Genomic comparison of two strains of Mycobacterium avium subsp. paratuberculosis with contrasting pathogenic phenotype.

In a previous study, we evaluated the degree of virulence of Mycobacterium avium subsp. paratuberculosis (Map) strains isolated from cattle in Argentina in a murine model. This assay allowed us to differentiate between high-virulent MapARG1347 and low-virulent MapARG1543 strains. To corroborate whether the differences in virulence could be attributed to genetic differences between the strains, we performed Whole Genome Sequencing and compared the genomes and gene content between them and determined the differences related to the reference strain MapK10. We found 233 SNPs/INDELS in one or both strains relative to Map K10. The two strains share most of the variations, but we found 15 mutations present in only one of the strains. Considering NS-SNP/INDELS that produced a severe effect in the coding sequence, we focus the analysis on four predicted proteins, putatively related to virulence. Survival of MapARG1347 strain in bMDM was higher than MapARG1543 and was more resistant to acidic pH and H2O2 stresses than MapK10. The genomic differences between the two strains found in genes MAP1203 (a putative peptidoglycan hydrolase), MAP0403 (a putative serine protease) MAP1003c (a member of the PE-PPE family) and MAP4152 (a putative mycofactocin binding protein) could contribute to explain the contrasting phenotype previously observed in mice models.

[From a pathogen's genome to an effective vaccine: the four-component meningococcal serogroup B vaccine]. / Del genoma de un patógeno a una vacuna efectiva: la vacuna de cuatro componentes frente a los meningococos del serogrupo B.

Invasive meningococcal disease (IMD), caused by the bacterium Neisseria meningitidis, entails significant mortality and morbidity. Disease incidence is highest in infants <1 year and young children globally. In Europe, N. meningitidis serogroup B is responsible for over 50% of overall IMD cases, whereas the majority of IMD cases in Latin America is caused either by serogroup B or C. The development of an effective vaccine against serogroup B has challenged the researchers for over half a century. Serogroup B capsular polysaccharide was an inappropriate vaccine antigen, and the success of outer membrane vesicle (OMV) vaccines was restricted to homologous bacterial strains. Reverse vaccinology led to the development of a 4-component meningococcal vaccine including three novel antigens, and OMVs (4CMenB). Each vaccine component has a different target. 4CMenB has been authorised based on its immunogenicity and safety data because the low disease incidence precluded formal clinical efficacy studies. Human serum bactericidal antibody (hSBA) assay tests functional antibodies in the serum of vaccinated individuals (i.e. the vaccine immunogenicity), and is the accepted correlate of protection. Vaccine strain coverage has been assessed both through hSBA assays and a more conservative method named Meningococcal Antigen Typing System (MATS). Effectiveness data of 4CMenB have been collected in the field since 2013. The vaccine proved effective in outbreak control in North America, and recent data from the introduction of the vaccine in the United Kingdom infant national immunisation programme reveal a vaccine effectiveness of 82.9% for the first two doses, with an acceptable safety profile.

Traumatismo craneal no accidental: a propósito de un caso / Abusive head trauma: Report of a case

El traumatismo craneal no accidental es una forma de maltrato infantil. Frecuentemente, se encuentran lesiones intracraneales, como el hematoma subdural y también las hemorragias retinianas, en general, sin otras lesiones externas. Por su complejidad, esta entidad requiere de un equipo médico multidisciplinario, donde el papel del especialista en imágenes es muy importante, ya que existen múltiples métodos diagnósticos que se complementan para arribar al correcto diagnóstico

The abusive head trauma is a form of child abuse. The most frequent injuries are intracranial lesions, such as subdural hematoma, as well as retinal hemorrhages, usually without other external injuries. Due to its complexity, this problem requires a multidisciplinary medical team, where the role of the radiologist is important, since there are multiple diagnostic methods that are complementary in order to arrive at the correct diagnosis

[Abusive head trauma: report of a case]. / Traumatismo craneal no accidental: a propósito de un caso.

