Effect of recombinant human erythropoietin expressions of apoptosis genes in rats following traumatic brain injury

Purpose: To explore the effect of recombinant human erythropoietin (r-HuEPO) on apoptosis in rats after traumatic brain injury. Methods: A total of 48 traumatic brain-injured Sprague Dawley (SD) rats were obtained by improved Feeney’s traumatic brain injury model, and were randomly divided into four groups: normal salinetreated rats (control) and rats treated with r-HuEPO at doses of 1000 U/kg, 3000 U/kg and 5000 U/kg. Brain tissues were collected on the 7th day after trauma surgery. Apoptotic cells, and NF-kappa B (NFĸB)-, c-myc-, and Fas/Fasl-positive cells were identified in brain tissues by immunohistochemical assay. Results: After treatment with r-HuEPO (3000 and 5000 U/kg), expression of NF-κB and Fas/Fasl were significantly decreased (p < 0.05) compared to control rats, especially at the 5000 U/kg dose (p < 0.01). However, for c-myc, no significant difference was observed between r-HuEPO treatment and control groups (p > 0.05). Compared to the 1000 U/kg r-HuEPO group, Fas/Fasl expression levels were significantly lower in the 3000 and 5000 U/kg r-HuEPO groups (p < 0.05). Additionally, expression of NF-κB and Fasl in the 5000 U/kg r-HuEPO group was significantly lower than that in the 3000 U/kg r- HuEPO group (p < 0.05). Moreover, the number of apoptotic cells in the r-HuEPO group (5000 U/kg) was significantly lower than in the control group (p < 0.05). Conclusion: Thus, r-HuEPO may be beneficial for treating traumatic brain injury via inhibition of NFkappa B and Fas/Fasl expressions.

How relevant is the origin of human capital for immigrant wages? Evidence from Spain

The objective of this article is to analyse the role played by the different components of human capital in the wage determination of immigrants in the Spanish labour market. Using microdata from the Encuesta Nacional de Inmigrantes, we find that human capital of immigrants acquired in Spain presents higher returns than human capital obtained in home countries, reflecting the limited international transferability of the latter. This result is reinforced by the strong heterogeneity observed in wage returns to different kinds of human capital across immigrants from different origins and, in particular, by the fact that immigrants with the higher returns to human capital acquired in their home countries are those coming from other developed countries and Latin America, the two regions more similar to Spain in terms of development and/or culture.

Expressions and clinic significance of miRNA-143, miRNA- 34A, miRNA-944, miRNA-101 and miRNA-218 in cervical cancer tissues

Purpose: To search for novel biomarkers for early diagnosis of cervical cancer, as well as novel therapeutic target for cervical cancer. Methods: A total of 96 cervical tissue specimens were collected from patients in the Second Affiliated Hospital of Zhengzhou University, out of which 10 were normal control. The remaining specimens (86) were cervical cancer specimens and were divided into 4 groups (A - D) based on tumor-biomarker levels of CA125 and SCC. Quantitative real-time polymerase chain reaction technology (qRT-PCR) was used to detect the expressions of miRNA-143, miRNA-34A, miRNA-944, miRNA-101 and miRNA-218 in the cervical cancer tissues. Results: The levels of CA125 (U/mL) and SCC (ug/L) expressed in normal control group and groups A - D were 11.75 and 0.73 (n = 10), 382 and 2.72 (n = 25), 912.9 and 3.93 (n = 21), 1675 and 5.87 (n = 29), and 2120 and 6.66 (n = 11), respectively. Furthermore, qRT-PCR results showed that the expressions of miRNA-944 and miRNA-218 in cervical cancer tissues were markedly up-regulated compared to normal control tissues (p < 0.01). In contrast, the expression level of miRNA-143, miRNA-34A, and miRNA-101 were significantly decreased (p < 0.01). Conclusion: The biomarkers, miRNA-143, miRNA-34A, miRNA-944, miRNA-101 and miRNA-218, can be considered novel for early diagnosis of cervical cancer.

