860 resultados para epitope mapping


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The applicability of image calibration to like-values in mapping water quality parameters from multitemporal images is explored, Six sets of water samples were collected at satellite overpasses over Moreton Bay, Brisbane, Australia. Analysis of these samples reveals that waters in this shallow bay are mostly TSS-dominated, even though they are occasionally dominated by chlorophyll as well. Three of the images were calibrated to a reference image based on invariant targets. Predictive models constructed from the reference image were applied to estimating total suspended sediment (TSS) and Secchi depth from another image at a discrepancy of around 35 percent. Application of the predictive model for TSS concentration to another image acquired at a time of different water types resulted in a discrepancy of 152 percent. Therefore, image calibration to like-values could be used to reliably map certain water quality parameters from multitemporal TM images so long as the water type under study remains unchanged. This method is limited in that the mapped results could be rather inaccurate if the water type under study has changed considerably. Thus, the approach needs to be refined in shallow water from multitemporal satellite imagery.

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Quantifying mass and energy exchanges within tropical forests is essential for understanding their role in the global carbon budget and how they will respond to perturbations in climate. This study reviews ecosystem process models designed to predict the growth and productivity of temperate and tropical forest ecosystems. Temperate forest models were included because of the minimal number of tropical forest models. The review provides a multiscale assessment enabling potential users to select a model suited to the scale and type of information they require in tropical forests. Process models are reviewed in relation to their input and output parameters, minimum spatial and temporal units of operation, maximum spatial extent and time period of application for each organization level of modelling. Organizational levels included leaf-tree, plot-stand, regional and ecosystem levels, with model complexity decreasing as the time-step and spatial extent of model operation increases. All ecosystem models are simplified versions of reality and are typically aspatial. Remotely sensed data sets and derived products may be used to initialize, drive and validate ecosystem process models. At the simplest level, remotely sensed data are used to delimit location, extent and changes over time of vegetation communities. At a more advanced level, remotely sensed data products have been used to estimate key structural and biophysical properties associated with ecosystem processes in tropical and temperate forests. Combining ecological models and image data enables the development of carbon accounting systems that will contribute to understanding greenhouse gas budgets at biome and global scales.

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This paper describes algorithms that can identify patterns of brain structure and function associated with Alzheimer's disease, schizophrenia, normal aging, and abnormal brain development based on imaging data collected in large human populations. Extraordinary information can be discovered with these techniques: dynamic brain maps reveal how the brain grows in childhood, how it changes in disease, and how it responds to medication. Genetic brain maps can reveal genetic influences on brain structure, shedding light on the nature-nurture debate, and the mechanisms underlying inherited neurobehavioral disorders. Recently, we created time-lapse movies of brain structure for a variety of diseases. These identify complex, shifting patterns of brain structural deficits, revealing where, and at what rate, the path of brain deterioration in illness deviates from normal. Statistical criteria can then identify situations in which these changes are abnormally accelerated, or when medication or other interventions slow them. In this paper, we focus on describing our approaches to map structural changes in the cortex. These methods have already been used to reveal the profile of brain anomalies in studies of dementia, epilepsy, depression, childhood and adult-onset schizophrenia, bipolar disorder, attention-deficit/ hyperactivity disorder, fetal alcohol syndrome, Tourette syndrome, Williams syndrome, and in methamphetamine abusers. Specifically, we describe an image analysis pipeline known as cortical pattern matching that helps compare and pool cortical data over time and across subjects. Statistics are then defined to identify brain structural differences between groups, including localized alterations in cortical thickness, gray matter density (GMD), and asymmetries in cortical organization. Subtle features, not seen in individual brain scans, often emerge when population-based brain data are averaged in this way. Illustrative examples are presented to show the profound effects of development and various diseases on the human cortex. Dynamically spreading waves of gray matter loss are tracked in dementia and schizophrenia, and these sequences are related to normally occurring changes in healthy subjects of various ages. (C) 2004 Published by Elsevier Inc.

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Progressive myoclonus epilepsy (PME) has a number of causes, of which Unverricht-Lundborg disease (ULD) is the most common. ULD has previously been mapped to a locus on chromosome 21 (EPM1). Subsequently, mutations in the cystatin B gene have been found in most cases. In the present work we identified an inbred Arab family with a clinical pattern compatible with ULD, but mutations in the cystatin B gene were absent. We sought to characterize the clinical and molecular features of the disorder. The family was studied by multiple field trips to their town to clarify details of the complex consanguineous relationships and to personally examine the family. DNA was collected for subsequent molecular analyses from 21 individuals. A genome-wide screen was performed using 811 microsatellite markers. Homozygosity mapping was used to identify loci of interest. There were eight affected individuals. Clinical onset was at 7.3 +/- 1.5 years with myoclonic or tonic-clonic seizures. All had myoclonus that progressed in severity over time and seven had tonic-clonic seizures. Ataxia, in addition to myoclonus, occurred in all. Detailed cognitive assessment was not possible, but there was no significant progressive dementia. There was intrafamily variation in severity; three required wheelchairs in adult life; the others could walk unaided. MRI, muscle and skin biopsies on one individual were unremarkable. We mapped the family to a 15-megabase region at the pericentromeric region of chromosome 12 with a maximum lod score of 6.32. Although the phenotype of individual subjects was typical of ULD, the mean age of onset (7.3 years versus 11 years for ULD) was younger. The locus on chromosome 12 does not contain genes for any other form of PME, nor does it have genes known to be related to cystatin B. This represents a new form of PME and we have designated the locus as EPM1B.

