Tissue engineering has offered unique opportunities for disease modeling and regenerative medicine; however, the success of these strategies is dependent on faithful reproduction of native cellular organization. Here, it is reported that ultrasound standing waves can be used to organize myoblast populations in material systems for the engineering of aligned muscle tissue constructs. Patterned muscle engineered using type I collagen hydrogels exhibits significant anisotropy in tensile strength, and under mechanical constraint, produced microscale alignment on a cell and fiber level. Moreover, acoustic patterning of myoblasts in gelatin methacryloyl hydrogels significantly enhances myofibrillogenesis and promotes the formation of muscle fibers containing aligned bundles of myotubes, with a width of 120–150 µm and a spacing of 180–220 µm. The ability to remotely pattern fibers of aligned myotubes without any material cues or complex fabrication procedures represents a significant advance in the field of muscle tissue engineering. In general, these results are the first instance of engineered cell fibers formed from the differentiation of acoustically patterned cells. It is anticipated that this versatile methodology can be applied to many complex tissue morphologies, with broader relevance for spatially organized cell cultures, organoid development, and bioelectronics.

Successful treatment of brain tumors such as glioblastoma multiforme (GBM) is limited in large part by the cumulative dose of Radiation Therapy (RT) that can be safely given and the blood-brain barrier (BBB), which limits the delivery of systemic anticancer agents into tumor tissue. Consequently, the overall prognosis remains grim. Herein, we report our pilot studies in cell culture experiments and in an animal model of GBM in which RT is complemented by PEGylated-gold nanoparticles (GNPs). GNPs significantly increased cellular DNA damage inflicted by ionizing radiation in human GBM-derived cell lines and resulted in reduced clonogenic survival (with dose-enhancement ratio of ∼1.3). Intriguingly, combined GNP and RT also resulted in markedly increased DNA damage to brain blood vessels. Follow-up in vitro experiments confirmed that the combination of GNP and RT resulted in considerably increased DNA damage in brain-derived endothelial cells. Finally, the combination of GNP and RT increased survival of mice with orthotopic GBM tumors. Prior treatment of mice with brain tumors resulted in increased extravasation and in-tumor deposition of GNP, suggesting that RT-induced BBB disruption can be leveraged to improve the tumor-tissue targeting of GNP and thus further optimize the radiosensitization of brain tumors by GNP. These exciting results together suggest that GNP may be usefully integrated into the RT treatment of brain tumors, with potential benefits resulting from increased tumor cell radiosensitization to preferential targeting of tumor-associated vasculature.

Endogenous biomarkers remain at the forefront of early disease detection efforts, but many lack the sensitivities and specificities necessary to influence disease management. Inspired by emerging adoptive cell transfer immunotherapies and the natural migration of immune cells to pathology, here we describe a new class of cell-based in vivo sensors for ultrasensitive disease detection. In our proof of concept, we perform adoptive transfer of syngeneic macrophages which were engineered to produce a synthetic biomarker upon adopting a 'tumor-associated' metabolic profile. Notably, the macrophage sensor detected tumors as small as 25-50 mm 3 , effectively tracked the immunological response in two models of acute inflammation, and was more sensitive than both protein and nucleic acid cancer biomarkers. This technology establishes a clinically translatable approach to early cancer detection and provides a conceptual framework for the use of engineered immune cells for the monitoring of many disease states in addition to cancer.

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Brain in vitro models are critically important to developing our understanding of basic nervous system cellular physiology, potential neurotoxic effects of chemicals, and specific cellular mechanisms of many disease states. In this study, we sought to address key shortcomings of current brain in vitro models: the scarcity of comparative data for cells originating from distinct brain regions and the lack of multiregional brain in vitro models. We demonstrated that rat neurons from different brain regions exhibit unique profiles regarding their cell composition, protein expression, metabolism, and electrical activity in vitro. In vivo, the brain is unique in its structural and functional organization, and the interactions and communication between different brain areas are essential components of proper brain function. This fact and the observation that neurons from different areas of the brain exhibit unique behaviors in vitro underline the importance of establishing multiregional brain in vitro models. Therefore, we here developed a multiregional brain-on-a-chip and observed a reduction of overall firing activity, as well as altered amounts of astrocytes and specific neuronal cell types compared with separately cultured neurons. Furthermore, this multiregional model was used to study the effects of phencyclidine, a drug known to induce schizophrenia-like symptoms in vivo, on individual brain areas separately while monitoring downstream effects on interconnected regions. Overall, this work provides a comparison of cells from different brain regions in vitro and introduces a multiregional brain-on-a-chip that enables the development of unique disease models incorporating essential in vivo features. Due to the scarcity of comparative data for cells from different brain regions in vitro, we demonstrated that neurons isolated from distinct brain areas exhibit unique behaviors in vitro. Moreover, in vivo proper brain function is dependent on the connection and communication of several brain regions, underlining the importance of developing multiregional brain in vitro models. We introduced a novel brain-on-a-chip model, implementing essential in vivo features, such as different brain areas and their functional connections.