Antioxidant, anti-lipidemic, hypoglycemic and antiproliferative effects of phenolics from Cortex Mori Radicis

Chao Li; Yao Peng; Wei Tang; Teng Li; Mansour K. Gatasheh; Rabab Ahmed Rasheed; Junning Fu; Juping He; Wei-dong Wang; Yingbin Shen; Yichao Yang; Yongsheng Chen; Arshad Mehmood Abbasi

doi:10.1016/j.arabjc.2022.103824

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Original article

06 2022

:15;

103824

doi:

10.1016/j.arabjc.2022.103824

Antioxidant, anti-lipidemic, hypoglycemic and antiproliferative effects of phenolics from Cortex Mori Radicis

Chao Li^{^a,1}, Yao Peng^{^b,1}, Wei Tang^{^a}, Teng Li^{^a}, Mansour K. Gatasheh^{^c}, Rabab Ahmed Rasheed^{^d}, Junning Fu^{^e}, Juping He^{^a}, Wei-dong Wang^{^a}, Yingbin Shen^{^b}, Yichao Yang^{^f}, Yongsheng Chen^{^e,⁎}, Arshad Mehmood Abbasi^{^g,^h,⁎}

a College of Food and Bioengineering, Xuzhou University of Technology, Xuzhou, Jiangsu, 221018, China

b School of Life Sciences, Guangzhou University, Guangzhou 510006, China

c Department of Biochemistry, College of Science, King Saud University, Riyadh 11451, Saudi Arabia

d Histology & Cell Biology Department, Faculty of Medicine, King Salman International University, South Sinai, Egypt

e Department of Food Science and Engineering, Jinan University, Guangzhou 510632, China

f School of Public Health, Guangzhou Medical University, Guangzhou 511436, China

g Department of Environmental Sciences, COMSATS University Islamabad, Abbattabad Campus 22060, Pakistan

h University of Gastronomic Sciences, Piazza Vittorio Emanuele II, 9, 12042 Pollenzo, Italy

⁎Corresponding authors at: Department of Environmental Sciences, COMSATS University Islamabad, Abbattabad Campus 22060, Pakistan (A.M. Abbasi). chysh11@126.com (Yongsheng Chen), amabbasi@cuiatd.edu.pk (Arshad Mehmood Abbasi)

Received: 2021-12-27, Accepted: 2022-2-24,

Disclaimer:
This article was originally published by Elsevier and was migrated to Scientific Scholar after the change of Publisher.

1 These authors contributed equally to this work.

Abstract

Cortex Mori Radicis (CMR) is enriched in various phenolics, this study aimed to estimate the antioxidant effect, enzyme (lipase, α-amylase, α-glucosidase and acetyl-cholinesterase) inhibition and the anti-proliferative effect of the phenolic compounds in CMR. However, the amount of these compounds obtained from CMR is highly dependent on the processing conditions. In this study, the processing parameters of extracting the phenolics from CMR using ultrasonic technique pooled with high-speed shearing extraction (UTPHSE) were optimized. Subsequently, the phenolics from Cortex Mori Radicis (PCMR) were purified using AB-8 macroporous resin, and their chemical analysis, antioxidant, enzyme inhibition, and antiproliferative activities were studied. Based on our findings, the optimal parameters of UTPHSE were: L/S ratio 25.8:1 (mL/g), voltage 81.0 V, ultrasonic temperature 51.8 ℃ and ultrasonic time 289 s. And under the optimal extraction conditions, the extraction rate of the PCMR was 0.531 ± 0.004%. Compared with PCMR, the contents of “total phenolics, flavonoids, flavonols, flavanols and phenolic acids” increased 2.30, 2.67, 2.59, 3.63 and 2.72 times in the purified phenolics from Cortex Mori Radicis (PPCMR), respectively. In addition, PPCMR depicted significant DPPH, ABTS⁺ and superoxide anion radicals’ scavenging capability, reducing power, ferric ion reducing antioxidant power (FRAP) and remarkable inhibitory activities on “lipase, alpha-amylase, alpha-glucosidase, and the proliferation of HeLa, HepG2 and NCI-H460”. At the same time, the morphological changes of HeLa, HepG2 and NCI-H460 cells suggested that PPCMR could effectively inhibit the proliferation of tumor cells in vitro. Therefore, PPCMR have good potential as natural antioxidants, antilipidemic, hypoglycemic, and antineoplastic agents in functional foods and pharmaceuticals.

Keywords

Cortex Mori Radicis

Phenolics

Ultrasonic

Antioxidant effect

Enzyme inhibitory effect

Antiproliferative effect

1 Introduction

The white mulberry “Morus alba L.”, the black mulberry “M. nigra L.” and the red mulberry “M. rubra L.” are three common species of the genus Morus, family Moraceae (Ercisli and Orhan, 2006). Among these, M. alba is native to northern China and widely cultivated in Europe, North America, South America and Africa (Imran et al., 2010; Paola et al., 2009). According to the Chinese pharmacopoeia, fruits, leaves and root bark of M. alba have been used as traditional Chinese medicines for thousands of years. Most of the previous studies were focused on food and medicinal applications of the leaves and fruits of M. alba. Specifically, its leaves have been widely reported for making tea or as food for silkworms to produce yarn (Hisato et al., 2008), and use of fruits in making health drinks in east Asian countries (Huang et al., 2020). The root bark of M. alba is also known as Cortex Mori Radicis (CMR), is a rich source of phenolics (Čulenová et al., 2020), flavonoids (Zheng et al., 2010), coumarins (Syah et al., 2004), triterpenoids (Ferrari et al., 2000) and alkaloids (Asano et al., 2001). As a traditional herbal medicine, CMR has been commonly used in China as anti-asthmatic, to reduce blood pressure and to treat cardiovascular diseases and diabetes (Kim et al., 2011; Shibata et al., 2007; Yang et al., 2010 ).

