**Quality Evaluation of** *Gastrodia Elata* **Tubers Based on HPLC Fingerprint Analyses and Quantitative Analysis of Multi-Components by Single Marker**

**Yehong Li 2,**†**, Yiming Zhang 1,**†**, Zejun Zhang 1, Yupiao Hu 1, Xiuming Cui 1,3,4 and Yin Xiong 1,3,4,\***


Academic Editors: Marcello Locatelli, Angela Tartaglia, Dora Melucci, Abuzar Kabir, Halil Ibrahim Ulusoy and Victoria Samanidou

Received: 24 February 2019; Accepted: 15 April 2019; Published: 17 April 2019

**Abstract:** *Gastrodia elata* (*G. elata*) tuber is a valuable herbal medicine used to treat many diseases. The procedure of establishing a reasonable and feasible quality assessment method for *G. elata* tuber is important to ensure its clinical safety and efficacy. In this research, an effective and comprehensive evaluation method for assessing the quality of *G. elata* has been developed, based on the analysis of high performance liquid chromatography (HPLC) fingerprint, combined with the quantitative analysis of multi-components by single marker (QAMS) method. The contents of the seven components, including gastrodin, *p*-hydroxybenzyl alcohol, *p*-hydroxy benzaldehyde, parishin A, parishin B, parishin C, and parishin E were determined, simultaneously, using gastrodin as the reference standard. The results demonstrated that there was no significant difference between the QAMS method and the traditional external standard method (ESM) (*p* > 0.05, RSD < 4.79%), suggesting that QAMS was a reliable and convenient method for the content determination of multiple components, especially when there is a shortage of reference substances. In conclusion, this strategy could be beneficial for simplifying the processes in the quality control of *G. elata* tuber and giving references to promote the quality standards of herbal medicines.

**Keywords:** *Gastrodia elata* tuber; quality evaluation; HPLC; QAMS

#### **1. Introduction**

*Gastrodia elata (G. elata)* Blume is a traditional medicinal herb that has been used in oriental countries, for centuries, to treat general paralysis, headaches, dizziness, rheumatism, convulsion, and epilepsy [1,2]. Modern pharmacological studies have demonstrated that the extracts of *G. elata* tuber and some compounds that originate from it, possesses wide-reaching biological activities, including anti-tumor, anti-virus, memory-improving, anti-oxidation, and anti-aging actions [3–5]. Nowadays, it is also widely used as a sub-material in food and Chinese Patent Medicines (CPM) [6], and this herbal medicine is also listed as one of the functional foods approved by the Ministry of Health in China [7,8]. As the wild *G. elata* is not sufficient enough for commercial large-scale exploitation, its artificial cultivation in medicine has become essential, to meet the increasing requirement of markers [6].

Due to their high medicinal value, *G. elata* tubers have been cultivated and produced in many areas of Asia, like China and Korea, which could lead to great differences in quality and, possibly, could lead to differences in the following clinical efficacies. Many studies have indicated that the efficacy and quality of herbal medicines are somewhat different depending on the cultivation soil and climate, based on the geographic origin, even when coming from the same species [9,10]. Therefore, a reasonable and effective method for the quality evaluation of *G. elata* tuber, plays an important role in its medication safety.

Gastrodin and its aglycone (*p*-hydroxybenzyl alcohol) are major components of the *G. elata* tuber, which are also markers for the quality control of this herbal medicine [11]. However, over 81 compounds from *G. elata* tuber have been currently isolated and identified. Along with the above two marker components, others like *p*-hydroxy benzaldehyde, parishin A, parishin B, parishin C, parishin E, and so on have also been reported to be correlated with the bioeffects of the *G. elata* tuber [12,13]. Accordingly, a qualitative analysis and quantification of one or two compounds, could be insufficient for a complete profile of the chemical characterization of the *G. elata* tuber, due to its complex compositions. In recent years, the chromatographic fingerprint analysis has been accepted as a strategy for the quality assessment of herbal medicines and preparations by the US Food and Drug Administration [14], State Food and Drug Administration of China [15], and the European Medicines Agency [16]. Since the fingerprint is characterized by more chemical information, the method is often used for the origin identification, species authentication, and quality control for herbal medicines, by observing the presence or absence of a limited number of peaks in the chromatographic fingerprints [17,18]. Therefore, the fingerprint analysis of high performance liquid chromatography (HPLC) was developed for the qualitative analysis of *G. elata* tuber.

A single standard to determine multiple components, also known as the quantitative analysis of multi-components by single marker (QAMS) [19], is a novel method designed for the quality evaluation of herbal medicines and related products [20]. Researchers have used QAMS to determine three components in Fructus Evodiae, simultaneously, by using rutaecarpine as the internal reference compound to calculate the relative correction factor of evodin and evodiamine [21]. To make up for the limitations of the fingerprint which cannot be quantified accurately, a QAMS method using berberine as the standard, was developed and validated for a simultaneous quantitative analysis of fourteen components [22]. This strategy could not only reduce the cost of the experiment and time of detection but could also be independent of the availability of all target ingredients [19]. Thus, the QAMS method was applied for a quantitative analysis of *G. elata* tuber.

This study aimed to establish a reliable and practical method, realizing both qualitative and quantitative analyses for *G. elata* tuber, via HPLC fingerprinting, combined with QAMS. The differences and similarities of the HPLC fingerprints were visually compared, using a hierarchical cluster analysis (HCA) and similarity analysis. The contents of seven major active constituents were accurately determined by both the QAMS method and external standard method (ESM), through which we hoped to offer a suitable and efficient approach for assessing the quality of *G. elata* tuber.

#### **2. Results and Discussion**

#### *2.1. Optimization of the Chromatographic Conditions*

As the components of *G. elata* tuber are very intricate, it is critical to optimize the chromatographic conditions, including favorable mobile phase systems, gradient elution systems, and the detection wavelength, to obtain an efficient separation of the target components. Lei [23] indicated that the HPLC fingerprints of *G. elata* tubers were the most informative, while the UV wavelength was 220 nm from HPLC-DAD-3D spectrum of *G. elata* tuber. So in this case, we chose the UV wavelength of 220 nm, to determinate the selected components. We chose acetonitrile-water containing 0.1% phosphoric acid system. The samples were dissolved in 60% methanol and ultrasound, for 60 min. We optimized the gradient elution system as Section 3.5, and 35 ◦C was selected as the proper temperature for analysis, while the flow rate was set at 1.0 mL/min. The S1 sample of *G. elata* tuber and the mixed standards

containing seven reference substances were analyzed to obtain the HPLC fingerprints (Figure 1) under the conditions of Section 3.5, producing sharp and symmetrical chromatographic peak shapes, good separation, and preventing the peak tailing.

