916 resultados para Functions of complex variables.
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Complex networks have been employed to model many real systems and as a modeling tool in a myriad of applications. In this paper, we use the framework of complex networks to the problem of supervised classification in the word disambiguation task, which consists in deriving a function from the supervised (or labeled) training data of ambiguous words. Traditional supervised data classification takes into account only topological or physical features of the input data. On the other hand, the human (animal) brain performs both low- and high-level orders of learning and it has facility to identify patterns according to the semantic meaning of the input data. In this paper, we apply a hybrid technique which encompasses both types of learning in the field of word sense disambiguation and show that the high-level order of learning can really improve the accuracy rate of the model. This evidence serves to demonstrate that the internal structures formed by the words do present patterns that, generally, cannot be correctly unveiled by only traditional techniques. Finally, we exhibit the behavior of the model for different weights of the low- and high-level classifiers by plotting decision boundaries. This study helps one to better understand the effectiveness of the model. Copyright (C) EPLA, 2012
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Categorical data cannot be interpolated directly because they are outcomes of discrete random variables. Thus, types of categorical variables are transformed into indicator functions that can be handled by interpolation methods. Interpolated indicator values are then backtransformed to the original types of categorical variables. However, aspects such as variability and uncertainty of interpolated values of categorical data have never been considered. In this paper we show that the interpolation variance can be used to map an uncertainty zone around boundaries between types of categorical variables. Moreover, it is shown that the interpolation variance is a component of the total variance of the categorical variables, as measured by the coefficient of unalikeability. (C) 2011 Elsevier Ltd. All rights reserved.
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The classification of texts has become a major endeavor with so much electronic material available, for it is an essential task in several applications, including search engines and information retrieval. There are different ways to define similarity for grouping similar texts into clusters, as the concept of similarity may depend on the purpose of the task. For instance, in topic extraction similar texts mean those within the same semantic field, whereas in author recognition stylistic features should be considered. In this study, we introduce ways to classify texts employing concepts of complex networks, which may be able to capture syntactic, semantic and even pragmatic features. The interplay between various metrics of the complex networks is analyzed with three applications, namely identification of machine translation (MT) systems, evaluation of quality of machine translated texts and authorship recognition. We shall show that topological features of the networks representing texts can enhance the ability to identify MT systems in particular cases. For evaluating the quality of MT texts, on the other hand, high correlation was obtained with methods capable of capturing the semantics. This was expected because the golden standards used are themselves based on word co-occurrence. Notwithstanding, the Katz similarity, which involves semantic and structure in the comparison of texts, achieved the highest correlation with the NIST measurement, indicating that in some cases the combination of both approaches can improve the ability to quantify quality in MT. In authorship recognition, again the topological features were relevant in some contexts, though for the books and authors analyzed good results were obtained with semantic features as well. Because hybrid approaches encompassing semantic and topological features have not been extensively used, we believe that the methodology proposed here may be useful to enhance text classification considerably, as it combines well-established strategies. (c) 2012 Elsevier B.V. All rights reserved.
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We study the spectral functions, and in particular the zeta function, associated to a class of sequences of complex numbers, called of spectral type. We investigate the decomposability of the zeta function associated to a double sequence with respect to some simple sequence, and we provide a technique for obtaining the first terms in the Laurent expansion at zero of the zeta function associated to a double sequence.
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The weakening mechanisms involved in the collapse of complex impact craters are controversial. The Araguainha impact crater, in Brazil, exposes a complex structure of 40 km in diameter, and is an excellent object to address this issue. Its core is dominated by granite. In addition to microstructural observations, magnetic studies reveal its internal fabric acquired during the collapse phase. All granite samples exhibit impact-related planar deformation features (PDFs) and planar fractures (PFs), which were overprinted by cataclasis. Cataclastic deformation has evolved from incipient brittle fracturing to the development of discrete shear bands in the center of the structure. Fracture planes are systematically decorated by tiny grains (<10 mu m) of magnetite and hematite, and the orientation of magnetic lineation and magnetic foliation obtained by the anisotropies of magnetic susceptibility (AMS) and anhysteretic remanence (AAR) are perfectly coaxial in all studied sites. Therefore, we could track the orientation of deformation features which are decorated by iron oxides using the AMS and AAR. The magnetic fabrics show a regular pattern at the borders of the central peak, with orientations consistent with the fabric of sediments at the crater's inner collar and complex in the center of the structure. Both the cataclastic flow revealed from microstructural observations and the structural pattern of the magnetic anisotropy match the predictions from numerical models of complex impact structures. The widespread occurrence of cataclasis in the central peak, and its orientations revealed by magnetic studies indicate that acoustic fluidization likely operates at all scales, including the mineral scales. The cataclastic flow made possible by acoustic fluidization results in an apparent plastic deformation at the macroscopic scale in the core. (C) 2012 Elsevier B.V. All rights reserved.
