Energy-density field approach for low- and medium-frequency vibroacoustic analysis of complex structures using a statistical computational model

NASA Astrophysics Data System (ADS)

Kassem, M.; Soize, C.; Gagliardini, L.

2009-06-01

In this paper, an energy-density field approach applied to the vibroacoustic analysis of complex industrial structures in the low- and medium-frequency ranges is presented. This approach uses a statistical computational model. The analyzed system consists of an automotive vehicle structure coupled with its internal acoustic cavity. The objective of this paper is to make use of the statistical properties of the frequency response functions of the vibroacoustic system observed from previous experimental and numerical work. The frequency response functions are expressed in terms of a dimensionless matrix which is estimated using the proposed energy approach. Using this dimensionless matrix, a simplified vibroacoustic model is proposed.

Variable Neural Adaptive Robust Control: A Switched System Approach

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

Lian, Jianming; Hu, Jianghai; Zak, Stanislaw H.

2015-05-01

Variable neural adaptive robust control strategies are proposed for the output tracking control of a class of multi-input multi-output uncertain systems. The controllers incorporate a variable-structure radial basis function (RBF) network as the self-organizing approximator for unknown system dynamics. The variable-structure RBF network solves the problem of structure determination associated with fixed-structure RBF networks. It can determine the network structure on-line dynamically by adding or removing radial basis functions according to the tracking performance. The structure variation is taken into account in the stability analysis of the closed-loop system using a switched system approach with the aid of the piecewisemore » quadratic Lyapunov function. The performance of the proposed variable neural adaptive robust controllers is illustrated with simulations.« less

Visualizing and Clustering Protein Similarity Networks: Sequences, Structures, and Functions.

PubMed

Mai, Te-Lun; Hu, Geng-Ming; Chen, Chi-Ming

2016-07-01

Research in the recent decade has demonstrated the usefulness of protein network knowledge in furthering the study of molecular evolution of proteins, understanding the robustness of cells to perturbation, and annotating new protein functions. In this study, we aimed to provide a general clustering approach to visualize the sequence-structure-function relationship of protein networks, and investigate possible causes for inconsistency in the protein classifications based on sequences, structures, and functions. Such visualization of protein networks could facilitate our understanding of the overall relationship among proteins and help researchers comprehend various protein databases. As a demonstration, we clustered 1437 enzymes by their sequences and structures using the minimum span clustering (MSC) method. The general structure of this protein network was delineated at two clustering resolutions, and the second level MSC clustering was found to be highly similar to existing enzyme classifications. The clustering of these enzymes based on sequence, structure, and function information is consistent with each other. For proteases, the Jaccard's similarity coefficient is 0.86 between sequence and function classifications, 0.82 between sequence and structure classifications, and 0.78 between structure and function classifications. From our clustering results, we discussed possible examples of divergent evolution and convergent evolution of enzymes. Our clustering approach provides a panoramic view of the sequence-structure-function network of proteins, helps visualize the relation between related proteins intuitively, and is useful in predicting the structure and function of newly determined protein sequences.

Lean Middleware

NASA Technical Reports Server (NTRS)

Maluf, David A.; Bell, David g.; Ashish, Naveen

2005-01-01

This paper describes an approach to achieving data integration across multiple sources in an enterprise, in a manner that is cost efficient and economically scalable. We present an approach that does not rely on major investment in structured, heavy-weight database systems for data storage or heavy-weight middleware responsible for integrated access. The approach is centered around pushing any required data structure and semantics functionality (schema) to application clients, as well as pushing integration specification and functionality to clients where integration can be performed on-the-fly .

Mutual connectivity analysis (MCA) using generalized radial basis function neural networks for nonlinear functional connectivity network recovery in resting-state functional MRI

NASA Astrophysics Data System (ADS)

D'Souza, Adora M.; Abidin, Anas Zainul; Nagarajan, Mahesh B.; Wismüller, Axel

2016-03-01

We investigate the applicability of a computational framework, called mutual connectivity analysis (MCA), for directed functional connectivity analysis in both synthetic and resting-state functional MRI data. This framework comprises of first evaluating non-linear cross-predictability between every pair of time series prior to recovering the underlying network structure using community detection algorithms. We obtain the non-linear cross-prediction score between time series using Generalized Radial Basis Functions (GRBF) neural networks. These cross-prediction scores characterize the underlying functionally connected networks within the resting brain, which can be extracted using non-metric clustering approaches, such as the Louvain method. We first test our approach on synthetic models with known directional influence and network structure. Our method is able to capture the directional relationships between time series (with an area under the ROC curve = 0.92 +/- 0.037) as well as the underlying network structure (Rand index = 0.87 +/- 0.063) with high accuracy. Furthermore, we test this method for network recovery on resting-state fMRI data, where results are compared to the motor cortex network recovered from a motor stimulation sequence, resulting in a strong agreement between the two (Dice coefficient = 0.45). We conclude that our MCA approach is effective in analyzing non-linear directed functional connectivity and in revealing underlying functional network structure in complex systems.

Mutual Connectivity Analysis (MCA) Using Generalized Radial Basis Function Neural Networks for Nonlinear Functional Connectivity Network Recovery in Resting-State Functional MRI.

PubMed

DSouza, Adora M; Abidin, Anas Zainul; Nagarajan, Mahesh B; Wismüller, Axel

2016-03-29

We investigate the applicability of a computational framework, called mutual connectivity analysis (MCA), for directed functional connectivity analysis in both synthetic and resting-state functional MRI data. This framework comprises of first evaluating non-linear cross-predictability between every pair of time series prior to recovering the underlying network structure using community detection algorithms. We obtain the non-linear cross-prediction score between time series using Generalized Radial Basis Functions (GRBF) neural networks. These cross-prediction scores characterize the underlying functionally connected networks within the resting brain, which can be extracted using non-metric clustering approaches, such as the Louvain method. We first test our approach on synthetic models with known directional influence and network structure. Our method is able to capture the directional relationships between time series (with an area under the ROC curve = 0.92 ± 0.037) as well as the underlying network structure (Rand index = 0.87 ± 0.063) with high accuracy. Furthermore, we test this method for network recovery on resting-state fMRI data, where results are compared to the motor cortex network recovered from a motor stimulation sequence, resulting in a strong agreement between the two (Dice coefficient = 0.45). We conclude that our MCA approach is effective in analyzing non-linear directed functional connectivity and in revealing underlying functional network structure in complex systems.

Structure-Function Network Mapping and Its Assessment via Persistent Homology

PubMed Central

2017-01-01

Understanding the relationship between brain structure and function is a fundamental problem in network neuroscience. This work deals with the general method of structure-function mapping at the whole-brain level. We formulate the problem as a topological mapping of structure-function connectivity via matrix function, and find a stable solution by exploiting a regularization procedure to cope with large matrices. We introduce a novel measure of network similarity based on persistent homology for assessing the quality of the network mapping, which enables a detailed comparison of network topological changes across all possible thresholds, rather than just at a single, arbitrary threshold that may not be optimal. We demonstrate that our approach can uncover the direct and indirect structural paths for predicting functional connectivity, and our network similarity measure outperforms other currently available methods. We systematically validate our approach with (1) a comparison of regularized vs. non-regularized procedures, (2) a null model of the degree-preserving random rewired structural matrix, (3) different network types (binary vs. weighted matrices), and (4) different brain parcellation schemes (low vs. high resolutions). Finally, we evaluate the scalability of our method with relatively large matrices (2514x2514) of structural and functional connectivity obtained from 12 healthy human subjects measured non-invasively while at rest. Our results reveal a nonlinear structure-function relationship, suggesting that the resting-state functional connectivity depends on direct structural connections, as well as relatively parsimonious indirect connections via polysynaptic pathways. PMID:28046127

An adaptive learning control system for large flexible structures

NASA Technical Reports Server (NTRS)

Thau, F. E.

1985-01-01

The objective of the research has been to study the design of adaptive/learning control systems for the control of large flexible structures. In the first activity an adaptive/learning control methodology for flexible space structures was investigated. The approach was based on using a modal model of the flexible structure dynamics and an output-error identification scheme to identify modal parameters. In the second activity, a least-squares identification scheme was proposed for estimating both modal parameters and modal-to-actuator and modal-to-sensor shape functions. The technique was applied to experimental data obtained from the NASA Langley beam experiment. In the third activity, a separable nonlinear least-squares approach was developed for estimating the number of excited modes, shape functions, modal parameters, and modal amplitude and velocity time functions for a flexible structure. In the final research activity, a dual-adaptive control strategy was developed for regulating the modal dynamics and identifying modal parameters of a flexible structure. A min-max approach was used for finding an input to provide modal parameter identification while not exceeding reasonable bounds on modal displacement.

Scale-Dependence of Processes Structuring Dung Beetle Metacommunities Using Functional Diversity and Community Deconstruction Approaches

PubMed Central

da Silva, Pedro Giovâni; Hernández, Malva Isabel Medina

2015-01-01

Community structure is driven by mechanisms linked to environmental, spatial and temporal processes, which have been successfully addressed using metacommunity framework. The relative importance of processes shaping community structure can be identified using several different approaches. Two approaches that are increasingly being used are functional diversity and community deconstruction. Functional diversity is measured using various indices that incorporate distinct community attributes. Community deconstruction is a way to disentangle species responses to ecological processes by grouping species with similar traits. We used these two approaches to determine whether they are improvements over traditional measures (e.g., species composition, abundance, biomass) for identification of the main processes driving dung beetle (Scarabaeinae) community structure in a fragmented mainland-island landscape in southern Brazilian Atlantic Forest. We sampled five sites in each of four large forest areas, two on the mainland and two on the island. Sampling was performed in 2012 and 2013. We collected abundance and biomass data from 100 sampling points distributed over 20 sampling sites. We studied environmental, spatial and temporal effects on dung beetle community across three spatial scales, i.e., between sites, between areas and mainland-island. The γ-diversity based on species abundance was mainly attributed to β-diversity as a consequence of the increase in mean α- and β-diversity between areas. Variation partitioning on abundance, biomass and functional diversity showed scale-dependence of processes structuring dung beetle metacommunities. We identified two major groups of responses among 17 functional groups. In general, environmental filters were important at both local and regional scales. Spatial factors were important at the intermediate scale. Our study supports the notion of scale-dependence of environmental, spatial and temporal processes in the distribution and functional organization of Scarabaeinae beetles. We conclude that functional diversity may be used as a complementary approach to traditional measures, and that community deconstruction allows sufficient disentangling of responses of different trait-based groups. PMID:25822150

Dissecting protein loops with a statistical scalpel suggests a functional implication of some structural motifs.

PubMed

Regad, Leslie; Martin, Juliette; Camproux, Anne-Claude

2011-06-20

One of the strategies for protein function annotation is to search particular structural motifs that are known to be shared by proteins with a given function. Here, we present a systematic extraction of structural motifs of seven residues from protein loops and we explore their correspondence with functional sites. Our approach is based on the structural alphabet HMM-SA (Hidden Markov Model - Structural Alphabet), which allows simplification of protein structures into uni-dimensional sequences, and advanced pattern statistics adapted to short sequences. Structural motifs of interest are selected by looking for structural motifs significantly over-represented in SCOP superfamilies in protein loops. We discovered two types of structural motifs significantly over-represented in SCOP superfamilies: (i) ubiquitous motifs, shared by several superfamilies and (ii) superfamily-specific motifs, over-represented in few superfamilies. A comparison of ubiquitous words with known small structural motifs shows that they contain well-described motifs as turn, niche or nest motifs. A comparison between superfamily-specific motifs and biological annotations of Swiss-Prot reveals that some of them actually correspond to functional sites involved in the binding sites of small ligands, such as ATP/GTP, NAD(P) and SAH/SAM. Our findings show that statistical over-representation in SCOP superfamilies is linked to functional features. The detection of over-represented motifs within structures simplified by HMM-SA is therefore a promising approach for prediction of functional sites and annotation of uncharacterized proteins.

Dissecting protein loops with a statistical scalpel suggests a functional implication of some structural motifs

PubMed Central

2011-01-01

Background One of the strategies for protein function annotation is to search particular structural motifs that are known to be shared by proteins with a given function. Results Here, we present a systematic extraction of structural motifs of seven residues from protein loops and we explore their correspondence with functional sites. Our approach is based on the structural alphabet HMM-SA (Hidden Markov Model - Structural Alphabet), which allows simplification of protein structures into uni-dimensional sequences, and advanced pattern statistics adapted to short sequences. Structural motifs of interest are selected by looking for structural motifs significantly over-represented in SCOP superfamilies in protein loops. We discovered two types of structural motifs significantly over-represented in SCOP superfamilies: (i) ubiquitous motifs, shared by several superfamilies and (ii) superfamily-specific motifs, over-represented in few superfamilies. A comparison of ubiquitous words with known small structural motifs shows that they contain well-described motifs as turn, niche or nest motifs. A comparison between superfamily-specific motifs and biological annotations of Swiss-Prot reveals that some of them actually correspond to functional sites involved in the binding sites of small ligands, such as ATP/GTP, NAD(P) and SAH/SAM. Conclusions Our findings show that statistical over-representation in SCOP superfamilies is linked to functional features. The detection of over-represented motifs within structures simplified by HMM-SA is therefore a promising approach for prediction of functional sites and annotation of uncharacterized proteins. PMID:21689388

Functional Architecture of the Retina: Development and Disease

PubMed Central

Hoon, Mrinalini; Okawa, Haruhisa; Santina, Luca Della; Wong, Rachel O.L.

2014-01-01

Structure and function are highly correlated in the vertebrate retina, a sensory tissue that is organized into cell layers with microcircuits working in parallel and together to encode visual information. All vertebrate retinas share a fundamental plan, comprising five major neuronal cell classes with cell body distributions and connectivity arranged in stereotypic patterns. Conserved features in retinal design have enabled detailed analysis and comparisons of structure, connectivity and function across species. Each species, however, can adopt structural and/or functional retinal specializations, implementing variations to the basic design in order to satisfy unique requirements in visual function. Recent advances in molecular tools, imaging and electrophysiological approaches have greatly facilitated identification of the cellular and molecular mechanisms that establish the fundamental organization of the retina and the specializations of its microcircuits during development. Here, we review advances in our understanding of how these mechanisms act to shape structure and function at the single cell level, to coordinate the assembly of cell populations, and to define their specific circuitry. We also highlight how structure is rearranged and function is disrupted in disease, and discuss current approaches to re-establish the intricate functional architecture of the retina. PMID:24984227

Functional architecture of the retina: development and disease.

PubMed

Hoon, Mrinalini; Okawa, Haruhisa; Della Santina, Luca; Wong, Rachel O L

2014-09-01

Structure and function are highly correlated in the vertebrate retina, a sensory tissue that is organized into cell layers with microcircuits working in parallel and together to encode visual information. All vertebrate retinas share a fundamental plan, comprising five major neuronal cell classes with cell body distributions and connectivity arranged in stereotypic patterns. Conserved features in retinal design have enabled detailed analysis and comparisons of structure, connectivity and function across species. Each species, however, can adopt structural and/or functional retinal specializations, implementing variations to the basic design in order to satisfy unique requirements in visual function. Recent advances in molecular tools, imaging and electrophysiological approaches have greatly facilitated identification of the cellular and molecular mechanisms that establish the fundamental organization of the retina and the specializations of its microcircuits during development. Here, we review advances in our understanding of how these mechanisms act to shape structure and function at the single cell level, to coordinate the assembly of cell populations, and to define their specific circuitry. We also highlight how structure is rearranged and function is disrupted in disease, and discuss current approaches to re-establish the intricate functional architecture of the retina. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

When structure affects function--the need for partial volume effect correction in functional and resting state magnetic resonance imaging studies.

PubMed

Dukart, Juergen; Bertolino, Alessandro

2014-01-01

Both functional and also more recently resting state magnetic resonance imaging have become established tools to investigate functional brain networks. Most studies use these tools to compare different populations without controlling for potential differences in underlying brain structure which might affect the functional measurements of interest. Here, we adapt a simulation approach combined with evaluation of real resting state magnetic resonance imaging data to investigate the potential impact of partial volume effects on established functional and resting state magnetic resonance imaging analyses. We demonstrate that differences in the underlying structure lead to a significant increase in detected functional differences in both types of analyses. Largest increases in functional differences are observed for highest signal-to-noise ratios and when signal with the lowest amount of partial volume effects is compared to any other partial volume effect constellation. In real data, structural information explains about 25% of within-subject variance observed in degree centrality--an established resting state connectivity measurement. Controlling this measurement for structural information can substantially alter correlational maps obtained in group analyses. Our results question current approaches of evaluating these measurements in diseased population with known structural changes without controlling for potential differences in these measurements.

Computational approaches for drug discovery.

PubMed

Hung, Che-Lun; Chen, Chi-Chun

2014-09-01

Cellular proteins are the mediators of multiple organism functions being involved in physiological mechanisms and disease. By discovering lead compounds that affect the function of target proteins, the target diseases or physiological mechanisms can be modulated. Based on knowledge of the ligand-receptor interaction, the chemical structures of leads can be modified to improve efficacy, selectivity and reduce side effects. One rational drug design technology, which enables drug discovery based on knowledge of target structures, functional properties and mechanisms, is computer-aided drug design (CADD). The application of CADD can be cost-effective using experiments to compare predicted and actual drug activity, the results from which can used iteratively to improve compound properties. The two major CADD-based approaches are structure-based drug design, where protein structures are required, and ligand-based drug design, where ligand and ligand activities can be used to design compounds interacting with the protein structure. Approaches in structure-based drug design include docking, de novo design, fragment-based drug discovery and structure-based pharmacophore modeling. Approaches in ligand-based drug design include quantitative structure-affinity relationship and pharmacophore modeling based on ligand properties. Based on whether the structure of the receptor and its interaction with the ligand are known, different design strategies can be seed. After lead compounds are generated, the rule of five can be used to assess whether these have drug-like properties. Several quality validation methods, such as cost function analysis, Fisher's cross-validation analysis and goodness of hit test, can be used to estimate the metrics of different drug design strategies. To further improve CADD performance, multi-computers and graphics processing units may be applied to reduce costs. © 2014 Wiley Periodicals, Inc.

Predicting nucleic acid binding interfaces from structural models of proteins

PubMed Central

Dror, Iris; Shazman, Shula; Mukherjee, Srayanta; Zhang, Yang; Glaser, Fabian; Mandel-Gutfreund, Yael

2011-01-01

The function of DNA- and RNA-binding proteins can be inferred from the characterization and accurate prediction of their binding interfaces. However the main pitfall of various structure-based methods for predicting nucleic acid binding function is that they are all limited to a relatively small number of proteins for which high-resolution three dimensional structures are available. In this study, we developed a pipeline for extracting functional electrostatic patches from surfaces of protein structural models, obtained using the I-TASSER protein structure predictor. The largest positive patches are extracted from the protein surface using the patchfinder algorithm. We show that functional electrostatic patches extracted from an ensemble of structural models highly overlap the patches extracted from high-resolution structures. Furthermore, by testing our pipeline on a set of 55 known nucleic acid binding proteins for which I-TASSER produces high-quality models, we show that the method accurately identifies the nucleic acids binding interface on structural models of proteins. Employing a combined patch approach we show that patches extracted from an ensemble of models better predicts the real nucleic acid binding interfaces compared to patches extracted from independent models. Overall, these results suggest that combining information from a collection of low-resolution structural models could be a valuable approach for functional annotation. We suggest that our method will be further applicable for predicting other functional surfaces of proteins with unknown structure. PMID:22086767

An extended view of nuclear lamin structure, function, and dynamics.

PubMed

Paddy, M R; Agard, D A; Sedat, J W

1992-08-01

Molecularly-based studies of nuclear lamins have progressed at a rapid rate in the last decade. However, we still have no answer to the most important question: what are the functions of lamins? In this review we describe recent experiments which challenge traditional views of lamin function and structure. These surprising results indicate that much lamin functionality remains to be discovered, and that more global approaches to lamin structure and function are especially appropriate at this time.

Combining Formal and Functional Approaches to Topic Structure

ERIC Educational Resources Information Center

Zellers, Margaret; Post, Brechtje

2012-01-01

Fragmentation between formal and functional approaches to prosodic variation is an ongoing problem in linguistic research. In particular, the frameworks of the Phonetics of Talk-in-Interaction (PTI) and Empirical Phonology (EP) take very different theoretical and methodological approaches to this kind of variation. We argue that it is fruitful to…

Use of a structured functional evaluation process for independent medical evaluations of claimants presenting with disabling mental illness: rationale and design for a multi-center reliability study.

PubMed

Bachmann, Monica; de Boer, Wout; Schandelmaier, Stefan; Leibold, Andrea; Marelli, Renato; Jeger, Joerg; Hoffmann-Richter, Ulrike; Mager, Ralph; Schaad, Heinz; Zumbrunn, Thomas; Vogel, Nicole; Bänziger, Oskar; Busse, Jason W; Fischer, Katrin; Kunz, Regina

2016-07-29

Work capacity evaluations by independent medical experts are widely used to inform insurers whether injured or ill workers are capable of engaging in competitive employment. In many countries, evaluation processes lack a clearly structured approach, standardized instruments, and an explicit focus on claimants' functional abilities. Evaluation of subjective complaints, such as mental illness, present additional challenges in the determination of work capacity. We have therefore developed a process for functional evaluation of claimants with mental disorders which complements usual psychiatric evaluation. Here we report the design of a study to measure the reliability of our approach in determining work capacity among patients with mental illness applying for disability benefits. We will conduct a multi-center reliability study, in which 20 psychiatrists trained in our functional evaluation process will assess 30 claimants presenting with mental illness for eligibility to receive disability benefits [Reliability of Functional Evaluation in Psychiatry, RELY-study]. The functional evaluation process entails a five-step structured interview and a reporting instrument (Instrument of Functional Assessment in Psychiatry [IFAP]) to document the severity of work-related functional limitations. We will videotape all evaluations which will be viewed by three psychiatrists who will independently rate claimants' functional limitations. Our primary outcome measure is the evaluation of claimant's work capacity as a percentage (0 to 100 %), and our secondary outcomes are the 12 mental functions and 13 functional capacities assessed by the IFAP-instrument. Inter-rater reliability of four psychiatric experts will be explored using multilevel models to estimate the intraclass correlation coefficient (ICC). Additional analyses include subgroups according to mental disorder, the typicality of claimants, and claimant perceived fairness of the assessment process. We hypothesize that a structured functional approach will show moderate reliability (ICC ≥ 0.6) of psychiatric evaluation of work capacity. Enrollment of actual claimants with mental disorders referred for evaluation by disability/accident insurers will increase the external validity of our findings. Finding moderate levels of reliability, we will continue with a randomized trial to test the reliability of a structured functional approach versus evaluation-as-usual.

Towards fully automated structure-based function prediction in structural genomics: a case study.

PubMed

Watson, James D; Sanderson, Steve; Ezersky, Alexandra; Savchenko, Alexei; Edwards, Aled; Orengo, Christine; Joachimiak, Andrzej; Laskowski, Roman A; Thornton, Janet M

2007-04-13

As the global Structural Genomics projects have picked up pace, the number of structures annotated in the Protein Data Bank as hypothetical protein or unknown function has grown significantly. A major challenge now involves the development of computational methods to assign functions to these proteins accurately and automatically. As part of the Midwest Center for Structural Genomics (MCSG) we have developed a fully automated functional analysis server, ProFunc, which performs a battery of analyses on a submitted structure. The analyses combine a number of sequence-based and structure-based methods to identify functional clues. After the first stage of the Protein Structure Initiative (PSI), we review the success of the pipeline and the importance of structure-based function prediction. As a dataset, we have chosen all structures solved by the MCSG during the 5 years of the first PSI. Our analysis suggests that two of the structure-based methods are particularly successful and provide examples of local similarity that is difficult to identify using current sequence-based methods. No one method is successful in all cases, so, through the use of a number of complementary sequence and structural approaches, the ProFunc server increases the chances that at least one method will find a significant hit that can help elucidate function. Manual assessment of the results is a time-consuming process and subject to individual interpretation and human error. We present a method based on the Gene Ontology (GO) schema using GO-slims that can allow the automated assessment of hits with a success rate approaching that of expert manual assessment.

Environmental and spatial drivers of taxonomic, functional, and phylogenetic characteristics of bat communities in human-modified landscapes.

PubMed

Cisneros, Laura M; Fagan, Matthew E; Willig, Michael R

2016-01-01

Assembly of species into communities following human disturbance (e.g., deforestation, fragmentation) may be governed by spatial (e.g., dispersal) or environmental (e.g., niche partitioning) mechanisms. Variation partitioning has been used to broadly disentangle spatial and environmental mechanisms, and approaches utilizing functional and phylogenetic characteristics of communities have been implemented to determine the relative importance of particular environmental (or niche-based) mechanisms. Nonetheless, few studies have integrated these quantitative approaches to comprehensively assess the relative importance of particular structuring processes. We employed a novel variation partitioning approach to evaluate the relative importance of particular spatial and environmental drivers of taxonomic, functional, and phylogenetic aspects of bat communities in a human-modified landscape in Costa Rica. Specifically, we estimated the amount of variation in species composition (taxonomic structure) and in two aspects of functional and phylogenetic structure (i.e., composition and dispersion) along a forest loss and fragmentation gradient that are uniquely explained by landscape characteristics (i.e., environment) or space to assess the importance of competing mechanisms. The unique effects of space on taxonomic, functional and phylogenetic structure were consistently small. In contrast, landscape characteristics (i.e., environment) played an appreciable role in structuring bat communities. Spatially-structured landscape characteristics explained 84% of the variation in functional or phylogenetic dispersion, and the unique effects of landscape characteristics significantly explained 14% of the variation in species composition. Furthermore, variation in bat community structure was primarily due to differences in dispersion of species within functional or phylogenetic space along the gradient, rather than due to differences in functional or phylogenetic composition. Variation among bat communities was related to environmental mechanisms, especially niche-based (i.e., environmental) processes, rather than spatial mechanisms. High variation in functional or phylogenetic dispersion, as opposed to functional or phylogenetic composition, suggests that loss or gain of niche space is driving the progressive loss or gain of species with particular traits from communities along the human-modified gradient. Thus, environmental characteristics associated with landscape structure influence functional or phylogenetic aspects of bat communities by effectively altering the ways in which species partition niche space.

Environmental and spatial drivers of taxonomic, functional, and phylogenetic characteristics of bat communities in human-modified landscapes

PubMed Central

Fagan, Matthew E.; Willig, Michael R.

2016-01-01

Background Assembly of species into communities following human disturbance (e.g., deforestation, fragmentation) may be governed by spatial (e.g., dispersal) or environmental (e.g., niche partitioning) mechanisms. Variation partitioning has been used to broadly disentangle spatial and environmental mechanisms, and approaches utilizing functional and phylogenetic characteristics of communities have been implemented to determine the relative importance of particular environmental (or niche-based) mechanisms. Nonetheless, few studies have integrated these quantitative approaches to comprehensively assess the relative importance of particular structuring processes. Methods We employed a novel variation partitioning approach to evaluate the relative importance of particular spatial and environmental drivers of taxonomic, functional, and phylogenetic aspects of bat communities in a human-modified landscape in Costa Rica. Specifically, we estimated the amount of variation in species composition (taxonomic structure) and in two aspects of functional and phylogenetic structure (i.e., composition and dispersion) along a forest loss and fragmentation gradient that are uniquely explained by landscape characteristics (i.e., environment) or space to assess the importance of competing mechanisms. Results The unique effects of space on taxonomic, functional and phylogenetic structure were consistently small. In contrast, landscape characteristics (i.e., environment) played an appreciable role in structuring bat communities. Spatially-structured landscape characteristics explained 84% of the variation in functional or phylogenetic dispersion, and the unique effects of landscape characteristics significantly explained 14% of the variation in species composition. Furthermore, variation in bat community structure was primarily due to differences in dispersion of species within functional or phylogenetic space along the gradient, rather than due to differences in functional or phylogenetic composition. Discussion Variation among bat communities was related to environmental mechanisms, especially niche-based (i.e., environmental) processes, rather than spatial mechanisms. High variation in functional or phylogenetic dispersion, as opposed to functional or phylogenetic composition, suggests that loss or gain of niche space is driving the progressive loss or gain of species with particular traits from communities along the human-modified gradient. Thus, environmental characteristics associated with landscape structure influence functional or phylogenetic aspects of bat communities by effectively altering the ways in which species partition niche space. PMID:27761338

Exploration of structural stability in deleterious nsSNPs of the XPA gene: A molecular dynamics approach.

PubMed

Nagasundaram, N; Priya Doss, C George

2011-01-01

Distinguishing the deleterious from the massive number of non-functional nsSNPs that occur within a single genome is a considerable challenge in mutation research. In this approach, we have used the existing in silico methods to explore the mutation-structure-function relationship in the XPAgene. We used the Sorting Intolerant From Tolerant (SIFT), Polymorphism Phenotyping (PolyPhen), I-Mutant 2.0, and the Protein Analysis THrough Evolutionary Relationships methods to predict the effects of deleterious nsSNPs on protein function and evaluated the impact of mutation on protein stability by Molecular Dynamics simulations. By comparing the scores of all the four in silico methods, nsSNP with an ID rs104894131 at position C108F was predicted to be highly deleterious. We extended our Molecular dynamics approach to gain insight into the impact of this non-synonymous polymorphism on structural changes that may affect the activity of the XPAgene. Based on the in silico methods score, potential energy, root-mean-square deviation, and root-mean-square fluctuation, we predict that deleterious nsSNP at position C108F would play a significant role in causing disease by the XPA gene. Our approach would present the application of in silicotools in understanding the functional variation from the perspective of structure, evolution, and phenotype.

Does Gender-Specific Differential Item Functioning Affect the Structure in Vocational Interest Inventories?

ERIC Educational Resources Information Center

Beinicke, Andrea; Pässler, Katja; Hell, Benedikt

2014-01-01

The study investigates consequences of eliminating items showing gender-specific differential item functioning (DIF) on the psychometric structure of a standard RIASEC interest inventory. Holland's hexagonal model was tested for structural invariance using a confirmatory methodological approach (confirmatory factor analysis and randomization…

Pattern similarity study of functional sites in protein sequences: lysozymes and cystatins

PubMed Central

Nakai, Shuryo; Li-Chan, Eunice CY; Dou, Jinglie

2005-01-01

Background Although it is generally agreed that topography is more conserved than sequences, proteins sharing the same fold can have different functions, while there are protein families with low sequence similarity. An alternative method for profile analysis of characteristic conserved positions of the motifs within the 3D structures may be needed for functional annotation of protein sequences. Using the approach of quantitative structure-activity relationships (QSAR), we have proposed a new algorithm for postulating functional mechanisms on the basis of pattern similarity and average of property values of side-chains in segments within sequences. This approach was used to search for functional sites of proteins belonging to the lysozyme and cystatin families. Results Hydrophobicity and β-turn propensity of reference segments with 3–7 residues were used for the homology similarity search (HSS) for active sites. Hydrogen bonding was used as the side-chain property for searching the binding sites of lysozymes. The profiles of similarity constants and average values of these parameters as functions of their positions in the sequences could identify both active and substrate binding sites of the lysozyme of Streptomyces coelicolor, which has been reported as a new fold enzyme (Cellosyl). The same approach was successfully applied to cystatins, especially for postulating the mechanisms of amyloidosis of human cystatin C as well as human lysozyme. Conclusion Pattern similarity and average index values of structure-related properties of side chains in short segments of three residues or longer were, for the first time, successfully applied for predicting functional sites in sequences. This new approach may be applicable to studying functional sites in un-annotated proteins, for which complete 3D structures are not yet available. PMID:15904486

Development of a structured approach for decomposition of complex systems on a functional basis

NASA Astrophysics Data System (ADS)

Yildirim, Unal; Felician Campean, I.

2014-07-01

The purpose of this paper is to present the System State Flow Diagram (SSFD) as a structured and coherent methodology to decompose a complex system on a solution- independent functional basis. The paper starts by reviewing common function modelling frameworks in literature and discusses practical requirements of the SSFD in the context of the current literature and current approaches in industry. The proposed methodology is illustrated through the analysis of a case study: design analysis of a generic Bread Toasting System (BTS).

Robust biological parametric mapping: an improved technique for multimodal brain image analysis

NASA Astrophysics Data System (ADS)

Yang, Xue; Beason-Held, Lori; Resnick, Susan M.; Landman, Bennett A.

2011-03-01

Mapping the quantitative relationship between structure and function in the human brain is an important and challenging problem. Numerous volumetric, surface, region of interest and voxelwise image processing techniques have been developed to statistically assess potential correlations between imaging and non-imaging metrics. Recently, biological parametric mapping has extended the widely popular statistical parametric approach to enable application of the general linear model to multiple image modalities (both for regressors and regressands) along with scalar valued observations. This approach offers great promise for direct, voxelwise assessment of structural and functional relationships with multiple imaging modalities. However, as presented, the biological parametric mapping approach is not robust to outliers and may lead to invalid inferences (e.g., artifactual low p-values) due to slight mis-registration or variation in anatomy between subjects. To enable widespread application of this approach, we introduce robust regression and robust inference in the neuroimaging context of application of the general linear model. Through simulation and empirical studies, we demonstrate that our robust approach reduces sensitivity to outliers without substantial degradation in power. The robust approach and associated software package provides a reliable way to quantitatively assess voxelwise correlations between structural and functional neuroimaging modalities.

When the lowest energy does not induce native structures: parallel minimization of multi-energy values by hybridizing searching intelligences.

PubMed

Lü, Qiang; Xia, Xiao-Yan; Chen, Rong; Miao, Da-Jun; Chen, Sha-Sha; Quan, Li-Jun; Li, Hai-Ou

2012-01-01

Protein structure prediction (PSP), which is usually modeled as a computational optimization problem, remains one of the biggest challenges in computational biology. PSP encounters two difficult obstacles: the inaccurate energy function problem and the searching problem. Even if the lowest energy has been luckily found by the searching procedure, the correct protein structures are not guaranteed to obtain. A general parallel metaheuristic approach is presented to tackle the above two problems. Multi-energy functions are employed to simultaneously guide the parallel searching threads. Searching trajectories are in fact controlled by the parameters of heuristic algorithms. The parallel approach allows the parameters to be perturbed during the searching threads are running in parallel, while each thread is searching the lowest energy value determined by an individual energy function. By hybridizing the intelligences of parallel ant colonies and Monte Carlo Metropolis search, this paper demonstrates an implementation of our parallel approach for PSP. 16 classical instances were tested to show that the parallel approach is competitive for solving PSP problem. This parallel approach combines various sources of both searching intelligences and energy functions, and thus predicts protein conformations with good quality jointly determined by all the parallel searching threads and energy functions. It provides a framework to combine different searching intelligence embedded in heuristic algorithms. It also constructs a container to hybridize different not-so-accurate objective functions which are usually derived from the domain expertise.

When the Lowest Energy Does Not Induce Native Structures: Parallel Minimization of Multi-Energy Values by Hybridizing Searching Intelligences

PubMed Central

Lü, Qiang; Xia, Xiao-Yan; Chen, Rong; Miao, Da-Jun; Chen, Sha-Sha; Quan, Li-Jun; Li, Hai-Ou

2012-01-01

Background Protein structure prediction (PSP), which is usually modeled as a computational optimization problem, remains one of the biggest challenges in computational biology. PSP encounters two difficult obstacles: the inaccurate energy function problem and the searching problem. Even if the lowest energy has been luckily found by the searching procedure, the correct protein structures are not guaranteed to obtain. Results A general parallel metaheuristic approach is presented to tackle the above two problems. Multi-energy functions are employed to simultaneously guide the parallel searching threads. Searching trajectories are in fact controlled by the parameters of heuristic algorithms. The parallel approach allows the parameters to be perturbed during the searching threads are running in parallel, while each thread is searching the lowest energy value determined by an individual energy function. By hybridizing the intelligences of parallel ant colonies and Monte Carlo Metropolis search, this paper demonstrates an implementation of our parallel approach for PSP. 16 classical instances were tested to show that the parallel approach is competitive for solving PSP problem. Conclusions This parallel approach combines various sources of both searching intelligences and energy functions, and thus predicts protein conformations with good quality jointly determined by all the parallel searching threads and energy functions. It provides a framework to combine different searching intelligence embedded in heuristic algorithms. It also constructs a container to hybridize different not-so-accurate objective functions which are usually derived from the domain expertise. PMID:23028708

The Paris-Sud yeast structural genomics pilot-project: from structure to function.

PubMed

Quevillon-Cheruel, Sophie; Liger, Dominique; Leulliot, Nicolas; Graille, Marc; Poupon, Anne; Li de La Sierra-Gallay, Inès; Zhou, Cong-Zhao; Collinet, Bruno; Janin, Joël; Van Tilbeurgh, Herman

2004-01-01

We present here the outlines and results from our yeast structural genomics (YSG) pilot-project. A lab-scale platform for the systematic production and structure determination is presented. In order to validate this approach, 250 non-membrane proteins of unknown structure were targeted. Strategies and final statistics are evaluated. We finally discuss the opportunity of structural genomics programs to contribute to functional biochemical annotation.

On the saturation of the refractive index structure function. II - Influence of the correlation length on astronomical 'seeing'

NASA Technical Reports Server (NTRS)

Venkatakrishnan, P.

1987-01-01

A physical length scale in the wavefront corresponding to the parameter (r sub 0) characterizing the loss in detail in a long exposure image is identified, and the influence of the correlation scale of turbulence as r sub 0 approaches this scale is shown. Allowing for the effect of 2-point correlations in the fluctuations of the refractive index, Venkatakrishnan and Chatterjee (1987) proposed a modified law for the phase structure function. It is suggested that the departure of the phase structure function from the 5/3 power law for length scales in the wavefront approaching the correlation scale of turbulence may lead to better 'seeing' at longer wavelengths.

Network diffusion accurately models the relationship between structural and functional brain connectivity networks

PubMed Central

Abdelnour, Farras; Voss, Henning U.; Raj, Ashish

2014-01-01

The relationship between anatomic connectivity of large-scale brain networks and their functional connectivity is of immense importance and an area of active research. Previous attempts have required complex simulations which model the dynamics of each cortical region, and explore the coupling between regions as derived by anatomic connections. While much insight is gained from these non-linear simulations, they can be computationally taxing tools for predicting functional from anatomic connectivities. Little attention has been paid to linear models. Here we show that a properly designed linear model appears to be superior to previous non-linear approaches in capturing the brain’s long-range second order correlation structure that governs the relationship between anatomic and functional connectivities. We derive a linear network of brain dynamics based on graph diffusion, whereby the diffusing quantity undergoes a random walk on a graph. We test our model using subjects who underwent diffusion MRI and resting state fMRI. The network diffusion model applied to the structural networks largely predicts the correlation structures derived from their fMRI data, to a greater extent than other approaches. The utility of the proposed approach is that it can routinely be used to infer functional correlation from anatomic connectivity. And since it is linear, anatomic connectivity can also be inferred from functional data. The success of our model confirms the linearity of ensemble average signals in the brain, and implies that their long-range correlation structure may percolate within the brain via purely mechanistic processes enacted on its structural connectivity pathways. PMID:24384152

From Structure to Function: A Comprehensive Compendium of Tools to Unveil Protein Domains and Understand Their Role in Cytokinesis.

PubMed

Rincon, Sergio A; Paoletti, Anne

2016-01-01

Unveiling the function of a novel protein is a challenging task that requires careful experimental design. Yeast cytokinesis is a conserved process that involves modular structural and regulatory proteins. For such proteins, an important step is to identify their domains and structural organization. Here we briefly discuss a collection of methods commonly used for sequence alignment and prediction of protein structure that represent powerful tools for the identification homologous domains and design of structure-function approaches to test experimentally the function of multi-domain proteins such as those implicated in yeast cytokinesis.

Mechanisms of hemispheric specialization: Insights from analyses of connectivity

PubMed Central

Stephan, Klaas Enno; Fink, Gereon R.; Marshall, John C.

2007-01-01

Traditionally, anatomical and physiological descriptions of hemispheric specialization have focused on hemispheric asymmetries of local brain structure or local functional properties, respectively. This article reviews the current state of an alternative approach that aims at unraveling the causes and functional principles of hemispheric specialization in terms of asymmetries in connectivity. Starting with an overview of the historical origins of the concept of lateralization, we briefly review recent evidence from anatomical and developmental studies that asymmetries in structural connectivity may be a critical factor shaping hemispheric specialization. These differences in anatomical connectivity, which are found both at the intra- and inter-regional level, are likely to form the structural substrate of different functional principles of information processing in the two hemispheres. The main goal of this article is to describe how these functional principles can be characterized using functional neuroimaging in combination with models of functional and effective connectivity. We discuss the methodology of established models of connectivity which are applicable to data from positron emission tomography and functional magnetic resonance imaging and review published studies that have applied these approaches to characterize asymmetries of connectivity during lateralized tasks. Adopting a model-based approach enables functional imaging to proceed from mere descriptions of asymmetric activation patterns to mechanistic accounts of how these asymmetries are caused. PMID:16949111

Mapping the Structure-Function Relationship in Glaucoma and Healthy Patients Measured with Spectralis OCT and Humphrey Perimetry

PubMed Central

Muñoz–Negrete, Francisco J.; Oblanca, Noelia; Rebolleda, Gema

2018-01-01

Purpose To study the structure-function relationship in glaucoma and healthy patients assessed with Spectralis OCT and Humphrey perimetry using new statistical approaches. Materials and Methods Eighty-five eyes were prospectively selected and divided into 2 groups: glaucoma (44) and healthy patients (41). Three different statistical approaches were carried out: (1) factor analysis of the threshold sensitivities (dB) (automated perimetry) and the macular thickness (μm) (Spectralis OCT), subsequently applying Pearson's correlation to the obtained regions, (2) nonparametric regression analysis relating the values in each pair of regions that showed significant correlation, and (3) nonparametric spatial regressions using three models designed for the purpose of this study. Results In the glaucoma group, a map that relates structural and functional damage was drawn. The strongest correlation with visual fields was observed in the peripheral nasal region of both superior and inferior hemigrids (r = 0.602 and r = 0.458, resp.). The estimated functions obtained with the nonparametric regressions provided the mean sensitivity that corresponds to each given macular thickness. These functions allowed for accurate characterization of the structure-function relationship. Conclusions Both maps and point-to-point functions obtained linking structure and function damage contribute to a better understanding of this relationship and may help in the future to improve glaucoma diagnosis. PMID:29850196

The Structure of Li7 and K7

NASA Technical Reports Server (NTRS)

Bauschlicher. Charles W., Jr.; Langhoff, Stephen R. (Technical Monitor)

1995-01-01

The self-consistent-field (SCF) approach and density functional theory, using the B3LYP hybrid functional, yield three low-lying structures for Li7(-). The relative separations differ for the SCF and B3LYP approaches, however the B3LYP results are in good agreement with the coupled cluster results. For K7(-), only an octahedron with one face capped is found to be a minimum; this the second most stable structure for Li7(-). A comparison of the computed separations between the low-lying states of K7 and the photoelectron detachment spectra does not allow an unambiguous assignment of the structure of K7(-).

Monte Carlo Simulations of Electron Energy-Loss Spectra with the Addition of Fine Structure from Density Functional Theory Calculations.

PubMed

Attarian Shandiz, Mohammad; Guinel, Maxime J-F; Ahmadi, Majid; Gauvin, Raynald

2016-02-01

A new approach is presented to introduce the fine structure of core-loss excitations into the electron energy-loss spectra of ionization edges by Monte Carlo simulations based on an optical oscillator model. The optical oscillator strength is refined using the calculated electron energy-loss near-edge structure by density functional theory calculations. This approach can predict the effects of multiple scattering and thickness on the fine structure of ionization edges. In addition, effects of the fitting range for background removal and the integration range under the ionization edge on signal-to-noise ratio are investigated.

Novel Material Systems and Methodologies for Transient Thermal Management

NASA Technical Reports Server (NTRS)

Oliva-Buisson, Yvette J.

2014-01-01

Development of multifunctional and thermally switchable systems to address reduced mass and components, and tailored for both structural and transient thermal applications. Active, passive, and novel combinations of the two functional approaches are being developed along two lines of research investigation: switchable systems and transient heat spreading. The approach is to build in thermal functionality to structural elements to lay the foundation for a revolution in the way high energy space systems are designed.

Predicting nucleic acid binding interfaces from structural models of proteins.

PubMed

Dror, Iris; Shazman, Shula; Mukherjee, Srayanta; Zhang, Yang; Glaser, Fabian; Mandel-Gutfreund, Yael

2012-02-01

The function of DNA- and RNA-binding proteins can be inferred from the characterization and accurate prediction of their binding interfaces. However, the main pitfall of various structure-based methods for predicting nucleic acid binding function is that they are all limited to a relatively small number of proteins for which high-resolution three-dimensional structures are available. In this study, we developed a pipeline for extracting functional electrostatic patches from surfaces of protein structural models, obtained using the I-TASSER protein structure predictor. The largest positive patches are extracted from the protein surface using the patchfinder algorithm. We show that functional electrostatic patches extracted from an ensemble of structural models highly overlap the patches extracted from high-resolution structures. Furthermore, by testing our pipeline on a set of 55 known nucleic acid binding proteins for which I-TASSER produces high-quality models, we show that the method accurately identifies the nucleic acids binding interface on structural models of proteins. Employing a combined patch approach we show that patches extracted from an ensemble of models better predicts the real nucleic acid binding interfaces compared with patches extracted from independent models. Overall, these results suggest that combining information from a collection of low-resolution structural models could be a valuable approach for functional annotation. We suggest that our method will be further applicable for predicting other functional surfaces of proteins with unknown structure. Copyright © 2011 Wiley Periodicals, Inc.

Protein Bricks: 2D and 3D Bio-Nanostructures with Shape and Function on Demand.

PubMed

Jiang, Jianjuan; Zhang, Shaoqing; Qian, Zhigang; Qin, Nan; Song, Wenwen; Sun, Long; Zhou, Zhitao; Shi, Zhifeng; Chen, Liang; Li, Xinxin; Mao, Ying; Kaplan, David L; Gilbert Corder, Stephanie N; Chen, Xinzhong; Liu, Mengkun; Omenetto, Fiorenzo G; Xia, Xiaoxia; Tao, Tiger H

2018-05-01

Precise patterning of polymer-based biomaterials for functional bio-nanostructures has extensive applications including biosensing, tissue engineering, and regenerative medicine. Remarkable progress is made in both top-down (based on lithographic methods) and bottom-up (via self-assembly) approaches with natural and synthetic biopolymers. However, most methods only yield 2D and pseudo-3D structures with restricted geometries and functionalities. Here, it is reported that precise nanostructuring on genetically engineered spider silk by accurately directing ion and electron beam interactions with the protein's matrix at the nanoscale to create well-defined 2D bionanopatterns and further assemble 3D bionanoarchitectures with shape and function on demand, termed "Protein Bricks." The added control over protein sequence and molecular weight of recombinant spider silk via genetic engineering provides unprecedented lithographic resolution (approaching the molecular limit), sharpness, and biological functions compared to natural proteins. This approach provides a facile method for patterning and immobilizing functional molecules within nanoscopic, hierarchical protein structures, which sheds light on a wide range of biomedical applications such as structure-enhanced fluorescence and biomimetic microenvironments for controlling cell fate. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Crystal structure optimisation using an auxiliary equation of state

NASA Astrophysics Data System (ADS)

Jackson, Adam J.; Skelton, Jonathan M.; Hendon, Christopher H.; Butler, Keith T.; Walsh, Aron

2015-11-01

Standard procedures for local crystal-structure optimisation involve numerous energy and force calculations. It is common to calculate an energy-volume curve, fitting an equation of state around the equilibrium cell volume. This is a computationally intensive process, in particular, for low-symmetry crystal structures where each isochoric optimisation involves energy minimisation over many degrees of freedom. Such procedures can be prohibitive for non-local exchange-correlation functionals or other "beyond" density functional theory electronic structure techniques, particularly where analytical gradients are not available. We present a simple approach for efficient optimisation of crystal structures based on a known equation of state. The equilibrium volume can be predicted from one single-point calculation and refined with successive calculations if required. The approach is validated for PbS, PbTe, ZnS, and ZnTe using nine density functionals and applied to the quaternary semiconductor Cu2ZnSnS4 and the magnetic metal-organic framework HKUST-1.

Protein Engineering Approaches in the Post-Genomic Era.

PubMed

Singh, Raushan K; Lee, Jung-Kul; Selvaraj, Chandrabose; Singh, Ranjitha; Li, Jinglin; Kim, Sang-Yong; Kalia, Vipin C

2018-01-01

Proteins are one of the most multifaceted macromolecules in living systems. Proteins have evolved to function under physiological conditions and, therefore, are not usually tolerant of harsh experimental and environmental conditions. The growing use of proteins in industrial processes as a greener alternative to chemical catalysts often demands constant innovation to improve their performance. Protein engineering aims to design new proteins or modify the sequence of a protein to create proteins with new or desirable functions. With the emergence of structural and functional genomics, protein engineering has been invigorated in the post-genomic era. The three-dimensional structures of proteins with known functions facilitate protein engineering approaches to design variants with desired properties. There are three major approaches of protein engineering research, namely, directed evolution, rational design, and de novo design. Rational design is an effective method of protein engineering when the threedimensional structure and mechanism of the protein is well known. In contrast, directed evolution does not require extensive information and a three-dimensional structure of the protein of interest. Instead, it involves random mutagenesis and selection to screen enzymes with desired properties. De novo design uses computational protein design algorithms to tailor synthetic proteins by using the three-dimensional structures of natural proteins and their folding rules. The present review highlights and summarizes recent protein engineering approaches, and their challenges and limitations in the post-genomic era. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

A Model-Based Approach for Microvasculature Structure Distortion Correction in Two-Photon Fluorescence Microscopy Images

PubMed Central

Dao, Lam; Glancy, Brian; Lucotte, Bertrand; Chang, Lin-Ching; Balaban, Robert S; Hsu, Li-Yueh

2015-01-01

SUMMARY This paper investigates a post-processing approach to correct spatial distortion in two-photon fluorescence microscopy images for vascular network reconstruction. It is aimed at in vivo imaging of large field-of-view, deep-tissue studies of vascular structures. Based on simple geometric modeling of the object-of-interest, a distortion function is directly estimated from the image volume by deconvolution analysis. Such distortion function is then applied to sub volumes of the image stack to adaptively adjust for spatially varying distortion and reduce the image blurring through blind deconvolution. The proposed technique was first evaluated in phantom imaging of fluorescent microspheres that are comparable in size to the underlying capillary vascular structures. The effectiveness of restoring three-dimensional spherical geometry of the microspheres using the estimated distortion function was compared with empirically measured point-spread function. Next, the proposed approach was applied to in vivo vascular imaging of mouse skeletal muscle to reduce the image distortion of the capillary structures. We show that the proposed method effectively improve the image quality and reduce spatially varying distortion that occurs in large field-of-view deep-tissue vascular dataset. The proposed method will help in qualitative interpretation and quantitative analysis of vascular structures from fluorescence microscopy images. PMID:26224257

Structural-functional lung imaging using a combined CT-EIT and a Discrete Cosine Transformation reconstruction method.

PubMed

Schullcke, Benjamin; Gong, Bo; Krueger-Ziolek, Sabine; Soleimani, Manuchehr; Mueller-Lisse, Ullrich; Moeller, Knut

2016-05-16

Lung EIT is a functional imaging method that utilizes electrical currents to reconstruct images of conductivity changes inside the thorax. This technique is radiation free and applicable at the bedside, but lacks of spatial resolution compared to morphological imaging methods such as X-ray computed tomography (CT). In this article we describe an approach for EIT image reconstruction using morphologic information obtained from other structural imaging modalities. This leads to recon- structed images of lung ventilation that can easily be superimposed with structural CT or MRI images, which facilitates image interpretation. The approach is based on a Discrete Cosine Transformation (DCT) of an image of the considered transversal thorax slice. The use of DCT enables reduction of the dimensionality of the reconstruction and ensures that only conductivity changes of the lungs are reconstructed and displayed. The DCT based approach is well suited to fuse morphological image information with functional lung imaging at low computational costs. Results on simulated data indicate that this approach preserves the morphological structures of the lungs and avoids blurring of the solution. Images from patient measurements reveal the capabilities of the method and demonstrate benefits in possible applications.

Structural-functional lung imaging using a combined CT-EIT and a Discrete Cosine Transformation reconstruction method

PubMed Central

Schullcke, Benjamin; Gong, Bo; Krueger-Ziolek, Sabine; Soleimani, Manuchehr; Mueller-Lisse, Ullrich; Moeller, Knut

2016-01-01

Lung EIT is a functional imaging method that utilizes electrical currents to reconstruct images of conductivity changes inside the thorax. This technique is radiation free and applicable at the bedside, but lacks of spatial resolution compared to morphological imaging methods such as X-ray computed tomography (CT). In this article we describe an approach for EIT image reconstruction using morphologic information obtained from other structural imaging modalities. This leads to recon- structed images of lung ventilation that can easily be superimposed with structural CT or MRI images, which facilitates image interpretation. The approach is based on a Discrete Cosine Transformation (DCT) of an image of the considered transversal thorax slice. The use of DCT enables reduction of the dimensionality of the reconstruction and ensures that only conductivity changes of the lungs are reconstructed and displayed. The DCT based approach is well suited to fuse morphological image information with functional lung imaging at low computational costs. Results on simulated data indicate that this approach preserves the morphological structures of the lungs and avoids blurring of the solution. Images from patient measurements reveal the capabilities of the method and demonstrate benefits in possible applications. PMID:27181695

An optimal strategy for functional mapping of dynamic trait loci.

PubMed

Jin, Tianbo; Li, Jiahan; Guo, Ying; Zhou, Xiaojing; Yang, Runqing; Wu, Rongling

2010-02-01

As an emerging powerful approach for mapping quantitative trait loci (QTLs) responsible for dynamic traits, functional mapping models the time-dependent mean vector with biologically meaningful equations and are likely to generate biologically relevant and interpretable results. Given the autocorrelation nature of a dynamic trait, functional mapping needs the implementation of the models for the structure of the covariance matrix. In this article, we have provided a comprehensive set of approaches for modelling the covariance structure and incorporated each of these approaches into the framework of functional mapping. The Bayesian information criterion (BIC) values are used as a model selection criterion to choose the optimal combination of the submodels for the mean vector and covariance structure. In an example for leaf age growth from a rice molecular genetic project, the best submodel combination was found between the Gaussian model for the correlation structure, power equation of order 1 for the variance and the power curve for the mean vector. Under this combination, several significant QTLs for leaf age growth trajectories were detected on different chromosomes. Our model can be well used to study the genetic architecture of dynamic traits of agricultural values.

A network function-based definition of communities in complex networks.

PubMed

Chauhan, Sanjeev; Girvan, Michelle; Ott, Edward

2012-09-01

We consider an alternate definition of community structure that is functionally motivated. We define network community structure based on the function the network system is intended to perform. In particular, as a specific example of this approach, we consider communities whose function is enhanced by the ability to synchronize and/or by resilience to node failures. Previous work has shown that, in many cases, the largest eigenvalue of the network's adjacency matrix controls the onset of both synchronization and percolation processes. Thus, for networks whose functional performance is dependent on these processes, we propose a method that divides a given network into communities based on maximizing a function of the largest eigenvalues of the adjacency matrices of the resulting communities. We also explore the differences between the partitions obtained by our method and the modularity approach (which is based solely on consideration of network structure). We do this for several different classes of networks. We find that, in many cases, modularity-based partitions do almost as well as our function-based method in finding functional communities, even though modularity does not specifically incorporate consideration of function.

Exploration of structural stability in deleterious nsSNPs of the XPA gene: A molecular dynamics approach

PubMed Central

NagaSundaram, N; Priya Doss, C George

2011-01-01

Background: Distinguishing the deleterious from the massive number of non-functional nsSNPs that occur within a single genome is a considerable challenge in mutation research. In this approach, we have used the existing in silico methods to explore the mutation-structure-function relationship in the XPAgene. Materials and Methods: We used the Sorting Intolerant From Tolerant (SIFT), Polymorphism Phenotyping (PolyPhen), I-Mutant 2.0, and the Protein Analysis THrough Evolutionary Relationships methods to predict the effects of deleterious nsSNPs on protein function and evaluated the impact of mutation on protein stability by Molecular Dynamics simulations. Results: By comparing the scores of all the four in silico methods, nsSNP with an ID rs104894131 at position C108F was predicted to be highly deleterious. We extended our Molecular dynamics approach to gain insight into the impact of this non-synonymous polymorphism on structural changes that may affect the activity of the XPAgene. Conclusion: Based on the in silico methods score, potential energy, root-mean-square deviation, and root-mean-square fluctuation, we predict that deleterious nsSNP at position C108F would play a significant role in causing disease by the XPA gene. Our approach would present the application of in silicotools in understanding the functional variation from the perspective of structure, evolution, and phenotype. PMID:22190868

Test Cases for Modeling and Validation of Structures with Piezoelectric Actuators

NASA Technical Reports Server (NTRS)

Reaves, Mercedes C.; Horta, Lucas G.

2001-01-01

A set of benchmark test articles were developed to validate techniques for modeling structures containing piezoelectric actuators using commercially available finite element analysis packages. The paper presents the development, modeling, and testing of two structures: an aluminum plate with surface mounted patch actuators and a composite box beam with surface mounted actuators. Three approaches for modeling structures containing piezoelectric actuators using the commercially available packages: MSC/NASTRAN and ANSYS are presented. The approaches, applications, and limitations are discussed. Data for both test articles are compared in terms of frequency response functions from deflection and strain data to input voltage to the actuator. Frequency response function results using the three different analysis approaches provided comparable test/analysis results. It is shown that global versus local behavior of the analytical model and test article must be considered when comparing different approaches. Also, improper bonding of actuators greatly reduces the electrical to mechanical effectiveness of the actuators producing anti-resonance errors.

Combining formal and functional approaches to topic structure.

PubMed

Zellers, Margaret; Post, Brechtje

2012-03-01

Fragmentation between formal and functional approaches to prosodic variation is an ongoing problem in linguistic research. In particular, the frameworks of the Phonetics of Talk-in-Interaction (PTI) and Empirical Phonology (EP) take very different theoretical and methodological approaches to this kind of variation. We argue that it is fruitful to adopt the insights of both PTI's qualitative analysis and EP's quantitative analysis and combine them into a multiple-methods approach. One realm in which it is possible to combine these frameworks is in the analysis of discourse topic structure and the prosodic cues relevant to it. By combining a quantitative and a qualitative approach to discourse topic structure, it is possible to give a better account of the observed variation in prosody, for example in the case of fundamental frequency (F0) peak timing, which can be explained in terms of pitch accent distribution over different topic structure categories. Similarly, local and global patterns in speech rate variation can be better explained and motivated by adopting insights from both PTI and EP in the study of topic structure. Combining PTI and EP can provide better accounts of speech data as well as opening up new avenues of investigation which would not have been possible in either approach alone.

Hybrid Density Functional Study of the Local Structures and Energy Levels of CaAl2O4:Ce3.

PubMed

Lou, Bibo; Jing, Weiguo; Lou, Liren; Zhang, Yongfan; Yin, Min; Duan, Chang-Kui

2018-05-03

First-principles calculations were carried out for the electronic structures of Ce 3+ in calcium aluminate phosphors, CaAl 2 O 4 , and their effects on luminescence properties. Hybrid density functional approaches were used to overcome the well-known underestimation of band gaps of conventional density functional approaches and to calculate the energy levels of Ce 3+ ions more accurately. The obtained 4f-5d excitation and emission energies show good consistency with measured values. A detailed energy diagram of all three sites is obtained, which explains qualitatively all of the luminescent phenomena. With the results of energy levels calculated by combining the hybrid functional of Heyd, Scuseria, and Ernzerhof (HSE06) and the constraint occupancy approach, we are able to construct a configurational coordinate diagram to analyze the processes of capture of a hole or an electron and luminescence. This approach can be applied for systematic high-throughput calculations in predicting Ce 3+ activated luminescent materials with a moderate computing requirement.

Integrated Controls-Structures Design Methodology for Flexible Spacecraft

NASA Technical Reports Server (NTRS)

Maghami, P. G.; Joshi, S. M.; Price, D. B.

1995-01-01

This paper proposes an approach for the design of flexible spacecraft, wherein the structural design and the control system design are performed simultaneously. The integrated design problem is posed as an optimization problem in which both the structural parameters and the control system parameters constitute the design variables, which are used to optimize a common objective function, thereby resulting in an optimal overall design. The approach is demonstrated by application to the integrated design of a geostationary platform, and to a ground-based flexible structure experiment. The numerical results obtained indicate that the integrated design approach generally yields spacecraft designs that are substantially superior to the conventional approach, wherein the structural design and control design are performed sequentially.

Structured penalties for functional linear models-partially empirical eigenvectors for regression.

PubMed

Randolph, Timothy W; Harezlak, Jaroslaw; Feng, Ziding

2012-01-01

One of the challenges with functional data is incorporating geometric structure, or local correlation, into the analysis. This structure is inherent in the output from an increasing number of biomedical technologies, and a functional linear model is often used to estimate the relationship between the predictor functions and scalar responses. Common approaches to the problem of estimating a coefficient function typically involve two stages: regularization and estimation. Regularization is usually done via dimension reduction, projecting onto a predefined span of basis functions or a reduced set of eigenvectors (principal components). In contrast, we present a unified approach that directly incorporates geometric structure into the estimation process by exploiting the joint eigenproperties of the predictors and a linear penalty operator. In this sense, the components in the regression are 'partially empirical' and the framework is provided by the generalized singular value decomposition (GSVD). The form of the penalized estimation is not new, but the GSVD clarifies the process and informs the choice of penalty by making explicit the joint influence of the penalty and predictors on the bias, variance and performance of the estimated coefficient function. Laboratory spectroscopy data and simulations are used to illustrate the concepts.

Probing Xist RNA Structure in Cells Using Targeted Structure-Seq

PubMed Central

Rutenberg-Schoenberg, Michael; Simon, Matthew D.

2015-01-01

The long non-coding RNA (lncRNA) Xist is a master regulator of X-chromosome inactivation in mammalian cells. Models for how Xist and other lncRNAs function depend on thermodynamically stable secondary and higher-order structures that RNAs can form in the context of a cell. Probing accessible RNA bases can provide data to build models of RNA conformation that provide insight into RNA function, molecular evolution, and modularity. To study the structure of Xist in cells, we built upon recent advances in RNA secondary structure mapping and modeling to develop Targeted Structure-Seq, which combines chemical probing of RNA structure in cells with target-specific massively parallel sequencing. By enriching for signals from the RNA of interest, Targeted Structure-Seq achieves high coverage of the target RNA with relatively few sequencing reads, thus providing a targeted and scalable approach to analyze RNA conformation in cells. We use this approach to probe the full-length Xist lncRNA to develop new models for functional elements within Xist, including the repeat A element in the 5’-end of Xist. This analysis also identified new structural elements in Xist that are evolutionarily conserved, including a new element proximal to the C repeats that is important for Xist function. PMID:26646615

Energy minimization for self-organized structure formation and actuation

NASA Astrophysics Data System (ADS)

Kofod, Guggi; Wirges, Werner; Paajanen, Mika; Bauer, Siegfried

2007-02-01

An approach for creating complex structures with embedded actuation in planar manufacturing steps is presented. Self-organization and energy minimization are central to this approach, illustrated with a model based on minimization of the hyperelastic free energy strain function of a stretched elastomer and the bending elastic energy of a plastic frame. A tulip-shaped gripper structure illustrates the technological potential of the approach. Advantages are simplicity of manufacture, complexity of final structures, and the ease with which any electroactive material can be exploited as means of actuation.

Assignment of functional activations to probabilistic cytoarchitectonic areas revisited.

PubMed

Eickhoff, Simon B; Paus, Tomas; Caspers, Svenja; Grosbras, Marie-Helene; Evans, Alan C; Zilles, Karl; Amunts, Katrin

2007-07-01

Probabilistic cytoarchitectonic maps in standard reference space provide a powerful tool for the analysis of structure-function relationships in the human brain. While these microstructurally defined maps have already been successfully used in the analysis of somatosensory, motor or language functions, several conceptual issues in the analysis of structure-function relationships still demand further clarification. In this paper, we demonstrate the principle approaches for anatomical localisation of functional activations based on probabilistic cytoarchitectonic maps by exemplary analysis of an anterior parietal activation evoked by visual presentation of hand gestures. After consideration of the conceptual basis and implementation of volume or local maxima labelling, we comment on some potential interpretational difficulties, limitations and caveats that could be encountered. Extending and supplementing these methods, we then propose a supplementary approach for quantification of structure-function correspondences based on distribution analysis. This approach relates the cytoarchitectonic probabilities observed at a particular functionally defined location to the areal specific null distribution of probabilities across the whole brain (i.e., the full probability map). Importantly, this method avoids the need for a unique classification of voxels to a single cortical area and may increase the comparability between results obtained for different areas. Moreover, as distribution-based labelling quantifies the "central tendency" of an activation with respect to anatomical areas, it will, in combination with the established methods, allow an advanced characterisation of the anatomical substrates of functional activations. Finally, the advantages and disadvantages of the various methods are discussed, focussing on the question of which approach is most appropriate for a particular situation.

Brain Structure and Resting-State Functional Connectivity in University Professors with High Academic Achievement

ERIC Educational Resources Information Center

Li, Weiwei; Yang, Wenjing; Li, Wenfu; Li, Yadan; Wei, Dongtao; Li, Huimin; Qiu, Jiang; Zhang, Qinglin

2015-01-01

Creative persons play an important role in technical innovation and social progress. There is little research on the neural correlates with researchers with high academic achievement. We used a combined structural (regional gray matter volume, rGMV) and functional (resting-state functional connectivity analysis, rsFC) approach to examine the…

Protein Structure and Function Prediction Using I-TASSER

PubMed Central

Yang, Jianyi; Zhang, Yang

2016-01-01

I-TASSER is a hierarchical protocol for automated protein structure prediction and structure-based function annotation. Starting from the amino acid sequence of target proteins, I-TASSER first generates full-length atomic structural models from multiple threading alignments and iterative structural assembly simulations followed by atomic-level structure refinement. The biological functions of the protein, including ligand-binding sites, enzyme commission number, and gene ontology terms, are then inferred from known protein function databases based on sequence and structure profile comparisons. I-TASSER is freely available as both an on-line server and a stand-alone package. This unit describes how to use the I-TASSER protocol to generate structure and function prediction and how to interpret the prediction results, as well as alternative approaches for further improving the I-TASSER modeling quality for distant-homologous and multi-domain protein targets. PMID:26678386

Damage tolerant design using collapse techniques

NASA Technical Reports Server (NTRS)

Haftka, R. T.

