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One of the obstacles limiting progress in the development of effective cancer therapies is the shortage of preclinical models that capture the dynamic nature of tumor microenvironments. Interstitial flow strongly impacts tumor response to chemotherapy; however, conventional in vitro cancer models largely disregard this key feature. Here, a proof of principle microfluidic platform for the generation of large arrays of breast tumor spheroids that are grown under close-to-physiological flow in a biomimetic hydrogel is reported. This cancer spheroids-on-a-chip model is used for time-and labor-efficient studies of the effects of drug dose and supply rate on the chemosensitivity of breast tumor spheroids. The capability to grow large arrays of tumor spheroids from patient-derived cells of different breast cancer subtypes is shown, and the correlation between in vivo drug efficacy and on-chip spheroid drug response is demonstrated. The proposed platform can serve as an in vitro preclinical model for the development of personalized cancer therapies and effective screening of new anticancer drugs.

Polymer hydrogels exhibit actuation properties that result in reversible shape transformations and have promising applications in soft robotics, drug delivery systems, sensors, and microfluidic devices. Actuation occurs due to differential hydrogel swelling and is generally achieved by modulating hydrogel composition. Here a different approach to hydrogel actuation that originates solely from its structural anisotropy is reported. For 3D-printed single-layer hydrogels formed by cellulose nanocrystals (CNCs) and gelatin methacryloyl it is shown that shear-induced orientation of CNCs results in anisotropic mechanical and swelling properties of the hydrogel. Upon swelling in water, planar hydrogels acquire multiple complex 3D shapes that are achieved by i) varying CNC orientation with respect to the shape on the hydrogel sheet and ii) patterning the hydrogel with the regions of shearmediated and random CNC orientation. This study shows the capability to generate multiple shapes from the same hydrogel actuator based on the degree of its structural anisotropy. In addition, it introduces a biocompatible nanocolloidal ink with shear-thinning and self-healing properties for additive manufacturing of hydrogel actuators.

Many applications of inorganic nanoparticles (NPs), including photocatalysis, photovoltaics, chemical and biochemical sensing, and theranostics, are governed by NP optical properties. Exploration and identification of reaction conditions for the synthesis of NPs with targeted spectroscopic characteristics is a time-, labor-, and resource-intensive task, as it involves the optimization of multiple interdependent reaction conditions. Integration of machine learning (ML) and microfluidics (MF) offers accelerated identification and optimization of reaction conditions for NP synthesis. Here, an autonomous ML-driven, oscillatory MF platform for the synthesis of NPs is reported. The platform utilized multiple recipes and reaction times for the synthesis of NPs with different dimensions, conducted spectroscopic NP characterization, and employed ML approaches to analyze multiple yet prioritized spectroscopic NP characteristics, and identified reaction conditions for the synthesis of NPs with targeted optical properties. The platform is also used to develop an understanding of the relationship between reaction conditions and NP properties. This study shows the strong potential of ML-driven oscillatory MF platforms in materials science and paves the way for automated NP development.

Advanced wound dressings improve wound healing by releasing antibacterial agents, accelerating wound closure, and reporting (sensing) changes in the wound’s state. The challenge with the release of antibacterial agents such as drugs, peptides, or nanoparticles is their unregulated administration. In addition, bacteria resistance to antibiotics stimulates the search for new types of antibacterial wound dressings. Here, we report a new approach to antibacterial wound dressings by utilizing a nanocolloidal hydrogel with strong Fe3+ ion sequestration capability, thus depriving bacteria of much-needed ionic iron and suppressing bacteria growth. The hydrogel was derived from cellulose nanocrystals decorated with carbon dots (C-dot/CNCs). Upon Fe3+ ion uptake by the nanofibrillar hydrogel, the photoluminescence of the hydrogel was quenched, due to adsorption of ions to the C-dot surface, thus reporting on the removal of ionic iron from the medium. The hydrogel suppressed the growth of antibiotic-resistant Gram-negative Escherichia coli, antibiotic-resistant Pseudomonas aeruginosa, and Gram-positive Staphylococcus aureus and was noncytotoxic for human fibroblasts. Wound dressings were readily fabricated using three-dimensional (3D) printing. The new mechanism of antibacterial performance of the hydrogel, its sensing capability, biocompatibility, and the capability to 3D print wound dressing patches make it a very promising material for the fabrication of advanced wound dressings.

Learning from the locomotion of natural organisms is one of the most effective strategies for designing microrobots. However, the development of bioinspired microrobots is still challenging because of technical bottlenecks such as design and seamless integration of high-performance actuation mechanism and high-density energy source for untethered locomotion. Directly harnessing the activation energy and intelligence of living tissues in synthetic micromachines provides an alternative route to developing biohybrid microrobots. Here, we propose an approach to engineering the genetic and nervous systems of a nematode worm, Caenorhabditis elegans, and creating an untethered, highly controllable living soft microrobot (called “RoboWorm”). A living worm is engineered through optogenetic and biochemical methods to shut down the signal transmissions between its neuronal and muscular systems while its muscle cells still remain optically excitable. Through dynamic modeling and experimental verification of the worm crawling, we found that the phase difference between the worm body curvature and the muscular activation pattern generates the thrust force for crawling locomotion. By reproducing the phase difference via optogenetic excitation of the worm body muscles, we emulated the major worm crawling behaviors in a controllable manner. Furthermore, with real-time visual feedback of the worm crawling, we realized closed-loop regulation of the movement direction and destination of single worms. This technology may facilitate scientific studies on the biophysics and neural basis of crawling locomotion of C. elegans and other nematode species.

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An integrated microfluidic flow-focusing platform for on-chip fabrication and filtration of cell-laden microgels.