Acquisition of Serum Antibodies Reactive With Enterohemorrhagic Escherichia coli Virulence-Associated Factors by Healthy Brazilian Children and Adults

Background: Patients with hemorrhagic colitis or hemolytic uremic syndrome due to enterohemorrhagic Escherichia coli (EHEC) develop serum IgM and IgG response to lipopolysaccharide (LPS) and to virulence factors such as intimin. The small numbers of cases of diarrhea associated with EHEC strains in Brazil suggests a pre-existing immunity probably due to previous contact with diarrheagenic E. coli. Our aim was to evaluate the development of the serum antibody repertoire to EHEC virulence factors in Brazilian children and adults. Methods: Serum IgM and IgG antibodies were determined by enzyme-linked immunosorbent assay with LPS O111, LPS O26, and LPS O157 in 101 children between 2 months and 10 years of age and in 100 adult sera, by immunoblotting with protein membrane extracts and purified beta intimin; the ability of adult sera to neutralize Shiga toxin2 was also investigated. Results: Children older than 24 months had IgM concentrations reactive with the 3 LPS equivalent to those seen in the adult group, and significantly higher than the group of younger children (P < 0.05). Anti-O26 and anti-O157 LPS IgG concentrations were equivalent between the 2 groups of children and were significantly different from the adult group (P < 0.05). The anti-O111 LPS IgG levels in older children were intermediate between the younger group, and adults (P < 0.05). Immunoblotting revealed strong protein reactivity, including the conserved and variable regions of beta intimin and more than 50% of the adult samples neutralized Shiga toxin 2. Conclusions: Our results demonstrate an increasing anti-LPS and antiprotein antibody response with age, which could provide protection against EHEC infections.

Atypical enteropathogenic Escherichia coli genomic background allows the acquisition of non-EPEC virulence factors

Atypical enteropathogenic Escherichia coli (aEPEC) has been associated with infantile diarrhea in many countries. The clonal structure of aEPEC is the object of active investigation but few works have dealt with its genetic relationship with other diarrheagenic E. coli (DEC). This study aimed to evaluate the genetic relationship of aEPEC with other DEC pathotypes. The phylogenetic relationships of DEC strains were evaluated by multilocus sequence typing. Genetic diversity was assessed by pulsed-field gel electrophoresis (PFGE). The phylogram showed that aEPEC strains were distributed in four major phylogenetic groups (A, B1, B2 and D). Cluster I ( group B1) contains the majority of the strains and other pathotypes [enteroaggregative, enterotoxigenic and enterohemorrhagic E. coli ( EHEC)]; cluster II ( group A) also contains enteroaggregative and diffusely adherent E. coli; cluster III ( group B2) has atypical and typical EPEC possessing H6 or H34 antigen; and cluster IV ( group D) contains aEPEC O55:H7 strains and EHEC O157:H7 strains. PFGE analysis confirmed that these strains encompass a great genetic diversity. These results indicate that aEPEC clonal groups have a particular genomic background - especially the strains of phylogenetic group B1 that probably made possible the acquisition and expression of virulence factors derived from non-EPEC pathotypes.

A population-based morphometric MRI study in patients with first-episode psychotic bipolar disorder: comparison with geographically matched healthy controls and major depressive disorder subjects

Objectives: Many morphometric magnetic resonance imaging (MRI) studies that have investigated the presence of gray matter (GM) volume abnormalities associated with the diagnosis of bipolar disorder (BD) have reported conflicting findings. None of these studies has compared patients with recent-onset psychotic BD with asymptomatic controls selected from exactly the same environment using epidemiological methods, or has directly contrasted BD patients against subjects with first-onset psychotic major depressive disorder (MDD). We examined structural brain differences between (i) BD (type I) subjects and MDD subjects with psychotic features in their first contact with the healthcare system in Brazil, and (ii) these two mood disorder groups relative to a sample of geographically matched asymptomatic controls. Methods: A total of 26 BD subjects, 20 subjects with MDD, and 94 healthy controls were examined using either of two identical MRI scanners and acquisition protocols. Diagnoses were based on DSM-IV criteria and confirmed one year after brain scanning. Image processing was conducted using voxel-based morphometry. Results: The BD group showed increased volume of the right dorsal anterior cingulate cortex relative to controls, while the MDD subjects exhibited bilateral foci GM deficits in the dorsolateral prefrontal cortex (p < 0.05, corrected for multiple comparisons). Direct comparison between BD and MDD patients showed a focus of GM reduction in the right-sided dorsolateral prefrontal cortex (p < 0.05, corrected for multiple comparisons) and a trend (p < 0.10, corrected) toward left-sided GM deficits in the dorsolateral prefrontal cortex of MDD patients. When analyses were repeated with scanner site as a confounding covariate the finding of increased right anterior cingulate volumes in BD patients relative to controls remained statistically significant (p = 0.01, corrected for multiple comparisons). Conclusions: These findings reinforce the view that there are important pathophysiological distinctions between BD and MDD, and indicate that subtle dorsal anterior cingulate abnormalities may be relevant to the pathophysiology of BD.

