67 resultados para Computational analysis

em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"


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Schistosomiasis is still an endemic disease in many regions, with 250 million people infected with Schistosoma and about 500,000 deaths per year. Praziquantel (PZQ) is the drug of choice for schistosomiasis treatment, however it is classified as Class II in the Biopharmaceutics Classification System, as its low solubility hinders its performance in biological systems. The use of cyclodextrins is a useful tool to increase the solubility and bioavailability of drugs. The aim of this work was to prepare an inclusion compound of PZQ and methyl-beta-cyclodextrin (MeCD), perform its physico-chemical characterization, and explore its in vitro cytotoxicity. SEM showed a change of the morphological characteristics of PZQ:MeCD crystals, and IR data supported this finding, with changes after interaction with MeCD including effects on the C-H of the aromatic ring, observed at 758 cm(-1). Differential scanning calorimetry measurements revealed that complexation occurred in a 1:1 molar ratio, as evidenced by the lack of a PZQ transition temperature after inclusion into the MeCD cavity. In solution, the PZQ UV spectrum profile in the presence of MeCD was comparable to the PZQ spectrum in a hydrophobic solvent. Phase solubility diagrams showed that there was a 5.5-fold increase in PZQ solubility, and were indicative of a type A(L) isotherm, that was used to determine an association constant (K(a)) of 140.8 M(-1). No cytotoxicity of the PZQ:MeCD inclusion compound was observed in tests using 3T3 cells. The results suggest that the association of PZQ with MeCD could be a good alternative for the treatment of schistosomiasis.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Axillary bud outgrowth determines shoot architecture and is under the control of endogenous hormones and a fine-tuned gene-expression network, which probably includes small RNAs (sRNAs). Although it is well known that sRNAs act broadly in plant development, our understanding about their roles in vegetative bud outgrowth remains limited. Moreover, the expression profiles of microRNAs (miRNAs) and their targets within axillary buds are largely unknown. Here, we employed sRNA next-generation sequencing as well as computational and gene-expression analysis to identify and quantify sRNAs and their targets in vegetative axillary buds of the biofuel crop sugarcane (Saccharum spp.). Computational analysis allowed the identification of 26 conserved miRNA families and two putative novel miRNAs, as well as a number of trans-acting small interfering RNAs. sRNAs associated with transposable elements and protein-encoding genes were similarly represented in both inactive and developing bud libraries. Conversely, sequencing and quantitative reverse transcription-PCR results revealed that specific miRNAs were differentially expressed in developing buds, and some correlated negatively with the expression of their targets at specific stages of axillary bud development. For instance, the expression patterns of miR159 and its target GAMYB suggested that they may play roles in regulating abscisic acid-signalling pathways during sugarcane bud outgrowth. Our work reveals, for the first time, differences in the composition and expression profiles of diverse sRNAs and targets between inactive and developing vegetative buds that, together with the endogenous balance of specific hormones, may be important in regulating axillary bud outgrowth. © 2013 © The Author(2) [2013].

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Developmental Coordination Disorder (DCD), a chronic and usually permanent condition found in children, is characterized by motor impairment that interferes with a child's activities of daily living and with academic achievement. One of the most popular tests for the quantitative diagnosis of DCD is the Movement Assessment Battery for Children (MABC). Based on the Battery's standardized scores, it is possible to identify children with typical development, children at risk of developing DCD, and children with DCD. This article describes a computational system we developed to assist with the analysis of results obtained in the MABC test. The tool was developed for the web environment and its database provides integration of MABC data. Thus, researchers around the world can share data and develop collaborative work in the DCD field. In order to help analysis processes, our system provides services for filtering data to show more specific sets of information and present the results in textual, table, and graphic formats, allowing easier and more comprehensive evaluation of the results.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Snake venom (sv) C-type lectins encompass a group of hemorrhagic toxins that are capable of interfering with blood stasis. A very well-studied svC-type lectin is the heterodimeric toxin, convulxin (CVX), from the venom of South American rattlesnake Crotalus durissus terrificus. CVX is able to activate platelets and induce their aggregation by acting via p62/GPVI collagen receptor. By using polymerase chain reaction homology screening, we have cloned several cDNA precursors of CVX subunit homologs. One of them, named crotacetin (CTC) beta-subunit, predicts a polypeptide with a topology very similar to the tridimensional conformations of other subunits of CVX-like snake toxins, as determined by computational analysis. Using gel permeation and reverse-phase high-performance liquid chromatography, CTC was purified from C. durissus venoms. CTC can be isolated from the venom of several C. durissus subspecies, but its quantitative predominance is in the venom of C. durissus cascavella. Functional analysis indicates that CTC induces platelet aggregation, and, importantly, exhibits an antimicrobial activity against Gram-positive and -negative bacteria, comparable with CVX.

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Piecewise-Linear Programming (PLP) is an important area of Mathematical Programming and concerns the minimisation of a convex separable piecewise-linear objective function, subject to linear constraints. In this paper a subarea of PLP called Network Piecewise-Linear Programming (NPLP) is explored. The paper presents four specialised algorithms for NPLP: (Strongly Feasible) Primal Simplex, Dual Method, Out-of-Kilter and (Strongly Polynomial) Cost-Scaling and their relative efficiency is studied. A statistically designed experiment is used to perform a computational comparison of the algorithms. The response variable observed in the experiment is the CPU time to solve randomly generated network piecewise-linear problems classified according to problem class (Transportation, Transshipment and Circulation), problem size, extent of capacitation, and number of breakpoints per arc. Results and conclusions on performance of the algorithms are reported.

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Inferences about leaf anatomical characteristics had largely been made by manually measuring diverse leaf regions, such as cuticle, epidermis and parenchyma to evaluate differences caused by environmental variables. Here we tested an approach for data acquisition and analysis in ecological quantitative leaf anatomy studies based on computer vision and pattern recognition methods. A case study was conducted on Gochnatia polymorpha (Less.) Cabrera (Asteraceae), a Neotropical savanna tree species that has high phenotypic plasticity. We obtained digital images of cross-sections of its leaves developed under different light conditions (sun vs. shade), different seasons (dry vs. wet) and in different soil types (oxysoil vs. hydromorphic soil), and analyzed several visual attributes, such as color, texture and tissues thickness in a perpendicular plane from microscopic images. The experimental results demonstrated that computational analysis is capable of distinguishing anatomical alterations in microscope images obtained from individuals growing in different environmental conditions. The methods presented here offer an alternative way to determine leaf anatomical differences. © 2013 Elsevier B.V.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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In this paper, a computational analysis, using a cellular automata model, has been developed to analyze post-feeding dispersal behavior of blow y larvae. This model aimed to: simulate the exponential decline of pupal number in relation to the feed source and spatial oscillation due to larval interaction during dispersal; study whether the prior pupal presence in uences distribution patterns of larval frequency; and compare obtained unidirectional dispersal patterns to the cross-dimensional ones. The cellular automata (CA) model was able to successfully reproduce the essential features of the larval dispersal process and, thus, show the importance of local interaction in the studied dispersal process dynamics. Oscillations could be explained by the interaction among dispersing larvae and intrinsic pupation time. The box size and the initial larval density were important factors for the experiment because they in uenced the results. Results showed that the unidirectional dispersal could be used to simulate the larval dispersion that occurs in the natural environment, because both models had a similar result. These results are important to understand how di erent factors can in uence the dynamics of blow y larval dispersal, bringing important results for behavioral ecology and forensic entomology

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Pós-graduação em Química - IQ