1982-01-01

A new approach to the design of structures for improved global damage tolerance is presented. In its undamaged condition the structure is designed subject to strength, displacement and buckling constraints. In the damaged condition the only constraint is that the structure will not collapse. The collapse load calculation is formulated as a maximization problem and solved by an interior extended penalty function. The design for minimum weight subject to constraints on the undamaged structure and a specified level of the collapse load is a minimization problem which is also solved by a penalty function formulation. Thus the overall problem is of a nested or multilevel optimization. Examples are presented to demonstrate the difference between the present and more traditional approaches.

Combined expert system/neural networks method for process fault diagnosis

DOEpatents

Reifman, Jaques; Wei, Thomas Y. C.

1995-01-01

A two-level hierarchical approach for process fault diagnosis is an operating system employs a function-oriented approach at a first level and a component characteristic-oriented approach at a second level, where the decision-making procedure is structured in order of decreasing intelligence with increasing precision. At the first level, the diagnostic method is general and has knowledge of the overall process including a wide variety of plant transients and the functional behavior of the process components. An expert system classifies malfunctions by function to narrow the diagnostic focus to a particular set of possible faulty components that could be responsible for the detected functional misbehavior of the operating system. At the second level, the diagnostic method limits its scope to component malfunctions, using more detailed knowledge of component characteristics. Trained artificial neural networks are used to further narrow the diagnosis and to uniquely identify the faulty component by classifying the abnormal condition data as a failure of one of the hypothesized components through component characteristics. Once an anomaly is detected, the hierarchical structure is used to successively narrow the diagnostic focus from a function misbehavior, i.e., a function oriented approach, until the fault can be determined, i.e., a component characteristic-oriented approach.

Combined expert system/neural networks method for process fault diagnosis

DOEpatents

Reifman, J.; Wei, T.Y.C.

1995-08-15

A two-level hierarchical approach for process fault diagnosis of an operating system employs a function-oriented approach at a first level and a component characteristic-oriented approach at a second level, where the decision-making procedure is structured in order of decreasing intelligence with increasing precision. At the first level, the diagnostic method is general and has knowledge of the overall process including a wide variety of plant transients and the functional behavior of the process components. An expert system classifies malfunctions by function to narrow the diagnostic focus to a particular set of possible faulty components that could be responsible for the detected functional misbehavior of the operating system. At the second level, the diagnostic method limits its scope to component malfunctions, using more detailed knowledge of component characteristics. Trained artificial neural networks are used to further narrow the diagnosis and to uniquely identify the faulty component by classifying the abnormal condition data as a failure of one of the hypothesized components through component characteristics. Once an anomaly is detected, the hierarchical structure is used to successively narrow the diagnostic focus from a function misbehavior, i.e., a function oriented approach, until the fault can be determined, i.e., a component characteristic-oriented approach. 9 figs.

Metalloproteomics: Forward and Reverse Approaches in Metalloprotein Structural and Functional Characterization

PubMed Central

Shi, Wuxian; Chance, Mark R.

2010-01-01

About one-third of all proteins are associated with a metal. Metalloproteomics is defined as the structural and functional characterization of metalloproteins on a genome-wide scale. The methodologies utilized in metalloproteomics, including both forward (bottom-up) and reverse (top-down) technologies, to provide information on the identity, quantity and function of metalloproteins are discussed. Important techniques frequently employed in metalloproteomics include classical proteomics tools such as mass spectrometry and 2-D gels, immobilized-metal affinity chromatography, bioinformatics sequence analysis and homology modeling, X-ray absorption spectroscopy and other synchrotron radiation based tools. Combinative applications of these techniques provide a powerful approach to understand the function of metalloproteins. PMID:21130021

Mapping higher-order relations between brain structure and function with embedded vector representations of connectomes.

PubMed

Rosenthal, Gideon; Váša, František; Griffa, Alessandra; Hagmann, Patric; Amico, Enrico; Goñi, Joaquín; Avidan, Galia; Sporns, Olaf

2018-06-05

Connectomics generates comprehensive maps of brain networks, represented as nodes and their pairwise connections. The functional roles of nodes are defined by their direct and indirect connectivity with the rest of the network. However, the network context is not directly accessible at the level of individual nodes. Similar problems in language processing have been addressed with algorithms such as word2vec that create embeddings of words and their relations in a meaningful low-dimensional vector space. Here we apply this approach to create embedded vector representations of brain networks or connectome embeddings (CE). CE can characterize correspondence relations among brain regions, and can be used to infer links that are lacking from the original structural diffusion imaging, e.g., inter-hemispheric homotopic connections. Moreover, we construct predictive deep models of functional and structural connectivity, and simulate network-wide lesion effects using the face processing system as our application domain. We suggest that CE offers a novel approach to revealing relations between connectome structure and function.

On the role of general system theory for functional neuroimaging

PubMed Central

Stephan, Klaas Enno

2004-01-01

One of the most important goals of neuroscience is to establish precise structure–function relationships in the brain. Since the 19th century, a major scientific endeavour has been to associate structurally distinct cortical regions with specific cognitive functions. This was traditionally accomplished by correlating microstructurally defined areas with lesion sites found in patients with specific neuropsychological symptoms. Modern neuroimaging techniques with high spatial resolution have promised an alternative approach, enabling non-invasive measurements of regionally specific changes of brain activity that are correlated with certain components of a cognitive process. Reviewing classic approaches towards brain structure–function relationships that are based on correlational approaches, this article argues that these approaches are not sufficient to provide an understanding of the operational principles of a dynamic system such as the brain but must be complemented by models based on general system theory. These models reflect the connectional structure of the system under investigation and emphasize context-dependent couplings between the system elements in terms of effective connectivity. The usefulness of system models whose parameters are fitted to measured functional imaging data for testing hypotheses about structure–function relationships in the brain and their potential for clinical applications is demonstrated by several empirical examples. PMID:15610393

Modeling and Circumventing the Effect of Sediments and Water Column on Receiver Functions

NASA Astrophysics Data System (ADS)

Audet, P.

2017-12-01

Teleseismic P-wave receiver functions are routinely used to resolve crust and mantle structure in various geologic settings. Receiver functions are approximations to the Earth's Green's functions and are composed of various scattered phase arrivals, depending on the complexity of the underlying Earth structure. For simple structure, the dominant arrivals (converted and back-scattered P-to-S phases) are well separated in time and can be reliably used in estimating crustal velocity structure. In the presence of sedimentary layers, strong reverberations typically produce high-amplitude oscillations that contaminate the early part of the wave train and receiver functions can be difficult to interpret in terms of underlying structure. The effect of a water column also limits the interpretability of under-water receiver functions due to the additional acoustic wave propagating within the water column that can contaminate structural arrivals. We perform numerical modeling of teleseismic Green's functions and receiver functions using a reflectivity technique for a range of Earth models that include thin sedimentary layers and overlying water column. These modeling results indicate that, as expected, receiver functions are difficult to interpret in the presence of sediments, but the contaminating effect of the water column is dependent on the thickness of the water layer. To circumvent these effects and recover source-side structure, we propose using an approach based on transfer function modeling that bypasses receiver functions altogether and estimates crustal properties directly from the waveforms (Frederiksen and Delayney, 2015). Using this approach, reasonable assumptions about the properties of the sedimentary layer can be included in forward calculations of the Green's functions that are convolved with radial waveforms to predict vertical waveforms. Exploration of model space using Monte Carlo-style search and least-square waveform misfits can be performed to estimate any model parameter of interest, including those of the sedimentary or water layer. We show how this method can be applied to OBS data using broadband stations from the Cascadia Initiative to recover oceanic plate structure.

A Critical Assessment of the Performance of Protein-ligand Scoring Functions Based on NMR Chemical Shift Perturbations

PubMed Central

Wang, Bing; Westerhoff, Lance M.; Merz, Kenneth M.

2008-01-01

We have generated docking poses for the FKBP-GPI complex using eight docking programs, and compared their scoring functions with scoring based on NMR chemical shift perturbations (NMRScore). Because the chemical shift perturbation (CSP) is exquisitely sensitive on the orientation of ligand inside the binding pocket, NMRScore offers an accurate and straightforward approach to score different poses. All scoring functions were inspected by their abilities to highly rank the native-like structures and separate them from decoy poses generated for a protein-ligand complex. The overall performance of NMRScore is much better than that of energy-based scoring functions associated with docking programs in both aspects. In summary, we find that the combination of docking programs with NMRScore results in an approach that can robustly determine the binding site structure for a protein-ligand complex, thereby, providing a new tool facilitating the structure-based drug discovery process. PMID:17867664

Diagnostic approaches for diabetic cardiomyopathy and myocardial fibrosis

PubMed Central

Maya, Lisandro; Villarreal, Francisco J.

2009-01-01

In diabetes mellitus, alterations in cardiac structure/function in the absence of ischemic heart disease, hypertension or other cardiac pathologies is termed diabetic cardiomyopathy. In the United States, the prevalence of diabetes mellitus continues to rise and the disease currently affects about 8% of the general population. Hence, it is imperative the use of appropriate diagnostic strategies for diabetic cardiomyopathy, which may help correctly identify the disease at early stages and implement suitable corrective therapies. Currently, there is no single diagnostic method for the identification of diabetic cardiomyopathy. Diabetic cardiomyopathy is known to induce changes in cardiac structure such as, myocardial hypertrophy, fibrosis and fat droplet deposition. Early changes in cardiac function are typically manifested as abnormal diastolic function that with time leads to loss of contractile function. Echocardiography based methods currently stands as the preferred diagnostic approach for diabetic cardiomyopathy, due to its wide availability and economical use. In addition to conventional techniques, magnetic resonance imaging and spectroscopy along with contrast agents are now leading new approaches in the diagnosis of myocardial fibrosis, and cardiac and hepatic metabolic changes. These strategies can be complemented with serum biomarkers so they can offer a clear picture as to diabetes-induced changes in cardiac structure/function even at very early stages of the disease. This review article intends to provide a summary of experimental and routine tools currently available to diagnose diabetic cardiomyopathy induced changes in cardiac structure/function. These tools can be reliably used in either experimental models of diabetes or for clinical applications. PMID:19595694

Integrated reclamation: Approaching ecological function?

Treesearch

Ann L. Hild; Nancy L. Shaw; Ginger B. Paige

2009-01-01

Attempts to reclaim arid and semiarid lands have traditionally targeted plant species composition. Much research attention has been directed to seeding rates, species mixes and timing of seeding. However, in order to attain functioning systems, attention to structure and process must compliment existing efforts. We ask how to use a systems approach to enhance...

A topological approach for protein classification

DOE PAGES

Cang, Zixuan; Mu, Lin; Wu, Kedi; ...

2015-11-04

Here, protein function and dynamics are closely related to its sequence and structure. However, prediction of protein function and dynamics from its sequence and structure is still a fundamental challenge in molecular biology. Protein classification, which is typically done through measuring the similarity between proteins based on protein sequence or physical information, serves as a crucial step toward the understanding of protein function and dynamics.

Cerebral perfusion computed tomography deconvolution via structure tensor total variation regularization

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

Zeng, Dong; Zhang, Xinyu; Bian, Zhaoying, E-mail: zybian@smu.edu.cn, E-mail: jhma@smu.edu.cn

Purpose: Cerebral perfusion computed tomography (PCT) imaging as an accurate and fast acute ischemic stroke examination has been widely used in clinic. Meanwhile, a major drawback of PCT imaging is the high radiation dose due to its dynamic scan protocol. The purpose of this work is to develop a robust perfusion deconvolution approach via structure tensor total variation (STV) regularization (PD-STV) for estimating an accurate residue function in PCT imaging with the low-milliampere-seconds (low-mAs) data acquisition. Methods: Besides modeling the spatio-temporal structure information of PCT data, the STV regularization of the present PD-STV approach can utilize the higher order derivativesmore » of the residue function to enhance denoising performance. To minimize the objective function, the authors propose an effective iterative algorithm with a shrinkage/thresholding scheme. A simulation study on a digital brain perfusion phantom and a clinical study on an old infarction patient were conducted to validate and evaluate the performance of the present PD-STV approach. Results: In the digital phantom study, visual inspection and quantitative metrics (i.e., the normalized mean square error, the peak signal-to-noise ratio, and the universal quality index) assessments demonstrated that the PD-STV approach outperformed other existing approaches in terms of the performance of noise-induced artifacts reduction and accurate perfusion hemodynamic maps (PHM) estimation. In the patient data study, the present PD-STV approach could yield accurate PHM estimation with several noticeable gains over other existing approaches in terms of visual inspection and correlation analysis. Conclusions: This study demonstrated the feasibility and efficacy of the present PD-STV approach in utilizing STV regularization to improve the accuracy of residue function estimation of cerebral PCT imaging in the case of low-mAs.« less

Propagation of eigenmodes and transfer functions in waveguide WDM structures

NASA Astrophysics Data System (ADS)

Mashkov, Vladimir A.; Francoeur, S.; Geuss, U.; Neiser, K.; Temkin, Henryk

1998-02-01

A method of propagation functions and transfer amplitudes suitable for the design of integrated optical circuits is presented. The method is based on vectorial formulation of electrodynamics: the distributions and propagation of electromagnetic fields in optical circuits is described by equivalent surface sources. This approach permits a division of complex optical waveguide structures into sets of primitive blocks and to separately calculate the transfer function and the transfer amplitude for each block. The transfer amplitude of the entire optical system is represented by a convolution of transfer amplitudes of its primitive blocks. The eigenvalues and eigenfunctions of arbitrary waveguide structure are obtained in the WKB approximation and compared with other methods. The general approach is illustrated with the transfer amplitude calculations for Dragone's star coupler and router.

Toward a standardized structural-functional group connectome in MNI space.

PubMed

Horn, Andreas; Blankenburg, Felix

2016-01-01

The analysis of the structural architecture of the human brain in terms of connectivity between its subregions has provided profound insights into its underlying functional organization and has coined the concept of the "connectome", a structural description of the elements forming the human brain and the connections among them. Here, as a proof of concept, we introduce a novel group connectome in standard space based on a large sample of 169 subjects from the Enhanced Nathan Kline Institute-Rockland Sample (eNKI-RS). Whole brain structural connectomes of each subject were estimated with a global tracking approach, and the resulting fiber tracts were warped into standard stereotactic (MNI) space using DARTEL. Employing this group connectome, the results of published tracking studies (i.e., the JHU white matter and Oxford thalamic connectivity atlas) could be largely reproduced directly within MNI space. In a second analysis, a study that examined structural connectivity between regions of a functional network, namely the default mode network, was reproduced. Voxel-wise structural centrality was then calculated and compared to others' findings. Furthermore, including additional resting-state fMRI data from the same subjects, structural and functional connectivity matrices between approximately forty thousand nodes of the brain were calculated. This was done to estimate structure-function agreement indices of voxel-wise whole brain connectivity. Taken together, the combination of a novel whole brain fiber tracking approach and an advanced normalization method led to a group connectome that allowed (at least heuristically) performing fiber tracking directly within MNI space. Such an approach may be used for various purposes like the analysis of structural connectivity and modeling experiments that aim at studying the structure-function relationship of the human connectome. Moreover, it may even represent a first step toward a standard DTI template of the human brain in stereotactic space. The standardized group connectome might thus be a promising new resource to better understand and further analyze the anatomical architecture of the human brain on a population level. Copyright © 2015 Elsevier Inc. All rights reserved.

Comparison of topological clustering within protein networks using edge metrics that evaluate full sequence, full structure, and active site microenvironment similarity.

PubMed

Leuthaeuser, Janelle B; Knutson, Stacy T; Kumar, Kiran; Babbitt, Patricia C; Fetrow, Jacquelyn S

2015-09-01

The development of accurate protein function annotation methods has emerged as a major unsolved biological problem. Protein similarity networks, one approach to function annotation via annotation transfer, group proteins into similarity-based clusters. An underlying assumption is that the edge metric used to identify such clusters correlates with functional information. In this contribution, this assumption is evaluated by observing topologies in similarity networks using three different edge metrics: sequence (BLAST), structure (TM-Align), and active site similarity (active site profiling, implemented in DASP). Network topologies for four well-studied protein superfamilies (enolase, peroxiredoxin (Prx), glutathione transferase (GST), and crotonase) were compared with curated functional hierarchies and structure. As expected, network topology differs, depending on edge metric; comparison of topologies provides valuable information on structure/function relationships. Subnetworks based on active site similarity correlate with known functional hierarchies at a single edge threshold more often than sequence- or structure-based networks. Sequence- and structure-based networks are useful for identifying sequence and domain similarities and differences; therefore, it is important to consider the clustering goal before deciding appropriate edge metric. Further, conserved active site residues identified in enolase and GST active site subnetworks correspond with published functionally important residues. Extension of this analysis yields predictions of functionally determinant residues for GST subgroups. These results support the hypothesis that active site similarity-based networks reveal clusters that share functional details and lay the foundation for capturing functionally relevant hierarchies using an approach that is both automatable and can deliver greater precision in function annotation than current similarity-based methods. © 2015 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

Comparison of topological clustering within protein networks using edge metrics that evaluate full sequence, full structure, and active site microenvironment similarity

PubMed Central

Leuthaeuser, Janelle B; Knutson, Stacy T; Kumar, Kiran; Babbitt, Patricia C; Fetrow, Jacquelyn S

2015-01-01

The development of accurate protein function annotation methods has emerged as a major unsolved biological problem. Protein similarity networks, one approach to function annotation via annotation transfer, group proteins into similarity-based clusters. An underlying assumption is that the edge metric used to identify such clusters correlates with functional information. In this contribution, this assumption is evaluated by observing topologies in similarity networks using three different edge metrics: sequence (BLAST), structure (TM-Align), and active site similarity (active site profiling, implemented in DASP). Network topologies for four well-studied protein superfamilies (enolase, peroxiredoxin (Prx), glutathione transferase (GST), and crotonase) were compared with curated functional hierarchies and structure. As expected, network topology differs, depending on edge metric; comparison of topologies provides valuable information on structure/function relationships. Subnetworks based on active site similarity correlate with known functional hierarchies at a single edge threshold more often than sequence- or structure-based networks. Sequence- and structure-based networks are useful for identifying sequence and domain similarities and differences; therefore, it is important to consider the clustering goal before deciding appropriate edge metric. Further, conserved active site residues identified in enolase and GST active site subnetworks correspond with published functionally important residues. Extension of this analysis yields predictions of functionally determinant residues for GST subgroups. These results support the hypothesis that active site similarity-based networks reveal clusters that share functional details and lay the foundation for capturing functionally relevant hierarchies using an approach that is both automatable and can deliver greater precision in function annotation than current similarity-based methods. PMID:26073648

Functional insights from proteome-wide structural modeling of Treponema pallidum subspecies pallidum, the causative agent of syphilis.

PubMed

Houston, Simon; Lithgow, Karen Vivien; Osbak, Kara Krista; Kenyon, Chris Richard; Cameron, Caroline E

2018-05-16

Syphilis continues to be a major global health threat with 11 million new infections each year, and a global burden of 36 million cases. The causative agent of syphilis, Treponema pallidum subspecies pallidum, is a highly virulent bacterium, however the molecular mechanisms underlying T. pallidum pathogenesis remain to be definitively identified. This is due to the fact that T. pallidum is currently uncultivatable, inherently fragile and thus difficult to work with, and phylogenetically distinct with no conventional virulence factor homologs found in other pathogens. In fact, approximately 30% of its predicted protein-coding genes have no known orthologs or assigned functions. Here we employed a structural bioinformatics approach using Phyre2-based tertiary structure modeling to improve our understanding of T. pallidum protein function on a proteome-wide scale. Phyre2-based tertiary structure modeling generated high-confidence predictions for 80% of the T. pallidum proteome (780/978 predicted proteins). Tertiary structure modeling also inferred the same function as primary structure-based annotations from genome sequencing pipelines for 525/605 proteins (87%), which represents 54% (525/978) of all T. pallidum proteins. Of the 175 T. pallidum proteins modeled with high confidence that were not assigned functions in the previously annotated published proteome, 167 (95%) were able to be assigned predicted functions. Twenty-one of the 175 hypothetical proteins modeled with high confidence were also predicted to exhibit significant structural similarity with proteins experimentally confirmed to be required for virulence in other pathogens. Phyre2-based structural modeling is a powerful bioinformatics tool that has provided insight into the potential structure and function of the majority of T. pallidum proteins and helped validate the primary structure-based annotation of more than 50% of all T. pallidum proteins with high confidence. This work represents the first T. pallidum proteome-wide structural modeling study and is one of few studies to apply this approach for the functional annotation of a whole proteome.

Computational predictions of the new Gallium nitride nanoporous structures

NASA Astrophysics Data System (ADS)

Lien, Le Thi Hong; Tuoc, Vu Ngoc; Duong, Do Thi; Thu Huyen, Nguyen

2018-05-01

Nanoporous structural prediction is emerging area of research because of their advantages for a wide range of materials science and technology applications in opto-electronics, environment, sensors, shape-selective and bio-catalysis, to name just a few. We propose a computationally and technically feasible approach for predicting Gallium nitride nanoporous structures with hollows at the nano scale. The designed porous structures are studied with computations using the density functional tight binding (DFTB) and conventional density functional theory methods, revealing a variety of promising mechanical and electronic properties, which can potentially find future realistic applications. Their stability is discussed by means of the free energy computed within the lattice-dynamics approach. Our calculations also indicate that all the reported hollow structures are wide band gap semiconductors in the same fashion with their parent’s bulk stable phase. The electronic band structures of these nanoporous structures are finally examined in detail.

Computational analysis of conserved RNA secondary structure in transcriptomes and genomes.

PubMed

Eddy, Sean R

2014-01-01

Transcriptomics experiments and computational predictions both enable systematic discovery of new functional RNAs. However, many putative noncoding transcripts arise instead from artifacts and biological noise, and current computational prediction methods have high false positive rates. I discuss prospects for improving computational methods for analyzing and identifying functional RNAs, with a focus on detecting signatures of conserved RNA secondary structure. An interesting new front is the application of chemical and enzymatic experiments that probe RNA structure on a transcriptome-wide scale. I review several proposed approaches for incorporating structure probing data into the computational prediction of RNA secondary structure. Using probabilistic inference formalisms, I show how all these approaches can be unified in a well-principled framework, which in turn allows RNA probing data to be easily integrated into a wide range of analyses that depend on RNA secondary structure inference. Such analyses include homology search and genome-wide detection of new structural RNAs.

An Exploratory Study on the Purpose, Structure, Format and Use of Syllabi at a Midwest Four-Year Undergraduate Private University

ERIC Educational Resources Information Center

Fink, Susan Jo Breakenridge

2011-01-01

The purpose of this study was to explore how instructors at a mid-sized Midwest four-year undergraduate private university view the purpose, structure, format and use of their course syllabi. The theory of structural functionalism and a quantitative research approach were employed. A group administration approach was used to distribute the paper…

Bridging the Gap between Structures and Properties: An Investigation and Evaluation of Students' Representational Competence

ERIC Educational Resources Information Center

Underwood, Sonia Miller

2011-01-01

The heart of learning chemistry is the ability to connect a compound's structure to its function; Lewis structures provide an essential link in this process. In many cases, their construction is taught using an algorithmic approach, containing a set of step-by-step rules. We believe that this approach is in direct conflict with the precepts of…

A multiomics approach to study the microbiome response to phytoplankton blooms.

PubMed

Song, Liyan

2017-06-01

Phytoplankton blooms are predictable features of marine and freshwater habitats. Despite a good knowledge base of the environmental factors controlling blooms, complex interactions between the bacterial and archaeal communities and phytoplankton bloom taxa are only now emerging. Here, the current research on bacterial community's structural and functional response to phytoplankton blooms is reviewed and discussed and further research is proposed. More attention should be paid on structure and function of autotrophic bacteria and archaea during phytoplankton blooms. A multiomics integration approach is needed to investigate bacterial and archaeal communities' diversity, metabolic diversity, and biogeochemical functions of microbial interactions during phytoplankton blooms.

Neck-Related Physical Function, Self-Efficacy, and Coping Strategies in Patients With Cervical Radiculopathy: A Randomized Clinical Trial of Postoperative Physiotherapy.

PubMed

Wibault, Johanna; Öberg, Birgitta; Dedering, Åsa; Löfgren, Håkan; Zsigmond, Peter; Persson, Liselott; Andell, Maria; R Jonsson, Margareta; Peolsson, Anneli

2017-06-01

The purpose of this study was to compare postoperative rehabilitation with structured physiotherapy to the standard approach in patients with cervical radiculopathy (CR) in a prospective randomized study at 6 months follow-up based on measures of neck-related physical function, self-efficacy, and coping strategies. Patients with persistent CR and scheduled for surgery (N = 202) were randomly assigned to structured postoperative physiotherapy or a standard postoperative approach. Structured postoperative physiotherapy combined neck-specific exercises with a behavioral approach. Baseline, 3-month, and 6-month evaluations included questionnaires and clinical examinations. Neck muscle endurance, active cervical range of motion, self-efficacy, pain catastrophizing (CSQ-CAT), perceived control over pain, and ability to decrease pain were analyzed for between-group differences using complete case and per-protocol approaches. No between-group difference was reported at the 6-month follow-up (P = .05-.99), but all outcomes had improved from baseline (P < .001). Patients undergoing structured postoperative physiotherapy with ≥50% attendance at treatment sessions had larger improvements in CSQ-CAT (P = .04) during the rehabilitation period from 3 to 6 months after surgery compared with the patients who received standard postoperative approach. No between-group difference was found at 6 months after surgery based on measures of neck-related physical function, self-efficacy, and coping strategies. However, the results confirm that neck-specific exercises are tolerated by patients with CR after surgery and may suggest a benefit from combining surgery with structured postoperative physiotherapy for patients with CR. Copyright © 2017. Published by Elsevier Inc.

Construction of a Hierarchical Architecture of Covalent Organic Frameworks via a Postsynthetic Approach.

PubMed

Zhang, Gen; Tsujimoto, Masahiko; Packwood, Daniel; Duong, Nghia Tuan; Nishiyama, Yusuke; Kadota, Kentaro; Kitagawa, Susumu; Horike, Satoshi

2018-02-21

Covalent organic frameworks (COFs) represent an emerging class of crystalline porous materials that are constructed by the assembly of organic building blocks linked via covalent bonds. Several strategies have been developed for the construction of new COF structures; however, a facile approach to fabricate hierarchical COF architectures with controlled domain structures remains a significant challenge, and has not yet been achieved. In this study, a dynamic covalent chemistry (DCC)-based postsynthetic approach was employed at the solid-liquid interface to construct such structures. Two-dimensional imine-bonded COFs having different aromatic groups were prepared, and a homogeneously mixed-linker structure and a heterogeneously core-shell hollow structure were fabricated by controlling the reactivity of the postsynthetic reactions. Solid-state nuclear magnetic resonance (NMR) spectroscopy and transmission electron microscopy (TEM) confirmed the structures. COFs prepared by a postsynthetic approach exhibit several functional advantages compared with their parent phases. Their Brunauer-Emmett-Teller (BET) surface areas are 2-fold greater than those of their parent phases because of the higher crystallinity. In addition, the hydrophilicity of the material and the stepwise adsorption isotherms of H 2 O vapor in the hierarchical frameworks were precisely controlled, which was feasible because of the distribution of various domains of the two COFs by controlling the postsynthetic reaction. The approach opens new routes for constructing COF architectures with functionalities that are not possible in a single phase.

Comparison of roll-to-roll replication approaches for microfluidic and optical functions in lab-on-a-chip diagnostic devices

NASA Astrophysics Data System (ADS)

Brecher, Christian; Baum, Christoph; Bastuck, Thomas

2015-03-01

Economically advantageous microfabrication technologies for lab-on-a-chip diagnostic devices substituting commonly used glass etching or injection molding processes are one of the key enablers for the emerging market of microfluidic devices. On-site detection in fields of life sciences, point of care diagnostics and environmental analysis requires compact, disposable and highly functionalized systems. Roll-to-roll production as a high volume process has become the emerging fabrication technology for integrated, complex high technology products within recent years (e.g. fuel cells). Differently functionalized polymer films enable researchers to create a new generation of lab-on-a-chip devices by combining electronic, microfluidic and optical functions in multilayer architecture. For replication of microfluidic and optical functions via roll-to-roll production process competitive approaches are available. One of them is to imprint fluidic channels and optical structures of micro- or nanometer scale from embossing rollers into ultraviolet (UV) curable lacquers on polymer substrates. Depending on dimension, shape and quantity of those structures there are alternative manufacturing technologies for the embossing roller. Ultra-precise diamond turning, electroforming or casting polymer materials are used either for direct structuring or manufacturing of roller sleeves. Mastering methods are selected for application considering replication quality required and structure complexity. Criteria for the replication quality are surface roughness and contour accuracy. Structure complexity is evaluated by shapes producible (e.g. linear, circular) and aspect ratio. Costs for the mastering process and structure lifetime are major cost factors. The alternative replication approaches are introduced and analyzed corresponding to the criteria presented. Advantages and drawbacks of each technology are discussed and exemplary applications are presented.

On imputing function to structure from the behavioural effects of brain lesions.

PubMed

Young, M P; Hilgetag, C C; Scannell, J W

2000-01-29

What is the link, if any, between the patterns of connections in the brain and the behavioural effects of localized brain lesions? We explored this question in four related ways. First, we investigated the distribution of activity decrements that followed simulated damage to elements of the thalamocortical network, using integrative mechanisms that have recently been used to successfully relate connection data to information on the spread of activation, and to account simultaneously for a variety of lesion effects. Second, we examined the consequences of the patterns of decrement seen in the simulation for each type of inference that has been employed to impute function to structure on the basis of the effects of brain lesions. Every variety of conventional inference, including double dissociation, readily misattributed function to structure. Third, we tried to derive a more reliable framework of inference for imputing function to structure, by clarifying concepts of function, and exploring a more formal framework, in which knowledge of connectivity is necessary but insufficient, based on concepts capable of mathematical specification. Fourth, we applied this framework to inferences about function relating to a simple network that reproduces intact, lesioned and paradoxically restored orientating behaviour. Lesion effects could be used to recover detailed and reliable information on which structures contributed to particular functions in this simple network. Finally, we explored how the effects of brain lesions and this formal approach could be used in conjunction with information from multiple neuroscience methodologies to develop a practical and reliable approach to inferring the functional roles of brain structures.

TIM Barrel Protein Structure Classification Using Alignment Approach and Best Hit Strategy

NASA Astrophysics Data System (ADS)

Chu, Jia-Han; Lin, Chun Yuan; Chang, Cheng-Wen; Lee, Chihan; Yang, Yuh-Shyong; Tang, Chuan Yi

2007-11-01

The classification of protein structures is essential for their function determination in bioinformatics. It has been estimated that around 10% of all known enzymes have TIM barrel domains from the Structural Classification of Proteins (SCOP) database. With its high sequence variation and diverse functionalities, TIM barrel protein becomes to be an attractive target for protein engineering and for the evolution study. Hence, in this paper, an alignment approach with the best hit strategy is proposed to classify the TIM barrel protein structure in terms of superfamily and family levels in the SCOP. This work is also used to do the classification for class level in the Enzyme nomenclature (ENZYME) database. Two testing data sets, TIM40D and TIM95D, both are used to evaluate this approach. The resulting classification has an overall prediction accuracy rate of 90.3% for the superfamily level in the SCOP, 89.5% for the family level in the SCOP and 70.1% for the class level in the ENZYME. These results demonstrate that the alignment approach with the best hit strategy is a simple and viable method for the TIM barrel protein structure classification, even only has the amino acid sequences information.

Information Resources Usage in Project Management Digital Learning System

ERIC Educational Resources Information Center

Davidovitch, Nitza; Belichenko, Margarita; Kravchenko, Yurii

2017-01-01

The article combines a theoretical approach to structuring knowledge that is based on the integrated use of fuzzy semantic network theory predicates, Boolean functions, theory of complexity of network structures and some practical aspects to be considered in the distance learning at the university. The paper proposes a methodological approach that…

A Self-Instructional Approach To the Teaching of Enzymology Involving Computer-Based Sequence Analysis and Molecular Modelling.

ERIC Educational Resources Information Center

Attwood, Paul V.

1997-01-01

Describes a self-instructional assignment approach to the teaching of advanced enzymology. Presents an assignment that offers a means of teaching enzymology to students that exposes them to modern computer-based techniques of analyzing protein structure and relates structure to enzyme function. (JRH)

Functional Anthology of Intrinsic Disorder. I. Biological Processes and Functions of Proteins with Long Disordered Regions

PubMed Central

Xie, Hongbo; Vucetic, Slobodan; Iakoucheva, Lilia M.; Oldfield, Christopher J.; Dunker, A. Keith; Uversky, Vladimir N.; Obradovic, Zoran

2008-01-01

Identifying relationships between function, amino acid sequence and protein structure represents a major challenge. In this study we propose a bioinformatics approach that identifies functional keywords in the Swiss-Prot database that correlate with intrinsic disorder. A statistical evaluation is employed to rank the significance of these correlations. Protein sequence data redundancy and the relationship between protein length and protein structure were taken into consideration to ensure the quality of the statistical inferences. Over 200,000 proteins from Swiss-Prot database were analyzed using this approach. The predictions of intrinsic disorder were carried out using PONDR VL3E predictor of long disordered regions that achieves an accuracy of above 86%. Overall, out of the 710 Swiss-Prot functional keywords that were each associated with at least 20 proteins, 238 were found to be strongly positively correlated with predicted long intrinsically disordered regions, whereas 302 were strongly negatively correlated with such regions. The remaining 170 keywords were ambiguous without strong positive or negative correlation with the disorder predictions. These functions cover a large variety of biological activities and imply that disordered regions are characterized by a wide functional repertoire. Our results agree well with literature findings, as we were able to find at least one illustrative example of functional disorder or order shown experimentally for the vast majority of keywords showing the strongest positive or negative correlation with intrinsic disorder. This work opens a series of three papers, which enriches the current view of protein structure-function relationships, especially with regards to functionalities of intrinsically disordered proteins and provides researchers with a novel tool that could be used to improve the understanding of the relationships between protein structure and function. The first paper of the series describes our statistical approach, outlines the major findings and provides illustrative examples of biological processes and functions positively and negatively correlated with intrinsic disorder. PMID:17391014

Functional anthology of intrinsic disorder. 1. Biological processes and functions of proteins with long disordered regions.

PubMed

Xie, Hongbo; Vucetic, Slobodan; Iakoucheva, Lilia M; Oldfield, Christopher J; Dunker, A Keith; Uversky, Vladimir N; Obradovic, Zoran

2007-05-01

Identifying relationships between function, amino acid sequence, and protein structure represents a major challenge. In this study, we propose a bioinformatics approach that identifies functional keywords in the Swiss-Prot database that correlate with intrinsic disorder. A statistical evaluation is employed to rank the significance of these correlations. Protein sequence data redundancy and the relationship between protein length and protein structure were taken into consideration to ensure the quality of the statistical inferences. Over 200,000 proteins from the Swiss-Prot database were analyzed using this approach. The predictions of intrinsic disorder were carried out using PONDR VL3E predictor of long disordered regions that achieves an accuracy of above 86%. Overall, out of the 710 Swiss-Prot functional keywords that were each associated with at least 20 proteins, 238 were found to be strongly positively correlated with predicted long intrinsically disordered regions, whereas 302 were strongly negatively correlated with such regions. The remaining 170 keywords were ambiguous without strong positive or negative correlation with the disorder predictions. These functions cover a large variety of biological activities and imply that disordered regions are characterized by a wide functional repertoire. Our results agree well with literature findings, as we were able to find at least one illustrative example of functional disorder or order shown experimentally for the vast majority of keywords showing the strongest positive or negative correlation with intrinsic disorder. This work opens a series of three papers, which enriches the current view of protein structure-function relationships, especially with regards to functionalities of intrinsically disordered proteins, and provides researchers with a novel tool that could be used to improve the understanding of the relationships between protein structure and function. The first paper of the series describes our statistical approach, outlines the major findings, and provides illustrative examples of biological processes and functions positively and negatively correlated with intrinsic disorder.

Towards quantitative classification of folded proteins in terms of elementary functions.

PubMed

Hu, Shuangwei; Krokhotin, Andrei; Niemi, Antti J; Peng, Xubiao

2011-04-01

A comparative classification scheme provides a good basis for several approaches to understand proteins, including prediction of relations between their structure and biological function. But it remains a challenge to combine a classification scheme that describes a protein starting from its well-organized secondary structures and often involves direct human involvement, with an atomary-level physics-based approach where a protein is fundamentally nothing more than an ensemble of mutually interacting carbon, hydrogen, oxygen, and nitrogen atoms. In order to bridge these two complementary approaches to proteins, conceptually novel tools need to be introduced. Here we explain how an approach toward geometric characterization of entire folded proteins can be based on a single explicit elementary function that is familiar from nonlinear physical systems where it is known as the kink soliton. Our approach enables the conversion of hierarchical structural information into a quantitative form that allows for a folded protein to be characterized in terms of a small number of global parameters that are in principle computable from atomary-level considerations. As an example we describe in detail how the native fold of the myoglobin 1M6C emerges from a combination of kink solitons with a very high atomary-level accuracy. We also verify that our approach describes longer loops and loops connecting α helices with β strands, with the same overall accuracy. ©2011 American Physical Society

Structure-function clustering in multiplex brain networks

NASA Astrophysics Data System (ADS)

Crofts, J. J.; Forrester, M.; O'Dea, R. D.

2016-10-01

A key question in neuroscience is to understand how a rich functional repertoire of brain activity arises within relatively static networks of structurally connected neural populations: elucidating the subtle interactions between evoked “functional connectivity” and the underlying “structural connectivity” has the potential to address this. These structural-functional networks (and neural networks more generally) are more naturally described using a multilayer or multiplex network approach, in favour of standard single-layer network analyses that are more typically applied to such systems. In this letter, we address such issues by exploring important structure-function relations in the Macaque cortical network by modelling it as a duplex network that comprises an anatomical layer, describing the known (macro-scale) network topology of the Macaque monkey, and a functional layer derived from simulated neural activity. We investigate and characterize correlations between structural and functional layers, as system parameters controlling simulated neural activity are varied, by employing recently described multiplex network measures. Moreover, we propose a novel measure of multiplex structure-function clustering which allows us to investigate the emergence of functional connections that are distinct from the underlying cortical structure, and to highlight the dependence of multiplex structure on the neural dynamical regime.

Observer-Based Adaptive Neural Network Control for Nonlinear Systems in Nonstrict-Feedback Form.

PubMed

Chen, Bing; Zhang, Huaguang; Lin, Chong

2016-01-01

This paper focuses on the problem of adaptive neural network (NN) control for a class of nonlinear nonstrict-feedback systems via output feedback. A novel adaptive NN backstepping output-feedback control approach is first proposed for nonlinear nonstrict-feedback systems. The monotonicity of system bounding functions and the structure character of radial basis function (RBF) NNs are used to overcome the difficulties that arise from nonstrict-feedback structure. A state observer is constructed to estimate the immeasurable state variables. By combining adaptive backstepping technique with approximation capability of radial basis function NNs, an output-feedback adaptive NN controller is designed through backstepping approach. It is shown that the proposed controller guarantees semiglobal boundedness of all the signals in the closed-loop systems. Two examples are used to illustrate the effectiveness of the proposed approach.

The management of a sexually charged clinical problem: social structural and psychoanalytic functionalist approaches in a therapeutic community.

PubMed

James, O W

1986-03-01

An event in a therapeutic community is examined from the perspectives of the structuralism of Durkheim and the functionalism of psychoanalysis. Although these two approaches might appear theoretically contradictory, analysis of the evidence shows them to be clinically complementary. The role of social structure in therapeutic communities requires deliberate conceptualization if such communities are to be demonstrably therapeutic.

Control system estimation and design for aerospace vehicles

NASA Technical Reports Server (NTRS)

Stefani, R. T.; Williams, T. L.; Yakowitz, S. J.

1972-01-01

The selection of an estimator which is unbiased when applied to structural parameter estimation is discussed. The mathematical relationships for structural parameter estimation are defined. It is shown that a conventional weighted least squares (CWLS) estimate is biased when applied to structural parameter estimation. Two approaches to bias removal are suggested: (1) change the CWLS estimator or (2) change the objective function. The advantages of each approach are analyzed.

Conformational Sampling in Template-Free Protein Loop Structure Modeling: An Overview

PubMed Central

Li, Yaohang

2013-01-01

Accurately modeling protein loops is an important step to predict three-dimensional structures as well as to understand functions of many proteins. Because of their high flexibility, modeling the three-dimensional structures of loops is difficult and is usually treated as a “mini protein folding problem” under geometric constraints. In the past decade, there has been remarkable progress in template-free loop structure modeling due to advances of computational methods as well as stably increasing number of known structures available in PDB. This mini review provides an overview on the recent computational approaches for loop structure modeling. In particular, we focus on the approaches of sampling loop conformation space, which is a critical step to obtain high resolution models in template-free methods. We review the potential energy functions for loop modeling, loop buildup mechanisms to satisfy geometric constraints, and loop conformation sampling algorithms. The recent loop modeling results are also summarized. PMID:24688696

Calculation of wakefields in 2D rectangular structures

DOE PAGES

Zagorodnov, I.; Bane, K. L. F.; Stupakov, G.

2015-10-19

We consider the calculation of electromagnetic fields generated by an electron bunch passing through a vacuum chamber structure that, in general, consists of an entry pipe, followed by some kind of transition or cavity, and ending in an exit pipe. We limit our study to structures having rectangular cross section, where the height can vary as function of longitudinal coordinate but the width and side walls remain fixed. For such structures, we derive a Fourier representation of the wake potentials through one-dimensional functions. A new numerical approach for calculating the wakes in such structures is proposed and implemented in themore » computer code echo(2d). The computation resource requirements for this approach are moderate and comparable to those for finding the wakes in 2D rotationally symmetric structures. Finally, we present numerical examples obtained with the new numerical code.« less

Multilevel Dynamic Generalized Structured Component Analysis for Brain Connectivity Analysis in Functional Neuroimaging Data.

PubMed

Jung, Kwanghee; Takane, Yoshio; Hwang, Heungsun; Woodward, Todd S

2016-06-01

We extend dynamic generalized structured component analysis (GSCA) to enhance its data-analytic capability in structural equation modeling of multi-subject time series data. Time series data of multiple subjects are typically hierarchically structured, where time points are nested within subjects who are in turn nested within a group. The proposed approach, named multilevel dynamic GSCA, accommodates the nested structure in time series data. Explicitly taking the nested structure into account, the proposed method allows investigating subject-wise variability of the loadings and path coefficients by looking at the variance estimates of the corresponding random effects, as well as fixed loadings between observed and latent variables and fixed path coefficients between latent variables. We demonstrate the effectiveness of the proposed approach by applying the method to the multi-subject functional neuroimaging data for brain connectivity analysis, where time series data-level measurements are nested within subjects.

Conformational sampling in template-free protein loop structure modeling: an overview.

PubMed

Li, Yaohang

2013-01-01

Accurately modeling protein loops is an important step to predict three-dimensional structures as well as to understand functions of many proteins. Because of their high flexibility, modeling the three-dimensional structures of loops is difficult and is usually treated as a "mini protein folding problem" under geometric constraints. In the past decade, there has been remarkable progress in template-free loop structure modeling due to advances of computational methods as well as stably increasing number of known structures available in PDB. This mini review provides an overview on the recent computational approaches for loop structure modeling. In particular, we focus on the approaches of sampling loop conformation space, which is a critical step to obtain high resolution models in template-free methods. We review the potential energy functions for loop modeling, loop buildup mechanisms to satisfy geometric constraints, and loop conformation sampling algorithms. The recent loop modeling results are also summarized.

ASICs Approach for the Implementation of a Symmetric Triangular Fuzzy Coprocessor and Its Application to Adaptive Filtering

NASA Technical Reports Server (NTRS)

Starks, Scott; Abdel-Hafeez, Saleh; Usevitch, Bryan

1997-01-01

This paper discusses the implementation of a fuzzy logic system using an ASICs design approach. The approach is based upon combining the inherent advantages of symmetric triangular membership functions and fuzzy singleton sets to obtain a novel structure for fuzzy logic system application development. The resulting structure utilizes a fuzzy static RAM to store the rule-base and the end-points of the triangular membership functions. This provides advantages over other approaches in which all sampled values of membership functions for all universes must be stored. The fuzzy coprocessor structure implements the fuzzification and defuzzification processes through a two-stage parallel pipeline architecture which is capable of executing complex fuzzy computations in less than 0.55us with an accuracy of more than 95%, thus making it suitable for a wide range of applications. Using the approach presented in this paper, a fuzzy logic rule-base can be directly downloaded via a host processor to an onchip rule-base memory with a size of 64 words. The fuzzy coprocessor's design supports up to 49 rules for seven fuzzy membership functions associated with each of the chip's two input variables. This feature allows designers to create fuzzy logic systems without the need for additional on-board memory. Finally, the paper reports on simulation studies that were conducted for several adaptive filter applications using the least mean squared adaptive algorithm for adjusting the knowledge rule-base.

Debt-maturity structures should match risk preferences.

PubMed

Gapenski, L C

1999-12-01

Key to any debt-maturity matching strategy is financing assets with the appropriate debt structure. Financial managers need to establish an optimal capital structure and then choose the best maturity-matching structure for their debt. Two maturity-matching strategies that are available to healthcare financial managers are the accounting approach and the finance approach. The accounting approach, which defines asset maturities as current or fixed, is a riskier financing strategy than the finance approach, which defines asset maturities as permanent or temporary. The added risk occurs because of the accounting approach's heavy reliance on short-term debt. The accounting approach offers the potential for lower costs at the expense of higher risk. Healthcare financial managers who believe the financing function should support the organization's operations without adding undue risk should use the finance approach to maturity matching. Asset maturities in those organizations then should be considered permanent or temporary rather than current or fixed, and the debt-maturity structure should reflect this.

Vertebrate Membrane Proteins: Structure, Function, and Insights from Biophysical Approaches

PubMed Central

MÜLLER, DANIEL J.; WU, NAN; PALCZEWSKI, KRZYSZTOF

2008-01-01

Membrane proteins are key targets for pharmacological intervention because they are vital for cellular function. Here, we analyze recent progress made in the understanding of the structure and function of membrane proteins with a focus on rhodopsin and development of atomic force microscopy techniques to study biological membranes. Membrane proteins are compartmentalized to carry out extra- and intracellular processes. Biological membranes are densely populated with membrane proteins that occupy approximately 50% of their volume. In most cases membranes contain lipid rafts, protein patches, or paracrystalline formations that lack the higher-order symmetry that would allow them to be characterized by diffraction methods. Despite many technical difficulties, several crystal structures of membrane proteins that illustrate their internal structural organization have been determined. Moreover, high-resolution atomic force microscopy, near-field scanning optical microscopy, and other lower resolution techniques have been used to investigate these structures. Single-molecule force spectroscopy tracks interactions that stabilize membrane proteins and those that switch their functional state; this spectroscopy can be applied to locate a ligand-binding site. Recent development of this technique also reveals the energy landscape of a membrane protein, defining its folding, reaction pathways, and kinetics. Future development and application of novel approaches during the coming years should provide even greater insights to the understanding of biological membrane organization and function. PMID:18321962

Radiative transfer in multilayered random medium with laminar structure - Green's function approach

NASA Technical Reports Server (NTRS)

Karam, M. A.; Fung, A. K.

1986-01-01

For a multilayered random medium with a laminar structure a Green's function approach is introduced to obtain the emitted intensity due to an arbitrary point source. It is then shown that the approach is applicable to both active and passive remote sensing. In active remote sensing, the computed radar backscattering cross section for the multilayered medium includes the effects of both volume multiple scattering and surface multiple scattering at the layer boundaries. In passive remote sensing, the brightness temperature is obtained for arbitrary temperature profiles in the layers. As an illustration the brightness temperature and reflectivity are calculated for a bounded layer and compared with results in the literature.

A real-space stochastic density matrix approach for density functional electronic structure.

PubMed

Beck, Thomas L

2015-12-21

The recent development of real-space grid methods has led to more efficient, accurate, and adaptable approaches for large-scale electrostatics and density functional electronic structure modeling. With the incorporation of multiscale techniques, linear-scaling real-space solvers are possible for density functional problems if localized orbitals are used to represent the Kohn-Sham energy functional. These methods still suffer from high computational and storage overheads, however, due to extensive matrix operations related to the underlying wave function grid representation. In this paper, an alternative stochastic method is outlined that aims to solve directly for the one-electron density matrix in real space. In order to illustrate aspects of the method, model calculations are performed for simple one-dimensional problems that display some features of the more general problem, such as spatial nodes in the density matrix. This orbital-free approach may prove helpful considering a future involving increasingly parallel computing architectures. Its primary advantage is the near-locality of the random walks, allowing for simultaneous updates of the density matrix in different regions of space partitioned across the processors. In addition, it allows for testing and enforcement of the particle number and idempotency constraints through stabilization of a Feynman-Kac functional integral as opposed to the extensive matrix operations in traditional approaches.

Free energy minimization to predict RNA secondary structures and computational RNA design.

PubMed

Churkin, Alexander; Weinbrand, Lina; Barash, Danny

2015-01-01

Determining the RNA secondary structure from sequence data by computational predictions is a long-standing problem. Its solution has been approached in two distinctive ways. If a multiple sequence alignment of a collection of homologous sequences is available, the comparative method uses phylogeny to determine conserved base pairs that are more likely to form as a result of billions of years of evolution than by chance. In the case of single sequences, recursive algorithms that compute free energy structures by using empirically derived energy parameters have been developed. This latter approach of RNA folding prediction by energy minimization is widely used to predict RNA secondary structure from sequence. For a significant number of RNA molecules, the secondary structure of the RNA molecule is indicative of its function and its computational prediction by minimizing its free energy is important for its functional analysis. A general method for free energy minimization to predict RNA secondary structures is dynamic programming, although other optimization methods have been developed as well along with empirically derived energy parameters. In this chapter, we introduce and illustrate by examples the approach of free energy minimization to predict RNA secondary structures.

Matrix Transfer Function Design for Flexible Structures: An Application

NASA Technical Reports Server (NTRS)

Brennan, T. J.; Compito, A. V.; Doran, A. L.; Gustafson, C. L.; Wong, C. L.

1985-01-01

The application of matrix transfer function design techniques to the problem of disturbance rejection on a flexible space structure is demonstrated. The design approach is based on parameterizing a class of stabilizing compensators for the plant and formulating the design specifications as a constrained minimization problem in terms of these parameters. The solution yields a matrix transfer function representation of the compensator. A state space realization of the compensator is constructed to investigate performance and stability on the nominal and perturbed models. The application is made to the ACOSSA (Active Control of Space Structures) optical structure.

A Semantic Map Approach to English Articles (A, The, and Ø)

ERIC Educational Resources Information Center

Butler, Brian C.

2012-01-01

The three structural possibilities marking a noun with an English article are "a," "the," and "Ø" (the absence of an article). Although these structural possibilities are simple, they encode a multitude of semantic and pragmatic functions, and it is these complex form-function interactions that this study explores and…

A frequency-based linguistic approach to protein decoding and design: Simple concepts, diverse applications, and the SCS Package

PubMed Central

Motomura, Kenta; Nakamura, Morikazu; Otaki, Joji M.

2013-01-01

Protein structure and function information is coded in amino acid sequences. However, the relationship between primary sequences and three-dimensional structures and functions remains enigmatic. Our approach to this fundamental biochemistry problem is based on the frequencies of short constituent sequences (SCSs) or words. A protein amino acid sequence is considered analogous to an English sentence, where SCSs are equivalent to words. Availability scores, which are defined as real SCS frequencies in the non-redundant amino acid database relative to their probabilistically expected frequencies, demonstrate the biological usage bias of SCSs. As a result, this frequency-based linguistic approach is expected to have diverse applications, such as secondary structure specifications by structure-specific SCSs and immunological adjuvants with rare or non-existent SCSs. Linguistic similarities (e.g., wide ranges of scale-free distributions) and dissimilarities (e.g., behaviors of low-rank samples) between proteins and the natural English language have been revealed in the rank-frequency relationships of SCSs or words. We have developed a web server, the SCS Package, which contains five applications for analyzing protein sequences based on the linguistic concept. These tools have the potential to assist researchers in deciphering structurally and functionally important protein sites, species-specific sequences, and functional relationships between SCSs. The SCS Package also provides researchers with a tool to construct amino acid sequences de novo based on the idiomatic usage of SCSs. PMID:24688703

A frequency-based linguistic approach to protein decoding and design: Simple concepts, diverse applications, and the SCS Package.

PubMed

Motomura, Kenta; Nakamura, Morikazu; Otaki, Joji M

2013-01-01

Protein structure and function information is coded in amino acid sequences. However, the relationship between primary sequences and three-dimensional structures and functions remains enigmatic. Our approach to this fundamental biochemistry problem is based on the frequencies of short constituent sequences (SCSs) or words. A protein amino acid sequence is considered analogous to an English sentence, where SCSs are equivalent to words. Availability scores, which are defined as real SCS frequencies in the non-redundant amino acid database relative to their probabilistically expected frequencies, demonstrate the biological usage bias of SCSs. As a result, this frequency-based linguistic approach is expected to have diverse applications, such as secondary structure specifications by structure-specific SCSs and immunological adjuvants with rare or non-existent SCSs. Linguistic similarities (e.g., wide ranges of scale-free distributions) and dissimilarities (e.g., behaviors of low-rank samples) between proteins and the natural English language have been revealed in the rank-frequency relationships of SCSs or words. We have developed a web server, the SCS Package, which contains five applications for analyzing protein sequences based on the linguistic concept. These tools have the potential to assist researchers in deciphering structurally and functionally important protein sites, species-specific sequences, and functional relationships between SCSs. The SCS Package also provides researchers with a tool to construct amino acid sequences de novo based on the idiomatic usage of SCSs.

Using multi-species occupancy models in structured decision making on managed lands

USGS Publications Warehouse

Sauer, John R.; Blank, Peter J.; Zipkin, Elise F.; Fallon, Jane E.; Fallon, Frederick W.

2013-01-01

Land managers must balance the needs of a variety of species when manipulating habitats. Structured decision making provides a systematic means of defining choices and choosing among alternative management options; implementation of a structured decision requires quantitative approaches to predicting consequences of management on the relevant species. Multi-species occupancy models provide a convenient framework for making structured decisions when the management objective is focused on a collection of species. These models use replicate survey data that are often collected on managed lands. Occupancy can be modeled for each species as a function of habitat and other environmental features, and Bayesian methods allow for estimation and prediction of collective responses of groups of species to alternative scenarios of habitat management. We provide an example of this approach using data from breeding bird surveys conducted in 2008 at the Patuxent Research Refuge in Laurel, Maryland, evaluating the effects of eliminating meadow and wetland habitats on scrub-successional and woodland-breeding bird species using summed total occupancy of species as an objective function. Removal of meadows and wetlands decreased value of an objective function based on scrub-successional species by 23.3% (95% CI: 20.3–26.5), but caused only a 2% (0.5, 3.5) increase in value of an objective function based on woodland species, documenting differential effects of elimination of meadows and wetlands on these groups of breeding birds. This approach provides a useful quantitative tool for managers interested in structured decision making.

Diagnosis and sensor validation through knowledge of structure and function

NASA Technical Reports Server (NTRS)

Scarl, Ethan A.; Jamieson, John R.; Delaune, Carl I.

1987-01-01

The liquid oxygen expert system 'LES' is proposed as the first capable of diagnostic reasoning from sensor data, using model-based knowledge of structure and function to find the expected state of all system objects, including sensors. The approach is generally algorithmic rather than heuristic, and represents uncertainties as sets of possibilities. Functional relationships are inverted to determine hypothetical values for potentially faulty objects, and may include conditional functions not normally considered to have inverses.

Use of designed sequences in protein structure recognition.

PubMed

Kumar, Gayatri; Mudgal, Richa; Srinivasan, Narayanaswamy; Sandhya, Sankaran

2018-05-09

Knowledge of the protein structure is a pre-requisite for improved understanding of molecular function. The gap in the sequence-structure space has increased in the post-genomic era. Grouping related protein sequences into families can aid in narrowing the gap. In the Pfam database, structure description is provided for part or full-length proteins of 7726 families. For the remaining 52% of the families, information on 3-D structure is not yet available. We use the computationally designed sequences that are intermediately related to two protein domain families, which are already known to share the same fold. These strategically designed sequences enable detection of distant relationships and here, we have employed them for the purpose of structure recognition of protein families of yet unknown structure. We first measured the success rate of our approach using a dataset of protein families of known fold and achieved a success rate of 88%. Next, for 1392 families of yet unknown structure, we made structural assignments for part/full length of the proteins. Fold association for 423 domains of unknown function (DUFs) are provided as a step towards functional annotation. The results indicate that knowledge-based filling of gaps in protein sequence space is a lucrative approach for structure recognition. Such sequences assist in traversal through protein sequence space and effectively function as 'linkers', where natural linkers between distant proteins are unavailable. This article was reviewed by Oliviero Carugo, Christine Orengo and Srikrishna Subramanian.

Towards aspect-oriented functional--structural plant modelling.

PubMed

Cieslak, Mikolaj; Seleznyova, Alla N; Prusinkiewicz, Przemyslaw; Hanan, Jim

2011-10-01

Functional-structural plant models (FSPMs) are used to integrate knowledge and test hypotheses of plant behaviour, and to aid in the development of decision support systems. A significant amount of effort is being put into providing a sound methodology for building them. Standard techniques, such as procedural or object-oriented programming, are not suited for clearly separating aspects of plant function that criss-cross between different components of plant structure, which makes it difficult to reuse and share their implementations. The aim of this paper is to present an aspect-oriented programming approach that helps to overcome this difficulty. The L-system-based plant modelling language L+C was used to develop an aspect-oriented approach to plant modelling based on multi-modules. Each element of the plant structure was represented by a sequence of L-system modules (rather than a single module), with each module representing an aspect of the element's function. Separate sets of productions were used for modelling each aspect, with context-sensitive rules facilitated by local lists of modules to consider/ignore. Aspect weaving or communication between aspects was made possible through the use of pseudo-L-systems, where the strict-predecessor of a production rule was specified as a multi-module. The new approach was used to integrate previously modelled aspects of carbon dynamics, apical dominance and biomechanics with a model of a developing kiwifruit shoot. These aspects were specified independently and their implementation was based on source code provided by the original authors without major changes. This new aspect-oriented approach to plant modelling is well suited for studying complex phenomena in plant science, because it can be used to integrate separate models of individual aspects of plant development and function, both previously constructed and new, into clearly organized, comprehensive FSPMs. In a future work, this approach could be further extended into an aspect-oriented programming language for FSPMs.

Functional regeneration and spectral reflectance of trees during succession in a highly diverse tropical dry forest ecosystem.

PubMed

Alvarez-Añorve, Mariana Y; Quesada, Mauricio; Sánchez-Azofeifa, G Arturo; Avila-Cabadilla, Luis Daniel; Gamon, John A

2012-05-01

The function of most ecosystems has been altered by human activities. To asses the recovery of plant communities, we must evaluate the recovery of plant functional traits. The seasonally dry tropical forest (SDTF), a highly threatened ecosystem, is assumed to recover relatively quickly from disturbance, but an integrated evaluation of recovery in floristic, structural, and functional terms has not been performed. In this study we aimed to (a) compare SDTF plant functional, floristic, and structural change along succession; (b) identify tree functional groups; and (c) explore the spectral properties of different successional stages. Across a SDTF successional gradient, we evaluated the change of species composition, vegetation structure, and leaf spectral reflectance and functional traits (related to water use, light acquisition, nutrient conservation, and CO(2) acquisition) of 25 abundant tree species. A complete recovery of SDTF takes longer than the time period inferred from floristic or structural data. Plant functional traits changed along succession from those that maximize photoprotection and heat dissipation in early succession, where temperature is an environmental constraint, to those that enhance light acquisition in late succession, where light may be limiting. A spectral indicator of plant photosynthetic performance (photochemical reflectance index) discriminated between early and late succession. This constitutes a foundation for further exploration of remote sensing technologies for studying tropical succession. A functional approach should be incorporated as a regular descriptor of forest succession because it provides a richer understanding of vegetation dynamics than is offered by either the floristic or structural approach alone.

Sequence-similar, structure-dissimilar protein pairs in the PDB.

PubMed

Kosloff, Mickey; Kolodny, Rachel

2008-05-01

It is often assumed that in the Protein Data Bank (PDB), two proteins with similar sequences will also have similar structures. Accordingly, it has proved useful to develop subsets of the PDB from which "redundant" structures have been removed, based on a sequence-based criterion for similarity. Similarly, when predicting protein structure using homology modeling, if a template structure for modeling a target sequence is selected by sequence alone, this implicitly assumes that all sequence-similar templates are equivalent. Here, we show that this assumption is often not correct and that standard approaches to create subsets of the PDB can lead to the loss of structurally and functionally important information. We have carried out sequence-based structural superpositions and geometry-based structural alignments of a large number of protein pairs to determine the extent to which sequence similarity ensures structural similarity. We find many examples where two proteins that are similar in sequence have structures that differ significantly from one another. The source of the structural differences usually has a functional basis. The number of such proteins pairs that are identified and the magnitude of the dissimilarity depend on the approach that is used to calculate the differences; in particular sequence-based structure superpositioning will identify a larger number of structurally dissimilar pairs than geometry-based structural alignments. When two sequences can be aligned in a statistically meaningful way, sequence-based structural superpositioning provides a meaningful measure of structural differences. This approach and geometry-based structure alignments reveal somewhat different information and one or the other might be preferable in a given application. Our results suggest that in some cases, notably homology modeling, the common use of nonredundant datasets, culled from the PDB based on sequence, may mask important structural and functional information. We have established a data base of sequence-similar, structurally dissimilar protein pairs that will help address this problem (http://luna.bioc.columbia.edu/rachel/seqsimstrdiff.htm).

NMR relaxation studies on the hydrate layer of intrinsically unstructured proteins.

PubMed

Bokor, Mónika; Csizmók, Veronika; Kovács, Dénes; Bánki, Péter; Friedrich, Peter; Tompa, Peter; Tompa, Kálmán

2005-03-01

Intrinsically unstructured/disordered proteins (IUPs) exist in a disordered and largely solvent-exposed, still functional, structural state under physiological conditions. As their function is often directly linked with structural disorder, understanding their structure-function relationship in detail is a great challenge to structural biology. In particular, their hydration and residual structure, both closely linked with their mechanism of action, require close attention. Here we demonstrate that the hydration of IUPs can be adequately approached by a technique so far unexplored with respect to IUPs, solid-state NMR relaxation measurements. This technique provides quantitative information on various features of hydrate water bound to these proteins. By freezing nonhydrate (bulk) water out, we have been able to measure free induction decays pertaining to protons of bound water from which the amount of hydrate water, its activation energy, and correlation times could be calculated. Thus, for three IUPs, the first inhibitory domain of calpastatin, microtubule-associated protein 2c, and plant dehydrin early responsive to dehydration 10, we demonstrate that they bind a significantly larger amount of water than globular proteins, whereas their suboptimal hydration and relaxation parameters are correlated with their differing modes of function. The theoretical treatment and experimental approach presented in this article may have general utility in characterizing proteins that belong to this novel structural class.

The Functional Breakdown Structure (FBS) and Its Relationship to Life Cycle Cost

NASA Technical Reports Server (NTRS)

DeHoff, Bryan; Levack, Danie J. H.; Rhodes, Russell E.

2009-01-01

The Functional Breakdown Structure (FBS) is a structured, modular breakdown of every function that must be addressed to perform a generic mission. It is also usable for any subset of the mission. Unlike a Work Breakdown Structure (WBS), the FBS is a function-oriented tree, not a product-oriented tree. The FBS details not products, but operations or activities that should be performed. The FBS is not tied to any particular architectural implementation because it is a listing of the needed functions, not the elements, of the architecture. The FBS for Space Transportation Systems provides a universal hierarchy of required functions, which include ground and space operations as well as infrastructure - it provides total visibility of the entire mission. By approaching the systems engineering problem from the functional view, instead of the element or hardware view, the SPST has created an exhaustive list of potential requirements which the architecture designers can use to evaluate the completeness of their designs. This is a new approach that will provide full accountability of all functions required to perform the planned mission. It serves as a giant check list to be sure that no functions are omitted, especially in the early architectural design phase. A significant characteristic of a FBS is that if architecture options are compared using this approach, then any missing or redundant elements of each option will be ' identified. Consequently, valid Life Cycle Costs (LCC) comparisons can be made. For example, one architecture option might not need a particular function while another option does. One option may have individual elements to perform each of three functions while another option needs only one element to perform the three functions. Once an architecture has been selected, the FBS will serve as a guide in development of the work breakdown structure, provide visibility of those technologies that need to be further developed to perform required functions, and help identify the personnel skills required to develop and operate the architecture. It also wifi allow the systems engineering activities to totally integrate each discipline to the maximum extent possible and optimize at the total system level, thus avoiding optimizing at the element level (stove-piping). In addition, it furnishes a framework that wifi help prevent over or under specifying requirements because all functions are identified and all elements are aligned to functions.

Orbital operations study. Volume 2: Interfacing activities analysis. Part 2: Structural and mechanical group

NASA Technical Reports Server (NTRS)

Mattson, H. L.; Gianformaggio, A.; Anderson, N. R.

1972-01-01

The activities of the structural and mechanical activity group of the orbital operations study project are discussed. Element interfaces, alternate approaches, design concepts, operational procedures, functional requirements, design influences, and approach selection are presented. The following areas are considered: (1) mating, (2) orbital assembly, (3) separation, EOS payload deployment, and EOS payload retraction.

