Predicting class II MHC-Peptide binding:a kernel based approach using similarity scores

Background - Modelling the interaction between potentially antigenic peptides and Major Histocompatibility Complex (MHC) molecules is a key step in identifying potential T-cell epitopes. For Class II MHC alleles, the binding groove is open at both ends, causing ambiguity in the positional alignment between the groove and peptide, as well as creating uncertainty as to what parts of the peptide interact with the MHC. Moreover, the antigenic peptides have variable lengths, making naive modelling methods difficult to apply. This paper introduces a kernel method that can handle variable length peptides effectively by quantifying similarities between peptide sequences and integrating these into the kernel. Results - The kernel approach presented here shows increased prediction accuracy with a significantly higher number of true positives and negatives on multiple MHC class II alleles, when testing data sets from MHCPEP [1], MCHBN [2], and MHCBench [3]. Evaluation by cross validation, when segregating binders and non-binders, produced an average of 0.824 AROC for the MHCBench data sets (up from 0.756), and an average of 0.96 AROC for multiple alleles of the MHCPEP database. Conclusion - The method improves performance over existing state-of-the-art methods of MHC class II peptide binding predictions by using a custom, knowledge-based representation of peptides. Similarity scores, in contrast to a fixed-length, pocket-specific representation of amino acids, provide a flexible and powerful way of modelling MHC binding, and can easily be applied to other dynamic sequence problems.

Identifying candidate subunit vaccines using an alignment-independent method based on principal amino acid properties

Subunit vaccine discovery is an accepted clinical priority. The empirical approach is time- and labor-consuming and can often end in failure. Rational information-driven approaches can overcome these limitations in a fast and efficient manner. However, informatics solutions require reliable algorithms for antigen identification. All known algorithms use sequence similarity to identify antigens. However, antigenicity may be encoded subtly in a sequence and may not be directly identifiable by sequence alignment. We propose a new alignment-independent method for antigen recognition based on the principal chemical properties of protein amino acid sequences. The method is tested by cross-validation on a training set of bacterial antigens and external validation on a test set of known antigens. The prediction accuracy is 83% for the cross-validation and 80% for the external test set. Our approach is accurate and robust, and provides a potent tool for the in silico discovery of medically relevant subunit vaccines.

Predicting class I major histocompatibility complex (MHC) binders using multivariate statistics:comparison of discriminant analysis and multiple linear regression

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.

Modeling the peptide-T cell receptor interaction by the comparative molecular similarity indices analysis-soft independent modeling of class analogy technique

A set of 38 epitopes and 183 non-epitopes, which bind to alleles of the HLA-A3 supertype, was subjected to a combination of comparative molecular similarity indices analysis (CoMSIA) and soft independent modeling of class analogy (SIMCA). During the process of T cell recognition, T cell receptors (TCR) interact with the central section of the bound nonamer peptide; thus only positions 4−8 were considered in the study. The derived model distinguished 82% of the epitopes and 73% of the non-epitopes after cross-validation in five groups. The overall preference from the model is for polar amino acids with high electron density and the ability to form hydrogen bonds. These so-called “aggressive” amino acids are flanked by small-sized residues, which enable such residues to protrude from the binding cleft and take an active role in TCR-mediated T cell recognition. Combinations of “aggressive” and “passive” amino acids in the middle part of epitopes constitute a putative TCR binding motif

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.

Optimised phase disposition pulse-width modulation strategy for hybrid-clamped multilevel inverters using switching state sequences

This study describes an optimised modulation strategy based on switching state sequences for the hybrid-clamped multilevel converter. Two key control variables defined as 'phase shift angle' and 'switching state change' for a five-level hybrid-clamped inverter are proposed to improve all switches' operation, and by changing their values, different control methods can be obtained for modulation optimisation purposes. Two example methods can solve the voltage imbalance problem of the dc-link capacitors and furthermore avoid two switches' simultaneous switching transitions and improve the inverter's performance as compared with the traditional phase disposition pulse-width modulation strategy. A 6 kW prototype inverter is developed and a range of simulation and experiments are carried out for validation. It is found that simulation and experimental results are in a good agreement and the proposed modulation strategy is verified in terms of low-order harmonic reduction.

Service productivity:what stops service firms from measuring it?

