Qualitative and quantitative characterization of carbohydrate profiles in three different parts of Poria cocos

Journal of Pharmaceutical and Biomedical Analysis 179 (2020) 113009

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Qualitative and quantitative characterization of carbohydrate profiles in three different parts of Poria cocos Lixia Zhu a,b , Xu Wang b , Sinchung Li a , Elizabeth R. Qi a , Jiang Meng c , Kelly Yin Ching Lam a , Xiaoping Dong a , Jun Xu a,∗ , Hubiao Chen a , Zhongzhen Zhao a,∗ a

School of Chinese Medicine, Hong Kong Baptist University, Kowloon, Hong Kong Special Administrative Region The National Hospital of Enshi Tujia and Miao Autonomous Prefecture, The Central Hospital of Enshi Tujia and Miao Autonomous Prefecture, Enshi 445000, Hubei, China c Department of Traditional Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou 510006, China b

a r t i c l e

i n f o

Article history: Received 11 September 2019 Received in revised form 22 November 2019 Accepted 23 November 2019 Available online 27 November 2019 Keywords: Poria cocos (Schw.) Wolf Different parts Carbohydrate HPGPC-CAD UHPLC-QqQ-MS/MS

a b s t r a c t Poria cocos (Schw.) Wolf has been widely used in traditional Chinese medicine (TCM) for centuries. Its three medicinal parts are Poria Cutis, the epidermis or fulingpi in Chinese; White Poria, the middle part or baifuling; and Poria cum Radix Pini, the sclerotium with some part of host pine root or fushen. The hostwood in fushen is the inner part, known as fushenmu. The epidermis, middle part and middle-plusinner part have different clinical applications, but the differences in their chemistry have not been well determined. Previous studies only concentrated on the differences in secondary metabolites in different parts of P. cocos; however, in this study, we focused on the carbohydrates, another major type of bioactive chemicals in P. cocos, which is also different from most of the other TCM researches. The carbohydrates (polysaccharides, oligosaccharides and monosaccharides) in three parts (epidermis, middle and inner part) of P. cocos were qualitatively and quantitatively characterized by high performance gel permeation chromatography coupled with charged aerosol detector (HPGPC-CAD) and ultra-performance liquid chromatography coupled with triple quadrupole mass spectrometry (UHPLC-QqQ-MS/MS). The obtained data were further processed by principal component analysis (PCA) and supervised orthogonal partial least squared discriminant analysis (OPLS-DA). The results showed that the epidermis contained more polysaccharides with larger molecular weight and higher amount of glucose residue than that of the middle and inner parts, indicating the epidermis as the key site of accumulation of P. cocos polysaccharides. When compared with the epidermis and inner part, the middle part contained the highest glucose molar ratio greater than 92 % in the three types of carbohydrates, whereas the inner part possessed the greatest molar ratio of mannose, xylose, arabinose, rhamnose, glucuronic acid, and galacturonic acid in all kinds of carbohydrates. Furthermore, PCA and OPLS-DA clearly demonstrated that arabinose, glucose, galacturonic acid, and ribose played key roles in the clusters between the epidermis, middle and inner parts. The observed differences in the chemical components in the three parts could provide some explanation for the discriminative clinical applications of Poria Cutis, White Poria, and Poria cum Radix Pini. These findings also provided a chemical basis for quality assessment of P. cocos. © 2019 Elsevier B.V. All rights reserved.

1. Introduction Poria cocos (Schw.) Wolf, also known as fuling in Chinese, is a well-known fungus that grows around the old and dead roots of

∗ Corresponding authors at: School of Chinese Medicine, Hong Kong Baptist University, 7th Baptist University Road, Kowloon Tong, Hong Kong Special Administrative Region. E-mail addresses: [email protected] (J. Xu), [email protected] (Z. Zhao). https://doi.org/10.1016/j.jpba.2019.113009 0731-7085/© 2019 Elsevier B.V. All rights reserved.

pine trees, and the first records can be traced back to an ancient classic of Chinese medicine ‘Shennong Bencao Jing’ as one of the highest grade medicinal herb [1–3]. P. cocos has been commonly used as a traditional Chinese medicine (TCM) for more than 2000 years and is still widely used as a medicinal and edible mushroom in many Asian and even European countries [1,4]. Because of its diuretic [5], spleen-invigorating and sedative effects, P. cocos is widely used to treat edema, chronic gastritis, gastric atony, acute gastro-enteric catarrh, nausea, emesis, dizziness, and insomnia [6,7]. In addition, pharmacological research demonstrated that P. cocos could also treat chronic kidney disease [8–11] and hyperlipidemia [12]. Due

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L. Zhu, X. Wang, S. Li et al. / Journal of Pharmaceutical and Biomedical Analysis 179 (2020) 113009 Table 1 Information of 13 batches of crude Poria cocos.

Fig. 1. The analytical strategy for quantitation of carbohydrates including polysaccharides, oligosaccharides, and monosaccharides in different parts of P. cocos.

to its wide range of beneficial health properties and unique effects, P. cocos is contained in approximately 15 % of traditional Chinese medicine preparations in the Chinese Pharmacopoeia (2015 edition) [2]. For centuries, three different parts of Poria cocos have been used for different therapeutic areas based on specific syndromes as identified in Chinese medicine (Fig. 1). Specifically, Poria Cutis, or fulingpi in Chinese, is the epidermis of the sclerotium and specializes in promoting diuresis and alleviating edema. White Poria, or baifuling, is the white dense middle part of the sclerotium; it has been used to induce diuresis and excrete dampness, strengthen the spleen and reconcil the stomach, as well as calm the mind. Poria cum Radix Pini (Poria with hostwood), or fushen, is the white central part with some part of the host pine root, also known as fushenmu (the inner part). Hence, fushen is the middle-plus-inner part; it specializes in calming the heart and tranquilizing the mind, as well as promoting diuresis. From the epidermis moving towards the inner part, the mind calming effect gradually increases, while diuresis induction decreases. In general, Poria Cutis (epidermis), White Poria (middle part) and Poria cum Radix Pini (middle-plusinner part) have historically been used for different syndromes or diseases. These facts lead to one question: what is the chemical material basis for differentiating use of the three medicinal parts? The different distribution of bioactive chemicals of P. cocos in its different parts are crucial to provide a scientific explanation and basis for the distinctive clinical applications of different parts. Secondary metabolites and carbohydrates are commonly regarded as the two principal types of components in most TCMs [13]. Nevertheless, nowadays, chemical characterization of most TCMs focuses on secondary metabolites since they are understood adequately [13], and P. cocos is treated similarly [1–3,14]. In contrast, carbohydrates (polymeric and monomeric carbohydrates) are largely ignored because the modern analytical techniques for characterizing secondary metabolites, such as LC–MS, have very limited use for direct analysis of carbohydrates. Recently, TCM carbohydrates have attracted more attention because they are promising

Sample no.

