Oral health and menopause

Hormone therapy (HT) is widely used to relieve climacteric symptoms in order to increase the well-being of the women. The benefits as well as side-effects of HT are well documented. The principal menopausal oral symptoms are dry mouth (DM) and sensation of painful mouth (PM) due to various causes. Profile studies have indicated that HT users are more health-conscious than non-users. The hypothesis of the present study was that there are differences in oral health between woman using HT and those not using HT. A questionnaire study of 3173 women of menopausal age (50-58 years old) was done to investigate the prevalence of self-assessed sensations of PM and DM. Of those women participating in the questionnaire study, a random sample of 400 (200 using, 200 not using HT) was examined clinically in a 2-year follow-up study. Oral status was recorded according to WHO methods using DMFT and CPITN indices. The saliva flows were measured, salivary total protein, albumin and immunoglobulin concentrations and selected periodontal micro-organisms were analysed, and panoramic tomography of the jaws was taken. The patients filled in a structured questionnaire on their systemic health, medication and health habits. According to our questionnaire study there was no significant difference in the occurrence of self- assessed PM or DM between the HT users and non-users. According to logistic regression analyses, climacteric complaints significantly correlated with the occurrence of PM (p=0.000) and DM (p=0.000) irrespective of the use of HT, indicating that PM and DM are associated with climacteric symptoms in general. There was no difference between the groups in DMFT index values at follow up. The number of filled teeth (FT) showed a significant (p<0.05) increase in the HT group at follow-up. Periodontitis was diagnosed in 79% of HT users at baseline and in 71% at the follow-up. The values for non-HT users were 80% vs. 76%, respectively (Ns.). The mean numbers of ≥ 6 mm deep periodontal pockets were 0.9 ± 1.7 at baseline vs. 1.1 ± 2.1 two years later in the HT group, and 1.0 ± 1.7 vs. 1.2 ± 1.9, respectively, in the non-HT group. In a large Finnish national health survey, the prevalence of peridontitis of women of this age group was lower, but the prevalence of severe periodontitis seemed to be higher than in our study. Salivary albumin, IgG and IgM concentrations decreased in the HT group during the 2-year follow up (p<0.05), possibly indicating an improvement in epithelial integrity. No difference was found in any other salivary parameters or in the prevalence of the periodontal bacteria between or within the groups. In conclusion, the present findings showed that 50 to 58 year old women living in Helsinki have fairly good oral and dental health. The occurrence of PM and DM seemed to be associated with climacteric symptoms in general, and the use of HT did not affect the oral symptoms studied.

Vaggvisor i Kvevlax : Språkliga strukturer och konstruktioner

Lullabies in Kvevlax. Linguistic structures and constructions. The study is a linguistic analysis of constructions that shape the texts used in lullabies in Kvevlax in Ostrobothnia in Finland. The empirical goal is to identify linguistic constructions in traditional lullabies that make use of the dialect of the region. The theoretical goal was to test the usability of Construction Grammar (CxG) in analyses of this type of material, and to further develop the formal description of Construction Grammar in such a way as to make it possible to analyze all kinds of linguistically complex texts. The material that I collected in the 1960s comprises approximately 600 lullabies and concomitant interviews with the singers on the use of lullabies. In 1991 I collected additional material in Kvevlax. The number of informants is close to 250. Supplementary material covering the Swedish-language regions in Finland was compiled from the archives of the Society of Swedish Literature in Finland. The first part of the study is mainly based on traditional grammar and gives general information about the language and the structures used in the lullabies. In the detailed study of the Kvevlax lullabies in the latter part of the study I use a version of Construction Grammar intended for the linguistic analysis of usage-based texts. The analysis focuses on the most salient constructions in the lullabies. The study shows that Construction Grammar as a method has more general applicability than traditional linguistic methods. The study identifies important constructions, including elements typical of this genre, that structure the text in different variants of the same lullabies. In addition, CxG made it possible to study pragmatic aspects of the interactional, cultural and contextual language that is used in communication with small children. The constructions found in lullabies are also used in language in general. In addition to being able to give detailed linguistic descriptions of the texts, Construction Grammar can also explain the multidimensionality of language and the variations in the texts. The use of CxG made it possible to show that variations are not random but follow prototypical linguistic patterns, constructions. Constructions are thus found to be linguistic resources with built-in variation potentials.

