Toward the prediction of class I and II mouse major histocompatibility complex-peptide-binding affinity:in silico bioinformatic step-by-step guide using quantitative structure-activity relationships

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.

In silico prediction of peptide-MHC binding affinity using SVRMHC

The binding between peptide epitopes and major histocompatibility complex (MHC) proteins is a major event in the cellular immune response. Accurate prediction of the binding between short peptides and class I or class II MHC molecules is an important task in immunoinformatics. SVRMHC which is a novel method to model peptide-MHC binding affinities based on support rector machine regression (SVR) is described in this chapter. SVRMHC is among a small handful of quantitative modeling methods that make predictions about precise binding affinities between a peptide and an MHC molecule. As a kernel-based learning method, SVRMHC has rendered models with demonstrated appealing performance in the practice of modeling peptide-MHC binding.

Memantine combined with an acetyl cholinesterase inhibitor:hope for the future?

Background:Memantine and cholinesterase inhibitors (ChEI) have distinct pharmacological actions, and interest in the use of combination therapy for Alzheimer's disease (AD) is increasing. Objective: To assess the available data on the use of memantine–ChEI combination and to develop evidence-based recommendations.Method: A systematic literature review with detailed discussion of the current evidence base. Results: Available data are limited: five studies of which two were randomized, double-blind, placebo-controlled trials. One study indicated that memantine–ChEI combination is not significantly more effective than placebo–ChEI in mild to moderate AD, but data were published in abstract and poster form only. A second study indicated that the memantine–ChEI combination is significantly more effective than placebo–ChEI in moderate to severe AD. The calculated effect sizes of 0.36 on cognition and 0.12 on function, which were the primary outcomes, were small, indicating a clinically minimal effect on cognition and no effect on function. No data are available on whether combination treatment is more effective than memantine monotherapy. Conclusion: The available data do not justify the use of combination therapy. Future studies should include three arms (memantine–placebo, placebo–ChEI, and memantine–ChEI), be of an adequate size and duration, and use pragmatic measures. Clinicians should have full access to data from any future trials.

Multimodal field data entry:performance and usability issues

Mobile technologies have yet to be widely adopted by the Architectural, Engineering, and Construction (AEC) industry despite being one of the major growth areas in computing in recent years. This lack of uptake in the AEC industry is likely due, in large part, to the combination of small screen size and inappropriate interaction demands of current mobile technologies. This paper discusses the scope for multimodal interaction design with a specific focus on speech-based interaction to enhance the suitability of mobile technology use within the AEC industry by broadening the field data input capabilities of such technologies. To investigate the appropriateness of using multimodal technology for field data collection in the AEC industry, we have developed a prototype Multimodal Field Data Entry (MFDE) application. This application, which allows concrete testing technicians to record quality control data in the field, has been designed to support two different modalities of data input speech-based data entry and stylus-based data entry. To compare the effectiveness or usability of, and user preference for, the different input options, we have designed a comprehensive lab-based evaluation of the application. To appropriately reflect the anticipated context of use within the study design, careful consideration had to be given to the key elements of a construction site that would potentially influence a test technician's ability to use the input techniques. These considerations and the resultant evaluation design are discussed in detail in this paper.

Towards the in silico identification of class II restricted T-cell epitopes:a partial least squares iterative self-consistent algorithm for affinity prediction

Motivation: The immunogenicity of peptides depends on their ability to bind to MHC molecules. MHC binding affinity prediction methods can save significant amounts of experimental work. The class II MHC binding site is open at both ends, making epitope prediction difficult because of the multiple binding ability of long peptides. Results: An iterative self-consistent partial least squares (PLS)-based additive method was applied to a set of 66 pep- tides no longer than 16 amino acids, binding to DRB1*0401. A regression equation containing the quantitative contributions of the amino acids at each of the nine positions was generated. Its predictability was tested using two external test sets which gave r pred =0.593 and r pred=0.655, respectively. Furthermore, it was benchmarked using 25 known T-cell epitopes restricted by DRB1*0401 and we compared our results with four other online predictive methods. The additive method showed the best result finding 24 of the 25 T-cell epitopes. Availability: Peptides used in the study are available from http://www.jenner.ac.uk/JenPep. The PLS method is available commercially in the SYBYL molecular modelling software package. The final model for affinity prediction of peptides binding to DRB1*0401 molecule is available at http://www.jenner.ac.uk/MHCPred. Models developed for DRB1*0101 and DRB1*0701 also are available in MHC- Pred

Distance Matrix Approach to Content Image Retrieval

As the volume of image data and the need of using it in various applications is growing significantly in the last days it brings a necessity of retrieval efficiency and effectiveness. Unfortunately, existing indexing methods are not applicable to a wide range of problem-oriented fields due to their operating time limitations and strong dependency on the traditional descriptors extracted from the image. To meet higher requirements, a novel distance-based indexing method for region-based image retrieval has been proposed and investigated. The method creates premises for considering embedded partitions of images to carry out the search with different refinement or roughening level and so to seek the image meaningful content.

