We evaluated layer-by-layer retinal thickness in spectral-domain optical coherence tomography (SD-OCT), determined by automated segmentation analysis (ASA) software in healthy and early age-related maculopathy (ARM) eyes. There were 57 eyes (specifically, 19 healthy eyes under 60 years old, 19 healthy eyes over 60, and 19 ARM eyes) recruited into this cross-sectional study. The mean ages were 36.78 (SD, ±13.82), 69.89 (SD, ±6.14), and 66.10 (SD, ±8.67) years, respectively, in the three study groups. The SD-OCT scans were transferred into a dedicated software program that performed automated segmentation of different retinal layers. Automated layer segmentation showed clear boundaries between the following layers: retinal nerve fiber layer (RNFL), ganglion cell layer plus inner plexiform layer (GCL+IPL), inner nuclear layer plus outer plexiform layer (INL+OPL), outer nuclear layer (ONL), and RPE complex. The thickness of the RNFL, ONL, and RPE layers did not show a statistically significant change across the three groups by ANOVA (P = 0.10, P = 0.09, P = 0.15, respectively). The thickness of GCL+IPL and INL+OPL was significantly different across the groups (P < 0.01), being reduced in the ARM eyes compared to healthy eyes, under and over 60 years old. The early morphologic involvement of the GCL+IPL and INL+OPL layers in ARM eyes, as revealed by the ASA, could be related to early anatomic changes described in the inner retina of ARM eyes. This finding may represent a morphologic correlation to the deficits in postreceptoral retinal function in ARM eyes.

This paper studies the temperature dependence of the electrical resistivity of low-cost commercial graphene-based strips, made from a mixture of epoxy and graphene nanoplatelets. An equivalent homogenous resistivity model is derived from the joint use of experimental data and simulation results obtained by means of a full three-dimensional (3D) numerical electrothermal model. Three different types of macroscopic strips (with surface dimensions of cm²) are analyzed, differing in their percentage of graphene nanoplatelets. The experimental results show a linear trend of resistivity in a wide temperature range (−60°C to +60°C), and a negative temperature coefficient . The derived analytical model of temperature-dependent resistivity follows the simple law commonly adopted for conventional conducting materials, such us copper. The model is then validated by using the graphene strips as heating elements by exploiting the Joule effect. These results suggest that such materials can be used as thermistors in sensing or heating applications.