Absolute Relative Bias Research Articles

Evolutionary Prediction of Biohydrogen Production by Dark Fermentation

The present work is a study of the performance and effect of operational parameters on biohydrogen production from palm oil mill effluent by dark fermentation in batch mode. The process parameters examined are pH (5, 5.5, and 6), temperature (30, 35, and 40 °C), substrate concentration (5000, 12 500, and 20 000 mg L−1) and inoculum volume (20, 25, and 30 mL). The inoculum concentration prepared was 10 000 mg L−1 volatile suspended solids. The experiments were designed by response surface methodology (RSM). The highest chemical oxygen demand (COD) removal, hydrogen percentage (H2%) and hydrogen yield (HY) obtained were 58.3%, 80%, and 4.83 mol H2/mole of COD consumed, respectively. Based on the experimental data obtained with the RSM design, gene expression programming (GEP) was developed to predict the COD removal, hydrogen production, and hydrogen yield as process responses. The projected models were assessed based on the correlation coefficient (R2), root mean square error, mean absolute relative error, scatter index, and BIAS. The results demonstrate that the GEP model outperformed the RSM model and was superior in predicting the response variables. Partial derivative sensitivity analysis was also employed to assess the effect of each variable on COD%, H2%, and HY prediction. The prediction uncertainty for COD%, H2%, and HY was quantified, and the results were ±0.11, ±0.17, and 0.015, respectively. According to the results, the GEP model is more efficient than the RSM model in predicting the experimental data for biological hydrogen production in the dark fermentation process.

Measurement of ceftolozane and tazobactam concentrations in plasma by UHPLC-MS/MS. Clinical application in the management of difficult-to-treat osteoarticular infections

BackgroundCeftolozane, in combination with the β-lactamase inhibitor tazobactam, is a new option in the pipeline against multidrug-resistant Gram-negative bacilli. As for other β-lactam antibiotics, optimizing the use of ceftolozane-tazobactam is advisable, especially in difficult-to-treat infections. In this regard, therapeutic drug monitoring would be required to guide the treatment of ceftolozane-tazobactam. Thus, we aimed to develop and validate procedures based on UHPLC-MS/MS for measurement of ceftolozane and tazobactam plasma concentrations in clinical practice. Material and methodsAnalyses were conducted using an Acquity® UPLC® integrated system coupled to an Acquity® TQD® tandem-quadrupole mass spectrometer. Ceftolozane, tazobactam and their internal standards (ceftazidime-D5 and sulbactam) were detected by electrospray ionization mass spectrometry in positive and negative ion multiple reaction monitoring modes, using transitions of 667.2 → 199.3/139.0 and 551.9 → 467.9 for ceftolozane and ceftazidime-D5, and 299.0 → 138/254.9 and 232.0 → 140.0 for tazobactam and sulbactam. Measurement procedures developed were used for guiding the treatment and adjusting daily dose of ceftolozane-tazobactam in patients with osteoarticular infections. ResultsCoefficients of variation and absolute relative biases were <7.9% and 6.5% in all cases. The lower limit of quantification, linearity, normalized-recoveries, normalized-matrix effects and measurement uncertainties for ceftolozane were: 0.97 mg/L, (0.97–125) mg/L, ≤113.6%, ≤108.7%, and ≤ 18.7%, respectively; and for tazobactam: 1.04 mg/L, (1.04–125) mg/L, ≤103.6%, ≤101.9%, and ≤ 20.0%. No interferences and carry-over were observed. Patients plasma concentrations were higher than the recommended 3–4 times the minimal inhibitory concentrations. ConclusionsOur measurement procedures are suitable for therapeutic drug monitoring of ceftolozane-tazobactam in patients with osteoarticular infections.

Traceability of immunosuppressant's mass concentration results obtained using different commercial calibrators

