Oxidative stability of phytosterols in food models and foods

An important safety aspect to be considered when foods are enriched with phytosterols and phytostanols is the oxidative stability of these lipid compounds, i.e. their resistance to oxidation and thus to the formation of oxidation products. This study concentrated on producing scientific data to support this safety evaluation process. In the absence of an official method for analyzing of phytosterol/stanol oxidation products, we first developed a new gas chromatographic - mass spectrometric (GC-MS) method. We then investigated factors affecting these compounds' oxidative stability in lipid-based food models in order to identify critical conditions under which significant oxidation reactions may occur. Finally, the oxidative stability of phytosterols and stanols in enriched foods during processing and storage was evaluated. Enriched foods covered a range of commercially available phytosterol/stanol ingredients, different heat treatments during food processing, and different multiphase food structures. The GC-MS method was a powerful tool for measuring the oxidative stability. Data obtained in food model studies revealed that the critical factors for the formation and distribution of the main secondary oxidation products were sterol structure, reaction temperature, reaction time, and lipid matrix composition. Under all conditions studied, phytostanols as saturated compounds were more stable than unsaturated phytosterols. In addition, esterification made phytosterols more reactive than free sterols at low temperatures, while at high temperatures the situation was the reverse. Generally, oxidation reactions were more significant at temperatures above 100°C. At lower temperatures, the significance of these reactions increased with increasing reaction time. The effect of lipid matrix composition was dependent on temperature; at temperatures above 140°C, phytosterols were more stable in an unsaturated lipid matrix, whereas below 140°C they were more stable in a saturated lipid matrix. At 140°C, phytosterols oxidized at the same rate in both matrices. Regardless of temperature, phytostanols oxidized more in an unsaturated lipid matrix. Generally, the distribution of oxidation products seemed to be associated with the phase of overall oxidation. 7-ketophytosterols accumulated when oxidation had not yet reached the dynamic state. Once this state was attained, the major products were 5,6-epoxyphytosterols and 7-hydroxyphytosterols. The changes observed in phytostanol oxidation products were not as informative since all stanol oxides quantified represented hydroxyl compounds. The formation of these secondary oxidation products did not account for all of the phytosterol/stanol losses observed during the heating experiments, indicating the presence of dimeric, oligomeric or other oxidation products, especially when free phytosterols and stanols were heated at high temperatures. Commercially available phytosterol/stanol ingredients were stable during such food processes as spray-drying and ultra high temperature (UHT)-type heating and subsequent long-term storage. Pan-frying, however, induced phytosterol oxidation and was classified as a rather deteriorative process. Overall, the findings indicated that although phytosterols and stanols are stable in normal food processing conditions, attention should be paid to their use in frying. Complex interactions between other food constituents also suggested that when new phytosterol-enriched foods are developed their oxidative stability must first be established. The results presented here will assist in choosing safe conditions for phytosterol/stanol enrichment.

Do Measurement Errors in GDP Announcements Cause Output Fluctuations?

This thesis studies empirically whether measurement errors in aggregate production statistics affect sentiment and future output. Initial announcements of aggregate production are subject to measurement error, because many of the data required to compile the statistics are produced with a lag. This measurement error can be gauged as the difference between the latest revised statistic and its initial announcement. Assuming aggregate production statistics help forecast future aggregate production, these measurement errors are expected to affect macroeconomic forecasts. Assuming agents’ macroeconomic forecasts affect their production choices, these measurement errors should affect future output through sentiment. This thesis is primarily empirical, so the theoretical basis, strategic complementarity, is discussed quite briefly. However, it is a model in which higher aggregate production increases each agent’s incentive to produce. In this circumstance a statistical announcement which suggests aggregate production is high would increase each agent’s incentive to produce, thus resulting in higher aggregate production. In this way the existence of strategic complementarity provides the theoretical basis for output fluctuations caused by measurement mistakes in aggregate production statistics. Previous empirical studies suggest that measurement errors in gross national product affect future aggregate production in the United States. Additionally it has been demonstrated that measurement errors in the Index of Leading Indicators affect forecasts by professional economists as well as future industrial production in the United States. This thesis aims to verify the applicability of these findings to other countries, as well as study the link between measurement errors in gross domestic product and sentiment. This thesis explores the relationship between measurement errors in gross domestic production and sentiment and future output. Professional forecasts and consumer sentiment in the United States and Finland, as well as producer sentiment in Finland, are used as the measures of sentiment. Using statistical techniques it is found that measurement errors in gross domestic product affect forecasts and producer sentiment. The effect on consumer sentiment is ambiguous. The relationship between measurement errors and future output is explored using data from Finland, United States, United Kingdom, New Zealand and Sweden. It is found that measurement errors have affected aggregate production or investment in Finland, United States, United Kingdom and Sweden. Specifically, it was found that overly optimistic statistics announcements are associated with higher output and vice versa.

