A quantitative study of the pathological changes in the cortical white matter in variant Creutzfeldt-Jakob disease (vCJD).

Objective: To quantify cortical white matter pathology in variant Creutzfeldt-Jakob disease (vCJD) and to correlate white and grey matter pathologies. Methods: Pathological changes were studied in immunolabeled sections of the frontal, parietal, occipital, and temporal cortex of eleven cases of vCJD. Results: Vacuolation ("spongiform change"), deposition of the disease form of prion protein (PrPsc), and a glial cell reaction were observed in the white matter. The density of the vacuoles was greatest in the white matter of the occipital cortex and glial cell density in the inferior temporal gyrus (ITG). Florid-type PrPsc deposits were present in approximately 50% of white matter regions studied. In the white matter of the frontal cortex (FC), vacuole density was negatively correlated with the densities of both glial cell nuclei and PrPsc deposits. In addition, in the frontal and parietal cortices the densities of glial cells and PrPsc deposits were positively correlated. In the FC and ITG, there was a negative correlation between the densities of the vacuoles in the white matter and the number of surviving neurons in laminae V/VI of the adjacent grey matter. In the FC, vacuole density in the white matter was negatively correlated with the density of the diffuse PrPsc deposits in laminae II/III and V/VI of the adjacent grey matter. In addition, the densities of PrPsc deposits in the white matter of the FC were positively correlated with the density of the diffuse PrPsc deposits in laminae II/III and V/VI and with the number of surviving neurons in laminae V/VI. Conclusion: The data suggest significant degeneration of cortical white matter in vCJD; the vacuolation being related to neuronal loss in the lower cortical laminae of adjacent grey matter, PrPsc deposits the result of leakage from damaged axons, and gliosis a reaction to these changes.

A quantitative analysis of optic nerve axons in elderly control subjects and patients with Alzheimer's disease

Objective: To study the density and cross-sectional area of axons in the optic nerve in elderly control subjects and in cases of Alzheimer's disease (AD) using an image analysis system. Methods: Sections of optic nerves from control and AD patients were stained with toluidine blue to reveal axon profiles. Results: The density of axons was reduced in both the center and peripheral portions of the optic nerve in AD compared with control patients. Analysis of axons with different cross-sectional areas suggested a specific loss of the smaller sized axons in AD, i.e., those with areas less that 1.99 μm2. An analysis of axons >11 μm2 in cross-sectional area suggested no specific loss of the larger axons in this group of patients. Conclusions: The data suggest that image analysis provides an accurate and reproducible method of quantifying axons in the optic nerve. In addition, the data suggest that axons are lost throughout the optic nerve with a specific loss of the smaller-sized axons. Loss of the smaller axons may explain the deficits in color vision observed in a significant proportion of patients with AD.

Foundations of an intervention package to improve communication in residential care settings:a mixed methods study

Background: The prevalence of hearing loss is considerably higher in individuals in residential care than in people within the community-dwelling population, and yet hearing aids and hearing services are relatively underused. Care staff have a key role in supporting access to services. Objectives: This study identifies staff perspectives on hearing loss and their views about potential hearing service improvements. Study design: A four-stage mixed methods study was used, made up of qualitative interviews, observation, a survey and a stakeholder involvement meeting. Results: The qualitative stages indicated that staff were concerned about their levels of interaction with residents. Staff considered maximizing communication as part of their professional role. The quantitative survey indicated that these views were widely held by staff, and the stakeholder stage identified the need for social support and dedicated staff training opportunities. Conclusion: Care home staff regard communication as a shared issue. Future interventions could enhance access to hearing services and provide care home staff with training in hearing loss and hearing aid management. © 2013 Informa Healthcare.

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.

Vitamin E-stabilised UHMWPE for orthopaedic implants:quantitative determination of vitamin E and characterisation of its transformation products