BackgroundDue to the high inter-variability in immunosuppressants pharmacokinetics, therapeutic drug monitoring of these drugs is essential in order to minimize the risk of rejection after organ transplantation. Thus, results facilitated to clinicians by clinical laboratories for these drugs should be as reliable as possible. The knowledge of metrological traceability and performing compatibility studies can allow ensuring reliability of these results, mainly, when laboratories introduce substantial changes in their measurement procedures, e.g., when they change the calibration materials. The aim of this study was to investigate, as an example, the traceability of the calibrator's assigned values from two manufacturers (Recipe and Chromsystems) and to perform compatibility studies for sirolimus and tacrolimus. Material and methodsTraceability was described according to ISO 17511. Compatibility studies, based on the CLSI EP029-A guideline, were performed verifying the trueness processing the ERM®-DA111a and ERM®-DA110a reference materials. ResultsTraceability studies reveled that sirolimus and tacrolimus results were traceable to SI, except for sirolimus if Chromsystems' calibrators was used. Using Recipe's calibrators, the absolute relative biases and their expanded uncertainties were 1.23% and ±6.10% for sirolimus, and 1.41% and ±3.02% for tacrolimus. Furthermore, when Chromsystems' calibrators were used, these values were 12.2% and ±6.02% for sirolimus, and 2.64% and ±2.94% for tacrolimus. ConclusionsResults reported a lack of traceability and compatibility of sirolimus' results when Chromsystems' calibrators was used. In order to avoid it, laboratories should only use calibrators with assigned values traceable to highest reference materials or, alternatively, perform a compatibility study and apply a bias correction factor.

Characterization of Remote Sensing Albedo Over Sloped Surfaces Based on DART Simulations and In Situ Observations

AbstractIn situ albedo measurement over sloped surfaces is pivotal to a wide range of remote sensing applications, such as the estimation and evaluation of surface energy budget at regional and global scales. However, existing albedo measurements over rugged terrain are limited and controversial and remain a major challenge. In this paper, two commonly measured broadband albedos, which depend on incoming/outgoing geometric conditions, were characterized over sloped surfaces and illustrated. These albedos are the horizontal/horizontal sloped surface albedo (HHSA) and inclined/inclined sloped surface albedo (IISA). The 3‐D Discrete Anisotropic Radiative Transfer (DART) model simulations over varying slopes were utilized to quantify differences in the albedos. In particular, the effects of the slope, aspect, the solar zenith angle, and the proportion of diffuse skylight were investigated. The results show that absolute (relative) biases between HHSA and IISA are significant, reaching up to 0.026 (61.8%), 0.134 (62.4%), and 0.114 (62.3%) in the visible, near‐infrared, and shortwave broadbands, respectively. In addition, the diurnal cycle differences between HHSA and IISA were also compared using DART simulations and in situ observations over four typical slopes. Comparisons reveal that topographic parameters (e.g., slope and aspect) and atmospheric conditions (e.g., diffuse skylight and atmospheric visibility) are the primary factors, while the optical and structural parameters have a smaller effect.

Estimating soil hydraulic conductivity using different data-driven models of ANN, GMDH and GMDH-HS

The saturated hydraulic conductivity ( $$K_{\text{s}}$$ ) is one of the important soil hydraulic properties which plays a significant role in developing flow transport models and irrigation and drainage practices. In this research, artificial neural networks approaches, group method of data handling (GMDH) model and a hybrid intelligent model based on combination of GMDH and harmony search (HS) model (GMDH-HS) were developed to estimate $$K_{\text{s}}$$ based on 151 field samples collected from the northeast of Iran. Eleven topsoil properties were used as input parameters to estimate $$K_{\text{s}}$$ . The five quantitative standard statistical performance evaluation measures, i.e., coefficient of efficiency, root-mean-square error, mean square relative error, mean absolute percentage error and relative bias, were employed to evaluate the performance of various developed models. Statistical results indicated that the best performance can be obtained by GMDH-HS in terms of different evaluated criteria during the training and testing datasets for $$K_{\text{s}}$$ estimation.

A systematic assessment and reduction of parametric uncertainties for a distributed hydrological model

Quantifying and reducing uncertainties in physics-based hydrological model parameters will improve model reliability for hydrological forecasting. We present an uncertainty quantification framework that combines the strengths of stepwise sensitivity analysis and adaptive surrogate-based multi-objective optimization to facilitate practical assessment and reduction of model parametric uncertainties. Framework performance was tested using the distributed hydrological model Coupled Routing and Excess Storage (CREST) for daily streamflow simulation over ten watersheds. By identifying sensitive parameters stepwisely, we reduced the number of parameters requiring calibration from twelve to seven, thus limiting the dimensionality of calibration problem. By updating surrogate models adaptively, we found the optimal sets of sensitive parameters with the surrogate-based multi-objective optimization. The calibrated CREST was able to satisfactorily simulate observed streamflow for all watersheds, improving one minus Nash-Sutcliffe efficiency (1−NSE) by 65–90% and percentage absolute relative bias (|RB|) by 60–95% compared to the default. The validation result demonstrated that the calibrated CREST was also able to reproduce observed streamflow outside the calibration period, improving 1−NSE by 40–85% and |RB| by 35–90% compared to the default. Overall, this uncertainty quantification framework is effective for assessment and reduction of model parametric uncertainties, the results of which improve model simulations and enhance understanding of model behaviors.