Structural and functional engineering of one-dimensional nanostructures for device applications

NASA Astrophysics Data System (ADS)

Singh, Krishna Veer

Fabrication of 1-D nanostructures has been an area of keen interest due to their application in nanodevices. Carbon nanotubes (CNTs) and semiconducting nanorods are 1-D nanostructures of great importance. There are various challenges related to structural and functional aspects of these materials, which need to be addressed for their adaptation in devices. To this end, two approaches have been developed: (1) structural engineering of the nanorods and (2) functionalization of CNTs for device applications. In first approach, a new technique to produce single crystal semiconducting nanorods was developed. Single crystalline structure of nanorods is essential to obtain reproducible performance. The novel synthesis technique 'template assisted sonoelectrochemical deposition' was utilized to develop 'copper sulfide' and 'copper indium sulfide' nanorods. The use of sonoelectrochemical method resulted in the best deposition rate as compared to stirring-assisted and regular electrochemical deposition, respectively. Observed increase in the bulk electrolyte temperature, high acoustic pressure and shock waves generated from the collapse of bubbles could explain improved mass transport and reaction rate, which results in the formation of single crystal nanorods. Nanorods in the range of 50-200nm in diameter were synthesized and electrically characterized as p-type semiconductors. Excellent structural and repeatable electrical properties of the various nanorods developed by this technique make it suitable for developing nanorods for device applications. In addition, detailed statistical analysis of the polycarbonate templates (50-200 nm nominal pore size) used in electrodeposition provided a better understanding of template's as well as nanorods' structure. In the second approach, we functionally engineered single walled carbon nanotubes (SWNTs) with peptide nucleic acid (PNA) to form functional conjugates for molecular electronics. SWNT-PNA-SWNT conjugates were synthesized using carbodiimide chemistry. Also in this work, the electric transport measurements of SWNT-PNA conjugates are reported for the first time. Corresponding analysis reveals that these conjugates exhibit diodic behaviour and in some devices negative differential resistance (NDR) was also observed. The unique electrical and structural properties of these conjugates make them a potential candidate for application in CNT based nanodevices. Hence, this work demonstrates novel techniques to functionally and structurally engineer 1-D nanomaterials for device applications.

Functional evolution and structural conservation in chimeric cytochromes p450: calibrating a structure-guided approach.

PubMed

Otey, Christopher R; Silberg, Jonathan J; Voigt, Christopher A; Endelman, Jeffrey B; Bandara, Geethani; Arnold, Frances H

2004-03-01

Recombination generates chimeric proteins whose ability to fold depends on minimizing structural perturbations that result when portions of the sequence are inherited from different parents. These chimeric sequences can display functional properties characteristic of the parents or acquire entirely new functions. Seventeen chimeras were generated from two CYP102 members of the functionally diverse cytochrome p450 family. Chimeras predicted to have limited structural disruption, as defined by the SCHEMA algorithm, displayed CO binding spectra characteristic of folded p450s. Even this small population exhibited significant functional diversity: chimeras displayed altered substrate specificities, a wide range in thermostabilities, up to a 40-fold increase in peroxidase activity, and ability to hydroxylate a substrate toward which neither parent heme domain shows detectable activity. These results suggest that SCHEMA-guided recombination can be used to generate diverse p450s for exploring function evolution within the p450 structural framework.

New approaches in renal microscopy: volumetric imaging and superresolution microscopy.

PubMed

Kim, Alfred H J; Suleiman, Hani; Shaw, Andrey S

2016-05-01

Histologic and electron microscopic analysis of the kidney has provided tremendous insight into structures such as the glomerulus and nephron. Recent advances in imaging, such as deep volumetric approaches and superresolution microscopy, have the capacity to dramatically enhance our current understanding of the structure and function of the kidney. Volumetric imaging can generate images millimeters below the surface of the intact kidney. Superresolution microscopy breaks the diffraction barrier inherent in traditional light microscopy, enabling the visualization of fine structures. Here, we describe new approaches to deep volumetric and superresolution microscopy of the kidney. Rapid advances in lasers, microscopic objectives, and tissue preparation have transformed our ability to deep volumetric image the kidney. Innovations in sample preparation have allowed for superresolution imaging with electron microscopy correlation, providing unprecedented insight into the structures within the glomerulus. Technological advances in imaging have revolutionized our capacity to image both large volumes of tissue and the finest structural details of a cell. These new advances have the potential to provide additional profound observations into the normal and pathologic functions of the kidney.

Defense Reform: Supporting the Whole-of-Government Approach in Tomorrow’s Crisis

DTIC Science & Technology

2017-03-29

government approach to trans-regional, multi-domain, and multi-functional threats. In addition to keeping military and political focus on broader...structure with more subordinate commands and less multi-domain and multi-functional integration, or in this case , vertical integration. Relying on ... APPROACH IN TOMORROW’S CRISIS 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Lt Col John B

Understanding the General Packing Rearrangements Required for Successful Template Based Modeling of Protein Structure from a CASP Experiment

PubMed Central

Day, Ryan; Joo, Hyun; Chavan, Archana; Lennox, Kristin P.; Chen, Ann; Dahl, David B.; Vannucci, Marina; Tsai, Jerry W.

2012-01-01

As an alternative to the common template based protein structure prediction methods based on main-chain position, a novel side-chain centric approach has been developed. Together with a Bayesian loop modeling procedure and a combination scoring function, the Stone Soup algorithm was applied to the CASP9 set of template based modeling targets. Although the method did not generate as large of perturbations to the template structures as necessary, the analysis of the results gives unique insights into the differences in packing between the target structures and their templates. Considerable variation in packing is found between target and template structures even when the structures are close, and this variation is found due to 2 and 3 body packing interactions. Outside the inherent restrictions in packing representation of the PDB, the first steps in correctly defining those regions of variable packing have been mapped primarily to local interactions, as the packing at the secondary and tertiary structure are largely conserved. Of the scoring functions used, a loop scoring function based on water structure exhibited some promise for discrimination. These results present a clear structural path for further development of a side-chain centered approach to template based modeling. PMID:23266765

Understanding the general packing rearrangements required for successful template based modeling of protein structure from a CASP experiment.

PubMed

Day, Ryan; Joo, Hyun; Chavan, Archana C; Lennox, Kristin P; Chen, Y Ann; Dahl, David B; Vannucci, Marina; Tsai, Jerry W

2013-02-01

As an alternative to the common template based protein structure prediction methods based on main-chain position, a novel side-chain centric approach has been developed. Together with a Bayesian loop modeling procedure and a combination scoring function, the Stone Soup algorithm was applied to the CASP9 set of template based modeling targets. Although the method did not generate as large of perturbations to the template structures as necessary, the analysis of the results gives unique insights into the differences in packing between the target structures and their templates. Considerable variation in packing is found between target and template structures even when the structures are close, and this variation is found due to 2 and 3 body packing interactions. Outside the inherent restrictions in packing representation of the PDB, the first steps in correctly defining those regions of variable packing have been mapped primarily to local interactions, as the packing at the secondary and tertiary structure are largely conserved. Of the scoring functions used, a loop scoring function based on water structure exhibited some promise for discrimination. These results present a clear structural path for further development of a side-chain centered approach to template based modeling. Copyright © 2012 Elsevier Ltd. All rights reserved.

Understanding and planning ecological restoration of plant-pollinator networks.

PubMed

Devoto, Mariano; Bailey, Sallie; Craze, Paul; Memmott, Jane

2012-04-01

Theory developed from studying changes in the structure and function of communities during natural or managed succession can guide the restoration of particular communities. We constructed 30 quantitative plant-flower visitor networks along a managed successional gradient to identify the main drivers of change in network structure. We then applied two alternative restoration strategies in silico (restoring for functional complementarity or redundancy) to data from our early successional plots to examine whether different strategies affected the restoration trajectories. Changes in network structure were explained by a combination of age, tree density and variation in tree diameter, even when variance explained by undergrowth structure was accounted for first. A combination of field data, a network approach and numerical simulations helped to identify which species should be given restoration priority in the context of different restoration targets. This combined approach provides a powerful tool for directing management decisions, particularly when management seeks to restore or conserve ecosystem function. © 2012 Blackwell Publishing Ltd/CNRS.

Self-consistent Green's function embedding for advanced electronic structure methods based on a dynamical mean-field concept

NASA Astrophysics Data System (ADS)

Chibani, Wael; Ren, Xinguo; Scheffler, Matthias; Rinke, Patrick

2016-04-01

We present an embedding scheme for periodic systems that facilitates the treatment of the physically important part (here a unit cell or a supercell) with advanced electronic structure methods, that are computationally too expensive for periodic systems. The rest of the periodic system is treated with computationally less demanding approaches, e.g., Kohn-Sham density-functional theory, in a self-consistent manner. Our scheme is based on the concept of dynamical mean-field theory formulated in terms of Green's functions. Our real-space dynamical mean-field embedding scheme features two nested Dyson equations, one for the embedded cluster and another for the periodic surrounding. The total energy is computed from the resulting Green's functions. The performance of our scheme is demonstrated by treating the embedded region with hybrid functionals and many-body perturbation theory in the GW approach for simple bulk systems. The total energy and the density of states converge rapidly with respect to the computational parameters and approach their bulk limit with increasing cluster (i.e., computational supercell) size.

Residues with similar hexagon neighborhoods share similar side-chain conformations.

PubMed

Li, Shuai Cheng; Bu, Dongbo; Li, Ming

2012-01-01

We present in this study a new approach to code protein side-chain conformations into hexagon substructures. Classical side-chain packing methods consist of two steps: first, side-chain conformations, known as rotamers, are extracted from known protein structures as candidates for each residue; second, a searching method along with an energy function is used to resolve conflicts among residues and to optimize the combinations of side chain conformations for all residues. These methods benefit from the fact that the number of possible side-chain conformations is limited, and the rotamer candidates are readily extracted; however, these methods also suffer from the inaccuracy of energy functions. Inspired by threading and Ab Initio approaches to protein structure prediction, we propose to use hexagon substructures to implicitly capture subtle issues of energy functions. Our initial results indicate that even without guidance from an energy function, hexagon structures alone can capture side-chain conformations at an accuracy of 83.8 percent, higher than 82.6 percent by the state-of-art side-chain packing methods.

Chip level modeling of LSI devices

NASA Technical Reports Server (NTRS)

Armstrong, J. R.

1984-01-01

The advent of Very Large Scale Integration (VLSI) technology has rendered the gate level model impractical for many simulation activities critical to the design automation process. As an alternative, an approach to the modeling of VLSI devices at the chip level is described, including the specification of modeling language constructs important to the modeling process. A model structure is presented in which models of the LSI devices are constructed as single entities. The modeling structure is two layered. The functional layer in this structure is used to model the input/output response of the LSI chip. A second layer, the fault mapping layer, is added, if fault simulations are required, in order to map the effects of hardware faults onto the functional layer. Modeling examples for each layer are presented. Fault modeling at the chip level is described. Approaches to realistic functional fault selection and defining fault coverage for functional faults are given. Application of the modeling techniques to single chip and bit slice microprocessors is discussed.

Nonlocal response with local optics

NASA Astrophysics Data System (ADS)

Kong, Jiantao; Shvonski, Alexander J.; Kempa, Krzysztof

2018-04-01

For plasmonic systems too small for classical, local simulations to be valid, but too large for ab initio calculations to be computationally feasible, we developed a practical approach—a nonlocal-to-local mapping that enables the use of a modified local system to obtain the response due to nonlocal effects to lowest order, at the cost of higher structural complexity. In this approach, the nonlocal surface region of a metallic structure is mapped onto a local dielectric film, mathematically preserving the nonlocality of the entire system. The most significant feature of this approach is its full compatibility with conventional, highly efficient finite difference time domain (FDTD) simulation codes. Our optimized choice of mapping is based on the Feibelman's d -function formalism, and it produces an effective dielectric function of the local film that obeys all required sum rules, as well as the Kramers-Kronig causality relations. We demonstrate the power of our approach combined with an FDTD scheme, in a series of comparisons with experiments and ab initio density functional theory calculations from the literature, for structures with dimensions from the subnanoscopic to microscopic range.

Design and Integration for High Performance Robotic Systems Based on Decomposition and Hybridization Approaches

PubMed Central

Zhang, Dan; Wei, Bin

2017-01-01

Currently, the uses of robotics are limited with respect to performance capabilities. Improving the performance of robotic mechanisms is and still will be the main research topic in the next decade. In this paper, design and integration for improving performance of robotic systems are achieved through three different approaches, i.e., structure synthesis design approach, dynamic balancing approach, and adaptive control approach. The purpose of robotic mechanism structure synthesis design is to propose certain mechanism that has better kinematic and dynamic performance as compared to the old ones. For the dynamic balancing design approach, it is normally accomplished based on employing counterweights or counter-rotations. The potential issue is that more weight and inertia will be included in the system. Here, reactionless based on the reconfiguration concept is put forward, which can address the mentioned problem. With the mechanism reconfiguration, the control system needs to be adapted thereafter. One way to address control system adaptation is by applying the “divide and conquer” methodology. It entails modularizing the functionalities: breaking up the control functions into small functional modules, and from those modules assembling the control system according to the changing needs of the mechanism. PMID:28075360

Novel trends in pair distribution function approaches on bulk systems with nanoscale heterogeneities

DOE PAGES

Emil S. Bozin; Billinge, Simon J. L.

2016-07-29

Novel materials for high performance applications increasingly exhibit structural order on the nanometer length scale; a domain where crystallography, the basis of Rietveld refinement, fails [1]. In such instances the total scattering approach, which treats Bragg and diffuse scattering on an equal basis, is a powerful approach. In recent years, the analysis of the total scattering data became an invaluable tool and the gold standard for studying nanocrystalline, nanoporous, and disordered crystalline materials. The data may be analyzed in reciprocal space directly, or Fourier transformed to the real-space atomic pair distribution function (PDF) and this intuitive function examined for localmore » structural information. Here we give a number of illustrative examples, for convenience picked from our own work, of recent developments and applications of total scattering and PDF analysis to novel complex materials. There are many other wonderful examples from the work of others.« less

Tracking the Reorganization of Module Structure in Time-Varying Weighted Brain Functional Connectivity Networks.

PubMed

Schmidt, Christoph; Piper, Diana; Pester, Britta; Mierau, Andreas; Witte, Herbert

2018-05-01

Identification of module structure in brain functional networks is a promising way to obtain novel insights into neural information processing, as modules correspond to delineated brain regions in which interactions are strongly increased. Tracking of network modules in time-varying brain functional networks is not yet commonly considered in neuroscience despite its potential for gaining an understanding of the time evolution of functional interaction patterns and associated changing degrees of functional segregation and integration. We introduce a general computational framework for extracting consensus partitions from defined time windows in sequences of weighted directed edge-complete networks and show how the temporal reorganization of the module structure can be tracked and visualized. Part of the framework is a new approach for computing edge weight thresholds for individual networks based on multiobjective optimization of module structure quality criteria as well as an approach for matching modules across time steps. By testing our framework using synthetic network sequences and applying it to brain functional networks computed from electroencephalographic recordings of healthy subjects that were exposed to a major balance perturbation, we demonstrate the framework's potential for gaining meaningful insights into dynamic brain function in the form of evolving network modules. The precise chronology of the neural processing inferred with our framework and its interpretation helps to improve the currently incomplete understanding of the cortical contribution for the compensation of such balance perturbations.

Measurements of the separated longitudinal structure function FL from hydrogen and deuterium targets at low Q2

NASA Astrophysics Data System (ADS)

Tvaskis, V.; Tvaskis, A.; Niculescu, I.; Abbott, D.; Adams, G. S.; Afanasev, A.; Ahmidouch, A.; Angelescu, T.; Arrington, J.; Asaturyan, R.; Avery, S.; Baker, O. K.; Benmouna, N.; Berman, B. L.; Biselli, A.; Blok, H. P.; Boeglin, W. U.; Bosted, P. E.; Brash, E.; Breuer, H.; Chang, G.; Chant, N.; Christy, M. E.; Connell, S. H.; Dalton, M. M.; Danagoulian, S.; Day, D.; Dodario, T.; Dunne, J. A.; Dutta, D.; El Khayari, N.; Ent, R.; Fenker, H. C.; Frolov, V. V.; Gaskell, D.; Garrow, K.; Gilman, R.; Gueye, P.; Hafidi, K.; Hinton, W.; Holt, R. J.; Horn, T.; Huber, G. M.; Jackson, H.; Jiang, X.; Jones, M. K.; Joo, K.; Kelly, J. J.; Keppel, C. E.; Kuhn, J.; Kinney, E.; Klein, A.; Kubarovsky, V.; Liang, Y.; Lolos, G.; Lung, A.; Mack, D.; Malace, S.; Markowitz, P.; Mbianda, G.; McGrath, E.; Mckee, D.; Meekins, D. G.; Mkrtchyan, H.; Napolitano, J.; Navasardyan, T.; Niculescu, G.; Nozar, M.; Ostapenko, T.; Papandreou, Z.; Potterveld, D.; Reimer, P. E.; Reinhold, J.; Roche, J.; Rock, S. E.; Schulte, E.; Segbefia, E.; Smith, C.; Smith, G. R.; Stoler, P.; Tadevosyan, V.; Tang, L.; Telfeyan, J.; Todor, L.; Ungaro, M.; Uzzle, A.; Vidakovic, S.; Villano, A.; Vulcan, W. F.; Warren, G.; Wesselmann, F.; Wojtsekhowski, B.; Wood, S. A.; Yan, C.; Zihlmann, B.

2018-04-01

Structure functions, as measured in lepton-nucleon scattering, have proven to be very useful in studying the partonic dynamics within the nucleon. However, it is experimentally difficult to separately determine the longitudinal and transverse structure functions, and consequently there are substantially less data available in particular for the longitudinal structure function. Here, we present separated structure functions for hydrogen and deuterium at low four-momentum transfer squared, Q2<1 GeV2 , and compare them with parton distribution parametrization and kT factorization approaches. While differences are found, the parametrizations generally agree with the data, even at the very low-Q2 scale of the data. The deuterium data show a smaller longitudinal structure function and a smaller ratio of longitudinal to transverse cross section, R , than the proton. This suggests either an unexpected difference in R for the proton and the neutron or a suppression of the gluonic distribution in nuclei.

Measurements of the separated longitudinal structure function F L from hydrogen and deuterium targets at low Q 2

DOE PAGES

Tvaskis, V.; Tvaskis, A.; Niculescu, I.; ...

2018-04-26

Structure functions, as measured in lepton-nucleon scattering, have proven to be very useful in studying the partonic dynamics within the nucleon. Furthermore, it is experimentally difficult to separately determine the longitudinal and transverse structure functions, and consequently there are substantially less data available in particular for the longitudinal structure function. Here, we present separated structure functions for hydrogen and deuterium at low four-momentum transfer squared, Q 2 < 1 GeV 2, and compare them with parton distribution parametrization and k T factorization approaches. While differences are found, the parametrizations generally agree with the data, even at the very low-Q 2more » scale of the data. The deuterium data show a smaller longitudinal structure function and a smaller ratio of longitudinal to transverse cross section, R, than the proton. This suggests either an unexpected difference in R for the proton and the neutron or a suppression of the gluonic distribution in nuclei.« less

Measurements of the separated longitudinal structure function F L from hydrogen and deuterium targets at low Q 2

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

Tvaskis, V.; Tvaskis, A.; Niculescu, I.

Structure functions, as measured in lepton-nucleon scattering, have proven to be very useful in studying the partonic dynamics within the nucleon. Furthermore, it is experimentally difficult to separately determine the longitudinal and transverse structure functions, and consequently there are substantially less data available in particular for the longitudinal structure function. Here, we present separated structure functions for hydrogen and deuterium at low four-momentum transfer squared, Q 2 < 1 GeV 2, and compare them with parton distribution parametrization and k T factorization approaches. While differences are found, the parametrizations generally agree with the data, even at the very low-Q 2more » scale of the data. The deuterium data show a smaller longitudinal structure function and a smaller ratio of longitudinal to transverse cross section, R, than the proton. This suggests either an unexpected difference in R for the proton and the neutron or a suppression of the gluonic distribution in nuclei.« less

Functional Classification of Immune Regulatory Proteins

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

Rubinstein, Rotem; Ramagopal, Udupi A.; Nathenson, Stanley G.

2013-05-01

Members of the immunoglobulin superfamily (IgSF) control innate and adaptive immunity and are prime targets for the treatment of autoimmune diseases, infectious diseases, and malignancies. We describe a computational method, termed the Brotherhood algorithm, which utilizes intermediate sequence information to classify proteins into functionally related families. This approach identifies functional relationships within the IgSF and predicts additional receptor-ligand interactions. As a specific example, we examine the nectin/nectin-like family of cell adhesion and signaling proteins and propose receptor-ligand interactions within this family. We were guided by the Brotherhood approach and present the high-resolution structural characterization of a homophilic interaction involving themore » class-I MHC-restricted T-cell-associated molecule, which we now classify as a nectin-like family member. The Brotherhood algorithm is likely to have a significant impact on structural immunology by identifying those proteins and complexes for which structural characterization will be particularly informative.« less

Functional enzyme-based modeling approach for dynamic simulation of denitrification process in hyporheic zone sediments: Genetically structured microbial community model

NASA Astrophysics Data System (ADS)

Song, H. S.; Li, M.; Qian, W.; Song, X.; Chen, X.; Scheibe, T. D.; Fredrickson, J.; Zachara, J. M.; Liu, C.

2016-12-01

Modeling environmental microbial communities at individual organism level is currently intractable due to overwhelming structural complexity. Functional guild-based approaches alleviate this problem by lumping microorganisms into fewer groups based on their functional similarities. This reduction may become ineffective, however, when individual species perform multiple functions as environmental conditions vary. In contrast, the functional enzyme-based modeling approach we present here describes microbial community dynamics based on identified functional enzymes (rather than individual species or their groups). Previous studies in the literature along this line used biomass or functional genes as surrogate measures of enzymes due to the lack of analytical methods for quantifying enzymes in environmental samples. Leveraging our recent development of a signature peptide-based technique enabling sensitive quantification of functional enzymes in environmental samples, we developed a genetically structured microbial community model (GSMCM) to incorporate enzyme concentrations and various other omics measurements (if available) as key modeling input. We formulated the GSMCM based on the cybernetic metabolic modeling framework to rationally account for cellular regulation without relying on empirical inhibition kinetics. In the case study of modeling denitrification process in Columbia River hyporheic zone sediments collected from the Hanford Reach, our GSMCM provided a quantitative fit to complex experimental data in denitrification, including the delayed response of enzyme activation to the change in substrate concentration. Our future goal is to extend the modeling scope to the prediction of carbon and nitrogen cycles and contaminant fate. Integration of a simpler version of the GSMCM with PFLOTRAN for multi-scale field simulations is in progress.

Structured functional additive regression in reproducing kernel Hilbert spaces.

PubMed

Zhu, Hongxiao; Yao, Fang; Zhang, Hao Helen

2014-06-01

Functional additive models (FAMs) provide a flexible yet simple framework for regressions involving functional predictors. The utilization of data-driven basis in an additive rather than linear structure naturally extends the classical functional linear model. However, the critical issue of selecting nonlinear additive components has been less studied. In this work, we propose a new regularization framework for the structure estimation in the context of Reproducing Kernel Hilbert Spaces. The proposed approach takes advantage of the functional principal components which greatly facilitates the implementation and the theoretical analysis. The selection and estimation are achieved by penalized least squares using a penalty which encourages the sparse structure of the additive components. Theoretical properties such as the rate of convergence are investigated. The empirical performance is demonstrated through simulation studies and a real data application.

Design of a structural and functional hierarchy for planning and control of telerobotic systems

NASA Technical Reports Server (NTRS)

Acar, Levent; Ozguner, Umit

1989-01-01

Hierarchical structures offer numerous advantages over conventional structures for the control of telerobotic systems. A hierarchically organized system can be controlled via undetailed task assignments and can easily adapt to changing circumstances. The distributed and modular structure of these systems also enables fast response needed in most telerobotic applications. On the other hand, most of the hierarchical structures proposed in the literature are based on functional properties of a system. These structures work best for a few given functions of a large class of systems. In telerobotic applications, all functions of a single system needed to be explored. This approach requires a hierarchical organization based on physical properties of a system and such a hierarchical organization is introduced. The decomposition, organization, and control of the hierarchical structure are considered, and a system with two robot arms and a camera is presented.

Computational approaches for rational design of proteins with novel functionalities

PubMed Central

Tiwari, Manish Kumar; Singh, Ranjitha; Singh, Raushan Kumar; Kim, In-Won; Lee, Jung-Kul

2012-01-01

Proteins are the most multifaceted macromolecules in living systems and have various important functions, including structural, catalytic, sensory, and regulatory functions. Rational design of enzymes is a great challenge to our understanding of protein structure and physical chemistry and has numerous potential applications. Protein design algorithms have been applied to design or engineer proteins that fold, fold faster, catalyze, catalyze faster, signal, and adopt preferred conformational states. The field of de novo protein design, although only a few decades old, is beginning to produce exciting results. Developments in this field are already having a significant impact on biotechnology and chemical biology. The application of powerful computational methods for functional protein designing has recently succeeded at engineering target activities. Here, we review recently reported de novo functional proteins that were developed using various protein design approaches, including rational design, computational optimization, and selection from combinatorial libraries, highlighting recent advances and successes. PMID:24688643

Synthesizing information-update functions using off-line symbolic processing

NASA Technical Reports Server (NTRS)

Rosenschein, Stanley J.

1990-01-01

This paper explores the synthesis of programs that track dynamic conditions in their environment. An approach is proposed in which the designer specifies, in a declarative language, aspects of the environment in which the program will be embedded. This specification is then automatically compiled into a program that, when executed, updates internal data structures so as to maintain as an invariant a desired correspondence between internal data structures and states of the external environment. This approach retains much of the flexibility of declarative programming while guaranteeing a hard bound on the execution time of information-update functions.

A novel approach for introducing cloud spatial structure into cloud radiative transfer parameterizations

NASA Astrophysics Data System (ADS)

Huang, Dong; Liu, Yangang

2014-12-01

Subgrid-scale variability is one of the main reasons why parameterizations are needed in large-scale models. Although some parameterizations started to address the issue of subgrid variability by introducing a subgrid probability distribution function for relevant quantities, the spatial structure has been typically ignored and thus the subgrid-scale interactions cannot be accounted for physically. Here we present a new statistical-physics-like approach whereby the spatial autocorrelation function can be used to physically capture the net effects of subgrid cloud interaction with radiation. The new approach is able to faithfully reproduce the Monte Carlo 3D simulation results with several orders less computational cost, allowing for more realistic representation of cloud radiation interactions in large-scale models.

Polarized targets in high energy physics

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

Cates, G.D. Jr.

1994-12-01

Various approaches are discussed for producing polarized nuclear targets for high energy physics experiments. As a unifying theme, examples are drawn from experiments to measure spin dependent structure functions of nucleons in deep inelastic scattering. This single physics goal has, over roughly two decades, been a driving force in advances in target technology. Actual or planned approaches have included solid targets polarized by dynamic nuclear polarization (DNP), several types of internal targets for use in storage rings, and gaseous {sup 3}He targets polarized by spin-exchange optical pumping. This last approach is the type of target adopted for SLAC E-142, anmore » experiment to measure the spin structure function of the neutron, and is described in detail.« less

A Multivariate Granger Causality Concept towards Full Brain Functional Connectivity.

PubMed

Schmidt, Christoph; Pester, Britta; Schmid-Hertel, Nicole; Witte, Herbert; Wismüller, Axel; Leistritz, Lutz

2016-01-01

Detecting changes of spatially high-resolution functional connectivity patterns in the brain is crucial for improving the fundamental understanding of brain function in both health and disease, yet still poses one of the biggest challenges in computational neuroscience. Currently, classical multivariate Granger Causality analyses of directed interactions between single process components in coupled systems are commonly restricted to spatially low- dimensional data, which requires a pre-selection or aggregation of time series as a preprocessing step. In this paper we propose a new fully multivariate Granger Causality approach with embedded dimension reduction that makes it possible to obtain a representation of functional connectivity for spatially high-dimensional data. The resulting functional connectivity networks may consist of several thousand vertices and thus contain more detailed information compared to connectivity networks obtained from approaches based on particular regions of interest. Our large scale Granger Causality approach is applied to synthetic and resting state fMRI data with a focus on how well network community structure, which represents a functional segmentation of the network, is preserved. It is demonstrated that a number of different community detection algorithms, which utilize a variety of algorithmic strategies and exploit topological features differently, reveal meaningful information on the underlying network module structure.

The application of 3D Zernike moments for the description of "model-free" molecular structure, functional motion, and structural reliability.

PubMed

Grandison, Scott; Roberts, Carl; Morris, Richard J

2009-03-01

Protein structures are not static entities consisting of equally well-determined atomic coordinates. Proteins undergo continuous motion, and as catalytic machines, these movements can be of high relevance for understanding function. In addition to this strong biological motivation for considering shape changes is the necessity to correctly capture different levels of detail and error in protein structures. Some parts of a structural model are often poorly defined, and the atomic displacement parameters provide an excellent means to characterize the confidence in an atom's spatial coordinates. A mathematical framework for studying these shape changes, and handling positional variance is therefore of high importance. We present an approach for capturing various protein structure properties in a concise mathematical framework that allows us to compare features in a highly efficient manner. We demonstrate how three-dimensional Zernike moments can be employed to describe functions, not only on the surface of a protein but throughout the entire molecule. A number of proof-of-principle examples are given which demonstrate how this approach may be used in practice for the representation of movement and uncertainty.

Analysis of the proton longitudinal structure function from the gluon distribution function

NASA Astrophysics Data System (ADS)

Boroun, G. R.; Rezaei, B.

2012-11-01

We make a critical, next-to-leading order, study of the relationship between the longitudinal structure function F L and the gluon distribution proposed in Cooper-Sarkar et al. (Z. Phys. C 39:281, 1988; Acta Phys. Pol. B 34:2911 2003), which is frequently used to extract the gluon distribution from the proton longitudinal structure function at small x. The gluon density is obtained by expanding at particular choices of the point of expansion and compared with the hard Pomeron behavior for the gluon density. Comparisons with H1 data are made and predictions for the proposed best approach are also provided.

Ab initio RNA folding by discrete molecular dynamics: From structure prediction to folding mechanisms

PubMed Central

Ding, Feng; Sharma, Shantanu; Chalasani, Poornima; Demidov, Vadim V.; Broude, Natalia E.; Dokholyan, Nikolay V.

2008-01-01

RNA molecules with novel functions have revived interest in the accurate prediction of RNA three-dimensional (3D) structure and folding dynamics. However, existing methods are inefficient in automated 3D structure prediction. Here, we report a robust computational approach for rapid folding of RNA molecules. We develop a simplified RNA model for discrete molecular dynamics (DMD) simulations, incorporating base-pairing and base-stacking interactions. We demonstrate correct folding of 150 structurally diverse RNA sequences. The majority of DMD-predicted 3D structures have <4 Å deviations from experimental structures. The secondary structures corresponding to the predicted 3D structures consist of 94% native base-pair interactions. Folding thermodynamics and kinetics of tRNAPhe, pseudoknots, and mRNA fragments in DMD simulations are in agreement with previous experimental findings. Folding of RNA molecules features transient, non-native conformations, suggesting non-hierarchical RNA folding. Our method allows rapid conformational sampling of RNA folding, with computational time increasing linearly with RNA length. We envision this approach as a promising tool for RNA structural and functional analyses. PMID:18456842

Rough-pipe flows and the existence of fully developed turbulence

NASA Astrophysics Data System (ADS)

Gioia, G.; Chakraborty, Pinaki; Bombardelli, Fabián A.

2006-03-01

It is widely believed that at high Reynolds number (Re) all turbulent flows approach a limiting state of "fully developed turbulence" in which the statistics of the velocity fluctuations are independent of Re. Nevertheless, direct measurements of the velocity fluctuations have failed to yield firm empirical evidence that even the second-order structure function becomes independent of Re at high Re, let alone structure functions of higher order. Here we relate the friction coefficient (f) of rough-pipe flows to the second-order structure function. Then we show that in light of experimental measurements of f our results yield unequivocal evidence that the second-order structure function becomes independent of Re at high Re, compatible with the existence of fully developed turbulence.

Abnormal functional connectivity during visuospatial processing is associated with disrupted organisation of white matter in autism

PubMed Central

McGrath, Jane; Johnson, Katherine; O'Hanlon, Erik; Garavan, Hugh; Leemans, Alexander; Gallagher, Louise

2013-01-01

Disruption of structural and functional neural connectivity has been widely reported in Autism Spectrum Disorder (ASD) but there is a striking lack of research attempting to integrate analysis of functional and structural connectivity in the same study population, an approach that may provide key insights into the specific neurobiological underpinnings of altered functional connectivity in autism. The aims of this study were (1) to determine whether functional connectivity abnormalities were associated with structural abnormalities of white matter (WM) in ASD and (2) to examine the relationships between aberrant neural connectivity and behavior in ASD. Twenty-two individuals with ASD and 22 age, IQ-matched controls completed a high-angular-resolution diffusion MRI scan. Structural connectivity was analysed using constrained spherical deconvolution (CSD) based tractography. Regions for tractography were generated from the results of a previous study, in which 10 pairs of brain regions showed abnormal functional connectivity during visuospatial processing in ASD. WM tracts directly connected 5 of the 10 region pairs that showed abnormal functional connectivity; linking a region in the left occipital lobe (left BA19) and five paired regions: left caudate head, left caudate body, left uncus, left thalamus, and left cuneus. Measures of WM microstructural organization were extracted from these tracts. Fractional anisotropy (FA) reductions in the ASD group relative to controls were significant for WM connecting left BA19 to left caudate head and left BA19 to left thalamus. Using a multimodal imaging approach, this study has revealed aberrant WM microstructure in tracts that directly connect brain regions that are abnormally functionally connected in ASD. These results provide novel evidence to suggest that structural brain pathology may contribute (1) to abnormal functional connectivity and (2) to atypical visuospatial processing in ASD. PMID:24133425

The neural correlates of obsessive-compulsive disorder: a multimodal perspective.

PubMed

Moreira, P S; Marques, P; Soriano-Mas, C; Magalhães, R; Sousa, N; Soares, J M; Morgado, P

2017-08-29

Obsessive-compulsive disorder (OCD) is one of the most debilitating psychiatric conditions. An extensive body of the literature has described some of the neurobiological mechanisms underlying the core manifestations of the disorder. Nevertheless, most reports have focused on individual modalities of structural/functional brain alterations, mainly through targeted approaches, thus possibly precluding the power of unbiased exploratory approaches. Eighty subjects (40 OCD and 40 healthy controls) participated in a multimodal magnetic resonance imaging (MRI) investigation, integrating structural and functional data. Voxel-based morphometry analysis was conducted to compare between-group volumetric differences. The whole-brain functional connectome, derived from resting-state functional connectivity (FC), was analyzed with the network-based statistic methodology. Results from structural and functional analysis were integrated in mediation models. OCD patients revealed volumetric reductions in the right superior temporal sulcus. Patients had significantly decreased FC in two distinct subnetworks: the first, involving the orbitofrontal cortex, temporal poles and the subgenual anterior cingulate cortex; the second, comprising the lingual and postcentral gyri. On the opposite, a network formed by connections between thalamic and occipital regions had significantly increased FC in patients. Integrative models revealed direct and indirect associations between volumetric alterations and FC networks. This study suggests that OCD patients display alterations in brain structure and FC, involving complex networks of brain regions. Furthermore, we provided evidence for direct and indirect associations between structural and functional alterations representing complex patterns of interactions between separate brain regions, which may be of upmost relevance for explaining the pathophysiology of the disorder.

Dynamic Programming for Structured Continuous Markov Decision Problems

NASA Technical Reports Server (NTRS)

Dearden, Richard; Meuleau, Nicholas; Washington, Richard; Feng, Zhengzhu

2004-01-01

We describe an approach for exploiting structure in Markov Decision Processes with continuous state variables. At each step of the dynamic programming, the state space is dynamically partitioned into regions where the value function is the same throughout the region. We first describe the algorithm for piecewise constant representations. We then extend it to piecewise linear representations, using techniques from POMDPs to represent and reason about linear surfaces efficiently. We show that for complex, structured problems, our approach exploits the natural structure so that optimal solutions can be computed efficiently.

On the Use of 3dB Qualification Margin for Structural Parts on Expendable Launch Vehicles

NASA Technical Reports Server (NTRS)

Yunis, Isam

2007-01-01

The standard random vibration qualification test used for Expendable Launch Vehicle components is Maximum Predicted Environment (MPE) + 6dB for a duration of 4 times the service life of the part. This can be a severe qualification test for these fatigue-sensitive structures. This paper uses flight data from several launch vehicles to establish that reducing the qualification approach to MPE+3dB for the duration of the peak environment (1x life) is valid for fatigue-sensitive structural components. Items that can be classified as fatigue-sensitive are probes, ducts, tubing, bellows, hoses, and any non-functional structure. Non-functional structure may be flight critical or carry fluid, but it cannot include any moving parts or electronics. This reduced qualification approach does not include primary or secondary structure which would be exclusively designed by peak loads, either transient or quasi-static, that are so large and of so few cycles as to make fatigue a moot point.

Differentiating between bipolar and unipolar depression in functional and structural MRI studies.

PubMed

Han, Kyu-Man; De Berardis, Domenico; Fornaro, Michele; Kim, Yong-Ku

2018-03-28

Distinguishing depression in bipolar disorder (BD) from unipolar depression (UD) solely based on clinical clues is difficult, which has led to the exploration of promising neural markers in neuroimaging measures for discriminating between BD depression and UD. In this article, we review structural and functional magnetic resonance imaging (MRI) studies that directly compare UD and BD depression based on neuroimaging modalities including functional MRI studies on regional brain activation or functional connectivity, structural MRI on gray or white matter morphology, and pattern classification analyses using a machine learning approach. Numerous studies have reported distinct functional and structural alterations in emotion- or reward-processing neural circuits between BD depression and UD. Different activation patterns in neural networks including the amygdala, anterior cingulate cortex (ACC), prefrontal cortex (PFC), and striatum during emotion-, reward-, or cognition-related tasks have been reported between BD and UD. A stronger functional connectivity pattern in BD was pronounced in default mode and in frontoparietal networks and brain regions including the PFC, ACC, parietal and temporal regions, and thalamus compared to UD. Gray matter volume differences in the ACC, hippocampus, amygdala, and dorsolateral prefrontal cortex (DLPFC) have been reported between BD and UD, along with a thinner DLPFC in BD compared to UD. BD showed reduced integrity in the anterior part of the corpus callosum and posterior cingulum compared to UD. Several studies performed pattern classification analysis using structural and functional MRI data to distinguish between UD and BD depression using a supervised machine learning approach, which yielded a moderate level of accuracy in classification. Copyright © 2018 Elsevier Inc. All rights reserved.

Flooding and arsenic contamination: Influences on ecosystem structure and function in an Appalachian headwater stream

Treesearch

Noah R. Lottig; H. Maurice Valett; Madeline E. Schreiber; Jackson R. Webster

2007-01-01

We investigated the influence of flooding and chronic arsenic contamination on ecosystem structure and function in a headwater stream adjacent to an abandoned arsenic (As) mine using an upstream (reference) and downstream (mine-influenced) comparative reach approach. In this study, floods were addressed as a pulse disturbance, and the abandoned As mine was...

A Participant-Oriented, Research-Based Approach for Design of a Biochemistry Workshop for Faculty at Undergraduate Institutions

ERIC Educational Resources Information Center

Owen, Rebecca L.; Breyer, Emelita D.

2005-01-01

The Molecular Genetics and Protein Structure and Function workshop is one of a series of workshops offered by the National Science Foundation-funded Center for Workshops in the Chemical Sciences. The workshop provides a hands-on introduction to current topics and techniques in molecular genetics and protein structure/function as applied to…

Beyond sex differences: new approaches for thinking about variation in brain structure and function

PubMed Central

Joel, Daphna; Fausto-Sterling, Anne

2016-01-01

In the study of variation in brain structure and function that might relate to sex and gender, language matters because it frames our research questions and methods. In this article, we offer an approach to thinking about variation in brain structure and function that pulls us outside the sex differences formulation. We argue that the existence of differences between the brains of males and females does not unravel the relations between sex and the brain nor is it sufficient to characterize a population of brains. Such characterization is necessary for studying sex effects on the brain as well as for studying brain structure and function in general. Animal studies show that sex interacts with environmental, developmental and genetic factors to affect the brain. Studies of humans further suggest that human brains are better described as belonging to a single heterogeneous population rather than two distinct populations. We discuss the implications of these observations for studies of brain and behaviour in humans and in laboratory animals. We believe that studying sex effects in context and developing or adopting analytical methods that take into account the heterogeneity of the brain are crucial for the advancement of human health and well-being. PMID:26833844

Electrospun microcrimped fibers with nonlinear mechanical properties enhance ligament fibroblast phenotype.

PubMed

Grace Chao, Pen-hsiu; Hsu, Hsiang-Yi; Tseng, Hsiao-Yun

2014-09-01

Fiber structure and order greatly impact the mechanical behavior of fibrous materials. In biological tissues, the nonlinear mechanics of fibrous scaffolds contribute to the functionality of the material. The nonlinear mechanical properties of the wavy structure (crimp) in collagen allow tissue flexibility while preventing over-extension. A number of approaches have tried to recreate this complex mechanical functionality. We generated microcrimped fibers by briefly heating electrospun parallel fibers over the glass transition temperature or by ethanol treatment. The crimp structure is similar to those of collagen fibers found in native aorta, intestines, or ligaments. Using poly-L-lactic acid fibers, we demonstrated that the bulk materials exhibit changed stress-strain behaviors with a significant increase in the toe region in correlation to the degree of crimp, similar to those observed in collagenous tissues. In addition to mimicking the stress-strain behavior of biological tissues, the microcrimped fibers are instructive in cell morphology and promote ligament phenotypic gene expression. This effect can be further enhanced by dynamic tensile loading, a physiological perturbation in vivo. This rapid and economical approach for microcrimped fiber production provides an accessible platform to study structure-function relationships and a novel functional scaffold for tissue engineering and cell mechanobiology studies.

Revisiting the structure/function relationships of H/ACA(-like) RNAs: a unified model for Euryarchaea and Crenarchaea

PubMed Central

Toffano-Nioche, Claire; Gautheret, Daniel; Leclerc, Fabrice

2015-01-01

A structural and functional classification of H/ACA and H/ACA-like motifs is obtained from the analysis of the H/ACA guide RNAs which have been identified previously in the genomes of Euryarchaea (Pyrococcus) and Crenarchaea (Pyrobaculum). A unified structure/function model is proposed based on the common structural determinants shared by H/ACA and H/ACA-like motifs in both Euryarchaea and Crenarchaea. Using a computational approach, structural and energetic rules for the guide:target RNA-RNA interactions are derived from structural and functional data on the H/ACA RNP particles. H/ACA(-like) motifs found in Pyrococcus are evaluated through the classification and their biological relevance is discussed. Extra-ribosomal targets found in both Pyrococcus and Pyrobaculum might support the hypothesis of a gene regulation mediated by H/ACA(-like) guide RNAs in archaea. PMID:26240384

Asymmetry of Hemispheric Network Topology Reveals Dissociable Processes between Functional and Structural Brain Connectome in Community-Living Elders

PubMed Central

Sun, Yu; Li, Junhua; Suckling, John; Feng, Lei

2017-01-01

Human brain is structurally and functionally asymmetrical and the asymmetries of brain phenotypes have been shown to change in normal aging. Recent advances in graph theoretical analysis have showed topological lateralization between hemispheric networks in the human brain throughout the lifespan. Nevertheless, apparent discrepancies of hemispheric asymmetry were reported between the structural and functional brain networks, indicating the potentially complex asymmetry patterns between structural and functional networks in aging population. In this study, using multimodal neuroimaging (resting-state fMRI and structural diffusion tensor imaging), we investigated the characteristics of hemispheric network topology in 76 (male/female = 15/61, age = 70.08 ± 5.30 years) community-dwelling older adults. Hemispheric functional and structural brain networks were obtained for each participant. Graph theoretical approaches were then employed to estimate the hemispheric topological properties. We found that the optimal small-world properties were preserved in both structural and functional hemispheric networks in older adults. Moreover, a leftward asymmetry in both global and local levels were observed in structural brain networks in comparison with a symmetric pattern in functional brain network, suggesting a dissociable process of hemispheric asymmetry between structural and functional connectome in healthy older adults. Finally, the scores of hemispheric asymmetry in both structural and functional networks were associated with behavioral performance in various cognitive domains. Taken together, these findings provide new insights into the lateralized nature of multimodal brain connectivity, highlight the potentially complex relationship between structural and functional brain network alterations, and augment our understanding of asymmetric structural and functional specializations in normal aging. PMID:29209197

Combining electronic structure and many-body theory with large databases: A method for predicting the nature of 4 f states in Ce compounds

NASA Astrophysics Data System (ADS)

Herper, H. C.; Ahmed, T.; Wills, J. M.; Di Marco, I.; Björkman, T.; Iuşan, D.; Balatsky, A. V.; Eriksson, O.

2017-08-01

Recent progress in materials informatics has opened up the possibility of a new approach to accessing properties of materials in which one assays the aggregate properties of a large set of materials within the same class in addition to a detailed investigation of each compound in that class. Here we present a large scale investigation of electronic properties and correlated magnetism in Ce-based compounds accompanied by a systematic study of the electronic structure and 4 f -hybridization function of a large body of Ce compounds. We systematically study the electronic structure and 4 f -hybridization function of a large body of Ce compounds with the goal of elucidating the nature of the 4 f states and their interrelation with the measured Kondo energy in these compounds. The hybridization function has been analyzed for more than 350 data sets (being part of the IMS database) of cubic Ce compounds using electronic structure theory that relies on a full-potential approach. We demonstrate that the strength of the hybridization function, evaluated in this way, allows us to draw precise conclusions about the degree of localization of the 4 f states in these compounds. The theoretical results are entirely consistent with all experimental information, relevant to the degree of 4 f localization for all investigated materials. Furthermore, a more detailed analysis of the electronic structure and the hybridization function allows us to make precise statements about Kondo correlations in these systems. The calculated hybridization functions, together with the corresponding density of states, reproduce the expected exponential behavior of the observed Kondo temperatures and prove a consistent trend in real materials. This trend allows us to predict which systems may be correctly identified as Kondo systems. A strong anticorrelation between the size of the hybridization function and the volume of the systems has been observed. The information entropy for this set of systems is about 0.42. Our approach demonstrates the predictive power of materials informatics when a large number of materials is used to establish significant trends. This predictive power can be used to design new materials with desired properties. The applicability of this approach for other correlated electron systems is discussed.

Recent advances in rational approaches for enzyme engineering

PubMed Central

Steiner, Kerstin; Schwab, Helmut

2012-01-01

Enzymes are an attractive alternative in the asymmetric syntheses of chiral building blocks. To meet the requirements of industrial biotechnology and to introduce new functionalities, the enzymes need to be optimized by protein engineering. This article specifically reviews rational approaches for enzyme engineering and de novo enzyme design involving structure-based approaches developed in recent years for improvement of the enzymes’ performance, broadened substrate range, and creation of novel functionalities to obtain products with high added value for industrial applications. PMID:24688651

The Human Placenta Project: Placental Structure, Development, and Function in Real Time

PubMed Central

Guttmacher, Alan E.; Maddox, Yvonne T.; Spong, Catherine Y.

2014-01-01

Despite its crucial role in the health of both the fetus and the pregnant woman, the placenta is the least understood human organ. Since a growing body of evidence also underscores the importance of placental development in the lifelong health of both mother and offspring, this lack of knowledge about placental structure and function is particularly concerning. Given modern approaches and technologies and the ability to develop new methods, we propose a coordinated “Human Placenta Project,” with the ultimate goal of understanding human placental structure, development, and function in real time. PMID:24661567

Use of Random and Site-Directed Mutagenesis to Probe Protein Structure-Function Relationships: Applied Techniques in the Study of Helicobacter pylori.

PubMed

Whitmire, Jeannette M; Merrell, D Scott

2017-01-01

Mutagenesis is a valuable tool to examine the structure-function relationships of bacterial proteins. As such, a wide variety of mutagenesis techniques and strategies have been developed. This chapter details a selection of random mutagenesis methods and site-directed mutagenesis procedures that can be applied to an array of bacterial species. Additionally, the direct application of the techniques to study the Helicobacter pylori Ferric Uptake Regulator (Fur) protein is described. The varied approaches illustrated herein allow the robust investigation of the structural-functional relationships within a protein of interest.

Structured functional additive regression in reproducing kernel Hilbert spaces

PubMed Central

Zhu, Hongxiao; Yao, Fang; Zhang, Hao Helen

2013-01-01

Summary Functional additive models (FAMs) provide a flexible yet simple framework for regressions involving functional predictors. The utilization of data-driven basis in an additive rather than linear structure naturally extends the classical functional linear model. However, the critical issue of selecting nonlinear additive components has been less studied. In this work, we propose a new regularization framework for the structure estimation in the context of Reproducing Kernel Hilbert Spaces. The proposed approach takes advantage of the functional principal components which greatly facilitates the implementation and the theoretical analysis. The selection and estimation are achieved by penalized least squares using a penalty which encourages the sparse structure of the additive components. Theoretical properties such as the rate of convergence are investigated. The empirical performance is demonstrated through simulation studies and a real data application. PMID:25013362

A conservative approach for treating young adult patients with porcelain laminate veneers.

PubMed

Chen, Yen-Wei; Raigrodski, Ariel J

2008-01-01

Controversy persists regarding the treatment planning criteria for young adult patients in need of esthetic restorations. The trend of conservative treatment modalities continues to become widely acknowledged. One of the conservative treatment modalities is porcelain laminate veneers (PLVs). PLVs not only provide suitable esthetics but also reliable functional strength. This article presents two anterior esthetic cases to demonstrate a conservative treatment planning approach and its application as a nontraditional solution for young adult patients. It is recommended that a conservative approach be used wherever possible as an alternative to treatment options that may aggressively sacrifice tooth structure as well as the health of the supporting tissues. By using a conservative approach to treatment with porcelain veneers, long-lasting, esthetic, and functional results may be achieved. Sacrificing as little tooth structure as possible and conserving the supporting tissues will facilitate prospective treatments for young adult patients.

Simultaneous optimization of biomolecular energy function on features from small molecules and macromolecules

PubMed Central

Park, Hahnbeom; Bradley, Philip; Greisen, Per; Liu, Yuan; Mulligan, Vikram Khipple; Kim, David E.; Baker, David; DiMaio, Frank

2017-01-01

Most biomolecular modeling energy functions for structure prediction, sequence design, and molecular docking, have been parameterized using existing macromolecular structural data; this contrasts molecular mechanics force fields which are largely optimized using small-molecule data. In this study, we describe an integrated method that enables optimization of a biomolecular modeling energy function simultaneously against small-molecule thermodynamic data and high-resolution macromolecular structural data. We use this approach to develop a next-generation Rosetta energy function that utilizes a new anisotropic implicit solvation model, and an improved electrostatics and Lennard-Jones model, illustrating how energy functions can be considerably improved in their ability to describe large-scale energy landscapes by incorporating both small-molecule and macromolecule data. The energy function improves performance in a wide range of protein structure prediction challenges, including monomeric structure prediction, protein-protein and protein-ligand docking, protein sequence design, and prediction of the free energy changes by mutation, while reasonably recapitulating small-molecule thermodynamic properties. PMID:27766851

Functional Annotation of Ion Channel Structures by Molecular Simulation.

PubMed

Trick, Jemma L; Chelvaniththilan, Sivapalan; Klesse, Gianni; Aryal, Prafulla; Wallace, E Jayne; Tucker, Stephen J; Sansom, Mark S P

2016-12-06

Ion channels play key roles in cell membranes, and recent advances are yielding an increasing number of structures. However, their functional relevance is often unclear and better tools are required for their functional annotation. In sub-nanometer pores such as ion channels, hydrophobic gating has been shown to promote dewetting to produce a functionally closed (i.e., non-conductive) state. Using the serotonin receptor (5-HT 3 R) structure as an example, we demonstrate the use of molecular dynamics to aid the functional annotation of channel structures via simulation of the behavior of water within the pore. Three increasingly complex simulation analyses are described: water equilibrium densities; single-ion free-energy profiles; and computational electrophysiology. All three approaches correctly predict the 5-HT 3 R crystal structure to represent a functionally closed (i.e., non-conductive) state. We also illustrate the application of water equilibrium density simulations to annotate different conformational states of a glycine receptor. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Bioinformatics approaches for structural and functional analysis of proteins in secondary metabolism in Withania somnifera.

PubMed

Sanchita; Singh, Swati; Sharma, Ashok

2014-11-01

Withania somnifera (Ashwagandha) is an affluent storehouse of large number of pharmacologically active secondary metabolites known as withanolides. These secondary metabolites are produced by withanolide biosynthetic pathway. Very less information is available on structural and functional aspects of enzymes involved in withanolides biosynthetic pathways of Withiana somnifera. We therefore performed a bioinformatics analysis to look at functional and structural properties of these important enzymes. The pathway enzymes taken for this study were 3-Hydroxy-3-methylglutaryl coenzyme A reductase, 1-Deoxy-D-xylulose-5-phosphate synthase, 1-Deoxy-D-xylulose-5-phosphate reductase, farnesyl pyrophosphate synthase, squalene synthase, squalene epoxidase, and cycloartenol synthase. The prediction of secondary structure was performed for basic structural information. Three-dimensional structures for these enzymes were predicted. The physico-chemical properties such as pI, AI, GRAVY and instability index were also studied. The current information will provide a platform to know the structural attributes responsible for the function of these protein until experimental structures become available.

Engineering of routes to heparin and related polysaccharides.

PubMed

Bhaskar, Ujjwal; Sterner, Eric; Hickey, Anne Marie; Onishi, Akihiro; Zhang, Fuming; Dordick, Jonathan S; Linhardt, Robert J

2012-01-01

Anticoagulant heparin has been shown to possess important biological functions that vary according to its fine structure. Variability within heparin's structure occurs owing to its biosynthesis and animal tissue-based recovery and adds another dimension to its complex polymeric structure. The structural variations in chain length and sulfation patterns mediate its interaction with many heparin-binding proteins, thereby eliciting complex biological responses. The advent of novel chemical and enzymatic approaches for polysaccharide synthesis coupled with high throughput combinatorial approaches for drug discovery have facilitated an increased effort to understand heparin's structure-activity relationships. An improved understanding would offer potential for new therapeutic development through the engineering of polysaccharides. Such a bioengineering approach requires the amalgamation of several different disciplines, including carbohydrate synthesis, applied enzymology, metabolic engineering, and process biochemistry.

From the crust to the core of neutron stars on a microscopic basis

NASA Astrophysics Data System (ADS)

Baldo, M.; Burgio, G. F.; Centelles, M.; Sharma, B. K.; Viñas, X.

2014-09-01

Within a microscopic approach the structure of Neutron Stars is usually studied by modelling the homogeneous nuclear matter of the core by a suitable Equation of State, based on a many-body theory, and the crust by a functional based on a more phenomenological approach. We present the first calculation of Neutron Star overall structure by adopting for the core an Equation of State derived from the Brueckner-Hartree-Fock theory and for the crust, including the pasta phase, an Energy Density Functional based on the same Equation of State, and which is able to describe accurately the binding energy of nuclei throughout the mass table. Comparison with other approaches is discussed. The relevance of the crust Equation of State for the Neutron Star radius is particularly emphasised.

A novel approach for introducing cloud spatial structure into cloud radiative transfer parameterizations

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

Huang, Dong; Liu, Yangang

2014-12-18

Subgrid-scale variability is one of the main reasons why parameterizations are needed in large-scale models. Although some parameterizations started to address the issue of subgrid variability by introducing a subgrid probability distribution function for relevant quantities, the spatial structure has been typically ignored and thus the subgrid-scale interactions cannot be accounted for physically. Here we present a new statistical-physics-like approach whereby the spatial autocorrelation function can be used to physically capture the net effects of subgrid cloud interaction with radiation. The new approach is able to faithfully reproduce the Monte Carlo 3D simulation results with several orders less computational cost,more » allowing for more realistic representation of cloud radiation interactions in large-scale models.« less

Patterning nanofibrils through the templated growth of multiple modified amyloid peptides

PubMed Central

Sakai, Hiroki; Watanabe, Ken; Kudoh, Fuki; Kamada, Rui; Chuman, Yoshiro; Sakaguchi, Kazuyasu

2016-01-01

There has been considerable interest in the patterning of functionalized nanowires because of the potential applications of these materials to the construction of nanodevices. A variety of biomolecular building blocks containing amyloid peptides have been used to functionalize nanowires. However, the patterning of self-assembled nanowires can be challenging because of the difficulties associated with controlling the self-assembly of these functionalized building blocks. Herein, we present a versatile approach for the patterning of nanowires based on the combination of templated fibril growth with a versatile functionalization method using our structure-controllable amyloid peptides (SCAPs). Using this approach, we have succeeded in the formation of multi-type nanowires with tandem domain structures in high yields. Given that the mixing-SCAP method can lead to the formation of tandem fibrils, it is noteworthy that our method allowed us to control the initiation of fibril formation from the gold nanoparticles, which were attached to a short fibril as initiation points. This approach could be used to prepare a wide variety of fibril patterns, and therefore holds great potential for the development of novel self-assembled nanodevices. PMID:27559011

Application of multivariable search techniques to structural design optimization

NASA Technical Reports Server (NTRS)

Jones, R. T.; Hague, D. S.

1972-01-01

Multivariable optimization techniques are applied to a particular class of minimum weight structural design problems: the design of an axially loaded, pressurized, stiffened cylinder. Minimum weight designs are obtained by a variety of search algorithms: first- and second-order, elemental perturbation, and randomized techniques. An exterior penalty function approach to constrained minimization is employed. Some comparisons are made with solutions obtained by an interior penalty function procedure. In general, it would appear that an interior penalty function approach may not be as well suited to the class of design problems considered as the exterior penalty function approach. It is also shown that a combination of search algorithms will tend to arrive at an extremal design in a more reliable manner than a single algorithm. The effect of incorporating realistic geometrical constraints on stiffener cross-sections is investigated. A limited comparison is made between minimum weight cylinders designed on the basis of a linear stability analysis and cylinders designed on the basis of empirical buckling data. Finally, a technique for locating more than one extremal is demonstrated.

Integrative computational approach for genome-based study of microbial lipid-degrading enzymes.

PubMed

Vorapreeda, Tayvich; Thammarongtham, Chinae; Laoteng, Kobkul

2016-07-01

Lipid-degrading or lipolytic enzymes have gained enormous attention in academic and industrial sectors. Several efforts are underway to discover new lipase enzymes from a variety of microorganisms with particular catalytic properties to be used for extensive applications. In addition, various tools and strategies have been implemented to unravel the functional relevance of the versatile lipid-degrading enzymes for special purposes. This review highlights the study of microbial lipid-degrading enzymes through an integrative computational approach. The identification of putative lipase genes from microbial genomes and metagenomic libraries using homology-based mining is discussed, with an emphasis on sequence analysis of conserved motifs and enzyme topology. Molecular modelling of three-dimensional structure on the basis of sequence similarity is shown to be a potential approach for exploring the structural and functional relationships of candidate lipase enzymes. The perspectives on a discriminative framework of cutting-edge tools and technologies, including bioinformatics, computational biology, functional genomics and functional proteomics, intended to facilitate rapid progress in understanding lipolysis mechanism and to discover novel lipid-degrading enzymes of microorganisms are discussed.

From Brain Maps to Cognitive Ontologies: Informatics and the Search for Mental Structure.

PubMed

Poldrack, Russell A; Yarkoni, Tal

2016-01-01

A major goal of cognitive neuroscience is to delineate how brain systems give rise to mental function. Here we review the increasingly large role informatics-driven approaches are playing in such efforts. We begin by reviewing a number of challenges conventional neuroimaging approaches face in trying to delineate brain-cognition mappings--for example, the difficulty in establishing the specificity of postulated associations. Next, we demonstrate how these limitations can potentially be overcome using complementary approaches that emphasize large-scale analysis--including meta-analytic methods that synthesize hundreds or thousands of studies at a time; latent-variable approaches that seek to extract structure from data in a bottom-up manner; and predictive modeling approaches capable of quantitatively inferring mental states from patterns of brain activity. We highlight the underappreciated but critical role for formal cognitive ontologies in helping to clarify, refine, and test theories of brain and cognitive function. Finally, we conclude with a speculative discussion of what future informatics developments may hold for cognitive neuroscience.

From brain maps to cognitive ontologies: informatics and the search for mental structure

PubMed Central

Poldrack, Russell A.; Yarkoni, Tal

2015-01-01

A major goal of cognitive neuroscience is to delineate how brain systems give rise to mental function. Here we review the increasingly large role informatics-driven approaches are playing in such efforts. We begin by reviewing a number of challenges conventional neuroimaging approaches face in trying to delineate brain-cognition mappings—for example, the difficulty in establishing the specificity of postulated associations. Next, we demonstrate how these limitations can potentially be overcome using complementary approaches that emphasize large-scale analysis—including meta-analytic methods that synthesize hundreds or thousands of studies at a time; latent-variable approaches that seek to extract structure from data in a bottom-up manner; and predictive modeling approaches capable of quantitatively inferring mental states from patterns of brain activity. We highlight the underappreciated but critical role for formal cognitive ontologies in helping to clarify, refine, and test theories of brain and cognitive function. Finally, we conclude with a speculative discussion of what future informatics developments may hold for cognitive neuroscience. PMID:26393866

An EQT-cDFT approach to determine thermodynamic properties of confined fluids.

PubMed

Mashayak, S Y; Motevaselian, M H; Aluru, N R

2015-06-28

We present a continuum-based approach to predict the structure and thermodynamic properties of confined fluids at multiple length-scales, ranging from a few angstroms to macro-meters. The continuum approach is based on the empirical potential-based quasi-continuum theory (EQT) and classical density functional theory (cDFT). EQT is a simple and fast approach to predict inhomogeneous density and potential profiles of confined fluids. We use EQT potentials to construct a grand potential functional for cDFT. The EQT-cDFT-based grand potential can be used to predict various thermodynamic properties of confined fluids. In this work, we demonstrate the EQT-cDFT approach by simulating Lennard-Jones fluids, namely, methane and argon, confined inside slit-like channels of graphene. We show that the EQT-cDFT can accurately predict the structure and thermodynamic properties, such as density profiles, adsorption, local pressure tensor, surface tension, and solvation force, of confined fluids as compared to the molecular dynamics simulation results.

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

Not Available

This report was prepared at the request of the Lawrence Livermore Laboratory (LLL) to provide background information for analyzing soil-structure interaction by the frequency-independent impedance function approach. LLL is conducting such analyses as part of its seismic review of selected operating plants under the Systematic Evaluation Program for the US Nuclear Regulatory Commission. The analytical background and basic assumptionsof the impedance function theory are briefly reviewed, and the role of radiation damping in soil-structure interaction analysis is discussed. The validity of modeling soil-structure interaction by using frequency-independent functions is evaluated based on data from several field tests. Finally, the recommendedmore » procedures for performing soil-structure interaction analyses are discussed with emphasis on the modal superposition method.« less

Permeating disciplines: Overcoming barriers between molecular simulations and classical structure-function approaches in biological ion transport.

PubMed

Howard, Rebecca J; Carnevale, Vincenzo; Delemotte, Lucie; Hellmich, Ute A; Rothberg, Brad S

2018-04-01

Ion translocation across biological barriers is a fundamental requirement for life. In many cases, controlling this process-for example with neuroactive drugs-demands an understanding of rapid and reversible structural changes in membrane-embedded proteins, including ion channels and transporters. Classical approaches to electrophysiology and structural biology have provided valuable insights into several such proteins over macroscopic, often discontinuous scales of space and time. Integrating these observations into meaningful mechanistic models now relies increasingly on computational methods, particularly molecular dynamics simulations, while surfacing important challenges in data management and conceptual alignment. Here, we seek to provide contemporary context, concrete examples, and a look to the future for bridging disciplinary gaps in biological ion transport. This article is part of a Special Issue entitled: Beyond the Structure-Function Horizon of Membrane Proteins edited by Ute Hellmich, Rupak Doshi and Benjamin McIlwain. Copyright © 2017 Elsevier B.V. All rights reserved.

A Case Study on the Application of a Structured Experimental Method for Optimal Parameter Design of a Complex Control System

NASA Technical Reports Server (NTRS)

Torres-Pomales, Wilfredo

2015-01-01

This report documents a case study on the application of Reliability Engineering techniques to achieve an optimal balance between performance and robustness by tuning the functional parameters of a complex non-linear control system. For complex systems with intricate and non-linear patterns of interaction between system components, analytical derivation of a mathematical model of system performance and robustness in terms of functional parameters may not be feasible or cost-effective. The demonstrated approach is simple, structured, effective, repeatable, and cost and time efficient. This general approach is suitable for a wide range of systems.

Nonparametric modeling of longitudinal covariance structure in functional mapping of quantitative trait loci.

PubMed

Yap, John Stephen; Fan, Jianqing; Wu, Rongling

2009-12-01

Estimation of the covariance structure of longitudinal processes is a fundamental prerequisite for the practical deployment of functional mapping designed to study the genetic regulation and network of quantitative variation in dynamic complex traits. We present a nonparametric approach for estimating the covariance structure of a quantitative trait measured repeatedly at a series of time points. Specifically, we adopt Huang et al.'s (2006, Biometrika 93, 85-98) approach of invoking the modified Cholesky decomposition and converting the problem into modeling a sequence of regressions of responses. A regularized covariance estimator is obtained using a normal penalized likelihood with an L(2) penalty. This approach, embedded within a mixture likelihood framework, leads to enhanced accuracy, precision, and flexibility of functional mapping while preserving its biological relevance. Simulation studies are performed to reveal the statistical properties and advantages of the proposed method. A real example from a mouse genome project is analyzed to illustrate the utilization of the methodology. The new method will provide a useful tool for genome-wide scanning for the existence and distribution of quantitative trait loci underlying a dynamic trait important to agriculture, biology, and health sciences.

