975 resultados para discovery of a similarity


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The ability to discriminate nestmates from non-nestmates in insect societies is essential to protect colonies from conspecific invaders. The acceptance threshold hypothesis predicts that organisms whose recognition systems classify recipients without errors should optimize the balance between acceptance and rejection. In this process, cuticular hydrocarbons play an important role as cues of recognition in social insects. The aims of this study were to determine whether guards exhibit a restrictive level of rejection towards chemically distinct individuals, becoming more permissive during the encounters with either nestmate or non-nestmate individuals bearing chemically similar profiles. The study demonstrates that Melipona asilvai (Hymenoptera: Apidae: Meliponini) guards exhibit a flexible system of nestmate recognition according to the degree of chemical similarity between the incoming forager and its own cuticular hydrocarbons profile. Guards became less restrictive in their acceptance rates when they encounter non-nestmates with highly similar chemical profiles, which they probably mistake for nestmates, hence broadening their acceptance level.

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Mobile devices are now capable of supporting a wide range of applications, many of which demand an ever increasing computational power. To this end, mobile cloud computing (MCC) has been proposed to address the limited computation power, memory, storage, and energy of such devices. An important challenge in MCC is to guarantee seamless discovery of services. To this end, this thesis proposes an architecture that provides user-transparent and low-latency service discovery, as well as automated service selection. Experimental results on a real cloud computing testbed demonstrated that the proposed work outperforms state of-the-art approaches by achieving extremely low discovery delay.

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With recent advances in mass spectrometry techniques, it is now possible to investigate proteins over a wide range of molecular weights in small biological specimens. This advance has generated data-analytic challenges in proteomics, similar to those created by microarray technologies in genetics, namely, discovery of "signature" protein profiles specific to each pathologic state (e.g., normal vs. cancer) or differential profiles between experimental conditions (e.g., treated by a drug of interest vs. untreated) from high-dimensional data. We propose a data analytic strategy for discovering protein biomarkers based on such high-dimensional mass-spectrometry data. A real biomarker-discovery project on prostate cancer is taken as a concrete example throughout the paper: the project aims to identify proteins in serum that distinguish cancer, benign hyperplasia, and normal states of prostate using the Surface Enhanced Laser Desorption/Ionization (SELDI) technology, a recently developed mass spectrometry technique. Our data analytic strategy takes properties of the SELDI mass-spectrometer into account: the SELDI output of a specimen contains about 48,000 (x, y) points where x is the protein mass divided by the number of charges introduced by ionization and y is the protein intensity of the corresponding mass per charge value, x, in that specimen. Given high coefficients of variation and other characteristics of protein intensity measures (y values), we reduce the measures of protein intensities to a set of binary variables that indicate peaks in the y-axis direction in the nearest neighborhoods of each mass per charge point in the x-axis direction. We then account for a shifting (measurement error) problem of the x-axis in SELDI output. After these pre-analysis processing of data, we combine the binary predictors to generate classification rules for cancer, benign hyperplasia, and normal states of prostate. Our approach is to apply the boosting algorithm to select binary predictors and construct a summary classifier. We empirically evaluate sensitivity and specificity of the resulting summary classifiers with a test dataset that is independent from the training dataset used to construct the summary classifiers. The proposed method performed nearly perfectly in distinguishing cancer and benign hyperplasia from normal. In the classification of cancer vs. benign hyperplasia, however, an appreciable proportion of the benign specimens were classified incorrectly as cancer. We discuss practical issues associated with our proposed approach to the analysis of SELDI output and its application in cancer biomarker discovery.

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Several natural products derived from entomopathogenic fungi have been shown to initiate neuronal differentiation in the rat pheochromocytoma PC12 cell line. After the successful completion of the total synthesis program, the reduction of structural complexity while retaining biological activity was targeted. In this study, farinosone C served as a lead structure and inspired the preparation of small molecules with reduced complexity, of which several were able to induce neurite outgrowth. This allowed for the elaboration of a detailed structure-activity relationship. Investigations on the mode of action utilizing a computational similarity ensemble approach suggested the involvement of the endocannabinoid system as potential target for our analogs and also led to the discovery of four potent new endocannabinoid transport inhibitors.

