X-Ray Studies On Crystalline Complexes Involving Amino-Acids And Peptides .11. Peptide Aggregation And Water-Structure In The Crystals Of A Hydrated 1-1 Complex Between L-Histidyl-L-Serine And Glycyl-L-Glutamic Acid

The hexahydrate of a 1:1 complex between L-histidyl-L-serine and glycyl-L-glutamic acid crystallizes in space group P1 with a = 4.706(1), b= 8.578(2), c= 16.521(3) ÅA; α= 85.9(1), β= 89.7(1)°, = 77.4(1). The crystal structure, solved by direct methods, has been refined to an R value of 0.046 for 2150 observed reflections. The two peptide molecules in the structure have somewhat extended conformations. The unlike molecules aggregate into separate alternating layers. Each layer is stabilized by hydrogen bonded head-to-tail sequences as well as sequences of hydrogen bonds involving peptide groups. The arrangement of molecules in each layer is similar to one of the plausible idealized arrangements of L-alanyl-L-alanine worked out from simple geometrical considerations. Adjacent layers in the structure are held together by interactions involving side chains as well as water molecules. The water structure observed in the complex provides a good model, at atomic resolution, for that in protein crystals. An interesting feature of the crystal structure is the existence of two water channels in the interfaces between adjacent peptide layers.

Visualization of in situ intracellular aggregation of two cataract-associated human gamma-crystallin mutants: Lose a tail, lose transparency

PURPOSE. To understand the molecular features underlying autosomal dominant congenital cataracts caused by the deletion mutations W156X in human gamma D-crystallin and W157X in human gamma C-crystallin. METHODS. Normal and mutant cDNAs (with the enhanced green fluorescent protein [EGFP] tag in the front) were cloned into the pEGFP-C1 vector, transfected into various cell lines, and observed under a confocal microscope for EGFP fluorescence. Normal and W156X gamma D cDNAs were also cloned into the pET21a(+) vector, and the recombinant proteins were overexpressed in the BL-21(DE3) pLysS strain of Escherichia coli, purified, and isolated. The conformational features, structural stability, and solubility in aqueous solution of the mutant protein were compared with those of the wild type using spectroscopic methods. Comparative molecular modeling was performed to provide additional structural information. RESULTS. Transfection of the EGFP-tagged mutant cDNAs into several cell lines led to the visualization of aggregates, whereas that of wild-type cDNAs did not. Turning to the properties of the expressed proteins, the mutant molecules show remarkable reduction in solubility. They also seem to have a greater degree of surface hydrophobicity than the wild-type molecules, most likely accounting for self-aggregation. Molecular modeling studies support these features. CONCLUSIONS. The deletion of C-terminal 18 residues of human gamma C-and gamma D-crystallins exposes the side chains of several hydrophobic residues in the sequence to the solvent, causing the molecule to self-aggregate. This feature appears to be reflected in situ on the introduction of the mutants in human lens epithelial cells.

X-ray studies on crystalline complexes involving amino acids and peptides. XV. Crystal structures of L-lysine D-glutamate and L-lysine D-aspartate monohydrate and the effect of chirality on molecular aggregation

L-Lysine D-glutamate crystallizes in the monoclinic space group P2(1) with a = 4.902, b = 30.719, c = 9.679 A, beta = 90 degrees and Z = 4. The crystals of L-lysine D-aspartate monohydrate belong to the orthorhombic space group P2(1)2(1)2(1) with a = 5.458, b = 7.152, c = 36.022 A and Z = 4. The structures were solved by the direct methods and refined to R values of 0.125 and 0.040 respectively for 1412 and 1503 observed reflections. The glutamate complex is highly pseudosymmetric. The lysine molecules in it assume a conformation with the side chain staggered between the alpha-amino and the alpha-carboxylate groups. The interactions of the side chain amino groups of lysine in the two complexes are such that they form infinite sequences containing alternating amino and carboxylate groups. The molecular aggregation in the glutamate complex is very similar to that observed in L-arginine D-aspartate and L-arginine D-glutamate trihydrate, with the formation of double layers consisting of both types of molecules. In contrast to the situation in the other three LD complexes, the unlike molecules in L-lysine D-aspartate monohydrate aggregate into alternating layers as in the case of most LL complexes. The arrangement of molecules in the lysine layer is nearly the same as in L-lysine L-aspartate, with head-to-tail sequences as the central feature. The arrangement of aspartate ions in the layers containing them is, however, somewhat unusual. Thus the comparison between the LL and the LD complexes analyzed so far indicates that the reversal of chirality of one of the components in a complex leads to profound changes in molecular aggregation, but these changes could be of more than one type.

