Chronic intermittent hypobaric hypoxia (CIHH) has protective effects on heart and brain against ischemia injury through mobilizing endogenous adaptive mechanisms. However, whether CIHH prevents against cognitive impairment was not elucidated. The present study aimed to investigate the effect and mechanism of CIHH treatment on ischemia/reperfusion (IR)-induced cognitive dysfunction. Mice were randomly divided into 8 groups: Control, Sham, CIHH (simulating 5000 m high-altitude for 28 days, 6 h per day), IR (three 16-min occlusions of bilateral common carotid arteries interrupted by two 10-min intervals), CIHH + IR, PD98059 (inhibitor of MEK1/2) + CIHH + IR, PD98059 + Sham and PD98059 + IR group. Morris water maze and step-down passive avoidance tests were performed to evaluate the capability of learning and memory 1 month after ischemia. Thionine dyeing was to examine histological manifestations of pyramidal neurons in hippocampus CA1 region. Western blotting assay was for measurement of the protein expressions in ERK1/2-CREB-BDNF signaling pathway. There were a shorter escape latency and a longer percentage of time retaining in the target quadrant in Morris water maze test, fewer times of errors in the step-down avoidance test and a higher neuronal density of the hippocampal CA1 subfield in CIHH + IR group than in IR group. CIHH upregulated the expressions of BDNF, phosphorylated CREB, ERK1/2 and TrkB with or without ischemia. The protective effects of CIHH were abolished by PD98059 administration 15 min before ischemia. CIHH ameliorated ischemia-induced cognitive dysfunction through activation of ERK1/2-CREB-BDNF signaling pathway.
We consider the higher-order Markov Chain, and characterize the second order Markov chains admitting every probability distribution vector as a stationary vector. The result is used to construct Markov chains of higher-order with the same property. We also study conditions under which the set of stationary vectors of the Markov chain has a certain affine dimension.
For an estimation with missing data, a crucial step is to determine if the data are missing completely at random (MCAR), in which case a complete‐case analysis would suffice. Most existing tests for MCAR do not provide a method for a subsequent estimation once the MCAR is rejected. In the setting of estimating means, we propose a unified approach for testing MCAR and the subsequent estimation. Upon rejecting MCAR, the same set of weights used for testing can then be used for estimation. The resulting estimators are consistent if the missingness of each response variable depends only on a set of fully observed auxiliary variables and the true outcome regression model is among the user‐specified functions for deriving the weights. The proposed method is based on the calibration idea from survey sampling literature and the empirical likelihood theory.
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