Project description:Fluconazole is frequently used for the treatment of invasive Candida infections in critically ill patients. However, alterations in renal functions might influence fluconazole clearance. Therefore, our objective was to study the impact of renal function on the population pharmacokinetics of fluconazole in critically ill patients with various degrees of renal function or undergoing continuous renal replacement therapy (CRRT). This was an open-label, multicenter observational study. Critically ill patients receiving fluconazole were included. Baseline and clinical data were collected. At days 3 and 7 of enrollment, blood samples were drawn for pharmacokinetic curves. Additionally, daily trough samples were taken. A nonlinear mixed-effects model was built, followed by Monte Carlo simulations for assessment of exposure to various dosages of fluconazole. Nineteen patients were included with a median age of 64.4 (range, 23 to 81) years and median weight of 82.0 (range, 44.0 to 119.5) kg. A linear two-compartment model best described fluconazole pharmacokinetics and demonstrated higher clearance than expected in critically ill patients. Simulations showed that daily dosages of 600 mg and 800 mg are needed for intensive care unit (ICU) patients with normal renal function and patients on CRRT, respectively, to achieve the EUCAST-recommended target fAUC (area under the concentration-time curve for the free, unbound fraction of the drug)/MIC ratio of 100. In conclusion, fluconazole clearance is highly variable in ICU patients and is strongly dependent on renal function and CRRT. Trough concentrations correlated well with the AUC, opening up opportunities for tailored dosing using therapeutic drug monitoring. We recommend doses of 400 mg for patients with poor to moderate renal function, 600 mg for patients with adequate renal function, and 800 mg for patients treated with CRRT. (This study has been registered at ClinicalTrials.gov under identifier NCT02666716.).

Project description:BackgroundNew polymorphism datasets from heterochroneous data have arisen thanks to recent advances in experimental and microbial molecular evolution, and the sequencing of ancient DNA (aDNA). However, classical tools for population genetics analyses do not take into account heterochrony between subsets, despite potential bias on neutrality and population structure tests. Here, we characterize the extent of such possible biases using serial coalescent simulations.Methodology/principal findingsWe first use a coalescent framework to generate datasets assuming no or different levels of heterochrony and contrast most classical population genetic statistics. We show that even weak levels of heterochrony ( approximately 10% of the average depth of a standard population tree) affect the distribution of polymorphism substantially, leading to overestimate the level of polymorphism theta, to star like trees, with an excess of rare mutations and a deficit of linkage disequilibrium, which are the hallmark of e.g. population expansion (possibly after a drastic bottleneck). Substantial departures of the tests are detected in the opposite direction for more heterochroneous and equilibrated datasets, with balanced trees mimicking in particular population contraction, balancing selection, and population differentiation. We therefore introduce simple corrections to classical estimators of polymorphism and of the genetic distance between populations, in order to remove heterochrony-driven bias. Finally, we show that these effects do occur on real aDNA datasets, taking advantage of the currently available sequence data for Cave Bears (Ursus spelaeus), for which large mtDNA haplotypes have been reported over a substantial time period (22-130 thousand years ago (KYA)).Conclusions/significanceConsidering serial sampling changed the conclusion of several tests, indicating that neglecting heterochrony could provide significant support for false past history of populations and inappropriate conservation decisions. We therefore argue for systematically considering heterochroneous models when analyzing heterochroneous samples covering a large time scale.

Project description:BackgroundWorking night shifts is associated with higher safety risks due to shift work-related fatigue. Nutrition, especially certain (macro) nutrient compositions, has been suggested to reduce fatigue, however, results of studies are contradictory. This could be explained by differences in the time interval investigated between the consumption of a meal and measurement of cognitive performance. Therefore, this observational study investigated the association between macronutrient intake and objective alertness at different time intervals during the night shift in nurses.Methods128 nurses, aged 20-61 years, completed an alertness test (Psychomotor Vigilance Task) during the night shift and a 24-h dietary recall after the night shift. This was repeated three times, always on the first night shift in a night shift series. The associations between macronutrient intake 0 to 1, 1 to 2, and 2 to 3 h before the PVT with alertness during the night shift were analyzed through Linear Mixed Models. The basic model was adjusted for age and gender and the adjusted model additionally for BMI, start time of PVT and energy and caffeine intake during the relevant time interval.ResultsProtein intake was not associated with objective alertness levels, while fat and carbohydrates intake had opposite associations with objective alertness levels over similar time intervals. Fat intake up to 1 h prior to the PVT was borderline associated with a longer median reaction time (RT) (ß = 9.00 ms/10 g fat, 95% CI: -0.21, 18.20), while a higher carbohydrate intake up to 1 h prior to the PVT was borderline associated with shorter median RTs (ß = -3.89, 95% CI: -7.85, 0.06). A higher fat intake 2 to 3 h prior to the PVT was associated with less lapses (log transformed ß = -0.16; 95% CI: -0.31, -0.02), while a higher carbohydrate intake 2 to 3 h prior to the PVT was associated with more lapses (ß = 0.06, 95% CI: 0.01, 0.12).ConclusionOur results contribute to understanding the association between macronutrient intake, as part of a mixed meal, and alertness levels. Conflicting results from previous studies may probably be due to time differences between macronutrient intake and alertness testing.

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