Profiling allergic asthma volatile metabolic patterns using a headspace-solid phase microextraction/gas chromatography based methodology

Allergicasthmarepresentsanimportantpublichealthissuewithsignificantgrowthovertheyears,especially in the paediatric population. Exhaled breath is a non-invasive, easily performed and rapid method forobtainingsamplesfromthelowerrespiratorytract.Inthepresentmanuscript,themetabolicvolatile profiles of allergic asthma and control children were evaluated by headspace solid-phase microextraction combined with gas chromatography–quadrupole mass spectrometry (HS-SPME/GC–qMS). The lack ofstudiesinbreathofallergicasthmaticchildrenbyHS-SPMEledtothedevelopmentofanexperimental design to optimize SPME parameters. To fulfil this objective, three important HS-SPME experimental parameters that influence the extraction efficiency, namely fibre coating, temperature and time extractions were considered. The selected conditions that promoted higher extraction efficiency corresponding to the higher GC peak areas and number of compounds were: DVB/CAR/PDMS coating fibre, 22◦C and 60min as the extraction temperature and time, respectively. The suitability of two containers, 1L Tedlar® bags and BIOVOC®, for breath collection and intra-individual variability were also investigated. The developed methodology was then applied to the analysis of children exhaled breath with allergicasthma(35),fromwhich13hadalsoallergicrhinitis,andhealthycontrolchildren(15),allowing to identify 44 volatiles distributed over the chemical families of alkanes (linear and ramified) ketones, aromatic hydrocarbons, aldehydes, acids, among others. Multivariate studies were performed by Partial LeastSquares–DiscriminantAnalysis(PLS–DA)usingasetof28selectedmetabolitesanddiscrimination between allergic asthma and control children was attained with a classification rate of 88%. The allergic asthma paediatric population was characterized mainly by the compounds linked to oxidative stress, such as alkanes and aldehydes. Furthermore, more detailed information was achieved combining the volatile metabolic data, suggested by PLS–DA model, and clinical data.

Technologies that motivates healthy toothbrushing: practices through social translucence

Fifty percent of the European Union’s population suffers from an oral disease. Studies have repeatedly shown that while acquiring healthy toothbrushing practices early on in one’s life is of significance, children and adults often fail to adhere to those. In this thesis we attempt to design and prototype interactive technologies that motivate healthy tooth brushing habits on individuals. Rather than focusing on the technologies’ persuasive power over individuals, we tap on the social mechanisms employed by families. In this sense, we think of these technologies as social translucent rather than persuasive, whose goal is to raise awareness within the family on each other’s habits and that aim at leveraging families’ existing social mechanisms for behavior change, rather than replacing them. More specifically, we aim to gain insights with respect to the following questions: a) What are the drivers and barriers towards adhering to healthy tooth brushing behaviors? b) Can we effectively measure toothbrushing behaviors? c) How can technologies leverage family communication practices in motivating proper toothbrushing behaviors? First, we present two studies about children and adults’ tooth brushing behaviors and how these are influenced by social interactions within the family. Secondly, we present the design and prototyping of two systems that sense toothbrushing practices and provide feedback, using the Social Translucence Framework as a design lens. We conclude with an overview of lessons learnt from the prototyping of these systems supported by an analysis of the strengths and pitfalls of the developed technologies.