A construção do direito à saúde no Brasil

O direito à saúde recebeu - pela primeira vez - tratamento constitucional no brasil em 1988, fruto de grande participação popular. Neste estudo, se busca compreender a extensão dessa afirmação e verificar sua implementação normativa e jurisprudencial. A partir do estudo da evolução dos conceitos de saúde e de direito, concluiu-se que o direito à saúde deve implicar a constante participação popular para que possa ser delimitado. Verificou-se, também, que o arcabouço normativo vem sendo construído em conformidade com as exigências constitucionais. Quanto à construção jurisprudencial, se percebeu que ela vem acontecendo de forma errática e que os tribunais superiores raramente enfrentam a discussão da política de saúde desenhada na Constituição da República Federativa do Brasil de 1988. Concluiu-se que a afirmação constitucional tem demonstrado vigor, haja vista o grande desenvolvimento normativo conforme `compreensão contemporânea; e que o controle judicial da realização da política sanitária é ainda incipiente

What loggers leave behind: Impacts on big-leaf mahogany (Swietenia macrophylla) commercial populations and potential for post-logging recovery in the Brazilian Amazon

The sustainability of current harvest practices for high-value Meliaceae can be assessed by quantifying logging intensity and projecting growth and survival by post-logging populations over anticipated intervals between harvests. From 100%-area inventories of big-leaf mahogany (Swietenia macrophylla) covering 204 ha or more at eight logged and unlogged forest sites across southern Brazilian Amazonia, we report generally higher landscape-scale densities and smaller population-level mean diameters in eastern forests compared to western forests, where most commercial stocks survive. Density of trees >= 20 cm diameter varied by two orders of magnitude and peaked at 1.17 ha(-1). Size class frequency distributions appeared unimodal at two high-density sites, but were essentially arnodal or flat elsewhere; diameter increment patterns indicate that populations were multi- or all-aged. At two high-density sites, conventional logging removed 93-95% of commercial trees (>= 45 cm diameter at the time of logging), illegally eliminated 31-47% of sub-merchantable trees, and targeted trees as small as 20 cm diameter. Projected recovery by commercial stems during 30 years after conventional logging represented 9.9-37.5% of initial densities and was highly dependent on initial logging intensity and size class frequency distributions of commercial trees. We simulated post-logging recovery over the same period at all sites according to the 2003 regulatory framework for mahogany in Brazil, which raised the minimum diameter cutting limit to 60 cm and requires retention during the first harvest of 20% of commercial-sized trees. Recovery during 30 years ranged from approximately 0 to 31% over 20% retention densities at seven of eight sites. At only one site where sub-merchantable trees dominated the population did the simulated density of harvestable stems after 30 years exceed initial commercial densities. These results indicate that 80% harvest intensity will not be sustainable over multiple cutting cycles for most populations without silvicultural interventions ensuring establishment and long-term growth of artificial regeneration to augment depleted natural stocks, including repeated tending of outplanted seedlings. Without improved harvest protocols for mahogany in Brazil as explored in this paper, future commercial supplies of this species as well as other high-value tropical timbers are endangered. Rapid changes in the timber industry and land-use in the Amazon are also significant challenges to sustainable management of mahogany. (C) 2007 Elsevier B.V. All rights reserved.

Association of polymorphisms at the ADIPOR1 regulatory region with type 2 diabetes and body mass index in a Brazilian population with European or African ancestry

