Article Physical Chemistry
September 2010 Vol.55 No.26: 2945–2950 doi: 10.1007/s11434-010-3348-4
SPECIAL TOPICS:
The action of medicinal animal horns on Escherichia coli growth investigated by microcalorimetry and chemometric analysis YAN Dan1, HAN YuMei1,2,3, LUO JiaoYang1,2, ZHANG Ping1, TANG HuiYing1, PENG Cheng2 & XIAO XiaoHe1* 1
Institute of Chinese Medicine, 302 Hospital of People’s Liberation Army, Beijing 100039, China; Chengdu University of Traditional Chinese Medicine, Chengdu 610075, China; 3 Chongqing Institute of Technology, Chongqing 400050, China
2
Received December 12, 2009; accepted April 1, 2010
The action of Cornu Cervi Pantotrichum (CCP), Cornu Cervi (CC) and Cornu Saigae Tataricae (CST) on Escherichia coli growth were investigated using microcalorimetry to find the heat change regularity of microbial growth. The similarity of thermogenic curves and thermodynamics parameters were investigated as evaluation index, such as the growth rate constant in the first exponential phase (k1), maximum power in the first exponential phase (P1), maximum power in the secondary exponential phase (P2), peak time in the first exponential phase (T1), peak time in the stationary phase (T2) and the total heat production in stage 1 (Q1), and the total heat production in stage 2 (Q2). Chemometric analysis was used as a reference for the bioactivity evaluation of medicinal animal horns. The results indicated that the similarity between CST and the control was smaller than that between CCP, CC and the control. Both CCP and CC could increase the heat in the microbial growth, whereas CST decreased it. The biotic thermal activity of different medicinal animal horns was objectively, qualitatively, and quantitatively evaluated by the similarity of thermogenic curves and thermodynamics parameters analysis. medicinal animal horns, microcalorimetry, chemometric analysis, Escherichia coli, thermokinetic characteristic parameters, thermal activity profile Citation:
Yan D, Han Y M, Luo J Y, et al. The action of medicinal animal horns on Escherichia coli growth investigated by microcalorimetry and chemometric analysis. Chinese Sci Bull, 2010, 55: 2945−2950, doi: 10.1007/s11434-010-3348-4
As examples of Chinese medicinal animal horns (MAH), Cornu Cervi Pantotrichum (CCP), Cornu Cervi (CC) and Cornu Saigae Tataricae (CST) were recorded in the Chinese Pharmacopoeia 2005 [1]. Each type contains such constituents as keratin, phospholipids, cholesterol and microelements. However, their properties and indications differ widely. Conventional methods for the quality control of plant medicine, such as assaying, have difficulty in evaluating the quality of MAH [2]. The evaluation methods for biological products are applied for reference. Firstly, the sources of MAH and biological products are similar. Similar to biological products, MAH originates from the body, tissues, *Corresponding author (email:
[email protected])
© Science China Press and Springer-Verlag Berlin Heidelberg 2010
organs, physiological or pathological products and excreta of animals. Secondly, the chemical compositions of MAH are similar to biological products, including proteins and polypeptides. Therefore, a new method for determining the bioactivity of MAH, including biological value and biological profile, would be valuable [3–7]. Both a biological model and a bioassay method are necessary to assess these characteristics. Intestinal flora commonly includes probiotics, harmful bacteria and intermediate flora. Their interactions maintain the relative balance of intestinal microecology. As the primary bacteria in intestinal flora, Escherichia coli (E. coli) constitutes normal flora along with other intestinal bacteria, showing an adverse reaction if any disbalance or metastasis csb.scichina.com
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of intestinal flora occurs [8,9]. The exertion of the tonifying effect of Chinese materia medica mainly correlates with their action of regulating the intestinal internal environment, balancing the microbial population, and intervening the metabolism of the intestinal bacteria [8,10,11]. E. coli is often utilized to determine the bioactivity of an antipyretic or antibiotic as an example of a living model, and thus provides a reasonable means to assess the bioactivity of MAH (CCP, CC and CST) [12–14]. Microcalorimetry is a quantitative, inexpensive and versatile method for measuring various reactions in physics, chemistry and biology. It provides a general analytical tool for the characterization of cell growth processes, and has been extensively used to investigate the interactions between drugs and cultured cells [15–18]. By monitoring the dynamic thermodynamics parameters and the thermogenic curves (P-t), microcalorimetry more specifically allows the investigation of the heat-output of slightly exothermic or endothermic processes occurring during the growth and metabolism of microorganisms, cells, tissues and organs under the action of drugs. In this study, we applied microcalorimetry, a kinetic and precise method, which focuses on the energy change of microbial growth, to investigate the action of MAH on the growth of E. coli. The similarity of the thermogenic curves and thermodynamics parameters were investigated, such as the growth rate constants in the first exponential phase (k1), maximum power in the first exponential phase (P1), maximum power in the secondary exponential phase (P2), peak time in the first exponential phase (T1), peak time in the stationary phase (T2), the total heat production in stage 1 (Q1) and the total heat production in stage 2 (Q2). Chemometric analysis was used to analyze these parameters to characterize the regularity of heat change when the growth of E. coli was affected by MAH, thereby allowing assessment of the bioactivity of MAH.
