Leukotrienes Are Upregulated and Associated with Human T-Lymphotropic Virus Type 1 (HTLV-1)-Associated Neuroinflammatory Disease

Leukotrienes (LTs) are lipid mediators involved in several inflammatory disorders. We investigated the LT pathway in human T-lymphotropic virus type 1 (HTLV-1) infection by evaluating LT levels in HTLV-1-infected patients classified according to the clinical status as asymptomatic carriers (HACs) and HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP) patients. Bioactive LTB4 and CysLTs were both increased in the plasma and in the supernatant of peripheral blood mononuclear cell cultures of HTLV-1-infected when compared to non-infected. Interestingly, CysLT concentrations were increased in HAM/TSP patients. Also, the concentration of plasma LTB4 and LTC4 positively correlated with the HTLV-1 proviral load in HTLV-1-infected individuals. The gene expression levels of LT receptors were differentially modulated in CD4(+) and CD8(+) T cells of HTLV-1-infected patients. Analysis of the overall plasma signature of immune mediators demonstrated that LT and chemokine amounts were elevated during HTLV-1 infection. Importantly, in addition to CysLTs, IP-10 was also identified as a biomarker for HAM/TSP activity. These data suggest that LTs are likely to be associated with HTLV-1 infection and HAM/TSP development, suggesting their putative use for clinical monitoring.

Prevalence of adults with type 1 diabetes who meet the goals of care in daily clinical practice: A nationwide multicenter study in Brazil

Objective: To determine the prevalence of patients with type 1 diabetes mellitus who meet the glycemic and cardiovascular (CV) risk factors goals and the frequency of screening for diabetic complications in Brazil according to the American Diabetes Association guidelines. Research design and methods: This was a cross-sectional, multicenter study conducted between December 2008 and December 2010 in 28 public clinics in 20 Brazilian cities. Data were obtained from 1774 adult patients (56.8% females, 57.2% Caucasians) aged 30.3 +/- 9.8 years with diabetes duration of 14.3 +/- 8.8 years. Results: Systolic blood pressure was at goal in 40.3% and diastolic blood pressure was at goal in 26.6% of hypertensive patients. LDL cholesterol and HbA1c were at the goal in 45.2% and 13.2% of the patients, respectively. Overweight was presented in 25.6% and obesity in 6.9%. Among those with more than 5 years of disease, screening for retinopathy was performed in the preceding year in 70.1%. Nephropathy and feet complications were screened in 63.1% and 65.1%, respectively. Conclusions: The majority of patients did not meet metabolic control goals and a substantial proportion was not screened for diabetic complications. These issues may increase the risk of chronic complications and negatively impact public health. (C) 2012 Elsevier Ireland Ltd. All rights reserved.

Automatic design of decision-tree induction algorithms tailored to flexible-receptor docking data

Background: This paper addresses the prediction of the free energy of binding of a drug candidate with enzyme InhA associated with Mycobacterium tuberculosis. This problem is found within rational drug design, where interactions between drug candidates and target proteins are verified through molecular docking simulations. In this application, it is important not only to correctly predict the free energy of binding, but also to provide a comprehensible model that could be validated by a domain specialist. Decision-tree induction algorithms have been successfully used in drug-design related applications, specially considering that decision trees are simple to understand, interpret, and validate. There are several decision-tree induction algorithms available for general-use, but each one has a bias that makes it more suitable for a particular data distribution. In this article, we propose and investigate the automatic design of decision-tree induction algorithms tailored to particular drug-enzyme binding data sets. We investigate the performance of our new method for evaluating binding conformations of different drug candidates to InhA, and we analyze our findings with respect to decision tree accuracy, comprehensibility, and biological relevance. Results: The empirical analysis indicates that our method is capable of automatically generating decision-tree induction algorithms that significantly outperform the traditional C4.5 algorithm with respect to both accuracy and comprehensibility. In addition, we provide the biological interpretation of the rules generated by our approach, reinforcing the importance of comprehensible predictive models in this particular bioinformatics application. Conclusions: We conclude that automatically designing a decision-tree algorithm tailored to molecular docking data is a promising alternative for the prediction of the free energy from the binding of a drug candidate with a flexible-receptor.

