Alterations in ether lipid metabolism and the consequences for the mouse lipidome.

Alkylglycerol monooxygenase (AGMO) and plasmanylethanolamine desaturase (PEDS1) are enzymes involved in ether lipid metabolism. While AGMO degrades plasmanyl lipids by oxidative cleavage of the ether bond, PEDS1 exclusively synthesizes a specific subclass of ether lipids, the plasmalogens, by introducing a vinyl ether double bond into plasmanylethanolamine phospholipids. Ether lipids are characterized by an ether linkage at the sn-1 position of the glycerol backbone and they are found in membranes of different cell types. Decreased plasmalogen levels have been associated with neurological diseases like Alzheimer's disease. Agmo-deficient mice do not present an obvious phenotype under unchallenged conditions. In contrast, Peds1 knockout mice display a growth phenotype. To investigate the molecular consequences of Agmo and Peds1 deficiency on the mouse lipidome, five tissues from each mouse model were isolated and subjected to high resolution mass spectrometry allowing the characterization of up to 2013 lipid species from 42 lipid subclasses. Agmo knockout mice moderately accumulated plasmanyl and plasmenyl lipid species. Peds1-deficient mice manifested striking changes characterized by a strong reduction of plasmenyl lipids and a concomitant massive accumulation of plasmanyl lipids resulting in increased total ether lipid levels in the analyzed tissues except for the class of phosphatidylethanolamines where total levels remained remarkably constant also in Peds1 knockout mice. The rate-limiting enzyme in ether lipid metabolism, FAR1, was not upregulated in Peds1-deficient mice, indicating that the selective loss of plasmalogens is not sufficient to activate the feedback mechanism observed in total ether lipid deficiency.

The automatic recognition and counting of cough.

BACKGROUND: Cough recordings have been undertaken for many years but the analysis of cough frequency and the temporal relation to trigger factors have proven problematic. Because cough is episodic, data collection over many hours is required, along with real-time aural analysis which is equally time-consuming. A method has been developed for the automatic recognition and counting of coughs in sound recordings. METHODS: The Hull Automatic Cough Counter (HACC) is a program developed for the analysis of digital audio recordings. HACC uses digital signal processing (DSP) to calculate characteristic spectral coefficients of sound events, which are then classified into cough and non-cough events by the use of a probabilistic neural network (PNN). Parameters such as the total number of coughs and cough frequency as a function of time can be calculated from the results of the audio processing. Thirty three smoking subjects, 20 male and 13 female aged between 20 and 54 with a chronic troublesome cough were studied in the hour after rising using audio recordings. RESULTS: Using the graphical user interface (GUI), counting the number of coughs identified by HACC in an hour long recording, took an average of 1 minute 35 seconds, a 97.5% reduction in counting time. HACC achieved a sensitivity of 80% and a specificity of 96%. Reproducibility of repeated HACC analysis is 100%. CONCLUSION: An automated system for the analysis of sound files containing coughs and other non-cough events has been developed, with a high robustness and good degree of accuracy towards the number of actual coughs in the audio recording.