The fate of vitamin E and the formation and identification of its transformation products were investigated at different stages of the manufacturing process of commercially produced cross-linked (by γ-irradiation) UHMWPE stabilised with vitamin E (vitamin E infused-post irradiation) used for tibia-components (as articulating surfaces) in total knee arthroplasty (total knee replacement). Vitamin E (α-tocopherol) and its transformation products were extracted from microtomed Tibia films and the different products were separated, isolated, purified using high performance liquid chromatography (HPLC), and characterised by spectroscopic methods and LC-MS. The amount of vitamin E and that of the products formed in the different Tibia samples and in their extracts were also quantified using FTIR and HPLC analysis and calibration curves. Thorough analysis of the Tibia extracts has shown that a number of vitamin E transformation products were formed at different concentrations at two selected stages of the implant manufacturing process that is before and after sterilisation by γ-irradiation. The identified products were found to correspond mainly to different stereoisomeric forms of a small number of vitamin E transformation products. Most of the observed products were of dimeric and trimeric nature with their identity confirmed through a detailed study of their spectral and chromatographic characteristics. It was found that the products of vitamin E, prior to the sterilisation step but after the crosslinking and doping of vitamin E, were mainly the dihydroxydimers and trimers (Tibia samples at this stage are referred to as “Tibia-VEPE”). After sterilisation and completion of the manufacturing process, additional dimers of vitamin E were also formed (Tibia samples at this stage are referred to as ‘Tibia-VEPE-Sterile’), Furthermore, two tocopherol-derived aldehydes (aldehyde 5-formyl-γ-tocopherol and aldehyde 7-formyl-γ-tocopherol) were also formed but at very low concentrations especially in the Tibia-VEPE-Sterile samples. The question of whether vitamin E becomes chemically reacted (grafted) onto the polymer matrix during the manufacturing process of the Tibia is also addressed.

The UK MPharm (1) - are we over reliant on traditional teaching methods?

Introduction-The design of the UK MPharm curriculum is driven by the Royal Pharmaceutical Society of Great Britain (RPSGB) accreditation process and the EU directive (85/432/EEC).[1] Although the RPSGB is informed about teaching activity in UK Schools of Pharmacy (SOPs), there is no database which aggregates information to provide the whole picture of pharmacy education within the UK. The aim of the teaching, learning and assessment study [2] was to document and map current programmes in the 16 established SOPs. Recent developments in programme delivery have resulted in a focus on deep learning (for example, through problem based learning approaches) and on being more student centred and less didactic through lectures. The specific objectives of this part of the study were (a) to quantify the content and modes of delivery of material as described in course documentation and (b) having categorised the range of teaching methods, ask students to rate how important they perceived each one for their own learning (using a three point Likert scale: very important, fairly important or not important). Material and methods-The study design compared three datasets: (1) quantitative course document review, (2) qualitative staff interview and (3) quantitative student self completion survey. All 16 SOPs provided a set of their undergraduate course documentation for the year 2003/4. The documentation variables were entered into Excel tables. A self-completion questionnaire was administered to all year four undergraduates, using a pragmatic mixture of methods, (n=1847) in 15 SOPs within Great Britain. The survey data were analysed (n=741) using SPSS, excluding non-UK students who may have undertaken part of their studies within a non-UK university. Results and discussion-Interviews showed that individual teachers and course module leaders determine the choice of teaching methods used. Content review of the documentary evidence showed that 51% of the taught element of the course was delivered using lectures, 31% using practicals (includes computer aided learning) and 18% small group or interactive teaching. There was high uniformity across the schools for the first three years; variation in the final year was due to the project. The average number of hours per year across 15 schools (data for one school were not available) was: year 1: 408 hours; year 2: 401 hours; year 3: 387 hours; year 4: 401 hours. The survey showed that students perceived lectures to be the most important method of teaching after dispensing or clinical practicals. Taking the very important rating only: 94% (n=694) dispensing or clinical practicals; 75% (n=558) lectures; 52% (n=386) workshops, 50% (n=369) tutorials, 43% (n=318) directed study. Scientific laboratory practices were rated very important by only 31% (n=227). The study shows that teaching of pharmacy to undergraduates in the UK is still essentially didactic through a high proportion of formal lectures and with high levels of staff-student contact. Schools consider lectures still to be the most cost effective means of delivering the core syllabus to large cohorts of students. However, this does limit the scope for any optionality within teaching, the scope for small group work is reduced as is the opportunity to develop multi-professional learning or practice placements. Although novel teaching and learning techniques such as e-learning have expanded considerably over the past decade, schools of pharmacy have concentrated on lectures as the best way of coping with the huge expansion in student numbers. References [1] Council Directive. Concerning the coordination of provisions laid down by law, regulation or administrative action in respect of certain activities in the field of pharmacy. Official Journal of the European Communities 1985;85/432/EEC. [2] Wilson K, Jesson J, Langley C, Clarke L, Hatfield K. MPharm Programmes: Where are we now? Report commissioned by the Pharmacy Practice Research Trust., 2005.

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.

