Modeling and optimization of poly(lactic acid)/poly(ℇ-caprolactone)/Nigella sativa extract nanofibers production for skin wounds healing by artificial neural network and response surface methodology models.

Electrospun fibrous scaffolds have great potential for the effective treatment of wounds. Novel blend scaffolds were fabricated from poly(ℇ- caprolactone) (PCL)/poly (lactic acid) (PLA) with Nigella sativa (NS) extract in different concentrations of 10 %, 15 %, 20 %, and 25 % by one nozzle electrospinning. RSM and ANN models were used to determine optimal nanofiber. The results showed that the ANN model had average goodness values of almost 1.992 which was higher than the RSM model with an amount of 1.823. The best sample was determined with the combination of parameters such as PLA/PCL (70:29) concentration, voltage 17 kV, and flow rate 0.2 ml/h in diameter of nanofiber 410 nm by Genetic Algorithm (GA) model with cost value 0.0216 that was lower than cost value (0.0927) of ANN model. The effect of NS extract on nanofibers properties showed that loading high concentrations of NS extract in PLA/PCL polymer solutions caused a decrease in nanofibers diameter, hydrophilicity, and tensile strength. Overall, PLA/PCL/NS 25 % nanofiber was selected as an optimal web with an average diameter of 370 ± 68 nm with a young modulus 5.94 MPa. This scaffold also exhibited the highest antibacterial activity, cell attachment, and cell viability based on the MTT assay.