Phenolics possess significant antioxidant, enzyme inhibitory and antitumor activities (Hu et al., 2020; Wu et al., 2020). Deghima et al. demonstrated that various antioxidant activities (antiradical, iron-chelating ability, reducing power and lipid peroxidation) of the root extract of Ranunculus macrophyllus were highly related to the contents of polyphenolics (Deghima et al., 2020). Likewise, polyphenols from young apple, tomato and lotus seed extracts depicted significant potential in α-glucosidase and acetylcholinesterase inhibition and anti-proliferative activities against HepG2 cell (Blaszczak et al., 2020; Tian et al., 2020; Yan et al., 2019 ). These findings revealed that phenolics have a variety of biological activities. Dipayan Sarkar and Kalidas Shetty 2014 found that human body cannot synthesize the phenolics, and often obtained from natural resources such as fruit, vegetables, medicinal plants and grains, etc. (Zou et al., 2017). Therefore, an efficient extraction method of phenolics plays an important role in their biological activity value. High-speed shearing extraction (HSE), is a highly efficient, environmentally friendly and energy saving novel technology for extracting active ingredients from plants (Song et al., 2019; Zhong et al., 2019). The principle of HSE is to use the high-speed rotating rotor in a solution to produce cavitation, mechanical and shear effects to rapidly dissolve the substances in plant cells to achieve balance.

Ultrasonic-assisted extraction process is the synergistic effect of cavitation, mechanical and thermal effects (Liu and Yang, 2018). The high intensity of the ultrasonic wave in the solvent causes pressure fluctuations, and the instantaneous generation of many vacuum cavitation bubbles (Rao and Rathod, 2015). These bubbles suddenly implode within a few milliseconds, accompanied by local temperature and pressure rise, which is conducive to the solvent penetration in plant cells and to improve the extraction effect (Teh and Birch, 2014). The above two methods have been widely used to extract active ingredients such as polyphenol (Guo et al., 2017), flavonoids (Cheng et al., 2016; Garcia-Castello et al., 2015), and polysaccharides (Lin et al., 2018). Yet, there is limited data about the extraction of phenols from “CMR” using “ultrasonic technology combined with high-speed shear extraction (utphse)”. Ultrasonic power installed to 250 W. Therefore, the objectives of this study were to: (a) to optimize the UTPHSE of the phenolics from CMR, (b) to purify the phenolics using AB-8 macroporous resin, (c) to study the composition of the purified phenolics from Cortex Mori Radicis (PPCMR) and their biological activities in vitro including antioxidant, enzyme inhibitory “lipase, alpha-amylase, alpha-glucosidase and acetylcholinesterase”, and anti-proliferative activities against various cancer cells’ lines.

2 Materials and methods

2.1

2.1 Sampling

CMR was purchased from Limin Herbal Pieces Co., Ltd. (Chengdu, Sichuan, China). After proper taxonomic recognition, specimen were submitted in the herbarium of Xuzhou University of Technology, under voucher number No. 20180322–1.CMR is dried at 60 °C in a GZX-9070MBE oven (Boxun, Shanghai, China), then uniformly ground to a fine powder using a WKX-160 mill (QingzhouJingcheng, Shandong, China), sieved through a 60 mesh sieve and stored at −20 °C.

2.2

2.2 Chemicals and reagents

Gallic acid (≥98%), rutin (≥98%), catechin (≥98%), caffeic acid (≥98%), ascorbic acid, 2,2-diphenyl-1-picrylhydrazyl (DPPH, D9132, ≥98.0%), porcine pancreatic lipase (Type II, EC 3.1.1.3; L3126), porcine pancreatic α-amylase (Type VI-B, EC 3.2.1.1, A3176), saccharomyces cerevisiae α-glucosidase (EC 3.2.1.20, G3651), electrophorus electricus’s acetyl-cholinesterase (electric eel) (Type VI-S, EC 3.1.1.7, C3389) and 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT, M5655, ≥97.5%) were acquired from Sigma-Aldrich Co., Ltd. (St. Louis, MO, USA). Cervical cancer cell line HeLa, liver tumor cell line HepG2, and lung carcinoma cell line NCI-H460 were acquired from the Cell Bank of the Committee for Typical Culture Conservation of the Chinese Academy of Sciences. Trypsin-EDTA solution and 5-Fluorouracil (5-FU, F6627, ≥99%) were acquired from Beyotime Biotechnology Co. Ltd. (Shanghai, China). All chemicals were of analytical grade and acquired from Sinopharm Chemical Reagent Co., Ltd. (Shanghai, China), while Anhui Sanxing Resin Technology Co., Ltd. (Bengbu, Anhui, China) supplied the macroporous resin AB-8.

2.3

2.3 Preparation of PPCMR

2.3.1

2.3.1 Extraction

A sample powder of 30 g was accurately weighed, transferred into the extraction vessel (2.0 L) and immersed in 70% ethanol (v/v). The cutter head of high speeds shearing machine (ZHBE-50, Zhijing, Zhengzhou, Henan, China), was put into the extraction container, and the extraction container was put into the ultrasonic cleaning machine (SB-5200DTN, Xinzhi, Ningbo, Zhengjiang, China). After the high-speed shearing machine was turned on, the voltage began to gradually increase. When the voltage reached the preset voltage, the ultrasonic cleaner was turned on, and the ultrasonic power was set to 250 W and the extraction time was counted. After finishing the extraction process, the crude extracts were collected, filtered, concentrated and lyophilized for the further purification.

2.3.2

2.3.2 Purification

2 g of crude extract was mixed in deionized water (500 mL), and pH was adjusted to 4.6 using hydrochloric acid (1 M) for the dynamic adsorption test. The samples were loaded into a column filled with AB-8 macroporous resin (2.6 cm × 60 cm) and a bed volume (BV) of 320 mL at 1BV/h flow-rate and subjected to dynamic desorption experiments. Elution was done using distilled water until the solution becomes colorless, the final cleaning was then performed with 3.5 BV ethanol (70%) at a flow rate of 0.5 BV/hour. Afterwards, the colorless eluate was concentrated and lyophilized to analyze its chemical properties and in vitro biological activities.

2.4

2.4 Determination of extraction rate

Extraction rate of the total phenolics was determined using the equation:

(1)

E x t r a c t i o n r a t e (%) = \frac{W_{e}}{W_{t}} \times 100

where: W_e symbolizes the amount of gallic acid equivalents recovered from the solution and W_t represents the amount of CMR.

