Wood biochemicals for the protection of health. Focus on hemicellulose, stilbenoids and lignans

Trees produce an enormous amount of compounds that are still scantly utilized.However, the results obtained from structurally similar biochemicals suggest that wood-derived compounds could be used for the protection of health in various applications. Polyphenols, for instance, could be extracted from wood in high quantities. Similar polyphenols to those in wood include resveratrol, found in grapes, and secoisolariciresinol, present in flaxseeds. Their consumption has been inversely associated with the incidence of various diseases, especially certain cancers and obesity-related disorders. The aim of this study was to determine the health-promoting effects of woodderived biochemicals. The effect of spruce hemicellulose on the growth of probiotic intestinal bacteria was studied. The results suggest that the bifidobacteria and lactobacilli can utilize hemicellulose and thus it has potential as a prebiotic compound. In particular, the efficacy of pine polyphenols to inhibit the growth of prostate cancer was our main interest. It was found that stilbenoids and lignans inhibited the proliferation of various cancer cells, and reduced the growth of prostate cancer xenografts in mice. The polyphenol rich pine knot extract was well tolerated in diet and extract-derived polyphenols were rapidly absorbed after intake. Furthermore, we determined the effect of the dietary pine knot extract on the weight gain and the expression of aromatase gene in reporter mouse expressing the promoter region of a human aromatase gene. It was found that dietary pine knot extract alleviated the obesity-induced inflammation in adipose tissue and downregulated the expression of a human aromatase gene. Taken together, several components of spruce and pine may have a future role as health-promoting compounds.

Automatic image-based identification of Saimaa ringed seals

The Saimaa ringed seal is one of the most endangered seals in the world. It is a symbol of Lake Saimaa and a lot of effort have been applied to save it. Traditional methods of seal monitoring include capturing the animals and installing sensors on their bodies. These invasive methods for identifying can be painful and affect the behavior of the animals. Automatic identification of seals using computer vision provides a more humane method for the monitoring. This Master's thesis focuses on automatic image-based identification of the Saimaa ringed seals. This consists of detection and segmentation of a seal in an image, analysis of its ring patterns, and identification of the detected seal based on the features of the ring patterns. The proposed algorithm is evaluated with a dataset of 131 individual seals. Based on the experiments with 363 images, 81\% of the images were successfully segmented automatically. Furthermore, a new approach for interactive identification of Saimaa ringed seals is proposed. The results of this research are a starting point for future research in the topic of seal photo-identification.

Automatic recognition of fish from video sequences

The problem of automatic recognition of the fish from the video sequences is discussed in this Master’s Thesis. This is a very urgent issue for many organizations engaged in fish farming in Finland and Russia because the process of automation control and counting of individual species is turning point in the industry. The difficulties and the specific features of the problem have been identified in order to find a solution and propose some recommendations for the components of the automated fish recognition system. Methods such as background subtraction, Kalman filtering and Viola-Jones method were implemented during this work for detection, tracking and estimation of fish parameters. Both the results of the experiments and the choice of the appropriate methods strongly depend on the quality and the type of a video which is used as an input data. Practical experiments have demonstrated that not all methods can produce good results for real data, whereas on synthetic data they operate satisfactorily.

Method for automatic detection of wheezing in lung sounds

The present report describes the development of a technique for automatic wheezing recognition in digitally recorded lung sounds. This method is based on the extraction and processing of spectral information from the respiratory cycle and the use of these data for user feedback and automatic recognition. The respiratory cycle is first pre-processed, in order to normalize its spectral information, and its spectrogram is then computed. After this procedure, the spectrogram image is processed by a two-dimensional convolution filter and a half-threshold in order to increase the contrast and isolate its highest amplitude components, respectively. Thus, in order to generate more compressed data to automatic recognition, the spectral projection from the processed spectrogram is computed and stored as an array. The higher magnitude values of the array and its respective spectral values are then located and used as inputs to a multi-layer perceptron artificial neural network, which results an automatic indication about the presence of wheezes. For validation of the methodology, lung sounds recorded from three different repositories were used. The results show that the proposed technique achieves 84.82% accuracy in the detection of wheezing for an isolated respiratory cycle and 92.86% accuracy for the detection of wheezes when detection is carried out using groups of respiratory cycles obtained from the same person. Also, the system presents the original recorded sound and the post-processed spectrogram image for the user to draw his own conclusions from the data.