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Herein, we report the discovery of the first potent and selective inhibitor of TRPV6, a calcium channel overexpressed in breast and prostate cancer, and its use to test the effect of blocking TRPV6-mediated Ca2+-influx on cell growth. The inhibitor was discovered through a computational method, xLOS, a 3D-shape and pharmacophore similarity algorithm, a type of ligand-based virtual screening (LBVS) method described briefly here. Starting with a single weakly active seed molecule, two successive rounds of LBVS followed by optimization by chemical synthesis led to a selective molecule with 0.3 μM inhibition of TRPV6. The ability of xLOS to identify different scaffolds early in LBVS was essential to success. The xLOS method may be generally useful to develop tool compounds for poorly characterized targets.

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Structure-function analysis of human Integrator subunit 4 Anupama Sataluri Advisor: Eric. J. Wagner, Ph.D. Uridine-rich small nuclear RNAs (U snRNA) are RNA Polymerase-II (RNAPII) transcripts that are ubiquitously expressed and are known to be essential for gene expression. snRNAs play a key role in mRNA splicing and in histone mRNA expression. Inaccurate snRNA biosynthesis can lead to diseases related to defective splicing and histone mRNA expression. Although the 3′ end formation mechanism and processing machinery of other RNAPII transcripts such as mRNA has been well studied, the mechanism of snRNA 3′ end processing has remained a mystery until the recent discovery of the machinery that mediates this process. In 2005, a complex of 14 subunits (the Integrator complex) associated with RNA Polymerase-II was discovered. The 14subunits were annotated Integrator 1-14 based on their size. The subunits of this complex together were found to facilitate 3′ end processing of snRNA. Identification of the Integrator complex propelled research in the direction of understanding the events of snRNA 3’end processing. Recent studies from our lab confirmed that Integrator subunit (IntS) 9 and 11 together perform the endonucleolytic cleavage of the nascent snRNA 3′ end to generate mature snRNA. However, the role of other members of the Integrator complex remains elusive. Current research in our lab is focused on deciphering the role of each subunit within the Integrator complex This work specifically focuses on elucidating the role of human Integrator subunit 4 (IntS4) and understanding how it facilitates the overall function of the complex. IntS4 has structural similarity with a protein called “Symplekin”, which is part of the mRNA 3’end processing machinery. Symplekin has been thoroughly researched in recent years and structure-function correlation studies in the context of mRNA 3’end processing have reported a scaffold function for Symplekin due to the presence of HEAT repeat motifs in its N-terminus. Based upon the structural similarity between IntS4 and Symplekin, we hypothesized that Integrator subunit 4 may be behaving as a Symplekin-like scaffold molecule that facilitates the interaction between other members of the Integrator Complex. To answer this question, the two important goals of this study were to: 1) identify the region of IntS4, which is important for snRNA 3′ end processing and 2) determine binding partners of IntS4 which promote its function as a scaffold. IntS4 structurally consists of a highly conserved N-terminus with 8 HEAT repeats, followed by a nonconserved C- terminus. A series of siRNA resistant N and C-terminus deletion constructs as well as specific point mutants within its N-terminal HEAT repeats were generated for human IntS4 and, utilizing a snRNA transcriptional readthrough GFP-reporter assay, we tested their ability to rescue misprocessing. This assay revealed a possible scaffold like property of IntS4. To probe IntS4 for interaction partners, we performed co-immunoprecipitation on nuclear extracts of IntS4 expressing stable cell lines and identified IntS3 and IntS5 among other Integrator subunits to be binding partners which facilitate the scaffold like function of hIntS4. These findings have established a critical role for IntS4 in snRNA 3′ end processing, identified that both its N and C termini are essential for its function, and mapped putative interaction domains with other Integrator subunits.

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Aims of study: The goals of this paper are to summarize and to compare plant species richness and floristic similarity at two spatial scales; mesohabitat (normal, eutrophic, and oligotrophic dehesas) and dehesa habitat; and to establish guidelines for conserving species diversity in dehesas. Area of study: We considered four dehesa sites in the western Peninsular Spain, located along a climatic and biogeographic gradient from north to south. Main results: Average alpha richness for mesohabitats was 75.6 species, and average alpha richness for dehesa sites was 146.3. Gamma richness assessed for the overall dehesa habitat was 340.0 species. The species richness figures of normal dehesa mesohabitat were significantly lesser than of the eutrophic mesohabitat and lesser than the oligotrophic mesohabitat too. No significant differences were found for species richness among dehesa sites. We have found more dissimilarity at local scale (mesohabitat) than at regional scale (habitat). Finally, the results of the similarity assessment between dehesa sites reflected both climatic and biogeographic gradients. Research highlights: An effective conservation of dehesas must take into account local and regional conditions all along their distribution range for ensuring the conservation of the main vascular plant species assemblages as well as the associated fauna

