Evidence-Based Complementary and Alternative Medicine
Volume 2016 (2016), Article ID 8469024, 8 pages
http://dx.doi.org/10.1155/2016/8469024

Research Article

Spectral Analysis of Chinese Medicinal Herbs Based on Delayed Luminescence

Jingxiang Pang,¹ Xiaoyan Zhu,² Yanli Liu,³ Jialei Fu,⁴ Xiaolei Zhao,¹ Meina Yang,¹ Eduard van Wijk,⁵ Mei Wang,⁵ Xiaoyan Nie,¹ and Jinxiang Han¹

¹Shandong Medicinal Biotechnology Center, Key Laboratory for Biotech-Drugs, Ministry of Health, Shandong Academy of Medical Sciences, Jinan, Shandong 250062, China
²Shandong Center for Disease Control and Prevention, Jinan, Shandong 250014, China
³Department of Basic Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong 250355, China
⁴Shandong Academy of Traditional Chinese Medicine, Jinan, Shandong 250014, China
⁵Sino-Dutch Centre for Preventive and Personalized Medicine/Centre for Photonics of Living Systems, Leiden University, 2300 RA Leiden, Netherlands

Received 13 April 2016; Accepted 9 June 2016

Academic Editor: Fabio Firenzuoli

Copyright © 2016 Jingxiang Pang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

Traditional Chinese medicine (TCM) plays a critical role in healthcare; however, it lacks scientific evidence to support the multidimensional therapeutic effects. These effects are based on experience, and, to date, there is no advanced tool to evaluate these experience based effects. In the current study, Chinese herbal materials classified with different cold and heat therapeutic properties, based on Chinese medicine principles, were investigated using spectral distribution, as well as the decay probability distribution based on delayed luminescence (DL). A detection system based on ultraweak biophoton emission was developed to determine the DL decay kinetics of the cold and heat properties of Chinese herbal materials. We constructed a mathematical model to fit the experimental data and characterize the properties of Chinese medicinal herbs with different parameters. The results demonstrated that this method has good reproducibility. Moreover, there is a significant difference () in the spectral distribution and the decay probability distribution of Chinese herbal materials with cold and heat properties. This approach takes advantage of the comprehensive nature of DL compared with more reductionist approaches and is more consistent with TCM principles, in which the core comprises holistic views.

1. Introduction

The cold and heat properties of Chinese medicinal herbs are classified according to the traditional Chinese medicine (TCM) principles, which comprise a core concept of TCM. The cold or heat property reflects a trend that Chinese medicinal herbs affect the transformation of heat or cold properties of the human body. Cold is a Yin disease factor that causes symptoms such as chilliness, headache, and body aches. Cold is reported to damage the Yang energy. Heat (also heat or flame) is also a Yang pathogenic factor with symptoms that include fever, inflammation, dry skin, and constipation. Chinese medicinal herbs regulate the cold or heat properties of the body to achieve a balance between them [1]. Cold herbs treat heat diseases, and heat herbs treat cold diseases. Thus, the cold or heat properties of Chinese medicinal herbs and the application of the corresponding knowledge regarding the diagnosis, differentiation, and treatment of diseases comprise important aspects in TCM. Recently, many groups have investigated herbs to identify their essence and properties [2–5]. However, the scientific evidence regarding the cold and heat properties of Chinese medicinal herbs has remained unclear. The development of a novel scientific method that provides a quantitative measure of these properties is a challenge and represents the aim of the present study.

Delayed luminescence (DL) is the long-term decay of ultraweak photon emission from biological systems following exposure to illumination, and it was discovered in green plants in 1951 [6]. DL technology has recently been used as a noninvasive tool to investigate germination, food quality, tumor cells, and environmental pollution [7–11]. DL is correlated with the functional state of the biological sample [12–15], which suggests that DL measurements may represent a potentially valuable method to analyze the cold and heat properties of Chinese medicinal herbs [16].

Despite the broad utility of DL, no study has investigated the DL signatures of Chinese herbal materials. In this study, a sensitive photon-counting system was constructed to collect DL spectra and characterize Chinese medicinal herbs [17].

