New psychoactive drugs, so-called legal highs, have gained more and more popularity during the last years. One of the most important groups of these legal high substances are the synthetic phenethylamines that share a common phenethylamine moiety. Based on certain structural characteristics, these synthetic phenethylamines can be divided into further subclasses, among which the synthetic cathinones ('bath salts') are particularly noteworthy. Synthetic cathinones are characterized by an additional carbonyl group attached at the beta position on the amino alkyl chain. Consumption of synthetic phenethylamines can lead to impairments similar to those observed after the use of, for instance, amphetamine or 3,4-methylenedioxy-N-methylamphetamine (MDMA, 'ecstasy'). These impairments include diverse neurological and psychological symptoms which can affect a safe driving behaviour. Although several reports on clinical symptoms and poisonings due to these substances have been published, most of these publications do not contain any analytical data. Additionally, there is still a lack of information concerning pharmacological and toxicological effects of these rather new psychoactive substances. In particular, the knowledge of the impact on the ability to drive following consumption of synthetic phenethylamines is relevant for the police as well as for forensic toxicologists. In this publication, several cases of individuals driving under the influence (DUI) of synthetic phenethylamines (4-fluoroamphetamine, mephedrone (4-methylmethcathinone, 4-MMC), 2-DPMP (desoxypipradol), methylenedioxypyrovalerone (MDPV), benzedrone, N-ethylamphetamine (etilamfetamine), 3-methylmethcathinone (3-MMC)) are presented, focusing on analytical results and signs of impairment.
In the sector of occupational safety and health only a limited amount of studies are concerned with the conversion of inhalable to respirable dust. This conversion is of high importance for retrospective evaluations of exposure levels or of occupational diseases. For this reason a possibility to convert inhalable into respirable dust is discussed in this study. To determine conversion functions from inhalable to respirable dust fractions, 15 120 parallel measurements in the exposure database MEGA (maintained at the Institute for Occupational Safety and Health of the German Social Accident Insurance) are investigated by regression analysis. For this purpose, the whole data set is split into the influencing factors working activity and material. Inhalable dust is the most important predictor variable and shows an adjusted coefficient of determination of 0.585 (R2 adjusted to sample size). Further improvement of the model is gained, when the data set is split into six working activities and three material groups (e.g. high temperature processing, adj. R2 = 0.668). The combination of these two variables leads to a group of data concerned with high temperature processing with metal, which gives rise to a better description than the whole data set (adj. R2 = 0.706). Although it is not possible to refine these groups further systematically, seven improved groups are formed by trial and error, with adj. R2 between 0.733 and 0.835: soldering, casting (metalworking), welding, high temperature cutting, blasting, chiseling/embossing, and wire drawing. The conversion functions for the seven groups are appropriate candidates for data reconstruction and retrospective exposure assessment. However, this is restricted to a careful analysis of the working conditions. All conversion functions are power functions with exponents between 0.454 and 0.946. Thus, the present data do not support the assumption that respirable and inhalable dust are linearly correlated in general.
Zur Bestimmung möglicher Umrechnungsfunktionen der Konzentration von einatembarem (E-Staub) in alveolengängigen Staub (A-Staub) wurden 15 120 Parallelmessungen aus der Expositionsdatenbank MEGA des Instituts für Arbeitsschutz der Deutschen Gesetzlichen Unfallversicherung (IFA) mithilfe der Regressionsanalyse untersucht. E-Staub ist die wichtigste Prediktorvariable und zeigt ein nach der Anzahl der Messpaare korrigiertes Bestimmtheitsmaß (adj. R2) von 0,585. Unter Berücksichtigung von Tätigkeit und Material ist es möglich, systematisch unabhängige Gruppen zu bilden. Außerdem wird durch die Kombination dieser beiden Variablen die beste Beschreibung des Datensatzes erreicht (Heißverarbeitung mit metallstaub-dominiertem Material; adj. R² = 0,706). Mithilfe einer „Trial & Error“- Auswertung können außerdem sieben spezifische, heuristische Gruppen erstellt werden, die für ausgewählte Tätigkeiten und Materialien gelten (adj. R² zwischen 0,733 und 0,835): Löten, Gießen, Schweißen, Hochtemperaturschneiden, Strahlen, Meißeln/Bossieren/Stemmen und Drahtziehen. Alle Umrechnungsfunktionen sind Potenzfunktionen mit Exponenten zwischen 0,454 und 0,946. Daraus folgt, dass aus den vorliegenden Daten generell kein linearer Zusammenhang zwischen A- und E-Staub-Konzentration angenommen werden kann.
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