Chronic Citalopram Administration Causes a Sustained Suppression of Serotonin Synthesis in the Mouse Forebrain

BACKGROUND:Serotonin (5-HT) is a neurotransmitter with important roles in the regulation of neurobehavioral processes, particularly those regulating affect in humans. Drugs that potentiate serotonergic neurotransmission by selectively inhibiting the reuptake of serotonin (SSRIs) are widely used for the treatment of psychiatric disorders. Although the regulation of serotonin synthesis may be an factor in SSRI efficacy, the effect of chronic SSRI administration on 5-HT synthesis is not well understood. Here, we describe effects of chronic administration of the SSRI citalopram (CIT) on 5-HT synthesis and content in the mouse forebrain. METHODOLOGY/PRINCIPAL FINDINGS:Citalopram was administered continuously to adult male C57BL/6J mice via osmotic minipump for 2 days, 14 days or 28 days. Plasma citalopram levels were found to be within the clinical range. 5-HT synthesis was assessed using the decarboxylase inhibition method. Citalopram administration caused a suppression of 5-HT synthesis at all time points. CIT treatment also caused a reduction in forebrain 5-HIAA content. Following chronic CIT treatment, forebrain 5-HT stores were more sensitive to the depleting effects of acute decarboxylase inhibition. CONCLUSIONS/SIGNIFICANCE:Taken together, these results demonstrate that chronic citalopram administration causes a sustained suppression of serotonin synthesis in the mouse forebrain. Furthermore, our results indicate that chronic 5-HT reuptake inhibition renders 5-HT brain stores more sensitive to alterations in serotonin synthesis. These results suggest that the regulation of 5-HT synthesis warrants consideration in efforts to develop novel antidepressant strategies

The population pharmacokinetics of citalopram after deliberate self-poisoning: A Bayesian approach

Defining the pharmacokinetics of drugs in overdose is complicated. Deliberate self-poisoning is generally impulsive and associated with poor accuracy in dose history. In addition, early blood samples are rarely collected to characterize the whole plasma-concentration time profile and the effect of decontamination on the pharmacokinetics is uncertain. The aim of this study was to explore a fully Bayesian methodology for population pharmacokinetic analysis of data that arose from deliberate self-poisoning with citalopram. Prior information on the pharmacokinetic parameters was elicited from 14 published studies on citalopram when taken in therapeutic doses. The data set included concentration-time data from 53 patients studied after 63 citalopram overdose events (dose range: 20-1700 mg). Activated charcoal was administered between 0.5 and 4 h after 17 overdose events. The clinical investigator graded the veracity of the patients' dosing history on a 5-point ordinal scale. Inclusion of informative priors stabilised the pharmacokinetic model and the population mean values could be estimated well. There were no indications of non-linear clearance after excessive doses. The final model included an estimated uncertainty of the dose amount which in a simulation study was shown to not affect the model's ability to characterise the effects of activated charcoal. The effect of activated charcoal on clearance and bioavailability was pronounced and resulted in a 72% increase and 22% decrease, respectively. These findings suggest charcoal administration is potentially beneficial after citalopram overdose. The methodology explored seems promising for exploring the dose-exposure relationship in the toxicological settings

Shape, sizing optimization and material selection based on mixed variables and genetic algorithm

In this work, we explore simultaneous designs of materials selection and structural optimization. As the material selection turns out to be a discrete process that finds the optimal distribution of materials over the design domain, it cannot be performed with common gradient-based optimization methods. In this paper, material selection is considered together with the shape and sizing optimization in a framework of multiobjective optimization of tracking the Pareto curve. The idea of mixed variables is often introduced in the case of mono-objective optimization. However, in the case of multi-objective optimization, we still face some hard key points related to the convexity and the continuity of the Pareto domain, which underline the originality of this work. In addition to the above aspect, there is a lack in the literature concerning the industrial applications that consider the mixed parameters. Continuous variables refer to structural parameters such as thickness, diameter and spring elastic constants while material ID is defined as binary design variable for each material. Both mechanical and thermal loads are considered in this work with the aim of minimizing the maximum stress and structural weight simultaneously. The efficiency of the design procedure is demonstrated through various numerical examples.Aerospace StructuresAerospace Engineerin