The anticancer drug metabolites endoxifen and 4-hydroxy-tamoxifen induce toxic effects on Daphnia pulex in a two-generation study.

Although pharmaceutical metabolites are found in the aquatic environment, their toxicity on living organisms is poorly studied in general. Endoxifen and 4-hydroxy-tamoxifen (4OHTam) are two metabolites of the widely used anticancer drug tamoxifen for the prevention and treatment of breast cancers. Both metabolites have a high pharmacological potency in vertebrates, attributing prodrug characteristics to tamoxifen. Tamoxifen and its metabolites are body-excreted by patients, and the parent compound is found in sewage treatment plan effluents and natural waters. The toxicity of these potent metabolites on non-target aquatic species is unknown, which forces environmental risk assessors to predict their toxicity on aquatic species using knowledge on the parent compounds. Therefore, the aim of this study was to assess the sensitivity of two generations of the freshwater microcrustacean Daphnia pulex towards 4OHTam and endoxifen. Two chronic tests of 4OHTam and endoxifen were run in parallel and several endpoints were assessed. The results show that the metabolites 4OHTam and endoxifen induced reproductive and survival effects. For both metabolites, the sensitivity of D. pulex increased in the second generation. The intrinsic rate of natural increase (r) decreased with increasing 4OHTam and endoxifen concentrations. The No-Observed Effect Concentrations (NOECs) calculated for the reproduction of the second generation exposed to 4OHTam and endoxifen were <1.8 and 4.3μg/L, respectively, whereas the NOECs that were calculated for the intrinsic rate of natural increase were <1.8 and 0.4μg/L, respectively. Our study raises questions about prodrug and active metabolites in environmental toxicology assessments of pharmaceuticals. Our findings also emphasize the importance of performing long-term experiments and considering multi-endpoints instead of the standard reproduction outcome.

Impact of model complexity on cross-temporal transferability in Maxent species distribution models: An assessment using paleobotanical data

Maximum entropy modeling (Maxent) is a widely used algorithm for predicting species distributions across space and time. Properly assessing the uncertainty in such predictions is non-trivial and requires validation with independent datasets. Notably, model complexity (number of model parameters) remains a major concern in relation to overfitting and, hence, transferability of Maxent models. An emerging approach is to validate the cross-temporal transferability of model predictions using paleoecological data. In this study, we assess the effect of model complexity on the performance of Maxent projections across time using two European plant species (Alnus giutinosa (L.) Gaertn. and Corylus avellana L) with an extensive late Quaternary fossil record in Spain as a study case. We fit 110 models with different levels of complexity under present time and tested model performance using AUC (area under the receiver operating characteristic curve) and AlCc (corrected Akaike Information Criterion) through the standard procedure of randomly partitioning current occurrence data. We then compared these results to an independent validation by projecting the models to mid-Holocene (6000 years before present) climatic conditions in Spain to assess their ability to predict fossil pollen presence-absence and abundance. We find that calibrating Maxent models with default settings result in the generation of overly complex models. While model performance increased with model complexity when predicting current distributions, it was higher with intermediate complexity when predicting mid-Holocene distributions. Hence, models of intermediate complexity resulted in the best trade-off to predict species distributions across time. Reliable temporal model transferability is especially relevant for forecasting species distributions under future climate change. Consequently, species-specific model tuning should be used to find the best modeling settings to control for complexity, notably with paleoecological data to independently validate model projections. For cross-temporal projections of species distributions for which paleoecological data is not available, models of intermediate complexity should be selected.

Transition mutation in codon 248 of the p53 tumor suppressor gene induced by reactive oxygen species and a nitric oxide-releasing compound.

Exposing the human bronchial epithelial cell line BEAS-2B to the nitric oxide (NO) donor sodium 1-(N,N-diethylamino)diazen-1-ium-1, 2-diolate (DEA/NO) at an initial concentration of 0.6 mM while generating superoxide ion at the rate of 1 microM/min with the hypoxanthine/xanthine oxidase (HX/XO) system induced C:G-->T:A transition mutations in codon 248 of the p53 gene. This pattern of mutagenicity was not seen by 'fish-restriction fragment length polymorphism/polymerase chain reaction' (fish-RFLP/PCR) on exposure to DEA/NO alone, however, exposure to HX/XO led to various mutations, suggesting that co-generation of NO and superoxide was responsible for inducing the observed point mutation. DEA/NO potentiated the ability of HX/XO to induce lipid peroxidation as well as DNA single- and double-strand breaks under these conditions, while 0.6 mM DEA/NO in the absence of HX/XO had no significant effect on these parameters. The results show that a point mutation seen at high frequency in certain common human tumors can be induced by simultaneous exposure to reactive oxygen species and a NO source.