The differentiation of fibre- and drug type Cannabis seedlings by gas chromatography/mass spectrometry and chemometric tools

Cannabis cultivation in order to produce drugs is forbidden in Switzerland. Thus, law enforcement authorities regularly ask forensic laboratories to determinate cannabis plant's chemotype from seized material in order to ascertain that the plantation is legal or not. As required by the EU official analysis protocol the THC rate of cannabis is measured from the flowers at maturity. When laboratories are confronted to seedlings, they have to lead the plant to maturity, meaning a time consuming and costly procedure. This study investigated the discrimination of fibre type from drug type Cannabis seedlings by analysing the compounds found in their leaves and using chemometrics tools. 11 legal varieties allowed by the Swiss Federal Office for Agriculture and 13 illegal ones were greenhouse grown and analysed using a gas chromatograph interfaced with a mass spectrometer. Compounds that show high discrimination capabilities in the seedlings have been identified and a support vector machines (SVMs) analysis was used to classify the cannabis samples. The overall set of samples shows a classification rate above 99% with false positive rates less than 2%. This model allows then discrimination between fibre and drug type Cannabis at an early stage of growth. Therefore it is not necessary to wait plants' maturity to quantify their amount of THC in order to determine their chemotype. This procedure could be used for the control of legal (fibre type) and illegal (drug type) Cannabis production

Buying drugs on a Darknet market: A better deal? Studying the online illicit drug market through the analysis of digital, physical and chemical data.

Darknet markets, also known as cryptomarkets, are websites located on the Darknet and designed to allow the trafficking of illicit products, mainly drugs. This study aims at presenting the added value of combining digital, chemical and physical information to reconstruct sellers' activities. In particular, this research focuses on Evolution, one of the most popular cryptomarkets active from January 2014 to March 2015. Evolution source code files were analysed using Python scripts based on regular expressions to extract information about listings (i.e., sales proposals) and sellers. The results revealed more than 48,000 listings and around 2700 vendors claiming to send illicit drug products from 70 countries. The most frequent categories of illicit drugs offered by vendors were cannabis-related products (around 25%) followed by ecstasy (MDA, MDMA) and stimulants (cocaine, speed). The cryptomarket was then especially studied from a Swiss point of view. Illicit drugs were purchased from three sellers located in Switzerland. The purchases were carried out to confront digital information (e.g., the type of drug, the purity, the shipping country and the concealment methods mentioned on listings) with the physical analysis of the shipment packaging and the chemical analysis of the received product (purity, cutting agents, chemical profile based on minor and major alkaloids, chemical class). The results show that digital information, such as concealment methods and shipping country, seems accurate. But the illicit drugs purity is found to be different from the information indicated on their respective listings. Moreover, chemical profiling highlighted links between cocaine sold online and specimens seized in Western Switzerland. This study highlights that (1) the forensic analysis of the received products allows the evaluation of the accuracy of digital data collected on the website, and (2) the information from digital and physical/chemical traces are complementary to evaluate the practices of the online selling of illicit drugs on cryptomarkets

A geographical analysis of trafficking on a popular darknet market

© 2017 Elsevier B.V. Cryptomarkets are online marketplaces, located on the darknet, that facilitate the trading of a variety of illegal goods, mostly drugs. While the literature essentially focus on drugs, various other goods and products related to financial or identity fraud, firearms, counterfeit goods, as well as doping products are also offered on these marketplaces. Through the analysis of relevant data collected on a popular marketplace in 2014–2015, Evolution, this research provides an analysis of the structure of trafficking (types and proportions of products, number of vendors and shipping countries). It also aims at highlighting geographical patterns in the trafficking of these products (e.g. trafficking flows, specialisation of vendors and assessment of their role in the distribution chain). The analysis of the flow of goods between countries emphasises the role of specific countries in the international and domestic trafficking, potentially informing law enforcement agencies to target domestic mails or international posts from specific countries. The research also highlights the large proportion of licit and illicit drug listings and vendors on Evolution, followed by various fraud issues (in particular, financial fraud), the sharing of knowledge (tutorials) and finally goods, currencies and precious metals (principally luxury goods). Looking at the shipping country, there seems to be a clear division between digital and physical products, with more specific information for physical goods. This reveals that the spatial analysis of trafficking is particularly meaningful in the case of physical products (such as illicit drugs) and to a lesser extent for digital products. Finally, the geographical analysis reveals that spatial patterns on Evolution tend to reflect the structure of the traditional illicit market. However, regarding illicit drugs, country-specificity has been observed and are presented in this article

