Variability of voriconazole plasma levels measured by new high-performance liquid chromatography and bioassay methods.

Voriconazole (VRC) is a broad-spectrum antifungal triazole with nonlinear pharmacokinetics. The utility of measurement of voriconazole blood levels for optimizing therapy is a matter of debate. Available high-performance liquid chromatography (HPLC) and bioassay methods are technically complex, time-consuming, or have a narrow analytical range. Objectives of the present study were to develop new, simple analytical methods and to assess variability of voriconazole blood levels in patients with invasive mycoses. Acetonitrile precipitation, reverse-phase separation, and UV detection were used for HPLC. A voriconazole-hypersusceptible Candida albicans mutant lacking multidrug efflux transporters (cdr1Delta/cdr1Delta, cdr2Delta/cdr2Delta, flu1Delta/flu1Delta, and mdr1Delta/mdr1Delta) and calcineurin subunit A (cnaDelta/cnaDelta) was used for bioassay. Mean intra-/interrun accuracies over the VRC concentration range from 0.25 to 16 mg/liter were 93.7% +/- 5.0%/96.5% +/- 2.4% (HPLC) and 94.9% +/- 6.1%/94.7% +/- 3.3% (bioassay). Mean intra-/interrun coefficients of variation were 5.2% +/- 1.5%/5.4% +/- 0.9% and 6.5% +/- 2.5%/4.0% +/- 1.6% for HPLC and bioassay, respectively. The coefficient of concordance between HPLC and bioassay was 0.96. Sequential measurements in 10 patients with invasive mycoses showed important inter- and intraindividual variations of estimated voriconazole area under the concentration-time curve (AUC): median, 43.9 mg x h/liter (range, 12.9 to 71.1) on the first and 27.4 mg x h/liter (range, 2.9 to 93.1) on the last day of therapy. During therapy, AUC decreased in five patients, increased in three, and remained unchanged in two. A toxic encephalopathy probably related to the increase of the VRC AUC (from 71.1 to 93.1 mg x h/liter) was observed. The VRC AUC decreased (from 12.9 to 2.9 mg x h/liter) in a patient with persistent signs of invasive aspergillosis. These preliminary observations suggest that voriconazole over- or underexposure resulting from variability of blood levels might have clinical implications. Simple HPLC and bioassay methods offer new tools for monitoring voriconazole therapy.

Assessment of transcript reconstruction methods for RNA-seq.

We evaluated 25 protocol variants of 14 independent computational methods for exon identification, transcript reconstruction and expression-level quantification from RNA-seq data. Our results show that most algorithms are able to identify discrete transcript components with high success rates but that assembly of complete isoform structures poses a major challenge even when all constituent elements are identified. Expression-level estimates also varied widely across methods, even when based on similar transcript models. Consequently, the complexity of higher eukaryotic genomes imposes severe limitations on transcript recall and splice product discrimination that are likely to remain limiting factors for the analysis of current-generation RNA-seq data.

An evaluation of new parsimony-based versus parametric inference methods in biogeography: a case study using the globally distributed plant family Sapindaceae

Aim  Recently developed parametric methods in historical biogeography allow researchers to integrate temporal and palaeogeographical information into the reconstruction of biogeographical scenarios, thus overcoming a known bias of parsimony-based approaches. Here, we compare a parametric method, dispersal-extinction-cladogenesis (DEC), against a parsimony-based method, dispersal-vicariance analysis (DIVA), which does not incorporate branch lengths but accounts for phylogenetic uncertainty through a Bayesian empirical approach (Bayes-DIVA). We analyse the benefits and limitations of each method using the cosmopolitan plant family Sapindaceae as a case study.Location  World-wide.Methods  Phylogenetic relationships were estimated by Bayesian inference on a large dataset representing generic diversity within Sapindaceae. Lineage divergence times were estimated by penalized likelihood over a sample of trees from the posterior distribution of the phylogeny to account for dating uncertainty in biogeographical reconstructions. We compared biogeographical scenarios between Bayes-DIVA and two different DEC models: one with no geological constraints and another that employed a stratified palaeogeographical model in which dispersal rates were scaled according to area connectivity across four time slices, reflecting the changing continental configuration over the last 110 million years.Results  Despite differences in the underlying biogeographical model, Bayes-DIVA and DEC inferred similar biogeographical scenarios. The main differences were: (1) in the timing of dispersal events - which in Bayes-DIVA sometimes conflicts with palaeogeographical information, and (2) in the lower frequency of terminal dispersal events inferred by DEC. Uncertainty in divergence time estimations influenced both the inference of ancestral ranges and the decisiveness with which an area can be assigned to a node.Main conclusions  By considering lineage divergence times, the DEC method gives more accurate reconstructions that are in agreement with palaeogeographical evidence. In contrast, Bayes-DIVA showed the highest decisiveness in unequivocally reconstructing ancestral ranges, probably reflecting its ability to integrate phylogenetic uncertainty. Care should be taken in defining the palaeogeographical model in DEC because of the possibility of overestimating the frequency of extinction events, or of inferring ancestral ranges that are outside the extant species ranges, owing to dispersal constraints enforced by the model. The wide-spanning spatial and temporal model proposed here could prove useful for testing large-scale biogeographical patterns in plants.

