We present a photocurable, biocompatible, and flexible silicone-hydrogel hybrid material for stereolithographic (SLA) printing of biomedical devices. The silicone-hydrogel polymer is similar to mixtures used for contact lenses. It is flexible and stretchable with a Young’s modulus of 78 MPa and a maximum elongation at break of 51%, shows a low degree of swelling (<4% v/v) in water, and can be bonded easily to flat glass substrates via a surface-modification method. The in vitro cytotoxicity of the material is assessed with a WST-8 cell viability assay using five different cell lines: HT1080, L929, and Hs27 fibroblasts, cardiomyocyte-like HL-1 cells, and neuronal-phenotype PC-12 cells. On this account, the silicone-hydrogel polymer is compared to several other common SLA printing materials used for cell-culture applications and polydimethylsiloxane (PDMS). A simple extraction step in water is sufficient for reaching biocompatibility of the material with respect to the tested cell types. The oxygen permeability of the silicone-hydrogel material is investigated and compared to that of PDMS, Medicalprint cleara commercial resin for medical products, and a short-chain hydrogel-based resin. As a proof of concept, we demonstrate a 3D-printed microfluidic device with integrated valves and mixers. Furthermore, we show a printed culture chamber for analyzing signal propagation in HL-1 cardiomyocyte cell networks. Ca2+ imaging is used to observe the signal propagation through the cardiac cell layers grown in the microchannels. The cells are shown to maintain normal electrophysiological activity within the printed chambers. Overall, the biocompatible silicone-hydrogel material will be an advancement for SLA printing in cell-culture and microfluidic lab-on-a-chip applications.
Superabsorbent polymers are materials that exhibit a high swelling behavior in liquids and can hold the absorbed liquid even against externally applied pressure. They are commercially used, for example, in baby diapers, fake snow, or swellable children's toys. Most commercially available superabsorbent polymers are based on polymerized and crosslinked sodium acrylate. Here, a material formulation to create 3D objects using stereolithographic printing of sodium acrylate is demonstrated. The material shows typical superabsorbent properties that cannot be reached with conventional 3D printing materials. The printed structures swell strongly (up to 20 times in weight) in aqueous environments and still show 65% of the swelling under an external load of 100 kPa. This swelling can be used for 3D printed parts that can automatically change their size or shape when exposed to water. To show the versatility of this approach, selected structures are 3D printed, including a ship and a medical stent. Also the applicability of actuation by printing a structure is demonstrated, which deforms to a self‐closing container upon exposure to water.
This work demonstrates a lateral flow assay concept on the basis of stochastic-impact electrochemistry. To this end, we first elucidate requirements to employ silver nanoparticles as redox-active labels. Then, we present a prototype that utilizes nanoimpacts from biotinylated silver nanoparticles as readouts to detect free biotin in solution based on competitive binding. The detection is performed in a membrane-based microfluidic system, where free biotin and biotinylated particles compete for streptavidin immobilized on embedded latex beads. Excess nanoparticles are then registered downstream at an array of detection electrodes. In this way, we establish a proof of concept that serves as a blueprint for future “digital” lateral flow sensors.
Cellular micromotion—a tiny movement of cell membranes on the nm-µm scale—has been proposed as a pathway for inter-cellular signal transduction and as a label-free proxy signal to neural activity. Here we harness several recent approaches of signal processing to detect such micromotion in video recordings of unlabeled cells. Our survey includes spectral filtering of the video signal, matched filtering, as well as 1D and 3D convolutional neural networks acting on pixel-wise time-domain data and a whole recording respectively.
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