Promotion of quality standard of herbal medicine by constituent removing and adding

ABSTRACT To identify major active constituents and measure their levels in a typical medicinal herb–_Rhizoma coptidis_, we applied the concept of removing and adding, taking inspiration from

functional genetic methods. As this herb has bacteriostatic properties and is used to treat bacterial diarrhea, we examined the effects of individual constituents (berberine, palmatine,

coptisine, epiberberine, jateorrhizine and columbamine) on the growth of _Shigella dysenteriae_ with microcalorimetry. The removing and adding procedures revealed that berberine and

coptisine were the main antibacterial constituents of _R. coptidis_, with bacteriostatic activities of 54.10% and 39.75%, respectively. The relative levels of berberine and coptisine in _R.

coptidis_ were 8.08%–31.92% and 4.05%–14.45%, respectively. On the basis of whole effect, the method of constituents removing and adding, coupled with a bioassay, is a useful strategy to

identify the active constituents and measure their levels in herbal medicines, which may provide reference to other natural products. SIMILAR CONTENT BEING VIEWED BY OTHERS EXPLORING THE

ANTIOXIDANT AND ANTIMICROBIAL PROPERTIES OF FIVE INDIGENOUS KENYAN PLANTS USED IN TRADITIONAL MEDICINE Article Open access 09 January 2025 PHYTOCHEMICAL SCREENING, UPLC ANALYSIS, EVALUATION

OF SYNERGISTIC ANTIOXIDANT AND ANTIBACTERIAL EFFICACY OF THREE MEDICINAL PLANTS USED IN KINSHASA, D.R. CONGO Article Open access 24 March 2025 PHYTOCHEMICAL PROFILING, ANTIOXIDANT POTENTIAL,

AND UHPLC-HRMS ANALYSIS OF _PHLOMIS_ GENUS AERIAL PARTS FOR THERAPEUTIC APPLICATIONS Article Open access 25 February 2025 INTRODUCTION The quality of a medicine provides an important

foundation for its clinical efficacy. Unlike pharmaceutical drugs that contain specific active constituents and exhibit clear dose-dependent effects, herbal medicines are often derived from

complex systems containing multiple components1,2. For a long time, the content detection of constituents is the main quality control (QC) method for herbal medicines. While as we

know3,4,5,6,7,8, herbal medicines are prepared from complex organisms that contain multiple active constituents that act additively to elicit effects that greater than those of the

individual components9,10,11. And the determination of indicators and their content level of the existing quality standard (QS) are often subjective without powerful evidences, which lead to

the uncorrelation between the QS and clinical efficacy12,13,14. Consequently, herbal medicines are poorly accepted by the mainstream of medical community, including medical experts,

clinical pharmacists, economists, sociologists and patients1,15,16,17,18. There are both genetic information (gene) and chemical information (constituent) existing in organisms. In the

identification of functional genes, the discovery and validation of each gene is closely related to the strategy of gene targeting and related techniques, including knockout and knock-in

methods19,20,21,22,23. This strategy has been successfully used to determine the contributions of functional genes within organisms, providing the basis for genetic screening and gene

therapy (Supplementary Fig. S1a). By this inspiration (Supplementary Fig. S1b), methods to identify the active constituents and measure their levels in herbs, as complex organisms, can

involve constituent removing (similar to knockout) and adding (similar to knock-in), which makes the setting of QS more well-founded related to the whole effect. As the discovery of

functional genes is closely related to the phenotypic analysis, the validation of active constituents in herbal medicines cannot be separated from the bioactivity detection.

Microcalorimetry, an automatic and quantifiable method that measures changes in energy levels at the cellular, tissue, organ, or whole organism levels etc., has been used in physical,

chemical and biochemical fields18,24,25,26,27,28. Compared with conventional methods (e.g., microplate and turbidimetry assays), microcalorimetry can provide detailed information on the

bacteriostatic effects of drugs in real-time, online and high-throughput screening assays. Therefore, microcalorimetry is widely used to assess the bacteriostatic activity of

drugs29,30,31,32,33. _Rhizoma coptidis_ (_R. coptidis_), an important herbal medicine to treat bacterial diarrhea, constipation, diabetes and other major diseases in Asia, Africa and Latin