**Figure 1.** The HPLC fingerprints of the *Gastrodia elata* tuber sample and the mixed standards. R: The mixed standards; S: The *G. elata* tuber sample. 1—Gastrodin; 2—*p*-Hydroxy benzyl alcohol; 3—Parishin E; 4—*p*-Hydroxy benzaldehyde; 5—Parishin B; 6—Parishin C; 7—Parishin A.

According to the retention time of each peak in the chromatogram [24], the peaks of 1, 2, 3, 4, 5, 6, and 7 were identified to be gastrodin, *p*-hydroxybenzyl alcohol, parishin E, *p*-hydroxy benzaldehyde, parishin B, parishin C, and parishin A. The separation degree of each peak was greater than 1.5, in the present HPLC system, indicating the peaks were well-separated, under the chromatographic conditions.

#### *2.2. Method Validation*

#### 2.2.1. Linearity

The mixed reference solution containing all the reference substances was diluted in series, with 60% methanol, to obtain six different concentrations for the seven reference curves. The linearity of each analyte was assessed by plotting its calibration curve with different concentrations and the corresponding peak areas. The results were shown in Table 1. The high correlation coefficient values indicated that there was a good correlation between the concentration and peak area of the seven compounds, at a relatively wide range of concentrations. The correlation coefficient of more than 0.9990, indicated a satisfactory linearity. The calibration curve could be utilized for the quantitative analysis in the given concentration range. The standard solution of the individual analyte was diluted gradually, to determine its Limit of Detection (LOD) and Limit of Quantity (LOQ) with signal-to-noise ratio of 3:1 and 10:1, respectively. LOD and LOQ values for the analytes are also listed in Table 1.


**Table 1.** The regression equations, Limit of Detection (LODs) and Limit of Quantity (LOQs) of seven components.

#### 2.2.2. Precision, Stability, Repeatability, and Accuracy

The precision was evaluated according to the assay of S1, in which the solution was analyzed for six times in a day, to evaluate the intra-day precision, and was analyzed on three consecutive days, to evaluate the inter-day precision. Calculating the RSDs of each chromatographic peak, the results showed that the RSDs of gastrodin, *p*-hydroxybenzyl alcohol, parishin E, *p*-hydroxy benzaldehyde, parishin B, parishin C, and parishin A were 1.93%, 1.10%, 1.29%, 2.30%, 2.03%, 2.63%, and 0.89% (n = 6), respectively, indicating that the precision of the method was good.

The stability was tested with the S1 solution that was stored at room temperature (25 ± 5 ◦C) and analyzed at 0, 2, 4, 6, 8, 12, and 24 h, to calculate the RSDs. The results showed that the RSDs of gastrodin, *p*-hydroxybenzyl alcohol, parishin E, *p*-hydroxy benzaldehyde, parishin B, parishin C, and parishin A were 1.15%, 2.04%, 1.51%, 2.37%, 2.10%, 1.12%, and 2.25%, respectively, suggesting that the method was stable within 24 h.

In the repeatability test, six duplicates of S1 were extracted and analyzed, according to the sample preparation procedure, and the HPLC method. The RSDs of the peak areas were calculated. The results showed that the RSDs of gastrodin, *p*-hydroxybenzyl alcohol, parishin E, *p*-hydroxy benzaldehyde, parishin B, parishin C, and parishin A were 1.25%, 2.15%, 1.60%, 1.81%, 1.72%, 1.84%, and 1.60% (n = 6), respectively, indicating that the repeatability of the method was good.

In the accuracy test, certain amounts of the seven analytes' standards were added to the *G. elata* tuber samples (S1), with the six replicates. Then, these seven mixed samples were treated, as in the method described above. Recovery rate was used as the evaluation index and calculated as Recovery rate (%) = (Found amount − Known amount) × 100%/Added amount. The RSD of the accuracy values of the seven components are shown in Table 2, respectively.


**Table 2.** RSD of precision, stability, repeatability and accuracy for determination of seven components.

The HPLC method was validated in terms of precision, repeatability, stability, and accuracy, as shown in Table 2. The RSD of the precision values of the seven components were less than 2.63%. RSD values for the stability and the repeatability were less than 2.37% and 2.15%, respectively. The recovery rates of the analytes ranged from 91.80% to 98.05%, with the RSD values being lower than 2.90%. All results indicated that the developed method was stable, accurate, and repeatable. This established

HPLC method could be applied for a simultaneous determination of gastrodin, *p*-hydroxybenzyl alcohol, parishin E, *p*-hydroxy benzaldehyde, parishin B, parishin C, and parishin A, in the *G. elata* tuber samples.

#### *2.3. HPLC Fingerprints Analysis*

The 21 batches of *G. elata* tuber samples from the different producing areas were prepared according to Section 3.3, and 10 μL of S1 sample solution was injected into the HPLC system according to the chromatographic conditions in Section 3.5, to obtain the fingerprints. The retention time was the horizontal axis and the peak area was the vertical axis; the 3D fingerprints of the 21 batches of *G. elata* tuber samples were established by the software Origin 9.0, as shown in Figure 2.

**Figure 2.** HPLC fingerprints of the 21 batches of *G. elata* tuber samples. 1—Gastrodin; 2—*p*-Hydroxy benzyl alcohol; 3—Parishin E; 4—*p*-Hydroxy benzaldehyde; 5—Parishin B; 6—Parishin C; 7—Parishin A.

According to Figure 2, the seven peaks with stable and better shape were determined to be the major ones for the HPLC fingerprints of *G. elata* tubers. The peak areas of the seven peaks are shown in Table 3. The variance coefficients of the peak area were greater than 32.2 percent, indicating that the content of each marker component varied greatly from place to place.


**Table 3.** The information and peak areas of the seven characteristic peaks in HPLC fingerprints of *G. elata* tubers.

<sup>1</sup> C.V. (%) = δ/μ × 100, δ—The standard deviation of peak area and μ—The average value of each peak area.

