Iis--integrated Interactome System: A Web-based Platform For The Annotation, Analysis And Visualization Of Protein-metabolite-gene-drug Interactions By Integrating A Variety Of Data Sources And Tools.

High-throughput screening of physical, genetic and chemical-genetic interactions brings important perspectives in the Systems Biology field, as the analysis of these interactions provides new insights into protein/gene function, cellular metabolic variations and the validation of therapeutic targets and drug design. However, such analysis depends on a pipeline connecting different tools that can automatically integrate data from diverse sources and result in a more comprehensive dataset that can be properly interpreted. We describe here the Integrated Interactome System (IIS), an integrative platform with a web-based interface for the annotation, analysis and visualization of the interaction profiles of proteins/genes, metabolites and drugs of interest. IIS works in four connected modules: (i) Submission module, which receives raw data derived from Sanger sequencing (e.g. two-hybrid system); (ii) Search module, which enables the user to search for the processed reads to be assembled into contigs/singlets, or for lists of proteins/genes, metabolites and drugs of interest, and add them to the project; (iii) Annotation module, which assigns annotations from several databases for the contigs/singlets or lists of proteins/genes, generating tables with automatic annotation that can be manually curated; and (iv) Interactome module, which maps the contigs/singlets or the uploaded lists to entries in our integrated database, building networks that gather novel identified interactions, protein and metabolite expression/concentration levels, subcellular localization and computed topological metrics, GO biological processes and KEGG pathways enrichment. This module generates a XGMML file that can be imported into Cytoscape or be visualized directly on the web. We have developed IIS by the integration of diverse databases following the need of appropriate tools for a systematic analysis of physical, genetic and chemical-genetic interactions. IIS was validated with yeast two-hybrid, proteomics and metabolomics datasets, but it is also extendable to other datasets. IIS is freely available online at: http://www.lge.ibi.unicamp.br/lnbio/IIS/.

Augmented Mixed Models For Clustered Proportion Data.

Often in biomedical research, we deal with continuous (clustered) proportion responses ranging between zero and one quantifying the disease status of the cluster units. Interestingly, the study population might also consist of relatively disease-free as well as highly diseased subjects, contributing to proportion values in the interval [0, 1]. Regression on a variety of parametric densities with support lying in (0, 1), such as beta regression, can assess important covariate effects. However, they are deemed inappropriate due to the presence of zeros and/or ones. To evade this, we introduce a class of general proportion density, and further augment the probabilities of zero and one to this general proportion density, controlling for the clustering. Our approach is Bayesian and presents a computationally convenient framework amenable to available freeware. Bayesian case-deletion influence diagnostics based on q-divergence measures are automatic from the Markov chain Monte Carlo output. The methodology is illustrated using both simulation studies and application to a real dataset from a clinical periodontology study.

Late Entry into HIV Care: Estimated Impact on AIDS Mortality Rates in Brazil, 2003-2006

Background: Worldwide, a high proportion of HIV-infected individuals enter into HIV care late. Here, our objective was to estimate the impact that late entry into HIV care has had on AIDS mortality rates in Brazil. Methodology/Principal Findings: We analyzed data from information systems regarding HIV-infected adults who sought treatment at public health care facilities in Brazil from 2003 to 2006. We initially estimated the prevalence of late entry into HIV care, as well as the probability of death in the first 12 months, the percentage of the risk of death attributable to late entry, and the number of avoidable deaths. We subsequently adjusted the annual AIDS mortality rate by excluding such deaths. Of the 115,369 patients evaluated, 50,358 (43.6%) had entered HIV care late, and 18,002 died in the first 12 months, representing a 16.5% probability of death in the first 12 months (95% CI: 16.3-16.7). By comparing patients who entered HIV care late with those who gained timely access, we found that the risk ratio for death was 49.5 (95% CI: 45.1-54.2). The percentage of the risk of death attributable to late entry was 95.5%, translating to 17,189 potentially avoidable deaths. Averting those deaths would have lowered the 2003-2006 AIDS mortality rate by 39.5%. Including asymptomatic patients with CD4(+) T cell counts >200 and <= 350 cells/mm(3) in the group who entered HIV care late increased this proportion by 1.8%. Conclusions/Significance: In Brazil, antiretroviral drugs reduced AIDS mortality by 43%. Timely entry would reduce that rate by a similar proportion, as well as resulting in a 45.2% increase in the effectiveness of the program for HIV care. The World Health Organization recommendation that asymptomatic patients with CD4(+) T cell counts <= 350 cells/mm(3) be treated would not have a significant impact on this scenario.