In this study, we report DL data collected from the roots of Chinese medicinal herbs. The aims are to identify a correlation between the physical parameters connected to DL and the cold and heat properties of Chinese medicinal herbs as well as establish an evaluation method and indicator of the cold or heat property of Chinese medicinal herbs. This approach provides a comprehensive picture of the herbs versus the more reductionist ideas used in chromatography approaches and is more consistent with the holistic view at the heart of TCM.

2. Material and Methods

2.1. Measurement System and Measurement Procedure of DL

The device (Figure 1) includes a dark sample chamber and a vertical photomultiplier tube (PMT) with a 46 mm photocathode (Electron Tubes Enterprises Ltd., UK, type 9558QB) [17]. The PMT is cooled to −25°C to reduce the dark count rate to less than 10 counts per second.

Figure 1: Hardware setup of spectral photon-counting system.

A 55 mm Petri dish filled with the dried samples was placed in the dark chamber 12 cm from the PMT shutter. Herbs (1 g) covered the bottom of the Petri dish. To excite the samples, we used a white LED (LED Engin, USA, type LZ4-00MD00). The interval time was 100 ms. The measurement time was 20 s. A shutter system between the excitation source and the sample controlled the excitation. A photon-counting unit (HAMAMATSU, C9744) was used for all data acquisition.

During the DL measurement, a spectral analysis was performed with seven long-pass cutoff optical interference filters (Schott, Germany) [18, 19]. These filters were placed in a rotating wheel, which was located between the photomultiplier and the shutter in front of the photomultiplier. The rotating wheel has 8 openings: open (without filter), GG395, GG450, GG495, OG550, RG610, RG665, and RG715 (Figure 1). This combination of long-pass cutoff filters produces DL curves for 8 wavelength ranges: all wavelengths, <395, 395–450, 450–495, 495–550, 550–610, 610–665, 665–715, and >715 nm, respectively. The wheel rotates counterclockwise.

2.2. Herbal Materials

All samples (37 raw root and Rhizome herbs) were collected by Jinan Jianlian Chinese medicinal herb store in Shandong province, China. An experienced herbalist (Professor Yuanbin Zhang) at the Shandong Academy of Medical Sciences identified the samples. The samples were divided into two groups based on their cold or heat properties (Table 1).

Table 1: Nomenclature of selected cold and heat Chinese medicinal herbs.

Pharmaceutical name
Chinese Pin Yin
Latin botanical name
Plant part used

Classification as cold
Radix Pulsatillae
Bai Tou Weng
Pulsatilla chinensis (Bge.) Regel.
Root

