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Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2021. For permissions please email: Journals.permissions@oup.com. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model), Pulmonary embolism (PE) is a recognized complication of SARS-COV2 infection due to hypercoagulability. Before the COVID era, the need for computed tomography pulmonary angiography (CTPA) to rule out PE was determined by clinical probability, based on Wells and Geneva scores, in association with D-dimer measurements. However, patients with SARS-COV2 infection have a pro-thrombotic and pro-inflammatory state which may compromise the usefulness of these algorithms to select patients for CTPA.

A total of 35 Brazilian isolates of Clostridium difficile from faecal stools and four isolates from hospital environments were analyzed by PCR ribotyping. A whole cell protein profile (as an alternative for serogrouping), in vitro toxin production and susceptibility to vancomycin, metronidazole and clindamycin were also investigated. All strains were typeable by both phenotypic and genotypic methods, and a total of 13 different PCR ribotypes were identified, of which seven (132, 133, 134, 135, 136, 142 and 143) were considered new types and accounted for 78.5% of all samples evaluated (including hospital environments). A non-toxigenic C. difficile PCR ribotype 133 was detected in all children groups examined (inpatients, outpatients and healthy children), whilst toxigenic PCR ribotypes 015, 131, 134 and 135 were associated mostly with symptomatic children. Serogroups G and D were disseminated both in patients from the community and from the pediatric hospital, with group G prevalent among outpatient children. All strains were susceptible to vancomycin and metronidazole but high levels of resistance to clindamycin were found, especially among serogroups G and D. Co-existence of different ribotypes and serogroups in the same individual was observed. The new seven ribotypes found in this investigation may represent strains characteristic of this region of Brazil.

The revision of the 1995 land cover dataset for the Vale do Sousa region, in the northwest of Portugal, was carried out by supervised classification of a multi‐spectral image from the Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) sensor. The nine reflective bands of ASTER were used, covering the spectral range from 0.52–2.43 µm. The image was initially ortho‐rectified and segmented into 51 186 objects, with an average object size of 135 pixels (about 3 ha). A total of 582 of these objects were identified for training nine land cover classes. The image was classified using an algorithm based on a fuzzy classifier, Support Vector Machines (SVM), K Nearest Neighbours (K‐NN) and a Logistic Discrimination (LD) classifier. The results from the classification were evaluated using a set of 277 validation sites, independently gathered. The overall accuracy was 44.6% for the fuzzy classifier, 70.5% for the SVM, 60.9% for the K‐NN and 72.2% for the LD classifier. The difficulty in discrimin...

The ability of Bacteroides fragilis strains, isolated from various sources, to produce bacteriocin was evaluated. All strains isolated from intestinal infections were producers in high levels and less susceptible to the others. Strains from other origins were found to produce bacteriocin at a medium level and they were variably susceptible. Some properties of one bacteriocin produced by the Bact. fragilis 079298-3 strain were analysed, providing evidence of its protein nature, with stability over a wide range of pH and retained inhibitory activity after heating. This variability seems to suggest that bacteriocin typing is a good method for this species.

Summary Bacteroides fragilis strains isolated from different sources, i. e. 1 strain (AA1) from an aquatic environment, 1 strain from normal flora (118310) and the type strain (ATCC 25285) originally isolated from clinical material, were analysed for both cell envelope proteins composition and surviving under oxidative stress starvation. All strains examined showed a similar survival response when cultured in drinking water with a ten-fold decrease in viable counts per day during the 7 days of analysis. The outer membrane protein (OMP) profiles of all strains were quite similar during the stress period as determined by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). However, the periplasmic proteins of the strain 118310 showed two protein bands at 48 and 58 kDa, respectively, that were absent in the strains AA1 and ATCC 25285 during the incubation period in potable water. Whole cells and periplasmic 35S-labelled proteins from bacteria cultured in drinking water showed a significant increase in proteins at 16, 18, 24, 26, 35, 48, and 58 kDa and 18, 22, 24, 48, 58, and 70 kDa, respectively, in all strains when compared to cells grown in BHI-PRAS media as detected by autoradiography following SDS-PAGE. These data suggest that B. fragilis may have a synthesis mechanism that allows them to adapt to adverse environments.

This communication describes a new method for producing stable, high concentrations of Sc2+ in optically clear CaF2 crystals. We have achieved Sc2+ concentrations as high as 3 × 1018 cm−3 without degradation of optical quality. We have converted as much as 5% of the scandium dopant to the divalent state. The concentration of divalent scandium is stable during room temperature storage for periods of at least one year.

UV and X-ray astronomy need hyperspectral imaging devices, i.e. large format (1000/spl times/1000) arrays of pixels in which each single-photon event is tagged with spectral information. Such devices permit multicolor imagery and surveys to be obtained with a single camera. Here we discuss the first-stage of development of a new generation of UV/X-ray detectors that will provide 0.1-0.01% energy resolution in an array format.

Aerosol dispersion and deposition inside an idealized mouth-throat has been numerically simulated using a stochastic Lagrangian model accounting for Brownian motion and particle-wall interaction. Delivery of nanoparticles to the lungs is extremely difficult, mainly due to their low inertia, and for this reason they are often loaded into larger carrier particles. Bearing in mind the potentialities of nanoparticles in advanced drug delivery, a set of monodisperse particles with diameters in the nanqsize range, as well as in the respirable and carrier ranges, were considered in the present simulations. Deposition patterns were obtained by tracking a total of 16,000 particles for each diameter. The results have shown that similar patterns were obtained in the mouth-throat for 400 nm particles and larger. A clear correspondence between secondary flow structures in the fluid and these deposition patterns was observed, demonstrating the role of the convective transport processes for this size range. In contrast, a much more uniform distribution of the particles adhering to the walls was noted for a size of 200 nm. It was also found that a very large amount of these particles (nearly 80%) is lost by deposition on the mouth-throat, thus recommending the use of larger carrier particles.