Scientific Journal Publishing – Yearly Volume and Open Access Availability

Introduction. We estimate the total yearly volume of peer-reviewed scientific journal articles published world-wide as well as the share of these articles available openly on the Web either directly or as copies in e-print repositories. Method. We rely on data from two commercial databases (ISI and Ulrich's Periodicals Directory) supplemented by sampling and Google searches. Analysis. A central issue is the finding that ISI-indexed journals publish far more articles per year (111) than non ISI-indexed journals (26), which means that the total figure we obtain is much lower than many earlier estimates. Our method of analysing the number of repository copies (green open access) differs from several earlier studies which have studied the number of copies in identified repositories, since we start from a random sample of articles and then test if copies can be found by a Web search engine. Results. We estimate that in 2006 the total number of articles published was approximately 1,350,000. Of this number 4.6% became immediately openly available and an additional 3.5% after an embargo period of, typically, one year. Furthermore, usable copies of 11.3% could be found in subject-specific or institutional repositories or on the home pages of the authors. Conclusions. We believe our results are the most reliable so far published and, therefore, should be useful in the on-going debate about Open Access among both academics and science policy makers. The method is replicable and also lends itself to longitudinal studies in the future.

Detecting Earnings Management Using Neural Networks

Detecting Earnings Management Using Neural Networks. Trying to balance between relevant and reliable accounting data, generally accepted accounting principles (GAAP) allow, to some extent, the company management to use their judgment and to make subjective assessments when preparing financial statements. The opportunistic use of the discretion in financial reporting is called earnings management. There have been a considerable number of suggestions of methods for detecting accrual based earnings management. A majority of these methods are based on linear regression. The problem with using linear regression is that a linear relationship between the dependent variable and the independent variables must be assumed. However, previous research has shown that the relationship between accruals and some of the explanatory variables, such as company performance, is non-linear. An alternative to linear regression, which can handle non-linear relationships, is neural networks. The type of neural network used in this study is the feed-forward back-propagation neural network. Three neural network-based models are compared with four commonly used linear regression-based earnings management detection models. All seven models are based on the earnings management detection model presented by Jones (1991). The performance of the models is assessed in three steps. First, a random data set of companies is used. Second, the discretionary accruals from the random data set are ranked according to six different variables. The discretionary accruals in the highest and lowest quartiles for these six variables are then compared. Third, a data set containing simulated earnings management is used. Both expense and revenue manipulation ranging between -5% and 5% of lagged total assets is simulated. Furthermore, two neural network-based models and two linear regression-based models are used with a data set containing financial statement data from 110 failed companies. Overall, the results show that the linear regression-based models, except for the model using a piecewise linear approach, produce biased estimates of discretionary accruals. The neural network-based model with the original Jones model variables and the neural network-based model augmented with ROA as an independent variable, however, perform well in all three steps. Especially in the second step, where the highest and lowest quartiles of ranked discretionary accruals are examined, the neural network-based model augmented with ROA as an independent variable outperforms the other models.

Markov random fields and spatial smoothing in improving of forest inventory estimates

Markov random fields (MRF) are popular in image processing applications to describe spatial dependencies between image units. Here, we take a look at the theory and the models of MRFs with an application to improve forest inventory estimates. Typically, autocorrelation between study units is a nuisance in statistical inference, but we take an advantage of the dependencies to smooth noisy measurements by borrowing information from the neighbouring units. We build a stochastic spatial model, which we estimate with a Markov chain Monte Carlo simulation method. The smooth values are validated against another data set increasing our confidence that the estimates are more accurate than the originals.

