A nanoengineered bioink loaded with therapeutic proteins is designed to direct cell function in a 3D printed construct. The bioink is developed from a hydrolytically degradable polymer and 2D synthetic nanoparticle. The synthesis of poly(ethylene glycol)‐dithiothreitol (PEGDTT) via a Michael‐like step growth polymerization results in acrylate terminated degradable macromer. The addition of 2D nanosilicates to PEGDTT results in formation of shear‐thinning bioinks with high printability and structural fidelity. The mechanical properties, swelling kinetics, and degradation rate of 3D printed constructs can be modulated by changing the ratio of PEG:PEGDTT and nanosilicates concentration. Due to high surface area and charged characteristic of nanosilicates, protein therapeutics can be sequestered in 3D printing structure for prolong duration. Sustained release of pro‐angiogenic therapeutics from 3D printed structure, promoted rapid migration of human endothelial umbilical vein cell. This approach to design biologically active inks to control and direct cell behavior can be used to engineer 3D complex tissue structure for regenerative medicine.

In article number https://doi.org/10.1002/adhm.201801553 by Charles W. Peak, Akhilesh K. Gaharwar, and co‐workers, a nanoengineered bioink loaded with therapeutic proteins is designed to direct cell function in a 3D printed construct. This approach to design biologically active inks to control and direct cell migration can be used to engineer 3D vascularized tissue structure for regenerative medicine.

At the beginning of the COVID-19 pandemic, many hospitals and healthcare institutions lacked an adequate supply of masks and other personal protective equipment. Moreover, protocols that were in place to ensure healthcare workers had appropriately sized masks consumed precious time and resources. Any determination of a user’s correct respirator size demanded an in-person assessment and had the potential to waste multiple respirators. Here we introduce IBARS (Image-based Application for Respirator Sizing), a novel tool which provides respirator size recommendations based on a facial image and basic user demographics. This solution obviates the need for an in-person assessment, providing an accurate size recommendation within seconds. The application has the potential to reduce time-per-worker respirator fitting, reduce overall respirator usage, and increase safety by providing hospitals with a non-contact option for sizing. Furthermore, future applications may assist healthcare institutions optimize supply chains by providing rapid assessments and re-assessments of appropriate respirator sizes used by their workers. Early testing indicated accuracy of 71.3% for the software (N=16), and further testing is underway at Houston Methodist Hospital.

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