Quantitative prediction of mouse class I MHC peptide binding affinity using support vector machine regression (SVR) models

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.

Epidemiology of myopia in a United Kingdom urban child population

The Aston Eye Study (AES) was instigated in October 2005 to determine the distribution of refractive error and associated ocular biometry in a sample of UK urban school children. The AES is the first study to compare outcome measures separately in White, South Asian and Black children. Children were selected from two age groups (Year 2 children aged 6/7 years, Year8 children aged 12/13 years of age) using random cluster sampling of schools in Birmingham, West Midlands UK. To date, the AES has examined 598 children (302 Year 2,296 Year 8). Using open-field cycloplegic autorefraction, the overall prevalence of myopia (=-0.50D SER in either eye) determined was 19.6%, with a higher prevalence in older (29.4%) compared to younger (9.9%) children (p<0.001). Using multiple logistic regression models, the risk of myopia was higher in Year 8 South Asian compared to White children and higher in children attending grammar schools relative to comprehensive schools. In addition, the prevalence of uncorrected ametropia was found to be high (Year 8: 12.84%, Year 2: 15.23%), which will be of concern to bodies responsible for the implementation of school vision screening strategies. Biometric data using non-contact partial coherence interferometry revealed a contributory effect of axial length (AL) and central corneal radius (CR) on myopic refraction, resulting in a strong coefficient of determination of the AL/CR ratio on refractive error. Ocular biometric measures did not vary significantly as a function of ethnicity, suggesting a greater miscorrelation of components in susceptible ethnic groups to account for their higher myopia prevalence. Corneal radius was found to be steeper in myopes in both age groups, but was found to flatten with increasing axial length. Due to the inextricable link between myopia and axial elongation, the paradoxical finding of the cornea demands further longitudinal investigation, particularly in relation to myopia onset. Questionnaire analysis revealed a history of myopia in parents and siblings to be significantly associated with myopia in Year 8 children, with a dose-dependent rise in the odds ratio of myopia evident with increasing number of myopic parents. By classifying socioeconomic status (SES) using Index of Multiple Deprivation values, it was found that Year 8 children from moderately deprived backgrounds were more at risk of myopia compared with children located at both extremities of the deprivation spectrum. However, the main effect of SES weakened following multivariate analysis, with South Asian ethnicity and grammar schooling remaining associated with Year 8 myopia after adjustment.

Comparative risk of microalbuminuria and proteinuria in UK residents of south Asian and white European ethnic background with type 2 diabetes:a report from UKADS

Objective - This study investigated and compared the prevalence of microalbuminuria and overt proteinuria and their determinants in a cohort of UK resident patients of white European or south Asian ethnicity with type 2 diabetes mellitus. Research design and methods - A total of 1978 patients, comprising 1486 of south Asian and 492 of white European ethnicity, in 25 general practices in Coventry and Birmingham inner city areas in England were studied in a cross-sectional study. Demographic and risk factor data were collected and presence of microalbuminuria and overt proteinuria assessed. Main outcome measures - Prevalences of microalbuminuria and overt proteinuria. Results - Urinary albumin:creatinine measurements were available for 1852 (94%) patients. The south Asian group had a lower prevalence of microalbuminuria, 19% vs. 23% and a higher prevalence of overt proteinuria, 8% vs. 3%, X2?=?15.85, 2df, P?=?0.0004. In multiple logistic regression models, adjusted for confounding factors, significantly increased risk for the south Asian vs. white European patients for overt proteinuria was shown; OR (95% CI) 2.17 (1.05, 4.49), P?=?0.0365. For microalbuminuria, an interaction effect for ethnicity and duration of diabetes suggested that risk for south Asian patients was lower in early years following diagnosis; OR for SA vs. WH at durations 0 and 1 year were 0.56 (0.37, 0.86) and 0.59 (0.39, 0.89) respectively. After 20 years’ duration, OR?=?1.40 (0.63, 3.08). Limitations - Comparability of ethnicity defined groups; statistical methods controlled for differences between groups, but residual confounding may remain. Analyses are based on a single measure of albumin:creatinine ratio. Conclusions - There were significant differences between ethnicity groups in risk factor profiles and microalbuminuria and overt proteinuria outcomes. Whilst south Asian patients had no excess risk of microalbuminuria, the risk of overt proteinuria was elevated significantly, which might be explained by faster progression of renal dysfunction in patients of south Asian ethnicity.

Consumer trial, continuous use, and economic benefits of a retail service innovation:the case of the personal shopping assistant

