Comparative In Vitro Metabolic Profile Study of Five Cathinone Derivatives

This study revealed the mass spectral fragmentation pattern and the in vitro metabolic behavior of the selected cathinone derivatives, providing meaningful information and scientific evidence in predicting their metabolic potential in vivo, and also promoting their analysis, detection, and clinical use.

Authors

Institutions

Publication Details

Journal
Current Drug Metabolism
Published
2024-12-01
DOI
https://doi.org/10.2174/0113892002348484250309011657
Citations
2
Primary Topic
Forensic Toxicology and Drug Analysis
Type
article
Field-Weighted Citation Impact
0.70
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Comparative In Vitro Metabolic Profile Study of Five Cathinone Derivatives

S. Xiang, Tian Zheng, Guoping Wu, Zhe Li et al.
2 citations
Current Drug Metabolism
Forensic Toxicology and Drug Analysis
0.70
article

Comparative In Vitro Metabolic Profile Study of Five Cathinone Derivatives

S. Xiang, Tian Zheng, Guoping Wu, Zhe Li, Liang Wu
article en
2 citations

Abstract

This study revealed the mass spectral fragmentation pattern and the in vitro metabolic behavior of the selected cathinone derivatives, providing meaningful information and scientific evidence in predicting their metabolic potential in vivo, and also promoting their analysis, detection, and clinical use.

Current Drug MetabolismVol. 25(10)
Nanjing University of Chinese Medicine (CN), Jiangsu Police Officer College (CN)
Good health and well-being
Openalex Percentile: Top 30%
Forensic Toxicology and Drug Analysis
0.70
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.