971 resultados para Class I cavities
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Aims: An important consideration in the design of a tumour vaccine is the ability of tumour-specific cytotoxic T lymphocytes (CTL) to recognise unmanipulated tumour cells in vivo. To determine whether B-CLL might use an escape strategy, the current studies compared B-CLL and normal B cell MHC class I expression. Methods: Flow cytometry, TAP allele PCR and MHC class I PCR were used. Results: While baseline expression of MHC class I did not differ, upregulation of MHC class I expression by B-CLL cells in response to IFN-gamma was reduced. No deletions or mutations of TAP 1 or 2 genes were detected. B-CLL cells upregulated TAP protein expression in response to IFN-gamma. Responsiveness of B-CLL MHC class I mRNA to IFN-gamma was not impaired. Conclusions: The data suggest that MHC class I molecules might be less stable at the cell surface in B-CLL than normal B cells, as a result of the described release of beta(2)m and beta(2)m-free class I heavy chains from the membrane. This relative MHC class I expression defect of B-CLL cells may reduce their susceptibility to CTL lysis in response to immunotherapeutic approaches.
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The underlying generic properties of {alpha}β TCRs that control MHC restriction remain largely unresolved. To investigate MHC restriction, we have examined the CTL response to a viral epitope that binds promiscuously to two human leukocyte Ags (HLAs) that differ by a single amino acid at position 156. Individuals expressing either HLA-B*3501 (156Leucine) or HLA-B*3508 (156Arginine) showed a potent CTL response to the 407HPVGEADYFEY417 epitope from EBV. Interestingly, the response was characterized by highly restricted TCR β-chain usage in both HLA-B*3501+ and HLA-B*3508+ individuals; however, this conserved TRBV9+ β-chain was associated with distinct TCR {alpha}-chains depending upon the HLA-B*35 allele expressed by the virus-exposed host. Functional assays confirmed that TCR {alpha}-chain usage determined the HLA restriction of the CTLs. Structural studies revealed significant differences in the mobility of the peptide when bound to HLA-B*3501 or HLA-B*3508. In HLA-B*3501, the bulged section of the peptide was disordered, whereas in HLA-B*3508 the bulged epitope adopted an ordered conformation. Collectively, these data demonstrate not only that mobile MHC-bound peptides can be highly immunogenic but can also stimulate an extremely biased TCR repertoire. In addition, TCR {alpha}-chain usage is shown to play a critical role in controlling MHC restriction between closely related allomorphs.
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T cell receptor (TCR) recognition of peptide-MHC class I (pMHC) complexes is a crucial event in the adaptive immune response to pathogens. Peptide epitopes often display a strong dominance hierarchy, resulting in focusing of the response on a limited number of the most dominant epitopes. Such T cell responses may be additionally restricted by particular MHC alleles in preference to others. We have studied this poorly understood phenomenon using Theileria parva, a protozoan parasite that causes an often fatal lymphoproliferative disease in cattle. Despite its antigenic complexity, CD8+ T cell responses induced by infection with the parasite show profound immunodominance, as exemplified by the Tp1(214-224) epitope presented by the common and functionally important MHC class I allele N*01301. We present a high-resolution crystal structure of this pMHC complex, demonstrating that the peptide is presented in a distinctive raised conformation. Functional studies using CD8+ T cell clones show that this impacts significantly on TCR recognition. The unconventional structure is generated by a hydrophobic ridge within the MHC peptide binding groove, found in a set of cattle MHC alleles. Extremely rare in all other species, this feature is seen in a small group of mouse MHC class I molecules. The data generated in this analysis contribute to our understanding of the structural basis for T cell-dependent immune responses, providing insight into what determines a highly immunogenic p-MHC complex, and hence can be of value in prediction of antigenic epitopes and vaccine design.
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Antigenic peptide is presented to a T-cell receptor (TCR) through the formation of a stable complex with a major histocompatibility complex (MHC) molecule. Various predictive algorithms have been developed to estimate a peptide's capacity to form a stable complex with a given MHC class II allele, a technique integral to the strategy of vaccine design. These have previously incorporated such computational techniques as quantitative matrices and neural networks. A novel predictive technique is described, which uses molecular modeling of predetermined crystal structures to estimate the stability of an MHC class II-peptide complex. The structures are remodeled, energy minimized, and annealed before the energetic interaction is calculated.
