PBD is an experimental design method used to screen a small number of important variables from multiple factors. Herewith, it was employed to screen the key factors of the PEF process for taxanes extraction. In this study, seven parameters (A: electric field strength, B: number of extractions, C: solid–liquid ratio, D: pulse number, E: centrifugal speed, F: flow rate, G: particle size) were selected as independent variables for further optimization. The factors and results of PBD assay are shown in Table 1. The ANOVA and regression analysis of PBD for prediction of significant extraction variables are presented in Table S1 from Supplementary Materials. According to ANOVA analysis (Table S1), this model does well in matching with the experimental results. Importantly, we can conclude that electric field strength (A), followed by pulse number (D) and particle size (G), are the key factors that affect taxanes extraction efficacy using PEF technology.

Based on the PBD results, BBD was employed for further optimization to maximize the TEF yield (Y, the response value) by using electric field strength (X₁), number of pulses (X₂), and particle size (X₃) as independent variables. The number of extractions, solid–liquid ratio, centrifugal speed, and flow rate were set as 1, 1:60, 8000 r/min, and 7 mL/min, respectively. The detailed experimental results of BBD assay are shown in Table 2, including the independent variables and predicted and actual values of TEF. The multiple quadratic regression equation is as shown below:(1)Y=653.56+86.28X1+47.53X2+27.11X3−37.42X1X2+6.65X1X3−52.48X2X3−81.71X12−52.60X22−75.16X32 where X₁, X₂, and X₃ denote the variables (coded) for the electric field strength (X₁), number of pulses (X₂), and particle size (X₃), respectively, and Y is the TEF.

Based on above data, RSM model was built, and ANOVA was employed to evaluate the accuracy of the model. ANOVA for RSM is shown in Table S2 from Supplementary Materials. As shown in Table S2, it is evident that the RSM model could do well in predicting the optimum experimental conditions. Based on this, we further evaluated the interactive effects of three experimental factors on TEF extraction process.

As shown in Figure 3, the results reveal that the mutual effect of pulse number (X₂) and particle size (X₃) is the strongest, while the mutual effect of electric field strength (X₁) and particle size (X₃) is the weakest. With an increase in the pulse number (X₂) and particle size (X₃), the extraction yield increased first and then reduced, which was in accordance with the single-factor results. Based on the multiple quadratic regression equation, we calculated the optimal experimental conditions of electric field strength, pulse number, and particle size, with the values of 17.419 kV/cm, 8.435, and 165.041 meshes, respectively. Under these conditions, we performed the taxanes extraction assay to evaluate the reliability of the RSM model. As shown in Table 3, the prediction and experimental values of the taxanes yields were 681.282 and 658.15 μg/g, respectively, and p value was 0.269. All data highlight that the RSM model is feasible for parameters optimization during taxanes extraction process.

Owing to the advantages of low cost, timeliness, and high accuracy, ANN models are widely used in nonlinear system prediction [21]. BP, the most popular ANN model, was employed to model the taxanes contents. This network was constructed according to the RSM experimental and virtual data (Table S3). The virtual samples, the performance of the ANN model and regression plot of the ANN model are shown in Table S3, Figures S1 and S2 from Supplementary Materials, respectively. For the simulation results of the BP model, we observed that the mean squared error was lower than 0.01 (Figure S1) and the correlation coefficient was higher than 0.99 (Figure S2), which indicates that the trained ANN model has a superior predictive ability.

Furthermore, we adopted the GA method to fit and optimize the BP model. As shown in Figure 4, the fitness value changed with the increase in generations. The linear weighted sum of each sub-objective became invariable after 44 generations, and the population gradually converged. To summarize, the above results suggest that we successfully constructed and optimized the GA-BP model for parameters optimization of taxanes extraction. Based on the optimum conditions predicted by this model, we also carried out the assay to compare the difference between prediction and experimental results, with the values of 703.0565 and 672.13 μg/g, respectively (Table 3).