Collecting time

Locality

FS-01 FS-02 FS-03 FS-04 FS-05 FS-06 FS-07 FS-08 FS-09 FS-10 FS-11 FS-12 FS-13

Jun., 2016 Jun., 2016 May, 2016 Jul.,2016 Jul.,2016 Jul.,2016 Aug.,2016 Aug.,2016 Sep., 2016 Sep., 2016 Sep., 2016 Sep., 2016 Oct., 2016

Hong Kong Hong Kong Hubei, China Yunnan, China Guangzhou, China Guangzhou, China Guangzhou, China Guangzhou, China Hong Kong Hunan, China Yunnan, China Hong Kong Yunnan, China

agents to treat or ameliorate various diseases or act as functional ingredients in food products [4,7,15,16]. P. cocos has been demonstrated that its polysaccharides exhibit various biological activities, including anti-nephritis [17], immunomodulation [18], antioxidation [19], anti-aging [20], anti-inflammation [21], antitumor [4], antidiabetic [4], and antihepatitis [4] effects. However, previous research, including our published study [1], focused only on the secondary metabolites to explain the chemical basis for the distinctive clinical applications of different parts of P. cocos; the differences in their carbohydrates have not been determined [1,14]. Thus, in this study, we continued the work with a part-specific characterization of P. cocos carbohydrates. We developed a qualitative and quantitative approach combined with multivariate statistical analysis to further explore the chemical differences between three parts (epidermis, middle and inner part) of P. cocos to provide more scientific evidence for their traditional empirical clinical applications. Specifically, the polysaccharides in different parts of P. cocos were qualitatively characterized by a high-performance gel permeation chromatography coupled with charged aerosol detector (HPGPC-CAD). Monosaccharide compositions of three kinds of carbohydrates (polysaccharides, oligosaccharides, and monosaccharides) were quantitatively determined by ultra-performance liquid chromatography coupled with triple quadrupole mass spectrometry (UHPLC-QqQ-MS/MS)-based method with chemical modifications (hydrolysis and/or derivative formation). Analysis of variance (ANOVA), principal component analysis (PCA), and supervised orthogonal partial least squared discriminant analysis (OPLS-DA) were applied to process and analyze the experimental data. Finally, the differences in the carbohydrates in different parts were qualitatively and quantitatively presented, and the discriminative clinical use of different medicinal parts (Poria Cutis, White Poria, and Poria cum Radix Pini) were understood to a certain extent based on carbohydrates as well as secondary metabolites. 2. Materials and methods 2.1. Plant materials Thirteen batches of crude Poria cocos with pine root attached (FS) were collected for this study. Of these, four batches were purchased from the Hong Kong medicine market, four from the Guangzhou medicine market, and another five were acquired directly from certified production regions in China, as specified in Table 1. The epidermis, middle and inner part of the thirteen batches were then dissected from the crude herbs and the dissected sample codes were accordingly marked as E-01 – E-13, M-01 – M-13 and I-01 – I-13. All crude and dissected samples were authenticated by Prof. Zhao Zhongzhen from the School of Chinese Medicine, Hong Kong Baptist University. Voucher specimens were deposited in the Bank

L. Zhu, X. Wang, S. Li et al. / Journal of Pharmaceutical and Biomedical Analysis 179 (2020) 113009

of China (Hong Kong) Chinese Medicines Centre of Hong Kong Baptist University (Fig. 1). 2.2. Chemicals and reagents The chemical markers of monosaccharides, namely d-mannose (Man), d-ribose (Rib), l-rhamnose monohydrate (Rha), dglucuronic acid (GlcA), d-galacturonic acid monohydrate (GalA), d-glucose (Glc), d-galactose (Gal), d-xylose (Xyl), l-arabinose (Ara), and d-fucose (Fuc), series of pullulans and dextrans with different molecular weights (6–805 kDa for pullulans, 1–670 kDa for dextrans), 1-Phenyl-3-methyl-5-pyrazolone (PMP) and ammonia solution (analytical grade) were purchased from Sigma (St. Louis, MO, USA). Trifluoroacetic acid (TFA) used for acid hydrolysis was supplied by Riedel-de Haën (Hanover, Honeywell International Inc., Germany). Glacial acetic acid and chloroform (analytical grade) were purchased from RCI Labscan Ltd (Pathumwan, Bangkok, Thailand). Acetonitrile was of MS grade from Merck (Darmstadt, Germany). Deionized water (> 18.2 M cm resistivity) was prepared by a Milli-Q water purification system (Millipore, Bedford, MA, USA). 2.3. Sample preparation 2.3.1. Pretreatment and extraction Each dissected sample (45 mesh; about 0.40 g) was first ultrasonicated with 20 mL of acetone for 1 h to remove lipophilic substances, and then extracted with water at 100 ◦ C (20 mL ×1 h × 2 times). The two extracted solutions were combined and evaporated at 50 ◦ C on a rotary evaporator until dry. The residue was redissolved in 2 mL of water and then centrifuged (4000 rpm) for 10 min to obtain the supernatant. Subsequently, the supernatant was deproteinized with Sevag reagent (n-butanol and chloroform in 1:4 ratio). After the deproteinization, the aqueous layer (0.6 mL) was diluted (5 times) and then subjected to acid hydrolysis followed by PMP derivatization or direct PMP derivatization without acid hydrolysis; meanwhile, the supernatant (1 mL) was precipitated by adding ethanol to make a final concentration of 80 % and left overnight (12 h) at 4 ◦ C. After centrifugation (4000 rpm for 15 min), the precipitate was collected, washed twice with 80 % ethanol, and dried (oven, 40 ◦ C) to remove the residual ethanol; hereafter it was completely redissolved in 5 mL of hot water (60 ◦ C) to yield the crude polysaccharide solution, and the polysaccharides were quantitatively determined by acid hydrolysis and PMP derivatization. For the determination of molecular weight distribution of the polysaccharides, a portion of crude polysaccharide solution was diluted to the crude herb concentration of 10 mg/mL for HPGPC-CAD analysis. 2.3.2. Acid hydrolysis of water extracts and polysaccharides The acid hydrolysis was performed according to our previous study [22] with minor modification. The prepared water extract or polysaccharide solution (0.50 mL) was mixed with 2.50 mL of 2 M TFA solution in a screw-cap vial and hydrolyzed for 1 h at 120 ◦ C. After cooling, the hydrolysate was evaporated at 55 ◦ C on a rotary evaporator until dry. Then 1 mL of water was added to dissolve the hydrolysate, and the precipitate was removed after centrifugation (15,000 rpm for 5 min); the supernatant was then subjected to PMP derivatization. 2.3.3. PMP derivatization of monosaccharides The sugar derivatization was performed referring to our previous report [22] with modifications. The acid hydrolysate (100 ␮L) was mixed with 100 ␮L ammonia water and 0.5 M PMP methanolic solution (200 ␮L). The mixture was reacted at 70 ◦ C for 30 min and then was cooled to room temperature. Afterwards, 100 ␮L

