Prediction of total quarter milk somatic cell counts based on foremilk sampling

Determination of somatic cell count (SCC) is used worldwide in dairy practice to describe the hygienic status of the milk and the udder health of cows. When SCC is tested on a quarter level to detect single quarters with high SCC levels of cows for practical reasons, mostly foremilk samples after prestimulation (i.e. cleaning of the udder) are used. However, SCC is usually different in different milk fractions. Therefore, the goal of this study was the investigation of the use of foremilk samples for the estimation of total quarter SCC. A total of 378 milkings in 19 dairy cows were performed with a special milking device to drain quarter milk separately. Foremilk samples were taken after udder stimulation and before cluster attachment. SCC was measured in foremilk samples and in total quarter milk. Total quarter milk SCC could not be predicted precisely from foremilk SCC measurements. At relatively high foremilk SCC levels (>300 x 10(3) cells/ml) foremilk SCC were higher than total quarter milk. At around (50-300) x 10(3) cells/ml foremilk and total quarter SCC did not differ considerably. Most interestingly, if foremilk SCC was lower than 50 x 10(3) cells/ml the total quarter SCC was higher than foremilk SCC. In addition, individual cows showed dramatic variations in foremilk SCC that were not very well related to total quarter milk SCC. In conclusion, foremilk samples are useful to detect high quarter milk SCC to recognize possibly infected quarters, only if precise cell counts are not required. However, foremilk samples can be deceptive if very low cell numbers are to be detected.

The risk prediction for SPM and its impact on the survival in patients with head and neck squamous cell carcinoma

Head and Neck Squamous Cell Carcinoma (HNSCC) is the sixth common malignancy in the world, with high rates of developing second primary malignancy (SPM) and moderately low survival rates. This disease has become an enormous challenge in the cancer research and treatments. For HNSCC patients, a highly significant cause of post-treatment mortality and morbidity is the development of SPM. Hence, assessment of predicting the risk for the development of SPM would be very helpful for patients, clinicians and policy makers to estimate the survival of patients with HNSCC. In this study, we built a prognostic model to predict the risk of developing SPM in patients with newly diagnosed HNSCC. The dataset used in this research was obtained from The University of Texas MD Anderson Cancer Center. For the first aim, we used stepwise logistic regression to identify the prognostic factors for the development of SPM. Our final model contained cancer site and overall cancer stage as our risk factors for SPM. The Hosmer-Lemeshow test (p-value= 0.15>0.05) showed the final prognostic model fit the data well. The area under the ROC curve was 0.72 that suggested the discrimination ability of our model was acceptable. The internal validation confirmed the prognostic model was a good fit and the final prognostic model would not over optimistically predict the risk of SPM. This model needs external validation by using large data sample size before it can be generalized to predict SPM risk for other HNSCC patients. For the second aim, we utilized a multistate survival analysis approach to estimate the probability of death for HNSCC patients taking into consideration of the possibility of SPM. Patients without SPM were associated with longer survival. These findings suggest that the development of SPM could be a predictor of survival rates among the patients with HNSCC.^

Definition of the HLA-A29 peptide ligand motif allows prediction of potential T-cell epitopes from the retinal soluble antigen, a candidate autoantigen in birdshot retinopathy.

The peptide-binding motif of HLA-A29, the predisposing allele for birdshot retinopathy, was determined after acid-elution of endogenous peptides from purified HLA-A29 molecules. Individual and pooled HPLC fractions were sequenced by Edman degradation. Major anchor residues could be defined as glutamate at the second position of the peptide and as tyrosine at the carboxyl terminus. In vitro binding of polyglycine synthetic peptides to purified HLA-A29 molecules also revealed the need for an auxiliary anchor residue at the third position, preferably phenylalanine. By using this motif, we synthesized six peptides from the retinal soluble antigen, a candidate autoantigen in autoimmune uveoretinitis. Their in vitro binding was tested on HLA-A29 and also on HLA-B44 and HLA-B61, two alleles sharing close peptide-binding motifs. Two peptides derived from the carboxyl-terminal sequence of the human retinal soluble antigen bound efficiently to HLA-A29. This study could contribute to the prediction of T-cell epitopes from retinal autoantigens implicated in birdshot retinopathy.

