Currently, a small number of diseases, particularly cardiovascular (CVDs), oncologic (ODs), neurodegenerative (NDDs), chronic respiratory diseases, as well as diabetes, form a severe burden to most of the countries worldwide. Hence, there is an urgent need for development of efficient diagnostic tools, particularly those enabling reliable detection of diseases, at their early stages, preferably using non-invasive approaches. Breath analysis is a non-invasive approach relying only on the characterisation of volatile composition of the exhaled breath (EB) that in turn reflects the volatile composition of the bloodstream and airways and therefore the status and condition of the whole organism metabolism. Advanced sampling procedures (solid-phase and needle traps microextraction) coupled with modern analytical technologies (proton transfer reaction mass spectrometry, selected ion flow tube mass spectrometry, ion mobility spectrometry, e-noses, etc.) allow the characterisation of EB composition to an unprecedented level. However, a key challenge in EB analysis is the proper statistical analysis and interpretation of the large and heterogeneous datasets obtained from EB research. There is no standard statistical framework/protocol yet available in literature that can be used for EB data analysis towards discovery of biomarkers for use in a typical clinical setup. Nevertheless, EB analysis has immense potential towards development of biomarkers for the early disease diagnosis of diseases.

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The growing cancer incidence and mortality worldwide claims for the development of novel diagnostic strategies. In this study we aimed to explore the potential of an innovative methodology, based on a needle trap microextraction (NTME), combined with gas chromatography-mass spectrometry (GC-MS), as new approach to isolate and profile urinary volatile organic metabolites (VOMs) from lung cancer (LC) patients and healthy individuals (CTRL). In this context, different experimental parameters with influence of NTME extraction efficiency including, temperature, equilibration time, headspace volume, ionic strength, pH, effects of sample volume and stirring, were investigated and optimized. For the DVB/CarX/Car1000 needle trap device (NTD), the best results were obtained using 40 mL headspace of a 4-mL acidified (pH = 2) urine sample with 20% NaCl and an extraction temperature of 50 °C for 40 min of equilibration time. The stability of the isolated VOMs was investigated up to 72 h after extraction. From the VOMs identified, belonging namely to ketones, sulphur and benzene derivatives, 98 presented a frequency of occurrence above 90%. Data were processed by discriminant analysis, retrieving differentiated clusters for LC and CTRL groups. As far we are aware, this is the first study using NTME/GC-MS to establish urinary volatomic profiles. Preliminary results are very promising, as broad and comprehensive volatile profiles were obtained. Moreover, the extended storage stability of the NTD devices opens new opportunities for sampling other matrices in a wide range of applications.

MEPS, the acronym of microextraction by packed sorbent, is a simple, fast and user- and environmentally-friendly miniaturization of the popular solid-phase extraction technique (SPE).