Investigating the modulation of oral drug absorption using in vitro models

Dipeptides can be absorbed into cells via the dipeptide transporter (which also transported tripeptides and dipeptide derivatives). The optimum conditions for measuring the inhibition of Gly-Pro uptake in Caco-2 cells were identified. A number of structure-activity relationships were identified. These included the effects of increasing the amino-acid chain-length, and the presence of a thiol or hydroxyl group in the side-chain increased IC50 while the presence of a hydroxyl group did not. The benzyl esters had lower or equal IC50 values compared to the parent dipeptides while the methyl esters had higher values. These results indicated that while molecular properties did affect IC50, the size, charge and composition of three particular groups caused the most significant effects, supporting the structure-activity relationship identified. An assay was developed using calcein-AM to show the inhibition of p-glycoprotein activity. There was no significant change due to the presence of mannitol but there was in the presence of clyclosporin A (p<0.01). Incubating the cells with the test solution for 30 minutes before the addition of the ester resulted in a significant (p<0.001) difference. The assay was specific for p-glycoprotein, as the presence MRP inhibitors had no effect (p>0.05). The modified protocol allowed the identification of p-glycoprotein inhibitors quickly and simply using a cell suspension of unmodified cells. The clinically relevant buffering of grapefruit juice to pH 7 led to a four-fold increase in intracellular calcein and hence significant inhibition of p-glycoprotein. Buffered orange and lemon juices had no effect on the assay. Flavone derivatives had previously been found to be inhibitors of CYP3A4 yet neither naringin nor naringenin had any significant effect at concentrations found in grapefruit juice. Of the other (non-grapefruit) flavone derivatives tested, hesperidin, found in orange juice, had no significant effect, kaempferol and rutin also had no effect while genistein significantly inhibited p-glycoprotein (results that support previous studies). Hydroxycinnamic acids had no effect on p-glycoprotein. Studies on other compounds found that the balance between inhibiting p-glycoprotein and disrupting cell membranes depends on the compound containing an oxygen atom and the size of the negative charge on it, as well as three-dimensional arrangement of the atoms.

Reducing suffering in animal models and procedures involving seizures, convulsions and epilepsy

This report is based on discussions and submissions from an expert working group consisting of veterinarians, animal care staff and scientists with expert knowledge relevant to the field and aims to facilitate the implementation of the Three Rs (replacement, reduction and refinement) in the use of animal models or procedures involving seizures, convulsions and epilepsy. Each of these conditions will be considered, the specific welfare issues discussed, and practical measures to reduce animal use and suffering suggested. The emphasis is on refinement since this has the greatest potential for immediate implementation, and some general issues for refinement are summarised to help achieve this, with more detail provided on a range of specific refinements.

A multi-level investigation of psychological contract breach and organizational identification through the lens of perceived organizational membership:testing a moderated-mediated model

Drawing on the perceived organizational membership theoretical framework and the social identity view of dissonance theory, I examined in this study the dynamics of the relationship between psychological contract breach and organizational identification. I included group-level transformational and transactional leadership as well as procedural justice in the hypothesized model as key antecedents for organizational membership processes. I further explored the mediating role of psychological contract breach in the relationship between leadership, procedural justice climate, and organizational identification and proposed separateness–connectedness self-schema as an important moderator of the above mediated relationship. Hierarchical linear modeling results from a sample of 864 employees from 162 work units in 10 Greek organizations indicated that employees' perception of psychological contract breach negatively affected their organizational identification. I also found psychological contract breach to mediate the impact of transformational and transactional leadership on organizational identification. Results further provided support for moderated mediation and showed that the indirect effects of transformational and transactional leadership on identification through psychological contract breach were stronger for employees with a low connectedness self-schema.

