Spectrum-effect relationship analysis by binary chromatographic fingerprint to identify components responsible for the antibacterial activity of the essential oil from Curcumae wenyujin

Antimicrobial and Antiproliferative Effects of Zingiberaceae Oils: A Natural Solution for Oral Health

Essential oils have been recognised for their potential benefits in oral care. The aim of this study was to evaluate the antibacterial and antiproliferative activity of essential oils derived from four Zingiberaceae species. A combination of GC/MS and GC-FID was employed to analyse these essential oils. The results showed that β-myrcene (79.77 %) followed by ethyl-cinnamate (40.14 %), β-curcumene (34.90 %), and alloaromadendrene (25.15 %) as the primary constituents of Curcuma mangga, Curcuma xanthorrhiza, Kaempferia galanga and Curcuma aeruginosa, respectively. The Zingiberaceae oils were tested for their antibacterial activity against oral bacteria using the disc diffusion test. Curcuma xanthorrhiza oil showed the largest inhibition zones against Streptococcus mitis (19.50±2.22 mm) and Streptococcus sanguinis (15.04±3.05 mm). Similarly, Curcuma mangga oil exhibited significant antibacterial activity against Streptococcus mutans (12.55±0.45 mm) and mixed oral bacteria (15.03±3.82 mm). Furthermore, the MTT viability assay revealed moderate inhibitory activity of these essential oils against H103 and ORL-204 oral cancer cells. The study findings demonstrate that Curcuma xanthorrhiza and Curcuma mangga essential oils have potent antibacterial properties, suggesting their potential use as natural alternatives to synthetic antibacterial agents in oral care products. However, further investigations are necessary to fully explore their therapeutic applications.

Spectrum-Effect Relationship in Chinese Herbal Medicine: Current Status and Future Perspectives

The quality of Chinese herbal medicine (CHM) directly impacts clinical efficacy and safety. Fingerprint technology is an internationally recognized method for evaluating the quality of CHM. However, the existing quality evaluation models based on fingerprint technology have blocked the ability to assess the internal quality of CHM and cannot comprehensively reflect the correlation between pharmacodynamic information and active constituents. Through mathematical methods, a connection between the "Spectrum" (fingerprint) and the "Effect" (pharmacodynamic data) was established to conduct a spectrum-effect relationship (SER) of CHM to unravel the active component information associated with the pharmacodynamic activity. Consequently, SER can efficiently address the limitations of the segmentation of chemical components and pharmacodynamic effect in CHM and further improve the quality evaluation of CHM. This review focuses on the recent research progress of SER in the field of CHM, including the establishment of fingerprint, the selection of data analysis methods, and their recent applications in the field of CHM. Various advanced fingerprint techniques are introduced, followed by the data analysis methods used in recent years are summarized. Finally, the applications of SER based on different research subjects are described in detail. In addition, the advantages of combining SER with other data are discussed through practical applications, and the research on SER is summarized and prospected. This review proves the validity and development potential of the SER and provides a reference for the development and application of quality evaluation methods for CHM.

Rapid identification of polypeptide from carbapenem-resistant and susceptible Escherichia coli via Orbitrap-MS and pattern recognition analyses

A rapid and accurate analytical method was established to identify CREC and CSEC. Orbitrap-MS was used to detect the polypeptide of CREC and CSEC strains, and MS data were analyzed by pattern recognition analyses such as hierarchical cluster analysis (HCA), principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal partial least squares discriminant analysis (OPLS-DA). HCA based on the farthest distance method could well distinguish the two types of E. coli, and the cophenetic correlation coefficient of the farthest distance method was 0.901. Comparing the results of PCA, PLS-DA, and OPLS-DA, OPLS-DA exhibited the highest accuracy in predicting the CREC and CSEC strains. A total of 26 compounds were identified, and six of the compounds were the highly significant difference between the two types of strains. MS combined with pattern recognition can achieve a more comprehensive and efficient statistical analysis of complex biological samples.

Spectrum-effect relationship between GC-QTOF-MS fingerprint and antioxidant, anti-inflammatory activities of Schizonepeta tenuifolia essential oil

Schizonepeta tenuifolia (Benth.) Briq, a traditional Chinese medicine, is an annual herbaceous plant that is widely distributed in China, Japan, and Korea. The essential oil (EO) of S. tenuifolia has antioxidant and anti-inflammatory properties. However, the components contributing to its antioxidant and anti-inflammatory activities remain unclear. This study was aimed at investigating the spectrum-effect relationship between GC-MS fingerprint and the antioxidant and anti-inflammatory effects of S. tenuifolia EO. Here, the fingerprints of EO from 10 batches of S. tenuifolia from various sources were established using GC-MS, and the antioxidant and anti-inflammatory bioactivities were evaluated using 2,2-diphenyl-1-picrylhydrazyl and nitric oxide inhibitory assays, respectively. Finally, 13 common peaks were identified from 10 batches of S. tenuifolia by searching against the standard mass spectra in NIST 14 and comparing the literature retention index. The different sources of S. tenuifolia EO exhibit mild antioxidant activities and significant anti-inflammatory effects. In particular, menthone (peak 3), isomenthone (peak 4), pulegone (peak 7), piperitone (peak 8), and β-caryophyllene (peak 11) might be the dominant constituents responsible for the antioxidant and anti-inflammatory activities of S. tenuifolia EO. This method may provide a time-saving, convenient way to screen the potential effective components of S. tenuifolia EO.

Screening and Identification of Antipyretic Components in the Postfrost Leaves of Morus alba Based on Multivariable and Continuous-Index Spectrum-Effect Correlation

The leaves of Morus alba (LMA) are crucial traditional Chinese medicine (TCM) of clearing heat. In ancient Chinese materia medica and the current Pharmacopoeia of the People's Republic of China, LMA are recorded to be harvested after frost for medicinal purpose. However, the reason and mechanism of this traditional usage have been still unknown so far. In this work, it was confirmed firstly that the antipyretic effect of LMA after frost was better than that of before frost significantly on feverish rats. Subsequently, the chemical profiles of LMA before and after frost were characterized by fingerprint, respectively. Then, the endemic peaks after frost and positive differential peaks were screened as the research object of spectrum-effect correlation by orthogonal signal correction partial least square discrimination (OPLS). Finally, a multivariable and continuous-index spectrum-effect correlation model coupled with OPLS was established. As a result, the antipyretic components of postfrost LMA were screened and identified as citric acid derivative and tryptophan which may be the synergistic material basis. The study can provide a scientific foundation for the enhancement of effects in the postfrost LMA. Moreover, the strategy of this research could provide a valuable reference for revealing the material basis of synergetic or antagonistic effects among other complex drug systems.