Search for Borrelia sp. in ticks collected from potential reservoirs in an urban forest reserve in the State of Mato Grosso do Sul, Brazil: a short report

A total of 128 ticks of the genus Amblyomma were recovered from 5 marsupials (Didelphis albiventris) - with 4 recaptures - and 17 rodents (16 Bolomys lasiurus and 1 Rattus norvegicus) captured in an urban forest reserve in Campo Grande, State of Mato Grosso do Sul, Brazil. Of the ticks collected, 95 (78.9%) were in larval form and 22 (21.1%) were nymphs; the only adult (0.8%) was identified as A. cajennense. Viewed under dark-field microscopy in the fourth month after seeding, 9 cultures prepared from spleens and livers of the rodents, blood of the marsupials, and macerates of Amblyomma sp. nymphs revealed spiral-shaped, spirochete-like structures resembling those of Borrelia sp. Some of them showed little motility, while others were non-motile. No such structures could be found either in positive Giemsa-stained culture smears or under electron microscopy. No PCR amplification of DNA from those cultures could be obtained by employing Leptospira sp., B. burgdorferi, and Borrelia sp. primers. These aspects suggest that the spirochete-like structures found in this study do not fit into the genera Borrelia or Leptospira, requiring instead to be isolated for proper identification.

Machine learning algorithms for spatial data. Case studies: Environmental pollution, natural hazards, renewable resources

This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

Leukemic cluster growth in culture is an independent risk factor for acute myeloid leukemia and short survival in patients with myelodysplastic syndrome

In patients with myelodysplastic syndrome (MDS) precursor cell cultures (colony-forming unit cells, CFU-C) can provide an insight into the growth potential of malignant myeloid cells. In a retrospective single-center study of 73 untreated MDS patients we assessed whether CFU-C growth patterns were of prognostic value in addition to established criteria. Abnormalities were classified as qualitative (i.e. leukemic cluster growth) or quantitative (i.e. strongly reduced/absent growth). Thirty-nine patients (53%) showed leukemic growth, 26 patients (36%) had strongly reduced/absent colony growth, and 12 patients showed both. In a univariate analysis the presence of leukemic growth was associated with strongly reduced survival (at 10 years 4 vs. 34%, p = 0.004), and a high incidence of transformation to AML (76 vs. 32%, p = 0.01). Multivariate analysis identified leukemic growth as a strong and independent predictor of early death (relative risk 2.12, p = 0.03) and transformation to AML (relative risk 2.63, p = 0.04). Quantitative abnormalities had no significant impact on the disease course. CFU- C assays have significant predictive value in addition to established prognostic factors in MDS. Leukemic growth identifies a subpopulation of MDS patients with poor prognosis.

Quantification of in vivo short echo-time proton magnetic resonance spectra at 14.1 T using two different approaches of modelling the macromolecule spectrum

Reliable quantification of the macromolecule signals in short echo-time H-1 MRS spectra is particularly important at high magnetic fields for an accurate quantification of metabolite concentrations (the neurochemical profile) due to effectively increased spectral resolution of the macromolecule components. The purpose of the present study was to assess two approaches of quantification, which take the contribution of macromolecules into account in the quantification step. H-1 spectra were acquired on a 14.1 T/26 cm horizontal scanner on five rats using the ultra-short echo-time SPECIAL (spin echo full intensity acquired localization) spectroscopy sequence. Metabolite concentrations were estimated using LCModel, combined with a simulated basis set of metabolites using published spectral parameters and either the spectrum of macromolecules measured in vivo, using an inversion recovery technique, or baseline simulated by the built-in spline function. The fitted spline function resulted in a smooth approximation of the in vivo macromolecules, but in accordance with previous studies using Subtract-QUEST could not reproduce completely all features of the in vivo spectrum of macromolecules at 14.1 T. As a consequence, the measured macromolecular 'baseline' led to a more accurate and reliable quantification at higher field strengths.

BlastR--fast and accurate database searches for non-coding RNAs.

We present and validate BlastR, a method for efficiently and accurately searching non-coding RNAs. Our approach relies on the comparison of di-nucleotides using BlosumR, a new log-odd substitution matrix. In order to use BlosumR for comparison, we recoded RNA sequences into protein-like sequences. We then showed that BlosumR can be used along with the BlastP algorithm in order to search non-coding RNA sequences. Using Rfam as a gold standard, we benchmarked this approach and show BlastR to be more sensitive than BlastN. We also show that BlastR is both faster and more sensitive than BlastP used with a single nucleotide log-odd substitution matrix. BlastR, when used in combination with WU-BlastP, is about 5% more accurate than WU-BlastN and about 50 times slower. The approach shown here is equally effective when combined with the NCBI-Blast package. The software is an open source freeware available from www.tcoffee.org/blastr.html.

