218 research outputs found

    Influence of must racking and fining procedures on the composition of white wine

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    A study of the effects of two kinds of must clarification. settling or filtration by rotary vacuum filter and 5 juice fining treatments (bentonite, potassium caseinate, and combinations: bentonite + gelatin, and bentonite + caseinate + microcrystalline cellulose) on wine characteristics was carried out using must of the white cultivar Parellada. Although the general characteristics (ethanol, color, limpidity, residual sugars, pH and acidity) of Parerllada wines were not modified, some wine components (e.g. nitrogenous substances, phenolic compounds and aroma) were lowered according to the type of must racking and juice fining agent added. The percentage of decrease of wine characteristics due to the pre-fermentative fining agent depends on the type of must racking. Highest losses were recorded when rotary vacuum filters were used for must racking, and when bentonite (0.3-0.5 g/l) was added to the juice as a fining agent before fermentation

    EnvMine: A text-mining system for the automatic extraction of contextual information

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    <p>Abstract</p> <p>Background</p> <p>For ecological studies, it is crucial to count on adequate descriptions of the environments and samples being studied. Such a description must be done in terms of their physicochemical characteristics, allowing a direct comparison between different environments that would be difficult to do otherwise. Also the characterization must include the precise geographical location, to make possible the study of geographical distributions and biogeographical patterns. Currently, there is no schema for annotating these environmental features, and these data have to be extracted from textual sources (published articles). So far, this had to be performed by manual inspection of the corresponding documents. To facilitate this task, we have developed EnvMine, a set of text-mining tools devoted to retrieve contextual information (physicochemical variables and geographical locations) from textual sources of any kind.</p> <p>Results</p> <p>EnvMine is capable of retrieving the physicochemical variables cited in the text, by means of the accurate identification of their associated units of measurement. In this task, the system achieves a recall (percentage of items retrieved) of 92% with less than 1% error. Also a Bayesian classifier was tested for distinguishing parts of the text describing environmental characteristics from others dealing with, for instance, experimental settings.</p> <p>Regarding the identification of geographical locations, the system takes advantage of existing databases such as GeoNames to achieve 86% recall with 92% precision. The identification of a location includes also the determination of its exact coordinates (latitude and longitude), thus allowing the calculation of distance between the individual locations.</p> <p>Conclusion</p> <p>EnvMine is a very efficient method for extracting contextual information from different text sources, like published articles or web pages. This tool can help in determining the precise location and physicochemical variables of sampling sites, thus facilitating the performance of ecological analyses. EnvMine can also help in the development of standards for the annotation of environmental features.</p

    Fast pseudo-CT synthesis from MRI T1-weighted images using a patch-based approach

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    MRI-based bone segmentation is a challenging task because bone tissue and air both present low signal intensity on MR images, making it difficult to accurately delimit the bone boundaries. However, estimating bone from MRI images may allow decreasing patient ionization by removing the need of patient-specific CT acquisition in several applications. In this work, we propose a fast GPU-based pseudo-CT generation from a patient-specific MRI T1-weighted image using a group-wise patch-based approach and a limited MRI and CT atlas dictionary. For every voxel in the input MR image, we compute the similarity of the patch containing that voxel with the patches of all MR images in the database, which lie in a certain anatomical neighborhood. The pseudo-CT is obtained as a local weighted linear combination of the CT values of the corresponding patches. The algorithm was implemented in a GPU. The use of patch-based techniques allows a fast and accurate estimation of the pseudo-CT from MR T1-weighted images, with a similar accuracy as the patient-specific CT. The experimental normalized cross correlation reaches 0.9324±0.0048 for an atlas with 10 datasets. The high NCC values indicate how our method can accurately approximate the patient-specific CT. The GPU implementation led to a substantial decrease in computational time making the approach suitable for real applications

    APIR4EMC: Autocalibrated parallel imaging reconstruction for extended multi-contrast imaging