Opposing Roles for Cannabinoid Receptor Type-1 (CB1) and Transient Receptor Potential Vanilloid Type-1 Channel (TRPV1) on the Modulation of Panic-Like Responses in Rats

The midbrain dorsal periaqueductal gray (dPAG) has an important role in orchestrating anxiety-and panic-related responses. Given the cellular and behavioral evidence suggesting opposite functions for cannabinoid type 1 receptor (CB1) and transient receptor potential vanilloid type-1 channel (TRPV1), we hypothesized that they could differentially influence panic-like reactions induced by electrical stimulation of the dPAG. Drugs were injected locally and the expression of CB1 and TRPV1 in this structure was assessed by immunofluorescence and confocal microscopy. The CB1-selective agonist, ACEA (0.01, 0.05 and 0.5 pmol) increased the threshold for the induction of panic-like responses solely at the intermediary dose, an effect prevented by the CB1-selective antagonist, AM251 (75 pmol). Panicolytic-like effects of ACEA at the higher dose were unmasked by pre-treatment with the TRPV1 antagonist capsazepine (0.1 nmol). Similarly to ACEA, capsazepine (1 and 10 nmol) raised the threshold for triggering panic-like reactions, an effect mimicked by another TRPV1 antagonist, SB366791 (1 nmol). Remarkably, the effects of both capsazepine and SB366791 were prevented by AM251 (75 pmol). These pharmacological data suggest that a common endogenous agonist may have opposite functions at a given synapse. Supporting this view, we observed that several neurons in the dPAG co-expressed CB1 and TRPV1. Thus, the present work provides evidence that an endogenous substance, possibly anandamide, may exert both panicolytic and panicogenic effects via its actions at CB1 receptors and TRPV1 channels, respectively. This tripartite set-point system might be exploited for the pharmacotherapy of panic attacks and anxiety-related disorders. Neuropsychopharmacology (2012) 37, 478-486; doi:10.1038/npp.2011.207; published online 21 September 2011

Characterization of selectivity and pharmacophores of type 1 sea anemone toxins by screening seven Na-v sodium channel isoforms

During their evolution, animals have developed a set of cysteine-rich peptides capable of binding various extracellular sites of voltage-gated sodium channels (VGSC). Sea anemone toxins that target VGSCs delay their inactivation process, but little is known about their selectivities. Here we report the investigation of three native type 1 toxins (CGTX-II, delta-AITX-Bcg1a and delta-AITX-Bcg1b) purified from the venom of Bunodosoma cangicum. Both delta-AITX-Bcg1a and delta-AITX-Bcg1b toxins were fully sequenced. The three peptides were evaluated by patch-clamp technique among Nav1.1-1.7 isoforms expressed in mammalian cell lines, and their preferential targets are Na(v)1.5 > 1.6 > 1.1. We also evaluated the role of some supposedly critical residues in the toxins which would interact with the channels, and observed that some substitutions are not critical as expected. In addition, CGTX-II and delta-AITX-Bcg1a evoke different shifts in activation/inactivation Boltzmann curves in Nav1.1 and 1.6. Moreover, our results suggest that the interaction region between toxins and VGSCs is not restricted to the supposed site 3 (S3-54 linker of domain IV), and this may be a consequence of distinct surface of contact of each peptide vs. targeted channel. Our data suggest that the contact surfaces of each peptide may be related to their surface charges, as CGTX-II is more positive than delta-AITX-Bcg1a and delta-AITX-Bcg1b. (C) 2011 Elsevier Inc. All rights reserved.

