Objective— Adiponectin is adipose-specific secretory protein and acts as anti-diabetic and anti-atherosclerotic molecule. We previously found peroxisome proliferators response element in adiponectin promoter region, suggesting that peroxisome proliferator-activated receptor (PPAR) ligands elevate adiponectin. Fibrates are known to be PPARα ligands and were shown to reduce risks of diabetes and cardiovascular disease. Effect of fibrates on adiponectin has not been clarified, whereas thiazolidinediones enhance adiponectin. Thus, we explored the possibility and mechanism that fibrates enhance adiponectin in humans, mice, and cells. Methods and Results— Significant increase of serum adiponectin was observed in bezafibrate-treated subjects compared with placebo group in patients enrolled in The Bezafibrate Infarction Prevention study. Higher baseline adiponectin levels were strongly associated with reduced risk of new diabetes. Fibrates, bezafibrate and fenofibrate, significantly elevated adiponectin levels in wild-type mice and 3T3-L1 adipocytes. Such an effect was not observed in PPARα-deficient mice and adipocytes. Fibrates activated adiponectin promoter but failed to enhance its activity when the point mutation occurred in peroxisome proliferators response element site and the endogenous PPARα was knocked down by PPARα-RNAi. Conclusions— Our results suggest that fibrates enhance adiponectin partly through adipose PPARα and measurement of adiponectin might be a useful tool for searching subjects at high risk for diabetes.
The impressive correlation between cardiovascular disease and glucose metabolism alterations has raised the likelihood that atherosclerosis and type 2 diabetes may share common antecedents. Inflammation is emerging as a conceivable etiologic mechanism for both. Interleukins are regulatory proteins with ability to accelerate or inhibit inflammatory processes. A novel interleukins classification is described, based on their role in diabetes and atherosclerosis, hypothesizing that each interleukin (IL) acts on both diseases in the same direction – regardless if harmful, favorable or neutral. The 29 known interleukins were clustered into three groups: noxious (the "bad", 8 members), comprising IL-1, IL-2, IL-6, IL-7, IL-8, IL-15, IL-17 and IL-18; protective (the "good", 5 members), comprising IL-4, IL-10, IL-11, IL-12 and IL-13; and "aloof", comprising IL-5, IL-9, IL-14, IL-16 and IL-19 through IL-29 (15 members). Each group presented converging effects on both diseases. IL-3 was reluctant to clustering. These observations imply that 1) favorable effects of a given IL on either diabetes or atherosclerosis predicts similar effects on the other; 2) equally, harmful IL effects on one disease can be extrapolated to the other; and 3) absence of influence of a given IL on one of these diseases forecasts lack of effects on the other. These facts further support the unifying etiologic theory of both ailments, emphasizing the importance of a cardiovascular diabetologic approach to interleukins for future research. Pharmacologic targeting of these cytokines might provide an effective means to simultaneously control both atherosclerosis and diabetes.
Multi-hypothesis tracking is a flexible and intuitive approach to tracking multiple nearby objects. However, the original formulation of its data association step is widely thought to scale poorly with the number of tracked objects. We propose enhancements including handling undetected objects and false measurements without inflating the size of the problem, early stopping during solution calculation, and providing for sparse or gated input. These changes collectively improve the computational time and space requirements of data association so that hundreds or thousands of hypotheses over hundreds of objects may be considered in real time. A multi-sensor simulation demonstrates that scaling up the hypothesis count can significantly improve performance in some applications.
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