2.5

2.5 Optimization

We examined the effects of ethanol volume fraction, liquid–solid ratio, voltage, ultrasonic temperature and time. The four-factor, three-level Box-Behnken experiment was used to estimate ideal extraction conditions of UTPHSE by selecting four significant factors, namely, liquid–solid ratio (x₁, 20–30 mL/g), voltage (x₂, 70–90 V), ultrasound temperature (x₃, 40–60 °C), and ultrasound time (x₄, 240–320 mL/g), based on the previous one-factor experiments. Design-Expert V 8.0.6 Trial software was used to evaluate the trial data State-Ease, Inc., Minneapolis MN, USA. Response surface analysis is based on the Eq. (2) using a generalized second-order polynomial model:

(2)

E x t r a c t i o n r a t e (%) = β_{0} + \sum_{i = 1}^{4} β_{i} x_{i} + \sum_{i = 1}^{4} β_{ii} {x_{i}}^{2} + \sum_{i = 1}^{3} \sum_{j = i + 1}^{4} β_{ij} x_{i} x_{j}

where: β₀ represent constant coefficient; β_i, β_ij and β_ii demonstrating the coefficient’s regression for linear, interaction and quadratic terms; x_i and x_j are the actual values of independent variables.

2.6

2.6 Phytochemical analysis

The total phenolics was estimated using the modified as described previously (Xiang et al., 2019). Gallic acid was used for the calibration, and the final value were reported as mg GAE/g.

The total flavonoids was determined based on Benabderrahim et al. (Benabderrahim et al., 2019). Rutin was used for the calibration, and the final value were reported as mg RE/g.

The total flavonols was estimated using the modified method as described previously (Oyedeji-Amusa and Ashafa, 2019). Rutin was used for the calibration, and the final value were reported as mg RE/g.

The total flavanols content was enumerated based on Jiao et al. (Jiao et al., 2018). Catechols was used for the calibration, and the total flavonoids content was presented as mg CE/g.

The total phenolic acids’ content was enumerated following previously described method of Timur Hakan Barak et al. (Barak et al., 2019). Caffeic acid was used for the calibration, and the final values were presented as mg CAE/g.

2.7

2.7 Antioxidant assays

2.7.1

2.7.1 DPPH radical scavenging assay

The DPPH inhibition potential of PPCMR was determined using the previously described the method (Zdunić et al., 2020). Precisely, various concentrations of PPCMR (50 µL) and 150 µL of DPPH (0.15 mM) were mixed in 96 well plates, and kept for 60 min (in dark) at 37 °C. The absorbance was measured with a microplate reader (Synergy H1, Bio-Tek. Winooski, VT, USA) at 517 nm. Positive control was ascorbic acid and DPPH scavenging activity was intended using the formula (3):

(3)

s c a v e n g i n g a c t i v i t y (%) = (1 - \frac{A_{s}}{A_{c}}) \times 100

where: A_s represents sample absorbance, A_c indicates absorbance of blank

2.7.2

2.7.2 ABTS⁺ scavenging assay

The inhibition potential of PPCMR towards ABTS radical was estimated by previously modified (Cătunescu et al., 2018). First, ABTS + radicals were prepared by mixing 5 mL of 7 mM ABTS solution with 88 μL of 140 mM potassium persulfate solution. Then, it was incubated for 12–16 h at its absorbance was adjusted to 0.85 ± 0.02 at 734 nm. Different concentrations of PPCMR (40 μL each) and ABTS radical solution (160 μL) were mixed in a 96-well plate, and kept in the dark at 37 °C for 60 min. The absorbance was then measured at 734 nm using a microplate reader. Final values were calculated by the formula (3), while ascorbic acid was the positive control:

2.7.3

2.7.3 Scavenging activity of superoxide anion

The superoxide anion radical scavenging potential of PPCMR was estimated by previously modified (Lei et al., 2019). Shortly, 20 μL of different concentrations of PPCMR and 100 μL of 50 mM Tris-HCl buffer (pH 8.20) were mixed in well plates and kept in the dark for 20 min at 37 °C. Afterwards, 8 μL of 3 mM pyrogallol (in 10 mM HCl) was injected into each well plate and kept in the dark at 37 °C for 5 min. Afterwards, 32 μL of 1 M hydrochloric acid was mixed to stop the process, and the absorbance was measured at 320 nm using a microplate reader. The final values were calculated using the Eq. (4), while ascorbic acid was the positive control:

(4)

s c a v e n g i n g a c t i v i t y (%) = (1 - \frac{A_{s} - A_{s b}}{A_{c}}) \times 100

where: A_s is the absorbance of sample group, A_sb is sample background group absorbance, and A_c represents absorbance of the blank control.

2.7.4

2.7.4 Reducing power assay

Ferric ion reduction capacity PPCMR, was evaluated by the previously described colorimetric method (Gali and Bedjou, 2018). Precisely, different concentrations of PPCMR (10 µL each), 25 μL phosphate buffer (0.2 M, pH 6.6, PBS), and 1% w/v potassium ferricyanide (25 μL) were mixed in well plates. The reaction was then stopped by adding 25 μL of trichloro-acetic acid (10% w/v) and incubated for 20 min at 37 °C. After centrifugation, 85 μL of distilled water and 17 μL of ferric chloride (0.1% w/v) were added to the supernatant, and the absorbance was measured at 700 nm using a microplate reader. The final values were calculated using the equation (5), while ascorbic acid was the positive control:

(5)

A_{r p} = A_{s} - A_{c}

where: A_rp is the reducing power, A_s and A_c indicate absorbance sample and control groups.

2.7.5

2.7.5 Ferric ion reducing antioxidant power (FRAP) assay

Reduction of ferric ion by PPCMR was anticipated using the method of Alves et al. (Alves et al., 2019). First, FRAP reagent was prepared by mixing 10 mM TPTZ (2,4,6-tripyridyl-s-triazine) with 40 mM HCl, ferric chloride (20 mM) and 0.3 M Macerate buffer (pH 3.6) at a ratio of 1:1:10, respectively. The 96-well plates were added with 185 μL of FRAP reagent and 15 μL of different concentrations of PPCMR, and incubated for 10 min in the dark at room temperature. The absorbance was measured at 593 nm using a microplate reader. FRAP(A_frap) values were calculated using the Eq. (5), while ascorbic acid was the positive control.