#### *2.4. Similarity Analysis*

According to the data of HPLC fingerprints in Figure 2, the similarity of HPLC fingerprints from the different producing regions were evaluated using the Similarity Evaluation System for chromatographic fingerprint of traditional Chinese medicines (TCM) (Version 2012), with correlation coefficient (median) on behalf of the similarity of HPLC fingerprints. We utilized the average correlation coefficient method of 21 batches of the samples for the multipoint correction, and the time window width was set to 0.5 [25], while the establishment of a common model was to generate a control fingerprints of the *G. elata* tuber. Compared with the reference fingerprint chromatogram (R), the similarities of the 21 batches of samples were higher than 0.96, indicating that the batch-to-batch consistency was good. The results suggested that those samples of *G. elata* tuber had a similar chemical composition, and the samples were collected from the same genus, even though they were from different producing countries or were produced under different processing conditions (Table 4). Therefore, the developed fingerprint by HPLC could be used as a practical tool for the qualitative identification of the *G. elata* tuber.



#### *2.5. Hierarchical Cluster Analysis (HCA)*

Using the peak areas of the seven compounds from the 21 *G. elata* tuber samples as the clustering variable, the HCA of the standardized data was performed with the heat map software of Heml 1.0. The graph in Figure 3 illustrated that the samples could be categorized into three groups. Group 1 contained S1 and S2 from Zhaotong, Yunnan in China; Group 2 contained S19 and S20 tubers from South Korea; and Group 3 contained the rest of samples. From the result, the samples from the same producing area were not always classified into the same group. For example, Zhaotong has been considered as the Daodi production area (area which produces authentic and superior medicinal materials) of the *G. elata* tuber in China. However, samples 1 to 6 from Zhaotong, showed different levels and ratios of chemical components, which could be due to the variations in harvesting time, planting patterns, dying methods, and other factors. Additionally, the preliminary processing method also contributes to the differences in the chemical composition. For instance, *G. elata* tubers and slices from South Korea were classified into different categories. Therefore, it is insufficient to determine the quality of the *G. elata* tubers by only their producing areas or any other single factor. Although the HCA could be used to classify the *G. elata* tubers on the basis of the peak areas of the seven components, it was hard to tell which group had a better quality. Therefore, other methods for the quantitative analysis of *G. elata* tubers should be developed, to reflect the quality difference.

**Figure 3.** Clustering analysis graph of the 21 *G. elata* tuber samples.

#### *2.6. Quantitative Analysis of Multiple Components by Single Marker*

Theoretically, the quantity (mass or concentration) of an analyte is in direct proportion of the detector response. Then, in multi-component quantitation, a typical botanical compound (readily available) might be selected as an internal standard and the relative correction factor (RCF) of this marker, and the other components can be calculated.

#### 2.6.1. Calculation of RCFs

It is of vital importance to select a proper internal referring standard for the accurate assay of multiple components in TCM. The component chosen as the internal referring substance should be stable, easily obtainable, and have relatively clear pharmacologic effects related to the clinical efficacy of the herbal medicine [26]. In this work, the gastrodin was used as an internal referring substance for its easy availability, lower cost, moderate retention value, and good stability.

In order to simultaneously determine the contents of the seven components in the *G. elata* tuber, by using the QAMS method, the relative correction factors (RCFs, *fx*) were first determined, according

to the ratio of the peak areas and the ratio of the concentration between the gastrodin and other compounds, as described in Section 3.6. We calculated the RCFs of six components (shown in Table 5).


**Table 5.** Relative correction factor (RCF) values of six components of the *G. elata* tuber.

#### 2.6.2. Results from the QAMS Method

After preparing the sample solutions of *G. elata* tubers, they were injected into the HPLC system to obtain the peak areas. The contents of seven compounds were calculated, according to the calibration curves. Those scattered in the vicinity of the lowest concentration point on the standard curve were determined with a one point ESM. Meanwhile, the contents of the seven components of the *G. elata* tuber calculated according to QAMS method, are shown in Table 6.

The validated traditional ESM and QAMS method were employed to test the 21 batches of *G. elata* tuber samples from the different producing areas, which were based on the principle of the linear relationship between a detector response and the levels of components within certain concentration ranges. The validation of the QAMS method might be implemented, based on *t*-test, correlation coefficient [27], RSD [28], and relative error [29], through a comparison with an external standard. Correlation coefficient, as a statistical parameter, ranging from 0 (no correlation) to 1 (complete correlation), reflecting the closeness of two variables, is often used in similarity assessments of traditional Chinese medicine fingerprints [30]. As shown in Table 7, Correlation coefficients of the assay results obtained from the two methods were calculated here; all coefficients were found to be >0.998. The data showed that the results of the two methods were highly correlated. Then, a *t*-test was performed for the calculated results, by the QAMS method, and the on detected results, by an external standard method. *p*-values of gastrodin, *p*-hydroxy benzyl alcohol, parishin E, *p*-hydroxy benzaldehyde, parishin B, parishin C and parishin A, were all >0.05. The relative error and RSD values were all lower than 5%. Above all, the results indicated that there was no significant difference between the data from the QAMS and the ESM method, indicating that the present QAMS method was reliable for the simultaneous quantification of the seven components of the *G. elata* tuber.


**Table 6.** Contents of the seven components in *G. elata* tubes determined by the external standard method (ESM) and the quantitative analysis of multi-componentssinglemarker(QAMS)methods(mg·g-1)1.

content was determined by RCFs; RSD—relative standard deviation; Total—the sum of the six alkaloid contents in each batch.

#### *Molecules* **2019** , *24*, 1521


Therelativeerror,RSD,correlationcoefficient,and*p*valuesofthecontentsfromtheESMandtheQAMS

RSD—relative standard deviation; *p* values—the paired *t*-test results; ESM—external standard method, and its content was determined by the calibration equationQAMS—quantitative analysis multi-components by single marker, and its content was determined by RCFs; \*\* *p* < 0.01.