Prediction of infant drug exposure through breastfeeding: population PK modeling and simulation of fluoxetine

BACKGROUND: Risks of significant infant drug exposurethrough breastmilk are poorly defined for many drugs, and largescalepopulation data are lacking. We used population pharmacokinetics(PK) modeling to predict fluoxetine exposure levels ofinfants via mother's milk in a simulated population of 1000 motherinfantpairs.METHODS: Using our original data on fluoxetine PK of 25breastfeeding women, a population PK model was developed withNONMEM and parameters, including milk concentrations, wereestimated. An exponential distribution model was used to account forindividual variation. Simulation random and distribution-constrainedassignment of doses, dosing time, feeding intervals and milk volumewas conducted to generate 1000 mother-infant pairs with characteristicssuch as the steady-state serum concentrations (Css) and infantdose relative to the maternal weight-adjusted dose (relative infantdose: RID). Full bioavailability and a conservative point estimate of1-month-old infant CYP2D6 activity to be 20% of the adult value(adjusted by weigth) according to a recent study, were assumed forinfant Css calculations.RESULTS: A linear 2-compartment model was selected as thebest model. Derived parameters, including milk-to-plasma ratios(mean: 0.66; SD: 0.34; range, 0 - 1.1) were consistent with the valuesreported in the literature. The estimated RID was below 10% in >95%of infants. The model predicted median infant-mother Css ratio was0.096 (range 0.035 - 0.25); literature reported mean was 0.07 (range0-0.59). Moreover, the predicted incidence of infant-mother Css ratioof >0.2 was less than 1%.CONCLUSION: Our in silico model prediction is consistent withclinical observations, suggesting that substantial systemic fluoxetineexposure in infants through human milk is rare, but further analysisshould include active metabolites. Our approach may be valid forother drugs. [supported by CIHR and Swiss National Science Foundation(SNSF)]

Parameter estimation for the distribution of single cell lag times.

In Quantitative Microbial Risk Assessment, it is vital to understand how lag times of individual cells are distributed over a bacterial population. Such identified distributions can be used to predict the time by which, in a growth-supporting environment, a few pathogenic cells can multiply to a poisoning concentration level. We model the lag time of a single cell, inoculated into a new environment, by the delay of the growth function characterizing the generated subpopulation. We introduce an easy-to-implement procedure, based on the method of moments, to estimate the parameters of the distribution of single cell lag times. The advantage of the method is especially apparent for cases where the initial number of cells is small and random, and the culture is detectable only in the exponential growth phase.

Biokinetics and dosimetry of 111 In-DOTA-NOC-ATE compared with 111In-DTPA-Octreotide

Aim: Biokinetics and dosimetry of 111In-DOTA-NOC-ATE (NOCATE) and 111In-DTPA-octreotide (Octreoscan?, OCTREO) were comparatively studied in the same patients. Patients and Methods: Seventeen patients (10 males, 7 females), mean age 60 years referred for an Octreoscan? because of carcinoid (N=9), unspecified neurodendocrine tumors (N=6), thymoma (N=1) or medullary thyroid carcinoma (N=1) accepted a second study with NOCATE. Four patients had no detectable tumor at the time of scanning. Whole-body (WB) anterior-posterior scans were recorded 0.5 (100% reference scan), 4, 24 and 48 hrs (N=17) and 120 hrs (N=6) after injection. OCTREO (178±15 MBq) preceded NOCATE (108±14 MBq) imaging with 16±5 days in 16 patients while 1 patient had first NOCATE followed 14 days later by OCTREO. Blood samples were taken 5, 15, 30, 60, 240 and 1440 min after injection. Background corrected geometric mean counts of WB, lung, kidney, liver, spleen and blood counts expressed in % of the initial composite WB and blood counts, respectively were fitted to bi- or single exponential curves and dosimetry was performed for male and female patients using MIRDOSE3.1 and OLINDA/EXM. Results: Initially, WB, lung and kidney activity was similar but retention was significantly higher for NOCATE compared with OCTREO. Liver and spleen uptake of NOCATE was higher from beginning (p<0.001) and remained so over time. Activity in rest of body showed similar α and β half-lives, but the β half-life fraction of NOCATE was much higher than OCTREO (49% vs. 19%, respectively). Blood T1/2β was longer for NOCATE compared with OCTREO (19 vs. 6h). Residence times were similar in male and female patients while they were in both genders higher for NOCATE than OCTREO. Consequently, effective dose (ED) for NOCATE (ED 114 and 134 μSv/MBq for man and women, respectively) exceeded that of OCTREO (ED = 61 and 71 μSv/MBq), the latter results being close to the ICRP-published radiation dose of OCTREO (ED = 54 and 71 µSv/MBq, respectively). Differential activity measurement in blood cells and plasma showed that only a minor fraction of NOCATE and OCTREO (<5 % in the mean) was bound to globular blood components. Conclusions: NOCATE showed higher retention in normal organs and delivered roughly twice the radiation dose of OCTREO. The ED of OCTREO in these patients was similar to ICRP80 report when adopting a bladder voiding interval of 2 hours.