3

glacial acetic acid was added to neutralize the reaction solution, and then this solution was extracted two times by chloroform (500 ␮L) to remove the excess PMP. Finally, the aqueous layer was centrifuged (15,000 rpm for 15 min) and diluted (10 times) before UHPLC-QqQ-MS/MS analysis. A standard solution, containing eight neutral monosaccharides (Man, Rib, Rha, Glc, Gal, Xyl, Ara, and Fuc) and two uronic acids (GlcA and GalA), was also treated as described above. 2.4. HPGPC-CAD analysis The polysaccharide extracts of three botanical parts of 13 samples were qualitatively analyzed using HPGPC performed on a Dionex UltiMate 3000 series UHPLC-PDA system coupled with CAD (Thermo Scientific, Waltham, MA, USA). The separation was achieved by two tandem TSK GMPWXL columns (300 mm × 7.8 mm, i.d. 10 ␮m) kept at 40 ◦ C. Ammonium acetate aqueous solution (20 mM) was used as mobile phase at a flow rate of 0.6 mL/min. The parameters of CAD were set as follows: data collection rate, 2 Hz; filter, 10 s; gain, 100 pA; and nebulizer heater, 60 ◦ C; and gas regulator mode, analytical. Ultraviolet (UV) detection wavelengths were set at 260 and 280 nm. A 20 ␮L aliquot of the solution was injected for analysis. Aqueous stock solutions of pullulans (2 mg/mL) with different molecular weights (6, 10, 21.7, 48.8, 113, 210, 366 and 805 kDa) and dextrans (2 mg/mL) with different molecular weights (1, 5, 12, 25, 50, 80, 150, 270, 410 and 670 kDa) were injected into the HPGPCCAD using the conditions described above for the construction of the molecular weight-retention time calibration curve by plotting logarithm of the molecular weight versus retention time of each reference compound [3]. 2.5. UHPLC-QqQ-MS/MS analysis UHPLC was performed on an Agilent 1290 Infinity system (Agilent Technologies, Palo Alto, CA) equipped with an auto-sampler and binary solvent delivery system. The chromatographic separation was performed with a Waters ACQUITY UPLC® HSS T3 (2.1 mm × 100 mm, i.d. 1.8 ␮m) and a VanGuardTM Pre-column (2.1 mm × 5 mm, i.d. 1.8 ␮m). The mobile phase consisted of (A) 20 mM ammonium acetate in water and (B) acetonitrile. The elution condition was optimized as follows: 17 % B (0–20 min), 17%–85% B (20–20.1 min), 85 % B (20–22 min), 85 %−17 % B (22–22.1 min), 17 % B (22.1–25 min). The flow rate was 0.4 mL/min. The column was maintained at 35 ◦ C. The injection volume was 2 ␮L. Mass spectrometry was performed on an Agilent 6460 TQ/MS system equipped with electrospray ionization (ESI) source. The conditions of the ESI source were as follows: drying gas (N2) flow rate, 8 L/min; drying gas temperature, 300 ◦ C; nebulizer pressure, 40 psi; capillary voltage, 3500 V (+) and 3000 V (-); nozzle voltage, 1000 V. The analysis was performed using multiple reaction monitoring (MRM) mode, and the detailed MRM conditions for each analyte are given in Table S1 (Supplementary data). Agilent MassHunter Quantitative Analysis Software B.04.00 was used to collect and process mass data. 2.6. UHPLC-QqQ-MS/MS quantitative method validation The developed UHPLC-QqQ-MS/MS method for quantitative analysis of PMP-labeled monosaccharides was validated under the above-described optimized conditions in terms of linearity, precision, sensitivity, stability, repeatability and accuracy. A series of standard solutions for constructing working standard curves was prepared by diluting the mixed stock standard solution, and a calibration curve was established by plotting peak areas (yaxis) versus concentrations (x-axis). The limits of detection (LODs)

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L. Zhu, X. Wang, S. Li et al. / Journal of Pharmaceutical and Biomedical Analysis 179 (2020) 113009

and limits of quantification (LOQs) were determined by continuously diluting the standard solution until the S/N (signal to noise) ratios reached around 3 and 10, respectively. A mixed standard solution was analyzed for six replicates within the same day and additionally on three consecutive days for evaluating intra- and inter-day precision, respectively. For the stability assessment, the extract of a sample (FS-10) was analyzed at 0, 2, 4, 8, 12, and 24 h at room temperature. Repeatability was evaluated by analyzing six sample solutions prepared individually from the same batch of samples (FS-10). The recovery test was conducted to assess the accuracy of the method by spiking the sample (FS-10) with approximately 100 % of known contents of reference compounds (Man: 1.258 mg, Rib: 68 ␮g, Rha: 40 ␮g, GlcA: 25 ␮g, GalA: 93 ␮g, Glc: 30 mg, Gal: 934 ␮g, Xyl: 818 ␮g, Ara: 271 ␮g, and Fuc: 380 ␮g) in the sample, with six independent spiked analyses. 2.7. Multivariate statistical analysis To statistically analyze HPGPC-CAD data, the weight-average molecular weight (Mw ) and number-average molecular weight (Mn ) of P. cocos polysaccharides in three dissected parts of each sample were calculated by the following equations [23]:

 (PAi Mi ) Mw = 

(1a)

PAi

Mn =

 PAi 

(1b)

(PAi /Mi )

in which PAi and Mi indicated peak area and molecular weight, respectively, for each polysaccharide peak (i) in the dissected sample. To statistically process the quantitative results for polysaccharides, oligosaccharides and monosaccharides in each sample, a coefficient (F) that integrates constituent monosaccharide information of P. cocos polysaccharides/oligosaccharides/monosaccharides was calculated by the following equations: Fjkm =

Cjkm 3 10 3   

, j, k, m ∈ N*

(2a)

Cjkm

j=1 k=1 m=1

Fsum(jk) =

10 

Fjkm , j = 1, 2, 3; k = 1, 2, 3; m ∈ N*

(2b)

m=1

where Cjkm represents the contents of each constituent monosaccharide (m) of a certain carbohydrate (k) determined by UHPLC-QqQ-MS/MS in each dissected sample (j); The type code of carbohydrates k from 1 to 3, respectively signifies the three kinds of carbohydrates (polysaccharides, oligosaccharides and monosaccharides); the sample code j from 1 to 3, in turn denotes the three dissected parts (epidermis, middle, and inner part). Fsum(jk) is the sum of each coefficient Fjkm of a certain carbohydrate (k) in a specified sample (j). N* denotes a set of positive integers. Then, the coefficient Fjkm was processed by one-way ANOVA and multiple comparisons using IBM SPSS Statistics 21.0 software (IBM, USA), and PCA and OPLS-DA using the software SIMCA-P Version 13.0 (Umetrics,Umeå, Sweden). All data are expressed as the mean ± SEM. Statistical differences in the contents or coefficient (Fjkm ) of each constituent monosaccharide (m) of a certain carbohydrate (k) among different botanical parts (j) from 13 P. Cocos samples were assessed by one-way ANOVA followed by the Tukey HSD multiple comparisons when the variance was homogeneous; Welch test followed by the Dunnett’s T3 multiple comparisons was conducted when the variance was hetero-homogeneous. A p-value no greater than 0.05 was considered as a significant difference.

