Understanding the Effect of Adsorption Geometry over Substrate Selectivity in the Surface-Enhanced Raman Scattering Spectra of Simazine and Atrazine

This paper studies the selectivity of Well-defined Au and Ag nanostructures as substrates for the SERS, (surface-enhanced Raman scattering) detection of simazine (6-chloro-N,N`-diethyl-1,3,5-triazine-2,4-diamine) and atrazine (6-chloro-N-ethyl-N`-isopropyl-1,3,5-triazine-2,4-diamine). Our data showed that simazine and atrazine displayed similar SERS spectra when the Au was employed as substrate. Conversely, distinct SERS signatures were obtained upon the utilization of Ag substrates. Density functional theory (DFT) calculations and vibrational assignments suggested that, while simazine and atrazine adsorbed on Au via the N3 position of the triazine ring, simazine adsorbed on Ag via N3 and atrazine via N5. The results presented herein demonstrated that the adsorption geometry of analyte molecules can play a central role over substrate selectivity in SERS, which is particularly important in applications involving ultrasensitive analysis of mixtures containing structurally similar molecules.

Artificial Neural Networks and the Study of the Psychoactivity of Cannabinoid Compounds

Cannabinoid compounds have widely been employed because of its medicinal and psychotropic properties. These compounds are isolated from Cannabis sativa (or marijuana) and are used in several medical treatments, such as glaucoma, nausea associated to chemotherapy, pain and many other situations. More recently, its use as appetite stimulant has been indicated in patients with cachexia or AIDS. In this work, the influence of several molecular descriptors on the psychoactivity of 50 cannabinoid compounds is analyzed aiming one obtain a model able to predict the psychoactivity of new cannabinoids. For this purpose, initially, the selection of descriptors was carried out using the Fisher`s weight, the correlation matrix among the calculated variables and principal component analysis. From these analyses, the following descriptors have been considered more relevant: E(LUMO) (energy of the lowest unoccupied molecular orbital), Log P (logarithm of the partition coefficient), VC4 (volume of the substituent at the C4 position) and LP1 (Lovasz-Pelikan index, a molecular branching index). To follow, two neural network models were used to construct a more adequate model for classifying new cannabinoid compounds. The first model employed was multi-layer perceptrons, with algorithm back-propagation, and the second model used was the Kohonen network. The results obtained from both networks were compared and showed that both techniques presented a high percentage of correctness to discriminate psychoactive and psychoinactive compounds. However, the Kohonen network was superior to multi-layer perceptrons.

Relationship between periodontitis and rheumatoid arthritis and the effect of non-surgical periodontal treatment

This study analyzed the association of periodontal disease (PD) and rheumatoid arthritis (RA). Seventy-five 35-60-year-old patients were assigned to 5 groups according to the presence (+) or not (-) of PD and RA and the treatment received (TR+) or not (TR-) for PD. Group 3 uses total prosthesis (TP). Clinical and laboratory evaluations were performed at baseline, 3 and 6 months of follow-up by probing pocket depth, bleeding on probing and plaque index for PD, HAQ, DAS28, SF-36 and laboratory: AAG, ESR, CRP for RA. Statistically significant differences for PD after 3 (p=0.0055) and after 6 months (p=0.0066) were obtained in Group 1 (RA+PD+TR+) and 2(RA+PD+TR-); significant reduction in the % of BOP after 6 months (p=0.0128) and significant reduction in the % of Pl after 3 (p=0.0128) and 6 months (p=0.0002) in Group 1. Statistically significant differences between Groups 1 and 3 (RA+TP) for DAS28 at baseline and after 3 months were observed, but not after 6 months. No other parameters for RA were significantly affected. The relationship between RA and PD disease activities is not clear, but the importance of periodontal treatment in the control of inflammation to avoid tooth extraction is evident.

