Metabonomic Study of Chinese Medicine Shuanglong Formula as an Effective Treatment for Myocardial Infarction in Rats Xiaoping Liang,†,§ Xi Chen,§ Qionglin Liang,*,§ Hongyang Zhang,†,‡ Ping Hu,‡ Yiming Wang,§ and Guoan Luo*,†,§ School of Pharmaceutics and College of Chemical and Molecular Engineering, East-China University of Science & Technology, 200237, PR China, and Key Laboratory of Bioorganic Phosphorus Chemistry & Chemical Biology (Ministry of Education), Department of Chemistry, Tsinghua University, Beijing 100084, PR China Received September 11, 2010
A UPLC/TOF-MS-based metabonomic study was conducted to assess the holistic efficacy of Traditional Chinese Medicine Shuanglong Formula (SLF) for myocardial infarction in rats. Thirty male Sprague-Dawley rats were randomly divided into five groups after surgery. The Panax ginseng group, Salvia miltiorrhiza group, and SLF group were treated with water extractions of Panax ginseng (PG), Salvia miltiorrhiza (SM), and SLF (the ratio of SM to PG was 3:7) at a dose of 5 g/kg · w · d for 21 consecutive days, respectively; the model group and sham surgery group were both treated with 0.9% saline solution. Urinary samples for metabonomic study, serum samples for biochemical measurement, and heart samples for histopathology were collected. As a result, metabonomics-based findings such as the PCA and PLS-DA plotting of metabolic state and analysis of potential biomarkers in urine correlated well to the assessment of serum biochemistry and histopathological assay, confirming that SLF exerted synergistic therapeutic efficacies to exhibit better effect on MI compared to PG or SM. The shifts in urinary TCA cycle as well as pentose phosphate pathway suggested that SLF may diminish cardiac injury of MI with its potential pharmacological effect in the regulation of myocardial energy metabolism. Keywords: Myocardial infarction • metabonomics • UPLC/TOF-MS • myocardial energy metabolism • traditional chinese medicine • synergistic effect
1. Introduction Myocardial infarction (MI) is associated with ischemic necrosis of cardiac muscles due to a decrease in the supply of blood to a portion of the myocardium below a critical level necessary for viability and proper physiological function.1 MI is a leading cause of morbidity and mortality, accounting for approximately 12 million deaths annually worldwide.2 It continues to be a significant problem in industrialized countries and is becoming an increasingly significant problem in developing countries. Current anti-ischemic medications such as β-blockers or calcium channel blockers, nitroglycerin, and angiotensin inhibitors are limited by their hemodynamic side effects, such as hypotension and bradycardia.3,4 Traditional Chinese Medicine (TCM), a unique medical system with the significant characteristic of the use of multicomponent drugs, can hit multiple targets with multiple components.5 It pursues an overall therapeutic effect with a multi-ingredient treatment in * To whom correspondence should be addressed. (G.L.) Tel/Fax: 86-1062781688. E-mail:
[email protected]. (Q.L.) Tel/Fax: 86-1062772263, E-mail:
[email protected]. † School of Pharmaceutics, East-China University of Science & Technology. ‡ College of Chemical and Molecular Engineering, East-China University of Science & Technology. § Tsinghua University.
790 Journal of Proteome Research 2011, 10, 790–799 Published on Web 11/22/2010
the form of combination drug formulas in an attempt to improve therapeutic efficacy and reduce drug-related side effects and may also be an effective way of decreasing drug resistance.6 Therefore, the study of TCM has aroused much interest recently especially due to its superiority in the treatment of complex multifactor diseases, such as cardiovascular diseases.7 Despite the great progress in the isolation and identification of many compounds from botanicals or TCM herbs, there is still a bottleneck in the development of methodology to characterize the holistic efficacy and synergism of multicomponent drugs, especially for the formulas of TCM. The emergence of metabonomics, which can impact the global metabolic state of entire organism, leads to high-throughput screening in the pharmaceutical industry and clinical diagnosis8,9 and may also provide a new vision of assessment of the holistic efficacy of TCM. Recently, an increasing number of publications have described metabonomic studies using various techniques including high-field nuclear magnetic resonance,10,11 gas chromatography/mass spectrometry,12,13 and liquid chromatographymass spectrometry (LC-MS).14,15 Among the analytical techniques in metabonomic research, LC-MS is recognized as one of the best analytical techniques in selectivity, sensitivity, and reproducibility.16 Furthermore, among the various LC-MS platforms, ultraperformance liquid chromatography-mass spec10.1021/pr1009299
2011 American Chemical Society
Shuanglong Formula as Effective Treatment for MI trometry (UPLC-MS) is considered to be suitable for metabolite profiling and metabonomics study,17-19 especially for largescale untargeted metabolic profiling due to its enhanced reproducibility of retention time.20 For cardiovascular diseases (CVDs), herbs have been used as medical treatments since the beginning of civilization and some of them (e.g., Salvia miltiorrhiza, Panax ginseng, and Digitalis) have become mainstays of human pharmacotherapy.21 Panax ginseng (PG) and Salvia miltiorrhiza (SM), for their excellent properties of protecting against myocardial ischemia, are widely used either alone or in combination with each other for patients with MI and other CVDs, in both China and other countries including the United States.21-23 Therefore, under the guidance of TCM theory (called “Fufang Peiwu” in the TCM system), Shuanglong Formula (SLF), a combination of SM and PG (at a ratio of 3:7), was designed by Professor Lianda Li, one of the most famous specialists in Xiyuan Hospital of China Academy of Chinese Medical Sciences, and has been used for the clinical treatment of CVDs for several years with clear active ingredients and effective quality control.24-26 Nevertheless, it is urgent to establish a proper approach for the activity evaluation of such a multicomponent medicine. A successful approach should exhibit the ability of not only characterization of the holistic efficacy but also interpretation of synergetic effect existing in the TCM formulas. In our previous study, a metabonomic approach based on UPLC/TOF-MS was developed to characterize the metabolic profile associated with isoproterenol-induced MI and demonstrated that the utility of metabolic profiling combined with multivariate analysis was a powerful tool to investigate the pathogenesis of CVDs.27 In the present study, we applied the metabonomic method to investigate the biochemical abnormalities in MI rats due to coronary artery ligation and assess the therapeutic effects of TCM SLF. The finding of metabolic pathways and potential biomarkers related to MI will be helpful to dissect the underlying efficacies and mechanisms of TCM in treating MI.
