Resultados de investigación

Relative concentrations of 74 inflammation-related serum proteins obtained by proximity extension assay (PEA, Olink) in patients with celiac disease and in non-celiac controls. Measurements were obtained while participants were on a gluten-free diet (≥1 month) at two time points: baseline (on GFD) and 4 hours after a single gluten challenge (10 g). NA indicates values below the limit of quantification., Background Diagnosis of celiac disease (CD) remains challenging in individuals already on a gluten-free diet (GFD). Although several alternative methods have been proposed, they have limitations. Identifying inflammation-related proteins that rapidly respond to gluten exposure in blood may offer diagnostic alternatives. Objective To characterize the inflammatory protein response to gluten in patients with CD on a GFD, and to assess the diagnostic potential of candidate biomarkers and their association with clinical symptoms. Methods Seventeen patients with CD and 15 non-CD individuals on a GFD (≥ 1 month) consumed 10 g of gluten. Serum, plasma and clinical symptoms were collected at baseline and 4 h post-gluten ingestion to assess changes in 92 inflammation-related proteins. Results Following gluten consumption, 18 proteins changed significantly only in patients with CD. Six showed an AUC ≥80%, and CCL20 achieved 85.7% sensitivity and 92.7% specificity for CD diagnosis. CCL20 level increases post-gluten challenge were higher in patients with vomiting but were also observed in those with absent or mild symptoms. Conclusion Gluten reintroduction triggers alterations in the inflammation-related protein profile of patients with CD. CCL20 emerges as a promising diagnostic candidate, its increase in plasma or serum, with low dependence on symptom presentation, may complement existing diagnostic approaches., Base de datos

We propose a scan test for the presence of spatial groupwise heteroskedasticity in cross-sectional data. The scan approach has been used in different fields before, including spatial econometric models, to detect instability in mean values of variables or regression residuals. In this paper, we extend its use to second order moments. Using large Monte Carlo simulations, we check the reliability of the proposed scan procedure to detect instabilities in the variance, the size and power of the test and its accuracy to find spatial clusters of observations with similar variances. Finally, we illustrate the usefulness of this test to improve the specification search in a spatial hedonic model, with an empirical application on housing prices in Madrid. | How to cite the database (APA style): Chasco, C.; Le Gallo, J. & López, FF. (2018). A scan test for spatial groupwise heteroscedasticity in cross-sectional models with an application on houses prices in Madrid [Data set & Code]. (doi: 10.23728/b2share.b862dd888bbd4799a86896c0763668a4).

In order to improve the skill of our telecommunication degree students, a group of teachers at the School of Telecommunication Engineering of the Universidade de Vigo set up the LIZGAIRO project as the means to introduce Agile techniques, and Scrum in particular, across a set of subjects in different courses both of the undergraduate and the graduate level. These datasets collect the responses to the surveys evaluating the satisfaction of students and teachers with the project.

Dataset of 400 pomegranate tree (Punica granatum L. ‘Wonderful’) images, with the corresponding fruit masks. The dataset is designed for training artificial intelligence models for instance segmentation. The pictures were collected by means of mobile devices (smartphones), in random trees, from different distances, orientations and in varying lighting conditions. The resolution of the images and masks is 640x480 pixels. The dataset is divided into training (70%), validation (15%) and test set (15%). Stratification was performed in 3 periods of the season to ensure that all fruit ripening stages were present in each subset. Masks consist of a very detailed manual annotation of the visible part for each of the fruits in the images.

Surfactants are often used in oral health products. The use these compounds has been related to several oral diseases. However, oral care products without surfactants have been unsuccessful as these components fulfil several functions. They serve as solubilizing, dispersing, emulsifying and wetting agents. They also promote foaming which provides a perception of cleanliness. Thus, a widespread use of oral care formulations without surfactants is unrealistic. It is then of interest to identify those with lower adverse effects. In this context, it is of great value to understand how surfactants interact with the first interfacial layer that they encounter i.e., salivary pellicles. These are proteinaceous nm-thick films that form on any type of surface upon exposure to saliva and that fulfil many functions e.g., they protect, lubricate and hydrate underlying oral tissues. The applicants have previously shown that Neutron Reflectometry (NR) is a powerful tool to investigate the structure of salivary pellicles. Here, we propose to use NR to study how their structure is affected by surfactants of relevance within oral care formulations.

Orthophotos, digital terrain models etc. provided by SDFE. See more information in the metadata file.This item is a part of the collection "Dataset for Bellinge: An urban drainage case study", https://doi.org/10.11583/DTU.c.5029124 Changes in version 2 - 31-08-2021- Updated documentation file- New names to subfolders