50 research outputs found
trial
No full textAIMS: We examined the contribution of changes in diet quality, physical activity and weight loss to improvements in insulin resistance (HOMA-IR index) and fasting glucose concentrations in a long-term behavioural trial. Furthermore, we compared the effects of lifestyle changes on glycaemic markers for individuals with and without prediabetes. MATERIALS AND METHODS: The PREMIER trial was an 18-month parallel randomized trial of the impact of behavioural lifestyle interventions implementing lifestyle recommendations (dietary changes, physical activity, moderate weight loss) in adults with prehypertension or stage 1 hypertension. We analysed data on 685 men and women without diabetes. Data on body weight, fitness (treadmill test), dietary intake (24-h recalls) and glycaemic outcomes were collected at baseline and at 6 and 18 months. We used general linear models to assess the association between the exposure variables and glycaemic markers. RESULTS: The mean (SD) age was 49.9 (8.8) years, the mean (SD) body mass index was 32.9 (5.7) kg/m , and 35% had prediabetes at baseline. Weight loss and improvements in fitness and diet quality were each significantly associated with lower HOMA-IR and fasting glucose concentrations at 6 and 18 months. Mediation analysis indicated that the effects of fitness and diet quality were partly mediated by weight loss, but significant direct effects of diet and fitness (independent of weight changes) were also observed. Furthermore, insulin sensitivity and fasting glucose improved significantly in participants with and without prediabetes. CONCLUSIONS: Our findings indicate that behavioural lifestyle interventions can substantially improve glucose metabolism in persons with and without prediabetes and that the effects of diet quality and physical activity are partly independent of weight loss
1309 The Etiological Value of Lactate Dehydrogenase in Respiratory Tract Viral Infections
No full text
Self-stabilizing minimum-degree spanning tree within one from the optimal degree
No full textInternational audienceWe propose a self-stabilizing algorithm for constructing a Minimum-Degree Spanning Tree (MDST) in undirected networks. Starting from an arbitrary state, our algorithm is guaranteed to converge to a legitimate state describing a spanning tree whose maximum node degree is at most ∆∗ + 1, where ∆∗ is the minimum possible maximum degree of a spanning tree of the network. To the best of our knowledge our algorithm is the first self stabilizing solution for the construction of a minimum-degree spanning tree in undirected graphs. The algorithm uses only local communications (nodes interact only with the neighbors at one hop distance). Moreover, the algorithm is designed to work in any asynchronous message passing network with reliable FIFO channels. Additionally, we use a fine grained atomicity model (i.e. the send/receive atomicity). The time complexity of our solution is O(mn2 log n) where m is the number of edges and n is the number of nodes. The memory complexity is O(δ log n) in the send-receive atomicity model (δ is the maximal degree of the network)
Self-stabilizing minimum degree spanning tree within one from the optimal degree
No full textInternational audienceWe propose a self-stabilizing algorithm for constructing a Minimum-Degree Spanning Tree (MDST) in undirected networks. Starting from an arbitrary state, our algorithm is guaranteed to converge to a legitimate state describing a spanning tree whose maximum node degree is at most ∆∗ + 1, where ∆∗ is the minimum possible maximum degree of a spanning tree of the network. To the best of our knowledge our algorithm is the first self stabilizing solution for the construction of a minimum-degree spanning tree in undirected graphs. The algorithm uses only local communications (nodes interact only with the neighbors at one hop distance). Moreover, the algorithm is designed to work in any asynchronous message passing network with reliable FIFO channels. Additionally, we use a fine grained atomicity model (i.e. the send/receive atomicity). The time complexity of our solution is O(mn2 log n) where m is the number of edges and n is the number of nodes. The memory complexity is O(δ log n) in the send-receive atomicity model (δ is the maximal degree of the network)
Study of the Optimum Dose of Ferromagnetic Nanoparticles Suitable for Cancer Therapy Using MFH
No full text