Changing employment relation systems in Japan:cases of the Mitsubishi Chemical Group and the Federation of Shinkin Banks

Over the past decade or so a number of changes have been observed in traditional Japanese employment relations (ERs) systems such as an increase in non-regular workers, a move towards performance-based systems and a continuous decline in union membership. There is a large body of Anglo-Saxon and Japanese literature providing evidence that national factors such as national institutions, national culture, and the business and economic environment have significantly influenced what were hitherto three ‘sacred’ aspects of Japanese ERs systems (ERSs). However, no research has been undertaken until now at the firm level regarding the extent to which changes in national factors influence ERSs across firms. This article develops a model to examine the impact of national factors on ER systems; and analyses the impact of national factors at the firm level ER systems. Based on information collected from two different groups of companies, namely Mitsubishi Chemical Group (MCG) and Federation of Shinkin Bank (FSB) the research finds that except for a few similarities, the impact of national factors is different on Japanese ER systems at the firm level. This indicates that the impact of national factors varies in the implementation of employment relations factors. In the case of MCG, national culture has less to do with seniority-based system. Study also reveals that the national culture factors have also less influence on an enterprise-based system in the case of FSB. This analysis is useful for domestic and international organizations as it helps to better understand the role of national factors in determining Japanese ERSs.

Evaluating spread models with a basket security

In this article we evaluate the most widely used spread decomposition models using Exchange Traded Funds (ETFs). These funds are an example of a basket security and allow the diversification of private information causing these securities to have lower adverse selection costs than individual securities. We use this feature as a criterion for evaluating spread decomposition models. Comparisons of adverse selection costs for ETF's and control securities obtained from spread decomposition models show that only the Glosten-Harris (1988) and the Madhavan-Richardson-Roomans (1997) models provide estimates of the spread that are consistent with the diversification of private information in a basket security. Our results are robust even after controlling for the stock exchange. © 2011 Copyright Taylor and Francis Group, LLC.

Optimal Decision Rules in Logical Recognition Models

The task of smooth and stable decision rules construction in logical recognition models is considered. Logical regularities of classes are defined as conjunctions of one-place predicates that determine the membership of features values in an intervals of the real axis. The conjunctions are true on a special no extending subsets of reference objects of some class and are optimal. The standard approach of linear decision rules construction for given sets of logical regularities consists in realization of voting schemes. The weighting coefficients of voting procedures are done as heuristic ones or are as solutions of complex optimization task. The modifications of linear decision rules are proposed that are based on the search of maximal estimations of standard objects for their classes and use approximations of logical regularities by smooth sigmoid functions.

Investigation of the causes of serious injury and fatal crashes: An analysis using econometric models

The rate of fatal crashes in Florida has remained significantly higher than the national average for the last several years. The 2003 statistics from the National Highway Traffic Safety Administration (NHTSA), the latest available, show a fatality rate in Florida of 1.71 per 100 million vehicle-miles traveled compared to the national average of 1.48 per 100 million vehicle-miles traveled. The objective of this research is to better understand the driver, environmental, and roadway factors that affect the probability of injury severity in Florida. ^ In this research, the ordered logit model was used to develop six injury severity models; single-vehicle and two-vehicle crashes on urban freeways and urban principal arterials and two-vehicle crashes at urban signalized and unsignalized intersections. The data used in this research included all crashes that occurred on the state highway system for the period from 2001 to 2003 in the Southeast Florida region, which includes the Miami-Dade, Broward and Palm Beach Counties.^ The results of the analysis indicate that the age group and gender of the driver at fault were significant factors of injury severity risk across all models. The greatest risk of severe injury was observed for the age groups 55 to 65 and 66 and older. A positive association between injury severity and the race of the driver at fault was also found. Driver at fault of Hispanic origin was associated with a higher risk of severe injury for both freeway models and for the two-vehicle crash model on arterial roads. A higher risk of more severe injury crash involvement was also found when an African-American was the at fault driver on two-vehicle crashes on freeways. In addition, the arterial class was also found to be positively associated with a higher risk of severe crashes. Six-lane divided arterials exhibited the highest injury severity risk of all arterial classes. The lowest severe injury risk was found for one way roads. Alcohol involvement by the driver at fault was also found to be a significant risk of severe injury for the single-vehicle crash model on freeways. ^