Association studies between ADIPOR1 genetic variants and predisposition to type 2 diabetes (DM2) have provided contradictory results. We determined if two single nucleotide polymorphisms (SNP c.-8503G>A and SNP c.10225C>G) in regulatory regions of ADIPOR1 in 567 Brazilian individuals of European (EA; N = 443) or African (AfA; N = 124) ancestry from rural (quilombo remnants; N = 439) and urban (N = 567) areas. We detected a significant effect of ethnicity on the distribution of the allelic frequencies of both SNPs in these populations (EA: -8503A = 0.27; AfA: -8503A = 0.16; P = 0.001 and EA: 10225G = 0.35; AfA: 10225G = 0.51; P < 0.001). Neither of the polymorphisms were associated with DM2 in the case-control study in EA (SNP c.-8503G>A: DM2 group -8503A = 0.26; control group -8503A = 0.30; P = 0.14/SNP 10225C>G: DM2 group 10225G = 0.37; control group 10225G = 0.32; P = 0.40) and AfA populations (SNP c.-8503G>A: DM2 group -8503A = 0.16; control group -8503A = 0.15; P = 0.34/SNP 10225C>G: DM2 group 10225G = 0.51; control group 10225G = 0.52; P = 0.50). Similarly, none of the polymorphisms were associated with metabolic/anthropometric risk factors for DM2 in any of the three populations, except for HDL cholesterol, which was significantly higher in AfA heterozygotes (GC = 53.75 ± 17.26 mg/dL) than in homozygotes. We conclude that ADIPOR1 polymorphisms are unlikely to be major risk factors for DM2 or for metabolic/anthropometric measurements that represent risk factors for DM2 in populations of European and African ancestries.

Essential regulatory elements for NHE3 gene transcription in renal proximal tubule cells

The objectives of the present study were to identify the cis-elements of the promoter absolutely required for the efficient rat NHE3 gene transcription and to locate positive and negative regulatory elements in the 5’-flanking sequence (5’FS), which might modulate the gene expression in proximal tubules, and to compare this result to those reported for intestinal cell lines. We analyzed the promoter activity of different 5’FS segments of the rat NHE3 gene, in the OKP renal proximal tubule cell line by measuring the activity of the reporter gene luciferase. Because the segment spanning the first 157 bp of 5’FS was the most active it was studied in more detail by sequential deletions, point mutations, and gel shift assays. The essential elements for gene transcription are in the region -85 to -33, where we can identify consensual binding sites for Sp1 and EGR-1, which are relevant to NHE3 gene basal transcription. Although a low level of transcription is still possible when the first 25 bp of the 5’FS are used as promoter, efficient transcription only occurs with 44 bp of 5’FS. There are negative regulatory elements in the segments spanning -1196 to -889 and -467 to -152, and positive enhancers between -889 and -479 bp of 5’FS. Transcription factors in the OKP cell nuclear extract efficiently bound to DNA elements of rat NHE3 promoter as demonstrated by gel shift assays, suggesting a high level of similarity between transcription factors of both species, including Sp1 and EGR-1.

Complex networks: the key to systems biology

Though introduced recently, complex networks research has grown steadily because of its potential to represent, characterize and model a wide range of intricate natural systems and phenomena. Because of the intrinsic complexity and systemic organization of life, complex networks provide a specially promising framework for systems biology investigation. The current article is an up-to-date review of the major developments related to the application of complex networks in biology, with special attention focused on the more recent literature. The main concepts and models of complex networks are presented and illustrated in an accessible fashion. Three main types of networks are covered: transcriptional regulatory networks, protein-protein interaction networks and metabolic networks. The key role of complex networks for systems biology is extensively illustrated by several of the papers reviewed.

Plasmodium vivax: Induction of CD4(+)CD25(+)FoxP3(+) Regulatory T Cells during Infection Are Directly Associated with Level of Circulating Parasites

Circulation CD4(+)CD25(+)FoxP3(+) regulatory T cells (Tregs) have been associated with the delicate balancing between control of overwhelming acute malaria infection and prevention of immune pathology due to disproportionate inflammatory responses to erythrocytic stage of the parasite. While the role of Tregs has been well-documented in murine models and P. falciparum infection, the phenotype and function of Tregs in P. vivax infection is still poorly characterized. In the current study, we demonstrated that patients with acute P. vivax infection presented a significant augmentation of circulating Tregs producing anti-inflammatory (IL-10 and TGF-beta) as well as pro-inflammatory (IFN-gamma, IL-17) cytokines, which was further positively correlated with parasite burden. Surface expression of GITR molecule and intracellular expression of CTLA-4 were significantly upregulated in Tregs from infected donors, presenting also a positive association between either absolute numbers of CD4(+)CD25(+)FoxP3(+)GITR(+) or CD4(+)CD25(+)FoxP3(+)CTLA-4(+) and parasite load. Finally, we demonstrate a suppressive effect of Treg cells in specific T cell proliferative responses of P. vivax infected subjects after antigen stimulation with Pv-AMA-1. Our findings indicate that malaria vivax infection lead to an increased number of activated Treg cells that are highly associated with parasite load, which probably exert an important contribution to the modulation of immune responses during P. vivax infection.

