837 resultados para quantitative research


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The etiology of complex diseases is heterogeneous. The presence of risk alleles in one or more genetic loci affects the function of a variety of intermediate biological pathways, resulting in the overt expression of disease. Hence, there is an increasing focus on identifying the genetic basis of disease by sytematically studying phenotypic traits pertaining to the underlying biological functions. In this paper we focus on identifying genetic loci linked to quantitative phenotypic traits in experimental crosses. Such genetic mapping methods often use a one stage design by genotyping all the markers of interest on the available subjects. A genome scan based on single locus or multi-locus models is used to identify the putative loci. Since the number of quantitative trait loci (QTLs) is very likely to be small relative to the number of markers genotyped, a one-stage selective genotyping approach is commonly used to reduce the genotyping burden, whereby markers are genotyped solely on individuals with extreme trait values. This approach is powerful in the presence of a single quantitative trait locus (QTL) but may result in substantial loss of information in the presence of multiple QTLs. Here we investigate the efficiency of sequential two stage designs to identify QTLs in experimental populations. Our investigations for backcross and F2 crosses suggest that genotyping all the markers on 60% of the subjects in Stage 1 and genotyping the chromosomes significant at 20% level using additional subjects in Stage 2 and testing using all the subjects provides an efficient approach to identify the QTLs and utilizes only 70% of the genotyping burden relative to a one stage design, regardless of the heritability and genotyping density. Complex traits are a consequence of multiple QTLs conferring main effects as well as epistatic interactions. We propose a two-stage analytic approach where a single-locus genome scan is conducted in Stage 1 to identify promising chromosomes, and interactions are examined using the loci on these chromosomes in Stage 2. We examine settings under which the two-stage analytic approach provides sufficient power to detect the putative QTLs.

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We propose robust and e±cient tests and estimators for gene-environment/gene-drug interactions in family-based association studies. The methodology is designed for studies in which haplotypes, quantitative pheno- types and complex exposure/treatment variables are analyzed. Using causal inference methodology, we derive family-based association tests and estimators for the genetic main effects and the interactions. The tests and estimators are robust against population admixture and strati¯cation without requiring adjustment for confounding variables. We illustrate the practical relevance of our approach by an application to a COPD study. The data analysis suggests a gene-environment interaction between a SNP in the Serpine gene and smok- ing status/pack years of smoking that reduces the FEV1 volume by about 0.02 liter per pack year of smoking. Simulation studies show that the pro- posed methodology is su±ciently powered for realistic sample sizes and that it provides valid tests and effect size estimators in the presence of admixture and stratification.

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PURPOSE: To quantify optical coherence tomography (OCT) images of the central retina in patients with blue-cone monochromatism (BCM) and achromatopsia (ACH) compared with healthy control individuals. METHODS: The study included 15 patients with ACH, 6 with BCM, and 20 control subjects. Diagnosis of BCM and ACH was established by visual acuity testing, morphologic examination, color vision testing, and Ganzfeld ERG recording. OCT images were acquired with the Stratus OCT 3 (Carl Zeiss Meditec AG, Oberkochen, Germany). Foveal OCT images were analyzed by calculating longitudinal reflectivity profiles (LRPs) from scan lines. Profiles were analyzed quantitatively to determine foveal thickness and distances between reflectivity layers. RESULTS: Patients with ACH and BCM had a mean visual acuity of 20/200 and 20/60, respectively. Color vision testing results were characteristic of the diseases. The LRPs of control subjects yielded four peaks (P1-P4), presumably representing the RPE (P1), the ovoid region of the photoreceptors (P2), the external limiting membrane (ELM) (P3), and the internal limiting membrane (P4). In patients with ACH, P2 was absent, but foveal thickness (P1-P4) did not differ significantly from that in the control subjects (187 +/- 20 vs. 192 +/- 14 microm, respectively). The distance from P1 to P3 did not differ significantly (78 +/- 10 vs. 82 +/- 5 microm) between ACH and controls subjects. In patients with BCM, P3 was lacking, and P2 advanced toward P1 compared with the control subjects (32 +/- 6 vs. 48 +/- 4 microm). Foveal thickness (153 +/- 16 microm) was significantly reduced compared with that in control subjects and patients with ACH. CONCLUSIONS: Quantitative OCT image analysis reveals distinct patterns for controls subjects and patients with ACH and BCM, respectively. Quantitative analysis of OCT imaging can be useful in differentiating retinal diseases affecting photoreceptors. Foveal thickness is similar in both normal subjects and patients with ACH but is decreased in patients with BCM.