Origin of the Grande Ronde Formation flows, Columbia River flood basalt group

Lavas belonging to the Grande Ronde Formation (GRB) constitute about 63% of the Columbia River Basalt Group (CRBG), a flood basalt province in the NW United States. A puzzling feature is the lack of phenocrysts (< 5%) in these chemically evolved lavas. Based mainly on this observation it has been hypothesized that GRB lavas were nearly primary melts generated by large-scale melting of eclogite. Another recent hypothesis holds that GRB magmas were extremely hydrous and rose rapidly from the mantle such that the dissolved water kept the magmas close to their liquidi. I present new textural and chemical evidence to show that GRB lavas were neither primary nor hydrous melts but were derived from other melts via efficient fractional crystallization and mixing in shallow intrusive systems. Texture and chemical features further suggest that the melt mixing process may have been exothermic, which forced variable melting of some of the existing phenocrysts. ^ Finally, reported here are the results of efforts to simulate the higher pressure histories of GRB using COMAGMAT and MELTS softwares. The intent was to evaluate (1) whether such melts could be derived from primary melts formed by partial melting of a peridotite source as an alternative to the eclogite model, or if bulk melting of eclogite is required; and (2) at what pressure such primary melts could have been in equilibrium with the mantle. I carried out both forward and inverse modeling. The best fit forward model indicates that most primitive parent melts related to GRB could have been multiply saturated at ∼1.5--2.0 GPa. I interpret this result to indicate that the parental melts last equilibrated with a peridotitic mantle at 1.5--2.0 GPa and such partial melts rose to ∼0.2 GPa where they underwent efficient mixing and fractionation before erupting. These models suggest that the source rock was not eclogitic but a fertile spinel lherzolite, and that the melts had ∼0.5% water. ^

Developing a leadership identity: A case study exploring a select group of Hispanic women at a Hispanic serving institution

Leadership is a socially constructed concept shaped by the context, values and experiences of society (Klenke, 1996); the historical context of gender and ethnicity in society affects views about leadership and who merits a leadership role. Therefore, developing an understanding of Hispanic women students’ leadership identity development is critical in broadening how we define leadership and develop leadership education. The purpose of this qualitative case study was to explore and describe the leadership identity development of a select group of women leaders at a Hispanic Serving Institution (HSI) in the southeast. A psychosocial approach to the study was utilized. In-depth interviews and focus groups were conducted with 11 self-identified Hispanic women students of sophomore, junior or senior standing with varying degrees of involvement in leadership activities at Florida International University. Participants were asked questions related to four topics; (a) leadership, (b) gender, (c) ethnic identity, and (d) influences that contributed to their understanding of self as leader. Five topics emerged from the data presented by the participants’: (a) encouraging relationships, (b) meaningful experiences, (c) self development, (d) the role of gender, and (e) impact of ethnicity. These themes contributed to the leadership identity development of the participants. Findings indicate that leadership identity development for Hispanic women college students at this HSI is complex. The concept of leadership identity development presented in the literature was challenged as findings indicate that the participants’ experiences living and attending a school in a majority-minority city influenced their development of a leadership identity. The data indicate that leadership is not gender or ethnicity neutral as differences exist in expectations of men and women in leadership roles. Gender expectations posed particular challenges for these women student leaders. The prescriptive nature of stage-based models was problematic as findings indicated leadership identity development a complicated and continuing process influenced strongly by relationships and experiences. This study enhanced knowledge of the ways that Hispanic women students become leaders and the influences that shape their leadership experiences which can assist higher education professionals in developing leadership programs and courses that address gender, multiculturalism and awareness of self as leader.

