Natural Bagaza virus infection in game birds in southern Spain

In late summer 2010 a mosquito born flavivirus not previously reported in Europe called Bagaza virus (BAGV) caused high mortality in red-legged partridges (Alectoris rufa) and ring-necked pheasants (Phasianus colchicus). We studied clinical findings, lesions and viral antigen distribution in naturally BAGV infected game birds in order to understand the apparently higher impact on red-legged partridges. The disease induced neurologic signs in the two galliform species and, to a lesser extent, in common wood pigeons (Columba palumbus). In red-legged partridges infection by BAGV caused severe haemosiderosis in the liver and spleen that was absent in pheasants and less evident in common wood pigeons. Also, BAGV antigen was present in vascular endothelium in multiple organs in red-legged partridges, and in the spleen in common wood pigeons, while in ring-necked pheasants it was only detected in neurons and glial cells in the brain. These findings indicate tropism of BAGV for endothelial cells and a severe haemolytic process in red-legged partridges in addition to the central nervous lesions that were found in all three species.

Retinal Macroglial Responses in Health and Disease

Due to their permanent and close proximity to neurons, glial cells perform essential tasks for the normal physiology of the retina. Astrocytes andM¨uller cells (retinal macroglia) provide physical support to neurons and supplement them with several metabolites and growth factors.Macroglia are involved in maintaining the homeostasis of extracellular ions and neurotransmitters, are essential for information processing in neural circuits, participate in retinal glucose metabolism and in removing metabolic waste products, regulate local blood flow, induce the blood-retinal barrier (BRB), play fundamental roles in local immune response, and protect neurons from oxidative damage. In response to polyetiological insults, glia cells react with a process called reactive gliosis, seeking to maintain retinal homeostasis. When malfunctioning, macroglial cells can become primary pathogenic elements. A reactive gliosis has been described in different retinal pathologies, including age-related macular degeneration (AMD), diabetes, glaucoma, retinal detachment, or retinitis pigmentosa. A better understanding of the dual, neuroprotective, or cytotoxic effect of macroglial involvement in retinal pathologies would help in treating the physiopathology of these diseases.The extensive participation of the macroglia in retinal diseases points to these cells as innovative targets for new drug therapies.

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.