Enhancing Speedup in Network Processing Applications by Exploiting Instruction Reuse with Flow Aggregation

Instruction reuse is a microarchitectural technique that improves the execution time of a program by removing redundant computations at run-time. Although this is the job of an optimizing compiler, they do not succeed many a time due to limited knowledge of run-time data. In this paper we examine instruction reuse of integer ALU and load instructions in network processing applications. Specifically, this paper attempts to answer the following questions: (1) How much of instruction reuse is inherent in network processing applications?, (2) Can reuse be improved by reducing interference in the reuse buffer?, (3) What characteristics of network applications can be exploited to improve reuse?, and (4) What is the effect of reuse on resource contention and memory accesses? We propose an aggregation scheme that combines the high-level concept of network traffic i.e. "flows" with a low level microarchitectural feature of programs i.e. repetition of instructions and data along with an architecture that exploits temporal locality in incoming packet data to improve reuse. We find that for the benchmarks considered, 1% to 50% of instructions are reused while the speedup achieved varies between 1% and 24%. As a side effect, instruction reuse reduces memory traffic and can therefore be considered as a scheme for low power.

Donut-Shaped Fingerprint In Homologous Polypeptide Relationships-A Topological Feature Related To Pathogenic Structural Changes In Conformational Disease

Features of homologous relationship of proteins can provide us a general picture of protein universe, assist protein design and analysis, and further our comprehension of the evolution of organisms. Here we carried Out a Study of the evolution Of protein molecules by investigating homologous relationships among residue segments. The motive was to identify detailed topological features of homologous relationships for short residue segments in the whole protein universe. Based on the data of a large number of non-redundant Proteins, the universe of non-membrane polypeptide was analyzed by considering both residue mutations and structural conservation. By connecting homologous segments with edges, we obtained a homologous relationship network of the whole universe of short residue segments, which we named the graph of polypeptide relationships (GPR). Since the network is extremely complicated for topological transitions, to obtain an in-depth understanding, only subgraphs composed of vital nodes of the GPR were analyzed. Such analysis of vital subgraphs of the GPR revealed a donut-shaped fingerprint. Utilization of this topological feature revealed the switch sites (where the beginning of exposure Of previously hidden "hot spots" of fibril-forming happens, in consequence a further opportunity for protein aggregation is Provided; 188-202) of the conformational conversion of the normal alpha-helix-rich prion protein PrPC to the beta-sheet-rich PrPSc that is thought to be responsible for a group of fatal neurodegenerative diseases, transmissible spongiform encephalopathies. Efforts in analyzing other proteins related to various conformational diseases are also introduced. (C) 2009 Elsevier Ltd. All rights reserved.

Authenticated Index Structures for Aggregation Queries in Outsourced Databases

In an outsourced database system the data owner publishes information through a number of remote, untrusted servers with the goal of enabling clients to access and query the data more efficiently. As clients cannot trust servers, query authentication is an essential component in any outsourced database system. Clients should be given the capability to verify that the answers provided by the servers are correct with respect to the actual data published by the owner. While existing work provides authentication techniques for selection and projection queries, there is a lack of techniques for authenticating aggregation queries. This article introduces the first known authenticated index structures for aggregation queries. First, we design an index that features good performance characteristics for static environments, where few or no updates occur to the data. Then, we extend these ideas and propose more involved structures for the dynamic case, where the database owner is allowed to update the data arbitrarily. Our structures feature excellent average case performance for authenticating queries with multiple aggregate attributes and multiple selection predicates. We also implement working prototypes of the proposed techniques and experimentally validate the correctness of our ideas.

