Diagnostic value of serum activin A and follistatin levels in women with peritoneal, ovarian and deep infiltrating endometriosis

Activin A is a growth factor, produced by the endometrium, whose actions are modulated by the binding protein follistatin. Both proteins are detectable in the peripheral serum and their concentrations may be increased in women with endometriosis. The present study was designed to evaluate whether serum levels of activin A and follistatin are altered, and therefore have a potential diagnostic value, in women with peritoneal, ovarian and deep infiltrating endometriosis. We performed a multicenter controlled study evaluating simultaneously serum activin A and follistatin concentrations in women with and without endometriosis. Women with endometriosis (n 139) were subdivided into three groups: peritoneal endometriosis (n 28); ovarian endometrioma (n 61) and deep infiltrating endometriosis (n 50). The control group (n 75) consisted of healthy women with regular menstrual cycles. Blood samples were collected from a peripheral vein and assayed for activin A and follistatin using commercially available enzyme immunoassay kits. The ovarian endometrioma group had serum activin A levels significantly higher than healthy controls (0.22 0.01 ng/ml versus 0.17 0.01 ng/ml, P 0.01). None of the endometriosis groups had serum follistatin levels which were significantly altered compared with healthy controls; however, levels found in the endometrioma group (2.34 0.32 ng/ml) were higher than that in the deep endometriosis group (1.50 0.17 ng/ml, P 0.05). The area under the receiver operating characteristic curve of activin A was 0.700 (95 confidence interval: 0.6050.794), while that of follistatin was 0.620 (95 confidence interval: 0.5100.730) for the diagnosis of ovarian endometrioma. The combination of both markers into a duo marker index did not improve significantly their diagnostic accuracy. The present study demonstrated that serum activin A and follistatin are not significantly altered in peritoneal or deep infiltrating endometriosis and have limited diagnostic accuracy in the diagnosis of ovarian endometrioma.

THE DEVELOPMENT AND EVALUATION OF SOFTWARE TO VERIFY DIAGNOSTIC ACCURACY

This article describes the development and evaluation of software that verifies the accuracy of diagnoses made by nursing students. The software was based on a model that uses fuzzy logic concepts, including PERL, the MySQL database for Internet accessibility, and the NANDA-I 2007-2008 classification system. The software was evaluated in terms of its technical quality and usability through specific instruments. The activity proposed in the software involves four stages in which students establish the relationship values between nursing diagnoses, defining characteristics/risk factors and clinical cases. The relationship values determined by students are compared to those of specialists, generating performance scores for the students. In the evaluation, the software demonstrated satisfactory outcomes regarding the technical quality and, according to the students, helped in their learning and may become an educational tool to teach the process of nursing diagnosis.

Prediction with measurement errors in finite populations

We address the problem of selecting the best linear unbiased predictor (BLUP) of the latent value (e.g., serum glucose fasting level) of sample subjects with heteroskedastic measurement errors. Using a simple example, we compare the usual mixed model BLUP to a similar predictor based on a mixed model framed in a finite population (FPMM) setup with two sources of variability, the first of which corresponds to simple random sampling and the second, to heteroskedastic measurement errors. Under this last approach, we show that when measurement errors are subject-specific, the BLUP shrinkage constants are based on a pooled measurement error variance as opposed to the individual ones generally considered for the usual mixed model BLUP. In contrast, when the heteroskedastic measurement errors are measurement condition-specific, the FPMM BLUP involves different shrinkage constants. We also show that in this setup, when measurement errors are subject-specific, the usual mixed model predictor is biased but has a smaller mean squared error than the FPMM BLUP which points to some difficulties in the interpretation of such predictors. (C) 2011 Elsevier By. All rights reserved.