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    Purpose: To improve image quality of multi-contrast imaging with the proposed Autocalibrated Parallel Imaging Reconstruction for Extended Multi-Contrast Imaging (APIR4EMC). Methods: APIR4EMC reconstructs multi-contrast images in an autocalibrated parallel imaging reconstruction framework by adding contrasts as virtual coils. Compensation of signal evolution along the echo train of different contrasts is performed to improve signal prediction for missing samples. As a proof of concept, we performed prospectively accelerated phantom and in-vivo brain acquisitions with T1, T1-fat saturated (Fatsat), T2, PD, and FLAIR contrasts. The k-space sampling patterns of these acquisitions were jointly optimized. Images were jointly reconstructed with the proposed APIR4EMC method as well as individually with GRAPPA. Root mean square error (RMSE) to fully sampled reference images and g-factor maps were computed for both methods in the phantom experiment. Visual evaluation was performed in the in-vivo experiment. Results: Compared to GRAPPA, APIR4EMC reduced artifacts and improved SNR of the reconstructed images in the phantom acquisitions. Quantitatively, APIR4EMC substantially reduced noise amplification (g-factor) as well as RMSE compared to GRAPPA. Signal evolution compensation reduced artifacts. In the in-vivo experiments, 1 mm3 isotropic 3D images with contrasts of T1, T1-Fatsat, T2, PD, and FLAIR were acquired in as little as 7.5 min with the acceleration factor of 9. Reconstruction quality was consistent with the phantom results. Conclusion: Compared to single contrast reconstruction with GRAPPA, APIR4EMC reduces artifacts and noise amplification in accelerated multi-contrast imaging

    Autocalibrated parallel imaging reconstruction with sampling pattern optimization for GRASE: APIR4GRASE

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    Purpose: To reduce artifacts and scan time of GRASE imaging by selecting an optimal sampling pattern and jointly reconstructing gradient echo and spin echo images. Methods: We jointly reconstruct images for the different echo types by considering these as additional virtual coil channels in the novel Autocalibrated Parallel Imaging Reconstruction with Sampling Pattern Optimization for GRASE (APIR4GRASE) method. Besides image reconstruction, we identify optimal sampling patterns for the acquisition. The selected optimal patterns were validated on phantom and in-vivo acquisitions. Comparison to the conventional GRASE without acceleration, and to the GRAPPA reconstruction with a single echo type was also performed. Results: Using identified optimal sampling patterns, APIR4GRASE eliminated modulation artifacts in both phantom and in-vivo experiments; mean square error (MSE) was reduced by 78% and 94%, respectively, compared to the conventional GRASE with similar scan time. Both artifacts and g-factor were reduced compared to the GRAPPA reconstruction with a single echo type. Conclusion: APIR4GRASE substantially improves the speed and quality of GRASE imaging over the state-of-the-art, and is able to reconstruct both spin echo and gradient echo images

    Mycobiome Profiles in Breast Milk from Healthy Women Depend on Mode of Delivery, Geographic Location, and Interaction with Bacteria

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    Recent studies report the presence of fungal species in breast milk of healthy mothers, suggesting a potential role in infant mycobiome development. In the present work, we aimed to determine whether the healthy human breast milk mycobiota is influenced by geographical location and mode of delivery, as well as to investigate its interaction with bacterial profiles in the same samples. A total of 80 mature breast milk samples from 4 different countries were analyzed by Illumina sequencing of the internal transcribed spacer 1 (ITS1) region, joining the 18S and 5.8S regions of the fungal rRNA region. Basidiomycota and Ascomycota were found to be the dominant phyla, with Malassezia and Davidiella being the most prevalent genera across countries. A core formed by Malassezia, Davidiella, Sistotrema, and Penicillium was shared in the milk samples from the different origins, although specific shifts in mycobiome composition were associated with geographic location and delivery mode. The presence of fungi in the breast milk samples was further confirmed by culture and isolate characterization, and fungal loads were estimated by quantitative PCR (qPCR) targeting the fungal ITS1 region. Cooccurrence network analysis of bacteria and fungi showed complex interactions that were influenced by geographical location, mode of delivery, maternal age, and pregestational body mass index. The presence of a breast milk mycobiome was confirmed in all samples analyzed, regardless of the geographic origin.IMPORTANCE During recent years, human breast milk has been documented as a potential source of bacteria for the newborn. Recently, we have reported the presence of fungi in breast milk from healthy mothers. It is well known that environmental and perinatal factors can affect milk bacteria; however, the impact on milk fungi is still unknown. The current report describes fungal communities (mycobiota) in breast milk samples across different geographic locations and the influence of the mode of delivery. We also provide novel insights on bacterium-fungus interactions, taking into account environmental and perinatal factors. We identified a core of four genera shared across locations, consisting of Malassezia, Davidiella, Sistotrema, and Penicillium, which have been reported to be present in the infant gut. Our data confirm the presence of fungi in breast milk across continents and support the potential role of breast milk in the initial seeding of fungal species in the infant gut

