Determination of picogram levels of midazolam, and 1- and 4-hydroxymidazolam in human plasma by gas chromatography-negative chemical ionization-mass spectrometry.

Midazolam is a widely accepted probe for phenotyping cytochrome P4503A. A gas chromatography-mass spectrometry (GC-MS)-negative chemical ionization method is presented which allows measuring very low levels of midazolam (MID), 1-OH midazolam (1OHMID) and 4-OH midazolam (4OHMID), in plasma, after derivatization with the reagent N-tert-butyldimethylsilyl-N-methyltrifluoroacetamide. The standard curves were linear over a working range of 20 pg/ml to 5 ng/ml for the three compounds, with the mean coefficients of correlation of the calibration curves (n = 6) being 0.999 for MID and 1OHMID, and 1.0 for 4OHMID. The mean recoveries measured at 100 pg/ml, 500 pg/ml, and 2 ng/ml, ranged from 76 to 87% for MID, from 76 to 99% for 1OHMID, from 68 to 84% for 4OHMID, and from 82 to 109% for N-ethyloxazepam (internal standard). Intra- (n = 7) and inter-day (n = 8) coefficients of variation determined at three concentrations ranged from 1 to 8% for MID, from 2 to 13% for 1OHMID and from 1 to 14% for 4OHMID. The percent theoretical concentrations (accuracy) were within +/-8% for MID and 1OHMID, within +/-9% for 4OHMID at 500 pg/ml and 2 ng/ml, and within +/-28% for 4OHMID at 100 pg/ml. The limits of quantitation were found to be 10 pg/ml for the three compounds. This method can be used for phenotyping cytochrome P4503A in humans following the administration of a very low oral dose of midazolam (75 microg), without central nervous system side-effects.

Predicting the deleterious effects of mutation load in fragmented populations.

Human-induced habitat fragmentation constitutes a major threat to biodiversity. Both genetic and demographic factors combine to drive small and isolated populations into extinction vortices. Nevertheless, the deleterious effects of inbreeding and drift load may depend on population structure, migration patterns, and mating systems and are difficult to predict in the absence of crossing experiments. We performed stochastic individual-based simulations aimed at predicting the effects of deleterious mutations on population fitness (offspring viability and median time to extinction) under a variety of settings (landscape configurations, migration models, and mating systems) on the basis of easy-to-collect demographic and genetic information. Pooling all simulations, a large part (70%) of variance in offspring viability was explained by a combination of genetic structure (F(ST)) and within-deme heterozygosity (H(S)). A similar part of variance in median time to extinction was explained by a combination of local population size (N) and heterozygosity (H(S)). In both cases the predictive power increased above 80% when information on mating systems was available. These results provide robust predictive models to evaluate the viability prospects of fragmented populations.