2. Experimental Section 2.1. Reagents and Materials. HPLC-grade methanol and acetonitrile were purchased from J. T. Baker (Phillipsburg, NJ, USA). The assay kits for lactate dehydrogenase (LDH), creatine kinases (CK), and nonesterified fatty acid (NEFA) were purchased from Nanjing Jiancheng Bioengineering Institute (Nanjing, China). The following compounds were obtained from Sigma-Aldrich (St. Louis, MO, USA): formic acid, leucineenkephalin, hippuric acid, citrate, oxalosuccinate, nonadecanoic acid, R-D-glucuronic acid 1-phosphate tripotassium salt pentahydrate, N-acetyl-DL-tryptophan, 6-phosphogluconic acid trisodium salt, N-acetyl-L-glutamine, guanosine, and xanthosine5′-monophosphate disodium salt. Ultrapure water (18.2 MΩ) was prepared with a Milli-Q water purification system (Millipore, France). All other chemicals used were of analytical grade. Panax ginseng (PG) was purchased from Changbai Mountain specialty cooperatives of Jilin Baigang (Jilin, China). Salvia miltiorrhiza (SM) was purchased from China National Group Corparation of Traditional and Herbal Medicine (Beijing, China). Shuanglong Formula (SLF) was a combination of SM and PG (at a ratio of 3:7). Dried and pulverized materials of PG (500 g), SM (500 g), and SLF (500 g) were ground and then refluxed with 4000 mL of water for 60 min, twice respectively. After cooling, the extracting solutions were filtered through a
research articles glass filter covered with filter paper. The solutions were condensed under decompression to roughly 150 mL and finally were freeze-dried. All TCM mixtures were under careful quality control to ensure their identity throughout all the experiments. As shown in Supplementary Figures S1-S3 and Tables S1-S3 in Supporting Information, 77 components of SLF were identified, and 18 of them were accurately quantified [3-(3,4dihydroxyhenyl) lactic acid, salvianolic acid B, rosmarinic acid, salvianolic acid A, salvianolic acid C, lithospermic acid, ginsenoside Rg1, ginsenoside Re, ginsenoside Ro, ginsenoside Rb1, ginsenoside Rc, ginsenoside Rb2, ginsenoside Rd, ginsenoside Rf, ginsenoside malonyl-Rb1, ginsenoside malonyl-Rc, ginsenoside malonyl-Rb2, and ginsenoside malonyl-Rd]. Two kinds of SLF mixtures, the combined mix extraction and the combination of postextraction, were analyzed by UPLC/TOF-MS, and no visual differences were observed from the chromatograms. The former was selected for this study because it is the traditional medication for patients. 2.2. Animals and Myocardial Infarction Study. Male Sprague-Dawley rats, 250 ( 20 g in weight, were purchased from the Centre of Laboratory Animals, Tsinghua University (Beijing, China). All animals were kept in an animal room with a temperature of 23 ( 2 °C, a humidity of 60 ( 5%, and a 12 h dark to light cycle. They had free access to food and water. The animal facilities and protocols were approved by the Institutional Animal Care and Use Committee, Tsinghua University. All procedures were in accordance with the National Institute of Heath’s guidelines regarding the principles of animal care (2004). The experiment animals were housed under the above conditions for a 2 week acclimation period. The myocardial infarction of rats was performed by ligating the left ventricular coronary artery, as described previously.28 Before the surgery (day 0), 24-h urine was collected in an individual metabolism cage and blood was collected from the ophthalmic vein for control samples. Then 33 rats were randomly selected to undergo MI or sham surgery. First, animals were anesthetized with urethane (1.3 g/kg, i.p.) and fixed on a pad while positioned on their backs. Then, following thoracotomy in the fourth left intercostal space, the heart was exteriorized, and a silk suture was looped around the proximal left coronary artery. After the heart had been returned to its normal position, the suture was securely ligated in the MI group. The thorax was closed under negative pressure. Rats that revealed an abnormal Q wave, less than 0.3 mV monitored by electrocardiogram (lead II), 1 day after the operation were considered to have developed acute myocardial infarction and were used for the experiment (MI rats). Of the 27 MI rats, 24 animals survived throughout the experiment while 3 animals died after surgery and were excluded in the later experiment. Additional 6 rats were treated in a similar manner except that coronary artery ligation was not done on them (sham surgery rats). No sham surgery animals died throughout the experiment. 2.3. Sample Collection. Each of the TCM extracts (PG, SM, and SLF) was dissolved in a certain amount of water to a concentration equal to 0.5 g of crude botanicals per milliliter of test solution. MI rats were randomly divided into four groups each of six rats as follows: PG group, SM group, SLF group, and model group, with oral gavage with the test solutions of PG, SM, SLF at a dose of 5 g/kg · w · d (equal to 10 mL/kg · w · d) and the same volume of 0.9% saline solution, respectively. In addition, there was the sham surgery group, with oral gavage with the same volume of 0.9% saline solution as model group. The five animal group were administrated as above for 21 Journal of Proteome Research • Vol. 10, No. 2, 2011 791
research articles consecutive days. It is worth noting that the use of 0.9% saline solution for the controls is an improper option since the background medium for the dosage administration is water. It would be more rational to use water gavage instead of 0.9% saline solution for the controls in this study, although there was little severe effect observed for such small amount of daily saline administration. Samples of 24-h urine were collected predose (day 0) and on days 1, 7, 14, and 21. The fresh urine samples were immediately centrifuged at 3500 rpm for 10 min at room temperature, to remove particle contaminants, and the supernatants were stored at -80 °C until UPLC/TOF-MS analysis. Blood samples were collected from the inferior caval vein before surgeries (used as normal control samples) and after 1 h of the final administration and then centrifuged at 3500 rpm for 10 min at 4 °C. The supernatant obtained was frozen immediately, stored at -80 °C, and thawed before analysis. After that, the rats were anesthetized and subjected to autopsy. Their hearts were taken out immediately and fixed in 10% formalin. Serum concentrations of LDH, NEFA, and CK were measured using an enzymatic UV test following the instructions of commercial assay kits. After the reaction with chromogenic agent, the LDH, NEFA, and CK displayed maximal absorption at 340, 550, and 340 nm, respectively, at 37 °C. 2.4. Histopathology. The heart samples were fixed and embedded in paraffin wax; 4-5 µm histologic sections of the paraffin-embedded tissues were stained with hematoxylineosin. The sections were examined under light microscope, and photomicrographs were taken. The areas of MI of the left ventricle were detected with a Leica image analysis system (10×), and infarct size (%) was expressed as myocardial infarct size/left ventricular area ×100%. 2.5. Sample Preparation and UPLC/TOF-MS Analysis. The urine samples were thawed before analysis, and 400 µL of methanol was added to 100 µL aliquots of urine. The mixture was vortex-mixed for 2 min followed by centrifugation at 12,000 rpm for 15 min at 4 °C. The clear supernatant was transferred and diluted at a ratio of 1:1 with methanol for analysis by UPLC/TOF-MS. A 4 µL injection of sample was made onto the column in each run. Chromatographic separation was performed on an Acquity UPLC BEH C18 column (2.1 × 100 mm, 1.7 µm, Waters Corp., Milford, USA) using a Waters ACQUITY UPLC system, equipped with a binary solvent delivery system, an autosampler, and a PDA detector. The column was maintained at 50 °C and eluted at a flow rate of 0.4 mL/min, using a mobile phase of (A) 0.1% (by volume) formic acid in water and (B) acetonitrile. The gradient program was optimized as follows: 0-10 min, 2% B to 15% B; 10-15 min, 15% B to 30% B; 15-17 min, 30% B to 95% B; 17-18 min, 95% B to 2% B; 18-22 min, equilibration with 2% B. The column eluent was directed to the mass spectrometer without split. Mass spectrometry was performed on a Waters LCT Premier orthogonal accelerated time-of-flight mass spectrometer (Waters Corp., Manchester, UK) with an electrospray ionization source (ESI) operating in negative ion mode (W mode of operation). The capillary voltage and the cone voltage were set at 2500 and 50 V, respectively. Nitrogen was used as the drying gas. The desolvation gas rate was set to 750 L/h at a temperature of 350 °C, the cone gas rate was set at 40 L/h, and the source temperature at 120 °C. The scan time and interscan delay were set to 0.2 and 0.02 s, respectively. All analyses were acquired using a LockSpray interface to ensure accuracy and 792
