Recognition of major histoincompatibilities after transplantation with marrow from HLA closely matched donors.

BACKGROUND: To determine the extent to which major histoincompatibilities are recognized after bone marrow transplantation, we characterized the specificity of the cytotoxic T lymphocytes isolated during graft-versus-host disease. We studied three patients transplanted with marrow from donors who were histoincompatible for different types of HLA antigens. METHODS: Patient 1 was mismatched for one "ABDR-antigen" (HLA-A2 versus A3). Two patients were mismatched for antigens that would usually not be taken into account by standard selection procedures: patient 2 was mismatched for an "HLA-A subtype" (A*0213 versus A*0201), whereas patient 3 was mismatched for HLA-C (HLA-C*0501 versus HLA-C*0701). All three HLA class I mismatches were detected by a pretransplant cytotoxic precursor test. RESULTS: Analysis of the specificity of the cytotoxic T lymphocyte clones isolated after transplantation showed that the incompatibilities detected by the pretransplant cytotoxic precursor assay were the targets recognized during graft-versus-host disease. CONCLUSIONS: Independent of whether the incompatibility consisted of a "full" mismatch, a "subtype" mismatch, or an HLA-C mismatch, all clones recognized the incompatible HLA molecule. In addition, some of these clones had undergone antigen selection and were clearly of higher specificity than the ones established before transplantation, indicating that they had been participating directly in the antihost immune response.

Low TCR avidity and lack of tumor cell recognition in CD8(+) T cells primed with the CEA-analogue CAP1-6D peptide.

The use of "altered peptide ligands" (APL), epitopes designed for exerting increased immunogenicity as compared with native determinants, represents nowadays one of the most utilized strategies for overcoming immune tolerance to self-antigens and boosting anti-tumor T cell-mediated immune responses. However, the actual ability of APL-primed T cells to cross-recognize natural epitopes expressed by tumor cells remains a crucial concern. In the present study, we show that CAP1-6D, a superagonist analogue of a carcinoembriyonic antigen (CEA)-derived HLA-A*0201-restricted epitope widely used in clinical setting, reproducibly promotes the generation of low-affinity CD8(+) T cells lacking the ability to recognized CEA-expressing colorectal carcinoma (CRC) cells. Short-term T cell cultures, obtained by priming peripheral blood mononuclear cells from HLA-A*0201(+) healthy donors or CRC patients with CAP1-6D, were indeed found to heterogeneously cross-react with saturating concentrations of the native peptide CAP1, but to fail constantly lysing or recognizing through IFN- gamma release CEA(+)CRC cells. Characterization of anti-CAP1-6D T cell avidity, gained through peptide titration, CD8-dependency assay, and staining with mutated tetramers (D227K/T228A), revealed that anti-CAP1-6D T cells exerted a differential interaction with the two CEA epitopes, i.e., displaying high affinity/CD8-independency toward the APL and low affinity/CD8-dependency toward the native CAP1 peptide. Our data demonstrate that the efficient detection of self-antigen expressed by tumors could be a feature of high avidity CD8-independent T cells, and underline the need for extensive analysis of tumor cross-recognition prior to any clinical usage of APL as anti-cancer vaccines.

Anàlisi del procés d'inclusió d'un alumne amb deficiència visual durant l'etapa d'educació infantil

L’objectiu d’aquest treball és analitzar la inclusió d’un infant amb deficiència visual durant l’etapa d’Educació Infantil, amb la finalitat d’establir propostes de millora al centre encaminades a potenciar mesures per a la inclusió de tot l’alumnat. Per a la realització d’aquest estudi primerament ha estat necessari conèixer la fonamentació teòrica del concepte de visió i d’inclusió escolar, així com també les implicacions per part del centre, la família i l’entorn. Per a realitzar aquest anàlisi hem utilitzat entrevistes i pautes d’observació validades, amb la finalitat de conèixer més a fons la trajectòria de l’infant a l’etapa d’Educació Infantil, sempre des d’una concepció interaccionista, és a dir, tenint en compte l’àmbit escolar, familiar i l’entorn. I ja per acabar, aquest anàlisi ha servit per a proposar propostes de millora per a la inclusió de futurs alumnes en el centre.

Maximum likelihood Linear Programming Data Fusion for Speaker Recognition

Biometric system performance can be improved by means of data fusion. Several kinds of information can be fused in order to obtain a more accurate classification (identification or verification) of an input sample. In this paper we present a method for computing the weights in a weighted sum fusion for score combinations, by means of a likelihood model. The maximum likelihood estimation is set as a linear programming problem. The scores are derived from a GMM classifier working on a different feature extractor. Our experimental results assesed the robustness of the system in front a changes on time (different sessions) and robustness in front a change of microphone. The improvements obtained were significantly better (error bars of two standard deviations) than a uniform weighted sum or a uniform weighted product or the best single classifier. The proposed method scales computationaly with the number of scores to be fussioned as the simplex method for linear programming.