Influence of dental metallic artifact from multislice CT in the assessment of simulated mandibular lesions

OBJECTIVE: This study evaluated the influence of metallic dental artifacts on the accuracy of simulated mandibular lesion detection by using multislice technology. MATERIAL AND METHODS: Fifteen macerated mandibles were used. Perforations were done simulating bone lesions and the mandibles were subjected to axial 16 rows multislice CT images using 0.5 mm of slice thickness with 0.3 mm interval of reconstruction. Metallic dental restorations were done and the mandibles were subjected again to CT in the same protocol. The images were analyzed to detect simulated lesions in the mandibles, verifying the loci number and if there was any cortical perforation exposing medullar bone. The analysis was performed by two independent examiners using e-film software. RESULTS: The samples without artifacts presented better results compared to the gold standard (dried mandible with perforations). In the samples without artifacts, all cortical perforation were identified and 46 loci were detected (of 51) in loci number analysis. Among the samples with artifacts, 12 lesions out of 14 were recognized regarding medullar invasion, and 40 out of 51 concerning loci number. The sensitivity in samples without artifacts was 90% and 100% regarding loci number and medullar invasion, respectively. In samples with artifacts, these values dropped to 78% and 86%, respectively. The presence of metallic restorations affected the sensitivity values of the method, but the difference was not significant (p>0.05). CONCLUSIONS: Although there were differences in the results of samples with and without artifacts, the presence of metallic restoration did not lead to misinterpretation of the final diagnosis. However, the validity of multislice CT imaging in this study was established for detection of simulated mandibular bone lesions.

The ichthyofauna of upper rio Capivari: defining conservation strategies based on the composition and distribution of fish species

Although the rio Capivari basin is recognized as an area of great importance for the ichthyofauna, it lacks virtually every basic requirement for the definition of appropriate conservation strategies, since not even its species composition is known. The objective of this work is to determine the composition and distribution of fish species in the upper rio Capivari basin, relating them to the local physical features, and to evaluate the effectiveness of proposed conservations units, delimited based on areas of native vegetation remains, on the conservation of local ichthyofauna. During 2007, 50 different watercourses were sampled with gillnets, cast nets and kick nets. A total of 1308 individuals belonging to 41 species were captured. Degree of conservation, altitude and width were the parameters that best explained fish species richness. Considering the recently proposed boundaries for potential conservation units in the region only 15 or 20 out of 41 species would be found in the State Park and Environmental Protection Area respectively. In practice, the proposed conservation units would not be effective tools for fish conservation, since it would be located in mountainous areas of high altitude, of headwaters streams and where few species are found. In such context, the conservation of specific stretches of larger rivers is critical.

Assessing the validity of a food frequency questionnaire among low-income women in São Paulo, southeastern Brazil

This study describes the validity of a food frequency questionnaire (FFQ) in 93 low-income women (20-65 years), participating in a case-control study in São Paulo, Brazil. Two FFQ (FFQ1 and FFQ2, 12 months apart) and three 24-hour dietary recalls (24hR) were conducted between 2003 and 2004 to estimate dietary intake during the past year. The Pearson correlation coefficients (crude, energy-adjusted and de-attenuated) were used for comparisons between FFQ and 24hR. The agreement between the methods was further examined by the Bland-Altman analysis. For the assessment of long-term reliability, the energy-adjusted intra-class correlation coefficients were mostly around 0.40, but higher for vitamin A and folate (0.50-0.56). Energy-adjusted, attenuation-corrected Pearson validity correlations between FFQ and DR ranged from 0.30-0.54 for macronutrients to 0.20-0.48 for micronutrients, with higher value for calcium (0.75). There were small proportions of grossly misclassified nutrient intakes, while Bland-Altman plots indicated that the FFQ is accurate in assessing nutrient intake at a group level.

Evaluation technique for determining wheel performance in the grinding of aerospace materials

Nickel-based super alloys are used in a variety of applications in which high-temperature strength and resistance to creep, corrosion, and oxidation are required, such as in aircraft gas turbines, combustion chambers, and automotive engine valves. The properties that make these materials suitable for these applications also make them difficult to grind. Grinding systems for such materials are often built around vitrified cBN (cubic boron nitride) wheels to realize maximum productivity and minimum cost per part. Conditions that yield the most economical combination of stock removal rate and wheel wear are key to the successful implementation of the grinding system. Identifying the transition point for excessive wheel wear is important. The aim of this study is to compare the performance of different cBN wheels when grinding difficult-to-grind (DTG) materials by determining the 'wheel wear characteristic curve', which correlates the G-ratio to the calculated tangential force per abrasive grain. With the proposed methodology, a threshold force per grit above which the wheel wear rate increases rapidly can be quickly identified. A comparison of performance for two abrasive product formulations in the grinding of three materials is presented. The obtained results can be applied for the development of grinding applications for DTG materials.

