Effect of age on atherogenicity of LDL and inflammatory markers in healthy women.

BACKGROUND AND AIM: Since using LDL level alone is insufficient as a method to identify individuals with incident coronary artery disease (CAD), other factors may be implicated in the pathogenesis of CAD. Additionally, controversy still remains regarding whether there is an age-related increase in circulating cytokines in healthy individuals. We investigated the influence of age on atherogenicity of LDL and inflammatory markers in healthy women. METHODS AND RESULTS: Two thousand nine hundred forty four healthy women form 30-79 years old (23.3 ± 0.05 kg/m²) were categorized into 5 age groups: 30-39, 40-49, 50-59, 60-69 and 70-79 years. BMI, smoking, drinking, and metabolic syndrome prevalence adjusted mean values of total-cholesterol progressively increased from the group age 30-39 years to the group age 40-49 and 50-59 years and thereafter decreased in the group age 60-69 and 70-79 years. Serum concentrations of C-reactive protein (CRP), tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) were higher in women aged 60-79 years than women aged 30-59 years. Plasma ox-LDL levels increased in the group age 50-59 years compared with the group age 30-39 and 40-49 years and further increased in the group age 60-69 and 70-79 years. Mean values of LDL particle size were smaller in women aged 60-79 years than those in women aged 30-59 years. After adjustment for BMI, smoking, drinking, and metabolic syndrome status, age was positively correlated with LDL-cholesterol (r = 0.095, P < 0.001), oxidized LDL (r = 0.305, P < 0.001), hs-CRP (r = 0.150, P < 0.001), TNF-α (r = 0.171, P < 0.001) and IL-6 (r = 0.294, P < 0.001) and negatively with LDL particle size (r = -0.239, P < 0.001). CONCLUSION: Our results indicate that LDL atherogenicity and inflammatory mediators can be better markers of CAD risk than known risk factors such as elevated concentrations of total- and LDL-cholesterol, decreased HDL-cholesterol levels and smoking in old healthy women.

Image restoration using a modified Hopfield network.

A modified Hopfield neural network model for regularized image restoration is presented. The proposed network allows negative autoconnections for each neuron. A set of algorithms using the proposed neural network model is presented, with various updating modes: sequential updates; n-simultaneous updates; and partially asynchronous updates. The sequential algorithm is shown to converge to a local minimum of the energy function after a finite number of iterations. Since an algorithm which updates all n neurons simultaneously is not guaranteed to converge, a modified algorithm is presented, which is called a greedy algorithm. Although the greedy algorithm is not guaranteed to converge to a local minimum, the l (1) norm of the residual at a fixed point is bounded. A partially asynchronous algorithm is presented, which allows a neuron to have a bounded time delay to communicate with other neurons. Such an algorithm can eliminate the synchronization overhead of synchronous algorithms.