Biogeographic Distribution Patterns and Their Correlates in the Diverse Frog Fauna of the Atlantic Forest Hotspot

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Refractive errors in a Brazilian population: age and sex distribution

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The young stellar cluster [DBS2003] 157 associated with the H ii region GAL 331.31-00.34

We report a study of the stellar content of the near-infrared (NIR) cluster [DBS2003] 157 embedded in the extended H ii region GAL 331.31-00.34, which is associated with the IRAS source 16085-5138. JHK photometry was carried out in order to identify potential ionizing candidates, and the follow-up NIR spectroscopy allowed the spectral classification of some sources, including two O-type stars. A combination of NIR photometry and spectroscopy data was used to obtain the distance of these two stars, with the method of spectroscopic parallax: IRS 298 (O6 V, 3.35 +/- 0.61 kpc) and IRS 339 (O9 V, 3.24 +/- 0.56 kpc). Adopting the average distance of 3.29 +/- 0.58 kpc and comparing the Lyman continuum luminosity of these stars with that required to account for the radio continuum flux of the H ii region, we conclude that these two stars are the ionizing sources of GAL 331.31-00.34. Young stellar objects (YSOs) were searched by using our NIR photometry and mid-infrared (MIR) data from the Galactic Legacy Infrared Mid-Plane Survey Extraordinaire (GLIMPSE) survey. The analysis of NIR and MIR colourcolour diagrams resulted in 47 YSO candidates. The GLIMPSE counterpart of IRAS 16085-5138, which presents IRAS colour indices compatible with an ultracompact H ii region, has been identified. The analysis of its spectral energy distribution between 2 and m revealed that this source shows a spectral index a= 3.6 between 2 and m, which is typical of a YSO immersed in a protostellar envelope. Lower limits to the bolometric luminosity and the mass of the embedded protostar have been estimated as L= 7.7 x 10(3) L? and M= 10 M?, respectively, which correspond to a B0B1 V zero-age main sequence star.

Diversity of the KIR gene cluster in an urban Brazilian population

The activity of natural killer cells depends on the balance between activating and inhibitory signals coming from their receptors. Among these are the killer cell immunoglobulin-like receptors (KIR) that recognize specific HLA class I allotypes. Here we characterized KIR genetic diversity and their HLA ligands in the population of Curitiba, Parana State (n = 164), and compared it with other worldwide populations. The distribution of 2DL4 alleles was also analyzed. The Curitiba population did not differ significantly from European and Euro-descendant populations, but as an admixed population showed higher genetic diversity. We found 27 KIR profiles, many of them uncommon in European populations, in agreement with the elevated historically recent gene flow in the study population. The frequencies of KIR genes and their respective HLA ligands were distributed independently and none of the analyzed individuals lacked functional KIR-HLA ligand combinations. KIR gene frequencies of 33 worldwide populations were consistent with geographic and ethnic distribution, in agreement with demography being the major factor shaping the observed gene content diversity of the KIR locus.

A Poisson mixed model with nonnormal random effect distribution

In this paper, we propose a random intercept Poisson model in which the random effect is assumed to follow a generalized log-gamma (GLG) distribution. This random effect accommodates (or captures) the overdispersion in the counts and induces within-cluster correlation. We derive the first two moments for the marginal distribution as well as the intraclass correlation. Even though numerical integration methods are, in general, required for deriving the marginal models, we obtain the multivariate negative binomial model from a particular parameter setting of the hierarchical model. An iterative process is derived for obtaining the maximum likelihood estimates for the parameters in the multivariate negative binomial model. Residual analysis is proposed and two applications with real data are given for illustration. (C) 2011 Elsevier B.V. All rights reserved.

