Testing for hereditary thrombophilia: a retrospective analysis of testing referred to a national laboratory

<p>Abstract</p> <p>Background</p> <p>Predisposition to venous thrombosis may be assessed through testing for defects and/or deficiencies of a number of hereditary factors. There is potential for confusion about which of these tests are appropriate in which settings. At least one set of recommendations has been published to guide such testing, but it is unclear how widely these have been disseminated.</p> <p>Methods</p> <p>We performed a retrospective analysis of laboratory orders and results at a national referral laboratory to gain insight into physicians' ordering practices, specifically comparing them against the ordering practices recommended by a 2002 College of American Pathologists (CAP) consensus conference on thrombophilia testing. Measurements included absolute and relative ordering volumes and positivity rates from approximately 200,000 thrombophilia tests performed from September 2005 through August 2006 at a national reference laboratory. Quality control data were used to estimate the proportion of samples that may have been affected by anticoagulant therapy. A sample of ordering laboratories was surveyed in order to assess potential measurement bias.</p> <p>Results</p> <p>Total antigen assays for protein C, protein S and antithrombin were ordered almost as frequently as functional assays for these analytes. The DNA test for factor V Leiden was ordered much more often than the corresponding functional assay. In addition, relative positivity rates coupled with elevations in prothrombin time (PT) in many of these patients suggest that these tests are often ordered in the setting of oral anticoagulant therapy.</p> <p>Conclusion</p> <p>In this real-world setting, testing for inherited thrombophilia is frequently at odds with the recommendations of the CAP consensus conference. There is a need for wider dissemination of concise thrombophilia testing guidelines.</p

Estimating uncertainty in ecosystem budget calculations

© The Authors, 2010. This article is distributed under the terms of the Creative Commons Attribution-Noncommercial License. The definitive version was published in Ecosystems 13 (2010): 239-248, doi:10.1007/s10021-010-9315-8.Ecosystem nutrient budgets often report values for pools and fluxes without any indication of uncertainty, which makes it difficult to evaluate the significance of findings or make comparisons across systems. We present an example, implemented in Excel, of a Monte Carlo approach to estimating error in calculating the N content of vegetation at the Hubbard Brook Experimental Forest in New Hampshire. The total N content of trees was estimated at 847 kg ha−1 with an uncertainty of 8%, expressed as the standard deviation divided by the mean (the coefficient of variation). The individual sources of uncertainty were as follows: uncertainty in allometric equations (5%), uncertainty in tissue N concentrations (3%), uncertainty due to plot variability (6%, based on a sample of 15 plots of 0.05 ha), and uncertainty due to tree diameter measurement error (0.02%). In addition to allowing estimation of uncertainty in budget estimates, this approach can be used to assess which measurements should be improved to reduce uncertainty in the calculated values. This exercise was possible because the uncertainty in the parameters and equations that we used was made available by previous researchers. It is important to provide the error statistics with regression results if they are to be used in later calculations; archiving the data makes resampling analyses possible for future researchers. When conducted using a Monte Carlo framework, the analysis of uncertainty in complex calculations does not have to be difficult and should be standard practice when constructing ecosystem budgets

Facilitating Joint Chaos and Fractal Analysis of Biosignals through Nonlinear Adaptive Filtering

Background: Chaos and random fractal theories are among the most important for fully characterizing nonlinear dynamics of complicated multiscale biosignals. Chaos analysis requires that signals be relatively noise-free and stationary, while fractal analysis demands signals to be non-rhythmic and scale-free. Methodology/Principal Findings: To facilitate joint chaos and fractal analysis of biosignals, we present an adaptive algorithm, which: (1) can readily remove nonstationarities from the signal, (2) can more effectively reduce noise in the signals than linear filters, wavelet denoising, and chaos-based noise reduction techniques; (3) can readily decompose a multiscale biosignal into a series of intrinsically bandlimited functions; and (4) offers a new formulation of fractal and multifractal analysis that is better than existing methods when a biosignal contains a strong oscillatory component. Conclusions: The presented approach is a valuable, versatile tool for the analysis of various types of biological signals. Its effectiveness is demonstrated by offering new important insights into brainwave dynamics and the very high accuracy in automatically detecting epileptic seizures from EEG signals