Distinct resistance mutation and polymorphism acquisition in HIV-1 protease of subtypes B and F1 from children and adult patients under virological failure

The goal of this work was to compare the differences between human immunodeficiency Virus type 1 (HIV-1) of B and F1 Subtypes in the acquisition of major and rninot- protease inhibitor (P1)-associated resistance mutations and of other polymorphisms at the protease (PR) gene, through a cross sectional Study. PR sequences from subtypes B and F1 isolates matched according to P1 exposure time from Brazilian patients were included in this study. Sequences were separated in four groups: 24 and 90 from children and 141 and 99 from adults infected with isolates of subtypes F1 and B, respectively. For comparison, 211 subype B and 79 subtype F1 PR sequences from drug-naive individuals Were included. Demographic and clinical data were similar among B- and F1-infected patients. In untreated patients, Mutations L1OV, K20R, and M361 were more frequent in subtype F1, while L63P, A7IT, and V771 were more prevalent in Subtype B. In treated patients, K20M, D30N, G73S, 184V, and L90M, were More prevalent in subtype B, and K20T and N88S Were more prevalent in Subtype F1. A higher proportion of subtype F1 than Of subtype B Strains Containing other polymorphisms was observed. V82L mutation was Present With increased frequency in isolates from children compared to isolates from adults infected with both subtypes. We could observe a faster resistance emergence in children than in adults, during treatment with protease inhibitors. This data provided evidence that, although rates of overall drug resistance do not differ between subtypes B and F1, the former accumulates resistance at higher proportion in specific amino acid positions of protease when compared to the latter. (c) 2008 Elsevier B.V. All rights reserved.

Patient Characteristics as Predictors of Image Quality and Diagnostic Accuracy of MDCT Compared With Conventional Coronary Angiography for Detecting Coronary Artery Stenoses: CORE-64 Multicenter International Trial

OBJECTIVE. The purpose of the study was to investigate patient characteristics associated with image quality and their impact on the diagnostic accuracy of MDCT for the detection of coronary artery stenosis. MATERIALS AND METHODS. Two hundred ninety-one patients with a coronary artery calcification (CAC) score of <= 600 Agatston units (214 men and 77 women; mean age, 59.3 +/- 10.0 years [SD]) were analyzed. An overall image quality score was derived using an ordinal scale. The accuracy of quantitative MDCT to detect significant (>= 50%) stenoses was assessed using quantitative coronary angiography (QCA) per patient and per vessel using a modified 19-segment model. The effect of CAC, obesity, heart rate, and heart rate variability on image quality and accuracy were evaluated by multiple logistic regression. Image quality and accuracy were further analyzed in subgroups of significant predictor variables. Diagnostic analysis was determined for image quality strata using receiver operating characteristic (ROC) curves. RESULTS. Increasing body mass index (BMI) (odds ratio [OR] = 0.89, p < 0.001), increasing heart rate (OR = 0.90, p < 0.001), and the presence of breathing artifact (OR = 4.97, p = 0.001) were associated with poorer image quality whereas sex, CAC score, and heart rate variability were not. Compared with examinations of white patients, studies of black patients had significantly poorer image quality (OR = 0.58, p = 0.04). At a vessel level, CAC score (10 Agatston units) (OR = 1.03, p = 0.012) and patient age (OR = 1.02, p = 0.04) were significantly associated with the diagnostic accuracy of quantitative MDCT compared with QCA. A trend was observed in differences in the areas under the ROC curves across image quality strata at the vessel level (p = 0.08). CONCLUSION. Image quality is significantly associated with patient ethnicity, BMI, mean scan heart rate, and the presence of breathing artifact but not with CAC score at a patient level. At a vessel level, CAC score and age were associated with reduced diagnostic accuracy.

