Rapid bioassay as indicator of potentially harmful effects for dioxin-like compounds in sample of Ya-Er Lake, China: Requirements for clean-up and comparison to chemical analysis

A rapid bioassay was established measuring the extracts of wildlife samples which were taken from Ya-Er Lake area, China. In extracts of these samples containing PCDD/Fs and PCBs, bioassay and chemically derived TCDD-equivalents (TEQs) were nearly identical. Our results indicate this bioassay is an excellent complement to chemical residue analysis and a useful tool in understanding the complex interactions of halogenated hydrocarbons. However, it must be mentioned that the proper prior clean-up method is very important for using the bioassay.

Comparison and evaluation of the specificity and binding capacity of commercial and in house affinity columns used in sample preparation for analysis of growth-promoting drugs

Immunoaffinity chromatography (IAC) and affinity chromatography (AC:) are widely used for extraction of drugs from biological samples. Fifteen column types were purchased from five different manufacturers and;their ability to bind specific drugs including beta-agonists and anabolic steroids over a range of analyte concentrations in fortified bovine urine samples was assessed. The performance data obtained from these columns were compared with columns produced in this laboratory (in house columns). The in house columns gave the highest recoveries, ranging from 92 to 100% at the 1 ng spiking concentration, for five of the seven analytes assessed. Forty percent (11 of 27) of all the commercial column assessments recorded recoveries of less than 50% even when the lowest spiking concentration was applied (1 ng). For one manufacturer, only one of seven different columns purchased delivered extraction efficiencies greater than 50%. The extraction efficiencies of the clenbuterol columns were the highest with all commercially prepared columns showing at least 50% binding of radiolabelled tracer. Recoveries of alpha-nortestosterone were the lowest. The variability of these products with respect to quality control requires constant monitoring.

Quantitative estimation of Br, Cl, K and Na in sample blood by NAA

Neutron activation analysis, using Au as flux monitor, was applied to determine the concentrations of Br, Cl, K and Na in blood of healthy male and female blood donors, selected from blood banks and hematological laboratories from different regions of Brazil. The aims of this study were to collect more reference values of the Brazilian population as well as to perform hematological investigations. The advantages as well as the limitations of using this nuclear procedure are discussed.

A simple parametric method for reducing sample sizes in gut passage time trials

Seed dispersal is now regularly analyzed using spatially explicit models, relying in part on frugivore gut passage times to produce model outputs. In determining species-specific gut passage times, there is a trade-off in sample size between minimizing collection effort and maintaining statistical reliability. Here we demonstrate that a two-parameter lognormal parametric distribution reliably fits empirical gut passage time distributions and is easily parameterized using relatively small data sets of approximately 30 defecations. We suggest this approach as a statistically reliable substitute for larger empirical gut passage data sets in seed dispersal modeling, and also as a way of using published gut passage data sets to parameterize new models.

The distribution of the sample minimum-variance frontier

In this paper, we present a finite sample analysis of the sample minimum-variance frontier under the assumption that the returns are independent and multivariate normally distributed. We show that the sample minimum-variance frontier is a highly biased estimator of the population frontier, and we propose an improved estimator of the population frontier. In addition, we provide the exact distribution of the out-of-sample mean and variance of sample minimum-variance portfolios. This allows us to understand the impact of estimation error on the performance of in-sample optimal portfolios. Key Words: minimum-variance frontier; efficiency set constants; finite sample distribution

Addressing issues in sparseness, ecological bias and formulation of the adjacency matrix in Bayesian spatio-temporal analysis of disease counts