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Tradicionalmente, el uso de técnicas de análisis de datos ha sido una de las principales vías para el descubrimiento de conocimiento oculto en grandes cantidades de datos, recopilados por expertos en diferentes dominios. Por otra parte, las técnicas de visualización también se han usado para mejorar y facilitar este proceso. Sin embargo, existen limitaciones serias en la obtención de conocimiento, ya que suele ser un proceso lento, tedioso y en muchas ocasiones infructífero, debido a la dificultad de las personas para comprender conjuntos de datos de grandes dimensiones. Otro gran inconveniente, pocas veces tenido en cuenta por los expertos que analizan grandes conjuntos de datos, es la degradación involuntaria a la que someten a los datos durante las tareas de análisis, previas a la obtención final de conclusiones. Por degradación quiere decirse que los datos pueden perder sus propiedades originales, y suele producirse por una reducción inapropiada de los datos, alterando así su naturaleza original y llevando en muchos casos a interpretaciones y conclusiones erróneas que podrían tener serias implicaciones. Además, este hecho adquiere una importancia trascendental cuando los datos pertenecen al dominio médico o biológico, y la vida de diferentes personas depende de esta toma final de decisiones, en algunas ocasiones llevada a cabo de forma inapropiada. Ésta es la motivación de la presente tesis, la cual propone un nuevo framework visual, llamado MedVir, que combina la potencia de técnicas avanzadas de visualización y minería de datos para tratar de dar solución a estos grandes inconvenientes existentes en el proceso de descubrimiento de información válida. El objetivo principal es hacer más fácil, comprensible, intuitivo y rápido el proceso de adquisición de conocimiento al que se enfrentan los expertos cuando trabajan con grandes conjuntos de datos en diferentes dominios. Para ello, en primer lugar, se lleva a cabo una fuerte disminución en el tamaño de los datos con el objetivo de facilitar al experto su manejo, y a la vez preservando intactas, en la medida de lo posible, sus propiedades originales. Después, se hace uso de efectivas técnicas de visualización para representar los datos obtenidos, permitiendo al experto interactuar de forma sencilla e intuitiva con los datos, llevar a cabo diferentes tareas de análisis de datos y así estimular visualmente su capacidad de comprensión. De este modo, el objetivo subyacente se basa en abstraer al experto, en la medida de lo posible, de la complejidad de sus datos originales para presentarle una versión más comprensible, que facilite y acelere la tarea final de descubrimiento de conocimiento. MedVir se ha aplicado satisfactoriamente, entre otros, al campo de la magnetoencefalografía (MEG), que consiste en la predicción en la rehabilitación de lesiones cerebrales traumáticas (Traumatic Brain Injury (TBI) rehabilitation prediction). Los resultados obtenidos demuestran la efectividad del framework a la hora de acelerar y facilitar el proceso de descubrimiento de conocimiento sobre conjuntos de datos reales. ABSTRACT Traditionally, the use of data analysis techniques has been one of the main ways of discovering knowledge hidden in large amounts of data, collected by experts in different domains. Moreover, visualization techniques have also been used to enhance and facilitate this process. However, there are serious limitations in the process of knowledge acquisition, as it is often a slow, tedious and many times fruitless process, due to the difficulty for human beings to understand large datasets. Another major drawback, rarely considered by experts that analyze large datasets, is the involuntary degradation to which they subject the data during analysis tasks, prior to obtaining the final conclusions. Degradation means that data can lose part of their original properties, and it is usually caused by improper data reduction, thereby altering their original nature and often leading to erroneous interpretations and conclusions that could have serious implications. Furthermore, this fact gains a trascendental importance when the data belong to medical or biological domain, and the lives of people depends on the final decision-making, which is sometimes conducted improperly. This is the motivation of this thesis, which proposes a new visual framework, called MedVir, which combines the power of advanced visualization techniques and data mining to try to solve these major problems existing in the process of discovery of valid information. Thus, the main objective is to facilitate and to make more understandable, intuitive and fast the process of knowledge acquisition that experts face when working with large datasets in different domains. To achieve this, first, a strong reduction in the size of the data is carried out in order to make the management of the data easier to the expert, while preserving intact, as far as possible, the original properties of the data. Then, effective visualization techniques are used to represent the obtained data, allowing the expert to interact easily and intuitively with the data, to carry out different data analysis tasks, and so visually stimulating their comprehension capacity. Therefore, the underlying objective is based on abstracting the expert, as far as possible, from the complexity of the original data to present him a more understandable version, thus facilitating and accelerating the task of knowledge discovery. MedVir has been succesfully applied to, among others, the field of magnetoencephalography (MEG), which consists in predicting the rehabilitation of Traumatic Brain Injury (TBI). The results obtained successfully demonstrate the effectiveness of the framework to accelerate and facilitate the process of knowledge discovery on real world datasets.

