946 resultados para Bayesian Latent Class
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Class II division 1 malocclusion occurs in 3.5 to 13 percent of 7 12 year-old children. It is the most common reason for orthodontic treatment in Finland. Correction is most commonly performed using headgear treatment. The aim of this study was to investigate the effects of cervical headgear treatment on dentition, facial skeletal and soft tissue growth, and upper airway structure, in children. 65 schoolchildren, 36 boys and 29 girls were studied. At the onset of treatment a mean age was 9.3 (range 6.6 12.4) years. All the children were consequently referred to an orthodontist because of Class II division 1 malocclusion. The included children had protrusive maxilla and an overjet of more than 2mm (3 to 11 mm). The children were treated with a Kloehn-type cervical headgear as the only appliance until Class I first molar relationships were achieved. The essential features of the headgear were cervical strong pulling forces, a long upward bent outer bow, and an expanded inner bow. Dental casts and lateral and posteroanterior cephalograms were taken before and after the treatment. The results were compared to a historical, cross-sectional Finnish cohort or to historical, age- and sex-matched normal Class I controls. The Class I first molar relationships were achieved in all the treated children. The mean treatment time was 1.7 (range 0.3-3.1) years. Phase 2 treatments were needed in 52% of the children, most often because of excess overjet or overbite. The treatment decreased maxillary protrusion by inhibiting alveolar forward growth, while the rest of the maxilla and mandible followed normal growth. The palate rotated anteriorly downward. The expansion of the inner bow of the headgear induced widening of the maxilla, nasal cavity, and the upper and lower dental arches. Class II malocclusion was associated with narrower oro- and hypopharyngeal space than in the Class I normal controls. The treatment increased the retropalatal airway space, while the rest of the airway remained unaffected. The facial profile improved esthetically, while the facial convexity decreased. Facial soft tissues masked the facial skeletal convexity, and the soft tissue changes were smaller than skeletal changes. In conclusion, the headgear treatment with the expanded inner bow may be used as an easy and simple method for Class II correction in growing children.
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Mille Ottling ran the dancing school. Therese Molling's daughter Liesel (Elizabeth) Gottschalk and brother Hal attended the same school during the mid 1920s
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The quality of species distribution models (SDMs) relies to a large degree on the quality of the input data, from bioclimatic indices to environmental and habitat descriptors (Austin, 2002). Recent reviews of SDM techniques, have sought to optimize predictive performance e.g. Elith et al., 2006. In general SDMs employ one of three approaches to variable selection. The simplest approach relies on the expert to select the variables, as in environmental niche models Nix, 1986 or a generalized linear model without variable selection (Miller and Franklin, 2002). A second approach explicitly incorporates variable selection into model fitting, which allows examination of particular combinations of variables. Examples include generalized linear or additive models with variable selection (Hastie et al. 2002); or classification trees with complexity or model based pruning (Breiman et al., 1984, Zeileis, 2008). A third approach uses model averaging, to summarize the overall contribution of a variable, without considering particular combinations. Examples include neural networks, boosted or bagged regression trees and Maximum Entropy as compared in Elith et al. 2006. Typically, users of SDMs will either consider a small number of variable sets, via the first approach, or else supply all of the candidate variables (often numbering more than a hundred) to the second or third approaches. Bayesian SDMs exist, with several methods for eliciting and encoding priors on model parameters (see review in Low Choy et al. 2010). However few methods have been published for informative variable selection; one example is Bayesian trees (O’Leary 2008). Here we report an elicitation protocol that helps makes explicit a priori expert judgements on the quality of candidate variables. This protocol can be flexibly applied to any of the three approaches to variable selection, described above, Bayesian or otherwise. We demonstrate how this information can be obtained then used to guide variable selection in classical or machine learning SDMs, or to define priors within Bayesian SDMs.
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Otto Gersuny (1890-1964), third row from the front wearing cap (see arrow)
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Brooks' Theorem says that if for a graph G,Δ(G)=n, then G is n-colourable, unless (1) n=2 and G has an odd cycle as a component, or (2) n>2 and Kn+1 is a component of G. In this paper we prove that if a graph G has none of some three graphs (K1,3;K5−e and H) as an induced subgraph and if Δ(G)greater-or-equal, slanted6 and d(G)<Δ(G), then χ(G)<Δ(G). Also we give examples to show that the hypothesis Δ(G)greater-or-equal, slanted6 can not be non-trivially relaxed and the graph K5−e can not be removed from the hypothesis. Moreover, for a graph G with none of K1,3;K5−e and H as an induced subgraph, we verify Borodin and Kostochka's conjecture that if for a graph G,Δ(G)greater-or-equal, slanted9 and d(G)<Δ(G), then χ(G)<Δ(G).