Productivity measurement poses a challenge for service organizations. Conventional management wisdom holds that this challenge is rooted in the difficulty of accurately quantifying service inputs and outputs. Few service firms have adequate service productivity measurement (SPM) systems in place and implementing such systems may involve organizational transformation. Combining field interviews and literature-based insights, the authors develop a conceptual model of antecedents of SPM in service firms and test it using data from 276 service firms. Results indicate that one out of five antecedents affects the choice to use SPM, namely, the degree of service standardization. In addition, all five hypothesized antecedents and one additional antecedent (perceived appropriateness of the current SPM) predict the degree of SPM usage. In particular, the degree of SPM is positively influenced by the degree of service standardization, service customization, investments in service productivity gains, and the appropriateness of current service productivity measures. In turn, customer integration and the perceived difficulty of measuring service productivity negatively affect SPM. The fact that customer integration impedes actual measurement of service productivity is a surprising finding, given that customer integration is widely seen as a means to increase service productivity. The authors conclude with implications for service organizations and directions for research.

Automatic maintenance of category hierarchy

Category hierarchy is an abstraction mechanism for efficiently managing large-scale resources. In an open environment, a category hierarchy will inevitably become inappropriate for managing resources that constantly change with unpredictable pattern. An inappropriate category hierarchy will mislead the management of resources. The increasing dynamicity and scale of online resources increase the requirement of automatically maintaining category hierarchy. Previous studies about category hierarchy mainly focus on either the generation of category hierarchy or the classification of resources under a pre-defined category hierarchy. The automatic maintenance of category hierarchy has been neglected. Making abstraction among categories and measuring the similarity between categories are two basic behaviours to generate a category hierarchy. Humans are good at making abstraction but limited in ability to calculate the similarities between large-scale resources. Computing models are good at calculating the similarities between large-scale resources but limited in ability to make abstraction. To take both advantages of human view and computing ability, this paper proposes a two-phase approach to automatically maintaining category hierarchy within two scales by detecting the internal pattern change of categories. The global phase clusters resources to generate a reference category hierarchy and gets similarity between categories to detect inappropriate categories in the initial category hierarchy. The accuracy of the clustering approaches in generating category hierarchy determines the rationality of the global maintenance. The local phase detects topical changes and then adjusts inappropriate categories with three local operations. The global phase can quickly target inappropriate categories top-down and carry out cross-branch adjustment, which can also accelerate the local-phase adjustments. The local phase detects and adjusts the local-range inappropriate categories that are not adjusted in the global phase. By incorporating the two complementary phase adjustments, the approach can significantly improve the topical cohesion and accuracy of category hierarchy. A new measure is proposed for evaluating category hierarchy considering not only the balance of the hierarchical structure but also the accuracy of classification. Experiments show that the proposed approach is feasible and effective to adjust inappropriate category hierarchy. The proposed approach can be used to maintain the category hierarchy for managing various resources in dynamic application environment. It also provides an approach to specialize the current online category hierarchy to organize resources with more specific categories.

Continuous quality improvement in a Maltese hospital using logical framework analysis

Purpose: The purpose of this paper is to present the application of logical framework analysis (LFA) for implementing continuous quality improvement (CQI) across multiple settings in a tertiary care hospital. Design/methodology/approach: This study adopts a multiple case study approach. LFA is implemented within three diverse settings, namely, intensive care unit, surgical ward, and acute in-patient psychiatric ward. First, problem trees are developed in order to determine the root causes of quality issues, specific to the three settings. Second, objective trees are formed suggesting solutions to the quality issues. Third, project plan template using logical framework (LOGFRAME) is created for each setting. Findings: This study shows substantial improvement in quality across the three settings. LFA proved to be effective to analyse quality issues and suggest improvement measures objectively. Research limitations/implications: This paper applies LFA in specific, albeit, diverse settings in one hospital. For validation purposes, it would be ideal to analyse in other settings within the same hospital, as well as in several hospitals. It also adopts a bottom-up approach when this can be triangulated with other sources of data. Practical implications: LFA enables top management to obtain an integrated view of performance. It also provides a basis for further quantitative research on quality management through the identification of key performance indicators and facilitates the development of a business case for improvement. Originality/value: LFA is a novel approach for the implementation of CQI programs. Although LFA has been used extensively for project development to source funds from development banks, its application in quality improvement within healthcare projects is scant.

All-optical processing using cross-phase modulation

The following thesis presents results obtained from both numerical simulation and laboratory experimentation (both of which were carried out by the author). When data is propagated along an optical transmission line some timing irregularities can occur such as timing jitter and phase wander. Traditionally these timing problems would have been corrected by converting the optical signal into the electrical domain and then compensating for the timing irregularity before converting the signal back into the optical domain. However, this thesis posses a potential solution to the problem by remaining completely in the optical domain, eliminating the need for electronics. This is desirable as not only does optical processing reduce the latency effect that their electronic counterpart have, it also holds the possibility of an increase in overall speed. A scheme was proposed which utilises the principle of wavelength conversion to dynamically convert timing irregularities (timing jitter and phase wander) into a change in wavelength (this occurs on a bit-by-bit level and so timing jitter and phase wander can be compensated for simultaneously). This was achieved by optically sampling a linearly chirped, locally generated clock source (the sampling function was achieved using a nonlinear optical loop mirror). The data, now with each bit or code word having a unique wavelength, is then propagated through a dispersion compensation module. The dispersion compensation effectively re-aligns the data in time and so thus, the timing irregularities are removed. The principle of operation was tested using computer simulation before being re-tested in a laboratory environment. A second stage was added to the device to create 3R regeneration. The second stage is used to simply convert the timing suppressed data back into a single wavelength. By controlling the relative timing displacement between stage one and stage two, the wavelength that is finally produced can be controlled.

