novel in a sense that it has higher specificity/accuracy values despite the use of smaller feature set as compared to existing approaches. Moreover, the proposed approach is capable of identifying AD patients in early stages. The dataset selected consists of 85 age and gender matched individuals from OASIS database. The features selected are volume of GM, WM, and CSF and size of hippocampus. Three different classification models (SVM, MLP, and J48) are used for identification of patients and controls. In addition, an ensemble of classifiers, based on majority voting, is adopted to overcome the error caused by an independent base classifier. Ten-fold cross validation strategy is applied for the evaluation of our scheme. Moreover, to evaluate the performance of proposed approach, individual features and combination of features are fed to individual classifiers and ensemble based classifier. Using size of left hippocampus as feature, the accuracy achieved with ensemble of classifiers is 93.75%, with 100% specificity and 87.5% sensitivity.

Building theory-based concepts: four-year-olds preferentially seek explanations for features of kinds.

PubMed

Cimpian, Andrei; Petro, Gina

2014-05-01

Is the structure of human concepts continuous across development, or does it undergo qualitative transformations? Extensive evidence with adults has demonstrated that they are motivated to understand why categories have the features they do. To investigate whether young children display a similar motivation-an issue that bears on the question of continuity vs. transformation in conceptual structure-we conducted three studies involving 4-year-olds (N=90) and adults (N=124). Experiments 1 and 2 suggested that 4-year-olds indeed display a strong motivation to explain why categories have the features they do. Specifically, when provided with the option of asking "why?" about features of novel categories vs. features of individuals from other novel categories, children preferred to ask "why?" about the category features. Moreover, children's explanatory preference was specific to facts about categories per se and did not extend to facts that were merely presented in the context of multiple category instances. Experiment 3 also ruled out the possibility that the category facts were preferred because these facts were more surprising. In sum, these three studies reveal an early-emerging motivation to make sense of the categories encountered in the world and, more generally, speak to the richness of children's conceptual representations. Copyright © 2014 Elsevier B.V. All rights reserved.

Arguing in L2: Discourse Structure and Textual Metadiscourse in Philippine Newspaper Editorials

ERIC Educational Resources Information Center

Tarrayo, Veronico N.; Duque, Marie Claire T.

2011-01-01

This study described the discourse structure and textual metadiscourse in newspaper editorials in the Philippines where English is used as a second language or L2. Specifically, it sought answers to the following questions: (1) What discourse features characterize the structure of the following parts of Philippine newspaper editorials--orientation…

New data concerning the age and specific features of magmatism of timanides in the southern part of the Lyapin structure (Northern Urals)

NASA Astrophysics Data System (ADS)

Petrov, G. A.; Ronkin, Yu. L.; Gerdes, A.; Maslov, A. V.

2017-10-01

New data on composition and age of Precambrian granites and volcanic rocks in the southern part of the Lyapin structure (Northern Urals) are considered. The geochemical features of the igneous rocks are similar to those of the rocks formed in both divergent and convergent environments. In the Late Precambrian (583-553 Ma), the investigated area is assumed to have been a part of the active margin above the mantle plume.

The PCP SYS IV Management System: Educational Overview.

ERIC Educational Resources Information Center

Siegel, Martin A.; Davis, Dennis M.

This paper describes the structure and function of the SYS IV PLATO Curriculum Project's (PCP) computer-based management system and justifies the system design. A consideration of features most critical in the design of management systems provides the context for a discussion of specific SYS IV features, which include its ability to deliver any…

Prediction of Protein-Protein Interaction Sites by Random Forest Algorithm with mRMR and IFS

PubMed Central

Li, Bi-Qing; Feng, Kai-Yan; Chen, Lei; Huang, Tao; Cai, Yu-Dong

2012-01-01

Prediction of protein-protein interaction (PPI) sites is one of the most challenging problems in computational biology. Although great progress has been made by employing various machine learning approaches with numerous characteristic features, the problem is still far from being solved. In this study, we developed a novel predictor based on Random Forest (RF) algorithm with the Minimum Redundancy Maximal Relevance (mRMR) method followed by incremental feature selection (IFS). We incorporated features of physicochemical/biochemical properties, sequence conservation, residual disorder, secondary structure and solvent accessibility. We also included five 3D structural features to predict protein-protein interaction sites and achieved an overall accuracy of 0.672997 and MCC of 0.347977. Feature analysis showed that 3D structural features such as Depth Index (DPX) and surface curvature (SC) contributed most to the prediction of protein-protein interaction sites. It was also shown via site-specific feature analysis that the features of individual residues from PPI sites contribute most to the determination of protein-protein interaction sites. It is anticipated that our prediction method will become a useful tool for identifying PPI sites, and that the feature analysis described in this paper will provide useful insights into the mechanisms of interaction. PMID:22937126

Conceptual Structure within and between Modalities

PubMed Central

Dilkina, Katia; Lambon Ralph, Matthew A.

2012-01-01

Current views of semantic memory share the assumption that conceptual representations are based on multimodal experience, which activates distinct modality-specific brain regions. This proposition is widely accepted, yet little is known about how each modality contributes to conceptual knowledge and how the structure of this contribution varies across these multiple information sources. We used verbal feature lists, features from drawings, and verbal co-occurrence statistics from latent semantic analysis to examine the informational structure in four domains of knowledge: perceptual, functional, encyclopedic, and verbal. The goals of the analysis were three-fold: (1) to assess the structure within individual modalities; (2) to compare structures between modalities; and (3) to assess the degree to which concepts organize categorically or randomly. Our results indicated significant and unique structure in all four modalities: perceptually, concepts organize based on prominent features such as shape, size, color, and parts; functionally, they group based on use and interaction; encyclopedically, they arrange based on commonality in location or behavior; and verbally, they group associatively or relationally. Visual/perceptual knowledge gives rise to the strongest hierarchical organization and is closest to classic taxonomic structure. Information is organized somewhat similarly in the perceptual and encyclopedic domains, which differs significantly from the structure in the functional and verbal domains. Notably, the verbal modality has the most unique organization, which is not at all categorical but also not random. The idiosyncrasy and complexity of conceptual structure across modalities raise the question of how all of these modality-specific experiences are fused together into coherent, multifaceted yet unified concepts. Accordingly, both methodological and theoretical implications of the present findings are discussed. PMID:23293593

Proteins without unique 3D structures: biotechnological applications of intrinsically unstable/disordered proteins.

PubMed

Uversky, Vladimir N

2015-03-01

Intrinsically disordered proteins (IDPs) and intrinsically disordered protein regions (IDPRs) are functional proteins or regions that do not have unique 3D structures under functional conditions. Therefore, from the viewpoint of their lack of stable 3D structure, IDPs/IDPRs are inherently unstable. As much as structure and function of normal ordered globular proteins are determined by their amino acid sequences, the lack of unique 3D structure in IDPs/IDPRs and their disorder-based functionality are also encoded in the amino acid sequences. Because of their specific sequence features and distinctive conformational behavior, these intrinsically unstable proteins or regions have several applications in biotechnology. This review introduces some of the most characteristic features of IDPs/IDPRs (such as peculiarities of amino acid sequences of these proteins and regions, their major structural features, and peculiar responses to changes in their environment) and describes how these features can be used in the biotechnology, for example for the proteome-wide analysis of the abundance of extended IDPs, for recombinant protein isolation and purification, as polypeptide nanoparticles for drug delivery, as solubilization tools, and as thermally sensitive carriers of active peptides and proteins. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The relationship between manuscript title structure and success: editorial decisions and citation performance for an ecological journal

PubMed Central

Fox, Charles W; Burns, C Sean

2015-01-01

A poorly chosen article title may make a paper difficult to discover or discourage readership when discovered, reducing an article's impact. Yet, it is unclear how the structure of a manuscript's title influences readership and impact. We used manuscript tracking data for all manuscripts submitted to the journal Functional Ecology from 2004 to 2013 and citation data for papers published in this journal from 1987 to 2011 to examine how title features changed and whether a manuscript's title structure was predictive of success during the manuscript review process and/or impact (citation) after publication. Titles of manuscripts submitted to Functional Ecology became marginally longer (after controlling for other variables), broader in focus (less frequent inclusion of genus and species names), and included more humor and subtitles over the period of the study. Papers with subtitles were less likely to be rejected by editors both pre- and post-peer review, although both effects were small and the presence of subtitles in published papers was not predictive of citations. Papers with specific names of study organisms in their titles fared poorly during editorial (but not peer) review and, if published, were less well cited than papers whose titles did not include specific names. Papers with intermediate length titles were more successful during editorial review, although the effect was small and title word count was not predictive of citations. No features of titles were predictive of reviewer willingness to review papers or the length of time a paper was in peer review. We conclude that titles have changed in structure over time, but features of title structure have only small or no relationship with success during editorial review and post-publication impact. The title feature that was most predictive of manuscript success: papers whose titles emphasize broader conceptual or comparative issues fare better both pre- and post-publication than do papers with organism-specific titles. PMID:26045949

The relationship between manuscript title structure and success: editorial decisions and citation performance for an ecological journal.

PubMed

Fox, Charles W; Burns, C Sean

2015-05-01

A poorly chosen article title may make a paper difficult to discover or discourage readership when discovered, reducing an article's impact. Yet, it is unclear how the structure of a manuscript's title influences readership and impact. We used manuscript tracking data for all manuscripts submitted to the journal Functional Ecology from 2004 to 2013 and citation data for papers published in this journal from 1987 to 2011 to examine how title features changed and whether a manuscript's title structure was predictive of success during the manuscript review process and/or impact (citation) after publication. Titles of manuscripts submitted to Functional Ecology became marginally longer (after controlling for other variables), broader in focus (less frequent inclusion of genus and species names), and included more humor and subtitles over the period of the study. Papers with subtitles were less likely to be rejected by editors both pre- and post-peer review, although both effects were small and the presence of subtitles in published papers was not predictive of citations. Papers with specific names of study organisms in their titles fared poorly during editorial (but not peer) review and, if published, were less well cited than papers whose titles did not include specific names. Papers with intermediate length titles were more successful during editorial review, although the effect was small and title word count was not predictive of citations. No features of titles were predictive of reviewer willingness to review papers or the length of time a paper was in peer review. We conclude that titles have changed in structure over time, but features of title structure have only small or no relationship with success during editorial review and post-publication impact. The title feature that was most predictive of manuscript success: papers whose titles emphasize broader conceptual or comparative issues fare better both pre- and post-publication than do papers with organism-specific titles.

A Feature-Based Approach to Modeling Protein–DNA Interactions

PubMed Central

Segal, Eran

2008-01-01

Transcription factor (TF) binding to its DNA target site is a fundamental regulatory interaction. The most common model used to represent TF binding specificities is a position specific scoring matrix (PSSM), which assumes independence between binding positions. However, in many cases, this simplifying assumption does not hold. Here, we present feature motif models (FMMs), a novel probabilistic method for modeling TF–DNA interactions, based on log-linear models. Our approach uses sequence features to represent TF binding specificities, where each feature may span multiple positions. We develop the mathematical formulation of our model and devise an algorithm for learning its structural features from binding site data. We also developed a discriminative motif finder, which discovers de novo FMMs that are enriched in target sets of sequences compared to background sets. We evaluate our approach on synthetic data and on the widely used TF chromatin immunoprecipitation (ChIP) dataset of Harbison et al. We then apply our algorithm to high-throughput TF ChIP data from mouse and human, reveal sequence features that are present in the binding specificities of mouse and human TFs, and show that FMMs explain TF binding significantly better than PSSMs. Our FMM learning and motif finder software are available at http://genie.weizmann.ac.il/. PMID:18725950

Spatial Data Transfer Standard (SDTS)

USGS Publications Warehouse

,

1995-01-01

The Spatial Data Transfer Standard (SOTS) is a mechanism for the transfer of spatial data between dissimilar computer systems. The SOTS specifies exchange constructs, addressing formats, structure, and content for spatially referenced vector and raster (including gridded) data. SOTS components are a conceptual model, specifications for a quality report, transfer module specifications, data dictionary specifications, and definitions of spatial features and attributes.

Algorithm-Dependent Generalization Bounds for Multi-Task Learning.

PubMed

Liu, Tongliang; Tao, Dacheng; Song, Mingli; Maybank, Stephen J

2017-02-01

Often, tasks are collected for multi-task learning (MTL) because they share similar feature structures. Based on this observation, in this paper, we present novel algorithm-dependent generalization bounds for MTL by exploiting the notion of algorithmic stability. We focus on the performance of one particular task and the average performance over multiple tasks by analyzing the generalization ability of a common parameter that is shared in MTL. When focusing on one particular task, with the help of a mild assumption on the feature structures, we interpret the function of the other tasks as a regularizer that produces a specific inductive bias. The algorithm for learning the common parameter, as well as the predictor, is thereby uniformly stable with respect to the domain of the particular task and has a generalization bound with a fast convergence rate of order O(1/n), where n is the sample size of the particular task. When focusing on the average performance over multiple tasks, we prove that a similar inductive bias exists under certain conditions on the feature structures. Thus, the corresponding algorithm for learning the common parameter is also uniformly stable with respect to the domains of the multiple tasks, and its generalization bound is of the order O(1/T), where T is the number of tasks. These theoretical analyses naturally show that the similarity of feature structures in MTL will lead to specific regularizations for predicting, which enables the learning algorithms to generalize fast and correctly from a few examples.

The role of ferroelectric domain structure in second harmonic generation in random quadratic media.

PubMed

Roppo, Vito; Wang, W; Kalinowski, K; Kong, Y; Cojocaru, C; Trull, J; Vilaseca, R; Scalora, M; Krolikowski, W; Kivshar, Yu

2010-03-01

We study theoretically and numerically the second harmonic generation in a nonlinear crystal with random distribution of ferroelectric domains. We show that the specific features of disordered domain structure greatly affect the emission pattern of the generated harmonics. This phenomena can be used to characterize the degree of disorder in nonlinear photonic structures.

Python Environment for Bayesian Learning: Inferring the Structure of Bayesian Networks from Knowledge and Data

PubMed Central

Shah, Abhik; Woolf, Peter

2009-01-01

Summary In this paper, we introduce pebl, a Python library and application for learning Bayesian network structure from data and prior knowledge that provides features unmatched by alternative software packages: the ability to use interventional data, flexible specification of structural priors, modeling with hidden variables and exploitation of parallel processing. PMID:20161541

Fabrication of biomimetic resorption lacunae-like structure on titanium surface and its osteoblast responses

NASA Astrophysics Data System (ADS)

Huo, Fangjun; Guo, Weihua; Wu, Hao; Wang, Yueting; He, Gang; Xie, Li; Tian, Weidong

2018-04-01

Biomimetic specific surface structure could improve biological behaviors of specific cells and eventual tissue integration. Featuring titanium surface with structures resembling bone resorption lacunae (RL) can be a promising approach to improve the osteoblast responses and osseointegration of implants. As a most common used dental implant surface, sandblasting and acid etching (SLA) surface has micro-sized structures with dimensions similar to RL, but great differences exist when it comes to shape and contour. In this work, by anodizing titanium substrate in a novel HCOONa/CH3COONa electrolyte, RL-like crater structures were fabricated with highly similar size, shape and contour. Compared with SLA, it was much more similar to RL structure in shape and contour. Furthermore, through subsequent alkali-heat treatment, nano-sized structures that overlaid the whole surface were obtained, which further mimic undercuts features inside the RL. The as-prepared surface was consisted of crystalline titania and exhibited super-hydrophilicity with good stability. In vitro evaluation results showed that the surface could significantly improve adhesion, proliferation and differentiation of MG63 cells in comparison with SLA. This new method may be a promising candidate for biomimetic modification of titanium implant to promote osseointegration.

2.4 Å resolution crystal structure of human TRAP1 NM , the Hsp90 paralog in the mitochondrial matrix

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sung, Nuri; Lee, Jungsoon; Kim, Ji-Hyun

2016-07-13

TRAP1 is an organelle-specific Hsp90 paralog that is essential for neoplastic growth. As a member of the Hsp90 family, TRAP1 is presumed to be a general chaperone facilitating the late-stage folding of Hsp90 client proteins in the mitochondrial matrix. Interestingly, TRAP1 cannot replace cytosolic Hsp90 in protein folding, and none of the known Hsp90 co-chaperones are found in mitochondria. Thus, the three-dimensional structure of TRAP1 must feature regulatory elements that are essential to the ATPase activity and chaperone function of TRAP1. Here, the crystal structure of a human TRAP1 NMdimer is presented, featuring an intact N-domain and M-domain structure, boundmore » to adenosine 5'-β,γ-imidotriphosphate (ADPNP). The crystal structure together with epitope-mapping results shows that the TRAP1 M-domain loop 1 contacts the neighboring subunit and forms a previously unobserved third dimer interface that mediates the specific interaction with mitochondrial Hsp70.« less

Transition section for acoustic waveguides

DOEpatents

Karplus, H.H.B.

1975-10-28

A means of facilitating the transmission of acoustic waves with minimal reflection between two regions having different specific acoustic impedances is described comprising a region exhibiting a constant product of cross-sectional area and specific acoustic impedance at each cross-sectional plane along the axis of the transition region. A variety of structures that exhibit this feature is disclosed, the preferred embodiment comprising a nested structure of doubly reentrant cones. This structure is useful for monitoring the operation of nuclear reactors in which random acoustic signals are generated in the course of operation.

Model Analysis of Fine Structures of Student Models: An Example with Newton's Third Law.

ERIC Educational Resources Information Center

Bao, Lei; Hogg, Kirsten; Zollman, Dean

2002-01-01

Studies the role of context in students' uses of alternative conceptual models by using Newton's third law. Identifies four contextual features that are frequently used by students in their reasoning. Probes the effects of specific contextual features on student reasoning using a multiple-choice survey. (Contains 39 references.) (Author/YDS)

Communication: Anion-specific response of mesoscopic organization in ionic liquids upon pressurization

NASA Astrophysics Data System (ADS)

Lo Celso, Fabrizio; Triolo, Alessandro; Gontrani, Lorenzo; Russina, Olga

2018-06-01

One of the outstanding features of ionic liquids is their inherently hierarchical structural organization at mesoscopic spatial scales. Recently experimental and computational studies showed the fading of this feature when pressurising. Here we use simulations to show that this effect is not general: appropriate anion choice leads to an obstinate resistance against pressurization.

Specific features of a single-pulse sliding discharge in neon near the threshold for spark breakdown

NASA Astrophysics Data System (ADS)

Trusov, K. K.

2017-08-01

Experimental data on the spatial structure of a single-pulse sliding discharge in neon at voltages below, equal to, and above the threshold for spark breakdown are discussed. The experiments were carried at gas pressures of 30 and 100 kPa and different polarities of the discharge voltage. Photographs of the plasma structure in two discharge chambers with different dimensions of the discharge zone and different thicknesses of an alumina dielectric plate on the surface of which the discharge develops are inspected. Common features of the prebreakdown discharge and its specific features depending on the voltage polarity and gas pressure are analyzed. It is shown that, at voltages below the threshold for spark breakdown, a low-current glow discharge with cathode and anode spots develops in the electrode gap. Above the breakdown threshold, regardless of the voltage polarity, spark channels directed from the cathode to the anode develop against the background of a low-current discharge.

Graduating to Postdoc: Information-Sharing in Support of Organizational Structures and Needs

NASA Technical Reports Server (NTRS)

Keller, Richard M.; Lucas, Paul J.; Compton, Michael M.; Stewart, Helen J.; Baya, Vinod; DelAlto, Martha

1999-01-01

The deployment of information-sharing systems in large organizations can significantly impact existing policies and procedures with regard to authority and control over information. Unless information-sharing systems explicitly support organizational structures and needs, these systems will be rejected summarily. The Postdoc system is a deployed Web-based information-sharing system created specifically to address organizational needs. Postdoc contains various organizational support features including a shared, globally navigable document space, as well as specialized access control, distributed administration, and mailing list features built around the key notion of hierarchical group structures. We review successes and difficulties in supporting organizational needs with Postdoc

Automatic programming of arc welding robots

NASA Astrophysics Data System (ADS)

Padmanabhan, Srikanth

Automatic programming of arc welding robots requires the geometric description of a part from a solid modeling system, expert weld process knowledge and the kinematic arrangement of the robot and positioner automatically. Current commercial solid models are incapable of storing explicitly product and process definitions of weld features. This work presents a paradigm to develop a computer-aided engineering environment that supports complete weld feature information in a solid model and to create an automatic programming system for robotic arc welding. In the first part, welding features are treated as properties or attributes of an object, features which are portions of the object surface--the topological boundary. The structure for representing the features and attributes is a graph called the Welding Attribute Graph (WAGRAPH). The method associates appropriate weld features to geometric primitives, adds welding attributes, and checks the validity of welding specifications. A systematic structure is provided to incorporate welding attributes and coordinate system information in a CSG tree. The specific implementation of this structure using a hybrid solid modeler (IDEAS) and an object-oriented programming paradigm is described. The second part provides a comprehensive methodology to acquire and represent weld process knowledge required for the proper selection of welding schedules. A methodology of knowledge acquisition using statistical methods is proposed. It is shown that these procedures did little to capture the private knowledge of experts (heuristics), but helped in determining general dependencies, and trends. A need was established for building the knowledge-based system using handbook knowledge and to allow the experts further to build the system. A methodology to check the consistency and validity for such knowledge addition is proposed. A mapping shell designed to transform the design features to application specific weld process schedules is described. A new approach using fixed path modified continuation methods is proposed in the final section to plan continuously the trajectory of weld seams in an integrated welding robot and positioner environment. The joint displacement, velocity, and acceleration histories all along the path as a function of the path parameter for the best possible welding condition are provided for the robot and the positioner to track various paths normally encountered in arc welding.

Changes in quantitative 3D shape features of the optic nerve head associated with age

NASA Astrophysics Data System (ADS)

Christopher, Mark; Tang, Li; Fingert, John H.; Scheetz, Todd E.; Abramoff, Michael D.

2013-02-01

Optic nerve head (ONH) structure is an important biological feature of the eye used by clinicians to diagnose and monitor progression of diseases such as glaucoma. ONH structure is commonly examined using stereo fundus imaging or optical coherence tomography. Stereo fundus imaging provides stereo views of the ONH that retain 3D information useful for characterizing structure. In order to quantify 3D ONH structure, we applied a stereo correspondence algorithm to a set of stereo fundus images. Using these quantitative 3D ONH structure measurements, eigen structures were derived using principal component analysis from stereo images of 565 subjects from the Ocular Hypertension Treatment Study (OHTS). To evaluate the usefulness of the eigen structures, we explored associations with the demographic variables age, gender, and race. Using regression analysis, the eigen structures were found to have significant (p < 0.05) associations with both age and race after Bonferroni correction. In addition, classifiers were constructed to predict the demographic variables based solely on the eigen structures. These classifiers achieved an area under receiver operating characteristic curve of 0.62 in predicting a binary age variable, 0.52 in predicting gender, and 0.67 in predicting race. The use of objective, quantitative features or eigen structures can reveal hidden relationships between ONH structure and demographics. The use of these features could similarly allow specific aspects of ONH structure to be isolated and associated with the diagnosis of glaucoma, disease progression and outcomes, and genetic factors.

An extensive analysis of various texture feature extractors to detect Diabetes Mellitus using facial specific regions.

PubMed

Shu, Ting; Zhang, Bob; Yan Tang, Yuan

2017-04-01

Researchers have recently discovered that Diabetes Mellitus can be detected through non-invasive computerized method. However, the focus has been on facial block color features. In this paper, we extensively study the effects of texture features extracted from facial specific regions at detecting Diabetes Mellitus using eight texture extractors. The eight methods are from four texture feature families: (1) statistical texture feature family: Image Gray-scale Histogram, Gray-level Co-occurance Matrix, and Local Binary Pattern, (2) structural texture feature family: Voronoi Tessellation, (3) signal processing based texture feature family: Gaussian, Steerable, and Gabor filters, and (4) model based texture feature family: Markov Random Field. In order to determine the most appropriate extractor with optimal parameter(s), various parameter(s) of each extractor are experimented. For each extractor, the same dataset (284 Diabetes Mellitus and 231 Healthy samples), classifiers (k-Nearest Neighbors and Support Vector Machines), and validation method (10-fold cross validation) are used. According to the experiments, the first and third families achieved a better outcome at detecting Diabetes Mellitus than the other two. The best texture feature extractor for Diabetes Mellitus detection is the Image Gray-scale Histogram with bin number=256, obtaining an accuracy of 99.02%, a sensitivity of 99.64%, and a specificity of 98.26% by using SVM. Copyright © 2017 Elsevier Ltd. All rights reserved.

Recurrent intraplate tectonism in the New Madrid seismic zone

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zoback, M.D.; Hamilton, R.M.; Crone, A.J.

1980-08-29

For the first time, New Madrid seismicity can be linked to specific structural features that have been reactivated through geologic time. Extensive seismic reflection profiling reveals major faults coincident with the main earthquake trends in the area and with structural deformation apparently caused by repeated episodes of igneous activity.

Developmental Trajectories of Structural and Pragmatic Language Skills in School-Aged Children with Williams Syndrome

ERIC Educational Resources Information Center

Van Den Heuvel, E.; Manders, E.; Swillen, A.; Zink, I.

2016-01-01

Background: This study aimed to compare developmental courses of structural and pragmatic language skills in school-aged children with Williams syndrome (WS) and children with idiopathic intellectual disability (IID). Comparison of these language trajectories could highlight syndrome-specific developmental features. Method: Twelve monolingual…

Kinematic parameters of signed verbs.

PubMed

Malaia, Evie; Wilbur, Ronnie B; Milkovic, Marina

2013-10-01

Sign language users recruit physical properties of visual motion to convey linguistic information. Research on American Sign Language (ASL) indicates that signers systematically use kinematic features (e.g., velocity, deceleration) of dominant hand motion for distinguishing specific semantic properties of verb classes in production ( Malaia & Wilbur, 2012a) and process these distinctions as part of the phonological structure of these verb classes in comprehension ( Malaia, Ranaweera, Wilbur, & Talavage, 2012). These studies are driven by the event visibility hypothesis by Wilbur (2003), who proposed that such use of kinematic features should be universal to sign language (SL) by the grammaticalization of physics and geometry for linguistic purposes. In a prior motion capture study, Malaia and Wilbur (2012a) lent support for the event visibility hypothesis in ASL, but there has not been quantitative data from other SLs to test the generalization to other languages. The authors investigated the kinematic parameters of predicates in Croatian Sign Language ( Hrvatskom Znakovnom Jeziku [HZJ]). Kinematic features of verb signs were affected both by event structure of the predicate (semantics) and phrase position within the sentence (prosody). The data demonstrate that kinematic features of motion in HZJ verb signs are recruited to convey morphological and prosodic information. This is the first crosslinguistic motion capture confirmation that specific kinematic properties of articulator motion are grammaticalized in other SLs to express linguistic features.

Predicting Cell Association of Surface-Modified Nanoparticles Using Protein Corona Structure - Activity Relationships (PCSAR).

PubMed

Kamath, Padmaja; Fernandez, Alberto; Giralt, Francesc; Rallo, Robert

2015-01-01

Nanoparticles are likely to interact in real-case application scenarios with mixtures of proteins and biomolecules that will absorb onto their surface forming the so-called protein corona. Information related to the composition of the protein corona and net cell association was collected from literature for a library of surface-modified gold and silver nanoparticles. For each protein in the corona, sequence information was extracted and used to calculate physicochemical properties and statistical descriptors. Data cleaning and preprocessing techniques including statistical analysis and feature selection methods were applied to remove highly correlated, redundant and non-significant features. A weighting technique was applied to construct specific signatures that represent the corona composition for each nanoparticle. Using this basic set of protein descriptors, a new Protein Corona Structure-Activity Relationship (PCSAR) that relates net cell association with the physicochemical descriptors of the proteins that form the corona was developed and validated. The features that resulted from the feature selection were in line with already published literature, and the computational model constructed on these features had a good accuracy (R(2)LOO=0.76 and R(2)LMO(25%)=0.72) and stability, with the advantage that the fingerprints based on physicochemical descriptors were independent of the specific proteins that form the corona.

Liquid-gas phase transition in asymmetric nuclear matter at finite temperature

NASA Astrophysics Data System (ADS)

Maruyama, Toshiki; Tatsumi, Toshitaka; Chiba, Satoshi

2010-03-01

Liquid-gas phase transition is discussed in warm asymmetric nuclear matter. Some peculiar features are figured out from the viewpoint of the basic thermodynamics about the phase equilibrium. We treat the mixed phase of the binary system based on the Gibbs conditions. When the Coulomb interaction is included, the mixed phase is no more uniform and the sequence of the pasta structures appears. Comparing the results with those given by the simple bulk calculation without the Coulomb interaction, we extract specific features of the pasta structures at finite temperature.

Functional MRI registration with tissue-specific patch-based functional correlation tensors.

PubMed

Zhou, Yujia; Zhang, Han; Zhang, Lichi; Cao, Xiaohuan; Yang, Ru; Feng, Qianjin; Yap, Pew-Thian; Shen, Dinggang

2018-06-01

Population studies of brain function with resting-state functional magnetic resonance imaging (rs-fMRI) rely on accurate intersubject registration of functional areas. This is typically achieved through registration using high-resolution structural images with more spatial details and better tissue contrast. However, accumulating evidence has suggested that such strategy cannot align functional regions well because functional areas are not necessarily consistent with anatomical structures. To alleviate this problem, a number of registration algorithms based directly on rs-fMRI data have been developed, most of which utilize functional connectivity (FC) features for registration. However, most of these methods usually extract functional features only from the thin and highly curved cortical grey matter (GM), posing great challenges to accurate estimation of whole-brain deformation fields. In this article, we demonstrate that additional useful functional features can also be extracted from the whole brain, not restricted to the GM, particularly the white-matter (WM), for improving the overall functional registration. Specifically, we quantify local anisotropic correlation patterns of the blood oxygenation level-dependent (BOLD) signals using tissue-specific patch-based functional correlation tensors (ts-PFCTs) in both GM and WM. Functional registration is then performed by integrating the features from different tissues using the multi-channel large deformation diffeomorphic metric mapping (mLDDMM) algorithm. Experimental results show that our method achieves superior functional registration performance, compared with conventional registration methods. © 2018 Wiley Periodicals, Inc.

Chromatin structure of the LCR in the human β-globin locus transcribing the adult δ- and β-globin genes.

PubMed

Kim, Seoyeon; Kim, Yea Woon; Shim, Sung Han; Kim, Chul Geun; Kim, Aeri

2012-03-01

The β-like globin genes are transcribed in a developmental stage specific fashion in erythroid cells. The specific transcription of globin genes is conferred by the locus control region (LCR), but the chromatin structure of the LCR in the human adult β-globin locus transcribing the δ- and β-globin genes is not clear. Here, we employed hybrid MEL cells that contain a human chromosome 11. The δ- and β-globin genes were highly transcribed in hybrid MEL/ch11 cells after transcriptional induction. LCR HS3 and HS2 were strongly occupied by erythroid specific transcriptional activators and co-factors in the induced locus. These HSs, but not HS4 and HS1, were in close proximity with the active globin genes as revealed by high resolution 3C experiments. The active features at HS3 were markedly established after transcriptional induction, while HS2 was in a relatively active conformation before the induction. Unexpectedly, HS1 did not show notable active features except histone hyperacetylation. Taken together, the LCR of the human β-globin locus transcribing the adult δ- and β-globin genes has HS specific chromatin structure. The structure at each HS, which is different from the locus transcribing the fetal globin genes, might relate to its role in transcribing the adult genes. Copyright © 2011 Elsevier Ltd. All rights reserved.

Cascade detection for the extraction of localized sequence features; specificity results for HIV-1 protease and structure-function results for the Schellman loop.

PubMed

Newell, Nicholas E

2011-12-15

The extraction of the set of features most relevant to function from classified biological sequence sets is still a challenging problem. A central issue is the determination of expected counts for higher order features so that artifact features may be screened. Cascade detection (CD), a new algorithm for the extraction of localized features from sequence sets, is introduced. CD is a natural extension of the proportional modeling techniques used in contingency table analysis into the domain of feature detection. The algorithm is successfully tested on synthetic data and then applied to feature detection problems from two different domains to demonstrate its broad utility. An analysis of HIV-1 protease specificity reveals patterns of strong first-order features that group hydrophobic residues by side chain geometry and exhibit substantial symmetry about the cleavage site. Higher order results suggest that favorable cooperativity is weak by comparison and broadly distributed, but indicate possible synergies between negative charge and hydrophobicity in the substrate. Structure-function results for the Schellman loop, a helix-capping motif in proteins, contain strong first-order features and also show statistically significant cooperativities that provide new insights into the design of the motif. These include a new 'hydrophobic staple' and multiple amphipathic and electrostatic pair features. CD should prove useful not only for sequence analysis, but also for the detection of multifactor synergies in cross-classified data from clinical studies or other sources. Windows XP/7 application and data files available at: https://sites.google.com/site/cascadedetect/home. nacnewell@comcast.net Supplementary information is available at Bioinformatics online.

Feature-Based Morphometry: Discovering Group-related Anatomical Patterns

PubMed Central

Toews, Matthew; Wells, William; Collins, D. Louis; Arbel, Tal

2015-01-01

This paper presents feature-based morphometry (FBM), a new, fully data-driven technique for discovering patterns of group-related anatomical structure in volumetric imagery. In contrast to most morphometry methods which assume one-to-one correspondence between subjects, FBM explicitly aims to identify distinctive anatomical patterns that may only be present in subsets of subjects, due to disease or anatomical variability. The image is modeled as a collage of generic, localized image features that need not be present in all subjects. Scale-space theory is applied to analyze image features at the characteristic scale of underlying anatomical structures, instead of at arbitrary scales such as global or voxel-level. A probabilistic model describes features in terms of their appearance, geometry, and relationship to subject groups, and is automatically learned from a set of subject images and group labels. Features resulting from learning correspond to group-related anatomical structures that can potentially be used as image biomarkers of disease or as a basis for computer-aided diagnosis. The relationship between features and groups is quantified by the likelihood of feature occurrence within a specific group vs. the rest of the population, and feature significance is quantified in terms of the false discovery rate. Experiments validate FBM clinically in the analysis of normal (NC) and Alzheimer's (AD) brain images using the freely available OASIS database. FBM automatically identifies known structural differences between NC and AD subjects in a fully data-driven fashion, and an equal error classification rate of 0.80 is achieved for subjects aged 60-80 years exhibiting mild AD (CDR=1). PMID:19853047

Formal Transformations from Graphically-Based Object-Oriented Representations to Theory-Based Specifications

DTIC Science & Technology

1996-06-01

for Software Synthesis." KBSE 󈨡. IEEE, 1993. 51. Kang, Kyo C., et al. Feature-Oriented Domain Analysis ( FODA ) Feasibility Study. Technical Report...and usefulness in domain analysis and modeling. Rumbaugh uses three distinct views to describe a domain: (1) the object model describes structural...Gibbons describe a methodology where Structured Analysis is used to build a hierarchical system structure chart. This structure chart is then translated

A structural portrait of the PDZ domain family.

PubMed

Ernst, Andreas; Appleton, Brent A; Ivarsson, Ylva; Zhang, Yingnan; Gfeller, David; Wiesmann, Christian; Sidhu, Sachdev S

2014-10-23

PDZ (PSD-95/Discs-large/ZO1) domains are interaction modules that typically bind to specific C-terminal sequences of partner proteins and assemble signaling complexes in multicellular organisms. We have analyzed the existing database of PDZ domain structures in the context of a specificity tree based on binding specificities defined by peptide-phage binding selections. We have identified 16 structures of PDZ domains in complex with high-affinity ligands and have elucidated four additional structures to assemble a structural database that covers most of the branches of the PDZ specificity tree. A detailed comparison of the structures reveals features that are responsible for the diverse specificities across the PDZ domain family. Specificity differences can be explained by differences in PDZ residues that are in contact with the peptide ligands, but these contacts involve both side-chain and main-chain interactions. Most PDZ domains bind peptides in a canonical conformation in which the ligand main chain adopts an extended β-strand conformation by interacting in an antiparallel fashion with a PDZ β-strand. However, a subset of PDZ domains bind peptides with a bent main-chain conformation and the specificities of these non-canonical domains could not be explained based on canonical structures. Our analysis provides a structural portrait of the PDZ domain family, which serves as a guide in understanding the structural basis for the diverse specificities across the family. Copyright © 2014 Elsevier Ltd. All rights reserved.

Root, Successive-Cyclic and Feature-Splitting Internal Merge: Implications for Feature-Inheritance and Transfer

ERIC Educational Resources Information Center

Obata, Miki

2010-01-01

The goal of the dissertation is to determine aspects of the structure of the human language faculty, a cognitive system, specifically focusing on human syntactic systems, (unique in the animal kingdom) which enable us to creatively produce an unlimited number of grammatical sentences (like the one you just read, probably never before written or…

System among the corticosteroids: specificity and molecular dynamics

PubMed Central

Brookes, Jennifer C.; Galigniana, Mario D.; Harker, Anthony H.; Stoneham, A. Marshall; Vinson, Gavin P.

2012-01-01

Understanding how structural features determine specific biological activities has often proved elusive. With over 161 000 steroid structures described, an algorithm able to predict activity from structural attributes would provide manifest benefits. Molecular simulations of a range of 35 corticosteroids show striking correlations between conformational mobility and biological specificity. Thus steroid ring A is important for glucocorticoid action, and is rigid in the most specific (and potent) examples, such as dexamethasone. By contrast, ring C conformation is important for the mineralocorticoids, and is rigid in aldosterone. Other steroids that are less specific, or have mixed functions, or none at all, are more flexible. One unexpected example is 11-deoxycorticosterone, which the methods predict (and our activity studies confirm) is not only a specific mineralocorticoid, but also has significant glucocorticoid activity. These methods may guide the design of new corticosteroid agonists and antagonists. They will also have application in other examples of ligand–receptor interactions. PMID:21613285

A comparative study of family-specific protein-ligand complex affinity prediction based on random forest approach

NASA Astrophysics Data System (ADS)

Wang, Yu; Guo, Yanzhi; Kuang, Qifan; Pu, Xuemei; Ji, Yue; Zhang, Zhihang; Li, Menglong

2015-04-01

The assessment of binding affinity between ligands and the target proteins plays an essential role in drug discovery and design process. As an alternative to widely used scoring approaches, machine learning methods have also been proposed for fast prediction of the binding affinity with promising results, but most of them were developed as all-purpose models despite of the specific functions of different protein families, since proteins from different function families always have different structures and physicochemical features. In this study, we proposed a random forest method to predict the protein-ligand binding affinity based on a comprehensive feature set covering protein sequence, binding pocket, ligand structure and intermolecular interaction. Feature processing and compression was respectively implemented for different protein family datasets, which indicates that different features contribute to different models, so individual representation for each protein family is necessary. Three family-specific models were constructed for three important protein target families of HIV-1 protease, trypsin and carbonic anhydrase respectively. As a comparison, two generic models including diverse protein families were also built. The evaluation results show that models on family-specific datasets have the superior performance to those on the generic datasets and the Pearson and Spearman correlation coefficients ( R p and Rs) on the test sets are 0.740, 0.874, 0.735 and 0.697, 0.853, 0.723 for HIV-1 protease, trypsin and carbonic anhydrase respectively. Comparisons with the other methods further demonstrate that individual representation and model construction for each protein family is a more reasonable way in predicting the affinity of one particular protein family.

SMOQ: a tool for predicting the absolute residue-specific quality of a single protein model with support vector machines

PubMed Central

2014-01-01

Background It is important to predict the quality of a protein structural model before its native structure is known. The method that can predict the absolute local quality of individual residues in a single protein model is rare, yet particularly needed for using, ranking and refining protein models. Results We developed a machine learning tool (SMOQ) that can predict the distance deviation of each residue in a single protein model. SMOQ uses support vector machines (SVM) with protein sequence and structural features (i.e. basic feature set), including amino acid sequence, secondary structures, solvent accessibilities, and residue-residue contacts to make predictions. We also trained a SVM model with two new additional features (profiles and SOV scores) on 20 CASP8 targets and found that including them can only improve the performance when real deviations between native and model are higher than 5Å. The SMOQ tool finally released uses the basic feature set trained on 85 CASP8 targets. Moreover, SMOQ implemented a way to convert predicted local quality scores into a global quality score. SMOQ was tested on the 84 CASP9 single-domain targets. The average difference between the residue-specific distance deviation predicted by our method and the actual distance deviation on the test data is 2.637Å. The global quality prediction accuracy of the tool is comparable to other good tools on the same benchmark. Conclusion SMOQ is a useful tool for protein single model quality assessment. Its source code and executable are available at: http://sysbio.rnet.missouri.edu/multicom_toolbox/. PMID:24776231

SMOQ: a tool for predicting the absolute residue-specific quality of a single protein model with support vector machines.

PubMed

Cao, Renzhi; Wang, Zheng; Wang, Yiheng; Cheng, Jianlin

2014-04-28

It is important to predict the quality of a protein structural model before its native structure is known. The method that can predict the absolute local quality of individual residues in a single protein model is rare, yet particularly needed for using, ranking and refining protein models. We developed a machine learning tool (SMOQ) that can predict the distance deviation of each residue in a single protein model. SMOQ uses support vector machines (SVM) with protein sequence and structural features (i.e. basic feature set), including amino acid sequence, secondary structures, solvent accessibilities, and residue-residue contacts to make predictions. We also trained a SVM model with two new additional features (profiles and SOV scores) on 20 CASP8 targets and found that including them can only improve the performance when real deviations between native and model are higher than 5Å. The SMOQ tool finally released uses the basic feature set trained on 85 CASP8 targets. Moreover, SMOQ implemented a way to convert predicted local quality scores into a global quality score. SMOQ was tested on the 84 CASP9 single-domain targets. The average difference between the residue-specific distance deviation predicted by our method and the actual distance deviation on the test data is 2.637Å. The global quality prediction accuracy of the tool is comparable to other good tools on the same benchmark. SMOQ is a useful tool for protein single model quality assessment. Its source code and executable are available at: http://sysbio.rnet.missouri.edu/multicom_toolbox/.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ruan, D; Shao, W; Low, D

Purpose: To evaluate and test the hypothesis that plan quality may be systematically affected by treatment delivery techniques and target-tocritical structure geometric relationship in radiotherapy for brain tumor. Methods: Thirty-four consecutive brain tumor patients treated between 2011–2014 were analyzed. Among this cohort, 10 were planned with 3DCRT, 11 with RadipArc, and 13 with helical IMRT on TomoTherapy. The selected dosimetric endpoints (i.e., PTV V100, maximum brainstem/chiasm/ optic nerve doses) were considered as a vector in a highdimensional space. A Pareto analysis was performed to identify the subset of Pareto-efficient plans.The geometric relationships, specifically the overlapping volume and centroid-of-mass distance betweenmore » each critical structure to the PTV were extracted as potential geometric features. The classification-tree analyses were repeated using these geometric features with and without the treatment modality as an additional categorical predictor. In both scenarios, the dominant features to prognosticate the Pareto membership were identified and the tree structures to provide optimal inference were recorded. The classification performance was further analyzed to determine the role of treatment modality in affecting plan quality. Results: Seven Pareto-efficient plans were identified based on dosimetric endpoints (3 from 3DCRT, 3 from RapicArc, 1 from Tomo), which implies that the evaluated treatment modality may have a minor influence on plan quality. Classification trees with/without the treatment modality as a predictor both achieved accuracy of 88.2%: with 100% sensitivity and 87.1% specificity for the former, and 66.7% sensitivity and 96.0% specificity for the latter. The coincidence of accuracy from both analyses further indicates no-to-weak dependence of plan quality on treatment modality. Both analyses have identified the brainstem to PTV distance as the primary predictive feature for Pareto-efficiency. Conclusion: Pareto evaluation and classification-tree analyses have indicated that plan quality depends strongly on geometry for brain tumor, specifically PTV-tobrain-stem-distance but minimally on treatment modality.« less

Recent Methods for Purification and Structure Determination of Oligonucleotides.

PubMed

Zhang, Qiulong; Lv, Huanhuan; Wang, Lili; Chen, Man; Li, Fangfei; Liang, Chao; Yu, Yuanyuan; Jiang, Feng; Lu, Aiping; Zhang, Ge

2016-12-18

Aptamers are single-stranded DNA or RNA oligonucleotides that can interact with target molecules through specific three-dimensional structures. The excellent features, such as high specificity and affinity for target proteins, small size, chemical stability, low immunogenicity, facile chemical synthesis, versatility in structural design and engineering, and accessible for site-specific modifications with functional moieties, make aptamers attractive molecules in the fields of clinical diagnostics and biopharmaceutical therapeutics. However, difficulties in purification and structural identification of aptamers remain a major impediment to their broad clinical application. In this mini-review, we present the recently attractive developments regarding the purification and identification of aptamers. We also discuss the advantages, limitations, and prospects for the major methods applied in purifying and identifying aptamers, which could facilitate the application of aptamers.

Critical Song Features for Auditory Pattern Recognition in Crickets

PubMed Central

Meckenhäuser, Gundula; Hennig, R. Matthias; Nawrot, Martin P.

2013-01-01

Many different invertebrate and vertebrate species use acoustic communication for pair formation. In the cricket Gryllus bimaculatus, females recognize their species-specific calling song and localize singing males by positive phonotaxis. The song pattern of males has a clear structure consisting of brief and regular pulses that are grouped into repetitive chirps. Information is thus present on a short and a long time scale. Here, we ask which structural features of the song critically determine the phonotactic performance. To this end we employed artificial neural networks to analyze a large body of behavioral data that measured females’ phonotactic behavior under systematic variation of artificially generated song patterns. In a first step we used four non-redundant descriptive temporal features to predict the female response. The model prediction showed a high correlation with the experimental results. We used this behavioral model to explore the integration of the two different time scales. Our result suggested that only an attractive pulse structure in combination with an attractive chirp structure reliably induced phonotactic behavior to signals. In a further step we investigated all feature sets, each one consisting of a different combination of eight proposed temporal features. We identified feature sets of size two, three, and four that achieve highest prediction power by using the pulse period from the short time scale plus additional information from the long time scale. PMID:23437054

Rotor systems research aircraft predesign study. Volume 4: Preliminary draft detail specification

NASA Technical Reports Server (NTRS)

Miller, A. N.; Linden, A. W.

1972-01-01

The RSRA requirements are presented in a detail specification format. Coverage of the requirements includes the following headings: (1) aircraft characteristics, (2) general features of design and construction, (3) aerodynamics, (4) structural design criteria, (5) flight control system, (6) propulsion subsystem, and (7) secondary power and distribution subsystem.

Targeted Information Dissemination

DTIC Science & Technology

2008-03-01

SETUP, RESULTS AND PERFORMANCE ANALYSIS .......................................... 36 APPENDIX C: TID API SPECIFICATION...are developed using FreePastry1. FreePastry provides an API for a structured P2P overlay network. Information Routing and address resolution is...the TID architecture to demonstrate its key features. TID interface API specifications are described in Appendix C. RSS feeds were used to obtain

Before Five: Early Childhood Care and Education in New Zealand.

ERIC Educational Resources Information Center

New Zealand Dept. of Education, Wellington.

This publication outlines the Government of New Zealand's new plans and policies for the administration of early childhood care and education. Specific features are discussed in detail in sections concerning: (1) early childhood care and education at the local level, specifically management structures and responsibilities, the use of Crown land,…

Putative Monofunctional Type I Polyketide Synthase Units: A Dinoflagellate-Specific Feature?

PubMed Central

Eichholz, Karsten; Beszteri, Bánk; John, Uwe

2012-01-01

Marine dinoflagellates (alveolata) are microalgae of which some cause harmful algal blooms and produce a broad variety of most likely polyketide synthesis derived phycotoxins. Recently, novel polyketide synthesase (PKS) transcripts have been described from the Florida red tide dinoflagellate Karenia brevis (gymnodiniales) which are evolutionarily related to Type I PKS but were apparently expressed as monofunctional proteins, a feature typical of Type II PKS. Here, we investigated expression units of PKS I-like sequences in Alexandrium ostenfeldii (gonyaulacales) and Heterocapsa triquetra (peridiniales) at the transcript and protein level. The five full length transcripts we obtained were all characterized by polyadenylation, a 3′ UTR and the dinoflagellate specific spliced leader sequence at the 5′end. Each of the five transcripts encoded a single ketoacylsynthase (KS) domain showing high similarity to K. brevis KS sequences. The monofunctional structure was also confirmed using dinoflagellate specific KS antibodies in Western Blots. In a maximum likelihood phylogenetic analysis of KS domains from diverse PKSs, dinoflagellate KSs formed a clade placed well within the protist Type I PKS clade between apicomplexa, haptophytes and chlorophytes. These findings indicate that the atypical PKS I structure, i.e., expression as putative monofunctional units, might be a dinoflagellate specific feature. In addition, the sequenced transcripts harbored a previously unknown, apparently dinoflagellate specific conserved N-terminal domain. We discuss the implications of this novel region with regard to the putative monofunctional organization of Type I PKS in dinoflagellates. PMID:23139807

Language translation, doman specific languages and ANTLR

NASA Technical Reports Server (NTRS)

Craymer, Loring; Parr, Terence

2002-01-01

We will discuss the features of ANTLR that make it an attractive tool for rapid developement of domain specific language translators and present some practical examples of its use: extraction of information from the Cassini Command Language specification, the processing of structured binary data, and IVL--an English-like language for generating VRML scene graph, which is used in configuring the jGuru.com server.

Faculty Agency in Striving University Contexts: Mundane yet Powerful Acts of Agency

ERIC Educational Resources Information Center

Gonzales, Leslie D.

2015-01-01

Drawing from Archer's critical realist theory of agency, this paper has two specific aims. First, the cultural and structural features of one "striving" institution are outlined. Then, I illustrate how faculty members asserted agency inside their striving university in ways intended to disrupt the structures and cultures that striving…

A computational analysis of the three isoforms of glutamate dehydrogenase reveals structural features of the isoform EC 1.4.1.4 supporting a key role in ammonium assimilation by plants

PubMed Central

Jaspard, Emmanuel

2006-01-01

Background There are three isoforms of glutamate dehydrogenase. The isoform EC 1.4.1.4 (GDH4) catalyses glutamate synthesis from 2-oxoglutarate and ammonium, using NAD(P)H. Ammonium assimilation is critical for plant growth. Although GDH4 from animals and prokaryotes are well characterized, there are few data concerning plant GDH4, even from those whose genomes are well annotated. Results A large set of the three GDH isoforms was built resulting in 116 non-redundant full polypeptide sequences. A computational analysis was made to gain more information concerning the structure – function relationship of GDH4 from plants (Eukaryota, Viridiplantae). The tested plant GDH4 sequences were the two ones known to date, those of Chlorella sorokiniana. This analysis revealed several structural features specific of plant GDH4: (i) the lack of a structure called "antenna"; (ii) the NAD(P)-binding motif GAGNVA; and (iii) a second putative coenzyme-binding motif GVLTGKG together with four residues involved in the binding of the reduced form of NADP. Conclusion A number of structural features specific of plant GDH4 have been found. The results reinforce the probable key role of GDH4 in ammonium assimilation by plants. Reviewers This article was reviewed by Tina Bakolitsa (nominated by Eugene Koonin), Martin Jambon (nominated by Laura Landweber), Sandor Pangor and Franck Eisenhaber. PMID:17173671

Volcanology and morphology

NASA Technical Reports Server (NTRS)

Bryan, W. B.

1976-01-01

Apollo 15 photographs of the southern parts of Serenitatis and Imbrium were used for a study of the morphology and distribution of wrinkle ridges. Volcanic and structural features along the south margin of Serenitatis were also studied, including the Dawes basalt cinder cones. Volcanic and structural features in crater Aitken were investigated as well. Study of crater Goclenius showed a close relationship between morphology of the impact crater and grabens which tend to parallel directions of the lunar grid. Similar trends were observed in the walls of crater Tsiolkovsky and other linear structures. Small craters of possible volcanic origin were also studied. Possible cinder cones were found associated with the Dawes basalt and in the floor of craters Aitken and Goclenius. Small pit craters were observed in the floors of these craters. Attempts were made to obtain contour maps of specific small features and to compare Orbiter and Apollo photographs to determine short term changes associated with other processes.

An unconventional family 1 uracil DNA glycosylase in Nitratifractor salsuginis.

PubMed

Li, Jing; Chen, Ran; Yang, Ye; Zhang, Zhemin; Fang, Guang-Chen; Xie, Wei; Cao, Weiguo

2017-12-01

The uracil DNA glycosylase superfamily consists of at least six families with a diverse specificity toward DNA base damage. Family 1 uracil N-glycosylase (UNG) exhibits exclusive specificity on uracil-containing DNA. Here, we report a family 1 UNG homolog from Nitratifractor salsuginis with distinct biochemical features that differentiate it from conventional family 1 UNGs. Globally, the crystal structure of N. salsuginisUNG shows a few additional secondary structural elements. Biochemical and enzyme kinetic analysis, coupled with structural determination, molecular modeling, and molecular dynamics simulations, shows that N. salsuginisUNG contains a salt bridge network that plays an important role in DNA backbone interactions. Disruption of the amino acid residues involved in the salt bridges greatly impedes the enzymatic activity. A tyrosine residue in motif 1 (GQDPY) is one of the distinct sequence features setting family 1 UNG apart from other families. The crystal structure of Y81G mutant indicates that several subtle changes may account for its inactivity. Unlike the conventional family 1 UNG enzymes, N. salsuginisUNG is not inhibited by Ugi, a potent inhibitor specific for family 1 UNG. This study underscores the diversity of paths that a uracil DNA glycosylase may take to acquire its unique structural and biochemical properties during evolution. Structure data are available in the PDB under accession numbers 5X3G and 5X3H. © 2017 Federation of European Biochemical Societies.

On the relationship between the dynamic behavior and nanoscale staggered structure of the bone

NASA Astrophysics Data System (ADS)

Qwamizadeh, Mahan; Zhang, Zuoqi; Zhou, Kun; Zhang, Yong Wei

2015-05-01

Bone, a typical load-bearing biological material, composed of ordinary base materials such as organic protein and inorganic mineral arranged in a hierarchical architecture, exhibits extraordinary mechanical properties. Up to now, most of previous studies focused on its mechanical properties under static loading. However, failure of the bone occurs often under dynamic loading. An interesting question is: Are the structural sizes and layouts of the bone related or even adapted to the functionalities demanded by its dynamic performance? In the present work, systematic finite element analysis was performed on the dynamic response of nanoscale bone structures under dynamic loading. It was found that for a fixed mineral volume fraction and unit cell area, there exists a nanoscale staggered structure at some specific feature size and layout which exhibits the fastest attenuation of stress waves. Remarkably, these specific feature sizes and layouts are in excellent agreement with those experimentally observed in the bone at the same scale, indicating that the structural size and layout of the bone at the nanoscale are evolutionarily adapted to its dynamic behavior. The present work points out the importance of dynamic effect on the biological evolution of load-bearing biological materials.

Can deformation of a polymer film with a rigid coating model geophysical processes?

NASA Astrophysics Data System (ADS)

Volynskii, A. L.; Bazhenov, S. L.

2007-12-01

The structural and mechanical behavior of polymer films with a thin rigid coating is analyzed. The behavior of such systems under applied stress is accompanied by the formation of a regular wavy surface relief and by regular fragmentation of the coating. The above phenomena are shown to be universal. Both phenomena (stress-induced development of a regular wavy surface relief and regular fragmentation of the coating) are provided by the specific features of mechanical stress transfer from a compliant soft support to a rigid thin coating. The above phenomena are associated with a specific structure of the system, which is referred to as “a rigid coating on a soft substratum” system (RCSS). Surface microrelief in RCSS systems is similar to the ocean floor relief in the vicinity of mid-oceanic ridges. Thus, the complex system composed of a young oceanic crust and upper Earth's mantle may be considered as typically “a solid coating on a soft substratum” system. Specific features of the ocean floor relief are analyzed in terms of the approach advanced for the description of the structural mechanical behavior of polymer films with a rigid coating. This analysis allowed to estimate the strength of an ocean floor.

[Polymorphism and structure of the population of Proteocephalus longicollis Zeder, 1800 (Cestoda: Proteocephalidae) in the vendace Coregonus albula L].

PubMed

Anikieva, L V; Kharin, V N; Spektor, E N

2004-01-01

Polymorphism and phenotypic diversity of a hostal ecoform of Proteocephalus longicollis from its typical host, the vendace, Coregonus albula L., were studied. A complex phenotypic structure of the parasite population and presence of morphologically different groupings were revealed. We distinguished four groupings based on the external characters and three groupings based on the feed and reproduction features; among latter groupings one has very specific variations of features. We conclude that P. longicollis has high intraspecific and intrapopulation heterogeneity, and the host plays a stabilising role in the parasite species formation.

Features of the Correlation Structure of Price Indices

PubMed Central

Gao, Xiangyun; An, Haizhong; Zhong, Weiqiong

2013-01-01

What are the features of the correlation structure of price indices? To answer this question, 5 types of price indices, including 195 specific price indices from 2003 to 2011, were selected as sample data. To build a weighted network of price indices each price index is represented by a vertex, and a positive correlation between two price indices is represented by an edge. We studied the features of the weighted network structure by applying economic theory to the analysis of complex network parameters. We found that the frequency of the price indices follows a normal distribution by counting the weighted degrees of the nodes, and we identified the price indices which have an important impact on the network's structure. We found out small groups in the weighted network by the methods of k-core and k-plex. We discovered structure holes in the network by calculating the hierarchy of the nodes. Finally, we found that the price indices weighted network has a small-world effect by calculating the shortest path. These results provide a scientific basis for macroeconomic control policies. PMID:23593399

Star formation and ISM morphology in tidally induced spiral structures

NASA Astrophysics Data System (ADS)

Pettitt, Alex R.; Tasker, Elizabeth J.; Wadsley, James W.; Keller, Ben W.; Benincasa, Samantha M.

2017-07-01

Tidal encounters are believed to be one of the key drivers of galactic spiral structure in the Universe. Such spirals are expected to produce different morphological and kinematic features compared to density wave and dynamic spiral arms. In this work, we present high-resolution simulations of a tidal encounter of a small mass companion with a disc galaxy. Included are the effects of gas cooling and heating, star formation and stellar feedback. The structure of the perturbed disc differs greatly from the isolated galaxy, showing clear spiral features that act as sites of new star formation, and displaying interarm spurs. The two arms of the galaxy, the bridge and tail, appear to behave differently; with different star formation histories and structure. Specific attention is focused on offsets between gas and stellar spiral features which can be directly compared to observations. We find that some offsets do exist between different media, with gaseous arms appearing mostly on the convex side of the stellar arms, though the exact locations appear highly time dependent. These results further highlight the differences between tidal spirals and other theories of arm structure.

Structured Kernel Dictionary Learning with Correlation Constraint for Object Recognition.

PubMed

Wang, Zhengjue; Wang, Yinghua; Liu, Hongwei; Zhang, Hao

2017-06-21

In this paper, we propose a new discriminative non-linear dictionary learning approach, called correlation constrained structured kernel KSVD, for object recognition. The objective function for dictionary learning contains a reconstructive term and a discriminative term. In the reconstructive term, signals are implicitly non-linearly mapped into a space, where a structured kernel dictionary, each sub-dictionary of which lies in the span of the mapped signals from the corresponding class, is established. In the discriminative term, by analyzing the classification mechanism, the correlation constraint is proposed in kernel form, constraining the correlations between different discriminative codes, and restricting the coefficient vectors to be transformed into a feature space, where the features are highly correlated inner-class and nearly independent between-classes. The objective function is optimized by the proposed structured kernel KSVD. During the classification stage, the specific form of the discriminative feature is needless to be known, while the inner product of the discriminative feature with kernel matrix embedded is available, and is suitable for a linear SVM classifier. Experimental results demonstrate that the proposed approach outperforms many state-of-the-art dictionary learning approaches for face, scene and synthetic aperture radar (SAR) vehicle target recognition.

Challenging the state-of-the-art in protein structure prediction: Highlights of experimental target structures for the 10th Critical Assessment of Techniques for Protein Structure Prediction Experiment CASP10

PubMed Central

Kryshtafovych, Andriy; Moult, John; Bales, Patrick; Bazan, J. Fernando; Biasini, Marco; Burgin, Alex; Chen, Chen; Cochran, Frank V.; Craig, Timothy K.; Das, Rhiju; Fass, Deborah; Garcia-Doval, Carmela; Herzberg, Osnat; Lorimer, Donald; Luecke, Hartmut; Ma, Xiaolei; Nelson, Daniel C.; van Raaij, Mark J.; Rohwer, Forest; Segall, Anca; Seguritan, Victor; Zeth, Kornelius; Schwede, Torsten

2014-01-01

For the last two decades, CASP has assessed the state of the art in techniques for protein structure prediction and identified areas which required further development. CASP would not have been possible without the prediction targets provided by the experimental structural biology community. In the latest experiment, CASP10, over 100 structures were suggested as prediction targets, some of which appeared to be extraordinarily difficult for modeling. In this paper, authors of some of the most challenging targets discuss which specific scientific question motivated the experimental structure determination of the target protein, which structural features were especially interesting from a structural or functional perspective, and to what extent these features were correctly reproduced in the predictions submitted to CASP10. Specifically, the following targets will be presented: the acid-gated urea channel, a difficult to predict trans-membrane protein from the important human pathogen Helicobacter pylori; the structure of human interleukin IL-34, a recently discovered helical cytokine; the structure of a functionally uncharacterized enzyme OrfY from Thermoproteus tenax formed by a gene duplication and a novel fold; an ORFan domain of mimivirus sulfhydryl oxidase R596; the fibre protein gp17 from bacteriophage T7; the Bacteriophage CBA-120 tailspike protein; a virus coat protein from metagenomic samples of the marine environment; and finally an unprecedented class of structure prediction targets based on engineered disulfide-rich small proteins. PMID:24318984

Use cases and DEMO: aligning functional features of ICT-infrastructure to business processes.

PubMed

Maij, E; Toussaint, P J; Kalshoven, M; Poerschke, M; Zwetsloot-Schonk, J H M

2002-11-12

The proper alignment of functional features of the ICT-infrastructure to business processes is a major challenge in health care organisations. This alignment takes into account that the organisational structure not only shapes the ICT-infrastructure, but that the inverse also holds. To solve the alignment problem, relevant features of the ICT-infrastructure should be derived from the organisational structure and the influence of this envisaged ICT to the work practices should be pointed out. The objective of our study was to develop a method to solve this alignment problem. In a previous study we demonstrated the appropriateness of the business process modelling methodology Dynamic Essential Modelling of Organizations (DEMO). A proven and widely used modelling language for expressing functional features is Unified Modelling Language (UML). In the context of a specific case study at the University Medical Centre Utrecht in the Netherlands we investigated if the combined use of DEMO and UML could solve the alignment problem. The study demonstrated that the DEMO models were suited as a starting point in deriving system functionality by using the use case concept of UML. Further, the case study demonstrated that in using this approach for the alignment problem, insight is gained into the mutual influence of ICT-infrastructure and organisation structure: (a) specification of independent, re-usable components-as a set of related functionalities-is realised, and (b) a helpful representation of the current and future work practice is provided for in relation to the envisaged ICT support.

A Structural and Functional Comparison Between Infectious and Non-Infectious Autocatalytic Recombinant PrP Conformers

PubMed Central

Noble, Geoffrey P.; Wang, Daphne W.; Walsh, Daniel J.; Barone, Justin R.; Miller, Michael B.; Nishina, Koren A.; Li, Sheng; Supattapone, Surachai

2015-01-01

Infectious prions contain a self-propagating, misfolded conformer of the prion protein termed PrPSc. A critical prediction of the protein-only hypothesis is that autocatalytic PrPSc molecules should be infectious. However, some autocatalytic recombinant PrPSc molecules have low or undetectable levels of specific infectivity in bioassays, and the essential determinants of recombinant prion infectivity remain obscure. To identify structural and functional features specifically associated with infectivity, we compared the properties of two autocatalytic recombinant PrP conformers derived from the same original template, which differ by >105-fold in specific infectivity for wild-type mice. Structurally, hydrogen/deuterium exchange mass spectrometry (DXMS) studies revealed that solvent accessibility profiles of infectious and non-infectious autocatalytic recombinant PrP conformers are remarkably similar throughout their protease-resistant cores, except for two domains encompassing residues 91-115 and 144-163. Raman spectroscopy and immunoprecipitation studies confirm that these domains adopt distinct conformations within infectious versus non-infectious autocatalytic recombinant PrP conformers. Functionally, in vitro prion propagation experiments show that the non-infectious conformer is unable to seed mouse PrPC substrates containing a glycosylphosphatidylinositol (GPI) anchor, including native PrPC. Taken together, these results indicate that having a conformation that can be specifically adopted by post-translationally modified PrPC molecules is an essential determinant of biological infectivity for recombinant prions, and suggest that this ability is associated with discrete features of PrPSc structure. PMID:26125623

The Rock Elm meteorite impact structure, Wisconsin: Geology and shock-metamorphic effects in quartz

USGS Publications Warehouse

French, B.M.; Cordua, W.S.; Plescia, J.B.

2004-01-01

The Rock Elm structure in southwest Wisconsin is an anomalous circular area of highly deformed rocks, ???6.5 km in diameter, located in a region of virtually horizontal undeformed sedimentary rocks. Shock-produced planar microstructures (PMs) have been identified in quartz grains in several lithologies associated with the structure: sandstones, quartzite pebbles, and breccia. Two distinct types of PMs are present: P1 features, which appear identical to planar fractures (PFs or cleavage), and P2 features, which are interpreted as possible incipient planar deformation features (PDFs). The latter are uniquely produced by the shock waves associated with meteorite impact events. Both types of PMs are oriented parallel to specific crystallographic planes in the quartz, most commonly to c(0001), ??112??2, and r/z101??1. The association of unusual, structurally deformed strata with distinct shock-produced microdeformation features in their quartz-bearing rocks establishes Rock Elm as a meteorite impact structure and supports the view that the presence of multiple parallel cleavages in quartz may be used independently as a criterion for meteorite impact. Preliminary paleontological studies indicate a minimum age of Middle Ordovician for the Rock Elm structure. A similar age estimate (450-400 Ma) is obtained independently by combining the results of studies of the general morphology of complex impact structures with estimated rates of sedimentation for the region. Such methods may be applicable to dating other old and deeply eroded impact structures formed in sedimentary target rocks.

