Journal of Analytical Methods in Chemistry
Volume 2018 (2018), Article ID 5890973, 14 pages
https://doi.org/10.1155/2018/5890973

Research Article

Analysis of the HPLC Fingerprint and QAMS for Sanhuang Gypsum Soup

Yi Peng, Minghui Dong, Jing Zou, and Zhihui Liu

Department of Pharmacy, Nanjing University of Traditional Chinese Medicine Affiliated Hospital, Nanjing 210029, China

Correspondence should be addressed to Zhihui Liu; liuzh1008@126.com

Received 12 March 2018; Revised 5 May 2018; Accepted 9 May 2018; Published 2 July 2018

Academic Editor: Eduardo Dellacassa

Copyright © 2018 Yi Peng et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

A valid and encyclopaedic evaluation method for assessing the quality of Sanhuang Gypsum Soup (SGS) has been set up based on analysis of high-performance liquid chromatography (HPLC) fingerprint combined with the quantitative analysis of multicomponents by single marker (QAMS) method, hierarchical cluster analysis (HCA), and similarity analysis. 20 peaks of the common model were obtained and used for the similarity analysis and HCA analysis. Berberine was selected as an internal reference, and the relative correction factors of mangiferin, geniposide, liquiritin, epiberberine, coptisine, baicalin, palmatine, harpagosid, wogonoside, cinnamic acid, cinnamic aldehyde, baicalein, glycyrrhizic acid, and wogonin were established. The accuracy of quantitative analysis of multicomponents by the single-marker method was verified by comparing the contents of the fourteen components calculated by the external standard method with those of the quantitative analysis of multicomponents by the single-marker method. No significant difference was found in the quantitative results of the established quantitative analysis of multicomponents by a single-marker method and an external standard method. In summary, these methods were applied to evaluate the quality of SGS successfully. As a result, these evaluation methods have great potential to be widely used in the quality control of traditional Chinese medicines (TCM).

1. Introduction

Perspiration is a considerable physiological phenomenon to maintain and control body temperature. Excessive sweat secretion can cause armpit moisture, resulting in unpleasant body odour, embarrassment, and inconvenience [1, 2]. Hyperhidrosis is an excessive sweating disease which can bring severe psychological burden and affect the quality of life of patients negatively. There are a variety of medical treatments and surgery for treating primary hyperhidrosis. However, the side effects of these drugs include thirst, dry eyes, dizziness, drowsiness, constipation, and urinary retention, which limit the scope of their use. Surgical treatment is mainly applied to patients who are not suitable for the abovementioned methods. Surgery is more traumatized and risky than other treatments. Therefore, surgical operation should be as a second or third option [3]. There is still a paucity of effective nonsurgical therapies. With the development of modern society, the elimination of body odour is given more and more people’s attention; this article is about introducing Sanhuang gypsum soup (SGS) which is a significant antiperspirant. Through the use of classical Chinese medicine SGS to regulate the internal environment of the human body, it achieves a good antiperspirant effect with small side and remarkable effects, which make up for deficiency of some medicine and surgery. Every year, more than ten thousands of patients have benefited from SGS by reducing excessive perspiration symptoms. SGS is a hospital preparation of Jiangsu Provincial Hospital of Traditional Chinese Medicine, which consists of coptidis rhizoma, phellodendri chinensis cortex, scutellariae radix, scrophulariae radix, anemarrhenae rhizome, gardeniae fructus, cinnamomi cortex, glycyrrhizae radix et rhizoma preparata cum melle, and gypsum fibrosum. These herbs can be used for treating and could exhibit action on excessive perspiration through anti-inflammatory and antipyretic properties. Studies have shown that SGS has many chemical constituents such as mangiferin, geniposide, coptisine, wogonin, wogonoside, baicalein, baicalinin, and cinnamic aldehyde [4–13] in accordance with herbs and preparations known to be beneficial for the treatment of excessive perspiration through anti-inflammatory properties and so on.

Although the SGS is prepared as a prescription with the combination of these herbs in well-defined formulae, no standard quality control method for this product has been reported up to now. Since the effect of SGS might result from the synergy of multiple components, a reliable, sensitive, and uncomplicated quantitative method based on the diverse constituents is need to be developed.

