Gas Chromatography-mass Spectrometry Fingerprint Research Articles

Shuanghuanglian Volatile Oil Exerts Antipyretic, Anti-inflammatory, and Antibacterial Synergistic Effects Through Multiple Pathways

Ethnopharmacological relevanceTraditional Chinese Medicine (TCM) has a rich history spanning 2,000 years. Shuanghuanglian, a traditional Chinese herbal formula composed of three botanicals, is primarily used to treat colds, respiratory infections (including bacterial pneumonia), and pharyngitis. Previous research has found that the volatile oil of Shuanghuanglian is crucial for its efficacy. However, there is a lack of studies investigating its mechanisms. Aim of the studyThis study aims to explore the antibacterial and anti-inflammatory mechanisms of Shuanghuanglian volatile oil and its potential to enhance the antibacterial effects when used in conjunction with antibiotics. MethodsDetermination of the GC-MS fingerprint of SVO using Gas Chromatography-Mass Spectrometry (GC-MS) , The antibacterial effects of SVO on multidrug-resistant Klebsiella pneumoniae (MDR-KP) were assessed by detecting MIC, checkerboard method assay, time-kill curves, resistance growth curves, transcriptome sequencing analysis, scanning electron microscopy(SEM), purification, and quantitative analysis of extracellular polysaccharides(EPS). In vivo part, an MDR-KP induced mouse pneumonia model was established to evaluate the mitigating effects of SVO on mouse pneumonia, using comprehensive network pharmacology and bioinformatics to identify genes related to bacterial pneumonia and potential targets of SVO. Validation was performed through molecular docking, qPCR, and ELISA tests. ResultsSVO modulates the expression of MDR-KP mRNA for wecB, wecC, murA, murD, murE, murF, inhibiting the synthesis of O-antigen polysaccharides and peptidoglycans, thereby compromising bacterial cell wall integrity and affecting the synthesis of biofilms. These actions not only exhibit antibacterial effects but also enhance antibacterial activity, restoring the sensitivity of CEF to MDR-KP. SVO suppresses the biological activity of PTGS2, reducing the production of Prostaglandin E2 (PGE2), thereby exerting antipyretic and anti-inflammatory effects, providing new insights for the development of natural non-steroidal anti-inflammatory drugs (NSAIDs). ConclusionsOur research indicates that SVO exerts antipyretic, anti-inflammatory, and antibacterial synergistic effects through multiple pathways.

Analysis of lipophilic fingerprints of edible wild rhubarb (Rheum ribes L.) using GC-MS combined with chemometrics

Rhubarb (Rheum ribes L.) is used globally as both a food supplement and a vegetable. The lipophilic fingerprints of wild rhubarb of Turkiye origin were investigated by gas chromatography-mass spectrometry (GC-MS) combined with chemometrics, including hierarchical cluster analysis (HCA) and principal component analysis (PCA). GC-MS results identified a total of 72 lipophi6lic compounds, including fatty acids, fatty acid esters, simple hydrocarbons and other organics, in all parts of the plant. PCA and HCA analyses revealed intraspecific lipophilic component variation among six wild rhubarb populations, as well as significant variation among lipophilic fingerprints in leaves, fruits, flowers, and roots. Among the compounds, palmitic acid, α-linolenic acid, ethyl palmitate, ethyl oleate, linoleic acid ethyl ester and n-tetracosane were important for the overall lipophilic fingerprints of all parts of the rhubarb. These findings highlight the potential of using HCA and PCA analysis in combination with GC-MS fingerprints as an effective analytical approach.

Insights into flavor formation of braised chicken: Based on E-nose, GC–MS, GC-IMS, and UPLC-Q-Exactive-MS/MS

Effects of braising duration on volatile organic compounds (VOCs) and lipids in chicken were investigated. Aroma profiles identified by an electronic nose were effective in differentiating braising stages. During braising process, a total of 25 key VOCs were detected in braised chicken, and sample braised for 210 min exhibited the highest level of key VOCs. Additionally, a gas chromatography mass spectrometry fingerprint was established to evaluate the distribution of VOCs throughout the braising process. Partial least square discriminant analysis indicated that 2-heptanone, 3-methyl-2-butanone, octanal, nonanal, butanal, (E)-2-pentenal, 1-octen-3-ol, 1-hexanol, pentanal, hexanal, and 1-pentanol significantly affected flavor characteristics of braised chicken. Furthermore, 88 differential lipids were screened, and glycerolipids metabolic was found to be main metabolic pathway during braising process. Triglycerides (TG) and phosphatidyl ethanolamine (PE), such as TG (16:0/18:1/18:2), TG (18:0/18:1/18:2), TG (18:1/18:2/18:3), TG (18:1/18:1/18:2), PE (O-18:2/18:2), PE(O-18:2/18:1), and TG (16:0/16:1/18:2), played a vital role in the generation of VOCs.