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To compare the prediction of hip fracture risk of several bone ultrasounds (QUS), 7062 Swiss women > or =70 years of age were measured with three QUSs (two of the heel, one of the phalanges). Heel QUSs were both predictive of hip fracture risk, whereas the phalanges QUS was not. INTRODUCTION: As the number of hip fracture is expected to increase during these next decades, it is important to develop strategies to detect subjects at risk. Quantitative bone ultrasound (QUS), an ionizing radiation-free method, which is transportable, could be interesting for this purpose. MATERIALS AND METHODS: The Swiss Evaluation of the Methods of Measurement of Osteoporotic Fracture Risk (SEMOF) study is a multicenter cohort study, which compared three QUSs for the assessment of hip fracture risk in a sample of 7609 elderly ambulatory women > or =70 years of age. Two QUSs measured the heel (Achilles+; GE-Lunar and Sahara; Hologic), and one measured the heel (DBM Sonic 1200; IGEA). The Cox proportional hazards regression was used to estimate the hazard of the first hip fracture, adjusted for age, BMI, and center, and the area under the ROC curves were calculated to compare the devices and their parameters. RESULTS: From the 7609 women who were included in the study, 7062 women 75.2 +/- 3.1 (SD) years of age were prospectively followed for 2.9 +/- 0.8 years. Eighty women reported a hip fracture. A decrease by 1 SD of the QUS variables corresponded to an increase of the hip fracture risk from 2.3 (95% CI, 1.7, 3.1) to 2.6 (95% CI, 1.9, 3.4) for the three variables of Achilles+ and from 2.2 (95% CI, 1.7, 3.0) to 2.4 (95% CI, 1.8, 3.2) for the three variables of Sahara. Risk gradients did not differ significantly among the variables of the two heel QUS devices. On the other hand, the phalanges QUS (DBM Sonic 1200) was not predictive of hip fracture risk, with an adjusted hazard risk of 1.2 (95% CI, 0.9, 1.5), even after reanalysis of the digitalized data and using different cut-off levels (1700 or 1570 m/s). CONCLUSIONS: In this elderly women population, heel QUS devices were both predictive of hip fracture risk, whereas the phalanges QUS device was not.

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The penetration, translocation, and distribution of ultrafine and nanoparticles in tissues and cells are challenging issues in aerosol research. This article describes a set of novel quantitative microscopic methods for evaluating particle distributions within sectional images of tissues and cells by addressing the following questions: (1) is the observed distribution of particles between spatial compartments random? (2) Which compartments are preferentially targeted by particles? and (3) Does the observed particle distribution shift between different experimental groups? Each of these questions can be addressed by testing an appropriate null hypothesis. The methods all require observed particle distributions to be estimated by counting the number of particles associated with each defined compartment. For studying preferential labeling of compartments, the size of each of the compartments must also be estimated by counting the number of points of a randomly superimposed test grid that hit the different compartments. The latter provides information about the particle distribution that would be expected if the particles were randomly distributed, that is, the expected number of particles. From these data, we can calculate a relative deposition index (RDI) by dividing the observed number of particles by the expected number of particles. The RDI indicates whether the observed number of particles corresponds to that predicted solely by compartment size (for which RDI = 1). Within one group, the observed and expected particle distributions are compared by chi-squared analysis. The total chi-squared value indicates whether an observed distribution is random. If not, the partial chi-squared values help to identify those compartments that are preferential targets of the particles (RDI > 1). Particle distributions between different groups can be compared in a similar way by contingency table analysis. We first describe the preconditions and the way to implement these methods, then provide three worked examples, and finally discuss the advantages, pitfalls, and limitations of this method.