The abusive head trauma is a form of child abuse. The most frequent injuries are intracranial lesions, such as subdural hematoma, as well as retinal hemorrhages, usually without other external injuries. Due to its complexity, this problem requires a multidisciplinary medical team, where the role of the radiologist is important, since there are multiple diagnostic methods that are complementary in order to arrive at the correct diagnosis.

A proposal of Texture Features for interactive CTA Segmentation by Active Learning.

Our objective is to create an interactive image segmentation system of the abdominal area for quick volumetric segmentation of the aorta requiring minimal intervention of the human operator. The aforementioned goal is to be achieved by an Active Learning image segmentation system over enhanced image texture features, obtained from the standard Gray Level Co-occurrence Matrix (GLCM) and the Local Binary Patterns (LBP). The process iterates the following steps: first, image segmentation is produced by a Random Forest (RF) classifier trained on a set of image texture features for labeled voxels. The human operator is presented with the most uncertain unlabeled voxels to select some of them for inclusion in the training set, retraining the RF classifier. The approach will be applied to the segmentation of the thrombus in Computed Tomography Angiography (CTA) data of Abdominal Aortic Aneurysm (AAA) patients. A priori knowledge on the expected shape of the target structures is used to filter out undesired detections. On going preliminary experiments on datasets containing diverse number of CT slices (between 216 and 560), each one consisting a real human contrast-enhanced sample of the abdominal area, are underway. The segmentation results obtained with simple image features were promising and highlight the capacity of the used texture features to describe the local variation of the AAA thrombus and thus to provide useful information to the classifier.

Prognostic value of changes in resting-state functional connectivity patterns in cognitive recovery after stroke: A 3T fMRI pilot study.

Resting-state studies conducted with stroke patients are scarce. First objective was to explore whether patients with good cognitive recovery showed differences in resting-state functional patterns of brain activity when compared to patients with poor cognitive recovery. Second objective was to determine whether such patterns were correlated with cognitive performance. Third objective was to assess the existence of prognostic factors for cognitive recovery. Eighteen right-handed stroke patients and eighteen healthy controls were included in the study. Stroke patients were divided into two groups according to their cognitive improvement observed at three months after stroke. Probabilistic independent component analysis was used to identify resting-state brain activity patterns. The analysis identified six networks: frontal, fronto-temporal, default mode network, secondary visual, parietal, and basal ganglia. Stroke patients showed significant decrease in brain activity in parietal and basal ganglia networks and a widespread increase in brain activity in the remaining ones when compared with healthy controls. When analyzed separately, patients with poor cognitive recovery (n=10) showed the same pattern as the whole stroke patient group, while patients with good cognitive recovery (n=8) showed increased activity only in the default mode network and fronto-temporal network, and decreased activity in the basal ganglia. We observe negative correlations between basal ganglia network activity and performance in Semantic Fluency test and Part A of the Trail Making Test for patients with poor cognitive recovery. A reverse pattern was observed between frontal network activity and the above mentioned tests for the same group. .

Discovering Alzheimer's disease and bipolar disorder white matter effects building computer aided diagnostic systems on brain diffusion tensor imaging features.

The aim of this study is to look for differential effects in white matter (WM) of bipolar disorder (BD) and Alzheimer's disease (AD) patients. We proceed by investigating the feasibility of discriminating between BD and AD patients, and from healthy controls (HC), using multivariate data analysis based on diffusion tensor imaging (DTI) data features. Specifically, support vector machine (SVM) classifiers were trained and tested on fractional anisotropy (FA). Voxel sites are selected as features for classification if their Pearson's correlation between FA values at voxel site across subjects and the indicative variable specifying the subject class is above the threshold set by a percentile of its empirical distribution. To avoid double dipping, selection was performed only on training data in a leave one out cross-validation study. Classification results show that FA features and a linear SVM classifier achieve perfect accuracy, sensitivity and specificity in AD vs. HC, BD vs. HC, and AD vs. BD leave-one-out cross-validation studies. The localization of the discriminant voxel sites on a probabilistic tractography atlas shows effects on seven major WM tracts in each hemisphere and two commissural tracts.