Quantitative structure-activity relationships and the prediction of MHC supermotifs

The underlying assumption in quantitative structure–activity relationship (QSAR) methodology is that related chemical structures exhibit related biological activities. We review here two QSAR methods in terms of their applicability for human MHC supermotif definition. Supermotifs are motifs that characterise binding to more than one allele. Supermotif definition is the initial in silico step of epitope-based vaccine design. The first QSAR method we review here—the additive method—is based on the assumption that the binding affinity of a peptide depends on contributions from both amino acids and the interactions between them. The second method is a 3D-QSAR method: comparative molecular similarity indices analysis (CoMSIA). Both methods were applied to 771 peptides binding to 9 HLA alleles. Five of the alleles (A*0201, A* 0202, A*0203, A*0206 and A*6802) belong to the HLA-A2 superfamily and the other four (A*0301, A*1101, A*3101 and A*6801) to the HLA-A3 superfamily. For each superfamily, supermotifs defined by the two QSAR methods agree closely and are supported by many experimental data.

Research of the Influence of Methods of Compression on the Co-efficient of Information Security of Objects Under Attacks

In this paper a possibility for quantitative measuring of information security of objects, exposed to information attacks and processed with methods of compression, is represented. A co-efficient of information security, which reflects the influence of the level of compression obtained after applying methods of compression to objects and the time, required by the attack to get access to the corresponding object, is proposed. Methods’ groups with the highest and respectively the lowest values of the co-efficient of information security for all methods’ groups in relation to all attacks’ groups are determined. Assessments and conclusions for future investigations are proposed.

Laser-induced breakdown spectroscopy quantitative analysis method via adaptive analytical line selection and relevance vector machine regression model

Abstract A new LIBS quantitative analysis method based on analytical line adaptive selection and Relevance Vector Machine (RVM) regression model is proposed. First, a scheme of adaptively selecting analytical line is put forward in order to overcome the drawback of high dependency on a priori knowledge. The candidate analytical lines are automatically selected based on the built-in characteristics of spectral lines, such as spectral intensity, wavelength and width at half height. The analytical lines which will be used as input variables of regression model are determined adaptively according to the samples for both training and testing. Second, an LIBS quantitative analysis method based on RVM is presented. The intensities of analytical lines and the elemental concentrations of certified standard samples are used to train the RVM regression model. The predicted elemental concentration analysis results will be given with a form of confidence interval of probabilistic distribution, which is helpful for evaluating the uncertainness contained in the measured spectra. Chromium concentration analysis experiments of 23 certified standard high-alloy steel samples have been carried out. The multiple correlation coefficient of the prediction was up to 98.85%, and the average relative error of the prediction was 4.01%. The experiment results showed that the proposed LIBS quantitative analysis method achieved better prediction accuracy and better modeling robustness compared with the methods based on partial least squares regression, artificial neural network and standard support vector machine.

A laser induced breakdown spectroscopy quantitative analysis method based on the robust least squares support vector machine regression model

Data fluctuation in multiple measurements of Laser Induced Breakdown Spectroscopy (LIBS) greatly affects the accuracy of quantitative analysis. A new LIBS quantitative analysis method based on the Robust Least Squares Support Vector Machine (RLS-SVM) regression model is proposed. The usual way to enhance the analysis accuracy is to improve the quality and consistency of the emission signal, such as by averaging the spectral signals or spectrum standardization over a number of laser shots. The proposed method focuses more on how to enhance the robustness of the quantitative analysis regression model. The proposed RLS-SVM regression model originates from the Weighted Least Squares Support Vector Machine (WLS-SVM) but has an improved segmented weighting function and residual error calculation according to the statistical distribution of measured spectral data. Through the improved segmented weighting function, the information on the spectral data in the normal distribution will be retained in the regression model while the information on the outliers will be restrained or removed. Copper elemental concentration analysis experiments of 16 certified standard brass samples were carried out. The average value of relative standard deviation obtained from the RLS-SVM model was 3.06% and the root mean square error was 1.537%. The experimental results showed that the proposed method achieved better prediction accuracy and better modeling robustness compared with the quantitative analysis methods based on Partial Least Squares (PLS) regression, standard Support Vector Machine (SVM) and WLS-SVM. It was also demonstrated that the improved weighting function had better comprehensive performance in model robustness and convergence speed, compared with the four known weighting functions.