A study in Britain and France of the development of cross-cultural in-house sales training using distance learning.

The thesis is concerned with cross-cultural distance learning in two countries: Great Britain and France. Taking the example of in-house sales training, it argues that it is possible to develop courses for use in two or more countries of differing culture and language. Two courses were developed by the researcher. Both were essentially print-based distance-learning courses designed to help salespeople achieve a better understanding of their customers. One used a quantitative, the other qualitative approach. One considered the concept of the return on investment and the other, for which a video support was also developed, considered the analysis of a customer's needs. Part 1 of the thesis considers differences in the training context between France and Britain followed by a review of the learning process with reference to distance learning. Part 2 looks at the choice of training medium course design and evaluation and sets out the methodology adopted, including problems encountered in this type of fieldwork. Part 3 analyses the data and draws conclusions from the findings, before offering a series of guidelines for those concerned with the development of cross-cultural in-house training courses. The results of the field tests on the two courses were analysed in relation to the socio-cultural, educational and experiential background of the learners as well as their preferred learning styles. The thesis argues that it is possible to develop effective in-house sales training courses to be used in two cultures and identifies key considerations which need to be taken into account when carrying out this type of work.

The significance of microaneurysms and haemorrhages within one optic disc diameter of the fovea

Free paper session INTRODUCTION. Microaneurysms and haemorrhages within the macula area are a poor predictor of macular oedema as shown by optical coherence tomography (OCT). Our research suggests that it is safe and cost effective to screen patients who present with these surrogate markers annually. PURPOSE. To determine whether microaneurysms (ma) and haemorrhages (hm) within one optic disc diameter of the fovea (ma/hm<1DD) are significant predictors of macular oedema. METHODS. Data were collected over a one-year period from patients attending digital diabetic retinopathy screening. Patients who presented with ma/hm<1DD also had an OCT scan. The fast macula scan on the Stratus OCT was used and an ophthalmologist reviewed the scans to determine whether macular oedema was present. Macular oedema was identified by thickening on the OCT cross-sections. Patients were split into two groups. Group one (325 eyes) included those with best VA?6/9 and group two (30 eyes) with best VA =6/12. Only patients who had no other referable features of diabetic retinopathy were selected. RESULTS. In group one, 6 (1.8%) out of 325 eyes showed thickening on the OCT and were referred to hospital eye service (HES) for further investigation. In group two, 6 (20%) out of 30 eyes showed thickening and were referred to HES. CONCLUSIONS. Ma/hm<1DD become more significant predictors of macular oedema when VA is reduced. Results confirm the grading criteria concerning microaneurysms predicting macular oedema for referable maculopathy in the English national screening programme. OCT is a useful method to accurately identify patients requiring referral to HES.

Writing for success:mentoring as a pedagogical tool – a cross- institutional study

The prominent position given to academic writing across contemporary academia is reflected in the substantive literature and debate devoted to the subject over the past 30 years. However, the massification of higher education, manifested by a shift from elite to mass education, has brought the issue into the public arena, with much debate focusing on the need for ‘modern-day' students to be taught how to write academically (Bjork et al., 2003; Ganobcsik-Williams, 2006). Indeed, Russell (2003) argued that academic writing has become a global ‘problem' in Higher Education because it sits between two contradictory pressures (p.V). On one end of the university ‘experience' increasing numbers of students, many from non-traditional backgrounds, enter higher education bringing with them a range of communication abilities. At the other end, many graduates leave university to work in specialised industries where employers expect them to have high level writing skills (Ashton, 2007; Russell, 2003; Torrence et al., 1999). By drawing attention to the issues around peer mentoring within an academic writing setting in three different higher education Institutions, this paper makes an important contribution to current debates. Based upon a critical analysis of the emergent findings of an empirical study into the role of peer writing mentors in promoting student transition to higher education, the paper adopts an academic literacies approach to discuss the role of writing mentoring in promoting transition and retention by developing students' academic writing. Attention is drawn to the manner in which student expectations of writing mentoring actually align with mentoring practices - particularly in terms of the writing process and critical thinking. Other issues such as the approachability of writing mentors, the practicalities of accessing writing mentoring and the wider learning environment are also discussed.