Joseph De Brabanter

Antioxidant potential of microalgae in relation to their phenolic and carotenoid content

In the past decades, food scientists have been searching for natural alternatives to replace synthetic antioxidants. In order to evaluate the potential of microalgae as new source of safe antioxidants, 32 microalgal biomass samples were screened for their antioxidant capacity using three antioxidant assays, and both total phenolic content and carotenoid content were measured. Microalgae were extracted using a one-step extraction with ethanol/water, and alternatively, a three-step fractionation procedure using successively hexane, ethyl acetate, and water. Antioxidant activity of the extracts varied strongly between species and further depended on growth conditions and the solvent used for extraction. It was found that industrially cultivated samples of Tetraselmis suecica, Botryococcus braunii, Neochloris oleoabundans, Isochrysis sp., Chlorella vulgaris, and Phaeodactylum tricornutum possessed the highest antioxidant capacities in this study and thus could be a potential new source of natural antioxidants. The results from the different types of extracts clearly indicated that next to the well-studied carotenoids, phenolic compounds also contribute significantly to the antioxidant capacity of microalgae.

Distributed, Signal Strength-Based Indoor Localization Algorithm for Use in Healthcare Environments

In current healthcare environments, a trend toward mobile and personalized interactions between people and nurse call systems is strongly noticeable. Therefore, it should be possible to locate patients at all times and in all places throughout the care facility. This paper aims at describing a method by which a mobile node can locate itself indoors, based on signal strength measurements and a minimal amount of yes/no decisions. The algorithm has been developed specifically for use in a healthcare environment. With extensive testing and statistical support, we prove that our algorithm can be used in a healthcare setting with an envisioned level of localization accuracy up to room revel (or region level in a corridor), while avoiding heavy investments since the hardware of an existing nurse call network can be reused. The approach opted for leads to very high scalability, since thousands of mobile nodes can locate themselves. Network timing issues and localization update delays are avoided, which ensures that a patient can receive the needed care in a time and resources efficient way.

Statistical approach of assessing the reliability of glucose sensors: the GLYCENSIT procedure.

Background: In healthcare, patients with diabetes are instructed on how to apply intensified insulin therapy in an optimal manner. Tight blood glucose control is also performed on patients treated in the intensive care unit (ICU). Different blood glucose meters and glucose monitoring systems (GMSs) are used to achieve this goal, and some may lack reliability. Methods: The GLYCENSIT procedure is a statistical assessment tool we are proposing for evaluating the significant difference of paired glucose measurements. The performance of the GlucoDay® system in the ICU is analyzed with GLYCENSIT. Results: The GLYCENSIT analysis comprises three phases: testing possible persistent measurement behavior as a function of the glycemic range, testing the number of measurement errors with respect to a standard criterion for binary assessment of glucose sensors, and computing the tolerance intervals that indicate possible test sensor deviations for new observations. The probability of the tolerance intervals directly reflects the number of samples and additionally improves current assessment techniques. The method can be tuned according to the clinicians preferences regarding significance level, tolerance level, and glycemic range cutoff values. The measurement behavior of the GlucoDay sensor is found to be persistent but inaccurate and returns wide tolerance intervals, suggesting that the GlucoDay sensor may not be sufficiently reliable for glycemia control in the ICU. Conclusions: The GLYCENSIT procedure aims to serve as statistical guide for clinicians in the assessment of glucose sensor devices.

Phylogenetic signal in phenotypic traits related to carbon source assimilation and chemical sensitivity in Acinetobacter species

A common belief is that the phylogeny of bacteria may reflect molecular functions and phenotypic characteristics, pointing towards phylogenetic conservatism of traits. Here, we tested this hypothesis for a large set of Acinetobacter strains. Members of the genus Acinetobacter are widespread in nature, demonstrate a high metabolic diversity and are resistant to several environmental stressors. Notably, some species are known to cause opportunistic human infections. A total of 133 strains belonging to 33 species with validly published names, two genomic species and species of an as-yet unknown taxonomic status were analyzed using the GENIII technology of Biolog, which allows high-throughput phenotyping. We estimated the strength and significance of the phylogenetic signal of each trait across phylogenetic reconstructions based on partial RNA polymerase subunit B (rpoB) and core genome sequences. Secondly, we tested whether phylogenetic distance was a good predictor of trait differentiation by Mantel test analysis. And finally, evolutionary model fitting was used to determine if the data for each phenotypic character was consistent with a phylogenetic or an essentially random model of trait distribution. Our data revealed that some key phenotypic traits related to substrate assimilation and chemical sensitivity are linked to the phylogenetic placement of Acinetobacter species. The strongest phylogenetic signals found were for utilization of different carbon sources such as some organic acids, amino acids and sugars, thus suggesting that in the diversification of Acinetobacter carbon source assimilation has had a relevant role. Future work should be aimed to clarify how such traits have shaped the remarkable ability of this bacterial group to dominate in a wide variety of habitats.

Characterization of the bacterial community composition in water of drinking water production and distribution systems in Flanders, Belgium

The quality of drinking water is influenced by its chemical and microbial composition which in turn may be affected by the source water and the different processes applied in drinking water purification systems. In this study, we investigated the bacterial diversity in different water samples from the production and distribution chain of thirteen drinking water production and distribution systems from Flanders (Belgium) that use surface water or groundwater as source water. Water samples were collected over two seasons from the source water, the processed drinking water within the production facility and out of the tap in houses along its distribution network. 454‐pyrosequencing of 16S ribosomal RNA gene sequences revealed a total of 1,570 species‐level bacterial operational taxonomic units. Strong differences in community composition were found between processed drinking water samples originating from companies that use surface water and other that use groundwater as source water. Proteobacteria was the most abundant phylum in all samples. Yet, several phyla including Actinobacteria were significantly more abundant in surface water while Cyanobacteria were more abundant in surface water and processed water originating from surface water. Gallionella, Acinetobacter, and Pseudomonas were the three most abundant genera detected. Members of the Acinetobacter genus were even found at a relative read abundance of up to 47.5% in processed water samples, indicating a general occurrence of Acinetobacter in drinking water (systems).