Application of the Mutual Information Minimization to speaker recognition / identification improvement

In this paper we propose the inversion of nonlinear distortions in order to improve the recognition rates of a speaker recognizer system. We study the effect of saturations on the test signals, trying to take into account real situations where the training material has been recorded in a controlled situation but the testing signals present some mismatch with the input signal level (saturations). The experimental results for speaker recognition shows that a combination of several strategies can improve the recognition rates with saturated test sentences from 80% to 89.39%, while the results with clean speech (without saturation) is 87.76% for one microphone, and for speaker identification can reduce the minimum detection cost function with saturated test sentences from 6.42% to 4.15%, while the results with clean speech (without saturation) is 5.74% for one microphone and 7.02% for the other one.

Improving a leaves automatic recognition process using PCA

In this work we present a simulation of a recognition process with perimeter characterization of a simple plant leaves as a unique discriminating parameter. Data coding allowing for independence of leaves size and orientation may penalize performance recognition for some varieties. Border description sequences are then used, and Principal Component Analysis (PCA) is applied in order to study which is the best number of components for the classification task, implemented by means of a Support Vector Machine (SVM) System. Obtained results are satisfactory, and compared with [4] our system improves the recognition success, diminishing the variance at the same time.

Automatic Recognition of Leaves by Shape Detection Pre-Processing with Ica

In this work we present a simulation of a recognition process with perimeter characterization of a simple plant leaves as a unique discriminating parameter. Data coding allowing for independence of leaves size and orientation may penalize performance recognition for some varieties. Border description sequences are then used to characterize the leaves. Independent Component Analysis (ICA) is then applied in order to study which is the best number of components to be considered for the classification task, implemented by means of an Artificial Neural Network (ANN). Obtained results with ICA as a pre-processing tool are satisfactory, and compared with some references our system improves the recognition success up to 80.8% depending on the number of considered independent components.

Empirical mode decomposition-based face recognition system

In this work we explore the multivariate empirical mode decomposition combined with a Neural Network classifier as technique for face recognition tasks. Images are simultaneously decomposed by means of EMD and then the distance between the modes of the image and the modes of the representative image of each class is calculated using three different distance measures. Then, a neural network is trained using 10- fold cross validation in order to derive a classifier. Preliminary results (over 98 % of classification rate) are satisfactory and will justify a deep investigation on how to apply mEMD for face recognition.

Dyslexia in a French-Spanish bilingual girl: behavioural and neural modulations following a visual attention span intervention.

We report the case study of a French-Spanish bilingual dyslexic girl, MP, who exhibited a severe visual attention (VA) span deficit but preserved phonological skills. Behavioural investigation showed a severe reduction of reading speed for both single items (words and pseudo-words) and texts in the two languages. However, performance was more affected in French than in Spanish. MP was administered an intensive VA span intervention programme. Pre-post intervention comparison revealed a positive effect of intervention on her VA span abilities. The intervention further transferred to reading. It primarily resulted in faster identification of the regular and irregular words in French. The effect of intervention was rather modest in Spanish that only showed a tendency for faster word reading. Text reading improved in the two languages with a stronger effect in French but pseudo-word reading did not improve in either French or Spanish. The overall results suggest that VA span intervention may primarily enhance the fast global reading procedure, with stronger effects in French than in Spanish. MP underwent two fMRI sessions to explore her brain activations before and after VA span training. Prior to the intervention, fMRI assessment showed that the striate and extrastriate visual cortices alone were activated but none of the regions typically involved in VA span. Post-training fMRI revealed increased activation of the superior and inferior parietal cortices. Comparison of pre- and post-training activations revealed significant activation increase of the superior parietal lobes (BA 7) bilaterally. Thus, we show that a specific VA span intervention not only modulates reading performance but further results in increased brain activity within the superior parietal lobes known to housing VA span abilities. Furthermore, positive effects of VA span intervention on reading suggest that the ability to process multiple visual elements simultaneously is one cause of successful reading acquisition.

Visual cortex in Alzheimer's disease: occurrence of neuronal death and glial proliferation, and correlation with pathological hallmarks.

Visual areas 17 and 18 were studied with morphometric methods for numbers of neurons, glia, senile plaques (SP), and neurofibrillary tangles (NFT) in 13 cases of Alzheimer's disease (AD) as compared to 11 controls. In AD cases, the mean neuronal density was significantly decreased by about 30% in both areas 17 and 18, while the glial density was increased significantly only in area 17. The volume of area 17 was unchanged in AD cases but its total number of neurons was decreased by 33% and its total number of glia increased by 45% compared to controls. In AD the number of SP was similar in areas 17 and 18, while that of NFT was significantly higher in area 18. The number of neurons with NFT was only 2% in area 17 and about 10% in area 18. The discrepancy between the loss of neurons and the amount of NFT suggests that neuronal loss can occur without passing through NFT degeneration. The deposition of SP was correlated with glial proliferation, but not with neuronal loss or neurofibrillary degeneration.