Hierarchical Ensemble Methods for Protein Function Prediction

PubMed Central

2014-01-01

Protein function prediction is a complex multiclass multilabel classification problem, characterized by multiple issues such as the incompleteness of the available annotations, the integration of multiple sources of high dimensional biomolecular data, the unbalance of several functional classes, and the difficulty of univocally determining negative examples. Moreover, the hierarchical relationships between functional classes that characterize both the Gene Ontology and FunCat taxonomies motivate the development of hierarchy-aware prediction methods that showed significantly better performances than hierarchical-unaware “flat” prediction methods. In this paper, we provide a comprehensive review of hierarchical methods for protein function prediction based on ensembles of learning machines. According to this general approach, a separate learning machine is trained to learn a specific functional term and then the resulting predictions are assembled in a “consensus” ensemble decision, taking into account the hierarchical relationships between classes. The main hierarchical ensemble methods proposed in the literature are discussed in the context of existing computational methods for protein function prediction, highlighting their characteristics, advantages, and limitations. Open problems of this exciting research area of computational biology are finally considered, outlining novel perspectives for future research. PMID:25937954

Unraveling protein catalysis through neutron diffraction

NASA Astrophysics Data System (ADS)

Myles, Dean

Neutron scattering and diffraction are exquisitely sensitive to the location, concentration and dynamics of hydrogen atoms in materials and provide a powerful tool for the characterization of structure-function and interfacial relationships in biological systems. Modern neutron scattering facilities offer access to a sophisticated, non-destructive suite of instruments for biophysical characterization that provide spatial and dynamic information spanning from Angstroms to microns and from picoseconds to microseconds, respectively. Applications range from atomic-resolution analysis of individual hydrogen atoms in enzymes, through to multi-scale analysis of hierarchical structures and assemblies in biological complexes, membranes and in living cells. Here we describe how the precise location of protein and water hydrogen atoms using neutron diffraction provides a more complete description of the atomic and electronic structures of proteins, enabling key questions concerning enzyme reaction mechanisms, molecular recognition and binding and protein-water interactions to be addressed. Current work is focused on understanding how molecular structure and dynamics control function in photosynthetic, cell signaling and DNA repair proteins. We will highlight recent studies that provide detailed understanding of the physiochemical mechanisms through which proteins recognize ligands and catalyze reactions, and help to define and understand the key principles involved.

SCOWLP classification: Structural comparison and analysis of protein binding regions

PubMed Central

Teyra, Joan; Paszkowski-Rogacz, Maciej; Anders, Gerd; Pisabarro, M Teresa

2008-01-01

Background Detailed information about protein interactions is critical for our understanding of the principles governing protein recognition mechanisms. The structures of many proteins have been experimentally determined in complex with different ligands bound either in the same or different binding regions. Thus, the structural interactome requires the development of tools to classify protein binding regions. A proper classification may provide a general view of the regions that a protein uses to bind others and also facilitate a detailed comparative analysis of the interacting information for specific protein binding regions at atomic level. Such classification might be of potential use for deciphering protein interaction networks, understanding protein function, rational engineering and design. Description Protein binding regions (PBRs) might be ideally described as well-defined separated regions that share no interacting residues one another. However, PBRs are often irregular, discontinuous and can share a wide range of interacting residues among them. The criteria to define an individual binding region can be often arbitrary and may differ from other binding regions within a protein family. Therefore, the rational behind protein interface classification should aim to fulfil the requirements of the analysis to be performed. We extract detailed interaction information of protein domains, peptides and interfacial solvent from the SCOWLP database and we classify the PBRs of each domain family. For this purpose, we define a similarity index based on the overlapping of interacting residues mapped in pair-wise structural alignments. We perform our classification with agglomerative hierarchical clustering using the complete-linkage method. Our classification is calculated at different similarity cut-offs to allow flexibility in the analysis of PBRs, feature especially interesting for those protein families with conflictive binding regions. The hierarchical classification of PBRs is implemented into the SCOWLP database and extends the SCOP classification with three additional family sub-levels: Binding Region, Interface and Contacting Domains. SCOWLP contains 9,334 binding regions distributed within 2,561 families. In 65% of the cases we observe families containing more than one binding region. Besides, 22% of the regions are forming complex with more than one different protein family. Conclusion The current SCOWLP classification and its web application represent a framework for the study of protein interfaces and comparative analysis of protein family binding regions. This comparison can be performed at atomic level and allows the user to study interactome conservation and variability. The new SCOWLP classification may be of great utility for reconstruction of protein complexes, understanding protein networks and ligand design. SCOWLP will be updated with every SCOP release. The web application is available at . PMID:18182098

Statistical discovery of site inter-dependencies in sub-molecular hierarchical protein structuring

PubMed Central

2012-01-01

Background Much progress has been made in understanding the 3D structure of proteins using methods such as NMR and X-ray crystallography. The resulting 3D structures are extremely informative, but do not always reveal which sites and residues within the structure are of special importance. Recently, there are indications that multiple-residue, sub-domain structural relationships within the larger 3D consensus structure of a protein can be inferred from the analysis of the multiple sequence alignment data of a protein family. These intra-dependent clusters of associated sites are used to indicate hierarchical inter-residue relationships within the 3D structure. To reveal the patterns of associations among individual amino acids or sub-domain components within the structure, we apply a k-modes attribute (aligned site) clustering algorithm to the ubiquitin and transthyretin families in order to discover associations among groups of sites within the multiple sequence alignment. We then observe what these associations imply within the 3D structure of these two protein families. Results The k-modes site clustering algorithm we developed maximizes the intra-group interdependencies based on a normalized mutual information measure. The clusters formed correspond to sub-structural components or binding and interface locations. Applying this data-directed method to the ubiquitin and transthyretin protein family multiple sequence alignments as a test bed, we located numerous interesting associations of interdependent sites. These clusters were then arranged into cluster tree diagrams which revealed four structural sub-domains within the single domain structure of ubiquitin and a single large sub-domain within transthyretin associated with the interface among transthyretin monomers. In addition, several clusters of mutually interdependent sites were discovered for each protein family, each of which appear to play an important role in the molecular structure and/or function. Conclusions Our results demonstrate that the method we present here using a k-modes site clustering algorithm based on interdependency evaluation among sites obtained from a sequence alignment of homologous proteins can provide significant insights into the complex, hierarchical inter-residue structural relationships within the 3D structure of a protein family. PMID:22793672

Statistical discovery of site inter-dependencies in sub-molecular hierarchical protein structuring.

PubMed

Durston, Kirk K; Chiu, David Ky; Wong, Andrew Kc; Li, Gary Cl

2012-07-13

Much progress has been made in understanding the 3D structure of proteins using methods such as NMR and X-ray crystallography. The resulting 3D structures are extremely informative, but do not always reveal which sites and residues within the structure are of special importance. Recently, there are indications that multiple-residue, sub-domain structural relationships within the larger 3D consensus structure of a protein can be inferred from the analysis of the multiple sequence alignment data of a protein family. These intra-dependent clusters of associated sites are used to indicate hierarchical inter-residue relationships within the 3D structure. To reveal the patterns of associations among individual amino acids or sub-domain components within the structure, we apply a k-modes attribute (aligned site) clustering algorithm to the ubiquitin and transthyretin families in order to discover associations among groups of sites within the multiple sequence alignment. We then observe what these associations imply within the 3D structure of these two protein families. The k-modes site clustering algorithm we developed maximizes the intra-group interdependencies based on a normalized mutual information measure. The clusters formed correspond to sub-structural components or binding and interface locations. Applying this data-directed method to the ubiquitin and transthyretin protein family multiple sequence alignments as a test bed, we located numerous interesting associations of interdependent sites. These clusters were then arranged into cluster tree diagrams which revealed four structural sub-domains within the single domain structure of ubiquitin and a single large sub-domain within transthyretin associated with the interface among transthyretin monomers. In addition, several clusters of mutually interdependent sites were discovered for each protein family, each of which appear to play an important role in the molecular structure and/or function. Our results demonstrate that the method we present here using a k-modes site clustering algorithm based on interdependency evaluation among sites obtained from a sequence alignment of homologous proteins can provide significant insights into the complex, hierarchical inter-residue structural relationships within the 3D structure of a protein family.

HPEPDOCK: a web server for blind peptide-protein docking based on a hierarchical algorithm.

PubMed

Zhou, Pei; Jin, Bowen; Li, Hao; Huang, Sheng-You

2018-05-09

Protein-peptide interactions are crucial in many cellular functions. Therefore, determining the structure of protein-peptide complexes is important for understanding the molecular mechanism of related biological processes and developing peptide drugs. HPEPDOCK is a novel web server for blind protein-peptide docking through a hierarchical algorithm. Instead of running lengthy simulations to refine peptide conformations, HPEPDOCK considers the peptide flexibility through an ensemble of peptide conformations generated by our MODPEP program. For blind global peptide docking, HPEPDOCK obtained a success rate of 33.3% in binding mode prediction on a benchmark of 57 unbound cases when the top 10 models were considered, compared to 21.1% for pepATTRACT server. HPEPDOCK also performed well in docking against homology models and obtained a success rate of 29.8% within top 10 predictions. For local peptide docking, HPEPDOCK achieved a high success rate of 72.6% on a benchmark of 62 unbound cases within top 10 predictions, compared to 45.2% for HADDOCK peptide protocol. Our HPEPDOCK server is computationally efficient and consumed an average of 29.8 mins for a global peptide docking job and 14.2 mins for a local peptide docking job. The HPEPDOCK web server is available at http://huanglab.phys.hust.edu.cn/hpepdock/.

Alpha-Helical Protein Domains Unify Strength and Robustness through Hierarchical Nanostructures

DTIC Science & Technology

2009-01-23

backbone atom (hydrogen donor) of peptide i + 4 in the polypeptide chain. Consequently, at each convolution , 3.5 H- bonds are found in a parallel...signaling and deformation behavior of cytoskeletal protein networks in cells (e.g. intermediate filaments vimentin and lamin as well as actin [7, 8... convolution . The Hierarchical Bell model enables one to predict the strength of different hierarchical bond arrangements as a function of the

Self-Assembling Multi-Component Nanofibers for Strong Bioinspired Underwater Adhesives

PubMed Central

Zhong, Chao; Gurry, Thomas; Cheng, Allen A; Downey, Jordan; Deng, Zhengtao; Stultz, Collin M.; Lu, Timothy K

2014-01-01

Many natural underwater adhesives harness hierarchically assembled amyloid nanostructures to achieve strong and robust interfacial adhesion under dynamic and turbulent environments. Despite recent advances, our understanding of the molecular design, self-assembly, and structure-function relationship of those natural amyloid fibers remains limited. Thus, designing biomimetic amyloid-based adhesives remains challenging. Here, we report strong and multi-functional underwater adhesives obtained from fusing mussel foot proteins (Mfps) of Mytilus galloprovincialis with CsgA proteins, the major subunit of Escherichia coli amyloid curli fibers. These hybrid molecular materials hierarchically self-assemble into higher-order structures, in which, according to molecular dynamics simulations, disordered adhesive Mfp domains are exposed on the exterior of amyloid cores formed by CsgA. Our fibers have an underwater adhesion energy approaching 20.9 mJ/m2, which is 1.5 times greater than the maximum of bio-inspired and bio-derived protein-based underwater adhesives reported thus far. Moreover, they outperform Mfps or curli fibers taken on their own at all pHs and exhibit better tolerance to auto-oxidation than Mfps at pH ≥7.0. This work establishes a platform for engineering multi-component self-assembling materials inspired by nature. PMID:25240674

Polycyclic aromatic hydrocarbon metabolic network in Mycobacterium vanbaalenii PYR-1.

PubMed

Kweon, Ohgew; Kim, Seong-Jae; Holland, Ricky D; Chen, Hongyan; Kim, Dae-Wi; Gao, Yuan; Yu, Li-Rong; Baek, Songjoon; Baek, Dong-Heon; Ahn, Hongsik; Cerniglia, Carl E

2011-09-01

This study investigated a metabolic network (MN) from Mycobacterium vanbaalenii PYR-1 for polycyclic aromatic hydrocarbons (PAHs) from the perspective of structure, behavior, and evolution, in which multilayer omics data are integrated. Initially, we utilized a high-throughput proteomic analysis to assess the protein expression response of M. vanbaalenii PYR-1 to seven different aromatic compounds. A total of 3,431 proteins (57.38% of the genome-predicted proteins) were identified, which included 160 proteins that seemed to be involved in the degradation of aromatic hydrocarbons. Based on the proteomic data and the previous metabolic, biochemical, physiological, and genomic information, we reconstructed an experiment-based system-level PAH-MN. The structure of PAH-MN, with 183 metabolic compounds and 224 chemical reactions, has a typical scale-free nature. The behavior and evolution of the PAH-MN reveals a hierarchical modularity with funnel effects in structure/function and intimate association with evolutionary modules of the functional modules, which are the ring cleavage process (RCP), side chain process (SCP), and central aromatic process (CAP). The 189 commonly upregulated proteins in all aromatic hydrocarbon treatments provide insights into the global adaptation to facilitate the PAH metabolism. Taken together, the findings of our study provide the hierarchical viewpoint from genes/proteins/metabolites to the network via functional modules of the PAH-MN equipped with the engineering-driven approaches of modularization and rationalization, which may expand our understanding of the metabolic potential of M. vanbaalenii PYR-1 for bioremediation applications.

Segmented molecular design of self-healing proteinaceous materials

PubMed Central

Sariola, Veikko; Pena-Francesch, Abdon; Jung, Huihun; Çetinkaya, Murat; Pacheco, Carlos; Sitti, Metin; Demirel, Melik C.

2015-01-01

Hierarchical assembly of self-healing adhesive proteins creates strong and robust structural and interfacial materials, but understanding of the molecular design and structure–property relationships of structural proteins remains unclear. Elucidating this relationship would allow rational design of next generation genetically engineered self-healing structural proteins. Here we report a general self-healing and -assembly strategy based on a multiphase recombinant protein based material. Segmented structure of the protein shows soft glycine- and tyrosine-rich segments with self-healing capability and hard beta-sheet segments. The soft segments are strongly plasticized by water, lowering the self-healing temperature close to body temperature. The hard segments self-assemble into nanoconfined domains to reinforce the material. The healing strength scales sublinearly with contact time, which associates with diffusion and wetting of autohesion. The finding suggests that recombinant structural proteins from heterologous expression have potential as strong and repairable engineering materials. PMID:26323335

Segmented molecular design of self-healing proteinaceous materials

NASA Astrophysics Data System (ADS)

Sariola, Veikko; Pena-Francesch, Abdon; Jung, Huihun; Çetinkaya, Murat; Pacheco, Carlos; Sitti, Metin; Demirel, Melik C.

2015-09-01

Hierarchical assembly of self-healing adhesive proteins creates strong and robust structural and interfacial materials, but understanding of the molecular design and structure-property relationships of structural proteins remains unclear. Elucidating this relationship would allow rational design of next generation genetically engineered self-healing structural proteins. Here we report a general self-healing and -assembly strategy based on a multiphase recombinant protein based material. Segmented structure of the protein shows soft glycine- and tyrosine-rich segments with self-healing capability and hard beta-sheet segments. The soft segments are strongly plasticized by water, lowering the self-healing temperature close to body temperature. The hard segments self-assemble into nanoconfined domains to reinforce the material. The healing strength scales sublinearly with contact time, which associates with diffusion and wetting of autohesion. The finding suggests that recombinant structural proteins from heterologous expression have potential as strong and repairable engineering materials.

Segmented molecular design of self-healing proteinaceous materials.

PubMed

Sariola, Veikko; Pena-Francesch, Abdon; Jung, Huihun; Çetinkaya, Murat; Pacheco, Carlos; Sitti, Metin; Demirel, Melik C

2015-09-01

Hierarchical assembly of self-healing adhesive proteins creates strong and robust structural and interfacial materials, but understanding of the molecular design and structure-property relationships of structural proteins remains unclear. Elucidating this relationship would allow rational design of next generation genetically engineered self-healing structural proteins. Here we report a general self-healing and -assembly strategy based on a multiphase recombinant protein based material. Segmented structure of the protein shows soft glycine- and tyrosine-rich segments with self-healing capability and hard beta-sheet segments. The soft segments are strongly plasticized by water, lowering the self-healing temperature close to body temperature. The hard segments self-assemble into nanoconfined domains to reinforce the material. The healing strength scales sublinearly with contact time, which associates with diffusion and wetting of autohesion. The finding suggests that recombinant structural proteins from heterologous expression have potential as strong and repairable engineering materials.

Hierarchical and non-hierarchical mineralisation of collagen

PubMed Central

Liu, Yan; Kim, Young-Kyung; Dai, Lin; Li, Nan; Khan, Sara; Pashley, David H.; Tay, Franklin R.

2010-01-01

Biomineralisation of collagen involves functional motifs incorporated in extracellular matrix protein molecules to accomplish the objectives of stabilising amorphous calcium phosphate into nanoprecursors and directing the nucleation and growth of apatite within collagen fibrils. Here we report the use of small inorganic polyphosphate molecules to template hierarchical intrafibrillar apatite assembly in reconstituted collagen in the presence of polyacrylic acid to sequester calcium and phosphate into transient amorphous nanophases. The use of polyphosphate without a sequestration analogue resulted only in randomly-oriented extrafibrillar precipitations along the fibrillar surface. Conversely, the use of polyacrylic acid without a templating analogue resulted only in non-hierarchical intrafibrillar mineralisation with continuous apatite strands instead of discrete crystallites. The ability of using simple non-protein molecules to recapitulate different levels of structural hierarchy in mineralised collagen signifies the ultimate simplicity in Nature’s biomineralisation design principles and challenges the need for using more complex recombinant matrix proteins in bioengineering applications. PMID:21040969

Protein-directed assembly of arbitrary three-dimensional nanoporous silica architectures.

PubMed

Khripin, Constantine Y; Pristinski, Denis; Dunphy, Darren R; Brinker, C Jeffrey; Kaehr, Bryan

2011-02-22

Through precise control of nanoscale building blocks, such as proteins and polyamines, silica condensing microorganisms are able to create intricate mineral structures displaying hierarchical features from nano- to millimeter-length scales. The creation of artificial structures of similar characteristics is facilitated through biomimetic approaches, for instance, by first creating a bioscaffold comprised of silica condensing moieties which, in turn, govern silica deposition into three-dimensional (3D) structures. In this work, we demonstrate a protein-directed approach to template silica into true arbitrary 3D architectures by employing cross-linked protein hydrogels to controllably direct silica condensation. Protein hydrogels are fabricated using multiphoton lithography, which enables user-defined control over template features in three dimensions. Silica deposition, under acidic conditions, proceeds throughout protein hydrogel templates via flocculation of silica nanoparticles by protein molecules, as indicated by dynamic light scattering (DLS) and time-dependent measurements of elastic modulus. Following silica deposition, the protein template can be removed using mild thermal processing yielding high surface area (625 m(2)/g) porous silica replicas that do not undergo significant volume change compared to the starting template. We demonstrate the capabilities of this approach to create bioinspired silica microstructures displaying hierarchical features over broad length scales and the infiltration/functionalization capabilities of the nanoporous silica matrix by laser printing a 3D gold image within a 3D silica matrix. This work provides a foundation to potentially understand and mimic biogenic silica condensation under the constraints of user-defined biotemplates and further should enable a wide range of complex inorganic architectures to be explored using silica transformational chemistries, for instance silica to silicon, as demonstrated herein.

Hierarchical viscosity of aqueous solution of tilapia scale collagen investigated via dielectric spectroscopy between 500 MHz and 2.5 THz

PubMed Central

Kawamata, H.; Kuwaki, S.; Mishina, T.; Ikoma, T.; Tanaka, J.; Nozaki, R.

2017-01-01

Aqueous solutions of biomolecules such as proteins are very important model systems for understanding the functions of biomolecules in actual life processes because interactions between biomolecules and the surrounding water molecules are considered to be important determinants of biomolecules’ functions. Globule proteins have been extensively studied via dielectric spectroscopy; the results indicate three relaxation processes originating from fluctuations in the protein molecule, the bound water and the bulk water. However, the characteristics of aqueous solutions of collagens have rarely been investigated. In this work, based on broadband dielectric measurements between 500 MHz and 2.5 THz, we demonstrate that the high viscosity of a collagen aqueous solution is due to the network structure being constructed of rod-like collagen molecules surrounding free water molecules and that the water molecules are not responsible for the viscosity. We determine that the macroscopic viscosity is related to the mean lifetime of the collagen-collagen interactions supporting the networks and that the local viscosity of the water surrounded by the networks is governed by the viscosity of free water as in the bulk. This hierarchical structure in the dynamics of the aqueous solution of biomolecules has been revealed for the first time. PMID:28345664

From Nano to Macro: Studying the Hierarchical Structure of the Corneal Extracellular Matrix

PubMed Central

Quantock, Andrew J.; Winkler, Moritz; Parfitt, Geraint J.; Young, Robert D.; Brown, Donald J.; Boote, Craig; Jester, James V.

2014-01-01

In this review, we discuss current methods for studying ocular extracellular matrix (ECM) assembly from the ‘nano’ to the ‘macro’ levels of hierarchical organization. Since collagen is the major structural protein in the eye, providing mechanical strength and controlling ocular shape, the methods presented focus on understanding the molecular assembly of collagen at the nanometer level using x-ray scattering through to the millimeter to centimeter level using nonlinear optical (NLO) imaging of second harmonic generated (SHG) signals. Three-dimensional analysis of ECM structure is also discussed, including electron tomography, serial block face scanning electron microscopy (SBF-SEM) and digital image reconstruction. Techniques to detect non-collagenous structural components of the ECM are also presented, and these include immunoelectron microscopy and staining with cationic dyes. Together, these various approaches are providing new insights into the structural blueprint of the ocular ECM, and in particular that of the cornea, which impacts upon our current understanding of the control of corneal shape, pathogenic mechanisms underlying ectatic disorders of the cornea and the potential for corneal tissue engineering. PMID:25819457

Support vector machine prediction of enzyme function with conjoint triad feature and hierarchical context.

PubMed

Wang, Yong-Cui; Wang, Yong; Yang, Zhi-Xia; Deng, Nai-Yang

2011-06-20

Enzymes are known as the largest class of proteins and their functions are usually annotated by the Enzyme Commission (EC), which uses a hierarchy structure, i.e., four numbers separated by periods, to classify the function of enzymes. Automatically categorizing enzyme into the EC hierarchy is crucial to understand its specific molecular mechanism. In this paper, we introduce two key improvements in predicting enzyme function within the machine learning framework. One is to introduce the efficient sequence encoding methods for representing given proteins. The second one is to develop a structure-based prediction method with low computational complexity. In particular, we propose to use the conjoint triad feature (CTF) to represent the given protein sequences by considering not only the composition of amino acids but also the neighbor relationships in the sequence. Then we develop a support vector machine (SVM)-based method, named as SVMHL (SVM for hierarchy labels), to output enzyme function by fully considering the hierarchical structure of EC. The experimental results show that our SVMHL with the CTF outperforms SVMHL with the amino acid composition (AAC) feature both in predictive accuracy and Matthew's correlation coefficient (MCC). In addition, SVMHL with the CTF obtains the accuracy and MCC ranging from 81% to 98% and 0.82 to 0.98 when predicting the first three EC digits on a low-homologous enzyme dataset. We further demonstrate that our method outperforms the methods which do not take account of hierarchical relationship among enzyme categories and alternative methods which incorporate prior knowledge about inter-class relationships. Our structure-based prediction model, SVMHL with the CTF, reduces the computational complexity and outperforms the alternative approaches in enzyme function prediction. Therefore our new method will be a useful tool for enzyme function prediction community.

Collective helicity switching of a DNA-coat assembly

NASA Astrophysics Data System (ADS)

Kim, Yongju; Li, Huichang; He, Ying; Chen, Xi; Ma, Xiaoteng; Lee, Myongsoo

2017-07-01

Hierarchical assemblies of biomolecular subunits can carry out versatile tasks at the cellular level with remarkable spatial and temporal precision. As an example, the collective motion and mutual cooperation between complex protein machines mediate essential functions for life, such as replication, synthesis, degradation, repair and transport. Nucleic acid molecules are far less dynamic than proteins and need to bind to specific proteins to form hierarchical structures. The simplest example of these nucleic acid-based structures is provided by a rod-shaped tobacco mosaic virus, which consists of genetic material surrounded by coat proteins. Inspired by the complexity and hierarchical assembly of viruses, a great deal of effort has been devoted to design similarly constructed artificial viruses. However, such a wrapping approach makes nucleic acid dynamics insensitive to environmental changes. This limitation generally restricts, for example, the amplification of the conformational dynamics between the right-handed B form to the left-handed Z form of double-stranded deoxyribonucleic acid (DNA). Here we report a virus-like hierarchical assembly in which the native DNA and a synthetic coat undergo repeated collective helicity switching triggered by pH change under physiological conditions. We also show that this collective helicity inversion occurs during translocation of the DNA-coat assembly into intracellular compartments. Translating DNA conformational dynamics into a higher level of hierarchical dynamics may provide an approach to create DNA-based nanomachines.

Hierarchical Levels of Abilities That Constitute Fraction Understanding at Elementary School

ERIC Educational Resources Information Center

Nicolaou, Aristoklis A.; Pitta-Pantazi, Demetra

2016-01-01

This article examines whether the 7 abilities found in a previous study carried out by the authors to constitute fraction understanding of sixth grade elementary school students determine hierarchical levels of fraction understanding. The 7 abilities were as follows: (a) fraction recognition, (b) definitions and mathematical explanations for…

Rapid self-assembly of complex biomolecular architectures during mussel byssus biofabrication

PubMed Central

Priemel, Tobias; Degtyar, Elena; Dean, Mason N.; Harrington, Matthew J.

2017-01-01

Protein-based biogenic materials provide important inspiration for the development of high-performance polymers. The fibrous mussel byssus, for instance, exhibits exceptional wet adhesion, abrasion resistance, toughness and self-healing capacity–properties that arise from an intricate hierarchical organization formed in minutes from a fluid secretion of over 10 different protein precursors. However, a poor understanding of this dynamic biofabrication process has hindered effective translation of byssus design principles into synthetic materials. Here, we explore mussel byssus assembly in Mytilus edulis using a synergistic combination of histological staining and confocal Raman microspectroscopy, enabling in situ tracking of specific proteins during induced thread formation from soluble precursors to solid fibres. Our findings reveal critical insights into this complex biological manufacturing process, showing that protein precursors spontaneously self-assemble into complex architectures, while maturation proceeds in subsequent regulated steps. Beyond their biological importance, these findings may guide development of advanced materials with biomedical and industrial relevance. PMID:28262668

Analysis of initial changes in the proteins of soybean root tip under flooding stress using gel-free and gel-based proteomic techniques.

PubMed

Yin, Xiaojian; Sakata, Katsumi; Nanjo, Yohei; Komatsu, Setsuko

2014-06-25

Flooding has a severe negative effect on soybean cultivation in the early stages of growth. To obtain a better understanding of the response mechanisms of soybean to flooding stress, initial changes in root tip proteins under flooding were analyzed using two proteomic techniques. Two-day-old soybeans were treated with flooding for 3, 6, 12, and 24h. The weight of soybeans increased during the first 3h of flooding, but root elongation was not observed. Using gel-based and gel-free proteomic techniques, 115 proteins were identified in root tips, of which 9 proteins were commonly detected by both methods. The 71 proteins identified by the gel-free proteomics were analyzed by a hierarchical clustering method based on induction levels during the flooding, and the proteins were divided into 5 clusters. Additional interaction analysis of the proteins revealed that ten proteins belonging to cluster I formed the center of a protein interaction network. mRNA expression analysis of these ten proteins showed that citrate lyase and heat shock protein 70 were down-regulated, whereas calreticulin was up-regulated in initial phase of flooding. These results suggest that flooding stress to soybean induces calcium-related signal transduction, which might play important roles in the early responses to flooding. Flooding has a severe negative effect on soybean cultivation, particularly in the early stages of growth. To better understand the response mechanisms of soybean to the early stages of flooding stress, two proteomic techniques were used. Two-day-old soybeans were treated without or with flooding for 3, 6, 12, and 24h. The fresh weight of soybeans increased during the first 3h of flooding stress, but the growth then slowed and no root elongation was observed. Using gel-based and gel-free proteomic techniques, 115 proteins were identified in root tips, of which 9 proteins were commonly detected by both methods. The 71 proteins identified by the gel-free proteomics were analyzed by a hierarchical clustering method based on induction levels during the flooding stress, and 5 protein clusters were recognized. Protein interaction analysis revealed that ten proteins belonging to cluster I formed the center of a protein interaction network. mRNA expression analysis of these ten proteins showed that citrate lyase and heat shock protein 70 were down-regulated in response to flooding stress, whereas calreticulin was up-regulated. These results suggest that flooding stress to soybean induces calcium-related signal transduction, which might play important roles in the early responses to flooding. Copyright © 2014 Elsevier B.V. All rights reserved.

Simulating protein folding initiation sites using an alpha-carbon-only knowledge-based force field

PubMed Central

Buck, Patrick M.; Bystroff, Christopher

2015-01-01

Protein folding is a hierarchical process where structure forms locally first, then globally. Some short sequence segments initiate folding through strong structural preferences that are independent of their three-dimensional context in proteins. We have constructed a knowledge-based force field in which the energy functions are conditional on local sequence patterns, as expressed in the hidden Markov model for local structure (HMMSTR). Carbon-alpha force field (CALF) builds sequence specific statistical potentials based on database frequencies for α-carbon virtual bond opening and dihedral angles, pairwise contacts and hydrogen bond donor-acceptor pairs, and simulates folding via Brownian dynamics. We introduce hydrogen bond donor and acceptor potentials as α-carbon probability fields that are conditional on the predicted local sequence. Constant temperature simulations were carried out using 27 peptides selected as putative folding initiation sites, each 12 residues in length, representing several different local structure motifs. Each 0.6 μs trajectory was clustered based on structure. Simulation convergence or representativeness was assessed by subdividing trajectories and comparing clusters. For 21 of the 27 sequences, the largest cluster made up more than half of the total trajectory. Of these 21 sequences, 14 had cluster centers that were at most 2.6 Å root mean square deviation (RMSD) from their native structure in the corresponding full-length protein. To assess the adequacy of the energy function on nonlocal interactions, 11 full length native structures were relaxed using Brownian dynamics simulations. Equilibrated structures deviated from their native states but retained their overall topology and compactness. A simple potential that folds proteins locally and stabilizes proteins globally may enable a more realistic understanding of hierarchical folding pathways. PMID:19137613

Q&A: How do gene regulatory networks control environmental responses in plants?

PubMed

Sun, Ying; Dinneny, José R

2018-04-11

A gene regulatory network (GRN) describes the hierarchical relationship between transcription factors, associated proteins, and their target genes. Studying GRNs allows us to understand how a plant's genotype and environment are integrated to regulate downstream physiological responses. Current efforts in plants have focused on defining the GRNs that regulate functions such as development and stress response and have been performed primarily in genetically tractable model plant species such as Arabidopsis thaliana. Future studies will likely focus on how GRNs function in non-model plants and change over evolutionary time to allow for adaptation to extreme environments. This broader understanding will inform efforts to engineer GRNs to create tailored crop traits.

QAARM: quasi-anharmonic autoregressive model reveals molecular recognition pathways in ubiquitin

PubMed Central

Savol, Andrej J.; Burger, Virginia M.; Agarwal, Pratul K.; Ramanathan, Arvind; Chennubhotla, Chakra S.

2011-01-01

Motivation: Molecular dynamics (MD) simulations have dramatically improved the atomistic understanding of protein motions, energetics and function. These growing datasets have necessitated a corresponding emphasis on trajectory analysis methods for characterizing simulation data, particularly since functional protein motions and transitions are often rare and/or intricate events. Observing that such events give rise to long-tailed spatial distributions, we recently developed a higher-order statistics based dimensionality reduction method, called quasi-anharmonic analysis (QAA), for identifying biophysically-relevant reaction coordinates and substates within MD simulations. Further characterization of conformation space should consider the temporal dynamics specific to each identified substate. Results: Our model uses hierarchical clustering to learn energetically coherent substates and dynamic modes of motion from a 0.5 μs ubiqutin simulation. Autoregressive (AR) modeling within and between states enables a compact and generative description of the conformational landscape as it relates to functional transitions between binding poses. Lacking a predictive component, QAA is extended here within a general AR model appreciative of the trajectory's temporal dependencies and the specific, local dynamics accessible to a protein within identified energy wells. These metastable states and their transition rates are extracted within a QAA-derived subspace using hierarchical Markov clustering to provide parameter sets for the second-order AR model. We show the learned model can be extrapolated to synthesize trajectories of arbitrary length. Contact: ramanathana@ornl.gov; chakracs@pitt.edu PMID:21685101

ECOD: An Evolutionary Classification of Protein Domains

PubMed Central

Kinch, Lisa N.; Pei, Jimin; Shi, Shuoyong; Kim, Bong-Hyun; Grishin, Nick V.

2014-01-01

Understanding the evolution of a protein, including both close and distant relationships, often reveals insight into its structure and function. Fast and easy access to such up-to-date information facilitates research. We have developed a hierarchical evolutionary classification of all proteins with experimentally determined spatial structures, and presented it as an interactive and updatable online database. ECOD (Evolutionary Classification of protein Domains) is distinct from other structural classifications in that it groups domains primarily by evolutionary relationships (homology), rather than topology (or “fold”). This distinction highlights cases of homology between domains of differing topology to aid in understanding of protein structure evolution. ECOD uniquely emphasizes distantly related homologs that are difficult to detect, and thus catalogs the largest number of evolutionary links among structural domain classifications. Placing distant homologs together underscores the ancestral similarities of these proteins and draws attention to the most important regions of sequence and structure, as well as conserved functional sites. ECOD also recognizes closer sequence-based relationships between protein domains. Currently, approximately 100,000 protein structures are classified in ECOD into 9,000 sequence families clustered into close to 2,000 evolutionary groups. The classification is assisted by an automated pipeline that quickly and consistently classifies weekly releases of PDB structures and allows for continual updates. This synchronization with PDB uniquely distinguishes ECOD among all protein classifications. Finally, we present several case studies of homologous proteins not recorded in other classifications, illustrating the potential of how ECOD can be used to further biological and evolutionary studies. PMID:25474468

ECOD: an evolutionary classification of protein domains.

PubMed

Cheng, Hua; Schaeffer, R Dustin; Liao, Yuxing; Kinch, Lisa N; Pei, Jimin; Shi, Shuoyong; Kim, Bong-Hyun; Grishin, Nick V

2014-12-01

Understanding the evolution of a protein, including both close and distant relationships, often reveals insight into its structure and function. Fast and easy access to such up-to-date information facilitates research. We have developed a hierarchical evolutionary classification of all proteins with experimentally determined spatial structures, and presented it as an interactive and updatable online database. ECOD (Evolutionary Classification of protein Domains) is distinct from other structural classifications in that it groups domains primarily by evolutionary relationships (homology), rather than topology (or "fold"). This distinction highlights cases of homology between domains of differing topology to aid in understanding of protein structure evolution. ECOD uniquely emphasizes distantly related homologs that are difficult to detect, and thus catalogs the largest number of evolutionary links among structural domain classifications. Placing distant homologs together underscores the ancestral similarities of these proteins and draws attention to the most important regions of sequence and structure, as well as conserved functional sites. ECOD also recognizes closer sequence-based relationships between protein domains. Currently, approximately 100,000 protein structures are classified in ECOD into 9,000 sequence families clustered into close to 2,000 evolutionary groups. The classification is assisted by an automated pipeline that quickly and consistently classifies weekly releases of PDB structures and allows for continual updates. This synchronization with PDB uniquely distinguishes ECOD among all protein classifications. Finally, we present several case studies of homologous proteins not recorded in other classifications, illustrating the potential of how ECOD can be used to further biological and evolutionary studies.

On Hierarchical Threshold Access Structures

DTIC Science & Technology

2010-11-01

One of the recent generalizations of (t, n) secret sharing for hierarchical threshold access structures is given by Tassa, where he answers the...of theoretical background. We give a conceptually simpler alternative for the understanding of the realization of hierarchical threshold access

Programming molecular self-assembly of intrinsically disordered proteins containing sequences of low complexity

NASA Astrophysics Data System (ADS)

Simon, Joseph R.; Carroll, Nick J.; Rubinstein, Michael; Chilkoti, Ashutosh; López, Gabriel P.

2017-06-01

Dynamic protein-rich intracellular structures that contain phase-separated intrinsically disordered proteins (IDPs) composed of sequences of low complexity (SLC) have been shown to serve a variety of important cellular functions, which include signalling, compartmentalization and stabilization. However, our understanding of these structures and our ability to synthesize models of them have been limited. We present design rules for IDPs possessing SLCs that phase separate into diverse assemblies within droplet microenvironments. Using theoretical analyses, we interpret the phase behaviour of archetypal IDP sequences and demonstrate the rational design of a vast library of multicomponent protein-rich structures that ranges from uniform nano-, meso- and microscale puncta (distinct protein droplets) to multilayered orthogonally phase-separated granular structures. The ability to predict and program IDP-rich assemblies in this fashion offers new insights into (1) genetic-to-molecular-to-macroscale relationships that encode hierarchical IDP assemblies, (2) design rules of such assemblies in cell biology and (3) molecular-level engineering of self-assembled recombinant IDP-rich materials.

Functions of Ribosomal Proteins in Assembly of Eukaryotic Ribosomes In Vivo

PubMed Central

2016-01-01

The proteome of cells is synthesized by ribosomes, complex ribonucleoproteins that in eukaryotes contain 79–80 proteins and four ribosomal RNAs (rRNAs) more than 5,400 nucleotides long. How these molecules assemble together and how their assembly is regulated in concert with the growth and proliferation of cells remain important unanswered questions. Here, we review recently emerging principles to understand how eukaryotic ribosomal proteins drive ribosome assembly in vivo. Most ribosomal proteins assemble with rRNA cotranscriptionally; their association with nascent particles is strengthened as assembly proceeds. Each subunit is assembled hierarchically by sequential stabilization of their subdomains. The active sites of both subunits are constructed last, perhaps to prevent premature engagement of immature ribosomes with active subunits. Late-assembly intermediates undergo quality-control checks for proper function. Mutations in ribosomal proteins that affect mostly late steps lead to ribosomopathies, diseases that include a spectrum of cell type–specific disorders that often transition from hypoproliferative to hyperproliferative growth. PMID:25706898

Controlled Fabrication of Silk Protein Sericin Mediated Hierarchical Hybrid Flowers and Their Excellent Adsorption Capability of Heavy Metal Ions of Pb(II), Cd(II) and Hg(II).

PubMed

Koley, Pradyot; Sakurai, Makoto; Aono, Masakazu

2016-01-27

Fabrication of protein-inorganic hybrid materials of innumerable hierarchical patterns plays a major role in the development of multifunctional advanced materials with their improved features in synergistic way. However, effective fabrication and applications of the hybrid structures is limited due to the difficulty in control and production cost. Here, we report the controlled fabrication of complex hybrid flowers with hierarchical porosity through a green and facile coprecipitation method by using industrial waste natural silk protein sericin. The large surface areas and porosity of the microsize hybrid flowers enable water purification through adsorption of different heavy metal ions. The high adsorption capacity depends on their morphology, which is changed largely by sericin concentration in their fabrication. Superior adsorption and greater selectivity of the Pb(II) ions have been confirmed by the characteristic growth of needle-shaped nanowires on the hierarchical surface of the hybrid flowers. These hybrid flowers show excellent thermal stability even after complete evaporation of the protein molecules, significantly increasing the porosity of the flower petals. A simple, cost-effective and environmental friendly fabrication method of the porous flowers will lead to a new solution to water pollution required in the modern industrial society.

Quantitative proteomic analysis of paired colorectal cancer and non-tumorigenic tissues reveals signature proteins and perturbed pathways involved in CRC progression and metastasis.

PubMed

Sethi, Manveen K; Thaysen-Andersen, Morten; Kim, Hoguen; Park, Cheol Keun; Baker, Mark S; Packer, Nicolle H; Paik, Young-Ki; Hancock, William S; Fanayan, Susan

2015-08-03

Modern proteomics has proven instrumental in our understanding of the molecular deregulations associated with the development and progression of cancer. Herein, we profile membrane-enriched proteome of tumor and adjacent normal tissues from eight CRC patients using label-free nanoLC-MS/MS-based quantitative proteomics and advanced pathway analysis. Of the 948 identified proteins, 184 proteins were differentially expressed (P<0.05, fold change>1.5) between the tumor and non-tumor tissue (69 up-regulated and 115 down-regulated in tumor tissues). The CRC tumor and non-tumor tissues clustered tightly in separate groups using hierarchical cluster analysis of the differentially expressed proteins, indicating a strong CRC-association of this proteome subset. Specifically, cancer associated proteins such as FN1, TNC, DEFA1, ITGB2, MLEC, CDH17, EZR and pathways including actin cytoskeleton and RhoGDI signaling were deregulated. Stage-specific proteome signatures were identified including up-regulated ribosomal proteins and down-regulated annexin proteins in early stage CRC. Finally, EGFR(+) CRC tissues showed an EGFR-dependent down-regulation of cell adhesion molecules, relative to EGFR(-) tissues. Taken together, this study provides a detailed map of the altered proteome and associated protein pathways in CRC, which enhances our mechanistic understanding of CRC biology and opens avenues for a knowledge-driven search for candidate CRC protein markers. Copyright © 2015 Elsevier B.V. All rights reserved.

Construction of Matryoshka-type structures from supercharged protein nanocages.

PubMed

Beck, Tobias; Tetter, Stephan; Künzle, Matthias; Hilvert, Donald

2015-01-12

Designing nanoscaled hierarchical structures with increasing levels of complexity is challenging. Here we show that electrostatic interactions between two complementarily supercharged protein nanocages can be effectively utilized to create nested Matryoshka-type structures. Cage-within-cage complexes containing spatially ordered iron oxide nanoparticles spontaneously self-assemble upon mixing positively supercharged ferritin compartments with AaLS-13, a larger shell-forming protein with a negatively supercharged lumen. Exploiting engineered Coulombic interactions and protein dynamics in this way opens up new avenues for creating hierarchically organized supramolecular assemblies for application as delivery vehicles, reaction chambers, and artificial organelles. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Hierarchical graphs for better annotations of rule-based models of biochemical systems

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

Hu, Bin; Hlavacek, William

2009-01-01

In the graph-based formalism of the BioNetGen language (BNGL), graphs are used to represent molecules, with a colored vertex representing a component of a molecule, a vertex label representing the internal state of a component, and an edge representing a bond between components. Components of a molecule share the same color. Furthermore, graph-rewriting rules are used to represent molecular interactions, with a rule that specifies addition (removal) of an edge representing a class of association (dissociation) reactions and with a rule that specifies a change of vertex label representing a class of reactions that affect the internal state of amore » molecular component. A set of rules comprises a mathematical/computational model that can be used to determine, through various means, the system-level dynamics of molecular interactions in a biochemical system. Here, for purposes of model annotation, we propose an extension of BNGL that involves the use of hierarchical graphs to represent (1) relationships among components and subcomponents of molecules and (2) relationships among classes of reactions defined by rules. We illustrate how hierarchical graphs can be used to naturally document the structural organization of the functional components and subcomponents of two proteins: the protein tyrosine kinase Lck and the T cell receptor (TCR)/CD3 complex. Likewise, we illustrate how hierarchical graphs can be used to document the similarity of two related rules for kinase-catalyzed phosphorylation of a protein substrate. We also demonstrate how a hierarchical graph representing a protein can be encoded in an XML-based format.« less

Nanomechanical strength mechanisms of hierarchical biological materials and tissues.

PubMed

Buehler, Markus J; Ackbarow, Theodor

2008-12-01

Biological protein materials (BPMs), intriguing hierarchical structures formed by assembly of chemical building blocks, are crucial for critical functions of life. The structural details of BPMs are fascinating: They represent a combination of universally found motifs such as alpha-helices or beta-sheets with highly adapted protein structures such as cytoskeletal networks or spider silk nanocomposites. BPMs combine properties like strength and robustness, self-healing ability, adaptability, changeability, evolvability and others into multi-functional materials at a level unmatched in synthetic materials. The ability to achieve these properties depends critically on the particular traits of these materials, first and foremost their hierarchical architecture and seamless integration of material and structure, from nano to macro. Here, we provide a brief review of this field and outline new research directions, along with a review of recent research results in the development of structure-property relationships of biological protein materials exemplified in a study of vimentin intermediate filaments.

Hierarchical assembly of centriole subdistal appendages via centrosome binding proteins CCDC120 and CCDC68.

PubMed

Huang, Ning; Xia, Yuqing; Zhang, Donghui; Wang, Song; Bao, Yitian; He, Runsheng; Teng, Junlin; Chen, Jianguo

2017-04-19

In animal cells, the centrosome is the main microtubule-organizing centre where microtubules are nucleated and anchored. The centriole subdistal appendages (SDAs) are the key structures that anchor microtubules in interphase cells, but the composition and assembly mechanisms of SDAs are not well understood. Here, we reveal that centrosome-binding proteins, coiled-coil domain containing (CCDC) 120 and CCDC68 are two novel SDA components required for hierarchical SDA assembly in human cells. CCDC120 is anchored to SDAs by ODF2 and recruits CEP170 and Ninein to the centrosome through different coiled-coil domains at its N terminus. CCDC68 is a CEP170-interacting protein that competes with CCDC120 in recruiting CEP170 to SDAs. Furthermore, CCDC120 and CCDC68 are required for centrosome microtubule anchoring. Our findings elucidate the molecular basis for centriole SDA hierarchical assembly and microtubule anchoring in human interphase cells.

3D Complex: A Structural Classification of Protein Complexes

PubMed Central

Levy, Emmanuel D; Pereira-Leal, Jose B; Chothia, Cyrus; Teichmann, Sarah A

2006-01-01

Most of the proteins in a cell assemble into complexes to carry out their function. It is therefore crucial to understand the physicochemical properties as well as the evolution of interactions between proteins. The Protein Data Bank represents an important source of information for such studies, because more than half of the structures are homo- or heteromeric protein complexes. Here we propose the first hierarchical classification of whole protein complexes of known 3-D structure, based on representing their fundamental structural features as a graph. This classification provides the first overview of all the complexes in the Protein Data Bank and allows nonredundant sets to be derived at different levels of detail. This reveals that between one-half and two-thirds of known structures are multimeric, depending on the level of redundancy accepted. We also analyse the structures in terms of the topological arrangement of their subunits and find that they form a small number of arrangements compared with all theoretically possible ones. This is because most complexes contain four subunits or less, and the large majority are homomeric. In addition, there is a strong tendency for symmetry in complexes, even for heteromeric complexes. Finally, through comparison of Biological Units in the Protein Data Bank with the Protein Quaternary Structure database, we identified many possible errors in quaternary structure assignments. Our classification, available as a database and Web server at http://www.3Dcomplex.org, will be a starting point for future work aimed at understanding the structure and evolution of protein complexes. PMID:17112313

Scale of association: hierarchical linear models and the measurement of ecological systems

Treesearch

Sean M. McMahon; Jeffrey M. Diez

2007-01-01

A fundamental challenge to understanding patterns in ecological systems lies in employing methods that can analyse, test and draw inference from measured associations between variables across scales. Hierarchical linear models (HLM) use advanced estimation algorithms to measure regression relationships and variance-covariance parameters in hierarchically structured...

EKPD: a hierarchical database of eukaryotic protein kinases and protein phosphatases.

PubMed

Wang, Yongbo; Liu, Zexian; Cheng, Han; Gao, Tianshun; Pan, Zhicheng; Yang, Qing; Guo, Anyuan; Xue, Yu

2014-01-01

We present here EKPD (http://ekpd.biocuckoo.org), a hierarchical database of eukaryotic protein kinases (PKs) and protein phosphatases (PPs), the key molecules responsible for the reversible phosphorylation of proteins that are involved in almost all aspects of biological processes. As extensive experimental and computational efforts have been carried out to identify PKs and PPs, an integrative resource with detailed classification and annotation information would be of great value for both experimentalists and computational biologists. In this work, we first collected 1855 PKs and 347 PPs from the scientific literature and various public databases. Based on previously established rationales, we classified all of the known PKs and PPs into a hierarchical structure with three levels, i.e. group, family and individual PK/PP. There are 10 groups with 149 families for the PKs and 10 groups with 33 families for the PPs. We constructed 139 and 27 Hidden Markov Model profiles for PK and PP families, respectively. Then we systematically characterized ∼50,000 PKs and >10,000 PPs in eukaryotes. In addition, >500 PKs and >400 PPs were computationally identified by ortholog search. Finally, the online service of the EKPD database was implemented in PHP + MySQL + JavaScript.

A hybrid-hierarchical genome assembly strategy to sequence the invasive golden mussel, Limnoperna fortunei

PubMed Central

Uliano-Silva, Marcela; Dondero, Francesco; Dan Otto, Thomas; Costa, Igor; Lima, Nicholas Costa Barroso; Americo, Juliana Alves; Mazzoni, Camila Junqueira; Prosdocimi, Francisco; Rebelo, Mauro de Freitas

2018-01-01

Abstract Background For more than 25 years, the golden mussel, Limnoperna fortunei, has aggressively invaded South American freshwaters, having travelled more than 5000 km upstream across 5 countries. Along the way, the golden mussel has outcompeted native species and economically harmed aquaculture, hydroelectric powers, and ship transit. We have sequenced the complete genome of the golden mussel to understand the molecular basis of its invasiveness and search for ways to control it. Findings We assembled the 1.6-Gb genome into 20 548 scaffolds with an N50 length of 312 Kb using a hybrid and hierarchical assembly strategy from short and long DNA reads and transcriptomes. A total of 60 717 coding genes were inferred from a customized transcriptome-trained AUGUSTUS run. We also compared predicted protein sets with those of complete molluscan genomes, revealing an exacerbation of protein-binding domains in L. fortunei. Conclusions We built one of the best bivalve genome assemblies available using a cost-effective approach using Illumina paired-end, mate-paired, and PacBio long reads. We expect that the continuous and careful annotation of L. fortunei’s genome will contribute to the investigation of bivalve genetics, evolution, and invasiveness, as well as to the development of biotechnological tools for aquatic pest control. PMID:29267857

Beyond the Central Dogma: Model-Based Learning of How Genes Determine Phenotypes

PubMed Central

Reinagel, Adam; Bray Speth, Elena

2016-01-01

In an introductory biology course, we implemented a learner-centered, model-based pedagogy that frequently engaged students in building conceptual models to explain how genes determine phenotypes. Model-building tasks were incorporated within case studies and aimed at eliciting students’ understanding of 1) the origin of variation in a population and 2) how genes/alleles determine phenotypes. Guided by theory on hierarchical development of systems-thinking skills, we scaffolded instruction and assessment so that students would first focus on articulating isolated relationships between pairs of molecular genetics structures and then integrate these relationships into an explanatory network. We analyzed models students generated on two exams to assess whether students’ learning of molecular genetics progressed along the theoretical hierarchical sequence of systems-thinking skills acquisition. With repeated practice, peer discussion, and instructor feedback over the course of the semester, students’ models became more accurate, better contextualized, and more meaningful. At the end of the semester, however, more than 25% of students still struggled to describe phenotype as an output of protein function. We therefore recommend that 1) practices like modeling, which require connecting genes to phenotypes; and 2) well-developed case studies highlighting proteins and their functions, take center stage in molecular genetics instruction. PMID:26903496

A hybrid-hierarchical genome assembly strategy to sequence the invasive golden mussel, Limnoperna fortunei.

PubMed

Uliano-Silva, Marcela; Dondero, Francesco; Dan Otto, Thomas; Costa, Igor; Lima, Nicholas Costa Barroso; Americo, Juliana Alves; Mazzoni, Camila Junqueira; Prosdocimi, Francisco; Rebelo, Mauro de Freitas

2018-02-01

For more than 25 years, the golden mussel, Limnoperna fortunei, has aggressively invaded South American freshwaters, having travelled more than 5000 km upstream across 5 countries. Along the way, the golden mussel has outcompeted native species and economically harmed aquaculture, hydroelectric powers, and ship transit. We have sequenced the complete genome of the golden mussel to understand the molecular basis of its invasiveness and search for ways to control it. We assembled the 1.6-Gb genome into 20 548 scaffolds with an N50 length of 312 Kb using a hybrid and hierarchical assembly strategy from short and long DNA reads and transcriptomes. A total of 60 717 coding genes were inferred from a customized transcriptome-trained AUGUSTUS run. We also compared predicted protein sets with those of complete molluscan genomes, revealing an exacerbation of protein-binding domains in L. fortunei. We built one of the best bivalve genome assemblies available using a cost-effective approach using Illumina paired-end, mate-paired, and PacBio long reads. We expect that the continuous and careful annotation of L. fortunei's genome will contribute to the investigation of bivalve genetics, evolution, and invasiveness, as well as to the development of biotechnological tools for aquatic pest control.

Tutorial on Protein Ontology Resources

PubMed Central

Arighi, Cecilia; Drabkin, Harold; Christie, Karen R.; Ross, Karen; Natale, Darren

2017-01-01

The Protein Ontology (PRO) is the reference ontology for proteins in the Open Biomedical Ontologies (OBO) foundry and consists of three sub-ontologies representing protein classes of homologous genes, proteoforms (e.g., splice isoforms, sequence variants, and post-translationally modified forms), and protein complexes. PRO defines classes of proteins and protein complexes, both species-specific and species non-specific, and indicates their relationships in a hierarchical framework, supporting accurate protein annotation at the appropriate level of granularity, analyses of protein conservation across species, and semantic reasoning. In this first section of this chapter, we describe the PRO framework including categories of PRO terms and the relationship of PRO to other ontologies and protein resources. Next, we provide a tutorial about the PRO website (proconsortium.org) where users can browse and search the PRO hierarchy, view reports on individual PRO terms, and visualize relationships among PRO terms in a hierarchical table view, a multiple sequence alignment view, and a Cytoscape network view. Finally, we describe several examples illustrating the unique and rich information available in PRO. PMID:28150233

PANDORA: keyword-based analysis of protein sets by integration of annotation sources.

PubMed

Kaplan, Noam; Vaaknin, Avishay; Linial, Michal

2003-10-01

Recent advances in high-throughput methods and the application of computational tools for automatic classification of proteins have made it possible to carry out large-scale proteomic analyses. Biological analysis and interpretation of sets of proteins is a time-consuming undertaking carried out manually by experts. We have developed PANDORA (Protein ANnotation Diagram ORiented Analysis), a web-based tool that provides an automatic representation of the biological knowledge associated with any set of proteins. PANDORA uses a unique approach of keyword-based graphical analysis that focuses on detecting subsets of proteins that share unique biological properties and the intersections of such sets. PANDORA currently supports SwissProt keywords, NCBI Taxonomy, InterPro entries and the hierarchical classification terms from ENZYME, SCOP and GO databases. The integrated study of several annotation sources simultaneously allows a representation of biological relations of structure, function, cellular location, taxonomy, domains and motifs. PANDORA is also integrated into the ProtoNet system, thus allowing testing thousands of automatically generated clusters. We illustrate how PANDORA enhances the biological understanding of large, non-uniform sets of proteins originating from experimental and computational sources, without the need for prior biological knowledge on individual proteins.

Phylogenetic classification and the universal tree.

PubMed

Doolittle, W F

1999-06-25

From comparative analyses of the nucleotide sequences of genes encoding ribosomal RNAs and several proteins, molecular phylogeneticists have constructed a "universal tree of life," taking it as the basis for a "natural" hierarchical classification of all living things. Although confidence in some of the tree's early branches has recently been shaken, new approaches could still resolve many methodological uncertainties. More challenging is evidence that most archaeal and bacterial genomes (and the inferred ancestral eukaryotic nuclear genome) contain genes from multiple sources. If "chimerism" or "lateral gene transfer" cannot be dismissed as trivial in extent or limited to special categories of genes, then no hierarchical universal classification can be taken as natural. Molecular phylogeneticists will have failed to find the "true tree," not because their methods are inadequate or because they have chosen the wrong genes, but because the history of life cannot properly be represented as a tree. However, taxonomies based on molecular sequences will remain indispensable, and understanding of the evolutionary process will ultimately be enriched, not impoverished.

Prion Amplification and Hierarchical Bayesian Modeling Refine Detection of Prion Infection

NASA Astrophysics Data System (ADS)

Wyckoff, A. Christy; Galloway, Nathan; Meyerett-Reid, Crystal; Powers, Jenny; Spraker, Terry; Monello, Ryan J.; Pulford, Bruce; Wild, Margaret; Antolin, Michael; Vercauteren, Kurt; Zabel, Mark

2015-02-01

Prions are unique infectious agents that replicate without a genome and cause neurodegenerative diseases that include chronic wasting disease (CWD) of cervids. Immunohistochemistry (IHC) is currently considered the gold standard for diagnosis of a prion infection but may be insensitive to early or sub-clinical CWD that are important to understanding CWD transmission and ecology. We assessed the potential of serial protein misfolding cyclic amplification (sPMCA) to improve detection of CWD prior to the onset of clinical signs. We analyzed tissue samples from free-ranging Rocky Mountain elk (Cervus elaphus nelsoni) and used hierarchical Bayesian analysis to estimate the specificity and sensitivity of IHC and sPMCA conditional on simultaneously estimated disease states. Sensitivity estimates were higher for sPMCA (99.51%, credible interval (CI) 97.15-100%) than IHC of obex (brain stem, 76.56%, CI 57.00-91.46%) or retropharyngeal lymph node (90.06%, CI 74.13-98.70%) tissues, or both (98.99%, CI 90.01-100%). Our hierarchical Bayesian model predicts the prevalence of prion infection in this elk population to be 18.90% (CI 15.50-32.72%), compared to previous estimates of 12.90%. Our data reveal a previously unidentified sub-clinical prion-positive portion of the elk population that could represent silent carriers capable of significantly impacting CWD ecology.

Prion amplification and hierarchical Bayesian modeling refine detection of prion infection.

PubMed

Wyckoff, A Christy; Galloway, Nathan; Meyerett-Reid, Crystal; Powers, Jenny; Spraker, Terry; Monello, Ryan J; Pulford, Bruce; Wild, Margaret; Antolin, Michael; VerCauteren, Kurt; Zabel, Mark

2015-02-10

Prions are unique infectious agents that replicate without a genome and cause neurodegenerative diseases that include chronic wasting disease (CWD) of cervids. Immunohistochemistry (IHC) is currently considered the gold standard for diagnosis of a prion infection but may be insensitive to early or sub-clinical CWD that are important to understanding CWD transmission and ecology. We assessed the potential of serial protein misfolding cyclic amplification (sPMCA) to improve detection of CWD prior to the onset of clinical signs. We analyzed tissue samples from free-ranging Rocky Mountain elk (Cervus elaphus nelsoni) and used hierarchical Bayesian analysis to estimate the specificity and sensitivity of IHC and sPMCA conditional on simultaneously estimated disease states. Sensitivity estimates were higher for sPMCA (99.51%, credible interval (CI) 97.15-100%) than IHC of obex (brain stem, 76.56%, CI 57.00-91.46%) or retropharyngeal lymph node (90.06%, CI 74.13-98.70%) tissues, or both (98.99%, CI 90.01-100%). Our hierarchical Bayesian model predicts the prevalence of prion infection in this elk population to be 18.90% (CI 15.50-32.72%), compared to previous estimates of 12.90%. Our data reveal a previously unidentified sub-clinical prion-positive portion of the elk population that could represent silent carriers capable of significantly impacting CWD ecology.

Understanding phylogenies in biology: the influence of a Gestalt Perceptual Principle.

PubMed

Novick, Laura R; Catley, Kefyn M

2007-12-01

Cladograms, hierarchical diagrams depicting evolutionary histories among (groups of) species, are commonly drawn in 2 informationally equivalent formats--tree and ladder. The authors hypothesize that these formats are not computationally equivalent because the Gestalt principle of good continuation obscures the hierarchical structure of ladders. Experimental results confirmed that university students (N = 44) prefer to subdivide ladders in accordance with good continuation rather than with the underlying hierarchical structure. Two subsequent experiments (N = 164) investigated cladogram understanding by examining students' ability to translate between formats (e.g., from tree to ladder). As predicted, students had greater difficulty understanding ladders than trees. This effect was larger for students with weaker backgrounds in biology. These results have important implications for evolution education reform.

Directed assembly of bio-inspired hierarchical materials with controlled nanofibrillar architectures

NASA Astrophysics Data System (ADS)

Tseng, Peter; Napier, Bradley; Zhao, Siwei; Mitropoulos, Alexander N.; Applegate, Matthew B.; Marelli, Benedetto; Kaplan, David L.; Omenetto, Fiorenzo G.

2017-05-01

In natural systems, directed self-assembly of structural proteins produces complex, hierarchical materials that exhibit a unique combination of mechanical, chemical and transport properties. This controlled process covers dimensions ranging from the nano- to the macroscale. Such materials are desirable to synthesize integrated and adaptive materials and systems. We describe a bio-inspired process to generate hierarchically defined structures with multiscale morphology by using regenerated silk fibroin. The combination of protein self-assembly and microscale mechanical constraints is used to form oriented, porous nanofibrillar networks within predesigned macroscopic structures. This approach allows us to predefine the mechanical and physical properties of these materials, achieved by the definition of gradients in nano- to macroscale order. We fabricate centimetre-scale material geometries including anchors, cables, lattices and webs, as well as functional materials with structure-dependent strength and anisotropic thermal transport. Finally, multiple three-dimensional geometries and doped nanofibrillar constructs are presented to illustrate the facile integration of synthetic and natural additives to form functional, interactive, hierarchical networks.

2012 Gordon Research Conference on Bioinspired Materials - Formal Schedule and Speaker/Poster Program

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

Chilkoti, Ashutosk

2012-06-29

The emerging, interdisciplinary field of Bioinspired Materials focuses on developing a fundamental understanding of the synthesis, directed self-assembly and hierarchical organization of natural occurring materials, and uses this understanding to engineer new bioinspired artificial materials for diverse applications. The inaugural 2012 Gordon Conference on Bioinspired Materials seeks to capture the excitement of this burgeoning field by a cutting-edge scientific program and roster of distinguished invited speakers and discussion leaders who will address the key issues in the field. The Conference will feature a wide range of topics, such as materials and devices from DNA, reprogramming the genetic code for designmore » of new materials, peptide, protein and carbohydrate based materials, biomimetic systems, complexity in self-assembly, and biomedical applications of bioinspired materials.« less

Evaluating a Bilingual Text-Mining System with a Taxonomy of Key Words and Hierarchical Visualization for Understanding Learner-Generated Text

ERIC Educational Resources Information Center

Kong, Siu Cheung; Li, Ping; Song, Yanjie

2018-01-01

This study evaluated a bilingual text-mining system, which incorporated a bilingual taxonomy of key words and provided hierarchical visualization, for understanding learner-generated text in the learning management systems through automatic identification and counting of matching key words. A class of 27 in-service teachers studied a course…

A structure adapted multipole method for electrostatic interactions in protein dynamics

NASA Astrophysics Data System (ADS)

Niedermeier, Christoph; Tavan, Paul

1994-07-01

We present an algorithm for rapid approximate evaluation of electrostatic interactions in molecular dynamics simulations of proteins. Traditional algorithms require computational work of the order O(N2) for a system of N particles. Truncation methods which try to avoid that effort entail untolerably large errors in forces, energies and other observables. Hierarchical multipole expansion algorithms, which can account for the electrostatics to numerical accuracy, scale with O(N log N) or even with O(N) if they become augmented by a sophisticated scheme for summing up forces. To further reduce the computational effort we propose an algorithm that also uses a hierarchical multipole scheme but considers only the first two multipole moments (i.e., charges and dipoles). Our strategy is based on the consideration that numerical accuracy may not be necessary to reproduce protein dynamics with sufficient correctness. As opposed to previous methods, our scheme for hierarchical decomposition is adjusted to structural and dynamical features of the particular protein considered rather than chosen rigidly as a cubic grid. As compared to truncation methods we manage to reduce errors in the computation of electrostatic forces by a factor of 10 with only marginal additional effort.

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.

Monitoring in real-time focal adhesion protein dynamics in response to a discrete mechanical stimulus

NASA Astrophysics Data System (ADS)

von Bilderling, Catalina; Caldarola, Martín; Masip, Martín E.; Bragas, Andrea V.; Pietrasanta, Lía I.

2017-01-01

The adhesion of cells to the extracellular matrix is a hierarchical, force-dependent, multistage process that evolves at several temporal scales. An understanding of this complex process requires a precise measurement of forces and its correlation with protein responses in living cells. We present a method to quantitatively assess live cell responses to a local and specific mechanical stimulus. Our approach combines atomic force microscopy with fluorescence imaging. Using this approach, we evaluated the recruitment of adhesion proteins such as vinculin, focal adhesion kinase, paxillin, and zyxin triggered by applying forces in the nN regime to live cells. We observed in real time the development of nascent adhesion sites, evident from the accumulation of early adhesion proteins at the position where the force was applied. We show that the method can be used to quantify the recruitment characteristic times for adhesion proteins in the formation of focal complexes. We also found a spatial remodeling of the mature focal adhesion protein zyxin as a function of the applied force. Our approach allows the study of a variety of complex biological processes involved in cellular mechanotransduction.

Phosphorylation of plastoglobular proteins in Arabidopsis thaliana

PubMed Central

Lohscheider, Jens N.; Friso, Giulia; van Wijk, Klaas J.

2016-01-01

Plastoglobules (PGs) are plastid lipid–protein particles with a small specialized proteome and metabolome. Among the 30 core PG proteins are six proteins of the ancient ABC1 atypical kinase (ABC1K) family and their locations in an Arabidopsis mRNA-based co-expression network suggested central regulatory roles. To identify candidate ABC1K targets and a possible ABC1K hierarchical phosphorylation network within the chloroplast PG proteome, we searched Arabidopsis phosphoproteomics data from publicly available sources. Evaluation of underlying spectra and/or associated information was challenging for a variety of reasons, but supported pSer sites and a few pThr sites in nine PG proteins, including five FIBRILLINS. PG phosphorylation motifs are discussed in the context of possible responsible kinases. The challenges of collection and evaluation of published Arabidopsis phosphorylation data are discussed, illustrating the importance of deposition of all mass spectrometry data in well-organized repositories such as PRIDE and ProteomeXchange. This study provides a starting point for experimental testing of phosho-sites in PG proteins and also suggests that phosphoproteomics studies specifically designed toward the PG proteome and its ABC1K are needed to understand phosphorylation networks in these specialized particles. PMID:26962209

Monitoring in real-time focal adhesion protein dynamics in response to a discrete mechanical stimulus.

PubMed

von Bilderling, Catalina; Caldarola, Martín; Masip, Martín E; Bragas, Andrea V; Pietrasanta, Lía I

2017-01-01

The adhesion of cells to the extracellular matrix is a hierarchical, force-dependent, multistage process that evolves at several temporal scales. An understanding of this complex process requires a precise measurement of forces and its correlation with protein responses in living cells. We present a method to quantitatively assess live cell responses to a local and specific mechanical stimulus. Our approach combines atomic force microscopy with fluorescence imaging. Using this approach, we evaluated the recruitment of adhesion proteins such as vinculin, focal adhesion kinase, paxillin, and zyxin triggered by applying forces in the nN regime to live cells. We observed in real time the development of nascent adhesion sites, evident from the accumulation of early adhesion proteins at the position where the force was applied. We show that the method can be used to quantify the recruitment characteristic times for adhesion proteins in the formation of focal complexes. We also found a spatial remodeling of the mature focal adhesion protein zyxin as a function of the applied force. Our approach allows the study of a variety of complex biological processes involved in cellular mechanotransduction.

HSYMDOCK: a docking web server for predicting the structure of protein homo-oligomers with Cn or Dn symmetry.

PubMed

Yan, Yumeng; Tao, Huanyu; Huang, Sheng-You

2018-05-26

A major subclass of protein-protein interactions is formed by homo-oligomers with certain symmetry. Therefore, computational modeling of the symmetric protein complexes is important for understanding the molecular mechanism of related biological processes. Although several symmetric docking algorithms have been developed for Cn symmetry, few docking servers have been proposed for Dn symmetry. Here, we present HSYMDOCK, a web server of our hierarchical symmetric docking algorithm that supports both Cn and Dn symmetry. The HSYMDOCK server was extensively evaluated on three benchmarks of symmetric protein complexes, including the 20 CASP11-CAPRI30 homo-oligomer targets, the symmetric docking benchmark of 213 Cn targets and 35 Dn targets, and a nonredundant test set of 55 transmembrane proteins. It was shown that HSYMDOCK obtained a significantly better performance than other similar docking algorithms. The server supports both sequence and structure inputs for the monomer/subunit. Users have an option to provide the symmetry type of the complex, or the server can predict the symmetry type automatically. The docking process is fast and on average consumes 10∼20 min for a docking job. The HSYMDOCK web server is available at http://huanglab.phys.hust.edu.cn/hsymdock/.

Hierarchical and Helical Self-assembly of ADP-ribosyl Cyclase into Large-scale Protein Microtubes

PubMed Central

Liu, Qun; Kriksunov, Irina A.; Wang, Zhongwu; Graeff, Richard; Lee, Hon Cheung; Hao, Quan

2013-01-01

Proteins are macromolecules with characteristic structures and biological functions. It is extremely challenging to obtain protein microtube structures through self-assembly as proteins are very complex and flexible. Here we present a strategy showing how a specific protein, ADP-ribosyl cyclase, helically self-assembles from monomers into hexagonal nanochains and further to highly ordered crystalline microtubes. The structures of protein nanochains and consequently self-assembled superlattice were determined by X-ray crystallography at 4.5 Å resolution and imaged by Scanning Electron Microscopy. The protein initially forms into dimers that have a fixed size of 5.6 nm, and then, helically self-assembles into 35.6 nm long hexagonal nanochains. One such nanochain consists of six dimers (12 monomers) that stack in order by a pseudo P61 screw axis. Seven nanochains produce a series of largescale assemblies, nanorods, forming the building blocks for microrods. A proposed aging process of microrods results in the formation of hollow microstructures. Synthesis and characterization of large scale self-assembled protein microtubes may pave a new pathway, capable of not only understanding the self-assembly dynamics of biological materials, but also directing design and fabrication of multifunctional nanobuilding blocks with particular applications in biomedical engineering. PMID:18956900

When mechanism matters: Bayesian forecasting using models of ecological diffusion

USGS Publications Warehouse

Hefley, Trevor J.; Hooten, Mevin B.; Russell, Robin E.; Walsh, Daniel P.; Powell, James A.