America for a long history32,34 (Supplementary Fig. S2), was studied in this research. There are a lot of protoberberine alkaloids in _R. coptidis_, of which the structure belongs to

isoquinoline alkaloids. The structural differences of those alkaloids are mainly caused by different groups bound to C2, C3, C9 and C10 (Supplementary Fig. S3). But their contributions to

the bacteriostatic activity of _R. coptidis_ and the content levels have not been clearly specified. Thus, we put forward the strategy of constituent removing and adding, hoping to discover

active constituents of _R. coptidis_ inhibiting _Shigella dysenteriae_ (_S. dysenteriae_) and their content limits. Specifically, we first removed the targeted constituents from _R.

coptidis_ to evaluate the inhibitory effects of the targeted constituent and its negative sample (samples lacking the targeted constituent) on the activity of _S. dysenteriae_, with

unmodified _R. coptidis_ extract as a reference sample. After confirming the identities of the active constituents, the targeted constituents were added into the negative samples

individually to measure their bacteriostatic effects. We believe that the difficulty of characterizing the active constituents and measuring their levels in herbs can be overcome by applying

the removing and adding strategy together with a bioassay. This method can provide an important reference for the establishment of QS related to the clinical efficacy. The experimental

strategy used in this study is shown in Fig. 1. RESULTS CONSTITUENT REMOVING AND CHEMICAL IDENTIFICATION A preparative thin layer chromatography plate (PTLCP) was used to achieve constituent

removal. Each band on the plate corresponded to one constituent and was regarded as a positive sample (namely targeted constituent marked by letter M+). The rest of bands was defined as the

corresponding negative sample (marked by letter M−). Next, we used Ultra-performance liquid chromatography (UPLC) and quadrupole time-of-flight mass spectrometry (Q-TOF MS) to identify the

constituent of each band and to determine whether there were residual compounds in the corresponding negative sample. Using this method, the constituents in the positive samples were

preliminarily identified (Supplementary Fig. S4) as berberine (BER), palmatine (PAL), coptisine (COP), epiberberine (EPI), jateorrhizine (JAT) and columbamine (COL), respectively. The levels

of the removed constituents in the negative samples were nearly undetectable (Supplementary Fig. S4). Furthermore, the molecular structures of the removed constituents were not damaged by

the removal procedure (Supplementary Fig. S5). IDENTIFICATION OF THE ACTIVE CONSTITUENTS The growth and metabolism of living organisms are accompanied by heat/energy production, which can be

affected by pathological changes or the action of drugs. Therefore, it is possible to evaluate changes in microbial heat production in the presence or absence of different drugs using

microcalorimetry. Accordingly, we determined the bioactivity of _R. coptidis_ extract, removed samples and added samples in terms of bacteriostasis. The normal growth thermogenic curve for

_S. dysenteria_e at 37°C is shown in Fig. 2a. The heat flow power-time (HFP-_t_) curve showed that the _S. dysenteriae_ metabolic profile included two main stages (stages 1 and 2) and five

phases, (lag phase [a–b], the first exponential growth phase [b–c], transition phase [c–d], the second exponential growth phase [d–e] and the decline phase [e–f]). The quantitative

thermokinetic parameters of the HFP-_t_ curve for _S. dysenteriae_ growth could be delineated using the equation (1): where _P_0 and _P_t represent the heat flow power at time 0 or time

(min), respectively. To test the reliability of the microcalorimetry, we repeated the experiment on eight occasions in untreated bacteria and obtained good reproducibility. We then

quantified the following thermokinetic parameters from the HFP-_t_ curves in the presence of difference concentrations of the samples: _p_1, _p_2, _t_1 and _t_2 (Table 1). PCA revealed that

_k_2 and _t_2 explained 87% of the variation of samples, including the _R. coptidis_ extract, removed samples and added samples. Therefore, we focused on parameters _k_2 and _t_2 in this

study. Figures 2b, c illustrate the effects of _R. coptidis_ (0.8 mg/mL) extract, removed constituents and corresponding negative samples on the HFP-_t_ curves of _S. dysenteriae_. We found

that, compared with the control and the _R. coptidis_ extract, the kinetics of the removed and negative samples showed marked variation (Supplementary Table S1). Next, we calculated the

inhibition ratio _I_ as equation (2) and the relative inhibition ratio _RI_ as equation (3) to quantify the contributions of the individual constituent to the bacteriostatic activity of _R.

coptidis_ extract. As shown in Fig. 2d, BER, COP, EPI, PAL and JAT + COL removed inhibited the growth and metabolism of _S. dysenteriae_; of which BER and COP had the greatest effects. The

bacteriostatic activities of BER− and COP− were significantly lower than that of _R. coptidis_ extract (_P_ < 0.01). Furthermore, the bacteriostatic activities of EPI−, PAL− and (JAT +