Our findings have established an HPLC method to evaluate the quality of SGS comprehensively. Due to the variety of components of traditional Chinese medicine preparations, any one of the active ingredients cannot reflect the overall curative effect of traditional Chinese medicine. Therefore, a comprehensive macroscopic analysis will become an inevitable trend. Chromatographic fingerprint analysis with integrated, macroscopic, and “fuzzy” nonlinear characteristics is more adapted to the traditional Chinese medicine theory needs. Under the premise of efficacy, toxicology, and clinical trials which have confirmed safety and efficacy of preparation, we can not only verify the authenticity of the preparation but also determine whether the stability of the quality exists or not along with a practical fingerprint. Unlike the content determination, the fingerprint can provide more informative and useful message than the determination of any single component. The US Food and Drug Administration (FDA) allows applicants to provide product chromatographic fingerprinting information in the phytomedical guidance (Draft for Comment). British Herbal Codex, Ayurvedic Codex, the Canadian Society of Medicinal and Aromatic Plants [14], and the German Society of Medicinal Plants [15] also accept chromatographic fingerprint. One of the first measures that China’s State Drug Administration has taken to strengthen the supervision of traditional Chinese medicine injections requires the research on the fingerprint of injections, which has taken into account its necessity and feasibility. It is accepted that preparation of acceptable quality can be exerted on its drug efficacy, what really matters is establishing an accurate and easy method.

Previously, our laboratory has researched on the fingerprints of the existing preparations which have been applied in the control of preparation quality. Also, to make up for the limitations of fingerprint that cannot be quantified accurately, a QAMS method using berberine as the standard was developed and validated for the simultaneous quantitative of 14 components [16]. This strategy can not only reduce the cost of the experiment and time of detection but also be independent of the availability of all the target ingredients [15]. To our knowledge, quality control of herb extracts and botanical ingredient by QAMS have been included both in USP 33-NF and in Ch.P.2010 edition (volume I). Our results showed that no significant difference was found in the results between our established QAMS method and the external standard method. No one has yet studied the fingerprints of SGS; this article first established the SGS fingerprinting method and also used the QAMS method to measure the preparation of 14 kinds of pharmacodynamics components. This method could potentially be applied for the identification of qualitative and quantitative quality of SGS.

This HPLC fingerprint method, therefore, provides a comprehensive platform for quality evaluation of SGS with more chemical information. The combination of HCA and similarity analysis presents the differences and similarities of the HPLC fingerprints. In the meantime, QAMS method was adopted to quantify the main active components by comparing with the external standard method (ESM) in all the SGS samples. Our findings offer a new routine for assessing the quality of TCM.

2. Materials and Methods

2.1. Chemicals and Reagents

Analysis was applied on three different HPLC systems, including (a) Agilent 1100 series with vacuum degasser (G1322A), quaternary pump (G1311A), autosampler (G1316A), and a ChemStation Workstation with VWD detector; (b) Agilent 1260 series with DAD detector and Agilent ChemStation Workstation; and (c) Waters 2695-2996 series with 2998PDA detector and empower workstation. The chromatographic separation was performed on an AmethyC₁₈ (4.6 mm × 250 mm, 5 μm) column, Agilent C₁₈ (4.6 mm × 250 mm, 5 μm) column, and HedraC₁₈ (4.6 mm × 250 mm, 5 μm) column.

The SPSS software (Edition 2.0) was used for conducting cluster analysis.

BP-211D electronic analytical balance (Germany Sartorius Company) was used to weigh the drugs. Sonicator (SK6200H, Shanghai Branch guided ultrasound instrument Co., Ltd.) was used to help dissolve the sample.

2.2. Materials

The batch numbers and origins of eight qualified Chinese herbal pieces of decoction are shown in Table 1. All pieces were purchased from Anhui Concord Pharmaceutical Pieces Co., Ltd. and identified by Professor Zhihui Liu of Nanjing University of Traditional Chinese Medicine.

Table 1: Species and geographical locations of eight Chinese herbal pieces in SGS.

Botanical name
Family
Collection site
Coordinates
Voucher ID

Coptis chinensis Franch.
Ranunculaceae
Sichuan
N30°15′49.6902″
S102°48′19.71″
16121204

Phellodendron chinense Schneid.
Rutaceae
Sichuan
N30°15′49.6902″
S102°48′19.71″
1508120316060500

Scutellaria baicalensis Georgi
Labidae
Heilongjiang
N47°7′17.9292″
S128°44′17.6316″
160401

Scrophularia ningpoensis Hemsl.
Scrophulariaceae
Yunnan
N24°28′31.0254″
S101°20′35.1816″
16060501

Anemarrhena asphodeloides Bge.
Liliaceae
Jiangsu
N33°8′24.6186″
S119°47′20.13″
16032208

Gardenia jasminoides Ellis
Rubiaceae
Jiangxi
N27°5′14.841″
S114°54′15.1956″
16122107

Cinnamomum cassia Presl.
Aceraceae
Sichuan
N30° 15′ 49.6902″
S102° 48′ 19.71″
16112519

Glycyrrhiza uralensis Fisch.
Legume
Neimenggu
N43°22′41.5914″
S115°3′34.1316″
16021710

Gypsum fibrosum
Monoclinic crystal system
Hunan
N27°37′31.0794″
S111°51′24.6924″
16120420

Fifteen batches of Sanhuang Gypsum Soup were provided by the Department of Pharmacy of Jiangsu Provincial Hospital. Their batch numbers were S1 (1707010), S2 (1704006), S3 (1712019), S4 (1711016), S5 (1704005), S6 (1703004), S7 (1711013), S8 (1711017), S9 (1705007), S10 (1704003), S11 (1704002), S12 (1704001), and S13 (1702015). Each single piece preparations and its negative preparations are made by our laboratory as per the preparation standard process.

