Browsing by Subject "pääkomponenttianalyysi"
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(2011)FTIR spectroscopy (Fourier transform infrared spectroscopy) is a fast method of analysis. The use of interferometers in Fourier devices enables the scanning of the whole infrared frequency region in a couple of seconds. There is no need to elaborate sample preparation when the FTIR spectrometer is equipped with an ATR accessory and the method is therefore easy to use. ATR accessory facilitates the analysis of various sample types. It is possible to measure infrared spectra from samples which are not suitable for traditional sample preparation methods. The data from FTIR spectroscopy is frequently combined with statistical multivariate analysis techniques. In cluster analysis the data from spectra can be grouped based on similarity. In hierarchical cluster analysis the similarity between objects is determined by calculating the distance between them. Principal component analysis reduces the dimensionality of the data and establishes new uncorrelated principal components. These principal components should preserve most of the variation of the original data. The possible applications of FTIR spectroscopy combined with multivariate analysis have been studied a lot. For example in food industry its feasibility in quality control has been evaluated. The method has also been used for the identification of chemical compositions of essential oils and for the detection of chemotypes in oil plants. In this study the use of the method was evaluated in the classification of hog's fennel extracts. FTIR spectra of extracts from different plant parts of hog's fennel were compared with the measured FTIR spectra of standard substances. The typical absorption bands in the FTIR spectra of standard substances were identified. The wave number regions of the intensive absorption bands in the spectra of furanocoumarins were selected for multivariate analyses. Multivariate analyses were also performed in the fingerprint region of IR spectra, including the wave number region 1785-725 cm-1. The aim was to classify extracts according to the habitat and coumarin concentration of the plants. Grouping according to habitat was detected, which could mainly be explained by coumarin concentrations as indicated by analyses of the wave number regions of the selected absorption bands. In these analyses extracts mainly grouped and differed by their total coumarin concentrations. In analyses of the wave number region 1785-725 cm-1 grouping according to habitat was also detected but this could not be explained by coumarin concentrations. These groupings may have been caused by similar concentrations of other compounds in the samples. Analyses using other wave number regions were also performed, but the results from these experiments did not differ from previous results. Multivariate analyses of second-order derivative spectra in the fingerprint region did not reveal any noticeable changes either. In future studies the method could perhaps be further developed by investigating narrower carefully selected wave number regions of second-order derivative spectra.
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(2018)Introduction: Stress can be found already in young children. It may be associated with, for example, family life situations, bullying or the daycare environment. The body secretes cortisol, a stress hormone, in response to stress. Abnormal corti- sol levels are associated with overweight and a preference for energy-dense foods high in sugar and fat. Studying the link between children’s stress and diet is important as the early childhood is an important period for the development of eat- ing habits as well as for the prevention of obesity and later chronic illnesses. Aims: The aim of this study is to investigate if hair cortisol concentration, a measure of long-term stress, is associated with the food patterns of three to six year old Finnish children. Other aims include determining the mean hair cortisol concen- tration in the sample and studying whether the concentration or food patterns differ by background factors. Materials and methods: The study is a part of the DAGIS study’s cross-sectional phase conducted in 66 daycare centers in Uusimaa and South Ostrobothnia in 2015–2016. The data consists of 864 three to six year old children, of whom 541 pro- vided the information needed to examine the main research question between hair cortisol and dietary intake. The data used in the study was collected through a food frequency questionnaire, food diaries, a guardian's background survey, child temperament survey, anthropometric measurements and hair samples. Food patterns were determined using prin- cipal component analysis. The hair cortisol content was measured from four centimeter hair samples using a chemiluminescence immunoassay. Correlation analysis and one-way analysis of variance were used to study if food pat- tern scores, hair cortisol content and background variables were associated with each other, as well as to examine whether the food pattern scores or cortisol levels differed by background variables. High cortisol levels were used to ex- plain low scores for the Health-conscious food pattern in a logistic regression analysis. Results: The average hair cortisol concentration among participants was 41.7 pg / mg (95% CI: 35.5–47.9 pg / mg) ranging from 0.24 to 879.6 pg / mg. The food patterns Sweet and salty treats, Health-conscious and Sandwich snacking were dis- tinguished from the food consumption data. Differences in background variables were observed for both main variables. For example, the age of the child was inversely associated to the cortisol content of the hair (r = -0.16, p < 0.001) and the concentration was higher in boys than in girls (p < 0.001). The children of parents with high education degrees had higher scores from the Health-conscious pattern than the children of parents with not more than vocational school or high-school level education (p <0.001) or a bachelor's degree (p < 0.01). Hair cortisol content was negatively linked to the Health-conscious pattern score (r = -0,086, p < 0.05), and a high concentration increased the odds of a low Health-conscious pattern score (OR = 4.1 [95% CI: 1.9-9 0] p < 0.001). Hair cortisol content did not significantly correlate with the other two dietary patterns. Conclusions: This study supports the link between long-term stress and lower-quality diet, as it shows that elevated hair cortisol levels and less health-conscious diets are connected in children. The results are not generalizable outside the sample, but give reason to further investigate the relationship between long-term stress and the development of chil- dren’s eating habits and health.
