Melanoma patients respond to a cytotoxic T lymphocyte-defined self-peptide with diverse and nonoverlapping T-cell receptor repertoires.

HLA-A2+ melanoma patients develop naturally a strong CD8+ T cell response to a self-peptide derived from Melan-A. Here, we have used HLA-A2/peptide tetramers to isolate Melan-A-specific T cells from tumor-infiltrated lymph nodes of two HLA-A2+ melanoma patients and analyzed their TCR beta chain V segment and complementarity determining region 3 length and sequence. We found a broad diversity in Melan-A-specific immune T-cell receptor (TCR) repertoires in terms of both TCR beta chain variable gene segment usage and clonal composition. In addition, immune TCR repertoires selected in the patients were not overlapping. In contrast to previously characterized CD8+ T-cell responses to viral infections, this study provides evidence against usage of highly restricted TCR repertoire in the natural response to a self-differentiation tumor antigen.

Fronts from two-dimensional dispersal kernels: Beyond the nonoverlapping-generations model

Most integrodifference models of biological invasions are based on the nonoverlapping-generations approximation. However, the effect of multiple reproduction events overlapping generations on the front speed can be very important especially for species with a long life spam . Only in one-dimensional space has this approximation been relaxed previously, although almost all biological invasions take place in two dimensions. Here we present a model that takes into account the overlapping generations effect or, more generally, the stage structure of the population , and we analyze the main differences with the corresponding nonoverlappinggenerations results

Percentage of nonoverlapping corrected data

The present study proposes a modification in one of the most frequently applied effect size procedures in single-case data analysis the percent of nonoverlapping data. In contrast to other techniques, the calculus and interpretation of this procedure is straightforward and it can be easily complemented by visual inspection of the graphed data. Although the percent of nonoverlapping data has been found to perform reasonably well in N = 1 data, the magnitude of effect estimates it yields can be distorted by trend and autocorrelation. Therefore, the data correction procedure focuses on removing the baseline trend from data prior to estimating the change produced in the behavior due to intervention. A simulation study is carried out in order to compare the original and the modified procedures in several experimental conditions. The results suggest that the new proposal is unaffected by trend and autocorrelation and can be used in case of unstable baselines and sequentially related measurements.

Morphological and molecular heterogeneity within nonmicrosatellite instability-high colorectal cancer

Colorectal cancer (CRC) has traditionally been classified into two groups: microsatellite stable/low-level instability (MSS/MSI-L) and high-level MSI (MSI-H) groups on the basis of multiple molecular and clinicopathologic criteria. Using methylated in tumor (MINT) markers 1, 2,12, and 31, we stratified 77 primary CRCs into three groups: MINT++ (>2), MINT+ (1-2), and MINT- (0 markers methylated). The MSS/MSI-L/ MINT++ group was indistinguishable from the MSI-H/MINT++ group with respect to methylation of p16(INK4a), p14(ARF), and RIZ1, and multiple morphological features. The only significant difference between MSI-H and non-MSI-H MINT++ cancers was the higher frequency of K-ras mutation (P < 0.004) and lower frequency of hMLH1 methylation (P < 0.001) in the latter. These data demonstrate that the separation of CRC into two nonoverlapping groups (MSI-H versus MSS/MSI-L) is a misleading oversimplification.

Direct visualization of Ras proteins in spatially distinct cell surface microdomains

Localization of signaling complexes to specific micro-domains coordinates signal transduction at the plasma membrane. Using immunogold electron microscopy of plasma membrane sheets coupled with spatial point pattern analysis, we have visualized morphologically featureless microdomains including lipid rafts, in situ and at high resolution. We find that an inner-plasma membrane lipid raft marker displays cholesterol-dependent clustering in microdomains with a mean diameter of 44 nm that occupy 35% of the cell surface. Cross-linking an outer-leaflet raft protein results in the redistribution of inner leaflet rafts, but they retain their modular structure. Analysis of Ras microlocalization shows that inactive H-ras is distributed between lipid rafts and a cholesterol-independent micro-domain. Conversely, activated H-ras and K-ras reside predominantly in nonoverlapping, cholesterol-independent microdomains. Galectin-1 stabilizes the association of activated H-ras with these nonraft microdomains, whereas K-ras clustering is supported by farnesylation, but not geranylgeranylation. These results illustrate that the inner plasma membrane comprises a complex mosaic of discrete microdomains. Differential spatial localization within this framework can likely account for the distinct signal outputs from the highly homologous Ras proteins.

