收藏切换
Study of rapid identification of cow-bezoar and its substitutes medicinal herbs using REIMS
收藏切换
PDF
Yan SHI, Wen-guang JING, Xian-long CHENG, Feng WEI**
Chinese Journal of Pharmaceutical Analysis | 2025, 45(2) : 350 - 360
Less
收藏切换
Chinese Journal of Pharmaceutical Analysis | 2025, 45(2): 350-360
Quality Control
Study of rapid identification of cow-bezoar and its substitutes medicinal herbs using REIMS
Full
Yan SHI, Wen-guang JING, Xian-long CHENG, Feng WEI**
Affiliations
  • National Institutes for Food and Drug Control, Beijing 102629, China
Published: 2025-02-28 doi: 10.16155/j.0254-1793.2024-0312
Outline
收藏切换
Objective:

To study the rapid identification of cow-bezoar and its substitutes medicinal herbs using the technique of rapid evaporative ionization mass spectrometry (REIMS) couple with machine learning.

Methods:

The samples were ionized and determined by REIMS with m/z 50-1 200 as scanning range in sensitive mode and negative ion mode, 0.2 s as scanning time, and using dry burning method. REIMS data of samples was recorded as continuous mode. Then the general situation of REIMS data distribution was studied and analyzed through the methods of cluster analysis and principal component analysis. Some models or algorithms, such as partial least squares discriminant analysis (PLS-DA), logistic regression (LR), decision tree (DT), random forest (RF) and adaptive boosting (AdaBoost, with LR and DT as base estimator respectively) were established. In the models training procedure, simulation synthesis data generated by algorithms of GaussianCopula, CTGAN, CopulaGAN and TVAE joined the original training set data as the new training set.

Results:

AdaBoost (DT as base estimator) trained with the new training set was the best model which could accurately predict cow-bezoar and its substitutes medicinal herbs. The accuracy for identifying the test set was 0.97, the precision was 0.90, the recall was 0.97, the F1 score was 0.93, and the AUC of ROC was 1.00. The probability output from the model could also be flexibly used by adjusting the probability threshold according to the actual application scenarios of drug regulation.

Conclusion:

The combination of REIMS technology and machine learning technology can achieve fast and accurate recognition of cow-bezoar and its substitutes medicinal herbs.

cow-bezoar  /  cultured cow-bezoar  /  artificial cow-bezoar  /  cow-bezoar cultured in vitro  /  REIMS  /  artificial intelligence  /  machine learning  /  authenticity identification  /  PLS-DA  /  logistic regression  /  decision tree  /  random forest  /  adaptive boosting  /  simulation data synthesis  /  identification probability
Yan SHI, Wen-guang JING, Xian-long CHENG, Feng WEI. Study of rapid identification of cow-bezoar and its substitutes medicinal herbs using REIMS[J]. Chinese Journal of Pharmaceutical Analysis, 2025 , 45 (2) : 350 -360 . DOI: 10.16155/j.0254-1793.2024-0312
Year 2025 volume 45 Issue 2
PDF
68
32
Cite this Article
BibTeX
Article Info
doi: 10.16155/j.0254-1793.2024-0312
  • Receive Date:2024-05-10
  • Online Date:2026-03-18
  • Published:2025-02-28
Article Data
Affiliations
History
  • Received:2024-05-10
Funding
Affiliations
    National Institutes for Food and Drug Control, Beijing 102629, China
References
Share
https://castjournals.cast.org.cn/joweb/ywfxzz/EN/10.16155/j.0254-1793.2024-0312
Share to
QR

Scan QR to access full text

Cite this article
BibTeX
Citations
表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
  • BibTeX
  • EndNote
  • RefWorks
  • TxT