Assessment of different formulations of oral Mycobacterium bovis Bacille Calmette-Guerin (BCG) vaccine in rodent models for immunogenicity and protection against aerosol challenge with M-bovis

Bovine tuberculosis (bTB) caused by infection with Mycobacterium bovis is causing considerable economic loss to farmers and Government in the United Kingdom as its incidence is increasing. Efforts to control bTB in the UK are hampered by the infection in Eurasian badgers (Metes metes) that represent a wildlife reservoir and source of recurrent M. bovis exposure to cattle. Vaccination of badgers with the human TB vaccine, M. bovis Bacille Calmette-Guerin (BCG), in oral bait represents a possible disease control tool and holds the best prospect for reaching badger populations over a wide geographical area. Using mouse and guinea pig models, we evaluated the immunogenicity and protective efficacy, respectively, of candidate badger oral vaccines based on formulation of BCG in lipid matrix, alginate beads, or a novel microcapsular hybrid of both lipid and alginate. Two different oral doses of BCG were evaluated in each formulation for their protective efficacy in guinea pigs, while a single dose was evaluated in mice. In mice, significant immune responses (based on lymphocyte proliferation and expression of IFN-gamma) were only seen with the lipid matrix and the lipid in alginate microcapsular formulation, corresponding to the isolation of viable BCG from alimentary tract lymph nodes. In guinea pigs, only BCG formulated in lipid matrix conferred protection to the spleen and lungs following aerosol route challenge with M. bovis. Protection was seen with delivery doses in the range 10(6)-10(7) CFU, although this was more consistent in the spleen at the higher dose. No protection in terms of organ CFU was seen with BCG administered in alginate beads or in lipid in alginate microcapsules, although 10(7) in the latter formulation conferred protection in terms of increasing body weight after challenge and a smaller lung to body weight ratio at necropsy. These results highlight the potential for lipid, rather than alginate, -based vaccine formulations as suitable delivery vehicles for an oral BCG vaccine in badgers.

Using architecture models to support the generation and operation of component-based adaptive systems

Modelling architectural information is particularly important because of the acknowledged crucial role of software architecture in raising the level of abstraction during development. In the MDE area, the level of abstraction of models has frequently been related to low-level design concepts. However, model-driven techniques can be further exploited to model software artefacts that take into account the architecture of the system and its changes according to variations of the environment. In this paper, we propose model-driven techniques and dynamic variability as concepts useful for modelling the dynamic fluctuation of the environment and its impact on the architecture. Using the mappings from the models to implementation, generative techniques allow the (semi) automatic generation of artefacts making the process more efficient and promoting software reuse. The automatic generation of configurations and reconfigurations from models provides the basis for safer execution. The architectural perspective offered by the models shift focus away from implementation details to the whole view of the system and its runtime change promoting high-level analysis. © 2009 Springer Berlin Heidelberg.

Factors determining disease duration in Alzheimer's disease:a postmortem study of 103 cases using the Kaplan-Meier estimator and Cox regression

Factors associated with duration of dementia in a consecutive series of 103 Alzheimer's disease (AD) cases were studied using the Kaplan-Meier estimator and Cox regression analysis (proportional hazard model). Mean disease duration was 7.1 years (range: 6 weeks-30 years, standard deviation = 5.18); 25% of cases died within four years, 50% within 6.9 years, and 75% within 10 years. Familial AD cases (FAD) had a longer duration than sporadic cases (SAD), especially cases linked to presenilin (PSEN) genes. No significant differences in duration were associated with age, sex, or apolipoprotein E (Apo E) genotype. Duration was reduced in cases with arterial hypertension. Cox regression analysis suggested longer duration was associated with an earlier disease onset and increased senile plaque (SP) and neurofibrillary tangle (NFT) pathology in the orbital gyrus (OrG), CA1 sector of the hippocampus, and nucleus basalis of Meynert (NBM). The data suggest shorter disease duration in SAD and in cases with hypertensive comorbidity. In addition, degree of neuropathology did not influence survival, but spread of SP/NFT pathology into the frontal lobe, hippocampus, and basal forebrain was associated with longer disease duration. © 2014 R. A. Armstrong.