Left nucleus accumbens atrophy in deficit schizophrenia: A preliminary study.

PubMed

De Rossi, Pietro; Dacquino, Claudia; Piras, Fabrizio; Caltagirone, Carlo; Spalletta, Gianfranco

2016-08-30

A question that remains to be answered is whether schizophrenia can be characterized by a single etiopathophysiology or whether separate sub-syndromes should be differentiated to define specific mechanisms for each sub-type. Individuals affected by the deficit subtype of schizophrenia (DSZ) display avolitional/amotivational features that respond poorly to conventional treatments. Characterizing DSZ from a neuroanatomical point of view may help clarify this issue and develop new treatment strategies. To determine if DSZ is associated with structural alterations in specific deep grey matter structures linked to its key clinical features, 22 DSZ patients, 22 non-deficit schizophrenia (NDSZ) patients and 22 healthy controls (HC) were recruited for a case-control cross-sectional study. High-resolution magnetic resonance imaging was performed in all subjects and volumes of deep grey matter structures were measured using FreeSurfer. DSZ patients displayed smaller left accumbens volumes compared to both NDSZ patients and HC. Moreover, age and duration of illness were significantly associated with lower volume of the left accumbens in DSZ but not in NDSZ. Findings indicate that DSZ is associated with lower volume of the nucleus accumbens in the dominant hemisphere. This is consistent with the psychopathological features and functional impairments present in DSZ and thus indicates a potential mechanism. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Reference manual for a Requirements Specification Language (RSL), version 2.0

NASA Technical Reports Server (NTRS)

Fisher, Gene L.; Cohen, Gerald C.

1993-01-01

This report is a Reference Manual for a general-purpose Requirements Specification Language, RSL. The purpose of RSL is to specify precisely the external structure of a mechanized system and to define requirements that the system must meet. A system can be comprised of a mixture of hardware, software, and human processing elements. RSL is a hybrid of features found in several popular requirements specification languages and includes constructs for formal mathematical specification.

Spatial Data Transfer Standard (SDTS)

USGS Publications Warehouse

,

1999-01-01

The American National Standards Institute?s (ANSI) Spatial Data Transfer Standard (SDTS) is a mechanism for archiving and transferring of spatial data (including metadata) between dissimilar computer systems. The SDTS specifies exchange constructs, such as format, structure, and content, for spatially referenced vector and raster (including gridded) data. The SDTS includes a flexible conceptual model, specifications for a quality report, transfer module specifications, data dictionary specifications, and definitions of spatial features and attributes.

Transcriptional control by G-quadruplexes: In vivo roles and perspectives for specific intervention.

PubMed

Armas, Pablo; David, Aldana; Calcaterra, Nora B

2017-01-01

G-quadruplexes are non-canonical DNA secondary structures involved in several genomic and molecular processes. Here, we summarize the main G-quadruplex features and evidences proving the in vivo role on the transcriptional regulation of genes required for zebrafish embryonic development. We also discuss alternative strategies for specifically interfering G-quadruplex in vivo.

Time to face the fats: what can mass spectrometry reveal about the structure of lipids and their interactions with proteins?

PubMed

Brown, Simon H J; Mitchell, Todd W; Oakley, Aaron J; Pham, Huong T; Blanksby, Stephen J

2012-09-01

Since the 1950s, X-ray crystallography has been the mainstay of structural biology, providing detailed atomic-level structures that continue to revolutionize our understanding of protein function. From recent advances in this discipline, a picture has emerged of intimate and specific interactions between lipids and proteins that has driven renewed interest in the structure of lipids themselves and raised intriguing questions as to the specificity and stoichiometry in lipid-protein complexes. Herein we demonstrate some of the limitations of crystallography in resolving critical structural features of ligated lipids and thus determining how these motifs impact protein binding. As a consequence, mass spectrometry must play an important and complementary role in unraveling the complexities of lipid-protein interactions. We evaluate recent advances and highlight ongoing challenges towards the twin goals of (1) complete structure elucidation of low, abundant, and structurally diverse lipids by mass spectrometry alone, and (2) assignment of stoichiometry and specificity of lipid interactions within protein complexes.

Time to Face the Fats: What Can Mass Spectrometry Reveal about the Structure of Lipids and Their Interactions with Proteins?

NASA Astrophysics Data System (ADS)

Brown, Simon H. J.; Mitchell, Todd W.; Oakley, Aaron J.; Pham, Huong T.; Blanksby, Stephen J.

2012-09-01

Since the 1950s, X-ray crystallography has been the mainstay of structural biology, providing detailed atomic-level structures that continue to revolutionize our understanding of protein function. From recent advances in this discipline, a picture has emerged of intimate and specific interactions between lipids and proteins that has driven renewed interest in the structure of lipids themselves and raised intriguing questions as to the specificity and stoichiometry in lipid-protein complexes. Herein we demonstrate some of the limitations of crystallography in resolving critical structural features of ligated lipids and thus determining how these motifs impact protein binding. As a consequence, mass spectrometry must play an important and complementary role in unraveling the complexities of lipid-protein interactions. We evaluate recent advances and highlight ongoing challenges towards the twin goals of (1) complete structure elucidation of low, abundant, and structurally diverse lipids by mass spectrometry alone, and (2) assignment of stoichiometry and specificity of lipid interactions within protein complexes.

Architecture engineering of supercapacitor electrode materials

NASA Astrophysics Data System (ADS)

Chen, Kunfeng; Li, Gong; Xue, Dongfeng

2016-02-01

The biggest challenge for today’s supercapacitor systems readily possessing high power density is their low energy density. Their electrode materials with controllable structure, specific surface area, electronic conductivity, and oxidation state, have long been highlighted. Architecture engineering of functional electrode materials toward powerful supercapacitor systems is becoming a big fashion in the community. The construction of ion-accessible tunnel structures can microscopically increase the specific capacitance and materials utilization; stiff 3D structures with high specific surface area can macroscopically assure high specific capacitance. Many exciting findings in electrode materials mainly focus on the construction of ice-folded graphene paper, in situ functionalized graphene, in situ crystallizing colloidal ionic particles and polymorphic metal oxides. This feature paper highlights some recent architecture engineering strategies toward high-energy supercapacitor electrode systems, including electric double-layer capacitance (EDLC) and pseudocapacitance.

Structural insights into species-specific features of the ribosome from the pathogen Staphylococcus aureus

PubMed Central

Eyal, Zohar; Matzov, Donna; Krupkin, Miri; Wekselman, Itai; Paukner, Susanne; Zimmerman, Ella; Rozenberg, Haim; Bashan, Anat; Yonath, Ada

2015-01-01

The emergence of bacterial multidrug resistance to antibiotics threatens to cause regression to the preantibiotic era. Here we present the crystal structure of the large ribosomal subunit from Staphylococcus aureus, a versatile Gram-positive aggressive pathogen, and its complexes with the known antibiotics linezolid and telithromycin, as well as with a new, highly potent pleuromutilin derivative, BC-3205. These crystal structures shed light on specific structural motifs of the S. aureus ribosome and the binding modes of the aforementioned antibiotics. Moreover, by analyzing the ribosome structure and comparing it with those of nonpathogenic bacterial models, we identified some unique internal and peripheral structural motifs that may be potential candidates for improving known antibiotics and for use in the design of selective antibiotic drugs against S. aureus. PMID:26464510

Predictive analysis of the influence of the chemical composition and pre-processing regimen on structural properties of steel alloys using machine learning techniques

NASA Astrophysics Data System (ADS)

Krishnamurthy, Narayanan; Maddali, Siddharth; Romanov, Vyacheslav; Hawk, Jeffrey

We present some structural properties of multi-component steel alloys as predicted by a random forest machine-learning model. These non-parametric models are trained on high-dimensional data sets defined by features such as chemical composition, pre-processing temperatures and environmental influences, the latter of which are based upon standardized testing procedures for tensile, creep and rupture properties as defined by the American Society of Testing and Materials (ASTM). We quantify the goodness of fit of these models as well as the inferred relative importance of each of these features, all with a conveniently defined metric and scale. The models are tested with synthetic data points, generated subject to the appropriate mathematical constraints for the various features. By this we highlight possible trends in the increase or degradation of the structural properties with perturbations in the features of importance. This work is presented as part of the Data Science Initiative at the National Energy Technology Laboratory, directed specifically towards the computational design of steel alloys.

Heritable Individual-Specific and Allele-Specific Chromatin Signatures in Humans

PubMed Central

McDaniell, Ryan; Lee, Bum-Kyu; Song, Lingyun; Liu, Zheng; Boyle, Alan P.; Erdos, Michael R.; Scott, Laura J.; Morken, Mario A.; Kucera, Katerina S.; Battenhouse, Anna; Keefe, Damian; Collins, Francis S.; Willard, Huntington F.; Lieb, Jason D.; Furey, Terrence S.; Crawford, Gregory E.; Iyer, Vishwanath R.; Birney, Ewan

2010-01-01

The extent to which variation in chromatin structure and transcription factor binding may influence gene expression, and thus underlie or contribute to variation in phenotype, is unknown. To address this question, we cataloged both individual-to-individual variation and differences between homologous chromosomes within the same individual (allele-specific variation) in chromatin structure and transcription factor binding in lymphoblastoid cells derived from individuals of geographically diverse ancestry. Ten percent of active chromatin sites were individual-specific; a similar proportion were allele-specific. Both individual-specific and allele-specific sites were commonly transmitted from parent to child, which suggests that they are heritable features of the human genome. Our study shows that heritable chromatin status and transcription factor binding differ as a result of genetic variation and may underlie phenotypic variation in humans. PMID:20299549

The GOAL-to-HAL/S translator specification. [for space shuttle

NASA Technical Reports Server (NTRS)

Stanten, S. F.; Flanders, J. H.

1973-01-01

The specification sets forth a technical framework within which to deal with the transfer of specific GOAL features to HAL/S. Key technical features of the translator are described which communicate with the data bank, handle repeat statements, and deal with software interrupts. GOAL programs, databank information, and GOAL system subroutines are integrated into one GOAL in HAL/S. This output is fully compatible HAL/S source ready for insertion into the HAL/S compiler. The Translator uses a PASS1 to establish all the global data needed for the HAL/S output program. Individual GOAL statements are translated in PASS2. The specification document makes extensive use of flowcharts to specify exactly how each variation of each GOAL statement is to be translated. The specification also deals with definitions and assumptions, executive support structure and implementation. An appendix, entitled GOAL-to-HAL Mapping, provides examples of translated GOAL statements.

Mitochondrial Telomeres as Molecular Markers for Identification of the Opportunistic Yeast Pathogen Candida parapsilosis

PubMed Central

Nosek, Jozef; Tomáška, L'ubomír; Ryčovská, Adriana; Fukuhara, Hiroshi

2002-01-01

Recent studies have demonstrated that a large number of organisms carry linear mitochondrial DNA molecules possessing specialized telomeric structures at their ends. Based on this specific structural feature of linear mitochondrial genomes, we have developed an approach for identification of the opportunistic yeast pathogen Candida parapsilosis. The strategy for identification of C. parapsilosis strains is based on PCR amplification of specific DNA sequences derived from the mitochondrial telomere region. This assay is complemented by immunodetection of a protein component of mitochondrial telomeres. The results demonstrate that mitochondrial telomeres represent specific molecular markers with potential applications in yeast diagnostics and taxonomy. PMID:11923346

Mysticism and schizophrenia: A phenomenological exploration of the structure of consciousness in the schizophrenia spectrum disorders.

PubMed

Parnas, Josef; Henriksen, Mads Gram

2016-07-01

Mysticism and schizophrenia are different categories of human existence and experience. Nonetheless, they exhibit important phenomenological affinities, which, however, remain largely unaddressed. In this study, we explore structural analogies between key features of mysticism and major clinical-phenomenological aspects of the schizophrenia spectrum disorders-i.e. attitudes, the nature of experience, and the 'other', mystical or psychotic reality. Not only do these features gravitate around the issue of the basic dimensions of consciousness, they crucially seem to implicate and presuppose a specific alteration of the very structure of consciousness. This finding has bearings for the understanding of consciousness and its psychopathological distortions. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Stuttering-Psycholinguistic Approach

ERIC Educational Resources Information Center

Hategan, Carolina Bodea; Anca, Maria; Prihoi, Lacramioara

2012-01-01

This research promotes psycholinguistic paradigm, it focusing in delimitating several specific particularities in stuttering pathology. Structural approach, on language sides proves both the recurrent aspects found within specialized national and international literature and the psycholinguistic approaches dependence on the features of the…

Image counter-forensics based on feature injection

NASA Astrophysics Data System (ADS)

Iuliani, M.; Rossetto, S.; Bianchi, T.; De Rosa, Alessia; Piva, A.; Barni, M.

2014-02-01

Starting from the concept that many image forensic tools are based on the detection of some features revealing a particular aspect of the history of an image, in this work we model the counter-forensic attack as the injection of a specific fake feature pointing to the same history of an authentic reference image. We propose a general attack strategy that does not rely on a specific detector structure. Given a source image x and a target image y, the adversary processes x in the pixel domain producing an attacked image ~x, perceptually similar to x, whose feature f(~x) is as close as possible to f(y) computed on y. Our proposed counter-forensic attack consists in the constrained minimization of the feature distance Φ(z) =│ f(z) - f(y)│ through iterative methods based on gradient descent. To solve the intrinsic limit due to the numerical estimation of the gradient on large images, we propose the application of a feature decomposition process, that allows the problem to be reduced into many subproblems on the blocks the image is partitioned into. The proposed strategy has been tested by attacking three different features and its performance has been compared to state-of-the-art counter-forensic methods.

Exploring the specific features of interfacial enzymology based on lipase studies.

PubMed

Aloulou, Ahmed; Rodriguez, Jorge A; Fernandez, Sylvie; van Oosterhout, Dirk; Puccinelli, Delphine; Carrière, Frédéric

2006-09-01

Many enzymes are active at interfaces in the living world (such as in the signaling processes at the surface of cell membranes, digestion of dietary lipids, starch and cellulose degradation, etc.), but fundamental enzymology remains largely focused on the interactions between enzymes and soluble substrates. The biochemical and kinetic characterization of lipolytic enzymes has opened up new paths of research in the field of interfacial enzymology. Lipases are water-soluble enzymes hydrolyzing insoluble triglyceride substrates, and studies on these enzymes have led to the development of specific interfacial kinetic models. Structure-function studies on lipases have thrown light on the interfacial recognition sites present in the molecular structure of these enzymes, the conformational changes occurring in the presence of lipids and amphiphiles, and the stability of the enzymes present at interfaces. The pH-dependent activity, substrate specificity and inhibition of these enzymes can all result from both "classical" interactions between a substrate or inhibitor and the active site, as well as from the adsorption of the enzymes at the surface of aggregated substrate particles such as oil drops, lipid bilayers or monomolecular lipid films. The adsorption step can provide an alternative target for improving substrate specificity and developing specific enzyme inhibitors. Several data obtained with gastric lipase, classical pancreatic lipase, pancreatic lipase-related protein 2 and phosphatidylserine-specific phospholipase A1 were chosen here to illustrate these specific features of interfacial enzymology.

Contribution of transposable elements and distal enhancers to evolution of human-specific features of interphase chromatin architecture in embryonic stem cells.

PubMed

Glinsky, Gennadi V

2018-03-01

Transposable elements have made major evolutionary impacts on creation of primate-specific and human-specific genomic regulatory loci and species-specific genomic regulatory networks (GRNs). Molecular and genetic definitions of human-specific changes to GRNs contributing to development of unique to human phenotypes remain a highly significant challenge. Genome-wide proximity placement analysis of diverse families of human-specific genomic regulatory loci (HSGRL) identified topologically associating domains (TADs) that are significantly enriched for HSGRL and designated rapidly evolving in human TADs. Here, the analysis of HSGRL, hESC-enriched enhancers, super-enhancers (SEs), and specific sub-TAD structures termed super-enhancer domains (SEDs) has been performed. In the hESC genome, 331 of 504 (66%) of SED-harboring TADs contain HSGRL and 68% of SEDs co-localize with HSGRL, suggesting that emergence of HSGRL may have rewired SED-associated GRNs within specific TADs by inserting novel and/or erasing existing non-coding regulatory sequences. Consequently, markedly distinct features of the principal regulatory structures of interphase chromatin evolved in the hESC genome compared to mouse: the SED quantity is 3-fold higher and the median SED size is significantly larger. Concomitantly, the overall TAD quantity is increased by 42% while the median TAD size is significantly decreased (p = 9.11E-37) in the hESC genome. Present analyses illustrate a putative global role for transposable elements and HSGRL in shaping the human-specific features of the interphase chromatin organization and functions, which are facilitated by accelerated creation of novel transcription factor binding sites and new enhancers driven by targeted placement of HSGRL at defined genomic coordinates. A trend toward the convergence of TAD and SED architectures of interphase chromatin in the hESC genome may reflect changes of 3D-folding patterns of linear chromatin fibers designed to enhance both regulatory complexity and functional precision of GRNs by creating predominantly a single gene (or a set of functionally linked genes) per regulatory domain structures. Collectively, present analyses reveal critical evolutionary contributions of transposable elements and distal enhancers to creation of thousands primate- and human-specific elements of a chromatin folding code, which defines the 3D context of interphase chromatin both restricting and facilitating biological functions of GRNs.

DemQSAR: predicting human volume of distribution and clearance of drugs

NASA Astrophysics Data System (ADS)

Demir-Kavuk, Ozgur; Bentzien, Jörg; Muegge, Ingo; Knapp, Ernst-Walter

2011-12-01

In silico methods characterizing molecular compounds with respect to pharmacologically relevant properties can accelerate the identification of new drugs and reduce their development costs. Quantitative structure-activity/-property relationship (QSAR/QSPR) correlate structure and physico-chemical properties of molecular compounds with a specific functional activity/property under study. Typically a large number of molecular features are generated for the compounds. In many cases the number of generated features exceeds the number of molecular compounds with known property values that are available for learning. Machine learning methods tend to overfit the training data in such situations, i.e. the method adjusts to very specific features of the training data, which are not characteristic for the considered property. This problem can be alleviated by diminishing the influence of unimportant, redundant or even misleading features. A better strategy is to eliminate such features completely. Ideally, a molecular property can be described by a small number of features that are chemically interpretable. The purpose of the present contribution is to provide a predictive modeling approach, which combines feature generation, feature selection, model building and control of overtraining into a single application called DemQSAR. DemQSAR is used to predict human volume of distribution (VDss) and human clearance (CL). To control overtraining, quadratic and linear regularization terms were employed. A recursive feature selection approach is used to reduce the number of descriptors. The prediction performance is as good as the best predictions reported in the recent literature. The example presented here demonstrates that DemQSAR can generate a model that uses very few features while maintaining high predictive power. A standalone DemQSAR Java application for model building of any user defined property as well as a web interface for the prediction of human VDss and CL is available on the webpage of DemPRED: http://agknapp.chemie.fu-berlin.de/dempred/.

DemQSAR: predicting human volume of distribution and clearance of drugs.

PubMed

Demir-Kavuk, Ozgur; Bentzien, Jörg; Muegge, Ingo; Knapp, Ernst-Walter

2011-12-01

In silico methods characterizing molecular compounds with respect to pharmacologically relevant properties can accelerate the identification of new drugs and reduce their development costs. Quantitative structure-activity/-property relationship (QSAR/QSPR) correlate structure and physico-chemical properties of molecular compounds with a specific functional activity/property under study. Typically a large number of molecular features are generated for the compounds. In many cases the number of generated features exceeds the number of molecular compounds with known property values that are available for learning. Machine learning methods tend to overfit the training data in such situations, i.e. the method adjusts to very specific features of the training data, which are not characteristic for the considered property. This problem can be alleviated by diminishing the influence of unimportant, redundant or even misleading features. A better strategy is to eliminate such features completely. Ideally, a molecular property can be described by a small number of features that are chemically interpretable. The purpose of the present contribution is to provide a predictive modeling approach, which combines feature generation, feature selection, model building and control of overtraining into a single application called DemQSAR. DemQSAR is used to predict human volume of distribution (VD(ss)) and human clearance (CL). To control overtraining, quadratic and linear regularization terms were employed. A recursive feature selection approach is used to reduce the number of descriptors. The prediction performance is as good as the best predictions reported in the recent literature. The example presented here demonstrates that DemQSAR can generate a model that uses very few features while maintaining high predictive power. A standalone DemQSAR Java application for model building of any user defined property as well as a web interface for the prediction of human VD(ss) and CL is available on the webpage of DemPRED: http://agknapp.chemie.fu-berlin.de/dempred/ .

Control-group feature normalization for multivariate pattern analysis of structural MRI data using the support vector machine.

PubMed

Linn, Kristin A; Gaonkar, Bilwaj; Satterthwaite, Theodore D; Doshi, Jimit; Davatzikos, Christos; Shinohara, Russell T

2016-05-15

Normalization of feature vector values is a common practice in machine learning. Generally, each feature value is standardized to the unit hypercube or by normalizing to zero mean and unit variance. Classification decisions based on support vector machines (SVMs) or by other methods are sensitive to the specific normalization used on the features. In the context of multivariate pattern analysis using neuroimaging data, standardization effectively up- and down-weights features based on their individual variability. Since the standard approach uses the entire data set to guide the normalization, it utilizes the total variability of these features. This total variation is inevitably dependent on the amount of marginal separation between groups. Thus, such a normalization may attenuate the separability of the data in high dimensional space. In this work we propose an alternate approach that uses an estimate of the control-group standard deviation to normalize features before training. We study our proposed approach in the context of group classification using structural MRI data. We show that control-based normalization leads to better reproducibility of estimated multivariate disease patterns and improves the classifier performance in many cases. Copyright © 2016 Elsevier Inc. All rights reserved.

PrAS: Prediction of amidation sites using multiple feature extraction.

PubMed

Wang, Tong; Zheng, Wei; Wuyun, Qiqige; Wu, Zhenfeng; Ruan, Jishou; Hu, Gang; Gao, Jianzhao

2017-02-01

Amidation plays an important role in a variety of pathological processes and serious diseases like neural dysfunction and hypertension. However, identification of protein amidation sites through traditional experimental methods is time consuming and expensive. In this paper, we proposed a novel predictor for Prediction of Amidation Sites (PrAS), which is the first software package for academic users. The method incorporated four representative feature types, which are position-based features, physicochemical and biochemical properties features, predicted structure-based features and evolutionary information features. A novel feature selection method, positive contribution feature selection was proposed to optimize features. PrAS achieved AUC of 0.96, accuracy of 92.1%, sensitivity of 81.2%, specificity of 94.9% and MCC of 0.76 on the independent test set. PrAS is freely available at https://sourceforge.net/p/praspkg. Copyright © 2016 Elsevier Ltd. All rights reserved.

Structure based re-design of the binding specificity of anti-apoptotic Bcl-xL

PubMed Central

Chen, T. Scott; Palacios, Hector; Keating, Amy E.

2012-01-01

Many native proteins are multi-specific and interact with numerous partners, which can confound analysis of their functions. Protein design provides a potential route to generating synthetic variants of native proteins with more selective binding profiles. Re-designed proteins could be used as research tools, diagnostics or therapeutics. In this work, we used a library screening approach to re-engineer the multi-specific anti-apoptotic protein Bcl-xL to remove its interactions with many of its binding partners, making it a high affinity and selective binder of the BH3 region of pro-apoptotic protein Bad. To overcome the enormity of the potential Bcl-xL sequence space, we developed and applied a computational/experimental framework that used protein structure information to generate focused combinatorial libraries. Sequence features were identified using structure-based modeling, and an optimization algorithm based on integer programming was used to select degenerate codons that maximally covered these features. A constraint on library size was used to ensure thorough sampling. Using yeast surface display to screen a designed library of Bcl-xL variants, we successfully identified a protein with ~1,000-fold improvement in binding specificity for the BH3 region of Bad over the BH3 region of Bim. Although negative design was targeted only against the BH3 region of Bim, the best re-designed protein was globally specific against binding to 10 other peptides corresponding to native BH3 motifs. Our design framework demonstrates an efficient route to highly specific protein binders and may readily be adapted for application to other design problems. PMID:23154169

Protein structure based prediction of catalytic residues.

PubMed

Fajardo, J Eduardo; Fiser, Andras

2013-02-22

Worldwide structural genomics projects continue to release new protein structures at an unprecedented pace, so far nearly 6000, but only about 60% of these proteins have any sort of functional annotation. We explored a range of features that can be used for the prediction of functional residues given a known three-dimensional structure. These features include various centrality measures of nodes in graphs of interacting residues: closeness, betweenness and page-rank centrality. We also analyzed the distance of functional amino acids to the general center of mass (GCM) of the structure, relative solvent accessibility (RSA), and the use of relative entropy as a measure of sequence conservation. From the selected features, neural networks were trained to identify catalytic residues. We found that using distance to the GCM together with amino acid type provide a good discriminant function, when combined independently with sequence conservation. Using an independent test set of 29 annotated protein structures, the method returned 411 of the initial 9262 residues as the most likely to be involved in function. The output 411 residues contain 70 of the annotated 111 catalytic residues. This represents an approximately 14-fold enrichment of catalytic residues on the entire input set (corresponding to a sensitivity of 63% and a precision of 17%), a performance competitive with that of other state-of-the-art methods. We found that several of the graph based measures utilize the same underlying feature of protein structures, which can be simply and more effectively captured with the distance to GCM definition. This also has the added the advantage of simplicity and easy implementation. Meanwhile sequence conservation remains by far the most influential feature in identifying functional residues. We also found that due the rapid changes in size and composition of sequence databases, conservation calculations must be recalibrated for specific reference databases.

Transcriptional control by G-quadruplexes: In vivo roles and perspectives for specific intervention

PubMed Central

Armas, Pablo; David, Aldana; Calcaterra, Nora B.

2017-01-01

ABSTRACT G-quadruplexes are non-canonical DNA secondary structures involved in several genomic and molecular processes. Here, we summarize the main G-quadruplex features and evidences proving the in vivo role on the transcriptional regulation of genes required for zebrafish embryonic development. We also discuss alternative strategies for specifically interfering G-quadruplex in vivo. PMID:27696937

Effect of temperature and magnetic field on disorder in semiconductor structures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Agrinskaya, N. V., E-mail: nina.agrins@mail.ioffe.ru; Kozub, V. I.

We present the results of consistent theoretical analysis of various factors that may lead to influence of temperature and external magnetic field on disorder in semiconductor structures. Main attention is paid to quantum well (QW) structures in which only QWs or both QW and barriers are doped (the doping level is assumed to be close to the value corresponding to the metal–insulator transition). The above factors include (i) ionization of localized states to the region of delocalized states above the mobility edge, which is presumed to exist in the impurity band; (ii) the coexistence in the upper and lower Hubbardmore » bands (upon doping of QWs as well as barriers); in this case, in particular, the external magnetic field determines the relative contribution of the upper Hubbard band due to spin correlations at doubly filled sites; and (iii) the contribution of the exchange interaction at pairs of sites, in which the external magnetic field can affect the relation between ferromagnetic and antiferromagnetic configurations. All these factors, which affect the structure and degree of disorder, lead to specific features in the temperature dependence of resistivity and determine specific features of the magnetoresistance. Our conclusions are compared with available experimental data.« less

Protein functional features are reflected in the patterns of mRNA translation speed.

PubMed

López, Daniel; Pazos, Florencio

2015-07-09

The degeneracy of the genetic code makes it possible for the same amino acid string to be coded by different messenger RNA (mRNA) sequences. These "synonymous mRNAs" may differ largely in a number of aspects related to their overall translational efficiency, such as secondary structure content and availability of the encoded transfer RNAs (tRNAs). Consequently, they may render different yields of the translated polypeptides. These mRNA features related to translation efficiency are also playing a role locally, resulting in a non-uniform translation speed along the mRNA, which has been previously related to some protein structural features and also used to explain some dramatic effects of "silent" single-nucleotide-polymorphisms (SNPs). In this work we perform the first large scale analysis of the relationship between three experimental proxies of mRNA local translation efficiency and the local features of the corresponding encoded proteins. We found that a number of protein functional and structural features are reflected in the patterns of ribosome occupancy, secondary structure and tRNA availability along the mRNA. One or more of these proxies of translation speed have distinctive patterns around the mRNA regions coding for certain protein local features. In some cases the three patterns follow a similar trend. We also show specific examples where these patterns of translation speed point to the protein's important structural and functional features. This support the idea that the genome not only codes the protein functional features as sequences of amino acids, but also as subtle patterns of mRNA properties which, probably through local effects on the translation speed, have some consequence on the final polypeptide. These results open the possibility of predicting a protein's functional regions based on a single genomic sequence, and have implications for heterologous protein expression and fine-tuning protein function.

Assessing future vent opening locations at the Somma-Vesuvio volcanic complex: 1. A new information geodatabase with uncertainty characterizations

NASA Astrophysics Data System (ADS)

Tadini, A.; Bisson, M.; Neri, A.; Cioni, R.; Bevilacqua, A.; Aspinall, W. P.

2017-06-01

This study presents new and revised data sets about the spatial distribution of past volcanic vents, eruptive fissures, and regional/local structures of the Somma-Vesuvio volcanic system (Italy). The innovative features of the study are the identification and quantification of important sources of uncertainty affecting interpretations of the data sets. In this regard, the spatial uncertainty of each feature is modeled by an uncertainty area, i.e., a geometric element typically represented by a polygon drawn around points or lines. The new data sets have been assembled as an updatable geodatabase that integrates and complements existing databases for Somma-Vesuvio. The data are organized into 4 data sets and stored as 11 feature classes (points and lines for feature locations and polygons for the associated uncertainty areas), totaling more than 1700 elements. More specifically, volcanic vent and eruptive fissure elements are subdivided into feature classes according to their associated eruptive styles: (i) Plinian and sub-Plinian eruptions (i.e., large- or medium-scale explosive activity); (ii) violent Strombolian and continuous ash emission eruptions (i.e., small-scale explosive activity); and (iii) effusive eruptions (including eruptions from both parasitic vents and eruptive fissures). Regional and local structures (i.e., deep faults) are represented as linear feature classes. To support interpretation of the eruption data, additional data sets are provided for Somma-Vesuvio geological units and caldera morphological features. In the companion paper, the data presented here, and the associated uncertainties, are used to develop a first vent opening probability map for the Somma-Vesuvio caldera, with specific attention focused on large or medium explosive events.

Williams syndrome-specific neuroanatomical profile and its associations with behavioral features.

PubMed

Fan, Chun Chieh; Brown, Timothy T; Bartsch, Hauke; Kuperman, Joshua M; Hagler, Donald J; Schork, Andrew; Searcy, Yvonne; Bellugi, Ursula; Halgren, Eric; Dale, Anders M

2017-01-01

Williams Syndrome (WS) is a rare genetic disorder with unique behavioral features. Yet the rareness of WS has limited the number and type of studies that can be conducted in which inferences are made about how neuroanatomical abnormalities mediate behaviors. In this study, we extracted a WS-specific neuroanatomical profile from structural magnetic resonance imaging (MRI) measurements and tested its association with behavioral features of WS. Using a WS adult cohort (22 WS, 16 healthy controls), we modeled a sparse representation of a WS-specific neuroanatomical profile. The predictive performances are robust within the training cohort (10-fold cross-validation, AUC = 1.0) and accurately identify all WS individuals in an independent child WS cohort (seven WS, 59 children with diverse developmental status, AUC = 1.0). The WS-specific neuroanatomical profile includes measurements in the orbitofrontal cortex, superior parietal cortex, Sylvian fissures, and basal ganglia, and variability within these areas related to the underlying size of hemizygous deletion in patients with partial deletions. The profile intensity mediated the overall cognitive impairment as well as personality features related to hypersociability. Our results imply that the unique behaviors in WS were mediated through the constellation of abnormalities in cortical-subcortical circuitry consistent in child WS and adult WS. The robustness of the derived WS-specific neuroanatomical profile also demonstrates the potential utility of our approach in both clinical and research applications.

American Research on the Family and Socialization

ERIC Educational Resources Information Center

Clausen, John A.

1978-01-01

Comments on a number of trends in American research on the family as an instrument of socialization, stressing studies of contextual and structural features more than studies seeking to delineate relationships between specific parental practices and child behavior. (BR)

Detection and analysis of diamond fingerprinting feature and its application

NASA Astrophysics Data System (ADS)

Li, Xin; Huang, Guoliang; Li, Qiang; Chen, Shengyi

2011-01-01

Before becoming a jewelry diamonds need to be carved artistically with some special geometric features as the structure of the polyhedron. There are subtle differences in the structure of this polyhedron in each diamond. With the spatial frequency spectrum analysis of diamond surface structure, we can obtain the diamond fingerprint information which represents the "Diamond ID" and has good specificity. Based on the optical Fourier Transform spatial spectrum analysis, the fingerprinting identification of surface structure of diamond in spatial frequency domain was studied in this paper. We constructed both the completely coherent diamond fingerprinting detection system illuminated by laser and the partially coherent diamond fingerprinting detection system illuminated by led, and analyzed the effect of the coherence of light source to the diamond fingerprinting feature. We studied rotation invariance and translation invariance of the diamond fingerprinting and verified the feasibility of real-time and accurate identification of diamond fingerprint. With the profit of this work, we can provide customs, jewelers and consumers with a real-time and reliable diamonds identification instrument, which will curb diamond smuggling, theft and other crimes, and ensure the healthy development of the diamond industry.

Some design constraints required for the assembly of software components: The incorporation of atomic abstract types into generically structured abstract types

NASA Technical Reports Server (NTRS)

Johnson, Charles S.

1986-01-01

It is nearly axiomatic, that to take the greatest advantage of the useful features available in a development system, and to avoid the negative interactions of those features, requires the exercise of a design methodology which constrains their use. A major design support feature of the Ada language is abstraction: for data, functions processes, resources, and system elements in general. Atomic abstract types can be created in packages defining those private types and all of the overloaded operators, functions, and hidden data required for their use in an application. Generically structured abstract types can be created in generic packages defining those structured private types, as buildups from the user-defined data types which are input as parameters. A study is made of the design constraints required for software incorporating either atomic or generically structured abstract types, if the integration of software components based on them is to be subsequently performed. The impact of these techniques on the reusability of software and the creation of project-specific software support environments is also discussed.

3D flower-like hierarchical Ag@nickel-cobalt hydroxide microsphere with enhanced electrochemical properties

NASA Astrophysics Data System (ADS)

Lv, Zijian; Zhong, Qin; Bu, Yunfei; Wu, Junpeng

2016-10-01

The morphology and electrical conductivity are essential to electrochemical performance of electrode materials in renewable energy conversion and storage technologies such as fuel cells and supercapacitors. Here, we explored a facile method to grow Ag@nickel-cobalt layered double hydroxide (Ag@Ni/Co-LDHs) with 3D flower-like microsphere structure. The results show the morphology of Ni/Co-LDHs varies with the introduction of Ag species. The prepared Ag@Ni/Co-LDHs not only exhibits an open hierarchical structure with high specific capacitance but also shows good electrical conductivity to support fast electron transport. Benefiting from the unique structural features, these flower-like Ag@Ni/Co-LDHs microspheres have impressive specific capacitance as high as 1768 F g-1 at 1 A g-1. It can be concluded that engineering the structure of the electrode can increase the efficiency of the specific capacitance as a battery-type electrode for hybrid supercapacitors.

Challenging the state of the art in protein structure prediction: Highlights of experimental target structures for the 10th Critical Assessment of Techniques for Protein Structure Prediction Experiment CASP10.

PubMed

Kryshtafovych, Andriy; Moult, John; Bales, Patrick; Bazan, J Fernando; Biasini, Marco; Burgin, Alex; Chen, Chen; Cochran, Frank V; Craig, Timothy K; Das, Rhiju; Fass, Deborah; Garcia-Doval, Carmela; Herzberg, Osnat; Lorimer, Donald; Luecke, Hartmut; Ma, Xiaolei; Nelson, Daniel C; van Raaij, Mark J; Rohwer, Forest; Segall, Anca; Seguritan, Victor; Zeth, Kornelius; Schwede, Torsten

2014-02-01

For the last two decades, CASP has assessed the state of the art in techniques for protein structure prediction and identified areas which required further development. CASP would not have been possible without the prediction targets provided by the experimental structural biology community. In the latest experiment, CASP10, more than 100 structures were suggested as prediction targets, some of which appeared to be extraordinarily difficult for modeling. In this article, authors of some of the most challenging targets discuss which specific scientific question motivated the experimental structure determination of the target protein, which structural features were especially interesting from a structural or functional perspective, and to what extent these features were correctly reproduced in the predictions submitted to CASP10. Specifically, the following targets will be presented: the acid-gated urea channel, a difficult to predict transmembrane protein from the important human pathogen Helicobacter pylori; the structure of human interleukin (IL)-34, a recently discovered helical cytokine; the structure of a functionally uncharacterized enzyme OrfY from Thermoproteus tenax formed by a gene duplication and a novel fold; an ORFan domain of mimivirus sulfhydryl oxidase R596; the fiber protein gene product 17 from bacteriophage T7; the bacteriophage CBA-120 tailspike protein; a virus coat protein from metagenomic samples of the marine environment; and finally, an unprecedented class of structure prediction targets based on engineered disulfide-rich small proteins. Copyright © 2013 The Authors. Wiley Periodicals, Inc.

Cartilage Tissue Engineering with Silk Fibroin Scaffolds Fabricated by Indirect Additive Manufacturing Technology.

PubMed

Chen, Chih-Hao; Liu, Jolene Mei-Jun; Chua, Chee-Kai; Chou, Siaw-Meng; Shyu, Victor Bong-Hang; Chen, Jyh-Ping

2014-03-13

Advanced tissue engineering (TE) technology based on additive manufacturing (AM) can fabricate scaffolds with a three-dimensional (3D) environment suitable for cartilage regeneration. Specifically, AM technology may allow the incorporation of complex architectural features. The present study involves the fabrication of 3D TE scaffolds by an indirect AM approach using silk fibroin (SF). From scanning electron microscopic observations, the presence of micro-pores and interconnected channels within the scaffold could be verified, resulting in a TE scaffold with both micro- and macro-structural features. The intrinsic properties, such as the chemical structure and thermal characteristics of SF, were preserved after the indirect AM manufacturing process. In vitro cell culture within the SF scaffold using porcine articular chondrocytes showed a steady increase in cell numbers up to Day 14. The specific production (per cell basis) of the cartilage-specific extracellular matrix component (collagen Type II) was enhanced with culture time up to 12 weeks, indicating the re-differentiation of chondrocytes within the scaffold. Subcutaneous implantation of the scaffold-chondrocyte constructs in nude mice also confirmed the formation of ectopic cartilage by histological examination and immunostaining.

Molecular Basis of Substrate Recognition and Degradation by Human Presequence Protease

PubMed Central

King, John V.; Liang, Wenguang G.; Scherpelz, Kathryn P.; Schilling, Alexander B.; Meredith, Stephen C.; Tang, Wei-Jen

2014-01-01

Summary Human Presequence Protease (hPreP) is an M16 metalloprotease localized in mitochondria. There, hPreP facilitates proteostasis by utilizing a ∼13,300Å3 catalytic chamber to degrade a diverse array of potentially toxic peptides, including mitochondrial presequences and amyloid-β (Aβ), the latter of which contributes to Alzheimer's disease pathogenesis. Here we report crystal structures for hPreP alone and in complex with Aβ, which show that hPreP uses size-exclusion and charge complementation for substrate recognition. These structures also reveal hPreP-specific features that permit a diverse array of peptides, with distinct distributions of charged and hydrophobic residues, to be specifically captured, cleaved, and their amyloidogenic features destroyed. SAXS analysis demonstrates that hPreP in solution exists in dynamic equilibrium between closed and open states, with the former being preferred. Furthermore, Aβ binding induces the closed state and hPreP dimerization. Together, these data reveal the molecular basis for flexible yet specific substrate recognition and degradation by hPreP. PMID:24931469

ANALYSIS OF CLINICAL AND DERMOSCOPIC FEATURES FOR BASAL CELL CARCINOMA NEURAL NETWORK CLASSIFICATION

PubMed Central

Cheng, Beibei; Stanley, R. Joe; Stoecker, William V; Stricklin, Sherea M.; Hinton, Kristen A.; Nguyen, Thanh K.; Rader, Ryan K.; Rabinovitz, Harold S.; Oliviero, Margaret; Moss, Randy H.

2012-01-01

Background Basal cell carcinoma (BCC) is the most commonly diagnosed cancer in the United States. In this research, we examine four different feature categories used for diagnostic decisions, including patient personal profile (patient age, gender, etc.), general exam (lesion size and location), common dermoscopic (blue-gray ovoids, leaf-structure dirt trails, etc.), and specific dermoscopic lesion (white/pink areas, semitranslucency, etc.). Specific dermoscopic features are more restricted versions of the common dermoscopic features. Methods Combinations of the four feature categories are analyzed over a data set of 700 lesions, with 350 BCCs and 350 benign lesions, for lesion discrimination using neural network-based techniques, including Evolving Artificial Neural Networks and Evolving Artificial Neural Network Ensembles. Results Experiment results based on ten-fold cross validation for training and testing the different neural network-based techniques yielded an area under the receiver operating characteristic curve as high as 0.981 when all features were combined. The common dermoscopic lesion features generally yielded higher discrimination results than other individual feature categories. Conclusions Experimental results show that combining clinical and image information provides enhanced lesion discrimination capability over either information source separately. This research highlights the potential of data fusion as a model for the diagnostic process. PMID:22724561

A local structure model for network analysis

DOE PAGES

Casleton, Emily; Nordman, Daniel; Kaiser, Mark

2017-04-01

The statistical analysis of networks is a popular research topic with ever widening applications. Exponential random graph models (ERGMs), which specify a model through interpretable, global network features, are common for this purpose. In this study we introduce a new class of models for network analysis, called local structure graph models (LSGMs). In contrast to an ERGM, a LSGM specifies a network model through local features and allows for an interpretable and controllable local dependence structure. In particular, LSGMs are formulated by a set of full conditional distributions for each network edge, e.g., the probability of edge presence/absence, depending onmore » neighborhoods of other edges. Additional model features are introduced to aid in specification and to help alleviate a common issue (occurring also with ERGMs) of model degeneracy. Finally, the proposed models are demonstrated on a network of tornadoes in Arkansas where a LSGM is shown to perform significantly better than a model without local dependence.« less

A local structure model for network analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Casleton, Emily; Nordman, Daniel; Kaiser, Mark

The statistical analysis of networks is a popular research topic with ever widening applications. Exponential random graph models (ERGMs), which specify a model through interpretable, global network features, are common for this purpose. In this study we introduce a new class of models for network analysis, called local structure graph models (LSGMs). In contrast to an ERGM, a LSGM specifies a network model through local features and allows for an interpretable and controllable local dependence structure. In particular, LSGMs are formulated by a set of full conditional distributions for each network edge, e.g., the probability of edge presence/absence, depending onmore » neighborhoods of other edges. Additional model features are introduced to aid in specification and to help alleviate a common issue (occurring also with ERGMs) of model degeneracy. Finally, the proposed models are demonstrated on a network of tornadoes in Arkansas where a LSGM is shown to perform significantly better than a model without local dependence.« less

The Distribution of the Informative Intensity of the Text in Terms of its Structure (On Materials of the English Texts in the Mining Sphere)

NASA Astrophysics Data System (ADS)

Znikina, Ludmila; Rozhneva, Elena

2017-11-01

The article deals with the distribution of informative intensity of the English-language scientific text based on its structural features contributing to the process of formalization of the scientific text and the preservation of the adequacy of the text with derived semantic information in relation to the primary. Discourse analysis is built on specific compositional and meaningful examples of scientific texts taken from the mining field. It also analyzes the adequacy of the translation of foreign texts into another language, the relationships between elements of linguistic systems, the degree of a formal conformance, translation with the specific objectives and information needs of the recipient. Some key words and ideas are emphasized in the paragraphs of the English-language mining scientific texts. The article gives the characteristic features of the structure of paragraphs of technical text and examples of constructions in English scientific texts based on a mining theme with the aim to explain the possible ways of their adequate translation.

Using landscape topology to compare continuous metaheuristics: a framework and case study on EDAs and ridge structure.

PubMed

Morgan, R; Gallagher, M

2012-01-01

In this paper we extend a previously proposed randomized landscape generator in combination with a comparative experimental methodology to study the behavior of continuous metaheuristic optimization algorithms. In particular, we generate two-dimensional landscapes with parameterized, linear ridge structure, and perform pairwise comparisons of algorithms to gain insight into what kind of problems are easy and difficult for one algorithm instance relative to another. We apply this methodology to investigate the specific issue of explicit dependency modeling in simple continuous estimation of distribution algorithms. Experimental results reveal specific examples of landscapes (with certain identifiable features) where dependency modeling is useful, harmful, or has little impact on mean algorithm performance. Heat maps are used to compare algorithm performance over a large number of landscape instances and algorithm trials. Finally, we perform a meta-search in the landscape parameter space to find landscapes which maximize the performance between algorithms. The results are related to some previous intuition about the behavior of these algorithms, but at the same time lead to new insights into the relationship between dependency modeling in EDAs and the structure of the problem landscape. The landscape generator and overall methodology are quite general and extendable and can be used to examine specific features of other algorithms.

Comparative interactomics provides evidence for functional specialization of the nuclear pore complex.

PubMed

Obado, Samson O; Field, Mark C; Rout, Michael P

2017-07-04

The core architecture of the eukaryotic cell was established well over one billion years ago, and is largely retained in all extant lineages. However, eukaryotic cells also possess lineage-specific features, frequently keyed to specific functional requirements. One quintessential core eukaryotic structure is the nuclear pore complex (NPC), responsible for regulating exchange of macromolecules between the nucleus and cytoplasm as well as acting as a nuclear organizational hub. NPC architecture has been best documented in one eukaryotic supergroup, the Opisthokonts (e.g. Saccharomyces cerevisiae and Homo sapiens), which although compositionally similar, have significant variations in certain NPC subcomplex structures. The variation of NPC structure across other taxa in the eukaryotic kingdom however, remains poorly understood. We explored trypanosomes, highly divergent organisms, and mapped and assigned their NPC proteins to specific substructures to reveal their NPC architecture. We showed that the NPC central structural scaffold is conserved, likely across all eukaryotes, but more peripheral elements can exhibit very significant lineage-specific losses, duplications or other alterations in their components. Amazingly, trypanosomes lack the major components of the mRNA export platform that are asymmetrically localized within yeast and vertebrate NPCs. Concomitant with this, the trypanosome NPC is ALMOST completely symmetric with the nuclear basket being the only major source of asymmetry. We suggest these features point toward a stepwise evolution of the NPC in which a coating scaffold first stabilized the pore after which selective gating emerged and expanded, leading to the addition of peripheral remodeling machineries on the nucleoplasmic and cytoplasmic sides of the pore.

Crystal Structure of a UDP-glucose-specific Glycosyltransferase from a Mycobacterium Species

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fulton, Zara; McAlister, Adrian; Wilce, Matthew C.J.

2008-10-24

Glycosyltransferases (GTs) are a large and ubiquitous family of enzymes that specifically transfer sugar moieties to a range of substrates. Mycobacterium tuberculosis contains a large number of GTs, many of which are implicated in cell wall synthesis, yet the majority of these GTs remain poorly characterized. Here, we report the high resolution crystal structures of an essential GT (MAP2569c) from Mycobacterium avium subsp. paratuberculosis (a close homologue of Rv1208 from M. tuberculosis) in its apo- and ligand-bound forms. The structure adopted the GT-A fold and possessed the characteristic DXD motif that coordinated an Mn{sup 2+} ion. Atypical of most GTsmore » characterized to date, MAP2569c exhibited specificity toward the donor substrate, UDP-glucose. The structure of this ligated complex revealed an induced fit binding mechanism and provided a basis for this unique specificity. Collectively, the structural features suggested that MAP2569c may adopt a 'retaining' enzymatic mechanism, which has implications for the classification of other GTs in this large superfamily.« less

A Method for WD40 Repeat Detection and Secondary Structure Prediction

PubMed Central

Wang, Yang; Jiang, Fan; Zhuo, Zhu; Wu, Xian-Hui; Wu, Yun-Dong

2013-01-01

WD40-repeat proteins (WD40s), as one of the largest protein families in eukaryotes, play vital roles in assembling protein-protein/DNA/RNA complexes. WD40s fold into similar β-propeller structures despite diversified sequences. A program WDSP (WD40 repeat protein Structure Predictor) has been developed to accurately identify WD40 repeats and predict their secondary structures. The method is designed specifically for WD40 proteins by incorporating both local residue information and non-local family-specific structural features. It overcomes the problem of highly diversified protein sequences and variable loops. In addition, WDSP achieves a better prediction in identifying multiple WD40-domain proteins by taking the global combination of repeats into consideration. In secondary structure prediction, the average Q3 accuracy of WDSP in jack-knife test reaches 93.7%. A disease related protein LRRK2 was used as a representive example to demonstrate the structure prediction. PMID:23776530

Discriminative analysis of schizophrenia using support vector machine and recursive feature elimination on structural MRI images.

PubMed

Lu, Xiaobing; Yang, Yongzhe; Wu, Fengchun; Gao, Minjian; Xu, Yong; Zhang, Yue; Yao, Yongcheng; Du, Xin; Li, Chengwei; Wu, Lei; Zhong, Xiaomei; Zhou, Yanling; Fan, Ni; Zheng, Yingjun; Xiong, Dongsheng; Peng, Hongjun; Escudero, Javier; Huang, Biao; Li, Xiaobo; Ning, Yuping; Wu, Kai

2016-07-01

Structural abnormalities in schizophrenia (SZ) patients have been well documented with structural magnetic resonance imaging (MRI) data using voxel-based morphometry (VBM) and region of interest (ROI) analyses. However, these analyses can only detect group-wise differences and thus, have a poor predictive value for individuals. In the present study, we applied a machine learning method that combined support vector machine (SVM) with recursive feature elimination (RFE) to discriminate SZ patients from normal controls (NCs) using their structural MRI data. We first employed both VBM and ROI analyses to compare gray matter volume (GMV) and white matter volume (WMV) between 41 SZ patients and 42 age- and sex-matched NCs. The method of SVM combined with RFE was used to discriminate SZ patients from NCs using significant between-group differences in both GMV and WMV as input features. We found that SZ patients showed GM and WM abnormalities in several brain structures primarily involved in the emotion, memory, and visual systems. An SVM with a RFE classifier using the significant structural abnormalities identified by the VBM analysis as input features achieved the best performance (an accuracy of 88.4%, a sensitivity of 91.9%, and a specificity of 84.4%) in the discriminative analyses of SZ patients. These results suggested that distinct neuroanatomical profiles associated with SZ patients might provide a potential biomarker for disease diagnosis, and machine-learning methods can reveal neurobiological mechanisms in psychiatric diseases.

Site-specific characterization of beetle horn shell with micromechanical bending test in focused ion beam system.

PubMed

Lee, Hyun-Taek; Kim, Ho-Jin; Kim, Chung-Soo; Gomi, Kenji; Taya, Minoru; Nomura, Shûhei; Ahn, Sung-Hoon

2017-07-15

Biological materials are the result of years of evolution and possess a number of efficient features and structures. Researchers have investigated the possibility of designing biomedical structures that take advantage of these structural features. Insect shells, such as beetle shells, are among the most promising types of biological material for biomimetic development. However, due to their intricate geometries and small sizes, it is challenging to measure the mechanical properties of these microscale structures. In this study, we developed an in-situ testing platform for site-specific experiments in a focused ion beam (FIB) system. Multi-axis nano-manipulators and a micro-force sensor were utilized in the testing platform to allow better results in the sample preparation and data acquisition. The entire test protocol, consisting of locating sample, ion beam milling and micro-mechanical bending tests, can be carried out without sample transfer or reattachment. We used our newly devised test platform to evaluate the micromechanical properties and structural features of each separated layer of the beetle horn shell. The Young's modulus of both the exocuticle and endocuticle layers was measured. We carried out a bending test to characterize the layers mechanically. The exocuticle layer bent in a brick-like manner, while the endocuticle layer exhibited a crack blunting effect. This paper proposed an in-situ manipulation/test method in focused ion beam for characterizing micromechanical properties of beetle horn shell. The challenge in precise and accurate fabrication for the samples with complex geometry was overcome by using nano-manipulators having multi-degree of freedom and a micro-gripper. With the aid of this specially designed test platform, bending tests were carried out on cantilever-shaped samples prepared by focused ion beam milling. Structural differences between exocuticle and endocuticle layers of beetle horn shell were explored and the results provided insight into the structural advantages of each biocomposite structure. Copyright © 2017 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Requirements Specification Language (RSL) and supporting tools

NASA Technical Reports Server (NTRS)

Frincke, Deborah; Wolber, Dave; Fisher, Gene; Cohen, Gerald C.

1992-01-01

This document describes a general purpose Requirement Specification Language (RSL). RSL is a hybrid of features found in several popular requirement specification languages. The purpose of RSL is to describe precisely the external structure of a system comprised of hardware, software, and human processing elements. To overcome the deficiencies of informal specification languages, RSL includes facilities for mathematical specification. Two RSL interface tools are described. The Browser view contains a complete document with all details of the objects and operations. The Dataflow view is a specialized, operation-centered depiction of a specification that shows how specified operations relate in terms of inputs and outputs.

Proepileptic patterns in EEG of WAG/Rij rats

NASA Astrophysics Data System (ADS)

Grubov, Vadim V.; Sitnikova, Evgenia Yu.; Nedaivozov, Vladimir O.; Koronovskii, Alexey A.

2018-04-01

In this paper we study specific oscillatory patterns on EEG signals of WAG/Rij rats. These patterns are known as proepileptic because they occur in time period during the development of absence-epilepsy before fully-formed epileptic seizures. In the paper we analyze EEG signals of WAG/Rij rats with continuous wavelet transform and empirical mode decomposition in order to find particular features of epileptic spike-wave discharges and nonepileptic sleep spindles. Then we introduce proepileptic activity as patterns that combine features of epileptic and non-epileptic activity. We analyze proepileptic activity in order to specify its features and time-frequency structure.

Volcanic features of Hawaii. A basis for comparison with Mars

NASA Technical Reports Server (NTRS)

Carr, M. H.; Greeley, R.

1980-01-01

Despite the difference in size Martian and Hawaiian volcanoes have numerous characteristics in common. Specific features such as lava channels, collapsed lava tubes, levees and flow fronts, all very common in Hawaii, are also abundant on the flanks of some of the Martian volcanoes. Striking differences also exist, such as the apparent lack of radial rift zones on some Martian volcanoes and the paucity of cinder and spatter cones. Some of the best photographs of Martian and Hawaiian volcanic features are presented. Descriptive legends are provided for each picture. An overview of the geological processes and structures depicted is included.

Legume Lectins: Proteins with Diverse Applications

PubMed Central

Lagarda-Diaz, Irlanda; Guzman-Partida, Ana Maria; Vazquez-Moreno, Luz

2017-01-01

Lectins are a diverse class of proteins distributed extensively in nature. Among these proteins; legume lectins display a variety of interesting features including antimicrobial; insecticidal and antitumor activities. Because lectins recognize and bind to specific glycoconjugates present on the surface of cells and intracellular structures; they can serve as potential target molecules for developing practical applications in the fields of food; agriculture; health and pharmaceutical research. This review presents the current knowledge of the main structural characteristics of legume lectins and the relationship of structure to the exhibited specificities; provides an overview of their particular antimicrobial; insecticidal and antitumor biological activities and describes possible applications based on the pattern of recognized glyco-targets. PMID:28604616

Nanoscale organization in the fluorinated room temperature ionic liquid: Tetraethyl ammonium (trifluoromethanesulfonyl)(nonafluorobutylsulfonyl)imide

NASA Astrophysics Data System (ADS)

Lo Celso, F.; Appetecchi, G. B.; Jafta, C. J.; Gontrani, L.; Canongia Lopes, J. N.; Triolo, A.; Russina, O.

2018-05-01

Fluorinated Room Temperature Ionic Liquids (FRTILs) are a branch of ionic liquids that is the object of growing interest for a wide range of potential applications, due to the synergic combination of specifically ionic features and those properties that stem from fluorous tails. So far limited experimental work exists on the micro- and mesoscopic structural organization in this class of compounds. Such a work is however necessary to fully understand morphological details at atomistic level that would have strong implications in terms of bulk properties. Here we use the synergy between X-ray and neutron scattering together with molecular dynamics simulations to access structural details of a technologically relevant FRTIL that is characterised by an anion bearing a long enough fluorinated tail to develop specific morphological features. In particular, we find the first experimental evidence that in FRTILs bearing an asymmetric bis(perfluoroalkyl)sulfonyl-imide anion, fluorous side chains tend to be spatially segregated into nm-scale spatial heterogeneities. This feature together with the well-established micro-segregation of side alkyl chains in conventional RTILs leads to the concept of triphilic ILs, whose technological applications are yet to be fully developed.

Predictive brain networks for major depression in a semi-multimodal fusion hierarchical feature reduction framework.

PubMed

Yang, Jie; Yin, Yingying; Zhang, Zuping; Long, Jun; Dong, Jian; Zhang, Yuqun; Xu, Zhi; Li, Lei; Liu, Jie; Yuan, Yonggui

2018-02-05

Major depressive disorder (MDD) is characterized by dysregulation of distributed structural and functional networks. It is now recognized that structural and functional networks are related at multiple temporal scales. The recent emergence of multimodal fusion methods has made it possible to comprehensively and systematically investigate brain networks and thereby provide essential information for influencing disease diagnosis and prognosis. However, such investigations are hampered by the inconsistent dimensionality features between structural and functional networks. Thus, a semi-multimodal fusion hierarchical feature reduction framework is proposed. Feature reduction is a vital procedure in classification that can be used to eliminate irrelevant and redundant information and thereby improve the accuracy of disease diagnosis. Our proposed framework primarily consists of two steps. The first step considers the connection distances in both structural and functional networks between MDD and healthy control (HC) groups. By adding a constraint based on sparsity regularization, the second step fully utilizes the inter-relationship between the two modalities. However, in contrast to conventional multi-modality multi-task methods, the structural networks were considered to play only a subsidiary role in feature reduction and were not included in the following classification. The proposed method achieved a classification accuracy, specificity, sensitivity, and area under the curve of 84.91%, 88.6%, 81.29%, and 0.91, respectively. Moreover, the frontal-limbic system contributed the most to disease diagnosis. Importantly, by taking full advantage of the complementary information from multimodal neuroimaging data, the selected consensus connections may be highly reliable biomarkers of MDD. Copyright © 2017 Elsevier B.V. All rights reserved.

Prediction of phenotypes of missense mutations in human proteins from biological assemblies.

PubMed

Wei, Qiong; Xu, Qifang; Dunbrack, Roland L

2013-02-01

Single nucleotide polymorphisms (SNPs) are the most frequent variation in the human genome. Nonsynonymous SNPs that lead to missense mutations can be neutral or deleterious, and several computational methods have been presented that predict the phenotype of human missense mutations. These methods use sequence-based and structure-based features in various combinations, relying on different statistical distributions of these features for deleterious and neutral mutations. One structure-based feature that has not been studied significantly is the accessible surface area within biologically relevant oligomeric assemblies. These assemblies are different from the crystallographic asymmetric unit for more than half of X-ray crystal structures. We find that mutations in the core of proteins or in the interfaces in biological assemblies are significantly more likely to be disease-associated than those on the surface of the biological assemblies. For structures with more than one protein in the biological assembly (whether the same sequence or different), we find the accessible surface area from biological assemblies provides a statistically significant improvement in prediction over the accessible surface area of monomers from protein crystal structures (P = 6e-5). When adding this information to sequence-based features such as the difference between wildtype and mutant position-specific profile scores, the improvement from biological assemblies is statistically significant but much smaller (P = 0.018). Combining this information with sequence-based features in a support vector machine leads to 82% accuracy on a balanced dataset of 50% disease-associated mutations from SwissVar and 50% neutral mutations from human/primate sequence differences in orthologous proteins. Copyright © 2012 Wiley Periodicals, Inc.

DNAproDB: an interactive tool for structural analysis of DNA–protein complexes

PubMed Central

Sagendorf, Jared M.

2017-01-01

Abstract Many biological processes are mediated by complex interactions between DNA and proteins. Transcription factors, various polymerases, nucleases and histones recognize and bind DNA with different levels of binding specificity. To understand the physical mechanisms that allow proteins to recognize DNA and achieve their biological functions, it is important to analyze structures of DNA–protein complexes in detail. DNAproDB is a web-based interactive tool designed to help researchers study these complexes. DNAproDB provides an automated structure-processing pipeline that extracts structural features from DNA–protein complexes. The extracted features are organized in structured data files, which are easily parsed with any programming language or viewed in a browser. We processed a large number of DNA–protein complexes retrieved from the Protein Data Bank and created the DNAproDB database to store this data. Users can search the database by combining features of the DNA, protein or DNA–protein interactions at the interface. Additionally, users can upload their own structures for processing privately and securely. DNAproDB provides several interactive and customizable tools for creating visualizations of the DNA–protein interface at different levels of abstraction that can be exported as high quality figures. All functionality is documented and freely accessible at http://dnaprodb.usc.edu. PMID:28431131

Segmenting Brain Tissues from Chinese Visible Human Dataset by Deep-Learned Features with Stacked Autoencoder

PubMed Central

Zhao, Guangjun; Wang, Xuchu; Niu, Yanmin; Tan, Liwen; Zhang, Shao-Xiang

2016-01-01

Cryosection brain images in Chinese Visible Human (CVH) dataset contain rich anatomical structure information of tissues because of its high resolution (e.g., 0.167 mm per pixel). Fast and accurate segmentation of these images into white matter, gray matter, and cerebrospinal fluid plays a critical role in analyzing and measuring the anatomical structures of human brain. However, most existing automated segmentation methods are designed for computed tomography or magnetic resonance imaging data, and they may not be applicable for cryosection images due to the imaging difference. In this paper, we propose a supervised learning-based CVH brain tissues segmentation method that uses stacked autoencoder (SAE) to automatically learn the deep feature representations. Specifically, our model includes two successive parts where two three-layer SAEs take image patches as input to learn the complex anatomical feature representation, and then these features are sent to Softmax classifier for inferring the labels. Experimental results validated the effectiveness of our method and showed that it outperformed four other classical brain tissue detection strategies. Furthermore, we reconstructed three-dimensional surfaces of these tissues, which show their potential in exploring the high-resolution anatomical structures of human brain. PMID:27057543

Segmenting Brain Tissues from Chinese Visible Human Dataset by Deep-Learned Features with Stacked Autoencoder.

PubMed

Zhao, Guangjun; Wang, Xuchu; Niu, Yanmin; Tan, Liwen; Zhang, Shao-Xiang

2016-01-01

Cryosection brain images in Chinese Visible Human (CVH) dataset contain rich anatomical structure information of tissues because of its high resolution (e.g., 0.167 mm per pixel). Fast and accurate segmentation of these images into white matter, gray matter, and cerebrospinal fluid plays a critical role in analyzing and measuring the anatomical structures of human brain. However, most existing automated segmentation methods are designed for computed tomography or magnetic resonance imaging data, and they may not be applicable for cryosection images due to the imaging difference. In this paper, we propose a supervised learning-based CVH brain tissues segmentation method that uses stacked autoencoder (SAE) to automatically learn the deep feature representations. Specifically, our model includes two successive parts where two three-layer SAEs take image patches as input to learn the complex anatomical feature representation, and then these features are sent to Softmax classifier for inferring the labels. Experimental results validated the effectiveness of our method and showed that it outperformed four other classical brain tissue detection strategies. Furthermore, we reconstructed three-dimensional surfaces of these tissues, which show their potential in exploring the high-resolution anatomical structures of human brain.

Substrate specificity of the ubiquitin and Ubl proteases

PubMed Central

Ronau, Judith A; Beckmann, John F; Hochstrasser, Mark

2016-01-01

Conjugation and deconjugation of ubiquitin and ubiquitin-like proteins (Ubls) to cellular proteins are highly regulated processes integral to cellular homeostasis. Most often, the C-termini of these small polypeptides are attached to lysine side chains of target proteins by an amide (isopeptide) linkage. Deubiquitinating enzymes (DUBs) and Ubl-specific proteases (ULPs) comprise a diverse group of proteases that recognize and remove ubiquitin and Ubls from their substrates. How DUBs and ULPs distinguish among different modifiers, or different polymeric forms of these modifiers, remains poorly understood. The specificity of ubiquitin/Ubl-deconjugating enzymes for particular substrates depends on multiple factors, ranging from the topography of specific substrate features, as in different polyubiquitin chain types, to structural elements unique to each enzyme. Here we summarize recent structural and biochemical studies that provide insights into mechanisms of substrate specificity among various DUBs and ULPs. We also discuss the unexpected specificities of non-eukaryotic proteases in these families. PMID:27012468

Calculation and Specification of the Multiple Chirality Displayed by Sugar Pyranoid Ring Structures.

ERIC Educational Resources Information Center

Shallenberger, Robert S.; And Others

1981-01-01

Describes a method, using simple algebraic notation, for calculating the nature of the salient features of a sugar pyranoid ring, the steric disposition of substituents about the reference, and the anomeric carbon atoms contained within the ring. (CS)

Transforming Administration in Academic Libraries.

ERIC Educational Resources Information Center

Honea, Sion M.