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A neural network model to predict ozone concentration in the Sao Paulo Metropolitan Area was developed, based on average values of meteorological variables in the morning (8:00-12:00 hr) and afternoon (13:00-17: 00 hr) periods. Outputs are the maximum and average ozone concentrations in the afternoon (12:00-17:00 hr). The correlation coefficient between computed and measured values was 0.82 and 0.88 for the maximum and average ozone concentration, respectively. The model presented good performance as a prediction tool for the maximum ozone concentration. For prediction periods from 1 to 5 days 0 to 23% failures (95% confidence) were obtained.
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Background: The hypothalamus plays a pivotal role in numerous mechanisms highly relevant to the maintenance of body homeostasis, such as the control of food intake and energy expenditure. Impairment of these mechanisms has been associated with the metabolic disturbances involved in the pathogenesis of obesity. Since rodent species constitute important models for metabolism studies and the rat hypothalamus is poorly characterized by proteomic strategies, we performed experiments aimed at constructing a two-dimensional gel electrophoresis (2-DE) profile of rat hypothalamus proteins. Results: As a first step, we established the best conditions for tissue collection and protein extraction, quantification and separation. The extraction buffer composition selected for proteome characterization of rat hypothalamus was urea 7 M, thiourea 2 M, CHAPS 4%, Triton X-100 0.5%, followed by a precipitation step with chloroform/methanol. Two-dimensional (2-D) gels of hypothalamic extracts from four-month-old rats were analyzed; the protein spots were digested and identified by using tandem mass spectrometry and database query using the protein search engine MASCOT. Eighty-six hypothalamic proteins were identified, the majority of which were classified as participating in metabolic processes, consistent with the finding of a large number of proteins with catalytic activity. Genes encoding proteins identified in this study have been related to obesity development. Conclusion: The present results indicate that the 2-DE technique will be useful for nutritional studies focusing on hypothalamic proteins. The data presented herein will serve as a reference database for studies testing the effects of dietary manipulations on hypothalamic proteome. We trust that these experiments will lead to important knowledge on protein targets of nutritional variables potentially able to affect the complex central nervous system control of energy homeostasis.
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Background The genetic mechanisms underlying interindividual blood pressure variation reflect the complex interplay of both genetic and environmental variables. The current standard statistical methods for detecting genes involved in the regulation mechanisms of complex traits are based on univariate analysis. Few studies have focused on the search for and understanding of quantitative trait loci responsible for gene × environmental interactions or multiple trait analysis. Composite interval mapping has been extended to multiple traits and may be an interesting approach to such a problem. Methods We used multiple-trait analysis for quantitative trait locus mapping of loci having different effects on systolic blood pressure with NaCl exposure. Animals studied were 188 rats, the progenies of an F2 rat intercross between the hypertensive and normotensive strain, genotyped in 179 polymorphic markers across the rat genome. To accommodate the correlational structure from measurements taken in the same animals, we applied univariate and multivariate strategies for analyzing the data. Results We detected a new quantitative train locus on a region close to marker R589 in chromosome 5 of the rat genome, not previously identified through serial analysis of individual traits. In addition, we were able to justify analytically the parametric restrictions in terms of regression coefficients responsible for the gain in precision with the adopted analytical approach. Conclusion Future work should focus on fine mapping and the identification of the causative variant responsible for this quantitative trait locus signal. The multivariable strategy might be valuable in the study of genetic determinants of interindividual variation of antihypertensive drug effectiveness.
