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This technology includes the method of blocking CD38 in expanded natural killer (NK) cell therapy in combination with daratumumab in patients with multiple myeloma. Our in vitro studies have already confirmed the addition of NK cells to myeloma cells that have been exposed to daratumumab enhances myeloma killing compared to single agent treatment.

This technology includes six human monoclonal antibodies (mAbs) that target tumor antigens derived from the CT-RCC HERV-E (human endogenous retrovirus type E) to generate Chimeric Antigen Receptor (CAR) T cells to treat patients with advanced clear cell renal cell carcinoma (ccRCC). These mAbs were identified from Adagene Inc’s human antibody phage library, and data show that majority of these mAbs only bind to CT-RCC HERV-E+ ccRCC cells, which express TM but not CT-RCC HERV-E non-expressing ccRCC cells nor non-RCC cells.

This technology includes a transgenic reporter mouse that expresses a fluorescent protein called mt-Keima, to be used to detect and quantify in vivo mitophagy. This fluorescent protein was originally described by a group in Japan and shown to be able to measure both the general process of autophagy and mitophagy. We extended these results by creating a living animal so that we could get a measurement for in vivo mitophagy. Our results demonstrate that our mt-Keima mouse allows for a straightforward and practical way to quantify mitophagy in vivo.

This technology includes a generated polyclonal antibody in rabbit that detects the mitochondrial uniporter (MCU) protein. This antibody was created by immunizing rabbits with a synthesized sequence of the MCU protein and can be used to identify and quantify MCU protein in various tissues. The polyclonal nature of the antibody ensures it recognizes multiple epitopes on the MCU, enhancing detection reliability. This technology is crucial for understanding MCU's role in mitochondrial function and mammalian physiology.

This technology includes a vaccine for lowering plasma triglycerides by inducing the formation of autoantibodies against either ANGPTL3 or ANGPTL4, which are inhibitors of Lipoprotein Lipase. This was done by conjugating synthetic peptides based on ANGPTL3 or ANGPTL4 to virus- like particles (VLPS). Injection of the vaccine in animal models was shown to induce the autoantibody against the target and to lower plasma triglycerides.

This technology includes a fully automatic 3D image processing system to segment the heart as well as other organs from contrast-enhanced cardiac computed tomography (CCT) images. Our method detects four cardiac chambers including left ventricle, right ventricle, left atrium, right atrium, as well as the ascending aorta and left ventricular myocardium. It also classifies noncardiac tissue structures in the CCT images such as lung, chest wall, spine, descending aorta, and liver.

This technology includes a small molecule drug (VDAC inhibitor, also known as VBIT4) that may be useful for inhibiting lupus disease. To test lupus animal model, VBIT4 was continuously administered for 5 weeks to mice and there was no mortality or clinical symptoms in these animals. Additionally, VBIT4 treatment blocked the development of skin lesions and alopecia of the ears and face, and suppressed the thickening of the epidermis that accompanies leukocyte infiltration.

This technology includes a microscopy method that reduces the speed penalty at least 1000-fold, while retaining resolution improvement. A Digital mirror device (DMD) or sweptfield confocal unit is used to create hundreds to thousands of excitation foci that are imaged to a sample mounted in a conventional microscope and record the resulting emissions on an array detector. Detection of each confocal spot is done in our proprietary software, as is the processing and deconvolution that is used for a 2x resolution enhancement.

This technology includes rhesus macaque induced pluripotent stem cells (iPSCs) lines from multiple animals and various types of cells to establish this pre-clinical model. iPSCs are a type of pluripotent stem cell that can be generated from adult somatic cells. The iPSC technology holds great potential for regenerative medicine. Before clinical application, it is critical to evaluate safety and efficacy in a clinically-relevant animal model. We propose that non-human primate models are particularly relevant to test iPSC-based cell therapies.

This technology includes a novel method to train deep learning convolution neural network model to improve the signal-noise-ratio for the magnetic resonance (MR) imaging. The novelty lies on the fact that actual MR imaging physics information is used in the deep learning training. The resulting model achieves significant signal-to-noise ratio (SNR) improved for different acceleration factors in MR imaging. The resulting model can be used for many body anatomies (e.g., brain, heart, liver, spine, etc.) to significantly improve the SNR.