GC-MS Fingerprinting Combined with Chemical Pattern-Recognition Analysis Reveals Novel Chemical Markers of the Medicinal Seahorse

Seahorse is a valuable marine-animal drug widely used in traditional Chinese medicine (TCM), and which was first documented in the “Ben Cao Jing Ji Zhu” during the Liang Dynasty. Hippocampus kelloggi (HK) is the most common seahorse species in the medicinal material market and is one of the genuine sources of medicinal seahorse documented in the Chinese pharmacopeia. It is mainly cultivated in the Shandong, Fujian, and Guangxi Provinces in China. However, pseudo-HK, represented by Hippocampus ingens (HI) due to its similar appearance and traits, is often found in the market, compromising the safety and efficacy of clinical use. Currently, there is a lack of reliable methods for identifying these species based on their chemical composition. In this study, we employed, for the first time, a strategy combining gas chromatography-mass spectrometry (GC-MS) fingerprints and chemical patterns in order to identify HK and HI; it is also the first metabolomic study to date of HI as to chemical components. The obtained results revealed remarkable similarities in the chemical fingerprints, while significant differences were also observed. By employing hierarchical cluster analysis (HCA) and principal component analysis (PCA), based on the relative contents of their characteristic peaks, all 34 samples were successfully differentiated according to their species of origin, with samples from the same species forming distinct clusters. Moreover, nonadecanoic acid and behenic acid were exclusively detected in HK samples, further distinguishing them from HI samples. Additionally, the relative contents of lauric acid, tetradecanoic acid, pentadecanoic acid, n-hexadecanoic acid, palmitoleic acid, margaric acid, oleic acid, fenozan acid, eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA) exhibited significant differences between HK and HI (p < 0.0001), as determined by an unpaired t-test. Orthogonal partial least squares discriminant analysis (OPLS-DA) identified seven components (DHA, EPA, n-hexadecanoic acid, tetradecanoic acid, palmitoleic acid, octadecanoic acid, and margaric acid) with high discriminatory value (VIP value > 1). Thus, nonadecanoic acid, behenic acid, and these seven compounds can be utilized as chemical markers for distinguishing HK from HI. In conclusion, our study successfully developed a combined strategy of GC-MS fingerprinting and chemical pattern recognition for the identification of HK and HI, and we also discovered chemical markers that can directly differentiate between the two species. This study can provide a foundation for the authentication of Hippocampus and holds significant importance for the conservation of wild seahorse resources.

Quality Evaluation of Volatile Oil in Yanyangke Mixture (YM) Based on GC-MS Fingerprint, GC Multicomponent Quantitative Analysis and Chemical Pattern Recognition Analysis.

Yanyangke mixture (YM) is composed of 12 kinds of traditional Chinese medicine (TCM) used for the treatment of patients with cough, dry throat and other diseases caused by acute or chronic pharyngitis or patients with difficulty in expectoration. With the wide application of YM in clinical practice, its quality control has attracted huge attention. Based on the multi-component characteristics of Chinese herbal medicines, it is pertinent to establish a quality evaluation system. A new idea is to adopt gas chromatography-mass spectrometry (GC-MS) chemical composition identification, GC-MS fingerprint, and GC content determination as a potential quality control index of the volatile oil in YM. In this study, the volatile oil of YM was extracted by steam distillation, and the chemical components of the volatile oil were analyzed by GC-MS, and 43 chemical components were identified. The fingerprint of the volatile oil from YM was established and the similarity evaluation was performed. Combined with chemometric methods, such as cluster analysis, principal component analysis and partial least squares analysis, the chemical composition differences of the volatile oil from different batches of YM were compared and the symbolic components affecting the quality of the volatile oil from different batches of YM were excavated. Finally, three components were selected as the potential active component markers of YM and the GC content determination method of these three components was established. A rapid, reasonable, and effective quality evaluation and control method of YM volatile oil was established, which provided a reference for further development and research on YM, as well as a new idea for research on other TCM prescriptions.