2.8

2.8 Enzyme inhibition assays

2.8.1

2.8.1 Inhibition of lipase

The inhibition potential of PPCMR for active lipase was estimated using a modified method previously reported (Marilena et al., 2019). Concisely, different concentrations of 50 μL of PPCMR were mixed with an equal volume of 1.2 U/m lipase solution in 0.1 M PBS (pH 8.0) in well plates, and incubated in the dark for 10 min at 37 °C. Afterwards, 100 μL of p-nitrophenyl palmitate (0.2 mM, PBS) was added and kept in the dark again under the same conditions. The absorbance was measured at 405 nm using a microplate reader (Synergy H1, Bio-Tek. Winooski, VT, USA). The inhibition rate of lipase was estimated using the equation (6) with orlistat as a positive control:

(6)

L i p a s e i n h i b i t i o n r a t e (%) = (1- \frac{A_{s} - A_{s b}}{A_{n} - A_{n b}}) \times 100

where: A_s is the absorbance of sample, A_sb is the absorbance of sample background group, A_n indicates absorbance of negative control, and A_nb is the absorbance of negative background control group.

2.8.2

2.8.2 Alpha-amylase inhibitory assay

The inhibition potential of PPCMR against α-amylase activities was determined by previously modified (Yuan et al., 2018). Briefly, 700 μL of different concentrations of PPCMR was mixed with 600 μL of soluble starch in a test tube and incubated in the dark for 5 min, then 200 μL of 20 U/ml α-amylase solution and 1% (m) 500 μL of dinitrosalicylic acid were added and incubated in the dark at 100 °C for 5 min. Cool to room temperature, dilute to 10 mL with deionized water, inoculate 200 μL of sample into a 96-well plate and measure absorbance at 540 nm using a microplate reader. The inhibition rate of α-amylase was estimated using Eq. (6) with acarbose as a positive control.

2.8.3

2.8.3 Inhibition of alpha-glucosidase

The inhibitory potential of PPCMR against the activity of α-glucosidase was estimated using the method as described previously (Zhang et al., 2020). Shortly, 40 μL of different concentrations of PPCMR was mixed with an equal volume of 5 mM p-nitrophenyl-D-glucopyranose (pH 7.0) in 0.1 M PBS and incubated for 10 min at 37 °C in the dark in a 96-well plate. Afterwards, 20 μL of α-glucosidase (40 U/mL in PBS) was mixed into the above mixture. Incubate again for 20 min under the same conditions and add 100 μL of sodium carbonate (0.3 mM). The absorbance was measured at 405 nm using a microplate reader, and inhibition rate of α-glucosidase was estimated using equation (6) with acarbose as a positive control.

2.8.4

2.8.4 Inhibitory assay for acetyl-cholinesterase activity

The acetyl-cholinesterase inhibitory potential of PPCMR was estimated using the modified method as described earlier (Zdunić et al., 2020). Various concentrations of PPCMR (100 μL each) were mixed with 20 μL of acetylcholinesterase (0.2 U/mL in 0.1 MPBS, pH 8.0) in a 96-well plate, and incubated in the dark at 37 °C for 15 min. Afterwards, 40 μL each of 5,5′-dithiobis (2-nitrobenzoic acid) (1 mM in PBS) and acetylthiocholine iodide (1.87 mM in PBS) were added to the above mixture and kept at 37 °C for 20 min in the dark. Absorbance was measured at 405 nm, and the inhibition rate of acetylcholinesterase was calculated using equation (6) with galantamine as a positive control.

2.9

2.9 Antiproliferative assays

2.9.1

2.9.1 Cell culture

Different cancer cell lines viz. cervical carcinoma cells (HeLa), Hepatoma or liver cancer cells (HepG2) and lung cancer cells (NCI-H460) were cultured in RPMI-1640 media containing heat-inactivated 10% FBS (Fetal bovine serum), 100 units/mL, and 100 g/mL streptomycin. Cell culture was carried out in Jiangsu Food Safety Biochip Testing Technology Engineering Laboratory, Xuzhou University of Technology, China. Cultured cells were kept in a moistened atmosphere with 5% CO₂ at 37 °C.

2.9.2

2.9.2 Cell viability assay

The succinate dehydrogenase activity (MTT assay) was estimated using the method as described previously with slight modifications to evaluate the anti-proliferative activities of PPCMR against HeLa, HepG-2 and NCI-H460 cells (Lu et al., 2018). In short, 100 μL of the cells at a density of 1 × 10⁵ cells/mL and the same volume of PPCMR were mixed to achieve the final concentrations of 0, 14.06, 28.12, 56.25, 112.50, 225.00, 450.00, 900.00 µg/mL, respectively. Afterwards, the mixture was gently shaken for 1 min and incubated for 24 and 48 h at 37 °C with 5% CO₂ in a humidified incubator. After treatment, 5 mg/mL of MTT (20 µL) was mixed in PBS, and incubated in a humidified incubator with 5% CO₂ for an additional 4 h at 37 °C. The mixture was centrifuged, and the frozen cell precipitate was dissolved in 150 μL DMSO. After incubation, the absorbance was measured by using a microplate reader (Synergy H1, Bio-Tek, Winooski, VT, USA) at 490 nm. The inhibition rate of α-glucosidase was estimated using the Eq. (7) with 5-FU as a positive control:

(7)

I n h i b i t i o n r a t e (%) = (1 - \frac{A_{s} - A_{b}}{A_{n} - A_{b}}) \times 100

where: A_s donates sample group's absorbance, A_n is the negative control group's absorbance, and A_b is the blank control group's absorbance.

