Partial rescue of retinal function in chronically hypoglycemic mice

Purpose. Mice rendered hypoglycemic by a null mutation in the glucagon receptor gene Gcgr display late-onset retinal degeneration and loss of retinal sensitivity. Acute hyperglycemia induced by dextrose ingestion does not restore their retinal function, which is consistent with irreversible loss of vision. The goal of this study was to establish whether long-term administration of high dietary glucose rescues retinal function and circuit connectivity in aged Gcgr−/− mice. Methods. Gcgr−/− mice were administered a carbohydrate-rich diet starting at 12 months of age. After 1 month of treatment, retinal function and structure were evaluated using electroretinographic (ERG) recordings and immunohistochemistry. Results. Treatment with a carbohydrate-rich diet raised blood glucose levels and improved retinal function in Gcgr−/− mice. Blood glucose increased from moderate hypoglycemia to euglycemic levels, whereas ERG b-wave sensitivity improved approximately 10-fold. Because the b-wave reflects the electrical activity of second-order cells, we examined for changes in rod-to-bipolar cell synapses. Gcgr−/− retinas have 20% fewer synaptic pairings than Gcgr+/− retinas. Remarkably, most of the lost synapses were located farthest from the bipolar cell body, near the distal boundary of the outer plexiform layer (OPL), suggesting that apical synapses are most vulnerable to chronic hypoglycemia. Although treatment with the carbohydrate-rich diet restored retinal function, it did not restore these synaptic contacts. Conclusions. Prolonged exposure to diet-induced euglycemia improves retinal function but does not reestablish synaptic contacts lost by chronic hypoglycemia. These results suggest that retinal neurons have a homeostatic mechanism that integrates energetic status over prolonged periods of time and allows them to recover functionality despite synaptic loss.

Familias de curvas elípticas adecuadas para Criptografía Basada en la Identidad

La Criptografía Basada en la Identidad hace uso de curvas elípticas que satisfacen ciertas condiciones (pairingfriendly curves), en particular, el grado de inmersión de dichas curvas debe ser pequeño. En este trabajo se obtienen familias explicitas de curvas elípticas idóneas para este escenario. Dicha criptografía está basada en el cálculo de emparejamientos sobre curvas, cálculo factible gracias al algoritmo de Miller. Proponemos una versión más eficiente que la clásica de este algoritmo usando la representación de un número en forma no adyacente (NAF).

Evaluation of sampling method effects in 3D non-rigid registration

Since the beginning of 3D computer vision problems, the use of techniques to reduce the data to make it treatable preserving the important aspects of the scene has been necessary. Currently, with the new low-cost RGB-D sensors, which provide a stream of color and 3D data of approximately 30 frames per second, this is getting more relevance. Many applications make use of these sensors and need a preprocessing to downsample the data in order to either reduce the processing time or improve the data (e.g., reducing noise or enhancing the important features). In this paper, we present a comparison of different downsampling techniques which are based on different principles. Concretely, five different downsampling methods are included: a bilinear-based method, a normal-based, a color-based, a combination of the normal and color-based samplings, and a growing neural gas (GNG)-based approach. For the comparison, two different models have been used acquired with the Blensor software. Moreover, to evaluate the effect of the downsampling in a real application, a 3D non-rigid registration is performed with the data sampled. From the experimentation we can conclude that depending on the purpose of the application some kernels of the sampling methods can improve drastically the results. Bilinear- and GNG-based methods provide homogeneous point clouds, but color-based and normal-based provide datasets with higher density of points in areas with specific features. In the non-rigid application, if a color-based sampled point cloud is used, it is possible to properly register two datasets for cases where intensity data are relevant in the model and outperform the results if only a homogeneous sampling is used.