Optical transition radiation used in the diagnostic of low energy and low current electron beams in particle accelerators

Optical transition radiation (OTR) plays an important role in beam diagnostics for high energy particle accelerators. Its linear intensity with beam current is a great advantage as compared to fluorescent screens, which are subject to saturation. Moreover, the measurement of the angular distribution of the emitted radiation enables the determination of many beam parameters in a single observation point. However, few works deals with the application of OTR to monitor low energy beams. In this work we describe the design of an OTR based beam monitor used to measure the transverse beam charge distribution of the 1.9-MeV electron beam of the linac injector of the IFUSP microtron using a standard vision machine camera. The average beam current in pulsed operation mode is of the order of tens of nano-Amps. Low energy and low beam current make OTR observation difficult. To improve sensitivity, the beam incidence angle on the target was chosen to maximize the photon flux in the camera field-of-view. Measurements that assess OTR observation (linearity with beam current, polarization, and spectrum shape) are presented, as well as a typical 1.9-MeV electron beam charge distribution obtained from OTR. Some aspects of emittance measurement using this device are also discussed. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4748519]

Influence Assessment in an Heteroscedastic Errors-in-Variables Model

The main goal of this article is to consider influence assessment in models with error-prone observations and variances of the measurement errors changing across observations. The techniques enable to identify potential influential elements and also to quantify the effects of perturbations in these elements on some results of interest. The approach is illustrated with data from the WHO MONICA Project on cardiovascular disease.

Homology and errors

A recent review of the homology concept in cladistics is critiqued in light of the historical literature. Homology as a notion relevant to the recognition of clades remains equivalent to synapomorphy. Some symplesiomorphies are homologies inasmuch as they represent synapomorphies of more inclusive taxa; others are complementary character states that do not imply any shared evolutionary history among the taxa that exhibit the state. Undirected character-state change (as characters optimized on an unrooted tree) is a necessary but not sufficient test of homology, because the addition of a root may alter parsimonious reconstructions. Primary and secondary homology are defended as realistic representations of discovery procedures in comparative biology, recognizable even in Direct Optimization. The epistemological relationship between homology as evidence and common ancestry as explanation is again emphasized. An alternative definition of homology is proposed. (c) The Willi Hennig Society 2012.

Respiratory inductive plethysmography: a comparative study between isovolume maneuver calibration and qualitative diagnostic calibration in healthy volunteers assessed in different positions

Objective: To compare two methods of respiratory inductive plethysmography (RIP) calibration in three different positions. Methods: We evaluated 28 healthy subjects (18 women and 10 men), with a mean age of 25.4 +/- 3.9 years. For all of the subjects, isovolume maneuver calibration (ISOCAL) and qualitative diagnostic calibration (QDC) were used in the orthostatic, sitting, and supine positions. In order to evaluate the concordance between the two calibration methods, we used ANOVA and Bland-Altman plots. Results: The values of the constant of proportionality (X) were significantly different between ISOCAL and QDC in the three positions evaluated: 1.6 +/- 0.5 vs. 2.0 +/- 1.2, in the supine position, 2.5 +/- 0.8 vs. 0.6 +/- 0.3 in the sitting position, and 2.0 +/- 0.8 vs. 0.6 +/- 0.3 in the orthostatic position (p < 0.05 for all). Conclusions: Our results suggest that QDC is an inaccurate method for the calibration of RIP. The K values obtained with ISOCAL reveal that RIP should be calibrated for each position evaluated.

Bayesian Analysis for Errors in Variables with Changepoint Models

Changepoint regression models have originally been developed in connection with applications in quality control, where a change from the in-control to the out-of-control state has to be detected based on the avaliable random observations. Up to now various changepoint models have been suggested for differents applications like reliability, econometrics or medicine. In many practical situations the covariate cannot be measured precisely and an alternative model are the errors in variable regression models. In this paper we study the regression model with errors in variables with changepoint from a Bayesian approach. From the simulation study we found that the proposed procedure produces estimates suitable for the changepoint and all other model parameters.

