The impact of measurement errors in the identification of regulatory networks

Background: There are several studies in the literature depicting measurement error in gene expression data and also, several others about regulatory network models. However, only a little fraction describes a combination of measurement error in mathematical regulatory networks and shows how to identify these networks under different rates of noise. Results: This article investigates the effects of measurement error on the estimation of the parameters in regulatory networks. Simulation studies indicate that, in both time series (dependent) and non-time series (independent) data, the measurement error strongly affects the estimated parameters of the regulatory network models, biasing them as predicted by the theory. Moreover, when testing the parameters of the regulatory network models, p-values computed by ignoring the measurement error are not reliable, since the rate of false positives are not controlled under the null hypothesis. In order to overcome these problems, we present an improved version of the Ordinary Least Square estimator in independent (regression models) and dependent (autoregressive models) data when the variables are subject to noises. Moreover, measurement error estimation procedures for microarrays are also described. Simulation results also show that both corrected methods perform better than the standard ones (i.e., ignoring measurement error). The proposed methodologies are illustrated using microarray data from lung cancer patients and mouse liver time series data. Conclusions: Measurement error dangerously affects the identification of regulatory network models, thus, they must be reduced or taken into account in order to avoid erroneous conclusions. This could be one of the reasons for high biological false positive rates identified in actual regulatory network models.

Influence of hardness of the harder body on wear regime transition in a sliding pair of steels

In the unlubricated sliding wear of steels the mild-severe and severe-mild wear transitions have long been investigated. The effect of system inputs such as normal load, sliding speed, environment humidity and temperature, material properties, among others, on those transitions have also been studied. Although transitions seem to be caused by microstructural changes, surfaces oxidation and work-hardening, some questions remain regarding the way each aspect is involved. Since the early studies in sliding wear, it has usually been assumed that only the material properties of the softer body influence the wear behavior of contacting surfaces. For example, the Archard equation involves only the hardness of the softer body, without considering the hardness of the harder body. This work aims to discuss the importance of the harder body hardness in determining the wear regime operation. For this, pin-on-disk wear tests were carried out, in which the disk material was always harder than the pin material. Variations of the friction force and vertical displacement of the pin were registered during the tests. A material characterization before and after tests was conducted using stereoscopy and scanning electron microscopy (SEM) methods, in addition to mass loss, surface roughness and microhardness measurements. The wear results confirmed the occurrence of a mild-severe wear transition when the disk hardness was decreased. The disk hardness to pin hardness ratio (H(d)/H(p)) was used as a criterion to establish the nature of surface contact deformation and to determine the wear regime transition. A predominantly elastic or plastic contact, characterized by H(d)/H(p) values higher or lower than one, results in a mild or severe wear regime operation, respectively. (c) 2009 Elsevier B.V. All rights reserved.

Comparison of Quantitative T-Wave Alternans Profiles of Healthy Subjects and ICD Patients

Background: Current relevance of T-wave alternans is based on its association with electrical disorder and elevated cardiac risk. Quantitative reports would improve understanding on TWA augmentation mechanisms during mental stress or prior to tachyarrhythmias. However, little information is available about quantitative TWA values in clinical populations. This study aims to create and compare TWA profiles of healthy subjects and ICD patients, evaluated on treadmill stress protocols. Methods: Apparently healthy subjects, not in use of any medication were recruited. All eligible ICD patients were capable of performing an attenuated stress test. TWA analysis was performed during a 15-lead treadmill test. The derived comparative profile consisted of TWA amplitude and its associated heart rate, at rest (baseline) and at peak TWA value. Chi-square or Mann-Whitney tests were used with p values <= 0.05. Discriminatory performance was evaluated by a binary logistic regression model. Results: 31 healthy subjects (8F, 23M) and 32 ICD patients (10F, 22M) were different on baseline TWA (1 +/- 2 mu V; 8 +/- 9 mu V; p < 0.001) and peak TWA values (26 +/- 13 mu V; 37 +/- 20 mu V; p = 0,009) as well as on baseline TWA heart rate (79 +/- 10 bpm; 67 +/- 15 bpm; p < 0.001) and peak TWA heart rate (118 +/- 8 bpm; 90 +/- 17 bpm; p < 0.001). The logistic model yielded sensitivity and specificity values of 88.9% and 92.9%, respectively. Conclusions: Healthy subjects and ICD patients have distinct TWA profiles. The new TWA profile representation (in amplitude-heart rate pairs) may help comparison among different research protocols. Ann Noninvasive Electrocardiol 2009;14(2):108-118.