2.9.3

2.9.3 Cell morphological analysis

The cell proliferation analysis (MTT assay) was estimated using the method as described previously (Yang et al., 2019). In a 6-well culture plate, each well was inoculated with cell solution (2 mL), and incubated for 24 h under humid conditions at room temperature with 5% CO₂ before removing the previous medium. It was further divided into a sample control group, a model control group and a positive control group, and incubated at 37 °C for another 24 and 48 h. To compare the morphological changes of the cells, all groups of cells were observed by inverted microscopy TS100-F (Nikon, Chiyoda District, Tokyo Metropolitan, Japan) at ×400 magnification.

2.10

2.10 Statistical analysis

The data were analyzed using Design-Expert V8.0.6 software and results of the Box-Behnken design, 2-D contour and 3-D response surface plots were plotted. Origin V9.1 software was used to illustrate the findings of antioxidant, enzyme inhibition and antiproliferation assays, while SPSS V18.0 software was used to calculate 50% scavenging concentration (SC₅₀) on DPPH, ABTS⁺ and superoxide anion radicals and the 50% inhibitory concentration (IC₅₀) on lipase, alpha-amylase, alpha-glucosidase and acetyl-cholinesterase. All data were expressed as mean ± standard deviation.

3 Results and discussion

3.1

3.1 Optimization of UTPHSE

3.1.1

3.1.1 Fitting the model

The interaction between four parameters including voltage, ultrasonic temperature, liquid to solid ratio and ultrasonic time (Table 1), was studied using Box Behnken experimental model, and multiple regression analysis was performed. The mathematical model was matched with the experimental data with the aim to find out an optimum range for the studied response. The following equation with coded values was used to describe the predicted model:

(8)

\begin{matrix} Extraction rate (%) = - 5.951 + 7.185 \times 1 0^{- 2} x_{1} + 7.006 \times 1 0^{- 2} x_{2} + 4.282 \times 1 0^{- 2} x_{3} + 1.102 \times 1 0^{- 2} x_{4} - \\ 9.5 \times 1 0^{- 5} x_{1} x_{2} + 3.1 \times 1 0^{- 4} x_{1} x_{3} + 5 \times 1 0^{- 6} x_{1} x_{4} + 9.5 \times 1 0^{- 5} x_{2} x_{3} + 1.375 \times 1 0^{- 5} x_{2} x_{4} + 3.75 \times 1 0^{- 6} x_{3} x_{4} - \\ 1.583 \times 1 0^{- 3} x_{1}^{2} - 4.707 \times 1 0^{- 4} x_{2}^{2} - 5.744 \times 1 0^{- 4} x_{3}^{2} - 2.153 \times 1 0^{- 5} x_{4}^{2} \end{matrix}

Table 1 Experiment results of Box-Behnken for the yield of PCMR.

No.	x₁	x₂	x₃	x₄	Extraction rate (%, Actual Value)	Extraction rate (%, Predicted Value)
1	20	70	50	280	0.417	0.414
2	30	70	50	280	0.433	0.443
3	20	90	50	280	0.444	0.443
4	30	90	50	280	0.441	0.453
5	25	80	40	240	0.393	0.401
6	25	80	60	240	0.426	0.434
7	25	80	40	320	0.428	0.429
8	25	80	60	320	0.467	0.467
9	20	80	50	240	0.428	0.427
10	30	80	50	240	0.436	0.445
11	20	80	50	320	0.463	0.455
12	30	80	50	320	0.475	0.477
13	25	70	40	280	0.397	0.402
14	25	90	40	280	0.394	0.403
15	25	70	60	280	0.427	0.419
16	25	90	60	280	0.462	0.457
17	20	80	40	280	0.415	0.415
18	30	80	40	280	0.428	0.405
19	20	80	60	280	0.406	0.420
20	30	80	60	280	0.481	0.471
21	25	70	50	240	0.433	0.424
22	25	90	50	240	0.447	0.432
23	25	70	50	320	0.438	0.443
24	25	90	50	320	0.474	0.474
25	25	80	50	280	0.514	0.525
26	25	80	50	280	0.530	0.525
27	25	80	50	280	0.524	0.525
28	25	80	50	280	0.524	0.525
29	25	80	50	280	0.532	0.525

Ratio of liquid to solid (x₁), voltage (x₂), ultrasonic temperature(x₃) and ultrasonic time (x₄).

As shown in Table 2, the significance of all coefficients is determined by the F-test and P-value. With the corresponding variables becoming more significant as the absolute P-value becomes smaller and the F-value becomes larger. The linear terms for liquid–solid ratio (x₁), voltage (x₂), and the interaction term of liquid–solid ratio and ultrasonic temperature (x₁_, x₃) were seen to be significant at the 0.05 level, and the linear terms for ultrasonic temperature (x₃), ultrasonic time (x₄) and all quadratic terms were significant at the 0.001 level, whereas the other terms were insignificant. As mentioned in Table 2, the model was highly significant at P < 0.0001, the Lack of Fit (P > 0.05) was insignificant, and the predictive model had a predictive coefficient (R²) of 0.9560 with an adequate accuracy of 13.978 (much greater than 4). Therefore, it was indicated that the predicted model is representative of the observed values, and could adequately explain the responses.

Table 2 ANOVA results of quadratic regression model for response surface.

Source	SS	df	MS	F-value	P-value	Sig.
Model	0.046	14	3.275 × 10⁻³	21.74	< 0.0001	***
x₁	1.220 × 10⁻³	1	1.220 × 10⁻³	8.1	0.013	*
x₂	1.141 × 10⁻³	1	1.141 × 10⁻³	7.57	0.0156	*
x₃	3.816 × 10⁻³	1	3.816 × 10⁻³	25.34	0.0002	***
x₄	2.760 × 10⁻³	1	2.760 × 10⁻³	18.32	0.0008	***
x₁x₂	9.025 × 10⁻⁵	1	9.025 × 10⁻⁵	0.6	0.4518
x₁x₃	9.610 × 10⁻⁴	1	9.610 × 10⁻⁴	6.38	0.0242	*
x₁x₄	4.000 × 10⁻⁶	1	4.000 × 10⁻⁶	0.027	0.8729
x₂x₃	3.610 × 10⁻⁴	1	3.610 × 10⁻⁴	2.4	0.1439
x₂x₄	1.210 × 10⁻⁴	1	1.210 × 10⁻⁴	0.8	0.3853
x₃x₄	9.000 × 10⁻⁶	1	9.000 × 10⁻⁶	0.06	0.8104
x₁²	0.010	1	0.010	67.41	< 0.0001	***
x₂²	0.014	1	0.014	95.39	< 0.0001	***
x₃²	0.021	1	0.021	142.08	< 0.0001	***
x₄²	7.694 × 10⁻³	1	7.694 × 10⁻³	51.08	< 0.0001	***
Residual	2.109 × 10⁻³	14	1.506 × 10⁻⁴
Lack of Fit	1.912 × 10⁻³	10	1.912 × 10⁻⁴	3.89	0.1014
Pure Error	1.968 × 10⁻⁴	4	4.920 × 10⁻⁵
Cor Total	0.048	28
	R² = 0.9560	Adeq.Precision = 13.978

Sig. significant level, * Significant at 0.05 level, ^** Significant at 0.01 level, ^*** Significant at 0.001 level.