1997-01-01

Examines the traditional hierarchical administrative structure in academic libraries. Also analyzes some of its features, and questions specific principles of management in order to propose a more balanced organizational type based on organizational behavior and leadership that will best enable academic libraries to meet challenges. (PEN)

Specific features of the cathodoluminescence spectra of AlInGaN QWs, caused by the influence of phase separation and internal electric fields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kuznetsova, Ya. V., E-mail: yana@mail.ioffe.ru; Jmerik, V. N.; Nechaev, D. V.

2016-07-15

The specific features of the cathodoluminescence (CL) spectra in AlInGaN heterostructures, caused by the influence of phase separation and internal electric fields, observed at varied CL excitation density, are studied. It is shown that the evolution of the CL spectrum and the variation in the spectral position of emission lines of nanoscale layers with current density in the primary electron beam makes it possible to identify the occurrence of phase separation in the layer and, in the absence of this separation, to estimate the electric-field strength in the active region of the structure.

Discovering rules for protein-ligand specificity using support vector inductive logic programming.

PubMed

Kelley, Lawrence A; Shrimpton, Paul J; Muggleton, Stephen H; Sternberg, Michael J E

2009-09-01

Structural genomics initiatives are rapidly generating vast numbers of protein structures. Comparative modelling is also capable of producing accurate structural models for many protein sequences. However, for many of the known structures, functions are not yet determined, and in many modelling tasks, an accurate structural model does not necessarily tell us about function. Thus, there is a pressing need for high-throughput methods for determining function from structure. The spatial arrangement of key amino acids in a folded protein, on the surface or buried in clefts, is often the determinants of its biological function. A central aim of molecular biology is to understand the relationship between such substructures or surfaces and biological function, leading both to function prediction and to function design. We present a new general method for discovering the features of binding pockets that confer specificity for particular ligands. Using a recently developed machine-learning technique which couples the rule-discovery approach of inductive logic programming with the statistical learning power of support vector machines, we are able to discriminate, with high precision (90%) and recall (86%) between pockets that bind FAD and those that bind NAD on a large benchmark set given only the geometry and composition of the backbone of the binding pocket without the use of docking. In addition, we learn rules governing this specificity which can feed into protein functional design protocols. An analysis of the rules found suggests that key features of the binding pocket may be tied to conformational freedom in the ligand. The representation is sufficiently general to be applicable to any discriminatory binding problem. All programs and data sets are freely available to non-commercial users at http://www.sbg.bio.ic.ac.uk/svilp_ligand/.

Structural and functional studies of a 50 kDa antigenic protein from Salmonella enterica serovar Typhi.

PubMed

Choong, Yee Siew; Lim, Theam Soon; Chew, Ai Lan; Aziah, Ismail; Ismail, Asma

2011-04-01

The high typhoid incidence rate in developing and under-developed countries emphasizes the need for a rapid, affordable and accessible diagnostic test for effective therapy and disease management. TYPHIDOT®, a rapid dot enzyme immunoassay test for typhoid, was developed from the discovery of a ∼50 kDa protein specific for Salmonella enterica serovar Typhi. However, the structure of this antigen remains unknown till today. Studies on the structure of this antigen are important to elucidate its function, which will in turn increase the efficiency of the development and improvement of the typhoid detection test. This paper described the predictive structure and function of the antigenically specific protein. The homology modeling approach was employed to construct the three-dimensional structure of the antigen. The built structure possesses the features of TolC-like outer membrane protein. Molecular docking simulation was also performed to further probe the functionality of the antigen. Docking results showed that hexamminecobalt, Co(NH(3))(6)(3+), as an inhibitor of TolC protein, formed favorable hydrogen bonds with D368 and D371 of the antigen. The single point (D368A, D371A) and double point (D368A and D371A) mutations of the antigen showed a decrease (single point mutation) and loss (double point mutations) of binding affinity towards hexamminecobalt. The architecture features of the built model and the docking simulation reinforced and supported that this antigen is indeed the variant of outer membrane protein, TolC. As channel proteins are important for the virulence and survival of bacteria, therefore this ∼50 kDa channel protein is a good specific target for typhoid detection test. Copyright © 2011 Elsevier Inc. All rights reserved.

Bacterial chemoreceptors: high-performance signaling in networked arrays.

PubMed

Hazelbauer, Gerald L; Falke, Joseph J; Parkinson, John S

2008-01-01

Chemoreceptors are crucial components in the bacterial sensory systems that mediate chemotaxis. Chemotactic responses exhibit exquisite sensitivity, extensive dynamic range and precise adaptation. The mechanisms that mediate these high-performance functions involve not only actions of individual proteins but also interactions among clusters of components, localized in extensive patches of thousands of molecules. Recently, these patches have been imaged in native cells, important features of chemoreceptor structure and on-off switching have been identified, and new insights have been gained into the structural basis and functional consequences of higher order interactions among sensory components. These new data suggest multiple levels of molecular interactions, each of which contribute specific functional features and together create a sophisticated signaling device.

Bacterial chemoreceptors: high-performance signaling in networked arrays

PubMed Central

Hazelbauer, Gerald L.; Falke, Joseph J.; Parkinson, John S.

2010-01-01

Chemoreceptors are crucial components in the bacterial sensory systems that mediate chemotaxis. Chemotactic responses exhibit exquisite sensitivity, extensive dynamic range and precise adaptation. The mechanisms that mediate these high-performance functions involve not only actions of individual proteins but also interactions among clusters of components, localized in extensive patches of thousands of molecules. Recently, these patches have been imaged in native cells, important features of chemoreceptor structure and on–off switching have been identified, and new insights have been gained into the structural basis and functional consequences of higher order interactions among sensory components. These new data suggest multiple levels of molecular interactions, each of which contribute specific functional features and together create a sophisticated signaling device. PMID:18165013

TOMML: A Rule Language for Structured Data

NASA Astrophysics Data System (ADS)

Cirstea, Horatiu; Moreau, Pierre-Etienne; Reilles, Antoine

We present the TOM language that extends JAVA with the purpose of providing high level constructs inspired by the rewriting community. TOM bridges thus the gap between a general purpose language and high level specifications based on rewriting. This approach was motivated by the promotion of rule based techniques and their integration in large scale applications. Powerful matching capabilities along with a rich strategy language are among TOM's strong features that make it easy to use and competitive with respect to other rule based languages. TOM is thus a natural choice for querying and transforming structured data and in particular XML documents [1]. We present here its main XML oriented features and illustrate its use on several examples.

Area-specific temporal control of corticospinal motor neuron differentiation by COUP-TFI

PubMed Central

Tomassy, Giulio Srubek; De Leonibus, Elvira; Jabaudon, Denis; Lodato, Simona; Alfano, Christian; Mele, Andrea; Macklis, Jeffrey D.; Studer, Michèle

2010-01-01

Transcription factors with gradients of expression in neocortical progenitors give rise to distinct motor and sensory cortical areas by controlling the area-specific differentiation of distinct neuronal subtypes. However, the molecular mechanisms underlying this area-restricted control are still unclear. Here, we show that COUP-TFI controls the timing of birth and specification of corticospinal motor neurons (CSMN) in somatosensory cortex via repression of a CSMN differentiation program. Loss of COUP-TFI function causes an area-specific premature generation of neurons with cardinal features of CSMN, which project to subcerebral structures, including the spinal cord. Concurrently, genuine CSMN differentiate imprecisely and do not project beyond the pons, together resulting in impaired skilled motor function in adult mice with cortical COUP-TFI loss-of-function. Our findings indicate that COUP-TFI exerts critical areal and temporal control over the precise differentiation of CSMN during corticogenesis, thereby enabling the area-specific functional features of motor and sensory areas to arise. PMID:20133588

Multiresolution texture models for brain tumor segmentation in MRI.

PubMed

Iftekharuddin, Khan M; Ahmed, Shaheen; Hossen, Jakir

2011-01-01

In this study we discuss different types of texture features such as Fractal Dimension (FD) and Multifractional Brownian Motion (mBm) for estimating random structures and varying appearance of brain tissues and tumors in magnetic resonance images (MRI). We use different selection techniques including KullBack - Leibler Divergence (KLD) for ranking different texture and intensity features. We then exploit graph cut, self organizing maps (SOM) and expectation maximization (EM) techniques to fuse selected features for brain tumors segmentation in multimodality T1, T2, and FLAIR MRI. We use different similarity metrics to evaluate quality and robustness of these selected features for tumor segmentation in MRI for real pediatric patients. We also demonstrate a non-patient-specific automated tumor prediction scheme by using improved AdaBoost classification based on these image features.

Very high resolution Earth observation features for monitoring plant and animal community structure across multiple spatial scales in protected areas

NASA Astrophysics Data System (ADS)

Mairota, Paola; Cafarelli, Barbara; Labadessa, Rocco; Lovergine, Francesco; Tarantino, Cristina; Lucas, Richard M.; Nagendra, Harini; Didham, Raphael K.

2015-05-01

Monitoring the status and future trends in biodiversity can be prohibitively expensive using ground-based surveys. Consequently, significant effort is being invested in the use of satellite remote sensing to represent aspects of the proximate mechanisms (e.g., resource availability) that can be related to biodiversity surrogates (BS) such as species community descriptors. We explored the potential of very high resolution (VHR) satellite Earth observation (EO) features as proxies for habitat structural attributes that influence spatial variation in habitat quality and biodiversity change. In a semi-natural grassland mosaic of conservation concern in southern Italy, we employed a hierarchical nested sampling strategy to collect field and VHR-EO data across three spatial extent levels (landscape, patch and plot). Species incidence and abundance data were collected at the plot level for plant, insect and bird functional groups. Spectral and textural VHR-EO image features were derived from a Worldview-2 image. Three window sizes (grains) were tested for analysis and computation of textural features, guided by the perception limits of different organisms. The modelled relationships between VHR-EO features and BS responses differed across scales, suggesting that landscape, patch and plot levels are respectively most appropriate when dealing with birds, plants and insects. This research demonstrates the potential of VHR-EO for biodiversity mapping and habitat modelling, and highlights the importance of identifying the appropriate scale of analysis for specific taxonomic groups of interest. Further, textural features are important in the modelling of functional group-specific indices which represent BS in high conservation value habitat types, and provide a more direct link to species interaction networks and ecosystem functioning, than provided by traditional taxonomic diversity indices.

Summary of an integrated ERTS-1 project and its results at the Missouri Geological Survey

NASA Technical Reports Server (NTRS)

Martin, J. A.; Allen, W. H.; Rath, D. L.; Rueff, A.

1974-01-01

Use of the ERTS imagery involved the recognition and interpretation of various ground patterns. Analysis and application are tied to ongoing programs. Specific studies utilizing the imagery and NASA aircraft photography are: a statewide lake and dam inventory; assessment of flooding and floodprone areas along the Missouri portion of the Mississippi and Missouri Rivers; land-use classification for several counties; structural features in selected areas; and Pleistocene features in northern Missouri. Though it has been suggested that repetitive coverage is not necessary for geologic studies, it is this specific feature along with the synoptic view of large portions of the State that provided the potential for the utilization of the ERTS imagery in Missouri. Other State agencies, Departments of Conservation, Agriculture, and Community Affairs, have expressed interest in the potential application of ERTS data in their respective fields.

A Thermoacidophile-Specific Protein Family, DUF3211, Functions as a Fatty Acid Carrier with Novel Binding Mode

PubMed Central

Miyakawa, Takuya; Sawano, Yoriko; Miyazono, Ken-ichi; Miyauchi, Yumiko; Hatano, Ken-ichi

2013-01-01

STK_08120 is a member of the thermoacidophile-specific DUF3211 protein family from Sulfolobus tokodaii strain 7. Its molecular function remains obscure, and sequence similarities for obtaining functional remarks are not available. In this study, the crystal structure of STK_08120 was determined at 1.79-Å resolution to predict its probable function using structure similarity searches. The structure adopts an α/β structure of a helix-grip fold, which is found in the START domain proteins with cavities for hydrophobic substrates or ligands. The detailed structural features implied that fatty acids are the primary ligand candidates for STK_08120, and binding assays revealed that the protein bound long-chain saturated fatty acids (>C14) and their trans-unsaturated types with an affinity equal to that for major fatty acid binding proteins in mammals and plants. Moreover, the structure of an STK_08120-myristic acid complex revealed a unique binding mode among fatty acid binding proteins. These results suggest that the thermoacidophile-specific protein family DUF3211 functions as a fatty acid carrier with a novel binding mode. PMID:23836863

Automatic Detection of Blue-White Veil and Related Structures in Dermoscopy Images

PubMed Central

Celebi, M. Emre; Iyatomi, Hitoshi; Stoecker, William V.; Moss, Randy H.; Rabinovitz, Harold S.; Argenziano, Giuseppe; Soyer, H. Peter

2011-01-01

Dermoscopy is a non-invasive skin imaging technique, which permits visualization of features of pigmented melanocytic neoplasms that are not discernable by examination with the naked eye. One of the most important features for the diagnosis of melanoma in dermoscopy images is the blue-white veil (irregular, structureless areas of confluent blue pigmentation with an overlying white “ground-glass” film). In this article, we present a machine learning approach to the detection of blue-white veil and related structures in dermoscopy images. The method involves contextual pixel classification using a decision tree classifier. The percentage of blue-white areas detected in a lesion combined with a simple shape descriptor yielded a sensitivity of 69.35% and a specificity of 89.97% on a set of 545 dermoscopy images. The sensitivity rises to 78.20% for detection of blue veil in those cases where it is a primary feature for melanoma recognition. PMID:18804955

Iterative feature refinement for accurate undersampled MR image reconstruction

NASA Astrophysics Data System (ADS)

Wang, Shanshan; Liu, Jianbo; Liu, Qiegen; Ying, Leslie; Liu, Xin; Zheng, Hairong; Liang, Dong

2016-05-01

Accelerating MR scan is of great significance for clinical, research and advanced applications, and one main effort to achieve this is the utilization of compressed sensing (CS) theory. Nevertheless, the existing CSMRI approaches still have limitations such as fine structure loss or high computational complexity. This paper proposes a novel iterative feature refinement (IFR) module for accurate MR image reconstruction from undersampled K-space data. Integrating IFR with CSMRI which is equipped with fixed transforms, we develop an IFR-CS method to restore meaningful structures and details that are originally discarded without introducing too much additional complexity. Specifically, the proposed IFR-CS is realized with three iterative steps, namely sparsity-promoting denoising, feature refinement and Tikhonov regularization. Experimental results on both simulated and in vivo MR datasets have shown that the proposed module has a strong capability to capture image details, and that IFR-CS is comparable and even superior to other state-of-the-art reconstruction approaches.

Comparing writing style feature-based classification methods for estimating user reputations in social media.

PubMed

Suh, Jong Hwan

2016-01-01

In recent years, the anonymous nature of the Internet has made it difficult to detect manipulated user reputations in social media, as well as to ensure the qualities of users and their posts. To deal with this, this study designs and examines an automatic approach that adopts writing style features to estimate user reputations in social media. Under varying ways of defining Good and Bad classes of user reputations based on the collected data, it evaluates the classification performance of the state-of-art methods: four writing style features, i.e. lexical, syntactic, structural, and content-specific, and eight classification techniques, i.e. four base learners-C4.5, Neural Network (NN), Support Vector Machine (SVM), and Naïve Bayes (NB)-and four Random Subspace (RS) ensemble methods based on the four base learners. When South Korea's Web forum, Daum Agora, was selected as a test bed, the experimental results show that the configuration of the full feature set containing content-specific features and RS-SVM combining RS and SVM gives the best accuracy for classification if the test bed poster reputations are segmented strictly into Good and Bad classes by portfolio approach. Pairwise t tests on accuracy confirm two expectations coming from the literature reviews: first, the feature set adding content-specific features outperform the others; second, ensemble learning methods are more viable than base learners. Moreover, among the four ways on defining the classes of user reputations, i.e. like, dislike, sum, and portfolio, the results show that the portfolio approach gives the highest accuracy.

Structure, recognition and adaptive binding in RNA aptamer complexes.

PubMed

Patel, D J; Suri, A K; Jiang, F; Jiang, L; Fan, P; Kumar, R A; Nonin, S

1997-10-10

Novel features of RNA structure, recognition and discrimination have been recently elucidated through the solution structural characterization of RNA aptamers that bind cofactors, aminoglycoside antibiotics, amino acids and peptides with high affinity and specificity. This review presents the solution structures of RNA aptamer complexes with adenosine monophosphate, flavin mononucleotide, arginine/citrulline and tobramycin together with an example of hydrogen exchange measurements of the base-pair kinetics for the AMP-RNA aptamer complex. A comparative analysis of the structures of these RNA aptamer complexes yields the principles, patterns and diversity associated with RNA architecture, molecular recognition and adaptive binding associated with complex formation.

Contribution of low-temperature single-molecule techniques to structural issues of pigment–protein complexes from photosynthetic purple bacteria

PubMed Central

Löhner, Alexander; Cogdell, Richard

2018-01-01

As the electronic energies of the chromophores in a pigment–protein complex are imposed by the geometrical structure of the protein, this allows the spectral information obtained to be compared with predictions derived from structural models. Thereby, the single-molecule approach is particularly suited for the elucidation of specific, distinctive spectral features that are key for a particular model structure, and that would not be observable in ensemble-averaged spectra due to the heterogeneity of the biological objects. In this concise review, we illustrate with the example of the light-harvesting complexes from photosynthetic purple bacteria how results from low-temperature single-molecule spectroscopy can be used to discriminate between different structural models. Thereby the low-temperature approach provides two advantages: (i) owing to the negligible photobleaching, very long observation times become possible, and more importantly, (ii) at cryogenic temperatures, vibrational degrees of freedom are frozen out, leading to sharper spectral features and in turn to better resolved spectra. PMID:29321265

Surfing the wave, cycle, life history, and genes/proteins expressed by testicular germ cells. Part 4: intercellular bridges, mitochondria, nuclear envelope, apoptosis, ubiquitination, membrane/voltage-gated channels, methylation/acetylation, and transcription factors.

PubMed

Hermo, Louis; Pelletier, R-Marc; Cyr, Daniel G; Smith, Charles E

2010-04-01

As germ cells divide and differentiate from spermatogonia to spermatozoa, they share a number of structural and functional features that are common to all generations of germ cells and these features are discussed herein. Germ cells are linked to one another by large intercellular bridges which serve to move molecules and even large organelles from the cytoplasm of one cell to another. Mitochondria take on different shapes and features and topographical arrangements to accommodate their specific needs during spermatogenesis. The nuclear envelope and pore complex also undergo extensive modifications concomitant with the development of germ cell generations. Apoptosis is an event that is normally triggered by germ cells and involves many proteins. It occurs to limit the germ cell pool and acts as a quality control mechanism. The ubiquitin pathway comprises enzymes that ubiquitinate as well as deubiquitinate target proteins and this pathway is present and functional in germ cells. Germ cells express many proteins involved in water balance and pH control as well as voltage-gated ion channel movement. In the nucleus, proteins undergo epigenetic modifications which include methylation, acetylation, and phosphorylation, with each of these modifications signaling changes in chromatin structure. Germ cells contain specialized transcription complexes that coordinate the differentiation program of spermatogenesis, and there are many male germ cell-specific differences in the components of this machinery. All of the above features of germ cells will be discussed along with the specific proteins/genes and abnormalities to fertility related to each topic. Copyright 2009 Wiley-Liss, Inc.

Airborne remote sensors applied to engineering geology and civil works design investigations

NASA Technical Reports Server (NTRS)

Gelnett, R. H.

1975-01-01

The usefulness of various airborne remote sensing systems in the detection and identification of regional and specific geologic structural features that may affect the design and location of engineering structures on major civil works projects is evaluated. The Butler Valley Dam and Blue Lake Project in northern California was selected as a demonstration site. Findings derived from the interpretation of various kinds of imagery used are given.

A functional selectivity mechanism at the serotonin-2A GPCR involves ligand-dependent conformations of intracellular loop 2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perez-Aguilar, Jose Manuel; Shan, Jufang; LeVine, Michael V.

With recent progress in determination of G protein-coupled receptor (GPCR) structure with crystallography, a variety of other experimental approaches (e.g., NMR spectroscopy, fluorescent-based assays, mass spectrometry techniques) are also being used to characterize state-specific and ligand-specific conformational states. MD simulations offer a powerful complementary approach to elucidate the dynamic features associated with ligand-specific GPCR conformations. To shed light on the conformational elements and dynamics of the important aspect of GPCR functional selectivity, we carried out unbiased microsecond-length MD simulations of the human serotonin 2A receptor (5-HT 2AR) in the absence of ligand and bound to four distinct serotonergic agonists. Themore » 5-HT 2AR is a suitable system to study the structural features involved in the ligand-dependent conformational heterogeneity of GPCRs because it is well-characterized experimentally and exhibits a strong agonist-specific phenotype in that some 5-HT 2AR agonists induce LSD-like hallucinations, while others lack this psychoactive property entirely. Here we report evidence for structural and dynamic differences in 5-HT 2AR interacting with such pharmacologically distinct ligands, hallucinogens, and nonhallucinogens obtained from all-atom MD simulations. Differential ligand binding contacts were identified for structurally similar hallucinogens and nonhallucinogens and found to correspond to different conformations in the intracellular loop 2 (ICL2). From the different ICL2 conformations, functional selective phenotypes are suggested through effects on dimerization and/or distinct direct interaction with effector proteins. Lastly, the findings are presented in the context of currently proposed hallucinogenesis mechanisms, and ICL2 is proposed as a fine-tuning selective switch that can differentiates modes of 5-HT 2AR activation.« less

A functional selectivity mechanism at the serotonin-2A GPCR involves ligand-dependent conformations of intracellular loop 2

DOE PAGES

Perez-Aguilar, Jose Manuel; Shan, Jufang; LeVine, Michael V.; ...

2014-10-14

With recent progress in determination of G protein-coupled receptor (GPCR) structure with crystallography, a variety of other experimental approaches (e.g., NMR spectroscopy, fluorescent-based assays, mass spectrometry techniques) are also being used to characterize state-specific and ligand-specific conformational states. MD simulations offer a powerful complementary approach to elucidate the dynamic features associated with ligand-specific GPCR conformations. To shed light on the conformational elements and dynamics of the important aspect of GPCR functional selectivity, we carried out unbiased microsecond-length MD simulations of the human serotonin 2A receptor (5-HT 2AR) in the absence of ligand and bound to four distinct serotonergic agonists. Themore » 5-HT 2AR is a suitable system to study the structural features involved in the ligand-dependent conformational heterogeneity of GPCRs because it is well-characterized experimentally and exhibits a strong agonist-specific phenotype in that some 5-HT 2AR agonists induce LSD-like hallucinations, while others lack this psychoactive property entirely. Here we report evidence for structural and dynamic differences in 5-HT 2AR interacting with such pharmacologically distinct ligands, hallucinogens, and nonhallucinogens obtained from all-atom MD simulations. Differential ligand binding contacts were identified for structurally similar hallucinogens and nonhallucinogens and found to correspond to different conformations in the intracellular loop 2 (ICL2). From the different ICL2 conformations, functional selective phenotypes are suggested through effects on dimerization and/or distinct direct interaction with effector proteins. Lastly, the findings are presented in the context of currently proposed hallucinogenesis mechanisms, and ICL2 is proposed as a fine-tuning selective switch that can differentiates modes of 5-HT 2AR activation.« less

Ancestral multipartite units in light-responsive plant promoters have structural features correlating with specific phototransduction pathways.

PubMed Central

Argüello-Astorga, G R; Herrera-Estrella, L R

1996-01-01

Regulation of plant gene transcription by light is mediated by multipartite cis-regulatory units. Previous attempts to identify structural features that are common to all light-responsive elements (LREs) have been unsuccessful. To address the question of what is needed to confer photoresponsiveness to a promoter, the upstream sequences from more than 110 light-regulated plant genes were analyzed by a new, phylogenetic-structural method. As a result, 30 distinct conserved DNA module arrays (CMAs) associated with light-responsive promoter regions were identified. Several of these CMAs have remained invariant throughout the evolutionary radiation of angiosperms and are conserved between homologous genes as well as between members of different gene families. The identified CMAs share a gene superfamily-specific core that correlates with the particular phytochrome-dependent transduction pathway that controls their expression, i.e. ACCTA(A/C)C(A/C) for the cGMP-dependent phenylpropanoid metabolism-associated genes, and GATA(A/T)GR for the Ca2+/calmodulin-dependent photosynthesis-associated nuclear genes. In addition to suggesting a general model for the functional and structural organization of LREs, the data obtained in this study indicate that angiosperm LREs probably evolved from complex cis-acting elements involved in regulatory processes other than photoregulation in gymnosperms. PMID:8938415

Enhancement of the Feature Extraction Capability in Global Damage Detection Using Wavelet Theory

NASA Technical Reports Server (NTRS)

Saleeb, Atef F.; Ponnaluru, Gopi Krishna

2006-01-01

The main objective of this study is to assess the specific capabilities of the defect energy parameter technique for global damage detection developed by Saleeb and coworkers. The feature extraction is the most important capability in any damage-detection technique. Features are any parameters extracted from the processed measurement data in order to enhance damage detection. The damage feature extraction capability was studied extensively by analyzing various simulation results. The practical significance in structural health monitoring is that the detection at early stages of small-size defects is always desirable. The amount of changes in the structure's response due to these small defects was determined to show the needed level of accuracy in the experimental methods. The arrangement of fine/extensive sensor network to measure required data for the detection is an "unlimited" ability, but there is a difficulty to place extensive number of sensors on a structure. Therefore, an investigation was conducted using the measurements of coarse sensor network. The white and the pink noises, which cover most of the frequency ranges that are typically encountered in the many measuring devices used (e.g., accelerometers, strain gauges, etc.) are added to the displacements to investigate the effect of noisy measurements in the detection technique. The noisy displacements and the noisy damage parameter values are used to study the signal feature reconstruction using wavelets. The enhancement of the feature extraction capability was successfully achieved by the wavelet theory.

Towards the Improved Discovery and Design of Functional Peptides: Common Features of Diverse Classes Permit Generalized Prediction of Bioactivity

PubMed Central

Mooney, Catherine; Haslam, Niall J.; Pollastri, Gianluca; Shields, Denis C.

2012-01-01

The conventional wisdom is that certain classes of bioactive peptides have specific structural features that endow their particular functions. Accordingly, predictions of bioactivity have focused on particular subgroups, such as antimicrobial peptides. We hypothesized that bioactive peptides may share more general features, and assessed this by contrasting the predictive power of existing antimicrobial predictors as well as a novel general predictor, PeptideRanker, across different classes of peptides. We observed that existing antimicrobial predictors had reasonable predictive power to identify peptides of certain other classes i.e. toxin and venom peptides. We trained two general predictors of peptide bioactivity, one focused on short peptides (4–20 amino acids) and one focused on long peptides ( amino acids). These general predictors had performance that was typically as good as, or better than, that of specific predictors. We noted some striking differences in the features of short peptide and long peptide predictions, in particular, high scoring short peptides favour phenylalanine. This is consistent with the hypothesis that short and long peptides have different functional constraints, perhaps reflecting the difficulty for typical short peptides in supporting independent tertiary structure. We conclude that there are general shared features of bioactive peptides across different functional classes, indicating that computational prediction may accelerate the discovery of novel bioactive peptides and aid in the improved design of existing peptides, across many functional classes. An implementation of the predictive method, PeptideRanker, may be used to identify among a set of peptides those that may be more likely to be bioactive. PMID:23056189

Recognizing ovarian cancer from co-registered ultrasound and photoacoustic images

NASA Astrophysics Data System (ADS)

Alqasemi, Umar; Kumavor, Patrick; Aguirre, Andres; Zhu, Quing

2013-03-01

Unique features in co-registered ultrasound and photoacoustic images of ex vivo ovarian tissue are introduced, along with the hypotheses of how these features may relate to the physiology of tumors. The images are compressed with wavelet transform, after which the mean Radon transform of the photoacoustic image is computed and fitted with a Gaussian function to find the centroid of the suspicious area for shift-invariant recognition process. In the next step, 24 features are extracted from a training set of images by several methods; including features from the Fourier domain, image statistics, and the outputs of different composite filters constructed from the joint frequency response of different cancerous images. The features were chosen from more than 400 training images obtained from 33 ex vivo ovaries of 24 patients, and used to train a support vector machine (SVM) structure. The SVM classifier was able to exclusively separate the cancerous from the non-cancerous cases with 100% sensitivity and specificity. At the end, the classifier was used to test 95 new images, obtained from 37 ovaries of 20 additional patients. The SVM classifier achieved 76.92% sensitivity and 95.12% specificity. Furthermore, if we assume that recognizing one image as a cancerous case is sufficient to consider the ovary as malignant, then the SVM classifier achieves 100% sensitivity and 87.88% specificity.

Role of multidetector computed tomography in evaluating incidentally detected breast lesions.

PubMed

Moschetta, Marco; Scardapane, Arnaldo; Lorusso, Valentina; Rella, Leonarda; Telegrafo, Michele; Serio, Gabriella; Angelelli, Giuseppe; Ianora, Amato Antonio Stabile

2015-01-01

Computed tomography (CT) does not represent the primary method for the evaluation of breast lesions; however, it can detect breast abnormalities, even when performed for other reasons related to thoracic structures. The aim of this study is to evaluate the potential benefits of 320-row multidetector CT (MDCT) in evaluating and differentiating incidentally detected breast lesions by using vessel probe and 3D analysis software with net enhancement value. Sixty-two breast lesions in 46 patients who underwent 320-row chest CT examination were retrospectively evaluated. CT scans were assessed searching for the presence, location, number, morphological features, and density of breast nodules. Net enhancement was calculated by subtracting precontrast density from the density obtained by postcontrast values. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy of CT were calculated for morphological features and net enhancement. Thirty of 62 lesions were found to be malignant at histological examination and 32 were found to be benign. When morphological features were considered, the sensitivity, specificity, accuracy, PPV, and NPV of CT were 87%, 100%, 88%, 100%, and 50%, respectively. Based on net enhancement, CT reached a sensitivity, specificity, accuracy, PPV, and NPV of 100%, 94%, 97%, 94%, and 100%, respectively. MDCT allows to recognize and characterize breast lesions based on morphological features. Net enhancement can be proposed as an additional accurate feature of CT.

Ada style guide (version 1.1)

NASA Technical Reports Server (NTRS)

Seidewitz, Edwin V.; Agresti, William; Ferry, Daniel; Lavallee, David; Maresca, Paul; Nelson, Robert; Quimby, Kelvin; Rosenberg, Jacob; Roy, Daniel; Shell, Allyn

1987-01-01

Ada is a programming language of considerable expressive power. The Ada Language Reference Manual provides a thorough definition of the language. However, it does not offer sufficient guidance on the appropriate use of Ada's powerful features. For this reason, the Goddard Space Flight Center Ada User's Group has produced this style guide which addresses such program style issues. The guide covers three areas of Ada program style: the structural decomposition of a program; the coding and the use of specific Ada features; and the textural formatting of a program.

Structures of two aptamers with differing ligand specificity reveal ruggedness in the functional landscape of RNA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Knappenberger, Andrew John; Reiss, Caroline Wetherington; Strobel, Scott A.

Two classes of riboswitches related to the ykkC guanidine-I riboswitch bind phosphoribosyl pyrophosphate (PRPP) and guanosine tetraphosphate (ppGpp). Here we report the co-crystal structure of the PRPP aptamer and its ligand. We also report the structure of the G96A point mutant that prefers ppGpp over PRPP with a dramatic 40,000-fold switch in specificity. The ends of the aptamer form a helix that is not present in the guanidine aptamer and is involved in the expression platform. In the mutant, the base of ppGpp replaces G96 in three-dimensional space. This disrupts the S-turn, which is a primary structural feature of themore » ykkC RNA motif. These dramatic differences in ligand specificity are achieved with minimal mutations. ykkC aptamers are therefore a prime example of an RNA fold with a rugged fitness landscape. The ease with which the ykkC aptamer acquires new specificity represents a striking case of evolvability in RNA.« less

Structures of two aptamers with differing ligand specificity reveal ruggedness in the functional landscape of RNA.

PubMed

Knappenberger, Andrew John; Reiss, Caroline Wetherington; Strobel, Scott A

2018-06-07

Two classes of riboswitches related to the ykkC guanidine-I riboswitch bind phosphoribosyl pyrophosphate (PRPP) and guanosine tetraphosphate (ppGpp). Here we report the co-crystal structure of the PRPP aptamer and its ligand. We also report the structure of the G96A point mutant that prefers ppGpp over PRPP with a dramatic 40,000-fold switch in specificity. The ends of the aptamer form a helix that is not present in the guanidine aptamer and is involved in the expression platform. In the mutant, the base of ppGpp replaces G96 in three-dimensional space. This disrupts the S-turn, which is a primary structural feature of the ykkC RNA motif. These dramatic differences in ligand specificity are achieved with minimal mutations. ykkC aptamers are therefore a prime example of an RNA fold with a rugged fitness landscape. The ease with which the ykkC aptamer acquires new specificity represents a striking case of evolvability in RNA. © 2018, Knappenberger et al.

Structural fingerprints and their evolution during oligomeric vs. oligomer-free amyloid fibril growth

PubMed Central

Foley, Joseph; Hill, Shannon E.; Miti, Tatiana; Mulaj, Mentor; Ciesla, Marissa; Robeel, Rhonda; Persichilli, Christopher; Raynes, Rachel; Westerheide, Sandy; Muschol, Martin

2013-01-01

Deposits of fibrils formed by disease-specific proteins are the molecular hallmark of such diverse human disorders as Alzheimer's disease, type II diabetes, or rheumatoid arthritis. Amyloid fibril formation by structurally and functionally unrelated proteins exhibits many generic characteristics, most prominently the cross β-sheet structure of their mature fibrils. At the same time, amyloid formation tends to proceed along one of two separate assembly pathways yielding either stiff monomeric filaments or globular oligomers and curvilinear protofibrils. Given the focus on oligomers as major toxic species, the very existence of an oligomer-free assembly pathway is significant. Little is known, though, about the structure of the various intermediates emerging along different pathways and whether the pathways converge towards a common or distinct fibril structures. Using infrared spectroscopy we probed the structural evolution of intermediates and late-stage fibrils formed during in vitro lysozyme amyloid assembly along an oligomeric and oligomer-free pathway. Infrared spectroscopy confirmed that both pathways produced amyloid-specific β-sheet peaks, but at pathway-specific wavenumbers. We further found that the amyloid-specific dye thioflavin T responded to all intermediates along either pathway. The relative amplitudes of thioflavin T fluorescence responses displayed pathway-specific differences and could be utilized for monitoring the structural evolution of intermediates. Pathway-specific structural features obtained from infrared spectroscopy and Thioflavin T responses were identical for fibrils grown at highly acidic or at physiological pH values and showed no discernible effects of protein hydrolysis. Our results suggest that late-stage fibrils formed along either pathway are amyloidogenic in nature, but have distinguishable structural fingerprints. These pathway-specific fingerprints emerge during the earliest aggregation events and persist throughout the entire cascade of aggregation intermediates formed along each pathway. PMID:24089713

Structural fingerprints and their evolution during oligomeric vs. oligomer-free amyloid fibril growth

NASA Astrophysics Data System (ADS)

Foley, Joseph; Hill, Shannon E.; Miti, Tatiana; Mulaj, Mentor; Ciesla, Marissa; Robeel, Rhonda; Persichilli, Christopher; Raynes, Rachel; Westerheide, Sandy; Muschol, Martin

2013-09-01

Deposits of fibrils formed by disease-specific proteins are the molecular hallmark of such diverse human disorders as Alzheimer's disease, type II diabetes, or rheumatoid arthritis. Amyloid fibril formation by structurally and functionally unrelated proteins exhibits many generic characteristics, most prominently the cross β-sheet structure of their mature fibrils. At the same time, amyloid formation tends to proceed along one of two separate assembly pathways yielding either stiff monomeric filaments or globular oligomers and curvilinear protofibrils. Given the focus on oligomers as major toxic species, the very existence of an oligomer-free assembly pathway is significant. Little is known, though, about the structure of the various intermediates emerging along different pathways and whether the pathways converge towards a common or distinct fibril structures. Using infrared spectroscopy we probed the structural evolution of intermediates and late-stage fibrils formed during in vitro lysozyme amyloid assembly along an oligomeric and oligomer-free pathway. Infrared spectroscopy confirmed that both pathways produced amyloid-specific β-sheet peaks, but at pathway-specific wavenumbers. We further found that the amyloid-specific dye thioflavin T responded to all intermediates along either pathway. The relative amplitudes of thioflavin T fluorescence responses displayed pathway-specific differences and could be utilized for monitoring the structural evolution of intermediates. Pathway-specific structural features obtained from infrared spectroscopy and Thioflavin T responses were identical for fibrils grown at highly acidic or at physiological pH values and showed no discernible effects of protein hydrolysis. Our results suggest that late-stage fibrils formed along either pathway are amyloidogenic in nature, but have distinguishable structural fingerprints. These pathway-specific fingerprints emerge during the earliest aggregation events and persist throughout the entire cascade of aggregation intermediates formed along each pathway.

Structural fingerprints and their evolution during oligomeric vs. oligomer-free amyloid fibril growth.

PubMed

Foley, Joseph; Hill, Shannon E; Miti, Tatiana; Mulaj, Mentor; Ciesla, Marissa; Robeel, Rhonda; Persichilli, Christopher; Raynes, Rachel; Westerheide, Sandy; Muschol, Martin

2013-09-28

Deposits of fibrils formed by disease-specific proteins are the molecular hallmark of such diverse human disorders as Alzheimer's disease, type II diabetes, or rheumatoid arthritis. Amyloid fibril formation by structurally and functionally unrelated proteins exhibits many generic characteristics, most prominently the cross β-sheet structure of their mature fibrils. At the same time, amyloid formation tends to proceed along one of two separate assembly pathways yielding either stiff monomeric filaments or globular oligomers and curvilinear protofibrils. Given the focus on oligomers as major toxic species, the very existence of an oligomer-free assembly pathway is significant. Little is known, though, about the structure of the various intermediates emerging along different pathways and whether the pathways converge towards a common or distinct fibril structures. Using infrared spectroscopy we probed the structural evolution of intermediates and late-stage fibrils formed during in vitro lysozyme amyloid assembly along an oligomeric and oligomer-free pathway. Infrared spectroscopy confirmed that both pathways produced amyloid-specific β-sheet peaks, but at pathway-specific wavenumbers. We further found that the amyloid-specific dye thioflavin T responded to all intermediates along either pathway. The relative amplitudes of thioflavin T fluorescence responses displayed pathway-specific differences and could be utilized for monitoring the structural evolution of intermediates. Pathway-specific structural features obtained from infrared spectroscopy and Thioflavin T responses were identical for fibrils grown at highly acidic or at physiological pH values and showed no discernible effects of protein hydrolysis. Our results suggest that late-stage fibrils formed along either pathway are amyloidogenic in nature, but have distinguishable structural fingerprints. These pathway-specific fingerprints emerge during the earliest aggregation events and persist throughout the entire cascade of aggregation intermediates formed along each pathway.

Structural and evolutionary adaptation of rhoptry kinases and pseudokinases, a family of coccidian virulence factors

PubMed Central

2013-01-01

Background The widespread protozoan parasite Toxoplasma gondii interferes with host cell functions by exporting the contents of a unique apical organelle, the rhoptry. Among the mix of secreted proteins are an expanded, lineage-specific family of protein kinases termed rhoptry kinases (ROPKs), several of which have been shown to be key virulence factors, including the pseudokinase ROP5. The extent and details of the diversification of this protein family are poorly understood. Results In this study, we comprehensively catalogued the ROPK family in the genomes of Toxoplasma gondii, Neospora caninum and Eimeria tenella, as well as portions of the unfinished genome of Sarcocystis neurona, and classified the identified genes into 42 distinct subfamilies. We systematically compared the rhoptry kinase protein sequences and structures to each other and to the broader superfamily of eukaryotic protein kinases to study the patterns of diversification and neofunctionalization in the ROPK family and its subfamilies. We identified three ROPK sub-clades of particular interest: those bearing a structurally conserved N-terminal extension to the kinase domain (NTE), an E. tenella-specific expansion, and a basal cluster including ROP35 and BPK1 that we term ROPKL. Structural analysis in light of the solved structures ROP2, ROP5, ROP8 and in comparison to typical eukaryotic protein kinases revealed ROPK-specific conservation patterns in two key regions of the kinase domain, surrounding a ROPK-conserved insert in the kinase hinge region and a disulfide bridge in the kinase substrate-binding lobe. We also examined conservation patterns specific to the NTE-bearing clade. We discuss the possible functional consequences of each. Conclusions Our work sheds light on several important but previously unrecognized features shared among rhoptry kinases, as well as the essential differences between active and degenerate protein kinases. We identify the most distinctive ROPK-specific features conserved across both active kinases and pseudokinases, and discuss these in terms of sequence motifs, evolutionary context, structural impact and potential functional relevance. By characterizing the proteins that enable these parasites to invade the host cell and co-opt its signaling mechanisms, we provide guidance on potential therapeutic targets for the diseases caused by coccidian parasites. PMID:23742205

Knowledge-based fragment binding prediction.

PubMed

Tang, Grace W; Altman, Russ B

2014-04-01

Target-based drug discovery must assess many drug-like compounds for potential activity. Focusing on low-molecular-weight compounds (fragments) can dramatically reduce the chemical search space. However, approaches for determining protein-fragment interactions have limitations. Experimental assays are time-consuming, expensive, and not always applicable. At the same time, computational approaches using physics-based methods have limited accuracy. With increasing high-resolution structural data for protein-ligand complexes, there is now an opportunity for data-driven approaches to fragment binding prediction. We present FragFEATURE, a machine learning approach to predict small molecule fragments preferred by a target protein structure. We first create a knowledge base of protein structural environments annotated with the small molecule substructures they bind. These substructures have low-molecular weight and serve as a proxy for fragments. FragFEATURE then compares the structural environments within a target protein to those in the knowledge base to retrieve statistically preferred fragments. It merges information across diverse ligands with shared substructures to generate predictions. Our results demonstrate FragFEATURE's ability to rediscover fragments corresponding to the ligand bound with 74% precision and 82% recall on average. For many protein targets, it identifies high scoring fragments that are substructures of known inhibitors. FragFEATURE thus predicts fragments that can serve as inputs to fragment-based drug design or serve as refinement criteria for creating target-specific compound libraries for experimental or computational screening.

Knowledge-based Fragment Binding Prediction

PubMed Central

Tang, Grace W.; Altman, Russ B.

2014-01-01

Target-based drug discovery must assess many drug-like compounds for potential activity. Focusing on low-molecular-weight compounds (fragments) can dramatically reduce the chemical search space. However, approaches for determining protein-fragment interactions have limitations. Experimental assays are time-consuming, expensive, and not always applicable. At the same time, computational approaches using physics-based methods have limited accuracy. With increasing high-resolution structural data for protein-ligand complexes, there is now an opportunity for data-driven approaches to fragment binding prediction. We present FragFEATURE, a machine learning approach to predict small molecule fragments preferred by a target protein structure. We first create a knowledge base of protein structural environments annotated with the small molecule substructures they bind. These substructures have low-molecular weight and serve as a proxy for fragments. FragFEATURE then compares the structural environments within a target protein to those in the knowledge base to retrieve statistically preferred fragments. It merges information across diverse ligands with shared substructures to generate predictions. Our results demonstrate FragFEATURE's ability to rediscover fragments corresponding to the ligand bound with 74% precision and 82% recall on average. For many protein targets, it identifies high scoring fragments that are substructures of known inhibitors. FragFEATURE thus predicts fragments that can serve as inputs to fragment-based drug design or serve as refinement criteria for creating target-specific compound libraries for experimental or computational screening. PMID:24762971

Identifying and Prioritizing Greater Sage-Grouse Nesting and Brood-Rearing Habitat for Conservation in Human-Modified Landscapes

PubMed Central

Dzialak, Matthew R.; Olson, Chad V.; Harju, Seth M.; Webb, Stephen L.; Mudd, James P.; Winstead, Jeffrey B.; Hayden-Wing, L.D.

2011-01-01

Background Balancing animal conservation and human use of the landscape is an ongoing scientific and practical challenge throughout the world. We investigated reproductive success in female greater sage-grouse (Centrocercus urophasianus) relative to seasonal patterns of resource selection, with the larger goal of developing a spatially-explicit framework for managing human activity and sage-grouse conservation at the landscape level. Methodology/Principal Findings We integrated field-observation, Global Positioning Systems telemetry, and statistical modeling to quantify the spatial pattern of occurrence and risk during nesting and brood-rearing. We linked occurrence and risk models to provide spatially-explicit indices of habitat-performance relationships. As part of the analysis, we offer novel biological information on resource selection during egg-laying, incubation, and night. The spatial pattern of occurrence during all reproductive phases was driven largely by selection or avoidance of terrain features and vegetation, with little variation explained by anthropogenic features. Specifically, sage-grouse consistently avoided rough terrain, selected for moderate shrub cover at the patch level (within 90 m2), and selected for mesic habitat in mid and late brood-rearing phases. In contrast, risk of nest and brood failure was structured by proximity to anthropogenic features including natural gas wells and human-created mesic areas, as well as vegetation features such as shrub cover. Conclusions/Significance Risk in this and perhaps other human-modified landscapes is a top-down (i.e., human-mediated) process that would most effectively be minimized by developing a better understanding of specific mechanisms (e.g., predator subsidization) driving observed patterns, and using habitat-performance indices such as those developed herein for spatially-explicit guidance of conservation intervention. Working under the hypothesis that industrial activity structures risk by enhancing predator abundance or effectiveness, we offer specific recommendations for maintaining high-performance habitat and reducing low-performance habitat, particularly relative to the nesting phase, by managing key high-risk anthropogenic features such as industrial infrastructure and water developments. PMID:22022587

Prediction of plant pre-microRNAs and their microRNAs in genome-scale sequences using structure-sequence features and support vector machine.

PubMed

Meng, Jun; Liu, Dong; Sun, Chao; Luan, Yushi

2014-12-30

MicroRNAs (miRNAs) are a family of non-coding RNAs approximately 21 nucleotides in length that play pivotal roles at the post-transcriptional level in animals, plants and viruses. These molecules silence their target genes by degrading transcription or suppressing translation. Studies have shown that miRNAs are involved in biological responses to a variety of biotic and abiotic stresses. Identification of these molecules and their targets can aid the understanding of regulatory processes. Recently, prediction methods based on machine learning have been widely used for miRNA prediction. However, most of these methods were designed for mammalian miRNA prediction, and few are available for predicting miRNAs in the pre-miRNAs of specific plant species. Although the complete Solanum lycopersicum genome has been published, only 77 Solanum lycopersicum miRNAs have been identified, far less than the estimated number. Therefore, it is essential to develop a prediction method based on machine learning to identify new plant miRNAs. A novel classification model based on a support vector machine (SVM) was trained to identify real and pseudo plant pre-miRNAs together with their miRNAs. An initial set of 152 novel features related to sequential structures was used to train the model. By applying feature selection, we obtained the best subset of 47 features for use with the Back Support Vector Machine-Recursive Feature Elimination (B-SVM-RFE) method for the classification of plant pre-miRNAs. Using this method, 63 features were obtained for plant miRNA classification. We then developed an integrated classification model, miPlantPreMat, which comprises MiPlantPre and MiPlantMat, to identify plant pre-miRNAs and their miRNAs. This model achieved approximately 90% accuracy using plant datasets from nine plant species, including Arabidopsis thaliana, Glycine max, Oryza sativa, Physcomitrella patens, Medicago truncatula, Sorghum bicolor, Arabidopsis lyrata, Zea mays and Solanum lycopersicum. Using miPlantPreMat, 522 Solanum lycopersicum miRNAs were identified in the Solanum lycopersicum genome sequence. We developed an integrated classification model, miPlantPreMat, based on structure-sequence features and SVM. MiPlantPreMat was used to identify both plant pre-miRNAs and the corresponding mature miRNAs. An improved feature selection method was proposed, resulting in high classification accuracy, sensitivity and specificity.

Music acquisition: effects of enculturation and formal training on development.

PubMed

Hannon, Erin E; Trainor, Laurel J

2007-11-01

Musical structure is complex, consisting of a small set of elements that combine to form hierarchical levels of pitch and temporal structure according to grammatical rules. As with language, different systems use different elements and rules for combination. Drawing on recent findings, we propose that music acquisition begins with basic features, such as peripheral frequency-coding mechanisms and multisensory timing connections, and proceeds through enculturation, whereby everyday exposure to a particular music system creates, in a systematic order of acquisition, culture-specific brain structures and representations. Finally, we propose that formal musical training invokes domain-specific processes that affect salience of musical input and the amount of cortical tissue devoted to its processing, as well as domain-general processes of attention and executive functioning.

Object similarity affects the perceptual strategy underlying invariant visual object recognition in rats

PubMed Central

Rosselli, Federica B.; Alemi, Alireza; Ansuini, Alessio; Zoccolan, Davide

2015-01-01

In recent years, a number of studies have explored the possible use of rats as models of high-level visual functions. One central question at the root of such an investigation is to understand whether rat object vision relies on the processing of visual shape features or, rather, on lower-order image properties (e.g., overall brightness). In a recent study, we have shown that rats are capable of extracting multiple features of an object that are diagnostic of its identity, at least when those features are, structure-wise, distinct enough to be parsed by the rat visual system. In the present study, we have assessed the impact of object structure on rat perceptual strategy. We trained rats to discriminate between two structurally similar objects, and compared their recognition strategies with those reported in our previous study. We found that, under conditions of lower stimulus discriminability, rat visual discrimination strategy becomes more view-dependent and subject-dependent. Rats were still able to recognize the target objects, in a way that was largely tolerant (i.e., invariant) to object transformation; however, the larger structural and pixel-wise similarity affected the way objects were processed. Compared to the findings of our previous study, the patterns of diagnostic features were: (i) smaller and more scattered; (ii) only partially preserved across object views; and (iii) only partially reproducible across rats. On the other hand, rats were still found to adopt a multi-featural processing strategy and to make use of part of the optimal discriminatory information afforded by the two objects. Our findings suggest that, as in humans, rat invariant recognition can flexibly rely on either view-invariant representations of distinctive object features or view-specific object representations, acquired through learning. PMID:25814936

Juvenile skeletogenesis in anciently diverged sea urchin clades.

PubMed

Gao, Feng; Thompson, Jeffrey R; Petsios, Elizabeth; Erkenbrack, Eric; Moats, Rex A; Bottjer, David J; Davidson, Eric H

2015-04-01

Mechanistic understanding of evolutionary divergence in animal body plans devolves from analysis of those developmental processes that, in forms descendant from a common ancestor, are responsible for their morphological differences. The last common ancestor of the two extant subclasses of sea urchins, i.e., euechinoids and cidaroids, existed well before the Permian/Triassic extinction (252 mya). Subsequent evolutionary divergence of these clades offers in principle a rare opportunity to solve the developmental regulatory events underlying a defined evolutionary divergence process. Thus (i) there is an excellent and fairly dense (if yet incompletely analyzed) fossil record; (ii) cladistically confined features of the skeletal structures of modern euechinoid and cidaroid sea urchins are preserved in fossils of ancestral forms; (iii) euechinoids and cidaroids are among current laboratory model systems in molecular developmental biology (here Strongylocentrotus purpuratus [Sp] and Eucidaris tribuloides [Et]); (iv) skeletogenic specification in sea urchins is uncommonly well understood at the causal level of interactions of regulatory genes with one another, and with known skeletogenic effector genes, providing a ready arsenal of available molecular tools. Here we focus on differences in test and perignathic girdle skeletal morphology that distinguish all modern euechinoid from all modern cidaroid sea urchins. We demonstrate distinct canonical test and girdle morphologies in juveniles of both species by use of SEM and X-ray microtomography. Among the sharply distinct morphological features of these clades are the internal skeletal structures of the perignathic girdle to which attach homologous muscles utilized for retraction and protraction of Aristotles׳ lantern and its teeth. We demonstrate that these structures develop de novo between one and four weeks after metamorphosis. In order to study the underlying developmental processes, a method of section whole mount in situ hybridization was adapted. This method displays current gene expression in the developing test and perignathic girdle skeletal elements of both Sp and Et juveniles. Active, specific expression of the sm37 biomineralization gene in these muscle attachment structures accompanies morphogenetic development of these clade-specific features in juveniles of both species. Skeletogenesis at these clade-specific muscle attachment structures displays molecular earmarks of the well understood embryonic skeletogenic GRN: thus the upstream regulatory gene alx1 and the gene encoding the vegfR signaling receptor are both expressed at the sites where they are formed. This work opens the way to analysis of the alternative spatial specification processes that were installed at the evolutionary divergence of the two extant subclasses of sea urchins. Copyright © 2015 Elsevier Inc. All rights reserved.

A tale of two centromeres--diversity of structure but conservation of function in plants and animals.

PubMed

Birchler, James A; Gao, Zhi; Han, Fangpu

2009-02-01

The structural and functional aspects of two specific centromeres, one drawn from the animal kingdom (Drosophila) and the other from the plant kingdom (maize), are compared. Both cases illustrate an epigenetic component to centromere specification. The observations of neocentromeres in Drosophila and inactive centromeres in maize constitute one line of evidence for this hypothesis. Another common feature is the divisibility of centromere function with reduced stability as the size decreases. The systems differ in that Drosophila has no common sequence repeat at all centromeres, whereas maize has a 150-bp unit present in tandem arrays together with a centromere-specific transposon, centromere retrotransposon maize, present at all primary constrictions. Aspects of centromere structure known only from one or the other system might be common to both, namely, the presence of centromere RNAs in the kinetochore as found in maize and the organization of the centromeric histone 3 in tetrameric nucleosomes.

Data standards for clinical research data collection forms: current status and challenges.

PubMed

Richesson, Rachel L; Nadkarni, Prakash

2011-05-01

Case report forms (CRFs) are used for structured-data collection in clinical research studies. Existing CRF-related standards encompass structural features of forms and data items, content standards, and specifications for using terminologies. This paper reviews existing standards and discusses their current limitations. Because clinical research is highly protocol-specific, forms-development processes are more easily standardized than is CRF content. Tools that support retrieval and reuse of existing items will enable standards adoption in clinical research applications. Such tools will depend upon formal relationships between items and terminological standards. Future standards adoption will depend upon standardized approaches for bridging generic structural standards and domain-specific content standards. Clinical research informatics can help define tools requirements in terms of workflow support for research activities, reconcile the perspectives of varied clinical research stakeholders, and coordinate standards efforts toward interoperability across healthcare and research data collection.

Composite foods: from structure to sensory perception.

PubMed

Scholten, Elke

2017-02-22

An understanding of the effect of structural features of foods in terms of specific sensory attributes is necessary to design foods with specific functionalities, such as reduced fat or increased protein content, and increased feeling of satiety or liking. Although the bulk rheological properties of both liquid and solid foods can be related to textural attributes such as thickness and firmness, they do not always correlate to more complex sensory attributes, such as creamy and smooth. These attributes are often a result of different contributions, including lubrication aspects and interactions between food and components present in the oral cavity. In this review, the different contributions for a variety of composite foods, such as dispersions, emulsions and emulsion-filled gels, are discussed. The rheological properties are discussed in relation to specific structural characteristics of the foods, which are then linked to lubrication aspects and sensory perception.

Protein structure based prediction of catalytic residues

PubMed Central

2013-01-01

Background Worldwide structural genomics projects continue to release new protein structures at an unprecedented pace, so far nearly 6000, but only about 60% of these proteins have any sort of functional annotation. Results We explored a range of features that can be used for the prediction of functional residues given a known three-dimensional structure. These features include various centrality measures of nodes in graphs of interacting residues: closeness, betweenness and page-rank centrality. We also analyzed the distance of functional amino acids to the general center of mass (GCM) of the structure, relative solvent accessibility (RSA), and the use of relative entropy as a measure of sequence conservation. From the selected features, neural networks were trained to identify catalytic residues. We found that using distance to the GCM together with amino acid type provide a good discriminant function, when combined independently with sequence conservation. Using an independent test set of 29 annotated protein structures, the method returned 411 of the initial 9262 residues as the most likely to be involved in function. The output 411 residues contain 70 of the annotated 111 catalytic residues. This represents an approximately 14-fold enrichment of catalytic residues on the entire input set (corresponding to a sensitivity of 63% and a precision of 17%), a performance competitive with that of other state-of-the-art methods. Conclusions We found that several of the graph based measures utilize the same underlying feature of protein structures, which can be simply and more effectively captured with the distance to GCM definition. This also has the added the advantage of simplicity and easy implementation. Meanwhile sequence conservation remains by far the most influential feature in identifying functional residues. We also found that due the rapid changes in size and composition of sequence databases, conservation calculations must be recalibrated for specific reference databases. PMID:23433045

Cartilage Tissue Engineering with Silk Fibroin Scaffolds Fabricated by Indirect Additive Manufacturing Technology

PubMed Central

Chen, Chih-Hao; Liu, Jolene Mei-Jun; Chua, Chee-Kai; Chou, Siaw-Meng; Shyu, Victor Bong-Hang; Chen, Jyh-Ping

2014-01-01

Advanced tissue engineering (TE) technology based on additive manufacturing (AM) can fabricate scaffolds with a three-dimensional (3D) environment suitable for cartilage regeneration. Specifically, AM technology may allow the incorporation of complex architectural features. The present study involves the fabrication of 3D TE scaffolds by an indirect AM approach using silk fibroin (SF). From scanning electron microscopic observations, the presence of micro-pores and interconnected channels within the scaffold could be verified, resulting in a TE scaffold with both micro- and macro-structural features. The intrinsic properties, such as the chemical structure and thermal characteristics of SF, were preserved after the indirect AM manufacturing process. In vitro cell culture within the SF scaffold using porcine articular chondrocytes showed a steady increase in cell numbers up to Day 14. The specific production (per cell basis) of the cartilage-specific extracellular matrix component (collagen Type II) was enhanced with culture time up to 12 weeks, indicating the re-differentiation of chondrocytes within the scaffold. Subcutaneous implantation of the scaffold-chondrocyte constructs in nude mice also confirmed the formation of ectopic cartilage by histological examination and immunostaining. PMID:28788558

Cryo-EM structure of the spinach chloroplast ribosome reveals the location of plastid-specific ribosomal proteins and extensions

PubMed Central

Graf, Michael; Arenz, Stefan; Huter, Paul; Dönhöfer, Alexandra; Nováček, Jiří

2017-01-01

Abstract Ribosomes are the protein synthesizing machines of the cell. Recent advances in cryo-EM have led to the determination of structures from a variety of species, including bacterial 70S and eukaryotic 80S ribosomes as well as mitoribosomes from eukaryotic mitochondria, however, to date high resolution structures of plastid 70S ribosomes have been lacking. Here we present a cryo-EM structure of the spinach chloroplast 70S ribosome, with an average resolution of 5.4 Å for the small 30S subunit and 3.6 Å for the large 50S ribosomal subunit. The structure reveals the location of the plastid-specific ribosomal proteins (RPs) PSRP1, PSRP4, PSRP5 and PSRP6 as well as the numerous plastid-specific extensions of the RPs. We discover many features by which the plastid-specific extensions stabilize the ribosome via establishing additional interactions with surrounding ribosomal RNA and RPs. Moreover, we identify a large conglomerate of plastid-specific protein mass adjacent to the tunnel exit site that could facilitate interaction of the chloroplast ribosome with the thylakoid membrane and the protein-targeting machinery. Comparing the Escherichia coli 70S ribosome with that of the spinach chloroplast ribosome provides detailed insight into the co-evolution of RP and rRNA. PMID:27986857

Hidden Markov model-derived structural alphabet for proteins: the learning of protein local shapes captures sequence specificity.

PubMed

Camproux, A C; Tufféry, P

2005-08-05

Understanding and predicting protein structures depend on the complexity and the accuracy of the models used to represent them. We have recently set up a Hidden Markov Model to optimally compress protein three-dimensional conformations into a one-dimensional series of letters of a structural alphabet. Such a model learns simultaneously the shape of representative structural letters describing the local conformation and the logic of their connections, i.e. the transition matrix between the letters. Here, we move one step further and report some evidence that such a model of protein local architecture also captures some accurate amino acid features. All the letters have specific and distinct amino acid distributions. Moreover, we show that words of amino acids can have significant propensities for some letters. Perspectives point towards the prediction of the series of letters describing the structure of a protein from its amino acid sequence.

Ethnic and Gender Considerations in the Use of Facial Injectables: African-American Patients.

PubMed

Burgess, Cheryl; Awosika, Olabola

2015-11-01

The United States is becoming increasingly more diverse as the nonwhite population continues to rise faster than ever. By 2044, the US Census Bureau projects that greater than 50% of the US population will be of nonwhite descent. Ethnic patients are the quickest growing portion of the cosmetic procedures market, with African-Americans comprising 7.1% of the 22% of ethnic minorities who received cosmetic procedures in the United States in 2014. The cosmetic concerns and natural features of this ethnic population are unique and guided by differing structural and aging processes than their white counterparts. As people of color increasingly seek nonsurgical cosmetic procedures, dermatologists and cosmetic surgeons must become aware that the Westernized look does not necessarily constitute beauty in these diverse people. The use of specialized aesthetic approaches and understanding of cultural and ethnic-specific features are warranted in the treatment of these patients. This article will review the key principles to consider when treating African-American patients, including the average facial structure of African-Americans, the impact of their ethnicity on aging and structure of face, and soft-tissue augmentation strategies specific to African-American skin.

Information Book Read-Alouds as Models for Second-Grade Authors

ERIC Educational Resources Information Center

Bradley, Linda Golson; Donovan, Carol A.

2010-01-01

This article discusses the instructional practice of supporting second graders' information book writing with focused read-alouds that include discussions of information book genre elements, features, and organizational structure. The authors present specific examples of instruction and discuss the resulting information book compositions by…

Effects of moiré lattice structure on electronic properties of graphene

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Lunan; Wu, Yun; Hershberger, M. T.

Here, we study structural and electronic properties of graphene grown on silicone carbide (SiC) substrate using a scanning tunneling microscope, spot-profile-analysis low-energy electron diffraction, and angle-resolved photoemission spectroscopy. We find several new replicas of Dirac cones in the Brillouin zone. Their locations can be understood in terms of a combination of basis vectors linked to SiC 6 × 6 and graphene 6√3×6√3 reconstruction. Therefore, these new features originate from the moiré caused by the lattice mismatch between SiC and graphene. More specifically, Dirac cone replicas are caused by underlying weak modulation of the ionic potential by the substrate that ismore » then experienced by the electrons in the graphene. We also demonstrate that this effect is equally strong in single- and trilayer graphene; therefore, the additional Dirac cones are intrinsic features rather than the result of photoelectron diffraction. These new features in the electronic structure are very important for the interpretation of recent transport measurements and can assist in tuning the properties of graphene for practical applications.« less

Effects of moiré lattice structure on electronic properties of graphene

NASA Astrophysics Data System (ADS)

Huang, Lunan; Wu, Yun; Hershberger, M. T.; Mou, Daixiang; Schrunk, Benjamin; Tringides, Michael C.; Hupalo, Myron; Kaminski, Adam

2017-07-01

We study structural and electronic properties of graphene grown on silicone carbide (SiC) substrate using a scanning tunneling microscope, spot-profile-analysis low-energy electron diffraction, and angle-resolved photoemission spectroscopy. We find several new replicas of Dirac cones in the Brillouin zone. Their locations can be understood in terms of a combination of basis vectors linked to SiC 6 × 6 and graphene 6 √{3 }×6 √{3 } reconstruction. Therefore, these new features originate from the moiré caused by the lattice mismatch between SiC and graphene. More specifically, Dirac cone replicas are caused by underlying weak modulation of the ionic potential by the substrate that is then experienced by the electrons in the graphene. We also demonstrate that this effect is equally strong in single- and trilayer graphene; therefore, the additional Dirac cones are intrinsic features rather than the result of photoelectron diffraction. These new features in the electronic structure are very important for the interpretation of recent transport measurements and can assist in tuning the properties of graphene for practical applications.

Effects of moiré lattice structure on electronic properties of graphene

DOE PAGES

Huang, Lunan; Wu, Yun; Hershberger, M. T.; ...

2017-07-10

Here, we study structural and electronic properties of graphene grown on silicone carbide (SiC) substrate using a scanning tunneling microscope, spot-profile-analysis low-energy electron diffraction, and angle-resolved photoemission spectroscopy. We find several new replicas of Dirac cones in the Brillouin zone. Their locations can be understood in terms of a combination of basis vectors linked to SiC 6 × 6 and graphene 6√3×6√3 reconstruction. Therefore, these new features originate from the moiré caused by the lattice mismatch between SiC and graphene. More specifically, Dirac cone replicas are caused by underlying weak modulation of the ionic potential by the substrate that ismore » then experienced by the electrons in the graphene. We also demonstrate that this effect is equally strong in single- and trilayer graphene; therefore, the additional Dirac cones are intrinsic features rather than the result of photoelectron diffraction. These new features in the electronic structure are very important for the interpretation of recent transport measurements and can assist in tuning the properties of graphene for practical applications.« less

Stimulus Dependency of Object-Evoked Responses in Human Visual Cortex: An Inverse Problem for Category Specificity

PubMed Central

Graewe, Britta; De Weerd, Peter; Farivar, Reza; Castelo-Branco, Miguel

2012-01-01

Many studies have linked the processing of different object categories to specific event-related potentials (ERPs) such as the face-specific N170. Despite reports showing that object-related ERPs are influenced by visual stimulus features, there is consensus that these components primarily reflect categorical aspects of the stimuli. Here, we re-investigated this idea by systematically measuring the effects of visual feature manipulations on ERP responses elicited by both structure-from-motion (SFM)-defined and luminance-defined object stimuli. SFM objects elicited a novel component at 200–250 ms (N250) over parietal and posterior temporal sites. We found, however, that the N250 amplitude was unaffected by restructuring SFM stimuli into meaningless objects based on identical visual cues. This suggests that this N250 peak was not uniquely linked to categorical aspects of the objects, but is strongly determined by visual stimulus features. We provide strong support for this hypothesis by parametrically manipulating the depth range of both SFM- and luminance-defined object stimuli and showing that the N250 evoked by SFM stimuli as well as the well-known N170 to static faces were sensitive to this manipulation. Importantly, this effect could not be attributed to compromised object categorization in low depth stimuli, confirming a strong impact of visual stimulus features on object-related ERP signals. As ERP components linked with visual categorical object perception are likely determined by multiple stimulus features, this creates an interesting inverse problem when deriving specific perceptual processes from variations in ERP components. PMID:22363479

Stimulus dependency of object-evoked responses in human visual cortex: an inverse problem for category specificity.