Tuning cell adhesion by direct nanostructuring silicon into cell repulsive/adhesive patterns

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

Premnath, Priyatha, E-mail: priyatha.premnath@ryerson.ca; Tavangar, Amirhossein, E-mail: atavanga@ryerson.ca; Tan, Bo, E-mail: tanbo@ryerson.ca

2015-09-10

Developing platforms that allow tuning cell functionality through incorporating physical, chemical, or mechanical cues onto the material surfaces is one of the key challenges in research in the field of biomaterials. In this respect, various approaches have been proposed and numerous structures have been developed on a variety of materials. Most of these approaches, however, demand a multistep process or post-chemical treatment. Therefore, a simple approach would be desirable to develop bio-functionalized platforms for effectively modulating cell adhesion and consequently programming cell functionality without requiring any chemical or biological surface treatment. This study introduces a versatile yet simple laser approachmore » to structure silicon (Si) chips into cytophobic/cytophilic patterns in order to modulate cell adhesion and proliferation. These patterns are fabricated on platforms through direct laser processing of Si substrates, which renders a desired computer-generated configuration into patterns. We investigate the morphology, chemistry, and wettability of the platform surfaces. Subsequently, we study the functionality of the fabricated platforms on modulating cervical cancer cells (HeLa) behaviour. The results from in vitro studies suggest that the nanostructures efficiently repel HeLa cells and drive them to migrate onto untreated sites. The study of the morphology of the cells reveals that cells evade the cytophobic area by bending and changing direction. Additionally, cell patterning, cell directionality, cell channelling, and cell trapping are achieved by developing different platforms with specific patterns. The flexibility and controllability of this approach to effectively structure Si substrates to cell-repulsive and cell-adhesive patterns offer perceptible outlook for developing bio-functionalized platforms for a variety of biomedical devices. Moreover, this approach could pave the way for developing anti-cancer platforms that selectively repel cancer cells while favoring the adhesion of normal cells. - Highlights: • Si platforms with cytophobic/philic patterns were developed to program cell growth. • Both nanotopography and chemistry contributed to the cytophobic property. • Cytophobic zones efficiently repel and drive HeLa cells to migrate to adhesive sites. • The approach enables cell patterning, directionality, channelling, and trapping. • This approach paves the way for developing anti-cancer platforms.« less

Methods to enable the design of bioactive small molecules targeting RNA

PubMed Central

Disney, Matthew D.; Yildirim, Ilyas; Childs-Disney, Jessica L.

2014-01-01

RNA is an immensely important target for small molecule therapeutics or chemical probes of function. However, methods that identify, annotate, and optimize RNA-small molecule interactions that could enable the design of compounds that modulate RNA function are in their infancies. This review describes recent approaches that have been developed to understand and optimize RNA motif-small molecule interactions, including Structure-Activity Relationships Through Sequencing (StARTS), quantitative structure-activity relationships (QSAR), chemical similarity searching, structure-based design and docking, and molecular dynamics (MD) simulations. Case studies described include the design of small molecules targeting RNA expansions, the bacterial A-site, viral RNAs, and telomerase RNA. These approaches can be combined to afford a synergistic method to exploit the myriad of RNA targets in the transcriptome. PMID:24357181

Methods to enable the design of bioactive small molecules targeting RNA.

PubMed

Disney, Matthew D; Yildirim, Ilyas; Childs-Disney, Jessica L

2014-02-21

RNA is an immensely important target for small molecule therapeutics or chemical probes of function. However, methods that identify, annotate, and optimize RNA-small molecule interactions that could enable the design of compounds that modulate RNA function are in their infancies. This review describes recent approaches that have been developed to understand and optimize RNA motif-small molecule interactions, including structure-activity relationships through sequencing (StARTS), quantitative structure-activity relationships (QSAR), chemical similarity searching, structure-based design and docking, and molecular dynamics (MD) simulations. Case studies described include the design of small molecules targeting RNA expansions, the bacterial A-site, viral RNAs, and telomerase RNA. These approaches can be combined to afford a synergistic method to exploit the myriad of RNA targets in the transcriptome.

Cholinesterase Confabs and Cousins: Approaching Forty Years

PubMed Central

Taylor, Palmer; De Jaco, Antonella; Comoletti, Davide; Miller, Meghan; Camp, Shelley

2013-01-01

In the past four decades of cholinesterase (ChE) research, we have seen substantive evolution of the field from one centered around substrate and inhibitor kinetic profiles and compound characterizations to the analysis of ChE structure, first through the gene families and then by x-ray crystallographic determinations of the free enzymes and their complexes and conjugates. Indeed, these endeavors have been facilitated by recombinant DNA technologies, structure determinations and parallel studies in related proteins in the α/β-hydrolase fold family. This approach has not only contributed to a fundamental understanding of structure and function of a large family of hydrolase-like proteins possessing functions other than catalysis, but also has been used to develop new practical strategies for scavenging and antidotal activity in cases of organophosphate insecticide or nerve agent exposure. PMID:23085121

Adaptive structures for precision controlled large space systems

NASA Technical Reports Server (NTRS)

Garba, John A.; Wada, Ben K.; Fanson, James L.

1991-01-01

The stringent accuracy and ground test validation requirements of some of the future space missions will require new approaches in structural design. Adaptive structures, structural systems that can vary their geometric congiguration as well as their physical properties, are primary candidates for meeting the functional requirements for such missions. Research performed in the development of such adaptive structural systems is described.

Modular assembly of thick multifunctional cardiac patches

PubMed Central

Fleischer, Sharon; Shapira, Assaf; Feiner, Ron; Dvir, Tal

2017-01-01

In cardiac tissue engineering cells are seeded within porous biomaterial scaffolds to create functional cardiac patches. Here, we report on a bottom-up approach to assemble a modular tissue consisting of multiple layers with distinct structures and functions. Albumin electrospun fiber scaffolds were laser-patterned to create microgrooves for engineering aligned cardiac tissues exhibiting anisotropic electrical signal propagation. Microchannels were patterned within the scaffolds and seeded with endothelial cells to form closed lumens. Moreover, cage-like structures were patterned within the scaffolds and accommodated poly(lactic-co-glycolic acid) (PLGA) microparticulate systems that controlled the release of VEGF, which promotes vascularization, or dexamethasone, an anti-inflammatory agent. The structure, morphology, and function of each layer were characterized, and the tissue layers were grown separately in their optimal conditions. Before transplantation the tissue and microparticulate layers were integrated by an ECM-based biological glue to form thick 3D cardiac patches. Finally, the patches were transplanted in rats, and their vascularization was assessed. Because of the simple modularity of this approach, we believe that it could be used in the future to assemble other multicellular, thick, 3D, functional tissues. PMID:28167795

Does shape co-variation between the skull and the mandible have functional consequences? A 3D approach for a 3D problem

PubMed Central

Cornette, Raphaël; Baylac, Michel; Souter, Thibaud; Herrel, Anthony

2013-01-01

Morpho-functional patterns are important drivers of phenotypic diversity given their importance in a fitness-related context. Although modularity of the mandible and skull has been studied extensively in mammals, few studies have explored shape co-variation between these two structures. Despite being developmentally independent, the skull and mandible form a functionally integrated unit. In the present paper we use 3D surface geometric morphometric methods allowing us to explore the form of both skull and mandible in its 3D complexity using the greater white-toothed shrew as a model. This approach allows an accurate 3D description of zones devoid of anatomical landmarks that are functionally important. Two-block partial least-squares approaches were used to describe the co-variation of form between skull and mandible. Moreover, a 3D biomechanical model was used to explore the functional consequences of the observed patterns of co-variation. Our results show the efficiency of the method in investigations of complex morpho-functional patterns. Indeed, the description of shape co-variation between the skull and the mandible highlighted the location and the intensity of their functional relationships through the jaw adductor muscles linking these two structures. Our results also demonstrated that shape co-variation in form between the skull and mandible has direct functional consequences on the recruitment of muscles during biting. PMID:23964811

A Structural Biology and Protein Engineering Approach to the Development of Antidotes against the Inhibition of Human Acetylcholinesterase by OP-based Nerve Agents

DTIC Science & Technology

2014-03-01

for Biotechnology, Gurgaon, India (Sep, 2013) by Joel L. Sussman, title: “Molecular Basis of How Nerve Agents through anti- Alzheimer Drugs Function...Molecular Basis of How Nerve Agents through anti- Alzheimer Drugs Function: 3D Structure of Acetylcholinesterase • Florida International University...FIU), Miami, FL (Dec 2013) - Invited Lecture by Joel L. Sussman, title: “Molecular Basis of anti- Alzheimer Drugs & Nerve Agents: 3D Structure of

REVIEWS OF TOPICAL PROBLEMS: Nonlinear dynamics of the brain: emotion and cognition

NASA Astrophysics Data System (ADS)

Rabinovich, Mikhail I.; Muezzinoglu, M. K.

2010-07-01

Experimental investigations of neural system functioning and brain activity are standardly based on the assumption that perceptions, emotions, and cognitive functions can be understood by analyzing steady-state neural processes and static tomographic snapshots. The new approaches discussed in this review are based on the analysis of transient processes and metastable states. Transient dynamics is characterized by two basic properties, structural stability and information sensitivity. The ideas and methods that we discuss provide an explanation for the occurrence of and successive transitions between metastable states observed in experiments, and offer new approaches to behavior analysis. Models of the emotional and cognitive functions of the brain are suggested. The mathematical object that represents the observed transient brain processes in the phase space of the model is a structurally stable heteroclinic channel. The possibility of using the suggested models to construct a quantitative theory of some emotional and cognitive functions is illustrated.

Understanding volatility correlation behavior with a magnitude cross-correlation function

NASA Astrophysics Data System (ADS)

Jun, Woo Cheol; Oh, Gabjin; Kim, Seunghwan

2006-06-01

We propose an approach for analyzing the basic relation between correlation properties of the original signal and its magnitude fluctuations by decomposing the original signal into its positive and negative fluctuation components. We use this relation to understand the following phenomenon found in many naturally occurring time series: the magnitude of the signal exhibits long-range correlation, whereas the original signal is short-range correlated. The applications of our approach to heart rate variability signals and high-frequency foreign exchange rates reveal that the difference between the correlation properties of the original signal and its magnitude fluctuations is induced by the time organization structure of the correlation function between the magnitude fluctuations of positive and negative components. We show that this correlation function can be described well by a stretched-exponential function and is related to the nonlinearity and the multifractal structure of the signals.

Understanding volatility correlation behavior with a magnitude cross-correlation function.

PubMed

Jun, Woo Cheol; Oh, Gabjin; Kim, Seunghwan

2006-06-01

We propose an approach for analyzing the basic relation between correlation properties of the original signal and its magnitude fluctuations by decomposing the original signal into its positive and negative fluctuation components. We use this relation to understand the following phenomenon found in many naturally occurring time series: the magnitude of the signal exhibits long-range correlation, whereas the original signal is short-range correlated. The applications of our approach to heart rate variability signals and high-frequency foreign exchange rates reveal that the difference between the correlation properties of the original signal and its magnitude fluctuations is induced by the time organization structure of the correlation function between the magnitude fluctuations of positive and negative components. We show that this correlation function can be described well by a stretched-exponential function and is related to the nonlinearity and the multifractal structure of the signals.

Combining protein sequence, structure, and dynamics: A novel approach for functional evolution analysis of PAS domain superfamily.

PubMed

Dong, Zheng; Zhou, Hongyu; Tao, Peng

2018-02-01

PAS domains are widespread in archaea, bacteria, and eukaryota, and play important roles in various functions. In this study, we aim to explore functional evolutionary relationship among proteins in the PAS domain superfamily in view of the sequence-structure-dynamics-function relationship. We collected protein sequences and crystal structure data from RCSB Protein Data Bank of the PAS domain superfamily belonging to three biological functions (nucleotide binding, photoreceptor activity, and transferase activity). Protein sequences were aligned and then used to select sequence-conserved residues and build phylogenetic tree. Three-dimensional structure alignment was also applied to obtain structure-conserved residues. The protein dynamics were analyzed using elastic network model (ENM) and validated by molecular dynamics (MD) simulation. The result showed that the proteins with same function could be grouped by sequence similarity, and proteins in different functional groups displayed statistically significant difference in their vibrational patterns. Interestingly, in all three functional groups, conserved amino acid residues identified by sequence and structure conservation analysis generally have a lower fluctuation than other residues. In addition, the fluctuation of conserved residues in each biological function group was strongly correlated with the corresponding biological function. This research suggested a direct connection in which the protein sequences were related to various functions through structural dynamics. This is a new attempt to delineate functional evolution of proteins using the integrated information of sequence, structure, and dynamics. © 2017 The Protein Society.

Murine intracochlear drug delivery: reducing concentration gradients within the cochlea.

PubMed

Borkholder, David A; Zhu, Xiaoxia; Hyatt, Brad T; Archilla, Alfredo S; Livingston, William J; Frisina, Robert D

2010-09-01

Direct delivery of compounds to the mammalian inner ear is most commonly achieved by absorption or direct injection through the round window membrane (RWM), or infusion through a basal turn cochleostomy. These methods provide direct access to cochlear structures, but with a strong basal-to-apical concentration gradient consistent with a diffusion-driven distribution. This gradient limits the efficacy of therapeutic approaches for apical structures, and puts constraints on practical therapeutic dose ranges. A surgical approach involving both a basal turn cochleostomy and a posterior semicircular canal canalostomy provides opportunities for facilitated perfusion of cochlear structures to reduce concentration gradients. Infusion of fixed volumes of artificial perilymph (AP) and sodium salicylate were used to evaluate two surgical approaches in the mouse: cochleostomy-only (CO), or cochleostomy-plus-canalostomy (C+C). Cochlear function was evaluated via closed-system distortion product otoacoustic emissions (DPOAE) threshold level measurements from 8 to 49 kHz. AP infusion confirmed no surgical impact to auditory function, while shifts in DPOAE thresholds were measured during infusion of salicylate and AP (washout). Frequency dependent shifts were compared for the CO and C+C approaches. Computer simulations modeling diffusion, volume flow, interscala transport, and clearance mechanisms provided estimates of drug concentration as a function of cochlear position. Simulated concentration profiles were compared to frequency-dependent shifts in measured auditory responses using a cochlear tonotopic map. The impact of flow rate on frequency dependent DPOAE threshold shifts was also evaluated for both surgical approaches. Both the C+C approach and a flow rate increase were found to provide enhanced response for lower frequencies, with evidence suggesting the C+C approach reduces concentration gradients within the cochlea. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Murine Intracochlear Drug Delivery: Reducing Concentration Gradients within the Cochlea

PubMed Central

Borkholder, David A.; Zhu, Xiaoxia; Hyatt, Brad T.; Archilla, Alfredo S.; Livingston, William J.; Frisina, Robert D.

2010-01-01

Direct delivery of compounds to the mammalian inner ear is most commonly achieved by absorption or direct injection through the round window membrane (RWM), or infusion through a basal turn cochleostomy. These methods provide direct access to cochlear structures, but with a strong basal-to-apical concentration gradient consistent with a diffusion-driven distribution. This gradient limits the efficacy of therapeutic approaches for apical structures, and puts constraints on practical therapeutic dose ranges. A surgical approach involving both a basal turn cochleostomy and a posterior semicircular canal canalostomy provides opportunities for facilitated perfusion of cochlear structures to reduce concentration gradients. Infusion of fixed volumes of artificial perilymph (AP) and sodium salicylate were used to evaluate two surgical approaches in the mouse: cochleostomy-only (CO), or cochleostomy-plus-canalostomy (C+C). Cochlear function was evaluated via closed-system distortion product otoacoustic emissions (DPOAE) threshold level measurements from 8-49 kHz. AP infusion confirmed no surgical impact to auditory function, while shifts in DPOAE thresholds were measured during infusion of salicylate and AP (washout). Frequency dependent shifts were compared for the CO and C+C approaches. Computer simulations modeling diffusion, volume flow, interscala transport, and clearance mechanisms provided estimates of drug concentration as a function of cochlear position. Simulated concentration profiles were compared to frequency-dependent shifts in measured auditory responses using a cochlear tonotopic map. The impact of flow rate on frequency dependent DPOAE threshold shifts was also evaluated for both surgical approaches. Both the C+C approach and a flow rate increase were found to provide enhanced response for lower frequencies, with evidence suggesting the C+C approach reduces concentration gradients within the cochlea. PMID:20451593

A unified framework for unraveling the functional interaction structure of a biomolecular network based on stimulus-response experimental data.

PubMed

Cho, Kwang-Hyun; Choo, Sang-Mok; Wellstead, Peter; Wolkenhauer, Olaf

2005-08-15

We propose a unified framework for the identification of functional interaction structures of biomolecular networks in a way that leads to a new experimental design procedure. In developing our approach, we have built upon previous work. Thus we begin by pointing out some of the restrictions associated with existing structure identification methods and point out how these restrictions may be eased. In particular, existing methods use specific forms of experimental algebraic equations with which to identify the functional interaction structure of a biomolecular network. In our work, we employ an extended form of these experimental algebraic equations which, while retaining their merits, also overcome some of their disadvantages. Experimental data are required in order to estimate the coefficients of the experimental algebraic equation set associated with the structure identification task. However, experimentalists are rarely provided with guidance on which parameters to perturb, and to what extent, to perturb them. When a model of network dynamics is required then there is also the vexed question of sample rate and sample time selection to be resolved. Supplying some answers to these questions is the main motivation of this paper. The approach is based on stationary and/or temporal data obtained from parameter perturbations, and unifies the previous approaches of Kholodenko et al. (PNAS 99 (2002) 12841-12846) and Sontag et al. (Bioinformatics 20 (2004) 1877-1886). By way of demonstration, we apply our unified approach to a network model which cannot be properly identified by existing methods. Finally, we propose an experiment design methodology, which is not limited by the amount of parameter perturbations, and illustrate its use with an in numero example.

Inpatient rehabilitation approach for a young woman with conversion hemiparesis and sensory deficits.

PubMed

Kanarek, Samantha L; Stevenson, Jennifer E; Wakefield, Holly; Reite, Elizabeth; Zumsteg, Jennifer M; Brockway, Jo Ann

2013-01-01

In the treatment of conversion disorder, the inpatient rehabilitation setting supports interdisciplinary functional goals and a structured approach consistent with encouraging psychological well-being. This case presentation illustrates 1 approach to the rehabilitation of hemiparesis secondary to conversion disorder that includes a behavioral management plan, as well as protocols for "learning to walk" and "learning to use your arm." We provide a practical starting point for advancing function in patients with conversion disorder when functional loss is present in both upper and lower extremities. Copyright © 2013 American Academy of Physical Medicine and Rehabilitation. Published by Elsevier Inc. All rights reserved.

Selective Laser Melting: a regular unit cell approach for the manufacture of porous, titanium, bone in-growth constructs, suitable for orthopedic applications.

PubMed

Mullen, Lewis; Stamp, Robin C; Brooks, Wesley K; Jones, Eric; Sutcliffe, Christopher J

2009-05-01

In this study, a novel porous titanium structure for the purpose of bone in-growth has been designed, manufactured and evaluated. The structure was produced by Selective Laser Melting (SLM); a rapid manufacturing process capable of producing highly intricate, functionally graded parts. The technique described utilizes an approach based on a defined regular unit cell to design and produce structures with a large range of both physical and mechanical properties. These properties can be tailored to suit specific requirements; in particular, functionally graded structures with bone in-growth surfaces exhibiting properties comparable to those of human bone have been manufactured. The structures were manufactured and characterized by unit cell size, strand diameter, porosity, and compression strength. They exhibited a porosity (10-95%) dependant compression strength (0.5-350 Mpa) comparable to the typical naturally occurring range. It is also demonstrated that optimized structures have been produced that possesses ideal qualities for bone in-growth applications and that these structures can be applied in the production of orthopedic devices. (c) 2008 Wiley Periodicals, Inc.

G-LoSA for Prediction of Protein-Ligand Binding Sites and Structures.

PubMed

Lee, Hui Sun; Im, Wonpil

2017-01-01

Recent advances in high-throughput structure determination and computational protein structure prediction have significantly enriched the universe of protein structure. However, there is still a large gap between the number of available protein structures and that of proteins with annotated function in high accuracy. Computational structure-based protein function prediction has emerged to reduce this knowledge gap. The identification of a ligand binding site and its structure is critical to the determination of a protein's molecular function. We present a computational methodology for predicting small molecule ligand binding site and ligand structure using G-LoSA, our protein local structure alignment and similarity measurement tool. All the computational procedures described here can be easily implemented using G-LoSA Toolkit, a package of standalone software programs and preprocessed PDB structure libraries. G-LoSA and G-LoSA Toolkit are freely available to academic users at http://compbio.lehigh.edu/GLoSA . We also illustrate a case study to show the potential of our template-based approach harnessing G-LoSA for protein function prediction.

Self-assembly of nucleic acids, silk and hybrid materials thereof.

PubMed

Humenik, Martin; Scheibel, Thomas

2014-12-17

Top-down approaches based on etching techniques have almost reached their limits in terms of dimension. Therefore, novel assembly strategies and types of nanomaterials are required to allow technological advances. Self-assembly processes independent of external energy sources and unlimited in dimensional scaling have become a very promising approach. Here,we highlight recent developments in self-assembled DNA-polymer, silk-polymer and silk-DNA hybrids as promising materials with biotic and abiotic moieties for constructing complex hierarchical materials in ‘bottom-up’ approaches. DNA block copolymers assemble into nanostructures typically exposing a DNA corona which allows functionalization, labeling and higher levels of organization due to its specific addressable recognition properties. In contrast, self-assembly of natural silk proteins as well as their recombinant variants yields mechanically stable β-sheet rich nanostructures. The combination of silk with abiotic polymers gains hybrid materials with new functionalities. Together, the precision of DNA hybridization and robustness of silk fibrillar structures combine in novel conjugates enable processing of higher-order structures with nanoscale architecture and programmable functions.

Self-assembly of nucleic acids, silk and hybrid materials thereof

NASA Astrophysics Data System (ADS)

Humenik, Martin; Scheibel, Thomas

2014-12-01

Top-down approaches based on etching techniques have almost reached their limits in terms of dimension. Therefore, novel assembly strategies and types of nanomaterials are required to allow technological advances. Self-assembly processes independent of external energy sources and unlimited in dimensional scaling have become a very promising approach. Here, we highlight recent developments in self-assembled DNA-polymer, silk-polymer and silk-DNA hybrids as promising materials with biotic and abiotic moieties for constructing complex hierarchical materials in ‘bottom-up’ approaches. DNA block copolymers assemble into nanostructures typically exposing a DNA corona which allows functionalization, labeling and higher levels of organization due to its specific addressable recognition properties. In contrast, self-assembly of natural silk proteins as well as their recombinant variants yields mechanically stable β-sheet rich nanostructures. The combination of silk with abiotic polymers gains hybrid materials with new functionalities. Together, the precision of DNA hybridization and robustness of silk fibrillar structures combine in novel conjugates enable processing of higher-order structures with nanoscale architecture and programmable functions.

The Structural Basis of IKs Ion-Channel Activation: Mechanistic Insights from Molecular Simulations.

PubMed

Ramasubramanian, Smiruthi; Rudy, Yoram

2018-06-05

Relating ion channel (iCh) structural dynamics to physiological function remains a challenge. Current experimental and computational techniques have limited ability to explore this relationship in atomistic detail over physiological timescales. A framework associating iCh structure to function is necessary for elucidating normal and disease mechanisms. We formulated a modeling schema that overcomes the limitations of current methods through applications of artificial intelligence machine learning. Using this approach, we studied molecular processes that underlie human IKs voltage-mediated gating. IKs malfunction underlies many debilitating and life-threatening diseases. Molecular components of IKs that underlie its electrophysiological function include KCNQ1 (a pore-forming tetramer) and KCNE1 (an auxiliary subunit). Simulations, using the IKs structure-function model, reproduced experimentally recorded saturation of gating-charge displacement at positive membrane voltages, two-step voltage sensor (VS) movement shown by fluorescence, iCh gating statistics, and current-voltage relationship. Mechanistic insights include the following: 1) pore energy profile determines iCh subconductance; 2) the entire protein structure, not limited to the pore, contributes to pore energy and channel subconductance; 3) interactions with KCNE1 result in two distinct VS movements, causing gating-charge saturation at positive membrane voltages and current activation delay; and 4) flexible coupling between VS and pore permits pore opening at lower VS positions, resulting in sequential gating. The new modeling approach is applicable to atomistic scale studies of other proteins on timescales of physiological function. Copyright © 2018 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Self-assembled hierarchically structured organic-inorganic composite systems.

PubMed

Tritschler, Ulrich; Cölfen, Helmut

2016-05-13

Designing bio-inspired, multifunctional organic-inorganic composite materials is one of the most popular current research objectives. Due to the high complexity of biocomposite structures found in nacre and bone, for example, a one-pot scalable and versatile synthesis approach addressing structural key features of biominerals and affording bio-inspired, multifunctional organic-inorganic composites with advanced physical properties is highly challenging. This article reviews recent progress in synthesizing organic-inorganic composite materials via various self-assembly techniques and in this context highlights a recently developed bio-inspired synthesis concept for the fabrication of hierarchically structured, organic-inorganic composite materials. This one-step self-organization concept based on simultaneous liquid crystal formation of anisotropic inorganic nanoparticles and a functional liquid crystalline polymer turned out to be simple, fast, scalable and versatile, leading to various (multi-)functional composite materials, which exhibit hierarchical structuring over several length scales. Consequently, this synthesis approach is relevant for further progress and scientific breakthrough in the research field of bio-inspired and biomimetic materials.

Neural network approach for characterizing structural transformations by X-ray absorption fine structure

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

Timoshenko, Janis; Frenkel, Anatoly I.; Cintins, Arturs

The knowledge of coordination environment around various atomic species in many functional materials provides a key for explaining their properties and working mechanisms. Many structural motifs and their transformations are difficult to detect and quantify in the process of work (operando conditions), due to their local nature, small changes, low dimensionality of the material, and/or extreme conditions. Here we use artificial neural network approach to extract the information on the local structure and its in-situ changes directly from the X-ray absorption fine structure spectra. We illustrate this capability by extracting the radial distribution function (RDF) of atoms in ferritic andmore » austenitic phases of bulk iron across the temperature-induced transition. Integration of RDFs allows us to quantify the changes in the iron coordination and material density, and to observe the transition from body-centered to face-centered cubic arrangement of iron atoms. Furthermore, this method is attractive for a broad range of materials and experimental conditions« less

Neural network approach for characterizing structural transformations by X-ray absorption fine structure

DOE PAGES

Timoshenko, Janis; Frenkel, Anatoly I.; Cintins, Arturs; ...

2018-05-25

The knowledge of coordination environment around various atomic species in many functional materials provides a key for explaining their properties and working mechanisms. Many structural motifs and their transformations are difficult to detect and quantify in the process of work (operando conditions), due to their local nature, small changes, low dimensionality of the material, and/or extreme conditions. Here we use artificial neural network approach to extract the information on the local structure and its in-situ changes directly from the X-ray absorption fine structure spectra. We illustrate this capability by extracting the radial distribution function (RDF) of atoms in ferritic andmore » austenitic phases of bulk iron across the temperature-induced transition. Integration of RDFs allows us to quantify the changes in the iron coordination and material density, and to observe the transition from body-centered to face-centered cubic arrangement of iron atoms. Furthermore, this method is attractive for a broad range of materials and experimental conditions« less

Multilayer networks reveal the spatial structure of seed-dispersal interactions across the Great Rift landscapes.

PubMed

Timóteo, Sérgio; Correia, Marta; Rodríguez-Echeverría, Susana; Freitas, Helena; Heleno, Ruben

2018-01-10

Species interaction networks are traditionally explored as discrete entities with well-defined spatial borders, an oversimplification likely impairing their applicability. Using a multilayer network approach, explicitly accounting for inter-habitat connectivity, we investigate the spatial structure of seed-dispersal networks across the Gorongosa National Park, Mozambique. We show that the overall seed-dispersal network is composed by spatially explicit communities of dispersers spanning across habitats, functionally linking the landscape mosaic. Inter-habitat connectivity determines spatial structure, which cannot be accurately described with standard monolayer approaches either splitting or merging habitats. Multilayer modularity cannot be predicted by null models randomizing either interactions within each habitat or those linking habitats; however, as habitat connectivity increases, random processes become more important for overall structure. The importance of dispersers for the overall network structure is captured by multilayer versatility but not by standard metrics. Highly versatile species disperse many plant species across multiple habitats, being critical to landscape functional cohesion.

Neural Network Approach for Characterizing Structural Transformations by X-Ray Absorption Fine Structure Spectroscopy

NASA Astrophysics Data System (ADS)

Timoshenko, Janis; Anspoks, Andris; Cintins, Arturs; Kuzmin, Alexei; Purans, Juris; Frenkel, Anatoly I.

2018-06-01

The knowledge of the coordination environment around various atomic species in many functional materials provides a key for explaining their properties and working mechanisms. Many structural motifs and their transformations are difficult to detect and quantify in the process of work (operando conditions), due to their local nature, small changes, low dimensionality of the material, and/or extreme conditions. Here we use an artificial neural network approach to extract the information on the local structure and its in situ changes directly from the x-ray absorption fine structure spectra. We illustrate this capability by extracting the radial distribution function (RDF) of atoms in ferritic and austenitic phases of bulk iron across the temperature-induced transition. Integration of RDFs allows us to quantify the changes in the iron coordination and material density, and to observe the transition from a body-centered to a face-centered cubic arrangement of iron atoms. This method is attractive for a broad range of materials and experimental conditions.

Classification of protein quaternary structure by functional domain composition

PubMed Central

Yu, Xiaojing; Wang, Chuan; Li, Yixue

2006-01-01

Background The number and the arrangement of subunits that form a protein are referred to as quaternary structure. Quaternary structure is an important protein attribute that is closely related to its function. Proteins with quaternary structure are called oligomeric proteins. Oligomeric proteins are involved in various biological processes, such as metabolism, signal transduction, and chromosome replication. Thus, it is highly desirable to develop some computational methods to automatically classify the quaternary structure of proteins from their sequences. Results To explore this problem, we adopted an approach based on the functional domain composition of proteins. Every protein was represented by a vector calculated from the domains in the PFAM database. The nearest neighbor algorithm (NNA) was used for classifying the quaternary structure of proteins from this information. The jackknife cross-validation test was performed on the non-redundant protein dataset in which the sequence identity was less than 25%. The overall success rate obtained is 75.17%. Additionally, to demonstrate the effectiveness of this method, we predicted the proteins in an independent dataset and achieved an overall success rate of 84.11% Conclusion Compared with the amino acid composition method and Blast, the results indicate that the domain composition approach may be a more effective and promising high-throughput method in dealing with this complicated problem in bioinformatics. PMID:16584572

Recent developments in structural proteomics for protein structure determination.

PubMed

Liu, Hsuan-Liang; Hsu, Jyh-Ping

2005-05-01

The major challenges in structural proteomics include identifying all the proteins on the genome-wide scale, determining their structure-function relationships, and outlining the precise three-dimensional structures of the proteins. Protein structures are typically determined by experimental approaches such as X-ray crystallography or nuclear magnetic resonance (NMR) spectroscopy. However, the knowledge of three-dimensional space by these techniques is still limited. Thus, computational methods such as comparative and de novo approaches and molecular dynamic simulations are intensively used as alternative tools to predict the three-dimensional structures and dynamic behavior of proteins. This review summarizes recent developments in structural proteomics for protein structure determination; including instrumental methods such as X-ray crystallography and NMR spectroscopy, and computational methods such as comparative and de novo structure prediction and molecular dynamics simulations.

Systematic analysis of snake neurotoxins' functional classification using a data warehousing approach.

PubMed

Siew, Joyce Phui Yee; Khan, Asif M; Tan, Paul T J; Koh, Judice L Y; Seah, Seng Hong; Koo, Chuay Yeng; Chai, Siaw Ching; Armugam, Arunmozhiarasi; Brusic, Vladimir; Jeyaseelan, Kandiah

2004-12-12

Sequence annotations, functional and structural data on snake venom neurotoxins (svNTXs) are scattered across multiple databases and literature sources. Sequence annotations and structural data are available in the public molecular databases, while functional data are almost exclusively available in the published articles. There is a need for a specialized svNTXs database that contains NTX entries, which are organized, well annotated and classified in a systematic manner. We have systematically analyzed svNTXs and classified them using structure-function groups based on their structural, functional and phylogenetic properties. Using conserved motifs in each phylogenetic group, we built an intelligent module for the prediction of structural and functional properties of unknown NTXs. We also developed an annotation tool to aid the functional prediction of newly identified NTXs as an additional resource for the venom research community. We created a searchable online database of NTX proteins sequences (http://research.i2r.a-star.edu.sg/Templar/DB/snake_neurotoxin). This database can also be found under Swiss-Prot Toxin Annotation Project website (http://www.expasy.org/sprot/).

A statistical approach for inferring the 3D structure of the genome.

PubMed

Varoquaux, Nelle; Ay, Ferhat; Noble, William Stafford; Vert, Jean-Philippe

2014-06-15

Recent technological advances allow the measurement, in a single Hi-C experiment, of the frequencies of physical contacts among pairs of genomic loci at a genome-wide scale. The next challenge is to infer, from the resulting DNA-DNA contact maps, accurate 3D models of how chromosomes fold and fit into the nucleus. Many existing inference methods rely on multidimensional scaling (MDS), in which the pairwise distances of the inferred model are optimized to resemble pairwise distances derived directly from the contact counts. These approaches, however, often optimize a heuristic objective function and require strong assumptions about the biophysics of DNA to transform interaction frequencies to spatial distance, and thereby may lead to incorrect structure reconstruction. We propose a novel approach to infer a consensus 3D structure of a genome from Hi-C data. The method incorporates a statistical model of the contact counts, assuming that the counts between two loci follow a Poisson distribution whose intensity decreases with the physical distances between the loci. The method can automatically adjust the transfer function relating the spatial distance to the Poisson intensity and infer a genome structure that best explains the observed data. We compare two variants of our Poisson method, with or without optimization of the transfer function, to four different MDS-based algorithms-two metric MDS methods using different stress functions, a non-metric version of MDS and ChromSDE, a recently described, advanced MDS method-on a wide range of simulated datasets. We demonstrate that the Poisson models reconstruct better structures than all MDS-based methods, particularly at low coverage and high resolution, and we highlight the importance of optimizing the transfer function. On publicly available Hi-C data from mouse embryonic stem cells, we show that the Poisson methods lead to more reproducible structures than MDS-based methods when we use data generated using different restriction enzymes, and when we reconstruct structures at different resolutions. A Python implementation of the proposed method is available at http://cbio.ensmp.fr/pastis. © The Author 2014. Published by Oxford University Press.

PREvaIL, an integrative approach for inferring catalytic residues using sequence, structural, and network features in a machine-learning framework.

PubMed

Song, Jiangning; Li, Fuyi; Takemoto, Kazuhiro; Haffari, Gholamreza; Akutsu, Tatsuya; Chou, Kuo-Chen; Webb, Geoffrey I

2018-04-14

Determining the catalytic residues in an enzyme is critical to our understanding the relationship between protein sequence, structure, function, and enhancing our ability to design novel enzymes and their inhibitors. Although many enzymes have been sequenced, and their primary and tertiary structures determined, experimental methods for enzyme functional characterization lag behind. Because experimental methods used for identifying catalytic residues are resource- and labor-intensive, computational approaches have considerable value and are highly desirable for their ability to complement experimental studies in identifying catalytic residues and helping to bridge the sequence-structure-function gap. In this study, we describe a new computational method called PREvaIL for predicting enzyme catalytic residues. This method was developed by leveraging a comprehensive set of informative features extracted from multiple levels, including sequence, structure, and residue-contact network, in a random forest machine-learning framework. Extensive benchmarking experiments on eight different datasets based on 10-fold cross-validation and independent tests, as well as side-by-side performance comparisons with seven modern sequence- and structure-based methods, showed that PREvaIL achieved competitive predictive performance, with an area under the receiver operating characteristic curve and area under the precision-recall curve ranging from 0.896 to 0.973 and from 0.294 to 0.523, respectively. We demonstrated that this method was able to capture useful signals arising from different levels, leveraging such differential but useful types of features and allowing us to significantly improve the performance of catalytic residue prediction. We believe that this new method can be utilized as a valuable tool for both understanding the complex sequence-structure-function relationships of proteins and facilitating the characterization of novel enzymes lacking functional annotations. Copyright © 2018 Elsevier Ltd. All rights reserved.

Imaging of the internal structure of comet 67P/Churyumov-Gerasimenko from radiotomography CONSERT Data (Rosetta Mission) through a full 3D regularized inversion of the Helmholtz equations on functional spaces

NASA Astrophysics Data System (ADS)

Barriot, Jean-Pierre; Serafini, Jonathan; Sichoix, Lydie; Benna, Mehdi; Kofman, Wlodek; Herique, Alain

We investigate the inverse problem of imaging the internal structure of comet 67P/ Churyumov-Gerasimenko from radiotomography CONSERT data by using a coupled regularized inversion of the Helmholtz equations. A first set of Helmholtz equations, written w.r.t a basis of 3D Hankel functions describes the wave propagation outside the comet at large distances, a second set of Helmholtz equations, written w.r.t. a basis of 3D Zernike functions describes the wave propagation throughout the comet with avariable permittivity. Both sets are connected by continuity equations over a sphere that surrounds the comet. This approach, derived from GPS water vapor tomography of the atmosphere,will permit a full 3D inversion of the internal structure of the comet, contrary to traditional approaches that use a discretization of space at a fraction of the radiowave wavelength.

Improving the measurement of semantic similarity by combining gene ontology and co-functional network: a random walk based approach.

PubMed

Peng, Jiajie; Zhang, Xuanshuo; Hui, Weiwei; Lu, Junya; Li, Qianqian; Liu, Shuhui; Shang, Xuequn

2018-03-19

Gene Ontology (GO) is one of the most popular bioinformatics resources. In the past decade, Gene Ontology-based gene semantic similarity has been effectively used to model gene-to-gene interactions in multiple research areas. However, most existing semantic similarity approaches rely only on GO annotations and structure, or incorporate only local interactions in the co-functional network. This may lead to inaccurate GO-based similarity resulting from the incomplete GO topology structure and gene annotations. We present NETSIM2, a new network-based method that allows researchers to measure GO-based gene functional similarities by considering the global structure of the co-functional network with a random walk with restart (RWR)-based method, and by selecting the significant term pairs to decrease the noise information. Based on the EC number (Enzyme Commission)-based groups of yeast and Arabidopsis, evaluation test shows that NETSIM2 can enhance the accuracy of Gene Ontology-based gene functional similarity. Using NETSIM2 as an example, we found that the accuracy of semantic similarities can be significantly improved after effectively incorporating the global gene-to-gene interactions in the co-functional network, especially on the species that gene annotations in GO are far from complete.

Micromechanics and Structural Response of Functionally Graded, Particulate-Matrix, Fiber-Reinforced Composites

PubMed Central

Genin, Guy M.; Birman, Victor

2009-01-01

Reinforcement of fibrous composites by stiff particles embedded in the matrix offers the potential for simple, economical functional grading, enhanced response to mechanical loads, and improved functioning at high temperatures. Here, we consider laminated plates made of such a material, with spherical reinforcement tailored by layer. The moduli for this material lie within relatively narrow bounds. Two separate moduli estimates are considered: a “two-step” approach in which fibers are embedded in a homogenized particulate matrix, and the Kanaun-Jeulin (2001) approach, which we re-derive in a simple way using the Benveniste (1988) method. Optimal tailoring of a plate is explored, and functional grading is shown to improve the performance of the structures considered. In the example of a square, simply supported, cross-ply laminated panel subjected to uniform transverse pressure, a modest functional grading offers significant improvement in performance. A second example suggests superior blast resistance of the panel achieved at the expense of only a small increase in weight. PMID:23874001

Accurate evaluation of exchange fields in finite element micromagnetic solvers

NASA Astrophysics Data System (ADS)

Chang, R.; Escobar, M. A.; Li, S.; Lubarda, M. V.; Lomakin, V.

2012-04-01

Quadratic basis functions (QBFs) are implemented for solving the Landau-Lifshitz-Gilbert equation via the finite element method. This involves the introduction of a set of special testing functions compatible with the QBFs for evaluating the Laplacian operator. The results by using QBFs are significantly more accurate than those via linear basis functions. QBF approach leads to significantly more accurate results than conventionally used approaches based on linear basis functions. Importantly QBFs allow reducing the error of computing the exchange field by increasing the mesh density for structured and unstructured meshes. Numerical examples demonstrate the feasibility of the method.

A Comprehensive Planning Model

ERIC Educational Resources Information Center

Temkin, Sanford

1972-01-01

Combines elements of the problem solving approach inherent in methods of applied economics and operations research and the structural-functional analysis common in social science modeling to develop an approach for economic planning and resource allocation for schools and other public sector organizations. (Author)

Electronic structure of LiCoO2 thin films: A combined photoemission spectroscopy and density functional theory study

NASA Astrophysics Data System (ADS)

Ensling, David; Thissen, Andreas; Laubach, Stefan; Schmidt, Peter C.; Jaegermann, Wolfram

2010-11-01

The electronic properties of LiCoO2 have been studied by theoretical band-structure calculations (using density functional theory) and experimental methods (photoemission). Synchrotron-induced photoelectron spectroscopy, resonant photoemission spectroscopy (ResPES), and soft x-ray absorption (XAS) have been applied to investigate the electronic structure of both occupied and unoccupied states. High-quality PES spectra were obtained from stoichiometric and highly crystalline LiCoO2 thin films deposited “in situ” by rf magnetron sputtering. An experimental approach of separating oxygen- and cobalt-derived (final) states by ResPES in the valence-band region is presented. The procedure takes advantage of an antiresonant behavior of cobalt-derived states at the 3p-3d excitation threshold. Information about the unoccupied density of states has been obtained by OK XAS. The structure of the CoL absorption edge is compared to semiempirical charge-transfer multiplet calculations. The experimental results are furthermore compared with band-structure calculations considering three different exchange potentials [generalized gradient approximation (GGA), using a nonlocal Hubbard U (GGA+U) and using a hybrid functional (Becke, three-parameter, Lee-Yang-Parr [B3LYP])]. For these different approaches total density of states and partial valence-band density of states have been investigated. The best qualitative agreement with experimental results has been obtained by using a GGA+U functional with U=2.9eV .

Investigating the Structural Impacts of I64T and P311S Mutations in APE1-DNA Complex: A Molecular Dynamics Approach

PubMed Central

Doss, C. George Priya; NagaSundaram, N.

2012-01-01

Background Elucidating the molecular dynamic behavior of Protein-DNA complex upon mutation is crucial in current genomics. Molecular dynamics approach reveals the changes on incorporation of variants that dictate the structure and function of Protein-DNA complexes. Deleterious mutations in APE1 protein modify the physicochemical property of amino acids that affect the protein stability and dynamic behavior. Further, these mutations disrupt the binding sites and prohibit the protein to form complexes with its interacting DNA. Principal Findings In this study, we developed a rapid and cost-effective method to analyze variants in APE1 gene that are associated with disease susceptibility and evaluated their impacts on APE1-DNA complex dynamic behavior. Initially, two different in silico approaches were used to identify deleterious variants in APE1 gene. Deleterious scores that overlap in these approaches were taken in concern and based on it, two nsSNPs with IDs rs61730854 (I64T) and rs1803120 (P311S) were taken further for structural analysis. Significance Different parameters such as RMSD, RMSF, salt bridge, H-bonds and SASA applied in Molecular dynamic study reveals that predicted deleterious variants I64T and P311S alters the structure as well as affect the stability of APE1-DNA interacting functions. This study addresses such new methods for validating functional polymorphisms of human APE1 which is critically involved in causing deficit in repair capacity, which in turn leads to genetic instability and carcinogenesis. PMID:22384055

A validated approach for modeling collapse of steel structures

NASA Astrophysics Data System (ADS)

Saykin, Vitaliy Victorovich

A civil engineering structure is faced with many hazardous conditions such as blasts, earthquakes, hurricanes, tornadoes, floods, and fires during its lifetime. Even though structures are designed for credible events that can happen during a lifetime of the structure, extreme events do happen and cause catastrophic failures. Understanding the causes and effects of structural collapse is now at the core of critical areas of national need. One factor that makes studying structural collapse difficult is the lack of full-scale structural collapse experimental test results against which researchers could validate their proposed collapse modeling approaches. The goal of this work is the creation of an element deletion strategy based on fracture models for use in validated prediction of collapse of steel structures. The current work reviews the state-of-the-art of finite element deletion strategies for use in collapse modeling of structures. It is shown that current approaches to element deletion in collapse modeling do not take into account stress triaxiality in vulnerable areas of the structure, which is important for proper fracture and element deletion modeling. The report then reviews triaxiality and its role in fracture prediction. It is shown that fracture in ductile materials is a function of triaxiality. It is also shown that, depending on the triaxiality range, different fracture mechanisms are active and should be accounted for. An approach using semi-empirical fracture models as a function of triaxiality are employed. The models to determine fracture initiation, softening and subsequent finite element deletion are outlined. This procedure allows for stress-displacement softening at an integration point of a finite element in order to subsequently remove the element. This approach avoids abrupt changes in the stress that would create dynamic instabilities, thus making the results more reliable and accurate. The calibration and validation of these models are shown. The calibration is performed using a particle swarm optimization algorithm to establish accurate parameters when calibrated to circumferentially notched tensile coupons. It is shown that consistent, accurate predictions are attained using the chosen models. The variation of triaxiality in steel material during plastic hardening and softening is reported. The range of triaxiality in steel structures undergoing collapse is investigated in detail and the accuracy of the chosen finite element deletion approaches is discussed. This is done through validation of different structural components and structural frames undergoing severe fracture and collapse.

Exploration of Novel Chemical Space: Synthesis and in vitro Evaluation of N-Functionalized Tertiary Sulfonimidamides.

PubMed

Izzo, Flavia; Schäfer, Martina; Lienau, Philip; Ganzer, Ursula; Stockman, Robert; Lücking, Ulrich

2018-05-04

An unprecedented set of structurally diverse sulfonimidamides (47 compounds) has been prepared by various N-functionalization reactions of tertiary =NH sulfonimidamide 2 aa. These N-functionalization reactions of model compound 2 aa include arylation, alkylation, trifluoromethylation, cyanation, sulfonylation, alkoxycarbonylation (carbamate formation) and aminocarbonylation (urea formation). Small molecule X-ray analyses of selected N-functionalized products are reported. To gain further insight into the properties of sulfonimidamides relevant to medicinal chemistry, a variety of structurally diverse reaction products were tested in selected in vitro assays. The described N-functionalization reactions provide a short and efficient approach to structurally diverse sulfonimidamides which have been the subject of recent, growing interest in the life sciences. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Large-Deformation Displacement Transfer Functions for Shape Predictions of Highly Flexible Slender Aerospace Structures

NASA Technical Reports Server (NTRS)

Ko, William L.; Fleischer, Van Tran

2013-01-01

Large deformation displacement transfer functions were formulated for deformed shape predictions of highly flexible slender structures like aircraft wings. In the formulation, the embedded beam (depth wise cross section of structure along the surface strain sensing line) was first evenly discretized into multiple small domains, with surface strain sensing stations located at the domain junctures. Thus, the surface strain (bending strains) variation within each domain could be expressed with linear of nonlinear function. Such piecewise approach enabled piecewise integrations of the embedded beam curvature equations [classical (Eulerian), physical (Lagrangian), and shifted curvature equations] to yield closed form slope and deflection equations in recursive forms.

Building Quakes: Detection of Weld Fractures in Buildings using High-Frequency Seismic Techniques

NASA Astrophysics Data System (ADS)

Heckman, V.; Kohler, M. D.; Heaton, T. H.

2009-12-01

Catastrophic fracture of welded beam-column connections in buildings was observed in the Northridge and Kobe earthquakes. Despite the structural importance of such connections, it can be difficult to locate damage in structural members underneath superficial building features. We have developed a novel technique to locate fracturing welds in buildings in real time using high-frequency information from seismograms. Numerical and experimental methods were used to investigate an approach for detecting the brittle fracture of welds of beam-column connections in instrumented steel moment-frame buildings through the use of time-reversed Green’s functions and wave propagation reciprocity. The approach makes use of a prerecorded catalogue of Green’s functions for an instrumented building to detect high-frequency failure events in the building during a later earthquake by screening continuous data for the presence of one or more of the events. This was explored experimentally by comparing structural responses of a small-scale laboratory structure under a variety of loading conditions. Experimentation was conducted on a polyvinyl chloride frame model structure with data recorded at a sample rate of 2000 Hz using piezoelectric accelerometers and a 24-bit digitizer. Green’s functions were obtained by applying impulsive force loads at various locations along the structure with a rubber-tipped force transducer hammer. We performed a blind test using cross-correlation techniques to determine if it was possible to use the catalogue of Green’s functions to pinpoint the absolute times and locations of subsequent, induced failure events in the structure. A finite-element method was used to simulate the response of the model structure to various source mechanisms in order to determine the types of elastic waves that were produced as well as to obtain a general understanding of the structural response to localized loading and fracture.

Integrative Structure Determination of Protein Assemblies by Satisfaction of Spatial Restraints

NASA Astrophysics Data System (ADS)

Alber, Frank; Chait, Brian T.; Rout, Michael P.; Sali, Andrej

To understand the cell, we need to determine the structures of macromolecular assemblies, many of which consist of tens to hundreds of components. A great variety of experimental data can be used to characterize the assemblies at several levels of resolution, from atomic structures to component configurations. To maximize completeness, resolution, accuracy, precision and efficiency of the structure determination, a computational approach is needed that can use spatial information from a variety of experimental methods. We propose such an approach, defined by its three main components: a hierarchical representation of the assembly, a scoring function consisting of spatial restraints derived from experimental data, and an optimization method that generates structures consistent with the data. We illustrate the approach by determining the configuration of the 456 proteins in the nuclear pore complex from Baker's yeast.

Time Scale Hierarchies in the Functional Organization of Complex Behaviors

PubMed Central

Perdikis, Dionysios; Huys, Raoul; Jirsa, Viktor K.

2011-01-01

Traditional approaches to cognitive modelling generally portray cognitive events in terms of ‘discrete’ states (point attractor dynamics) rather than in terms of processes, thereby neglecting the time structure of cognition. In contrast, more recent approaches explicitly address this temporal dimension, but typically provide no entry points into cognitive categorization of events and experiences. With the aim to incorporate both these aspects, we propose a framework for functional architectures. Our approach is grounded in the notion that arbitrary complex (human) behaviour is decomposable into functional modes (elementary units), which we conceptualize as low-dimensional dynamical objects (structured flows on manifolds). The ensemble of modes at an agent’s disposal constitutes his/her functional repertoire. The modes may be subjected to additional dynamics (termed operational signals), in particular, instantaneous inputs, and a mechanism that sequentially selects a mode so that it temporarily dominates the functional dynamics. The inputs and selection mechanisms act on faster and slower time scales then that inherent to the modes, respectively. The dynamics across the three time scales are coupled via feedback, rendering the entire architecture autonomous. We illustrate the functional architecture in the context of serial behaviour, namely cursive handwriting. Subsequently, we investigate the possibility of recovering the contributions of functional modes and operational signals from the output, which appears to be possible only when examining the output phase flow (i.e., not from trajectories in phase space or time). PMID:21980278

Functionally Graded Designer Viscoelastic Materials Tailored to Perform Prescribed Tasks with Probabilistic Failures and Lifetimes

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

Hilton, Harry H.

Protocols are developed for formulating optimal viscoelastic designer functionally graded materials tailored to best respond to prescribed loading and boundary conditions. In essence, an inverse approach is adopted where material properties instead of structures per se are designed and then distributed throughout structural elements. The final measure of viscoelastic material efficacy is expressed in terms of failure probabilities vs. survival time000.

Beyond sex differences: new approaches for thinking about variation in brain structure and function.

PubMed

Joel, Daphna; Fausto-Sterling, Anne

2016-02-19

In the study of variation in brain structure and function that might relate to sex and gender, language matters because it frames our research questions and methods. In this article, we offer an approach to thinking about variation in brain structure and function that pulls us outside the sex differences formulation. We argue that the existence of differences between the brains of males and females does not unravel the relations between sex and the brain nor is it sufficient to characterize a population of brains. Such characterization is necessary for studying sex effects on the brain as well as for studying brain structure and function in general. Animal studies show that sex interacts with environmental, developmental and genetic factors to affect the brain. Studies of humans further suggest that human brains are better described as belonging to a single heterogeneous population rather than two distinct populations. We discuss the implications of these observations for studies of brain and behaviour in humans and in laboratory animals. We believe that studying sex effects in context and developing or adopting analytical methods that take into account the heterogeneity of the brain are crucial for the advancement of human health and well-being. © 2016 The Author(s).

Enhanced disease characterization through multi network functional normalization in fMRI.

PubMed

Çetin, Mustafa S; Khullar, Siddharth; Damaraju, Eswar; Michael, Andrew M; Baum, Stefi A; Calhoun, Vince D

2015-01-01

Conventionally, structural topology is used for spatial normalization during the pre-processing of fMRI. The co-existence of multiple intrinsic networks which can be detected in the resting brain are well-studied. Also, these networks exhibit temporal and spatial modulation during cognitive task vs. rest which shows the existence of common spatial excitation patterns between these identified networks. Previous work (Khullar et al., 2011) has shown that structural and functional data may not have direct one-to-one correspondence and functional activation patterns in a well-defined structural region can vary across subjects even for a well-defined functional task. The results of this study and the existence of the neural activity patterns in multiple networks motivates us to investigate multiple resting-state networks as a single fusion template for functional normalization for multi groups of subjects. We extend the previous approach (Khullar et al., 2011) by co-registering multi group of subjects (healthy control and schizophrenia patients) and by utilizing multiple resting-state networks (instead of just one) as a single fusion template for functional normalization. In this paper we describe the initial steps toward using multiple resting-state networks as a single fusion template for functional normalization. A simple wavelet-based image fusion approach is presented in order to evaluate the feasibility of combining multiple functional networks. Our results showed improvements in both the significance of group statistics (healthy control and schizophrenia patients) and the spatial extent of activation when a multiple resting-state network applied as a single fusion template for functional normalization after the conventional structural normalization. Also, our results provided evidence that the improvement in significance of group statistics lead to better accuracy results for classification of healthy controls and schizophrenia patients.

Structural frequency functions for an impulsive, distributed forcing function

NASA Technical Reports Server (NTRS)

Bateman, Vesta I.

1987-01-01

The response of a penetrator structure to a spatially distributed mechanical impulse with a magnitude approaching field test force levels (1-2 Mlb) were measured. The frequency response function calculated from the response to this unique forcing function is compared to frequency response functions calculated from response to point forces of about 2000 pounds. The results show that the strain gages installed on the penetrator case respond similiarly to a point, axial force and to a spatially distributed, axial force. This result suggests that the distributed axial force generated in a penetration event may be reconstructed as a point axial force when the penetrator behaves in linear manner.

Sampling Enrichment toward Target Structures Using Hybrid Molecular Dynamics-Monte Carlo Simulations

PubMed Central

Yang, Kecheng; Różycki, Bartosz; Cui, Fengchao; Shi, Ce; Chen, Wenduo; Li, Yunqi

2016-01-01

Sampling enrichment toward a target state, an analogue of the improvement of sampling efficiency (SE), is critical in both the refinement of protein structures and the generation of near-native structure ensembles for the exploration of structure-function relationships. We developed a hybrid molecular dynamics (MD)-Monte Carlo (MC) approach to enrich the sampling toward the target structures. In this approach, the higher SE is achieved by perturbing the conventional MD simulations with a MC structure-acceptance judgment, which is based on the coincidence degree of small angle x-ray scattering (SAXS) intensity profiles between the simulation structures and the target structure. We found that the hybrid simulations could significantly improve SE by making the top-ranked models much closer to the target structures both in the secondary and tertiary structures. Specifically, for the 20 mono-residue peptides, when the initial structures had the root-mean-squared deviation (RMSD) from the target structure smaller than 7 Å, the hybrid MD-MC simulations afforded, on average, 0.83 Å and 1.73 Å in RMSD closer to the target than the parallel MD simulations at 310K and 370K, respectively. Meanwhile, the average SE values are also increased by 13.2% and 15.7%. The enrichment of sampling becomes more significant when the target states are gradually detectable in the MD-MC simulations in comparison with the parallel MD simulations, and provide >200% improvement in SE. We also performed a test of the hybrid MD-MC approach in the real protein system, the results showed that the SE for 3 out of 5 real proteins are improved. Overall, this work presents an efficient way of utilizing solution SAXS to improve protein structure prediction and refinement, as well as the generation of near native structures for function annotation. PMID:27227775

Sampling Enrichment toward Target Structures Using Hybrid Molecular Dynamics-Monte Carlo Simulations.

PubMed

Yang, Kecheng; Różycki, Bartosz; Cui, Fengchao; Shi, Ce; Chen, Wenduo; Li, Yunqi

2016-01-01

Sampling enrichment toward a target state, an analogue of the improvement of sampling efficiency (SE), is critical in both the refinement of protein structures and the generation of near-native structure ensembles for the exploration of structure-function relationships. We developed a hybrid molecular dynamics (MD)-Monte Carlo (MC) approach to enrich the sampling toward the target structures. In this approach, the higher SE is achieved by perturbing the conventional MD simulations with a MC structure-acceptance judgment, which is based on the coincidence degree of small angle x-ray scattering (SAXS) intensity profiles between the simulation structures and the target structure. We found that the hybrid simulations could significantly improve SE by making the top-ranked models much closer to the target structures both in the secondary and tertiary structures. Specifically, for the 20 mono-residue peptides, when the initial structures had the root-mean-squared deviation (RMSD) from the target structure smaller than 7 Å, the hybrid MD-MC simulations afforded, on average, 0.83 Å and 1.73 Å in RMSD closer to the target than the parallel MD simulations at 310K and 370K, respectively. Meanwhile, the average SE values are also increased by 13.2% and 15.7%. The enrichment of sampling becomes more significant when the target states are gradually detectable in the MD-MC simulations in comparison with the parallel MD simulations, and provide >200% improvement in SE. We also performed a test of the hybrid MD-MC approach in the real protein system, the results showed that the SE for 3 out of 5 real proteins are improved. Overall, this work presents an efficient way of utilizing solution SAXS to improve protein structure prediction and refinement, as well as the generation of near native structures for function annotation.

Applications of large-scale density functional theory in biology

NASA Astrophysics Data System (ADS)

Cole, Daniel J.; Hine, Nicholas D. M.

2016-10-01

Density functional theory (DFT) has become a routine tool for the computation of electronic structure in the physics, materials and chemistry fields. Yet the application of traditional DFT to problems in the biological sciences is hindered, to a large extent, by the unfavourable scaling of the computational effort with system size. Here, we review some of the major software and functionality advances that enable insightful electronic structure calculations to be performed on systems comprising many thousands of atoms. We describe some of the early applications of large-scale DFT to the computation of the electronic properties and structure of biomolecules, as well as to paradigmatic problems in enzymology, metalloproteins, photosynthesis and computer-aided drug design. With this review, we hope to demonstrate that first principles modelling of biological structure-function relationships are approaching a reality.

Maximum Likelihood Analysis of Nonlinear Structural Equation Models with Dichotomous Variables

ERIC Educational Resources Information Center

Song, Xin-Yuan; Lee, Sik-Yum

2005-01-01

In this article, a maximum likelihood approach is developed to analyze structural equation models with dichotomous variables that are common in behavioral, psychological and social research. To assess nonlinear causal effects among the latent variables, the structural equation in the model is defined by a nonlinear function. The basic idea of the…

Assessing ecosystem restoration alternatives in eastern deciduous forests: the view from belowground

Treesearch

Ralph E.J. Boerner; Adam T. Coates; Daniel A. Yaussy; Thomas A. Waldrop

2008-01-01

Both structural and functional approaches to restoration of eastern deciduous forests are becoming more common as recognition of the altered state of these ecosystems grows. In our study, structural restoration involves mechanically modifying the woody plant assemblage to a species composition, density, and community structure specified by the restoration goals....

Validation of Clay Modeling as a Learning Tool for the Periventricular Structures of the Human Brain

ERIC Educational Resources Information Center

Akle, Veronica; Peña-Silva, Ricardo A.; Valencia, Diego M.; Rincón-Perez, Carlos W.

2018-01-01

Visualizing anatomical structures and functional processes in three dimensions (3D) are important skills for medical students. However, contemplating 3D structures mentally and interpreting biomedical images can be challenging. This study examines the impact of a new pedagogical approach to teaching neuroanatomy, specifically how building a…

On the sound insulation of acoustic metasurface using a sub-structuring approach

NASA Astrophysics Data System (ADS)

Yu, Xiang; Lu, Zhenbo; Cheng, Li; Cui, Fangsen

2017-08-01

The feasibility of using an acoustic metasurface (AMS) with acoustic stop-band property to realize sound insulation with ventilation function is investigated. An efficient numerical approach is proposed to evaluate its sound insulation performance. The AMS is excited by a reverberant sound source and the standardized sound reduction index (SRI) is numerically investigated. To facilitate the modeling, the coupling between the AMS and the adjacent acoustic fields is formulated using a sub-structuring approach. A modal based formulation is applied to both the source and receiving room, enabling an efficient calculation in the frequency range from 125 Hz to 2000 Hz. The sound pressures and the velocities at the interface are matched by using a transfer function relation based on ;patches;. For illustration purposes, numerical examples are investigated using the proposed approach. The unit cell constituting the AMS is constructed in the shape of a thin acoustic chamber with tailored inner structures, whose stop-band property is numerically analyzed and experimentally demonstrated. The AMS is shown to provide effective sound insulation of over 30 dB in the stop-band frequencies from 600 to 1600 Hz. It is also shown that the proposed approach has the potential to be applied to a broad range of AMS studies and optimization problems.

Locating damage using integrated global-local approach with wireless sensing system and single-chip impedance measurement device.

PubMed

Lin, Tzu-Hsuan; Lu, Yung-Chi; Hung, Shih-Lin

2014-01-01

This study developed an integrated global-local approach for locating damage on building structures. A damage detection approach with a novel embedded frequency response function damage index (NEFDI) was proposed and embedded in the Imote2.NET-based wireless structural health monitoring (SHM) system to locate global damage. Local damage is then identified using an electromechanical impedance- (EMI-) based damage detection method. The electromechanical impedance was measured using a single-chip impedance measurement device which has the advantages of small size, low cost, and portability. The feasibility of the proposed damage detection scheme was studied with reference to a numerical example of a six-storey shear plane frame structure and a small-scale experimental steel frame. Numerical and experimental analysis using the integrated global-local SHM approach reveals that, after NEFDI indicates the approximate location of a damaged area, the EMI-based damage detection approach can then identify the detailed damage location in the structure of the building.

UET: a database of evolutionarily-predicted functional determinants of protein sequences that cluster as functional sites in protein structures.

PubMed

Lua, Rhonald C; Wilson, Stephen J; Konecki, Daniel M; Wilkins, Angela D; Venner, Eric; Morgan, Daniel H; Lichtarge, Olivier

2016-01-04

The structure and function of proteins underlie most aspects of biology and their mutational perturbations often cause disease. To identify the molecular determinants of function as well as targets for drugs, it is central to characterize the important residues and how they cluster to form functional sites. The Evolutionary Trace (ET) achieves this by ranking the functional and structural importance of the protein sequence positions. ET uses evolutionary distances to estimate functional distances and correlates genotype variations with those in the fitness phenotype. Thus, ET ranks are worse for sequence positions that vary among evolutionarily closer homologs but better for positions that vary mostly among distant homologs. This approach identifies functional determinants, predicts function, guides the mutational redesign of functional and allosteric specificity, and interprets the action of coding sequence variations in proteins, people and populations. Now, the UET database offers pre-computed ET analyses for the protein structure databank, and on-the-fly analysis of any protein sequence. A web interface retrieves ET rankings of sequence positions and maps results to a structure to identify functionally important regions. This UET database integrates several ways of viewing the results on the protein sequence or structure and can be found at http://mammoth.bcm.tmc.edu/uet/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Function-specific and Enhanced Brain Structural Connectivity Mapping via Joint Modeling of Diffusion and Functional MRI.

PubMed

Chu, Shu-Hsien; Parhi, Keshab K; Lenglet, Christophe

2018-03-16

A joint structural-functional brain network model is presented, which enables the discovery of function-specific brain circuits, and recovers structural connections that are under-estimated by diffusion MRI (dMRI). Incorporating information from functional MRI (fMRI) into diffusion MRI to estimate brain circuits is a challenging task. Usually, seed regions for tractography are selected from fMRI activation maps to extract the white matter pathways of interest. The proposed method jointly analyzes whole brain dMRI and fMRI data, allowing the estimation of complete function-specific structural networks instead of interactively investigating the connectivity of individual cortical/sub-cortical areas. Additionally, tractography techniques are prone to limitations, which can result in erroneous pathways. The proposed framework explicitly models the interactions between structural and functional connectivity measures thereby improving anatomical circuit estimation. Results on Human Connectome Project (HCP) data demonstrate the benefits of the approach by successfully identifying function-specific anatomical circuits, such as the language and resting-state networks. In contrast to correlation-based or independent component analysis (ICA) functional connectivity mapping, detailed anatomical connectivity patterns are revealed for each functional module. Results on a phantom (Fibercup) also indicate improvements in structural connectivity mapping by rejecting false-positive connections with insufficient support from fMRI, and enhancing under-estimated connectivity with strong functional correlation.

Experimental Approaches for Solution X-Ray Scattering and Fiber Diffraction

PubMed Central

Irving, T. C.

2008-01-01

X-ray scattering and diffraction from non-crystalline systems have gained renewed interest in recent years, as focus shifts from the structural chemistry information gained by high-resolution studies to the context of structural physiology at larger length scales. Such techniques permit the study of isolated macromolecules as well as highly organized macromolecular assemblies as a whole under near-physiological conditions. Time-resolved approaches, made possible by advanced synchrotron instrumentation, add a critical dimension to many of these investigations. This article reviews experimental approaches in non-crystalline x-ray scattering and diffraction that may be used to illuminate important scientific questions such as protein/nucleic acid folding and structure-function relationships in large macromolecular assemblies. PMID:18801437

Determination of functional collective motions in a protein at atomic resolution using coherent neutron scattering

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

Hong, Liang; Jain, Nitin; Cheng, Xiaolin

Protein function often depends on global, collective internal motions. However, the simultaneous quantitative experimental determination of the forms, amplitudes, and time scales of these motions has remained elusive. We demonstrate that a complete description of these large-scale dynamic modes can be obtained using coherent neutron-scattering experiments on perdeuterated samples. With this approach, a microscopic relationship between the structure, dynamics, and function in a protein, cytochrome P450cam, is established. The approach developed here should be of general applicability to protein systems.