Solution to Green–Ampt infiltration model using a two-step curve-fitting approach

Infiltration is an important hydrological process affecting the runoff, groundwater recharge and solute transport process. The Green–Ampt (GA) model, describing one-dimensional infiltration process, yields an implicit equation for estimation of cumulative infiltration with time. In this paper, an explicit approximation to the GA model is derived using two-step curve-fitting technique. The Marquardt’s algorithm is employed for least-squares estimation of nonlinear parameters. Performance of the proposed model is compared with the implicit GA model using numerical and published field experimental data. The quantitative statistical indicators namely, percent relative error (RE), maximum absolute percent relative error (MARE), percent bias (PB), and Nash–Sutcliffe modeling efficiency (E), are used to assess the performance of the proposed model. The solution of the proposed model matched very well with that of the implicit GA model with MARE ≤ 0.146%, PB ≤ 0.070%, and E value approximately equal to 1 for both the dimensionless numerical and dimensional field experimental infiltration estimates. Simulation results of the proposed model demonstrated the capability of the derived model in estimating infiltration rate and cumulative infiltration accurately and can be applied to solve variety of real-life hydrological problems.

New method for estimating daily global solar radiation over sloped topography in China

A new scheme for the estimation of daily global solar radiation over sloped topography in China is developed based on the Iqbal model C and MODIS cloud fraction. The effects of topography are determined using a digital elevation model. The scheme is tested using observations of solar radiation at 98 stations in China, and the results show that the mean absolute bias error is 1.51 MJ m−2 d−1 and the mean relative absolute bias error is 10.57%. Based on calculations using this scheme, the distribution of daily global solar radiation over slopes in China on four days in the middle of each season (15 January, 15 April, 15 July and 15 October 2003) at a spatial resolution of 1 km × 1 km are analyzed. To investigate the effects of topography on global solar radiation, the results determined in four mountains areas (Tianshan, Kunlun Mountains, Qinling, and Nanling) are discussed, and the typical characteristics of solar radiation over sloped surfaces revealed. In general, the new scheme can produce reasonable characteristics of solar radiation distribution at a high spatial resolution in mountain areas, which will be useful in analyses of mountain climate and planning for agricultural production.

Validation and Calibration of QAA Algorithm for CDOM Absorption Retrieval in the Changjiang (Yangtze) Estuarine and Coastal Waters

Distribution, migration and transformation of chromophoric dissolved organic matter (CDOM) in coastal waters are closely related to marine biogeochemical cycle. Ocean color remote sensing retrieval of CDOM absorption coefficient (ag(λ)) can be used as an indicator to trace the distribution and variation characteristics of the Changjiang diluted water, and further to help understand estuarine and coastal biogeochemical processes in large spatial and temporal scales. The quasi-analytical algorithm (QAA) has been widely applied to remote sensing inversions of optical and biogeochemical parameters in water bodies such as oceanic and coastal waters, however, whether the algorithm can be applicable to highly turbid waters (i.e., Changjiang estuarine and coastal waters) is still unknown. In this study, large amounts of in situ data accumulated in the Changjiang estuarine and coastal waters from 9 cruise campaigns during 2011 and 2015 are used to verify and calibrate the QAA. Furthermore, the QAA is remodified for CDOM retrieval by employing a CDOM algorithm (QAA_CDOM). Consequently, based on the QAA and the QAA_CDOM, we developed a new version of algorithm, named QAA_cj, which is more suitable for highly turbid waters, e.g., Changjiang estuarine and coastal waters, to decompose ag from adg (CDOM and non-pigmented particles absorption coefficient). By comparison of matchups between Geostationary Ocean Color Imager (GOCI) retrievals and in situ data, it reveals that the accuracy of retrievals from calibrated QAA is significantly improved. The root mean square error (RMSE), mean absolute relative error (MARE) and bias of total absorption coefficients (a(λ)) are lower than 1.17, 0.52 and 0.66 m−1, and ag(λ) at 443 nm are lower than 0.07, 0.42 and 0.018 m−1. These results indicate that the calibrated algorithm has a better applicability and prospect for highly turbid coastal waters with extremely complicated optical properties. Thus, reliable CDOM products from the improved QAA_cj can advance our understanding of the land-ocean interaction process by earth observations in monitoring spatial-temporal distribution of the river plume into sea.