In the present study, compared with the RSM model, the GA-BP model exhibited a better prediction performance (Table S4), which is in line with other scholars [10,24,30]. Evaluation of the predictive capacities of RSM and GA-BP modeling systems are shown in Table S4 from Supplementary Materials. Under the recommended conditions of RSM and GA-BP, the experimental TEFs were 658.15 ± 31.26 and 672.13 ± 32.45 μg/g, respectively. In addition, as shown in Table 3, it is evident that the prediction and optimization capabilities of RSM are not as good as those of GA-BP. We herein speculate that the higher TEF under the recommended process parameters of GA-BP may be attributed to the lower electric field strength as well as pulse number.

Until now, taxanes have been mainly extracted from Taxus needles via solid–liquid extraction method, ultrasonic extraction method, etc. [7]. To determine the difference in extraction efficacy between PEF technology and the conventional methods, we compared the yields of taxanes in different treatment groups, including the control group, the SL group, and the US group. All groups adopted the same solvents and solid–liquid ratio. As shown in Table 4, it was apparent that the yields of 10-DAB III, baccatine III, 10-DAT, cephalomannine, paclitaxel, and TEF by PEF treatment were 1.02–1.66, 1.24–2.80, 1.09–1.78, 1.24–2.20, 1.06–1.98, and 1.07–1.84 folds those of control, SL and US treatment, which indicates the extraction yields of PEF treatment were much higher than conventional treatments. Compared with the control group, SL group treated the samples with a higher temperature and more extractions, thereby leading to the increase in taxanes yields. However, the process of this method inevitably utilizes a large amount of organic solvent and takes a long time, which may cause the degradation and coagulation of active ingredients [46]. The yields of TEF in US group was significantly enhanced; however, there are some drawbacks for US treatment, such as the fact that prolonged ultrasonic treatment and its related thermal effect may destroy the functional structure of target compounds and accelerate the volatilization of the solvents. In the present study, we highlight the potential application value of PEF technology as a promising method for taxanes extraction, which exhibits a higher extraction efficacy and shorter time compared with the conventional methods. As the extraction solvent composed of dichloromethane and ethanol (1:1 v/v) used in this experiment is not a green reagent, we therefore emphasize here that the further optimization direction is to replace the organic solvents with clean, non-toxic, green, and highly specific extractants and use them in conjunction with PEF technology to maximize extraction yields. Furthermore, considering that the extraction rate is closely associated with the microstructure changes of particles, and in order to further verify the above results and visually compare the differences among every group, we performed SEM assays to observe the surface morphology of Taxus cuspidate. As shown in Figure 5, the samples of the control group presented a smooth and intact surface, whereas the surface of Taxus cuspidata in other treated groups, especially in PEF treated group, were rough with a few irregularly shaped cavities, which enlarge the surface area of particles and reduce the mass transfer resistance due to the irreversible electroporation process [14]. Collectively, these results all support the potential usage of PEF for taxanes extraction.

The annual stems and leaves of Taxus cuspidata collected from Changbai Mountain (Jilin, China) were washed and dried at 40 °C to constant weights. Then, the samples were crushed and sealed for storage in a dry environment.

Dichloromethane and ethanol (both analytical-grade) were purchased from Damao Chemical Reagent Factory (Tianjin, China). Acetonitrile and methanol (both chromatographic grade) were provided by Thermo Fisher Scientific (Rockville, MD, USA). Purified water was produced by Hangzhou Wahaha Company (Hangzhou, China). Paclitaxel, 10-deacetylbaccatin III (10-DAB III), baccatine III, cephalomannine, and 10-deacetyltaxol (10-DAT) with purity >98% were bought from Shanghai Yuanye Bio-Technology Co., Ltd. (Shanghai, China).

The PEF extraction system used here involves a high-voltage pulse generator, an oscilloscope, a coaxial liquid material processing chamber, and a pump [12].

The generator was formed by two 1.5-mm-long stainless steel electrodes. The chamber diameter was set as 0.1 cm for processing samples. The bidirectional triangular pulse wave form with real-time voltage and current were displayed on the oscilloscope. The pulse width, frequency range, peak output voltage, and current were 2 μs, 40–3000 Hz, 10 kV, and 20 A, respectively. The electric field strength and pulse number were changed by adjusting the input voltage and frequency. The calculation formulas are as follows:(2)n=πr2lf/103v (3)E=Vpp/2l where n is the pulse number, r is the electrode radius (0.5 mm), l is the distance between electrodes (1.5 mm), f is frequency (Hz), v is flow rate (mL/s), E is the electric field strength (kV/cm), and V_pp is the displayed real-time voltage on the oscillograph (kV).