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Abstract Background The CHD7 (Chromodomain Helicase DNA binding protein 7) gene encodes a member of the chromodomain family of ATP-dependent chromatin remodeling enzymes. Mutations in the CHD7 gene are found in individuals with CHARGE, a syndrome characterized by multiple birth malformations in several tissues. CHD7 was identified as a binding partner of PBAF complex (Polybromo and BRG Associated Factor containing complex) playing a central role in the transcriptional reprogramming process associated to the formation of multipotent migratory neural crest, a transient cell population associated with the genesis of various tissues. CHD7 is a large gene containing 38 annotated exons and spanning 200 kb of genomic sequence. Although genes containing such number of exons are expected to have several alternative transcripts, there are very few evidences of alternative transcripts associated to CHD7 to date indicating that alternative splicing associated to this gene is poorly characterized. Findings Here, we report the cloning and characterization by experimental and computational studies of a novel alternative transcript of the human CHD7 (named CHD7 CRA_e), which lacks most of its coding exons. We confirmed by overexpression of CHD7 CRA_e alternative transcript that it is translated into a protein isoform lacking most of the domains displayed by the canonical isoform. Expression of the CHD7 CRA_e transcript was detected in normal liver, in addition to the DU145 human prostate carcinoma cell line from which it was originally isolated. Conclusions Our findings indicate that the splicing event associated to the CHD7 CRA_e alternative transcript is functional. The characterization of the CHD7 CRA_e novel isoform presented here not only sets the basis for more detailed functional studies of this isoform, but, also, contributes to the alternative splicing annotation of the CHD7 gene and the design of future functional studies aimed at the elucidation of the molecular functions of its gene products.
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Background: Aging is associated with complex and constant remodeling of the immune function, resulting in an increasing susceptibility to infection and others diseases. The infections caused by Gram-negative microorganisms, present in nursing homes and hospitals, constitute one of the most common infections in the elderly, and are mainly combated by innate immune cells. Although the functions of innate immunity seem more preserved during aging than of adaptive immune mechanisms, two systems operate in an integrated way in the body, so that injury in one part of the immune system inevitably affects the other as they are part of a defensive network. The aim of this study was to investigate the in vitro production of proinflammatory (TNF-α, IL-6, IL-1α, CXCL-8 and MCP-1) and antiinflammatory (TGF-α and IL-10) cytokines by monocytes, stimulated or not (basal) with lipopolysaccharide, from healthy young and elderly subjects. By means of PBMCs, we also studied if cytokine profile is altered in these different patient groups, in the presence of lymphocytes, under the same experimental conditions. Results: The monocytes from elderly presented higher basal production of TNF-α, MCP-1 and lower of TGF-α than young monocytes. PBMC showed similar cytokines production, irrespective age or stimulation presence. In the presence of lymphocytes, the spontaneous production of IL-10 was higher and of TGF-α was lower than monocytes, regardless of age. After LPS-stimulation, the presence of lymphocytes resulted in increased IL-6, IL-1α, MCP-1 and IL-10 and decreased CXCL-8 and TGF-α in comparison to pure culture of monocytes from young patients. With age, the same differences were observed, except for CXCL-8 and TGF-α which production was the same between monocytes and PBMC stimulated with LPS.
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The reinforcement omission effect (ROE) has been attributed to both motivational and attentional consequences of surprising reinforcement omission. Recent evidence suggests that the basolateral complex of the amygdala is involved in motivational components related to reinforcement value, whereas the central nucleus of the amygdala is involved in the processing of the attentional consequences of surprise. This study was designed to verify whether the mechanisms involved in the ROE depend on the integrity of either the basolateral amygdala complex or central nucleus of the amygdala. The ROE was evaluated in rats with lesions of either the central nucleus or basolateral complex of the amygdala and trained on a fixed-interval schedule procedure (Experiment 1) and fixed-interval with limited hold signaled schedule procedure (Experiment 2). The results of Experiment 1 showed that sham-operated rats and rats with lesions of either the central nucleus or basolateral area displayed the ROE. In contrast, in Experiment 2, subjects with lesions of the central nucleus or basolateral complex of the amygdala exhibited a smaller ROE compared with sham-operated subjects. Thus, the effects of selective lesions of amygdala subregions on the ROE in rats depended on the training procedure. Furthermore, the absence of differences between the lesioned groups in either experiment did not allow the dissociation of attentional or motivational components of the ROE with functions of specific areas of the amygdala. Thus, results did not show a functional double-dissociation between the central nucleus and basolateral area in the ROE.