Discrimination of Syzygium samarangense cv. ‘Giant Green’ Leaves at Different Maturity Stages by FTIR and GCMS Fingerprinting

‘Giant Green’ is one of the Syzygium samarangense cultivars planted throughout Malaysia because it has great potential for benefitting human health. However, its variation in chemical compounds, especially in the leaves at different maturity stages, cannot be systematically discriminated. Hence, Fourier transform infrared spectroscopy (FTIR) and gas chromatography–mass spectrometry (GCMS) coupled with chemometric tools were applied to discriminate between the different stages of leaves, namely, young, mature, and old leaves. The chemical variability among the samples was evaluated by using principal component analysis (PCA) and hierarchical clustering analysis (HCA) techniques. For discrimination, partial least squares discrimination analysis (PLS-DA) was applied, and then partial least squares (PLS) was used to determine the correlation between biological activities (antioxidant and alpha-glucosidase inhibitory assay) and maturity stages of ‘Giant Green’ leaves. As a result, the PCA, HCA, and PLS-DA of the FTIR and GC-MS data showed the separation between clusters for the different maturity stages of the leaves. Additionally, the PLS result demonstrated that the young leaves showed a strong correlation between metabolite quantities and biological activities. The findings of this study revealed that FTIR and GC-MS coupled with chemometric analyses can be used as a rapid method for the discrimination of bioactive structural functions in relation to their biological activity.

A Novel Generative Adversarial Network Model Based on GC-MS Analysis for the Classification of Taif Rose

Rose oil production is believed to be dependent on only a few genotypes of the famous rose Rosa damascena. The aim of this study was to develop a novel GC-MS fingerprint based on the need to expand the genetic resources of oil-bearing rose for industrial cultivation in the Taif region (Saudi Arabia). Gas chromatography-mass spectrometry (GC-MS) is a widely used analytical technique for determining the volatile composition of distilled rose oil from flower data. Because biosample availability, prohibitive costs, and ethical concerns limit observations in agricultural research, we aimed to enhance the quality of analysis by combining real observations with samples generated in silico. This study proposes a novel artificial intelligence model based on generative adversarial neural networks (GANs) to classify Taif rose cultivars using raw GC-MS data. We employed a variant of the GAN known as conditional stacked GANs (cSGANs) to predict Taif rose’s oil content and other latent characteristics without the need to conduct laboratory tests. A hierarchical stack of conditional GANs is used in this algorithm to generate images. A cluster model was developed based on the dataset provided, to quantify the diversity that should be implemented in the proposed model. The networks were trained using the cross-entropy and minimax loss functions. The accuracy of the proposed model was assessed by measuring losses as a function of the number of epochs. The results prove the ability of the proposed model to perfectly generate new real samples of different classes based on the GC-MS fingerprint.

The effects of green banana flour fortification on volatiles compounds of bread: A fingerprinting approach

• Green banana flour preparation affects volatile profile of fortified bread • Significant changes in volatile compounds occurs above 20% of fortification • Furans and Strecker aldehydes were the most abundant volatiles in bread crust • Esters and alcohol were more observed in breadcrumb • Majority of volatile compounds can be linked with the Maillard reaction This study investigated the effects of whole green banana flour (GBF) fortification on volatiles compounds of bread. The volatiles were determined in the bread crumb and crust using headspace solid-phase micro-extraction and gas chromatography-mass spectrometry (GC-MS) method. The GC-MS fingerprinting method enabled the detection of more than 100 volatiles, including alcohol and ester in crumb and furan and aldehyde in the crust. After data analysis using chemometrics, an apparent effect of the GBF fortification on the volatile compounds of bread was observed. In particular, the amounts of furans and Strecker aldehydes increased due to GBF fortification. These volatile compounds are known end products of the Maillard reaction and Strecker degradation, indicating the level of the fortification influenced the concentration of precursors available for these reactions. This work demonstrated that GBF fortification level could modify the volatiles composition of bread, possibly leading toa unique volatile flavor profile.