Cook it! Fun, fast food for less: community nutrition education programme

This training manual was produced to support the Cook it! programme, which was specially developed for use in Northern Ireland. The Cook it! programme is delivered in the community by trained facilitators and can be used with a wide range of groups, including young/single parents, young people leaving residential care, offenders during rehabilitation programmes, older people in sheltered accomodation etc.The manual contains all the information needed to deliver Cook it! programmes in the community, including background information on healthy eating, information about dealing with special dietary requirements, sessions outlines, photocopiable resources and 75 recipes for snacks and meals.This updated version replaces the March 2007 edition.For information on training as a Cook it! facilitator, contact the health promotion service in your local Health and Social Care Trust.

Obesity and the environment: regulating the growth of fast food outlets

A ‘healthy people, healthy places’ briefing. This briefing summarises the importance of action on obesity and a specific focus on fast food takeaways, and outlines the regulatory and other approaches that can be taken at local level. Th briefing paper addresses the opportunities to limit the number of fast food takeaways (especially near schools) and ways in which fast food offers can be made healthier.

UOC Algorithms

Aplicació per a iPad a mode de repositori de continguts relacionats amb l'ensenyament d'assignatures d'informàtica.

Effects of tetrodotoxin and ion replacements on the short-circuit current induced by Escherichiacoli heat stable enterotoxin across small intestine of the gerbil (Gerbillus cheesmani)

The effects of mucosally added Escherichia coli heat stable enterotoxin (STa 30 ng ml-1) on the basal short-circuit current (Isc in µA cm-2) across stripped and unstripped sheets of jejuna and ilea taken from fed, starved (4 days, water ad lib) and undernourished (50% control food intake for 21 days) gerbil (Gerbillus cheesmani) were investigated. The effect of neurotoxin tetrodotoxin (TTX 10 µM) and the effects of replacing chloride by gluconate or the effects of removing bicarbonate from bathing buffers on the maximum increase in Isc induced by STa were also investigated. The maximum increase in Isc which resulted from the addition of STa were significantly higher in jejuna and ilea taken from starved and undernourished gerbils when compared with the fed control both using stripped and unstripped sheets. In the two regions of the small intestine taken from fed and starved animals TTX reduced the maximum increase in Isc induced by STa across unstripped sheets only. Moreover in jejuna and ilea taken from undernourished gerbils TTX reduced significantly the maximum increase in Isc induced by STa across stripped and unstripped sheets. Replacing chloride by gluconate decreased the maximum increase in Isc induced by STa across jejuna and ilea taken from undernourished gerbils only. Removing bicarbonates from bathing buffer decreased the maximum increase in Isc across the jejuna and ilea taken from starved and undernourished gerbils.

Traitement non chirurgical des rectites postactiniques ou radiques chroniques [Non-surgical treatment of acute and late radiation proctitis]

Pelvic external radiotherapy with or without brachytherapy plays an important role in the management of pelvic cancers. Despite recent technical innovations including conformal three-dimensional (3D) external beam radiotherapy and more recently intensity modulated radiotherapy (IMRT), local side effects can occur secondary to normal tissue damage caused by ionising radiation. Morbidity depends on the anatomic position of the rectum within the pelvis and the fast turnover rate of the mucosa, as well as the characteristics of the radiation treatment and patient co-morbidities. Medical management is sometimes complex and merits herein a short review.

The effect of thrombolysis on short-term improvement depends on initial stroke severity.

A large number of parameters have been identified as predictors of early outcome in patients with acute ischemic stroke. In the present work we analyzed a wide range of demographic, metabolic, physiological, clinical, laboratory and neuroimaging parameters in a large population of consecutive patients with acute ischemic stroke with the aim of identifying independent predictors of the early clinical course. We used prospectively collected data from the Acute Stroke Registry and Analysis of Lausanne. All consecutive patients with ischemic stroke admitted to our stroke unit and/or intensive care unit between 1 January 2003 and 12 December 2008 within 24 h after last-well time were analyzed. Univariate and multivariate analyses were performed to identify significant associations with the National Institute of Health Stroke Scale (NIHSS) score at admission and 24 h later. We also sought any interactions between the identified predictors. Of the 1,730 consecutive patients with acute ischemic stroke who were included in the analysis, 260 (15.0%) were thrombolyzed (mostly intravenously) within the recommended time window. In multivariate analysis, the NIHSS score at 24 h after admission was associated with the NIHSS score at admission (β = 1, p < 0.001), initial glucose level (β = 0.05, p < 0.002) and thrombolytic intervention (β = -2.91, p < 0.001). There was a significant interaction between thrombolysis and the NIHSS score at admission (p < 0.001), indicating that the short-term effect of thrombolysis decreases with increasing initial stroke severity. Thrombolytic treatment, lower initial glucose level and lower initial stroke severity predict a favorable early clinical course. The short-term effect of thrombolysis appears mainly in minor and moderate strokes, and decreases with increasing initial stroke severity.