2017-01-01

Ecological diffusion is a theory that can be used to understand and forecast spatio-temporal processes such as dispersal, invasion, and the spread of disease. Hierarchical Bayesian modelling provides a framework to make statistical inference and probabilistic forecasts, using mechanistic ecological models. To illustrate, we show how hierarchical Bayesian models of ecological diffusion can be implemented for large data sets that are distributed densely across space and time. The hierarchical Bayesian approach is used to understand and forecast the growth and geographic spread in the prevalence of chronic wasting disease in white-tailed deer (Odocoileus virginianus). We compare statistical inference and forecasts from our hierarchical Bayesian model to phenomenological regression-based methods that are commonly used to analyse spatial occurrence data. The mechanistic statistical model based on ecological diffusion led to important ecological insights, obviated a commonly ignored type of collinearity, and was the most accurate method for forecasting.

Drosophila histone locus bodies form by hierarchical recruitment of components

PubMed Central

White, Anne E.; Burch, Brandon D.; Yang, Xiao-cui; Gasdaska, Pamela Y.; Dominski, Zbigniew; Marzluff, William F.

2011-01-01

Nuclear bodies are protein- and RNA-containing structures that participate in a wide range of processes critical to genome function. Molecular self-organization is thought to drive nuclear body formation, but whether this occurs stochastically or via an ordered, hierarchical process is not fully understood. We addressed this question using RNAi and proteomic approaches in Drosophila melanogaster to identify and characterize novel components of the histone locus body (HLB), a nuclear body involved in the expression of replication-dependent histone genes. We identified the transcription elongation factor suppressor of Ty 6 (Spt6) and a homologue of mammalian nuclear protein of the ataxia telangiectasia–mutated locus that is encoded by the homeotic gene multisex combs (mxc) as novel HLB components. By combining genetic manipulation in both cell culture and embryos with cytological observations of Mxc, Spt6, and the known HLB components, FLICE-associated huge protein, Mute, U7 small nuclear ribonucleoprotein, and MPM-2 phosphoepitope, we demonstrated sequential recruitment and hierarchical dependency for localization of factors to HLBs during development, suggesting that ordered assembly can play a role in nuclear body formation. PMID:21576393

Robustness and optimal use of design principles of arthropod exoskeletons studied by ab initio-based multiscale simulations.

PubMed

Nikolov, S; Fabritius, H; Petrov, M; Friák, M; Lymperakis, L; Sachs, C; Raabe, D; Neugebauer, J

2011-02-01

Recently, we proposed a hierarchical model for the elastic properties of mineralized lobster cuticle using (i) ab initio calculations for the chitin properties and (ii) hierarchical homogenization performed in a bottom-up order through all length scales. It has been found that the cuticle possesses nearly extremal, excellent mechanical properties in terms of stiffness that strongly depend on the overall mineral content and the specific microstructure of the mineral-protein matrix. In this study, we investigated how the overall cuticle properties changed when there are significant variations in the properties of the constituents (chitin, amorphous calcium carbonate (ACC), proteins), and the volume fractions of key structural elements such as chitin-protein fibers. It was found that the cuticle performance is very robust with respect to variations in the elastic properties of chitin and fiber proteins at a lower hierarchy level. At higher structural levels, variations of design parameters such as the volume fraction of the chitin-protein fibers have a significant influence on the cuticle performance. Furthermore, we observed that among the possible variations in the cuticle ingredients and volume fractions, the experimental data reflect an optimal use of the structural variations regarding the best possible performance for a given composition due to the smart hierarchical organization of the cuticle design. Copyright © 2011. Elsevier Ltd. All rights reserved.

Population-reaction model and microbial experimental ecosystems for understanding hierarchical dynamics of ecosystems.

PubMed

Hosoda, Kazufumi; Tsuda, Soichiro; Kadowaki, Kohmei; Nakamura, Yutaka; Nakano, Tadashi; Ishii, Kojiro

2016-02-01

Understanding ecosystem dynamics is crucial as contemporary human societies face ecosystem degradation. One of the challenges that needs to be recognized is the complex hierarchical dynamics. Conventional dynamic models in ecology often represent only the population level and have yet to include the dynamics of the sub-organism level, which makes an ecosystem a complex adaptive system that shows characteristic behaviors such as resilience and regime shifts. The neglect of the sub-organism level in the conventional dynamic models would be because integrating multiple hierarchical levels makes the models unnecessarily complex unless supporting experimental data are present. Now that large amounts of molecular and ecological data are increasingly accessible in microbial experimental ecosystems, it is worthwhile to tackle the questions of their complex hierarchical dynamics. Here, we propose an approach that combines microbial experimental ecosystems and a hierarchical dynamic model named population-reaction model. We present a simple microbial experimental ecosystem as an example and show how the system can be analyzed by a population-reaction model. We also show that population-reaction models can be applied to various ecological concepts, such as predator-prey interactions, climate change, evolution, and stability of diversity. Our approach will reveal a path to the general understanding of various ecosystems and organisms. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Role of Surface Charge Density in Nanoparticle-templated Assembly of Bromovirus Protein Cages

PubMed Central

Daniel, Marie-Christine; Tsvetkova, Irina B.; Quinkert, Zachary T.; Murali, Ayaluru; De, Mrinmoy; Rotello, Vincent M.; Kao, C. Cheng; Dragnea, Bogdan

2010-01-01

Self-assembling icosahedral protein cages have potencially useful physical and chemical characteristics for a variety of nanotechnology applications, ranging from therapeutic or diagnostic vectors to building blocks for hierarchical materials. For application-specific functional control of protein cage assemblies, a deeper understanding of the interaction between the protein cage and its payload is necessary. Protein-cage encapsulated nanoparticles, with their well-defined surface chemistry, allow for systematic control over key parameters of encapsulation such as the surface charge, hydrophobicity, and size. Independent control over these variables allows experimental testing of different assembly mechanism models. Previous studies done with Brome mosaic virus capsids and negatively-charged gold nanoparticles indicated that the result of the self-assembly process depends on the diameter of the particle. However, in these experiments, the surface-ligand density was maintained at saturation levels, while the total charge and the radius of curvature remained coupled variables, making the interpretation of the observed dependence on the core size difficult. The current work furnishes evidence of a critical surface charge density for assembly through an analysis aimed at decoupling the surface charge the core size. PMID:20575505

Hierarchical virtual screening approaches in small molecule drug discovery.

PubMed

Kumar, Ashutosh; Zhang, Kam Y J

2015-01-01

Virtual screening has played a significant role in the discovery of small molecule inhibitors of therapeutic targets in last two decades. Various ligand and structure-based virtual screening approaches are employed to identify small molecule ligands for proteins of interest. These approaches are often combined in either hierarchical or parallel manner to take advantage of the strength and avoid the limitations associated with individual methods. Hierarchical combination of ligand and structure-based virtual screening approaches has received noteworthy success in numerous drug discovery campaigns. In hierarchical virtual screening, several filters using ligand and structure-based approaches are sequentially applied to reduce a large screening library to a number small enough for experimental testing. In this review, we focus on different hierarchical virtual screening strategies and their application in the discovery of small molecule modulators of important drug targets. Several virtual screening studies are discussed to demonstrate the successful application of hierarchical virtual screening in small molecule drug discovery. Copyright © 2014 Elsevier Inc. All rights reserved.

Applied Graph-Mining Algorithms to Study Biomolecular Interaction Networks

PubMed Central

2014-01-01

Protein-protein interaction (PPI) networks carry vital information on the organization of molecular interactions in cellular systems. The identification of functionally relevant modules in PPI networks is one of the most important applications of biological network analysis. Computational analysis is becoming an indispensable tool to understand large-scale biomolecular interaction networks. Several types of computational methods have been developed and employed for the analysis of PPI networks. Of these computational methods, graph comparison and module detection are the two most commonly used strategies. This review summarizes current literature on graph kernel and graph alignment methods for graph comparison strategies, as well as module detection approaches including seed-and-extend, hierarchical clustering, optimization-based, probabilistic, and frequent subgraph methods. Herein, we provide a comprehensive review of the major algorithms employed under each theme, including our recently published frequent subgraph method, for detecting functional modules commonly shared across multiple cancer PPI networks. PMID:24800226

Hierarchical cortical transcriptome disorganization in autism.

PubMed

Lombardo, Michael V; Courchesne, Eric; Lewis, Nathan E; Pramparo, Tiziano

2017-01-01

Autism spectrum disorders (ASD) are etiologically heterogeneous and complex. Functional genomics work has begun to identify a diverse array of dysregulated transcriptomic programs (e.g., synaptic, immune, cell cycle, DNA damage, WNT signaling, cortical patterning and differentiation) potentially involved in ASD brain abnormalities during childhood and adulthood. However, it remains unclear whether such diverse dysregulated pathways are independent of each other or instead reflect coordinated hierarchical systems-level pathology. Two ASD cortical transcriptome datasets were re-analyzed using consensus weighted gene co-expression network analysis (WGCNA) to identify common co-expression modules across datasets. Linear mixed-effect models and Bayesian replication statistics were used to identify replicable differentially expressed modules. Eigengene network analysis was then utilized to identify between-group differences in how co-expression modules interact and cluster into hierarchical meta-modular organization. Protein-protein interaction analyses were also used to determine whether dysregulated co-expression modules show enhanced interactions. We find replicable evidence for 10 gene co-expression modules that are differentially expressed in ASD cortex. Rather than being independent non-interacting sources of pathology, these dysregulated co-expression modules work in synergy and physically interact at the protein level. These systems-level transcriptional signals are characterized by downregulation of synaptic processes coordinated with upregulation of immune/inflammation, response to other organism, catabolism, viral processes, translation, protein targeting and localization, cell proliferation, and vasculature development. Hierarchical organization of meta-modules (clusters of highly correlated modules) is also highly affected in ASD. These findings highlight that dysregulation of the ASD cortical transcriptome is characterized by the dysregulation of multiple coordinated transcriptional programs producing synergistic systems-level effects that cannot be fully appreciated by studying the individual component biological processes in isolation.

Category Theoretic Analysis of Hierarchical Protein Materials and Social Networks

PubMed Central

Spivak, David I.; Giesa, Tristan; Wood, Elizabeth; Buehler, Markus J.

2011-01-01

Materials in biology span all the scales from Angstroms to meters and typically consist of complex hierarchical assemblies of simple building blocks. Here we describe an application of category theory to describe structural and resulting functional properties of biological protein materials by developing so-called ologs. An olog is like a “concept web” or “semantic network” except that it follows a rigorous mathematical formulation based on category theory. This key difference ensures that an olog is unambiguous, highly adaptable to evolution and change, and suitable for sharing concepts with other olog. We consider simple cases of beta-helical and amyloid-like protein filaments subjected to axial extension and develop an olog representation of their structural and resulting mechanical properties. We also construct a representation of a social network in which people send text-messages to their nearest neighbors and act as a team to perform a task. We show that the olog for the protein and the olog for the social network feature identical category-theoretic representations, and we proceed to precisely explicate the analogy or isomorphism between them. The examples presented here demonstrate that the intrinsic nature of a complex system, which in particular includes a precise relationship between structure and function at different hierarchical levels, can be effectively represented by an olog. This, in turn, allows for comparative studies between disparate materials or fields of application, and results in novel approaches to derive functionality in the design of de novo hierarchical systems. We discuss opportunities and challenges associated with the description of complex biological materials by using ologs as a powerful tool for analysis and design in the context of materiomics, and we present the potential impact of this approach for engineering, life sciences, and medicine. PMID:21931622

Analyzing Single-Molecule Protein Transportation Experiments via Hierarchical Hidden Markov Models

PubMed Central

Chen, Yang; Shen, Kuang

2017-01-01

To maintain proper cellular functions, over 50% of proteins encoded in the genome need to be transported to cellular membranes. The molecular mechanism behind such a process, often referred to as protein targeting, is not well understood. Single-molecule experiments are designed to unveil the detailed mechanisms and reveal the functions of different molecular machineries involved in the process. The experimental data consist of hundreds of stochastic time traces from the fluorescence recordings of the experimental system. We introduce a Bayesian hierarchical model on top of hidden Markov models (HMMs) to analyze these data and use the statistical results to answer the biological questions. In addition to resolving the biological puzzles and delineating the regulating roles of different molecular complexes, our statistical results enable us to propose a more detailed mechanism for the late stages of the protein targeting process. PMID:28943680

Hydroxyapatite hierarchically nanostructured porous hollow microspheres: rapid, sustainable microwave-hydrothermal synthesis by using creatine phosphate as an organic phosphorus source and application in drug delivery and protein adsorption.

PubMed

Qi, Chao; Zhu, Ying-Jie; Lu, Bing-Qiang; Zhao, Xin-Yu; Zhao, Jing; Chen, Feng; Wu, Jin

2013-04-22

Hierarchically nanostructured porous hollow microspheres of hydroxyapatite (HAP) are a promising biomaterial, owing to their excellent biocompatibility and porous hollow structure. Traditionally, synthetic hydroxyapatite is prepared by using an inorganic phosphorus source. Herein, we report a new strategy for the rapid, sustainable synthesis of HAP hierarchically nanostructured porous hollow microspheres by using creatine phosphate disodium salt as an organic phosphorus source in aqueous solution through a microwave-assisted hydrothermal method. The as-obtained products are characterized by powder X-ray diffraction (XRD), Fourier-transform IR (FTIR) spectroscopy, SEM, TEM, Brunauer-Emmett-Teller (BET) nitrogen sorptometry, dynamic light scattering (DLS), and thermogravimetric analysis (TGA). SEM and TEM micrographs show that HAP hierarchically nanostructured porous hollow microspheres consist of HAP nanosheets or nanorods as the building blocks and DLS measurements show that the diameters of HAP hollow microspheres are within the range 0.8-1.5 μm. The specific surface area and average pore size of the HAP porous hollow microspheres are 87.3 m(2) g(-1) and 20.6 nm, respectively. The important role of creatine phosphate disodium salt and the influence of the experimental conditions on the products were systematically investigated. This method is facile, rapid, surfactant-free and environmentally friendly. The as-prepared HAP porous hollow microspheres show a relatively high drug-loading capacity and protein-adsorption ability, as well as sustained drug and protein release, by using ibuprofen as a model drug and hemoglobin (Hb) as a model protein, respectively. These experiments indicate that the as-prepared HAP porous hollow microspheres are promising for applications in biomedical fields, such as drug delivery and protein adsorption. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The chromosome axis controls meiotic events through a hierarchical assembly of HORMA domain proteins

PubMed Central

Kim, Yumi; Rosenberg, Scott C.; Kugel, Christine L.; Kostow, Nora; Rog, Ofer; Davydov, Vitaliy; Su, Tiffany Y.; Dernburg, Abby F.; Corbett, Kevin D.

2014-01-01

Summary Proteins of the HORMA domain family play central but poorly understood roles in chromosome organization and dynamics during meiosis. In C. elegans, four such proteins (HIM-3, HTP-1, HTP-2, and HTP-3) have distinct but overlapping functions. Through combined biochemical, structural, and in vivo analysis, we find that these proteins form hierarchical complexes through binding of their HORMA domains to cognate peptides within their partners’ C-terminal tails, analogous to the “safety belt” binding mechanism of Mad2. These interactions are critical for recruitment of HIM-3, HTP-1, and HTP-2 to chromosome axes. HTP-3, in addition to recruiting the other HORMA domain proteins to the axis, plays an independent role in sister chromatid cohesion and double-strand break formation. Finally, we find that mammalian HORMAD1 binds a peptide motif found both at its own C-terminus and that of HORMAD2, indicating that this mode of intermolecular association is a conserved feature of meiotic chromosome structure in eukaryotes. PMID:25446517

Predicting helix–helix interactions from residue contacts in membrane proteins

PubMed Central

Lo, Allan; Chiu, Yi-Yuan; Rødland, Einar Andreas; Lyu, Ping-Chiang; Sung, Ting-Yi; Hsu, Wen-Lian

2009-01-01

Motivation: Helix–helix interactions play a critical role in the structure assembly, stability and function of membrane proteins. On the molecular level, the interactions are mediated by one or more residue contacts. Although previous studies focused on helix-packing patterns and sequence motifs, few of them developed methods specifically for contact prediction. Results: We present a new hierarchical framework for contact prediction, with an application in membrane proteins. The hierarchical scheme consists of two levels: in the first level, contact residues are predicted from the sequence and their pairing relationships are further predicted in the second level. Statistical analyses on contact propensities are combined with other sequence and structural information for training the support vector machine classifiers. Evaluated on 52 protein chains using leave-one-out cross validation (LOOCV) and an independent test set of 14 protein chains, the two-level approach consistently improves the conventional direct approach in prediction accuracy, with 80% reduction of input for prediction. Furthermore, the predicted contacts are then used to infer interactions between pairs of helices. When at least three predicted contacts are required for an inferred interaction, the accuracy, sensitivity and specificity are 56%, 40% and 89%, respectively. Our results demonstrate that a hierarchical framework can be applied to eliminate false positives (FP) while reducing computational complexity in predicting contacts. Together with the estimated contact propensities, this method can be used to gain insights into helix-packing in membrane proteins. Availability: http://bio-cluster.iis.sinica.edu.tw/TMhit/ Contact: tsung@iis.sinica.edu.tw Supplementary information:Supplementary data are available at Bioinformatics online. PMID:19244388

Bottom-up GGM algorithm for constructing multiple layered hierarchical gene regulatory networks

USDA-ARS?s Scientific Manuscript database

Multilayered hierarchical gene regulatory networks (ML-hGRNs) are very important for understanding genetics regulation of biological pathways. However, there are currently no computational algorithms available for directly building ML-hGRNs that regulate biological pathways. A bottom-up graphic Gaus...

A new multi-scale method to reveal hierarchical modular structures in biological networks.

PubMed

Jiao, Qing-Ju; Huang, Yan; Shen, Hong-Bin

2016-11-15

Biological networks are effective tools for studying molecular interactions. Modular structure, in which genes or proteins may tend to be associated with functional modules or protein complexes, is a remarkable feature of biological networks. Mining modular structure from biological networks enables us to focus on a set of potentially important nodes, which provides a reliable guide to future biological experiments. The first fundamental challenge in mining modular structure from biological networks is that the quality of the observed network data is usually low owing to noise and incompleteness in the obtained networks. The second problem that poses a challenge to existing approaches to the mining of modular structure is that the organization of both functional modules and protein complexes in networks is far more complicated than was ever thought. For instance, the sizes of different modules vary considerably from each other and they often form multi-scale hierarchical structures. To solve these problems, we propose a new multi-scale protocol for mining modular structure (named ISIMB) driven by a node similarity metric, which works in an iteratively converged space to reduce the effects of the low data quality of the observed network data. The multi-scale node similarity metric couples both the local and the global topology of the network with a resolution regulator. By varying this resolution regulator to give different weightings to the local and global terms in the metric, the ISIMB method is able to fit the shape of modules and to detect them on different scales. Experiments on protein-protein interaction and genetic interaction networks show that our method can not only mine functional modules and protein complexes successfully, but can also predict functional modules from specific to general and reveal the hierarchical organization of protein complexes.

Fabrication of hierarchical hybrid structures using bio-enabled layer-by-layer self-assembly.

PubMed

Hnilova, Marketa; Karaca, Banu Taktak; Park, James; Jia, Carol; Wilson, Brandon R; Sarikaya, Mehmet; Tamerler, Candan

2012-05-01

Development of versatile and flexible assembly systems for fabrication of functional hybrid nanomaterials with well-defined hierarchical and spatial organization is of a significant importance in practical nanobiotechnology applications. Here we demonstrate a bio-enabled self-assembly technique for fabrication of multi-layered protein and nanometallic assemblies utilizing a modular gold-binding (AuBP1) fusion tag. To accomplish the bottom-up assembly we first genetically fused the AuBP1 peptide sequence to the C'-terminus of maltose-binding protein (MBP) using two different linkers to produce MBP-AuBP1 hetero-functional constructs. Using various spectroscopic techniques, surface plasmon resonance (SPR) and localized surface plasmon resonance (LSPR), we verified the exceptional binding and self-assembly characteristics of AuBP1 peptide. The AuBP1 peptide tag can direct the organization of recombinant MBP protein on various gold surfaces through an efficient control of the organic-inorganic interface at the molecular level. Furthermore using a combination of soft-lithography, self-assembly techniques and advanced AuBP1 peptide tag technology, we produced spatially and hierarchically controlled protein multi-layered assemblies on gold nanoparticle arrays with high molecular packing density and pattering efficiency in simple, reproducible steps. This model system offers layer-by-layer assembly capability based on specific AuBP1 peptide tag and constitutes novel biological routes for biofabrication of various protein arrays, plasmon-active nanometallic assemblies and devices with controlled organization, packing density and architecture. Copyright © 2011 Wiley Periodicals, Inc.

The Protein-DNA Interface database

PubMed Central

2010-01-01

The Protein-DNA Interface database (PDIdb) is a repository containing relevant structural information of Protein-DNA complexes solved by X-ray crystallography and available at the Protein Data Bank. The database includes a simple functional classification of the protein-DNA complexes that consists of three hierarchical levels: Class, Type and Subtype. This classification has been defined and manually curated by humans based on the information gathered from several sources that include PDB, PubMed, CATH, SCOP and COPS. The current version of the database contains only structures with resolution of 2.5 Å or higher, accounting for a total of 922 entries. The major aim of this database is to contribute to the understanding of the main rules that underlie the molecular recognition process between DNA and proteins. To this end, the database is focused on each specific atomic interface rather than on the separated binding partners. Therefore, each entry in this database consists of a single and independent protein-DNA interface. We hope that PDIdb will be useful to many researchers working in fields such as the prediction of transcription factor binding sites in DNA, the study of specificity determinants that mediate enzyme recognition events, engineering and design of new DNA binding proteins with distinct binding specificity and affinity, among others. Finally, due to its friendly and easy-to-use web interface, we hope that PDIdb will also serve educational and teaching purposes. PMID:20482798

The Protein-DNA Interface database.

PubMed

Norambuena, Tomás; Melo, Francisco

2010-05-18

The Protein-DNA Interface database (PDIdb) is a repository containing relevant structural information of Protein-DNA complexes solved by X-ray crystallography and available at the Protein Data Bank. The database includes a simple functional classification of the protein-DNA complexes that consists of three hierarchical levels: Class, Type and Subtype. This classification has been defined and manually curated by humans based on the information gathered from several sources that include PDB, PubMed, CATH, SCOP and COPS. The current version of the database contains only structures with resolution of 2.5 A or higher, accounting for a total of 922 entries. The major aim of this database is to contribute to the understanding of the main rules that underlie the molecular recognition process between DNA and proteins. To this end, the database is focused on each specific atomic interface rather than on the separated binding partners. Therefore, each entry in this database consists of a single and independent protein-DNA interface.We hope that PDIdb will be useful to many researchers working in fields such as the prediction of transcription factor binding sites in DNA, the study of specificity determinants that mediate enzyme recognition events, engineering and design of new DNA binding proteins with distinct binding specificity and affinity, among others. Finally, due to its friendly and easy-to-use web interface, we hope that PDIdb will also serve educational and teaching purposes.

Biomedical and Catalytic Opportunities of Virus-Like Particles in Nanotechnology

PubMed Central

Schwarz, B.; Uchida, M.; Douglas, T.

2016-01-01

Within biology, molecules are arranged in hierarchical structures that coordinate and control the many processes that allow for complex organisms to exist. Proteins and other functional macromolecules are often studied outside their natural nanostructural context because it remains difficult to create controlled arrangements of proteins at this size scale. Viruses are elegantly simple nanosystems that exist at the interface of living organisms and nonliving biological machines. Studied and viewed primarily as pathogens to be combatted, viruses have emerged as models of structural efficiency at the nanoscale and have spurred the development of biomimetic nanoparticle systems. Virus-like particles (VLPs) are noninfectious protein cages derived from viruses or other cage-forming systems. VLPs provide incredibly regular scaffolds for building at the nanoscale. Composed of self-assembling protein subunits, VLPs provide both a model for studying materials’ assembly at the nanoscale and useful building blocks for materials design. The robustness and degree of understanding of many VLP structures allow for the ready use of these systems as versatile nanoparticle platforms for the conjugation of active molecules or as scaffolds for the structural organization of chemical processes. Lastly the prevalence of viruses in all domains of life has led to unique activities of VLPs in biological systems most notably the immune system. Here we discuss recent efforts to apply VLPs in a wide variety of applications with the aim of highlighting how the common structural elements of VLPs have led to their emergence as paradigms for the understanding and design of biological nanomaterials. PMID:28057256

Differential Proteomic Analysis Reveals the Effect of Calcium on Malus baccata Borkh. Leaves under Temperature Stress.

PubMed

Li, Lijie; Su, Hong; Ma, Huaiyu; Lyu, Deguo

2017-08-11

In the cool apple-producing areas of northern China, air temperature during early spring changes in a rapid and dramatic manner, which affects the growth and development of apple trees at the early stage of the growing season. Previous studies have shown that the treatment of calcium can increase the cold tolerance of Malus baccata Borkh., a widely-used rootstock apple tree in northern China. To better understand the physiological function of calcium in the response of M. baccata to temperature stress, we analyzed the effect of calcium treatment (2% CaCl₂) on M. baccata leaves under temperature stress. Physiological analysis showed that temperature stress aggravated membrane lipid peroxidation, reduced chlorophyll content and induced photo-inhibition in leaves, whereas these indicators of stress injuries were alleviated by the application of calcium. An isobaric tags for relative and absolute quantitation (iTRAQ)-based proteomics approach was used in this study. Among the 2114 proteins that were detected in M. baccata leaves, 41, 25, and 34 proteins were differentially regulated by the increasing, decreasing, and changing temperature treatments, respectively. Calcium treatment induced 9 and 15 proteins after increasing and decreasing temperature, respectively, in comparison with non-treated plants. These calcium-responsive proteins were mainly related to catalytic activity, binding, and structural molecule activity. Hierarchical cluster analysis indicated that the changes in abundance of the proteins under increasing temperature and changing temperature treatments were similar, and the changes in protein abundance under decreasing temperature and increasing temperature with calcium treatment were similar. The findings of this study will allow a better understanding of the mechanisms underlying the role of calcium in M. baccata leaves under temperature stress.

Differential Proteomic Analysis Reveals the Effect of Calcium on Malus baccata Borkh. Leaves under Temperature Stress

PubMed Central

Li, Lijie; Su, Hong; Ma, Huaiyu; Lyu, Deguo

2017-01-01

In the cool apple-producing areas of northern China, air temperature during early spring changes in a rapid and dramatic manner, which affects the growth and development of apple trees at the early stage of the growing season. Previous studies have shown that the treatment of calcium can increase the cold tolerance of Malus baccata Borkh., a widely-used rootstock apple tree in northern China. To better understand the physiological function of calcium in the response of M. baccata to temperature stress, we analyzed the effect of calcium treatment (2% CaCl2) on M. baccata leaves under temperature stress. Physiological analysis showed that temperature stress aggravated membrane lipid peroxidation, reduced chlorophyll content and induced photo-inhibition in leaves, whereas these indicators of stress injuries were alleviated by the application of calcium. An isobaric tags for relative and absolute quantitation (iTRAQ)-based proteomics approach was used in this study. Among the 2114 proteins that were detected in M. baccata leaves, 41, 25, and 34 proteins were differentially regulated by the increasing, decreasing, and changing temperature treatments, respectively. Calcium treatment induced 9 and 15 proteins after increasing and decreasing temperature, respectively, in comparison with non-treated plants. These calcium-responsive proteins were mainly related to catalytic activity, binding, and structural molecule activity. Hierarchical cluster analysis indicated that the changes in abundance of the proteins under increasing temperature and changing temperature treatments were similar, and the changes in protein abundance under decreasing temperature and increasing temperature with calcium treatment were similar. The findings of this study will allow a better understanding of the mechanisms underlying the role of calcium in M. baccata leaves under temperature stress. PMID:28800123

Hierarchical Spatiotemporal Dynamics of Speech Rhythm and Articulation

ERIC Educational Resources Information Center

Tilsen, Samuel Edward

2009-01-01

Hierarchy is one of the most important concepts in the scientific study of language. This dissertation aims to understand why we observe hierarchical structures in speech by investigating the cognitive processes from which they emerge. To that end, the dissertation explores how articulatory, rhythmic, and prosodic patterns of speech interact.…

Understanding Phylogenies in Biology: The Influence of a Gestalt Perceptual Principle

ERIC Educational Resources Information Center

Novick, Laura R.; Catley, Kefyn M.

2007-01-01

Cladograms, hierarchical diagrams depicting evolutionary histories among (groups of) species, are commonly drawn in 2 informationally equivalent formats--tree and ladder. The authors hypothesize that these formats are not computationally equivalent because the Gestalt principle of good continuation obscures the hierarchical structure of ladders.…

Active Interaction Mapping as a tool to elucidate hierarchical functions of biological processes.

PubMed

Farré, Jean-Claude; Kramer, Michael; Ideker, Trey; Subramani, Suresh

2017-07-03

Increasingly, various 'omics data are contributing significantly to our understanding of novel biological processes, but it has not been possible to iteratively elucidate hierarchical functions in complex phenomena. We describe a general systems biology approach called Active Interaction Mapping (AI-MAP), which elucidates the hierarchy of functions for any biological process. Existing and new 'omics data sets can be iteratively added to create and improve hierarchical models which enhance our understanding of particular biological processes. The best datatypes to further improve an AI-MAP model are predicted computationally. We applied this approach to our understanding of general and selective autophagy, which are conserved in most eukaryotes, setting the stage for the broader application to other cellular processes of interest. In the particular application to autophagy-related processes, we uncovered and validated new autophagy and autophagy-related processes, expanded known autophagy processes with new components, integrated known non-autophagic processes with autophagy and predict other unexplored connections.

Hierarchical zwitterionic modification of a SERS substrate enables real-time drug monitoring in blood plasma

NASA Astrophysics Data System (ADS)

Sun, Fang; Hung, Hsiang-Chieh; Sinclair, Andrew; Zhang, Peng; Bai, Tao; Galvan, Daniel David; Jain, Priyesh; Li, Bowen; Jiang, Shaoyi; Yu, Qiuming

2016-11-01

Surface-enhanced Raman spectroscopy (SERS) is an ultrasensitive analytical technique with molecular specificity, making it an ideal candidate for therapeutic drug monitoring (TDM). However, in critical diagnostic media including blood, nonspecific protein adsorption coupled with weak surface affinities and small Raman activities of many analytes hinder the TDM application of SERS. Here we report a hierarchical surface modification strategy, first by coating a gold surface with a self-assembled monolayer (SAM) designed to attract or probe for analytes and then by grafting a non-fouling zwitterionic polymer brush layer to effectively repel protein fouling. We demonstrate how this modification can enable TDM applications by quantitatively and dynamically measuring the concentrations of several analytes--including an anticancer drug (doxorubicin), several TDM-requiring antidepressant and anti-seizure drugs, fructose and blood pH--in undiluted plasma. This hierarchical surface chemistry is widely applicable to many analytes and provides a generalized platform for SERS-based biosensing in complex real-world media.

Clustering PPI data by combining FA and SHC method.

PubMed

Lei, Xiujuan; Ying, Chao; Wu, Fang-Xiang; Xu, Jin

2015-01-01

Clustering is one of main methods to identify functional modules from protein-protein interaction (PPI) data. Nevertheless traditional clustering methods may not be effective for clustering PPI data. In this paper, we proposed a novel method for clustering PPI data by combining firefly algorithm (FA) and synchronization-based hierarchical clustering (SHC) algorithm. Firstly, the PPI data are preprocessed via spectral clustering (SC) which transforms the high-dimensional similarity matrix into a low dimension matrix. Then the SHC algorithm is used to perform clustering. In SHC algorithm, hierarchical clustering is achieved by enlarging the neighborhood radius of synchronized objects continuously, while the hierarchical search is very difficult to find the optimal neighborhood radius of synchronization and the efficiency is not high. So we adopt the firefly algorithm to determine the optimal threshold of the neighborhood radius of synchronization automatically. The proposed algorithm is tested on the MIPS PPI dataset. The results show that our proposed algorithm is better than the traditional algorithms in precision, recall and f-measure value.

Clustering PPI data by combining FA and SHC method

PubMed Central

2015-01-01

Clustering is one of main methods to identify functional modules from protein-protein interaction (PPI) data. Nevertheless traditional clustering methods may not be effective for clustering PPI data. In this paper, we proposed a novel method for clustering PPI data by combining firefly algorithm (FA) and synchronization-based hierarchical clustering (SHC) algorithm. Firstly, the PPI data are preprocessed via spectral clustering (SC) which transforms the high-dimensional similarity matrix into a low dimension matrix. Then the SHC algorithm is used to perform clustering. In SHC algorithm, hierarchical clustering is achieved by enlarging the neighborhood radius of synchronized objects continuously, while the hierarchical search is very difficult to find the optimal neighborhood radius of synchronization and the efficiency is not high. So we adopt the firefly algorithm to determine the optimal threshold of the neighborhood radius of synchronization automatically. The proposed algorithm is tested on the MIPS PPI dataset. The results show that our proposed algorithm is better than the traditional algorithms in precision, recall and f-measure value. PMID:25707632

Hierarchical zwitterionic modification of a SERS substrate enables real-time drug monitoring in blood plasma

PubMed Central

Sun, Fang; Hung, Hsiang-Chieh; Sinclair, Andrew; Zhang, Peng; Bai, Tao; Galvan, Daniel David; Jain, Priyesh; Li, Bowen; Jiang, Shaoyi; Yu, Qiuming

2016-01-01

Surface-enhanced Raman spectroscopy (SERS) is an ultrasensitive analytical technique with molecular specificity, making it an ideal candidate for therapeutic drug monitoring (TDM). However, in critical diagnostic media including blood, nonspecific protein adsorption coupled with weak surface affinities and small Raman activities of many analytes hinder the TDM application of SERS. Here we report a hierarchical surface modification strategy, first by coating a gold surface with a self-assembled monolayer (SAM) designed to attract or probe for analytes and then by grafting a non-fouling zwitterionic polymer brush layer to effectively repel protein fouling. We demonstrate how this modification can enable TDM applications by quantitatively and dynamically measuring the concentrations of several analytes—including an anticancer drug (doxorubicin), several TDM-requiring antidepressant and anti-seizure drugs, fructose and blood pH—in undiluted plasma. This hierarchical surface chemistry is widely applicable to many analytes and provides a generalized platform for SERS-based biosensing in complex real-world media. PMID:27834380

Artificial muscle-like function from hierarchical supramolecular assembly of photoresponsive molecular motors

NASA Astrophysics Data System (ADS)

Chen, Jiawen; Leung, Franco King-Chi; Stuart, Marc C. A.; Kajitani, Takashi; Fukushima, Takanori; van der Giessen, Erik; Feringa, Ben L.

2018-02-01

A striking feature of living systems is their ability to produce motility by amplification of collective molecular motion from the nanoscale up to macroscopic dimensions. Some of nature's protein motors, such as myosin in muscle tissue, consist of a hierarchical supramolecular assembly of very large proteins, in which mechanical stress induces a coordinated movement. However, artificial molecular muscles have often relied on covalent polymer-based actuators. Here, we describe the macroscopic contractile muscle-like motion of a supramolecular system (comprising 95% water) formed by the hierarchical self-assembly of a photoresponsive amphiphilic molecular motor. The molecular motor first assembles into nanofibres, which further assemble into aligned bundles that make up centimetre-long strings. Irradiation induces rotary motion of the molecular motors, and propagation and accumulation of this motion lead to contraction of the fibres towards the light source. This system supports large-amplitude motion, fast response, precise control over shape, as well as weight-lifting experiments in water and air.

Computational studies of the 2D self-assembly of bacterial microcompartment shell proteins

NASA Astrophysics Data System (ADS)

Mahalik, Jyoti; Brown, Kirsten; Cheng, Xiaolin; Fuentes-Cabrera, Miguel

Bacterial microcomartments (BMCs) are subcellular organelles that exist within wide variety of bacteria and function like nano-reactors. Among the different types of BMCs known, the carboxysome has been studied the most. The carboxysomes plays an important role in the transport of metabolites across its outer proteinaceous shell. Plenty of studies have investigated the structure of this shell, yet little is known about its self-assembly . Understanding the self-assembly process of BMCs' shell might allow disrupting their functioning and designing new synthetic nano-reactors. We have investigated the self-assembly process of a major protein component of the carboxysome's shell using a Monte Carlo technique that employed a coarse-grained protein model that was calibrated with the all-atomistic potential of mean force. The simulations reveal that this protein self-assembles into clusters that resemble what were seen experimentally in 2D layers. Further analysis of the simulation results suggests that the 2D self-assembly of carboxysome's facets is driven by nucleation-growth process, which in turn could play an important role in the hierarchical self-assembly of BMCs' shell in general. 1. Science Undergraduate Laboratory Internships, ORNL 2. Oak Ridge Leadership Computing Facility, ORNL.

A hypothetical hierarchical mechanism of the self-assembly of the Escherichia coli RNA polymerase σ(70) subunit.

PubMed

Koroleva, O N; Dubrovin, E V; Tolstova, A P; Kuzmina, N V; Laptinskaya, T V; Yaminsky, I V; Drutsa, V L

2016-02-21

Diverse morphology of aggregates of amyloidogenic proteins has been attracting much attention in the last few years, and there is still no complete understanding of the relationships between various types of aggregates. In this work, we propose the model, which universally explains the formation of morphologically different (wormlike and rodlike) aggregates on the example of a σ(70) subunit of RNA polymerase, which has been recently shown to form amyloid fibrils. Aggregates were studied using AFM in solution and depolarized dynamic light scattering. The obtained results demonstrate comparably low Young's moduli of the wormlike structures (7.8-12.3 MPa) indicating less structured aggregation of monomeric proteins than that typical for β-sheet formation. To shed light on the molecular interaction of the protein during the aggregation, early stages of fibrillization of the σ(70) subunit were modeled using all-atom molecular dynamics. Simulations have shown that the σ(70) subunit is able to form quasi-symmetric extended dimers, which may further interact with each other and grow linearly. The proposed general model explains different pathways of σ(70) subunit aggregation and may be valid for other amyloid proteins.

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

Hierarchical Structure Controls Nanomechanical Properties of Vimentin Intermediate Filaments

PubMed Central

Qin, Zhao; Kreplak, Laurent; Buehler, Markus J.

2009-01-01

Intermediate filaments (IFs), in addition to microtubules and microfilaments, are one of the three major components of the cytoskeleton in eukaryotic cells, playing a vital role in mechanotransduction and in providing mechanical stability to cells. Despite the importance of IF mechanics for cell biology and cell mechanics, the structural basis for their mechanical properties remains unknown. Specifically, our understanding of fundamental filament properties, such as the basis for their great extensibility, stiffening properties, and their exceptional mechanical resilience remains limited. This has prevented us from answering fundamental structure-function relationship questions related to the biomechanical role of intermediate filaments, which is crucial to link structure and function in the protein material's biological context. Here we utilize an atomistic-level model of the human vimentin dimer and tetramer to study their response to mechanical tensile stress, and describe a detailed analysis of the mechanical properties and associated deformation mechanisms. We observe a transition from alpha-helices to beta-sheets with subsequent interdimer sliding under mechanical deformation, which has been inferred previously from experimental results. By upscaling our results we report, for the first time, a quantitative comparison to experimental results of IF nanomechanics, showing good agreement. Through the identification of links between structures and deformation mechanisms at distinct hierarchical levels, we show that the multi-scale structure of IFs is crucial for their characteristic mechanical properties, in particular their ability to undergo severe deformation of ≈300% strain without breaking, facilitated by a cascaded activation of a distinct deformation mechanisms operating at different levels. This process enables IFs to combine disparate properties such as mechanosensitivity, strength and deformability. Our results enable a new paradigm in studying biological and mechanical properties of IFs from an atomistic perspective, and lay the foundation to understanding how properties of individual protein molecules can have profound effects at larger length-scales. PMID:19806221

Hierarchical structure controls nanomechanical properties of vimentin intermediate filaments.

PubMed

Qin, Zhao; Kreplak, Laurent; Buehler, Markus J

2009-10-06

Intermediate filaments (IFs), in addition to microtubules and microfilaments, are one of the three major components of the cytoskeleton in eukaryotic cells, playing a vital role in mechanotransduction and in providing mechanical stability to cells. Despite the importance of IF mechanics for cell biology and cell mechanics, the structural basis for their mechanical properties remains unknown. Specifically, our understanding of fundamental filament properties, such as the basis for their great extensibility, stiffening properties, and their exceptional mechanical resilience remains limited. This has prevented us from answering fundamental structure-function relationship questions related to the biomechanical role of intermediate filaments, which is crucial to link structure and function in the protein material's biological context. Here we utilize an atomistic-level model of the human vimentin dimer and tetramer to study their response to mechanical tensile stress, and describe a detailed analysis of the mechanical properties and associated deformation mechanisms. We observe a transition from alpha-helices to beta-sheets with subsequent interdimer sliding under mechanical deformation, which has been inferred previously from experimental results. By upscaling our results we report, for the first time, a quantitative comparison to experimental results of IF nanomechanics, showing good agreement. Through the identification of links between structures and deformation mechanisms at distinct hierarchical levels, we show that the multi-scale structure of IFs is crucial for their characteristic mechanical properties, in particular their ability to undergo severe deformation of approximately 300% strain without breaking, facilitated by a cascaded activation of a distinct deformation mechanisms operating at different levels. This process enables IFs to combine disparate properties such as mechanosensitivity, strength and deformability. Our results enable a new paradigm in studying biological and mechanical properties of IFs from an atomistic perspective, and lay the foundation to understanding how properties of individual protein molecules can have profound effects at larger length-scales.

Selective Removal of Hemoglobin from Blood Using Hierarchical Copper Shells Anchored to Magnetic Nanoparticles

PubMed Central

Wang, Yaokun; Yan, Mingyang

2017-01-01

Hierarchical copper shells anchored on magnetic nanoparticles were designed and fabricated to selectively deplete hemoglobin from human blood by immobilized metal affinity chromatography. Briefly, CoFe2O4 nanoparticles coated with polyacrylic acid were first synthesized by a one-pot solvothermal method. Hierarchical copper shells were then deposited by immobilizing Cu2+ on nanoparticles and subsequently by reducing between the solid CoFe2O4@COOH and copper solution with NaBH4. The resulting nanoparticles were characterized by scanning electron microscopy, transmission electron microscopy, Fourier transform infrared spectrometry, X-ray photoelectron spectroscopy, and vibrating sample magnetometry. The particles were also tested against purified bovine hemoglobin over a range of pH, contact time, and initial protein concentration. Hemoglobin adsorption followed pseudo-second-order kinetics and reached equilibrium in 90 min. Isothermal data also fit the Langmuir model well, with calculated maximum adsorption capacity 666 mg g−1. Due to the high density of Cu2+ on the shell, the nanoparticles efficiently and selectively deplete hemoglobin from human blood. Taken together, the results demonstrate that the particles with hierarchical copper shells effectively remove abundant, histidine-rich proteins, such as hemoglobin from human blood, and thereby minimize interference in diagnostic and other assays. PMID:28316987

Proteomic Response and Quality Maintenance in Postharvest Fruit of Strawberry (Fragaria × ananassa) to Exogenous Cytokinin.

PubMed

Li, Li; Li, Dongdong; Luo, Zisheng; Huang, Xinhong; Li, Xihong

2016-06-01

The limitations in current understanding of the molecular mechanisms underlying fruit response to the application of plant growth regulators have increasingly become major challenges in improvement of crop quality. This study aimed to evaluate the response of strawberry to the preharvest application of exogenous cytokinin known as forchlorfenuron (CPPU). Postharvest internal and physiological quality attributes were characterized following storage under different conditions. Hierarchical clustering analysis via a label-free proteomic quantitative approach identified a total of 124 proteins in strawberries across all treatments. The expression profiles of both proteins and genes spanned the ranged role of cytokinin involved in primary and secondary metabolism, stress response, and so on. Eighty-eight proteins and fifty-six proteins were significantly regulated immediately at harvest and after storage, respectively. In general, the glycolysis in strawberry was only regulated by CPPU before storage; in addition to the accelerated photosynthesis and acid metabolism, CPPU application maintained higher capacity of resistance in strawberry to stress stimuli after storage, in comparison to control. Nevertheless, the volatile biosynthesis in strawberry has been suppressed by exogenous CPPU. Novel cytokinin response proteins and processes were identified in addition to the main transcriptomic expression to gain insights into the phytohormone control of fruit postharvest quality.

Hierarchical flexural strength of enamel: transition from brittle to damage-tolerant behaviour

PubMed Central

Bechtle, Sabine; Özcoban, Hüseyin; Lilleodden, Erica T.; Huber, Norbert; Schreyer, Andreas; Swain, Michael V.; Schneider, Gerold A.

2012-01-01

Hard, biological materials are generally hierarchically structured from the nano- to the macro-scale in a somewhat self-similar manner consisting of mineral units surrounded by a soft protein shell. Considerable efforts are underway to mimic such materials because of their structurally optimized mechanical functionality of being hard and stiff as well as damage-tolerant. However, it is unclear how different hierarchical levels interact to achieve this performance. In this study, we consider dental enamel as a representative, biological hierarchical structure and determine its flexural strength and elastic modulus at three levels of hierarchy using focused ion beam (FIB) prepared cantilevers of micrometre size. The results are compared and analysed using a theoretical model proposed by Jäger and Fratzl and developed by Gao and co-workers. Both properties decrease with increasing hierarchical dimension along with a switch in mechanical behaviour from linear-elastic to elastic-inelastic. We found Gao's model matched the results very well. PMID:22031729

Universal partitioning of the hierarchical fold network of 50-residue segments in proteins

PubMed Central

Ito, Jun-ichi; Sonobe, Yuki; Ikeda, Kazuyoshi; Tomii, Kentaro; Higo, Junichi

2009-01-01

Background Several studies have demonstrated that protein fold space is structured hierarchically and that power-law statistics are satisfied in relation between the numbers of protein families and protein folds (or superfamilies). We examined the internal structure and statistics in the fold space of 50 amino-acid residue segments taken from various protein folds. We used inter-residue contact patterns to measure the tertiary structural similarity among segments. Using this similarity measure, the segments were classified into a number (Kc) of clusters. We examined various Kc values for the clustering. The special resolution to differentiate the segment tertiary structures increases with increasing Kc. Furthermore, we constructed networks by linking structurally similar clusters. Results The network was partitioned persistently into four regions for Kc ≥ 1000. This main partitioning is consistent with results of earlier studies, where similar partitioning was reported in classifying protein domain structures. Furthermore, the network was partitioned naturally into several dozens of sub-networks (i.e., communities). Therefore, intra-sub-network clusters were mutually connected with numerous links, although inter-sub-network ones were rarely done with few links. For Kc ≥ 1000, the major sub-networks were about 40; the contents of the major sub-networks were conserved. This sub-partitioning is a novel finding, suggesting that the network is structured hierarchically: Segments construct a cluster, clusters form a sub-network, and sub-networks constitute a region. Additionally, the network was characterized by non-power-law statistics, which is also a novel finding. Conclusion Main findings are: (1) The universe of 50 residue segments found here was characterized by non-power-law statistics. Therefore, the universe differs from those ever reported for the protein domains. (2) The 50-residue segments were partitioned persistently and universally into some dozens (ca. 40) of major sub-networks, irrespective of the number of clusters. (3) These major sub-networks encompassed 90% of all segments. Consequently, the protein tertiary structure is constructed using the dozens of elements (sub-networks). PMID:19454039

Multiscale imaging of bone microdamage

PubMed Central

Poundarik, Atharva A.; Vashishth, Deepak

2015-01-01

Bone is a structural and hierarchical composite that exhibits remarkable ability to sustain complex mechanical loading and resist fracture. Bone quality encompasses various attributes of bone matrix from the quality of its material components (type-I collagen, mineral and non-collagenous matrix proteins) and cancellous microarchitecture, to the nature and extent of bone microdamage. Microdamage, produced during loading, manifests in multiple forms across the scales of hierarchy in bone and functions to dissipate energy and avert fracture. Microdamage formation is a key determinant of bone quality, and through a range of biological and physical mechanisms, accumulates with age and disease. Accumulated microdamage in bone decreases bone strength and increases bone’s propensity to fracture. Thus, a thorough assessment of microdamage, across the hierarchical levels of bone, is crucial to better understand bone quality and bone fracture. This review article details multiple imaging modalities that have been used to study and characterize microdamage; from bulk staining techniques originally developed by Harold Frost to assess linear microcracks, to atomic force microscopy, a modality that revealed mechanistic insights into the formation diffuse damage at the ultrastructural level in bone. New automated techniques using imaging modalities such as microcomputed tomography are also presented for a comprehensive overview. PMID:25664772

Exploring the Free Energy Landscape: From Dynamics to Networks and Back

PubMed Central

Prada-Gracia, Diego; Gómez-Gardeñes, Jesús; Echenique, Pablo; Falo, Fernando

2009-01-01

Knowledge of the Free Energy Landscape topology is the essential key to understanding many biochemical processes. The determination of the conformers of a protein and their basins of attraction takes a central role for studying molecular isomerization reactions. In this work, we present a novel framework to unveil the features of a Free Energy Landscape answering questions such as how many meta-stable conformers there are, what the hierarchical relationship among them is, or what the structure and kinetics of the transition paths are. Exploring the landscape by molecular dynamics simulations, the microscopic data of the trajectory are encoded into a Conformational Markov Network. The structure of this graph reveals the regions of the conformational space corresponding to the basins of attraction. In addition, handling the Conformational Markov Network, relevant kinetic magnitudes as dwell times and rate constants, or hierarchical relationships among basins, completes the global picture of the landscape. We show the power of the analysis studying a toy model of a funnel-like potential and computing efficiently the conformers of a short peptide, dialanine, paving the way to a systematic study of the Free Energy Landscape in large peptides. PMID:19557191

The protein folding network

NASA Astrophysics Data System (ADS)

Rao, Francesco; Caflisch, Amedeo

2004-03-01

Networks are everywhere. The conformation space of a 20-residue antiparallel beta-sheet peptide [1], sampled by molecular dynamics simulations, is mapped to a network. Conformations are nodes of the network, and the transitions between them are links. As previously found for the World-Wide Web as well as for social and biological networks , the conformation space contains highly connected hubs like the native state which is the most populated free energy basin. Furthermore, the network shows a hierarchical modularity [2] which is consistent with the funnel mechanism of folding [3] and is not observed for a random heteropolymer lacking a native state. Here we show that the conformation space network describes the free energy landscape without requiring projections into arbitrarily chosen reaction coordinates. The network analysis provides a basis for understanding the heterogeneity of the folding transition state and the existence of multiple pathways. [1] P. Ferrara and A. Caflisch, Folding simulations of a three-stranded antiparallel beta-sheet peptide, PNAS 97, 10780-10785 (2000). [2] Ravasz, E. and Barabási, A. L. Hierarchical organization in complex networks. Phys. Rev. E 67, 026112 (2003). [3] Dill, K. and Chan, H From Levinthal to pathways to funnels. Nature Struct. Biol. 4, 10-19 (1997)

Exploring the free energy landscape: from dynamics to networks and back.

PubMed

Prada-Gracia, Diego; Gómez-Gardeñes, Jesús; Echenique, Pablo; Falo, Fernando

2009-06-01

Knowledge of the Free Energy Landscape topology is the essential key to understanding many biochemical processes. The determination of the conformers of a protein and their basins of attraction takes a central role for studying molecular isomerization reactions. In this work, we present a novel framework to unveil the features of a Free Energy Landscape answering questions such as how many meta-stable conformers there are, what the hierarchical relationship among them is, or what the structure and kinetics of the transition paths are. Exploring the landscape by molecular dynamics simulations, the microscopic data of the trajectory are encoded into a Conformational Markov Network. The structure of this graph reveals the regions of the conformational space corresponding to the basins of attraction. In addition, handling the Conformational Markov Network, relevant kinetic magnitudes as dwell times and rate constants, or hierarchical relationships among basins, completes the global picture of the landscape. We show the power of the analysis studying a toy model of a funnel-like potential and computing efficiently the conformers of a short peptide, dialanine, paving the way to a systematic study of the Free Energy Landscape in large peptides.

Hierarchical structure of the energy landscape of proteins revisited by time series analysis. I. Mimicking protein dynamics in different time scales

NASA Astrophysics Data System (ADS)

Alakent, Burak; Camurdan, Mehmet C.; Doruker, Pemra

2005-10-01

Time series models, which are constructed from the projections of the molecular-dynamics (MD) runs on principal components (modes), are used to mimic the dynamics of two proteins: tendamistat and immunity protein of colicin E7 (ImmE7). Four independent MD runs of tendamistat and three independent runs of ImmE7 protein in vacuum are used to investigate the energy landscapes of these proteins. It is found that mean-square displacements of residues along the modes in different time scales can be mimicked by time series models, which are utilized in dividing protein dynamics into different regimes with respect to the dominating motion type. The first two regimes constitute the dominance of intraminimum motions during the first 5ps and the random walk motion in a hierarchically higher-level energy minimum, which comprise the initial time period of the trajectories up to 20-40ps for tendamistat and 80-120ps for ImmE7. These are also the time ranges within which the linear nonstationary time series are completely satisfactory in explaining protein dynamics. Encountering energy barriers enclosing higher-level energy minima constrains the random walk motion of the proteins, and pseudorelaxation processes at different levels of minima are detected in tendamistat, depending on the sampling window size. Correlation (relaxation) times of 30-40ps and 150-200ps are detected for two energy envelopes of successive levels for tendamistat, which gives an overall idea about the hierarchical structure of the energy landscape. However, it should be stressed that correlation times of the modes are highly variable with respect to conformational subspaces and sampling window sizes, indicating the absence of an actual relaxation. The random-walk step sizes and the time length of the second regime are used to illuminate an important difference between the dynamics of the two proteins, which cannot be clarified by the investigation of relaxation times alone: ImmE7 has lower-energy barriers enclosing the higher-level energy minimum, preventing the protein to relax and letting it move in a random-walk fashion for a longer period of time.

An Analysis of Prospective Teachers' Knowledge for Constructing Concept Maps

ERIC Educational Resources Information Center

Subramaniam, Karthigeyan; Esprívalo Harrell, Pamela

2015-01-01

Background: Literature contends that a teacher's knowledge of concept map-based tasks influence how their students perceive the task and execute the creation of acceptable concept maps. Teachers who are skilled concept mappers are able to (1) understand and apply the operational terms to construct a hierarchical/non-hierarchical concept map; (2)…

Yeast Mitoribosome Large Subunit Assembly Proceeds by Hierarchical Incorporation of Protein Clusters and Modules on the Inner Membrane.

PubMed

Zeng, Rui; Smith, Erin; Barrientos, Antoni

2018-03-06

Mitoribosomes are specialized for the synthesis of hydrophobic membrane proteins encoded by mtDNA, all essential for oxidative phosphorylation. Despite their linkage to human mitochondrial diseases and the recent cryoelectron microscopy reconstruction of yeast and mammalian mitoribosomes, how they are assembled remains obscure. Here, we dissected the yeast mitoribosome large subunit (mtLSU) assembly process by systematic genomic deletion of 44 mtLSU proteins (MRPs). Analysis of the strain collection unveiled 37 proteins essential for functional mtLSU assembly, three of which are critical for mtLSU 21S rRNA stability. Hierarchical cluster analysis of mtLSU subassemblies accumulated in mutant strains revealed co-operative assembly of protein sets forming structural clusters and preassembled modules. It also indicated crucial roles for mitochondrion-specific membrane-binding MRPs in anchoring newly transcribed 21S rRNA to the inner membrane, where assembly proceeds. Our results define the yeast mtLSU assembly landscape in vivo and provide a foundation for studies of mitoribosome assembly across evolution. Copyright © 2018 Elsevier Inc. All rights reserved.

Autogrid-based clustering of kinases: selection of representative conformations for docking purposes.

PubMed

Marzaro, Giovanni; Ferrarese, Alessandro; Chilin, Adriana

2014-08-01

The selection of the most appropriate protein conformation is a crucial aspect in molecular docking experiments. In order to reduce the errors arising from the use of a single protein conformation, several authors suggest the use of several tridimensional structures for the target. However, the selection of the most appropriate protein conformations still remains a challenging goal. The protein 3D-structures selection is mainly performed based on pairwise root-mean-square-deviation (RMSD) values computation, followed by hierarchical clustering. Herein we report an alternative strategy, based on the computation of only two atom affinity map for each protein conformation, followed by multivariate analysis and hierarchical clustering. This methodology was applied on seven different kinases of pharmaceutical interest. The comparison with the classical RMSD-based strategy was based on cross-docking of co-crystallized ligands. In the case of epidermal growth factor receptor kinase, also the docking performance on 220 known ligands were evaluated, followed by 3D-QSAR studies. In all the cases, the herein proposed methodology outperformed the RMSD-based one.

Origin of the Reflectin Gene and Hierarchical Assembly of Its Protein.

PubMed

Guan, Zhe; Cai, Tiantian; Liu, Zhongmin; Dou, Yunfeng; Hu, Xuesong; Zhang, Peng; Sun, Xin; Li, Hongwei; Kuang, Yao; Zhai, Qiran; Ruan, Hao; Li, Xuanxuan; Li, Zeyang; Zhu, Qihui; Mai, Jingeng; Wang, Qining; Lai, Luhua; Ji, Jianguo; Liu, Haiguang; Xia, Bin; Jiang, Taijiao; Luo, Shu-Jin; Wang, Hong-Wei; Xie, Can

2017-09-25

Cephalopods, the group of animals including octopus, squid, and cuttlefish, have remarkable ability to instantly modulate body coloration and patterns so as to blend into surrounding environments [1, 2] or send warning signals to other animals [3]. Reflectin is expressed exclusively in cephalopods, filling the lamellae of intracellular Bragg reflectors that exhibit dynamic iridescence and structural color change [4]. Here, we trace the possible origin of the reflectin gene back to a transposon from the symbiotic bioluminescent bacterium Vibrio fischeri and report the hierarchical structural architecture of reflectin protein. Intrinsic self-assembly, and higher-order assembly tightly modulated by aromatic compounds, provide insights into the formation of multilayer reflectors in iridophores and spherical microparticles in leucophores and may form the basis of structural color change in cephalopods. Self-assembly and higher-order assembly in reflectin originated from a core repeating octapeptide (here named protopeptide), which may be from the same symbiotic bacteria. The origin of the reflectin gene and assembly features of reflectin protein are of considerable biological interest. The hierarchical structural architecture of reflectin and its domain and protopeptide not only provide insights for bioinspired photonic materials but also serve as unique "assembly tags" and feasible molecular platforms in biotechnology. Copyright © 2017 Elsevier Ltd. All rights reserved.

Correlation between hierarchical structure of crystal networks and macroscopic performance of mesoscopic soft materials and engineering principles.

PubMed

Lin, Naibo; Liu, Xiang Yang

2015-11-07

This review examines how the concepts and ideas of crystallization can be extended further and applied to the field of mesoscopic soft materials. It concerns the structural characteristics vs. the macroscopic performance, and the formation mechanism of crystal networks. Although this subject can be discussed in a broad sense across the area of mesoscopic soft materials, our main focus is on supramolecular materials, spider and silkworm silks, and biominerals. First, the occurrence of a hierarchical structure, i.e. crystal network and domain network structures, will facilitate the formation kinetics of mesoscopic phases and boost up the macroscopic performance of materials in some cases (i.e. spider silk fibres). Second, the structure and performance of materials can be correlated in some way by the four factors: topology, correlation length, symmetry/ordering, and strength of association of crystal networks. Moreover, four different kinetic paths of crystal network formation are identified, namely, one-step process of assembly, two-step process of assembly, mixed mode of assembly and foreign molecule mediated assembly. Based on the basic mechanisms of crystal nucleation and growth, the formation of crystal networks, such as crystallographic mismatch (or noncrystallographic) branching (tip branching and fibre side branching) and fibre/polymeric side merging, are reviewed. This facilitates the rational design and construction of crystal networks in supramolecular materials. In this context, the (re-)construction of a hierarchical crystal network structure can be implemented by thermal, precipitate, chemical, and sonication stimuli. As another important class of soft materials, the unusual mechanical performance of spider and silkworm silk fibres are reviewed in comparison with the regenerated silk protein derivatives. It follows that the considerably larger breaking stress and unusual breaking strain of spider silk fibres vs. silkworm silk fibres can be interpreted according to the synergistically correlated hierarchical structures of the domain and crystal networks, which can be quantified by the hierarchical structural correlation and the four structural parameters. Based on the concept of crystal networks, the new understanding acquired will transfer the research and engineering of mesoscopic materials, particularly, soft functional materials, to a new phase.

Biomimetic structural engineering of P22 virus-like particles for catalysis and immune modulation

NASA Astrophysics Data System (ADS)

Schwarz, Benjamin

Within biology molecules are arranged in hierarchical structures that coordinate and control the many processes that allow for complex organisms to exist. Proteins and other functional macromolecules are often studied outside their natural nanostructural context because it remains difficult to create controlled arrangements of proteins at this size scale. Viruses are elegantly simple nano-systems that exist at the interface of living organisms and non-living biological machines. Studied and viewed primarily as pathogens to be combatted, viruses have emerged as models of structural efficiency at the nanoscale and have spurred the development of biomimetic nanoparticle systems. Virus-like particles (VLPs) are noninfectious protein cages derived from viruses or other cage-forming systems. VLPs provide incredibly regular scaffolds for building at the nanoscale. In this work I have utilized the VLP derived from the bacteriophage P22 as a platform for the organization of enzymes, antigens, and immune-stimulating proteins inside and outside the capsid through purely genetic means. In the case of enzymes, encapsulation of a two-enzyme pathway has led to the development of metabolic nanoparticle catalysts and an expanded understanding of the control that structure exerts on metabolic flux. These same structural elements applied to the delivery of protein subunit antigens directed at cytotoxic T cell immunity result in drastically enhanced antigen processing and lasting immunological memory. Lastly, presentation of immune-stimulating proteins from the Tumor Necrosis Factor Super Family on the surface of the P22 VLP enhances the cell signaling efficiency of these compounds 50-fold and provides strategies for the application of these proteins as immune modulatory oncology therapeutics. In all of these cases, the reintroduction of nanostructure to these protein systems, reminiscent of their natural environment, has led to both new technologies and a better understanding of the role of structure in biological processes.

Hierarchical Coloured Petrinet Based Healthcare Infrastructure Interdependency Model

NASA Astrophysics Data System (ADS)

Nivedita, N.; Durbha, S.

2014-11-01

To ensure a resilient Healthcare Critical Infrastructure, understanding the vulnerabilities and analysing the interdependency on other critical infrastructures is important. To model this critical infrastructure and its dependencies, Hierarchal Coloured petri net modelling approach for simulating the vulnerability of Healthcare Critical infrastructure in a disaster situation is studied.. The model enables to analyse and understand various state changes, which occur when there is a disruption or damage to any of the Critical Infrastructure, and its cascading nature. It also enables to explore optimal paths for evacuation during the disaster. The simulation environment can be used to understand and highlight various vulnerabilities of Healthcare Critical Infrastructure during a flood disaster scenario; minimize consequences; and enable timely, efficient response.

On the design of composite protein-quantum dot biomaterials via self-assembly.

PubMed

Majithia, Ravish; Patterson, Jan; Bondos, Sarah E; Meissner, Kenith E

2011-10-10

Incorporation of nanoparticles during the hierarchical self-assembly of protein-based materials can impart function to the resulting composite materials. Herein we demonstrate that the structure and nanoparticle distribution of composite fibers are sensitive to the method of nanoparticle addition and the physicochemical properties of both the nanoparticle and the protein. Our model system consists of a recombinant enhanced green fluorescent protein-Ultrabithorax (EGFP-Ubx) fusion protein and luminescent CdSe-ZnS core-shell quantum dots (QDs), allowing us to optically assess the distribution of both the protein and nanoparticle components within the composite material. Although QDs favorably interact with EGFP-Ubx monomers, the relatively rough surface morphology of composite fibers suggests EGFP-Ubx-QD conjugates impact self-assembly. Indeed, QDs templated onto EGFP-Ubx film post-self-assembly can be subsequently drawn into smooth composite fibers. Additionally, the QD surface charge impacts QD distribution within the composite material, indicating that surface charge plays an important role in self-assembly. QDs with either positively or negatively charged coatings significantly enhance fiber extensibility. Conversely, QDs coated with hydrophobic moieties and suspended in toluene produce composite fibers with a heterogeneous distribution of QDs and severely altered fiber morphology, indicating that toluene severely disrupts Ubx self-assembly. Understanding factors that impact the protein-nanoparticle interaction enables manipulation of the structure and mechanical properties of composite materials. Since proteins interact with nanoparticle surface coatings, these results should be applicable to other types of nanoparticles with similar chemical groups on the surface.

Architectural protein subclasses shape 3-D organization of genomes during lineage commitment

PubMed Central

Phillips-Cremins, Jennifer E.; Sauria, Michael E. G.; Sanyal, Amartya; Gerasimova, Tatiana I.; Lajoie, Bryan R.; Bell, Joshua S. K.; Ong, Chin-Tong; Hookway, Tracy A.; Guo, Changying; Sun, Yuhua; Bland, Michael J.; Wagstaff, William; Dalton, Stephen; McDevitt, Todd C.; Sen, Ranjan; Dekker, Job; Taylor, James; Corces, Victor G.

2013-01-01

Summary Understanding the topological configurations of chromatin may reveal valuable insights into how the genome and epigenome act in concert to control cell fate during development. Here we generate high-resolution architecture maps across seven genomic loci in embryonic stem cells and neural progenitor cells. We observe a hierarchy of 3-D interactions that undergo marked reorganization at the sub-Mb scale during differentiation. Distinct combinations of CTCF, Mediator, and cohesin show widespread enrichment in looping interactions at different length scales. CTCF/cohesin anchor long-range constitutive interactions that form the topological basis for invariant sub-domains. Conversely, Mediator/cohesin together with pioneer factors bridge shortrange enhancer-promoter interactions within and between larger sub-domains. Knockdown of Smc1 or Med12 in ES cells results in disruption of spatial architecture and down-regulation of genes found in cohesin-mediated interactions. We conclude that cell type-specific chromatin organization occurs at the sub-Mb scale and that architectural proteins shape the genome in hierarchical length scales. PMID:23706625

Ex vivo mammalian prions are formed of paired double helical prion protein fibrils.

PubMed

Terry, Cassandra; Wenborn, Adam; Gros, Nathalie; Sells, Jessica; Joiner, Susan; Hosszu, Laszlo L P; Tattum, M Howard; Panico, Silvia; Clare, Daniel K; Collinge, John; Saibil, Helen R; Wadsworth, Jonathan D F

2016-05-01

Mammalian prions are hypothesized to be fibrillar or amyloid forms of prion protein (PrP), but structures observed to date have not been definitively correlated with infectivity and the three-dimensional structure of infectious prions has remained obscure. Recently, we developed novel methods to obtain exceptionally pure preparations of prions from mouse brain and showed that pathogenic PrP in these high-titre preparations is assembled into rod-like assemblies. Here, we have used precise cell culture-based prion infectivity assays to define the physical relationship between the PrP rods and prion infectivity and have used electron tomography to define their architecture. We show that infectious PrP rods isolated from multiple prion strains have a common hierarchical assembly comprising twisted pairs of short fibres with repeating substructure. The architecture of the PrP rods provides a new structural basis for understanding prion infectivity and can explain the inability to systematically generate high-titre synthetic prions from recombinant PrP. © 2016 The Authors.

Biomedical and Catalytic Opportunities of Virus-Like Particles in Nanotechnology.

PubMed

Schwarz, B; Uchida, M; Douglas, T

2017-01-01

Within biology, molecules are arranged in hierarchical structures that coordinate and control the many processes that allow for complex organisms to exist. Proteins and other functional macromolecules are often studied outside their natural nanostructural context because it remains difficult to create controlled arrangements of proteins at this size scale. Viruses are elegantly simple nanosystems that exist at the interface of living organisms and nonliving biological machines. Studied and viewed primarily as pathogens to be combatted, viruses have emerged as models of structural efficiency at the nanoscale and have spurred the development of biomimetic nanoparticle systems. Virus-like particles (VLPs) are noninfectious protein cages derived from viruses or other cage-forming systems. VLPs provide incredibly regular scaffolds for building at the nanoscale. Composed of self-assembling protein subunits, VLPs provide both a model for studying materials' assembly at the nanoscale and useful building blocks for materials design. The robustness and degree of understanding of many VLP structures allow for the ready use of these systems as versatile nanoparticle platforms for the conjugation of active molecules or as scaffolds for the structural organization of chemical processes. Lastly the prevalence of viruses in all domains of life has led to unique activities of VLPs in biological systems most notably the immune system. Here we discuss recent efforts to apply VLPs in a wide variety of applications with the aim of highlighting how the common structural elements of VLPs have led to their emergence as paradigms for the understanding and design of biological nanomaterials. © 2017 Elsevier Inc. All rights reserved.

Complex scenes and situations visualization in hierarchical learning algorithm with dynamic 3D NeoAxis engine

NASA Astrophysics Data System (ADS)

Graham, James; Ternovskiy, Igor V.

2013-06-01

We applied a two stage unsupervised hierarchical learning system to model complex dynamic surveillance and cyber space monitoring systems using a non-commercial version of the NeoAxis visualization software. The hierarchical scene learning and recognition approach is based on hierarchical expectation maximization, and was linked to a 3D graphics engine for validation of learning and classification results and understanding the human - autonomous system relationship. Scene recognition is performed by taking synthetically generated data and feeding it to a dynamic logic algorithm. The algorithm performs hierarchical recognition of the scene by first examining the features of the objects to determine which objects are present, and then determines the scene based on the objects present. This paper presents a framework within which low level data linked to higher-level visualization can provide support to a human operator and be evaluated in a detailed and systematic way.

Phrase Mining of Textual Data to Analyze Extracellular Matrix Protein Patterns Across Cardiovascular Disease.

