Processing for deodorization is widely used in the production of animal-derived Chinese medicinal materials. In this study, Heracles Neo ultra-fast gas-phase electronic nose combined with chemometrics was employed to analyze the overall odor difference of Cervi Cornu Pantotrichum(focusing on that derived from Cervus nippon Temminck in this study) before and after processing. The results showed that the electronic nose effectively distinguished between the medicinal materials and decoction pieces of Cervi Cornu Pantotrichum. HS-GC-MS was used to identify and quantify the volatile components in the medicinal materials and decoction pieces of Cervi Cornu Pantotrichum, and 35 and 37 volatile components were detected in the medicinal materials and decoction pieces, respectively. The medicinal materials and decoction pieces contained 28 common volatile components contributing to the odor of Cervi Cornu Pantotrichum. The odor activity value(OAV) of each volatile component was calculated based on the olfactory threshold and relative content. The results showed that there were 17 key odor substances such as isovaleraldehyde, 2-methylbutanal, isobutyraldehyde, hexanal, and methanethiol in the medicinal materials and decoction pieces of Cervi Cornu Pantotrichum. All of them had bad odor and were the main source of the odor of Cervi Cornu Pantotrichum. The results of principal component analysis(PCA) and orthogonal partial least squares-discriminant analysis(OPLS-DA) showed that there were significant differences in volatile components between the medicinal materials and decoction pieces of Cervi Cornu Pantotrichum. Based on the thresholds of P<0.05 and Variable Importance in Projection(VIP)>1, 21 differential volatile odor components were screened out. Among them, isopentanol, isovaleraldehyde, 2-methylbutanal, n-nonanal, and dimethylamine were the key differential odor compounds between the medicinal materials and decoction pieces of Cervi Cornu Pantotrichum. The odor compounds and their relative content reduced, and some flavor substances such as esters were produced after processing with wine, which was the main reason for the reduction of the odor after processing of Cervi Cornu Pantotrichum.
Odorants/analysis* ; Electronic Nose ; Gas Chromatography-Mass Spectrometry/methods* ; Animals ; Volatile Organic Compounds/analysis* ; Deer ; Drugs, Chinese Herbal/chemistry*

A serum metabolomics analysis method based on gas chromatography-mass spectrometry(GC-MS) was used to investigate the metabolic regulation mechanism of Hericium erinaceus(H. erinaceus) polysaccharides on radiation injury. A mouse model of radiation injury was established by ~(60)Co-γ irradiation. High and low dose groups of H. erinaceus polysaccharide injection were designed, and Rubiae Radix et Rhizoma extract was set as the positive control group to investigate the therapeutic effects and metabolic reaction pathways of H. erinaceus polysaccharides on radiation injury. The metabolites of serum samples were collected by GC-MS, and principal component analysis(PCA) was conducted to establish the metabolic profiles of each group of mice. Partial least squares discriminant analysis(PLS-DA), t-test(P<0.05), and variable importance in the projection(VIP>1) were used to screen out the differential metabolite. Metabolite identification and construction of related metabolic pathways and metabolic networks were achieved by using online databases such as HMDB and METLIN. The results showed that 12 differential metabolites in the serum of mice irradiated at 6.5 Gy that were associated with the radiation injury model, including lactic acid, alanine, urea, serine, threonine, glycerol, L-5-oxoproline, L-lysine, stearic acid, stearic acid, oleic acid, and 1-monopalmitoylglucoside. Two metabolic pathways were enriched: glycerolipid metabolism and metabolism of glycine, serine, and threonine. 18 differential metabolites in the serum of mice irradiated at 8.5 Gy were associated with the radiation injury model, including lactic acid, alanine, urea, L-leucine, glycerol, nonanoic acid, serine, threonine, L-5-oxoproline, phenylalanine, L-ornithine, 1,5-dehydroorbital, L-lysine, L-tyrosine, pectic, oleic, stearic, and cholesterol. Four metabolic pathways were enriched: phenylalanine, tyrosine, and tryptophan synthesis, phenylalanine metabolism, glyceride metabolism, and glycine, serine, and threonine metabolism. It was suggested that H. erinaceus polysaccharides could intervene in radiation injury by altering amino acid and fatty acid synthesis in mice. It was assumed that H. erinaceus polysaccharides regulated the level of metabolic pathways through lipid metabolism and amino acid metabolism, thus affecting energy metabolism and amino acid metabolism and exerting its therapeutic effect on radiation damage.
Animals ; Mice ; Metabolomics/methods* ; Gas Chromatography-Mass Spectrometry/methods* ; Polysaccharides/pharmacology* ; Male ; Hericium/chemistry* ; Drugs, Chinese Herbal/administration & dosage* ; Metabolome/drug effects* ; Gamma Rays/adverse effects*

