Breath ethane concentrations in healthy volunteers correlate with a systemic marker of lipid peroxidation but not with omega-3 Fatty Acid availability

Review of Lipid Biomarkers and Signals of Photooxidative Stress in Plants

The degree of unsaturation of plant lipids is high, making them sensitive to oxidation. They thus constitute primary targets of reactive oxygen species and oxidative stress. Moreover, the hydroperoxides generated during lipid peroxidation decompose in a variety of secondary products which can propagate oxidative stress or trigger signaling mechanisms. Both primary and secondary products of lipid oxidation are helpful markers of oxidative stress in plants. This chapter describes a number of methods that have been developed to measure those biomarkers and signals, with special emphasis on the monitoring of photooxidative stress. Depending on their characteristics, those lipid markers provide information not only on the oxidation status of plant tissues but also on the origin of lipid peroxidation, the localization of the damage, or the type of reactive oxygen species involved.

Highly Sensitive Oxygen Sensing Characteristics Observed in IGZO Based Gasistor in a Mixed Gas Ambient at Room Temperature

Oxygen (O₂) sensing in trace amounts and mixed gas is essential in many types of industries. Semiconductor sensors have proven to be invaluable tools for the O₂ measurements in a wide concentration range, but the sensors are only able to quantify O₂ in a concentration range of subppm, thus far, especially in mixed gas. We present in this paper a new concept for O₂ sensing with incomparable sensitivity using IGZO-films with oxygen vacancy-based conducting filaments (CFs). O₂ sensing relies on rupturing of the CFs, and the proposed device quickly recovers to the initial state using a pulse of 0.6 V/90 μs after the sensing. The proposed device has a high sensitivity of 14 even at an O₂ concentration of 500 ppb, a detection limit of 150 ppb for O₂ at RT, and excellent selectivity for O₂ in mixed gas, which is remarkable compared to other gas sensors. The proposed device can be widely used in gas sensors especially for detecting O₂ at a low ppb level, which is due to excellent sensing characteristics.

Influence of sociodemographic, lifestyle and genetic characteristics on maternal DHA and other polyunsaturated fatty acid status in pregnancy: A systematic review

INTRODUCTION

Omega-3 DHA is important for the prevention of preterm birth, however there is limited knowledge of the determinants of omega-3 status during pregnancy. The primary objective of this systematic review was to synthesise data from existing studies assessing relationships between sociodemographic, diet, lifestyle and genetic factors and maternal DHA status.

MATERIALS AND METHODS

The Medline, Embase, Amed, and CINAHL databases were searched for studies reporting measures of maternal omega-3 status and a sociodemographic/lifestyle/genetic characteristic.

RESULTS

Twenty-two studies were included in the final analyses. Higher dietary fish consumption/PUFA intake, higher education level and an older maternal age were associated with higher maternal omega-3 status. Higher alcohol intake, smoking and FADS genotype were each associated with lower maternal omega-3 status.

DISCUSSION

Differences in findings between studies make it difficult to draw clear conclusions about the relationship between these factors and maternal omega-3 DHA status, although socioeconomic status may play a role.

MEMS sensor array-based electronic nose for breath analysis-a simulation study

The paper presents a simulation study of breath analysis based on theoretical models of microelectromechanical structure (MEMS) cantilever sensor array. The purpose of this study is to suggest a methodology for the development of MEMS electronic nose (e-nose) for monitoring disease-specific volatiles in exhaled breath. Oxidative stress and diabetes are taken as case studies for the assessment of e-nose designs. The detection of ethane for general oxidative stress, isoprene for hypoxia, and acetone for diabetes are considered for targeted detection. A number of volatiles concurrently present in the exhaled breath are taken as interferents. The MEMS cantilevers are coated with volatile-selective polymers and are analyzed in both the static and dynamic modes. The sensor array is defined by polymer selections based on three data mining methods: principal component analysis (PCA), fuzzy c-means clustering (FCM), and fuzzy subtractive clustering (FSC). This utilizes vapor/polymer partition coefficients as a database. Analyses are carried out to find optimal combinations of the polymer selection method and cantilever sensing mode. Virtual breath analysis experiments are analyzed by PCA for target discrimination. It is found that no single combination works best in all conditions. The acetone (diabetes) detection is best in both sensing modes with the polymers selected by FSC; the isoprene (hypoxia) is detectable only in static sensing mode with polymers selected by FCM clustering; and the ethane (oxidative stress) detection is possible by all sensing modes and polymer selections, provided the breath samples are preconcentrated. This study suggests that it is difficult to realize a single general-purpose MEMS breath analyzer. The dedicated analyzers for specific disease indications can however be made with an optimal combination of sensing mode and polymer coatings.