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Liang et al. reproducibility. Leucine-enkephalin was used as the reference compound (m/z 554.2615 for negative ion mode) at a concentration of 50 fmol/L and a flow rate of 5 µL/min. Data was collected in centroid mode from m/z 100 to m/z 1500 with a LockSpray frequency of 10 s and data averaging over 10 scans. 2.6. Data Processing. The MS spectra were first processed using the MarkerLynx Applications Manager version 4.1 (Waters Corp., Manchester, UK). MarkerLynx incorporates an ApexTrack-peak detection package, which allows detection and retention time alignment of the peaks eluting in each chromatogram. The data were combined into a single matrix by aligning peaks with the exact mass/retention time pair (EMRT) together from each data file in the data set, along with their associated intensities. The ion intensities for each peak detected were then normalized, within each sample, to the sum of the peak intensities in that sample and multiplied by 10,000. The processing of area-normalization had little effect on the conclusion of trajectory analysis but improved the tightness of clustering in PLS-DA modeling by comparing the result of the area-normalized data modeling with that of the nonnormalized data modeling (as shown in the Supporting Information). At the same time, the fingerprints of test doses of SLF were acquired and processed at the same procedure to get a data sheet of external dose-containing ions as listed in the Supporting Information. Then the data list of all samples was reformed by removing the ions overlap with that of SLF. The processed data list was then exported and processed by the principal component analysis (PCA) and partial least-squaresdiscriminant analysis (PLS-DA) in the software package SIMCA-P 11.5 version (Umetrics AB, Umeå, Sweden).
3. Result 3.1. Metabonomic Study. 3.1.1. Establishment of Metabolic Fingerprints. To optimize the experimental conditions, a preinvestigation was conducted before the full study. Fingerprints of a small batch of test urinary samples were acquired in positive and negative mode, respectively. We observed that higher noise and matrix effect in ESI positive mode resulted in a higher baseline, which led to the neglect of some metabolites of low abundance and the concomitance of multiple adduction ions. Relatively, adequate information of metabolites could be detected, and most usually formed dominating quasi-molecular ion [M - H]- or [M+HCOO]- with a higher signal/noise in the ESI negative mode. Therefore, considering maximization of the number of detectable metabolites and the quality of data acquired, full-scan detection was eventually set as ESI negative mode. After careful optimization of the flow rate and column temperature for the chromatography and capillary voltage, flow, and temperature of desolvation gas for the mass spectrometry detector, the optimal parameters were fixed as listed in Section 2.5. As a result, a higher flow rate (0.4 mL/min) was used to achieve a higher efficiency of the UPLC column and to reduce the run time under the consideration of the tolerance in backpressure elevation and the effect on the spray and desolvation. Accordingly, a relatively higher column temperature (50 °C) was set to reduce the column pressure resulting from the high flow rate. Additionally, the flow and temperature of desolvation gas were set at 750 L/h and 350 °C, respectively, so as to remove redundant solvent resulting from the high flow rate and to improve the efficiency of desolvation and ionization. Based on the optimal condition, a representative base peak intensity chromatogram of the rat urine obtained in ESI negative mode is shown in Figure 1. After processing as Section 2.6, a list of
Shuanglong Formula as Effective Treatment for MI
research articles DA) was more focused on the actual class discriminating variation in the data compared to the unsupervised approach (PCA). As a consequence, the PLS-DA method was employed to bring out the specific variation between MI and treatment groups. When the supervised pattern recognition was employed, the integrity of the mathematical model was evaluated first before being used for further interpretation. Commonly, R2Y provides an estimate of how well the model fits the Y data, whereas Q2Y is an estimate of how well the model predicts the Y. Both the Q2Y and R2Y close to 1 indicate an excellent model, whereas the poor ratio of them is likely to be the onset of model overfitting. To validate the model against overfitting, a typical 7-round cross-validation was carried out with 1/7 of the samples being excluded from the model in each round. This procedure was repeated in an iterative manner until each sample had been excluded once and the Q2 and R2 values were calculated from the results in SIMCA-P package (as shown in Figure 3).
Figure 1. Representative base peak intensity chromatogram of the rat urine obtained in ESI negative mode based on UPLC/TOFMS.
more than 8000 compounds could be exported for each sample. The precision and repeatability of the UPLC-MS method were validated by the reduplicate analysis of six injections of the same QC samples and six parallel samples prepared using the same preparation protocol, respectively. The relative standard deviations of the peak retention time and area value were less than 5.0%. The resulting data showed that the precision and repeatability of the proposed method were satisfactory for metabonomic analysis. 3.1.2. PCA and PLS-DA Processing of UPLC-MS Data. Within metabonomics PCA and PLS-DA approaches are frequently used to distinguish between classes expected to show metabolic differences. In this work, both PCA and PLS-DA had been tried and exhibited satisfactory classification (as shown in Figures 2 and 3). The supervised pattern recognition (PLS-
After being processed by PCA and PLS-DA in the software SIMCA-P package, mean-centered PCA and PLS-DA score plots could be generated to trace and compare the dynamic recovery of metabolic events in rats. In the PCA and PLS-DA maps, each spot represented a sample and each assembly of samples indicated a particular metabolic pattern at different time points. The locus marked by arrows represented the trend of mean metabolite pattern change. As shown in Figure 2A-C or Figure 3A-C, the metabolic state of each group on day 1 was far away from the initial position (day 0, prior to MI surgery), which indicated that MI disturbed the endogenous substances metabolism and significantly altered the metabolic fingerprints of urine compared to the normal state. From day 1 to day 21 the trajectory direction gradually moved to the initial space. The trajectory returned to within the initial space, indicating recovery of the disturbed metabolism state. Compared to the treatment of a single herb (PG group or SM group), the combination-based treatment (SLF group) revealed better performance in the recovery of the MI surgery-induced dis-
Figure 2. PCA scores plots of rat urine data of SLF group (A), SM group (B), PG group (C), and comparison of normal controls, model group, sham surgery group, PG group, SLF group, and SM group on day 21 (D). MG, model group; SSG, sham surgery group; SLFG, SLF group; PGG, PG group; SMG, SM group. Journal of Proteome Research • Vol. 10, No. 2, 2011 793
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Figure 3. PLS-DA scores plots of rat urine data on days 0, 1, 7, 14, and 21. (A) Dynamic mean-centered PLS-DA score plot of rat urine data of SLF group (Q2Y(cum) ) 0.744, R2X(cum) ) 0.523, R2Y(cum) ) 0.978). (B) Dynamic mean-centered PLS-DA score plot of rat urine data of SM group (Q2Y(cum) ) 0.661, R2X(cum) ) 0.540, R2Y(cum) ) 0.943). (C) Dynamic mean-centered PLS-DA score plot of rat urine data of PG group (Q2Y(cum) ) 0.838, R2X(cum) ) 0.578, R2Y(cum) ) 0.979). (D) Comparison of normal controls, model group, sham surgery group, PG group, SLF group, and SM group on day 21 (Q2Y(cum) ) 0.500, R2X(cum) ) 0.516, R2Y(cum) ) 0.903). MG, model group; SSG, sham surgery group; SLFG, SLF group; PGG, PG group; SMG, SM group.