Comparison of IMERG Level-3 and TMPA 3B42V7 in Estimating Typhoon-Related Heavy Rain

Typhoon-related heavy rain has unique structures in both time and space, and use of satellite-retrieved products to delineate the structure of heavy rain is especially meaningful for early warning systems and disaster management. This study compares two newly-released satellite products from the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG final run) and the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA 3B42V7) with daily rainfall observed by ground rain gauges. The comparison is implemented for eight typhoons over the coastal region of China for a two-year period from 2014 to 2015. The results show that all correlation coefficients (CCs) of both IMERG and TMPA for the investigated typhoon events are significant at the 0.01 level, but they tend to underestimate the heavy rainfall, especially around the storm center. The IMERG final run exhibits an overall better performance than TMPA 3B42V7. It is also shown that both products have a better applicability (i.e., a smaller absolute relative bias) when rain intensities are within 20–40 and 80–100 mm/day than those of 40–80 mm/day and larger than 100 mm/day. In space, they generally have the best applicability within the range of 50–100 km away from typhoon tracks, and have the worst applicability beyond the 300-km range. The results are beneficial to understand the errors of satellite data in operational applications, such as storm monitoring and hydrological modeling.

A new zenith-looking narrow-band radiometer-based system (ZEN) for dust aerosol optical depth monitoring

Abstract. A new zenith-looking narrow-band radiometer based system (ZEN), conceived for dust aerosol optical depth (AOD) monitoring, is presented in this paper. The ZEN system comprises a new radiometer (ZEN-R41) and a methodology for AOD retrieval (ZEN-LUT). ZEN-R41 has been designed to be stand alone and without moving parts, making it a low-cost and robust instrument with low maintenance, appropriate for deployment in remote and unpopulated desert areas. The ZEN-LUT method is based on the comparison of the measured zenith sky radiance (ZSR) with a look-up table (LUT) of computed ZSRs. The LUT is generated with the LibRadtran radiative transfer code. The sensitivity study proved that the ZEN-LUT method is appropriate for inferring AOD from ZSR measurements with an AOD standard uncertainty up to 0.06 for AOD500 nm ∼ 0.5 and up to 0.15 for AOD500 nm ∼ 1.0, considering instrumental errors of 5 %. The validation of the ZEN-LUT technique was performed using data from AErosol RObotic NETwork (AERONET) Cimel Electronique 318 photometers (CE318). A comparison between AOD obtained by applying the ZEN-LUT method on ZSRs (inferred from CE318 diffuse-sky measurements) and AOD provided by AERONET (derived from CE318 direct-sun measurements) was carried out at three sites characterized by a regular presence of desert mineral dust aerosols: Izaña and Santa Cruz in the Canary Islands and Tamanrasset in Algeria. The results show a coefficient of determination (R2) ranging from 0.99 to 0.97, and root mean square errors (RMSE) ranging from 0.010 at Izaña to 0.032 at Tamanrasset. The comparison of ZSR values from ZEN-R41 and the CE318 showed absolute relative mean bias (RMB) &lt; 10 %. ZEN-R41 AOD values inferred from ZEN-LUT methodology were compared with AOD provided by AERONET, showing a fairly good agreement in all wavelengths, with mean absolute AOD differences &lt; 0.030 and R2 higher than 0.97.

Addressing the problem of missing data in decision tree modeling

ABSTRACTTree-based models (TBMs) can substitute missing data using the surrogate approach (SUR). The aim of this study is to compare the performance of statistical imputation against the performance of SUR in TBMs. Employing empirical data, a TBM was constructed. Thereafter, 10%, 20%, and 40% of variable values appeared as the first split was deleted, and imputed with and without the use of outcome variables in the imputation model (IMP− and IMP+). This was repeated one thousand times. Absolute relative bias above 0.10 was defined as sever (SARB). Subsequently, in a series of simulations, the following parameters were changed: the degree of correlation among variables, the number of variables truly associated with the outcome, and the missing rate. At a 10% missing rate, the proportion of times SARB was observed in either SUR or IMP− was two times higher than in IMP+ (28% versus 13%). When the missing rate was increased to 20%, all these proportions were approximately doubled. Irrespective of the missing rate, IMP+ was about 65% less likely to produce SARB than SUR. Results of IMP− and SUR were comparable up to a 20% missing rate. At a high missing rate, IMP− was 76% more likely to provide SARB estimates. Statistical imputation of missing data and the use of outcome variable in the imputation model is recommended, even in the content of TBM.