3. Results and discussion 3.1. Development of sample preparation The sample extraction and pretreatment conditions were optimized. The carbohydrates in all the samples, including polysaccharides, oligosaccharides, and monosaccharides, could be completely extracted at 100 ◦ C after two extractions (1 h each time). The complete extraction was confirmed by the absence of carbohydrates in a subsequent third extraction with the sulfuric acid-phenol method. For precipitating the polysaccharides, we used 80 % of ethanol based on our previous study [3]. In addition, TFA was selected for acid hydrolysis of different polymeric carbohydrates in P. cocos water extracts because of its important advantages. To be specific, TFA can hydrolyze glycosidic bonds, but the side reaction of monosaccharide degradation during hydrolysis is relatively small; the reaction time is short and there is no need for conventional neutralization, as TFA is volatile and can be easily removed by evaporation under reduced pressure [22,25,26]. The conditions for acid hydrolysis were optimized using the crude P. cocos with pine root attached (FS-10). Specifically, the concentration of TFA, the reaction time, and temperature of acid hydrolysis were investigated based on orthogonal array design (Table S2, Supplementary data). The results suggested that 2 M TFA, 120 ◦ C and 1 h should be selected for the most efficient acid hydrolysis (Table S3, Supplementary data). In the PMP derivatization, the number of times that chloroform removed the excess PMP reagents was optimized, and the results showed that the detected signal of all constituent monosaccharides dropped by more than 50 % when chloroform extracted three times, as seen in Fig. S1 (Supplementary data). Thus, chloroform extraction was selected twice because of enough high signal for accurate quantification of each analyte. 3.2. Selection of analytical methods The carbohydrates with different polymeric degrees in three botanical parts of P. cocos, including polysaccharides, oligosaccharides, and monosaccharides, could be quantitatively determined by an analytical strategy as shown in Fig. 1. First, the water extract of each botanical part was hydrolyzed, and the monosaccharides in the hydrolysate were then determined by PMP derivatization and UHPLC-QqQ-MS/MS analysis as the total free carbohydrate content of each botanical part. Besides, the water extract was directly subjected to derivatization and mass spectrometry analysis. The determined monosaccharides on this occasion were regarded as the free monosaccharides in each botanical part since polymeric carbohydrates did not release monosaccharides without acidic hydrolysis. Meanwhile, the P. cocos polysaccharides were produced by ethanol precipitation and then characterized by the acidic hydrolysis, derivatization, and mass spectrometry analysis. Afterward, the difference between the value of the total carbohydrate content and the sum of monosaccharides and polysaccharides was considered as the content of oligosaccharides in each botanical part (Fig. 1). HPGPC, a type of size exclusion chromatography that separates polymers based on molecular size, is an effective tool for characterizing molecular weight distribution of polysaccharides in dietary and herbal materials by the developed molecular weight-retention time calibration curve using a series of glycan standards, generally dextrans [24]. Here HPGPC with two tandem GPC columns was employed to characterize molecular weight distribution of polysaccharides in different botanical parts of P. Cocos, and two series of glycan substances with different chemical structures, namely dextrans and pullulans, were integrated for constructing a more reliable molecular weight–retention time calibration curve [22]. CAD, a new kind of universal detector that produces charged aerosol

L. Zhu, X. Wang, S. Li et al. / Journal of Pharmaceutical and Biomedical Analysis 179 (2020) 113009

5

Fig. 2. Typical HPGPC-CAD chromatograms, Mw , and Mn of P. cocos polysaccharides from the three parts of P. cocos samples. E: epidermis; M: middle part; I: inner part; MW: molecular weight.

particles measured by an electrometer, was used instead of the conventional evaporative light scattering detector (ELSD) to directly detect HPGPC-eluted P. cocos polysaccharides, owing to its higher sensitivity [27], as shown in Fig. 2A. MRM mode performed on QqQ-MS/MS is a powerful tool for the simultaneous quantitative determination of multiple components in dietary and herbal complex matrices by screening of assigned precursor ion-to-product ion pair to achieve high sensitivity and superior specificity. In this study, an UHPLC-QqQ-MS/MS method by MRM mode was established according to our previous report with modifications [26]. All PMP-derivatized monosaccharides possessed abundant precursor ion with protonated molecular ions [M+2PMP+H]+ and two same product ion at m/z 187 and m/z 175, which were selected as the ion-pairs to be monitored in MRM mode. Due to its stronger signal than at m/z 187 for determining each analyte, thus daughter ion at m/z 175 was chosen as quantifier, which is deduced to be generated by [M + PMP – Cn H2n Om + H]+ (neutral sugars) or [M + PMP – Cn H2n-2 Om + H]+ (uronic acids), where n and m denote the numbers of carbon and oxygen atoms in the original monosaccharides, respectively [26] (Table S1, Supplementary data). The other MRM conditions for each analyte were also optimized, as shown in Table S1. Under these conditions, ten monosaccharides that contain four groups of isomers, namely two uronic acids: GlcA and GalA, three pentoses: Rib, Xyl, and Ara, three hexoses: Man, Glc, and Gal, and two hexose deoxy sugars: Rha and Fuc, were completely quantified (Fig. S2, Supplementary data). Furthermore, the reported study seems to not detect uronic acids in water-soluble polysaccharides from P. cocos, but interestingly GlcA and GalA were found in this study, which was attributed to the very high sensitivity of QqQ-MS/MS. 3.3. Quantitative method validation Quantitative method validation for the established UHPLC-QqQMS/MS analysis was performed for linearity, intra- and inter-day precision, LODs, LOQs, stability, recovery, and repeatability, as summarized in Table 2. All correlation coefficient values (r > 0.995) demonstrated a good linear relationship between the analyte concentrations and their peak areas within the test ranges. The intra- and inter-day variations of ten analytes (RSDs) were within 0.63–5.42 % and 1.61–5.88 %, respectively. The LODs and LOQs were in the range of 0.87–2.82 ng/mL and 2.38–9.13 ng/mL, respectively. The RSDs for stability were not more than 9.00 %. As for repeatability, the RSDs were lower than 7.20 % for total free carbohydrates, 7.87 % for polysaccharides, and 9.01 % for free monosaccharides. The developed method also had acceptable accuracy with spike recovery of 93.80–106.52 % for all analytes. All these results clearly demonstrated that the proposed quanti-

tative UHPLC-QqQ-MS/MS method was linear, precise, sensitive, stable, accurate, and repeatable enough for simultaneous determination of ten constituent monosaccharides in free polysaccharides, oligosaccharides and monosaccharides from different parts of P. cocos samples.