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Tutkimuksen aiheita olivat yhteiskuntaluokkien väliset erot sairastavuudessa ja alentuneessa toimintakyvyssä, sekä fyysisen työkuormituksen ja joidenkin muiden työolojen vaikutus sairastavuuteen. Empiirisestä työstä on raportoitu myös neljässä kansainvälisissä tieteellisissä aikakauskirjoissa julkaistussa artikkelissa. Tässä julkaistu yhteenveto sisältää tulosten yhteenvedon lisäksi myös tutkimusta koskevien käsitteellisten ja teoreettisten kysymysten sekä tutkimustradition kriittisen katsauksen. Työn päätavoitteita olivat 1) tutkia fyysisesti kuormittavan työn, ja jossain määrin muiden työolojen osuutta yhteiskuntaluokkien välisiin eroihin sairaudessa ja toimintakyvyn alentuneisuudessa; 2) tutkia työn fyysisen kuormittavuuden, työhön liittyvien vaikutusmahdollisuuksien ja hallinnan (decision latitude), luokka-aseman, iän ja sukupuolen yhteisvaikutuksia heikentyneeseen terveydentilaan; sekä 3) tutkia missä määrin mekaanisten työaltisteiden ja tuki- ja liikuntaelinsairastavuuden välinen yhteys voi selittää yhteiskuntaluokkien välisiä eroja heikentyneessä yleisessä terveydentilassa. Tutkittavat olivat keski-ikäisiä Helsingin kaupungin työntekijöitä. Analyysit perustuivat poikittaisasetelmaan, ja käytetty aineisto oli Helsinki Health Studyn vuosien 2000 ja 2002 välillä kerättyä aineistoa. Analyyseihin käytetyssä aineistossa oli 3740:stä 8002:een tutkittavaa. Tulosten perusteella fyysisillä (sekä fysikaalisilla) työoloilla on merkittävä vaikutus yhteiskuntaluokkien välisiin eroihin yleisessä sairastavuudessa, toimintakyvyn heikentymisessä, tuki- ja liikuntaelinsairastavuudessa sekä itsearvioidussa terveydentilassa. Naisilla lähes puolet heikentyneen toimintakyvyn ja koetun terveydentilan luokkaeroista vaikutti olevan selitettävissä fyysisellä työkuormituksella. Hallintamahdollisuuksien ei havaittu merkittävästi muuttavan fyysisen kuormituksen vaikutusta toimintakykyyn. Fyysisen kuormittavuuden terveysvaikutus voimistui kasvavan iän mukaan enemmän naisilla kuin miehillä. Osa, mutta ei koko fyysisen kuormituksen vaikutus yhteiskuntaluokkien eroihin heikentyneessä terveydessä vaikutti välittyvän tuki- ja liikuntaelinsairastavuuden kautta. Terveys ja sairaus eivät ole yhtenäisiä tiloja, ja siksi monet eri sosiaalisesti ja rakenteellisesti määräytyvät olosuhteet todennäköisesti vaikuttavat yhteiskunnallisten terveyserojen syntymiseen. Fyysis-materiaalisten olojen vaikutusta terveyserojen syntyyn nyky-yhteiskunnassa on mahdollisesti aliarvioitu. Yhteiskuntaluokkien väliset erot fyysis-materiaalisissa olosuhteissa eivät ole kadonneet, ja nämä erot todennäköisesti vaikuttavat terveyserojen syntyyn.