Supporting content-based image retrieval and computer-aided diagnosis systems with association rule-based techniques

In this work, we take advantage of association rule mining to support two types of medical systems: the Content-based Image Retrieval (CBIR) systems and the Computer-Aided Diagnosis (CAD) systems. For content-based retrieval, association rules are employed to reduce the dimensionality of the feature vectors that represent the images and to improve the precision of the similarity queries. We refer to the association rule-based method to improve CBIR systems proposed here as Feature selection through Association Rules (FAR). To improve CAD systems, we propose the Image Diagnosis Enhancement through Association rules (IDEA) method. Association rules are employed to suggest a second opinion to the radiologist or a preliminary diagnosis of a new image. A second opinion automatically obtained can either accelerate the process of diagnosing or to strengthen a hypothesis, increasing the probability of a prescribed treatment be successful. Two new algorithms are proposed to support the IDEA method: to pre-process low-level features and to propose a preliminary diagnosis based on association rules. We performed several experiments to validate the proposed methods. The results indicate that association rules can be successfully applied to improve CBIR and CAD systems, empowering the arsenal of techniques to support medical image analysis in medical systems. (C) 2009 Elsevier B.V. All rights reserved.

3.0-T MRI evaluation of patients with chronic liver diseases: initial observations

Purpose: To describe the use of 3.0-T magnetic resonance imaging (MRI) for the evaluation of chronic liver diseases. Materials and Methods: Two groups of patients who had chronic liver diseases and underwent 3.0-T MRI for evaluation of the liver were included in the study. The first group of patients included 66 consecutive patients (33 male, 33 female; mean age +/- standard deviation, 56 +/- 11). The second group of patients included 30 consecutive patients (18 males, 12 females; mean age +/- standard deviation, 53 +/- 10) in whom Variable-Rate Selective Excitation (VERSE) pulses and improved adjustments procedure were used during the acquisitions. Imaging findings of chronic liver diseases, predetermined artifacts and image quality of all individual sequences in the first group and predetermined artifacts and image quality of T2-weighted sequences in the second group were reviewed retrospectively and independently by two reviewers. chi-Square tests were used to compare the findings between two groups of patients and individual sequences. Kappa statistics were used to determine the extent of agreement between the reviewers. Results: Fifteen dysplastic nodules in 6 of 66 (9%) patients and 12 hepatocellular carcinomas in 11 of 66 (17%) patients were detected. Excluding motion artifacts, three-dimensional (313) T1-weighted gradient-echo (GE) sequence was the least affected sequence by the artifacts. Image quality of T1-weighted 3D-GE sequences was excellent in 43 of 66 (65%) patients. In-phase and out-of-phase T1-weighted spoiled GE (SGE) images were fair in 62 of 66 (94%) and 61 of 66 (92%) patients, respectively. The image quality of short tau inversion recovery (STIR) and half-Fourier rapid acquisition with relaxation enhancement (RARE) sequences were fair in 31 of 66 (47%) and 53 of 66 (80%) patients. STIR and half-Fourier RARE sequences in the second group demonstrated significantly better image quality (P=.03 and P<.0001). Conclusion: 3.0-T MRI allows the acquisition of very high quality postgadolinium 3D-GE sequence, which permitted the detection and characterization of lesions in the setting of chronic liver diseases. The use of VERSE pulses and improved adjustments procedure improved the image quality of T2-weighted sequences. In-phase/out-of-phase SGE sequences are at present of fair quality. (C) 2008 Elsevier Inc. All rights reserved.

Water excitation MPRAGE: An alternative sequence for postcontrast imaging of the abdomen in noncooperative patients at 1.5 Tesla and 3.0 Tesla MRI