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(2015)Background: Obesity is increasing rapidly all over the world. Obesity is becoming more common even in very young children. It has been estimated that globally approximately twenty percent of children have problems with their weight. Studies that have examined the association between obesity and nutrition have typically been focused to single nutrients or food groups. The knowledge from dietary pattern analysis considers also the synergistic effect between different components in foods, thus giving more information about food behaviour and the effect of the whole diet. Childhood and youth are critical time in shaping food choices and food habits learned at a young age often follow to adulthood. It is important to recognize differences in food consumption between obese and normal weight children and adolescents. Analysing dietary patterns gives information about the whole diet and makes it possible to identify harmful eating habits. Goals: The purpose of this study was to identify differences in the diets of normal weight and obese Finnish adolescents. The main goal was to determine if the dietary patterns between obese and normal weight adolescents differ and to determine if the dietary patterns are related to obesity. The research also studied the correlation of lifestyle and socioeconomic factors to obesity and to dietary patterns. Subjects and methods: The subjects consist of two different groups; patients, who had been diagnosed with severe obesity before the age of seven (n=68) and controls whose weight had been normal in childhood (n=73). Subjects were 15- to 25-year old in the time of the study. The study design is a comparative study in a cross-sectional design. Subjects filled a research form that asked information about socioeconomic and lifestyle factors from subjects and their parents. A food frequency questionnaire was used to assess food consumption from the previous month. Principal component analysis was used to define major dietary patterns. Logistic regression and Spearman´s rank correlation (rs) was used to determine associations between dietary patterns and obesity. Associations between lifestyle and socioeconomic factors and obesity were assessed with Spearman´s rank correlation. Obesity was determined by using BMI classification, waist circumference and body fat percentage. Results: Two major dietary patterns were identified; health conscious pattern and snacking pattern. The dietary patterns between patients and controls differed in women, where controls more often followed the health conscious pattern (p=0,008). After adjusting for confounding factors, the health conscious pattern was inversely associated to overweight. Subjects who represented the highest tertile of the health conscious pattern had lower risk of overweight (OR=0,21, 95 % CI 0,06 - 0,76) and high body fat percentage (OR=0,16, 95 % CI 0,03 - 0,89) compared to subjects who represented the lowest tertile. The analysis was also done separately for men and women, but no association was found after adjusting for all confounding factors. A positive correlation was found between snacking pattern and BMI (rs=0,36, p=0,05) and waist circumference (rs=0,43, p=0,02) in men patients and a negative correlation was found between health conscious pattern and BMI in women patients (rs=-0,43, p=0,018). A positive correlation was found between patient BMI and mother´s BMI (rs=0,42, p=0,001) and waist circumference (rs=0,47, p<0,0001) and a negative correlation between patients BMI and mother´s education (rs=-0,34, p=0,02). Conclusions: The association between obesity and nutrition might be more complex in adolescents than in adults. A diet that includes fresh and cooked vegetables, fruits, berries, seeds, beans, fish, dairy products and whole grain products may be inversely associated to overweight and higher body fat percentage. A diet that includes lots of snacking products may be associated to obesity in men. In researches that study obesity in children or adolescents, results should be examined, if possible, separately for both sexes.