Spectrum-Efficacy Relationships between GC-MS Fingerprints of Essential Oil from Valerianae Jatamansi Rhizoma et Radix and the Efficacy of Inhibiting Microglial Activation

The bioactive ingredients of essential oil from Valerianae Jatamansi Rhizoma et Radix (the Rhizome et Radix from Valerianae Jatamansi Jones) (EOVJRR) on the efficacy of inhibiting microglial activation were investigated with the approach of spectrum-efficacy relationship. Fourteen batches of Valerianae Jatamansi Rhizoma et Radix were extracted and analyzed by gas chromatography-mass spectrometry (GC-MS), and their activities in the efficacy of inhibiting microglial activation were assayed by measuring the inflammatory responses induced by lipopolysaccharide (LPS) in microglia cells from mice. The spectrum-efficacy relationships between fingerprints and the efficacy of inhibiting microglial activation of EOVJRR were established by grey relational analysis (GRA). Twenty common peaks were obtained from the GC-MS fingerprints of EOVJRR. P12 (vetivenol), P1 (bornyl acetate), P5 (seychellene), and P3 (β-elemene) indicated inhibition on microglia activation together, according to the spectrum-efficacy relationships. The current results established a general model for the spectrum-efficacy relationships of EOVJRR by GC-MS and the efficacy of inhibiting microglial activation, which could be applied to identify the bioactive ingredient and control the quality of herbs.

Study on GC-MS fingerprint of petroleum ether fraction of Shenqi Jiangtang Granules

ObjectiveTo establish gas chromatography-mass spectrometry (GC-MS) fingerprint method for the petroleum ether fraction of Shenqi Jiangtang Granules (SQJTG) and evaluate the product quality. MethodsThe GC-MS fingerprint of petroleum ether fraction of SQJTG was established by GC-MS, and the chemical components corresponding to the fingerprint peaks were structurally identified on NIST2014. The batch consistency of SQJTG products was evaluated based on the chemical composition of petroleum ether parts by using fingerprint similarity evaluation and Principal components analysis (PCA) technology. At the same time, Hotelling's T2 and DMODX statistics are used to set the control range for the quality of different batches of products. ResultsTwenty-two components were identified from the petroleum ether part of SQJTG, accounting for 60.94% of the total components separated. The similarity of fingerprints of petroleum ether parts of 24 batches of SQJTG was greater than 0.95. The PCA of 24 batches of samples were all under the control limits of Hotellin’s T2 and DMODX statistics, indicating that the petroleum ether parts of different batches of SQJTG were consistent. ConclusionThe developed GC-MS fingerprint method can be used to evaluate the quality of SQJTG.

Gas chromatography-mass spectrometry fingerprint and in vitro cytotoxic studies of Rubus steudneri leaf fractions against michigan cancer foundation-7 breast cancer cell line

Aim: Rubus steudneri Schweinf. (Rosaceae) is one of three Rubus species that grow in Ethiopia. Studies of this species have been restricted to in vitro antioxidant, antidiabetic, and nutritional evaluation. Until today, no identification has been made of its phytochemical fingerprints, resulting in an unclear picture of its phytochemical constituents. This study investigated the phytochemical composition of R. steudneri and its in vitro cytotoxicity against Michigan Cancer Foundation-7 (MCF-7) breast cancer cell lines and Vero cell lines. Materials and Methods: The leaf powder was subjected to liquid–liquid fractionation using n-hexane, chloroform, ethyl acetate, methanol, and water as solvents and the obtained fractions were subjected to flash chromatography and in vitro cytotoxicity studies in MCF-7 cell lines at concentrations from 1 to 1000 μg/mL, using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay. Results: The chloroform fraction proved to be the most promising of the bioactive fractions, with 50% of cytotoxicity inhibition for concentrations of 10 μg/mL on MCF-7 cell lines and 125 μg/mL on Vero cell lines. Two important drug leads, namely butyl isobutyl phthalate and 2-pyrrolidinone 5-(cyclohexylmethyl), were identified in chloroform fraction using gas chromatography-mass spectrometry (GC-MS) and may be responsible for the in vitro cytotoxicity. Flow cytometer results indicated that the chloroform fraction arrests cell cycle in the sub-G1 phase at a concentration of 100 μg/mL on MCF-7 cell lines, which proves that metabolites in this fraction may belong to the apoptotic population. Conclusion: In this study, butyl isobutyl phthalate and pyrrolidinone 5-(cyclohexylmethyl), which have significant cytotoxic effects and cell cycle arrest, are extracted. Further in-depth research is in progress to prove the anticancer activity of R. steudneri in search of new leads for anticancer drugs.