MicroRNA expression profile in head and neck cancer: HOX-cluster embedded microRNA-196a and microRNA-10b dysregulation implicated in cell proliferation

Abstract Background Current evidence implicates aberrant microRNA expression patterns in human malignancies; measurement of microRNA expression may have diagnostic and prognostic applications. Roles for microRNAs in head and neck squamous cell carcinomas (HNSCC) are largely unknown. HNSCC, a smoking-related cancer, is one of the most common malignancies worldwide but reliable diagnostic and prognostic markers have not been discovered so far. Some studies have evaluated the potential use of microRNA as biomarkers with clinical application in HNSCC. Methods MicroRNA expression profile of oral squamous cell carcinoma samples was determined by means of DNA microarrays. We also performed gain-of-function assays for two differentially expressed microRNA using two squamous cell carcinoma cell lines and normal oral keratinocytes. The effect of the over-expression of these molecules was evaluated by means of global gene expression profiling and cell proliferation assessment. Results Altered microRNA expression was detected for a total of 72 microRNAs. Among these we found well studied molecules, such as the miR-17-92 cluster, comprising potent oncogenic microRNA, and miR-34, recently found to interact with p53. HOX-cluster embedded miR-196a/b and miR-10b were up- and down-regulated, respectively, in tumor samples. Since validated HOX gene targets for these microRNAs are not consistently deregulated in HNSCC, we performed gain-of-function experiments, in an attempt to outline their possible role. Our results suggest that both molecules interfere in cell proliferation through distinct processes, possibly targeting a small set of genes involved in cell cycle progression. Conclusions Functional data on miRNAs in HNSCC is still scarce. Our data corroborate current literature and brings new insights into the role of microRNAs in HNSCC. We also show that miR-196a and miR-10b, not previously associated with HNSCC, may play an oncogenic role in this disease through the deregulation of cell proliferation. The study of microRNA alterations in HNSCC is an essential step to the mechanistic understanding of tumor formation and could lead to the discovery of clinically relevant biomarkers.

Knowledge Flows and Networks: the Interplay between Local and Global Linkages within Bangalore IT Cluster

This doctoral work gains deeper insight into the dynamics of knowledge flows within and across clusters, unfolding their features, directions and strategic implications. Alliances, networks and personnel mobility are acknowledged as the three main channels of inter-firm knowledge flows, thus offering three heterogeneous measures to analyze the phenomenon. The interplay between the three channels and the richness of available research methods, has allowed for the elaboration of three different papers and perspectives. The common empirical setting is the IT cluster in Bangalore, for its distinguished features as a high-tech cluster and for its steady yearly two-digit growth around the service-based business model. The first paper deploys both a firm-level and a tie-level analysis, exploring the cases of 4 domestic companies and of 2 MNCs active the cluster, according to a cluster-based perspective. The distinction between business-domain knowledge and technical knowledge emerges from the qualitative evidence, further confirmed by quantitative analyses at tie-level. At firm-level, the specialization degree seems to be influencing the kind of knowledge shared, while at tie-level both the frequency of interaction and the governance mode prove to determine differences in the distribution of knowledge flows. The second paper zooms out and considers the inter-firm networks; particularly focusing on the role of cluster boundary, internal and external networks are analyzed, in their size, long-term orientation and exploration degree. The research method is purely qualitative and allows for the observation of the evolving strategic role of internal network: from exploitation-based to exploration-based. Moreover, a causal pattern is emphasized, linking the evolution and features of the external network to the evolution and features of internal network. The final paper addresses the softer and more micro-level side of knowledge flows: personnel mobility. A social capital perspective is here developed, which considers both employees’ acquisition and employees’ loss as building inter-firm ties, thus enhancing company’s overall social capital. Negative binomial regression analyses at dyad-level test the significant impact of cluster affiliation (cluster firms vs non-cluster firms), industry affiliation (IT firms vs non-IT fims) and foreign affiliation (MNCs vs domestic firms) in shaping the uneven distribution of personnel mobility, and thus of knowledge flows, among companies.