Assessment of clusters of transcription factor binding sites in relationship to human promoter, CpG islands and gene expression

BACKGROUND: Gene expression is regulated mainly by transcription factors (TFs) that interact with regulatory cis-elements on DNA sequences. To identify functional regulatory elements, computer searching can predict TF binding sites (TFBS) using position weight matrices (PWMs) that represent positional base frequencies of collected experimentally determined TFBS. A disadvantage of this approach is the large output of results for genomic DNA. One strategy to identify genuine TFBS is to utilize local concentrations of predicted TFBS. It is unclear whether there is a general tendency for TFBS to cluster at promoter regions, although this is the case for certain TFBS. Also unclear is the identification of TFs that have TFBS concentrated in promoters and to what level this occurs. This study hopes to answer some of these questions. RESULTS: We developed the cluster score measure to evaluate the correlation between predicted TFBS clusters and promoter sequences for each PWM. Non-promoter sequences were used as a control. Using the cluster score, we identified a PWM group called PWM-PCP, in which TFBS clusters positively correlate with promoters, and another PWM group called PWM-NCP, in which TFBS clusters negatively correlate with promoters. The PWM-PCP group comprises 47% of the 199 vertebrate PWMs, while the PWM-NCP group occupied 11 percent. After reducing the effect of CpG islands (CGI) against the clusters using partial correlation coefficients among three properties (promoter, CGI and predicted TFBS cluster), we identified two PWM groups including those strongly correlated with CGI and those not correlated with CGI. CONCLUSION: Not all PWMs predict TFBS correlated with human promoter sequences. Two main PWM groups were identified: (1) those that show TFBS clustered in promoters associated with CGI, and (2) those that show TFBS clustered in promoters independent of CGI. Assessment of PWM matches will allow more positive interpretation of TFBS in regulatory regions

Kinematics and dynamics for computer animation

This tutorial will focus on the physical principles of kinematics and dynamics. After explaining the basic equations for point masses and rigid bodies a new approach for the dynamic simulation of multi-linked models with wobbling mass is presented, which has led to new insight in the field of biomechanics, but which has not been used in computer animation so far

Copying you copying me:Interpersonal motor co-ordination influences automatic imitation

Moving in a co-ordinated fashion with another individual changes our behaviour towards them; we tend to like them more, find them more attractive, and are more willing to co-operate with them. It is generally assumed that this effect on behaviour results from alterations in representations of self and others. Specifically, through neurophysiological perception-action matching mechanisms, interpersonal motor co-ordination (IMC) is believed to forge a neural coupling between actor and observer, which serves to blur boundaries in conceptual self-other representations and causes positive views of the self to be projected onto others. An investigation into this potential neural mechanism is lacking, however. Moreover, the specific components of IMC that might influence this mechanism have not yet been specified. In the present study we exploited a robust behavioural phenomenon - automatic imitation - to assess the degree to which IMC influences neural action observation-execution matching mechanisms. This revealed that automatic imitation is reduced when the actions of another individual are perceived to be synchronised in time, but are spatially incongruent, with our own. We interpret our findings as evidence that IMC does indeed exert an effect on neural perception-action matching mechanisms, but this serves to promote better self-other distinction. Our findings demonstrate that further investigation is required to understand the complex relationship between neural perception-action coupling, conceptual self-other representations, and social behaviour