PubMed

Liem, David Alexandre; Murali, Sanjana; Sigdel, Dibakar; Shi, Yu; Wang, Xuan; Shen, Jiaming; Choi, Howard; Caufield, J Harry; Wang, Wei; Ping, Peipei; Han, Jiawei

2018-05-18

Extracellular matrix (ECM) proteins have been shown to play important roles regulating multiple biological processes in an array of organ systems, including the cardiovascular system. By using a novel bioinformatics text-mining tool, we studied six categories of cardiovascular disease (CVD), namely ischemic heart disease (IHD), cardiomyopathies (CM), cerebrovascular accident (CVA), congenital heart disease (CHD), arrhythmias (ARR), and valve disease (VD), anticipating novel ECM protein-disease and protein-protein relationships hidden within vast quantities of textual data. We conducted a phrase-mining analysis, delineating the relationships of 709 ECM proteins with the six groups of CVDs reported in 1,099,254 abstracts. The technology pipeline known as Context-aware Semantic Online Analytical Processing (CaseOLAP) was applied to semantically rank the association of proteins to each and all six CVDs, performing analyses to quantify each protein-disease relationship. We performed principal component analysis and hierarchical clustering of the data, where each protein is visualized as a six dimensional vector. We found that ECM proteins display variable degrees of association with the six CVDs; certain CVDs share groups of associated proteins whereas others have divergent protein associations. We identified 82 ECM proteins sharing associations with all six CVDs. Our bioinformatics analysis ascribed distinct ECM pathways (via Reactome) from this subset of proteins, namely insulin-like growth factor regulation and interleukin-4 and interleukin-13 signaling, suggesting their contribution to the pathogenesis of all six CVDs. Finally, we performed hierarchical clustering analysis and identified protein clusters associated with a targeted CVD; analyses revealed unexpected insights underlying ECM-pathogenesis of CVDs.

An exactly solvable model of hierarchical self-assembly

NASA Astrophysics Data System (ADS)

Dudowicz, Jacek; Douglas, Jack F.; Freed, Karl F.

2009-06-01

Many living and nonliving structures in the natural world form by hierarchical organization, but physical theories that describe this type of organization are scarce. To address this problem, a model of equilibrium self-assembly is formulated in which dynamically associating species organize into hierarchical structures that preserve their shape at each stage of assembly. In particular, we consider symmetric m-gons that associate at their vertices into Sierpinski gasket structures involving the hierarchical association of triangles, squares, hexagons, etc., at their corner vertices, thereby leading to fractal structures after many generations of assembly. This rather idealized model of hierarchical assembly yields an infinite sequence of self-assembly transitions as the morphology progressively organizes to higher levels of the hierarchy, and these structures coexists at dynamic equilibrium, as found in real hierarchically self-assembling systems such as amyloid fiber forming proteins. Moreover, the transition sharpness progressively grows with increasing m, corresponding to larger and larger loops in the assembled structures. Calculations are provided for several basic thermodynamic properties (including the order parameters for assembly for each stage of the hierarchy, average mass of clusters, specific heat, transition sharpness, etc.) that are required for characterizing the interaction parameters governing this type of self-assembly and for elucidating other basic qualitative aspects of these systems. Our idealized model of hierarchical assembly gives many insights into this ubiquitous type of self-organization process.

Quantitative Characteristics of Gene Regulation by Small RNA

PubMed Central

Levine, Erel; Zhang, Zhongge; Kuhlman, Thomas; Hwa, Terence

2007-01-01

An increasing number of small RNAs (sRNAs) have been shown to regulate critical pathways in prokaryotes and eukaryotes. In bacteria, regulation by trans-encoded sRNAs is predominantly found in the coordination of intricate stress responses. The mechanisms by which sRNAs modulate expression of its targets are diverse. In common to most is the possibility that interference with the translation of mRNA targets may also alter the abundance of functional sRNAs. Aiming to understand the unique role played by sRNAs in gene regulation, we studied examples from two distinct classes of bacterial sRNAs in Escherichia coli using a quantitative approach combining experiment and theory. Our results demonstrate that sRNA provides a novel mode of gene regulation, with characteristics distinct from those of protein-mediated gene regulation. These include a threshold-linear response with a tunable threshold, a robust noise resistance characteristic, and a built-in capability for hierarchical cross-talk. Knowledge of these special features of sRNA-mediated regulation may be crucial toward understanding the subtle functions that sRNAs can play in coordinating various stress-relief pathways. Our results may also help guide the design of synthetic genetic circuits that have properties difficult to attain with protein regulators alone. PMID:17713988

Hierarchical Cluster Formation in Concentrated Monoclonal Antibody Formulations

NASA Astrophysics Data System (ADS)

Godfrin, P. Douglas; Zarzar, Jonathan; Zarraga, Isidro Dan; Porcar, Lionel; Falus, Peter; Wagner, Norman; Liu, Yun

Reversible cluster formation has been identified as an underlying cause of large solution viscosities observed in some concentrated monoclonal antibody (mAb) formulations. As high solution viscosity prevents the use of subcutaneous injection as a delivery method for some mAbs, a fundamental understanding of the interactions responsible for high viscosities in concentrated mAb solutions is of significant relevance to mAb applications in human health care as well as of intellectual interest. Here, we present a detailed investigation of a well-studied IgG1 based mAb to relate the short time dynamics and microstructure to significant viscosity changes over a range of pharmaceutically relevant physiochemical conditions. Using a combination of experimental techniques, it is found that upon adding Na2SO4, these antibodies dimerize in solution. Proteins form strongly bounded reversible dimers at dilute concentrations that, when concentrated, interact with each other to form loosely bounded, large, transient clusters. The combined effect of forming strongly bounded dimers and a large transient network is a significant increase in the solution viscosity. Strongly bounded, reversible dimers may exist in many IgG1 based mAb systems such that these results contribute to a more comprehensive understanding of the physical mechanisms producing high viscosities in concentrated protein solutions.

Hierarchical nanostructures for functional materials.

PubMed

Qin, Zhao; Buehler, Markus J

2018-07-13

Naturally occurring biomaterials often have amazing functions, such as mechanical, thermal, electromagnetic, biological, optical and acoustic. These superior performances are often due to their hierarchical organizations of natural materials, starting from the nanoscopic scale and extending all the way to the macroscopic level. This topical issue features articles dedicated to understanding, designing and characterizing complex de novo hierarchical materials for a variety of applications. This research area is quickly evolving, and we hope that future work will drive the rational designs of innovative functional materials and generate deep impacts to broad engineering fields that address major societal challenges and needs.

Hierarchical nanostructures for functional materials

NASA Astrophysics Data System (ADS)

Qin, Zhao; Buehler, Markus J.

2018-07-01

Naturally occurring biomaterials often have amazing functions, such as mechanical, thermal, electromagnetic, biological, optical and acoustic. These superior performances are often due to their hierarchical organizations of natural materials, starting from the nanoscopic scale and extending all the way to the macroscopic level. This topical issue features articles dedicated to understanding, designing and characterizing complex de novo hierarchical materials for a variety of applications. This research area is quickly evolving, and we hope that future work will drive the rational designs of innovative functional materials and generate deep impacts to broad engineering fields that address major societal challenges and needs.

Professionals’ views on interprofessional stroke team functioning

PubMed Central

Cramm, Jane M; Nieboer, Anna P

2011-01-01

Introduction The quality of integrated stroke care depends on smooth team functioning but professionals may not always work well together. Professionals’ perspectives on the factors that influence stroke team functioning remain largely unexamined. Understanding their experiences is critical to indentifying measures to improve team functioning. The aim of this study was to identify the factors that contributed to the success of interprofessional stroke teams as perceived by team members. Methods We distributed questionnaires to professionals within 34 integrated stroke care teams at various health care facilities in 9 Dutch regions. 558 respondents (response rate: 39%) completed the questionnaire. To account for the hierarchical structure of the study design we fitted a hierarchical random-effects model. The hierarchical structure comprised 558 stroke team members (level 1) nested in 34 teams (level 2). Results Analyses showed that personal development, social well-being, interprofessional education, communication, and role understanding significantly contributed to stroke team functioning. Team-level constructs affecting interprofessional stroke team functioning were communication and role understanding. No significant relationships were found with individual-level personal autonomy and team-level cohesion. Discussion and conclusion Our findings suggest that interventions to improve team members’ social well-being, communication, and role understanding will improve teams’ performance. To further advance interprofessional team functioning, healthcare organizations should pay attention to developing professionals’ interpersonal skills and interprofessional education. PMID:23390409

Statistical Analysis of Variation in the Human Plasma Proteome

DOE PAGES

Corzett, Todd H.; Fodor, Imola K.; Choi, Megan W.; ...

2010-01-01

Quantifying the variation in the human plasma proteome is an essential prerequisite for disease-specific biomarker detection. We report here on the longitudinal and individual variation in human plasma characterized by two-dimensional difference gel electrophoresis (2-D DIGE) using plasma samples from eleven healthy subjects collected three times over a two week period. Fixed-effects modeling was used to remove dye and gel variability. Mixed-effects modeling was then used to quantitate the sources of proteomic variation. The subject-to-subject variation represented the largest variance component, while the time-within-subject variation was comparable to the experimental variation found in a previous technical variability study where onemore » human plasma sample was processed eight times in parallel and each was then analyzed by 2-D DIGE in triplicate. Here, 21 protein spots had larger than 50% CV, suggesting that these proteins may not be appropriate as biomarkers and should be carefully scrutinized in future studies. Seventy-eight protein spots showing differential protein levels between different individuals or individual collections were identified by mass spectrometry and further characterized using hierarchical clustering. The results present a first step toward understanding the complexity of longitudinal and individual variation in the human plasma proteome, and provide a baseline for improved biomarker discovery.« less

Statistical analysis of variation in the human plasma proteome.

PubMed

Corzett, Todd H; Fodor, Imola K; Choi, Megan W; Walsworth, Vicki L; Turteltaub, Kenneth W; McCutchen-Maloney, Sandra L; Chromy, Brett A

2010-01-01

Quantifying the variation in the human plasma proteome is an essential prerequisite for disease-specific biomarker detection. We report here on the longitudinal and individual variation in human plasma characterized by two-dimensional difference gel electrophoresis (2-D DIGE) using plasma samples from eleven healthy subjects collected three times over a two week period. Fixed-effects modeling was used to remove dye and gel variability. Mixed-effects modeling was then used to quantitate the sources of proteomic variation. The subject-to-subject variation represented the largest variance component, while the time-within-subject variation was comparable to the experimental variation found in a previous technical variability study where one human plasma sample was processed eight times in parallel and each was then analyzed by 2-D DIGE in triplicate. Here, 21 protein spots had larger than 50% CV, suggesting that these proteins may not be appropriate as biomarkers and should be carefully scrutinized in future studies. Seventy-eight protein spots showing differential protein levels between different individuals or individual collections were identified by mass spectrometry and further characterized using hierarchical clustering. The results present a first step toward understanding the complexity of longitudinal and individual variation in the human plasma proteome, and provide a baseline for improved biomarker discovery.

Hierarchical recruitment of ribosomal proteins and assembly factors remodels nucleolar pre-60S ribosomes.

PubMed

Biedka, Stephanie; Micic, Jelena; Wilson, Daniel; Brown, Hailey; Diorio-Toth, Luke; Woolford, John L

2018-04-24

Ribosome biogenesis involves numerous preribosomal RNA (pre-rRNA) processing events to remove internal and external transcribed spacer sequences, ultimately yielding three mature rRNAs. Removal of the internal transcribed spacer 2 spacer RNA is the final step in large subunit pre-rRNA processing and begins with endonucleolytic cleavage at the C 2 site of 27SB pre-rRNA. C 2 cleavage requires the hierarchical recruitment of 11 ribosomal proteins and 14 ribosome assembly factors. However, the function of these proteins in C 2 cleavage remained unclear. In this study, we have performed a detailed analysis of the effects of depleting proteins required for C 2 cleavage and interpreted these results using cryo-electron microscopy structures of assembling 60S subunits. This work revealed that these proteins are required for remodeling of several neighborhoods, including two major functional centers of the 60S subunit, suggesting that these remodeling events form a checkpoint leading to C 2 cleavage. Interestingly, when C 2 cleavage is directly blocked by depleting or inactivating the C 2 endonuclease, assembly progresses through all other subsequent steps. © 2018 Biedka et al.

YTPdb: a wiki database of yeast membrane transporters.

PubMed

Brohée, Sylvain; Barriot, Roland; Moreau, Yves; André, Bruno

2010-10-01

Membrane transporters constitute one of the largest functional categories of proteins in all organisms. In the yeast Saccharomyces cerevisiae, this represents about 300 proteins ( approximately 5% of the proteome). We here present the Yeast Transport Protein database (YTPdb), a user-friendly collaborative resource dedicated to the precise classification and annotation of yeast transporters. YTPdb exploits an evolution of the MediaWiki web engine used for popular collaborative databases like Wikipedia, allowing every registered user to edit the data in a user-friendly manner. Proteins in YTPdb are classified on the basis of functional criteria such as subcellular location or their substrate compounds. These classifications are hierarchical, allowing queries to be performed at various levels, from highly specific (e.g. ammonium as a substrate or the vacuole as a location) to broader (e.g. cation as a substrate or inner membranes as location). Other resources accessible for each transporter via YTPdb include post-translational modifications, K(m) values, a permanently updated bibliography, and a hierarchical classification into families. The YTPdb concept can be extrapolated to other organisms and could even be applied for other functional categories of proteins. YTPdb is accessible at http://homes.esat.kuleuven.be/ytpdb/. Copyright © 2010 Elsevier B.V. All rights reserved.

The hierarchical structure of self-reported impulsivity

PubMed Central

Kirby, Kris N.; Finch, Julia C.

2010-01-01

The hierarchical structure of 95 self-reported impulsivity items, along with delay-discount rates for money, was examined. A large sample of college students participated in the study (N = 407). Items represented every previously proposed dimension of self-reported impulsivity. Exploratory PCA yielded at least 7 interpretable components: Prepared/Careful, Impetuous, Divertible, Thrill and Risk Seeking, Happy-Go-Lucky, Impatiently Pleasure Seeking, and Reserved. Discount rates loaded on Impatiently Pleasure Seeking, and correlated with the impulsiveness and venturesomeness scales from the I7 (Eysenck, Pearson, Easting, & Allsopp, 1985). The hierarchical emergence of the components was explored, and we show how this hierarchical structure may help organize conflicting dimensions found in previous analyses. Finally, we argue that the discounting model (Ainslie, 1975) provides a qualitative framework for understanding the dimensions of impulsivity. PMID:20224803

Resolving protein interactions and organization downstream the T cell antigen receptor using single-molecule localization microscopy: a review

NASA Astrophysics Data System (ADS)

Sherman, Eilon

2016-06-01

Signal transduction is mediated by heterogeneous and dynamic protein complexes. Such complexes play a critical role in diverse cell functions, with the important example of T cell activation. Biochemical studies of signalling complexes and their imaging by diffraction limited microscopy have resulted in an intricate network of interactions downstream the T cell antigen receptor (TCR). However, in spite of their crucial roles in T cell activation, much remains to be learned about these signalling complexes, including their heterogeneous contents and size distribution, their complex arrangements in the PM, and the molecular requirements for their formation. Here, we review how recent advancements in single molecule localization microscopy have helped to shed new light on the organization of signalling complexes in single molecule detail in intact T cells. From these studies emerges a picture where cells extensively employ hierarchical and dynamic patterns of nano-scale organization to control the local concentration of interacting molecular species. These patterns are suggested to play a critical role in cell decision making. The combination of SMLM with more traditional techniques is expected to continue and critically contribute to our understanding of multimolecular protein complexes and their significance to cell function.

Silk-regulated hierarchical hollow magnetite/carbon nanocomposite spheroids for lithium-ion battery anodes.

PubMed

Sheng, Weiqin; Zhu, Guobin; Kaplan, David L; Cao, Chuanbao; Zhu, Hesun; Lu, Qiang

2015-03-20

Hierarchical olive-like structured carbon-Fe3O4 nanocomposite particles composed of a hollow interior and a carbon coated surface are prepared by a facile, silk protein-assisted hydrothermal method. Silk nanofibers as templates and carbon precursors first regulate the formation of hollow Fe2O3 microspheres and then they are converted into carbon by a reduction process into Fe3O4. This process significantly simplifies the fabrication and carbon coating processes to form complex hollow structures. When tested as anode materials for lithium-ion batteries, these hollow carbon-coated particles exhibit high capacity (900 mAh g(-1)), excellent cycle stability (180 cycles) and rate performance due to their unique hierarchical hollow structure and carbon coating.

System and methods for predicting transmembrane domains in membrane proteins and mining the genome for recognizing G-protein coupled receptors

DOEpatents

Trabanino, Rene J; Vaidehi, Nagarajan; Hall, Spencer E; Goddard, William A; Floriano, Wely

2013-02-05

The invention provides computer-implemented methods and apparatus implementing a hierarchical protocol using multiscale molecular dynamics and molecular modeling methods to predict the presence of transmembrane regions in proteins, such as G-Protein Coupled Receptors (GPCR), and protein structural models generated according to the protocol. The protocol features a coarse grain sampling method, such as hydrophobicity analysis, to provide a fast and accurate procedure for predicting transmembrane regions. Methods and apparatus of the invention are useful to screen protein or polynucleotide databases for encoded proteins with transmembrane regions, such as GPCRs.

Analysis of Soluble Proteins in Natural Cordyceps sinensis from Different Producing Areas by Sodium Dodecyl Sulfate-Polyacrylamide Gel Electrophoresis and Two-dimensional Electrophoresis

PubMed Central

Li, Chun-Hong; Zuo, Hua-Li; Zhang, Qian; Wang, Feng-Qin; Hu, Yuan-Jia; Qian, Zheng-Ming; Li, Wen-Jia; Xia, Zhi-Ning; Yang, Feng-Qing

2017-01-01

Background: As one of the bioactive components in Cordyceps sinensis (CS), proteins were rarely used as index components to study the correlation between the protein components and producing areas of natural CS. Objective: Protein components of 26 natural CS samples produced in Qinghai, Tibet, and Sichuan provinces were analyzed and compared to investigate the relationship among 26 different producing areas. Materials and Methods: Proteins from 26 different producing areas were extracted by Tris-HCl buffer with Triton X-100, and separated using sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and two-dimensional electrophoresis (2-DE). Results: The SDS-PAGE results indicated that the number of protein bands and optical density curves of proteins in 26 CS samples was a bit different. However, the 2-DE results showed that the numbers and abundance of protein spots in protein profiles of 26 samples were obviously different and showed certain association with producing areas. Conclusions: Based on the expression values of matched protein spots, 26 batches of CS samples can be divided into two main categories (Tibet and Qinghai) by hierarchical cluster analysis. SUMMARY The number of protein bands and optical density curves of proteins in 26 Cordyceps sinensis samples were a bit different on the sodium dodecyl sulfate-polyacrylamide gel electrophoresis protein profilesNumbers and abundance of protein spots in protein profiles of 26 samples were obvious different on two-dimensional electrophoresis mapsTwenty-six different producing areas of natural Cordyceps sinensis samples were divided into two main categories (Tibet and Qinghai) by Hierarchical cluster analysis based on the values of matched protein spots. Abbreviations Used: SDS-PAGE: Sodium dodecyl sulfate polyacrylamide gel electrophoresis, 2-DE: Two-dimensional electrophoresis, Cordyceps sinensis: CS, TCMs: Traditional Chinese medicines PMID:28250651

Analysis of Soluble Proteins in Natural Cordyceps sinensis from Different Producing Areas by Sodium Dodecyl Sulfate-Polyacrylamide Gel Electrophoresis and Two-dimensional Electrophoresis.

PubMed

Li, Chun-Hong; Zuo, Hua-Li; Zhang, Qian; Wang, Feng-Qin; Hu, Yuan-Jia; Qian, Zheng-Ming; Li, Wen-Jia; Xia, Zhi-Ning; Yang, Feng-Qing

2017-01-01

As one of the bioactive components in Cordyceps sinensis (CS), proteins were rarely used as index components to study the correlation between the protein components and producing areas of natural CS. Protein components of 26 natural CS samples produced in Qinghai, Tibet, and Sichuan provinces were analyzed and compared to investigate the relationship among 26 different producing areas. Proteins from 26 different producing areas were extracted by Tris-HCl buffer with Triton X-100, and separated using sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and two-dimensional electrophoresis (2-DE). The SDS-PAGE results indicated that the number of protein bands and optical density curves of proteins in 26 CS samples was a bit different. However, the 2-DE results showed that the numbers and abundance of protein spots in protein profiles of 26 samples were obviously different and showed certain association with producing areas. Based on the expression values of matched protein spots, 26 batches of CS samples can be divided into two main categories (Tibet and Qinghai) by hierarchical cluster analysis. The number of protein bands and optical density curves of proteins in 26 Cordyceps sinensis samples were a bit different on the sodium dodecyl sulfate-polyacrylamide gel electrophoresis protein profilesNumbers and abundance of protein spots in protein profiles of 26 samples were obvious different on two-dimensional electrophoresis mapsTwenty-six different producing areas of natural Cordyceps sinensis samples were divided into two main categories (Tibet and Qinghai) by Hierarchical cluster analysis based on the values of matched protein spots. Abbreviations Used : SDS-PAGE: Sodium dodecyl sulfate polyacrylamide gel electrophoresis, 2-DE: Two-dimensional electrophoresis, Cordyceps sinensis : CS, TCMs: Traditional Chinese medicines.

Label-free proteomic analysis of intestinal mucosa proteins in common carp (Cyprinus carpio) infected with Aeromonas hydrophila.

PubMed

Di, Guilan; Li, Hui; Zhang, Chao; Zhao, Yanjing; Zhou, Chuanjiang; Naeem, Sajid; Li, Li; Kong, Xianghui

2017-07-01

Outbreaks of infectious diseases in common carp Cyprinus carpio, a major cultured fish in northern regions of China, constantly result in significant economic losses. Until now, information proteomic on immune defence remains limited. In the present study, a profile of intestinal mucosa immune response in Cyprinus carpio was investigated after 0, 12, 36 and 84 h after challenging tissues with Aeromonas hydrophila at a concentration of 1.4 × 10 8  CFU/mL. Proteomic profiles in different samples were compared using label-free quantitative proteomic approach. Based on MASCOT database search, 1149 proteins were identified in samples after normalisation of proteins. Treated groups 1 (T1) and 2 (T2) were first clustered together and then clustered with control (C group). The distance between C and treated group 3 (T3) represented the maxima according to hierarchical cluster analysis. Therefore, comparative analysis between C and T3 was selected in the following analysis. A total of 115 proteins with differential abundance were detected to show conspicuous expressing variances. A total of 52 up-regulated proteins and 63 down-regulated proteins were detected in T3. Gene ontology analysis showed that identified up-regulated differentially expressed proteins in T3 were mainly localised in the hemoglobin complex, and down-regulated proteins in T3 were mainly localised in the major histocompatibility complex II protein complex. Forty-six proteins of differential abundance (40% of 115) were involved in immune response, with 17 up-regulated and 29 down-regulated proteins detected in T3. This study is the first to report proteome response of carp intestinal mucosa against A. hydrophila infection; information obtained contribute to understanding defence mechanisms of carp intestinal mucosa. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparison of a species distribution model and a process model from a hierarchical perspective to quantify effects of projected climate change on tree species

Treesearch

Jeffrey E. Schneiderman; Hong S. He; Frank R. Thompson; William D. Dijak; Jacob S. Fraser

2015-01-01

Tree species distribution and abundance are affected by forces operating across a hierarchy of ecological scales. Process and species distribution models have been developed emphasizing forces at different scales. Understanding model agreement across hierarchical scales provides perspective on prediction uncertainty and ultimately enables policy makers and managers to...

Understanding seasonal variability of uncertainty in hydrological prediction

NASA Astrophysics Data System (ADS)

Li, M.; Wang, Q. J.

2012-04-01

Understanding uncertainty in hydrological prediction can be highly valuable for improving the reliability of streamflow prediction. In this study, a monthly water balance model, WAPABA, in a Bayesian joint probability with error models are presented to investigate the seasonal dependency of prediction error structure. A seasonal invariant error model, analogous to traditional time series analysis, uses constant parameters for model error and account for no seasonal variations. In contrast, a seasonal variant error model uses a different set of parameters for bias, variance and autocorrelation for each individual calendar month. Potential connection amongst model parameters from similar months is not considered within the seasonal variant model and could result in over-fitting and over-parameterization. A hierarchical error model further applies some distributional restrictions on model parameters within a Bayesian hierarchical framework. An iterative algorithm is implemented to expedite the maximum a posterior (MAP) estimation of a hierarchical error model. Three error models are applied to forecasting streamflow at a catchment in southeast Australia in a cross-validation analysis. This study also presents a number of statistical measures and graphical tools to compare the predictive skills of different error models. From probability integral transform histograms and other diagnostic graphs, the hierarchical error model conforms better to reliability when compared to the seasonal invariant error model. The hierarchical error model also generally provides the most accurate mean prediction in terms of the Nash-Sutcliffe model efficiency coefficient and the best probabilistic prediction in terms of the continuous ranked probability score (CRPS). The model parameters of the seasonal variant error model are very sensitive to each cross validation, while the hierarchical error model produces much more robust and reliable model parameters. Furthermore, the result of the hierarchical error model shows that most of model parameters are not seasonal variant except for error bias. The seasonal variant error model is likely to use more parameters than necessary to maximize the posterior likelihood. The model flexibility and robustness indicates that the hierarchical error model has great potential for future streamflow predictions.

Estimating mono- and bi-phasic regression parameters using a mixture piecewise linear Bayesian hierarchical model

PubMed Central

Zhao, Rui; Catalano, Paul; DeGruttola, Victor G.; Michor, Franziska

2017-01-01

The dynamics of tumor burden, secreted proteins or other biomarkers over time, is often used to evaluate the effectiveness of therapy and to predict outcomes for patients. Many methods have been proposed to investigate longitudinal trends to better characterize patients and to understand disease progression. However, most approaches assume a homogeneous patient population and a uniform response trajectory over time and across patients. Here, we present a mixture piecewise linear Bayesian hierarchical model, which takes into account both population heterogeneity and nonlinear relationships between biomarkers and time. Simulation results show that our method was able to classify subjects according to their patterns of treatment response with greater than 80% accuracy in the three scenarios tested. We then applied our model to a large randomized controlled phase III clinical trial of multiple myeloma patients. Analysis results suggest that the longitudinal tumor burden trajectories in multiple myeloma patients are heterogeneous and nonlinear, even among patients assigned to the same treatment cohort. In addition, between cohorts, there are distinct differences in terms of the regression parameters and the distributions among categories in the mixture. Those results imply that longitudinal data from clinical trials may harbor unobserved subgroups and nonlinear relationships; accounting for both may be important for analyzing longitudinal data. PMID:28723910

Application of growing hierarchical SOM for visualisation of network forensics traffic data.

PubMed

Palomo, E J; North, J; Elizondo, D; Luque, R M; Watson, T

2012-08-01

Digital investigation methods are becoming more and more important due to the proliferation of digital crimes and crimes involving digital evidence. Network forensics is a research area that gathers evidence by collecting and analysing network traffic data logs. This analysis can be a difficult process, especially because of the high variability of these attacks and large amount of data. Therefore, software tools that can help with these digital investigations are in great demand. In this paper, a novel approach to analysing and visualising network traffic data based on growing hierarchical self-organising maps (GHSOM) is presented. The self-organising map (SOM) has been shown to be successful for the analysis of highly-dimensional input data in data mining applications as well as for data visualisation in a more intuitive and understandable manner. However, the SOM has some problems related to its static topology and its inability to represent hierarchical relationships in the input data. The GHSOM tries to overcome these limitations by generating a hierarchical architecture that is automatically determined according to the input data and reflects the inherent hierarchical relationships among them. Moreover, the proposed GHSOM has been modified to correctly treat the qualitative features that are present in the traffic data in addition to the quantitative features. Experimental results show that this approach can be very useful for a better understanding of network traffic data, making it easier to search for evidence of attacks or anomalous behaviour in a network environment. Copyright © 2012 Elsevier Ltd. All rights reserved.

Cooperativity and modularity in protein folding

PubMed Central

Sasai, Masaki; Chikenji, George; Terada, Tomoki P.

2016-01-01

A simple statistical mechanical model proposed by Wako and Saitô has explained the aspects of protein folding surprisingly well. This model was systematically applied to multiple proteins by Muñoz and Eaton and has since been referred to as the Wako-Saitô-Muñoz-Eaton (WSME) model. The success of the WSME model in explaining the folding of many proteins has verified the hypothesis that the folding is dominated by native interactions, which makes the energy landscape globally biased toward native conformation. Using the WSME and other related models, Saitô emphasized the importance of the hierarchical pathway in protein folding; folding starts with the creation of contiguous segments having a native-like configuration and proceeds as growth and coalescence of these segments. The Φ-values calculated for barnase with the WSME model suggested that segments contributing to the folding nucleus are similar to the structural modules defined by the pattern of native atomic contacts. The WSME model was extended to explain folding of multi-domain proteins having a complex topology, which opened the way to comprehensively understanding the folding process of multi-domain proteins. The WSME model was also extended to describe allosteric transitions, indicating that the allosteric structural movement does not occur as a deterministic sequential change between two conformations but as a stochastic diffusive motion over the dynamically changing energy landscape. Statistical mechanical viewpoint on folding, as highlighted by the WSME model, has been renovated in the context of modern methods and ideas, and will continue to provide insights on equilibrium and dynamical features of proteins. PMID:28409080

A strategy for absolute proteome quantification with mass spectrometry by hierarchical use of peptide-concatenated standards.

PubMed

Kito, Keiji; Okada, Mitsuhiro; Ishibashi, Yuko; Okada, Satoshi; Ito, Takashi

2016-05-01

The accurate and precise absolute abundance of proteins can be determined using mass spectrometry by spiking the sample with stable isotope-labeled standards. In this study, we developed a strategy of hierarchical use of peptide-concatenated standards (PCSs) to quantify more proteins over a wider dynamic range. Multiple primary PCSs were used for quantification of many target proteins. Unique "ID-tag peptides" were introduced into individual primary PCSs, allowing us to monitor the exact amounts of individual PCSs using a "secondary PCS" in which all "ID-tag peptides" were concatenated. Furthermore, we varied the copy number of the "ID-tag peptide" in each PCS according to a range of expression levels of target proteins. This strategy accomplished absolute quantification over a wider range than that of the measured ratios. The quantified abundance of budding yeast proteins showed a high reproducibility for replicate analyses and similar copy numbers per cell for ribosomal proteins, demonstrating the accuracy and precision of this strategy. A comparison with the absolute abundance of transcripts clearly indicated different post-transcriptional regulation of expression for specific functional groups. Thus, the approach presented here is a faithful method for the absolute quantification of proteomes and provides insights into biological mechanisms, including the regulation of expressed protein abundance. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Proteomic analysis of muscle between hybrid abalone and parental lines Haliotis gigantea Reeve and Haliotis discus hannai Ino

PubMed Central

Di, G; Luo, X; You, W; Zhao, J; Kong, X; Ke, C

2015-01-01

To understand the potential molecular mechanism of heterosis, protein expression patterns were compared from hybrids of Haliotis gigantea (G) and Haliotis discus hannai (D) using two-dimensional gel electrophoresis (2-DE) and matrix-assisted laser desorption/ionization time-of-flight/time-of-flight analyses. Expression differences were observed in muscle samples from the four groups with 673±21.0 stained spots for H. discus hannai ♀ × H. discus hannai ♂ (DD), 692±25.6 for H. gigantea ♀ × H. gigantea ♂ (GG), 679±16.2 for H. discus hannai ♀ × H. gigantea ♂ (DG) (F1 hybrid) and 700±19 for H. gigantea ♀ × H. discus hannai ♂ (GD) (F1 hybrid). Different 2-DE image muscle protein spots had a mirrored relationship between purebreds and the F1 hybrid, suggesting that all stained spots in F1 hybrid muscle were on 2-DEs from parents. DD and DG clustered together first, and then clustered with GD, whereas the distance of DD and GG was maximal according to hierarchical cluster analysis. We identified 136 differentially expressed protein spots involved in major biological processes, including energy metabolism and stress response. Most energy metabolism proteins were additive, and stress-induced proteins displayed additivity or over-dominance. In these 136 identified protein spots, hybrid offspring with additivity or over-dominance accounted for 68.38%. Data show that a proteomic approach can provide functional prediction of abalone interspecific hybridization. PMID:25669609

Proteomic analysis during of spore germination of Moniliophthora perniciosa, the causal agent of witches' broom disease in cacao.

PubMed

Mares, Joise Hander; Gramacho, Karina Peres; Santos, Everton Cruz; da Silva Santiago, André; Santana, Juliano Oliveira; de Sousa, Aurizângela Oliveira; Alvim, Fátima Cerqueira; Pirovani, Carlos Priminho

2017-08-17

Moniliophthora perniciosa is a phytopathogenic fungus responsible for witches' broom disease of cacao trees (Theobroma cacao L.). Understanding the molecular events during germination of the pathogen may enable the development of strategies for disease control in these economically important plants. In this study, we determined a comparative proteomic profile of M. perniciosa basidiospores during germination by two-dimensional SDS-PAGE and mass spectrometry. A total of 316 proteins were identified. Molecular changes during the development of the germinative tube were identified by a hierarchical clustering analysis based on the differential accumulation of proteins. Proteins associated with fungal filamentation, such as septin and kinesin, were detected only 4 h after germination (hag). A transcription factor related to biosynthesis of the secondary metabolite fumagillin, which can form hybrids with polyketides, was induced 2 hag, and polyketide synthase was observed 4 hag. The accumulation of ATP synthase, binding immunoglobulin protein (BiP), and catalase was validated by western blotting. In this study, we showed variations in protein expression during the early germination stages of fungus M. perniciosa. Proteins associated with fungal filamentation, and consequently with virulence, were detected in basidiospores 4 hag., for example, septin and kinesin. We discuss these results and propose a model of the germination of fungus M. perniciosa. This research can help elucidate the mechanisms underlying basic processes of host invasion and to develop strategies for control of the disease.

Topology of foreign exchange markets using hierarchical structure methods

NASA Astrophysics Data System (ADS)

Naylor, Michael J.; Rose, Lawrence C.; Moyle, Brendan J.

2007-08-01

This paper uses two physics derived hierarchical techniques, a minimal spanning tree and an ultrametric hierarchical tree, to extract a topological influence map for major currencies from the ultrametric distance matrix for 1995-2001. We find that these two techniques generate a defined and robust scale free network with meaningful taxonomy. The topology is shown to be robust with respect to method, to time horizon and is stable during market crises. This topology, appropriately used, gives a useful guide to determining the underlying economic or regional causal relationships for individual currencies and to understanding the dynamics of exchange rate price determination as part of a complex network.

New insight in magnetic saturation behavior of nickel hierarchical structures

NASA Astrophysics Data System (ADS)

Ma, Ji; Zhang, Jianxing; Liu, Chunting; Chen, Kezheng

2017-09-01

It is unanimously accepted that non-ferromagnetic inclusions in a ferromagnetic system will lower down total saturation magnetization in unit of emu/g. In this study, ;lattice strain; was found to be another key factor to have critical impact on magnetic saturation behavior of the system. The lattice strain determined assembling patterns of primary nanoparticles in hierarchical structures and was intimately related with the formation process of these architectures. Therefore, flower-necklace-like and cauliflower-like nickel hierarchical structures were used as prototype systems to evidence the relationship between assembling patterns of primary nanoparticles and magnetic saturation behaviors of these architectures. It was found that the influence of lattice strain on saturation magnetization outperformed that of non-ferromagnetic inclusions in these hierarchical structures. This will enable new insights into fundamental understanding of related magnetic effects.

Modes of Interaction between Individuals Dominate the Topologies of Real World Networks

PubMed Central

Lee, Insuk; Kim, Eiru; Marcotte, Edward M.

2015-01-01

We find that the topologies of real world networks, such as those formed within human societies, by the Internet, or among cellular proteins, are dominated by the mode of the interactions considered among the individuals. Specifically, a major dichotomy in previously studied networks arises from modeling networks in terms of pairwise versus group tasks. The former often intrinsically give rise to scale-free, disassortative, hierarchical networks, whereas the latter often give rise to single- or broad-scale, assortative, nonhierarchical networks. These dependencies explain contrasting observations among previous topological analyses of real world complex systems. We also observe this trend in systems with natural hierarchies, in which alternate representations of the same networks, but which capture different levels of the hierarchy, manifest these signature topological differences. For example, in both the Internet and cellular proteomes, networks of lower-level system components (routers within domains or proteins within biological processes) are assortative and nonhierarchical, whereas networks of upper-level system components (internet domains or biological processes) are disassortative and hierarchical. Our results demonstrate that network topologies of complex systems must be interpreted in light of their hierarchical natures and interaction types. PMID:25793969

Hierarchical Partitioning of Metazoan Protein Conservation Profiles Provides New Functional Insights

PubMed Central

Witztum, Jonathan; Persi, Erez; Horn, David; Pasmanik-Chor, Metsada; Chor, Benny

2014-01-01

The availability of many complete, annotated proteomes enables the systematic study of the relationships between protein conservation and functionality. We explore this question based solely on the presence or absence of protein homologues (a.k.a. conservation profiles). We study 18 metazoans, from two distinct points of view: the human's and the fly's. Using the GOrilla gene ontology (GO) analysis tool, we explore functional enrichment of the “universal proteins”, those with homologues in all 17 other species, and of the “non-universal proteins”. A large number of GO terms are strongly enriched in both human and fly universal proteins. Most of these functions are known to be essential. A smaller number of GO terms, exhibiting markedly different properties, are enriched in both human and fly non-universal proteins. We further explore the non-universal proteins, whose conservation profiles are consistent with the “tree of life” (TOL consistent), as well as the TOL inconsistent proteins. Finally, we applied Quantum Clustering to the conservation profiles of the TOL consistent proteins. Each cluster is strongly associated with one or a small number of specific monophyletic clades in the tree of life. The proteins in many of these clusters exhibit strong functional enrichment associated with the “life style” of the related clades. Most previous approaches for studying function and conservation are “bottom up”, studying protein families one by one, and separately assessing the conservation of each. By way of contrast, our approach is “top down”. We globally partition the set of all proteins hierarchically, as described above, and then identify protein families enriched within different subdivisions. While supporting previous findings, our approach also provides a tool for discovering novel relations between protein conservation profiles, functionality, and evolutionary history as represented by the tree of life. PMID:24594619

Predicting protein subcellular locations using hierarchical ensemble of Bayesian classifiers based on Markov chains.

PubMed

Bulashevska, Alla; Eils, Roland

2006-06-14

The subcellular location of a protein is closely related to its function. It would be worthwhile to develop a method to predict the subcellular location for a given protein when only the amino acid sequence of the protein is known. Although many efforts have been made to predict subcellular location from sequence information only, there is the need for further research to improve the accuracy of prediction. A novel method called HensBC is introduced to predict protein subcellular location. HensBC is a recursive algorithm which constructs a hierarchical ensemble of classifiers. The classifiers used are Bayesian classifiers based on Markov chain models. We tested our method on six various datasets; among them are Gram-negative bacteria dataset, data for discriminating outer membrane proteins and apoptosis proteins dataset. We observed that our method can predict the subcellular location with high accuracy. Another advantage of the proposed method is that it can improve the accuracy of the prediction of some classes with few sequences in training and is therefore useful for datasets with imbalanced distribution of classes. This study introduces an algorithm which uses only the primary sequence of a protein to predict its subcellular location. The proposed recursive scheme represents an interesting methodology for learning and combining classifiers. The method is computationally efficient and competitive with the previously reported approaches in terms of prediction accuracies as empirical results indicate. The code for the software is available upon request.

Bayesian models: A statistical primer for ecologists

USGS Publications Warehouse

Hobbs, N. Thompson; Hooten, Mevin B.

2015-01-01

Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This textbook provides a comprehensive and accessible introduction to the latest Bayesian methods—in language ecologists can understand. Unlike other books on the subject, this one emphasizes the principles behind the computations, giving ecologists a big-picture understanding of how to implement this powerful statistical approach.Bayesian Models is an essential primer for non-statisticians. It begins with a definition of probability and develops a step-by-step sequence of connected ideas, including basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and inference from single and multiple models. This unique book places less emphasis on computer coding, favoring instead a concise presentation of the mathematical statistics needed to understand how and why Bayesian analysis works. It also explains how to write out properly formulated hierarchical Bayesian models and use them in computing, research papers, and proposals.This primer enables ecologists to understand the statistical principles behind Bayesian modeling and apply them to research, teaching, policy, and management.Presents the mathematical and statistical foundations of Bayesian modeling in language accessible to non-statisticiansCovers basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and moreDeemphasizes computer coding in favor of basic principlesExplains how to write out properly factored statistical expressions representing Bayesian models

(Im)Perfect robustness and adaptation of metabolic networks subject to metabolic and gene-expression regulation: marrying control engineering with metabolic control analysis.

PubMed

He, Fei; Fromion, Vincent; Westerhoff, Hans V

2013-11-21

Metabolic control analysis (MCA) and supply-demand theory have led to appreciable understanding of the systems properties of metabolic networks that are subject exclusively to metabolic regulation. Supply-demand theory has not yet considered gene-expression regulation explicitly whilst a variant of MCA, i.e. Hierarchical Control Analysis (HCA), has done so. Existing analyses based on control engineering approaches have not been very explicit about whether metabolic or gene-expression regulation would be involved, but designed different ways in which regulation could be organized, with the potential of causing adaptation to be perfect. This study integrates control engineering and classical MCA augmented with supply-demand theory and HCA. Because gene-expression regulation involves time integration, it is identified as a natural instantiation of the 'integral control' (or near integral control) known in control engineering. This study then focuses on robustness against and adaptation to perturbations of process activities in the network, which could result from environmental perturbations, mutations or slow noise. It is shown however that this type of 'integral control' should rarely be expected to lead to the 'perfect adaptation': although the gene-expression regulation increases the robustness of important metabolite concentrations, it rarely makes them infinitely robust. For perfect adaptation to occur, the protein degradation reactions should be zero order in the concentration of the protein, which may be rare biologically for cells growing steadily. A proposed new framework integrating the methodologies of control engineering and metabolic and hierarchical control analysis, improves the understanding of biological systems that are regulated both metabolically and by gene expression. In particular, the new approach enables one to address the issue whether the intracellular biochemical networks that have been and are being identified by genomics and systems biology, correspond to the 'perfect' regulatory structures designed by control engineering vis-à-vis optimal functions such as robustness. To the extent that they are not, the analyses suggest how they may become so and this in turn should facilitate synthetic biology and metabolic engineering.

(Im)Perfect robustness and adaptation of metabolic networks subject to metabolic and gene-expression regulation: marrying control engineering with metabolic control analysis

PubMed Central

2013-01-01

Background Metabolic control analysis (MCA) and supply–demand theory have led to appreciable understanding of the systems properties of metabolic networks that are subject exclusively to metabolic regulation. Supply–demand theory has not yet considered gene-expression regulation explicitly whilst a variant of MCA, i.e. Hierarchical Control Analysis (HCA), has done so. Existing analyses based on control engineering approaches have not been very explicit about whether metabolic or gene-expression regulation would be involved, but designed different ways in which regulation could be organized, with the potential of causing adaptation to be perfect. Results This study integrates control engineering and classical MCA augmented with supply–demand theory and HCA. Because gene-expression regulation involves time integration, it is identified as a natural instantiation of the ‘integral control’ (or near integral control) known in control engineering. This study then focuses on robustness against and adaptation to perturbations of process activities in the network, which could result from environmental perturbations, mutations or slow noise. It is shown however that this type of ‘integral control’ should rarely be expected to lead to the ‘perfect adaptation’: although the gene-expression regulation increases the robustness of important metabolite concentrations, it rarely makes them infinitely robust. For perfect adaptation to occur, the protein degradation reactions should be zero order in the concentration of the protein, which may be rare biologically for cells growing steadily. Conclusions A proposed new framework integrating the methodologies of control engineering and metabolic and hierarchical control analysis, improves the understanding of biological systems that are regulated both metabolically and by gene expression. In particular, the new approach enables one to address the issue whether the intracellular biochemical networks that have been and are being identified by genomics and systems biology, correspond to the ‘perfect’ regulatory structures designed by control engineering vis-à-vis optimal functions such as robustness. To the extent that they are not, the analyses suggest how they may become so and this in turn should facilitate synthetic biology and metabolic engineering. PMID:24261908

Protein- mediated enamel mineralization

PubMed Central

Moradian-Oldak, Janet

2012-01-01

Enamel is a hard nanocomposite bioceramic with significant resilience that protects the mammalian tooth from external physical and chemical damages. The remarkable mechanical properties of enamel are associated with its hierarchical structural organization and its thorough connection with underlying dentin. This dynamic mineralizing system offers scientists a wealth of information that allows the study of basic principals of organic matrix-mediated biomineralization and can potentially be utilized in the fields of material science and engineering for development and design of biomimetic materials. This chapter will provide a brief overview of enamel hierarchical structure and properties as well as the process and stages of amelogenesis. Particular emphasis is given to current knowledge of extracellular matrix protein and proteinases, and the structural chemistry of the matrix components and their putative functions. The chapter will conclude by discussing the potential of enamel for regrowth. PMID:22652761

The architecture of amyloid-like peptide fibrils revealed by X-ray scattering, diffraction and electron microscopy

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

Langkilde, Annette E., E-mail: annette.langkilde@sund.ku.dk; Morris, Kyle L.; Serpell, Louise C.

The aggregation process and the fibril state of an amyloidogenic peptide suggest monomer addition to be the prevailing mechanism of elongation and a model of the peptide packing in the fibrils has been obtained. Structural analysis of protein fibrillation is inherently challenging. Given the crucial role of fibrils in amyloid diseases, method advancement is urgently needed. A hybrid modelling approach is presented enabling detailed analysis of a highly ordered and hierarchically organized fibril of the GNNQQNY peptide fragment of a yeast prion protein. Data from small-angle X-ray solution scattering, fibre diffraction and electron microscopy are combined with existing high-resolution X-raymore » crystallographic structures to investigate the fibrillation process and the hierarchical fibril structure of the peptide fragment. The elongation of these fibrils proceeds without the accumulation of any detectable amount of intermediate oligomeric species, as is otherwise reported for, for example, glucagon, insulin and α-synuclein. Ribbons constituted of linearly arranged protofilaments are formed. An additional hierarchical layer is generated via the pairing of ribbons during fibril maturation. Based on the complementary data, a quasi-atomic resolution model of the protofilament peptide arrangement is suggested. The peptide structure appears in a β-sheet arrangement reminiscent of the β-zipper structures evident from high-resolution crystal structures, with specific differences in the relative peptide orientation. The complexity of protein fibrillation and structure emphasizes the need to use multiple complementary methods.« less

Comparing Chemistry to Outcome: The Development of a Chemical Distance Metric, Coupled with Clustering and Hierarchal Visualization Applied to Macromolecular Crystallography

PubMed Central

Bruno, Andrew E.; Ruby, Amanda M.; Luft, Joseph R.; Grant, Thomas D.; Seetharaman, Jayaraman; Montelione, Gaetano T.; Hunt, John F.; Snell, Edward H.

2014-01-01

Many bioscience fields employ high-throughput methods to screen multiple biochemical conditions. The analysis of these becomes tedious without a degree of automation. Crystallization, a rate limiting step in biological X-ray crystallography, is one of these fields. Screening of multiple potential crystallization conditions (cocktails) is the most effective method of probing a proteins phase diagram and guiding crystallization but the interpretation of results can be time-consuming. To aid this empirical approach a cocktail distance coefficient was developed to quantitatively compare macromolecule crystallization conditions and outcome. These coefficients were evaluated against an existing similarity metric developed for crystallization, the C6 metric, using both virtual crystallization screens and by comparison of two related 1,536-cocktail high-throughput crystallization screens. Hierarchical clustering was employed to visualize one of these screens and the crystallization results from an exopolyphosphatase-related protein from Bacteroides fragilis, (BfR192) overlaid on this clustering. This demonstrated a strong correlation between certain chemically related clusters and crystal lead conditions. While this analysis was not used to guide the initial crystallization optimization, it led to the re-evaluation of unexplained peaks in the electron density map of the protein and to the insertion and correct placement of sodium, potassium and phosphate atoms in the structure. With these in place, the resulting structure of the putative active site demonstrated features consistent with active sites of other phosphatases which are involved in binding the phosphoryl moieties of nucleotide triphosphates. The new distance coefficient, CDcoeff, appears to be robust in this application, and coupled with hierarchical clustering and the overlay of crystallization outcome, reveals information of biological relevance. While tested with a single example the potential applications related to crystallography appear promising and the distance coefficient, clustering, and hierarchal visualization of results undoubtedly have applications in wider fields. PMID:24971458

In Which Ways and to What Extent Do English and Shanghai Students Understand Linear Function?

ERIC Educational Resources Information Center

Wang, Yuqian; Barmby, Patrick; Bolden, David

2017-01-01

This study investigates how students in England and Shanghai understand linear function. Understanding is defined theoretically in terms of five hierarchical levels: Dependent Relationship; Connecting Representations; Property Noticing; Object Analysis; and Inventising. A pilot study instrument presented a set of problems to both cohorts, showing…

Perceptions of societal developmental hierarchies in Europe and beyond: A Bulgarian Perspective

PubMed Central

Melegh, Attila; Thornton, Arland; Philipov, Dimiter; Young-DeMarco, Linda

2012-01-01

We examine how ordinary citizens in Bulgaria view the developmental levels of European countries and certain states outside of Europe. Our research is motivated by the understanding that scholars and policy makers have for centuries used developmental hierarchies to characterize countries and that this perception of differential development has shaped interactions among different groups, countries and regions. We expect that views of such developmental hierarchies and models have great potential for influencing demographic and family behavior and political and cultural identities of ordinary people. Using data from a 2009 survey in Bulgaria we document that developmental hierarchies are widely perceived in Bulgaria, but are distributed differentially by age, education, and degree of urbanization. We also consider internal mechanisms underlying this hierarchical understanding of development and how hierarchical understandings may be related to national identities. PMID:23807821

CytoCluster: A Cytoscape Plugin for Cluster Analysis and Visualization of Biological Networks.

PubMed

Li, Min; Li, Dongyan; Tang, Yu; Wu, Fangxiang; Wang, Jianxin

2017-08-31

Nowadays, cluster analysis of biological networks has become one of the most important approaches to identifying functional modules as well as predicting protein complexes and network biomarkers. Furthermore, the visualization of clustering results is crucial to display the structure of biological networks. Here we present CytoCluster, a cytoscape plugin integrating six clustering algorithms, HC-PIN (Hierarchical Clustering algorithm in Protein Interaction Networks), OH-PIN (identifying Overlapping and Hierarchical modules in Protein Interaction Networks), IPCA (Identifying Protein Complex Algorithm), ClusterONE (Clustering with Overlapping Neighborhood Expansion), DCU (Detecting Complexes based on Uncertain graph model), IPC-MCE (Identifying Protein Complexes based on Maximal Complex Extension), and BinGO (the Biological networks Gene Ontology) function. Users can select different clustering algorithms according to their requirements. The main function of these six clustering algorithms is to detect protein complexes or functional modules. In addition, BinGO is used to determine which Gene Ontology (GO) categories are statistically overrepresented in a set of genes or a subgraph of a biological network. CytoCluster can be easily expanded, so that more clustering algorithms and functions can be added to this plugin. Since it was created in July 2013, CytoCluster has been downloaded more than 9700 times in the Cytoscape App store and has already been applied to the analysis of different biological networks. CytoCluster is available from http://apps.cytoscape.org/apps/cytocluster.

CytoCluster: A Cytoscape Plugin for Cluster Analysis and Visualization of Biological Networks

PubMed Central

Li, Min; Li, Dongyan; Tang, Yu; Wang, Jianxin

2017-01-01

Nowadays, cluster analysis of biological networks has become one of the most important approaches to identifying functional modules as well as predicting protein complexes and network biomarkers. Furthermore, the visualization of clustering results is crucial to display the structure of biological networks. Here we present CytoCluster, a cytoscape plugin integrating six clustering algorithms, HC-PIN (Hierarchical Clustering algorithm in Protein Interaction Networks), OH-PIN (identifying Overlapping and Hierarchical modules in Protein Interaction Networks), IPCA (Identifying Protein Complex Algorithm), ClusterONE (Clustering with Overlapping Neighborhood Expansion), DCU (Detecting Complexes based on Uncertain graph model), IPC-MCE (Identifying Protein Complexes based on Maximal Complex Extension), and BinGO (the Biological networks Gene Ontology) function. Users can select different clustering algorithms according to their requirements. The main function of these six clustering algorithms is to detect protein complexes or functional modules. In addition, BinGO is used to determine which Gene Ontology (GO) categories are statistically overrepresented in a set of genes or a subgraph of a biological network. CytoCluster can be easily expanded, so that more clustering algorithms and functions can be added to this plugin. Since it was created in July 2013, CytoCluster has been downloaded more than 9700 times in the Cytoscape App store and has already been applied to the analysis of different biological networks. CytoCluster is available from http://apps.cytoscape.org/apps/cytocluster. PMID:28858211

Actin and Endocytosis in Budding Yeast

PubMed Central

Goode, Bruce L.; Eskin, Julian A.; Wendland, Beverly

2015-01-01

Endocytosis, the process whereby the plasma membrane invaginates to form vesicles, is essential for bringing many substances into the cell and for membrane turnover. The mechanism driving clathrin-mediated endocytosis (CME) involves > 50 different protein components assembling at a single location on the plasma membrane in a temporally ordered and hierarchal pathway. These proteins perform precisely choreographed steps that promote receptor recognition and clustering, membrane remodeling, and force-generating actin-filament assembly and turnover to drive membrane invagination and vesicle scission. Many critical aspects of the CME mechanism are conserved from yeast to mammals and were first elucidated in yeast, demonstrating that it is a powerful system for studying endocytosis. In this review, we describe our current mechanistic understanding of each step in the process of yeast CME, and the essential roles played by actin polymerization at these sites, while providing a historical perspective of how the landscape has changed since the preceding version of the YeastBook was published 17 years ago (1997). Finally, we discuss the key unresolved issues and where future studies might be headed. PMID:25657349

Using PPI network autocorrelation in hierarchical multi-label classification trees for gene function prediction.

PubMed

Stojanova, Daniela; Ceci, Michelangelo; Malerba, Donato; Dzeroski, Saso

2013-09-26

Ontologies and catalogs of gene functions, such as the Gene Ontology (GO) and MIPS-FUN, assume that functional classes are organized hierarchically, that is, general functions include more specific ones. This has recently motivated the development of several machine learning algorithms for gene function prediction that leverages on this hierarchical organization where instances may belong to multiple classes. In addition, it is possible to exploit relationships among examples, since it is plausible that related genes tend to share functional annotations. Although these relationships have been identified and extensively studied in the area of protein-protein interaction (PPI) networks, they have not received much attention in hierarchical and multi-class gene function prediction. Relations between genes introduce autocorrelation in functional annotations and violate the assumption that instances are independently and identically distributed (i.i.d.), which underlines most machine learning algorithms. Although the explicit consideration of these relations brings additional complexity to the learning process, we expect substantial benefits in predictive accuracy of learned classifiers. This article demonstrates the benefits (in terms of predictive accuracy) of considering autocorrelation in multi-class gene function prediction. We develop a tree-based algorithm for considering network autocorrelation in the setting of Hierarchical Multi-label Classification (HMC). We empirically evaluate the proposed algorithm, called NHMC (Network Hierarchical Multi-label Classification), on 12 yeast datasets using each of the MIPS-FUN and GO annotation schemes and exploiting 2 different PPI networks. The results clearly show that taking autocorrelation into account improves the predictive performance of the learned models for predicting gene function. Our newly developed method for HMC takes into account network information in the learning phase: When used for gene function prediction in the context of PPI networks, the explicit consideration of network autocorrelation increases the predictive performance of the learned models. Overall, we found that this holds for different gene features/ descriptions, functional annotation schemes, and PPI networks: Best results are achieved when the PPI network is dense and contains a large proportion of function-relevant interactions.

Hierarchical structure of stock price fluctuations in financial markets

NASA Astrophysics Data System (ADS)

Gao, Ya-Chun; Cai, Shi-Min; Wang, Bing-Hong

2012-12-01

The financial market and turbulence have been broadly compared on account of the same quantitative methods and several common stylized facts they share. In this paper, the She-Leveque (SL) hierarchy, proposed to explain the anomalous scaling exponents deviating from Kolmogorov monofractal scaling of the velocity fluctuation in fluid turbulence, is applied to study and quantify the hierarchical structure of stock price fluctuations in financial markets. We therefore observed certain interesting results: (i) the hierarchical structure related to multifractal scaling generally presents in all the stock price fluctuations we investigated. (ii) The quantitatively statistical parameters that describe SL hierarchy are different between developed financial markets and emerging ones, distinctively. (iii) For the high-frequency stock price fluctuation, the hierarchical structure varies with different time periods. All these results provide a novel analogy in turbulence and financial market dynamics and an insight to deeply understand multifractality in financial markets.

Leading virtual teams: hierarchical leadership, structural supports, and shared team leadership.

PubMed

Hoch, Julia E; Kozlowski, Steve W J

2014-05-01

Using a field sample of 101 virtual teams, this research empirically evaluates the impact of traditional hierarchical leadership, structural supports, and shared team leadership on team performance. Building on Bell and Kozlowski's (2002) work, we expected structural supports and shared team leadership to be more, and hierarchical leadership to be less, strongly related to team performance when teams were more virtual in nature. As predicted, results from moderation analyses indicated that the extent to which teams were more virtual attenuated relations between hierarchical leadership and team performance but strengthened relations for structural supports and team performance. However, shared team leadership was significantly related to team performance regardless of the degree of virtuality. Results are discussed in terms of needed research extensions for understanding leadership processes in virtual teams and practical implications for leading virtual teams. (c) 2014 APA, all rights reserved.

Hierarchically-Driven Approach for Quantifying Fatigue Crack Initiation and Short Crack Growth Behavior in Aerospace Materials

DTIC Science & Technology

2016-08-31

crack initiation and SCG mechanisms (initiation and growth versus resistance). 2. Final summary Here, we present a hierarchical form of multiscale...prismatic faults in -Ti: A combined quantum mechanics /molecular mechanics study 2. Nano-indentation and slip transfer (critical in understanding crack...initiation) 3. An extended-finite element framework (XFEM) to study SCG mechanisms 4. Atomistic methods to develop a grain and twin boundaries database

Emotion Comprehension: The Impact of Nonverbal Intelligence

ERIC Educational Resources Information Center

Albanese, Ottavia; De Stasio, Simona; Di Chiacchio, Carlo; Fiorilli, Caterina; Pons, Francisco

2010-01-01

A substantial body of research has established that emotion understanding develops throughout early childhood and has identified three hierarchical developmental phases: external, mental, and reflexive. The authors analyzed nonverbal intelligence and its effect on children's improvement of emotion understanding and hypothesized that cognitive…

Global Mapping of Traditional Chinese Medicine into Bioactivity Space and Pathways Annotation Improves Mechanistic Understanding and Discovers Relationships between Therapeutic Action (Sub)classes

PubMed Central

Mohamad Zobir, Siti Zuraidah; Mohd Fauzi, Fazlin; Liggi, Sonia; Drakakis, Georgios; Fu, Xianjun; Fan, Tai-Ping; Bender, Andreas

2016-01-01

Traditional Chinese medicine (TCM) still needs more scientific rationale to be proven for it to be accepted further in the West. We are now in the position to propose computational hypotheses for the mode-of-actions (MOAs) of 45 TCM therapeutic action (sub)classes from in silico target prediction algorithms, whose target was later annotated with Kyoto Encyclopedia of Genes and Genomes pathway, and to discover the relationship between them by generating a hierarchical clustering. The results of 10,749 TCM compounds showed 183 enriched targets and 99 enriched pathways from Estimation Score ≤ 0 and ≥ 5% of compounds/targets in a (sub)class. The MOA of a (sub)class was established from supporting literature. Overall, the most frequent top three enriched targets/pathways were immune-related targets such as tyrosine-protein phosphatase nonreceptor type 2 (PTPN2) and digestive system such as mineral absorption. We found two major protein families, G-protein coupled receptor (GPCR), and protein kinase family contributed to the diversity of the bioactivity space, while digestive system was consistently annotated pathway motif, which agreed with the important treatment principle of TCM, “the foundation of acquired constitution” that includes spleen and stomach. In short, the TCM (sub)classes, in many cases share similar targets/pathways despite having different indications. PMID:26989424

Limitations of a morphological criterion of adaptive inference in the fossil record.

PubMed

Ravosa, Matthew J; Menegaz, Rachel A; Scott, Jeremiah E; Daegling, David J; McAbee, Kevin R

2016-11-01

Experimental analyses directly inform how an anatomical feature or complex functions during an organism's lifetime, which serves to increase the efficacy of comparative studies of living and fossil taxa. In the mammalian skull, food material properties and feeding behaviour have a pronounced influence on the development of the masticatory apparatus. Diet-related variation in loading magnitude and frequency induce a cascade of changes at the gross, tissue, cellular, protein and genetic levels, with such modelling and remodelling maintaining the integrity of oral structures vis-à-vis routine masticatory stresses. Ongoing integrative research using rabbit and rat models of long-term masticatory plasticity offers unique insight into the limitations of functional interpretations of fossilised remains. Given the general restriction of the palaeontological record to bony elements, we argue that failure to account for the disparity in the hierarchical network of responses of hard versus soft tissues may overestimate the magnitude of the adaptive divergence that is inferred from phenotypic differences. Second, we note that the developmental onset and duration of a loading stimulus associated with a given feeding behaviour can impart large effects on patterns of intraspecific variation that can mirror differences observed among taxa. Indeed, plasticity data are relevant to understanding evolutionary transformations because rabbits raised on different diets exhibit levels of morphological disparity comparable to those found between closely related primate species that vary in diet. Lastly, pronounced variation in joint form, and even joint function, can also characterise adult conspecifics that differ solely in age. In sum, our analyses emphasise the importance of a multi-site and hierarchical approach to understanding determinants of morphological variation, one which incorporates critical data on performance. © 2015 Cambridge Philosophical Society.

The study of dynamic force acted on water strider leg departing from water surface

NASA Astrophysics Data System (ADS)

Sun, Peiyuan; Zhao, Meirong; Jiang, Jile; Zheng, Yelong

2018-01-01

Water-walking insects such as water striders can skate on the water surface easily with the help of the hierarchical structure on legs. Numerous theoretical and experimental studies show that the hierarchical structure would help water strider in quasi-static case such as load-bearing capacity. However, the advantage of the hierarchical structure in the dynamic stage has not been reported yet. In this paper, the function of super hydrophobicity and the hierarchical structure was investigated by measuring the adhesion force of legs departing from the water surface at different lifting speed by a dynamic force sensor. The results show that the adhesion force decreased with the increase of lifting speed from 0.02 m/s to 0.4 m/s, whose mechanic is investigated by Energy analysis. In addition, it can be found that the needle shape setae on water strider leg can help them depart from water surface easily. Thus, it can serve as a starting point to understand how the hierarchical structure on the legs help water-walking insects to jump upward rapidly to avoid preying by other insects.

Selective Template Wetting Routes to Hierarchical Polymer Films: Polymer Nanotubes from Phase-Separated Films via Solvent Annealing.

PubMed

Ko, Hao-Wen; Cheng, Ming-Hsiang; Chi, Mu-Huan; Chang, Chun-Wei; Chen, Jiun-Tai

2016-03-01

We demonstrate a novel wetting method to prepare hierarchical polymer films with polymer nanotubes on selective regions. This strategy is based on the selective wetting abilities of polymer chains, annealed in different solvent vapors, into the nanopores of porous templates. Phase-separated films of polystyrene (PS) and poly(methyl methacrylate) (PMMA), two commonly used polymers, are prepared as a model system. After anodic aluminum oxide (AAO) templates are placed on the films, the samples are annealed in vapors of acetic acid, in which the PMMA chains are swollen and wet the nanopores of the AAO templates selectively. As a result, hierarchical polymer films containing PMMA nanotubes can be obtained after the AAO templates are removed. The distribution of the PMMA nanotubes of the hierarchical polymer films can also be controlled by changing the compositions of the polymer blends. This work not only presents a novel method to fabricate hierarchical polymer films with polymer nanotubes on selective regions, but also gives a deeper understanding in the selective wetting ability of polymer chains in solvent vapors.

Moisture condensation behavior of hierarchically carbon nanotube-grafted carbon nanofibers.

PubMed

Park, Kyu-Min; Lee, Byoung-Sun; Youk, Ji Ho; Lee, Jinyong; Yu, Woong-Reol

2013-11-13

Hierarchical micro/nanosurfaces with nanoscale roughness on microscale uneven substrates have been the subject of much recent research interest because of phenomena such as superhydrophobicity. However, an understanding of the effect of the difference in the scale of the hierarchical entities, i.e., nanoscale roughness on microscale uneven substrates as opposed to nanoscale roughness on (a larger) nanoscale uneven surface, is still lacking. In this study, we investigated the effect of the difference in scale between the nano- and microscale features. We fabricated carbon nanotube-grafted carbon nanofibers (CNFs) by dispersing a catalyst precursor in poly (acrylonitrile) (PAN) solution, electrospinning the PAN/catalyst precursor solution, carbonization of electrospun PAN nanofibers, and direct growth of carbon nanotubes (CNTs) on the CNFs. We investigated the relationships between the catalyst concentrations, the size of catalyst nanoparticles on CNFs, and the sizes of CNFs and CNTs. Interestingly, the hydrophobic behavior of micro/nano and nano/nano hierarchical surfaces with water droplets was similar; however a significant difference in the water condensation behavior was observed. Water condensed into smaller droplets on the nano/nano hierarchical surface, causing it to dry much faster.

A hierarchical Bayesian model for understanding the spatiotemporal dynamics of the intestinal epithelium

PubMed Central

Parker, Aimée; Pin, Carmen; Carding, Simon R.; Watson, Alastair J. M.; Byrne, Helen M.

2017-01-01

Our work addresses two key challenges, one biological and one methodological. First, we aim to understand how proliferation and cell migration rates in the intestinal epithelium are related under healthy, damaged (Ara-C treated) and recovering conditions, and how these relations can be used to identify mechanisms of repair and regeneration. We analyse new data, presented in more detail in a companion paper, in which BrdU/IdU cell-labelling experiments were performed under these respective conditions. Second, in considering how to more rigorously process these data and interpret them using mathematical models, we use a probabilistic, hierarchical approach. This provides a best-practice approach for systematically modelling and understanding the uncertainties that can otherwise undermine the generation of reliable conclusions—uncertainties in experimental measurement and treatment, difficult-to-compare mathematical models of underlying mechanisms, and unknown or unobserved parameters. Both spatially discrete and continuous mechanistic models are considered and related via hierarchical conditional probability assumptions. We perform model checks on both in-sample and out-of-sample datasets and use them to show how to test possible model improvements and assess the robustness of our conclusions. We conclude, for the present set of experiments, that a primarily proliferation-driven model suffices to predict labelled cell dynamics over most time-scales. PMID:28753601

A hierarchical Bayesian model for understanding the spatiotemporal dynamics of the intestinal epithelium.

PubMed

Maclaren, Oliver J; Parker, Aimée; Pin, Carmen; Carding, Simon R; Watson, Alastair J M; Fletcher, Alexander G; Byrne, Helen M; Maini, Philip K

2017-07-01

Our work addresses two key challenges, one biological and one methodological. First, we aim to understand how proliferation and cell migration rates in the intestinal epithelium are related under healthy, damaged (Ara-C treated) and recovering conditions, and how these relations can be used to identify mechanisms of repair and regeneration. We analyse new data, presented in more detail in a companion paper, in which BrdU/IdU cell-labelling experiments were performed under these respective conditions. Second, in considering how to more rigorously process these data and interpret them using mathematical models, we use a probabilistic, hierarchical approach. This provides a best-practice approach for systematically modelling and understanding the uncertainties that can otherwise undermine the generation of reliable conclusions-uncertainties in experimental measurement and treatment, difficult-to-compare mathematical models of underlying mechanisms, and unknown or unobserved parameters. Both spatially discrete and continuous mechanistic models are considered and related via hierarchical conditional probability assumptions. We perform model checks on both in-sample and out-of-sample datasets and use them to show how to test possible model improvements and assess the robustness of our conclusions. We conclude, for the present set of experiments, that a primarily proliferation-driven model suffices to predict labelled cell dynamics over most time-scales.

Genetically encoded lipid-polypeptide hybrid biomaterials that exhibit temperature-triggered hierarchical self-assembly

NASA Astrophysics Data System (ADS)

Mozhdehi, Davoud; Luginbuhl, Kelli M.; Simon, Joseph R.; Dzuricky, Michael; Berger, Rüdiger; Varol, H. Samet; Huang, Fred C.; Buehne, Kristen L.; Mayne, Nicholas R.; Weitzhandler, Isaac; Bonn, Mischa; Parekh, Sapun H.; Chilkoti, Ashutosh

2018-05-01

Post-translational modification of proteins is a strategy widely used in biological systems. It expands the diversity of the proteome and allows for tailoring of both the function and localization of proteins within cells as well as the material properties of structural proteins and matrices. Despite their ubiquity in biology, with a few exceptions, the potential of post-translational modifications in biomaterials synthesis has remained largely untapped. As a proof of concept to demonstrate the feasibility of creating a genetically encoded biohybrid material through post-translational modification, we report here the generation of a family of three stimulus-responsive hybrid materials—fatty-acid-modified elastin-like polypeptides—using a one-pot recombinant expression and post-translational lipidation methodology. These hybrid biomaterials contain an amphiphilic domain, composed of a β-sheet-forming peptide that is post-translationally functionalized with a C14 alkyl chain, fused to a thermally responsive elastin-like polypeptide. They exhibit temperature-triggered hierarchical self-assembly across multiple length scales with varied structure and material properties that can be controlled at the sequence level.

bcl::Cluster : A method for clustering biological molecules coupled with visualization in the Pymol Molecular Graphics System.

PubMed

Alexander, Nathan; Woetzel, Nils; Meiler, Jens

2011-02-01

Clustering algorithms are used as data analysis tools in a wide variety of applications in Biology. Clustering has become especially important in protein structure prediction and virtual high throughput screening methods. In protein structure prediction, clustering is used to structure the conformational space of thousands of protein models. In virtual high throughput screening, databases with millions of drug-like molecules are organized by structural similarity, e.g. common scaffolds. The tree-like dendrogram structure obtained from hierarchical clustering can provide a qualitative overview of the results, which is important for focusing detailed analysis. However, in practice it is difficult to relate specific components of the dendrogram directly back to the objects of which it is comprised and to display all desired information within the two dimensions of the dendrogram. The current work presents a hierarchical agglomerative clustering method termed bcl::Cluster. bcl::Cluster utilizes the Pymol Molecular Graphics System to graphically depict dendrograms in three dimensions. This allows simultaneous display of relevant biological molecules as well as additional information about the clusters and the members comprising them.

Circadian systems biology in Metazoa.

