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Published on: November 8, 2024
GC-MS-Based Quantification and Chemometric Discrimination of Multi-Marker Profiles in Carthami Flos-Based
Won-Young Cho1, Hyundu Roh1, Jiyeon Gong1
1College of Pharmacy and Research Institute of Pharmaceutical Sciences, Woosuk University, Wanju, Republic of Korea.
This study developed a gas chromatography-mass spectrometry (GC-MS) method to analyze fatty acids in Carthami Flos (CF) and deer antler (CFC) pharmacopuncture. The method successfully differentiated CF and CFC formulations, ensuring quality control for traditional Korean medicine.
Area of Science:
- Pharmacology
- Analytical Chemistry
- Traditional Medicine
Background:
- Pharmacopuncture, a key component of traditional Korean medicine, requires robust quality assessment for clinical reliability.
- Chemical consistency and accurate profiling of marker compounds are crucial for ensuring the efficacy and safety of pharmacopuncture formulations.
- Carthami Flos (CF) and its combination with deer antler (CFC) are commonly used in pharmacopuncture, necessitating standardized quality control methods.
Purpose of the Study:
- To establish a quantitative gas chromatography-mass spectrometry (GC-MS) approach for profiling key fatty acid marker compounds in CF and CFC formulations.
- To evaluate the feasibility of this GC-MS method for the comparative quality assessment and discrimination of CF and CFC pharmacopuncture.
- To identify and quantify specific fatty acids (palmitic acid, stearic acid, oleic acid, linoleic acid) in CF and CFC.
Main Methods:
- Utilized gas chromatography-mass spectrometry (GC-MS) with selective ion monitoring (SIM) mode for sensitive and selective quantification of four fatty acids.
- Employed retention times and mass spectral fragment ions for unambiguous identification of analytes.
- Applied univariate analysis and principal component analysis (PCA) for statistical evaluation and sample discrimination.
Main Results:
- Successfully detected and quantified palmitic acid, stearic acid, oleic acid, and linoleic acid in both CF and CFC formulations.
- The SIM mode effectively differentiated structurally similar fatty acids, with linoleic acid being the most abundant.
- Principal component analysis (PCA) clearly discriminated between CF and CFC samples, explaining 97.56% of the variance.
Conclusions:
- The developed GC-MS-based multi-marker profiling method is effective for quantitative comparison of CF and CFC pharmacopuncture.
- This approach enables robust discrimination between CF and CFC formulations, supporting quality control in traditional Korean medicine.
- The study demonstrates the utility of GC-MS for ensuring the chemical consistency and quality of complex herbal formulations.
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