In vitro characterization of polycaprolactone matrices generated in aqueous media

In this study, a novel process of dissolving polycaprolactone (PCL) matrices in glacial acetic acid was explored in which matrices spontaneously formed upon contact with water. Scanning electron microscopy analysis showed rough architecture and holes on the self-assembled matrix relative to matrices formed after dissolving in chloroform. Immersion in the gelatin solution reduced its roughness and number of micropores. Atomic force microscopy (AFM) analysis confirmed the increased roughness of the self-assembled matrices. The roughness of the matrices decreased after incubation in 1N NaOH for 10 min. AFM analysis also revealed that the self-assembled matrix had a net positive surface charge, whereas chloroform-cast matrix had a negative surface charge. The surface charge of self-assembled matrix after immersion in gelatin changed to negative. However, incubation in NaOH did not affect the surface charge. The tensile properties were tested in both the dry state (25 degrees Celsius) and the wet state (37 degrees Celsius) by immersion in phosphate-buffered saline. Self-assembled matrix had lower elastic modulus, break stress and break strain than chloroform-cast matrix in both states. The elastic modulus in the wet condition was reduced by half in self-assembled matrix but tensile strain increased. Samples were further analyzed by ramp-hold test for assessing stress relaxation behavior. Both self-assembled and chloroform-cast matrices had similar trends in stress relaxation behavior. However, stress accumulation in self-assembled matrix was half that of chloroform-cast matrix. In vitro cell cultures were conducted using human foreskin fibroblast (HFF-1) in serum-free medium. Cytoskeletal actin staining showed cell adhesion and spreading on all matrices. Cell retention was significantly increased in self-assembled matrix compared to chloroform-cast matrix. Addition of gelatin improved the retention of seeded cells on the surface. In summary, PCL matrices generated using this novel technique show significant promise in biomedical applications.