Scalable Deep Color Quantization: a Cluster Imitation Approach.

Color quantization reduces the number of colors used in an image while preserving its content, which is essential in pixel art and knitting art creation. Traditional methods primarily focus on visual fidelity and treat it as a clustering problem in the RGB space. While effective in large (5-6 bits) color spaces, these approaches cannot guarantee semantics in small (1-2 bits) color spaces. On the other hand, deep color quantization methods use network viewers such as AlexNet and ResNet for supervision, effectively preserving semantics in small color spaces. However, in large color spaces, they lag behind traditional methods in terms of visual fidelity. In this work, we propose ColorCNN+, a novel approach that combines the strengths of both. It uses network viewer signals for supervision in small color spaces and learns to cluster the colors in large color spaces. Noteworthily, it is non-trivial for neural networks to do clustering, where existing deep clustering methods often need K-means to cluster the features. In this work, through a newly introduced cluster imitation loss, ColorCNN+ learns to directly output the cluster assignment without any additional steps. Furthermore, ColorCNN+ supports multiple color space sizes and network viewers, offering scalability and easy deployment. Experimental results demonstrate competitive performance of ColorCNN+ across various settings. Code is available at link.

Endocytosis blocks the vesicular secretion of exosome marker proteins.

Exosomes are secreted vesicles of ~30 to 150 nm diameter that play important roles in human health and disease. To better understand how cells release these vesicles, we examined the biogenesis of the most highly enriched human exosome marker proteins, the exosomal tetraspanins CD81, CD9, and CD63. We show here that endocytosis inhibits their vesicular secretion and, in the case of CD9 and CD81, triggers their destruction. Furthermore, we show that syntenin, a previously described exosome biogenesis factor, drives the vesicular secretion of CD63 by blocking CD63 endocytosis and that other endocytosis inhibitors also induce the plasma membrane accumulation and vesicular secretion of CD63. Finally, we show that CD63 is an expression-dependent inhibitor of endocytosis that triggers the vesicular secretion of lysosomal proteins and the clathrin adaptor AP-2 mu2. These results suggest that the vesicular secretion of exosome marker proteins in exosome-sized vesicles occurs primarily by an endocytosis-independent pathway.

Antigen-display exosomes provide adjuvant-free protection against SARS-CoV-2 disease at nanogram levels of spike protein.

As the only bionormal nanovesicle, exosomes have high potential as a nanovesicle for delivering vaccines and therapeutics. We show here that the loading of type-1 membrane proteins into the exosome membrane is induced by exosome membrane anchor domains, EMADs, that maximize protein delivery to the plasma membrane, minimize protein sorting to other compartments, and direct proteins into exosome membranes. Using SARS-CoV-2 spike as an example and EMAD13 as our most effective exosome membrane anchor, we show that cells expressing a spike-EMAD13 fusion protein produced exosomes that carry dense arrays of spike trimers on 50% of all exosomes. Moreover, we find that immunization with spike-EMAD13 exosomes induced strong neutralizing antibody responses and protected hamsters against SARS-CoV-2 disease at doses of just 0.5-5 ng of spike protein, without adjuvant, demonstrating that antigen-display exosomes are particularly immunogenic, with important implications for both structural and expression-dependent vaccines.