A wake-up call: are degenerative diseases provoked by some of our normal food constituents? A case for nutrigenomics.
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Administration, Oral↗
Biomedical subjects
I Søndergaard
Publications and source records attributed to I Søndergaard.
Induction of systemic CTL responses in melanoma patients by dendritic cell vaccination: cessation of CTL responses is associated with disease progression.
Two HLA-A2-positive patients with advanced stage IV melanoma were treated with monocyte-derived dendritic cells (DC) pulsed with either tumor peptide antigens from gp100, MART-1 and MAGE-3 alone or in combination with autologous oncolysates. Clinically, the rapid progression of disease was substantially stalled and both patients were alive for more than 15 months after initiation of therapy. Specific CTL reactivity against several tumor antigens was detectable in peripheral blood, which declined just before reactivation of disease progression. Furthermore, CD3 zeta-chain expression detected by Western lotting was decreased in PBL at this time. In summary, our data confirm that DC-based vaccinations induce peptide-specific T cells in the peripheral blood of advanced-stage melanoma patients. Although successful induction of systemic tumor antigen-specific CTL may not lead to objective clinical tumor regression, their presence are indicative of a prolonged survival.
Aged↗
Classification of wheat varieties: use of two-dimensional gel electrophoresis for varieties that can not be classified by matrix assisted laser desorpiton/ionization-time of flight-mass spectrometry and an artificial neural network.
Analyzing a gliadin extract by matrix assisted laser desorption/ionization-time of flight-mass spectrometry (MALDI-TOF-MS) combined with an artificial neural network (ANN) is a suitable method for identification of wheat varieties. However, the ANN can not distinguish between all different wheat varieties. Two-dimensional polyacrylamide gel electrophoresis (2-D PAGE) was applied to three pairs of wheat varieties, which can not be classified correctly by ANN. By 2-D PAGE the varieties in the three pairs can be discriminated and these six wheat varieties can be separated from each other, which could not be separated by MALDI-TOF-MS and NN.
Electrophoresis, Gel, Two-Dimensional↗
Identification of barley and rye varieties using matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry with neural networks.
Cereal varieties are normally identified using time-consuming methods such as visual examination of either the intact grain or one-dimensional electrophoretic patterns of the grain storage proteins. A fast method for identification of wheat (Triticum aestivum L.) varieties has previously been developed, which combines analysis of alcohol-soluble wheat proteins (gliadins) using matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry with neural networks. Here we have applied the same method for the identification of both barley (Hordeum vulgare L.) and rye (Secale cereale L.) varieties. For barley, 95% of the mass spectra were correctly classified. This is an encouraging result, since in earlier experiments only a grouping into subsets of varieties was possible. However, the method was not useful in the classification of rye, due to the strong similarity between mass spectra of different varieties.
Glutens↗
Poor correspondence between predicted and experimental binding of peptides to class I MHC molecules.
Naturally processed peptides presented by class I major histocompatibility complex (MHC) molecules display a characteristic allele specific motif of two or more essential amino acid side chains, the so-called peptide anchor residues, in the context of an 8-10 amino acid long peptide. Knowledge of the peptide binding motif of individual class I MHC molecules permits the selection of potential peptide antigens from proteins of infectious organisms that could induce protective T-cell-mediated immunity. Several methods have been developed for the prediction of potential class I MHC binding peptides. One is based on a simple scanning for the presence of primary peptide anchor residues in the sequence of interest. A more sophisticated technology is the utilization of predictive computer algorithms. Here, we have analyzed the experimental binding of 84 peptides selected on the basis of the presence of peptide binding motifs for individual class I MHC molecules. The actual binding was compared with the results obtained when analyzing the same peptides by two well-known, publicly available computer algorithms. We conclude that there is no strong correlation between actual and predicted binding when using predictive computer algorithms. Furthermore, we found a high number of false-negatives when using a predictive algorithm compared to simple scanning for the presence of primary anchor residues. We conclude that the peptide binding assay remains an important step in the identification of cytotoxic T lymphocyte (CTL) epitopes which can not be substituted by predictive algorithms.