Identification of cholinoceptive glycinergic neurons in the mammalian retina

The light-evoked release of acetylcholine (ACh) affects the responses of many retinal ganglion cells, in part via nicotinic acetylcholine receptors (nAChRs). nAChRs that contain beta2alpha3 neuronal nicotinic acetylcholine receptors have been identified and localized in the rabbit retina; these nAChRs are recognized by the monoclonal antibody mAb210. We have examined the expression of beta2alpha3 nAChRs by glycinergic amacrine cells in the rabbit retina and have identified different subpopulations of nicotinic cholinoceptive glycinergic cells using double and triple immunohistochemistry with quantitative analysis. Here we demonstrate that about 70% of the cholinoceptive amacrine cells in rabbit retina are glycinergic cells. At least three nonoverlapping subpopulations of mAb210 glycine-immunoreactive cells can be distinguished with antibodies against calretinin, calbindin, and gamma-aminobutyric acid (GABA)(A) receptors. The cholinergic cells in rabbit retina are thought to synapse only on other cholinergic cells and ganglion cells. Thus, the expression of beta2alpha3 nAChRs on diverse populations of glycinergic cells is puzzling. To explore this finding, the subcellular localization of beta2alpha3 was studied at the electron microscopic level. mAb210 immunoreactivity was localized on the dendrites of amacrines and ganglion cells throughout the inner plexiform layer, and much of the labeling was not associated with recognizable synapses. Thus, our findings indicate that ACh in the mammalian retina may modulate glycinergic circuits via extrasynaptic beta2alpha3 nAChRs. (C) 2002 Wiley-Liss, Inc.

A shared-disk parallel cluster file system

Dissertação apresentada para obtenção do Grau de Doutor em Informática Pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Identification of key amino acids of the mouse mammary tumor virus superantigen involved in the specific interaction with T-cell receptor V(beta) domains.

Mouse mammary tumor virus (MMTV) is a retrovirus encoding a superantigen that is recognized in association with major histocompatibility complex class II by the variable region of the beta chain (V(beta)) of the T-cell receptor. The C-terminal 30 to 40 amino acids of the superantigen of different MMTVs display high sequence variability that correlates with the recognition of particular T-cell receptor V(beta) chains. Interestingly, MMTV(SIM) and mtv-8 superantigens are highly homologous but have nonoverlapping T-cell receptor V(beta) specificities. To determine the importance of these few differences for specific V(beta) interaction, we studied superantigen responses in mice to chimeric and mutant MMTV(SIM) and mtv-8 superantigens expressed by recombinant vaccinia viruses. We show that only a few changes (two to six residues) within the C terminus are necessary to modify superantigen recognition by specific V(beta)s. Thus, the introduction of the MMTV(SIM) residues 314-315 into the mtv-8 superantigen greatly decreased its V(beta)12 reactivity without gain of MMTV(SIM)-specific function. The introduction of MMTV(SIM)-specific residues 289 to 295, however, induced a recognition pattern that was a mixture of MMTV(SIM)- and mtv-8-specific V(beta) reactivities: both weak MMTV(SIM)-specific V(beta)4 and full mtv-8-specific V(beta)11 recognition were observed while V(beta)12 interaction was lost. The combination of the two MMTV(SIM)-specific regions in the mtv-8 superantigen established normal MMTV(SIM)-specific V(beta)4 reactivity and completely abolished mtv-8-specific V(beta)5, -11, and -12 interactions. These new functional superantigens with mixed V(beta) recognition patterns allowed us to precisely delineate sites relevant for molecular interactions between the SIM or mtv-8 superantigen and the T-cell receptor V(beta) domain within the 30 C-terminal residues of the viral superantigen.

Brain tissue properties differentiate between motor and limbic basal ganglia circuits.