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Quantitative structure-activity relationship (QSAR) analysis is a cornerstone of modern informatics. Predictive computational models of peptide-major histocompatibility complex (MHC)-binding affinity based on QSAR technology have now become important components of modern computational immunovaccinology. Historically, such approaches have been built around semiqualitative, classification methods, but these are now giving way to quantitative regression methods. We review three methods--a 2D-QSAR additive-partial least squares (PLS) and a 3D-QSAR comparative molecular similarity index analysis (CoMSIA) method--which can identify the sequence dependence of peptide-binding specificity for various class I MHC alleles from the reported binding affinities (IC50) of peptide sets. The third method is an iterative self-consistent (ISC) PLS-based additive method, which is a recently developed extension to the additive method for the affinity prediction of class II peptides. The QSAR methods presented here have established themselves as immunoinformatic techniques complementary to existing methodology, useful in the quantitative prediction of binding affinity: current methods for the in silico identification of T-cell epitopes (which form the basis of many vaccines, diagnostics, and reagents) rely on the accurate computational prediction of peptide-MHC affinity. We have reviewed various human and mouse class I and class II allele models. Studied alleles comprise HLA-A*0101, HLA-A*0201, HLA-A*0202, HLA-A*0203, HLA-A*0206, HLA-A*0301, HLA-A*1101, HLA-A*3101, HLA-A*6801, HLA-A*6802, HLA-B*3501, H2-K(k), H2-K(b), H2-D(b) HLA-DRB1*0101, HLA-DRB1*0401, HLA-DRB1*0701, I-A(b), I-A(d), I-A(k), I-A(S), I-E(d), and I-E(k). In this chapter we show a step-by-step guide into predicting the reliability and the resulting models to represent an advance on existing methods. The peptides used in this study are available from the AntiJen database (http://www.jenner.ac.uk/AntiJen). The PLS method is available commercially in the SYBYL molecular modeling software package. The resulting models, which can be used for accurate T-cell epitope prediction, will be made are freely available online at the URL http://www.jenner.ac.uk/MHCPred.
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The accurate in silico identification of T-cell epitopes is a critical step in the development of peptide-based vaccines, reagents, and diagnostics. It has a direct impact on the success of subsequent experimental work. Epitopes arise as a consequence of complex proteolytic processing within the cell. Prior to being recognized by T cells, an epitope is presented on the cell surface as a complex with a major histocompatibility complex (MHC) protein. A prerequisite therefore for T-cell recognition is that an epitope is also a good MHC binder. Thus, T-cell epitope prediction overlaps strongly with the prediction of MHC binding. In the present study, we compare discriminant analysis and multiple linear regression as algorithmic engines for the definition of quantitative matrices for binding affinity prediction. We apply these methods to peptides which bind the well-studied human MHC allele HLA-A*0201. A matrix which results from combining results of the two methods proved powerfully predictive under cross-validation. The new matrix was also tested on an external set of 160 binders to HLA-A*0201; it was able to recognize 135 (84%) of them.
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Cleavage by the proteasome is responsible for generating the C terminus of T-cell epitopes. Modeling the process of proteasome cleavage as part of a multi-step algorithm for T-cell epitope prediction will reduce the number of non-binders and increase the overall accuracy of the predictive algorithm. Quantitative matrix-based models for prediction of the proteasome cleavage sites in a protein were developed using a training set of 489 naturally processed T-cell epitopes (nonamer peptides) associated with HLA-A and HLA-B molecules. The models were validated using an external test set of 227 T-cell epitopes. The performance of the models was good, identifying 76% of the C-termini correctly. The best model of proteasome cleavage was incorporated as the first step in a three-step algorithm for T-cell epitope prediction, where subsequent steps predicted TAP affinity and MHC binding using previously derived models.