PubMed

Lin, Li-Ling; Huang, Hsuan-Cheng; Juan, Hsueh-Fen

2015-11-01

Systems biology, which can be defined as integrative biology, comprises multistage processes that can be used to understand components of complex biological systems of living organisms and provides hierarchical information to decoding life. Using systems biology approaches such as genomics, transcriptomics and proteomics, it is now possible to delineate more complicated interactions between circadian control systems and diseases. The circadian rhythm is a multiscale phenomenon existing within the body that influences numerous physiological activities such as changes in gene expression, protein turnover, metabolism and human behavior. In this review, we describe the relationships between the circadian control system and its related genes or proteins, and circadian rhythm disorders in systems biology studies. To maintain and modulate circadian oscillation, cells possess elaborative feedback loops composed of circadian core proteins that regulate the expression of other genes through their transcriptional activities. The disruption of these rhythms has been reported to be associated with diseases such as arrhythmia, obesity, insulin resistance, carcinogenesis and disruptions in natural oscillations in the control of cell growth. This review demonstrates that lifestyle is considered as a fundamental factor that modifies circadian rhythm, and the development of dysfunctions and diseases could be regulated by an underlying expression network with multiple circadian-associated signals. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Comprehensive analysis of orthologous protein domains using the HOPS database.

PubMed

Storm, Christian E V; Sonnhammer, Erik L L

2003-10-01

One of the most reliable methods for protein function annotation is to transfer experimentally known functions from orthologous proteins in other organisms. Most methods for identifying orthologs operate on a subset of organisms with a completely sequenced genome, and treat proteins as single-domain units. However, it is well known that proteins are often made up of several independent domains, and there is a wealth of protein sequences from genomes that are not completely sequenced. A comprehensive set of protein domain families is found in the Pfam database. We wanted to apply orthology detection to Pfam families, but first some issues needed to be addressed. First, orthology detection becomes impractical and unreliable when too many species are included. Second, shorter domains contain less information. It is therefore important to assess the quality of the orthology assignment and avoid very short domains altogether. We present a database of orthologous protein domains in Pfam called HOPS: Hierarchical grouping of Orthologous and Paralogous Sequences. Orthology is inferred in a hierarchic system of phylogenetic subgroups using ortholog bootstrapping. To avoid the frequent errors stemming from horizontally transferred genes in bacteria, the analysis is presently limited to eukaryotic genes. The results are accessible in the graphical browser NIFAS, a Java tool originally developed for analyzing phylogenetic relations within Pfam families. The method was tested on a set of curated orthologs with experimentally verified function. In comparison to tree reconciliation with a complete species tree, our approach finds significantly more orthologs in the test set. Examples for investigating gene fusions and domain recombination using HOPS are given.

Facilitation of Ferroelectric Switching via Mechanical Manipulation of Hierarchical Nanoscale Domain Structures.

PubMed

Chen, Zibin; Hong, Liang; Wang, Feifei; Ringer, Simon P; Chen, Long-Qing; Luo, Haosu; Liao, Xiaozhou

2017-01-06

Heterogeneous ferroelastic transition that produces hierarchical 90° tetragonal nanodomains via mechanical loading and its effect on facilitating ferroelectric domain switching in relaxor-based ferroelectrics were explored. Combining in situ electron microscopy characterization and phase-field modeling, we reveal the nature of the transition process and discover that the transition lowers by 40% the electrical loading threshold needed for ferroelectric domain switching. Our results advance the fundamental understanding of ferroelectric domain switching behavior.

High Temperature Deformation Mechanism in Hierarchical and Single Precipitate Strengthened Ferritic Alloys by In Situ Neutron Diffraction Studies.

PubMed

Song, Gian; Sun, Zhiqian; Li, Lin; Clausen, Bjørn; Zhang, Shu Yan; Gao, Yanfei; Liaw, Peter K

2017-04-07

The ferritic Fe-Cr-Ni-Al-Ti alloys strengthened by hierarchical-Ni 2 TiAl/NiAl or single-Ni 2 TiAl precipitates have been developed and received great attentions due to their superior creep resistance, as compared to conventional ferritic steels. Although the significant improvement of the creep resistance is achieved in the hierarchical-precipitate-strengthened ferritic alloy, the in-depth understanding of its high-temperature deformation mechanisms is essential to further optimize the microstructure and mechanical properties, and advance the development of the creep resistant materials. In the present study, in-situ neutron diffraction has been used to investigate the evolution of elastic strain of constitutive phases and their interactions, such as load-transfer/load-relaxation behavior between the precipitate and matrix, during tensile deformation and stress relaxation at 973 K, which provide the key features in understanding the governing deformation mechanisms. Crystal-plasticity finite-element simulations were employed to qualitatively compare the experimental evolution of the elastic strain during tensile deformation at 973 K. It was found that the coherent elastic strain field in the matrix, created by the lattice misfit between the matrix and precipitate phases for the hierarchical-precipitate-strengthened ferritic alloy, is effective in reducing the diffusional relaxation along the interface between the precipitate and matrix phases, which leads to the strong load-transfer capability from the matrix to precipitate.

Leading processes of patient care and treatment in hierarchical healthcare organizations in Sweden--process managers' experiences.

PubMed

Nilsson, Kerstin; Sandoff, Mette

2015-01-01

The purpose of this study is to gain better understanding of the roles and functions of process managers by describing Swedish process managers' experiences of leading processes involving patient care and treatment when working in a hierarchical health-care organization. This study is based on an explorative design. The data were gathered from interviews with 12 process managers at three Swedish hospitals. These data underwent qualitative and interpretative analysis with a modified editing style. The process managers' experiences of leading processes in a hierarchical health-care organization are described under three themes: having or not having a mandate, exposure to conflict situations and leading process development. The results indicate a need for clarity regarding process manager's responsibility and work content, which need to be communicated to all managers and staff involved in the patient care and treatment process, irrespective of department. There also needs to be an emphasis on realistic expectations and orientation of the goals that are an intrinsic part of the task of being a process manager. Generalizations from the results of the qualitative interview studies are limited, but a deeper understanding of the phenomenon was reached, which, in turn, can be transferred to similar settings. This study contributes qualitative descriptions of leading care and treatment processes in a functional, hierarchical health-care organization from process managers' experiences, a subject that has not been investigated earlier.

Definition and structure of body-relatedness from the perspective of patients with severe somatoform disorder and their therapists.

PubMed

Kalisvaart, Hanneke; van Broeckhuysen, Saskia; Bühring, Martina; Kool, Marianne B; van Dulmen, Sandra; Geenen, Rinie

2012-01-01

How a patient is connected with one's body is core to rehabilitation of somatoform disorder but a common model to describe body-relatedness is missing. The aim of our study was to investigate the components and hierarchical structure of body-relatedness as perceived by patients with severe somatoform disorder and their therapists. Interviews with patients and therapists yielded statements about components of body-relatedness. Patients and therapists individually sorted these statements according to similarity. Hierarchical cluster analysis was applied to these sortings. Analysis of variance was used to compare the perceived importance of the statements between patients and therapists. The hierarchical structure included 71 characteristics of body-relatedness. It consisted of three levels with eight clusters at the lowest level: 1) understanding, 2) acceptance, 3) adjustment, 4) respect for the body, 5) regulation, 6) confidence, 7) self-esteem, and 8) autonomy. The cluster 'understanding' was considered most important by patients and therapists. Patients valued 'regulating the body' more than therapists. According to patients with somatoform disorders and their therapists, body-relatedness includes awareness of the body and self by understanding, accepting and adjusting to bodily signals, by respecting and regulating the body, by confiding and esteeming oneself and by being autonomous. This definition and structure of body-relatedness may help professionals to improve interdisciplinary communication, assessment, and treatment, and it may help patients to better understand their symptoms and treatment. (German language abstract, Abstract S1; Spanish language abstract, Abstract S2).

Constructive Epistemic Modeling: A Hierarchical Bayesian Model Averaging Method

NASA Astrophysics Data System (ADS)

Tsai, F. T. C.; Elshall, A. S.

2014-12-01

Constructive epistemic modeling is the idea that our understanding of a natural system through a scientific model is a mental construct that continually develops through learning about and from the model. Using the hierarchical Bayesian model averaging (HBMA) method [1], this study shows that segregating different uncertain model components through a BMA tree of posterior model probabilities, model prediction, within-model variance, between-model variance and total model variance serves as a learning tool [2]. First, the BMA tree of posterior model probabilities permits the comparative evaluation of the candidate propositions of each uncertain model component. Second, systemic model dissection is imperative for understanding the individual contribution of each uncertain model component to the model prediction and variance. Third, the hierarchical representation of the between-model variance facilitates the prioritization of the contribution of each uncertain model component to the overall model uncertainty. We illustrate these concepts using the groundwater modeling of a siliciclastic aquifer-fault system. The sources of uncertainty considered are from geological architecture, formation dip, boundary conditions and model parameters. The study shows that the HBMA analysis helps in advancing knowledge about the model rather than forcing the model to fit a particularly understanding or merely averaging several candidate models. [1] Tsai, F. T.-C., and A. S. Elshall (2013), Hierarchical Bayesian model averaging for hydrostratigraphic modeling: Uncertainty segregation and comparative evaluation. Water Resources Research, 49, 5520-5536, doi:10.1002/wrcr.20428. [2] Elshall, A.S., and F. T.-C. Tsai (2014). Constructive epistemic modeling of groundwater flow with geological architecture and boundary condition uncertainty under Bayesian paradigm, Journal of Hydrology, 517, 105-119, doi: 10.1016/j.jhydrol.2014.05.027.

Principles Supporting the Perceptional Teaching of Physics: A ``Practical Teaching Philosophy''

NASA Astrophysics Data System (ADS)

Kurki-Suonio, Kaarle

2011-03-01

This article sketches a framework of ideas developed in the context of decades of physics teacher-education that was entitled the "perceptional approach". Individual learning and the scientific enterprise are interpreted as different manifestations of the same process aimed at understanding the natural and social worlds. The process is understood to possess the basic nature of perception, where empirical meanings are first born and then conceptualised. The accumulation of perceived gestalts in the "structure of the mind" leads to structural perception and the generation of conceptual hierarchies, which form a general principle for the expansion of our understanding. The process undergoes hierarchical development from early sensory perception to individual learning and finally to science. The process is discussed in terms of a three-process dynamic. Scientific and technological processes are driven by the interaction of the mind and nature. They are embedded in the social process due to the interaction of individual minds. These sub-processes are defined by their aims: The scientific process affects the mind and aims at understanding; the technological process affects nature and aims at human well-being; and the social process aims at mutual agreement and cooperation. In hierarchical development the interaction of nature and the mind gets structured into a "methodical cycle" by procedures involving conscious activities. Its intuitive nature is preserved due to subordination of the procedures to empirical meanings. In physics, two dimensions of hierarchical development are distinguished: Unification development gives rise to a generalisation hierarchy of concepts; Quantification development transfers the empirical meanings to quantities, laws and theories representing successive hierarchical levels of quantitative concepts. Consequences for physics teaching are discussed in principle, and in the light of examples and experiences from physics teacher education.

Quantitative comparison of alternative methods for coarse-graining biological networks

PubMed Central

Bowman, Gregory R.; Meng, Luming; Huang, Xuhui

2013-01-01

Markov models and master equations are a powerful means of modeling dynamic processes like protein conformational changes. However, these models are often difficult to understand because of the enormous number of components and connections between them. Therefore, a variety of methods have been developed to facilitate understanding by coarse-graining these complex models. Here, we employ Bayesian model comparison to determine which of these coarse-graining methods provides the models that are most faithful to the original set of states. We find that the Bayesian agglomerative clustering engine and the hierarchical Nyström expansion graph (HNEG) typically provide the best performance. Surprisingly, the original Perron cluster cluster analysis (PCCA) method often provides the next best results, outperforming the newer PCCA+ method and the most probable paths algorithm. We also show that the differences between the models are qualitatively significant, rather than being minor shifts in the boundaries between states. The performance of the methods correlates well with the entropy of the resulting coarse-grainings, suggesting that finding states with more similar populations (i.e., avoiding low population states that may just be noise) gives better results. PMID:24089717

Emulsion-Assisted Polymerization-Induced Hierarchical Self-Assembly of Giant Sea Urchin-like Aggregates in a Large Scale.

PubMed

Xu, Qingsong; Huang, Tong; Li, Shanlong; Li, Ke; Li, Chuanlong; Liu, Yannan; Wang, Yuling; Yu, Chunyang; Zhou, Yongfeng

2018-05-09

Hierarchical solution self-assembly has nowadays become an important biomimetic method to prepare highly complex and multifunctional supramolecular structures. However, despites the great progress, it is still highly challenging to prepare hierarchical self-assemblies in a large scale since the self-assembly processes are generally performed at high dilution. Herein, we report an emulsion-assisted polymerization-induced self-assembly (EAPISA) method with the advantages of in-situ self-assembly process, scalable preparation and facile functionalization to prepare hierarchical multiscale sea urchin-like aggregates (SUAs). It also extends horizons of PISA in monomers and in polymerization method. The obtained SUAs from amphiphilic alternating copolymers represent a novel self-assembled structure with micron-sized rattan ball-like capsule (RBC) acting as the hollow core body and radiating nanotubes tens of micrometers in length as the hollow spines. They can effectively capture model proteins at an ultra-low concentration (≈10 nM) after functionalized with amino groups through click copolymerization. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

On the application of multilevel modeling in environmental and ecological studies

USGS Publications Warehouse

Qian, Song S.; Cuffney, Thomas F.; Alameddine, Ibrahim; McMahon, Gerard; Reckhow, Kenneth H.

2010-01-01

This paper illustrates the advantages of a multilevel/hierarchical approach for predictive modeling, including flexibility of model formulation, explicitly accounting for hierarchical structure in the data, and the ability to predict the outcome of new cases. As a generalization of the classical approach, the multilevel modeling approach explicitly models the hierarchical structure in the data by considering both the within- and between-group variances leading to a partial pooling of data across all levels in the hierarchy. The modeling framework provides means for incorporating variables at different spatiotemporal scales. The examples used in this paper illustrate the iterative process of model fitting and evaluation, a process that can lead to improved understanding of the system being studied.

Large-Scale Proteome Comparative Analysis of Developing Rhizomes of the Ancient Vascular Plant Equisetum Hyemale

PubMed Central

Balbuena, Tiago Santana; He, Ruifeng; Salvato, Fernanda; Gang, David R.; Thelen, Jay J.

2012-01-01

Horsetail (Equisetum hyemale) is a widespread vascular plant species, whose reproduction is mainly dependent on the growth and development of the rhizomes. Due to its key evolutionary position, the identification of factors that could be involved in the existence of the rhizomatous trait may contribute to a better understanding of the role of this underground organ for the successful propagation of this and other plant species. In the present work, we characterized the proteome of E. hyemale rhizomes using a GeLC-MS spectral-counting proteomics strategy. A total of 1,911 and 1,860 non-redundant proteins were identified in the rhizomes apical tip and elongation zone, respectively. Rhizome-characteristic proteins were determined by comparisons of the developing rhizome tissues to developing roots. A total of 87 proteins were found to be up-regulated in both horsetail rhizome tissues in relation to developing roots. Hierarchical clustering indicated a vast dynamic range in the regulation of the 87 characteristic proteins and revealed, based on the regulation profile, the existence of nine major protein groups. Gene ontology analyses suggested an over-representation of the terms involved in macromolecular and protein biosynthetic processes, gene expression, and nucleotide and protein binding functions. Spatial difference analysis between the rhizome apical tip and the elongation zone revealed that only eight proteins were up-regulated in the apical tip including RNA-binding proteins and an acyl carrier protein, as well as a KH domain protein and a T-complex subunit; while only seven proteins were up-regulated in the elongation zone including phosphomannomutase, galactomannan galactosyltransferase, endoglucanase 10 and 25, and mannose-1-phosphate guanyltransferase subunits alpha and beta. This is the first large-scale characterization of the proteome of a plant rhizome. Implications of the findings were discussed in relation to other underground organs and related species. PMID:22740841

Temporal impact of the vascular wilt pathogen Verticillium dahliae on tomato root proteome.

PubMed

Witzel, Katja; Buhtz, Anja; Grosch, Rita

2017-10-03

The soil-borne fungus Verticillium dahliae is the causal agent of wilting disease and affects a wide range of plant species worldwide. Here, we report on the time-resolved analysis of the tomato root proteome in response to fungal colonization. Tomato (Solanum lycopersicum cv. Hildares) was inoculated with V. dahliae at the two-leaf stage and roots were harvested at 7, 14 and 21 days post inoculation (dpi). In order to identify proteins related to the fungal spread at the different time points, a subsequent proteome analysis by two-dimensional differential gel electrophoresis (2D-DIGE) was conducted on samples from three independent experiments. Hierarchical clustering and k-means clustering of identified proteins distinguished early and late responses to fungal colonization. The results underline that plant defense and adaptation responses are timely coordinated. Proteins involved in oxidative stress were down-regulated at 7 dpi but induced 21 dpi indicating versatile reactive oxygen species signaling interacting with salicylic acid defence signaling at that stage of infection. Drought-stress proteins were induced at 21 dpi, reflecting the beginning of wilting symptoms. Notably, two proteins involved in energy-generating pathways were induced throughout all sampling dates and may reflect the increase in metabolic activity to maintain root growth and, concurrently, activate defense responses. Mounting of defense responses requires a substantial flux of carbon and nitrogen from primary to secondary metabolites. In-depth understanding of these key metabolic pathways required for growth and defense responses, especially at proteome level, will allow the development of breeding strategies for crops where Verticillium tolerance is absent. Our data show early and late responses of tomato root proteins towards pathogen infection and identify primary metabolism enzymes affected by V. dahliae. Those proteins represent candidates for plant improvement. Copyright © 2017 Elsevier B.V. All rights reserved.

Hierarchical multistage MCMC follow-up of continuous gravitational wave candidates

NASA Astrophysics Data System (ADS)

Ashton, G.; Prix, R.

2018-05-01

Leveraging Markov chain Monte Carlo optimization of the F statistic, we introduce a method for the hierarchical follow-up of continuous gravitational wave candidates identified by wide-parameter space semicoherent searches. We demonstrate parameter estimation for continuous wave sources and develop a framework and tools to understand and control the effective size of the parameter space, critical to the success of the method. Monte Carlo tests of simulated signals in noise demonstrate that this method is close to the theoretical optimal performance.

A Framework for Teaching Social and Environmental Sustainability to Undergraduate Business Majors

ERIC Educational Resources Information Center

Brumagim, Alan L.; Cann, Cynthia W.

2012-01-01

The authors outline an undergraduate exercise to help students more fully understand the environmental and social justice aspects of business sustainability activities. A simple hierarchical framework, based on Maslow's (1943) work, was utilized to help the students understand, analyze, and judge the vast amount of corporate sustainability…

Automated analysis and reannotation of subcellular locations in confocal images from the Human Protein Atlas.

PubMed

Li, Jieyue; Newberg, Justin Y; Uhlén, Mathias; Lundberg, Emma; Murphy, Robert F

2012-01-01

The Human Protein Atlas contains immunofluorescence images showing subcellular locations for thousands of proteins. These are currently annotated by visual inspection. In this paper, we describe automated approaches to analyze the images and their use to improve annotation. We began by training classifiers to recognize the annotated patterns. By ranking proteins according to the confidence of the classifier, we generated a list of proteins that were strong candidates for reexamination. In parallel, we applied hierarchical clustering to group proteins and identified proteins whose annotations were inconsistent with the remainder of the proteins in their cluster. These proteins were reexamined by the original annotators, and a significant fraction had their annotations changed. The results demonstrate that automated approaches can provide an important complement to visual annotation.

The Analysis of Image Segmentation Hierarchies with a Graph-based Knowledge Discovery System

NASA Technical Reports Server (NTRS)

Tilton, James C.; Cooke, diane J.; Ketkar, Nikhil; Aksoy, Selim

2008-01-01

Currently available pixel-based analysis techniques do not effectively extract the information content from the increasingly available high spatial resolution remotely sensed imagery data. A general consensus is that object-based image analysis (OBIA) is required to effectively analyze this type of data. OBIA is usually a two-stage process; image segmentation followed by an analysis of the segmented objects. We are exploring an approach to OBIA in which hierarchical image segmentations provided by the Recursive Hierarchical Segmentation (RHSEG) software developed at NASA GSFC are analyzed by the Subdue graph-based knowledge discovery system developed by a team at Washington State University. In this paper we discuss out initial approach to representing the RHSEG-produced hierarchical image segmentations in a graphical form understandable by Subdue, and provide results on real and simulated data. We also discuss planned improvements designed to more effectively and completely convey the hierarchical segmentation information to Subdue and to improve processing efficiency.

A neural model of hierarchical reinforcement learning.

PubMed

Rasmussen, Daniel; Voelker, Aaron; Eliasmith, Chris

2017-01-01

We develop a novel, biologically detailed neural model of reinforcement learning (RL) processes in the brain. This model incorporates a broad range of biological features that pose challenges to neural RL, such as temporally extended action sequences, continuous environments involving unknown time delays, and noisy/imprecise computations. Most significantly, we expand the model into the realm of hierarchical reinforcement learning (HRL), which divides the RL process into a hierarchy of actions at different levels of abstraction. Here we implement all the major components of HRL in a neural model that captures a variety of known anatomical and physiological properties of the brain. We demonstrate the performance of the model in a range of different environments, in order to emphasize the aim of understanding the brain's general reinforcement learning ability. These results show that the model compares well to previous modelling work and demonstrates improved performance as a result of its hierarchical ability. We also show that the model's behaviour is consistent with available data on human hierarchical RL, and generate several novel predictions.

Multi-scale, Hierarchically Nested Young Stellar Structures in LEGUS Galaxies

NASA Astrophysics Data System (ADS)

Thilker, David A.; LEGUS Team

2017-01-01

The study of star formation in galaxies has predominantly been limited to either young stellar clusters and HII regions, or much larger kpc-scale morphological features such as spiral arms. The HST Legacy ExtraGalactic UV Survey (LEGUS) provides a rare opportunity to link these scales in a diverse sample of nearby galaxies and obtain a more comprehensive understanding of their co-evolution for comparison against model predictions. We have utilized LEGUS stellar photometry to identify young, resolved stellar populations belonging to several age bins and then defined nested hierarchical structures as traced by these subsamples of stars. Analagous hierarchical structures were also defined using LEGUS catalogs of unresolved young stellar clusters. We will present our emerging results concerning the physical properties (e.g. area, star counts, stellar mass, star formation rate, ISM characteristics), occupancy statistics (e.g. clusters per substructure versus age and scale, parent/child demographics) and relation to overall galaxy morphology/mass for these building blocks of hierarchical star-forming structure.

Guiding lead optimization with GPCR structure modeling and molecular dynamics.

PubMed

Heifetz, Alexander; James, Tim; Morao, Inaki; Bodkin, Michael J; Biggin, Philip C

2016-10-01

G-protein coupled receptor (GPCR) modeling approaches are widely used in the hit-to-lead and lead optimization stages of drug discovery. Modern protocols that involve molecular dynamics simulation can address key issues such as the free energy of binding (affinity), ligand-induced GPCR flexibility, ligand binding kinetics, conserved water positions and their role in ligand binding and the effects of mutations. The goals of these calculations are to predict the structures of the complexes between existing ligands and their receptors, to understand the key interactions and to utilize these insights in the design of new molecules with improved binding, selectivity or other pharmacological properties. In this review we present a brief survey of various computational approaches illustrated through a hierarchical GPCR modeling protocol and its prospective application in three industrial drug discovery projects. Copyright © 2016 Elsevier Ltd. All rights reserved.

The coherence lifetime-borrowing effect in vibronically coupled molecular aggregates under non-perturbative system-environment interactions.

NASA Astrophysics Data System (ADS)

Yeh, Shu-Hao; Engel, Gregory S.; Kais, Sabre

Recently it has been suggested that the long-lived coherences in some photosynthetic pigment-protein systems, such as the Fenna-Matthews-Olson complex, could be attributed to the mixing of the pigments' electronic and vibrational degrees of freedom. In order to verify whether this is the case and to understand its underlying mechanism, a theoretical model capable of including both the electronic excitations and intramolecular vibrational modes of the pigments is necessary. Our model simultaneously considers the electronic and vibrational degrees of freedom, treating the system-environment interactions non-perturbatively by implementing the hierarchical equations of motion approach. Here we report the simulated two-dimensional electronic spectra of vibronically coupled molecular dimers to demonstrate how the electronic coherence lifetimes can be extended by borrowing the lifetime from the vibrational coherences. Funded by Qatar National Research Fund and Qatar Environment and Energy Research Institute.

High temperature deformation mechanism in hierarchical and single precipitate strengthened ferritic alloys by in situ neutron diffraction studies

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

Song, Gian; Sun, Zhiqian; Li, Lin

Here, the ferritic Fe-Cr-Ni-Al-Ti alloys strengthened by hierarchical-Ni 2TiAl/NiAl or single-Ni 2TiAl precipitates have been developed and received great attentions due to their superior creep resistance, as compared to conventional ferritic steels. Although the significant improvement of the creep resistance is achieved in the hierarchical-precipitate-strengthened ferritic alloy, the in-depth understanding of its high-temperature deformation mechanisms is essential to further optimize the microstructure and mechanical properties, and advance the development of the creep resistant materials. In the present study, in-situ neutron diffraction has been used to investigate the evolution of elastic strain of constitutive phases and their interactions, such as load-transfer/load-relaxationmore » behavior between the precipitate and matrix, during tensile deformation and stress relaxation at 973 K, which provide the key features in understanding the governing deformation mechanisms. Crystal-plasticity finite-element simulations were employed to qualitatively compare the experimental evolution of the elastic strain during tensile deformation at 973 K. It was found that the coherent elastic strain field in the matrix, created by the lattice misfit between the matrix and precipitate phases for the hierarchical-precipitate-strengthened ferritic alloy, is effective in reducing the diffusional relaxation along the interface between the precipitate and matrix phases, which leads to the strong load-transfer capability from the matrix to precipitate.« less

Epidemic spreading on hierarchical geographical networks with mobile agents

NASA Astrophysics Data System (ADS)

Han, Xiao-Pu; Zhao, Zhi-Dan; Hadzibeganovic, Tarik; Wang, Bing-Hong

2014-05-01

Hierarchical geographical traffic networks are critical for our understanding of scaling laws in human trajectories. Here, we investigate the susceptible-infected epidemic process evolving on hierarchical networks in which agents randomly walk along the edges and establish contacts in network nodes. We employ a metapopulation modeling framework that allows us to explore the contagion spread patterns in relation to multi-scale mobility behaviors. A series of computer simulations revealed that a shifted power-law-like negative relationship between the peak timing of epidemics τ0 and population density, and a logarithmic positive relationship between τ0 and the network size, can both be explained by the gradual enlargement of fluctuations in the spreading process. We employ a semi-analytical method to better understand the nature of these relationships and the role of pertinent demographic factors. Additionally, we provide a quantitative discussion of the efficiency of a border screening procedure in delaying epidemic outbreaks on hierarchical networks, yielding a rather limited feasibility of this mitigation strategy but also its non-trivial dependence on population density, infector detectability, and the diversity of the susceptible region. Our results suggest that the interplay between the human spatial dynamics, network topology, and demographic factors can have important consequences for the global spreading and control of infectious diseases. These findings provide novel insights into the combined effects of human mobility and the organization of geographical networks on spreading processes, with important implications for both epidemiological research and health policy.

High Temperature Deformation Mechanism in Hierarchical and Single Precipitate Strengthened Ferritic Alloys by In Situ Neutron Diffraction Studies

PubMed Central

Song, Gian; Sun, Zhiqian; Li, Lin; Clausen, Bjørn; Zhang, Shu Yan; Gao, Yanfei; Liaw, Peter K.

2017-01-01

The ferritic Fe-Cr-Ni-Al-Ti alloys strengthened by hierarchical-Ni2TiAl/NiAl or single-Ni2TiAl precipitates have been developed and received great attentions due to their superior creep resistance, as compared to conventional ferritic steels. Although the significant improvement of the creep resistance is achieved in the hierarchical-precipitate-strengthened ferritic alloy, the in-depth understanding of its high-temperature deformation mechanisms is essential to further optimize the microstructure and mechanical properties, and advance the development of the creep resistant materials. In the present study, in-situ neutron diffraction has been used to investigate the evolution of elastic strain of constitutive phases and their interactions, such as load-transfer/load-relaxation behavior between the precipitate and matrix, during tensile deformation and stress relaxation at 973 K, which provide the key features in understanding the governing deformation mechanisms. Crystal-plasticity finite-element simulations were employed to qualitatively compare the experimental evolution of the elastic strain during tensile deformation at 973 K. It was found that the coherent elastic strain field in the matrix, created by the lattice misfit between the matrix and precipitate phases for the hierarchical-precipitate-strengthened ferritic alloy, is effective in reducing the diffusional relaxation along the interface between the precipitate and matrix phases, which leads to the strong load-transfer capability from the matrix to precipitate. PMID:28387230

High temperature deformation mechanism in hierarchical and single precipitate strengthened ferritic alloys by in situ neutron diffraction studies

DOE PAGES

Song, Gian; Sun, Zhiqian; Li, Lin; ...

2017-04-07

Here, the ferritic Fe-Cr-Ni-Al-Ti alloys strengthened by hierarchical-Ni 2TiAl/NiAl or single-Ni 2TiAl precipitates have been developed and received great attentions due to their superior creep resistance, as compared to conventional ferritic steels. Although the significant improvement of the creep resistance is achieved in the hierarchical-precipitate-strengthened ferritic alloy, the in-depth understanding of its high-temperature deformation mechanisms is essential to further optimize the microstructure and mechanical properties, and advance the development of the creep resistant materials. In the present study, in-situ neutron diffraction has been used to investigate the evolution of elastic strain of constitutive phases and their interactions, such as load-transfer/load-relaxationmore » behavior between the precipitate and matrix, during tensile deformation and stress relaxation at 973 K, which provide the key features in understanding the governing deformation mechanisms. Crystal-plasticity finite-element simulations were employed to qualitatively compare the experimental evolution of the elastic strain during tensile deformation at 973 K. It was found that the coherent elastic strain field in the matrix, created by the lattice misfit between the matrix and precipitate phases for the hierarchical-precipitate-strengthened ferritic alloy, is effective in reducing the diffusional relaxation along the interface between the precipitate and matrix phases, which leads to the strong load-transfer capability from the matrix to precipitate.« less

Molecular Signatures of Immune Activation and Epithelial Barrier Remodeling Are Enhanced during the Luteal Phase of the Menstrual Cycle: Implications for HIV Susceptibility.

PubMed

Birse, Kenzie; Arnold, Kelly B; Novak, Richard M; McCorrister, Stuart; Shaw, Souradet; Westmacott, Garrett R; Ball, Terry B; Lauffenburger, Douglas A; Burgener, Adam

2015-09-01

The variable infectivity and transmissibility of HIV/SHIV has been recently associated with the menstrual cycle, with particular susceptibility observed during the luteal phase in nonhuman primate models and ex vivo human explant cultures, but the mechanism is poorly understood. Here, we performed an unbiased, mass spectrometry-based proteomic analysis to better understand the mucosal immunological processes underpinning this observed susceptibility to HIV infection. Cervicovaginal lavage samples (n = 19) were collected, characterized as follicular or luteal phase using days since last menstrual period, and analyzed by tandem mass spectrometry. Biological insights from these data were gained using a spectrum of computational methods, including hierarchical clustering, pathway analysis, gene set enrichment analysis, and partial least-squares discriminant analysis with LASSO feature selection. Of the 384 proteins identified, 43 were differentially abundant between phases (P < 0.05, ≥2-fold change). Cell-cell adhesion proteins and antiproteases were reduced, and leukocyte recruitment (interleukin-8 pathway, P = 1.41E-5) and extravasation proteins (P = 5.62E-4) were elevated during the luteal phase. LASSO/PLSDA identified a minimal profile of 18 proteins that best distinguished the luteal phase. This profile included cytoskeletal elements and proteases known to be involved in cellular movement. Gene set enrichment analysis associated CD4(+) T cell and neutrophil gene set signatures with the luteal phase (P < 0.05). Taken together, our findings indicate a strong association between proteins involved in tissue remodeling and leukocyte infiltration with the luteal phase, which may represent potential hormone-associated mechanisms of increased susceptibility to HIV. Recent studies have discovered an enhanced susceptibility to HIV infection during the progesterone-dominant luteal phase of the menstrual cycle. However, the mechanism responsible for this enhanced susceptibility has not yet been determined. Understanding the source of this vulnerability will be important for designing efficacious HIV prevention technologies for women. Furthermore, these findings may also be extrapolated to better understand the impact of exogenous hormone application, such as the use of hormonal contraceptives, on HIV acquisition risk. Hormonal contraceptives are the most widely used contraceptive method in sub-Saharan Africa, the most HIV-burdened area of the world. For this reason, research conducted to better understand how hormones impact host immunity and susceptibility factors important for HIV infection is a global health priority. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Alkylation Damage by Lipid Electrophiles Targets Functional Protein Systems*

PubMed Central

Codreanu, Simona G.; Ullery, Jody C.; Zhu, Jing; Tallman, Keri A.; Beavers, William N.; Porter, Ned A.; Marnett, Lawrence J.; Zhang, Bing; Liebler, Daniel C.

2014-01-01

Protein alkylation by reactive electrophiles contributes to chemical toxicities and oxidative stress, but the functional impact of alkylation damage across proteomes is poorly understood. We used Click chemistry and shotgun proteomics to profile the accumulation of proteome damage in human cells treated with lipid electrophile probes. Protein target profiles revealed three damage susceptibility classes, as well as proteins that were highly resistant to alkylation. Damage occurred selectively across functional protein interaction networks, with the most highly alkylation-susceptible proteins mapping to networks involved in cytoskeletal regulation. Proteins with lower damage susceptibility mapped to networks involved in protein synthesis and turnover and were alkylated only at electrophile concentrations that caused significant toxicity. Hierarchical susceptibility of proteome systems to alkylation may allow cells to survive sublethal damage while protecting critical cell functions. PMID:24429493

Understanding the mind of a worm: hierarchical network structure underlying nervous system function in C. elegans.

PubMed

Chatterjee, Nivedita; Sinha, Sitabhra

2008-01-01

The nervous system of the nematode C. elegans provides a unique opportunity to understand how behavior ('mind') emerges from activity in the nervous system ('brain') of an organism. The hermaphrodite worm has only 302 neurons, all of whose connections (synaptic and gap junctional) are known. Recently, many of the functional circuits that make up its behavioral repertoire have begun to be identified. In this paper, we investigate the hierarchical structure of the nervous system through k-core decomposition and find it to be intimately related to the set of all known functional circuits. Our analysis also suggests a vital role for the lateral ganglion in processing information, providing an essential connection between the sensory and motor components of the C. elegans nervous system.

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.

Hierarchical coordinate systems for understanding complexity and its evolution, with applications to genetic regulatory networks.

PubMed

Egri-Nagy, Attila; Nehaniv, Chrystopher L

2008-01-01

Beyond complexity measures, sometimes it is worthwhile in addition to investigate how complexity changes structurally, especially in artificial systems where we have complete knowledge about the evolutionary process. Hierarchical decomposition is a useful way of assessing structural complexity changes of organisms modeled as automata, and we show how recently developed computational tools can be used for this purpose, by computing holonomy decompositions and holonomy complexity. To gain insight into the evolution of complexity, we investigate the smoothness of the landscape structure of complexity under minimal transitions. As a proof of concept, we illustrate how the hierarchical complexity analysis reveals symmetries and irreversible structure in biological networks by applying the methods to the lac operon mechanism in the genetic regulatory network of Escherichia coli.

Domains and facets: hierarchical personality assessment using the revised NEO personality inventory.

PubMed

Costa, P T; McCrae, R R

1995-02-01

Personality traits are organized hierarchically, with narrow, specific traits combining to define broad, global factors. The Revised NEO Personality Inventory (NEO-PI-R; Costa & McCrae, 1992c) assesses personality at both levels, with six specific facet scales in each of five broad domains. This article describes conceptual issues in specifying facets of a domain and reports evidence on the validity of NEO-PI-R facet scales. Facet analysis-the interpretation of a scale in terms of the specific facets with which it correlates-is illustrated using alternative measures of the five-factor model and occupational scales. Finally, the hierarchical interpretation of personality profiles is discussed. Interpretation on the domain level yields a rapid understanding of the individual interpretation of specific facet scales gives a more detailed assessment.

Structural and metabolic transitions of C4 leaf development and differentiation defined by microscopy and quantitative proteomics in maize.

PubMed

Majeran, Wojciech; Friso, Giulia; Ponnala, Lalit; Connolly, Brian; Huang, Mingshu; Reidel, Edwin; Zhang, Cankui; Asakura, Yukari; Bhuiyan, Nazmul H; Sun, Qi; Turgeon, Robert; van Wijk, Klaas J

2010-11-01

C(4) grasses, such as maize (Zea mays), have high photosynthetic efficiency through combined biochemical and structural adaptations. C(4) photosynthesis is established along the developmental axis of the leaf blade, leading from an undifferentiated leaf base just above the ligule into highly specialized mesophyll cells (MCs) and bundle sheath cells (BSCs) at the tip. To resolve the kinetics of maize leaf development and C(4) differentiation and to obtain a systems-level understanding of maize leaf formation, the accumulation profiles of proteomes of the leaf and the isolated BSCs with their vascular bundle along the developmental gradient were determined using large-scale mass spectrometry. This was complemented by extensive qualitative and quantitative microscopy analysis of structural features (e.g., Kranz anatomy, plasmodesmata, cell wall, and organelles). More than 4300 proteins were identified and functionally annotated. Developmental protein accumulation profiles and hierarchical cluster analysis then determined the kinetics of organelle biogenesis, formation of cellular structures, metabolism, and coexpression patterns. Two main expression clusters were observed, each divided in subclusters, suggesting that a limited number of developmental regulatory networks organize concerted protein accumulation along the leaf gradient. The coexpression with BSC and MC markers provided strong candidates for further analysis of C(4) specialization, in particular transporters and biogenesis factors. Based on the integrated information, we describe five developmental transitions that provide a conceptual and practical template for further analysis. An online protein expression viewer is provided through the Plant Proteome Database.

A Phenomenological Investigation of Experiences Regarding Workplace Bullying in Higher Education

ERIC Educational Resources Information Center

Burris, Patricia

2012-01-01

Understanding academic bullying begins with gaining a better understanding of bullying behaviors in general. Academic bullying causes harm and extends over a period of time (Fogg, 2008). The tenure system and hierarchical nature of higher education contribute to the occurrence of bullying in colleges and universities (Fogg, 2003, p. A12). While…

The Neural Correlates of Hierarchical Predictions for Perceptual Decisions.

PubMed

Weilnhammer, Veith A; Stuke, Heiner; Sterzer, Philipp; Schmack, Katharina

2018-05-23

Sensory information is inherently noisy, sparse, and ambiguous. In contrast, visual experience is usually clear, detailed, and stable. Bayesian theories of perception resolve this discrepancy by assuming that prior knowledge about the causes underlying sensory stimulation actively shapes perceptual decisions. The CNS is believed to entertain a generative model aligned to dynamic changes in the hierarchical states of our volatile sensory environment. Here, we used model-based fMRI to study the neural correlates of the dynamic updating of hierarchically structured predictions in male and female human observers. We devised a crossmodal associative learning task with covertly interspersed ambiguous trials in which participants engaged in hierarchical learning based on changing contingencies between auditory cues and visual targets. By inverting a Bayesian model of perceptual inference, we estimated individual hierarchical predictions, which significantly biased perceptual decisions under ambiguity. Although "high-level" predictions about the cue-target contingency correlated with activity in supramodal regions such as orbitofrontal cortex and hippocampus, dynamic "low-level" predictions about the conditional target probabilities were associated with activity in retinotopic visual cortex. Our results suggest that our CNS updates distinct representations of hierarchical predictions that continuously affect perceptual decisions in a dynamically changing environment. SIGNIFICANCE STATEMENT Bayesian theories posit that our brain entertains a generative model to provide hierarchical predictions regarding the causes of sensory information. Here, we use behavioral modeling and fMRI to study the neural underpinnings of such hierarchical predictions. We show that "high-level" predictions about the strength of dynamic cue-target contingencies during crossmodal associative learning correlate with activity in orbitofrontal cortex and the hippocampus, whereas "low-level" conditional target probabilities were reflected in retinotopic visual cortex. Our findings empirically corroborate theorizations on the role of hierarchical predictions in visual perception and contribute substantially to a longstanding debate on the link between sensory predictions and orbitofrontal or hippocampal activity. Our work fundamentally advances the mechanistic understanding of perceptual inference in the human brain. Copyright © 2018 the authors 0270-6474/18/385008-14$15.00/0.

Hierarchical self-assembly of actin in micro-confinements using microfluidics

PubMed Central

Deshpande, Siddharth; Pfohl, Thomas

2012-01-01

We present a straightforward microfluidics system to achieve step-by-step reaction sequences in a diffusion-controlled manner in quasi two-dimensional micro-confinements. We demonstrate the hierarchical self-organization of actin (actin monomers—entangled networks of filaments—networks of bundles) in a reversible fashion by tuning the Mg2+ ion concentration in the system. We show that actin can form networks of bundles in the presence of Mg2+ without any cross-linking proteins. The properties of these networks are influenced by the confinement geometry. In square microchambers we predominantly find rectangular networks, whereas triangular meshes are predominantly found in circular chambers. PMID:24032070

Hierarchical coarse-graining strategy for protein-membrane systems to access mesoscopic scales

PubMed Central

Ayton, Gary S.; Lyman, Edward

2014-01-01

An overall multiscale simulation strategy for large scale coarse-grain simulations of membrane protein systems is presented. The protein is modeled as a heterogeneous elastic network, while the lipids are modeled using the hybrid analytic-systematic (HAS) methodology, where in both cases atomistic level information obtained from molecular dynamics simulation is used to parameterize the model. A feature of this approach is that from the outset liposome length scales are employed in the simulation (i.e., on the order of ½ a million lipids plus protein). A route to develop highly coarse-grained models from molecular-scale information is proposed and results for N-BAR domain protein remodeling of a liposome are presented. PMID:20158037

Three-Dimensional Hierarchical Plasmonic Nano-Architecture Enhanced Surface-Enhanced Raman Scattering Immuno-Sensor for Cancer Biomarker Detection in Blood Plasma

PubMed Central

Li, Ming; Cushing, Scott K.; Zhang, Jianming; Suri, Savan; Evans, Rebecca; Petros, William P.; Gibson, Laura F.; Ma, Dongling; Liu, Yuxin; Wu, Nianqiang

2013-01-01

A three-dimensional (3D) hierarchical plasmonic nano-architecture has been designed for a sensitive surface-enhanced Raman scattering (SERS) immuno-sensor for protein biomarker detection. The capture antibody molecules are immobilized on a plasmonic gold triangle nano-array pattern. On the other hand, the detection antibody molecules are linked to the gold nano-star@Raman-reporter@silica sandwich nanoparticles. When protein biomarkers are present, the sandwich nanoparticles are captured over the gold triangle nano-array, forming a confined 3D plasmonic field, leading to the enhanced electromagnetic field in intensity and in 3D space. As a result, the Raman reporter molecules are exposed to a high density of “hot spots”, which amplifies the Raman signal remarkably, improving the sensitivity of the SERS immuno-sensor. This SERS immuno-sensor exhibits a wide linear range (0.1 pg/mL to 10 ng/mL), and a low limit of detection (7 fg/mL) toward human immunoglobulin G (IgG) protein in the buffer solution. This biosensor has been successfully used for detection of the vascular endothelial growth factor (VEGF) in the human blood plasma from clinical breast cancer patient samples. PMID:23659430

Hydrogen-Bond Driven Loop-Closure Kinetics in Unfolded Polypeptide Chains

PubMed Central

Daidone, Isabella; Neuweiler, Hannes; Doose, Sören; Sauer, Markus; Smith, Jeremy C.

2010-01-01

Characterization of the length dependence of end-to-end loop-closure kinetics in unfolded polypeptide chains provides an understanding of early steps in protein folding. Here, loop-closure in poly-glycine-serine peptides is investigated by combining single-molecule fluorescence spectroscopy with molecular dynamics simulation. For chains containing more than 10 peptide bonds loop-closing rate constants on the 20–100 nanosecond time range exhibit a power-law length dependence. However, this scaling breaks down for shorter peptides, which exhibit slower kinetics arising from a perturbation induced by the dye reporter system used in the experimental setup. The loop-closure kinetics in the longer peptides is found to be determined by the formation of intra-peptide hydrogen bonds and transient β-sheet structure, that accelerate the search for contacts among residues distant in sequence relative to the case of a polypeptide chain in which hydrogen bonds cannot form. Hydrogen-bond-driven polypeptide-chain collapse in unfolded peptides under physiological conditions found here is not only consistent with hierarchical models of protein folding, that highlights the importance of secondary structure formation early in the folding process, but is also shown to speed up the search for productive folding events. PMID:20098498

Understanding movement data and movement processes: current and emerging directions.

PubMed

Schick, Robert S; Loarie, Scott R; Colchero, Fernando; Best, Benjamin D; Boustany, Andre; Conde, Dalia A; Halpin, Patrick N; Joppa, Lucas N; McClellan, Catherine M; Clark, James S

2008-12-01

Animal movement has been the focus on much theoretical and empirical work in ecology over the last 25 years. By studying the causes and consequences of individual movement, ecologists have gained greater insight into the behavior of individuals and the spatial dynamics of populations at increasingly higher levels of organization. In particular, ecologists have focused on the interaction between individuals and their environment in an effort to understand future impacts from habitat loss and climate change. Tools to examine this interaction have included: fractal analysis, first passage time, Lévy flights, multi-behavioral analysis, hidden markov models, and state-space models. Concurrent with the development of movement models has been an increase in the sophistication and availability of hierarchical bayesian models. In this review we bring these two threads together by using hierarchical structures as a framework for reviewing individual models. We synthesize emerging themes in movement ecology, and propose a new hierarchical model for animal movement that builds on these emerging themes. This model moves away from traditional random walks, and instead focuses inference on how moving animals with complex behavior interact with their landscape and make choices about its suitability.

Protein chainmail variants in dsDNA viruses

PubMed Central

Zhou, Z. Hong; Chiou, Joshua

2017-01-01

First discovered in bacteriophage HK97, biological chainmail is a highly stable system formed by concatenated protein rings. Each subunit of the ring contains the HK97-like fold, which is characterized by its submarine-like shape with a 5-stranded β sheet in the axial (A) domain, spine helix in the peripheral (P) domain, and an extended (E) loop. HK97 capsid consists of covalently-linked copies of just one HK97-like fold protein and represents the most effective strategy to form highly stable chainmail needed for dsDNA genome encapsidation. Recently, near-atomic resolution structures enabled by cryo electron microscopy (cryoEM) have revealed a range of other, more complex variants of this strategy for constructing dsDNA viruses. The first strategy, exemplified by P22-like phages, is the attachment of an insertional (I) domain to the core 5-stranded β sheet of the HK97-like fold. The atomic models of the Bordetella phage BPP-1 showcases an alternative topology of the classic HK97 topology of the HK97-like fold, as well as the second strategy for constructing stable capsids, where an auxiliary jellyroll protein dimer serves to cement the non-covalent chainmail formed by capsid protein subunits. The third strategy, found in lambda-like phages, uses auxiliary protein trimers to stabilize the underlying non-covalent chainmail near the 3-fold axis. Herpesviruses represent highly complex viruses that use a combination of these strategies, resulting in four-level hierarchical organization including a non-covalent chainmail formed by the HK97-like fold domain found in the floor region. A thorough understanding of these structures should help unlock the enigma of the emergence and evolution of dsDNA viruses and inform bioengineering efforts based on these viruses. PMID:29177192

Efficient algorithms for accurate hierarchical clustering of huge datasets: tackling the entire protein space.

PubMed

Loewenstein, Yaniv; Portugaly, Elon; Fromer, Menachem; Linial, Michal

2008-07-01

UPGMA (average linking) is probably the most popular algorithm for hierarchical data clustering, especially in computational biology. However, UPGMA requires the entire dissimilarity matrix in memory. Due to this prohibitive requirement, UPGMA is not scalable to very large datasets. We present a novel class of memory-constrained UPGMA (MC-UPGMA) algorithms. Given any practical memory size constraint, this framework guarantees the correct clustering solution without explicitly requiring all dissimilarities in memory. The algorithms are general and are applicable to any dataset. We present a data-dependent characterization of hardness and clustering efficiency. The presented concepts are applicable to any agglomerative clustering formulation. We apply our algorithm to the entire collection of protein sequences, to automatically build a comprehensive evolutionary-driven hierarchy of proteins from sequence alone. The newly created tree captures protein families better than state-of-the-art large-scale methods such as CluSTr, ProtoNet4 or single-linkage clustering. We demonstrate that leveraging the entire mass embodied in all sequence similarities allows to significantly improve on current protein family clusterings which are unable to directly tackle the sheer mass of this data. Furthermore, we argue that non-metric constraints are an inherent complexity of the sequence space and should not be overlooked. The robustness of UPGMA allows significant improvement, especially for multidomain proteins, and for large or divergent families. A comprehensive tree built from all UniProt sequence similarities, together with navigation and classification tools will be made available as part of the ProtoNet service. A C++ implementation of the algorithm is available on request.

Atomic structure and hierarchical assembly of a cross-β amyloid fibril

PubMed Central

Fitzpatrick, Anthony W. P.; Debelouchina, Galia T.; Bayro, Marvin J.; Clare, Daniel K.; Caporini, Marc A.; Bajaj, Vikram S.; Jaroniec, Christopher P.; Wang, Luchun; Ladizhansky, Vladimir; Müller, Shirley A.; MacPhee, Cait E.; Waudby, Christopher A.; Mott, Helen R.; De Simone, Alfonso; Knowles, Tuomas P. J.; Saibil, Helen R.; Vendruscolo, Michele; Orlova, Elena V.; Griffin, Robert G.; Dobson, Christopher M.

2013-01-01

The cross-β amyloid form of peptides and proteins represents an archetypal and widely accessible structure consisting of ordered arrays of β-sheet filaments. These complex aggregates have remarkable chemical and physical properties, and the conversion of normally soluble functional forms of proteins into amyloid structures is linked to many debilitating human diseases, including several common forms of age-related dementia. Despite their importance, however, cross-β amyloid fibrils have proved to be recalcitrant to detailed structural analysis. By combining structural constraints from a series of experimental techniques spanning five orders of magnitude in length scale—including magic angle spinning nuclear magnetic resonance spectroscopy, X-ray fiber diffraction, cryoelectron microscopy, scanning transmission electron microscopy, and atomic force microscopy—we report the atomic-resolution (0.5 Å) structures of three amyloid polymorphs formed by an 11-residue peptide. These structures reveal the details of the packing interactions by which the constituent β-strands are assembled hierarchically into protofilaments, filaments, and mature fibrils. PMID:23513222

Recombinant spider silk from aqueous solutions via a bio-inspired microfluidic chip

NASA Astrophysics Data System (ADS)

Peng, Qingfa; Zhang, Yaopeng; Lu, Li; Shao, Huili; Qin, Kankan; Hu, Xuechao; Xia, Xiaoxia

2016-11-01

Spiders achieve superior silk fibres by controlling the molecular assembly of silk proteins and the hierarchical structure of fibres. However, current wet-spinning process for recombinant spidroins oversimplifies the natural spinning process. Here, water-soluble recombinant spider dragline silk protein (with a low molecular weight of 47 kDa) was adopted to prepare aqueous spinning dope. Artificial spider silks were spun via microfluidic wet-spinning, using a continuous post-spin drawing process (WS-PSD). By mimicking the natural spinning apparatus, shearing and elongational sections were integrated in the microfluidic spinning chip to induce assembly, orientation of spidroins, and fibril structure formation. The additional post-spin drawing process following the wet-spinning section partially mimics the spinning process of natural spider silk and substantially contributes to the compact aggregation of microfibrils. Subsequent post-stretching further improves the hierarchical structure of the fibres, including the crystalline structure, orientation, and fibril melting. The tensile strength and elongation of post-treated fibres reached up to 510 MPa and 15%, respectively.

Dynamic anticipatory processing of hierarchical sequential events: a common role for Broca's area and ventral premotor cortex across domains?

PubMed

Fiebach, Christian J; Schubotz, Ricarda I

2006-05-01

This paper proposes a domain-general model for the functional contribution of ventral premotor cortex (PMv) and adjacent Broca's area to perceptual, cognitive, and motor processing. We propose to understand this frontal region as a highly flexible sequence processor, with the PMv mapping sequential events onto stored structural templates and Broca's Area involved in more complex, hierarchical or hypersequential processing. This proposal is supported by reference to previous functional neuroimaging studies investigating abstract sequence processing and syntactic processing.

Effects of catalyst pore structure and acid properties on the dehydration of glycerol.

PubMed

Choi, Youngbo; Park, Hongseok; Yun, Yang Sik; Yi, Jongheop

2015-03-01

Hierarchical porous catalysts have recently attracted increasing interest because of the enhanced accessibility to active sites on such materials. In this context, previously reported hierarchically mesoporous ASN and ASPN materials are evaluated by applying them to the dehydration of glycerol, and demonstrate excellent catalytic performance. In addition, a comprehensive understanding of the effects of pore structures and the acid properties on the reaction through comparative studies with microporous HZSM-5 and mesoporous AlMCM-41 is provided. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Alignment hierarchies: engineering architecture from the nanometre to the micrometre scale.

PubMed

Kureshi, Alvena; Cheema, Umber; Alekseeva, Tijna; Cambrey, Alison; Brown, Robert

2010-12-06

Natural tissues are built of metabolites, soluble proteins and solid extracellular matrix components (largely fibrils) together with cells. These are configured in highly organized hierarchies of structure across length scales from nanometre to millimetre, with alignments that are dominated by anisotropies in their fibrillar matrix. If we are to successfully engineer tissues, these hierarchies need to be mimicked with an understanding of the interaction between them. In particular, the movement of different elements of the tissue (e.g. molecules, cells and bulk fluids) is controlled by matrix structures at distinct scales. We present three novel systems to introduce alignment of collagen fibrils, cells and growth factor gradients within a three-dimensional collagen scaffold using fluid flow, embossing and layering of construct. Importantly, these can be seen as different parts of the same hierarchy of three-dimensional structure, as they are all formed into dense collagen gels. Fluid flow aligns collagen fibrils at the nanoscale, embossed topographical features provide alignment cues at the microscale and introducing layered configuration to three-dimensional collagen scaffolds provides microscale- and mesoscale-aligned pathways for protein factor delivery as well as barriers to confine protein diffusion to specific spatial directions. These seemingly separate methods can be employed to increase complexity of simple extracellular matrix scaffolds, providing insight into new approaches to directly fabricate complex physical and chemical cues at different hierarchical scales, similar to those in natural tissues.

Morphology and mechanical properties of multi-stranded amyloid fibrils probed by atomistic and coarse-grained simulations

NASA Astrophysics Data System (ADS)

Yoon, Gwonchan; Lee, Myeongsang; Kim, Kyungwoo; In Kim, Jae; Chang, Hyun Joon; Baek, Inchul; Eom, Kilho; Na, Sungsoo

2015-12-01

Amyloid fibrils are responsible for pathogenesis of various diseases and exhibit the structural feature of an ordered, hierarchical structure such as multi-stranded helical structure. As the multi-strandedness of amyloid fibrils has recently been found to be highly correlated with their toxicity and infectivity, it is necessary to study how the hierarchical (i.e. multi-stranded) structure of amyloid fibril is formed. Moreover, although it has recently been reported that the nanomechanics of amyloid proteins plays a key role on the amyloid-induced pathogenesis, a critical role that the multi-stranded helical structure of the fibrils plays in their nanomechanical properties has not fully characterized. In this work, we characterize the morphology and mechanical properties of multi-stranded amyloid fibrils by using equilibrium molecular dynamics simulation and elastic network model. It is shown that the helical pitch of multi-stranded amyloid fibril is linearly proportional to the number of filaments comprising the amyloid fibril, and that multi-strandedness gives rise to improving the bending rigidity of the fibril. Moreover, we have also studied the morphology and mechanical properties of a single protofilament (filament) in order to understand the effect of cross-β structure and mutation on the structures and mechanical properties of amyloid fibrils. Our study sheds light on the underlying design principles showing how the multi-stranded amyloid fibril is formed and how the structure of amyloid fibrils governs their nanomechanical properties.

Structural evolution of photocrosslinked silk fibroin and silk fibroin-based hybrid hydrogels: A small angle and ultra-small angle scattering investigation.

PubMed

Whittaker, Jasmin L; Balu, Rajkamal; Knott, Robert; de Campo, Liliana; Mata, Jitendra P; Rehm, Christine; Hill, Anita J; Dutta, Naba K; Roy Choudhury, Namita

2018-07-15

Regenerated Bombyx mori silk fibroin (RSF) is a widely recognized protein for biomedical applications; however, its hierarchical gel structure is poorly understood. In this paper, the hierarchical structure of photocrosslinked RSF and RSF-based hybrid hydrogel systems: (i) RSF/Rec1-resilin and (ii) RSF/poly(N-vinylcaprolactam (PVCL) is reported for the first time using small-angle scattering (SAS) techniques. The structure of RSF in dilute to concentrated solution to fabricated hydrogels were characterized using small angle X-ray scattering (SAXS), small angle neutron scattering (SANS) and ultra-small angle neutron scattering (USANS) techniques. The RSF hydrogel exhibited three distinctive structural characteristics: (i) a Porod region in the length scale of 2 to 3nm due to hydrophobic domains (containing β-sheets) which exhibits sharp interfaces with the amorphous matrix of the hydrogel and the solvent, (ii) a Guinier region in the length scale of 4 to 20nm due to hydrophilic domains (containing turns and random coil), and (iii) a Porod-like region in the length scale of few micrometers due to water pores/channels exhibiting fractal-like characteristics. Addition of Rec1-resilin or PVCL to RSF and subsequent crosslinking systematically increased the nanoscale size of hydrophobic and hydrophilic domains, whereas decreased the homogeneity of pore size distribution in the microscale. The presented results have implications on the fundamental understanding of the structure-property relationship of RSF-based hydrogels. Copyright © 2018. Published by Elsevier B.V.

Resolving the Framework Position of Organic Structure-Directing Agents in Hierarchical Zeolites via Polarized Stimulated Raman Scattering.

PubMed

Fleury, Guillaume; Steele, Julian A; Gerber, Iann C; Jolibois, F; Puech, P; Muraoka, Koki; Keoh, Sye Hoe; Chaikittisilp, Watcharop; Okubo, Tatsuya; Roeffaers, Maarten B J

2018-04-05

The direct synthesis of hierarchically intergrown silicalite-1 can be achieved using a specific diquaternary ammonium agent. However, the location of these molecules in the zeolite framework, which is critical to understand the formation of the material, remains unclear. Where traditional characterization tools have previously failed, herein we use polarized stimulated Raman scattering (SRS) microscopy to resolve molecular organization inside few-micron-sized crystals. Through a combination of experiment and first-principles calculations, our investigation reveals the preferential location of the templating agent inside the linear pores of the MFI framework. Besides illustrating the attractiveness of SRS microscopy in the field of material science to study and spatially resolve local molecular distribution as well as orientation, these results can be exploited in the design of new templating agents for the preparation of hierarchical zeolites.

A new hierarchical method to find community structure in networks

NASA Astrophysics Data System (ADS)

Saoud, Bilal; Moussaoui, Abdelouahab

2018-04-01

Community structure is very important to understand a network which represents a context. Many community detection methods have been proposed like hierarchical methods. In our study, we propose a new hierarchical method for community detection in networks based on genetic algorithm. In this method we use genetic algorithm to split a network into two networks which maximize the modularity. Each new network represents a cluster (community). Then we repeat the splitting process until we get one node at each cluster. We use the modularity function to measure the strength of the community structure found by our method, which gives us an objective metric for choosing the number of communities into which a network should be divided. We demonstrate that our method are highly effective at discovering community structure in both computer-generated and real-world network data.

Electrospun nanofibres to mimic natural hierarchical structure of tissues: application in musculoskeletal regeneration.

PubMed

Sankar, Sharanya; Sharma, Chandra S; Rath, Subha N; Ramakrishna, Seeram

2018-01-01

Biomimetic scaffolds mimicking the natural hierarchical structure of tissues have recently attracted the interest of researchers and provide a promising strategy to resemble the nonhomogeneous property of tissues. This review provides an overview of the various hierarchical length scales in the native tissues of the musculoskeletal system. It further focuses on electrospinning as a technique to mimic the tissue structures with specific emphasis on bone. The effect of cellular alignment, infiltration, vascularisation, and differentiation in these nanostructures has also been discussed. An outline of the various additive manufacturing techniques in combination with electrospinning has been elaborated. The review concludes with the challenges and future directions to understand the intricacies of bottom-up approach to engineer the systems at a macroscale. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Biominerals- hierarchical nanocomposites: the example of bone

PubMed Central

Beniash, Elia

2010-01-01

Many organisms incorporate inorganic solids in their tissues to enhance their functional, primarily mechanical, properties. These mineralized tissues, also called biominerals, are unique organo-mineral nanocomposites, organized at several hierarchical levels, from nano- to macroscale. Unlike man made composite materials, which often are simple physical blends of their components, the organic and inorganic phases in biominerals interface at the molecular level. Although these tissues are made of relatively weak components at ambient conditions, their hierarchical structural organization and intimate interactions between different elements lead to superior mechanical properties. Understanding basic principles of formation, structure and functional properties of these tissues might lead to novel bioinspired strategies for material design and better treatments for diseases of the mineralized tissues. This review focuses on general principles of structural organization, formation and functional properties of biominerals on the example the bone tissues. PMID:20827739

Topology of the correlation networks among major currencies using hierarchical structure methods

NASA Astrophysics Data System (ADS)

Keskin, Mustafa; Deviren, Bayram; Kocakaplan, Yusuf

2011-02-01

We studied the topology of correlation networks among 34 major currencies using the concept of a minimal spanning tree and hierarchical tree for the full years of 2007-2008 when major economic turbulence occurred. We used the USD (US Dollar) and the TL (Turkish Lira) as numeraires in which the USD was the major currency and the TL was the minor currency. We derived a hierarchical organization and constructed minimal spanning trees (MSTs) and hierarchical trees (HTs) for the full years of 2007, 2008 and for the 2007-2008 period. We performed a technique to associate a value of reliability to the links of MSTs and HTs by using bootstrap replicas of data. We also used the average linkage cluster analysis for obtaining the hierarchical trees in the case of the TL as the numeraire. These trees are useful tools for understanding and detecting the global structure, taxonomy and hierarchy in financial data. We illustrated how the minimal spanning trees and their related hierarchical trees developed over a period of time. From these trees we identified different clusters of currencies according to their proximity and economic ties. The clustered structure of the currencies and the key currency in each cluster were obtained and we found that the clusters matched nicely with the geographical regions of corresponding countries in the world such as Asia or Europe. As expected the key currencies were generally those showing major economic activity.

eLoom and Flatland: specification, simulation and visualization engines for the study of arbitrary hierarchical neural architectures.

PubMed

Caudell, Thomas P; Xiao, Yunhai; Healy, Michael J

2003-01-01

eLoom is an open source graph simulation software tool, developed at the University of New Mexico (UNM), that enables users to specify and simulate neural network models. Its specification language and libraries enables users to construct and simulate arbitrary, potentially hierarchical network structures on serial and parallel processing systems. In addition, eLoom is integrated with UNM's Flatland, an open source virtual environments development tool to provide real-time visualizations of the network structure and activity. Visualization is a useful method for understanding both learning and computation in artificial neural networks. Through 3D animated pictorially representations of the state and flow of information in the network, a better understanding of network functionality is achieved. ART-1, LAPART-II, MLP, and SOM neural networks are presented to illustrate eLoom and Flatland's capabilities.

A neural model of hierarchical reinforcement learning

PubMed Central

Rasmussen, Daniel; Eliasmith, Chris

2017-01-01

We develop a novel, biologically detailed neural model of reinforcement learning (RL) processes in the brain. This model incorporates a broad range of biological features that pose challenges to neural RL, such as temporally extended action sequences, continuous environments involving unknown time delays, and noisy/imprecise computations. Most significantly, we expand the model into the realm of hierarchical reinforcement learning (HRL), which divides the RL process into a hierarchy of actions at different levels of abstraction. Here we implement all the major components of HRL in a neural model that captures a variety of known anatomical and physiological properties of the brain. We demonstrate the performance of the model in a range of different environments, in order to emphasize the aim of understanding the brain’s general reinforcement learning ability. These results show that the model compares well to previous modelling work and demonstrates improved performance as a result of its hierarchical ability. We also show that the model’s behaviour is consistent with available data on human hierarchical RL, and generate several novel predictions. PMID:28683111

Hierarchical and coupling model of factors influencing vessel traffic flow.

PubMed

Liu, Zhao; Liu, Jingxian; Li, Huanhuan; Li, Zongzhi; Tan, Zhirong; Liu, Ryan Wen; Liu, Yi

2017-01-01

Understanding the characteristics of vessel traffic flow is crucial in maintaining navigation safety, efficiency, and overall waterway transportation management. Factors influencing vessel traffic flow possess diverse features such as hierarchy, uncertainty, nonlinearity, complexity, and interdependency. To reveal the impact mechanism of the factors influencing vessel traffic flow, a hierarchical model and a coupling model are proposed in this study based on the interpretative structural modeling method. The hierarchical model explains the hierarchies and relationships of the factors using a graph. The coupling model provides a quantitative method that explores interaction effects of factors using a coupling coefficient. The coupling coefficient is obtained by determining the quantitative indicators of the factors and their weights. Thereafter, the data obtained from Port of Tianjin is used to verify the proposed coupling model. The results show that the hierarchical model of the factors influencing vessel traffic flow can explain the level, structure, and interaction effect of the factors; the coupling model is efficient in analyzing factors influencing traffic volumes. The proposed method can be used for analyzing increases in vessel traffic flow in waterway transportation system.

Hierarchical and coupling model of factors influencing vessel traffic flow

PubMed Central

Liu, Jingxian; Li, Huanhuan; Li, Zongzhi; Tan, Zhirong; Liu, Ryan Wen; Liu, Yi

2017-01-01

Understanding the characteristics of vessel traffic flow is crucial in maintaining navigation safety, efficiency, and overall waterway transportation management. Factors influencing vessel traffic flow possess diverse features such as hierarchy, uncertainty, nonlinearity, complexity, and interdependency. To reveal the impact mechanism of the factors influencing vessel traffic flow, a hierarchical model and a coupling model are proposed in this study based on the interpretative structural modeling method. The hierarchical model explains the hierarchies and relationships of the factors using a graph. The coupling model provides a quantitative method that explores interaction effects of factors using a coupling coefficient. The coupling coefficient is obtained by determining the quantitative indicators of the factors and their weights. Thereafter, the data obtained from Port of Tianjin is used to verify the proposed coupling model. The results show that the hierarchical model of the factors influencing vessel traffic flow can explain the level, structure, and interaction effect of the factors; the coupling model is efficient in analyzing factors influencing traffic volumes. The proposed method can be used for analyzing increases in vessel traffic flow in waterway transportation system. PMID:28414747

Tailoring lumazine synthase assemblies for bionanotechnology.

PubMed

Azuma, Yusuke; Edwardson, Thomas G W; Hilvert, Donald

2018-05-21

Nanoscale compartments formed by hierarchical protein self-assembly are valuable platforms for nanotechnology development. The well-defined structure and broad chemical functionality of protein cages, as well as their amenability to genetic and chemical modification, have enabled their repurposing for diverse applications. In this review, we summarize progress in the engineering of the cage-forming enzyme lumazine synthase. This bacterial nanocompartment has proven to be a malleable scaffold. The natural protein has been diversified to afford a family of unique proteinaceous capsules that have been modified, evolved and assembled with other components to produce nanoreactors, artificial organelles, delivery vehicles and virus mimics.

Hierarchical Time-Lagged Independent Component Analysis: Computing Slow Modes and Reaction Coordinates for Large Molecular Systems.

PubMed

Pérez-Hernández, Guillermo; Noé, Frank

2016-12-13

Analysis of molecular dynamics, for example using Markov models, often requires the identification of order parameters that are good indicators of the rare events, i.e. good reaction coordinates. Recently, it has been shown that the time-lagged independent component analysis (TICA) finds the linear combinations of input coordinates that optimally represent the slow kinetic modes and may serve in order to define reaction coordinates between the metastable states of the molecular system. A limitation of the method is that both computing time and memory requirements scale with the square of the number of input features. For large protein systems, this exacerbates the use of extensive feature sets such as the distances between all pairs of residues or even heavy atoms. Here we derive a hierarchical TICA (hTICA) method that approximates the full TICA solution by a hierarchical, divide-and-conquer calculation. By using hTICA on distances between heavy atoms we identify previously unknown relaxation processes in the bovine pancreatic trypsin inhibitor.

Who is the boss? Individual recognition memory and social hierarchy formation in crayfish.

PubMed

Jiménez-Morales, Nayeli; Mendoza-Ángeles, Karina; Porras-Villalobos, Mercedes; Ibarra-Coronado, Elizabeth; Roldán-Roldán, Gabriel; Hernández-Falcón, Jesús

2018-01-01

Under laboratory conditions, crayfish establish hierarchical orders through agonistic encounters whose outcome defines the dominant one and one, or more, submissive animals. These agonistic encounters are ritualistic, based on threats, pushes, attacks, grabs, and avoidance behaviors that include retreats and escape responses. Agonistic behavior in a triad of unfamiliar, size-matched animals is intense on the first day of social interaction and the intensity fades on daily repetitions. The dominant animal keeps its status for long periods, and the submissive ones seem to remember 'who the boss is'. It has been assumed that animals remember and recognize their hierarchical status by urine signals, but the putative substance mediating this recognition has not been reported. The aim of this work was to characterize this hierarchical recognition memory. Triads of unfamiliar crayfish (male animals, size and weight-matched) were faced during standardized agonistic protocols for five consecutive days to analyze memory acquisition dynamics (Experiment 1). In Experiment 2, dominant crayfish were shifted among triads to disclose whether hierarchy depended upon individual recognition memory or recognition of status. The maintenance of the hierarchical structure without behavioral reinforcement was assessed by immobilizing the dominant animal during eleven daily agonistic encounters, and considering any shift in the dominance order (Experiment 3). Standard amnesic treatments (anisomycin, scopolamine or cold-anesthesia) were given to all members of the triads immediately after the first interaction session to prevent individual recognition memory consolidation and evaluate its effect on the hierarchical order (Experiment 4). Acquisition of hierarchical recognition occurs at the first agonistic encounter and agonistic behavior gradually diminishes in the following days; animals keep their hierarchical order despite the inability of the dominant crayfish to attack the submissive ones. Finally, blocking of protein synthesis or muscarinic receptors and cold anesthesia impair memory consolidation. These findings suggest that agonistic encounters induces the acquisition of a robust and lasting social recognition memory in crayfish. Copyright © 2017 Elsevier Inc. All rights reserved.