Actions of the Kunitz-type serine protease inhibitor Amblyomin-X on VEGF-A-induced angiogenesis

Amblyomin-X is a Kunitz-type serine protease inhibitor (Kunitz-type SPI) designed from the cDNA library of the Amblyomma cajennense tick, which displays in vivo anti-tumor activities. Here, the mechanisms of actions of Amblyomin-X in vascular endothelial growth factor A (VEGF-A)-induced angiogenesis were characterized. Topical application of Amblyomin-X (10 or 100 ng/10 mu l; each 48 h) inhibited VEGF-A-induced (10 ng/10 mu l; each 48 h) angiogenesis in the dorsal subcutaneous tissue in male Swiss mice. Moreover, similar effect was observed in the VEGF-A-induced angiogenesis in the chicken chorioallantoic membrane (CAM). Additional in vitro assays in t-End cells showed that Amblyomin-X treatment delayed the cell cycle, by maintaining them in G0/G1 phase, and inhibited cell proliferation and adhesion, tube formation and membrane expression of the adhesion molecule platelet-endothelial cell adhesion molecule-1 (PECAM-I), regardless of mRNA synthesis. Together, results herein reveal the role of Kunitz-type SPI on in vivo VEGF-A-induced angiogenesis, by exerting modulatory actions on endothelial cell proliferation and adhesion, especially on membrane expression of PECAM-1. These data provide further mechanisms of actions of Kunitz-type SPI, corroborating their relevance as scientific tools in the design of therapeutic molecules. (C) 2012 Elsevier Ltd. All rights reserved.

Autoantibodies and High-Risk HLA Susceptibility Markers in First-Degree Relatives of Brazilian Patients with Type 1 Diabetes Mellitus: A Progression to Disease Based Study

The objective of this study was to determine the frequencies of autoantibodies to heterogeneous islet-cell cytoplasmic antigens (ICA), glutamic acid decarboxylase(65) (GAD(65)A), insulinoma-associated antigen-2 (IA-2A) and insulin (IAA)-and human leukocyte antigen (HLA) class II markers (HLA-DR and -DQ) in first degree relatives of heterogeneous Brazilian patients with type I diabetes(T1DM). A major focus of this study was to determine the influence of age, gender, proband characteristics and ancestry on the prevalence of autoantibodies and HLA-DR and -DQ alleles on disease progression and genetic predisposition to T1DM among the first-degree relatives. IAA, ICA, GAD(65)A, IA-2A and HLA- class II alleles were determined in 546 first-degree-relatives, 244 siblings, 55 offspring and 233 parents of 178 Brazilian patients with T1DM. Overall, 8.9% of the relatives were positive for one or more autoantibodies. IAA was the only antibody detected in parents. GAD(65) was the most prevalent antibody in offspring and siblings as compared to parents and it was the sole antibody detected in offspring. Five siblings were positive for the IA-2 antibody. A significant number (62.1%) of siblings had 1 or 2 high risk HLA haplotypes. During a 4-year follow-up study, 5 siblings (expressing HLA-DR3 or -DR4 alleles) and 1 offspring positive for GAD(65)A progressed to diabetes. The data indicated that the GAD(65) and IA-2 antibodies were the strongest predictors of T1DM in our study population. The high risk HLA haplotypes alone were not predictive of progression to overt diabetes.

Interleukin-18 and interferon-gamma polymorphisms are implicated on proviral load and susceptibility to human T-lymphotropic virus type 1 infection