The study investigated the intrinsic changes in material basis of Angelicae Sinensis Radix during wine processing by headspace-gas chromatography-ion mobility spectrometry(HS-GC-IMS), headspace-solid phase microextraction-gas chromatography-mass spectrometry(HS-SPME-GC-MS), and ultra-high performance liquid chromatography-quadrupole-orbitrap mass spectrometry(UPLC-Q-Orbitrap-MS) combined with chemometrics. HS-GC-IMS fingerprints of Angelicae Sinensis Radix before and after wine processing were established to analyze the variation trends of volatile components and characterize volatile small-molecule substances before and after processing. Principal component analysis(PCA) and orthogonal partial least squares-discriminant analysis(OPLS-DA) were employed for differentiation and difference analysis. A total of 89 volatile components in Angelicae Sinensis Radix were identified by HS-GC-IMS, including 14 unsaturated hydrocarbons, 16 aldehydes, 13 ketones, 9 alcohols, 16 esters, 6 organic acids, and 15 other compounds. HS-SPME-GC-MS detected 118 volatile components, comprising 42 unsaturated hydrocarbons, 11 aromatic compounds, 30 alcohols, 8 alkanes, 6 organic acids, 4 ketones, 7 aldehydes, 5 esters, and 5 other volatile compounds. UPLC-Q-Orbitrap-MS identified 76 non-volatile compounds. PCA revealed distinct clusters of raw and wine-processed Angelicae Sinensis Radix samples across the three detection methods. Both PCA and OPLS-DA effectively discriminated between the two groups, and 145 compounds(VIP>1) were identified as critical markers for evaluating processing quality, including 4-methyl-3-penten-2-one, ethyl 2-methylpentanoate, and 2,4-dimethyl-1,3-dioxolane detected by HS-GC-IMS, angelic acid, β-pinene, and germacrene B detected by HS-SPME-GC-MS, and L-tryptophan, licoricone, and angenomalin detected by UPLC-Q-Orbitrap-MS. In conclusion, the integration of the three detection methods with chemometrics elucidates the differences in the chemical material basis between raw and wine-processed Angelicae Sinensis Radix, providing a scientific foundation for understanding the processing mechanisms and clinical applications of wine-processed Angelicae Sinensis Radix.
Wine/analysis* ; Gas Chromatography-Mass Spectrometry/methods* ; Chromatography, High Pressure Liquid/methods* ; Angelica sinensis/chemistry* ; Solid Phase Microextraction/methods* ; Drugs, Chinese Herbal/isolation & purification* ; Chemometrics ; Volatile Organic Compounds/chemistry* ; Principal Component Analysis ; Ion Mobility Spectrometry/methods*

A method for determining volatile organic compounds (VOCs) emitted from medical molecular sieve oxygen concentrators was developed using thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS). The oxygen concentrator gas was sampled at a flow rate of 0.5 L/min through a branched sampling system onto Tenax GR/carbopack B adsorption tubes. The adsorbed compounds were desorbed and introduced using a programmed temperature vaporization inlet system, followed by chromatographic separation on an SH-I-624Sil MS column. Four VOCs (BHT-Q, PTBP, BHT-quinol, and EHB) were detected in the medical oxygen concentrator using this method. Calibration curves for these compounds exhibited excellent linearity ( R ²>0.99) within the range of 3~100 ng. With a sampling volume of 20 L, the detection limit of the four VOCs ranged from 0.003 9 to 0.022 2 μg/m ³. Spike recovery rates for the four VOCs were between 95% and 115%, with relative standard deviations (RSDs) below 5% ( n=6). The method is simple, rapid, highly sensitive, and accurate, making it suitable for VOCs detection in medical molecular sieve oxygen concentrators.
Volatile Organic Compounds/analysis* ; Gas Chromatography-Mass Spectrometry/methods* ; Oxygen

