914 resultados para RESIDUAL-BASED TESTS


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Trabecular bone is a porous mineralized tissue playing a major load bearing role in the human body. Prediction of age-related and disease-related fractures and the behavior of bone implant systems needs a thorough understanding of its structure-mechanical property relationships, which can be obtained using microcomputed tomography-based finite element modeling. In this study, a nonlinear model for trabecular bone as a cohesive-frictional material was implemented in a large-scale computational framework and validated by comparison of μFE simulations with experimental tests in uniaxial tension and compression. A good correspondence of stiffness and yield points between simulations and experiments was found for a wide range of bone volume fraction and degree of anisotropy in both tension and compression using a non-calibrated, average set of material parameters. These results demonstrate the ability of the model to capture the effects leading to failure of bone for three anatomical sites and several donors, which may be used to determine the apparent behavior of trabecular bone and its evolution with age, disease, and treatment in the future.

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Objective: In schizophrenia, abnormalities in nonverbal behaviors have always been considered as highly relevant. However, due to methodological limitations, nonverbal behavior was rarely quantified objectively. Recent methodological advances now allow a quantification of body movement from ordinary video recordings. We showed that patients’ objectively measured amount of movement in social role-play interactions was closely associated with their symptom profiles (Kupper, Ramseyer, Hoffmann, & Tschacher, Schizophrenia Research 2010). In the present study, a replication of these results in the context of semi-standardized PANSS (Positive and Negative Syndrome Scale) interviews was intended. Methods: 17 patients with schizophrenia were analyzed during the initial 15-min sequence of a videotaped PANSS interview using Motion Energy Analysis (MEA). The amount of patients’ movement was then correlated with their PANSS symptom scores. Results: Sizeable and significant correlations between negative symptoms and reduced movements (r = -.68, p<0.01) and reduced movement speed (r = -.80, p<0.001) were found. Moreover, cognitive symptoms were related to reduced movement speed (r = -.70, p<.01). Conclusion: Negative symptoms were reliably indicated by patients’ nonverbal behavior in psychopathology interviews. Hence, the main result of our earlier study, examining patients’ nonverbal behavior in role play tests, was replicated for the less structured interactions in psychopathological interviews. Results could encourage the use of MEA in a wide range of videotaped social interactions of patients with schizophrenia and other psychiatric disorders.

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The main objective of this preliminary study was to further clarify the association between testosterone (T) levels and depression by investigating symptom-based depression subtypes in a sample of 64 men. The data were taken from the ZInEP epidemiology survey. Gonadal hormones of a melancholic (n  = 25) and an atypical (n = 14) depression subtype, derived from latent class analysis, were compared with those of healthy controls (n  = 18). Serum T was assayed using an enzyme-linked immunosorbent assay procedure. Analysis of variance, analysis of covariance, non-parametrical tests, and generalized linear regression models were performed to examine group differences. The atypical depressive subtype showed significantly lower T levels compared with the melancholic depressives. While accumulative evidence indicates that, beyond psychosocial characteristics, the melancholic and atypical depressive subtypes are also distinguishable by biological correlates, the current study expanded this knowledge to include gonadal hormones. Further longitudinal research is warranted to disclose causality by linking the multiple processes in pathogenesis of depression.