3.4. Qualitative characterization of polysaccharides in different parts P. cocos polysaccharides in three dissected parts (epidermis, middle and inner part) were qualitatively compared to characterize their part-specific localization. The molecular weight distributions of P. cocos polysaccharides in all dissected samples from thirteen batches of P. cocos were characterized by HPGPC-CAD from the constructed molecular weight–retention time calibration curve (y = −0.2741x + 9.1402, r = 0.9985) [3]. The typical HPGPC chromatograms are shown in Fig. 2A, and the mean Mw and Mn of each part-specific sample from 13 P. cocos samples were respectively calculated according to the Eqs. (1a) and (1b) (Fig. 2B). The chromatograms indicated that the molar mass ranges of polysaccharides in different parts were different. Polysaccharides in the inner part possessed the widest molecular weight distribution from 7.42 ± 0.53–363.16 ± 299.09 kDa, while the ranges in the middle part (5.78 ± 0.17–129.93 ± 33.35 kDa) and epidermis (9.42 ± 1.43–40.87 ± 18.14 kDa) were considerably narrower (Fig. 2A). Both the mean Mw and Mn of polysaccharides in the inner part (Mw : 26.66 ± 13.20 kDa; Mn : 9.92 ± 0.56 kDa) and epidermis (Mw : 12.03 ± 1.26 kDa; Mn : 10.85 ± 1.27 kDa) were larger than those in the middle part (Mw : 11.55 ± 1.71 kDa; Mn : 7.50 ± 0.66 kDa) (Fig. 2B). The results revealed that polysaccharides with greater molar masses were centered in the epidermis and inner part, while the middle part mainly contained polysaccharides with lower molecular weights.

3.5. Monosaccharide composition analysis of carbohydrates in different parts Monosaccharide compositions of the polysaccharides, oligosaccharides, and the free monosaccharides in different parts of 13 P. cocos samples were characterized using the precolumn derivatization followed by UHPLC-QqQ-MS/MS quantitation. The typical chromatograms are shown in Fig. S2 (Supplementary data). Ten monosaccharides, i.e., Man, Rib, Rha, GlcA, GalA, Glc, Gal, Xyl, Ara, and Fuc, were found to be the main constituent monosaccharides of the three carbohydrates in different parts of P. cocos materials. The content of polysaccharides, oligosaccharides, and monosaccharides in each dissected sample was calculated based on the sum of con-

3.82 1.59 6.41 4.95 2.18 3.04 5.63 7.87 5.69 2.94 6.09 6.16 4.85 7.20 3.93 5.36 1.61 5.98 4.07 6.94 101.86 (5.08) 100.15 (9.77) 102.35 (6.85) 100.17 (9.16) 99.54 (8.05) 101.10 (6.44) 99.73 (3.07) 93.80 (3.49) 97.83 (4.13) 106.52 (6.06) 4.87 6.46 4.15 3.92 3.56 6.68 7.01 7.24 2.38 9.13 1.79 2.53 1.28 1.67 1.31 2.15 2.29 2.35 0.87 2.82 5.32 8.25 6.32 9.00 3.43 7.80 2.13 4.29 5.44 4.88 1.66 5.87 1.37 4.96 3.25 4.13 1.61 5.88 3.15 3.62 0.63 4.11 2.03 5.42 2.08 3.39 2.87 3.05 4.28 1.71 5–4000 10–1000 5–1000 4–800 4–800 250–200000 10–4000 10–6400 2.5–1000 10–1000 0.9972 0.9956 0.9984 0.9978 0.9990 0.9979 0.9982 0.9983 0.9996 0.9985

Inter-Day Intra-Day r

Linear Range (ng/mL) Equation

y = 99.38x–8797.88 y = 50.82x–564.03 y = 41.04x–174.45 y = 49.09x–334.93 y = 52.99x–366.22 y = 154.64x–761,958.53 y = 180.97x – 17,445.84 y = 70.87x – 8758.24 y = 318.64x + 581.01 y = 1.37x + 130.65 Man Rib Rha GlcA GalA Glc Gal Xyl Ara Fuc

Polysaccharides Total carbohydrates

Repeatability (RSD, %, n = 6)

Sensitivity (ng/mL) Spike Recovery (Mean (RSD), %, LODs LOQs n = 6) Stability (24 h, RSD, %) Precision (RSD, %, n = 6) Linearity Analytes

Table 2 The established UHPLC-QqQ-MS/MS method validation for quantitative determination of ten constituent monosaccharides.

5.78 4.66 7.85 8.34 5.17 7.92 9.01 2.93 6.58 4.86

L. Zhu, X. Wang, S. Li et al. / Journal of Pharmaceutical and Biomedical Analysis 179 (2020) 113009

Monosaccharides

6

stituent monosaccharides; the results were summarized in Tables S4–S6 (Supplementary data). Since the experimental results showed that the absolute amounts of polysaccharides, oligosaccharides, and monosaccharides in different parts of 13 P. cocos samples varied remarkably, relative content (content ratio) instead of the absolute amount of carbohydrates should be better able to reveal their universal distribution patterns in different parts. Given this premise, we proposed the coefficient F for inter-individual comparison of the samples (Fig. 3). In order to be able to compare between monosaccharide compositions, between different carbohydrates, and between different parts, the coefficient F is defined as the ratio between the content of each constituent monosaccharide of polysaccharides/oligosaccharides/monosaccharides in each dissected sample and the total content of the three carbohydrates in the three parts of each P. cocos sample. The sum of coefficient F in each sample polysaccharides/oligosaccharides/monosaccharides was expressed as Fsum . The statistical results are summarized in Fig. 3. They demonstrate that the coefficient can exclude any interference caused by the differences in absolute contents of carbohydrates, and thus effectively reveal the part-specific distribution patterns of polysaccharides, oligosaccharides and monosaccharides in the P. cocos materials. Comparison of three parts indicated that the epidermis contained (Fsum ) the greatest amount of total carbohydrates (48.02 ± 4.49 %), polysaccharides (22.21 ± 4.36 %) and oligosaccharides (14.25 ± 2.17 %), the middle part came next (total carbohydrates: 29.55 ± 4.05 %, p < 0.01; polysaccharides: 10.22 ± 2.33 %, p < 0.05; oligosaccharides: 8.03 ± 1.84 %), and then the inner part with the lowest content of total carbohydrates (22.43 ± 3.13 %; p < 0.001), polysaccharides (8.05 ± 1.35 %; p < 0.01) and oligosaccharides (7.70 ± 1.50 %; p < 0.05), while there was no significant difference (p > 0.05) in monosaccharides among the three parts. The abundant polysaccharides and oligosaccharides in the epidermis were largely attributed to their much higher glucose contents (F = 19.24 ± 4.36 %, 11.59 ± 2.19 %, respectively) than those in the middle part (F = 9.04 ± 2.35 %, 7.47 ± 1.77 %, respectively) and inner part (F = 6.19 ± 1.23 %, 3.45 ± 1.36 %, respectively) (Fig. 3). The result showed P. cocos contains abundant oligosaccharides and monosaccharides in addition to rich polysaccharides. However, unfortunately, oligosaccharides and monosaccharides in P. cocos have hardly been characterized so far, whereas some research indicates that they have various bioactivities [15,16], suggesting that there is an importance to investigate P. cocos oligosaccharides and monosaccharides. Besides, the amount F of most of the non-glucose constituent monosaccharides of three kinds of carbohydrates greatly varied between different parts. Specifically, for polysaccharides, the epidermis contained the highest amounts of Man, Rib, Rha, GlcA, Glc, Xyl, Ara, and Fuc, while GalA mainly accumulated in the inner part; for oligosaccharides, the largest amounts of Fuc and Glc existed in the epidermis, while the amounts of Man, Rha, GlcA, GalA, and Xyl in the inner part were highest; for monosaccharides, the epidermis contained the greatest amounts of Rib, Gal, and Fuc, while the inner part possessed the highest amounts of Man, Rha, GlcA, Xyl, and Ara. Generally, except for Glc, the other nine constituent monosaccharides hydrolyzed by three kinds of carbohydrates possessed the lowest amounts in the middle part (Fig. 3). To visualize monosaccharide compositions of various carbohydrates in different parts, we calculated the relative molar ratio percentages of constituent monosaccharides (Table 3). The result showed the three types of carbohydrates, and the total carbohydrates in middle part contained the highest Glc molar ratio greater than 92 %, those in epidermis came next, and then those in inner part with the lowest Glc molar ratio less than 78 %. Additionally, compared with the epidermis and middle part, we found that the