The Effect of Spatial Scale on Predicting Time Series: A Study on Epidemiological System Identification

A susceptible-infective-recovered (SIR) epidemiological model based on probabilistic cellular automaton (PCA) is employed for simulating the temporal evolution of the registered cases of chickenpox in Arizona, USA, between 1994 and 2004. At each time step, every individual is in one of the states S, I, or R. The parameters of this model are the probabilities of each individual (each cell forming the PCA lattice ) passing from a state to another state. Here, the values of these probabilities are identified by using a genetic algorithm. If nonrealistic values are allowed to the parameters, the predictions present better agreement with the historical series than if they are forced to present realistic values. A discussion about how the size of the PCA lattice affects the quality of the model predictions is presented. Copyright (C) 2009 L. H. A. Monteiro et al.

Democracy on the edge: limits and possibilities for the implementation of an urban reform agenda in Brazil

In Brazil the 1990s constituted years of institutional achievements in the fields of housing and urban rights, given the incorporation of the principles of the social function of cities and property, the recognition of tenure rights for slum dwellers and the direct participation of citizens in the decision making process of urban policies, within the 1988 Constitution. These proposals have become the pillars of the Urban Reform agenda which has penetrated the federal government apparatus since the creation of the Ministry of Cities under Lula's administration. The article evaluates the limits and possibilities for the implementation of this agenda through the analysis of two policies proposed by the Ministry: the National Council of Cities and the campaign for Participatory Master Plans. The approach is based on the organization of the Brazilian State in terms of urban development, the relationship with the political system and the characteristics of Brazilian democracy.

Cosmic distance duality relation and the shape of galaxy clusters

Context. Observations in the cosmological domain are heavily dependent on the validity of the cosmic distance-duality (DD) relation, eta = D(L)(z)(1+ z)(2)/D(A)(z) = 1, an exact result required by the Etherington reciprocity theorem where D(L)(z) and D(A)(z) are, respectively, the luminosity and angular diameter distances. In the limit of very small redshifts D(A)(z) = D(L)(z) and this ratio is trivially satisfied. Measurements of Sunyaev-Zeldovich effect (SZE) and X-rays combined with the DD relation have been used to determine D(A)(z) from galaxy clusters. This combination offers the possibility of testing the validity of the DD relation, as well as determining which physical processes occur in galaxy clusters via their shapes. Aims. We use WMAP (7 years) results by fixing the conventional Lambda CDM model to verify the consistence between the validity of DD relation and different assumptions about galaxy cluster geometries usually adopted in the literature. Methods. We assume that. is a function of the redshift parametrized by two different relations: eta(z) = 1+eta(0)z, and eta(z) = 1+eta(0)z/(1+z), where eta(0) is a constant parameter quantifying the possible departure from the strict validity of the DD relation. In order to determine the probability density function (PDF) of eta(0), we consider the angular diameter distances from galaxy clusters recently studied by two different groups by assuming elliptical (isothermal) and spherical (non-isothermal) beta models. The strict validity of the DD relation will occur only if the maximum value of eta(0) PDF is centered on eta(0) = 0. Results. It was found that the elliptical beta model is in good agreement with the data, showing no violation of the DD relation (PDF peaked close to eta(0) = 0 at 1 sigma), while the spherical (non-isothermal) one is only marginally compatible at 3 sigma. Conclusions. The present results derived by combining the SZE and X-ray surface brightness data from galaxy clusters with the latest WMAP results (7-years) favors the elliptical geometry for galaxy clusters. It is remarkable that a local property like the geometry of galaxy clusters might be constrained by a global argument provided by the cosmic DD relation.

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.

