There is a current void in efficient, cell-specific, retinal drug delivery systems, thus developing a safe, effective, selective drug delivery system would open novel therapeutic avenues. We previously demonstrated that femtosecond (fs) laser irradiation can selectively transfect DNA plasmids into cultured cells in the presence of functionalised gold nanoparticles (AuNPs) (1). Here, we sought out to selectively optoporate retinal cells in vivo with functionalized AuNPs and a 800nm fs laser. The cell-surface Kv1.1 voltage-gated channel was chosen to target retinal ganglion cells (RGCs) in the rat retina. The eyes of anesthetized rats were placed in the beam path of an optical system consisting of a fs laser and an ophthalmoscope for fundus visualization. Following Kv1.1-AuNP and FITC-dextran intravitreal injection and incubation, irradiation resulted in FITC uptake by retinal cells. In addition, similar experiments with Cy3-siRNA clearly show that the technique can effectively deliver siRNA into RGCs. Importantly, neither AuNP intravitreal injection nor irradiation resulted in RGC death, as determined by RBPMS quantification 1 week following AuNP injection and/or irradiation. Since living biological tissues absorb energy very weakly at 800nm, this non-invasive tool may provide a safe, cost effective approach to selectively target retinal cells and limit complications associated with surgical interventions, and potential biological hazards associated with viral-based gene therapy. In addition, given the extensive use of lasers in ophthalmic practice, our proposed technology may be seamlessly inserted to current clinical setups. (1) E. Bergeron et al, Nanoscale, 7, 17836 (2015).
The distortion of a signal due to noise contamination can be overcome by using a decomposition of the signal in a base of wavelets. If the decomposition coefficients are small compared with the noise, the scene is dominated by the distortion. On the contrary, if they are bigger in absolute value, the signal is stronger that the noise. A way of reconstructing an image with a lower level of noise is accomplished neglecting the coefficients which values are lower than a threshold, and replacing them by zero. In this work we present a method that applies the thresholding of the wavelet coefficients in order to perform pattern recognition of noisy scenes. The method could be implemented in optical processing by using a Vander Lugt correlator architecture operating with liquid crystal displays. The function to be recognized is decomposed in sub-bands based on the Gabor decomposition, in the frequency plane. Hard thresholding is performed and the threshold is generated with accurate support functions in the filter plane. The criterion for the threshold selection is chosen to optimize the signal to noise ratio in the output plane. Numerical simulations results are shown and comparisons with other filters are made.
We propose here a method to optically perform multiple feature extraction using wavelet transforms. The method is based on obtaining the optical correlation by means of a Vander Lugt architecture, where the scene and the filter are displayed on spatial light modulators (SLM). Multiple phase filters containing the information about the features that we are interested on extracting are designed and then displayed on a SLM working in mostly phase mode. We have designed filters where edges and corners or different characteristic frequencies contained on the input scene are detected. Simulated and experimental results are shown.