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BACKGROUND Residual acetabular dysplasia is seen in combination with femoral pathomorphologies including an aspherical femoral head and valgus neck-shaft angle with high antetorsion. It is unclear how these femoral pathomorphologies affect range of motion (ROM) and impingement zones after periacetabular osteotomy. QUESTIONS/PURPOSES (1) Does periacetabular osteotomy (PAO) restore the typically excessive ROM in dysplastic hips compared with normal hips; (2) how do impingement locations differ in dysplastic hips before and after PAO compared with normal hips; (3) does a concomitant cam-type morphology adversely affect internal rotation; and (4) does a concomitant varus-derotation intertrochanteric osteotomy (IO) affect external rotation? METHODS Between January 1999 and March 2002, we performed 200 PAOs for dysplasia; of those, 27 hips (14%) met prespecified study inclusion criteria, including availability of a pre- and postoperative CT scan that included the hip and the distal femur. In general, we obtained those scans to evaluate the pre- and postoperative acetabular and femoral morphology, the degree of acetabular reorientation, and healing of the osteotomies. Three-dimensional surface models based on CT scans of 27 hips before and after PAO and 19 normal hips were created. Normal hips were obtained from a population of CT-based computer-assisted THAs using the contralateral hip after exclusion of symptomatic hips or hips with abnormal radiographic anatomy. Using validated and computerized methods, we then determined ROM (flexion/extension, internal- [IR]/external rotation [ER], adduction/abduction) and two motion patterns including the anterior (IR in flexion) and posterior (ER in extension) impingement tests. The computed impingement locations were assigned to anatomical locations of the pelvis and the femur. ROM was calculated separately for hips with (n = 13) and without (n = 14) a cam-type morphology and PAOs with (n = 9) and without (n = 18) a concomitant IO. A post hoc power analysis based on the primary research question with an alpha of 0.05 and a beta error of 0.20 revealed a minimal detectable difference of 4.6° of flexion. RESULTS After PAO, flexion, IR, and adduction/abduction did not differ from the nondysplastic control hips with the numbers available (p ranging from 0.061 to 0.867). Extension was decreased (19° ± 15°; range, -18° to 30° versus 28° ± 3°; range, 19°-30°; p = 0.017) and ER in 0° flexion was increased (25° ± 18°; range, -10° to 41° versus 38° ± 7°; range, 17°-41°; p = 0.002). Dysplastic hips had a higher prevalence of extraarticular impingement at the anteroinferior iliac spine compared with normal hips (48% [13 of 27 hips] versus 5% [one of 19 hips], p = 0.002). A PAO increased the prevalence of impingement for the femoral head from 30% (eight of 27 hips) preoperatively to 59% (16 of 27 hips) postoperatively (p = 0.027). IR in flexion was decreased in hips with a cam-type deformity compared with those with a spherical femoral head (p values from 0.002 to 0.047 for 95°-120° of flexion). A concomitant IO led to a normalization of ER in extension (eg, 37° ± 7° [range, 21°-41°] of ER in 0° of flexion in hips with concomitant IO compared with 38° ± 7° [range, 17°-41°] in nondysplastic control hips; p = 0.777). CONCLUSIONS Using computer simulation of hip ROM, we could show that the PAO has the potential to restore the typically excessive ROM in dysplastic hips. However, a PAO can increase the prevalence of secondary intraarticular impingement of the aspherical femoral head and extraarticular impingement of the anteroinferior iliac spines in flexion and internal rotation. A cam-type morphology can result in anterior impingement with restriction of IR. Additionally, a valgus hip with high antetorsion can result in posterior impingement with decreased ER in extension, which can be normalized with a varus derotation IO of the femur. However, indication of an additional IO needs to be weighed against its inherent morbidity and possible complications. The results are based on a limited number of hips with a pre- and postoperative CT scan after PAO. Future prospective studies are needed to verify the current results based on computer simulation and to test their clinical importance.

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Tick-borne encephalitis (TBE) is one of the most dangerous human neurological infections occurring in Europe and Northern parts of Asia with thousands of cases and millions vaccinated against it. The risk of TBE might be assessed through analyses of the samples taken from wildlife or from animals which are in close contact with humans. Dogs have been shown to be a good sentinel species for these studies. Serological assays for diagnosis of TBE in dogs are mainly based on purified and inactivated TBEV antigens. Here we describe novel dog anti-TBEV IgG monoclonal antibody (MAb)-capture assay which is based on TBEV prME subviral particles expressed in mammalian cells from Semliki Forest virus (SFV) replicon as well as IgG immunofluorescence assay (IFA) which is based on Vero E6 cells transfected with the same SFV replicon. We further demonstrate their use in a small-scale TBEV seroprevalence study of dogs representing different regions of Finland. Altogether, 148 dog serum samples were tested by novel assays and results were compared to those obtained with a commercial IgG enzyme immunoassay (EIA), hemagglutination inhibition test and IgG IFA with TBEV infected cells. Compared to reference tests, the sensitivities of the developed assays were 90-100% and the specificities of the two assays were 100%. Analysis of the dog serum samples showed a seroprevalence of 40% on Åland Islands and 6% on Southwestern archipelago of Finland. In conclusion, a specific and sensitive EIA and IFA for the detection of IgG antibodies in canine sera were developed. Based on these assays the seroprevalence of IgG antibodies in dogs from different regions of Finland was assessed and was shown to parallel the known human disease burden as the Southwestern archipelago and Åland Islands in particular had considerable dog TBEV antibody prevalence and represent areas with high risk of TBE for humans.