1 Materials and methods 1.1
Instrumentation
An 8-channel heat conduction calorimeter (TAM air, Thermometric AB, Sweden) was held together in a single removable block for heat flow measurements in the milliwatt range under isothermal conditions. 1.2
Materials
Escherichia coli (CCTCC AB91112) was provided by the Chinese Center for Type Culture Collections, National Institute for the Control of Pharmaceutical and Biological Products, China. E. coli was grown in a peptone culture medium, which contained 10 g peptone, 5 g beef extract and 5 g NaCl per liter. Medium pH was adjusted to 7.0–7.2 with 1 mol/L NaOH and 1 mol/L HCl. The medium was steril-
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ized at 121°C for 30 min. Simulated gastric fluid was prepared as follows: 16.4 mL hydrochloric acid 10% (g/mL), 800 mL water and 10 g pepsin were mixed in turn and shaken, after which 1000 mL water was added. CCP is the hairy, nonossifying young horn of a male deer or stag of Cervus nippon Temminck, vertebrate of the family Cervidae (Jilin, China). CC is the ossified horn of a male deer or stag of Cervus nippon Temminck (Jilin, China). CST is the horn of Saiga tatarica Linnaeus (Xinjiang, China). All of these medicinal animal horns were supplied by Beijing Tongrentang Technologies Co., Ltd. 1.3
Sample preparation
Considering the chemical components and administration route of these drugs, simulated gastric fluid was used to prepare the sample solutions in this study. Firstly, 2 g powder of each type of medicinal animal horns was weighed and added into three volumetric flasks. Secondly, 15 mL simulated gastric fluid was added and after ultrasonication for 5 min, the volumetric flasks were cooled. Thirdly, simulated gastric fluid was added into the flasks up to the containing mark. The flasks were then vibrated in an oscillator at 37°C for an hour. After standing for 5 min, the supernatant was finally obtained as the sample solution. 1.4
Experimental procedure
The microcalorimeter was thermostated at 37°C, and the ampule method was adopted. All of the ampules, filled with MAH and a cell suspension of E. coli, were sealed up and put into an 8-channel calorimeter block. All procedures were completely sterilized. After about 30 min (the temperature of the ampules reached 37°C), the thermogenic curves were recorded until they returned to the baseline. Because the bacterial metabolic process was monitored under isothermal and isochoric conditions, the nutrients and oxygen consumed by the cells was limited. All data was continuously collected using the dedicated software package (PicoLog TC-80, TA Corporation, USA). 1.5
Chemometric analysis
(1) Similarity analysis. To learn from the similarity analysis for HPLC chromatographic fingerprints of traditional Chinese medicine from different sources [19], the thermogenic curves of E. coli growth affected by different concentrations of MAH are evaluated by their similarities, which come from the calculation of the correlative coefficients of the original data. In this study, the correlation coefficients of similarity among the thermogenic curves of E. coli growth with and without MAH were calculated using the cosine method [20]. (2) Principle component analysis. From the thermogenic curves of E. coli growth, many quantitative parameters were
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obtained which represented the bioactive effects of MAH. In order to reduce the parameters and find the change potency of the effects, the main parameters, which reflected the potency, were analyzed. Principle component analysis (PCA) is a sophisticated technique which is widely used for reducing the dimensions of multivariate problems. As a nonparametric method of classification, it makes no assumptions about the basic statistical data distribution [21, 22]. It reduces the dimensionality of the original data set by explaining the correlation amongst a large number of variables in terms of a smaller number of underlying factors (PCs) without losing much information. Here, PCA was performed on the many quantitative parameters taken from the thermogenic curves to determine the main parameters utilizing Unscrambler 9.8 from Camo AS (Trondheim, Norway).