Integration of miRNA and mRNA expression with DNA copy number of Ewing sarcoma cell lines

Ewing sarcoma is an aggressive and poorly differentiated malignancy of bone and soft tissue. It primarily affects children, adolescents, and young adults, with a slight male predominance. It is characterized by a translocation between chromosomes 11 and 22 resulting in the EWSR1-FLI1fusion transcription factor. The aim of this study is to identify putative Ewing sarcoma target genes through an integrative analysis of three microarray data sets. Array comparative genomic hybridization is used to measure changes in DNA copy number, and analyzed to detect common chromosomal aberrations. mRNA and miRNA microarrays are used to measure expression of protein-coding and miRNA genes, and these results integrated with the copy number data. Chromosomal aberrations typically contain also bystanders in addition to the driving tumor suppressor and oncogenes, and integration with expression helps to identify the true targets. Correlation between expression of miRNAs and their predicted target mRNAs is also evaluated to assess the results of post-transcriptional miRNA regulation on mRNA levels. The highest frequencies of copy number gains were identified in chromosome 8, 1q, and X. Losses were most frequent in 9p21.3, which also showed an enrichment of copy number breakpoints relative to the rest of the genome. Copy number losses in 9p21.3 were found have a statistically significant effect on the expression of MTAP, but not on CDKN2A, which is a known tumor-suppressor in the same locus. MTAP was also down-regulated in the Ewing sarcoma cell lines compared to mesenchymal stem cells. Genes exhibiting elevated expression in association with copy number gains and up-regulation compared to the reference samples included DCAF7, ENO2, MTCP1, andSTK40. Differentially expressed miRNAs were detected by comparing Ewing sarcoma cell lines against mesenchymal stem cells. 21 up-regulated and 32 down-regulated miRNAs were identified, includingmiR-145, which has been previously linked to Ewing sarcoma. The EWSR1-FLI1 fusion gene represses miR-145, which in turn targets FLI1 forming a mutually repressive feedback loop. In addition higher expression linked to copy number gains and compared to mesenchymal stem cells, STK40 was also found to be a target of four different miRNAs that were all down-regulated in Ewing sarcoma cell lines compared to the reference samples. SLCO5A1 was identified as the only up-regulated gene within a frequently gained region in chromosome 8. This region was gained in over 90 % of the cell lines, and also with a higher frequency than the neighboring regions. In addition, SLCO5A1 was found to be a target of three miRNAs that were down-regulated compared to the mesenchymal stem cells.

Patterns in permuted binary matrices

Reorganizing a dataset so that its hidden structure can be observed is useful in any data analysis task. For example, detecting a regularity in a dataset helps us to interpret the data, compress the data, and explain the processes behind the data. We study datasets that come in the form of binary matrices (tables with 0s and 1s). Our goal is to develop automatic methods that bring out certain patterns by permuting the rows and columns. We concentrate on the following patterns in binary matrices: consecutive-ones (C1P), simultaneous consecutive-ones (SC1P), nestedness, k-nestedness, and bandedness. These patterns reflect specific types of interplay and variation between the rows and columns, such as continuity and hierarchies. Furthermore, their combinatorial properties are interlinked, which helps us to develop the theory of binary matrices and efficient algorithms. Indeed, we can detect all these patterns in a binary matrix efficiently, that is, in polynomial time in the size of the matrix. Since real-world datasets often contain noise and errors, we rarely witness perfect patterns. Therefore we also need to assess how far an input matrix is from a pattern: we count the number of flips (from 0s to 1s or vice versa) needed to bring out the perfect pattern in the matrix. Unfortunately, for most patterns it is an NP-complete problem to find the minimum distance to a matrix that has the perfect pattern, which means that the existence of a polynomial-time algorithm is unlikely. To find patterns in datasets with noise, we need methods that are noise-tolerant and work in practical time with large datasets. The theory of binary matrices gives rise to robust heuristics that have good performance with synthetic data and discover easily interpretable structures in real-world datasets: dialectical variation in the spoken Finnish language, division of European locations by the hierarchies found in mammal occurrences, and co-occuring groups in network data. In addition to determining the distance from a dataset to a pattern, we need to determine whether the pattern is significant or a mere occurrence of a random chance. To this end, we use significance testing: we deem a dataset significant if it appears exceptional when compared to datasets generated from a certain null hypothesis. After detecting a significant pattern in a dataset, it is up to domain experts to interpret the results in the terms of the application.

