In patients with suspected fungal pneumonia, an Aspergillus secondary metabolite signature in breath can identify individuals with IA. These results provide proof-of-concept that direct detection of exogenous fungal metabolites in breath can be used as a novel, noninvasive, pathogen-specific approach to identifying the precise microbial cause of pneumonia.

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Gas chromatography/differential mobility spectrometry (GC/DMS) has been investigated for characterization of fuels. Neat fuel samples were sampled using solid-phase microextraction (SPME) and analyzed using a micromachined differential mobility spectrometer with a photoionization source interfaced to a gas chromatograph. The coupling of DMS to GC offers an additional order of information in that two-way data are obtained with respect to compensation voltages and retention time. A fuzzy rule-building expert system (FuRES) was used as a multivariate classifier for the two-way gas chromatograms of fuels, including rocket (RP-1, RG-1), diesel, and jet (JP-4, JP-5, JP-7, JP-TS, JetA-3639, Jet A-3688, Jet A-3690, Jet A-3694, and Jet A-generic) fuels. The GC-DMS with SPME was able to produce characteristic profiles of the fuels and a classification rate of 95 +/- 0.3% obtained with a FuRES model. The classification system also had perfect classification for each fuel sample when applied one month later.