This study is based on ultra-high-performance liquid chromatography(UPLC), gas chromatography-mass spectrometry(GC-MS), and network pharmacology methods to analyze and predict potential quality markers(Q-markers) of Artemisiae Argyi Folium. First, UPLC and GC-MS techniques were used to analyze the content of 12 non-volatile components and 8 volatile components in the leaves of 33 Artemisia argyi germplasm resources as candidate Q-markers. Subsequently, network pharmacology was employed to construct a "component-target-pathway-efficacy" network to screen out core Q-markers, and the biological activity of the markers was validated using molecular docking. Finally, cluster analysis and principal component analysis were performed on the content of Q-markers in the 33 A. argyi germplasm resources. The results showed that 18 candidate components, 60 targets, and 185 relationships were identified, which were associated with 72 pathways related to the treatment of 11 diseases and exhibited 5 other effects. Based on the combination of freedom and component specificity, six components, including eupatilin, cineole, β-caryophyllene, dinatin, jaceosidin, and caryophyllene oxide were selected as potential Q-markers for Artemisiae Argyi Folium. According to the content of these six markers, cluster analysis divided the 33 A. argyi germplasm resources into three groups, and principal component analysis identified S14 as having the highest overall quality. This study provides a reference for exploring Q-markers of Artemisiae Argyi Folium, establishing a quality evaluation system, further studying its pharmacological mechanisms, and breeding new varieties.
Molecular Docking Simulation ; Network Pharmacology ; Plant Breeding ; Chromatography, High Pressure Liquid/methods* ; Gas Chromatography-Mass Spectrometry ; Artemisia/chemistry* ; Drugs, Chinese Herbal/chemistry*

This study aims to compare the chemical constituents in 24 batches of Artemisiae Argyi Folium samples collected from three different Dao-di producing areas(Anguo in Hebei, Nanyang in Henan, and Qichun in Hubei). An ultra-performance liquid chromatography(UPLC) method was established to determine the content of 13 nonvolatile components, and headspace-gas chromatography-mass spectrometry(HS-GC-MS) was employed for qualitative analysis and comparison of the volatile components. The content of phenolic acids in Artemisiae Argyi Folium was higher than that of flavonoids, and the content of nonvolatile components showed no significant differences among the samples from the three Dao-di producing areas. A total of 40 volatile components were identified, and the relative content of volatile components in Artemisiae Argyi Folium was significantly different among the samples from different Dao-di producing areas. The principal component analysis and partial least squares discriminant analysis identified 8 volatile components as the potential markers for discrimination of Artemisiae Argyi Folium samples from different Dao-di producing areas. This study revealed the differences in the chemical composition of Artemisiae Argyi Folium samples from three different Dao-di producing areas, providing analytical methods and a scientific basis for the discrimination and quality evaluation of Artemisia Argyi Folium in different Dao-di producing areas.
Gas Chromatography-Mass Spectrometry ; Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Flavonoids/analysis* ; Plant Leaves/chemistry* ; Artemisia/chemistry*

OBJECTIVES: To establish the GC-MS qualitative and quantitative analysis methods for the synthetic cannabinoids, its main matrix and additives in suspicious electronic cigarette (e-cigarette) oil samples. METHODS: The e-cigarette oil samples were analyzed by GC-MS after diluted with methanol. Synthetic cannabinoids, its main matrix and additives in e-cigarette oil samples were qualitatively analyzed by the characteristic fragment ions and retention time. The synthetic cannabinoids were quantitatively analyzed by using the selective ion monitoring mode. RESULTS: The linear range of each compound in GC-MS quantitative method was 0.025-1 mg/mL, the matrix recovery rate was 94%-103%, the intra-day precision relative standard deviations (RSD) was less than 2.5%, and inter-day precision RSD was less than 4.0%. Five indoles or indazole amide synthetic cannabinoids were detected in 25 e-cigarette samples. The main matrixes of e-cigarette samples were propylene glycol and glycerol. Additives such as N,2,3-trimethyl-2-isopropyl butanamide (WS-23), glycerol triacetate and nicotine were detected in some samples. The content range of synthetic cannabinoids in 25 e-cigarette samples was 0.05%-2.74%. CONCLUSIONS The GC-MS method for synthesizing cannabinoid, matrix and additive in e-cigarette oil samples has good selectivity, high resolution, low detection limit, and can be used for simultaneous qualitative and quantitative analysis of multiple components; The explored fragment ion fragmentation mechanism of the electron bombardment ion source of indole or indoxamide compounds helps to identify such substances or other compounds with similar structures in cases.
Gas Chromatography-Mass Spectrometry/methods* ; Electronic Nicotine Delivery Systems ; Illicit Drugs/analysis* ; Indazoles/chemistry* ; Glycerol/analysis* ; Cannabinoids ; Indoles/chemistry* ; Ions

