ABSTRACT
Here, an artificial intelligence (AI)-based approach was employed to optimize the production of electrospun scaffolds for in vivo wound healing applications. By combining polycaprolactone (PCL) and poly(ethylene glycol) (PEG) in various concentration ratios, dissolved in chloroform (CHCl3) and dimethylformamide (DMF), 125 different polymer combinations were created. From these polymer combinations, electrospun nanofiber meshes were produced and characterized structurally and mechanically via microscopic techniques, including chemical composition and fiber diameter determination. Subsequently, these data were used to train a neural network, creating an AI model to predict the optimal scaffold production solution. Guided by the predictions and experimental outcomes of the AI model, the most promising scaffold for further in vitro analyses was identified. Moreover, we enriched this selected polymer combination by incorporating antibiotics, aiming to develop electrospun nanofiber scaffolds tailored for in vivo wound healing applications. Our study underscores three noteworthy conclusions: (i) the application of AI is pivotal in the fields of material and biomedical sciences, (ii) our methodology provides an effective blueprint for the initial screening of biomedical materials, and (iii) electrospun PCL/PEG antibiotic-bearing scaffolds exhibit outstanding results in promoting neoangiogenesis and facilitating in vivo wound treatment.
ABSTRACT
Fibrin hydrogels have proven highly suitable scaffold materials for skeletal muscle tissue engineering in the past. Certain parameters of those types of scaffolds, however, greatly affect cellular mechanobiology and therefore the myogenic outcome. The aim of this study was to identify the influence of apparent elastic properties of fibrin scaffolds in 2D and 3D on myoblasts and evaluate if those effects differ between murine and human cells. Therefore, myoblasts were cultured on fibrin-coated multiwell plates ("2D") or embedded in fibrin hydrogels ("3D") with different elastic moduli. Firstly, we established an almost linear correlation between hydrogels' fibrinogen concentrations and apparent elastic moduli in the range of 7.5 mg/ml to 30 mg/ml fibrinogen (corresponds to a range of 7.7-30.9 kPa). The effects of fibrin hydrogel elastic modulus on myoblast proliferation changed depending on culture type (2D vs 3D) with an inhibitory effect at higher fibrinogen concentrations in 3D gels and vice versa in 2D. The opposite effect was evident in differentiating myoblasts as shown by gene expression analysis of myogenesis marker genes and altered myotube morphology. Furthermore, culture in a 3D environment slowed down proliferation compared to 2D, with a significantly more pronounced effect on human myoblasts. Differentiation potential was also substantially impaired upon incorporation into 3D gels in human, but not in murine, myoblasts. With this study, we gained further insight in the influence of apparent elastic modulus and culture type on cellular behavior and myogenic outcome of skeletal muscle tissue engineering approaches. Furthermore, the results highlight the need to adapt parameters of 3D culture setups established for murine cells when applied to human cells.