PubMed

Graewe, Britta; De Weerd, Peter; Farivar, Reza; Castelo-Branco, Miguel

2012-01-01

Many studies have linked the processing of different object categories to specific event-related potentials (ERPs) such as the face-specific N170. Despite reports showing that object-related ERPs are influenced by visual stimulus features, there is consensus that these components primarily reflect categorical aspects of the stimuli. Here, we re-investigated this idea by systematically measuring the effects of visual feature manipulations on ERP responses elicited by both structure-from-motion (SFM)-defined and luminance-defined object stimuli. SFM objects elicited a novel component at 200-250 ms (N250) over parietal and posterior temporal sites. We found, however, that the N250 amplitude was unaffected by restructuring SFM stimuli into meaningless objects based on identical visual cues. This suggests that this N250 peak was not uniquely linked to categorical aspects of the objects, but is strongly determined by visual stimulus features. We provide strong support for this hypothesis by parametrically manipulating the depth range of both SFM- and luminance-defined object stimuli and showing that the N250 evoked by SFM stimuli as well as the well-known N170 to static faces were sensitive to this manipulation. Importantly, this effect could not be attributed to compromised object categorization in low depth stimuli, confirming a strong impact of visual stimulus features on object-related ERP signals. As ERP components linked with visual categorical object perception are likely determined by multiple stimulus features, this creates an interesting inverse problem when deriving specific perceptual processes from variations in ERP components.

Using Multispectral False Color Imaging to Characterize Tropical Cyclone Structure and Environment

NASA Astrophysics Data System (ADS)

Cossuth, J.; Bankert, R.; Richardson, K.; Surratt, M. L.

2016-12-01

The Naval Research Laboratory's (NRL) tropical cyclone (TC) web page (http://www.nrlmry.navy.mil/TC.html) has provided nearly two decades of near real-time access to TC-centric images and products by TC forecasters and enthusiasts around the world. Particularly, microwave imager and sounder information that is featured on this site provides crucial internal storm structure information by allowing users to perceive hydrometeor structure, providing key details beyond cloud top information provided by visible and infrared channels. Towards improving TC analysis techniques and helping advance the utility of the NRL TC webpage resource, new research efforts are presented. This work demonstrates results as well as the methodology used to develop new automated, objective satellite-based TC structure and intensity guidance and enhanced data fusion imagery products that aim to bolster and streamline TC forecast operations. This presentation focuses on the creation and interpretation of false color RGB composite imagery that leverages the different emissive and scattering properties of atmospheric ice, liquid, and vapor water as well as ocean surface roughness as seen by microwave radiometers. Specifically, a combination of near-realtime data and a standardized digital database of global TCs in microwave imagery from 1987-2012 is employed as a climatology of TC structures. The broad range of TC structures, from pinhole eyes through multiple eyewall configurations, is characterized as resolved by passive microwave sensors. The extraction of these characteristic features from historical data also lends itself to statistical analysis. For example, histograms of brightness temperature distributions allows a rigorous examination of how structural features are conveyed in image products, allowing a better representation of colors and breakpoints as they relate to physical features. Such climatological work also suggests steps to better inform the near-real time application of upcoming satellite datasets to TC analyses.

Characterization of Novel Plasmonic, Photonic, and Semiconductor Microstructures

NASA Astrophysics Data System (ADS)

Sears, Jasmine Soria

The fields of telecommunications and optoelectronics are under constant pressure to shrink devices and reduce power consumption. Micro-scale photonic and plasmonic structures can trap light and enhance the brightness of active emitters; thus, these types of structures are promising avenues to accomplishing the goals of miniaturization and efficiency. A deeper understanding of specific structures is important in order to gauge their suitability for specific applications. In this dissertation, two types of microstructures are explored: one-dimensional silicon photonic crystals and self-assembled indium islands. This dissertation will provide novel characterization of these structures and a description of how to utilize or compensate for the observed features. A photonic crystal can act as a tiny resonator for certain wavelengths, making it a promising structure for applications that require extremely small lasers. However, because of silicon’s indirect bandgap, a silicon photonic crystal cavity would require the addition of an active emitter to function as a light source. Attempts to incorporate erbium into these cavities, and the observation of an unusual coupling phenomenon, will be discussed. Self-assembled indium islands are plasmonic structures that can be grown via molecular beam epitaxy. In theory, these islands should be pure indium nanoantennas on top of a smooth gallium arsenide substrate. In practice, the component materials are less segregated than predicted, giving rise to unexpected hollow dome shapes and a sub-surface indium layer. Although these features were not an intended result of indium island growth, they provide information regarding the island formation process and potentially contribute additional applications.

Protein control of true, gated, and coupled electron transfer reactions.

PubMed

Davidson, Victor L

2008-06-01

Electron transfer (ET) through and between proteins is a fundamental biological process. The rates of ET depend upon the thermodynamic driving force, the reorganization energy, and the degree of electronic coupling between the reactant and product states. The analysis of protein ET reactions is complicated by the fact that non-ET processes might influence the observed ET rate in kinetically complex biological systems. This Account describes studies of the methylamine dehydrogenase-amicyanin-cytochrome c-551i protein ET complex that have revealed the influence of several features of the protein structure on the magnitudes of the physical parameters for true ET reactions and how they dictate the kinetic mechanisms of non-ET processes that sometimes influence protein ET reactions. Kinetic and thermodynamic studies, coupled with structural information and biochemical data, are necessary to fully describe the ET reactions of proteins. Site-directed mutagenesis can be used to elucidate specific structure-function relationships. When mutations selectively alter the electronic coupling, reorganization energy, or driving force for the ET reaction, it becomes possible to use the parameters of the ET process to determine how specific amino acid residues and other features of the protein structure influence the ET rates. When mutations alter the kinetic mechanism for ET, one can determine the mechanisms by which non-ET processes, such as protein conformational changes or proton transfers, control the rates of ET reactions and how specific amino acid residues and certain features of the protein structure influence these non-ET reactions. A complete description of the mechanism of regulation of biological ET reactions enhances our understanding of metabolism, respiration, and photosynthesis at the molecular level. Such information has important medical relevance. Defective protein ET leads to production of the reactive oxygen species and free radicals that are associated with aging and many disease states. Defective ET within the respiratory chain also causes certain mitochondrial myopathies. An understanding of the mechanisms of regulation of protein ET is also of practical value because it provides a logical basis for the design of applications utilizing redox enzymes, such as enzyme-based electrode sensors and fuel cells.

On the determination of the origin of linear anomaly in the macrostructure of VPPA welded 2219-T87 aluminum alloy

NASA Technical Reports Server (NTRS)

Jemian, W. A.

1986-01-01

The objective was to determine the cause and significance of the weld radiograph enigma, which is a linear anomaly in the features of the X-ray film. By observing features on available radiographs and in studying published reports of similar features it was possible to conclude that there are many manifestations of the enigma, and that they are all specific features of fine structure in radiographs due to natural processes connected with welding and to specific X-ray absorption and diffraction phenomena. These processes include the thermal distribution and liquid metal flow in welding, the development of microstructure, morpohology, second phase particles and porosity due to the solidification process and to the pattern of residual stresses after the weld metal has cooled to the ambient temperature. Microdensitometer traces were made across weld radiographs of standard and enigmatic types. Similar patterns were produced by computer simulation. These show that the enigma is a relatively low contrast feature compared to real weld defects, such as undercuts or centerline cracks. The enigma can be distinguished from weld defects by these microdensitometer traces. The enigma effect on weld properties is not known but is expected to be minor.

On the determination of the origin of linear anomaly in the macrostructure of VPPA welded 2219-T87 aluminum alloy: Preliminary report

NASA Technical Reports Server (NTRS)

Jemian, W. A.

1986-01-01

The cause and significance of the weld radiograph enigma, which is a linear anomaly in the features of the X-ray film is examined. By observing features on available radiographs and in studying published reports of similar features, it was possible to conclude that there are many manifestations of the enigma, and that they are all specific features of fine structure in radiographs due to natural processes connected with welding and to specific X-ray absorption and diffraction phenomena. These processes include the thermal distribution and liquid metal flow in welding, the development of microstructure, morphology, second phase particles and porosity due to the solidification process, and to the pattern of residual stresses after the weld metal has cooled to the ambient temperature. Microdensitometer traces were made across weld radiographs of standard enigmatic types. Similar patterns were produced by computer simulation. These show that the enigma is a relatively low contrast feature compared to real weld defects, such as undercuts or centerline cracks. The enigma can be distinguished from weld defects by these microdensitometer traces. The enigma effect on weld properties is not known but is expected to be minor.

Multimedia Classifier

NASA Astrophysics Data System (ADS)

Costache, G. N.; Gavat, I.

2004-09-01

Along with the aggressive growing of the amount of digital data available (text, audio samples, digital photos and digital movies joined all in the multimedia domain) the need for classification, recognition and retrieval of this kind of data became very important. In this paper will be presented a system structure to handle multimedia data based on a recognition perspective. The main processing steps realized for the interesting multimedia objects are: first, the parameterization, by analysis, in order to obtain a description based on features, forming the parameter vector; second, a classification, generally with a hierarchical structure to make the necessary decisions. For audio signals, both speech and music, the derived perceptual features are the melcepstral (MFCC) and the perceptual linear predictive (PLP) coefficients. For images, the derived features are the geometric parameters of the speaker mouth. The hierarchical classifier consists generally in a clustering stage, based on the Kohonnen Self-Organizing Maps (SOM) and a final stage, based on a powerful classification algorithm called Support Vector Machines (SVM). The system, in specific variants, is applied with good results in two tasks: the first, is a bimodal speech recognition which uses features obtained from speech signal fused to features obtained from speaker's image and the second is a music retrieval from large music database.

Binding affinities of vascular endothelial growth factor (VEGF) for heparin-derived oligosaccharides

PubMed Central

Zhao, Wenjing; McCallum, Scott A.; Xiao, Zhongping; Zhang, Fuming; Linhardt, Robert J.

2011-01-01

Heparin and heparan sulphate (HS) exert their wide range of biological activities by interacting with extracellular protein ligands. Among these important protein ligands are various angiogenic growth factors and cytokines. HS-binding to vascular endothelial growth factor (VEGF) regulates multiple aspects of vascular development and function through its specific interaction with HS. Many studies have focused on HS-derived or HS-mimicking structures for the characterization of VEGF165 interaction with HS. Using a heparinase 1-prepared small library of heparin-derived oligosaccharides ranging from hexasaccharide to octadecasaccharide, we systematically investigated the heparin-specific structural features required for VEGF binding. We report the apparent affinities for the association between the heparin-derived oligosaccharides with both VEGF165 and VEGF55, a peptide construct encompassing exclusively the heparin-binding domain of VEGF165. An octasaccharide was the minimum size of oligosaccharide within the library to efficiently bind to both forms of VEGF and that a tetradecasaccharide displayed an effective binding affinity to VEGF165 comparable to unfractionated heparin. The range of relative apparent binding affinities among VEGF and the panel of heparin-derived oligosaccharides demonstrate that VEGF binding affinity likely depends on the specific structural features of these oligosaccharides including their degree of sulphation and sugar ring stereochemistry and conformation. Notably, the unique 3-O-sulpho group found within the specific antithrombin binding site of heparin is not required for VEGF165 binding. These findings afford new insight into the inherent kinetics and affinities for VEGF association with heparin and heparin-derived oligosaccharides with key residue specific modifications and may potentially benefit the future design of oligosaccharide-based anti-angiogenesis drugs. PMID:21658003

Automated prediction of protein function and detection of functional sites from structure.

PubMed

Pazos, Florencio; Sternberg, Michael J E

2004-10-12

Current structural genomics projects are yielding structures for proteins whose functions are unknown. Accordingly, there is a pressing requirement for computational methods for function prediction. Here we present PHUNCTIONER, an automatic method for structure-based function prediction using automatically extracted functional sites (residues associated to functions). The method relates proteins with the same function through structural alignments and extracts 3D profiles of conserved residues. Functional features to train the method are extracted from the Gene Ontology (GO) database. The method extracts these features from the entire GO hierarchy and hence is applicable across the whole range of function specificity. 3D profiles associated with 121 GO annotations were extracted. We tested the power of the method both for the prediction of function and for the extraction of functional sites. The success of function prediction by our method was compared with the standard homology-based method. In the zone of low sequence similarity (approximately 15%), our method assigns the correct GO annotation in 90% of the protein structures considered, approximately 20% higher than inheritance of function from the closest homologue.

Fault-tolerant control of large space structures using the stable factorization approach

NASA Technical Reports Server (NTRS)

Razavi, H. C.; Mehra, R. K.; Vidyasagar, M.

1986-01-01

Large space structures are characterized by the following features: they are in general infinite-dimensional systems, and have large numbers of undamped or lightly damped poles. Any attempt to apply linear control theory to large space structures must therefore take into account these features. Phase I consisted of an attempt to apply the recently developed Stable Factorization (SF) design philosophy to problems of large space structures, with particular attention to the aspects of robustness and fault tolerance. The final report on the Phase I effort consists of four sections, each devoted to one task. The first three sections report theoretical results, while the last consists of a design example. Significant results were obtained in all four tasks of the project. More specifically, an innovative approach to order reduction was obtained, stabilizing controller structures for plants with an infinite number of unstable poles were determined under some conditions, conditions for simultaneous stabilizability of an infinite number of plants were explored, and a fault tolerance controller design that stabilizes a flexible structure model was obtained which is robust against one failure condition.

The representation of semantic knowledge in a child with Williams syndrome.

PubMed

Robinson, Sally J; Temple, Christine M

2009-05-01

This study investigated whether there are distinct types of semantic knowledge with distinct representational bases during development. The representation of semantic knowledge in a teenage child (S.T.) with Williams syndrome was explored for the categories of animals, fruit, and vegetables, manipulable objects, and nonmanipulable objects. S.T.'s lexical stores were of a normal size but the volume of "sensory feature" semantic knowledge she generated in oral descriptions was reduced. In visual recognition decisions, S.T. made more false positives to nonitems than did controls. Although overall naming of pictures was unimpaired, S.T. exhibited a category-specific anomia for nonmanipulable objects and impaired naming of visual-feature descriptions of animals. S.T.'s performance was interpreted as reflecting the impaired integration of distinctive features from perceptual input, which may impact upon nonmanipulable objects to a greater extent than the other knowledge categories. Performance was used to inform adult-based models of semantic representation, with category structure proposed to emerge due to differing degrees of dependency upon underlying knowledge types, feature correlations, and the acquisition of information from modality-specific processing modules.

Elementary teachers' perceptions about the effective features of explicit-reflective nature of science instruction

NASA Astrophysics Data System (ADS)

Adibelli-Sahin, Elif; Deniz, Hasan

2017-04-01

This qualitative study explored elementary teachers' perceptions about the effective features of explicit-reflective nature of science (NOS) instruction. Our participants were four elementary teachers from a public charter school located in the Southwestern U.S.A. The four elementary teachers participated in an academic year-long professional development about NOS which consisted of NOS training and NOS teaching phases. After each phase of the professional development, we specifically asked our participants which features of the explicit-reflective NOS instruction they found effective in improving their NOS conceptions by presenting pre- and post-profiles of their NOS conceptions. We identified nine features perceived by the participants as effective components of explicit-reflective NOS instruction: (1) specific focus on NOS content, (2) participation in hands-on NOS activities, (3) introductory NOS readings, (4) multiple types/forms of reflection, (5) multiple exposure to NOS content, (6) structural consistency in the presentation of NOS content, (7) the evaluation of secondary NOS data from elementary students, (8) the analysis of national and state science standards in terms of NOS content, and (9) NOS teaching experience.

Polymyxins and quinazolines are LSD1/KDM1A inhibitors with unusual structural features.

PubMed

Speranzini, Valentina; Rotili, Dante; Ciossani, Giuseppe; Pilotto, Simona; Marrocco, Biagina; Forgione, Mariantonietta; Lucidi, Alessia; Forneris, Federico; Mehdipour, Parinaz; Velankar, Sameer; Mai, Antonello; Mattevi, Andrea

2016-09-01

Because of its involvement in the progression of several malignant tumors, the histone lysine-specific demethylase 1 (LSD1) has become a prominent drug target in modern medicinal chemistry research. We report on the discovery of two classes of noncovalent inhibitors displaying unique structural features. The antibiotics polymyxins bind at the entrance of the substrate cleft, where their highly charged cyclic moiety interacts with a cluster of positively charged amino acids. The same site is occupied by quinazoline-based compounds, which were found to inhibit the enzyme through a most peculiar mode because they form a pile of five to seven molecules that obstruct access to the active center. These data significantly indicate unpredictable strategies for the development of epigenetic inhibitors.

Acceleration Testing: A Better, Faster, Cheaper Alternative for Strength Qualification Testing

NASA Technical Reports Server (NTRS)

Mattiello, Carmine F.

1997-01-01

This paper addresses the advantages of utilizing a centrifuge test over the conventional static load test methods to structurally qualify aerospace structures. Three recent test cases are reviewed and used as examples to highlight these benefits. In addition, the overall capability of Goddard's High Capacity Centrifuge (HCC) is outlined along with some unique features that were designed specifically to reduce costs, test turn around time, and increase test item safety.

Reinforcement learning algorithms for robotic navigation in dynamic environments.

PubMed

Yen, Gary G; Hickey, Travis W

2004-04-01

The purpose of this study was to examine improvements to reinforcement learning (RL) algorithms in order to successfully interact within dynamic environments. The scope of the research was that of RL algorithms as applied to robotic navigation. Proposed improvements include: addition of a forgetting mechanism, use of feature based state inputs, and hierarchical structuring of an RL agent. Simulations were performed to evaluate the individual merits and flaws of each proposal, to compare proposed methods to prior established methods, and to compare proposed methods to theoretically optimal solutions. Incorporation of a forgetting mechanism did considerably improve the learning times of RL agents in a dynamic environment. However, direct implementation of a feature-based RL agent did not result in any performance enhancements, as pure feature-based navigation results in a lack of positional awareness, and the inability of the agent to determine the location of the goal state. Inclusion of a hierarchical structure in an RL agent resulted in significantly improved performance, specifically when one layer of the hierarchy included a feature-based agent for obstacle avoidance, and a standard RL agent for global navigation. In summary, the inclusion of a forgetting mechanism, and the use of a hierarchically structured RL agent offer substantially increased performance when compared to traditional RL agents navigating in a dynamic environment.

Teaching structure: student use of software tools for understanding macromolecular structure in an undergraduate biochemistry course.

PubMed

Jaswal, Sheila S; O'Hara, Patricia B; Williamson, Patrick L; Springer, Amy L

2013-01-01

Because understanding the structure of biological macromolecules is critical to understanding their function, students of biochemistry should become familiar not only with viewing, but also with generating and manipulating structural representations. We report a strategy from a one-semester undergraduate biochemistry course to integrate use of structural representation tools into both laboratory and homework activities. First, early in the course we introduce the use of readily available open-source software for visualizing protein structure, coincident with modules on amino acid and peptide bond properties. Second, we use these same software tools in lectures and incorporate images and other structure representations in homework tasks. Third, we require a capstone project in which teams of students examine a protein-nucleic acid complex and then use the software tools to illustrate for their classmates the salient features of the structure, relating how the structure helps explain biological function. To ensure engagement with a range of software and database features, we generated a detailed template file that can be used to explore any structure, and that guides students through specific applications of many of the software tools. In presentations, students demonstrate that they are successfully interpreting structural information, and using representations to illustrate particular points relevant to function. Thus, over the semester students integrate information about structural features of biological macromolecules into the larger discussion of the chemical basis of function. Together these assignments provide an accessible introduction to structural representation tools, allowing students to add these methods to their biochemical toolboxes early in their scientific development. © 2013 by The International Union of Biochemistry and Molecular Biology.

Improving EEG-Based Driver Fatigue Classification Using Sparse-Deep Belief Networks.

PubMed

Chai, Rifai; Ling, Sai Ho; San, Phyo Phyo; Naik, Ganesh R; Nguyen, Tuan N; Tran, Yvonne; Craig, Ashley; Nguyen, Hung T

2017-01-01

This paper presents an improvement of classification performance for electroencephalography (EEG)-based driver fatigue classification between fatigue and alert states with the data collected from 43 participants. The system employs autoregressive (AR) modeling as the features extraction algorithm, and sparse-deep belief networks (sparse-DBN) as the classification algorithm. Compared to other classifiers, sparse-DBN is a semi supervised learning method which combines unsupervised learning for modeling features in the pre-training layer and supervised learning for classification in the following layer. The sparsity in sparse-DBN is achieved with a regularization term that penalizes a deviation of the expected activation of hidden units from a fixed low-level prevents the network from overfitting and is able to learn low-level structures as well as high-level structures. For comparison, the artificial neural networks (ANN), Bayesian neural networks (BNN), and original deep belief networks (DBN) classifiers are used. The classification results show that using AR feature extractor and DBN classifiers, the classification performance achieves an improved classification performance with a of sensitivity of 90.8%, a specificity of 90.4%, an accuracy of 90.6%, and an area under the receiver operating curve (AUROC) of 0.94 compared to ANN (sensitivity at 80.8%, specificity at 77.8%, accuracy at 79.3% with AUC-ROC of 0.83) and BNN classifiers (sensitivity at 84.3%, specificity at 83%, accuracy at 83.6% with AUROC of 0.87). Using the sparse-DBN classifier, the classification performance improved further with sensitivity of 93.9%, a specificity of 92.3%, and an accuracy of 93.1% with AUROC of 0.96. Overall, the sparse-DBN classifier improved accuracy by 13.8, 9.5, and 2.5% over ANN, BNN, and DBN classifiers, respectively.

Improving EEG-Based Driver Fatigue Classification Using Sparse-Deep Belief Networks

PubMed Central

Chai, Rifai; Ling, Sai Ho; San, Phyo Phyo; Naik, Ganesh R.; Nguyen, Tuan N.; Tran, Yvonne; Craig, Ashley; Nguyen, Hung T.

2017-01-01

This paper presents an improvement of classification performance for electroencephalography (EEG)-based driver fatigue classification between fatigue and alert states with the data collected from 43 participants. The system employs autoregressive (AR) modeling as the features extraction algorithm, and sparse-deep belief networks (sparse-DBN) as the classification algorithm. Compared to other classifiers, sparse-DBN is a semi supervised learning method which combines unsupervised learning for modeling features in the pre-training layer and supervised learning for classification in the following layer. The sparsity in sparse-DBN is achieved with a regularization term that penalizes a deviation of the expected activation of hidden units from a fixed low-level prevents the network from overfitting and is able to learn low-level structures as well as high-level structures. For comparison, the artificial neural networks (ANN), Bayesian neural networks (BNN), and original deep belief networks (DBN) classifiers are used. The classification results show that using AR feature extractor and DBN classifiers, the classification performance achieves an improved classification performance with a of sensitivity of 90.8%, a specificity of 90.4%, an accuracy of 90.6%, and an area under the receiver operating curve (AUROC) of 0.94 compared to ANN (sensitivity at 80.8%, specificity at 77.8%, accuracy at 79.3% with AUC-ROC of 0.83) and BNN classifiers (sensitivity at 84.3%, specificity at 83%, accuracy at 83.6% with AUROC of 0.87). Using the sparse-DBN classifier, the classification performance improved further with sensitivity of 93.9%, a specificity of 92.3%, and an accuracy of 93.1% with AUROC of 0.96. Overall, the sparse-DBN classifier improved accuracy by 13.8, 9.5, and 2.5% over ANN, BNN, and DBN classifiers, respectively. PMID:28326009

Some Comments on the Nature of Chinese ESP Coursebooks.

ERIC Educational Resources Information Center

Johns, Ann M.

English for specific purposes (ESP) coursebooks compiled by writers in the People's Republic of China are described. Eight textbooks are examined focusing on their common features in terms of reading passages, reliance upon Chinese language, focus upon the Chinese environment, emphasis upon structural grammar, focus upon vocabulary, rhetorical…

HUMAN GLYCERALDEHYDE 3-PHOSPHATE DEHYDROGENASE-2 (GAPD2) GENE IS EXPRESSED SPECIFICALLY IN SPERMATOGENIC CELLS

EPA Science Inventory

Although the process of glycolysis is highly conserved in eukaryotes, several glycolytic enzymes have unique structural or functional features in spermatogenic cells. We previously identified and characterized the mouse complementary DNA (cDNA) and a gene for 1 of these enzymes, ...

Transformation of the Schoolhouse. Annual Report for 1969.

ERIC Educational Resources Information Center

Coughlin, Gaila, Ed.

This report reviews some of the more important educational innovations that have transformed the arrangement of space and design of the schoolhouse environment. Design, structural, and functional features are described for open plan schools (schools without interior walls). Consideration is given to the use of performance specifications in the…

Network Interface Specification for the T1 Microprocessor

DTIC Science & Technology

1994-05-01

features data transfer directly to/from processor registers, hardware dispatch directly to Active Message handlers (along with limited context...Implementation Choices 9 3.1 Overview .................................... 9 3.2 Context ..................................... 10 3.3 Data Transfer...details of the data transfer functional units, interconnect structure, and network operation. Application Layer Communication Model Communication

Research on Higher Education: A U.S. Perspective.

ERIC Educational Resources Information Center

Toombs, William

Characteristics of U.S. higher education are identified, along with the structural features that influence the nature of research, specific research topics, and the locations of research activities. This information was obtained from several sources, including the Educational Resources Information Center database for the years 1981 and 1982, the…

Structure, phase transformations, mechanical characteristics, and cold resistance of low-carbon martensitic steels

NASA Astrophysics Data System (ADS)

Kozvonin, V. A.; Shatsov, A. A.; Ryaposov, I. V.; Zakirova, M. G.; Generalova, K. N.

2016-08-01

Temper-resistant low-carbon Cr-Mn-Ni-Mo-V-Nb steels with concentrations of carbon of 0.15 and 0.27 wt % have been studied. It has been shown that, upon quenching, various morphological types of the α phase can be formed. The structure of the steels is stable in the course of heating below critical temperatures and remains a lath-type structure in the intercritical temperature range. Specific features of structural and phase transformations, as well as the dependence of the mechanical characteristics of the steels, on the tempering temperature have been determined.

Resilience of Adapting Networks: Results from a Stylized Infrastructure Model.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beyeler, Walter E.; Vugrin, Eric D.; Forden, Geoffrey Ethan

2015-01-01

Adaptation is believed to be a source of resilience in systems. It has been difficult to measure the contribution of adaptation to resilience, unlike other resilience mechanisms such as restoration and recovery. One difficulty comes from treating adaptation as a deus ex machina that is interjected after a disruption. This provides no basis for bounding possible adaptive responses. We can bracket the possible effects of adaptation when we recognize that it occurs continuously, and is in part responsible for the current system’s properties. In this way the dynamics of the system’s pre-disruption structure provides information about post-disruption adaptive reaction. Seenmore » as an ongoing process, adaptation has been argued to produce “robust-yet-fragile” systems. Such systems perform well under historical stresses but become committed to specific features of those stresses in a way that makes them vulnerable to system-level collapse when those features change. In effect adaptation lessens the cost of disruptions within a certain historical range, at the expense of increased cost from disruptions outside that range. Historical adaptive responses leave a signature in the structure of the system. Studies of ecological networks have suggested structural metrics that pick out systemic resilience in the underlying ecosystems. If these metrics are generally reliable indicators of resilience they provide another strategy for gaging adaptive resilience. To progress in understanding how the process of adaptation and the property of resilience interrelate in infrastructure systems, we pose some specific questions: Does adaptation confer resilience?; Does it confer resilience to novel shocks as well, or does it tune the system to fragility?; Can structural features predict resilience to novel shocks?; Are there policies or constraints on the adaptive process that improve resilience?.« less

Loss of integrity and atrophy in cingulate structural covariance networks in Parkinson's disease.

PubMed

de Schipper, Laura J; van der Grond, Jeroen; Marinus, Johan; Henselmans, Johanna M L; van Hilten, Jacobus J

2017-01-01

In Parkinson's disease (PD), the relation between cortical brain atrophy on MRI and clinical progression is not straightforward. Determination of changes in structural covariance networks - patterns of covariance in grey matter density - has shown to be a valuable technique to detect subtle grey matter variations. We evaluated how structural network integrity in PD is related to clinical data. 3 Tesla MRI was performed in 159 PD patients. We used nine standardized structural covariance networks identified in 370 healthy subjects as a template in the analysis of the PD data. Clinical assessment comprised motor features (Movement Disorder Society-Unified Parkinson's Disease Rating Scale; MDS-UPDRS motor scale) and predominantly non-dopaminergic features (SEverity of Non-dopaminergic Symptoms in Parkinson's Disease; SENS-PD scale: postural instability and gait difficulty, psychotic symptoms, excessive daytime sleepiness, autonomic dysfunction, cognitive impairment and depressive symptoms). Voxel-based analyses were performed within networks significantly associated with PD. The anterior and posterior cingulate network showed decreased integrity, associated with the SENS-PD score, p = 0.001 (β = - 0.265, η p 2  = 0.070) and p = 0.001 (β = - 0.264, η p 2  = 0.074), respectively. Of the components of the SENS-PD score, cognitive impairment and excessive daytime sleepiness were associated with atrophy within both networks. We identified loss of integrity and atrophy in the anterior and posterior cingulate networks in PD patients. Abnormalities of both networks were associated with predominantly non-dopaminergic features, specifically cognition and excessive daytime sleepiness. Our findings suggest that (components of) the cingulate networks display a specific vulnerability to the pathobiology of PD and may operate as interfaces between networks involved in cognition and alertness.

Multi-channel MRI segmentation of eye structures and tumors using patient-specific features

PubMed Central

Ciller, Carlos; De Zanet, Sandro; Kamnitsas, Konstantinos; Maeder, Philippe; Glocker, Ben; Munier, Francis L.; Rueckert, Daniel; Thiran, Jean-Philippe

2017-01-01

Retinoblastoma and uveal melanoma are fast spreading eye tumors usually diagnosed by using 2D Fundus Image Photography (Fundus) and 2D Ultrasound (US). Diagnosis and treatment planning of such diseases often require additional complementary imaging to confirm the tumor extend via 3D Magnetic Resonance Imaging (MRI). In this context, having automatic segmentations to estimate the size and the distribution of the pathological tissue would be advantageous towards tumor characterization. Until now, the alternative has been the manual delineation of eye structures, a rather time consuming and error-prone task, to be conducted in multiple MRI sequences simultaneously. This situation, and the lack of tools for accurate eye MRI analysis, reduces the interest in MRI beyond the qualitative evaluation of the optic nerve invasion and the confirmation of recurrent malignancies below calcified tumors. In this manuscript, we propose a new framework for the automatic segmentation of eye structures and ocular tumors in multi-sequence MRI. Our key contribution is the introduction of a pathological eye model from which Eye Patient-Specific Features (EPSF) can be computed. These features combine intensity and shape information of pathological tissue while embedded in healthy structures of the eye. We assess our work on a dataset of pathological patient eyes by computing the Dice Similarity Coefficient (DSC) of the sclera, the cornea, the vitreous humor, the lens and the tumor. In addition, we quantitatively show the superior performance of our pathological eye model as compared to the segmentation obtained by using a healthy model (over 4% DSC) and demonstrate the relevance of our EPSF, which improve the final segmentation regardless of the classifier employed. PMID:28350816

The crystal structure of mammalian inositol 1,3,4,5,6-pentakisphosphate 2-kinase reveals a new zinc-binding site and key features for protein function

PubMed Central

Franco-Echevarría, Elsa; Sanz-Aparicio, Julia; Brearley, Charles A.; González-Rubio, Juana M.; González, Beatriz

2017-01-01

Inositol 1,3,4,5,6-pentakisphosphate 2-kinases (IP5 2-Ks) are part of a family of enzymes in charge of synthesizing inositol hexakisphosphate (IP6) in eukaryotic cells. This protein and its product IP6 present many roles in cells, participating in mRNA export, embryonic development, and apoptosis. We reported previously that the full-length IP5 2-K from Arabidopsis thaliana is a zinc metallo-enzyme, including two separated lobes (the N- and C-lobes). We have also shown conformational changes in IP5 2-K and have identified the residues involved in substrate recognition and catalysis. However, the specific features of mammalian IP5 2-Ks remain unknown. To this end, we report here the first structure for a murine IP5 2-K in complex with ATP/IP5 or IP6. Our structural findings indicated that the general folding in N- and C-lobes is conserved with A. thaliana IP5 2-K. A helical scaffold in the C-lobe constitutes the inositol phosphate-binding site, which, along with the participation of the N-lobe, endows high specificity to this protein. However, we also noted large structural differences between the orthologues from these two eukaryotic kingdoms. These differences include a novel zinc-binding site and regions unique to the mammalian IP5 2-K, as an unexpected basic patch on the protein surface. In conclusion, our findings have uncovered distinct features of a mammalian IP5 2-K and set the stage for investigations into protein-protein or protein-RNA interactions important for IP5 2-K function and activity. PMID:28450399

Improve the prediction of RNA-binding residues using structural neighbours.

PubMed

Li, Quan; Cao, Zanxia; Liu, Haiyan

2010-03-01

The interactions between RNA-binding proteins (RBPs) with RNA play key roles in managing some of the cell's basic functions. The identification and prediction of RNA binding sites is important for understanding the RNA-binding mechanism. Computational approaches are being developed to predict RNA-binding residues based on the sequence- or structure-derived features. To achieve higher prediction accuracy, improvements on current prediction methods are necessary. We identified that the structural neighbors of RNA-binding and non-RNA-binding residues have different amino acid compositions. Combining this structure-derived feature with evolutionary (PSSM) and other structural information (secondary structure and solvent accessibility) significantly improves the predictions over existing methods. Using a multiple linear regression approach and 6-fold cross validation, our best model can achieve an overall correct rate of 87.8% and MCC of 0.47, with a specificity of 93.4%, correctly predict 52.4% of the RNA-binding residues for a dataset containing 107 non-homologous RNA-binding proteins. Compared with existing methods, including the amino acid compositions of structure neighbors lead to clearly improvement. A web server was developed for predicting RNA binding residues in a protein sequence (or structure),which is available at http://mcgill.3322.org/RNA/.

Breed-Specific Magnetic Resonance Imaging Characteristics of Necrotizing Encephalitis in Dogs

PubMed Central

Flegel, Thomas

2017-01-01

Diagnosing necrotizing encephalitis, with its subcategories of necrotizing leukoencephalitis and necrotizing meningoencephalitis, based on magnetic resonance imaging alone can be challenging. However, there are breed-specific imaging characteristics in both subcategories that allow establishing a clinical diagnosis with a relatively high degree of certainty. Typical breed specific imaging features, such as lesion distribution, signal intensity, contrast enhancement, and gross changes of brain structure (midline shift, ventriculomegaly, and brain herniation) are summarized here, using current literature, for the most commonly affected canine breeds: Yorkshire Terrier, French Bulldog, Pug, and Chihuahua. PMID:29255715

Unexpected features of the dark proteome.

PubMed

Perdigão, Nelson; Heinrich, Julian; Stolte, Christian; Sabir, Kenneth S; Buckley, Michael J; Tabor, Bruce; Signal, Beth; Gloss, Brian S; Hammang, Christopher J; Rost, Burkhard; Schafferhans, Andrea; O'Donoghue, Seán I

2015-12-29

We surveyed the "dark" proteome-that is, regions of proteins never observed by experimental structure determination and inaccessible to homology modeling. For 546,000 Swiss-Prot proteins, we found that 44-54% of the proteome in eukaryotes and viruses was dark, compared with only ∼14% in archaea and bacteria. Surprisingly, most of the dark proteome could not be accounted for by conventional explanations, such as intrinsic disorder or transmembrane regions. Nearly half of the dark proteome comprised dark proteins, in which the entire sequence lacked similarity to any known structure. Dark proteins fulfill a wide variety of functions, but a subset showed distinct and largely unexpected features, such as association with secretion, specific tissues, the endoplasmic reticulum, disulfide bonding, and proteolytic cleavage. Dark proteins also had short sequence length, low evolutionary reuse, and few known interactions with other proteins. These results suggest new research directions in structural and computational biology.

Numerical and Experimental Investigation of Cavitating Characteristics in Centrifugal Pump with Gap Impeller

NASA Astrophysics Data System (ADS)

Zhu, Bing; Chen, Hongxun; Wei, Qun

2014-06-01

This paper is to study the cavitating characteristics in a low specific speed centrifugal pump with gap structure impeller experimentally and numerically. A scalable DES numerical method is proposed and developed by introducing the von Karman scale instead of the local grid scale, which can switch at the RANS and LES region interface smoothly and reasonably. The SDES method can detect and grasp unsteady scale flow structures, which were proved by the flow around a triangular prism and the cavitation flow in a centrifugal pump. Through numerical and experimental research, it's shown that the simulated results match qualitatively with tested cavitation performances and visualization patterns, and we can conclude that the gap structure impeller has a superior feature of cavitation suppression. Its mechanism may be the guiding flow feature of the small vice blade and the pressure auto-balance effect of the gap tunnel.

Perspective: Optical measurement of feature dimensions and shapes by scatterometry

NASA Astrophysics Data System (ADS)

Diebold, Alain C.; Antonelli, Andy; Keller, Nick

2018-05-01

The use of optical scattering to measure feature shape and dimensions, scatterometry, is now routine during semiconductor manufacturing. Scatterometry iteratively improves an optical model structure using simulations that are compared to experimental data from an ellipsometer. These simulations are done using the rigorous coupled wave analysis for solving Maxwell's equations. In this article, we describe the Mueller matrix spectroscopic ellipsometry based scatterometry. Next, the rigorous coupled wave analysis for Maxwell's equations is presented. Following this, several example measurements are described as they apply to specific process steps in the fabrication of gate-all-around (GAA) transistor structures. First, simulations of measurement sensitivity for the inner spacer etch back step of horizontal GAA transistor processing are described. Next, the simulated metrology sensitivity for sacrificial (dummy) amorphous silicon etch back step of vertical GAA transistor processing is discussed. Finally, we present the application of plasmonically active test structures for improving the sensitivity of the measurement of metal linewidths.

Bone morphology of the hind limbs in two caviomorph rodents.

PubMed

de Araújo, F A P; Sesoko, N F; Rahal, S C; Teixeira, C R; Müller, T R; Machado, M R F

2013-04-01

In order to evaluate the hind limbs of caviomorph rodents a descriptive analysis of the Cuniculus paca (Linnaeus, 1766) and Hydrochoerus hydrochaeris (Linnaeus, 1766) was performed using anatomical specimens, radiography, computed tomography (CT) and full-coloured prototype models to generate bone anatomy data. The appendicular skeleton of the two largest rodents of Neotropical America was compared with the previously reported anatomical features of Rattus norvegicus (Berkenhout, 1769) and domestic Cavia porcellus (Linnaeus, 1758). The structures were analyzed macroscopically and particular findings of each species reported. Features including the presence of articular fibular projection and lunulae were observed in the stifle joint of all rodents. Imaging aided in anatomical description and, specifically in the identification of bone structures in Cuniculus paca and Hydrochoerus hydrochaeris. The imaging findings were correlated with the anatomical structures observed. The data may be used in future studies comparing these animals to other rodents and mammalian species. © 2012 Blackwell Verlag GmbH.

Unexpected features of the dark proteome

PubMed Central

Perdigão, Nelson; Heinrich, Julian; Stolte, Christian; Sabir, Kenneth S.; Buckley, Michael J.; Tabor, Bruce; Signal, Beth; Gloss, Brian S.; Hammang, Christopher J.; Rost, Burkhard; Schafferhans, Andrea

2015-01-01

We surveyed the “dark” proteome–that is, regions of proteins never observed by experimental structure determination and inaccessible to homology modeling. For 546,000 Swiss-Prot proteins, we found that 44–54% of the proteome in eukaryotes and viruses was dark, compared with only ∼14% in archaea and bacteria. Surprisingly, most of the dark proteome could not be accounted for by conventional explanations, such as intrinsic disorder or transmembrane regions. Nearly half of the dark proteome comprised dark proteins, in which the entire sequence lacked similarity to any known structure. Dark proteins fulfill a wide variety of functions, but a subset showed distinct and largely unexpected features, such as association with secretion, specific tissues, the endoplasmic reticulum, disulfide bonding, and proteolytic cleavage. Dark proteins also had short sequence length, low evolutionary reuse, and few known interactions with other proteins. These results suggest new research directions in structural and computational biology. PMID:26578815

Coupling Sensing Hardware with Data Interrogation Software for Structural Health Monitoring

DOE PAGES

Farrar, Charles R.; Allen, David W.; Park, Gyuhae; ...

2006-01-01

The process of implementing a damage detection strategy for aerospace, civil and mechanical engineering infrastructure is referred to as structural health monitoring (SHM). The authors' approach is to address the SHM problem in the context of a statistical pattern recognition paradigm. In this paradigm, the process can be broken down into four parts: (1) Operational Evaluation, (2) Data Acquisition and Cleansing, (3) Feature Extraction and Data Compression, and (4) Statistical Model Development for Feature Discrimination. These processes must be implemented through hardware or software and, in general, some combination of these two approaches will be used. This paper will discussmore » each portion of the SHM process with particular emphasis on the coupling of a general purpose data interrogation software package for structural health monitoring with a modular wireless sensing and processing platform. More specifically, this paper will address the need to take an integrated hardware/software approach to developing SHM solutions.« less

nextPARS: parallel probing of RNA structures in Illumina

PubMed Central

Saus, Ester; Willis, Jesse R.; Pryszcz, Leszek P.; Hafez, Ahmed; Llorens, Carlos; Himmelbauer, Heinz

2018-01-01

RNA molecules play important roles in virtually every cellular process. These functions are often mediated through the adoption of specific structures that enable RNAs to interact with other molecules. Thus, determining the secondary structures of RNAs is central to understanding their function and evolution. In recent years several sequencing-based approaches have been developed that allow probing structural features of thousands of RNA molecules present in a sample. Here, we describe nextPARS, a novel Illumina-based implementation of in vitro parallel probing of RNA structures. Our approach achieves comparable accuracy to previous implementations, while enabling higher throughput and sample multiplexing. PMID:29358234

Deep Multimodal Distance Metric Learning Using Click Constraints for Image Ranking.

PubMed

Yu, Jun; Yang, Xiaokang; Gao, Fei; Tao, Dacheng

2017-12-01

How do we retrieve images accurately? Also, how do we rank a group of images precisely and efficiently for specific queries? These problems are critical for researchers and engineers to generate a novel image searching engine. First, it is important to obtain an appropriate description that effectively represent the images. In this paper, multimodal features are considered for describing images. The images unique properties are reflected by visual features, which are correlated to each other. However, semantic gaps always exist between images visual features and semantics. Therefore, we utilize click feature to reduce the semantic gap. The second key issue is learning an appropriate distance metric to combine these multimodal features. This paper develops a novel deep multimodal distance metric learning (Deep-MDML) method. A structured ranking model is adopted to utilize both visual and click features in distance metric learning (DML). Specifically, images and their related ranking results are first collected to form the training set. Multimodal features, including click and visual features, are collected with these images. Next, a group of autoencoders is applied to obtain initially a distance metric in different visual spaces, and an MDML method is used to assign optimal weights for different modalities. Next, we conduct alternating optimization to train the ranking model, which is used for the ranking of new queries with click features. Compared with existing image ranking methods, the proposed method adopts a new ranking model to use multimodal features, including click features and visual features in DML. We operated experiments to analyze the proposed Deep-MDML in two benchmark data sets, and the results validate the effects of the method.

Structural hierarchy of autism spectrum disorder symptoms: an integrative framework.

PubMed

Kim, Hyunsik; Keifer, Cara M; Rodriguez-Seijas, Craig; Eaton, Nicholas R; Lerner, Matthew D; Gadow, Kenneth D

2018-01-01

In an attempt to resolve questions regarding the symptom classification of autism spectrum disorder (ASD), previous research generally aimed to demonstrate superiority of one model over another. Rather than adjudicating which model may be optimal, we propose an alternative approach that integrates competing models using Goldberg's bass-ackwards method, providing a comprehensive understanding of the underlying symptom structure of ASD. The study sample comprised 3,825 individuals, consecutive referrals to a university hospital developmental disabilities specialty clinic or a child psychiatry outpatient clinic. This study analyzed DSM-IV-referenced ASD symptom statements from parent and teacher versions of the Child and Adolescent Symptom Inventory-4R. A series of exploratory structural equation models was conducted in order to produce interpretable latent factors that account for multivariate covariance. Results indicated that ASD symptoms were structured into an interpretable hierarchy across multiple informants. This hierarchy includes five levels; key features of ASD bifurcate into different constructs with increasing specificity. This is the first study to examine an underlying structural hierarchy of ASD symptomatology using the bass-ackwards method. This hierarchy demonstrates how core features of ASD relate at differing levels of resolution, providing a model for conceptualizing ASD heterogeneity and a structure for integrating divergent theories of cognitive processes and behavioral features that define the disorder. These findings suggest that a more coherent and complete understanding of the structure of ASD symptoms may be reflected in a metastructure rather than at one level of resolution. © 2017 Association for Child and Adolescent Mental Health.

Prediction of redox-sensitive cysteines using sequential distance and other sequence-based features.

PubMed

Sun, Ming-An; Zhang, Qing; Wang, Yejun; Ge, Wei; Guo, Dianjing

2016-08-24

Reactive oxygen species can modify the structure and function of proteins and may also act as important signaling molecules in various cellular processes. Cysteine thiol groups of proteins are particularly susceptible to oxidation. Meanwhile, their reversible oxidation is of critical roles for redox regulation and signaling. Recently, several computational tools have been developed for predicting redox-sensitive cysteines; however, those methods either only focus on catalytic redox-sensitive cysteines in thiol oxidoreductases, or heavily depend on protein structural data, thus cannot be widely used. In this study, we analyzed various sequence-based features potentially related to cysteine redox-sensitivity, and identified three types of features for efficient computational prediction of redox-sensitive cysteines. These features are: sequential distance to the nearby cysteines, PSSM profile and predicted secondary structure of flanking residues. After further feature selection using SVM-RFE, we developed Redox-Sensitive Cysteine Predictor (RSCP), a SVM based classifier for redox-sensitive cysteine prediction using primary sequence only. Using 10-fold cross-validation on RSC758 dataset, the accuracy, sensitivity, specificity, MCC and AUC were estimated as 0.679, 0.602, 0.756, 0.362 and 0.727, respectively. When evaluated using 10-fold cross-validation with BALOSCTdb dataset which has structure information, the model achieved performance comparable to current structure-based method. Further validation using an independent dataset indicates it is robust and of relatively better accuracy for predicting redox-sensitive cysteines from non-enzyme proteins. In this study, we developed a sequence-based classifier for predicting redox-sensitive cysteines. The major advantage of this method is that it does not rely on protein structure data, which ensures more extensive application compared to other current implementations. Accurate prediction of redox-sensitive cysteines not only enhances our understanding about the redox sensitivity of cysteine, it may also complement the proteomics approach and facilitate further experimental investigation of important redox-sensitive cysteines.

Autonomous navigation of structured city roads

NASA Astrophysics Data System (ADS)

Aubert, Didier; Kluge, Karl C.; Thorpe, Chuck E.

1991-03-01

Autonomous road following is a domain which spans a range of complexity from poorly defined unmarked dirt roads to well defined well marked highly struc-. tured highways. The YARF system (for Yet Another Road Follower) is designed to operate in the middle of this range of complexity driving on urban streets. Our research program has focused on the use of feature- and situation-specific segmentation techniques driven by an explicit model of the appearance and geometry of the road features in the environment. We report results in robust detection of white and yellow painted stripes fitting a road model to detected feature locations to determine vehicle position and local road geometry and automatic location of road features in an initial image. We also describe our planned extensions to include intersection navigation.

A novel SOI LDMOS with substrate field plate and variable-k dielectric buried layer

NASA Astrophysics Data System (ADS)

Li, Qi; Wen, Yi; Zhang, Fabi; Li, Haiou; Xiao, Gongli; Chen, Yonghe; Fu, Tao

2018-09-01

A novel silicon-on-insulator (SOI) lateral double-diffused metal-oxide-semiconductor (LDMOS) structure has been proposed. The new structure features a substrate field plate (SFP) and a variable-k dielectric buried layer (VKBL). The SFP and VKBL improve the breakdown voltage by introducing new electric field peaks in the surface electric field distribution. Moreover, the SFP reduces the specific ON-resistance through an enhanced auxiliary depletion effect on the drift region. The simulation results indicate that compared to the conventional SOI LDMOS structure, the breakdown voltage is improved from 118 V to 221 V, the specific ON-resistance is decreased from 7.15 mΩ·cm2 to 3.81 mΩ·cm2, the peak value of surface temperature is declined by 38 K.

Visualization of protein sequence features using JavaScript and SVG with pViz.js.

PubMed

Mukhyala, Kiran; Masselot, Alexandre

2014-12-01

pViz.js is a visualization library for displaying protein sequence features in a Web browser. By simply providing a sequence and the locations of its features, this lightweight, yet versatile, JavaScript library renders an interactive view of the protein features. Interactive exploration of protein sequence features over the Web is a common need in Bioinformatics. Although many Web sites have developed viewers to display these features, their implementations are usually focused on data from a specific source or use case. Some of these viewers can be adapted to fit other use cases but are not designed to be reusable. pViz makes it easy to display features as boxes aligned to a protein sequence with zooming functionality but also includes predefined renderings for secondary structure and post-translational modifications. The library is designed to further customize this view. We demonstrate such applications of pViz using two examples: a proteomic data visualization tool with an embedded viewer for displaying features on protein structure, and a tool to visualize the results of the variant_effect_predictor tool from Ensembl. pViz.js is a JavaScript library, available on github at https://github.com/Genentech/pviz. This site includes examples and functional applications, installation instructions and usage documentation. A Readme file, which explains how to use pViz with examples, is available as Supplementary Material A. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

An EEG-based functional connectivity measure for automatic detection of alcohol use disorder.

PubMed

Mumtaz, Wajid; Saad, Mohamad Naufal B Mohamad; Kamel, Nidal; Ali, Syed Saad Azhar; Malik, Aamir Saeed

2018-01-01

The abnormal alcohol consumption could cause toxicity and could alter the human brain's structure and function, termed as alcohol used disorder (AUD). Unfortunately, the conventional screening methods for AUD patients are subjective and manual. Hence, to perform automatic screening of AUD patients, objective methods are needed. The electroencephalographic (EEG) data have been utilized to study the differences of brain signals between alcoholics and healthy controls that could further developed as an automatic screening tool for alcoholics. In this work, resting-state EEG-derived features were utilized as input data to the proposed feature selection and classification method. The aim was to perform automatic classification of AUD patients and healthy controls. The validation of the proposed method involved real-EEG data acquired from 30 AUD patients and 30 age-matched healthy controls. The resting-state EEG-derived features such as synchronization likelihood (SL) were computed involving 19 scalp locations resulted into 513 features. Furthermore, the features were rank-ordered to select the most discriminant features involving a rank-based feature selection method according to a criterion, i.e., receiver operating characteristics (ROC). Consequently, a reduced set of most discriminant features was identified and utilized further during classification of AUD patients and healthy controls. In this study, three different classification models such as Support Vector Machine (SVM), Naïve Bayesian (NB), and Logistic Regression (LR) were used. The study resulted into SVM classification accuracy=98%, sensitivity=99.9%, specificity=95%, and f-measure=0.97; LR classification accuracy=91.7%, sensitivity=86.66%, specificity=96.6%, and f-measure=0.90; NB classification accuracy=93.6%, sensitivity=100%, specificity=87.9%, and f-measure=0.95. The SL features could be utilized as objective markers to screen the AUD patients and healthy controls. Copyright © 2017 Elsevier B.V. All rights reserved.

Concept-based query language approach to enterprise information systems

NASA Astrophysics Data System (ADS)

Niemi, Timo; Junkkari, Marko; Järvelin, Kalervo

2014-01-01

In enterprise information systems (EISs) it is necessary to model, integrate and compute very diverse data. In advanced EISs the stored data often are based both on structured (e.g. relational) and semi-structured (e.g. XML) data models. In addition, the ad hoc information needs of end-users may require the manipulation of data-oriented (structural), behavioural and deductive aspects of data. Contemporary languages capable of treating this kind of diversity suit only persons with good programming skills. In this paper we present a concept-oriented query language approach to manipulate this diversity so that the programming skill requirements are considerably reduced. In our query language, the features which need technical knowledge are hidden in application-specific concepts and structures. Therefore, users need not be aware of the underlying technology. Application-specific concepts and structures are represented by the modelling primitives of the extended RDOOM (relational deductive object-oriented modelling) which contains primitives for all crucial real world relationships (is-a relationship, part-of relationship, association), XML documents and views. Our query language also supports intensional and extensional-intensional queries, in addition to conventional extensional queries. In its query formulation, the end-user combines available application-specific concepts and structures through shared variables.

Relevans og intention. To analyser af en massemedietekst om okonomisk politik. ROLIG-papir 33 (Relevance and Intention. Two Analyses of a Mass Media Text on Economic Politics. ROLIG-paper 33).

ERIC Educational Resources Information Center

Heltoft, Lars; Geist, Uwe

The three papers in this publication analyze a newspaper article on "economic politics," or more specifically, the devaluing of the Danish kroner. The papers all examine some linguistic or structural feature of the language used in writing the article. Specific focus is on relevance theory and relevance in the article, the use of text…

Millimeter-wave antenna design

NASA Technical Reports Server (NTRS)

Leighton, R. B.

1977-01-01

Problems and opportunities are discussed for adapting certain design features and construction techniques, developed for producing high accuracy ground based radio dishes, to producing milimeter wave dishes for space use. Specifically considered is a foldable telescope of 24 m aperture and 9.6 m focal length, composed of 37 rigid hexagonal panels, which will fit within the 4.5 m diameter x 18 m long payload limits of space shuttle. As here conceived, the telescope would be a free flyer with its own power and pointing systems. Some of the structural design features and construction procedures are considered.

Determination of dosimetric and kinetic features of gamma irradiated solid calcium ascorbate dihydrate using ESR spectroscopy

NASA Astrophysics Data System (ADS)

Tuner, H.

2013-01-01

Effects of gamma radiation on solid calcium ascorbate dihydrate were studied using electron spin resonance (ESR) spectroscopy. Irradiated samples were found to present two specific ESR lines with shoulder at low and high magnetic field sides. Structural and kinetic features of the radicalic species responsible for experimental ESR spectrum were explored through the variations of the signal intensities with applied microwave power, variable temperature, high-temperature annealing and room temperature storage time studies. Dosimetric potential of the sample was also determined using spectrum area and measured signal intensity measurements. It was concluded that three radicals with different spectroscopic and kinetic features were produced upon gamma irradiation.

Transformations of dislocation martensite in tempering secondary-hardening steel

NASA Astrophysics Data System (ADS)

Gorynin, I. V.; Rybin, V. V.; Malyshevskii, V. A.; Semicheva, T. G.; Sherokhina, L. G.

1999-09-01

Analysis of the evolution of the fine structure of secondary-hardening steel in tempering makes it possible to understand the nature of processes that cause changes in the strength and ductility. They are connected with the changes that occur in the solid solution, the ensemble of disperse segregations of the carbide phase, and the dislocation structure of martensite. These transformations are interrelated, and their specific features are determined by the chemical composition of the steel.

Prediction of beta-turns at over 80% accuracy based on an ensemble of predicted secondary structures and multiple alignments.

PubMed

Zheng, Ce; Kurgan, Lukasz

2008-10-10

beta-turn is a secondary protein structure type that plays significant role in protein folding, stability, and molecular recognition. To date, several methods for prediction of beta-turns from protein sequences were developed, but they are characterized by relatively poor prediction quality. The novelty of the proposed sequence-based beta-turn predictor stems from the usage of a window based information extracted from four predicted three-state secondary structures, which together with a selected set of position specific scoring matrix (PSSM) values serve as an input to the support vector machine (SVM) predictor. We show that (1) all four predicted secondary structures are useful; (2) the most useful information extracted from the predicted secondary structure includes the structure of the predicted residue, secondary structure content in a window around the predicted residue, and features that indicate whether the predicted residue is inside a secondary structure segment; (3) the PSSM values of Asn, Asp, Gly, Ile, Leu, Met, Pro, and Val were among the top ranked features, which corroborates with recent studies. The Asn, Asp, Gly, and Pro indicate potential beta-turns, while the remaining four amino acids are useful to predict non-beta-turns. Empirical evaluation using three nonredundant datasets shows favorable Q total, Q predicted and MCC values when compared with over a dozen of modern competing methods. Our method is the first to break the 80% Q total barrier and achieves Q total = 80.9%, MCC = 0.47, and Q predicted higher by over 6% when compared with the second best method. We use feature selection to reduce the dimensionality of the feature vector used as the input for the proposed prediction method. The applied feature set is smaller by 86, 62 and 37% when compared with the second and two third-best (with respect to MCC) competing methods, respectively. Experiments show that the proposed method constitutes an improvement over the competing prediction methods. The proposed prediction model can better discriminate between beta-turns and non-beta-turns due to obtaining lower numbers of false positive predictions. The prediction model and datasets are freely available at http://biomine.ece.ualberta.ca/BTNpred/BTNpred.html.

Prediction of beta-turns at over 80% accuracy based on an ensemble of predicted secondary structures and multiple alignments

PubMed Central

Zheng, Ce; Kurgan, Lukasz

2008-01-01

Background β-turn is a secondary protein structure type that plays significant role in protein folding, stability, and molecular recognition. To date, several methods for prediction of β-turns from protein sequences were developed, but they are characterized by relatively poor prediction quality. The novelty of the proposed sequence-based β-turn predictor stems from the usage of a window based information extracted from four predicted three-state secondary structures, which together with a selected set of position specific scoring matrix (PSSM) values serve as an input to the support vector machine (SVM) predictor. Results We show that (1) all four predicted secondary structures are useful; (2) the most useful information extracted from the predicted secondary structure includes the structure of the predicted residue, secondary structure content in a window around the predicted residue, and features that indicate whether the predicted residue is inside a secondary structure segment; (3) the PSSM values of Asn, Asp, Gly, Ile, Leu, Met, Pro, and Val were among the top ranked features, which corroborates with recent studies. The Asn, Asp, Gly, and Pro indicate potential β-turns, while the remaining four amino acids are useful to predict non-β-turns. Empirical evaluation using three nonredundant datasets shows favorable Qtotal, Qpredicted and MCC values when compared with over a dozen of modern competing methods. Our method is the first to break the 80% Qtotal barrier and achieves Qtotal = 80.9%, MCC = 0.47, and Qpredicted higher by over 6% when compared with the second best method. We use feature selection to reduce the dimensionality of the feature vector used as the input for the proposed prediction method. The applied feature set is smaller by 86, 62 and 37% when compared with the second and two third-best (with respect to MCC) competing methods, respectively. Conclusion Experiments show that the proposed method constitutes an improvement over the competing prediction methods. The proposed prediction model can better discriminate between β-turns and non-β-turns due to obtaining lower numbers of false positive predictions. The prediction model and datasets are freely available at . PMID:18847492

Structural Mechanisms of Plant Glucan Phosphatases in Starch Metabolism

PubMed Central

Meekins, David A.; Vander Kooi, Craig W.; Gentry, Matthew S.

2016-01-01

Glucan phosphatases are a recently discovered class of enzymes that dephosphorylate starch and glycogen, thereby regulating energy metabolism. Plant genomes encode for two glucan phosphatases called Starch EXcess4 (SEX4) and Like Sex Four2 (LSF2) that regulate starch metabolism by selectively dephosphorylating glucose moieties within starch glucan chains. Recently, the structures of both SEX4 and LSF2 were determined, with and without phosphoglucan products bound, revealing the mechanism for their unique activities. This review explores the structural and enzymatic features of the plant glucan phosphatases and outlines how they are uniquely adapted for carrying out their cellular functions. We outline the physical mechanisms employed by SEX4 and LSF2 to interact with starch glucans: SEX4 binds glucan chains via a continuous glucan binding platform comprised of its Dual Specificity Phosphatase (DSP) domain and Carbohydrate Binding Module (CBM) while LSF2 utilizes Surface Binding Sites (SBSs). SEX4 and LSF2 both contain a unique network of aromatic residues in their catalytic DSP domains that serve as glucan engagement platforms and are unique to the glucan phosphatases. We also discuss the phosphoglucan substrate specificities inherent to SEX4 and LSF2 and outline structural features within the active site that govern glucan orientation. This review defines the structural mechanism of the plant glucan phosphatases with respect to phosphatases, starch metabolism, and protein-glucan interaction; thereby providing a framework for their applications in both agricultural and industrial settings. PMID:26934589

Common structural features of toxic intermediates from α-synuclein and GroES fibrillogenesis detected using cryogenic coherent X-ray diffraction imaging.

PubMed

Kameda, Hiroshi; Usugi, Sayaka; Kobayashi, Mana; Fukui, Naoya; Lee, Seki; Hongo, Kunihiro; Mizobata, Tomohiro; Sekiguchi, Yuki; Masaki, Yu; Kobayashi, Amane; Oroguchi, Tomotaka; Nakasako, Masayoshi; Takayama, Yuki; Yamamoto, Masaki; Kawata, Yasushi

2017-01-01

The aggregation and deposition of α-synuclein (αSyn) in neuronal cells is correlated to pathogenesis of Parkinson's disease. Although the mechanism of αSyn aggregation and fibril formation has been studied extensively, the structural hallmarks that are directly responsible for toxicity toward cells are still under debate. Here, we have compared the structural characteristics of the toxic intermediate molecular species of αSyn and similar toxic species of another protein, GroES, using coherent X-ray diffraction analysis. Using coherent X-ray free electron laser pulses of SACLA, we analysed αSyn and GroES fibril intermediate species and characterized various aggregate structures. Unlike previous studies where an annular oligomeric form of αSyn was identified, particle reconstruction from scattering traces suggested that the specific forms of the toxic particles were varied, with the sizes of the particles falling within a specific range. We did however discover a common structural feature in both αSyn and GroES samples; the edges of the detected particles were nearly parallel and produced a characteristic diffraction pattern in the diffraction experiments. The presence of parallel-edged particles in toxic intermediates of αSyn and GroES fibrillogenesis pointed towards a plausible common molecular interface that leads to the formation of mature fibrils. © The Authors 2016. Published by Oxford University Press on behalf of the Japanese Biochemical Society. All rights reserved.

Coma morphology of comet 67P controlled by insolation over irregular nucleus

NASA Astrophysics Data System (ADS)

Shi, X.; Hu, X.; Mottola, S.; Sierks, H.; Keller, H. U.; Rose, M.; Güttler, C.; Fulle, M.; Fornasier, S.; Agarwal, J.; Pajola, M.; Tubiana, C.; Bodewits, D.; Barbieri, C.; Lamy, P. L.; Rodrigo, R.; Koschny, D.; Barucci, M. A.; Bertaux, J.-L.; Bertini, I.; Boudreault, S.; Cremonese, G.; Da Deppo, V.; Davidsson, B.; Debei, S.; De Cecco, M.; Deller, J.; Groussin, O.; Gutiérrez, P. J.; Hviid, S. F.; Ip, W.-H.; Jorda, L.; Knollenberg, J.; Kovacs, G.; Kramm, J.-R.; Kührt, E.; Küppers, M.; Lara, L. M.; Lazzarin, M.; Lopez-Moreno, J. J.; Marzari, F.; Naletto, G.; Oklay, N.; Toth, I.; Vincent, J.-B.

2018-05-01

While the structural complexity of cometary comae is already recognizable from telescopic observations1, the innermost region, within a few radii of the nucleus, was not resolved until spacecraft exploration became a reality2,3. The dust coma displays jet-like features of enhanced brightness superposed on a diffuse background1,4,5. Some features can be traced to specific areas on the nucleus, and result conceivably from locally enhanced outgassing and/or dust emission6-8. However, diffuse or even uniform activity over topographic concavity can converge to produce jet-like features9,10. Therefore, linking observed coma morphology to the distribution of activity on the nucleus is difficult11,12. Here, we study the emergence of dust activity at sunrise on comet 67P/Churyumov-Gerasimenko using high-resolution, stereo images from the OSIRIS camera onboard the Rosetta spacecraft, where the sources and formation of the jet-like features are resolved. We perform numerical simulations to show that the ambient dust coma is driven by pervasive but non-uniform water outgassing from the homogeneous surface layer. Physical collimations of gas and dust flows occur at local maxima of insolation and also via topographic focusing. Coma structures are projected to exhibit jet-like features that vary with the perspective of the observer. For an irregular comet such as 67P/Churyumov-Gerasimenko, near-nucleus coma structures can be concealed in the shadow of the nucleus, which further complicates the picture.

Methodologies for Verification and Validation of Space Launch System (SLS) Structural Dynamic Models

NASA Technical Reports Server (NTRS)

Coppolino, Robert N.