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ABSTRACT: Nanotechnology in its widest sense seeks to exploit the special biophysical and chemical properties of materials at the nanoscale. While the potential technological, diagnostic or therapeutic applications are promising there is a growing body of evidence that the special technological features of nanoparticulate material are associated with biological effects formerly not attributed to the same materials at a larger particle scale. Therefore, studies that address the potential hazards of nanoparticles on biological systems including human health are required. Due to its large surface area the lung is one of the major sites of interaction with inhaled nanoparticles. One of the great challenges of studying particle-lung interactions is the microscopic visualization of nanoparticles within tissues or single cells both in vivo and in vitro. Once a certain type of nanoparticle can be identified unambiguously using microscopic methods it is desirable to quantify the particle distribution within a cell, an organ or the whole organism. Transmission electron microscopy provides an ideal tool to perform qualitative and quantitative analyses of particle-related structural changes of the respiratory tract, to reveal the localization of nanoparticles within tissues and cells and to investigate the 3D nature of nanoparticle-lung interactions.This article provides information on the applicability, advantages and disadvantages of electron microscopic preparation techniques and several advanced transmission electron microscopic methods including conventional, immuno and energy-filtered electron microscopy as well as electron tomography for the visualization of both model nanoparticles (e.g. polystyrene) and technologically relevant nanoparticles (e.g. titanium dioxide). Furthermore, we highlight possibilities to combine light and electron microscopic techniques in a correlative approach. Finally, we demonstrate a formal quantitative, i.e. stereological approach to analyze the distributions of nanoparticles in tissues and cells.This comprehensive article aims to provide a basis for scientists in nanoparticle research to integrate electron microscopic analyses into their study design and to select the appropriate microscopic strategy.

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Arabidopsis thaliana has emerged as a leading model species in plant genetics and functional genomics including research on the genetic causes of heterosis. We applied a triple testcross (TTC) design and a novel biometrical approach to identify and characterize quantitative trait loci (QTL) for heterosis of five biomass-related traits by (i) estimating the number, genomic positions, and genetic effects of heterotic QTL, (ii) characterizing their mode of gene action, and (iii) testing for presence of epistatic effects by a genomewide scan and marker x marker interactions. In total, 234 recombinant inbred lines (RILs) of Arabidopsis hybrid C24 x Col-0 were crossed to both parental lines and their F1 and analyzed with 110 single-nucleotide polymorphism (SNP) markers. QTL analyses were conducted using linear transformations Z1, Z2, and Z3 calculated from the adjusted entry means of TTC progenies. With Z1, we detected 12 QTL displaying augmented additive effects. With Z2, we mapped six QTL for augmented dominance effects. A one-dimensional genome scan with Z3 revealed two genomic regions with significantly negative dominance x additive epistatic effects. Two-way analyses of variance between marker pairs revealed nine digenic epistatic interactions: six reflecting dominance x dominance effects with variable sign and three reflecting additive x additive effects with positive sign. We conclude that heterosis for biomass-related traits in Arabidopsis has a polygenic basis with overdominance and/or epistasis being presumably the main types of gene action.