The results from the QAMS determination of the 21 batches of *G. elata* tuber samples showed the mean contents of 3.5275 mg·g-1, 0.9060 mg·g−1, and 0.3398 mg·g−<sup>1</sup> for gastrodin, *p*-hydroxy benzyl alcohol, and *p*-hydroxy benzaldehyde; and 3.6511 mg·g<sup>−</sup>1, 9.5303 mg·g<sup>−</sup>1, 2.7901 mg·g<sup>−</sup>1, and 0.1766 mg·g−<sup>1</sup> for the parishin E, parishin A, parishin B, and parishin C, respectively (Table 4). It was obvious that parishin A is one of the most abundant components in *G. elata* tuber, thus, is well-deserved as a reference substance and index for quality assessment and control of the *G. elata* tuber. Obvious inter-batch content variations could be found for all these components with the mean ranging from 0.1766 mg·g−<sup>1</sup> to 9.5303 mg·g−1; these seven components in total averaged 20.7031 mg·g−<sup>1</sup> in the *G. elata* tuber, for the 21 batches of samples. The data in Table 4 shows differences among various samples. To show the clear classification of the *G. elata* tuber samples, the QAMS method with chemometrics analysis was performed in the subsequent analyses.

Meanwhile, the results (Table 6) illustrated that there were remarkable differences in the contents of the seven components, in *G. elata* tubers from different regions, which could be attributed to the variations of genetics, plant origins, environmental factors, drying process, storage conditions, and so on. It was obvious that gastrodin is one of the most abundant components in *G. elata* tuber. Combined with its activities related to the efficacies of *G. elata* tuber [31], gastrodin is well-deserved as a reference substance and index for quality assessment and control of *G. elata* tuber.

In the Chinese Pharmacopoeia of 2015 edition, gastrodin and *p*-hydroxy benzyl alcohol are determined as the marker components for the quality control and evaluation of *G. elata* tuber. Despite their close correlation with the efficacies of *G. elata* tuber, gastrodin can transform to *p*-hydroxybenzyl alcohol, which is the aglycone and metabolite of gastrodin [32]. Fresh *G. elata* tubers have to be processed before being traded as materia medica in the market. During the steaming process, the change trend of the gastrodin content was often contrary to the one of *p*-hydroxybenzyl alcohol. When the content of gastrodin was increased, the content of *p*-hydroxybenzyl alcohol was generally decreased, and vice versa. Additionally, different processing methods will result in different variation of the contents of the two components. Choi et al. [33] applied drying methods of freeze drying, hot air, infrared ray, and steaming, to process *G. elata* tuber. The results showed that after steaming, the content of gastrodin in *G. elata* tuber processed by freeze drying was decreased, whereas, the content of *p*-hydroxybenzyl alcohol was increased. However, tubers processed by hot-air and infrared ray drying showed the opposite results. Such transformations between gastrodin and *p*-hydroxybenzyl alcohol might be due to the deglycosylation or glycosylation, during the processing. Since the herbal medicine in the global market is often processed or dried by different methods, which results in the fluctuation in the content of single component, it is relatively stable and more comprehensive to reflect on the quality of *G. elata* tuber by monitoring multiple components, instead of a single one.

#### **3. Materials and Methods**

#### *3.1. Plant Material*

Samples of *G. elata* tuber from different producing areas were collected, as shown in Table 8.


**Table 8.** The information of *G. elata* tubers from different producing areas.

#### *3.2. Chemicals*

The reference standards of gastrodin (no. B21243, purity HPLC ≥ 98%), *p*-hydroxybenzyl alcohol (no. B20326, purity HPLC ≥ 98%), *p*-hydroxy benzaldehyde (no. B20327, purity HPLC ≥ 99%), parishin A (no. BP1063, purity HPLC ≥ 98%), parishin B (no. BP1064, purity HPLC ≥ 98%), parishin C (no. B20913, purity HPLC ≥ 98%), parishin E (no. BP1648, purity HPLC ≥ 98%) were purchased from Sichuan Victory Biological Technology Co., Ltd. (Sichuan, China), and their structures are shown in Figures 4 and 5. Methyl alcohol was purchased from the Tianjin Fengchuan Chemical Reagent Technology Co. Ltd. Acetonitrile (HPLC grade) was purchased from Sigma-Aldrich, Inc. (St. Louis, MO, USA). Phosphoric acid was purchased from the Tianjin JinDongTianZheng Precision Chemical Reagent Factory. Ultrapure water was generated with an UPT-I-20T ultrapure water system (Yunnan Ultrapure Technology, Inc., Yunnan, China). All other chemicals used were of analytical grade.

**Figure 4.** The structures of some compounds in the *G. elata* tuber. (**a**) Gastrodin [34], (**b**) *p*-hydroxy benzaldehyde [35], and (**c**) *p*-hydroxybenzyl alcohol [36].

**Figure 5.** The structures of parishins in the *G. elata* tuber. The structure of parishins [13]: RA. parishin A, RB. parishin B, RC. parishin C, RE. parishin E.

#### *3.3. Preparation of the Sample Solution*

The 21 batches of dried *G. elata* tubers from different producing areas were crushed by a Wiggling high-speed Chinese medicine shredder, then powdered and sieved through a 40-mesh sieve. The sample solution of *G. elata* tuber was precisely absorbed (2.0 mg) and immersed in 25 mL volumetric flask, with 60% methanol. Additional 60% methanol was added to compensate for the weight loss after ultrasonic extraction for 60 min, and shaking it well. All solutions were filtered through 0.22 μm filter membranes, before being precisely injected into the HPLC system.

#### *3.4. Reference Solution Preparation*

The reference solution of *G. elata* tuber was prepared by accurately dissolving weighed samples of each compound in 60% methanol, making a mixture of 0.8 mg/mL of parishin A, 0.9 mg/mL of parishin B, 0.5 mg/mL of parishin E, 1.5 mg/mL of *p*-hydroxy benzaldehyde, 3.4 mg/mL of *p*-hydroxybenzyl alcohol, 0.9 mg/mL of gastrodin, 1.3 mg/mL of parishin C, mixed evenly. All the standard solutions were stored in a refrigerator at 4 ◦C, before use.

#### *3.5. Chromatographic Procedures*

The HPLC analysis of the *G. elata* tuber were done on an Agilent 1260 series system (Agilent Technologies, Santa Clara, CA, USA) consisting of a G1311B pump, a G4212B DAD detector, and a G1329B auto-sampler. The YMC-Tyiart C18 column (250 × 4.6 mm, 5 μm) was adopted for the analysis. The mobile phase consisted of A (0.1% phosphate solution) and B (acetonitrile). The gradient mode was as follows: 3–5% B for 0–11 min; 5% B for 11–18 min; 5–14% B for 18–31 min; 14% B for 31–38 min; 14–20% B for 38–48min; 20–24% B for 48–55 min; 24–80% B for 55–75 min; 80–100% B for 75–80 min; 100% B for 80–95 min; 100–70% B for 95–100 min; 70–50% B for 100–105 min; 50–30% B for 105–110 min; 30–3% B for 110–115 min; 3% B for 115–130 min. The flow rate was set at 1.0 mL/min. The detection wavelength was 220 nm. The column temperature was set at 35 ◦C and sample volume was 10 μL.