Membrane Compartmentalization Reducing the Mobility of Lipids and Proteins within a Model Plasma Membrane.

PubMed

Koldsø, Heidi; Reddy, Tyler; Fowler, Philip W; Duncan, Anna L; Sansom, Mark S P

2016-09-01

The cytoskeleton underlying cell membranes may influence the dynamic organization of proteins and lipids within the bilayer by immobilizing certain transmembrane (TM) proteins and forming corrals within the membrane. Here, we present coarse-grained resolution simulations of a biologically realistic membrane model of asymmetrically organized lipids and TM proteins. We determine the effects of a model of cytoskeletal immobilization of selected membrane proteins using long time scale coarse-grained molecular dynamics simulations. By introducing compartments with varying degrees of restraints within the membrane models, we are able to reveal how compartmentalization caused by cytoskeletal immobilization leads to reduced and anomalous diffusional mobility of both proteins and lipids. This in turn results in a reduced rate of protein dimerization within the membrane and of hopping of membrane proteins between compartments. These simulations provide a molecular realization of hierarchical models often invoked to explain single-molecule imaging studies of membrane proteins.

AptRank: an adaptive PageRank model for protein function prediction on   bi-relational graphs.

PubMed

Jiang, Biaobin; Kloster, Kyle; Gleich, David F; Gribskov, Michael

2017-06-15

Diffusion-based network models are widely used for protein function prediction using protein network data and have been shown to outperform neighborhood-based and module-based methods. Recent studies have shown that integrating the hierarchical structure of the Gene Ontology (GO) data dramatically improves prediction accuracy. However, previous methods usually either used the GO hierarchy to refine the prediction results of multiple classifiers, or flattened the hierarchy into a function-function similarity kernel. No study has taken the GO hierarchy into account together with the protein network as a two-layer network model. We first construct a Bi-relational graph (Birg) model comprised of both protein-protein association and function-function hierarchical networks. We then propose two diffusion-based methods, BirgRank and AptRank, both of which use PageRank to diffuse information on this two-layer graph model. BirgRank is a direct application of traditional PageRank with fixed decay parameters. In contrast, AptRank utilizes an adaptive diffusion mechanism to improve the performance of BirgRank. We evaluate the ability of both methods to predict protein function on yeast, fly and human protein datasets, and compare with four previous methods: GeneMANIA, TMC, ProteinRank and clusDCA. We design four different validation strategies: missing function prediction, de novo function prediction, guided function prediction and newly discovered function prediction to comprehensively evaluate predictability of all six methods. We find that both BirgRank and AptRank outperform the previous methods, especially in missing function prediction when using only 10% of the data for training. The MATLAB code is available at https://github.rcac.purdue.edu/mgribsko/aptrank . gribskov@purdue.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Development of new smart materials and spinning systems inspired by natural silks and their applications

NASA Astrophysics Data System (ADS)

Cheng, Jie; Lee, Sang-Hoon

2015-12-01

Silks produced by spiders and silkworms are charming natural biological materials with highly optimized hierarchical structures and outstanding physicomechanical properties. The superior performance of silks relies on the integration of a unique protein sequence, a distinctive spinning process, and complex hierarchical structures. Silks have been prepared to form a variety of morphologies and are widely used in diverse applications, for example, in the textile industry, as drug delivery vehicles, and as tissue engineering scaffolds. This review presents an overview of the organization of natural silks, in which chemical and physical functions are optimized, as well as a range of new materials inspired by the desire to mimic natural silk structure and synthesis.

Twin boundary spacing effects on shock response and spall behaviors of hierarchically nanotwinned fcc metals

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

Yuan, Fuping, E-mail: fpyuan@lnm.imech.ac.cn; Chen, Liu, E-mail: chenliu@imech.ac.cn; Jiang, Ping, E-mail: jping@imech.ac.cn

2014-02-14

Atomistic deformation mechanisms of hierarchically nano-twinned (NT) Ag under shock conditions have been investigated using a series of large-scale molecular dynamics simulations. For the same grain size d and the same spacing of primary twins λ{sub 1}, the average flow stress behind the shock front in hierarchically NT Ag first increases with decreasing spacing of secondary twins λ{sub 2}, achieving a maximum at a critical λ{sub 2}, and then drops as λ{sub 2} decreases further. Above the critical λ{sub 2}, the deformation mechanisms are dominated by three type strengthening mechanisms: (a) partial dislocations emitted from grain boundaries (GBs) travel acrossmore » other boundaries; (b) partial dislocations emitted from twin boundaries (TBs) travel across other TBs; (c) formation of tertiary twins. Below the critical λ{sub 2}, the deformation mechanism are dominated by two softening mechanisms: (a) detwinning of secondary twins; (b) formation of new grains by cross slip of partial dislocations. Moreover, the twin-free nanocrystalline (NC) Ag is found to have lower average flow stress behind the shock front than those of all hierarchically NT Ag samples except the one with the smallest λ{sub 2} of 0.71 nm. No apparent correlation between the spall strength and λ{sub 2} is observed in hierarchically NT Ag, since voids always nucleate at both GBs and boundaries of the primary twins. However, twin-free NC Ag is found to have higher spall strength than hierarchically NT Ag. Voids can only nucleate from GBs for twin-free NC Ag, therefore, twin-free NC Ag has less nucleation sources along the shock direction when compared to hierarchically NT Ag, which requiring higher tensile stress to create spallation. These findings should contribute to the understandings of deformation mechanisms of hierarchically NT fcc metals under extreme deformation conditions.« less

Stochastic dynamics of virus capsid formation: direct versus hierarchical self-assembly

PubMed Central

2012-01-01

Background In order to replicate within their cellular host, many viruses have developed self-assembly strategies for their capsids which are sufficiently robust as to be reconstituted in vitro. Mathematical models for virus self-assembly usually assume that the bonds leading to cluster formation have constant reactivity over the time course of assembly (direct assembly). In some cases, however, binding sites between the capsomers have been reported to be activated during the self-assembly process (hierarchical assembly). Results In order to study possible advantages of such hierarchical schemes for icosahedral virus capsid assembly, we use Brownian dynamics simulations of a patchy particle model that allows us to switch binding sites on and off during assembly. For T1 viruses, we implement a hierarchical assembly scheme where inter-capsomer bonds become active only if a complete pentamer has been assembled. We find direct assembly to be favorable for reversible bonds allowing for repeated structural reorganizations, while hierarchical assembly is favorable for strong bonds with small dissociation rate, as this situation is less prone to kinetic trapping. However, at the same time it is more vulnerable to monomer starvation during the final phase. Increasing the number of initial monomers does have only a weak effect on these general features. The differences between the two assembly schemes become more pronounced for more complex virus geometries, as shown here for T3 viruses, which assemble through homogeneous pentamers and heterogeneous hexamers in the hierarchical scheme. In order to complement the simulations for this more complicated case, we introduce a master equation approach that agrees well with the simulation results. Conclusions Our analysis shows for which molecular parameters hierarchical assembly schemes can outperform direct ones and suggests that viruses with high bond stability might prefer hierarchical assembly schemes. These insights increase our physical understanding of an essential biological process, with many interesting potential applications in medicine and materials science. PMID:23244740

Modeling responses of large-river fish populations to global climate change through downscaling and incorporation of predictive uncertainty

USGS Publications Warehouse

Wildhaber, Mark L.; Wikle, Christopher K.; Anderson, Christopher J.; Franz, Kristie J.; Moran, Edward H.; Dey, Rima; Mader, Helmut; Kraml, Julia

2012-01-01

Climate change operates over a broad range of spatial and temporal scales. Understanding its effects on ecosystems requires multi-scale models. For understanding effects on fish populations of riverine ecosystems, climate predicted by coarse-resolution Global Climate Models must be downscaled to Regional Climate Models to watersheds to river hydrology to population response. An additional challenge is quantifying sources of uncertainty given the highly nonlinear nature of interactions between climate variables and community level processes. We present a modeling approach for understanding and accomodating uncertainty by applying multi-scale climate models and a hierarchical Bayesian modeling framework to Midwest fish population dynamics and by linking models for system components together by formal rules of probability. The proposed hierarchical modeling approach will account for sources of uncertainty in forecasts of community or population response. The goal is to evaluate the potential distributional changes in an ecological system, given distributional changes implied by a series of linked climate and system models under various emissions/use scenarios. This understanding will aid evaluation of management options for coping with global climate change. In our initial analyses, we found that predicted pallid sturgeon population responses were dependent on the climate scenario considered.

Functional adaptation of crustacean exoskeletal elements through structural and compositional diversity: a combined experimental and theoretical study.

PubMed

Fabritius, Helge-Otto; Ziegler, Andreas; Friák, Martin; Nikolov, Svetoslav; Huber, Julia; Seidl, Bastian H M; Ruangchai, Sukhum; Alagboso, Francisca I; Karsten, Simone; Lu, Jin; Janus, Anna M; Petrov, Michal; Zhu, Li-Fang; Hemzalová, Pavlína; Hild, Sabine; Raabe, Dierk; Neugebauer, Jörg

2016-09-09

The crustacean cuticle is a composite material that covers the whole animal and forms the continuous exoskeleton. Nano-fibers composed of chitin and protein molecules form most of the organic matrix of the cuticle that, at the macroscale, is organized in up to eight hierarchical levels. At least two of them, the exo- and endocuticle, contain a mineral phase of mainly Mg-calcite, amorphous calcium carbonate and phosphate. The high number of hierarchical levels and the compositional diversity provide a high degree of freedom for varying the physical, in particular mechanical, properties of the material. This makes the cuticle a versatile material ideally suited to form a variety of skeletal elements that are adapted to different functions and the eco-physiological strains of individual species. This review presents our recent analytical, experimental and theoretical studies on the cuticle, summarising at which hierarchical levels structure and composition are modified to achieve the required physical properties. We describe our multi-scale hierarchical modeling approach based on the results from these studies, aiming at systematically predicting the structure-composition-property relations of cuticle composites from the molecular level to the macro-scale. This modeling approach provides a tool to facilitate the development of optimized biomimetic materials within a knowledge-based design approach.

Efficient algorithms for accurate hierarchical clustering of huge datasets: tackling the entire protein space

PubMed Central

Loewenstein, Yaniv; Portugaly, Elon; Fromer, Menachem; Linial, Michal

2008-01-01

Motivation: UPGMA (average linking) is probably the most popular algorithm for hierarchical data clustering, especially in computational biology. However, UPGMA requires the entire dissimilarity matrix in memory. Due to this prohibitive requirement, UPGMA is not scalable to very large datasets. Application: We present a novel class of memory-constrained UPGMA (MC-UPGMA) algorithms. Given any practical memory size constraint, this framework guarantees the correct clustering solution without explicitly requiring all dissimilarities in memory. The algorithms are general and are applicable to any dataset. We present a data-dependent characterization of hardness and clustering efficiency. The presented concepts are applicable to any agglomerative clustering formulation. Results: We apply our algorithm to the entire collection of protein sequences, to automatically build a comprehensive evolutionary-driven hierarchy of proteins from sequence alone. The newly created tree captures protein families better than state-of-the-art large-scale methods such as CluSTr, ProtoNet4 or single-linkage clustering. We demonstrate that leveraging the entire mass embodied in all sequence similarities allows to significantly improve on current protein family clusterings which are unable to directly tackle the sheer mass of this data. Furthermore, we argue that non-metric constraints are an inherent complexity of the sequence space and should not be overlooked. The robustness of UPGMA allows significant improvement, especially for multidomain proteins, and for large or divergent families. Availability: A comprehensive tree built from all UniProt sequence similarities, together with navigation and classification tools will be made available as part of the ProtoNet service. A C++ implementation of the algorithm is available on request. Contact: lonshy@cs.huji.ac.il PMID:18586742

An improved approach to infer protein-protein interaction based on a hierarchical vector space model.

PubMed

Zhang, Jiongmin; Jia, Ke; Jia, Jinmeng; Qian, Ying

2018-04-27

Comparing and classifying functions of gene products are important in today's biomedical research. The semantic similarity derived from the Gene Ontology (GO) annotation has been regarded as one of the most widely used indicators for protein interaction. Among the various approaches proposed, those based on the vector space model are relatively simple, but their effectiveness is far from satisfying. We propose a Hierarchical Vector Space Model (HVSM) for computing semantic similarity between different genes or their products, which enhances the basic vector space model by introducing the relation between GO terms. Besides the directly annotated terms, HVSM also takes their ancestors and descendants related by "is_a" and "part_of" relations into account. Moreover, HVSM introduces the concept of a Certainty Factor to calibrate the semantic similarity based on the number of terms annotated to genes. To assess the performance of our method, we applied HVSM to Homo sapiens and Saccharomyces cerevisiae protein-protein interaction datasets. Compared with TCSS, Resnik, and other classic similarity measures, HVSM achieved significant improvement for distinguishing positive from negative protein interactions. We also tested its correlation with sequence, EC, and Pfam similarity using online tool CESSM. HVSM showed an improvement of up to 4% compared to TCSS, 8% compared to IntelliGO, 12% compared to basic VSM, 6% compared to Resnik, 8% compared to Lin, 11% compared to Jiang, 8% compared to Schlicker, and 11% compared to SimGIC using AUC scores. CESSM test showed HVSM was comparable to SimGIC, and superior to all other similarity measures in CESSM as well as TCSS. Supplementary information and the software are available at https://github.com/kejia1215/HVSM .

Partial unfolding and refolding for structure refinement: A unified approach of geometric simulations and molecular dynamics.

PubMed

Kumar, Avishek; Campitelli, Paul; Thorpe, M F; Ozkan, S Banu

2015-12-01

The most successful protein structure prediction methods to date have been template-based modeling (TBM) or homology modeling, which predicts protein structure based on experimental structures. These high accuracy predictions sometimes retain structural errors due to incorrect templates or a lack of accurate templates in the case of low sequence similarity, making these structures inadequate in drug-design studies or molecular dynamics simulations. We have developed a new physics based approach to the protein refinement problem by mimicking the mechanism of chaperons that rehabilitate misfolded proteins. The template structure is unfolded by selectively (targeted) pulling on different portions of the protein using the geometric based technique FRODA, and then refolded using hierarchically restrained replica exchange molecular dynamics simulations (hr-REMD). FRODA unfolding is used to create a diverse set of topologies for surveying near native-like structures from a template and to provide a set of persistent contacts to be employed during re-folding. We have tested our approach on 13 previous CASP targets and observed that this method of folding an ensemble of partially unfolded structures, through the hierarchical addition of contact restraints (that is, first local and then nonlocal interactions), leads to a refolding of the structure along with refinement in most cases (12/13). Although this approach yields refined models through advancement in sampling, the task of blind selection of the best refined models still needs to be solved. Overall, the method can be useful for improved sampling for low resolution models where certain of the portions of the structure are incorrectly modeled. © 2015 Wiley Periodicals, Inc.

Bayesian module identification from multiple noisy networks.

PubMed

Zamani Dadaneh, Siamak; Qian, Xiaoning

2016-12-01

Module identification has been studied extensively in order to gain deeper understanding of complex systems, such as social networks as well as biological networks. Modules are often defined as groups of vertices in these networks that are topologically cohesive with similar interaction patterns with the rest of the vertices. Most of the existing module identification algorithms assume that the given networks are faithfully measured without errors. However, in many real-world applications, for example, when analyzing protein-protein interaction networks from high-throughput profiling techniques, there is significant noise with both false positive and missing links between vertices. In this paper, we propose a new model for more robust module identification by taking advantage of multiple observed networks with significant noise so that signals in multiple networks can be strengthened and help improve the solution quality by combining information from various sources. We adopt a hierarchical Bayesian model to integrate multiple noisy snapshots that capture the underlying modular structure of the networks under study. By introducing a latent root assignment matrix and its relations to instantaneous module assignments in all the observed networks to capture the underlying modular structure and combine information across multiple networks, an efficient variational Bayes algorithm can be derived to accurately and robustly identify the underlying modules from multiple noisy networks. Experiments on synthetic and protein-protein interaction data sets show that our proposed model enhances both the accuracy and resolution in detecting cohesive modules, and it is less vulnerable to noise in the observed data. In addition, it shows higher power in predicting missing edges compared to individual-network methods.

Hierarchical species distribution models

USGS Publications Warehouse

Hefley, Trevor J.; Hooten, Mevin B.

2016-01-01

Determining the distribution pattern of a species is important to increase scientific knowledge, inform management decisions, and conserve biodiversity. To infer spatial and temporal patterns, species distribution models have been developed for use with many sampling designs and types of data. Recently, it has been shown that count, presence-absence, and presence-only data can be conceptualized as arising from a point process distribution. Therefore, it is important to understand properties of the point process distribution. We examine how the hierarchical species distribution modeling framework has been used to incorporate a wide array of regression and theory-based components while accounting for the data collection process and making use of auxiliary information. The hierarchical modeling framework allows us to demonstrate how several commonly used species distribution models can be derived from the point process distribution, highlight areas of potential overlap between different models, and suggest areas where further research is needed.

Hierarchical Chunking of Sequential Memory on Neuromorphic Architecture with Reduced Synaptic Plasticity

PubMed Central

Li, Guoqi; Deng, Lei; Wang, Dong; Wang, Wei; Zeng, Fei; Zhang, Ziyang; Li, Huanglong; Song, Sen; Pei, Jing; Shi, Luping

2016-01-01

Chunking refers to a phenomenon whereby individuals group items together when performing a memory task to improve the performance of sequential memory. In this work, we build a bio-plausible hierarchical chunking of sequential memory (HCSM) model to explain why such improvement happens. We address this issue by linking hierarchical chunking with synaptic plasticity and neuromorphic engineering. We uncover that a chunking mechanism reduces the requirements of synaptic plasticity since it allows applying synapses with narrow dynamic range and low precision to perform a memory task. We validate a hardware version of the model through simulation, based on measured memristor behavior with narrow dynamic range in neuromorphic circuits, which reveals how chunking works and what role it plays in encoding sequential memory. Our work deepens the understanding of sequential memory and enables incorporating it for the investigation of the brain-inspired computing on neuromorphic architecture. PMID:28066223

Hierarchical Bayes approach for subgroup analysis.

PubMed

Hsu, Yu-Yi; Zalkikar, Jyoti; Tiwari, Ram C

2017-01-01

In clinical data analysis, both treatment effect estimation and consistency assessment are important for a better understanding of the drug efficacy for the benefit of subjects in individual subgroups. The linear mixed-effects model has been used for subgroup analysis to describe treatment differences among subgroups with great flexibility. The hierarchical Bayes approach has been applied to linear mixed-effects model to derive the posterior distributions of overall and subgroup treatment effects. In this article, we discuss the prior selection for variance components in hierarchical Bayes, estimation and decision making of the overall treatment effect, as well as consistency assessment of the treatment effects across the subgroups based on the posterior predictive p-value. Decision procedures are suggested using either the posterior probability or the Bayes factor. These decision procedures and their properties are illustrated using a simulated example with normally distributed response and repeated measurements.

Bioinspired synthesis and self-assembly of hybrid organic–inorganic nanomaterials

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

Zhang, Honghu

Nature is replete with complex organic–inorganic hierarchical materials of diverse yet specific functions. These materials are intricately designed under physiological conditions through biomineralization and biological self-assembly processes. Tremendous efforts have been devoted to investigating mechanisms of such biomineralization and biological self-assembly processes as well as gaining inspiration to develop biomimetic methods for synthesis and self-assembly of functional nanomaterials. In this work, we focus on the bioinspired synthesis and self-assembly of functional inorganic nanomaterials templated by specialized macromolecules including proteins, DNA and polymers. The in vitro biomineralization process of the magnetite biomineralizing protein Mms6 has been investigated using small-angle X-ray scattering.more » Templated by Mms6, complex magnetic nanomaterials can be synthesized on surfaces and in the bulk. DNA and synthetic polymers have been exploited to construct macroscopic two- and three-dimensional (2D and 3D) superlattices of gold nanocrystals. Employing X-ray scattering and spectroscopy techniques, the self-assembled structures and the self-assembly mechanisms have been studied, and theoretical models have been developed. Our results show that specialized macromolecules including proteins, DNA and polymers act as effective templates for synthesis and self-assembly of nanomaterials. These bottom-up approaches provide promising routes to fabricate hybrid organic–inorganic nanomaterials with rationally designed hierarchical structures, targeting specific functions.« less

Understanding to Hierarchical Microstructures of Crab (Chinese hairy) Shell as a Natural Architecture

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

Chuanqiang, Zhou; Xiangxiang, Gong; School of Chemistry and Chemical Engineering, Yangzhou University, Yangzhou

This work was done to better understand the microstructures, composition and mechanical properties of Chinese hairy crab shell. For fully revealing its hierarchical microstructure, the crab shell was observed with electron microscope under different magnifications from different facets. XRD, EDS, FTIR and TGA techniques have been used to characterize the untreated and chemically-treated crab shells, which provided enough information to determine the species and relative content of components in this biomaterial. Combined the microstructures with constituents analysis, the structural principles of crab shell was detailedly realized from different structural levels beyond former reports. To explore the relationship between structure andmore » function, the mechanical properties of shell have been measured through performing tensile tests. The contributions of organics and minerals in shell to the mechanical properties were also discussed by measuring the tensile strength of de-calcification samples treated with HCl solution.« less

Fostering radical conceptual change through dual-situated learning model

NASA Astrophysics Data System (ADS)

She, Hsiao-Ching

2004-02-01

This article examines how the Dual-Situated Learning Model (DSLM) facilitates a radical change of concepts that involve the understanding of matter, process, and hierarchical attributes. The DSLM requires knowledge of students' prior beliefs of science concepts and the nature of these concepts. In addition, DSLM also serves two functions: it creates dissonance with students' prior knowledge by challenging their epistemological and ontological beliefs about science concepts, and it provides essential mental sets for students to reconstruct a more scientific view of the concepts. In this study, the concept heat transfer: heat conduction and convection, which requires an understanding of matter, process, and hierarchical attributes, was chosen to examine how DSLM can facilitate radical conceptual change among students. Results show that DSLM has great potential to foster a radical conceptual change process in learning heat transfer. Radical conceptual change can definitely be achieved and does not necessarily involve a slow or gradual process.

Mesoporous bioactive glass nanolayer-functionalized 3D-printed scaffolds for accelerating osteogenesis and angiogenesis

NASA Astrophysics Data System (ADS)

Zhang, Yali; Xia, Lunguo; Zhai, Dong; Shi, Mengchao; Luo, Yongxiang; Feng, Chun; Fang, Bing; Yin, Jingbo; Chang, Jiang; Wu, Chengtie

2015-11-01

The hierarchical microstructure, surface and interface of biomaterials are important factors influencing their bioactivity. Porous bioceramic scaffolds have been widely used for bone tissue engineering by optimizing their chemical composition and large-pore structure. However, the surface and interface of struts in bioceramic scaffolds are often ignored. The aim of this study is to incorporate hierarchical pores and bioactive components into the bioceramic scaffolds by constructing nanopores and bioactive elements on the struts of scaffolds and further improve their bone-forming activity. Mesoporous bioactive glass (MBG) modified β-tricalcium phosphate (MBG-β-TCP) scaffolds with a hierarchical pore structure and a functional strut surface (~100 nm of MBG nanolayer) were successfully prepared via 3D printing and spin coating. The compressive strength and apatite-mineralization ability of MBG-β-TCP scaffolds were significantly enhanced as compared to β-TCP scaffolds without the MBG nanolayer. The attachment, viability, alkaline phosphatase (ALP) activity, osteogenic gene expression (Runx2, BMP2, OPN and Col I) and protein expression (OPN, Col I, VEGF, HIF-1α) of rabbit bone marrow stromal cells (rBMSCs) as well as the attachment, viability and angiogenic gene expression (VEGF and HIF-1α) of human umbilical vein endothelial cells (HUVECs) in MBG-β-TCP scaffolds were significantly upregulated compared with conventional bioactive glass (BG)-modified β-TCP (BG-β-TCP) and pure β-TCP scaffolds. Furthermore, MBG-β-TCP scaffolds significantly enhanced the formation of new bone in vivo as compared to BG-β-TCP and β-TCP scaffolds. The results suggest that application of the MBG nanolayer to modify 3D-printed bioceramic scaffolds offers a new strategy to construct hierarchically porous scaffolds with significantly improved physicochemical and biological properties, such as mechanical properties, osteogenesis, angiogenesis and protein expression for bone tissue engineering applications, in which the incorporation of nanostructures and bioactive components into the scaffold struts synergistically play a key role in the improved bone formation.

Automated hierarchical classification of protein domain subfamilies based on functionally-divergent residue signatures

PubMed Central

2012-01-01

Background The NCBI Conserved Domain Database (CDD) consists of a collection of multiple sequence alignments of protein domains that are at various stages of being manually curated into evolutionary hierarchies based on conserved and divergent sequence and structural features. These domain models are annotated to provide insights into the relationships between sequence, structure and function via web-based BLAST searches. Results Here we automate the generation of conserved domain (CD) hierarchies using a combination of heuristic and Markov chain Monte Carlo (MCMC) sampling procedures and starting from a (typically very large) multiple sequence alignment. This procedure relies on statistical criteria to define each hierarchy based on the conserved and divergent sequence patterns associated with protein functional-specialization. At the same time this facilitates the sequence and structural annotation of residues that are functionally important. These statistical criteria also provide a means to objectively assess the quality of CD hierarchies, a non-trivial task considering that the protein subgroups are often very distantly related—a situation in which standard phylogenetic methods can be unreliable. Our aim here is to automatically generate (typically sub-optimal) hierarchies that, based on statistical criteria and visual comparisons, are comparable to manually curated hierarchies; this serves as the first step toward the ultimate goal of obtaining optimal hierarchical classifications. A plot of runtimes for the most time-intensive (non-parallelizable) part of the algorithm indicates a nearly linear time complexity so that, even for the extremely large Rossmann fold protein class, results were obtained in about a day. Conclusions This approach automates the rapid creation of protein domain hierarchies and thus will eliminate one of the most time consuming aspects of conserved domain database curation. At the same time, it also facilitates protein domain annotation by identifying those pattern residues that most distinguish each protein domain subgroup from other related subgroups. PMID:22726767

Quantifying the Hierarchical Order in Self-Aligned Carbon Nanotubes from Atomic to Micrometer Scale.

PubMed

Meshot, Eric R; Zwissler, Darwin W; Bui, Ngoc; Kuykendall, Tevye R; Wang, Cheng; Hexemer, Alexander; Wu, Kuang Jen J; Fornasiero, Francesco

2017-06-27

Fundamental understanding of structure-property relationships in hierarchically organized nanostructures is crucial for the development of new functionality, yet quantifying structure across multiple length scales is challenging. In this work, we used nondestructive X-ray scattering to quantitatively map the multiscale structure of hierarchically self-organized carbon nanotube (CNT) "forests" across 4 orders of magnitude in length scale, from 2.0 Å to 1.5 μm. Fully resolved structural features include the graphitic honeycomb lattice and interlayer walls (atomic), CNT diameter (nano), as well as the greater CNT ensemble (meso) and large corrugations (micro). Correlating orientational order across hierarchical levels revealed a cascading decrease as we probed finer structural feature sizes with enhanced sensitivity to small-scale disorder. Furthermore, we established qualitative relationships for single-, few-, and multiwall CNT forest characteristics, showing that multiscale orientational order is directly correlated with number density spanning 10 9 -10 12 cm -2 , yet order is inversely proportional to CNT diameter, number of walls, and atomic defects. Lastly, we captured and quantified ultralow-q meridional scattering features and built a phenomenological model of the large-scale CNT forest morphology, which predicted and confirmed that these features arise due to microscale corrugations along the vertical forest direction. Providing detailed structural information at multiple length scales is important for design and synthesis of CNT materials as well as other hierarchically organized nanostructures.

Hierarchical structure of the energy landscape of proteins revisited by time series analysis. II. Investigation of explicit solvent effects

NASA Astrophysics Data System (ADS)

Alakent, Burak; Camurdan, Mehmet C.; Doruker, Pemra

2005-10-01

Time series analysis tools are employed on the principal modes obtained from the Cα trajectories from two independent molecular-dynamics simulations of α-amylase inhibitor (tendamistat). Fluctuations inside an energy minimum (intraminimum motions), transitions between minima (interminimum motions), and relaxations in different hierarchical energy levels are investigated and compared with those encountered in vacuum by using different sampling window sizes and intervals. The low-frequency low-indexed mode relationship, established in vacuum, is also encountered in water, which shows the reliability of the important dynamics information offered by principal components analysis in water. It has been shown that examining a short data collection period (100ps) may result in a high population of overdamped modes, while some of the low-frequency oscillations (<10cm-1) can be captured in water by using a longer data collection period (1200ps). Simultaneous analysis of short and long sampling window sizes gives the following picture of the effect of water on protein dynamics. Water makes the protein lose its memory: future conformations are less dependent on previous conformations due to the lowering of energy barriers in hierarchical levels of the energy landscape. In short-time dynamics (<10ps), damping factors extracted from time series model parameters are lowered. For tendamistat, the friction coefficient in the Langevin equation is found to be around 40-60cm-1 for the low-indexed modes, compatible with literature. The fact that water has increased the friction and that on the other hand has lubrication effect at first sight contradicts. However, this comes about because water enhances the transitions between minima and forces the protein to reduce its already inherent inability to maintain oscillations observed in vacuum. Some of the frequencies lower than 10cm-1 are found to be overdamped, while those higher than 20cm-1 are slightly increased. As for the long-time dynamics in water, it is found that random-walk motion is maintained for approximately 200ps (about five times of that in vacuum) in the low-indexed modes, showing the lowering of energy barriers between the higher-level minima.

Protein functional landscapes, dynamics, allostery: a tortuous path towards a universal theoretical framework.

PubMed

Zhuravlev, Pavel I; Papoian, Garegin A

2010-08-01

Energy landscape theories have provided a common ground for understanding the protein folding problem, which once seemed to be overwhelmingly complicated. At the same time, the native state was found to be an ensemble of interconverting states with frustration playing a more important role compared to the folding problem. The landscape of the folded protein - the native landscape - is glassier than the folding landscape; hence, a general description analogous to the folding theories is difficult to achieve. On the other hand, the native basin phase volume is much smaller, allowing a protein to fully sample its native energy landscape on the biological timescales. Current computational resources may also be used to perform this sampling for smaller proteins, to build a 'topographical map' of the native landscape that can be used for subsequent analysis. Several major approaches to representing this topographical map are highlighted in this review, including the construction of kinetic networks, hierarchical trees and free energy surfaces with subsequent structural and kinetic analyses. In this review, we extensively discuss the important question of choosing proper collective coordinates characterizing functional motions. In many cases, the substates on the native energy landscape, which represent different functional states, can be used to obtain variables that are well suited for building free energy surfaces and analyzing the protein's functional dynamics. Normal mode analysis can provide such variables in cases where functional motions are dictated by the molecule's architecture. Principal component analysis is a more expensive way of inferring the essential variables from the protein's motions, one that requires a long molecular dynamics simulation. Finally, the two popular models for the allosteric switching mechanism, 'preexisting equilibrium' and 'induced fit', are interpreted within the energy landscape paradigm as extreme points of a continuum of transition mechanisms. Some experimental evidence illustrating each of these two models, as well as intermediate mechanisms, is presented and discussed.

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

Directed self-assembly of proteins into discrete radial patterns

PubMed Central

Thakur, Garima; Prashanthi, Kovur; Thundat, Thomas

2013-01-01

Unlike physical patterning of materials at nanometer scale, manipulating soft matter such as biomolecules into patterns is still in its infancy. Self-assembled monolayer (SAM) with surface density gradient has the capability to drive biomolecules in specific directions to create hierarchical and discrete structures. Here, we report on a two-step process of self-assembly of the human serum albumin (HSA) protein into discrete ring structures based on density gradient of SAM. The methodology involves first creating a 2-dimensional (2D) polyethylene glycol (PEG) islands with responsive carboxyl functionalities. Incubation of proteins on such pre-patterned surfaces results in direct self-assembly of protein molecules around PEG islands. Immobilization and adsorption of protein on such structures over time evolve into the self-assembled patterns. PMID:23719678

Using hierarchical clustering of secreted protein families to classify and rank candidate effectors of rust fungi

USDA-ARS?s Scientific Manuscript database

Rust fungi are obligate biotrophic pathogens causing considerable damage on crop plants. P. graminis f. sp. tritici, the causal agent of wheat stem rust, and M. larici-populina, the poplar rust pathogen, have strong deleterious impact on wheat and poplar wood production, respectively. The recently r...

CoMoDo: identifying dynamic protein domains based on covariances of motion.

PubMed

Wieninger, Silke A; Ullmann, G Matthias

2015-06-09

Most large proteins are built of several domains, compact units which enable functional protein motions. Different domain assignment approaches exist, which mostly rely on concepts of stability, folding, and evolution. We describe the automatic assignment method CoMoDo, which identifies domains based on protein dynamics. Covariances of atomic fluctuations, here calculated by an Elastic Network Model, are used to group residues into domains of different hierarchical levels. The so-called dynamic domains facilitate the study of functional protein motions involved in biological processes like ligand binding and signal transduction. By applying CoMoDo to a large number of proteins, we demonstrate that dynamic domains exhibit features absent in the commonly assigned structural domains, which can deliver insight into the interactions between domains and between subunits of multimeric proteins. CoMoDo is distributed as free open source software at www.bisb.uni-bayreuth.de/CoMoDo.html .

SHARPEN-systematic hierarchical algorithms for rotamers and proteins on an extended network.

PubMed

Loksha, Ilya V; Maiolo, James R; Hong, Cheng W; Ng, Albert; Snow, Christopher D

2009-04-30

Algorithms for discrete optimization of proteins play a central role in recent advances in protein structure prediction and design. We wish to improve the resources available for computational biologists to rapidly prototype such algorithms and to easily scale these algorithms to many processors. To that end, we describe the implementation and use of two new open source resources, citing potential benefits over existing software. We discuss CHOMP, a new object-oriented library for macromolecular optimization, and SHARPEN, a framework for scaling CHOMP scripts to many computers. These tools allow users to develop new algorithms for a variety of applications including protein repacking, protein-protein docking, loop rebuilding, or homology model remediation. Particular care was taken to allow modular energy function design; protein conformations may currently be scored using either the OPLSaa molecular mechanical energy function or an all-atom semiempirical energy function employed by Rosetta. (c) 2009 Wiley Periodicals, Inc.

Collaborative Hierarchy.

ERIC Educational Resources Information Center

Maris, Mariann

The University of Wisconsin-Milwaukee writing program is collaborative, not divisionary, as some, such as Jeanne Gunner, have suggested. Three terms are useful in understanding the relationships and ethics governing operations at Wisconsin-Milwaukee: (1) authority and collaboration; (2) hierarchical difference; (3) professional respect.…

Growth Mechanism of Pumpkin-Shaped Vaterite Hierarchical Structures

NASA Astrophysics Data System (ADS)

Ma, Guobin; Xu, Yifei; Wang, Mu

2015-03-01

CaCO3-based biominerals possess sophisticated hierarchical structures and promising mechanical properties. Recent researches imply that vaterite may play an important role in formation of CaCO3-based biominerals. However, as a less common polymorph of CaCO3, the growth mechanism of vaterite remains not very clear. Here we report the growth of a pumpkin-shaped vaterite hierarchical structure with a six-fold symmetrical axis and lamellar microstructure. We demonstrate that the growth is controlled by supersaturation and the intrinsic crystallographic anisotropy of vaterite. For the scenario of high supersaturation, the nucleation rate is higher than the lateral extension rate, favoring the ``double-leaf'' spherulitic growth. Meanwhile, nucleation occurs preferentially in < 11 2 0 > as determined by the crystalline structure of vaterite, modulating the grown products with a hexagonal symmetry. The results are beneficial for an in-depth understanding of the biomineralization of CaCO3. The growth mechanism may also be applicable to interpret the formation of similar hierarchical structures of other materials. The authors gratefully acknowledge the financial support from National Science Foundation of China (Grant Nos. 51172104 and 50972057) and National Key Basic Research Program of China (Grant No. 2010CB630705).

Construction of three-dimensional graphene interfaces into carbon fiber textiles for increasing deposition of nickel nanoparticles: flexible hierarchical magnetic textile composites for strong electromagnetic shielding

NASA Astrophysics Data System (ADS)

Bian, Xing-Ming; Liu, Lin; Li, Hai-Bing; Wang, Chan-Yuan; Xie, Qing; Zhao, Quan-Liang; Bi, Song; Hou, Zhi-Ling

2017-01-01

Since manipulating electromagnetic waves with electromagnetic active materials for environmental and electric engineering is a significant task, here a novel prototype is reported by introducing reduced graphene oxide (RGO) interfaces in carbon fiber (CF) networks for a hierarchical carbon fiber/reduced graphene oxide/nickel (CF-RGO-Ni) composite textile. Upon charaterizations of the microscopic morphologies, electrical and magnetic properties, the presence of three-dimensional RGO interfaces and bifunctional nickel nanoparticles substantially influences the related physical properties in the resulting hierarchical composite textiles. Eletromagnetic interference (EMI) shielding performance suggests that the hierarchical composite textiles hold a strong shielding effectiveness greater than 61 dB, showing greater advantages than conventional polymeric and foamy shielding composites. As a polymer-free lightweight structure, flexible CF-RGO-Ni composites of all electromagnetic active components offer unique understanding of the multi-scale and multiple mechanisms in electromagnetic energy consumption. Such a novel prototype of shielding structures along with convenient technology highlight a strategy to achieve high-performance EMI shielding, coupled with a universal approach for preparing advanced lightweight composites with graphene interfaces.

One-pot pseudomorphic crystallization of mesoporous porous silica to hierarchical porous zeolites

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

Xing, Jun-Ling; Jiang, Shu-Hua; Pang, Jun-Ling

2015-09-15

Hierarchically porous silica with mesopore and zeolitic micropore was synthesized via pseudomorphic crystallization under high-temperature hydrothermal treatment in the presence of cetyltrimethylammonium tosylate and tetrapropylammonium ions. A combined characterization using small-angle X-ray diffraction (XRD), nitrogen adsorption, high-resolution transmission electron microscopy (TEM), thermogravimetric analysis (TG), and elemental analysis showed that dual templates, CTA{sup +} and TPA{sup +} molecules, can work in a cooperative manner to synthesize mesoporous zeolite in a one-pot system by precisely tuning the reaction conditions, such as reaction time and temperature, and type and amount of heterometal atoms. It is found that the presence of Ti precursor ismore » critical to the successful synthesis of such nanostructure. It not only retards the nucleation and growth of crystalline MFI domains, but also acts as nano-binder or nano-glue to favor the assembly of zeolite nanoblocks. - Graphical abstract: Display Omitted - Highlights: • A facile method to synthesize mesoporous zeolites with hierarchical porosity was presented. • It gives a new insight into keeping the balance between mesoscopic and molecular ordering in hierarchical porous materials. • A new understanding on the solid–solid transformation mechanism for the synthesis of titanosilicate zeolites was proposed.« less

Emotional intelligence is a second-stratum factor of intelligence: evidence from hierarchical and bifactor models.

PubMed

MacCann, Carolyn; Joseph, Dana L; Newman, Daniel A; Roberts, Richard D

2014-04-01

This article examines the status of emotional intelligence (EI) within the structure of human cognitive abilities. To evaluate whether EI is a 2nd-stratum factor of intelligence, data were fit to a series of structural models involving 3 indicators each for fluid intelligence, crystallized intelligence, quantitative reasoning, visual processing, and broad retrieval ability, as well as 2 indicators each for emotion perception, emotion understanding, and emotion management. Unidimensional, multidimensional, hierarchical, and bifactor solutions were estimated in a sample of 688 college and community college students. Results suggest adequate fit for 2 models: (a) an oblique 8-factor model (with 5 traditional cognitive ability factors and 3 EI factors) and (b) a hierarchical solution (with cognitive g at the highest level and EI representing a 2nd-stratum factor that loads onto g at λ = .80). The acceptable relative fit of the hierarchical model confirms the notion that EI is a group factor of cognitive ability, marking the expression of intelligence in the emotion domain. The discussion proposes a possible expansion of Cattell-Horn-Carroll theory to include EI as a 2nd-stratum factor of similar standing to factors such as fluid intelligence and visual processing.

Construction of three-dimensional graphene interfaces into carbon fiber textiles for increasing deposition of nickel nanoparticles: flexible hierarchical magnetic textile composites for strong electromagnetic shielding.

PubMed

Bian, Xing-Ming; Liu, Lin; Li, Hai-Bing; Wang, Chan-Yuan; Xie, Qing; Zhao, Quan-Liang; Bi, Song; Hou, Zhi-Ling

2017-01-27

Since manipulating electromagnetic waves with electromagnetic active materials for environmental and electric engineering is a significant task, here a novel prototype is reported by introducing reduced graphene oxide (RGO) interfaces in carbon fiber (CF) networks for a hierarchical carbon fiber/reduced graphene oxide/nickel (CF-RGO-Ni) composite textile. Upon charaterizations of the microscopic morphologies, electrical and magnetic properties, the presence of three-dimensional RGO interfaces and bifunctional nickel nanoparticles substantially influences the related physical properties in the resulting hierarchical composite textiles. Eletromagnetic interference (EMI) shielding performance suggests that the hierarchical composite textiles hold a strong shielding effectiveness greater than 61 dB, showing greater advantages than conventional polymeric and foamy shielding composites. As a polymer-free lightweight structure, flexible CF-RGO-Ni composites of all electromagnetic active components offer unique understanding of the multi-scale and multiple mechanisms in electromagnetic energy consumption. Such a novel prototype of shielding structures along with convenient technology highlight a strategy to achieve high-performance EMI shielding, coupled with a universal approach for preparing advanced lightweight composites with graphene interfaces.

Uncovering the structure-function relationship in spider silk

NASA Astrophysics Data System (ADS)

Yarger, Jeffery L.; Cherry, Brian R.; van der Vaart, Arjan

2018-03-01

All spiders produce protein-based biopolymer fibres that we call silk. The most studied of these silks is spider dragline silk, which is very tough and relatively abundant compared with other types of spider silks. Considerable research has been devoted to understanding the relationship between the molecular structure and mechanical properties of spider dragline silks. In this Review, we overview experimental and computational studies that have provided a wealth of detail at the molecular level on the highly conserved repetitive core and terminal regions of spider dragline silk. We also discuss the role of the nanocrystalline β-sheets and amorphous regions in determining the properties of spider silk fibres, endowing them with strength and elasticity. Additionally, we outline imaging techniques and modelling studies that elucidate the importance of the hierarchical structure of silk fibres at the molecular level. These insights into structure-function relationships can guide the reverse engineering of spider silk to enable the production of superior synthetic fibres.

Subtle balance of tropoelastin molecular shape and flexibility regulates dynamics and hierarchical assembly.

PubMed

Yeo, Giselle C; Tarakanova, Anna; Baldock, Clair; Wise, Steven G; Buehler, Markus J; Weiss, Anthony S

2016-02-01

The assembly of the tropoelastin monomer into elastin is vital for conferring elasticity on blood vessels, skin, and lungs. Tropoelastin has dual needs for flexibility and structure in self-assembly. We explore the structure-dynamics-function interplay, consider the duality of molecular order and disorder, and identify equally significant functional contributions by local and global structures. To study these organizational stratifications, we perturb a key hinge region by expressing an exon that is universally spliced out in human tropoelastins. We find a herniated nanostructure with a displaced C terminus and explain by molecular modeling that flexible helices are replaced with substantial β sheets. We see atypical higher-order cross-linking and inefficient assembly into discontinuous, thick elastic fibers. We explain this dysfunction by correlating local and global structural effects with changes in the molecule's assembly dynamics. This work has general implications for our understanding of elastomeric proteins, which balance disordered regions with defined structural modules at multiple scales for functional assembly.

Crystal Structure of the 3.8-MDa Respiratory Supermolecule Hemocyanin at 3.0 Å Resolution.

PubMed

Gai, Zuoqi; Matsuno, Asuka; Kato, Koji; Kato, Sanae; Khan, Md Rafiqul Islam; Shimizu, Takeshi; Yoshioka, Takeya; Kato, Yuki; Kishimura, Hideki; Kanno, Gaku; Miyabe, Yoshikatsu; Terada, Tohru; Tanaka, Yoshikazu; Yao, Min

2015-12-01

Molluscan hemocyanin, a copper-containing oxygen transporter, is one of the largest known proteins. Although molluscan hemocyanins are currently applied as immunotherapeutic agents, their precise structure has not been determined because of their enormous size. Here, we have determined the first X-ray crystal structure of intact molluscan hemocyanin. The structure unveiled the architecture of the 3.8-MDa supermolecule composed of homologous functional units (FUs), wherein the dimers of FUs hierarchically associated to form the entire cylindrical decamer. Most of the specific inter-FU interactions were localized at narrow regions in the FU dimers, suggesting that rigid FU dimers formed by specific interactions assemble with flexibility. Furthermore, the roles of carbohydrates in assembly and allosteric effect, and conserved sulfur-containing residues in copper incorporation, were revealed. The precise structural information obtained in this study will accelerate our understanding of the molecular basis of hemocyanin and its future applications. Copyright © 2015 Elsevier Ltd. All rights reserved.

Theoretical Study of the Initial Stages of Self-Assembly of a Carboxysome’s Facet

DOE PAGES

Mahalik, J. P.; Brown, Kirsten A.; Cheng, Xiaolin; ...

2016-02-24

Bacterial microcompartments, BMCs, are organelles that exist within wide variety of bacteria and act as nanofactories. Among the different types of known BMCs, the carboxysome has been studied the most. The carboxysome plays an important role in the light-independent part of the photosynthesis process, where its icosahedral-like proteinaceous shell acts as a membrane that controls the transport of metabolites. Although a structural model exists for the carboxysome shell, it remains largely unknown how the shell proteins self-assemble. Understanding the self-assembly process can provide insights into how the shell affects the carboxysome s function and how it can be modified tomore » create new functionalities, such as artificial nanoreactors and artificial protein membranes. Here, we explain a theoretical framework that employs Monte Carlo simulations with a coarse-grain potential that reproduces well the atomistic potential of mean force; employing this framework, we are able to capture the initial stages of the 2D self-assembly of CcmK2 hexamers, a major protein-shell component of the carboxysome's facet. The simulations reveal that CcmK2 hexamers self-assemble into clusters that resemble what was seen experimentally in 2D layers. Further analysis of the simulation results suggests that the 2D self-assembly of carboxysome s facets is driven by a nucleation growth process, which in turn could play an important role in the hierarchical self- assembly of BMC shells in general.« less

SCPS: a fast implementation of a spectral method for detecting protein families on a genome-wide scale.

PubMed

Nepusz, Tamás; Sasidharan, Rajkumar; Paccanaro, Alberto

2010-03-09

An important problem in genomics is the automatic inference of groups of homologous proteins from pairwise sequence similarities. Several approaches have been proposed for this task which are "local" in the sense that they assign a protein to a cluster based only on the distances between that protein and the other proteins in the set. It was shown recently that global methods such as spectral clustering have better performance on a wide variety of datasets. However, currently available implementations of spectral clustering methods mostly consist of a few loosely coupled Matlab scripts that assume a fair amount of familiarity with Matlab programming and hence they are inaccessible for large parts of the research community. SCPS (Spectral Clustering of Protein Sequences) is an efficient and user-friendly implementation of a spectral method for inferring protein families. The method uses only pairwise sequence similarities, and is therefore practical when only sequence information is available. SCPS was tested on difficult sets of proteins whose relationships were extracted from the SCOP database, and its results were extensively compared with those obtained using other popular protein clustering algorithms such as TribeMCL, hierarchical clustering and connected component analysis. We show that SCPS is able to identify many of the family/superfamily relationships correctly and that the quality of the obtained clusters as indicated by their F-scores is consistently better than all the other methods we compared it with. We also demonstrate the scalability of SCPS by clustering the entire SCOP database (14,183 sequences) and the complete genome of the yeast Saccharomyces cerevisiae (6,690 sequences). Besides the spectral method, SCPS also implements connected component analysis and hierarchical clustering, it integrates TribeMCL, it provides different cluster quality tools, it can extract human-readable protein descriptions using GI numbers from NCBI, it interfaces with external tools such as BLAST and Cytoscape, and it can produce publication-quality graphical representations of the clusters obtained, thus constituting a comprehensive and effective tool for practical research in computational biology. Source code and precompiled executables for Windows, Linux and Mac OS X are freely available at http://www.paccanarolab.org/software/scps.

Systematic, spatial imaging of large multimolecular assemblies and the emerging principles of supramolecular order in biological systems

PubMed Central

Schubert, Walter

2013-01-01

Understanding biological systems at the level of their relational (emergent) molecular properties in functional protein networks relies on imaging methods, able to spatially resolve a tissue or a cell as a giant, non-random, topologically defined collection of interacting supermolecules executing myriads of subcellular mechanisms. Here, the development and findings of parameter-unlimited functional super-resolution microscopy are described—a technology based on the fluorescence imaging cycler (IC) principle capable of co-mapping thousands of distinct biomolecular assemblies at high spatial resolution and differentiation (<40 nm distances). It is shown that the subcellular and transcellular features of such supermolecules can be described at the compositional and constitutional levels; that the spatial connection, relational stoichiometry, and topology of supermolecules generate hitherto unrecognized functional self-segmentation of biological tissues; that hierarchical features, common to thousands of simultaneously imaged supermolecules, can be identified; and how the resulting supramolecular order relates to spatial coding of cellular functionalities in biological systems. A large body of observations with IC molecular systems microscopy collected over 20 years have disclosed principles governed by a law of supramolecular segregation of cellular functionalities. This pervades phenomena, such as exceptional orderliness, functional selectivity, combinatorial and spatial periodicity, and hierarchical organization of large molecular systems, across all species investigated so far. This insight is based on the high degree of specificity, selectivity, and sensitivity of molecular recognition processes for fluorescence imaging beyond the spectral resolution limit, using probe libraries controlled by ICs. © 2013 The Authors. Journal of Molecular Recognition published by John Wiley & Sons, Ltd. PMID:24375580

Regional Modeling of Ecosystem Services Provided by Stream Fishes

EPA Science Inventory

Fish habitat and biodiversity for fish are valuable ecosystem services provided by rivers. Future land development and climate change will likely alter these services, and an understanding of these responses can guide management and restoration priorities. We used hierarchical mo...

A hierarchical competing systems model of the emergence and early development of executive function

PubMed Central

Marcovitch, Stuart; Zelazo, Philip David

2010-01-01

The hierarchical competing systems model (HCSM) provides a framework for understanding the emergence and early development of executive function – the cognitive processes underlying the conscious control of behavior – in the context of search for hidden objects. According to this model, behavior is determined by the joint influence of a developmentally invariant habit system and a conscious representational system that becomes increasingly influential as children develop. This article describes a computational formalization of the HCSM, reviews behavioral and computational research consistent with the model, and suggests directions for future research on the development of executive function. PMID:19120405

Multi-label learning with fuzzy hypergraph regularization for protein subcellular location prediction.

PubMed

Chen, Jing; Tang, Yuan Yan; Chen, C L Philip; Fang, Bin; Lin, Yuewei; Shang, Zhaowei

2014-12-01

Protein subcellular location prediction aims to predict the location where a protein resides within a cell using computational methods. Considering the main limitations of the existing methods, we propose a hierarchical multi-label learning model FHML for both single-location proteins and multi-location proteins. The latent concepts are extracted through feature space decomposition and label space decomposition under the nonnegative data factorization framework. The extracted latent concepts are used as the codebook to indirectly connect the protein features to their annotations. We construct dual fuzzy hypergraphs to capture the intrinsic high-order relations embedded in not only feature space, but also label space. Finally, the subcellular location annotation information is propagated from the labeled proteins to the unlabeled proteins by performing dual fuzzy hypergraph Laplacian regularization. The experimental results on the six protein benchmark datasets demonstrate the superiority of our proposed method by comparing it with the state-of-the-art methods, and illustrate the benefit of exploiting both feature correlations and label correlations.

Genomic analysis of the hierarchical structure of regulatory networks

PubMed Central

Yu, Haiyuan; Gerstein, Mark

2006-01-01

A fundamental question in biology is how the cell uses transcription factors (TFs) to coordinate the expression of thousands of genes in response to various stimuli. The relationships between TFs and their target genes can be modeled in terms of directed regulatory networks. These relationships, in turn, can be readily compared with commonplace “chain-of-command” structures in social networks, which have characteristic hierarchical layouts. Here, we develop algorithms for identifying generalized hierarchies (allowing for various loop structures) and use these approaches to illuminate extensive pyramid-shaped hierarchical structures existing in the regulatory networks of representative prokaryotes (Escherichia coli) and eukaryotes (Saccharomyces cerevisiae), with most TFs at the bottom levels and only a few master TFs on top. These masters are situated near the center of the protein–protein interaction network, a different type of network from the regulatory one, and they receive most of the input for the whole regulatory hierarchy through protein interactions. Moreover, they have maximal influence over other genes, in terms of affecting expression-level changes. Surprisingly, however, TFs at the bottom of the regulatory hierarchy are more essential to the viability of the cell. Finally, one might think master TFs achieve their wide influence through directly regulating many targets, but TFs with most direct targets are in the middle of the hierarchy. We find, in fact, that these midlevel TFs are “control bottlenecks” in the hierarchy, and this great degree of control for “middle managers” has parallels in efficient social structures in various corporate and governmental settings. PMID:17003135

How children perceive fractals: Hierarchical self-similarity and cognitive development

PubMed Central

Martins, Maurício Dias; Laaha, Sabine; Freiberger, Eva Maria; Choi, Soonja; Fitch, W. Tecumseh

2014-01-01

The ability to understand and generate hierarchical structures is a crucial component of human cognition, available in language, music, mathematics and problem solving. Recursion is a particularly useful mechanism for generating complex hierarchies by means of self-embedding rules. In the visual domain, fractals are recursive structures in which simple transformation rules generate hierarchies of infinite depth. Research on how children acquire these rules can provide valuable insight into the cognitive requirements and learning constraints of recursion. Here, we used fractals to investigate the acquisition of recursion in the visual domain, and probed for correlations with grammar comprehension and general intelligence. We compared second (n = 26) and fourth graders (n = 26) in their ability to represent two types of rules for generating hierarchical structures: Recursive rules, on the one hand, which generate new hierarchical levels; and iterative rules, on the other hand, which merely insert items within hierarchies without generating new levels. We found that the majority of fourth graders, but not second graders, were able to represent both recursive and iterative rules. This difference was partially accounted by second graders’ impairment in detecting hierarchical mistakes, and correlated with between-grade differences in grammar comprehension tasks. Empirically, recursion and iteration also differed in at least one crucial aspect: While the ability to learn recursive rules seemed to depend on the previous acquisition of simple iterative representations, the opposite was not true, i.e., children were able to acquire iterative rules before they acquired recursive representations. These results suggest that the acquisition of recursion in vision follows learning constraints similar to the acquisition of recursion in language, and that both domains share cognitive resources involved in hierarchical processing. PMID:24955884

Manufacture and characterisation of EmDerm-novel hierarchically structured bio-active scaffolds for tissue regeneration.

PubMed

Lim, Xuxin; Potter, Matthew; Cui, Zhanfeng; Dye, Julian F

2018-06-05

There are significant challenges for using emulsion templating as a method of manufacturing macro-porous protein scaffolds. Issues include protein denaturation by adsorption at hydrophobic interfaces, emulsion instability, oil droplet and surfactant removal after protein gelation, and compatible cross-linking methods. We investigated an oil-in-water macro-emulsion stabilised with a surfactant blend, as a template for manufacturing protein-based nano-structured bio-intelligent scaffolds (EmDerm) with tuneable micro-scale porosity for tissue regeneration. Prototype EmDerm scaffolds were made using either collagen, through thermal gelation, fibrin, through enzymatic coagulation or collagen-fibrin composite. Pore size was controlled via surfactant-to-oil phase ratio. Scaffolds were crosslink-stabilised with EDC/NHS for varying durations. Scaffold micro-architecture and porosity were characterised with SEM, and mechanical properties by tensiometry. Hydrolytic and proteolytic degradation profiles were quantified by mass decrease over time. Human dermal fibroblasts, endothelial cells and bone marrow derived mesenchymal stem cells were used to investigate cytotoxicity and cell proliferation within each scaffold. EmDerm scaffolds showed nano-scale based hierarchical structures, with mean pore diameters ranging from 40-100 microns. The Young's modulus range was 1.1-2.9 MPa, and ultimate tensile strength was 4-16 MPa. Degradation rate was related to cross-linking duration. Each EmDerm scaffold supported excellent cell ingress and proliferation compared to the reference materials Integra™ and Matriderm™. Emulsion templating is a novel rapid method of fabricating nano-structured fibrous protein scaffolds with micro-scale pore dimensions. These scaffolds hold promising clinical potential for regeneration of the dermis and other soft tissues, e.g., for burns or chronic wound therapies.

Exploring factors that influence the spread and sustainability of a dysphagia innovation: an instrumental case study.

PubMed

Ilott, Irene; Gerrish, Kate; Eltringham, Sabrina A; Taylor, Carolyn; Pownall, Sue

2016-08-18

Swallowing difficulties challenge patient safety due to the increased risk of malnutrition, dehydration and aspiration pneumonia. A theoretically driven study was undertaken to examine the spread and sustainability of a locally developed innovation that involved using the Inter-Professional Dysphagia Framework to structure education for the workforce. A conceptual framework with 3 spread strategies (hierarchical control, participatory adaptation and facilitated evolution) was blended with a processual approach to sustaining organisational change. The aim was to understand the processes, mechanism and outcomes associated with the spread and sustainability of this safety initiative. An instrumental case study, prospectively tracked a dysphagia innovation for 34 months (April 2011 to January 2014) in a large health care organisation in England. A train-the-trainer intervention (as participatory adaptation) was deployed on care pathways for stroke and fractured neck of femur. Data were collected at the organisational and clinical level through interviews (n = 30) and document review. The coding frame combined the processual approach with the spread mechanisms. Pre-determined outcomes included the number of staff trained about dysphagia and impact related to changes in practice. The features and processes associated with hierarchical control and participatory adaptation were identified. Leadership, critical junctures, temporality and making the innovation routine were aspects of hierarchical control. Participatory adaptation was evident on the care pathways through stakeholder responses, workload and resource pressures. Six of the 25 ward based trainers cascaded the dysphagia training. The expected outcomes were achieved when the top-down mandate (hierarchical control) was supplemented by local engagement and support (participatory adaptation). Frameworks for spread and sustainability were combined to create a 'small theory' that described the interventions, the processes and desired outcomes a priori. This novel methodological approach confirmed what is known about spread and sustainability, highlighted the particularity of change and offered new insights into the factors associated with hierarchical control and participatory adaptation. The findings illustrate the dualities of organisational change as universal and context specific; as particular and amendable to theoretical generalisation. Appreciating these dualities may contribute to understanding why many innovations fail to become routine.

7TMRmine: a Web server for hierarchical mining of 7TMR proteins

PubMed Central

Lu, Guoqing; Wang, Zhifang; Jones, Alan M; Moriyama, Etsuko N

2009-01-01

Background Seven-transmembrane region-containing receptors (7TMRs) play central roles in eukaryotic signal transduction. Due to their biomedical importance, thorough mining of 7TMRs from diverse genomes has been an active target of bioinformatics and pharmacogenomics research. The need for new and accurate 7TMR/GPCR prediction tools is paramount with the accelerated rate of acquisition of diverse sequence information. Currently available and often used protein classification methods (e.g., profile hidden Markov Models) are highly accurate for identifying their membership information among already known 7TMR subfamilies. However, these alignment-based methods are less effective for identifying remote similarities, e.g., identifying proteins from highly divergent or possibly new 7TMR families. In this regard, more sensitive (e.g., alignment-free) methods are needed to complement the existing protein classification methods. A better strategy would be to combine different classifiers, from more specific to more sensitive methods, to identify a broader spectrum of 7TMR protein candidates. Description We developed a Web server, 7TMRmine, by integrating alignment-free and alignment-based classifiers specifically trained to identify candidate 7TMR proteins as well as transmembrane (TM) prediction methods. This new tool enables researchers to easily assess the distribution of GPCR functionality in diverse genomes or individual newly-discovered proteins. 7TMRmine is easily customized and facilitates exploratory analysis of diverse genomes. Users can integrate various alignment-based, alignment-free, and TM-prediction methods in any combination and in any hierarchical order. Sixteen classifiers (including two TM-prediction methods) are available on the 7TMRmine Web server. Not only can the 7TMRmine tool be used for 7TMR mining, but also for general TM-protein analysis. Users can submit protein sequences for analysis, or explore pre-analyzed results for multiple genomes. The server currently includes prediction results and the summary statistics for 68 genomes. Conclusion 7TMRmine facilitates the discovery of 7TMR proteins. By combining prediction results from different classifiers in a multi-level filtering process, prioritized sets of 7TMR candidates can be obtained for further investigation. 7TMRmine can be also used as a general TM-protein classifier. Comparisons of TM and 7TMR protein distributions among 68 genomes revealed interesting differences in evolution of these protein families among major eukaryotic phyla. PMID:19538753

Psychological autonomy and hierarchical relatedness as organizers of developmental pathways

PubMed Central

Keller, Heidi

2016-01-01

The definition of self and others can be regarded as embodying the two dimensions of autonomy and relatedness. Autonomy and relatedness are two basic human needs and cultural constructs at the same time. This implies that they may be differently defined yet remain equally important. The respective understanding of autonomy and relatedness is socialized during the everyday experiences of daily life routines from birth on. In this paper, two developmental pathways are portrayed that emphasize different conceptions of autonomy and relatedness that are adaptive in two different environmental contexts with very different affordances and constraints. Western middle-class children are socialized towards psychological autonomy, i.e. the primacy of own intentions, wishes, individual preferences and emotions affording a definition of relatedness as psychological negotiable construct. Non-Western subsistence farmer children are socialized towards hierarchical relatedness, i.e. positioning oneself into the hierarchical structure of a communal system affording a definition of autonomy as action oriented, based on responsibility and obligations. Infancy can be regarded as a cultural lens through which to study the different socialization agendas. Parenting strategies that aim at supporting these different socialization goals in German and Euro-American parents on the one hand and Nso farmers from North Western Cameroon on the other hand are described. It is concluded that different pathways need to be considered in order to understand human psychology from a global perspective. PMID:26644589

Psychological autonomy and hierarchical relatedness as organizers of developmental pathways.

PubMed

Keller, Heidi

2016-01-19

The definition of self and others can be regarded as embodying the two dimensions of autonomy and relatedness. Autonomy and relatedness are two basic human needs and cultural constructs at the same time. This implies that they may be differently defined yet remain equally important. The respective understanding of autonomy and relatedness is socialized during the everyday experiences of daily life routines from birth on. In this paper, two developmental pathways are portrayed that emphasize different conceptions of autonomy and relatedness that are adaptive in two different environmental contexts with very different affordances and constraints. Western middle-class children are socialized towards psychological autonomy, i.e. the primacy of own intentions, wishes, individual preferences and emotions affording a definition of relatedness as psychological negotiable construct. Non-Western subsistence farmer children are socialized towards hierarchical relatedness, i.e. positioning oneself into the hierarchical structure of a communal system affording a definition of autonomy as action oriented, based on responsibility and obligations. Infancy can be regarded as a cultural lens through which to study the different socialization agendas. Parenting strategies that aim at supporting these different socialization goals in German and Euro-American parents on the one hand and Nso farmers from North Western Cameroon on the other hand are described. It is concluded that different pathways need to be considered in order to understand human psychology from a global perspective. © 2015 The Author(s).

Materials taking a lesson from nature.

PubMed

Tian, Liangfei; Croisier, Emmanuel; Frauenrath, Holger

2013-01-01

Structural biomaterials with their often extraordinary properties and versatile functions are typically constructed from very limited sets of building blocks and types of supramolecular interactions. In this review we discuss how, inspired by nature's design principles for protein-based materials, oligopeptide-modified polymers can be used as a versatile toolbox to program nanostructure and hierarchical structure formation in synthetic materials.

Relating soil geochemical properties to arsenic bioaccessibility through hierarchical modeling.

EPA Science Inventory

Interest in improved understanding of relationships among soil properties and arsenic (As) bioaccessibility has motivated the use of regression models for As bioaccessibility prediction. However, limits in the numbers and types of soils included in previous studies restrict the u...

Upscaling issues in ecohydrological observations

USDA-ARS?s Scientific Manuscript database

Scale is recognized as a central concept in the description of the hierarchical organization of our world. Pressing environmental and societal problems such require an understanding of how processes operate at different scales, and how they can be linked across scales. Ecohydrology as many other dis...

Matriarch: A Python Library for Materials Architecture.

PubMed

Giesa, Tristan; Jagadeesan, Ravi; Spivak, David I; Buehler, Markus J

2015-10-12

Biological materials, such as proteins, often have a hierarchical structure ranging from basic building blocks at the nanoscale (e.g., amino acids) to assembled structures at the macroscale (e.g., fibers). Current software for materials engineering allows the user to specify polypeptide chains and simple secondary structures prior to molecular dynamics simulation, but is not flexible in terms of the geometric arrangement of unequilibrated structures. Given some knowledge of a larger-scale structure, instructing the software to create it can be very difficult and time-intensive. To this end, the present paper reports a mathematical language, using category theory, to describe the architecture of a material, i.e., its set of building blocks and instructions for combining them. While this framework applies to any hierarchical material, here we concentrate on proteins. We implement this mathematical language as an open-source Python library called Matriarch. It is a domain-specific language that gives the user the ability to create almost arbitrary structures with arbitrary amino acid sequences and, from them, generate Protein Data Bank (PDB) files. In this way, Matriarch is more powerful than commercial software now available. Matriarch can be used in tandem with molecular dynamics simulations and helps engineers design and modify biologically inspired materials based on their desired functionality. As a case study, we use our software to alter both building blocks and building instructions for tropocollagen, and determine their effect on its structure and mechanical properties.

Haemopoietic stem cells.

PubMed

Bellantuono, Ilaria

2004-04-01

Considerable effort has been made in recent years in understanding the mechanisms that govern stem cell generation, proliferation, self-renewal, commitment and lately plasticity. In the development of the haemopoietic system during embryonic and fetal life the notion of different pools of stem cells arising from the endothelium is gaining consensus. Gene expression profiling of populations of stem cells is bringing to light categories of genes important for self-renewal or commitment. Besides the role of transcription factors in lineage decision, the role of soluble factors and transmembrane proteins, very active at the time of embryo development, are taking central stage in the maintenance and in vitro expansion of haemopoietic stem cells (HSCs). The hierarchical model of haemopoietic development is being questioned with reports of lineage switching and plasticity of haemopoietic stem cells to non-haemopoietic cells. Yet the understanding of the overall process is still very fragmented and hypothetical. This is mainly due to the absence of appropriate markers to enable selection of homogeneous stem cell populations and the need to rely on retrospective functional assays, able only to determine the overall behaviour of a population of cells. This review is intended to be an overview of the haemopoietic system and a critical re-visitation of issues such as plasticity and self-renewal important for therapeutic applications of haemopoietic stem cells.

Plasma Membrane is Compartmentalized by a Self-Similar Cortical Actin Meshwork

NASA Astrophysics Data System (ADS)

Sadegh, Sanaz; Higgins, Jenny L.; Mannion, Patrick C.; Tamkun, Michael M.; Krapf, Diego

2017-01-01

A broad range of membrane proteins display anomalous diffusion on the cell surface. Different methods provide evidence for obstructed subdiffusion and diffusion on a fractal space, but the underlying structure inducing anomalous diffusion has never been visualized because of experimental challenges. We addressed this problem by imaging the cortical actin at high resolution while simultaneously tracking individual membrane proteins in live mammalian cells. Our data confirm that actin introduces barriers leading to compartmentalization of the plasma membrane and that membrane proteins are transiently confined within actin fences. Furthermore, superresolution imaging shows that the cortical actin is organized into a self-similar meshwork. These results present a hierarchical nanoscale picture of the plasma membrane.

Estimation and Application of Ecological Memory Functions in Time and Space

NASA Astrophysics Data System (ADS)

Itter, M.; Finley, A. O.; Dawson, A.

2017-12-01

A common goal in quantitative ecology is the estimation or prediction of ecological processes as a function of explanatory variables (or covariates). Frequently, the ecological process of interest and associated covariates vary in time, space, or both. Theory indicates many ecological processes exhibit memory to local, past conditions. Despite such theoretical understanding, few methods exist to integrate observations from the recent past or within a local neighborhood as drivers of these processes. We build upon recent methodological advances in ecology and spatial statistics to develop a Bayesian hierarchical framework to estimate so-called ecological memory functions; that is, weight-generating functions that specify the relative importance of local, past covariate observations to ecological processes. Memory functions are estimated using a set of basis functions in time and/or space, allowing for flexible ecological memory based on a reduced set of parameters. Ecological memory functions are entirely data driven under the Bayesian hierarchical framework—no a priori assumptions are made regarding functional forms. Memory function uncertainty follows directly from posterior distributions for model parameters allowing for tractable propagation of error to predictions of ecological processes. We apply the model framework to simulated spatio-temporal datasets generated using memory functions of varying complexity. The framework is also applied to estimate the ecological memory of annual boreal forest growth to local, past water availability. Consistent with ecological understanding of boreal forest growth dynamics, memory to past water availability peaks in the year previous to growth and slowly decays to zero in five to eight years. The Bayesian hierarchical framework has applicability to a broad range of ecosystems and processes allowing for increased understanding of ecosystem responses to local and past conditions and improved prediction of ecological processes.

Relationship between global structural parameters and Enzyme Commission hierarchy: implications for function prediction.