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(2020)Tekoälyä ja koneoppimista hyödynnetään yhä useammilla tieteen ja liike-elämän aloilla ja tekoälyteknologioiden kehittyessä niiden käyttämisestä tulee yhä helpompaa ja yleisempää. Koneoppimisessa käytettävissä malleissa on taustalla paljon erilaista matematiikkaa ja tilastotiedettä. Menetelmien syvällinen ymmärtäminen ja soveltaminen vaatii ymmärrystä taustalla olevista matemaattisista rajoitteista ja sovellusmahdollisuuksista. Tässä tutkielmassa tarkastellaan koneoppimisen matemaattista perustaa. Työ on jaettu kahteen osaan. Ensimmäisessä osassa esitellään muutamia koneoppimisessa tarvittavia matematiikan osa-alueita, joita tarvitaan koneoppimisessa: lineaarialgebran ja matriisilaskennan sekä todennäköisyyslaskennan perusteita. Tämä osa toimii johdantona tai kertausmateriaalina kyseisiin matematiikan osa-alueisiin. Työn toisessa osassa esitellään yleisesti koneoppimisen peruskäsitteitä ja muotoillaan koneoppimisprosessia matemaattisesti. Sitten käydään läpi kaksi koneoppimismenetelmää, lineaarinen regressioanalyysi ja pääkomponenttianalyysi (PCA). Molemmista menetelmistä esitetään perusperiaate, matemaattista taustaa ja käytännön esimerkkejä Python-ohjelmointikielellä. Tutkielma perustuu kirjallisuuskatsaukseen.
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(2010)Children's participation has been a subject in the international research since past ten years. This research has explored participation from the standpoint of the UN's Convention of the Rights of the Child and focused mainly on schoolchildren or on the working youth's chances in developing countries to have impact on their own lives (eg. Sinclair, 2004 and Thomas, 2002). In Finland there has been less research about the children's rights while the main focus has been on the customers of the child welfare system. This study examines children's participation in Helsinki metropolitan area via the views and the practices of the personnel of early childhood education. The adopted viewpoint is Shier's level model of participation (2001), in which the children's participation process is building in phases, is observed via the everyday actions of the kindergarten personnel. Attention has been paid on the special characteristics of the Finnish early childhood education. This study was part of VKK-Metro's research project. The inquiry in May 2010 was directed to all working teams in the kindergartens of the Helsinki metropolitan area. Of these 56.59 % (1116 teams) answered. The quantitative data analyzed by principal component analysis gave four principal components, from which three were named after Shier's participation model. The fourth component included variables about rules and power. The level model of participation fit well to assess early childhood education in the Helsinki metropolitan area. The professionalism of the personnel became emphasized in the area of everyday interactions between the personnel and the children. Important aspects of the children's participation are to become heard, to get support in the play and in interaction and to be able to share both power and responsibility with personnel of the early childhood education.
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(2018)Study research how finnish farmers react to risk. Outcome is that finnish farmers are in average risk averse, and they weight lower probabilities more than high. Questionnaire was sent to 5 000 farmers, which 820 farmers sent their answer. Questionnaire included questions related to principal component analysis to confirm reliability. After analysis there were to principal components, which were compared in regression analysis with risk parameters alfa (value function parameter) and gamma (weighting function) with farmer's background information. Two principal components were not significant when alfa or gamma was dependent variable. Production sector was significant variable when weighting function parameter gamma acted as dependent variable. Age, amount of field owned or farms location did not have any meaning in attitudes towards risk. Study research how finnish farmers react to risk. Outcome is that finnish farmers are in average risk averse, and they weight lower probabilities more than high. Questionnaire was sent to 5 000 farmers, which 820 farmers sent their answer. Questionnaire included questions related to principal component analysis to confirm reliability. After analysis there were to principal components, which were compared in regression analysis with risk parameters alfa (value function parameter) and gamma (weighting function) with farmer's background information. Two principal components were not significant when alfa or gamma was dependent variable. Production sector was significant variable when weighting function parameter gamma acted as dependent variable. Age, amount of field owned or farms location did not have any meaning in attitudes towards risk.