COL)− were not significantly different to that of _R. coptidis_ extract. Thus, BER and COP appear to be the main bacteriostatic constituents of _R. coptidis_ extract with contributions to

the bacteriostatic activity of 54.10% and 39.75%, respectively (Fig. 2d). where _K_2c is the growth rate constant of the second exponential growth phase of _S. dysenteriae_ in the culture

medium alone; _k_2s is the growth rate constant of the second exponential growth phase of _S. dysenteriae_ exposed to the test samples; _I_s is the inhibition ratio of samples under

evaluation; _I_e is the inhibition ratio of _R. coptidis_ extract (reference); and _RI_ is the relative inhibition ratio. CONSTITUENT ADDING AND CHEMICAL IDENTIFICATION After confirming that

BER and COP were the main bioactive constituents of _R. coptidis_, we added BER to its negative sample (BER−) to final concentrations of 0, 15, 45, 60, 80 and 120 μg/mL, which was

equivalent to the relative content of BER in _R. coptidis_ extract was (14.52%, based on the no-show detection process). HPLC was used to confirm the chemical compositions of the added

samples. We also prepared added samples of COP at concentrations of 0, 8, 16, 32, 64 and 128 μg/mL, similar to the COP content in _R. coptidis_ extract (5.3%, based on the no-show detection

method). The HPLC profiles are shown in Fig. 3a, b and Supplementary Fig. S6. LEVELS OF THE ACTIVE CONSTITUENTS The bacteriostatic activity of samples adding BER or COP was assessed by

microcalorimetry (Fig. 3c,d) and _I_ and _RI_ were calculated (Tables 1 and 2). The relationship between _RI_ and BER or COP concentrations are shown in Fig. 4. To determine the correlation

between the concentrations of active constituents in added samples and _I_, we calculated the change in _I_ induced by the each concentration of active constituents (_P_) using equation (4):

where _I_n is the inhibition ratio of the negative sample lacking the targeted constituent; _I_i is the inhibition ratio of the negative sample following the targeted constituent added; and

_W_ is the corresponding total concentration of the targeted constituent causing _I_i. As illustrated in Fig. 4, the relative potencies of COP (i.e., _P_COP) and BER (i.e., _P_BER) were

similar (red curves in Fig. 4). For both constituents, their relative potencies increased with increasing weight. However, the potency started to decrease when the weight passed a threshold

level. Therefore, the peak values in the _P_COP and _P_BER curves (e and f in Fig. 4) are likely to show the greatest potencies. Therefore, the concentrations of COP and BER that showed the

greatest efficiency were 32 μg/mL and 80 μg/mL, respectively. We calculated that the greatest efficiency of COP and BER is at the relative concentrations 14.45% and 31.92%, respectively. The

dose–response curves in Fig. 4 (blue curves) revealed some differences in _I_COP and _I_BER. Points a and b in Fig. 4 correspond to the _RI_s of COP and BER, respectively. These values

differed because the corresponding negative samples contained other constituents. Points c and d in Fig. 4 correspond to the _RI_s of 8 μg/mL COP and 15 μg/mL BER, respectively. At

concentrations of COP and BER exceeding 8 μg/mL and 15 μg/mL, respectively, the _RI_s increased rapidly and there was a significant difference between _I_i and _I_n. We also found that the

relative compositions of COP and BER which showed the best efficiency were 4.05% and 8.08%, respectively (Tables 1 and 2). The _RI_ of COP did not increase markedly with further increases in

concentrations after point g. Thus, the concentration of 32 μg/mL, corresponding to point g, might be the maximum dose of COP. By contrast, because there was no apparent plateau for _I_BER,

we could not determine the maximum dose of BER. Although this finding might be due to synergistic effects of BER combined with other constituents of the negative samples, further studies

are needed to confirm this possibility. By comparing the _I_BER and _P_BER curves, we found that _P_BER decreased sharply after point f, but _I_BER did not increase substantially.

