Cadmium and lead accumulate in humans and can have toxic effects. Exposure to cadmium is well known to cause kidney damage. Cadmium binds to metallothioneins, proteins that play a role in cadmium transport. Lead exposure’s main effect is on the central nervous system, but associations with kidney disease have also been found, although it is unknown if the latter is a causal association. The main source of both metals within the non-smoking population is from the diet. This thesis aims to 1) compare the biomarkers lead and cadmium concentration in whole-blood, plasma and urine with regard to their ability to discriminate between individuals with different mean concentrations, and to describe the effect of urinary dilution, 2) estimate the association between end-stage renal disease and blood concentrations of cadmium, lead and mercury, using prospectively collected samples for exposure evaluation, 3) use longitudinal data on kidney function makers to evaluate kidney recovery after a substantial decrease in cadmium exposure, and 4) assess the influence of metallothionein polymorphisms (MT1A rs11076161, MT2A rs10636 and MT2A rs28366003) on cadmium-associated kidney toxicity and recovery due to a reduction in Cd exposure. Repeated sampling of whole-blood, plasma and urine was conducted on 48 occupationally lead-exposed men and 20 individuals under normal environmental lead exposure, for estimation of the day-to-day and between individual-variation. Prospective samples were obtained for 118 cases that later in life developed end-stage renal disease, and 378 matched controls. Erythrocyte cadmium, lead, and mercury concentrations were determined and the risk of developing end-stage renal disease associated with metal concentrations was estimated. For evaluation of kidney recovery after a reduction in cadmium exposure and to test for gene-environment interactions, follow-up data on N-acetyl-β‑d-glucosaminidase, β2‑microglobulin, albumin, and gene polymorphisms were obtained for 412 individuals within the Chinese population and the relation to blood and urinary cadmium was assessed. The concentration of lead in blood was found to be the biomarker with the largest fraction of the total variance attributable to between-individual variation, and was therefore the biomarker with the best ability to discriminate between individuals with different mean concentrations, both for individuals under occupational and normal environmental exposure (91 and 95%, respectively). Adjusting for urinary dilution had a great effect on the fraction of the total variance attributable to between-individual variation among individuals with normal lead exposure but only a minor effect among those who were occupationally exposed. Variance analysis showed that blood concentrations were also the best discriminating biomarker for cadmium. Erythrocyte lead was, in a univariate model, associated with an increased risk of developing end-stage renal disease [odds ratio (OR) = 1.54 for an interquartile range increase, with a 95% confidence interval (CI) = 1.18-2.00], while erythrocyte mercury was negatively associated (OR = 0.75 for an interquartile range increase, with a 95% CI = 0.56-0.99). For erythrocyte cadmium, the OR was 1.15 with a 95% CI of 0.99-1.34. Associations with lead and cadmium were only seen among men. In the study on kidney recovery, the proportion of individuals with albumin level above the 95th percentile decreased between baseline and follow up, but no decrease was found for the tubular markers N-acetyl-β‑d-glucosaminidase and β2-microglobulin. Metallothionein polymorphisms modified cadmium-associated effects on N-acetyl-β‑d-glucosaminidase and β2-microglobulin levels but did not modify cadmium-associated change in any of the kidney function markers between baseline and follow up after a substantial decrease in exposure. Blood concentrations of lead and cadmium are the biomarkers with the best ability to discriminate between individuals with different mean concentrations. Adjustment for urinary dilution has great influence on the fraction of the total variance attributed to between individual variation among urine samples with low lead concentrations, but only a small influence on samples with high lead concentrations. This suggests a difference in excretion. The association between end-stage renal disease and low-level lead exposure, as assessed through prospective erythrocyte samples, gives reason for concern, although further studies are needed to determine causality. A cadmium-associated increase in albumin is reversible after a substantial reduction in exposure, but this is not the case for the observed tubular effects. The tubular kidney effects of cadmium might be modified by the MT1A rs11076161 polymorphism. / För att bedöma exponering för kadmium och bly mäts ofta deras koncentrationer i blod eller urin. Dessa studerades i longitudinella data för 48 blyarbetare och 20 individer med normal miljömässig exponering. Blod- och urinprover