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Fig. 3. Relative content of ten constituent monosaccharides (coefficient Y, %) in P. cocos polysaccharides from the three parts of 13 P. cocos samples (* p<0.05, ** p<0.01, and *** p<0.001). E: epidermis; M: middle part; I: inner part.

Table 3 Relative molar ratio (%) of the constituent monosaccharides of various carbohydrates in different parts of P. cocos. Different parts

Epidermis

Middle part

Inner part

Monosaccharide composition: Man : Rib : Rha : GlcA : GalA : Glc : Gal : Xyl : Ara : Fuc Polysaccharides

Oligosaccharides

Monosaccharides

Total carbohydrates

3.81 : 0.12 : 0.07 : 0.03 : 0.14 : 89.10 : 4.09 : 1.13 : 0.14 : 1.37 2.17 : 0.04 : 0.01 : 0.01 : 0.02 : 92.83 : 3.83 : 0.58 : 0.05 : 0.46 7.96 : 0.11 : 0.17 : 0.08 : 0.88 : 77.42 : 6.83 : 5.34 : 0.35 : 0.86

5.83 : 0.24 : 0.44 : 0.09 : 0.22 : 81.42 : 0.18 : 4.62 : 0.76 : 6.21 3.07 : 0.29 : 0.06 : 0.05 : 0.05 : 94.16 : 0.14 : 0.74 : 0.24 : 1.20 17.77 : 0.26 : 1.11 : 0.23 : 1.39 : 44.89 : 0.51 : 29.14 : 2.20 : 2.51

0.95 : 0.64 : 0.11 : 0.09 : 0.08 : 85.61 : 1.23 : 4.77 : 1.26 : 5.25 0.43 : 0.20 : 0.01 : 0.05 : 0.02 : 97.49 : 0.18 : 0.41 : 0.15 : 1.07 2.79 : 0.45 : 0.43 : 0.74 : 0.83 : 72.01 : 2.68 : 9.77 : 5.17 : 5.14

3.82 : 0.26 : 0.18 : 0.06 : 0.15 : 86.14 : 2.37 : 2.89 : 0.55 : 3.58 1.79 : 0.16 : 0.02 : 0.03 : 0.03 : 94.77 : 1.65 : 0.56 : 0.13 : 0.85 10.02 : 0.26 : 0.58 : 0.32 : 1.05 : 64.13 : 3.36 : 15.19 : 2.40 : 2.68

inner part possessed the greatest molar ratio of Man, Xyl, Ara, Rha, GlcA, and GalA in all kinds of carbohydrates. 3.6. Multivariate statistical analysis In order to further characterize the dissimilarity of carbohydrates profiles between different parts of P. cocos, PCA and OPLS-DA based on monosaccharide composition were employed to process the coefficients F of each sample. PCA, an unbiased multivariate analysis technique, was initially applied to investigate whether the three parts could be differentiated according to differences in the targeted carbohydrates. As shown in Fig. 4A, the PCA score plot based on P. cocos polysaccharides showed that there is not a clear separation for the three botanical parts, in which the first principal component accounted for 47.2 % of the variance, providing a good PCA model with good reproducibility (R2X = 0.90, close to 1) and good predictability (Q2 = 0.51, greater than 0.5). In order to further explore the differences in P. cocos polysaccharides among three parts, OPLS-DA, a supervised latent structures-discriminant analysis method, which utilizes class information to maximize the separation between inter-groups and minimize the separation between intra-groups, was performed to achieve better discrim-

ination among the three parts [2]. The scores plot of OPLS-DA demonstrated that all 39 dissected samples were clearly classified into three groups, the epidermis, middle and inner part samples, according to differences in constituent monosaccharides of P. cocos polysaccharides (Fig. 4B). The OPLS-DA model fit parameters were 0.90 of R2X, 0.72 of R2Y, and 0.53 of Q2, which indicated that the OPLS-DA model established has good fitness and prediction. Based on their variable importance (VIP) values (i.e., greater than 1.0) of OPLS-DA, Ara, Glc, GalA, and Rib were the four main constituent monosaccharides contributing to the clusters in the epidermis, middle and inner parts (Fig. 4C), and these four compounds corresponded to those ion points in red far away from zero in the loading scatter plot (Fig. 4D). PCA and OPLS-DA were also employed to process the coefficients F from oligosaccharides and monosaccharides respectively, and the results visually showed different samples were not completely separated (Fig. 4E–H). Altogether, the quantitative characterizations of polysaccharides, oligosaccharides, and monosaccharides clearly exhibited the variations in the distribution of various carbohydrates in different parts. As seen in Figs. 3 and 4, there was a large difference between polysaccharides of the three parts, while the dissimilari-

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Fig. 4. PCA score plot and OPLS-DA score plot based on the monosaccharide composition of polysaccharides (A, B, C, and D), oligosaccharides (E and F), and monosaccharides (G and H) in different parts of 13 P. cocos samples.

ties in oligosaccharides and monosaccharides were relatively small between different parts. At present, pharmacological research has demonstrated that P. cocos polysaccharides possess anti-nephritic [17], immunomodulating [18], anti-inflammatory [21], anti-oxidant [19], and

anti-tumor effects [4], etc [7]. These pharmacological activities of polysaccharides are closely related to their physical and chemical properties in addition to their amount, such as monosaccharide composition, molecular weight, solubility, primary structure, glycosidic linkages, chain conformation, degree of branching, sub-