The study of doping market: how to produce intelligence from Internet forums

Despite the predominant role played by Internet in the distribution of doping substances, little is currently known about the online offer of doping products. Therefore, the study focuses on the detection of doping substances and suppliers discussed in Internet forums. It aims at having a comprehensive understanding of products and sellers to lead an operational monitoring of the online doping market. Thirteen community forums on the Internet were investigated and one million topics were extracted with source code scrappers. Then, a semantic analysis was conducted with a semi-automatic process to classify the relevant words according to doping matters. Additionally, the ranking of doping products, active substances and suppliers in regards to the number of contributors to the forums were established and analyzed over time. Finally, promotion methods of suppliers were evaluated. The results show that anabolic androgenic steroids, used to enhance body image and performance, are the most discussed type of products. A temporal analysis illustrates the stability of the most popular products as well as the emergence of new products such as peptides (e.g. CJC-1295). 327 suppliers were detected, mostly with dedicated websites or direct sales by e-mail as selling methods. Globally, the implemented methodology shows its ability to detect products and suppliers as well as to follow their temporal trends. The intelligence will serve the definition of online monitoring strategies (e.g. the selection of appropriate keywords). Additionally, it also allows the adjustment of customs inspection strategies and anti-doping analysis by monitoring the popular and emerging substances

Transfer of heroin profiling method from conventional GC-MS to Fast-GC-MS and UHPLC-MS/MS

Peer reviewe

Innovative methodology to transfer conventional GC-MS heroin profiling to UHPLC-MS/MS

Nowadays, in forensic laboratories, heroin profiling is frequently carried out by gas chromatography coupled with mass spectrometry (GC-MS). This analytical technique is well established, provides good sensitivity and reproducibility, and allows the use of large databases. Despite those benefits, recently introduced analytical techniques, such as ultra-high-pressure liquid chromatography (UHPLC), could offer better chromatographic performance, which needs to be considered to increase the analysis throughput for heroin profiling. With the latter, chromatographic conditions were optimized through commercial modeling software and two atmospheric pressure ionization sources were evaluated. Data obtained from UHPLC-MS/MS were thus transferred, thanks to mathematical models to mimic GC-MS data. A calibration and a validation set of representative heroin samples were selected among the database to establish a transfer methodology and assess the models' abilities to transfer using principal component analysis and hierarchical classification analysis. These abilities were evaluated by computing the frequency of successful classification of UHPLC-MS/MS data among GC-MS database. Seven mathematical models were tested to adjust UHPLC-MS/MS data to GC-MS data. A simplified mathematical model was finally selected and offered a frequency of successful transfer equal to 95%. Figur

Potentiel criminalistique de l'étude du trafic de drogues au Canada à partir des données collectées sur les cryptomarchés

Cryptomarkets represent a new innovation for illegal goods trafficking, where drugs are predominantly found. After an overview of the features these sites offer, to understand the virtual world in which users operate, a critical analysis of existing criminological studies suggests a forensic support to better understand how to relate this world essentially described by its virtual data, to reality. A descriptive analysis of Canadian market data is performed to depict an overall picture of drug sales and to explore a strategy targeting the most active sellers. Finally, the use of drug profiling as a way to obtain objective empirical data is discussed, as a means of offsetting uncertainty about virtual data. This article is part of a process of connection-making between criminal sciences, criminology, and forensic science, not limited to the criminalization of prohibited practices, but also to the understanding of phenomena and criminal networks for the purpose of developing efficient strategies for monitoring and neutralizing such threats. © 2016 Canadian Society of Forensic Science