Algorithms↗
An assay for peptide binding to HLA-Cw*0102.
The assembly assay for peptide binding to class I major histocompatibility complex (MHC) molecules is based on the ability of peptides to stabilize MHC class I molecules synthesized by transporter associated with antigen processing (TAP)-deficient cell. The TAP-deficient cell line T2 has previously been used in the assembly assay to analyze peptide binding to HLA-A*0201 and -B*5101. In this study, we have extended this technique to assay for peptides binding to endogenous HLA-Cw*0102 molecules. We have analyzed the peptide binding of 20 peptides with primary anchor motifs for HLA-Cw*0102. One-third of the peptides analyzed bound with high affinity, half of the peptides examined did not bind, whereas the remaining peptides displayed intermediate binding activity. Interest in HLA-C molecules has increased significantly in recent years, since it has been shown that HLA-C molecules both can present peptides to cytotoxic T lymphocytes (CTL) and in addition are able to inhibit natural killer (NK)-mediated lysis.
Animals↗
From image processing to classification: IV. Classification of electrophoretic patterns by neural networks and statistical methods enable quality assessment of wheat varieties for breadmaking.
The end-use quality of products made from doughs consisting of wheat flour and water is often dependent upon the storage (gluten) proteins of the grain endosperm. Today the electrophoretic patterns of the high molecular weight (HMW) glutenin subunits are used for quality selections in wheat breeding programs in several countries. In this study, we used two multivariate techniques to classify digitized patterns from isoelectric focusing of gliadins and glutenins: a two-layered neural network architecture consisting of a self-organizing feature map and a feed-forward classifier [1], and discriminant analysis [2,3]. Three groups of seven wheat varieties (Triticum aestivum L.), associated with poor, medium or good properties in relation to bread-making quality, were used. The best classification results were obtained by the neural network model, based on data from the gliadin fraction: it was possible to classify varieties associated with poor or good quality, with recognition rates of 70 and 69%, respectively. The statistical method was better suited to solve the classification problem when the data was based on the glutenin fraction: if a specific variety was already known to be non-poor, this method enabled us to classify the medium- and good-quality classes with recognition rates of 90 and 88%, respectively. The results obtained were confirmed by correlation coefficients.
Discriminant Analysis↗
Determinants of decision-making in the screening procedure of a community psychiatric service.
This study is a predictor analysis of the screening procedure followed by a psychiatric service for a period of 1 year preceding and a period of 1 year following the introduction of community psychiatry. Throughout this period, the psychiatric service consisted of a local service within the catchment area and a central service at a psychiatric hospital outside the area. At the time of the reorganization, the responsibility for the psychiatric service was transferred from the public health authorities to the social services. Before the reorganization, screenings were conducted on the basis of referral papers or simply as a result of telephone communication. After the reorganization, the screening procedure was intensified by means of a pre-examination. One aim of the reorganization was to ensure that the severely mentally ill take priority over patients characterized predominantly by social strain. Patients with manic-depressive psychosis and other psychoses showed a significantly increased probability of being accepted for treatment, whereas those with schizophrenia showed no significant increase, irrespective of the service reorganization. Similarly, manic-depressive psychosis and other psychoses (not schizophrenia) were significant predictors of hospitalization at the mental hospital outside the catchment area as well as hospitalization in the local facilities, irrespective of the service reorganization. Indicators of social strain were not given higher priority following the service reorganization.
Adult↗
From image processing to classification: I. Modeling disturbances of isoelectric focusing patterns.
In order to optimize the conditions for evaluation of isoelectric focusing (IEF) patterns by digital image processing, the sources of error in determination of the pI values were analyzed together with the influence of a varying background. The effects of band distortions, in the spectra of the individual lanes, were examined. In order to minimize the effect of these distortions, optimal conditions for handling IEF patterns by digital image processing were elucidated. The systematic part of the global deformation on the gels was investigated and an algorithm was developed by which it was possible to correct for a part of the individual distortions. The effects of various corrections for lane distortions were illustrated by classification, using different types of discriminant analysis. Finally the background disturbances were examined, and described by a mathematical model.
