Reconstruction of molecular networks involved in citokine-induced myotubes atrophy integrating microRNA and mRNA expression

Pós-graduação em Ciências Biológicas (Genética) - IBB

SERS mapping in langmuir-blodgett films and single-molecule detection

Plasmon-enhanced spectroscopic techniques have expanded single-molecule detection (SMD) and are revolutionizing areas such as bio-imaging and single-cell manipulation. Surface-enhanced (resonance) Raman scattering (SERS or SERRS) combines high sensitivity with molecularfingerprint information at the single-molecule level. Spectra originating from single-molecule SERS experiments are rare events, which occur only if a single molecule is located in a hot-spot zone. In this spot, the molecule is selectively exposed to a significant enhancement associated with a high, local electromagnetic field in the plasmonic substrate. Here, we report an SMD study with an electrostatic approach in which a Langmuir film of a phospholipid with anionic polar head groups (PO 4 -) was doped with cationic methylene blue (MB), creating a homogeneous, two-dimensional distribution of dyes in the monolayer. The number of dyes in the probed area of the Langmuir-Blodgett (LB) film coating the Ag nanostructures established a regime in which single-molecule events were observed, with the identification based on direct matching of the observed spectrum at each point of the mapping with a reference spectrum for the MB molecule. In addition, advanced fitting techniques were tested with the data obtained from micro-Raman mapping, thus achieving real-time processing to extract the MB single-molecule spectra. © 2013 Society for Applied Spectroscopy.

Análise de propriedades topológicas das redes biológicas integradas da Escherichia coli e da Saccharomyces cerevisiae

Biological processes are complex and possess emergent properties that can not be explained or predict by reductionism methods. To overcome the limitations of reductionism, researchers have been used a group of methods known as systems biology, a new interdisciplinary eld of study aiming to understand the non-linear interactions among components embedded in biological processes. These interactions can be represented by a mathematical object called graph or network, where the elements are represented by nodes and the interactions by edges that link pair of nodes. The networks can be classi- ed according to their topologies: if node degrees follow a Poisson distribution in a given network, i.e. most nodes have approximately the same number of links, this is a random network; if node degrees follow a power-law distribution in a given network, i.e. small number of high-degree nodes and high number of low-degree nodes, this is a scale-free network. Moreover, networks can be classi ed as hierarchical or non-hierarchical. In this study, we analised Escherichia coli and Saccharomyces cerevisiae integrated molecular networks, which have protein-protein interaction, metabolic and transcriptional regulation interactions. By using computational methods, such as MathematicaR , and data collected from public databases, we calculated four topological parameters: the degree distribution P(k), the clustering coe cient C(k), the closeness centrality CC(k) and the betweenness centrality CB(k). P(k) is a function that calculates the total number of nodes with k degree connection and is used to classify the network as random or scale-free. C(k) shows if a network is hierarchical, i.e. if the clusterization coe cient depends on node degree. CC(k) is an indicator of how much a node it is in the lesse way among others some nodes of the network and the CB(k) is a pointer of how a particular node is among several ...(Complete abstract click electronic access below)

Metformin and soybean-derived bioactive molecules attenuate the expansion of stem cell-like epithelial subpopulation and confer apoptotic sensitivity in human colon cancer cells

Colorectal cancer (CRC) is a disease whose genesis may include metabolic dysregulation. Cancer stem cells are attractive targets for therapeutic interventions since their aberrant expansion may underlie tumor initiation, progression, and recurrence. To investigate the actions of metabolic regulators on cancer stem cell-like cells (CSC) in CRC, we determined the effects of soybean-derived bioactive molecules and the anti-diabetes drug metformin (MET), alone and together, on the growth, survival, and frequency of CSC in human HCT116 cells. Effects of MET (60 μM) and soybean components genistein (Gen, 2 μM), lunasin (Lun, 2 μM), β-conglycinin (β-con, 3 μM), and glycinin (Gly, 3 μM) on HCT116 cell proliferation, apoptosis, and mRNA/protein expression and on the frequency of the CSC CD133(+)CD44(+) subpopulation by colonosphere assay and fluorescence-activated cell sorting/flow cytometry were evaluated. MET, Gen, and Lun, individually and together, inhibited HCT116 viability and colonosphere formation and, conversely, enhanced HCT116 apoptosis. Reductions in frequency of the CSC CD133(+)CD44(+) subpopulation with MET, Gen, and Lun were found to be associated with increased PTEN and reduced FASN expression. In cells under a hyperinsulinemic state mimicking metabolic dysregulation and without and with added PTEN-specific inhibitor SF1670, colonosphere formation and frequency of the CD133(+)CD44(+) subpopulation were decreased by MET, Lun and Gen, alone and when combined. Moreover, MET + Lun + Gen co-treatment increased the pro-apoptotic and CD133(+)CD44(+)-inhibitory efficacy of 5-fluorouracil under hyperinsulinemic conditions. Results identify molecular networks shared by MET and bioavailable soy food components, which potentially may be harnessed to increase drug efficacy in diabetic and non-diabetic patients with CRC.

Molecular mapping of the viral determinants of systemic wilting induced by a Lettuce mosaic virus (LMV) isolate in some lettuce cultivars

The isolate AF199 of Lettuce mosaic virus (LMV, genus Potyvirus) causes local lesions followed by systemic wilting and plant death in the lettuce cultivars Ithaca and Vanguard 75. Analysis of the phenotype of virus chimeras revealed that a region within the PI protein coding region (nucleotides 112-386 in the viral genome) and/or another one within the CI protein coding region (nucleoticles 5496-5855) are sufficient together to cause the lethal wilting in Ithaca, but not in Vanguard 75. This indicates that the determinants of this particular symptom are different in these two lettuce cultivars. The wilting phenotype was not directly correlated with differences in the deduced amino acid sequence of these two regions. Furthermore, transient expression of the LMV-AF 199 proteins, separately or in combination, did not induce local necrosis or any other visible reaction in the plants. Together, these results Suggest that the systemic wilting reaction might be Clue to RNA rather than protein sequences. (c) 2004 Elsevier B.V. All rights reserved.