#### *3.6. Theory of the QAMS Method*

Methods for calculating the RCFs have been previously reported [24,37]. First, gastrodin was selected as the internal standard, and a multipoint method (Equation (1)) was used to calculate the relative correction factors (RCF) for *p*-hydroxy benzaldehyde, *p*-hydroxybenzyl alcohol, parishin A, parishin B, parishin E, and parishin C. Then the content of the measured component was calculated according to Equation (2) [38].

The RCFs were calculated using the calibration curves as follows:

$$f\_{k/s} = \frac{\mathbf{a\_k}}{\mathbf{a\_s}} \tag{1}$$

The content of the measured component was calculated as follows:

$$\mathbf{C}\_{\mathbf{k}} = \frac{\mathbf{A}\_{\mathbf{k}}}{\left(\mathbf{A}\_{\mathbf{s}} \times f\_{\mathbf{k}/\mathbf{s}}\right)}\tag{2}$$

where, as is the ratio of the slope of internal standard reference calibration equations; ak is the ratio of the slope of measured component calibration equations; Ak is the peak area of the measured component; and As is the peak area of the internal standard reference [37].

The content of the multi-marker components measured by QAMS was compared with results from ESM, to validate the methods of QAMS.

#### *3.7. Data Analysis*

We used the ESM and QAMS to calculate the seven components in 21 batches of *G. elata* tuber, to verify the feasibility of QAMS. At the same time, HCA was performed using the heat map software of Heml 1.0, to further investigate the difference among the *G. elata* tuber samples. The data were analyzed and evaluated by the Similarity Evaluation System for the chromatographic fingerprint of TCM (Version 2012), to evaluate similarities of the chromatographic profiles of the *G. elata* tuber.

#### **4. Conclusions**

In this study, the quality assessment method of *G. elata* tubers were established using QAMS methods, in combination with HPLC fingerprints analyses. The *G. elata* tubers from different areas were analyzed by HPLC fingerprints and the contents of the seven components in *G. elata* tuber samples was determined by the QAMS method. On the basis of these results, the quality of *G. elata* tubers could be quantified and better identified comprehensively by HCA of synthesis and similarity analysis. HPLC fingerprint analyses, combined with the QAMS methods, could be a powerful and reliable way to provide both qualitative insight and quantitative data for comprehensive quality assessment of the complex multi-component systems. QAMS combined with the HPLC fingerprint might offer a holistic phytochemical profile of botanicals, along with similarity analysis and HCA of synthesis, and the quality of *G. elata* tubers would be evaluated and better and more comprehensively identified. Moreover, in subsequent analyses, it is also necessary to combine the chemical analysis, biological evaluation, pharmacological activity, and other methods to evaluate the quality of *G. elata* tubers for better studying the clinical effect.

**Author Contributions:** Y.X. supervised the project and designed the experimental works; Y.L. performed the chemical analyses and wrote the paper; Y.Z., Z.Z., Y.H., and X.C. contributed to sample process and data analyses; Y.X. revised the paper. All authors read and approved the final manuscript.

**Funding:** This research was funded by Applied Basic Research Key Project of Yunnan (2017ZF005 and 2017ZF001).

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **Abbreviations**

The following abbreviations have been used in this manuscript.



RCF Relative correction factor

#### **References**


**Sample Availability:** Samples of the compounds are available from the authors.

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

### *Article* **Protein-Based Fingerprint Analysis for the Identification of** *Ranae Oviductus* **Using RP-HPLC**

**Yuanshuai Gan <sup>1</sup> , Yao Xiao 1, Shihan Wang 2, Hongye Guo 1, Min Liu 1, Zhihan Wang <sup>3</sup> and Yongsheng Wang 1,\***


Received: 16 April 2019; Accepted: 29 April 2019; Published: 30 April 2019

**Abstract:** This work demonstrated a method combining reversed-phase high-performance liquid chromatography (RP-HPLC) with chemometrics analysis to identify the authenticity of *Ranae Oviductus*. The fingerprint chromatograms of the *Ranae Oviductus* protein were established through an Agilent Zorbax 300SB-C8 column and diode array detection at 215 nm, using 0.085% TFA (*v*/*v*) in acetonitrile (A) and 0.1% TFA in ultrapure water (B) as mobile phase. The similarity was in the range of 0.779–0.980. The fingerprint chromatogram of *Ranae Oviductus* showed a significant difference with counterfeit products. Hierarchical clustering analysis (HCA) and principal component analysis (PCA) successfully identified *Ranae Oviductus* from the samples. These results indicated that the method established in this work was reliable.

**Keywords:** *Ranae Oviductus*; identification; protein; RP-HPLC; fingerprint

#### **1. Introduction**

*Rana chensinensis* is mainly distributed in the Changbai Mountain area, China. *Ranae Oviductus* is the dried oviduct of female *Rana temporaria chensinensis* David. The *Ranae Oviductus* is a potent traditional Chinese medicine that has been used in clinical studies for thousands of years. Today it is widely used as a nutrient food. It has been reported that *Ranae Oviductus* has significant effects in enhancing immunity, anti-fatigue, anti-aging, and lowering blood fat [1–4]. As a precious traditional Chinese medicine, *Ranae Oviductus* has been in short supply because of its limited production [5]. Its high price and lucrative profits have tempted many counterfeit products, such as bullfrog oviduct, toad oviduct, or frog oviduct, to inundate the market, resulting in the uneven quality of *Ranae Oviductus* in the market [6,7]. Those counterfeits have a similar appearance but have less efficacy. To guarantee the quality of *Ranae Oviductus*, its authenticity identification has attracted more and more attention from the pharmacists, doctors, and medicinal scientists. The identification method of *Ranae Oviductus* is still under development. In the 2005 China Pharmacopoeia, the appearance and expansion degree were employed as discriminating items of *Ranae Oviductus* [8]. Our group has reported using UV spectra to identify *Ranae Oviductus* [9]. According to a previous study, it is difficult to identify the *Ranae Oviductus* and counterfeit products using traditional methods [10]. Therefore, it is essential to establish a highly reliable method for the identification of *Ranae Oviductus*.