2.3. Chemical Reagents and Standards

Mangiferin, geniposide, liquiritin, epiberberine, coptisine, baicalin, palmatine, berberine, harpagosid, wogonoside, cinnamic acid, cinnamic aldehyde, baicalein, glycyrrhizic acid, and wogonin were all supplied by Chengdu Mansi Biotechnology Co., Ltd. The purity of each ingredient was greater than 98% as determined by HPLC. Acetonitrile of HPLC grade and formic acid of analytical grade were purchased from Merck (Darmstadt, Germany) and Roe Scientific Inc. (USA). A Milli-Q water (Millipore, Inc., USA) purification system was applied to purify water for the HPLC analysis.

2.4. Preparation of the Sample Solution

The sample solution of SGS was precisely absorbed (5 ml) and immersed in 25 mL volumetric flask with methanol. Additional methanol was added to compensate the weight loss after ultrasonic extraction for 30 min. All solutions were filtered through 0.45 μm filter membranes before being injected into the HPLC system precisely.

2.5. Reference Solution Preparation

A mixed stock solution containing reference standards was prepared by dissolving weighed samples of each compound in methanol accurately. Then, the stock solutions were diluted to establish the calibration curves based on six appropriate concentrations with the ranges of 2.80–88.70 μg·ml⁻¹ for mangiferin, 14.80–472.90 μg·ml⁻¹ for geniposide, 3.20–101.00 μg·ml⁻¹ for liquiritin, 1.40–44.30 μg·ml⁻¹ for epiberberine, 6.40–204.10 μg·ml⁻¹ for coptisine, 19.80–632.50 μg·ml⁻¹ for baicalin, 1.80–56.80 μg·ml⁻¹ for palmatine, 15.30–488.40 μg·ml⁻¹ for berberine, 2.60–82.60 μg·ml⁻¹ for harpagosid, 4.60–145.82 μg·ml⁻¹ for wogonoside, 0.30–9.51 μg·ml⁻¹ for cinnamic acid, 0.20–6.34 μg·ml⁻¹ for cinnamic aldehyde, 0.50–15.85 μg·ml⁻¹ for baicalein, 1.10–34.00 μg·ml⁻¹ for glycyrrhizic acid, and 0.30–9.51 μg·ml⁻¹ for wogonin.

2.6. Chromatographic Procedures

Analytes were separated on a reverse phase C₁₈ column (Amethyl-ODS-2 C₁₈ column, 250 mm ∗ 4.6 mm ∗ 5 μm).

Mobile phase consists of 0.1% phosphoric acid (A)-acetonitrile (B), gradient elution program was as follows: 0∼2 min, 12% B; 2∼7 min, 12%∼20% B; 7∼17 min, 20%∼25% B; 17∼25 min, 25%∼32% B; 25∼32 min, 32%∼35% B; 32∼45 min, 35%∼44% B; 45∼50 min, 44%∼45% B; 50∼55 min, 45%∼50% B; 55∼56 min, 50% B; 56∼61 min, 12% B. Flow rate: 0.8 mL·min⁻¹; column temperature: 35°C; injection volume: 10 μL; UV detection wavelength: 250 nm. On the basis of chromatographic conditions, all the components had good resolution.

2.7. Data Analysis

The data were analyzed and evaluated by Similarity Evaluation System for chromatographic fingerprint of TCM (Version 2004 A) which was recommended by the SFDA of China for evaluating similarities of chromatographic profiles of TCM. The similarity among different chromatograms was determined by calculating the correlative coefficient or cosine value of the vectorial angle [17–19]. HCA was carried out by calculating Squared Euclidean distance to distinguish preparation of different batches using SPSS. At the same time, we used the external standard method (ESM) and QAMS to calculate the 15 active components in 13 batches of SGS, respectively, to verify the feasibility of QAMS.

3. Results and Discussion

3.1. Chromatograph Optimization

At present, there are no single liquid phase conditions that can divide 15 components of SGS with good resolution. As the ingredients of SGS are very intricate, it is critical to establish a favorable mobile phase system, gradient elution system, and detection wavelength to obtain efficient separation of the numerous target components. The suitable ingredient of the HPLC method was investigated by checking peak resolution and the peak purity of SGS. In this case, some different mobile phases were tested which were acetonitrile-water, methanol-water, methanol-water containing phosphoric acid or formic acid at different concentrations, acetonitrile-water with acetic acid, formic acid, and phosphoric acid at different concentrations. Experimental results show that acetonitrile-water containing 0.2% phosphoric acid system produced sharp and symmetrical chromatographic peak shapes, good separation, and prevented the peak tailing. Chromatogram with the maximum number of peaks also relies on best conditions for preparation of sample solution. On the basis of the investigation of different solvent and ultrasonic time, it can be concluded that samples are dissolved in methanol and ultrasound 30 minutes; we can get better resolution and reproducibility of fingerprint chromatograms under the conditions of Section 2.6. Under the above chromatographic conditions, all the components were well separated (Figure 1).