Putative neuroprotective compounds in in vitro models of dopaminergic neurodegeneration

Parkinson´s disease (PD) is a debilitating age-related neurological disorder that affects various motor skills and can lead to a loss of cognitive functions. The motor symptoms are the result of the progressive degeneration of dopaminergic neurons within the substantia nigra. The factors that influence the pathogenesis and the progression of the neurodegeneration remain mostly unclear. This study investigated the role of various programmed cell death (PCD) pathways, oxidative stress, and glial cells both in dopaminergic neurodegeneration and in the protective action of various drugs. To this end, we exposed dopaminergic neuroblastoma cells (SH-SY5Y cells) to 6-OHDA, which produces oxidative stress and activates various PCD modalities that result in neuronal degeneration. Additionally, to explore the role of glia, we prepared rat midbrain primary mixed-cell cultures containing both neurons and glial cell types such as microglia and astroglia and then exposed the cultures to either MPP plus or lipopolysaccharide. Our results revealed that 6-OHDA activated several PCD pathways including apoptosis, autophagic stress, lysosomal membrane permeabilization, and perhaps paraptosis in SH-SY5Y cells. Furthermore, we found that minocycline protected SH-SY5Y cells from 6-OHDA by inhibiting both apoptotic and non-apoptotic PCD modalities. We also observed an inconsistent neuroprotective effect of various dietary anti-oxidant compounds against 6-OHDA toxicity in vitro in SH-SY5Y cells. Specifically, quercetin and curcumin exerted neuroprotection only within a narrow concentration range and a limited time frame, whereas resveratrol and epigallocatechin 3-gallate provided no protection whatsoever. Lastly, we found that molecules such as amantadine may delay or even halt the neurodegeneration in primary cell cultures by inhibiting the release of neurotoxic factors from overactivated microglia and by enhancing the pro-survival actions of astroglia. Together these data suggest that the strategy of dampening oxidative species with anti-oxidants is less effective than preventing the production of toxic factors such as oxidative and pro-inflammatory molecules by pathologically activated microglia. This would subsequently prevent the activation of various PCD modalities that cause neuronal degeneration.

Questions to Artificial Nature: A Philosophical Study of Interdisciplinary Models and their Functions in Scientific Practice

This thesis presents an interdisciplinary analysis of how models and simulations function in the production of scientific knowledge. The work is informed by three scholarly traditions: studies on models and simulations in philosophy of science, so-called micro-sociological laboratory studies within science and technology studies, and cultural-historical activity theory. Methodologically, I adopt a naturalist epistemology and combine philosophical analysis with a qualitative, empirical case study of infectious-disease modelling. This study has a dual perspective throughout the analysis: it specifies the modelling practices and examines the models as objects of research. The research questions addressed in this study are: 1) How are models constructed and what functions do they have in the production of scientific knowledge? 2) What is interdisciplinarity in model construction? 3) How do models become a general research tool and why is this process problematic? The core argument is that the mediating models as investigative instruments (cf. Morgan and Morrison 1999) take questions as a starting point, and hence their construction is intentionally guided. This argument applies the interrogative model of inquiry (e.g., Sintonen 2005; Hintikka 1981), which conceives of all knowledge acquisition as process of seeking answers to questions. The first question addresses simulation models as Artificial Nature, which is manipulated in order to answer questions that initiated the model building. This account develops further the "epistemology of simulation" (cf. Winsberg 2003) by showing the interrelatedness of researchers and their objects in the process of modelling. The second question clarifies why interdisciplinary research collaboration is demanding and difficult to maintain. The nature of the impediments to disciplinary interaction are examined by introducing the idea of object-oriented interdisciplinarity, which provides an analytical framework to study the changes in the degree of interdisciplinarity, the tools and research practices developed to support the collaboration, and the mode of collaboration in relation to the historically mutable object of research. As my interest is in the models as interdisciplinary objects, the third research problem seeks to answer my question of how we might characterise these objects, what is typical for them, and what kind of changes happen in the process of modelling. Here I examine the tension between specified, question-oriented models and more general models, and suggest that the specified models form a group of their own. I call these Tailor-made models, in opposition to the process of building a simulation platform that aims at generalisability and utility for health-policy. This tension also underlines the challenge of applying research results (or methods and tools) to discuss and solve problems in decision-making processes.

