Peak expiratory flow values are higher in older and taller healthy male children: An observational study

Purpose: Peak expiratory flow (PEF) was measured in healthy children aged five to ten years in order to provide baseline values and to determine correlations between PEF and factors such as gender, age and type of school. Methods: After the Ethical Committee of Research in Human of the School of Medicine of ABC - FMABC approval, PEF and height were measured in 1942 children between five and ten years old from nine public schools and nine private schools throughout Sao Bernardo do Campo City. PEF was measured using the Mini-Wright Peak Flow Meter (Clement Clarke International Ltd.) and. height was measured using a Sanny professional stadiometer. Results: Significant differences were found in values for PEF: higher values were seen in older students in comparison with younger students, in males in comparison with females and in students from private schools in comparison with public schools, with average values ranging from 206 L/min to 248 L/min,. Linear correlations were seen for PEF values with both height and age (Spearman Coefficient). Conclusions: Differences were seen for PEF between genders and between types of school, and a linear correlation was seen for PEF with both age and height in healthy children from five to ten years old.

Local star formation triggered by supernova shocks in magnetized diffuse neutral clouds

In this work, considering the impact of a supernova remnant (SNR) with a neutral magnetized cloud we derived analytically a set of conditions that are favourable for driving gravitational instability in the cloud and thus star formation. Using these conditions, we have built diagrams of the SNR radius, R(SNR), versus the initial cloud density, n(c), that constrain a domain in the parameter space where star formation is allowed. This work is an extension to previous study performed without considering magnetic fields (Melioli et al. 2006, hereafter Paper I). The diagrams are also tested with fully three-dimensional MHD radiative cooling simulations involving a SNR and a self-gravitating cloud and we find that the numerical analysis is consistent with the results predicted by the diagrams. While the inclusion of a homogeneous magnetic field approximately perpendicular to the impact velocity of the SNR with an intensity similar to 1 mu G within the cloud results only a small shrinking of the star formation zone in the diagram relative to that without magnetic field, a larger magnetic field (similar to 10 mu G) causes a significant shrinking, as expected. Though derived from simple analytical considerations these diagrams provide a useful tool for identifying sites where star formation could be triggered by the impact of a supernova blast wave. Applications of them to a few regions of our own Galaxy (e.g. the large CO shell in the direction of Cassiopeia, and the Edge Cloud 2 in the direction of the Scorpious constellation) have revealed that star formation in those sites could have been triggered by shock waves from SNRs for specific values of the initial neutral cloud density and the SNR radius. Finally, we have evaluated the effective star formation efficiency for this sort of interaction and found that it is generally smaller than the observed values in our own Galaxy (SFE similar to 0.01-0.3). This result is consistent with previous work in the literature and also suggests that the mechanism presently investigated, though very powerful to drive structure formation, supersonic turbulence and eventually, local star formation, does not seem to be sufficient to drive global star formation in normal star-forming galaxies, not even when the magnetic field in the neutral clouds is neglected.

Bothrops insularis venomics: A proteomic analysis supported by transcriptomic-generated sequence data

A joint transcriptomic and proteomic approach employing two-dimensional electrophoresis, liquid chromatography and mass spectrometry was carried out to identify peptides and proteins expressed by the venom gland of the snake Bothrops insularis, an endemic species of Queimada Grande Island, Brazil. Four protein families were mainly represented in processed spots, namely metalloproteinase, serine proteinase, phospholipase A(2) and lectin. Other represented families were growth factors, the developmental protein G10, a disintegrin and putative novel bradykinin-potentiating peptides. The enzymes were present in several isoforms. Most of the experimental data agreed with predicted values for isoelectric point and M(r) of proteins found in the transcriptome of the venom gland. The results also support the existence of posttranslational modifications and of proteolytic processing of precursor molecules which could lead to diverse multifunctional proteins. This study provides a preliminary reference map for proteins and peptides present in Bothrops insularis whole venom establishing the basis for comparative studies of other venom proteomes which could help the search for new drugs and the improvement of venom therapeutics. Altogether, our data point to the influence of transcriptional and post-translational events on the final venom composition and stress the need for a multivariate approach to snake venomics studies. (c) 2009 Elsevier B.V. All rights reserved.

Taxon surrogates among Amazonian mammals: Can total species richness be predicted by single orders?