NADPH oxidase-dependent redox signalling in cardiac hypertrophy, remodelling and failure

Markers of increased oxidative stress are known to be elevated following acute myocardial infarction and in the context of chronic left ventricular hypertrophy or heart failure, and their levels may correlate with the degree of contractile dysfunction or cardiac deficit. An obvious pathological mechanism that may account for this correlation is the potential deleterious effects of increased oxidative stress through the induction of cellular dysfunction, energetic deficit or cell death. However, reactive oxygen species have several much more subtle effects in the remodelling or failing heart that involve specific redox-regulated modulation of signalling pathways and gene expression. Such redox-sensitive regulation appears to play important roles in the development of several components of the phenotype of the failing heart, for example cardiomyocyte hypertrophy, interstitial fibrosis and chamber remodelling. In this article, we review the evidence supporting the involvement of reactive oxygen species and redox signalling pathways in the development of cardiac hypertrophy and heart failure, with a particular focus on the NADPH oxidase family of superoxide-generating enzymes which appear to be especially important in redox signalling.

Verification and validation of numerical models of the transport of insulation debris

A combination of the two-fluid and drift flux models have been used to model the transport of fibrous debris. This debris is generated during loss of coolant accidents in the primary circuit of pressurized or boiling water nuclear reactors, as high pressure steam or water jets can damage adjacent insulation materials including mineral wool blankets. Fibre agglomerates released from the mineral wools may reach the containment sump strainers, where they can accumulate and compromise the long-term operation of the emergency core cooling system. Single-effect experiments of sedimentation in a quiescent rectangular column and sedimentation in a horizontal flow are used to verify and validate this particular application of the multiphase numerical models. The utilization of both modeling approaches allows a number of pseudocontinuous dispersed phases of spherical wetted agglomerates to be modeled simultaneously. Key effects on the transport of the fibre agglomerates are particle size, density and turbulent dispersion, as well as the relative viscosity of the fluid-fibre mixture.

Comparison of Multivariate and Univariate Models for Genetic Evaluation of Milk Yield based on Test Day Data

2000 Mathematics Subject Classification: 62H12, 62P99

A közalkalmazotti béremelés hatása a tanárok pályaelhagyási döntéseire (The effect of a public-sector pay increase on teachers attrition)

A tanárok pályaelhagyási döntését vizsgálva, a tanulmány a következő két kérdésre keresi a választ. Milyen szerepet játszanak e döntésekben a keresetek, alternatív kereseti lehetőségek? Hogyan hatott a tanárok pályaelhagyására a 2002. évi közalkalmazotti béremelés? Az elemzéshez az OEP-ONYF-FH összekapcsolt nagymintás adatbázis felhasználásával kétféle modellt becsült a szerző: 1. két lehetőséget megkülönböztetve (elhagyja a tanári pályát/nem hagyja el) Cox-féle arányos hazárdfüggvényeket, 2. a pályaelhagyás okai között a más állásba kerülést és az egyéb pályaelhagyási okokat megkülönböztetve versengő kockázati modelleket. Az eredmények azt mutatják, hogy a kereseti lehetőségek hatnak a pályaelhagyási döntésekre. A magasabb jövedelem és magasabb relatív kereset csökkenti annak valószínűségét, hogy egy tanár elhagyja a pályát, és más pályán helyezkedjen el, vagy nem foglalkoztatotti státusba kerüljön. A közalkalmazotti béremelés átmenetileg csökkentette a pályaelhagyás valószínűségét a fiatal tanárok körében, de a hatás egy-két év alatt eltűnt. Az 51 évesnél idősebb tanárokat pedig inkább a pályán tartotta a béremelés, csökkentette annak valószínűségét is, hogy más pályán helyezkedjenek el, vagy hogy nem foglalkoztatotti státusba kerüljenek. ______ The paper investigates teachers decisions to leave the profession. It first examines the role in such decisions of pay compared with earnings in alternative occupations, and then discusses how the public-sector pay increase of 2002 af-fected exit decisions by teachers. Duration models were estimated using large merged administrative data sets. First binary-choice Cox proportional hazard models (leaving teaching profession or not), then competing risk models that distinguish exits to another occupation and exits to a non-working state. Results show that earnings matter. Higher wages reduce the probability of exiting teacher profession to go to another occupation or to non-employment. The public-sector pay increase decreased the probability of inexperienced teachers leaving the teacher profession temporarily, but the effect disappeared after one or two years. For experienced teachers over 51 years old, the wage increase was found to reduce attrition.