Simulação de fluxo de fluidos em meios porosos desordenados uma análise de efeito de escala na estimativa da permeabilidade e do coeficiente de arrasto

The present study provides a methodology that gives a predictive character the computer simulations based on detailed models of the geometry of a porous medium. We using the software FLUENT to investigate the flow of a viscous Newtonian fluid through a random fractal medium which simplifies a two-dimensional disordered porous medium representing a petroleum reservoir. This fractal model is formed by obstacles of various sizes, whose size distribution function follows a power law where exponent is defined as the fractal dimension of fractionation Dff of the model characterizing the process of fragmentation these obstacles. They are randomly disposed in a rectangular channel. The modeling process incorporates modern concepts, scaling laws, to analyze the influence of heterogeneity found in the fields of the porosity and of the permeability in such a way as to characterize the medium in terms of their fractal properties. This procedure allows numerically analyze the measurements of permeability k and the drag coefficient Cd proposed relationships, like power law, for these properties on various modeling schemes. The purpose of this research is to study the variability provided by these heterogeneities where the velocity field and other details of viscous fluid dynamics are obtained by solving numerically the continuity and Navier-Stokes equations at pore level and observe how the fractal dimension of fractionation of the model can affect their hydrodynamic properties. This study were considered two classes of models, models with constant porosity, MPC, and models with varying porosity, MPV. The results have allowed us to find numerical relationship between the permeability, drag coefficient and the fractal dimension of fractionation of the medium. Based on these numerical results we have proposed scaling relations and algebraic expressions involving the relevant parameters of the phenomenon. In this study analytical equations were determined for Dff depending on the geometrical parameters of the models. We also found a relation between the permeability and the drag coefficient which is inversely proportional to one another. As for the difference in behavior it is most striking in the classes of models MPV. That is, the fact that the porosity vary in these models is an additional factor that plays a significant role in flow analysis. Finally, the results proved satisfactory and consistent, which demonstrates the effectiveness of the referred methodology for all applications analyzed in this study.

Detecting expressions of blame or praise in text

The growth of social networking platforms has drawn a lot of attentions to the need for social computing. Social computing utilises human insights for computational tasks as well as design of systems that support social behaviours and interactions. One of the key aspects of social computing is the ability to attribute responsibility such as blame or praise to social events. This ability helps an intelligent entity account and understand other intelligent entities’ social behaviours, and enriches both the social functionalities and cognitive aspects of intelligent agents. In this paper, we present an approach with a model for blame and praise detection in text. We build our model based on various theories of blame and include in our model features used by humans determining judgment such as moral agent causality, foreknowledge, intentionality and coercion. An annotated corpus has been created for the task of blame and praise detection from text. The experimental results show that while our model gives similar results compared to supervised classifiers on classifying text as blame, praise or others, it outperforms supervised classifiers on more finer-grained classification of determining the direction of blame and praise, i.e., self-blame, blame-others, self-praise or praise-others, despite not using labelled training data.

Regionalismos léxicos y paremiológicos en la narrativa de Jorge Amado: aspectos sociolingüístico y antropológico

The work of Jorge Amado collects and processes relevant aspects of Brazilian miscegenation and allows discussion on various issues relating to the cultural productions of the country. If on the one hand the racial mixture can be seen as the result of an harmonious process, as is traditional Brazilian thought that comes from XVIII century, on the other hand it portrays the customs of Bahian society at different times, mixing the humorous tone to the optimistic view of the world. As for the miscegenation, reality of the Bahian people, as of all Brazil, can also be analyzed in their heterogeneity, for whom observes that, in the end, the crossing of economic, social and cultural boundaries have been, in many cases, quite problematic. The aim of this work is to make a journey into reality, past and present in Brazil, to understand the lexical regionalisms present in each work; it is important to understand the history of slavery, indigenous groups and the relation that the white man had with this world. All that enormous database of spoken language (a true linguistic laboratory) served and is serving to describe the Portuguese in Brazil in its regional, ethnic and social varieties. (Bagno, 2011: 104-105) I analyze here two works by Jorge Amado, Gabriela, Clove and Cinnamon: Chronicle of an Inner City and Tieta of Agreste, which constitute the corpus of this work, which will consist in detecting an extensive glossary and the collection thereof as well as paremiological regionalisms; phrases or expressions corresponding to a region and time of Brazil...