Radix Dichroae
Chang Shan
Dichroa febrifuga Lour.
Root

Radix Stephaniae Tetrandrae
Fang Ji
Stephania tetrandra S. Moore.
Root

Radix Scutellariae
Huang Qin
Scutellaria baicalensis Georgi.
Root

Radix Rhapontici
Lou Lu
Rhaponticum uniflorum (L.) DC.
Root

Radix Changii
Ming Dang Shen
Changium smyrnioides Wolff.
Root

Radix Curcumae
Yu Jin
Curcuma wenyujin Y. H. Chen et C. Ling.
Root

Radix Arnebiae
Zi Cao
Lithospermum erythrorhizon Sien. et Zucc.
Root

Radix Scrophulariae
Xuan Shen
Scrophularia ningpoensis Hemsl.
Root

Radix Paeoniae Alba
Bai Shao
Paeonia lactiflora Pall.
Root

Radix Trichosanthis
Tian Hua Fen
Trichosanthes kirilowii Maxim.
Root

Radix Puerariae
Ge Gen
Pueraria lobata (Willd.) Ohwi.
Root

Radix Panacis Quinquefolii
Xi Yang Shen
Panax quinquefolius L.
Root

Radix Paeoniae Rubra
Chi Shao
Paeonia lactiflora Pall.
Root

Radix Peucedani
Qian Hu
Peucedanum praeruptorum Dunn.
Root

Radix Stellariae
Yin Chai Hu
Stellaria dichotoma L. var. lanceolata Bge.
Root

Radix Sophorae Flavescentis
Ku Shen
Sophora flavescens Ait.
Root

Radix Ophiopogonis
Mai Dong
Ophiopogon japonicus (Thunb.) Ker-Gawl.
Root

Radix Adenophorae
Nan Sha Shen
Adenophora tetraphylla (Thunb.) Fisch.
Root

Rhizoma Phragmitis
Lu Gen
Phragmites communis (L.) Trin.
Rhizome

Rhizoma Anemarrhenae
Zhi Mu
Anemarrhena asphodeloides Bge.
Rhizome

Rhizoma Belamcandae
She Gan
Belamcanda chinensis (L.) DC.
Rhizome

Radix et Rhizome Polygoni Cuspidati
Hu Zhang
Polygonum cuspidatum Sieb. et. Zucc.
Rhizome and root

Classification as heat
Radix Morindae Officinalis
Ba Ji Tian
Morinda officinalis How.
Root

Radix Angelicae Dahuricae
Bai Zhi
Angelica dahurica (Fisch. ex Hoffm.) Benth. et Hook. F.
Root

Radix Vladimiriae
Chuan Mu Xiang
Vladimiria souliei (Franch.) Ling.
Root

Radix Angelicae Sinensis
Dang Gui
Angelica sinensis (Oliv.) Diels.
Root

Radix Linderae
Wu Yao
Lindera strychnifolia (Sieb. et Zucc.) Vill.
Root

Radix Polygalae
Yuan Zhi
Polygala tenuifolia Willd.
Root

Radix Stemonae
Bai Bu
Stemona sessilifolia (Miq.) Miq.
Root

Radix Angelicae Pubescentis
Du Huo
Angelica pubescens Maxim. F. biserrata.
Root

Radix Saposhnikoviae
Fang Feng
Saposhnikovia divaricata (Turez.) Schischk.
Root

Radix Astragali
Hunag Qi
Astragalus membranaceus (Fisch.) Bge.
Root

Rhizoma Atractylodis Macrocephalae
Bai Zhu
Atractylodes macrocephala Koidz.
Rhizome

Rhizome Galanga
Gao Liang Jiang
Alpinia officinarum Hance.
Rhizome

Radix et Rhizome Ginseng Rubra
Hong Shen
Panax ginseng C. A. Mey.
Rhizome and root

Radix et Rhizome Asteris
Zi Wan
Aster tataricus L. f.
Rhizome and root

2.3. Preparation of Powder

The herbal samples were pulverized to 0.125–0.177 mm with a grinder (Jinsui Company, Zhejiang province, China, type JSP-350). Different diameters of herbal particles were selected with 125, 150, and 850 μm sieves (Yongkang Company, Zhejiang province, China). The sieved samples were subsequently placed in a 55 mm Petri dish and stored in a light-tight box (Chengsheng Company, Tianjin) with silica desiccant (Dingfeng Company, Zhejiang province, China, 3–5 mm Blue) for at least 16 hours prior to the DL measurements [20–23]. The water content of the samples was 6.4–7.9% according to the Chinese pharmacopoeia (2010). The room temperature was maintained at °C [24–26].

2.4. Data Analysis

Each sample was measured at least three times, and the decay kinetic data were averaged for subsequent data analysis. Statistical analyses were conducted using SPSS V.17 software (SPSS, USA). We used an independent-sample test to compare the DL kinetic parameters of the herbal samples. values less than 0.05 were considered significant. For data fitting, Statistic 10 software was used.

3. Results

3.1. DL Reproducibility Testing

We selected two representative Chinese medicinal herbs with heat and cold properties to measure the reproducibility of the DL experiments. Each sample was analyzed with the powders of five independent batches of herbs under the same experimental conditions. Empty Petri dishes served as a control (Figure 2). Figure 2 also presents the long time decay emission of two Chinese medicinal herbs (Radix Sophorae Flavescentis (classified as cold) and Radix et Rhizome Ginseng Rubra (classified as heat)) following white light illumination. The reproducibility of the technique was good. The standard deviation of the DL intensity values was <5% in the first 5 seconds and 5–15% during subsequent time points. This difference occurred because the signal was lower at the later time points; thus, the influence of the noise increased.