2018-01-01

Responses to challenges associated with verification and validation (V&V) of Space Launch System (SLS) structural dynamics models are presented in this paper. Four methodologies addressing specific requirements for V&V are discussed. (1) Residual Mode Augmentation (RMA), which has gained acceptance by various principals in the NASA community, defines efficient and accurate FEM modal sensitivity models that are useful in test-analysis correlation and reconciliation and parametric uncertainty studies. (2) Modified Guyan Reduction (MGR) and Harmonic Reduction (HR, introduced in 1976), developed to remedy difficulties encountered with the widely used Classical Guyan Reduction (CGR) method, are presented. MGR and HR are particularly relevant for estimation of "body dominant" target modes of shell-type SLS assemblies that have numerous "body", "breathing" and local component constituents. Realities associated with configuration features and "imperfections" cause "body" and "breathing" mode characteristics to mix resulting in a lack of clarity in the understanding and correlation of FEM- and test-derived modal data. (3) Mode Consolidation (MC) is a newly introduced procedure designed to effectively "de-feature" FEM and experimental modes of detailed structural shell assemblies for unambiguous estimation of "body" dominant target modes. Finally, (4) Experimental Mode Verification (EMV) is a procedure that addresses ambiguities associated with experimental modal analysis of complex structural systems. Specifically, EMV directly separates well-defined modal data from spurious and poorly excited modal data employing newly introduced graphical and coherence metrics.

bpRNA: large-scale automated annotation and analysis of RNA secondary structure.

PubMed

Danaee, Padideh; Rouches, Mason; Wiley, Michelle; Deng, Dezhong; Huang, Liang; Hendrix, David

2018-05-09

While RNA secondary structure prediction from sequence data has made remarkable progress, there is a need for improved strategies for annotating the features of RNA secondary structures. Here, we present bpRNA, a novel annotation tool capable of parsing RNA structures, including complex pseudoknot-containing RNAs, to yield an objective, precise, compact, unambiguous, easily-interpretable description of all loops, stems, and pseudoknots, along with the positions, sequence, and flanking base pairs of each such structural feature. We also introduce several new informative representations of RNA structure types to improve structure visualization and interpretation. We have further used bpRNA to generate a web-accessible meta-database, 'bpRNA-1m', of over 100 000 single-molecule, known secondary structures; this is both more fully and accurately annotated and over 20-times larger than existing databases. We use a subset of the database with highly similar (≥90% identical) sequences filtered out to report on statistical trends in sequence, flanking base pairs, and length. Both the bpRNA method and the bpRNA-1m database will be valuable resources both for specific analysis of individual RNA molecules and large-scale analyses such as are useful for updating RNA energy parameters for computational thermodynamic predictions, improving machine learning models for structure prediction, and for benchmarking structure-prediction algorithms.

Modification of electronic structure, magnetic structure, and topological phase of bismuthene by point defects

NASA Astrophysics Data System (ADS)

Kadioglu, Yelda; Kilic, Sevket Berkay; Demirci, Salih; Aktürk, O. Üzengi; Aktürk, Ethem; Ciraci, Salim

2017-12-01

This paper reveals how the electronic structure, magnetic structure, and topological phase of two-dimensional (2D), single-layer structures of bismuth are modified by point defects. We first showed that a free-standing, single-layer, hexagonal structure of bismuth, named h-bismuthene, exhibits nontrivial band topology. We then investigated interactions between single foreign adatoms and bismuthene structures, which comprise stability, bonding, electronic structure, and magnetic structures. Localized states in diverse locations of the band gap and resonant states in band continua of bismuthene are induced upon the adsorption of different adatoms, which modify electronic and magnetic properties. Specific adatoms result in reconstruction around the adsorption site. Single vacancies and divacancies can form readily in bismuthene structures and remain stable at high temperatures. Through rebondings, Stone-Whales-type defects are constructed by divacancies, which transform into a large hole at high temperature. Like adsorbed adatoms, vacancies induce also localized gap states, which can be eliminated through rebondings in divacancies. We also showed that not only the optical and magnetic properties, but also the topological features of pristine h-bismuthene can be modified by point defects. The modification of the topological features depends on the energies of localized states and also on the strength of coupling between point defects.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Janjusic, Tommy; Kartsaklis, Christos

Application analysis is facilitated through a number of program profiling tools. The tools vary in their complexity, ease of deployment, design, and profiling detail. Specifically, understand- ing, analyzing, and optimizing is of particular importance for scientific applications where minor changes in code paths and data-structure layout can have profound effects. Understanding how intricate data-structures are accessed and how a given memory system responds is a complex task. In this paper we describe a trace profiling tool, Glprof, specifically aimed to lessen the burden of the programmer to pin-point heavily involved data-structures during an application's run-time, and understand data-structure run-time usage.more » Moreover, we showcase the tool's modularity using additional cache simulation components. We elaborate on the tool's design, and features. Finally we demonstrate the application of our tool in the context of Spec bench- marks using the Glprof profiler and two concurrently running cache simulators, PPC440 and AMD Interlagos.« less

Structural characterization of a D-isomer specific 2-hydroxyacid dehydrogenase from Lactobacillus delbrueckii ssp. bulgaricus.

PubMed

Holton, Simon J; Anandhakrishnan, Madhankumar; Geerlof, Arie; Wilmanns, Matthias

2013-02-01

Hydroxyacid dehydrogenases, responsible for the stereospecific conversion of 2-keto acids to 2-hydroxyacids in lactic acid producing bacteria, have a range of biotechnology applications including antibiotic synthesis, flavor development in dairy products and the production of valuable synthons. The genome of Lactobacillus delbrueckii ssp. bulgaricus, a member of the heterogeneous group of lactic acid bacteria, encodes multiple hydroxyacid dehydrogenases whose structural and functional properties remain poorly characterized. Here, we report the apo and coenzyme NAD⁺ complexed crystal structures of the L. bulgaricusD-isomer specific 2-hydroxyacid dehydrogenase, D2-HDH. Comparison with closely related members of the NAD-dependent dehydrogenase family reveals that whilst the D2-HDH core fold is structurally conserved, the substrate-binding site has a number of non-canonical features that may influence substrate selection and thus dictate the physiological function of the enzyme. Copyright © 2012 Elsevier Inc. All rights reserved.

Biomorphic networks: approach to invariant feature extraction and segmentation for ATR

NASA Astrophysics Data System (ADS)

Baek, Andrew; Farhat, Nabil H.

1998-10-01

Invariant features in two dimensional binary images are extracted in a single layer network of locally coupled spiking (pulsating) model neurons with prescribed synapto-dendritic response. The feature vector for an image is represented as invariant structure in the aggregate histogram of interspike intervals obtained by computing time intervals between successive spikes produced from each neuron over a given period of time and combining such intervals from all neurons in the network into a histogram. Simulation results show that the feature vectors are more pattern-specific and invariant under translation, rotation, and change in scale or intensity than achieved in earlier work. We also describe an application of such networks to segmentation of line (edge-enhanced or silhouette) images. The biomorphic spiking network's capabilities in segmentation and invariant feature extraction may prove to be, when they are combined, valuable in Automated Target Recognition (ATR) and other automated object recognition systems.

Effects of metric hierarchy and rhyme predictability on word duration in The Cat in the Hat.

PubMed

Breen, Mara

2018-05-01

Word durations convey many types of linguistic information, including intrinsic lexical features like length and frequency and contextual features like syntactic and semantic structure. The current study was designed to investigate whether hierarchical metric structure and rhyme predictability account for durational variation over and above other features in productions of a rhyming, metrically-regular children's book: The Cat in the Hat (Dr. Seuss, 1957). One-syllable word durations and inter-onset intervals were modeled as functions of segment number, lexical frequency, word class, syntactic structure, repetition, and font emphasis. Consistent with prior work, factors predicting longer word durations and inter-onset intervals included more phonemes, lower frequency, first mention, alignment with a syntactic boundary, and capitalization. A model parameter corresponding to metric grid height improved model fit of word durations and inter-onset intervals. Specifically, speakers realized five levels of metric hierarchy with inter-onset intervals such that interval duration increased linearly with increased height in the metric hierarchy. Conversely, speakers realized only three levels of metric hierarchy with word duration, demonstrating that they shortened the highly predictable rhyme resolutions. These results further understanding of the factors that affect spoken word duration, and demonstrate the myriad cues that children receive about linguistic structure from nursery rhymes. Copyright © 2018 Elsevier B.V. All rights reserved.

Automated global structure extraction for effective local building block processing in XCS.

PubMed

Butz, Martin V; Pelikan, Martin; Llorà, Xavier; Goldberg, David E

2006-01-01

Learning Classifier Systems (LCSs), such as the accuracy-based XCS, evolve distributed problem solutions represented by a population of rules. During evolution, features are specialized, propagated, and recombined to provide increasingly accurate subsolutions. Recently, it was shown that, as in conventional genetic algorithms (GAs), some problems require efficient processing of subsets of features to find problem solutions efficiently. In such problems, standard variation operators of genetic and evolutionary algorithms used in LCSs suffer from potential disruption of groups of interacting features, resulting in poor performance. This paper introduces efficient crossover operators to XCS by incorporating techniques derived from competent GAs: the extended compact GA (ECGA) and the Bayesian optimization algorithm (BOA). Instead of simple crossover operators such as uniform crossover or one-point crossover, ECGA or BOA-derived mechanisms are used to build a probabilistic model of the global population and to generate offspring classifiers locally using the model. Several offspring generation variations are introduced and evaluated. The results show that it is possible to achieve performance similar to runs with an informed crossover operator that is specifically designed to yield ideal problem-dependent exploration, exploiting provided problem structure information. Thus, we create the first competent LCSs, XCS/ECGA and XCS/BOA, that detect dependency structures online and propagate corresponding lower-level dependency structures effectively without any information about these structures given in advance.

Remote sensing of geologic mineral occurrences for the Colorado mineral belt using LANDSAT data

NASA Technical Reports Server (NTRS)

Carpenter, R. H. (Principal Investigator); Trexler, D. W.

1976-01-01

The author has identified the following significant results. LANDSAT imagery was examined as a practical and productive tool for mineral exploration along the Colorado Mineral Belt. An attempt was made to identify all large, active and/or abandoned mining districts on the imagery which initially were discovered by surface manifestations. A number of strong photolinements, circular features, and color anomalies were identified. Some of these form a part of the structural and igneous volcanic framework in which mineral deposits occur. No specific mineral deposits such as veins or porphyries were identified. Promising linear and concentric features were field checked at several locations. Some proved to be fault zones and calderas; others were strictly topographic features related to stream or glacial entrenchment. The Silverton Caldera region and the Idaho Springs-Central City district were chosen and studied as case histories to evaluate the application of LANDSAT imagery to mineral exploration. Evidence of specific mineralization related to ore deposits in these two areas were observed only on low level photography.

Computer-aided diagnostic approach of dermoscopy images acquiring relevant features

NASA Astrophysics Data System (ADS)

Castillejos-Fernández, H.; Franco-Arcega, A.; López-Ortega, O.

2016-09-01

In skin cancer detection, automated analysis of borders, colors, and structures of a lesion relies upon an accurate segmentation process and it is an important first step in any Computer-Aided Diagnosis (CAD) system. However, irregular and disperse lesion borders, low contrast, artifacts in images and variety of colors within the interest region make the problem difficult. In this paper, we propose an efficient approach of automatic classification which considers specific lesion features. First, for the selection of lesion skin we employ the segmentation algorithm W-FCM.1 Then, in the feature extraction stage we consider several aspects: the area of the lesion, which is calculated by correlating axes and we calculate the specific the value of asymmetry in both axes. For color analysis we employ an ensemble of clusterers including K-Means, Fuzzy K-Means and Kohonep maps, all of which estimate the presence of one or more colors defined in ABCD rule and the values for each of the segmented colors. Another aspect to consider is the type of structures that appear in the lesion Those are defined by using the ell-known GLCM method. During the classification stage we compare several methods in order to define if the lesion is benign or malignant. An important contribution of the current approach in segmentation-classification problem resides in the use of information from all color channels together, as well as the measure of each color in the lesion and the axes correlation. The segmentation and classification measures have been performed using sensibility, specificity, accuracy and AUC metric over a set of dermoscopy images from ISDIS data set

Dynamics of feature categorization.

PubMed

Martí, Daniel; Rinzel, John

2013-01-01

In visual and auditory scenes, we are able to identify shared features among sensory objects and group them according to their similarity. This grouping is preattentive and fast and is thought of as an elementary form of categorization by which objects sharing similar features are clustered in some abstract perceptual space. It is unclear what neuronal mechanisms underlie this fast categorization. Here we propose a neuromechanistic model of fast feature categorization based on the framework of continuous attractor networks. The mechanism for category formation does not rely on learning and is based on biologically plausible assumptions, for example, the existence of populations of neurons tuned to feature values, feature-specific interactions, and subthreshold-evoked responses upon the presentation of single objects. When the network is presented with a sequence of stimuli characterized by some feature, the network sums the evoked responses and provides a running estimate of the distribution of features in the input stream. If the distribution of features is structured into different components or peaks (i.e., is multimodal), recurrent excitation amplifies the response of activated neurons, and categories are singled out as emerging localized patterns of elevated neuronal activity (bumps), centered at the centroid of each cluster. The emergence of bump states through sequential, subthreshold activation and the dependence on input statistics is a novel application of attractor networks. We show that the extraction and representation of multiple categories are facilitated by the rich attractor structure of the network, which can sustain multiple stable activity patterns for a robust range of connectivity parameters compatible with cortical physiology.

Experimental analysis for fabrication of high-aspect-ratio piezoelectric ceramic structure by micro-powder injection molding process

NASA Astrophysics Data System (ADS)

Han, Jun Sae; Gal, Chang Woo; Park, Jae Man; Kim, Jong Hyun; Park, Seong Jin

2018-04-01

Aspect ratio effects in the micro-powder injection molding process were experimentally analyzed for fabrication of high-aspect-ratio piezoelectric ceramic structure. The mechanisms of critical defects have been studied according to individual manufacturing steps. In the molding process, incomplete filling phenomenon determines the critical aspect ratios of a micro pattern. According to mold temperature, an incomplete filling phenomenon has been analyzed with respect to different pattern sizes and aspect ratio. In demolding and drying process, the capillary behavior of sacrificial polymeric mold insert determines the critical aspect ratio of a micro pattern. With respect to pattern dimensions, slumping behavior has been analyzed. Based on our current systems, micro PZT feature has stability when it has lower aspect ratio than 5. Under optimized processing conditions, 20 μm and 40 μm ceramic rod array feature which has 5 of aspect ratio were successfully fabricated by the developed process. Further modification points to fabricate the smaller and higher feature were specifically addressed.

Three-dimensional structure-activity relationship modeling of cocaine binding to two monoclonal antibodies by comparative molecular field analysis.

PubMed

Paula, Stefan; Tabet, Michael R; Keenan, Susan M; Welsh, William J; Ball, W James

2003-01-17

Successful immunotherapy of cocaine addiction and overdoses requires cocaine-binding antibodies with specific properties, such as high affinity and selectivity for cocaine. We have determined the affinities of two cocaine-binding murine monoclonal antibodies (mAb: clones 3P1A6 and MM0240PA) for cocaine and its metabolites by [3H]-radioligand binding assays. mAb 3P1A6 (K(d) = 0.22 nM) displayed a 50-fold higher affinity for cocaine than mAb MM0240PA (K(d) = 11 nM) and also had a greater specificity for cocaine. For the systematic exploration of both antibodies' binding specificities, we used a set of approximately 35 cocaine analogues as structural probes by determining their relative binding affinities (RBAs) using an enzyme-linked immunosorbent competition assay. Three-dimensional quantitative structure-activity relationship (3D-QSAR) models on the basis of comparative molecular field analysis (CoMFA) techniques correlated the binding data with structural features of the ligands. The analysis indicated that despite the mAbs' differing specificities for cocaine, the relative contributions of the steric (approximately 80%) and electrostatic (approximately 20%) field interactions to ligand-binding were similar. Generated three-dimensional CoMFA contour plots then located the specific regions about cocaine where the ligand/receptor interactions occurred. While the overall binding patterns of the two mAbs had many features in common, distinct differences were observed about the phenyl ring and the methylester group of cocaine. Furthermore, using previously published data, a 3D-QSAR model was developed for cocaine binding to the dopamine reuptake transporter (DAT) that was compared to the mAb models. Although the relative steric and electrostatic field contributions were similar to those of the mAbs, the DAT cocaine-binding site showed a preference for negatively charged ligands. Besides establishing molecular level insight into the interactions that govern cocaine binding specificity by biopolymers, the three-dimensional images obtained reflect the properties of the mAbs binding pockets and provide the initial information needed for the possible design of novel antibodies with properties optimized for immunotherapy. Copyright 2003 Elsevier Science Ltd.

Serbian: The Serbian Language in Education in Hungary. Regional Dossiers Series

ERIC Educational Resources Information Center

Paulik, Anton, Comp.; Solymosi, Judit, Comp.

2014-01-01

This regional dossier aims at providing a concise description of and basic statistics on minority language education in a specific region of Europe--the territory of Magyarország (Hungary). Aspects that are addressed include features of the education system, recent educational policies, main actors, legal arrangements, and support structures, as…

47 CFR 1.1311 - Environmental information to be included in the environmental assessment (EA).

Code of Federal Regulations, 2014 CFR

2014-10-01

... earth stations, a description of the facilities as well as supporting structures and appurtenances, and..., the applicant's analysis must utilize the best scientific and commercial data available, see 50 CFR...'s environmental impact, if any. The EA shall deal specifically with any feature of the site which...

47 CFR 1.1311 - Environmental information to be included in the environmental assessment (EA).

Code of Federal Regulations, 2013 CFR

2013-10-01

... earth stations, a description of the facilities as well as supporting structures and appurtenances, and..., the applicant's analysis must utilize the best scientific and commercial data available, see 50 CFR...'s environmental impact, if any. The EA shall deal specifically with any feature of the site which...

47 CFR 1.1311 - Environmental information to be included in the environmental assessment (EA).

Code of Federal Regulations, 2012 CFR

2012-10-01

... earth stations, a description of the facilities as well as supporting structures and appurtenances, and..., the applicant's analysis must utilize the best scientific and commercial data available, see 50 CFR...'s environmental impact, if any. The EA shall deal specifically with any feature of the site which...

Friulian: The Friulian Language in Education in Italy. Regional Dossiers Series

ERIC Educational Resources Information Center

Petris, Cinzia, Comp.

2014-01-01

This regional dossier aims to provide a concise, description and basic statistics about minority language education in a specific region of Europe. Aspects that are addressed include features of the education system, recent educational policies, main actors, legal arrangements, and support structures, as well as quantitative aspects, such as the…

Catalan: The Catalan Language in Education in Spain, 2nd Edition. Regional Dossiers Series

ERIC Educational Resources Information Center

Areny, Maria, Comp.; Mayans, Pere, Comp.; Forniès, David, Comp.

2013-01-01

Regional dossiers aim at providing a concise description and basic statistics about minority language education in a specific region of Europe. Aspects that are addressed include features of the education system, recent educational policies, main actors, legal arrangements, and support structures, as well as quantitative aspects, such as the…

Distribution and Features of the Six Classes of Peroxiredoxins

PubMed Central

Poole, Leslie B.; Nelson, Kimberly J.

2016-01-01

Peroxiredoxins are cysteine-dependent peroxide reductases that group into 6 different, structurally discernable classes. In 2011, our research team reported the application of a bioinformatic approach called active site profiling to extract active site-proximal sequence segments from the 29 distinct, structurally-characterized peroxiredoxins available at the time. These extracted sequences were then used to create unique profiles for the six groups which were subsequently used to search GenBank(nr), allowing identification of ∼3500 peroxiredoxin sequences and their respective subgroups. Summarized in this minireview are the features and phylogenetic distributions of each of these peroxiredoxin subgroups; an example is also provided illustrating the use of the web accessible, searchable database known as PREX to identify subfamily-specific peroxiredoxin sequences for the organism Vitis vinifera (grape). PMID:26810075

Broad Learning System: An Effective and Efficient Incremental Learning System Without the Need for Deep Architecture.

PubMed

Chen, C L Philip; Liu, Zhulin

2018-01-01

Broad Learning System (BLS) that aims to offer an alternative way of learning in deep structure is proposed in this paper. Deep structure and learning suffer from a time-consuming training process because of a large number of connecting parameters in filters and layers. Moreover, it encounters a complete retraining process if the structure is not sufficient to model the system. The BLS is established in the form of a flat network, where the original inputs are transferred and placed as "mapped features" in feature nodes and the structure is expanded in wide sense in the "enhancement nodes." The incremental learning algorithms are developed for fast remodeling in broad expansion without a retraining process if the network deems to be expanded. Two incremental learning algorithms are given for both the increment of the feature nodes (or filters in deep structure) and the increment of the enhancement nodes. The designed model and algorithms are very versatile for selecting a model rapidly. In addition, another incremental learning is developed for a system that has been modeled encounters a new incoming input. Specifically, the system can be remodeled in an incremental way without the entire retraining from the beginning. Satisfactory result for model reduction using singular value decomposition is conducted to simplify the final structure. Compared with existing deep neural networks, experimental results on the Modified National Institute of Standards and Technology database and NYU NORB object recognition dataset benchmark data demonstrate the effectiveness of the proposed BLS.

Giant surfactants provide a versatile platform for sub-10-nm nanostructure engineering

PubMed Central

Yu, Xinfei; Yue, Kan; Hsieh, I-Fan; Li, Yiwen; Dong, Xue-Hui; Liu, Chang; Xin, Yu; Wang, Hsiao-Fang; Shi, An-Chang; Newkome, George R.; Chen, Er-Qiang; Zhang, Wen-Bin; Cheng, Stephen Z. D.

2013-01-01

The engineering of structures across different length scales is central to the design of novel materials with controlled macroscopic properties. Herein, we introduce a unique class of self-assembling materials, which are built upon shape- and volume-persistent molecular nanoparticles and other structural motifs, such as polymers, and can be viewed as a size-amplified version of the corresponding small-molecule counterparts. Among them, “giant surfactants” with precise molecular structures have been synthesized by “clicking” compact and polar molecular nanoparticles to flexible polymer tails of various composition and architecture at specific sites. Capturing the structural features of small-molecule surfactants but possessing much larger sizes, giant surfactants bridge the gap between small-molecule surfactants and block copolymers and demonstrate a duality of both materials in terms of their self-assembly behaviors. The controlled structural variations of these giant surfactants through precision synthesis further reveal that their self-assemblies are remarkably sensitive to primary chemical structures, leading to highly diverse, thermodynamically stable nanostructures with feature sizes around 10 nm or smaller in the bulk, thin-film, and solution states, as dictated by the collective physical interactions and geometric constraints. The results suggest that this class of materials provides a versatile platform for engineering nanostructures with sub-10-nm feature sizes. These findings are not only scientifically intriguing in understanding the chemical and physical principles of the self-assembly, but also technologically relevant, such as in nanopatterning technology and microelectronics. PMID:23716680

Structural and spectroscopic features of proton hydrates in the crystalline state. Solid-state DFT study on HCl and triflic acid hydrates

NASA Astrophysics Data System (ADS)

Vener, M. V.; Chernyshov, I. Yu.; Rykounov, A. A.; Filarowski, A.

2018-01-01

Crystalline HCl and CF3SO3H hydrates serve as excellent model systems for protonated water and perfluorosulphonic acid membranes, respectively. They contain characteristic H3O+, H5О+2, H7О+3 and H3O+(H2O)3 (the Eigen cation) structures. The properties of these cations in the crystalline hydrates of strong monobasic acids are studied by solid-state density function theory (DFT). Simultaneous consideration of the HCl and CF3SO3H hydrates reveals the impact of the size of a counter ion and the crystalline environment on the structure and infrared active bands of the simplest proton hydrates. The H7O+3 structure is very sensitive to the size of the counter ion and symmetry of the local environment. This makes it virtually impossible to identify the specific features of H7O+3 in molecular crystals. The H3O+ ion can be treated as the Eigen-like cation in the crystalline state. Structural, infrared and electron-density features of H5О+2 and the Eigen cation are virtually insensitive to the size of the counter ion and the symmetry of the local crystalline environment. These cations can be considered as the simplest stable proton hydrates in the condensed phase. Finally, the influence of the Grimme correction on the structure and harmonic frequencies of the molecular crystals with short (strong) intermolecular O-H···O bonds is discussed.

Social capital calculations in economic systems: Experimental study

NASA Astrophysics Data System (ADS)

Chepurov, E. G.; Berg, D. B.; Zvereva, O. M.; Nazarova, Yu. Yu.; Chekmarev, I. V.

2017-11-01

The paper describes the social capital study for a system where actors are engaged in an economic activity. The focus is on the analysis of communications structural parameters (transactions) between the actors. Comparison between transaction network graph structure and the structure of a random Bernoulli graph of the same dimension and density allows revealing specific structural features of the economic system under study. Structural analysis is based on SNA-methodology (SNA - Social Network Analysis). It is shown that structural parameter values of the graph formed by agent relationship links may well characterize different aspects of the social capital structure. The research advocates that it is useful to distinguish the difference between each agent social capital and the whole system social capital.

Second harmonic generation microscopy differentiates collagen type I and type III in COPD

NASA Astrophysics Data System (ADS)

Suzuki, Masaru; Kayra, Damian; Elliott, W. Mark; Hogg, James C.; Abraham, Thomas

2012-03-01

The structural remodeling of extracellular matrix proteins in peripheral lung region is an important feature in chronic obstructive pulmonary disease (COPD). Multiphoton microscopy is capable of inducing specific second harmonic generation (SHG) signal from non-centrosymmetric structural proteins such as fibrillar collagens. In this study, SHG microscopy was used to examine structural remodeling of the fibrillar collagens in human lungs undergoing emphysematous destruction (n=2). The SHG signals originating from these diseased lung thin sections from base to apex (n=16) were captured simultaneously in both forward and backward directions. We found that the SHG images detected in the forward direction showed well-developed and well-structured thick collagen fibers while the SHG images detected in the backward direction showed striking different morphological features which included the diffused pattern of forward detected structures plus other forms of collagen structures. Comparison of these images with the wellestablished immunohistochemical staining indicated that the structures detected in the forward direction are primarily the thick collagen type I fibers and the structures identified in the backward direction are diffusive structures of forward detected collagen type I plus collagen type III. In conclusion, we here demonstrate the feasibility of SHG microscopy in differentiating fibrillar collagen subtypes and understanding their remodeling in diseased lung tissues.

Prediction of active sites of enzymes by maximum relevance minimum redundancy (mRMR) feature selection.

PubMed

Gao, Yu-Fei; Li, Bi-Qing; Cai, Yu-Dong; Feng, Kai-Yan; Li, Zhan-Dong; Jiang, Yang

2013-01-27

Identification of catalytic residues plays a key role in understanding how enzymes work. Although numerous computational methods have been developed to predict catalytic residues and active sites, the prediction accuracy remains relatively low with high false positives. In this work, we developed a novel predictor based on the Random Forest algorithm (RF) aided by the maximum relevance minimum redundancy (mRMR) method and incremental feature selection (IFS). We incorporated features of physicochemical/biochemical properties, sequence conservation, residual disorder, secondary structure and solvent accessibility to predict active sites of enzymes and achieved an overall accuracy of 0.885687 and MCC of 0.689226 on an independent test dataset. Feature analysis showed that every category of the features except disorder contributed to the identification of active sites. It was also shown via the site-specific feature analysis that the features derived from the active site itself contributed most to the active site determination. Our prediction method may become a useful tool for identifying the active sites and the key features identified by the paper may provide valuable insights into the mechanism of catalysis.

Histopathological Image Classification using Discriminative Feature-oriented Dictionary Learning

PubMed Central

Vu, Tiep Huu; Mousavi, Hojjat Seyed; Monga, Vishal; Rao, Ganesh; Rao, UK Arvind

2016-01-01

In histopathological image analysis, feature extraction for classification is a challenging task due to the diversity of histology features suitable for each problem as well as presence of rich geometrical structures. In this paper, we propose an automatic feature discovery framework via learning class-specific dictionaries and present a low-complexity method for classification and disease grading in histopathology. Essentially, our Discriminative Feature-oriented Dictionary Learning (DFDL) method learns class-specific dictionaries such that under a sparsity constraint, the learned dictionaries allow representing a new image sample parsimoniously via the dictionary corresponding to the class identity of the sample. At the same time, the dictionary is designed to be poorly capable of representing samples from other classes. Experiments on three challenging real-world image databases: 1) histopathological images of intraductal breast lesions, 2) mammalian kidney, lung and spleen images provided by the Animal Diagnostics Lab (ADL) at Pennsylvania State University, and 3) brain tumor images from The Cancer Genome Atlas (TCGA) database, reveal the merits of our proposal over state-of-the-art alternatives. Moreover, we demonstrate that DFDL exhibits a more graceful decay in classification accuracy against the number of training images which is highly desirable in practice where generous training is often not available. PMID:26513781

Competition between Anion Binding and Dimerization Modulates Staphylococcus aureus Phosphatidylinositol-specific Phospholipase C Enzymatic Activity*

PubMed Central

Cheng, Jiongjia; Goldstein, Rebecca; Stec, Boguslaw; Gershenson, Anne; Roberts, Mary F.

2012-01-01

Staphylococcus aureus phosphatidylinositol-specific phospholipase C (PI-PLC) is a secreted virulence factor for this pathogenic bacterium. A novel crystal structure shows that this PI-PLC can form a dimer via helix B, a structural feature present in all secreted, bacterial PI-PLCs that is important for membrane binding. Despite the small size of this interface, it is critical for optimal enzyme activity. Kinetic evidence, increased enzyme specific activity with increasing enzyme concentration, supports a mechanism where the PI-PLC dimerization is enhanced in membranes containing phosphatidylcholine (PC). Mutagenesis of key residues confirm that the zwitterionic phospholipid acts not by specific binding to the protein, but rather by reducing anionic lipid interactions with a cationic pocket on the surface of the S. aureus enzyme that stabilizes monomeric protein. Despite its structural and sequence similarity to PI-PLCs from other Gram-positive pathogenic bacteria, S. aureus PI-PLC appears to have a unique mechanism where enzyme activity is modulated by competition between binding of soluble anions or anionic lipids to the cationic sensor and transient dimerization on the membrane. PMID:23038258

Figure-Ground Segmentation Using Factor Graphs

PubMed Central

Shen, Huiying; Coughlan, James; Ivanchenko, Volodymyr

2009-01-01

Foreground-background segmentation has recently been applied [26,12] to the detection and segmentation of specific objects or structures of interest from the background as an efficient alternative to techniques such as deformable templates [27]. We introduce a graphical model (i.e. Markov random field)-based formulation of structure-specific figure-ground segmentation based on simple geometric features extracted from an image, such as local configurations of linear features, that are characteristic of the desired figure structure. Our formulation is novel in that it is based on factor graphs, which are graphical models that encode interactions among arbitrary numbers of random variables. The ability of factor graphs to express interactions higher than pairwise order (the highest order encountered in most graphical models used in computer vision) is useful for modeling a variety of pattern recognition problems. In particular, we show how this property makes factor graphs a natural framework for performing grouping and segmentation, and demonstrate that the factor graph framework emerges naturally from a simple maximum entropy model of figure-ground segmentation. We cast our approach in a learning framework, in which the contributions of multiple grouping cues are learned from training data, and apply our framework to the problem of finding printed text in natural scenes. Experimental results are described, including a performance analysis that demonstrates the feasibility of the approach. PMID:20160994

Biochemical Regulatory Features of Activation-Induced Cytidine Deaminase Remain Conserved from Lampreys to Humans

PubMed Central

King, Justin J.; Amemiya, Chris T.; Hsu, Ellen

2017-01-01

ABSTRACT Activation-induced cytidine deaminase (AID) is a genome-mutating enzyme that initiates class switch recombination and somatic hypermutation of antibodies in jawed vertebrates. We previously described the biochemical properties of human AID and found that it is an unusual enzyme in that it exhibits binding affinities for its substrate DNA and catalytic rates several orders of magnitude higher and lower, respectively, than a typical enzyme. Recently, we solved the functional structure of AID and demonstrated that these properties are due to nonspecific DNA binding on its surface, along with a catalytic pocket that predominantly assumes a closed conformation. Here we investigated the biochemical properties of AID from a sea lamprey, nurse shark, tetraodon, and coelacanth: representative species chosen because their lineages diverged at the earliest critical junctures in evolution of adaptive immunity. We found that these earliest-diverged AID orthologs are active cytidine deaminases that exhibit unique substrate specificities and thermosensitivities. Significant amino acid sequence divergence among these AID orthologs is predicted to manifest as notable structural differences. However, despite major differences in sequence specificities, thermosensitivities, and structural features, all orthologs share the unusually high DNA binding affinities and low catalytic rates. This absolute conservation is evidence for biological significance of these unique biochemical properties. PMID:28716949

Sequential structural damage diagnosis algorithm using a change point detection method

NASA Astrophysics Data System (ADS)

Noh, H.; Rajagopal, R.; Kiremidjian, A. S.

2013-11-01

This paper introduces a damage diagnosis algorithm for civil structures that uses a sequential change point detection method. The general change point detection method uses the known pre- and post-damage feature distributions to perform a sequential hypothesis test. In practice, however, the post-damage distribution is unlikely to be known a priori, unless we are looking for a known specific type of damage. Therefore, we introduce an additional algorithm that estimates and updates this distribution as data are collected using the maximum likelihood and the Bayesian methods. We also applied an approximate method to reduce the computation load and memory requirement associated with the estimation. The algorithm is validated using a set of experimental data collected from a four-story steel special moment-resisting frame and multiple sets of simulated data. Various features of different dimensions have been explored, and the algorithm was able to identify damage, particularly when it uses multidimensional damage sensitive features and lower false alarm rates, with a known post-damage feature distribution. For unknown feature distribution cases, the post-damage distribution was consistently estimated and the detection delays were only a few time steps longer than the delays from the general method that assumes we know the post-damage feature distribution. We confirmed that the Bayesian method is particularly efficient in declaring damage with minimal memory requirement, but the maximum likelihood method provides an insightful heuristic approach.

A Fast, Open EEG Classification Framework Based on Feature Compression and Channel Ranking

PubMed Central

Han, Jiuqi; Zhao, Yuwei; Sun, Hongji; Chen, Jiayun; Ke, Ang; Xu, Gesen; Zhang, Hualiang; Zhou, Jin; Wang, Changyong

2018-01-01

Superior feature extraction, channel selection and classification methods are essential for designing electroencephalography (EEG) classification frameworks. However, the performance of most frameworks is limited by their improper channel selection methods and too specifical design, leading to high computational complexity, non-convergent procedure and narrow expansibility. In this paper, to remedy these drawbacks, we propose a fast, open EEG classification framework centralized by EEG feature compression, low-dimensional representation, and convergent iterative channel ranking. First, to reduce the complexity, we use data clustering to compress the EEG features channel-wise, packing the high-dimensional EEG signal, and endowing them with numerical signatures. Second, to provide easy access to alternative superior methods, we structurally represent each EEG trial in a feature vector with its corresponding numerical signature. Thus, the recorded signals of many trials shrink to a low-dimensional structural matrix compatible with most pattern recognition methods. Third, a series of effective iterative feature selection approaches with theoretical convergence is introduced to rank the EEG channels and remove redundant ones, further accelerating the EEG classification process and ensuring its stability. Finally, a classical linear discriminant analysis (LDA) model is employed to classify a single EEG trial with selected channels. Experimental results on two real world brain-computer interface (BCI) competition datasets demonstrate the promising performance of the proposed framework over state-of-the-art methods. PMID:29713262

Low-Rank Discriminant Embedding for Multiview Learning.

PubMed

Li, Jingjing; Wu, Yue; Zhao, Jidong; Lu, Ke

2017-11-01

This paper focuses on the specific problem of multiview learning where samples have the same feature set but different probability distributions, e.g., different viewpoints or different modalities. Since samples lying in different distributions cannot be compared directly, this paper aims to learn a latent subspace shared by multiple views assuming that the input views are generated from this latent subspace. Previous approaches usually learn the common subspace by either maximizing the empirical likelihood, or preserving the geometric structure. However, considering the complementarity between the two objectives, this paper proposes a novel approach, named low-rank discriminant embedding (LRDE), for multiview learning by taking full advantage of both sides. By further considering the duality between data points and features of multiview scene, i.e., data points can be grouped based on their distribution on features, while features can be grouped based on their distribution on the data points, LRDE not only deploys low-rank constraints on both sample level and feature level to dig out the shared factors across different views, but also preserves geometric information in both the ambient sample space and the embedding feature space by designing a novel graph structure under the framework of graph embedding. Finally, LRDE jointly optimizes low-rank representation and graph embedding in a unified framework. Comprehensive experiments in both multiview manner and pairwise manner demonstrate that LRDE performs much better than previous approaches proposed in recent literatures.

Conditions for building a community of practice in an advanced physics laboratory

NASA Astrophysics Data System (ADS)

Irving, Paul W.; Sayre, Eleanor C.

2014-06-01

We use the theory of communities of practice and the concept of accountable disciplinary knowledge to describe how a learning community develops in the context of an upper-division physics laboratory course. The change in accountable disciplinary knowledge motivates students' enculturation into a community of practice. The enculturation process is facilitated by four specific structural features of the course and supported by a primary instructional choice. The four structural features are "paucity of instructor time," "all in a room together," "long and difficult experiments," and "same experiments at different times." The instructional choice is the encouragement of the sharing and development of knowledge and understanding by the instructor. The combination of the instructional choice and structural features promotes the development of the learning community in which students engage in authentic practices of a physicist. This results in a classroom community that can provide students with the opportunity to have an accelerated trajectory towards being a more central participant of the community of a practice of physicists. We support our claims with video-based observations of laboratory classroom interactions and individual, semistructured interviews with students about their laboratory experiences and physics identity.

Magnetoconductance signatures of subband structure in semiconductor nanowires

NASA Astrophysics Data System (ADS)

Holloway, Gregory; Haapamaki, Chris; Lapierre, Ray; Baugh, Jonathan

2015-03-01

Understanding the subband structure due to radial confinement in semiconductor nanowires can benefit technologies ranging from optical sensors to quantum information processing. An axial magnetic field couples to the orbital angular momentum, giving rise to non-trivial features in electronic transport as a function of magnetic field. Previous reports focused on conduction electrons confined to a thin shell near the nanowire surface, which lead to flux-periodic energies and conductance oscillations. Here, we calculate the eigenstates for more general radial potentials with moderate to low surface band bending such that electrons are distributed more uniformly across the nanowire cross-section. It is found that the energy spectrum becomes aperiodic in both gate voltage and magnetic field as the radial potential becomes flatter. The behavior of an energy level is dictated by its angular momentum, and this allows, in principle, each state to be identified based on its dependence on magnetic field and the chemical potential. We experimentally investigate a short-channel InAs nanowire FET in search of conductance features that reveal this subband structure. A quantitative measure for assigning conductance features to specific transverse states is introduced and applied to this device.

Prospecting Biotechnologically-Relevant Monooxygenases from Cold Sediment Metagenomes: An In Silico Approach

DOE PAGES

Musumeci, Matias A.; Lozada, Mariana; Rial, Daniela V.; ...

2017-04-09

The goal of this work was to identify sequences encoding monooxygenase biocatalysts with novel features by in silico mining an assembled metagenomic dataset of polar and subpolar marine sediments. The targeted enzyme sequences were Baeyer-Villiger and bacterial cytochrome P450 monooxygenases (CYP153). These enzymes have wide-ranging applications, from the synthesis of steroids, antibiotics, mycotoxins and pheromones to the synthesis of monomers for polymerization and anticancer precursors, due to their extraordinary enantio-, regio-, and chemo- selectivity that are valuable features for organic synthesis. Phylogenetic analyses were used to select the most divergent sequences affiliated to these enzyme families among the 264 putativemore » monooxygenases recovered from the ~14 million protein-coding sequences in the assembled metagenome dataset. Three-dimensional structure modeling and docking analysis suggested features useful in biotechnological applications in five metagenomic sequences, such as wide substrate range, novel substrate specificity or regioselectivity. Further analysis revealed structural features associated with psychrophilic enzymes, such as broader substrate accessibility, larger catalytic pockets or low domain interactions, suggesting that they could be applied in biooxidations at room or low temperatures, saving costs inherent to energy consumption. As a result, this work allowed the identification of putative enzyme candidates with promising features from metagenomes, providing a suitable starting point for further developments.« less

Prospecting Biotechnologically-Relevant Monooxygenases from Cold Sediment Metagenomes: An In Silico Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Musumeci, Matias A.; Lozada, Mariana; Rial, Daniela V.

The goal of this work was to identify sequences encoding monooxygenase biocatalysts with novel features by in silico mining an assembled metagenomic dataset of polar and subpolar marine sediments. The targeted enzyme sequences were Baeyer-Villiger and bacterial cytochrome P450 monooxygenases (CYP153). These enzymes have wide-ranging applications, from the synthesis of steroids, antibiotics, mycotoxins and pheromones to the synthesis of monomers for polymerization and anticancer precursors, due to their extraordinary enantio-, regio-, and chemo- selectivity that are valuable features for organic synthesis. Phylogenetic analyses were used to select the most divergent sequences affiliated to these enzyme families among the 264 putativemore » monooxygenases recovered from the ~14 million protein-coding sequences in the assembled metagenome dataset. Three-dimensional structure modeling and docking analysis suggested features useful in biotechnological applications in five metagenomic sequences, such as wide substrate range, novel substrate specificity or regioselectivity. Further analysis revealed structural features associated with psychrophilic enzymes, such as broader substrate accessibility, larger catalytic pockets or low domain interactions, suggesting that they could be applied in biooxidations at room or low temperatures, saving costs inherent to energy consumption. As a result, this work allowed the identification of putative enzyme candidates with promising features from metagenomes, providing a suitable starting point for further developments.« less

Prospecting Biotechnologically-Relevant Monooxygenases from Cold Sediment Metagenomes: An In Silico Approach.

PubMed

Musumeci, Matías A; Lozada, Mariana; Rial, Daniela V; Mac Cormack, Walter P; Jansson, Janet K; Sjöling, Sara; Carroll, JoLynn; Dionisi, Hebe M

2017-04-09

The goal of this work was to identify sequences encoding monooxygenase biocatalysts with novel features by in silico mining an assembled metagenomic dataset of polar and subpolar marine sediments. The targeted enzyme sequences were Baeyer-Villiger and bacterial cytochrome P450 monooxygenases (CYP153). These enzymes have wide-ranging applications, from the synthesis of steroids, antibiotics, mycotoxins and pheromones to the synthesis of monomers for polymerization and anticancer precursors, due to their extraordinary enantio-, regio-, and chemo- selectivity that are valuable features for organic synthesis. Phylogenetic analyses were used to select the most divergent sequences affiliated to these enzyme families among the 264 putative monooxygenases recovered from the ~14 million protein-coding sequences in the assembled metagenome dataset. Three-dimensional structure modeling and docking analysis suggested features useful in biotechnological applications in five metagenomic sequences, such as wide substrate range, novel substrate specificity or regioselectivity. Further analysis revealed structural features associated with psychrophilic enzymes, such as broader substrate accessibility, larger catalytic pockets or low domain interactions, suggesting that they could be applied in biooxidations at room or low temperatures, saving costs inherent to energy consumption. This work allowed the identification of putative enzyme candidates with promising features from metagenomes, providing a suitable starting point for further developments.

Prospecting Biotechnologically-Relevant Monooxygenases from Cold Sediment Metagenomes: An In Silico Approach

PubMed Central

Musumeci, Matías A.; Lozada, Mariana; Rial, Daniela V.; Mac Cormack, Walter P.; Jansson, Janet K.; Sjöling, Sara; Carroll, JoLynn; Dionisi, Hebe M.

2017-01-01

The goal of this work was to identify sequences encoding monooxygenase biocatalysts with novel features by in silico mining an assembled metagenomic dataset of polar and subpolar marine sediments. The targeted enzyme sequences were Baeyer–Villiger and bacterial cytochrome P450 monooxygenases (CYP153). These enzymes have wide-ranging applications, from the synthesis of steroids, antibiotics, mycotoxins and pheromones to the synthesis of monomers for polymerization and anticancer precursors, due to their extraordinary enantio-, regio-, and chemo- selectivity that are valuable features for organic synthesis. Phylogenetic analyses were used to select the most divergent sequences affiliated to these enzyme families among the 264 putative monooxygenases recovered from the ~14 million protein-coding sequences in the assembled metagenome dataset. Three-dimensional structure modeling and docking analysis suggested features useful in biotechnological applications in five metagenomic sequences, such as wide substrate range, novel substrate specificity or regioselectivity. Further analysis revealed structural features associated with psychrophilic enzymes, such as broader substrate accessibility, larger catalytic pockets or low domain interactions, suggesting that they could be applied in biooxidations at room or low temperatures, saving costs inherent to energy consumption. This work allowed the identification of putative enzyme candidates with promising features from metagenomes, providing a suitable starting point for further developments. PMID:28397770

Bird sound spectrogram decomposition through Non-Negative Matrix Factorization for the acoustic classification of bird species.

PubMed

Ludeña-Choez, Jimmy; Quispe-Soncco, Raisa; Gallardo-Antolín, Ascensión

2017-01-01

Feature extraction for Acoustic Bird Species Classification (ABSC) tasks has traditionally been based on parametric representations that were specifically developed for speech signals, such as Mel Frequency Cepstral Coefficients (MFCC). However, the discrimination capabilities of these features for ABSC could be enhanced by accounting for the vocal production mechanisms of birds, and, in particular, the spectro-temporal structure of bird sounds. In this paper, a new front-end for ABSC is proposed that incorporates this specific information through the non-negative decomposition of bird sound spectrograms. It consists of the following two different stages: short-time feature extraction and temporal feature integration. In the first stage, which aims at providing a better spectral representation of bird sounds on a frame-by-frame basis, two methods are evaluated. In the first method, cepstral-like features (NMF_CC) are extracted by using a filter bank that is automatically learned by means of the application of Non-Negative Matrix Factorization (NMF) on bird audio spectrograms. In the second method, the features are directly derived from the activation coefficients of the spectrogram decomposition as performed through NMF (H_CC). The second stage summarizes the most relevant information contained in the short-time features by computing several statistical measures over long segments. The experiments show that the use of NMF_CC and H_CC in conjunction with temporal integration significantly improves the performance of a Support Vector Machine (SVM)-based ABSC system with respect to conventional MFCC.

Bird sound spectrogram decomposition through Non-Negative Matrix Factorization for the acoustic classification of bird species

PubMed Central

Quispe-Soncco, Raisa

2017-01-01

Feature extraction for Acoustic Bird Species Classification (ABSC) tasks has traditionally been based on parametric representations that were specifically developed for speech signals, such as Mel Frequency Cepstral Coefficients (MFCC). However, the discrimination capabilities of these features for ABSC could be enhanced by accounting for the vocal production mechanisms of birds, and, in particular, the spectro-temporal structure of bird sounds. In this paper, a new front-end for ABSC is proposed that incorporates this specific information through the non-negative decomposition of bird sound spectrograms. It consists of the following two different stages: short-time feature extraction and temporal feature integration. In the first stage, which aims at providing a better spectral representation of bird sounds on a frame-by-frame basis, two methods are evaluated. In the first method, cepstral-like features (NMF_CC) are extracted by using a filter bank that is automatically learned by means of the application of Non-Negative Matrix Factorization (NMF) on bird audio spectrograms. In the second method, the features are directly derived from the activation coefficients of the spectrogram decomposition as performed through NMF (H_CC). The second stage summarizes the most relevant information contained in the short-time features by computing several statistical measures over long segments. The experiments show that the use of NMF_CC and H_CC in conjunction with temporal integration significantly improves the performance of a Support Vector Machine (SVM)-based ABSC system with respect to conventional MFCC. PMID:28628630

Specific Features of the Domain Structure of BaTiO3 Crystals during Thermal Heating and Cooling

NASA Astrophysics Data System (ADS)

Kiselev, D. A.; Ilina, T. S.; Malinkovich, M. D.; Sergeeva, O. N.; Bolshakova, N. N.; Semenova, E. M.; Kuznetsova, Yu. V.

2018-04-01

This paper presents the results of the study of the domain structure of barium titanate crystals in a wide temperature range including the Curie point ( T C) using the polarization-optical method in the reflected light and the force microscopy of the piezoelectric response. It is shown that a new a-c domain structure forms during cyclic heating of the crystal above T C and subsequent cooling to the ferroelectric phase. The role of uncompensated charges appeared on the crystal surface during the phase transition and their influence on the formation of the domain structure during cooling are discussed.

Charge order-superfluidity transition in a two-dimensional system of hard-core bosons and emerging domain structures

NASA Astrophysics Data System (ADS)

Moskvin, A. S.; Panov, Yu. D.; Rybakov, F. N.; Borisov, A. B.

2017-11-01

We have used high-performance parallel computations by NVIDIA graphics cards applying the method of nonlinear conjugate gradients and Monte Carlo method to observe directly the developing ground state configuration of a two-dimensional hard-core boson system with decrease in temperature, and its evolution with deviation from a half-filling. This has allowed us to explore unconventional features of a charge order—superfluidity phase transition, specifically, formation of an irregular domain structure, emergence of a filamentary superfluid structure that condenses within of the charge-ordered phase domain antiphase boundaries, and formation and evolution of various topological structures.

Molecular engineering of phosphole-based conjugated materials

NASA Astrophysics Data System (ADS)

Ren, Yi

The work in this thesis focuses on the molecular engineering of phosphorus-based conjugated materials. In the first part (Chapters Two and Three), new phosphorus-based conjugated systems were designed and synthesized to study the effect of the heteroelement on the electronic properties of the π-conjugated systems. The second part (Chapters Four and Five) deals with the self-assembly features of specifically designed phosphorus-based conjugated systems. In Chapter Two, electron-poor and electron-rich aromatic substituents were introduced to the dithienophosphole core in order to balance the electron-accepting and electron-donating character of the systems. Furthermore, an intriguing intramolecular charge transfer process could be observed between two dithienophosphole cores in a bridged bisphosphole-system. In Chapter Three, a secondary heteroelement (Si, P, S) was incorporated in the phosphorus-based conjugated systems. Extensive structure-property studies revealed that the secondary heteroelement can effectively manipulate the communication in phosphinine-based systems. The study of a heterotetracene system allowed for selectively applying distinct heteroatom (S/P) chemistries, which offers a powerful tool for the modification of the electronic structure of the system. More importantly, the heteroatom-specific electronic nature (S/P) can be utilized to selectively control different photophysical aspects (energy gap and fluorescence quantum yield). Furthermore, additional molecular engineering of the heterotetracene provided access to well-defined 1D microstructures, which opened the door for designing multi-functional self-assembled phosphorus-based materials. In Chapter Four, the self-organizing phosphole-lipid system is introduced, which combines the features of phospholipids with the electronics of phospholes. Its amphiphilic nature induces intriguing self-assembly features - liquid crystal and soft crystal architectures, both exhibiting well-organized lamellar structure at a wide range of temperatures. Importantly, its dynamic structure endows the phosphole-lipid system with intriguing external stimuli-responsive features allowing for the modification of the emission of the system without further chemical modification. Chapter Five describes how further molecular engineering allowed for access to a series of new highly fluorescent phosphole-lipid organogels. Remarkably, the external-stimuli responsive features of the system can be amplified in a donor-acceptor system accessible through changes in long distance fluorescence resonance energy transfer processes. In addition, the first fluorescent liquid phospholes could also be accessed in the context of the work on the new phosphole-lipid system.

A Flexible Mechanism of Rule Selection Enables Rapid Feature-Based Reinforcement Learning

PubMed Central

Balcarras, Matthew; Womelsdorf, Thilo

2016-01-01

Learning in a new environment is influenced by prior learning and experience. Correctly applying a rule that maps a context to stimuli, actions, and outcomes enables faster learning and better outcomes compared to relying on strategies for learning that are ignorant of task structure. However, it is often difficult to know when and how to apply learned rules in new contexts. In our study we explored how subjects employ different strategies for learning the relationship between stimulus features and positive outcomes in a probabilistic task context. We test the hypothesis that task naive subjects will show enhanced learning of feature specific reward associations by switching to the use of an abstract rule that associates stimuli by feature type and restricts selections to that dimension. To test this hypothesis we designed a decision making task where subjects receive probabilistic feedback following choices between pairs of stimuli. In the task, trials are grouped in two contexts by blocks, where in one type of block there is no unique relationship between a specific feature dimension (stimulus shape or color) and positive outcomes, and following an un-cued transition, alternating blocks have outcomes that are linked to either stimulus shape or color. Two-thirds of subjects (n = 22/32) exhibited behavior that was best fit by a hierarchical feature-rule model. Supporting the prediction of the model mechanism these subjects showed significantly enhanced performance in feature-reward blocks, and rapidly switched their choice strategy to using abstract feature rules when reward contingencies changed. Choice behavior of other subjects (n = 10/32) was fit by a range of alternative reinforcement learning models representing strategies that do not benefit from applying previously learned rules. In summary, these results show that untrained subjects are capable of flexibly shifting between behavioral rules by leveraging simple model-free reinforcement learning and context-specific selections to drive responses. PMID:27064794

Fabrication and Characterization of Woodpile Structures for Direct Laser Acceleration

DOE Office of Scientific and Technical Information (OSTI.GOV)

McGuinness, C.; Colby, E.; England, R.J.

2010-08-26

An eight and nine layer three dimensional photonic crystal with a defect designed specifically for accelerator applications has been fabricated. The structures were fabricated using a combination of nanofabrication techniques, including low pressure chemical vapor deposition, optical lithography, and chemical mechanical polishing. Limits imposed by the optical lithography set the minimum feature size to 400 nm, corresponding to a structure with a bandgap centered at 4.26 {micro}m. Reflection spectroscopy reveal a peak in reflectivity about the predicted region, and good agreement with simulation is shown. The eight and nine layer structures will be aligned and bonded together to form themore » complete seventeen layer woodpile accelerator structure.« less

Spatial and Feature-Based Attention in a Layered Cortical Microcircuit Model

PubMed Central

Wagatsuma, Nobuhiko; Potjans, Tobias C.; Diesmann, Markus; Sakai, Ko; Fukai, Tomoki

2013-01-01

Directing attention to the spatial location or the distinguishing feature of a visual object modulates neuronal responses in the visual cortex and the stimulus discriminability of subjects. However, the spatial and feature-based modes of attention differently influence visual processing by changing the tuning properties of neurons. Intriguingly, neurons' tuning curves are modulated similarly across different visual areas under both these modes of attention. Here, we explored the mechanism underlying the effects of these two modes of visual attention on the orientation selectivity of visual cortical neurons. To do this, we developed a layered microcircuit model. This model describes multiple orientation-specific microcircuits sharing their receptive fields and consisting of layers 2/3, 4, 5, and 6. These microcircuits represent a functional grouping of cortical neurons and mutually interact via lateral inhibition and excitatory connections between groups with similar selectivity. The individual microcircuits receive bottom-up visual stimuli and top-down attention in different layers. A crucial assumption of the model is that feature-based attention activates orientation-specific microcircuits for the relevant feature selectively, whereas spatial attention activates all microcircuits homogeneously, irrespective of their orientation selectivity. Consequently, our model simultaneously accounts for the multiplicative scaling of neuronal responses in spatial attention and the additive modulations of orientation tuning curves in feature-based attention, which have been observed widely in various visual cortical areas. Simulations of the model predict contrasting differences between excitatory and inhibitory neurons in the two modes of attentional modulations. Furthermore, the model replicates the modulation of the psychophysical discriminability of visual stimuli in the presence of external noise. Our layered model with a biologically suggested laminar structure describes the basic circuit mechanism underlying the attention-mode specific modulations of neuronal responses and visual perception. PMID:24324628

The power of social networks and social support in promotion of physical activity and body mass index among African American adults.

PubMed

Flórez, Karen R; Richardson, Andrea S; Ghosh-Dastidar, Madhumita Bonnie; Troxel, Wendy; DeSantis, Amy; Colabianchi, Natalie; Dubowitz, Tamara

2018-04-01

Social support and social networks can elucidate important structural and functional aspects of social relationships that are associated with health-promoting behaviors, including Physical Activity (PA) and weight. A growing number of studies have investigated the relationship between social support, social networks, PA and obesity specifically among African Americans; however, the evidence is mixed and many studies focus exclusively on African American women. Most studies have also focused on either functional or structural aspects of social relationships (but not both) and few have objectively measured moderate-to-vigorous physical activity (MVPA) and body mass index (BMI). Cross-sectional surveys of adult African American men and women living in two low-income predominantly African American neighborhoods in Pittsburgh, PA (N = 799) measured numerous structural features as well as functional aspects of social relationships. Specifically, structural features included social isolation, and social network size and diversity. Functional aspects included perceptions of social support for physical activity from the social network in general as well as from family and friends specifically. Height, weight, and PA were objectively measured. From these, we derived Body Mass Index (BMI) and moderate-to-vigorous physical activity (MVPA). All regression models were stratified by gender, and included age, income, education, employment, marital status, physical limitations, and a neighborhood indicator. Greater social isolation was a significant predictor of lower BMI among men only. Among women only, social isolation was significantly associated with increased MVPA whereas, network diversity was significantly associated with reduced MVPA. Future research would benefit from in-depth qualitative investigations to understand how social networks may act to influence different types of physical activity among African Americans, as well as understand how they can be possible levers for health promotion and prevention.

Material Parameter Sensitivity of Predicted Injury in the Lower Leg

DTIC Science & Technology

2015-06-01

in a region of the structure that experienced the largest strains due to geometric or structural features, e.g., a sharp curve or point. The specific...Annals of Biomedical Engineering. 2012;40(12):2519–2531. 23. Iwamoto M, Omori K, Kimpara H, Nakahira Y, Tamura A, Watanabe I, Miki K, Hasegawa J...cortical layer; the void space between the inner scaled bone and the original outer bone was considered the cortical shell. Thus, a sharp interface exists

Towards automated processing of clinical Finnish: sublanguage analysis and a rule-based parser.

PubMed

Laippala, Veronika; Ginter, Filip; Pyysalo, Sampo; Salakoski, Tapio

2009-12-01

In this paper, we present steps taken towards more efficient automated processing of clinical Finnish, focusing on daily nursing notes in a Finnish Intensive Care Unit (ICU). First, we analyze ICU Finnish as a sublanguage, identifying its specific features facilitating, for example, the development of a specialized syntactic analyser. The identified features include frequent omission of finite verbs, limitations in allowed syntactic structures, and domain-specific vocabulary. Second, we develop a formal grammar and a parser for ICU Finnish, thus providing better tools for the development of further applications in the clinical domain. The grammar is implemented in the LKB system in a typed feature structure formalism. The lexicon is automatically generated based on the output of the FinTWOL morphological analyzer adapted to the clinical domain. As an additional experiment, we study the effect of using Finnish constraint grammar to reduce the size of the lexicon. The parser construction thus makes efficient use of existing resources for Finnish. The grammar currently covers 76.6% of ICU Finnish sentences, producing highly accurate best-parse analyzes with F-score of 91.1%. We find that building a parser for the highly specialized domain sublanguage is not only feasible, but also surprisingly efficient, given an existing morphological analyzer with broad vocabulary coverage. The resulting parser enables a deeper analysis of the text than was previously possible.

Structure and properties of polyethylene films used in heavy lift balloons

NASA Technical Reports Server (NTRS)

Khoury, F.; Crissman, J. M.; Fanconi, B. M.; Wagner, H. L.; Botz, L. H.

1985-01-01

The following features of five polyethylene films used by NASA in the construction of heavy lift balloons have been examined: molecular weight, molecular weight distribution, branching, melting behavior, density, surface texture, birefringence, orientation of crystalline regions, unlaxial deformation in the machine and transverse directions, and the effect of sample geometry and strain rate on deformation behavior. The goal of this exploratory study was to determine whether there are significant differences in any of the above mentioned features, or combination of features between the films. The acquisition of such information is a first step towards determining whether there are any specific correlations between film characteristics and the incidence of catastrophic failure of balloons during ascent through the troposphere. This exploratory study has resulted in the identification of similarities and differences between various features of the films.

Identification of upstream and intragenic regulatory elements that confer cell-type-restricted and differentiation-specific expression on the muscle creatine kinase gene

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sternberg, E.A.; Spizz, G.; Perry, W.M.

1988-07-01

Terminal differentiation of skeletal myobalsts is accompanied by induction of a series of tissue-specific gene products, which includes the muscle isoenzymte of creatine kinase (MCK). To begin to define the sequences and signals involved in MCK regulation in developing muscle cells, the mouse MCK gene has been isolated. Sequence analysis of 4,147 bases of DNA surrounding the transcription initiation site revealed several interesting structural features, some of which are common to other muscle-specific genes and to cellular and viral enhancers.

Tuning the porosity of mesoporous NiO through calcining isostructural Ni-MOFs toward supercapacitor applications

NASA Astrophysics Data System (ADS)

Hou, Xiang-Yang; Yan, Xiao-Li; Wang, Xiao; Zhai, Quan-Guo

2018-07-01

NiO has an unusually high theoretical specific capacitance and possess relatively high electrical conductivity compared to other metal oxides. However, the reported specific capacitance of the NiO-based electrodes is far below the theoretical value up to now. In this paper, three porous NiO materials with different specific surface area were synthesized simply by calcining iso-structural Ni-based MOFs templates. The formation mechanism of NiO was discussed by taking into account the thermal behavior and intrinsic structural features of the Ni-MOFs. Taking advantages of the Ni-MOFs precursors, all prepared NiO compounds are mesoporous and their porosity can be tuned by the structure of MOFs. Specially, due to the high porosity, three NiO exhibited an improved electrochemical performance and the specific discharge capacitances are of 102, 105, and 116 F g-1 at the current density of 1 A g-1, respectively. The specific capacitance of 1-NiO-450 is approximately 93.2% of its maximum value after 3000 cycles, which obviously superior to most of the previously reported NiO electrode materials and suggests their promising applications in supercapacitors.

Structure-Specific Statistical Mapping of White Matter Tracts

PubMed Central

Yushkevich, Paul A.; Zhang, Hui; Simon, Tony; Gee, James C.

2008-01-01

We present a new model-based framework for the statistical analysis of diffusion imaging data associated with specific white matter tracts. The framework takes advantage of the fact that several of the major white matter tracts are thin sheet-like structures that can be effectively modeled by medial representations. The approach involves segmenting major tracts and fitting them with deformable geometric medial models. The medial representation makes it possible to average and combine tensor-based features along directions locally perpendicular to the tracts, thus reducing data dimensionality and accounting for errors in normalization. The framework enables the analysis of individual white matter structures, and provides a range of possibilities for computing statistics and visualizing differences between cohorts. The framework is demonstrated in a study of white matter differences in pediatric chromosome 22q11.2 deletion syndrome. PMID:18407524

Demersal fish assemblages on seamounts and other rugged features in the northeastern Caribbean

NASA Astrophysics Data System (ADS)

Quattrini, Andrea M.; Demopoulos, Amanda W. J.; Singer, Randal; Roa-Varon, Adela; Chaytor, Jason D.

2017-05-01

Recent investigations of demersal fish communities in deepwater (>50 m) habitats have considerably increased our knowledge of the factors that influence the assemblage structure of fishes across mesophotic to deep-sea depths. While different habitat types influence deepwater fish distribution, whether different types of rugged seafloor features provide functionally equivalent habitat for fishes is poorly understood. In the northeastern Caribbean, different types of rugged features (e.g., seamounts, banks, canyons) punctuate insular margins, and thus create a remarkable setting in which to compare demersal fish communities across various features. Concurrently, several water masses are vertically layered in the water column, creating strong stratification layers corresponding to specific abiotic conditions. In this study, we examined differences among fish assemblages across different features (e.g., seamount, canyon, bank/ridge) and water masses at depths ranging from 98 to 4060 m in the northeastern Caribbean. We conducted 26 remotely operated vehicle dives across 18 sites, identifying 156 species of which 42% of had not been previously recorded from particular depths or localities in the region. While rarefaction curves indicated fewer species at seamounts than at other features in the NE Caribbean, assemblage structure was similar among the different types of features. Thus, similar to seamount studies in other regions, seamounts in the Anegada Passage do not harbor distinct communities from other types of rugged features. Species assemblages, however, differed among depths, with zonation generally corresponding to water mass boundaries in the region. High species turnover occurred at depths <1200 m, and may be driven by changes in water mass characteristics including temperature (4.8-24.4 °C) and dissolved oxygen (2.2-9.5 mg per l). Our study suggests the importance of water masses in influencing community structure of benthic fauna, while considerably adding to the knowledge of mesophotic and deep-sea fish biogeography.

Demersal fish assemblages on seamounts and other rugged features in the northeastern Caribbean

USGS Publications Warehouse

Quattrini, Andrea M.; Demopoulos, Amanda W. J.; Singer, Randal; Roa-Varon, Adela; Chaytor, Jason D.

2017-01-01

Recent investigations of demersal fish communities in deepwater (>50 m) habitats have considerably increased our knowledge of the factors that influence the assemblage structure of fishes across mesophotic to deep-sea depths. While different habitat types influence deepwater fish distribution, whether different types of rugged seafloor features provide functionally equivalent habitat for fishes is poorly understood. In the northeastern Caribbean, different types of rugged features (e.g., seamounts, banks, canyons) punctuate insular margins, and thus create a remarkable setting in which to compare demersal fish communities across various features. Concurrently, several water masses are vertically layered in the water column, creating strong stratification layers corresponding to specific abiotic conditions. In this study, we examined differences among fish assemblages across different features (e.g., seamount, canyon, bank/ridge) and water masses at depths ranging from 98 to 4060 m in the northeastern Caribbean. We conducted 26 remotely operated vehicle dives across 18 sites, identifying 156 species of which 42% of had not been previously recorded from particular depths or localities in the region. While rarefaction curves indicated fewer species at seamounts than at other features in the NE Caribbean, assemblage structure was similar among the different types of features. Thus, similar to seamount studies in other regions, seamounts in the Anegada Passage do not harbor distinct communities from other types of rugged features. Species assemblages, however, differed among depths, with zonation generally corresponding to water mass boundaries in the region. High species turnover occurred at depths <1200 m, and may be driven by changes in water mass characteristics including temperature (4.8–24.4 °C) and dissolved oxygen (2.2–9.5 mg per l). Our study suggests the importance of water masses in influencing community structure of benthic fauna, while considerably adding to the knowledge of mesophotic and deep-sea fish biogeography.