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(2019)The Great Cormorant (Phalacrocorax carbo) is among the most recent additions to the Finnish avifauna: the current breeding population dates back to 1996. Historical and archeological data clearly demonstrate that the 20th century breeding range expansion of the species in the Baltic region is a re-colonisation event. The two subspecies of Cormorant in Europe are the nominate subspecies P. carbo carbo and the continental subspecies P. c. sinensis. The Cormorants currently breeding in Finland belong to the subspecies sinensis. P. c. carbo lives on the coasts of the North Sea and North Atlantic and visit Finland only during migration. However, osteological evidence suggests that carbo was prevalent subspecies in the Baltic area during prehistoric times, only to disappear in the Late Middle Age (by circa 1500 AD). The subspecies of the Cormorant differ in average size and weight, the details of the plumage and the angle of the gular pouch. P. c. carbo is on average larger than sinensis. However, males are larger than females in both subspecies. The subspecies differ in their ecological characteristics, e.g. preferred prey, breeding sites and migratory behaviour. However, only bones remain from the prehistoric Baltic Cormorants and therefore, soft tissues or behavioural characteristics cannot be used for their identification. The known osteological measurements of the subspecies overlap, and it has previously been possible to distinguish only the two extremes, large P. c. carbo males and small P. c. sinensis females. Here, I looked into features that would enable distinguishing of the skeletons of all the specimens of both subspecies. The primary material of my Master’s thesis consists of 65 specimens representing birds of both subspecies and sexes. The material has been collected from the Baltic basin and the western Gulf of Bothnia in Sweden and the Åland islands in Finland. In addition, I examined 11 specimens of the subspecies carbo from the collections of the Swedish Museum of Natural History (Naturhistoriska riksmuseet). I focused on the most diagnostic elements of the skeleton: skull, sternum and the large bones of the limbs. Moreover, I examined bones that may be associated with ecological differences between the subspecies, such as the sclerotic ring, the os nuchale, and the length of the distalmost phalanx bone of the opposable hallux toe. I wanted to find out if there are osteological differences between the males and females or the two subspecies. The statistical method used for testing the hypotheses and examining subspecific averages was the analysis of variance (ANOVA). The measurements were also analysed with Principal Component Analysis to investigate the proportional differences. The bones of the two subspecies differed in particular in the length of the forearm bones. Reliable discriminating features also included the depth of the bill and the measurements of leg bones. These are subspecific adaptations to their preferred habitats, prey, nesting sites and migratory behaviour. The relatively short wings of P. c. carbo make it an excellent diver, but a less efficient flyer. This subspecies migrates shorter distances, and is able to overwinter relatively far up in the north. In contrast, P. c. sinensis is able to fly with greater speed and efficiency during migration to avoid adverse conditions. The depth of the bill is an important factor determining the snapping power of the bill, which makes P. c. carbo better suited for handling big or powerful prey. The contemporary Baltic Sea is warmer and less marine than during earlier periods. The current brackish environment seems to favor the subspecies sinensis over carbo, although human persecution may also have had an effect on the previous demise of subspecies carbo. My results support the view that the subspecies of the Great Cormorant are clearly distinct morphologically. My result also suggest that skeletal research is an underutilised method in bird taxonomy, and studying the proportions of bones helps to perceive ecological and biological differences between bird subspecies.
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(2019)Tausta ja tavoitteet. Aikaisempi tutkimus on osoittanut videopelien vaikuttavan pelaajaan positiivisilla tavoilla, esimerkiksi kehittämällä pelaajan kognitiivisia kykyjä ja oppimistuloksia. Pelissä kehittymisen tutkimus edistää pelien positiivisten vaikutusten maksimointia niin kaupallisissa kuin opetus- ja hyötypeleissäkin. PIFF2¬¬-kehys on pelikokemuksen määrittelyn malli, johon pohjautuvilla kyselyillä voidaan mitata pelikokemuksen itsenäisiä osa-alueita ja täten pelikokemusta toistomittauksissa. Tämän tutkimuksen tavoitteena oli selvittää pelikokemuksen yhteyttä pelissä kehittymiseen. Pyrkimyksenä oli saada selville, mitkä pelikokemuksen tekijät ovat yhteydessä pelissä kehittymiseen sekä muodostaa hypoteeseja jatkotutkimukselle. Menetelmät. Tutkimuksen data saatiin yhdeksältä koehenkilöltä, jotka pelasivat tutkimusta varten kehitettyä peliä kotioloissaan kahdeksan viikon ajan. Peli yhdistää aiemmin muissa tutkimuksissa käytettyjen kaupallisten pelien ominaisuuksia. Pelaajilta kerättiin dataa heidän suoriutumisestaan pelissä toiminta-, strategia- sekä pulmaelementeissä. Lisäksi koehenkilöiden tuli täyttää jokaisen pelin jälkeen PIFF2¬¬-kehykseen pohjautuva pelikokemuskysely, jolla mitattiin pelaajan pelikokemuksen piirteitä, kuten jatkamisen halua, läsnäolon tunnetta ja kontrollia. Pelisuoriutumisdatan analysoinnin helpottamiseksi tehtiin pääkomponenttianalyysi, jolla datan dimensioita saatiin vähennettyä. Pääkomponenttianalyysin tuloksena muodostettiin yksi pelitaitomuuttuja. Yhdistettyä pelitaitomuuttujaa käytettiin kokeen aikana arvioimaan pelaajien kehitystä, jota verrattiin pelikokemuskyselyn eri muuttujiin sekä näistä muodostettuun yhteiseen pelikokemusmuuttujaan. Tulokset ja johtopäätökset. Pelikokemuksen ja pelissä kehittymisen vertailu osoitti, että jatkamisen halulla oli yhteys pelissä kehittymiseen. Yhdistetty pelitaitomuuttuja toimi hyvin mittaamaan pelaajan kehitystä tutkimuksessa käytetyssä pelissä. Johtopäätöksenä pelikokemuksella ja pelissä kehittymisellä on yhteys. Tutkimus osoittaa myös tarpeen pelikokemuksen ja pelissä kehittymisen yhteyden jatkotutkimukselle ja esittää jatkotutkimukselle hypoteesiksi jatkamisen halun olevan yhteydessä pelissä kehittymiseen.