Desarrollo y validación de un procedimiento de medida para la medición simultánea de la concentración de masa de ceftazidima, meropenem y piperacilina en el plasma mediante UHPLC-MS/MS

IntroductionCeftazidime, meropenem and piperacillin are broad spectrum antibiotics often used for the empirical treatment of infections in critically ill patients with sepsis. These antibiotics show time-dependent antimicrobial activity, meaning that the antibiotic mass concentration in plasma should be measured and maintained above the minimal inhibitory concentration. The aim of this study was to develop and to validate an ultra-performance liquid chromatography-tandem mass spectrometry procedure for the simultaneous measurement of ceftazidime, meropenem, and piperacillin mass concentration in plasma. Material and methodsAfter protein precipitation with acetonitrile and subsequent dilution of the supernatant with water, eluates were introduced into a reverse-phase C18 column using a water/methanol gradient containing formic acid. Antibiotics were detected by electrospray ionisation mass spectrometry in multiple reaction monitoring mode. ResultsThe lower limits of quantification were close to 0.50mg/l. Coefficients of variation and absolute relative biases were less than 10.8 and 12.0%, respectively. Recovery values ranged from 55.7 to 77.4%. Evaluation of the matrix effect showed ion enhancement for all antibiotics. No interferences or carry-over were observed. ConclusionsThe validated measurement procedure could be used in daily clinical laboratory practice to measure the mass concentration of these antibiotics in plasma, and in critically ill patients with sepsis.

Comparative study on the speckle filters for the very high-resolution polarimetric synthetic aperture radar imagery

With the emergence of very high-resolution airborne synthetic aperture radar systems, it is necessary to reinvestigate these proposed methods with respect to their despeckling performances. As for the very high resolution polarimetric synthetic aperture radar (PolSAR) data, the presumption that the resolution cell is much larger than the radar wavelength becomes ineffective. Therefore, some classic and new filters are thoroughly reviewed. For the evaluation of speckle filters, both indicators for polarimetric information and spatial information are listed. The absolute relative bias is introduced, with the purpose of measuring the filtering performance concerning the indicators for polarimetric information. Moreover, the ratio of half power point width is employed to quantitatively assess the degree of point target preservation. A series of experiments are carried out based on the real PolSAR imagery which is obtained from an uninhabited aerial vehicle synthetic aperture radar system. It can be concluded that existing filters can only attain good performance with reference to part of the indicators. As regards very high-resolution PolSAR imagery, it is necessary to conceive more apposite new filters or make improved versions of the existing filters.

Uplift capacity prediction of suction caisson in clay using a hybrid intelligence method (GMDH-HS)

Suction caissons are widely used for offshore facilities foundation or anchor system. They should be very stable and also to provide stability of main massive structures those are upon them. Suction caisson uplift capacity is the main issue to determine their stability. During recent years, many artificial intelligence (AI) methods such as artificial neural network (ANN), genetic programming (GP) and multivariate adaptive regression spline (MARS) have been used for suction caisson uplift capacity prediction. In this study, a novel hybrid intelligent method based on combination of group method of data handling (GMDH) and harmony search (HS) optimization method which is called GMDH-HS has been developed for suction caisson uplift capacity prediction. At first, the Mackey-Glass time series data were used for validation of developed method. The results of Mackey-Glass modeling were compared to conventional GMDH with two kinds of transfer function called GMDH1 and GMDH2. Five statistical indices such as coefficient of efficiency (CE), root mean square Error (RMSE), mean square relative error (MSRE), mean absolute percentage error (MAPE) and relative bias (RB) were used to evaluate performance of applied method. Then the GMDH-HS method has been used for suction caisson uplift capacity prediction. The 62 data set of laboratory measurements were collected from published literature that 51 sets used to train new developed method and the remaining data set used for testing. Not only the results of suction caisson uplift capacity prediction using GMDH-HS were evaluated with statistical indices, but also the results were compared to some artificial methods by previously works. The results indicated that performance of GMDH-HS was found more efficient when compared to other applied method in predicting the suction caisson uplift capacity.