Business Clusters in Eastern Europe: Policy Analysis and Cluster Performance

Clusters have increasingly become an essential part of policy discourses at all levels, EU, national, regional, dealing with regional development, competitiveness, innovation, entrepreneurship, SMEs. These impressive efforts in promoting the concept of clusters on the policy-making arena have been accompanied by much less academic and scientific research work investigating the actual economic performance of firms in clusters, the design and execution of cluster policies and going beyond singular case studies to a more methodologically integrated and comparative approach to the study of clusters and their real-world impact. The theoretical background is far from being consolidated and there is a variety of methodologies and approaches for studying and interpreting this phenomenon while at the same time little comparability among studies on actual cluster performances. The conceptual framework of clustering suggests that they affect performance but theory makes little prediction as to the ultimate distribution of the value being created by clusters. This thesis takes the case of Eastern European countries for two reasons. One is that clusters, as coopetitive environments, are a new phenomenon as the previous centrally-based system did not allow for such types of firm organizations. The other is that, as new EU member states, they have been subject to the increased popularization of the cluster policy approach by the European Commission, especially in the framework of the National Reform Programmes related to the Lisbon objectives. The originality of the work lays in the fact that starting from an overview of theoretical contributions on clustering, it offers a comparative empirical study of clusters in transition countries. There have been very few examples in the literature that attempt to examine cluster performance in a comparative cross-country perspective. It adds to this an analysis of cluster policies and their implementation or lack of such as a way to analyse the way the cluster concept has been introduced to transition economies. Our findings show that the implementation of cluster policies does vary across countries with some countries which have embraced it more than others. The specific modes of implementation, however, are very similar, based mostly on soft measures such as funding for cluster initiatives, usually directed towards the creation of cluster management structures or cluster facilitators. They are essentially founded on a common assumption that the added values of clusters is in the creation of linkages among firms, human capital, skills and knowledge at the local level, most often perceived as the regional level. Often times geographical proximity is not a necessary element in the application process and cluster application are very similar to network membership. Cluster mapping is rarely a factor in the selection of cluster initiatives for funding and the relative question about critical mass and expected outcomes is not considered. In fact, monitoring and evaluation are not elements of the cluster policy cycle which have received a lot of attention. Bulgaria and the Czech Republic are the countries which have implemented cluster policies most decisively, Hungary and Poland have made significant efforts, while Slovakia and Romania have only sporadically and not systematically used cluster initiatives. When examining whether, in fact, firms located within regional clusters perform better and are more efficient than similar firms outside clusters, we do find positive results across countries and across sectors. The only country with negative impact from being located in a cluster is the Czech Republic.

Distribution and Transmission of Medicinal Plant Knowledge in the Andean Highlands: A Case Study from Peru and Bolivia

This paper presents a study of patterns in the distribution and transmission of medicinal plant knowledge in rural Andean communities in Peru and Bolivia. Interviews and freelisting exercises were conducted with 18 households at each study site. The amount of medicinal plant knowledge of households was compared in relation to their socioeconomic characteristics. Cluster analysis was applied to identify households that possessed similar knowledge. The different modes of knowledge transmission were also assessed. Our study shows that while the amount of plant knowledge is determined by individual motivation and experience, the type of knowledge is influenced by the community of residence, age, migratory activity, and market integration. Plant knowledge was equally transmitted vertically and horizontally, which indicates that it is first acquired within the family but then undergoes transformations as a result of subsequent contacts with other knowledge sources, including age peers.

Distribution of RTX toxin genes in strains of [Actinobacillus] rossii and [Pasteurella] mairii