Improving link prediction in complex networks by adaptively exploiting multiple structural features of networks

NASA Astrophysics Data System (ADS)

Ma, Chuang; Bao, Zhong-Kui; Zhang, Hai-Feng

2017-10-01

So far, many network-structure-based link prediction methods have been proposed. However, these methods only highlight one or two structural features of networks, and then use the methods to predict missing links in different networks. The performances of these existing methods are not always satisfied in all cases since each network has its unique underlying structural features. In this paper, by analyzing different real networks, we find that the structural features of different networks are remarkably different. In particular, even in the same network, their inner structural features are utterly different. Therefore, more structural features should be considered. However, owing to the remarkably different structural features, the contributions of different features are hard to be given in advance. Inspired by these facts, an adaptive fusion model regarding link prediction is proposed to incorporate multiple structural features. In the model, a logistic function combing multiple structural features is defined, then the weight of each feature in the logistic function is adaptively determined by exploiting the known structure information. Last, we use the "learnt" logistic function to predict the connection probabilities of missing links. According to our experimental results, we find that the performance of our adaptive fusion model is better than many similarity indices.

Automatic detection of obstructive sleep apnea using speech signals.

PubMed

Goldshtein, Evgenia; Tarasiuk, Ariel; Zigel, Yaniv

2011-05-01

Obstructive sleep apnea (OSA) is a common disorder associated with anatomical abnormalities of the upper airways that affects 5% of the population. Acoustic parameters may be influenced by the vocal tract structure and soft tissue properties. We hypothesize that speech signal properties of OSA patients will be different than those of control subjects not having OSA. Using speech signal processing techniques, we explored acoustic speech features of 93 subjects who were recorded using a text-dependent speech protocol and a digital audio recorder immediately prior to polysomnography study. Following analysis of the study, subjects were divided into OSA (n=67) and non-OSA (n=26) groups. A Gaussian mixture model-based system was developed to model and classify between the groups; discriminative features such as vocal tract length and linear prediction coefficients were selected using feature selection technique. Specificity and sensitivity of 83% and 79% were achieved for the male OSA and 86% and 84% for the female OSA patients, respectively. We conclude that acoustic features from speech signals during wakefulness can detect OSA patients with good specificity and sensitivity. Such a system can be used as a basis for future development of a tool for OSA screening. © 2011 IEEE

Unraveling Appalachian tectonics: domain analysis of topographic lineaments in Pennsylvania

NASA Astrophysics Data System (ADS)

Karimi, B.; Schon, K.; Nussbaum, G. W.; Storer, N. D.; McGuire, J. L.; Hardcastle, K.

2016-12-01

Litho-tectonic provinces provide different components of a regions' tectonic history, and are identified as spatial entities with common structural elements, or a number of contiguous related elements. The province boundaries are easily identified when geomorphic expressions are distinct, or significant rock exposure allows for little uncertainty. When exposures are limited, locations of boundaries between provinces are uncertain. In such instances, satellite imagery can be quite advantageous, as tectonically sourced features (faults, folds, fractures, and joints) may exert a strong control on topographic patterns by creating pathways for weathering and erosion. Lineament analyses of topography often focus on well-pronounced tectonic features to interpret regional tectonics. We suggest that lineament analyses including all topographic features may include more subtle tectonic features, resulting in the identification of minor heterogeneities within litho-tectonic provinces. Our study focuses on Appalachian tectonics, specifically in Pennsylvania (PA), home to the Appalachian Orocline and 5 distinct tectonic provinces. Using hillshades from a digital elevation model (DEM) of PA, we manually pick all topographic lineaments 1 km or greater, discriminating only against man-made structures. The final lineament coverage of the state is subdivided into smaller areas for which rose diagrams were prepared. The dominant lineament trends were compared and associated with known structural features. Peaks with no known source are marked as possible tectonic features requiring further research. A domain analysis is performed on the lineament data to identify the extent and interplay of swarms, followed by an investigation of their azimuthal compatibility. We present the results of our domain analysis of all topographic lineaments in the context of identifying litho-tectonic provinces associated with Appalachian tectonics in Pennsylvania, and possible heterogeneities within them.

Structure–Function Studies of DNA Polymerase λ

PubMed Central

2015-01-01

DNA polymerase λ (pol λ) functions in DNA repair with its main roles considered to be filling short gaps during repair of double-strand breaks by nonhomologous end joining and during base excision repair. As indicated by structural and biochemical studies over the past 10 years, pol λ shares many common properties with other family X siblings (pol β, pol μ, and terminal deoxynucleotidyl transferase) but also has unique structural features that determine its specific functions. In this review, we consider how structural studies over the past decade furthered our understanding of the behavior and biological roles of pol λ. PMID:24716527

Effect of Long-Period Ordering of the Structure of a Plant on the Initial Stages of Photosynthesis

NASA Astrophysics Data System (ADS)

Korshunov, M. A.; Shabanov, A. V.; Bukhanov, E. R.; Shabanov, V. F.

2018-01-01

Using data on the structure of plant leaves, specific features of light propagation in biophotoniccrystal structures have been established by the transfer matrix method. Splitting of the stopband in two bands has been found. The density of photonic states and the electromagnetic field value have been calculated. The occurrence of two photosystems (splitting of the stopband in two bands), the peculiarity of the long-wavelength quantum yield and its enhancement (Emerson effect), and water dissociation in the soft mode due to an increase in the electromagnetic field on the layers are explained.

Exact coupling threshold for structural transition reveals diversified behaviors in interconnected networks.

PubMed

Darabi Sahneh, Faryad; Scoglio, Caterina; Van Mieghem, Piet

2015-10-01

An interconnected network features a structural transition between two regimes [F. Radicchi and A. Arenas, Nat. Phys. 9, 717 (2013)]: one where the network components are structurally distinguishable and one where the interconnected network functions as a whole. Our exact solution for the coupling threshold uncovers network topologies with unexpected behaviors. Specifically, we show conditions that superdiffusion, introduced by Gómez et al. [Phys. Rev. Lett. 110, 028701 (2013)], can occur despite the network components functioning distinctly. Moreover, we find that components of certain interconnected network topologies are indistinguishable despite very weak coupling between them.

Structural health monitoring for ship structures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Farrar, Charles; Park, Gyuhae; Angel, Marian

2009-01-01

Currently the Office of Naval Research is supporting the development of structural health monitoring (SHM) technology for U.S. Navy ship structures. This application is particularly challenging because of the physical size of these structures, the widely varying and often extreme operational and environmental conditions associated with these ships missions, lack of data from known damage conditions, limited sensing that was not designed specifically for SHM, and the management of the vast amounts of data that can be collected during a mission. This paper will first define a statistical pattern recognition paradigm for SHM by describing the four steps of (1)more » Operational Evaluation, (2) Data Acquisition, (3) Feature Extraction, and (4) Statistical Classification of Features as they apply to ship structures. Note that inherent in the last three steps of this process are additional tasks of data cleansing, compression, normalization and fusion. The presentation will discuss ship structure SHM challenges in the context of applying various SHM approaches to sea trials data measured on an aluminum multi-hull high-speed ship, the HSV-2 Swift. To conclude, the paper will discuss several outstanding issues that need to be addressed before SHM can make the transition from a research topic to actual field applications on ship structures and suggest approaches for addressing these issues.« less

Quantification of Lignin and Its Structural Features in Plant Biomass Using 13C Lignin as Internal Standard for Pyrolysis-GC-SIM-MS.

PubMed

van Erven, Gijs; de Visser, Ries; Merkx, Donny W H; Strolenberg, Willem; de Gijsel, Peter; Gruppen, Harry; Kabel, Mirjam A

2017-10-17

Understanding the mechanisms underlying plant biomass recalcitrance at the molecular level can only be achieved by accurate analyses of both the content and structural features of the molecules involved. Current quantification of lignin is, however, majorly based on unspecific gravimetric analysis after sulfuric acid hydrolysis. Hence, our research aimed at specific lignin quantification with concurrent characterization of its structural features. Hereto, for the first time, a polymeric 13 C lignin was used as internal standard (IS) for lignin quantification via analytical pyrolysis coupled to gas chromatography with mass-spectrometric detection in selected ion monitoring mode (py-GC-SIM-MS). In addition, relative response factors (RRFs) for the various pyrolysis products obtained were determined and applied. First, 12 C and 13 C lignin were isolated from nonlabeled and uniformly 13 C labeled wheat straw, respectively, and characterized by heteronuclear single quantum coherence (HSQC), nuclear magnetic resonance (NMR), and py-GC/MS. The two lignin isolates were found to have identical structures. Second, 13 C-IS based lignin quantification by py-GC-SIM-MS was validated in reconstituted biomass model systems with known contents of the 12 C lignin analogue and was shown to be extremely accurate (>99.9%, R 2 > 0.999) and precise (RSD < 1.5%). Third, 13 C-IS based lignin quantification was applied to four common poaceous biomass sources (wheat straw, barley straw, corn stover, and sugar cane bagasse), and lignin contents were in good agreement with the total gravimetrically determined lignin contents. Our robust method proves to be a promising alternative for the high-throughput quantification of lignin in milled biomass samples directly and simultaneously provides a direct insight into the structural features of lignin.

Quantification of Lignin and Its Structural Features in Plant Biomass Using 13C Lignin as Internal Standard for Pyrolysis-GC-SIM-MS

PubMed Central

2017-01-01

Understanding the mechanisms underlying plant biomass recalcitrance at the molecular level can only be achieved by accurate analyses of both the content and structural features of the molecules involved. Current quantification of lignin is, however, majorly based on unspecific gravimetric analysis after sulfuric acid hydrolysis. Hence, our research aimed at specific lignin quantification with concurrent characterization of its structural features. Hereto, for the first time, a polymeric 13C lignin was used as internal standard (IS) for lignin quantification via analytical pyrolysis coupled to gas chromatography with mass-spectrometric detection in selected ion monitoring mode (py-GC-SIM-MS). In addition, relative response factors (RRFs) for the various pyrolysis products obtained were determined and applied. First, 12C and 13C lignin were isolated from nonlabeled and uniformly 13C labeled wheat straw, respectively, and characterized by heteronuclear single quantum coherence (HSQC), nuclear magnetic resonance (NMR), and py-GC/MS. The two lignin isolates were found to have identical structures. Second, 13C-IS based lignin quantification by py-GC-SIM-MS was validated in reconstituted biomass model systems with known contents of the 12C lignin analogue and was shown to be extremely accurate (>99.9%, R2 > 0.999) and precise (RSD < 1.5%). Third, 13C-IS based lignin quantification was applied to four common poaceous biomass sources (wheat straw, barley straw, corn stover, and sugar cane bagasse), and lignin contents were in good agreement with the total gravimetrically determined lignin contents. Our robust method proves to be a promising alternative for the high-throughput quantification of lignin in milled biomass samples directly and simultaneously provides a direct insight into the structural features of lignin. PMID:28926698

Integrating prior information into microwave tomography Part 1: Impact of detail on image quality.

PubMed

Kurrant, Douglas; Baran, Anastasia; LoVetri, Joe; Fear, Elise

2017-12-01

The authors investigate the impact that incremental increases in the level of detail of patient-specific prior information have on image quality and the convergence behavior of an inversion algorithm in the context of near-field microwave breast imaging. A methodology is presented that uses image quality measures to characterize the ability of the algorithm to reconstruct both internal structures and lesions embedded in fibroglandular tissue. The approach permits key aspects that impact the quality of reconstruction of these structures to be identified and quantified. This provides insight into opportunities to improve image reconstruction performance. Patient-specific information is acquired using radar-based methods that form a regional map of the breast. This map is then incorporated into a microwave tomography algorithm. Previous investigations have demonstrated the effectiveness of this approach to improve image quality when applied to data generated with two-dimensional (2D) numerical models. The present study extends this work by generating prior information that is customized to vary the degree of structural detail to facilitate the investigation of the role of prior information in image formation. Numerical 2D breast models constructed from magnetic resonance (MR) scans, and reconstructions formed with a three-dimensional (3D) numerical breast model are used to assess if trends observed for the 2D results can be extended to 3D scenarios. For the blind reconstruction scenario (i.e., no prior information), the breast surface is not accurately identified and internal structures are not clearly resolved. A substantial improvement in image quality is achieved by incorporating the skin surface map and constraining the imaging domain to the breast. Internal features within the breast appear in the reconstructed image. However, it is challenging to discriminate between adipose and glandular regions and there are inaccuracies in both the structural properties of the glandular region and the dielectric properties reconstructed within this structure. Using a regional map with a skin layer only marginally improves this situation. Increasing the structural detail in the prior information to include internal features leads to reconstructions for which the interface that delineates the fat and gland regions can be inferred. Different features within the glandular region corresponding to tissues with varying relative permittivity values, such as a lesion embedded within glandular structure, emerge in the reconstructed images. Including knowledge of the breast surface and skin layer leads to a substantial improvement in image quality compared to the blind case, but the images have limited diagnostic utility for applications such as tumor response tracking. The diagnostic utility of the reconstruction technique is improved considerably when patient-specific structural information is used. This qualitative observation is supported quantitatively with image metrics. © 2017 American Association of Physicists in Medicine.

Cognitive Emotion Regulation Strategies in Anxiety and Depression Understood as Types of Personality.

PubMed

Domaradzka, Ewa; Fajkowska, Małgorzata

2018-01-01

The identification of distinctive and overlapping features of anxiety and depression remains an important scientific problem. Currently, the literature does not allow to determine stable similarities and differences in the use of cognitive emotion regulation strategies (CERS) in anxiety and depression, especially concerning the adaptive strategies. Consequently, the aim of this study was to identify the overlapping and distinctive patterns of CERS use in the recently proposed types of anxiety and depression in a general population. In this dimensional approach, types of anxiety and depression are considered as personality types and distinguished based on their specific structural composition and functional role (reactive or regulative) in stimulation processing. 1,632 participants from a representative sample completed the Anxiety and Depression Questionnaire (measuring the Arousal and Apprehension Types of anxiety and the Valence and Anhedonic Types of depression) and the Cognitive Emotion Regulation Questionnaire. Regression analyses were conducted with the affective types as predictors. The co-occurrence of the types was accounted for in order to examine their independent relationships with the CERS. We found that reactive arousal anxiety was not related to any strategies, while regulative apprehension anxiety primarily predicted the use of rumination, which is presumably related to the type's cognitive structural components. The strategy specific to reactive valence depression was other-blame (as predicted by the high negative affect in its structure), and the regulative, most structurally complex anhedonic depression predicted the use of the largest number of strategies, including the adaptive ones. The relationships between the types of depression and self-blame and refocus on planning were moderated by sex but the effects were small. These findings fit into the current trend of exploring the shared and specific features of anxiety and depression, which might facilitate their differentiation by identifying CERS that are characteristic for the specific types. This information can be used for supporting diagnosis and targeting selected strategies in therapy both in clinical and non-clinical populations.

Bearing diagnostics: A method based on differential geometry

NASA Astrophysics Data System (ADS)

Tian, Ye; Wang, Zili; Lu, Chen; Wang, Zhipeng

2016-12-01

The structures around bearings are complex, and the working environment is variable. These conditions cause the collected vibration signals to become nonlinear, non-stationary, and chaotic characteristics that make noise reduction, feature extraction, fault diagnosis, and health assessment significantly challenging. Thus, a set of differential geometry-based methods with superiorities in nonlinear analysis is presented in this study. For noise reduction, the Local Projection method is modified by both selecting the neighborhood radius based on empirical mode decomposition and determining noise subspace constrained by neighborhood distribution information. For feature extraction, Hessian locally linear embedding is introduced to acquire manifold features from the manifold topological structures, and singular values of eigenmatrices as well as several specific frequency amplitudes in spectrograms are extracted subsequently to reduce the complexity of the manifold features. For fault diagnosis, information geometry-based support vector machine is applied to classify the fault states. For health assessment, the manifold distance is employed to represent the health information; the Gaussian mixture model is utilized to calculate the confidence values, which directly reflect the health status. Case studies on Lorenz signals and vibration datasets of bearings demonstrate the effectiveness of the proposed methods.

[Strategy of molecular design of drugs: the unification of macro-properties and micro-structures of a molecule].

PubMed

Guo, Zong-Ru

2008-03-01

The interaction of a drug with the organism involves both the disposition of a drug by the organism and the action of a drug on the organism. The disposition of various exogenous substances, including drugs, complies with general rules. The underlying physical and chemical changes to different drugs in view of time and space, i. e. pharmacokinetics, share common characteristics, that is the tout ensemble of a molecule and its macroscopic properties convey direct effect on the pharmacokinetic behavior as the tendency and consequence of biological evolution. The action of a drug on the organism, on the other hand, implicates the physico-chemical binding of a drug molecule to the target protein, which induces pharmacological and toxicological effects. The biological reactions, no matter beneficial or adverse, are all specific and individual manifestation of the drug molecule and determined by the interactive binding between definitive atoms or groups of the drug molecule and the macromolecular target in three-dimension. Such critical atoms, groups, or fragments responsible for the interaction reflect the microscopic structures of drug molecules and are called pharmacophore. In this context, a drug molecule is presumed as an assembly of macroscopic property and microscopic structure, with the macroscopic properties determining the absorption, distribution, metabolism and elimination of drugs and the microscopic structure coining pharmacological action. The knowledge of the internal relationship between macroscopy/microscopy and PK/PD conduces to comprehension of drug action and guides molecular drug design, because this conception facilitates the identification of structural features necessary for biological response, and the determination of factors modulating the physico-chemical and pharmacokinetic properties. The factors determining macro-properties include molecular weight, solubility, charge, lipophilicity (partition), and polar surface area, etc., which are destined by molecular scaffolds and/or side chain(s) apart from pharmacophore. The features of micro-structures contributing to specific activity contain hydrogen bonding donor and acceptor, positive and negative charge centers, hydrophobic centers and centers of aromatic rings. Different combinations and spacial arrangements of these features determine the distinct activity presented. The macro-property and micro-structure are integrated into a single molecule, and are inseparable. The macro-property reflects overall contribution of atoms and groups in the micro-structure. On the other hand, structural changes aimed to adjust macroscopic property usually alter the relative position of the microscopic structure. The goal of molecular drug design is to integrate the macroscopic and microscopic factors in optimized manner. In the early stage of molecular design, both macroscopic property and microscopic structure should be considered to make pharmacodynamics, pharmacokinetics, and physico-chemical properties in optimal match. Therefore, it required the existence of structural overlapping among acceptable pharmacokinetics, visible developing potential and specific pharmacodynamics. The larger the scope of overlapping, the higher the possibility to be a drug.

A review of reagents for fluorescence microscopy of cellular compartments and structures, part I: BacMam labeling and reagents for vesicular structures.

PubMed

Dolman, Nick J; Kilgore, Jason A; Davidson, Michael W

2013-07-01

Fluorescent labeling of vesicular structures in cultured cells, particularly for live cells, can be challenging for a number of reasons. The first challenge is to identify a reagent that will be specific enough where some structures have a number of potential reagents and others very few options. The emergence of BacMam constructs has allowed more easy-to-use choices. Presented here is a discussion of BacMam constructs as well as a review of commercially-available reagents for labeling vesicular structures in cells, including endosomes, peroxisomes, lysosomes, and autophagosomes, complete with a featured reagent for each structure, recommended protocol, troubleshooting guide, and example image. © 2013 by John Wiley & Sons, Inc.

Electroactive nanoparticle directed assembly of functionalized graphene nanosheets into hierarchical structures with hybrid compositions for flexible supercapacitors

NASA Astrophysics Data System (ADS)

Choi, Bong Gill; Huh, Yun Suk; Hong, Won Hi; Erickson, David; Park, Ho Seok

2013-04-01

Hierarchical structures of hybrid materials with the controlled compositions have been shown to offer a breakthrough for energy storage and conversion. Here, we report the integrative assembly of chemically modified graphene (CMG) building blocks into hierarchical complex structures with the hybrid composition for high performance flexible pseudocapacitors. The formation mechanism of hierarchical CMG/Nafion/RuO2 (CMGNR) microspheres, which is triggered by the cooperative interplay during the in situ synthesis of RuO2 nanoparticles (NPs), was extensively investigated. In particular, the hierarchical CMGNR microspheres consisting of the aggregates of CMG/Nafion (CMGN) nanosheets and RuO2 NPs provided large surface area and facile ion accessibility to storage sites, while the interconnected nanosheets offered continuous electron pathways and mechanical integrity. The synergistic effect of CMGNR hybrids on the supercapacitor (SC) performance was derived from the hybrid composition of pseudocapacitive RuO2 NPs with the conductive CMGNs as well as from structural features. Consequently, the CMGNR-SCs showed a specific capacitance as high as 160 F g-1, three-fold higher than that of conventional graphene SCs, and a capacitance retention of >95% of the maximum value even after severe bending and 1000 charge-discharge tests due to the structural and compositional features.Hierarchical structures of hybrid materials with the controlled compositions have been shown to offer a breakthrough for energy storage and conversion. Here, we report the integrative assembly of chemically modified graphene (CMG) building blocks into hierarchical complex structures with the hybrid composition for high performance flexible pseudocapacitors. The formation mechanism of hierarchical CMG/Nafion/RuO2 (CMGNR) microspheres, which is triggered by the cooperative interplay during the in situ synthesis of RuO2 nanoparticles (NPs), was extensively investigated. In particular, the hierarchical CMGNR microspheres consisting of the aggregates of CMG/Nafion (CMGN) nanosheets and RuO2 NPs provided large surface area and facile ion accessibility to storage sites, while the interconnected nanosheets offered continuous electron pathways and mechanical integrity. The synergistic effect of CMGNR hybrids on the supercapacitor (SC) performance was derived from the hybrid composition of pseudocapacitive RuO2 NPs with the conductive CMGNs as well as from structural features. Consequently, the CMGNR-SCs showed a specific capacitance as high as 160 F g-1, three-fold higher than that of conventional graphene SCs, and a capacitance retention of >95% of the maximum value even after severe bending and 1000 charge-discharge tests due to the structural and compositional features. Electronic supplementary information (ESI) available: Electrodeposition procedure, TEM, SEM, and AFM images, XPS, FT-IR, and XRD spectra, mechanical strain-stress curve, textural and conductive properties, and impedance spectroscopy. See DOI: 10.1039/c3nr33674c

Manx Gaelic: The Manx Gaelic Language in Education in the Isle of Man. Regional Dossiers Series

ERIC Educational Resources Information Center

McArdle, Fiona, Comp.; Teare, Robert, Comp.

2016-01-01

This regional dossier aims at providing a concise description of and basic statistics on minority language education in a specific region of Europe--the Isle of Man. Aspects that are addressed include features of the education system, recent educational policies, main actors, legal arrangements, and support structures, as well as quantitative…

Motivation within Role-Playing as a Means to Intensify College Students' Educational Activity

ERIC Educational Resources Information Center

Burenkova, Olga Mikhailovna; Arkhipova, Irina Vladimirovna; Semenov, Sergei Aleksandrovich; Samarenkina, Saniya Zakirzyanovna

2015-01-01

This article covers college students' educational activity issues while studying a foreign language; analyzes special aspects of motivation introduction, their specific features. It also defines role and structure of role-playing. The authors come to the conclusion that introduction of role-playing in an educational process will bring it closer to…

Structure and Strategies in Children's Educational Television: The Roles of Program Type and Learning Strategies in Children's Learning

ERIC Educational Resources Information Center

Linebarger, Deborah L.; Piotrowski, Jessica Taylor

2010-01-01

Educational TV has been consistently linked to children's learning. In this research, educational TV characteristics were identified, coded, and tested for their influence on children's program-specific comprehension and vocabulary outcomes. Study 1 details a content analysis of TV features including a program's macrostructure (i.e., narrative or…

Memories of Morocco: The Influence of Age, Schooling, and Environment on Memory

ERIC Educational Resources Information Center

Wagner, Daniel A.

1978-01-01

The relationships of structural features of memory (e.g., short-term store) and of control processes in memory (e.g., verbal rehearsal) were compared according to age, rural-urban differences, and amount of education. Culturally-specific skills were also investigated in Moroccan rug sellers and Koranic students, and in American college students.…

Teachers' Perceptions of the Learning Environment and Their Knowledge Base in a Training Program for Novice University Teachers

ERIC Educational Resources Information Center

Johannes, Christine; Fendler, Jan; Seidel, Tina

2013-01-01

Despite the complexity of teaching, learning to teach in universities is often "learning by doing". To provide novice university teachers with pedagogic teaching knowledge and to help them develop specific teaching objectives, we created a structured, video-based, one-year training program. In focusing on the core features of…

Identifying Affordances of 3D Printed Tangible Models for Understanding Core Biological Concepts

ERIC Educational Resources Information Center

Davenport, Jodi L.; Silberglitt, Matt; Boxerman, Jonathan; Olson, Arthur

2014-01-01

3D models derived from actual molecular structures have the potential to transform student learning in biology. We share findings related to our research questions: 1) what types of interactions with a protein folding kit promote specific learning objectives?, and 2) what features of the instructional environment (e.g., peer interactions, teacher…

Long-Term Memory for Music: Infants Remember Tempo and Timbre

ERIC Educational Resources Information Center

Trainor, Laurel J.; Wu, Luann; Tsang, Christine D.

2004-01-01

We show that infants' long-term memory representations for melodies are not just reduced to the structural features of relative pitches and durations, but contain surface or performance tempo- and timbre-specific information. Using a head turn preference procedure, we found that after a one week exposure to an old English folk song, infants…

Sorbian: The Sorbian Language in Education in Germany, 2nd Edition. Regional Dossiers Series

ERIC Educational Resources Information Center

Brezan, Beate, Comp.; Nowak, Meto, Comp.

2016-01-01

This regional dossier aims to provide a concise, description and basic statistics about minority language education in a specific region of Europe. Aspects that are addressed include features of the education system, recent educational policies, main actors, legal arrangements, and support structures, as well as quantitative aspects, such as the…

North Frisian: The North Frisian Language in Education in Germany, 3rd Edition. Regional Dossiers Series

ERIC Educational Resources Information Center

Walker, Alastair G. H., Comp.

2015-01-01

This regional dossier aims to provide a concise, description and basic statistics about minority language education in a specific region of Europe. Aspects that are addressed include features of the education system, recent educational policies, main actors, legal arrangements, and support structures, as well as quantitative aspects, such as the…

Swedish: The Swedish Language in Education in Finland, 2nd Edition. Regional Dossiers Series

ERIC Educational Resources Information Center

Østern, Anna-Lena, Comp.; Harju-Luukkainen, Heidi, Comp.

2013-01-01

This regional dossier aims to provide a concise, description and basic statistics about minority language education in a specific region of Europe. Aspects that are addressed include features of the education system, recent educational policies, main actors, legal arrangements, and support structures, as well as quantitative aspects, such as the…

Ladin: The Ladin Language in Education in Italy, 2nd Edition. Regional Dossiers Series

ERIC Educational Resources Information Center

Verra, Roland, Comp.

2016-01-01

This regional dossier aims to provide a concise, description and basic statistics about minority language education in a specific region of Europe. Aspects that are addressed include features of the education system, recent educational policies, main actors, legal arrangements, and support structures, as well as quantitative aspects, such as the…

Galician: The Galician Language in Education in Spain, 2nd Edition. Regional Dossiers Series

ERIC Educational Resources Information Center

Costas, Xosé-Henrique, Comp.; Expósito-Loureiro, Andrea, Comp.

2016-01-01

This regional dossier aims to provide a concise, description and basic statistics about minority language education in a specific region of Europe. Aspects that are addressed include features of the education system, recent educational policies, main actors, legal arrangements, and support structures, as well as quantitative aspects, such as the…

Welsh: The Welsh Language in Education in the UK, 2nd Edition. Regional Dossiers Series

ERIC Educational Resources Information Center

Jones, Meirion Prys, Comp.; Jones, Ceinwen, Comp.

2014-01-01

This regional dossier aims to provide a concise, description and basic statistics about minority language education in a specific region of Europe. Aspects that are addressed include features of the education system, recent educational policies, main actors, legal arrangements, and support structures, as well as quantitative aspects, such as the…

Irish: The Irish Language in Education in the Republic of Ireland, 2nd Edition. Regional Dossiers Series

ERIC Educational Resources Information Center

Ó Murchú, Helen, Comp.

2016-01-01

This regional dossier aims to provide a concise, description and basic statistics about minority language education in a specific region of Europe. Aspects that are addressed include features of the education system, recent educational policies, main actors, legal arrangements, and support structures, as well as quantitative aspects, such as the…

Asturian: The Asturian Language in Education in Spain, 2nd Edition. Regional Dossiers Series

ERIC Educational Resources Information Center

González-Riaño, Xosé Antón, Comp.; Fernández-Costales, Alberto, Comp.

2014-01-01

This regional dossier aims to provide a concise, description and basic statistics about minority language education in a specific region of Europe. Aspects that are addressed include features of the education system, recent educational policies, main actors, legal arrangements, and support structures, as well as quantitative aspects, such as the…

High-Temperature Magnetism as a Probe for Structural and Compositional Uniformity in Ligand-Capped Magnetite Nanoparticles

PubMed Central

2015-01-01

To investigate magnetostructural relationships in colloidal magnetite (Fe3O4) nanoparticles (NPs) at high temperature (300–900 K), we measured the temperature dependence of magnetization (M) of oleate-capped magnetite NPs ca. 20 nm in size. Magnetometry revealed an unusual irreversible high-temperature dependence of M for these NPs, with dip and loop features observed during heating–cooling cycles. Detailed characterizations of as-synthesized and annealed Fe3O4 NPs as well as reference ligand-free Fe3O4 NPs indicate that both types of features in M(T) are related to thermal decomposition of the capping ligands. The ligand decomposition upon the initial heating induces a reduction of Fe3+ to Fe2+ and the associated dip in M, leading to more structurally and compositionally uniform magnetite NPs. Having lost the protective ligands, the NPs continually sinter during subsequent heating cycles, resulting in divergent M curves featuring loops. The increase in M with sintering proceeds not only through elimination of a magnetically dead layer on the particle surface, as a result of a decrease in specific surface area with increasing size, but also through an uncommonly invoked effect resulting from a significant change in Fe3+/Fe2+ ratio with heat treatment. The interpretation of irreversible features in M(T) indicates that reversible M(T) behavior, conversely, can be expected only for ligand-free, structurally and compositionally uniform magnetite NPs, suggesting a general applicability of high-temperature M(T) measurements as an analytical method for probing the structure and composition of magnetic nanomaterials. PMID:25506407

Application of complex discrete wavelet transform in classification of Doppler signals using complex-valued artificial neural network.

PubMed

Ceylan, Murat; Ceylan, Rahime; Ozbay, Yüksel; Kara, Sadik

2008-09-01

In biomedical signal classification, due to the huge amount of data, to compress the biomedical waveform data is vital. This paper presents two different structures formed using feature extraction algorithms to decrease size of feature set in training and test data. The proposed structures, named as wavelet transform-complex-valued artificial neural network (WT-CVANN) and complex wavelet transform-complex-valued artificial neural network (CWT-CVANN), use real and complex discrete wavelet transform for feature extraction. The aim of using wavelet transform is to compress data and to reduce training time of network without decreasing accuracy rate. In this study, the presented structures were applied to the problem of classification in carotid arterial Doppler ultrasound signals. Carotid arterial Doppler ultrasound signals were acquired from left carotid arteries of 38 patients and 40 healthy volunteers. The patient group included 22 males and 16 females with an established diagnosis of the early phase of atherosclerosis through coronary or aortofemoropopliteal (lower extremity) angiographies (mean age, 59 years; range, 48-72 years). Healthy volunteers were young non-smokers who seem to not bear any risk of atherosclerosis, including 28 males and 12 females (mean age, 23 years; range, 19-27 years). Sensitivity, specificity and average detection rate were calculated for comparison, after training and test phases of all structures finished. These parameters have demonstrated that training times of CVANN and real-valued artificial neural network (RVANN) were reduced using feature extraction algorithms without decreasing accuracy rate in accordance to our aim.

Psychometric modeling of abuse and dependence symptoms across six illicit substances indicates novel dimensions of misuse

PubMed Central

Clark, Shaunna L.; Gillespie, Nathan A.; Adkins, Daniel E.; Kendler, Kenneth S.; Neale, Michael C.

2015-01-01

Aims This study explored the factor structure of DSM III-R/IV symptoms for substance abuse and dependence across six illicit substance categories in a population-based sample of males. Method DSM III-R/IV drug abuse and dependence symptoms for cannabis, sedatives, stimulants, cocaine, opioids and hallucinogens from 4179 males born 1940-1970 from the population-based Virginia Adult Twin Study of Psychiatric and Substance Use Disorders were analyzed. Confirmatory factor analyses tested specific hypotheses regarding the latent structure of substance misuse for a comprehensive battery of 13 misuse symptoms measured across six illicit substance categories (78 items). Results Among the models fit, the latent structure of substance misuse was best represented by a combination of substance-specific factors and misuse symptom-specific factors. We found no support for a general liability factor to illicit substance misuse. Conclusions Results indicate that liability to misuse illicit substances is drug class specific, with little evidence for a general liability factor. Additionally, unique dimensions capturing propensity toward specific misuse symptoms (e.g., tolerance, withdrawal) across substances were identified. While this finding requires independent replication, the possibility of symptom-specific misuse factors, present in multiple substances, raises the prospect of genetic, neurobiological and behavioral predispositions toward distinct, narrowly defined features of drug abuse and dependence. PMID:26517709

Feature engineering for MEDLINE citation categorization with MeSH.

PubMed

Jimeno Yepes, Antonio Jose; Plaza, Laura; Carrillo-de-Albornoz, Jorge; Mork, James G; Aronson, Alan R

2015-04-08

Research in biomedical text categorization has mostly used the bag-of-words representation. Other more sophisticated representations of text based on syntactic, semantic and argumentative properties have been less studied. In this paper, we evaluate the impact of different text representations of biomedical texts as features for reproducing the MeSH annotations of some of the most frequent MeSH headings. In addition to unigrams and bigrams, these features include noun phrases, citation meta-data, citation structure, and semantic annotation of the citations. Traditional features like unigrams and bigrams exhibit strong performance compared to other feature sets. Little or no improvement is obtained when using meta-data or citation structure. Noun phrases are too sparse and thus have lower performance compared to more traditional features. Conceptual annotation of the texts by MetaMap shows similar performance compared to unigrams, but adding concepts from the UMLS taxonomy does not improve the performance of using only mapped concepts. The combination of all the features performs largely better than any individual feature set considered. In addition, this combination improves the performance of a state-of-the-art MeSH indexer. Concerning the machine learning algorithms, we find that those that are more resilient to class imbalance largely obtain better performance. We conclude that even though traditional features such as unigrams and bigrams have strong performance compared to other features, it is possible to combine them to effectively improve the performance of the bag-of-words representation. We have also found that the combination of the learning algorithm and feature sets has an influence in the overall performance of the system. Moreover, using learning algorithms resilient to class imbalance largely improves performance. However, when using a large set of features, consideration needs to be taken with algorithms due to the risk of over-fitting. Specific combinations of learning algorithms and features for individual MeSH headings could further increase the performance of an indexing system.

The new applications of sputtering and ion plating

NASA Technical Reports Server (NTRS)

Spalvins, T.

1977-01-01

The potential industrial applications of sputtering and ion plating are strictly governed by the unique features these methods possess. The outstanding features of each method, the resultant coating characteristics and the various sputtering modes and configurations are discussed. New, more complex coatings and deposits can be developed such as graded composition structures (metal-ceramic seals), laminated and dispersion strengthened composites which improve the mechanical properties and high temperature stability. Specific industrial areas where future effort of sputtering and ion plating will concentrate to develop intricate alloy or compound coatings and solve difficult problem areas are discussed.

Road map to adaptive optimal control. [jet engine control

NASA Technical Reports Server (NTRS)

Boyer, R.

1980-01-01

A building block control structure leading toward adaptive, optimal control for jet engines is developed. This approach simplifies the addition of new features and allows for easier checkout of the control by providing a baseline system for comparison. Also, it is possible to eliminate certain features that do not have payoff by being selective in the addition of new building blocks to be added to the baseline system. The minimum risk approach specifically addresses the need for active identification of the plant to be controlled in real time and real time optimization of the control for the identified plant.

Molecular Signatures of Tissue-Specific Microvascular Endothelial Cell Heterogeneity in Organ Maintenance and Regeneration

PubMed Central

Nolan, Daniel J.; Ginsberg, Michael; Israely, Edo; Palikuqi, Brisa; Poulos, Michael G.; James, Daylon; Ding, Bi-Sen; Schachterle, William; Liu, Ying; Rosenwaks, Zev; Butler, Jason M.; Xiang, Jenny; Rafii, Arash; Shido, Koji; Rabbany, Sina Y.; Elemento, Olivier; Rafii, Shahin

2013-01-01

SUMMARY Microvascular endothelial cells (ECs) within different tissues are endowed with distinct but as yet unrecognized structural, phenotypic, and functional attributes. We devised EC purification, cultivation, profiling, and transplantation models that establish tissue-specific molecular libraries of ECs devoid of lymphatic ECs or parenchymal cells. These libraries identify attributes that confer ECs with their organotypic features. We show that clusters of transcription factors, angiocrine growth factors, adhesion molecules, and chemokines are expressed in unique combinations by ECs of each organ. Furthermore, ECs respond distinctly in tissue regeneration models, hepatectomy, and myeloablation. To test the data set, we developed a transplantation model that employs generic ECs differentiated from embryonic stem cells. Transplanted generic ECs engraft into regenerating tissues and acquire features of organotypic ECs. Collectively, we demonstrate the utility of informational databases of ECs toward uncovering the extravascular and intrinsic signals that define EC heterogeneity. These factors could be exploited therapeutically to engineer tissue-specific ECs for regeneration. PMID:23871589

Understanding and Manipulating Electrostatic Fields at the Protein-Protein Interface Using Vibrational Spectroscopy and Continuum Electrostatics Calculations.

PubMed

Ritchie, Andrew W; Webb, Lauren J

2015-11-05

Biological function emerges in large part from the interactions of biomacromolecules in the complex and dynamic environment of the living cell. For this reason, macromolecular interactions in biological systems are now a major focus of interest throughout the biochemical and biophysical communities. The affinity and specificity of macromolecular interactions are the result of both structural and electrostatic factors. Significant advances have been made in characterizing structural features of stable protein-protein interfaces through the techniques of modern structural biology, but much less is understood about how electrostatic factors promote and stabilize specific functional macromolecular interactions over all possible choices presented to a given molecule in a crowded environment. In this Feature Article, we describe how vibrational Stark effect (VSE) spectroscopy is being applied to measure electrostatic fields at protein-protein interfaces, focusing on measurements of guanosine triphosphate (GTP)-binding proteins of the Ras superfamily binding with structurally related but functionally distinct downstream effector proteins. In VSE spectroscopy, spectral shifts of a probe oscillator's energy are related directly to that probe's local electrostatic environment. By performing this experiment repeatedly throughout a protein-protein interface, an experimental map of measured electrostatic fields generated at that interface is determined. These data can be used to rationalize selective binding of similarly structured proteins in both in vitro and in vivo environments. Furthermore, these data can be used to compare to computational predictions of electrostatic fields to explore the level of simulation detail that is necessary to accurately predict our experimental findings.

Magnetic ordering and crystal field effects in quasi-caged structure compound PrFe2Al8

NASA Astrophysics Data System (ADS)

Nair, Harikrishnan S.; Ghosh, Sarit K.; Ramesh Kumar, K.; Strydom, André M.

2016-04-01

The compound PrFe2Al8 possesses a three-dimensional network structure resulting from the packing of Al polyhedra centered at the transition metal element Fe and the rare earth Pr. Along the c-axis, Fe and Pr form chains which are separated from each other by the Al-network. In this paper, the magnetism and crystalline electric field effects in PrFe2Al8 are investigated through the analysis of magnetization and specific heat data. A magnetic phase transition in the Pr lattice is identified at TNPr ≈ 4 K in dc magnetization and ac susceptibility data. At 2 K, the magnetization isotherm presents a ferromagnetic saturation, however, failing to reach full spin-only ferromagnetic moment of Pr3+. Metamagnetic step-like low-field features are present in the magnetization curve at 2 K which is shown to shift upon field-cooling the material. Arrott plots centered around TPrN display "S"-like features suggestive of an inhomogeneous magnetic state. The magnetic entropy, Sm, estimated from specific heat outputs a value of R ln(2) at TN2 suggesting a doublet state for Pr3+. The magnetic specific heat is modeled by using a 9-level Schottky equation pertinent to the Pr3+ ion with J=4. Given the crystalline electric field situation of Pr3+, the inference of a doublet state from specific heat and consequent long-range magnetic order is an unexpected result.

Bimodal pair f-KdV dynamics in star-forming clouds

NASA Astrophysics Data System (ADS)

Karmakar, Pralay Kumar; Haloi, Archana; Roy, Supriya

2018-04-01

A theoretical formalism for investigating the bimodal conjugational mode dynamics of hybrid source, dictated by a unique pair of forced Korteweg-de Vries (f-KdV) equations in a complex turbo-magnetized star-forming cloud, is reported. It uses a standard multi-scale analysis executed over the cloud-governing equations in a closure form to derive the conjugated pair f-KdV system. We numerically see the structural features of two distinctive classes of eigenmode patterns stemming from the conjoint gravito-electrostatic interplay. The electrostatic compressive monotonic aperiodic shock-like patterns and gravitational compressive non-monotonic oscillatory shock-like structures are excitable. It is specifically revealed that the constitutive grain-charge (grain-mass) acts as electrostatic stabilizer (gravitational destabilizer) against the global cloud collapse dynamics. The basic features of the nonlinear coherent structures are confirmed in systematic phase-plane landscapes, indicating electrostatic irregular non-homoclinic open trajectories and gravitational atypical non-chaotic homoclinic fixed-point attractors. The relevance in the real astro-cosmic scenarios of the early phases of structure formation via wave-driven fluid-accretive transport processes is summarily emphasized.

Classification of document page images based on visual similarity of layout structures

NASA Astrophysics Data System (ADS)

Shin, Christian K.; Doermann, David S.

1999-12-01

Searching for documents by their type or genre is a natural way to enhance the effectiveness of document retrieval. The layout of a document contains a significant amount of information that can be used to classify a document's type in the absence of domain specific models. A document type or genre can be defined by the user based primarily on layout structure. Our classification approach is based on 'visual similarity' of the layout structure by building a supervised classifier, given examples of the class. We use image features, such as the percentages of tex and non-text (graphics, image, table, and ruling) content regions, column structures, variations in the point size of fonts, the density of content area, and various statistics on features of connected components which can be derived from class samples without class knowledge. In order to obtain class labels for training samples, we conducted a user relevance test where subjects ranked UW-I document images with respect to the 12 representative images. We implemented our classification scheme using the OC1, a decision tree classifier, and report our findings.

Final Report Grant No. DE-FG02-98ER20307 Lipopolysaccharide Structures and Genes Required for Root Nodule Development August 1, 2004 to July 31, 2008

DOE Office of Scientific and Technical Information (OSTI.GOV)

Noel, K. Dale

This project dealt with the plant-bacterial symbiosis that gives rise to root nodules on leguminous plants in which the bacteria carry out nitrogen fixation. Nitrogen fixation, like carbon dioxide fixation, is essential for life on planet earth, and this symbiosis is estimated to account for half of all nitrogen fixed on land. Aside from being important for the sustenance of global life, this ability allows legumes to grow without nitrogen fertilizers. Basic studies such as this project are aimed at understanding the symbiosis well enough that eventually it can be engineered into important crop species so that they no longermore » depend on nitrogen fertilizer for growth. The production and distribution of excessive fertilizer needed for optimal crop yields is responsible for a significant portion of the energy costs in agriculture. The specific aims of this work were to further the understanding of a bacterial factor that is essential for the symbiotic infection process. This factor is a bacterial surface molecule, lipopolysaccharide O antigen. In this project we showed that, not only the presence, but the specific structure of this molecule is crucial for infection. Although the success of bacterial infections in many pathogenic and mutualistic interactions have been shown to depend on intact O antigen, it has been very rare to establish that specific features of the structure are important. One of the features in this case is the presence of one additional methyl group on one sugar in the O antigen. It is very surprising that such a minor change should have an observable effect. This work sets the stage for biochemical studies of possible plant receptors that may be involved. During the course of this grant period, we developed a method of testing the importance of this bacterial component at stages of nodule development beyond the step that is blocked by null mutation. The method works adequately for this purpose and is being improved. It has implications for testing the roles of other important bacterial factors at multiple stages of nodule development. The project also investigated the biosynthesis of this bacterial factor. It has a complex structure and the first accomplishment was the determination of the sequences of genetic regions known to be important. Next the discovered genes were mutated to identify the 26 that are required for its synthesis. In addition, six others were discovered that are believed to change its structure under various environmental conditions. By studying mutants affected in specific genes, genes were associated with each of the predicted steps in the biosynthesis. Current work is testing the predicted biosynthetic model with studies conducted in vitro with bacterial extracts. Overall, the work funded by this grant establishes this system as a model for host-bacterial interactions based on specific polysaccharide structure. All areas that are needed for a comprehensive model have been significantly advanced: the biological function, the structural features that are crucial, the complete set of bacterial genes involved, and a model for the biosynthesis.« less

Ultra high molecular weight polyethylene: Optical features at millimeter wavelengths

NASA Astrophysics Data System (ADS)

D'Alessandro, G.; Paiella, A.; Coppolecchia, A.; Castellano, M. G.; Colantoni, I.; de Bernardis, P.; Lamagna, L.; Masi, S.

2018-05-01

The next generation of experiments for the measurement of the Cosmic Microwave Background (CMB) requires more and more the use of advanced materials, with specific physical and structural properties. An example is the material used for receiver's cryostat windows and internal lenses. The large throughput of current CMB experiments requires a large diameter (of the order of 0.5 m) of these parts, resulting in heavy structural and optical requirements on the material to be used. Ultra High Molecular Weight (UHMW) polyethylene (PE) features high resistance to traction and good transmissivity in the frequency range of interest. In this paper, we discuss the possibility of using UHMW PE for windows and lenses in experiments working at millimeter wavelengths, by measuring its optical properties: emissivity, transmission and refraction index. Our measurements show that the material is well suited to this purpose.

A study of nitrogen incorporation in pyramidal site-controlled quantum dots

PubMed Central

2011-01-01

We present the results of a study of nitrogen incorporation in metalorganic-vapour-phase epitaxy-grown site-controlled quantum dots (QDs). We report for the first time on a significant incorporation (approximately 0.3%), producing a noteworthy red shift (at least 50 meV) in some of our samples. Depending on the level of nitrogen incorporation/exposure, strong modifications of the optical features are found (variable distribution of the emission homogeneity, fine-structure splitting, few-particle effects). We discuss our results, especially in relation to a specific reproducible sample which has noticeable features: the usual pattern of the excitonic transitions is altered and the fine-structure splitting is suppressed to vanishing values. Distinctively, nitrogen incorporation can be achieved without detriment to the optical quality, as confirmed by narrow linewidths and photon correlation spectroscopy. PMID:22029752

REPDOSE: A database on repeated dose toxicity studies of commercial chemicals--A multifunctional tool.

PubMed

Bitsch, A; Jacobi, S; Melber, C; Wahnschaffe, U; Simetska, N; Mangelsdorf, I

2006-12-01

A database for repeated dose toxicity data has been developed. Studies were selected by data quality. Review documents or risk assessments were used to get a pre-screened selection of available valid data. The structure of the chemicals should be rather simple for well defined chemical categories. The database consists of three core data sets for each chemical: (1) structural features and physico-chemical data, (2) data on study design, (3) study results. To allow consistent queries, a high degree of standardization categories and glossaries were developed for relevant parameters. At present, the database consists of 364 chemicals investigated in 1018 studies which resulted in a total of 6002 specific effects. Standard queries have been developed, which allow analyzing the influence of structural features or PC data on LOELs, target organs and effects. Furthermore, it can be used as an expert system. First queries have shown that the database is a very valuable tool.

A wirelessly programmable actuation and sensing system for structural health monitoring

NASA Astrophysics Data System (ADS)

Long, James; Büyüköztürk, Oral

2016-04-01

Wireless sensor networks promise to deliver low cost, low power and massively distributed systems for structural health monitoring. A key component of these systems, particularly when sampling rates are high, is the capability to process data within the network. Although progress has been made towards this vision, it remains a difficult task to develop and program 'smart' wireless sensing applications. In this paper we present a system which allows data acquisition and computational tasks to be specified in Python, a high level programming language, and executed within the sensor network. Key features of this system include the ability to execute custom application code without firmware updates, to run multiple users' requests concurrently and to conserve power through adjustable sleep settings. Specific examples of sensor node tasks are given to demonstrate the features of this system in the context of structural health monitoring. The system comprises of individual firmware for nodes in the wireless sensor network, and a gateway server and web application through which users can remotely submit their requests.

The impact of the structural features of the rock mass on seismicity in Polish coal mines

NASA Astrophysics Data System (ADS)

Patyńska, Renata

2017-11-01

The article presents seismic activity induced in the coal mines of the Upper Silesian Coal Basin (GZW) in relation to the locations of the occurrence of rockbursts. The comparison of these measurements with the structural features of the rock mass of coal mines indicates the possibility of estimating the so-called Unitary Energy Expenditure (UEE) in a specific time. The obtained values of UEE were compared with the distribution of seismic activity in GZW mines. The level of seismic activity in the analysed period changed and depended on the intensity of mining works and diverse mining and geological conditions. Five regions, where tremors occurred (Bytom Trough, Main Saddle, Main Trough, Kazimierz Trough, and Jejkowice and Chwałowice Trough) which belong to various structural units of the Upper Silesia were analyzed. It was found out that rock bursts were recorded only in three regions: Main Saddle, Bytom Trough, and Jejkowice and Chwałowice Trough.

Sequence, Structure, and Context Preferences of Human RNA Binding Proteins.

PubMed

Dominguez, Daniel; Freese, Peter; Alexis, Maria S; Su, Amanda; Hochman, Myles; Palden, Tsultrim; Bazile, Cassandra; Lambert, Nicole J; Van Nostrand, Eric L; Pratt, Gabriel A; Yeo, Gene W; Graveley, Brenton R; Burge, Christopher B

2018-06-07

RNA binding proteins (RBPs) orchestrate the production, processing, and function of mRNAs. Here, we present the affinity landscapes of 78 human RBPs using an unbiased assay that determines the sequence, structure, and context preferences of these proteins in vitro by deep sequencing of bound RNAs. These data enable construction of "RNA maps" of RBP activity without requiring crosslinking-based assays. We found an unexpectedly low diversity of RNA motifs, implying frequent convergence of binding specificity toward a relatively small set of RNA motifs, many with low compositional complexity. Offsetting this trend, however, we observed extensive preferences for contextual features distinct from short linear RNA motifs, including spaced "bipartite" motifs, biased flanking nucleotide composition, and bias away from or toward RNA structure. Our results emphasize the importance of contextual features in RNA recognition, which likely enable targeting of distinct subsets of transcripts by different RBPs that recognize the same linear motif. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Spermatological characters of the pseudophyllidean cestode Bothriocephalus scorpii (Müller, 1776).

PubMed

Levron, Céline; Brunanská, Magdaléna; Poddubnaya, Larisa G

2006-06-01

Spermiogenesis of Bothriocephalus scorpii (Cestoda, Pseudophyllidea) includes an orthogonal development of two flagella, followed by a flagellar rotation and a proximo-distal fusion with the median cytoplasmic process. The fusion occurs at the level of four attachment zones. The presence of dense material in the apical region of the differentiation zone in the early stage of spermiogenesis appears to be a characteristic feature for the Pseudophyllidea. The mature spermatozoon possesses two axonemes of 9+"1" pattern of the Trepaxonemata, nucleus, cortical microtubules, electron-dense granules and crested body. The anterior part of the gamete exhibits a centriole surrounded by electron-dense tubular structures arranged as incomplete spiral. When the crested body disappears, the electron-dense tubular structures are arranged into a ring encircling the axoneme. The electron-dense tubular structures and their arrangement appear to be a specific feature for the clade "Bothriocephalidea". The organization of the posterior extremity of the gamete with the nucleus is described for the first time in the Pseudophyllidea.

Comparative analyses of structural features and scaffold diversity for purchasable compound libraries.

PubMed

Shang, Jun; Sun, Huiyong; Liu, Hui; Chen, Fu; Tian, Sheng; Pan, Peichen; Li, Dan; Kong, Dexin; Hou, Tingjun

2017-04-21

Large purchasable screening libraries of small molecules afforded by commercial vendors are indispensable sources for virtual screening (VS). Selecting an optimal screening library for a specific VS campaign is quite important to improve the success rates and avoid wasting resources in later experimental phases. Analysis of the structural features and molecular diversity for different screening libraries can provide valuable information to the decision making process when selecting screening libraries for VS. In this study, the structural features and scaffold diversity of eleven purchasable screening libraries and Traditional Chinese Medicine Compound Database (TCMCD) were analyzed and compared. Their scaffold diversity represented by the Murcko frameworks and Level 1 scaffolds was characterized by the scaffold counts and cumulative scaffold frequency plots, and visualized by Tree Maps and SAR Maps. The analysis demonstrates that, based on the standardized subsets with similar molecular weight distributions, Chembridge, ChemicalBlock, Mucle, TCMCD and VitasM are more structurally diverse than the others. Compared with all purchasable screening libraries, TCMCD has the highest structural complexity indeed but more conservative molecular scaffolds. Moreover, we found that some representative scaffolds were important components of drug candidates against different drug targets, such as kinases and guanosine-binding protein coupled receptors, and therefore the molecules containing pharmacologically important scaffolds found in screening libraries might be potential inhibitors against the relevant targets. This study may provide valuable perspective on which purchasable compound libraries are better for you to screen. Graphical abstract Selecting diverse compound libraries with scaffold analyses.

Identification of DNA-Binding Proteins Using Structural, Electrostatic and Evolutionary Features

PubMed Central

Nimrod, Guy; Szilágyi, András; Leslie, Christina; Ben-Tal, Nir

2009-01-01

Summary DNA binding proteins (DBPs) often take part in various crucial processes of the cell's life cycle. Therefore, the identification and characterization of these proteins are of great importance. We present here a random forests classifier for identifying DBPs among proteins with known three-dimensional structures. First, clusters of evolutionarily conserved regions (patches) on the protein's surface are detected using the PatchFinder algorithm; previous studies showed that these regions are typically the proteins' functionally important regions. Next, we train a classifier using features like the electrostatic potential, cluster-based amino acid conservation patterns and the secondary structure content of the patches, as well as features of the whole protein including its dipole moment. Using 10-fold cross validation on a dataset of 138 DNA-binding proteins and 110 proteins which do not bind DNA, the classifier achieved a sensitivity and a specificity of 0.90, which is overall better than the performance of previously published methods. Furthermore, when we tested 5 different methods on 11 new DBPs which did not appear in the original dataset, only our method annotated all correctly. The resulting classifier was applied to a collection of 757 proteins of known structure and unknown function. Of these proteins, 218 were predicted to bind DNA, and we anticipate that some of them interact with DNA using new structural motifs. The use of complementary computational tools supports the notion that at least some of them do bind DNA. PMID:19233205

Identification of DNA-binding proteins using structural, electrostatic and evolutionary features.

PubMed

Nimrod, Guy; Szilágyi, András; Leslie, Christina; Ben-Tal, Nir

2009-04-10

DNA-binding proteins (DBPs) participate in various crucial processes in the life-cycle of the cells, and the identification and characterization of these proteins is of great importance. We present here a random forests classifier for identifying DBPs among proteins with known 3D structures. First, clusters of evolutionarily conserved regions (patches) on the surface of proteins were detected using the PatchFinder algorithm; earlier studies showed that these regions are typically the functionally important regions of proteins. Next, we trained a classifier using features like the electrostatic potential, cluster-based amino acid conservation patterns and the secondary structure content of the patches, as well as features of the whole protein, including its dipole moment. Using 10-fold cross-validation on a dataset of 138 DBPs and 110 proteins that do not bind DNA, the classifier achieved a sensitivity and a specificity of 0.90, which is overall better than the performance of published methods. Furthermore, when we tested five different methods on 11 new DBPs that did not appear in the original dataset, only our method annotated all correctly. The resulting classifier was applied to a collection of 757 proteins of known structure and unknown function. Of these proteins, 218 were predicted to bind DNA, and we anticipate that some of them interact with DNA using new structural motifs. The use of complementary computational tools supports the notion that at least some of them do bind DNA.

Structural and biochemical insights into 7β-hydroxysteroid dehydrogenase stereoselectivity.

PubMed

Savino, Simone; Ferrandi, Erica Elisa; Forneris, Federico; Rovida, Stefano; Riva, Sergio; Monti, Daniela; Mattevi, Andrea

2016-06-01

Hydroxysteroid dehydrogenases are of great interest as biocatalysts for transformations involving steroid substrates. They feature a high degree of stereo- and regio-selectivity, acting on a defined atom with a specific configuration of the steroid nucleus. The crystal structure of 7β-hydroxysteroid dehydrogenase from Collinsella aerofaciens reveals a loop gating active-site accessibility, the bases of the specificity for NADP(+) , and the general architecture of the steroid binding site. Comparison with 7α-hydroxysteroid dehydrogenase provides a rationale for the opposite stereoselectivity. The presence of a C-terminal extension reshapes the substrate site of the β-selective enzyme, possibly leading to an inverted orientation of the bound substrate. Proteins 2016; 84:859-865. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Protein–Mineral Interactions: Molecular Dynamics Simulations Capture Importance of Variations in Mineral Surface Composition and Structure

DOE Office of Scientific and Technical Information (OSTI.GOV)

Andersen, Amity; Reardon, Patrick N.; Chacon, Stephany S.

Molecular dynamics simulations, conventional and metadynamics, were performed to determine the interaction of model protein Gb1 over kaolinite (001), Na+-montmorillonite (001), Ca2+-montmorillonite (001), goethite (100), and Na+-birnessite (001) mineral surfaces. Gb1, a small (56 residue) protein with a well-characterized solution-state nuclear magnetic resonance (NMR) structure and having α-helix, four-fold β-sheet, and hydrophobic core features, is used as a model protein to study protein soil mineral interactions and gain insights on structural changes and potential degradation of protein. From our simulations, we observe little change to the hydrated Gb1 structure over the kaolinite, montmorillonite, and goethite surfaces relative to its solvatedmore » structure without these mineral surfaces present. Over the Na+-birnessite basal surface, however, the Gb1 structure is highly disturbed as a result of interaction with this birnessite surface. Unraveling of the Gb1 β-sheet at specific turns and a partial unraveling of the α-helix is observed over birnessite, which suggests specific vulnerable residue sites for oxidation or hydrolysis possibly leading to fragmentation.« less

Conjunction of Conducting Polymer Nanostructures with Macroporous Structured Graphene Thin Films for High-Performance Flexible Supercapacitors.

PubMed

Memon, Mushtaque A; Bai, Wei; Sun, Jinhua; Imran, Muhammad; Phulpoto, Shah Nawaz; Yan, Shouke; Huang, Yong; Geng, Jianxin

2016-05-11

Fabrication of hybridized structures is an effective strategy to promote the performances of graphene-based composites for energy storage/conversion applications. In this work, macroporous structured graphene thin films (MGTFs) are fabricated on various substrates including flexible graphene papers (GPs) through an ice-crystal-induced phase separation process. The MGTFs prepared on GPs (MGTF@GPs) are recognized with remarkable features such as interconnected macroporous configuration, sufficient exfoliation of the conductive RGO sheets, and good mechanical flexibility. As such, the flexible MGTF@GPs are demonstrated as a versatile conductive platform for depositing conducting polymers (CPs), e.g., polyaniline (PAn), polypyrrole, and polythiophene, through in situ electropolymerization. The contents of the CPs in the composite films are readily controlled by varying the electropolymerization time. Notably, electrodeposition of PAn leads to the formation of nanostructures of PAn nanofibers on the walls of the macroporous structured RGO framework (PAn@MGTF@GPs): thereafter, the PAn@MGTF@GPs display a unique structural feature that combine the nanostructures of PAn nanofibers and the macroporous structures of RGO sheets. Being used as binder-free electrodes for flexible supercapacitors, the PAn@MGTF@GPs exhibit excellent electrochemical performance, in particular a high areal specific capacity (538 mF cm(-2)), high cycling stability, and remarkable capacitive stability to deformation, due to the unique electrode structures.

Abstract Profiles of Structural Stability Point to Universal Tendencies, Family-Specific Factors, and Ancient Connections between Languages

PubMed Central

Dediu, Dan; Levinson, Stephen C.

2012-01-01

Language is the best example of a cultural evolutionary system, able to retain a phylogenetic signal over many thousands of years. The temporal stability (conservatism) of basic vocabulary is relatively well understood, but the stability of the structural properties of language (phonology, morphology, syntax) is still unclear. Here we report an extensive Bayesian phylogenetic investigation of the structural stability of numerous features across many language families and we introduce a novel method for analyzing the relationships between the “stability profiles” of language families. We found that there is a strong universal component across language families, suggesting the existence of universal linguistic, cognitive and genetic constraints. Against this background, however, each language family has a distinct stability profile, and these profiles cluster by geographic area and likely deep genealogical relationships. These stability profiles seem to show, for example, the ancient historical relationships between the Siberian and American language families, presumed to be separated by at least 12,000 years, and possible connections between the Eurasian families. We also found preliminary support for the punctuated evolution of structural features of language across families, types of features and geographic areas. Thus, such higher-level properties of language seen as an evolutionary system might allow the investigation of ancient connections between languages and shed light on the peopling of the world. PMID:23028843

Abstract profiles of structural stability point to universal tendencies, family-specific factors, and ancient connections between languages.

PubMed

Dediu, Dan; Levinson, Stephen C

2012-01-01

Language is the best example of a cultural evolutionary system, able to retain a phylogenetic signal over many thousands of years. The temporal stability (conservatism) of basic vocabulary is relatively well understood, but the stability of the structural properties of language (phonology, morphology, syntax) is still unclear. Here we report an extensive Bayesian phylogenetic investigation of the structural stability of numerous features across many language families and we introduce a novel method for analyzing the relationships between the "stability profiles" of language families. We found that there is a strong universal component across language families, suggesting the existence of universal linguistic, cognitive and genetic constraints. Against this background, however, each language family has a distinct stability profile, and these profiles cluster by geographic area and likely deep genealogical relationships. These stability profiles seem to show, for example, the ancient historical relationships between the Siberian and American language families, presumed to be separated by at least 12,000 years, and possible connections between the Eurasian families. We also found preliminary support for the punctuated evolution of structural features of language across families, types of features and geographic areas. Thus, such higher-level properties of language seen as an evolutionary system might allow the investigation of ancient connections between languages and shed light on the peopling of the world.

Detection of communities with Naming Game-based methods

PubMed Central

Ribeiro, Carlos Henrique Costa

2017-01-01

Complex networks are often organized in groups or communities of agents that share the same features and/or functions, and this structural organization is built naturally with the formation of the system. In social networks, we argue that the dynamic of linguistic interactions of agreement among people can be a crucial factor in generating this community structure, given that sharing opinions with another person bounds them together, and disagreeing constantly would probably weaken the relationship. We present here a computational model of opinion exchange that uncovers the community structure of a network. Our aim is not to present a new community detection method proper, but to show how a model of social communication dynamics can reveal the (simple and overlapping) community structure in an emergent way. Our model is based on a standard Naming Game, but takes into consideration three social features: trust, uncertainty and opinion preference, that are built over time as agents communicate among themselves. We show that the separate addition of each social feature in the Naming Game results in gradual improvements with respect to community detection. In addition, the resulting uncertainty and trust values classify nodes and edges according to role and position in the network. Also, our model has shown a degree of accuracy both for non-overlapping and overlapping communities that are comparable with most algorithms specifically designed for topological community detection. PMID:28797097

Prediction of Protein Modification Sites of Pyrrolidone Carboxylic Acid Using mRMR Feature Selection and Analysis

PubMed Central

Zheng, Lu-Lu; Niu, Shen; Hao, Pei; Feng, KaiYan; Cai, Yu-Dong; Li, Yixue

2011-01-01

Pyrrolidone carboxylic acid (PCA) is formed during a common post-translational modification (PTM) of extracellular and multi-pass membrane proteins. In this study, we developed a new predictor to predict the modification sites of PCA based on maximum relevance minimum redundancy (mRMR) and incremental feature selection (IFS). We incorporated 727 features that belonged to 7 kinds of protein properties to predict the modification sites, including sequence conservation, residual disorder, amino acid factor, secondary structure and solvent accessibility, gain/loss of amino acid during evolution, propensity of amino acid to be conserved at protein-protein interface and protein surface, and deviation of side chain carbon atom number. Among these 727 features, 244 features were selected by mRMR and IFS as the optimized features for the prediction, with which the prediction model achieved a maximum of MCC of 0.7812. Feature analysis showed that all feature types contributed to the modification process. Further site-specific feature analysis showed that the features derived from PCA's surrounding sites contributed more to the determination of PCA sites than other sites. The detailed feature analysis in this paper might provide important clues for understanding the mechanism of the PCA formation and guide relevant experimental validations. PMID:22174779

Paralog-Specific Patterns of Structural Disorder and Phosphorylation in the Vertebrate SH3-SH2-Tyrosine Kinase Protein Family.