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Galaxy clusters occupy a special position in the cosmic hierarchy as they are the largest bound structures in the Universe. There is now general agreement on a hierarchical picture for the formation of cosmic structures, in which galaxy clusters are supposed to form by accretion of matter and merging between smaller units. During merger events, shocks are driven by the gravity of the dark matter in the diffuse barionic component, which is heated up to the observed temperature. Radio and hard-X ray observations have discovered non-thermal components mixed with the thermal Intra Cluster Medium (ICM) and this is of great importance as it calls for a “revision” of the physics of the ICM. The bulk of present information comes from the radio observations which discovered an increasing number of Mpcsized emissions from the ICM, Radio Halos (at the cluster center) and Radio Relics (at the cluster periphery). These sources are due to synchrotron emission from ultra relativistic electrons diffusing through µG turbulent magnetic fields. Radio Halos are the most spectacular evidence of non-thermal components in the ICM and understanding the origin and evolution of these sources represents one of the most challenging goal of the theory of the ICM. Cluster mergers are the most energetic events in the Universe and a fraction of the energy dissipated during these mergers could be channelled into the amplification of the magnetic fields and into the acceleration of high energy particles via shocks and turbulence driven by these mergers. Present observations of Radio Halos (and possibly of hard X-rays) can be best interpreted in terms of the reacceleration scenario in which MHD turbulence injected during these cluster mergers re-accelerates high energy particles in the ICM. The physics involved in this scenario is very complex and model details are difficult to test, however this model clearly predicts some simple properties of Radio Halos (and resulting IC emission in the hard X-ray band) which are almost independent of the details of the adopted physics. In particular in the re-acceleration scenario MHD turbulence is injected and dissipated during cluster mergers and thus Radio Halos (and also the resulting hard X-ray IC emission) should be transient phenomena (with a typical lifetime <» 1 Gyr) associated with dynamically disturbed clusters. The physics of the re-acceleration scenario should produce an unavoidable cut-off in the spectrum of the re-accelerated electrons, which is due to the balance between turbulent acceleration and radiative losses. The energy at which this cut-off occurs, and thus the maximum frequency at which synchrotron radiation is produced, depends essentially on the efficiency of the acceleration mechanism so that observations at high frequencies are expected to catch only the most efficient phenomena while, in principle, low frequency radio surveys may found these phenomena much common in the Universe. These basic properties should leave an important imprint in the statistical properties of Radio Halos (and of non-thermal phenomena in general) which, however, have not been addressed yet by present modellings. The main focus of this PhD thesis is to calculate, for the first time, the expected statistics of Radio Halos in the context of the re-acceleration scenario. In particular, we shall address the following main questions: • Is it possible to model “self-consistently” the evolution of these sources together with that of the parent clusters? • How the occurrence of Radio Halos is expected to change with cluster mass and to evolve with redshift? How the efficiency to catch Radio Halos in galaxy clusters changes with the observing radio frequency? • How many Radio Halos are expected to form in the Universe? At which redshift is expected the bulk of these sources? • Is it possible to reproduce in the re-acceleration scenario the observed occurrence and number of Radio Halos in the Universe and the observed correlations between thermal and non-thermal properties of galaxy clusters? • Is it possible to constrain the magnetic field intensity and profile in galaxy clusters and the energetic of turbulence in the ICM from the comparison between model expectations and observations? Several astrophysical ingredients are necessary to model the evolution and statistical properties of Radio Halos in the context of re-acceleration model and to address the points given above. For these reason we deserve some space in this PhD thesis to review the important aspects of the physics of the ICM which are of interest to catch our goals. In Chapt. 1 we discuss the physics of galaxy clusters, and in particular, the clusters formation process; in Chapt. 2 we review the main observational properties of non-thermal components in the ICM; and in Chapt. 3 we focus on the physics of magnetic field and of particle acceleration in galaxy clusters. As a relevant application, the theory of Alfv´enic particle acceleration is applied in Chapt. 