Moderate consumption of red wine is associated with a decreased incidence of cardiovascular diseases in populations with relatively high amount of fat in the diet. However, the mechanisms involved in this protective effect are not completely understood. Here we show that moderate consumption of red wine (equivalent to 2 glasses/day in humans) but not ethanol only, improves blood flow recovery by 32% after hindlimb ischemia in hypercholesterolemic ApoE-deficient mice. In ischemic tissues, red wine consumption reduces oxidative stress and increases capillary density by 46%. Endothelial progenitor cells (EPCs) have been shown to have an important role in postnatal neovascularization. We found that the number of EPCs is increased by 60% in ApoE mice exposed to red wine. Moreover, the migratory capacity of EPCs is significantly improved in red wine-drinking mice. The wine used in our study is a cabernet sauvignon from Languedoc-Roussillon, France, which contains a relatively high concentration (4-6 mg/L) of the polyphenolic antioxidant resveratrol. We demonstrate that resveratrol can rescue oxidized low-density lipoprotein (oxLDL)-induced impairment of in vitro angiogenic activities in human umbilical vein endothelial cells (HUVECs). Resveratrol exposure is also associated with increased activation of Akt/eNOS together with a restoration of nitric oxide production in HUVECs exposed to oxLDL. Our study suggests that moderate consumption of red wine improves ischemia-induced neovascularization in high-cholesterol conditions by increasing the number and the functional activities of EPCs and by restoring the Akt-eNOS-NO pathway.

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We propose a self-stabilizing algorithm for computing a maximal matching in an anonymous network. The complexity is O(n 3 ) moves with high probability, under the adversarial distributed daemon. In this algorithm, each node can determine whether one of its neighbors points to it or to another node, leading to a contradiction with the anonymous assumption. To solve this problem, we provide under the classical link-register model, a self-stabilizing algorithm that gives a unique name to a link such that this name is shared by both extremities of the link.

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