Identifying and differentiating bacteria based on their emitted volatile organic compounds (VOCs) opens vast opportunities for rapid diagnostics. Secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS) is an ideal technique for VOC-biomarker discovery because of its speed, sensitivity towards polar molecules and compound characterization possibilities. Here, an in vitro SESI-HRMS workflow to find biomarkers for cystic fibrosis (CF)-related pathogens P. aeruginosa, S. pneumoniae, S. aureus, H. influenzae, E. coli and S. maltophilia is described. From 180 headspace samples, the six pathogens are distinguishable in the first three principal components and predictive analysis with a support vector machine algorithm using leave-one-out cross-validation exhibited perfect accuracy scores for the differentiation between the groups. Additionally, 94 distinctive features were found by recursive feature elimination and further characterized by SESI-MS/MS, which yielded 33 putatively identified biomarkers. In conclusion, the six pathogens can be distinguished in vitro based on their VOC profiles as well as the herein reported putative biomarkers. In the future, these putative biomarkers might be helpful for pathogen detection in vivo based on breath samples from patients with CF.

Pd films deposited at room temperature have been found to grow epitaxially on GaN grown by metalorganic vapor phase epitaxy (MOVPE). The Pd films were deposited on GaN substrates cleaned by chemicals only, and in a conventional e‐beam evaporation system with a vacuum of ∼1×10⁻⁷ Torr. MeV ⁴He backscattering spectrometry and the Read x‐ray camera were used to evaluate the Pd films. The effects of various chemical etchants—such as aqua regia, HCl:H₂O, and HF:H₂O—on the epitaxial quality of the Pd films have also been investigated. Ni and Pt films deposited on GaN in a similar manner were also found to be epitaxial.

Environmental volatile organic compounds (VOCs) from the ambient air potentially influence on-line breath analysis measurements by secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS). The aim of this study was to investigate how inhaling through a VOC filter affects the detected breath profiles and whether it is feasible to integrate such filters into routine measurements. A total of 24 adult participants performed paired breath analysis measurements with and without the use of an activated carbon filter for inspiration. Concordance correlation coefficients (CCCs) and the Bland–Altman analysis were used to assess the agreement between the two methods. Additionally, the effect on a selection of known metabolites and contaminants was analyzed. Out of all the detected features, 78.3% showed at least a moderate agreement before and after filter usage (CCC > 0.9). The decrease in agreement of the remaining m/z features was mostly associated with reduced signal intensities after filter usage. Although a moderate-to-substantial concordance was found for almost 80% of the m/z features, the filter still had an effect by decreasing signal intensities, not only for contaminants, but also for some of the studied metabolites. Operationally, the use of the filter complicated and slowed down the conductance of measurements, limiting its applicability in clinical studies.

The early detection of inflammation and infection is important to prevent irreversible lung damage in cystic fibrosis. Novel and non-invasive monitoring tools would be of high benefit for the quality of life of patients. Our group previously detected over 100 exhaled mass-to-charge (m/z) features, using on-line secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS), which distinguish children with cystic fibrosis from healthy controls. The aim of this study was to annotate as many m/z features as possible with putative chemical structures. Compound identification was performed by applying a rigorous workflow, which included the analysis of on-line MS² spectra and a literature comparison. A total of 49 discriminatory exhaled compounds were putatively identified. A group of compounds including glycolic acid, glyceric acid and xanthine were elevated in the cystic fibrosis group. A large group of acylcarnitines and aldehydes were found to be decreased in cystic fibrosis. The proposed compound identification workflow was used to identify signatures of volatile organic compounds that discriminate children with cystic fibrosis from healthy controls, which is the first step for future non-invasive and personalized applications.

Excessive or prolonged periparturient negative energy balance (NEB) is an important issue for dairy producers, and may be associated with increased risk of clinical disease and impaired production and reproductive performance. Affected cows commonly have elevated circulating levels of non-esterified fatty acids (NEFA) prior to calving and increased beta-hydroxybutyrate (BHB) postpartum. Monitoring the incidence of subclinical ketosis postpartum has been the recommended method of surveillance for this problem. Prepartum, blood NEFA concentration may be used to detect cows at risk for problems with severe NEB. Serum NEFA greater than 0.4 mEq/L NEFA has been proposed to identify excessive prepartum NEB. Measuring NEFA has traditionally involved submission of serum to a diagnostic laboratory. The DVM NEFA test (Veterinary Diagnostics. Newburg, Wisconsin, USA) is a new, rapid, spectophotometry method to determine NEFA concentration in serum through light absorbance. The objective of this study was to determine the test characteristics of the DVM NEFA test and its usefulness as a method of identifying problems with NEB in prepartum dairy cows.