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Background - The binding between peptide epitopes and major histocompatibility complex proteins (MHCs) is an important event in the cellular immune response. Accurate prediction of the binding between short peptides and the MHC molecules has long been a principal challenge for immunoinformatics. Recently, the modeling of MHC-peptide binding has come to emphasize quantitative predictions: instead of categorizing peptides as "binders" or "non-binders" or as "strong binders" and "weak binders", recent methods seek to make predictions about precise binding affinities. Results - We developed a quantitative support vector machine regression (SVR) approach, called SVRMHC, to model peptide-MHC binding affinities. As a non-linear method, SVRMHC was able to generate models that out-performed existing linear models, such as the "additive method". By adopting a new "11-factor encoding" scheme, SVRMHC takes into account similarities in the physicochemical properties of the amino acids constituting the input peptides. When applied to MHC-peptide binding data for three mouse class I MHC alleles, the SVRMHC models produced more accurate predictions than those produced previously. Furthermore, comparisons based on Receiver Operating Characteristic (ROC) analysis indicated that SVRMHC was able to out-perform several prominent methods in identifying strongly binding peptides. Conclusion - As a method with demonstrated performance in the quantitative modeling of MHC-peptide binding and in identifying strong binders, SVRMHC is a promising immunoinformatics tool with not inconsiderable future potential.
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Quantitative structure–activity relationship (QSAR) analysis is a main cornerstone of modern informatic disciplines. Predictive computational models, based on QSAR technology, of peptide-major histocompatibility complex (MHC) binding affinity have now become a vital component of modern day computational immunovaccinology. Historically, such approaches have been built around semi-qualitative, classification methods, but these are now giving way to quantitative regression methods. The additive method, an established immunoinformatics technique for the quantitative prediction of peptide–protein affinity, was used here to identify the sequence dependence of peptide binding specificity for three mouse class I MHC alleles: H2–Db, H2–Kb and H2–Kk. As we show, in terms of reliability the resulting models represent a significant advance on existing methods. They can be used for the accurate prediction of T-cell epitopes and are freely available online (http://www.jenner.ac.uk/MHCPred).
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Objectives To evaluate the change in masticatory efficiency and quality of life of patients treated with mandibular Kennedy class I removable partial dentures (RPDs) and maxillary complete dentures at the Department of Dentistry of the Federal University of Rio Grande do Norte. Materials and methods A total of 33 Kennedy class I patients were rehabilitated with maxillary complete dentures, and mandibular RPDs were selected for this non-randomized prospective intervention study. The patients had a mean age of 59.1 years. Masticatory efficiency was evaluated by colorimetric assay using fuchsin capsules. The measurements were conducted at baseline and 2 and 6 months after prosthesis insertion. Quality of life was evaluated using the Oral Health Impact Profile (OHIP-14) at baseline and 6 months after denture insertion. The Kolmogorov-Smirnov normality test was applied. Masticatory efficiency was evaluated by repeated measures ANOVA. Oral health-related quality of life was compared using the paired t test. Results There was no statistically significant difference in masticatory efficiency after denture insertion (p = 0.101). Significant differences were found (p = 0.010) for oral health-related quality of life. A significant improvement in psychological discomfort (p < 0.01) and psychological disability (p < 0.01) was observed. Mean difference value (95 % confidence interval) was 6.8 (3.8 to 9.7) points, reflecting a low impact of oral health on quality of life, considering the 0–56 range of variation of the OHIP-14 and a Cohen’s d of 1.13. Conclusion According to the results of the present study, rehabilitation with Kennedy class I RPDs and complete dentures did not influence masticatory efficiency but improved oral health-related quality of life. Clinical relevance The association between the patient’s quality of life and the masticatory efficiency is important for treatment predictability.
