Vascular endothelial cell function responds to steady laminar shear stress; however, the underlying mechanisms are not fully elucidated. In the present study, we examined the effect of steady laminar shear stress on vascular endothelial cell autophagy and endothelial cell nitric oxide synthase (eNOS) and endothelin-1 (ET-1) expression using an ex vivo perfusion system. Human vascular endothelial cells and common arteries of New Zealand rabbits were pretreated with or without rapamycin or 3-MA for 30 min. These were then placed in an ex vivo cell perfusion system or an ex vivo organ perfusion system under static conditions (0 dynes/cm2) or steady laminar shear stress (5 or 15 dynes/cm2) for 1 h. In both ex vivo perfusion vascular endothelial cells and vascular vessel segment, steady laminar shear stress promoted autophagy and eNOS expression and inhibited ET-1 expression. Compared with steady laminar shear stress treatment alone, the pretreatment of autophagy inducer rapamycin obviously strengthened the expression of eNOS and decreased the expression of ET-1 in both the 5 and 15 dynes/cm2 treatment groups. Moreover, when pretreated with the autophagy inhibitor 3-MA, the eNOS expression was obviously inhibited and the ET-1 expression was reversed. These findings demonstrate that autophagy is upregulated under steady laminar shear stress, improving endothelial cell maintenance of vascular tone function.
The automatic semantic segmentation of point cloud data is important for applications in the fields of machine vision, virtual reality, and smart cities. The processing capability of the point cloud segmentation method with PointNet++ as the baseline needs to be improved for extremely imbalanced point cloud scenes. To address this problem, in this study, we designed a weighted sampling method based on farthest point sampling (FPS), which adjusts the sampling weight value according to the loss value of the model to equalize the sampling process. We also introduced the relational learning of the neighborhood space of the sampling center point in the feature encoding process, where the feature importance is distinguished by using a self-attention model. Finally, the global–local features were aggregated and transmitted using the hybrid pooling method. The experimental results of the six-fold crossover experiment showed that on the S3DIS semantic segmentation dataset, the proposed network achieved 9.5% and 11.6% improvement in overall point-wise accuracy (OA) and mean of class-wise intersection over union (MIoU), respectively, compared with the baseline. On the Vaihingen dataset, the proposed network achieved 4.2% and 3.9% improvement in OA and MIoU, respectively, compared with the baseline. Compared with the segmentation results of other network models on public datasets, our algorithm achieves a good balance between OA and MIoU.
Durability improvement is always important for steel–concrete structures exposed to chloride salt environment. The present research investigated the influence of a novel nano-precursor inhibiting material (NPI), organic carboxylic acid ammonium salt, on the mechanical and transport properties of concrete. The NPI caused a slight reduction in the strength of concrete at later ages. NPI significantly decreased water absorption and slowed down the speed of water absorption of concrete. In addition, the NPI decreased the charge passed and the chloride migration coefficient, and the results of the natural chloride diffusion showed that the NPI decreased the chloride concentration and the chloride diffusion coefficient. The NPI effectively improved the resistance of chloride penetration into testing concrete. The improvement in the impermeability of concrete was ascribed to the incorporation with the NPI, which resulted in increasing the contact angle of cement pastes. The contact angle went up from 17.8° to 85.8° for 0% and 1.2% NPI, respectively, and cement pastes became less hydrophilic. Some small pore throats were unconnected. Besides, the NPI also optimized the pore size distribution of hardened cement paste.
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