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Most solid tumors become stiff with progression of cancer. Cancer Associated Fibroblasts (CAFs), most abundant stromal cells in the tumor microenvironment (TME), are known to mediate such stiffening. While the biochemical crosstalk between CAFs and cancer cells have been widely investigated, it is not clear if and how CAFs in stiffer TME promote metastatic progression. To gather insights into the process, we controlled the mechanical stiffness of the substrates and collected gene expression data with human colorectal CAFs. We cultured human primary CAFs on 2D polyacrylamide hydrogels with increasing elastic modulus (E) of 1, 10 and 40 kPa, and performed genome-wide transcriptome analyses in these cells to identify expression levels of ~16000 genes. The high-quality RNAseq results can be an excellent data-source for bioinformatic analysis for identifying novel pathways and biomarkers in cancer development and metastatic progression. With thorough analysis and accurate interpretation, this data may help researchers understand the role of mechanical stiffness of the TME in CAF-cancer cell crosstalk.

Due to its specificity, fluorescence microscopy has become a quintessential imaging tool in cell biology. However, photobleaching, phototoxicity, and related artifacts continue to limit fluorescence microscopy’s utility. Recently, it has been shown that artificial intelligence (AI) can transform one form of contrast into another. We present phase imaging with computational specificity (PICS), a combination of quantitative phase imaging and AI, which provides information about unlabeled live cells with high specificity. Our imaging system allows for automatic training, while inference is built into the acquisition software and runs in real-time. Applying the computed fluorescence maps back to the quantitative phase imaging (QPI) data, we measured the growth of both nuclei and cytoplasm independently, over many days, without loss of viability. Using a QPI method that suppresses multiple scattering, we measured the dry mass content of individual cell nuclei within spheroids. In its current implementation, PICS offers a versatile quantitative technique for continuous simultaneous monitoring of individual cellular components in biological applications where long-term label-free imaging is desirable.

Tissue-on-chip systems represent promising platforms for monitoring and controlling tissue functions in vitro for various purposes in biomedical research. The two-dimensional (2D) layouts of these constructs constrain the types of interactions that can be studied and limit their relevance to three-dimensional (3D) tissues. The development of 3D electronic scaffolds and microphysiological devices with geometries and functions tailored to realistic 3D tissues has the potential to create important possibilities in advanced sensing and control. This study presents classes of compliant 3D frameworks that incorporate microscale strain sensors for high-sensitivity measurements of contractile forces of engineered optogenetic muscle tissue rings, supported by quantitative simulations. Compared with traditional approaches based on optical microscopy, these 3D mechanical frameworks and sensing systems can measure not only motions but also contractile forces with high accuracy and high temporal resolution. Results of active tension force measurements of engineered muscle rings under different stimulation conditions in long-term monitoring settings for over 5 wk and in response to various chemical and drug doses demonstrate the utility of such platforms in sensing and modulation of muscle and other tissues. Possibilities for applications range from drug screening and disease modeling to biohybrid robotic engineering.

Pumps are critical life-sustaining components for all animals. At the earliest stages of life, the tubular embryonic heart works as a valveless pump capable of generating unidirectional blood flow. Inspired by this elementary pump, we developed an example of a biohybrid valveless pump-bot powered by engineered skeletal muscle. Our pump-bot consists of a soft hydrogel tube connected at both ends to a stiffer polydimethylsiloxane (PDMS) scaffold, creating an impedance mismatch. A contractile muscle ring wraps around the hydrogel tube at an off-center location, squeezing the tube with or without buckling it locally. Cyclic muscle contractions, spontaneous or electrically stimulated, further squeeze the tube, resulting in elastic waves that propagate along the soft tube and get reflected back at the soft/stiff tube boundaries. Asymmetric placement of muscle ring results in a time delay between the wave arrivals, thus establishing a net unidirectional fluid flow irrespective of whether the tube is buckled or not. Flow rates of up to 22.5 μL/min are achieved by the present pump-bot, which are at least three orders of magnitude higher than those from cardiomyocyte-powered valve pumps of similar size. Owning to its simple geometry, robustness, ease of fabrication, and high pumping performance, our pump-bot is particularly well-suited for a wide range of biomedical applications in microfluidics, drug delivery, biomedical devices, cardiovascular pumping system, and more.

Motivated by the unexplored potential of in vitro neural systems for computing and by the corresponding need of versatile, scalable interfaces for multimodal interaction, an accurate, modular, fully customizable, and portable recording/stimulation solution that can be easily fabricated, robustly operated, and broadly disseminated is presented. This approach entails a reconfigurable platform that works across multiple industry standards and that enables a complete signal chain, from neural substrates sampled through micro‐electrode arrays (MEAs) to data acquisition, downstream analysis, and cloud storage. Built‐in modularity supports the seamless integration of electrical/optical stimulation and fluidic interfaces. Custom MEA fabrication leverages maskless photolithography, favoring the rapid prototyping of a variety of configurations, spatial topologies, and constitutive materials. Through a dedicated analysis and management software suite, the utility and robustness of this system are demonstrated across neural cultures and applications, including embryonic stem cell‐derived and primary neurons, organotypic brain slices, 3D engineered tissue mimics, concurrent calcium imaging, and long‐term recording. Overall, this technology, termed “mind in vitro” to underscore the computing inspiration, provides an end‐to‐end solution that can be widely deployed due to its affordable (>10× cost reduction) and open‐source nature, catering to the expanding needs of both conventional and unconventional electrophysiology.