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Human experimental pain models require standardized stimulation and quantitative assessment of the evoked responses. This approach can be applied to healthy volunteers and pain patients before and after pharmacological interventions. Standardized stimuli of different modalities (ie, mechanical, chemical, thermal or electrical) can be applied to the skin, muscles and viscera for a differentiated and comprehensive assessment of various pain pathways and mechanisms. Using a multi-modal, multi-tissue approach, new and existing analgesic drugs can be profiled by their modulation of specific biomarkers. It has been shown that biomarkers, for example, those related to the central integration of repetitive nociceptive stimuli, can predict efficacy of a given drug in neuropathic pain conditions. Human experimental pain models can bridge animal and clinical pain research, and act as translational research providing new possibilities for designing successful clinical trials. Proof-of-concept studies provide cheap, fast and reliable information on dose-efficacy relationships and how pain sensed in the skin, muscles and viscera are inhibited.

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What motivates students to perform and pursue engineering design tasks? This study examines this question by way of three Learning Through Service (LTS) programs: 1) an on-going longitudinal study examining the impacts of service on engineering students, 2) an on-going analysis of an international senior design capstone program, and 3) an on-going evaluation of an international graduate-level research program. The evaluation of these programs incorporates both qualitative and quantitative methods, utilizing surveys, questionnaires, and interviews, which help to provide insight on what motivates students to do engineering design work. The quantitative methods were utilized in analyzing various instruments including: a Readiness assessment inventory, Intercultural Development Inventory, Sustainable Engineering through Service Learning survey, the Impacts of Service on Engineering Students’ survey, Motivational narratives, as well as some analysis for interview text. The results of these instruments help to provide some much needed insight on how prepared students are to participate in engineering programs. Additional qualitative methods include: Word clouds, Motivational narratives, as well as interview analysis. This thesis focused on how these instruments help to determine what motivates engineering students to pursue engineering design tasks. These instruments aim to collect some more in-depth information than the quantitative instruments will allow. Preliminary results suggest that of the 120 interviews analyzed Interest/Enjoyment, Application of knowledge and skills, as well as gaining knowledge are key motivating factors regardless of gender or academic level. Together these findings begin to shed light on what motivates students to perform engineering design tasks, which can be applied for better recruitment and retention in university programs.

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To analyze the impact of opacities in the optical pathway and image compression of 32-bit raw data to 8-bit jpg images on quantified optical coherence tomography (OCT) image analysis.

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PURPOSE: To correlate the dimension of the visual field (VF) tested by Goldman kinetic perimetry with the extent of visibility of the highly reflective layer between inner and outer segments of photoreceptors (IOS) seen in optical coherence tomography (OCT) images in patients with retinitis pigmentosa (RP). METHODS: In a retrospectively designed cross-sectional study, 18 eyes of 18 patients with RP were examined with OCT and Goldmann perimetry using test target I4e and compared with 18 eyes of 18 control subjects. A-scans of raw scan data of Stratus OCT images (Carl Zeiss Meditec, AG, Oberkochen, Germany) were quantitatively analyzed for the presence of the signal generated by the highly reflective layer between the IOS in OCT images. Starting in the fovea, the distance to which this signal was detectable was measured. Visual fields were analyzed by measuring the distance from the center point to isopter I4e. OCT and visual field data were analyzed in a clockwise fashion every 30 degrees , and corresponding measures were correlated. RESULTS: In corresponding alignments, the distance from the center point to isopter I4e and the distance to which the highly reflective signal from the IOS can be detected correlate significantly (r = 0.75, P < 0.0001). The greater the distance in VF, the greater the distance measured in OCT. CONCLUSIONS: The authors hypothesize that the retinal structure from which the highly reflective layer between the IOS emanates is of critical importance for visual and photoreceptor function. Further research is warranted to determine whether this may be useful as an objective marker of progression of retinal degeneration in patients with RP.