The main objective of this PhD was to further develop Bayesian spatio-temporal models (specifically the Conditional Autoregressive (CAR) class of models), for the analysis of sparse disease outcomes such as birth defects. The motivation for the thesis arose from problems encountered when analyzing a large birth defect registry in New South Wales. The specific components and related research objectives of the thesis were developed from gaps in the literature on current formulations of the CAR model, and health service planning requirements. Data from a large probabilistically-linked database from 1990 to 2004, consisting of fields from two separate registries: the Birth Defect Registry (BDR) and Midwives Data Collection (MDC) were used in the analyses in this thesis. The main objective was split into smaller goals. The first goal was to determine how the specification of the neighbourhood weight matrix will affect the smoothing properties of the CAR model, and this is the focus of chapter 6. Secondly, I hoped to evaluate the usefulness of incorporating a zero-inflated Poisson (ZIP) component as well as a shared-component model in terms of modeling a sparse outcome, and this is carried out in chapter 7. The third goal was to identify optimal sampling and sample size schemes designed to select individual level data for a hybrid ecological spatial model, and this is done in chapter 8. Finally, I wanted to put together the earlier improvements to the CAR model, and along with demographic projections, provide forecasts for birth defects at the SLA level. Chapter 9 describes how this is done. For the first objective, I examined a series of neighbourhood weight matrices, and showed how smoothing the relative risk estimates according to similarity by an important covariate (i.e. maternal age) helped improve the model’s ability to recover the underlying risk, as compared to the traditional adjacency (specifically the Queen) method of applying weights. Next, to address the sparseness and excess zeros commonly encountered in the analysis of rare outcomes such as birth defects, I compared a few models, including an extension of the usual Poisson model to encompass excess zeros in the data. This was achieved via a mixture model, which also encompassed the shared component model to improve on the estimation of sparse counts through borrowing strength across a shared component (e.g. latent risk factor/s) with the referent outcome (caesarean section was used in this example). Using the Deviance Information Criteria (DIC), I showed how the proposed model performed better than the usual models, but only when both outcomes shared a strong spatial correlation. The next objective involved identifying the optimal sampling and sample size strategy for incorporating individual-level data with areal covariates in a hybrid study design. I performed extensive simulation studies, evaluating thirteen different sampling schemes along with variations in sample size. This was done in the context of an ecological regression model that incorporated spatial correlation in the outcomes, as well as accommodating both individual and areal measures of covariates. Using the Average Mean Squared Error (AMSE), I showed how a simple random sample of 20% of the SLAs, followed by selecting all cases in the SLAs chosen, along with an equal number of controls, provided the lowest AMSE. The final objective involved combining the improved spatio-temporal CAR model with population (i.e. women) forecasts, to provide 30-year annual estimates of birth defects at the Statistical Local Area (SLA) level in New South Wales, Australia. The projections were illustrated using sixteen different SLAs, representing the various areal measures of socio-economic status and remoteness. A sensitivity analysis of the assumptions used in the projection was also undertaken. By the end of the thesis, I will show how challenges in the spatial analysis of rare diseases such as birth defects can be addressed, by specifically formulating the neighbourhood weight matrix to smooth according to a key covariate (i.e. maternal age), incorporating a ZIP component to model excess zeros in outcomes and borrowing strength from a referent outcome (i.e. caesarean counts). An efficient strategy to sample individual-level data and sample size considerations for rare disease will also be presented. Finally, projections in birth defect categories at the SLA level will be made.

Novel Mass Spectrometric Analysis Methods for Anabolic Androgenic Steroids in Sports Drug Testing