Assessing the impact of business group diversification on the internationalization of their affiliates: The case of Latin American firms

This dissertation explored the capacity of business group diversification to generate value to their affiliates in an institutional environment characterized by the adoption of structural pro-market reforms. In particular, the three empirical essays explored the impact of business group diversification on the internationalization process of their affiliates. ^ The first essay examined the direct effect of business group diversification on firm performance and its moderating effect on the multinationality-performance relationship. It further explored whether such moderating effect varies depending upon whether the focal affiliate is a manufacturing or service firm. The findings suggested that the benefits of business group diversification on firm performance have a threshold, that those benefits are significant at earlier stages of internationalization and that these benefits are stronger for service firms. ^ The second essay studied the capacity of business group diversification to ameliorate the negative effects of the added complexity faced by its affiliates when they internationalized. The essay explored this capacity in different dimensions of international complexity. The results indicated that business group diversification effectively ameliorated the effects of the added international complexity. This positive effect is stronger in the institutional voids rather than the societal complexity dimension. In the former dimension, diversified business groups can use both their non-market resources and previous experience to ameliorate the effects of complexity on firm performance. ^ The last essay explored whether the benefits of business group diversification on the scope-performance relationship varies depending on the level of development of the network of subsidiaries and the region of operation of the focal firm. The results suggested that the benefits of business group diversification are location bound within the region but that they are not related to the level of development of the targeted countries. ^ The three essays use longitudinal analyses on a sample of Latin American firms to test the hypotheses. While the first essay used multilevel models and fix effects models, the last two essays used exclusively fix effects models to assess the impact of business group diversification. In conclusion, this dissertation aimed to explain the capacity of business group diversification to generate value under conditions of institutional change.^

The effects of student -centered and traditional models of teaching on reading skills

A pre-test, post-test, quasi-experimental design was used to examine the effects of student-centered and traditional models of reading instruction on outcomes of literal comprehension and critical thinking skills. The sample for this study consisted of 101 adult students enrolled in a high-level developmental reading course at a large, urban community college in the Southeastern United States. The experimental group consisted of 48 students, and the control group consisted of 53 students. Students in the experimental group were limited in the time spent reading a course text of basic skills, with instructors using supplemental materials such as poems, news articles, and novels. Discussions, the reading-writing connection, and student choice in material selection were also part of the student-centered curriculum. Students in the control group relied heavily on a course text and vocabulary text for reading material, with great focus placed on basic skills. Activities consisted primarily of multiple-choice questioning and quizzes. The instrument used to collect pre-test data was Descriptive Tests of Language Skills in Reading Comprehension; post-test data were taken from the Florida College Basic Skills Exit Test. A MANCOVA was used as the statistical method to determine if either model of instruction led to significantly higher gains in literal comprehension skills or critical thinking skills. A paired samples t-test was also used to compare pre-test and post-test means. The results of the MANCOVA indicated no significant difference between instructional models on scores of literal comprehension and critical thinking. Neither was there any significant difference in scores between subgroups of age (under 25 and 25 and older) and language background (native English speaker and second-language learner). The results of the t-test indicated, however, that students taught under both instructional models made significant gains in on both literal comprehension and critical thinking skills from pre-test to post-test.

Chlorine contribution to quantitative structure and activity relationship models of disinfection by -products' quantum chemical descriptors and toxicities

Quantitative Structure-Activity Relationship (QSAR) has been applied extensively in predicting toxicity of Disinfection By-Products (DBPs) in drinking water. Among many toxicological properties, acute and chronic toxicities of DBPs have been widely used in health risk assessment of DBPs. These toxicities are correlated with molecular properties, which are usually correlated with molecular descriptors. The primary goals of this thesis are: (1) to investigate the effects of molecular descriptors (e.g., chlorine number) on molecular properties such as energy of the lowest unoccupied molecular orbital (E LUMO) via QSAR modelling and analysis; (2) to validate the models by using internal and external cross-validation techniques; (3) to quantify the model uncertainties through Taylor and Monte Carlo Simulation. One of the very important ways to predict molecular properties such as ELUMO is using QSAR analysis. In this study, number of chlorine (NCl ) and number of carbon (NC) as well as energy of the highest occupied molecular orbital (EHOMO) are used as molecular descriptors. There are typically three approaches used in QSAR model development: (1) Linear or Multi-linear Regression (MLR); (2) Partial Least Squares (PLS); and (3) Principle Component Regression (PCR). In QSAR analysis, a very critical step is model validation after QSAR models are established and before applying them to toxicity prediction. The DBPs to be studied include five chemical classes: chlorinated alkanes, alkenes, and aromatics. In addition, validated QSARs are developed to describe the toxicity of selected groups (i.e., chloro-alkane and aromatic compounds with a nitro- or cyano group) of DBP chemicals to three types of organisms (e.g., Fish, T. pyriformis, and P.pyosphoreum) based on experimental toxicity data from the literature. The results show that: (1) QSAR models to predict molecular property built by MLR, PLS or PCR can be used either to select valid data points or to eliminate outliers; (2) The Leave-One-Out Cross-Validation procedure by itself is not enough to give a reliable representation of the predictive ability of the QSAR models, however, Leave-Many-Out/K-fold cross-validation and external validation can be applied together to achieve more reliable results; (3) E LUMO are shown to correlate highly with the NCl for several classes of DBPs; and (4) According to uncertainty analysis using Taylor method, the uncertainty of QSAR models is contributed mostly from NCl for all DBP classes.