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PURPOSE: To identify and quantitate specific changes in optical coherence tomography (OCT) images of patients with type 2 idiopathic perifoveal telangiectasia (IPT). METHODS: In a prospectively designed, observational, case-control study, 28 eyes of 14 consecutive patients with IPT were examined with OCT and compared with eyes of 14 unaffected control subjects. Light reflectivity profiles of raw scan data of OCT images were quantitatively analyzed for differences in distance between different retinal reflectivity layers and their respective reflectivities. Maculae were examined in four separate regions: (1) central fovea, (2) nasal perifovea, (3) temporal perifovea, and (4) outside the fovea. RESULTS: Retinal thinning, shortening of the photoreceptor outer segments and loss of reflectivity of the photoreceptor ellipsoid region were found in the central foveal region as well as the nasal and temporal perifoveal regions in eyes with IPT. In addition, increased reflectivity of the outer nuclear layer was found in a sharply demarcated area of the inferotemporal perifoveal region in all affected eyes. Retinal tissue located more than 2000 mum away from the foveola was indistinguishable from that in normal eyes. CONCLUSIONS: Quantitative OCT analysis shows unique and specific changes in the photoreceptors of the central macula in IPT which can be detected from first clinical presentation. These changes may be of use as an additional diagnostic tool. Correlation of the findings in the outer nuclear layer with histologic studies may help identify the nature of the reflectivity increase and define more clearly the type of damage sustained by the photoreceptors in this condition.

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Methodological evaluation of the proteomic analysis of cardiovascular-tissue material has been performed with a special emphasis on establishing examinations that allow reliable quantitative analysis of silver-stained readouts. Reliability, reproducibility, robustness and linearity were addressed and clarified. In addition, several types of normalization procedures were evaluated and new approaches are proposed. It has been found that the silver-stained readout offers a convenient approach for quantitation if a linear range for gel loading is defined. In addition, a broad range of a 10-fold input (loading 20-200 microg per gel) fulfills the linearity criteria, although at the lowest input (20 microg) a portion of protein species will remain undetected. The method is reliable and reproducible within a range of 65-200 microg input. The normalization procedure using the sum of all spot intensities from a silver-stained 2D pattern has been shown to be less reliable than other approaches, namely, normalization through median or through involvement of interquartile range. A special refinement of the normalization through virtual segmentation of pattern, and calculation of normalization factor for each stratum provides highly satisfactory results. The presented results not only provide evidence for the usefulness of silver-stained gels for quantitative evaluation, but they are directly applicable to the research endeavor of monitoring alterations in cardiovascular pathophysiology.

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Multi-parametric and quantitative magnetic resonance imaging (MRI) techniques have come into the focus of interest, both as a research and diagnostic modality for the evaluation of patients suffering from mild cognitive decline and overt dementia. In this study we address the question, if disease related quantitative magnetization transfer effects (qMT) within the intra- and extracellular matrices of the hippocampus may aid in the differentiation between clinically diagnosed patients with Alzheimer disease (AD), patients with mild cognitive impairment (MCI) and healthy controls. We evaluated 22 patients with AD (n=12) and MCI (n=10) and 22 healthy elderly (n=12) and younger (n=10) controls with multi-parametric MRI. Neuropsychological testing was performed in patients and elderly controls (n=34). In order to quantify the qMT effects, the absorption spectrum was sampled at relevant off-resonance frequencies. The qMT-parameters were calculated according to a two-pool spin-bath model including the T1- and T2 relaxation parameters of the free pool, determined in separate experiments. Histograms (fixed bin-size) of the normalized qMT-parameter values (z-scores) within the anterior and posterior hippocampus (hippocampal head and body) were subjected to a fuzzy-c-means classification algorithm with downstreamed PCA projection. The within-cluster sums of point-to-centroid distances were used to examine the effects of qMT- and diffusion anisotropy parameters on the discrimination of healthy volunteers, patients with Alzheimer and MCIs. The qMT-parameters T2(r) (T2 of the restricted pool) and F (fractional pool size) differentiated between the three groups (control, MCI and AD) in the anterior hippocampus. In our cohort, the MT ratio, as proposed in previous reports, did not differentiate between MCI and AD or healthy controls and MCI, but between healthy controls and AD.