    Standardizing admission and discharge processes to improve patient flow: a cross sectional study

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    Background: The aim of this study was to evaluate how hospital capacity was managed focusing on standardizing the admission and discharge processes. Methods: This study was set in a 900-bed university affiliated hospital of the National Health Service, near Barcelona (Spain). This is a cross-sectional study of a set of interventions which were gradually implemented between April and December 2008. Mainly, they were focused on standardizing the admission and discharge processes to improve patient flow. Primary administrative data was obtained from the 2007 and 2009 Hospital Database. Main outcome measures were median length of stay, percentage of planned discharges, number of surgery cancellations and median number of delayed emergency admissions at 8:00 am. For statistical bivariate analysis, we used a Chi-squared for linear trend for qualitative variables and a Wilcoxon signed ranks test and a Mann-Whitney test for non-normal continuous variables. Results: The median patients' global length of stay was 8.56 days in 2007 and 7.93 days in 2009 (p < 0.051). The percentage of patients admitted the same day as surgery increased from 64.87% in 2007 to 86.01% in 2009 (p < 0.05). The number of cancelled interventions due to lack of beds was 216 patients in 2007 and 42 patients in 2009. The median number of planned discharges went from 43.05% in 2007 to 86.01% in 2009 (p < 0.01). The median number of emergency patients waiting for an in-hospital bed at 8:00 am was 5 patients in 2007 and 3 patients in 2009 (p < 0.01). Conclusions: In conclusion, standardization of admission and discharge processes are largely in our control. There is a significant opportunity to create important benefits for increasing bed capacity and hospital throughput

    Defining functional distances over Gene Ontology

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    <p>Abstract</p> <p>Background</p> <p>A fundamental problem when trying to define the functional relationships between proteins is the difficulty in quantifying functional similarities, even when well-structured ontologies exist regarding the activity of proteins (i.e. 'gene ontology' -GO-). However, functional metrics can overcome the problems in the comparing and evaluating functional assignments and predictions. As a reference of proximity, previous approaches to compare GO terms considered linkage in terms of ontology weighted by a probability distribution that balances the non-uniform 'richness' of different parts of the Direct Acyclic Graph. Here, we have followed a different approach to quantify functional similarities between GO terms.</p> <p>Results</p> <p>We propose a new method to derive 'functional distances' between GO terms that is based on the simultaneous occurrence of terms in the same set of Interpro entries, instead of relying on the structure of the GO. The coincidence of GO terms reveals natural biological links between the GO functions and defines a distance model <it>D</it><sub><it>f </it></sub>which fulfils the properties of a Metric Space. The distances obtained in this way can be represented as a hierarchical 'Functional Tree'.</p> <p>Conclusion</p> <p>The method proposed provides a new definition of distance that enables the similarity between GO terms to be quantified. Additionally, the 'Functional Tree' defines groups with biological meaning enhancing its utility for protein function comparison and prediction. Finally, this approach could be for function-based protein searches in databases, and for analysing the gene clusters produced by DNA array experiments.</p
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