Figure 2: DL decay curve of Radix Sophorae Flavescentis (cold) and Radix et Rhizome Ginseng Rubra (heat) with no filter. Each sample was prepared in triplicate and analysis repeated three times. The noise of the empty dish is far lower than the signal.

3.2. Decay Probability Distribution of DL

The kinetics of the light-induced DL temporal trends have been described by a hyperbolic function law in multiple previous studies [27–30]:

Here, is the initial intensity following illumination, is the index factor associated with the rate of decay, and is the characteristic time, which is a constant specific to the sample.

Previous results implied that the DL of dried Chinese herbal materials is a complicated light emission process, which is similar to previous reports regarding sera and bacteria [31, 32]. To obtain comprehensive information regarding this complex decay process, we used a widely accepted approach in which time-resolved DL decays are described as continuous distributions of decay times or rate constants via the introduction of a probability density function as follows [33–35]:

where is a normalizing constant and is a rate constant of the decay process. Based on (1) and (2), we obtain

Therefore, the decay probability distribution may be obtained through anti-Laplace transform processing:

where . Based on (4), decay probability distributions were created for 13 heat herbs and 24 cold herbs (Figure 3(a)). The cold and heat groups have substantially different decay probability distributions. The difference may also be correlated with the different ages and growth locations or postharvest processing. This leads to various complex reactions, including changes in the chemical makeup of the herbs and internal structural changes. Ultimately, external influences will be reflected in the overall efficacy of the TCM. To analyze the differences between the heat and cold Chinese medicinal herbs and to describe the DL decay kinetics, we used the peak decay rate and its corresponding peak value. From , we obtain and as follows:

(a)

(b)

(c)

Figure 3: (a) The decay probability distribution in heat (red) and cold (black) herbs. (b) Comparison of the average of (23 cold herbs versus 14 heat herbs), the cold herbs average of is , and the heat herbs average of is ; . (c) Comparison of the average of (23 cold versus 14 heat herbs), the average of is of the cold herbs, and the average of is ; value < 0.05.

According to (1), three parameters, including , , and , may be obtained by fitting the experimental data. According to (5), represents the peak value, and represents the peak decay rate. As shown in Figures 3(b) and 3(c), the average of is of 23 cold herbs, which is substantially less than the average of of 14 heat herbs () and significant at . In addition, the average of is from the cold herbs which was increased compared with the heat herbs () and significant at .

3.3. DL Emission Spectra of Chinese Medicinal Herbs

Another intrinsic parameter that could be used to develop a strategy of discrimination is based on the measurement of emission spectra. Our initial findings are that the DL emission spectra of different properties of Chinese herbal materials are also with obvious difference. We used 7 different long-pass filters (as described in Section 2.1) to measure DL. Different spectra were collected based on the filter set used. Along with the filter wheel rotation, the emission photons can be obtained in different spectral range depending on the filter. In order to analyze the spectral components of emission spectrum, we calculated the photon radiation of different spectral range mentioned in Section 2.1. For example, by the photons of G450 minus G395, we can get the photons spectral range 395 nm–450 nm. We normalized the spectra to compare the peak locations by dividing the photon counts at each wavelength by the total number of photons. The peak location is characteristic of the herb. Figure 4 shows the average values and standard errors for the spectra of the heat and cold herbs. The most common characteristic spectral behavior is located from 550 to 610 nm. In comparison with the heat herbs, the cold herbs have a higher ratio range from 350 to 610 nm, and the heat herbs have a higher ratio range from 610 to 715 nm. These trends in the spectral distribution may be associated with the cold and heat properties of Chinese medicinal herbs.

Figure 4: Spectral distribution of DL emission of 37 peaks found in the herbs normalized to their sum.