Characterising the online weapons trafficking on cryptomarkets

Weapons related webpages from nine cryptomarkets were manually duplicated in February 2016. Information about the listings (i.e. sales proposals) and vendors' profiles were extracted to draw an overview of the actual online trafficking of weapons. Relationships between vendors were also inferred through the analysis of online digital traces and content similarities. Weapons trafficking is mainly concentrated on two major cryptomarkets. Besides, it accounts for a very small proportion of the illicit trafficking on cryptomarkets compared to the illicit drugs trafficking. Among all weapon related listings (n=386), firearms only account for approximately 25% of sales proposal since the proportion of non-lethal and melee weapons is important (around 46%). Based on the recorded pseudonyms, a total of 96 vendor profiles were highlighted. Some pseudonyms were encountered on several cryptomarkets, suggesting that some vendors may manage accounts on different markets. This hypothesis was strengthened by comparing pseudonyms to online traces such as PGP keys, images and profiles descriptions. Such a method allowed to estimate more accurately the number of vendors offering weapons across cryptomarkets. Finally, according to the gathered data, the extent of the weapons trafficking on the cryptomarkets appear to be limited compared to other illicit goods

Adversarial Matching of Dark Net Market Vendor Accounts

Many datasets feature seemingly disparate entries that actually refer to the same entity. Reconciling these entries, or matching, is challenging, especially in situations where there are errors in the data. In certain contexts, the situation is even more complicated: an active adversary may have a vested interest in having the matching process fail. By leveraging eight years of data, we investigate one such adversarial context: matching different online anonymous marketplace vendor handles to unique sellers. Using a combination of random forest classifiers and hierarchical clustering on a set of features that would be hard for an adversary to forge or mimic, we manage to obtain reasonable performance (over 75% precision and recall on labels generated using heuristics), despite generally lacking any ground truth for training. Our algorithm performs particularly well for the top 30% of accounts by sales volume, and hints that 22,163 accounts with at least one confirmed sale map to 15,652 distinct sellers---of which 12,155 operate only one account, and the remainder between 2 and 11 different accounts. Case study analysis further confirms that our algorithm manages to identify non-trivial matches, as well as impersonation attempts

Int J Mol Sci

The placenta is a key organ for fetal and brain development. Its epigenome can be regarded as a biochemical record of the prenatal environment and a potential mechanism of its association with the future health of the fetus. We investigated associations between placental DNA methylation levels and child behavioral and emotional difficulties, assessed at 3 years of age using the Strengths and Difficulties Questionnaire (SDQ) in 441 mother-child dyads from the EDEN cohort. Hypothesis-driven and exploratory analyses (on differentially methylated probes (EWAS) and regions (DMR)) were adjusted for confounders, technical factors, and cell composition estimates, corrected for multiple comparisons, and stratified by child sex. Hypothesis-driven analyses showed an association of cg26703534 () with emotional symptoms, and exploratory analyses identified two probes, cg09126090 (intergenic region) and cg10305789 (), as negatively associated with peer relationship problems, as well as 33 DMRs, mostly positively associated with at least one of the SDQ subscales. Among girls, most associations were seen with emotional difficulties, whereas in boys, DMRs were as much associated with emotional than behavioral difficulties. This study provides the first evidence of associations between placental DNA methylation and child behavioral and emotional difficulties. Our results suggest sex-specific associations and might provide new insights into the mechanisms of neurodevelopment.Exposition prénatale au tabac et à la pollution atmosphérique et effets sur la santé respiratoire et le neurodévelopment de l'enfant: rôle de la méthylation placentaireHorizon 2020 research and innovation programm