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Electrohydrodynamic (EHD) printing is a micro-nano printing technology based on the principles of electric field and fluid dynamics. It is characterized by high resolution, high precision, and high speed, applied to various materials, including metals, ceramics, and organic materials. Compared with traditional printing technologies, EHD printing offers advantages such as low manufacturing cost, simple process, and direct fabrication, making it highly promising in the field of micro-nano manufacturing. Polyethylene oxide (PEO) is a highly water-soluble polymer that has been widely used in various fields due to its low toxicity and ease of processing. In this study, a finite element simulation model was developed using simulation software to simulate and analyze the mechanisms of focused jetting and deposition of PEO solution under an electric field. Based on the principles of electrohydrodynamics, a self-built EHD printing system was used to investigate the influence of different solution mass fractions and printing parameters on fiber formation, and the optimal process window of EHD printing PEO solution was obtained. Ultimately, ordered deposition of fiber lines ranging from 1.761 to 6.093 [micro]m was achieved. The simulation results were consistent with the experimental results, validating the effectiveness of the established model in guiding jetting outcomes. Highlights * Independently building a low-cost electrohydrodynamic (EHD) printing system. * Finite element simulation of EHD printing process. * Mechanism analysis of PEO solution jetting and deposition. * Optimal process window for PEO solution EHD printing. * Influence of key process parameters on fiber forming width. KEYWORDS cone-jet printing, electrohydrodynamic (EHD) printing, finite element simulation, polyethylene oxide (PEO) solution, 1 | INTRODUCTION The electrohydrodynamic (EHD) printing technology is a novel method for manufacturing micro-nano structures and devices. It offers advantages such as low manufacturing costs, flexible and simple process, [...]

Natural hydrogels are widely employed in tissue engineering and have excellent biodegradability and biocompatibility. Unfortunately, the utilization of such hydrogels in the field of three‐dimensional (3D) printing nasal cartilage is constrained by their subpar mechanical characteristics. In this study, we provide a multicrosslinked network hybrid ink made of photocurable gelatin, hyaluronic acid, and acrylamide (AM). The ink may be processed into intricate 3D hydrogel structures with good biocompatibility and high stiffness properties using 3D printing technology based on digital light processing (DLP), including intricate shapes resembling noses. By varying the AM content, the mechanical behavior and biocompatibility of the hydrogels can be adjusted. In comparison to the gelatin methacryloyl (GelMA)/hyaluronic acid methacryloyl (HAMA) hydrogel, adding AM considerably enhances the hydrogel's mechanical properties while also enhancing printing quality. Meanwhile, the biocompatibility of the multicrosslinked network hydrogels and the development of cartilage were assessed using neonatal Sprague–Dawley (SD) rat chondrocytes (CChons). Cells sown on the hydrogels considerably multiplied after 7 days of culture and kept up the expression of particular proteins. Together, our findings point to GelMA/HAMA/polyacrylamide (PAM) hydrogel as a potential material for nasal cartilage restoration. The photocuring multicrosslinked network ink composed of appropriate proportions of GelMA/HAMA/PAM is very suitable for DLP 3D printing and will play an important role in the construction of nasal cartilage, ear cartilage, articular cartilage, and other tissues and organs in the future. Notably, previous studies have not explored the application of 3D‐printed GelMA/HAMA/PAM hydrogels for nasal cartilage regeneration. [ABSTRACT FROM AUTHOR]

Follow-up policies following treatment are indispensable and effective in reducing the number of complications of chronic diseases, and hence the cost of treating complications, but bring additional follow-up cost inevitably. This paper introduces the virtual age method to measure the effect of follow-up on the patient's risk of developing a complication, and further proposes a mixed integer nonlinear programming model to develop the optimal periodic follow-up policies from a cost perspective. By means of the proposed model, the optimal timing and type of follow-up checkups for heterogeneous patients can be derived, achieving a tradeoff between costs of treating complications and follow-up. A case study of pediatric type 1 diabetes mellitus patients is presented to illustrate the applicability of the proposed method and analyse the impacts of significant input parameters on the optimal model solutions. The findings form the basis to design flexible and effective follow-up policies for monitoring patients with chronic diseases. [ABSTRACT FROM AUTHOR]