Manual and semi-automatic quantification of in vivo ¹H-MRS data for the classification of human primary brain tumors

In vivo proton magnetic resonance spectroscopy (¹H-MRS) is a technique capable of assessing biochemical content and pathways in normal and pathological tissue. In the brain, ¹H-MRS complements the information given by magnetic resonance images. The main goal of the present study was to assess the accuracy of ¹H-MRS for the classification of brain tumors in a pilot study comparing results obtained by manual and semi-automatic quantification of metabolites. In vivo single-voxel ¹H-MRS was performed in 24 control subjects and 26 patients with brain neoplasms that included meningiomas, high-grade neuroglial tumors and pilocytic astrocytomas. Seven metabolite groups (lactate, lipids, N-acetyl-aspartate, glutamate and glutamine group, total creatine, total choline, myo-inositol) were evaluated in all spectra by two methods: a manual one consisting of integration of manually defined peak areas, and the advanced method for accurate, robust and efficient spectral fitting (AMARES), a semi-automatic quantification method implemented in the jMRUI software. Statistical methods included discriminant analysis and the leave-one-out cross-validation method. Both manual and semi-automatic analyses detected differences in metabolite content between tumor groups and controls (P < 0.005). The classification accuracy obtained with the manual method was 75% for high-grade neuroglial tumors, 55% for meningiomas and 56% for pilocytic astrocytomas, while for the semi-automatic method it was 78, 70, and 98%, respectively. Both methods classified all control subjects correctly. The study demonstrated that ¹H-MRS accurately differentiated normal from tumoral brain tissue and confirmed the superiority of the semi-automatic quantification method.

Semi-automatic measurement of visual verticality perception in humans reveals a new category of visual field dependency

Previous assessment of verticality by means of rod and rod and frame tests indicated that human subjects can be more (field dependent) or less (field independent) influenced by a frame placed around a tilted rod. In the present study we propose a new approach to these tests. The judgment of visual verticality (rod test) was evaluated in 50 young subjects (28 males, ranging in age from 20 to 27 years) by randomly projecting a luminous rod tilted between -18 and +18° (negative values indicating left tilts) onto a tangent screen. In the rod and frame test the rod was displayed within a luminous fixed frame tilted at +18 or -18°. Subjects were instructed to verbally indicate the rod’s inclination direction (forced choice). Visual dependency was estimated by means of a Visual Index calculated from rod and rod and frame test values. Based on this index, volunteers were classified as field dependent, intermediate and field independent. A fourth category was created within the field-independent subjects for whom the amount of correct guesses in the rod and frame test exceeded that of the rod test, thus indicating improved performance when a surrounding frame was present. In conclusion, the combined use of subjective visual vertical and the rod and frame test provides a specific and reliable form of evaluation of verticality in healthy subjects and might be of use to probe changes in brain function after central or peripheral lesions.

Intensive chemotherapy as salvage treatment for solid tumors: focus on germ cell cancer

Germ cell tumors present contrasting biological and molecular features compared to many solid tumors, which may partially explain their unusual sensitivity to chemotherapy. Reduced DNA repair capacity and enhanced induction of apoptosis appear to be key factors in the sensitivity of germ cell tumors to cisplatin. Despite substantial cure rates, some patients relapse and subsequently die of their disease. Intensive doses of chemotherapy are used to counter mechanisms of drug resistance. So far, high-dose chemotherapy with hematopoietic stem cell support for solid tumors is used only in the setting of testicular germ cell tumors. In that indication, high-dose chemotherapy is given as the first or late salvage treatment for patients with either relapsed or progressive tumors after initial conventional salvage chemotherapy. High-dose chemotherapy is usually given as two or three sequential cycles using carboplatin and etoposide with or without ifosfamide. The administration of intensive therapy carries significant side effects and can only be efficiently and safely conducted in specialized referral centers to assure optimum patient care outcomes. In breast and ovarian cancer, most studies have demonstrated improvement in progression-free survival (PFS), but overall survival remained unchanged. Therefore, most of these approaches have been dropped. In germ cell tumors, clinical trials are currently investigating novel therapeutic combinations and active treatments. In particular, the integration of targeted therapies constitutes an important area of research for patients with a poor prognosis.