Determination of functional collective motions in a protein at atomic resolution using coherent neutron scattering

DOE PAGES

Hong, Liang; Jain, Nitin; Cheng, Xiaolin; ...

2016-10-14

Protein function often depends on global, collective internal motions. However, the simultaneous quantitative experimental determination of the forms, amplitudes, and time scales of these motions has remained elusive. We demonstrate that a complete description of these large-scale dynamic modes can be obtained using coherent neutron-scattering experiments on perdeuterated samples. With this approach, a microscopic relationship between the structure, dynamics, and function in a protein, cytochrome P450cam, is established. The approach developed here should be of general applicability to protein systems.

Combination of complex momentum representation and Green's function methods in relativistic mean-field theory

NASA Astrophysics Data System (ADS)

Shi, Min; Niu, Zhong-Ming; Liang, Haozhao

2018-06-01

We have combined the complex momentum representation method with the Green's function method in the relativistic mean-field framework to establish the RMF-CMR-GF approach. This new approach is applied to study the halo structure of 74Ca. All the continuum level density of concerned resonant states are calculated accurately without introducing any unphysical parameters, and they are independent of the choice of integral contour. The important single-particle wave functions and densities for the halo phenomenon in 74Ca are discussed in detail.

Real-time seismic monitoring and functionality assessment of a building

USGS Publications Warehouse

Celebi, M.; ,

2005-01-01

This paper presents recent developments and approaches (using GPS technology and real-time double-integration) to obtain displacements and, in turn, drift ratios, in real-time or near real-time to meet the needs of the engineering and user community in seismic monitoring and assessing the functionality and damage condition of structures. Drift ratios computed in near real-time allow technical assessment of the damage condition of a building. Relevant parameters, such as the type of connections and story structural characteristics (including geometry) are used in computing drifts corresponding to several pre-selected threshold stages of damage. Thus, drift ratios determined from real-time monitoring can be compared to pre-computed threshold drift ratios. The approaches described herein can be used for performance evaluation of structures and can be considered as building health-monitoring applications.

A practical approach to assessing structure, function, and value of street tree populations in small communities

Treesearch

S.E. Maco; E.G. McPherson

2003-01-01

This study demonstrates an approach to quantify the structure, benefits, and costs of street tree populations in resource-limited communities without tree inventories. Using the city of Davis, California, U.S., as a model, existing data on the benefits and costs of municipal trees were applied to the results of a sample inventory of the city’s public and private street...

Hidden relationships between metalloproteins unveiled by structural comparison of their metal sites

NASA Astrophysics Data System (ADS)

Valasatava, Yana; Andreini, Claudia; Rosato, Antonio

2015-03-01

Metalloproteins account for a substantial fraction of all proteins. They incorporate metal atoms, which are required for their structure and/or function. Here we describe a new computational protocol to systematically compare and classify metal-binding sites on the basis of their structural similarity. These sites are extracted from the MetalPDB database of minimal functional sites (MFSs) in metal-binding biological macromolecules. Structural similarity is measured by the scoring function of the available MetalS2 program. Hierarchical clustering was used to organize MFSs into clusters, for each of which a representative MFS was identified. The comparison of all representative MFSs provided a thorough structure-based classification of the sites analyzed. As examples, the application of the proposed computational protocol to all heme-binding proteins and zinc-binding proteins of known structure highlighted the existence of structural subtypes, validated known evolutionary links and shed new light on the occurrence of similar sites in systems at different evolutionary distances. The present approach thus makes available an innovative viewpoint on metalloproteins, where the functionally crucial metal sites effectively lead the discovery of structural and functional relationships in a largely protein-independent manner.

A new look at the simultaneous analysis and design of structures

NASA Technical Reports Server (NTRS)

Striz, Alfred G.

1994-01-01

The minimum weight optimization of structural systems, subject to strength and displacement constraints as well as size side constraints, was investigated by the Simultaneous ANalysis and Design (SAND) approach. As an optimizer, the code NPSOL was used which is based on a sequential quadratic programming (SQP) algorithm. The structures were modeled by the finite element method. The finite element related input to NPSOL was automatically generated from the input decks of such standard FEM/optimization codes as NASTRAN or ASTROS, with the stiffness matrices, at present, extracted from the FEM code ANALYZE. In order to avoid ill-conditioned matrices that can be encountered when the global stiffness equations are used as additional nonlinear equality constraints in the SAND approach (with the displacements as additional variables), the matrix displacement method was applied. In this approach, the element stiffness equations are used as constraints instead of the global stiffness equations, in conjunction with the nodal force equilibrium equations. This approach adds the element forces as variables to the system. Since, for complex structures and the associated large and very sparce matrices, the execution times of the optimization code became excessive due to the large number of required constraint gradient evaluations, the Kreisselmeier-Steinhauser function approach was used to decrease the computational effort by reducing the nonlinear equality constraint system to essentially a single combined constraint equation. As the linear equality and inequality constraints require much less computational effort to evaluate, they were kept in their previous form to limit the complexity of the KS function evaluation. To date, the standard three-bar, ten-bar, and 72-bar trusses have been tested. For the standard SAND approach, correct results were obtained for all three trusses although convergence became slower for the 72-bar truss. When the matrix displacement method was used, correct results were still obtained, but the execution times became excessive due to the large number of constraint gradient evaluations required. Using the KS function, the computational effort dropped, but the optimization seemed to become less robust. The investigation of this phenomenon is continuing. As an alternate approach, the code MINOS for the optimization of sparse matrices can be applied to the problem in lieu of the Kreisselmeier-Steinhauser function. This investigation is underway.

Spectral functions with the density matrix renormalization group: Krylov-space approach for correction vectors

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

None, None

Frequency-dependent correlations, such as the spectral function and the dynamical structure factor, help illustrate condensed matter experiments. Within the density matrix renormalization group (DMRG) framework, an accurate method for calculating spectral functions directly in frequency is the correction-vector method. The correction vector can be computed by solving a linear equation or by minimizing a functional. Our paper proposes an alternative to calculate the correction vector: to use the Krylov-space approach. This paper also studies the accuracy and performance of the Krylov-space approach, when applied to the Heisenberg, the t-J, and the Hubbard models. The cases we studied indicate that themore » Krylov-space approach can be more accurate and efficient than the conjugate gradient, and that the error of the former integrates best when a Krylov-space decomposition is also used for ground state DMRG.« less

Spectral functions with the density matrix renormalization group: Krylov-space approach for correction vectors

DOE PAGES

None, None

2016-11-21

Frequency-dependent correlations, such as the spectral function and the dynamical structure factor, help illustrate condensed matter experiments. Within the density matrix renormalization group (DMRG) framework, an accurate method for calculating spectral functions directly in frequency is the correction-vector method. The correction vector can be computed by solving a linear equation or by minimizing a functional. Our paper proposes an alternative to calculate the correction vector: to use the Krylov-space approach. This paper also studies the accuracy and performance of the Krylov-space approach, when applied to the Heisenberg, the t-J, and the Hubbard models. The cases we studied indicate that themore » Krylov-space approach can be more accurate and efficient than the conjugate gradient, and that the error of the former integrates best when a Krylov-space decomposition is also used for ground state DMRG.« less

Improving consensus structure by eliminating averaging artifacts

PubMed Central

KC, Dukka B

2009-01-01

Background Common structural biology methods (i.e., NMR and molecular dynamics) often produce ensembles of molecular structures. Consequently, averaging of 3D coordinates of molecular structures (proteins and RNA) is a frequent approach to obtain a consensus structure that is representative of the ensemble. However, when the structures are averaged, artifacts can result in unrealistic local geometries, including unphysical bond lengths and angles. Results Herein, we describe a method to derive representative structures while limiting the number of artifacts. Our approach is based on a Monte Carlo simulation technique that drives a starting structure (an extended or a 'close-by' structure) towards the 'averaged structure' using a harmonic pseudo energy function. To assess the performance of the algorithm, we applied our approach to Cα models of 1364 proteins generated by the TASSER structure prediction algorithm. The average RMSD of the refined model from the native structure for the set becomes worse by a mere 0.08 Å compared to the average RMSD of the averaged structures from the native structure (3.28 Å for refined structures and 3.36 A for the averaged structures). However, the percentage of atoms involved in clashes is greatly reduced (from 63% to 1%); in fact, the majority of the refined proteins had zero clashes. Moreover, a small number (38) of refined structures resulted in lower RMSD to the native protein versus the averaged structure. Finally, compared to PULCHRA [1], our approach produces representative structure of similar RMSD quality, but with much fewer clashes. Conclusion The benchmarking results demonstrate that our approach for removing averaging artifacts can be very beneficial for the structural biology community. Furthermore, the same approach can be applied to almost any problem where averaging of 3D coordinates is performed. Namely, structure averaging is also commonly performed in RNA secondary prediction [2], which could also benefit from our approach. PMID:19267905

Functional brain connectivity is predictable from anatomic network's Laplacian eigen-structure.

PubMed

Abdelnour, Farras; Dayan, Michael; Devinsky, Orrin; Thesen, Thomas; Raj, Ashish

2018-05-15

How structural connectivity (SC) gives rise to functional connectivity (FC) is not fully understood. Here we mathematically derive a simple relationship between SC measured from diffusion tensor imaging, and FC from resting state fMRI. We establish that SC and FC are related via (structural) Laplacian spectra, whereby FC and SC share eigenvectors and their eigenvalues are exponentially related. This gives, for the first time, a simple and analytical relationship between the graph spectra of structural and functional networks. Laplacian eigenvectors are shown to be good predictors of functional eigenvectors and networks based on independent component analysis of functional time series. A small number of Laplacian eigenmodes are shown to be sufficient to reconstruct FC matrices, serving as basis functions. This approach is fast, and requires no time-consuming simulations. It was tested on two empirical SC/FC datasets, and was found to significantly outperform generative model simulations of coupled neural masses. Copyright © 2018. Published by Elsevier Inc.

Structural approaches to knowledge exchange: comparing practices across five centres of excellence in public health.

PubMed

Van der Graaf, P; Francis, O; Doe, E; Barrett, E; O'Rorke, M; Docherty, G

2018-03-01

In 2008, five UKCRC Public Health Research Centres of Excellence were created to develop a coordinated approach to policy and practice engagement and knowledge exchange. The five Centres have developed their own models and practices for achieving these aims, which have not been compared in detail to date. We applied an extended version of Saner's model for the interface between science and policy to compare five case studies of knowledge exchanges, one from each centre. We compared these practices on three dimensions within our model (focus, function and type/scale) to identify barriers and facilitators for knowledge exchange. The case studies shared commonalities in their range of activities (type) but illustrated different ways of linking these activities (function). The Centres' approaches ranged from structural to more organic, and varied in the extent that they engaged internal audiences (focus). Each centre addressed policymakers at different geographical levels and scale. This article emphasizes the importance of linking a range of activities that engage policymakers at different levels, intensities and points in their decision-making processes to build relationships. Developing a structural approach to knowledge exchange activities in different contexts presents challenges of resource, implementation and evaluation.

Low-dose dynamic myocardial perfusion CT image reconstruction using pre-contrast normal-dose CT scan induced structure tensor total variation regularization

NASA Astrophysics Data System (ADS)

Gong, Changfei; Han, Ce; Gan, Guanghui; Deng, Zhenxiang; Zhou, Yongqiang; Yi, Jinling; Zheng, Xiaomin; Xie, Congying; Jin, Xiance

2017-04-01

Dynamic myocardial perfusion CT (DMP-CT) imaging provides quantitative functional information for diagnosis and risk stratification of coronary artery disease by calculating myocardial perfusion hemodynamic parameter (MPHP) maps. However, the level of radiation delivered by dynamic sequential scan protocol can be potentially high. The purpose of this work is to develop a pre-contrast normal-dose scan induced structure tensor total variation regularization based on the penalized weighted least-squares (PWLS) criteria to improve the image quality of DMP-CT with a low-mAs CT acquisition. For simplicity, the present approach was termed as ‘PWLS-ndiSTV’. Specifically, the ndiSTV regularization takes into account the spatial-temporal structure information of DMP-CT data and further exploits the higher order derivatives of the objective images to enhance denoising performance. Subsequently, an effective optimization algorithm based on the split-Bregman approach was adopted to minimize the associative objective function. Evaluations with modified dynamic XCAT phantom and preclinical porcine datasets have demonstrated that the proposed PWLS-ndiSTV approach can achieve promising gains over other existing approaches in terms of noise-induced artifacts mitigation, edge details preservation, and accurate MPHP maps calculation.

A comparison of different methods to implement higher order derivatives of density functionals

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

van Dam, Hubertus J.J.

Density functional theory is the dominant approach in electronic structure methods today. To calculate properties higher order derivatives of the density functionals are required. These derivatives might be implemented manually,by automatic differentiation, or by symbolic algebra programs. Different authors have cited different reasons for using the particular method of their choice. This paper presents work where all three approaches were used and the strengths and weaknesses of each approach are considered. It is found that all three methods produce code that is suffficiently performanted for practical applications, despite the fact that our symbolic algebra generated code and our automatic differentiationmore » code still have scope for significant optimization. The automatic differentiation approach is the best option for producing readable and maintainable code.« less

Rehabilitation Medicine Approaches to Pain Management.

PubMed

Cheville, Andrea L; Smith, Sean R; Basford, Jeffrey R

2018-06-01

Rehabilitation medicine offers strategies that reduce musculoskeletal pain, targeted approaches to alleviate movement-related pain, and interventions to optimize patients' function despite the persistence of pain. These approaches fall into four categories: modulating nociception, stabilizing and unloading painful structures, influencing pain perception, and alleviating soft tissue musculotendinous pain. Incorporating these interventions into individualized, comprehensive pain management programs offers the potential to empower patients and limit pain associated with mobility and required daily activities. Rehabilitative approach may be particularly helpful for patients with refractory movement-associated pain and functional vulnerability, and for those who do not wish for, or cannot, tolerate pharmacoanalgesia. Copyright © 2018 Elsevier Inc. All rights reserved.

Efficient conformational space exploration in ab initio protein folding simulation.

PubMed

Ullah, Ahammed; Ahmed, Nasif; Pappu, Subrata Dey; Shatabda, Swakkhar; Ullah, A Z M Dayem; Rahman, M Sohel

2015-08-01

Ab initio protein folding simulation largely depends on knowledge-based energy functions that are derived from known protein structures using statistical methods. These knowledge-based energy functions provide us with a good approximation of real protein energetics. However, these energy functions are not very informative for search algorithms and fail to distinguish the types of amino acid interactions that contribute largely to the energy function from those that do not. As a result, search algorithms frequently get trapped into the local minima. On the other hand, the hydrophobic-polar (HP) model considers hydrophobic interactions only. The simplified nature of HP energy function makes it limited only to a low-resolution model. In this paper, we present a strategy to derive a non-uniform scaled version of the real 20×20 pairwise energy function. The non-uniform scaling helps tackle the difficulty faced by a real energy function, whereas the integration of 20×20 pairwise information overcomes the limitations faced by the HP energy function. Here, we have applied a derived energy function with a genetic algorithm on discrete lattices. On a standard set of benchmark protein sequences, our approach significantly outperforms the state-of-the-art methods for similar models. Our approach has been able to explore regions of the conformational space which all the previous methods have failed to explore. Effectiveness of the derived energy function is presented by showing qualitative differences and similarities of the sampled structures to the native structures. Number of objective function evaluation in a single run of the algorithm is used as a comparison metric to demonstrate efficiency.

Constructive Approaches for Understanding the Origin of Self-Replication and Evolution.

PubMed

Ichihashi, Norikazu; Yomo, Tetsuya

2016-07-13

The mystery of the origin of life can be divided into two parts. The first part is the origin of biomolecules: under what physicochemical conditions did biomolecules such as amino acids, nucleotides, and their polymers arise? The second part of the mystery is the origin of life-specific functions such as the replication of genetic information, the reproduction of cellular structures, metabolism, and evolution. These functions require the coordination of many different kinds of biological molecules. A direct strategy to approach the second part of the mystery is the constructive approach, in which life-specific functions are recreated in a test tube from specific biological molecules. Using this approach, we are able to employ design principles to reproduce life-specific functions, and the knowledge gained through the reproduction process provides clues as to their origins. In this mini-review, we introduce recent insights gained using this approach, and propose important future directions for advancing our understanding of the origins of life.

Structural electronic and mechanical properties of YM2 (M=Mn, Fe, Co) laves phase compounds: First principle calculations analyzed with datamining approach

NASA Astrophysics Data System (ADS)

Saidi, F.; Sebaa, N.; Mahmoudi, A.; Aourag, H.; Merad, G.; Dergal, M.

2018-06-01

We performed first-principle calculations to investigate structural, phase stability, electronic and mechanical properties for the Laves phases YM2 (M = Mn, Fe, Co) with C15, C14 and C36 structures. We used the density functional theory within the framework of both pseudo-potentials and plane wave basis using VASP (Vienna Ab Initio Software Package). The calculated equilibrium structural parameters are in accordance with available theoretical values. Mechanical properties were calculated, discussed, and analyzed with data mining approach in terms of structure stability. The results reveal that YCo2 is harder than YFe2 and YMn2.

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.

Functional reasoning in diagnostic problem solving

NASA Technical Reports Server (NTRS)

Sticklen, Jon; Bond, W. E.; Stclair, D. C.

1988-01-01

This work is one facet of an integrated approach to diagnostic problem solving for aircraft and space systems currently under development. The authors are applying a method of modeling and reasoning about deep knowledge based on a functional viewpoint. The approach recognizes a level of device understanding which is intermediate between a compiled level of typical Expert Systems, and a deep level at which large-scale device behavior is derived from known properties of device structure and component behavior. At this intermediate functional level, a device is modeled in three steps. First, a component decomposition of the device is defined. Second, the functionality of each device/subdevice is abstractly identified. Third, the state sequences which implement each function are specified. Given a functional representation and a set of initial conditions, the functional reasoner acts as a consequence finder. The output of the consequence finder can be utilized in diagnostic problem solving. The paper also discussed ways in which this functional approach may find application in the aerospace field.

Theoretical Neuroanatomy:Analyzing the Structure, Dynamics,and Function of Neuronal Networks

NASA Astrophysics Data System (ADS)

Seth, Anil K.; Edelman, Gerald M.

The mammalian brain is an extraordinary object: its networks give rise to our conscious experiences as well as to the generation of adaptive behavior for the organism within its environment. Progress in understanding the structure, dynamics and function of the brain faces many challenges. Biological neural networks change over time, their detailed structure is difficult to elucidate, and they are highly heterogeneous both in their neuronal units and synaptic connections. In facing these challenges, graph-theoretic and information-theoretic approaches have yielded a number of useful insights and promise many more.

Using Refined Regression Analysis To Assess The Ecological Services Of Restored Wetlands

EPA Science Inventory

A hierarchical approach to regression analysis of wetland water treatment was conducted to determine which factors are the most appropriate for characterizing wetlands of differing structure and function. We used this approach in an effort to identify the types and characteristi...

Using 1H and 13C NMR chemical shifts to determine cyclic peptide conformations: a combined molecular dynamics and quantum mechanics approach.

PubMed

Nguyen, Q Nhu N; Schwochert, Joshua; Tantillo, Dean J; Lokey, R Scott

2018-05-10

Solving conformations of cyclic peptides can provide insight into structure-activity and structure-property relationships, which can help in the design of compounds with improved bioactivity and/or ADME characteristics. The most common approaches for determining the structures of cyclic peptides are based on NMR-derived distance restraints obtained from NOESY or ROESY cross-peak intensities, and 3J-based dihedral restraints using the Karplus relationship. Unfortunately, these observables are often too weak, sparse, or degenerate to provide unequivocal, high-confidence solution structures, prompting us to investigate an alternative approach that relies only on 1H and 13C chemical shifts as experimental observables. This method, which we call conformational analysis from NMR and density-functional prediction of low-energy ensembles (CANDLE), uses molecular dynamics (MD) simulations to generate conformer families and density functional theory (DFT) calculations to predict their 1H and 13C chemical shifts. Iterative conformer searches and DFT energy calculations on a cyclic peptide-peptoid hybrid yielded Boltzmann ensembles whose predicted chemical shifts matched the experimental values better than any single conformer. For these compounds, CANDLE outperformed the classic NOE- and 3J-coupling-based approach by disambiguating similar β-turn types and also enabled the structural elucidation of the minor conformer. Through the use of chemical shifts, in conjunction with DFT and MD calculations, CANDLE can help illuminate conformational ensembles of cyclic peptides in solution.

FAST TRACK COMMUNICATION: Preferential functionalization on zigzag graphene nanoribbons: first-principles calculations

NASA Astrophysics Data System (ADS)

Lee, Hoonkyung

2010-09-01

We investigate the functionalization of functional groups to graphene nanoribbons with zigzag and armchair edges using first-principles calculations. We find that the formation energy for the configuration of the functional groups functionalized to the zigzag edge is ~ 0.2 eV per functional group lower than that to the armchair edge. The formation energy difference arises from a structural deformation on the armchair edge by the functionalization whereas there is no structural deformation on the zigzag edge. Selective functionalization on the zigzag edge takes place at a condition of the temperature and the pressure of ~ 25 °C and 10 - 5 atm. Our findings show that selective functionalization can offer the opportunity for an approach to the separation of zigzag graphene nanoribbons with their solubility change.

Scientific evaluation of traditional Chinese medicine under DSHEA: a conundrum. Dietary Supplement Health and Education Act.

PubMed

Chang, J

1999-04-01

In the United States, traditional Chinese medicines (TCM) are currently sold as dietary supplements, as defined by The Dietary Supplement Health and Education Act (DSHEA). This legislation is unique to the United States and while "structure and function" claims are allowable under DSHEA, disease claims are not. The narrow definition, however, poses a challenge to designing appropriate clinical studies that can provide data for "structure and function" claim substantiation. The process of melding Chinese herbal medicines into the dietary supplement category is complex and there is a need to define a clinical trial paradigm carefully that addresses "structure and function claims" without sacrificing scientific rigor. It is frequently not recognized that TCM favors an amalgamation of several herbs to generate the putative clinical effect. Because of this historical multiherb approach, the reliance on retrospective data to support the potential health benefits of an herb extract has severe limitations. Notwithstanding the immense value of identifying the pharmacological activity of a TCM herb to a chemical suitable for pharmaceutical development, another approach to safe and efficacious herbal products is to develop a standardized herbal extract. This article highlights issues related to the latter approach and will discuss a research-based strategy that may be suitable for validating, in part, the putative health benefits of TCM.

QMEANclust: estimation of protein model quality by combining a composite scoring function with structural density information.

PubMed

Benkert, Pascal; Schwede, Torsten; Tosatto, Silvio Ce

2009-05-20

The selection of the most accurate protein model from a set of alternatives is a crucial step in protein structure prediction both in template-based and ab initio approaches. Scoring functions have been developed which can either return a quality estimate for a single model or derive a score from the information contained in the ensemble of models for a given sequence. Local structural features occurring more frequently in the ensemble have a greater probability of being correct. Within the context of the CASP experiment, these so called consensus methods have been shown to perform considerably better in selecting good candidate models, but tend to fail if the best models are far from the dominant structural cluster. In this paper we show that model selection can be improved if both approaches are combined by pre-filtering the models used during the calculation of the structural consensus. Our recently published QMEAN composite scoring function has been improved by including an all-atom interaction potential term. The preliminary model ranking based on the new QMEAN score is used to select a subset of reliable models against which the structural consensus score is calculated. This scoring function called QMEANclust achieves a correlation coefficient of predicted quality score and GDT_TS of 0.9 averaged over the 98 CASP7 targets and perform significantly better in selecting good models from the ensemble of server models than any other groups participating in the quality estimation category of CASP7. Both scoring functions are also benchmarked on the MOULDER test set consisting of 20 target proteins each with 300 alternatives models generated by MODELLER. QMEAN outperforms all other tested scoring functions operating on individual models, while the consensus method QMEANclust only works properly on decoy sets containing a certain fraction of near-native conformations. We also present a local version of QMEAN for the per-residue estimation of model quality (QMEANlocal) and compare it to a new local consensus-based approach. Improved model selection is obtained by using a composite scoring function operating on single models in order to enrich higher quality models which are subsequently used to calculate the structural consensus. The performance of consensus-based methods such as QMEANclust highly depends on the composition and quality of the model ensemble to be analysed. Therefore, performance estimates for consensus methods based on large meta-datasets (e.g. CASP) might overrate their applicability in more realistic modelling situations with smaller sets of models based on individual methods.

Structural, elastic, electronic, optical and thermoelectric properties of the Zintl-phase Ae3AlAs3 (Ae = Sr, Ba)

NASA Astrophysics Data System (ADS)

Benahmed, A.; Bouhemadou, A.; Alqarni, B.; Guechi, N.; Al-Douri, Y.; Khenata, R.; Bin-Omran, S.

2018-05-01

First-principles calculations were performed to investigate the structural, elastic, electronic, optical and thermoelectric properties of the Zintl-phase Ae3AlAs3 (Ae = Sr, Ba) using two complementary approaches based on density functional theory. The pseudopotential plane-wave method was used to explore the structural and elastic properties whereas the full-potential linearised augmented plane wave approach was used to study the structural, electronic, optical and thermoelectric properties. The calculated structural parameters are in good consistency with the corresponding measured ones. The single-crystal and polycrystalline elastic constants and related properties were examined in details. The electronic properties, including energy band dispersions, density of states and charge-carrier effective masses, were computed using Tran-Blaha modified Becke-Johnson functional for the exchange-correlation potential. It is found that both studied compounds are direct band gap semiconductors. Frequency-dependence of the linear optical functions were predicted for a wide photon energy range up to 15 eV. Charge carrier concentration and temperature dependences of the basic parameters of the thermoelectric properties were explored using the semi-classical Boltzmann transport model. Our calculations unveil that the studied compounds are characterised by a high thermopower for both carriers, especially the p-type conduction is more favourable.

Bio-inspired configurable multiscale extracellular matrix-like structures for functional alignment and guided orientation of cells.

PubMed

Bae, Won-Gyu; Kim, Jangho; Choung, Yun-Hoon; Chung, Yesol; Suh, Kahp Y; Pang, Changhyun; Chung, Jong Hoon; Jeong, Hoon Eui

2015-11-01

Inspired by the hierarchically organized protein fibers in extracellular matrix (ECM) as well as the physiological importance of multiscale topography, we developed a simple but robust method for the design and manipulation of precisely controllable multiscale hierarchical structures using capillary force lithography in combination with an original wrinkling technique. In this study, based on our proposed fabrication technology, we approached a conceptual platform that can mimic the hierarchically multiscale topographical and orientation cues of the ECM for controlling cell structure and function. We patterned the polyurethane acrylate-based nanotopography with various orientations on the microgrooves, which could provide multiscale topography signals of ECM to control single and multicellular morphology and orientation with precision. Using our platforms, we found that the structures and orientations of fibroblast cells were greatly influenced by the nanotopography, rather than the microtopography. We also proposed a new approach that enables the generation of native ECM having nanofibers in specific three-dimensional (3D) configurations by culturing fibroblast cells on the multiscale substrata. We suggest that our methodology could be used as efficient strategies for the design and manipulation of various functional platforms, including well-defined 3D tissue structures for advanced regenerative medicine applications. Copyright © 2015 Elsevier Ltd. All rights reserved.

Climate extremes drive changes in functional community structure.

PubMed

Boucek, Ross E; Rehage, Jennifer S

2014-06-01

The response of communities to climate extremes can be quite variable. Much of this variation has been attributed to differences in community-specific functional trait diversity, as well as community composition. Yet, few if any studies have explicitly tested the response of the functional trait structure of communities following climate extremes (CEs). Recently in South Florida, two independent, but sequential potential CEs took place, a 2010 cold front, followed by a 2011 drought, both of which had profound impacts on a subtropical estuarine fish community. These CEs provided an opportunity to test whether the structure of South Florida fish communities following each extreme was a result of species-specific differences in functional traits. From historical temperature (1927-2012) and freshwater inflows records into the estuary (1955-2012), we determined that the cold front was a statistically extreme disturbance, while the drought was not, but rather a decadal rare disturbance. The two disturbances predictably affected different parts of functional community structure and thus different component species. The cold front virtually eliminated tropical species, including large-bodied snook, mojarra species, nonnative cichlids, and striped mullet, while having little affect on temperate fishes. Likewise, the drought severely impacted freshwater fishes including Florida gar, bowfin, and two centrarchids, with little effect on euryhaline species. Our findings illustrate the ability of this approach to predict and detect both the filtering effects of different types of disturbances and the implications of the resulting changes in community structure. Further, we highlight the value of this approach to developing predictive frameworks for better understanding community responses to global change. © 2014 John Wiley & Sons Ltd.

Characterizing left-right gait balance using footstep-induced structural vibrations

NASA Astrophysics Data System (ADS)

Fagert, Jonathon; Mirshekari, Mostafa; Pan, Shijia; Zhang, Pei; Noh, Hae Young

2017-04-01

In this paper, we introduce a method for estimating human left/right walking gait balance using footstep-induced structural vibrations. Understanding human gait balance is an integral component of assessing gait, neurological and musculoskeletal conditions, overall health status, and risk of falls. Existing techniques utilize pressure- sensing mats, wearable devices, and human observation-based assessment by healthcare providers. These existing methods are collectively limited in their operation and deployment; often requiring dense sensor deployment or direct user interaction. To address these limitations, we utilize footstep-induced structural vibration responses. Based on the physical insight that the vibration energy is a function of the force exerted by a footstep, we calculate the vibration signal energy due to a footstep and use it to estimate the footstep force. By comparing the footstep forces while walking, we determine balance. This approach enables non-intrusive gait balance assessment using sparsely deployed sensors. The primary research challenge is that the floor vibration signal energy is also significantly affected by the distance between the footstep location and the vibration sensor; this function is unclear in real-world scenarios and is a mixed function of wave propagation and structure-dependent properties. We overcome this challenge through footstep localization and incorporating structural factors into an analytical force-energy-distance function. This function is estimated through a nonlinear least squares regression analysis. We evaluate the performance of our method with a real-world deployment in a campus building. Our approach estimates footstep forces with a RMSE of 61.0N (8% of participant's body weight), representing a 1.54X improvement over the baseline.

A holistic approach to determine tree structural complexity based on laser scanning data and fractal analysis.

PubMed

Seidel, Dominik

2018-01-01

The three-dimensional forest structure affects many ecosystem functions and services provided by forests. As forests are made of trees it seems reasonable to approach their structure by investigating individual tree structure. Based on three-dimensional point clouds from laser scanning, a newly developed holistic approach is presented that enables to calculate the box dimension as a measure of structural complexity of individual trees using fractal analysis. It was found that the box dimension of trees was significantly different among the tested species, among trees belonging to the same species but exposed to different growing conditions (at gap vs. forest interior) or to different kinds of competition (intraspecific vs. interspecific). Furthermore, it was shown that the box dimension is positively related to the trees' growth rate. The box dimension was identified as an easy to calculate measure that integrates the effect of several external drivers of tree structure, such as competition strength and type, while simultaneously providing information on structure-related properties, like tree growth.

Metagenomic analysis reveals significant changes of microbial compositions and protective functions during drinking water treatment.

PubMed

Chao, Yuanqing; Ma, Liping; Yang, Ying; Ju, Feng; Zhang, Xu-Xiang; Wu, Wei-Min; Zhang, Tong

2013-12-19

The metagenomic approach was applied to characterize variations of microbial structure and functions in raw (RW) and treated water (TW) in a drinking water treatment plant (DWTP) at Pearl River Delta, China. Microbial structure was significantly influenced by the treatment processes, shifting from Gammaproteobacteria and Betaproteobacteria in RW to Alphaproteobacteria in TW. Further functional analysis indicated the basic metabolic functions of microorganisms in TW did not vary considerably. However, protective functions, i.e. glutathione synthesis genes in 'oxidative stress' and 'detoxification' subsystems, significantly increased, revealing the surviving bacteria may have higher chlorine resistance. Similar results were also found in glutathione metabolism pathway, which identified the major reaction for glutathione synthesis and supported more genes for glutathione metabolism existed in TW. This metagenomic study largely enhanced our knowledge about the influences of treatment processes, especially chlorination, on bacterial community structure and protective functions (e.g. glutathione metabolism) in ecosystems of DWTPs.

RNA and RNP as Building Blocks for Nanotechnology and Synthetic Biology.

PubMed

Ohno, Hirohisa; Saito, Hirohide

2016-01-01

Recent technologies that aimed to elucidate cellular function have revealed essential roles for RNA molecules in living systems. Our knowledge concerning functional and structural information of naturally occurring RNA and RNA-protein (RNP) complexes is increasing rapidly. RNA and RNP interaction motifs are structural units that function as building blocks to constitute variety of complex structures. RNA-central synthetic biology and nanotechnology are constructive approaches that employ the accumulated information and build synthetic RNA (RNP)-based circuits and nanostructures. Here, we describe how to design and construct synthetic RNA (RNP)-based devices and structures at the nanometer-scale for biological and future therapeutic applications. RNA/RNP nanostructures can also be utilized as the molecular scaffold to control the localization or interactions of target molecule(s). Moreover, RNA motifs recognized by RNA-binding proteins can be applied to make protein-responsive translational "switches" that can turn gene expression "on" or "off" depending on the intracellular environment. This "synthetic RNA and RNP world" will expand tools for nanotechnology and synthetic biology. In addition, these reconstructive approaches would lead to a greater understanding of building principle in naturally occurring RNA/RNP molecules and systems. Copyright © 2016 Elsevier Inc. All rights reserved.

A Four-Dimensional Probabilistic Atlas of the Human Brain

PubMed Central

Mazziotta, John; Toga, Arthur; Evans, Alan; Fox, Peter; Lancaster, Jack; Zilles, Karl; Woods, Roger; Paus, Tomas; Simpson, Gregory; Pike, Bruce; Holmes, Colin; Collins, Louis; Thompson, Paul; MacDonald, David; Iacoboni, Marco; Schormann, Thorsten; Amunts, Katrin; Palomero-Gallagher, Nicola; Geyer, Stefan; Parsons, Larry; Narr, Katherine; Kabani, Noor; Le Goualher, Georges; Feidler, Jordan; Smith, Kenneth; Boomsma, Dorret; Pol, Hilleke Hulshoff; Cannon, Tyrone; Kawashima, Ryuta; Mazoyer, Bernard

2001-01-01

The authors describe the development of a four-dimensional atlas and reference system that includes both macroscopic and microscopic information on structure and function of the human brain in persons between the ages of 18 and 90 years. Given the presumed large but previously unquantified degree of structural and functional variance among normal persons in the human population, the basis for this atlas and reference system is probabilistic. Through the efforts of the International Consortium for Brain Mapping (ICBM), 7,000 subjects will be included in the initial phase of database and atlas development. For each subject, detailed demographic, clinical, behavioral, and imaging information is being collected. In addition, 5,800 subjects will contribute DNA for the purpose of determining genotype– phenotype–behavioral correlations. The process of developing the strategies, algorithms, data collection methods, validation approaches, database structures, and distribution of results is described in this report. Examples of applications of the approach are described for the normal brain in both adults and children as well as in patients with schizophrenia. This project should provide new insights into the relationship between microscopic and macroscopic structure and function in the human brain and should have important implications in basic neuroscience, clinical diagnostics, and cerebral disorders. PMID:11522763

Fermi liquid, clustering, and structure factor in dilute warm nuclear matter

NASA Astrophysics Data System (ADS)

Röpke, G.; Voskresensky, D. N.; Kryukov, I. A.; Blaschke, D.

2018-02-01

Properties of nuclear systems at subsaturation densities can be obtained from different approaches. We demonstrate the use of the density autocorrelation function which is related to the isothermal compressibility and, after integration, to the equation of state. This way we connect the Landau Fermi liquid theory well elaborated in nuclear physics with the approaches to dilute nuclear matter describing cluster formation. A quantum statistical approach is presented, based on the cluster decomposition of the polarization function. The fundamental quantity to be calculated is the dynamic structure factor. Comparing with the Landau Fermi liquid theory which is reproduced in lowest approximation, the account of bound state formation and continuum correlations gives the correct low-density result as described by the second virial coefficient and by the mass action law (nuclear statistical equilibrium). Going to higher densities, the inclusion of medium effects is more involved compared with other quantum statistical approaches, but the relation to the Landau Fermi liquid theory gives a promising approach to describe not only thermodynamic but also collective excitations and non-equilibrium properties of nuclear systems in a wide region of the phase diagram.

Ab initio structure prediction of silicon and germanium sulfides for lithium-ion battery materials

NASA Astrophysics Data System (ADS)

Hsueh, Connie; Mayo, Martin; Morris, Andrew J.

Conventional experimental-based approaches to materials discovery, which can rely heavily on trial and error, are time-intensive and costly. We discuss approaches to coupling experimental and computational techniques in order to systematize, automate, and accelerate the process of materials discovery, which is of particular relevance to developing new battery materials. We use the ab initio random structure searching (AIRSS) method to conduct a systematic investigation of Si-S and Ge-S binary compounds in order to search for novel materials for lithium-ion battery (LIB) anodes. AIRSS is a high-throughput, density functional theory-based approach to structure prediction which has been successful at predicting the structures of LIBs containing sulfur and silicon and germanium. We propose a lithiation mechanism for Li-GeS2 anodes as well as report new, theoretically stable, layered and porous structures in the Si-S and Ge-S systems that pique experimental interest.

Analysis of spatial correlations in a model two-dimensional liquid through eigenvalues and eigenvectors of atomic-level stress matrices.

PubMed

Levashov, V A; Stepanov, M G

2016-01-01

Considerations of local atomic-level stresses associated with each atom represent a particular approach to address structures of disordered materials at the atomic level. We studied structural correlations in a two-dimensional model liquid using molecular dynamics simulations in the following way. We diagonalized the atomic-level stress tensor of every atom and investigated correlations between the eigenvalues and orientations of the eigenvectors of different atoms as a function of distance between them. It is demonstrated that the suggested approach can be used to characterize structural correlations in disordered materials. In particular, we found that changes in the stress correlation functions on decrease of temperature are the most pronounced for the pairs of atoms with separation distance that corresponds to the first minimum in the pair density function. We also show that the angular dependencies of the stress correlation functions previously reported by Wu et al. [Phys. Rev. E 91, 032301 (2015)10.1103/PhysRevE.91.032301] do not represent the anisotropic Eshelby's stress fields, as it is suggested, but originate in the rotational properties of the stress tensors.

Machine learning of single molecule free energy surfaces and the impact of chemistry and environment upon structure and dynamics

NASA Astrophysics Data System (ADS)

Mansbach, Rachael A.; Ferguson, Andrew L.

2015-03-01

The conformational states explored by polymers and proteins can be controlled by environmental conditions (e.g., temperature, pressure, and solvent) and molecular chemistry (e.g., molecular weight and side chain identity). We introduce an approach employing the diffusion map nonlinear machine learning technique to recover single molecule free energy landscapes from molecular simulations, quantify changes to the landscape as a function of external conditions and molecular chemistry, and relate these changes to modifications of molecular structure and dynamics. In an application to an n-eicosane chain, we quantify the thermally accessible chain configurations as a function of temperature and solvent conditions. In an application to a family of polyglutamate-derivative homopeptides, we quantify helical stability as a function of side chain length, resolve the critical side chain length for the helix-coil transition, and expose the molecular mechanisms underpinning side chain-mediated helix stability. By quantifying single molecule responses through perturbations to the underlying free energy surface, our approach provides a quantitative bridge between experimentally controllable variables and microscopic molecular behavior, guiding and informing rational engineering of desirable molecular structure and function.

Machine learning of single molecule free energy surfaces and the impact of chemistry and environment upon structure and dynamics.

PubMed

Mansbach, Rachael A; Ferguson, Andrew L

2015-03-14

The conformational states explored by polymers and proteins can be controlled by environmental conditions (e.g., temperature, pressure, and solvent) and molecular chemistry (e.g., molecular weight and side chain identity). We introduce an approach employing the diffusion map nonlinear machine learning technique to recover single molecule free energy landscapes from molecular simulations, quantify changes to the landscape as a function of external conditions and molecular chemistry, and relate these changes to modifications of molecular structure and dynamics. In an application to an n-eicosane chain, we quantify the thermally accessible chain configurations as a function of temperature and solvent conditions. In an application to a family of polyglutamate-derivative homopeptides, we quantify helical stability as a function of side chain length, resolve the critical side chain length for the helix-coil transition, and expose the molecular mechanisms underpinning side chain-mediated helix stability. By quantifying single molecule responses through perturbations to the underlying free energy surface, our approach provides a quantitative bridge between experimentally controllable variables and microscopic molecular behavior, guiding and informing rational engineering of desirable molecular structure and function.

Conformational and functional analysis of molecular dynamics trajectories by Self-Organising Maps

PubMed Central

2011-01-01

Background Molecular dynamics (MD) simulations are powerful tools to investigate the conformational dynamics of proteins that is often a critical element of their function. Identification of functionally relevant conformations is generally done clustering the large ensemble of structures that are generated. Recently, Self-Organising Maps (SOMs) were reported performing more accurately and providing more consistent results than traditional clustering algorithms in various data mining problems. We present a novel strategy to analyse and compare conformational ensembles of protein domains using a two-level approach that combines SOMs and hierarchical clustering. Results The conformational dynamics of the α-spectrin SH3 protein domain and six single mutants were analysed by MD simulations. The Cα's Cartesian coordinates of conformations sampled in the essential space were used as input data vectors for SOM training, then complete linkage clustering was performed on the SOM prototype vectors. A specific protocol to optimize a SOM for structural ensembles was proposed: the optimal SOM was selected by means of a Taguchi experimental design plan applied to different data sets, and the optimal sampling rate of the MD trajectory was selected. The proposed two-level approach was applied to single trajectories of the SH3 domain independently as well as to groups of them at the same time. The results demonstrated the potential of this approach in the analysis of large ensembles of molecular structures: the possibility of producing a topological mapping of the conformational space in a simple 2D visualisation, as well as of effectively highlighting differences in the conformational dynamics directly related to biological functions. Conclusions The use of a two-level approach combining SOMs and hierarchical clustering for conformational analysis of structural ensembles of proteins was proposed. It can easily be extended to other study cases and to conformational ensembles from other sources. PMID:21569575

Computation-Facilitated Assignment of Function in the Enolase Superfamily: A Regiochemically Distinct Galactarate Dehydratase from Oceanobacillus iheyensis†

PubMed Central

Rakus, John F.; Kalyanaraman, Chakrapani; Fedorov, Alexander A.; Fedorov, Elena V.; Mills-Groninger, Fiona P.; Toro, Rafael; Bonanno, Jeffrey; Bain, Kevin; Sauder, J. Michael; Burley, Stephen K.; Almo, Steven C.; Jacobson, Matthew P.; Gerlt, John A.

2009-01-01

The structure of an uncharacterized member of the enolase superfamily from Oceanobacillus iheyensis (GI: 23100298; IMG locus tag Ob2843; PDB Code 2OQY) was determined by the New York SGX Research Center for Structural Genomics (NYSGXRC). The structure contained two Mg2+ ions located 10.4 Å from one another, with one located in the canonical position in the (β/α)7β-barrel domain (although the ligand at the end of the fifth β-strand is His, unprecedented in structurally characterized members of the superfamily); the second is located in a novel site within the capping domain. In silico docking of a library of mono- and diacid sugars to the active site predicted a diacid sugar as a likely substrate. Activity screening of a physical library of acid sugars identified galactarate as the substrate (kcat = 6.8 s−1, KM = 620 μM; kcat/KM = 1.1 × 104 M−1 s−1), allowing functional assignment of Ob2843 as galactarate dehydratase (GalrD-II) The structure of a complex of the catalytically impaired Y90F mutant with Mg2+ and galactarate allowed identification of a Tyr 164-Arg 162 dyad as the base that initiates the reaction by abstraction of the α-proton and Tyr 90 as the acid that facilitates departure of the β-OH leaving group. The enzyme product is 2-keto-3-deoxy-D-threo-4,5-dihydroxyadipate, the enantiomer of the product obtained in the GalrD reaction catalyzed by a previously characterized bifunctional L-talarate/galactarate dehydratase (TalrD/GalrD). On the basis of the different active site structures and different regiochemistries, we recognize that these functions represent an example of apparent, not actual, convergent evolution of function. The structure of GalrD-II and its active site architecture allow identification of the seventh functionally and structurally characterized subgroup in the enolase superfamily. This study provides an additional example that an integrated sequence/structure-based strategy employing computational approaches is a viable approach for directing functional assignment of unknown enzymes discovered in genome projects. PMID:19883118

De Novo Proteins with Life-Sustaining Functions Are Structurally Dynamic.

PubMed

Murphy, Grant S; Greisman, Jack B; Hecht, Michael H

2016-01-29

Designing and producing novel proteins that fold into stable structures and provide essential biological functions are key goals in synthetic biology. In initial steps toward achieving these goals, we constructed a combinatorial library of de novo proteins designed to fold into 4-helix bundles. As described previously, screening this library for sequences that function in vivo to rescue conditionally lethal mutants of Escherichia coli (auxotrophs) yielded several de novo sequences, termed SynRescue proteins, which rescued four different E. coli auxotrophs. In an effort to understand the structural requirements necessary for auxotroph rescue, we investigated the biophysical properties of the SynRescue proteins, using both computational and experimental approaches. Results from circular dichroism, size-exclusion chromatography, and NMR demonstrate that the SynRescue proteins are α-helical and relatively stable. Surprisingly, however, they do not form well-ordered structures. Instead, they form dynamic structures that fluctuate between monomeric and dimeric states. These findings show that a well-ordered structure is not a prerequisite for life-sustaining functions, and suggests that dynamic structures may have been important in the early evolution of protein function. Copyright © 2015 Elsevier Ltd. All rights reserved.

Quantification of Soil Pore Structure Based on Minkowski-Functions

NASA Astrophysics Data System (ADS)

Vogel, H.; Weller, U.; Schlüter, S.

2009-05-01

The porous structure in soils and other geologic media is typically a complex 3-dimensional object. Most of the physical material properties including mechanical and hydraulic characteristics are immediately linked to this structure which can be directly observed using non-invasive techniques as e.g. X-ray tomography. It is an old dream and still a formidable challenge to related structural features of porous media to their physical properties. In this contribution we present a scale-invariant concept to quantify pore structure based on a limited set of meaningful morphological functions. They are based on d+1 Minkowski functionals as defined for d-dimensional bodies. These basic quantities are determined as a function of pore size obtained by filter procedures using mathematical morphology. The resulting Minkowski functions provide valuable information on pore size, pore surface area and pore topology having the potential to be linked to physical properties. The theoretical background and the related algorithms are presented and the approach is demonstrated for the structure of an arable topsoil obtained by X-ray micro tomography. We also discuss the fundamental problem of limited resolution which is critical for any attempt to quantify structural features at any scale.

Operation Manual for the Intensity Based Interrogation of Fibre Bragg Grating Arrays on Vibrating Structures

DTIC Science & Technology

2011-01-01

based demodulation approach for the measurement of strains, induced by structural vibrations, using Fiber Bragg Gratings ( FBG ). This companion...provide the Frequency Response Functions from a series of FBG arrays attached to a vibrating structure. RELEASE LIMITATION Approved for... FBG arrays attached to a vibrating structure. Both this technical note and its companion technical report are formal contributions to an

Taxonomic and functional patterns of macrobenthic communities on a high-Arctic shelf: A case study from the Laptev Sea

NASA Astrophysics Data System (ADS)

Kokarev, V. N.; Vedenin, A. A.; Basin, A. B.; Azovsky, A. I.

2017-11-01

The studies of functional structure of high-Arctic Ecosystems are scarce. We used data on benthic macrofauna from 500-km latitudinal transect in the eastern Laptev Sea, from the Lena delta to the continental shelf break, to describe spatial patterns in species composition, taxonomic and functional structure in relation to environmental factors. Both taxonomy-based approach and Biological Trait analysis yielded similar results and showed general depth-related gradient in benthic diversity and composition. This congruence between taxonomical and functional dimensions of community organization suggests that the same environmental factors (primarily riverine input and regime of sedimentation) have similar effect on both community structure and functioning. BTA also revealed a distinct functional structure of stations situated at the Eastern Lena valley, with dominance of motile, burrowing sub-surface deposit-feeders and absence of sedentary tube-dwelling forms. The overall spatial distribution of benthic assemblages corresponds well to that described there in preceding decades, evidencing the long-term stability of bottom ecosystem. Strong linear relationship between species and traits diversity, however, indicates low functional redundancy, which potentially makes the ecosystem susceptible to a species loss or structural shifts.

Little Mito: The Story of the Origins of a Cell.

ERIC Educational Resources Information Center

Vail, Stephanie; Herreid, Clyde Freeman

2002-01-01

Uses the case study method approach to teach about cell structure, organelle functions, the origin of eukaryotic cells, and evolution. Presents a story in which each structure of the cell is characterized with a personality. Includes teaching notes and classroom management strategies. (YDS)

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

Trevisanutto, Paolo E.; Vignale, Giovanni, E-mail: vignaleg@missouri.edu

Ab initio electronic structure calculations of two-dimensional layered structures are typically performed using codes that were developed for three-dimensional structures, which are periodic in all three directions. The introduction of a periodicity in the third direction (perpendicular to the layer) is completely artificial and may lead in some cases to spurious results and to difficulties in treating the action of external fields. In this paper we develop a new approach, which is “native” to quasi-2D materials, making use of basis function that are periodic in the plane, but atomic-like in the perpendicular direction. We show how some of the basicmore » tools of ab initio electronic structure theory — density functional theory, GW approximation and Bethe-Salpeter equation — are implemented in the new basis. We argue that the new approach will be preferable to the conventional one in treating the peculiarities of layered materials, including the long range of the unscreened Coulomb interaction in insulators, and the effects of strain, corrugations, and external fields.« less

Complex basis functions for molecular resonances: Methodology and applications

NASA Astrophysics Data System (ADS)

White, Alec; McCurdy, C. William; Head-Gordon, Martin

The computation of positions and widths of metastable electronic states is a challenge for molecular electronic structure theory because, in addition to the difficulty of the many-body problem, such states obey scattering boundary conditions. These resonances cannot be addressed with naïve application of traditional bound state electronic structure theory. Non-Hermitian electronic structure methods employing complex basis functions is one way that we may rigorously treat resonances within the framework of traditional electronic structure theory. In this talk, I will discuss our recent work in this area including the methodological extension from single determinant SCF-based approaches to highly correlated levels of wavefunction-based theory such as equation of motion coupled cluster and many-body perturbation theory. These approaches provide a hierarchy of theoretical methods for the computation of positions and widths of molecular resonances. Within this framework, we may also examine properties of resonances including the dependence of these parameters on molecular geometry. Some applications of these methods to temporary anions and dianions will also be discussed.

Outer-valence Electron Spectra of Prototypical Aromatic Heterocycles from an Optimally Tuned Range-Separated Hybrid Functional

PubMed Central

2014-01-01

Density functional theory with optimally tuned range-separated hybrid (OT-RSH) functionals has been recently suggested [Refaely-Abramson et al. Phys. Rev. Lett.2012, 109, 226405] as a nonempirical approach to predict the outer-valence electronic structure of molecules with the same accuracy as many-body perturbation theory. Here, we provide a quantitative evaluation of the OT-RSH approach by examining its performance in predicting the outer-valence electron spectra of several prototypical gas-phase molecules, from aromatic rings (benzene, pyridine, and pyrimidine) to more complex organic systems (terpyrimidinethiol and copper phthalocyanine). For a range up to several electronvolts away from the frontier orbital energies, we find that the outer-valence electronic structure obtained from the OT-RSH method agrees very well (typically within ∼0.1–0.2 eV) with both experimental photoemission and theoretical many-body perturbation theory data in the GW approximation. In particular, we find that with new strategies for an optimal choice of the short-range fraction of Fock exchange, the OT-RSH approach offers a balanced description of localized and delocalized states. We discuss in detail the sole exception found—a high-symmetry orbital, particular to small aromatic rings, which is relatively deep inside the valence state manifold. Overall, the OT-RSH method is an accurate DFT-based method for outer-valence electronic structure prediction for such systems and is of essentially the same level of accuracy as contemporary GW approaches, at a reduced computational cost. PMID:24839410

Discovery and characterization of natural products that act as pheromones in fish.

PubMed

Li, Ke; Buchinger, Tyler J; Li, Weiming

2018-06-20

Covering: up to 2018 Fish use a diverse collection of molecules to communicate with conspecifics. Since Karlson and Lüscher termed these molecules 'pheromones', chemists and biologists have joined efforts to characterize their structures and functions. In particular, the understanding of insect pheromones developed at a rapid pace, set, in part, by the use of bioassay-guided fractionation and natural product chemistry. Research on vertebrate pheromones, however, has progressed more slowly. Initially, biologists characterized fish pheromones by screening commercially available compounds suspected to act as pheromones based upon their physiological function. Such biology-driven screening has proven a productive approach to studying pheromones in fish. However, the many functions of fish pheromones and diverse metabolites that fish release make predicting pheromone identity difficult and necessitate approaches led by chemistry. Indeed, the few cases in which pheromone identification was led by natural product chemistry indicated novel or otherwise unpredicted compounds act as pheromones. Here, we provide a brief review of the approaches to identifying pheromones, placing particular emphasis on the promise of using natural product chemistry together with assays of biological activity. Several case studies illustrate bioassay-guided fractionation as an approach to pheromone identification in fish and the unexpected diversity of pheromone structures discovered by natural product chemistry. With recent advances in natural product chemistry, bioassay-guided fractionation is likely to unveil an even broader collection of pheromone structures and enable research that spans across disciplines.

DFT study of CdS-PVA film

NASA Astrophysics Data System (ADS)

Bala, Vaneeta; Tripathi, S. K.; Kumar, Ranjan

2015-02-01

Density functional theory has been applied to study cadmium sulphide-polyvinyl alcohol nanocomposite film. Structural models of two isotactic-polyvinyl alcohol (I-PVA) chains around one cadmium sulphide nanoparticle is considered in which each chain consists three monomer units of [-(CH2CH(OH))-]. All of the hydroxyl groups in I-PVA chains are directed to cadmium sulphide nanoparticle. Electronic and structural properties are investigated using ab-intio density functional code, SIESTA. Structural optimizations are done using local density approximations (LDA). The exchange correlation functional of LDA is parameterized by the Ceperley-Alder (CA) approach. The core electrons are represented by improved Troulier-Martins pseudopotentials. Densities of states clearly show the semiconducting nature of cadmium sulphide polyvinyl alcohol nanocomposite.

Guiding principles for peptide nanotechnology through directed discovery.

PubMed

Lampel, A; Ulijn, R V; Tuttle, T

2018-05-21

Life's diverse molecular functions are largely based on only a small number of highly conserved building blocks - the twenty canonical amino acids. These building blocks are chemically simple, but when they are organized in three-dimensional structures of tremendous complexity, new properties emerge. This review explores recent efforts in the directed discovery of functional nanoscale systems and materials based on these same amino acids, but that are not guided by copying or editing biological systems. The review summarises insights obtained using three complementary approaches of searching the sequence space to explore sequence-structure relationships for assembly, reactivity and complexation, namely: (i) strategic editing of short peptide sequences; (ii) computational approaches to predicting and comparing assembly behaviours; (iii) dynamic peptide libraries that explore the free energy landscape. These approaches give rise to guiding principles on controlling order/disorder, complexation and reactivity by peptide sequence design.

Experimental demonstration of two-dimensional hybrid waveguide-integrated plasmonic crystals on silicon-on-insulator platform

NASA Astrophysics Data System (ADS)

Ren, Guanghui; Yudistira, Didit; Nguyen, Thach G.; Khodasevych, Iryna; Schoenhardt, Steffen; Berean, Kyle J.; Hamm, Joachim M.; Hess, Ortwin; Mitchell, Arnan

2017-07-01

Nanoscale plasmonic structures can offer unique functionality due to extreme sub-wavelength optical confinement, but the realization of complex plasmonic circuits is hampered by high propagation losses. Hybrid approaches can potentially overcome this limitation, but only few practical approaches based on either single or few element arrays of nanoantennas on dielectric nanowire have been experimentally demonstrated. In this paper, we demonstrate a two dimensional hybrid photonic plasmonic crystal interfaced with a standard silicon photonic platform. Off resonance, we observe low loss propagation through our structure, while on resonance we observe strong propagation suppression and intense concentration of light into a dense lattice of nanoscale hot-spots on the surface providing clear evidence of a hybrid photonic plasmonic crystal bandgap. This fully integrated approach is compatible with established silicon-on-insulator (SOI) fabrication techniques and constitutes a significant step toward harnessing plasmonic functionality within SOI photonic circuits.

Extending existing structural identifiability analysis methods to mixed-effects models.

PubMed

Janzén, David L I; Jirstrand, Mats; Chappell, Michael J; Evans, Neil D

2018-01-01

The concept of structural identifiability for state-space models is expanded to cover mixed-effects state-space models. Two methods applicable for the analytical study of the structural identifiability of mixed-effects models are presented. The two methods are based on previously established techniques for non-mixed-effects models; namely the Taylor series expansion and the input-output form approach. By generating an exhaustive summary, and by assuming an infinite number of subjects, functions of random variables can be derived which in turn determine the distribution of the system's observation function(s). By considering the uniqueness of the analytical statistical moments of the derived functions of the random variables, the structural identifiability of the corresponding mixed-effects model can be determined. The two methods are applied to a set of examples of mixed-effects models to illustrate how they work in practice. Copyright © 2017 Elsevier Inc. All rights reserved.

Bioinformatic Analysis of the Contribution of Primer Sequences to Aptamer Structures

PubMed Central

Ellington, Andrew D.

2009-01-01

Aptamers are nucleic acid molecules selected in vitro to bind a particular ligand. While numerous experimental studies have examined the sequences, structures, and functions of individual aptamers, considerably fewer studies have applied bioinformatics approaches to try to infer more general principles from these individual studies. We have used a large Aptamer Database to parse the contributions of both random and constant regions to the secondary structures of more than 2000 aptamers. We find that the constant, primer-binding regions do not, in general, contribute significantly to aptamer structures. These results suggest that (a) binding function is not contributed to nor constrained by constant regions; (b) in consequence, the landscape of functional binding sequences is sparse but robust, favoring scenarios for short, functional nucleic acid sequences near origins; and (c) many pool designs for the selection of aptamers are likely to prove robust. PMID:18594898

Deformation behavior of dragonfly-inspired nodus structured wing in gliding flight through experimental visualization approach.

PubMed

Zhang, Sheng; Sunami, Yuta; Hashimoto, Hiromu

2018-04-10

Dragonfly has excellent flight performance and maneuverability due to the complex vein structure of wing. In this research, nodus as an important structural element of the dragonfly wing is investigated through an experimental visualization approach. Three vein structures were fabricated as, open-nodus structure, closed-nodus structure (with a flex-limiter) and rigid wing. The samples were conducted in a wind tunnel with a high speed camera to visualize the deformation of wing structure in order to study the function of nodus structured wing in gliding flight. According to the experimental results, nodus has a great influence on the flexibility of the wing structure. Moreover, the closed-nodus wing (with a flex-limiter) enables the vein structure to be flexible without losing the strength and rigidity of the joint. These findings enhance the knowledge of insect-inspired nodus structured wing and facilitate the application of Micro Air Vehicle (MAV) in gliding flight.

Architectural Environment: A Resource Kit.

ERIC Educational Resources Information Center

J.B. Speed Art Museum, Louisville, KY.

There are many ways to approach the investigation of architecture. One can look at structural form, climate and topography, the aesthetics of style and decoration, building function, historical factors, cultural meanings, or technology and techniques associated with construction. This resource kit touches upon a few of these approaches, ranging…

A machine-learned computational functional genomics-based approach to drug classification.

PubMed

Lötsch, Jörn; Ultsch, Alfred

2016-12-01

The public accessibility of "big data" about the molecular targets of drugs and the biological functions of genes allows novel data science-based approaches to pharmacology that link drugs directly with their effects on pathophysiologic processes. This provides a phenotypic path to drug discovery and repurposing. This paper compares the performance of a functional genomics-based criterion to the traditional drug target-based classification. Knowledge discovery in the DrugBank and Gene Ontology databases allowed the construction of a "drug target versus biological process" matrix as a combination of "drug versus genes" and "genes versus biological processes" matrices. As a canonical example, such matrices were constructed for classical analgesic drugs. These matrices were projected onto a toroid grid of 50 × 82 artificial neurons using a self-organizing map (SOM). The distance, respectively, cluster structure of the high-dimensional feature space of the matrices was visualized on top of this SOM using a U-matrix. The cluster structure emerging on the U-matrix provided a correct classification of the analgesics into two main classes of opioid and non-opioid analgesics. The classification was flawless with both the functional genomics and the traditional target-based criterion. The functional genomics approach inherently included the drugs' modulatory effects on biological processes. The main pharmacological actions known from pharmacological science were captures, e.g., actions on lipid signaling for non-opioid analgesics that comprised many NSAIDs and actions on neuronal signal transmission for opioid analgesics. Using machine-learned techniques for computational drug classification in a comparative assessment, a functional genomics-based criterion was found to be similarly suitable for drug classification as the traditional target-based criterion. This supports a utility of functional genomics-based approaches to computational system pharmacology for drug discovery and repurposing.

Justifying quasiparticle self-consistent schemes via gradient optimization in Baym-Kadanoff theory.

PubMed

Ismail-Beigi, Sohrab

2017-09-27

The question of which non-interacting Green's function 'best' describes an interacting many-body electronic system is both of fundamental interest as well as of practical importance in describing electronic properties of materials in a realistic manner. Here, we study this question within the framework of Baym-Kadanoff theory, an approach where one locates the stationary point of a total energy functional of the one-particle Green's function in order to find the total ground-state energy as well as all one-particle properties such as the density matrix, chemical potential, or the quasiparticle energy spectrum and quasiparticle wave functions. For the case of the Klein functional, our basic finding is that minimizing the length of the gradient of the total energy functional over non-interacting Green's functions yields a set of self-consistent equations for quasiparticles that is identical to those of the quasiparticle self-consistent GW (QSGW) (van Schilfgaarde et al 2006 Phys. Rev. Lett. 96 226402-4) approach, thereby providing an a priori justification for such an approach to electronic structure calculations. In fact, this result is general, applies to any self-energy operator, and is not restricted to any particular approximation, e.g., the GW approximation for the self-energy. The approach also shows that, when working in the basis of quasiparticle states, solving the diagonal part of the self-consistent Dyson equation is of primary importance while the off-diagonals are of secondary importance, a common observation in the electronic structure literature of self-energy calculations. Finally, numerical tests and analytical arguments show that when the Dyson equation produces multiple quasiparticle solutions corresponding to a single non-interacting state, minimizing the length of the gradient translates into choosing the solution with largest quasiparticle weight.

Structure/function relations of hemostatic nonwoven dressings based on greige cotton

USDA-ARS?s Scientific Manuscript database

A variety of natural and synthetic fibers are employed in hemostatic dressings. Here we demonstrate the use of greige cotton as a functional fiber, which when combined with hydrophilic and hydrophobic fibers in hydroentangled nonwoven materials, promotes accelerated clotting. A biophysical approach...

Nonlinear and Nonequilibrium Spin Injection in Magnetic Tunneling Junctions

NASA Astrophysics Data System (ADS)

Guo, Hong

2007-03-01

Quantitative analysis of charge and spin quantum transport in spintronic devices requires an atomistic first principles approach that can handle nonlinear and nonequilibrium transport conditions. We have developed an approach for this purpose based on real space density functional theory (DFT) carried out within the Keldysh nonequilibrium Green's function formalism (NEGF). We report theoretical analysis of nonlinear and nonequilibrium spin injection and quantum transport in Fe/MgO/Fe trilayer structures as a function of external bias voltage. Devices with well relaxed atomic structures and with FeO oxidization layers are investigated as a function of external bias voltage. We also report calculations of nonequilibrium spin injection into molecular layers and graphene. Comparisons to experimental data will be presented. Work in collaborations with: Derek Waldron, Vladimir Timochevski (McGill University); Ke Xia (Institute of Physics, Chinese Academy of Science, Beijing, China); Eric Zhu, Jian Wang (University of Hong Kong); Paul Haney, and Allan MacDonald (University of Texas at Austin).

Assessment of flood-induced changes of phytoplankton along a river-floodplain system using the morpho-functional approach.

PubMed

Mihaljević, Melita; Spoljarić, Dubravka; Stević, Filip; Zuna Pfeiffer, Tanja

2013-10-01

In this research, we aimed to find out how the differences in hydrological connectivity between the main river channel and adjacent floodplain influence the changes in phytoplankton community structure along a river-floodplain system. The research was performed in the River Danube floodplain (Croatian river section) in the period 2008-2009 characterised by different flooding pattern on an annual time scale. By utilising the morpho-functional approach and multivariate analyses, the flood-derived structural changes of phytoplankton were analysed. The lake stability during the isolation phase triggered the specific pattern of morpho-functional groups (MFG) which were characterised by cyanobacterial species achieving very high biomass. Adversely, the high water turbulence in the lake during the frequent and extreme flooding led to evident similarity between lake and river assemblages. Besides different diatom species (groups of small and large centrics and pennates), which are the most abundant representatives in the river phytoplankton, many other groups such as cryptophytes and colonial phytomonads appeared to indicate altered conditions in the floodplain driven by flooding. Having different functional properties, small centric diatom taxa sorted to only one MFG cannot clearly reflect environmental changes that are shown by the species-level pattern. Disadvantages in using the MFG approach highlight that it is still necessary to combine it with taxonomical approach in monitoring of phytoplankton in the river-floodplain ecosystems.

Investigating Sodium Storage Mechanisms in Tin Anodes: A Combined Pair Distribution Function Analysis, Density Functional Theory, and Solid-State NMR Approach.