Volatile composition and sensory properties of Vitis vinifera red cultivars from north west Spain: correlation between sensory and instrumental analysis.

The aroma and volatile composition of wines from five red cultivars from NW Spain (Brancellao, Mencía, Merenzao, Mouratón and Sousón) have been studied by gas chromatography-mass spectrometry (GC-MS) and sensory descriptive analysis (SDA) during three consecutive vintages (2007-2009) in order to characterize these wines. In addition, relationships between the instrumental (volatile) and sensory variables were analyzed through the application of partial least squares regression (PLSR). Results revealed that the effect of "cultivar" was very important as a third of compounds (16 in total) varied significantly (P≤0.05) among varieties. Mencía wines presented the highest concentrations of γ-nonalactone, whereas Sousón wines were the richest in monoterpene compounds. On the contrary, no significant difference was observed with respect to the esters content, probably as a consequence of using the same yeast for all vinifications. Twenty out of 51 quantified volatile compounds were present in some samples at concentrations higher than their corresponding odor thresholds (OAV>1), thus contributing to the final wine aroma. Partial least square (PLS) regression was applied to volatile compounds with OAV>0.2 and aroma descriptors with %GM>10. PLSR yielded a satisfactory model for the prediction of four important aroma descriptors in this set of wines--aroma quality, aroma intensity, herbaceous and red fruit--from instrumental analysis data. This work contributes to gaining knowledge about the sensory profiles and its relation to the volatile composition of minority Galician red grape cultivars.

Computer aided diagnosis system for Alzheimer disease using brain diffusion tensor imaging features selected by Pearson's correlation.

The aim of this paper is to obtain discriminant features from two scalar measures of Diffusion Tensor Imaging (DTI) data, Fractional Anisotropy (FA) and Mean Diffusivity (MD), and to train and test classifiers able to discriminate Alzheimer's Disease (AD) patients from controls on the basis of features extracted from the FA or MD volumes. In this study, support vector machine (SVM) classifier was trained and tested on FA and MD data. Feature selection is done computing the Pearson's correlation between FA or MD values at voxel site across subjects and the indicative variable specifying the subject class. Voxel sites with high absolute correlation are selected for feature extraction. Results are obtained over an on-going study in Hospital de Santiago Apostol collecting anatomical T1-weighted MRI volumes and DTI data from healthy control subjects and AD patients. FA features and a linear SVM classifier achieve perfect accuracy, sensitivity and specificity in several cross-validation studies, supporting the usefulness of DTI-derived features as an image-marker for AD and to the feasibility of building Computer Aided Diagnosis systems for AD based on them.

Identifying associations between amino acid changes and meta information in alignments.

MOTIVATION: We present a method that identifies associations between amino acid changes in potentially significant sites in an alignment (taking into account several amino acid properties) with phenotypic data, through the phylogenetic mixed model. The latter accounts for the dependency of the observations (organisms). It is known from previous studies that the pathogenic aspect of many organisms may be associated with a single or just few changes in amino acids, which have a strong structural and/or functional impact on the protein. Discovering these sites is a big step toward understanding pathogenicity. Our method is able to discover such sites in proteins responsible for the pathogenic character of a group of bacteria. RESULTS: We use our method to predict potentially significant sites in the RpoS protein from a set of 209 bacteria. Several sites with significant differences in biological relevant regions were found. AVAILABILITY: Our tool is publicly available on the CRAN network at http://cran.r-project.org/ CONTACT: naya@pasteur.edu.uy SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Detection of type II endoleaks in abdominal aortic aneurysms after endovascular repair.