Cramer-Rao bound analysis of location estimation in multi-hop wireless sensor networks

Location estimation is important for wireless sensor network (WSN) applications. In this paper we propose a Cramer-Rao Bound (CRB) based analytical approach for two centralized multi-hop localization algorithms to get insights into the error performance and its sensitivity to the distance measurement error, anchor node density and placement. The location estimation performance is compared with four distributed multi-hop localization algorithms by simulation to evaluate the efficiency of the proposed analytical approach. The numerical results demonstrate the complex tradeoff between the centralized and distributed localization algorithms on accuracy, complexity and communication overhead. Based on this analysis, an efficient and scalable performance evaluation tool can be designed for localization algorithms in large scale WSNs, where simulation-based evaluation approaches are impractical. © 2013 IEEE.

Using SAT for Combinational Implementation Checking

The problem of checking whether a system of incompletely specified Boolean functions is implemented by the given combinational circuit is considered. The task is reduced to testing out if two given logical descriptions are equivalent on the domain of one of them having functional indeterminacy. We present a novel SAT-based verification method that is used for testing whether the given circuit satisfies all the conditions represented by the system of incompletely specified Boolean functions.

Weak form equation–based finite-element modeling of viscoelastic asphalt mixtures

The objective of this study is to demonstrate using weak form partial differential equation (PDE) method for a finite-element (FE) modeling of a new constitutive relation without the need of user subroutine programming. The viscoelastic asphalt mixtures were modeled by the weak form PDE-based FE method as the examples in the paper. A solid-like generalized Maxwell model was used to represent the deforming mechanism of a viscoelastic material, the constitutive relations of which were derived and implemented in the weak form PDE module of Comsol Multiphysics, a commercial FE program. The weak form PDE modeling of viscoelasticity was verified by comparing Comsol and Abaqus simulations, which employed the same loading configurations and material property inputs in virtual laboratory test simulations. Both produced identical results in terms of axial and radial strain responses. The weak form PDE modeling of viscoelasticity was further validated by comparing the weak form PDE predictions with real laboratory test results of six types of asphalt mixtures with two air void contents and three aging periods. The viscoelastic material properties such as the coefficients of a Prony series model for the relaxation modulus were obtained by converting from the master curves of dynamic modulus and phase angle. Strain responses of compressive creep tests at three temperatures and cyclic load tests were predicted using the weak form PDE modeling and found to be comparable with the measurements of the real laboratory tests. It was demonstrated that the weak form PDE-based FE modeling can serve as an efficient method to implement new constitutive models and can free engineers from user subroutine programming.

Does Lost Time Cost You Money and Create High Risk?

The aim of the case study is to express the delayed repair time impact on the revenues and profit in numbers with the example of the outage of power plant units. Main steps of risk assessment: • creating project plan suitable for risk assessment • identification of the risk factors for each project activities • scenario-analysis based evaluation of risk factors • selection of the critical risk factors based on the results of quantitative risk analysis • formulating risk response actions for the critical risks • running Monte-Carlo simulation [1] using the results of scenario-analysis • building up a macro which creates the connection among the results of the risk assessment, the production plan and the business plan.

Developing methods for testing the resistance of white cabbage against Thrips tabaci

Since the damage of the onion thrips (Thrips tabaci Lindemann) first occurred on white cabbage in Hungary several observations have been carried out, both in Hungary and abroad, to assess varietal resistance. The use of a new evaluation method for field screening is described and the result of the monitoring of 64 varieties is reported. The most susceptible varieties were ‘Bejo 1860’, ‘SG 3164’, ‘Quisto’, ‘Green Gem’ and ‘Ramada’. On the other hand, ‘Golden Cross’, ‘Balashi’, ‘Riana’, ‘Autumn Queen’, ‘Leopard’, Ama-Daneza’ and ‘Galaxy’ suffered the least damage under natural infestation. Methods for testing the patterns of resistance are also described and evaluated. In case of plants at the few leaf growth stage significant negative correlation was found between egg mortality and the egg laying preference of adults. The results of the other antibiotic and antixenotic tests were greatly affected by differences in the physiological age and condition of the varieties.

Quota bonuses as localized sales bonuses

Managerial bonus schemes and their effects on firm strategies and market outcomes are extensively discussed in the literature. Though quota bonuses are not uncommon in practice, they have not been analysed so far. In this article we compare quota bonuses to profit-based evaluation and sales (quantity) bonuses. In a duopoly setting with independent demand shocks we find that under certain circumstances choosing quota bonuses is a dominant strategy. This may explain the widespread use of quota bonuses in situations where incentive problems are relevant.