A generic model of execution for synthesizing domain-specific models

Software engineering researchers are challenged to provide increasingly more powerful levels of abstractions to address the rising complexity inherent in software solutions. One new development paradigm that places models as abstraction at the forefront of the development process is Model-Driven Software Development (MDSD). MDSD considers models as first class artifacts, extending the capability for engineers to use concepts from the problem domain of discourse to specify apropos solutions. A key component in MDSD is domain-specific modeling languages (DSMLs) which are languages with focused expressiveness, targeting a specific taxonomy of problems. The de facto approach used is to first transform DSML models to an intermediate artifact in a HLL e.g., Java or C++, then execute that resulting code.^ Our research group has developed a class of DSMLs, referred to as interpreted DSMLs (i-DSMLs), where models are directly interpreted by a specialized execution engine with semantics based on model changes at runtime. This execution engine uses a layered architecture and is referred to as a domain-specific virtual machine (DSVM). As the domain-specific model being executed descends the layers of the DSVM the semantic gap between the user-defined model and the services being provided by the underlying infrastructure is closed. The focus of this research is the synthesis engine, the layer in the DSVM which transforms i-DSML models into executable scripts for the next lower layer to process.^ The appeal of an i-DSML is constrained as it possesses unique semantics contained within the DSVM. Existing DSVMs for i-DSMLs exhibit tight coupling between the implicit model of execution and the semantics of the domain, making it difficult to develop DSVMs for new i-DSMLs without a significant investment in resources.^ At the onset of this research only one i-DSML had been created for the user- centric communication domain using the aforementioned approach. This i-DSML is the Communication Modeling Language (CML) and its DSVM is the Communication Virtual machine (CVM). A major problem with the CVM's synthesis engine is that the domain-specific knowledge (DSK) and the model of execution (MoE) are tightly interwoven consequently subsequent DSVMs would need to be developed from inception with no reuse of expertise.^ This dissertation investigates how to decouple the DSK from the MoE and subsequently producing a generic model of execution (GMoE) from the remaining application logic. This GMoE can be reused to instantiate synthesis engines for DSVMs in other domains. The generalized approach to developing the model synthesis component of i-DSML interpreters utilizes a reusable framework loosely coupled to DSK as swappable framework extensions.^ This approach involves first creating an i-DSML and its DSVM for a second do- main, demand-side smartgrid, or microgrid energy management, and designing the synthesis engine so that the DSK and MoE are easily decoupled. To validate the utility of the approach, the SEs are instantiated using the GMoE and DSKs of the two aforementioned domains and an empirical study to support our claim of reduced developmental effort is performed.^

Multilevel structural equation models for longitudinal data where predictors are measured more frequently than outcomes : an application to the effects of stress on the cognitive function of nurses

Funded by Chief Scientist Office, Scotland. Grant Number: CZH/4/394 Economic and Social Research Council grant as part of the National Centre for Research Methods. Grant Number: RES-576-25-0032

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.