The frequency of CD127(low) expressing CD4(+)CD25(high) T regulatory cells is inversely correlated with human T lymphotrophic virus type-1 (HTLV-1) proviral load in HTLV-1-infection and HTLV-1-associated myelopathy/tropical spastic paraparesis

Background: CD4(+)CD25(high) regulatory T (T(Reg)) cells modulate antigen-specific T cell responses, and can suppress anti-viral immunity. In HTLV-1 infection, a selective decrease in the function of T(Reg) cell mediated HTLV-1-tax inhibition of FOXP3 expression has been described. The purpose of this study was to assess the frequency and phenotype of T(Reg) cells in HTLV-1 asymptomatic carriers and in HTLV-1-associated neurological disease (HAM/TSP) patients, and to correlate with measures of T cell activation. Results: We were able to confirm that HTLV-1 drives activation, spontaneous IFN gamma production, and proliferation of CD4+ T cells. We also observed a significantly lower proportion of CTLA-4(+) T(Reg) cells (CD4(+)CD25(high) T cells) in subjects with HAM/TSP patients compared to healthy controls. Ki-67 expression was negatively correlated to the frequency of CTLA-4(+) T(Reg) cells in HAM/TSP only, although Ki-67 expression was inversely correlated with the percentage of CD127(low) T(Reg) cells in healthy control subjects. Finally, the proportion of CD127(low) T(Reg) cells correlated inversely with HTLV-1 proviral load. Conclusion: Taken together, the results suggest that T(Reg) cells may be subverted in HAM/TSP patients, which could explain the marked cellular activation, spontaneous cytokine production, and proliferation of CD4(+) T cells, in particular those expressing the CD25(high)CD127(low) phenotype. T(Reg) cells represent a potential target for therapeutic intervention for patients with HTLV-1-related neurological diseases.

Prolonged Survival of Allografts Induced by Mycobacterial Hsp70 Is Dependent on CD4+CD25+Regulatory T Cells

Background: Heat shock proteins (Hsps) are stress induced proteins with immunomodulatory properties. The Hsp70 of Mycobacterium tuberculosis (TBHsp70) has been shown to have an anti-inflammatory role on rodent autoimmune arthritis models, and the protective effects were demonstrated to be dependent on interleukin-10 (IL-10). We have previously observed that TBHsp70 inhibited maturation of dendritic cells (DCs) and induced IL-10 production by these cells, as well as in synovial fluid cells. Methodology/Principal Findings: We investigated if TBHsp70 could inhibit allograft rejection in two murine allograft systems, a transplanted allogeneic melanoma and a regular skin allograft. In both systems, treatment with TBHsp70 significantly inhibited rejection of the graft, and correlated with regulatory T cells (Tregs) recruitment. This effect was not tumor mediated because injection of TBHsp70 in tumor-free mice induced an increase of Tregs in the draining lymph nodes as well as inhibition of proliferation of lymph node T cells and an increase in IL-10 production. Finally, TBHsp70 inhibited skin allograft acute rejection, and depletion of Tregs using a monoclonal antibody completely abolished this effect. Conclusions/Significance: We present the first evidence for an immunosuppressive role for this protein in a graft rejection system, using an innovative approach - immersion of the graft tissue in TBHsp70 solution instead of protein injection. Also, this is the first study that demonstrates dependence on Treg cells for the immunosuppressive role of TBHsp70. This finding is relevant for the elucidation of the immunomodulatory mechanism of TBHsp70. We propose that this protein can be used not only for chronic inflammatory diseases, but is also useful for organ transplantation management.

