296 resultados para Flow quantification

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Rb-82cardiac PET has been used to non-invasively assess myocardial blood flow (MBF)and myocardial flow reserve (MFR). The impact of MBF and MFR for predictingmajor adverse cardiovascular events (MACE) has not been investigated in aprospective study, which was our aim. MATERIAL AND METHODS: In total, 280patients (65±10y, 36% women) with known or suspected CAD were prospectivelyenrolled. They all underwent both a rest and adenosine stress Rb-82 cardiacPET/CT. Dynamic acquisitions were processed with the FlowQuant 2.1.3 softwareand analyzed semi-quantitatively (SSS, SDS) and quantitatively (MBF, MFR) andreported using the 17-segment AHA model. Patients were stratified based on SDS,stress MBF and MFR and allocated into tertiles. For each group, annualizedevent rates were computed by dividing the number of annualized MACE (cardiacdeath, myocardial infarction, revascularisation or hospitalisation forcardiac-related event) by the sum of individual follow-up periods in years.Outcome were analysed for each group using Kaplan-Meier event-free survivalcurves and compared using the log-rank test. Multivariate analysis wasperformed in a stepwise fashion using Cox proportional hazards regressionmodels (p<0.05 for model inclusion). RESULTS: In a median follow-up of 256days (range 168-440d), 44 MACE were observed. Ischemia (SDS≥2) was observed in95 patients who had higher annualized MACE rate as compared to those without(55% vs. 9.8%, p<0.0001). The group with the lowest MFR tertile (MFR<1.76)had higher MACE rate than the two highest tertiles (51% vs. 9% and 14%,p<0.0001). Similarly, the group with the lowest stress MBF tertile(MBF<1.78mL/min/g) had the highest annualized MACE rate (41% vs. 26% and 6%,p=0.0002). On multivariate analysis, the addition of MFR or stress MBF to SDSsignificantly increased the global χ2 (from 56 to 60, p=0.04; and from56 to 63, p=0.01). The best prognostic power was obtained in a model combiningSDS (p<0.001) and stress MBF (p=0.01). Interestingly, the integration ofstress MBF enhanced risk stratification even in absence of ischemia.CONCLUSIONS: Quantification of MBF or MFR in Rb-82 cardiac PET/CT providesindependent and incremental prognostic information over semi-quantitativeassessment with SDS and is of value for risk stratification.

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BACKGROUND: Several analysis software packages for myocardial blood flow (MBF) quantification from cardiac PET studies exist, but they have not been compared using concordance analysis, which can characterize precision and bias separately. Reproducible measurements are needed for quantification to fully develop its clinical potential. METHODS: Fifty-one patients underwent dynamic Rb-82 PET at rest and during adenosine stress. Data were processed with PMOD and FlowQuant (Lortie model). MBF and myocardial flow reserve (MFR) polar maps were quantified and analyzed using a 17-segment model. Comparisons used Pearson's correlation ρ (measuring precision), Bland and Altman limit-of-agreement and Lin's concordance correlation ρc = ρ·C b (C b measuring systematic bias). RESULTS: Lin's concordance and Pearson's correlation values were very similar, suggesting no systematic bias between software packages with an excellent precision ρ for MBF (ρ = 0.97, ρc = 0.96, C b = 0.99) and good precision for MFR (ρ = 0.83, ρc = 0.76, C b = 0.92). On a per-segment basis, no mean bias was observed on Bland-Altman plots, although PMOD provided slightly higher values than FlowQuant at higher MBF and MFR values (P < .0001). CONCLUSIONS: Concordance between software packages was excellent for MBF and MFR, despite higher values by PMOD at higher MBF values. Both software packages can be used interchangeably for quantification in daily practice of Rb-82 cardiac PET.

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AIMS: Bicuspid aortic valve (BAV) causes complex flow patterns in the ascending aorta (AAo), which may compromise the accuracy of flow measurement by phase-contrast magnetic resonance (PC-MR). Therefore, we aimed to assess and compare the accuracy of forward flow measurement in the AAo, where complex flow is more dominant in BAV patients, with flow quantification in the left ventricular outflow tract (LVOT) and the aortic valve orifice (AV), where complex flow is less important, in BAV patients and controls. METHODS AND RESULTS: Flow was measured by PC-MR in 22 BAV patients and 20 controls at the following positions: (i) LVOT, (ii) AV, and (iii) AAo, and compared with the left ventricular stroke volume (LVSV). The correlation between the LVSV and the forward flow in the LVOT, the AV, and the AAo was good in BAV patients (r = 0.97/0.96/0.93; P < 0.01) and controls (r = 0.96/0.93/0.93; P < 0.01). However, in relation with the LVSV, the forward flow in the AAo was mildly underestimated in controls and much more in BAV patients [median (inter-quartile range): 9% (4%/15%) vs. 22% (8%/30%); P < 0.01]. This was not the case in the LVOT and the AV. The severity of flow underestimation in the AAo was associated with flow eccentricity. CONCLUSION: Flow measurement in the AAo leads to an underestimation of the forward flow in BAV patients. Measurement in the LVOT or the AV, where complex flow is less prominent, is an alternative means for quantifying the systolic forward flow in BAV patients.