The feasibility of different modern analytical techniques for the mass spectrometric detection of anabolic androgenic steroids (AAS) in human urine was examined in order to enhance the prevalent analytics and to find reasonable strategies for effective sports drug testing. A comparative study of the sensitivity and specificity between gas chromatography (GC) combined with low (LRMS) and high resolution mass spectrometry (HRMS) in screening of AAS was carried out with four metabolites of methandienone. Measurements were done in selected ion monitoring mode with HRMS using a mass resolution of 5000. With HRMS the detection limits were considerably lower than with LRMS, enabling detection of steroids at low 0.2-0.5 ng/ml levels. However, also with HRMS, the biological background hampered the detection of some steroids. The applicability of liquid-phase microextraction (LPME) was studied with metabolites of fluoxymesterone, 4-chlorodehydromethyltestosterone, stanozolol and danazol. Factors affecting the extraction process were studied and a novel LPME method with in-fiber silylation was developed and validated for GC/MS analysis of the danazol metabolite. The method allowed precise, selective and sensitive analysis of the metabolite and enabled simultaneous filtration, extraction, enrichment and derivatization of the analyte from urine without any other steps in sample preparation. Liquid chromatographic/tandem mass spectrometric (LC/MS/MS) methods utilizing electrospray ionization (ESI), atmospheric pressure chemical ionization (APCI) and atmospheric pressure photoionization (APPI) were developed and applied for detection of oxandrolone and metabolites of stanozolol and 4-chlorodehydromethyltestosterone in urine. All methods exhibited high sensitivity and specificity. ESI showed, however, the best applicability, and a LC/ESI-MS/MS method for routine screening of nine 17-alkyl-substituted AAS was thus developed enabling fast and precise measurement of all analytes with detection limits below 2 ng/ml. The potential of chemometrics to resolve complex GC/MS data was demonstrated with samples prepared for AAS screening. Acquired full scan spectral data (m/z 40-700) were processed by the OSCAR algorithm (Optimization by Stepwise Constraints of Alternating Regression). The deconvolution process was able to dig out from a GC/MS run more than the double number of components as compared with the number of visible chromatographic peaks. Severely overlapping components, as well as components hidden in the chromatographic background could be isolated successfully. All studied techniques proved to be useful analytical tools to improve detection of AAS in urine. Superiority of different procedures is, however, compound-dependent and different techniques complement each other.

Critical review on the stability of illicit drugs in sewers and wastewater samples

Wastewater-based epidemiology (WBE) applies advanced analytical methods to quantify drug residues in wastewater with the aim to estimate illicit drug use at the population level. Transformation processes during transport in sewers (chemical and biological reactors) and storage of wastewater samples before analysis are expected to change concentrations of different drugs to varying degrees. Ignoring transformation for drugs with low to medium stability will lead to an unknown degree of systematic under- or overestimation of drug use, which should be avoided. This review aims to summarize the current knowledge related to the stability of commonly investigated drugs and, furthermore, suggest a more effective approach to future experiments. From over 100 WBE studies, around 50 mentioned the importance of stability and 24 included tests in wastewater. Most focused on in-sample stability (i.e., sample preparation, preservation and storage) and some extrapolated to in-sewer stability (i.e., during transport in real sewers). While consistent results were reported for rather stable compounds (e.g., MDMA and methamphetamine), a varying range of stability under different or similar conditions was observed for other compounds (e.g., cocaine, amphetamine and morphine). Wastewater composition can vary considerably over time, and different conditions prevail in different sewer systems. In summary, this indicates that more systematic studies are needed to: i) cover the range of possible conditions in sewers and ii) compare results more objectively. To facilitate the latter, we propose a set of parameters that should be reported for in-sewer stability experiments. Finally, a best practice of sample collection, preservation, and preparation before analysis is suggested in order to minimize transformation during these steps.

Unrealized expectations of jumps in volatility: An explanation to the low and time-varying predictive power of implied volatility

The low predictive power of implied volatility in forecasting the subsequently realized volatility is a well-documented empirical puzzle. As suggested by e.g. Feinstein (1989), Jackwerth and Rubinstein (1996), and Bates (1997), we test whether unrealized expectations of jumps in volatility could explain this phenomenon. Our findings show that expectations of infrequently occurring jumps in volatility are indeed priced in implied volatility. This has two important consequences. First, implied volatility is actually expected to exceed realized volatility over long periods of time only to be greatly less than realized volatility during infrequently occurring periods of very high volatility. Second, the slope coefficient in the classic forecasting regression of realized volatility on implied volatility is very sensitive to the discrepancy between ex ante expected and ex post realized jump frequencies. If the in-sample frequency of positive volatility jumps is lower than ex ante assessed by the market, the classic regression test tends to reject the hypothesis of informational efficiency even if markets are informationally effective.