4 where we report the most important results from calculations we have done in the framework of the re-acceleration scenario. In this Chapter we show that a fraction of the energy of fluid turbulence driven in the ICM by the cluster mergers can be channelled into the injection of Alfv´en waves at small scales and that these waves can efficiently re-accelerate particles and trigger Radio Halos and hard X-ray emission. The main part of this PhD work, the calculation of the statistical properties of Radio Halos and non-thermal phenomena as expected in the context of the re-acceleration model and their comparison with observations, is presented in Chapts.5, 6, 7 and 8. In Chapt.5 we present a first approach to semi-analytical calculations of statistical properties of giant Radio Halos. The main goal of this Chapter is to model cluster formation, the injection of turbulence in the ICM and the resulting particle acceleration process. We adopt the semi–analytic extended Press & Schechter (PS) theory to follow the formation of a large synthetic population of galaxy clusters and assume that during a merger a fraction of the PdV work done by the infalling subclusters in passing through the most massive one is injected in the form of magnetosonic waves. Then the processes of stochastic acceleration of the relativistic electrons by these waves and the properties of the ensuing synchrotron (Radio Halos) and inverse Compton (IC, hard X-ray) emission of merging clusters are computed under the assumption of a constant rms average magnetic field strength in emitting volume. The main finding of these calculations is that giant Radio Halos are naturally expected only in the more massive clusters, and that the expected fraction of clusters with Radio Halos is consistent with the observed one. In Chapt. 6 we extend the previous calculations by including a scaling of the magnetic field strength with cluster mass. The inclusion of this scaling allows us to derive the expected correlations between the synchrotron radio power of Radio Halos and the X-ray properties (T, LX) and mass of the hosting clusters. For the first time, we show that these correlations, calculated in the context of the re-acceleration model, are consistent with the observed ones for typical µG strengths of the average B intensity in massive clusters. The calculations presented in this Chapter allow us to derive the evolution of the probability to form Radio Halos as a function of the cluster mass and redshift. The most relevant finding presented in this Chapter is that the luminosity functions of giant Radio Halos at 1.4 GHz are expected to peak around a radio power » 1024 W/Hz and to flatten (or cut-off) at lower radio powers because of the decrease of the electron re-acceleration efficiency in smaller galaxy clusters. In Chapt. 6 we also derive the expected number counts of Radio Halos and compare them with available observations: we claim that » 100 Radio Halos in the Universe can be observed at 1.4 GHz with deep surveys, while more than 1000 Radio Halos are expected to be discovered in the next future by LOFAR at 150 MHz. This is the first (and so far unique) model expectation for the number counts of Radio Halos at lower frequency and allows to design future radio surveys. Based on the results of Chapt. 6, in Chapt.7 we present a work in progress on a “revision” of the occurrence of Radio Halos. We combine past results from the NVSS radio survey (z » 0.05 − 0.2) with our ongoing GMRT Radio Halos Pointed Observations of 50 X-ray luminous galaxy clusters (at z » 0.2−0.4) and discuss the possibility to test our model expectations with the number counts of Radio Halos at z » 0.05 − 0.4. The most relevant limitation in the calculations presented in Chapt. 5 and 6 is the assumption of an “averaged” size of Radio Halos independently of their radio luminosity and of the mass of the parent clusters. This assumption cannot be released in the context of the PS formalism used to describe the formation process of clusters, while a more detailed analysis of the physics of cluster mergers and of the injection process of turbulence in the ICM would require an approach based on numerical (possible MHD) simulations of a very large volume of the Universe which is however well beyond the aim of this PhD thesis. On the other hand, in Chapt.8 we report our discovery of novel correlations between the size (RH) of Radio Halos and their radio power and between RH and the cluster mass within the Radio Halo region, MH. In particular this last “geometrical” MH − RH correlation allows us to “observationally” overcome the limitation of the “average” size of Radio Halos. Thus in this Chapter, by making use of this “geometrical” correlation and of a simplified form of the re-acceleration model based on the results of Chapt. 5 and 6 we are able to discuss expected correlations between the synchrotron power and the thermal cluster quantities relative to the radio emitting region. This is a new powerful tool of investigation and we show that all the observed correlations (PR − RH, PR − MH, PR − T, PR − LX, . . . ) now become well understood in the context of the re-acceleration model. In addition, we find that observationally the size of Radio Halos scales non-linearly with the virial radius of the parent cluster, and this immediately means that the fraction of the cluster volume which is radio emitting increases with cluster mass and thus that the non-thermal component in clusters is not self-similar.
