The Biochemical Profile of Post-Mortem Brain from People Who Suffered from Epilepsy Reveals Novel Insights into the Etiopathogenesis of the Disease.

Epilepsy not-otherwise-specified (ENOS) is one of the most common causes of chronic disorders impacting human health, with complex multifactorial etiology and clinical presentation. Understanding the metabolic processes associated with the disorder may aid in the discovery of preventive and therapeutic measures. Post-mortem brain samples were harvested from the frontal cortex (BA8/46) of people diagnosed with ENOS cases (n = 15) and age- and sex-matched control subjects (n = 15). We employed a targeted metabolomics approach using a combination of proton nuclear magnetic resonance (1H-NMR) and direct injection/liquid chromatography tandem mass spectrometry (DI/LC-MS/MS). We accurately identified and quantified 72 metabolites using 1H-NMR and 159 using DI/LC-MS/MS. Among the 212 detected metabolites, 14 showed significant concentration changes between ENOS cases and controls (p < 0.05; q < 0.05). Of these, adenosine monophosphate and O-acetylcholine were the most commonly selected metabolites used to develop predictive models capable of discriminating between ENOS and unaffected controls. Metabolomic set enrichment analysis identified ethanol degradation, butyrate metabolism and the mitochondrial beta-oxidation of fatty acids as the top three significantly perturbed metabolic pathways. We report, for the first time, the metabolomic profiling of postmortem brain tissue form patients who died from epilepsy. These findings can potentially expand upon the complex etiopathogenesis and help identify key predictive biomarkers of ENOS.

Wide-ranging alterations in the brain fatty acid complement of subjects with late Alzheimer's disease as detected by GC-MS.

Disturbed lipid metabolism is a well-established feature of human Alzheimer's disease (AD). The present study used gas chromatography-mass spectrometry (GC-MS) analysis of fatty acid methyl esters (FAMES) to profile all detectable fatty acid (FA) species present in post-mortem neocortical tissue (Brodmann 7 region). Quantitative targeted analysis was undertaken from 29 subjects (n=15 age-matched controls; n=14 late-stage AD). GC-MS analysis of FAMES detected a total of 24 FAs and of these, 20 were fully quantifiable. The results showed significant and wide ranging elevations in AD brain FA concentrations. A total of 9 FAs were elevated in AD with cis-13,16-docosenoic acid increased most (170%; P=0.033). Intriguingly, docosahexanoic acid (DHA; C22:6) concentrations were elevated (47%; P=0.018) which conflicts with the findings of others (unaltered or decreased) in some brain regions after the onset of AD. Furthermore, our results appear to indicate that subject gender influences brain FA levels in AD subjects (but not in age-matched control subjects). Among AD subjects 7 FA species were significantly higher in males than in females. These preliminary findings pinpoint FA disturbances as potentially important in the pathology of AD. Further work is required to determine if such changes are influenced by disease severity or different types of dementia.

The application of near-infrared (NIR) and Raman spectroscopy to detect adulteration of oil used in animal feed production.

Basic vegetable blends (BVB's) and soya oils, used in the animal feed industry, are sometimes adulterated with transformer and mineral oil as a means of illegally increasing profit. A set of BVB's and soya oil samples adulterated with transformer oil and mineral oil were characterised using both NIRS and Raman spectroscopy. Applying chemometrics to the NIRS and Raman spectral data, very good calibration and prediction statistics were obtained for transformer and mineral oils. Using NIRS, R2 values greater than 0.99 were obtained with corresponding values for root mean squared error of calibration and prediction (<0.57 and <0.55, respectively). Using Raman, R2 values greater than 0.97 were obtained with the root mean squared error of calibration (<2.01) and prediction (<1.92) calculated. Furthermore, using a qualitative approach it was possible, using PCA, to discriminate between 100% soya and BVB. This study demonstrates that both NIRS and Raman technology can be successfully applied as rapid screening techniques for the detection of oil adulteration and fraud in the food and feed industry.

Comparing GC-MS, HPLC and ¹H NMR analysis of beef longissimus dorsi tissue extracts to determine the effect of suspension technique and ageing.

Beef longissimus dorsi muscle samples matured over a 21 day period were analysed using three different analytical techniques; (1)H NMR, GC-MS and HPLC. The data from the three experimental techniques were correlated with each other to determine if the results were statistically similar to each other. From our analysis we determined that the metabolites measured using (1)H NMR were statistically similar to the compounds quantified using the chromatography techniques (p<0.001). In addition, using PCA, we were able to show that different metabolites, measured using the various analytical techniques produced very similar scores and loadings plots for all the analysis and extraction techniques undertaken across the 21 day time domain. Using a combination of these three different techniques provides a unique and holistic insight into the biochemistry behind the conversion of muscle to meat which would not be possible using any single technique alone.