turbed metabolism state, which can be observed from not only the comparison of dynamic trajectory as shown in Figure 2A-C or Figure 3A-C but also the comparison of normal controls, model group, sham surgery group, PG group, SLF group, and SM group on day 21 as shown in Figure 2D or Figure 3D. Additionally, it is obvious that the trajectory of the model group was far away from the position of normal control even after 21 days’ survival without medication, which excluded the suspicion of self-cure of the MI rats during the experiment. The results suggested that the test TCM doses did have a significant efficacy in MI rats, and furthermore, the combination of PG and SM (as named as the formula SLF) intensified therapeutic efficacies on MI rats, which could be also confirmed by the assay of clinical chemistry as addressed in Section 3.2. 3.1.3. Identification of MI-Related Metabolites. Variables (metabolites) that significantly contributed to the clustering and discrimination were identified according to a threshold of variable importance in the projection (VIP) values (VIP > 1), which could be generated after PLS-DA processing. In order to select potential biomarkers worthy of preferential study in the next step, these differential metabolites were validated using Student’s t test. The critical p-value was set to 0.05 for significantly differential variables in this study. Following the criterion above, 18 significantly differential endogenous metabolites were selected for further study. Identification of these metabolites was then carried out as follows, and the results are listed in Table 1. First, the possible elemental compositions of the selected compounds were generated by using the software MassLynx according to the following procedure: the calculated mass, mass deviation (mDa and ppm), double bond equivalent, formula, and i-fit value (the isotopic pattern of the selected ion) were 794
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calculated with the selected m/z ions. The lower i-fit value and smaller mass deviation indicate a more accurate elemental composition. Then, the structure information was obtained by searching freely accessible databases of KEGG (http://www.genome.jp) and HMDB (http://www.hmdb.ca) utilizing detected molecular weights and elemental compositions. As a result, 17 metabolites were identified on the basis of accurate elemental compositions and context of retention time with available databases. Since a single TOF mass analyzer was used in this study, we recognized there was a flaw in definitely designating a compound due to the absence of fragmentation information. As compensation, 10 of them were confirmed with available reference standards by matching their retention time and accurate mass measurement. As shown in Table 1, among the 18 metabolites, the levels of 11 compounds (nos. 1-11) were observed significantly altered in the model group, and there was no statistically significant difference in the sham surgery group compared to controls. At the same time, they were observed significantly altered in the SLF group compared to the model group, with no statistically significant difference compared to normal controls. Considering their immediate correlativity and potential bioactivity as discussed later, these significantly differential endogenous metabolites such as D-glucuronic acid 1-phosphate, 6-phosphogluconic acid, citrate, and oxalosuccinate were assumed as potential biomarkers, which may be related to the injury of MI and can be used as a potential efficacy indicator for the medication of MI. In this context, we tentatively used the term “potential biomarkers” to acknowledge their potential value and at the same time to indicate its uncertainty. The next four metabolites (nos. 12-15), xan-
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Shuanglong Formula as Effective Treatment for MI a
Table 1. Identification of Significantly Differential Endogenous Metabolites in the Rat Urine no.
tR (min)
m/z
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
4.42 4.60 0.86 4.65 2.32 4.62 10.22 11.23 11.22 5.96 5.34 7.33 6.44 11.22 2.37 10.17 1.54 2.25
178.0490 273.0058 191.0216 275.0215 188.9854 245.0112 201.0213 297.2981 595.2036 187.0060 336.0726 283.0822 338.0891 442.0197 242.0121 333.0065 227.9975 239.9968
selected ion
[M [M [M [M [M [M [M [M [M [M [M [M [M [M
+ -
H]H]H]H]H]H]H]H]H]H]H]H]HCOO]H]-
[M - H][M - H][M + HCOO]-
elemental composition
identification results
MGc
SSGc
SLFGc
SLFGd
C9H9NO3 C6H11O10P C6H8O7 C6H13O10P C6H6O7 C13H14NO3 C7H7O5P C19H38O2 C36H40N2O6 C7H12N2O4 C11H19N3O7S C10H12N4O6 C10H13N5O5 C10H15N5O11P2
hippuric acidb b D-glucuronic acid 1-phosphate b citrate 6-phosphogluconic acidb oxalosuccinateb N-acetyl-DL-tryptophanb benzoylphosphate nonadecanoic acidb urobilinogen N-acetylglutamineb S-(hydroxymethyl)glutathione xanthosineb guanosineb guanoine diphosphate unknown nicotinamide ribotide 5-phosphoribosylamine glucosamine
+ (V) + (v) + (V) + (v) + (V) + (V) + (V) + (V) + (V) + (V) + (V) + (V) + (V) + (V) + (V) s s s
s s s s s s s s s s s + (V) + (V) + (V) + (V) s s s
s s s s s s s s + (v) s s + (v) s s s + (V) + (v) + (v)
+ (v) + (V) + (v) + (V) + (v) + (v) + (v) + (v) + (v) + (v) + (v) +(v) + (v) + (v) + (v) + (V) + (v) + (v)
C11H15N2O8P C5H12NO7P C6H13NO6
a “v” means a higher level of metabolites, whereas “V” represents a lower level of metabolites. All data were represent intensities values of metabolites on day 21. “+” means a statistically significant difference (P < 0.05), whereas “s” represents no statistically significant difference. b Confirmed with authentic standards. c Compared to normal controls. d Compared to the model group. MG, model group; SSG, sham surgery group; SLFG, SLF group; PGG, PG group; SMG, SM group.