Limited financial sources and the difficulty in performing complete surveys, allied to the speed of habitat fragmentation and the urgent necessity in select conservation areas, create the necessity of using some methodologies which bypass these problems. One possibility is the use of surrogate taxa that might be used as indicator of others groups richness and even total richness of an area. We investigated if the use of surrogate taxon is useful among seven mammal orders in Amazon. We tested through Pearson`s correlation (Bonferroni`s adjusted) if (1) there was a correlation between richness of total species and some order; (2) there was a significant pair wise correlation between species richness of each order; and (3) the combination of two orders would give better results as a surrogate for the total richness. The correlations found, in general, were positive. It means that the increase in the richness of an order was followed by its increase in another order, as well as in the total species richness. Only Didelphimorphia was significantly correlated with the total species richness. In the pair wise analyses only one assembly, Primates and Artiodactyla, was significantly correlated with total richness. Since indicator species are more effective within taxonomic groups (life-history characteristics are likely to be more different among than within major taxonomic groups), we suggest that an indicator group might be chosen for each one. In this case, for mammals from Amazon, it would be Didelphimorphia. (C) 2008 Elsevier Ltd. All rights reserved.

Comparison of signal-to-cutoff values in first, second, and third generation enzyme immunoassays for the diagnosis of HTLV-1/2 infection in ""at-risk"" individuals from Sao Paulo, Brazil

Data obtained during routine diagnosis of human T-cell lymphotropic virus type 1 (HTLV-1) and 2 (HTLV-2) in ""at-risk"" individuals from Sao Paulo, Brazil using signal-to-cutoff (S/C) values obtained by first, second, and third generation enzyme immunoassay (EIA) kits, were compared. The highest S/C values were obtained with third generation EIA kits, but no correlation was detected between these values and specific antibody reactivity to HTLV-1, HTLV-2, or untyped HTLV (p = 0.302). In addition, use of these third generation kits resulted in HTLV-1/2 false-positive samples. In contrast, first and second generation EIA kits showed high specificity, and the second generation EIA kits showed the highest efficiency, despite lower S/C values. Using first and second generation EIA kits, significant differences in specific antibody detection of HTLV-1, relative to HTLV-2 (p = 0.019 for first generation and p < 0.001 for second generation EIA kits) and relative to untyped HTLV (p = 0.025 for first generation EIA kits), were observed. These results were explained by the composition and format of the assays. In addition, using receiver operating characteristics (ROC) analysis, a slight adjustment in cutoff values for third generation EIA kits improved their specificities and should be used when HTLV ""at-risk"" populations from this geographic area are to be evaluated. (C) 2009 Elsevier B.V. All rights reserved.

Analysis of genotypic variation in genes associated with virulence in Aggregatibacter actinomycetemcomitans clinical isolates

Background and Objective: Although certain serotypes of Aggregatibacter actinomycetemcomitans are associated more with aggressive periodontitis than are other serotypes, the correlation between distinct lineages and virulence traits in this species is poorly understood. This study aimed to evaluate the polymorphism of genes encoding putative virulence factors of clinical isolates, and to correlate these findings with A. actinomycetemcomitans serotypes, genotypes and periodontal status of the hosts. Material and Methods: Twenty-six clinical isolates from diverse geographic populations with different periodontal conditions were evaluated. Genotyping was performed using pulse-field gel electrophoresis. Polymorphisms in the genes encoding leukotoxin, Aae, ApaH and determinants for serotype-specific O polysaccharide were investigated. Results: The isolates were classified into serotypes a-f, and exhibited three apaH genotypes, five aae alleles and 25 macrorestriction profiles. Two serotype b isolates (7.7%), obtained from Brazilian patients with aggressive periodontitis, were associated with the highly leukotoxic genotype; these isolates showed identical fingerprint patterns and aae and apaH genotypes. Serotype c, obtained from various periodontal conditions, was the most prevalent among Brazilian isolates, and isolates were distributed in two aae alleles, but formed a genetically distinct group based on apaH analysis. Cluster analysis showed a close relationship between fingerprinting genotypes and serotypes/apaH genotypes, but not with aae genotypes. Conclusion: Apart from the deletion in the ltx promoter region, no disease-associated markers were identified. Non-JP2-like strains recovered from individuals with periodontal disease exhibited considerable genetic variation regarding aae/apaH genotypes, serotypes and XhoI DNA fingerprints.