Optimization of nuclear magnetic resonance and gas chromatography-mass spectrometry-based fingerprinting methods to characterize goat milk powder

This study is the first to provide a comprehensive characterization of the liquid and volatile fractions of whole goat milk powder (GMP). Robust nuclear magnetic resonance (NMR)- and gas chromatography-mass spectrometry (GC-MS)-based chemical fingerprinting methods were optimized and implemented. The untargeted 1H-NMR analysis resolved 44 metabolites in the liquid fractions of GMP. The NMR fingerprinting technique effectively identified metabolites coming from the aliphatic, sugar, and aromatic regions that can be important in defining the technological properties and quality of the GMP. The untargeted headspace gas chromatography-mass spectrometry fingerprinting was able to detect a total of 50 volatiles including alkanes, ketones, alcohols, aromatics, alkenes, aldehydes, esters, acid, and sulfur compounds. The GMP was dominated by volatiles in the alkane group, while only a few esters were detected. Goat milk is a premium product and vulnerable to fraudulent activities such as adulteration or counterfeit. Therefore, proper characterization and identification is a crucial first step to verify its authenticity and quality.

Quality assessment and differentiation of Aucklandiae Radix and Vladimiriae Radix based on GC-MS fingerprint and chemometrics analysis: basis for clinical application.

Vladimiriae Radix, a geo-authentic medicinal herb found in Sichuan Province in China, is highly similar in chemical composition and pharmacological activity to Aucklandiae Radix. It is often used in local practice and as a substitute for Aucklandiae Radix in the treatment of gastrointestinal tract diseases. However, Vladimiriae Radix is preferred to Aucklandiae Radix in traditional Chinese medicine in Sichuan. In order to compare the difference in quality between the two species and differentiate them according to their chemical profiles, and further to explain the rationality of using Vladimiriae Radix as a substitute and explore the reason for the medication preference in Sichuan, similarity was evaluated using gas chromatography-mass spectrometry (GC-MS) fingerprinting and chemometric analysis. Volatile compounds were identified by comparing mass spectra with spectral data from the National Institute of Standards and Technology library 14.L (NIST 14.L) and the linear retention indices (RI) with those previously reported. The results showed that the similarity between the samples from Aucklandiae Radix (>96%) was greater than that of Vladimiriae Radix (>80%). In addition, 41 and 38 compounds were identified in 10 batches of Vladimiriae Radix and Aucklandiae Radix, respectively, and 21 compounds were common to both species, of which dehydrocostus lactone and aplotaxene were abundant in both. However, γ-patchoulene, longicyclene, β-gurjunene, humulene1,2-epoxide, and β-patchoulene were unique to Vladimiriae Radix, while 4-terpineol, α-ionone, trans-α-bergamotene, γ-selinene, and camphene were characteristic compounds of Aucklandiae Radix. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) suggested that the two species were well differentiated with regard to the level of essential oils. Orthogonal partial least squares discriminant analysis (OPLS-DA) further showed that compounds including costol, aplotaxene, caryophyllene, humulene, and β-eudesmol, together with the characteristic compounds of the two species, could be regarded as potential markers for differentiation, among which β-eudesmol, which is richer in Vladimiriae Radix, and β-patchoulene, which is unique to Vladimiriae Radix, have potential therapeutic effects on gastrointestinal diseases. The results obtained in this study distinguished Vladimiriae Radix and Aucklandiae Radix on a chemical level, and the similarity in chemical constituents may provide a basis for the rationality of Vladimiriae Radix as a substitute, while β-patchoulene and β-eudesmol existing in Vladimiriae Radix provide a theoretical basis for its preferential use in Sichuan. The analysis method established here has important implications for the quality control and differentiation of Vladimiriae Radix and Aucklandiae Radix, which can also serve as a reference for the identification of similar species. Graphical abstract.

Color discrimination and gas chromatography-mass spectrometry fingerprint based on chemometrics analysis for the quality evaluation of Schizonepetae Spica.