Purpose: To evaluate the diagnostic image quality of post-gadolinium water excitation-magnetization-prepared rapid gradient-echo (WE-MPRAGE) sequence in abdominal examinations of noncooperative patients at 1.5 Tesla (T) and 3.0T MRI. Materials and Methods: Eighty-nine consecutive patients (48 males and 41 females; mean age +/- standard deviation, 54.6 +/- 16.6 years) who had MRI examinations including postgadolinium WE-MPRAGE were included in the study. Of 89 patients, 33 underwent noncooperative protocol at 1.5T. 10 under-went noncooperative protocol at 3.0T, and 46 underwent cooperative protocol at 3.0T. Postgadolinium WE-MPRAGE, MPRAGE, and three-dimensional gradient-echo sequences of these three different groups were qualitatively evaluated for image quality, extent of artifacts, lesion conspicuity, and homogeneity of fat-attenuation by two reviewers retrospectively, independently, and blindly. The results were compared using Wilcoxon signed rank and Mann-Whitney U tests. Kappa statistics were used to measure the extent of agreement between the reviewers. Results: The average scores indicated that the images were diagnostic for WE-MPRAGE at 1.5T and 3.0T in noncooperative patients. WE-MPRAGE achieved homogenous fat-attenuation in 31/33 (94%) of noncooperative patients at 1.5T and 10/10 (100%) of noncooperative patients at 3.0T. WE-MPRAGE at 3.0T had better results for image quality, extent of artifacts, lesion conspicuity and homogeneity of fat-attenuation compared with WE-MPRAGE at 1.5T. in noncooperative patients (P = 0.0008, 0.0006, 0.0024, and 0.0042: respectively). Kappa statistics varied between 0.76 and 1.00, representing good to excellent agreement. Conclusion: WE-MPRAGE may be used as a T1-weighted postgadolinium fat-attenuated sequence in noncooperative patients, particularly at 3.0T MRI.

An association rule-based method to support medical image diagnosis with efficiency

In this paper, we propose a method based on association rule-mining to enhance the diagnosis of medical images (mammograms). It combines low-level features automatically extracted from images and high-level knowledge from specialists to search for patterns. Our method analyzes medical images and automatically generates suggestions of diagnoses employing mining of association rules. The suggestions of diagnosis are used to accelerate the image analysis performed by specialists as well as to provide them an alternative to work on. The proposed method uses two new algorithms, PreSAGe and HiCARe. The PreSAGe algorithm combines, in a single step, feature selection and discretization, and reduces the mining complexity. Experiments performed on PreSAGe show that this algorithm is highly suitable to perform feature selection and discretization in medical images. HiCARe is a new associative classifier. The HiCARe algorithm has an important property that makes it unique: it assigns multiple keywords per image to suggest a diagnosis with high values of accuracy. Our method was applied to real datasets, and the results show high sensitivity (up to 95%) and accuracy (up to 92%), allowing us to claim that the use of association rules is a powerful means to assist in the diagnosing task.

The role of integrated information acquisition and management in the analysis of coastal ecosystem change

This book chapter represents a synthesis of the work which started in my PhD and which has been the conceptual basis for all of my research since 1993. The chapter presents a method for scientists and managers to use for selecting the type of remotely sensed data to use to meet their information needs associated with a mapping, monitoring or modelling application. The work draws on results from several of my ARC projects, CRC Rainforest and Coastal projects and theses of P.Scarth , K.Joyce and C.Roelfsema.

Effect of image analysis software on neurofunctional activation during processing of emotional human faces

Functional brain imaging techniques such as functional MRI (fMRI) that allow the in vivo investigation of the human brain have been exponentially employed to address the neurophysiological substrates of emotional processing. Despite the growing number of fMRI studies in the field, when taken separately these individual imaging studies demonstrate contrasting findings and variable pictures, and are unable to definitively characterize the neural networks underlying each specific emotional condition. Different imaging packages, as well as the statistical approaches for image processing and analysis, probably have a detrimental role by increasing the heterogeneity of findings. In particular, it is unclear to what extent the observed neurofunctional response of the brain cortex during emotional processing depends on the fMRI package used in the analysis. In this pilot study, we performed a double analysis of an fMRI dataset using emotional faces. The Statistical Parametric Mapping (SPM) version 2.6 (Wellcome Department of Cognitive Neurology, London, UK) and the XBAM 3.4 (Brain Imaging Analysis Unit, Institute of Psychiatry, Kings College London, UK) programs, which use parametric and non-parametric analysis, respectively, were used to assess our results. Both packages revealed that processing of emotional faces was associated with an increased activation in the brain`s visual areas (occipital, fusiform and lingual gyri), in the cerebellum, in the parietal cortex, in the cingulate cortex (anterior and posterior cingulate), and in the dorsolateral and ventrolateral prefrontal cortex. However, blood oxygenation level-dependent (BOLD) response in the temporal regions, insula and putamen was evident in the XBAM analysis but not in the SPM analysis. Overall, SPM and XBAM analyses revealed comparable whole-group brain responses. Further Studies are needed to explore the between-group compatibility of the different imaging packages in other cognitive and emotional processing domains. (C) 2009 Elsevier Ltd. All rights reserved.