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(2020)Background: In middle-income countries, such as Kenya there are signs of a nutrition transition towards a Western diet. From the public health perspective, it is important to understand the sociodemographic factors behind the whole diet. The nutrition research should therefore focus on the big picture of the diet rather than on the single nutrients. Dietary patterns can be used to explore the whole diet. With data-based dietary patterns, it is possible to investigate which food items are used or disused together. Based on previous studies, the differences in dietary patterns might be explained by sociodemographic factors. However, there are only few studies examining the association between sociodemographic factors and children’s dietary patterns in middle-income countries. Aims: The aim of the study was to investigate what kind of dietary patterns can be recognized among Kenyan children living in Nairobi. Additionally, this study aimed to investigate the association between sociodemographic factors (gender, education, wealth and living area) and dietary patterns. Materials and methods: The data used in this study is from the cross-sectional study of KENFIN-EDURA project. The data was collected with a food frequency questionnaire and background forms. 160 participants were recruited and 149 (93 %) of them completed the questionnaire. The participants were 914-year-olds, of whom 52 % were girls and 48 % were boys. Participants lived in Nairobi, either in a low-income area called Kayole or in a middle-income area called Langata. The participants reported the consumption frequencies of 174 food items, of which 39 were left out from the analyses. The food items that no one or only one person used were left out from the analyses. Also, the food items for which a big variance on reporting was suspected, were left out. The remaining 135 food items were collapsed into 19 food groups. Dietary patterns were formed with principal component analysis, and factor scores for participants for each dietary pattern were calculated. A higher value for factor score indicates a higher correlation between participant’s diet and dietary pattern. The mean factor scores were investigated by t-test for area and gender, and by analysis of variance for parent’s education and household’s wealth. The associations between sociodemographic factors and dietary patterns were examined by linear regression analysis. Finally, the examination was done separately for both areas. Results: Three dietary patterns were recognized, and these explained 36 % of the total variance in food consumption of the study population. The recognized dietary patterns were named based on food items loading most strongly in the patterns. The patterns were labelled 1) snacks, fast food and meat, 2) dairy products and plant protein, and 3) traditional Kenyan. Snacks, fast food and meat and traditional Kenyan dietary patterns were associated to living in Langata. The children from wealthier families scored higher on the dairy products and plant protein dietary pattern. When analyses were done separately for both areas, the only statistically significant result was the positive association between snacks, fast food and meat dietary pattern and wealth in Langata. Conclusions: Three dietary patterns were recognized among Nairobian children and two of these were similar to the patterns recognized in previous studies. One of them included energy-dense foods and meat, and the other plant-based products and dairy products. Living area and wealth appeared to be the most important sociodemographic factors associated with children’s diet. Nevertheless, the association between sociodemographic factors and children’s dietary patterns should be investigated more in order to reduce sociodemographic differences in diets.