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stituents, and the charge on the polymer [19,28]. The reported findings showed that the monosaccharide composition of polysaccharides is an important factor that determines its treatment effect [29,30]. Specifically, constituent monosaccharides, namely Xyl, Ara, and Man, were reported as main active components to protect against myocardial injury [29], and Xyl, Ara, Man, Rha, GlcA, and GalA appeared to display antioxidant activity for immune regulation [30]. According to TCM theory, the heart controls mental and emotional activities, therefore, the myocardial protection and antioxidant effect of Xyl, Ara, Man, Rha, GlcA, and GalA in P. cocos is conducive to its sedative effects. Compared with the epidermis and middle part, Poria cum Radix Pini (middle-plus-inner part) and the host pine root (the inner part) are reputed to have unique sedative and mind-tranquilizing effects [1]. As expected, there is a consistently higher ratio of Xyl, Ara, Man, Rha, GlcA, and GalA hydrolyzed from all three kinds of carbohydrates and total carbohydrates occurring in the inner part. In addition, the qualitative and quantitative characterizations of P. cocos polysaccharides clearly revealed its variations in distribution of different parts. To be specific, the epidermis contained more polysaccharides with larger molecular weight Mn and higher amount of Glc residue than middle and inner parts, indicating the epidermis is the key site of accumulation of P. cocos polysaccharides. By contrast, the middle part possessed the polysaccharides with the lowest molecular weight Mn and the highest Glc molar ratio. Unfortunately, to the best of our knowledge, the association between the molecular size of polysaccharides in P. cocos water extracts and their biological activity has not been determined so far. Therefore, whether these characteristic polysaccharides are correspondingly related to the specific diuretic effect of the epidermis and the unique dampness-excreting and spleen-strengthening effect of the middle part, warrants further chemically structural and pharmacological investigation. Additionally, recent studies demonstrated that several triterpenes, such as poricoic acid A and poricoic acid ZA, ZC, ZD, ZE, ZG, and ZH, exhibited a significant renoprotective effect [8–11] which is closely associated with the diuretic activity of P. cocos. As expected, poricoic acid A has been elucidated to mainly accumulate in the epidermis that specializes in inducing diuresis according to our previous research [1]. In summary, our findings in this study of P. cocos carbohydrates and in our previous study of P. cocos triterpenes provide a comprehensive chemical explanation and basis for the differentiating clinical uses of Poria Cutis, White Poria, and Poria cum Radix Pini. 4. Conclusion In this study, an efficient qualitative HPGPC-CAD and quantitative UHPLC-QqQ-MS/MS method followed by PCA and OPLS-DA was established for part-specific characterization of P. cocos polysaccharides, oligosaccharides and monosaccharides. Consequently, the differences in the molecular weight distribution of P. cocos polysaccharides and monosaccharide composition of the three carbohydrates between different parts were first revealed. Combined with our previous study [1], the dissimilarities among secondary metabolites and carbohydrates of different parts provided some scientific evidence for their traditional part-specific clinical application. Meanwhile, our research developed an effective analytical method for different carbohydrates in P. cocos as well as other medicinal fungus to assess their quality. Author statement Lixia Zhu and Jun Xu conceived and designed the experiment; Lixia Zhu and Sinchung Li performed the experiment; Lixia Zhu, Xu Wang, and Jiang Meng processed the data; Lixia Zhu wrote the

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paper; Kelly Yin Ching Lam collected the samples; Xiaoping Dong, Hubiao Chen, and Zhongzhen Zhao guided the experiment; Elizabeth R. Qi and Jun Xu revised the paper; Zhongzhen Zhao acquired funding for the research. All authors read and approved the final manuscript. Declaration of Competing Interest All authors declare there is no conflict of interest. Acknowledgments This work was funded by the Research Grants Council (Project No. 12141516) and the National Natural Science Foundation of the People’s Republic of China (Project No. 11475248). We acknowledge Mr. Alan Ho from the School of Chinese Medicine, Hong Kong Baptist University, for his technical support in the UHPLC-QqQMS/MS analysis. Appendix A. Supplementary data Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.jpba.2019. 113009. References [1] L.X. Zhu, J. Xu, S.J. Zhang, R.J. Wang, Q. Huang, H.B. Chen, X.P. Dong, Z.Z. Zhao, Qualitatively and quantitatively comparing secondary metabolites in three medicinal parts derived from Poria cocos (Schw.) Wolf using UHPLC-QTOF-MS/MS-based chemical profiling, J. Pharm. Biomed. Anal. 150 (2018) 278–286. [2] L.X. Zhu, J. Xu, R.J. Wang, H.X. Li, Y.Z. Tan, H.B. Chen, X.P. Dong, Z.Z. Zhao, Correlation between quality and geographical origins of Poria cocos revealed by qualitative fingerprint profiling and quantitative determination of triterpenoid acids, Molecules 23 (2018) 2200–2216. [3] L.X. Zhu, J. Xu, Y. Wu, L.F. Su, K.Y.C. Lam, E.R. Qi, X.P. Dong, H.B. Chen, Y.D. Liu, Z.Z. Zhao, Comparative quality of the forms of decoction pieces evaluated by multidimensional chemical analysis and chemometrics: Poria cocos, a pilot study, J. Food Drug Anal. 27 (2019) 766–777. [4] X.L. Li, Y.L. He, P.J. Zeng, Y. Liu, M. Zhang, C. Hao, H. Wang, Z.H. Lv, L.J. Zhang, Molecular basis for Poria cocos mushroom polysaccharide used as an antitumour drug in China, J. Cell. Mol. Med. 23 (2019) 4–20. [5] Y.Y. Zhao, Y.L. Feng, X. Du, Z.H. Xi, X.L. Cheng, F. Wei, Diuretic activity of the ethanol and aqueous extracts of the surface layer of Poria cocos in rat, J. Ethnopharmacol. 144 (2012) 775–778. [6] J.L. Ríos, Chemical constituents and pharmacological properties of Poria cocos, Planta Med. 77 (2011) 681–691. [7] X.J. Jia, L.S. Ma, P. Li, M.W. Chen, C.W. He, Prospects of Poria cocos polysaccharides: isolation process, structural features and bioactivities, Trends Food Sci. Tech. 54 (2016) 52–62. [8] D.Q. Chen, Y.L. Feng, L. Chen, J.R. Liu, M. Wang, N.D. Vaziri, Y.Y. Zhao, Poricoic acid A enhances melatonin inhibition of AKI-to-CKD transition by regulating Gas6/AxleNFe␬B/Nrf2 axis, Free Radic. Bio. Med. 134 (2019) 484–497. [9] M. Wang, D.Q. Chen, M.C. Wang, H. Chen, L. Chen, D. Liu, H. Zhao, Y.Y. Zhao, Poricoic acid ZA, a novel RAS inhibitor, attenuates tubulo-interstitial fibrosis and podocyte injury by inhibiting TGF-␤/Smad signaling pathway, Phytomedicine 36 (2017) 243–253. [10] M. Wang, D.Q. Chen, L. Chen, G. Cao, H. Zhao, D. Liu, N.D. Vaziri, Y. Guo, Y.Y. Zhao, Novel inhibitors of the cellular reninangiotensin system components, poricoic acids, target Smad3 phosphorylation and Wnt/ˇ-catenin pathway against renal fibrosis, Brit. J. Pharmacol. 175 (2018) 2689–2708. [11] M. Wang, D.Q. Chen, L. Chen, D. Liu, H. Zhao, Z.H. Zhang, N.D. Vaziri, Y. Guo, Y.Y. Zhao, G. Cao, Novel RAS inhibitors poricoic acid ZG and poricoic acid ZH attenuate renal fibrosis via a wnt/ˇ-catenin pathway and targeted phosphorylation of smad3 signaling, J. Agric. Food Chem. 66 (2018) 1828–1842. [12] H. Miao, Y.H. Zhao, N.D. Vaziri, D.D. Tang, H. Chen, H. Chen, M. Khazaeli, M. Tarbiat-Boldaji, L. Hatami, Y.Y. Zhao, Lipidomics biomarkers of diet-induced hyperlipidemia and its treatment with Poria cocos, J. Agric. Food Chem. 64 (2016) 969–979. [13] W.F. Zhong, W.S. Tong, S.S. Zhou, K.F. Yip, S.L. Li, Z.Z. Zhao, J. Xu, H.B. Chen, Qualitative and quantitative characterization of secondary metabolites and carbohydrates in Bai-Hu-Tang using ultraperformance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry and ultraperformance liquid chromatography coupled with photodiode array detector, J. Food Drug Anal. 25 (2017) 946–959.