Genetic and epigenetic mechanisms of tumor predisposition in hereditary non-polyposis colorectal carcinoma and sporadic cancers

Individuals with inherited deficiency in DNA mismatch repair(MMR) (Lynch syndrome) LS are predisposed to different cancers in a non-random fashion. Endometrial cancer (EC) is the most common extracolonic malignancy in LS. LS represents the best characterized form of hereditary nonpolyposis colorectal carcinoma (HNPCC). Other forms of familial non-polyposis colon cancer exist, including familial colorectal cancer type X (FCCX). This syndrome resembles LS, but MMR gene defects are excluded and the predisposition genes are unknown so far. To address why different organs are differently susceptible to cancer development, we examined molecular similarities and differences in selected cancers whose frequency varies in LS individuals. Tumors that are common (colorectal, endometrial, gastric) and less common (brain, urological) in LS were characterized for MMR protein expression, microsatellite instability (MSI), and by altered DNA methylation. We also studied samples of histologically normal endometrium, endometrial hyperplasia,and cancer for molecular alterations to identify potential markers that could predict malignant transformation in LS and sporadic cases. Our results suggest that brain and kidney tumors follow a different pathway for cancer development than the most common LS related cancers.Our results suggest also that MMR defects are detectable in endometrial tissues from a proportion of LS mutation carriers prior to endometrial cancer development. Traditionally (complex) atypical hyperplasia has been considered critical for progression to malignancy. Our results suggest that complex hyperplasia without atypia is equally important as a precursor lesion of malignancy. Tumor profiles from Egypt were compared with colorectal tumors from Finland to evaluate if there are differences specific to the ethnic origin (East vs.West). Results showed for the first time a distinct genetic and epigenetic signature in the Egyptian CRC marked by high methylation of microsatellite stable tumors associated with advanced stage, and low frequency of Wnt signaling activation, suggesting a novel pathway. DNA samples from FCCX families were studied with genome wide linkage analysis using microsatellite markers. Selected genes from the linked areas were tested for possible mutations that could explain predisposition to a large number of colon adenomas and carcinomas seen in these families. Based on the results from the linkage analysis, a number of areas with tentative linkage were identified in family 20. We narrowed down these areas by additional microsatellite markers to found a mutation in the BMPR1A gene. Sequencing of an additional 17 FCCX families resulted in a BMPR1A mutation frequency of 2/18 families (11%). Clarification of the mechanisms of the differential tumor susceptibility in LS increases the understanding of gene and organ specific targets of MMR deficiency. While it is generally accepted that widespread MMR deficiency and consequent microsatellite instability (MSI) drives tumorigenesis in LS, the timing of molecular alterations is controversial. In particular, it is important to know that alterations may occur several years before cancer formation, at stages that are still histologically regarded as normal. Identification of molecular markers that could predict the risk of malignant transformation may be used to improve surveillance and cancer prevention in genetically predisposed individuals. Significant fractions of families with colorectal and/or endometrial cancer presently lack molecular definition altogether. Our findings expand the phenotypic spectrum of BMPR1A mutations and, for the first time, link FCCX families to the germline mutation of a specific gene. In particular, our observations encourage screening of additional families with FCCX for BMPR1A mutation, which is necessary in obtaining a reliable estimate of the share of BMPR1A-associated cases among all FCCX families worldwide. Clinically, the identification of predisposing mutations enables targeted cancer prevention in proven mutation carriers and thereby reduces cancer morbidity and mortality in the respective families.

Light scattering in random media with wavelength-scale structures : astronomical and industrial applications