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Transcription is controlled by promoter-selective transcriptional factors (TFs), which bind to cis-regulatory enhancers elements, termed hormone response elements (HREs), in a specific subset of genes. Regulation by these factors involves either the recruitment of coactivators or corepressors and direct interaction with the basal transcriptional machinery (1). Hormone-activated nuclear receptors (NRs) are well characterized transcriptional factors (2) that bind to the promoters of their target genes and recruit primary and secondary coactivator proteins which possess many enzymatic activities required for gene expression (1,3,4). In the present study, using single-cell high-resolution fluorescent microscopy and high throughput microscopy (HTM) coupled to computational imaging analysis, we investigated transcriptional regulation controlled by the estrogen receptor alpha (ERalpha), in terms of large scale chromatin remodeling and interaction with the associated coactivator SRC-3 (Steroid Receptor Coactivator-3), a member of p160 family (28) primary coactivators. ERalpha is a steroid-dependent transcriptional factor (16) that belongs to the NRs superfamily (2,3) and, in response to the hormone 17-ß estradiol (E2), regulates transcription of distinct target genes involved in development, puberty, and homeostasis (8,16). ERalpha spends most of its lifetime in the nucleus and undergoes a rapid (within minutes) intranuclear redistribution following the addition of either agonist or antagonist (17,18,19). We designed a HeLa cell line (PRL-HeLa), engineered with a chromosomeintegrated reporter gene array (PRL-array) containing multicopy hormone response-binding elements for ERalpha that are derived from the physiological enhancer/promoter region of the prolactin gene. Following GFP-ER transfection of PRL-HeLa cells, we were able to observe in situ ligand dependent (i) recruitment to the array of the receptor and associated coregulators, (ii) chromatin remodeling, and (iii) direct transcriptional readout of the reporter gene. Addition of E2 causes a visible opening (decondensation) of the PRL-array, colocalization of RNA Polymerase II, and transcriptional readout of the reporter gene, detected by mRNA FISH. On the contrary, when cells were treated with an ERalpha antagonist (Tamoxifen or ICI), a dramatic condensation of the PRL-array was observed, displacement of RNA Polymerase II, and complete decreasing in the transcriptional FISH signal. All p160 family coactivators (28) colocalize with ERalpha at the PRL-array. Steroid Receptor Coactivator-3 (SRC-3/AIB1/ACTR/pCIP/RAC3/TRAM1) is a p160 family member and a known oncogenic protein (4,34). SRC-3 is regulated by a variety of posttranslational modifications, including methylation, phosphorylation, acetylation, ubiquitination and sumoylation (4,35). These events have been shown to be important for its interaction with other coactivator proteins and NRs and for its oncogenic potential (37,39). A number of extracellular signaling molecules, like steroid hormones, growth factors and cytokines, induce SRC-3 phosphorylation (40). These actions are mediated by a wide range of kinases, including extracellular-regulated kinase 1 and 2 (ERK1-2), c-Jun N-terminal kinase, p38 MAPK, and IkB kinases (IKKs) (41,42,43). Here, we report SRC-3 to be a nucleocytoplasmic shuttling protein, whose cellular localization is regulated by phosphorylation and interaction with ERalpha. Using a combination of high throughput and fluorescence microscopy, we show that both chemical inhibition (with U0126) and siRNA downregulation of the MAP/ERK1/2 kinase (MEK1/2) pathway induce a cytoplasmic shift in SRC-3 localization, whereas stimulation by EGF signaling enhances its nuclear localization by inducing phosphorylation at T24, S857, and S860, known partecipants in the regulation of SRC-3 activity (39). Accordingly, the cytoplasmic localization of a non-phosphorylatable SRC-3 mutant further supports these results. In the presence of ERalpha, U0126 also dramatically reduces: hormone-dependent colocalization of ERalpha and SRC-3 in the nucleus; formation of ER-SRC-3 coimmunoprecipitation complex in cell lysates; localization of SRC-3 at the ER-targeted prolactin promoter array (PRL-array) and transcriptional activity. Finally, we show that SRC-3 can also function as a cotransporter, facilitating the nuclear-cytoplasmic shuttling of estrogen receptor. While a wealth of studies have revealed the molecular functions of NRs and coregulators, there is a paucity of data on how these functions are spatiotemporally organized in the cellular context. Technically and conceptually, our findings have a new impact upon evaluating gene transcriptional control and mechanisms of action of gene regulators.