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PURPOSE: To evaluate accuracy and reproducibility of flow velocity and volume measurements in a phantom and in human coronary arteries using breathhold velocity-encoded (VE) MRI with spiral k-space sampling at 3 Tesla. MATERIALS AND METHODS: Flow velocity assessment was performed using VE MRI with spiral k-space sampling. Accuracy of VE MRI was tested in vitro at five constant flow rates. Reproducibility was investigated in 19 healthy subjects (mean age 25.4 +/- 1.2 years, 11 men) by repeated acquisition in the right coronary artery (RCA). RESULTS: MRI-measured flow rates correlated strongly with volumetric collection (Pearson correlation r = 0.99; P < 0.01). Due to limited sample resolution, VE MRI overestimated the flow rate by 47% on average when nonconstricted region-of-interest segmentation was used. Using constricted region-of-interest segmentation with lumen size equal to ground-truth luminal size, less than 13% error in flow rate was found. In vivo RCA flow velocity assessment was successful in 82% of the applied studies. High interscan, intra- and inter-observer agreement was found for almost all indices describing coronary flow velocity. Reproducibility for repeated acquisitions varied by less than 16% for peak velocity values and by less than 24% for flow volumes. CONCLUSION: 3T breathhold VE MRI with spiral k-space sampling enables accurate and reproducible assessment of RCA flow velocity.

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PURPOSE: Quantification of myocardial blood flow (MBF) with generator-produced (82)Rb is an attractive alternative for centres without an on-site cyclotron. Our aim was to validate (82)Rb-measured MBF in relation to that measured using (15)O-water, as a tracer 100% of which can be extracted from the circulation even at high flow rates, in healthy control subject and patients with mild coronary artery disease (CAD). METHODS: MBF was measured at rest and during adenosine-induced hyperaemia with (82)Rb and (15)O-water PET in 33 participants (22 control subjects, aged 30 ± 13 years; 11 CAD patients without transmural infarction, aged 60 ± 13 years). A one-tissue compartment (82)Rb model with ventricular spillover correction was used. The (82)Rb flow-dependent extraction rate was derived from (15)O-water measurements in a subset of 11 control subjects. Myocardial flow reserve (MFR) was defined as the hyperaemic/rest MBF. Pearson's correlation r, Bland-Altman 95% limits of agreement (LoA), and Lin's concordance correlation ρ (c) (measuring both precision and accuracy) were used. RESULTS: Over the entire MBF range (0.66-4.7 ml/min/g), concordance was excellent for MBF (r = 0.90, [(82)Rb-(15)O-water] mean difference ± SD = 0.04 ± 0.66 ml/min/g, LoA = -1.26 to 1.33 ml/min/g, ρ(c) = 0.88) and MFR (range 1.79-5.81, r = 0.83, mean difference = 0.14 ± 0.58, LoA = -0.99 to 1.28, ρ(c) = 0.82). Hyperaemic MBF was reduced in CAD patients compared with the subset of 11 control subjects (2.53 ± 0.74 vs. 3.62 ± 0.68 ml/min/g, p = 0.002, for (15)O-water; 2.53 ± 1.01 vs. 3.82 ± 1.21 ml/min/g, p = 0.013, for (82)Rb) and this was paralleled by a lower MFR (2.65 ± 0.62 vs. 3.79 ± 0.98, p = 0.004, for (15)O-water; 2.85 ± 0.91 vs. 3.88 ± 0.91, p = 0.012, for (82)Rb). Myocardial perfusion was homogeneous in 1,114 of 1,122 segments (99.3%) and there were no differences in MBF among the coronary artery territories (p > 0.31). CONCLUSION: Quantification of MBF with (82)Rb with a newly derived correction for the nonlinear extraction function was validated against MBF measured using (15)O-water in control subjects and patients with mild CAD, where it was found to be accurate at high flow rates. (82)Rb-derived MBF estimates seem robust for clinical research, advancing a step further towards its implementation in clinical routine.