A influência do jogo dramático na compreensão de textos narrativos no contexto do 1.º Ciclo do Ensino Básico

Relatório de Estágio apresentado à Escola Superior de Educação do Instituto Politécnico de Castelo Branco para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Educação Pré-Escolar e Ensino do 1.º Ciclo do Ensino Básico.

Transcriptional profiling in Saccharomyces cerevisiae relevant for predicting alachlor mechanisms of toxicity

Alachlor has been a commonly applied herbicide and is a substance of ecotoxicological concern. The present study aims to identify molecular biomarkers in the eukaryotic model Saccharomyces cerevisiae that can be used to predict potential cytotoxic effects of alachlor, while providing new mechanistic clues with possible relevance for experimentally less accessible eukaryotes. It focuses on genome-wide expression profiling in a yeast population in response to two exposure scenarios exerting effects from slight to moderate magnitude at phenotypic level. In particular, 100 and 264 genes, respectively, were found as differentially expressed on a 2-h exposure of yeast cells to the lowest observed effect concentration (110 mg/L) and the 20% inhibitory concentration (200 mg/L) of alachlor, in comparison with cells not exposed to the herbicide. The datasets of alachlor-responsive genes showed functional enrichment in diverse metabolic, transmembrane transport, cell defense, and detoxification categories. In general, the modifications in transcript levels of selected candidate biomarkers, assessed by quantitative reverse transcriptase polymerase chain reaction, confirmed the microarray data and varied consistently with the growth inhibitory effects of alachlor. Approximately 16% of the proteins encoded by alachlor-differentially expressed genes were found to share significant homology with proteins from ecologically relevant eukaryotic species. The biological relevance of these results is discussed in relation to new insights into the potential adverse effects of alachlor in health of organisms from ecosystems, particularly in worst-case situations such as accidental spills or careless storage, usage, and disposal.

Left atrial anatomy relevant to catheter ablation

The rapid development of interventional procedures for the treatment of arrhythmias in humans, especially the use of catheter ablation techniques, has renewed interest in cardiac anatomy. Although the substrates of atrial fibrillation (AF), its initiation and maintenance, remain to be fully elucidated, catheter ablation in the left atrium (LA) has become a common therapeutic option for patients with this arrhythmia. Using ablation catheters, various isolation lines and focal targets are created, the majority of which are based on gross anatomical, electroanatomical, and myoarchitectual patterns of the left atrial wall. Our aim was therefore to review the gross morphological and architectural features of the LA and their relations to extracardiac structures. The latter have also become relevant because extracardiac complications of AF ablation can occur, due to injuries to the phrenic and vagal plexus nerves, adjacent coronary arteries, or the esophageal wall causing devastating consequences.

Pros and cons on legislative issues relevant to the Iowa Development Commission, February 17, 1972

This material provides information which will assist committee members in making decisions on the pros and cons on Legislative issues relevant to the Iowa Development commission.

Sparse hierarchical Bayesian models for detecting relevant antigenic sites in virus evolution

