BackgroundEarly exercise after stroke promoted angiogenesis and increased microvessles density. However, whether these newly formatted vessels indeed give rise to functional vascular and improve the cerebral blood flow (CBF) in impaired brain region is still unclear. The present study aimed to determine the effect of early exercise on angiogenesis and CBF in ischemic region.MethodsAdult male Sprague Dawley rats were subjected to 90 min middle cerebral artery occlusion(MCAO)and randomly divided into early exercise and non-exercised control group 24 h later. Two weeks later, CBF in ischemic region was determined by laser speckle flowmetry(LSF). Meantime, micro vessels density, the expression of tie-2, total Akt and phosphorylated Akt (p-Akt), and infarct volume were detected with immunohistochemistry, 2,3,5 triphenyltetrazolium chloride (TTC) staining and western blotting respectively. The function was evaluated by seven point’s method.ResultsOur results showed that CBF, vessel density and expression of Tie-2, p-Akt in ischemic region were higher in early exercise group compared with those in non-exercise group. Consistent with these results, rats in early exercise group had a significantly reduced infarct volume and better functional outcomes than those in non-exercise group.ConclusionsOur results indicated that early exercise after MCAO improved the CBF in ischemic region, reduced infarct volume and promoted the functional outcomes, the underlying mechanism was correlated with angiogenesis in the ischemic cortex.
Mining association rules with multiple minimum supports is an important generalization of the association-rule-mining problem, which was recently proposed by Liu et al. Instead of setting a single minimum support threshold for all items, they allow users to specify multiple minimum supports to reflect the natures of the items, and an Apriori-based algorithm, named MSapriori, is developed to mine all frequent itemsets. In this paper, we study the same problem but with two additional improvements. First, we propose a FP-tree-like structure, MIS-tree, to store the crucial information about frequent patterns. Accordingly, an efficient MIS-tree-based algorithm, called the CFP-growth algorithm, is developed for mining all frequent itemsets. Second, since each item can have its own minimum support, it is very difficult for users to set the appropriate thresholds for all items at a time. In practice, users need to tune items' supports and run the mining algorithm repeatedly until a satisfactory end is reached. To speed up this time-consuming tuning process, an efficient algorithm which can maintain the MIS-tree structure without rescanning database is proposed. Experiments on both synthetic and real-life datasets show that our algorithms are much more efficient and scalable than the previous algorithm. D
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.