Accordingly, we speculate that the concentration of 80 μg/mL, which corresponds to point f, could be the maximum dose limit of BER. By comparing the relative compositions of the knocked in

constituents (Table 1), we found that the relative composition of BER with the greatest efficiency was 31.92%. DISCUSSION Currently, the choice of QC indicators for herbal medicines is often

subjective without forceful evidences12,13,14. Inspired by the discovery of functional genes, we put forward the strategy of constituent removing and adding according to the dual attributes

of genetic information (genes) and chemical information (constituents) of organisms, hoping to promote the QC of herbal medicines. With this method, we found that the main bioactive

constituents in _R. coptidis_ that inhibited the growth of _S. dysenteriae_ were BER and COP, with contributions to the bacteriostatic activity of 54.10% and 39.75%, respectively. By adding

BER and COP into their negative samples, we found that the relative concentrations of BER and COP were 8.08%–31.92% and 4.05%–14.45%, respectively. We also found that BER alone did not fully

account for the bacteriostatic activity of _R. coptidis_, although BER preparations are now widely used in clinical settings. Although our strategy was inspired by gene knockout and

knock-in, there are fundamental differences between these methods. In particular, gene knockout and knock-in involves gene recombination and changes to the expression of genes through

knockout, knock down and silencing, which has dynamic features and can be expanded19,20,21,22,23. In terms of removing and adding of the constituents of an herbal medicine, there are five

technical issues that need to be considered: (1) What constituent is being removed? (2) Was the removed constituent a single compound? (3) Does removal affect the structure of the targeted

constituent? (4) How to add the constituent? (5) Are there any sensitive and high-throughput methods that can be used to assess the bioactivity? To deal with those issues in the study of

constituent removing and adding of herbs, we used the convenient and reliable PTLCP to remove the bioactive constituents capable of inhibiting the growth of _S. dysenteriae_. Although JAT

and COL were not separated completely, the result showed that the combination of them contributed little to the bacteriostatic activity of _R. coptidis_ extract, which meant that the two

constituents were not mainly active ones. Additionally, we performed HPLC and MS-MS to confirm that the removed constituents were not damaged and there were almost no residual constituents

in the negative samples. We also verified that the active constituents were added correctly. By using PTLCP, we were able to prepare sufficient quantities of samples. Although there are many

methods available to assess bacteriostatic activity, we used a sensitive and high-throughput method called microcalorimetry to assess the bioactivity of the removed and added constituents.

A common characteristic of complex living organisms, such as herbal medicines, is that all of the constituents work together to produce an effect that is greater than the effects of the

individual constituents. Unlike the traditional method of separating and then testing the activity of individual phytochemicals, we tried to avoid the limitations of reductionism in studies

of complex systems without considering the interactions among constituents. Instead, we removed the targeted constituents from a complex system and then added them into the system to

investigate the activity of samples. In this way, we ensure our conclusions can be used to establish a QS for herbs that is suitable for the clinical use and has guaranteed the clinical

efficacy. Although there is a limitation of the strategy for its dependence on the separation of constituents, the combination of multiple techniques such as preparative high performance

liquid chromatography and high speed counter current chromatography could be used to remove the targeted constituent35,36,37. Meanwhile, with the development of further researches on the

constituent separation of herbal medicines, we believe that the strategy will also be improved better. Further studies that evaluate the synergistic and antagonistic properties of the

bioactive constituents of herbs would aid the development of multicomponent drugs. METHODS MATERIALS _R. coptidis_ (_Coptis chinensis_ Franch.) samples of about 5 years old were obtained

using Good Agricultural Practice from Shizhu county, Chongqing province, China, in October 2010. All of the samples satisfied the standard for _R. coptidis_ in the Chinese Pharmacopoeia and

the Japanese Pharmacopoeia. Reference compounds, including BER, PAL, COP, EPI, JAT and COL were obtained from the National Institutes for Food and Drug Control (NIFDC) (Beijing, China);

their purities were not less than 99.0% by high-performance liquid chromatography (HPLC). _S. dysenteriae_ (CMCC B 51252) was provided by the China Center for Type Culture Collection (Wuhan

University, Wuhan, China). _S. dysenteriae_ is the main pathogen causing dysentery. _R. coptidis_ cures dysentery by inhibiting such pathogens. _S. dysenteriae_ is frequently used to study

the bioactivity of drugs used to treat diarrhea. Luria-Bertani (L.B.) culture medium was used in the bioassay and contained 5 g yeast extract, 5 g sodium chloride and 10 g peptone in 1000 mL

(pH = 7.2–7.4). The culture medium was sterilized at 121°C under 0.1 MPa for 30 min and stored at 4°C until required. Acetonitrile and methanol (chromatographic grade) were purchased from

Fisher Chemicals (Pittsburgh, PA). Water was purified using a Milli-Q Water Purification System (Millipore, Bedford, MA). Silica Gel G preparative thin layer chromatography plates (PTLCP, 20