Molecular Characterization and Physical Mapping of Two Classes of 5S rDNA in the Genomes of Gymnotus sylvius and G. inaequilabiatus (Gymnotiformes, Gymnotidae)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Molecular mapping of two loci that confer resistance to Asian rust in soybean

Asian soybean rust (ASR) is caused by the fungal pathogen Phakopsora pachyrhizi Sydow & Sydow. It was first identified in Brazil in 2001 and quickly infected soybean areas in several countries in South America. Primary efforts to combat this disease must involve the development of resistant cultivars. Four distinct genes that confer resistance against ASR have been reported: Rpp1, Rpp2, Rpp3, and Rpp4. However, no cultivar carrying any of those resistance loci has been released. The main objective of this study was to genetically map Rpp2 and Rpp4 resistance genes. Two F(2:3) populations, derived from the crosses between the resistant lines PI 230970 (Rpp2), PI 459025 (Rpp4) and the susceptible cultivar BRS 184, were used in this study. The mapping populations and parental lines were inoculated with a field isolate of P. pachyrhizi and evaluated for lesion type as resistant (RB lesions) or susceptible (TAN lesions). The mapping populations were screened with SSR markers, using the bulk segregant analysis (BSA) to expedite the identification of linked markers. Both resistance genes showed an expected segregation ratio for a dominant trait. This study allowed mapping Rpp2 and Rpp4 loci on the linkage groups J and G, respectively. The associated markers will be of great value on marker assisted selection for this trait.

A Learning Function for Parameter Reduction in Spiking Neural Networks with Radial Basis Function

Spiking neural networks - networks that encode information in the timing of spikes - are arising as a new approach in the artificial neural networks paradigm, emergent from cognitive science. One of these new models is the pulsed neural network with radial basis function, a network able to store information in the axonal propagation delay of neurons. Learning algorithms have been proposed to this model looking for mapping input pulses into output pulses. Recently, a new method was proposed to encode constant data into a temporal sequence of spikes, stimulating deeper studies in order to establish abilities and frontiers of this new approach. However, a well known problem of this kind of network is the high number of free parameters - more that 15 - to be properly configured or tuned in order to allow network convergence. This work presents for the first time a new learning function for this network training that allow the automatic configuration of one of the key network parameters: the synaptic weight decreasing factor.

Genetic parameters for body weight, carcass chemical composition and yield in a broiler-layer cross developed for QTL mapping

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

Transcriptomics and systems biology analysis in identification of specific pathways involved in cacao resistance and susceptibility to witches' broom disease

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Comparative study between RBF and radial-PPS neural networks

The study of function approximation is motivated by the human limitation and inability to register and manipulate with exact precision the behavior variations of the physical nature of a phenomenon. These variations are referred to as signals or signal functions. Many real world problem can be formulated as function approximation problems and from the viewpoint of artificial neural networks these can be seen as the problem of searching for a mapping that establishes a relationship from an input space to an output space through a process of network learning. Several paradigms of artificial neural networks (ANN) exist. Here we will be investigated a comparative of the ANN study of RBF with radial Polynomial Power of Sigmoids (PPS) in function approximation problems. Radial PPS are functions generated by linear combination of powers of sigmoids functions. The main objective of this paper is to show the advantages of the use of the radial PPS functions in relationship traditional RBF, through adaptive training and ridge regression techniques.

Application of neural networks to identify features of dynamical grounding systems

The accurate identification of features of dynamical grounding systems are extremely important to define the operational safety and proper functioning of electric power systems. Several experimental tests and theoretical investigations have been carried out to obtain characteristics and parameters associated with the technique of grounding. The grounding system involves a lot of non-linear parameters. This paper describes a novel approach for mapping characteristics of dynamical grounding systems using artificial neural networks. The network acts as identifier of structural features of the grounding processes. So that output parameters can be estimated and generalized from an input parameter set. The results obtained by the network are compared with other approaches also used to model grounding systems.

Analysis of plant LTR-retrotransposons at the fine-scale family level reveals individual molecular patterns

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

Molecular detection of Paracoccidioides brasiliensis in road-killed wild animals

Paracoccidioides brasiliensis infections have been little studied in wild and/or domestic animals, which may represent an important indicator of the presence of the pathogen in nature. Road-killed wild animals have been used for surveillance of vectors of zoonotic pathogens and may offer new opportunities for eco-epidemiological studies of paracoccidiodomycosis (PCM). The presence of P. brasiliensis infection was evaluated by Nested-PCR in tissue samples collected from 19 road-killed animals; 3 Cavia aperea (guinea pig), 5 Cerdocyon thous (crab-eating-fox), 1 Dasypus novemcinctus (nine-banded armadillo), 1 Dasypus septemcinctus (seven-banded armadillo), 2 Didelphis albiventris (white-eared opossum), 1 Eira barbara (tayra), 2 Gallictis vittata (grison), 2 Procyon cancrivorus (raccoon) and 2 Sphiggurus spinosus (porcupine). Specific P. brasiliensis amplicons were detected in (a) several organs of the two armadillos and one guinea pig, (b) the lung and liver of the porcupine, and (c) the lungs of raccoons and grisons. P. brasiliensis infection in wild animals from endemic areas might be more common than initially postulated. Molecular techniques can be used for detecting new hosts and mapping 'hot spot' areas of PCM.