(a)

(b)

(c)

(d)

(e)

(f)

(g)

(h)

(i)

(j)

(k)

Figure 1: (a) Mixed standard solution, (b) negative sample without coptidis rhizoma, (c) negative sample without scrophulariae radix, (d) negative sample without anemarrhenae rhizome, (e) negative sample without gardeniae fructus, (f) negative sample without coptidis rhizoma and phellodendri chinensis cortex, (g) negative sample without glycyrrhizae radix et rhizoma preparata cum melle, (h) negative sample without cinnamomi cortex, (i) negative sample without phellodendri chinensis cortex, (j) negative sample without scutellariae radix, and (k) SGS sample. 1, mangiferin; 2, geniposide; 3, liquiritin; 4, epiberberine; 5, coptisine; 6, baicalin; 7, palmatine; 8, berberine; 9, harpagosid; 10, wogonoside; 10, cinnamic acid; 11, cinnamic aldehyde; 12, baicalein; 13, glycyrrhizic acid; and 14, wogonin.

3.2. Method Validation

3.2.1. Linearity

A mixed solution containing all the reference substances were prepared and diluted in series with methanol to obtain six different concentrations. The different concentration of the mixed solution was used for constructing the reference curve. As shown in Table 2, good calibration curves of 15 compounds were obtained, and high correlation coefficient values (R² > 0.999) were shown with good linearity at a wide range relatively. In response to sample concentration, the peak area of the analyte is determined by least squares linear regression to obtain a linear equation.

Table 2: Standard curves of fifteen kinds of reference components.

Compounds
Regression equations
Linear ranges (μg·mL⁻¹)
R²

Mangiferin
y = 29.897x + 30.359
2.80–88.70
0.9998

Geniposide
y = 11.306x − 40.123
14.80–472.90
0.9997

Liquiritin
y = 6.9865x − 5.2633
3.20–101.00
1.0000

Epiberberine
y = 23.477x − 12.998
1.40–44.30
0.9998

Coptisine
y = 11.677x − 31.945
6.40–204.10
0.9998

Baicalin
y = 17.312x − 189.17
19.80–632.50
0.9999

Palmatine
y = 39.570x − 21.105
1.80–56.80
0.9999

Berberine
y = 38.357x + 108.6
15.30–488.40
0.9999

Harpagosid
y = 9.5715x + 8.4144
2.60–82.60
0.9998

Wogonoside
y = 16.462x + 11.105
4.60–145.82
0.9999

Cinnamic acid
y = 32.7x + 0.4639
0.30–9.51
0.9998

Cinnamic aldehyde
y = 15.523x − 0.1567
0.20–6.34
0.9998

Baicalein
y = 25.996x + 3.789
0.50–15.85
0.9998

Glycyrrhizic acid
y = 7.5138x + 1.333
1.10–34.00
0.9999

Wogonin
y = 21.652x + 0.8509
0.30–9.51
1.0000

3.2.2. Precision, Stability, Repeatability, and Recovery

The same mixed standard solution of 10 µl was injected for six consecutive times under chromatographic conditions, and their RSDs were calculated. The RSD of mangiferin, geniposide, liquiritin, epiberberine, coptisine, baicalin, palmatine, berberine, harpagosid, wogonoside, cinnamic acid, cinnamic aldehyde, baicalein, glycyrrhizic acid, and wogonin was 1.94%, 0.72%, 0.88%, 0.54%, 0.62%, 0.97%, 0.93%, 1.35%, 0.98%, 1.33%, 0.67%, 1.40%, 1.08%, 0.96%, and 1.49% which indicated that the developed method had a good precision.

The stability of the sample solutions was analyzed at 0, 2, 4, 8, 12, and 24 h at room temperature. It was found that the sample solutions were stable within 24 h (RSD ≤ 5.0%).

To confirm the repeatability of the method, six independently prepared solutions from the same batch were analyzed. The RSD values of the peak area was 0.37%, 0.31%, 1.52%, 0.72%, 1.00%, 0.20%, 0.71%, 0.18%, 0.88%, 0.50%, 3.02%, 3.65%, 2.30%, 1.68%, and 3.23%, respectively. The results indicated the method is reproducible.

The recovery was performed by adding a known amount of individual standards into a certain amount of the SGS sample. The mixture was extracted and analyzed by using the method mentioned above. The average recoveries of 6 samples are shown in Table 3. The results show that the method is accurate. The recoveries of the 15 compounds which are shown in Table 3 ranged from 70.08% to 111.45% with RSDs ≤ 5.0%.

