Zanetti NI, Costantino A, Lazzarini N, Ferrero AA, Centeno ND. Dermestes maculatus (Coleoptera: Dermestidae) development under fluoxetine effect using two drug administration models.
J Forensic Sci 2020;
66:245-254. [PMID:
33034905 DOI:
10.1111/1556-4029.14575]
[Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 08/14/2020] [Accepted: 08/20/2020] [Indexed: 11/27/2022]
Abstract
Fluoxetine is a selective serotonin reuptake inhibitor, commonly used for the treatment of a variety of psychopathological conditions. As such, fluoxetine may be expected to appear in clinical and forensic cases. Dermestes maculatus De Geer (Coleoptera: Dermestidae) has been recognized as a relevant component of the insect fauna associated with decomposing human and animal remains. Experiments were conducted to study the effect of fluoxetine on developing D. maculatus using two-drug administration models: a non-living animal model (pork muscle) and a living one (Sus scrofa L. pigs). We assessed the duration of immature stages and total life cycle, as well as morphological parameters (body length, cephalic width, and weight). The effect of fluoxetine was studied at an overdose concentration: In the non-living animal model the drug was mixed with macerated pork muscle (2000 mg/kg) and in the living animal model, pigs were given the drug orally (833 mg/kg). A control was used for each model. Daily observations were performed from the beginning to the end of the experiments. GC-MS was used for drug detection and quantification. There were no statistically significant differences in the duration of immature stages, life cycle, larval mortality, morphological parameters, or sex ratio, between treatment and control, regardless of the drug administration model. Given that fluoxetine had no detectable effect on the development of D. maculatus, detection of this drug in forensic situations would not compromise the accuracy of PMI estimations.
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