Endothelial Nitric Oxide Genotypes and Haplotypes Are Not Associated with End-Stage Renal Disease

The identification of genetic markers associated with chronic kidney disease (CKD) may help to predict its development. Because reduced nitric oxide (NO) bioavailability and endothelial dysfunction are involved in CKD, genetic polymorphisms in the gene encoding the enzyme involved in NO synthesis (endothelial NO synthase [eNos]) may affect the susceptibility to CKD and the development of end-stage renal disease (ESRD). We compared genotype and haplotype distributions of three relevant eNOS polymorphisms (T(-786) C in the promoter region, Glu298Asp in exon 7, and 4b/4a in intron 4) in 110 healthy control subjects and 127 ESRD patients. Genotypes for the T(-786) C and Glu298Asp polymorphisms were determined by TaqMan (R) Allele Discrimination assay and real-time polymerase chain reaction. Genotypes for the intron 4 polymorphism were determined by polymerase chain reaction and fragment separation by electrophoresis. The software program PHASE 2.1 was used to estimate the haplotypes frequencies. We considered significant a probability value of p < 0.05/number of haplotypes (p < 0.05/8 = 0.0063). We found no significant differences between groups with respect to age, ethnicity, and gender. CKD patients had higher blood pressure, total cholesterol, and creatinine levels than healthy control subjects (all p < 0.05). Genotype and allele distributions for the three eNOS polymorphisms were similar in both groups (p > 0.05). We found no significant differences in haplotype distribution between groups (p > 0.05). The lack of significant associations between eNOS polymorphisms and ESRD suggests that eNOS polymorphisms may not be relevant to the genetic component of CKD that leads to ESRD.

Endothelial Nitric Oxide Synthase Haplotypes Associated with Aura in Patients with Migraine

There is strong evidence implicating nitric oxide (NO) in the pathophysiology of migraine and aura. Therefore, genetic polymorphisms in the endothelial NO synthase (eNOS) gene have been studied as candidate markers for migraine susceptibility. We compared for the first time the distribution of eNOS haplotypes including the three clinically relevant eNOS polymorphisms (T(-786)C in the promoter, rs2070744; Glu298Asp in exon 7, rs1799983; and a 27 bp variable number of tandem repeats in intron 4) and two additional tagging single-nucleotide polymorphisms (rs3918226 and rs743506) in 178 women with migraine (134 without aura and 44 with aura) and 117 healthy controls (control group). Genotypes were determined by TaqMan allele discrimination assay, real-time polymerase chain reaction, and polymerase chain reaction followed by fragment separation by electrophoresis. The GA (rs743506) genotype was more common in the control group than in women with migraine (odds ratio = 0.47, 95% confidence interval [CI] 0.29-0.78, p<0.01). No significant differences were found in allele distributions for the five eNOS polymorphisms. However, the haplotypes including the variants ""C C a Glu G"" and the variants ""C C b Glu G"" were more common in women with migraine with aura than in women with migraine without aura (odds ratio = 30.71, 95% CI = 1.61-586.4 and odds ratio = 17.26, 95% CI = 1.94-153.4, respectively; both p<0.0015625). These findings suggest that these two eNOS haplotypes affect the susceptibility to the presence of aura in patients with migraine.

A simplified minimal residual disease polymerase chain reaction method at early treatment points can stratify children with acute lymphoblastic leukemia into good and poor outcome groups

Background Minimal residual disease is an important independent prognostic factor in childhood acute lymphoblastic leukemia. The classical detection methods such as multiparameter flow cytometry and real-time quantitative polymerase chain reaction analysis are expensive, time-consuming and complex, and require considerable technical expertise. Design and Methods We analyzed 229 consecutive children with acute lymphoblastic leukemia treated according to the GBTLI-99 protocol at three different Brazilian centers. Minimal residual disease was analyzed in bone marrow samples at diagnosis and on days 14 and 28 by conventional homo/heteroduplex polymerase chain reaction using a simplified approach with consensus primers for IG and TCR gene rearrangements. Results At least one marker was detected by polymerase chain reaction in 96.4%, of the patients. By combining the minimal residual disease results obtained on days 14 and 28, three different prognostic groups were identified: minimal residual disease negative on days 14 and 28, positive on day 14/negative on day 28, and positive on both. Five-year event-free survival rates were 85%, 75.6%,, and 27.8%, respectively (p<0.0001). The same pattern of stratification held true for the group of intensively treated children. When analyzed in other subgroups of patients such as those at standard and high risk at diagnosis, those with positive B-derived CD10, patients positive for the TEL/AML1 transcript, and patients in morphological remission on a day 28 marrow, the event-free survival rate was found to be significantly lower in patients with positive minimal residual disease on day 28. Multivariate analysis demonstrated that the detection of minimal residual disease on day 28 is the most significant prognostic factor. Conclusions This simplified strategy for detection of minimal residual disease was feasible, reproducible, cheaper and simpler when compared with other methods, and allowed powerful discrimination between children with acute lymphoblastic leukemia with a good and poor outcome.