Abdominal aortic aneurysm (AAA) is a condition where the weakening of the aortic wall leads to its widening and the generation of a thrombus. To prevent a possible rupture of the aortic wall, AAA can be treated non-invasively by means of the endovascular aneurysm repair technique (EVAR), consisting of placing a stent-graft inside the aorta by a cateter to exclude the aneurysm sac from the blood circulation. A major complication is the presence of liquid blood turbulences, called endoleaks, in the thrombus formed in the space between the aortic wall and the stent-graft. In this paper we propose an automatic method for the detection of type II endoleaks in computer tomography angiography (CTA) images. The lumen and thrombus in the aneurysm area are first segmented using a radial model approach. Then, these regions are split into Thrombus Connected Components (TCCs) using a watershed-based segmentation and geometric and image content-based characteristics are obtained for each TCC. Finally, TCCs are classified into endoleaks and non-endoleaks using a multilayer Perceptron (MLP) trained on manual labeled sample TCCs provided by experts.

Neurocognitive disorder detection based on feature vectors extracted from VBM analysis of structural MRI.

Dementia is a growing concern due to the aging process of the western societies. Non-invasive detection is therefore a high priority research endeavor. In this paper we report results of classification systems applied to the feature vectors obtained by a feature extraction method computed on structural magnetic resonance imaging (sMRI) volumes for the detection of two neurological disorders with cognitive impairment: myotonic dystrophy of type 1 (MD1) and Alzheimer disease (AD). The feature extraction process is based on the voxel clusters detected by voxel-based morphometry (VBM) analysis of sMRI upon a set of patient and control subjects. This feature extraction process is specific for each kind of disease and is grounded on the findings obtained by medical experts. The 10-fold cross-validation results of several statistical and neural network based classification algorithms trained and tested on these features show high specificity and moderate sensitivity of the classifiers, suggesting that the approach is better suited for rejecting than for detecting early stages of the diseases.

Industrially processed vacuum-packed peeled Kennebec potatoes: process optimization, sensory evaluation, and consumer response.

UNLABELLED: To optimize the processing and storage of Kennebec potatoes for sale in peeled, vacuum-packed ready-to-cook form, we studied the effects of blanching, various anti-browning solutions, and storage temperature. Unblanched potatoes pretreated with a mixture of 1% ascorbic acid and 0.5% citric acid, and stored at 2 °C, were found to have a shelf life of at least 1 mo without browning. Potatoes so treated differed sensorially from fresh potatoes, but were well received by consumers. PRACTICAL APPLICATION: The process described here maintains the characteristics of fresh potato with all the amenities of a processed product.

Short communication: contribution of the immunovirological state and traditional cardiovascular risk factors to low HDL-cholesterol in HIV patients.

The prevalence of low HDL-C levels in an HIV population and its related factors was investigated. We undertook a multicenter, cross-sectional study of all HIV patients on regular follow-up in five hospitals (Southern Spain). A physical examination and fasting laboratory analysis were performed and a questionnaire about cardiovascular risk factors was provided. One thousand and seventy-two patients were included, 43.8% of whom had low HDL-C levels. The prevalence of low HDL-C was higher among patients diagnosed with AIDS, those not on antiretroviral therapy, those with a detectable HIV viral load, those with CD4 cell counts ≤350 cells/µl, smokers, and those with hypertriglyceridemia. For patients on antiretroviral therapy, the prevalence of low HDL-C was higher for those on protease inhibitors than those taking nonnucleoside reverse transcriptase inhibitors. In the multivariate analysis, low HDL-C levels were associated with tobacco use (OR 1.37, 95% CI 1.04-1.8; p = 0.04), hypertriglyceridemia (OR 2.94, 95% CI 2.2-3.8; p < 0.00001), CD4 cells count ≤350 cells/µl (OR 1.74, 95% CI 1.2-2.3; p < 0.0001), and a detectable HIV viral load (OR 1.85, 95% CI 1.3-2.5; p < 0.0001). The immunological and virological conditions, in addition to traditional cardiovascular risk factors such as tobacco use and hypertriglyceridemia, affect HDL-C levels in HIV-infected patients. For patients on antiretroviral therapy, the use of protease inhibitors is associated with a higher probability of low levels of HDL-C. Although it is not clear if the higher HDL-C levels associated with antiretroviral use are surrogates for decreased cardiovascular disease risk, this may be another reason to start antiretroviral therapy earlier.