Uncertainty in forest simulators and forest planning systems

The forest simulator is a computerized model for predicting forest growth and future development as well as effects of forest harvests and treatments. The forest planning system is a decision support tool, usually including a forest simulator and an optimisation model, for finding the optimal forest management actions. The information produced by forest simulators and forest planning systems is used for various analytical purposes and in support of decision making. However, the quality and reliability of this information can often be questioned. Natural variation in forest growth and estimation errors in forest inventory, among other things, cause uncertainty in predictions of forest growth and development. This uncertainty stemming from different sources has various undesirable effects. In many cases outcomes of decisions based on uncertain information are something else than desired. The objective of this thesis was to study various sources of uncertainty and their effects in forest simulators and forest planning systems. The study focused on three notable sources of uncertainty: errors in forest growth predictions, errors in forest inventory data, and stochastic fluctuation of timber assortment prices. Effects of uncertainty were studied using two types of forest growth models, individual tree-level models and stand-level models, and with various error simulation methods. New method for simulating more realistic forest inventory errors was introduced and tested. Also, three notable sources of uncertainty were combined and their joint effects on stand-level net present value estimates were simulated. According to the results, the various sources of uncertainty can have distinct effects in different forest growth simulators. The new forest inventory error simulation method proved to produce more realistic errors. The analysis on the joint effects of various sources of uncertainty provided interesting knowledge about uncertainty in forest simulators.

Role of thrombin in coronary artery bypass grafting

Thrombin is a multifunctional protease, which has a central role in the development and progression of coronary atherosclerotic lesions and it is a possible mediator of myocardial ischemia-reperfusion injury. Its generation and procoagulant activity are greatly upregulated during cardiopulmonary bypass (CPB). On the other hand, activated protein C, a physiologic anticoagulant that is activated by thrombomodulin-bound thrombin, has been beneficial in various models of ischemia-reperfusion. Therefore, our aim in this study was to test whether thrombin generation or protein C activation during coronary artery bypass grafting (CABG) associate with postoperative myocardial damage or hemodynamic changes. To further investigate the regulation of thrombin during CABG, we tested whether preoperative thrombophilic factors associate with increased CPB-related generation of thrombin or its procoagulant activity. We also measured the anticoagulant effects of heparin during CPB with a novel coagulation test, prothrombinase-induced clotting time (PiCT), and compared the performance of this test with the present standard of laboratory-based anticoagulation monitoring. One hundred patients undergoing elective on-pump CABG were studied prospectively. A progressive increase in markers of thrombin generation (F1+2), fibrinolysis (D-dimer), and fibrin formation (soluble fibrin monomer complexes) was observed during CPB, which was further distinctly propagated by reperfusion after myocardial ischemia, and continued to peak after the neutralization of heparin with protamine. Thrombin generation during reperfusion after CABG associated with postoperative myocardial damage and increased pulmonary vascular resistance. Activated protein C levels increased only slightly during CPB before the release of the aortic clamp, but reperfusion and more significantly heparin neutralization caused a massive increase in activated protein C levels. Protein C activation was clearly delayed in relation to both thrombin generation and fibrin formation. Even though activated protein C associated dynamically with postoperative hemodynamic performance, it did not associate with postoperative myocardial damage. Preoperative thrombophilic variables did not associate with perioperative thrombin generation or its procoagulant activity. Therefore, our results do not favor routine thrombophilia screening before CABG. There was poor agreement between PiCT and other measurements of heparin effects in the setting of CPB. However, lower heparin levels during CPB associated with inferior thrombin control and high heparin levels during CPB associated with fewer perioperative transfusions of blood products. Overall, our results suggest that hypercoagulation after CABG, especially during reperfusion, might be clinically important.

On the behaviour of some physical parameterization methods in high-resolution numerical weather prediction models