Brazilian guidelines for the application of transcranial ultrasound as a diagnostic test for the confirmation of brain death

Neurosonological studies, specifically transcranial Doppler (TCD) and transcranial color-coded duplex (TCCD), have high level of specificity and sensitivity and they are used as complementary tests for the diagnosis of brain death (BD). A group of experts, from the Neurosonology Department of the Brazilian Academy of Neurology, created a task force to determine the criteria for the following aspects of diagnosing BD in Brazil: the reliability of TCD methodology; the reliability of TCCD methodology; neurosonology training and skills; the diagnosis of encephalic circulatory arrest; and exam documentation for BD. The results of this meeting are presented in the current paper.

A General Latent Class Model for Performance Evaluation of Diagnostic Tests in the Absence of a Gold Standard: An Application to Chagas Disease

We propose a new general Bayesian latent class model for evaluation of the performance of multiple diagnostic tests in situations in which no gold standard test exists based on a computationally intensive approach. The modeling represents an interesting and suitable alternative to models with complex structures that involve the general case of several conditionally independent diagnostic tests, covariates, and strata with different disease prevalences. The technique of stratifying the population according to different disease prevalence rates does not add further marked complexity to the modeling, but it makes the model more flexible and interpretable. To illustrate the general model proposed, we evaluate the performance of six diagnostic screening tests for Chagas disease considering some epidemiological variables. Serology at the time of donation (negative, positive, inconclusive) was considered as a factor of stratification in the model. The general model with stratification of the population performed better in comparison with its concurrents without stratification. The group formed by the testing laboratory Biomanguinhos FIOCRUZ-kit (c-ELISA and rec-ELISA) is the best option in the confirmation process by presenting false-negative rate of 0.0002% from the serial scheme. We are 100% sure that the donor is healthy when these two tests have negative results and he is chagasic when they have positive results.

Flow Visualization with Quantified Spatial and Temporal Errors Using Edge Maps

Robust analysis of vector fields has been established as an important tool for deriving insights from the complex systems these fields model. Traditional analysis and visualization techniques rely primarily on computing streamlines through numerical integration. The inherent numerical errors of such approaches are usually ignored, leading to inconsistencies that cause unreliable visualizations and can ultimately prevent in-depth analysis. We propose a new representation for vector fields on surfaces that replaces numerical integration through triangles with maps from the triangle boundaries to themselves. This representation, called edge maps, permits a concise description of flow behaviors and is equivalent to computing all possible streamlines at a user defined error threshold. Independent of this error streamlines computed using edge maps are guaranteed to be consistent up to floating point precision, enabling the stable extraction of features such as the topological skeleton. Furthermore, our representation explicitly stores spatial and temporal errors which we use to produce more informative visualizations. This work describes the construction of edge maps, the error quantification, and a refinement procedure to adhere to a user defined error bound. Finally, we introduce new visualizations using the additional information provided by edge maps to indicate the uncertainty involved in computing streamlines and topological structures.

Serologic and molecular diagnostic and bioassay in mice for detection of Toxoplasma gondii in free ranges chickens from Pantanal of Mato Grosso do Sul