More than 40% of the components in *Ranae Oviductus* are proteins and the proteins are the major bioactive components of *Ranae Oviductus* [11,12]. However, the identification of *Ranae Oviductus* and counterfeit products using HPLC based on protein has not been studied yet. In addition, reversed-phase high-performance liquid chromatography (RP-HPLC) is a simple, fast, and effective technique for protein separation and characterization, as used for protein in milk, wheat gliadin, and transgenic zein [13–15]. On the other hand, the fingerprint chromatogram is considered as a comprehensive qualitative and quantitative method for the identification of different species, especially in the quality assessment of traditional Chinese medicines [16]. The World Health Organization (WHO) has admitted the use of chromatographic fingerprints as an identification strategy for traditional Chinese medicinal preparations [17]. Many reports have employed HPLC fingerprint chromatograms to study the quality control of traditional Chinese medicines. For example, Lu et al. used the HPLC fingerprint to identify Chinese *Angelica* from related umbellifer herbs. Sun et al. analyzed polysaccharides from different *Ganoderma*. Li et al. established the fingerprint analysis of polyphenols, which were extracted from pomegranate peel, with reliable results [18–20].

In this work, the main proteins components of *Ranae Oviductus* were used as the study objects. We used RP-HPLC to establish a fingerprint method for the identification of*Ranae Oviductus*. Ten batches of *Ranae Oviductus* were collected from different main producing areas of the Changbai Mountains. A protein reference chromatogram was established using those *Ranae Oviductus*, based on protein composition similarity analysis. Furthermore, the difference between the authentic *Ranae Oviductus* and counterfeit products were investigated. The results were verified via a chemometric approach, utilizing principal component analysis and hierarchical clustering analysis. Both showed that the newly established *Ranae Oviductus* identification method was reliable.

#### **2. Materials and Methods**

#### *2.1. Chemicals and Samples*

The petroleum ether, guanidine hydrochloride, and ammonium sulfate analytical grade were purchased from Beijing Chemical Factory (Beijing, China). The dithiothreitol (DTT) and trifluoroacetic acid (TFA) were purchased from Sigma-Aldrich (St. Louis, MO, USA). The HPLC-grade acetonitrile (MeCN) and HPLC-grade methanol were purchased from Fisher (Fisher Scientific, USA). The ultrapure water was obtained from a gradient water purification system (Water Purifier, Sichuan, China).

*Ranae Oviductus*, bullfrog oviduct, toad oviduct and frog oviduct were provided by Jilin Province Rana Industry Association which were collected from the Changbai Mountain area in the Jilin province of China. The specific location is shown on the map in Figure 1. Ten batches of *Ranae Oviductus* samples were collected from different regions from the main producing area of the Changbai Mountain range. The specific collection information is shown in Table 1.

**Figure 1.** Distribution map of origins for *Ranae Oviductus* and its counterfeits in the Changbai mountain area.


**Table 1.** Origin and collecting date of the *Ranae Oviductus* samples and their counterfeits.

#### *2.2. Protein Extraction*

The dried *Ranae Oviductus* was pulverized into a powder (passing through a 20-mesh sieve) and degreased with petroleum ether at room temperature. After filtration, the powder was placed in an oven at 55 ◦C for 1 h. Afterward, 0.50 g of the sample was added to PBS buffer (50 mL, 0.1 M pH 7.4). After continuously stirring for 8 h, the mixture was centrifuged at 5000 r/min for 15 min. The supernatant was collected and the precipitate was extracted again. The two centrifugal supernatants were combined. To the supernatant, an ammonium sulfate solid was slowly added until to 60% saturation [21,22]. The mixture was centrifuged at 8000 r/min for 20 min after standing at 4 ◦C for 1 h. The precipitate was dissolved in 6 M guanidine hydrochloride (containing 10 mM DTT) [23,24], and dialyzed in distilled water in a dialysis bag (molecular weight cutoff: 8000 Da) for 12 h [25]. The sample solution was finally scaled to 5 mL with 6 M guanidine hydrochloride (containing 10 mM DTT) in a volumetric flask and filtrated with a 0.45 μm filter membrane prior HPLC injection [26]. The preparations of bullfrog oviduct, toad oviduct and frog oviduct were the same as that for *Ranae Oviductus*.

#### *2.3. RP-HPLC Chromatography Analysis*

The samples were separated using an Agilent Technologies 1200 Series liquid chromatograph (Agilent Technologies, Pittsburgh, PA, USA) equipped with a quaternary pump, autosampler, thermostatted column compartment, diode array detector (DAD), and UV detector. The columns used were the Agilent Zorbax 300SB-C8 column (250 × 4.6 mm, 5 μm) and Agilent Zorbax SB-C18 column (250 × 4.6 mm, 5 μm) with mobile phase A (0.085% TFA in *v*/*v* with acetonitrile) and mobile phase B (0.1% TFA in *v*/*v* with ultrapure water) [27,28]. Gradient elution was adopted as follows, from 12–30% A in the first 52 min, and from 30–44% A in the next 28 min. The injection volume was 20 μL. The optimized separation conditions were tested under the different detection wavelengths, flow rates and temperatures [29]. The data were recorded and processed using the Agilent Chemstation software.

#### *2.4. Validation of the RP-HPLC Method*

*Ranae Oviductus* sample (S1) was used to verify the RP-HPLC method. A precision analysis was carried out by repeatedly injecting the same solution 5 times on the same day. The repeatability was assessed by injecting 5 separate solutions obtained from the same *Ranae Oviductus* sample. The stability was evaluated by analyzing the same sample solution at different time periods of 0, 2, 4, 8, 16 and 24 h at room temperature.

#### *2.5. Establishment of the HPLC Fingerprint*

The common characteristic peaks and similarities of fingerprint data of 10 batches of *Ranae Oviductus* were investigated using the professional software Similarity Evaluation System for the Chromatographic Fingerprint, according to the recommendations of the State Food and Drug Administration (SFDA). The HPLC fingerprint data of the samples were imported to the evaluation system (the solvent peaks in the first 4 min were removed and the time window was set at 0.2 s). The calibration method was multi-point calibration. The significant common peaks were labeled as mark peaks and the reference chromatogram fingerprint was generated with a mean value method. The similarity of the fingerprint data was represented by a correlation coefficient (similarity) and the higher similarity between the two samples resulted in a correlation coefficient value close to 1. The correlation coefficients of all chromatograms of 10 batches of *Ranae Oviductus* samples were calculated throughout the study and a correlation analysis was performed.