Table 3: The results of recovery of fifteen components in samples ().

Compound
Original (mg)
Added amount (mg)
Detected amount (mg)
Recovery (%)
RSD (%)

Mangiferin
0.0241
0.0241
0.0478
93.96
1.18

Geniposide
0.1036
0.1036
0.2032
99.58
2.60

Liquiritin
0.0198
0.0198
0.0380
96.11
3.42

Epiberberine
0.0073
0.0073
0.0142
103.46
3.61

Coptisine
0.0223
0.0223
0.0438
110.19
3.16

Baicalin
0.1226
0.1226
0.2139
81.82
2.61

Palmatine
0.0104
0.0104
0.0200
97.21
2.28

Berberine
0.0748
0.0748
0.1539
101.87
5.31

Harpagosid
0.0212
0.0212
0.0433
100.01
3.56

Wogonoside
0.0307
0.0307
0.0620
99.81
3.33

Cinnamic acid
0.0023
0.0023
0.0048
111.45
2.38

Cinnamic aldehyde
0.0023
0.0023
0.0040
70.08
5.00

Baicalein
0.0048
0.0048
0.0095
79.84
3.73

Glycyrrhizic acid
0.0079
0.0079
0.0155
94.08
2.52

Wogonin
0.0028
0.0028
0.0056
98.34
4.19

3.3. HPLC Fingerprint and Similarity Analysis

Thirteen batches of samples were prepared according to Section 2.5, and 10 μL was injected into the HPLC system according to the chromatographic conditions given under Section 2.6, and then the chromatograms were recorded and entered into the similarity analysis software. We selected S (1) as the reference chromatogram, the utilization of the average correlation coefficient method of 13 batches of samples for multipoint correction, time window width is set to 0.5, while the establishment of a common model is to generate a control fingerprinting SGS, the antithesis fingerprint chromatogram was shown in Figure 2. Fingerprint chromatograms of 13 batches of SGS can be seen in Figure 3. As compared with the reference fingerprint chromatograms, the similarities of 13 batches of samples shown in Table 4, and the results are all above 0.95. On the basis of these results, we concluded that SGS between different batches are of good consistency and in line with the relevant requirements of the fingerprints. Palmatine is the main active ingredient of coptidis rhizoma; the corresponding peaks have favorable resolution, and the retention time is stable and moderate. Therefore, we selected palmatine (no. 11 peak) as the reference peak and calculated the relative retention time of the other common peaks. We can see that the retention time of the common peak is stable. According to the retention time of each fingerprint, a total of 20 common peaks were identified while 14 of them were determined. However, it should be pointed out that the chemical property of cinnamic aldehyde is very unstable due to its alkene structure of the molecule which has poor stability when exposed to light and oxygen, so it is not within the category of the common peaks [20]. This can be in accordance with S11 without the peak of cinnamic aldehyde. To gain better understanding of ascription of common peaks, reference standards and single TCM pieces were used. The peaks 2, 3, 6, 8, 9, 10, 11, 12, 13, 16, 17, 18, 19, and 20 were identified as mangiferin, geniposide, liquiritin, epiberberine, coptisine, baicalin, palmatine, berberine, harpagosid, wogonoside, cinnamic acid, cinnamic aldehyde, baicalein, glycyrrhizic acid, and wogonin, respectively (Figure 4). The peak 1 belongs to phellodendri chinensis cortex. The peak 4 belongs to both phellodendri chinensis cortex and coptidis rhizoma. The peaks 5, 14, and 15 belong to scutellariae radix. The peak 7 belongs to scrophulariae radix.

Figure 2: Antithesis fingerprint chromatogram of SGS.

Figure 3: Fingerprint chromatograms of 13 batches of SGS.

Table 4: Similarities of 13 batches SGS.