The PEF extraction assay was performed as described previously with some modifications [12]. Briefly, the dried Taxus cuspidata powder was firstly mixed with the extractant, which was a mixture of ethanol and dichloromethane (1:1, v/v). Then, the parameters, including the pulse number and flow rate of the PEF instrument, were set according to the experimental protocol. The peristaltic pump was switched on, and the treatment liquid consisting of Taxus cuspidata powder and extractant was pumped into the chamber. After the treatment liquid flowed through both electrodes stably and continuously, the voltage switch was turned on and set as required. Under this process, the taxanes were extracted from Taxus cuspidata powder into the extractant. Finally, the products were collected for centrifugation.

After PEF treatment, the suspension of the solution was centrifuged at 8000 r/min for 10 min at 4 °C, and then the dichloromethane-ethanol layer was gathered to evaporate at ≤40 °C until complete drying. After that, the residues were dissolved in methanol, passed through a 0.22 μm filter membrane, and stored in a brown bottle at −20 °C for further analysis.

Content of each type of taxanes in the extracts was quantified using a high-performance liquid chromatograph (HPLC, Waters e2695 Separations Module) according to Fan et al. [7] with some modifications. Taxanes were separated through a C18 reverse-phase column (5 μm 4.6 × 250 mm²). The flow rate, column temperature, and injection volume were set as 1.0 mL/min, 30 °C, and 10 μL, respectively. The mobile phase consisted of water (eluent A) and acetonitrile (eluent B). The gradient elution procedure was set as follows: 40 to 50% B (1–10 min), 50 to 53% B (10–13 min), 53 to 73% B (13–25 min), 73 to 40% B (25–27 min), and 40% B (27–30 min). The detection wavelength was 227 nm. Five main taxanes were identified by matching the spectral characteristics between the samples and standards. The concentrations of paclitaxel, 10-DAB III, baccatine III, cephalomannine and 10-DAT were calculated using the calibration curves. The total content of the five main taxanes (TEF, μg taxanes equivalents/g of Taxus cuspidata) was calculated as follows:(4)TEF=C × V/W where C (μg/mL) is the total content of five main taxanes, V (mL) is the volume of extraction solution recovered, W (g) is the weight of Taxus cuspidata, and TEF (μg/g) represents the extraction rate of taxanes in Taxus cuspidata.

After the optimization of taxanes extraction conditions, three independent experiments were carried out to evaluate the difference between the experimental values and the predicted values, so as to determine the superiority of the prediction model.

To compare the extraction efficacy of TEF and the conventional extraction methods, four treatment groups, including the control group, the SL group, the US group, and the PEF group, were set to extract the taxanes. For the control group, the experiment was performed by using a dichloromethane-ethanol system without PEF treatment. For SL treatment group, 2 g Taxus cuspidata powder was accurately weighed and extracted with 40 mL of dichloromethane-ethanol (1:1, v/v) solution in a reflux device at 40 °C. After 4 h, the suspension was centrifugated to collect the supernatants. The precipitate was extracted twice under the above conditions. Finally, a total of 120 mL suspension was used to determine the taxanes content. For US treatment group, the experiment was conducted as described previously with some modifications [6]. Briefly, 2 g of Taxus cuspidata powder was mixed with 120 mL of extractant and placed in a sonication chamber. The extractant was a 1:1 mixture of dichloromethane and ethanol. The temperature, power, and duration of ultrasonic treatment were set as 40 °C, 200 W, and 1.1 h, respectively.

The microstructures of residues after control, SL, US, and PEF treatments were observed by an XL-30 ESEM-FEG SEM device (FEI Company, Hillsboro, OR, USA). Before observation, all samples were processed as described by Xu et al. [25].

All experiments were conducted three times, and the results were expressed as mean ± standard deviation. Significant differences were set at p < 0.05 by ANOVA, Duncan’s new multiple range test, or t-test using IBM SPSS Statistics 25.0 (IBM, New York, NY, USA).