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Behavioural tests to assess affective states are widely used in human research and have recently been extended to animals. These tests assume that affective state influences cognitive processing, and that animals in a negative affective state interpret ambiguous information as expecting a negative outcome (displaying a negative cognitive bias). Most of these tests however, require long discrimination training. The aim of the study was to validate an exploration based cognitive bias test, using two different handling methods, as previous studies have shown that standard tail handling of mice increases physiological and behavioural measures of anxiety compared to cupped handling. Therefore, we hypothesised that tail handled mice would display a negative cognitive bias. We handled 28 female CD-1 mice for 16 weeks using either tail handling or cupped handling. The mice were then trained in an eight arm radial maze, where two adjacent arms predicted a positive outcome (darkness and food), while the two opposite arms predicted a negative outcome (no food, white noise and light). After six days of training, the mice were also given access to the four previously unavailable intermediate ambiguous arms of the radial maze and tested for cognitive bias. We were unable to validate this test, as mice from both handling groups displayed a similar pattern of exploration. Furthermore, we examined whether maze exploration is affected by the expression of stereotypic behaviour in the home cage. Mice with higher levels of stereotypic behaviour spent more time in positive arms and avoided ambiguous arms, displaying a negative cognitive bias. While this test needs further validation, our results indicate that it may allow the assessment of affective state in mice with minimal training— a major confound in current cognitive bias paradigms.

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Genetic anticipation is defined as a decrease in age of onset or increase in severity as the disorder is transmitted through subsequent generations. Anticipation has been noted in the literature for over a century. Recently, anticipation in several diseases including Huntington's Disease, Myotonic Dystrophy and Fragile X Syndrome were shown to be caused by expansion of triplet repeats. Anticipation effects have also been observed in numerous mental disorders (e.g. Schizophrenia, Bipolar Disorder), cancers (Li-Fraumeni Syndrome, Leukemia) and other complex diseases. ^ Several statistical methods have been applied to determine whether anticipation is a true phenomenon in a particular disorder, including standard statistical tests and newly developed affected parent/affected child pair methods. These methods have been shown to be inappropriate for assessing anticipation for a variety of reasons, including familial correlation and low power. Therefore, we have developed family-based likelihood modeling approaches to model the underlying transmission of the disease gene and penetrance function and hence detect anticipation. These methods can be applied in extended families, thus improving the power to detect anticipation compared with existing methods based only upon parents and children. The first method we have proposed is based on the regressive logistic hazard model. This approach models anticipation by a generational covariate. The second method allows alleles to mutate as they are transmitted from parents to offspring and is appropriate for modeling the known triplet repeat diseases in which the disease alleles can become more deleterious as they are transmitted across generations. ^ To evaluate the new methods, we performed extensive simulation studies for data simulated under different conditions to evaluate the effectiveness of the algorithms to detect genetic anticipation. Results from analysis by the first method yielded empirical power greater than 87% based on the 5% type I error critical value identified in each simulation depending on the method of data generation and current age criteria. Analysis by the second method was not possible due to the current formulation of the software. The application of this method to Huntington's Disease and Li-Fraumeni Syndrome data sets revealed evidence for a generation effect in both cases. ^

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We apply the efficient unit-roots tests of Elliott, Rothenberg, and Stock (1996), and Elliott (1998) to twenty-one real exchange rates using monthly data of the G-7 countries from the post-Bretton Woods floating exchange rate period. Our results indicate that, for eighteen out of the twenty-one real exchange rates, the null hypothesis of a unit root can be rejected at the 10% significance level or better using the Elliot et al (1996) DF-GLS test. The unit-root null hypothesis is also rejected for one additional real exchange rate when we allow for one endogenously determined break in the time series of the real exchange rate as in Perron (1997). In all, we find favorable evidence to support long-run purchasing power parity in nineteen out of twenty-one real exchange rates. Second, we find no strong evidence to suggest that the use of non-U.S. dollar-based real exchange rates tend to produce more favorable result for long-run PPP than the use of U.S. dollar-based real exchange rates as Lothian (1998) has concluded.

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It is important to check the fundamental assumption of most popular Item Response Theory models, unidimensionality. However, it is hard for educational and psychological tests to be strictly unidimensional. The tests studied in this paper are from a standardized high-stake testing program. They feature potential multidimensionality by presenting various item types and item sets. Confirmatory factor analyses with one-factor and bifactor models, and based on both linear structural equation modeling approach and nonlinear IRT approach were conducted. The competing models were compared and the implications of the bifactor model for checking essential unidimensionality were discussed.