Listeria monocytogenes in two different poultry facilities: Manual and automatic evisceration

Listeriosis is a serious foodborne disease caused by Listeria monocytogenes, a pathogen often found in food processing plants. Poultry meat and its derivatives may harbor L. monocytogenes even if good manufacturing practices are implanted in abattoirs. Little information exists in Brazil on the frequency of L. monocytogenes contamination, even though the country is considered the top poultry meat exporter in the world. This study attempted to compare 2 exporters poultry facilities following same the standards but differing only in manual (plant M) or automatic (plant A) evisceration. Eight hundred fifty-one samples from food, food contact and non-food contact surfaces, water, and workers` hands were collected from cage to finished products over a 1-yr period. In plant A, 20.1% of the samples were positive for L. monocytogenes, whereas in plant M, 16.4% was found. The greatest incidence of contamination with the pathogen in plant A was found in non- food contact surfaces (27.3%), while in plant M, it was found in products (19.4%). The most prevalent serovars were 1/2a or 3a (plant M) and 4b, 4d, or 4e (plant A). Despite having proper hygiene and good manufacturing practices, controlling the entry and persistence of L. monocytogenes in processing facilities remains a formidable task.

Multifidus muscle recovery is not automatic after resolution of acute, first-episode low back pain

Study Design. A clinical study was conducted on 39 patients with acute, first-episode, unilateral low back pain and unilateral, segmental inhibition of the multifidus muscle. Patients were allocated randomly to a control or treatment group. Objectives. To document the natural course of lumbar multifidus recovery and to evaluate the effectiveness of specific, localized, exercise therapy on muscle recovery. Summary of Background Data. Acute low back pain usually resolves spontaneously, but the recurrence rate is high. Inhibition of multifidus occurs with acute, first-episode, low back pain, and pathologic changes in this muscle have been linked with poor outcome and recurrence of symptoms. Methods. Patients in group 1 received medical treatment only. Patients in group 2 received medical treatment and specific, localized, exercise therapy. Outcome measures for both groups included 4 weekly assessments of pain, disability, range of motion, and size of the multifidus cross-sectional area. Independent examiners were blinded to group allocation. Patients were reassessed at a 10-week follow-up examination. Results. Multifidus muscle recovery was not spontaneous on remission of painful symptoms in patients in group 1. Muscle recovery was more rapid and more complete in patients in group 2 who received exercise therapy (P = 0.0001). Other outcome measurements were similar for the two groups at the 4-week examination. Although they resumed normal levels of activity, patients in group 1 still had decreased multifidus muscle size at the 10-week follow-up examination. Conclusions. Multifidus muscle recovery is not spontaneous on remission of painful symptoms. Lack of localized, muscle support may be one reason for the high recurrence rate of low back pain following the initial episode.