3.1.2

3.1.2 Response surface analysis

Predicting the effect of four variables on the extraction rate of PCMR by the regression model. The model generated tri-dimensional response surfaces and two-dimensional contour plots to show the link between the independent and dependent variables (Fig. 1 a-l). On one three-dimensional surface, two variables are represented, while the other two stays constant. The degree of contact was represented in the contour's form. The oval had a considerable impact, whereas roundness had no effect. The interaction between the liquid–solid ratio and ultrasonic temperature (x₁x₃) was excellent at the 0.05 level, as shown in Fig. 1(c). In contrast, the interaction of the other two factors was insignificant.

Two-dimensional contour plots (a, c, e, g, i, k) and response surface plots (b, d, f, h, j, l) showing the effect of liquid–solid ratio, voltage, ultrasonic temperature and ultrasonic time on the extraction rates of PCMR.

3.1.3

3.1.3 Verification experiments

The ideal extraction conditions to obtain the maximum extraction rate of PCMR from regression Eq. (8) were: liquid–solid ratio 25.8:1 (mL/g), voltage 81.0 V, ultrasonic temperature 51.8 ℃, and ultrasonic time 289 s. The expected extraction rate was 0.529%. Under these extraction process conditions, the PCMR extraction rate was 0.531 ± 0.004%, which was consistent with the predicted values, suggesting that the model was appropriate for the extraction process described above.

3.2

3.2 Purification of PCMR

The AB-8 macroporous resin has been reported in many previous studies to have physicochemical stability, adsorption/desorption selectivity and recoverability and is now widely used for the purification of plant phenols (Cui et al., 2018; Hamed et al., 2019). The purification of phenolics from sweet potato leaves with AB-8 macroporous resin has been reported to be efficient, economical and environmentally friendly, with great potential for industrial production (Xi et al., 2015). In this study, the contents of total phenols, flavonoids, flavonols, flavanols and phenolic acids were analysed by UV–Vis spectrophotometry before and after purification, as shown in Table 3, where AB-8 macroporous resin performs well in PCMR purification. The purities of total phenolics, flavonoids, flavonols, flavanols and phenolic acids were significantly improved, which indicated that AB-8 macroporous resin was an ideal purification medium with high separation efficiency.

Table 3 The contents of total phenolics, flavonoids, flavonols, flavanols and phenolic acids in PPCMR before and after AB-8 resin purification.

Measurement	Before purification	After purification	Multiplication of content after purification
Total phenolics (mg GAE/g)	79.90 ± 0.98	263.6 ± 0.70	2.30
Total flavonoids(mg RE/g)	74. 20 ± 1.46	272.0 ± 1.68	2.67
Total flavonols (mg RE/g)	29.20 ± 0.88	104.7 ± 0.89	2.59
Total flavanols (mg CE/g)	4.790 ± 0.10	22.21 ± 0.34	3.63
Total phenolic acids(mg CAE/g)	47.75 ± 1.45	184.4 ± 2.03	2.86

3.3

3.3 Antioxidant activities

Common methods used to evaluate antioxidant capacity are DPPH, ABTS⁺ and superoxide anion radical scavenging assays. The DPPH radical scavenging capacity assay is widely used to test the antioxidant capacity of various antioxidant samples because of its simplicity, rapidity and sensitivity. The ABTS⁺ radical scavenging capacity assay is commonly used to assess the total antioxidant capacity of different active substances. The superoxide anion assay uses NADH-PMS-NBT as a superoxide anion (O²⁻) generating system to detect the reducing capacity of reducing substances in the system. All of these reflect the ability of the sample to provide hydrogen atoms and block free radical chain reactions (Mohamed et al., 2019; Pérez-Jiménez et al., 2007). It could be seen from Fig. 2(a-c) that with the increase of the concentrations of PPCMR, the scavenging rates of DPPH, ABTS⁺ and superoxide anion radicals gradually increased, and there was a certain dose–response relationship between them. The SC₅₀ values of PPCMR for DPPH, ABTS⁺ and superoxide anion radical scavenging activities were 80.32, 12.89 and 14.27 μg/mL, respectively and the SC₅₀ values of ascorbic acid were 6.74, 4.48 and 4.24 μg/mL, respectively. This indicated that DPPH, ABTS⁺ and superoxide anion radicals scavenging activities of PPCMR were weaker than those of ascorbic acid, but this does not affect them as effective free radical scavengers. In previous studies, the researchers got the similar results. They concluded that the derivatives from Morus alba root bark showed good antioxidant activity in DPPH and ONOO⁻ scavenging assays (Muanda et al., 2010; Paudel et al., 2020). The RP and FRAP analysis reflected the capacity of the sample to decrease potassium (Fe³⁺) to potassium ferrocyanide (Fe²⁺) and TPTZ-Fe(III) to TPTZ-Fe(II) (Sokamte et al., 2019; Yang et al., 2011). Both assays could be used as indicators to assess potential antioxidant properties. As illustrated in Fig. 2(d-e), with the increase of the concentrations of PPCMR, the A_rp and A_frap values of PPCMR gradually increased, and there was a certain dose–response relationship between them. However, the RP and FRAP activities of PPCMR were lower than those of ascorbic acid, which implied that ascorbic acid possessed a stronger effect. But this couldn’t prevent PPCMR from becoming a good natural antioxidant. Furthermore, our findings were corresponding to the previous reports (Abdel-Haleem et al., 2017; Murugan and Parimelazhagan, 2014).