Averting the legacy of kidney disease - focus on childhood

World Kidney Day 2016 focuses on kidney disease in childhood and the antecedents of adult kidney disease that can begin in earliest childhood. Chronic kidney disease (CKD) in childhood differs from that in adults, in that the largest diagnostic group among children includes congenital anomalies and inherited disorders, with glomerulopathies and kidney disease as a consequence of diabetes being relatively uncommon. In addition, many children with acute kidney injury will ultimately develop sequelae that may lead to hypertension and CKD in later childhood or in adult life. Children born early or who are small-for-date newborns have relatively increased risk for the development of CKD later in life. Persons with a high-risk birth and early childhood history should be watched closely in order to help detect early signs of kidney disease in time to provide effective prevention or treatment. Successful therapy is feasible for advanced CKD in childhood; there is evidence that children fare better than adults, if they receive kidney replacement therapy including dialysis and transplantation, although only a minority of children may require this ultimate intervention. Because there are disparities in access to care, effort is needed so that children with kidney disease, wherever they live, may be treated effectively, irrespective of their geographic or economic circumstances. Our hope is that the World Kidney Day will inform the general public, policy makers and caregivers about the needs and possibilities surrounding kidney disease in childhood.

NEW BUSINESS MODELS – Sustainability as a main focus

A business model is a structure frame of an organization that can bring significant benefits and competitive advantage when structured properly. The aim of this paper was to observe and describe development of business models’ and identify factors and elements of a business model that are in a key role from the perspective of an organizational sustainability. One is striving to bring out in this thesis how should truly sustainable business model look like and what are main characteristics of it. Additionally, some recommendations that could be helpful in order to build sustainable and balanced business model in a company are presented in this work. The meaning was to make theoretical and in some extent practical acquaintance with such new business models as open business model and sustainable business model. Long-term sustainability achievement in a company was in a centric role and used as a main criteria when constructing sustainable business model structure. The main research question in this study aims to answer: What a firm should consider in order to develop profitable and sustainable business model? This study is qualitative in nature and it was conducted using content analyze as a main method of this research. The perspective of the target data in this study is an outlook of its producers of how sustainability is reached in an organization throw business model and which practices are important and has to be taken into account. The material was gathered mainly from secondary sources and the theoretical framework was outright built based on secondary data. The secondary data that have been mostly dissertations, academic writings, cases, academic journals and academic books have been analyzed from the point of view of sustainability perspective. As a result it became evident that a structure of a business model and its implementation along with a strategy is often what leads companies to success. However, for the most part, overall business environment decides and delimits how the most optimal business model should be constructed in order to be effective and sustainable. The evaluation of key factors and elements in business model leading organization to sustainability should be examined throw triple bottom line perspective, where key dimensions are environmental, social and economic. It was concluded that dimensions should be evaluated as equal in order to attain total long lasting sustainability, contradicting traditional perspective in business where profit production is seen as only main goal of a business.

Players of Th-cell differentiation and immune dysregulation – focus on GIMAP family genes

The balance of T helper (Th) cell differentiation is the fundamental process that ensures that the immune system functions correctly and effectively. The differentiation is a fine tuned event, the outcome of which is driven by activation of the T-cell in response to recognition of the specific antigen presented. The co-stimulatory signals from the surrounding cytokine milieu help to determine the outcome. An impairment in the differentiation processes may lead to an imbalance in immune responses and lead to immune-mediated pathologies. An over-representation of Th1 type cytokine producing cells leads to tissue-specific inflammation and autoimmunity, and excessive Th2 response is causative for atopy, asthma and allergy. The major factors of Th-cell differentiation and in the related disease mechanisms have been extensively studied, but the fine tuning of these processes by the other factors cannot be discarded. In the work presented in this thesis, the association of T-cell receptor costimulatory molecules CTLA4 and ICOS with autoimmune diabetes were studied. The underlying aspect of the study was to explore the polymorphism in these genes with the different disease rates observed in two geographically close populations. The main focus of this thesis was set on a GTPase of the immunity associated protein (GIMAP) family of small GTPases. GIMAP genes and proteins are differentially regulated during human Th-cell differentiation and have been linked to immune-mediated disorders. GIMAP4 is believed to contribute to the immunological balance via its role in T-cell survival. To elucidate the function of GIMAP4 and GIMAP5 and their role in human immunity, a study combining genetic association in different immunological diseases and complementing functional analyses was conducted. The study revealed interesting connections with the high susceptibility risk genes. In addition, the role of GIMAP4 during Th1-cell differentiation was investigated. A novel function of GIMAP4 in relation to cytokine secretion was discovered. Further assessment of GIMAP4 and GIMAP5 effect for the transcriptomic profile of differentiating Th1-cells revealed new insights for GIMAP4 and GIMAP5 function.