Table 2. Summary of Intensity Values of Potential Biomarkers in Each Group on Day 21 peak intensity (mean ( SD, n ) 6) biomarkers
control
model group
SM group
PG group
SLF group
sham surgery group
hippuric acid D-glucuronic acid 1-phosphate citrate 6-phosphogluconic acid oxalosuccinate N-acetyl-DL-tryptophan benzoylphosphate nonadecanoic acid urobilinogen N-acetylglutamine S-(hydroxymethyl)glutathione
293.5 ( 37.8b 89.2 ( 13.7b 115.2 ( 46.9b 41.68 ( 1.56b 56.49 ( 5.65b 296.7 ( 46.0b 265.0 ( 95.9b 191.7 ( 37.5b 65.33 ( 3.76b 88.1 ( 11.7b 41.67 ( 3.11b
63.91 ( 1.33a 287.5 ( 16.4a 17.75 ( 2.06a 239.2 ( 11.7a 4.68 ( 0.13a 31.93 ( 1.79a 58.57 ( 4.50a 39.23 ( 5.26a 9.61 ( 0.91a 28.45 ( 4.84a 5.38 ( 0.51a
212.9 ( 13.4a,b 142.1 ( 15.2a,b 108.40 ( 4.52b 76.25 ( 5.08a,b 48.14 ( 2.06b 99.4 ( 12.1a,b 261.1 ( 17.3b 190.9 ( 24.3b 149.65 ( 5.09a,b 69.71 ( 2.94a,b 35.09 ( 9.02b
243.1 ( 30.7a,b 120.1 ( 14.5a,b 91.06 ( 7.75a,b 62.74 ( 1.16a,b 51.17 ( 2.55b 173.48 ( 1.98a,b 188.4 ( 27.5a,b 176.6 ( 15.6b 200.4 ( 35.8a,b 50.13 ( 2.32a,b 24.48 ( 1.73a,b
260.2 ( 70.0b 92.8 ( 14.7b 88.51 ( 7.64b 56.40 ( 8.43b 55.09 ( 2.02b 278.4 ( 17.9b 260.2 ( 11.0b 183.8 ( 48.5b 99.12 ( 9.28a,b 98.8 ( 17.3b 42.21 ( 2.19b
280.3 ( 36.0b 86.9 ( 10.6b 95.3 ( 16.0b 64.49 ( 6.78b 51.40 ( 3.50b 277.3 ( 16.7b 254.1 ( 38.7b 161.9 ( 27.3b 57.80 ( 8.27b 66.08 ( 3.51b 45.27 ( 2.41b
a
P < 0.05, compared to normal controls.
b
P < 0.05, compared to the model group.
thosine, guanosine, guanoine diphosphate, and the “unknown” compound, were observed with significant decreases in both the model group and sham surgery group compared to normal controls, appearing to correlate to surgical but not MI-induced injury. Otherwise the observation of their increases to nearly normal levels in SLF group may correlate to positive effects of SLF medication on surgical injury, but they were excluded in the list of potential biomarkers of MI. The other three metabolites (nos. 16-18), nicotinamide ribotide, 5-phosphoribosylamine, and glucosamine, exhibited significant alterations in SLF group but no statistically significant difference in the model group. Such alterations of metabolism appeared to not immediately correlate to anti-MI but may relate to other bioactivity of SLF. The alterations of peak intensity of the 11 potential biomarkers of five groups were summarized in Table 2. It was obvious that most of the biomarkers in SLF group revealed a highest degree of recovery among three treatment groups after 21 days’ therapeutic intervention, which was in conformity with clinical observations discussed later and could be attributed
to the fact that SLF can amplify the therapeutic efficacies of each component and exert synergistic therapeutic efficacies. 3.2. Serum Biochemical and Histological Assay. 3.2.1. Serum Biochemical Measurement. On day 21, biochemical measurements revealed a significant elevation in the levels of CK, LDH, and NEFA in the model group as compared to controls and the sham surgery group (Table 3), indicating the success of the ischemia model after coronary artery ligation and lower levels of self-recovery. Among treatment groups, a statistically significant restoration in CK, LDH, and NEFA levels was observed in rats treated with the bitherapy of PG and SM (SLF) compared with those treated with monotherapy (PG or SM). Although there was a recovery trend toward normal levels in the monotherapy groups, it was not statistically significant (P > 0.05) with the exception of LDH in SM group (P < 0.05). These results demonstrated that SLF had a better performance in recovering the clinical biochemistry in the MI model compared with the monotherapy (PG or SM). 3.2.2. Effects of Myocardial Infarction on Myocardial Tissue. As shown in Figure 4A, histopathological examination of myocardial tissue of model group depicted clear myonecrotic areas. There was complete myonecrosis with fibroblastic Journal of Proteome Research • Vol. 10, No. 2, 2011 795
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Table 3. LDH, CK, and NEFA Activities in Serum of Myocardial Ischemia Rats Induced by Coronary Artery Ligation (Mean ( SD, n ) 6)a
a
Group
LDH (µmol · mL-1)
CK (µmol · mL-1)
NEFA (µmol · mL-1)
Model group Normal control sham surgery group SLF group PG group SM group
4.36 ( 0.88 2.57 ( 0.49*** 2.72 ( 0.50*** 2.91 ( 0.42** 3.79 ( 0.67 3.61 ( 0.51*
1.08 ( 0.30 0.55 ( 0.24** 0.67 ( 0.33** 0.71 ( 0.35* 0.95 ( 0.22 0.85 ( 0.30
0.59 ( 0.24 0.25 ( 0.18** 0.38 ( 0.15* 0.34 ( 0.19* 0.49 ( 0.17 0.42 ( 0.12
LDH, lactate dehydrogenase; CK, creatine kinases; NEFA, nonesterified fatty acid. *P < 0.05, **P < 0.01, ***P < 0.001 vs model group.
Figure 4. Cardiac muscle tissue of rats in light microscope (magnification 100 diameters). (A) Model group, (B) sham surgery group, (C) PG group, (D) SM group, (E) SLF group.
proliferation and presence of chronic inflammatory cells. Moreover, marked edema and vacuolar changes along with subendocardial myonecrotic patches were clearly visible in the model group. However, in the sham surgery group (Figure 4B), integrity of myocardial cell membrane was observed with the exception of some striated muscle rupture. In the PG group (Figure 4C) and SM group (Figure 4D), focal myonecrosis with myophagocytosis and lymphocytic infiltration (myocarditis) was observed, whereas in the SLF group (Figure 4E), no confluent area of multiple subendocardial damage was seen and a reduction in inflammatory cells was observed. The above observations suggested that both the bitherapy group (SLF) and the monotherapy groups could decrease myocardial damage, but the bitherapy group exerted synergic effects on MI compared to the monotherapy groups. 3.2.3. Determination of Myocardial Infarct Size. The above biochemical findings and histopathological studies were further confirmed by cardiac infarction size evaluation. As shown in Figure 5, compared to the model group, the infarct areas of the SLF group (P < 0.01) and PG group (P < 0.05) were significantly decreased, but those of the SM group were not significantly changed. Each monotherapy reduced infarct size in MI rats to a certain degree, but neither of them were equal to the bitherapy SLF. The result also supported the existence of synergic effects of the bitherapy and could be corroborated with the metabonomic study and biochemical assay above.