× 20 cm wide, 1 mm thick) were purchased from Yantai Chemical Industry Research Institute (Shandong, China). All other chemicals were purchased from Beijing Chemical Factory (Beijing,

China) and were of analytical grade. PREPARATION OF THE STANDARD SOLUTIONS AND THE _R. COPTIDIS_ EXTRACT Standard solutions containing BER, PAL, COP, EPI, JAT and COL were prepared by

accurately weighing specific amounts of each substance and dissolving them in methanol in a volumetric flask. The concentrations of the standard solutions were as follows: BER 0.155 mg/mL,

PAL 0.045 mg/mL, COP 0.032 mg/mL, EPI 0.035 mg/mL, JAT 0.016 mg/mL and COL 0.018 mg/mL. The _R. coptidis_ extract was prepared as follows. The herb was first dried at room temperature and

milled into a powder. Then, about 50 g of the powder was transferred to a flask containing 500 mL of purified water and mixed for 30 min. Reflux extraction was performed twice for 1.0 h

each. The resulting solution was filtered while it was still hot and the filtrate was collected. Finally, the filtrate was evaporated to dryness and the solid residue was dried in a

desiccator. CONSTITUENT REMOVING A silica Gel G PTLCP was used to separate and obtain the constituents of _R. coptidis_. The water extract of _R. coptidis_ and standard solutions of BER,

PAL, COP, EPI, JAT and COL were spotted onto the same plate and developed in a mixture of toluene, ethylacetate, methanol, isopropanol and ammonia water (6:3:1.5:1.5:0.5, _v_/_v_). After

observing the plate under daylight, the bands corresponding to the relative retention values of each reference compound were retrieved. These procedures were repeated. Then, the merged

silica chips were extracted with methanol and the suspensions were filtered and centrifuged. The supernatants were collected and evaporated to dryness for further chemical analysis and for

use in bioassays to identify the active constituents in _R. coptidis_. CONSTITUENT ADDING After identifying the bioactive constituents of _R. coptidis_, we applied the added procedure. In

this phase, the active constituents were dissolved in L.B. culture medium to the required concentrations. Then, the dissolved constituent was added into the negative sample (prepared in L.B.

culture medium) without the corresponding constituent. Then, we performed chemical analyses to characterize the constituents. Finally, microcalorimetry was performed to determine the

bioactivity of different amounts of each active constituent to determine their levels in the herbal extract. CHEMICAL ANALYSIS HPLC was performed to determine the levels of the active

constituents in _R. coptidis_ extract, evaluate the changes in the chemical constituents following removing and adding, as follows. HPLC was performed using an Agilent 1200 HPLC system

(Agilent Technologies, Santa Clara, CA). Chromatographic separation and detection of samples were performed on a Kromasil™ C18 column (250 mm × 4.6 mm, 5 μm) at a column temperature of 30°C

with a flow rate of 0.6 mL/min using a solution of acetonitrile/water (0.05 mol/L potassium dihydrogen phosphate) (50:50, _v_/_v_). Then, sodium dodecyl sulfate was added to a concentration

of 0.4 g/100 mL of solution (pH = 4.0). The standard solutions, _R. coptidis_ extract, active constituents obtained by PTLCP separation and the added samples were filtered through a 0.22 μM

Millipore membrane (Carrigtwohill, Co. Cork, Ireland) and injected into the HPLC system for chemical analysis. BIOACTIVITY ASSAY The bioactivity experiments were performed using the ampoule

method at 37°C with a 3114/3236 TAM air isothermal microcalorimeter (Thermometric AB, Jarfalla, Sweden). _S. dysenteriae_ were inoculated into 100 mL of L.B. culture medium at an initial

density of 1 × 106 colony forming units (CFU) per mL. Then, 10 mL of the bacterial suspension was added to sterilized 20-mL glass ampoules. The _R. coptidis_ extract, removed samples and

added samples were then added to the bacterial suspension. Each ampoule was sealed and placed in an eight-channel calorimeter. When the temperature of the ampoules reached 37°C, heat flow

power-time (HFP-_t_) curves were recorded for each sample until the values returned to baseline. Each experiment was repeated three times. All data were continuously recorded using PicoLog