2 Results 2.1
Thermogenic curves
Figure 1 shows the thermogenic curves of E. coli without MAH. According to the principles of microorganism growth [15,23,24], the curve was divided into two stages (stages 1 and 2) and the following five phases: a lag phase (A–B), the first exponential growth phase (B–C), a stationary phase (C–D), the second exponential growth phase (D–E), and a decline phase (E–F). Under the above-mentioned conditions, the sample solutions of three MAH at different concentrations were added into TAM air in turn. The corresponding thermogenic curves of E. coli growth affected by different concentrations of three MAH solutions are shown in Figure 2. As seen from the profiles of these curves, the growth of the E. coli samples were influenced by these MAH. 2.2 Quantitative thermokinetic parameters for E. coli growth By analyzing the five phases in the thermogenic curves of E. coli without MAH, the second exponential growth phase (D–E) was regarded as part of a stationary phase because
Figure 2 P-t curves of E. coli growth with different concentrations of CCP (a), CC (b) and CST (c). E. coli was cultured in a peptone culture medium with different concentrations of the three MAH, and monitored by a microcalorimeter at 37°C.
the growth rate constant of the phase (D–E) was very small and much less than that of the phase (B–C) [25]. In this phase (D–E), the growth of E. coli was so complicated that the exponential metabolism model of E. coli was not suitable for a fitting calculation. Therefore, the exponential metabolism model of E. coli was used in the first exponential growth phase (B–C) [26]. Pt = P0 exp (kt) or ln Pt = ln P0 + kt,
Figure 1 P-t growth curves of E. coli cultured in a peptone culture medium and monitored by a microcalorimeter at 37°C.
where P0 represents the heat-output power at the beginning of the baseline, and Pt represents it at time t. Thus, using the data ln Pt and t taken from the curves to fit a linear equation, each growth rate constant k1 of the first exponential phase for the growth of E. coli at 37°C without MAH was calcu-
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lated and is shown in Table 1, where k1= (0.0137±0.00031) min–1. All correlation coefficients were greater than 0.98, and the standard deviation (SD) was 0.003, indicating that good correlation and reproducibility were obtained under identical experimental conditions. Heterogeneity will occur if the microbial population grows under the restrictive cultivated conditions. Dynamic growth involves a nonlinear and multi-variable process. To obtain the other thermokinetic parameters, OriginLab software (OriginLab Corporation, Northampton, USA) was used for the thermogenic curves. The quantitative thermokinetic parameters obtained from the thermogenic curves of E. coli growth affected by different concentrations of Table 1
CST
2.3
Data analysis
(1) Similarity analysis of thermogenic curves. The cosine vector method was applied to analyze the similarity of the thermogenic curves to characterize the differences. The thermogenic curve which showed the growth of E. coli without MAH was regarded as the reference, and the thermogenic curves of CCP, CC and CST at different concentrations were compared with it. The corresponding data set of similarity is shown in Figure 3.
3 14.0 0.993
4 13.8 0.987
5 13.4 0.993
6 13.9 0.989
SD a) 0.31 0.003
Thermokinetic results of the action of MAH on E. coli ( X ± SD, n=6)
Sample Control CCP
CC
MAH solutions are shown in Table 2. Suitable chemometric methods were utilized in this evaluation.