Understanding how virus strains offer protection against closely related emerging strains is vital for creating effective vaccines. For many viruses, including Foot-and-Mouth Disease Virus (FMDV) and the Influenza virus where multiple serotypes often co-circulate, in vitro testing of large numbers of vaccines can be infeasible. Therefore the development of an in silico predictor of cross-protection between strains is important to help optimise vaccine choice. Vaccines will offer cross-protection against closely related strains, but not against those that are antigenically distinct. To be able to predict cross-protection we must understand the antigenic variability within a virus serotype, distinct lineages of a virus, and identify the antigenic residues and evolutionary changes that cause the variability. In this thesis we present a family of sparse hierarchical Bayesian models for detecting relevant antigenic sites in virus evolution (SABRE), as well as an extended version of the method, the extended SABRE (eSABRE) method, which better takes into account the data collection process. The SABRE methods are a family of sparse Bayesian hierarchical models that use spike and slab priors to identify sites in the viral protein which are important for the neutralisation of the virus. In this thesis we demonstrate how the SABRE methods can be used to identify antigenic residues within different serotypes and show how the SABRE method outperforms established methods, mixed-effects models based on forward variable selection or l1 regularisation, on both synthetic and viral datasets. In addition we also test a number of different versions of the SABRE method, compare conjugate and semi-conjugate prior specifications and an alternative to the spike and slab prior; the binary mask model. We also propose novel proposal mechanisms for the Markov chain Monte Carlo (MCMC) simulations, which improve mixing and convergence over that of the established component-wise Gibbs sampler. The SABRE method is then applied to datasets from FMDV and the Influenza virus in order to identify a number of known antigenic residue and to provide hypotheses of other potentially antigenic residues. We also demonstrate how the SABRE methods can be used to create accurate predictions of the important evolutionary changes of the FMDV serotypes. In this thesis we provide an extended version of the SABRE method, the eSABRE method, based on a latent variable model. The eSABRE method takes further into account the structure of the datasets for FMDV and the Influenza virus through the latent variable model and gives an improvement in the modelling of the error. We show how the eSABRE method outperforms the SABRE methods in simulation studies and propose a new information criterion for selecting the random effects factors that should be included in the eSABRE method; block integrated Widely Applicable Information Criterion (biWAIC). We demonstrate how biWAIC performs equally to two other methods for selecting the random effects factors and combine it with the eSABRE method to apply it to two large Influenza datasets. Inference in these large datasets is computationally infeasible with the SABRE methods, but as a result of the improved structure of the likelihood, we are able to show how the eSABRE method offers a computational improvement, leading it to be used on these datasets. The results of the eSABRE method show that we can use the method in a fully automatic manner to identify a large number of antigenic residues on a variety of the antigenic sites of two Influenza serotypes, as well as making predictions of a number of nearby sites that may also be antigenic and are worthy of further experiment investigation.

Normalização automática de descrições de hotéis

As descrições de produtos turísticos na área da hotelaria, aviação, rent-a-car e pacotes de férias baseiam-se sobretudo em descrições textuais em língua natural muito heterogénea com estilos, apresentações e conteúdos muito diferentes entre si. Uma vez que o sector do turismo é bastante dinâmico e que os seus produtos e ofertas estão constantemente em alteração, o tratamento manual de normalização de toda essa informação não é possível. Neste trabalho construiu-se um protótipo que permite a classificação e extracção automática de informação a partir de descrições de produtos de turismo. Inicialmente a informação é classificada quanto ao tipo. Seguidamente são extraídos os elementos relevantes de cada tipo e gerados objectos facilmente computáveis. Sobre os objectos extraídos, o protótipo com recurso a modelos de textos e imagens gera automaticamente descrições normalizadas e orientadas a um determinado mercado. Esta versatilidade permite um novo conjunto de serviços na promoção e venda dos produtos que seria impossível implementar com a informação original. Este protótipo, embora possa ser aplicado a outros domínios, foi avaliado na normalização da descrição de hotéis. As frases descritivas do hotel são classificadas consoante o seu tipo (Local, Serviços e/ou Equipamento) através de um algoritmo de aprendizagem automática que obtém valores médios de cobertura de 96% e precisão de 72%. A cobertura foi considerada a medida mais importante uma vez que a sua maximização permite que não se percam frases para processamentos posteriores. Este trabalho permitiu também a construção e população de uma base de dados de hotéis que possibilita a pesquisa de hotéis pelas suas características. Esta funcionalidade não seria possível utilizando os conteúdos originais. ABSTRACT: The description of tourism products, like hotel, aviation, rent-a-car and holiday packages, is strongly supported on natural language expressions. Due to the extent of tourism offers and considering the high dynamics in the tourism sector, manual data management is not a reliable or scalable solution. Offer descriptions - in the order of thousands - are structured in different ways, possibly comprising different languages, complementing and/or overlap one another. This work aims at creating a prototype for the automatic classification and extraction of relevant knowledge from tourism-related text expressions. Captured knowledge is represented in a normalized/standard format to enable new services based on this information in order to promote and sale tourism products that would be impossible to implement with the raw information. Although it could be applied to other areas, this prototype was evaluated in the normalization of hotel descriptions. Hotels descriptive sentences are classified according their type (Location, Services and/or Equipment) using a machine learning algorithm. The built setting obtained an average recall of 96% and precision of 72%. Recall considered the most important measure of performance since its maximization allows that sentences were not lost in further processes. As a side product a database of hotels was built and populated with search facilities on its characteristics. This ability would not be possible using the original contents.