Strategies for genetic model specification in the screening of genome-wide meta-analysis signals for further replication

Background Meta-analysis is increasingly being employed as a screening procedure in large-scale association studies to select promising variants for follow-up studies. However, standard methods for meta-analysis require the assumption of an underlying genetic model, which is typically unknown a priori. This drawback can introduce model misspecifications, causing power to be suboptimal, or the evaluation of multiple genetic models, which augments the number of false-positive associations, ultimately leading to waste of resources with fruitless replication studies. We used simulated meta-analyses of large genetic association studies to investigate naive strategies of genetic model specification to optimize screenings of genome-wide meta-analysis signals for further replication. Methods Different methods, meta-analytical models and strategies were compared in terms of power and type-I error. Simulations were carried out for a binary trait in a wide range of true genetic models, genome-wide thresholds, minor allele frequencies (MAFs), odds ratios and between-study heterogeneity (tau(2)). Results Among the investigated strategies, a simple Bonferroni-corrected approach that fits both multiplicative and recessive models was found to be optimal in most examined scenarios, reducing the likelihood of false discoveries and enhancing power in scenarios with small MAFs either in the presence or in absence of heterogeneity. Nonetheless, this strategy is sensitive to tau(2) whenever the susceptibility allele is common (MAF epsilon 30%), resulting in an increased number of false-positive associations compared with an analysis that considers only the multiplicative model. Conclusion Invoking a simple Bonferroni adjustment and testing for both multiplicative and recessive models is fast and an optimal strategy in large meta-analysis-based screenings. However, care must be taken when examined variants are common, where specification of a multiplicative model alone may be preferable.

The Bypass Angioplasty Revascularization Investigation 2 Diabetes Randomized Trial of Different Treatment Strategies in Type 2 Diabetes Mellitus With Stable Ischemic Heart Disease Impact of Treatment Strategy on Cardiac Mortality and Myocardial Infarction

Background-The Bypass Angioplasty Revascularization Investigation 2 Diabetes (BARI 2D) trial in 2368 patients with stable ischemic heart disease assigned before randomization to percutaneous coronary intervention or coronary artery bypass grafting strata reported similar 5-year all-cause mortality rates with insulin sensitization versus insulin provision therapy and with a strategy of prompt initial coronary revascularization and intensive medical therapy or intensive medical therapy alone with revascularization reserved for clinical indication(s). In this report, we examine the predefined secondary end points of cardiac death and myocardial infarction (MI). Methods and Results-Outcome data were analyzed by intention to treat; the Kaplan-Meier method was used to assess 5-year event rates. Nominal P values are presented. During an average 5.3-year follow-up, there were 316 deaths (43% were attributed to cardiac causes) and 279 first MI events. Five-year cardiac mortality did not differ between revascularization plus intensive medical therapy (5.9%) and intensive medical therapy alone groups (5.7%; P = 0.38) or between insulin sensitization (5.7%) and insulin provision therapy (6%; P = 0.76). In the coronary artery bypass grafting stratum (n = 763), MI events were significantly less frequent in revascularization plus intensive medical therapy versus intensive medical therapy alone groups (10.0% versus 17.6%; P = 0.003), and the composite end points of all-cause death or MI (21.1% versus 29.2%; P = 0.010) and cardiac death or MI (P = 0.03) were also less frequent. Reduction in MI (P = 0.001) and cardiac death/MI (P = 0.002) was significant only in the insulin sensitization group. Conclusions-In many patients with type 2 diabetes mellitus and stable ischemic coronary disease in whom angina symptoms are controlled, similar to those enrolled in the percutaneous coronary intervention stratum, intensive medical therapy alone should be the first-line strategy. In patients with more extensive coronary disease, similar to those enrolled in the coronary artery bypass grafting stratum, prompt coronary artery bypass grafting, in the absence of contraindications, intensive medical therapy, and an insulin sensitization strategy appears to be a preferred therapeutic strategy to reduce the incidence of MI. Clinical Trial Registration-URL: http://www.clinicaltrials.gov. Unique identifier: NCT00006305. (Circulation. 2009;120:2529-2540.)