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La présentation d'antigène par les molécules d'histocompatibilité majeure de classe I (CMHI) permet au système immunitaire adaptatif de détecter et éliminer les agents pathogènes intracellulaires et des cellules anormales. La surveillance immunitaire est effectuée par les lymphocytes T CD8 qui interagissent avec le répertoire de peptides associés au CMHI présentés à la surface de toutes cellules nucléées. Les principaux gènes humains de CMHI, HLA-A et HLA-B, sont très polymorphes et par conséquent montrent des différences dans la présentation des antigènes. Nous avons étudié les différences qualitatives et quantitatives dans l'expression et la liaison peptidique de plusieurs allotypes HLA. Utilisant la technique de cytométrie de flux quantitative nous avons établi une hiérarchie d'expression pour les quatre HLA-A, B allotypes enquête. Nos résultats sont compatibles avec une corrélation inverse entre l'expression allotypique et la diversité des peptides bien que d'autres études soient nécessaires pour consolider cette hypothèse. Les origines mondiales du répertoire de peptides associés au CMHI restent une question centrale à la fois fondamentalement et dans la recherche de cibles immunothérapeutiques. Utilisant des techniques protéogénomiques, nous avons identifié et analysé 25,172 peptides CMHI isolées à partir des lymphocytes B de 18 personnes qui exprime collectivement 27 allotypes HLA-A,B. Alors que 58% des gènes ont été la source de 1-64 peptides CMHI par gène, 42% des gènes ne sont pas représentés dans l'immunopeptidome. Dans l'ensemble, l’immunopeptidome présenté par 27 allotypes HLA-A,B ne couvrent que 17% des séquences exomiques exprimées dans les cellules des sujets. Nous avons identifié plusieurs caractéristiques des transcrits et des protéines qui améliorent la production des peptides CMHI. Avec ces données, nous avons construit un modèle de régression logistique qui prédit avec une grande précision si un gène de notre ensemble de données ou à partir d'ensembles de données indépendants génèrerait des peptides CMHI. Nos résultats montrent la sélection préférentielle des peptides CMHI à partir d'un répertoire limité de produits de gènes avec des caractéristiques distinctes. L'idée que le système immunitaire peut surveiller des peptides CMHI couvrant seulement une fraction du génome codant des protéines a des implications profondes dans l'auto-immunité et l'immunologie du cancer.
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La présentation d'antigène par les molécules d'histocompatibilité majeure de classe I (CMHI) permet au système immunitaire adaptatif de détecter et éliminer les agents pathogènes intracellulaires et des cellules anormales. La surveillance immunitaire est effectuée par les lymphocytes T CD8 qui interagissent avec le répertoire de peptides associés au CMHI présentés à la surface de toutes cellules nucléées. Les principaux gènes humains de CMHI, HLA-A et HLA-B, sont très polymorphes et par conséquent montrent des différences dans la présentation des antigènes. Nous avons étudié les différences qualitatives et quantitatives dans l'expression et la liaison peptidique de plusieurs allotypes HLA. Utilisant la technique de cytométrie de flux quantitative nous avons établi une hiérarchie d'expression pour les quatre HLA-A, B allotypes enquête. Nos résultats sont compatibles avec une corrélation inverse entre l'expression allotypique et la diversité des peptides bien que d'autres études soient nécessaires pour consolider cette hypothèse. Les origines mondiales du répertoire de peptides associés au CMHI restent une question centrale à la fois fondamentalement et dans la recherche de cibles immunothérapeutiques. Utilisant des techniques protéogénomiques, nous avons identifié et analysé 25,172 peptides CMHI isolées à partir des lymphocytes B de 18 personnes qui exprime collectivement 27 allotypes HLA-A,B. Alors que 58% des gènes ont été la source de 1-64 peptides CMHI par gène, 42% des gènes ne sont pas représentés dans l'immunopeptidome. Dans l'ensemble, l’immunopeptidome présenté par 27 allotypes HLA-A,B ne couvrent que 17% des séquences exomiques exprimées dans les cellules des sujets. Nous avons identifié plusieurs caractéristiques des transcrits et des protéines qui améliorent la production des peptides CMHI. Avec ces données, nous avons construit un modèle de régression logistique qui prédit avec une grande précision si un gène de notre ensemble de données ou à partir d'ensembles de données indépendants génèrerait des peptides CMHI. Nos résultats montrent la sélection préférentielle des peptides CMHI à partir d'un répertoire limité de produits de gènes avec des caractéristiques distinctes. L'idée que le système immunitaire peut surveiller des peptides CMHI couvrant seulement une fraction du génome codant des protéines a des implications profondes dans l'auto-immunité et l'immunologie du cancer.