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OBJECTIVES: The purpose of this study was to compare myocardial blood flow (MBF) and myocardial flow reserve (MFR) estimates from rubidium-82 positron emission tomography ((82)Rb PET) data using 10 software packages (SPs) based on 8 tracer kinetic models. BACKGROUND: It is unknown how MBF and MFR values from existing SPs agree for (82)Rb PET. METHODS: Rest and stress (82)Rb PET scans of 48 patients with suspected or known coronary artery disease were analyzed in 10 centers. Each center used 1 of 10 SPs to analyze global and regional MBF using the different kinetic models implemented. Values were considered to agree if they simultaneously had an intraclass correlation coefficient >0.75 and a difference <20% of the median across all programs. RESULTS: The most common model evaluated was the Ottawa Heart Institute 1-tissue compartment model (OHI-1-TCM). MBF values from 7 of 8 SPs implementing this model agreed best. Values from 2 other models (alternative 1-TCM and Axially distributed) also agreed well, with occasional differences. The MBF results from other models (e.g., 2-TCM and retention) were less in agreement with values from OHI-1-TCM. CONCLUSIONS: SPs using the most common kinetic model-OHI-1-TCM-provided consistent results in measuring global and regional MBF values, suggesting that they may be used interchangeably to process data acquired with a common imaging protocol.

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OBJECTIVES: The purpose of this study was to compare a novel compressed sensing (CS)-based single-breath-hold multislice magnetic resonance cine technique with the standard multi-breath-hold technique for the assessment of left ventricular (LV) volumes and function. BACKGROUND: Cardiac magnetic resonance is generally accepted as the gold standard for LV volume and function assessment. LV function is 1 of the most important cardiac parameters for diagnosis and the monitoring of treatment effects. Recently, CS techniques have emerged as a means to accelerate data acquisition. METHODS: The prototype CS cine sequence acquires 3 long-axis and 4 short-axis cine loops in 1 single breath-hold (temporal/spatial resolution: 30 ms/1.5 × 1.5 mm(2); acceleration factor 11.0) to measure left ventricular ejection fraction (LVEFCS) as well as LV volumes and LV mass using LV model-based 4D software. For comparison, a conventional stack of multi-breath-hold cine images was acquired (temporal/spatial resolution 40 ms/1.2 × 1.6 mm(2)). As a reference for the left ventricular stroke volume (LVSV), aortic flow was measured by phase-contrast acquisition. RESULTS: In 94% of the 33 participants (12 volunteers: mean age 33 ± 7 years; 21 patients: mean age 63 ± 13 years with different LV pathologies), the image quality of the CS acquisitions was excellent. LVEFCS and LVEFstandard were similar (48.5 ± 15.9% vs. 49.8 ± 15.8%; p = 0.11; r = 0.96; slope 0.97; p < 0.00001). Agreement of LVSVCS with aortic flow was superior to that of LVSVstandard (overestimation vs. aortic flow: 5.6 ± 6.5 ml vs. 16.2 ± 11.7 ml, respectively; p = 0.012) with less variability (r = 0.91; p < 0.00001 for the CS technique vs. r = 0.71; p < 0.01 for the standard technique). The intraobserver and interobserver agreement for all CS parameters was good (slopes 0.93 to 1.06; r = 0.90 to 0.99). CONCLUSIONS: The results demonstrated the feasibility of applying the CS strategy to evaluate LV function and volumes with high accuracy in patients. The single-breath-hold CS strategy has the potential to replace the multi-breath-hold standard cardiac magnetic resonance technique.