Centrifuge modeling of oblique pipe-soil interaction in dense and loose sand

Due to relative ground movement, buried pipelines experience geotechnical loads. The imposed geotechnical loads may initiate pipeline deformations that affect system serviceability and integrity. Engineering guidelines (e.g., ALA, 2005; Honegger and Nyman, 2001) provide the technical framework to develop idealized structural models to analyze pipe‒soil interaction events and assess pipe mechanical response. The soil behavior is modeled using discrete springs that represent the geotechnical loads per unit pipe length developed during the interaction event. Soil forces are defined along three orthogonal directions (i.e., axial, lateral and vertical) to analyze the response of pipelines. Nonlinear load-displacement relationships of soil defined by a spring, is independent of neighboring spring elements. However, recent experimental and numerical studies demonstrate significant coupling effects during oblique (i.e., not along one of the orthogonal axes) pipe‒soil interaction events. In the present study, physical modeling using a geotechnical centrifuge was conducted to improve the current understanding of soil load coupling effects of buried pipes in loose and dense sand. A section of pipeline, at shallow burial depth, was translated through the soil at different oblique angles in the axial-lateral plane. The force exerted by the soil on pipe is critically examined to assess the significance of load coupling effects and establish a yield envelope. The displacements required to soil yield force are also examined to assess potential coupling in mobilization distance. A set of laboratory tests were conducted on the sand used for centrifuge modeling to find the stress-strain behavior of sand, which was used to examine the possible mechanisms of centrifuge model test. The yield envelope, deformation patterns, and interpreted failure mechanisms obtained from centrifuge modeling are compared with other physical modeling and numerical simulations available in the literature.

Dynamic Programming Approaches for Estimating and Applying Large-scale Discrete Choice Models

People go through their life making all kinds of decisions, and some of these decisions affect their demand for transportation, for example, their choices of where to live and where to work, how and when to travel and which route to take. Transport related choices are typically time dependent and characterized by large number of alternatives that can be spatially correlated. This thesis deals with models that can be used to analyze and predict discrete choices in large-scale networks. The proposed models and methods are highly relevant for, but not limited to, transport applications. We model decisions as sequences of choices within the dynamic discrete choice framework, also known as parametric Markov decision processes. Such models are known to be difficult to estimate and to apply to make predictions because dynamic programming problems need to be solved in order to compute choice probabilities. In this thesis we show that it is possible to explore the network structure and the flexibility of dynamic programming so that the dynamic discrete choice modeling approach is not only useful to model time dependent choices, but also makes it easier to model large-scale static choices. The thesis consists of seven articles containing a number of models and methods for estimating, applying and testing large-scale discrete choice models. In the following we group the contributions under three themes: route choice modeling, large-scale multivariate extreme value (MEV) model estimation and nonlinear optimization algorithms. Five articles are related to route choice modeling. We propose different dynamic discrete choice models that allow paths to be correlated based on the MEV and mixed logit models. The resulting route choice models become expensive to estimate and we deal with this challenge by proposing innovative methods that allow to reduce the estimation cost. For example, we propose a decomposition method that not only opens up for possibility of mixing, but also speeds up the estimation for simple logit models, which has implications also for traffic simulation. Moreover, we compare the utility maximization and regret minimization decision rules, and we propose a misspecification test for logit-based route choice models. The second theme is related to the estimation of static discrete choice models with large choice sets. We establish that a class of MEV models can be reformulated as dynamic discrete choice models on the networks of correlation structures. These dynamic models can then be estimated quickly using dynamic programming techniques and an efficient nonlinear optimization algorithm. Finally, the third theme focuses on structured quasi-Newton techniques for estimating discrete choice models by maximum likelihood. We examine and adapt switching methods that can be easily integrated into usual optimization algorithms (line search and trust region) to accelerate the estimation process. The proposed dynamic discrete choice models and estimation methods can be used in various discrete choice applications. In the area of big data analytics, models that can deal with large choice sets and sequential choices are important. Our research can therefore be of interest in various demand analysis applications (predictive analytics) or can be integrated with optimization models (prescriptive analytics). Furthermore, our studies indicate the potential of dynamic programming techniques in this context, even for static models, which opens up a variety of future research directions.

New Bivariate Lifetime Distributions Based on Bath-Tub Shaped Failure Rate

A class of lifetime distributions which has received considerable attention in modelling and analysis of lifetime data is the class of lifetime distributions with bath-tub shaped failure rate functions because of their extensive applications. The purpose of this thesis was to introduce a new class of bivariate lifetime distributions with bath-tub shaped failure rates (BTFRFs). In this research, first we reviewed univariate lifetime distributions with bath-tub shaped failure rates, and several multivariate extensions of a univariate failure rate function. Then we introduced a new class of bivariate distributions with bath-tub shaped failure rates (hazard gradients). Specifically, the new class of bivariate lifetime distributions were developed using the method of Morgenstern’s method of defining bivariate class of distributions with given marginals. The computer simulations and numerical computations were used to investigate the properties of these distributions.