PubMed

Dos Santos, Helena G; Siltberg-Liberles, Jessica

2016-09-19

One of the largest multigene families in Metazoa are the tyrosine kinases (TKs). These are important multifunctional proteins that have evolved as dynamic switches that perform tyrosine phosphorylation and other noncatalytic activities regulated by various allosteric mechanisms. TKs interact with each other and with other molecules, ultimately activating and inhibiting different signaling pathways. TKs are implicated in cancer and almost 30 FDA-approved TK inhibitors are available. However, specific binding is a challenge when targeting an active site that has been conserved in multiple protein paralogs for millions of years. A cassette domain (CD) containing SH3-SH2-Tyrosine Kinase domains reoccurs in vertebrate nonreceptor TKs. Although part of the CD function is shared between TKs, it also presents TK specific features. Here, the evolutionary dynamics of sequence, structure, and phosphorylation across the CD in 17 TK paralogs have been investigated in a large-scale study. We establish that TKs often have ortholog-specific structural disorder and phosphorylation patterns, while secondary structure elements, as expected, are highly conserved. Further, domain-specific differences are at play. Notably, we found the catalytic domain to fluctuate more in certain secondary structure elements than the regulatory domains. By elucidating how different properties evolve after gene duplications and which properties are specifically conserved within orthologs, the mechanistic understanding of protein evolution is enriched and regions supposedly critical for functional divergence across paralogs are highlighted. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Spectra-structure correlations of saturated and unsaturated medium-chain fatty acids. Near-infrared and anharmonic DFT study of hexanoic acid and sorbic acid

NASA Astrophysics Data System (ADS)

Grabska, Justyna; Beć, Krzysztof B.; Ishigaki, Mika; Wójcik, Marek J.; Ozaki, Yukihiro

2017-10-01

Quantum chemical reproduction of entire NIR spectra is a new trend, enabled by contemporary advances in the anharmonic approaches. At the same time, recent increase of the importance of NIR spectroscopy of biological samples raises high demand for gaining deeper understanding of NIR spectra of biomolecules, i.e. fatty acids. In this work we investigate saturated and unsaturated medium-chain fatty acids, hexanoic acid and sorbic acid, in the near-infrared region. By employing fully anharmonic density functional theory (DFT) calculations we reproduce the experimental NIR spectra of these systems, including the highly specific spectral features corresponding to the dimerization of fatty acids. Broad range of concentration levels from 5 · 10- 4 M in CCl4 to pure samples are investigated. The major role of cyclic dimers can be evidenced for the vast majority of these samples. A highly specific NIR feature of fatty acids, the elevation of spectral baseline around 6500-4000 cm- 1, is being explained by the contributions of combination bands resulting from the vibrations of hydrogen-bonded OH groups in the cyclic dimers. Based on the high agreement between the calculated and experimental NIR spectra, a detailed NIR band assignments are proposed for hexanoic acid and sorbic acid. Subsequently, the correlations between the structure and NIR spectra are elucidated, emphasizing the regions in which clear and universal traces of specific bands corresponding to saturated and unsaturated alkyl chains can be established, thus demonstrating the wavenumber regions highly valuable for structural identifications.

Spectra-structure correlations of saturated and unsaturated medium-chain fatty acids. Near-infrared and anharmonic DFT study of hexanoic acid and sorbic acid.

PubMed

Grabska, Justyna; Beć, Krzysztof B; Ishigaki, Mika; Wójcik, Marek J; Ozaki, Yukihiro

2017-10-05

Quantum chemical reproduction of entire NIR spectra is a new trend, enabled by contemporary advances in the anharmonic approaches. At the same time, recent increase of the importance of NIR spectroscopy of biological samples raises high demand for gaining deeper understanding of NIR spectra of biomolecules, i.e. fatty acids. In this work we investigate saturated and unsaturated medium-chain fatty acids, hexanoic acid and sorbic acid, in the near-infrared region. By employing fully anharmonic density functional theory (DFT) calculations we reproduce the experimental NIR spectra of these systems, including the highly specific spectral features corresponding to the dimerization of fatty acids. Broad range of concentration levels from 5·10 -4 M in CCl 4 to pure samples are investigated. The major role of cyclic dimers can be evidenced for the vast majority of these samples. A highly specific NIR feature of fatty acids, the elevation of spectral baseline around 6500-4000cm -1 , is being explained by the contributions of combination bands resulting from the vibrations of hydrogen-bonded OH groups in the cyclic dimers. Based on the high agreement between the calculated and experimental NIR spectra, a detailed NIR band assignments are proposed for hexanoic acid and sorbic acid. Subsequently, the correlations between the structure and NIR spectra are elucidated, emphasizing the regions in which clear and universal traces of specific bands corresponding to saturated and unsaturated alkyl chains can be established, thus demonstrating the wavenumber regions highly valuable for structural identifications. Copyright © 2017 Elsevier B.V. All rights reserved.

Common and Distant Structural Characteristics of Feruloyl Esterase Families from Aspergillus oryzae

PubMed Central

Udatha, D. B. R. K. Gupta; Mapelli, Valeria; Panagiotou, Gianni; Olsson, Lisbeth

2012-01-01

Background Feruloyl esterases (FAEs) are important biomass degrading accessory enzymes due to their capability of cleaving the ester links between hemicellulose and pectin to aromatic compounds of lignin, thus enhancing the accessibility of plant tissues to cellulolytic and hemicellulolytic enzymes. FAEs have gained increased attention in the area of biocatalytic transformations for the synthesis of value added compounds with medicinal and nutritional applications. Following the increasing attention on these enzymes, a novel descriptor based classification system has been proposed for FAEs resulting into 12 distinct families and pharmacophore models for three FAE sub-families have been developed. Methodology/Principal Findings The feruloylome of Aspergillus oryzae contains 13 predicted FAEs belonging to six sub-families based on our recently developed descriptor-based classification system. The three-dimensional structures of the 13 FAEs were modeled for structural analysis of the feruloylome. The three genes coding for three enzymes, viz., A.O.2, A.O.8 and A.O.10 from the feruloylome of A. oryzae, representing sub-families with unknown functional features, were heterologously expressed in Pichia pastoris, characterized for substrate specificity and structural characterization through CD spectroscopy. Common feature-based pharamacophore models were developed according to substrate specificity characteristics of the three enzymes. The active site residues were identified for the three expressed FAEs by determining the titration curves of amino acid residues as a function of the pH by applying molecular simulations. Conclusions/Significance Our findings on the structure-function relationships and substrate specificity of the FAEs of A. oryzae will be instrumental for further understanding of the FAE families in the novel classification system. The developed pharmacophore models could be applied for virtual screening of compound databases for short listing the putative substrates prior to docking studies or for post-processing docking results to remove false positives. Our study exemplifies how computational predictions can complement to the information obtained through experimental methods. PMID:22745763

Common and distant structural characteristics of feruloyl esterase families from Aspergillus oryzae.

PubMed

Udatha, D B R K Gupta; Mapelli, Valeria; Panagiotou, Gianni; Olsson, Lisbeth

2012-01-01

Feruloyl esterases (FAEs) are important biomass degrading accessory enzymes due to their capability of cleaving the ester links between hemicellulose and pectin to aromatic compounds of lignin, thus enhancing the accessibility of plant tissues to cellulolytic and hemicellulolytic enzymes. FAEs have gained increased attention in the area of biocatalytic transformations for the synthesis of value added compounds with medicinal and nutritional applications. Following the increasing attention on these enzymes, a novel descriptor based classification system has been proposed for FAEs resulting into 12 distinct families and pharmacophore models for three FAE sub-families have been developed. The feruloylome of Aspergillus oryzae contains 13 predicted FAEs belonging to six sub-families based on our recently developed descriptor-based classification system. The three-dimensional structures of the 13 FAEs were modeled for structural analysis of the feruloylome. The three genes coding for three enzymes, viz., A.O.2, A.O.8 and A.O.10 from the feruloylome of A. oryzae, representing sub-families with unknown functional features, were heterologously expressed in Pichia pastoris, characterized for substrate specificity and structural characterization through CD spectroscopy. Common feature-based pharamacophore models were developed according to substrate specificity characteristics of the three enzymes. The active site residues were identified for the three expressed FAEs by determining the titration curves of amino acid residues as a function of the pH by applying molecular simulations. Our findings on the structure-function relationships and substrate specificity of the FAEs of A. oryzae will be instrumental for further understanding of the FAE families in the novel classification system. The developed pharmacophore models could be applied for virtual screening of compound databases for short listing the putative substrates prior to docking studies or for post-processing docking results to remove false positives. Our study exemplifies how computational predictions can complement to the information obtained through experimental methods.

Conservation of the Human Integrin-Type Beta-Propeller Domain in Bacteria

PubMed Central

Chouhan, Bhanupratap; Denesyuk, Alexander; Heino, Jyrki; Johnson, Mark S.; Denessiouk, Konstantin

2011-01-01

Integrins are heterodimeric cell-surface receptors with key functions in cell-cell and cell-matrix adhesion. Integrin α and β subunits are present throughout the metazoans, but it is unclear whether the subunits predate the origin of multicellular organisms. Several component domains have been detected in bacteria, one of which, a specific 7-bladed β-propeller domain, is a unique feature of the integrin α subunits. Here, we describe a structure-derived motif, which incorporates key features of each blade from the X-ray structures of human αIIbβ3 and αVβ3, includes elements of the FG-GAP/Cage and Ca2+-binding motifs, and is specific only for the metazoan integrin domains. Separately, we searched for the metazoan integrin type β-propeller domains among all available sequences from bacteria and unicellular eukaryotic organisms, which must incorporate seven repeats, corresponding to the seven blades of the β-propeller domain, and so that the newly found structure-derived motif would exist in every repeat. As the result, among 47 available genomes of unicellular eukaryotes we could not find a single instance of seven repeats with the motif. Several sequences contained three repeats, a predicted transmembrane segment, and a short cytoplasmic motif associated with some integrins, but otherwise differ from the metazoan integrin α subunits. Among the available bacterial sequences, we found five examples containing seven sequential metazoan integrin-specific motifs within the seven repeats. The motifs differ in having one Ca2+-binding site per repeat, whereas metazoan integrins have three or four sites. The bacterial sequences are more conserved in terms of motif conservation and loop length, suggesting that the structure is more regular and compact than those example structures from human integrins. Although the bacterial examples are not full-length integrins, the full-length metazoan-type 7-bladed β-propeller domains are present, and sometimes two tandem copies are found. PMID:22022374

Long-range electrostatic complementarity governs substrate recognition by human chymotrypsin C, a key regulator of digestive enzyme activation.

PubMed

Batra, Jyotica; Szabó, András; Caulfield, Thomas R; Soares, Alexei S; Sahin-Tóth, Miklós; Radisky, Evette S

2013-04-05

Human chymotrypsin C (CTRC) is a pancreatic serine protease that regulates activation and degradation of trypsinogens and procarboxypeptidases by targeting specific cleavage sites within their zymogen precursors. In cleaving these regulatory sites, which are characterized by multiple flanking acidic residues, CTRC shows substrate specificity that is distinct from that of other isoforms of chymotrypsin and elastase. Here, we report the first crystal structure of active CTRC, determined at 1.9-Å resolution, revealing the structural basis for binding specificity. The structure shows human CTRC bound to the small protein protease inhibitor eglin c, which binds in a substrate-like manner filling the S6-S5' subsites of the substrate binding cleft. Significant binding affinity derives from burial of preferred hydrophobic residues at the P1, P4, and P2' positions of CTRC, although acidic P2' residues can also be accommodated by formation of an interfacial salt bridge. Acidic residues may also be specifically accommodated in the P6 position. The most unique structural feature of CTRC is a ring of intense positive electrostatic surface potential surrounding the primarily hydrophobic substrate binding site. Our results indicate that long-range electrostatic attraction toward substrates of concentrated negative charge governs substrate discrimination, which explains CTRC selectivity in regulating active digestive enzyme levels.

Remote Sensing Observations of Thunderstorm Features in Latvia

NASA Astrophysics Data System (ADS)

Avotniece, Zanita; Briede, Agrita; Klavins, Maris; Aniskevich, Svetlana

2017-12-01

Thunderstorms are the most hazardous meteorological phenomena in Latvia in the summer season, and the assessment of their characteristics is essential for the development of an effective national climate and weather prediction service. However, the complex nature of convective processes sets specific limitations to their observation, analysis and forecasting. Therefore, the aim of this study is to analyse thunderstorm features associated with severe thunderstorms observed in weather radar and satellite data in Latvia over the period 2006-2015. The obtained results confirm the applicability of the selected thunderstorm features for thunderstorm nowcasting and analysis in Latvia. The most frequent features observed on days with thunderstorm were maximum radar reflectivities exceeding 50 dBZ and the occurrence of overshooting tops and tilted updrafts, while the occurrence of gravity waves, V-shaped storm structures and small ice particles have been found to be useful indicators of increased thunderstorm severity potential.

Improved method for predicting protein fold patterns with ensemble classifiers.

PubMed

Chen, W; Liu, X; Huang, Y; Jiang, Y; Zou, Q; Lin, C

2012-01-27

Protein folding is recognized as a critical problem in the field of biophysics in the 21st century. Predicting protein-folding patterns is challenging due to the complex structure of proteins. In an attempt to solve this problem, we employed ensemble classifiers to improve prediction accuracy. In our experiments, 188-dimensional features were extracted based on the composition and physical-chemical property of proteins and 20-dimensional features were selected using a coupled position-specific scoring matrix. Compared with traditional prediction methods, these methods were superior in terms of prediction accuracy. The 188-dimensional feature-based method achieved 71.2% accuracy in five cross-validations. The accuracy rose to 77% when we used a 20-dimensional feature vector. These methods were used on recent data, with 54.2% accuracy. Source codes and dataset, together with web server and software tools for prediction, are available at: http://datamining.xmu.edu.cn/main/~cwc/ProteinPredict.html.

Subcutaneous soft tissue sarcoma with rhabdoid features in a dog.

PubMed

Sayama, Ayako; Okado, Keiko; Imaoka, Masako; Yokouchi, Yusuke; Jindo, Toshimasa; Takasaki, Wataru

2014-07-01

A nine-year-old male beagle dog had a white spherical mass in the subcutis of the left lumbar region. Microscopically, spindle to oval cells diffusely proliferated in the fibrous and myxoid stroma. Many neoplastic cells showed rhabdoid features or vacuolated cytoplasm. Immunohistochemically, the neoplastic cells were positive for vimentin and S100 and partly positive for neuron-specific enolase and glial fibrillary acidic protein but were negative for von Willebrand factor, desmin and α-smooth muscle actin. Ultrastructurally, the neoplastic cells had abundant cytoplasmic processes and desmosome-like structures. Cytoplasmic inclusions of rhabdoid-featured cells in HE sections were composed of aggregates of intermediate filaments, and cytoplasmic vacuoles were identified as an invagination of cytoplasm. Although malignant peripheral nerve sheath tumor was suggested according to these results, the present case was diagnosed as a soft tissue sarcoma with rhabdoid features due to a lack of identification of the basal lamina under electron microscopy.

Pathogenic features and characteristics of food borne pathogens biofilm: Biomass, viability and matrix.

PubMed

Lin, Shiqi; Yang, Ling; Chen, Gu; Li, Bing; Chen, Dingqiang; Li, Lin; Xu, Zhenbo

2017-10-01

Biofilm is a ubiquitous growth pattern of bacterial species survival but is notorious for its threat on public health and food contamination. Extensive studies of the biofilm structure, formation, quantification, quorum sensing system and underlying control strategies have been reported during the past decades. Insightful elucidation of the pathogenic features and characteristic of bacterial biofilm can facilitate in devising appropriate control strategies for biofilm eradication. Therefore, this review mainly summarized the pathogenic features of biofilms from food borne microorganisms, including the biomass (which could be quantified using crystal violet and fluorogenic dye Syto9 assays), viability (which could be determined by tetrazolium salts, fluorescein diacetate, resazurin staining and alamar blue assays) and matrix (which are commonly detected by dimethyl methylene blue and wheat germ agglutinin assays). In addition, three features were further compared with its particular benefits in specific application. Copyright © 2017 Elsevier Ltd. All rights reserved.

Subcutaneous Soft Tissue Sarcoma with Rhabdoid Features in a Dog

PubMed Central

Sayama, Ayako; Okado, Keiko; Imaoka, Masako; Yokouchi, Yusuke; Jindo, Toshimasa; Takasaki, Wataru

2014-01-01

A nine-year-old male beagle dog had a white spherical mass in the subcutis of the left lumbar region. Microscopically, spindle to oval cells diffusely proliferated in the fibrous and myxoid stroma. Many neoplastic cells showed rhabdoid features or vacuolated cytoplasm. Immunohistochemically, the neoplastic cells were positive for vimentin and S100 and partly positive for neuron-specific enolase and glial fibrillary acidic protein but were negative for von Willebrand factor, desmin and α-smooth muscle actin. Ultrastructurally, the neoplastic cells had abundant cytoplasmic processes and desmosome-like structures. Cytoplasmic inclusions of rhabdoid-featured cells in HE sections were composed of aggregates of intermediate filaments, and cytoplasmic vacuoles were identified as an invagination of cytoplasm. Although malignant peripheral nerve sheath tumor was suggested according to these results, the present case was diagnosed as a soft tissue sarcoma with rhabdoid features due to a lack of identification of the basal lamina under electron microscopy. PMID:25352714

Towards in vivo focal cortical dysplasia phenotyping using quantitative MRI.

PubMed

Adler, Sophie; Lorio, Sara; Jacques, Thomas S; Benova, Barbora; Gunny, Roxana; Cross, J Helen; Baldeweg, Torsten; Carmichael, David W

2017-01-01

Focal cortical dysplasias (FCDs) are a range of malformations of cortical development each with specific histopathological features. Conventional radiological assessment of standard structural MRI is useful for the localization of lesions but is unable to accurately predict the histopathological features. Quantitative MRI offers the possibility to probe tissue biophysical properties in vivo and may bridge the gap between radiological assessment and ex-vivo histology. This review will cover histological, genetic and radiological features of FCD following the ILAE classification and will explain how quantitative voxel- and surface-based techniques can characterise these features. We will provide an overview of the quantitative MRI measures available, their link with biophysical properties and finally the potential application of quantitative MRI to the problem of FCD subtyping. Future research linking quantitative MRI to FCD histological properties should improve clinical protocols, allow better characterisation of lesions in vivo and tailored surgical planning to the individual.

Structural properties of prokaryotic promoter regions correlate with functional features.

PubMed

Meysman, Pieter; Collado-Vides, Julio; Morett, Enrique; Viola, Roberto; Engelen, Kristof; Laukens, Kris

2014-01-01

The structural properties of the DNA molecule are known to play a critical role in transcription. In this paper, the structural profiles of promoter regions were studied within the context of their diversity and their function for eleven prokaryotic species; Escherichia coli, Klebsiella pneumoniae, Salmonella Typhimurium, Pseudomonas auroginosa, Geobacter sulfurreducens Helicobacter pylori, Chlamydophila pneumoniae, Synechocystis sp., Synechoccocus elongates, Bacillus anthracis, and the archaea Sulfolobus solfataricus. The main anchor point for these promoter regions were transcription start sites identified through high-throughput experiments or collected within large curated databases. Prokaryotic promoter regions were found to be less stable and less flexible than the genomic mean across all studied species. However, direct comparison between species revealed differences in their structural profiles that can not solely be explained by the difference in genomic GC content. In addition, comparison with functional data revealed that there are patterns in the promoter structural profiles that can be linked to specific functional loci, such as sigma factor regulation or transcription factor binding. Interestingly, a novel structural element clearly visible near the transcription start site was found in genes associated with essential cellular functions and growth in several species. Our analyses reveals the great diversity in promoter structural profiles both between and within prokaryotic species. We observed relationships between structural diversity and functional features that are interesting prospects for further research to yet uncharacterized functional loci defined by DNA structural properties.

Structural Basis for Prereceptor Modulation of Plant Hormones by GH3 Proteins

DOE Office of Scientific and Technical Information (OSTI.GOV)

Westfall, Corey S.; Zubieta, Chloe; Herrmann, Jonathan

Acyl acid amido synthetases of the GH3 family act as critical prereceptor modulators of plant hormone action; however, the molecular basis for their hormone selectivity is unclear. Here, we report the crystal structures of benzoate-specific Arabidopsis thaliana AtGH3.12/PBS3 and jasmonic acid-specific AtGH3.11/JAR1. These structures, combined with biochemical analysis, define features for the conjugation of amino acids to diverse acyl acid substrates and highlight the importance of conformational changes in the carboxyl-terminal domain for catalysis. We also identify residues forming the acyl acid binding site across the GH3 family and residues critical for amino acid recognition. Our results demonstrate how amore » highly adaptable three-dimensional scaffold is used for the evolution of promiscuous activity across an enzyme family for modulation of plant signaling molecules.« less

Synthesis and Biological Evaluation of Botulinum Neurotoxin A Protease Inhibitors

PubMed Central

Li, Bing; Pai, Ramdas; Cardinale, Steven C.; Butler, Michelle M.; Peet, Norton P.; Moir, Donald T.; Bavari, Sina; Bowlin, Terry L.

2010-01-01

NSC 240898 was previously identified as a botulinum neurotoxin A light chain (BoNT/A LC) endopeptidase inhibitor by screening the National Cancer Institute Open Repository diversity set. Two types of analogs have been synthesized and shown to inhibit BoNT/A LC in a FRET-based enzyme assay, with confirmation in an HPLC-based assay. These two series of compounds have also been evaluated for inhibition of anthrax lethal factor (LF), an unrelated metalloprotease, to examine enzyme specificity of the BoNT/A LC inhibition. The most potent inhibitor against BoNT/A LC in these two series is compound 12 (IC50 = 2.5 µM, FRET assay), which is 4.4-fold more potent than the lead structure, and 11.2-fold more selective for BoNT/A LC versus the anthrax LF metalloproteinase. Structure-activity relationship studies have revealed structural features important to potency and enzyme specificity. PMID:20155918

Distributed acoustic cues for caller identity in macaque vocalization.

PubMed

Fukushima, Makoto; Doyle, Alex M; Mullarkey, Matthew P; Mishkin, Mortimer; Averbeck, Bruno B

2015-12-01

Individual primates can be identified by the sound of their voice. Macaques have demonstrated an ability to discern conspecific identity from a harmonically structured 'coo' call. Voice recognition presumably requires the integrated perception of multiple acoustic features. However, it is unclear how this is achieved, given considerable variability across utterances. Specifically, the extent to which information about caller identity is distributed across multiple features remains elusive. We examined these issues by recording and analysing a large sample of calls from eight macaques. Single acoustic features, including fundamental frequency, duration and Weiner entropy, were informative but unreliable for the statistical classification of caller identity. A combination of multiple features, however, allowed for highly accurate caller identification. A regularized classifier that learned to identify callers from the modulation power spectrum of calls found that specific regions of spectral-temporal modulation were informative for caller identification. These ranges are related to acoustic features such as the call's fundamental frequency and FM sweep direction. We further found that the low-frequency spectrotemporal modulation component contained an indexical cue of the caller body size. Thus, cues for caller identity are distributed across identifiable spectrotemporal components corresponding to laryngeal and supralaryngeal components of vocalizations, and the integration of those cues can enable highly reliable caller identification. Our results demonstrate a clear acoustic basis by which individual macaque vocalizations can be recognized.

Distributed acoustic cues for caller identity in macaque vocalization

PubMed Central

Doyle, Alex M.; Mullarkey, Matthew P.; Mishkin, Mortimer; Averbeck, Bruno B.

2015-01-01

Individual primates can be identified by the sound of their voice. Macaques have demonstrated an ability to discern conspecific identity from a harmonically structured ‘coo’ call. Voice recognition presumably requires the integrated perception of multiple acoustic features. However, it is unclear how this is achieved, given considerable variability across utterances. Specifically, the extent to which information about caller identity is distributed across multiple features remains elusive. We examined these issues by recording and analysing a large sample of calls from eight macaques. Single acoustic features, including fundamental frequency, duration and Weiner entropy, were informative but unreliable for the statistical classification of caller identity. A combination of multiple features, however, allowed for highly accurate caller identification. A regularized classifier that learned to identify callers from the modulation power spectrum of calls found that specific regions of spectral–temporal modulation were informative for caller identification. These ranges are related to acoustic features such as the call’s fundamental frequency and FM sweep direction. We further found that the low-frequency spectrotemporal modulation component contained an indexical cue of the caller body size. Thus, cues for caller identity are distributed across identifiable spectrotemporal components corresponding to laryngeal and supralaryngeal components of vocalizations, and the integration of those cues can enable highly reliable caller identification. Our results demonstrate a clear acoustic basis by which individual macaque vocalizations can be recognized. PMID:27019727

Model-Independent Phenotyping of C. elegans Locomotion Using Scale-Invariant Feature Transform

PubMed Central

Koren, Yelena; Sznitman, Raphael; Arratia, Paulo E.; Carls, Christopher; Krajacic, Predrag; Brown, André E. X.; Sznitman, Josué

2015-01-01

To uncover the genetic basis of behavioral traits in the model organism C. elegans, a common strategy is to study locomotion defects in mutants. Despite efforts to introduce (semi-)automated phenotyping strategies, current methods overwhelmingly depend on worm-specific features that must be hand-crafted and as such are not generalizable for phenotyping motility in other animal models. Hence, there is an ongoing need for robust algorithms that can automatically analyze and classify motility phenotypes quantitatively. To this end, we have developed a fully-automated approach to characterize C. elegans’ phenotypes that does not require the definition of nematode-specific features. Rather, we make use of the popular computer vision Scale-Invariant Feature Transform (SIFT) from which we construct histograms of commonly-observed SIFT features to represent nematode motility. We first evaluated our method on a synthetic dataset simulating a range of nematode crawling gaits. Next, we evaluated our algorithm on two distinct datasets of crawling C. elegans with mutants affecting neuromuscular structure and function. Not only is our algorithm able to detect differences between strains, results capture similarities in locomotory phenotypes that lead to clustering that is consistent with expectations based on genetic relationships. Our proposed approach generalizes directly and should be applicable to other animal models. Such applicability holds promise for computational ethology as more groups collect high-resolution image data of animal behavior. PMID:25816290

Enhanced Regulatory Sequence Prediction Using Gapped k-mer Features

PubMed Central

Mohammad-Noori, Morteza; Beer, Michael A.

2014-01-01

Abstract Oligomers of length k, or k-mers, are convenient and widely used features for modeling the properties and functions of DNA and protein sequences. However, k-mers suffer from the inherent limitation that if the parameter k is increased to resolve longer features, the probability of observing any specific k-mer becomes very small, and k-mer counts approach a binary variable, with most k-mers absent and a few present once. Thus, any statistical learning approach using k-mers as features becomes susceptible to noisy training set k-mer frequencies once k becomes large. To address this problem, we introduce alternative feature sets using gapped k-mers, a new classifier, gkm-SVM, and a general method for robust estimation of k-mer frequencies. To make the method applicable to large-scale genome wide applications, we develop an efficient tree data structure for computing the kernel matrix. We show that compared to our original kmer-SVM and alternative approaches, our gkm-SVM predicts functional genomic regulatory elements and tissue specific enhancers with significantly improved accuracy, increasing the precision by up to a factor of two. We then show that gkm-SVM consistently outperforms kmer-SVM on human ENCODE ChIP-seq datasets, and further demonstrate the general utility of our method using a Naïve-Bayes classifier. Although developed for regulatory sequence analysis, these methods can be applied to any sequence classification problem. PMID:25033408

Enhanced regulatory sequence prediction using gapped k-mer features.

PubMed

Ghandi, Mahmoud; Lee, Dongwon; Mohammad-Noori, Morteza; Beer, Michael A

2014-07-01

Oligomers of length k, or k-mers, are convenient and widely used features for modeling the properties and functions of DNA and protein sequences. However, k-mers suffer from the inherent limitation that if the parameter k is increased to resolve longer features, the probability of observing any specific k-mer becomes very small, and k-mer counts approach a binary variable, with most k-mers absent and a few present once. Thus, any statistical learning approach using k-mers as features becomes susceptible to noisy training set k-mer frequencies once k becomes large. To address this problem, we introduce alternative feature sets using gapped k-mers, a new classifier, gkm-SVM, and a general method for robust estimation of k-mer frequencies. To make the method applicable to large-scale genome wide applications, we develop an efficient tree data structure for computing the kernel matrix. We show that compared to our original kmer-SVM and alternative approaches, our gkm-SVM predicts functional genomic regulatory elements and tissue specific enhancers with significantly improved accuracy, increasing the precision by up to a factor of two. We then show that gkm-SVM consistently outperforms kmer-SVM on human ENCODE ChIP-seq datasets, and further demonstrate the general utility of our method using a Naïve-Bayes classifier. Although developed for regulatory sequence analysis, these methods can be applied to any sequence classification problem.

A neuro-fuzzy architecture for real-time applications

NASA Technical Reports Server (NTRS)

Ramamoorthy, P. A.; Huang, Song

1992-01-01

Neural networks and fuzzy expert systems perform the same task of functional mapping using entirely different approaches. Each approach has certain unique features. The ability to learn specific input-output mappings from large input/output data possibly corrupted by noise and the ability to adapt or continue learning are some important features of neural networks. Fuzzy expert systems are known for their ability to deal with fuzzy information and incomplete/imprecise data in a structured, logical way. Since both of these techniques implement the same task (that of functional mapping--we regard 'inferencing' as one specific category under this class), a fusion of the two concepts that retains their unique features while overcoming their individual drawbacks will have excellent applications in the real world. In this paper, we arrive at a new architecture by fusing the two concepts. The architecture has the trainability/adaptibility (based on input/output observations) property of the neural networks and the architectural features that are unique to fuzzy expert systems. It also does not require specific information such as fuzzy rules, defuzzification procedure used, etc., though any such information can be integrated into the architecture. We show that this architecture can provide better performance than is possible from a single two or three layer feedforward neural network. Further, we show that this new architecture can be used as an efficient vehicle for hardware implementation of complex fuzzy expert systems for real-time applications. A numerical example is provided to show the potential of this approach.

Learning to rank using user clicks and visual features for image retrieval.

PubMed

Yu, Jun; Tao, Dacheng; Wang, Meng; Rui, Yong

2015-04-01

The inconsistency between textual features and visual contents can cause poor image search results. To solve this problem, click features, which are more reliable than textual information in justifying the relevance between a query and clicked images, are adopted in image ranking model. However, the existing ranking model cannot integrate visual features, which are efficient in refining the click-based search results. In this paper, we propose a novel ranking model based on the learning to rank framework. Visual features and click features are simultaneously utilized to obtain the ranking model. Specifically, the proposed approach is based on large margin structured output learning and the visual consistency is integrated with the click features through a hypergraph regularizer term. In accordance with the fast alternating linearization method, we design a novel algorithm to optimize the objective function. This algorithm alternately minimizes two different approximations of the original objective function by keeping one function unchanged and linearizing the other. We conduct experiments on a large-scale dataset collected from the Microsoft Bing image search engine, and the results demonstrate that the proposed learning to rank models based on visual features and user clicks outperforms state-of-the-art algorithms.

The Gemini NICI Planet-Finding Campaign: asymmetries in the HD 141569 disc

NASA Astrophysics Data System (ADS)

Biller, Beth A.; Liu, Michael C.; Rice, Ken; Wahhaj, Zahed; Nielsen, Eric; Hayward, Thomas; Kuchner, Marc J.; Close, Laird M.; Chun, Mark; Ftaclas, Christ; Toomey, Douglas W.

2015-07-01

We report here the highest resolution near-IR imaging to date of the HD 141569A disc taken as part of the NICI (near infrared coronagraphic imager) Science Campaign. We recover four main features in the NICI images of the HD 141569 disc discovered in previous Hubble Space Telescope (HST) imaging: (1) an inner ring/spiral feature. Once deprojected, this feature does not appear circular. (2) An outer ring which is considerably brighter on the western side compared to the eastern side, but looks fairly circular in the deprojected image. (3) An additional arc-like feature between the inner and outer ring only evident on the east side. In the deprojected image, this feature appears to complete the circle of the west side inner ring and (4) an evacuated cavity from 175 au inwards. Compared to the previous HST imaging with relatively large coronagraphic inner working angles (IWA), the NICI coronagraph allows imaging down to an IWA of 0.3 arcsec. Thus, the inner edge of the inner ring/spiral feature is well resolved and we do not find any additional disc structures within 175 au. We note some additional asymmetries in this system. Specifically, while the outer ring structure looks circular in this deprojection, the inner bright ring looks rather elliptical. This suggests that a single deprojection angle is not appropriate for this system and that there may be an offset in inclination between the two ring/spiral features. We find an offset of 4 ± 2 au between the inner ring and the star centre, potentially pointing to unseen inner companions.

Atomic force microscopy study of the structure function relationships of the biofilm-forming bacterium Streptococcus mutans

NASA Astrophysics Data System (ADS)

Cross, Sarah E.; Kreth, Jens; Zhu, Lin; Qi, Fengxia; Pelling, Andrew E.; Shi, Wenyuan; Gimzewski, James K.

2006-02-01

Atomic force microscopy (AFM) has garnered much interest in recent years for its ability to probe the structure, function and cellular nanomechanics inherent to specific biological cells. In particular, we have used AFM to probe the important structure-function relationships of the bacterium Streptococcus mutans. S. mutans is the primary aetiological agent in human dental caries (tooth decay), and is of medical importance due to the virulence properties of these cells in biofilm initiation and formation, leading to increased tolerance to antibiotics. We have used AFM to characterize the unique surface structures of distinct mutants of S. mutans. These mutations are located in specific genes that encode surface proteins, thus using AFM we have resolved characteristic surface features for mutant strains compared to the wild type. Ultimately, our characterization of surface morphology has shown distinct differences in the local properties displayed by various S. mutans strains on the nanoscale, which is imperative for understanding the collective properties of these cells in biofilm formation.

Structural basis for IL-1α recognition by a modified DNA aptamer that specifically inhibits IL-1α signaling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ren, Xiaoming; Gelinas, Amy D.; von Carlowitz, Ira

IL-1α is an essential cytokine that contributes to inflammatory responses and is implicated in various forms of pathogenesis and cancer. Here we report a naphthyl modified DNA aptamer that specifically binds IL-1α and inhibits its signaling pathway. By solving the crystal structure of the IL-1α/aptamer, we provide a high-resolution structure of this critical cytokine and we reveal its functional interaction interface with high-affinity ligands. The non-helical aptamer, which represents a highly compact nucleic acid structure, contains a wealth of new conformational features, including an unknown form of G-quadruplex. The IL-1α/aptamer interface is composed of unusual polar and hydrophobic elements, alongmore » with an elaborate hydrogen bonding network that is mediated by sodium ion. IL-1α uses the same interface to interact with both the aptamer and its cognate receptor IL-1RI, thereby suggesting a novel route to immunomodulatory therapeutics.« less

Metrics for comparing neuronal tree shapes based on persistent homology.

PubMed

Li, Yanjie; Wang, Dingkang; Ascoli, Giorgio A; Mitra, Partha; Wang, Yusu

2017-01-01

As more and more neuroanatomical data are made available through efforts such as NeuroMorpho.Org and FlyCircuit.org, the need to develop computational tools to facilitate automatic knowledge discovery from such large datasets becomes more urgent. One fundamental question is how best to compare neuron structures, for instance to organize and classify large collection of neurons. We aim to develop a flexible yet powerful framework to support comparison and classification of large collection of neuron structures efficiently. Specifically we propose to use a topological persistence-based feature vectorization framework. Existing methods to vectorize a neuron (i.e, convert a neuron to a feature vector so as to support efficient comparison and/or searching) typically rely on statistics or summaries of morphometric information, such as the average or maximum local torque angle or partition asymmetry. These simple summaries have limited power in encoding global tree structures. Based on the concept of topological persistence recently developed in the field of computational topology, we vectorize each neuron structure into a simple yet informative summary. In particular, each type of information of interest can be represented as a descriptor function defined on the neuron tree, which is then mapped to a simple persistence-signature. Our framework can encode both local and global tree structure, as well as other information of interest (electrophysiological or dynamical measures), by considering multiple descriptor functions on the neuron. The resulting persistence-based signature is potentially more informative than simple statistical summaries (such as average/mean/max) of morphometric quantities-Indeed, we show that using a certain descriptor function will give a persistence-based signature containing strictly more information than the classical Sholl analysis. At the same time, our framework retains the efficiency associated with treating neurons as points in a simple Euclidean feature space, which would be important for constructing efficient searching or indexing structures over them. We present preliminary experimental results to demonstrate the effectiveness of our persistence-based neuronal feature vectorization framework.

Metrics for comparing neuronal tree shapes based on persistent homology

PubMed Central

Li, Yanjie; Wang, Dingkang; Ascoli, Giorgio A.; Mitra, Partha

2017-01-01

As more and more neuroanatomical data are made available through efforts such as NeuroMorpho.Org and FlyCircuit.org, the need to develop computational tools to facilitate automatic knowledge discovery from such large datasets becomes more urgent. One fundamental question is how best to compare neuron structures, for instance to organize and classify large collection of neurons. We aim to develop a flexible yet powerful framework to support comparison and classification of large collection of neuron structures efficiently. Specifically we propose to use a topological persistence-based feature vectorization framework. Existing methods to vectorize a neuron (i.e, convert a neuron to a feature vector so as to support efficient comparison and/or searching) typically rely on statistics or summaries of morphometric information, such as the average or maximum local torque angle or partition asymmetry. These simple summaries have limited power in encoding global tree structures. Based on the concept of topological persistence recently developed in the field of computational topology, we vectorize each neuron structure into a simple yet informative summary. In particular, each type of information of interest can be represented as a descriptor function defined on the neuron tree, which is then mapped to a simple persistence-signature. Our framework can encode both local and global tree structure, as well as other information of interest (electrophysiological or dynamical measures), by considering multiple descriptor functions on the neuron. The resulting persistence-based signature is potentially more informative than simple statistical summaries (such as average/mean/max) of morphometric quantities—Indeed, we show that using a certain descriptor function will give a persistence-based signature containing strictly more information than the classical Sholl analysis. At the same time, our framework retains the efficiency associated with treating neurons as points in a simple Euclidean feature space, which would be important for constructing efficient searching or indexing structures over them. We present preliminary experimental results to demonstrate the effectiveness of our persistence-based neuronal feature vectorization framework. PMID:28809960

Molecular Dynamics Simulations and Structural Analysis of Giardia duodenalis 14-3-3 Protein-Protein Interactions.

PubMed

Cau, Ylenia; Fiorillo, Annarita; Mori, Mattia; Ilari, Andrea; Botta, Maurizo; Lalle, Marco

2015-12-28

Giardiasis is a gastrointestinal diarrheal illness caused by the protozoan parasite Giardia duodenalis, which affects annually over 200 million people worldwide. The limited antigiardial drug arsenal and the emergence of clinical cases refractory to standard treatments dictate the need for new chemotherapeutics. The 14-3-3 family of regulatory proteins, extensively involved in protein-protein interactions (PPIs) with pSer/pThr clients, represents a highly promising target. Despite homology with human counterparts, the single 14-3-3 of G. duodenalis (g14-3-3) is characterized by a constitutive phosphorylation in a region critical for target binding, thus affecting the function and the conformation of g14-3-3/clients interaction. However, to approach the design of specific small molecule modulators of g14-3-3 PPIs, structural elucidations are required. Here, we present a detailed computational and crystallographic study exploring the implications of g14-3-3 phosphorylation on protein structure and target binding. Self-Guided Langevin Dynamics and classical molecular dynamics simulations show that phosphorylation affects locally and globally g14-3-3 conformation, inducing a structural rearrangement more suitable for target binding. Profitable features for g14-3-3/clients interaction were highlighted using a hydrophobicity-based descriptor to characterize g14-3-3 client peptides. Finally, the X-ray structure of g14-3-3 in complex with a mode-1 prototype phosphopeptide was solved and combined with structure-based simulations to identify molecular features relevant for clients binding to g14-3-3. The data presented herein provide a further and structural understanding of g14-3-3 features and set the basis for drug design studies.

Using complex networks for text classification: Discriminating informative and imaginative documents

NASA Astrophysics Data System (ADS)

de Arruda, Henrique F.; Costa, Luciano da F.; Amancio, Diego R.

2016-01-01

Statistical methods have been widely employed in recent years to grasp many language properties. The application of such techniques have allowed an improvement of several linguistic applications, such as machine translation and document classification. In the latter, many approaches have emphasised the semantical content of texts, as is the case of bag-of-word language models. These approaches have certainly yielded reasonable performance. However, some potential features such as the structural organization of texts have been used only in a few studies. In this context, we probe how features derived from textual structure analysis can be effectively employed in a classification task. More specifically, we performed a supervised classification aiming at discriminating informative from imaginative documents. Using a networked model that describes the local topological/dynamical properties of function words, we achieved an accuracy rate of up to 95%, which is much higher than similar networked approaches. A systematic analysis of feature relevance revealed that symmetry and accessibility measurements are among the most prominent network measurements. Our results suggest that these measurements could be used in related language applications, as they play a complementary role in characterising texts.

CheS-Mapper - Chemical Space Mapping and Visualization in 3D.

PubMed

Gütlein, Martin; Karwath, Andreas; Kramer, Stefan

2012-03-17

Analyzing chemical datasets is a challenging task for scientific researchers in the field of chemoinformatics. It is important, yet difficult to understand the relationship between the structure of chemical compounds, their physico-chemical properties, and biological or toxic effects. To that respect, visualization tools can help to better comprehend the underlying correlations. Our recently developed 3D molecular viewer CheS-Mapper (Chemical Space Mapper) divides large datasets into clusters of similar compounds and consequently arranges them in 3D space, such that their spatial proximity reflects their similarity. The user can indirectly determine similarity, by selecting which features to employ in the process. The tool can use and calculate different kind of features, like structural fragments as well as quantitative chemical descriptors. These features can be highlighted within CheS-Mapper, which aids the chemist to better understand patterns and regularities and relate the observations to established scientific knowledge. As a final function, the tool can also be used to select and export specific subsets of a given dataset for further analysis.

CheS-Mapper - Chemical Space Mapping and Visualization in 3D

PubMed Central

2012-01-01

Analyzing chemical datasets is a challenging task for scientific researchers in the field of chemoinformatics. It is important, yet difficult to understand the relationship between the structure of chemical compounds, their physico-chemical properties, and biological or toxic effects. To that respect, visualization tools can help to better comprehend the underlying correlations. Our recently developed 3D molecular viewer CheS-Mapper (Chemical Space Mapper) divides large datasets into clusters of similar compounds and consequently arranges them in 3D space, such that their spatial proximity reflects their similarity. The user can indirectly determine similarity, by selecting which features to employ in the process. The tool can use and calculate different kind of features, like structural fragments as well as quantitative chemical descriptors. These features can be highlighted within CheS-Mapper, which aids the chemist to better understand patterns and regularities and relate the observations to established scientific knowledge. As a final function, the tool can also be used to select and export specific subsets of a given dataset for further analysis. PMID:22424447

Ultrastructural analysis of testicular tissue and sperm by transmission and scanning electron microscopy.

PubMed

Chemes, Hector E

2013-01-01

Transmission electron microscopy (TEM) studies have provided the basis for an in-depth understanding of the cell biology and normal functioning of the testis and male gametes and have opened the way to characterize the functional role played by specific organelles in spermatogenesis and sperm function. The development of the scanning electron microscope (SEM) extended these boundaries to the recognition of cell and organ surface features and the architectural array of cells and tissues. The merging of immunocytochemical and histochemical approaches with electron microscopy has completed a series of technical improvements that integrate structural and functional features to provide a broad understanding of cell biology in health and disease. With these advances the detailed study of the intricate structural and molecular organization as well as the chemical composition of cellular organelles is now possible. Immunocytochemistry is used to identify proteins or other components and localize them in specific cells or organelles with high specificity and sensitivity, and histochemistry can be used to understand their function (i.e., enzyme activity). When these techniques are used in conjunction with electron microscopy their resolving power is further increased to subcellular levels. In the present chapter we will describe in detail various ultrastructural techniques that are now available for basic or translational research in reproductive biology and reproductive medicine. These include TEM, ultrastructural immunocytochemistry, ultrastructural histochemistry, and SEM.

Revealing mesoscopic structural universality with diffusion.

PubMed

Novikov, Dmitry S; Jensen, Jens H; Helpern, Joseph A; Fieremans, Els

2014-04-08

Measuring molecular diffusion is widely used for characterizing materials and living organisms noninvasively. This characterization relies on relations between macroscopic diffusion metrics and structure at the mesoscopic scale commensurate with the diffusion length. Establishing such relations remains a fundamental challenge, hindering progress in materials science, porous media, and biomedical imaging. Here we show that the dynamical exponent in the time dependence of the diffusion coefficient distinguishes between the universality classes of the mesoscopic structural complexity. Our approach enables the interpretation of diffusion measurements by objectively selecting and modeling the most relevant structural features. As an example, the specific values of the dynamical exponent allow us to identify the relevant mesoscopic structure affecting MRI-measured water diffusion in muscles and in brain, and to elucidate the structural changes behind the decrease of diffusion coefficient in ischemic stroke.

Parental Socialization and Community Context: A Longitudinal Analysis of the Structural Sources of Low Self-Control

ERIC Educational Resources Information Center

Pratt, Travis C.; Turner, Michael G.; Piquero, Alex R.

2004-01-01

Several empirical studies have attempted to estimate the effect of low self-control on criminal and "analogous" behaviors. Most of these studies have shown that low self-control is an important feature of the cause(s) of crime. Although research is beginning to emerge that targets more specifically the "roots" of self-control via parental…

The Effect of Specific Language Features on the Complexity of Systems for Automated Essay Scoring.

ERIC Educational Resources Information Center

Cohen, Yoav; Ben-Simon, Anat; Hovav, Myra

This paper focuses on the relationship between different aspects of the linguistic structure of a given language and the complexity of the computer program, whether existing or prospective, that is to be used for the scoring of essays in that language. The first part of the paper discusses common scales used to assess writing products, then…

Isolation by distance, resistance and/or clusters? Lessons learned from a forest-dwelling carnivore inhabiting a heterogeneous landscape

Treesearch

Aritz Ruiz-Gonzalez; Samuel A. Cushman; Maria Jose Madeira; Ettore Randi; Benjamin J. Gomez-Moliner

2015-01-01

Landscape genetics provides a valuable framework to understand how landscape features influence gene flow and to disentangle the factors that lead to discrete and/or clinal population structure. Here, we attempt to differentiate between these processes in a forest-dwelling small carnivore [European pine marten (Martes martes)]. Specifically, we used...

Nenets, Khanty and Selkup: The Nenets, Khanty and Selkup Language in Education in the Yamal Region in Russia. Regional Dossiers Series

ERIC Educational Resources Information Center

Laptander, Roza Ivanovna, Comp.

2016-01-01

This regional dossier aims to provide a concise, description and basic statistics about minority language education in a specific region of Europe. Aspects that are addressed include features of the education system, recent educational policies, main actors, legal arrangements, and support structures, as well as quantitative aspects, such as the…

Platyhelminth Venom Allergen-Like (VAL) proteins: revealing structural diversity, class-specific features and biological associations across the phylum

PubMed Central

CHALMERS, IAIN W.; HOFFMANN, KARL F.

2012-01-01

SUMMARY During platyhelminth infection, a cocktail of proteins is released by the parasite to aid invasion, initiate feeding, facilitate adaptation and mediate modulation of the host immune response. Included amongst these proteins is the Venom Allergen-Like (VAL) family, part of the larger sperm coating protein/Tpx-1/Ag5/PR-1/Sc7 (SCP/TAPS) superfamily. To explore the significance of this protein family during Platyhelminthes development and host interactions, we systematically summarize all published proteomic, genomic and immunological investigations of the VAL protein family to date. By conducting new genomic and transcriptomic interrogations to identify over 200 VAL proteins (228) from species in all 4 traditional taxonomic classes (Trematoda, Cestoda, Monogenea and Turbellaria), we further expand our knowledge related to platyhelminth VAL diversity across the phylum. Subsequent phylogenetic and tertiary structural analyses reveal several class-specific VAL features, which likely indicate a range of roles mediated by this protein family. Our comprehensive analysis of platyhelminth VALs represents a unifying synopsis for understanding diversity within this protein family and a firm context in which to initiate future functional characterization of these enigmatic members. PMID:22717097

The use of virtual patient scenarios as a vehicle for teaching professionalism.

PubMed

Marei, H F; Al-Eraky, M M; Almasoud, N N; Donkers, J; Van Merrienboer, J J G

2018-05-01

This study aimed to measure students' perceptions of virtual patient scenarios (VPs) for developing ethical reasoning skills and to explore features in VP design that are necessary to promote professionalism. Sixty-five dental students participated in learning sessions that involved collaborative practice with five VPs (four high fidelity and one low fidelity), followed by reflection sessions. Students' perceptions towards the use of VPs in developing ethical reasoning skills were assessed using a questionnaire that involved 10 closed and three open-ended questions. High-fidelity VPs were perceived as significantly better for developing ethical reasoning skills than low-fidelity VPs. Analyses of answers to open-ended questions revealed two new features that are specific for VPs intended for teaching professionalism, which are VP dramatic structure and how it should end. VPs intended for teaching professionalism need to have high fidelity, follow a specific dramatic structure and should include multiple plausible endings. The use of VPs as part of a collaborative activity that is followed by a reflection session is perceived as an effective tool for the development of ethical reasoning skills in dental education. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

An “ADME Module” in the Adverse Outcome Pathway ...

EPA Pesticide Factsheets

The Adverse Outcome Pathway (AOP) framework has generated intense interest for its utility to organize knowledge on the toxicity mechanisms, starting from a molecular initiating event (MIE) to an adverse outcome across various levels of biological organization. While the AOP framework is designed to be chemical agnostic, it is widely recognized that considering chemicals’ absorption, distribution, metabolism, and excretion (ADME) behaviors is critical in applying the AOP framework in chemical-specific risk assessment. Currently, information being generated as part of the Organisation for Economic Co-operation and Development (OECD) AOP Development Programme is being consolidated into an AOP Knowledgebase (http://aopwiki.org). To enhance the use of this Knowledgebase in risk assessment, an ADME Module has been developed to contain the ADME information needed to connect MIEs and other key events in an AOP for specific chemicals. The conceptual structure of this module characterizes the potential of a chemical to reach the target MIE based on either its structure-based features or relative rates of ADME. The key features of this module include (1) a framework for connecting biology-based AOP to biochemical-based ADME and chemical/human activity-based exposure pathways; (2) links to qualitative tools (e.g., structure-based cheminformatic model) that screen for chemicals that could potentially reach the target MIE; (3) links to quantitative tools (e.g., dose-r

Malignant lymphoma simulating lymph node toxoplasmosis.

PubMed

Miettinen, M; Franssila, K

1982-03-01

On histological examination of 667 cases originally suspected of lymph node toxoplasmosis, 12 cases were diagnosed as malignant lymphoma and 15 cases as atypical hyperplasia (AH), suspicious of malignant lymphoma. All 12 malignant cases were of Hodgkin's disease: eight of the lymphocyte predominant nodular type, two of lymphocyte predominant diffuse type, and two of the nodular sclerosis type. In all cases, the lymph nodes contained small groups of epithelioid cells which were virtually indistinguishable from those seen in toxoplasmosis. In the differential diagnosis between lymph node toxoplasmosis and malignant lymphoma, the following features were found helpful. In toxoplasmosis the general structure is preserved and germinal centres are frequent, while in malignant lymphoma and in AH the general structure is destroyed. However, in some cases of toxoplasmosis germinal centres may be difficult to identify because their margins are indistinct due to clusters of epithelioid cells. Also, in some types of Hodgkin's disease and in some cases of AH with epithelioid cells, the general structure of the lymph node may be partially preserved. The occurrence of epithelioid cells within germinal centres seems to be a specific feature for toxoplasmosis; it was never seen in malignant lymphoma nor in AH. The occurrence of strands of monocytoid cells (unreife Sinushistiocytose) though a fairly typical feature of toxoplasmosis, was also occasionally seen in Hodgkin's disease or AH.

Landmark-based deep multi-instance learning for brain disease diagnosis.

PubMed

Liu, Mingxia; Zhang, Jun; Adeli, Ehsan; Shen, Dinggang

2018-01-01

In conventional Magnetic Resonance (MR) image based methods, two stages are often involved to capture brain structural information for disease diagnosis, i.e., 1) manually partitioning each MR image into a number of regions-of-interest (ROIs), and 2) extracting pre-defined features from each ROI for diagnosis with a certain classifier. However, these pre-defined features often limit the performance of the diagnosis, due to challenges in 1) defining the ROIs and 2) extracting effective disease-related features. In this paper, we propose a landmark-based deep multi-instance learning (LDMIL) framework for brain disease diagnosis. Specifically, we first adopt a data-driven learning approach to discover disease-related anatomical landmarks in the brain MR images, along with their nearby image patches. Then, our LDMIL framework learns an end-to-end MR image classifier for capturing both the local structural information conveyed by image patches located by landmarks and the global structural information derived from all detected landmarks. We have evaluated our proposed framework on 1526 subjects from three public datasets (i.e., ADNI-1, ADNI-2, and MIRIAD), and the experimental results show that our framework can achieve superior performance over state-of-the-art approaches. Copyright © 2017 Elsevier B.V. All rights reserved.

Quantitative Wood Anatomy-Practical Guidelines.

PubMed

von Arx, Georg; Crivellaro, Alan; Prendin, Angela L; Čufar, Katarina; Carrer, Marco

2016-01-01

Quantitative wood anatomy analyzes the variability of xylem anatomical features in trees, shrubs, and herbaceous species to address research questions related to plant functioning, growth, and environment. Among the more frequently considered anatomical features are lumen dimensions and wall thickness of conducting cells, fibers, and several ray properties. The structural properties of each xylem anatomical feature are mostly fixed once they are formed, and define to a large extent its functionality, including transport and storage of water, nutrients, sugars, and hormones, and providing mechanical support. The anatomical features can often be localized within an annual growth ring, which allows to establish intra-annual past and present structure-function relationships and its sensitivity to environmental variability. However, there are many methodological challenges to handle when aiming at producing (large) data sets of xylem anatomical data. Here we describe the different steps from wood sample collection to xylem anatomical data, provide guidance and identify pitfalls, and present different image-analysis tools for the quantification of anatomical features, in particular conducting cells. We show that each data production step from sample collection in the field, microslide preparation in the lab, image capturing through an optical microscope and image analysis with specific tools can readily introduce measurement errors between 5 and 30% and more, whereby the magnitude usually increases the smaller the anatomical features. Such measurement errors-if not avoided or corrected-may make it impossible to extract meaningful xylem anatomical data in light of the rather small range of variability in many anatomical features as observed, for example, within time series of individual plants. Following a rigid protocol and quality control as proposed in this paper is thus mandatory to use quantitative data of xylem anatomical features as a powerful source for many research topics.

Quantitative Wood Anatomy—Practical Guidelines

PubMed Central

von Arx, Georg; Crivellaro, Alan; Prendin, Angela L.; Čufar, Katarina; Carrer, Marco

2016-01-01

Quantitative wood anatomy analyzes the variability of xylem anatomical features in trees, shrubs, and herbaceous species to address research questions related to plant functioning, growth, and environment. Among the more frequently considered anatomical features are lumen dimensions and wall thickness of conducting cells, fibers, and several ray properties. The structural properties of each xylem anatomical feature are mostly fixed once they are formed, and define to a large extent its functionality, including transport and storage of water, nutrients, sugars, and hormones, and providing mechanical support. The anatomical features can often be localized within an annual growth ring, which allows to establish intra-annual past and present structure-function relationships and its sensitivity to environmental variability. However, there are many methodological challenges to handle when aiming at producing (large) data sets of xylem anatomical data. Here we describe the different steps from wood sample collection to xylem anatomical data, provide guidance and identify pitfalls, and present different image-analysis tools for the quantification of anatomical features, in particular conducting cells. We show that each data production step from sample collection in the field, microslide preparation in the lab, image capturing through an optical microscope and image analysis with specific tools can readily introduce measurement errors between 5 and 30% and more, whereby the magnitude usually increases the smaller the anatomical features. Such measurement errors—if not avoided or corrected—may make it impossible to extract meaningful xylem anatomical data in light of the rather small range of variability in many anatomical features as observed, for example, within time series of individual plants. Following a rigid protocol and quality control as proposed in this paper is thus mandatory to use quantitative data of xylem anatomical features as a powerful source for many research topics. PMID:27375641

Image-based overlay measurement using subsurface ultrasonic resonance force microscopy

NASA Astrophysics Data System (ADS)

Tamer, M. S.; van der Lans, M. J.; Sadeghian, H.

2018-03-01

Image Based Overlay (IBO) measurement is one of the most common techniques used in Integrated Circuit (IC) manufacturing to extract the overlay error values. The overlay error is measured using dedicated overlay targets which are optimized to increase the accuracy and the resolution, but these features are much larger than the IC feature size. IBO measurements are realized on the dedicated targets instead of product features, because the current overlay metrology solutions, mainly based on optics, cannot provide sufficient resolution on product features. However, considering the fact that the overlay error tolerance is approaching 2 nm, the overlay error measurement on product features becomes a need for the industry. For sub-nanometer resolution metrology, Scanning Probe Microscopy (SPM) is widely used, though at the cost of very low throughput. The semiconductor industry is interested in non-destructive imaging of buried structures under one or more layers for the application of overlay and wafer alignment, specifically through optically opaque media. Recently an SPM technique has been developed for imaging subsurface features which can be potentially considered as a solution for overlay metrology. In this paper we present the use of Subsurface Ultrasonic Resonance Force Microscopy (SSURFM) used for IBO measurement. We used SSURFM for imaging the most commonly used overlay targets on a silicon substrate and photoresist. As a proof of concept we have imaged surface and subsurface structures simultaneously. The surface and subsurface features of the overlay targets are fabricated with programmed overlay errors of +/-40 nm, +/-20 nm, and 0 nm. The top layer thickness changes between 30 nm and 80 nm. Using SSURFM the surface and subsurface features were successfully imaged and the overlay errors were extracted, via a rudimentary image processing algorithm. The measurement results are in agreement with the nominal values of the programmed overlay errors.

Semantic memory: a feature-based analysis and new norms for Italian.

PubMed

Montefinese, Maria; Ambrosini, Ettore; Fairfield, Beth; Mammarella, Nicola

2013-06-01

Semantic norms for properties produced by native speakers are valuable tools for researchers interested in the structure of semantic memory and in category-specific semantic deficits in individuals following brain damage. The aims of this study were threefold. First, we sought to extend existing semantic norms by adopting an empirical approach to category (Exp. 1) and concept (Exp. 2) selection, in order to obtain a more representative set of semantic memory features. Second, we extensively outlined a new set of semantic production norms collected from Italian native speakers for 120 artifactual and natural basic-level concepts, using numerous measures and statistics following a feature-listing task (Exp. 3b). Finally, we aimed to create a new publicly accessible database, since only a few existing databases are publicly available online.

Giant axonal neuropathy-like disease in an Alexandrine parrot (Psittacula eupatria).

PubMed

Stent, Andrew; Gosbell, Matthew; Tatarczuch, Liliana; Summers, Brian A

2015-09-01

A chronic progressive neurological condition in an Alexandrine parrot (Psittacula eupatria) was manifest as intention tremors, incoordination, and seizure activity. Histology revealed large eosinophilic bodies throughout the central nervous system, and electron microscopy demonstrated that these bodies were greatly expanded axons distended by short filamentous structures that aggregated to form long strands. The presence of periodic acid-Schiff-positive material within the neuronal bodies of Purkinje cells and ganglionic neurons is another distinctive feature of this disease. The histological features of this case display some features consistent with giant axonal neuropathy as reported in humans and dogs. Based on investigation of the lineage in this case, an underlying inherited defect is suspected, but some additional factor appears to have altered the specific disease presentation in this bird. © 2015 The Author(s).

The mitochondrial genomes of Campodea fragilis and C. lubbocki(Hexapoda: Diplura): high genetic divergence in a morphologically uniformtaxon

DOE Office of Scientific and Technical Information (OSTI.GOV)

Podsiadlowski, L.; Carapelli, A.; Nardi, F.

2005-12-01

Mitochondrial genomes from two dipluran hexapods of the genus Campodea have been sequenced. Gene order is the same as in most other hexapods and crustaceans. Secondary structures of tRNAs reveal specific structural changes in tRNA-C, tRNA-R, tRNA-S1 and tRNA-S2. Comparative analyses of nucleotide and amino acid composition, as well as structural features of both ribosomal RNA subunits, reveal substantial differences among the analyzed taxa. Although the two Campodea species are morphologically highly uniform, genetic divergence is larger than expected, suggesting a long evolutionary history under stable ecological conditions.

A lack of Birbeck granules in Langerhans cells is associated with a naturally occurring point mutation in the human Langerin gene.

PubMed

Verdijk, Pauline; Dijkman, Remco; Plasmeijer, Elsemieke I; Mulder, Aat A; Zoutman, Willem H; Mieke Mommaas, A; Tensen, Cornelis P

2005-04-01

A heterozygous mutation in the Langerin gene corresponding to position 837 in the Langerin mRNA was identified in a person deficient in Birbeck granules (BG). This mutation results in an amino acid replacement of tryptophan by arginine at position 264 in the carbohydrate recognition domain of the Langerine protein. Expression of mutated Langerin in human fibroblasts induces tubular-like structures that are negative for BG-specific antibodies and do not resemble the characteristic structural features of BG.

Speckle contrast techniques in the study of tissue thermal modification and denaturation

NASA Astrophysics Data System (ADS)

Agafonov, Dmitry N.; Kuznetsova, Liana V.; Zimnyakov, Dmitry A.; Sviridov, Alexander P.; Omelchenko, Alexander I.

2002-05-01

Results of the contrast analysis of time-averaged dynamic speckle patterns in application to monitoring of the structure modification of the thermally treated collagenous tissue such as cartilage are presented. The modification presumably induced by the bound to free water phase transition in the matrix of the treated tissue cause the specific feature of evolution of the time-averaged speckle contrast with the change of the current temperature of modified collagen tissue. This evolution appears as hysteresis associated with irreversible changes in tissue structure.

Background and survey of bioreplication techniques.

PubMed

Pulsifer, Drew Patrick; Lakhtakia, Akhlesh

2011-09-01

Bioreplication is the direct reproduction of a biological structure in order to realize at least one specific functionality. Current bioreplication techniques include the sol-gel technique, atomic layer deposition, physical vapor deposition, and imprint lithography and casting. The combined use of a focused ion beam and a scanning electron microscope could develop into a bioreplication technique as well. Some of these techniques are more suitable for reproducing surface features, others for bulk three-dimensional structures. Industrial upscaling appears possible only for imprint lithography and casting (which can be replaced by stamping).

New crystals of the CsHSO{sub 4}–CsH{sub 2}PO{sub 4}–H{sub 2}O system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Makarova, I. P., E-mail: makarova@crys.ras.ru; Grebenev, V. V.; Komornikov, V. A.

2016-11-15

Cs{sub 6}H(HSO{sub 4}){sub 3}(H{sub 2}PO{sub 4}){sub 4} crystals, grown for the first time based on an analysis of the phase diagram of the CsHSO{sub 4}–CsH{sub 2}PO{sub 4}–H{sub 2}O ternary system, have been investigated by structural analysis using synchrotron radiation. The atomic structure of the crystals is determined and its specific features are analyzed.

Effective Moment Feature Vectors for Protein Domain Structures

PubMed Central

Shi, Jian-Yu; Yiu, Siu-Ming; Zhang, Yan-Ning; Chin, Francis Yuk-Lun

2013-01-01

Imaging processing techniques have been shown to be useful in studying protein domain structures. The idea is to represent the pairwise distances of any two residues of the structure in a 2D distance matrix (DM). Features and/or submatrices are extracted from this DM to represent a domain. Existing approaches, however, may involve a large number of features (100–400) or complicated mathematical operations. Finding fewer but more effective features is always desirable. In this paper, based on some key observations on DMs, we are able to decompose a DM image into four basic binary images, each representing the structural characteristics of a fundamental secondary structure element (SSE) or a motif in the domain. Using the concept of moments in image processing, we further derive 45 structural features based on the four binary images. Together with 4 features extracted from the basic images, we represent the structure of a domain using 49 features. We show that our feature vectors can represent domain structures effectively in terms of the following. (1) We show a higher accuracy for domain classification. (2) We show a clear and consistent distribution of domains using our proposed structural vector space. (3) We are able to cluster the domains according to our moment features and demonstrate a relationship between structural variation and functional diversity. PMID:24391828

Ordinal measures for iris recognition.

PubMed

Sun, Zhenan; Tan, Tieniu

2009-12-01

Images of a human iris contain rich texture information useful for identity authentication. A key and still open issue in iris recognition is how best to represent such textural information using a compact set of features (iris features). In this paper, we propose using ordinal measures for iris feature representation with the objective of characterizing qualitative relationships between iris regions rather than precise measurements of iris image structures. Such a representation may lose some image-specific information, but it achieves a good trade-off between distinctiveness and robustness. We show that ordinal measures are intrinsic features of iris patterns and largely invariant to illumination changes. Moreover, compactness and low computational complexity of ordinal measures enable highly efficient iris recognition. Ordinal measures are a general concept useful for image analysis and many variants can be derived for ordinal feature extraction. In this paper, we develop multilobe differential filters to compute ordinal measures with flexible intralobe and interlobe parameters such as location, scale, orientation, and distance. Experimental results on three public iris image databases demonstrate the effectiveness of the proposed ordinal feature models.

Musical emotions: predicting second-by-second subjective feelings of emotion from low-level psychoacoustic features and physiological measurements.