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We describe here a DNA polymerase family highly conserved in Euryarchaeota, a subdomain of Archaea. The DNA polymerase is composed of two proteins, DP1 and DP2. Sequence analysis showed that considerable similarity exists between DP1 and the second subunit of eukaryotic DNA polymerase δ, a protein essential for the propagation of Eukarya, and that DP2 has conserved motifs found in proteins with nucleotide-polymerizing activity. These results, together with our previous biochemical analyses of one of the members, DNA polymerase II (DP1 + DP2) from Pyrococcus furiosus, implicate the DNA polymerases of this family in the DNA replication process of Euryarchaeota. The discovery of this DNA-polymerase family, aside from providing an opportunity to enhance our knowledge of the evolution of DNA polymerases, is a significant step toward the complete understanding of DNA replication across the three domains of life.

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A computer analysis of 2328 protein sequences comprising about 60% of the Escherichia coli gene products was performed using methods for database screening with individual sequences and alignment blocks. A high fraction of E. coli proteins--86%--shows significant sequence similarity to other proteins in current databases; about 70% show conservation at least at the level of distantly related bacteria, and about 40% contain ancient conserved regions (ACRs) shared with eukaryotic or Archaeal proteins. For > 90% of the E. coli proteins, either functional information or sequence similarity, or both, are available. Forty-six percent of the E. coli proteins belong to 299 clusters of paralogs (intraspecies homologs) defined on the basis of pairwise similarity. Another 10% could be included in 70 superclusters using motif detection methods. The majority of the clusters contain only two to four members. In contrast, nearly 25% of all E. coli proteins belong to the four largest superclusters--namely, permeases, ATPases and GTPases with the conserved "Walker-type" motif, helix-turn-helix regulatory proteins, and NAD(FAD)-binding proteins. We conclude that bacterial protein sequences generally are highly conserved in evolution, with about 50% of all ACR-containing protein families represented among the E. coli gene products. With the current sequence databases and methods of their screening, computer analysis yields useful information on the functions and evolutionary relationships of the vast majority of genes in a bacterial genome. Sequence similarity with E. coli proteins allows the prediction of functions for a number of important eukaryotic genes, including several whose products are implicated in human diseases.

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We report on the discovery of a new member of the magnetar class, SGR J1935+2154, and on its timing and spectral properties measured by an extensive observational campaign carried out between 2014 July and 2015 March with Chandra and XMM–Newton (11 pointings). We discovered the spin period of SGR J1935+2154 through the detection of coherent pulsations at a period of about 3.24 s. The magnetar is slowing down at a rate of P˙=1.43(1)×10−11 s s−1 and with a decreasing trend due to a negative P¨ of −3.5(7) × 10−19 s s−2. This implies a surface dipolar magnetic field strength of ∼2.2 × 1014 G, a characteristic age of about 3.6 kyr and a spin-down luminosity Lsd ∼1.7 × 1034 erg s−1. The source spectrum is well modelled by a blackbody with temperature of about 500 eV plus a power-law component with photon index of about 2. The source showed a moderate long-term variability, with a flux decay of about 25 per cent during the first four months since its discovery, and a re-brightening of the same amount during the second four months. The X-ray data were also used to study the source environment. In particular, we discovered a diffuse emission extending on spatial scales from about 1 arcsec up to at least 1 arcmin around SGR J1935+2154 both in Chandra and XMM–Newton data. This component is constant in flux (at least within uncertainties) and its spectrum is well modelled by a power-law spectrum steeper than that of the pulsar. Though a scattering halo origin seems to be more probable we cannot exclude that part, or all, of the diffuse emission is due to a pulsar wind nebula.

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The cyclotides are a family of small disulfide rich proteins that have a cyclic peptide backbone and a cystine knot formed by three conserved disulfide bonds. The combination of these two structural motifs contributes to the exceptional chemical, thermal and enzymatic stability of the cyclotides, which retain bioactivity after boiling. They were initially discovered based on native medicine or screening studies associated with some of their various activities, which include uterotonic action, anti-HIV activity, neurotensin antagonism, and cytotoxicity. They are present in plants from the Rubiaceae, Violaceae and Cucurbitaccae families and their natural function in plants appears to be in host defense: they have potent activity against certain insect pests and they also have antimicrobial activity. There are currently around 50 published sequences of cyclotides and their rate of discovery has been increasing over recent years. Ultimately the family may comprise thousands of members. This article describes the background to the discovery of the cyclotides, their structural characterization, chemical synthesis, genetic origin, biological activities and potential applications in the pharmaceutical and agricultural industries. Their unique topological features make them interesting from a protein folding perspective. Because of their highly stable peptide framework they might make useful templates in drug design programs, and their insecticidal activity opens the possibility of applications in crop protection.