Cost-effectiveness of natriuretic peptide-based screening and collaborative care: a report from the STOP-HF (St Vincent's Screening TO Prevent Heart Failure) study

AIMS: Prevention of cardiovascular disease and heart failure (HF) in a cost-effective manner is a public health goal. This work aims to assess the cost-effectiveness of the St Vincent's Screening TO Prevent Heart Failure (STOP-HF) intervention.

METHODS AND RESULTS: This is a substudy of 1054 participants with cardiovascular risk factors [median age 65.8 years, interquartile range (IQR) 57.8:72.4, with 4.3 years, IQR 3.4:5.2, follow-up]. Annual natriuretic peptide-based screening was performed, with collaborative cardiovascular care between specialist physicians and general practitioners provided to patients with BNP levels >50 pg/mL. Analysis of cost per case prevented and cost-effectiveness per quality-adjusted life year (QALY) gained was performed. The primary clinical endpoint of LV dysfunction (LVD) with or without HF was reduced in intervention patients [odds ratio (OR) 0.60; 95% confidence interval (CI) 0.38-0.94; P = 0.026]. There were 157 deaths and/or emergency hospitalizations for major adverse cardiac events (MACE) in the control group vs. 102 in the intervention group (OR 0.68; 95% CI 0.49-0.93; P = 0.01). The cost per case of LVD/HF prevented was €9683 (sensitivity range -€843 to €20 210), whereas the cost per MACE prevented was €3471 (sensitivity range -€302 to €7245). Cardiovascular hospitalization savings offset increased outpatient and primary care costs. The cost per QALY gain was €1104 and the intervention has an 88% probability of being cost-effective at a willingness to pay threshold of €30 000.

CONCLUSION: Among patients with cardiovascular risk factors, natriuretic peptide-based screening and collaborative care reduced LVD, HF, and MACE, and has a high probability of being cost-effective.

TRIAL REGISTRATION: NCT00921960.

Natriuretic peptide-based screening and collaborative care for heart failure:the STOP-HF randomized trial

IMPORTANCE: Prevention strategies for heart failure are needed.

OBJECTIVE: To determine the efficacy of a screening program using brain-type natriuretic peptide (BNP) and collaborative care in an at-risk population in reducing newly diagnosed heart failure and prevalence of significant left ventricular (LV) systolic and/or diastolic dysfunction.

DESIGN, SETTING, AND PARTICIPANTS: The St Vincent's Screening to Prevent Heart Failure Study, a parallel-group randomized trial involving 1374 participants with cardiovascular risk factors (mean age, 64.8 [SD, 10.2] years) recruited from 39 primary care practices in Ireland between January 2005 and December 2009 and followed up until December 2011 (mean follow-up, 4.2 [SD, 1.2] years).

INTERVENTION: Patients were randomly assigned to receive usual primary care (control condition; n=677) or screening with BNP testing (n=697). Intervention-group participants with BNP levels of 50 pg/mL or higher underwent echocardiography and collaborative care between their primary care physician and specialist cardiovascular service.

MAIN OUTCOMES AND MEASURES: The primary end point was prevalence of asymptomatic LV dysfunction with or without newly diagnosed heart failure. Secondary end points included emergency hospitalization for arrhythmia, transient ischemic attack, stroke, myocardial infarction, peripheral or pulmonary thrombosis/embolus, or heart failure.

RESULTS: A total of 263 patients (41.6%) in the intervention group had at least 1 BNP reading of 50 pg/mL or higher. The intervention group underwent more cardiovascular investigations (control, 496 per 1000 patient-years vs intervention, 850 per 1000 patient-years; incidence rate ratio, 1.71; 95% CI, 1.61-1.83; P<.001) and received more renin-angiotensin-aldosterone system-based therapy at follow-up (control, 49.6%; intervention, 56.5%; P=.01). The primary end point of LV dysfunction with or without heart failure was met in 59 (8.7%) of 677 in the control group and 37 (5.3%) of 697 in the intervention group (odds ratio [OR], 0.55; 95% CI, 0.37-0.82; P = .003). Asymptomatic LV dysfunction was found in 45 (6.6%) of 677 control-group patients and 30 (4.3%) of 697 intervention-group patients (OR, 0.57; 95% CI, 0.37-0.88; P = .01). Heart failure occurred in 14 (2.1%) of 677 control-group patients and 7 (1.0%) of 697 intervention-group patients (OR, 0.48; 95% CI, 0.20-1.20; P = .12). The incidence rates of emergency hospitalization for major cardiovascular events were 40.4 per 1000 patient-years in the control group vs 22.3 per 1000 patient-years in the intervention group (incidence rate ratio, 0.60; 95% CI, 0.45-0.81; P = .002).