Algorithms↗
From image processing to classification: II. Classification of electrophoretic patterns using self-organizing feature maps and feed-forward neural networks.
In a recent study, isoelectric focusing patterns were classified with a neural network using the back-propagation algorithm [1]. In order to further study the classification process and to generalize the presentation of electrophoretic patterns, Kohonen's self-organizing feature maps [2] were applied in this study. Although these feature maps are very efficient in many pattern recognition tasks, our data proved to be too complex for classification with an unsupervised system. Therefore, a second supervised network on top of the feature map was necessary. As in [3], a feed-forward network trained by the back-propagation algorithm was used. The final system allows us to correctly classify 90% of all wheat varieties. Moreover, the system proved to be reliable, reasonable in training time and shows the same accuracy in different experimental setups.
Algorithms↗
From image processing to classification: III. Matching patterns by shifting and stretching.
A method for the classification of electrophoretic patterns is described and tested on a data set representing ten wheat varieties. The method attempts to match each electropherogram to each variety by a transformation involving displacement and stretching along the x-axis. This is done essentially by the method of least squares, which uses only the information contained in the electropherogram itself to adjust it to the variety in question. The method is completely automatic and works extremely well by classifying 98% of the spectra correctly, judged by cross validation.
Algorithms↗
Classification of wheat varieties by isoelectric focusing patterns of gliadins and neural network.
Classification of wheat varieties, using isoelectric focusing patterns of the gliadins, image processing and neural networks, is described. The method was compared to a statistical classification method, discriminant analysis. The isoelectric point and the area of each band were calculated by image processing. Different methods of presenting the electrophoretic patterns to the neural network were studied. The most effective method was transformation of the electrophoretic pattern to a small (11 x 47 pixels) representation of the original digitized image, which was presented to the neural network as a vector. The neural network was trained with a number of patterns and tested with new patterns from different electrophoretic runs of the same wheat varieties. In this study we used ten different wheat varieties and the neural network was able to classify 95.5% of the patterns correctly. The statistical classification method classified the same data set 91.8% correctly. We conclude that both the neural network and discriminant analysis were able to classify the patterns correctly with a high degree of certainty. The patterns that were misclassified were indistinguishable by visual inspection.
Discriminant Analysis↗
Classification of crossed immunoelectrophoretic patterns using digital image processing and artificial neural networks.
A method is presented which makes it possible to present crossed immunoelectrophoretic patterns to an artificial neural network. The electrophoretic patterns are presented for the artificial neural network as three-dimensional vectors and it is shown that it is possible with this representation to train the network to learn the patterns and classify them. It was found that the ability to generalize was substantially increased by the addition of noise to the input patterns during training. Furthermore, the addition of noise decreased the number of presentations needed to reach the predetermined error level. The trained neural network was able to classify all distorted patterns correctly within an error range of 1%.
Image Processing, Computer-Assisted↗
Evidence of a common regulation of IgE and IgG-subclass antibodies in humans during immunotherapy.
Based on a 3-year prospective study of 20 pollen-allergic patients, where a detailed analysis of the IgE, IgG1 and IgG4 immune response was performed, we propose that a common regulatory mechanism exists between the IgE and IgG1 synthesis and between IgE and IgG4 synthesis during immunotherapy. It was found that the IgE immune response to a number of antigens was quantitatively diminished during the period of immunotherapy when IgG1 was present early (week 12), and for other antigens there was a rise in IgE without an early IgG1 antibody response. Additionally, it was found that for some antigens a rise in IgE antibodies was contrasted by a fall in the IgG4 antibody response and for other antigens the opposite was true, indicating a regulatory mechanism between the IgE and the IgG4 synthesis. A statistical analysis showed that these findings were statistically significant at the 0.01% level for the IgE/IgG1 relationship and at the 0.05% level for the IgE/IgG4 relationship. These findings could have implications for future immunotherapy regimens.
Desensitization, Immunologic↗
A computational approach to the description of individual immune responses. IgE and IgG-subclass allergen-specific antibodies formed during immunotherapy.