Protein aggregation in the brain: the molecular basis for Alzheimer's and Parkinson's diseases.

Developing effective treatments for neurodegenerative diseases is one of the greatest medical challenges of the 21st century. Although many of these clinical entities have been recognized for more than a hundred years, it is only during the past twenty years that the molecular events that precipitate disease have begun to be understood. Protein aggregation is a common feature of many neurodegenerative diseases, and it is assumed that the aggregation process plays a central role in pathogenesis. In this process, one molecule (monomer) of a soluble protein interacts with other monomers of the same protein to form dimers, oligomers, and polymers. Conformation changes in three-dimensional structure of the protein, especially the formation of beta-strands, often accompany the process. Eventually, as the size of the aggregates increases, they may precipitate as insoluble amyloid fibrils, in which the structure is stabilized by the beta-strands interacting within a beta-sheet. In this review, we discuss this theme as it relates to the two most common neurodegenerative conditions-Alzheimer's and Parkinson's diseases.

Integrative analysis of chemo-transcriptomic profiles for drug-feature specific gene expression signatures

One of the major challenges in systems biology is to understand the complex responses of a biological system to external perturbations or internal signalling depending on its biological conditions. Genome-wide transcriptomic profiling of cellular systems under various chemical perturbations allows the manifestation of certain features of the chemicals through their transcriptomic expression profiles. The insights obtained may help to establish the connections between human diseases, associated genes and therapeutic drugs. The main objective of this study was to systematically analyse cellular gene expression data under various drug treatments to elucidate drug-feature specific transcriptomic signatures. We first extracted drug-related information (drug features) from the collected textual description of DrugBank entries using text-mining techniques. A novel statistical method employing orthogonal least square learning was proposed to obtain drug-feature-specific signatures by integrating gene expression with DrugBank data. To obtain robust signatures from noisy input datasets, a stringent ensemble approach was applied with the combination of three techniques: resampling, leave-one-out cross validation, and aggregation. The validation experiments showed that the proposed method has the capacity of extracting biologically meaningful drug-feature-specific gene expression signatures. It was also shown that most of signature genes are connected with common hub genes by regulatory network analysis. The common hub genes were further shown to be related to general drug metabolism by Gene Ontology analysis. Each set of genes has relatively few interactions with other sets, indicating the modular nature of each signature and its drug-feature-specificity. Based on Gene Ontology analysis, we also found that each set of drug feature (DF)-specific genes were indeed enriched in biological processes related to the drug feature. The results of these experiments demonstrated the pot- ntial of the method for predicting certain features of new drugs using their transcriptomic profiles, providing a useful methodological framework and a valuable resource for drug development and characterization.

Rank Aggregation for Pattern Classifier Selection in Remote Sensing Images

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Gaussian Multiscale Aggregation oriented to Hand Biometric Segmentation in Mobile Devices

New trends in biometrics are oriented to mobile devices in order to increase the overall security in daily actions like bank account access, e-commerce or even document protection within the mobile. However, applying biometrics to mobile devices imply challenging aspects in biometric data acquisition, feature extraction or private data storage. Concretely, this paper attempts to deal with the problem of hand segmentation given a picture of the hand in an unknown background, requiring an accurate result in terms of hand isolation. For the sake of user acceptability, no restrictions are done on background, and therefore, hand images can be taken without any constraint, resulting segmentation in an exigent task. Multiscale aggregation strategies are proposed in order to solve this problem due to their accurate results in unconstrained and complicated scenarios, together with their properties in time performance. This method is evaluated with a public synthetic database with 480000 images considering different backgrounds and illumination environments. The results obtained in terms of accuracy and time performance highlight their capability of being a suitable solution for the problem of hand segmentation in contact-less environments, outperforming competitive methods in literature like Lossy Data Compression image segmentation (LDC).