togs var annan till var tredje månad. Kadmium- och blykoncentrationer mättes sedan i helblod, plasma och urin. Koncentrationer av bly i blod var den biomarkör som hade den största andelen av den totala variationen som kunde förklaras av skillnader mellan individer, och var därför den biomarkör med den bästa förmågan att särskilja på individer med olika medelkoncentration, både för individer med yrkesexponering och normal miljömässig exponering (91 respektive 95% av variansen berodde på vilken individ blodprovet kom ifrån). Justering för urinens utspädning av bly i urin förbättrar oftast urins användbarhet som biomarkör. För bly stämde detta bara hos dem som inte var blyarbetare. Blodkoncentrationer var också den biomarkör med störst andel av den totala variation som kunde förklaras med skillnader mellan individer för kadmium. Kadmium och bly ackumuleras i njure respektive ben och kan ha toxikologiska effekter. Det är välkänt att höga exponeringsnivåer av kadmium orsakar njurskada och även vid lägre exponeringsnivåer har studier funnit samband med markörer för njurfunktion. Exponering för bly påverkar i första hand det centrala nervsystemet. Studier har dock funnit samband mellan koncentrationer av bly i blod och njurens glomerulära filtrationshastighet. Det är oklart både om dessa associationer, vid låga exponeringsnivåer, är viktiga för hälsan och om de verkligen beror på att kadmium och bly orsakar njurskada. För att studera end-stage renal disease användes prospektiva kohorter där personer lämnat blodprov för forskning: Västerbottens interventionsprogram med prover som tagits vid Västerbottens hälsoundersökningar, MONICA-undersökningar i Norr- och Västerbotten, mammografiundersökningarna i Västerbotten och Malmö kost cancer. Sammanlagt ingick över ett hundra tusen individer i dessa kohorter. Med hjälp av det Svenska njurregistret identifierades sedan 118 personer som senare i livet fått end-stage renal disease. Dessa jämfördes med 378 kontroller. För dessa 496 personer tinades blodprovet (närmare bestämt röda blodkroppar) upp och analyserades för kadmium och bly. För att undersöka njurens förmåga till återhämtning studerades tre områden i Kina varav ett tidigare varit kraftigt kadmiumexponerat. Erytrocytkoncentrationer av bly var, utan att ta hänsyn till några andra variabler, associerat med en ökad risk för att utveckla end-stage renal disease (med oddskvoten 1.54 för en interquartile range ökning av erytrocytbly, med ett 95% konfidensintervall 1.18-2.00). Sambanden kvarstod också efter att ha tagit hänsyn till övriga variabler. För erytrocytkadmium var oddskvoten 1.15 med 95% konfidensintervall 0.99-1.34, och sambandet försvagades när hänsyn togs till andra variabler. Associationerna sågs bland män men inte bland kvinnor. Eftersom kadmium vid höga nivåer orsakar njurskada är det också av intresse att studera om påverkan på njuren går över om exponeringen minskas. Totalt följdes 412 individer upp med mätningar av markörer för njurfunktion och kadmiumkoncentrationer i blod och urin. Första undersökningen gjordes 1998, då man just hade slutat äta kadmiumförorenat ris. En andra undersökning gjordes 2006. Andelen individer med avvikande albuminvärde i urin var lägre vid uppföljningen jämfört med vid baslinjen, men ingen minskning sågs för markörer för tubulär förmåga att återta proteiner. Åttioprocent av kadmium i celler är bundet till proteinet metallotheonin, vilket skyddar mot cellskada, men har också en roll i transporten av kadmium från levern till njurarna. En tidigare studie har visat att njurens känslighet för kadmiumexponering var associerad med genetiska skillnader i detta protein. För att studera genetiska associationer studerades de 412 personerna i den kinesiska studien [då också individernas genotyper av metallotheonin-polymorfierna MT1A rs11076161 (G/A), MT2A rs10636 (G/C) och MT2A rs28366003 (A/G) bestämdes]. Genetiken spelade roll för sambandet mellan förmåga att återta proteiner och kadmium men påverkade inte förändring av njurfunktion efter att man slutat äta kadmiumförorenat ris. Kadmium- och blykoncentrationer i blod är de biomarkörer, av koncentrationer i blod, plasma och urin, med den bästa förmågan att skilja på individer med olika medelkoncentrationer. Justering för urinutspädning påverkade andelen av den totala variationen som kunde förklaras av skillnader mellan individer i stor utsträckning för individer med normal miljömässig exponering men inte bland yrkesexponerade, vilket tyder på en skillnad i hur utsöndringen går till. Associationen mellan end-stage renal disease och låg exponering för bly, uppmätta i prospektiva erytrocytprover, ger orsak till oro, men ytterligare studier behövs för att kunna utvärdera om detta är ett kausalt samband. En kadmiumrelaterad skada av den glomerulära filtrationen är reversibel efter en kraftig reducering i exponering, men detta är inte fallet för tubulär skada. De tubulära njureffekterna av kadmiumexponering kan påverkas av metallotheonin-polymorfier.