Detailed evaluation of the IgE and IgG-subclass immune response during immunotherapy can now be performed by crossed radio immunoelectrophoresis (CRIE). Some new concepts are introduced facilitating the handling of the vast amount of data obtained by quantitating the immune response. These concepts are "distance" between antibody responses and "immune response width". The 20 patients included in this study were pollen-allergic patients who underwent specific immunotherapy in a 3-year prospective study. It was found that the immune response during immunotherapy was restricted to IgG1 and IgG4 antibodies. The semi-quantitative CRIE analysis correlated with the RAST analysis for the IgE samples before start of immunotherapy, for the IgG1 samples at week 12, and for all the IgG4 samples. During immunotherapy the number of IgG1 antibodies directed to the different antigens increased towards 11 antigens and decreased towards six. For the IgG4 antibodies the number of reactions increased towards 15 antigens and decreased towards four. The increase is generally paralleled by an increase in quantitative immune response as well. For some of the antigens a rise in the IgE antibodies is contrasted by a fall in the IgG4 antibody response, and for other antigens the opposite was true, indicating a regulatory mechanism between the IgE and the IgG4 synthesis. The IgE immune response to a number of antigens, including the major allergens before the start of immunotherapy, was quantitatively diminished during the period of immunotherapy when IgG1 was present early (week 12) in the period, and for other antigens there was a rise in IgE without an early IgG1 antibody response. This suggests that IgG1 can have a regulating influence on the IgE synthesis. Finally, we have found that IgE antibodies with specificities not present in the samples taken before immunotherapy were formed during immunotherapy. These new IgE antibodies do not, however, seem to impair the outcome of treatment.
Antigens↗
Allergen-containing immune complexes used for immunotherapy of allergic asthma. II. IgE and IgG immune response during and after hyposensitization of sensitized guinea pigs.
In a previous study guinea pigs inbred for their ability to develop respiratory anaphylaxis to experimental antigens have been used for comparison of different forms of immunotherapy (IT). Passive, active and combined (immune complexes prepared from antigen and specific IgG) IT was compared with placebo. In the present study methods were evaluated for determination of the allergen-specific IgE and IgG. IgE was determined by the passive cutaneous anaphylactic test (PCA) and the variability of this test on different strains of the recipient guinea pig was investigated. The same strain as used for the IT study was found to produce the most potent response. Radioimmunometric assays (RIA) were developed and validated for determination of specific IgG1 and IgG2. The IgE and IgG immune response in animals from the IT study were then evaluated by means of PCA and RIA. Animals from all four treatment groups were sensitized during the first part of the IT study, and responded with a marked IgE synthesis which later stabilized on a more moderate level. In spite of notably reduced symptoms in groups treated with active and combined IT, no difference in the IgE level was found between the four groups. In contrast to IgE, mean group titers of IgG1 and IgG2 in the groups receiving active or combined IT rose drastically during the first part of therapy and closely paralleled the clinical response during the rest of the study period. However, in the individual animals, no correlations were found between immune response and clinical symptoms. Thus, the strong IgG response during immunotherapy may not be causally related to the outcome of treatment.
Animals↗
Immunochemical cross-reactivity between albumin and solid-phase adsorbed histamine.
For production of an antibody against histamine, this was coupled to human serum albumin (HSA) and used for immunization of rabbits. To test the antiserum, an immunoradiometric assay was developed comprising solid-phase bound histamine, antisera and radiolabelled protein A. Titration and inhibition experiments revealed that histamine adsorbed onto a solid-phase could bind the antiserum. However, neither free histamine nor histamine coupled to unrelated carriers could inhibit the binding of antiserum to the solid-phase histamine. Cross-reactivity was demonstrated between HSA and solid-phase bound histamine, as the immunoradiometric assay was inhibited by HSA. This unexpected cross-reactivity was established, as a commercially available antiserum with specificity to HSA without histamine also bound to the solid-phase bound histamine. It is suggested that preparations of antibodies against histamine are tested for this possible cross-reactivity.
Adsorption↗
Improvement of specific immunotherapy by human IgG and modified allergens.
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Allergens↗