Despite advances in understanding basic organizational principles of the human basal ganglia, accurate in vivo assessment of their anatomical properties is essential to improve early diagnosis in disorders with corticosubcortical pathology and optimize target planning in deep brain stimulation. Main goal of this study was the detailed topological characterization of limbic, associative, and motor subdivisions of the subthalamic nucleus (STN) in relation to corresponding corticosubcortical circuits. To this aim, we used magnetic resonance imaging and investigated independently anatomical connectivity via white matter tracts next to brain tissue properties. On the basis of probabilistic diffusion tractography we identified STN subregions with predominantly motor, associative, and limbic connectivity. We then computed for each of the nonoverlapping STN subregions the covariance between local brain tissue properties and the rest of the brain using high-resolution maps of magnetization transfer (MT) saturation and longitudinal (R1) and transverse relaxation rate (R2*). The demonstrated spatial distribution pattern of covariance between brain tissue properties linked to myelin (R1 and MT) and iron (R2*) content clearly segregates between motor and limbic basal ganglia circuits. We interpret the demonstrated covariance pattern as evidence for shared tissue properties within a functional circuit, which is closely linked to its function. Our findings open new possibilities for investigation of changes in the established covariance pattern aiming at accurate diagnosis of basal ganglia disorders and prediction of treatment outcome.

Assembling genes from predicted exons in linear time with dynamic programming

In a number of programs for gene structure prediction in higher eukaryotic genomic sequences, exon prediction is decoupled from gene assembly: a large pool of candidate exons is predicted and scored from features located in the query DNA sequence, and candidate genes are assembled from such a pool as sequences of nonoverlapping frame-compatible exons. Genes are scored as a function of the scores of the assembled exons, and the highest scoring candidate gene is assumed to be the most likely gene encoded by the query DNA sequence. Considering additive gene scoring functions, currently available algorithms to determine such a highest scoring candidate gene run in time proportional to the square of the number of predicted exons. Here, we present an algorithm whose running time grows only linearly with the size of the set of predicted exons. Polynomial algorithms rely on the fact that, while scanning the set of predicted exons, the highest scoring gene ending in a given exon can be obtained by appending the exon to the highest scoring among the highest scoring genes ending at each compatible preceding exon. The algorithm here relies on the simple fact that such highest scoring gene can be stored and updated. This requires scanning the set of predicted exons simultaneously by increasing acceptor and donor position. On the other hand, the algorithm described here does not assume an underlying gene structure model. Indeed, the definition of valid gene structures is externally defined in the so-called Gene Model. The Gene Model specifies simply which gene features are allowed immediately upstream which other gene features in valid gene structures. This allows for great flexibility in formulating the gene identification problem. In particular it allows for multiple-gene two-strand predictions and for considering gene features other than coding exons (such as promoter elements) in valid gene structures.

Specificity and affinity of monoclonal antibodies against carcinoembryonic antigen.

The binding specificities of 52 well-characterized monoclonal antibodies (Mabs) against carcinoembryonic antigen (CEA) from 12 different research groups were studied by immunohistochemistry and immuno flow cytometry. In addition, the binding constant for the interaction between Mab and CEA was determined by a solution-phase assay. Cryostat sections of colon carcinoma and normal colon, stomach, liver, pancreas, and spleen were studied by immunohistochemistry. Peripheral blood granulocytes, monocytes, and lymphocytes were assayed by immuno flow cytometry. The Mabs used here have previously been classified into five essentially nonoverlapping epitope groups (GOLD 1-5) (Cancer Res., 49: 4852-4858, 1989). Most Mabs cross-reacted with different normal tissues, ranging from highly cross-reactive Mabs (positive reaction with 8 of 9 discriminating tissues) to relatively specific Mabs (positive reaction with 1 of 9 discriminating tissues). Five Mabs (10%) were specific, reacting only with colon carcinoma, normal colon mucosa, and normal gastric foveola. There was a correlation between epitope group and binding specificity. Mabs with a high degree of CEA specificity almost exclusively belonged to epitope groups 1, 2, and 3, while highly cross-reactive Mabs belonged to epitope groups 4 and 5. There was no correlation between antibody specificity and affinity for CEA. Specific Mabs with high as well as low affinity were found.