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Linkage and association studies are major analytical tools to search for susceptibility genes for complex diseases. With the availability of large collection of single nucleotide polymorphisms (SNPs) and the rapid progresses for high throughput genotyping technologies, together with the ambitious goals of the International HapMap Project, genetic markers covering the whole genome will be available for genome-wide linkage and association studies. In order not to inflate the type I error rate in performing genome-wide linkage and association studies, multiple adjustment for the significant level for each independent linkage and/or association test is required, and this has led to the suggestion of genome-wide significant cut-off as low as 5 × 10 −7. Almost no linkage and/or association study can meet such a stringent threshold by the standard statistical methods. Developing new statistics with high power is urgently needed to tackle this problem. This dissertation proposes and explores a class of novel test statistics that can be used in both population-based and family-based genetic data by employing a completely new strategy, which uses nonlinear transformation of the sample means to construct test statistics for linkage and association studies. Extensive simulation studies are used to illustrate the properties of the nonlinear test statistics. Power calculations are performed using both analytical and empirical methods. Finally, real data sets are analyzed with the nonlinear test statistics. Results show that the nonlinear test statistics have correct type I error rates, and most of the studied nonlinear test statistics have higher power than the standard chi-square test. This dissertation introduces a new idea to design novel test statistics with high power and might open new ways to mapping susceptibility genes for complex diseases. ^

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With the recognition of the importance of evidence-based medicine, there is an emerging need for methods to systematically synthesize available data. Specifically, methods to provide accurate estimates of test characteristics for diagnostic tests are needed to help physicians make better clinical decisions. To provide more flexible approaches for meta-analysis of diagnostic tests, we developed three Bayesian generalized linear models. Two of these models, a bivariate normal and a binomial model, analyzed pairs of sensitivity and specificity values while incorporating the correlation between these two outcome variables. Noninformative independent uniform priors were used for the variance of sensitivity, specificity and correlation. We also applied an inverse Wishart prior to check the sensitivity of the results. The third model was a multinomial model where the test results were modeled as multinomial random variables. All three models can include specific imaging techniques as covariates in order to compare performance. Vague normal priors were assigned to the coefficients of the covariates. The computations were carried out using the 'Bayesian inference using Gibbs sampling' implementation of Markov chain Monte Carlo techniques. We investigated the properties of the three proposed models through extensive simulation studies. We also applied these models to a previously published meta-analysis dataset on cervical cancer as well as to an unpublished melanoma dataset. In general, our findings show that the point estimates of sensitivity and specificity were consistent among Bayesian and frequentist bivariate normal and binomial models. However, in the simulation studies, the estimates of the correlation coefficient from Bayesian bivariate models are not as good as those obtained from frequentist estimation regardless of which prior distribution was used for the covariance matrix. The Bayesian multinomial model consistently underestimated the sensitivity and specificity regardless of the sample size and correlation coefficient. In conclusion, the Bayesian bivariate binomial model provides the most flexible framework for future applications because of its following strengths: (1) it facilitates direct comparison between different tests; (2) it captures the variability in both sensitivity and specificity simultaneously as well as the intercorrelation between the two; and (3) it can be directly applied to sparse data without ad hoc correction. ^

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Monte Carlo simulation has been conducted to investigate parameter estimation and hypothesis testing in some well known adaptive randomization procedures. The four urn models studied are Randomized Play-the-Winner (RPW), Randomized Pôlya Urn (RPU), Birth and Death Urn with Immigration (BDUI), and Drop-the-Loses Urn (DL). Two sequential estimation methods, the sequential maximum likelihood estimation (SMLE) and the doubly adaptive biased coin design (DABC), are simulated at three optimal allocation targets that minimize the expected number of failures under the assumption of constant variance of simple difference (RSIHR), relative risk (ORR), and odds ratio (OOR) respectively. Log likelihood ratio test and three Wald-type tests (simple difference, log of relative risk, log of odds ratio) are compared in different adaptive procedures. ^ Simulation results indicates that although RPW is slightly better in assigning more patients to the superior treatment, the DL method is considerably less variable and the test statistics have better normality. When compared with SMLE, DABC has slightly higher overall response rate with lower variance, but has larger bias and variance in parameter estimation. Additionally, the test statistics in SMLE have better normality and lower type I error rate, and the power of hypothesis testing is more comparable with the equal randomization. Usually, RSIHR has the highest power among the 3 optimal allocation ratios. However, the ORR allocation has better power and lower type I error rate when the log of relative risk is the test statistics. The number of expected failures in ORR is smaller than RSIHR. It is also shown that the simple difference of response rates has the worst normality among all 4 test statistics. The power of hypothesis test is always inflated when simple difference is used. On the other hand, the normality of the log likelihood ratio test statistics is robust against the change of adaptive randomization procedures. ^

