Collagen-based scaffolds are gaining more prominence in the field of tissue engineering. However, readily available collagen scaffolds either lack the rigid structure (hydrogels) and/or the organization (biopapers) seen in many organ tissues, such as the cornea and meniscus. Direct-write electrospinning is a promising potential additive manufacturing technique for constructing highly ordered fibrous scaffolds for tissue engineering and foundational studies in cellular behavior, but requires specific process parameters (voltage, relative humidity, solvent) in order to produce organized structures depending on the polymer chosen. To date, no work has been done to optimize direct-write electrospinning parameters for use with pure collagen. In this work, a custom electrospinning 3D printer was constructed to derive optimal direct write electrospinning parameters (voltage, relative humidity and acetic acid concentrations) for pure collagen. A LabVIEW program was built to automate control of the print stage. Relative humidity and electrospinning current were monitored in real-time to determine the impact on fiber morphology. Fiber orientation was analyzed via a newly defined parameter (spin quality ratio (SQR)). Finally, tensile tests were performed on electrospun fibrous mats as a proof of concept.
Ophthalmic brachytherapy dose calculations were performed as an independent verification of commercial dosimetry software (BEBIG Plaque Simulator). Excel spreadsheets were constructed to follow the formalism of the AAPM Task Group No. 43. As a software commissioning tool, TG43 seed-based coordinates were reformatted to be compatible with plaque-based BEBIG dose tables for centrally positioned seeds. Plaque central axis doses were also calculated for rings of seeds. Close agreement with BEBIG doses was obtained in both cases. Tailored spreadsheet versions were subsequently created to verify patient treatment plans. Treatment time and dose to a specified central-axis point are calculated for ROPES plaques fully loaded with 1-125 model 6702 seeds.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.