#### *2.6. Data Analysis*

Hierarchical clustering analysis (HCA) is a cluster analysis technique that reflects the similarities and differences between samples in the form of a hierarchical tree diagram [30,31]. This method is easier to observe than the complex raw data. Based on the clustering method between different groups and the Pearson correlation intervals, SPSS (version 25.0; SPSS Inc., Chicago, IL, USA) was used to group the different samples in this study.

Principal component analysis (PCA) is a classification method that uses dimensionality reduction techniques to simplify numerous original variables into several representative composite indicators [32,33]. According to the contribution rate of each comprehensive indicator, the information of the original data could be reflected when using appropriate numbers of principal components (PCs) [34]. In this study, PCA was performed using SPSS (version 25.0; SPSS Inc., Chicago, IL, USA) and the fractional scatter plot was interpreted by the relationship between PC1, PC2, and PC3 for visual analysis of the data matrix.

#### **3. Results and Discussion**

#### *3.1. Optimization of the RP-HPLC Conditions*

In order to improve the separation rate of the proteins in *Ranae Oviductus*, the *Ranae Oviductus* (S1) collected from the China Changbai mountain area were systematically investigated. The RP-HPLC chromatography method was optimized through the detection wavelength, separation column, flow rate and temperature. Three classical UV detection conditions were previously reported: 215 nm corresponding to the maximum absorption of peptide bonds; 254 nm corresponding to the maximum absorption of phenylalanine residues; and 280 nm corresponding to tyrosine and maximum absorption of tyrosine residues and tryptophan residues [35]. Figure 2a shows the UV absorption diagram of *Ranae Oviductus* using a diode array detector (DAD) with a wavelength range of 195–300 nm. The red region in the diagram indicated a larger absorption value. Although obvious solvent peaks around 215 nm were observed, the analysis of the core substance was not affected. The UV absorption diagram suggested that the separation effect at 215 nm was better than 254 nm and 280 nm.

Two types of columns (Agilent Zorbax SB-C18 column 250 × 4.6 mm, 5 μm, 80 Å and Agilent Zorbax 300SB-C8 column 250 × 4.6 mm, 5 μm, 300 Å) were used to examine the column effect on the protein separation of *Ranae Oviductus*. The results showed that the C8 column had a higher separation rate than the C18 column, which could be attributed to the large molecular weight of the proteins (Figure 2b). Therefore, the C8 column with a 300 Å pore diameter was selected for this study.

**Figure 2.** Optimization of reversed-phase high-performance liquid chromatography (RP-HPLC) separation method of the proteins from *Ranae Oviductus*. (**a**) The detection wavelength effect on the RP-HPLC chromatography of the *Ranae Oviductus* proteins. Diode array detector (DAD), 195–300 nm. (**b**) Column type effect on RP-HPLC chromatography of the *Ranae Oviductus* proteins (Agilent Zorbax 300SB-C8 column 250 × 4.6 mm, 5 μm, 300 Å and Agilent Zorbax SB-C18 column 250 × 4.6 mm, 5 μm, 80 Å). (**c**) Flow rate effect RP-HPLC chromatography of *Ranae Oviductus* (1.0 mL/min, 1.5 mL/min, 2.0 mL/min). (**d**) Temperature effect of RP-HPLC chromatography on the *Ranae Oviductus* proteins (40 ◦C, 45 ◦C, and 50 ◦C).

Since the flow rate of the mobile phase can affect the isolation efficiency, three flow rates (1.0, 1.5, 2.0 mL/min) were tested in this study. High flow rates showed that peaks overlapped (Figure 2c). The flow rate of 1.0 mL/min showed the highest separation effect and this, therefore, was chosen for the study.

On the other hand, the temperature played an important role in the RP-HPLC separation. Theoretically, high temperatures can increase the motion rate of proteins. In this study, three different temperatures (40, 45, and 50 ◦C) were investigated (Figure 2d). From the results, we could see that only one peak (t = 74.8 min) at 40 ◦C was observed, but two shoulder by shoulder peaks appeared at 45 and 50 ◦C. More proteins separated at 45 and 50 ◦C. Excessive temperature may damage the column's sorbent, therefore, 45 ◦C was selected as the optimum temperature.

#### *3.2. RP-HPLC Methodology Validation*

The accuracy of the RP-HPLC method was investigated through consecutive tests five times, using the same sample solution (*Ranae Oviductus* sample S1) within one day. The relative standard deviations (RSD) of the retention times and peak areas of the 12 common peaks were smaller than 2.02% and 4.23%, respectively. The repeatability was determined by injecting five separate sample solutions of the *Ranae Oviductus* sample. The results showed that the RSD of the retention time and peak area of the 12 common peaks were smaller than 2.96% and 5.62%, which suggested that the RP-HPLC method had good repeatability. The stability test was carried out at room temperature for 0, 2, 4, 8, 16 and 24 h. The RSD of the retention times and peak area were smaller than 2.62% and 5.22%. All tests indicated that the RP-HPLC method established in this work satisfied the requirements of protein fingerprinting analysis of *Ranae Oviductus*.

#### *3.3. HPLC Fingerprint of Ranae Oviductus Protein*

The protein chromatographic spectra of *Ranae Oviductus* collected from 10 sampling sites in Changbai Mountain area showed a similar profile using the optimized RP-HPLC method (Figure 3a). Based on the retention time, the 12 significant common-peaks were labeled with number 1 to 12. The 12 significant common-peaks in the *Ranae Oviductus* protein spectra were labeled as mark peaks according to the Chromatographic Fingerprint Similarity Evaluation System (2012 Edition) (Beijing, China). A reference fingerprint chromatographic spectrum of 10 batches of *Ranae Oviductus* was created (Figure 3b). The similarity was in the range of 0.779–0.980 (Table 2). The RSD value of the retention time of each common-peak was smaller than 4.70% and the RSD value of the relative peak area was smaller than 5.47%. This result pointed out that the common-peaks appearing in the chromatographic spectra were reliable in the analysis of *Ranae Oviductus*.


**Table 2.** Similarity values of 10 batches of *Ranae Oviductus* protein and reference chromatographic fingerprint spectra.

