Jean-Pierre Stockis

Anthocyanin/Polyphenolic–Rich Fruit Juice Reduces Oxidative Cell Damage in an Intervention Study with Patients on Hemodialysis

Hemodialysis patients face an elevated risk of cancer, arteriosclerosis, and other diseases, ascribed in part to increased oxidative stress. Red fruit juice with high anthocyanin/polyphenol content had been shown to reduce oxidative damage in healthy probands. To test its preventive potential in hemodialysis patients, 21 subjects in a pilot intervention study consumed 200 mL/day of red fruit juice (3-week run-in; 4-week juice uptake; 3-week wash-out). Weekly blood sampling was done to monitor DNA damage (comet assay ± formamidopyrimidine-DNA glycosylase enzyme), glutathione, malondialdehyde, protein carbonyls, trolox equivalent antioxidant capacity, triglycerides, and DNA binding capacity of the transcription factor nuclear factor-κB. Results show a significant decrease of DNA oxidation damage (P < 0.0001), protein and lipid peroxidation (P < 0.0001 and P < 0.001, respectively), and nuclear factor-κB binding activity (P < 0.01), and an increase of glutathione level and status (both P < 0.0001) during juice uptake. We attribute this reduction in oxidative (cell) damage in hemodialysis patients to the especially high anthocyanin/polyphenol content of the juice. This provides promising perspectives into the prevention of chronic diseases such as cancer and cardiovascular disease in population subgroups exposed to enhanced oxidative stress like hemodialysis patients. (Cancer Epidemiol Biomarkers Prev 2008;17(12):3372–80)

Antioxidant‐rich coffee reduces DNA damage, elevates glutathione status and contributes to weight control: Results from an intervention study

Epidemiological and experimental evidence increasingly suggests coffee consumption to be correlated to prevention or delay of degenerative diseases connected with oxidative cellular stress. In an intervention study comprising 33 healthy volunteers, we examined DNA-protective and antioxidative effects exerted in vivo by daily ingestion of 750 mL of freshly brewed coffee rich in both green coffee bean constituents as well as roast products. The study design encompassed an initial 4 wk of wash-out, followed by 4 wk of coffee intake and 4 wk of second wash-out. At the start and after each study phase blood samples were taken to monitor biomarkers of oxidative stress response. In addition, body weight/composition and intake of energy/nutrients were recorded. In the coffee ingestion period, the primary endpoint, oxidative DNA damage as measured by the Comet assay (± FPG), was markedly reduced (p<0.001). Glutathione level (p<0.05) and GSR-activity (p<0.01) were elevated. Body weight (p<0.01)/body fat (p<0.05) and energy (p<0.001)/nutrient (p<0.001-0.05) intake were reduced. Our results allow to conclude that daily consumption of 3-4 cups of brew from a special Arabica coffee exerts health beneficial effects, as evidenced by reduced oxidative damage, body fat mass and energy/nutrient uptake.

Effects of Hemodialysis, Dialyser Type and Iron Infusion on Oxidative Stress in Uremic Patients

Uremic patients undergoing hemodialysis (HD) are considered to face an elevated risk for atherosclerosis and cancer. This has been attributed in part to an increased oxidative stress. In this pilot study, oxidative cell damage in blood of HD-patients was compared to those of controls: total DNA damage (basic and specific oxidative DNA damage), modulation of glutathione levels (total and oxidized glutathione) and of lipid peroxidation were monitored via the Comet assay (with and without FPG), a kinetic photometric assay and HPLC quantification of plasma malondialdehyde (MDA), respectively. In some samples, leukocytes were analysed for malondialdehyde–deoxyguanosine-adducts (M1dG) with an immunoslot blot technique. HD-patients (n=21) showed a significant increase of total DNA damage (p<10-12), compared to controls (n=12). In a subset of patients and controls, GSSG levels and M1dG, however, only increased slightly, while tGSH and MDA levels did not differ. The influence of different low flux HD-membranes was tested in a pilot study with nine patients consecutively dialysed on three membrane types for four weeks each. In addition to the individual disposition of the patient, the dialyser membrane had a significant impact on oxidative stress. Total DNA damage was found to be almost identical for polysulfone and vitamin E coated cellulosic membranes, whereas a slight, but significant increase was observed with cellulose-diacetate (p<0.001). In patients receiving iron infusion during HD, MDA-formation (n=11) and total DNA damage (n=10) were additionally increased (p<0.005). Our results show an increased oxidative damage in HD-patients, compared to healthy volunteers. Significant influences were found for the dialyser membrane type and iron infusion.

Bootstrapping nonparametric estimators of the volatility function

We prove that the bootstrap works in a quite general sense for nonparametric estimators of the trend and volatility functions in nonlinear AR-ARCH-models. We illustrate the implications of this result by constructing uniform confidence bands for those functions based on localized nonparametric function estimates. As an application, we study the trend and volatility of a time series of high frequency foreign exchange rate returns.

On Geometric Ergodicity of CHARME Models

In this article we consider a CHARME model, a class of generalized mixture of nonlinear nonparametric AR-ARCH time series. To provide sets of conditions under which such processes are geometrically ergodic and, therefore, satisfy some mixing conditions, we apply the theory of Markov chains to derive asymptotic stability of this model. These results form the basis for deriving an asymptotic theory for nonparametric estimation. As an illustration, neural network sieve estimates for the autoregressive and volatility functions are considered, and consistency of the parameter estimates is obtained.

Mixtures of nonparametric autoregressions

We consider data generating mechanisms which can be represented as mixtures of finitely many regression or autoregression models. We propose nonparametric estimators for the functions characterising the various mixture components based on a local quasi maximum likelihood approach and prove their consistency. We present an EM algorithm for calculating the estimates numerically which is mainly based on iteratively applying common local smoothers and discuss its convergence properties.

Quantile Sieve Estimates For Time Series

We consider the problem of estimating the conditional quantile of a time series at time t given observations of the same and perhaps other time series available at time t - 1. We discuss sieve estimates which are a nonparametric versions of the Koenker-Bassett regression quantiles and do not require the specification of the innovation law. We prove consistency of those estimates and illustrate their good performance for light- and heavy-tailed distributions of the innovations with a small simulation study. As an economic application, we use the estimates for calculating the value at risk of some stock price series.