Schizonepetae Spica (SS), the dried spike of Schizonepeta tenuifolia Briq., is a traditional Chinese medicinal herb. According to the color of persistent calyx, SS is categorized into two classes: the yellowish-green-type and the brownish-type. Based on the chemometrics analysis of gas chromatography-mass spectrometry (GC-MS), a novel model of identifying and evaluating the quality of SS in different colors was constructed for the first time in this work. 20 batches SS samples of different colors were collected and used to extract essential oils. The average essential oils yield of SS in yellowish-green color was significantly higher than that of SS in brownish color from the same origin (p<0.05). The GC-MS fingerprints of 20 batches SS samples whose correlation coefficients were over 0.964 demonstrated SS samples were consistent to some extent in spite of slightly different chemical indexes. A total of 39 common volatiles compounds were identified. Hierarchical clustering analysis (HCA), principal component analysis (PCA) and partial least-squares discriminate analysis (PLS-DA) were developed to distinguish SS samples characterized by different colors. Consistent results were obtained to show that SS samples could be successfully grouped according to their color. Finally, 4,5,6,7-tetrahydro-3,6-dimethyl-benzofuran and pulegone were detected as the key variables for discriminating SS samples of different colors and for quality control. The obtained results proved that SS of good quality were often yellowish-green and those of poor quality were often brownish.

Discriminant analysis and similarity evaluation of gas chromatography-mass spectrometry fingerprints of aroma components in green tea grading

Two series of 41 Xinyang Maojian tea samples were investigated and the gas chromatography-mass spectrometry (GC-MS) fingerprints of their aroma components of seven different grades were established using headspace solid-phase micro extraction (HS-SPME) and GC-MS. Based on the 23 selected characteristic aroma components, the samples could be classified into seven different groups through discriminant analysis with four and three groups in two separate series. Six fingerprint similarity calculation methods that reflect the differences between grades of tea to different extents were employed, and the new improved extent similarity method was demonstrated to be the best among them. The results for the similarity evaluation displayed good correlation with the actual grades, especially for the series of tea of higher qualities, and the differences between the different grades of teas could be quantified.

Comparative Analysis of Volatile Components from Rough and Manufactured Roots of Radix Gentianae macrophyllae by GC-MS

Radix Gentianae macrophyllae is a traditional Chinese medicine (Qinjiao in Chinese). In this paper, the volatile components extracted from rough Qinjiao (raw, unprocessed Qinjiao)and manufactured Qinjiao (Yinpian,commercial Qinjiao) roots were investigated and comprehensively analyzed and compared by gas chromatography-mass spectrometry (GC-MS) and related chemometrics methods for the first time. The main components were identified belonging to aldehydes, aromatics, fatty acid derivatives, alcohols, esters, ketones, alkanes, terpenoids and others. The discrimination of the samples from manufactured Qinjiao (Yinpian) and rough Qinjiao was achieved by principal component analysis (PCA). The results confirmed that rough samples were characterized by the presence of trans-2-nonenal, linalool and nonanol while manufactured samples were characterized by the presence of pentadecanoic acid and stearyl acetate. The results proved that GC-MS fingerprint combined with PCA approach is a simple, rapid and novelty method which is suitable for the quality control of the raw materials of Qinjiao.

Discrimination of Acori Tatarinowii Rhizoma from two habitats based on GC-MS fingerprinting and LASSO-PLS-DA

This study is intended to explore the chemical differences of Acori Tatarinowii Rhizoma (ATR) samples collected from two habitats, Sichuan and Anhui provinces, China. Gas chromatography-mass spectrometry (GC-MS) was applied to establishing the quantitative chemical fingerprints of ATRs. A total of 104 volatile compounds were identified and quantified with the information of mass spectra and retention index (RI). Furthermore, least absolute shrinkage and selection operator (LASSO), a sparse regularization method, combined with subsampling was employed to improve the classification ability of partial least squares-discriminant analysis (PLS-DA). After variable selection by LASSO, three chemical markers, β-elemene, α-selinene and α-asarone, were identified for the discrimination of ATRs from two habitats, and the total classification correct rate was increased from 82.76% to 96.55%. The proposed LASSO-PLS-DA method can serve as an efficient strategy for screening marked chemical components and geo-herbalism research of traditional Chinese medicines.