Interleukin-18 (IL-18) and interferon-gamma (IFN-?) exert important functions in both innate and adaptive immune responses against intracellular pathogens and viruses. Previous studies suggested that host genetic factors, including cytokines gene polymorphisms, could be involved in the pathogenesis of human T-cell leukemia virus type 1 (HTLV-1)-associated myelopathy/tropical spastic paraparesis (HAM/TSP). Thus, we analyzed -137C/G and -607A/C of the IL-18 promoter and +874T/A of the IFN-? in DNA samples from 98 HTLV-1-infected individuals exhibiting or not clinical symptoms and 150 healthy control individuals. The IL-18 promoter -607CC genotype was significantly lower in HTLV-1 asymptomatic carriers (HAC) and HTLV-1-infected individuals (HAC + HAM/TSP) than healthy control group. In contrast, the -607AC genotype was significantly higher in HAC and HTLV-1-infected individuals group compared to the healthy control group. The -137G/-607A IL-18 haplotype was higher in infected group than healthy control group, and the -137C/-607C IL-18 haplotype was increased in the healthy control group compared to the others. Finally, the IFN-? polymorphism analysis showed that the HTLV-1-infected individuals with +874AT genotype presented higher proviral load than +874AA genotype. These data indicate that the IL-18-607AC genotype and -137G/-607A haplotype could be a risk factor for HTLV-1 infection, whereas the protective effect could be conferred by -607CC genotype and -137C/-607C haplotype. Also, the IFN-? could be implicated on the proviral load levels.

Network-based high level data classification

Traditional supervised data classification considers only physical features (e. g., distance or similarity) of the input data. Here, this type of learning is called low level classification. On the other hand, the human (animal) brain performs both low and high orders of learning and it has facility in identifying patterns according to the semantic meaning of the input data. Data classification that considers not only physical attributes but also the pattern formation is, here, referred to as high level classification. In this paper, we propose a hybrid classification technique that combines both types of learning. The low level term can be implemented by any classification technique, while the high level term is realized by the extraction of features of the underlying network constructed from the input data. Thus, the former classifies the test instances by their physical features or class topologies, while the latter measures the compliance of the test instances to the pattern formation of the data. Our study shows that the proposed technique not only can realize classification according to the pattern formation, but also is able to improve the performance of traditional classification techniques. Furthermore, as the class configuration's complexity increases, such as the mixture among different classes, a larger portion of the high level term is required to get correct classification. This feature confirms that the high level classification has a special importance in complex situations of classification. Finally, we show how the proposed technique can be employed in a real-world application, where it is capable of identifying variations and distortions of handwritten digit images. As a result, it supplies an improvement in the overall pattern recognition rate.

Competing regression models for longitudinal data

The choice of an appropriate family of linear models for the analysis of longitudinal data is often a matter of concern for practitioners. To attenuate such difficulties, we discuss some issues that emerge when analyzing this type of data via a practical example involving pretestposttest longitudinal data. In particular, we consider log-normal linear mixed models (LNLMM), generalized linear mixed models (GLMM), and models based on generalized estimating equations (GEE). We show how some special features of the data, like a nonconstant coefficient of variation, may be handled in the three approaches and evaluate their performance with respect to the magnitude of standard errors of interpretable and comparable parameters. We also show how different diagnostic tools may be employed to identify outliers and comment on available software. We conclude by noting that the results are similar, but that GEE-based models may be preferable when the goal is to compare the marginal expected responses.

Enhancing health care for type 2 diabetes in Northern Brazil: A pilot study of pharmaceutical care in community pharmacy

To evaluate the impact of a medication therapy management (MTM) program on the clinical outcomes and the quality of life (QoL) of a group of elderly patients with type 2 diabetes mellitus (DM). The study was conducted in a community pharmacy in Aracaju, Brazil, from February to November 2009. A quasi-experimental, longitudinal, prospective study was conducted by intervention. The group patients received medication therapy management from a clinical pharmacist. A sample of convenience was obtained for patients of both genders aged from 60 to 75 years. Monthly visits were scheduled over 10 months. At these consultations, sociodemographic, clinical data were obtained. QoL assessment was conducted using a generic instrument-the Medical Outcomes Studies 36-item Short Form Survey (SF-36 (R)). In total, 34 completed the study. The mean age of the patients was 65.9 (4.7) years. In total, 117 DRPs were identified. Patients' baseline and final evaluation measures for glycosylated hemoglobin, capillary blood glucose, blood pressure, and waist circumference were significantly different (p < 0.05). The domains of QoL assessed by the SF-36 (R) also shows significant differences between patients' baseline and final evaluation scores. The co-responsibility and active participation on the part of the elderly may have helped pharmacotherapy achieve its clinical and humanistic aims.