PubMed

Stratford, Joshua M; Mayo, Martin; Allan, Phoebe K; Pecher, Oliver; Borkiewicz, Olaf J; Wiaderek, Kamila M; Chapman, Karena W; Pickard, Chris J; Morris, Andrew J; Grey, Clare P

2017-05-31

The alloying mechanism of high-capacity tin anodes for sodium-ion batteries is investigated using a combined theoretical and experimental approach. Ab initio random structure searching (AIRSS) and high-throughput screening using a species-swap method provide insights into a range of possible sodium-tin structures. These structures are linked to experiments using both average and local structure probes in the form of operando pair distribution function analysis, X-ray diffraction, and 23 Na solid-state nuclear magnetic resonance (ssNMR), along with ex situ 119 Sn ssNMR. Through this approach, we propose structures for the previously unidentified crystalline and amorphous intermediates. The first electrochemical process of sodium insertion into tin results in the conversion of crystalline tin into a layered structure consisting of mixed Na/Sn occupancy sites intercalated between planar hexagonal layers of Sn atoms (approximate stoichiometry NaSn 3 ). Following this, NaSn 2 , which is predicted to be thermodynamically stable by AIRSS, forms; this contains hexagonal layers closely related to NaSn 3 , but has no tin atoms between the layers. NaSn 2 is broken down into an amorphous phase of approximate composition Na 1.2 Sn. Reverse Monte Carlo refinements of an ab initio molecular dynamics model of this phase show that the predominant tin connectivity is chains. Further reaction with sodium results in the formation of structures containing Sn-Sn dumbbells, which interconvert through a solid-solution mechanism. These structures are based upon Na 5-x Sn 2 , with increasing occupancy of one of its sodium sites commensurate with the amount of sodium added. ssNMR results indicate that the final product, Na 15 Sn 4 , can store additional sodium atoms as an off-stoichiometry compound (Na 15+x Sn 4 ) in a manner similar to Li 15 Si 4 .

Investigating Sodium Storage Mechanisms in Tin Anodes: A Combined Pair Distribution Function Analysis, Density Functional Theory, and Solid-State NMR Approach

DOE PAGES

Stratford, Joshua M.; Mayo, Martin; Allan, Phoebe K.; ...

2017-05-04

Here, the alloying mechanism of high-capacity tin anodes for sodium-ion batteries is investigated using a combined theoretical and experimental approach. Ab initio random structure searching (AIRSS) and high-throughput screening using a species-swap method provide insights into a range of possible sodium–tin structures. These structures are linked to experiments using both average and local structure probes in the form of operando pair distribution function analysis, X-ray diffraction, and 23Na solid-state nuclear magnetic resonance (ssNMR), along with ex situ 119Sn ssNMR. Through this approach, we propose structures for the previously unidentified crystalline and amorphous intermediates. The first electrochemical process of sodium insertionmore » into tin results in the conversion of crystalline tin into a layered structure consisting of mixed Na/Sn occupancy sites intercalated between planar hexagonal layers of Sn atoms (approximate stoichiometry NaSn 3). Following this, NaSn 2, which is predicted to be thermodynamically stable by AIRSS, forms; this contains hexagonal layers closely related to NaSn 3, but has no tin atoms between the layers. NaSn 2 is broken down into an amorphous phase of approximate composition Na 1.2Sn. Reverse Monte Carlo refinements of an ab initio molecular dynamics model of this phase show that the predominant tin connectivity is chains. Further reaction with sodium results in the formation of structures containing Sn–Sn dumbbells, which interconvert through a solid-solution mechanism. These structures are based upon Na 5–xSn 2, with increasing occupancy of one of its sodium sites commensurate with the amount of sodium added. ssNMR results indicate that the final product, Na 15Sn 4, can store additional sodium atoms as an off-stoichiometry compound (Na 15+xSn 4) in a manner similar to Li 15Si 4.« less

Investigating Sodium Storage Mechanisms in Tin Anodes: A Combined Pair Distribution Function Analysis, Density Functional Theory, and Solid-State NMR Approach

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

Stratford, Joshua M.; Mayo, Martin; Allan, Phoebe K.

Here, the alloying mechanism of high-capacity tin anodes for sodium-ion batteries is investigated using a combined theoretical and experimental approach. Ab initio random structure searching (AIRSS) and high-throughput screening using a species-swap method provide insights into a range of possible sodium–tin structures. These structures are linked to experiments using both average and local structure probes in the form of operando pair distribution function analysis, X-ray diffraction, and 23Na solid-state nuclear magnetic resonance (ssNMR), along with ex situ 119Sn ssNMR. Through this approach, we propose structures for the previously unidentified crystalline and amorphous intermediates. The first electrochemical process of sodium insertionmore » into tin results in the conversion of crystalline tin into a layered structure consisting of mixed Na/Sn occupancy sites intercalated between planar hexagonal layers of Sn atoms (approximate stoichiometry NaSn 3). Following this, NaSn 2, which is predicted to be thermodynamically stable by AIRSS, forms; this contains hexagonal layers closely related to NaSn 3, but has no tin atoms between the layers. NaSn 2 is broken down into an amorphous phase of approximate composition Na 1.2Sn. Reverse Monte Carlo refinements of an ab initio molecular dynamics model of this phase show that the predominant tin connectivity is chains. Further reaction with sodium results in the formation of structures containing Sn–Sn dumbbells, which interconvert through a solid-solution mechanism. These structures are based upon Na 5–xSn 2, with increasing occupancy of one of its sodium sites commensurate with the amount of sodium added. ssNMR results indicate that the final product, Na 15Sn 4, can store additional sodium atoms as an off-stoichiometry compound (Na 15+xSn 4) in a manner similar to Li 15Si 4.« less

Ligand-guided optimization of CXCR4 homology models for virtual screening using a multiple chemotype approach

NASA Astrophysics Data System (ADS)

Neves, Marco A. C.; Simões, Sérgio; Sá e Melo, M. Luisa

2010-12-01

CXCR4 is a G-protein coupled receptor for CXCL12 that plays an important role in human immunodeficiency virus infection, cancer growth and metastasization, immune cell trafficking and WHIM syndrome. In the absence of an X-ray crystal structure, theoretical modeling of the CXCR4 receptor remains an important tool for structure-function analysis and to guide the discovery of new antagonists with potential clinical use. In this study, the combination of experimental data and molecular modeling approaches allowed the development of optimized ligand-receptor models useful for elucidation of the molecular determinants of small molecule binding and functional antagonism. The ligand-guided homology modeling approach used in this study explicitly re-shaped the CXCR4 binding pocket in order to improve discrimination between known CXCR4 antagonists and random decoys. Refinement based on multiple test-sets with small compounds from single chemotypes provided the best early enrichment performance. These results provide an important tool for structure-based drug design and virtual ligand screening of new CXCR4 antagonists.

Atrial fibrillation driver mechanisms: Insight from the isolated human heart.

PubMed

Csepe, Thomas A; Hansen, Brian J; Fedorov, Vadim V

2017-01-01

Although there have been great technological advances in the treatment of atrial fibrillation (AF), current therapies remain limited due to a narrow understanding of AF mechanisms in the human heart. This review will highlight our recent studies on explanted human hearts where we developed and employed a novel functional-structural mapping approach by integrating high-resolution simultaneous endo-epicardial and panoramic optical mapping with 3D gadolinium-enhanced MRI to define the spatiotemporal characteristics of AF drivers and their structural substrates. The results allow us to postulate that the primary mechanism of AF maintenance in human hearts is a limited number of localized intramural microanatomic reentrant AF drivers anchored to heart-specific 3D fibrotically insulated myobundle tracks, which may remain hidden to clinical single-surface electrode mapping. We suggest that ex vivo human heart studies, by using an integrated 3D functional and structural mapping approach, will help to reveal defining features of AF drivers as well as validate and improve clinical approaches to detect and target these AF drivers in patients with cardiac diseases. Copyright © 2016 Elsevier Inc. All rights reserved.

The Limits of Functional Analysis in the Study of Mass Communication.

ERIC Educational Resources Information Center

Anderson, James A.; Meyer, Timothy P.

The fundamental limits of the functional approach to the study of mass communication are embodied in two of its criticisms. The first weakness is in its logical structure and the second involves the limits that are set by known methods. Functional analysis has difficulties as a meaningful research perspective because the process of mass…

Functional MRI Preprocessing in Lesioned Brains: Manual Versus Automated Region of Interest Analysis

PubMed Central

Garrison, Kathleen A.; Rogalsky, Corianne; Sheng, Tong; Liu, Brent; Damasio, Hanna; Winstein, Carolee J.; Aziz-Zadeh, Lisa S.

2015-01-01

Functional magnetic resonance imaging (fMRI) has significant potential in the study and treatment of neurological disorders and stroke. Region of interest (ROI) analysis in such studies allows for testing of strong a priori clinical hypotheses with improved statistical power. A commonly used automated approach to ROI analysis is to spatially normalize each participant’s structural brain image to a template brain image and define ROIs using an atlas. However, in studies of individuals with structural brain lesions, such as stroke, the gold standard approach may be to manually hand-draw ROIs on each participant’s non-normalized structural brain image. Automated approaches to ROI analysis are faster and more standardized, yet are susceptible to preprocessing error (e.g., normalization error) that can be greater in lesioned brains. The manual approach to ROI analysis has high demand for time and expertise, but may provide a more accurate estimate of brain response. In this study, commonly used automated and manual approaches to ROI analysis were directly compared by reanalyzing data from a previously published hypothesis-driven cognitive fMRI study, involving individuals with stroke. The ROI evaluated is the pars opercularis of the inferior frontal gyrus. Significant differences were identified in task-related effect size and percent-activated voxels in this ROI between the automated and manual approaches to ROI analysis. Task interactions, however, were consistent across ROI analysis approaches. These findings support the use of automated approaches to ROI analysis in studies of lesioned brains, provided they employ a task interaction design. PMID:26441816

Graph coarse-graining reveals differences in the module-level structure of functional brain networks.

PubMed

Kujala, Rainer; Glerean, Enrico; Pan, Raj Kumar; Jääskeläinen, Iiro P; Sams, Mikko; Saramäki, Jari

2016-11-01

Networks have become a standard tool for analyzing functional magnetic resonance imaging (fMRI) data. In this approach, brain areas and their functional connections are mapped to the nodes and links of a network. Even though this mapping reduces the complexity of the underlying data, it remains challenging to understand the structure of the resulting networks due to the large number of nodes and links. One solution is to partition networks into modules and then investigate the modules' composition and relationship with brain functioning. While this approach works well for single networks, understanding differences between two networks by comparing their partitions is difficult and alternative approaches are thus necessary. To this end, we present a coarse-graining framework that uses a single set of data-driven modules as a frame of reference, enabling one to zoom out from the node- and link-level details. As a result, differences in the module-level connectivity can be understood in a transparent, statistically verifiable manner. We demonstrate the feasibility of the method by applying it to networks constructed from fMRI data recorded from 13 healthy subjects during rest and movie viewing. While independently partitioning the rest and movie networks is shown to yield little insight, the coarse-graining framework enables one to pinpoint differences in the module-level structure, such as the increased number of intra-module links within the visual cortex during movie viewing. In addition to quantifying differences due to external stimuli, the approach could also be applied in clinical settings, such as comparing patients with healthy controls. © 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Computational predictions of zinc oxide hollow structures

NASA Astrophysics Data System (ADS)

Tuoc, Vu Ngoc; Huan, Tran Doan; Thao, Nguyen Thi

2018-03-01

Nanoporous materials are emerging as potential candidates for a wide range of technological applications in environment, electronic, and optoelectronics, to name just a few. Within this active research area, experimental works are predominant while theoretical/computational prediction and study of these materials face some intrinsic challenges, one of them is how to predict porous structures. We propose a computationally and technically feasible approach for predicting zinc oxide structures with hollows at the nano scale. The designed zinc oxide hollow structures are studied with computations using the density functional tight binding and conventional density functional theory methods, revealing a variety of promising mechanical and electronic properties, which can potentially find future realistic applications.

Magnetic field effects on charge structure factors of gapped graphene structure

NASA Astrophysics Data System (ADS)

Rezania, Hamed; Tawoose, Nasrin

2018-02-01

We present the behaviors of dynamical and static charge susceptibilities of undoped gapped graphene using the Green's function approach in the context of tight binding model Hamiltonian. Specially, the effects of magnetic field on the plasmon modes of gapped graphene structure are investigated via calculating correlation function of charge density operators. Our results show the increase of magnetic field leads to disappear high frequency plasmon mode for gapped case. We also show that low frequency plasmon mode has not affected by increase of magnetic field and chemical potential. Finally the temperature dependence of static charge structure factor of gapp graphene structure is studied. The effects of both magnetic field and gap parameter on the static structure factor are discusses in details.

LSMS

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

Eisenbach, Markus; Li, Ying Wai; Liu, Xianglin

2017-12-01

LSMS is a first principles, Density Functional theory based, electronic structure code targeted mainly at materials applications. LSMS calculates the local spin density approximation to the diagonal part of the electron Green's function. The electron/spin density and energy are easily determined once the Green's function is known. Linear scaling with system size is achieved in the LSMS by using several unique properties of the real space multiple scattering approach to the Green's function.

Cityscape genetics: structural vs. functional connectivity of an urban lizard population.

PubMed

Beninde, Joscha; Feldmeier, Stephan; Werner, Maike; Peroverde, Daniel; Schulte, Ulrich; Hochkirch, Axel; Veith, Michael

2016-10-01

Functional connectivity is essential for the long-term persistence of populations. However, many studies assess connectivity with a focus on structural connectivity only. Cityscapes, namely urban landscapes, are particularly dynamic and include numerous potential anthropogenic barriers to animal movements, such as roads, traffic or buildings. To assess and compare structural connectivity of habitats and functional connectivity of gene flow of an urban lizard, we here combined species distribution models (SDMs) with an individual-based landscape genetic optimization procedure. The most important environmental factors of the SDMs are structural diversity and substrate type, with high and medium levels of structural diversity as well as open and rocky/gravel substrates contributing most to structural connectivity. By contrast, water cover was the best model of all environmental factors following landscape genetic optimization. The river is thus a major barrier to gene flow, while of the typical anthropogenic factors only buildings showed an effect. Nonetheless, using SDMs as a basis for landscape genetic optimization provided the highest ranked model for functional connectivity. Optimizing SDMs in this way can provide a sound basis for models of gene flow of the cityscape, and elsewhere, while presence-only and presence-absence modelling approaches showed differences in performance. Additionally, interpretation of results based on SDM factor importance can be misleading, dictating more thorough analyses following optimization of SDMs. Such approaches can be adopted for management strategies, for example aiming to connect native common wall lizard populations or disconnect them from non-native introduced populations, which are currently spreading in many cities in Central Europe. © 2016 John Wiley & Sons Ltd.

Final Technical Report for DE-SC0001878 [Theory and Simulation of Defects in Oxide Materials

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

Chelikowsky, James R.

2014-04-14

We explored a wide variety of oxide materials and related problems, including materials at the nanoscale and generic problems associated with oxide materials such as the development of more efficient computational tools to examine these materials. We developed and implemented methods to understand the optical and structural properties of oxides. For ground state properties, our work is predominantly based on pseudopotentials and density functional theory (DFT), including new functionals and going beyond the local density approximation (LDA): LDA+U. To study excited state properties (quasiparticle and optical excitations), we use time dependent density functional theory, the GW approach, and GW plusmore » Bethe-Salpeter equation (GW-BSE) methods based on a many-body Green function approaches. Our work focused on the structural, electronic, optical and magnetic properties of defects (such as oxygen vacancies) in hafnium oxide, titanium oxide (both bulk and clusters) and related materials. We calculated the quasiparticle defect states and charge transition levels of oxygen vacancies in monoclinic hafnia. we presented a milestone G0W0 study of two of the crystalline phases of dye-sensitized TiO{sub 2} clusters. We employed hybrid density functional theory to examine the electronic structure of sexithiophene/ZnO interfaces. To identify the possible effect of epitaxial strain on stabilization of the ferromagnetic state of LaCoO{sub 3} (LCO), we compare the total energy of the magnetic and nonmagnetic states of the strained theoretical bulk structure.« less

The 4D nucleome project.

PubMed

Dekker, Job; Belmont, Andrew S; Guttman, Mitchell; Leshyk, Victor O; Lis, John T; Lomvardas, Stavros; Mirny, Leonid A; O'Shea, Clodagh C; Park, Peter J; Ren, Bing; Politz, Joan C Ritland; Shendure, Jay; Zhong, Sheng

2017-09-13

The 4D Nucleome Network aims to develop and apply approaches to map the structure and dynamics of the human and mouse genomes in space and time with the goal of gaining deeper mechanistic insights into how the nucleus is organized and functions. The project will develop and benchmark experimental and computational approaches for measuring genome conformation and nuclear organization, and investigate how these contribute to gene regulation and other genome functions. Validated experimental technologies will be combined with biophysical approaches to generate quantitative models of spatial genome organization in different biological states, both in cell populations and in single cells.

The 4D Nucleome Project

PubMed Central

Dekker, Job; Belmont, Andrew S.; Guttman, Mitchell; Leshyk, Victor O.; Lis, John T.; Lomvardas, Stavros; Mirny, Leonid A.; O’Shea, Clodagh C.; Park, Peter J.; Ren, Bing; Ritland Politz, Joan C.; Shendure, Jay; Zhong, Sheng

2017-01-01

Preface The 4D Nucleome Network aims to develop and apply approaches to map the structure and dynamics of the human and mouse genomes in space and time with the goal of gaining deeper mechanistic understanding of how the nucleus is organized and functions. The project will develop and benchmark experimental and computational approaches for measuring genome conformation and nuclear organization, and investigate how these contribute to gene regulation and other genome functions. Validated experimental approaches will be combined with biophysical modeling to generate quantitative models of spatial genome organization in different biological states, both in cell populations and in single cells. PMID:28905911

A Two-Stage Approach to Missing Data: Theory and Application to Auxiliary Variables

ERIC Educational Resources Information Center

Savalei, Victoria; Bentler, Peter M.

2009-01-01

A well-known ad-hoc approach to conducting structural equation modeling with missing data is to obtain a saturated maximum likelihood (ML) estimate of the population covariance matrix and then to use this estimate in the complete data ML fitting function to obtain parameter estimates. This 2-stage (TS) approach is appealing because it minimizes a…

Sliding mode control: an approach to regulate nonlinear chemical processes

PubMed

Camacho; Smith

2000-01-01

A new approach for the design of sliding mode controllers based on a first-order-plus-deadtime model of the process, is developed. This approach results in a fixed structure controller with a set of tuning equations as a function of the characteristic parameters of the model. The controller performance is judged by simulations on two nonlinear chemical processes.

Bessel beam CARS of axially structured samples

NASA Astrophysics Data System (ADS)

Heuke, Sandro; Zheng, Juanjuan; Akimov, Denis; Heintzmann, Rainer; Schmitt, Michael; Popp, Jürgen

2015-06-01

We report about a Bessel beam CARS approach for axial profiling of multi-layer structures. This study presents an experimental implementation for the generation of CARS by Bessel beam excitation using only passive optical elements. Furthermore, an analytical expression is provided describing the generated anti-Stokes field by a homogeneous sample. Based on the concept of coherent transfer functions, the underling resolving power of axially structured geometries is investigated. It is found that through the non-linearity of the CARS process in combination with the folded illumination geometry continuous phase-matching is achieved starting from homogeneous samples up to spatial sample frequencies at twice of the pumping electric field wave. The experimental and analytical findings are modeled by the implementation of the Debye Integral and scalar Green function approach. Finally, the goal of reconstructing an axially layered sample is demonstrated on the basis of the numerically simulated modulus and phase of the anti-Stokes far-field radiation pattern.

Bessel beam CARS of axially structured samples.

PubMed

Heuke, Sandro; Zheng, Juanjuan; Akimov, Denis; Heintzmann, Rainer; Schmitt, Michael; Popp, Jürgen

2015-06-05

We report about a Bessel beam CARS approach for axial profiling of multi-layer structures. This study presents an experimental implementation for the generation of CARS by Bessel beam excitation using only passive optical elements. Furthermore, an analytical expression is provided describing the generated anti-Stokes field by a homogeneous sample. Based on the concept of coherent transfer functions, the underling resolving power of axially structured geometries is investigated. It is found that through the non-linearity of the CARS process in combination with the folded illumination geometry continuous phase-matching is achieved starting from homogeneous samples up to spatial sample frequencies at twice of the pumping electric field wave. The experimental and analytical findings are modeled by the implementation of the Debye Integral and scalar Green function approach. Finally, the goal of reconstructing an axially layered sample is demonstrated on the basis of the numerically simulated modulus and phase of the anti-Stokes far-field radiation pattern.

Vectorial model for guided-mode resonance gratings

NASA Astrophysics Data System (ADS)

Fehrembach, A.-L.; Gralak, B.; Sentenac, A.

2018-04-01

We propose a self-consistent vectorial method, based on a Green's function technique, to describe the resonances that appear in guided-mode resonance gratings. The model provides intuitive expressions of the reflectivity and transmittivity matrices of the structure, involving coupling integrals between the modes of a planar reference structure and radiative modes. When one mode is excited, the diffracted field for a suitable polarization can be written as the sum of a resonant and a nonresonant term, thus extending the intuitive approach used to explain the Fano shape of the resonance in scalar configurations. When two modes are excited, we derive a physical analysis in a configuration which requires a vectorial approach. We provide numerical validations of our model. From a technical point of view, we show how the Green's tensor of our planar reference structure can be expressed as two scalar Green's functions, and how to deal with the singularity of the Green's tensor.

Integrated microsystems packaging approach with LCP

NASA Astrophysics Data System (ADS)

Jaynes, Paul; Shacklette, Lawrence W.

2006-05-01

Within the government communication market there is an increasing push to further miniaturize systems with the use of chip-scale packages, flip-chip bonding, and other advances over traditional packaging techniques. Harris' approach to miniaturization includes these traditional packaging advances, but goes beyond this level of miniaturization by combining the functional and structural elements of a system, thus creating a Multi-Functional Structural Circuit (MFSC). An emerging high-frequency, near hermetic, thermoplastic electronic substrate material, Liquid Crystal Polymer (LCP), is the material that will enable the combination of the electronic circuit and the physical structure of the system. The first embodiment of this vision for Harris is the development of a battlefield acoustic sensor module. This paper will introduce LCP and its advantages for MFSC, present an example of the work that Harris has performed, and speak to LCP MFSCs' potential benefits to miniature communications modules and sensor platforms.

Methods to assess Drosophila heart development, function and aging

PubMed Central

Ocorr, Karen; Vogler, Georg; Bodmer, Rolf

2014-01-01

In recent years the Drosophila heart has become an established model of many different aspects of human cardiac disease. This model has allowed identification of disease-causing mechanisms underlying congenital heart disease and cardiomyopathies and has permitted the study underlying genetic, metabolic and age-related contributions to heart function. In this review we discuss methods currently employed in the analysis of the Drosophila heart structure and function, such as optical methods to infer heart function and performance, electrophysiological and mechanical approaches to characterize cardiac tissue properties, and conclude with histological techniques used in the study of heart development and adult structure. PMID:24727147

Bioinspired Wood Nanotechnology for Functional Materials.

PubMed

Berglund, Lars A; Burgert, Ingo

2018-05-01

It is a challenging task to realize the vision of hierarchically structured nanomaterials for large-scale applications. Herein, the biomaterial wood as a large-scale biotemplate for functionalization at multiple scales is discussed, to provide an increased property range to this renewable and CO 2 -storing bioresource, which is available at low cost and in large quantities. The Progress Report reviews the emerging field of functional wood materials in view of the specific features of the structural template and novel nanotechnological approaches for the development of wood-polymer composites and wood-mineral hybrids for advanced property profiles and new functions. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Mobile communications satellite antenna flight experiment definition

NASA Technical Reports Server (NTRS)

Freeland, Robert E.

1987-01-01

Results of a NASA-sponsored study to determine the technical feasibility and cost of a Shuttle-based flight experiment specifically intended for the MSAT commercial user community are presented. The experiment will include demonstrations of technology in the areas of radio frequency, sensing and control, and structures. The results of the structural subsystem study summarized here include experiment objective and technical approach, experiment structural description, structure/environment interactions, structural characterization, thermal characterization, structural measurement system, and experiment functional description.

Structure of a viscoplastic theory

NASA Technical Reports Server (NTRS)

Freed, Alan D.

1988-01-01

The general structure of a viscoplastic theory is developed from physical and thermodynamical considerations. The flow equation is of classical form. The dynamic recovery approach is shown to be superior to the hardening function approach for incorporating nonlinear strain hardening into the material response through the evolutionary equation for back stress. A novel approach for introducing isotropic strain hardening into the theory is presented, which results in a useful simplification. In particular, the limiting stress for the kinematic saturation of state (not the drag stress) is the chosen scalar-valued state variable. The resulting simplification is that there is no coupling between dynamic and thermal recovery terms in each evolutionary equation. The derived theory of viscoplasticity has the structure of a two-surface plasticity theory when the response is plasticlike, and the structure of a Bailey-Orowan creep theory when the response is creeplike.

Mold-Based Application of Laser-Induced Periodic Surface Structures (LIPSS) on Biomaterials for Nanoscale Patterning.

PubMed

Hendrikson, Wim; Masman-Bakker, Wendy; van Bochove, Bas; Skolski, Johann; Eichstädt, Justus; Koopman, Bart; van Blitterswijk, Clemens; Grijpma, Dirk; Römer, Gert-Willem; Moroni, Lorenzo; Rouwkema, Jeroen

2016-01-01

Laser-induced periodic surface structures (LIPSS) are highly regular, but at the same time contain a certain level of disorder. The application of LIPSS is a promising method to functionalize biomaterials. However, the absorption of laser energy of most polymer biomaterials is insufficient for the direct application of LIPSS. Here, we report the application of LIPSS to relevant biomaterials using a two-step approach. First, LIPSS are fabricated on a stainless steel surface. Then, the structures are replicated onto biomaterials using the steel as a mold. Results show that LIPSS can be transferred successfully using this approach, and that human mesenchymal stromal cells respond to the transferred structures. With this approach, the range of biomaterials that can be supplied with LIPSS increases dramatically. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Ecological connectivity networks in rapidly expanding cities.

PubMed

Nor, Amal Najihah M; Corstanje, Ron; Harris, Jim A; Grafius, Darren R; Siriwardena, Gavin M

2017-06-01

Urban expansion increases fragmentation of the landscape. In effect, fragmentation decreases connectivity, causes green space loss and impacts upon the ecology and function of green space. Restoration of the functionality of green space often requires restoring the ecological connectivity of this green space within the city matrix. However, identifying ecological corridors that integrate different structural and functional connectivity of green space remains vague. Assessing connectivity for developing an ecological network by using efficient models is essential to improve these networks under rapid urban expansion. This paper presents a novel methodological approach to assess and model connectivity for the Eurasian tree sparrow ( Passer montanus ) and Yellow-vented bulbul ( Pycnonotus goiavier ) in three cities (Kuala Lumpur, Malaysia; Jakarta, Indonesia and Metro Manila, Philippines). The approach identifies potential priority corridors for ecological connectivity networks. The study combined circuit models, connectivity analysis and least-cost models to identify potential corridors by integrating structure and function of green space patches to provide reliable ecological connectivity network models in the cities. Relevant parameters such as landscape resistance and green space structure (vegetation density, patch size and patch distance) were derived from an expert and literature-based approach based on the preference of bird behaviour. The integrated models allowed the assessment of connectivity for both species using different measures of green space structure revealing the potential corridors and least-cost pathways for both bird species at the patch sites. The implementation of improvements to the identified corridors could increase the connectivity of green space. This study provides examples of how combining models can contribute to the improvement of ecological networks in rapidly expanding cities and demonstrates the usefulness of such models for biodiversity conservation and urban planning.

A Study of Penalty Function Methods for Constraint Handling with Genetic Algorithm

NASA Technical Reports Server (NTRS)

Ortiz, Francisco

2004-01-01

COMETBOARDS (Comparative Evaluation Testbed of Optimization and Analysis Routines for Design of Structures) is a design optimization test bed that can evaluate the performance of several different optimization algorithms. A few of these optimization algorithms are the sequence of unconstrained minimization techniques (SUMT), sequential linear programming (SLP) and the sequential quadratic programming techniques (SQP). A genetic algorithm (GA) is a search technique that is based on the principles of natural selection or "survival of the fittest". Instead of using gradient information, the GA uses the objective function directly in the search. The GA searches the solution space by maintaining a population of potential solutions. Then, using evolving operations such as recombination, mutation and selection, the GA creates successive generations of solutions that will evolve and take on the positive characteristics of their parents and thus gradually approach optimal or near-optimal solutions. By using the objective function directly in the search, genetic algorithms can be effectively applied in non-convex, highly nonlinear, complex problems. The genetic algorithm is not guaranteed to find the global optimum, but it is less likely to get trapped at a local optimum than traditional gradient-based search methods when the objective function is not smooth and generally well behaved. The purpose of this research is to assist in the integration of genetic algorithm (GA) into COMETBOARDS. COMETBOARDS cast the design of structures as a constrained nonlinear optimization problem. One method used to solve constrained optimization problem with a GA to convert the constrained optimization problem into an unconstrained optimization problem by developing a penalty function that penalizes infeasible solutions. There have been several suggested penalty function in the literature each with there own strengths and weaknesses. A statistical analysis of some suggested penalty functions is performed in this study. Also, a response surface approach to robust design is used to develop a new penalty function approach. This new penalty function approach is then compared with the other existing penalty functions.

Interference between extrinsic and intrinsic losses in x-ray absorption fine structure

NASA Astrophysics Data System (ADS)

Campbell, L.; Hedin, L.; Rehr, J. J.; Bardyszewski, W.

2002-02-01

The interference between extrinsic and intrinsic losses in x-ray absorption fine structure (XAFS) is treated within a Green's-function formalism, without explicit reference to final states. The approach makes use of a quasiboson representation of excitations and perturbation theory in the interaction potential between electrons and quasibosons. These losses lead to an asymmetric broadening of the main quasiparticle peak plus an energy-dependent satellite in the spectral function. The x-ray absorption spectra (XAS) is then given by a convolution of an effective spectral function over a one-electron cross section. It is shown that extrinsic and intrinsic losses tend to cancel near excitation thresholds, and correspondingly, the strength in the main peak increases. At high energies, the theory crosses over to the sudden approximation. These results thus explain the observed weakness of multielectron excitations in XAS. The approach is applied to estimate the many-body corrections to XAFS, beyond the usual mean-free path, using a phasor summation over the spectral function. The asymmetry of the spectral function gives rise to an additional many-body phase shift in the XAFS formula.

Fetal functional imaging portrays heterogeneous development of emerging human brain networks

PubMed Central

Jakab, András; Schwartz, Ernst; Kasprian, Gregor; Gruber, Gerlinde M.; Prayer, Daniela; Schöpf, Veronika; Langs, Georg

2014-01-01

The functional connectivity architecture of the adult human brain enables complex cognitive processes, and exhibits a remarkably complex structure shared across individuals. We are only beginning to understand its heterogeneous structure, ranging from a strongly hierarchical organization in sensorimotor areas to widely distributed networks in areas such as the parieto-frontal cortex. Our study relied on the functional magnetic resonance imaging (fMRI) data of 32 fetuses with no detectable morphological abnormalities. After adapting functional magnetic resonance acquisition, motion correction, and nuisance signal reduction procedures of resting-state functional data analysis to fetuses, we extracted neural activity information for major cortical and subcortical structures. Resting fMRI networks were observed for increasing regional functional connectivity from 21st to 38th gestational weeks (GWs) with a network-based statistical inference approach. The overall connectivity network, short range, and interhemispheric connections showed sigmoid expansion curve peaking at the 26–29 GW. In contrast, long-range connections exhibited linear increase with no periods of peaking development. Region-specific increase of functional signal synchrony followed a sequence of occipital (peak: 24.8 GW), temporal (peak: 26 GW), frontal (peak: 26.4 GW), and parietal expansion (peak: 27.5 GW). We successfully adapted functional neuroimaging and image post-processing approaches to correlate macroscopical scale activations in the fetal brain with gestational age. This in vivo study reflects the fact that the mid-fetal period hosts events that cause the architecture of the brain circuitry to mature, which presumably manifests in increasing strength of intra- and interhemispheric functional macro connectivity. PMID:25374531

Fetal functional imaging portrays heterogeneous development of emerging human brain networks.

PubMed

Jakab, András; Schwartz, Ernst; Kasprian, Gregor; Gruber, Gerlinde M; Prayer, Daniela; Schöpf, Veronika; Langs, Georg

2014-01-01

The functional connectivity architecture of the adult human brain enables complex cognitive processes, and exhibits a remarkably complex structure shared across individuals. We are only beginning to understand its heterogeneous structure, ranging from a strongly hierarchical organization in sensorimotor areas to widely distributed networks in areas such as the parieto-frontal cortex. Our study relied on the functional magnetic resonance imaging (fMRI) data of 32 fetuses with no detectable morphological abnormalities. After adapting functional magnetic resonance acquisition, motion correction, and nuisance signal reduction procedures of resting-state functional data analysis to fetuses, we extracted neural activity information for major cortical and subcortical structures. Resting fMRI networks were observed for increasing regional functional connectivity from 21st to 38th gestational weeks (GWs) with a network-based statistical inference approach. The overall connectivity network, short range, and interhemispheric connections showed sigmoid expansion curve peaking at the 26-29 GW. In contrast, long-range connections exhibited linear increase with no periods of peaking development. Region-specific increase of functional signal synchrony followed a sequence of occipital (peak: 24.8 GW), temporal (peak: 26 GW), frontal (peak: 26.4 GW), and parietal expansion (peak: 27.5 GW). We successfully adapted functional neuroimaging and image post-processing approaches to correlate macroscopical scale activations in the fetal brain with gestational age. This in vivo study reflects the fact that the mid-fetal period hosts events that cause the architecture of the brain circuitry to mature, which presumably manifests in increasing strength of intra- and interhemispheric functional macro connectivity.

A Bayesian spatial model for neuroimaging data based on biologically informed basis functions.

PubMed

Huertas, Ismael; Oldehinkel, Marianne; van Oort, Erik S B; Garcia-Solis, David; Mir, Pablo; Beckmann, Christian F; Marquand, Andre F

2017-11-01

The dominant approach to neuroimaging data analysis employs the voxel as the unit of computation. While convenient, voxels lack biological meaning and their size is arbitrarily determined by the resolution of the image. Here, we propose a multivariate spatial model in which neuroimaging data are characterised as a linearly weighted combination of multiscale basis functions which map onto underlying brain nuclei or networks or nuclei. In this model, the elementary building blocks are derived to reflect the functional anatomy of the brain during the resting state. This model is estimated using a Bayesian framework which accurately quantifies uncertainty and automatically finds the most accurate and parsimonious combination of basis functions describing the data. We demonstrate the utility of this framework by predicting quantitative SPECT images of striatal dopamine function and we compare a variety of basis sets including generic isotropic functions, anatomical representations of the striatum derived from structural MRI, and two different soft functional parcellations of the striatum derived from resting-state fMRI (rfMRI). We found that a combination of ∼50 multiscale functional basis functions accurately represented the striatal dopamine activity, and that functional basis functions derived from an advanced parcellation technique known as Instantaneous Connectivity Parcellation (ICP) provided the most parsimonious models of dopamine function. Importantly, functional basis functions derived from resting fMRI were more accurate than both structural and generic basis sets in representing dopamine function in the striatum for a fixed model order. We demonstrate the translational validity of our framework by constructing classification models for discriminating parkinsonian disorders and their subtypes. Here, we show that ICP approach is the only basis set that performs well across all comparisons and performs better overall than the classical voxel-based approach. This spatial model constitutes an elegant alternative to voxel-based approaches in neuroimaging studies; not only are their atoms biologically informed, they are also adaptive to high resolutions, represent high dimensions efficiently, and capture long-range spatial dependencies, which are important and challenging objectives for neuroimaging data. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Computer analysis of protein functional sites projection on exon structure of genes in Metazoa.

PubMed

Medvedeva, Irina V; Demenkov, Pavel S; Ivanisenko, Vladimir A

2015-01-01

Study of the relationship between the structural and functional organization of proteins and their coding genes is necessary for an understanding of the evolution of molecular systems and can provide new knowledge for many applications for designing proteins with improved medical and biological properties. It is well known that the functional properties of proteins are determined by their functional sites. Functional sites are usually represented by a small number of amino acid residues that are distantly located from each other in the amino acid sequence. They are highly conserved within their functional group and vary significantly in structure between such groups. According to this facts analysis of the general properties of the structural organization of the functional sites at the protein level and, at the level of exon-intron structure of the coding gene is still an actual problem. One approach to this analysis is the projection of amino acid residue positions of the functional sites along with the exon boundaries to the gene structure. In this paper, we examined the discontinuity of the functional sites in the exon-intron structure of genes and the distribution of lengths and phases of the functional site encoding exons in vertebrate genes. We have shown that the DNA fragments coding the functional sites were in the same exons, or in close exons. The observed tendency to cluster the exons that code functional sites which could be considered as the unit of protein evolution. We studied the characteristics of the structure of the exon boundaries that code, and do not code, functional sites in 11 Metazoa species. This is accompanied by a reduced frequency of intercodon gaps (phase 0) in exons encoding the amino acid residue functional site, which may be evidence of the existence of evolutionary limitations to the exon shuffling. These results characterize the features of the coding exon-intron structure that affect the functionality of the encoded protein and allow a better understanding of the emergence of biological diversity.

Hydration of Caffeine at High Temperature by Neutron Scattering and Simulation Studies.

PubMed

Tavagnacco, L; Brady, J W; Bruni, F; Callear, S; Ricci, M A; Saboungi, M L; Cesàro, A

2015-10-22

The solvation of caffeine in water is examined with neutron diffraction experiments at 353 K. The experimental data, obtained by taking advantage of isotopic H/D substitution in water, were analyzed by empirical potential structure refinement (EPSR) in order to extract partial structure factors and site-site radial distribution functions. In parallel, molecular dynamics (MD) simulations were carried out to interpret the data and gain insight into the intermolecular interactions in the solutions and the solvation process. The results obtained with the two approaches evidence differences in the individual radial distribution functions, although both confirm the presence of caffeine stacks at this temperature. The two approaches point to different accessibility of water to the caffeine sites due to different stacking configurations.

Inference of Functionally-Relevant N-acetyltransferase Residues Based on Statistical Correlations.

PubMed

Neuwald, Andrew F; Altschul, Stephen F

2016-12-01

Over evolutionary time, members of a superfamily of homologous proteins sharing a common structural core diverge into subgroups filling various functional niches. At the sequence level, such divergence appears as correlations that arise from residue patterns distinct to each subgroup. Such a superfamily may be viewed as a population of sequences corresponding to a complex, high-dimensional probability distribution. Here we model this distribution as hierarchical interrelated hidden Markov models (hiHMMs), which describe these sequence correlations implicitly. By characterizing such correlations one may hope to obtain information regarding functionally-relevant properties that have thus far evaded detection. To do so, we infer a hiHMM distribution from sequence data using Bayes' theorem and Markov chain Monte Carlo (MCMC) sampling, which is widely recognized as the most effective approach for characterizing a complex, high dimensional distribution. Other routines then map correlated residue patterns to available structures with a view to hypothesis generation. When applied to N-acetyltransferases, this reveals sequence and structural features indicative of functionally important, yet generally unknown biochemical properties. Even for sets of proteins for which nothing is known beyond unannotated sequences and structures, this can lead to helpful insights. We describe, for example, a putative coenzyme-A-induced-fit substrate binding mechanism mediated by arginine residue switching between salt bridge and π-π stacking interactions. A suite of programs implementing this approach is available (psed.igs.umaryland.edu).

Exploring Protein Dynamics Space: The Dynasome as the Missing Link between Protein Structure and Function

PubMed Central

Hensen, Ulf; Meyer, Tim; Haas, Jürgen; Rex, René; Vriend, Gert; Grubmüller, Helmut

2012-01-01

Proteins are usually described and classified according to amino acid sequence, structure or function. Here, we develop a minimally biased scheme to compare and classify proteins according to their internal mobility patterns. This approach is based on the notion that proteins not only fold into recurring structural motifs but might also be carrying out only a limited set of recurring mobility motifs. The complete set of these patterns, which we tentatively call the dynasome, spans a multi-dimensional space with axes, the dynasome descriptors, characterizing different aspects of protein dynamics. The unique dynamic fingerprint of each protein is represented as a vector in the dynasome space. The difference between any two vectors, consequently, gives a reliable measure of the difference between the corresponding protein dynamics. We characterize the properties of the dynasome by comparing the dynamics fingerprints obtained from molecular dynamics simulations of 112 proteins but our approach is, in principle, not restricted to any specific source of data of protein dynamics. We conclude that: 1. the dynasome consists of a continuum of proteins, rather than well separated classes. 2. For the majority of proteins we observe strong correlations between structure and dynamics. 3. Proteins with similar function carry out similar dynamics, which suggests a new method to improve protein function annotation based on protein dynamics. PMID:22606222

Estimation of health effects of prenatal methylmercury exposure using structural equation models.

PubMed

Budtz-Jørgensen, Esben; Keiding, Niels; Grandjean, Philippe; Weihe, Pal

2002-10-14

Observational studies in epidemiology always involve concerns regarding validity, especially measurement error, confounding, missing data, and other problems that may affect the study outcomes. Widely used standard statistical techniques, such as multiple regression analysis, may to some extent adjust for these shortcomings. However, structural equations may incorporate most of these considerations, thereby providing overall adjusted estimations of associations. This approach was used in a large epidemiological data set from a prospective study of developmental methyl-mercury toxicity. Structural equation models were developed for assessment of the association between biomarkers of prenatal mercury exposure and neuropsychological test scores in 7 year old children. Eleven neurobehavioral outcomes were grouped into motor function and verbally mediated function. Adjustment for local dependence and item bias was necessary for a satisfactory fit of the model, but had little impact on the estimated mercury effects. The mercury effect on the two latent neurobehavioral functions was similar to the strongest effects seen for individual test scores of motor function and verbal skills. Adjustment for contaminant exposure to poly chlorinated biphenyls (PCBs) changed the estimates only marginally, but the mercury effect could be reduced to non-significance by assuming a large measurement error for the PCB biomarker. The structural equation analysis allows correction for measurement error in exposure variables, incorporation of multiple outcomes and incomplete cases. This approach therefore deserves to be applied more frequently in the analysis of complex epidemiological data sets.

Towards aspect-oriented functional–structural plant modelling

PubMed Central

Cieslak, Mikolaj; Seleznyova, Alla N.; Prusinkiewicz, Przemyslaw; Hanan, Jim

2011-01-01

Background and Aims Functional–structural plant models (FSPMs) are used to integrate knowledge and test hypotheses of plant behaviour, and to aid in the development of decision support systems. A significant amount of effort is being put into providing a sound methodology for building them. Standard techniques, such as procedural or object-oriented programming, are not suited for clearly separating aspects of plant function that criss-cross between different components of plant structure, which makes it difficult to reuse and share their implementations. The aim of this paper is to present an aspect-oriented programming approach that helps to overcome this difficulty. Methods The L-system-based plant modelling language L+C was used to develop an aspect-oriented approach to plant modelling based on multi-modules. Each element of the plant structure was represented by a sequence of L-system modules (rather than a single module), with each module representing an aspect of the element's function. Separate sets of productions were used for modelling each aspect, with context-sensitive rules facilitated by local lists of modules to consider/ignore. Aspect weaving or communication between aspects was made possible through the use of pseudo-L-systems, where the strict-predecessor of a production rule was specified as a multi-module. Key Results The new approach was used to integrate previously modelled aspects of carbon dynamics, apical dominance and biomechanics with a model of a developing kiwifruit shoot. These aspects were specified independently and their implementation was based on source code provided by the original authors without major changes. Conclusions This new aspect-oriented approach to plant modelling is well suited for studying complex phenomena in plant science, because it can be used to integrate separate models of individual aspects of plant development and function, both previously constructed and new, into clearly organized, comprehensive FSPMs. In a future work, this approach could be further extended into an aspect-oriented programming language for FSPMs. PMID:21724653

EVALUATING THE INTEGRITY OF SALT MARSHES IN NARRAGANSETT BAY SUBESTUARIES USING A WATESHED APPROACH

EPA Science Inventory

A watershed approach to examine measures of structure and function in salt marshes of similar geomorphology and hydrology in Narragansett Bay was used to develop a reference system for evaluating salt marsh integrity. We describe integrity as the capability of a salt marsh to pro...

Confidence Intervals for a Semiparametric Approach to Modeling Nonlinear Relations among Latent Variables

ERIC Educational Resources Information Center

Pek, Jolynn; Losardo, Diane; Bauer, Daniel J.

2011-01-01

Compared to parametric models, nonparametric and semiparametric approaches to modeling nonlinearity between latent variables have the advantage of recovering global relationships of unknown functional form. Bauer (2005) proposed an indirect application of finite mixtures of structural equation models where latent components are estimated in the…

Understand protein functions by comparing the similarity of local structural environments.

PubMed

Chen, Jiawen; Xie, Zhong-Ru; Wu, Yinghao

2017-02-01

The three-dimensional structures of proteins play an essential role in regulating binding between proteins and their partners, offering a direct relationship between structures and functions of proteins. It is widely accepted that the function of a protein can be determined if its structure is similar to other proteins whose functions are known. However, it is also observed that proteins with similar global structures do not necessarily correspond to the same function, while proteins with very different folds can share similar functions. This indicates that function similarity is originated from the local structural information of proteins instead of their global shapes. We assume that proteins with similar local environments prefer binding to similar types of molecular targets. In order to testify this assumption, we designed a new structural indicator to define the similarity of local environment between residues in different proteins. This indicator was further used to calculate the probability that a given residue binds to a specific type of structural neighbors, including DNA, RNA, small molecules and proteins. After applying the method to a large-scale non-redundant database of proteins, we show that the positive signal of binding probability calculated from the local structural indicator is statistically meaningful. In summary, our studies suggested that the local environment of residues in a protein is a good indicator to recognize specific binding partners of the protein. The new method could be a potential addition to a suite of existing template-based approaches for protein function prediction. Copyright © 2016 Elsevier B.V. All rights reserved.

Structural and functional predictors of regional peak pressures under the foot during walking.

PubMed

Morag, E; Cavanagh, P R

1999-04-01

The objective of this study was to identify structural and functional factors which are predictors of peak pressure underneath the human foot during walking. Peak plantar pressure during walking and eight data sets of structural and functional measures were collected on 55 asymptomatic subjects between 20 and 70 yr. A best subset regression approach was used to establish models which predicted peak regional pressure under the foot. Potential predictor variables were chosen from physical characteristics, anthropometric data, passive range of motion (PROM), measurements from standardized weight bearing foot radiographs, mechanical properties of the plantar soft tissue, stride parameters, foot motion in 3D, and EMG during walking. Peak pressure values under the rearfoot, midfoot, MTH1, and hallux were measured. Heel pressure was a function of linear kinematics, longitudinal arch structure, thickness of plantar soft tissue, and age. Midfoot pressure prediction was dominated by arch structure, while MTH1 pressure was a function of radiographic measurements, talo-crural joint motion, and gastrocnemius activity. Hallux pressure was a function of structural measures and MTP1 joint motion. Foot structure and function predicted only approximately 50% of the variance in peak pressure, although the relative contributions in different anatomical regions varied dramatically. Structure was dominant in predicting peak pressure under the midfoot and MTH1, while both structure and function were important at the heel and hallux. The predictive models developed in this study give insight into potential etiological factors associated with elevated plantar pressure. They also provide direction for future studies designed to reduce elevated pressure in "at-risk" patients.

The proteome: structure, function and evolution

PubMed Central

Fleming, Keiran; Kelley, Lawrence A; Islam, Suhail A; MacCallum, Robert M; Muller, Arne; Pazos, Florencio; Sternberg, Michael J.E

2006-01-01

This paper reports two studies to model the inter-relationships between protein sequence, structure and function. First, an automated pipeline to provide a structural annotation of proteomes in the major genomes is described. The results are stored in a database at Imperial College, London (3D-GENOMICS) that can be accessed at www.sbg.bio.ic.ac.uk. Analysis of the assignments to structural superfamilies provides evolutionary insights. 3D-GENOMICS is being integrated with related proteome annotation data at University College London and the European Bioinformatics Institute in a project known as e-protein (http://www.e-protein.org/). The second topic is motivated by the developments in structural genomics projects in which the structure of a protein is determined prior to knowledge of its function. We have developed a new approach PHUNCTIONER that uses the gene ontology (GO) classification to supervise the extraction of the sequence signal responsible for protein function from a structure-based sequence alignment. Using GO we can obtain profiles for a range of specificities described in the ontology. In the region of low sequence similarity (around 15%), our method is more accurate than assignment from the closest structural homologue. The method is also able to identify the specific residues associated with the function of the protein family. PMID:16524832

Divergence of Structure and Function in the Haloacid Dehalogenase Enzyme Superfamily: Bacteroides thetaiotaomicron BT2127 is an Inorganic Pyrophosphatase+

PubMed Central

Huang, Hua; Yury, Patskovsky; Toro, Rafael; Farelli, Jeremiah D.; Pandya, Chetanya; Almo, Steven C.; Allen, Karen N.; Dunaway-Mariano, Debra

2012-01-01

The explosion of protein sequence information requires that current strategies for function assignment must evolve to complement experimental approaches with computationally-based function prediction. This necessitates the development of strategies based on the identification of sequence markers in the form of specificity determinants and a more informed definition of orthologues. Herein, we have undertaken the function assignment of the unknown Haloalkanoate Dehalogenase superfamily member BT2127 (Uniprot accession # Q8A5V9) from Bacteroides thetaiotaomicron using an integrated bioinformatics/structure/mechanism approach. The substrate specificity profile and steady-state rate constants of BT2127 (with kcat/Km value for pyrophosphate of ∼1 × 105 M−1 s−1), together with the gene context, supports the assigned in vivo function as an inorganic pyrophosphatase. The X-ray structural analysis of the wild-type BT2127 and several variants generated by site-directed mutagenesis shows that substrate discrimination is based, in part, on active site space restrictions imposed by the cap domain (specifically by residues Tyr76 and Glu47). Structure guided site directed mutagenesis coupled with kinetic analysis of the mutant enzymes identified the residues required for catalysis, substrate binding, and domain-domain association. Based on this structure-function analysis, the catalytic residues Asp11, Asp13, Thr113, and Lys147 as well the metal binding residues Asp171, Asn172 and Glu47 were used as markers to confirm BT2127 orthologues identified via sequence searches. This bioinformatic analysis demonstrated that the biological range of BT2127 orthologue is restricted to the phylum Bacteroidetes/Chlorobi. The key structural determinants in the divergence of BT2127 and its closest homologue β-phosphoglucomutase control the leaving group size (phosphate vs. glucose-phosphate) and the position of the Asp acid/base in the open vs. closed conformations. HADSF pyrophosphatases represent a third mechanistic and fold type for bacterial pyrophosphatases. PMID:21894910

Modelling and enhanced molecular dynamics to steer structure-based drug discovery.

PubMed

Kalyaanamoorthy, Subha; Chen, Yi-Ping Phoebe

2014-05-01

The ever-increasing gap between the availabilities of the genome sequences and the crystal structures of proteins remains one of the significant challenges to the modern drug discovery efforts. The knowledge of structure-dynamics-functionalities of proteins is important in order to understand several key aspects of structure-based drug discovery, such as drug-protein interactions, drug binding and unbinding mechanisms and protein-protein interactions. This review presents a brief overview on the different state of the art computational approaches that are applied for protein structure modelling and molecular dynamics simulations of biological systems. We give an essence of how different enhanced sampling molecular dynamics approaches, together with regular molecular dynamics methods, assist in steering the structure based drug discovery processes. Copyright © 2013 Elsevier Ltd. All rights reserved.

Improved Displacement Transfer Functions for Structure Deformed Shape Predictions Using Discretely Distributed Surface Strains

NASA Technical Reports Server (NTRS)

Ko, William L.; Fleischer, Van Tran

2012-01-01

In the formulations of earlier Displacement Transfer Functions for structure shape predictions, the surface strain distributions, along a strain-sensing line, were represented with piecewise linear functions. To improve the shape-prediction accuracies, Improved Displacement Transfer Functions were formulated using piecewise nonlinear strain representations. Through discretization of an embedded beam (depth-wise cross section of a structure along a strain-sensing line) into multiple small domains, piecewise nonlinear functions were used to describe the surface strain distributions along the discretized embedded beam. Such piecewise approach enabled the piecewise integrations of the embedded beam curvature equations to yield slope and deflection equations in recursive forms. The resulting Improved Displacement Transfer Functions, written in summation forms, were expressed in terms of beam geometrical parameters and surface strains along the strain-sensing line. By feeding the surface strains into the Improved Displacement Transfer Functions, structural deflections could be calculated at multiple points for mapping out the overall structural deformed shapes for visual display. The shape-prediction accuracies of the Improved Displacement Transfer Functions were then examined in view of finite-element-calculated deflections using different tapered cantilever tubular beams. It was found that by using the piecewise nonlinear strain representations, the shape-prediction accuracies could be greatly improved, especially for highly-tapered cantilever tubular beams.

Elucidating the ensemble of functionally-relevant transitions in protein systems with a robotics-inspired method.

PubMed

Molloy, Kevin; Shehu, Amarda

2013-01-01

Many proteins tune their biological function by transitioning between different functional states, effectively acting as dynamic molecular machines. Detailed structural characterization of transition trajectories is central to understanding the relationship between protein dynamics and function. Computational approaches that build on the Molecular Dynamics framework are in principle able to model transition trajectories at great detail but also at considerable computational cost. Methods that delay consideration of dynamics and focus instead on elucidating energetically-credible conformational paths connecting two functionally-relevant structures provide a complementary approach. Effective sampling-based path planning methods originating in robotics have been recently proposed to produce conformational paths. These methods largely model short peptides or address large proteins by simplifying conformational space. We propose a robotics-inspired method that connects two given structures of a protein by sampling conformational paths. The method focuses on small- to medium-size proteins, efficiently modeling structural deformations through the use of the molecular fragment replacement technique. In particular, the method grows a tree in conformational space rooted at the start structure, steering the tree to a goal region defined around the goal structure. We investigate various bias schemes over a progress coordinate for balance between coverage of conformational space and progress towards the goal. A geometric projection layer promotes path diversity. A reactive temperature scheme allows sampling of rare paths that cross energy barriers. Experiments are conducted on small- to medium-size proteins of length up to 214 amino acids and with multiple known functionally-relevant states, some of which are more than 13Å apart of each-other. Analysis reveals that the method effectively obtains conformational paths connecting structural states that are significantly different. A detailed analysis on the depth and breadth of the tree suggests that a soft global bias over the progress coordinate enhances sampling and results in higher path diversity. The explicit geometric projection layer that biases the exploration away from over-sampled regions further increases coverage, often improving proximity to the goal by forcing the exploration to find new paths. The reactive temperature scheme is shown effective in increasing path diversity, particularly in difficult structural transitions with known high-energy barriers.

Protein loop modeling using a new hybrid energy function and its application to modeling in inaccurate structural environments.

PubMed

Park, Hahnbeom; Lee, Gyu Rie; Heo, Lim; Seok, Chaok

2014-01-01

Protein loop modeling is a tool for predicting protein local structures of particular interest, providing opportunities for applications involving protein structure prediction and de novo protein design. Until recently, the majority of loop modeling methods have been developed and tested by reconstructing loops in frameworks of experimentally resolved structures. In many practical applications, however, the protein loops to be modeled are located in inaccurate structural environments. These include loops in model structures, low-resolution experimental structures, or experimental structures of different functional forms. Accordingly, discrepancies in the accuracy of the structural environment assumed in development of the method and that in practical applications present additional challenges to modern loop modeling methods. This study demonstrates a new strategy for employing a hybrid energy function combining physics-based and knowledge-based components to help tackle this challenge. The hybrid energy function is designed to combine the strengths of each energy component, simultaneously maintaining accurate loop structure prediction in a high-resolution framework structure and tolerating minor environmental errors in low-resolution structures. A loop modeling method based on global optimization of this new energy function is tested on loop targets situated in different levels of environmental errors, ranging from experimental structures to structures perturbed in backbone as well as side chains and template-based model structures. The new method performs comparably to force field-based approaches in loop reconstruction in crystal structures and better in loop prediction in inaccurate framework structures. This result suggests that higher-accuracy predictions would be possible for a broader range of applications. The web server for this method is available at http://galaxy.seoklab.org/loop with the PS2 option for the scoring function.

Active damage interrogation system for structural health monitoring

NASA Astrophysics Data System (ADS)

Lichtenwalner, Peter F.; Dunne, James P.; Becker, Ronald S.; Baumann, Erwin W.

1997-05-01

An integrated and automated smart structures approach for in situ damage assessment has been implemented and evaluated in a laboratory environment for health monitoring of a realistic aerospace structural component. This approach, called Active Damage Interrogation (ADI), utilizes an array of piezoelectric transducers attached to or embedded within the structure for both actuation and sensing. The ADI system, which is model independent, actively interrogates the structure through broadband excitation of multiple actuators across the desired frequency range. Statistical analysis of the changes in transfer functions between actuator/sensor pairs is used to detect, localize, and assess the severity of damage in the structure. This paper presents the overall concept of the ADI system and provides experimental results of damage assessment studies conducted for a composite structural component of the MD-900 Explorer helicopter rotor system. The potential advantages of this approach include simplicity (no need for a model), sensitivity, and low cost implementation. The results obtained thus far indicate considerably promise for integrated structural health monitoring of aerospace vehicles, leading to the practice of condition-based maintenance and consequent reduction in life cycle costs.

Multiple Volume Scattering in Random Media and Periodic Structures with Applications in Microwave Remote Sensing and Wave Functional Materials

NASA Astrophysics Data System (ADS)

Tan, Shurun

The objective of my research is two-fold: to study wave scattering phenomena in dense volumetric random media and in periodic wave functional materials. For the first part, the goal is to use the microwave remote sensing technique to monitor water resources and global climate change. Towards this goal, I study the microwave scattering behavior of snow and ice sheet. For snowpack scattering, I have extended the traditional dense media radiative transfer (DMRT) approach to include cyclical corrections that give rise to backscattering enhancements, enabling the theory to model combined active and passive observations of snowpack using the same set of physical parameters. Besides DMRT, a fully coherent approach is also developed by solving Maxwell's equations directly over the entire snowpack including a bottom half space. This revolutionary new approach produces consistent scattering and emission results, and demonstrates backscattering enhancements and coherent layer effects. The birefringence in anisotropic snow layers is also analyzed by numerically solving Maxwell's equation directly. The effects of rapid density fluctuations in polar ice sheet emission in the 0.5˜2.0 GHz spectrum are examined using both fully coherent and partially coherent layered media emission theories that agree with each other and distinct from incoherent approaches. For the second part, the goal is to develop integral equation based methods to solve wave scattering in periodic structures such as photonic crystals and metamaterials that can be used for broadband simulations. Set upon the concept of modal expansion of the periodic Green's function, we have developed the method of broadband Green's function with low wavenumber extraction (BBGFL), where a low wavenumber component is extracted and results a non-singular and fast-converging remaining part with simple wavenumber dependence. We've applied the technique to simulate band diagrams and modal solutions of periodic structures, and to construct broadband Green's functions including periodic scatterers.

De Novo Protein Structure Prediction

NASA Astrophysics Data System (ADS)

Hung, Ling-Hong; Ngan, Shing-Chung; Samudrala, Ram

An unparalleled amount of sequence data is being made available from large-scale genome sequencing efforts. The data provide a shortcut to the determination of the function of a gene of interest, as long as there is an existing sequenced gene with similar sequence and of known function. This has spurred structural genomic initiatives with the goal of determining as many protein folds as possible (Brenner and Levitt, 2000; Burley, 2000; Brenner, 2001; Heinemann et al., 2001). The purpose of this is twofold: First, the structure of a gene product can often lead to direct inference of its function. Second, since the function of a protein is dependent on its structure, direct comparison of the structures of gene products can be more sensitive than the comparison of sequences of genes for detecting homology. Presently, structural determination by crystallography and NMR techniques is still slow and expensive in terms of manpower and resources, despite attempts to automate the processes. Computer structure prediction algorithms, while not providing the accuracy of the traditional techniques, are extremely quick and inexpensive and can provide useful low-resolution data for structure comparisons (Bonneau and Baker, 2001). Given the immense number of structures which the structural genomic projects are attempting to solve, there would be a considerable gain even if the computer structure prediction approach were applicable to a subset of proteins.

Adaptivity and smart algorithms for fluid-structure interaction

NASA Technical Reports Server (NTRS)

Oden, J. Tinsley

1990-01-01

This paper reviews new approaches in CFD which have the potential for significantly increasing current capabilities of modeling complex flow phenomena and of treating difficult problems in fluid-structure interaction. These approaches are based on the notions of adaptive methods and smart algorithms, which use instantaneous measures of the quality and other features of the numerical flowfields as a basis for making changes in the structure of the computational grid and of algorithms designed to function on the grid. The application of these new techniques to several problem classes are addressed, including problems with moving boundaries, fluid-structure interaction in high-speed turbine flows, flow in domains with receding boundaries, and related problems.

Wave steering effects in anisotropic composite structures: Direct calculation of the energy skew angle through a finite element scheme.

PubMed

Chronopoulos, D

2017-01-01

A systematic expression quantifying the wave energy skewing phenomenon as a function of the mechanical characteristics of a non-isotropic structure is derived in this study. A structure of arbitrary anisotropy, layering and geometric complexity is modelled through Finite Elements (FEs) coupled to a periodic structure wave scheme. A generic approach for efficiently computing the angular sensitivity of the wave slowness for each wave type, direction and frequency is presented. The approach does not involve any finite differentiation scheme and is therefore computationally efficient and not prone to the associated numerical errors. Copyright © 2016 Elsevier B.V. All rights reserved.

Unveiling the complex network of interactions in Ionic Liquids: a combined EXAFS and Molecular Dynamics approach

NASA Astrophysics Data System (ADS)

Serva, A.; Migliorati, V.; Lapi, A.; D'Angelo, P.

2016-05-01

The structural properties of geminal dicationic ionic liquids ([Cn (mim)2]Br2)/water mixtures have been investigated by means of extended X-ray absorption fine structure (EXAFS) spectroscopy and Molecular Dynamics (MD) simulations. This synergic approach allowed us to assess the reliability of the MD results and to provide accurate structural information about the first coordination shell of the Br- ion. We found that the local environment around the anion changes as a function of the water concentration, while it is the same independently from the length of the bridge-alkyl chain. Moreover, as regards the long-range structural organization, no tail-tail aggregation occurs with increasing alkyl chain length.

Disturbed prefrontal and temporal brain function during emotion and cognition interaction in criminal psychopathy.

PubMed

Müller, Jürgen L; Sommer, Monika; Döhnel, Katrin; Weber, Tatjana; Schmidt-Wilcke, Tobias; Hajak, Göran

2008-01-01

Impaired emotional responsiveness has been revealed as a hallmark of psychopathy. In spite of an increasing database on emotion processing, studies on cognitive function and in particular on the impact of emotion on cognition in psychopathy are rare. We used pictures from the International Affective Picture Set (IAPS) and a Simon Paradigm to address emotion-cognition interaction while functional and structural imaging data were obtained in 12 healthy controls and 10 psychopaths. We found an impaired emotion-cognition interaction in psychopaths that correlated with a changed prefrontal and temporal brain activation. With regard to the temporal cortex, it is shown that structure and function of the right superior temporal gyrus is disturbed in psychopathy, supporting a neurobiological approach to psychopathy, in which structure and function of the right STG may be important. (c) 2008 John Wiley & Sons, Ltd.

Chemical modulation of M13 bacteriophage and its functional opportunities for nanomedicine

PubMed Central

Chung, Woo-Jae; Lee, Doe-Young; Yoo, So Young

2014-01-01

M13 bacteriophage (phage) has emerged as an attractive bionanomaterial owing to its genetically tunable surface chemistry and its potential to self-assemble into hierarchical structures. Furthermore, because of its unique nanoscopic structure, phage has been proposed as a model system in soft condensed physics and as a biomimetic building block for structured functional materials. Genetic engineering of phage provides great opportunities to develop novel nanomaterials with functional surface peptide motifs; however, this biological approach is generally limited to peptides containing the 20 natural amino acids. To extend the scope of phage applications, strategies involving chemical modification have been employed to incorporate a wider range of functional groups, including synthetic chemical compounds. In this review, we introduce the design of chemoselective phage functionalization and discuss how such a strategy is combined with genetic engineering for a variety of medical applications, as reported in recent literature. PMID:25540583

Chemical modulation of M13 bacteriophage and its functional opportunities for nanomedicine.

PubMed

Chung, Woo-Jae; Lee, Doe-Young; Yoo, So Young

2014-01-01

M13 bacteriophage (phage) has emerged as an attractive bionanomaterial owing to its genetically tunable surface chemistry and its potential to self-assemble into hierarchical structures. Furthermore, because of its unique nanoscopic structure, phage has been proposed as a model system in soft condensed physics and as a biomimetic building block for structured functional materials. Genetic engineering of phage provides great opportunities to develop novel nanomaterials with functional surface peptide motifs; however, this biological approach is generally limited to peptides containing the 20 natural amino acids. To extend the scope of phage applications, strategies involving chemical modification have been employed to incorporate a wider range of functional groups, including synthetic chemical compounds. In this review, we introduce the design of chemoselective phage functionalization and discuss how such a strategy is combined with genetic engineering for a variety of medical applications, as reported in recent literature.

Applications of matched field processing to damage detection in composite wind turbine blades

NASA Astrophysics Data System (ADS)

Tippmann, Jeffery D.; Lanza di Scalea, Francesco

2015-03-01

There are many structures serving vital infrastructure, energy, and national security purposes. Inspecting the components and areas of the structure most prone to failure during maintenance operations by using non- destructive evaluation methods has been essential in avoiding costly, but preventable, catastrophic failures. In many cases, the inspections are performed by introducing acoustic, ultrasonic, or even thermographic waves into the structure and then evaluating the response. Sometimes the structure, or a component, is not accessible for active inspection methods. Because of this, there is a growing interest to use passive methods, such as using ambient noise, or sources of opportunity, to produce a passive impulse response function similar to the active approach. Several matched field processing techniques most notably used in oceanography and seismology applications are examined in more detail. While sparse array imaging in structures has been studied for years, all methods studied previously have used an active interrogation approach. Here, structural damage detection is studied by use of the reconstructed impulse response functions in ambient noise within sparse array imaging techniques, such as matched-field processing. This has been studied in experiments on a 9-m wind turbine blade.

Synthesis design of artificial magnetic metamaterials using a genetic algorithm.