Light scattering, or scattering and absorption of electromagnetic waves, is an important tool in all remote-sensing observations. In astronomy, the light scattered or absorbed by a distant object can be the only source of information. In Solar-system studies, the light-scattering methods are employed when interpreting observations of atmosphereless bodies such as asteroids, atmospheres of planets, and cometary or interplanetary dust. Our Earth is constantly monitored from artificial satellites at different wavelengths. With remote sensing of Earth the light-scattering methods are not the only source of information: there is always the possibility to make in situ measurements. The satellite-based remote sensing is, however, superior in the sense of speed and coverage if only the scattered signal can be reliably interpreted. The optical properties of many industrial products play a key role in their quality. Especially for products such as paint and paper, the ability to obscure the background and to reflect light is of utmost importance. High-grade papers are evaluated based on their brightness, opacity, color, and gloss. In product development, there is a need for computer-based simulation methods that could predict the optical properties and, therefore, could be used in optimizing the quality while reducing the material costs. With paper, for instance, pilot experiments with an actual paper machine can be very time- and resource-consuming. The light-scattering methods presented in this thesis solve rigorously the interaction of light and material with wavelength-scale structures. These methods are computationally demanding, thus the speed and accuracy of the methods play a key role. Different implementations of the discrete-dipole approximation are compared in the thesis and the results provide practical guidelines in choosing a suitable code. In addition, a novel method is presented for the numerical computations of orientation-averaged light-scattering properties of a particle, and the method is compared against existing techniques. Simulation of light scattering for various targets and the possible problems arising from the finite size of the model target are discussed in the thesis. Scattering by single particles and small clusters is considered, as well as scattering in particulate media, and scattering in continuous media with porosity or surface roughness. Various techniques for modeling the scattering media are presented and the results are applied to optimizing the structure of paper. However, the same methods can be applied in light-scattering studies of Solar-system regoliths or cometary dust, or in any remote-sensing problem involving light scattering in random media with wavelength-scale structures.

Lypsylehmän energiataseen mallintaminen tuotoskauden alkuvaiheessa

Energiataseen mallinnus on osa KarjaKompassi-hankkeeseen liittyvää kehitystyötä. Tutkielman tavoitteena oli kehittää lypsylehmän energiatasetta etukäteen ennustavia ja tuotoskauden aikana saatavia tietoja hyödyntäviä matemaattisia malleja. Selittävinä muuttujina olivat dieetti-, rehu-, maitotuotos-, koelypsy-, elopaino- ja kuntoluokkatiedot. Tutkimuksen aineisto kerättiin 12 Suomessa tehdyistä 8 – 28 laktaatioviikon pituisesta ruokintakokeesta, jotka alkoivat heti poikimisen jälkeen. Mukana olleista 344 lypsylehmästä yksi neljäsosa oli friisiläis- ja loput ayshire-rotuisia. Vanhempien lehmien päätiedosto sisälsi 2647 havaintoa (koe * lehmä * laktaatioviikko) ja ensikoiden 1070. Aineisto käsiteltiin SAS-ohjelmiston Mixed-proseduuria käyttäen ja poikkeavat havainnot poistettiin Tukeyn menetelmällä. Korrelaatioanalyysillä tarkasteltiin energiataseen ja selittävien muuttujien välisiä yhteyksiä. Energiatase mallinnettiin regressioanalyysillä. Laktaatiopäivän vaikutusta energiataseeseen selitettiin viiden eri funktion avulla. Satunnaisena tekijänä mallissa oli lehmä kokeen sisällä. Mallin sopivuutta aineistoon tarkasteltiin jäännösvirheen, selitysasteen ja Bayesin informaatiokriteerin avulla. Parhaat mallit testattiin riippumattomassa aineistossa. Laktaatiopäivän vaikutusta energiataseeseen selitti hyvin Ali-Schaefferin funktio, jota käytettiin perusmallina. Kaikissa energiatasemalleissa vaihtelu kasvoi laktaatioviikosta 12. alkaen, kun havaintojen määrä väheni ja energiatase muuttui positiiviseksi. Ennen poikimista käytettävissä olevista muuttujista dieetin väkirehuosuus ja väkirehun syönti-indeksi paransivat selitysastetta ja pienensivät jäännösvirhettä. Ruokinnan onnistumista voidaan seurata maitotuotoksen, maidon rasvapitoisuuden ja rasva-valkuaissuhteen tai EKM:n sisältävillä malleilla. EKM:n vakiointi pienensi mallin jäännösvirhettä. Elopaino ja kuntoluokka olivat heikkoja selittäjiä. Malleja voidaan hyödyntää karjatason ruokinnan suunnittelussa ja seurannassa, mutta yksittäisen lehmän energiataseen ennustamiseen ne eivät sovellu.