Integration and visualization of systems biology data in context of the genome

Background: High-density tiling arrays and new sequencing technologies are generating rapidly increasing volumes of transcriptome and protein-DNA interaction data. Visualization and exploration of this data is critical to understanding the regulatory logic encoded in the genome by which the cell dynamically affects its physiology and interacts with its environment. Results: The Gaggle Genome Browser is a cross-platform desktop program for interactively visualizing high-throughput data in the context of the genome. Important features include dynamic panning and zooming, keyword search and open interoperability through the Gaggle framework. Users may bookmark locations on the genome with descriptive annotations and share these bookmarks with other users. The program handles large sets of user-generated data using an in-process database and leverages the facilities of SQL and the R environment for importing and manipulating data. A key aspect of the Gaggle Genome Browser is interoperability. By connecting to the Gaggle framework, the genome browser joins a suite of interconnected bioinformatics tools for analysis and visualization with connectivity to major public repositories of sequences, interactions and pathways. To this flexible environment for exploring and combining data, the Gaggle Genome Browser adds the ability to visualize diverse types of data in relation to its coordinates on the genome. Conclusions: Genomic coordinates function as a common key by which disparate biological data types can be related to one another. In the Gaggle Genome Browser, heterogeneous data are joined by their location on the genome to create information-rich visualizations yielding insight into genome organization, transcription and its regulation and, ultimately, a better understanding of the mechanisms that enable the cell to dynamically respond to its environment.

PAMM: A Redox Regulatory Protein That Modulates Osteoclast Differentiation

The central role of reactive oxygen species (ROS) in osteoclast differentiation and in bone homeostasis prompted us to characterize the redox regulatory system of osteoclasts. In this report, we describe the expression and functional characterization of PAMM, a CXXC motif-containing peroxiredoxin 2-like protein expressed in bone marrow monocytes on stimulation with M-CSF and RANKL. Expression of wild-type (but not C to G mutants of the CXXC domain) PAMM in HEK293 cells results in an increased GSH/GSSG ratio, indicating a shift toward a more reduced environment. Expression of PAMM in RAW264.7 monocytes protected cells from hydrogen peroxide-induced oxidative stress, indicating that PAMM regulates cellular redox status. RANKL stimulation of RAW 264.7 cells caused a decrease in the GSH/GSSG ratio (reflecting a complementary increase in ROS). In addition, RANKL-induced osteoclast formation requires phosphorylation and translocation of NF-kappa B and c-Jun. In stably transfected RAW 264.7 cells, PAMM overexpression prevented the reduction of GSH/GSSG induced by RANKL. Concurrently, PAMM expression completely abolished RANKL-induced p100 NF-kappa B and c-Jun activation, as well as osteoclast formation. We conclude that PAMM is a redox regulatory protein that modulates osteoclast differentiation in vitro. PAMM expression may affect bone resorption in vivo and help to maintain bone mass. Antioxid. Redox Signal. 13, 27-37.

Complete Genome Viral Phylogenies Suggests the Concerted Evolution of Regulatory Cores and Accessory Satellites

We consider the concerted evolution of viral genomes in four families of DNA viruses. Given the high rate of horizontal gene transfer among viruses and their hosts, it is an open question as to how representative particular genes are of the evolutionary history of the complete genome. To address the concerted evolution of viral genes, we compared genomic evolution across four distinct, extant viral families. For all four viral families we constructed DNA-dependent DNA polymerase-based (DdDp) phylogenies and in addition, whole genome sequence, as quantitative descriptions of inter-genome relationships. We found that the history of the polymerase gene was highly predictive of the history of the genome as a whole, which we explain in terms of repeated, co-divergence events of the core DdDp gene accompanied by a number of satellite, accessory genetic loci. We also found that the rate of gene gain in baculovirus and poxviruses proceeds significantly more quickly than the rate of gene loss and that there is convergent acquisition of satellite functions promoting contextual adaptation when distinct viral families infect related hosts. The congruence of the genome and polymerase trees suggests that a large set of viral genes, including polymerase, derive from a phylogenetically conserved core of genes of host origin, secondarily reinforced by gene acquisition from common hosts or co-infecting viruses within the host. A single viral genome can be thought of as a mutualistic network, with the core genes acting as an effective host and the satellite genes as effective symbionts. Larger virus genomes show a greater departure from linkage equilibrium between core and satellites functions.