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Suramin is a polysulphonated napthylurea used as an antiprotozoal/anthelminitic drug, which also inhibits a broad range of enzymes. Suramin binding to recombinant human secreted group IIA phospholipase A(2) (hsPLA(2)GIIA) was investigated by molecular dynamics simulations (MD) and isothermal titration calorimetry (ITC). MD indicated two possible bound suramin conformations mediated by hydrophobic and electrostatic interactions with amino-acids in three regions of the protein. namely the active-site and residues located in the N- and C-termini, respectively. All three binding sites are located on the phospholipid membrane recognition surface, suggesting that suramin may inhibit the enzyme, and indeed a 90% reduction in hydrolytic activity was observed in the presence of 100 nM suramin. These results correlated with ITC data, which demonstrated 2.7 suramin binding sites on the hsPLA(2)GIIA, and indicates that suramin represents a novel class of phosphohpase A(2) inhibitor. (C) 2009 Elsevier Inc. All rights reserved.

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Multitemporal Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) imagery was used to assess coastline morphological changes in southeastern Brazil. A spectral linear mixing approach (SLMA) was used to estimate fraction imagery representing amounts of vegetation, clean water (a proxy for shade) and soil. Fraction abundances were related to erosive and depositional features. Shoreline, sandy banks (including emerged and submerged banks) and sand spits were highlighted mainly by clean water and soil fraction imagery. To evaluate changes in the coastline geomorphic features, the fraction imagery generated for each data set was classified in a contextual approach using a segmentation technique and ISOSEG, an unsupervised classification. Evaluation of the classifications was performed visually and by an error matrix relating ground-truth data to classification results. Comparison of the classification results revealed an intense transformation in the coastline, and that erosive and depositional features are extremely dynamic and subject to change in short periods of time.

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Background: The fact that some cancers and viral infections can be controlled by effector CD8 T cells led to the possibility of utilising minimal CD8 T cell epitope peptides as vaccines. However using minimal CD8 T cell epitope peptide immunisations and a tumour protection model in mice, we have previously shown that functional memory CD8 T cells are not generated unless CD4 T help is provided at the time of CD8 T cell priming. Short-lived effector cells nevertheless are generated in the absence of T help. Aim: To determine the role of CD4 T help in multiple immunisations. Method: Minimal CD8 T cell peptides of HPV16 E7 protein and Ovalbumin were used (with adjuvants Quil-A or IFA) as immunogens in C57BL mice. The presence of effector CD8 T cells were determined by tumour protection assays and was quantified by IFN-gamma ELISPOT assays. Results: In the present study we show that unless T help is provided at the time CD8 T cells are primed, no CD8 effector cells are generated when boosted with the vaccine again in the absence of T help. Our results further show that this failure could be prevented by the inclusion of a T helper peptide during the primary or booster immunisations.

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Motor cortex stimulation oriented by functional cortical mapping is used mainly for treating otherwise intractable neurological disorders, however. its mechanism of action remains elusive. Herein, we present a new method for functional mapping of the rat motor cortex using non-invasive transdural electrical stimulation. This method allows a non-invasive mapping of the surface of the neocortex providing a differentiation of representative motor areas. This Study may facilitate further investigation about the mechanisms mediating the effects of electrical stimulation, possibly benefiting patients who do not respond to this neuromodulation therapy. (c) 2009 Elsevier B.V. All rights reserved.

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Streptococcus pyogenes infections remain a health problem in several countries due to poststreptococcal sequelae. We developed a vaccine epitope (StreptInCor) composed of 55 amino acids residues of the C-terminal portion of the M protein that encompasses both T and B cell protective epitopes. The nuclear magnetic resonance (NMR) structure of the StreptInCor peptide showed that the structure was composed of two microdomains linked by an 18-residue alpha-helix. A chemical stability study of the StreptInCor folding/unfolding process using far-UV circular dichroism showed that the structure was chemically stable with respect to pH and the concentration of urea. The T cell epitope is located in the first microdomain and encompasses 11 out of the 18 alpha-helix residues, whereas the B cell epitope is in the second microdomain and showed no alpha-helical structure. The prediction of StreptInCor epitope binding to different HLA class II molecules was evaluated based on an analysis of the 55 residues and the theoretical possibilities for the processed peptides to fit into the P1, P4, P6, and P9 pockets in the groove of several HLA class II molecules. We observed 7 potential sites along the amino acid sequence of StreptInCor that were capable of recognizing HLA class II molecules (DRB1*, DRB3*, DRB4*, and DRB5*). StreptInCoroverlapping peptides induced cellular and humoral immune responses of individuals bearing different HLA class II molecules and could be considered as a universal vaccine epitope.

