Upregulation of miR-489-3p Attenuates Cerebral Ischemia/Reperfusion Injury by Targeting Histone Deacetylase 2 (HDAC2).

Cerebral ischemia/reperfusion (I/R) injury is the continuation and deterioration of ischemic injury, and there are no effective treatment strategies for this condition. It has been reported that microRNAs (miRNAs) are considered as potential targets to protect the brain against I/R injury. Previous studies have shown that miR-489-3p plays a vital role in regulating apoptosis of neurons. miR-489-3p is considered as a potential target to protect the brain against I/R injury-induced neuron apoptosis. This study aimed to explore the molecular mechanism of miR-489-3p in protection against cerebral I/R injury. A rat model with cerebral I/R injury was established using the MCAO method. The cell model was constructed using the oxygen­glucose deprivation (OGD) method. The expression of miR-489-3p was detected by qRT-PCR. The expression of HDAC2 was detected by Western blot assay and immunofluorescence assay. Cell apoptosis was evaluated by flow cytometry and TUNEL staining assay. The relationship between miR-489-3p and HDAC2 was determined by bioinformatics analysis and luciferase reporter assay. Rescue experiments were performed to investigate the mechanism of the miR-489-3p/HDAC2 axis. miR-489-39 was significantly downregulated, while HDAC2 was upregulated during cerebral I/R injury both in vitro and in vivo. Upregulation of miR-489-3p obviously attenuated cerebral I/R injury by increasing PC12 cell viability, reducing LDH release, and inhibiting cell apoptosis. HDAC2 was identified as a direct target of miR-489-3p. Silencing of HDAC2 showed a neuroprotective effect against OGD/R injury in vitro. Overexpression of HDAC2 significantly attenuated the protective effects of miR-489-3p mimics on cell injury in vitro. Our results revealed that the upregulation of miR-489-3p attenuated cerebral I/R injury by negatively regulating HDAC2.

Do street-level scene perceptions affect housing prices in Chinese megacities? An analysis using open access datasets and deep learning.

Many studies have explored the relationship between housing prices and environmental characteristics using the hedonic price model (HPM). However, few studies have deeply examined the impact of scene perception near residential units on housing prices. This article used house purchasing records from FANG.com and open access geolocation data (including massive street view pictures, point of interest (POI) data and road network data) and proposed a framework named "open-access-dataset-based hedonic price modeling (OADB-HPM)" for comprehensive analysis in Beijing and Shanghai, China. A state-of-the-art deep learning framework and massive Baidu street view panoramas were employed to visualize and quantify three major scene perception characteristics (greenery, sky and building view indexes, abbreviated GVI, SVI and BVI, respectively) at the street level. Then, the newly introduced scene perception characteristics were combined with other traditional characteristics in the HPM to calculate marginal prices, and the results for Beijing and Shanghai were explored and compared. The empirical results showed that the greenery and sky perceptual elements at the property level can significantly increase the housing price in Beijing (RMB 39,377 and 6011, respectively) and Shanghai (RMB 21,689 and 2763, respectively), indicating an objectively higher willingness by buyers to pay for houses that provide the ability to perceive natural elements in the surrounding environment. This study developed quantification tools to help decision makers and planners understand and analyze the interaction between residents and urban scene components.