Growth rate constants k1 of E. coli cultured in a peptone culture medium and monitored by a microcalorimeter at 37°C
Experiment no. 1 2 k1(×10–3 min–1) 13.3 14.0 r b) 0.991 0.994 a) SD is the standard deviation. b) r is the correlation coefficient. Table 2
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C (mg/mL) 0 5 10 15 20 25 5 10 15 20 25 5 10 15 20 25
k1(×10–3 min–1) 13.8±0.30 15.3±0.22 16.6±0.32 15.1±0.15 16.4±0.24 15.2±0.11 16.0±0.09 16.0±0.35 16.1±0.26 15.6±0.18 16.2±0.41 12.1±0.33 11.0±0.37 10.2±0.29 9.10±0.16 8.22±0.21
P1 (mW) 0.750±0.018 0.768±0.036 0.742±0.016 0.756±0.022 0.757±0.034 0.749±0.030 0.854±0.027 0.845±0.041 0.835±0.038 0.833±0.024 0.827±0.033 0.733±0.028 0.668±0.036 0.495±0.019 0.519±0.031 0.444±0.025
T1 (min) 247.2±1.69 282.1±2.26 281.8±1.32 273.3±2.02 271.1±0.92 270.9±2.86 226.4±1.67 219.7±2.39 223.9±1.63 211.6±1.82 209.3±0.89 224.1±1.69 234.6±2.41 248.7±2.09 279.3±1.97 306.9±2.42
Figure 3 Delineation of similarities of thermogenic curves between the control and MAH.
Q1 (J) 4.51±0.15 6.91±0.21 6.29±0.25 6.64±0.09 6.44±0.28 6.65±0.14 6.22±0.18 6.27±0.22 6.32±0.13 5.94±0.30 6.07±0.27 6.95±0.23 7.14±0.32 6.58±0.12 6.85±0.20 7.06±0.29
P2 (mW) 1.495±0.012 1.377±0.032 1.496±0.024 1.602±0.028 1.793±0.018 1.942±0.035 1.512±0.032 1.511±0.026 1.715±0.011 1.913±0.041 1.986±0.027 1.317±0.022 1.282±0.032 1.292±0.030 1.268±0.021 1.222±0.038
T2 (min) 909.1±2.33 973.3±2.05 939.0±2.15 893.2±1.82 825.2±1.39 774.3±0.98 958.91.27 901.3±1.39 802.0±2.30 746.4±2.59 732.3±1.63 1290.3±1.77 1321.8±2.08 1372.6±1.95 1505.7±2.96 1609.2±2.45
Q2 (J) 48.86±0.23 50.03±0.35 53.02±0.17 55.31±0.42 57.10±0.36 58.80±0.25 50.18±0.27 52.59±0.32 53.98±0.19 55.74±0.37 57.97±0.32 47.89±0.39 46.88±0.15 46.11±0.13 44.32±0.37 43.85±0.22
Figure 3 shows that two similarity trends appeared when the thermogenic curves of the control were compared with the curves for the three MAH. Firstly, the similarity trends of CCP and CC were similar, especially when both of them were at low concentrations (0–15 mg/mL). Only when both CCP and CC were at a high concentration (15–25 mg/mL), was the similarity between CCP and the control smaller than that between CC and the control. Secondly, the similarity between CST and the control was the smallest which indicated that CST impacted E. coli growth the most significantly. The thermogenic curves in Figure 2 also showed that the curves of CCP and CC approached the Y axis, while CST gradually approached the X axis with increasing concentration. (2) Thermokinetic characteristic parameters. As a qualitative analysis, the above-mentioned similarity analysis
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identified the variation of the thermogenic curves of E. coli affected by the three MAH. The thermokinetic parameters were characterized to discover the action of MAH on E. coli. However, some of the data (k1, P1, T1, Q1, P2, T2 and Q2) contained overlapping and low-quality information. These shortcomings made it difficult to directly uncover the regularity of the data. Considering that certain associability existed between these parameters, a few unrelated comprehensive parameters were needed as much as possible to cover the information of primary multi-variables. Principle component analysis of chemometric analysis was applied to search for these comprehensive parameters, in order to evaluated the action of MAH on E. coli. Principle component analysis (PCA) is utilized in applied statistics and data analysis for summarizing multivariate variation. It facilitates visualizing the information of the data set in a few principal components, while retaining the maximum possible variability within that set. PCA was performed on seven quantitative parameters: k1, P1, T1, Q1, P2, T2 and Q2. On the basis that the eigenvalues were larger than one, three principal components of CCP accounting for 96.9% of the total variance were considered to be significant. Two principal components of CC accounting for 97.6% of the total variance were considered to be significant. The score plot of the principal components (Figure 4(a) and (b)) showed that parameters 5 (P2) and 7 (Q2) may be the main two parameters which were significant in evaluating the effect of CCP and CC. Two principal components of CST accounting for 97.2% of the total variance