S1
S2
S3
S4
S5
S6
S7
S8
S9
S10
S11
S12
S13
R

S1
1
0.984
0.984
0.982
0.989
0.981
0.991
0.99
0.978
0.984
0.982
0.987
0.978
0.994

S2
0.984
1
0.975
0.978
0.985
0.986
0.985
0.995
0.997
0.987
0.979
0.973
0.994
0.994

S3
0.984
0.975
1
0.991
0.987
0.978
0.974
0.974
0.964
0.983
0.995
0.995
0.959
0.991

S4
0.982
0.978
0.991
1
0.991
0.99
0.98
0.975
0.972
0.99
0.987
0.988
0.96
0.992

S5
0.989
0.985
0.987
0.991
1
0.985
0.992
0.989
0.98
0.985
0.988
0.988
0.975
0.996

S6
0.981
0.986
0.978
0.99
0.985
1
0.983
0.982
0.985
0.993
0.972
0.972
0.974
0.992

S7
0.991
0.985
0.974
0.98
0.992
0.983
1
0.992
0.983
0.98
0.975
0.979
0.983
0.992

S8
0.99
0.995
0.974
0.975
0.989
0.982
0.992
1
0.994
0.982
0.977
0.975
0.993
0.994

S9
0.978
0.997
0.964
0.972
0.98
0.985
0.983
0.994
1
0.985
0.969
0.963
0.994
0.989

S10
0.984
0.987
0.983
0.99
0.985
0.993
0.98
0.982
0.985
1
0.977
0.977
0.973
0.993

S11
0.982
0.979
0.995
0.987
0.988
0.972
0.975
0.977
0.969
0.977
1
0.994
0.966
0.99

S12
0.987
0.973
0.995
0.988
0.988
0.972
0.979
0.975
0.963
0.977
0.994
1
0.962
0.99

S13
0.978
0.994
0.959
0.96
0.975
0.974
0.983
0.993
0.994
0.973
0.966
0.962
1
0.985

R
0.994
0.994
0.991
0.992
0.996
0.992
0.992
0.994
0.989
0.993
0.99
0.99
0.985
1

Figure 4: Comparison of single TCM pieces and SGS sample.

3.4. Hierarchical Cluster Analysis

The 13 ∗ 20 matrices were obtained from 20 common peak areas of fingerprints of 13 batches of SGS. The cluster analysis was performed by using spss 2.0 software. The Euclidean distance was chosen as the measure of the distance between groups. The results are shown in Figure 5. S3, S4, S5, and S12 batches of samples are divided into a category; the remaining batches are divided into another classification, which indicates that there are differences in the content of the components in the samples prepared from different raw material TCM pieces. And it suggested that HCA was a valid method for the identification of the source of TCM pieces.

Figure 5: Clustering analysis graph of 13 SGS samples.

3.5. Quantitative Analysis of Multicomponents by a Single Marker (QAMS)

It is well established that many variations of experimental conditions, such as concentrations of standard, detector, and peak measurement parameters, would extremely influence the RCFs. Accordingly, the accuracy of RCFs may affect the final analysis results. Nevertheless, RCFs, which was calculated by linear-regression equation in the experiment, was considered to be accurate and stable [21, 22]. The RCFs were calculated using the calibration curves as follows:

The content of the measured component was calculated as follows:

is the ratio of the slope of internal standard reference calibration equations; is the ratio of the slope of measured component calibration equations; is the peak area of the measured component; is the peak area of the internal standard reference.

We investigated the influence of different instruments and different columns on the RCF values, and results are shown in Table 5 which illustrated RCF values had good repeatability on different chromatographic systems and different columns.

Table 5: RCFs of berberine to mangiferin, geniposide, liquiritin, epiberberine, coptisine, baicalin, palmatine, harpagosid, wogonoside, cinnamic acid, cinnamic aldehyde, baicalein, glycyrrhizic acid, and wogonin on different instruments and different columns.

Instrument
Column
Mangiferin
Geniposide
Liquiritin
Epiberberine
Coptisine
Baicalin
Palmatine
Harpagosid
Wogonoside
Cinnamic acid
Cinnamic aldehyde
Baicalein
Glycyrrhizic acid
Wogonin

Waters2695-2998
Amethy
0.7632
0.3112
0.1888
0.6033
0.3144
0.4421
1.0451
0.2561
0.4321
0.8611
0.4043
0.6811
0.1993
0.5532

Hedra
0.7794
0.3008
0.1791
0.6215
0.3211
0.4351
1.0733
0.2671
0.4411
0.8835
0.4156
0.6632
0.1911
0.5783

Agilent
0.7794
0.2948
0.1821
0.6121
0.3044
0.4513
1.0316
0.2495
0.4292
0.8525
0.4047
0.6777
0.1959
0.5645

Agilent1100
Amethy
0.7553
0.3138
0.1813
0.5988
0.3198
0.4579
1.0651
0.2355
0.4351
0.8421
0.4255
0.6843
0.2021
0.5547

Hedra
0.7421
0.3097
0.1923
0.5899
0.3176
0.4621
1.0688
0.2466
0.4284
0.8311
0.4322
0.6731
0.2124
0.5832

Agilent
0.7342
0.3201
0.1799
0.6031
0.3021
0.4633
1.0803
0.2611
0.4511
0.8941
0.4167
0.6864
0.2145
0.5401

Mean

0.7589
0.3084
0.1839
0.6048
0.3132
0.4520
1.0607
0.2527
0.4362
0.8607
0.4165
0.6776
0.2025
0.5623

RSD (%)

2.48
2.97
2.91
1.80
2.58
2.52
1.75
4.45
1.98
2.81
2.67
1.26
4.56
2.90

In this paper, we selected cheap, readily available, and chemically stable berberine as an internal reference standard for the quantitative determination of other active components. In addition to that, berberine is the main active ingredient of phellodendri chinensis cortex and coptidis rhizoma, so this study eventually takes it as an internal reference standard. The relative retention time has been used to locate target chromatographic peaks.

where is the retention time of internal standard reference and is the retention time of measured component.