Morgenstern type bivariate Lindley Distribution

In this paper, a bivariate Lindley distribution using Morgenstern approach is proposed which can be used for modeling bivariate life time data. Some characteristics of the distribution like moment generating function, joint moments, Pearson correlation coefficient, survival function, hazard rate function, mean residual life function, vitality function and stress-strength parameter R=Pr(Y<X), are derived. The conditions under which the proposed distribution is an increasing (decreasing) failure rate distribution and positive (negative) quadrant dependent is discussed. Also, the method of estimating model parameters and stress-strength parameter by maximum likelihood is elucidated. Numerical illustration using simulated data is carried out to access the estimates in terms of mean squared error and relative absolute bias.

The CM SAF ATOVS data record: overview of methodology and evaluation of total column water and profiles of tropospheric humidity

Abstract. Recently, the reprocessed Advanced Television Infrared Observation Satellite (TIROS)-N Operational Vertical Sounder (ATOVS) tropospheric water vapour and temperature data record was released by the EUMETSAT Satellite Application Facility on Climate Monitoring (CM~SAF). ATOVS observations from infrared and microwave sounders onboard the National Oceanic and Atmospheric Agency (NOAA)-15–19 satellites and EUMETSAT's Meteorological Operational (Metop-A) satellite have been consistently reprocessed to generate 13 years (1999–2011) of global water vapour and temperature daily and monthly means with a spatial resolution of 90 km × 90 km. The data set is referenced under the following digital object identifier (DOI): doi:10.5676/EUM_SAF_CM/WVT_ATOVS/V001. After preprocessing, a maximum likelihood solution scheme was applied to the observations to simultaneously infer temperature and water vapour profiles. In a post-processing step, an objective interpolation method (Kriging) was applied to allow for gap filling. The product suite includes total precipitable water vapour (TPW), layer-integrated precipitable water vapour (LPW) and layer mean temperature for five tropospheric layers between the surface and 200 hPa, as well as specific humidity and temperature at six tropospheric levels between 1000 and 200 hPa. To our knowledge, this is the first time that the ATOVS record (1998–now) has been consistently reprocessed (1999–2011) to retrieve water vapour. TPW and LPW products were compared to corresponding products from the Global Climate Observing System (GCOS) Upper-Air Network (GUAN) radiosonde observations and from the Atmospheric Infrared Sounder (AIRS) version 5 satellite data record. TPW shows a good agreement with the GUAN radiosonde data: average bias and root mean square error (RMSE) are −0.2 and 3.3 kg m−2, respectively. For LPW, the maximum absolute (relative) bias and RMSE values decrease (increase) strongly with height. The maximum bias and RMSE are found at the lowest layer and are −0.7 and 2.5 kg m−2, respectively. While the RMSE relative to AIRS is generally smaller, the TPW bias relative to AIRS is larger, with dominant contributions from precipitating areas. The consistently reprocessed ATOVS data record exhibits improved quality and stability relative to the operational CM SAF products when compared to the TPW from GUAN radiosonde data over the period 2004–2011. Finally, it became evident that the change in the number of satellites used for the retrieval combined with the use of the Kriging leads to breakpoints in the ATOVS data record; therefore, a variability analysis of the data record is not recommended for the time period from January 1999 to January 2001.

Measurement of total and free docetaxel concentration in human plasma by ultra-performance liquid chromatography–tandem mass spectrometry

Docetaxel is a semi-synthetic taxane with cytotoxic anti-neoplastic activity and, currently used as anticancer agent in several types of cancer. Docetaxel is highly bound to plasma proteins, and this significantly determines its clearance and activity. Therefore, measurement of free docetaxel in plasma is pharmacologically important when pharmacokinetics is investigated. We developed and validated chromatographic methods by ultra-performance liquid chromatography-tandem mass spectrometry to measure total and free docetaxel concentration in human plasma. The final validated methods involved liquid–liquid extraction followed by dryness under nitrogen evaporation. To measure free docetaxel concentration, sample preparation was preceded by ultrafiltration. Chromatographic separation was achieved using an Acquity® UPLC® BEH™ (2.1×100mm id, 1.7μm) reverse-phase C18 column at a flow rate of 0.4mL/min, using isocratic elution mode containing ammonium acetate/formic acid in water/methanol (30:70 v/v) as mobile phase. Docetaxel and its internal standard (paclitaxel) were detected by electrospray ionization mass spectrometry in positive ion multiple reaction monitoring mode using mass-to-charge (m/z) transitions of 808.3→527.0 (quantifier) and 808.3→509.0 (qualifier); and 854.3→569.0 (quantifier) and 854,3→509,0 (qualifier), respectively. The run time per sample was 3.5min. The limits of quantification were 1,95 and 0.42μg/L and linearity was observed between 1.95 and 1000 and 0.42–100μg/L for total and free docetaxel, respectively. Coefficients of variation and absolute relative biases were less than 13.8% and 10.0%. Recovery values were greater than 79.4%. Evaluation of the matrix effect showed ion suppression and no carry-over was observed. The validated methods could be useful for both therapeutic drug monitoring and pharmacokinetic studies. They could be applied to daily clinical laboratory practice to measure the concentration of total and free docetaxel in plasma.