Heparin affects the interaction of kininogen on endothelial cells

In the plasma kallikrein-kinin system, it has been shown that when plasma prekallikrein (PM) and high molecular weight kininogen (HK) assemble on endothelial cells, plasma kallikrein (huPK) becomes available to cleave HK, releasing bradykinin, a potent mediator of the inflammatory response. Because the formation of soluble glycosaminoglycans occurs concomitantly during the inflammatory processes, the effect of these polysaccharides on the interaction of HK on the cell surface or extracellular matrix (ECM) of two endothelial cell lines (ECV304 and RAEC) was investigated. In the presence of Zn(+2), HK binding to the surface or ECM of RAEC was abolished by heparin; reduced by heparan sulfate, keratan sulfate, chondroitin 4-sulfate or dermatan sulfate; and not affected by chondroitin 6-sulfate. By contrast, only heparin reduced HK binding to the ECV304 cell surface or ECM. Using heparin-correlated molecules such as low molecular weight dextran sulfate, low molecular weight heparin and N-desulfated heparin, we suggest that these effects were mainly dependent on the charge density and on the N-sulfated glucosamine present in heparin. Surprisingly, PM binding to cell- or ECM-bound-HK and PM activation was not modified by heparin. However, the hydrolysis of HK by huPK, releasing BK in the fluid phase, was augmented by this glycosaminoglycan in the presence of Zn(2+). Thus, a functional dichotomy exists in which soluble glycosaminoglycans may possibly either increase or decrease the formation of BK. In conclusion, glycosaminoglycans that accumulated in inflammatory fluids or used as a therapeutic drug (e.g., heparin) could act as pro- or anti-inflammatory mediators depending on different factors within the cell environment. (C) 2011 Elsevier Masson SAS. All rights reserved.

The contribution of self-efficacy and depression to disability and work status in chronic pain patients: A comparison between Australian and Brazilian samples

There is evidence that cognitions (beliefs) and mood contribute to physical disability and work status in people with chronic pain. However, most of the current evidence comes from North America and Europe. This study examined the contribution of demographic, pain and psychosocial factors to disability and work status in chronic pain patients in two matched samples from quite different countries (Australia and Brazil). Data were collected from 311 chronic pain patients in each country. The results suggest that although demographic and pain variables (especially pain levels) contribute disability, self-efficacy beliefs made a significant contribution to disability in both samples. Age and educational level also contributed to unemployment in both samples. But there were some differences, with self-efficacy and physical disability contributing to work status only in the Brazilian sample. In contrast, depression was the only psychological risk factor for unemployment in the Australian sample. Catastrophising and pain acceptance did not contribute to disability or unemployment in either sample. These findings confirm key aspects of biopsychosocial models of pain in two culturally and linguistically different chronic pain samples from different countries. They suggest that different chronic pain populations may share more similarities than differences. (C) 2008 European Federation of Chapters of the International Association for the Study of Pain. Published

Surveillance Programme for Healthcare Associated Infections in the State of Sao Paulo, Brazil. Implementation and the first three years` results

Governmental programmes should be developed to collect and analyse data on healthcare associated infections (HAIs). This study describes the healthcare setting and both the implementation and preliminary results of the Programme for Surveillance of Healthcare Associated Infections in the State of Sao Paulo (PSHAISP), Brazil, from 2004 to 2006. Characterisation of the healthcare settings was carried out using a national database. The PSHAISP was implemented using components for acute care hospitals (ACH) or long term care facilities (LTCF). The components for surveillance in ACHs were surgical unit, intensive care unit and high risk nursery. The infections included in the surveillance were surgical site infection in clean surgery, pneumonia, urinary tract infection and device-associated bloodstream infections. Regarding the LTCF component, pneumonia, scabies and gastroenteritis in all inpatients were reported. In the first year of the programme there were 457 participating healthcare settings, representing 51.1% of the hospitals registered in the national database. Data obtained in this study are the initial results and have already been used for education in both surveillance and the prevention of HAI. The results of the PSHAISP show that it is feasible to collect data from a large number of hospitals. This will assist the State of Sao Paulo in assessing the impact of interventions and in resource allocation. (C) 2010 The Hospital Infection Society. Published by Elsevier Ltd. All rights reserved.

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.