Exploring the knowledge contained in neuroimages: Statistical discriminant analysis and automatic segmentation of the most significant changes

Objective: The aim of this article is to propose an integrated framework for extracting and describing patterns of disorders from medical images using a combination of linear discriminant analysis and active contour models. Methods: A multivariate statistical methodology was first used to identify the most discriminating hyperplane separating two groups of images (from healthy controls and patients with schizophrenia) contained in the input data. After this, the present work makes explicit the differences found by the multivariate statistical method by subtracting the discriminant models of controls and patients, weighted by the pooled variance between the two groups. A variational level-set technique was used to segment clusters of these differences. We obtain a label of each anatomical change using the Talairach atlas. Results: In this work all the data was analysed simultaneously rather than assuming a priori regions of interest. As a consequence of this, by using active contour models, we were able to obtain regions of interest that were emergent from the data. The results were evaluated using, as gold standard, well-known facts about the neuroanatomical changes related to schizophrenia. Most of the items in the gold standard was covered in our result set. Conclusions: We argue that such investigation provides a suitable framework for characterising the high complexity of magnetic resonance images in schizophrenia as the results obtained indicate a high sensitivity rate with respect to the gold standard. (C) 2010 Elsevier B.V. All rights reserved.

Oropouche virus entry into HeLa cells involves clathrin and requires endosomal acidification

Oropouche virus (ORO), family Bunyaviridae, is the second most frequent cause of arboviral febrile illness in Brazil. Studies were conducted to understand ORO entry in HeLa cells. Chlorpromazine inhibited early steps of ORO replication cycle, consistent with entry/uncoating. The data indicate that ORO enters HeLa cells by clathrin-coated vesicles, by a mechanism susceptible to endosomal acidification inhibitors. Transmission electron microscopy and immunofluorescence indicated that ORO associates with clathrin-coated pits and can be found in association with late endosomes in a time shorter than 1 h. (C) 2008 Elsevier B.V. All rights reserved.

Vitamin B12 stalls the 80 S ribosomal complex on the hepatitis C internal ribosome entry site

The effect of cyanocobalamin (CNCbl, vitamin 1312) on hepatitis C virus internal ribosome entry site (HCV IRES)-dependent initiation of translation was studied by ribosomal toeprinting and sucrose gradient centrifugation analysis. These results suggested that CNCbl did not inhibit HCV IRES-dependent translation by a competitive binding mechanism. CNCbl allowed 80 S elongation complex formation on the mRNA, but stalled the initiation at that point, effectively trapping the 80 S ribosomal complexes on the HCV TRES. CNCbl had no effect on cap-dependent mRNA, consistent with the known mRNA specificity of this translational inhibitor. To help elucidate the mechanism, comparative data were collected for the well-characterised translation inhibitors cycloheximide and 5'-guanylyl-imidophosphate, Although CNCbl stalled HCV IRES-dependent translation at approximately the same step in initiation as cycloheximide, the mechanisms of these two inhibitors are distinct. (C) 2002 Elsevier Science Ltd. All rights reserved.

Longitudinal study of veterinarians from entry to the veterinary course to ten years after graduation: career paths

Objective To map out the career paths of veterinarians during their first 10 years after graduation, and to determine if this could have been predicted at entry to the veterinary course. Design Longitudinal study of students who started their course at The University of Queensland in 1985 and 1986, and who completed questionnaires in their first and fifth year as students, and in their second, sixth and eleventh year as veterinarians. Methods Data from 129 (96%) questionnaires completed during the eleventh year after graduation were coded numerically then analysed, together with data from previous questionnaires, with SAS System 7 for Windows 95. Results Ten years after they graduated, 80% were doing veterinary work, 60% were in private practice, 40% in small animal practice and 18% in mixed practice. The equivalent of 25% of the working time of all females was taken up by family duties. When part-time work was taken into account, veterinary work constituted the equivalent of 66% of the group working full-time. That 66% consisted of 52% on small animals, 7% on horses, 6% on cattle/sheep and 1% on pigs/poultry. Those who had grown up on farms with animals were twice as likely to be working with farm animals as were those from other backgrounds. Forecasts made on entry to the veterinary course were of no value in predicting who would remain in mixed practice. Conclusions Fewer than one-fifth of graduates were in mixed practice after 10 years, but the number was higher for those who grew up on farms with animals. Forecasts that may be made at interview before entry to the course were of little value in predicting the likelihood of remaining in mixed veterinary practice.