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In genetic epidemiology, population-based disease registries are commonly used to collect genotype or other risk factor information concerning affected subjects and their relatives. This work presents two new approaches for the statistical inference of ascertained data: a conditional and full likelihood approaches for the disease with variable age at onset phenotype using familial data obtained from population-based registry of incident cases. The aim is to obtain statistically reliable estimates of the general population parameters. The statistical analysis of familial data with variable age at onset becomes more complicated when some of the study subjects are non-susceptible, that is to say these subjects never get the disease. A statistical model for a variable age at onset with long-term survivors is proposed for studies of familial aggregation, using latent variable approach, as well as for prospective studies of genetic association studies with candidate genes. In addition, we explore the possibility of a genetic explanation of the observed increase in the incidence of Type 1 diabetes (T1D) in Finland in recent decades and the hypothesis of non-Mendelian transmission of T1D associated genes. Both classical and Bayesian statistical inference were used in the modelling and estimation. Despite the fact that this work contains five studies with different statistical models, they all concern data obtained from nationwide registries of T1D and genetics of T1D. In the analyses of T1D data, non-Mendelian transmission of T1D susceptibility alleles was not observed. In addition, non-Mendelian transmission of T1D susceptibility genes did not make a plausible explanation for the increase in T1D incidence in Finland. Instead, the Human Leucocyte Antigen associations with T1D were confirmed in the population-based analysis, which combines T1D registry information, reference sample of healthy subjects and birth cohort information of the Finnish population. Finally, a substantial familial variation in the susceptibility of T1D nephropathy was observed. The presented studies show the benefits of sophisticated statistical modelling to explore risk factors for complex diseases.
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The photograph shows Gisela Kleinermann (standing at the right end of the line) with her class at the ‘Juedische Schule’ in Dresden, late summer of 1938, as she and her mother were preparing for her immigration to the USA. Most other children were deported in October 1938 and perished in the Holocaust. The teacher, Jacob Blum (center back) emigrated to Palestine.
Latent TGF-β binding proteins -3 and -4 : transcriptional control and extracellular matrix targeting
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Extracellular matrix (ECM) is a complex network of various proteins and proteoglycans which provides tissues with structural strength and resilience. By harvesting signaling molecules like growth factors ECM has the capacity to control cellular functions including proliferation, differentiation and cell survival. Latent transforming growth factor β (TGF-β) binding proteins (LTBPs) associate fibrillar structures of the ECM and mediate the efficient secretion and ECM deposition of latent TGF-β. The current work was conducted to determine the regulatory regions of LTBP-3 and -4 genes to gain insight into their tissue-specific expression which also has impact on TGF-β biology. Furthermore, the current research aimed at defining the ECM targeting of the N-terminal variants of LTBP-4 (LTBP-4S and -4L), which is required to understand their functions in tissues and to gain insight into conditions in which TGF-β is activated. To characterize the regulatory regions of LTBP-3 and -4 genes in silico and functional promoter analysis techniques were employed. It was found that the expression of LTBP-4S and -4L are under control of two independent promoters. This finding was in accordance with the observed expression patterns of LTBP-4S and -4L in human tissues. All promoter regions characterized in this study were TATAless, GC-rich and highly conserved between human and mouse species. Putative binding sites for Sp1 and GATA family of transcription factors were recognized in all of these regulatory regions. It is possible that these transcription factors control the basal expression of LTBP-3 and -4 genes. Smad binding element was found within the LTBP-3 and -4S promoter regions, but it was not present in LTBP-4L promoter. Although this element important for TGF-β signaling was present in LTBP-4S promoter, TGF-β did not induce its transcriptional activity. LTBP-3 promoter activity and mRNA expression instead were stimulated by TGF-β1 in osteosarcoma cells. It was found that the stimulatory effect of TGF-β was mediated by Smad and Erk MAPK signaling pathways. The current work explored the ECM targeting of LTBP-4S and identified binding partners of this protein. It was found that the N-terminal end of LTBP-4S possesses fibronectin (FN) binding sites which are critical for its ECM targeting. FN deficient fibroblasts incorporated LTBP-4S into their ECM only after addition of exogenous FN. Furthermore, LTBP-4S was found to have heparin binding regions, of which the C-terminal binding site mediated fibroblast adhesion. Soluble heparin prevented the ECM association of LTBP-4S in fibroblast cultures. In the current work it was observed that there are significant differences in the secretion, processing and ECM targeting of LTBP-4S and -4L. Interestingly, it was observed that most of the secreted LTBP-4L was associated with latent TGF-β1, whereas LTBP-4S was mainly secreted as a free form from CHO cells. This thesis provides information on transcriptional regulation of LTBP-3 and -4 genes, which is required for the deeper understanding of their tissue-specific functions. Further, the current work elucidates the structural variability of LTBPs, which appears to have impact on secretion and ECM targeting of TGF-β. These findings may advance understanding the abnormal activation of TGF-β which is associated with connective tissue disorders and cancer.