Tumor slices as a model to evaluate doxorubicin in vitro treatment and expression of trios of genes PRSS11, MTSS1, CLPTM1 and PRSS11, MTSS1, SMYD2 in canine mammary gland cancer

Background: In women with breast cancer submitted to neoadjuvant chemotherapy based in doxorubicin, tumor expression of groups of three genes (PRSS11, MTSS1, CLPTM1 and PRSS11, MTSS1, SMYD2) have classified them as responsive or resistant. We have investigated whether expression of these trios of genes could predict mammary carcinoma response in dogs and whether tumor slices, which maintain epithelial-mesenchymal interactions, could be used to evaluate drug response in vitro. Methods: Tumors from 38 dogs were sliced and cultured with or without doxorubicin 1 mu M for 24 h. Tumor cells were counted by two observers to establish a percentage variation in cell number, between slices. Based on these results, a reduction in cell number between treated and control samples >= 21.7%, arbitrarily classified samples, as drug responsive. Tumor expression of PRSS11, MTSS1, CLPTM1 and SMYD2, was evaluated by real time PCR. Relative expression results were then transformed to their natural logarithm values, which were spatially disposed according to the expression of trios of genes, comprising PRSS11, MTSS1, CLPTM1 and PRSS11, MTSS1, SMYD2. Fisher linear discrimination test was used to generate a separation plane between responsive and non-responsive tumors. Results: Culture of tumor slices for 24 h was feasible. Nine samples were considered responsive and 29 non-responsive to doxorubicin, considering the pre-established cut-off value of cell number reduction = 21.7%, between doxorubicin treated and control samples. Relative gene expression was evaluated and tumor samples were then spatially distributed according to the expression of the trios of genes: PRSS11, MTSS1, CLPTM1 and PRSS11, MTSS1, SMYD2. A separation plane was generated. However, no clear separation between responsive and non-responsive samples could be observed. Conclusion: Three-dimensional distribution of samples according to the expression of the trios of genes PRSS11, MTSS1, CLPTM1 and PRSS11, MTSS1, SMYD2 could not predict doxorubicin in vitro responsiveness. Short term culture of mammary gland cancer slices may be an interesting model to evaluate chemotherapy activity.

Plasma Superoxide Dismutase-1 as a Surrogate Marker of Vivax Malaria Severity

Background: Severe outcomes have been described for both Plasmodium falciparum and P. vivax infections. The identification of sensitive and reliable markers of disease severity is fundamental to improving patient care. An intense pro-inflammatory response with oxidative stress and production of reactive oxygen species is present in malaria. Inflammatory cytokines such as tumor necrosis factor-alpha (TNF-alpha) and antioxidant agents such as superoxide dismutase-1 (SOD-1) are likely candidate biomarkers for disease severity. Here we tested whether plasma levels of SOD-1 could serve as a biomarker of severe vivax malaria. Methodology/Principal Findings: Plasma samples were obtained from residents of the Brazilian Amazon with a high risk for P. vivax transmission. Malaria diagnosis was made by both microscopy and nested PCR. A total of 219 individuals were enrolled: non-infected volunteers (n = 90) and individuals with vivax malaria: asymptomatic (n = 60), mild (n = 50) and severe infection (n = 19). SOD-1 was directly associated with parasitaemia, plasma creatinine and alanine amino-transaminase levels, while TNF-alpha correlated only with the later enzyme. The predictive power of SOD-1 and TNF-alpha levels was compared. SOD-1 protein levels were more effective at predicting vivax malaria severity than TNF-alpha. For discrimination of mild infection, elevated SOD-1 levels showed greater sensitivity than TNF-alpha (76% vs. 30% respectively; p < 0.0001), with higher specificity (100% vs. 97%; p < 0.0001). In predicting severe vivax malaria, SOD-1 levels exhibited higher sensitivity than TNF-alpha (80% vs. 56%, respectively; p < 0.0001; likelihood ratio: 7.45 vs. 3.14; p, 0.0001). Neither SOD-1 nor TNF-alpha could discriminate P. vivax infections from those caused by P. falciparum. Conclusion: SOD-1 is a powerful predictor of disease severity in individuals with different clinical presentations of vivax malaria.