Starting with the relationship between mulberry leaves and silkworm droppings as food and metabolites, this study systematically compared the chemical components, screened out differential components, and quantitatively analyzed the main differential components based on ultra-high performance liquid chromatography with quadrupole time-of-flight mass spectrometry(UPLC-Q-TOF-MS) and UPLC-Q-TRAP-MS combined with principal component analysis(PCA) and orthogonal partial least squares-discriminant analysis(OPLS-DA). Moreover, the in vitro enzymatic transformation of the representative differential components was studied. The results showed that(1) 95 components were identified from mulberry leaves and silkworm droppings, among which 27 components only exist in mulberry leaves and 8 components in silkworm droppings. The main differential components were flavonoid glycosides and chlorogenic acids.(2) Nineteen components with significant difference were quantitatively analyzed, and the components with significant differences and high content were neochlorogenic acid, chlorogenic acid, and rutin.(3) The crude protease in the mid-gut of silkworm significantly metabolized neochlorogenic acid and chlorogenic acid, which may be an important reason for the efficacy change in mulberry leaves and silkworm droppings. This study lays a scientific foundation for the development, utilization, and quality control of mulberry leaves and silkworm droppings. It provides references for clarifying the possible material basis and mechanism of the pungent-cool and dispersing nature of mulberry leaves transforming into the pungent-warm and dampness-resolving nature of silkworm droppings, and offers a new idea for the study of nature-effect transformation mechanism of traditional Chinese medicine.
Animals ; Bombyx ; Morus/chemistry* ; Chlorogenic Acid/analysis* ; Gas Chromatography-Mass Spectrometry ; Chromatography, High Pressure Liquid/methods* ; Plant Leaves/chemistry*

OBJECTIVES: To identify 1-(4-fluorophenyl)-2-(1-pyrrolidinyl) pentan-1-one (4-F-α-PVP) analog 1-(4-fluoro-3-methyl phenyl)-2-(1-pyrrolidinyl) pentan-1-one (4-F-3-Methyl-α-PVP) hydrochloride without reference substance. METHODS: The direct-injection electron ionization-mass spectrometry (EI-MS), GC-MS, electrospray ionization-high resolution mass spectrometry (ESI-HRMS), ultra-high performance liquid chromatography-high resolution tandem mass spectrometry (UPLC-HRMS/MS), nuclear magnetic resonance (NMR), ion chromatography and Fourier transform infrared spectroscopy (FTIR) were integrated utilized to achieve the structural analysis and characterization of the unknown compound in the sample, and the cleavage mechanism of the fragment ions was deduced by EI-MS and UPLC-HRMS/MS. RESULTS: By analyzing the direct-injection EI-MS, GC-MS, ESI-HRMS and UPLC-HRMS/MS of the compound in the samples, it was concluded that the unknown compound was a structural analog of 4-F-α-PVP, possibly with one more methyl group in the benzene ring. According to the analysis results of ¹H-NMR and ¹³C-NMR, it was further proved that the methyl group is located at the 3-position of the benzene ring. Since the actual number of hydrogen in ¹H-NMR analysis was one more than 4-F-3-Methyl-α-PVP neutral molecule, it was inferred that the compound existed in the form of salt. Ion chromatography analysis results showed that the compound contained chlorine anion (content 11.14%-11.16%), with the structural analysis of main functional group information by FTIR, the unknown compound was finally determined to be 4-F-3-Methyl-α-PVP hydrochloride. CONCLUSIONS A comprehensive method using EI-MS, GC-MS, ESI-HRMS, UPLC-HRMS/MS, NMR, ion chromatography and FTIR to identify 4-F-3-Methyl-α-PVP hydrochloride in samples is established, which will be helpful for the forensic science laboratory to identify this compound or other analog compounds.
Benzene ; Gas Chromatography-Mass Spectrometry/methods* ; Spectrometry, Mass, Electrospray Ionization ; Chromatography, High Pressure Liquid/methods*

Objective: To establish a method for detection of 6 BTEXs in urine by Purge and Trap-Gas Chromatography-Mass Spectrometry. Methods: The urine sample need not be diluted, but directly purge and trap in the bottle, separated by gas chromatography column, then simultaneously analyzed by retention time locking (RTL) method and selective ion scanning mode (SIM) . Results: The linear range of 6 BTEXs in urine was good, the correlation coefficient was between 0.997 4 and 0.998 9. The minimum quantification limits was 0.010-0.036 μg/L. The precision was 1.9%-4.7%, and the recovery was 93.1%-101.9%. Conclusion: The method has the advantages of wide linear range, high sensitivity and recovery. It is suitable for the determination of 6 BTEXs in urine of low level occupational-exposed or non-exposed population.
Gas Chromatography-Mass Spectrometry/methods* ; Occupational Exposure