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.

From Polymorph Screening to Dissolution Testing - Solid Phase Analysis during Pharmaceutical Development and Manufacturing

Solid materials can exist in different physical structures without a change in chemical composition. This phenomenon, known as polymorphism, has several implications on pharmaceutical development and manufacturing. Various solid forms of a drug can possess different physical and chemical properties, which may affect processing characteristics and stability, as well as the performance of a drug in the human body. Therefore, knowledge and control of the solid forms is fundamental to maintain safety and high quality of pharmaceuticals. During manufacture, harsh conditions can give rise to unexpected solid phase transformations and therefore change the behavior of the drug. Traditionally, pharmaceutical production has relied on time-consuming off-line analysis of production batches and finished products. This has led to poor understanding of processes and drug products. Therefore, new powerful methods that enable real time monitoring of pharmaceuticals during manufacturing processes are greatly needed. The aim of this thesis was to apply spectroscopic techniques to solid phase analysis within different stages of drug development and manufacturing, and thus, provide a molecular level insight into the behavior of active pharmaceutical ingredients (APIs) during processing. Applications to polymorph screening and different unit operations were developed and studied. A new approach to dissolution testing, which involves simultaneous measurement of drug concentration in the dissolution medium and in-situ solid phase analysis of the dissolving sample, was introduced and studied. Solid phase analysis was successfully performed during different stages, enabling a molecular level insight into the occurring phenomena. Near-infrared (NIR) spectroscopy was utilized in screening of polymorphs and processing-induced transformations (PITs). Polymorph screening was also studied with NIR and Raman spectroscopy in tandem. Quantitative solid phase analysis during fluidized bed drying was performed with in-line NIR and Raman spectroscopy and partial least squares (PLS) regression, and different dehydration mechanisms were studied using in-situ spectroscopy and partial least squares discriminant analysis (PLS-DA). In-situ solid phase analysis with Raman spectroscopy during dissolution testing enabled analysis of dissolution as a whole, and provided a scientific explanation for changes in the dissolution rate. It was concluded that the methods applied and studied provide better process understanding and knowledge of the drug products, and therefore, a way to achieve better quality.

Design and testing of stand-specific bucking instructions for use on modern cut-to-length harvesters

This study addresses three important issues in tree bucking optimization in the context of cut-to-length harvesting. (1) Would the fit between the log demand and log output distributions be better if the price and/or demand matrices controlling the bucking decisions on modern cut-to-length harvesters were adjusted to the unique conditions of each individual stand? (2) In what ways can we generate stand and product specific price and demand matrices? (3) What alternatives do we have to measure the fit between the log demand and log output distributions, and what would be an ideal goodness-of-fit measure? Three iterative search systems were developed for seeking stand-specific price and demand matrix sets: (1) A fuzzy logic control system for calibrating the price matrix of one log product for one stand at a time (the stand-level one-product approach); (2) a genetic algorithm system for adjusting the price matrices of one log product in parallel for several stands (the forest-level one-product approach); and (3) a genetic algorithm system for dividing the overall demand matrix of each of the several log products into stand-specific sub-demands simultaneously for several stands and products (the forest-level multi-product approach). The stem material used for testing the performance of the stand-specific price and demand matrices against that of the reference matrices was comprised of 9 155 Norway spruce (Picea abies (L.) Karst.) sawlog stems gathered by harvesters from 15 mature spruce-dominated stands in southern Finland. The reference price and demand matrices were either direct copies or slightly modified versions of those used by two Finnish sawmilling companies. Two types of stand-specific bucking matrices were compiled for each log product. One was from the harvester-collected stem profiles and the other was from the pre-harvest inventory data. Four goodness-of-fit measures were analyzed for their appropriateness in determining the similarity between the log demand and log output distributions: (1) the apportionment degree (index), (2) the chi-square statistic, (3) Laspeyres quantity index, and (4) the price-weighted apportionment degree. The study confirmed that any improvement in the fit between the log demand and log output distributions can only be realized at the expense of log volumes produced. Stand-level pre-control of price matrices was found to be advantageous, provided the control is done with perfect stem data. Forest-level pre-control of price matrices resulted in no improvement in the cumulative apportionment degree. Cutting stands under the control of stand-specific demand matrices yielded a better total fit between the demand and output matrices at the forest level than was obtained by cutting each stand with non-stand-specific reference matrices. The theoretical and experimental analyses suggest that none of the three alternative goodness-of-fit measures clearly outperforms the traditional apportionment degree measure. Keywords: harvesting, tree bucking optimization, simulation, fuzzy control, genetic algorithms, goodness-of-fit