The risk of angiosarcoma following primary breast cancer

Lymphangiosarcoma of the upper extremity is a rare and aggressive tumour reported to occur following post-mastectomy lymphoedema (Stewart–Treves syndrome). Haemangiosarcoma, a related rare tumour, has occasionally been reported to occur in the breast following irradiation. We conducted a case-control study using the University of Southern California-Cancer Surveillance Program, the population-based cancer registry for Los Angeles County, to evaluate the relationship between invasive female breast cancer and subsequent upper extremity or chest lymphangiosarcoma and haemangiosarcoma together referred to as angiosarcoma. Cases were females diagnosed between 1972 and 1995 with angiosarcoma of the upper extremity (n = 20) or chest (n = 48) who were 25 years of age or older and residing in Los Angeles County when diagnosed. Other sarcomas at the same anatomic sites were also studied. Controls were females diagnosed with cancers other than sarcoma during the same time period (n = 266 444). Cases and controls were then compared with respect to history of a prior invasive epithelial breast cancer. A history of breast cancer increased the risk of upper extremity angiosarcoma by more than 59-fold (odds ratio [OR] = 59.3, 95% confidence interval [95% CI] = 21.9–152.8). A strong increase in risk after breast cancer was also observed for angiosarcoma of the chest and breast (OR = 11.6, 95% CI = 4.3–26.1) and for other sarcomas of the chest and breast (OR = 3.3, 95% CI = 1.1–1.7). © 1999 Cancer Research Campaig

A stable pattern of EEG spectral coherence distinguishes children with autism from neuro-typical controls - a large case control study

<p>Abstract</p> <p>Background</p> <p>The autism rate has recently increased to 1 in 100 children. Genetic studies demonstrate poorly understood complexity. Environmental factors apparently also play a role. Magnetic resonance imaging (MRI) studies demonstrate increased brain sizes and altered connectivity. Electroencephalogram (EEG) coherence studies confirm connectivity changes. However, genetic-, MRI- and/or EEG-based diagnostic tests are not yet available. The varied study results likely reflect methodological and population differences, small samples and, for EEG, lack of attention to group-specific artifact.</p> <p>Methods</p> <p>Of the 1,304 subjects who participated in this study, with ages ranging from 1 to 18 years old and assessed with comparable EEG studies, 463 children were diagnosed with autism spectrum disorder (ASD); 571 children were neuro-typical controls (C). After artifact management, principal components analysis (PCA) identified EEG spectral coherence factors with corresponding loading patterns. The 2- to 12-year-old subsample consisted of 430 ASD- and 554 C-group subjects (n = 984). Discriminant function analysis (DFA) determined the spectral coherence factors' discrimination success for the two groups. Loading patterns on the DFA-selected coherence factors described ASD-specific coherence differences when compared to controls.</p> <p>Results</p> <p>Total sample PCA of coherence data identified 40 factors which explained 50.8% of the total population variance. For the 2- to 12-year-olds, the 40 factors showed highly significant group differences (<it>P </it>< 0.0001). Ten randomly generated split half replications demonstrated high-average classification success (C, 88.5%; ASD, 86.0%). Still higher success was obtained in the more restricted age sub-samples using the jackknifing technique: 2- to 4-year-olds (C, 90.6%; ASD, 98.1%); 4- to 6-year-olds (C, 90.9%; ASD 99.1%); and 6- to 12-year-olds (C, 98.7%; ASD, 93.9%). Coherence loadings demonstrated reduced short-distance and reduced, as well as increased, long-distance coherences for the ASD-groups, when compared to the controls. Average spectral loading per factor was wide (10.1 Hz).</p> <p>Conclusions</p> <p>Classification success suggests a stable coherence loading pattern that differentiates ASD- from C-group subjects. This might constitute an EEG coherence-based phenotype of childhood autism. The predominantly reduced short-distance coherences may indicate poor local network function. The increased long-distance coherences may represent compensatory processes or reduced neural pruning. The wide average spectral range of factor loadings may suggest over-damped neural networks.</p

Plane-Parallel Radiance Transport for Global Illumination in Vegetation

This paper applies plane parallel radiance transport techniques to scattering from vegetation. The leaves, stems, and branches are represented as a volume density of scattering surfaces, depending only on height and the vertical component of the surface normal. Ordinary differential equations are written for the multiply scattered radiance as a function of the height above the ground, with the sky radiance and ground reflectance as boundary conditions. They are solved using a two-pass integration scheme to unify the two-point boundary conditions, and Fourier series for the dependence on the azimuthal angle. The resulting radiance distribution is used to precompute diffuse and specular `ambient` shading tables, as a function of height and surface normal, to be used in rendering, together with a z-buffer shadow algorithm for direct solar illumination