Evolutionary tuning of SVM parameter values in multiclass problems

Support vector machines (SVMs) were originally formulated for the solution of binary classification problems. In multiclass problems, a decomposition approach is often employed, in which the multiclass problem is divided into multiple binary subproblems, whose results are combined. Generally, the performance of SVM classifiers is affected by the selection of values for their parameters. This paper investigates the use of genetic algorithms (GAs) to tune the parameters of the binary SVMs in common multiclass decompositions. The developed GA may search for a set of parameter values common to all binary classifiers or for differentiated values for each binary classifier. (C) 2008 Elsevier B.V. All rights reserved.

Poly-bagging predictors for classification modelling for credit scoring

Credit scoring modelling comprises one of the leading formal tools for supporting the granting of credit. Its core objective consists of the generation of a score by means of which potential clients can be listed in the order of the probability of default. A critical factor is whether a credit scoring model is accurate enough in order to provide correct classification of the client as a good or bad payer. In this context the concept of bootstraping aggregating (bagging) arises. The basic idea is to generate multiple classifiers by obtaining the predicted values from the fitted models to several replicated datasets and then combining them into a single predictive classification in order to improve the classification accuracy. In this paper we propose a new bagging-type variant procedure, which we call poly-bagging, consisting of combining predictors over a succession of resamplings. The study is derived by credit scoring modelling. The proposed poly-bagging procedure was applied to some different artificial datasets and to a real granting of credit dataset up to three successions of resamplings. We observed better classification accuracy for the two-bagged and the three-bagged models for all considered setups. These results lead to a strong indication that the poly-bagging approach may promote improvement on the modelling performance measures, while keeping a flexible and straightforward bagging-type structure easy to implement. (C) 2011 Elsevier Ltd. All rights reserved.

DFT study of the electronic, vibrational, and optical properties of SnO(2)

We report results on the electronic, vibrational, and optical properties of SnO(2) obtained using first-principles calculations performed within the density functional theory. All the calculated phonon frequencies, real and imaginary parts of complex dielectric function, the energy-loss spectrum, the refractive index, the extinction, and the absorption coefficients show good agreement with experimental results. Based on our calculations, the SnO(2) electron and hole effective masses were found to be strongly anisotropic. The lattice contribution to the low-frequency region of the SnO(2) dielectric function arising from optical phonons was also determined resulting the values of E > (1aSyen) (latt) (0) = 14.6 and E > (1ayen) (latt) (0) = 10.7 for directions perpendicular and parallel to the tetragonal c-axis, respectively. This is in excellent agreement with the available experimental data. After adding the electronic contribution to the lattice contribution, a total average value of E >(1)(0) = 18.2 is predicted for the static permittivity constant of SnO(2).

Can efficiency of the photosensitizer be predicted by its photostability in solution?

We have investigated a possible correlation between the photostability and photodynamic efficacy for different photosensitizers; hematoporphyrin derivatives and chlorines. To perform such analysis, we combined the depth of necrosis (d (nec)) measurement, expressed by the light threshold dose and a photodegradation parameter, measured from investigation of photosensitizer degradation in solution. The d (nec) analysis allows us to determine the light threshold dose and compare its value with the existent results in the literature. The use of simple models to understand basic features of Photodynamic Therapy (PDT) may contribute to the solid establishment of dosimetry in PDT, enhancing its use in the clinical management of cancers and others lesions. Using hematoporphyrin derivatives and chlorines photosensitizers we investigated their properties related to the photodegradation in solution and the light threshold dose (D (th)) in rat livers.

Quantitative structure-activity relationships for a series of inhibitors of cruzain from Trypanosoma cruzi: Molecular modeling, CoMFA and CoMSIA studies

Human parasitic diseases are the foremost threat to human health and welfare around the world. Trypanosomiasis is a very serious infectious disease against which the currently available drugs are limited and not effective. Therefore, there is an urgent need for new chemotherapeutic agents. One attractive drug target is the major cysteine protease from Trypanosoma cruzi, cruzain. In the present work, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) studies were conducted on a series of thiosemicarbazone and semicarbazone derivatives as inhibitors of cruzain. Molecular modeling studies were performed in order to identify the preferred binding mode of the inhibitors into the enzyme active site, and to generate structural alignments for the three-dimensional quantitative structure-activity relationship (3D QSAR) investigations. Statistically significant models were obtained (CoMFA. r(2) = 0.96 and q(2) = 0.78; CoMSIA, r(2) = 0.91 and q(2) = 0.73), indicating their predictive ability for untested compounds. The models were externally validated employing a test set, and the predicted values were in good agreement with the experimental results. The final QSAR models and the information gathered from the 3D CoMFA and CoMSIA contour maps provided important insights into the chemical and structural basis involved in the molecular recognition process of this family of cruzain inhibitors, and should be useful for the design of new structurally related analogs with improved potency. (C) 2009 Elsevier Inc. All rights reserved.

