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Neuroinflammation-related amyloid-beta peptide (Aβ) accumulation after cerebral ischemia/reperfusion (I/R) accounts for cerebral I/R injuries and poststroke dementia. Recently, pyroptosis, a proinflammatory cell death, has been identified as a crucial pathological link of cerebral I/R injuries. However, whether pyroptosis acts as a trigger of Aβ accumulation after cerebral I/R has not yet been demonstrated. Blood-brain barrier (BBB) and glymphatic system mediated by aquaporin-4 (AQP-4) on astrocytic endfeet are important pathways for the clearance of Aβ in the brain, and pyroptosis especially occurring in astrocytes after cerebral I/R potentially damages BBB integrity and glymphatic function and thus influences Aβ clearance and brain homeostasis. In present study, the method of middle cerebral artery occlusion/reperfusion (MCAO/R) was used for building models of focal cerebral I/R injuries in rats. Then, we used lipopolysaccharide and glycine as the agonist and inhibitor of pyroptosis, respectively, Western blotting for detections of pyroptosis, AQP-4, and Aβ1-42 oligomers, laser confocal microscopy for observations of pyroptosis and Aβ locations, and immunohistochemical stainings of SMI 71 (a specific marker for BBB integrity)/AQP-4 and Nissl staining for evaluating, respectively, BBB-glymphatic system and neuronal damage. The results showed that pyroptosis obviously promoted the loss of BBB integrity and AQP-4 polarization, brain edema, Aβ accumulation, and the formation of Aβ1-42 oligomers and thus increased neuronal damage after cerebral I/R. However, glycine could inhibit cerebral I/R-induced pyroptosis by alleviating cytomembrane damage and downregulating expression levels of cleaved caspase-11/1, N-terminal gasdermin D, NLRP3 (nucleotide-binding domain, leucine-rich repeat containing protein 3), interleukin-6 (IL-6) and IL-1β and markedly abate above pathological changes. Our study revealed that pyroptosis is a considerable factor causing toxic Aβ accumulation, dysfunctional BBB-glymphatic system, and neurological deficits after cerebral I/R, suggesting that targeting pyroptosis is a potential strategy for the prevention of ischemic stroke sequelae including dementia.

This paper proposes a perceptual medical image fusion framework based on morphological component analysis combining convolutional sparsity and pulse-coupled neural network, which is called MCA-CS-PCNN for short. Source images are first decomposed into cartoon components and texture components by morphological component analysis, and a convolutional sparse representation of cartoon layers and texture layers is produced by prelearned dictionaries. Then, convolutional sparsity is used as a stimulus to motivate the PCNN for dealing with cartoon layers and texture layers. Finally, the medical fused image is computed via combining fused cartoon layers and texture layers. Experimental results verify that the MCA-CS-PCNN model is superior to the state-of-the-art fusion strategy.

The analysis of the spatiotemporal trends of precipitation and drought is relevant for the future development and sustainable management of water resources in a given region. In this study, precipitation and Standardized Precipitation Index (SPI) trends were analyzed through applying linear regression, Mann–Kendall, and Spearman’s Rho tests at the 5% significance level. For this goal, meteorological data from 9 meteorological stations in and around Aksu Basin during the period 1960–2010 was used, and two main annual drought periods were detected (1978-1979 and 1983–1986), while the extremely dry years were recorded in 1975 and 1985 at almost all of the stations. The monthly analysis of precipitation series indicates that all stations had increasing trend in July, October, and December, while both increasing and decreasing trends were found in other months. For the seasonal scale, precipitation series had increasing trends in summer and winter. 33% of the stations had the decreasing trend on precipitation in the spring series, and it was 11% in the autumn. At the same time, the SPI-12 values of all stations had the increasing trend. The significant trends were detected at Aheqi, Baicheng, Keping, and Kuche stations.