The relationship between prevalent medial meniscal intrasubstance signal changes and incident medial meniscal tears in women over a 1-year period assessed with 3.0 T MRI

Objective Intrasubstance meniscal signal changes not reaching the articular surface on fast spin echo (FSE) sequences are considered to represent mucoid degeneration on MRI. The aim of this study was to evaluate the association of prevalent intrasubstance signal changes with incident tears of the medial meniscus detected on 3.0 T MRI over a 1-year period. Materials and methods A total of 161 women aged a parts per thousand yen40 years participated in a longitudinal 1-year observational study of knee osteoarthritis. MRI (3.0 T) was performed at baseline and 12-month follow-up. The anterior horn, body, and posterior horn of the medial meniscus were scored by two experienced musculoskeletal radiologists using the Boston-Leeds Osteoarthritis Knee Score (BLOKS) system. Four grades were used to describe the meniscal morphology: grade 0 (normal), grade 1 (intrasubstance signal changes not reaching the articular surface), grade 2 (single tears), and grade 3 (complex tears and maceration). Fisher`s exact test and the Cochran-Armitage trend test were performed to evaluate whether baseline intrasubstance signal changes (grade 1) predict incident meniscal tears/maceration (grades 2 and/or 3) in the same subregion of the medial meniscus, when compared to subregions without pathology as the reference group (grade 0). Results Medial meniscal intrasubstance signal changes at baseline did not predict tears at follow-up when evaluating the anterior and posterior horns (left-sided p-values 0.06 and 0.59, respectively). No incident tears were detected in the body. Conclusion We could not demonstrate an association between prevalent medial meniscal intrasubstance signal changes with incident tears over a 1-year period.

Improved likelihood inference in Birnbaum-Saunders regressions

The Birnbaum-Saunders regression model is commonly used in reliability studies. We address the issue of performing inference in this class of models when the number of observations is small. Our simulation results suggest that the likelihood ratio test tends to be liberal when the sample size is small. We obtain a correction factor which reduces the size distortion of the test. Also, we consider a parametric bootstrap scheme to obtain improved critical values and improved p-values for the likelihood ratio test. The numerical results show that the modified tests are more reliable in finite samples than the usual likelihood ratio test. We also present an empirical application. (C) 2009 Elsevier B.V. All rights reserved.

Use of Metals and Anion Species with Chemometrics Tools for Classification of Unprocessed and Processed Coconut Waters

Coconut water is a natural isotonic, nutritive, and low-caloric drink. Preservation process is necessary to increase its shelf life outside the fruit and to improve commercialization. However, the influence of the conservation processes, antioxidant addition, maturation time, and soil where coconut is cultivated on the chemical composition of coconut water has had few arguments and studies. For these reasons, an evaluation of coconut waters (unprocessed and processed) was carried out using Ca, Cu, Fe, K, Mg, Mn, Na, Zn, chloride, sulfate, phosphate, malate, and ascorbate concentrations and chemometric tools. The quantitative determinations were performed by electrothermal atomic absorption spectrometry, inductively coupled plasma optical emission spectrometry, and capillary electrophoresis. The results showed that Ca, K, and Zn concentrations did not present significant alterations between the samples. The ranges of Cu, Fe, Mg, Mn, PO (4) (3-) , and SO (4) (2-) concentrations were as follows: Cu (3.1-120 A mu g L(-1)), Fe (60-330 A mu g L(-1)), Mg (48-123 mg L(-1)), Mn (0.4-4.0 mg L(-1)), PO (4) (3-) (55-212 mg L(-1)), and SO (4) (2-) (19-136 mg L(-1)). The principal component analysis (PCA) and hierarchical cluster analysis (HCA) were applied to differentiate unprocessed and processed samples. Multivariated analysis (PCA and HCA) were compared through one-way analysis of variance with Tukey-Kramer multiple comparisons test, and p values less than 0.05 were considered to be significant.

