Induction of CD8+ Cytotoxic T Lymphocytes With MHC Class I Restriction by a Soluble Truncated Oncoprotein

CD8+ cytotoxic T lymphocytes (CTLs), which play a major role in the immunological defense against cancer, recognize endogenously produced peptides in the context of MHC class I molecules. We investigated how to induce CD8+ CTL responses against the HER2/neu/c-erbB2 (HER2) oncoprotein often overexpressed in a wide range of human adenocarcinomas. The immunization of BALB/c mice with a syngeneic cell line transduced with HER2 cDNA led to a successful induction of CD8+ CTLs which specifically destroyed HER2-expressing tumor cells. The CTLs recognized the HER2-derived peptide 1 (TYLPTNASL, pos. 63rd-71st amino acid) in the context of MHC class I Kd. The immunization of mice with a truncated HER2 oncoprotein containing 144 amino acids of HER2 (N terminus to 144th amino acid) failed to elicit measurable CTL activity for HER2-expressing target cells. We reconstituted the truncated HER2 protein into a mannan-coated liposome, and complexed the protein with a cholesterol-bearing mannan polysaccharide respectively. Both of these complexes were capable of inducing killer cells specific for HER2-expressing cells in murine model after immunization. These killer cells are Kd restricted CD8+ CTLs which recognize peptide 1. The cholesterol-bearing mannan polysaccharide facilitated the induction of specific CD8+ CTLs by an exogenous HER2 oncoprotein, and may therefore be useful in the development of cancer vaccines

Induction of CD8+ Cytotoxic T Lymphocytes With MHC Class I Restriction by a Soluble Truncated Oncoprotein

CD8+ cytotoxic T lymphocytes (CTLs), which play a major role in the immunological defense against cancer, recognize endogenously produced peptides in the context of MHC class I molecules. We investigated how to induce CD8+ CTL responses against the HER2/neu/c-erbB2 (HER2) oncoprotein often overexpressed in a wide range of human adenocarcinomas. The immunization of BALB/c mice with a syngeneic cell line transduced with HER2 cDNA led to a successful induction of CD8+ CTLs which specifically destroyed HER2-expressing tumor cells. The CTLs recognized the HER2-derived peptide 1 (TYLPTNASL, pos. 63rd-71st amino acid) in the context of MHC class I Kd. The immunization of mice with a truncated HER2 oncoprotein containing 144 amino acids of HER2 (N terminus to 144th amino acid) failed to elicit measurable CTL activity for HER2-expressing target cells. We reconstituted the truncated HER2 protein into a mannan-coated liposome, and complexed the protein with a cholesterol-bearing mannan polysaccharide respectively. Both of these complexes were capable of inducing killer cells specific for HER2-expressing cells in murine model after immunization. These killer cells are Kd restricted CD8+ CTLs which recognize peptide 1. The cholesterol-bearing mannan polysaccharide facilitated the induction of specific CD8+ CTLs by an exogenous HER2 oncoprotein, and may therefore be useful in the development of cancer vaccines

Cached Transformers: Improving Transformers with Differentiable Memory Cache

This work introduces a new Transformer model called Cached Transformer, which uses Gated Recurrent Cached (GRC) attention to extend the self-attention mechanism with a differentiable memory cache of tokens. GRC attention enables attending to both past and current tokens, increasing the receptive field of attention and allowing for exploring long-range dependencies. By utilizing a recurrent gating unit to continuously update the cache, our model achieves significant advancements in \textbf{six} language and vision tasks, including language modeling, machine translation, ListOPs, image classification, object detection, and instance segmentation. Furthermore, our approach surpasses previous memory-based techniques in tasks such as language modeling and displays the ability to be applied to a broader range of situations.Comment: AAAI 202

Real-time Controllable Denoising for Image and Video

Controllable image denoising aims to generate clean samples with human perceptual priors and balance sharpness and smoothness. In traditional filter-based denoising methods, this can be easily achieved by adjusting the filtering strength. However, for NN (Neural Network)-based models, adjusting the final denoising strength requires performing network inference each time, making it almost impossible for real-time user interaction. In this paper, we introduce Real-time Controllable Denoising (RCD), the first deep image and video denoising pipeline that provides a fully controllable user interface to edit arbitrary denoising levels in real-time with only one-time network inference. Unlike existing controllable denoising methods that require multiple denoisers and training stages, RCD replaces the last output layer (which usually outputs a single noise map) of an existing CNN-based model with a lightweight module that outputs multiple noise maps. We propose a novel Noise Decorrelation process to enforce the orthogonality of the noise feature maps, allowing arbitrary noise level control through noise map interpolation. This process is network-free and does not require network inference. Our experiments show that RCD can enable real-time editable image and video denoising for various existing heavy-weight models without sacrificing their original performance.Comment: CVPR 202