Diet Carotenoid Lutein Modulates The Expression Of Genes Related To Oxygen Transporters And Decreases Dna Damage And Oxidative Stress In Mice.

Lutein (LT) is a carotenoid obtained by diet and despite its antioxidant activity had been biochemically reported, few studies are available concerning its influence on the expression of antioxidant genes. The expression of 84 genes implicated in antioxidant defense was quantified using quantitative reverse transcription polymerase chain reaction array. DNA damage was measured by comet assay and glutathione (GSH) and thiobarbituric acid reactive substances (TBARS) were quantified as biochemical parameters of oxidative stress in mouse kidney and liver. cDDP treatment reduced concentration of GSH and increased TBARS, parameters that were ameliorated in treatment associated with LT. cDDP altered the expression of 32 genes, increasing the expression of GPx2, APC, Nqo1 and CCs. LT changed the expression of 37 genes with an induction of 13 mainly oxygen transporters. In treatments associating cDDP and LT, 30 genes had their expression changed with a increase of the same genes of the cDDP treatment alone. These results suggest that LT might act scavenging reactive species and also inducing the expression of genes related to a better antioxidant response, highlighting the improvement of oxygen transport. This improved redox state of the cell through LT treatment could be related to the antigenotoxic and antioxidant effects observed.

Ihwg-μnir: A Miniaturised Near-infrared Gas Sensor Based On Substrate-integrated Hollow Waveguides Coupled To A Micro-nir-spectrophotometer.

A miniaturised gas analyser is described and evaluated based on the use of a substrate-integrated hollow waveguide (iHWG) coupled to a microsized near-infrared spectrophotometer comprising a linear variable filter and an array of InGaAs detectors. This gas sensing system was applied to analyse surrogate samples of natural fuel gas containing methane, ethane, propane and butane, quantified by using multivariate regression models based on partial least square (PLS) algorithms and Savitzky-Golay 1(st) derivative data preprocessing. The external validation of the obtained models reveals root mean square errors of prediction of 0.37, 0.36, 0.67 and 0.37% (v/v), for methane, ethane, propane and butane, respectively. The developed sensing system provides particularly rapid response times upon composition changes of the gaseous sample (approximately 2 s) due the minute volume of the iHWG-based measurement cell. The sensing system developed in this study is fully portable with a hand-held sized analyser footprint, and thus ideally suited for field analysis. Last but not least, the obtained results corroborate the potential of NIR-iHWG analysers for monitoring the quality of natural gas and petrochemical gaseous products.