Relevant Aspects on Teaching Probability and Statistics in Basic General Education

Probability and Statistics were included in the Basic General Education curricula by the Ministry of Public Education (Costa Rica), since 1995. To analyze the teaching reality in these fields, a research was conducted in two educational regions of the country: Heredia and Pérez Zeledón. The survey included university training and updating processes of teachers teaching Statistics and Probability in the schools. The research demonstrated the limited university training in these fields, the dissatisfaction of teachers about it, and the poor support of training institutions to their professional exercise.

Molecular simulations and modeling of pharmaceutically relevant RNA-processing enzymes

The two-metal-ion architecture is a structural feature found in a variety of RNA processing metalloenzymes or ribozymes (RNA-based enzymes), which control the biogenesis and the metabolism of vital RNAs, including non-coding RNAs (ncRNAs). Notably, such ncRNAs are emerging as key players for the regulation of cellular homeostasis, and their altered expression has been often linked to the development of severe human pathologies, from cancer to mental disorders. Accordingly, understanding the biological processing of ncRNAs is foundational for the development of novel therapeutic strategies and tools. Here, we use state-of the-art molecular simulations, complemented with X-ray crystallography and biochemical experiments, to characterize the RNA processing cycle as catalyzed by two two-metal-ion enzymes: the group II intron ribozymes and the RNase H1. We show that multiple and diverse cations are strategically recruited at and timely released from the enzymes’ active site during catalysis. Such a controlled cations’ trafficking leads to the recursive formation and disruption of an extended two-metal ion architecture that is functional for RNA-hydrolysis – from substrate recruitment to product release. Importantly, we found that these cations’ binding sites are conserved among other RNA-processing machineries, including the human spliceosome and CRISPR-Cas systems, suggesting that an evolutionarily-converged catalytic strategy is adopted by these enzymes to process RNA molecules. Thus, our findings corroborate and sensibly extend the current knowledge of two-metal-ion enzymes, and support the design of novel drugs targeting RNA-processing metalloenzymes or ribozymes as well as the rational engineering of novel programmable gene-therapy tools.

Simulation of photoinduced processes in organic chromophores: mapping photochemically relevant states for accurate dynamics

The simulation of ultrafast photoinduced processes is a fundamental step towards the understanding of the underlying molecular mechanism and interpretation/prediction of experimental data. Performing a computer simulation of a complex photoinduced process is only possible introducing some approximations but, in order to obtain reliable results, the need to reduce the complexity must balance with the accuracy of the model, which should include all the relevant degrees of freedom and a quantitatively correct description of the electronic states involved in the process. This work presents new computational protocols and strategies for the parameterisation of accurate models for photochemical/photophysical processes based on state-of-the-art multiconfigurational wavefunction-based methods. The required ingredients for a dynamics simulation include potential energy surfaces (PESs) as well as electronic state couplings, which must be mapped across the wide range of geometries visited during the wavepacket/trajectory propagation. The developed procedures allow to obtain solid and extended databases reducing as much as possible the computational cost, thanks to, e.g., specific tuning of the level of theory for different PES regions and/or direct calculation of only the needed components of vectorial quantities (like gradients or nonadiabatic couplings). The presented approaches were applied to three case studies (azobenzene, pyrene, visual rhodopsin), all requiring an accurate parameterisation but for different reasons. The resulting models and simulations allowed to elucidate the mechanism and time scale of the internal conversion, reproducing or even predicting new transient experiments. The general applicability of the developed protocols to systems with different peculiarities and the possibility to parameterise different types of dynamics on an equal footing (classical vs purely quantum) prove that the developed procedures are flexible enough to be tailored for each specific system, and pave the way for exact quantum dynamics with multiple degrees of freedom.