Pressure of massless hot scalar theory in the boundary effective theory framework

We use the boundary effective theory approach to thermal field theory in order to calculate the pressure of a system of massless scalar fields with quartic interaction. The method naturally separates the infrared physics, and is essentially nonperturbative. To lowest order, the main ingredient is the solution of the free Euler-Lagrange equation with nontrivial (time) boundary conditions. We derive a resummed pressure, which is in good agreement with recent calculations found in the literature, following a very direct and compact procedure.

Gene Expression Complex Networks: Synthesis, Identification, and Analysis

Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdos-Renyi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabasi-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree k variation, decreasing its network recovery rate with the increase of k. The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.

Inference of gene regulatory networks from time series by Tsallis entropy

Background: The inference of gene regulatory networks (GRNs) from large-scale expression profiles is one of the most challenging problems of Systems Biology nowadays. Many techniques and models have been proposed for this task. However, it is not generally possible to recover the original topology with great accuracy, mainly due to the short time series data in face of the high complexity of the networks and the intrinsic noise of the expression measurements. In order to improve the accuracy of GRNs inference methods based on entropy (mutual information), a new criterion function is here proposed. Results: In this paper we introduce the use of generalized entropy proposed by Tsallis, for the inference of GRNs from time series expression profiles. The inference process is based on a feature selection approach and the conditional entropy is applied as criterion function. In order to assess the proposed methodology, the algorithm is applied to recover the network topology from temporal expressions generated by an artificial gene network (AGN) model as well as from the DREAM challenge. The adopted AGN is based on theoretical models of complex networks and its gene transference function is obtained from random drawing on the set of possible Boolean functions, thus creating its dynamics. On the other hand, DREAM time series data presents variation of network size and its topologies are based on real networks. The dynamics are generated by continuous differential equations with noise and perturbation. By adopting both data sources, it is possible to estimate the average quality of the inference with respect to different network topologies, transfer functions and network sizes. Conclusions: A remarkable improvement of accuracy was observed in the experimental results by reducing the number of false connections in the inferred topology by the non-Shannon entropy. The obtained best free parameter of the Tsallis entropy was on average in the range 2.5 <= q <= 3.5 (hence, subextensive entropy), which opens new perspectives for GRNs inference methods based on information theory and for investigation of the nonextensivity of such networks. The inference algorithm and criterion function proposed here were implemented and included in the DimReduction software, which is freely available at http://sourceforge.net/projects/dimreduction and http://code.google.com/p/dimreduction/.

The impact of measurement errors in the identification of regulatory networks

Background: There are several studies in the literature depicting measurement error in gene expression data and also, several others about regulatory network models. However, only a little fraction describes a combination of measurement error in mathematical regulatory networks and shows how to identify these networks under different rates of noise. Results: This article investigates the effects of measurement error on the estimation of the parameters in regulatory networks. Simulation studies indicate that, in both time series (dependent) and non-time series (independent) data, the measurement error strongly affects the estimated parameters of the regulatory network models, biasing them as predicted by the theory. Moreover, when testing the parameters of the regulatory network models, p-values computed by ignoring the measurement error are not reliable, since the rate of false positives are not controlled under the null hypothesis. In order to overcome these problems, we present an improved version of the Ordinary Least Square estimator in independent (regression models) and dependent (autoregressive models) data when the variables are subject to noises. Moreover, measurement error estimation procedures for microarrays are also described. Simulation results also show that both corrected methods perform better than the standard ones (i.e., ignoring measurement error). The proposed methodologies are illustrated using microarray data from lung cancer patients and mouse liver time series data. Conclusions: Measurement error dangerously affects the identification of regulatory network models, thus, they must be reduced or taken into account in order to avoid erroneous conclusions. This could be one of the reasons for high biological false positive rates identified in actual regulatory network models.