title: Using Cluster Analysis and ICP-MS to Identify Groups of Ecstasy Tablets in Sao Paulo State, Brazil.
abstract: The variations found in the elemental composition in ecstasy samples result in spectral profiles with useful information for data analysis, and cluster analysis of these profiles can help uncover different categories of the drug. We provide a cluster analysis of ecstasy tablets based on their elemental composition. Twenty-five elements were determined by ICP-MS in tablets apprehended by Sao Paulo's State Police, Brazil. We employ the K-means clustering algorithm along with C4.5 decision tree to help us interpret the clustering results. We found a better number of two clusters within the data, which can refer to the approximated number of sources of the drug which supply the cities of seizures. The C4.5 model was capable of differentiating the ecstasy samples from the two clusters with high prediction accuracy using the leave-one-out cross-validation. The model used only Nd, Ni, and Pb concentration values in the classification of the samples.
authors.affiliation: Instituto de Informática, Universidade Federal de Goiás, Goiânia, Goiás, Brazil.
authors.forename: Camila
authors.initials: C
authors.lastname: Maione
authors.affiliation: Laboratório de Toxicologia e Essencialidade de Metais, Departamento de Análises Clínicas, Toxicológicas e Bromatológicas, Faculdade de Ciências Farmacêuticas de Ribeirão Preto-USP, Ribeirão Preto, São Paulo, Brazil.
authors.forename: Vanessa Cristina
authors.initials: VC
authors.lastname: de Oliveira Souza
authors.affiliation: Laboratório de Química e Toxicologia Forense, Instituto de Criminalística de São Paulo, São Paulo, São Paulo, Brazil.
authors.forename: Loraine Rezende
authors.initials: LR
authors.lastname: Togni
authors.affiliation: Centro de Controle de Intoxicação, Universidade de Campinas, Campinas, São Paulo, Brazil.
authors.forename: José Luiz
authors.initials: JL
authors.lastname: da Costa
authors.affiliation: Department of Chemistry, University of Central Florida, Orlando, FL.|National Center for Forensic Science, University of Central Florida, Orlando, FL.
authors.forename: Andres Dobal
authors.initials: AD
authors.lastname: Campiglia
authors.affiliation: Laboratório de Toxicologia e Essencialidade de Metais, Departamento de Análises Clínicas, Toxicológicas e Bromatológicas, Faculdade de Ciências Farmacêuticas de Ribeirão Preto-USP, Ribeirão Preto, São Paulo, Brazil.
authors.forename: Fernando
authors.initials: F
authors.lastname: Barbosa
authors.affiliation: Instituto de Informática, Universidade Federal de Goiás, Goiânia, Goiás, Brazil.
authors.forename: Rommel Melgaço
authors.initials: RM
authors.lastname: Barbosa
mesh_terms: D000465:Algorithms; D001938:Brazil; D016000:Cluster Analysis; D003663:Decision Trees; D004340:Drug Contamination; D064423:Drug Trafficking; D006801:Humans; D013287:Illicit Drugs / Q000737:chemistry*; D013058:Mass Spectrometry / Q000379:methods; D018817:N-Methyl-3,4-methylenedioxyamphetamine / Q000737:chemistry*; D013607:Tablets
chemical_list: D013287:Illicit Drugs; D013607:Tablets; D018817:N-Methyl-3,4-methylenedioxyamphetamine
keywords: chemometrics; clustering; data mining; ecstasy; forensic science; forensic toxicology; inductively coupled plasma mass spectrometry