Distributed Feature Selection in Large n and Large p Regression Problems

Fitting statistical models is computationally challenging when the sample size or the dimension of the dataset is huge. An attractive approach for down-scaling the problem size is to first partition the dataset into subsets and then fit using distributed algorithms. The dataset can be partitioned either horizontally (in the sample space) or vertically (in the feature space), and the challenge arise in defining an algorithm with low communication, theoretical guarantees and excellent practical performance in general settings. For sample space partitioning, I propose a MEdian Selection Subset AGgregation Estimator ({\em message}) algorithm for solving these issues. The algorithm applies feature selection in parallel for each subset using regularized regression or Bayesian variable selection method, calculates the `median' feature inclusion index, estimates coefficients for the selected features in parallel for each subset, and then averages these estimates. The algorithm is simple, involves very minimal communication, scales efficiently in sample size, and has theoretical guarantees. I provide extensive experiments to show excellent performance in feature selection, estimation, prediction, and computation time relative to usual competitors.

While sample space partitioning is useful in handling datasets with large sample size, feature space partitioning is more effective when the data dimension is high. Existing methods for partitioning features, however, are either vulnerable to high correlations or inefficient in reducing the model dimension. In the thesis, I propose a new embarrassingly parallel framework named {\em DECO} for distributed variable selection and parameter estimation. In {\em DECO}, variables are first partitioned and allocated to m distributed workers. The decorrelated subset data within each worker are then fitted via any algorithm designed for high-dimensional problems. We show that by incorporating the decorrelation step, DECO can achieve consistent variable selection and parameter estimation on each subset with (almost) no assumptions. In addition, the convergence rate is nearly minimax optimal for both sparse and weakly sparse models and does NOT depend on the partition number m. Extensive numerical experiments are provided to illustrate the performance of the new framework.

For datasets with both large sample sizes and high dimensionality, I propose a new "divided-and-conquer" framework {\em DEME} (DECO-message) by leveraging both the {\em DECO} and the {\em message} algorithm. The new framework first partitions the dataset in the sample space into row cubes using {\em message} and then partition the feature space of the cubes using {\em DECO}. This procedure is equivalent to partitioning the original data matrix into multiple small blocks, each with a feasible size that can be stored and fitted in a computer in parallel. The results are then synthezied via the {\em DECO} and {\em message} algorithm in a reverse order to produce the final output. The whole framework is extremely scalable.

Lady Nugent and Tom Cringle on the veranda : early nineteenth century observations on a Caribbean architectural feature

This study of the veranda as seen through the eyes of Lady Maria Nugent and Michael Scott, alias Tom Cringle, clearly demonstrates the important role that the piazza, as it was then more commonly known, played in the life of early nineteenth century Caribbean colonial society. The popularity of the veranda throughout the region, in places influenced by different European as well as African cultures, and among all classes of people, suggests that the appeal of this typical feature was based on something more than architectural fashion. A place of relative comfort in hot weather, the veranda is also a space at the interface of indoors and outdoors which allows for a wide variety of uses, for solitary or small or large group activities, many of which were noted by Nugent and Scott. Quintessentially, the veranda is a place in which to relax and take pleasure, not least of which is the enjoyment of the prospect, be it a panoramic view, a peaceful garden or a lively street scene. Despite the great changes in the nature of society, in the Caribbean and in many other parts of the world, the veranda and related structures such as the balcony continue to play at least as important a role in daily life as they did two centuries ago. The veranda of today’s Californian or Australian bungalow, and the balcony of the apartment block in the residential area of the modern city are among the contemporary equivalents of the lower and upper piazzas of Lady Nugent’s and Tom Cringle’s day.