4. Discussion

Many groups have used analytical techniques and clinical tools to investigate Chinese medicinal herbs. However, to date, modern TCM studies have not resulted in breakthroughs because of conceptual and methodological limitations. Here, we demonstrate how DL may represent an important tool to overcome some of these challenges.

The traditional analysis methods used in TCM are LC-MS and GC-MS. These approaches measure chemical compositions, including active ingredients. In general, the chemical composition governs the therapeutic properties of Chinese herbal materials. However, many earlier investigations have demonstrated that some Chinese medicinal herbs with similar chemical compositions exhibit different therapeutic properties [36, 37]. This finding may be because the entirety of the chemical repertoire in the herb is not assayed because of losses during sample preparation or low constituent abundance [38, 39]. This issue prevents a complete characterization of Chinese medicinal herbs. Moreover, traditional chemical methods emphasize a unique and specific chemical composition, which is in sharp contrast to the holistic view at the heart of TCM.

To overcome these limitations, we proposed the use of DL to characterize herbs because of its many advantages. First, it is fast, convenient, and affordable. Sample processing is limited to a simple grinding step. Samples may be immediately tested after grinding without additional chemical reagents. Moreover, very low detection limits are possible because of the sensitivity of PMTs. Importantly, this approach treats the herb as a whole, complex, and open system, which is how the body will metabolize them following consumption [40]. This approach is in sharp contrast to the reductionist approach taken in a chromatographic scheme.

5. Conclusion

We report a repeatable DL measurement protocol for dried Chinese medicinal herbs. We used this approach to analyze heat and cold Chinese medicinal herbs and identified a significant difference in the decay probability distribution between the two sample types. The peak decay rate () and the peak weight value () offered explicit discrimination between the cold and heat property herbs. The spectral behavior trends were also different and may indicate an underlying mechanism of action in TCM. Nevertheless, these findings require further validation with additional samples.

In conclusion, DL is a novel tool used to investigate materials. DL offers comprehensive information regarding both chemical constituents and energy. It is a direct, rapid, and cumulative assay that provides novel information regarding the biological nature of herbal medicines.

Competing Interests

The authors declare that they have no competing interests.

Acknowledgments

This work was supported by a grant from the National Natural Science Foundation of China (no. 81273997), International Science & Technology Cooperation Program of China (no. 2014DFA30380), Shandong Province Natural Science Foundation, China (no. ZR2015HQ016), and Shandong Provincial Chinese Medicine Science and Technology Development Plan, China (no. 2013-215).

References

X. Gao, Science of Chinese Materia Medica, Publishing House of China of Traditional Chinese Medicine, Beijing, China, 2007.

B. Nie, J. Du, G. Xu et al., “Classification and discrimination for traditional Chinese medicine nature based on OSC-OPLS/O2PLS-DA,” in Proceedings of the International Forum on Information Technology and Applications (IFITA '10), pp. 354–357, Kunming, China, July 2010.

S. Feng, Y. Liu, X. Wang et al., “Application of multivariate statistical analysis in correlation between GC-MS chromatograms of polysaccharide hydrolysis composition acetylation and cold-heat nature of traditional Chinese medicine,” Chinese Journal of Experimental Traditional Medical Formulae, vol. 9, pp. 143–146, 2013.

C.-S. Yuan, C.-Z. Wang, S. M. Wicks, and L.-W. Qi, “Chemical and pharmacological studies of saponins with a focus on American ginseng,” Journal of Ginseng Research, vol. 34, no. 3, pp. 160–167, 2010.

Y.-L. Zhao, J.-B. Wang, X.-H. Xiao et al., “Study on the cold and hot properties of medicinal herbs by thermotropism in mice behavior,” Journal of Ethnopharmacology, vol. 133, no. 3, pp. 980–985, 2011.

B. L. strehler and W. arnold, “Light production by green plants,” The Journal of General Physiology, vol. 34, no. 6, pp. 809–820, 1951.

J. A. Abbott, “Quality measurement of fruits and vegetables,” Postharvest Biology and Technology, vol. 15, no. 3, pp. 207–225, 1999.