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Purpose: To evaluate the influence of dentin moisture on bond strengths of an etch-and-rinse bonding agent to primary dentin clinically and in the laboratory. Methods: The sample consisted of two groups of 20 caries-free primary second molars: molars in exfoliation period (clinical group) and extracted molars (laboratory group). Class I cavities were prepared in all specimens leaving a flat dentin surface on the pulpal floor. A two-step etch-and-rinse adhesive was vigorously rubbed on either dry (n= 5) or wet demineralized dentin (n= 5) under clinical or laboratory conditions. After restorative procedures, the teeth from the clinical group were extracted after 20 minutes. All samples were processed and underwent microtensile bond strength test and silver nitrate uptake evaluation under scanning electron microscopy. Results: Statistically higher bond strength values were observed when the bonding was performed under laboratory conditions and on a wet demineralized dentin. Most of the failures were adhesive and mixed irrespective of the experimental condition. Silver nitrate uptake occurred in all groups irrespective of the experimental condition. Resin-dentin bond strengths produced in the laboratory in primary teeth may overestimate those produced under clinical circumstances. (Am J Dent 2011;24:221-225).
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Objectives: To evaluate the effect of chemical degradation on bond strength of resin-modified glass-ionomer cements bonded to primary and permanent dentin. Methods: Class I cavities of permanent and primary extracted human molars were restored with two resin-modified glass-ionomer cements: Fuji 11 LC and Vitremer, and stored in water for 24 h. Half samples were immersed in 10% NaOCl aqueous solution for 5 h. Teeth were sectioned into beams and tested for microtensile bond strengths. Results were analyzed with multiple ANOVA and Tukey`s tests (p < 0.05). Analysis of debonded surfaces was performed by SEM. Results: 24 h bond strengths for Vitremer and Fuji 11 LC were similar. For Fuji 11, bond strength values were higher for primary than for permanent dentin. Vitremer bond strength was similar for both. Chemical degradation did not affect Fuji I] LC bond strength to dentin. However, decreases in bond strength were found for Vitremer groups after NaOCl immersion. Signs of glass ionomer-dentin interaction were evident by SEM analysis for Fuji 11 LC specimens. Conclusions: Vitremer and Fuji II presented similar bond strength at 24. Vitremer dentin bonds were prone to chemical degradation. Fuji II LC-dentin bonds showed typical features of glass-ionomer dentin interaction at the bonded interfaces, and were resistant to in vitro degradation. (C) 2009 Elsevier Ltd. All rights reserved.
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Aim To evaluate and compare the response of pulps of rats capped with resin-modified glass-ionomer cement (RMGIC) or self-etching adhesive system.Methodology Class I cavities were prepared on the occlusal surface of 54 maxillary first molars of 27 rats. Pulp exposure was performed on the cavity floor. The following resin-based materials were applied as pulp-capping agents: G1, Clearfil Liner Bond 2V (CLB 2V; Kuraray Co., Japan); G2, Vitrebond (VIT; 3M/ESPE, USA). In group 3 (control group), a calcium hydroxide/saline paste (CH; Labsynth, Brazil) was used. The cavities were restored with amalgam. After 7, 30 and 60 days, the animals were sacrificed and the jaws were processed for microscopic evaluation.Results Despite the inflammatory response caused by the experimental and the control materials at 7 days, pulpal healing associated with calcified barrier formation was observed at 60 days following the pulp therapy. Both resin-based materials promoted a large zone of cell-rich fibrodentine matrix deposition on the pulp horn related to the pulp exposure site, which was larger to VIT than to CLB 2V specimens. Tertiary dentine underneath the fibrodentine matrix was deposited by a layer of elongated pulpal cells. The remaining pulpal tissue exhibited normal histological characteristics. In the control group, healing and dentine-bridge formation was observed at 30 days. Pulpal breakdown occurred only when bacterial infection occurred.Conclusion Both experimental pulp-capping agents allowed pulpal healing characterized by cell-rich fibrodentine and tertiary dentine deposition as well as calcified barrier formation.