Potent T cell response to a class I-binding 13-mer viral epitope and the influence of HLA micropolymorphism in controlling epitope length

The BZLF1 antigen of Epstein-Barr virus includes three overlapping sequences of different lengths that conform to the binding motif of human leukocyte antigen (HLA) B*3501. These 9-mer ((56)LPOGQLTAy(64)), 11-mer ((54)EPLPQGQLTAy(64)), and 13-mer ((52)LPEPLPQGQLTAY(64)) peptides all bound well to B*3501; however, the CTL response in individuals expressing this HILA allele was directed strongly and exclusively towards the 11-mer peptide. In contrast, EBV-exposed donors expressing HLA B*3503 showed no significant CTL response to these peptides because the single amino acid difference between B*3501 and B*3503 within the F pocket inhibited HLA binding by these peptides. The extraordinarily long 13-mer peptide was the target for the CTL response in individuals expressing B*3508, which differs from B*3501 at a single position within the D pocket (B*3501, 156 Leucine; B*3508, 156 Arginine). This minor difference was shown to enhance binding of the 13-mer peptide, presumably through a stabilizing interaction between the negatively charged glutamate at position 3 of the peptide and the positively charged arginine at HLA position 156. The 13-mer epitope defined in this study represents the longest class I-binding viral epitope identified to date as a minimal determinant. Furthermore, the potency of the response indicates that peptides of this length do not present a major structural barrier to CTL recognition.

TCR{alpha} Genes Direct MHC Restriction in the Potent Human T Cell Response to a Class I-Bound Viral Epitope

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.

Development of a post-mitotic, neuronal-astrocytic cell system, for the prediction of acute neurotoxicity in humans

The human NT2.D1 cell line was differentiated to form both a 1:2 co-culture of post-mitotic NT2 neuronal and NT2 astrocytic (NT2.N/A) cells and a pure NT2.N culture. The respective sensitivities to several test chemicals of the NT2.N/A, the NT2.N, and the NT2.D1 cells were evaluated and compared with the CCF-STTG1 astrocytoma cell line, using a combination of basal cytotoxicity and biochemical endpoints. Using the MTT assay, the basal cytotoxicity data estimated the comparative toxicities of the test chemicals (chronic neurotoxin 2,5-hexanedione, cytotoxins 2,3- and 3,4-hexanedione and acute neurotoxins tributyltin- and trimethyltin- chloride) and also provided the non-cytotoxic concentration-range for each compound. Biochemical endpoints examined over the non-cytotoxic range included assays for ATP levels, oxidative status (H2O2 and GSH levels) and caspase-3 levels as an indicator of apoptosis. although the endpoints did not demonstrate the known neurotoxicants to be consistently more toxic to the cell systems with the greatest number of neuronal properties, the NT2 astrocytes appeared to contribute positively to NT2 neuronal health following exposure to all the test chemicals. The NT2.N/A co-culture generally maintained superior ATP and GSH levels and reduced H2O2 levels in comparison with the NT2.N mono-culture. In addition, the pure NT2.N culture showed a significantly lower level of caspase-3 activation compared with the co-culture, suggesting NT2 astrocytes may be important in modulating the mode of cell death following toxic insult. Overall, these studies provide evidence that an in vitro integrated population of post-mitotic human neurons and astrocytes may offer significant relevance to the human in vivo heterogeneous nervous system, when initially screening compounds for acute neurotoxic potential.

Toward the atomistic simulation of T cell epitopes automated construction of MHC:peptide structures for free energy calculations

Epitopes mediated by T cells lie at the heart of the adaptive immune response and form the essential nucleus of anti-tumour peptide or epitope-based vaccines. Antigenic T cell epitopes are mediated by major histocompatibility complex (MHC) molecules, which present them to T cell receptors. Calculating the affinity between a given MHC molecule and an antigenic peptide using experimental approaches is both difficult and time consuming, thus various computational methods have been developed for this purpose. A server has been developed to allow a structural approach to the problem by generating specific MHC:peptide complex structures and providing configuration files to run molecular modelling simulations upon them. A system has been produced which allows the automated construction of MHC:peptide structure files and the corresponding configuration files required to execute a molecular dynamics simulation using NAMD. The system has been made available through a web-based front end and stand-alone scripts. Previous attempts at structural prediction of MHC:peptide affinity have been limited due to the paucity of structures and the computational expense in running large scale molecular dynamics simulations. The MHCsim server (http://igrid-ext.cryst.bbk.ac.uk/MHCsim) allows the user to rapidly generate any desired MHC:peptide complex and will facilitate molecular modelling simulation of MHC complexes on an unprecedented scale.