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Introduction. Postnatal neurogenesis in the hippocampal dentate gyrus, can be modulated by numerous determinants, such as hormones, transmitters and stress. Among the factors positively interfering with neurogenesis, the complexity of the environment appears to play a particularly striking role. Adult mice reared in an enriched environment produce more neurons and exhibit better performance in hippocampus-specific learning tasks. While the effects of complex environments on hippocampal neurogenesis are well documented, there is a lack of information on the effects of living under socio-sensory deprivation conditions. Due to the immaturity of rats and mice at birth, studies dealing with the effects of environmental enrichment on hippocampal neurogenesis were carried out in adult animals, i.e. during a period of relatively low rate of neurogenesis. The impact of environment is likely to be more dramatic during the first postnatal weeks, because at this time granule cell production is remarkably higher than at later phases of development. The aim of the present research was to clarify whether and to what extent isolated or enriched rearing conditions affect hippocampal neurogenesis during the early postnatal period, a time window characterized by a high rate of precursor proliferation and to elucidate the mechanisms underlying these effects. The experimental model chosen for this research was the guinea pig, a precocious rodent, which, at 4-5 days of age can be independent from maternal care. Experimental design. Animals were assigned to a standard (control), an isolated, or an enriched environment a few days after birth (P5-P6). On P14-P17 animals received one daily bromodeoxyuridine (BrdU) injection, to label dividing cells, and were sacrificed either on P18, to evaluate cell proliferation or on P45, to evaluate cell survival and differentiation. Methods. Brain sections were processed for BrdU immunhistochemistry, to quantify the new born and surviving cells. The phenotype of the surviving cells was examined by means of confocal microscopy and immunofluorescent double-labeling for BrdU and either a marker of neurons (NeuN) or a marker of astrocytes (GFAP). Apoptotic cell death was examined with the TUNEL method. Serial sections were processed for immunohistochemistry for i) vimentin, a marker of radial glial cells, ii) BDNF (brain-derived neurotrofic factor), a neurotrophin involved in neuron proliferation/survival, iii) PSA-NCAM (the polysialylated form of the neural cell adhesion molecule), a molecule associated with neuronal migration. Total granule cell number in the dentate gyrus was evaluated by stereological methods, in Nissl-stained sections. Results. Effects of isolation. In P18 isolated animals we found a reduced cell proliferation (-35%) compared to controls and a lower expression of BDNF. Though in absolute terms P45 isolated animals had less surviving cells than controls, they showed no differences in survival rate and phenotype percent distribution compared to controls. Evaluation of the absolute number of surviving cells of each phenotype showed that isolated animals had a reduced number of cells with neuronal phenotype than controls. Looking at the location of the new neurons, we found that while in control animals 76% of them had migrated to the granule cell layer, in isolated animals only 55% of the new neurons had reached this layer. Examination of radial glia cells of P18 and P45 animals by vimentin immunohistochemistry showed that in isolated animals radial glia cells were reduced in density and had less and shorter processes. Granule cell count revealed that isolated animals had less granule cells than controls (-32% at P18 and -42% at P45). Effects of enrichment. In P18 enriched animals there was an increase in cell proliferation (+26%) compared to controls and a higher expression of BDNF. Though in both groups there was a decline in the number of BrdU-positive cells by P45, enriched animals had more surviving cells (+63) and a higher survival rate than controls. No differences were found between control and enriched animals in phenotype percent distribution. Evaluation of the absolute number of cells of each phenotype showed that enriched animals had a larger number of cells of each phenotype than controls. Looking at the location of cells of each phenotype we found that enriched animals had more new neurons in the granule cell layer and more astrocytes and cells with undetermined phenotype in the hilus. Enriched animals had a higher expression of PSA-NCAM in the granule cell layer and hilus Vimentin immunohistochemistry showed that in enriched animals radial glia cells were more numerous and had more processes.. Granule cell count revealed that enriched animals had more granule cells than controls (+37% at P18 and +31% at P45). Discussion. Results show that isolation rearing reduces hippocampal cell proliferation but does not affect cell survival, while enriched rearing increases both cell proliferation and cell survival. Changes in the expression of BDNF are likely to contribute to he effects of environment on precursor cell proliferation. The reduction and increase in final number of granule neurons in isolated and enriched animals, respectively, are attributable to the effects of environment on cell proliferation and survival and not to changes in the differentiation program. As radial glia cells play a pivotal role in neuron guidance to the granule cell layer, the reduced number of radial glia cells in isolated animals and the increased number in enriched animals suggests that the size of radial glia population may change dynamically, in order to match changes in neuron production. The high PSA-NCAM expression in enriched animals may concur to favor the survival of the new neurons by facilitating their migration to the granule cell layer. Conclusions. By using a precocious rodent we could demonstrate that isolated/enriched rearing conditions, at a time window during which intense granule cell proliferation takes place, lead to a notable decrease/increase of total granule cell number. The time-course and magnitude of postnatal granule cell production in guinea pigs are more similar to the human and non-human primate condition than in rats and mice. Translation of current data to humans would imply that exposure of children to environments poor/rich of stimuli may have a notably large impact on dentate neurogenesis and, very likely, on hippocampus dependent memory functions.