Longitudinal study of veterinarians from entry to the veterinary course to 10 years after graduation: attitudes to work, career and profession

Objective To describe the attitudes of veterinarians to their work, career and profession during the 10 years after graduation. Design Longitudinal study of students who started their course at The University of Queensland in 1985 and 1986, and who completed questionnaires in their first and fifth year as students, and after one, five and 10 years as veterinarians. Methods Data from 129 (96%) questionnaires completed after 10 years as a veterinarian were coded numerically then analysed, together with data from previous questionnaires, with SAS System 7 for Windows 95. Results After 10 years, almost all respondents were either very glad they had done the veterinary course (57%) or generally glad, though with some misgivings (37%). Despite this, only 55% would definitely become a veterinarian if they 'had to do it over again'. The responses for about one-third were different from those given five years earlier. The views of many were related to the level of support and encouragement received in their first job after graduation. There were 42% who were working less than half-time as veterinarians, and their main reasons were, in order, raising children, long hours of work, attitudes of bosses and clients, and poor pay. A majority was concerned about the ethics and competence of some colleagues, and almost all believed that consideration of costs must influence the type of treatment animals receive. Conclusions Most veterinarians were glad to have done the veterinary course, but for about one-quarter their career had not lived up to expectations and almost half would not do it again in another incarnation. Stress, hours of work, difficulties in balancing personal life with career and low income were important concerns for many. Low income may contribute to the low number of males entering the veterinary profession.

Automatic segmentation and 3D feature extraction of protein aggregates in Caenorhabditis Elegans

In the last years, it has become increasingly clear that neurodegenerative diseases involve protein aggregation, a process often used as disease progression readout and to develop therapeutic strategies. This work presents an image processing tool to automatic segment, classify and quantify these aggregates and the whole 3D body of the nematode Caenorhabditis Elegans. A total of 150 data set images, containing different slices, were captured with a confocal microscope from animals of distinct genetic conditions. Because of the animals’ transparency, most of the slices pixels appeared dark, hampering their body volume direct reconstruction. Therefore, for each data set, all slices were stacked in one single 2D image in order to determine a volume approximation. The gradient of this image was input to an anisotropic diffusion algorithm that uses the Tukey’s biweight as edge-stopping function. The image histogram median of this outcome was used to dynamically determine a thresholding level, which allows the determination of a smoothed exterior contour of the worm and the medial axis of the worm body from thinning its skeleton. Based on this exterior contour diameter and the medial animal axis, random 3D points were then calculated to produce a volume mesh approximation. The protein aggregations were subsequently segmented based on an iso-value and blended with the resulting volume mesh. The results obtained were consistent with qualitative observations in literature, allowing non-biased, reliable and high throughput protein aggregates quantification. This may lead to a significant improvement on neurodegenerative diseases treatment planning and interventions prevention

Real-time 3D interactive segmentation of echocardiographic data through user-based deformation of B-spline explicit active surfaces

Image segmentation is an ubiquitous task in medical image analysis, which is required to estimate morphological or functional properties of given anatomical targets. While automatic processing is highly desirable, image segmentation remains to date a supervised process in daily clinical practice. Indeed, challenging data often requires user interaction to capture the required level of anatomical detail. To optimize the analysis of 3D images, the user should be able to efficiently interact with the result of any segmentation algorithm to correct any possible disagreement. Building on a previously developed real-time 3D segmentation algorithm, we propose in the present work an extension towards an interactive application where user information can be used online to steer the segmentation result. This enables a synergistic collaboration between the operator and the underlying segmentation algorithm, thus contributing to higher segmentation accuracy, while keeping total analysis time competitive. To this end, we formalize the user interaction paradigm using a geometrical approach, where the user input is mapped to a non-cartesian space while this information is used to drive the boundary towards the position provided by the user. Additionally, we propose a shape regularization term which improves the interaction with the segmented surface, thereby making the interactive segmentation process less cumbersome. The resulting algorithm offers competitive performance both in terms of segmentation accuracy, as well as in terms of total analysis time. This contributes to a more efficient use of the existing segmentation tools in daily clinical practice. Furthermore, it compares favorably to state-of-the-art interactive segmentation software based on a 3D livewire-based algorithm.