Characterizing chaotic melodies in automatic music composition

In this paper, we initially present an algorithm for automatic composition of melodies using chaotic dynamical systems. Afterward, we characterize chaotic music in a comprehensive way as comprising three perspectives: musical discrimination, dynamical influence on musical features, and musical perception. With respect to the first perspective, the coherence between generated chaotic melodies (continuous as well as discrete chaotic melodies) and a set of classical reference melodies is characterized by statistical descriptors and melodic measures. The significant differences among the three types of melodies are determined by discriminant analysis. Regarding the second perspective, the influence of dynamical features of chaotic attractors, e.g., Lyapunov exponent, Hurst coefficient, and correlation dimension, on melodic features is determined by canonical correlation analysis. The last perspective is related to perception of originality, complexity, and degree of melodiousness (Euler's gradus suavitatis) of chaotic and classical melodies by nonparametric statistical tests. (c) 2010 American Institute of Physics. [doi: 10.1063/1.3487516]

Generalized connectivity between any two nodes in a complex network

This article focuses on the identification of the number of paths with different lengths between pairs of nodes in complex networks and how these paths can be used for characterization of topological properties of theoretical and real-world complex networks. This analysis revealed that the number of paths can provide a better discrimination of network models than traditional network measurements. In addition, the analysis of real-world networks suggests that the long-range connectivity tends to be limited in these networks and may be strongly related to network growth and organization.

Protein-polysaccharide viscoelastic matrices: synergic effects of amylose on lysozyme physical gelation in aqueous dimethylsulfoxide

A synergic effect of amylose on rheological characteristics of lysozyme physical gels evolved out of dimethylsulfoxide-water was verified and analyzed. The dynamics of the gels were experimentally approached by oscillatory rheology. The synergic effect was characterized by a decrease in the threshold DMSO volume fraction required for lysozyme gelation, and by a significant strengthening of the gel structure at over-critical solvent and protein concentrations. Drastic changes in the relaxation and creep curve patterns for systems in the presence of amylose were verified. Complex viscosity dependence on temperature was found to conform to an Arrhenius-like equation, allowing the determination of an activation energy term (Ea, apparent) for discrimination of gel rigidity. A dilatant effect was found to be induced by temperature on the flow behavior of lysozyme dispersions in DMSO-H(2)O in sub-critical conditions for gelation, which was greatly intensified by the presence of amylose in the samples. That transition was interpreted as reflecting a change from a predominant colloidal flow regime, where globular components are the prevailing structural elements, to a mainly fibrillar, polymeric flow behavior.

Self-organized distribution of periodicity and chaos in an electrochemical oscillator

We report a detailed numerical investigation of a prototype electrochemical oscillator, in terms of high-resolution phase diagrams for an experimentally relevant section of the control (parameter) space. The prototype model consists of a set of three autonomous ordinary differential equations which captures the general features of electrochemical oscillators characterized by a partially hidden negative differential resistance in an N-shaped current-voltage stationary curve. By computing Lyapunov exponents, we provide a detailed discrimination between chaotic and periodic phases of the electrochemical oscillator. Such phases reveal the existence of an intricate structure of domains of periodicity self-organized into a chaotic background. Shrimp-like periodic regions previously observed in other discrete and continuous systems were also observed here, which corroborate the universal nature of the occurrence of such structures. In addition, we have also found a structured period distribution within the order region. Finally we discuss the possible experimental realization of comparable phase diagrams.

Determination of the geographical origin of Brazilian wines by isotope and mineral analysis

In the present research, we studied wines from three different south Brazilian winemaking regions with the purpose of differentiating them by geographical origin of the grapes. Brazil`s wide territory and climate diversity allow grape cultivation and winemaking in many regions of different and unique characteristics. The wine grape cultivation for winemaking concentrates in the South Region, mainly in the Serra GaA(0)cha, the mountain area of the state of Rio Grande do Sul, which is responsible for 90% of the domestic wine production. However, in recent years, two new production regions have developed: the Campanha, the plains to the south and the Serra do Sudeste, the hills to the southeast of the state. Analysis of isotopic ratios of (18)O/(16)O of wine water, (13)C/(12)C of ethanol, and of minerals were used to characterize wines from different regions. The isotope analysis of delta(18)O of wine water and minerals Mg and Rb were the most efficient to differentiate the regions. By using isotope and mineral analysis, and discrimination analysis, it was possible to classify the wines from south Brazil.

