Researchers from the University of Illinois have developed a new synthetic tissue microenvironment that may give cancer researchers the next-best look at tumor growth and behavior. The 3D patterned vasculature tumor microenvironment is created by changing the flow rates of fluid channels and the structures are made of alginate that was mixed with breast cancer cells in the outer layer and macrophages on the inner layer. The 3D vascularization, a network of capillaries that carry drugs and other materials are created can go from straight, to snakelike, to any shape, that offers modelling for metastasis, because the vessel architecture can be tuned on the ﬂy.
The technology accurately predicted the clinically measured EC50 of three drugs: Gefitinib, zoledronic acid, and RAC inhibitor. This quick process to create synthetic tumor microenvironments lends to tremendous potential such as model systems for high-throughput screening for drug efficacy, as well as flowable and vascularized lab-on-a-fiber platforms. Finally, biopsied cancer cells lends to personalized cancer treatments with this device that could realistically and quickly recreate microenvironments found across biology.
Dr. John Rogers from the University of Illinois at Urbana-Champaign has developed bioresorbable silicon electronics that can be used for real-time sensing of neural electrical activity. This invention could prevent follow-up neural surgeries, and has potentials for long-term monitoring of patients.
Dr. Andrew Smith from the University of Illinois has developed new quantum dots with a multidentate polymer coating that minimizes size while maintaining stability and improving efficiency of conjugation. Quantum dots are promising agents for cellular and molecular imaging, but their bulky organic coatings have limited their use in cells. Dr. Smith's quantum dots are small, stable, and can be conjugated to targeting molecules and purified easily.
Dr. Hergenrother from the University of IL has developed a novel antibiotic that is effective against certain antibiotic-resistant gram-negative bacteria. His powerful predictive algorithm determines accumulation of molecules in Gram-negative bacteria and enables conversion of known Gram-positive only antibiotics into novel compounds with Gram-negative potency.