A DNA Vaccine Encoding Multiple HIV CD4 Epitopes Elicits Vigorous Polyfunctional, Long-Lived CD4(+) and CD8(+) T Cell Responses

T-cell based vaccines against HIV have the goal of limiting both transmission and disease progression by inducing broad and functionally relevant T cell responses. Moreover, polyfunctional and long-lived specific memory T cells have been associated to vaccine-induced protection. CD4(+) T cells are important for the generation and maintenance of functional CD8(+) cytotoxic T cells. We have recently developed a DNA vaccine encoding 18 conserved multiple HLA-DR-binding HIV-1 CD4 epitopes (HIVBr18), capable of eliciting broad CD4(+) T cell responses in multiple HLA class II transgenic mice. Here, we evaluated the breadth and functional profile of HIVBr18-induced immune responses in BALB/c mice. Immunized mice displayed high-magnitude, broad CD4(+)/CD8(+) T cell responses, and 8/18 vaccine-encoded peptides were recognized. In addition, HIVBr18 immunization was able to induce polyfunctional CD4(+) and CD8(+) T cells that proliferate and produce any two cytokines (IFN gamma/TNF alpha, IFN gamma/IL-2 or TNF alpha/IL-2) simultaneously in response to HIV-1 peptides. For CD4(+) T cells exclusively, we also detected cells that proliferate and produce all three tested cytokines simultaneously (IFN gamma/TNF alpha/IL-2). The vaccine also generated long-lived central and effector memory CD4(+) T cells, a desirable feature for T-cell based vaccines. By virtue of inducing broad, polyfunctional and long-lived T cell responses against conserved CD4(+) T cell epitopes, combined administration of this vaccine concept may provide sustained help for CD8(+) T cells and antibody responses-elicited by other HIV immunogens.

A comparison of the critical impeller speed for solids suspension in a bench-scale and a pilot-scale mechanical flotation cell

This paper compares the critical impeller speed results for 6 L Denver and Wemco bench-scale flotation cells with findings from a study by Van der Westhuizen and Deglon [Van der Westhuizen, A.P., Deglon, D.A., 2007. Evaluation of solids suspension in a pilot-scale mechanical flotation cell: the critical impeller speed. Minerals Engineering 20,233-240; Van der Westhuizen, A.P., Deglon, D.A., 2008. Solids suspension in a pilot scale mechanical flotation cell: a critical impeller speed correlation. Minerals Engineering 21, 621-629] conducted in a 125 L Batequip flotation cell. Understanding solids suspension has become increasingly important due to dramatic increases in flotation cell sizes. The critical impeller speed is commonly used to indicate the effectiveness of solids suspension. The minerals used in this study were apatite, quartz and hematite. The critical impeller speed was found to be strongly dependent on particle size, solids density and air flow rate, with solids concentration having a lesser influence. Liquid viscosity was found to have a negligible effect. The general Zwietering-type critical impeller speed correlation developed by Van der Westhuizen and Deglon [Van der Westhuizen, A.P., Deglon, D.A., 2008. Solids suspension in a pilot scale mechanical flotation cell: a critical impeller speed correlation. Minerals Engineering 21, 621-629] was found to be applicable to all three flotation machines. The exponents for particle size, solids concentration and liquid viscosity were equivalent for all three cells. The exponent for solids density was found to be less significant than that obtained by the previous authors, and to be consistent with values reported in the general literature for stirred tanks. Finally, a new dimensionless critical impeller speed correlation is proposed where the particle size is divided by the impeller diameter. This modified equation generally predicts the experimental measurements well, with most predictions within 10% of the experimental. (C) 2009 Elsevier Ltd. All rights reserved.

Strategies for identifying and predicting islet autoantigen T-cell epitopes in insulin-dependent diabetes mellitus

T cells recognize peptide epitopes bound to major histocompatibility complex molecules. Human T-cell epitopes have diagnostic and therapeutic applications in autoimmune diseases. However, their accurate definition within an autoantigen by T-cell bioassay, usually proliferation, involves many costly peptides and a large amount of blood, We have therefore developed a strategy to predict T-cell epitopes and applied it to tyrosine phosphatase IA-2, an autoantigen in IDDM, and HLA-DR4(*0401). First, the binding of synthetic overlapping peptides encompassing IA-2 was measured directly to purified DR4. Secondly, a large amount of HLA-DR4 binding data were analysed by alignment using a genetic algorithm and were used to train an artificial neural network to predict the affinity of binding. This bioinformatic prediction method was then validated experimentally and used to predict DR4 binding peptides in IA-2. The binding set encompassed 85% of experimentally determined T-cell epitopes. Both the experimental and bioinformatic methods had high negative predictive values, 92% and 95%, indicating that this strategy of combining experimental results with computer modelling should lead to a significant reduction in the amount of blood and the number of peptides required to define T-cell epitopes in humans.