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The discovery of the Woodleigh impact structure, first identified by R. P. lasky, bears a number of parallels with that of the Chlcxulub impact structure of K-T boundary age, underpinning complications inherent in the study of buried impact structures by geophysical techniques and drilling. Questions raised in connection with the diameter of the Woodleigh impact structure reflect uncertainties in criteria used to define original crater sizes in eroded and buried impact structures as well as limits on the geological controls at Woodleigh. The truncation of the regional Ajona - Wandagee gravity ridges by the outer aureole of the Woodleigh structure, a superposed arcuate magnetic anomaly along the eastern part of the structure, seismic-reflection data indicating a central > 37 km-diameter dome, correlation of fault patterns between Woodleigh and less-deeply eroded impact structures (Ries crater, Chesapeake Bay), and morphometric estimates all indicate a final diameter of 120 km. At Woodleigh, pre-hydrothermal shock-induced melting and diaplectic transformations are heavily masked by pervasive alteration of the shocked gneisses to montmorillonite-dominated clays, accounting for the high MgO and low K2O of cryptocrystalline components. The possible contamination of sub-crater levels of the Woodlelgh impact structure by meteoritic components, suggested by high Ni, Co, Cr, Ni/ Co and Ni/Cr ratios, requires further siderophile element analyses of vein materials. Although stratigraphic age constraints on the impact event are broad (post-Middle Devonian to pre-Early Jurassic) high-temperature (200-250 degrees C) pervasive hydrothermal activity dated by K-Ar isotopes of illite - smectite indicates an age of 359 +/- 4 Ma. To date neither Late Devonian crater fill, nor impact ejecta fallout units have been identified, although metallic meteoritic ablation spherules of a similar age have been found in the Conning Basin.

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Cyclotides are mini-proteins of 28-37 amino acid residues that have the unusual feature of a head-to-tail cyclic backbone surrounding a cystine knot. This molecular architecture gives the cyclotides heightened resistance to thermal, chemical and enzymatic degradation and has prompted investigations into their use as scaffolds in peptide therapeutics. There are now more than 80 reported cyclotide sequences from plants in the families Rubiaceae, Violaceae and Cucurbitaceae, with a wide variety of biological activities observed. However, potentially limiting the development of cyclotide-based therapeutics is a lack of understanding of the mechanism by which these peptides are cyclized in vivo. Until now, no linear versions of cyclotides have been reported, limiting our understanding of the cyclization mechanism. This study reports the discovery of a naturally occurring linear cyclotide, violacin A, from the plant Viola odorata and discusses the implications for in vivo cyclization of peptides. The elucidation of the cDNA clone of violacin A revealed a point mutation that introduces a stop codon, which inhibits the translation of a key Asn residue that is thought to be required for cyclization. The three-dimensional solution structure of violacin A was determined and found to adopt the cystine knot fold of native cyclotides. Enzymatic stability assays on violacin A indicate that despite an increase in the flexibility of the structure relative to cyclic counterparts, the cystine knot preserves the overall stability of the molecule. (c) 2006 Elsevier Ltd. All rights reserved.

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Humans play a role in deciding the fate of species in the current extinction wave. Because of the previous Similarity Principle, physical attractiveness and likeability, it has been argued that public choice favours the survival of species that satisfy these criteria at the expense of other species. This paper empirically tests this argument by considering a hypothetical ‘Ark’ situation. Surveys of 204 members of the Australian public inquired whether they are in favour of the survival of each of 24 native mammal, bird and reptile species (prior to and after information provision about each species). The species were ranked by percentage of ‘yes’ votes received. Species composition by taxon in various fractions of the ranking was determined. If the previous Similarity Principle holds, mammals should rank highly and dominate the top fractions of animals saved in the hierarchical list. We find that although mammals would be over-represented in the ‘Ark’, birds and reptiles are unlikely to be excluded when social choice is based on numbers ‘voting’ for the survival of each species. Support for the previous Similarity Principle is apparent particularly after information provision. Public policy implications of this are noted and recommendations are given.