As the basic pathological changes of diabetic retinopathy (DR), the destruction of the blood-retina barrier (BRB) and vascular leakage have attracted extensive attention. Without timely intervention, BRB damage will eventually lead to serious visual impairment. However, due to the delicate structure and complex function of the BRB, the mechanism underlying damage to the BRB in DR has not been fully clarified. Here, we used single-cell RNA sequencing (RNA-seq) technology to analyze 35,910 cells from the retina of healthy and streptozotocin (STZ)-induced diabetic rats, focusing on the degeneration of the main cells constituting the rat BRB in DR and the new definition of two subpopulations of Müller cells at the cell level, Ctxn3+Müller and Ctxn3−Müller cells. We analyzed the characteristics and significant differences between the two groups of Müller cells and emphasized the importance of the Ctxn3+Müller subgroup in diseases. In endothelial cells, we found possible mechanisms of self-protection and adhesion and recruitment to pericytes. In addition, we constructed a communication network between endothelial cells, pericytes, and Müller subsets and clarified the complex regulatory relationship between cells. In summary, we constructed an atlas of the iBRB in the early stage of DR and elucidate the degeneration of its constituent cells and Müller cells and the regulatory relationship between them, providing a series of potential targets for the early treatment of DR.

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In view of the difficulty of sensor installation and complicated process in traditional structure health monitoring, a feature point monitoring based on optical flow is proposed in this paper. A high-speed camera is applied to capture the dynamic response of the structure under excitation, and feature point could be selected and marked at any position in the video. The movement of the selected point could be traced and calculated by feature optical flow method, and the displacement time series of the feature point could be obtained. Results show that the displacement time series obtained from proposed method in this paper is consistent with the data of the pull-wire displacement sensor, the maximum displacement error is 3.3%, the method proposed is more flexible, convenient and of low cost.