Modern-day weather forecasting is highly dependent on Numerical Weather Prediction (NWP) models as the main data source. The evolving state of the atmosphere with time can be numerically predicted by solving a set of hydrodynamic equations, if the initial state is known. However, such a modelling approach always contains approximations that by and large depend on the purpose of use and resolution of the models. Present-day NWP systems operate with horizontal model resolutions in the range from about 40 km to 10 km. Recently, the aim has been to reach operationally to scales of 1 4 km. This requires less approximations in the model equations, more complex treatment of physical processes and, furthermore, more computing power. This thesis concentrates on the physical parameterization methods used in high-resolution NWP models. The main emphasis is on the validation of the grid-size-dependent convection parameterization in the High Resolution Limited Area Model (HIRLAM) and on a comprehensive intercomparison of radiative-flux parameterizations. In addition, the problems related to wind prediction near the coastline are addressed with high-resolution meso-scale models. The grid-size-dependent convection parameterization is clearly beneficial for NWP models operating with a dense grid. Results show that the current convection scheme in HIRLAM is still applicable down to a 5.6 km grid size. However, with further improved model resolution, the tendency of the model to overestimate strong precipitation intensities increases in all the experiment runs. For the clear-sky longwave radiation parameterization, schemes used in NWP-models provide much better results in comparison with simple empirical schemes. On the other hand, for the shortwave part of the spectrum, the empirical schemes are more competitive for producing fairly accurate surface fluxes. Overall, even the complex radiation parameterization schemes used in NWP-models seem to be slightly too transparent for both long- and shortwave radiation in clear-sky conditions. For cloudy conditions, simple cloud correction functions are tested. In case of longwave radiation, the empirical cloud correction methods provide rather accurate results, whereas for shortwave radiation the benefit is only marginal. Idealised high-resolution two-dimensional meso-scale model experiments suggest that the reason for the observed formation of the afternoon low level jet (LLJ) over the Gulf of Finland is an inertial oscillation mechanism, when the large-scale flow is from the south-east or west directions. The LLJ is further enhanced by the sea-breeze circulation. A three-dimensional HIRLAM experiment, with a 7.7 km grid size, is able to generate a similar LLJ flow structure as suggested by the 2D-experiments and observations. It is also pointed out that improved model resolution does not necessary lead to better wind forecasts in the statistical sense. In nested systems, the quality of the large-scale host model is really important, especially if the inner meso-scale model domain is small.

Studies on Binary Time Series Models with Applications to Empirical Macroeconomics and Finance

This thesis studies binary time series models and their applications in empirical macroeconomics and finance. In addition to previously suggested models, new dynamic extensions are proposed to the static probit model commonly used in the previous literature. In particular, we are interested in probit models with an autoregressive model structure. In Chapter 2, the main objective is to compare the predictive performance of the static and dynamic probit models in forecasting the U.S. and German business cycle recession periods. Financial variables, such as interest rates and stock market returns, are used as predictive variables. The empirical results suggest that the recession periods are predictable and dynamic probit models, especially models with the autoregressive structure, outperform the static model. Chapter 3 proposes a Lagrange Multiplier (LM) test for the usefulness of the autoregressive structure of the probit model. The finite sample properties of the LM test are considered with simulation experiments. Results indicate that the two alternative LM test statistics have reasonable size and power in large samples. In small samples, a parametric bootstrap method is suggested to obtain approximately correct size. In Chapter 4, the predictive power of dynamic probit models in predicting the direction of stock market returns are examined. The novel idea is to use recession forecast (see Chapter 2) as a predictor of the stock return sign. The evidence suggests that the signs of the U.S. excess stock returns over the risk-free return are predictable both in and out of sample. The new "error correction" probit model yields the best forecasts and it also outperforms other predictive models, such as ARMAX models, in terms of statistical and economic goodness-of-fit measures. Chapter 5 generalizes the analysis of univariate models considered in Chapters 2 4 to the case of a bivariate model. A new bivariate autoregressive probit model is applied to predict the current state of the U.S. business cycle and growth rate cycle periods. Evidence of predictability of both cycle indicators is obtained and the bivariate model is found to outperform the univariate models in terms of predictive power.

Inference on Cointegration in Vector Autoregressive Models (summary section only)

In the thesis we consider inference for cointegration in vector autoregressive (VAR) models. The thesis consists of an introduction and four papers. The first paper proposes a new test for cointegration in VAR models that is directly based on the eigenvalues of the least squares (LS) estimate of the autoregressive matrix. In the second paper we compare a small sample correction for the likelihood ratio (LR) test of cointegrating rank and the bootstrap. The simulation experiments show that the bootstrap works very well in practice and dominates the correction factor. The tests are applied to international stock prices data, and the .nite sample performance of the tests are investigated by simulating the data. The third paper studies the demand for money in Sweden 1970—2000 using the I(2) model. In the fourth paper we re-examine the evidence of cointegration between international stock prices. The paper shows that some of the previous empirical results can be explained by the small-sample bias and size distortion of Johansen’s LR tests for cointegration. In all papers we work with two data sets. The first data set is a Swedish money demand data set with observations on the money stock, the consumer price index, gross domestic product (GDP), the short-term interest rate and the long-term interest rate. The data are quarterly and the sample period is 1970(1)—2000(1). The second data set consists of month-end stock market index observations for Finland, France, Germany, Sweden, the United Kingdom and the United States from 1980(1) to 1997(2). Both data sets are typical of the sample sizes encountered in economic data, and the applications illustrate the usefulness of the models and tests discussed in the thesis.