Delivery of multiple CD8 cytotoxic T cell epitopes by DNA vaccination

Development of CD8 alpha beta CTL epitope-based vaccines requires an effective strategy capable of co-delivering large numbers of CTL epitopes, Here we describe a DNA plasmid encoding a polyepitope or polytope protein, which contained multiple contiguous minimal murine CTL epitopes, Mice vaccinated with this plasmid made MHC-restricted CTL responses to each of the epitopes, and protective CTL were demonstrated in recombinant vaccinia virus, influenza virus, and tumor challenge models, CTL responses generated by polytope DNA plasmid vaccination lasted for 1 yr, could be enhanced by co-delivering a gene for granulocyte-macrophage CSF, and appeared to be induced in the absence of CD4 T cell-mediated help, The ability to deliver large numbers of CTL epitopes using relatively small polytope constructs and DNA vaccination technology should find application in the design of human epitope-based CTL vaccines, in particular in vaccines against EBV, HIV, and certain cancers.

Prediction of MHC class II-binding peptides using an evolutionary algorithm and artificial neural network

Motivation: Prediction methods for identifying binding peptides could minimize the number of peptides required to be synthesized and assayed, and thereby facilitate the identification of potential T-cell epitopes. We developed a bioinformatic method for the prediction of peptide binding to MHC class II molecules. Results: Experimental binding data and expert knowledge of anchor positions and binding motifs were combined with an evolutionary algorithm (EA) and an artificial neural network (ANN): binding data extraction --> peptide alignment --> ANN training and classification. This method, termed PERUN, was implemented for the prediction of peptides that bind to HLA-DR4(B1*0401). The respective positive predictive values of PERUN predictions of high-, moderate-, low- and zero-affinity binder-a were assessed as 0.8, 0.7, 0.5 and 0.8 by cross-validation, and 1.0, 0.8, 0.3 and 0.7 by experimental binding. This illustrates the synergy between experimentation and computer modeling, and its application to the identification of potential immunotheraaeutic peptides.

Prediction of promiscuous peptides that bind HLA class I molecules

Promiscuous T-cell epitopes make ideal targets for vaccine development. We report here a computational system, multipred, for the prediction of peptide binding to the HLA-A2 supertype. It combines a novel representation of peptide/MHC interactions with a hidden Markov model as the prediction algorithm. multipred is both sensitive and specific, and demonstrates high accuracy of peptide-binding predictions for HLA-A*0201, *0204, and *0205 alleles, good accuracy for *0206 allele, and marginal accuracy for *0203 allele. multipred replaces earlier requirements for individual prediction models for each HLA allelic variant and simplifies computational aspects of peptide-binding prediction. Preliminary testing indicates that multipred can predict peptide binding to HLA-A2 supertype molecules with high accuracy, including those allelic variants for which no experimental binding data are currently available.

Methods for prediction of peptide binding to MHC molecules: A comparative study

Background: A variety of methods for prediction of peptide binding to major histocompatibility complex (MHC) have been proposed. These methods are based on binding motifs, binding matrices, hidden Markov models (HMM), or artificial neural networks (ANN). There has been little prior work on the comparative analysis of these methods. Materials and Methods: We performed a comparison of the performance of six methods applied to the prediction of two human MHC class I molecules, including binding matrices and motifs, ANNs, and HMMs. Results: The selection of the optimal prediction method depends on the amount of available data (the number of peptides of known binding affinity to the MHC molecule of interest), the biases in the data set and the intended purpose of the prediction (screening of a single protein versus mass screening). When little or no peptide data are available, binding motifs are the most useful alternative to random guessing or use of a complete overlapping set of peptides for selection of candidate binders. As the number of known peptide binders increases, binding matrices and HMM become more useful predictors. ANN and HMM are the predictive methods of choice for MHC alleles with more than 100 known binding peptides. Conclusion: The ability of bioinformatic methods to reliably predict MHC binding peptides, and thereby potential T-cell epitopes, has major implications for clinical immunology, particularly in the area of vaccine design.