PubMed

Chen, P Y; Chen, C H; Wang, H; Tsai, J H; Ni, W X

2008-08-18

In this article, we present a genetic algorithm (GA) as one branch of artificial intelligence (AI) for the optimization-design of the artificial magnetic metamaterial whose structure is automatically generated by computer through the filling element methodology. A representative design example, metamaterials with permeability of negative unity, is investigated and the optimized structures found by the GA are presented. It is also demonstrated that our approach is effective for the synthesis of functional magnetic and electric metamaterials with optimal structures. This GA-based optimization-design technique shows great versatility and applicability in the design of functional metamaterials.

Get Your Requirements Straight: Storyboarding Revisited

NASA Astrophysics Data System (ADS)

Haesen, Mieke; Luyten, Kris; Coninx, Karin

Current user-centred software engineering (UCSE) approaches provide many techniques to combine know-how available in multidisciplinary teams. Although the involvement of various disciplines is beneficial for the user experience of the future application, the transition from a user needs analysis to a structured interaction analysis and UI design is not always straightforward. We propose storyboards, enriched by metadata, to specify functional and non-functional requirements. Accompanying tool support should facilitate the creation and use of storyboards. We used a meta-storyboard for the verification of storyboarding approaches.

Volumetric brain magnetic resonance imaging predicts functioning in bipolar disorder: A machine learning approach.

PubMed

Sartori, Juliana M; Reckziegel, Ramiro; Passos, Ives Cavalcante; Czepielewski, Leticia S; Fijtman, Adam; Sodré, Leonardo A; Massuda, Raffael; Goi, Pedro D; Vianna-Sulzbach, Miréia; Cardoso, Taiane de Azevedo; Kapczinski, Flávio; Mwangi, Benson; Gama, Clarissa S

2018-08-01

Neuroimaging studies have been steadily explored in Bipolar Disorder (BD) in the last decades. Neuroanatomical changes tend to be more pronounced in patients with repeated episodes. Although the role of such changes in cognition and memory is well established, daily-life functioning impairments bulge among the consequences of the proposed progression. The objective of this study was to analyze MRI volumetric modifications in BD and healthy controls (HC) as possible predictors of daily-life functioning through a machine learning approach. Ninety-four participants (35 DSM-IV BD type I and 59 HC) underwent clinical and functioning assessments, and structural MRI. Functioning was assessed using the Functioning Assessment Short Test (FAST). The machine learning analysis was used to identify possible candidates of regional brain volumes that could predict functioning status, through a support vector regression algorithm. Patients with BD and HC did not differ in age, education and marital status. There were significant differences between groups in gender, BMI, FAST score, and employment status. There was significant correlation between observed and predicted FAST score for patients with BD, but not for controls. According to the model, the brain structures volumes that could predict FAST scores were: left superior frontal cortex, left rostral medial frontal cortex, right white matter total volume and right lateral ventricle volume. The machine learning approach demonstrated that brain volume changes in MRI were predictors of FAST score in patients with BD and could identify specific brain areas related to functioning impairment. Copyright © 2018 Elsevier Ltd. All rights reserved.

A finite element formulation for scattering from electrically large 2-dimensional structures

NASA Technical Reports Server (NTRS)

Ross, Daniel C.; Volakis, John L.

1992-01-01

A finite element formulation is given using the scattered field approach with a fictitious material absorber to truncate the mesh. The formulation includes the use of arbitrary approximation functions so that more accurate results can be achieved without any modification to the software. Additionally, non-polynomial approximation functions can be used, including complex approximation functions. The banded system that results is solved with an efficient sparse/banded iterative scheme and as a consequence, large structures can be analyzed. Results are given for simple cases to verify the formulation and also for large, complex geometries.

Non-Invasive Visualization and Quantitation of Cardiovascular Structure and Function.

ERIC Educational Resources Information Center

Ritman, E. L.; And Others

1979-01-01

Described is a new approach to investigative physiology based on computerized transaxial tomography, in which visualization and measurement of the internal structure of the cardiopulmonary system is possible without postmortem, biopsy, or vivisection procedures. Examples are given for application of the Dynamic Spatial Reconstructor (DSR). (CS)

Data mining graphene: Correlative analysis of structure and electronic degrees of freedom in graphenic monolayers with defects

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

Ziatdinov, Maxim A.; Fujii, Shintaro; Kiguchi, Manabu

The link between changes in the material crystal structure and its mechanical, electronic, magnetic, and optical functionalities known as the structure-property relationship is the cornerstone of the contemporary materials science research. The recent advances in scanning transmission electron and scanning probe microscopies (STEM and SPM) have opened an unprecedented path towards examining the materials structure property relationships on the single-impurity and atomic-configuration levels. Lacking, however, are the statistics-based approaches for cross-correlation of structure and property variables obtained in different information channels of the STEM and SPM experiments. Here we have designed an approach based on a combination of sliding windowmore » Fast Fourier Transform, Pearson correlation matrix, linear and kernel canonical correlation, to study a relationship between lattice distortions and electron scattering from the SPM data on graphene with defects. Our analysis revealed that the strength of coupling to strain is altered between different scattering channels which can explain coexistence of several quasiparticle interference patterns in the nanoscale regions of interest. In addition, the application of the kernel functions allowed us extracting a non-linear component of the relationship between the lattice strain and scattering intensity in graphene. Lastly, the outlined approach can be further utilized to analyzing correlations in various multi-modal imaging techniques where the information of interest is spatially distributed and has usually a complex multidimensional nature.« less

Data mining graphene: Correlative analysis of structure and electronic degrees of freedom in graphenic monolayers with defects

DOE PAGES

Ziatdinov, Maxim A.; Fujii, Shintaro; Kiguchi, Manabu; ...

2016-11-09

The link between changes in the material crystal structure and its mechanical, electronic, magnetic, and optical functionalities known as the structure-property relationship is the cornerstone of the contemporary materials science research. The recent advances in scanning transmission electron and scanning probe microscopies (STEM and SPM) have opened an unprecedented path towards examining the materials structure property relationships on the single-impurity and atomic-configuration levels. Lacking, however, are the statistics-based approaches for cross-correlation of structure and property variables obtained in different information channels of the STEM and SPM experiments. Here we have designed an approach based on a combination of sliding windowmore » Fast Fourier Transform, Pearson correlation matrix, linear and kernel canonical correlation, to study a relationship between lattice distortions and electron scattering from the SPM data on graphene with defects. Our analysis revealed that the strength of coupling to strain is altered between different scattering channels which can explain coexistence of several quasiparticle interference patterns in the nanoscale regions of interest. In addition, the application of the kernel functions allowed us extracting a non-linear component of the relationship between the lattice strain and scattering intensity in graphene. Lastly, the outlined approach can be further utilized to analyzing correlations in various multi-modal imaging techniques where the information of interest is spatially distributed and has usually a complex multidimensional nature.« less

Characterizing Atomistic Geometries and Potential Functions Using Strain Functionals

NASA Astrophysics Data System (ADS)

Kober, Edward; Mathew, Nithin; Rudin, Sven

2017-06-01

We demonstrate the use of strain tensor functionals for characterizing arbitrarily ordered atomistic structures. This approach defines a Gaussian-weighted neighborhood around each atom and characterizes that local geometry in terms of n-th order strain tensors, which are equivalent to the n-th order moments/derivatives of the neighborhood. Fourth order expansions can distinguish the cubic structures (and deformations thereof), but sixth order expansions are required to fully characterize hexagonal structures. These functions are continuous and smooth and much less sensitive to thermal fluctuations than other descriptors based on discrete neighborhoods. Reducing these metrics to rotational invariant descriptors allows a large number of defect structures to be readily identified and forms the basis of a classification scheme that allows molecular dynamics simulations to be readily analyzed. Applications to the analysis of shock waves impinging on samples of Cu, Ta and Ti will be presented. The method has been extended to vector fields as well, enabling the local stress to be cast in terms of rotationally invariant functions as well. The stress-strain correlations can then be used as the basis for developing and analyzing potential functions.

A new statistical framework to assess structural alignment quality using information compression

PubMed Central

Collier, James H.; Allison, Lloyd; Lesk, Arthur M.; Garcia de la Banda, Maria; Konagurthu, Arun S.

2014-01-01

Motivation: Progress in protein biology depends on the reliability of results from a handful of computational techniques, structural alignments being one. Recent reviews have highlighted substantial inconsistencies and differences between alignment results generated by the ever-growing stock of structural alignment programs. The lack of consensus on how the quality of structural alignments must be assessed has been identified as the main cause for the observed differences. Current methods assess structural alignment quality by constructing a scoring function that attempts to balance conflicting criteria, mainly alignment coverage and fidelity of structures under superposition. This traditional approach to measuring alignment quality, the subject of considerable literature, has failed to solve the problem. Further development along the same lines is unlikely to rectify the current deficiencies in the field. Results: This paper proposes a new statistical framework to assess structural alignment quality and significance based on lossless information compression. This is a radical departure from the traditional approach of formulating scoring functions. It links the structural alignment problem to the general class of statistical inductive inference problems, solved using the information-theoretic criterion of minimum message length. Based on this, we developed an efficient and reliable measure of structural alignment quality, I-value. The performance of I-value is demonstrated in comparison with a number of popular scoring functions, on a large collection of competing alignments. Our analysis shows that I-value provides a rigorous and reliable quantification of structural alignment quality, addressing a major gap in the field. Availability: http://lcb.infotech.monash.edu.au/I-value Contact: arun.konagurthu@monash.edu Supplementary information: Online supplementary data are available at http://lcb.infotech.monash.edu.au/I-value/suppl.html PMID:25161241

Approach to assess consequences of hypoxia disturbance events for benthic ecosystem functioning

NASA Astrophysics Data System (ADS)

Gogina, Mayya; Darr, Alexander; Zettler, Michael L.

2014-01-01

Our study challenges the functional approach for its usefulness in assessing the consequences of hypoxia disturbance events on macrofaunal communities in the south-western Baltic Sea. Time series for two decades of observations from two monitoring stations, one in the Fehmarnbelt (exposed to aperiodic hypoxia), and another in the Darss Rise (normoxic conditions) is used. Our results designate differences of functional structure of benthic fauna communities between sites based on biological traits that characterise species role in modifying the environment, behavioural strategies, morphology and life history, thus suggesting differences in functioning. Hypoxic years reveal sharp increase of the role of sedentary species, suspension filter feeders, epibenthic structures, globulose form, medium/large size of individuals, preponderance of species with long lifespan (caused for instance by remaining ocean quahog). The link of functional and species diversity to the stagnation periods is proposed for the Darss station that exhibit continuous changes and low temporal variability of traits distribution. Before the major inflow in 1993 the increased role of small size organisms, containing calcium carbonate, filter feeders and grazers, higher presence of semi-pelagic species is observed. The hypoxic events and water renewal processes impact the communities not only in respect to species composition but also functionally.

Towards Self-Assembled Hybrid Artificial Cells: Novel Bottom-Up Approaches to Functional Synthetic Membranes

PubMed Central

Brea, Roberto J.; Hardy, Michael D.; Devaraj, Neal K.

2015-01-01

There has been increasing interest in utilizing bottom-up approaches to develop synthetic cells. A popular methodology is the integration of functionalized synthetic membranes with biological systems, producing “hybrid” artificial cells. This Concept article covers recent advances and the current state-of-the-art of such hybrid systems. Specifically, we describe minimal supramolecular constructs that faithfully mimic the structure and/or function of living cells, often by controlling the assembly of highly ordered membrane architectures with defined functionality. These studies give us a deeper understanding of the nature of living systems, bring new insights into the origin of cellular life, and provide novel synthetic chassis for advancing synthetic biology. PMID:26149747

From Databases to Modelling of Functional Pathways

PubMed Central

2004-01-01

This short review comments on current informatics resources and methodologies in the study of functional pathways in cell biology. It highlights recent achievements in unveiling the structural design of protein and gene networks and discusses current approaches to model and simulate the dynamics of regulatory pathways in the cell. PMID:18629070

From databases to modelling of functional pathways.

PubMed

Nasi, Sergio

2004-01-01

This short review comments on current informatics resources and methodologies in the study of functional pathways in cell biology. It highlights recent achievements in unveiling the structural design of protein and gene networks and discusses current approaches to model and simulate the dynamics of regulatory pathways in the cell.

Bayesian estimation of the transmissivity spatial structure from pumping test data

NASA Astrophysics Data System (ADS)

Demir, Mehmet Taner; Copty, Nadim K.; Trinchero, Paolo; Sanchez-Vila, Xavier

2017-06-01

Estimating the statistical parameters (mean, variance, and integral scale) that define the spatial structure of the transmissivity or hydraulic conductivity fields is a fundamental step for the accurate prediction of subsurface flow and contaminant transport. In practice, the determination of the spatial structure is a challenge because of spatial heterogeneity and data scarcity. In this paper, we describe a novel approach that uses time drawdown data from multiple pumping tests to determine the transmissivity statistical spatial structure. The method builds on the pumping test interpretation procedure of Copty et al. (2011) (Continuous Derivation method, CD), which uses the time-drawdown data and its time derivative to estimate apparent transmissivity values as a function of radial distance from the pumping well. A Bayesian approach is then used to infer the statistical parameters of the transmissivity field by combining prior information about the parameters and the likelihood function expressed in terms of radially-dependent apparent transmissivities determined from pumping tests. A major advantage of the proposed Bayesian approach is that the likelihood function is readily determined from randomly generated multiple realizations of the transmissivity field, without the need to solve the groundwater flow equation. Applying the method to synthetically-generated pumping test data, we demonstrate that, through a relatively simple procedure, information on the spatial structure of the transmissivity may be inferred from pumping tests data. It is also shown that the prior parameter distribution has a significant influence on the estimation procedure, given the non-uniqueness of the estimation procedure. Results also indicate that the reliability of the estimated transmissivity statistical parameters increases with the number of available pumping tests.

Mobility power flow analysis of an L-shaped plate structure subjected to distributed loading

NASA Technical Reports Server (NTRS)

Cuschieri, J. M.; Cimmerman, B.

1990-01-01

An analytical investigation based in the Mobility Power Flow (MPF) method is presented for the determination of the vibrational response and power flow for two coupled flat plate structures in an L-shaped configuration, subjected to distributed excitation. The principle of the MPF method consists of dividing the global structure into a series of subsystems coupled together using mobility functions. Each separate subsystem is analyzed independently to determine the structural mobility functions for the junction and excitation locations. The mobility functions, together with the characteristics of the junction between the subsystems, are then used to determine the response of the global structure and the MPF. In the considered coupled plate structure, MPF expressions are derived for distributed mechanical excitation which is independent of the structure response. However using a similar approach with some modifications excitation by an acoustic plane wave can be considered. Some modifications are required to deal with the latter case are necessary because the forces (acoustic pressure) acting on the structure are dependent on the response of the structure due to the presence of the scattered pressure.

Energy density and rate limitations in structural composite supercapacitors

NASA Astrophysics Data System (ADS)

Snyder, J. F.; Gienger, E.; Wetzel, E. D.; Xu, K.

2012-06-01

The weight and volume of conventional energy storage technologies greatly limits their performance in mobile platforms. Traditional research efforts target improvements in energy density to reduce device size and mass. Enabling a device to perform additional functions, such as bearing mechanical load, is an alternative approach as long as the total mass efficiency exceeds that of the individual materials it replaces. Our research focuses on structural composites that function as batteries and supercapacitors. These multifunctional devices could be used to replace conventional structural components, such as vehicle frame elements, to provide significant system-level weight reductions and extend mission times. Our approach is to design structural properties directly into the electrolyte and electrode materials. Solid polymer electrolyte materials bind the system and transfer load to the fibers while conducting ions between the electrodes. Carbon fiber electrodes provide a route towards optimizing both energy storage and load-bearing capabilities, and may also obviate the need for a separate current collector. The components are being integrated using scalable, cost-effective composite processing techniques that are amenable to complex part shapes. Practical considerations of energy density and rate behavior are described here as they relate to materials used. Our results highlight the viability as well as the challenges of this multifunctional approach towards energy storage.

Introduction to the Wetland Book 1: Wetland structure and function, management, and nethods

USGS Publications Warehouse

Davidson, Nick C.; Middleton, Beth A.; McInnes, Robert J.; Everard, Mark; Irvine, Kenneth; Van Dam, Anne A.; Finlayson, C. Max; Finlayson, C. Max; Everard, Mark; Irvine, Kenneth; McInnes, Robert J.; Middleton, Beth A.; Van Dam, Anne A.; Davidson, Nick C.

2016-01-01

The Wetland Book 1 is designed as a ‘first port-of-call’ reference work for information on the structure and functions of wetlands, current approaches to wetland management, and methods for researching and understanding wetlands. Contributions by experts summarize key concepts, orient the reader to the major issues, and support further research on such issues by individuals and multidisciplinary teams. The Wetland Book 1 is organized in three parts - Wetland structure and function; Wetland management; and Wetland methods - each of which is divided into a number of thematic Sections. Each Section starts with one or more overview chapters, supported by chapters providing further information and case studies on different aspects of the theme.

High resolution multidetector CT aided tissue analysis and quantification of lung fibrosis

NASA Astrophysics Data System (ADS)

Zavaletta, Vanessa A.; Karwoski, Ronald A.; Bartholmai, Brian; Robb, Richard A.

2006-03-01

Idiopathic pulmonary fibrosis (IPF, also known as Idiopathic Usual Interstitial Pneumontis, pathologically) is a progressive diffuse lung disease which has a median survival rate of less than four years with a prevalence of 15-20/100,000 in the United States. Global function changes are measured by pulmonary function tests and the diagnosis and extent of pulmonary structural changes are typically assessed by acquiring two-dimensional high resolution CT (HRCT) images. The acquisition and analysis of volumetric high resolution Multi-Detector CT (MDCT) images with nearly isotropic pixels offers the potential to measure both lung function and structure. This paper presents a new approach to three dimensional lung image analysis and classification of normal and abnormal structures in lungs with IPF.

Predicting taxonomic and functional structure of microbial communities in acid mine drainage

PubMed Central

Kuang, Jialiang; Huang, Linan; He, Zhili; Chen, Linxing; Hua, Zhengshuang; Jia, Pu; Li, Shengjin; Liu, Jun; Li, Jintian; Zhou, Jizhong; Shu, Wensheng

2016-01-01

Predicting the dynamics of community composition and functional attributes responding to environmental changes is an essential goal in community ecology but remains a major challenge, particularly in microbial ecology. Here, by targeting a model system with low species richness, we explore the spatial distribution of taxonomic and functional structure of 40 acid mine drainage (AMD) microbial communities across Southeast China profiled by 16S ribosomal RNA pyrosequencing and a comprehensive microarray (GeoChip). Similar environmentally dependent patterns of dominant microbial lineages and key functional genes were observed regardless of the large-scale geographical isolation. Functional and phylogenetic β-diversities were significantly correlated, whereas functional metabolic potentials were strongly influenced by environmental conditions and community taxonomic structure. Using advanced modeling approaches based on artificial neural networks, we successfully predicted the taxonomic and functional dynamics with significantly higher prediction accuracies of metabolic potentials (average Bray–Curtis similarity 87.8) as compared with relative microbial abundances (similarity 66.8), implying that natural AMD microbial assemblages may be better predicted at the functional genes level rather than at taxonomic level. Furthermore, relative metabolic potentials of genes involved in many key ecological functions (for example, nitrogen and phosphate utilization, metals resistance and stress response) were extrapolated to increase under more acidic and metal-rich conditions, indicating a critical strategy of stress adaptation in these extraordinary communities. Collectively, our findings indicate that natural selection rather than geographic distance has a more crucial role in shaping the taxonomic and functional patterns of AMD microbial community that readily predicted by modeling methods and suggest that the model-based approach is essential to better understand natural acidophilic microbial communities. PMID:26943622

Predicting taxonomic and functional structure of microbial communities in acid mine drainage.

PubMed

Kuang, Jialiang; Huang, Linan; He, Zhili; Chen, Linxing; Hua, Zhengshuang; Jia, Pu; Li, Shengjin; Liu, Jun; Li, Jintian; Zhou, Jizhong; Shu, Wensheng

2016-06-01

Predicting the dynamics of community composition and functional attributes responding to environmental changes is an essential goal in community ecology but remains a major challenge, particularly in microbial ecology. Here, by targeting a model system with low species richness, we explore the spatial distribution of taxonomic and functional structure of 40 acid mine drainage (AMD) microbial communities across Southeast China profiled by 16S ribosomal RNA pyrosequencing and a comprehensive microarray (GeoChip). Similar environmentally dependent patterns of dominant microbial lineages and key functional genes were observed regardless of the large-scale geographical isolation. Functional and phylogenetic β-diversities were significantly correlated, whereas functional metabolic potentials were strongly influenced by environmental conditions and community taxonomic structure. Using advanced modeling approaches based on artificial neural networks, we successfully predicted the taxonomic and functional dynamics with significantly higher prediction accuracies of metabolic potentials (average Bray-Curtis similarity 87.8) as compared with relative microbial abundances (similarity 66.8), implying that natural AMD microbial assemblages may be better predicted at the functional genes level rather than at taxonomic level. Furthermore, relative metabolic potentials of genes involved in many key ecological functions (for example, nitrogen and phosphate utilization, metals resistance and stress response) were extrapolated to increase under more acidic and metal-rich conditions, indicating a critical strategy of stress adaptation in these extraordinary communities. Collectively, our findings indicate that natural selection rather than geographic distance has a more crucial role in shaping the taxonomic and functional patterns of AMD microbial community that readily predicted by modeling methods and suggest that the model-based approach is essential to better understand natural acidophilic microbial communities.

Insights into multimodal imaging classification of ADHD

PubMed Central

Colby, John B.; Rudie, Jeffrey D.; Brown, Jesse A.; Douglas, Pamela K.; Cohen, Mark S.; Shehzad, Zarrar

2012-01-01

Attention deficit hyperactivity disorder (ADHD) currently is diagnosed in children by clinicians via subjective ADHD-specific behavioral instruments and by reports from the parents and teachers. Considering its high prevalence and large economic and societal costs, a quantitative tool that aids in diagnosis by characterizing underlying neurobiology would be extremely valuable. This provided motivation for the ADHD-200 machine learning (ML) competition, a multisite collaborative effort to investigate imaging classifiers for ADHD. Here we present our ML approach, which used structural and functional magnetic resonance imaging data, combined with demographic information, to predict diagnostic status of individuals with ADHD from typically developing (TD) children across eight different research sites. Structural features included quantitative metrics from 113 cortical and non-cortical regions. Functional features included Pearson correlation functional connectivity matrices, nodal and global graph theoretical measures, nodal power spectra, voxelwise global connectivity, and voxelwise regional homogeneity. We performed feature ranking for each site and modality using the multiple support vector machine recursive feature elimination (SVM-RFE) algorithm, and feature subset selection by optimizing the expected generalization performance of a radial basis function kernel SVM (RBF-SVM) trained across a range of the top features. Site-specific RBF-SVMs using these optimal feature sets from each imaging modality were used to predict the class labels of an independent hold-out test set. A voting approach was used to combine these multiple predictions and assign final class labels. With this methodology we were able to predict diagnosis of ADHD with 55% accuracy (versus a 39% chance level in this sample), 33% sensitivity, and 80% specificity. This approach also allowed us to evaluate predictive structural and functional features giving insight into abnormal brain circuitry in ADHD. PMID:22912605

A three-way parallel ICA approach to analyze links among genetics, brain structure and brain function.

PubMed

Vergara, Victor M; Ulloa, Alvaro; Calhoun, Vince D; Boutte, David; Chen, Jiayu; Liu, Jingyu

2014-09-01

Multi-modal data analysis techniques, such as the Parallel Independent Component Analysis (pICA), are essential in neuroscience, medical imaging and genetic studies. The pICA algorithm allows the simultaneous decomposition of up to two data modalities achieving better performance than separate ICA decompositions and enabling the discovery of links between modalities. However, advances in data acquisition techniques facilitate the collection of more than two data modalities from each subject. Examples of commonly measured modalities include genetic information, structural magnetic resonance imaging (MRI) and functional MRI. In order to take full advantage of the available data, this work extends the pICA approach to incorporate three modalities in one comprehensive analysis. Simulations demonstrate the three-way pICA performance in identifying pairwise links between modalities and estimating independent components which more closely resemble the true sources than components found by pICA or separate ICA analyses. In addition, the three-way pICA algorithm is applied to real experimental data obtained from a study that investigate genetic effects on alcohol dependence. Considered data modalities include functional MRI (contrast images during alcohol exposure paradigm), gray matter concentration images from structural MRI and genetic single nucleotide polymorphism (SNP). The three-way pICA approach identified links between a SNP component (pointing to brain function and mental disorder associated genes, including BDNF, GRIN2B and NRG1), a functional component related to increased activation in the precuneus area, and a gray matter component comprising part of the default mode network and the caudate. Although such findings need further verification, the simulation and in-vivo results validate the three-way pICA algorithm presented here as a useful tool in biomedical data fusion applications. Copyright © 2014 Elsevier Inc. All rights reserved.

Three novel approaches to structural identifiability analysis in mixed-effects models.

PubMed

Janzén, David L I; Jirstrand, Mats; Chappell, Michael J; Evans, Neil D

2016-05-06

Structural identifiability is a concept that considers whether the structure of a model together with a set of input-output relations uniquely determines the model parameters. In the mathematical modelling of biological systems, structural identifiability is an important concept since biological interpretations are typically made from the parameter estimates. For a system defined by ordinary differential equations, several methods have been developed to analyse whether the model is structurally identifiable or otherwise. Another well-used modelling framework, which is particularly useful when the experimental data are sparsely sampled and the population variance is of interest, is mixed-effects modelling. However, established identifiability analysis techniques for ordinary differential equations are not directly applicable to such models. In this paper, we present and apply three different methods that can be used to study structural identifiability in mixed-effects models. The first method, called the repeated measurement approach, is based on applying a set of previously established statistical theorems. The second method, called the augmented system approach, is based on augmenting the mixed-effects model to an extended state-space form. The third method, called the Laplace transform mixed-effects extension, is based on considering the moment invariants of the systems transfer function as functions of random variables. To illustrate, compare and contrast the application of the three methods, they are applied to a set of mixed-effects models. Three structural identifiability analysis methods applicable to mixed-effects models have been presented in this paper. As method development of structural identifiability techniques for mixed-effects models has been given very little attention, despite mixed-effects models being widely used, the methods presented in this paper provides a way of handling structural identifiability in mixed-effects models previously not possible. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Some semiclassical structure constants for AdS 4 × CP 3

NASA Astrophysics Data System (ADS)

Ahn, Changrim; Bozhilov, Plamen

2018-02-01

We compute structure constants in three-point functions of three string states in AdS 4× CP 3 in the framework of the semiclassical approach. We consider HHL correlation functions where two of the states are "heavy" string states of finite-size giant magnons carrying one or two angular momenta and the other one corresponds to such "light" states as dilaton operators with non-zero momentum, primary scalar operators, and singlet scalar operators with higher string levels.

On some properties of bone functional adaptation phenomenon useful in mechanical design.

PubMed

Nowak, Michał

2010-01-01

The paper discusses some unique properties of trabecular bone functional adaptation phenomenon, useful in mechanical design. On the basis of the biological process observations and the principle of constant strain energy density on the surface of the structure, the generic structural optimisation system has been developed. Such approach allows fulfilling mechanical theorem for the stiffest design, comprising the optimisations of size, shape and topology, using the concepts known from biomechanical studies. Also the biomimetic solution of multiple load problems is presented.

An Ab Initio Study of CuCO

NASA Technical Reports Server (NTRS)

Bauschlicher, Charles W., Jr.

1994-01-01

Modified coupled-pair functional (MCPF) calculations and coupled cluster singles and doubles calculations, which include a perturbational estimate of the connected triples [CCSD(T)], yield a bent structure for CuCO, thus, supporting the prediction of a nonlinear structure based on density functional (DF) calculations. Our best estimate for the binding energy is 4.9 +/- 1.4 kcal/mol; this is in better agreement with experiment (6.0 +/- 1.2 kcal/mol) than the DF approach which yields a value (19.6 kcal/mol) significantly larger than experiment.

Transfer Function Identification Using Orthogonal Fourier Transform Modeling Functions

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.

2013-01-01

A method for transfer function identification, including both model structure determination and parameter estimation, was developed and demonstrated. The approach uses orthogonal modeling functions generated from frequency domain data obtained by Fourier transformation of time series data. The method was applied to simulation data to identify continuous-time transfer function models and unsteady aerodynamic models. Model fit error, estimated model parameters, and the associated uncertainties were used to show the effectiveness of the method for identifying accurate transfer function models from noisy data.

Quantification of soil structure based on Minkowski functions

NASA Astrophysics Data System (ADS)

Vogel, H.-J.; Weller, U.; Schlüter, S.

2010-10-01

The structure of soils and other geologic media is a complex three-dimensional object. Most of the physical material properties including mechanical and hydraulic characteristics are immediately linked to the structure given by the pore space and its spatial distribution. It is an old dream and still a formidable challenge to relate structural features of porous media to their functional properties. Using tomographic techniques, soil structure can be directly observed at a range of spatial scales. In this paper we present a scale-invariant concept to quantify complex structures based on a limited set of meaningful morphological functions. They are based on d+1 Minkowski functionals as defined for d-dimensional bodies. These basic quantities are determined as a function of pore size or aggregate size obtained by filter procedures using mathematical morphology. The resulting Minkowski functions provide valuable information on the size of pores and aggregates, the pore surface area and the pore topology having the potential to be linked to physical properties. The theoretical background and the related algorithms are presented and the approach is demonstrated for the pore structure of an arable soil and the pore structure of a sand both obtained by X-ray micro-tomography. We also analyze the fundamental problem of limited resolution which is critical for any attempt to quantify structural features at any scale using samples of different size recorded at different resolutions. The results demonstrate that objects smaller than 5 voxels are critical for quantitative analysis.

Resolution of structural heterogeneity in dynamic crystallography

PubMed Central

Ren, Zhong; Chan, Peter W. Y.; Moffat, Keith; Pai, Emil F.; Royer, William E.; Šrajer, Vukica; Yang, Xiaojing

2013-01-01

Dynamic behavior of proteins is critical to their function. X-­ray crystallography, a powerful yet mostly static technique, faces inherent challenges in acquiring dynamic information despite decades of effort. Dynamic ‘structural changes’ are often indirectly inferred from ‘structural differences’ by comparing related static structures. In contrast, the direct observation of dynamic structural changes requires the initiation of a biochemical reaction or process in a crystal. Both the direct and the indirect approaches share a common challenge in analysis: how to interpret the structural heterogeneity intrinsic to all dynamic processes. This paper presents a real-space approach to this challenge, in which a suite of analytical methods and tools to identify and refine the mixed structural species present in multiple crystallographic data sets have been developed. These methods have been applied to representative scenarios in dynamic crystallography, and reveal structural information that is otherwise difficult to interpret or inaccessible using conventional methods. PMID:23695239

Resolution of structural heterogeneity in dynamic crystallography.

PubMed

Ren, Zhong; Chan, Peter W Y; Moffat, Keith; Pai, Emil F; Royer, William E; Šrajer, Vukica; Yang, Xiaojing

2013-06-01

Dynamic behavior of proteins is critical to their function. X-ray crystallography, a powerful yet mostly static technique, faces inherent challenges in acquiring dynamic information despite decades of effort. Dynamic `structural changes' are often indirectly inferred from `structural differences' by comparing related static structures. In contrast, the direct observation of dynamic structural changes requires the initiation of a biochemical reaction or process in a crystal. Both the direct and the indirect approaches share a common challenge in analysis: how to interpret the structural heterogeneity intrinsic to all dynamic processes. This paper presents a real-space approach to this challenge, in which a suite of analytical methods and tools to identify and refine the mixed structural species present in multiple crystallographic data sets have been developed. These methods have been applied to representative scenarios in dynamic crystallography, and reveal structural information that is otherwise difficult to interpret or inaccessible using conventional methods.

Protein Delivery into Plant Cells: Toward In vivo Structural Biology

PubMed Central

Cedeño, Cesyen; Pauwels, Kris; Tompa, Peter

2017-01-01

Understanding the biologically relevant structural and functional behavior of proteins inside living plant cells is only possible through the combination of structural biology and cell biology. The state-of-the-art structural biology techniques are typically applied to molecules that are isolated from their native context. Although most experimental conditions can be easily controlled while dealing with an isolated, purified protein, a serious shortcoming of such in vitro work is that we cannot mimic the extremely complex intracellular environment in which the protein exists and functions. Therefore, it is highly desirable to investigate proteins in their natural habitat, i.e., within live cells. This is the major ambition of in-cell NMR, which aims to approach structure-function relationship under true in vivo conditions following delivery of labeled proteins into cells under physiological conditions. With a multidisciplinary approach that includes recombinant protein production, confocal fluorescence microscopy, nuclear magnetic resonance (NMR) spectroscopy and different intracellular protein delivery strategies, we explore the possibility to develop in-cell NMR studies in living plant cells. While we provide a comprehensive framework to set-up in-cell NMR, we identified the efficient intracellular introduction of isotope-labeled proteins as the major bottleneck. Based on experiments with the paradigmatic intrinsically disordered proteins (IDPs) Early Response to Dehydration protein 10 and 14, we also established the subcellular localization of ERD14 under abiotic stress. PMID:28469623

Design, fabrication and control of origami robots

NASA Astrophysics Data System (ADS)

Rus, Daniela; Tolley, Michael T.

2018-06-01

Origami robots are created using folding processes, which provide a simple approach to fabricating a wide range of robot morphologies. Inspired by biological systems, engineers have started to explore origami folding in combination with smart material actuators to enable intrinsic actuation as a means to decouple design from fabrication complexity. The built-in crease structure of origami bodies has the potential to yield compliance and exhibit many soft body properties. Conventional fabrication of robots is generally a bottom-up assembly process with multiple low-level steps for creating subsystems that include manual operations and often multiple iterations. By contrast, natural systems achieve elegant designs and complex functionalities using top-down parallel transformation approaches such as folding. Folding in nature creates a wide spectrum of complex morpho-functional structures such as proteins and intestines and enables the development of structures such as flowers, leaves and insect wings. Inspired by nature, engineers have started to explore folding powered by embedded smart material actuators to create origami robots. The design and fabrication of origami robots exploits top-down, parallel transformation approaches to achieve elegant designs and complex functionalities. In this Review, we first introduce the concept of origami robotics and then highlight advances in design principles, fabrication methods, actuation, smart materials and control algorithms. Applications of origami robots for a variety of devices are investigated, and future directions of the field are discussed, examining both challenges and opportunities.

Work domain constraints for modelling surgical performance.

PubMed

Morineau, Thierry; Riffaud, Laurent; Morandi, Xavier; Villain, Jonathan; Jannin, Pierre

2015-10-01

Three main approaches can be identified for modelling surgical performance: a competency-based approach, a task-based approach, both largely explored in the literature, and a less known work domain-based approach. The work domain-based approach first describes the work domain properties that constrain the agent's actions and shape the performance. This paper presents a work domain-based approach for modelling performance during cervical spine surgery, based on the idea that anatomical structures delineate the surgical performance. This model was evaluated through an analysis of junior and senior surgeons' actions. Twenty-four cervical spine surgeries performed by two junior and two senior surgeons were recorded in real time by an expert surgeon. According to a work domain-based model describing an optimal progression through anatomical structures, the degree of adjustment of each surgical procedure to a statistical polynomial function was assessed. Each surgical procedure showed a significant suitability with the model and regression coefficient values around 0.9. However, the surgeries performed by senior surgeons fitted this model significantly better than those performed by junior surgeons. Analysis of the relative frequencies of actions on anatomical structures showed that some specific anatomical structures discriminate senior from junior performances. The work domain-based modelling approach can provide an overall statistical indicator of surgical performance, but in particular, it can highlight specific points of interest among anatomical structures that the surgeons dwelled on according to their level of expertise.

A top-down approach to crystal engineering of a racemic Δ2-isoxazoline.

PubMed

Lombardo, Giuseppe M; Rescifina, Antonio; Chiacchio, Ugo; Bacchi, Alessia; Punzo, Francesco

2014-02-01

The crystal structure of racemic dimethyl (4RS,5RS)-3-(4-nitrophenyl)-4,5-dihydroisoxazole-4,5-dicarboxylate, C13H12N2O7, has been determined by single-crystal X-ray diffraction. By analysing the degree of growth of the morphologically important crystal faces, a ranking of the most relevant non-covalent interactions determining the crystal structure can be inferred. The morphological information is considered with an approach opposite to the conventional one: instead of searching inside the structure for the potential key interactions and using them to calculate the crystal habit, the observed crystal morphology is used to define the preferential lines of growth of the crystal, and then this information is interpreted by means of density functional theory (DFT) calculations. Comparison with the X-ray structure confirms the validity of the strategy, thus suggesting this top-down approach to be a useful tool for crystal engineering.

A Bayesian Approach for Determining Protein Side-Chain Rotamer Conformations Using Unassigned NOE Data

PubMed Central

Zeng, Jianyang; Roberts, Kyle E.; Zhou, Pei

2011-01-01

Abstract A major bottleneck in protein structure determination via nuclear magnetic resonance (NMR) is the lengthy and laborious process of assigning resonances and nuclear Overhauser effect (NOE) cross peaks. Recent studies have shown that accurate backbone folds can be determined using sparse NMR data, such as residual dipolar couplings (RDCs) or backbone chemical shifts. This opens a question of whether we can also determine the accurate protein side-chain conformations using sparse or unassigned NMR data. We attack this question by using unassigned nuclear Overhauser effect spectroscopy (NOESY) data, which records the through-space dipolar interactions between protons nearby in three-dimensional (3D) space. We propose a Bayesian approach with a Markov random field (MRF) model to integrate the likelihood function derived from observed experimental data, with prior information (i.e., empirical molecular mechanics energies) about the protein structures. We unify the side-chain structure prediction problem with the side-chain structure determination problem using unassigned NMR data, and apply the deterministic dead-end elimination (DEE) and A* search algorithms to provably find the global optimum solution that maximizes the posterior probability. We employ a Hausdorff-based measure to derive the likelihood of a rotamer or a pairwise rotamer interaction from unassigned NOESY data. In addition, we apply a systematic and rigorous approach to estimate the experimental noise in NMR data, which also determines the weighting factor of the data term in the scoring function derived from the Bayesian framework. We tested our approach on real NMR data of three proteins: the FF Domain 2 of human transcription elongation factor CA150 (FF2), the B1 domain of Protein G (GB1), and human ubiquitin. The promising results indicate that our algorithm can be applied in high-resolution protein structure determination. Since our approach does not require any NOE assignment, it can accelerate the NMR structure determination process. PMID:21970619

Scanning holographic optical tweezers.

PubMed

Shaw, L A; Panas, Robert M; Spadaccini, C M; Hopkins, J B

2017-08-01

The aim of this Letter is to introduce a new optical tweezers approach, called scanning holographic optical tweezers (SHOT), which drastically increases the working area (WA) of the holographic-optical tweezers (HOT) approach, while maintaining tightly focused laser traps. A 12-fold increase in the WA is demonstrated. The SHOT approach achieves its utility by combining the large WA of the scanning optical tweezers (SOT) approach with the flexibility of the HOT approach for simultaneously moving differently structured optical traps in and out of the focal plane. This Letter also demonstrates a new heuristic control algorithm for combining the functionality of the SOT and HOT approaches to efficiently allocate the available laser power among a large number of traps. The proposed approach shows promise for substantially increasing the number of particles that can be handled simultaneously, which would enable optical tweezers additive fabrication technologies to rapidly assemble microgranular materials and structures in reasonable build times.

Coupling Adaptation Tipping Points and Engineering Options: New Insights for Resilient Water Infrastructure Replacement Planning

NASA Astrophysics Data System (ADS)

Smet, K.; de Neufville, R.; van der Vlist, M.

2017-12-01

This work presents an innovative approach for replacement planning for aging water infrastructure given uncertain future conditions. We draw upon two existing methodologies to develop an integrated long-term replacement planning framework. We first expand the concept of Adaptation Tipping Points to generate long-term planning timelines that incorporate drivers of investment related to both internal structural processes as well as changes in external operating conditions. Then, we use Engineering Options to explore different actions taken at key moments in this timeline. Contrasting to the traditionally more static approach to infrastructure design, designing the next generation of infrastructure so it can be changed incrementally is a promising method to safeguard current investments given future uncertainty. This up-front inclusion of structural options in the system actively facilitates future adaptation, transforming uncertainty management in infrastructure planning from reactive to more proactive. A two-part model underpins this approach. A simulation model generates diverse future conditions, allowing development of timelines of intervention moments in the structure's life. This feeds into an economic model, evaluating the lifetime performance of different replacement strategies, making explicit the value of different designs and their flexibility. A proof of concept study demonstrates this approach for a pumping station. The strategic planning timelines for this structure demonstrate that moments when capital interventions become necessary due to reduced functionality from structural degradation or changed operating conditions are widely spread over the structure's life. The disparate timing of these necessary interventions supports an incremental, adaptive mindset when considering end-of-life and replacement decisions. The analysis then explores different replacement decisions, varying the size and specific options included in the proposed new structure. Results show that incremental adaptive designs and incorporating options can improve economic performance, as compared to traditional, "build it once & build it big" designs. The benefit from incorporating flexibility varies with structural functionality, future conditions and the specific options examined.

Structural-functional relationships between eye orbital imaging biomarkers and clinical visual assessments

NASA Astrophysics Data System (ADS)

Yao, Xiuya; Chaganti, Shikha; Nabar, Kunal P.; Nelson, Katrina; Plassard, Andrew; Harrigan, Rob L.; Mawn, Louise A.; Landman, Bennett A.

2017-02-01

Eye diseases and visual impairment affect millions of Americans and induce billions of dollars in annual economic burdens. Expounding upon existing knowledge of eye diseases could lead to improved treatment and disease prevention. This research investigated the relationship between structural metrics of the eye orbit and visual function measurements in a cohort of 470 patients from a retrospective study of ophthalmology records for patients (with thyroid eye disease, orbital inflammation, optic nerve edema, glaucoma, intrinsic optic nerve disease), clinical imaging, and visual function assessments. Orbital magnetic resonance imaging (MRI) and computed tomography (CT) images were retrieved and labeled in 3D using multi-atlas label fusion. Based on the 3D structures, both traditional radiology measures (e.g., Barrett index, volumetric crowding index, optic nerve length) and novel volumetric metrics were computed. Using stepwise regression, the associations between structural metrics and visual field scores (visual acuity, functional acuity, visual field, functional field, and functional vision) were assessed. Across all models, the explained variance was reasonable (R2 0.1-0.2) but highly significant (p < 0.001). Instead of analyzing a specific pathology, this study aimed to analyze data across a variety of pathologies. This approach yielded a general model for the connection between orbital structural imaging biomarkers and visual function.

First-principles approach to calculating energy level alignment at aqueous semiconductor interfaces.

PubMed

Kharche, Neerav; Muckerman, James T; Hybertsen, Mark S

2014-10-24

A first-principles approach is demonstrated for calculating the relationship between an aqueous semiconductor interface structure and energy level alignment. The physical interface structure is sampled using density functional theory based molecular dynamics, yielding the interface electrostatic dipole. The  GW approach from many-body perturbation theory is used to place the electronic band edge energies of the semiconductor relative to the occupied 1b1 energy level in water. The application to the specific cases of nonpolar (101¯0) facets of GaN and ZnO reveals a significant role for the structural motifs at the interface, including the degree of interface water dissociation and the dynamical fluctuations in the interface Zn-O and O-H bond orientations. These effects contribute up to 0.5 eV.

Casimir force in brane worlds: Coinciding results from Green's and zeta function approaches

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

Linares, Roman; Morales-Tecotl, Hugo A.; Pedraza, Omar

2010-06-15

Casimir force encodes the structure of the field modes as vacuum fluctuations and so it is sensitive to the extra dimensions of brane worlds. Now, in flat spacetimes of arbitrary dimension the two standard approaches to the Casimir force, Green's function, and zeta function yield the same result, but for brane world models this was only assumed. In this work we show that both approaches yield the same Casimir force in the case of universal extra dimensions and Randall-Sundrum scenarios with one and two branes added by p compact dimensions. Essentially, the details of the mode eigenfunctions that enter themore » Casimir force in the Green's function approach get removed due to their orthogonality relations with a measure involving the right hypervolume of the plates, and this leaves just the contribution coming from the zeta function approach. The present analysis corrects previous results showing a difference between the two approaches for the single brane Randall-Sundrum; this was due to an erroneous hypervolume of the plates introduced by the authors when using the Green's function. For all the models we discuss here, the resulting Casimir force can be neatly expressed in terms of two four-dimensional Casimir force contributions: one for the massless mode and the other for a tower of massive modes associated with the extra dimensions.« less

On Correspondence of BRST-BFV, Dirac, and Refined Algebraic Quantizations of Constrained Systems

NASA Astrophysics Data System (ADS)

Shvedov, O. Yu.

2002-11-01

The correspondence between BRST-BFV, Dirac, and refined algebraic (group averaging, projection operator) approaches to quantizing constrained systems is analyzed. For the closed-algebra case, it is shown that the component of the BFV wave function corresponding to maximal (minimal) value of number of ghosts and antighosts in the Schrodinger representation may be viewed as a wave function in the refined algebraic (Dirac) quantization approach. The Giulini-Marolf group averaging formula for the inner product in the refined algebraic quantization approach is obtained from the Batalin-Marnelius prescription for the BRST-BFV inner product, which should be generally modified due to topological problems. The considered prescription for the correspondence of states is observed to be applicable to the open-algebra case. The refined algebraic quantization approach is generalized then to the case of nontrivial structure functions. A simple example is discussed. The correspondence of observables for different quantization methods is also investigated.

Achievements and Challenges in Computational Protein Design.

PubMed

Samish, Ilan

2017-01-01

Computational protein design (CPD), a yet evolving field, includes computer-aided engineering for partial or full de novo designs of proteins of interest. Designs are defined by a requested structure, function, or working environment. This chapter describes the birth and maturation of the field by presenting 101 CPD examples in a chronological order emphasizing achievements and pending challenges. Integrating these aspects presents the plethora of CPD approaches with the hope of providing a "CPD 101". These reflect on the broader structural bioinformatics and computational biophysics field and include: (1) integration of knowledge-based and energy-based methods, (2) hierarchical designated approach towards local, regional, and global motifs and the integration of high- and low-resolution design schemes that fit each such region, (3) systematic differential approaches towards different protein regions, (4) identification of key hot-spot residues and the relative effect of remote regions, (5) assessment of shape-complementarity, electrostatics and solvation effects, (6) integration of thermal plasticity and functional dynamics, (7) negative design, (8) systematic integration of experimental approaches, (9) objective cross-assessment of methods, and (10) successful ranking of potential designs. Future challenges also include dissemination of CPD software to the general use of life-sciences researchers and the emphasis of success within an in vivo milieu. CPD increases our understanding of protein structure and function and the relationships between the two along with the application of such know-how for the benefit of mankind. Applied aspects range from biological drugs, via healthier and tastier food products to nanotechnology and environmentally friendly enzymes replacing toxic chemicals utilized in the industry.

Selected Topics in Light Front Field Theory and Applications to the High Energy Phenomena

NASA Astrophysics Data System (ADS)

Kundu, Rajen

1999-10-01

In this thesis, we have presented some of the aspects of light-front (LF) field theory through their successful application in the Deep Inelastic Scattering (DIS). We have developed a LFQCD Hamiltonian description of the DIS structure functions starting from Bjorken-Johnson-Low limit of virtual forward Compton scattering amplitude and using LF current commutators. We worked in the LF gauge A^+=0 and used the old-fashioned LFQCD perturbation theory in our calculations. The importance of our work are summarized below. Our approach shares the intution of parton model and addresses directly the structure functions, which are experimental objects, instead of its moments as in OPE method. Moreover, it can potentially incorporate the non-perturbative contents of the structure functions as we have demonstrated by introducing a new factorization scheme. In the context of nucleonic helicity structure, the well known gauge fixed LF helicity operator is shown to provide consistent physical information and helps us defining new relevant structure functions. The anomalous dimensions relevant for the Q^2-evolution of such structure functions are calculated. Our study is important in establishing the equivalance of LF field theory and the usual equal-time one through perturbative calculations of the dressed parton structure functions reproducing the well known results. Also the importance of Gallilean boost symmetry in understanding the correctness of any higher order calculation using (x^+)-ordered LFQCD perturbation theory are emphasized.

Preprocessing method to correct illumination pattern in sinusoidal-based structured illumination microscopy

NASA Astrophysics Data System (ADS)

Shabani, H.; Doblas, A.; Saavedra, G.; Preza, C.

2018-02-01

The restored images in structured illumination microscopy (SIM) can be affected by residual fringes due to a mismatch between the illumination pattern and the sinusoidal model assumed by the restoration method. When a Fresnel biprism is used to generate a structured pattern, this pattern cannot be described by a pure sinusoidal function since it is distorted by an envelope due to the biprism's edge. In this contribution, we have investigated the effect of the envelope on the restored SIM images and propose a computational method in order to address it. The proposed approach to reduce the effect of the envelope consists of two parts. First, the envelope of the structured pattern, determined through calibration data, is removed from the raw SIM data via a preprocessing step. In the second step, a notch filter is applied to the images, which are restored using the well-known generalized Wiener filter, to filter any residual undesired fringes. The performance of our approach has been evaluated numerically by simulating the effect of the envelope on synthetic forward images of a 6-μm spherical bead generated using the real pattern and then restored using the SIM approach that is based on an ideal pure sinusoidal function before and after our proposed correction method. The simulation result shows 74% reduction in the contrast of the residual pattern when the proposed method is applied. Experimental results from a pollen grain sample also validate the proposed approach.

Functional brain networks reconstruction using group sparsity-regularized learning.

PubMed

Zhao, Qinghua; Li, Will X Y; Jiang, Xi; Lv, Jinglei; Lu, Jianfeng; Liu, Tianming

2018-06-01

Investigating functional brain networks and patterns using sparse representation of fMRI data has received significant interests in the neuroimaging community. It has been reported that sparse representation is effective in reconstructing concurrent and interactive functional brain networks. To date, most of data-driven network reconstruction approaches rarely take consideration of anatomical structures, which are the substrate of brain function. Furthermore, it has been rarely explored whether structured sparse representation with anatomical guidance could facilitate functional networks reconstruction. To address this problem, in this paper, we propose to reconstruct brain networks utilizing the structure guided group sparse regression (S2GSR) in which 116 anatomical regions from the AAL template, as prior knowledge, are employed to guide the network reconstruction when performing sparse representation of whole-brain fMRI data. Specifically, we extract fMRI signals from standard space aligned with the AAL template. Then by learning a global over-complete dictionary, with the learned dictionary as a set of features (regressors), the group structured regression employs anatomical structures as group information to regress whole brain signals. Finally, the decomposition coefficients matrix is mapped back to the brain volume to represent functional brain networks and patterns. We use the publicly available Human Connectome Project (HCP) Q1 dataset as the test bed, and the experimental results indicate that the proposed anatomically guided structure sparse representation is effective in reconstructing concurrent functional brain networks.

New algorithms to represent complex pseudoknotted RNA structures in dot-bracket notation.

PubMed

Antczak, Maciej; Popenda, Mariusz; Zok, Tomasz; Zurkowski, Michal; Adamiak, Ryszard W; Szachniuk, Marta

2018-04-15

Understanding the formation, architecture and roles of pseudoknots in RNA structures are one of the most difficult challenges in RNA computational biology and structural bioinformatics. Methods predicting pseudoknots typically perform this with poor accuracy, often despite experimental data incorporation. Existing bioinformatic approaches differ in terms of pseudoknots' recognition and revealing their nature. A few ways of pseudoknot classification exist, most common ones refer to a genus or order. Following the latter one, we propose new algorithms that identify pseudoknots in RNA structure provided in BPSEQ format, determine their order and encode in dot-bracket-letter notation. The proposed encoding aims to illustrate the hierarchy of RNA folding. New algorithms are based on dynamic programming and hybrid (combining exhaustive search and random walk) approaches. They evolved from elementary algorithm implemented within the workflow of RNA FRABASE 1.0, our database of RNA structure fragments. They use different scoring functions to rank dissimilar dot-bracket representations of RNA structure. Computational experiments show an advantage of new methods over the others, especially for large RNA structures. Presented algorithms have been implemented as new functionality of RNApdbee webserver and are ready to use at http://rnapdbee.cs.put.poznan.pl. mszachniuk@cs.put.poznan.pl. Supplementary data are available at Bioinformatics online.

Combined DFT and BS study on the exchange coupling of dinuclear sandwich-type POM: comparison of different functionals and reliability of structure modeling.

PubMed

Yin, Bing; Xue, GangLin; Li, JianLi; Bai, Lu; Huang, YuanHe; Wen, ZhenYi; Jiang, ZhenYi

2012-05-01

The exchange coupling of a group of three dinuclear sandwich-type polyoxomolybdates [MM'(AsMo7O27)2](12-) with MM' = CrCr, FeFe, FeCr are theoretically predicted from combined DFT and broken-symmetry (BS) approach. Eight different XC functionals are utilized to calculate the exchange-coupling constant J from both the full crystalline structures and model structures of smaller size. The comparison between theoretical values and accurate experimental results supports the applicability of DFT-BS method in this new type of sandwich-type dinuclear polyoxomolybdates. However, a careful choice of functionals is necessary to achieve the desired accuracy. The encouraging results obtained from calculations on model structures highlight the great potential of application of structure modeling in theoretical study of POM. Structural modeling may not only reduce the computational cost of large POM species but also be able to take into account the external field effect arising from solvent molecules in solution or counterions in crystal.

Quasiparticle band structure of rocksalt-CdO determined using maximally localized Wannier functions.

PubMed

Dixit, H; Lamoen, D; Partoens, B

2013-01-23

CdO in the rocksalt structure is an indirect band gap semiconductor. Thus, in order to determine its band gap one needs to calculate the complete band structure. However, in practice, the exact evaluation of the quasiparticle band structure for the large number of k-points which constitute the different symmetry lines in the Brillouin zone can be an extremely demanding task compared to the standard density functional theory (DFT) calculation. In this paper we report the full quasiparticle band structure of CdO using a plane-wave pseudopotential approach. In order to reduce the computational effort and time, we make use of maximally localized Wannier functions (MLWFs). The MLWFs offer a highly accurate method for interpolation of the DFT or GW band structure from a coarse k-point mesh in the irreducible Brillouin zone, resulting in a much reduced computational effort. The present paper discusses the technical details of the scheme along with the results obtained for the quasiparticle band gap and the electron effective mass.

EVALUATING THE INTEGRITY OF SALT MARSHES IN NARRAGANSETT BAY SUB-ESTUARIES USING A WATERSHED APPROACH

EPA Science Inventory

A watershed approach to examine measures of structure and function in salt marshes of similar geomorphology and hydrology in Narragansett Bay is being used to develop a reference system for evaluating salt marsh integrity. We describe integrity as the capability of a salt marsh t...

System-level strategies for conserving rare or little-known species

Treesearch

Bruce G. Marcot; Carolyn Hull Sieg

2007-01-01

In this chapter we review the literature on system-level strategies for conserving rare or little-known (RLK) species, continuing from the species-level approaches addressed in the previous chapter. We define system-level approaches as those that result in conservation actions focused on providing for community or ecosystem composition, structure, or function.

Disrupted brain network functional dynamics and hyper-correlation of structural and functional connectome topology in patients with breast cancer prior to treatment.

PubMed

Kesler, Shelli R; Adams, Marjorie; Packer, Melissa; Rao, Vikram; Henneghan, Ashley M; Blayney, Douglas W; Palesh, Oxana

2017-03-01

Several previous studies have demonstrated that cancer chemotherapy is associated with brain injury and cognitive dysfunction. However, evidence suggests that cancer pathogenesis alone may play a role, even in non-CNS cancers. Using a multimodal neuroimaging approach, we measured structural and functional connectome topology as well as functional network dynamics in newly diagnosed patients with breast cancer. Our study involved a novel, pretreatment assessment that occurred prior to the initiation of any cancer therapies, including surgery with anesthesia. We enrolled 74 patients with breast cancer age 29-65 and 50 frequency-matched healthy female controls who underwent anatomic and resting-state functional MRI as well as cognitive testing. Compared to controls, patients with breast cancer demonstrated significantly lower functional network dynamics ( p  = .046) and cognitive functioning ( p  < .02, corrected). The breast cancer group also showed subtle alterations in structural local clustering and functional local clustering ( p  < .05, uncorrected) as well as significantly increased correlation between structural global clustering and functional global clustering compared to controls ( p  = .03). This hyper-correlation between structural and functional topologies was significantly associated with cognitive dysfunction ( p  = .005). Our findings could not be accounted for by psychological distress and suggest that non-CNS cancer may directly and/or indirectly affect the brain via mechanisms such as tumor-induced neurogenesis, inflammation, and/or vascular changes, for example. Our results also have broader implications concerning the importance of the balance between structural and functional connectome properties as a potential biomarker of general neurologic deficit.

Compared effects of missense mutations in Very-Long-Chain Acyl-CoA Dehydrogenase deficiency: Combined analysis by structural, functional and pharmacological approaches.

PubMed

Gobin-Limballe, Stéphanie; McAndrew, Ryan P; Djouadi, Fatima; Kim, Jung-Ja; Bastin, Jean

2010-05-01

Very-Long-Chain Acyl-CoA Dehydrogenase deficiency (VLCADD) is an autosomal recessive disorder considered as one of the more common ss-oxidation defects, possibly associated with neonatal cardiomyopathy, infantile hepatic coma, or adult-onset myopathy. Numerous gene missense mutations have been described in these VLCADD phenotypes, but only few of them have been structurally and functionally analyzed, and the molecular basis of disease variability is still poorly understood. To address this question, we first analyzed fourteen disease-causing amino acid changes using the recently described crystal structure of VLCAD. The predicted effects varied from the replacement of amino acid residues lining the substrate binding cavity, involved in holoenzyme-FAD interactions or in enzyme dimerisation, predicted to have severe functional consequences, up to amino acid substitutions outside key enzyme domains or lying on near enzyme surface, with predicted milder consequences. These data were combined with functional analysis of residual fatty acid oxidation (FAO) and VLCAD protein levels in patient cells harboring these mutations, before and after pharmacological stimulation by bezafibrate. Mutations identified as detrimental to the protein structure in the 3-D model were generally associated to profound FAO and VLCAD protein deficiencies in the patient cells, however, some mutations affecting FAD binding or monomer-monomer interactions allowed a partial response to bezafibrate. On the other hand, bezafibrate restored near-normal FAO rates in some mutations predicted to have milder consequences on enzyme structure. Overall, combination of structural, biochemical, and pharmacological analysis allowed assessment of the relative severity of individual mutations, with possible applications for disease management and therapeutic approach. Copyright 2010 Elsevier B.V. All rights reserved.

Chemometric strategy for modeling metabolic biological space along the gastrointestinal tract and assessing microbial influences.

PubMed

Martin, François-Pierre J; Montoliu, Ivan; Kochhar, Sunil; Rezzi, Serge

2010-12-01

Over the past decade, the analysis of metabolic data with advanced chemometric techniques has offered the potential to explore functional relationships among biological compartments in relation to the structure and function of the intestine. However, the employed methodologies, generally based on regression modeling techniques, have given emphasis to region-specific metabolic patterns, while providing only limited insights into the spatiotemporal metabolic features of the complex gastrointestinal system. Hence, novel approaches are needed to analyze metabolic data to reconstruct the metabolic biological space associated with the evolving structures and functions of an organ such as the gastrointestinal tract. Here, we report the application of multivariate curve resolution (MCR) methodology to model metabolic relationships along the gastrointestinal compartments in relation to its structure and function using data from our previous metabonomic analysis. The method simultaneously summarizes metabolite occurrence and contribution to continuous metabolic signatures of the different biological compartments of the gut tract. This methodology sheds new light onto the complex web of metabolic interactions with gut symbionts that modulate host cell metabolism in surrounding gut tissues. In the future, such an approach will be key to provide new insights into the dynamic onset of metabolic deregulations involved in region-specific gastrointestinal disorders, such as Crohn's disease or ulcerative colitis.

A concept for fault tolerant design and improved availability of active composite elastic structures

NASA Astrophysics Data System (ADS)

Soeffker, D.; Wolters, K.; Krajcin, I.

2005-05-01

New functionalities, higher comfort and increasing performance requirements are often be solved by adding new technologies to existing (passive) solutions. Monitoring and control approaches uses additional sensors and actuators, new materials, microprocessors and new devices realizing new and improved functionalities. Two effects are becoming more and more interesting: (1) the lifetime of new actuators/materials strongly depends on the usage-history, (2) the functionality of the new composed systems depends on the fully functionality of all elements. In the consequence, the availability of such new systems is decreased by the number of elements and depends strongly on the use. These effects are known and act against new developments improving performance behavior also in mechanical engineering, automotive systems etc. This will be also the case for multifunctional composite or compound systems such as piezomaterials, magnetostrictive alloys or smart memory alloys (SMA) and is actually within the focus of the Structural-Health-Monitoring (SHM)-community. This contribution explains a new and systematically structured methodological approach to avoid and eliminate failures in mechatronical systems in an integrated and intelligent way to achieve a desirable or required amount of utilization in compliance with a defined failure rate. The result is an enhancement of the dependability of such a system.

Identification of Functionally Related Enzymes by Learning-to-Rank Methods.

PubMed

Stock, Michiel; Fober, Thomas; Hüllermeier, Eyke; Glinca, Serghei; Klebe, Gerhard; Pahikkala, Tapio; Airola, Antti; De Baets, Bernard; Waegeman, Willem

2014-01-01

Enzyme sequences and structures are routinely used in the biological sciences as queries to search for functionally related enzymes in online databases. To this end, one usually departs from some notion of similarity, comparing two enzymes by looking for correspondences in their sequences, structures or surfaces. For a given query, the search operation results in a ranking of the enzymes in the database, from very similar to dissimilar enzymes, while information about the biological function of annotated database enzymes is ignored. In this work, we show that rankings of that kind can be substantially improved by applying kernel-based learning algorithms. This approach enables the detection of statistical dependencies between similarities of the active cleft and the biological function of annotated enzymes. This is in contrast to search-based approaches, which do not take annotated training data into account. Similarity measures based on the active cleft are known to outperform sequence-based or structure-based measures under certain conditions. We consider the Enzyme Commission (EC) classification hierarchy for obtaining annotated enzymes during the training phase. The results of a set of sizeable experiments indicate a consistent and significant improvement for a set of similarity measures that exploit information about small cavities in the surface of enzymes.

A miniaturized technique for assessing protein thermodynamics and function using fast determination of quantitative cysteine reactivity.

PubMed

Isom, Daniel G; Marguet, Philippe R; Oas, Terrence G; Hellinga, Homme W

2011-04-01

Protein thermodynamic stability is a fundamental physical characteristic that determines biological function. Furthermore, alteration of thermodynamic stability by macromolecular interactions or biochemical modifications is a powerful tool for assessing the relationship between protein structure, stability, and biological function. High-throughput approaches for quantifying protein stability are beginning to emerge that enable thermodynamic measurements on small amounts of material, in short periods of time, and using readily accessible instrumentation. Here we present such a method, fast quantitative cysteine reactivity, which exploits the linkage between protein stability, sidechain protection by protein structure, and structural dynamics to characterize the thermodynamic and kinetic properties of proteins. In this approach, the reaction of a protected cysteine and thiol-reactive fluorogenic indicator is monitored over a gradient of temperatures after a short incubation time. These labeling data can be used to determine the midpoint of thermal unfolding, measure the temperature dependence of protein stability, quantify ligand-binding affinity, and, under certain conditions, estimate folding rate constants. Here, we demonstrate the fQCR method by characterizing these thermodynamic and kinetic properties for variants of Staphylococcal nuclease and E. coli ribose-binding protein engineered to contain single, protected cysteines. These straightforward, information-rich experiments are likely to find applications in protein engineering and functional genomics. Copyright © 2010 Wiley-Liss, Inc.

Minimal gravity and Frobenius manifolds: bulk correlation on sphere and disk

NASA Astrophysics Data System (ADS)

Aleshkin, Konstantin; Belavin, Vladimir; Rim, Chaiho

2017-11-01

There are two alternative approaches to the minimal gravity — direct Liouville approach and matrix models. Recently there has been a certain progress in the matrix model approach, growing out of presence of a Frobenius manifold (FM) structure embedded in the theory. The previous studies were mainly focused on the spherical topology. Essentially, it was shown that the action principle of Douglas equation allows to define the free energy and to compute the correlation numbers if the resonance transformations are properly incorporated. The FM structure allows to find the explicit form of the resonance transformation as well as the closed expression for the partition function. In this paper we elaborate on the case of gravitating disk. We focus on the bulk correlators and show that in the similar way as in the closed topology the generating function can be formulated using the set of flat coordinates on the corresponding FM. Moreover, the resonance transformations, which follow from the spherical topology consideration, are exactly those needed to reproduce FZZ result of the Liouville gravity approach.

Creation of Functional Micro/Nano Systems through Top-down and Bottom-up Approaches

PubMed Central

Wong, Tak-Sing; Brough, Branden; Ho, Chih-Ming

2009-01-01

Mimicking nature’s approach in creating devices with similar functional complexity is one of the ultimate goals of scientists and engineers. The remarkable elegance of these naturally evolved structures originates from bottom-up self-assembly processes. The seamless integration of top-down fabrication and bottom-up synthesis is the challenge for achieving intricate artificial systems. In this paper, technologies necessary for guided bottom-up assembly such as molecular manipulation, molecular binding, and the self assembling of molecules will be reviewed. In addition, the current progress of synthesizing mechanical devices through top-down and bottom-up approaches will be discussed. PMID:19382535

New approach in the quantum statistical parton distribution

NASA Astrophysics Data System (ADS)

Sohaily, Sozha; Vaziri (Khamedi), Mohammad

2017-12-01

An attempt to find simple parton distribution functions (PDFs) based on quantum statistical approach is presented. The PDFs described by the statistical model have very interesting physical properties which help to understand the structure of partons. The longitudinal portion of distribution functions are given by applying the maximum entropy principle. An interesting and simple approach to determine the statistical variables exactly without fitting and fixing parameters is surveyed. Analytic expressions of the x-dependent PDFs are obtained in the whole x region [0, 1], and the computed distributions are consistent with the experimental observations. The agreement with experimental data, gives a robust confirm of our simple presented statistical model.

Know Your Enemy: Successful Bioinformatic Approaches to Predict Functional RNA Structures in Viral RNAs.