Breath Testing by Fourier Transform Infrared Spectroscopy for Solvent Intoxication Diagnostics

Technical or contaminated ethanol products are sometimes ingested either accidentally or on purpose. Typical misused products are black-market liquor and automotive products, e.g., windshield washer fluids. In addition to less toxic solvents, these liquids may contain the deadly methanol. Symptoms of even lethal solvent poisoning are often non-specific at the early stage. The present series of studies was carried out to develop a method for solvent intoxication breath diagnostics to speed up the diagnosis procedure conventionally based on blood tests. Especially in the case of methanol ingestion, the analysis method should be sufficiently sensitive and accurate to determine the presence of even small amounts of methanol from the mixture of ethanol and other less-toxic components. In addition to the studies on the FT-IR method, the Dräger 7110 evidential breath analyzer was examined to determine its ability to reveal a coexisting toxic solvent. An industrial Fourier transform infrared analyzer was modified for breath testing. The sample cell fittings were widened and the cell size reduced in order to get an alveolar sample directly from a single exhalation. The performance and the feasibility of the Gasmet FT-IR analyzer were tested in clinical settings and in the laboratory. Actual human breath screening studies were carried out with healthy volunteers, inebriated homeless men, emergency room patients and methanol-intoxicated patients. A number of the breath analysis results were compared to blood test results in order to approximate the blood-breath relationship. In the laboratory experiments, the analytical performance of the Gasmet FT-IR analyzer and Dräger 7110 evidential breath analyzer was evaluated by means of artificial samples resembling exhaled breath. The investigations demonstrated that a successful breath ethanol analysis by Dräger 7110 evidential breath analyzer could exclude any significant methanol intoxication. In contrast, the device did not detect very high levels of acetone, 1-propanol and 2-propanol in simulated breath. The Dräger 7110 evidential breath ethanol analyzer was not equipped to recognize the interfering component. According to the studies the Gasmet FT-IR analyzer was adequately sensitive, selective and accurate for solvent intoxication diagnostics. In addition to diagnostics, the fast breath solvent analysis proved feasible for controlling the ethanol and methanol concentration during haemodialysis treatment. Because of the simplicity of the sampling and analysis procedure, non-laboratory personnel, such as police officers or social workers, could also operate the analyzer for screening purposes.

Ventricular repolarization during cardiovascular autonomic function testing

The autonomic nervous system is an important modulator of ventricular repolarization and arrhythmia vulnerability. This study explored the effects of cardiovascular autonomic function tests on repolarization and its heterogeneity, with a special reference to congenital arrhythmogenic disorders typically associated with stress-induced fatal ventricular arrhythmias. The first part explored the effects of standardized autonomic tests on QT intervals in a 12-lead electrocardiogram and in multichannel magnetocardiography in 10 healthy adults. The second part studied the effects of deep breathing, Valsalva manouvre, mental stress, sustained handgrip and mild exercise on QT intervals in asymptomatic patients with LQT1 subtype of the hereditary long QT syndrome (n=9) and in patients with arrhythmogenic right ventricular dysplasia (ARVD, n=9). Even strong sympathetic activation had no effects on spatial QT interval dispersion in healthy subjects, but deep respiratory efforts and Valsalva influenced it in ways that were opposite in electrocardiographic and magnetocardiographic recordings. LQT1 patients showed blunted QT interval and sinus nodal responses to sympathetic challenge, as well as an exaggerated QT prolongation during the recovery phases. LQT1 patients showed a QT interval recovery overshoot in 2.4 ± 1.7 tests compared with 0.8 ± 0.7 in healthy controls (P = 0.02). Valsalva strain prolonged the T wave peak to T wave end interval only in the LQT1 patients, considered to reflect the arrhythmogenic substrate in this syndrome. ARVD patients showed signs of abnormal repolarization in the right ventricle, modulated by abrupt sympathetic activation. An electrocardiographic marker reflecting interventricular dispersion of repolarization was introduced. It showed that LQT1 patients exhibit a repolarization gradient from the left ventricle towards the right ventricle, significantly larger than in controls. In contrast, ARVD patients showed a repolarization gradient from the right ventricle towards the left. Valsalva strain amplified the repolarization gradient in LQT1 patients whereas it transiently reversed it in patients with ARVD. In conclusion, intrathoracic volume and pressure changes influence regional electrocardiographic and magnetocardiographic QT interval measurements differently. Especially recovery phases of standard cardiovascular autonomic functions tests and Valsalva manoeuvre reveal the abnormal repolarization in asymptomatic LQT1 patients. Both LQT1 and ARVD patients have abnormal interventricular repolarization gradients, modulated by abrupt sympathetic activation. Autonomic testing and in particular the Valsalva manoeuvre are potentially useful in unmasking abnormal repolarization in these syndromes.