4. Discussion To enhance therapeutic efficacy, combination therapy has been advocated for thousands of years by prescriptions called 796
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Figure 5. Cardiac infarction area in myocardial ischemia rats induced by coronary artery ligation (mean ( SD, n ) 6); *P < 0.05, **P < 0.01, ***P < 0.001 vs model group. MG, model group; SSG, sham surgery group; SLFG, SLF group; PGG, PG group; SMG, SM group.
formulas or fufang5,29 in TCM, a unique medical system assisting the ancient Chinese in dealing with disease. On the basis of the symptoms and characteristics of patients and guided by the theories of TCM, formulas are designed to contain a combination of different types of medicinal herbs. It is believed that, at least in some formulas, multiple components could hit multiple targets and exert synergistic therapeutic efficacies.5,6 In the past few years, the pharmaceutical industry has seen a shift from the search for “magic bullets” that specifically employ a single disease-curing molecule to the pursuit of combination therapies that comprise more than one
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Shuanglong Formula as Effective Treatment for MI
Figure 6. Effects of myocardial infarction on myocardial energy metabolism.
active ingredient.30 The Chinese medicine SLF, one example of multicomponent medicines, has been proven to be very effective in treating human CVDs especially for MI with clear active ingredients. On the basis of the chemical analysis of SLF in our lab (see Supporting Information) as well as literature reports, we believe that the main hydrophilic components from SLF are ginsenosides and salvianolic acids.22,24,31 Ginsenosides have been reported to protect against myocardial damage with concomitant increased 6-keto-PGF1R and decreased lipid peroxidation.32 Salvianolic acids could improve cardiac function through improving coronary microcirculation33 and preventing cardiomyocyte apoptosis.34,35 Ginsenosides and salvianolic acids both have antioxidant effects36,37 and can regulate enzyme activity.38,39 In this study, the extraction method of test materials had been optimized carefully by the amount of water and time of refluxing and strict quality control has been well established for every stage of the experiment. There was little change in the recovery of components detected between the individual ingredients and the combined mix extraction. In addition, we found hardly any new disappearing or emerging peaks by comparing the individual ingredients with the combined formula and also observed little visual difference by comparing the chromatogram of the mix extraction with that by combination postextraction. Therefore, we assumed that there were few cross-reactions in SLF extraction during refluxing. Considering the fact that each ingredient of the mix SLF was present at a lower concentration than each individual dose and therefore the dose of each component in SLF was smaller, we could conclude that the combined therapy was indeed more efficacious on MI than the individual (PG or SM) on the basis of a strong synergetic effect between ginsenosides and salvianolic acids through complex physiological effects in vivo. These results were also in agreement with the report of a proteomic study,40 supporting the rationale of the TCM formula: mutual reinforcement of the compounds and lead to improved therapeutic efficacy. In the present study, the metabonomic analysis revealed MIinduced changes in the ratio profiles of certain endogenous
metabolites, some of which were indentified and assumed as potential biomarkers to indicate the injury of myocardial ischemia and efficacy of medications. When we examined the data in Table 1, we found that most of the interested metabolites were involved in metabolic processes related to myocardial energy metabolism, including the TCA cycle (citrate and oxalosuccinate), pentose phosphate pathway (6-phosphogluconic acid and D-glucuronic acid 1-phosphate), and amino acid metabolism (N-acetyl-DL-tryptophan and N-acetylglutamine). As shown in Figure 6, under the condition of MI, myocardial blood flow became inadequate to meet oxygen demand and myocardial ischemia developed, resulting in reduced formation of adenosine triphosphate (ATP) via aerobic mechanisms and accelerated anaerobic ATP production by glycolysis. Meanwhile, the levels of citrate and oxalosuccinate in TCA cycle were decreased, whereas the lactate41,42 via glycolysis was increased. The lactate represents the end product of anaerobic or nonoxidative glycolysis and has been used as a marker of ischemia in patients and in experimental animal studies.43,44 However, the lactate level was not detected in this study because of its small molecular weight (90.08), which was lower than the selected mass range (m/z 100 to m/z 1500). Increased 6-phosphogluconic acid and D-glucuronic acid 1-phosphate suggested pentose phosphate pathway transferred to energy supply pathway from the main reducing power (NADPH) productive pathway when the TCA cycle was blocked. Furthermore, the TCA cycle was not only the pathway of sugar decomposition but also the pathway of fuel molecules oxidation, such as fatty acids and amino acids. Therefore, the reduction of TCA cycle intermediates also led to the reduction of fatty acid and amino acid metabolites, such as N-acetyl-DL-tryptophan and N-acetylglutamine. Alterations in CK, LDH, and NEFA have been considered as important markers in the assessment of myocardial injury.27,45 Generally, fatty acids are the main fuel for the healthy heart, with a lesser contribution coming from the oxidation of glucose and lactate. Myocardial ischemia dramatically alters fuel metabolism, causing an accelerated rate of glucose conversion to lactate and elevated levels of fatty acids. This causes a dramatic disruption in cell homeostasis (e.g., lactate accumulaJournal of Proteome Research • Vol. 10, No. 2, 2011 797
research articles tion and a decrease in pH and ATP), which results in increased CK and LDH levels.46 In this study, CK, LDH, and NEFA were measured, and their significant rise in the levels was observed in model group rats compared to those of normal controls. These observations were in conformity with previous reports and demonstrated that both myocardial tissue and cells in MI rats had been damaged. In summary, myocardial metabolism was dramatically altered by myocardial ischemia. The rates of oxygen consumption and ATP production were reduced, leading to a reduction in ATP content, high rates of glycolysis, lactate accumulation, and decreased intracellar pH. This hypothesis can be confirmed by the significant deviation of biomarkers in the model group compared with normal controls and their recovery in line with expectations in treatment groups. Most interesting, the metabonomic study provided a visualized pattern and relative quantitative estimation to evaluate the effect of various therapies. For example, as demonstrated by the visual plotting of metabolic state in Figures 2 and 3 and the estimation of potential biomarkers shown in Table 2, SLF group showed the highest degree of recovery among three treatment groups after 21 days of therapeutic intervention. These metabonomic results were in conformity with clinical observations and could be attributed to the fact that SLF can amplify the therapeutic efficacies of each component and exert synergistic therapeutic efficacies. Although the synergism theory of TCM system has been claimed and practiced for thousands of years, it is still difficult to be understood internationally and needs to be interpretted with current analytical and biomedical approaches. The metabonomic study combining with pathological inspections and clinical chemistry measures may help us understand the synergetic effect of combined therapy of TCM.