CONCLUSION AND RELEVANCE: Among patients at risk of heart failure, BNP-based screening and collaborative care reduced the combined rates of LV systolic dysfunction, diastolic dysfunction, and heart failure.

TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT00921960.

Coupling short-term (B2G model) and long-term (g-function) models for ground source heat exchanger simulation in TRNSYS. Application in a real installation

Ground-source heat pump (GSHP) systems represent one of the most promising techniques for heating and cooling in buildings. These systems use the ground as a heat source/sink, allowing a better efficiency thanks to the low variations of the ground temperature along the seasons. The ground-source heat exchanger (GSHE) then becomes a key component for optimizing the overall performance of the system. Moreover, the short-term response related to the dynamic behaviour of the GSHE is a crucial aspect, especially from a regulation criteria perspective in on/off controlled GSHP systems. In this context, a novel numerical GSHE model has been developed at the Instituto de Ingeniería Energética, Universitat Politècnica de València. Based on the decoupling of the short-term and the long-term response of the GSHE, the novel model allows the use of faster and more precise models on both sides. In particular, the short-term model considered is the B2G model, developed and validated in previous research works conducted at the Instituto de Ingeniería Energética. For the long-term, the g-function model was selected, since it is a previously validated and widely used model, and presents some interesting features that are useful for its combination with the B2G model. The aim of the present paper is to describe the procedure of combining these two models in order to obtain a unique complete GSHE model for both short- and long-term simulation. The resulting model is then validated against experimental data from a real GSHP installation.

Outlier effects on robust joint modelling of longitudinal and survival data

Robust joint modelling is an emerging field of research. Through the advancements in electronic patient healthcare records, the popularly of joint modelling approaches has grown rapidly in recent years providing simultaneous analysis of longitudinal and survival data. This research advances previous work through the development of a novel robust joint modelling methodology for one of the most common types of standard joint models, that which links a linear mixed model with a Cox proportional hazards model. Through t-distributional assumptions, longitudinal outliers are accommodated with their detrimental impact being down weighed and thus providing more efficient and reliable estimates. The robust joint modelling technique and its major benefits are showcased through the analysis of Northern Irish end stage renal disease patients. With an ageing population and growing prevalence of chronic kidney disease within the United Kingdom, there is a pressing demand to investigate the detrimental relationship between the changing haemoglobin levels of haemodialysis patients and their survival. As outliers within the NI renal data were found to have significantly worse survival, identification of outlying individuals through robust joint modelling may aid nephrologists to improve patient's survival. A simulation study was also undertaken to explore the difference between robust and standard joint models in the presence of increasing proportions and extremity of longitudinal outliers. More efficient and reliable estimates were obtained by robust joint models with increasing contrast between the robust and standard joint models when a greater proportion of more extreme outliers are present. Through illustration of the gains in efficiency and reliability of parameters when outliers exist, the potential of robust joint modelling is evident. The research presented in this thesis highlights the benefits and stresses the need to utilise a more robust approach to joint modelling in the presence of longitudinal outliers.

Failure Mechanisms and Local Scour at Coastal Structures induced by Tsunamis

On March 11 2011, an exceptionally large tsunami event was triggered by a massive earthquake offshore, the northeast coast of Japan, which affected coastal infrastructure such as seawalls, coastal dikes and breakwaters in the Tohoku region. Such infrastructure was built to protect against the Level 1 tsunamis that previously hit the region, but not for events as significant as the 2011 Tohoku tsunami, which was categorized as a Level 2 tsunami [Shibayama et al. 2013]. The failure mechanisms of concrete-armoured dikes, breakwaters and seawalls due to Level 2 tsunamis are still not fully understood by researchers and engineers. This paper investigates the failure modes and mechanisms of damaged coastal structures in Miyagi and Fukushima Prefectures, following the authors' post-disaster field surveys carried out between 2011 and 2013. Six significant failure mechanisms were identified for the coastal dikes and seawalls affected by this tsunami: 1) Leeward toe scour failure, 2) Crown armour failure, 3) Leeward slope armour failure, 4) Seaward toe and armour failure, 5) Overturning failure, and 6) Parapet wall failure, in which leeward toe scour being recognized as the major failure mechanism in most surveyed locations. The authors also propose a simple practical mathematical model for predicting the scour depth at the leeward toe of the coastal dikes, by considering the effects of the tsunami hydrodynamics, the soil properties and the type of structure. The key advantage of this model is that it depends entirely on quantities that are measurable in the field. Furthermore this model was further refined by conducting a series of hydraulic model experiments aimed to understand the governing factors of the leeward toe scour failure. Finally, based on the results obtained, key recommendations are given for the design of resilient coastal defence structures that can survive a level 2 tsunami event.