A systems model for community injury prevention

The purpose of this study was to develop, explicate, and validate a comprehensive model in order to more effectively assess community injury prevention needs, plan and target efforts, identify potential interventions, and provide a framework for an outcome-based evaluation of the effectiveness of interventions. A systems model approach was developed to conceptualize the major components of inputs, efforts, outcomes and feedback within a community setting. Profiling of multiple data sources demonstrated a community feedback mechanism that increased awareness of priority issues and elicited support from traditional as well as non-traditional injury prevention partners. Injury countermeasures including education, enforcement, engineering, and economic incentives were presented for their potential synergistic effect impacting on knowledge, attitudes, or behaviors of a targeted population. Levels of outcome data were classified into ultimate, intermediate and immediate indicators to assist with determining the effectiveness of intervention efforts. A collaboration between business and health care was successful in achieving data access and use of an emergency department level of injury data for monitoring of the impact of community interventions. Evaluation of injury events and preventive efforts within the context of a dynamic community systems environment was applied to a study community with examples detailing actual profiling and trending of injuries. The resulting model of community injury prevention was validated using a community focus group, community injury prevention coordinators, and injury prevention national experts. ^

Horizontal genetic transfer in asexual fungi

Four aspects of horizontal genetic transfer during heterokaryon formation were examined in the asexual pathogen Fusarium oxysporum f.sp. cubense (Foc): (1) variability based on method of heterokaryon formation; (2) differences in nuclear and mitochondrial inheritance; (3) the occurrence of recombination without nuclear fusion; (4) the occurrence of horizontal genetic transfer between distantly related isolates. The use of non-pathogenic strains of Fusarium oxysporum as biocontrol agents warrants a closer examination at the reproductive life cycle of this fungus, particularly if drug resistance or pathogenicity genes can be transmitted horizontally. Experiments were divided into three phases. Phase I looked at heterokaryon formation by hyphal anastomosis and protoplast fusion. Phase II was a time course of heterokaryon formation to look at patterns of nuclear and mitochondrial inheritance. Phase III examined the genetic relatedness of the different vegetative compatibility groups using a multilocus analysis approach. Heterokaryon formation was evident within and between vegetative compatibility groups. Observation of non-parental genotypes after heterokaryon formation confirmed that, although a rare event, horizontal genetic transfer occurred during heterokaryon formation. Uniparental mitochondria inheritance was observed in heterokaryons formed either by hyphal anastomosis or protoplast fusion. Drug resistance was expressed during heterokaryon formation, even across greater genetic distances than those distances imposed by vegetative compatibility. Phylogenies inferred from different molecular markers were incongruent at a significant level, challenging the clonal origins of Foc. Mating type genes were identified in this asexual pathogen Polymorphisms were detected within a Vegetative Compatibility Group (VCG) suggesting non-clonal inheritance and/or sexual recombination in Foc. This research was funded in part by a NIH-NIGMS (National Institutes of Health-National Institute of General Medical Sciences) Grant through the MBRS (Minority Biomedical Research Support), the Department of Biological Sciences and the Tropical Biology Program at FIU. ^

Spatial-temporal mining of archived automatic vehicle location (AVL) data for transit service planning applications

An Automatic Vehicle Location (AVL) system is a computer-based vehicle tracking system that is capable of determining a vehicle's location in real time. As a major technology of the Advanced Public Transportation System (APTS), AVL systems have been widely deployed by transit agencies for purposes such as real-time operation monitoring, computer-aided dispatching, and arrival time prediction. AVL systems make a large amount of transit performance data available that are valuable for transit performance management and planning purposes. However, the difficulties of extracting useful information from the huge spatial-temporal database have hindered off-line applications of the AVL data. ^ In this study, a data mining process, including data integration, cluster analysis, and multiple regression, is proposed. The AVL-generated data are first integrated into a Geographic Information System (GIS) platform. The model-based cluster method is employed to investigate the spatial and temporal patterns of transit travel speeds, which may be easily translated into travel time. The transit speed variations along the route segments are identified. Transit service periods such as morning peak, mid-day, afternoon peak, and evening periods are determined based on analyses of transit travel speed variations for different times of day. The seasonal patterns of transit performance are investigated by using the analysis of variance (ANOVA). Travel speed models based on the clustered time-of-day intervals are developed using important factors identified as having significant effects on speed for different time-of-day periods. ^ It has been found that transit performance varied from different seasons and different time-of-day periods. The geographic location of a transit route segment also plays a role in the variation of the transit performance. The results of this research indicate that advanced data mining techniques have good potential in providing automated techniques of assisting transit agencies in service planning, scheduling, and operations control. ^