Introducing “DoPP”: A Graphical User-Friendly Application for the Rapid Species Identification of Psychoactive Plant Materials and Quantification of Psychoactive Small Molecules Using DART-MS Data-Reference-Cited by-同舟云学术

Introducing “DoPP”: A Graphical User-Friendly Application for the Rapid Species Identification of Psychoactive Plant Materials and Quantification of Psychoactive Small Molecules Using DART-MS Data

Published:2022-11-17 Issue:48 Volume:94 Page:16570-16578
ISSN:0003-2700
Container-title:Analytical Chemistry
language:en
Short-container-title:Anal. Chem.

Author:

Beyramysoltan Samira¹,Chambers Megan I.¹,Osborne Amy M.¹,Ventura Mónica I.¹,Musah Rabi A.¹^ORCID

Affiliation:

1. Department of Chemistry, University at Albany, State University of New York, 1400 Washington Avenue, Albany, New York 12222, United States

Funder

Division of Chemistry

University at Albany

National Institute of Justice

Publisher

American Chemical Society (ACS)

Subject

Analytical Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.analchem.2c01614

Reference37 articles.

1. Drugs of abuse

2. Hallucinogenic plants of abuse

3. Biomedical analysis of New Psychoactive Substances (NPS) of natural origin

4. Medicinal plants: Traditions of yesterday and drugs of tomorrow

5. Call it a “nightshade”—A hierarchical classification approach to identification of hallucinogenic Solanaceae spp. using DART-HRMS-derived chemical signatures

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Development of a novel seized drug screening method utilizing DART-MS and used weigh paper;Forensic Chemistry;2024-07

2. Medcheck: a novel software for automated de-formulation of traditional Chinese medicine (TCM) prescriptions by liquid chromatography-mass spectrometry;J PHARM ANAL;2024

3. Medcheck: A novel software for automated de-formulation of traditional Chinese medicine (TCM) prescriptions by liquid chromatography-mass spectrometry;Journal of Pharmaceutical Analysis;2024-06

4. Development and validation of a multimodal model in predicting severe acute pancreatitis based on radiomics and deep learning;International Journal of Medical Informatics;2024-04