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The bedside Exhaled Drug MONitor – EDMON measures exhaled propofol in ppbv every minute based on multi-capillary column – ion mobility spectrometry (MCC-IMS). The MCC pre-separates gas samples, thereby reducing the influence of the high humidity in human breath. However, preliminary analyses identified substantial measurement deviations between dry and humid calibration standards. We therefore performed an analytical validation of the EDMON to evaluate the influence of humidity on measurement performance. A calibration gas generator was used to generate gaseous propofol standards measured by an EDMON device to assess linearity, precision, carry-over, resolution, and the influence of different levels of humidity at 100% and 1.7% (without additional) relative humidity (reference temperature: 37°C). EDMON measurements were roughly half the actual concentration without additional humidity and roughly halved again at 100% relative humidity. Standard concentrations and EDMON values correlated linearly at 100% relative humidity (R²=0.97). The measured values were stable over 100min with a variance ≤ 10% in over 96% of the measurements. Carry-over effects were low with 5% at 100% relative humidity after 5min of equilibration. EDMON measurement resolution at 100% relative humidity was 0.4 and 0.6 ppbv for standard concentrations of 3 ppbv and 41 ppbv. The influence of humidity on measurement performance was best described by a second-order polynomial function (R²≥0.99) with influence reaching a maximum at about 70% relative humidity. We conclude that EDMON measurements are strongly influenced by humidity and should therefore be corrected for sample humidity to obtain accurate estimates of exhaled propofol concentrations.

BACKGROUND Volatile anesthetics potentially trigger malignant hyperthermia crises in susceptible patients. We therefore aimed to identify preparation procedures for the Draeger Primus that minimize residual concentrations of desflurane and sevoflurane with and without activated charcoal filtration. METHODS A Draeger Primus test workstation was primed with 7% desflurane or 2.5% sevoflurane for 2 hours. Residual anesthetic concentrations were evaluated with five preparation procedures, three fresh gas flow rates, and three distinct applications of activated charcoal filters. Finally, non-exchangeable and autoclaved parts of the workstation were tested for residual emission of volatile anesthetics. Concentrations were measured by multicapillary column-ion mobility spectrometry with limits of detection/quantification being

We define breathomics as the metabolomics study of exhaled air. It is a strongly emerging metabolomics research field that mainly focuses on health-related volatile organic compounds (VOCs). Since the amount of these compounds varies with health status, breathomics holds great promise to deliver non-invasive diagnostic tools. Thus, the main aim of breathomics is to find patterns of VOCs related to abnormal (for instance inflammatory) metabolic processes occurring in the human body. Recently, analytical methods for measuring VOCs in exhaled air with high resolution and high throughput have been extensively developed. Yet, the application of machine learning methods for fingerprinting VOC profiles in the breathomics is still in its infancy. Therefore, in this paper, we describe the current state of the art in data pre-processing and multivariate analysis of breathomics data. We start with the detailed pre-processing pipelines for breathomics data obtained from gas-chromatography mass spectrometry and an ion-mobility spectrometer coupled to multi-capillary columns. The outcome of data pre-processing is a matrix containing the relative abundances of a set of VOCs for a group of patients under different conditions (e.g. disease stage, treatment). Independently of the utilized analytical method, the most important question, 'which VOCs are discriminatory?', remains the same. Answers can be given by several modern machine learning techniques (multivariate statistics) and, therefore, are the focus of this paper. We demonstrate the advantages as well the drawbacks of such techniques. We aim to help the community to understand how to profit from a particular method. In parallel, we hope to make the community aware of the existing data fusion methods, as yet unresearched in breathomics.

Recentemente, a técnica de Espectrometria de Mobilidade Iónica associada a uma coluna multicapilar (MCC-IMS) tem sido aplicada à análise do ar exalado dos seres humanos. O ar que é expelido na respiração contém compostos orgânicos voláteis (VOCs) que possuem informação importante relativa ao estado metabólico do sujeito. Existem inúmeras vantagens na utilização desta tecnologia relativamente às técnicas de rastreio através do sangue, designadamente o facto de ser um processo não doloroso, não invasivo e a recolha de amostras não necessita de ser efectuada por pessoal médico especializado. Esta técnica está a ser desenvolvida com progressos no diagnóstico precoce do cancro do pulmão (entre outros) ou da doença pulmonar obstrutiva crónica (DPOC), e também para controlo da medicação ou na fase terapêutica. Esta técnica é utilizada para detetar analitos em matrizes voláteis através da sua mobilidade iónica e combina alta sensibilidade através de um limite de deteção da ordem dos baixos ppbv [ng/L], com baixos custos de manutenção. O principal objectivo do trabalho desenvolvido nesta dissertação foi a projecção e implementação de uma interface gráfica que permita a detecção automática dos picos presentes nos espectros 3D de MCC-IMS. Para esta finalidade foi implementado um algoritmo que permite obter a informação acerca da posição e intensidade dos máximos de cada pico. A identificação automática de compostos relativos a cada pico detectado foi igualmente implementada através da ligação à base de dados existente, passível de ser aumentada no decorrer das medições experimentais. Além disso, foi desenvolvida uma ferramenta que permite eliminar influências da matriz, seja do ar ambiente, do sistema ou outro, por meio da subtracção dos espectros de background aos espectros experimentais. A interface desenvolvida foi testada para diferentes medições experimentais de aquisição dos espectros de ar exalado com a tecnologia de MCC-IMS e os resultados obtidos foram apresentados como comunicação científica de painel na Conferência iMed 4.0 em 2012 na FCM-UNL e na Conferência Internacional Breath Analysis Summit, na Alemanha em Junho de 2013.