This thesis addresses the computation and organization of conceptual knowledge. Specifically, it focuses on the recruitment of concrete knowledge during single word reading using behavioural and electrophysiological methodologies. Chapters 1 and 2 assess how number of visual semantic features listed by participants as being part of a given concept influence the speed of word meaning computation, and its neural underpinnings, providing evidence for modality-specific neural organization. Chapter 3 assesses the flexibility of knowledge activation as a function of specific task constraints, suggesting a multi-faceted approach to semantic richness is needed. Chapter 4 describes a novel application of recent statistical advances to the analysis of real-time electrophysiological data, and highlights some limitations of standard analytical approaches. Chapter 5 assesses the real-time influence of several types of knowledge on the neuroelectric activity underlying concrete word meaning computation. A timecourse of sensory-based knowledge type activation is outlined. Finally, Chapter 6 describes a novel approach whereby real-time electrophysiological brain activity is used to predict the speed of semantic decision making, providing further evidence of a highly flexible, but finely structured, human semantic memory system.

This thesis addresses the computation and organization of conceptual knowledge. Specifically, it focuses on the recruitment of concrete knowledge during single word reading using behavioural and electrophysiological methodologies. Chapters 1 and 2 assess how number of visual semantic features listed by participants as being part of a given concept influence the speed of word meaning computation, and its neural underpinnings, providing evidence for modality-specific neural organization. Chapter 3 assesses the flexibility of knowledge activation as a function of specific task constraints, suggesting a multi-faceted approach to semantic richness is needed. Chapter 4 describes a novel application of recent statistical advances to the analysis of real-time electrophysiological data, and highlights some limitations of standard analytical approaches. Chapter 5 assesses the real-time influence of several types of knowledge on the neuroelectric activity underlying concrete word meaning computation. A timecourse of sensory-based knowledge type activation is outlined. Finally, Chapter 6 describes a novel approach whereby real-time electrophysiological brain activity is used to predict the speed of semantic decision making, providing further evidence of a highly flexible, but finely structured, human semantic memory system.

High levels of automation in manufacturing industries are leading to data sets of increasing size and dimension. The challenge facing statisticians and field professionals is to develop methodology to help meet this demand. Functional data is one example of high-dimensional data characterized by observations recorded as a function of some continuous measure, such as time. An application considered in this thesis comes from the automotive industry. It involves a production process in which valve seats are force-fitted by a ram into cylinder heads of automobile engines. For each insertion, the force exerted by the ram is automatically recorded every fraction of a second for about two and a half seconds, generating a force profile. We can think of these profiles as individual functions of time summarized into collections of curves. The focus of this thesis is the analysis of functional process data such as the valve seat insertion example. A number of techniques are set forth. In the first part, two ways to model a single curve are considered: a b-spline fit via linear regression, and a nonlinear model based on differential equations. Each of these approaches is incorporated into a mixed effects model for multiple curves, and multivariate process monitoring techniques are applied to the predicted random effects in order to identify anomalous curves. In the second part, a Bayesian hierarchical model is used to cluster low-dimensional summaries of the curves into meaningful groups. The belief is that the clusters correspond to distinct types of processes (e.g. various types of “good” or “faulty” assembly). New observations can be assigned to one of these by calculating the probabilities of belonging to each cluster. Mahalanobis distances are used to identify new observations not belonging to any of the existing clusters. Synthetic and real data are used to validate the results.