PubMed

Lim, Chun Shen; Brown, Chris M

2017-01-01

Structured RNA elements may control virus replication, transcription and translation, and their distinct features are being exploited by novel antiviral strategies. Viral RNA elements continue to be discovered using combinations of experimental and computational analyses. However, the wealth of sequence data, notably from deep viral RNA sequencing, viromes, and metagenomes, necessitates computational approaches being used as an essential discovery tool. In this review, we describe practical approaches being used to discover functional RNA elements in viral genomes. In addition to success stories in new and emerging viruses, these approaches have revealed some surprising new features of well-studied viruses e.g., human immunodeficiency virus, hepatitis C virus, influenza, and dengue viruses. Some notable discoveries were facilitated by new comparative analyses of diverse viral genome alignments. Importantly, comparative approaches for finding RNA elements embedded in coding and non-coding regions differ. With the exponential growth of computer power we have progressed from stem-loop prediction on single sequences to cutting edge 3D prediction, and from command line to user friendly web interfaces. Despite these advances, many powerful, user friendly prediction tools and resources are underutilized by the virology community.

Know Your Enemy: Successful Bioinformatic Approaches to Predict Functional RNA Structures in Viral RNAs

PubMed Central

Lim, Chun Shen; Brown, Chris M.

2018-01-01

Structured RNA elements may control virus replication, transcription and translation, and their distinct features are being exploited by novel antiviral strategies. Viral RNA elements continue to be discovered using combinations of experimental and computational analyses. However, the wealth of sequence data, notably from deep viral RNA sequencing, viromes, and metagenomes, necessitates computational approaches being used as an essential discovery tool. In this review, we describe practical approaches being used to discover functional RNA elements in viral genomes. In addition to success stories in new and emerging viruses, these approaches have revealed some surprising new features of well-studied viruses e.g., human immunodeficiency virus, hepatitis C virus, influenza, and dengue viruses. Some notable discoveries were facilitated by new comparative analyses of diverse viral genome alignments. Importantly, comparative approaches for finding RNA elements embedded in coding and non-coding regions differ. With the exponential growth of computer power we have progressed from stem-loop prediction on single sequences to cutting edge 3D prediction, and from command line to user friendly web interfaces. Despite these advances, many powerful, user friendly prediction tools and resources are underutilized by the virology community. PMID:29354101

Contribution to viscosity from the structural relaxation via the atomic scale Green-Kubo stress correlation function.

PubMed

Levashov, V A

2017-11-14

We studied the connection between the structural relaxation and viscosity for a binary model of repulsive particles in the supercooled liquid regime. The used approach is based on the decomposition of the macroscopic Green-Kubo stress correlation function into the correlation functions between the atomic level stresses. Previously we used the approach to study an iron-like single component system of particles. The role of vibrational motion has been addressed through the demonstration of the relationship between viscosity and the shear waves propagating over large distances. In our previous considerations, however, we did not discuss the role of the structural relaxation. Here we suggest that the contribution to viscosity from the structural relaxation can be taken into account through the consideration of the contribution from the atomic stress auto-correlation term only. This conclusion, however, does not mean that only the auto-correlation term represents the contribution to viscosity from the structural relaxation. Previously the role of the structural relaxation for viscosity has been addressed through the considerations of the transitions between inherent structures and within the mode-coupling theory by other authors. In the present work, we study the structural relaxation through the considerations of the parent liquid and the atomic level stress correlations in it. The comparison with the results obtained on the inherent structures also is made. Our current results suggest, as our previous observations, that in the supercooled liquid regime, the vibrational contribution to viscosity extends over the times that are much larger than the Einstein's vibrational period and much larger than the times that it takes for the shear waves to propagate over the model systems. Besides addressing the atomic level shear stress correlations, we also studied correlations between the atomic level pressure elements.

Contribution to viscosity from the structural relaxation via the atomic scale Green-Kubo stress correlation function

NASA Astrophysics Data System (ADS)

Levashov, V. A.

2017-11-01

We studied the connection between the structural relaxation and viscosity for a binary model of repulsive particles in the supercooled liquid regime. The used approach is based on the decomposition of the macroscopic Green-Kubo stress correlation function into the correlation functions between the atomic level stresses. Previously we used the approach to study an iron-like single component system of particles. The role of vibrational motion has been addressed through the demonstration of the relationship between viscosity and the shear waves propagating over large distances. In our previous considerations, however, we did not discuss the role of the structural relaxation. Here we suggest that the contribution to viscosity from the structural relaxation can be taken into account through the consideration of the contribution from the atomic stress auto-correlation term only. This conclusion, however, does not mean that only the auto-correlation term represents the contribution to viscosity from the structural relaxation. Previously the role of the structural relaxation for viscosity has been addressed through the considerations of the transitions between inherent structures and within the mode-coupling theory by other authors. In the present work, we study the structural relaxation through the considerations of the parent liquid and the atomic level stress correlations in it. The comparison with the results obtained on the inherent structures also is made. Our current results suggest, as our previous observations, that in the supercooled liquid regime, the vibrational contribution to viscosity extends over the times that are much larger than the Einstein's vibrational period and much larger than the times that it takes for the shear waves to propagate over the model systems. Besides addressing the atomic level shear stress correlations, we also studied correlations between the atomic level pressure elements.

Odua Weston Jambi Hotel’s Structural Building Design with Prestressed Concrete Slab System Approach

NASA Astrophysics Data System (ADS)

Bayuaji, R.; Darmawan, M. S.; Rofiq, M. A.; Santoso, S. E.; Hardiyanto, E.

2017-11-01

Odua Weston Jambi Hotel is an eight-floor hotel and located in a prone to earth-quake area. This building used conventional concrete to its structural beam and column. This research’s purpose was to maximize the second-floor’s function by modifing its architectural design. Special Moment Resisting Frame System (SMRFS) approach was used in the structural design, referred to SNI 03-2847-2013 dan SNI 1726-2012 and to compensate the needs of a spacious hall without any column in the centre of the hall, so therefore, prestressed concrete plate is used to solve this problem.

Conceptual design of tetraazaporphyrin- and subtetraazaporphyrin-based functional nanocarbon materials: electronic structures, topologies, optical properties, and methane storage capacities.

PubMed

Belosludov, Rodion V; Rhoda, Hannah M; Zhdanov, Ravil K; Belosludov, Vladimir R; Kawazoe, Yoshiyuki; Nemykin, Victor N

2016-05-11

A large variety of conceptual three- and fourfold tetraazaporphyrin- and subtetraazaporphyrin-based functional 3D nanocage and nanobarrel structures have been proposed on the basis of in silico design. The designed structures differ in their sizes, topology, porosity, and conjugation properties. The stability of nanocages of Oh symmetry and nanobarrels of D4h symmetry was revealed on the basis of DFT and MD calculations, whereas their optical properties were assessed using a TDDFT approach and a long-range corrected LC-wPBE exchange-correlation functional. It was shown that the electronic structures and vertical excitation energies of the functional nanocage and nanobarrel structures could be easily tuned via their size, topology, and the presence of bridging sp(3) carbon atoms. TDDFT calculations suggest significantly lower excitation energies in fully conjugated nanocages and nanobarrels compared with systems with bridging sp(3) carbon fragments. Based on DFT and TDDFT calculations, the optical properties of the new materials can rival those of known quantum dots and are superior to those of monomeric phthalocyanines and their analogues. The methane gas adsorption properties of the new nanostructures and nanotubes generated by conversion from nanobarrels were studied using an MD simulation approach. The ability to store large quantities of methane (106-216 cm(3) (STP) cm(-3)) was observed in all cases with several compounds being close to or exceeding the DOE target of 180 cm(3) (STP) cm(-3) for material-based methane storage at a pressure of 3.5 MPa and room temperature.

Virtual Plants Need Water Too: Functional-Structural Root System Models in the Context of Drought Tolerance Breeding

PubMed Central

Ndour, Adama; Vadez, Vincent; Pradal, Christophe; Lucas, Mikaël

2017-01-01

Developing a sustainable agricultural model is one of the great challenges of the coming years. The agricultural practices inherited from the Green Revolution of the 1960s show their limits today, and new paradigms need to be explored to counter rising issues such as the multiplication of climate-change related drought episodes. Two such new paradigms are the use of functional-structural plant models to complement and rationalize breeding approaches and a renewed focus on root systems as untapped sources of plant amelioration. Since the late 1980s, numerous functional and structural models of root systems were developed and used to investigate the properties of root systems in soil or lab-conditions. In this review, we focus on the conception and use of such root models in the broader context of research on root-driven drought tolerance, on the basis of root system architecture (RSA) phenotyping. Such models result from the integration of architectural, physiological and environmental data. Here, we consider the different phenotyping techniques allowing for root architectural and physiological study and their limits. We discuss how QTL and breeding studies support the manipulation of RSA as a way to improve drought resistance. We then go over the integration of the generated data within architectural models, how those architectural models can be coupled with functional hydraulic models, and how functional parameters can be measured to feed those models. We then consider the assessment and validation of those hydraulic models through confrontation of simulations to experimentations. Finally, we discuss the up and coming challenges facing root systems functional-structural modeling approaches in the context of breeding. PMID:29018456

Virtual Plants Need Water Too: Functional-Structural Root System Models in the Context of Drought Tolerance Breeding.

PubMed

Ndour, Adama; Vadez, Vincent; Pradal, Christophe; Lucas, Mikaël

2017-01-01

Developing a sustainable agricultural model is one of the great challenges of the coming years. The agricultural practices inherited from the Green Revolution of the 1960s show their limits today, and new paradigms need to be explored to counter rising issues such as the multiplication of climate-change related drought episodes. Two such new paradigms are the use of functional-structural plant models to complement and rationalize breeding approaches and a renewed focus on root systems as untapped sources of plant amelioration. Since the late 1980s, numerous functional and structural models of root systems were developed and used to investigate the properties of root systems in soil or lab-conditions. In this review, we focus on the conception and use of such root models in the broader context of research on root-driven drought tolerance, on the basis of root system architecture (RSA) phenotyping. Such models result from the integration of architectural, physiological and environmental data. Here, we consider the different phenotyping techniques allowing for root architectural and physiological study and their limits. We discuss how QTL and breeding studies support the manipulation of RSA as a way to improve drought resistance. We then go over the integration of the generated data within architectural models, how those architectural models can be coupled with functional hydraulic models, and how functional parameters can be measured to feed those models. We then consider the assessment and validation of those hydraulic models through confrontation of simulations to experimentations. Finally, we discuss the up and coming challenges facing root systems functional-structural modeling approaches in the context of breeding.

Theory of buckling and post-buckling behavior of elastic structures

NASA Technical Reports Server (NTRS)

Budiansky, B.

1974-01-01

The present paper provides a unified, general presentation of the basic theory of the buckling and post-buckling behavior of elastic structures in a form suitable for application to a wide variety of special problems. The notation of functional analysis is used for this purpose. Before the general analysis, simple conceptual models are used to elucidate the basic concepts of bifurcation buckling, snap buckling, imperfection sensitivity, load-shortening relations, and stability. The energy approach, the virtual-work approach, and mode interaction are discussed. The derivations and results are applicable to continua and finite-dimensional systems. The virtual-work and energy approaches are given separate treatments, but their equivalence is made explicit. The basic concepts of stability occupy a secondary position in the present approach.

Predicting the Oxygen-Binding Properties of Platinum Nanoparticle Ensembles by Combining High-Precision Electron Microscopy and Density Functional Theory.

PubMed

Aarons, Jolyon; Jones, Lewys; Varambhia, Aakash; MacArthur, Katherine E; Ozkaya, Dogan; Sarwar, Misbah; Skylaris, Chris-Kriton; Nellist, Peter D

2017-07-12

Many studies of heterogeneous catalysis, both experimental and computational, make use of idealized structures such as extended surfaces or regular polyhedral nanoparticles. This simplification neglects the morphological diversity in real commercial oxygen reduction reaction (ORR) catalysts used in fuel-cell cathodes. Here we introduce an approach that combines 3D nanoparticle structures obtained from high-throughput high-precision electron microscopy with density functional theory. Discrepancies between experimental observations and cuboctahedral/truncated-octahedral particles are revealed and discussed using a range of widely used descriptors, such as electron-density, d-band centers, and generalized coordination numbers. We use this new approach to determine the optimum particle size for which both detrimental surface roughness and particle shape effects are minimized.

A statistical physics perspective on alignment-independent protein sequence comparison.

PubMed

Chattopadhyay, Amit K; Nasiev, Diar; Flower, Darren R

2015-08-01

Within bioinformatics, the textual alignment of amino acid sequences has long dominated the determination of similarity between proteins, with all that implies for shared structure, function and evolutionary descent. Despite the relative success of modern-day sequence alignment algorithms, so-called alignment-free approaches offer a complementary means of determining and expressing similarity, with potential benefits in certain key applications, such as regression analysis of protein structure-function studies, where alignment-base similarity has performed poorly. Here, we offer a fresh, statistical physics-based perspective focusing on the question of alignment-free comparison, in the process adapting results from 'first passage probability distribution' to summarize statistics of ensemble averaged amino acid propensity values. In this article, we introduce and elaborate this approach. © The Author 2015. Published by Oxford University Press.

New Statistical Model for Variability of Aerosol Optical Thickness: Theory and Application to MODIS Data over Ocean

NASA Technical Reports Server (NTRS)

Alexandrov, Mikhail Dmitrievic; Geogdzhayev, Igor V.; Tsigaridis, Konstantinos; Marshak, Alexander; Levy, Robert; Cairns, Brian

2016-01-01

A novel model for the variability in aerosol optical thickness (AOT) is presented. This model is based on the consideration of AOT fields as realizations of a stochastic process, that is the exponent of an underlying Gaussian process with a specific autocorrelation function. In this approach AOT fields have lognormal PDFs and structure functions having the correct asymptotic behavior at large scales. The latter is an advantage compared with fractal (scale-invariant) approaches. The simple analytical form of the structure function in the proposed model facilitates its use for the parameterization of AOT statistics derived from remote sensing data. The new approach is illustrated using a month-long global MODIS AOT dataset (over ocean) with 10 km resolution. It was used to compute AOT statistics for sample cells forming a grid with 5deg spacing. The observed shapes of the structure functions indicated that in a large number of cases the AOT variability is split into two regimes that exhibit different patterns of behavior: small-scale stationary processes and trends reflecting variations at larger scales. The small-scale patterns are suggested to be generated by local aerosols within the marine boundary layer, while the large-scale trends are indicative of elevated aerosols transported from remote continental sources. This assumption is evaluated by comparison of the geographical distributions of these patterns derived from MODIS data with those obtained from the GISS GCM. This study shows considerable potential to enhance comparisons between remote sensing datasets and climate models beyond regional mean AOTs.

Assessing the functional mechanical properties of bioengineered organs with emphasis on the lung.

PubMed

Suki, Béla

2014-09-01

Recently, an exciting new approach has emerged in regenerative medicine pushing the forefront of tissue engineering to create bioartificial organs. The basic idea is to create biological scaffolds made of extracellular matrix (ECM) that preserves the three-dimensional architecture of an entire organ. These scaffolds are then used as templates for functional tissue and organ reconstruction after re-seeding the structure with stem cells or appropriately differentiated cells. In order to make sure that these bioartificial organs will be able to function in the mechanical environment of the native tissue, it is imperative to fully characterize their mechanical properties and match them with those of the normal native organs. This mini-review briefly summarizes modern measurement techniques of mechanical function characterized mostly by the material or volumetric stiffness. Micro-scale and macro-scale techniques such as atomic force microscopy and the tissue strip stress-strain approach are discussed with emphasis on those that combine mechanical measurements with structural visualization. Proper micro-scale stiffness helps attachment and differentiation of cells in the bioartificial organ whereas macro-scale functionality is provided by the overall mechanical properties of the construct. Several approaches including failure mechanics are also described, which specifically probe the contributions of the main ECM components including collagen, elastin, and proteoglycans to organ level ECM function. Advantages, drawbacks, and possible pitfalls as well as interpretation of the data are given throughout. Finally, specific techniques to assess the functionality of the ECM of bioartificial lungs are separately discussed. © 2014 Wiley Periodicals, Inc.

Structural damage continuous monitoring by using a data driven approach based on principal component analysis and cross-correlation analysis

NASA Astrophysics Data System (ADS)

Camacho-Navarro, Jhonatan; Ruiz, Magda; Villamizar, Rodolfo; Mujica, Luis; Moreno-Beltrán, Gustavo; Quiroga, Jabid

2017-05-01

Continuous monitoring for damage detection in structural assessment comprises implementation of low cost equipment and efficient algorithms. This work describes the stages involved in the design of a methodology with high feasibility to be used in continuous damage assessment. Specifically, an algorithm based on a data-driven approach by using principal component analysis and pre-processing acquired signals by means of cross-correlation functions, is discussed. A carbon steel pipe section and a laboratory tower were used as test structures in order to demonstrate the feasibility of the methodology to detect abrupt changes in the structural response when damages occur. Two types of damage cases are studied: crack and leak for each structure, respectively. Experimental results show that the methodology is promising in the continuous monitoring of real structures.

Generalized neurofuzzy network modeling algorithms using Bézier-Bernstein polynomial functions and additive decomposition.

PubMed

Hong, X; Harris, C J

2000-01-01

This paper introduces a new neurofuzzy model construction algorithm for nonlinear dynamic systems based upon basis functions that are Bézier-Bernstein polynomial functions. This paper is generalized in that it copes with n-dimensional inputs by utilising an additive decomposition construction to overcome the curse of dimensionality associated with high n. This new construction algorithm also introduces univariate Bézier-Bernstein polynomial functions for the completeness of the generalized procedure. Like the B-spline expansion based neurofuzzy systems, Bézier-Bernstein polynomial function based neurofuzzy networks hold desirable properties such as nonnegativity of the basis functions, unity of support, and interpretability of basis function as fuzzy membership functions, moreover with the additional advantages of structural parsimony and Delaunay input space partition, essentially overcoming the curse of dimensionality associated with conventional fuzzy and RBF networks. This new modeling network is based on additive decomposition approach together with two separate basis function formation approaches for both univariate and bivariate Bézier-Bernstein polynomial functions used in model construction. The overall network weights are then learnt using conventional least squares methods. Numerical examples are included to demonstrate the effectiveness of this new data based modeling approach.

Unified control/structure design and modeling research

NASA Technical Reports Server (NTRS)

Mingori, D. L.; Gibson, J. S.; Blelloch, P. A.; Adamian, A.

1986-01-01

To demonstrate the applicability of the control theory for distributed systems to large flexible space structures, research was focused on a model of a space antenna which consists of a rigid hub, flexible ribs, and a mesh reflecting surface. The space antenna model used is discussed along with the finite element approximation of the distributed model. The basic control problem is to design an optimal or near-optimal compensator to suppress the linear vibrations and rigid-body displacements of the structure. The application of an infinite dimensional Linear Quadratic Gaussian (LQG) control theory to flexible structure is discussed. Two basic approaches for robustness enhancement were investigated: loop transfer recovery and sensitivity optimization. A third approach synthesized from elements of these two basic approaches is currently under development. The control driven finite element approximation of flexible structures is discussed. Three sets of finite element basic vectors for computing functional control gains are compared. The possibility of constructing a finite element scheme to approximate the infinite dimensional Hamiltonian system directly, instead of indirectly is discussed.

Overview on the Surface Functionalization Mechanism and Determination of Surface Functional Groups of Plasma Treated Carbon Nanotubes.

PubMed

Saka, Cafer

2018-01-02

The use of carbon materials for many applications is due to the unique diversity of structures and properties ranging from chemical bonds between the carbon atoms of the materials to nanostructures, crystallite alignment, and microstructures. Carbon nanotubes and other nanoscale carbonaceous materials draw much attention due to their physical and chemical properties, such as high strength, high resistance to corrosion, electrical and thermal conductivity, stability and a qualified adsorbent. Carbon-based nanomaterials, which have a relatively large specific area and layered structure, can be used as an adsorbent for efficient removal of organic and inorganic contaminants. However, one of the biggest obstacles to the development of carbon-based nanomaterials adsorbents is insolubility and the lack of functional groups on the surface. There are several approaches to introduce functional groups on carbon nanotubes. One of these approaches, plasma applications, now has an important place in the creation of surface functional groups as a flexible, fast, and environmentally friendly method. This review focuses on recent information concerning the surface functionalization and modification of plasma treated carbon nanotube. This review considers the surface properties, advantages, and disadvantages of plasma-applied carbon nanotubes. It also examines the reaction mechanisms involved in the functional groups on the surface.

Community structure in networks of functional connectivity: resolving functional organization in the rat brain with pharmacological MRI.

PubMed

Schwarz, Adam J; Gozzi, Alessandro; Bifone, Angelo

2009-08-01

In the study of functional connectivity, fMRI data can be represented mathematically as a network of nodes and links, where image voxels represent the nodes and the connections between them reflect a degree of correlation or similarity in their response. Here we show that, within this framework, functional imaging data can be partitioned into 'communities' of tightly interconnected voxels corresponding to maximum modularity within the overall network. We evaluated this approach systematically in application to networks constructed from pharmacological MRI (phMRI) of the rat brain in response to acute challenge with three different compounds with distinct mechanisms of action (d-amphetamine, fluoxetine, and nicotine) as well as vehicle (physiological saline). This approach resulted in bilaterally symmetric sub-networks corresponding to meaningful anatomical and functional connectivity pathways consistent with the purported mechanism of action of each drug. Interestingly, common features across all three networks revealed two groups of tightly coupled brain structures that responded as functional units independent of the specific neurotransmitter systems stimulated by the drug challenge, including a network involving the prefrontal cortex and sub-cortical regions extending from the striatum to the amygdala. This finding suggests that each of these networks includes general underlying features of the functional organization of the rat brain.

Calculating the n-point correlation function with general and efficient python code

NASA Astrophysics Data System (ADS)

Genier, Fred; Bellis, Matthew

2018-01-01

There are multiple approaches to understanding the evolution of large-scale structure in our universe and with it the role of baryonic matter, dark matter, and dark energy at different points in history. One approach is to calculate the n-point correlation function estimator for galaxy distributions, sometimes choosing a particular type of galaxy, such as luminous red galaxies. The standard way to calculate these estimators is with pair counts (for the 2-point correlation function) and with triplet counts (for the 3-point correlation function). These are O(n2) and O(n3) problems, respectively and with the number of galaxies that will be characterized in future surveys, having efficient and general code will be of increasing importance. Here we show a proof-of-principle approach to the 2-point correlation function that relies on pre-calculating galaxy locations in coarse “voxels”, thereby reducing the total number of necessary calculations. The code is written in python, making it easily accessible and extensible and is open-sourced to the community. Basic results and performance tests using SDSS/BOSS data will be shown and we discuss the application of this approach to the 3-point correlation function.

Brain networks, structural realism, and local approaches to the scientific realism debate.

PubMed

Yan, Karen; Hricko, Jonathon

2017-08-01

We examine recent work in cognitive neuroscience that investigates brain networks. Brain networks are characterized by the ways in which brain regions are functionally and anatomically connected to one another. Cognitive neuroscientists use various noninvasive techniques (e.g., fMRI) to investigate these networks. They represent them formally as graphs. And they use various graph theoretic techniques to analyze them further. We distinguish between knowledge of the graph theoretic structure of such networks (structural knowledge) and knowledge of what instantiates that structure (nonstructural knowledge). And we argue that this work provides structural knowledge of brain networks. We explore the significance of this conclusion for the scientific realism debate. We argue that our conclusion should not be understood as an instance of a global structural realist claim regarding the structure of the unobservable part of the world, but instead, as a local structural realist attitude towards brain networks in particular. And we argue that various local approaches to the realism debate, i.e., approaches that restrict realist commitments to particular theories and/or entities, are problematic insofar as they don't allow for the possibility of such a local structural realist attitude. Copyright © 2017 Elsevier Ltd. All rights reserved.

Exploiting the Synergy of Powder X-ray Diffraction and Solid-State NMR Spectroscopy in Structure Determination of Organic Molecular Solids

PubMed Central

2013-01-01

We report a strategy for structure determination of organic materials in which complete solid-state nuclear magnetic resonance (NMR) spectral data is utilized within the context of structure determination from powder X-ray diffraction (XRD) data. Following determination of the crystal structure from powder XRD data, first-principles density functional theory-based techniques within the GIPAW approach are exploited to calculate the solid-state NMR data for the structure, followed by careful scrutiny of the agreement with experimental solid-state NMR data. The successful application of this approach is demonstrated by structure determination of the 1:1 cocrystal of indomethacin and nicotinamide. The 1H and 13C chemical shifts calculated for the crystal structure determined from the powder XRD data are in excellent agreement with those measured experimentally, notably including the two-dimensional correlation of 1H and 13C chemical shifts for directly bonded 13C–1H moieties. The key feature of this combined approach is that the quality of the structure determined is assessed both against experimental powder XRD data and against experimental solid-state NMR data, thus providing a very robust validation of the veracity of the structure. PMID:24386493

Exploiting the Synergy of Powder X-ray Diffraction and Solid-State NMR Spectroscopy in Structure Determination of Organic Molecular Solids.

PubMed

Dudenko, Dmytro V; Williams, P Andrew; Hughes, Colan E; Antzutkin, Oleg N; Velaga, Sitaram P; Brown, Steven P; Harris, Kenneth D M

2013-06-13

We report a strategy for structure determination of organic materials in which complete solid-state nuclear magnetic resonance (NMR) spectral data is utilized within the context of structure determination from powder X-ray diffraction (XRD) data. Following determination of the crystal structure from powder XRD data, first-principles density functional theory-based techniques within the GIPAW approach are exploited to calculate the solid-state NMR data for the structure, followed by careful scrutiny of the agreement with experimental solid-state NMR data. The successful application of this approach is demonstrated by structure determination of the 1:1 cocrystal of indomethacin and nicotinamide. The 1 H and 13 C chemical shifts calculated for the crystal structure determined from the powder XRD data are in excellent agreement with those measured experimentally, notably including the two-dimensional correlation of 1 H and 13 C chemical shifts for directly bonded 13 C- 1 H moieties. The key feature of this combined approach is that the quality of the structure determined is assessed both against experimental powder XRD data and against experimental solid-state NMR data, thus providing a very robust validation of the veracity of the structure.

Towards a comprehensive understanding of emerging dynamics and function of pancreatic islets: A complex network approach. Comment on "Network science of biological systems at different scales: A review" by Gosak et al.

NASA Astrophysics Data System (ADS)

Loppini, Alessandro

2018-03-01

Complex network theory represents a comprehensive mathematical framework to investigate biological systems, ranging from sub-cellular and cellular scales up to large-scale networks describing species interactions and ecological systems. In their exhaustive and comprehensive work [1], Gosak et al. discuss several scenarios in which the network approach was able to uncover general properties and underlying mechanisms of cells organization and regulation, tissue functions and cell/tissue failure in pathology, by the study of chemical reaction networks, structural networks and functional connectivities.

What can one learn about material structure given a single first-principles calculation?

NASA Astrophysics Data System (ADS)

Rajen, Nicholas; Coh, Sinisa

2018-05-01

We extract a variable X from electron orbitals Ψn k and energies En k in the parent high-symmetry structure of a wide range of complex oxides: perovskites, rutiles, pyrochlores, and cristobalites. Even though calculation was done only in the parent structure, with no distortions, we show that X dictates material's true ground-state structure. We propose using Wannier functions to extract concealed variables such as X both for material structure prediction and for high-throughput approaches.

Symbolic Regression for the Estimation of Transfer Functions of Hydrological Models

NASA Astrophysics Data System (ADS)

Klotz, D.; Herrnegger, M.; Schulz, K.

2017-11-01

Current concepts for parameter regionalization of spatially distributed rainfall-runoff models rely on the a priori definition of transfer functions that globally map land surface characteristics (such as soil texture, land use, and digital elevation) into the model parameter space. However, these transfer functions are often chosen ad hoc or derived from small-scale experiments. This study proposes and tests an approach for inferring the structure and parametrization of possible transfer functions from runoff data to potentially circumvent these difficulties. The concept uses context-free grammars to generate possible proposition for transfer functions. The resulting structure can then be parametrized with classical optimization techniques. Several virtual experiments are performed to examine the potential for an appropriate estimation of transfer function, all of them using a very simple conceptual rainfall-runoff model with data from the Austrian Mur catchment. The results suggest that a priori defined transfer functions are in general well identifiable by the method. However, the deduction process might be inhibited, e.g., by noise in the runoff observation data, often leading to transfer function estimates of lower structural complexity.

Students Fail to Transfer Knowledge of Chromosome Structure to Topics Pertaining to Cell Division

ERIC Educational Resources Information Center

Newman, Dina L.; Catavero, Christina M.; Wright, L. Kate

2012-01-01

Cellular processes that rely on knowledge of molecular behavior are difficult for students to comprehend. For example, thorough understanding of meiosis requires students to integrate several complex concepts related to chromosome structure and function. Using a grounded theory approach, we have unified classroom observations, assessment data, and…

The Use of Structural Behavioral Assessment to Develop Interventions for Secondary Students Exhibiting Challenging Behaviors

ERIC Educational Resources Information Center

Losinski, Mickey; Maag, John W.; Katsiyannis, Antonis; Ryan, Joseph B.

2015-01-01

Structural behavioral assessment (SBA) involves a series of heuristic approaches similar to those used with functional behavioral assessment (FBA). It involves assessing contextual variables that precede the occurrence of a behavior. These variables have also been termed antecedents, setting events, or establishing operations. Once these variables…

Mentor Texts and the Coding of Academic Writing Structures: A Functional Approach

ERIC Educational Resources Information Center

Escobar Alméciga, Wilder Yesid; Evans, Reid

2014-01-01

The purpose of the present pedagogical experience was to address the English language writing needs of university-level students pursuing a degree in bilingual education with an emphasis in the teaching of English. Using mentor texts and coding academic writing structures, an instructional design was developed to directly address the shortcomings…

A Structured Approach to Homepage Design.

ERIC Educational Resources Information Center

Gregory, Gwen; Brown, M. Marlo

With no standards governing their creation, a variety of formats are being used for World Wide Web homepages. Some are well organized, present their information clearly, and work with multiple browsers. Others, however, are slow to load, function poorly with some Web browsing software, and are so badly structured that they are very difficult to…

Successful Outcomes from a Structured Curriculum Used in the Veterans Affairs Low Vision Intervention Trial

ERIC Educational Resources Information Center

Stelmack, Joan A.; Rinne, Stephen; Mancil, Rickilyn M.; Dean, Deborah; Moran, D'Anna; Tang, X. Charlene; Cummings, Roger; Massof, Robert W.

2008-01-01

A low vision rehabilitation program with a structured curriculum was evaluated in a randomized controlled trial. The treatment group demonstrated large improvements in self-reported visual function (reading, mobility, visual information processing, visual motor skills, and overall). The team approach and the protocols of the treatment program are…

Combined experimental and theoretical studies on the molecular structures, spectroscopy, and inhibitor activity of 3-(2-thienyl)acrylic acid through AIM, NBO,FT-IR, FT-Raman, UV and HOMO-LUMO analyses, and molecular docking

NASA Astrophysics Data System (ADS)

Issaoui, N.; Ghalla, H.; Bardak, F.; Karabacak, M.; Aouled Dlala, N.; Flakus, H. T.; Oujia, B.

2017-02-01

In this work, the molecular structures and vibrational spectral analyses of 3-(2-Theinyl)acrylic acid (3-2TAA) monomer and dimer structures have been reported by using density functional theory calculations at B3LYP/6-311++G(d,p) level of theory. The complete assignments of the fundamental vibrational modes were obtained using potential energy distribution. Intermolecular interactions were analyzed by orbital NBO and topological AIM approaches. The electronic properties have been carried out using TD-DFT approach. Great agreements between experimental and theoretical values were achieved throughout the analysis of structural parameters and spectroscopic features. Inhibitor characteristics on human monoamine oxidase B (MAOB) enzyme of two determined stable conformers of 3-2TAA (β and γ) along with four selective inhibitors, namely safinamide, a coumarin analogue, farnesol, and phenyethylhydrazine were investigated via molecular docking. Moreover, molecular electrostatic potential (MEP) and temperature dependency of thermodynamic functions have been reported.

Scale separation for multi-scale modeling of free-surface and two-phase flows with the conservative sharp interface method

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

Han, L.H., E-mail: Luhui.Han@tum.de; Hu, X.Y., E-mail: Xiangyu.Hu@tum.de; Adams, N.A., E-mail: Nikolaus.Adams@tum.de

In this paper we present a scale separation approach for multi-scale modeling of free-surface and two-phase flows with complex interface evolution. By performing a stimulus-response operation on the level-set function representing the interface, separation of resolvable and non-resolvable interface scales is achieved efficiently. Uniform positive and negative shifts of the level-set function are used to determine non-resolvable interface structures. Non-resolved interface structures are separated from the resolved ones and can be treated by a mixing model or a Lagrangian-particle model in order to preserve mass. Resolved interface structures are treated by the conservative sharp-interface model. Since the proposed scale separationmore » approach does not rely on topological information, unlike in previous work, it can be implemented in a straightforward fashion into a given level set based interface model. A number of two- and three-dimensional numerical tests demonstrate that the proposed method is able to cope with complex interface variations accurately and significantly increases robustness against underresolved interface structures.« less

Application of Nuclear Magnetic Resonance and Hybrid Methods to Structure Determination of Complex Systems.

PubMed

Prischi, Filippo; Pastore, Annalisa

2016-01-01

The current main challenge of Structural Biology is to undertake the structure determination of increasingly complex systems in the attempt to better understand their biological function. As systems become more challenging, however, there is an increasing demand for the parallel use of more than one independent technique to allow pushing the frontiers of structure determination and, at the same time, obtaining independent structural validation. The combination of different Structural Biology methods has been named hybrid approaches. The aim of this review is to critically discuss the most recent examples and new developments that have allowed structure determination or experimentally-based modelling of various molecular complexes selecting them among those that combine the use of nuclear magnetic resonance and small angle scattering techniques. We provide a selective but focused account of some of the most exciting recent approaches and discuss their possible further developments.

Structure modification and functionality of whey proteins: quantitative structure-activity relationship approach.

PubMed

Nakai, S; Li-Chan, E

1985-10-01

According to the original idea of quantitative structure-activity relationship, electric, hydrophobic, and structural parameters should be taken into consideration for elucidating functionality. Changes in these parameters are reflected in the property of protein solubility upon modification of whey proteins by heating. Although solubility is itself a functional property, it has been utilized to explain other functionalities of proteins. However, better correlations were obtained when hydrophobic parameters of the proteins were used in conjunction with solubility. Various treatments reported in the literature were applied to whey protein concentrate in an attempt to obtain whipping and gelling properties similar to those of egg white. Mapping simplex optimization was used to search for the best results. Improvement in whipping properties by pepsin hydrolysis may have been due to higher protein solubility, and good gelling properties resulting from polyphosphate treatment may have been due to an increase in exposable hydrophobicity. However, the results of angel food cake making were still unsatisfactory.

Structure-Function Perturbation and Dissociation of Tetrameric Urate Oxidase by High Hydrostatic Pressure

PubMed Central

Girard, Eric; Marchal, Stéphane; Perez, Javier; Finet, Stéphanie; Kahn, Richard; Fourme, Roger; Marassio, Guillaume; Dhaussy, Anne-Claire; Prangé, Thierry; Giffard, Marion; Dulin, Fabienne; Bonneté, Françoise; Lange, Reinhard; Abraini, Jacques H.; Mezouar, Mohamed; Colloc'h, Nathalie

2010-01-01

Abstract Structure-function relationships in the tetrameric enzyme urate oxidase were investigated using pressure perturbation. As the active sites are located at the interfaces between monomers, enzyme activity is directly related to the integrity of the tetramer. The effect of hydrostatic pressure on the enzyme was investigated by x-ray crystallography, small-angle x-ray scattering, and fluorescence spectroscopy. Enzymatic activity was also measured under pressure and after decompression. A global model, consistent with all measurements, discloses structural and functional details of the pressure-induced dissociation of the tetramer. Before dissociating, the pressurized protein adopts a conformational substate characterized by an expansion of its substrate binding pocket at the expense of a large neighboring hydrophobic cavity. This substate should be adopted by the enzyme during its catalytic mechanism, where the active site has to accommodate larger intermediates and product. The approach, combining several high-pressure techniques, offers a new (to our knowledge) means of exploring structural and functional properties of transient states relevant to protein mechanisms. PMID:20483346

PROFESS: a PROtein Function, Evolution, Structure and Sequence database

PubMed Central

Triplet, Thomas; Shortridge, Matthew D.; Griep, Mark A.; Stark, Jaime L.; Powers, Robert; Revesz, Peter

2010-01-01

The proliferation of biological databases and the easy access enabled by the Internet is having a beneficial impact on biological sciences and transforming the way research is conducted. There are ∼1100 molecular biology databases dispersed throughout the Internet. To assist in the functional, structural and evolutionary analysis of the abundant number of novel proteins continually identified from whole-genome sequencing, we introduce the PROFESS (PROtein Function, Evolution, Structure and Sequence) database. Our database is designed to be versatile and expandable and will not confine analysis to a pre-existing set of data relationships. A fundamental component of this approach is the development of an intuitive query system that incorporates a variety of similarity functions capable of generating data relationships not conceived during the creation of the database. The utility of PROFESS is demonstrated by the analysis of the structural drift of homologous proteins and the identification of potential pancreatic cancer therapeutic targets based on the observation of protein–protein interaction networks. Database URL: http://cse.unl.edu/∼profess/ PMID:20624718

Three-dimensional habitat structure and landscape genetics: a step forward in estimating functional connectivity.

PubMed

Milanesi, P; Holderegger, R; Bollmann, K; Gugerli, F; Zellweger, F

2017-02-01

Estimating connectivity among fragmented habitat patches is crucial for evaluating the functionality of ecological networks. However, current estimates of landscape resistance to animal movement and dispersal lack landscape-level data on local habitat structure. Here, we used a landscape genetics approach to show that high-fidelity habitat structure maps derived from Light Detection and Ranging (LiDAR) data critically improve functional connectivity estimates compared to conventional land cover data. We related pairwise genetic distances of 128 Capercaillie (Tetrao urogallus) genotypes to least-cost path distances at multiple scales derived from land cover data. Resulting β values of linear mixed effects models ranged from 0.372 to 0.495, while those derived from LiDAR ranged from 0.558 to 0.758. The identification and conservation of functional ecological networks suffering from habitat fragmentation and homogenization will thus benefit from the growing availability of detailed and contiguous data on three-dimensional habitat structure and associated habitat quality. © 2016 by the Ecological Society of America.

Functional Nanoclay Suspension for Printing-Then-Solidification of Liquid Materials.

PubMed

Jin, Yifei; Compaan, Ashley; Chai, Wenxuan; Huang, Yong

2017-06-14

Additive manufacturing (AM) enables the freeform fabrication of complex structures from various build materials. The objective of this study is to develop a novel Laponite nanoclay-enabled "printing-then-solidification" additive manufacturing approach to extrude complex three-dimensional (3D) structures made of various liquid build materials. Laponite, a member of the smectite mineral family, is investigated to serve as a yield-stress support bath material for the extrusion printing of liquid build materials. Using the printing-then-solidification approach, the printed structure remains liquid and retains its shape with the help of the Laponite support bath. Then the completed liquid structures are solidified in situ by applying suitable cross-linking mechanisms. Finally, the solidified structures are harvested from the Laponite nanoclay support bath for any further processing as needed. Due to its chemical and physical stability, liquid build materials with different solidification/curing/gelation mechanisms can be fabricated in the Laponite bath using the printing-then-solidification approach. The feasibility of the proposed Laponite-enabled printing-then-solidification approach is demonstrated by fabricating several complicated structures made of various liquid build materials, including alginate with ionic cross-linking, gelatin with thermal cross-linking, and SU-8 with photo-cross-linking. During gelatin structure printing, living cells are included and the postfabrication cell viability is above 90%.

Determination of structure and properties of molecular crystals from first principles.

PubMed

Szalewicz, Krzysztof

2014-11-18

CONSPECTUS: Until recently, it had been impossible to predict structures of molecular crystals just from the knowledge of the chemical formula for the constituent molecule(s). A solution of this problem has been achieved using intermolecular force fields computed from first principles. These fields were developed by calculating interaction energies of molecular dimers and trimers using an ab initio method called symmetry-adapted perturbation theory (SAPT) based on density-functional theory (DFT) description of monomers [SAPT(DFT)]. For clusters containing up to a dozen or so atoms, interaction energies computed using SAPT(DFT) are comparable in accuracy to the results of the best wave function-based methods, whereas the former approach can be applied to systems an order of magnitude larger than the latter. In fact, for monomers with a couple dozen atoms, SAPT(DFT) is about equally time-consuming as the supermolecular DFT approach. To develop a force field, SAPT(DFT) calculations are performed for a large number of dimer and possibly also trimer configurations (grid points in intermolecular coordinates), and the interaction energies are then fitted by analytic functions. The resulting force fields can be used to determine crystal structures and properties by applying them in molecular packing, lattice energy minimization, and molecular dynamics calculations. In this way, some of the first successful determinations of crystal structures were achieved from first principles, with crystal densities and lattice parameters agreeing with experimental values to within about 1%. Crystal properties obtained using similar procedures but empirical force fields fitted to crystal data have typical errors of several percent due to low sensitivity of empirical fits to interactions beyond those of the nearest neighbors. The first-principles approach has additional advantages over the empirical approach for notional crystals and cocrystals since empirical force fields can only be extrapolated to such cases. As an alternative to applying SAPT(DFT) in crystal structure calculations, one can use supermolecular DFT interaction energies combined with scaled dispersion energies computed from simple atom-atom functions, that is, use the so-called DFT+D approach. Whereas the standard DFT methods fail for intermolecular interactions, DFT+D performs reasonably well since the dispersion correction is used not only to provide the missing dispersion contribution but also to fix other deficiencies of DFT. The latter cancellation of errors is unphysical and can be avoided by applying the so-called dispersionless density functional, dlDF. In this case, the dispersion energies are added without any scaling. The dlDF+D method is also one of the best performing DFT+D methods. The SAPT(DFT)-based approach has been applied so far only to crystals with rigid monomers. It can be extended to partly flexible monomers, that is, to monomers with only a few internal coordinates allowed to vary. However, the costs will increase relative to rigid monomer cases since the number of grid points increases exponentially with the number of dimensions. One way around this problem is to construct force fields with approximate couplings between inter- and intramonomer degrees of freedom. Another way is to calculate interaction energies (and possibly forces) "on the fly", i.e., in each step of lattice energy minimization procedure. Such an approach would be prohibitively expensive if it replaced analytic force fields at all stages of the crystal predictions procedure, but it can be used to optimize a few dozen candidate structures determined by other methods.

Quantum Mechanics Approach to Hydration Energies and Structures of Alanine and Dialanine.

PubMed

Lanza, Giuseppe; Chiacchio, Maria A

2017-06-20

A systematic approach to the phenomena related to hydration of biomolecules is reported at the state of the art of electronic-structure methods. Large-scale CCSD(T), MP4-SDQ, MP2, and DFT(M06-2X) calculations for some hydrated complexes of alanine and dialanine (Ala⋅13 H 2 O, Ala 2 H + ⋅18 H 2 O, and Ala 2 ⋅18 H 2 O) are compared with experimental data and other elaborate modeling to assess the reliability of a simple bottom-up approach. The inclusion of a minimal number of water molecules for microhydration of the polar groups together with the polarizable continuum model is sufficient to reproduce the relative bulk thermodynamic functions of the considered biomolecules. These quantities depend on the adopted electronic-structure method, which should be chosen with great care. Nevertheless, the computationally feasible MP2 and M06-2X functionals with the aug-cc-pVTZ basis set satisfactorily reproduce values derived by high-level CCSD(T) and MP4-SDQ methods, and thus they are suitable for future developments of more elaborate and hence more biochemically significant peptides. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Convergent functional architecture of the superior parietal lobule unraveled with multimodal neuroimaging approaches.

PubMed

Wang, Jiaojian; Yang, Yong; Fan, Lingzhong; Xu, Jinping; Li, Changhai; Liu, Yong; Fox, Peter T; Eickhoff, Simon B; Yu, Chunshui; Jiang, Tianzi

2015-01-01

The superior parietal lobule (SPL) plays a pivotal role in many cognitive, perceptive, and motor-related processes. This implies that a mosaic of distinct functional and structural subregions may exist in this area. Recent studies have demonstrated that the ongoing spontaneous fluctuations in the brain at rest are highly structured and, like coactivation patterns, reflect the integration of cortical locations into long-distance networks. This suggests that the internal differentiation of a complex brain region may be revealed by interaction patterns that are reflected in different neuroimaging modalities. On the basis of this perspective, we aimed to identify a convergent functional organization of the SPL using multimodal neuroimaging approaches. The SPL was first parcellated based on its structural connections as well as on its resting-state connectivity and coactivation patterns. Then, post hoc functional characterizations and connectivity analyses were performed for each subregion. The three types of connectivity-based parcellations consistently identified five subregions in the SPL of each hemisphere. The two anterior subregions were found to be primarily involved in action processes and in visually guided visuomotor functions, whereas the three posterior subregions were primarily associated with visual perception, spatial cognition, reasoning, working memory, and attention. This parcellation scheme for the SPL was further supported by revealing distinct connectivity patterns for each subregion in all the used modalities. These results thus indicate a convergent functional architecture of the SPL that can be revealed based on different types of connectivity and is reflected by different functions and interactions. © 2014 Wiley Periodicals, Inc.

Structure-based analysis of catalysis and substrate definition in the HIT protein family.

PubMed

Lima, C D; Klein, M G; Hendrickson, W A

1997-10-10

The histidine triad (HIT) protein family is among the most ubiquitous and highly conserved in nature, but a biological activity has not yet been identified for any member of the HIT family. Fragile histidine triad protein (FHIT) and protein kinase C interacting protein (PKCI) were used in a structure-based approach to elucidate characteristics of in vivo ligands and reactions. Crystallographic structures of apo, substrate analog, pentacovalent transition-state analog, and product states of both enzymes reveal a catalytic mechanism and define substrate characteristics required for catalysis, thus unifying the HIT family as nucleotidyl hydrolases, transferases, or both. The approach described here may be useful in identifying structure-function relations between protein families identified through genomics.

A new scaling approach for the mesoscale simulation of magnetic domain structures using Monte Carlo simulations

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

Radhakrishnan, B.; Eisenbach, M.; Burress, Timothy A.

2017-01-24

A new scaling approach has been proposed for the spin exchange and the dipole–dipole interaction energy as a function of the system size. The computed scaling laws are used in atomistic Monte Carlo simulations of magnetic moment evolution to predict the transition from single domain to a vortex structure as the system size increases. The width of a 180° – domain wall extracted from the simulated structures is in close agreement with experimentally values for an F–Si alloy. In conclusion, the transition size from a single domain to a vortex structure is also in close agreement with theoretically predicted andmore » experimentally measured values for Fe.« less

Covariant extension of the GPD overlap representation at low Fock states

DOE PAGES

Chouika, N.; Mezrag, C.; Moutarde, H.; ...

2017-12-26

Here, we present a novel approach to compute generalized parton distributions within the lightfront wave function overlap framework. We show how to systematically extend generalized parton distributions computed within the DGLAP region to the ERBL one, fulfilling at the same time both the polynomiality and positivity conditions. We exemplify our method using pion lightfront wave functions inspired by recent results of non-perturbative continuum techniques and algebraic nucleon lightfront wave functions. We also test the robustness of our algorithm on reggeized phenomenological parameterizations. This approach paves the way to a better understanding of the nucleon structure from non-perturbative techniques and tomore » a unification of generalized parton distributions and transverse momentum dependent parton distribution functions phenomenology through lightfront wave functions.« less

Stress Intensity Factors for Cracking Metal Structures under Rapid Thermal Loading. Volume 2. Theoretical Background

DTIC Science & Technology

1989-08-01

thermal pulse loadings. The work couples a Green’s function integration technique for transient thermal stresses with the well-known influence ... function approach for calculating stress intensity factors. A total of seven most commonly used crack models were investigated in this study. A computer

The Inexpressive Male: Functional-Conflict and Role Theory as Contrasting Explanations.

ERIC Educational Resources Information Center

Balswick, Jack

1979-01-01

Compares functional-conflict and role theory perspectives in their ability to explain male inexpressiveness. The role theory approach incorporates the individual and the social structure in explaining male inexpressiveness. Change in male expressiveness can be expected if males are encouraged to devote more time and energy to emotionally laden…

Designing sustainable soils in Earth's critical zone

NASA Astrophysics Data System (ADS)

Banwart, Steven Allan; de Souza, Danielle Maia; Menon, Manoj; Nikolaidis, Nikolaos; Panagos, Panos; Vala Ragnardsdottir, Kristin; Rousseva, Svelta; van Gaans, Pauline

2014-05-01

The demographic drivers of increasing human population and wealth are creating tremendous environmental pressures from growing intensity of land use, resulting in soil and land degradation worldwide. Environmental services are provided through multiple soil functions that include biomass production, water storage and transmission, nutrient transformations, contaminant attenuation, carbon and nitrogen storage, providing habitat and maintaining the genetic diversity of the land environment. One of the greatest challenges of the 21st century is to identify key risks to soil, and to design mitigation strategies to manage these risks and to enhance soil functions that can last into the future. The scientific study of Earth's Critical Zone (CZ), the thin surface layer that extends vertically from the top of the tree canopy to the bottom of aquifers, provides an essential integrating scientific framework to study, protect and enhance soil functions. The research hypothesis is that soil structure, the geometric architecture of solids, pores and biomass, is a critical indicator and essential factor of productive soil functions. The experimental design selects a network of Critical Zone Observatories (CZOs) as advanced field research sites along a gradient of land use intensity in order to quantify soil structure and soil processes that dictate the flows and transformations of material and energy as soil functions. The CZOs focus multidisciplinary expertise on soil processes, field observation and data interpretation, management science and ecological economics. Computational simulation of biophysical processes provides a quantitative method of integration for the range of theory and observations that are required to quantify the linkages between changes in soil structure and soil functions. Key results demonstrate that changes in soil structure can be quantified through the inputs of organic carbon and nitrogen from plant productivity and microbial activity, coupled with particle aggregation dynamics and organic matter mineralization. Simulation results show that soil structure is highly dynamic and is sensitive to organic matter production and minearlisation rates as influenced by vegetation, tillage and organic carbon amendments. These results point to a step-change in the capability to design soil management and land use through computational simulation. This approach of "sustainability by design" describes the mechanistic process linkages that exist between the above-ground inputs to the CZ and the internal processes that produce soil functions. This approach provides a rational, scientific approach to selecting points of intervention with the CZ in order to design methods to mitigate soil threats and to enhance and sustain vital soil functions. Furthermore, this approach provides a successful pilot study to the use of international networks of CZOs as a planetary-scale laboratory to test the response of CZ process rates along gradients of global environmental change - and to test adaptation strategies to manage the risks arising from the CZ impacts. Acknowledgements. The authors acknowledge the substantial contributions of the entire team of investigators and funding of the SoilTrEC project (EC FP7, agreement no. 244118; www.soiltrec.eu).

Identifying functionally informative evolutionary sequence profiles.

PubMed

Gil, Nelson; Fiser, Andras

2018-04-15

Multiple sequence alignments (MSAs) can provide essential input to many bioinformatics applications, including protein structure prediction and functional annotation. However, the optimal selection of sequences to obtain biologically informative MSAs for such purposes is poorly explored, and has traditionally been performed manually. We present Selection of Alignment by Maximal Mutual Information (SAMMI), an automated, sequence-based approach to objectively select an optimal MSA from a large set of alternatives sampled from a general sequence database search. The hypothesis of this approach is that the mutual information among MSA columns will be maximal for those MSAs that contain the most diverse set possible of the most structurally and functionally homogeneous protein sequences. SAMMI was tested to select MSAs for functional site residue prediction by analysis of conservation patterns on a set of 435 proteins obtained from protein-ligand (peptides, nucleic acids and small substrates) and protein-protein interaction databases. Availability and implementation: A freely accessible program, including source code, implementing SAMMI is available at https://github.com/nelsongil92/SAMMI.git. andras.fiser@einstein.yu.edu. Supplementary data are available at Bioinformatics online.

Modulation of Endothelial Glycocalyx Structure under Inflammatory Conditions

PubMed Central

Kolářová, Hana; Ambrůzová, Barbora; Švihálková Šindlerová, Lenka; Klinke, Anna; Kubala, Lukáš

2014-01-01

The glycocalyx of the endothelium is an intravascular compartment that creates a barrier between circulating blood and the vessel wall. The glycocalyx is suggested to play an important role in numerous physiological processes including the regulation of vascular permeability, the prevention of the margination of blood cells to the vessel wall, and the transmission of shear stress. Various theoretical models and experimental approaches provide data about changes to the structure and functions of the glycocalyx under various types of inflammatory conditions. These alterations are suggested to promote inflammatory processes in vessels and contribute to the pathogenesis of number of diseases. In this review we summarize current knowledge about the modulation of the glycocalyx under inflammatory conditions and the consequences for the course of inflammation in vessels. The structure and functions of endothelial glycocalyx are briefly discussed in the context of methodological approaches regarding the determination of endothelial glycocalyx and the uncertainty and challenges involved in glycocalyx structure determination. In addition, the modulation of glycocalyx structure under inflammatory conditions and the possible consequences for pathogenesis of selected diseases and medical conditions (in particular, diabetes, atherosclerosis, ischemia/reperfusion, and sepsis) are summarized. Finally, therapeutic strategies to ameliorate glycocalyx dysfunction suggested by various authors are discussed. PMID:24803742

Motivation, emotion regulation, and the latent structure of psychopathology: An integrative and convergent historical perspective.

PubMed

Beauchaine, Theodore P; Zisner, Aimee

2017-09-01

Motivational models of psychopathology have long been advanced by psychophysiologists, and have provided key insights into neurobiological mechanisms of a wide range of psychiatric disorders. These accounts emphasize individual differences in activity and reactivity of bottom-up, subcortical neural systems of approach and avoidance in affecting behavior. Largely independent literatures emphasize the roles of top-down, cortical deficits in emotion regulation and executive function in conferring vulnerability to psychopathology. To date however, few models effectively integrate functions performed by bottom-up emotion generation system with those performed by top-down emotion regulation systems in accounting for alternative expressions of psychopathology. In this article, we present such a model, and describe how it accommodates the well replicated bifactor structure of psychopathology. We describe how excessive approach motivation maps directly into externalizing liability, how excessive passive avoidance motivation maps directly into internalizing liability, and how emotion dysregulation and executive function map onto general liability. This approach is consistent with the Research Domain Criteria initiative, which assumes that a limited number of brain systems interact to confer vulnerability to many if not most forms of psychopathology. Copyright © 2017 Elsevier B.V. All rights reserved.

Viewing Golgi structure and function from a different perspective--insights from electron tomography.

PubMed

Marsh, Brad J; Pavelka, Margit

2013-01-01

Historically, ultrastructural investigations, which have focused on elucidating the biological idiosyncrasies of the Golgi apparatus, have tended towards oversimplified or fallacious hypotheses when postulating how the Golgi apparatus reorganizes itself both structurally and functionally to fulfill the plethora of cellular processes underpinned by this complex organelle. Key questions are still unanswered with regard to how changes in Golgi architecture correlate so reproducibly to changes in its functional priorities under different physiological conditions or experimental perturbations. This fact alone serves to highlight how the technical limitations associated with conventional two-dimensional imaging approaches employed in the past failed to adequately capture the extraordinary complexity of the Golgi's three-dimensional (3D) structure-now a hallmark of this challenging organelle. Consequently, this has hampered progress towards developing a clear understanding of how changes in its structure and function typically occur in parallel. In this chapter, we highlight but a few of the significant new insights regarding variations in the Golgi's structure-function relationships that have been afforded over recent years through advanced electron microscopic techniques for 3D image reconstruction, commonly referred to as electron tomography. Copyright © 2013 Elsevier Inc. All rights reserved.

Systematic approach to developing empirical interatomic potentials for III-N semiconductors

NASA Astrophysics Data System (ADS)

Ito, Tomonori; Akiyama, Toru; Nakamura, Kohji

2016-05-01

A systematic approach to the derivation of empirical interatomic potentials is developed for III-N semiconductors with the aid of ab initio calculations. The parameter values of empirical potential based on bond order potential are determined by reproducing the cohesive energy differences among 3-fold coordinated hexagonal, 4-fold coordinated zinc blende, wurtzite, and 6-fold coordinated rocksalt structures in BN, AlN, GaN, and InN. The bond order p is successfully introduced as a function of the coordination number Z in the form of p = a exp(-bZn ) if Z ≤ 4 and p = (4/Z)α if Z ≥ 4 in empirical interatomic potential. Moreover, the energy difference between wurtzite and zinc blende structures can be successfully evaluated by considering interaction beyond the second-nearest neighbors as a function of ionicity. This approach is feasible for developing empirical interatomic potentials applicable to a system consisting of poorly coordinated atoms at surfaces and interfaces including nanostructures.

Ab initio calculations of the concentration dependent band gap reduction in dilute nitrides

NASA Astrophysics Data System (ADS)

Rosenow, Phil; Bannow, Lars C.; Fischer, Eric W.; Stolz, Wolfgang; Volz, Kerstin; Koch, Stephan W.; Tonner, Ralf

2018-02-01

While being of persistent interest for the integration of lattice-matched laser devices with silicon circuits, the electronic structure of dilute nitride III/V-semiconductors has presented a challenge to ab initio computational approaches. The origin of the computational problems is the strong distortion exerted by the N atoms on most host materials. Here, these issues are resolved by combining density functional theory calculations based on the meta-GGA functional presented by Tran and Blaha (TB09) with a supercell approach for the dilute nitride Ga(NAs). Exploring the requirements posed to supercells, it is shown that the distortion field of a single N atom must be allowed to decrease so far that it does not overlap with its periodic images. This also prevents spurious electronic interactions between translational symmetric atoms, allowing us to compute band gaps in very good agreement with experimentally derived reference values. In addition to existing approaches, these results offer a promising ab initio avenue to the electronic structure of dilute nitride semiconductor compounds.

Learning Grasp Context Distinctions that Generalize

NASA Technical Reports Server (NTRS)

Platt, Robert; Grupen, Roderic A.; Fagg, Andrew H.

2006-01-01

Control-based approaches to grasp synthesis create grasping behavior by sequencing and combining control primitives. In the absence of any other structure, these approaches must evaluate a large number of feasible control sequences as a function of object shape, object pose, and task. This work explores a new approach to grasp synthesis that limits consideration to variations on a generalized localize-reach-grasp control policy. A new learning algorithm, known as schema structured learning, is used to learn which instantiations of the generalized policy are most likely to lead to a successful grasp in different problem contexts. Two experiments are described where Dexter, a bimanual upper torso, learns to select an appropriate grasp strategy as a function of object eccentricity and orientation. In addition, it is shown that grasp skills learned in this way can generalize to new objects. Results are presented showing that after learning how to grasp a small, representative set of objects, the robot's performance quantitatively improves for similar objects that it has not experienced before.

Application of Machine Learning Approaches for Protein-protein Interactions Prediction.

PubMed

Zhang, Mengying; Su, Qiang; Lu, Yi; Zhao, Manman; Niu, Bing

2017-01-01

Proteomics endeavors to study the structures, functions and interactions of proteins. Information of the protein-protein interactions (PPIs) helps to improve our knowledge of the functions and the 3D structures of proteins. Thus determining the PPIs is essential for the study of the proteomics. In this review, in order to study the application of machine learning in predicting PPI, some machine learning approaches such as support vector machine (SVM), artificial neural networks (ANNs) and random forest (RF) were selected, and the examples of its applications in PPIs were listed. SVM and RF are two commonly used methods. Nowadays, more researchers predict PPIs by combining more than two methods. This review presents the application of machine learning approaches in predicting PPI. Many examples of success in identification and prediction in the area of PPI prediction have been discussed, and the PPIs research is still in progress. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Basic Emotions in Human Neuroscience: Neuroimaging and Beyond.

PubMed

Celeghin, Alessia; Diano, Matteo; Bagnis, Arianna; Viola, Marco; Tamietto, Marco

2017-01-01

The existence of so-called 'basic emotions' and their defining attributes represents a long lasting and yet unsettled issue in psychology. Recently, neuroimaging evidence, especially related to the advent of neuroimaging meta-analytic methods, has revitalized this debate in the endeavor of systems and human neuroscience. The core theme focuses on the existence of unique neural bases that are specific and characteristic for each instance of basic emotion. Here we review this evidence, outlining contradictory findings, strengths and limits of different approaches. Constructionism dismisses the existence of dedicated neural structures for basic emotions, considering that the assumption of a one-to-one relationship between neural structures and their functions is central to basic emotion theories. While these critiques are useful to pinpoint current limitations of basic emotions theories, we argue that they do not always appear equally generative in fostering new testable accounts on how the brain relates to affective functions. We then consider evidence beyond PET and fMRI, including results concerning the relation between basic emotions and awareness and data from neuropsychology on patients with focal brain damage. Evidence from lesion studies are indeed particularly informative, as they are able to bring correlational evidence typical of neuroimaging studies to causation, thereby characterizing which brain structures are necessary for, rather than simply related to, basic emotion processing. These other studies shed light on attributes often ascribed to basic emotions, such as automaticity of perception, quick onset, and brief duration. Overall, we consider that evidence in favor of the neurobiological underpinnings of basic emotions outweighs dismissive approaches. In fact, the concept of basic emotions can still be fruitful, if updated to current neurobiological knowledge that overcomes traditional one-to-one localization of functions in the brain. In particular, we propose that the structure-function relationship between brain and emotions is better described in terms of pluripotentiality, which refers to the fact that one neural structure can fulfill multiple functions, depending on the functional network and pattern of co-activations displayed at any given moment.

Integrative computational models of cardiac arrhythmias -- simulating the structurally realistic heart

PubMed Central

Trayanova, Natalia A; Tice, Brock M

2009-01-01

Simulation of cardiac electrical function, and specifically, simulation aimed at understanding the mechanisms of cardiac rhythm disorders, represents an example of a successful integrative multiscale modeling approach, uncovering emergent behavior at the successive scales in the hierarchy of structural complexity. The goal of this article is to present a review of the integrative multiscale models of realistic ventricular structure used in the quest to understand and treat ventricular arrhythmias. It concludes with the new advances in image-based modeling of the heart and the promise it holds for the development of individualized models of ventricular function in health and disease. PMID:20628585

Unraveling secrets of telomeres: one molecule at a time

PubMed Central

Lin, Jiangguo; Kaur, Parminder; Countryman, Preston; Opresko, Patricia L.; Wang, Hong

2016-01-01

Telomeres play important roles in maintaining the stability of linear chromosomes. Telomere maintenance involves dynamic actions of multiple proteins interacting with long repetitive sequences and complex dynamic DNA structures, such as G-quadruplexes, T-loops and t-circles. Given the heterogeneity and complexity of telomeres, single-molecule approaches are essential to fully understand the structure-function relationships that govern telomere maintenance. In this review, we present a brief overview of the principles of single-molecule imaging and manipulation techniques. We then highlight results obtained from applying these single-molecule techniques for studying structure, dynamics and functions of G-quadruplexes, telomerase, and shelterin proteins. PMID:24569170

Unsteady Aerodynamic Force Sensing from Strain Data

NASA Technical Reports Server (NTRS)

Pak, Chan-Gi

2017-01-01

A simple approach for computing unsteady aerodynamic forces from simulated measured strain data is proposed in this study. First, the deflection and slope of the structure are computed from the unsteady strain using the two-step approach. Velocities and accelerations of the structure are computed using the autoregressive moving average model, on-line parameter estimator, low-pass filter, and a least-squares curve fitting method together with analytical derivatives with respect to time. Finally, aerodynamic forces over the wing are computed using modal aerodynamic influence coefficient matrices, a rational function approximation, and a time-marching algorithm.

Effect of ladder diagrams on optical absorption spectra in a quasiparticle self-consistent GW framework

NASA Astrophysics Data System (ADS)

Cunningham, Brian; Grüning, Myrta; Azarhoosh, Pooya; Pashov, Dimitar; van Schilfgaarde, Mark

2018-03-01

We present an approach to calculate the optical absorption spectra that combines the quasiparticle self-consistent GW method [Phys. Rev. B 76, 165106 (2007), 10.1103/PhysRevB.76.165106] for the electronic structure with the solution of the ladder approximation to the Bethe-Salpeter equation for the macroscopic dielectric function. The solution of the Bethe-Salpeter equation has been implemented within an all-electron framework, using a linear muffin-tin orbital basis set, with the contribution from the nonlocal self-energy to the transition dipole moments (in the optical limit) evaluated explicitly. This approach addresses those systems whose electronic structure is poorly described within the standard perturbative GW approaches with density-functional theory calculations as a starting point. The merits of this approach have been exemplified by calculating optical absorption spectra of a strongly correlated transition metal oxide, NiO, and a narrow gap semiconductor, Ge. In both cases, the calculated spectrum is in good agreement with the experiment. It is also shown that for systems whose electronic structure is well-described within the standard perturbative GW , such as Si, LiF, and h -BN , the performance of the present approach is in general comparable to the standard GW plus Bethe-Salpeter equation. It is argued that both vertex corrections to the electronic screening and the electron-phonon interaction are responsible for the observed systematic overestimation of the fundamental band gap and spectrum onset.

Probabilistic simulation of uncertainties in thermal structures

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Shiao, Michael

1990-01-01

Development of probabilistic structural analysis methods for hot structures is a major activity at Lewis Research Center. It consists of five program elements: (1) probabilistic loads; (2) probabilistic finite element analysis; (3) probabilistic material behavior; (4) assessment of reliability and risk; and (5) probabilistic structural performance evaluation. Recent progress includes: (1) quantification of the effects of uncertainties for several variables on high pressure fuel turbopump (HPFT) blade temperature, pressure, and torque of the Space Shuttle Main Engine (SSME); (2) the evaluation of the cumulative distribution function for various structural response variables based on assumed uncertainties in primitive structural variables; (3) evaluation of the failure probability; (4) reliability and risk-cost assessment, and (5) an outline of an emerging approach for eventual hot structures certification. Collectively, the results demonstrate that the structural durability/reliability of hot structural components can be effectively evaluated in a formal probabilistic framework. In addition, the approach can be readily extended to computationally simulate certification of hot structures for aerospace environments.