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A sensitive and specific ultra performance liquid chromatography-tandem mass spectrometry method for the simultaneous quantification of nicotine, its metabolites cotinine and trans-3'-hydroxycotinine and varenicline in human plasma was developed and validated. Sample preparation was realized by solid phase extraction of the target compounds and of the internal standards (nicotine-d4, cotinine-d3, trans-3'-hydroxycotinine-d3 and CP-533,633, a structural analog of varenicline) from 0.5mL of plasma, using a mixed-mode cation exchange support. Chromatographic separations were performed on a hydrophilic interaction liquid chromatography column (HILIC BEH 2.1×100mm, 1.7μm). A gradient program was used, with a 10mM ammonium formate buffer pH 3/acetonitrile mobile phase at a flow of 0.4mL/min. The compounds were detected on a triple quadrupole mass spectrometer, operated with an electrospray interface in positive ionization mode and quantification was performed using multiple reaction monitoring. Matrix effects were quantitatively evaluated with success, with coefficients of variation inferior to 8%. The procedure was fully validated according to Food and Drug Administration guidelines and to Société Française des Sciences et Techniques Pharmaceutiques. The concentration range was 2-500ng/mL for nicotine, 1-1000ng/mL for cotinine, 2-1000ng/mL for trans-3'-hydroxycotinine and 1-500ng/mL for varenicline, according to levels usually measured in plasma. Trueness (86.2-113.6%), repeatability (1.9-12.3%) and intermediate precision (4.4-15.9%) were found to be satisfactory, as well as stability in plasma. The procedure was successfully used to quantify nicotine, its metabolites and varenicline in more than 400 plasma samples from participants in a clinical study on smoking cessation.

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Like numerous torrents in mountainous regions, the Illgraben creek (canton of Wallis, SW Switzerland) produces almost every year several debris flows. The total area of the active catchment is only 4.7 km², but large events ranging from 50'000 to 400'000 m³ are common (Zimmermann 2000). Consequently, the pathway of the main channel often changes suddenly. One single event can for instance fill the whole river bed and dig new several-meters-deep channels somewhere else (Bardou et al. 2003). The quantification of both, the rhythm and the magnitude of these changes, is very important to assess the variability of the bed's cross section and long profile. These parameters are indispensable for numerical modelling, as they should be considered as initial conditions. To monitor the channel evolution an Optech ILRIS 3D terrestrial laser scanner (LIDAR) was used. LIDAR permits to make a complete high precision 3D model of the channel and its surroundings by scanning it from different view points. The 3D data are treated and interpreted with the software Polyworks from Innovmetric Software Inc. Sequential 3D models allow for the determination of the variation in the bed's cross section and long profile. These data will afterwards be used to quantify the erosion and the deposition in the torrent reaches. To complete the chronological evolution of the landforms, precise digital terrain models, obtained by high resolution photogrammetry based on old aerial photographs, will be used. A 500 m long section of the Illgraben channel was scanned on 18th of August 2005 and on 7th of April 2006. These two data sets permit identifying the changes of the channel that occurred during the winter season. An upcoming scanning campaign in September 2006 will allow for the determination of the changes during this summer. Preliminary results show huge variations in the pathway of the Illgraben channel, as well as important vertical and lateral erosion of the river bed. Here we present the results of a river bank on the left (north-western) flank of the channel (Figure 1). For the August 2005 model the scans from 3 viewpoints were superposed, whereas the April 2006 3D image was obtained by combining 5 separate scans. The bank was eroded. The bank got eroded essentially on its left part (up to 6.3 m), where it is hit by the river and the debris flows (Figures 2 and 3). A debris cone has also formed (Figure 3), which suggests that a part of the bank erosion is due to shallow landslides. They probably occur when the river erosion creates an undercut slope. These geometrical data allow for the monitoring of the alluvial dynamics (i.e. aggradation and degradation) on different time scales and the influence of debris flows occurrence on these changes. Finally, the resistance against erosion of the bed's cross section and long profile will be analysed to assess the variability of these two key parameters. This information may then be used in debris flow simulation.

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A selective and sensitive method was developed for the simultaneous quantification of seven typical antipsychotic drugs (cis-chlorprothixene, flupentixol, haloperidol, levomepromazine, pipamperone, promazine and zuclopenthixol) in human plasma. Ultra-high performance liquid chromatography (UHPLC) was used for complete separation of the compounds in less than 4.5min on an Acquity UPLC BEH C18 column (2.1mm×50mm; 1.7μm), with a gradient elution of ammonium formate buffer pH 4.0 and acetonitrile at a flow rate of 400μl/min. Detection was performed on a tandem quadrupole mass spectrometer (MS/MS) equipped with an electrospray ionization interface. A simple protein precipitation procedure with acetonitrile was used for sample preparation. Thanks to the use of stable isotope-labeled internal standards for all analytes, internal standard-normalized matrix effects were in the range of 92-108%. The method was fully validated to cover large concentration ranges of 0.2-90ng/ml for haloperidol, 0.5-90ng/ml for flupentixol, 1-450ng/ml for levomepromazine, promazine and zuclopenthixol and 2-900ng/ml for cis-chlorprothixene and pipamperone. Trueness (89.1-114.8%), repeatability (1.8-9.9%), intermediate precision (1.9-16.3%) and accuracy profiles (<30%) were in accordance with the latest international recommendations. The method was successfully used in our laboratory for routine quantification of more than 500 patient plasma samples for therapeutic drug monitoring. To the best of our knowledge, this is the first UHPLC-MS/MS method for the quantification of the studied drugs with a sample preparation based on protein precipitation.