High levels of automation in manufacturing industries are leading to data sets of increasing size and dimension. The challenge facing statisticians and field professionals is to develop methodology to help meet this demand. Functional data is one example of high-dimensional data characterized by observations recorded as a function of some continuous measure, such as time. An application considered in this thesis comes from the automotive industry. It involves a production process in which valve seats are force-fitted by a ram into cylinder heads of automobile engines. For each insertion, the force exerted by the ram is automatically recorded every fraction of a second for about two and a half seconds, generating a force profile. We can think of these profiles as individual functions of time summarized into collections of curves. The focus of this thesis is the analysis of functional process data such as the valve seat insertion example. A number of techniques are set forth. In the first part, two ways to model a single curve are considered: a b-spline fit via linear regression, and a nonlinear model based on differential equations. Each of these approaches is incorporated into a mixed effects model for multiple curves, and multivariate process monitoring techniques are applied to the predicted random effects in order to identify anomalous curves. In the second part, a Bayesian hierarchical model is used to cluster low-dimensional summaries of the curves into meaningful groups. The belief is that the clusters correspond to distinct types of processes (e.g. various types of “good” or “faulty” assembly). New observations can be assigned to one of these by calculating the probabilities of belonging to each cluster. Mahalanobis distances are used to identify new observations not belonging to any of the existing clusters. Synthetic and real data are used to validate the results.

Receptor occupancy assessed by Positron Emission Tomography (PET) can provide important translational information to help bridge information from one drug to another or from animal to man. The aim of this thesis was to develop nonlinear mixed effects methods for estimation of the relationship between drug exposure and receptor occupancy for the two mGluR5 antagonists AZD9272 and AZD2066 and for the 5HT1B receptor antagonist AZD3783. Also the optimal design for improved estimation of the relationship between drug exposure and receptor occupancy as well as for improved dose finding in neuropathic pain treatment, was investigated. Different modeling approaches were applied. For AZD9272, the radioligand kinetics and receptor occupancy was simultaneously estimated using arterial concentrations as input function and including two brain regions of interest. For AZD2066, a model was developed where brain/plasma partition coefficients from ten different brain regions were included simultaneously as observations. For AZD3783, the simplified reference tissue model was extended to allow different non-specific binding in the reference region and brain regions of interest and the possibility of using white matter as reference was also evaluated. The optimal dose-selection for improved precision of receptor occupancy as well as for improved precision of the minimum effective dose of a neuropathic pain treatment was assessed, using the D-optimal as well as the Ds-optimal criteria. Simultaneous modelling of radioligand and occupancy provided a means to avoid simplifications or approximations and provided the possibility to tests or to relax assumptions. Inclusion of several brain regions of different receptor density simultaneously in the analysis, markedly improved the precision of the affinity parameter. Higher precision was achieved in relevant parameters with designs based on the Ds compared to the D-optimal criterion. The optimal design for improved precision of the relationship between dose and receptor occupancy depended on the number of brain regions and the receptor density of these regions. In conclusion, this thesis presents novel non-linear mixed effects models estimating the relationship between drug exposure and receptor occupancy, providing useful translational information, allowing for a better informed drug-development.