PubMed

Boareto, Marcelo; Yamagishi, Michel E B; Caticha, Nestor; Leite, Vitor B P

2012-10-01

In protein databases there is a substantial number of proteins structurally determined but without function annotation. Understanding the relationship between function and structure can be useful to predict function on a large scale. We have analyzed the similarities in global physicochemical parameters for a set of enzymes which were classified according to the four Enzyme Commission (EC) hierarchical levels. Using relevance theory we introduced a distance between proteins in the space of physicochemical characteristics. This was done by minimizing a cost function of the metric tensor built to reflect the EC classification system. Using an unsupervised clustering method on a set of 1025 enzymes, we obtained no relevant clustering formation compatible with EC classification. The distance distributions between enzymes from the same EC group and from different EC groups were compared by histograms. Such analysis was also performed using sequence alignment similarity as a distance. Our results suggest that global structure parameters are not sufficient to segregate enzymes according to EC hierarchy. This indicates that features essential for function are rather local than global. Consequently, methods for predicting function based on global attributes should not obtain high accuracy in main EC classes prediction without relying on similarities between enzymes from training and validation datasets. Furthermore, these results are consistent with a substantial number of studies suggesting that function evolves fundamentally by recruitment, i.e., a same protein motif or fold can be used to perform different enzymatic functions and a few specific amino acids (AAs) are actually responsible for enzyme activity. These essential amino acids should belong to active sites and an effective method for predicting function should be able to recognize them. Copyright © 2012 Elsevier Ltd. All rights reserved.

Facile method for preparing superoleophobic surfaces with hierarchical microcubic/nanowire structures

NASA Astrophysics Data System (ADS)

Kwak, Wonshik; Hwang, Woonbong

2016-02-01

To facilitate the fabrication of superoleophobic surfaces having hierarchical microcubic/nanowire structures (HMNS), even for low surface tension liquids including octane (surface tension = 21.1 mN m-1), and to understand the influences of surface structures on the oleophobicity, we developed a convenient method to achieve superoleophobic surfaces on aluminum substrates using chemical acid etching, anodization and fluorination treatment. The liquid repellency of the structured surface was validated through observable experimental results the contact and sliding angle measurements. The etching condition required to ensure high surface roughness was established, and an optimal anodizing condition was determined, as a critical parameter in building the superoleophobicity. The microcubic structures formed by acid etching are essential for achieving the formation of the hierarchical structure, and therefore, the nanowire structures formed by anodization lead to an enhancement of the superoleophobicity for low surface tension liquids. Under optimized morphology by microcubic/nanowire structures with fluorination treatment, the contact angle over 150° and the sliding angle less than 10° are achieved even for octane.

Evading the strength–ductility trade-off dilemma in steel through gradient hierarchical nanotwins

PubMed Central

Wei, Yujie; Li, Yongqiang; Zhu, Lianchun; Liu, Yao; Lei, Xianqi; Wang, Gang; Wu, Yanxin; Mi, Zhenli; Liu, Jiabin; Wang, Hongtao; Gao, Huajian

2014-01-01

The strength–ductility trade-off has been a long-standing dilemma in materials science. This has limited the potential of many structural materials, steels in particular. Here we report a way of enhancing the strength of twinning-induced plasticity steel at no ductility trade-off. After applying torsion to cylindrical twinning-induced plasticity steel samples to generate a gradient nanotwinned structure along the radial direction, we find that the yielding strength of the material can be doubled at no reduction in ductility. It is shown that this evasion of strength–ductility trade-off is due to the formation of a gradient hierarchical nanotwinned structure during pre-torsion and subsequent tensile deformation. A series of finite element simulations based on crystal plasticity are performed to understand why the gradient twin structure can cause strengthening and ductility retention, and how sequential torsion and tension lead to the observed hierarchical nanotwinned structure through activation of different twinning systems. PMID:24686581

Fractal multi-level organisation of human groups in a virtual world.

PubMed

Fuchs, Benedikt; Sornette, Didier; Thurner, Stefan

2014-10-06

Humans are fundamentally social. They form societies which consist of hierarchically layered nested groups of various quality, size, and structure. The anthropologic literature has classified these groups as support cliques, sympathy groups, bands, cognitive groups, tribes, linguistic groups, and so on. Anthropologic data show that, on average, each group consists of approximately three subgroups. However, a general understanding of the structural dependence of groups at different layers is largely missing. We extend these early findings to a very large high-precision large-scale internet-based social network data. We analyse the organisational structure of a complete, multi-relational, large social multiplex network of a human society consisting of about 400,000 odd players of an open-ended massive multiplayer online game for which we know all about their various group memberships at different layers. Remarkably, the online players' society exhibits the same type of structured hierarchical layers as found in hunter-gatherer societies. Our findings suggest that the hierarchical organisation of human society is deeply nested in human psychology.

Application of X-ray and neutron small angle scattering techniques to study the hierarchical structure of plant cell walls: a review.

PubMed

Martínez-Sanz, Marta; Gidley, Michael J; Gilbert, Elliot P

2015-07-10

Plant cell walls present an extremely complex structure of hierarchically assembled cellulose microfibrils embedded in a multi-component matrix. The biosynthesis process determines the mechanism of cellulose crystallisation and assembly, as well as the interaction of cellulose with other cell wall components. Thus, a knowledge of cellulose microfibril and bundle architecture, and the structural role of matrix components, is crucial for understanding cell wall functional and technological roles. Small angle scattering techniques, combined with complementary methods, provide an efficient approach to characterise plant cell walls, covering a broad and relevant size range while minimising experimental artefacts derived from sample treatment. Given the system complexity, approaches such as component extraction and the use of plant cell wall analogues are typically employed to enable the interpretation of experimental results. This review summarises the current research status on the characterisation of the hierarchical structure of plant cell walls using small angle scattering techniques. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

Fractal multi-level organisation of human groups in a virtual world

PubMed Central

Fuchs, Benedikt; Sornette, Didier; Thurner, Stefan

2014-01-01

Humans are fundamentally social. They form societies which consist of hierarchically layered nested groups of various quality, size, and structure. The anthropologic literature has classified these groups as support cliques, sympathy groups, bands, cognitive groups, tribes, linguistic groups, and so on. Anthropologic data show that, on average, each group consists of approximately three subgroups. However, a general understanding of the structural dependence of groups at different layers is largely missing. We extend these early findings to a very large high-precision large-scale internet-based social network data. We analyse the organisational structure of a complete, multi-relational, large social multiplex network of a human society consisting of about 400,000 odd players of an open-ended massive multiplayer online game for which we know all about their various group memberships at different layers. Remarkably, the online players' society exhibits the same type of structured hierarchical layers as found in hunter-gatherer societies. Our findings suggest that the hierarchical organisation of human society is deeply nested in human psychology. PMID:25283998

Biomedical application of hierarchically built structures based on metal oxides

NASA Astrophysics Data System (ADS)

Korovin, M. S.; Fomenko, A. N.

2017-12-01

Nowadays, the use of hierarchically built structures in biology and medicine arouses much interest. The aim of this work is to review and summarize the available literature data about hierarchically organized structures in biomedical application. Nanoparticles can serve as an example of such structures. Medicine holds a special place among various application methods of similar systems. Special attention is paid to inorganic nanoparticles based on different metal oxides and hydroxides, such as iron, zinc, copper, and aluminum. Our investigations show that low-dimensional nanostructures based on aluminum oxides and hydroxides have an inhibitory effect on tumor cells and possess an antimicrobial activity. At the same time, it is obvious that the large-scale use of nanoparticles by humans needs to thoroughly study their properties. Special attention should be paid to the study of nanoparticle interaction with living biological objects. The numerous data show that there is no clear understanding of interaction mechanisms between nanoparticles and various cell types.

Sensory integration dynamics in a hierarchical network explains choice probabilities in cortical area MT

PubMed Central

Wimmer, Klaus; Compte, Albert; Roxin, Alex; Peixoto, Diogo; Renart, Alfonso; de la Rocha, Jaime

2015-01-01

Neuronal variability in sensory cortex predicts perceptual decisions. This relationship, termed choice probability (CP), can arise from sensory variability biasing behaviour and from top-down signals reflecting behaviour. To investigate the interaction of these mechanisms during the decision-making process, we use a hierarchical network model composed of reciprocally connected sensory and integration circuits. Consistent with monkey behaviour in a fixed-duration motion discrimination task, the model integrates sensory evidence transiently, giving rise to a decaying bottom-up CP component. However, the dynamics of the hierarchical loop recruits a concurrently rising top-down component, resulting in sustained CP. We compute the CP time-course of neurons in the medial temporal area (MT) and find an early transient component and a separate late contribution reflecting decision build-up. The stability of individual CPs and the dynamics of noise correlations further support this decomposition. Our model provides a unified understanding of the circuit dynamics linking neural and behavioural variability. PMID:25649611

Fractal multi-level organisation of human groups in a virtual world

NASA Astrophysics Data System (ADS)

Fuchs, Benedikt; Sornette, Didier; Thurner, Stefan

2014-10-01

Humans are fundamentally social. They form societies which consist of hierarchically layered nested groups of various quality, size, and structure. The anthropologic literature has classified these groups as support cliques, sympathy groups, bands, cognitive groups, tribes, linguistic groups, and so on. Anthropologic data show that, on average, each group consists of approximately three subgroups. However, a general understanding of the structural dependence of groups at different layers is largely missing. We extend these early findings to a very large high-precision large-scale internet-based social network data. We analyse the organisational structure of a complete, multi-relational, large social multiplex network of a human society consisting of about 400,000 odd players of an open-ended massive multiplayer online game for which we know all about their various group memberships at different layers. Remarkably, the online players' society exhibits the same type of structured hierarchical layers as found in hunter-gatherer societies. Our findings suggest that the hierarchical organisation of human society is deeply nested in human psychology.

Megadalton Complexes in the Chloroplast Stroma of Arabidopsis thaliana Characterized by Size Exclusion Chromatography, Mass Spectrometry, and Hierarchical Clustering*

PubMed Central

Olinares, Paul Dominic B.; Ponnala, Lalit; van Wijk, Klaas J.

2010-01-01

To characterize MDa-sized macromolecular chloroplast stroma protein assemblies and to extend coverage of the chloroplast stroma proteome, we fractionated soluble chloroplast stroma in the non-denatured state by size exclusion chromatography with a size separation range up to ∼5 MDa. To maximize protein complex stability and resolution of megadalton complexes, ionic strength and composition were optimized. Subsequent high accuracy tandem mass spectrometry analysis (LTQ-Orbitrap) identified 1081 proteins across the complete native mass range. Protein complexes and assembly states above 0.8 MDa were resolved using hierarchical clustering, and protein heat maps were generated from normalized protein spectral counts for each of the size exclusion chromatography fractions; this complemented previous analysis of stromal complexes up to 0.8 MDa (Peltier, J. B., Cai, Y., Sun, Q., Zabrouskov, V., Giacomelli, L., Rudella, A., Ytterberg, A. J., Rutschow, H., and van Wijk, K. J. (2006) The oligomeric stromal proteome of Arabidopsis thaliana chloroplasts. Mol. Cell. Proteomics 5, 114–133). This combined experimental and bioinformatics analyses resolved chloroplast ribosomes in different assembly and functional states (e.g. 30, 50, and 70 S), which enabled the identification of plastid homologues of prokaryotic ribosome assembly factors as well as proteins involved in co-translational modifications, targeting, and folding. The roles of these ribosome-associating proteins will be discussed. Known RNA splice factors (e.g. CAF1/WTF1/RNC1) as well as uncharacterized proteins with RNA-binding domains (pentatricopeptide repeat, RNA recognition motif, and chloroplast ribosome maturation), RNases, and DEAD box helicases were found in various sized complexes. Chloroplast DNA (>3 MDa) was found in association with the complete heteromeric plastid-encoded DNA polymerase complex, and a dozen other DNA-binding proteins, e.g. DNA gyrase, topoisomerase, and various DNA repair enzymes. The heteromeric ≥5-MDa pyruvate dehydrogenase complex and the 0.8–1-MDa acetyl-CoA carboxylase complex associated with uncharacterized biotin carboxyl carrier domain proteins constitute the entry point to fatty acid metabolism in leaves; we suggest that their large size relates to the need for metabolic channeling. Protein annotations and identification data are available through the Plant Proteomics Database, and mass spectrometry data are available through Proteomics Identifications database. PMID:20423899

Hierarchical learning architecture with automatic feature selection for multiclass protein fold classification.

PubMed

Huang, Chuen-Der; Lin, Chin-Teng; Pal, Nikhil Ranjan

2003-12-01

The structure classification of proteins plays a very important role in bioinformatics, since the relationships and characteristics among those known proteins can be exploited to predict the structure of new proteins. The success of a classification system depends heavily on two things: the tools being used and the features considered. For the bioinformatics applications, the role of appropriate features has not been paid adequate importance. In this investigation we use three novel ideas for multiclass protein fold classification. First, we use the gating neural network, where each input node is associated with a gate. This network can select important features in an online manner when the learning goes on. At the beginning of the training, all gates are almost closed, i.e., no feature is allowed to enter the network. Through the training, gates corresponding to good features are completely opened while gates corresponding to bad features are closed more tightly, and some gates may be partially open. The second novel idea is to use a hierarchical learning architecture (HLA). The classifier in the first level of HLA classifies the protein features into four major classes: all alpha, all beta, alpha + beta, and alpha/beta. And in the next level we have another set of classifiers, which further classifies the protein features into 27 folds. The third novel idea is to induce the indirect coding features from the amino-acid composition sequence of proteins based on the N-gram concept. This provides us with more representative and discriminative new local features of protein sequences for multiclass protein fold classification. The proposed HLA with new indirect coding features increases the protein fold classification accuracy by about 12%. Moreover, the gating neural network is found to reduce the number of features drastically. Using only half of the original features selected by the gating neural network can reach comparable test accuracy as that using all the original features. The gating mechanism also helps us to get a better insight into the folding process of proteins. For example, tracking the evolution of different gates we can find which characteristics (features) of the data are more important for the folding process. And, of course, it also reduces the computation time.

An Improved Ultrasensitive Enzyme-Linked Immunosorbent Assay Using Hydrangea-Like Antibody-Enzyme-Inorganic Three-in-One Nanocomposites.

PubMed

Wei, Tianxiang; Du, Dan; Zhu, Mei-Jun; Lin, Yuehe; Dai, Zhihui

2016-03-01

Protein-inorganic nanoflowers, composed of protein and copper(II) phosphate (Cu3(PO4)2), have recently grabbed people's attention. Because the synthetic method requires no organic solvent and because of the distinct hierarchical nanostructure, protein-inorganic nanoflowers display enhanced catalytic activity and stability and would be a promising tool in biocatalytical processes and biological and biomedical fields. In this work, we first coimmobilized the enzyme, antibody, and Cu3(PO4)2 into a three-in-one hybrid protein-inorganic nanoflower to enable it to possess dual functions: (1) the antibody portion retains the ability to specifically capture the corresponding antigen; (2) the nanoflower has enhanced enzymatic activity and stability to produce an amplified signal. The prepared antibody-enzyme-inorganic nanoflower was first applied in an enzyme-linked immunosorbent assay to serve as a novel enzyme-labeled antibody for Escherichia coli O157:H7 (E. coli O157:H7) determination. The detection limit is 60 CFU L(-1), which is far superior to commercial ELISA systems. The three-in-one antibody (anti-E. coli O157:H7 antibody)-enzyme (horseradish peroxidase)-inorganic (Cu3(PO4)2) nanoflower has some advantages over commercial enzyme-antibody conjugates. First, it is much easier to prepare and does not need any complex covalent modification. Second, it has fairly high capture capability and catalytic activity because it is presented as aggregates of abundant antibodies and enzymes. Third, it has enhanced enzymatic stability compared to the free form of enzyme due to the unique hierarchical nanostructure.

Toward a General Approach for RNA-Templated Hierarchical Assembly of Split-Proteins

PubMed Central

Furman, Jennifer L.; Badran, Ahmed H.; Ajulo, Oluyomi; Porter, Jason R.; Stains, Cliff I.; Segal, David J.; Ghosh, Indraneel

2010-01-01

The ability to conditionally turn on a signal or induce a function in the presence of a user-defined RNA target has potential applications in medicine and synthetic biology. Although sequence-specific pumilio repeat proteins can target a limited set of ssRNA sequences, there are no general methods for targeting ssRNA with designed proteins. As a first step toward RNA recognition, we utilized the RNA binding domain of argonaute, implicated in RNA interference, for specifically targeting generic 2-nucleotide, 3' overhangs of any dsRNA. We tested the reassembly of a split-luciferase enzyme guided by argonaute-mediated recognition of newly generated nucleotide overhangs when ssRNA is targeted by a designed complementary guide sequence. This approach was successful when argonaute was utilized in conjunction with a pumilio repeat and expanded the scope of potential ssRNA targets. However, targeting any desired ssRNA remained elusive as two argonaute domains provided minimal reassembled split-luciferase. We next designed and tested a second hierarchical assembly, wherein ssDNA guides are appended to DNA hairpins that serve as a scaffold for high affinity zinc fingers attached to split-luciferase. In the presence of a ssRNA target containing adjacent sequences complementary to the guides, the hairpins are brought into proximity, allowing for zinc finger binding and concomitant reassembly of the fragmented luciferase. The scope of this new approach was validated by specifically targeting RNA encoding VEGF, hDM2, and HER2. These approaches provide potentially general design paradigms for the conditional reassembly of fragmented proteins in the presence of any desired ssRNA target. PMID:20681585

El paradigma jerarquico de formacion de estructuras

NASA Astrophysics Data System (ADS)

Lambas, D. G.

This contribution aims at showing our current understanding of the hierarchical clustering scenario for structure formation, its main success in terms of agreement of theoretical predictions and observations, and the most direct tests that provide confidence on the validity of the paradigm. FULL TEXT IN SPANISH

Scale and scaling in soils

USDA-ARS?s Scientific Manuscript database

Scale is recognized as a central concept in the description of the hierarchical organization of our world. Pressing environmental and societal problems such require an understanding of how processes operate at different scales, and how they can be linked across scales. Soil science as many other dis...

Student conceptions about the DNA structure within a hierarchical organizational level: Improvement by experiment- and computer-based outreach learning.

PubMed

Langheinrich, Jessica; Bogner, Franz X

2015-01-01

As non-scientific conceptions interfere with learning processes, teachers need both, to know about them and to address them in their classrooms. For our study, based on 182 eleventh graders, we analyzed the level of conceptual understanding by implementing the "draw and write" technique during a computer-supported gene technology module. To give participants the hierarchical organizational level which they have to draw, was a specific feature of our study. We introduced two objective category systems for analyzing drawings and inscriptions. Our results indicated a long- as well as a short-term increase in the level of conceptual understanding and in the number of drawn elements and their grades concerning the DNA structure. Consequently, we regard the "draw and write" technique as a tool for a teacher to get to know students' alternative conceptions. Furthermore, our study points the modification potential of hands-on and computer-supported learning modules. © 2015 The International Union of Biochemistry and Molecular Biology.

Hierarchical Heteroclinics in Dynamical Model of Cognitive Processes: Chunking

NASA Astrophysics Data System (ADS)

Afraimovich, Valentin S.; Young, Todd R.; Rabinovich, Mikhail I.

Combining the results of brain imaging and nonlinear dynamics provides a new hierarchical vision of brain network functionality that is helpful in understanding the relationship of the network to different mental tasks. Using these ideas it is possible to build adequate models for the description and prediction of different cognitive activities in which the number of variables is usually small enough for analysis. The dynamical images of different mental processes depend on their temporal organization and, as a rule, cannot be just simple attractors since cognition is characterized by transient dynamics. The mathematical image for a robust transient is a stable heteroclinic channel consisting of a chain of saddles connected by unstable separatrices. We focus here on hierarchical chunking dynamics that can represent several cognitive activities. Chunking is the dynamical phenomenon that means dividing a long information chain into shorter items. Chunking is known to be important in many processes of perception, learning, memory and cognition. We prove that in the phase space of the model that describes chunking there exists a new mathematical object — heteroclinic sequence of heteroclinic cycles — using the technique of slow-fast approximations. This new object serves as a skeleton of motions reflecting sequential features of hierarchical chunking dynamics and is an adequate image of the chunking processing.

Processing prosodic structure by adults with language-based learning disability.

PubMed

Bahl, Megha; Plante, Elena; Gerken, LouAnn

2009-01-01

Two experiments investigated the ability of adults with a history of language-based learning disability (hLLD) and their normal language (NL) peers to learn prosodic patterns of a novel language. Participants were exposed to stimuli from an artificial language and tested on items that required generalization of the stress patterns and the hierarchical principles of stress assignment that could be inferred from the input. In Study 1, the NL group successfully generalized the patterns of stress heard during familiarization, but failed to show generalization of the hierarchical principles. The hLLD group performed at chance for both types of generalization items. In Study 2, the intensity of stress elements was increased. The performance of the NL group improved whereas the hLLD groups' performance decreased on both types of generalization items. The results indicate that NL adults are able to successfully abstract the complex hierarchical rules of stress if the prosodic cues are made sufficiently salient, but this same task is difficult for adults with hLLD. The reader will be able to understand: (1) the difference in the ability of hLLD and NL adults to process stress assignment in an implicit learning context and (2) that typical adults can abstract complex hierarchical rules of stress assignment when provided with strong cues.

Efficient and accurate Greedy Search Methods for mining functional modules in protein interaction networks.

PubMed

He, Jieyue; Li, Chaojun; Ye, Baoliu; Zhong, Wei

2012-06-25

Most computational algorithms mainly focus on detecting highly connected subgraphs in PPI networks as protein complexes but ignore their inherent organization. Furthermore, many of these algorithms are computationally expensive. However, recent analysis indicates that experimentally detected protein complexes generally contain Core/attachment structures. In this paper, a Greedy Search Method based on Core-Attachment structure (GSM-CA) is proposed. The GSM-CA method detects densely connected regions in large protein-protein interaction networks based on the edge weight and two criteria for determining core nodes and attachment nodes. The GSM-CA method improves the prediction accuracy compared to other similar module detection approaches, however it is computationally expensive. Many module detection approaches are based on the traditional hierarchical methods, which is also computationally inefficient because the hierarchical tree structure produced by these approaches cannot provide adequate information to identify whether a network belongs to a module structure or not. In order to speed up the computational process, the Greedy Search Method based on Fast Clustering (GSM-FC) is proposed in this work. The edge weight based GSM-FC method uses a greedy procedure to traverse all edges just once to separate the network into the suitable set of modules. The proposed methods are applied to the protein interaction network of S. cerevisiae. Experimental results indicate that many significant functional modules are detected, most of which match the known complexes. Results also demonstrate that the GSM-FC algorithm is faster and more accurate as compared to other competing algorithms. Based on the new edge weight definition, the proposed algorithm takes advantages of the greedy search procedure to separate the network into the suitable set of modules. Experimental analysis shows that the identified modules are statistically significant. The algorithm can reduce the computational time significantly while keeping high prediction accuracy.

Folding energy landscape and network dynamics of small globular proteins

PubMed Central

Hori, Naoto; Chikenji, George; Berry, R. Stephen; Takada, Shoji

2009-01-01

The folding energy landscape of proteins has been suggested to be funnel-like with some degree of ruggedness on the slope. How complex the landscape, however, is still rather unclear. Many experiments for globular proteins suggested relative simplicity, whereas molecular simulations of shorter peptides implied more complexity. Here, by using complete conformational sampling of 2 globular proteins, protein G and src SH3 domain and 2 related random peptides, we investigated their energy landscapes, topological properties of folding networks, and folding dynamics. The projected energy surfaces of globular proteins were funneled in the vicinity of the native but also have other quite deep, accessible minima, whereas the randomized peptides have many local basins, including some leading to seriously misfolded forms. Dynamics in the denatured part of the network exhibited basin-hopping itinerancy among many conformations, whereas the protein reached relatively well-defined final stages that led to their native states. We also found that the folding network has the hierarchic nature characterized by the scale-free and the small-world properties. PMID:19114654

Folding energy landscape and network dynamics of small globular proteins.

PubMed

Hori, Naoto; Chikenji, George; Berry, R Stephen; Takada, Shoji

2009-01-06

The folding energy landscape of proteins has been suggested to be funnel-like with some degree of ruggedness on the slope. How complex the landscape, however, is still rather unclear. Many experiments for globular proteins suggested relative simplicity, whereas molecular simulations of shorter peptides implied more complexity. Here, by using complete conformational sampling of 2 globular proteins, protein G and src SH3 domain and 2 related random peptides, we investigated their energy landscapes, topological properties of folding networks, and folding dynamics. The projected energy surfaces of globular proteins were funneled in the vicinity of the native but also have other quite deep, accessible minima, whereas the randomized peptides have many local basins, including some leading to seriously misfolded forms. Dynamics in the denatured part of the network exhibited basin-hopping itinerancy among many conformations, whereas the protein reached relatively well-defined final stages that led to their native states. We also found that the folding network has the hierarchic nature characterized by the scale-free and the small-world properties.

CDD/SPARCLE: functional classification of proteins via subfamily domain architectures.

PubMed

Marchler-Bauer, Aron; Bo, Yu; Han, Lianyi; He, Jane; Lanczycki, Christopher J; Lu, Shennan; Chitsaz, Farideh; Derbyshire, Myra K; Geer, Renata C; Gonzales, Noreen R; Gwadz, Marc; Hurwitz, David I; Lu, Fu; Marchler, Gabriele H; Song, James S; Thanki, Narmada; Wang, Zhouxi; Yamashita, Roxanne A; Zhang, Dachuan; Zheng, Chanjuan; Geer, Lewis Y; Bryant, Stephen H

2017-01-04

NCBI's Conserved Domain Database (CDD) aims at annotating biomolecular sequences with the location of evolutionarily conserved protein domain footprints, and functional sites inferred from such footprints. An archive of pre-computed domain annotation is maintained for proteins tracked by NCBI's Entrez database, and live search services are offered as well. CDD curation staff supplements a comprehensive collection of protein domain and protein family models, which have been imported from external providers, with representations of selected domain families that are curated in-house and organized into hierarchical classifications of functionally distinct families and sub-families. CDD also supports comparative analyses of protein families via conserved domain architectures, and a recent curation effort focuses on providing functional characterizations of distinct subfamily architectures using SPARCLE: Subfamily Protein Architecture Labeling Engine. CDD can be accessed at https://www.ncbi.nlm.nih.gov/Structure/cdd/cdd.shtml. Published by Oxford University Press on behalf of Nucleic Acids Research 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.

NUMERICAL SIMULATION OF NANOINDENTATION AND PATCH CLAMP EXPERIMENTS ON MECHANOSENSITIVE CHANNELS OF LARGE CONDUCTANCE IN ESCHERICHIA COLI

PubMed Central

Tang, Yuye; Chen, Xi; Yoo, Jejoong; Yethiraj, Arun; Cui, Qiang

2010-01-01

A hierarchical simulation framework that integrates information from all-atom simulations into a finite element model at the continuum level is established to study the mechanical response of a mechanosensitive channel of large conductance (MscL) in bacteria Escherichia Coli (E.coli) embedded in a vesicle formed by the dipalmitoylphosphatidycholine (DPPC) lipid bilayer. Sufficient structural details of the protein are built into the continuum model, with key parameters and material properties derived from molecular mechanics simulations. The multi-scale framework is used to analyze the gating of MscL when the lipid vesicle is subjective to nanoindentation and patch clamp experiments, and the detailed structural transitions of the protein are obtained explicitly as a function of external load; it is currently impossible to derive such information based solely on all-atom simulations. The gating pathways of E.coli-MscL qualitatively agree with results from previous patch clamp experiments. The gating mechanisms under complex indentation-induced deformation are also predicted. This versatile hierarchical multi-scale framework may be further extended to study the mechanical behaviors of cells and biomolecules, as well as to guide and stimulate biomechanics experiments. PMID:21874098

Deciphering hierarchical features in the energy landscape of adenylate kinase folding/unfolding

NASA Astrophysics Data System (ADS)

Taylor, J. Nicholas; Pirchi, Menahem; Haran, Gilad; Komatsuzaki, Tamiki

2018-03-01

Hierarchical features of the energy landscape of the folding/unfolding behavior of adenylate kinase, including its dependence on denaturant concentration, are elucidated in terms of single-molecule fluorescence resonance energy transfer (smFRET) measurements in which the proteins are encapsulated in a lipid vesicle. The core in constructing the energy landscape from single-molecule time-series across different denaturant concentrations is the application of rate-distortion theory (RDT), which naturally considers the effects of measurement noise and sampling error, in combination with change-point detection and the quantification of the FRET efficiency-dependent photobleaching behavior. Energy landscapes are constructed as a function of observation time scale, revealing multiple partially folded conformations at small time scales that are situated in a superbasin. As the time scale increases, these denatured states merge into a single basin, demonstrating the coarse-graining of the energy landscape as observation time increases. Because the photobleaching time scale is dependent on the conformational state of the protein, possible nonequilibrium features are discussed, and a statistical test for violation of the detailed balance condition is developed based on the state sequences arising from the RDT framework.

Beyond Recall in Reading Comprehension: Five Key Planning Decisions.

ERIC Educational Resources Information Center

Sinatra, Richard; Annacone, Dominic

Over the years, teacher questions have consistently aimed at literal comprehension, indicating that teachers lack understanding of the reading-thinking-questioning hierarchy. Benjamin Bloom's "Cognitive Taxonomy" can serve as a hierarchical framework for the design of questions. Within this framework, a teacher can confront decision…

Purification and characterization of DR_2577 (SlpA) a major S-layer protein from Deinococcus radiodurans

PubMed Central

Farci, Domenica; Bowler, Matthew W.; Esposito, Francesca; McSweeney, Sean; Tramontano, Enzo; Piano, Dario

2015-01-01

The protein DR_2577 is a major Surface layer component of the radio-resistant bacterium Deinococcus radiodurans. In the present study DR_2577 has been purified and its oligomeric profile characterized by means of size exclusion chromatography and gel electrophoresis. DR_2577 was found to be organized into three hierarchical orders characterized by monomers, stable dimers formed by the occurrence of disulfide bonds, and hexamers resulting from a combination of dimers. The structural implications of these findings are discussed providing new elements for a more integrated model of this S-layer. PMID:26074883

Purification and characterization of DR_2577 (SlpA) a major S-layer protein from Deinococcus radiodurans

DOE PAGES

Farci, Domenica; Bowler, Matthew W.; Esposito, Francesca; ...

2015-06-03

The protein DR_2577 is a major Surface layer component of the radio-resistant bacterium Deinococcus radiodurans. In the present study DR_2577 has been purified and its oligomeric profile characterized by means of size exclusion chromatography and gel electrophoresis. DR_2577 was found to be organized into three hierarchical orders characterized by monomers, stable dimers formed by the occurrence of disulfide bonds, and hexamers resulting from a combination of dimers. Finally, the structural implications of these findings are discussed providing new elements for a more integrated model of this S-layer.

Isolation of a human anti-epidermal growth factor receptor Fab antibody, EG-19-11, with subnanomolar affinity from naïve immunoglobulin repertoires using a hierarchical antibody library system.

PubMed

Hur, Byung-ung; Yoon, Jae-bong; Liu, Li-Kun; Cha, Sang-hoon

2010-11-30

Specific antibodies that possess a subnanomolar affinity are very difficult to obtain from human naïve immunoglobulin repertoires without the use of lengthy affinity optimization procedures. Here, we designed a hierarchical phage-displayed antibody library system to generate an enormous diversity of combinatorial Fab fragments (6×10(17)) and attempted to isolate high-affinity Fabs against the human epidermal growth factor receptor (EGFR). A primary antibody library, designated HuDVFab-8L, comprising 4.5×10(9) human naïve heavy chains and eight unspecified human naïve light chains was selected against the EGFR-Fc protein by biopanning, and four anti-EGFR Fab clones were isolated. Because one of the Fab clones, denoted EG-L2-11, recognized a native EGFR expressed on A431 cells, the heavy chain of the Fab was shuffled with a human naïve light chain repertoire with a diversity of 1.4×10(8) and selected a second time against the EGFR-Fc protein again. One EG-L2-11 variant, denoted EG-19-11, recognized an EGFR epitope that was almost the same as that bound by cetuximab and had a K(D) of approximately 540 pM for soluble EGFR, which is about 7-fold higher than that of the FabC225 derived from cetuximab. This variant was also internalized by A431 cells, likely via receptor-mediated endocytosis, and it efficiently inhibited EGF-mediated tyrosine phosphorylation of the EGFR. These results demonstrate that the use of our hierarchical antibody library system is advantageous in generating fully human antibodies especially with a therapeutic purpose. Copyright © 2010 Elsevier B.V. All rights reserved.

iSBatch: a batch-processing platform for data analysis and exploration of live-cell single-molecule microscopy images and other hierarchical datasets.

PubMed

Caldas, Victor E A; Punter, Christiaan M; Ghodke, Harshad; Robinson, Andrew; van Oijen, Antoine M

2015-10-01

Recent technical advances have made it possible to visualize single molecules inside live cells. Microscopes with single-molecule sensitivity enable the imaging of low-abundance proteins, allowing for a quantitative characterization of molecular properties. Such data sets contain information on a wide spectrum of important molecular properties, with different aspects highlighted in different imaging strategies. The time-lapsed acquisition of images provides information on protein dynamics over long time scales, giving insight into expression dynamics and localization properties. Rapid burst imaging reveals properties of individual molecules in real-time, informing on their diffusion characteristics, binding dynamics and stoichiometries within complexes. This richness of information, however, adds significant complexity to analysis protocols. In general, large datasets of images must be collected and processed in order to produce statistically robust results and identify rare events. More importantly, as live-cell single-molecule measurements remain on the cutting edge of imaging, few protocols for analysis have been established and thus analysis strategies often need to be explored for each individual scenario. Existing analysis packages are geared towards either single-cell imaging data or in vitro single-molecule data and typically operate with highly specific algorithms developed for particular situations. Our tool, iSBatch, instead allows users to exploit the inherent flexibility of the popular open-source package ImageJ, providing a hierarchical framework in which existing plugins or custom macros may be executed over entire datasets or portions thereof. This strategy affords users freedom to explore new analysis protocols within large imaging datasets, while maintaining hierarchical relationships between experiments, samples, fields of view, cells, and individual molecules.

Hierarchical regulation of photosynthesis gene expression by the oxygen-responsive PrrBA and AppA-PpsR systems of Rhodobacter sphaeroides.

PubMed

Gomelsky, Larissa; Moskvin, Oleg V; Stenzel, Rachel A; Jones, Denise F; Donohue, Timothy J; Gomelsky, Mark

2008-12-01

In the facultatively phototrophic proteobacterium Rhodobacter sphaeroides, formation of the photosynthetic apparatus is oxygen dependent. When oxygen tension decreases, the response regulator PrrA of the global two-component PrrBA system is believed to directly activate transcription of the puf, puh, and puc operons, encoding structural proteins of the photosynthetic complexes, and to indirectly upregulate the photopigment biosynthesis genes bch and crt. Decreased oxygen also results in inactivation of the photosynthesis-specific repressor PpsR, bringing about derepression of the puc, bch, and crt operons. We uncovered a hierarchical relationship between these two regulatory systems, earlier thought to function independently. We also more accurately assessed the spectrum of gene targets of the PrrBA system. First, expression of the appA gene, encoding the PpsR antirepressor, is PrrA dependent, which establishes one level of hierarchical dominance of the PrrBA system over AppA-PpsR. Second, restoration of the appA transcript to the wild-type level is insufficient for rescuing phototrophic growth impairment of the prrA mutant, whereas inactivation of ppsR is sufficient. This suggests that in addition to controlling appA transcription, PrrA affects the activity of the AppA-PpsR system via an as yet unidentified mechanism(s). Third, PrrA directly activates several bch and crt genes, traditionally considered to be the PpsR targets. Therefore, in R. sphaeroides, the global PrrBA system regulates photosynthesis gene expression (i) by rigorous control over the photosynthesis-specific AppA-PpsR regulatory system and (ii) by extensive direct transcription activation of genes encoding structural proteins of photosynthetic complexes as well as genes encoding photopigment biosynthesis enzymes.

Bioinspired Hierarchical Alumina-Graphene Oxide-Poly(vinyl alcohol) Artificial Nacre with Optimized Strength and Toughness.

PubMed

Wang, Jinrong; Qiao, Jinliang; Wang, Jianfeng; Zhu, Ying; Jiang, Lei

2015-05-06

Due to hierarchical organization of micro- and nanostructures, natural nacre exhibits extraordinary strength and toughness, and thus provides a superior model for the design and fabrication of high-performance artificial composite materials. Although great progress has been made in constructing layered composites by alternately stacking hard inorganic platelets and soft polymers, the real issue is that the excellent strength of these composites was obtained at the sacrifice of toughness. In this work, inspired by the layered aragonite microplatelets/chitin nanofibers-protein structure of natural nacre, alumina microplatelets-graphene oxide nanosheets-poly(vinyl alcohol) (Al2O3/GO-PVA) artificial nacre is successfully constructed through layer-by-layer bottom-up assembly, in which Al2O3 and GO-PVA act as "bricks" and "mortar", respectively. The artificial nacre has hierarchical "brick-and-mortar" structure and exhibits excellent strength (143 ± 13 MPa) and toughness (9.2 ± 2.7 MJ/m(3)), which are superior to those of natural nacre (80-135 MPa, 1.8 MJ/m(3)). It was demonstrated that the multiscale hierarchical structure of ultrathin GO nanosheets and submicrometer-thick Al2O3 platelets can deal with the conflict between strength and toughness, thus leading to the excellent mechanical properties that cannot be obtained using only one size of platelet. We strongly believe that the work presented here provides a creative strategy for designing and developing new composites with excellent strength and toughness.

Hierarchical classification of land use types using multiple vegetation indices to measure the effects of urbanization.

PubMed

Shishir, Sharmin; Tsuyuzaki, Shiro

2018-05-11

Detecting fine-scale spatiotemporal land use changes is a prerequisite for understanding and predicting the effects of urbanization and its related human impacts on the ecosystem. Land use changes are frequently examined using vegetation indices (VIs), although the validation of these indices has not been conducted at a high resolution. Therefore, a hierarchical classification was constructed to obtain accurate land use types at a fine scale. The characteristics of four popular VIs were investigated prior to examining the hierarchical classification by using Purbachal New Town, Bangladesh, which exhibits ongoing urbanization. These four VIs are the normalized difference VI (NDVI), green-red VI (GRVI), enhanced VI (EVI), and two-band EVI (EVI2). The reflectance data were obtained by the IKONOS (0.8-m resolution) and WorldView-2 sensor (0.5-m resolution) in 2001 and 2015, respectively. The hierarchical classification of land use types was constructed using a decision tree (DT) utilizing all four of the examined VIs. The accuracy of the classification was evaluated using ground truth data with multiple comparisons and kappa (κ) coefficients. The DT showed overall accuracies of 96.1 and 97.8% in 2001 and 2015, respectively, while the accuracies of the VIs were less than 91.2%. These results indicate that each VI exhibits unique advantages. In addition, the DT was the best classifier of land use types, particularly for native ecosystems represented by Shorea forests and homestead vegetation, at the fine scale. Since the conservation of these native ecosystems is of prime importance, DTs based on hierarchical classifications should be used more widely.

Hierarchically assembled Au microspheres and sea urchin-like architectures: formation mechanism and SERS study

NASA Astrophysics Data System (ADS)

Wang, Xiansong; Yang, Da-Peng; Huang, Peng; Li, Min; Li, Chao; Chen, Di; Cui, Daxiang

2012-11-01

The hierarchically assembled Au microspheres/sea urchin-like structures have been synthesized in aqueous solution at room temperature with and without proteins (bovine serum albumin, BSA) as mediators. The average diameter of an individual Au microsphere is 300-600 nm, which is composed of some compact nanoparticles with an average diameter of about 15 nm. Meanwhile, the sea urchin-like Au architecture exhibits an average diameter of 600-800 nm, which is made up of some nanopricks with an average length of 100-200 nm. These products are characterized by means of scanning electron microscopy (SEM), X-ray diffraction (XRD) and transmission electronic microscopy (TEM). It is found that the BSA and ascorbic acid (AA) have great effects on the morphology of the resulting products. Two different growth mechanisms are proposed. The study on surface enhanced Raman scattering (SERS) activities is also carried out between Au microspheres and Au sea urchin-like architectures. It is found that Au urchin-like architectures possess much higher SERS activity than the Au microspheres. Our work may shed light on the design and synthesis of hierarchically self-assembled 3D micro/nano-architectures for SERS, catalysis and biosensors.The hierarchically assembled Au microspheres/sea urchin-like structures have been synthesized in aqueous solution at room temperature with and without proteins (bovine serum albumin, BSA) as mediators. The average diameter of an individual Au microsphere is 300-600 nm, which is composed of some compact nanoparticles with an average diameter of about 15 nm. Meanwhile, the sea urchin-like Au architecture exhibits an average diameter of 600-800 nm, which is made up of some nanopricks with an average length of 100-200 nm. These products are characterized by means of scanning electron microscopy (SEM), X-ray diffraction (XRD) and transmission electronic microscopy (TEM). It is found that the BSA and ascorbic acid (AA) have great effects on the morphology of the resulting products. Two different growth mechanisms are proposed. The study on surface enhanced Raman scattering (SERS) activities is also carried out between Au microspheres and Au sea urchin-like architectures. It is found that Au urchin-like architectures possess much higher SERS activity than the Au microspheres. Our work may shed light on the design and synthesis of hierarchically self-assembled 3D micro/nano-architectures for SERS, catalysis and biosensors. Electronic supplementary information (ESI) available. See DOI: 10.1039/c2nr32405a

Hierarchically assembled Au microspheres and sea urchin-like architectures: formation mechanism and SERS study.

PubMed

Wang, Xiansong; Yang, Da-Peng; Huang, Peng; Li, Min; Li, Chao; Chen, Di; Cui, Daxiang

2012-12-21

The hierarchically assembled Au microspheres/sea urchin-like structures have been synthesized in aqueous solution at room temperature with and without proteins (bovine serum albumin, BSA) as mediators. The average diameter of an individual Au microsphere is 300-600 nm, which is composed of some compact nanoparticles with an average diameter of about 15 nm. Meanwhile, the sea urchin-like Au architecture exhibits an average diameter of 600-800 nm, which is made up of some nanopricks with an average length of 100-200 nm. These products are characterized by means of scanning electron microscopy (SEM), X-ray diffraction (XRD) and transmission electronic microscopy (TEM). It is found that the BSA and ascorbic acid (AA) have great effects on the morphology of the resulting products. Two different growth mechanisms are proposed. The study on surface enhanced Raman scattering (SERS) activities is also carried out between Au microspheres and Au sea urchin-like architectures. It is found that Au urchin-like architectures possess much higher SERS activity than the Au microspheres. Our work may shed light on the design and synthesis of hierarchically self-assembled 3D micro/nano-architectures for SERS, catalysis and biosensors.

Using the social cognitive theory to understand physical activity among dialysis patients.

PubMed

Patterson, Megan S; Umstattd Meyer, M Renée; Beaujean, A Alexander; Bowden, Rodney G

2014-08-01

The purpose of this study was to use the social cognitive theory (SCT) constructs self-efficacy, outcome expectations, and self-regulation to better understand associations of physical activity (PA) behaviors among dialysis patients after controlling for demographic and health-related factors. This study was cross-sectional in design. Participants (N = 115; mean age = 61.51 years, SD = 14.01) completed self-report questionnaires during a regularly scheduled dialysis treatment session. Bivariate and hierarchical linear regression analyses were conducted to examine relationships among SCT constructs and PA. Significant relationships between PA and self-efficacy (r = .336), self-regulation (r = .280), and outcome expectations (r = .265) were detected among people on dialysis in bivariate analyses. Hierarchical linear regression revealed significant increases in variance explained for the addition of self-efficacy, self-regulation, and covariates (p < .01). Younger age, self-efficacy, and self-regulation were associated (p < .10) with greater participation in physical activity in the final model (R² = .272). Conclusion/Implication: This research supports the use of SCT in understanding PA among people undergoing dialysis treatment. The findings of this study can help health educators and health care practitioners better understand PA and how to promote it among this population. Future research should further investigate which activities dialysis patients participate in across the life span of their disease. Future PA programs should focus on increasing a patient's self-efficacy and self-regulation.

Protein retention on plasma-treated hierarchical nanoscale gold-silver platform

PubMed Central

Fang, Jinghua; Levchenko, Igor; Mai-Prochnow, Anne; Keidar, Michael; Cvelbar, Uros; Filipic, Gregor; Han, Zhao Jun; Ostrikov, Kostya (Ken)

2015-01-01

Dense arrays of gold-supported silver nanowires of about 100 nm in diameter grown directly in the channels of nanoporous aluminium oxide membrane were fabricated and tested as a novel platform for the immobilization and retention of BSA proteins in the microbial-protective environments. Additional treatment of the silver nanowires using low-temperature plasmas in the inductively-coupled plasma reactor and an atmospheric-pressure plasma jet have demonstrated that the morphology of the nanowire array can be controlled and the amount of the retained protein may be increased due to the plasma effect. A combination of the neutral gold sublayer with the antimicrobial properties of silver nanowires could significantly enhance the efficiency of the platforms used in various biotechnological processes. PMID:26307515

Digested disorder

PubMed Central

DeForte, Shelly; Reddy, Krishna D; Uversky, Vladimir N

2013-01-01

The current literature on intrinsically disordered proteins is overwhelming. To keep interested readers up to speed with this literature, we continue a “Digested Disorder” project and represent a series of reader’s digest type articles objectively representing the research papers and reviews on intrinsically disordered proteins. The only 2 criteria for inclusion in this digest are the publication date (a paper should be published within the covered time frame) and topic (a paper should be dedicated to any aspect of protein intrinsic disorder). The current digest issue covers papers published during the period of April, May, and June of 2013. The papers are grouped hierarchically by topics they cover, and for each of the included paper a short description is given on its major findings. PMID:28516028

Digested disorder: Quarterly intrinsic disorder digest (April-May-June, 2013).

PubMed

DeForte, Shelly; Reddy, Krishna D; Uversky, Vladimir N

2013-01-01

The current literature on intrinsically disordered proteins is overwhelming. To keep interested readers up to speed with this literature, we continue a "Digested Disorder" project and represent a series of reader's digest type articles objectively representing the research papers and reviews on intrinsically disordered proteins. The only 2 criteria for inclusion in this digest are the publication date (a paper should be published within the covered time frame) and topic (a paper should be dedicated to any aspect of protein intrinsic disorder). The current digest issue covers papers published during the period of April, May, and June of 2013. The papers are grouped hierarchically by topics they cover, and for each of the included paper a short description is given on its major findings.

Protein retention on plasma-treated hierarchical nanoscale gold-silver platform

NASA Astrophysics Data System (ADS)

Fang, Jinghua; Levchenko, Igor; Mai-Prochnow, Anne; Keidar, Michael; Cvelbar, Uros; Filipic, Gregor; Han, Zhao Jun; Ostrikov, Kostya (Ken)

2015-08-01

Dense arrays of gold-supported silver nanowires of about 100 nm in diameter grown directly in the channels of nanoporous aluminium oxide membrane were fabricated and tested as a novel platform for the immobilization and retention of BSA proteins in the microbial-protective environments. Additional treatment of the silver nanowires using low-temperature plasmas in the inductively-coupled plasma reactor and an atmospheric-pressure plasma jet have demonstrated that the morphology of the nanowire array can be controlled and the amount of the retained protein may be increased due to the plasma effect. A combination of the neutral gold sublayer with the antimicrobial properties of silver nanowires could significantly enhance the efficiency of the platforms used in various biotechnological processes.

Perspective Taking Promotes Action Understanding and Learning

ERIC Educational Resources Information Center

Lozano, Sandra C.; Martin Hard, Bridgette; Tversky, Barbara

2006-01-01

People often learn actions by watching others. The authors propose and test the hypothesis that perspective taking promotes encoding a hierarchical representation of an actor's goals and subgoals-a key process for observational learning. Observers segmented videos of an object assembly task into coarse and fine action units. They described what…

Predicting South Korean University Students' Happiness through Social Support and Efficacy Beliefs

ERIC Educational Resources Information Center

Lee, Diane Sookyoung; Padilla, Amado M.

2016-01-01

This study investigated the adversity and coping experiences of 198 South Korean university students and takes a cultural lens in understanding how social and individual factors shape their happiness. Hierarchical linear regression analyses suggest that Korean students' perceptions of social support significantly predicted their happiness,…

A Relational Approach to Mentoring Women Doctoral Students

ERIC Educational Resources Information Center

Gammel, Jo Ann; Rutstein-Riley, Amy

2016-01-01

Our study examines the relationships of six dyads of women advisors and advisees in one doctoral program to understand power, context, and personal transformation. We found that mentoring is context specific and power dynamics range from equitable to hierarchical. This article explores the connection between relational cultural theory and…

Developmental Relationships in the Dynamic Library Environment: Re-Conceptualizing Mentoring for the Future

ERIC Educational Resources Information Center

Murphy, Sarah Anne

2008-01-01

This article examines the current conceptualization of mentoring in academic libraries and argues that traditional hierarchical mentoring relationships are no longer sufficient for developing tomorrow's leaders. Drawing insights from the management and human resources development literature, it concludes that an expanded understanding of…

Resilience, Bullying, and Mental Health: Factors Associated with Improved Outcomes

ERIC Educational Resources Information Center

Moore, Brian; Woodcock, Stuart

2017-01-01

Resilience is associated with bouncing back from adversity, and the term currently enjoys significant popular appeal. However, understanding of resilience is often superficial. The current paper examined 105 primary and high school students' experiences of resilience and bullying, and considered resilience as a hierarchical factorial model. The…

Secondary Mathematics Course Trajectories: Understanding Accumulated Disadvantages in Mathematics in Grades 9-12

ERIC Educational Resources Information Center

Schiller, Kathryn S.; Hunt, Donald J.

2011-01-01

Schools are institutions in which students' course taking creates series of linked learning opportunities continually shaped by not only curricular structures but demographic and academic backgrounds. In contrast to a seven-step normative course sequence reflecting the conventional hierarchical structure of mathematics, analysis of more than…

Drunkorexia: Understanding the Co-Occurrence of Alcohol Consumption and Eating/Exercise Weight Management Behaviors

ERIC Educational Resources Information Center

Barry, Adam E.; Piazza-Gardner, Anna K.

2012-01-01

Objective: Examine the co-occurrence of alcohol consumption, physical activity, and disordered eating behaviors via a drunkorexia perspective. Participants: Nationally representative sample (n = 22,488) of college students completing the Fall 2008 National College Health Assessment. Methods: Hierarchical logistic regression was employed to…

Testing the Hierarchical SDT Model: The Case of Performance-Oriented Classrooms

ERIC Educational Resources Information Center

Van Nuland, Hanneke J. C.; Taris, Toon W.; Boekaerts, Monique; Martens, Rob L.

2012-01-01

The self-determination theory (SDT) assumes that healthy motivation needs to be intrinsic in nature and that the basic psychological needs competence, autonomy and relatedness are prerequisites for intrinsically motivated behaviour. Intrinsically motivated students in turn show more persistence and understanding of classroom material. However, in…

Self in Self-Worth Protection: The Relationship of Possible Selves and Self-Protective Strategies

ERIC Educational Resources Information Center

Seli, Helena; Dembo, Myron H.; Crocker, Stephen

2009-01-01

This study examined community college students' future-related self-concept, termed "possible selves," in relationship to their current academic behavior with a focus on self-worth protective strategies. As demonstrated via hierarchical regression, possible selves added to understanding the students' self-protective behavior above and…

University Student Satisfaction: An Empirical Analysis

ERIC Educational Resources Information Center

Clemes, Michael D.; Gan, Christopher E. C.; Kao, Tzu-Hui

2008-01-01

The purpose of this research is to gain an empirical understanding of students' overall satisfaction with their academic university experiences. A hierarchal model is used as a framework for this analysis. Fifteen hypotheses are formulated and tested, in order to identify the dimensions of service quality as perceived by university students, to…

Active Commuting Patterns at a Large, Midwestern College Campus

ERIC Educational Resources Information Center

Bopp, Melissa; Kaczynski, Andrew; Wittman, Pamela

2011-01-01

Objective: To understand patterns and influences on active commuting (AC) behavior. Participants: Students and faculty/staff at a university campus. Methods: In April-May 2008, respondents answered an online survey about mode of travel to campus and influences on commuting decisions. Hierarchical regression analyses predicted variance in walking…

Skill Components of Task Analysis

ERIC Educational Resources Information Center

Adams, Anne E.; Rogers, Wendy A.; Fisk, Arthur D.

2013-01-01

Some task analysis methods break down a task into a hierarchy of subgoals. Although an important tool of many fields of study, learning to create such a hierarchy (redescription) is not trivial. To further the understanding of what makes task analysis a skill, the present research examined novices' problems with learning Hierarchical Task…

Real-Time Dynamics of Emerging Actin Networks in Cell-Mimicking Compartments

PubMed Central

Deshpande, Siddharth; Pfohl, Thomas

2015-01-01

Understanding the cytoskeletal functionality and its relation to other cellular components and properties is a prominent question in biophysics. The dynamics of actin cytoskeleton and its polymorphic nature are indispensable for the proper functioning of living cells. Actin bundles are involved in cell motility, environmental exploration, intracellular transport and mechanical stability. Though the viscoelastic properties of actin-based structures have been extensively probed, the underlying microstructure dynamics, especially their disassembly, is not fully understood. In this article, we explore the rich dynamics and emergent properties exhibited by actin bundles within flow-free confinements using a microfluidic set-up and epifluorescence microscopy. After forming entangled actin filaments within cell-sized quasi two-dimensional confinements, we induce their bundling using three different fundamental mechanisms: counterion condensation, depletion interactions and specific protein-protein interactions. Intriguingly, long actin filaments form emerging networks of actin bundles via percolation leading to remarkable properties such as stress generation and spindle-like intermediate structures. Simultaneous sharing of filaments in different links of the network is an important parameter, as short filaments do not form networks but segregated clusters of bundles instead. We encounter a hierarchical process of bundling and its subsequent disassembly. Additionally, our study suggests that such percolated networks are likely to exist within living cells in a dynamic fashion. These observations render a perspective about differential cytoskeletal responses towards numerous stimuli. PMID:25785606

Molecular and cellular events during blastocyst implantation in the receptive uterus: clues from mouse models

PubMed Central

MATSUMOTO, Hiromichi

2017-01-01

The success of implantation is an interactive process between the blastocyst and the uterus. Synchronized development of embryos with uterine differentiation to a receptive state is necessary to complete pregnancy. The period of uterine receptivity for implantation is limited and referred to as the “implantation window”, which is regulated by ovarian steroid hormones. Implantation process is complicated due to the many signaling molecules in the hierarchical mechanisms with the embryo-uterine dialogue. The mouse is widely used in animal research, and is uniquely suited for reproductive studies, i.e., having a large litter size and brief estrous cycles. This review first describes why the mouse is the preferred model for implantation studies, focusing on uterine morphology and physiological traits, and then highlights the knowledge on uterine receptivity and the hormonal regulation of blastocyst implantation in mice. Our recent study revealed that selective proteolysis in the activated blastocyst is associated with the completion of blastocyst implantation after embryo transfer. Furthermore, in the context of blastocyst implantation in the mouse, this review discusses the window of uterine receptivity, hormonal regulation, uterine vascular permeability and angiogenesis, the delayed-implantation mouse model, morphogens, adhesion molecules, crosslinker proteins, extracellular matrix, and matricellular proteins. A better understanding of uterine and blastocyst biology during the peri-implantation period should facilitate further development of reproductive technology. PMID:28638003

Impact of human milk pasteurization on the kinetics of peptide release during in vitro dynamic term newborn digestion.

PubMed

Deglaire, Amélie; De Oliveira, Samira C; Jardin, Julien; Briard-Bion, Valérie; Emily, Mathieu; Ménard, Olivia; Bourlieu, Claire; Dupont, Didier

2016-07-01

Holder pasteurization (62.5°C, 30 min) ensures sanitary quality of donor's human milk but also denatures beneficial proteins. Understanding whether this further impacts the kinetics of peptide release during gastrointestinal digestion of human milk was the aim of the present paper. Mature raw (RHM) or pasteurized (PHM) human milk were digested (RHM, n = 2; PHM, n = 3) by an in vitro dynamic system (term stage). Label-free quantitative peptidomics was performed on milk and digesta (ten time points). Ascending hierarchical clustering was conducted on "Pasteurization × Digestion time" interaction coefficients. Preproteolysis occurred in human milk (159 unique peptides; RHM: 91, PHM: 151), mostly on β-casein (88% of the endogenous peptides). The predicted cleavage number increased with pasteurization, potentially through plasmin activation (plasmin cleavages: RHM, 53; PHM, 76). During digestion, eight clusters resumed 1054 peptides from RHM and PHM, originating for 49% of them from β-casein. For seven clusters (57% of peptides), the kinetics of peptide release differed between RHM and PHM. The parent protein was significantly linked to the clustering (p-value = 1.4 E-09), with β-casein and lactoferrin associated to clusters in an opposite manner. Pasteurization impacted selectively gastric and intestinal kinetics of peptide release in term newborns, which may have further nutritional consequences. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Application of a hierarchical enzyme classification method reveals the role of gut microbiome in human metabolism

PubMed Central

2015-01-01

Background Enzymes are known as the molecular machines that drive the metabolism of an organism; hence identification of the full enzyme complement of an organism is essential to build the metabolic blueprint of that species as well as to understand the interplay of multiple species in an ecosystem. Experimental characterization of the enzymatic reactions of all enzymes in a genome is a tedious and expensive task. The problem is more pronounced in the metagenomic samples where even the species are not adequately cultured or characterized. Enzymes encoded by the gut microbiota play an essential role in the host metabolism; thus, warranting the need to accurately identify and annotate the full enzyme complements of species in the genomic and metagenomic projects. To fulfill this need, we develop and apply a method called ECemble, an ensemble approach to identify enzymes and enzyme classes and study the human gut metabolic pathways. Results ECemble method uses an ensemble of machine-learning methods to accurately model and predict enzymes from protein sequences and also identifies the enzyme classes and subclasses at the finest resolution. A tenfold cross-validation result shows accuracy between 97 and 99% at different levels in the hierarchy of enzyme classification, which is superior to comparable methods. We applied ECemble to predict the entire complements of enzymes from ten sequenced proteomes including the human proteome. We also applied this method to predict enzymes encoded by the human gut microbiome from gut metagenomic samples, and to study the role played by the microbe-derived enzymes in the human metabolism. After mapping the known and predicted enzymes to canonical human pathways, we identified 48 pathways that have at least one bacteria-encoded enzyme, which demonstrates the complementary role of gut microbiome in human gut metabolism. These pathways are primarily involved in metabolizing dietary nutrients such as carbohydrates, amino acids, lipids, cofactors and vitamins. Conclusions The ECemble method is able to hierarchically assign high quality enzyme annotations to genomic and metagenomic data. This study demonstrated the real application of ECemble to understand the indispensable role played by microbe-encoded enzymes in the healthy functioning of human metabolic systems. PMID:26099921

Application of a hierarchical enzyme classification method reveals the role of gut microbiome in human metabolism.

PubMed

Mohammed, Akram; Guda, Chittibabu

2015-01-01

Enzymes are known as the molecular machines that drive the metabolism of an organism; hence identification of the full enzyme complement of an organism is essential to build the metabolic blueprint of that species as well as to understand the interplay of multiple species in an ecosystem. Experimental characterization of the enzymatic reactions of all enzymes in a genome is a tedious and expensive task. The problem is more pronounced in the metagenomic samples where even the species are not adequately cultured or characterized. Enzymes encoded by the gut microbiota play an essential role in the host metabolism; thus, warranting the need to accurately identify and annotate the full enzyme complements of species in the genomic and metagenomic projects. To fulfill this need, we develop and apply a method called ECemble, an ensemble approach to identify enzymes and enzyme classes and study the human gut metabolic pathways. ECemble method uses an ensemble of machine-learning methods to accurately model and predict enzymes from protein sequences and also identifies the enzyme classes and subclasses at the finest resolution. A tenfold cross-validation result shows accuracy between 97 and 99% at different levels in the hierarchy of enzyme classification, which is superior to comparable methods. We applied ECemble to predict the entire complements of enzymes from ten sequenced proteomes including the human proteome. We also applied this method to predict enzymes encoded by the human gut microbiome from gut metagenomic samples, and to study the role played by the microbe-derived enzymes in the human metabolism. After mapping the known and predicted enzymes to canonical human pathways, we identified 48 pathways that have at least one bacteria-encoded enzyme, which demonstrates the complementary role of gut microbiome in human gut metabolism. These pathways are primarily involved in metabolizing dietary nutrients such as carbohydrates, amino acids, lipids, cofactors and vitamins. The ECemble method is able to hierarchically assign high quality enzyme annotations to genomic and metagenomic data. This study demonstrated the real application of ECemble to understand the indispensable role played by microbe-encoded enzymes in the healthy functioning of human metabolic systems.

Hierarchical Helical Order in the Twisted Growth of Plant Organs

NASA Astrophysics Data System (ADS)

Wada, Hirofumi

2012-09-01

The molecular and cellular basis of left-right asymmetry in plant morphogenesis is a fundamental issue in biology. A rapidly elongating root or hypocotyl of twisting mutants of Arabidopsis thaliana exhibits a helical growth with a handedness opposite to that of the underlying cortical microtubule arrays in epidermal cells. However, how such a hierarchical helical order emerges is currently unknown. We propose a model for investigating macroscopic chiral asymmetry in Arabidopsis mutants. Our elastic model suggests that the helical pattern observed is a direct consequence of the simultaneous presence of anisotropic growth and tilting of cortical microtubule arrays. We predict that the root helical pitch angle is a function of the microtubule helical angle and elastic moduli of the tissues. The proposed model is versatile and is potentially important for other biological systems ranging from protein fibrous structures to tree trunks.

A Factor Graph Approach to Automated GO Annotation

PubMed Central

Spetale, Flavio E.; Tapia, Elizabeth; Krsticevic, Flavia; Roda, Fernando; Bulacio, Pilar

2016-01-01

As volume of genomic data grows, computational methods become essential for providing a first glimpse onto gene annotations. Automated Gene Ontology (GO) annotation methods based on hierarchical ensemble classification techniques are particularly interesting when interpretability of annotation results is a main concern. In these methods, raw GO-term predictions computed by base binary classifiers are leveraged by checking the consistency of predefined GO relationships. Both formal leveraging strategies, with main focus on annotation precision, and heuristic alternatives, with main focus on scalability issues, have been described in literature. In this contribution, a factor graph approach to the hierarchical ensemble formulation of the automated GO annotation problem is presented. In this formal framework, a core factor graph is first built based on the GO structure and then enriched to take into account the noisy nature of GO-term predictions. Hence, starting from raw GO-term predictions, an iterative message passing algorithm between nodes of the factor graph is used to compute marginal probabilities of target GO-terms. Evaluations on Saccharomyces cerevisiae, Arabidopsis thaliana and Drosophila melanogaster protein sequences from the GO Molecular Function domain showed significant improvements over competing approaches, even when protein sequences were naively characterized by their physicochemical and secondary structure properties or when loose noisy annotation datasets were considered. Based on these promising results and using Arabidopsis thaliana annotation data, we extend our approach to the identification of most promising molecular function annotations for a set of proteins of unknown function in Solanum lycopersicum. PMID:26771463

A Factor Graph Approach to Automated GO Annotation.

PubMed

Spetale, Flavio E; Tapia, Elizabeth; Krsticevic, Flavia; Roda, Fernando; Bulacio, Pilar

2016-01-01

As volume of genomic data grows, computational methods become essential for providing a first glimpse onto gene annotations. Automated Gene Ontology (GO) annotation methods based on hierarchical ensemble classification techniques are particularly interesting when interpretability of annotation results is a main concern. In these methods, raw GO-term predictions computed by base binary classifiers are leveraged by checking the consistency of predefined GO relationships. Both formal leveraging strategies, with main focus on annotation precision, and heuristic alternatives, with main focus on scalability issues, have been described in literature. In this contribution, a factor graph approach to the hierarchical ensemble formulation of the automated GO annotation problem is presented. In this formal framework, a core factor graph is first built based on the GO structure and then enriched to take into account the noisy nature of GO-term predictions. Hence, starting from raw GO-term predictions, an iterative message passing algorithm between nodes of the factor graph is used to compute marginal probabilities of target GO-terms. Evaluations on Saccharomyces cerevisiae, Arabidopsis thaliana and Drosophila melanogaster protein sequences from the GO Molecular Function domain showed significant improvements over competing approaches, even when protein sequences were naively characterized by their physicochemical and secondary structure properties or when loose noisy annotation datasets were considered. Based on these promising results and using Arabidopsis thaliana annotation data, we extend our approach to the identification of most promising molecular function annotations for a set of proteins of unknown function in Solanum lycopersicum.

Protein Secondary Structure Prediction Using Deep Convolutional Neural Fields.

PubMed

Wang, Sheng; Peng, Jian; Ma, Jianzhu; Xu, Jinbo

2016-01-11

Protein secondary structure (SS) prediction is important for studying protein structure and function. When only the sequence (profile) information is used as input feature, currently the best predictors can obtain ~80% Q3 accuracy, which has not been improved in the past decade. Here we present DeepCNF (Deep Convolutional Neural Fields) for protein SS prediction. DeepCNF is a Deep Learning extension of Conditional Neural Fields (CNF), which is an integration of Conditional Random Fields (CRF) and shallow neural networks. DeepCNF can model not only complex sequence-structure relationship by a deep hierarchical architecture, but also interdependency between adjacent SS labels, so it is much more powerful than CNF. Experimental results show that DeepCNF can obtain ~84% Q3 accuracy, ~85% SOV score, and ~72% Q8 accuracy, respectively, on the CASP and CAMEO test proteins, greatly outperforming currently popular predictors. As a general framework, DeepCNF can be used to predict other protein structure properties such as contact number, disorder regions, and solvent accessibility.

Protein Secondary Structure Prediction Using Deep Convolutional Neural Fields

NASA Astrophysics Data System (ADS)

Wang, Sheng; Peng, Jian; Ma, Jianzhu; Xu, Jinbo

2016-01-01

Protein secondary structure (SS) prediction is important for studying protein structure and function. When only the sequence (profile) information is used as input feature, currently the best predictors can obtain ~80% Q3 accuracy, which has not been improved in the past decade. Here we present DeepCNF (Deep Convolutional Neural Fields) for protein SS prediction. DeepCNF is a Deep Learning extension of Conditional Neural Fields (CNF), which is an integration of Conditional Random Fields (CRF) and shallow neural networks. DeepCNF can model not only complex sequence-structure relationship by a deep hierarchical architecture, but also interdependency between adjacent SS labels, so it is much more powerful than CNF. Experimental results show that DeepCNF can obtain ~84% Q3 accuracy, ~85% SOV score, and ~72% Q8 accuracy, respectively, on the CASP and CAMEO test proteins, greatly outperforming currently popular predictors. As a general framework, DeepCNF can be used to predict other protein structure properties such as contact number, disorder regions, and solvent accessibility.

Unraveling proteome changes of Holstein beef M. semitendinosus and its relationship to meat discoloration during post-mortem storage analyzed by label-free mass spectrometry.

PubMed

Yu, Qianqian; Wu, Wei; Tian, Xiaojing; Hou, Man; Dai, Ruitong; Li, Xingmin

2017-02-10

Label-free proteomics was applied to characterize the effect of post-mortem storage time (0, 4, and 9days at 4°C±1°C) on the proteome changes of M. semitendinosus (SM) in Holstein cattle, and correlations between differentially abundant proteins and meat color traits were investigated. The redness (a*) value decreased significantly (P<0.05) during post-mortem storage, meanwhile, the relative proportion of metmyoglobin increased significantly (P<0.05) from 16.99% at day 0 to 40.26% at day 9. A total of 118 proteins with significant changes (fold change>1.5, P<0.05) was identified by comparisons of day 4 vs. day 0, day 9 vs. day 0, and day 9 vs. day 4. Principal component and hierarchical cluster analyses of these proteins were performed, and results exhibited clear distinctions among samples from different storage times. Eighteen differentially abundant proteins were correlated closely with the a* value of meat. Bioinformatics analyses revealed that most of these proteins were involved in glycolysis and energy metabolism, electron-transfer processes, and the antioxidation function, which implied an underlying connection between meat discoloration and these biological processes. It is always a challenge for scientists to improve the stability of meat color during post-mortem storage and retail display. However, the mechanism involved in meat discoloration has not been unraveled completely, and the application of label-free proteomics in studying meat discoloration has not been reported. Our work discovers some key proteins in SM muscle of Holstein cattle that were correlated with a* value of meat via label-free proteomics. Bioinformatics analyses revealed that some of these differentially abundant proteins were involved in glycolysis and energy metabolism, electron-transfer processes, and the antioxidation function, which implied an underlying connection between meat discoloration and these biological processes. These results provide the theoretic basis on understanding of complicated biochemical changes and underlying molecular mechanisms responsible for meat discoloration. Copyright © 2016 Elsevier B.V. All rights reserved.

The Metabolic Status Drives Acclimation of Iron Deficiency Responses in Chlamydomonas reinhardtii as Revealed by Proteomics Based Hierarchical Clustering and Reverse Genetics*

PubMed Central

Höhner, Ricarda; Barth, Johannes; Magneschi, Leonardo; Jaeger, Daniel; Niehues, Anna; Bald, Till; Grossman, Arthur; Fufezan, Christian; Hippler, Michael

2013-01-01

Iron is a crucial cofactor in numerous redox-active proteins operating in bioenergetic pathways including respiration and photosynthesis. Cellular iron management is essential to sustain sufficient energy production and minimize oxidative stress. To produce energy for cell growth, the green alga Chlamydomonas reinhardtii possesses the metabolic flexibility to use light and/or carbon sources such as acetate. To investigate the interplay between the iron-deficiency response and growth requirements under distinct trophic conditions, we took a quantitative proteomics approach coupled to innovative hierarchical clustering using different “distance-linkage combinations” and random noise injection. Protein co-expression analyses of the combined data sets revealed insights into cellular responses governing acclimation to iron deprivation and regulation associated with photosynthesis dependent growth. Photoautotrophic growth requirements as well as the iron deficiency induced specific metabolic enzymes and stress related proteins, and yet differences in the set of induced enzymes, proteases, and redox-related polypeptides were evident, implying the establishment of distinct response networks under the different conditions. Moreover, our data clearly support the notion that the iron deficiency response includes a hierarchy for iron allocation within organelles in C. reinhardtii. Importantly, deletion of a bifunctional alcohol and acetaldehyde dehydrogenase (ADH1), which is induced under low iron based on the proteomic data, attenuates the remodeling of the photosynthetic machinery in response to iron deficiency, and at the same time stimulates expression of stress-related proteins such as NDA2, LHCSR3, and PGRL1. This finding provides evidence that the coordinated regulation of bioenergetics pathways and iron deficiency response is sensitive to the cellular and chloroplast metabolic and/or redox status, consistent with systems approach data. PMID:23820728

Wavelet Algorithms for Illumination Computations

NASA Astrophysics Data System (ADS)

Schroder, Peter

One of the core problems of computer graphics is the computation of the equilibrium distribution of light in a scene. This distribution is given as the solution to a Fredholm integral equation of the second kind involving an integral over all surfaces in the scene. In the general case such solutions can only be numerically approximated, and are generally costly to compute, due to the geometric complexity of typical computer graphics scenes. For this computation both Monte Carlo and finite element techniques (or hybrid approaches) are typically used. A simplified version of the illumination problem is known as radiosity, which assumes that all surfaces are diffuse reflectors. For this case hierarchical techniques, first introduced by Hanrahan et al. (32), have recently gained prominence. The hierarchical approaches lead to an asymptotic improvement when only finite precision is required. The resulting algorithms have cost proportional to O(k^2 + n) versus the usual O(n^2) (k is the number of input surfaces, n the number of finite elements into which the input surfaces are meshed). Similarly a hierarchical technique has been introduced for the more general radiance problem (which allows glossy reflectors) by Aupperle et al. (6). In this dissertation we show the equivalence of these hierarchical techniques to the use of a Haar wavelet basis in a general Galerkin framework. By so doing, we come to a deeper understanding of the properties of the numerical approximations used and are able to extend the hierarchical techniques to higher orders. In particular, we show the correspondence of the geometric arguments underlying hierarchical methods to the theory of Calderon-Zygmund operators and their sparse realization in wavelet bases. The resulting wavelet algorithms for radiosity and radiance are analyzed and numerical results achieved with our implementation are reported. We find that the resulting algorithms achieve smaller and smoother errors at equivalent work.

