Changes in volatile compounds of human urine as it ages: their interaction with water.

The urinary odors are commonly perceived as unpleasant. While numerous studies have identified the volatile organic compounds (VOCs) released from urine, the odorants responsible for the urine odor are not well characterized. Furthermore, anecdotal reports suggest that the odor of aged urine is different from that of fresh urine.

Changes in volatile compounds of mouse urine as it ages: their interactions with water and urinary proteins.

Mice release a variety of chemical signals, particularly through urine, which mediate social interactions and endocrine function. Studies have been conducted to investigate the stability of urinary chemosignals in mice. Neuroendocrine and behavioral responses of mice to urine samples of male and female conspecifics which have aged for different amounts of time have been examined, demonstrating that the quality and intensity of signaling molecules in urine change over time.

Differential binding between volatile ligands and major urinary proteins due to genetic variation in mice.

Two different structural classes of chemical signals in mouse urine, i.e., volatile organic compounds (VOCs) and the major urinary proteins (MUPs), interact closely because MUPs sequester VOCs.

Metabolite differentiation and discovery lab (MeDDL): a new tool for biomarker discovery and mass spectral visualization.

The goal of this work was to design and implement a prototype software tool for the visualization and analysis of small molecule metabolite GC-MS and LC-MS data for biomarker discovery. The key features of the Metabolite Differentiation and Discovery Lab (MeDDL) software platform include support for the manipulation of large data sets, tools to provide a multifaceted view of the individual experimental results, and a software architecture amenable to modification and addition of new algorithms and software components. The MeDDL tool, through its emphasis on visualization, provides unique opportunities by combining the following: easy use of both GC-MS and LC-MS data; use of both manufacturer specific data files as well as netCDF (network Common Data Form); preprocessing (peak registration and alignment in both time and mass); powerful visualization tools; and built in data analysis functionality.