**6. Conclusions**

The general aim of this chapter was to establish an analysis for a comparison of retinal tissues with retinopathy diabetic and healthy tissues, which is an important problem to mechanically understanding of the processes that lead to the experimental observations.

In retinal tissues, metrics as quantification of Voronoi polygons and Delaunay triangles, are not sensitive to register changes in cellular organization, because in the first geometry, the number of dominant polygons are both six and five sides in both cases, and in the second geometry are presented the same amount of triangles Delaunay, as it has been reported by many authors [2–7]. Similarly, Kaccie and Roorda [50] showed that Voronoi regions gradually increase in size at higher eccentricities.

In this chapter, we focused here on the photoreceptor degeneration in an animal model of retinal degenerative disease, retinopathy diabetic, in which we investigate how pathology affects mosaic organization. We analyzed 128 retinal tissues here, eventually we found abnormality in retinal tissues. This spacing rule is enough to simulate the geometry of mosaics, suggesting that interactions between the mosaic cells satisfy tessellation formations of healthy tissues and pathological damaged

tissues. Once generated, cells migrate to their layer, and a simple rule controlling the spacing between cells of the same type suffices to control mosaic formation [51, 52]. This ensures uniform coverage of the retina by each type of cell, regarding the mechanisms that control the genesis of the different retinal cells.

From the Voronoi analyses, the parameter of Eq. (1), was also obtained. This has been reported to be very sensitive to changes in photoreceptors spacing [11]. Independently of the number of sides of the Voronoi polygons, the PR spacing increased in the samples with DR, what represents an expansion in cellular spacing.

Based on the results obtained, the metric that are suggested to detect morphological changes in retinal tissues with DR is the metric of the mean averaged distance (Eq. (1), **Figure 17**) and the mean square deviation of the angles (Eq. (3), **Table 2**), in both cases *P* value <0.05.

In this study, among the tools presented that are highly reliable and ready to be tested with human retinas are the mean averaged distance (Eq. (1)) and the mean square deviation of the angles (Eq. (3)), which have a high sensitivity to detect changes in DR tissues, by using retinal images obtained with a fundus camera or AOSLO. We consider that the tools mentioned (Eqs. (1) and (2)) are reliable enough to perform clinical level tests.

A much more effective developmental design, consistent with the experimental observations so far available, is that cell genesis and cell positioning are determined separately, which requires a combination of experimental and theoretical tools. Although we learn from comparing real data to obtain patterns, a mathematical model is needed to investigate the contribution from many retinal processes. The understanding of the distribution of cone density and spacing as a function of retinal eccentricity in the same eye and between fellow eyes of the same subject could be of great clinical utility when monitoring a subject longitudinally over time or when comparing controls with presumptive pathologic cases.

Several studies of diabetic retinopathy have focused especially on the retinal vasculature, but recent studies suggest that the neural retina also is involved. Oxidative stress and local inflammatory changes have been shown to play important roles in the pathogenesis of this retinopathy, but the source of reactive oxygen species has been less clear. Du et al. [53] accumulating evidence suggests that photoreceptor cells play a previously unappreciated role in the development of early stages of diabetic retinopathy, but the mechanism by which this occurs is not clear. The oxidative stress in retinas of diabetic mice emanates from neural photoreceptor cells, and elimination of these cells in diabetes inhibits both the oxidative stress and inflammatory changes shown to cause the vascular lesions of diabetic retinopathy. These studies suggest a mechanism by which neural cells can initiate the vascular injury characteristic of diabetic retinopathy.

Finally, we show in this chapter provides new insight into the mechanisms loss of cells observed of mice retinas, and could be used to rescue inner retinal neurons from secondary degeneration, enlarging the time window in which receptor transplants or substitution may be for the benefit of subjects suffering retinal degenerative diseases.