Strains of [Actinobacillus] rossii, [Pasteurella] mairii and [Pasteurella] aerogenes can be isolated from abortion in swine. The RTX toxin Pax has previously been found only in those [P.] aerogenes strains isolated from abortion. Nothing is known about RTX toxins in field isolates of the other two species. To gain insight into the distribution of selected RTX toxin genes and their association with abortion, PCR screening for the pax, apxII and apxIII operons on 21 [A.] rossii and seven [P.] mairii isolates was done. Since species can be phenotypically misidentified, the study was backed up by a phylogenetic analysis of all strains based on 16S rRNA, rpoB and infB genes. The pax gene was detected in all [P.] mairii but not in [A.] rossii strains. No apx genes were found in [P.] mairii but different gene combinations for apx were detected in [A.] rossii strains. Most of these strains were positive for apxIII, either alone or in combination with apxII. Whereas pax was found to be associated to strains from abortion no such indication could be found with apx in [A.] rossii strains. Phylogenetically [A.] rossii strains formed a heterogeneous cluster separated from Actinobacillus sensu stricto. [P.] mairii strains clustered with [P.] aerogenes but forming a separate branch. The fact that [P.] aerogenes, [P.] mairii and [A.] rossii can phylogenetically clearly be identified and might contain distinct RTX toxin genes allows their proper diagnosis and will further help to investigate their role as pathogens.

Multilevel Latent Class Models with Dirichlet Mixing Distribution

Latent class analysis (LCA) and latent class regression (LCR) are widely used for modeling multivariate categorical outcomes in social sciences and biomedical studies. Standard analyses assume data of different respondents to be mutually independent, excluding application of the methods to familial and other designs in which participants are clustered. In this paper, we develop multilevel latent class model, in which subpopulation mixing probabilities are treated as random effects that vary among clusters according to a common Dirichlet distribution. We apply the Expectation-Maximization (EM) algorithm for model fitting by maximum likelihood (ML). This approach works well, but is computationally intensive when either the number of classes or the cluster size is large. We propose a maximum pairwise likelihood (MPL) approach via a modified EM algorithm for this case. We also show that a simple latent class analysis, combined with robust standard errors, provides another consistent, robust, but less efficient inferential procedure. Simulation studies suggest that the three methods work well in finite samples, and that the MPL estimates often enjoy comparable precision as the ML estimates. We apply our methods to the analysis of comorbid symptoms in the Obsessive Compulsive Disorder study. Our models' random effects structure has more straightforward interpretation than those of competing methods, thus should usefully augment tools available for latent class analysis of multilevel data.

Taxonomic position and geographical distribution of the common sheep G1 and camel G6 strains of Echinococcus granulosus in three African countries

The taxonomic and phylogenetic status of Echinococcus granulosus strains are still controversial and under discussion. In the present study, we investigated the genetic polymorphism of E. granulosus isolates originating from three countries of Africa, including a region of Algeria, where the common G1 sheep and the camel G6 strains coexist sympatrically. Seventy-one hydatid cysts were collected from sheep, cattle, camels, and humans. Two mitochondrial markers (cox1 and nad1) were used for strain identification. Two nuclear markers (actII and hbx2) were used to study the possible occurrence of cross-fertilization. Despite the heterogeneity observed among the G1 isolates, they were all localized within one robust cluster. A second strong cluster was also observed containing all of the G6 isolates. Both strains appeared as two distinct groups, and no cases of interbreeding were found. Thus, the attribution of a species rank can be suggested. We also found the Tasmanian sheep G2 strain for the first time in Africa. Because of the slight variations observed between the common sheep and the Tasmanian sheep strains, further studies should be carried out to elucidate the epidemiological relevance of this genetic discrimination.

TGF-beta1 in Aplysia: role in long-term changes in the excitability of sensory neurons and distribution of TbetaR-II-like immunoreactivity.