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(2022)The Arctic is facing a major turning point with climate change and the region's climate will experience a particularly sharp rise in temperature. Subarctic ponds are important habitats and shelters for many organisms in the area but are nevertheless poorly known compared to larger water bodies. Along with climate change, the importance of studying ponds becomes more important as they are the first to manifest a changing climate. Factors affecting the water properties of subarctic ponds include the characteristics of the catchment area, such as its location relative to the sea, altitude, bedrock, and soil. Of the climatic factors, the temperature in the summer months and the amount of precipitation are of great importance. The purpose of the thesis was to find out the factors influencing the water properties of ponds in the Kilpisjärvi region and how the water properties vary between ponds. Water samples were collected from 94 tundra ponds in and around Malla Strict Nature Reserve and in the areas around Ailakkavaara in August-September 2018 and 2019. The collected samples were later analyzed in the laboratory of the Department of Geosciences and Geography in University of Helsinki. The hydrochemical variables studied were metals dissolved in water, major ions, and total phosphorus and nitrogen. Variables describing catchment characteristics such as the Normalized Difference Vegetation Index (NDVI), TWI (Topographic Wetness Index) and climatic variables such as precipitation during the summer months and average temperature in July were collected from open spatial data sources. Based on the results of the principal component analysis (PCA), the chemical properties of pond waters vary slightly on average between Malla and Ailakkavaara, but there is more variation within the regions. The characteristics of the catchment areas and the climate clearly influenced the vegetation type surrounding the ponds, but these factors were not as strongly reflected in the characteristics of the pond waters. The absolute amounts of nutrients and water-dissolved metals are small, but the relative variation between ponds is substantial. Based on GAM-modeling, influence of groundwater (deuterium excess) was the single most significant factor influencing water quality, which was the explanatory variable for several water properties. The drier-than-average summer months in the study years emphasize the importance of runoff to water quality. Rainfall during the summer months, altitude, mean temperature in July, and amount of vegetation (NDVI) were the main factors influencing the subarctic ponds in the study. The increase in temperature caused by climate change will raise the temperature of pond waters and increased precipitation will increase the runoff of metals dissolved in ponds.
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Valon vaikutus korianterin (Coriandrum sativum) ja tillin (Anethum graveolens) flavoriyhdisteisiin (2023)Indoor gardening is continuously increasing among consumers. Consumers and greenhouse entrepreneurs are looking for ways to optimize growing conditions for their plants to produce high quality and good yield. So far, the effects of LED lights on the plant biomass production and on the composition of volatile aroma compounds have been investigated. However, the effects of different lights on the taste and odor of homegrown herbs is yet to be discovered. The aim of this study was to investigate how different light conditions would affect the composition of compounds that are mainly responsible for the specific flavor of selected model plants. The main goal was to investigate what type of volatile compounds could be obtained in plants grown under different light conditions. The second goal was to investigate how non-volatile saliva soluble compounds could be modified due to the different growing conditions. Coriander and dill were selected as model plants. Coriander is globally utilized herb while dill is one of the most used herbs in the Nordic countries. Due to their strong flavor, both of these herbs divide consumer opinions and therefore investigation of their flavor modification is important. Coriander and dill were grown in domestic smart gardens manufactured by Plantui Oy. Used light conditions included control, green and blue light. Control light composed of a combination of blue, green and red light. Light source was LED lights. The herbs were grown at +22 °C and at humidity of 56.5 %. Used nutrients were ready-made mixtures by Plantui Oy. The composition of artificial saliva was optimized with commercial coriander and dill for the investigation of flavor compounds. Coriander and dill samples were extracted with the developed artificial saliva after which the volatile compounds were analyzed by a combination of gas chromatography and mass spectrometry (GC-MS) and non-volatile compounds by a combination of liquid chromatography and mass spectrometry (LC-MS). Principal component analysis (PCA) was utilized to investigate the composition of volatile compounds while partial least squares-discriminant analysis (PLS-DA) was used to investigate the differences in the non-volatile compounds. Used light conditions altered the chemical composition of herb leaves. Also, light conditions had a visible effect on plant growth. For example, herbs grown in blue light germinated weakly and produced less biomass. The profile of volatile compounds in corianders grown under green and blue light differed from those grown under control light. For dill, the profiles differed only for the samples grown under blue light. Majority of the volatile compounds were components of the essential oils of herbs and compounds that enhance stress tolerance. When looking at saliva soluble non-volatile compounds, coriander grown under blue light was different from the one grown under control light while for dill a difference was observed both under blue and green light. Based on the results, special light recipes can be developed to modify the flavor of coriander and dill. Further research is still needed, especially on the effects of light conditions in plant cell signaling and thereby on the morphological changes in plants and as a consequence on their flavor compounds.