Structure-Based Approach for the Study of Estrogen Receptor Binding Affinity and Subtype Selectivity

Estrogens exert important physiological effects through the modulation of two human estrogen receptor (hER) subtypes, alpa (hER alpha) and beta (hER beta). Because the levels and relative proportion of hER alpha and hER beta differ significantly in different target cells, selective hER ligands could target specific tissues or pathways regulated by one receptor subtype without affecting the other. To understand the structural and chemical basis by which small molecule modulators are able to discriminate between the two subtypes, we have applied three-dimensional target-based approaches employing a series of potent hER-ligands. Comparative molecular field analysis (CoMFA) studies were applied to a data set of 81 hER modulators, for which binding affinity values were collected for both hER alpha and hER beta. Significant statistical coefficients were obtained (hER alpha, q(2) = 0.76; hER beta, q(2) = 0.70), indicating the internal consistency of the models. The generated models were validated using external test sets, and the predicted values were in good agreement with the experimental results. Five hER crystal structures were used in GRID/PCA investigations to generate molecular interaction fields (MIF) maps. hER alpha and hER beta were separated using one factor. The resulting 3D information was integrated with the aim of revealing the most relevant structural features involved in hER subtype selectivity. The final QSAR and GRID/PCA models and the information gathered from 3D contour maps should be useful for the design or novel hER modulators with improved selectivity.

Three-dimensional quantitative structure-activity relationships for a large series of potent antitubercular agents

Comparative molecular field analysis (CoMFA) studies were conducted on a series of 100 isoniazid derivatives as anti-tuberculosis agents using two receptor-independent structural data set alignment strategies: (1) rigid-body fit, and (2) pharmacophore-based. Significant cross-validated correlation coefficients were obtained (CoMFA(1), q(2) = 0,75 and CoMFA(2), q(2) = 0.74), indicating the potential of the models for untested compounds. The models were then used to predict the inhibitory potency of 20 test set compounds that were not included in the training set, and the predicted values were in good agreement with the experimental results.

Quantitative structure-activity studies on a series of migrastatin analogs as inhibitors of cancer cell metastasis

Migrastatin, a macrolide natural product, and its structurally related analogs are potent inhibitors of cancer cell metastasis, invasion and migration. In the present work, a specialized fragment-based method was employed to develop QSAR models for a series of migrastatin and isomigrastatin analogs. Significant correlation coefficients were obtained (best model, q(2) = 0.76 and r(2) = 0.91) indicating that the QSAR models possess high internal consistency. The best model was then used to predict the potency of an external test set, and the predicted values were in good agreement with the experimental results (R(2) (pred) = 0.85). The final model and the corresponding contribution maps, combined with molecular modeling studies, provided important insights into the key structural features for the anticancer activity of this family of synthetic compounds based on natural products.

Classical and hologram QSAR studies on a series of inhibitors of trypanosomatid Glyceraldehyde-3-Phosphate Dehydrogenase

Leishmaniasis and trypanosomiasis are major causes of morbidity and mortality in both tropical and subtropical regions of the world. The current available drugs are limited, ineffective, and require long treatment regimens. Due to the high dependence of trypanosomatids on glycolysis as a source of energy, some glycolytic enzymes have been identified as attractive targets for drug design. In the present work, classical Two-Dimensional Quantitative Structure -Activity Relationships (2D QSAR) and Hologram QSAR (HQSAR) studies were performed on a series of adenosine derivatives as inhibitors of Leishmania mexicana Glyceraldehyde-3-Phosphate Dehydrogenase (LmGAPDH). Significant correlation coefficients (classical QSAR, r(2)=0.83 and q(2) =0.81; HQSAR, r(2)=0.91 and q(2) =0.86) were obtained for the 56 training set compounds, indicating the potential of the models for untested compounds. The models were then externally validated using a test set of 14 structurally related compounds and the predicted values were in good agreement with the experimental results (classical QSAR, r(pred)(2) = 0.94; HQSAR, r(pred)(2) = 0.92).