Antioxidant activities of PPCMR. (a) DPPH radical scavenging activities; (b) ABTS+ radical scavenging activities; (c) Superoxide anion radical scavenging activities; (d) RP activities and (e) FRAP activities. Ascorbic acid was used as a positive control. Each value is presented as mean ± SD (n = 3).

3.4

3.4 Enzyme inhibitory activities

Lipase is involved in the metabolism of triglycerides, and is the basic enzyme for lipid hydrolysis (Spínola et al., 2020). Hyperlipidemia arises from excessive lipase activity, producing too much monoglycerides and fatty acids. Lipase inhibitors promote the elimination of lipids from the body by reducing the amount of lipid hydrolysates, which leads to weight loss. α-amylase and α-glucosidase are considered therapeutic targets for the regulation of postprandial hyperglycemia (Jonathan et al., 2018; Young et al., 2010). Acetylcholinesterase is a neurotransmitter hydrolase that rapidly hydrolyzes acetylcholine at choline synapses, preventing acetylcholine accumulation and maintaining normal physiological function of the nervous system (Oliveira et al., 2011; Masuoka et al., 2019). Future treatment of Alzheimer's disease by inhibition of acetylcholinesterase is expected and may be used to treat Parkinson's disease, aging, and myasthenia gravis (Bianco et al., 2015; Masondo et al., 2018). The inhibitory activities of PPCMR against lipase, α-amylase, α-glucosidase and acetyl-cholinesterase were presented in Fig. 3(a-d). The PPCMR within the selected concentration range could inhibit the enzyme activities dose-dependently. The IC₅₀ values of PPCMR against lipase, α-amylase, α-glucosidase and acetyl-cholinesterase were 0.27 mg/mL, 1.25 mg/mL, 0.35 mg/mL and 85.18 μg/mL, respectively. However, the IC₅₀ values of the positive controls (orlistat, acarbose, acarbose and galantamine) were 0.16 mg/mL, 2.76 mg/mL, 0.94 mg/mL, 0.016 μg/mL, respectively. The results showed that there were only a few differences of inhibition effect between the PPCMR and the positive controls on lipase, α-amylase, α-glucosidase. However, the inhibition effect of PPCMR on acetyl-cholinesterase was more than five thousand times lower than that of galantamine. Thus, the experimental results indicated that PPCMR had remarkable inhibition effects on lipase, α-amylase and α-glucosidase activities, but their inhibition effect on acetyl-cholinesterase activity was comparatively ineffective. According to the literatures, the results were similar to earlier studies. Cortex Mori's prenylated flavonoids, flavonols and alkaloids are small molecule α-glucosidase inhibitory components, and its flavonoid derivatives could significantly inhibit on pancreatic lipase activities (Akhter et al., 2013; Ha et al., 2018; Liu et al., 2013; Hou et al., 2018; Chen et al., 2018; Sadeer et al., 2019 ).

Enzyme inhibitory activities of PPCMR. (a) Lipase inhibitory activities; (b) α-amylase inhibitory activities; (c) α-glucosidase inhibitor activities; (d) Acetylcholinesterase inhibitory activities. Each value is presented as mean ± SD (n = 3).

3.5

3.5 Antiproliferative activities

It is one of the important methods to find high specific anticancer drugs to evaluate the anticancer performance using cancer cell lines in vitro (Irshad et al., 2014). MTT assay and other detection methods based on tetrazolium haline are the most popular techniques for quantitative assessment of cell proliferation, viability and cytotoxicity (Tim, 1983). Its mechanism is to reduce exogenous MTT to water-insoluble blue purple formazine crystals through succinate dehydrogenase in mitochondria of living cells, nevertheless dead cells have no such function (Zhu et al., 2013). The antiproliferative activities of PPCMR against HeLa, HepG2 and NCI-H460 were presented in Fig. 4(a-c). The antiproliferative activities of PPCMR increased with the increase of the concentrations in both 24 and 48 h of incubation time When the concentrations increased from 150 to 900 μg/mL, the inhibition rates of 24 h of PPCMR treatment ranged from 7.670 ± 1.33% to 58.67 ± 1.53%, 17.66 ± 3.29% to 78.25 ± 3.80%, −2.21 ± 5.53% to 86.49 ± 2.38%, and of 48 h of PPCMR treatment ranged from 0.28 ± 2.78% to 85.57 ± 2.42%, 6.50 ± 4.87% to 84.73 ± 2.81%, −2.79 ± 4.17% to 92.65 ± 1.60%, for the HeLa, HepG2 and NCI-H460 cells, respectively. In general, the result of 48 h treatment was better than that of the 24 h treatment. Similar outcomes were also reported previously (Lu et al., 2018).

Antiproliferative activities of PPCMR. (a) Human cervical cancer Hela cell inhibiting activities; (b) Human hepatoma HepG2 cell inhibiting activities; (c) Human lung cancer NCI-H460 cell inhibiting activities. Each value is presented as mean ± SD (n = 3).

3.6

3.6 Cellular morphology

Cell morphology is a common indicator of the physiological and growth status of cells. The physiological and growth status of the cells can be assessed by observation at the morphology of the cells, so as to further reflect the effect of drugs on cell growth (Xiaoqiang et al., 2019). Morphological changes of HeLa, HepG2 and NCI-H460 cells treated or untreated with different concentrations of PPCMR were observed after 24 and 48 h. As shown in Figs. 5–7 , PPCMR exhibited antiproliferative on HeLa, HepG2 and NCI-H460 cells in a time and dosage-related manner. According to the model control group, it could be seen that the cells of HeLa, HepG2 and NCIH460 all presented irregular shapes and grew adherent to the inner wall of the culture plate. Especially after the 48 h of culture, the cells were tightly connected, and the cell number increased significantly. However, compared with the model control group, after PPCMR (750 and 900 μg/mL) or 5-FU treatment for 24 and 48 h, the number of adherent cells decreased significantly, the cell morphology changed from an irregular shape to a round shape. At the same time, it could also be seen that 900 μg/mL PPCMR treatment was more effective than that of 750 μg/mL. Collectively, these results suggested that PPCMR effectively inhibits the proliferation of HeLa, HepG2 and NCI-H460 cells in vitro. The outcome of the assay was similar to that of the literature, they found that treatment in a dose-dependent manner of Mori Cortex Radicis extracts had the better anti-proliferative activity on Raw 264.7 cells, also speculated that the anti-inflammatory activity may be related to p38-Mitogen-activated protein kinase (MAPK), and Nuclear factor Kappa B (NF-κB) (Seo et al., 2013; Bayazid et al., 2019).