Laser-induced breakdown spectroscopy and chemometrics for classification of toys relying on toxic elements

Quality control of toys for avoiding children exposure to potentially toxic elements is of utmost relevance and it is a common requirement in national and/or international norms for health and safety reasons. Laser-induced breakdown spectroscopy (LIBS) was recently evaluated at authors` laboratory for direct analysis of plastic toys and one of the main difficulties for the determination of Cd. Cr and Pb was the variety of mixtures and types of polymers. As most norms rely on migration (lixiviation) protocols, chemometric classification models from LIBS spectra were tested for sampling toys that present potential risk of Cd, Cr and Pb contamination. The classification models were generated from the emission spectra of 51 polymeric toys and by using Partial Least Squares - Discriminant Analysis (PLS-DA), Soft Independent Modeling of Class Analogy (SIMCA) and K-Nearest Neighbor (KNN). The classification models and validations were carried out with 40 and 11 test samples, respectively. Best results were obtained when KNN was used, with corrected predictions varying from 95% for Cd to 100% for Cr and Pb. (C) 2011 Elsevier B.V. All rights reserved.

Breastfeeding, sleep and wake circadian rhythms show distinct temporal emerging patterns

The emerging patterns of breastfeeding, sleep and wake circadian rhythms in an infant and the breastfeeding emergence pattern of his elder sister are presented. Both children were raised under regular contact with photic and non-photic Zeitgebers. Data are related to the first four months of life of the infants, which correspond to the exclusive and ad libitum breastfeeding stage of their lives. Discrimination is made of fasting-associated-wakefulness (FAW) which is a wake state without feeding. Our data show that while FAW episodes are concentrated in the diurnal phase of the day since the first week of life, breastfeeding rhythm takes longer to show statistically significant circadian periodicity (four weeks) and to become monophasic, concentrated in the diurnal phase of the day (three/four months). This precedence of the consolidation of FAW rhythm indicates tight association between nocturnal sleep fragmentation and the drive to feed, in the first months of life of infants.

COMPARATIVE STUDY OF THE SENSITIVITY OF DIABETIC LOWER EXTREMITIES WITH AND WITHOUT ULCERS USING THE PSSD (TM)

Introduction To determine and compare thresholds of cutaneous sensitivity of lower extremities in diabetic patients with an ulcer on only one lower extremity Methods and Materials The study group included 20 patients with mean age of 61 6 and average time with diabetes of 12 4 years All patients were previously tested using Semmes-Weinstein monofilament 5 07 Sensitivity was evaluated using the two point discrimination test and the PSSD (TM) (Pressure-Specified Sensory Device) in order to assess touch thresholds in a quantitative manner, in g/mm(2) Three skin areas were tested hallux pulp, dorsum of foot and medial heel, including four tests 1 point static, 1 point moving, 2 points static and 2 points moving Results Mean 2 point discrimination distance in mm was higher in feet with ulcers, but the difference between extremities was only statistically significant for the hallux. With the PSSD (TM), all patients had higher pressure thresholds in feet with ulcers when compared with feet without ulcers, in all tests, with statistical significance Conclusion The PSSD (TM) was able to differentiate levels of sensation between extremities with and without ulcers in diabetic patients, with statistical significance

Power Transformer Differential Protection Based on Clarke`s Transform and Fuzzy Systems

The power transformer is a piece of electrical equipment that needs continuous monitoring and fast protection since it is very expensive and an essential element for a power system to perform effectively. The most common protection technique used is the percentage differential logic, which provides discrimination between an internal fault and different operating conditions. Unfortunately, there are some operating conditions of power transformers that can affect the protection behavior and the power system stability. This paper proposes the development of a new algorithm to improve the differential protection performance by using fuzzy logic and Clarke`s transform. An electrical power system was modeled using Alternative Transients Program (ATP) software to obtain the operational conditions and fault situations needed to test the algorithm developed. The results were compared to a commercial relay for validation, showing the advantages of the new method.

Using Bayesian networks with rule extraction to infer the risk of weed infestation in a corn-crop

This paper describes the modeling of a weed infestation risk inference system that implements a collaborative inference scheme based on rules extracted from two Bayesian network classifiers. The first Bayesian classifier infers a categorical variable value for the weed-crop competitiveness using as input categorical variables for the total density of weeds and corresponding proportions of narrow and broad-leaved weeds. The inferred categorical variable values for the weed-crop competitiveness along with three other categorical variables extracted from estimated maps for the weed seed production and weed coverage are then used as input for a second Bayesian network classifier to infer categorical variables values for the risk of infestation. Weed biomass and yield loss data samples are used to learn the probability relationship among the nodes of the first and second Bayesian classifiers in a supervised fashion, respectively. For comparison purposes, two types of Bayesian network structures are considered, namely an expert-based Bayesian classifier and a naive Bayes classifier. The inference system focused on the knowledge interpretation by translating a Bayesian classifier into a set of classification rules. The results obtained for the risk inference in a corn-crop field are presented and discussed. (C) 2009 Elsevier Ltd. All rights reserved.