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In groundwater applications, Monte Carlo methods are employed to model the uncertainty on geological parameters. However, their brute-force application becomes computationally prohibitive for highly detailed geological descriptions, complex physical processes, and a large number of realizations. The Distance Kernel Method (DKM) overcomes this issue by clustering the realizations in a multidimensional space based on the flow responses obtained by means of an approximate (computationally cheaper) model; then, the uncertainty is estimated from the exact responses that are computed only for one representative realization per cluster (the medoid). Usually, DKM is employed to decrease the size of the sample of realizations that are considered to estimate the uncertainty. We propose to use the information from the approximate responses for uncertainty quantification. The subset of exact solutions provided by DKM is then employed to construct an error model and correct the potential bias of the approximate model. Two error models are devised that both employ the difference between approximate and exact medoid solutions, but differ in the way medoid errors are interpolated to correct the whole set of realizations. The Local Error Model rests upon the clustering defined by DKM and can be seen as a natural way to account for intra-cluster variability; the Global Error Model employs a linear interpolation of all medoid errors regardless of the cluster to which the single realization belongs. These error models are evaluated for an idealized pollution problem in which the uncertainty of the breakthrough curve needs to be estimated. For this numerical test case, we demonstrate that the error models improve the uncertainty quantification provided by the DKM algorithm and are effective in correcting the bias of the estimate computed solely from the MsFV results. The framework presented here is not specific to the methods considered and can be applied to other combinations of approximate models and techniques to select a subset of realizations

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AIMS: We studied the respective added value of the quantitative myocardial blood flow (MBF) and the myocardial flow reserve (MFR) as assessed with (82)Rb positron emission tomography (PET)/CT in predicting major adverse cardiovascular events (MACEs) in patients with suspected myocardial ischaemia. METHODS AND RESULTS: Myocardial perfusion images were analysed semi-quantitatively (SDS, summed difference score) and quantitatively (MBF, MFR) in 351 patients. Follow-up was completed in 335 patients and annualized MACE (cardiac death, myocardial infarction, revascularization, or hospitalization for congestive heart failure or de novo stable angor) rates were analysed with the Kaplan-Meier method in 318 patients after excluding 17 patients with early revascularizations (<60 days). Independent predictors of MACEs were identified by multivariate analysis. During a median follow-up of 624 days (inter-quartile range 540-697), 35 MACEs occurred. An annualized MACE rate was higher in patients with ischaemia (SDS >2) (n = 105) than those without [14% (95% CI = 9.1-22%) vs. 4.5% (2.7-7.4%), P < 0.0001]. The lowest MFR tertile group (MFR <1.8) had the highest MACE rate [16% (11-25%) vs. 2.9% (1.2-7.0%) and 4.3% (2.1-9.0%), P < 0.0001]. Similarly, the lowest stress MBF tertile group (MBF <1.8 mL/min/g) had the highest MACE rate [14% (9.2-22%) vs. 7.3% (4.2-13%) and 1.8% (0.6-5.5%), P = 0.0005]. Quantitation with stress MBF or MFR had a significant independent prognostic power in addition to semi-quantitative findings. The largest added value was conferred by combining stress MBF to SDS. This holds true even for patients without ischaemia. CONCLUSION: Perfusion findings in (82)Rb PET/CT are strong MACE outcome predictors. MBF quantification has an added value allowing further risk stratification in patients with normal and abnormal perfusion images.