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(2022)Subarktisten lampien vesikemia on muuttunut nopeasti viime vuosikymmeninä ympäristössä tapahtuneiden voimakkaiden muutosten johdosta. Subarktisten alueiden vesistötutkimuksissa on oltu erityisesti kiinnostuneita valuma-alueen kasvillisuuden muutoksista ilmaston lämpenemisen seurauksena. Maankamaran osalta huomio on ollut kallioperän kemiallisessa koostumuksessa. Tämän lopputyön keskiössä oli valuma-alueen tekijöistä maaperä. Lopputyön tavoitteena oli tarkastella, kuinka hyvin maaperämuuttujat selittävät lampien vesikemiaa. Maaperän kemiallisia ominaisuuksia kuvasi ICP-massaspektrometrillä määritetyt maaperänäytteiden helposti liukenevien alkuaineiden pitoisuudet. Lisäksi hehkutushäviömenetelmällä (LOI) määritettiin maaperän orgaanisen aineksen määrä. Maaperän rakennetta tarkasteltiin valuma-alueen maalajin ja maanpeiteluokkien peittävyysprosenttien avulla ja pohjavesivaikutteisuudella. Pääkomponenttianalyysin (PCA) mukaan vesikemian muuttujat eivät vaihdelleet kovinkaan yhdenmukaisesti; liuenneiden ionien kokonaismäärä ja runsaina esiintyneiden ionien pitoisuudet olivat kohtalaisen yhdenmukaisesti vaihtelevia. Valuma-aluetta kuvaavat muuttujat eivät sen sijaan PCA-analyysin mukaan olleet yhdenmukaisesti vaihtelevia. Yleistetyssä lineaarisessa mallissa (GLM) vesikemiaa kuvaavista muuttujista rinnejyrkkyys, varvikkojen ja heinikkojen laajuus sekä pohjavesivaikutteisuus selittivät tilastollisesti merkitsevästi lammen veden kemiaa. Pohjavesivaikutteisuus, jota mitattiin haihtuneisuutta kuvaavalla D-excess-arvolla, selitti ainoana muuttujana laajasti veden kemiallista vaihtelua. Se selitti pH:n sekä Al:n, Mn:n, Fe:n, Si:n ja TP:n vaihtelua. Yleisesti GLM-mallit olivat kuitenkin selitysvoimaltaan heikkoja. Ainoastaan veden Al:n ja Si:n pitoisuuksia selittävät mallit olivat selitysasteiltaan kohtalaisia. Tässä lopputyössä tutkittiin lisäksi sedimenttikivistä koostuvan Mallatunturien ja magmakivistä koostuvan Ailakkavaaran alueiden eroa lampien vesikemioissa. Samankaltaisuusanalyysissä (ANOSIM) löydettiin pieni ero alueiden välillä vesikemiassa. Maaperäominaisuuksien välillä ANOSIM-testissä löytyi myös heikko eroavaisuus alueiden välillä. Maaperissä oli yleisesti valuma-alueiden sisällä suurta vaihtelua, sillä maaperän alkuainepitoisuudet vaihtelivat merkittävästi eri puolilla lampea. Yleisesti tilastonanalyysien tulokset viittasivat siihen, että maaperä on tärkeä vesikemiaan vaikuttava tekijä valunnan tapahtuessa pohjavesikerroksen kautta. Lisäksi maaperän mineraaliaineksen koostumus selittää analyysin mukaan jonkin verran lampien vesikemian vaihtelua.