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The vast majority of known proteins have not yet been experimentally characterized and little is known about their function. The design and implementation of computational tools can provide insight into the function of proteins based on their sequence, their structure, their evolutionary history and their association with other proteins. Knowledge of the three-dimensional (3D) structure of a protein can lead to a deep understanding of its mode of action and interaction, but currently the structures of <1% of sequences have been experimentally solved. For this reason, it became urgent to develop new methods that are able to computationally extract relevant information from protein sequence and structure. The starting point of my work has been the study of the properties of contacts between protein residues, since they constrain protein folding and characterize different protein structures. Prediction of residue contacts in proteins is an interesting problem whose solution may be useful in protein folding recognition and de novo design. The prediction of these contacts requires the study of the protein inter-residue distances related to the specific type of amino acid pair that are encoded in the so-called contact map. An interesting new way of analyzing those structures came out when network studies were introduced, with pivotal papers demonstrating that protein contact networks also exhibit small-world behavior. In order to highlight constraints for the prediction of protein contact maps and for applications in the field of protein structure prediction and/or reconstruction from experimentally determined contact maps, I studied to which extent the characteristic path length and clustering coefficient of the protein contacts network are values that reveal characteristic features of protein contact maps. Provided that residue contacts are known for a protein sequence, the major features of its 3D structure could be deduced by combining this knowledge with correctly predicted motifs of secondary structure. In the second part of my work I focused on a particular protein structural motif, the coiled-coil, known to mediate a variety of fundamental biological interactions. Coiled-coils are found in a variety of structural forms and in a wide range of proteins including, for example, small units such as leucine zippers that drive the dimerization of many transcription factors or more complex structures such as the family of viral proteins responsible for virus-host membrane fusion. The coiled-coil structural motif is estimated to account for 5-10% of the protein sequences in the various genomes. Given their biological importance, in my work I introduced a Hidden Markov Model (HMM) that exploits the evolutionary information derived from multiple sequence alignments, to predict coiled-coil regions and to discriminate coiled-coil sequences. The results indicate that the new HMM outperforms all the existing programs and can be adopted for the coiled-coil prediction and for large-scale genome annotation. Genome annotation is a key issue in modern computational biology, being the starting point towards the understanding of the complex processes involved in biological networks. The rapid growth in the number of protein sequences and structures available poses new fundamental problems that still deserve an interpretation. Nevertheless, these data are at the basis of the design of new strategies for tackling problems such as the prediction of protein structure and function. Experimental determination of the functions of all these proteins would be a hugely time-consuming and costly task and, in most instances, has not been carried out. As an example, currently, approximately only 20% of annotated proteins in the Homo sapiens genome have been experimentally characterized. A commonly adopted procedure for annotating protein sequences relies on the "inheritance through homology" based on the notion that similar sequences share similar functions and structures. This procedure consists in the assignment of sequences to a specific group of functionally related sequences which had been grouped through clustering techniques. The clustering procedure is based on suitable similarity rules, since predicting protein structure and function from sequence largely depends on the value of sequence identity. However, additional levels of complexity are due to multi-domain proteins, to proteins that share common domains but that do not necessarily share the same function, to the finding that different combinations of shared domains can lead to different biological roles. In the last part of this study I developed and validate a system that contributes to sequence annotation by taking advantage of a validated transfer through inheritance procedure of the molecular functions and of the structural templates. After a cross-genome comparison with the BLAST program, clusters were built on the basis of two stringent constraints on sequence identity and coverage of the alignment. The adopted measure explicity answers to the problem of multi-domain proteins annotation and allows a fine grain division of the whole set of proteomes used, that ensures cluster homogeneity in terms of sequence length. A high level of coverage of structure templates on the length of protein sequences within clusters ensures that multi-domain proteins when present can be templates for sequences of similar length. This annotation procedure includes the possibility of reliably transferring statistically validated functions and structures to sequences considering information available in the present data bases of molecular functions and structures.