COMPLETE H-1 AND C-13 NMR STRUCTURAL ASSIGNMENTS FOR A GROUP OF FOUR GOYAZENSOLIDE-TYPE FURANOHELIANGOLIDES

Four goyazensolide-type sesquiterpene lactones - lychnofolide, centratherin, goyazensolide and goyazensolide acetate - were thoroughly studied by NMR experimental techniques. H-1 NMR, C-13 NMR {H-1}, COSY, HMQC, HMBC, J-res. and NOE experiments were performed to provide the needed structural information. Complete and unequivocal assignment, including the determination of all multiplicities, was obtained for each structure and the data collections are presented in tables.

Colibacillosis in lambs is associated to type I heat-stable enterotoxin in a farm in Sao Paulo State, Brazil

Twenty seven (48.2%) culture supernatants of 56 Escherichia coli isolated from diarrheic lamb feces (7 to 10 days old) in Sao Paulo State, Brazil, presented positive results to suckling mice assay (fluid accumulation) but none caused cytopathic effects on Vero and CHO cells, indicating that these strains did not produced LT or VT toxins. PCR assays showed that these 27 E. coli strains harbored estA, that codifies for STa, but not for stx1, stx2 or cnf genes. The positive STa strains were checked for genes that codify for F41, F17 and K99 fimbriae, wich are considered colonization factors in ETEC. Only F17 was detect in two samples (7.4%). Twelve of 27 STa positive carried hlyA gene and presented hemolytic activity in blood Agar. Presence of rotavirus was not detected among the diarrheic feces. These data suggests that STa must be an important diarrheagenic factor to small ruminants in Sao Paulo State.

Constraining the dark energy and smoothness parameter with type Ia supernovae and gamma-ray bursts

The existence of inhomogeneities in the observed Universe modifies the distance-redshift relations thereby affecting the results of cosmological tests in comparison to the ones derived assuming spatially uniform models. By modeling the inhomogeneities through a Zeldovich-Kantowski-Dyer-Roeder approach which is phenomenologically characterized by a smoothness parameter alpha, we rediscuss the constraints on the cosmic parameters based on type Ia supernovae (SNe Ia) and gamma-ray bursts (GRBs) data. The present analysis is restricted to a flat Lambda CDM model with the reasonable assumption that Lambda does not clump. A chi(2) analysis using 557 SNe Ia data from the Union2 compilation data (R. Amanullah et al., Astrophys. J. 716, 712 (2010).) constrains the pair of parameters (Omega(m), alpha) to Omega(m) = 0.27(-0.03)(+0.08) (2 sigma) and alpha >= 0.25. A similar analysis based only on 59 Hymnium GRBs (H. Wei, J. Cosmol. Astropart. Phys. 08 (2010) 020.) constrains the matter density parameter to be Omega(m) = 0.35(-0.24)(+0.62) (2 sigma) while all values for the smoothness parameter are allowed. By performing a joint analysis, it is found that Omega(m) = 0.27(-0.06)(+0.06) and alpha >= 0.52. As a general result, although considering that current GRB data alone cannot constrain the smoothness alpha parameter, our analysis provides an interesting cosmological probe for dark energy even in the presence of inhomogeneities.

Stem cell therapy for type 1 diabetes mellitus: a review of recent clinical trials

Stem cell therapy is one of the most promising treatments for the near future. It is expected that this kind of therapy can ameliorate or even reverse some diseases. With regard to type 1 diabetes, studies analyzing the therapeutic effects of stem cells in humans began in 2003 in the Hospital das Clínicas of the Faculty of Medicine of Ribeirão Preto - SP USP, Brazil, and since then other centers in different countries started to randomize patients in their clinical trials. Herein we summarize recent data about beta cell regeneration, different ways of immune intervention and what is being employed in type 1 diabetic patients with regard to stem cell repertoire to promote regeneration and/or preservation of beta cell mass.