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We reported on the death by poisoning of a one-month-old baby that had followed the death of one of her sister (due to cyamemazine overdose). Exhumation of the corpse was done 8 months after burial and revealed the presence of amitriptyline. Parent drug and its metabolite were analysed by HPLC–MS/MS in positive ionisation mode on a C 18 analytical column using a gradient of acetonitrile and 2 mM formate buffer at pH = 3. Quantification is based on the main ion m/ z = 233, the common product ion of nortriptyline (MH +, m/ z 264), amitriptyline (MH +, m/ z 278) and nortriptyline D3 used as internal standard (MH +, m/ z 267). Amitriptyline and nortriptyline in the liver were measured at a concentration of 29.8 and 3.6 μg/g, respectively. Hair analyses revealed the presence of amitriptyline and nortriptyline at concentrations of 1811 and 43 pg/mg, respectively, while complementary analyses showed the presence of bromazepam in the hair at a concentration of 740 pg/mg, thus documenting previous administrations. The mother confessed later having used the drinkable form of the pharmaceutical LAROXYL ® by pouring the content of a 20 ml bottle (at 40 mg/ml) into the feeding-bottle of her child. The milk was sweet but still bitter and following the testimony of a close relative, the whole family helped to feed the crying baby.

The purpose of this investigation was to determine the cause of death of a 13-year-old girl, where none was immediately evident. Our analysis showed it to be a very unusual case of a drug-facilitated sexual assault (DFSA), which led to the tragic death of the young rape victim and then to the suicide of the rapist. The incapacitating agent used was chloroform. The post-mortem analysis revealed a blood concentration of 833.9 mg/l for the girl, whereas the quantitation of chloroform in various fluids and viscera of the rapist proved that he had recently been handling the solvent (with concentrations in fat tissues 20 times higher than in his blood). This case draws attention to the need for broad searches for volatile substances in such investigations.

Climate change impacts forest functioning and dynamics, and large uncertainties remain regarding the interactions between species composition, demographic processes, and environmental drivers. There are few robust tools available to link these processes, which precludes accurate projections and recommendations for long-term forest management. Forest gap-models present a balance between complexity and generality and are widely used in predictive forest ecology. However, their relevance to tackle questions about the links between species composition, climate and forest functioning is unclear. In this regard, demonstrating the ability of gap-models to predict the growth of forest stands at the annual time scale - representing a sensitive and integrated signal of tree functioning and mortality risk - appears as a fundamental step. In this study, we aimed at assessing the ability of a gap-model to accurately predict forest growth in the short-term and potential community composition in the long-term, across a wide range of species and environmental conditions. To do so, we present the gap-model ForCEEPS, calibrated using an original parameterization procedure for the main tree species in France. ForCEEPS was shown to satisfactorily predict forest annual growth (averaged over a few years) at the plot level from mountain to Mediterranean climates, regardless the species. Such an accuracy was not gained at the cost of losing precision for long-term predictions, as the model showed a strong ability to predict potential community composition along a gradient of sites with contrasted conditions. The mechanistic relevance of ForCEEPS parameterization was explored by showing the congruence between the values of key model parameter and species functional traits. We further showed that accounting for the spatial configuration of crowns within forest stands, the effects of climatic constraints and the variability of shade tolerances in the species community are all crucial to better predict short-term productivity with gap-models. The dual ability of predicting short-term functioning and long-term community composition, as well as the balance between generality and realism (i.e., predicting accuracy) of the new generation of gap-models may open great perspectives for the exploration of the biodiversity-ecosystem functioning relationships, species coexistence mechanisms, and the impacts of climate change on forest ecosystems. Competing Interest Statement The authors have declared no competing interest.