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Myelin proteolipid protein (PLP) contains 2 immunodominant encephalitogenic epitopes in SJL mice, namely PLP residues 139-151 and 178-191. DM20, a minor isoform of PLP, lacks residues 116-150 and consequently contains only the single major encephalitogenic epitope 178-191. However, it has been found previously that bovine DM20 is not encephalitogenic in SJL mice. Since residue 188 within peptide 178-191 is phenylalanine (F) in murine DM20 and alanine (A) in bovine DM20, we tested the effect of this difference on the immune responses and induction of EAE. SJL mice were immunized with either highly purified murine or bovine DM20. Residues 178-191 were found to be immunodominant for each, but only murine and not bovine DM20 was encephalitogenic. A synthetic peptide corresponding to the murine 178-191 sequence (F188) was also encephalitogenic, whereas the peptide corresponding to the bovine sequence (A188) was not. Both F188 and A188 bind with high affinity to I-A(s) and both are recognized by the SJL T cell repertoire. A188-specific T cell lines reacted to both A188 and F188, but F188-specific T cell lines were not stimulated by A188. F188-specific T cell lines produced mRNA for the Th1 cytokines IL2 and IFN gamma and, in passive transfer experiments, were encephalitogenic upon stimulation with F188, but not A188. In contrast, A188-specific T cell lines produced mRNA for IL4, IL5 and IL10, in addition to IL2 and IFN gamma, and were not encephalitogenic after stimulation with either F188 or A188. Cotransfer of A188-specific T cell lines with F188-specific T cell lines resulted in protection from EAE. Thus, A188 induces a functionally different phenotype of T cells from that induced by F188. Taken together these data suggest that the failure of bovine DM20 to induce EAE may be attributable to induction of protective rather than pathogenic T cells by the immunodominant epitope.

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Functional magnetic resonance imaging (fMRI) based on BOLD signal has been used to indirectly measure the local neural activity induced by cognitive tasks or stimulation. Most fMRI data analysis is carried out using the general linear model (GLM), a statistical approach which predicts the changes in the observed BOLD response based on an expected hemodynamic response function (HRF). In cases when the task is cognitively complex or in cases of diseases, variations in shape and/or delay may reduce the reliability of results. A novel exploratory method using fMRI data, which attempts to discriminate between neurophysiological signals induced by the stimulation protocol from artifacts or other confounding factors, is introduced in this paper. This new method is based on the fusion between correlation analysis and the discrete wavelet transform, to identify similarities in the time course of the BOLD signal in a group of volunteers. We illustrate the usefulness of this approach by analyzing fMRI data from normal subjects presented with standardized human face pictures expressing different degrees of sadness. The results show that the proposed wavelet correlation analysis has greater statistical power than conventional GLM or time domain intersubject correlation analysis. (C) 2010 Elsevier B.V. All rights reserved.

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Simultaneous acquisition of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) aims to disentangle the description of brain processes by exploiting the advantages of each technique. Most studies in this field focus on exploring the relationships between fMRI signals and the power spectrum at some specific frequency bands (alpha, beta, etc.). On the other hand, brain mapping of EEG signals (e.g., interictal spikes in epileptic patients) usually assumes an haemodynamic response function for a parametric analysis applying the GLM, as a rough approximation. The integration of the information provided by the high spatial resolution of MR images and the high temporal resolution of EEG may be improved by referencing them by transfer functions, which allows the identification of neural driven areas without strong assumptions about haemodynamic response shapes or brain haemodynamic`s homogeneity. The difference on sampling rate is the first obstacle for a full integration of EEG and fMRI information. Moreover, a parametric specification of a function representing the commonalities of both signals is not established. In this study, we introduce a new data-driven method for estimating the transfer function from EEG signal to fMRI signal at EEG sampling rate. This approach avoids EEG subsampling to fMRI time resolution and naturally provides a test for EEG predictive power over BOLD signal fluctuations, in a well-established statistical framework. We illustrate this concept in resting state (eyes closed) and visual simultaneous fMRI-EEG experiments. The results point out that it is possible to predict the BOLD fluctuations in occipital cortex by using EEG measurements. (C) 2010 Elsevier Inc. All rights reserved.

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Functional magnetic resonance imaging (fMRI) is currently one of the most widely used methods for studying human brain function in vivo. Although many different approaches to fMRI analysis are available, the most widely used methods employ so called ""mass-univariate"" modeling of responses in a voxel-by-voxel fashion to construct activation maps. However, it is well known that many brain processes involve networks of interacting regions and for this reason multivariate analyses might seem to be attractive alternatives to univariate approaches. The current paper focuses on one multivariate application of statistical learning theory: the statistical discrimination maps (SDM) based on support vector machine, and seeks to establish some possible interpretations when the results differ from univariate `approaches. In fact, when there are changes not only on the activation level of two conditions but also on functional connectivity, SDM seems more informative. We addressed this question using both simulations and applications to real data. We have shown that the combined use of univariate approaches and SDM yields significant new insights into brain activations not available using univariate methods alone. In the application to a visual working memory fMRI data, we demonstrated that the interaction among brain regions play a role in SDM`s power to detect discriminative voxels. (C) 2008 Elsevier B.V. All rights reserved.