The Brazilian consumer's understanding and perceptions of organic vegetables: a Focus Group approach

Focus Group is a tool which generates, through interview sessions with a small number of participants, preliminary data to be used in subsequent quantitative stages. Many consumer studies use qualitative research with the aim of obtaining information and opinions on a specific product or situation. The objective of the present study was to obtain knowledge on the opinion, understanding and perception of the Brazilian consumer with respect to vegetables, focusing on organic products, using Focus Group Sessions. Four Focus Group Sessions were held with men and women in different environments, following a previously elaborated interview guide. In this study, it was observed that the consumers demonstrated being interested in having a healthy diet, based on fruit, vegetables and natural products. However, only a few declared consuming organic foods. Some participants did not know what the term organic meant, and most of them think that organic products are still very expensive, are not easily available in the supermarkets, do not have a good appearance, mainly in terms of size and packaging, and their certification is not always trustworthy. Almost all participants stated that they read package labels and among the items most observed were best-before date, nutritional information, production system and price. This study has identified important vegetable attributes perceived by the consumer, favouring the planning of a subsequent quantitative research. The results suggest that more information on the benefits of organic agriculture has to be passed on to consumers in order to contribute to a higher consumption of such products.

Sentence Compression with Supervised Machine Learning

The subject of the thesis is automatic sentence compression with machine learning, so that the compressed sentences remain both grammatical and retain their essential meaning. There are multiple possible uses for the compression of natural language sentences. In this thesis the focus is generation of television program subtitles, which often are compressed version of the original script of the program. The main part of the thesis consists of machine learning experiments for automatic sentence compression using different approaches to the problem. The machine learning methods used for this work are linear-chain conditional random fields and support vector machines. Also we take a look which automatic text analysis methods provide useful features for the task. The data used for machine learning is supplied by Lingsoft Inc. and consists of subtitles in both compressed an uncompressed form. The models are compared to a baseline system and comparisons are made both automatically and also using human evaluation, because of the potentially subjective nature of the output. The best result is achieved using a CRF - sequence classification using a rich feature set. All text analysis methods help classification and most useful method is morphological analysis. Tutkielman aihe on suomenkielisten lauseiden automaattinen tiivistäminen koneellisesti, niin että lyhennetyt lauseet säilyttävät olennaisen informaationsa ja pysyvät kieliopillisina. Luonnollisen kielen lauseiden tiivistämiselle on monta käyttötarkoitusta, mutta tässä tutkielmassa aihetta lähestytään television ohjelmien tekstittämisen kautta, johon käytännössä kuuluu alkuperäisen tekstin lyhentäminen televisioruudulle paremmin sopivaksi. Tutkielmassa kokeillaan erilaisia koneoppimismenetelmiä tekstin automaatiseen lyhentämiseen ja tarkastellaan miten hyvin erilaiset luonnollisen kielen analyysimenetelmät tuottavat informaatiota, joka auttaa näitä menetelmiä lyhentämään lauseita. Lisäksi tarkastellaan minkälainen lähestymistapa tuottaa parhaan lopputuloksen. Käytetyt koneoppimismenetelmät ovat tukivektorikone ja lineaarisen sekvenssin mallinen CRF. Koneoppimisen tukena käytetään tekstityksiä niiden eri käsittelyvaiheissa, jotka on saatu Lingsoft OY:ltä. Luotuja malleja vertaillaan Lopulta mallien lopputuloksia evaluoidaan automaattisesti ja koska teksti lopputuksena on jossain määrin subjektiivinen myös ihmisarviointiin perustuen. Vertailukohtana toimii kirjallisuudesta poimittu menetelmä. Tutkielman tuloksena paras lopputulos saadaan aikaan käyttäen CRF sekvenssi-luokittelijaa laajalla piirrejoukolla. Kaikki kokeillut teksin analyysimenetelmät auttavat luokittelussa, joista tärkeimmän panoksen antaa morfologinen analyysi.