Identifying frames:a comparison of research methods

Framing plays an important role in public policy. Interest groups strategically highlight some aspects of a policy proposal while downplaying others in order to steer the policy debate in a favorable direction. Despite the importance of framing, we still know relatively little about the framing strategies of interest groups due to methodological difficulties that have prevented scholars from systematically studying interest group framing across a large number of interest groups and multiple policy debates. This article therefore provides an overview of three novel research methods that allow researchers to systematically measure interest group frames. More specifically, this article introduces a word-based quantitative text analysis technique, a manual, computer-assisted content analysis approach and face-to-face interviews designed to systematically identify interest group frames. The results generated by all three techniques are compared on the basis of a case study of interest group framing in an environmental policy debate in the European Union.

Revealing 4-hydroxynonenal-histidine adducts as qualitative and quantitative biomarker of oxidative stress, lipid peroxidation and oxidative homeostasis

Findings on growth regulating activities of the end-product of lipid peroxidation 4-hydroxy-2-nonenal (HNE), which acts as a “second messenger of free radicals”, overlapped with the development of antibodies specific for the aldehyde-protein adducts. These led to qualitative immunochemical determinations of the HNE presence in various pathophysiological processes and to the change of consideration of the aldehyde’s bioactivities from toxicity into cell signalling. Moreover, findings of the HNE-protein adduct in various organs under physiological circumstances support the concept of “oxidative homeostasis”, which implies that oxidative stress and lipid peroxidation are not only pathological but also physiological processes. Reactive aldehydes, at least HNE, could play important role in oxidative homeostasis, while complementary research approaches might reveal the relevance of the aldehydic-protein adducts as major biomarkers of oxidative stress, lipid peroxidation and oxidative homeostasis. Aiming to join efforts in such research activities researchers interacting through the International 4-Hydroxynonenal Club acting within the SFRR-International and through networking projects of the system of the European Cooperation in Science and Technology (COST) carried validation of the methods for lipid peroxidation and further developed the genuine 4-HNE-His ELISA founding quantitative and qualitative methods for detection of 4-HNE-His adducts as valuable tool to study oxidative stress and lipid peroxidation in cell cultures, various organs and tissues and eventually for human plasma and serum analyses [1]. Reference: 1. Weber, Daniela. Lidija, Milkovic. Measurement of HNE-protein adducts in human plasma and serum by ELISA—Comparison of two primary antibodies. Redox Biol. 2013. 226-233.

Formal methods for the development and verification of autonomic IT systems

This chapter explores ways in which rigorous mathematical techniques, termed formal methods, can be employed to improve the predictability and dependability of autonomic computing. Model checking, formal specification, and quantitative verification are presented in the contexts of conflict detection in autonomic computing policies, and of implementation of goal and utility-function policies in autonomic IT systems, respectively. Each of these techniques is illustrated using a detailed case study, and analysed to establish its merits and limitations. The analysis is then used as a basis for discussing the challenges and opportunities of this endeavour to transition the development of autonomic IT systems from the current practice of using ad-hoc methods and heuristic towards a more principled approach. © 2012, IGI Global.

A quantitative study of tau pathology in eleven cases of chronic traumatic encephalopathy

AIMS: To quantify tau pathology of chronic traumatic encephalopathy (CTE) and investigate influence of dot-like lesions (DL), brain region, co-morbidity, and sporting career length. METHODS: Densities of neurofibrillary tangles (NFT), astrocytic tangles (AT), DL, oligodendroglial inclusions (GI), neuropil threads (NT), vacuoles, neurons, and enlarged neurons (EN) were measured in tau-immunoreactive sections of upper cortical laminae of frontal and temporal lobe, hippocampus (HC), amygdala, and substantia nigra (SN) of eleven cases of CTE. RESULTS: DL were a consistent finding in CTE. Densities of NFT, NT and DL were greatest in sectors CA1 and CA2 of the HC. Densities of AT were lower than NFT, small numbers of GI were recorded in temporal lobe, and low densities of vacuoles and EN were consistently present. β-amyloid containing neuritic plaques (NP) also occurred at low density. Densities of NFT, NT, DL, and AT were greater in sulci than gyri while vacuole density was greater in gyri. Principal components analysis (PCA) suggested that sporting career length and densities of NFT in entorhinal cortex, NT in CA2 and SN, and vacuolation in the DG were significant sources of variation among cases. CONCLUSION: DL are frequent in CTE suggesting affinity with argyrophilic grain disease (AGD) and Parkinson's disease dementia (PD-Dem). Densities of AT in all regions and NT/DL in sectors CA2/4 were consistent features of CTE. The eleven cases are neuropathologically heterogeneous which may result from genetic diversity, and variation in anatomical pathways subjected to trauma. This article is protected by copyright. All rights reserved.