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(2021)Extracellular vesicles (EVs) are nano-sized lipid bilayer-delimited particles, released by cells. They take part in intercellular communication by their molecular composition and are part of both physiological and pathophysiological functions. EVs can be extracted from bodily fluids, and they are particularly abundant in blood. The purpose of this thesis was to evaluate the use of Raman spectroscopy in the characterization of EVs. Raman spectroscopy is an analysis method based on the interaction of light and matter, and the inelastic scattering of light, and it is used to get information on the biochemical composition of a substance. Principal component analysis (PCA) was used to investigate if Raman spectroscopy could differentiate two different platelet-derived EV samples, a red blood cell-derived EV-sample and a red blood cell-derived reference material. Evaluation of the characterization also included a stability study of these samples, where it was examined if any temperature dependent changes occurred that could be detected by Raman spectroscopy. Additionally, the applicability of Raman spectroscopy for lipoprotein contamination detection was evaluated by examining if purification of an EV sample decreased the intensity of carotenoid peaks typical for lipoprotein spectra. Raman spectroscopy was able to differentiate all three EV samples and the red blood cell-derived reference material from each other. The most clear differences were found between red blood cell and platelet-derived samples, due to for example the characteristic haemoglobin peaks of red blood cell-derived samples. Differences were also found between the two platelet EV samples, which were thought to implicate difference in protein compositions. The characterization of red blood cell-derived samples proved to be difficult because haemoglobin contained in the samples covered most of the other signal from the samples. Stability studies implicated that during fridge storage the carotenoid peak intensity of platelet-derived EV samples decreases due to the degradation of carotenoids. In the red blood cell-derived samples, no differences assignable to changes in some specific components of the samples were observed. Contamination studies suggested the intensity of the carotenoid peaks may increase due to purification of the sample. This was counter to the assumption and may suggest the carotenoids of the EV samples are not from lipoprotein contamination, but part of the EV composition. In conclusion, Raman spectroscopy proved to be a promising method for characterization and identification of different EV samples.
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(2020)A population is said to be genetically structured when it can be divided into subpopulations based on genetic differences between the individuals. As in case of Finland for example, the population has been shown to consist of genetic subpopulations that correspond strongly to geographical subgroups. Such information may be interesting when seeking answers to questions related to the settlement and migration history of some population. Information about genetic population structure is also required for example in studies looking for associations between genetic variants and some inheritable disease to ensure that the groups with and without diagnosis of the disease resemble each other genetically except for the genetic variants causing the disease. In my thesis, I have compared how two different mathematical models, principal component analysis (PCA) and generative topographic mapping (GTM), visualize ancestry and identify genetic structure in Finnish population. PCA was introduced already in 1901, and nowadays it is a standard tool in identifying genetic structure and visualizing ancestry. GTM instead was published relatively recently, in 1998, and has not yet been applied in population structure studies as widely than PCA. Both PCA and GTM transform high-dimensional data to a low-dimensional, interpretable representation where relationships between observations of the data are summarized. In case of data containing genetic heterogeneity between individuals, this representation gives a visual approximation of the genetic structure of the population. However, Hèlèna A. Gaspar and Gerome Breen found in 2018 that GTM is able to classify ancestry of populations from around the world more accurately than PCA: the differences recognized by PCA were mainly between geographically most distant populations, while GTM detected also more their subpopulations. My aims in the thesis were to examine whether applying the methods for Finnish data would give similar results, and to give thorough presentations of the mathematical background for both the methods. I also discuss how the results fit into what is currently known about the genetic population structure in Finland. The study results are based on data from the FINRISK Study Survey collected by the National Institute for Health and Welfare (THL) in 1992-2012 and include 35 499 samples. After performing quality control on the data, I analysed the data with SmartPCA program and ugtm Python package implementing PCA and GTM, respectively. The final results have been presented for such 2010 individuals that participated the FINRISK Study Survey in 1997 and whose both parents were born close to each other. I have assigned the individuals into distinct geographical subgroups according to the birthplaces of their mothers to find out whether PCA and GTM identify individuals having a similar geographical origin to be genetically close to each other. Based on the results, the genetic structure in Finland is clearly geographically clustered, which fits into what is known from earlier studies. The results were also similar to those observed by Gaspar and Breen: Both the methods identified the genetic substructure but GTM was able to recognize more subtle differences in ancestry between the geographically defined subgroups than PCA. For example, GTM discovered the group corresponding to the region of Northern Ostrobothnia to consist of four smaller separate subgroups, while PCA interpreted the individuals with a Northern Ostrobothnian origin to be genetically rather homogeneous. Locating these individuals on the map of Finland according to the birthplaces of their mothers reveals that they also make four geographical clusters corresponding to the genetic subpopulations detected by GTM. As a final conclusion I state that GTM is a noteworthy alternative to PCA for studying genetic population structure, especially when it comes to identifying substructures from a population that PCA may interpret to be genetically homogeneous. I also note that the reason why GTM generally seems to be capable of more fine-grained clustering than PCA, is probably that PCA as a linear model may cause more bias to the results than GTM which accounts for also non-linear relationships when transforming the data into a more interpretable form.
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