Exogenous recombinant human transforming growth factor beta-1 (TGF-beta1) induced long-term facilitation of Aplysia sensory-motor synapses. In addition, 5-HT-induced facilitation was blocked by application of a soluble fragment of the extracellular portion of the TGF-beta1 type II receptor (TbetaR-II), which presumably acted by scavenging an endogenous TGF-beta1-like molecule. Because TbetaR-II is essential for transmembrane signaling by TGF-beta, we sought to determine whether Aplysia tissues contained TbetaR-II and specifically, whether neurons expressed the receptor. Western blot analysis of Aplysia tissue extracts demonstrated the presence of a TbetaR-II-immunoreactive protein in several tissue types. The expression and distribution of TbetaR-II-immunoreactive proteins in the central nervous system was examined by immunohistochemistry to elucidate sites that may be responsive to TGF-beta1 and thus may play a role in synaptic plasticity. Sensory neurons in the ventral-caudal cluster of the pleural ganglion were immunoreactive for TbetaR-II, as well as many neurons in the pedal, abdominal, buccal, and cerebral ganglia. Sensory neurons cultured in isolation and cocultured sensory and motor neurons were also immunoreactive. TGF-beta1 affected the biophysical properties of cultured sensory neurons, inducing an increase of excitability that persisted for at least 48 hr. Furthermore, exposure to TGF-beta1 resulted in a reduction in the firing threshold of sensory neurons. These results provide further support for the hypothesis that TGF-beta1 plays a role in long-term synaptic plasticity in Aplysia.

A community-based assessment of the spatiotemporal distribution of influenza in a U.S.-Mexico border county during the spring 2009 novel H1N1 swine-origin influenza A pandemic

This study retrospectively evaluated the spatial and temporal disease patterns associated with influenza-like illness (ILI), positive rapid influenza antigen detection tests (RIDT), and confirmed H1N1 S-OIV cases reported to the Cameron County Department of Health and Human Services between April 26 and May 13, 2009 using the space-time permutation scan statistic software SaTScan in conjunction with geographical information system (GIS) software ArcGIS 9.3. The rate and age-adjusted relative risk of each influenza measure was calculated and a cluster analysis was conducted to determine the geographic regions with statistically higher incidence of disease. A Poisson distribution model was developed to identify the effect that socioeconomic status, population density, and certain population attributes of a census block-group had on that area's frequency of S-OIV confirmed cases over the entire outbreak. Predominant among the spatiotemporal analyses of ILI, RIDT and S-OIV cases in Cameron County is the consistent pattern of a high concentration of cases along the southern border with Mexico. These findings in conjunction with the slight northward space-time shifts of ILI and RIDT cluster centers highlight the southern border as the primary site for public health interventions. Finally, the community-based multiple regression model revealed that three factors—percentage of the population under age 15, average household size, and the number of high school graduates over age 25—were significantly associated with laboratory-confirmed S-OIV in the Lower Rio Grande Valley. Together, these findings underscore the need for community-based surveillance, improve our understanding of the distribution of the burden of influenza within the community, and have implications for vaccination and community outreach initiatives.^

Kawasaki syndrome: Cluster analysis of incident cases presenting to a pediatric tertiary care hospital in Texas from January 1, 2005 to December 31, 2009

Background: Despite almost 40 years of research into the etiology of Kawasaki Syndrome (KS), there is little research published on spatial and temporal clustering of KS cases. Previous analysis has found significant spatial and temporal clustering of cases, therefore cluster analyses were performed to substantiate these findings and provide insight into incident KS cases discharged from a pediatric tertiary care hospital. Identifying clusters from a single institution would allow for prospective analysis of risk factors and potential exposures for further insight into KS etiology. ^ Methods: A retrospective study was carried out to examine the epidemiology and distribution of patients presenting to Texas Children’s Hospital in Houston, Texas, with a diagnosis of Acute Febrile Mucocutaneous Lymph Node Syndrome (MCLS) upon discharge from January 1, 2005 to December 31, 2009. Spatial, temporal, and space-time cluster analyses were performed using the Bernoulli model with case and control event data. ^ Results: 397 of 102,761 total patients admitted to Texas Children’s Hospital had a principal or secondary diagnosis of Acute Febrile MCLS upon over the 5 year period. Demographic data for KS cases remained consistent with known disease epidemiology. Spatial, temporal, and space-time analyses of clustering using the Bernoulli model demonstrated no statistically significant clusters. ^ Discussion: Despite previous findings of spatial-temporal clustering of KS cases, there were no significant clusters of KS cases discharged from a single institution. This implicates the need for an expanded approach to conducting spatial-temporal cluster analysis and KS surveillance given the limitations of evaluating data from a single institution.^