The internal reference is berberine; the relative retentions between the other target peaks and berberine were obtained in different columns and HPLC instruments. Results are shown in Table 6. The results showed that their RSDs ≤ 5% and no interference with other components; the relative retention time can be applied to locate the peak component of the analytes.

Table 6: Rentention time (min) of berberine to mangiferin, geniposide, liquiritin, epiberberine, coptisine, baicalin, palmatine, harpagosid, wogonoside, cinnamic acid, cinnamic aldehyde, baicalein, glycyrrhizic acid, and wogonin on different instruments and different columns.

Instrument
Column
Mangiferin
Geniposide
Liquiritin
Epiberberine
Coptisine
Baicalin
Palmatine
Harpagosid
Wogonoside
Cinnamic acid
Cinnamic aldehyde
Baicalein
Glycyrrhizic acid
Wogonin

Waters2695-2998
Amethy
0.38
0.40
0.58
0.80
0.83
0.92
0.97
1.04
1.14
1.17
1.34
1.41
1.60
1.81

Hedra
0.41
0.43
0.62
0.82
0.84
0.96
0.97
1.06
1.11
1.18
1.28
1.54
1.59
2.02

Agilent
0.39
0.41
0.60
0.81
0.83
0.94
0.97
1.05
1.13
1.17
1.30
1.48
1.60
1.91

Agilent1100
Amethy
0.36
0.39
0.57
0.75
0.81
0.90
0.95
1.02
1.13
1.16
1.30
1.38
1.59
1.79

Hedra
0.37
0.41
0.58
0.77
0.83
0.92
0.96
1.05
1.12
1.16
1.33
1.40
1.58
1.78

Agilent
0.40
0.42
0.60
0.82
0.85
0.94
0.99
1.06
1.16
1.19
1.36
1.43
1.62
1.83

Mean

0.39
0.41
0.59
0.79
0.83
0.93
0.97
1.05
1.13
1.17
1.32
1.44
1.60
1.86

RSD (%)

5.00
3.03
3.38
4.03
2.76
2.66
1.90
1.85
2.32
1.77
2.95
4.33
1.95
5.00

We measured the multicomponent content of 13 batches SGS (Figure 6); the results showed that there were significant differences in some contents of 15 ingredients, such as cinnamic aldehyde and baicalein, which indicated that only a few ingredients of the standard determination of content could not control the quality of SGS effectively. It is necessary to use multiple active ingredients as index components to control the quality of TCM preparations more comprehensively.

Figure 6: The contents of 15 active components in 13 batches of SGS.

To validate the difference between ESM and QAMS method using RCFs, 13 SGS samples were analyzed for their active ingredients. The calculated results are shown in Table 7. Standard method difference (SMD) is calculated according to the following equation:

where and represent the concentrations of an analyte assayed by the external standard method and QAMS method, respectively [23]. All the values of standard deviation (SMD < 0.05) revealed that there were no significant differences between ESM and QAMS methods of all SGS samples.

Table 7: Comparison of the results from the ESM and QAMS (μg·ml⁻¹).

Batch number
Berberine
Mangiferin
Geniposide
Liquiritin
Epiberberine
Coptisine
Baicalin
Palmatine

ESM
QAMS
ESM
QAMS
ESM
QAMS
ESM
QAMS
ESM
QAMS
ESM
QAMS
ESM
QAMS
ESM

1
109.5341
40.2024
40.2261
181.4930
189.7332
23.0219
24.3703
6.3113
7.0281
46.8326
50.7789
134.5759
148.9816
11.4799
12.3100

2
89.2249
37.5741
37.7510
179.5150
188.7602
15.1217
16.3549
5.8212
6.5595
40.4232
44.4416
140.9748
156.3753
10.5081
11.3749

3
129.1133
35.8398
35.6103
157.0895
164.0831
15.6869
16.7843
7.5026
8.2207
54.0515
57.9725
163.0149
177.5168
12.7851
13.5988

4
124.5509
39.7362
39.6241
177.6354
185.2223
16.2344
17.3568
8.0797
8.8171
57.6934
61.7406
178.8141
193.8060
13.3434
14.1801

5
131.7465
42.8953
42.8017
215.0841
223.2552
13.4517
14.4941
8.1313
8.8596
58.7696
62.7683
177.6743
192.4197
13.8791
14.7108

6
91.8581
33.9407
33.9713
167.7467
176.4659
13.4688
14.6373
8.0163
8.8171
41.8712
45.8975
161.3843
177.2857
13.0916
14.0284

7
93.6830
33.7007
33.7037
184.5859
193.7133
12.6430
13.7785
5.6230
6.3466
40.0668
44.0134
121.2770
135.8693
10.4254
11.2738