[Analysis of the natural radioactivity due to the radon gas in the underground of Rome]. / Analisi della radioattività naturale dovuta al gas radon presente negli ambienti sotterranei della metropolitana di Roma.

BACKGROUND: Radon is a decay product of 238Uranium which is classified by WHO/IARC as group 1 carcinogen, given its causal relationship with lung neoplasia. An annual concentration of this gas higher than 500 Bq/m3 in workplace is considered potentially dangerous by the italian legislation. No data are currently available on radon level in underground tunnels, which are a potentially important source of exposure both for workers and travellers. MATERIAL AND METHODS: Measurements have been performed in a station and within the trains. Two months integrated measures, and 5 days continuous (hourly) assessments have been performed. Integrated measurements have been performed by means of 12 passive dosimeters, containing a detector made of CR39 (polymeric type), whereas active scintillation-type dosimeters have been employed for continuous assessments. RESULTS: Two months integrated measures: radon level in the station was 665 +/- 71 Bq/m3, whereas values within the trains ranged between 96 and 117 Bq/m3. Continuous measurements: Mean radon level during work activities was 783 +/- 536 Bq/m3 and thereafter it rose to 850 +/- 131 Bq/m3 CONCLUSIONS: Radon nelle levels in underground tunnels may exceed attention levels, whereas within trains they remain well below these levels. Further studies focused to assess the risk of underground employers are needed.

Energy aspects of the synchronization of model neurons.

We have deduced an energy function for a Hindmarsh-Rose model neuron and we have used it to evaluate the energy consumption of the neuron during its signaling activity. We investigate the balance of energy in the synchronization of two bidirectional linearly coupled neurons at different values of the coupling strength. We show that when two neurons are coupled there is a specific cost associated to the cooperative behavior. We find that the energy consumption of the neurons is incoherent until very near the threshold of identical synchronization, which suggests that cooperative behaviors without complete synchrony could be energetically more advantageous than those with complete synchrony.

Systemic lupus erythematosus in Europe at the change of the millennium: lessons from the "Euro-Lupus Project".

The "Euro-Lupus Cohort" is composed by 1000 patients with systemic lupus erythematosus (SLE) that have been followed prospectively since 1991. These patients have been gathered by a European consortium--the "Euro-Lupus Project Group". This consortium was originated as part of the network promoted by the "European Working Party on SLE", a working group created in 1990 in order to promote research in Europe on the different problems related to this disease. The "Euro-Lupus Cohort" provides an updated information on the SLE morbidity and mortality characteristics in the present decade as well as defines several clinical and immunological prognostic factors.

Dust in the underground railway tunnels of an Italian town.

This article assesses hazards associated with exposure to dust in tunnels and platforms of the A and B lines of Rome's underground railway and provides an informed opinion on the risks to workers and the travelling public of exposure to tunnel dust. The study focused on the analysis and measurement of dust granulometric classes PM10, respirable fraction, respirable combustible dust, and the organic, metallic, siliceous, and fibrous components. Comparing the measurement values from the tunnels and platforms with those found at the entrances to the underground railway stations, it emerges that dust concentration in the tunnels and platforms is three times higher, with a maximum PM10 value of 479 microg/m3. Averaged over 24 hours, in relation to the above ground levels, drivers and station staff are exposed to an additional value of 11 microg/m3 and 10 microg/m3, respectively. If commuters were to remain in the trains or on the station platforms, the 24-hour average exposure would increase by 3 microg/m3. Iron and silica were the major components found in the dust. The use of silica sand in the emergency braking system of the carriages is capable of causing a dispersion of quartz in the air in percentages varying from 5% to 14%. Methods are suggested in this article for the reduction of dust dispersion.

Minimization of the energy flow in the synchronization of nonidentical chaotic systems.

We argue that maintaining a synchronized regime between different chaotic systems requires a net flow of energy between the guided system and an external energy source. This energy flow can be spontaneously reduced if the systems are flexible enough as to structurally approach each other through an adequate adaptive change in their parameter values. We infer that this reduction of energy can play a role in the synchronization of bursting neurons and other natural oscillators.