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Hypertension is usually defined as having values of systolic blood pressure ≥140 mmHg, diastolic blood pressure ≥90 mmHg. Hypertension is one of the main adverse effects of glucocorticoid on the cardiovascular system. Glucocorticoids are essential hormones, secreted from adrenal glands in circadian fashion. Glucocorticoid's effect on blood pressure is conveyed by the glucocorticoid receptor (NR3C1), an omnipresent nuclear transcription factor. Although polymorphisms in this gene have long been implicated to be a causal factor for cardiovascular diseases such as hypertension, no study has yet thoroughly interrogated the gene's polymorphisms for their effect on blood pressure levels. Therefore, I have first resequenced ∼30 kb of the gene, encompassing all exons, promoter regions, 5'/3' UTRs as well as at least 1.5 kb of the gene's flanking regions from 114 chromosome 5 monosomic cell lines, comprised of three major American ethnic groups—European American, African American and Mexican American. I observed 115 polymorphisms and 14 common molecularly phased haplotypes. A subset of markers was chosen for genotyping study populations of GENOA (Genetic Epidemiology Network of Atherosclerosis; 1022 non-Hispanic whites, 1228 African Americans and 954 Mexican Americans). Since these study populations include sibships, the family-based association test was performed on 4 blood pressure-related quantitative variables—pulse, systolic blood pressure, diastolic blood pressure and mean arterial pressure. Using these analyses, multiple correlated SNPs are significantly protective against high systolic blood pressure in non-Hispanic whites, which includes rsb198, a SNP formerly associated with beneficial body compositions. Haplotype association analysis also supports this finding and all p-values remained significant after permutation tests. I therefore conclude that multiple correlated SNPs on the gene may confer protection against high blood pressure in non-Hispanic whites. ^

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This study retrospectively evaluated the spatial and temporal disease patterns associated with influenza-like illness (ILI), positive rapid influenza antigen detection tests (RIDT), and confirmed H1N1 S-OIV cases reported to the Cameron County Department of Health and Human Services between April 26 and May 13, 2009 using the space-time permutation scan statistic software SaTScan in conjunction with geographical information system (GIS) software ArcGIS 9.3. The rate and age-adjusted relative risk of each influenza measure was calculated and a cluster analysis was conducted to determine the geographic regions with statistically higher incidence of disease. A Poisson distribution model was developed to identify the effect that socioeconomic status, population density, and certain population attributes of a census block-group had on that area's frequency of S-OIV confirmed cases over the entire outbreak. Predominant among the spatiotemporal analyses of ILI, RIDT and S-OIV cases in Cameron County is the consistent pattern of a high concentration of cases along the southern border with Mexico. These findings in conjunction with the slight northward space-time shifts of ILI and RIDT cluster centers highlight the southern border as the primary site for public health interventions. Finally, the community-based multiple regression model revealed that three factors—percentage of the population under age 15, average household size, and the number of high school graduates over age 25—were significantly associated with laboratory-confirmed S-OIV in the Lower Rio Grande Valley. Together, these findings underscore the need for community-based surveillance, improve our understanding of the distribution of the burden of influenza within the community, and have implications for vaccination and community outreach initiatives.^

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Objectives. Triple Negative Breast Cancer (TNBC) lack expression of estrogen receptors (ER), progesterone receptors (PR), and absence of Her2 gene amplification. Current literature has identified TNBC and over-expression of cyclo-oxygenase-2 (COX-2) protein in primary breast cancer to be independent markers of poor prognosis in terms of overall and distant disease free survival. The purpose of this study was to compare COX-2 over-expression in TNBC patients to those patients who expressed one or more of the three tumor markers (i.e. ER, and/or PR, and/or Her2).^ Methods. Using a secondary data analysis, a cross-sectional design was implemented to examine the association of interest. Data collected from two ongoing protocols titled "LAB04-0657: a model for COX-2 mediated bone metastasis (Specific aim 3)" and "LAB04-0698: correlation of circulating tumor cells and COX-2 expression in primary breast cancer metastasis" was used for analysis. A sample of 125 female patients was analyzed using Chi-square tests and logistic regression models. ^ Results. COX-2 over-expression was present in 33% (41/125) and 28% (35/124) patients were identified as having TNBC. TNBC status was associated with elevated COX-2 expression (OR= 3.34; 95% CI= 1.40–8.22) and high tumor grade (OR= 4.09; 95% CI= 1.58–10.82). In a multivariable analysis, TNBC status was an important predictor of COX-2 expression after adjusting for age, menopausal status, BMI, and lymph node status (OR= 3.31; 95% CI: 1.26–8.67; p=0.01).^ Conclusion. TNBC is associated with COX-2 expression—a known marker of poor prognosis in patients with operable breast cancer. Replication of these results in a study with a larger sample size, or a future randomized clinical trial demonstrating an improved prognosis with COX-2 suppression in these patients would support this hypothesis.^