Measurement of ceftazidime concentration in human plasma by ultra-performance liquid chromatography-tandem mass spectrometry. Application to critically ill patients and patients with osteoarticular infections.

Ceftazidime is an antibiotic belonging to the third generation of the cephalosporin family. It is indicated in the treatment of serious, simple or mixed bacterial infections, and its administration in continuous or intermittent infusion allows optimization of the concentration of antibiotic to keep it above the minimum inhibitory concentration. We developed and validated a chromatographic method by ultra-performance liquid chromatography-tandem mass spectrometry to measure ceftazidime concentration in human plasma. Following extraction with acetonitrile and 1,2-dichloroethane, the chromatographic separation was achieved using an Acquity ® UPLC ® BEH(TM) (2.1 × 100 mm i.d., 1.7 µm) reverse-phase C18 column, with a water-acetonitrile linear gradient containing 0.1% formic acid at a 0.4 mL/min flow rate. Ceftazidime and its internal standard (cefotaxime) were detected by electrospray ionization mass spectrometry in positive ion multiple reaction monitoring mode using mass-to-charge transitions of 547.0 → 467.9/396.1 and 456.0 → 395.8/324.1, respectively. The limit of quantification was 0.58 mg/L and linearity was observed in the range 0.58-160 mg/L. Coefficients of variation and absolute relative biases were <9.8 and 8.4%. The mean recovery for ceftazidime was 74.4 ± 8.1%. Evaluation of the matrix effect showed ion enhancement, and no carry-over was observed. The validated method could be applied to daily clinical laboratory practice to measure the concentration of ceftazidime in plasma.

Modeling solubility of CO2 in aqueous MDEA solution using electrolyte SAFT-HR EoS

The electrolyte SAFT-HR (eSAFT-HR) equation of state (EoS) has been successfully applied to model the solubility of CO2 in aqueous N-methyldiethanolamine (MDEA) solutions in a wide range of temperature (298–413 K), pressure (2.84–7565 kPa), MDEA concentration (18.8–50.1 wt%), and CO2 loading (0.00025–1.31608). A consistent database including 413 experimental data points is used in this study. The eSAFT-HR EoS is composed of the SAFT-HR EoS, the explicit simple version of the mean spherical approximation (MSA) theory and the Born equation. Vapor–liquid equilibrium calculations are performed to adjust the binary interaction parameters (BIP) for H2O–MDEA and H2O–CO2 binary solutions. Having the BIPs between the molecular species, the solubility of CO2 in the ternary aqueous solution of MDEA is calculated by simultaneous vapor–liquid and chemical equilibrium calculation algorithm. Also, to improve the results of the solubility of CO2 in the ternary CO2–MDEA–H2O systems, two additional BIPs (kMDEAH+−MDEA,kMDEAH+−CO2) are optimized using eSAFT-HR EoS. To decide which BIP has the most influence on the results a sensitivity analysis is made. Since the ion MDEAH+ does not exist in the binary solutions, these parameters are adjusted to the solubility data of the ternary solution. The BIPs are considered to be temperature dependent. For the ternary solution the overall average absolute percent relative deviation (AAD%) and mean BIAS percent deviation (BIAS%) are 11.2 and 4, respectively. To verify the ability of the model, the eSAFT-HR EoS is used to model the solubility data of Huttenhuis et al. (2007) for the MDEA–CO2–H2O system at the temperature of 298 K. The obtained AAD% and BIAS% are 25.6% and 5.5%, respectively. The results obtained by the eSAFT-HR EoS are in good agreement with the experimental data.