With societies aging all around the world, the global burden of degenerative diseases is expected to increase exponentially. From the perspective drug development, degenerative diseases represent an especially challenging class. Clinical trials, in this context often termed disease progression studies, are long, costly, require many individuals, and have low success rates. Therefore, it is crucial to use informative study designs and to analyze efficiently the obtained trial data. The development of novel approaches intended towards facilitating both the design and the analysis of disease progression studies was the aim of this thesis. This aim was pursued in three stages (i) the characterization and extension of pharmacometric software, (ii) the development of new methodology around statistical power, and (iii) the demonstration of application benefits. The optimal design software PopED was extended to simplify the application of optimal design methodology when planning a disease progression study. The performance of non-linear mixed effect estimation algorithms for trial data analysis was evaluated in terms of bias, precision, robustness with respect to initial estimates, and runtime. A novel statistic allowing for explicit optimization of study design for statistical power was derived and found to perform superior to existing methods. Monte-Carlo power studies were accelerated through application of parametric power estimation, delivering full power versus sample size curves from a few hundred Monte-Carlo samples. Optimal design and an explicit optimization for statistical power were applied to the planning of a study in Alzheimer's disease, resulting in a 30% smaller study size when targeting 80% power. The analysis of ADAS-cog score data was improved through application of item response theory, yielding a more exact description of the assessment score, an increased statistical power and an enhanced insight in the assessment properties. In conclusion, this thesis presents novel pharmacometric methods that can help addressing the challenges of designing and planning disease progression studies.

The question of adverbs and the meaning of the present perfect across varieties of English is central to sociolinguistic variationist methodologies that have approached the study of the present perfect (Winford, 1993; Tagliamonte, 1997; van Herk, 2008, 2010; Davydova, 2010; Tagliamonte, 2013). This dissertation attempts to disentangle the effect of adverbial support from the three canonical readings of the present perfect (Resultative, Experiential and Continuative). Canadian English, an understudied variety of English, is used to situate the results seen in the Early Modern English data. Early Modern English reflects the time period in which English has acquired the full modern use of the present perfect with the three readings. In order to address both these questions and current controversies over statistical models in sociolinguistics, different statistical models are used: both the traditional Goldvarb X (Sankoff, Tagliamonte and Smith, 2005) and the newer mixed-effects logistic regression (Johnson, 2009). What is missing from the previous literature in sociolinguistics that advocates logistic mixed-effects models, and provided in this dissertation, is a clear statement of where they are inappropriate to use and their limitations. The rate of adverbial marking of the present perfect in Canadian English falls between rates reported for US and British English in previous studies. The data show in both time periods that while adverbs are highly favored in continuative contexts, they are strongly disfavored in experiential and resultative contexts. In Early Modern English, adverbial support functions statistically differently for resultatives and experientials, but that difference collapses in the Canadian English sample. Both this and the other linguistic contexts support a different analysis for each set of data with respect to adverbial independence from the meaning of the present perfect form. Finally, when the focus of the analysis is on linguistic rather than social factors, both the traditional and newer models provide similar results. Where there are differences, however, these can be accounted for by the number of tokens and different estimation techniques for each model.

The cost of releasing a new drug on the market has increased rapidly in the last decade. The reasons for this increase vary with the drug, but the need to make correct decisions earlier in the drug development process and to maximize the information gained throughout the process is evident. Optimal experimental design (OD) describes the procedure of maximizing relevant information in drug development and drug treatment processes. While various optimization criteria can be considered in OD, the most common is to optimize the unknown model parameters for an upcoming study. To date, OD has mainly been used to optimize the independent variables, e.g. sample times, but it can be used for any design variable in a study. This thesis addresses the OD of multiple continuous or discrete design variables for nonlinear mixed effects models. The methodology for optimizing and the optimization of different types of models with either continuous or discrete data are presented and the benefits of OD for such models are shown. A software tool for optimizing these models in parallel is developed and three OD examples are demonstrated: 1) optimization of an intravenous glucose tolerance test resulting in a reduction in the number of samples by a third, 2) optimization of drug compound screening experiments resulting in the estimation of nonlinear kinetics and 3) an individual dose-finding study for the treatment of children with ciclosporin before kidney transplantation resulting in a reduction in the number of blood samples to ~27% of the original number and an 83% reduction in the study duration. This thesis uses examples and methodology to show that studies in drug development and drug treatment can be optimized using nonlinear mixed effects OD. This provides a tool than can lower the cost and increase the overall efficiency of drug development and drug treatment.

Thesis (Ph.D.) OGI School of Science & Engineering at OHSU, June 2008. / Includes bibliographical references (leaves 138-145).