NCT02050425 (registered at ClinicalTrials.gov).

Noninvasive, real-time pharmacokinetic (PK) monitoring of ketamine, propofol, and valproic acid, and their metabolites was achieved in mice, using secondary electrospray ionization and high-resolution mass spectrometry. The PK profile of a drug influences its efficacy and toxicity because it determines exposure time and levels. The antidepressant and anaesthetic ketamine (Ket) and four Ket metabolites were studied in detail and their PK was simultaneously determined following application of different sub-anaesthetic doses of Ket. Bioavailability after oral administration vs. intraperitoneal injection was also investigated. In contrast to conventional studies that require many animals to be sacrificed even for low-resolution PK curves, this novel approach yields real-time PK curves with a hitherto unmatched time resolution (10 s), and none of the animals has to be sacrificed. This thus represents a major step forward not only in animal welfare, but also major cost and time savings.

BACKGROUND:Amino acids are frequently determined in clinical chemistry. However, current analysis methods are time-consuming, invasive, and suffer from artifacts during sampling, sample handling, and sample preparation. We hypothesized in this proof-of-principle study that plasma concentrations of amino acids can be estimated by measuring their concentrations in exhaled breath. A novel breath analysis technique described here allows such measurements to be carried out in real-time and noninvasively, which should facilitate efficient diagnostics and give insights into human physiology.

No abstract

The detection of bacterial-specific volatile metabolites may be a valuable tool to predict infection. Here we applied a real-time mass spectrometric technique to investigate differences in volatile metabolic profiles of oral bacteria that cause periodontitis. We coupled a secondary electrospray ionization (SESI) source to a commercial high-resolution mass spectrometer to interrogate the headspace from bacterial cultures and human saliva. We identified 120 potential markers characteristic for periodontal pathogens Aggregatibacter actinomycetemcomitans (n = 13), Porphyromonas gingivalis (n = 70), Tanerella forsythia (n = 30) and Treponema denticola (n = 7) in in vitro cultures. In a second proof-of-principle phase, we found 18 (P. gingivalis, T. forsythia and T. denticola) of the 120 in vitro compounds in the saliva from a periodontitis patient with confirmed infection with P. gingivalis, T. forsythia and T. denticola with enhanced ion intensity compared to two healthy controls. In conclusion, this method has the ability to identify individual metabolites of microbial pathogens in a complex medium such as saliva.