The effects of Chronic Lycopene Supplementation on Exercise-Induced Oxidative Stress and Glucose Homeostasis.

Lycopene can exert antioxidant effects against peripheral and cellular oxidative stress and may be associated with reduced diabetic risk. Conversely, exercise-induced free radicals are thought to underpin many of the desirable whole-body adaptations following training and the use of antioxidants within the exercise model remains debatable. PURPOSE: To investigate the effect of lycopene supplementation on oxidative stress and glucose homeostasis following acute aerobic exercise. METHOD: Twenty-eight (n=28) apparently healthy male volunteers were recruited (age 24 ± 4 years; weight 78 ± 10 kg; height 178 ± 8 cm; 2max 40 ± 7 ml·kg-1 ·min-1 ) in a randomised, single blind, placebo-controlled study. Participants were required to attend the Laboratory on two occasions: prior to and following 6 weeks of supplementation of either 10mg lycopene (LG; n=15) or placebo (PG; n=13) followed by a bout of acute exercise for one hour at 65% 2max. Exogenous glucose oxidation was then measured on an isotope ratio mass spectrometer in a sub-group of participants (n=14) following exercise, by administration of a standard oral glucose tolerance test (OGTT; 75g glucose). Venous blood samples were drawn for measurement of oxidative stress parameters, plasma glucose and insulin. RESULTS: Plasma lycopene increased in LG only (0.01 ± 0.004 vs.0.02 ± 0.007 µmol/L; P <0.05) following supplementation and remained elevated post exercise compared to PG (0.01 ± 0.004 vs. 0.02 ± 0.009 µmol/L; P <0.05). There were no changes in other markers of oxidative stress (SOD, LOOHs, F2 ISP and Alkoxyl radical) either between or within the trials, (P >0.05, respectively). A main effect for an increase in insulin was observed two hours post OGTT in the sub-groups (Pooled data, P <0.05) but trends in the HOMA scores were evident with a 57% increase for LG (2.20 ± 1.84 vs. 5.14 ± 2.5; P >0.05) and an 11% decrease for PG (2.17 ± 1.06 vs. 1.94 ± 1.53; P >0.05). No change in plasma glucose was detected at any point, or after the OGTT (P >0.05). CONCLUSION: In healthy males, lycopene supplementation had no effect on post exercise levels of ROS or markers of lipid peroxidation, despite an increase in plasma lycopene. However, lycopene supplementation may affect post exercise insulin sensitivity in response to glucose consumption, but further parallel research is required.

The inclusion of open-ended questions on quantitative surveys of children: Dealing with unanticipated responses relating to child abuse and neglect

Web surveys have been shown to be a viable, and relatively inexpensive, method of data collection with children. For this reason, the Kids’ Life and Times (KLT) was developed as an annual online survey of 10 and 11 year old children. Each year, approximately 4,000 children participate in the survey. Throughout the six years that KLT has been running, a range of questions has been asked that are both policy-relevant and important to the lives of children. Given the method employed by the survey, no extremely sensitive questions that might cause the children distress are included. The majority of questions on KLT are closed yielding quantitative data that are analysed statistically; however, one regular open-ended question is included at the end of KLT each year so that the children can suggest questions that they think should be asked on the survey the following year. While most of the responses are innocuous, each year a small minority of children suggest questions on child abuse and neglect. This paper reports the responses to this question and reflects on how researchers can, and should, deal with this issue from both a methodological and an ethical perspective.

An ultra-short-term wind power prediction method using “offline classification and optimization, online model matching” based on time series features

The applicability of ultra-short-term wind power prediction (USTWPP) models is reviewed. The USTWPP method proposed extracts featrues from historical data of wind power time series (WPTS), and classifies every short WPTS into one of several different subsets well defined by stationary patterns. All the WPTS that cannot match any one of the stationary patterns are sorted into the subset of nonstationary pattern. Every above WPTS subset needs a USTWPP model specially optimized for it offline. For on-line application, the pattern of the last short WPTS is recognized, then the corresponding prediction model is called for USTWPP. The validity of the proposed method is verified by simulations.