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were considered to be significant. The score plot of the principal components (Figure 4(c)) showed that parameters 1 (k1) and 3 (T1) might be the main two parameters for evaluating the effect of CST. The values of P2, Q2 (CCP and CC) and k1, T1 (CST) in Table 2 indicated the regularity of the action of three MAH on E. coli. Based on Figure 5, P2 and Q2 generally showed an increscent tendency with the increase of the concentrations of CCP and CC. When the concentration of CC and CCP was low (0–10 mg/mL), the P2 of CC did not change significantly, and the P2 of CCP generally decreased before increasing again. The k1 of CST gradually decreased when the concentration was increasing. The T1 of CST shortened at a concentration of 0–5 mg/mL, while it was prolonged when the concentration was above 5 mg/mL. Linear regression analysis was employed to analyze the concentrations of the three MAH and the corresponding thermokinetic parameters, which were obtained from PCA. The coefficient correlation test indicated fine linear relationships (r >0.96) which meant that fine dependence existed between these parameters and their associated concentrations.
3 Discussion This study investigated the characteristics and regularity of E. coli growth affected by the three MAH by means of analyzing their thermogenic curves and thermokinetic parameters. It was found that thermokinetic parameters P2 and Q2
Figure 4 Score plots for PCA. The scatter plots were obtained by PCA for the seven quantitative thermokinetic parameters (1) k1, (2) P1, (3) T1, (4) Q1, (5) P2, (6) T2 and (7) Q2 which were taken from the metabolic power-time profiles of E. coli growth with different concentrations of CCP (a), CC (b) and CST (c), utilizing Unscrambler 9.8 from Camo AS (Trondheim, Norway). The main parameters were marked with circles.
Figure 5 Relationship between thermokinetic characteristic parameters and the concentration of MAH. The changes of P2 and Q2 related to the concentration of CCP and CC (a), the changes of k1 and T1 related to the concentration of CST (b).
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provided information about the action of CCP and CC on E. coli growth. The results showed that CCP and CC increased heat quantity during E. coli growth. This conclusion was in accordance with the tonifying effect of CCP and CC, which invigorated such physiological activities as anti-aging and accelerating gastrointestinal motility. Similarly, the thermokinetic parameters k1 and T1 provided information about the action of CST on E. coli growth. The k1 and T1 of CST indicated that CST inhibited E. coli growth, and prolonged T1. The heat quantity of E. coli growth affected by CST showed a downtrend (Table 2). This conclusion was in accordance with the relieving heat effect of CST, which is known to inhibit the physiological activities of organisms. The thermokinetic parameters and thermogenic curves provided information about the biothermal activity to objectively, qualitatively and quantitatively evaluate the biothermal activity of three MAH. This investigation also determined that MAH regulates the heat quantity changes during the growth of E. coli. CCP and CC increased the heat quantity of the bacterial reaction system, while CST decreased it. This result indicated that microcalorimetry is a means of evaluating the medicinal characteristics of traditional Chinese medicine in order to link it to modern science.
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Conclusions
In this study, a microcalorimetry method was developed to investigate quantitative thermokinetic parameters including k1, T1, P2, Q2 and qualitative thermogenic curves using a similarity analysis based on the heat change of microorganisms. This method achieved the goal of dynamically monitoring the entire process of microorganism growth during its exposure to drugs and made it possible to qualitatively and quantitatively reflect the entire process of drug bioactivity.
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20 This work was supported by the National Natural Science Foundation of China (30625042 and 30873385), and the Key Technology of the National Great New Drugs Development Project of China (2009ZX09502-003 and 2009ZX09308-005).
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