E. Costanzo, M. Gulino, L. Lanzanò et al., “Single seed viability checked by delayed luminescence,” European Biophysics Journal, vol. 37, no. 2, pp. 235–238, 2008.

C. de Mello Gallep, E. Confort, M. T. Braghini et al., “Measurements of ultra-weak delayed luminescence in coffee seeds (Coffea arabica and C. canephora) and their germination potential: some indications for a photonic approach in seed viability,” in Proceedings of the 11th Brazilian Symposium of Microwave and Optoeletronics, pp. 1–7, 2004.

J. Bürger and W. Schmidt, “Long term delayed luminescence: a possible fast and convenient assay for nutrition deficiencies and environmental pollution damages in plants,” Plant and Soil, vol. 109, no. 1, pp. 79–83, 1988.

L. Lanzanò, A. Scordino, S. Privitera, S. Tudisco, and F. Musumeci, “Spectral analysis of delayed Luminescence from human skin as a possible non-invasive diagnostic tool,” European Biophysics Journal, vol. 36, no. 7, pp. 823–829, 2007.

A. Scordino, A. Triglia, F. Musumeci, F. Grasso, and Z. Rajfur, “Influence of the presence of atrazine in water on the in-vivo delayed luminescence of Acetabularia acetabulum,” Journal of Photochemistry and Photobiology B: Biology, vol. 32, no. 1-2, pp. 11–17, 1996.

V. Goltsev, I. Zaharieva, P. Chernev, and R. J. Strasser, “Delayed fluorescence in photosynthesis,” Photosynthesis Research, vol. 101, no. 2-3, pp. 217–232, 2009.

J. H. Kang, T. S. Kim, D. Jeong, H.-S. Lee, S.-H. Park, and K.-S. Soh, “Effect of dehydration stress on delayed luminescence in plant leaves,” Journal of the Korean Physical Society, vol. 52, no. 1, pp. 132–136, 2008.

J. Han, M. Yang, and Y. Chen, “Quantum: may be a new-found messenger in biological systems,” BioScience Trends, vol. 5, no. 3, pp. 89–92, 2011.

L. Brizhik, F. Musumeci, A. Scordino, M. Tedesco, and A. Triglia, “Nonlinear dependence of the delayed luminescence yield on the intensity of irradiation in the framework of a correlated soliton model,” Physical Review E, vol. 67, no. 2, Article ID 021902, 2003.

Meluna Research, Geldermalsen, The Netherlands

S. Tryka, “Cut-off filter method for light-induced photon emission spectra estimation,” Computers & Chemistry, vol. 22, no. 1, pp. 113–118, 1998.

K. Staninski, M. Kaczmarek, S. Lis, D. Komar, and A. Szyczewski, “Spectral analysis in ultraweak emissions of chemi- and electrochemiluminescence systems,” Journal of Rare Earths, vol. 27, no. 4, pp. 593–597, 2009.

Y. Yan, F.-A. Popp, and G. M. Rothe, “Correlation between germination capacity and biophoton emission of barley seeds (Hordeum vulgare L.),” Seed Science and Technology, vol. 31, no. 2, pp. 249–258, 2003.

F. Musumeci, R. Grasso, L. Lanzanò et al., “Delayed luminescence: a novel technique to obtain new insights into water structure,” Journal of Biological Physics, vol. 38, no. 1, pp. 181–195, 2012.

M. Gulino, P. Bellia, F. Falciglia et al., “Role of water content in dielectric properties and delayed luminescence of bovine Achilles' tendon,” FEBS Letters, vol. 579, no. 27, pp. 6101–6104, 2005.

M. Gulino, R. Grasso, L. Lanzanò et al., “Lifetime of low-density water domains in salt solutions by time-resolved delayed luminescence,” Chemical Physics Letters, vol. 497, no. 1–3, pp. 99–102, 2010.

M. Monti, A. Zrimec, A. Beran et al., “Delayed luminescence of Prorocentrum minimum under controlled conditions,” Harmful Algae, vol. 4, no. 3, pp. 643–650, 2005.