TC-80 software (TA Corporation, New Castle, USA). Microcalorimetry data are repeatable and the method provides real-time, online, dynamic information to characterize the amount of heat

produced by organisms. We measured the following thermokinetic parameters: the growth rate constants of the first and second exponential phases (_k_1 and _k_2), the heat flow power (HFP) of

the first and the second highest peaks (_p_1 and _p_2) and the appearance time of the first and second highest peaks (_t_1 and _t_2) from the HFP-_t_ curves. DATA ANALYSIS Quantitative

thermokinetic parameters were analyzed using Origin 8.5 software (OriginLab Company, Northampton, USA) to plot the HFP-_t_ curves and calculate the thermokinetic parameters. Principal

component analysis (PCA) is a data reduction technique that can be used to extract data, remove redundant information, highlight hidden features and visualize the relationships among

numerous variables with a small number of underlying factors (principal components or PCs) without losing crucial information38. Therefore, we performed PCA to identify the main parameters

derived from the HFP-_t_ curves. We also applied analysis of variance (ANOVA) to test for differences in the bioactivity of different samples and identify the active components. This

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3285–3296 (2009). Article  CAS  Google Scholar  Download references ACKNOWLEDGEMENTS This study was supported by the National Natural Science Foundation of China (Grant No. 81274078,

81322052, 81073043 and 81303222), China Postdoctoral Science Foundation (Grant No. 2013M532130) and the Open Research Fund of the State Key Laboratory Breeding Base of Systematic Research,

Development and Utilization of Chinese Medicinal Resources. The funding sources were not involved in study design, data collection or analysis, writing of the manuscript or the decision to

publish the results. AUTHOR INFORMATION Author notes * Yan Dan, Li Junxian and Xiong Yin contributed equally to this work. AUTHORS AND AFFILIATIONS * China Military Institute of Chinese

Materia Medica, Military 302 Hospital, Beijing, 100039, China Dan Yan, Junxian Li, Yin Xiong, Congen Zhang, Ruiling Wang, Cheng Jin, Jiangyu Li, Lingling Qiu, Xueai Song & Xiaohe Xiao *

National Center of Biomedical Analysis, Beijing, 100850, China Dan Yan * College of Traditional Chinese Pharmacy, Beijing University of Chinese Medicine, Beijing, 100102, China Yin Xiong *

Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences, Beijing, 100094, China Jiaoyang Luo & Yuling Lin * Beijing Physical Examination Center, Beijing, 100077,

China Yumei Han & Hong Qian * Chengdu University of Traditional Chinese Medicine, Chengdu, 610075, China Cheng Peng Authors * Dan Yan View author publications You can also search for

this author inPubMed Google Scholar * Junxian Li View author publications You can also search for this author inPubMed Google Scholar * Yin Xiong View author publications You can also search

for this author inPubMed Google Scholar * Congen Zhang View author publications You can also search for this author inPubMed Google Scholar * Jiaoyang Luo View author publications You can

also search for this author inPubMed Google Scholar * Yumei Han View author publications You can also search for this author inPubMed Google Scholar * Ruiling Wang View author publications

You can also search for this author inPubMed Google Scholar * Cheng Jin View author publications You can also search for this author inPubMed Google Scholar * Hong Qian View author

publications You can also search for this author inPubMed Google Scholar * Jiangyu Li View author publications You can also search for this author inPubMed Google Scholar * Lingling Qiu View

author publications You can also search for this author inPubMed Google Scholar * Cheng Peng View author publications You can also search for this author inPubMed Google Scholar * Yuling

Lin View author publications You can also search for this author inPubMed Google Scholar * Xueai Song View author publications You can also search for this author inPubMed Google Scholar *

Xiaohe Xiao View author publications You can also search for this author inPubMed Google Scholar CONTRIBUTIONS D.Y., J.L. and C.Z. conducted the experiments. D.Y., J.L. and Y.X. wrote the

manuscript and prepared figures. J.L., Y.H., H.Q. and L.Q. conducted sample collection and data analysis. C.P., X.S., J.L., R.W., C.J. and Y.L. provide materials and data. D.Y. and X.X.

conceived the study. All authors reviewed the manuscript. ETHICS DECLARATIONS COMPETING INTERESTS The authors declare no competing financial interests. ELECTRONIC SUPPLEMENTARY MATERIAL

SUPPLEMENTARY INFORMATION Supporting Information RIGHTS AND PERMISSIONS This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit

http://creativecommons.org/licenses/by/3.0/ Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Yan, D., Li, J., Xiong, Y. _et al._ Promotion of quality standard of herbal

medicine by constituent removing and adding. _Sci Rep_ 4, 3668 (2014). https://doi.org/10.1038/srep03668 Download citation * Received: 09 July 2013 * Accepted: 11 December 2013 * Published:

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