Automatic modeling of pectus excavatum corrective prosthesis using artificial neural networks

Pectus excavatum is the most common deformity of the thorax. Pre-operative diagnosis usually includes Computed Tomography (CT) to successfully employ a thoracic prosthesis for anterior chest wall remodeling. Aiming at the elimination of radiation exposure, this paper presents a novel methodology for the replacement of CT by a 3D laser scanner (radiation-free) for prosthesis modeling. The complete elimination of CT is based on an accurate determination of ribs position and prosthesis placement region through skin surface points. The developed solution resorts to a normalized and combined outcome of an artificial neural network (ANN) set. Each ANN model was trained with data vectors from 165 male patients and using soft tissue thicknesses (STT) comprising information from the skin and rib cage (automatically determined by image processing algorithms). Tests revealed that ribs position for prosthesis placement and modeling can be estimated with an average error of 5.0 ± 3.6 mm. One also showed that the ANN performance can be improved by introducing a manually determined initial STT value in the ANN normalization procedure (average error of 2.82 ± 0.76 mm). Such error range is well below current prosthesis manual modeling (approximately 11 mm), which can provide a valuable and radiation-free procedure for prosthesis personalization.

Automatic modeling of pectus excavatum corrective prosthesis using artificial neural networks

Pectus excavatum is the most common deformity of the thorax. Pre-operative diagnosis usually includes Computed Tomography (CT) to successfully employ a thoracic prosthesis for anterior chest wall remodeling. Aiming at the elimination of radiation exposure, this paper presents a novel methodology for the replacement of CT by a 3D laser scanner (radiation-free) for prosthesis modeling. The complete elimination of CT is based on an accurate determination of ribs position and prosthesis placement region through skin surface points. The developed solution resorts to a normalized and combined outcome of an artificial neural network (ANN) set. Each ANN model was trained with data vectors from 165 male patients and using soft tissue thicknesses (STT) comprising information from the skin and rib cage (automatically determined by image processing algorithms). Tests revealed that ribs position for prosthesis placement and modeling can be estimated with an average error of 5.0 ± 3.6 mm. One also showed that the ANN performance can be improved by introducing a manually determined initial STT value in the ANN normalization procedure (average error of 2.82 ± 0.76 mm). Such error range is well below current prosthesis manual modeling (approximately 11 mm), which can provide a valuable and radiation-free procedure for prosthesis personalization.

Artificial neural networks for automatic modelling of the pectus excavatum corrective prosthesis

Pectus excavatum is the most common deformity of the thorax and usually comprises Computed Tomography (CT) examination for pre-operative diagnosis. Aiming at the elimination of the high amounts of CT radiation exposure, this work presents a new methodology for the replacement of CT by a laser scanner (radiation-free) in the treatment of pectus excavatum using personally modeled prosthesis. The complete elimination of CT involves the determination of ribs external outline, at the maximum sternum depression point for prosthesis placement, based on chest wall skin surface information, acquired by a laser scanner. The developed solution resorts to artificial neural networks trained with data vectors from 165 patients. Scaled Conjugate Gradient, Levenberg-Marquardt, Resilient Back propagation and One Step Secant gradient learning algorithms were used. The training procedure was performed using the soft tissue thicknesses, determined using image processing techniques that automatically segment the skin and rib cage. The developed solution was then used to determine the ribs outline in data from 20 patient scanners. Tests revealed that ribs position can be estimated with an average error of about 6.82±5.7 mm for the left and right side of the patient. Such an error range is well below current prosthesis manual modeling (11.7±4.01 mm) even without CT imagiology, indicating a considerable step forward towards CT replacement by a 3D scanner for prosthesis personalization.