5. Conclusion Metabonomics-based findings such as the PLS-DA plotting of metabolic state and analysis of potential biomarkers in urine suggested that the bitherapy SLF has a better therapeutic effect on MI than either of the monotherapies (PG or SM). The demonstration was also confirmed by conventional assessment such as serum biochemistry and histopathological assay. It revealed that SLF enhanced myocardial energy metabolism and further improved myocardial function through synergistic therapeutic efficacies between PG and SM. We believe such a metabonomics-based approach may be extended to other related studies such as evaluating the efficacy of Chinese medicine and exploring the potential synergism of traditional formulas. Abbreviations: MI, myocardial infarction; UPLC/TOF-MS, ultraperformance liquid chromatography tandem time-of-flight mass spectrometry; SLF, Shuanglong Formula; PG, Panax ginseng; SM, Salvia miltiorrhiza; TCM, traditional chinese medicine; CVDs, cardiovascular diseases; LDH, lactate dehydrogenase; CK, creatine kinases; NEFA, nonesterified fatty acid; PCA, principal components analysis; PLS-DA, partial leastsquares-discriminant analysis; ATP, adenosine triphosphate; TCA, tricarboxylic acids; ESI, electrospray ionization source; LC-MS, liquid chromatography-mass spectrometry.
Acknowledgment. This work was financially supported by the National Basic Research Program (973 Program) of China (2007CB714505, 2007CB511903), Major Special Project for New Drugs (2009ZX09311-001, 2009ZX09103-354, 2008ZX09202), National Key Techno798
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Liang et al. logies R&D Program (2006BAI08B04- 01), and Natural Science and Technology Foundation (20805026).
Supporting Information Available: Total ion chromatogram of shuanglong formula; total ion chromatogram of Salvia miltiorrhiza; total ion chromatogram of Panax ginseng; identification and quantitative assay of major components of shuanglong formula; identification and quantitative assay of major components of Salvia miltiorrhiza; identification and quantitative assay of major components of Panax ginseng; PLSDA scores plot based on the non-normalized data. This material is available free of charge via the Internet at http://pubs.acs.org. References (1) Chattopadhyay, A.; Biswas, S.; Bandyopadhyay, D.; Sarkar, C.; Datta, A. D. Effect of isoproterenol on lipid peroxidation and antioxidant enzymes of myocardial tissue of mice and protection by quinidine. Mol. Cell. Biochem. 2003, 245, 43–49. (2) Fenton, D. E. Myocardial infarction. Available at: http://www. emedicine.com/EMERG/topic 327.htm. (3) Parang, P.; Singh, B.; Arora, R. Metabolic modulators for chronic cardiac ischemia. J. Cardiovasc. Pharmacol. Ther. 2005, 10 (4), 217– 223. (4) Jani, S.; Bergmann, S. R. Metabolic modulation of myocardial ischemia. Curr. Cardiol. Rep. 2006, 8, 123–130. (5) Anonymous The Inner Canon of Emperor Huang; Chinese Medical Ancient Books Publishing House: Beijing, 2003. (6) Wang, L.; Zhou, G. B.; Liu, P.; Song, J. H.; Liang, Y.; Yan, X. J.; Xu, F.; Wang, B. S.; Mao, J. H.; Shen, Z. X.; Chen, S. J.; Chen, Z. Dissection of mechanisms of Chinese medicinal formula RealgarIndigo naturalis as an effective treatment for promyelocytic leukemia. Proc. Natl. Acad. Sci. U.S.A. 2008, 105, 4826–4831. (7) Zimmermann, G. R.; Lehar, J.; Keith, C. T. Multi-target therapeutics: when the whole is greater than the sum of the parts. Drug Discovery Today 2007, 12 (1-2), 34–42. (8) Robertson, D. G.; Reily, M. D.; Baker, J. D. Metabonomics in pharmaceutical discovery and development. J. Proteome. Res. 2007, 6, 526–539. (9) Lindon, J. C.; Holmes, E.; Nicholson, K. Metabonomics techniques and applications to pharmaceutical research & development. Pharm. Res. 2006, 23 (6), 1075–1088. (10) Nicholls, A. W.; Mortishire-Smith, R. J.; Nicholson, J. K. NMR spectroscopic-based metabonomic studies of urinary metabolite variation in acclimatizing germ-free rats. Chem. Res. Toxicol. 2003, 16, 1395–1404. (11) Duarte, I. F.; Stanley, E. G.; Holmes, E.; Gil, A. M.; Tang, H. R.; Ferdinand, R.; Mckee, C. G.; Nicholson, J. K.; Vilca-Melendez, H.; Heaton, N.; Murphy, G. M. Metabolic assessment of human liver transplants from biopsy samples at the donor and recipient stages using high-resolution magic angle spinning 1H NMR spectroscopy. Anal. Chem. 2005, 77, 5570–5578. (12) Zhang, Q.; Wang, G.; Du, Y.; Zhu, L.; A, J. GC/MS analysis of rat urine for metabonomic research. J. Chromatogr. B 2007, 854, 20– 25. (13) Major, H. J.; Williams, R.; Wilson, A. J.; Wilson, I. D. A metabonomic analysis of plasma from Zucker rat strains using gas chromatography/mass spectrometry and pattern recognition. Rapid Commun. Mass Spectrom. 2006, 20, 3295–3302. (14) Yang, J.; Xu, G. W.; Zheng, W. F.; Kong, H. W.; Wang, C.; Zhao, X. J.; Pang, T. Strategy for metabonomics research based on highperformance liquid chromatography and liquid chromatography coupled with tandem mass spectrometry. J. Chromagr. A 2005, 1084, 214–221. (15) Lutz, U.; Lutz, R. W.; Lutz, W. K. Metabolic profiling of glucuronides in human urine by LC-MS/MS and partial least-squares discriminant analysis for classification and prediction of gender. Anal. Chem. 2006, 78, 4564–4571. (16) Theodoridis, G.; Gika, H. G.; Wilson, I. D. LC-MS-based methodology for global metabolite profiling in metabonomics/metabolomics. TrAC, Trends Anal. Chem. 2008, 27, 251–260. (17) Xie, G. X.; Zheng, X. J.; Qi, X.; Cao, Y.; Chi, Y.; Su, M. M.; Ni, Y.; Qiu, Y. P.; Liu, Y. M.; Li, H. K.; Zhao, A. H.; Jia, W. Metabonomic evaluation of melamine-induced acute renal toxicity in rats. J. Proteome Res. 2010, 9 (1), 125–133. (18) Wilson, I. D.; Nicholson, J. K.; Castro-Perez, J.; Granger, J. H.; Johnson, K. A.; Smith, B. W.; Plumb, R. S. High resolution “ultra performance” liquid chromatography coupled to oa-TOF mass
research articles
Shuanglong Formula as Effective Treatment for MI
(19)
(20)