Comparing 'visual' effect size indices for single-case designs

Effect size indices are indispensable for carrying out meta-analyses and can also be seen as an alternative for making decisions about the effectiveness of a treatment in an individual applied study. The desirable features of the procedures for quantifying the magnitude of intervention effect include educational/clinical meaningfulness, calculus easiness, insensitivity to autocorrelation, low false alarm and low miss rates. Three effect size indices related to visual analysis are compared according to the aforementioned criteria. The comparison is made by means of data sets with known parameters: degree of serial dependence, presence or absence of general trend, changes in level and/or in slope. The percent of nonoverlapping data showed the highest discrimination between data sets with and without intervention effect. In cases when autocorrelation or trend is present, the percentage of data points exceeding the median may be a better option to quantify the effectiveness of a psychological treatment.

Choosing among techniques for quantifying single-case intervention effectiveness

If single case experimental designs are to be used to establish guidelines for evidence-based interventions in clinical and educational settings, numerical values that reflect treatment effect sizes are required. The present study compares four recently developed procedures for quantifying the magnitude of intervention effect using data with known characteristics. Monte Carlo methods were used to generate AB designs data with potential confounding variables (serial dependence, linear and curvilinear trend, and heteroscedasticity between phases) and two types of treatment effect (level and slope change). The results suggest that data features are important for choosing the appropriate procedure and, thus, inspecting the graphed data visually is a necessary initial stage. In the presence of serial dependence or a change in data variability, the Nonoverlap of All Pairs (NAP) and the Slope and Level Change (SLC) were the only techniques of the four examined that performed adequately. Introducing a data correction step in NAP renders it unaffected by linear trend, as is also the case for the Percentage of Nonoverlapping Corrected Data and SLC. The performance of these techniques indicates that professionals" judgments concerning treatment effectiveness can be readily complemented by both visual and statistical analyses. A flowchart to guide selection of techniques according to the data characteristics identified by visual inspection is provided.

Natural gene-expression variation in Down syndrome modulates the outcome of gene-dosage imbalance.

Down syndrome (DS) is characterized by extensive phenotypic variability, with most traits occurring in only a fraction of affected individuals. Substantial gene-expression variation is present among unaffected individuals, and this variation has a strong genetic component. Since DS is caused by genomic-dosage imbalance, we hypothesize that gene-expression variation of human chromosome 21 (HSA21) genes in individuals with DS has an impact on the phenotypic variability among affected individuals. We studied gene-expression variation in 14 lymphoblastoid and 17 fibroblast cell lines from individuals with DS and an equal number of controls. Gene expression was assayed using quantitative real-time polymerase chain reaction on 100 and 106 HSA21 genes and 23 and 26 non-HSA21 genes in lymphoblastoid and fibroblast cell lines, respectively. Surprisingly, only 39% and 62% of HSA21 genes in lymphoblastoid and fibroblast cells, respectively, showed a statistically significant difference between DS and normal samples, although the average up-regulation of HSA21 genes was close to the expected 1.5-fold in both cell types. Gene-expression variation in DS and normal samples was evaluated using the Kolmogorov-Smirnov test. According to the degree of overlap in expression levels, we classified all genes into 3 groups: (A) nonoverlapping, (B) partially overlapping, and (C) extensively overlapping expression distributions between normal and DS samples. We hypothesize that, in each cell type, group A genes are the most dosage sensitive and are most likely involved in the constant DS traits, group B genes might be involved in variable DS traits, and group C genes are not dosage sensitive and are least likely to participate in DS pathological phenotypes. This study provides the first extensive data set on HSA21 gene-expression variation in DS and underscores its role in modulating the outcome of gene-dosage imbalance.

Reversible and high capacity data hiding in medical images

In this paper we introduce a highly efficient reversible data hiding system. It is based on dividing the image into tiles and shifting the histograms of each image tile between its minimum and maximum frequency. Data are then inserted at the pixel level with the largest frequency to maximize data hiding capacity. It exploits the special properties of medical images, where the histogram of their nonoverlapping image tiles mostly peak around some gray values and the rest of the spectrum is mainlyempty. The zeros (or minima) and peaks (maxima) of the histograms of the image tiles are then relocated to embed the data. The grey values of some pixels are therefore modified.High capacity, high fidelity, reversibility and multiple data insertions are the key requirements of data hiding in medical images. We show how histograms of image tiles of medical images can be exploited to achieve these requirements. Compared with data hiding method applied to the whole image, our scheme can result in 30%-200% capacity improvement and still with better image quality, depending on the medical image content. Additional advantages of the proposed method include hiding data in the regions of non-interest and better exploitation of spatial masking.