Glass filaments containing digital holographic codes are ideal substrates for multiplexed bioreactions. We describe a multiplex assay platform that provides for many hundreds of unique probes in a single well of a standard 96-well microplate.

The preservation of musical works produced in the past requires their digitalization and transformation into a machine-readable format. The processing of handwritten musical scores by computers remains far from ideal. One of the fundamental stages to carry out this task is the staff line detection. We investigate a general-purpose, knowledge-free method for the automatic detection of music staff lines based on a stable path approach. Lines affected by curvature, discontinuities, and inclination are robustly detected. Experimental results show that the proposed technique consistently outperforms well-established algorithms.

Cosmetic assessment of conservative breast cancer treatment plays a major role in the study of breast cancer techniques. Objective assessment methods are being preferred to overcome the drawbacks of subjective evaluation. In this paper a methodology for the objective assessment of conservative breast cancer treatment is proposed. The quantitative measures used in this research provide an objective way to calculate the overall cosmetic result. We report experiments using support vector machines to derive an optimal assessment rule. The results seem to indicate that it is possible to construct an algorithm for a complete objective classification of the aesthetic result of breast conservative treatment.

We use tunable excitation from a Cr:LiSAF laser at 225 nm and 270-300 nm to excite emission from B. subtilis (globigii) spores (BG) and E. coli vegetative cells suspended in water. We report the dispersed fluorescence between 250 and 660 nm for both species. The 3400 cm−1 Raman shift from water provides intrinsic calibration which allows the determination of absolute fluorescence yields. Photobleaching of BG spores at 225, 275 and 300 nm shows an increase at shorter wavelengths. Reproducible spectra can only be obtained at laser powers below 5 mJ cm−2pulse−1.

The direct transformation of the energy of an incident high-energy photon into a measurable potential difference within an absorbing metal is investigated. Experimental evidence is presented that the effect arises from the inherent energy dependence of the electronic density of states, rather than from a simple temperature excursion. The similarities between the results on Al and YBa2Cu3O7 samples indicate that the effect is universal in nature. We assert it may be used as the basis of a fast, energy resolving, individual photon detector for the ultraviolet radiation and x-rays.

Clostridium difficile strains were detected in 14 of 210 (6.7 %) faecal samples from children in Rio de Janeiro, Brazil, by cultivating faeces on cycloserine/cefoxitin/fructose agar after alcohol-shock. Two main groups of children were studied: inpatients (n = 96) and outpatients (n = 114). The inpatient group consisted of children on antibiotics or immunosuppressors who presented with diarrhoea and other children who did not present with diarrhoea and were not under an antibiotic or chemotherapeutic regimen. Among the outpatients, two groups were examined: namely, a group that comprised children who presented with diarrhoea and were occasionally under an antibiotic regimen and another group that comprised patients who were not taking antibiotics. After cytotoxic assay, toxigenic C. difficile (Cd tox+) strains were detected in 4.2 % of inpatients and 3.5 % of outpatients. Exclusion of other infectious causes of diarrhoea indicated a typical case of C. difficile-associated paediatric diarrhoea in the community. Among Cd tox+ isolates, no variations were detected by PCR for toxin A that employed primers NK9 and NKVO11. No resistance was found to metronidazole or vancomycin among strains that were isolated from children who presented with diarrhoea, but the MIC(50) and MIC(90) values for clindamycin were 6-8 and 16 microg ml(-1), respectively. Resistance to clindamycin seems to be more disseminated in strains from outpatients than in those from inpatients (P0.05). In conclusion, these data suggest that investigation for C. difficile infection should be taken into account in paediatric diarrhoea in both inpatients and outpatients in developing countries.

This paper describes a new method for dealing with multiple regression problems. This method integrates a clustering technique with regression trees, leading to what we have named as clustered regression trees. We use the clustering method to form sub-samples of the given data that are similar in terms of the predictor variables. By proceeding this way we aim at facilitating the subsequent regression modeling process based on the assumption of a certain smoothness of the regression surface. For each of the found clusters we obtain a different regression tree. These clustered regression trees can be used to predict the response value for a query case by an averaging process based on the cluster membership probabilities of the case. We have carried out a series of experimental comparisons of our proposal that have shown a significant predictive accuracy advantage over the use of a single regression tree.

In this work, we present new ways of dealing with categorical attributes; in particular, the methodology introduced here concerns the use of these attributes in binary decision trees. We consider essentially two main operations; the first one consists in using the joint distribution of two or more categorical attributes in order to increase the final performance of the decision tree; the second - and the most important - operation, concerns the extraction of relatively few predictive binary attributes from a categorical attribute; specially, when the latter has a large number of values. With more than two classes to predict, most of the present binary decision tree software needs to test an exponential number of binary attributes for each categorical attribute; which can be prohibitive. Our method, ARCADE, is independent of the number of classes to be predicted, and it starts by reducing significantly the number of values of the initial categorical attribute. This is done by clustering the initial values, using a hierarchical classification method. Each cluster of values will then represent a new value of a new categorical attribute. This new attribute will then be used in the decision tree, instead of the initial one. Nevertheless, not all of the binary attributes associated with this new categorical attribute will be used; only those which are predictive. The reduction in the complexity of the search for the best binary split is therefore enormous, as will be seen in the application that we consider; that is, the old and still lively protein secondary structure prediction problem.