Effect of PPCMR on morphology of HeLa cells. (a) Negative control group (24 h); (b) Negative control group (48 h); (c) 150 µg/mL 5-FU treatment group (24 h); (d) 150 µg/mL 5-FU treatment group (48 h); (e) 750 µg/mL PPCMR treatment group (24 h); (f) 750 µg/mL PPCMR treatment group (48 h); (g) 900 µg/mL PPCMR treatment group (24 h); (h) 900 µg/mL PPCMR treatment group (48 h).

Effect of PPCMR on morphology of HepG2 cells. (a) Negative control group (24 h); (b) Negative control group (48 h); (c) 150 µg/mL 5-FU treatment group (24 h); (d) 150 µg/mL 5-FU treatment group (48 h). (e) 750 µg/mL PPCMR treatment group (24 h); (f) 750 µg/mL PPCMR treatment group (48 h); (g) 900 µg/mL PPCMR treatment group (24 h); (h) 900 µg/mL PPCMR treatment group (48 h).

Effect of PPCMR on morphology of NCIH460 cells. (a) Negative control group (24 h); (b) Negative control group (48 h); (c) 150 µg/mL 5-FU treatment group (24 h); (d) 150 µg/mL 5-FU treatment group (48 h); (e) 750 µg/mL PPCMR treatment group (24 h); (f) 750 µg/mL PPCMR treatment group (48 h); (g) 900 µg/mL PPCMR treatment group (24 h); (h) 900 µg/mL PPCMR treatment group (48 h).

4 Conclusions

In this study, an efficient UTPHSE technique and Box-Behnken design were used to optimize the extraction process of PMCR. The ideal constraints were: liquid–solid ratio 25.8:1 (mL/g), voltage 81.0 V, ultrasonic temperature 51.8 ℃ and ultrasonic time 289 s. Under these conditions of the extraction process, the experimental extraction rate was 0.531 ± 0.004%, which was in good agreement with the predicted value (0.529%), suggesting that the model is suitable for the above extraction process. In this study, we carried out, for the first time, an in-depth assessment of the antioxidant, enzyme (lipase, α-amylase, α-glucosidase and acetyl-cholinesterase) inhibitory and antiproliferative properties of PPCMR. It could be concluded from this research that PPCMR have the potential to be employed as natural antioxidants, or antilipidemic, hypoglycemic or antineoplastic agents in the nutraceutical and pharmaceutical industries, however not suitable to be used as an acetyl-cholinesterase inhibitor. Further studies are needed to elucidate the mechanisms of anti-lipid, hypoglycemic or anti-tumor activity of PPCMR in vivo.

Author contributions

Experimental design, analysis, writing-C.L, Y.P, W.T, T.L, J.C and Y.S; data analysis, interpretation, software-C.L, Y.P, W.W, Y.Y and Y.S; final draft, validation, resources- C.L, Y.P, T.L, J.F, J.H and Y.C; visualization, proof reading, funding acquisition-A.M.A, M.K.G, R.A.R. All authors have read the published version of the manuscript and agrees with its contents.

Acknowledgments

The authors extend their appreciation to the Researchers supporting project number (RSP-2021/393), King Saud University, Riyadh, Saudi Arabia.

Funding

This work was supported by the National Natural Science Foundation of China (No. 31401496), the “333” Project (No. 2016), the Xuzhou Institute of Technology Project (No. XKY2018137), the Guangzhou Science and Technology Innovation and Development Special Fund Project (No. 201804010378), the Guangdong Natural Science Fund Project (No. 2017A030310406).

Institutional review board statement

Not applicable.

Data availability statement

In the article and manuscript the information referred to in the data used to support the results of this study.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Antioxidant, anti-lipidemic, hypoglycemic and antiproliferative effects of phenolics from Cortex Mori Radicis

Abstract

Keywords

Cortex Mori Radicis

Phenolics

Ultrasonic

Antioxidant effect

Enzyme inhibitory effect

Antiproliferative effect

1 Introduction

2 Materials and methods

2.1 Sampling

2.2 Chemicals and reagents

2.3 Preparation of PPCMR

2.3.1 Extraction

2.3.2 Purification

2.4 Determination of extraction rate

2.5 Optimization

2.6 Phytochemical analysis

2.7 Antioxidant assays

2.7.1 DPPH radical scavenging assay

2.7.2 ABTS+ scavenging assay

2.7.3 Scavenging activity of superoxide anion

2.7.4 Reducing power assay

2.7.5 Ferric ion reducing antioxidant power (FRAP) assay

2.8 Enzyme inhibition assays

2.8.1 Inhibition of lipase

2.8.2 Alpha-amylase inhibitory assay

2.8.3 Inhibition of alpha-glucosidase

2.8.4 Inhibitory assay for acetyl-cholinesterase activity

2.9 Antiproliferative assays

2.9.1 Cell culture

2.9.2 Cell viability assay

2.9.3 Cell morphological analysis

2.10 Statistical analysis

3 Results and discussion

3.1 Optimization of UTPHSE

3.1.1 Fitting the model

3.1.2 Response surface analysis

3.1.3 Verification experiments

3.2 Purification of PCMR

3.3 Antioxidant activities

3.4 Enzyme inhibitory activities

3.5 Antiproliferative activities

3.6 Cellular morphology

4 Conclusions

Author contributions

Acknowledgments

Funding

Institutional review board statement

Data availability statement

Declaration of Competing Interest

References:

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2.7.2 ABTS⁺ scavenging assay