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

ABSTRACTThe essential oil from Curcumae wenyujin (CWEO) has antibacterial activity, but the antibacterial compounds in the CWEO have not been identified. The spectrum-effect relationship between chemical compositions and pharmacological activity is regarded as a potentially useful tool to screen bioactive compounds. The binary chromatographic fingerprint of CWEO was established by gas chromatography/mass spectrometry (GC-MS) and high-performance liquid chromatography/diode-array (HPLC-DAD). A data-level information integration method was used to investigate the chemical characteristics encoded in two chromatographic fingerprints. Additionally, the antibacterial activity against Escherichia coli (E. coli）was determined by the liquid dilution method. The spectrum-effect relationship between the binary chromatographic fingerprint and antibacterial activity was investigated with principal component analysis (PCA) and orthogonal projection to latent structures (OPLS) analysis. Compared with a single data matrix, the combined data matrix allowed more accurate identification of the strong outliers in the PCA. Additionally, the results of OPLS were used to establish a spectrum-effect relationship with a closer correlation than that generated with the single data matrix. The results indicated that germacrone, curdione, and furanodiene were detected in HPLC and GC-MS fingerprints, and may be the main antibacterial components.Abbreviations: CWEO, essential oil from C. wenyujin; MIC, minimum inhibitory concentration; OPLS, orthogonal projection to latent structures.

Development of DNA and GC-MS Fingerprints for Authentication and Quality Control of Piper nigrum L. and Its Adulterant Carica papaya L.

Piper nigrum L. (family: Piperaceae) is cultivated for its mature fruit/berries. Generally dried, they are one of the most important commercial spice/food additives. The dried fruit of P. nigrum is almost similar in morphology to seeds of Carica papaya L. and is used as an adulterant of P. nigrum. Molecular technology and plant metabolomics are effective tools for unequivocal authentication and detection of food ingredients. In this study, DNA fingerprinting-based quality control markers [sequence characterized amplified region (SCAR) markers] were employed for authentication and discrimination of P. nigrum from its adulterant C. papaya. The 500- and 750-bp-sized SCAR markers of P. nigrum and C. papaya were amplified using their specific SCAR primer sets. Further, metabolic profiling was carried out using gas chromatography–mass spectrometry (GC-MS) on the fruits and seeds of P. nigrum and C. papaya, respectively. For P. nigrum and for C. papaya, 84 and 61 chemically diverse metabolites were observed, respectively, among which 44 and 33 metabolites were putatively selected, respectively. The detection efficiency of GC-MS was assessed by combining the powdered samples of both P. nigrum and C. papaya in different ratios and was able to detect as low as 20 mg/g (w/w) (20,000 ppm) of metabolites. Multivariate data analysis and clustering analysis was performed on the mixture samples of both the food ingredients. Thus, development of SCAR markers along with the phytochemical fingerprints can correlate DNA fingerprinting data with the quantity of active ingredient and/or phytochemical constituents associated with the specific spice/herb/(s).

Quality control analysis of Safoof-e-Pathar phori: Antiurolithiatic formulation

Aim: Safoof-e-Pathar phori (SPP), a Unani polyherbomineral formulation used for antilithiatic activity. The present study involves standardization of SPP to assess the quality. SPP were subjected to pharmacognostic studies, physiochemical properties, phytochemical analysis, high-performance thin layer chromatography (HPTLC), high-performance liquid chromatography (HPLC), and gas chromatography-mass spectrometry (GC-MS) fingerprint profile to set the standards, which can be used as reference of quality by herbal industries for its preparation and human use. Materials and Methods: The quality control of SPP has been carried out as per the AYUSH and WHO guidelines. The HPTLC fingerprinting has been done using chloroform: ethyl acetate (9:2, v/v) for petroleum ether extract, chloroform: toluene: ethyl acetate (7:2:4, v/v/v) for chloroform extract and for methanol extract petroleum ether: ethyl acetate (9:2, v/v) was used as mobile phase. HPLC was carried out using mobile phase consisted of acetonitrile and water in the ratio of 50:50 (v/v) for the methanolic extract. GC-MS fingerprinting profile has been carried out using hexane extract. Result: SPP was subjected to qualitative estimation of phytochemicals using standard methods, which revealed the presence of various bioactive components such as anthraquinone glycosides, carbohydrates, resins, proteins, flavonoids, phenolics, tannins, and terpenoids. The quantitative estimation of total phenolics and flavonoid content showed 0.44 mg/g and 1.02 mg/g, respectively. The HPTLC fingerprint showed presence of number of compounds for extracts at different R f values. However, HPLC fingerprinting showed presence of 23 well-separated compounds and GC-MS showed presence of 22 compounds. Conclusion: The quality control parameters in present study reveal complete standardization profile of SPP for the 1 st time, which would be of immense value in checking quality of developed formulation for human use.