Holsback L., Pena H.F.J., Ragozo A., Lopes E. G., Gennari S. M. & Soares R. M. 2012. Serologic and molecular diagnostic and bioassay in mice for detection of Toxoplasma gondii in free range chickens from Pantanal of Mato Grosso do Sul. Pesquisa Veterinaria Brasileira 32(8): 721-726. Setor de Veterinaria e Producao Animal, Universidade Estadual do Norte do Parana, Campus Luiz Meneghel, Rodovia BR 369 Km 54, Bandeirantes, PR 86360-000, Brazil. E-mail: lhsfertonani@uenp.edu.br The aim of this study was to investigate the occurrence of Toxoplasma gondii and compare the results obtained in the Modified Agglutination Test (MAT), Polimerase Chain Reaction (PCR) and bioassay in mice. In order to accomplish this, 40 free-range chickens from eight farms in neighboring areas to the Pantanal in Nhecolandia, Mato Grosso do Sul, were euthanized and blood samples, brain and heart were collected. The occurrence of anti-T. gondii antibodies found in chickens was 67.5% (27 samples), considering as a cutoff point the dilution 1:5. Among the samples analyzed, 7 (25.9%) were positive in the dilution 1: 5, 3 (11.1%) in 1: 10, 2 (7.4%) in 1: 20, 3 (11.1%) in 1: 320, 1 (3.7%) in 1: 640, 3 (11.1%) in 1: 1280, 2 (7.4%) in 1: 2560, 4 (14.8%) in 1: 5120 and 2 (7.4%) in 1: 10.240. From the mixture of tissue samples (brain and heart) from the chickens analyzed, 16 (40%) presented electrophoretic bands compatible with T. gondii by PCR (gene B1). In the comparison of techniques, 59.26% positivity in PCR was revealed among animals that were seropositive in MAT (cutoff 1: 5). From 141 inoculated mice, six (4.44%) died of acute toxoplasmosis between 15 and 23 days after inoculation. Surviving mice were sacrificed at 74 days after inoculation, and a total of 28 cysts were found in the brains of 10 distinct groups. From the seropositive hens, 27 bioassays were performed and 11 (40.7%) isolates were obtained. A greater number of isolations happened in mice that were inoculated with tissues from chickens that had high titers for anti-T. gondii antibodies. Chronic infection in mice was observed in nine groups (33.3%) from five different properties. Among the surviving mice, 25.6% were positive for T. gondii in MAT (1: 25). From mice positive in PCR, 87.5% were also positive in MAT. Among the PCR-negative mice, 5.2% were positive for T. gondii in MAT. It can be concluded through this study that the occurrence of infecton by T. gondii in the rural properties studied was high, that PCR directed to gene B1 does not confirm the viability of the parasite, but it can be used as a screening method for the selection of chickens infected by T. gondii, that the animals with titer greater than 10 must be prioritized for the selection of animals for bioassay, since for them, the chances of isolating the parasite are greater and that seroconversion in experimentally infected mice is not a good indicator for isolating the agent.

Competing regression models for longitudinal data

The choice of an appropriate family of linear models for the analysis of longitudinal data is often a matter of concern for practitioners. To attenuate such difficulties, we discuss some issues that emerge when analyzing this type of data via a practical example involving pretestposttest longitudinal data. In particular, we consider log-normal linear mixed models (LNLMM), generalized linear mixed models (GLMM), and models based on generalized estimating equations (GEE). We show how some special features of the data, like a nonconstant coefficient of variation, may be handled in the three approaches and evaluate their performance with respect to the magnitude of standard errors of interpretable and comparable parameters. We also show how different diagnostic tools may be employed to identify outliers and comment on available software. We conclude by noting that the results are similar, but that GEE-based models may be preferable when the goal is to compare the marginal expected responses.

Auriculo-Condylar Syndrome. Confronting a Diagnostic Challenge

Auriculo-condylar syndrome (ACS) is characterized by typical ears malformation (so-called "question mark" ears), prominent cheeks, microstomia, and abnormality of the temporomandibular joint and condyle of the mandible. In this report we describe a new simplex case and a previously unreported family with affected individuals in three generations documenting clinical variability. Linkage study for markers located in candidate region for ACS1 (1p21.1-q23.3) was excluded in our familial case, reinforcing the hypothesis of genetic heterogeneity for this condition. A review of the literature focusing diagnostic criteria and features of ACS was performed. (C) 2011 Wiley Periodicals, Inc.

Software Application That Evaluates the Diagnostic Accuracy of Nursing Students

PURPOSE: Apply the educational software Fuzzy Kitten with undergraduate Brazilian nursing students. METHODS: This software, based on fuzzy logic, generates performance scores that evaluate the ability to identify defining characteristics/risk factors present in clinical cases, relate them with nursing diagnoses, and determine the diagnoses freely or using a decision support model. FINDINGS: There were differences in student performance compared to the year of the course. The time to perform the activity did not present a significant relation to the performance. The students' scores in the diagnoses indicated by the model was superior (p = .01). CONCLUSIONS: The software was able to evaluate the diagnostic accuracy of students. IMPLICATIONS: The software enables an objective evaluation of diagnostic accuracy.