(21) (22) (23) (24) (25) (26)
(27)
(28)
(29) (30) (31)
(32) (33)
spectrometry as a tool for differential metabolic pathway profiling in functional genomic studies. J. Proteome Res. 2005, 4 (2), 591– 598. Castro-Perez, J.; Plumb, R.; Granger, J. H.; Beattie, I.; Joncour, K.; Wright, A. Increasing throughout and information content for in vitro drug metabolism experiments using ultr-performance liquid chromatography coupled to a quadrupole time-of-flight mass spectrometer. Rapid Commun. Mass Spectrom. 2005, 19, 843–848. Nordstrom, A.; O’Maille, G.; Qin, C.; Siuzdak, G. Nonlinear data alignment for UPLC-MS based metabolomics: quantitative analysis of endogenous and exogenous metabolites in human serum. Anal. Chem. 2006, 78, 3289–3295. Nick, N. H.; Lin, G. I.; Frishman, W. H. Herbal medicine for the treatment of cardiovascular disease: Clinical considerations. Arch. Intern. Med. 1998, 9, 2225–2234. Cheng, T. O. Cardiovascular effects of Danshen. Int. J. Cardiol. 2007, 121, 9–22. Lu, J. M.; Yao, Q. Z.; Chen, C. Y. Ginseng compounds: an update on their mechanisms and medical applications. Curr. Vasc. Pharmacol. 2009, 7 (3), 293–302. Liu, X. D.; Liang, Q. L.; Luo, G. A.; Wang, Y. M. Components identification and extraction optimization of Shuangshen Prescription. Chin. Tradit. Pat. Med. 2005, 27 (10), 1128–1132. Hu, P.; Liang, Q. L.; Luo, G. A.; et al. Multi-component HPLC fingerprinting of radix salviae miltiorrhizae and its LC-MS-MS identification. Chem. Pharm. bull. 2005, 53 (6), 677–683. Qu, J.; Liang, Q. L.; Luo, G. A.; et al. Screening and identification of glycosides in biological samples using energy-gradient neutral loss scan and liquid chromatography tandem mass spectrometry. Anal. Chem. 2004, 76 (8), 2239–2247. Zhang, H. Y.; Chen, X.; Hu, P.; Liang, Q. L.; Liang, X. P.; Wang, Y. M.; Luo, G. A. Metabonomic profiling of rat serum associated with isoproterenol-induced myocardial infarction using ultraperformance liquid chromatography/time of-flight mass spectrometry and multivariate analysis. Talanta 2009, 79, 254–259. Wang, J. W.; Liu, X. L.; Ren, B.; Rupp, H.; Takeda, N.; Dhalla, N. S. Modification of myosin gene expression by imidapril in failing heart due to myocardial infarction. J. Mol. Cell. Cardiol. 2002, 34, 847–857. Anonymous Formularies for 52 Kinds of Disorders; Culture Relics Press: Beijing, 1979. Qiu, J. “Back to the future” for Chinese herbal medicines. Nat. Rev. Drug Discovery 2007, 6, 506–507. Cheng, Y. Y.; Zhang, H. J. Solid-phase extraction and liquid chromatography-electrospray mass spectrometric analysis of saponins in a Chinese patent medicine of formulated Salvia miltiorrhizae and Panax notoginseng. J. Pharmaceut. Biomed. 2006, 40, 429–432. Chen, X. Cardiovascular protection by ginsenosides and their nitric oxide releasing action. Clin. Exp. Pharmacol. P. 1996, 23, 728– 732. Chen, J. X.; Wang, S. R.; Zhao, M. J.; Lu, X. Y.; Zhang, Z.; Qin, Y. Effect of different drug dosage to activate blood circulation and
(34)
(35)
(36)
(37)
(38) (39) (40)
(41) (42) (43)
(44)
(45) (46)
to nourish qi on cardiac function and structure of congestive heart failure rats after acute myocardial infarction. Zhongguo Zhong Yao Za Zhi 2003, 28, 446–449. Au-Yeung, K. K.; Zhu, D. Y.; , O. K.; Siow, Y. L. Inhibition of stress activated protein kinase in the ischemic/reperfused heart: role of magnesium tanshinonate B in preventing apoptosis. Biochem. Phar 2001, 62 (4), 483–493. Yamamura, T.; Otani, H.; Nakao, Y.; Hattori, R.; Osako, M.; Imamura, H. IGF-I differentially regulates Bcl-xL and Bax and confers myocardial protection in the rat heart. Am. J. Physiol. Heart. Circ. Physiol. 2001, 280 (3), 1191–1200. Ji, X. Y.; Tan, B. K. H.; Zhu, Y. C.; Linz, W.; Zhu, Y. Z. Comparison of cardioprotective effects using ramipril and DanShen for the treatment of acute myocardial infarction in rats. Life Sci. 2003, 73, 1413–1426. Wang, Z.; Li, M.; Wu, W. K.; Tan, H. M.; Geng, D. F. Ginsenoside Rb1 preconditioning protects against myocardial infarction after regional ischemia and reperfusion by activation of phosphatidylinositol-3-kinase signal transduction. Cardiovasc. Drugs Ther. 2008, 22, 443–452. Ferrando, A. Effects of a standardized panax ginseng extract on the skeletal muscle of the rat: a comparative study in animals at rest and under exercise. Planta Med. 1999, 65, 239–243. , O. K.; Lynn, E. G.; Vazhappilly, R.; Au-Yeung, K. K.; Zhu, D. Y.; Siow, Y. L. Magnesium tanshinoate B (MTB) inhibits low density lipoprotein oxidation. Life Sci. 2001, 68, 903–912. Fan, X. M.; Li, X.; Lv, S. F.; Wang, Y. M.; Zhao, Y. F.; Luo, G. A. Comparative proteomics research on rat MSCs differentiation induced by Shuanglong Formula. J. Ethnopharmacol. 2010, 131, 575–580. Stanley, W. C.; Sabbah, H. N. Metabolic therapy for ischemic heart disease: the rationale for inhibition of fatty acid oxidation. Heart Failure Rev. 2005, 10, 275–279. Stanley, W. C.; Recchia, F. A.; Lopaschuk, G. D. Myocardial substrate metabolism in the normal and failing heart. Physiol. Rev. 2005, 85, 1093–1129. Guth, B. D.; Wisneski, J. A.; Neese, R. A.; White, F. C.; Heusch, G.; Mazer, C. D.; Gertz, E. W. Myocardial lactate release during ischemia in swine. Relation to regional blood flow. Circulation 1990, 81, 1948–1958. Dyck, J. R. B.; Cheng, J. F.; Stanley, W. C.; Barr, R.; Chandler, M. P.; Brown, S.; Wallace, D.; Arrhenius, T.; Harmon, C.; Yang, G.; Nadzan, A. M.; Lopaschuk, G. D. Malonyl coenzyme a decarboxylase inhibition protects the ischemic heart by inhibiting fatty acid oxidation and stimulating glucose oxidation. Circ. Res. 2004, 94, e78-e84. Wexler, B. C.; Judd, J. T.; Kittinger, G. W. Myocardial necrosis induced by isoproterenol in rats. Angiology 1968, 19, 665–682. Wolff, A. A.; Rotmensch, H. H.; Stanley, W. C.; Ferrari, R. Metabolic approaches to the treatment of ischemic heart disease: the clinicians’ perspective. Heart Failure Rev. 2002, 7, 187–203.
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