Diet and condition of American Alligators (Alligator mississippiensis)in three central Florida lakes

Understanding the diet of crocodilians is important because diet affects condition, behavior, growth, and reproduction. By examining the diet of crocodilians, valuable knowledge is gained about predator-prey interactions and prey utilization among habitats. In this study, I examined the diet and condition of adult American alligators (Alligator mississippiensis) in three central Florida lakes, Griffin, Apopka, and Woodruff. Two hundred adult alligators were captured and lavaged from March through October 2001, from April through October 2002, and from April through August 2003. Alligators ate a variety of vertebrate and invertebrate prey, but vertebrates were more abundant and fish dominated alligator diets in the lakes. Species composition of fish varied among the lakes. The majority of the diet of alligators from Lakes Apopka and Woodruff was fish, 90% and 84% respectively. Lake Apopka alligators consumed a significantly (P = 0.006) higher proportion of fish in their diet. Fish were 54% of the diet of Lake Griffin alligators and the infrequent occurrence of reptiles, mammals, birds, and amphibians often resulted in a large biomass. Differences in alligator diets among lakes may be due to differences in sample size (higher numbers of samples from Lake Griffin), prey availability, habitat, prey vulnerability, or prey size. Alligator condition (Fulton’s Condition Factor, K) was significantly (P < 0.001) different among the lakes. Alligators from Lake Apopka had the highest condition, followed by those from Lake Griffin, and alligators from Lake Woodruff had the lowest condition. Composition of fish along with diversity and equitability of fish in alligator diets may have contributed to differences in condition among lakes. Condition was probably also due to factors other than diet such as alligator hunting behavior, alligator density, or year-round optimal temperature that prolongs feeding. The observed diet and condition differences probably reflect both habitat differences and prey availability in these three lakes.

Photomechanically Induced Phase Transitions in Ferroelectric Liquid Crystals

We report optically induced phase transtions occurring in two different host ferroelectric liquid crystals; SCE13 a multicomponentmixture optimised for room temperature performance, and CE8 a single component liquid crystal. These act as host liquid crystals for a novel guest azo dye, which can be made to photoisomerise using low power density U.V. illumination, resulting in dramatic changes in sample properties. We have shown that the magnitude of spontaneous polarisation of systems can be isothermally and reversibly induced or reduced, with the consequent appearance or disappearance of optical switching hysteresis. We discuss the parameters controlling the behaviour of the systems under U.V. illumination and suggest mechansims by which the transitions may occur. © 1993, Taylor & Francis Group, LLC. All rights reserved.

Modification of the trapped field in bulk high-temperature superconductors as a result of the drilling of a pattern of artificial columnar holes

The trapped magnetic field is examined in bulk high-temperature superconductors that are artificially drilled along their c-axis. The influence of the hole pattern on the magnetization is studied and compared by means of numerical models and Hall probe mapping techniques. To this aim, we consider two bulk YBCO samples with a rectangular cross-section that are drilled each by six holes arranged either on a rectangular lattice (sample I) or on a centered rectangular lattice (sample II). For the numerical analysis, three different models are considered for calculating the trapped flux: (i), a two-dimensional (2D) Bean model neglecting demagnetizing effects and flux creep, (ii), a 2D finite-element model neglecting demagnetizing effects but incorporating magnetic relaxation in the form of an E-J power law, and, (iii), a 3D finite element analysis that takes into account both the finite height of the sample and flux creep effects. For the experimental analysis, the trapped magnetic flux density is measured above the sample surface by Hall probe mapping performed before and after the drilling process. The maximum trapped flux density in the drilled samples is found to be smaller than that in the plain samples. The smallest magnetization drop is found for sample II, with the centered rectangular lattice. This result is confirmed by the numerical models. In each sample, the relative drops that are calculated independently with the three different models are in good agreement. As observed experimentally, the magnetization drop calculated in the sample II is the smallest one and its relative value is comparable to the measured one. By contrast, the measured magnetization drop in sample (1) is much larger than that predicted by the simulations, most likely because of a change of the microstructure during the drilling process.