PubMed

Coutinho, Eduardo; Cangelosi, Angelo

2011-08-01

We sustain that the structure of affect elicited by music is largely dependent on dynamic temporal patterns in low-level music structural parameters. In support of this claim, we have previously provided evidence that spatiotemporal dynamics in psychoacoustic features resonate with two psychological dimensions of affect underlying judgments of subjective feelings: arousal and valence. In this article we extend our previous investigations in two aspects. First, we focus on the emotions experienced rather than perceived while listening to music. Second, we evaluate the extent to which peripheral feedback in music can account for the predicted emotional responses, that is, the role of physiological arousal in determining the intensity and valence of musical emotions. Akin to our previous findings, we will show that a significant part of the listeners' reported emotions can be predicted from a set of six psychoacoustic features--loudness, pitch level, pitch contour, tempo, texture, and sharpness. Furthermore, the accuracy of those predictions is improved with the inclusion of physiological cues--skin conductance and heart rate. The interdisciplinary work presented here provides a new methodology to the field of music and emotion research based on the combination of computational and experimental work, which aid the analysis of the emotional responses to music, while offering a platform for the abstract representation of those complex relationships. Future developments may aid specific areas, such as, psychology and music therapy, by providing coherent descriptions of the emotional effects of specific music stimuli. 2011 APA, all rights reserved

Co-Conserved MAPK Features Couple D-Domain Docking Groove to Distal Allosteric Sites via the C-Terminal Flanking Tail

PubMed Central

Nguyen, Tuan; Ruan, Zheng; Oruganty, Krishnadev; Kannan, Natarajan

2015-01-01

Mitogen activated protein kinases (MAPKs) form a closely related family of kinases that control critical pathways associated with cell growth and survival. Although MAPKs have been extensively characterized at the biochemical, cellular, and structural level, an integrated evolutionary understanding of how MAPKs differ from other closely related protein kinases is currently lacking. Here, we perform statistical sequence comparisons of MAPKs and related protein kinases to identify sequence and structural features associated with MAPK functional divergence. We show, for the first time, that virtually all MAPK-distinguishing sequence features, including an unappreciated short insert segment in the β4-β5 loop, physically couple distal functional sites in the kinase domain to the D-domain peptide docking groove via the C-terminal flanking tail (C-tail). The coupling mediated by MAPK-specific residues confers an allosteric regulatory mechanism unique to MAPKs. In particular, the regulatory αC-helix conformation is controlled by a MAPK-conserved salt bridge interaction between an arginine in the αC-helix and an acidic residue in the C-tail. The salt-bridge interaction is modulated in unique ways in individual sub-families to achieve regulatory specificity. Our study is consistent with a model in which the C-tail co-evolved with the D-domain docking site to allosterically control MAPK activity. Our study provides testable mechanistic hypotheses for biochemical characterization of MAPK-conserved residues and new avenues for the design of allosteric MAPK inhibitors. PMID:25799139

Sequence-specific bias correction for RNA-seq data using recurrent neural networks.

PubMed

Zhang, Yao-Zhong; Yamaguchi, Rui; Imoto, Seiya; Miyano, Satoru

2017-01-25

The recent success of deep learning techniques in machine learning and artificial intelligence has stimulated a great deal of interest among bioinformaticians, who now wish to bring the power of deep learning to bare on a host of bioinformatical problems. Deep learning is ideally suited for biological problems that require automatic or hierarchical feature representation for biological data when prior knowledge is limited. In this work, we address the sequence-specific bias correction problem for RNA-seq data redusing Recurrent Neural Networks (RNNs) to model nucleotide sequences without pre-determining sequence structures. The sequence-specific bias of a read is then calculated based on the sequence probabilities estimated by RNNs, and used in the estimation of gene abundance. We explore the application of two popular RNN recurrent units for this task and demonstrate that RNN-based approaches provide a flexible way to model nucleotide sequences without knowledge of predetermined sequence structures. Our experiments show that training a RNN-based nucleotide sequence model is efficient and RNN-based bias correction methods compare well with the-state-of-the-art sequence-specific bias correction method on the commonly used MAQC-III data set. RNNs provides an alternative and flexible way to calculate sequence-specific bias without explicitly pre-determining sequence structures.

Automated detection of retinal whitening in malarial retinopathy

NASA Astrophysics Data System (ADS)

Joshi, V.; Agurto, C.; Barriga, S.; Nemeth, S.; Soliz, P.; MacCormick, I.; Taylor, T.; Lewallen, S.; Harding, S.

2016-03-01

Cerebral malaria (CM) is a severe neurological complication associated with malarial infection. Malaria affects approximately 200 million people worldwide, and claims 600,000 lives annually, 75% of whom are African children under five years of age. Because most of these mortalities are caused by the high incidence of CM misdiagnosis, there is a need for an accurate diagnostic to confirm the presence of CM. The retinal lesions associated with malarial retinopathy (MR) such as retinal whitening, vessel discoloration, and hemorrhages, are highly specific to CM, and their detection can improve the accuracy of CM diagnosis. This paper will focus on development of an automated method for the detection of retinal whitening which is a unique sign of MR that manifests due to retinal ischemia resulting from CM. We propose to detect the whitening region in retinal color images based on multiple color and textural features. First, we preprocess the image using color and textural features of the CMYK and CIE-XYZ color spaces to minimize camera reflex. Next, we utilize color features of the HSL, CMYK, and CIE-XYZ channels, along with the structural features of difference of Gaussians. A watershed segmentation algorithm is used to assign each image region a probability of being inside the whitening, based on extracted features. The algorithm was applied to a dataset of 54 images (40 with whitening and 14 controls) that resulted in an image-based (binary) classification with an AUC of 0.80. This provides 88% sensitivity at a specificity of 65%. For a clinical application that requires a high specificity setting, the algorithm can be tuned to a specificity of 89% at a sensitivity of 82%. This is the first published method for retinal whitening detection and combining it with the detection methods for vessel discoloration and hemorrhages can further improve the detection accuracy for malarial retinopathy.

Sequence Based Prediction of Antioxidant Proteins Using a Classifier Selection Strategy

PubMed Central

Zhang, Lina; Zhang, Chengjin; Gao, Rui; Yang, Runtao; Song, Qing

2016-01-01

Antioxidant proteins perform significant functions in maintaining oxidation/antioxidation balance and have potential therapies for some diseases. Accurate identification of antioxidant proteins could contribute to revealing physiological processes of oxidation/antioxidation balance and developing novel antioxidation-based drugs. In this study, an ensemble method is presented to predict antioxidant proteins with hybrid features, incorporating SSI (Secondary Structure Information), PSSM (Position Specific Scoring Matrix), RSA (Relative Solvent Accessibility), and CTD (Composition, Transition, Distribution). The prediction results of the ensemble predictor are determined by an average of prediction results of multiple base classifiers. Based on a classifier selection strategy, we obtain an optimal ensemble classifier composed of RF (Random Forest), SMO (Sequential Minimal Optimization), NNA (Nearest Neighbor Algorithm), and J48 with an accuracy of 0.925. A Relief combined with IFS (Incremental Feature Selection) method is adopted to obtain optimal features from hybrid features. With the optimal features, the ensemble method achieves improved performance with a sensitivity of 0.95, a specificity of 0.93, an accuracy of 0.94, and an MCC (Matthew’s Correlation Coefficient) of 0.880, far better than the existing method. To evaluate the prediction performance objectively, the proposed method is compared with existing methods on the same independent testing dataset. Encouragingly, our method performs better than previous studies. In addition, our method achieves more balanced performance with a sensitivity of 0.878 and a specificity of 0.860. These results suggest that the proposed ensemble method can be a potential candidate for antioxidant protein prediction. For public access, we develop a user-friendly web server for antioxidant protein identification that is freely accessible at http://antioxidant.weka.cc. PMID:27662651

Hierarchical Multi-atlas Label Fusion with Multi-scale Feature Representation and Label-specific Patch Partition

PubMed Central

Wu, Guorong; Kim, Minjeong; Sanroma, Gerard; Wang, Qian; Munsell, Brent C.; Shen, Dinggang

2014-01-01

Multi-atlas patch-based label fusion methods have been successfully used to improve segmentation accuracy in many important medical image analysis applications. In general, to achieve label fusion a single target image is first registered to several atlas images, after registration a label is assigned to each target point in the target image by determining the similarity between the underlying target image patch (centered at the target point) and the aligned image patch in each atlas image. To achieve the highest level of accuracy during the label fusion process it’s critical the chosen patch similarity measurement accurately captures the tissue/shape appearance of the anatomical structure. One major limitation of existing state-of-the-art label fusion methods is that they often apply a fixed size image patch throughout the entire label fusion procedure. Doing so may severely affect the fidelity of the patch similarity measurement, which in turn may not adequately capture complex tissue appearance patterns expressed by the anatomical structure. To address this limitation, we advance state-of-the-art by adding three new label fusion contributions: First, each image patch now characterized by a multi-scale feature representation that encodes both local and semi-local image information. Doing so will increase the accuracy of the patch-based similarity measurement. Second, to limit the possibility of the patch-based similarity measurement being wrongly guided by the presence of multiple anatomical structures in the same image patch, each atlas image patch is further partitioned into a set of label-specific partial image patches according to the existing labels. Since image information has now been semantically divided into different patterns, these new label-specific atlas patches make the label fusion process more specific and flexible. Lastly, in order to correct target points that are mislabeled during label fusion, a hierarchically approach is used to improve the label fusion results. In particular, a coarse-to-fine iterative label fusion approach is used that gradually reduces the patch size. To evaluate the accuracy of our label fusion approach, the proposed method was used to segment the hippocampus in the ADNI dataset and 7.0 tesla MR images, sub-cortical regions in LONI LBPA40 dataset, mid-brain regions in SATA dataset from MICCAI 2013 segmentation challenge, and a set of key internal gray matter structures in IXI dataset. In all experiments, the segmentation results of the proposed hierarchical label fusion method with multi-scale feature representations and label-specific atlas patches are more accurate than several well-known state-of-the-art label fusion methods. PMID:25463474

Deep Learning in Medical Image Analysis

PubMed Central

Shen, Dinggang; Wu, Guorong; Suk, Heung-Il

2016-01-01

The computer-assisted analysis for better interpreting images have been longstanding issues in the medical imaging field. On the image-understanding front, recent advances in machine learning, especially, in the way of deep learning, have made a big leap to help identify, classify, and quantify patterns in medical images. Specifically, exploiting hierarchical feature representations learned solely from data, instead of handcrafted features mostly designed based on domain-specific knowledge, lies at the core of the advances. In that way, deep learning is rapidly proving to be the state-of-the-art foundation, achieving enhanced performances in various medical applications. In this article, we introduce the fundamentals of deep learning methods; review their successes to image registration, anatomical/cell structures detection, tissue segmentation, computer-aided disease diagnosis or prognosis, and so on. We conclude by raising research issues and suggesting future directions for further improvements. PMID:28301734

Histological features of the vomeronasal organ in the giraffe, Giraffa camelopardalis.

PubMed

Kondoh, Daisuke; Nakamura, Kentaro G; Ono, Yurie S; Yuhara, Kazutoshi; Bando, Gen; Watanabe, Kenichi; Horiuchi, Noriyuki; Kobayashi, Yoshiyasu; Sasaki, Motoki; Kitamura, Nobuo

2017-06-01

The vomeronasal organ (VNO) that preferentially detects species-specific substances is diverse among animal species, and its morphological properties seem to reflect the ecological features of animals. This histological study of two female reticulated giraffes (Giraffa camelopardalis reticulata) found that the VNO is developed in giraffes. The lateral and medial regions of the vomeronasal lumen were covered with sensory and nonsensory epithelia, respectively. The vomeronasal glands were positive for periodic acid-Schiff and alcian blue (pH 2.5) stains. The VNO comprises several large veins like others in the order Cetartiodactyla, suggesting that these veins function in a pumping mechanism in this order. In addition, numerous thin-walled vessels located immediately beneath the epithelia covering the lumen entirely surrounded the vomeronasal lumen. This sponge-like structure might function as a specific secondary pump in giraffes. © 2017 Wiley Periodicals, Inc.

Neuron-specific enolase levels in drug-naïve young adults with major depressive disorder.

PubMed

Wiener, Carolina David; Molina, Mariane Lopez; Passos, Miguel; Moreira, Fernanda Pedrotti; Bittencourt, Guilherme; de Mattos Souza, Luciano Dias; da Silva, Ricardo Azevedo; Jansen, Karen; Oses, Jean Pierre

2016-05-04

The aim of this study is to assess neuron-specific enolase (NSE) levels and clinical features in subjects with major depressive disorder (MDD). This is a cross-sectional study with drug-naïve young adults with MDD (aged 18-29 years). Serum levels of NSE were assessed using the electrochemiluminescence method. MDD diagnosis, suicidal ideation, and time of disease were assessed using the Structured Clinical Interview for DSM-IV (SCID). The Hamilton Depression Rating Scale (HDRS) and Hamilton Anxiety Rating Scale (HARS) were used to assess depressive and anxiety symptoms. No relationship was observed between NSE levels and severity of depressive and anxiety symptoms, time of disease, and suicidal ideation. These results suggest that NSE serum levels were not associated with clinical features of MDD among drug-naïve young adults. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

[The age-specific features of palm dermatoglyphics in the adults subjects].

PubMed

Teplov, K V; Bozhchenko, A P; Tolmachev, I A; Moiseenko, S A

2016-01-01

This article was designed to consider the congenital age-specific features of palm dermatoglyphics in the adults subjects (including the type of the papillary patterns, axial tri-radii, the termini of palmar main lines, the rudiments of palmar lines, the dermatoglyphic ridge count between the stable anatomical structures). The objective of the study was to look for the new diagnostic markers of the biological age. It included the identification of the palm prints obtained from 180 Caucasoid men and 120 women at the age varying from 16 to 80 years. The results of the mathematical and statistical analysis provided the basis for drawing up the list of 18 attributes of palm dermatoglyphics significantly (p<0.05) differing in the frequency of occurrence between the representatives of individual age groups. The methods are proposed allowing to use these findings for the expert evaluation of the age of unknown subjects.

Identification of input variables for feature based artificial neural networks-saccade detection in EOG recordings.

PubMed

Tigges, P; Kathmann, N; Engel, R R

1997-07-01

Though artificial neural networks (ANN) are excellent tools for pattern recognition problems when signal to noise ratio is low, the identification of decision relevant features for ANN input data is still a crucial issue. The experience of the ANN designer and the existing knowledge and understanding of the problem seem to be the only links for a specific construction. In the present study a backpropagation ANN based on modified raw data inputs showed encouraging results. Investigating the specific influences of prototypical input patterns on a specially designed ANN led to a new sparse and efficient input data presentation. This data coding obtained by a semiautomatic procedure combining existing expert knowledge and the internal representation structures of the raw data based ANN yielded a list of feature vectors, each representing the relevant information for saccade identification. The feature based ANN produced a reduction of the error rate of nearly 40% compared with the raw data ANN. An overall correct classification of 92% of so far unknown data was realized. The proposed method of extracting internal ANN knowledge for the production of a better input data representation is not restricted to EOG recordings, and could be used in various fields of signal analysis.

Laser-induced patterns on metals and polymers for biomimetic surface engineering

NASA Astrophysics Data System (ADS)

Kietzig, Anne-Marie; Lehr, Jorge; Matus, Luke; Liang, Fang

2014-03-01

One common feature of many functional surfaces found in nature is their modular composition often exhibiting several length scales. Prominent natural examples for extreme behaviors can be named in various plant leaf (rose, peanut, lotus) or animal toe surfaces (Gecko, tree frog). Influence factors of interest are the surface's chemical composition, its microstructure, its organized or random roughness and hence the resulting surface wetting and adhesion character. Femtosecond (fs) laser micromachining offers a possibility to render all these factors in one single processing step on metallic and polymeric surfaces. Exemplarily, studies on Titanium and PTFE are shown, where the dependence of the resulting feature sizes on lasing intensity is investigated. While Ti surfaces show rigid surface patterns of micrometer scaled features with superimposed nanostructures, PTFE exhibits elastic hairy structures of nanometric diameter, which upon a certain threshold tend to bundle to larger features. Both surface patterns can be adjusted to mimic specific wetting and flow behaviour as seen on natural examples. Therefore, fs-laser micromachining is suggested as an interesting industrially scalable technique to pattern and fine-tune the surface wettability of a surface to the desired extends in one process step. Possible applications can be seen with surfaces, which require specific wetting, fouling, icing, friction or cell adhesion behaviour.

Crystal Structure of Human Dual-Specificity Tyrosine-Regulated Kinase 3 Reveals New Structural Features and Insights into its Auto-phosphorylation.

PubMed

Kim, Kuglae; Cha, Jeong Seok; Cho, Yong-Soon; Kim, Hoyoung; Chang, Nienping; Kim, Hye-Jung; Cho, Hyun-Soo

2018-05-11

Dual-specificity tyrosine-regulated kinases (DYRKs) auto-phosphorylate a critical tyrosine residue in their activation loop and phosphorylate their substrate on serine and threonine residues. The auto-phosphorylation occurs intramolecularly and is a one-off event. DYRK3 is selectively expressed at a high level in hematopoietic cells and attenuates erythroblast development, leading to anemia. In the present study, we determined the crystal structure of the mature form of human DYRK3 in complex with harmine, an ATP competitive inhibitor. The crystal structure revealed a phosphorylation site, residue S350, whose phosphorylation increases the stability of DYRK3 and enhances its kinase activity. In addition, our structural and biochemical assays suggest that the N-terminal auto-phosphorylation accessory domain stabilizes the DYRK3 protein, followed by auto-phosphorylation of the tyrosine of the activation loop, which is important for kinase activity. Finally, our docking analysis provides information for the design of novel and potent therapeutics to treat anemia. Copyright © 2018 Elsevier Ltd. All rights reserved.

The Thiamine-Pyrophosphate-Motif

NASA Technical Reports Server (NTRS)

Ciszak, Ewa; Dominiak, Paulina

2004-01-01

Thiamin pyrophosphate (TPP), a derivative of vitamin B1, is a cofactor for enzymes performing catalysis in pathways of energy production including the well known decarboxylation of a-keto acid dehydrogenases followed by transketolation. TPP-dependent enzymes constitute a structurally and functionally diverse group exhibiting multimeric subunit organization, multiple domains and two chemically equivalent catalytic centers. Annotation of functional TPP-dependcnt enzymes, therefore, has not been trivial due to low sequence similarity related to this complex organization. Our approach to analysis of structures of known TPP-dependent enzymes reveals for the first time features common to this group, which we have termed the TPP-motif. The TPP-motif consists of specific spatial arrangements of structural elements and their specific contacts to provide for a flip-flop, or alternate site, enzymatic mechanism of action. Analysis of structural elements entrained in the flip-flop action displayed by TPP-dependent enzymes reveals a novel definition of the common amino acid sequences. These sequences allow for annotation of TPP-dependent enzymes, thus advancing functional proteomics. Further details of three-dimensional structures of TPP-dependent enzymes will be discussed.

Multiple-wavelength neutron holography with pulsed neutrons

PubMed Central

Hayashi, Kouichi; Ohoyama, Kenji; Happo, Naohisa; Matsushita, Tomohiro; Hosokawa, Shinya; Harada, Masahide; Inamura, Yasuhiro; Nitani, Hiroaki; Shishido, Toetsu; Yubuta, Kunio

2017-01-01

Local structures around impurities in solids provide important information for understanding the mechanisms of material functions, because most of them are controlled by dopants. For this purpose, the x-ray absorption fine structure method, which provides radial distribution functions around specific elements, is most widely used. However, a similar method using neutron techniques has not yet been developed. If one can establish a method of local structural analysis with neutrons, then a new frontier of materials science can be explored owing to the specific nature of neutron scattering—that is, its high sensitivity to light elements and magnetic moments. Multiple-wavelength neutron holography using the time-of-flight technique with pulsed neutrons has great potential to realize this. We demonstrated multiple-wavelength neutron holography using a Eu-doped CaF2 single crystal and obtained a clear three-dimensional atomic image around trivalent Eu substituted for divalent Ca, revealing an interesting feature of the local structure that allows it to maintain charge neutrality. The new holography technique is expected to provide new information on local structures using the neutron technique. PMID:28835917

Structural Influence on the Dominance of Virus-Specific CD4 T Cell Epitopes in Zika Virus Infection.

PubMed

Koblischke, Maximilian; Stiasny, Karin; Aberle, Stephan W; Malafa, Stefan; Tschouchnikas, Georgios; Schwaiger, Julia; Kundi, Michael; Heinz, Franz X; Aberle, Judith H

2018-01-01

Zika virus (ZIKV) has recently caused explosive outbreaks in Pacific islands, South- and Central America. Like with other flaviviruses, protective immunity is strongly dependent on potently neutralizing antibodies (Abs) directed against the viral envelope protein E. Such Ab formation is promoted by CD4 T cells through direct interaction with B cells that present epitopes derived from E or other structural proteins of the virus. Here, we examined the extent and epitope dominance of CD4 T cell responses to capsid (C) and envelope proteins in Zika patients. All patients developed ZIKV-specific CD4 T cell responses, with substantial contributions of C and E. In both proteins, immunodominant epitopes clustered at sites that are structurally conserved among flaviviruses but have highly variable sequences, suggesting a strong impact of protein structural features on immunodominant CD4 T cell responses. Our data are particularly relevant for designing flavivirus vaccines and their evaluation in T cell assays and provide insights into the importance of viral protein structure for epitope selection and antigenicity.

First principles examination of electronic structure and optical features of 4H-GaN1-xPx polytype alloys

NASA Astrophysics Data System (ADS)

Laref, A.; Hussain, Z.; Laref, S.; Yang, J. T.; Xiong, Y. C.; Luo, S. J.

2018-04-01

By using first-principles calculations, we compute the electronic band structures and typical aspects of the optical spectra of hexagonally structured GaN1-xPx alloys. Although a type III-V semiconductor, GaP commonly possesses a zinc-blende structure with an indirect band gap; as such, it may additionally form hexagonal polytypes under specific growth conditions. The electronic structures and optical properties are calculated by combining a non-nitride III-V semiconductor and a nitride III-V semiconductor, as GaP and GaN crystallizing in a 4H polytype, with the N composition ranging between x = 0-1. For all studied materials, the energy gap is found to be direct. The optical properties of the hexagonal materials may illustrate the strong polarization dependence owing to the crystalline anisotropy. This investigation for GaN1-xPx alloys is anticipated to supply paramount information for applications in the visible/ultraviolet spectral regions. At a specific concentration, x, these alloys would be exclusively appealing candidates for solar-cell applications.

Multiple-wavelength neutron holography with pulsed neutrons.

PubMed

Hayashi, Kouichi; Ohoyama, Kenji; Happo, Naohisa; Matsushita, Tomohiro; Hosokawa, Shinya; Harada, Masahide; Inamura, Yasuhiro; Nitani, Hiroaki; Shishido, Toetsu; Yubuta, Kunio

2017-08-01

Local structures around impurities in solids provide important information for understanding the mechanisms of material functions, because most of them are controlled by dopants. For this purpose, the x-ray absorption fine structure method, which provides radial distribution functions around specific elements, is most widely used. However, a similar method using neutron techniques has not yet been developed. If one can establish a method of local structural analysis with neutrons, then a new frontier of materials science can be explored owing to the specific nature of neutron scattering-that is, its high sensitivity to light elements and magnetic moments. Multiple-wavelength neutron holography using the time-of-flight technique with pulsed neutrons has great potential to realize this. We demonstrated multiple-wavelength neutron holography using a Eu-doped CaF 2 single crystal and obtained a clear three-dimensional atomic image around trivalent Eu substituted for divalent Ca, revealing an interesting feature of the local structure that allows it to maintain charge neutrality. The new holography technique is expected to provide new information on local structures using the neutron technique.

Luminescence studies of HgCdTe- and InAsSb-based quantum-well structures

NASA Astrophysics Data System (ADS)

Izhnin, I. I.; Izhnin, A. I.; Fitsych, O. I.; Voitsekhovskii, A. V.; Gorn, D. I.; Semakova, A. A.; Bazhenov, N. L.; Mynbaev, K. D.; Zegrya, G. G.

2018-04-01

Results of photoluminescence studies of single-quantum-well HgCdTe-based structures and electroluminescence studies of multiple-quantum-well InAsSb-based structures are reported. HgCdTe structures were grown with molecular beam epitaxy on GaAs substrates. InAsSb-based structures were grown with metal-organic chemical vapor deposition on InAs substrates. The common feature of luminescence spectra of all the structures was the presence of peaks with the energy much larger than that of calculated optical transitions between the first quantization levels for electrons and heavy holes. Possibility of observation of optical transitions between the quantization levels of electrons and first and/or second heavy and light hole levels is discussed in the paper in relation to the specifics of the electronic structure of the materials under consideration.

Mediastinal lymph node detection and station mapping on chest CT using spatial priors and random forest

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Jiamin; Hoffman, Joanne; Zhao, Jocelyn

2016-07-15

Purpose: To develop an automated system for mediastinal lymph node detection and station mapping for chest CT. Methods: The contextual organs, trachea, lungs, and spine are first automatically identified to locate the region of interest (ROI) (mediastinum). The authors employ shape features derived from Hessian analysis, local object scale, and circular transformation that are computed per voxel in the ROI. Eight more anatomical structures are simultaneously segmented by multiatlas label fusion. Spatial priors are defined as the relative multidimensional distance vectors corresponding to each structure. Intensity, shape, and spatial prior features are integrated and parsed by a random forest classifiermore » for lymph node detection. The detected candidates are then segmented by the following curve evolution process. Texture features are computed on the segmented lymph nodes and a support vector machine committee is used for final classification. For lymph node station labeling, based on the segmentation results of the above anatomical structures, the textual definitions of mediastinal lymph node map according to the International Association for the Study of Lung Cancer are converted into patient-specific color-coded CT image, where the lymph node station can be automatically assigned for each detected node. Results: The chest CT volumes from 70 patients with 316 enlarged mediastinal lymph nodes are used for validation. For lymph node detection, their system achieves 88% sensitivity at eight false positives per patient. For lymph node station labeling, 84.5% of lymph nodes are correctly assigned to their stations. Conclusions: Multiple-channel shape, intensity, and spatial prior features aggregated by a random forest classifier improve mediastinal lymph node detection on chest CT. Using the location information of segmented anatomic structures from the multiatlas formulation enables accurate identification of lymph node stations.« less

Structure of the Human Protein Kinase ZAK in Complex with Vemurafenib

PubMed Central

Mathea, Sebastian; Abdul Azeez, Kamal R.; Salah, Eidarus; Tallant, Cynthia; Wolfreys, Finn; Konietzny, Rebecca; Fischer, Roman; Lou, Hua Jane; Brennan, Paul E.; Schnapp, Gisela; Pautsch, Alexander; Kessler, Benedikt M.; Turk, Benjamin E.; Knapp, Stefan

2017-01-01

The mixed lineage kinase ZAK is a key regulator of the MAPK pathway mediating cell survival and inflammatory response. ZAK is targeted by several clinically approved kinase inhibitors, and inhibition of ZAK has been reported to protect from doxorubicin-induced cardiomyopathy. On the other hand, unintended targeting of ZAK has been linked to severe adverse effects such as the development of cutaneous squamous cell carcinoma. Therefore, both specific inhibitors of ZAK, as well as anticancer drugs lacking off-target activity against ZAK, may provide therapeutic benefit. Here we report the first crystal structure of ZAK in complex with the B-RAF inhibitor vemurafenib. The co-crystal structure displayed a number of ZAK-specific features including a highly distorted P loop conformation enabling rational inhibitor design. Positional scanning peptide library analysis revealed a unique substrate specificity of the ZAK kinase including unprecedented preferences for histidine residues at positions −1 and +2 relative to the phosphoacceptor site. In addition, we screened a library of clinical kinase inhibitors identifying several inhibitors that potently inhibit ZAK, demonstrating that this kinase is commonly mistargeted by currently used anticancer drugs. PMID:26999302

A feature refinement approach for statistical interior CT reconstruction

NASA Astrophysics Data System (ADS)

Hu, Zhanli; Zhang, Yunwan; Liu, Jianbo; Ma, Jianhua; Zheng, Hairong; Liang, Dong

2016-07-01

Interior tomography is clinically desired to reduce the radiation dose rendered to patients. In this work, a new statistical interior tomography approach for computed tomography is proposed. The developed design focuses on taking into account the statistical nature of local projection data and recovering fine structures which are lost in the conventional total-variation (TV)—minimization reconstruction. The proposed method falls within the compressed sensing framework of TV minimization, which only assumes that the interior ROI is piecewise constant or polynomial and does not need any additional prior knowledge. To integrate the statistical distribution property of projection data, the objective function is built under the criteria of penalized weighed least-square (PWLS-TV). In the implementation of the proposed method, the interior projection extrapolation based FBP reconstruction is first used as the initial guess to mitigate truncation artifacts and also provide an extended field-of-view. Moreover, an interior feature refinement step, as an important processing operation is performed after each iteration of PWLS-TV to recover the desired structure information which is lost during the TV minimization. Here, a feature descriptor is specifically designed and employed to distinguish structure from noise and noise-like artifacts. A modified steepest descent algorithm is adopted to minimize the associated objective function. The proposed method is applied to both digital phantom and in vivo Micro-CT datasets, and compared to FBP, ART-TV and PWLS-TV. The reconstruction results demonstrate that the proposed method performs better than other conventional methods in suppressing noise, reducing truncated and streak artifacts, and preserving features. The proposed approach demonstrates its potential usefulness for feature preservation of interior tomography under truncated projection measurements.

A feature refinement approach for statistical interior CT reconstruction.

PubMed

Hu, Zhanli; Zhang, Yunwan; Liu, Jianbo; Ma, Jianhua; Zheng, Hairong; Liang, Dong

2016-07-21

Interior tomography is clinically desired to reduce the radiation dose rendered to patients. In this work, a new statistical interior tomography approach for computed tomography is proposed. The developed design focuses on taking into account the statistical nature of local projection data and recovering fine structures which are lost in the conventional total-variation (TV)-minimization reconstruction. The proposed method falls within the compressed sensing framework of TV minimization, which only assumes that the interior ROI is piecewise constant or polynomial and does not need any additional prior knowledge. To integrate the statistical distribution property of projection data, the objective function is built under the criteria of penalized weighed least-square (PWLS-TV). In the implementation of the proposed method, the interior projection extrapolation based FBP reconstruction is first used as the initial guess to mitigate truncation artifacts and also provide an extended field-of-view. Moreover, an interior feature refinement step, as an important processing operation is performed after each iteration of PWLS-TV to recover the desired structure information which is lost during the TV minimization. Here, a feature descriptor is specifically designed and employed to distinguish structure from noise and noise-like artifacts. A modified steepest descent algorithm is adopted to minimize the associated objective function. The proposed method is applied to both digital phantom and in vivo Micro-CT datasets, and compared to FBP, ART-TV and PWLS-TV. The reconstruction results demonstrate that the proposed method performs better than other conventional methods in suppressing noise, reducing truncated and streak artifacts, and preserving features. The proposed approach demonstrates its potential usefulness for feature preservation of interior tomography under truncated projection measurements.

Morphological optimization for access to dual oxidants in biofilms

PubMed Central

Kempes, Christopher P.; Okegbe, Chinweike; Mears-Clarke, Zwoisaint; Follows, Michael J.; Dietrich, Lars E. P.

2014-01-01

A major theme driving research in biology is the relationship between form and function. In particular, a longstanding goal has been to understand how the evolution of multicellularity conferred fitness advantages. Here we show that biofilms of the bacterium Pseudomonas aeruginosa produce structures that maximize cellular reproduction. Specifically, we develop a mathematical model of resource availability and metabolic response within colony features. This analysis accurately predicts the measured distribution of two types of electron acceptors: oxygen, which is available from the atmosphere, and phenazines, redox-active antibiotics produced by the bacterium. Using this model, we demonstrate that the geometry of colony structures is optimal with respect to growth efficiency. Because our model is based on resource dynamics, we also can anticipate shifts in feature geometry based on changes to the availability of electron acceptors, including variations in the external availability of oxygen and genetic manipulation that renders the cells incapable of phenazine production. PMID:24335705

Support-vector-machine tree-based domain knowledge learning toward automated sports video classification

NASA Astrophysics Data System (ADS)

Xiao, Guoqiang; Jiang, Yang; Song, Gang; Jiang, Jianmin

2010-12-01

We propose a support-vector-machine (SVM) tree to hierarchically learn from domain knowledge represented by low-level features toward automatic classification of sports videos. The proposed SVM tree adopts a binary tree structure to exploit the nature of SVM's binary classification, where each internal node is a single SVM learning unit, and each external node represents the classified output type. Such a SVM tree presents a number of advantages, which include: 1. low computing cost; 2. integrated learning and classification while preserving individual SVM's learning strength; and 3. flexibility in both structure and learning modules, where different numbers of nodes and features can be added to address specific learning requirements, and various learning models can be added as individual nodes, such as neural networks, AdaBoost, hidden Markov models, dynamic Bayesian networks, etc. Experiments support that the proposed SVM tree achieves good performances in sports video classifications.

Noise-gating to Clean Astrophysical Image Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

DeForest, C. E.

I present a family of algorithms to reduce noise in astrophysical images and image sequences, preserving more information from the original data than is retained by conventional techniques. The family uses locally adaptive filters (“noise gates”) in the Fourier domain to separate coherent image structure from background noise based on the statistics of local neighborhoods in the image. Processing of solar data limited by simple shot noise or by additive noise reveals image structure not easily visible in the originals, preserves photometry of observable features, and reduces shot noise by a factor of 10 or more with little to nomore » apparent loss of resolution. This reveals faint features that were either not directly discernible or not sufficiently strongly detected for quantitative analysis. The method works best on image sequences containing related subjects, for example movies of solar evolution, but is also applicable to single images provided that there are enough pixels. The adaptive filter uses the statistical properties of noise and of local neighborhoods in the data to discriminate between coherent features and incoherent noise without reference to the specific shape or evolution of those features. The technique can potentially be modified in a straightforward way to exploit additional a priori knowledge about the functional form of the noise.« less

Noise-gating to Clean Astrophysical Image Data

NASA Astrophysics Data System (ADS)

DeForest, C. E.

2017-04-01

I present a family of algorithms to reduce noise in astrophysical images and image sequences, preserving more information from the original data than is retained by conventional techniques. The family uses locally adaptive filters (“noise gates”) in the Fourier domain to separate coherent image structure from background noise based on the statistics of local neighborhoods in the image. Processing of solar data limited by simple shot noise or by additive noise reveals image structure not easily visible in the originals, preserves photometry of observable features, and reduces shot noise by a factor of 10 or more with little to no apparent loss of resolution. This reveals faint features that were either not directly discernible or not sufficiently strongly detected for quantitative analysis. The method works best on image sequences containing related subjects, for example movies of solar evolution, but is also applicable to single images provided that there are enough pixels. The adaptive filter uses the statistical properties of noise and of local neighborhoods in the data to discriminate between coherent features and incoherent noise without reference to the specific shape or evolution of those features. The technique can potentially be modified in a straightforward way to exploit additional a priori knowledge about the functional form of the noise.

Archaeal DNA replication.

PubMed

Kelman, Lori M; Kelman, Zvi

2014-01-01

DNA replication is essential for all life forms. Although the process is fundamentally conserved in the three domains of life, bioinformatic, biochemical, structural, and genetic studies have demonstrated that the process and the proteins involved in archaeal DNA replication are more similar to those in eukaryal DNA replication than in bacterial DNA replication, but have some archaeal-specific features. The archaeal replication system, however, is not monolithic, and there are some differences in the replication process between different species. In this review, the current knowledge of the mechanisms governing DNA replication in Archaea is summarized. The general features of the replication process as well as some of the differences are discussed.

Structural comparison of lipophosphoglycan from Leishmania turanica and L. major, two species transmitted by Phlebotomus papatasi.

PubMed

Volf, Petr; Nogueira, Paula M; Myskova, Jitka; Turco, Salvatore J; Soares, Rodrigo P

2014-10-01

The lipophosphoglycan (LPG) of Leishmania major has a major role in the attachment to Phlebotomus papatasi midgut. Here, we investigated the comparative structural features of LPG of L. turanica, another species transmitted by P. papatasi. The mAb WIC 79.3, specific for terminal Gal(β1,3) side-chains, strongly reacted with L. turanica LPG. In contrast, L. turanica LPG was not recognized by arabinose-specific mAb 3F12. In conclusion, LPGs from L. major and L. turanica are similar, with the latter being less arabinosylated than L. major's. The high galactose content in L. turanica LPG is consistent with its predicted recognition by P. papatasi lectin PpGalec. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Biochemical and Structural Analysis of an Eis Family Aminoglycoside Acetyltransferase from Bacillus anthracis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Green, Keith D.; Biswas, Tapan; Chang, Changsoo

Proteins from the enhanced intracellular survival (Eis) family are versatile acetyltransferases that acetylate amines at multiple positions of several aminoglycosides (AGs). Their upregulation confers drug resistance. Homologues of Eis are present in diverse bacteria, including many pathogens. Eis from Mycobacterium tuberculosis (Eis_Mtb) has been well characterized. In this study, we explored the AG specificity and catalytic efficiency of the Eis family protein from Bacillus anthracis (Eis_Ban). Kinetic analysis of specificity and catalytic efficiency of acetylation of six AGs indicates that Eis_Ban displays significant differences from Eis_Mtb in both substrate binding and catalytic efficiency. The number of acetylated amines was alsomore » different for several AGs, indicating a distinct regiospecificity of Eis_Ban. Furthermore, most recently identified inhibitors of Eis_Mtb did not inhibit Eis_Ban, underscoring the differences between these two enzymes. To explain these differences, we determined an Eis_Ban crystal structure. The comparison of the crystal structures of Eis_Ban and Eis_Mtb demonstrates that critical residues lining their respective substrate binding pockets differ substantially, explaining their distinct specificities. Our results suggest that acetyltransferases of the Eis family evolved divergently to garner distinct specificities while conserving catalytic efficiency, possibly to counter distinct chemical challenges. The unique specificity features of these enzymes can be utilized as tools for developing AGs with novel modifications and help guide specific AG treatments to avoid Eis-mediated resistance.« less

Feature-to-Feature Inference Under Conditions of Cue Restriction and Dimensional Correlation.

PubMed

Lancaster, Matthew E; Homa, Donald

2017-01-01

The present study explored feature-to-feature and label-to-feature inference in a category task for different category structures. In the correlated condition, each of the 4 dimensions comprising the category was positively correlated to each other and to the category label. In the uncorrelated condition, no correlation existed between the 4 dimensions comprising the category, although the dimension to category label correlation matched that of the correlated condition. After learning, participants made inference judgments of a missing feature, given 1, 2, or 3 feature cues; on half the trials, the category label was also included as a cue. The results showed superior inference of features following training on the correlated structure, with accurate inference when only a single feature was presented. In contrast, a single-feature cue resulted in chance levels of inference for the uncorrelated structure. Feature inference systematically improved with number of cues after training on the correlated structure. Surprisingly, a similar outcome was obtained for the uncorrelated structure, an outcome that must have reflected mediation via the category label. A descriptive model is briefly introduced to explain the results, with a suggestion that this paradigm might be profitably extended to hierarchical structures where the levels of feature-to-feature inference might vary with the depth of the hierarchy.

Novel chromatin texture features for the classification of pap smears

NASA Astrophysics Data System (ADS)

Bejnordi, Babak E.; Moshavegh, Ramin; Sujathan, K.; Malm, Patrik; Bengtsson, Ewert; Mehnert, Andrew

2013-03-01

This paper presents a set of novel structural texture features for quantifying nuclear chromatin patterns in cells on a conventional Pap smear. The features are derived from an initial segmentation of the chromatin into bloblike texture primitives. The results of a comprehensive feature selection experiment, including the set of proposed structural texture features and a range of different cytology features drawn from the literature, show that two of the four top ranking features are structural texture features. They also show that a combination of structural and conventional features yields a classification performance of 0.954±0.019 (AUC±SE) for the discrimination of normal (NILM) and abnormal (LSIL and HSIL) slides. The results of a second classification experiment, using only normal-appearing cells from both normal and abnormal slides, demonstrates that a single structural texture feature measuring chromatin margination yields a classification performance of 0.815±0.019. Overall the results demonstrate the efficacy of the proposed structural approach and that it is possible to detect malignancy associated changes (MACs) in Papanicoloau stain.

The metabotropic glutamate receptors: structure, activation mechanism and pharmacology.

PubMed

Pin, Jean-Philippe; Acher, Francine

2002-06-01

The metabotropic glutamate receptors are G-protein coupled receptors (GPCR) involved in the regulation of many synapses, including most glutamatergic fast excitatory synapses. Eight subtypes have been identified that can be classified into three groups. The molecular characterization of these receptors revealed proteins much more complex than any other GPCRs. They are composed of a Venus Flytrap (VFT) module where glutamate binds, connected to a heptahelical domain responsible for G-protein coupling. Recent data including the structure of the VFT module determined with and without glutamate, indicate that these receptors function as dimers. Moreover a number of intracellular proteins can regulate their targeting and transduction mechanism. Such structural features of mGlu receptors offer multiple possibilities for synthetic compounds to modulate their activity. In addition to agonists and competitive antagonists acting at the glutamate binding site, a number of non-competitive antagonists with inverse agonist activity, and positive allosteric modulators have been discovered. These later compounds share specific properties that make them good candidates for therapeutic applications. First, their non-amino acid structure makes them pass more easily the blood brain barrier. Second, they are much more selective than any other compound identified so far, being the first subtype selective molecules. Third, for the negative modulators, their non competitive mechanism of action makes them relatively unaffected by high concentrations of glutamate that may be present in disease states (e.g. stroke, epilepsy, neuropathic pain, etc.). Fourth, like the benzodiazepines acting at the GABA(A) receptors, the positive modulators offer a new way to increase the activity of these receptors in vivo, with a low risk of inducing their desensitization. The present review article focuses on the specific structural features of these receptors and highlights the various possibilities these offer for drug development.

Molecular modeling of class I and II alleles of the major histocompatibility complex in Salmo salar.

PubMed

Cárdenas, Constanza; Bidon-Chanal, Axel; Conejeros, Pablo; Arenas, Gloria; Marshall, Sergio; Luque, F Javier

2010-12-01

Knowledge of the 3D structure of the binding groove of major histocompatibility (MHC) molecules, which play a central role in the immune response, is crucial to shed light into the details of peptide recognition and polymorphism. This work reports molecular modeling studies aimed at providing 3D models for two class I and two class II MHC alleles from Salmo salar (Sasa), as the lack of experimental structures of fish MHC molecules represents a serious limitation to understand the specific preferences for peptide binding. The reliability of the structural models built up using bioinformatic tools was explored by means of molecular dynamics simulations of their complexes with representative peptides, and the energetics of the MHC-peptide interaction was determined by combining molecular mechanics interaction energies and implicit continuum solvation calculations. The structural models revealed the occurrence of notable differences in the nature of residues at specific positions in the binding groove not only between human and Sasa MHC proteins, but also between different Sasa alleles. Those differences lead to distinct trends in the structural features that mediate the binding of peptides to both class I and II MHC molecules, which are qualitatively reflected in the relative binding affinities. Overall, the structural models presented here are a valuable starting point to explore the interactions between MHC receptors and pathogen-specific interactions and to design vaccines against viral pathogens.

Myosin MyTH4-FERM structures highlight important principles of convergent evolution.

PubMed

Planelles-Herrero, Vicente José; Blanc, Florian; Sirigu, Serena; Sirkia, Helena; Clause, Jeffrey; Sourigues, Yannick; Johnsrud, Daniel O; Amigues, Beatrice; Cecchini, Marco; Gilbert, Susan P; Houdusse, Anne; Titus, Margaret A

2016-05-24

Myosins containing MyTH4-FERM (myosin tail homology 4-band 4.1, ezrin, radixin, moesin, or MF) domains in their tails are found in a wide range of phylogenetically divergent organisms, such as humans and the social amoeba Dictyostelium (Dd). Interestingly, evolutionarily distant MF myosins have similar roles in the extension of actin-filled membrane protrusions such as filopodia and bind to microtubules (MT), suggesting that the core functions of these MF myosins have been highly conserved over evolution. The structures of two DdMyo7 signature MF domains have been determined and comparison with mammalian MF structures reveals that characteristic features of MF domains are conserved. However, across millions of years of evolution conserved class-specific insertions are seen to alter the surfaces and the orientation of subdomains with respect to each other, likely resulting in new sites for binding partners. The MyTH4 domains of Myo10 and DdMyo7 bind to MT with micromolar affinity but, surprisingly, their MT binding sites are on opposite surfaces of the MyTH4 domain. The structural analysis in combination with comparison of diverse MF myosin sequences provides evidence that myosin tail domain features can be maintained without strict conservation of motifs. The results illustrate how tuning of existing features can give rise to new structures while preserving the general properties necessary for myosin tails. Thus, tinkering with the MF domain enables it to serve as a multifunctional platform for cooperative recruitment of various partners, allowing common properties such as autoinhibition of the motor and microtubule binding to arise through convergent evolution.

New software for statistical analysis of Cambridge Structural Database data

PubMed Central

Sykes, Richard A.; McCabe, Patrick; Allen, Frank H.; Battle, Gary M.; Bruno, Ian J.; Wood, Peter A.

2011-01-01

A collection of new software tools is presented for the analysis of geometrical, chemical and crystallographic data from the Cambridge Structural Database (CSD). This software supersedes the program Vista. The new functionality is integrated into the program Mercury in order to provide statistical, charting and plotting options alongside three-dimensional structural visualization and analysis. The integration also permits immediate access to other information about specific CSD entries through the Mercury framework, a common requirement in CSD data analyses. In addition, the new software includes a range of more advanced features focused towards structural analysis such as principal components analysis, cone-angle correction in hydrogen-bond analyses and the ability to deal with topological symmetry that may be exhibited in molecular search fragments. PMID:22477784

Data mining the PDB for glyco-related data.

PubMed

Lütteke, Thomas; von der Lieth, Claus W

2009-01-01

The 3D structural data of glycoprotein or protein-carbohydrate complexes that are found in the Protein Data Bank (PDB) are an interesting data source for glycobiologists. Unfortunately, carbohydrate components are difficult to find with the means provided by the PDB. The GLYCOSCIENCES.de internet portal offers a variety of tools and databases to locate and analyze these structures. This chapter describes how to find PDB entries that feature a specific carbohydrate structure and how to locate carbohydrate residues in a 3D structure file and to check their consistency. In addition to this, methods to statistically analyze torsion angles and the abundance of amino acids both in the neighborhood of glycosylation sites and in the spatial vicinity of non-covalently bound carbohydrate chains are summarized.

Structural investigation of the Grenville Province by radar and other imaging and nonimaging sensors

NASA Technical Reports Server (NTRS)

Lowman, P. D., Jr.; Blodget, H. W.; Webster, W. J., Jr.; Paia, S.; Singhroy, V. H.; Slaney, V. R.

1984-01-01

The structural investigation of the Canadian Shield by orbital radar and LANDSAT, is outlined. The area includes parts of the central metasedimentary belt and the Ontario gneiss belt, and major structures as well-expressed topographically. The primary objective is to apply SIR-B data to the mapping of this key part of the Grenville orogen, specifically ductile fold structures and associated features, and igneous, metamorphic, and sedimentary rock (including glacial and recent sediments). Secondary objectives are to support the Canadian RADARSAT project by evaluating the baseline parameters of a Canadian imaging radar satellite planned for late in the decade. The baseline parameters include optimum incidence and azimuth angles. The experiment is to develop techniques for the use of multiple data sets.

Subject-to-Subject Raising and the Syntax of Tense in L2 Spanish: A Full Access Approach

ERIC Educational Resources Information Center

Campos-Dintrans, Gonzalo; Pires, Acrisio; Rothman, Jason

2014-01-01

This paper investigates the acquisition of syntax in L2 grammars. We tested adult L2 speakers of Spanish (English L1) on the feature specification of T(ense), which is different in English and Spanish in so-called subject-to-subject raising structures. We present experimental results with the verb parecer "to seem/to appear" in different…

On Steady-State Tropical Cyclones

DTIC Science & Technology

2014-01-01

components of the velocity vector, specific humidity, suspended liquid water, perturbation Exner function and perturbation density potential...vorticity and spin-up function, respectively. If the flow is symmetrically stable, the partial differential equation (10) is elliptic with a forcing term...Upper-level inflow jets A prominent feature of the radial velocity component shown in Figure 2(c) is the layered structure of inflow and outflow in the

FT-Raman investigation of milled-wood lignins : softwood, hardwood, and chemically modified black spruce lignins

Treesearch

Umesh P. Agarwal; James D. McSweeny; Sally A. Ralph

2011-01-01

Raman spectroscopy is being increasingly applied to study wood and other lignin-containing biomass/biomaterials. Lignin’s contribution to the Raman spectra of such materials needs to be understood in the context of various lignin structures, substructures, and functional groups so that lignin-specific features could be identified and the spectral information could be...

Role of the Substrate Specificity-Defining Residues of Human SIRT5 in Modulating the Structural Stability and Inhibitory Features of the Enzyme.

PubMed

Yu, Junru; Haldar, Manas; Mallik, Sanku; Srivastava, D K

2016-01-01

Sirtuins are emerging as the key regulators of metabolism and aging, and their potential activators and inhibitors are being explored as therapeutics for improving health and treating associated diseases. Despite the global structural similarity among all seven isoforms of sirtuins (of which most of them catalyze the deacetylation reaction), SIRT5 is the only isoform that catalyzes the cleavage of negatively charged acylated substrates, and the latter feature appears to be encoded by the presence of Tyr102 and Arg105 residues at the active site pocket of the enzyme. To determine the contributions of the above residues in SIRT5 (vis a vis the corresponding residues of SIRT1) on substrate selectivity, inhibition by EX527 and nicotinamide, secondary structural features and thermal stability of the enzymes, we created single and double mutations (viz. Y102A, R105l, and Y102A/R105I) in SIRT5. The kinetic data revealed that while Y102A mutant enzyme catalyzed both deacetylation and desuccinylation reactions with comparable efficiencies, R105I and Y102A/R105I mutant enzymes favored the deacetylase reaction. Like SIRT1, the nicotinamide inhibition of SIRT5 double mutant (Y102A/R105I) exhibited the mixed non-competitive behavior. On the other hand, the desuccinylation reaction of both wild-type and Y102A mutant enzymes conformed to the competitive inhibition model. The inhibitory potency of EX527 progressively increased from Y102A, R105I, to Y102A/R105 mutant enzymes in SIRT5, but it did not reach to the level obtained with SIRT1. The CD spectroscopic data for the wild-type and mutant enzymes revealed changes in the secondary structural features of the enzymes, and such changes were more pronounced on examining their thermal denaturation patterns. A cumulative account of our experimental data reveal mutual cooperation between Y102 and R105 residues in promoting the desuccinylation versus deacetylation reaction in SIRT5, and the overall catalytic feature of the enzyme is manifested via the mutation induced modulation in the protein structure.

Role of the Substrate Specificity-Defining Residues of Human SIRT5 in Modulating the Structural Stability and Inhibitory Features of the Enzyme

PubMed Central

Yu, Junru; Haldar, Manas; Mallik, Sanku; Srivastava, D. K.

2016-01-01

Sirtuins are emerging as the key regulators of metabolism and aging, and their potential activators and inhibitors are being explored as therapeutics for improving health and treating associated diseases. Despite the global structural similarity among all seven isoforms of sirtuins (of which most of them catalyze the deacetylation reaction), SIRT5 is the only isoform that catalyzes the cleavage of negatively charged acylated substrates, and the latter feature appears to be encoded by the presence of Tyr102 and Arg105 residues at the active site pocket of the enzyme. To determine the contributions of the above residues in SIRT5 (vis a vis the corresponding residues of SIRT1) on substrate selectivity, inhibition by EX527 and nicotinamide, secondary structural features and thermal stability of the enzymes, we created single and double mutations (viz. Y102A, R105l, and Y102A/R105I) in SIRT5. The kinetic data revealed that while Y102A mutant enzyme catalyzed both deacetylation and desuccinylation reactions with comparable efficiencies, R105I and Y102A/R105I mutant enzymes favored the deacetylase reaction. Like SIRT1, the nicotinamide inhibition of SIRT5 double mutant (Y102A/R105I) exhibited the mixed non-competitive behavior. On the other hand, the desuccinylation reaction of both wild-type and Y102A mutant enzymes conformed to the competitive inhibition model. The inhibitory potency of EX527 progressively increased from Y102A, R105I, to Y102A/R105 mutant enzymes in SIRT5, but it did not reach to the level obtained with SIRT1. The CD spectroscopic data for the wild-type and mutant enzymes revealed changes in the secondary structural features of the enzymes, and such changes were more pronounced on examining their thermal denaturation patterns. A cumulative account of our experimental data reveal mutual cooperation between Y102 and R105 residues in promoting the desuccinylation versus deacetylation reaction in SIRT5, and the overall catalytic feature of the enzyme is manifested via the mutation induced modulation in the protein structure. PMID:27023330

Aromatic Structure in Simulates Titan Aerosol

NASA Technical Reports Server (NTRS)

Trainer, Melissa G.; Loeffler, M. J.; Anderson, C. M.; Hudson, R. L.; Samuelson, R. E.; Moore, M. A.

2011-01-01

Observations of Titan by the Cassini Composite Infrared Spectrometer (CIRS) between 560 and 20 per centimeter (approximately 18 to 500 micrometers) have been used to infer the vertical variations of Titan's ice abundances, as well as those of the aerosol from the surface to an altitude of 300 km [1]. The aerosol has a broad emission feature centered approximately at 140 per centimeter (71 micrometers). As seen in Figure 1, this feature cannot be reproduced using currently available optical constants from laboratory-generated Titan aerosol analogs [2]. The far-IR is uniquely qualified for investigating low-energy vibrational motions within the lattice structures of COITIDlex aerosol. The feature observed by CIRS is broad, and does not likely arise from individual molecules, but rather is representative of the skeletal movements of macromolecules. Since Cassini's arrival at Titan, benzene (C6H6) has been detected in the atmosphere at ppm levels as well as ions that may be polycyclic aromatic hydrocarbons (PAHs) [3]. We speculate that the feature may be a blended composite that can be identified with low-energy vibrations of two-dimensional lattice structures of large molecules, such as PAHs or nitrogenated aromatics. Such structures do not dominate the composition of analog materials generated from CH4 and N2 irradiation. We are performing studies forming aerosol analog via UV irradiation of aromatic precursors - specifically C6H6 - to understand how the unique chemical architecture of the products will influence the observable aerosol characteristics. The optical and chemical properties of the aromatic analog will be compared to those formed from CH4/N2 mixtures, with a focus on the as-yet unidentified far-IR absorbance feature. Preliminary results indicate that the photochemically-formed aromatic aerosol has distinct chemical composition, and may incorporate nitrogen either into the ring structure or adjoined chemical groups. These compositional differences are demonstrated in the aerosol mass spectra shown in Figure 2. The aromatic aerosol also demonstrates strong chemical reactivity when exposed to laboratory air, indicating substantial stored chemical potential. Oxidatoin and solubility studies wil be presented and implicatoins for prebiotic chemistry o nTitan will be discussed.

Morphologic interpretation of fertile structures in glossopterid gymnosperms

USGS Publications Warehouse

Schopf, J.M.

1976-01-01

The problem of determining affinity among glossopterid gymnosperms is beset by deficiencies in preservation, natural dissociation of parts, and scarcity of features assuredly critical for morphologic comprarison. The glossopterids probably are not a very heterogeneous group of plants, but this is difficult to prove. The Gondwana glacial "hiatus" has resulted in the omission of a critical chapter glossopterid evolution. As a consequence, morphologic features and phyletic probabilities must be evaluated on a much more hypothetical basis than would otherwise be justified. Confusion has arisen from the lack of morphologic terms that permit clear discussion of a newly evolved type of reproductive structure in glossopterids. The structure, here designated a "fertiliger", consists of a leafy bract, a partially adnate stalk, and a fertile head or capitulum. Seven types of fertile structures are discussed, all of which are bilaterally symmetrical and have different features on dorsiventral surfaces. I regard all fertiligers as ovulate but this interpretation may bot be acceptable to some workers; others may not accept dorsiventral organization of the capitulum as being fundamental. Among glossopterids, however, in spite of differences in preservation that may seem to support a variant interpretation, these ovulate fertiligers are the distinctive features that show general consistency. A single fertile bract bearing several capitula, as exemplified by Lidgettonia, is called a compound fertiliger. Staminate structures (microsporophylls) of glossopterids are separately classified as Eretmonia, Glossotheca, and possibly as other taxa. Only the manner of sporangial attachment is not entirely clear. It seems likely the staminate parts have previously been confused with scale leaves and are actually coextensive in distribution with the glossopterids. A tentative phyletic model suggests the distant derivation of glossopterids from middle Carboniferous cordaiteans. Many details must be speculative due to the lack of a pertinent fossil record, but this interpretation accounts for some features that have no counterpart in pteridosperms. Permineralized ovules from Antarctica provide general support for this working hypothesis, but specific evidence is lacking. Furthermore, it seems unlikely angiosperms originated from glossopterids; it is more reasonable to consider the glossopterids as possible distant ancestors of the Gnetales. ?? 1976.

Enhancing membrane protein subcellular localization prediction by parallel fusion of multi-view features.

PubMed

Yu, Dongjun; Wu, Xiaowei; Shen, Hongbin; Yang, Jian; Tang, Zhenmin; Qi, Yong; Yang, Jingyu

2012-12-01

Membrane proteins are encoded by ~ 30% in the genome and function importantly in the living organisms. Previous studies have revealed that membrane proteins' structures and functions show obvious cell organelle-specific properties. Hence, it is highly desired to predict membrane protein's subcellular location from the primary sequence considering the extreme difficulties of membrane protein wet-lab studies. Although many models have been developed for predicting protein subcellular locations, only a few are specific to membrane proteins. Existing prediction approaches were constructed based on statistical machine learning algorithms with serial combination of multi-view features, i.e., different feature vectors are simply serially combined to form a super feature vector. However, such simple combination of features will simultaneously increase the information redundancy that could, in turn, deteriorate the final prediction accuracy. That's why it was often found that prediction success rates in the serial super space were even lower than those in a single-view space. The purpose of this paper is investigation of a proper method for fusing multiple multi-view protein sequential features for subcellular location predictions. Instead of serial strategy, we propose a novel parallel framework for fusing multiple membrane protein multi-view attributes that will represent protein samples in complex spaces. We also proposed generalized principle component analysis (GPCA) for feature reduction purpose in the complex geometry. All the experimental results through different machine learning algorithms on benchmark membrane protein subcellular localization datasets demonstrate that the newly proposed parallel strategy outperforms the traditional serial approach. We also demonstrate the efficacy of the parallel strategy on a soluble protein subcellular localization dataset indicating the parallel technique is flexible to suite for other computational biology problems. The software and datasets are available at: http://www.csbio.sjtu.edu.cn/bioinf/mpsp.

Integrating epigenomic data and 3D genomic structure with a new measure of chromatin assortativity.

PubMed

Pancaldi, Vera; Carrillo-de-Santa-Pau, Enrique; Javierre, Biola Maria; Juan, David; Fraser, Peter; Spivakov, Mikhail; Valencia, Alfonso; Rico, Daniel

2016-07-08

Network analysis is a powerful way of modeling chromatin interactions. Assortativity is a network property used in social sciences to identify factors affecting how people establish social ties. We propose a new approach, using chromatin assortativity, to integrate the epigenomic landscape of a specific cell type with its chromatin interaction network and thus investigate which proteins or chromatin marks mediate genomic contacts. We use high-resolution promoter capture Hi-C and Hi-Cap data as well as ChIA-PET data from mouse embryonic stem cells to investigate promoter-centered chromatin interaction networks and calculate the presence of specific epigenomic features in the chromatin fragments constituting the nodes of the network. We estimate the association of these features with the topology of four chromatin interaction networks and identify features localized in connected areas of the network. Polycomb group proteins and associated histone marks are the features with the highest chromatin assortativity in promoter-centered networks. We then ask which features distinguish contacts amongst promoters from contacts between promoters and other genomic elements. We observe higher chromatin assortativity of the actively elongating form of RNA polymerase 2 (RNAPII) compared with inactive forms only in interactions between promoters and other elements. Contacts among promoters and between promoters and other elements have different characteristic epigenomic features. We identify a possible role for the elongating form of RNAPII in mediating interactions among promoters, enhancers, and transcribed gene bodies. Our approach facilitates the study of multiple genome-wide epigenomic profiles, considering network topology and allowing the comparison of chromatin interaction networks.

Perception of initial obstruent voicing is influenced by gestural organization

PubMed Central

Best, Catherine T.; Hallé, Pierre A.

2009-01-01

Cross-language differences in phonetic settings for phonological contrasts of stop voicing have posed a challenge for attempts to relate specific phonological features to specific phonetic details. We probe the phonetic-phonological relationship for voicing contrasts more broadly, analyzing in particular their relevance to nonnative speech perception, from two theoretical perspectives: feature geometry and articulatory phonology. Because these perspectives differ in assumptions about temporal/phasing relationships among features/gestures within syllable onsets, we undertook a cross-language investigation on perception of obstruent (stop, fricative) voicing contrasts in three nonnative onsets that use a common set of features/gestures but with differing time-coupling. Listeners of English and French, which differ in their phonetic settings for word-initial stop voicing distinctions, were tested on perception of three onset types, all nonnative to both English and French, that differ in how initial obstruent voicing is coordinated with a lateral feature/gesture and additional obstruent features/gestures. The targets, listed from least complex to most complex onsets, were: a lateral fricative voicing distinction (Zulu /ɬ/-ɮ/), a laterally-released affricate voicing distinction (Tlingit /tɬ/-/dɮ/), and a coronal stop voicing distinction in stop+/l/ clusters (Hebrew /tl/-/dl/). English and French listeners' performance reflected the differences in their native languages' stop voicing distinctions, compatible with prior perceptual studies on singleton consonant onsets. However, both groups' abilities to perceive voicing as a separable parameter also varied systematically with the structure of the target onsets, supporting the notion that the gestural organization of syllable onsets systematically affects perception of initial voicing distinctions. PMID:20228878

The Two-Level Theory of verb meaning: An approach to integrating the semantics of action with the mirror neuron system.

PubMed

Kemmerer, David; Gonzalez-Castillo, Javier

2010-01-01

Verbs have two separate levels of meaning. One level reflects the uniqueness of every verb and is called the "root". The other level consists of a more austere representation that is shared by all the verbs in a given class and is called the "event structure template". We explore the following hypotheses about how, with specific reference to the motor features of action verbs, these two distinct levels of semantic representation might correspond to two distinct levels of the mirror neuron system. Hypothesis 1: Root-level motor features of verb meaning are partially subserved by somatotopically mapped mirror neurons in the left primary motor and/or premotor cortices. Hypothesis 2: Template-level motor features of verb meaning are partially subserved by representationally more schematic mirror neurons in Brodmann area 44 of the left inferior frontal gyrus. Evidence has been accumulating in support of the general neuroanatomical claims made by these two hypotheses-namely, that each level of verb meaning is associated with the designated cortical areas. However, as yet no studies have satisfied all the criteria necessary to support the more specific neurobiological claims made by the two hypotheses-namely, that each level of verb meaning is associated with mirror neurons in the pertinent brain regions. This would require demonstrating that within those regions the same neuronal populations are engaged during (a) the linguistic processing of particular motor features of verb meaning, (b) the execution of actions with the corresponding motor features, and (c) the observation of actions with the corresponding motor features. 2008 Elsevier Inc. All rights reserved.

THE TWO-LEVEL THEORY OF VERB MEANING: AN APPROACH TO INTEGRATING THE SEMANTICS OF ACTION WITH THE MIRROR NEURON SYSTEM

PubMed Central

Kemmerer, David; Castillo, Javier Gonzalez

2010-01-01

Verbs have two separate levels of meaning. One level reflects the uniqueness of every verb and is called the “root.” The other level consists of a more austere representation that is shared by all the verbs in a given class and is called the “event structure template.” We explore the following hypotheses about how, with specific reference to the motor features of action verbs, these two distinct levels of semantic representation might correspond to two distinct levels of the mirror neuron system. Hypothesis 1: Root-level motor features of verb meaning are partially subserved by somatotopically mapped mirror neurons in the left primary motor and/or premotor cortices. Hypothesis 2: Template-level motor features of verb meaning are partially subserved by representationally more schematic mirror neurons in Brodmann area 44 of the left inferior frontal gyrus. Evidence has been accumulating in support of the general neuroanatomical claims made by these two hypotheses—namely, that each level of verb meaning is associated with the designated cortical areas. However, as yet no studies have satisfied all the criteria necessary to support the more specific neurobiological claims made by the two hypotheses—namely, that each level of verb meaning is associated with mirror neurons in the pertinent brain regions. This would require demonstrating that within those regions the same neuronal populations are engaged during (a) the linguistic processing of particular motor features of verb meaning, (b) the execution of actions with the corresponding motor features, and (c) the observation of actions with the corresponding motor features. PMID:18996582

Structured sparse linear graph embedding.

PubMed

Wang, Haixian

2012-03-01

Subspace learning is a core issue in pattern recognition and machine learning. Linear graph embedding (LGE) is a general framework for subspace learning. In this paper, we propose a structured sparse extension to LGE (SSLGE) by introducing a structured sparsity-inducing norm into LGE. Specifically, SSLGE casts the projection bases learning into a regression-type optimization problem, and then the structured sparsity regularization is applied to the regression coefficients. The regularization selects a subset of features and meanwhile encodes high-order information reflecting a priori structure information of the data. The SSLGE technique provides a unified framework for discovering structured sparse subspace. Computationally, by using a variational equality and the Procrustes transformation, SSLGE is efficiently solved with closed-form updates. Experimental results on face image show the effectiveness of the proposed method. Copyright © 2011 Elsevier Ltd. All rights reserved.

Revealing mesoscopic structural universality with diffusion

PubMed Central

Novikov, Dmitry S.; Jensen, Jens H.; Helpern, Joseph A.; Fieremans, Els

2014-01-01

Measuring molecular diffusion is widely used for characterizing materials and living organisms noninvasively. This characterization relies on relations between macroscopic diffusion metrics and structure at the mesoscopic scale commensurate with the diffusion length. Establishing such relations remains a fundamental challenge, hindering progress in materials science, porous media, and biomedical imaging. Here we show that the dynamical exponent in the time dependence of the diffusion coefficient distinguishes between the universality classes of the mesoscopic structural complexity. Our approach enables the interpretation of diffusion measurements by objectively selecting and modeling the most relevant structural features. As an example, the specific values of the dynamical exponent allow us to identify the relevant mesoscopic structure affecting MRI-measured water diffusion in muscles and in brain, and to elucidate the structural changes behind the decrease of diffusion coefficient in ischemic stroke. PMID:24706873