Use of flow cytometric methods for single-cell analysis in environmental microbiology

Flow cytometry (FCM) is emerging as an important tool in environmental microbiology. Although flow cytometry applications have to date largely been restricted to certain specialized fields of microbiology, such as the bacterial cell cycle and marine phytoplankton communities, technical advances in instrumentation and methodology are leading to its increased popularity and extending its range of applications. Here we will focus on a number of recent flow cytometry developments important for addressing questions in environmental microbiology. These include (i) the study of microbial physiology under environmentally relevant conditions, (ii) new methods to identify active microbial populations and to isolate previously uncultured microorganisms, and (iii) the development of high-throughput autofluorescence bioreporter assays

The molecular basis of social behavior: models, methods and advances.

Elucidating the molecular and neural basis of complex social behaviors such as communal living, division of labor and warfare requires model organisms that exhibit these multi-faceted behavioral phenotypes. Social insects, such as ants, bees, wasps and termites, are attractive models to address this problem, with rich ecological and ethological foundations. However, their atypical systems of reproduction have hindered application of classical genetic approaches. In this review, we discuss how recent advances in social insect genomics, transcriptomics, and functional manipulations have enhanced our ability to observe and perturb gene expression, physiology and behavior in these species. Such developments begin to provide an integrated view of the molecular and cellular underpinnings of complex social behavior.

Mapping of Environmental Data Using Kernel-Based Methods

Recently, kernel-based Machine Learning methods have gained great popularity in many data analysis and data mining fields: pattern recognition, biocomputing, speech and vision, engineering, remote sensing etc. The paper describes the use of kernel methods to approach the processing of large datasets from environmental monitoring networks. Several typical problems of the environmental sciences and their solutions provided by kernel-based methods are considered: classification of categorical data (soil type classification), mapping of environmental and pollution continuous information (pollution of soil by radionuclides), mapping with auxiliary information (climatic data from Aral Sea region). The promising developments, such as automatic emergency hot spot detection and monitoring network optimization are discussed as well.

Comparison of Energy Minimization Methods for 3-D Brain Tissue Classification

This paper presents 3-D brain tissue classificationschemes using three recent promising energy minimizationmethods for Markov random fields: graph cuts, loopybelief propagation and tree-reweighted message passing.The classification is performed using the well knownfinite Gaussian mixture Markov Random Field model.Results from the above methods are compared with widelyused iterative conditional modes algorithm. Theevaluation is performed on a dataset containing simulatedT1-weighted MR brain volumes with varying noise andintensity non-uniformities. The comparisons are performedin terms of energies as well as based on ground truthsegmentations, using various quantitative metrics.

Comparison of different methods for thin section EM analysis of Mycobacterium smegmatis.

Bacteria are generally difficult specimens to prepare for conventional resin section electron microscopy and mycobacteria, with their thick and complex cell envelope layers being especially prone to artefacts. Here we made a systematic comparison of different methods for preparing Mycobacterium smegmatis for thin section electron microscopy analysis. These methods were: (1) conventional preparation by fixatives and epoxy resins at ambient temperature. (2) Tokuyasu cryo-section of chemically fixed bacteria. (3) rapid freezing followed by freeze substitution and embedding in epoxy resin at room temperature or (4) combined with Lowicryl HM20 embedding and ultraviolet (UV) polymerization at low temperature and (5) CEMOVIS, or cryo electron microscopy of vitreous sections. The best preservation of bacteria was obtained with the cryo electron microscopy of vitreous sections method, as expected, especially with respect to the preservation of the cell envelope and lipid bodies. By comparison with cryo electron microscopy of vitreous sections both the conventional and Tokuyasu methods produced different, undesirable artefacts. The two different types of freeze-substitution protocols showed variable preservation of the cell envelope but gave acceptable preservation of the cytoplasm, but not lipid bodies, and bacterial DNA. In conclusion although cryo electron microscopy of vitreous sections must be considered the 'gold standard' among sectioning methods for electron microscopy, because it avoids solvents and stains, the use of optimally prepared freeze substitution also offers some advantages for ultrastructural analysis of bacteria.

Methods for integration site distribution analyses in animal cell genomes.

The question of where retroviral DNA becomes integrated in chromosomes is important for understanding (i) the mechanisms of viral growth, (ii) devising new anti-retroviral therapy, (iii) understanding how genomes evolve, and (iv) developing safer methods for gene therapy. With the completion of genome sequences for many organisms, it has become possible to study integration targeting by cloning and sequencing large numbers of host-virus DNA junctions, then mapping the host DNA segments back onto the genomic sequence. This allows statistical analysis of the distribution of integration sites relative to the myriad types of genomic features that are also being mapped onto the sequence scaffold. Here we present methods for recovering and analyzing integration site sequences.