Systematic Review: Drug Repositioning for Congenital Disorders of Glycosylation (CDG)

Advances in research have boosted therapy development for congenital disorders of glycosylation (CDG), a group of rare genetic disorders affecting protein and lipid glycosylation and glycosylphosphatidylinositol anchor biosynthesis. The (re)use of known drugs for novel medical purposes, known as drug repositioning, is growing for both common and rare disorders. The latest innovation concerns the rational search for repositioned molecules which also benefits from artificial intelligence (AI). Compared to traditional methods, drug repositioning accelerates the overall drug discovery process while saving costs. This is particularly valuable for rare diseases. AI tools have proven their worth in diagnosis, in disease classification and characterization, and ultimately in therapy discovery in rare diseases. The availability of biomarkers and reliable disease models is critical for research and development of new drugs, especially for rare and heterogeneous diseases such as CDG. This work reviews the literature related to repositioned drugs for CDG, discovered by serendipity or through a systemic approach. Recent advances in biomarkers and disease models are also outlined as well as stakeholders’ views on AI for therapy discovery in CDG.     

Acoustic seafloor sediment classification using self-organizingfeature maps

A self-organizing feature map (SOFM), a kind of artificial neural network (ANN) architecture, is used in this work for continental shelf seafloor sediment classification. Echo data are acquired using an echosounding system from three types of seafloor sediment areas. Excellent classification (~100%) for an ideal output neuron grid size of 15×1 is obtained for a moving average of 35 input snapshots     

Assessing the feasibility of a global model for multi-temporal burned area mapping using SPOT-VEGETATION data

The possibility of using the Syst@me Probatoire de l'Observation de la Terre (SPOT)-VEGETATION (VGT) data for global burned area mapping with a single algorithm was investigated. Using VGT images from south-eastern Africa, the Iberian Peninsula and south-eastern Siberia/north-eastern China, we analysed the variability of the spectral signature of burned areas and its relationship with land cover, and performed the selection of the best variables for burned area mapping. The results show that in grasslands and croplands, near-infrared (NIR) and short-wave infrared (SWIR) reflectance always decreases as a result of fire. In forests and woodlands, there may occur a simultaneous decrease of SWIR and NIR or an increase of SWIR and a decrease of NIR. Burning of green vegetation (high values of the Normalized Difference Vegetation Index (NDVI)) tends to result in an increase of the SWIR. The best variables for burned area mapping are different in each region. Only the NIR allows a good discrimination of burned areas in all study areas. We derived a logistic regression model for multi-temporal burned area mapping in tropical, temperate and boreal regions, which handles the spectral variability of burned areas dependent on the type of vegetation. The results underline the feasibility of a single model for global burned area mapping.     

Characterizing landscape changes in central Rondonia using Landsat TM imagery

An analysis of landscape changes in a region of pioneer settlements in central Rondonia, western Brazilian Amazon, was derived from Landsat TM data. Total deforested area increased from 206 x 103 ha in 1977, to 565 x 103 ha in 1985 and to 1210 x 103 ha, or 35.5% of the region, in 1995. Eighty-one per cent of the total 1995 deforestation had occurred in regions within 12.5km from areas of pioneer colonization deforested by 1977. Deforested area exceeded 79% in regions within 12.5km from the region's first road.     

Application of SVM-RFE on EEG signals for detecting the most relevant scalp regions linked to affective valence processing

In this work, event related potentials (ERPs) induced by visual stimuli categorized with different value of affective valence are studied. EEG signals are recorded during visualization of selected pictures belonging to International Affective Picture System (IAPS). A Morlet wavelet filter is used to transform the EEG input space to a topography-time–frequency feature space. Support vector machine-recursive feature elimination (SVM-RFE) is applied for detecting scalp spectral dynamics of interest (SSDOIs) in this feature space, allowing to identify the most relevant time intervals, frequency bands and EEG channels. This feature selection method has proven to outperform the classical t-test in the discrimination of brain cortex regions involved in affective valence processing. Furthermore, the presented combination of feature extraction and selection techniques can be applied as an alternative in other different clinical applications.     

Monitoring of ochratoxin A exposure of the Portuguese population through a nationwide urine survey — Winter 2007

Ochratoxin A (OTA) is a mycotoxin produced by a variety of fungi, such as Penicillium verrucosum and Aspergillium spp., which has been found to have a wide number of potentially deadly toxic effects, and can enter the human organism through a variety of means. It then finds its way into the bloodstream and, after a lengthy process, is eventually excreted through the urine. It can thus be detected in its original form not only in blood samples but also in this biological medium. As such, and in an attempt to evaluate the exposure of the Portuguese population to this mycotoxin, morning urine samples were collected during the Winter of 2007, from each of five geographically distinct Portuguese locations — Bragança, Porto, Coimbra, Alentejo, and Algarve — and subjected to extraction by immunoaffinity columns and to OTA quantification through liquid chromatography coupled with fluorescence detection. Prevalent incidence was higher than 95% with Coimbra being the exception (incidence of 73.3%). In nearly all locations, the OTA content of most samples was found to be above the limit of quantification (LOQ) of 0.008 ng/ml. Indeed, excluding Coimbra, with an OTA content level of 0.014 ng/ml, all regions featured content values over 0.021 ng/ml.     

Assessment of the presence and dynamics of fungi in drinking water sources using cultural and molecular methods

A comparison of different isolation techniques and culture media for detection of filamentous fungi and yeasts in the aquatic environment revealed that the use of membrane filtration with the media dichloran rose bengal chloramphenicol (DRBC) optimized fungi detection in terms of abundance and variety in three untreated water sources with very different characteristics (surface water, spring water, and groundwater). The diversity of the fungi population captured by direct DNA extraction of fungi collected by membrane filtration was compared with the isolates obtained after selective growth using different culture media through amplification of the internal transcribed spacer gene and denaturing gradient gel electrophoresis (DGGE). The Czapek-Dox agar, Sabouraud dextrose agar, and DRBC media showed closer similarities to those obtained by the uncultured biomass for the different water sources. Based on these data and the best enumeration results, DRBC is recommended for the assessment of fungi in water sources using culture-based methods. DGGE was also used to monitor temporal variations in the fungal population structure and showed that each water matrix possessed a distinct population profile as well as that changes in the fungal community can be expected in the different matrices throughout the year.     

Characterization of new FIR laser lines from CD3-rockingand asymmetric CD3 deformation modes of 13CD3OD

In this paper, we report new optically pumped far-infrared (FIR) laser lines from the in-plane CD₃-rocking and asymmetric CD ₃ deformation absorption vibrational bands of ¹³CD ₃OD. A waveguide CO₂ laser of wide tunability (290 MHz) was used as the pump source, and a Fabry-Perot open cavity as the FIR laser resonator. Optoacoustic absorption spectrum was used as a guide to search for new FIR laser lines. We could observe 13 new laser lines in the range 103-491 μm. The lines were characterized according to wavelength, relative polarization, relative intensity, and optimum working pressure. The transferred lamb-dip technique was used to measure the frequency absorption transition for both new and previously reported laser lines