10

L. Zhu, X. Wang, S. Li et al. / Journal of Pharmaceutical and Biomedical Analysis 179 (2020) 113009

[14] W.H. Wang, H.J. Dong, R.Y. Yan, H. Li, P.Y. Li, P. Chen, B. Yang, Z.M. Wang, Comparative study of lanostane-type triterpene acids in different parts of Poria cocos (Schw.) Wolf by UHPLC–Fourier transform MS and UHPLC-triple quadruple MS, J. Pharm. Biomed. Anal. 102 (2015) 203–214. [15] S. Patel, A. Goyal, Functional oligosaccharides: production, properties and applications, World J. Microbiol. Biotechnol. 27 (2011) 1119–1128. [16] H. Sakoguchi, A. Yoshihara, K. Izumori, M. Sato, Screening of biologically active monosaccharides: growth inhibitory effects of D-allose, D-talose, and L-idose against the nematode Caenorhabditis elegans, Biosci. Biotechnol. Biochem. 80 (2016) 1058–1061. [17] T. Hattori, K. Hayashi, T. Nagao, K. Furuta, M. Ito, Y. Suzuki, Studies on antinephritic effects of plant components (3): effect of pachyman, a main component of Poria Cocos Wolf on original-type anti-GBM nephritis in rats and its mechanisms, J. Pharmacol. 59 (1992) 89–96. [18] H. Tian, Z.J. Liu, Y.W. Pu, Y.X. Bao, Immunomodulatory effects exerted by Poria Cocos polysaccharides via TLR4/TRAF6/NF-␬B signaling in vitro and in vivo, Biomed. Pharmacother. 112 (2019), 108709. [19] X.P. Chen, Q.C. Tang, Y. Chen, W.X. Wang, S.B. Li, Simultaneous extraction of polysaccharides from Poria cocos by ultrasonic technique and its inhibitory activities against oxidative injury in rats with cervical cancer, Carbohydr. Polym. 79 (2010) 409–413. [20] A.J. Hou, T.Y. Chen, S.P. Peng, R. Xiang, P. Liu, Studies on the anti-aging effects of pachymaran, Pharmacol. Clin. Chin. Mater. Med. 20 (2004) 10–11. [21] M.K. Lu, J.J. Cheng, C.Y. Lin, C.C. Chang, Purification, structural elucidation, and anti-inflammatory effect of a water-soluble 1,6-branched 1,3-␣-D-galactan from cultured mycelia of Poria cocos, Food Chem. 118 (2010) 349–356. [22] J. Xu, S.L. Li, R.Q. Yue, C.H. Ko, J.M. Hu, J. Liu, H.M. Ho, T. Yi, Z.Z. Zhao, J. Zhou, P.C. Leung, H.B. Chen, Q.B. Han, A novel and rapid HPGPC-based strategy for quality control of saccharide-dominant herbal materials: Dendrobium officinale, a case study, Anal. Bioanal. Chem. 406 (2014) 6409–6417.

[23] L. Zhou, J.D. Xu, S.S. Zhou, Q. Mao, M. Kong, H. Shen, X.Y. Li, S.M. Duan, J. Xu, S.L. Li, Integrating targeted glycomics and untargeted metabolomics to investigate the processing chemistry of herbal medicines, a case study on Rehmanniae Radix, J. Chromatogr. A 1472 (2016) 74–87. [24] L.H. Tung, Method of calculating molecular weight distribution function from gel permeation chromatograms, J. Appl. Polym. Sci. 10 (1966) 375–385. [25] D. Fengel, G. Wegener, Hydrolysis of Polysaccharides with Trifluoroacetic Acid and its Application to Rapid Wood and Pulp Analysis, Advances in Chemistry, American Chemical Society, Washington, DC, 1979, pp. 145–158. [26] Q.L. Chen, Y.J. Chen, S.S. Zhou, K.M. Yip, J. Xu, H.B. Chen, Z.Z. Zhao, Laser microdissection hyphenated with high performance gel permeation chromatography-charged aerosol detector and ultraperformance liquid chromatography-triple quadrupole mass spectrometry for histochemical analysis of polysaccharides in herbal medicine: ginseng, a case study, Int. J. Biol. Macromol. 107 (2018) 332–342. [27] N. Vervoort, D. Daemen, G. Torok, Performance evaluation of evaporative light scattering detection and charged aerosol detection in reversed phase liquid chromatography, J. Chromatogr. A 1189 (2008) 92–100. [28] L.Q. Yang, L.M. Zhang, Chemical structural and chain conformational characterization of some bioactive polysaccharides isolated from natural sources, Carbohydr. Polym. 76 (2009) 349–361. [29] S.H. Lim, Y. Kim, K.N. Yun, J.Y. Kim, J.H. Jang, M.J. Han, J.W. Lee, Plant-based foods containing cell wall polysaccharides rich in specific active monosaccharides protect against myocardial injury in rat myocardial infarction models, Sci. Rep. 6 (2016) 38728. [30] Q. Wang, F. Wang, Z.H. Xu, Z.Y. Ding, Bioactive mushroom polysaccharides: a review on monosaccharide composition, biosynthesis and regulation, Molecules 22 (2017) 955–967.