Service innovations in retailing have the potential to benefit consumers as well as retailers. This research models key factors associated with the trial and continuous use of a specific self-service technology (SST), the personal shopping assistant (PSA), and estimates retailer benefits from implementing that innovation. Based on theoretical insights from prior SST studies, diffusion of innovation literature, and the technology acceptance model (TAM), this study develops specific hypotheses and tests them on a sample of 104 actual users of the PSA and 345 nonusers who shopped at the retail store offering the PSA device. Results indicate that factors affecting initial trial are different from those affecting continuous use. More specifically, consumers' trust toward the retailer, novelty seeking, and market mavenism are positively related to trial, while technology anxiety hinders the likelihood of trying the PSA. Perceived ease of use of the device positively impacts continuous use while consumers' need for interaction in shopping environments reduces the likelihood of continuous use. Importantly, there is evidence on retailer benefits from introducing the innovation since consumers using the PSA tend to spend more during each shopping trip. However, given the high costs of technology, the payback period for recovery of investments in innovation depends largely upon continued use of the innovation by consumers. Important implications are provided for retailers considering investments in new in-store service innovations. Incorporation of technology within physical stores affords opportunities for the retailer to reduce costs, while enhancing service provided to consumers. Therefore, service innovations in retailing have the potential to benefit consumers as well as retailers. This research models key factors associated with the trial and continuous use of a specific SST in the retail context, the PSA, and estimates retailer benefits from implementing that innovation. In so doing, the study contributes to the nascent area of research on SSTs in the retail sector. Based on theoretical insights from prior SST studies, diffusion of innovation literature, and the TAM, this study develops specific hypotheses regarding the (1) antecedent effects of technological anxiety, novelty seeking, market mavenism, and trust in the retailer on trial of the service innovation; (2) the effects of ease of use, perceived waiting time, and need for interaction on continuous use of the innovation; and (3) the effect of use of innovation on consumer spending at the store. The hypotheses were tested on a sample of 104 actual users of the PSA and 345 nonusers who shopped at the retail store offering the PSA device, one of the early adopters of PSA in Germany. Data were analyzed using logistic regression (antecedents of trial), multiple regression (antecedents of continuous use), and propensity score matching (assessing retailer benefits). Results indicate that factors affecting initial trial are different from those affecting continuous use. More specifically, consumers' trust toward the retailer, novelty seeking, and market mavenism are positively related to trial, while technology anxiety hinders the likelihood of trying the PSA. Perceived ease of use of the device positively impacts continuous use, while consumers' need for interaction in shopping environments reduces the likelihood of continuous use. Importantly, there is evidence on retailer benefits from introducing the innovation since consumers using the PSA tend to spend more during each shopping trip. However, given the high costs of technology, the payback period for recovery of investments in innovation depends largely upon continued use of the innovation by consumers. Important implications are provided for retailers considering investments in new in-store service innovations. The study contributes to the literature through its (1) simultaneous examination of antecedents of trial and continuous usage of a specific SST, (2) the demonstration of economic benefits of SST introduction for the retailer, and (3) contribution to the stream of research on service innovation, as against product innovation.

AllerTOP v.2 - a server for in silico prediction of allergens

Allergy is an overreaction by the immune system to a previously encountered, ordinarily harmless substance - typically proteins - resulting in skin rash, swelling of mucous membranes, sneezing or wheezing, or other abnormal conditions. The use of modified proteins is increasingly widespread: their presence in food, commercial products, such as washing powder, and medical therapeutics and diagnostics, makes predicting and identifying potential allergens a crucial societal issue. The prediction of allergens has been explored widely using bioinformatics, with many tools being developed in the last decade; many of these are freely available online. Here, we report a set of novel models for allergen prediction utilizing amino acid E-descriptors, auto- and cross-covariance transformation, and several machine learning methods for classification, including logistic regression (LR), decision tree (DT), naïve Bayes (NB), random forest (RF), multilayer perceptron (MLP) and k nearest neighbours (kNN). The best performing method was kNN with 85.3% accuracy at 5-fold cross-validation. The resulting model has been implemented in a revised version of the AllerTOP server (http://www.ddg-pharmfac.net/AllerTOP). © Springer-Verlag 2014.

AllerTOP - a server for in silico prediction of allergens

Background: Allergy is a form of hypersensitivity to normally innocuous substances, such as dust, pollen, foods or drugs. Allergens are small antigens that commonly provoke an IgE antibody response. There are two types of bioinformatics-based allergen prediction. The first approach follows FAO/WHO Codex alimentarius guidelines and searches for sequence similarity. The second approach is based on identifying conserved allergenicity-related linear motifs. Both approaches assume that allergenicity is a linearly coded property. In the present study, we applied ACC pre-processing to sets of known allergens, developing alignment-independent models for allergen recognition based on the main chemical properties of amino acid sequences.Results: A set of 684 food, 1,156 inhalant and 555 toxin allergens was collected from several databases. A set of non-allergens from the same species were selected to mirror the allergen set. The amino acids in the protein sequences were described by three z-descriptors (z1, z2 and z3) and by auto- and cross-covariance (ACC) transformation were converted into uniform vectors. Each protein was presented as a vector of 45 variables. Five machine learning methods for classification were applied in the study to derive models for allergen prediction. The methods were: discriminant analysis by partial least squares (DA-PLS), logistic regression (LR), decision tree (DT), naïve Bayes (NB) and k nearest neighbours (kNN). The best performing model was derived by kNN at k = 3. It was optimized, cross-validated and implemented in a server named AllerTOP, freely accessible at http://www.pharmfac.net/allertop. AllerTOP also predicts the most probable route of exposure. In comparison to other servers for allergen prediction, AllerTOP outperforms them with 94% sensitivity.Conclusions: AllerTOP is the first alignment-free server for in silico prediction of allergens based on the main physicochemical properties of proteins. Significantly, as well allergenicity AllerTOP is able to predict the route of allergen exposure: food, inhalant or toxin. © 2013 Dimitrov et al.; licensee BioMed Central Ltd.