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The pathogenesis of age-related macular degeneration involves chronic oxidative stress, impaired degradation of membranous discs shed from photoreceptor outer segments and accumulation of lysosomal lipofuscin in retinal pigment epithelial (RPE) cells. It has been estimated that a major part of cellular proteolysis occurs in proteasomes, but the importance of proteasomes and the other proteolytic pathways including autophagy in RPE cells is poorly understood. Prior to proteolysis, heat shock proteins (Hsps), agents that function as molecular chaperones, attempt to refold misfolded proteins and thus prevent the accumulation of cytoplasmic protein aggregates. In the present study, the roles of the Hsp70 molecular chaperone and proteasomal and lysosomal proteolytic pathways were evaluated in human RPE cells (ARPE-19). The Hsp70 and ubiquitin protein levels and localization were analysed by Western blotting and immunofluorescense. Confocal and transmission electron microscopy were used to detect cellular organelles and to evaluate the morphological changes. Hsp70 levels were modulated using RNA interference and overexpression techniques. Cell viability was measured by colorimetric assay. The proteasome inhibitor MG-132 evoked the accumulation of perinuclear aggregates positive for Hsp70, ubiquitin-protein conjugates and the lysosomal membrane protein LAMP-2. Interestingly, the hsp70 mRNA depletion significantly increased cell death in conjunction with proteasome inhibition. We found that the accumulation of lysosomes was reversible: a cessation of proteasome inhibition led to clearance of the deposits via a mechanism believed to include autophagy. The molecular chaperone Hsp70, proteasomes and autophagy have an important regulatory role in the protein turnover of human RPE cells and may thus open new avenues for understanding degenerative processes in retinal cells.

The problem of estimating spectral reflectances from the responses of a digital camera has received considerable attention recently. This problem can be cast as a regularized regression problem or as a statistical inversion problem. We discuss some previously suggested estimation methods based on critically undersampled RGB measurements and describe some relations between them. We concentrate mainly on those models that are using a priori information in the form of high-resolution measurements. We use the "kernel machine" framework in our evaluations and concentrate on the use of multiple illuminations and on the investigation of the performance of global and locally adapted estimation methods. We also introduce a nonlinear transformation of reflectance values to ensure that the estimated reflection spectra fulfill physically motivated boundary conditions. The reported experimental results are derived from measured and simulated camera responses from the Munsell Matte, NCS, and Pantone data sets.

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