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Recombinant immunotoxins (RITs) constitute a promising solution to hematologic cancers (e.g., Multiple Myeloma [MM]). RITs are chimeric proteins composed of a targeting domain fused to a bacterial toxin. Upon binding to a cancer cell displaying the target antigen, RITs are internalized, metabolized and the released toxin kills the cell. While highly active and effective, current RITs have short half-lives, requiring them to be used in high concentrations for treatment. At such high concentrations, RITs may show nonspecific activity and kill healthy 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 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.

Researchers at the National Cancer Institute (NCI) have developed orthotopic allograft models for pancreatic cancer that utilize low passage primary pancreatic adenocarcinoma cells or tumor fragments implanted into the cancer-free pancreata of recipient syngeneic immunocompetent mice. Tumor development in these models is more synchronized, latency is substantially shortened, and tumors develop only in one location, as pre-determined by the choice of a site for cells/tumor fragment implantation.

This technology includes an alpha-galactosidase-A knockout mouse model that can be used to study Fabry disease, an X-linked lysosomal storage disorder. Alpha-galactosidase-A is a crucial enzyme responsible for the breakdown of glycolipids, particularly globotriaosylceramide (Gb3), within lysosomes. In Fabry disease, a rare and inherited lysosomal storage disorder, mutations in the GLA gene lead to deficient or non-functional alpha-galactosidase-A enzyme activity.

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.

This technology includes the creation and use of A3 adenosine receptor (A3AR)-selective agonists for treating chemotherapy-induced peripheral neuropathy, chronic neuropathic pain, rheumatoid arthritis, psoriasis, and other conditions. A3 receptors for adenosine are found in most cells and endogenous activation of the A3 receptors can result in apoptosis, thereby relieving the inflammation or targeting a tumor. A3AR agonists have been a promising strategy for the treatment of various diseases.

This technology includes a gene-based magnetic resonance imaging (MRI) reporter platform that harnesses adeno-associated virus (AAV) delivery of the metal transporter Zip14 to create image contrast wherever the gene is expressed. By driving Zip14 from cell-specific promoters, investigators obtain robust, long-lasting signal changes on standard clinical MRI sequences (e.g., MPRAGE and GRE), enabling real-time visualization of living cells and their gene-expression patterns.