Ion pair stabilization effects on a series of procaine structural analogs

In this work, a series of 10 structural procaine analogs have been synthesized in order to investigate the structural features affecting the stability of ion pair formation and its influence on the lipophilicity of ionizable compounds. The structural variation within this series was focused on the terminal nitrogen substituents and on the intermediate chain linkage nature. The hydrophobic parameters log P(n) and log P(i) (partition coefficient of the neutral and ionic species, respectively), as well as the ionization constants pK(a) and pK(a)(oct), were obtained from log D-pH profiles measured at pH values ranging from 2 to 12. The difference between log P(i) and log P(n) values (i.e. difflog P) of each prepared compound was considered a measure of the stability of ion pair formation. In this set, the difflog P values varied nearly over one log unit, ranging from -2.40 to -3.37. It has been observed that the presence of hydrogen bonding groups (especially donor) and low steric hindrance around the terminal amine ionizable group increases the relative lipophilicity of the ionic species as compared to the corresponding neutral species. These results were interpreted as due to the increased stability of ion pairs of the compounds bearing these structural features. (C) 2010 Elsevier B.V. All rights reserved.

Haplotype distribution of five nuclear genes based on network genealogies and Bayesian inference indicates that Trypanosoma cruzi hybrid strains are polyphyletic

Chagas disease is still a major public health problem in Latin America. Its causative agent, Trypanosoma cruzi, can be typed into three major groups, T. cruzi I, T. cruzi II and hybrids. These groups each have specific genetic characteristics and epidemiological distributions. Several highly virulent strains are found in the hybrid group; their origin is still a matter of debate. The null hypothesis is that the hybrids are of polyphyletic origin, evolving independently from various hybridization events. The alternative hypothesis is that all extant hybrid strains originated from a single hybridization event. We sequenced both alleles of genes encoding EF-1 alpha, actin and SSU rDNA of 26 T. cruzi strains and DHFR-TS and TR of 12 strains. This information was used for network genealogy analysis and Bayesian phylogenies. We found T. cruzi I and T. cruzi II to be monophyletic and that all hybrids had different combinations of T. cruzi I and T. cruzi II haplotypes plus hybrid-specific haplotypes. Bootstrap values (networks) and posterior probabilities (Bayesian phylogenies) of clades supporting the monophyly of hybrids were far below the 95% confidence interval, indicating that the hybrid group is polyphyletic. We hypothesize that T. cruzi I and T. cruzi II are two different species and that the hybrids are extant representatives of independent events of genome hybridization, which sporadically have sufficient fitness to impact on the epidemiology of Chagas disease.

Using Bayesian networks with rule extraction to infer the risk of weed infestation in a corn-crop

This paper describes the modeling of a weed infestation risk inference system that implements a collaborative inference scheme based on rules extracted from two Bayesian network classifiers. The first Bayesian classifier infers a categorical variable value for the weed-crop competitiveness using as input categorical variables for the total density of weeds and corresponding proportions of narrow and broad-leaved weeds. The inferred categorical variable values for the weed-crop competitiveness along with three other categorical variables extracted from estimated maps for the weed seed production and weed coverage are then used as input for a second Bayesian network classifier to infer categorical variables values for the risk of infestation. Weed biomass and yield loss data samples are used to learn the probability relationship among the nodes of the first and second Bayesian classifiers in a supervised fashion, respectively. For comparison purposes, two types of Bayesian network structures are considered, namely an expert-based Bayesian classifier and a naive Bayes classifier. The inference system focused on the knowledge interpretation by translating a Bayesian classifier into a set of classification rules. The results obtained for the risk inference in a corn-crop field are presented and discussed. (C) 2009 Elsevier Ltd. All rights reserved.

