Comparative study of the effects of clozapine and clothiapine in different preparations of guinea pig and rat isolated organs

Development and Validation of a GC-MS Method for the Detection and Quantification of Clotiapine in Blood and Urine Specimens and Application to a Postmortem Case

Introduction. Clotiapine is an atypical antipsychotic of the dibenzothiazepine class introduced in a few European countries since 1970, efficient in treatment-resistant schizophrenic patients. There is little published data on the therapeutic and toxic concentrations of this drug. Aims. The aim of the present study is the development and validation of a method that allows the detection and quantification of clotiapine in blood and urine specimens by gas chromatography-mass spectrometry (GC-MS). Methods. Validation was performed working on spiked postmortem blood and urine samples. Samples were extracted with liquid-liquid extraction (LLE) technique at pH 8.5 with n-hexane/dichloromethane (85/15 v/v) and analysis was followed by GC-MS. Methadone-d9 was used as internal standard. Results. The limit of detection (LOD) was 1.2 and 1.3 ng/mL for urine and blood, respectively, while the lower limit of quantification (LLOQ) was 3.9 and 4.3 ng/mL, respectively. Linearity, precision, selectivity, accuracy, and recovery were also determined. The method was applied to a postmortem case. The blood and urine clotiapine concentrations were 1.32 and 0.49 μg/mL, respectively. Conclusions. A reliable GC-MS method for the detection and quantification of clotiapine in blood and urine samples has been developed and fully validated and then applied to a postmortem case.

Effect of serotonin on gonadal function

The role of endogenous serotonin in the regulation of spermato- and oogenesis was studied in experiments on rabbits. The involvement of the peripheral serotoninergic structures in the studied processes is demonstrated.

Optimization of a mathematical topological pattern for the prediction of antihistaminic activity

Molecular topology was used to develop a mathematical model capable of classifying compounds according to antihistaminic activity. The equations used for this purpose were derived using multilinear regression and linear discriminant analysis. The topological pattern of activity obtained allows the reliable prediction of antihistaminic activity in drugs frequently used for other therapeutic purposes. Based on the results, the proposed pattern is seemingly only valid for drugs that interact with histamine through competitive inhibition with H1 receptors.