Automatic Counting of Microglial Cells in Healthy and Glaucomatous Mouse Retinas

Proliferation of microglial cells has been considered a sign of glial activation and a hallmark of ongoing neurodegenerative diseases. Microglia activation is analyzed in animal models of different eye diseases. Numerous retinal samples are required for each of these studies to obtain relevant data of statistical significance. Because manual quantification of microglial cells is time consuming, the aim of this study was develop an algorithm for automatic identification of retinal microglia. Two groups of adult male Swiss mice were used: age-matched controls (naïve, n = 6) and mice subjected to unilateral laser-induced ocular hypertension (lasered; n = 9). In the latter group, both hypertensive eyes and contralateral untreated retinas were analyzed. Retinal whole mounts were immunostained with anti Iba-1 for detecting microglial cell populations. A new algorithm was developed in MATLAB for microglial quantification; it enabled the quantification of microglial cells in the inner and outer plexiform layers and evaluates the area of the retina occupied by Iba-1+ microglia in the nerve fiber-ganglion cell layer. The automatic method was applied to a set of 6,000 images. To validate the algorithm, mouse retinas were evaluated both manually and computationally; the program correctly assessed the number of cells (Pearson correlation R = 0.94 and R = 0.98 for the inner and outer plexiform layers respectively). Statistically significant differences in glial cell number were found between naïve, lasered eyes and contralateral eyes (P<0.05, naïve versus contralateral eyes; P<0.001, naïve versus lasered eyes and contralateral versus lasered eyes). The algorithm developed is a reliable and fast tool that can evaluate the number of microglial cells in naïve mouse retinas and in retinas exhibiting proliferation. The implementation of this new automatic method can enable faster quantification of microglial cells in retinal pathologies.

Development of a program of radiopaque lesions images via radiographic cases for active learning in oral medicine

Through the creation of this project in English, we have made a file of radiographic images that will be used by third year dental students in order to improve the practical teaching part of the subject of Oral Medicine, essentially by incorporating these files to the Virtual Campus. We have selected the most representative radiopaque radiographic images studied in pathology lectures given. We have prepared a file with 59 radiopaque radiographic images. These lesions have been divided according to their relationship and number with the tooth, into the following groups: “Anatomic radiopacities”, “Periapical radiopacities”, “Solitary radiopacities not necessarily contacting teeth”,“Multiple separate radiopacities”, and “Generalized radiopacities”. We created 4 flowcharts synthesizing the mayor explanatory bases of each pathological process in relation to other pathologies within each location. We have focused primarily in those clinical and radiographic features that can help us differentiate one pathology from another. We believe that by giving the student a knowledge base through each flowchart, as well as provide clinical cases, will start their curiosity to seek new cases on the Internet or try to look for images that we have not been able to locate due to low frequency. In addition, as this project has been done in English, it will provide the students with necessary tools to do a literature search, as most of the medical and dental literature is in English; thus far, providing the student with this material necessary to make the appropriate searched using keywords in English.