M. N. Jamaludin and M. Balakrishnan, “Development of spectral delayed luminescence system for whole saliva analysis: a prototype study,” Jurnal Teknologi, vol. 67, no. 1, pp. 7–14, 2014.

M. W. Ho, F. Musumeci, A. Scordino, A. Triglia, and G. Privitera, “Delayed luminescence from bovine Achilles' tendon and its dependence on collagen structure,” Journal of Photochemistry and Photobiology B: Biology, vol. 66, no. 3, pp. 165–170, 2002.

H. Frauenfelder, P. G. Wolynes, and R. H. Austin, “Biological physics,” Reviews of Modern Physics, vol. 71, no. 2, pp. S419–S430, 1999.

G. Palazzo, A. Mallardi, A. Hochkoeppler, L. Cordone, and G. Venturoli, “Electron transfer kinetics in photosynthetic reaction centers embedded in trehalose glasses: trapping of conformational substates at room temperature,” Biophysical Journal, vol. 82, no. 2, pp. 558–568, 2002.

L. Brizhik, A. Scordino, A. Triglia, and F. Musumeci, “Delayed luminescence of biological systems arising from correlated many-soliton states,” Physical Review E, vol. 64, no. 3, Article ID 031902, 2001.

P. Chen, X. Li, Y. Wang, H. Bai, and L. Lin, “Distinguish on the viability of human umbilical cord mesenchymal stem cells using delayed luminescence,” Optoelectronics Letters, vol. 10, no. 5, pp. 391–394, 2014.

A. Scordino, A. Triglia, and F. Musumeci, “Analogous features of delayed luminescence from Acetabularia acetabulum and some solid state systems,” Journal of Photochemistry and Photobiology B: Biology, vol. 56, no. 2-3, pp. 181–186, 2000.

P. Chen, L. Zhang, F. Zhang et al., “Spectral discrimination between normal and leukemic human sera using delayed luminescence,” Biomedical Optics Express, vol. 3, no. 8, pp. 1787–1792, 2012.

F. Musumeci, L. A. Applegate, G. Privitera, A. Scordino, S. Tudisco, and H. J. Niggli, “Spectral analysis of laser-induced ultraweak delayed luminescence in cultured normal and tumor human cells: temperature dependence,” Journal of Photochemistry and Photobiology B: Biology, vol. 79, no. 2, pp. 93–99, 2005.

L. Lanzanò, L. Sui, E. Costanzo et al., “Time-resolved spectral measurements of delayed luminescence from a single soybean seed: effects of thermal damage and correlation with germination performance,” Luminescence, vol. 24, no. 6, pp. 409–415, 2009.

F. Musumeci, G. Privitera, A. Scordino et al., “Discrimination between normal and cancer cells by using spectral analysis of delayed luminescence,” Applied Physics Letters, vol. 86, no. 15, Article ID 153902, 2005.

C.-F. Chen, W.-F. Chiou, and J.-T. Zhang, “Comparison of the pharmacological effects of Panax ginseng and Panax quinquefolium,” Acta Pharmacologica Sinica, vol. 29, no. 9, pp. 1103–1108, 2008.

A. S. Attele, J. A. Wu, and C.-S. Yuan, “Ginseng pharmacology: multiple constituents and multiple actions,” Biochemical Pharmacology, vol. 58, no. 11, pp. 1685–1693, 1999.

Y. Zhang, X. Lyu, T. Liu, J. Luo, W. Zhang, and Q. Mu, “Analysis of nonpolar components from ginseng of different ages,” American Journal of Plant Sciences, vol. 4, no. 1, pp. 92–97, 2013.

H. Zhu, C. Wang, Y. Qi, F. Song, Z. Liu, and S. Liu, “Rapid quality assessment of Radix Aconiti Preparata using direct analysis in real time mass spectrometry,” Analytica Chimica Acta, vol. 752, pp. 69–77, 2012.

F. A. Popp and Y. Yan, “Delayed luminescence of biological systems in terms of coherent states,” Physics Letters A, vol. 293, no. 1-2, pp. 93–97, 2002.