8
83.4633
28.7922
28.7534
161.0843
170.0976
11.7671
12.9197
4.9025
5.6224
37.9355
41.9581
118.3847
133.3277
9.5326
10.3893

9
87.8692
35.7417
35.8779
191.4261
201.1430
15.2532
16.4980
5.3645
6.0910
47.1242
51.3784
151.7083
167.5237
9.7197
10.5662

10
96.1076
33.3683
33.3358
163.7588
172.1319
13.7647
14.9235
5.8754
6.6021
44.4223
48.4666
171.5295
187.5098
10.4331
11.2738

11
81.0647
21.1692
20.8931
96.3176
103.2304
10.2344
11.3452
3.7042
4.3872
33.2648
37.1624
93.3769
107.5653
7.3989
8.1907

12
127.4969
35.4701
35.2424
160.0752
167.1788
18.2031
19.3607
6.7088
7.4114
56.9690
60.9699
139.2935
153.3139
11.8422
12.6385

13
66.2826
26.8813
27.0141
161.2528
171.6896
10.7070
11.9177
4.4526
5.1965
32.0308
36.1347
95.5600
110.5690
7.9011
8.7719

value

1.0000
0.9990
1.0000
1.0000
1.0000
1.0000
1.0000

SMD

−0.14%
4.84%
5.00%
4.40%
3.88%
4.64%
5.00%

Harpagosid
Wogonoside
Cinnamic acid
Cinnamic aldehyde
Baicalein
Glycyrrhizic acid
Wogonin

QAMS
ESM
QAMS
ESM
QAMS
ESM
QAMS
ESM
QAMS
ESM
QAMS
ESM
QAMS
ESM

14.2582
13.7492
41.5099
41.9147
4.3225
4.4343
10.1104
10.3781
3.8998
3.8544
10.7680
10.8733
2.8363
2.8704

14.3794
13.9581
41.7443
42.4007
3.3197
3.4251
8.1171
8.3811
4.2131
4.2006
10.3196
10.4741
3.3573
3.4246

13.6995
13.1223
42.3230
42.5829
3.0224
3.0887
8.5102
8.7032
5.2322
5.2008
11.9814
12.0711
3.6155
3.6556

14.3017
13.7492
48.7639
49.2042
3.6181
3.7003
10.8341
11.0868
6.0932
6.0856
12.1021
12.2042
4.6062
4.6716

17.3874
16.8835
45.4335
45.7417
3.2033
3.2722
12.8653
13.1482
6.2136
6.2010
10.8139
10.8733
4.1144
4.1636

15.7097
15.3163
48.3223
49.1435
3.4117
3.5168
6.2494
6.4485
4.9259
4.9315
9.4250
9.5424
3.8532
3.9327

12.4737
11.9730
36.3218
36.7513
2.9684
3.0581
7.2536
7.4792
3.2858
3.2390
11.1098
11.2726
2.7346
2.7780

11.7217
11.2417
35.2517
35.7794
2.6324
2.7217
9.3460
9.6695
3.3857
3.3544
9.5254
9.6755
2.8142
2.8704

14.9799
14.5850
41.7833
42.4614
3.9107
4.0367
7.6140
7.8657
4.4720
4.4699
10.9594
11.1395
4.2506
4.3483

16.8469
16.4655
46.1440
46.8351
2.4359
2.5076
5.3190
5.4822
4.5214
4.5084
12.1523
12.3373
4.0377
4.1174

8.5808
8.0029
24.3588
24.5414
1.9207
1.9878
4.0460
4.1938
2.0815
2.0080
8.7446
8.8770
3.2131
3.2861

11.9582
11.3462
35.5964
35.7186
3.8293
3.9144
9.8943
10.1205
3.9137
3.8544
12.1083
12.2042
3.5242
3.5632

9.5187
9.0477
27.3810
27.8824
2.6982
2.8135
5.8692
6.1264
3.3202
3.3159
10.0833
10.3410
2.9233
3.0090

1.0000
1.0000
1.0000
1.0000
1.0000
0.9990
1.0000

−4.00%
1.15%
2.84%
2.92%
−0.80%
1.28%
1.75%

4. Conclusion

On the basis of these results, we concluded that HPLC fingerprint method based on chemical constituents profiling was an effective and stable tool, and QAMS method was feasible to quantify the active compounds by RCFs for evaluating the quality of SGS. Along with similarity analysis and HCA of synthesis, the quality of SGS would be evaluated and better identified comprehensively. This method could potentially be applied in the quality control of TCM.

Data Availability

The datasets used or analyzed during the current study are available from the corresponding author on reasonable request. All data generated or analyzed during this study are included in this submitted manuscript.

Disclosure

Minghui Dong is the co-first author.

Conflicts of Interest

The authors declare no conflicts of interest.

Acknowledgments

This work was supported by the advantages discipline of Universities in Jiangsu Province (PATA2014).

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