Tarinakontekstin vaikutus sanojen muistamiseen kompleksisessa työmuistitehtävässä

Objectives. The sentence span task is a complex working memory span task used for estimating total working memory capacity for both processing (sentence comprehension) and storage (remembering a set of words). Several traditional models of working memory suggest that performance on these tasks relies on phonological short-term storage. However, long-term memory effects as well as the effects of expertise and strategies have challenged this view. This study uses a working memory task that aids the creation of retrieval structures in the form of stories, which have been shown to form integrated structures in longterm memory. The research question is whether sentence and story contexts boost memory performance in a complex working memory task. The hypothesis is that storage of the words in the task takes place in long-term memory. Evidence of this would be better recall for words as parts of sentences than for separate words, and, particularly, a beneficial effect for words as part of an organized story. Methods. Twenty stories consisting of five sentences each were constructed, and the stimuli in all experimental conditions were based on these sentences and sentence-final words, reordered and recombined for the other conditions. Participants read aloud sets of five sentences that either formed a story or not. In one condition they had to report all the last words at the end of the set, in another, they memorised an additional separate word with each sentence. The sentences were presented on the screen one word at a time (500 ms). After the presentation of each sentence, the participant verified a statement about the sentence. After five sentences, the participant repeated back the words in correct positions. Experiment 1 (n=16) used immediate recall, experiment 2 (n=21) both immediate recall and recall after a distraction interval (the operation span task). In experiment 2 a distracting mental arithmetic task was presented instead of recall in half of the trials, and an individual word was added before each sentence in the two experimental conditions when the participants were to memorize the sentence final words. Subjects also performed a listening span task (in exp.1) or an operation span task (exp.2) to allow comparison of the estimated span and performance in the story task. Results were analysed using correlations, repeated measures ANOVA and a chi-square goodness of fit test on the distribution of errors. Results and discussion. Both the relatedness of the sentences (the story condition) and the inclusion of the words into sentences helped memory. An interaction showed that the story condition had a greater effect on last words than separate words. The beneficial effect of the story was shown in all serial positions. The effects remained in delayed recall. When the sentences formed stories, performance in verification of the statements about sentence context was better. This, as well as the differing distributions of errors in different experimental conditions, suggest different levels of representation are in use in the different conditions. In the story condition, the nature of these representations could be in the form of an organized memory structure, a situation model. The other working memory tasks had only few week correlations to the story task. This could indicate that different processes are in use in the tasks. The results do not support short-term phonological storage, but instead are compatible with the words being encoded to LTM during the task.

Expression and function of angiotensins in the regulation of intraocular pressure - an experimental study

Glaucoma is a multifactorial long-term ocular neuropathy associated with progressive loss of the visual field, retinal nerve fiber structural abnormalities and optic disc changes. Like arterial hypertension it is usually a symptomless disease, but if left untreated leads to visual disability and eventual blindness. All therapies currently used aim to lower intraocular pressure (IOP) in order to minimize cell death. Drugs with new mechanisms of action could protect glaucomatous eyes against blindness. Renin-angiotensin system (RAS) is known to regulate systemic blood pressure and compounds acting on it are in wide clinical use in the treatment of hypertension and heart failure but not yet in ophthalmological use. There are only few previous studies concerning intraocular RAS, though evidence is accumulating that drugs antagonizing RAS can also lower IOP, the only treatable risk factor in glaucoma. The main aim of this experimental study was to clarify the expression of the renin-angiotensin system in the eye tissues and to test its potential oculohypotensive effects and mechanisms. In addition, the possible relationship between the development of hypertension and IOP was evaluated in animal models. In conclusion, a novel angiotensin receptor type (Mas), as well as ACE2 enzyme- producing agonists for Mas, were described for the first time in the eye structures participating in the regulation of IOP. In addition, a Mas receptor agonist significantly reduced even normal IOP. The effect was abolished by a specific receptor antagonist. Intraocular, local RAS would thus to be involved in the regulation of IOP, probably even more in pathological conditions such as glaucoma though there was no unambiguous relationship between arterial and ocular hypertension. The findings suggest the potential as antiglaucomatous drugs of agents which increase ACE2 activity and the formation of angiotensin (1-7), or activate Mas receptors.