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A simple and sensitive liquid chromatography-electrospray ionization mass spectrometry method was developed for the simultaneous quantification in human plasma of all selective serotonin reuptake inhibitors (citalopram, fluoxetine, fluvoxamine, paroxetine and sertraline) and their main active metabolites (desmethyl-citalopram and norfluoxetine). A stable isotope-labeled internal standard was used for each analyte to compensate for the global method variability, including extraction and ionization variations. After sample (250μl) pre-treatment with acetonitrile (500μl) to precipitate proteins, a fast solid-phase extraction procedure was performed using mixed mode Oasis MCX 96-well plate. Chromatographic separation was achieved in less than 9.0min on a XBridge C18 column (2.1×100mm; 3.5μm) using a gradient of ammonium acetate (pH 8.1; 50mM) and acetonitrile as mobile phase at a flow rate of 0.3ml/min. The method was fully validated according to Société Française des Sciences et Techniques Pharmaceutiques protocols and the latest Food and Drug Administration guidelines. Six point calibration curves were used to cover a large concentration range of 1-500ng/ml for citalopram, desmethyl-citalopram, paroxetine and sertraline, 1-1000ng/ml for fluoxetine and fluvoxamine, and 2-1000ng/ml for norfluoxetine. Good quantitative performances were achieved in terms of trueness (84.2-109.6%), repeatability (0.9-14.6%) and intermediate precision (1.8-18.0%) in the entire assay range including the lower limit of quantification. Internal standard-normalized matrix effects were lower than 13%. The accuracy profiles (total error) were mainly included in the acceptance limits of ±30% for biological samples. The method was successfully applied for routine therapeutic drug monitoring of more than 1600 patient plasma samples over 9 months. The β-expectation tolerance intervals determined during the validation phase were coherent with the results of quality control samples analyzed during routine use. This method is therefore precise and suitable both for therapeutic drug monitoring and pharmacokinetic studies in most clinical laboratories.

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A sensitive and selective ultra-high performance liquid chromatography (UHPLC) tandem mass spectrometry (MS/MS) method was developed for the fast quantification of ten psychotropic drugs and metabolites in human plasma for the needs of our laboratory (amisulpride, asenapine, desmethyl-mirtazapine, iloperidone, mirtazapine, norquetiapine, olanzapine, paliperidone, quetiapine and risperidone). Stable isotope-labeled internal standards were used for all analytes, to compensate for the global method variability, including extraction and ionization variations. Sample preparation was performed by generic protein precipitation with acetonitrile. Chromatographic separation was achieved in less than 3.0min on an Acquity UPLC BEH Shield RP18 column (2.1mm×50mm; 1.7μm), using a gradient elution of 10mM ammonium formate buffer pH 3.0 and acetonitrile at a flow rate of 0.4ml/min. The compounds were quantified on a tandem quadrupole mass spectrometer operating in positive electrospray ionization mode, using multiple reaction monitoring. The method was fully validated according to the latest recommendations of international guidelines. Eight point calibration curves were used to cover a large concentration range 0.5-200ng/ml for asenapine, desmethyl-mirtazapine, iloperidone, mirtazapine, olanzapine, paliperidone and risperidone, and 1-1500ng/ml for amisulpride, norquetiapine and quetiapine. Good quantitative performances were achieved in terms of trueness (93.1-111.2%), repeatability (1.3-8.6%) and intermediate precision (1.8-11.5%). Internal standard-normalized matrix effects ranged between 95 and 105%, with a variability never exceeding 6%. The accuracy profiles (total error) were included in the acceptance limits of ±30% for biological samples. This method is therefore suitable for both therapeutic drug monitoring and pharmacokinetic studies.

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The biocontrol activity of the root-colonizing Pseudomonas fluorescens strain CHA0 is largely determined by the production of antifungal metabolites, especially 2,4-diacetylphloroglucinol. The expression of these metabolites depends on abiotic and biotic environmental factors, in particular, elements present in the rhizosphere. In this study, we have developed a new method for the in situ analysis of antifungal gene expression using flow cytometry combined with green fluorescent protein (GFP)-based reporter fusions to the phlA and prnA genes essential for the production of the antifungal compounds 2,4-diacetylphloroglucinol and pyrrolnitrin, respectively, in strain CHA0. Expression of phlA-gfp and prnA-gfp in CHA0 cells harvested from the rhizosphere of a set of plant species as well as from the roots of healthy, leaf pathogen-attacked, and physically stressed plants were analyzed using a FACSCalibur. After subtraction of background fluorescence emitted by plant-derived particles and CHA0 cells not carrying the gfp reporters, the average gene expression per bacterial cell could be calculated. Levels of phlA and prnA expression varied significantly in the rhizospheres of different plant species. Physical stress and leaf pathogen infection lowered phlA expression levels in the rhizosphere of cucumber. Our results demonstrate that the newly developed approach is suitable to monitor differences in levels of antifungal gene expression in response to various plant-derived factors. An advantage of the method is that it allows quantification of bacterial gene expression in rhizosphere populations at a single-cell level. To our best knowledge, this is the first study using flow cytometry for the in situ analysis of biocontrol gene expression in a plant-beneficial bacterium in the rhizosphere.