Hierarchical drivers of reef-fish metacommunity structure.

PubMed

MacNeil, M Aaron; Graham, Nicholas A J; Polunin, Nicholas V C; Kulbicki, Michel; Galzin, René; Harmelin-Vivien, Mireille; Rushton, Steven P

2009-01-01

Coral reefs are highly complex ecological systems, where multiple processes interact across scales in space and time to create assemblages of exceptionally high biodiversity. Despite the increasing frequency of hierarchically structured sampling programs used in coral-reef science, little progress has been made in quantifying the relative importance of processes operating across multiple scales. The vast majority of reef studies are conducted, or at least analyzed, at a single spatial scale, ignoring the implicitly hierarchical structure of the overall system in favor of small-scale experiments or large-scale observations. Here we demonstrate how alpha (mean local number of species), beta diversity (degree of species dissimilarity among local sites), and gamma diversity (overall species richness) vary with spatial scale, and using a hierarchical, information-theoretic approach, we evaluate the relative importance of site-, reef-, and atoll-level processes driving the fish metacommunity structure among 10 atolls in French Polynesia. Process-based models, representing well-established hypotheses about drivers of reef-fish community structure, were assembled into a candidate set of 12 hierarchical linear models. Variation in fish abundance, biomass, and species richness were unevenly distributed among transect, reef, and atoll levels, establishing the relative contribution of variation at these spatial scales to the structure of the metacommunity. Reef-fish biomass, species richness, and the abundance of most functional-groups corresponded primarily with transect-level habitat diversity and atoll-lagoon size, whereas detritivore and grazer abundances were largely correlated with potential covariates of larval dispersal. Our findings show that (1) within-transect and among-atoll factors primarily drive the relationship between alpha and gamma diversity in this reef-fish metacommunity; (2) habitat is the primary correlate with reef-fish metacommunity structure at multiple spatial scales; and (3) inter-atoll connectedness was poorly correlated with the nonrandom clustering of reef-fish species. These results demonstrate the importance of modeling hierarchical data and processes in understanding reef-fish metacommunity structure.

Biological hierarchies and the nature of extinction.

PubMed

Congreve, Curtis R; Falk, Amanda R; Lamsdell, James C

2018-05-01

Hierarchy theory recognises that ecological and evolutionary units occur in a nested and interconnected hierarchical system, with cascading effects occurring between hierarchical levels. Different biological disciplines have routinely come into conflict over the primacy of different forcing mechanisms behind evolutionary and ecological change. These disconnects arise partly from differences in perspective (with some researchers favouring ecological forcing mechanisms while others favour developmental/historical mechanisms), as well as differences in the temporal framework in which workers operate. In particular, long-term palaeontological data often show that large-scale (macro) patterns of evolution are predominantly dictated by shifts in the abiotic environment, while short-term (micro) modern biological studies stress the importance of biotic interactions. We propose that thinking about ecological and evolutionary interactions in a hierarchical framework is a fruitful way to resolve these conflicts. Hierarchy theory suggests that changes occurring at lower hierarchical levels can have unexpected, complex effects at higher scales due to emergent interactions between simple systems. In this way, patterns occurring on short- and long-term time scales are equally valid, as changes that are driven from lower levels will manifest in different forms at higher levels. We propose that the dual hierarchy framework fits well with our current understanding of evolutionary and ecological theory. Furthermore, we describe how this framework can be used to understand major extinction events better. Multi-generational attritional loss of reproductive fitness (MALF) has recently been proposed as the primary mechanism behind extinction events, whereby extinction is explainable solely through processes that result in extirpation of populations through a shutdown of reproduction. While not necessarily explicit, the push to explain extinction through solely population-level dynamics could be used to suggest that environmentally mediated patterns of extinction or slowed speciation across geological time are largely artefacts of poor preservation or a coarse temporal scale. We demonstrate how MALF fits into a hierarchical framework, showing that MALF can be a primary forcing mechanism at lower scales that still results in differential survivorship patterns at the species and clade level which vary depending upon the initial environmental forcing mechanism. Thus, even if MALF is the primary mechanism of extinction across all mass extinction events, the primary environmental cause of these events will still affect the system and result in differential responses. Therefore, patterns at both temporal scales are relevant. © 2017 Cambridge Philosophical Society.

Causal Relation Analysis Tool of the Case Study in the Engineer Ethics Education

NASA Astrophysics Data System (ADS)

Suzuki, Yoshio; Morita, Keisuke; Yasui, Mitsukuni; Tanada, Ichirou; Fujiki, Hiroyuki; Aoyagi, Manabu

In engineering ethics education, the virtual experiencing of dilemmas is essential. Learning through the case study method is a particularly effective means. Many case studies are, however, difficult to deal with because they often include many complex causal relationships and social factors. It would thus be convenient if there were a tool that could analyze the factors of a case example and organize them into a hierarchical structure to get a better understanding of the whole picture. The tool that was developed applies a cause-and-effect matrix and simple graph theory. It analyzes the causal relationship between facts in a hierarchical structure and organizes complex phenomena. The effectiveness of this tool is shown by presenting an actual example.

On the usefulness of 'what' and 'where' pathways in vision.

PubMed

de Haan, Edward H F; Cowey, Alan

2011-10-01

The primate visual brain is classically portrayed as a large number of separate 'maps', each dedicated to the processing of specific visual cues, such as colour, motion or faces and their many features. In order to understand this fractionated architecture, the concept of cortical 'pathways' or 'streams' was introduced. In the currently prevailing view, the different maps are organised hierarchically into two major pathways, one involved in recognition and memory (the ventral stream or 'what' pathway) and the other in the programming of action (the dorsal stream or 'where' pathway). In this review, we question this heuristically influential but potentially misleading linear hierarchical pathway model and argue instead for a 'patchwork' or network model. Copyright © 2011 Elsevier Ltd. All rights reserved.

The role of the non-collagenous matrix in tendon function.

PubMed

Thorpe, Chavaunne T; Birch, Helen L; Clegg, Peter D; Screen, Hazel R C

2013-08-01

Tendon consists of highly ordered type I collagen molecules that are grouped together to form subunits of increasing diameter. At each hierarchical level, the type I collagen is interspersed with a predominantly non-collagenous matrix (NCM) (Connect. Tissue Res., 6, 1978, 11). Whilst many studies have investigated the structure, organization and function of the collagenous matrix within tendon, relatively few have studied the non-collagenous components. However, there is a growing body of research suggesting the NCM plays an important role within tendon; adaptations to this matrix may confer the specific properties required by tendons with different functions. Furthermore, age-related alterations to non-collagenous proteins have been identified, which may affect tendon resistance to injury. This review focuses on the NCM within the tensional region of developing and mature tendon, discussing the current knowledge and identifying areas that require further study to fully understand structure-function relationships within tendon. This information will aid in the development of appropriate techniques for tendon injury prevention and treatment. © 2013 The Authors. International Journal of Experimental Pathology © 2013 International Journal of Experimental Pathology.

Spatially Resolved Quantification of Chromatin Condensation through Differential Local Rheology in Cell Nuclei Fluorescence Lifetime Imaging

PubMed Central

Spagnol, Stephen T.; Dahl, Kris Noel

2016-01-01

The linear sequence of DNA encodes access to the complete set of proteins that carry out cellular functions. Yet, much of the functionality appropriate for each cell is nested within layers of dynamic regulation and organization, including a hierarchy of chromatin structural states and spatial arrangement within the nucleus. There remain limitations in our understanding of gene expression within the context of nuclear organization from an inability to characterize hierarchical chromatin organization in situ. Here we demonstrate the use of fluorescence lifetime imaging microscopy (FLIM) to quantify and spatially resolve chromatin condensation state using cell-permeable, DNA-binding dyes (Hoechst 33342 and PicoGreen). Through in vitro and in situ experiments we demonstrate the sensitivity of fluorescence lifetime to condensation state through the mechanical effects that accompany the structural changes and are reflected through altered viscosity. The establishment of FLIM for resolving and quantifying chromatin condensation state opens the door for single-measurement mechanical studies of the nucleus and for characterizing the role of genome structure and organization in nuclear processes that accompany physiological and pathological changes. PMID:26765322

Diffusion of aromatic hydrocarbons in hierarchical mesoporous H-ZSM-5 zeolite

DOE PAGES

Bu, Lintao; Nimlos, Mark R.; Robichaud, David J.; ...

2018-02-08

Hierarchical mesoporous zeolites exhibit higher catalytic activities and longer lifetime compared to the traditional microporous zeolites due to improved diffusivity of substrate molecules and their enhanced access to the zeolite active sites. Understanding diffusion of biomass pyrolysis vapors and their upgraded products in such materials is fundamentally important during catalytic fast pyrolysis (CFP) of lignocellulosic biomass, since diffusion makes major contribution to determine shape selectivity and product distribution. However, diffusivities of biomass relevant species in hierarchical mesoporous zeolites are poorly characterized, primarily due to the limitations of the available experimental technology. In this work, molecular dynamics (MD) simulations are utilizedmore » to investigate the diffusivities of several selected coke precursor molecules, benzene, naphthalene, and anthracene, in hierarchical mesoporous H-ZSM-5 zeolite. The effects of temperature and size of mesopores on the diffusivity of the chosen model compounds are examined. The simulation results demonstrate that diffusion within the microspores as well as on the external surface of mesoporous H-ZSM-5 dominates only at low temperature. At pyrolysis relevant temperatures, mass transfer is essentially conducted via diffusion along the mesopores. Additionally, the results illustrate the heuristic diffusion model, such as the extensively used Knudsen diffusion, overestimates the diffusion of bulky molecules in the mesopores, thus making MD simulation a powerful and compulsory approach to explore diffusion in zeolites.« less

Understanding Diffusion in Hierarchical Zeolites with House-of-Cards Nanosheets.

PubMed

Bai, Peng; Haldoupis, Emmanuel; Dauenhauer, Paul J; Tsapatsis, Michael; Siepmann, J Ilja

2016-08-23

Introducing mesoporosity to conventional microporous sorbents or catalysts is often proposed as a solution to enhance their mass transport rates. Here, we show that diffusion in these hierarchical materials is more complex and exhibits non-monotonic dependence on sorbate loading. Our atomistic simulations of n-hexane in a model system containing microporous nanosheets and mesopore channels indicate that diffusivity can be smaller than in a conventional zeolite with the same micropore structure, and this observation holds true even if we confine the analysis to molecules completely inside the microporous nanosheets. Only at high sorbate loadings or elevated temperatures, when the mesopores begin to be sufficiently populated, does the overall diffusion in the hierarchical material exceed that in conventional microporous zeolites. Our model system is free of structural defects, such as pore blocking or surface disorder, that are typically invoked to explain slower-than-expected diffusion phenomena in experimental measurements. Examination of free energy profiles and visualization of molecular diffusion pathways demonstrates that the large free energy cost (mostly enthalpic in origin) for escaping from the microporous region into the mesopores leads to more tortuous diffusion paths and causes this unusual transport behavior in hierarchical nanoporous materials. This knowledge allows us to re-examine zero-length-column chromatography data and show that these experimental measurements are consistent with the simulation data when the crystallite size instead of the nanosheet thickness is used for the nominal diffusional length.

Temporal Dynamics and Spatial Variation of Azoxystrobin and Propiconazole Resistance in Zymoseptoria tritici: A Hierarchical Survey of Commercial Winter Wheat Fields in the Willamette Valley, Oregon.

PubMed

Hagerty, Christina H; Anderson, Nicole P; Mundt, Christopher C

2017-03-01

Fungicide resistance can cause disease control failure in agricultural systems, and is particularly concerning with Zymoseptoria tritici, the causal agent of Septoria tritici blotch of wheat. In North America, the first quinone outside inhibitor resistance in Z. tritici was discovered in the Willamette Valley of Oregon in 2012, which prompted this hierarchical survey of commercial winter wheat fields to monitor azoxystrobin- and propiconazole-resistant Z. tritici. Surveys were conducted in June 2014, January 2015, May 2015, and January 2016. The survey was organized in a hierarchical scheme: regions within the Willamette Valley, fields within the region, transects within the field, and samples within the transect. Overall, frequency of azoxystrobin-resistant isolates increased from 63 to 93% from June 2014 to January 2016. Resistance to azoxystrobin increased over time even within fields receiving no strobilurin applications. Propiconazole sensitivity varied over the course of the study but, overall, did not significantly change. Sensitivity to both fungicides showed no regional aggregation within the Willamette Valley. Greater than 80% of spatial variation in fungicide sensitivity was at the smallest hierarchical scale (within the transect) of the survey for both fungicides, and the resistance phenotypes were randomly distributed within sampled fields. Results suggest a need for a better understanding of the dynamics of fungicide resistance at the landscape level.

Hierarchical Nanomorphologies Promote Exciton Dissociation in Polymer: Fullerene Bulk Heterojunction Solar Cells

NASA Astrophysics Data System (ADS)

Chen, Wei; Darling, Seth

2012-02-01

In the last fifteen years, research efforts have led to organic photovoltaic (OPV) devices with power conversion efficiencies (PCEs) up to ˜8%, but these values are still insufficient for the devices to become widely marketable. To further improve solar cell performance a thorough understanding of the complex structure-property relationships in the OPV devices is required. In this work, we demonstrated that the OPV active layer of PTB7:fullerene bulk heterojunction (BHJ) solar cells, which set a historic record of PCE (7.4%), involves hierarchical nanomorphologies ranging from several nanometers of crystallites to tens of nanometers of nanocrystallite aggregates in PTB7-rich and fullerene-rich domains, themselves hundreds of nanometers in size. These hierarchical nanomorphologies with optimum crystallinity and intermixing of PTB7 with fullerenes are coupled to significantly enhanced exciton dissociation, which consequently contribute to photocurrent, leading to the superior performance of PTB7:fullerene BHJ solar cells. New insights of performance-related structures afforded by the current study should aid in the rational design of even higher performance polymeric solar cells.

Implications of the Hierarchical Structure of Psychopathology for Psychiatric Neuroimaging.

PubMed

Zald, David H; Lahey, Benjamin B

2017-05-01

Research into the neurobiological substrates of psychopathology has been impeded by heterogeneity within diagnostic categories, comorbidity among mental disorders, and the presence of symptoms that transcend diagnostic categories. Solutions to these issues increasingly focus neurobiological research on isolated or narrow groupings of symptoms or functional constructs rather than categorical diagnoses. Here we argue for a more integrative approach that also incorporates the broad hierarchical structure of psychopathological symptoms and their etiological mechanisms. This approach places clinical neuroscience research in the context of a hierarchy of empirically defined factors of symptoms such as internalizing disorders, externalizing disorders, and the general factor of psychopathology. Application of this hierarchical approach has the potential to reveal neural substrates that nonspecifically contribute to multiple forms of psychopathology and their comorbidity, and in doing so, facilitate the study of mechanisms that are specific to single dimensions and subsets of symptoms. Neurobiological research on the hierarchy of dimensions of psychopathology is only just beginning to emerge, but has the potential to radically alter our understanding of the neurobiology of abnormal behavior.

Risk Assessment for Mobile Systems Through a Multilayered Hierarchical Bayesian Network.

PubMed

Li, Shancang; Tryfonas, Theo; Russell, Gordon; Andriotis, Panagiotis

2016-08-01

Mobile systems are facing a number of application vulnerabilities that can be combined together and utilized to penetrate systems with devastating impact. When assessing the overall security of a mobile system, it is important to assess the security risks posed by each mobile applications (apps), thus gaining a stronger understanding of any vulnerabilities present. This paper aims at developing a three-layer framework that assesses the potential risks which apps introduce within the Android mobile systems. A Bayesian risk graphical model is proposed to evaluate risk propagation in a layered risk architecture. By integrating static analysis, dynamic analysis, and behavior analysis in a hierarchical framework, the risks and their propagation through each layer are well modeled by the Bayesian risk graph, which can quantitatively analyze risks faced to both apps and mobile systems. The proposed hierarchical Bayesian risk graph model offers a novel way to investigate the security risks in mobile environment and enables users and administrators to evaluate the potential risks. This strategy allows to strengthen both app security as well as the security of the entire system.

Quantifying inter- and intra-population niche variability using hierarchical bayesian stable isotope mixing models.

PubMed

Semmens, Brice X; Ward, Eric J; Moore, Jonathan W; Darimont, Chris T

2009-07-09

Variability in resource use defines the width of a trophic niche occupied by a population. Intra-population variability in resource use may occur across hierarchical levels of population structure from individuals to subpopulations. Understanding how levels of population organization contribute to population niche width is critical to ecology and evolution. Here we describe a hierarchical stable isotope mixing model that can simultaneously estimate both the prey composition of a consumer diet and the diet variability among individuals and across levels of population organization. By explicitly estimating variance components for multiple scales, the model can deconstruct the niche width of a consumer population into relevant levels of population structure. We apply this new approach to stable isotope data from a population of gray wolves from coastal British Columbia, and show support for extensive intra-population niche variability among individuals, social groups, and geographically isolated subpopulations. The analytic method we describe improves mixing models by accounting for diet variability, and improves isotope niche width analysis by quantitatively assessing the contribution of levels of organization to the niche width of a population.

Hierarchical Model for the Analysis of Scattering Data of Complex Materials

DOE PAGES

Oyedele, Akinola; Mcnutt, Nicholas W.; Rios, Orlando; ...

2016-05-16

Interpreting the results of scattering data for complex materials with a hierarchical structure in which at least one phase is amorphous presents a significant challenge. Often the interpretation relies on the use of large-scale molecular dynamics (MD) simulations, in which a structure is hypothesized and from which a radial distribution function (RDF) can be extracted and directly compared against an experimental RDF. This computationally intensive approach presents a bottleneck in the efficient characterization of the atomic structure of new materials. Here, we propose and demonstrate an approach for a hierarchical decomposition of the RDF in which MD simulations are replacedmore » by a combination of tractable models and theory at the atomic scale and the mesoscale, which when combined yield the RDF. We apply the procedure to a carbon composite, in which graphitic nanocrystallites are distributed in an amorphous domain. We compare the model with the RDF from both MD simulation and neutron scattering data. Ultimately, this procedure is applicable for understanding the fundamental processing-structure-property relationships in complex magnetic materials.« less

Beyond comorbidity: Toward a dimensional and hierarchal approach to understanding psychopathology across the lifespan

PubMed Central

Forbes, Miriam K.; Tackett, Jennifer L.; Markon, Kristian E.; Krueger, Robert F.

2016-01-01

In this review, we propose a novel developmentally informed framework to push research beyond a focus on comorbidity between discrete diagnostic categories, and to move towards research based on the well-validated dimensional and hierarchical structure of psychopathology. For example, a large body of research speaks to the validity and utility of the Internalizing and Externalizing (IE) spectra as organizing constructs for research on common forms of psychopathology. The IE spectra act as powerful explanatory variables that channel the psychopathological effects of genetic and environmental risk factors, predict adaptive functioning, and account for the likelihood of disorder-level manifestations of psychopathology. As such, our proposed theoretical framework uses the IE spectra as central constructs to guide future psychopathology research across the lifespan. The framework is particularly flexible, as any of the facets or factors from the dimensional and hierarchical structure of psychopathology can form the focus of research. We describe the utility and strengths of this framework for developmental psychopathology in particular, and explore avenues for future research. PMID:27739384

Implications of the Hierarchical Structure of Psychopathology for Psychiatric Neuroimaging

PubMed Central

Zald, David H.; Lahey, Benjamin B.

2017-01-01

Research into the neurobiological substrates of psychopathology has been impeded by heterogeneity within diagnostic categories, comorbidity among mental disorders, and the presence of symptoms that transcend diagnostic categories. Solutions to these issues increasingly focus neurobiological research on isolated or narrow groupings of symptoms or functional constructs rather than categorical diagnoses. Here we argue for a more integrative approach that also incorporates the broad hierarchical structure of psychopathological symptoms and their etiological mechanisms. This approach places clinical neuroscience research in the context of a hierarchy of empirically defined factors of symptoms such as internalizing disorders, externalizing disorders, and the general factor of psychopathology. Application of this hierarchical approach has the potential to reveal neural substrates that nonspecifically contribute to multiple forms of psychopathology and their comorbidity, and in doing so, facilitate the study of mechanisms that are specific to single dimensions and subsets of symptoms. Neurobiological research on the hierarchy of dimensions of psychopathology is only just beginning to emerge, but has the potential to radically alter our understanding of the neurobiology of abnormal behavior. PMID:28713866

Tandem Repeat Proteins Inspired By Squid Ring Teeth

NASA Astrophysics Data System (ADS)

Pena-Francesch, Abdon

Proteins are large biomolecules consisting of long chains of amino acids that hierarchically assemble into complex structures, and provide a variety of building blocks for biological materials. The repetition of structural building blocks is a natural evolutionary strategy for increasing the complexity and stability of protein structures. However, the relationship between amino acid sequence, structure, and material properties of protein systems remains unclear due to the lack of control over the protein sequence and the intricacies of the assembly process. In order to investigate the repetition of protein building blocks, a recently discovered protein from squids is examined as an ideal protein system. Squid ring teeth are predatory appendages located inside the suction cups that provide a strong grasp of prey, and are solely composed of a group of proteins with tandem repetition of building blocks. The objective of this thesis is the understanding of sequence, structure and property relationship in repetitive protein materials inspired in squid ring teeth for the first time. Specifically, this work focuses on squid-inspired structural proteins with tandem repeat units in their sequence (i.e., repetition of alternating building blocks) that are physically cross-linked via beta-sheet structures. The research work presented here tests the hypothesis that, in these systems, increasing the number of building blocks in the polypeptide chain decreases the protein network defects and improves the material properties. Hence, the sequence, nanostructure, and properties (thermal, mechanical, and conducting) of tandem repeat squid-inspired protein materials are examined. Spectroscopic structural analysis, advanced materials characterization, and entropic elasticity theory are combined to elucidate the structure and material properties of these repetitive proteins. This approach is applied not only to native squid proteins but also to squid-inspired synthetic polypeptides that allow for a fine control of the sequence and network morphology. The results provided in this work establish a clear dependence between the repetitive building blocks, the network morphology, and the properties of squid-inspired repetitive protein materials. Increasing the number of tandem repeat units in SRT-inspired proteins led to more effective protein networks with superior properties. Through increasing tandem repetition and optimization of network morphology, highly efficient protein materials capable of withstanding deformations up to 400% of their original length, with MPa-GPa modulus, high energy absorption (50 MJ m-3), peak proton conductivity of 3.7 mS cm-1 (at pH 7, highest reported to date for biological materials), and peak thermal conductivity of 1.4 W m-1 K -1 (which exceeds that of most polymer materials) were developed. These findings introduce new design rules in the engineering of proteins based on tandem repetition and morphology control, and provide a novel framework for tailoring and optimizing the properties of protein-based materials.

Bim and VDAC1 are hierarchically essential for mitochondrial ATF2 mediated cell death.

PubMed

Liu, Zhaoyun; Luo, Qianfu; Guo, Chunbao

2015-01-01

ATF2 mediated cytochrome c release is the formation of a channel with some unknown factors larger than that of the individual proteins. BHS-only proteins (BH3s), such as Bim, could induce BAX and VDAC, forming a new channel. According to this facts, we can speculated that there is possible signal relationship with BH3s and ATF2, which is associated with mitochondrial-based death programs. The growth inhibitory effects of mitochondrial ATF2 were tested in cancer cell lines B16F10, A549, EG7, and LL2. Apoptosis was measured by flow cytometry. The effects of ATF2 and levels of apoptosis regulatory proteins were measured by Western blotting. The interaction of proteins were evaluated by immunoprecipitation analysis. The in vivo antitumor activity of mitochondrial ATF2 were tested in xenograft B16F10 models. Genotoxic stress enabled mitochondrial ATF2 accumulation, perturbing the HK1-VDAC1 complex, increasing mitochondrial permeability, and promoting apoptosis. ATF2 inhibition strongly reduced the conformational activation of Bim, suggesting that Bim acts downstream of ATF2. Although Bim downregulation had no effect on ATF2 activation, Bim knockdown abolished VDAC1 activation; the failure of VDAC1 activation in Bim-depleted cells could be reversed by the BH3-only protein mimic ABT-737. We also demonstrate that silencing of ATF2 in B16F10 cells increases both the incidence and prevalence of tumor xenografts in vivo, whereas stably mitochondrial ATF2 transfection inhibited B16F10 tumor xenografts growth. Altogether, these results show that ATF2 is a component of the apoptosis machinery that involves a hierarchical contribution of ATF2, Bim, and VDAC1. Our data offer new insight into the mechanism of mitochondrial ATF2 in mitochondrial apoptosis.

Applications of cell-free protein synthesis in synthetic biology: Interfacing bio-machinery with synthetic environments.

PubMed

Lee, Kyung-Ho; Kim, Dong-Myung

2013-11-01

Synthetic biology is built on the synthesis, engineering, and assembly of biological parts. Proteins are the first components considered for the construction of systems with designed biological functions because proteins carry out most of the biological functions and chemical reactions inside cells. Protein synthesis is considered to comprise the most basic levels of the hierarchical structure of synthetic biology. Cell-free protein synthesis has emerged as a powerful technology that can potentially transform the concept of bioprocesses. With the ability to harness the synthetic power of biology without many of the constraints of cell-based systems, cell-free protein synthesis enables the rapid creation of protein molecules from diverse sources of genetic information. Cell-free protein synthesis is virtually free from the intrinsic constraints of cell-based methods and offers greater flexibility in system design and manipulability of biological synthetic machinery. Among its potential applications, cell-free protein synthesis can be combined with various man-made devices for rapid functional analysis of genomic sequences. This review covers recent efforts to integrate cell-free protein synthesis with various reaction devices and analytical platforms. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Single Honeybee Silk Protein Mimics Properties of Multi-Protein Silk

PubMed Central

Sutherland, Tara D.; Church, Jeffrey S.; Hu, Xiao; Huson, Mickey G.; Kaplan, David L.; Weisman, Sarah

2011-01-01

Honeybee silk is composed of four fibrous proteins that, unlike other silks, are readily synthesized at full-length and high yield. The four silk genes have been conserved for over 150 million years in all investigated bee, ant and hornet species, implying a distinct functional role for each protein. However, the amino acid composition and molecular architecture of the proteins are similar, suggesting functional redundancy. In this study we compare materials generated from a single honeybee silk protein to materials containing all four recombinant proteins or to natural honeybee silk. We analyse solution conformation by dynamic light scattering and circular dichroism, solid state structure by Fourier Transform Infrared spectroscopy and Raman spectroscopy, and fiber tensile properties by stress-strain analysis. The results demonstrate that fibers artificially generated from a single recombinant silk protein can reproduce the structural and mechanical properties of the natural silk. The importance of the four protein complex found in natural silk may lie in biological silk storage or hierarchical self-assembly. The finding that the functional properties of the mature material can be achieved with a single protein greatly simplifies the route to production for artificial honeybee silk. PMID:21311767

Hierarchical layered and semantic-based image segmentation using ergodicity map

NASA Astrophysics Data System (ADS)

Yadegar, Jacob; Liu, Xiaoqing

2010-04-01

Image segmentation plays a foundational role in image understanding and computer vision. Although great strides have been made and progress achieved on automatic/semi-automatic image segmentation algorithms, designing a generic, robust, and efficient image segmentation algorithm is still challenging. Human vision is still far superior compared to computer vision, especially in interpreting semantic meanings/objects in images. We present a hierarchical/layered semantic image segmentation algorithm that can automatically and efficiently segment images into hierarchical layered/multi-scaled semantic regions/objects with contextual topological relationships. The proposed algorithm bridges the gap between high-level semantics and low-level visual features/cues (such as color, intensity, edge, etc.) through utilizing a layered/hierarchical ergodicity map, where ergodicity is computed based on a space filling fractal concept and used as a region dissimilarity measurement. The algorithm applies a highly scalable, efficient, and adaptive Peano- Cesaro triangulation/tiling technique to decompose the given image into a set of similar/homogenous regions based on low-level visual cues in a top-down manner. The layered/hierarchical ergodicity map is built through a bottom-up region dissimilarity analysis. The recursive fractal sweep associated with the Peano-Cesaro triangulation provides efficient local multi-resolution refinement to any level of detail. The generated binary decomposition tree also provides efficient neighbor retrieval mechanisms for contextual topological object/region relationship generation. Experiments have been conducted within the maritime image environment where the segmented layered semantic objects include the basic level objects (i.e. sky/land/water) and deeper level objects in the sky/land/water surfaces. Experimental results demonstrate the proposed algorithm has the capability to robustly and efficiently segment images into layered semantic objects/regions with contextual topological relationships.

Supramolecular Engineering of Hierarchically Self-Assembled, Bioinspired, Cholesteric Nanocomposites Formed by Cellulose Nanocrystals and Polymers.

PubMed

Zhu, Baolei; Merindol, Remi; Benitez, Alejandro J; Wang, Baochun; Walther, Andreas

2016-05-04

Natural composites are hierarchically structured by combination of ordered colloidal and molecular length scales. They inspire future, biomimetic, and lightweight nanocomposites, in which extraordinary mechanical properties are in reach by understanding and mastering hierarchical structure formation as tools to engineer multiscale deformation mechanisms. Here we describe a hierarchically self-assembled, cholesteric nanocomposite with well-defined colloid-based helical structure and supramolecular hydrogen bonds engineered on the molecular level in the polymer matrix. We use reversible addition-fragmentation transfer polymerization to synthesize well-defined hydrophilic, nonionic polymers with a varying functionalization density of 4-fold hydrogen-bonding ureidopyrimidinone (UPy) motifs. We show that these copolymers can be coassembled with cellulose nanocrystals (CNC), a sustainable, stiff, rod-like reinforcement, to give ordered cholesteric phases with characteristic photonic stop bands. The dimensions of the helical pitch are controlled by the ratio of polymer/CNC, confirming a smooth integration into the colloidal structure. With respect to the effect of the supramolecular motifs, we demonstrate that those regulate the swelling when exposing the biomimetic hybrids to water, and they allow engineering the photonic response. Moreover, the amount of hydrogen bonds and the polymer fraction are decisive in defining the mechanical properties. An Ashby plot comparing previous ordered CNC-based nanocomposites with our new hierarchical ones reveals that molecular engineering allows us to span an unprecedented mechanical property range from highest inelastic deformation (strain up to ∼13%) to highest stiffness (E ∼ 15 GPa) and combinations of both. We envisage that further rational design of the molecular interactions will provide efficient tools for enhancing the multifunctional property profiles of such bioinspired nanocomposites.

Clinical time series prediction: Toward a hierarchical dynamical system framework.

PubMed

Liu, Zitao; Hauskrecht, Milos

2015-09-01

Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. We tested our framework by first learning the time series model from data for the patients in the training set, and then using it to predict future time series values for the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive performance. Copyright © 2014 Elsevier B.V. All rights reserved.

Reasoning about Evolution's Grand Patterns: College Students' Understanding of the Tree of Life

ERIC Educational Resources Information Center

Novick, Laura R.; Catley, Kefyn M.

2013-01-01

Tree thinking involves using cladograms, hierarchical diagrams depicting the evolutionary history of a set of taxa, to reason about evolutionary relationships and support inferences. Tree thinking is indispensable in modern science. College students' tree-thinking skills were investigated using tree (much more common in professional biology) and…

Understanding the Effects of Personal and School Religiosity on the Decision to Abort a Premarital Pregnancy

ERIC Educational Resources Information Center

Adamczyk, Amy

2009-01-01

Although much research has examined the relationship between religion and abortion attitudes, few studies have examined whether religion influences abortion behavior. This study looks at whether individual and school religiosity influence reported abortion behavior among women who become pregnant while unmarried. Hierarchical Logistic Models are…

Multiple drivers, scales, and interactions influence southern Appalachian stream salamander occupancy

Treesearch

Kristen K. Cecala; John C. Maerz; Brian J. Halstead; John R. Frisch; Ted L. Gragson; Jeffrey Hepinstall-Cymerman; David S. Leigh; C. Rhett Jackson; James T. Peterson; Catherine M. Pringle

2018-01-01

Understanding how factors that vary in spatial scale relate to population abundance is vital to forecasting species responses to environmental change. Stream and river ecosystems are inherently hierarchical, potentially resulting in organismal responses to fine‐scale changes in patch characteristics that are conditional on the watershed context. Here, we...

Hierarchical analysis of species distributions and abundance across environmental gradients

Treesearch

Jeffery Diez; Ronald H. Pulliam

2007-01-01

Abiotic and biotic processes operate at multiple spatial and temporal scales to shape many ecological processes, including species distributions and demography. Current debate about the relative roles of niche-based and stochastic processes in shaping species distributions and community composition reflects, in part, the challenge of understanding how these processes...

Fostering Radical Conceptual Change through Dual-Situated Learning Model

ERIC Educational Resources Information Center

She, Hsiao-Ching

2004-01-01

This article examines how the Dual-Situated Learning Model (DSLM) facilitates a radical change of concepts that involve the understanding of matter, process, and hierarchical attributes. The DSLM requires knowledge of students' prior beliefs of science concepts and the nature of these concepts. In addition, DSLM also serves two functions: it…

A Dynamic Systems Theory Model of Visual Perception Development

ERIC Educational Resources Information Center

Coté, Carol A.

2015-01-01

This article presents a model for understanding the development of visual perception from a dynamic systems theory perspective. It contrasts to a hierarchical or reductionist model that is often found in the occupational therapy literature. In this proposed model vision and ocular motor abilities are not foundational to perception, they are seen…

An Investigation of Teacher Impact on Student Inquiry Science Performance Using a Hierarchical Linear Model

ERIC Educational Resources Information Center

Liu, Ou Lydia; Lee, Hee-Sun; Linn, Marcia C.

2010-01-01

Teachers play a central role in inquiry science classrooms. In this study, we investigate how seven teacher variables (i.e., gender, experience, perceived importance of inquiry and traditional teaching, workshop attendance, partner teacher, use of technology) affect student knowledge integration understanding of science topics drawing on previous…

Drawing the Line between Constituent Structure and Coherence Relations in Visual Narratives

ERIC Educational Resources Information Center

Cohn, Neil; Bender, Patrick

2017-01-01

Theories of visual narrative understanding have often focused on the changes in meaning across a sequence, like shifts in characters, spatial location, and causation, as cues for breaks in the structure of a discourse. In contrast, the theory of visual narrative grammar posits that hierarchic "grammatical" structures operate at the…

More Content and More Depth: Coping with New GCSEs

ERIC Educational Resources Information Center

Douglas, Euan

2017-01-01

SOLO taxonomy models the levels of understanding within a topic; its hierarchal nature can support progression and challenge. Flipped learning is a strategy that uses homework to build background knowledge, thereby maximising the impact of lesson time. Both flipped learning and SOLO taxonomy can be used to support student learning, either combined…

Principals' Leadership Behaviors as Perceived by Teachers in At-Risk Middle Schools

ERIC Educational Resources Information Center

Johnson, R. Anthony

2011-01-01

A need for greater understanding of teachers' (N = 530) perceptions of the leadership behaviors of principals in Title I middle schools (n = 13) is prevalent exists. The researcher used the "Audit of Principal Effectiveness" survey to collect data. The researcher also used Hierarchical Linear Modeling as the quantitative analysis.…

Exploring Differential Bundle Functioning in Mathematics by Gender: The Effect of Hierarchical Modelling

ERIC Educational Resources Information Center

Ong, Yoke Mooi; Williams, Julian; Lamprianou, Iasonas

2013-01-01

Researchers interested in exploring substantive group differences are increasingly attending to bundles of items (or testlets): the aim is to understand how gender differences, for instance, are explained by differential performances on different types or bundles of items, hence differential bundle functioning (DBF). Some previous work has…

A Framework for Understanding Chinese Leadership: A Cultural Approach

ERIC Educational Resources Information Center

Liu, Peng

2017-01-01

Chinese culture is widely regarded as being dominated by Confucian thought, which is characterized as focusing on morality, relationalism and collectivism. Also, Chinese culture has been deemed to be very hierarchical and lacking in a sense of autonomy. However, there has been little attention paid to other diverse elements in Chinese culture and…

Troubleshooting Complex Equipment in the Military Services: Research and Prospects. Technical Report No. 92.

ERIC Educational Resources Information Center

Bond, Nicholas A.; Towne, Douglas M.

Psychological approaches to the troubleshooting of complex military equipments are designed to improve the selection, motivation, and training of technicians. Methods for enhancing the understanding of the physical relations in equipment, the hierarchical analysis and practice of sub-skills, and the general logic of searching behavior are aspects…

Experience of Social Support among Working Mothers: A Concept Map

ERIC Educational Resources Information Center

Phang, A. Young; Lee, Ki-Hak

2009-01-01

The purpose of the study was to identify, categorize, and provide a model for the understanding of social support among Korean working mothers. The participants were interviewed and asked what kind of social support they received that allowed them to maintain work and family life. Using multidimensional scaling and hierarchical clustering analysis…

Development of a computational model on the neural activity patterns of a visual working memory in a hierarchical feedforward Network

NASA Astrophysics Data System (ADS)

An, Soyoung; Choi, Woochul; Paik, Se-Bum

2015-11-01

Understanding the mechanism of information processing in the human brain remains a unique challenge because the nonlinear interactions between the neurons in the network are extremely complex and because controlling every relevant parameter during an experiment is difficult. Therefore, a simulation using simplified computational models may be an effective approach. In the present study, we developed a general model of neural networks that can simulate nonlinear activity patterns in the hierarchical structure of a neural network system. To test our model, we first examined whether our simulation could match the previously-observed nonlinear features of neural activity patterns. Next, we performed a psychophysics experiment for a simple visual working memory task to evaluate whether the model could predict the performance of human subjects. Our studies show that the model is capable of reproducing the relationship between memory load and performance and may contribute, in part, to our understanding of how the structure of neural circuits can determine the nonlinear neural activity patterns in the human brain.

Modelling approaches for evaluating multiscale tendon mechanics

PubMed Central

Fang, Fei; Lake, Spencer P.

2016-01-01

Tendon exhibits anisotropic, inhomogeneous and viscoelastic mechanical properties that are determined by its complicated hierarchical structure and varying amounts/organization of different tissue constituents. Although extensive research has been conducted to use modelling approaches to interpret tendon structure–function relationships in combination with experimental data, many issues remain unclear (i.e. the role of minor components such as decorin, aggrecan and elastin), and the integration of mechanical analysis across different length scales has not been well applied to explore stress or strain transfer from macro- to microscale. This review outlines mathematical and computational models that have been used to understand tendon mechanics at different scales of the hierarchical organization. Model representations at the molecular, fibril and tissue levels are discussed, including formulations that follow phenomenological and microstructural approaches (which include evaluations of crimp, helical structure and the interaction between collagen fibrils and proteoglycans). Multiscale modelling approaches incorporating tendon features are suggested to be an advantageous methodology to understand further the physiological mechanical response of tendon and corresponding adaptation of properties owing to unique in vivo loading environments. PMID:26855747

Modeling methodology for supply chain synthesis and disruption analysis

NASA Astrophysics Data System (ADS)

Wu, Teresa; Blackhurst, Jennifer

2004-11-01

The concept of an integrated or synthesized supply chain is a strategy for managing today's globalized and customer driven supply chains in order to better meet customer demands. Synthesizing individual entities into an integrated supply chain can be a challenging task due to a variety of factors including conflicting objectives, mismatched incentives and constraints of the individual entities. Furthermore, understanding the effects of disruptions occurring at any point in the system is difficult when working toward synthesizing supply chain operations. Therefore, the goal of this research is to present a modeling methodology to manage the synthesis of a supply chain by linking hierarchical levels of the system and to model and analyze disruptions in the integrated supply chain. The contribution of this research is threefold: (1) supply chain systems can be modeled hierarchically (2) the performance of synthesized supply chain system can be evaluated quantitatively (3) reachability analysis is used to evaluate the system performance and verify whether a specific state is reachable, allowing the user to understand the extent of effects of a disruption.

Hierarchical Organization and Disassortative Mixing of Correlation-Based Weighted Financial Networks

NASA Astrophysics Data System (ADS)

Cai, Shi-Min; Zhou, Yan-Bo; Zhou, Tao; Zhou, Pei-Ling

Correlation-based weighted financial networks are analyzed to present cumulative distribution of strength with a power-law tail, which suggests that a small number of hub-like stocks have greater influence on the whole fluctuation of financial market than others. The relationship between clustering and connectivity of vertices emphasizes hierarchical organization, which has been depicted by minimal span tree in previous work. These results urge us to further study the mixing patter of financial network to understand the tendency for vertices to be connected to vertices that are like (or unlike) them in some way. The measurement of average nearest-neighbor degree running over classes of vertices with degree k shows a descending trend when k increases. This interesting result is first uncovered in our work, and suggests the disassortative mixing of financial network which refers to a bias in favor of connections between dissimilar vertices. All the results in weighted complex network aspect may provide some insights to deeper understand the underlying mechanism of financial market and model the evolution of financial market.

Wavelets and molecular structure

NASA Astrophysics Data System (ADS)

Carson, Mike

1996-08-01

The wavelet method offers possibilities for display, editing, and topological comparison of proteins at a user-specified level of detail. Wavelets are a mathematical tool that first found application in signal processing. The multiresolution analysis of a signal via wavelets provides a hierarchical series of `best' lower-resolution approximations. B-spline ribbons model the protein fold, with one control point per residue. Wavelet analysis sets limits on the information required to define the winding of the backbone through space, suggesting a recognizable fold is generated from a number of points equal to 1/4 or less the number of residues. Wavelets applied to surfaces and volumes show promise in structure-based drug design.

Cobalt ferrite nanocrystals: out-performing magnetotactic bacteria.

PubMed

Prozorov, Tanya; Palo, Pierre; Wang, Lijun; Nilsen-Hamilton, Marit; Jones, DeAnna; Orr, Daniel; Mallapragada, Surya K; Narasimhan, Balaji; Canfield, Paul C; Prozorov, Ruslan

2007-10-01

Magnetotactic bacteria produce exquisitely ordered chains of uniform magnetite (Fe(3)O(4)) nanocrystals, and the use of the bacterial mms6 protein allows for the shape-selective synthesis of Fe(3)O(4) nanocrystals. Cobalt ferrite (CoFe(2)O(4)) nanoparticles, on the other hand, are not known to occur in living organisms. Here we report on the use of the recombinant mms6 protein in a templated synthesis of CoFe(2)O(4) nanocrystals in vitro. We have covalently attached the full-length mms6 protein and a synthetic C-terminal domain of mms6 protein to self-assembling polymers in order to template hierarchical CoFe(2)O(4) nanostructures. This new synthesis pathway enables facile room-temperature shape-specific synthesis of complex magnetic crystalline nanomaterials with particle sizes in the range of 40-100 nm that are difficult to produce using conventional techniques.

Digested disorder

PubMed Central

Uversky, Vladimir N

2013-01-01

The current literature on intrinsically disordered proteins is blooming. A simple PubMed search for “intrinsically disordered protein OR natively unfolded protein” returns about 1,800 hits (as of June 17, 2013), with many papers published quite recently. To keep interested readers up to speed with this literature, we are starting a “Digested Disorder” project, which will encompass a series of reader’s digest type of publications aiming at the objective representation of the research papers and reviews on intrinsically disordered proteins. The only two criteria for inclusion in this digest are the publication date (a paper should be published within the covered time frame) and topic (a paper should be dedicated to any aspect of protein intrinsic disorder). The current digest covers papers published during the period of January, February and March of 2013. The papers are grouped hierarchically by topics they cover, and for each of the included paper a short description is given on its major findings. PMID:28516015

ClusCo: clustering and comparison of protein models.

PubMed

Jamroz, Michal; Kolinski, Andrzej

2013-02-22

The development, optimization and validation of protein modeling methods require efficient tools for structural comparison. Frequently, a large number of models need to be compared with the target native structure. The main reason for the development of Clusco software was to create a high-throughput tool for all-versus-all comparison, because calculating similarity matrix is the one of the bottlenecks in the protein modeling pipeline. Clusco is fast and easy-to-use software for high-throughput comparison of protein models with different similarity measures (cRMSD, dRMSD, GDT_TS, TM-Score, MaxSub, Contact Map Overlap) and clustering of the comparison results with standard methods: K-means Clustering or Hierarchical Agglomerative Clustering. The application was highly optimized and written in C/C++, including the code for parallel execution on CPU and GPU, which resulted in a significant speedup over similar clustering and scoring computation programs.

Cooperative Subunit Refolding of a Light-Harvesting Protein through a Self-Chaperone Mechanism.

PubMed

Laos, Alistair J; Dean, Jacob C; Toa, Zi S D; Wilk, Krystyna E; Scholes, Gregory D; Curmi, Paul M G; Thordarson, Pall

2017-07-10

The fold of a protein is encoded by its amino acid sequence, but how complex multimeric proteins fold and assemble into functional quaternary structures remains unclear. Here we show that two structurally different phycobiliproteins refold and reassemble in a cooperative manner from their unfolded polypeptide subunits, without biological chaperones. Refolding was confirmed by ultrafast broadband transient absorption and two-dimensional electronic spectroscopy to probe internal chromophores as a marker of quaternary structure. Our results demonstrate a cooperative, self-chaperone refolding mechanism, whereby the β-subunits independently refold, thereby templating the folding of the α-subunits, which then chaperone the assembly of the native complex, quantitatively returning all coherences. Our results indicate that subunit self-chaperoning is a robust mechanism for heteromeric protein folding and assembly that could also be applied in self-assembled synthetic hierarchical systems. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

The Plasma Membrane is Compartmentalized by a Self-Similar Cortical Actin Fractal

NASA Astrophysics Data System (ADS)

Sadegh, Sanaz; Higgin, Jenny; Mannion, Patrick; Tamkun, Michael; Krapf, Diego

A broad range of membrane proteins display anomalous diffusion on the cell surface. Different methods provide evidence for obstructed subdiffusion and diffusion on a fractal space, but the underlying structure inducing anomalous diffusion has never been visualized due to experimental challenges. We addressed this problem by imaging the cortical actin at high resolution while simultaneously tracking individual membrane proteins in live mammalian cells. Our data show that actin introduces barriers leading to compartmentalization of the plasma membrane and that membrane proteins are transiently confined within actin fences. Furthermore, superresolution imaging shows that the cortical actin is organized into a self-similar fractal. These results present a hierarchical nanoscale picture of the plasma membrane and demonstrate direct interactions between the actin cortex and the cell surface.

Digested disorder

PubMed Central

Reddy, Krishna D; DeForte, Shelly; Uversky, Vladimir N

2014-01-01

The current literature on intrinsically disordered proteins grows fast. To keep interested readers up to speed with this literature, we continue a “Digested Disorder” project and represent a new issue of reader’s digest of the research papers and reviews on intrinsically disordered proteins. The only 2 criteria for inclusion in this digest are the publication date (a paper should be published within the covered time frame) and topic (a paper should be dedicated to any aspect of protein intrinsic disorder). The current digest issue covers papers published during the third quarter of 2013; i.e., during the period of June, July, and September of 2013. Similar to previous issues, the papers are grouped hierarchically by topics they cover, and for each of the included paper a short description is given on its major findings. PMID:28232877

Roles of chromatin insulator proteins in higher-order chromatin organization and transcription regulation

PubMed Central

Vogelmann, Jutta; Valeri, Alessandro; Guillou, Emmanuelle; Cuvier, Olivier; Nollmann, Marcelo

2013-01-01

Eukaryotic chromosomes are condensed into several hierarchical levels of complexity: DNA is wrapped around core histones to form nucleosomes, nucleosomes form a higher-order structure called chromatin, and chromatin is subsequently compartmentalized in part by the combination of multiple specific or unspecific long-range contacts. The conformation of chromatin at these three levels greatly influences DNA metabolism and transcription. One class of chromatin regulatory proteins called insulator factors may organize chromatin both locally, by setting up barriers between heterochromatin and euchromatin, and globally by establishing platforms for long-range interactions. Here, we review recent data revealing a global role of insulator proteins in the regulation of transcription through the formation of clusters of long-range interactions that impact different levels of chromatin organization. PMID:21983085

Protein-mediated loops in supercoiled DNA create large topological domains

PubMed Central

Yan, Yan; Ding, Yue; Leng, Fenfei; Dunlap, David; Finzi, Laura

2018-01-01

Abstract Supercoiling can alter the form and base pairing of the double helix and directly impact protein binding. More indirectly, changes in protein binding and the stress of supercoiling also influence the thermodynamic stability of regulatory, protein-mediated loops and shift the equilibria of fundamental DNA/chromatin transactions. For example, supercoiling affects the hierarchical organization and function of chromatin in topologically associating domains (TADs) in both eukaryotes and bacteria. On the other hand, a protein-mediated loop in DNA can constrain supercoiling within a plectonemic structure. To characterize the extent of constrained supercoiling, 400 bp, lac repressor-secured loops were formed in extensively over- or under-wound DNA under gentle tension in a magnetic tweezer. The protein-mediated loops constrained variable amounts of supercoiling that often exceeded the maximum writhe expected for a 400 bp plectoneme. Loops with such high levels of supercoiling appear to be entangled with flanking domains. Thus, loop-mediating proteins operating on supercoiled substrates can establish topological domains that may coordinate gene regulation and other DNA transactions across spans in the genome that are larger than the separation between the binding sites. PMID:29538766

Molecular basis of protein structure in proanthocyanidin and anthocyanin-enhanced Lc-transgenic alfalfa in relation to nutritive value using synchrotron-radiation FTIR microspectroscopy: A novel approach

NASA Astrophysics Data System (ADS)

Yu, Peiqiang; Jonker, Arjan; Gruber, Margaret

2009-09-01

To date there has been very little application of synchrotron radiation-based Fourier transform infrared microspectroscopy (SRFTIRM) to the study of molecular structures in plant forage in relation to livestock digestive behavior and nutrient availability. Protein inherent structure, among other factors such as protein matrix, affects nutritive quality, fermentation and degradation behavior in both humans and animals. The relative percentage of protein secondary structure influences protein value. A high percentage of β-sheets usually reduce the access of gastrointestinal digestive enzymes to the protein. Reduced accessibility results in poor digestibility and as a result, low protein value. The objective of this study was to use SRFTIRM to compare protein molecular structure of alfalfa plant tissues transformed with the maize Lc regulatory gene with non-transgenic alfalfa protein within cellular and subcellular dimensions and to quantify protein inherent structure profiles using Gaussian and Lorentzian methods of multi-component peak modeling. Protein molecular structure revealed by this method included α-helices, β-sheets and other structures such as β-turns and random coils. Hierarchical cluster analysis and principal component analysis of the synchrotron data, as well as accurate spectral analysis based on curve fitting, showed that transgenic alfalfa contained a relatively lower ( P < 0.05) percentage of the model-fitted α-helices (29 vs. 34) and model-fitted β-sheets (22 vs. 27) and a higher ( P < 0.05) percentage of other model-fitted structures (49 vs. 39). Transgenic alfalfa protein displayed no difference ( P > 0.05) in the ratio of α-helices to β-sheets (average: 1.4) and higher ( P < 0.05) ratios of α-helices to others (0.7 vs. 0.9) and β-sheets to others (0.5 vs. 0.8) than the non-transgenic alfalfa protein. The transgenic protein structures also exhibited no difference ( P > 0.05) in the vibrational intensity of protein amide I (average of 24) and amide II areas (average of 10) and their ratio (average of 2.4) compared with non-transgenic alfalfa. Cluster analysis and principal component analysis showed no significant differences between the two genotypes in the broad molecular fingerprint region, amides I and II regions, and the carbohydrate molecular region, indicating they are highly related to each other. The results suggest that transgenic Lc-alfalfa leaves contain similar proteins to non-transgenic alfalfa (because amide I and II intensities were identical), but a subtle difference in protein molecular structure after freeze drying. Further study is needed to understand the relationship between these structural profiles and biological features such as protein nutrient availability, protein bypass and digestive behavior of livestock fed with this type of forage.

Molecular Basis of Protein Structure in Proanthocyanidin and Anthocyanin-Enhanced Lc-transgenic Alfalfa in Relation to Nutritive Value Using Synchrotron-Radiation FTIR Microspectroscopy: A Novel Approach

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

Yu, P.; Jonker, A; Gruber, M

2009-01-01

To date there has been very little application of synchrotron radiation-based Fourier transform infrared microspectroscopy (SRFTIRM) to the study of molecular structures in plant forage in relation to livestock digestive behavior and nutrient availability. Protein inherent structure, among other factors such as protein matrix, affects nutritive quality, fermentation and degradation behavior in both humans and animals. The relative percentage of protein secondary structure influences protein value. A high percentage of e-sheets usually reduce the access of gastrointestinal digestive enzymes to the protein. Reduced accessibility results in poor digestibility and as a result, low protein value. The objective of this studymore » was to use SRFTIRM to compare protein molecular structure of alfalfa plant tissues transformed with the maize Lc regulatory gene with non-transgenic alfalfa protein within cellular and subcellular dimensions and to quantify protein inherent structure profiles using Gaussian and Lorentzian methods of multi-component peak modeling. Protein molecular structure revealed by this method included a-helices, e-sheets and other structures such as e-turns and random coils. Hierarchical cluster analysis and principal component analysis of the synchrotron data, as well as accurate spectral analysis based on curve fitting, showed that transgenic alfalfa contained a relatively lower (P < 0.05) percentage of the model-fitted a-helices (29 vs. 34) and model-fitted e-sheets (22 vs. 27) and a higher (P < 0.05) percentage of other model-fitted structures (49 vs. 39). Transgenic alfalfa protein displayed no difference (P > 0.05) in the ratio of a-helices to e-sheets (average: 1.4) and higher (P < 0.05) ratios of a-helices to others (0.7 vs. 0.9) and e-sheets to others (0.5 vs. 0.8) than the non-transgenic alfalfa protein. The transgenic protein structures also exhibited no difference (P > 0.05) in the vibrational intensity of protein amide I (average of 24) and amide II areas (average of 10) and their ratio (average of 2.4) compared with non-transgenic alfalfa. Cluster analysis and principal component analysis showed no significant differences between the two genotypes in the broad molecular fingerprint region, amides I and II regions, and the carbohydrate molecular region, indicating they are highly related to each other. The results suggest that transgenic Lc-alfalfa leaves contain similar proteins to non-transgenic alfalfa (because amide I and II intensities were identical), but a subtle difference in protein molecular structure after freeze drying. Further study is needed to understand the relationship between these structural profiles and biological features such as protein nutrient availability, protein bypass and digestive behavior of livestock fed with this type of forage.« less

Bioinspired Nanoscale Materials for Biomedical and Energy Applications

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

Bhattacharya, Priyanka; Du, Dan; Lin, Yuehe

2014-05-01

The demand of green, affordable and environmentally sustainable materials has encouraged scientists in different fields to draw inspiration from nature in developing materials with unique properties such as miniaturization, hierarchical organization, and adaptability. Together with the exceptional properties of nanomaterials, over the past century, the field of bioinspired nanomaterials has taken huge leaps. While on one hand, the sophistication of hierarchical structures endow biological systems with multifunctionality, the synthetic control on the creation of nanomaterials enables the design of materials with specific functionalities. The aim of this review is to provide a comprehensive, up-to-date overview of the field of bioinspiredmore » nanomaterials, which we have broadly categorized into biotemplates and biomimics. We will discuss the application of bioinspired nanomaterials as biotemplates in catalysis, nanomedicine, immunoassays and in energy, drawing attention to novel materials such as protein cages. Further, the applications of bioinspired materials in tissue engineering and biomineralization will also be discussed.« less

Efficient steady-state solver for hierarchical quantum master equations

NASA Astrophysics Data System (ADS)

Zhang, Hou-Dao; Qiao, Qin; Xu, Rui-Xue; Zheng, Xiao; Yan, YiJing

2017-07-01

Steady states play pivotal roles in many equilibrium and non-equilibrium open system studies. Their accurate evaluations call for exact theories with rigorous treatment of system-bath interactions. Therein, the hierarchical equations-of-motion (HEOM) formalism is a nonperturbative and non-Markovian quantum dissipation theory, which can faithfully describe the dissipative dynamics and nonlinear response of open systems. Nevertheless, solving the steady states of open quantum systems via HEOM is often a challenging task, due to the vast number of dynamical quantities involved. In this work, we propose a self-consistent iteration approach that quickly solves the HEOM steady states. We demonstrate its high efficiency with accurate and fast evaluations of low-temperature thermal equilibrium of a model Fenna-Matthews-Olson pigment-protein complex. Numerically exact evaluation of thermal equilibrium Rényi entropies and stationary emission line shapes is presented with detailed discussion.

Hierarchical Protein Free Energy Landscapes from Variationally Enhanced Sampling.

PubMed

Shaffer, Patrick; Valsson, Omar; Parrinello, Michele

2016-12-13

In recent work, we demonstrated that it is possible to obtain approximate representations of high-dimensional free energy surfaces with variationally enhanced sampling ( Shaffer, P.; Valsson, O.; Parrinello, M. Proc. Natl. Acad. Sci. , 2016 , 113 , 17 ). The high-dimensional spaces considered in that work were the set of backbone dihedral angles of a small peptide, Chignolin, and the high-dimensional free energy surface was approximated as the sum of many two-dimensional terms plus an additional term which represents an initial estimate. In this paper, we build on that work and demonstrate that we can calculate high-dimensional free energy surfaces of very high accuracy by incorporating additional terms. The additional terms apply to a set of collective variables which are more coarse than the base set of collective variables. In this way, it is possible to build hierarchical free energy surfaces, which are composed of terms that act on different length scales. We test the accuracy of these free energy landscapes for the proteins Chignolin and Trp-cage by constructing simple coarse-grained models and comparing results from the coarse-grained model to results from atomistic simulations. The approach described in this paper is ideally suited for problems in which the free energy surface has important features on different length scales or in which there is some natural hierarchy.

Hierarchical folding free energy landscape of HP35 revealed by most probable path clustering.

PubMed

Jain, Abhinav; Stock, Gerhard

2014-07-17

Adopting extensive molecular dynamics simulations of villin headpiece protein (HP35) by Shaw and co-workers, a detailed theoretical analysis of the folding of HP35 is presented. The approach is based on the recently proposed most probable path algorithm which identifies the metastable states of the system, combined with dynamical coring of these states in order to obtain a consistent Markov state model. The method facilitates the construction of a dendrogram associated with the folding free-energy landscape of HP35, which reveals a hierarchical funnel structure and shows that the native state is rather a kinetic trap than a network hub. The energy landscape of HP35 consists of the entropic unfolded basin U, where the prestructuring of the protein takes place, the intermediate basin I, which is connected to U via the rate-limiting U → I transition state reflecting the formation of helix-1, and the native basin N, containing a state close to the NMR structure and a native-like state that exhibits enhanced fluctuations of helix-3. The model is in line with recent experimental observations that the intermediate and native states differ mostly in their dynamics (locked vs unlocked states). Employing dihedral angle principal component analysis, subdiffusive motion on a multidimensional free-energy surface is found.

Reciprocal Prioritization to Dietary Glycans by Gut Bacteria in a Competitive Environment Promotes Stable Coexistence

PubMed Central

Tuncil, Yunus E.; Xiao, Yao; Porter, Nathan T.; Reuhs, Bradley L.

2017-01-01

ABSTRACT When presented with nutrient mixtures, several human gut Bacteroides species exhibit hierarchical utilization of glycans through a phenomenon that resembles catabolite repression. However, it is unclear how closely these observed physiological changes, often measured by altered transcription of glycan utilization genes, mirror actual glycan depletion. To understand the glycan prioritization strategies of two closely related human gut symbionts, Bacteroides ovatus and Bacteroides thetaiotaomicron, we performed a series of time course assays in which both species were individually grown in a medium with six different glycans that both species can degrade. Disappearance of the substrates and transcription of the corresponding polysaccharide utilization loci (PULs) were measured. Each species utilized some glycans before others, but with different priorities per species, providing insight into species-specific hierarchical preferences. In general, the presence of highly prioritized glycans repressed transcription of genes involved in utilizing lower-priority nutrients. However, transcriptional sensitivity to some glycans varied relative to the residual concentration in the medium, with some PULs that target high-priority substrates remaining highly expressed even after their target glycan had been mostly depleted. Coculturing of these organisms in the same mixture showed that the hierarchical orders generally remained the same, promoting stable coexistence. Polymer length was found to be a contributing factor for glycan utilization, thereby affecting its place in the hierarchy. Our findings not only elucidate how B. ovatus and B. thetaiotaomicron strategically access glycans to maintain coexistence but also support the prioritization of carbohydrate utilization based on carbohydrate structure, advancing our understanding of the relationships between diet and the gut microbiome. PMID:29018117

fast_protein_cluster: parallel and optimized clustering of large-scale protein modeling data.

PubMed

Hung, Ling-Hong; Samudrala, Ram

2014-06-15

fast_protein_cluster is a fast, parallel and memory efficient package used to cluster 60 000 sets of protein models (with up to 550 000 models per set) generated by the Nutritious Rice for the World project. fast_protein_cluster is an optimized and extensible toolkit that supports Root Mean Square Deviation after optimal superposition (RMSD) and Template Modeling score (TM-score) as metrics. RMSD calculations using a laptop CPU are 60× faster than qcprot and 3× faster than current graphics processing unit (GPU) implementations. New GPU code further increases the speed of RMSD and TM-score calculations. fast_protein_cluster provides novel k-means and hierarchical clustering methods that are up to 250× and 2000× faster, respectively, than Clusco, and identify significantly more accurate models than Spicker and Clusco. fast_protein_cluster is written in C++ using OpenMP for multi-threading support. Custom streaming Single Instruction Multiple Data (SIMD) extensions and advanced vector extension intrinsics code accelerate CPU calculations, and OpenCL kernels support AMD and Nvidia GPUs. fast_protein_cluster is available under the M.I.T. license. (http://software.compbio.washington.edu/fast_protein_cluster) © The Author 2014. Published by Oxford University Press.

Clustering and Network Analysis of Reverse Phase Protein Array Data.

PubMed

Byron, Adam

2017-01-01

Molecular profiling of proteins and phosphoproteins using a reverse phase protein array (RPPA) platform, with a panel of target-specific antibodies, enables the parallel, quantitative proteomic analysis of many biological samples in a microarray format. Hence, RPPA analysis can generate a high volume of multidimensional data that must be effectively interrogated and interpreted. A range of computational techniques for data mining can be applied to detect and explore data structure and to form functional predictions from large datasets. Here, two approaches for the computational analysis of RPPA data are detailed: the identification of similar patterns of protein expression by hierarchical cluster analysis and the modeling of protein interactions and signaling relationships by network analysis. The protocols use freely available, cross-platform software, are easy to implement, and do not require any programming expertise. Serving as data-driven starting points for further in-depth analysis, validation, and biological experimentation, these and related bioinformatic approaches can accelerate the functional interpretation of RPPA data.

LocTree2 predicts localization for all domains of life

PubMed Central

Goldberg, Tatyana; Hamp, Tobias; Rost, Burkhard

2012-01-01

Motivation: Subcellular localization is one aspect of protein function. Despite advances in high-throughput imaging, localization maps remain incomplete. Several methods accurately predict localization, but many challenges remain to be tackled. Results: In this study, we introduced a framework to predict localization in life's three domains, including globular and membrane proteins (3 classes for archaea; 6 for bacteria and 18 for eukaryota). The resulting method, LocTree2, works well even for protein fragments. It uses a hierarchical system of support vector machines that imitates the cascading mechanism of cellular sorting. The method reaches high levels of sustained performance (eukaryota: Q18=65%, bacteria: Q6=84%). LocTree2 also accurately distinguishes membrane and non-membrane proteins. In our hands, it compared favorably with top methods when tested on new data. Availability: Online through PredictProtein (predictprotein.org); as standalone version at http://www.rostlab.org/services/loctree2. Contact: localization@rostlab.org Supplementary Information: Supplementary data are available at Bioinformatics online. PMID:22962467

Digested disorder: Quarterly intrinsic disorder digest (January/February/March, 2013).

PubMed

Uversky, Vladimir N

2013-01-01

The current literature on intrinsically disordered proteins is blooming. A simple PubMed search for "intrinsically disordered protein OR natively unfolded protein" returns about 1,800 hits (as of June 17, 2013), with many papers published quite recently. To keep interested readers up to speed with this literature, we are starting a "Digested Disorder" project, which will encompass a series of reader's digest type of publications aiming at the objective representation of the research papers and reviews on intrinsically disordered proteins. The only two criteria for inclusion in this digest are the publication date (a paper should be published within the covered time frame) and topic (a paper should be dedicated to any aspect of protein intrinsic disorder). The current digest covers papers published during the period of January, February and March of 2013. The papers are grouped hierarchically by topics they cover, and for each of the included paper a short description is given on its major findings.

Nonlinear hierarchical multiscale modeling of cortical bone considering its nanoscale microstructure.

PubMed

Ghanbari, J; Naghdabadi, R

2009-07-22

We have used a hierarchical multiscale modeling scheme for the analysis of cortical bone considering it as a nanocomposite. This scheme consists of definition of two boundary value problems, one for macroscale, and another for microscale. The coupling between these scales is done by using the homogenization technique. At every material point in which the constitutive model is needed, a microscale boundary value problem is defined using a macroscopic kinematical quantity and solved. Using the described scheme, we have studied elastic properties of cortical bone considering its nanoscale microstructural constituents with various mineral volume fractions. Since the microstructure of bone consists of mineral platelet with nanometer size embedded in a protein matrix, it is similar to the microstructure of soft matrix nanocomposites reinforced with hard nanostructures. Considering a representative volume element (RVE) of the microstructure of bone as the microscale problem in our hierarchical multiscale modeling scheme, the global behavior of bone is obtained under various macroscopic loading conditions. This scheme may be suitable for modeling arbitrary bone geometries subjected to a variety of loading conditions. Using the presented method, mechanical properties of cortical bone including elastic moduli and Poisson's ratios in two major directions and shear modulus is obtained for different mineral volume fractions.

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.