Towards Optimal Testing of Auditory Memory : Methodological development of recording of the mismatch negativity (MMN) of the auditory event-related potential (ERP)

The overlapping sound pressure waves that enter our brain via the ears and auditory nerves must be organized into a coherent percept. Modelling the regularities of the auditory environment and detecting unexpected changes in these regularities, even in the absence of attention, is a necessary prerequisite for orientating towards significant information as well as speech perception and communication, for instance. The processing of auditory information, in particular the detection of changes in the regularities of the auditory input, gives rise to neural activity in the brain that is seen as a mismatch negativity (MMN) response of the event-related potential (ERP) recorded by electroencephalography (EEG). --- As the recording of MMN requires neither a subject s behavioural response nor attention towards the sounds, it can be done even with subjects with problems in communicating or difficulties in performing a discrimination task, for example, from aphasic and comatose patients, newborns, and even fetuses. Thus with MMN one can follow the evolution of central auditory processing from the very early, often critical stages of development, and also in subjects who cannot be examined with the more traditional behavioural measures of auditory discrimination. Indeed, recent studies show that central auditory processing, as indicated by MMN, is affected in different clinical populations, such as schizophrenics, as well as during normal aging and abnormal childhood development. Moreover, the processing of auditory information can be selectively impaired for certain auditory attributes (e.g., sound duration, frequency) and can also depend on the context of the sound changes (e.g., speech or non-speech). Although its advantages over behavioral measures are undeniable, a major obstacle to the larger-scale routine use of the MMN method, especially in clinical settings, is the relatively long duration of its measurement. Typically, approximately 15 minutes of recording time is needed for measuring the MMN for a single auditory attribute. Recording a complete central auditory processing profile consisting of several auditory attributes would thus require from one hour to several hours. In this research, I have contributed to the development of new fast multi-attribute MMN recording paradigms in which several types and magnitudes of sound changes are presented in both speech and non-speech contexts in order to obtain a comprehensive profile of auditory sensory memory and discrimination accuracy in a short measurement time (altogether approximately 15 min for 5 auditory attributes). The speed of the paradigms makes them highly attractive for clinical research, their reliability brings fidelity to longitudinal studies, and the language context is especially suitable for studies on language impairments such as dyslexia and aphasia. In addition I have presented an even more ecological paradigm, and more importantly, an interesting result in view of the theory of MMN where the MMN responses are recorded entirely without a repetitive standard tone. All in all, these paradigms contribute to the development of the theory of auditory perception, and increase the feasibility of MMN recordings in both basic and clinical research. Moreover, they have already proven useful in studying for instance dyslexia, Asperger syndrome and schizophrenia.

Sensitivity of wetland methane emissions to model assumptions: application and model testing against site observations

Abstract. Methane emissions from natural wetlands and rice paddies constitute a large proportion of atmospheric methane, but the magnitude and year-to-year variation of these methane sources is still unpredictable. Here we describe and evaluate the integration of a methane biogeochemical model (CLM4Me; Riley et al., 2011) into the Community Land Model 4.0 (CLM4CN) in order to better explain spatial and temporal variations in methane emissions. We test new functions for soil pH and redox potential that impact microbial methane production in soils. We also constrain aerenchyma in plants in always-inundated areas in order to better represent wetland vegetation. Satellite inundated fraction is explicitly prescribed in the model because there are large differences between simulated fractional inundation and satellite observations. A rice paddy module is also incorporated into the model, where the fraction of land used for rice production is explicitly prescribed. The model is evaluated at the site level with vegetation cover and water table prescribed from measurements. Explicit site level evaluations of simulated methane emissions are quite different than evaluating the grid cell averaged emissions against available measurements. Using a baseline set of parameter values, our model-estimated average global wetland emissions for the period 1993–2004 were 256 Tg CH4 yr−1, and rice paddy emissions in the year 2000 were 42 Tg CH4 yr−1. Tropical wetlands contributed 201 Tg CH4 yr−1, or 78 % of the global wetland flux. Northern latitude (>50 N) systems contributed 12 Tg CH4 yr−1. We expect this latter number may be an underestimate due to the low high-latitude inundated area captured by satellites and unrealistically low high-latitude productivity and soil carbon predicted by CLM4. Sensitivity analysis showed a large range (150–346 Tg CH4 yr−1) in predicted global methane emissions. The large range was sensitive to: (1) the amount of methane transported through aerenchyma, (2) soil pH (± 100 Tg CH4 yr−1), and (3) redox inhibition (± 45 Tg CH4 yr−1).