Multicollinearity and financial constraint in investment decisions: a Bayesian generalized ridge regression

This paper addresses the investment decisions considering the presence of financial constraints of 373 large Brazilian firms from 1997 to 2004, using panel data. A Bayesian econometric model was used considering ridge regression for multicollinearity problems among the variables in the model. Prior distributions are assumed for the parameters, classifying the model into random or fixed effects. We used a Bayesian approach to estimate the parameters, considering normal and Student t distributions for the error and assumed that the initial values for the lagged dependent variable are not fixed, but generated by a random process. The recursive predictive density criterion was used for model comparisons. Twenty models were tested and the results indicated that multicollinearity does influence the value of the estimated parameters. Controlling for capital intensity, financial constraints are found to be more important for capital-intensive firms, probably due to their lower profitability indexes, higher fixed costs and higher degree of property diversification.

Mitochondrial sequence data and Dipsacales phylogeny: Mixed models, partitioned Bayesian analyses, and model selection

Phylogenetic analyses of chloroplast DNA sequences, morphology, and combined data have provided consistent support for many of the major branches within the angiosperm, clade Dipsacales. Here we use sequences from three mitochondrial loci to test the existing broad scale phylogeny and in an attempt to resolve several relationships that have remained uncertain. Parsimony, maximum likelihood, and Bayesian analyses of a combined mitochondrial data set recover trees broadly consistent with previous studies, although resolution and support are lower than in the largest chloroplast analyses. Combining chloroplast and mitochondrial data results in a generally well-resolved and very strongly supported topology but the previously recognized problem areas remain. To investigate why these relationships have been difficult to resolve we conducted a series of experiments using different data partitions and heterogeneous substitution models. Usually more complex modeling schemes are favored regardless of the partitions recognized but model choice had little effect on topology or support values. In contrast there are consistent but weakly supported differences in the topologies recovered from coding and non-coding matrices. These conflicts directly correspond to relationships that were poorly resolved in analyses of the full combined chloroplast-mitochondrial data set. We suggest incongruent signal has contributed to our inability to confidently resolve these problem areas. (c) 2007 Elsevier Inc. All rights reserved.

Are torque values of preadjusted brackets precise?

OBJECTIVE: The aim of the present study was to verify the torque precision of metallic brackets with MBT prescription using the canine brackets as the representative sample of six commercial brands. MATERIAL AND METHODS: Twenty maxillary and 20 mandibular canine brackets of one of the following commercial brands were selected: 3M Unitek, Abzil, American Orthodontics, TP Orthodontics, Morelli and Ortho Organizers. The torque angle, established by reference points and lines, was measured by an operator using an optical microscope coupled to a computer. The values were compared to those established by the MBT prescription. RESULTS: The results showed that for the maxillary canine brackets, only the Morelli torque (-3.33º) presented statistically significant difference from the proposed values (-7º). For the mandibular canines, American Orthodontics (-6.34º) and Ortho Organizers (-6.25º) presented statistically significant differences from the standards (-6º). Comparing the brands, Morelli presented statistically significant differences in comparison with all the other brands for maxillary canine brackets. For the mandibular canine brackets, there was no statistically significant difference between the brands. CONCLUSIONS: There are significant variations in torque values of some of the brackets assessed, which would clinically compromise the buccolingual positioning of the tooth at the end of orthodontic treatment.

Bone response to a Ca- and P-enriched titanium surface obtained by anodization

This study evaluated bone response to a Ca- and P- enriched titanium (Ti) surface treated by a multiphase anodic spark deposition coating (BSP-AK). Two mongrel dogs received bilateral implantation of 3 Ti cylinders (4.1 x 12 mm) in the humerus, being either BSP-AK treated or untreated (machined - control). At 8 weeks postimplantation, bone fragments containing the implants were harvested and processed for histologic and histomorphometric analyses. Bone formation was observed in cortical area and towards the medullary canal associated to approximately 1/3 of implant extension. In most cases, in the medullary area, collagen fiber bundles were detected adjacent and oriented parallel to Ti surfaces. Such connective tissue formation exhibited focal areas of mineralized matrix lined by active osteoblasts. The mean percentages of bone-to-implant contact were 2.3 (0.0-7.2 range) for BSP-AK and 0.4 (0.0-1.3 range) for control. Although the Mann-Whitney test did not detect statistically significant differences between groups, these results indicate a trend of BSP-AK treated surfaces to support contact osteogenesis in an experimental model that produces low bone-to-implant contact values.