**Figure 3.** (**a**) HPLC fingerprint chromatographic spectra of 10 batches of *Ranae Oviductus* proteins. (**b**) The reference protein chromatographic spectra of *Ranae Oviductus*.

#### *3.4. Fingerprint Spectra Analysis*

The fingerprint spectra analysis of *Ranae Oviductus* and counterfeit products (bullfrog oviduct, toad oviduct and frog oviduct) were performed depending on the aforementioned optimized RP-HPLC method. The results showed a significant difference. By comparing Figure 4a,b, we could see that the significant common-peaks appeared at around 30 min in the reference fingerprint of *Ranae Oviductus*. In contrary, the counterfeit products, including the bullfrog oviduct, showed four common-peaks (peak A, peak B, peak C and peak D) in 0–30 min and the toad oviduct, showed three common-peaks (peak J, peak K, peak L) in the same time period. *Ranae Oviductus* showed 12 common-peaks (peak1-peak12) in 30–80 min, whereas, the bullfrog oviduct and toad oviduct only showed five common-peaks. The frog oviduct only showed four tiny common-peaks (Figure 4c), which was a finding consistent with a previous report. Huang, et al. [36] reported that the protein types in frog oviduct were less than that of other species by using the SDS-PAGE method. Both the protein extraction method and the RP-HPLC conditions were optimized according to the *Ranae Oviductus* sample, which may have not been adequate for frog oviduct. Through the comparison, we noticed that even the three counterfeit products had a significant difference (Figure 4d). The bullfrog oviduct (nine peaks) and toad oviduct (eight peaks) had more peaks than the frog oviduct (four peaks), but the retention time was different. Therefore, although *Rana chensinensis*, bullfrog, toad, and frog are similar amphibians, they are not the same species. Their genetic differences cause the expression of different types of proteins in the fallopian tubes, so that in RP-HPLC chromatographic spectra, they showed significant differences. Those differences can be used to identify *Ranae Oviductus* and counterfeit products.

**Figure 4.** The comparison of *Ranae Oviductus* and counterfeit products. (**a**) Comparison of the protein HPLC fingerprint chromatogram of *Ranae Oviductus* (Std) and protein HPLC fingerprint chromatograms of the bullfrog oviduct (B1, B2). (**b**) Comparison of the protein HPLC fingerprint chromatogram of *Ranae Oviductus* (Std) and the protein HPLC fingerprint chromatograms of the toad oviduct (T1, T2). (**c**) Comparison of the protein HPLC fingerprint chromatogram of *Ranae Oviductus* (Std) and the protein HPLC fingerprint chromatograms of the frog oviduct (F1, F2). (**d**) Comparison of the protein HPLC fingerprint chromatograms of three counterfeits (bullfrog oviduct, toad oviduct, frog oviduct) of *Ranae Oviductus*.

#### *3.5. Hierarchical Cluster Analysis (HCA)*

Hierarchical cluster analysis was carried out using the relative peak areas of the characteristic peaks of *Ranae Oviductus* and counterfeit products. The 16 samples were analyzed using SPSS 25.0 software and the results are shown in Figure 5a. Obviously, there were four clusters when the interval of abscissa was 10. Cluster I, Cluster II and Cluster III were composed of the bullfrog oviduct sample, frog oviduct sample and toad oviduct sample, respectively. Cluster IV referred to the 10 samples of *Ranae Oviductus* used in the establishment of the fingerprint. The sample S1 with low similarity to *Ranae Oviductus* also showed a low correlation in Cluster IV. When the interval of abscissa was 25, the sample was divided into two clusters, one authentic and another one counterfeit.

**Figure 5.** (**a**) The results of hierarchical cluster analysis of 10 batches of *Ranae Oveductus* and six counterfeit samples, (**b**) principal component analysis (PCA) score chart of 10 batches of *Ranae Oveductus* and six counterfeit samples in the first three principal components (PCs).

#### *3.6. Principal Component Analysis(PCA)*

As an effective data analysis technique, PCA has been used to study the classification of samples [37]. To directly reflect the difference between authentic and counterfeit products, 16 samples were used to perform the PCA analysis, based on the relative peak areas of the characteristic peaks of the samples. The variance contribution rates of the three main components (PC1, PC2, and PC3) were 31.34%, 27.61%, and 26.73%, respectively. The cumulative variance contribution rate of the three PCs was 85.68% and those variables reflected the majority of total information. To visualize the analysis results, the score charts were drawn using the three main components of PC1, PC2 and PC3 (Figure 5b). Four aggregation states are showed in Figure 5b. *Ranae Oviductus*, bullfrog oviduct, toad oviduct, and frog oviduct samples were classified in the a, b, c, and d regions, respectively. The *Ranae Oviductus* samples S1–10 could be classified in the same area (the a region), the bullfrog oviduct was classified in the b region, the toad oviduct was classified in the c region, and the frog oviduct was classified in the d region. The results were consistent with the HCA analysis, that both *Ranae Oviductus* and the counterfeit products were correctly classified. Comparing the similarity analysis with the HCA, PCA can provide a more visual comparison of the chromatograms.

#### **4. Conclusions**

This study used the RP-HPLC method and fingerprint technique to establish a chromatographic fingerprint of the proteins from *Ranae Oviductus*. Ten batches of *Ranae Oviductus* collected from the Changbai mountain area were used to analyze the protein components. The results showed 12 common-peaks in the reference fingerprint chromatographic spectrum. In combination with stoichiometry HCA and PCA, the results suggested that the method established in this work can satisfy the identification of *Ranae Oviductus* and counterfeit products. The method established in this work provides a promising approach for the identification of *Ranae Oviductus* and counterfeit products.

**Author Contributions:** Conceptualization, Y.W.; methodology, Y.W. and Y.G.; formal analysis, Y.G., Y.X., S.W. and H.G.; investigation, Y.G., Y.X., S.W., H.G. and M.L.; data curation, Y.G., S.W. and H.G.; writing—original draft preparation, Y.G., Y.X., S.W. and H.G.; writing—review and editing, Z.W., S.W. and Y.W.; visualization, Y.G., S.W., Z.W. and H.G.; supervision, Y.W.; project administration, S.W. and Y.W.; funding acquisition, Y.W.

**Funding:** This research was funded by Administration of Traditional Chinese Medicine of Jilin Province, grant number DBXM085-2018 and Jilin Bureau of Quality and Technical Supervision, grant number 2019037.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


**Sample Availability:** Not available.

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