In-Depth Proteomic Analysis of the Hippocampus in a Rat Model after Cerebral Ischaemic Injury and Repair by Danhong Injection (DHI)

PubMed Central

Cui, Yiran; Liu, Xin; Li, Xianyu; Yang, Hongjun

2017-01-01

Stroke is the second most common cause of death worldwide. A systematic description and characterization of the strokes and the effects induced in the hippocampus have not been performed so far. Here, we analysed the protein expression in the hippocampus 24 h after cerebral ischaemic injury and repair. Drug intervention using Danhong injection (DHI), which has been reported to have good therapeutic effects in a clinical setting, was selected for our study of cerebral ischaemia repair in rat models. A larger proteome dataset and total 4091 unique proteins were confidently identified in three biological replicates by combining tissue extraction for rat hippocampus and LC-MS/MS analysis. A label-free approach was then used to quantify the differences among the four experimental groups (Naive, Sham, middle cerebral artery occlusion (MCAO) and MCAO + DHI groups) and showed that about 2500 proteins on average were quantified in each of the experiment group. Bioinformatics analysis revealed that in total 280 unique proteins identified above were differentially expressed (P < 0.05). By combining the subcellular localization, hierarchical clustering and pathway information with the results from injury and repair phase, 12 significant expressed proteins were chosen and verified with respect to their potential as candidates for cerebral ischaemic injury by Western blot. The primary three signalling pathways of the candidates related may be involved in molecular mechanisms related to cerebral ischaemic injury. In addition, a glycogen synthase kinase-3β (Gsk-3β) inhibitor of the candidates with the best corresponding expression trends between western blotting (WB) and label-free quantitative results were chosen for further validation. The results of Western blot analysis of protein expression and 2,3,5- chloride three phenyl tetrazole (TTC) staining of rat brains showed that DHI treatment and Gsk-3β inhibitor are both able to confer protection against ischaemic injury in rat MCAO model. The observations of the present study provide a novel understanding regarding the regulatory mechanism of cerebral ischaemic injury. PMID:28672812

An integrated structure- and system-based framework to identify new targets of metabolites and known drugs

PubMed Central

Naveed, Hammad; Hameed, Umar S.; Harrus, Deborah; Bourguet, William; Arold, Stefan T.; Gao, Xin

2015-01-01

Motivation: The inherent promiscuity of small molecules towards protein targets impedes our understanding of healthy versus diseased metabolism. This promiscuity also poses a challenge for the pharmaceutical industry as identifying all protein targets is important to assess (side) effects and repositioning opportunities for a drug. Results: Here, we present a novel integrated structure- and system-based approach of drug-target prediction (iDTP) to enable the large-scale discovery of new targets for small molecules, such as pharmaceutical drugs, co-factors and metabolites (collectively called ‘drugs’). For a given drug, our method uses sequence order–independent structure alignment, hierarchical clustering and probabilistic sequence similarity to construct a probabilistic pocket ensemble (PPE) that captures promiscuous structural features of different binding sites on known targets. A drug’s PPE is combined with an approximation of its delivery profile to reduce false positives. In our cross-validation study, we use iDTP to predict the known targets of 11 drugs, with 63% sensitivity and 81% specificity. We then predicted novel targets for these drugs—two that are of high pharmacological interest, the peroxisome proliferator-activated receptor gamma and the oncogene B-cell lymphoma 2, were successfully validated through in vitro binding experiments. Our method is broadly applicable for the prediction of protein-small molecule interactions with several novel applications to biological research and drug development. Availability and implementation: The program, datasets and results are freely available to academic users at http://sfb.kaust.edu.sa/Pages/Software.aspx. Contact: xin.gao@kaust.edu.sa and stefan.arold@kaust.edu.sa Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26286808

Circulating and synovial antibody profiling of juvenile arthritis patients by nucleic acid programmable protein arrays

PubMed Central

2012-01-01

Introduction Juvenile idiopathic arthritis (JIA) is a heterogeneous disease characterized by chronic joint inflammation of unknown cause in children. JIA is an autoimmune disease and small numbers of autoantibodies have been reported in JIA patients. The identification of antibody markers could improve the existing clinical management of patients. Methods A pilot study was performed on the application of a high-throughput platform, the nucleic acid programmable protein array (NAPPA), to assess the levels of antibodies present in the systemic circulation and synovial joint of a small cohort of juvenile arthritis patients. Plasma and synovial fluid from 10 JIA patients was screened for antibodies against 768 proteins on NAPPAs. Results Quantitative reproducibility of NAPPAs was demonstrated with > 0.95 intra-array and inter-array correlations. A strong correlation was also observed for the levels of antibodies between plasma and synovial fluid across the study cohort (r = 0.96). Differences in the levels of 18 antibodies were revealed between sample types across all patients. Patients were segregated into two clinical subtypes with distinct antibody signatures by unsupervised hierarchical cluster analysis. Conclusion The NAPPAs provide a high-throughput quantitatively reproducible platform to screen for disease-specific autoantibodies at the proteome level on a microscope slide. The strong correlation between the circulating antibody levels and those of the inflamed joint represents a novel finding and provides confidence to use plasma for discovery of autoantibodies in JIA, thus circumventing the challenges associated with joint aspiration. We expect that autoantibody profiling of JIA patients on NAPPAs could yield antibody markers that can act as criteria to stratify patients, predict outcomes and understand disease etiology at the molecular level. PMID:22510425

Development of hierarchical, tunable pore size polymer foams for ICF targets

DOE PAGES

Hamilton, Christopher E.; Lee, Matthew Nicholson; Parra-Vasquez, A. Nicholas Gerardo

2016-08-01

In this study, one of the great challenges of inertial confinement fusion experiments is poor understanding of the effects of reactant heterogeneity on fusion reactions. The Marble campaign, conceived at Los Alamos National Laboratory, aims to gather new insights into this issue by utilizing target capsules containing polymer foams of variable pore sizes, tunable over an order of magnitude. Here, we describe recent and ongoing progress in the development of CH and CH/CD polymer foams in support of Marble. Hierarchical and tunable pore sizes have been achieved by utilizing a sacrificial porogen template within an open-celled poly(divinylbenzene) or poly(divinylbenzene-co-styrene) aerogelmore » matrix, resulting in low-density foams (~30 mg/ml) with continuous multimodal pore networks.« less

Towards a multilevel cognitive probabilistic representation of space

NASA Astrophysics Data System (ADS)

Tapus, Adriana; Vasudevan, Shrihari; Siegwart, Roland

2005-03-01

This paper addresses the problem of perception and representation of space for a mobile agent. A probabilistic hierarchical framework is suggested as a solution to this problem. The method proposed is a combination of probabilistic belief with "Object Graph Models" (OGM). The world is viewed from a topological optic, in terms of objects and relationships between them. The hierarchical representation that we propose permits an efficient and reliable modeling of the information that the mobile agent would perceive from its environment. The integration of both navigational and interactional capabilities through efficient representation is also addressed. Experiments on a set of images taken from the real world that validate the approach are reported. This framework draws on the general understanding of human cognition and perception and contributes towards the overall efforts to build cognitive robot companions.

Smectic Layer Origami via Preprogrammed Photoalignment.

PubMed

Ma, Ling-Ling; Tang, Ming-Jie; Hu, Wei; Cui, Ze-Qun; Ge, Shi-Jun; Chen, Peng; Chen, Lu-Jian; Qian, Hao; Chi, Li-Feng; Lu, Yan-Qing

2017-04-01

Hierarchical architecture is of vital importance in soft materials. Focal conic domains (FCDs) of smectic liquid crystals, characterized by an ordered lamellar structure, attract intensive attention. Simultaneously tailoring the geometry and clustering characteristics of FCDs remains a challenge. Here, the 3D smectic layer origami via a 2D preprogrammed photoalignment film is accomplished. Full control of hierarchical superstructures is demonstrated, including the domain size, shape, and orientation, and the lattice symmetry of fragmented toric FCDs. The unique symmetry breaking of resultant superstructures combined with the optical anisotropy of the liquid crystals induces an intriguing polarization-dependent diffraction. This work broadens the scientific understanding of self-assembled soft materials and may inspire new opportunities for advanced functional materials and devices. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Galaxy formation through hierarchical clustering

NASA Astrophysics Data System (ADS)

White, Simon D. M.; Frenk, Carlos S.

1991-09-01

Analytic methods for studying the formation of galaxies by gas condensation within massive dark halos are presented. The present scheme applies to cosmogonies where structure grows through hierarchical clustering of a mixture of gas and dissipationless dark matter. The simplest models consistent with the current understanding of N-body work on dissipationless clustering, and that of numerical and analytic work on gas evolution and cooling are adopted. Standard models for the evolution of the stellar population are also employed, and new models for the way star formation heats and enriches the surrounding gas are constructed. Detailed results are presented for a cold dark matter universe with Omega = 1 and H(0) = 50 km/s/Mpc, but the present methods are applicable to other models. The present luminosity functions contain significantly more faint galaxies than are observed.

The Double-Stranded DNA Virosphere as a Modular Hierarchical Network of Gene Sharing

PubMed Central

Iranzo, Jaime

2016-01-01

ABSTRACT Virus genomes are prone to extensive gene loss, gain, and exchange and share no universal genes. Therefore, in a broad-scale study of virus evolution, gene and genome network analyses can complement traditional phylogenetics. We performed an exhaustive comparative analysis of the genomes of double-stranded DNA (dsDNA) viruses by using the bipartite network approach and found a robust hierarchical modularity in the dsDNA virosphere. Bipartite networks consist of two classes of nodes, with nodes in one class, in this case genomes, being connected via nodes of the second class, in this case genes. Such a network can be partitioned into modules that combine nodes from both classes. The bipartite network of dsDNA viruses includes 19 modules that form 5 major and 3 minor supermodules. Of these modules, 11 include tailed bacteriophages, reflecting the diversity of this largest group of viruses. The module analysis quantitatively validates and refines previously proposed nontrivial evolutionary relationships. An expansive supermodule combines the large and giant viruses of the putative order “Megavirales” with diverse moderate-sized viruses and related mobile elements. All viruses in this supermodule share a distinct morphogenetic tool kit with a double jelly roll major capsid protein. Herpesviruses and tailed bacteriophages comprise another supermodule, held together by a distinct set of morphogenetic proteins centered on the HK97-like major capsid protein. Together, these two supermodules cover the great majority of currently known dsDNA viruses. We formally identify a set of 14 viral hallmark genes that comprise the hubs of the network and account for most of the intermodule connections. PMID:27486193

Understanding and reaching family forest owners: lessons from social marketing research

Treesearch

Brett J. Butler; Mary Tyrrell; Geoff Feinberg; Scott VanManen; Larry Wiseman; Scott Wallinger

2007-01-01

Social marketing--the use of commercial marketing techniques to effect positive social change--is a promising means by which to develop more effective and efficient outreach, policies, and services for family forest owners. A hierarchical, multivariate analysis based on landowners' attitudes reveals four groups of owners to whom programs can be tailored: woodland...

A Multidimensional Approach to Explore the Understanding of the Notion of Absolute Value

ERIC Educational Resources Information Center

Gagatsis, Athanasios; Panaoura, Areti

2014-01-01

The study aimed to investigate students' conceptions on the notion of absolute value and their abilities in applying the specific notion in routine and non-routine situations. A questionnaire was constructed and administered to 17-year-old students. Data were analysed using the hierarchical clustering of variables and the implicative method, while…

Psychosocial Costs of Racism to Whites: Understanding Patterns among University Students

ERIC Educational Resources Information Center

Spanierman, Lisa B.; Todd, Nathan R.; Anderson, Carolyn J.

2009-01-01

This investigation adds to the growing body of scholarship on the psychosocial costs of racism to Whites (PCRW), which refer to consequences of being in the dominant position in an unjust, hierarchical system of societal racism. Extending research that identified 5 distinct constellations of costs of racism (L. B. Spanierman, V. P. Poteat, A. M.…

A Literature Review: The Effect of Implementing Technology in a High School Mathematics Classroom

ERIC Educational Resources Information Center

Murphy, Daniel

2016-01-01

This study is a literature review to investigate the effects of implementing technology into a high school mathematics classroom. Mathematics has a hierarchical structure in learning and it is essential that students get a firm understanding of mathematics early in education. Some students that miss beginning concepts may continue to struggle with…

Posttraumatic Stress in U.S. Marines: The Role of Unit Cohesion and Combat Exposure

ERIC Educational Resources Information Center

Armistead-Jehle, Patrick; Johnston, Scott L.; Wade, Nathaniel G.; Ecklund, Christofer J.

2011-01-01

Combat exposure is a consistent predictor of posttraumatic stress (PTS). Understanding factors that might buffer the effects of combat exposure is crucial for helping service members weather the stress of war. In a study of U.S. Marines returning from Iraq, hierarchical multiple regression analyses revealed that unit cohesion and combat exposure…

Hierarchies and Learning in the Conservatoire: Exploring What Students Learn through the Lens of Bourdieu

ERIC Educational Resources Information Center

Perkins, Rosie

2013-01-01

This article explores the intersection between institutional hierarchies and learning at a UK conservatoire. Conceptualizing learning as a social practice situated in a hierarchical social space, the article draws on the theorization of Bourdieu to understand how students are positioned in the conservatoire field and what this means in terms of…

Destination Motivation, Cultural Orientation, and Adaptation: International Students' Destination-Loyalty Intention

ERIC Educational Resources Information Center

Jamaludin, Nor Lelawati; Sam, David Lackland; Sandal, Gro Mjeldheim

2018-01-01

This study aims to understand factors predicting destination-loyalty intention in international education. A sample of 378 long-term (n = 195) and short-term (n = 183) international students participated in the study carried out in 2014 through an on-line survey at the University of Bergen, Norway. Using a series of hierarchical regression…

Assessing Team-Based Instructional Design Problem Solutions of Hierarchical Versus Heterarchical Web-Based Hypermedia Cases

ERIC Educational Resources Information Center

Dabbagh, Nada; Denisar, Katrina

2005-01-01

For this study, we examined the cogency, comprehensiveness, and viability of team-based problem solutions of a Web-based hypermedia case designed to promote student understanding of the practice of instructional design. Participants were 14 students enrolled in a graduate course on advanced instructional design. The case was presented to students…

Hierarchical population structure in greater sage-grouse provides insight into management boundary delineation

Treesearch

Todd B. Cross; David E. Naugle; John C. Carlson; Michael K. Schwartz

2016-01-01

Understanding population structure is important for guiding ongoing conservation and restoration efforts. The greater sage-grouse (Centrocercus urophasianus) is a species of concern distributed across 1.2 million km2 of western North America. We genotyped 1499 greater sagegrouse from 297 leks across Montana, North Dakota and South Dakota using a 15 locus...

I'm OK, You're (Not) OK: Teaching in a World of Relativism.

ERIC Educational Resources Information Center

Ryder, Phyllis Mentzell

1995-01-01

Examines three techniques to overcome relativism: (1) a hierarchical view, in which the socially constructed view is superior; (2) a belief that a true understanding of personal experience will lead to political awareness; and (3) an assertion that the socially constructed view is more ethical than other views. Argues that first two approaches are…

The Frontal Lobes and Theory of Mind: Developmental Concepts from Adult Focal Lesion Research

ERIC Educational Resources Information Center

Stuss, Donald T.; Anderson, Vicki

2004-01-01

The primary objective in this paper is to present a framework to understand the structure of consciousness. We argue that consciousness has been difficult to define because there are different kinds of consciousness, hierarchically organized, which need to be differentiated. Our framework is based on evidence from adult focal lesion research. The…

Competition alters tree growth responses to climate at individual and stand scales

Treesearch

Kevin R. Ford; Ian K. Breckheimer; Jerry F. Franklin; James A. Freund; Steve J. Kroiss; Andrew J. Larson; Elinore J. Theobald; Janneke HilleRisLambers

2017-01-01

Understanding how climate affects tree growth is essential for assessing climate change impacts on forests but can be confounded by effects of competition, which strongly influences tree responses to climate. We characterized the joint influences of tree size, competition, and climate on diameter growth using hierarchical Bayesian methods applied to permanent sample...

A hierarchical network approach for modeling Rift Valley fever epidemics with applications in North America

USDA-ARS?s Scientific Manuscript database

Rift Valley fever (RVF) is a vector-borne zoonotic disease which causes high morbidity and mortality in livestock. In the event Rift Valley fever virus is introduced to the United States or other non-endemic areas, understanding the potential patterns of spread and the areas at risk based on disease...

2 x 2 Achievement Goals and Achievement Emotions: A Cluster Analysis of Students' Motivation

ERIC Educational Resources Information Center

Jang, Leong Yeok; Liu, Woon Chia

2012-01-01

This study sought to better understand the adoption of multiple achievement goals at an intra-individual level, and its links to emotional well-being, learning, and academic achievement. Participants were 480 Secondary Two students (aged between 13 and 14 years) from two coeducational government schools. Hierarchical cluster analysis revealed the…

Factors Contributing to under Representation of Female Teachers in Headship Positions in Primary Schools in Eldoret Municipality, Kenya

ERIC Educational Resources Information Center

Barmao, Catherine

2013-01-01

This paper analyses factors contributing to under representation of female teachers in headship positions in Eldoret Municipality Kenya. The study was guided by socialization theory to hierarchical gender prescriptions which gave three distinct theoretical traditions that help, understand sex and gender. Descriptive survey was adopted for the…

Hierarchical carbon nanopetal/polypyrrole nanocomposite electrodes with brush-like architecture for supercapacitors.

PubMed

Cherusseri, Jayesh; Kar, Kamal K

2016-03-28

Hierarchical 3D nanocomposite electrodes with tube brush-like morphology are synthesized by electrochemically depositing polypyrrole (PPY) on carbon nanopetal (CNP) coated carbon fibers (CFs). Initially CNPs are synthesized on CF substrate by chemical vapour deposition. The CNPs synthesized on CF (CNPCF) are further used as an electrically conducting large surface area bearing template for the electropolymerization of PPY in order to fabricate CNPCF-PPY nanocomposite electrodes for supercapacitors (SCs). The CF in CNPCF-PPY nanocomposite functions as (i) a mechanical support for the CNPs, (ii) a current collector for the SC cell and also (iii) to prevent the agglomeration of CNPs within the CNPCF-PPY nanocomposite. Transmission electron microscopy and scanning electron microscopy are used to examine the surface morphology of CNPCF-PPY nanocomposites. The chemical structure of the nanocomposites is analysed by Fourier transform infrared spectroscopy. X-Ray photoelectron spectroscopy has been used to understand the chemical bonding states of the hierarchical CNPCF-PPY nanocomposites. The electrochemical properties of symmetric type CNPCF-PPY SC cells are examined by electrochemical impedance spectroscopy, cyclic voltammetry and galvanostatic charge-discharge measurements. The hierarchical CNPCF-PPY SC exhibits a maximum gravimetric capacitance of 280.4 F g(-1) and an area specific capacitance of 210.3 mF cm(-2) at a current density of 0.42 mA cm(-2). The CNPCF-PPY SC cell exhibits good cycling stability of more than 5000 cycles. The present study proclaims the development of a novel lightweight SC with high-performance.

A hierarchical instrumental decision theory of nicotine dependence.

PubMed

Hogarth, Lee; Troisi, Joseph R

2015-01-01

It is important to characterize the learning processes governing tobacco-seeking in order to understand how best to treat this behavior. Most drug learning theories have adopted a Pavlovian framework wherein the conditioned response is the main motivational process. We favor instead a hierarchical instrumental decision account, wherein expectations about the instrumental contingency between voluntary tobacco-seeking and the receipt of nicotine reward determines the probability of executing this behavior. To support this view, we review titration and nicotine discrimination research showing that internal signals for deprivation/satiation modulate expectations about the current incentive value of smoking, thereby modulating the propensity of this behavior. We also review research on cue-reactivity which has shown that external smoking cues modulate expectations about the probability of the tobacco-seeking response being effective, thereby modulating the propensity of this behavior. Economic decision theory is then considered to elucidate how expectations about the value and probability of response-nicotine contingency are integrated to form an overall utility estimate for that option for comparison with qualitatively different, nonsubstitute reinforcers, to determine response selection. As an applied test for this hierarchical instrumental decision framework, we consider how well it accounts for individual liability to smoking uptake and perseveration, pharmacotherapy, cue-extinction therapies, and plain packaging. We conclude that the hierarchical instrumental account is successful in reconciling this broad range of phenomenon precisely because it accepts that multiple diverse sources of internal and external information must be integrated to shape the decision to smoke.

On the origin of biological construction, with a focus on multicellularity.

PubMed

van Gestel, Jordi; Tarnita, Corina E

2017-10-17

Biology is marked by a hierarchical organization: all life consists of cells; in some cases, these cells assemble into groups, such as endosymbionts or multicellular organisms; in turn, multicellular organisms sometimes assemble into yet other groups, such as primate societies or ant colonies. The construction of new organizational layers results from hierarchical evolutionary transitions, in which biological units (e.g., cells) form groups that evolve into new units of biological organization (e.g., multicellular organisms). Despite considerable advances, there is no bottom-up, dynamical account of how, starting from the solitary ancestor, the first groups originate and subsequently evolve the organizing principles that qualify them as new units. Guided by six central questions, we propose an integrative bottom-up approach for studying the dynamics underlying hierarchical evolutionary transitions, which builds on and synthesizes existing knowledge. This approach highlights the crucial role of the ecology and development of the solitary ancestor in the emergence and subsequent evolution of groups, and it stresses the paramount importance of the life cycle: only by evaluating groups in the context of their life cycle can we unravel the evolutionary trajectory of hierarchical transitions. These insights also provide a starting point for understanding the types of subsequent organizational complexity. The central research questions outlined here naturally link existing research programs on biological construction (e.g., on cooperation, multilevel selection, self-organization, and development) and thereby help integrate knowledge stemming from diverse fields of biology.

Protein Assembly and Building Blocks: Beyond the Limits of the LEGO Brick Metaphor.

PubMed

Levy, Yaakov

2017-09-26

Proteins, like other biomolecules, have a modular and hierarchical structure. Various building blocks are used to construct proteins of high structural complexity and diverse functionality. In multidomain proteins, for example, domains are fused to each other in different combinations to achieve different functions. Although the LEGO brick metaphor is justified as a means of simplifying the complexity of three-dimensional protein structures, several fundamental properties (such as allostery or the induced-fit mechanism) make deviation from it necessary to respect the plasticity, softness, and cross-talk that are essential to protein function. In this work, we illustrate recently reported protein behavior in multidomain proteins that deviates from the LEGO brick analogy. While earlier studies showed that a protein domain is often unaffected by being fused to another domain or becomes more stable following the formation of a new interface between the tethered domains, destabilization due to tethering has been reported for several systems. We illustrate that tethering may sometimes result in a multidomain protein behaving as "less than the sum of its parts". We survey these cases for which structure additivity does not guarantee thermodynamic additivity. Protein destabilization due to fusion to other domains may be linked in some cases to biological function and should be taken into account when designing large assemblies.

Raman spectroscopy of single extracellular vesicles reveals subpopulations with varying membrane content (Conference Presentation)

NASA Astrophysics Data System (ADS)

Smith, Zachary J.; Lee, Changwon; Rojalin, Tatu; Carney, Randy P.; Hazari, Sidhartha; Knudson, Alisha; Lam, Kit S.; Saari, Heikki; Lazaro Ibañez, Elisa; Viitala, Tapani; Laaksonen, Timo; Yliperttula, Marjo; Wachsmann-Hogiu, Sebastian

2016-03-01

Exosomes are small (~100nm) membrane bound vesicles excreted by cells as part of their normal biological processes. These extracellular vesicles are currently an area of intense research, since they were recently found to carry functional mRNA that allows transfer of proteins and other cellular instructions between cells. Exosomes have been implicated in a wide range of diseases, including cancer. Cancer cells are known to have increased exosome production, and may use those exosomes to prepare remote environments for metastasis. Therefore, there is a strong need to develop characterization methods to help understand the structure and function of these vesicles. However, current techniques, such as proteomics and genomics technologies, rely on aggregating a large amount of exosome material and reporting on chemical content that is averaged over many millions of exosomes. Here we report on the use of laser-tweezers Raman spectroscopy (LTRS) to probe individual vesicles, discovering distinct heterogeneity among exosomes both within a cell line, as well as between different cell lines. Through principal components analysis followed by hierarchical clustering, we have identified four "subpopulations" of exosomes shared across seven cell lines. The key chemical differences between these subpopulations, as determined by spectral analysis of the principal component loadings, are primarily related to membrane composition. Specifically, the differences can be ascribed to cholesterol content, cholesterol to phospholipid ratio, and surface protein expression. Thus, we have shown LTRS to be a powerful method to probe the chemical content of single extracellular vesicles.

Environmental Signals and Regulatory Pathways That Influence Exopolysaccharide Production in Rhizobia

PubMed Central

Janczarek, Monika

2011-01-01

Rhizobia are Gram-negative bacteria that can exist either as free-living bacteria or as nitrogen-fixing symbionts inside root nodules of leguminous plants. The composition of the rhizobial outer surface, containing a variety of polysaccharides, plays a significant role in the adaptation of these bacteria in both habitats. Among rhizobial polymers, exopolysaccharide (EPS) is indispensable for the invasion of a great majority of host plants which form indeterminate-type nodules. Various functions are ascribed to this heteropolymer, including protection against environmental stress and host defense, attachment to abiotic and biotic surfaces, and in signaling. The synthesis of EPS in rhizobia is a multi-step process regulated by several proteins at both transcriptional and post-transcriptional levels. Also, some environmental factors (carbon source, nitrogen and phosphate starvation, flavonoids) and stress conditions (osmolarity, ionic strength) affect EPS production. This paper discusses the recent data concerning the function of the genes required for EPS synthesis and the regulation of this process by several environmental signals. Up till now, the synthesis of rhizobial EPS has been best studied in two species, Sinorhizobium meliloti and Rhizobium leguminosarum. The latest data indicate that EPS synthesis in rhizobia undergoes very complex hierarchical regulation, in which proteins engaged in quorum sensing and the regulation of motility genes also participate. This finding enables a better understanding of the complex processes occurring in the rhizosphere which are crucial for successful colonization and infection of host plant roots. PMID:22174640

Search for Allergens from the Pollen Proteome of Sunflower (Helianthus annuus L.): A Major Sensitizer for Respiratory Allergy Patients.

PubMed

Ghosh, Nandini; Sircar, Gaurab; Saha, Bodhisattwa; Pandey, Naren; Gupta Bhattacharya, Swati

2015-01-01

Respiratory allergy triggered by pollen allergens is increasing at an alarming rate worldwide. Sunflower pollen is thought to be an important source of inhalant allergens. Present study aims to identify the prevalence of sunflower pollinosis among the Indian allergic population and characterizes the pollen allergens using immuno-proteomic tools. Clinico-immunological tests were performed to understand the prevalence of sensitivity towards sunflower pollen among the atopic population. Sera from selected sunflower positive patients were used as probe to detect the IgE-reactive proteins from the one and two dimensional electrophoretic separated proteome of sunflower pollen. The antigenic nature of the sugar moiety of the glycoallergens was studied by meta-periodate modification of IgE-immunoblot. Finally, these allergens were identified by mass-spectrometry. Prevalence of sunflower pollen sensitization was observed among 21% of the pollen allergic population and associated with elevated level of specific IgE and histamine in the sera of these patients. Immunoscreening of sunflower pollen proteome with patient sera detected seven IgE-reactive proteins with varying molecular weight and pI. Hierarchical clustering of 2D-immunoblot data highlighted three allergens characterized by a more frequent immuno-reactivity and increased levels of IgE antibodies in the sera of susceptible patients. These allergens were considered as the major allergens of sunflower pollen and were found to have their glycan moiety critical for inducing IgE response. Homology driven search of MS/MS data of these IgE-reactive proteins identified seven previously unreported allergens from sunflower pollen. Three major allergenic proteins were identified as two pectate lyases and a cysteine protease. Novelty of the present report is the identification of a panel of seven sunflower pollen allergens for the first time at immuno-biochemical and proteomic level, which substantiated the clinical evidence of sunflower allergy. Further purification and recombinant expression of these allergens will improve component-resolved diagnosis and therapy of pollen allergy.

Impacts of forest fragmentation on species richness: a hierarchical approach to community modelling

USGS Publications Warehouse

Zipkin, Elise F.; DeWan, Amielle; Royle, J. Andrew

2009-01-01

1. Species richness is often used as a tool for prioritizing conservation action. One method for predicting richness and other summaries of community structure is to develop species-specific models of occurrence probability based on habitat or landscape characteristics. However, this approach can be challenging for rare or elusive species for which survey data are often sparse. 2. Recent developments have allowed for improved inference about community structure based on species-specific models of occurrence probability, integrated within a hierarchical modelling framework. This framework offers advantages to inference about species richness over typical approaches by accounting for both species-level effects and the aggregated effects of landscape composition on a community as a whole, thus leading to increased precision in estimates of species richness by improving occupancy estimates for all species, including those that were observed infrequently. 3. We developed a hierarchical model to assess the community response of breeding birds in the Hudson River Valley, New York, to habitat fragmentation and analysed the model using a Bayesian approach. 4. The model was designed to estimate species-specific occurrence and the effects of fragment area and edge (as measured through the perimeter and the perimeter/area ratio, P/A), while accounting for imperfect detection of species. 5. We used the fitted model to make predictions of species richness within forest fragments of variable morphology. The model revealed that species richness of the observed bird community was maximized in small forest fragments with a high P/A. However, the number of forest interior species, a subset of the community with high conservation value, was maximized in large fragments with low P/A. 6. Synthesis and applications. Our results demonstrate the importance of understanding the responses of both individual, and groups of species, to environmental heterogeneity while illustrating the utility of hierarchical models for inference about species richness for conservation. This framework can be used to investigate the impacts of land-use change and fragmentation on species or assemblage richness, and to further understand trade-offs in species-specific occupancy probabilities associated with landscape variability.

Vav family exchange factors: an integrated regulatory and functional view

PubMed Central

Bustelo, Xosé R

2014-01-01

The Vav family is a group of tyrosine phosphorylation-regulated signal transduction molecules hierarchically located downstream of protein tyrosine kinases. The main function of these proteins is to work as guanosine nucleotide exchange factors (GEFs) for members of the Rho GTPase family. In addition, they can exhibit a variety of catalysis-independent roles in specific signaling contexts. Vav proteins play essential signaling roles for both the development and/or effector functions of a large variety of cell lineages, including those belonging to the immune, nervous, and cardiovascular systems. They also contribute to pathological states such as cancer, immune-related dysfunctions, and atherosclerosis. Here, I will provide an integrated view about the evolution, regulation, and effector properties of these signaling molecules. In addition, I will discuss the pros and cons for their potential consideration as therapeutic targets. PMID:25483299

Digested disorder: Quarterly intrinsic disorder digest (July-August-September, 2013).

PubMed

Reddy, Krishna D; DeForte, Shelly; Uversky, Vladimir N

2014-01-01

The current literature on intrinsically disordered proteins grows fast. To keep interested readers up to speed with this literature, we continue a "Digested Disorder" project and represent a new issue of reader's digest of the research papers and reviews on intrinsically disordered proteins. The only 2 criteria for inclusion in this digest are the publication date (a paper should be published within the covered time frame) and topic (a paper should be dedicated to any aspect of protein intrinsic disorder). The current digest issue covers papers published during the third quarter of 2013; i.e., during the period of June, July, and September of 2013. Similar to previous issues, the papers are grouped hierarchically by topics they cover, and for each of the included paper a short description is given on its major findings.

A test of the hierarchical model of litter decomposition.

PubMed

Bradford, Mark A; Veen, G F Ciska; Bonis, Anne; Bradford, Ella M; Classen, Aimee T; Cornelissen, J Hans C; Crowther, Thomas W; De Long, Jonathan R; Freschet, Gregoire T; Kardol, Paul; Manrubia-Freixa, Marta; Maynard, Daniel S; Newman, Gregory S; Logtestijn, Richard S P; Viketoft, Maria; Wardle, David A; Wieder, William R; Wood, Stephen A; van der Putten, Wim H

2017-12-01

Our basic understanding of plant litter decomposition informs the assumptions underlying widely applied soil biogeochemical models, including those embedded in Earth system models. Confidence in projected carbon cycle-climate feedbacks therefore depends on accurate knowledge about the controls regulating the rate at which plant biomass is decomposed into products such as CO 2 . Here we test underlying assumptions of the dominant conceptual model of litter decomposition. The model posits that a primary control on the rate of decomposition at regional to global scales is climate (temperature and moisture), with the controlling effects of decomposers negligible at such broad spatial scales. Using a regional-scale litter decomposition experiment at six sites spanning from northern Sweden to southern France-and capturing both within and among site variation in putative controls-we find that contrary to predictions from the hierarchical model, decomposer (microbial) biomass strongly regulates decomposition at regional scales. Furthermore, the size of the microbial biomass dictates the absolute change in decomposition rates with changing climate variables. Our findings suggest the need for revision of the hierarchical model, with decomposers acting as both local- and broad-scale controls on litter decomposition rates, necessitating their explicit consideration in global biogeochemical models.

Hierarchical Aligned Cluster Analysis for Temporal Clustering of Human Motion.

PubMed

Zhou, Feng; De la Torre, Fernando; Hodgins, Jessica K

2013-03-01

Temporal segmentation of human motion into plausible motion primitives is central to understanding and building computational models of human motion. Several issues contribute to the challenge of discovering motion primitives: the exponential nature of all possible movement combinations, the variability in the temporal scale of human actions, and the complexity of representing articulated motion. We pose the problem of learning motion primitives as one of temporal clustering, and derive an unsupervised hierarchical bottom-up framework called hierarchical aligned cluster analysis (HACA). HACA finds a partition of a given multidimensional time series into m disjoint segments such that each segment belongs to one of k clusters. HACA combines kernel k-means with the generalized dynamic time alignment kernel to cluster time series data. Moreover, it provides a natural framework to find a low-dimensional embedding for time series. HACA is efficiently optimized with a coordinate descent strategy and dynamic programming. Experimental results on motion capture and video data demonstrate the effectiveness of HACA for segmenting complex motions and as a visualization tool. We also compare the performance of HACA to state-of-the-art algorithms for temporal clustering on data of a honey bee dance. The HACA code is available online.

Retrieval Capabilities of Hierarchical Networks: From Dyson to Hopfield

NASA Astrophysics Data System (ADS)

Agliari, Elena; Barra, Adriano; Galluzzi, Andrea; Guerra, Francesco; Tantari, Daniele; Tavani, Flavia

2015-01-01

We consider statistical-mechanics models for spin systems built on hierarchical structures, which provide a simple example of non-mean-field framework. We show that the coupling decay with spin distance can give rise to peculiar features and phase diagrams much richer than their mean-field counterpart. In particular, we consider the Dyson model, mimicking ferromagnetism in lattices, and we prove the existence of a number of metastabilities, beyond the ordered state, which become stable in the thermodynamic limit. Such a feature is retained when the hierarchical structure is coupled with the Hebb rule for learning, hence mimicking the modular architecture of neurons, and gives rise to an associative network able to perform single pattern retrieval as well as multiple-pattern retrieval, depending crucially on the external stimuli and on the rate of interaction decay with distance; however, those emergent multitasking features reduce the network capacity with respect to the mean-field counterpart. The analysis is accomplished through statistical mechanics, Markov chain theory, signal-to-noise ratio technique, and numerical simulations in full consistency. Our results shed light on the biological complexity shown by real networks, and suggest future directions for understanding more realistic models.

Real-time hierarchically distributed processing network interaction simulation

NASA Technical Reports Server (NTRS)

Zimmerman, W. F.; Wu, C.

1987-01-01

The Telerobot Testbed is a hierarchically distributed processing system which is linked together through a standard, commercial Ethernet. Standard Ethernet systems are primarily designed to manage non-real-time information transfer. Therefore, collisions on the net (i.e., two or more sources attempting to send data at the same time) are managed by randomly rescheduling one of the sources to retransmit at a later time interval. Although acceptable for transmitting noncritical data such as mail, this particular feature is unacceptable for real-time hierarchical command and control systems such as the Telerobot. Data transfer and scheduling simulations, such as token ring, offer solutions to collision management, but do not appropriately characterize real-time data transfer/interactions for robotic systems. Therefore, models like these do not provide a viable simulation environment for understanding real-time network loading. A real-time network loading model is being developed which allows processor-to-processor interactions to be simulated, collisions (and respective probabilities) to be logged, collision-prone areas to be identified, and network control variable adjustments to be reentered as a means of examining and reducing collision-prone regimes that occur in the process of simulating a complete task sequence.

Phylogenetic continuum indicates "galaxies" in the protein universe: preliminary results on the natural group structures of proteins.

PubMed

Ladunga, I

1992-04-01

The markedly nonuniform, even systematic distribution of sequences in the protein "universe" has been analyzed by methods of protein taxonomy. Mapping of the natural hierarchical system of proteins has revealed some dense cores, i.e., well-defined clusterings of proteins that seem to be natural structural groupings, possibly seeds for a future protein taxonomy. The aim was not to force proteins into more or less man-made categories by discriminant analysis, but to find structurally similar groups, possibly of common evolutionary origin. Single-valued distance measures between pairs of superfamilies from the Protein Identification Resource were defined by two chi 2-like methods on tripeptide frequencies and the variable-length subsequence identity method derived from dot-matrix comparisons. Distance matrices were processed by several methods of cluster analysis to detect phylogenetic continuum between highly divergent proteins. Only well-defined clusters characterized by relatively unique structural, intracellular environmental, organismal, and functional attribute states were selected as major protein groups, including subsets of viral and Escherichia coli proteins, hormones, inhibitors, plant, ribosomal, serum and structural proteins, amino acid synthases, and clusters dominated by certain oxidoreductases and apolar and DNA-associated enzymes. The limited repertoire of functional patterns due to small genome size, the high rate of recombination, specific features of the bacterial membranes, or of the virus cycle canalize certain proteins of viruses and Gram-negative bacteria, respectively, to organismal groups.

Skill components of task analysis

PubMed Central

Rogers, Wendy A.; Fisk, Arthur D.

2017-01-01

Some task analysis methods break down a task into a hierarchy of subgoals. Although an important tool of many fields of study, learning to create such a hierarchy (redescription) is not trivial. To further the understanding of what makes task analysis a skill, the present research examined novices’ problems with learning Hierarchical Task Analysis and captured practitioners’ performance. All participants received a task description and analyzed three cooking and three communication tasks by drawing on their knowledge of those tasks. Thirty six younger adults (18–28 years) in Study 1 analyzed one task before training and five afterwards. Training consisted of a general handout that all participants received and an additional handout that differed between three conditions: a list of steps, a flow-diagram, and concept map. In Study 2, eight experienced task analysts received the same task descriptions as in Study 1 and demonstrated their understanding of task analysis while thinking aloud. Novices’ initial task analysis scored low on all coding criteria. Performance improved on some criteria but was well below 100 % on others. Practitioners’ task analyses were 2–3 levels deep but also scored low on some criteria. A task analyst’s purpose of analysis may be the reason for higher specificity of analysis. This research furthers the understanding of Hierarchical Task Analysis and provides insights into the varying nature of task analyses as a function of experience. The derived skill components can inform training objectives. PMID:29075044

Polymeric assembly of gluten proteins in an aqueous ethanol solvent.

PubMed

Dahesh, Mohsen; Banc, Amélie; Duri, Agnès; Morel, Marie-Hélène; Ramos, Laurence

2014-09-25

The supramolecular organization of wheat gluten proteins is largely unknown due to the intrinsic complexity of this family of proteins and their insolubility in water. We fractionate gluten in a water/ethanol mixture (50/50 v/v) and obtain a protein extract which is depleted in gliadin, the monomeric part of wheat gluten proteins, and enriched in glutenin, the polymeric part of wheat gluten proteins. We investigate the structure of the proteins in the solvent used for extraction over a wide range of concentration, by combining X-ray scattering and multiangle static and dynamic light scattering. Our data show that, in the ethanol/water mixture, the proteins display features characteristic of flexible polymer chains in a good solvent. In the dilute regime, the proteins form very loose structures of characteristic size 150 nm, with an internal dynamics which is quantitatively similar to that of branched polymer coils. In more concentrated regimes, data highlight a hierarchical structure with one characteristic length scale of the order of a few nm, which displays the scaling with concentration expected for a semidilute polymer in good solvent, and a fractal arrangement at a much larger length scale. This structure is strikingly similar to that of polymeric gels, thus providing some factual knowledge to rationalize the viscoelastic properties of wheat gluten proteins and their assemblies.

Similar protein expression profiles of ovarian and endometrial high-grade serous carcinomas.

PubMed

Hiramatsu, Kosuke; Yoshino, Kiyoshi; Serada, Satoshi; Yoshihara, Kosuke; Hori, Yumiko; Fujimoto, Minoru; Matsuzaki, Shinya; Egawa-Takata, Tomomi; Kobayashi, Eiji; Ueda, Yutaka; Morii, Eiichi; Enomoto, Takayuki; Naka, Tetsuji; Kimura, Tadashi

2016-03-01

Ovarian and endometrial high-grade serous carcinomas (HGSCs) have similar clinical and pathological characteristics; however, exhaustive protein expression profiling of these cancers has yet to be reported. We performed protein expression profiling on 14 cases of HGSCs (7 ovarian and 7 endometrial) and 18 endometrioid carcinomas (9 ovarian and 9 endometrial) using iTRAQ-based exhaustive and quantitative protein analysis. We identified 828 tumour-expressed proteins and evaluated the statistical similarity of protein expression profiles between ovarian and endometrial HGSCs using unsupervised hierarchical cluster analysis (P<0.01). Using 45 statistically highly expressed proteins in HGSCs, protein ontology analysis detected two enriched terms and proteins composing each term: IMP2 and MCM2. Immunohistochemical analyses confirmed the higher expression of IMP2 and MCM2 in ovarian and endometrial HGSCs as well as in tubal and peritoneal HGSCs than in endometrioid carcinomas (P<0.01). The knockdown of either IMP2 or MCM2 by siRNA interference significantly decreased the proliferation rate of ovarian HGSC cell line (P<0.01). We demonstrated the statistical similarity of the protein expression profiles of ovarian and endometrial HGSC beyond the organs. We suggest that increased IMP2 and MCM2 expression may underlie some of the rapid HGSC growth observed clinically.

Cryogenic 3D printing for producing hierarchical porous and rhBMP-2-loaded Ca-P/PLLA nanocomposite scaffolds for bone tissue engineering.

PubMed

Wang, Chong; Zhao, Qilong; Wang, Min

2017-06-07

The performance of bone tissue engineering scaffolds can be assessed through cell responses to scaffolds, including cell attachment, infiltration, morphogenesis, proliferation, differentiation, etc, which are determined or heavily influenced by the composition, structure, mechanical properties, and biological properties (e.g. osteoconductivity and osteoinductivity) of scaffolds. Although some promising 3D printing techniques such as fused deposition modeling and selective laser sintering could be employed to produce biodegradable bone tissue engineering scaffolds with customized shapes and tailored interconnected pores, effective methods for fabricating scaffolds with well-designed hierarchical porous structure (both interconnected macropores and surface micropores) and tunable osteoconductivity/osteoinductivity still need to be developed. In this investigation, a novel cryogenic 3D printing technique was investigated and developed for producing hierarchical porous and recombinant human bone morphogenetic protein-2 (rhBMP-2)-loaded calcium phosphate (Ca-P) nanoparticle/poly(L-lactic acid) nanocomposite scaffolds, in which the Ca-P nanoparticle-incorporated scaffold layer and rhBMP-2-encapsulated scaffold layer were deposited alternatingly using different types of emulsions as printing inks. The mechanical properties of the as-printed scaffolds were comparable to those of human cancellous bone. Sustained releases of Ca 2+ ions and rhBMP-2 were achieved and the biological activity of rhBMP-2 was well-preserved. Scaffolds with a desirable hierarchical porous structure and dual delivery of Ca 2+ ions and rhBMP-2 exhibited superior performance in directing the behaviors of human bone marrow-derived mesenchymal stem cells and caused improved cell viability, attachment, proliferation, and osteogenic differentiation, which has suggested their great potential for bone tissue engineering.

Characterizing the course of back pain after osteoporotic vertebral fracture: a hierarchical cluster analysis of a prospective cohort study.

PubMed

Toyoda, Hiromitsu; Takahashi, Shinji; Hoshino, Masatoshi; Takayama, Kazushi; Iseki, Kazumichi; Sasaoka, Ryuichi; Tsujio, Tadao; Yasuda, Hiroyuki; Sasaki, Takeharu; Kanematsu, Fumiaki; Kono, Hiroshi; Nakamura, Hiroaki

2017-09-23

This study demonstrated four distinct patterns in the course of back pain after osteoporotic vertebral fracture (OVF). Greater angular instability in the first 6 months after the baseline was one factor affecting back pain after OVF. Understanding the natural course of symptomatic acute OVF is important in deciding the optimal treatment strategy. We used latent class analysis to classify the course of back pain after OVF and identify the risk factors associated with persistent pain. This multicenter cohort study included 218 consecutive patients with ≤ 2-week-old OVFs who were enrolled at 11 institutions. Dynamic x-rays and back pain assessment with a visual analog scale (VAS) were obtained at enrollment and at 1-, 3-, and 6-month follow-ups. The VAS scores were used to characterize patient groups, using hierarchical cluster analysis. VAS for 128 patients was used for hierarchical cluster analysis. Analysis yielded four clusters representing different patterns of back pain progression. Cluster 1 patients (50.8%) had stable, mild pain. Cluster 2 patients (21.1%) started with moderate pain and progressed quickly to very low pain. Patients in cluster 3 (10.9%) had moderate pain that initially improved but worsened after 3 months. Cluster 4 patients (17.2%) had persistent severe pain. Patients in cluster 4 showed significant high baseline pain intensity, higher degree of angular instability, and higher number of previous OVFs, and tended to lack regular exercise. In contrast, patients in cluster 2 had significantly lower baseline VAS and less angular instability. We identified four distinct groups of OVF patients with different patterns of back pain progression. Understanding the course of back pain after OVF may help in its management and contribute to future treatment trials.

Spatial patterns of breeding success of grizzly bears derived from hierarchical multistate models.

PubMed

Fisher, Jason T; Wheatley, Matthew; Mackenzie, Darryl

2014-10-01

Conservation programs often manage populations indirectly through the landscapes in which they live. Empirically, linking reproductive success with landscape structure and anthropogenic change is a first step in understanding and managing the spatial mechanisms that affect reproduction, but this link is not sufficiently informed by data. Hierarchical multistate occupancy models can forge these links by estimating spatial patterns of reproductive success across landscapes. To illustrate, we surveyed the occurrence of grizzly bears (Ursus arctos) in the Canadian Rocky Mountains Alberta, Canada. We deployed camera traps for 6 weeks at 54 surveys sites in different types of land cover. We used hierarchical multistate occupancy models to estimate probability of detection, grizzly bear occupancy, and probability of reproductive success at each site. Grizzly bear occupancy varied among cover types and was greater in herbaceous alpine ecotones than in low-elevation wetlands or mid-elevation conifer forests. The conditional probability of reproductive success given grizzly bear occupancy was 30% (SE = 0.14). Grizzly bears with cubs had a higher probability of detection than grizzly bears without cubs, but sites were correctly classified as being occupied by breeding females 49% of the time based on raw data and thus would have been underestimated by half. Repeated surveys and multistate modeling reduced the probability of misclassifying sites occupied by breeders as unoccupied to <2%. The probability of breeding grizzly bear occupancy varied across the landscape. Those patches with highest probabilities of breeding occupancy-herbaceous alpine ecotones-were small and highly dispersed and are projected to shrink as treelines advance due to climate warming. Understanding spatial correlates in breeding distribution is a key requirement for species conservation in the face of climate change and can help identify priorities for landscape management and protection. © 2014 Society for Conservation Biology.

Neuroanatomical Markers of Social Hierarchy Recognition in Humans: A Combined ERP/MRI Study.

PubMed

Santamaría-García, Hernando; Burgaleta, Miguel; Sebastián-Gallés, Nuria

2015-07-29

Social hierarchy is an ubiquitous principle of social organization across animal species. Although some progress has been made in our understanding of how humans infer hierarchical identity, the neuroanatomical basis for perceiving key social dimensions of others remains unexplored. Here, we combined event-related potentials and structural MRI to reveal the neuroanatomical substrates of early status recognition. We designed a covertly simulated hierarchical setting in which participants performed a task either with a superior or with an inferior player. Participants showed higher amplitude in the N170 component when presented with a picture of a superior player compared with an inferior player. Crucially, the magnitude of this effect correlated with brain morphology of the posterior cingulate cortex, superior temporal gyrus, insula, fusiform gyrus, and caudate nucleus. We conclude that early recognition of social hierarchies relies on the structural properties of a network involved in the automatic recognition of social identity. Humans can perceive social hierarchies very rapidly, an ability that is key for social interactions. However, some individuals are more sensitive to hierarchical information than others. Currently, it is unknown how brain structure supports such fast-paced processes of social hierarchy perception and their individual differences. Here, we addressed this issue for the first time by combining the high temporal resolution of event-related potentials (ERPs) and the high spatial resolution of structural MRI. This methodological approach allowed us to unveil a novel association between ERP neuromarkers of social hierarchy perception and the morphology of several cortical and subcortical brain regions typically assumed to play a role in automatic processes of social cognition. Our results are a step forward in our understanding of the human social brain. Copyright © 2015 the authors 0270-6474/15/3510843-08$15.00/0.

Understanding Disproportionate Representation in Special Education by Examining Group Differences in Behavior Ratings

ERIC Educational Resources Information Center

Peters, Christina D.; Kranzler, John H.; Algina, James; Smith, Stephen W.; Daunic, Ann P.

2014-01-01

The aim of the current study was to examine mean-group differences on behavior rating scales and variables that may predict such differences. Sixty-five teachers completed the Clinical Assessment of Behavior-Teacher Form (CAB-T) for a sample of 982 students. Four outcome variables from the CAB-T were assessed. Hierarchical linear modeling was used…

Static Extraction and Conformance Analysis of Hierarchical Runtime Architectural Structure

DTIC Science & Technology

2010-05-14

Example: CryptoDB 253 Architectural Component Java Class Note CustomerManager cryptodb.test.CustomerManager AKA “ crypto consumer” CustomerManager.Receipts...PROVIDERS PLAIN KEYID KEYMANAGEMENT KEYSTORAGE CRYPTO (+) (+) (+) (+) (+) (+) (+)(+) Figure 7.29: CryptoDB: Level-0 OOG with String objects...better understand this communication, we declared different domains for plain-text (PLAIN), encrypted ( CRYPTO ), alias identifier (ALIASID), and key

Abrupt Strategy Change Underlies Gradual Performance Change: Bayesian Hierarchical Models of Component and Aggregate Strategy Use

ERIC Educational Resources Information Center

Wynton, Sarah K. A.; Anglim, Jeromy

2017-01-01

While researchers have often sought to understand the learning curve in terms of multiple component processes, few studies have measured and mathematically modeled these processes on a complex task. In particular, there remains a need to reconcile how abrupt changes in strategy use can co-occur with gradual changes in task completion time. Thus,…

Studies of the molecular interaction between cellulose and lignin as a model for the hierarchical structure of wood

Treesearch

Wolfgang G. Glasser; Timothy G. Rials; Stephen S. Kelly; Vipul Dave

1998-01-01

Wood and dietary fiber products all belong to a class of biomolecular composites that are rich in cellulose and lignin. The interaction between cellulose and lignin determines such properties as mechanical strength (wood); creep, durability, and aging; cellulose purity (pulp); and digestibility (nutrients). The understanding of the interaction between cellulose and...

Placing Deviance in a Legal and Local Context: A Multilevel Analysis of Cigarette Use in the European Union

ERIC Educational Resources Information Center

Vuolo, Mike

2012-01-01

Though it has produced a high-quality body of research, the study of substance use has remained highly individualized in its focus. This paper adds further sociological understanding to that research. Using hierarchical models, the following explores how institutional and criminological theories can be incorporated into substance use research by…

Student Conceptions about the DNA Structure within a Hierarchical Organizational Level: Improvement by Experiment- and Computer-Based Outreach Learning

ERIC Educational Resources Information Center

Langheinrich, Jessica; Bogner, Franz X.

2015-01-01

As non-scientific conceptions interfere with learning processes, teachers need both, to know about them and to address them in their classrooms. For our study, based on 182 eleventh graders, we analyzed the level of conceptual understanding by implementing the "draw and write" technique during a computer-supported gene technology module.…

My Body Had a Mind of Its Own: On Teaching, the Illusion of Control, and the Terrifying Limits of Governmentality (Part 2)

ERIC Educational Resources Information Center

Koza, Julia Eklund

2010-01-01

In the final installment of her two-part essay, Julia Eklund Koza analyzes prevalent control and management discourse in education, specifically, music education. Arguing that dominant understandings are hierarchical, gendered, illusory, and integrally related to projects and practices largely unrelated to schooling, she invites teachers and…

Machine Understanding of Human Implicit Intention

DTIC Science & Technology

2013-05-18

Cognitive Neurodynamics , Hokkaido, Japan, June 2011, Hokkaido, Japan (Plenary Talk) - Soo-Young Lee, Implicit Intention Recognition and Hierarchical...subject’s response with the accuracy of about 80% by SVM. 15. SUBJECT TERMS Brain Science and Engineering; Cognitive Neuroscience; Human-Computer...oscillations have been related to a variety of functions such as perception, cognition , sleep, etc. For a long time, researchers have found the sensory and

Making Graphical Inferences: A Hierarchical Framework

DTIC Science & Technology

2004-08-01

from graphs is considered one of the more complex skills graph readers should possess. According to the National Council of Teachers of Mathematics ...understanding graphical perception. Human Computer Interaction, 8, 353-388. NCTM : Standards for Mathematics . (2003, 2003). Pinker, S. (1990). A theory... NCTM ) the simplest type of question involves the extraction or comparison of a few explicitly represented data points (read-offs) ( NCTM : Standards

Differentiation of Students' Reasoning on Linear and Quadratic Geometric Number Patterns

ERIC Educational Resources Information Center

Lin, Fou-Lai; Yang, Kai-Lin

2004-01-01

There are two purposes in this study. One is to compare how 7th and 8th graders reason on linear and quadratic geometric number patterns when they have not learned this kind of tasks in school. The other is to explore the hierarchical relations among the four components of reasoning on geometric number patterns: understanding, generalizing,…

A SELDI mass spectrometry study of experimental autoimmune encephalomyelitis: sample preparation, reproducibility, and differential protein expression patterns.

PubMed

Azzam, Sausan; Broadwater, Laurie; Li, Shuo; Freeman, Ernest J; McDonough, Jennifer; Gregory, Roger B

2013-05-01

Experimental autoimmune encephalomyelitis (EAE) is an autoimmune, inflammatory disease of the central nervous system that is widely used as a model of multiple sclerosis (MS). Mitochondrial dysfunction appears to play a role in the development of neuropathology in MS and may also play a role in disease pathology in EAE. Here, surface enhanced laser desorption ionization mass spectrometry (SELDI-MS) has been employed to obtain protein expression profiles from mitochondrially enriched fractions derived from EAE and control mouse brain. To gain insight into experimental variation, the reproducibility of sub-cellular fractionation, anion exchange fractionation as well as spot-to-spot and chip-to-chip variation using pooled samples from brain tissue was examined. Variability of SELDI mass spectral peak intensities indicates a coefficient of variation (CV) of 15.6% and 17.6% between spots on a given chip and between different chips, respectively. Thinly slicing tissue prior to homogenization with a rotor homogenizer showed better reproducibility (CV = 17.0%) than homogenization of blocks of brain tissue with a Teflon® pestle (CV = 27.0%). Fractionation of proteins with anion exchange beads prior to SELDI-MS analysis gave overall CV values from 16.1% to 18.6%. SELDI mass spectra of mitochondrial fractions obtained from brain tissue from EAE mice and controls displayed 39 differentially expressed proteins (p≤ 0.05) out of a total of 241 protein peaks observed in anion exchange fractions. Hierarchical clustering analysis showed that protein fractions from EAE animals with severe disability clearly segregated from controls. Several components of electron transport chain complexes (cytochrome c oxidase subunit 6b1, subunit 6C, and subunit 4; NADH dehydrogenase flavoprotein 3, alpha subcomplex subunit 2, Fe-S protein 4, and Fe-S protein 6; and ATP synthase subunit e) were identified as possible differentially expressed proteins. Myelin Basic Protein isoform 8 (MBP8) (14.2 kDa) levels were lower in EAE samples with advanced disease relative to controls, while an MBP fragment (12. 4kDa), likely due to calpain digestion, was increased in EAE relative to controls. The appearance of MBP in mitochondrially enriched fractions is due to tissue freezing and storage, as MBP was not found associated with mitochondria obtained from fresh tissue. SELDI mass spectrometry can be employed to explore the proteome of a complex tissue (brain) and obtain protein profiles of differentially expressed proteins from protein fractions. Appropriate homogenization protocols and protein fractionation using anion exchange beads can be employed to reduce sample complexity without introducing significant additional variation into the SELDI mass spectra beyond that inherent in the SELDI- MS method itself. SELDI-MS coupled with principal component analysis and hierarchical cluster analysis provides protein patterns that can clearly distinguish the disease state from controls. However, identification of individual differentially expressed proteins requires a separate purification of the proteins of interest by polyacrylamide electrophoresis prior to trypsin digestion and peptide mass fingerprint analysis, and unambiguous identification of differentially expressed proteins can be difficult if protein bands consist of several proteins with similar molecular weights.

A SELDI mass spectrometry study of experimental autoimmune encephalomyelitis: sample preparation, reproducibility, and differential protein expression patterns

PubMed Central

2013-01-01

Background Experimental autoimmune encephalomyelitis (EAE) is an autoimmune, inflammatory disease of the central nervous system that is widely used as a model of multiple sclerosis (MS). Mitochondrial dysfunction appears to play a role in the development of neuropathology in MS and may also play a role in disease pathology in EAE. Here, surface enhanced laser desorption ionization mass spectrometry (SELDI-MS) has been employed to obtain protein expression profiles from mitochondrially enriched fractions derived from EAE and control mouse brain. To gain insight into experimental variation, the reproducibility of sub-cellular fractionation, anion exchange fractionation as well as spot-to-spot and chip-to-chip variation using pooled samples from brain tissue was examined. Results Variability of SELDI mass spectral peak intensities indicates a coefficient of variation (CV) of 15.6% and 17.6% between spots on a given chip and between different chips, respectively. Thinly slicing tissue prior to homogenization with a rotor homogenizer showed better reproducibility (CV = 17.0%) than homogenization of blocks of brain tissue with a Teflon® pestle (CV = 27.0%). Fractionation of proteins with anion exchange beads prior to SELDI-MS analysis gave overall CV values from 16.1% to 18.6%. SELDI mass spectra of mitochondrial fractions obtained from brain tissue from EAE mice and controls displayed 39 differentially expressed proteins (p≤ 0.05) out of a total of 241 protein peaks observed in anion exchange fractions. Hierarchical clustering analysis showed that protein fractions from EAE animals with severe disability clearly segregated from controls. Several components of electron transport chain complexes (cytochrome c oxidase subunit 6b1, subunit 6C, and subunit 4; NADH dehydrogenase flavoprotein 3, alpha subcomplex subunit 2, Fe-S protein 4, and Fe-S protein 6; and ATP synthase subunit e) were identified as possible differentially expressed proteins. Myelin Basic Protein isoform 8 (MBP8) (14.2 kDa) levels were lower in EAE samples with advanced disease relative to controls, while an MBP fragment (12. 4kDa), likely due to calpain digestion, was increased in EAE relative to controls. The appearance of MBP in mitochondrially enriched fractions is due to tissue freezing and storage, as MBP was not found associated with mitochondria obtained from fresh tissue. Conclusions SELDI mass spectrometry can be employed to explore the proteome of a complex tissue (brain) and obtain protein profiles of differentially expressed proteins from protein fractions. Appropriate homogenization protocols and protein fractionation using anion exchange beads can be employed to reduce sample complexity without introducing significant additional variation into the SELDI mass spectra beyond that inherent in the SELDI- MS method itself. SELDI-MS coupled with principal component analysis and hierarchical cluster analysis provides protein patterns that can clearly distinguish the disease state from controls. However, identification of individual differentially expressed proteins requires a separate purification of the proteins of interest by polyacrylamide electrophoresis prior to trypsin digestion and peptide mass fingerprint analysis, and unambiguous identification of differentially expressed proteins can be difficult if protein bands consist of several proteins with similar molecular weights. PMID:23635033

Interplay Between Conceptual Expectations and Movement Predictions Underlies Action Understanding.

PubMed

Ondobaka, Sasha; de Lange, Floris P; Wittmann, Marco; Frith, Chris D; Bekkering, Harold

2015-09-01

Recent accounts of understanding goal-directed action underline the importance of a hierarchical predictive architecture. However, the neural implementation of such an architecture remains elusive. In the present study, we used functional neuroimaging to quantify brain activity associated with predicting physical movements, as they were modulated by conceptual-expectations regarding the purpose of the object involved in the action. Participants observed object-related actions preceded by a cue that generated both conceptual goal expectations and movement goal predictions. In 2 tasks, observers judged whether conceptual or movement goals matched or mismatched the cue. At the conceptual level, expected goals specifically recruited the posterior cingulate cortex, irrespectively of the task and the perceived movement goal. At the movement level, neural activation of the parieto-frontal circuit, including inferior frontal gyrus and the inferior parietal lobe, reflected unpredicted movement goals. Crucially, this movement prediction error was only present when the purpose of the involved object was expected. These findings provide neural evidence that prior conceptual expectations influence processing of physical movement goals and thereby support the hierarchical predictive account of action processing. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Regulation of Effector Delivery by Type III Secretion Chaperone Proteins in Erwinia amylovora.

PubMed

Castiblanco, Luisa F; Triplett, Lindsay R; Sundin, George W

2018-01-01

Type III secretion (TTS) chaperones are critical for the delivery of many effector proteins from Gram-negative bacterial pathogens into host cells, functioning in the stabilization and hierarchical delivery of the effectors to the type III secretion system (TTSS). The plant pathogen Erwinia amylovora secretes at least four TTS effector proteins: DspE, Eop1, Eop3, and Eop4. DspE specifically interacts with the TTS chaperone protein DspF, which stabilizes the effector protein in the cytoplasm and promotes its efficient translocation through the TTSS. However, the role of E. amylovora chaperones in regulating the delivery of other secreted effectors is unknown. In this study, we identified functional interactions between the effector proteins DspE, Eop1, and Eop3 with the TTS chaperones DspF, Esc1 and Esc3 in yeast. Using site-directed mutagenesis, secretion, and translocation assays, we demonstrated that the three TTS chaperones have additive roles for the secretion and translocation of DspE into plant cells whereas DspF negatively affects the translocation of Eop1 and Eop3. Collectively, these results indicate that TTS chaperone proteins exhibit a cooperative behavior to orchestrate the effector secretion and translocation dynamics in E. amylovora .

Structural alphabets derived from attractors in conformational space

PubMed Central

2010-01-01

Background The hierarchical and partially redundant nature of protein structures justifies the definition of frequently occurring conformations of short fragments as 'states'. Collections of selected representatives for these states define Structural Alphabets, describing the most typical local conformations within protein structures. These alphabets form a bridge between the string-oriented methods of sequence analysis and the coordinate-oriented methods of protein structure analysis. Results A Structural Alphabet has been derived by clustering all four-residue fragments of a high-resolution subset of the protein data bank and extracting the high-density states as representative conformational states. Each fragment is uniquely defined by a set of three independent angles corresponding to its degrees of freedom, capturing in simple and intuitive terms the properties of the conformational space. The fragments of the Structural Alphabet are equivalent to the conformational attractors and therefore yield a most informative encoding of proteins. Proteins can be reconstructed within the experimental uncertainty in structure determination and ensembles of structures can be encoded with accuracy and robustness. Conclusions The density-based Structural Alphabet provides a novel tool to describe local conformations and it is specifically suitable for application in studies of protein dynamics. PMID:20170534

Hierarchical charge distribution controls self-assembly process of silk in vitro

NASA Astrophysics Data System (ADS)

Zhang, Yi; Zhang, Cencen; Liu, Lijie; Kaplan, David L.; Zhu, Hesun; Lu, Qiang

2015-12-01

Silk materials with different nanostructures have been developed without the understanding of the inherent transformation mechanism. Here we attempt to reveal the conversion road of the various nanostructures and determine the critical regulating factors. The regulating conversion processes influenced by a hierarchical charge distribution were investigated, showing different transformations between molecules, nanoparticles and nanofibers. Various repulsion and compressive forces existed among silk fibroin molecules and aggregates due to the exterior and interior distribution of charge, which further controlled their aggregating and deaggregating behaviors and finally formed nanofibers with different sizes. Synergistic action derived from molecular mobility and concentrations could also tune the assembly process and final nanostructures. It is suggested that the complicated silk fibroin assembly processes comply a same rule based on charge distribution, offering a promising way to develop silk-based materials with designed nanostructures.

Approaches for advancing scientific understanding of macrosystems

USGS Publications Warehouse

Levy, Ofir; Ball, Becky A.; Bond-Lamberty, Ben; Cheruvelil, Kendra S.; Finley, Andrew O.; Lottig, Noah R.; Surangi W. Punyasena,; Xiao, Jingfeng; Zhou, Jizhong; Buckley, Lauren B.; Filstrup, Christopher T.; Keitt, Tim H.; Kellner, James R.; Knapp, Alan K.; Richardson, Andrew D.; Tcheng, David; Toomey, Michael; Vargas, Rodrigo; Voordeckers, James W.; Wagner, Tyler; Williams, John W.

2014-01-01

The emergence of macrosystems ecology (MSE), which focuses on regional- to continental-scale ecological patterns and processes, builds upon a history of long-term and broad-scale studies in ecology. Scientists face the difficulty of integrating the many elements that make up macrosystems, which consist of hierarchical processes at interacting spatial and temporal scales. Researchers must also identify the most relevant scales and variables to be considered, the required data resources, and the appropriate study design to provide the proper inferences. The large volumes of multi-thematic data often associated with macrosystem studies typically require validation, standardization, and assimilation. Finally, analytical approaches need to describe how cross-scale and hierarchical dynamics and interactions relate to macroscale phenomena. Here, we elaborate on some key methodological challenges of MSE research and discuss existing and novel approaches to meet them.

Stepwise Splitting Growth and Pseudocapacitive Properties of Hierarchical Three-Dimensional Co3O4 Nanobooks

PubMed Central

Chen, Huilong; Lu, Shuang; Gong, Feilong; Liu, Huanzhen; Li, Feng

2017-01-01

Three-dimensional hierarchical Co3O4 nanobooks have been synthesized successfully on a large scale by calcining orthorhombic Co(CO3)0.5(OH)·0.11H2O precursors with identical morphologies. Based on the influence of reaction time and urea concentration on the nanostructures of the precursors, a stepwise splitting growth mechanism can be proposed to understand the formation of the 3D nanobooks. The 3D Co3O4 nanobooks exhibit excellent pseudocapacitive performances with specific capacitances of 590, 539, 476, 453, and 421 F/g at current densities of 0.5, 1, 2, 4, and 8 A/g, respectively. The devices can retain ca. 97.4% of the original specific capacitances after undergoing charge–discharge cycle tests 1000 times continuously at 4 A/g. PMID:28394297

Green self-assembly of zein-conjugated ZnO/Cd(OH)Cl hierarchical nanocomposites with high cytotoxicity and immune organs targeting

NASA Astrophysics Data System (ADS)

Wang, Hua-Jie; Cao, Ying; Wang, Cai-Feng; Cui, Shi-Zhong; Mi, Li-Wei; Miyazawa, Teruo

2016-04-01

Inorganic nanomedicines in the fight against cancer have progressed rapidly during recent years, with the synergistic advantages of multifunctional nanosystems compared to single component. Herein, a drug-combination opinion was introduced into “nanomedicine” based on the understanding of Trojan horse-anti-tumor mechanism of inorganic nano-medicines. Moreover, we reported the green and facile synthesis route of mono-dispersed and rod-like zein-conjugated ZnO/Cd(OH)Cl hierarchical nanocomposites. We found that the nanocomposites exhibited high-efficiency killing ability to tumor cells through lipid peroxidation mediated-membrane disintegration route. The safety studies in BALB/c mice didn’t detect injection anaphylaxis, hemolysis and cytotoxicity. More interestingly, the nano-composites could specially accumulate in liver and kidney, which will be helpful for targeting cure to these regional cancers.

Exploring physics concepts among novice teachers through CMAP tools

NASA Astrophysics Data System (ADS)

Suprapto, N.; Suliyanah; Prahani, B. K.; Jauhariyah, M. N. R.; Admoko, S.

2018-03-01

Concept maps are graphical tools for organising, elaborating and representing knowledge. Through Cmap tools software, it can be explored the understanding and the hierarchical structuring of physics concepts among novice teachers. The software helps physics teachers indicated a physics context, focus questions, parking lots, cross-links, branching, hierarchy, and propositions. By using an exploratory quantitative study, a total 13-concept maps with different physics topics created by novice physics teachers were analysed. The main differences of scoring between lecturer and peer-teachers’ scoring were also illustrated. The study offered some implications, especially for physics educators to determine the hierarchical structure of the physics concepts, to construct a physics focus question, and to see how a concept in one domain of knowledge represented on the map is related to a concept in another domain shown on the map.

Modular Self-Assembly of Protein Cage Lattices for Multistep Catalysis

DOE PAGES

Uchida, Masaki; McCoy, Kimberly; Fukuto, Masafumi; ...

2017-11-13

The assembly of individual molecules into hierarchical structures is a promising strategy for developing three-dimensional materials with properties arising from interaction between the individual building blocks. Virus capsids are elegant examples of biomolecular nanostructures, which are themselves hierarchically assembled from a limited number of protein subunits. Here, we demonstrate the bio-inspired modular construction of materials with two levels of hierarchy: the formation of catalytically active individual virus-like particles (VLPs) through directed self-assembly of capsid subunits with enzyme encapsulation, and the assembly of these VLP building blocks into three-dimensional arrays. The structure of the assembled arrays was successfully altered from anmore » amorphous aggregate to an ordered structure, with a face-centered cubic lattice, by modifying the exterior surface of the VLP without changing its overall morphology, to modulate interparticle interactions. The assembly behavior and resultant lattice structure was a consequence of interparticle interaction between exterior surfaces of individual particles and thus independent of the enzyme cargos encapsulated within the VLPs. These superlattice materials, composed of two populations of enzyme-packaged VLP modules, retained the coupled catalytic activity in a two-step reaction for isobutanol synthesis. As a result, this study demonstrates a significant step toward the bottom-up fabrication of functional superlattice materials using a self-assembly process across multiple length scales and exhibits properties and function that arise from the interaction between individual building blocks.« less

Modular Self-Assembly of Protein Cage Lattices for Multistep Catalysis

PubMed Central

Uchida, Masaki; McCoy, Kimberly; Fukuto, Masafumi; Yang, Lin; Yoshimura, Hideyuki; Miettinen, Heini M.; LaFrance, Ben; Patterson, Dustin P.; Schwarz, Benjamin; Karty, Jonathan A.; Prevelige, Peter E.; Lee, Byeongdu; Douglas, Trevor

2018-01-01

The assembly of individual molecules into hierarchical structures is a promising strategy for developing three-dimensional materials with properties arising from interaction between the individual building blocks. Virus capsids are elegant examples of biomolecular nanostructures, which are themselves hierarchically assembled from a limited number of protein subunits. Here we demonstrate the bio-inspired modular construction of materials with two levels of hierarchy; the formation of catalytically active individual virus-like particles (VLPs) through directed self-assembly of capsid subunits with enzyme encapsulation, and the assembly of these VLP building blocks into three-dimensional arrays. The structure of the assembled arrays was successfully altered from an amorphous aggregate to an ordered structure, with a face-centered cubic lattice, by modifying the exterior surface of the VLP without changing its overall morphology, to modulate interparticle interactions. The assembly behavior and resultant lattice structure was a consequence of interparticle interaction between exterior surfaces of individual particles, and thus independent of the enzyme cargos encapsulated within the VLPs. These superlattice materials, composed of two populations of enzyme packaged VLP modules, retained the coupled catalytic activity in a two-step reaction for isobutanol synthesis. This study demonstrates a significant step toward the bottom-up fabrication of functional superlattice materials using a self-assembly process across multiple length scales, and exhibits properties and function that arise from the interaction between individual building blocks. PMID:29131580

Modular Self-Assembly of Protein Cage Lattices for Multistep Catalysis

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

Uchida, Masaki; McCoy, Kimberly; Fukuto, Masafumi

The assembly of individual molecules into hierarchical structures is a promising strategy for developing three-dimensional materials with properties arising from interaction between the individual building blocks. Virus capsids are elegant examples of biomolecular nanostructures, which are themselves hierarchically assembled from a limited number of protein subunits. Here, we demonstrate the bio-inspired modular construction of materials with two levels of hierarchy: the formation of catalytically active individual virus-like particles (VLPs) through directed self-assembly of capsid subunits with enzyme encapsulation, and the assembly of these VLP building blocks into three-dimensional arrays. The structure of the assembled arrays was successfully altered from anmore » amorphous aggregate to an ordered structure, with a face-centered cubic lattice, by modifying the exterior surface of the VLP without changing its overall morphology, to modulate interparticle interactions. The assembly behavior and resultant lattice structure was a consequence of interparticle interaction between exterior surfaces of individual particles and thus independent of the enzyme cargos encapsulated within the VLPs. These superlattice materials, composed of two populations of enzyme-packaged VLP modules, retained the coupled catalytic activity in a two-step reaction for isobutanol synthesis. As a result, this study demonstrates a significant step toward the bottom-up fabrication of functional superlattice materials using a self-assembly process across multiple length scales and exhibits properties and function that arise from the interaction between individual building blocks.« less

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